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1,620 | A missense mutation in Katnal1 underlies behavioural, neurological and ciliary anomalies
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5761721/
SHA: f4cebabd74b16e710fb41a737d8ef84b7d565d8d
Authors: Banks, G; Lassi, G; Hoerder-Suabedissen, A; Tinarelli, F; Simon, M M; Wilcox, A; Lau, P; Lawson, T N; Johnson, S; Rutman, A; Sweeting, M; Chesham, J E; Barnard, A R; Horner, N; Westerberg, H; Smith, L B; Molnár, Z; Hastings, M H; Hirst, R A; Tucci, V; Nolan, P M
Date: 2017-04-04
DOI: 10.1038/mp.2017.54
License: cc-by
Abstract: Microtubule severing enzymes implement a diverse range of tissue-specific molecular functions throughout development and into adulthood. Although microtubule severing is fundamental to many dynamic neural processes, little is known regarding the role of the family member Katanin p60 subunit A-like 1, KATNAL1, in central nervous system (CNS) function. Recent studies reporting that microdeletions incorporating the KATNAL1 locus in humans result in intellectual disability and microcephaly suggest that KATNAL1 may play a prominent role in the CNS; however, such associations lack the functional data required to highlight potential mechanisms which link the gene to disease symptoms. Here we identify and characterise a mouse line carrying a loss of function allele in Katnal1. We show that mutants express behavioural deficits including in circadian rhythms, sleep, anxiety and learning/memory. Furthermore, in the brains of Katnal1 mutant mice we reveal numerous morphological abnormalities and defects in neuronal migration and morphology. Furthermore we demonstrate defects in the motile cilia of the ventricular ependymal cells of mutants, suggesting a role for Katnal1 in the development of ciliary function. We believe the data we present here are the first to associate KATNAL1 with such phenotypes, demonstrating that the protein plays keys roles in a number of processes integral to the development of neuronal function and behaviour.
Text: Microtubule severing enzymes are a family of AAA-ATPase proteins that participate in fundamental cellular processes such as mitosis, ciliary biogenesis and growth cone motility. In neurons this family is known to control such processes as axonal elongation 1 and synaptic development. 2 In addition, mutations in microtubule severing enzyme genes SPG4, KATNB1 and KATNAL2 are associated with hereditary spastic paraplegia, cerebral malformations and autism, respectively, [3] [4] [5] [6] and mutations in Fign cause a range of phenotypes in mice. 7 Currently the microtubule severing enzyme KATNAL1 is poorly characterised and it is not yet understood how the enzyme functions in the nervous system. Recent evidence from genetic characterisation of human patients suggests that haploinsufficiency of KATNAL1 is linked with a number of symptoms including intellectual disability (ID) and craniofacial dysmorphologies. 8, 9 It is also notable that a very rare KATNAL1 mutation has been associated with schizophrenia 10 (http://atgu.mgh.harvard.edu/~spurcell/genebook/gene book.cgi?user = guest&cmd = verb-gene&tbox = KATNAL1) and that Peters syndrome and autism have both been associated with the chromosomal region containing the KATNAL1 locus. 11, 12 Although such association studies strongly suggest that KATNAL1 plays a fundamental role in the central nervous system (CNS), additional studies using cellular or animals models are required to understand how the gene may be causative for disease. Here we present the first study describing neural and behavioural deficits associated with a loss of function allele of Katnal1 in the mouse. This mutant mouse line was independently identified in two parallel phenotyping screens, which demonstrated that mutant mice showed both male sterility and circadian phenotypes. Subsequent behavioural investigations demonstrated that this mutation is associated with anxiety and memory deficits. Underlying these behavioural phenotypes, we identified histopathological abnormalities in the brains of Katnal1 1H/1H mutants, including disordered cellular layers in the hippocampus and cortex and substantially larger ventricles. Further investigations demonstrated that Katnal1 1H/1H mice show neuronal migration and ciliary function deficits suggesting KATNAL1 plays an essential role in these processes. These findings are the first to our knowledge to conclusively show that mutations in Katnal1 lead to behavioural and neuronal disturbances and provide insight regarding the clinical associations that have been linked to the gene. performed on mouse cohorts that were partially or completely congenic on the C57BL/6 J background.
Circadian wheel running was performed as previously described. 14 Sleep assessment by electroencephalography and electromyography Electroencephalography and electromyography was performed as previously described. 15 Behavioural phenotyping Spontaneous alternation. Mice were placed in a walled T-maze (black polyvinyl chloride, lined with sawdust; stem = 88 × 13 cm; arms = 32 × 13 cm) and allowed to enter a goal arm of their choice. The mouse was confined in the goal arm for 30 s, before being allowed a second free choice of goal arm. An alternation was recorded if the second choice differed from that of the first. One trial was performed per day for 10 days.
Open field behaviour. Mice were placed into a walled arena (grey polyvinyl chloride; 45 × 45 cm) and allowed to explore for 20 min. Animals were monitored by EthoVision XT analysis software (Noldus, Wageningen, Netherlands).
Video tracking in the home cage. Activity in the home cage was recorded by video tracking as previously described. 16 Morris water maze and ultrasonic vocalisation. These tests were performed as previously described. 17 Brain histology and immunofluorescence Brains were mounted in OCT (VWR) and 12 μm coronal sections taken. Sections were stained with hematoxylin and eosin, or immunolabelled following standard protocols.
In vivo neuronal migration assessment was performed as previously described 18 using embryos at either E13 or E15 (three mothers per age group) and pups at P9. Cell counts were performed using ImageJ (NIH, Bethesda, MD, USA).
In vitro neuronal migration assessment was performed using a Boyden chamber migration protocol as previously described. 19 Micro-computed tomography scanning Micro-computed tomography was performed using a Skyscan 1172 at 90 kV, 112 μA using an aluminium and copper filter, a rotation step of 0.250 degrees and a pixel size of 4.96 μm.
Segmentation, volume calculation and 3D modelling was performed using ITK-SNAP version 3.0.0 (ref. 20) and 3DSlicer. 21 Golgi-Cox staining of neurons Golgi-Cox neuronal staining was performed using the FD Rapid GolgiStain Kit (FD NeuroTechnologies, Columbia, MD, USA). Neurons were analysed using ImageJ.
Brains from P2 mice were dissected, and the dorsal cerebral half was sectioned (250 μm) through the floor of the lateral and 3rd ventricle using a vibratome. Ciliary beat frequency and pattern was analysed as previously described. 22 Electron microscopy For Scanning Electron Microscopy the ependymal lining of the lateral ventricle was fixed in 2.5% glutaraldehyde, 2% paraformaldehyde in 0.1 M phosphate buffer, incubated in 2% osmium tetroxide, and dehydrated through ethanol solutions. Samples were critical point dried using an Emitech K850 (Quorum Technologies, East Sussex, UK), coated with platinum using a Quorom Q150R S sputter coater (Quorum Technologies). and visualised using a JEOL LSM-6010 scanning electron microscope (Jeol, Herts, UK).
Transmission electron microscopy was performed as previously described. 22 Statistical analysis Data was analysed using two-tailed students T test or AVOVA using SPSS (IBM) or GraphPad Prism 5.0 (GraphPad Software, La Jolla, CA, USA). Significance level for all analysis was set at Po 0.05. All graphs are presented showing mean ± s.e.m.
Additional and more detailed methods can be found in supplementary information.
Identification and cloning of the Katnal1 1H mutation To identify novel gene mutations affecting circadian behaviour we undertook a circadian running wheel screen of pedigrees of N-ethyl-N-nitrosourea mutagenised mice. 13 In one pedigree 17.65% of animals showed a short circadian period in constant darkness (o 23 h observed in 12 out of 68 animals screened). An outcross using an affected female produced no affected animals (33 animals screened). In subsequent intercross screens 15.5% of animals were affected (53 out of 342 animals screened), suggesting that the pedigree carries a mutation causing a recessive circadian phenotype which is 60% penetrant. We found no gender bias in affected animals (proportion of affected animals: male = 47.2%; female = 52.8%).
Concurrently a male sterility phenotype was identified within the same pedigree. 23 Genome-wide SNP linkage analysis mapped the circadian and sterility phenotypes to the same region on chromosome 5 and subsequent sequencing identified the causative mutation as a T to G single point mutation within exon seven of the Katnal1 gene. For full details of mapping and identification of the mutation see reference 23. This mutant allele was designated Katnal1 1H , and results in a leucine to valine substitution at residue 286 of the protein. In vitro functional analysis demonstrated that the mutation is a recessive loss-offunction allele. 23 3D modelling of the protein suggests that this loss of function is due to hydrophobic changes in the AAA domain of the enzyme (Supplementary Figure S1 ). Genotyping confirmed that the mutation was homozygous in affected circadian animals and wild type or heterozygous in unaffected animals, confirming that Katnal1 1H was causative for the circadian phenotype.
Circadian and sleep anomalies in Katnal1 1H/1H mice More extensive circadian phenotyping conducted on Katnal1 homozygotes (Katnal1 1H/1H ) and wild-type littermates (Katnal1 +/+ ) confirmed that Katnal1 1H/1H mice had a shorter free-running circadian period (Figures 1a-c) and furthermore revealed that Katnal1 1H/1H animals were more active in the light phase of the light/dark cycle (Figure 1d ), showed increased anticipation of light to dark transitions and greater shift in activity onset when released from light/dark cycles to constant darkness ( Figure 1e ). Data and cohort details are given in Supplementary Table S1 . Bioluminescence recordings performed using PER2::LUCIFERASE reporter mice carrying the Katnal1 1H mutation revealed that these circadian changes were not due to changes to the core molecular clock of the suprachiasmatic nucleus (the site of the master circadian clock in the brain; Supplementary Figure S2 ).
Circadian disruptions are often associated with deficits in sleep homeostasis. Therefore to complement our circadian studies we conducted wireless electroencephalography recordings over a baseline period of 24 h and following a 6 h period of sleep deprivation. A detailed summary of electroencephalography analysis is given in Supplementary Table S1. Compared to wildtype littermates, the non-REM delta power of Katnal1 1H/1H mice was higher in the dark phase of baseline sleep (mixed ANOVA, interaction factors 'genotype X time, F(1,88) = 8.91, P = 0.0175) ( Figure 1f ) and in both the light and dark phases of recovery sleep (mixed ANOVA, interaction factors 'genotype X time', F(1,136) = 11.93, P = 0.0086; Figure 1g ). All other sleep parameters were unaffected in Katnal1 1H/1H animals.
Katnal1 1H/1H mice display a spectrum of behavioural deficits Human patients carrying a heterozygous deletion incorporating the Katnal1 locus show a number of cognitive deficits including ID and a delay in language acquisition. 8, 9 We therefore investigated whether these deficits were modelled in Katnal1 1H/1H mice by subjecting animal cohorts to a battery of behavioural tests. Data and cohort details are given in Supplementary Table S2 .
Both working memory and spatial memory were significantly poorer in Katnal1 1H/1H mice, as evidenced by reduced spontaneous alternations in a T-maze ( Figure 2a ) and in the Morris water maze where mutants take longer to find the platform in acquisition trials (Figure 2b Compared to wild-type littermates, Katnal1 1H/1H animals have a shorter period (c), are more active in the light phase of the light/dark cycle (d) and show an earlier onset of activity in light/dark transitions and in the transition from light/dark cycles to constant darkness (e). In EEG recordings during sleep, Katnal1 1H/1H mice show increased non-REM delta power in the dark phase of the light/dark cycle (f) and following sleep deprivation (g). *P ⩽ 0.05; **P ⩽ 0.01; ***P ⩽ 0.001. EEG, electroencephalography; DD, constant darkness; LD, light/dark cycle. type = 164 ± 12 m, Katnal1 1H/1H = 243 ± 20 m, P = 0.02; distance travelled in periphery of open field: wild type = 4.3 ± 0.2 m, Katnal1 1H/1H = 6 ± 0.3 m, P = 0.004). Conversely when mouse activity was recorded in the home cage, we found no difference between genotypes (distance travelled over 24 h: wild type = 399 ± 77 m, Katnal1 1H/1H = 418 ± 41 m, P = 0.833) suggesting that the former activity differences were due to the novel environment of the open field rather than generalised hyperactivity in Katnal1 1H/1H animals. Finally, in certain conditions (such as maternal separation) mice emit ultrasonic vocalisations (USVs). To test whether Katnal1 1H/1H animals vocalised differently to wild types, we separated pups at postnatal days 7-8 (the age at which mice show peak of USV emission 24 ) and recorded their USVs. In these tests, compared to wild types, Katnal1 1H/1H pups produced fewer ( Figure 2g ) and shorter (Figure 2h ) vocalisations, containing fewer phrases (Figure 2i ). Gross brain morphological abnormalities in Katnal1 1H/1H mice Since we observed a number of behavioural phenotypes in Katnal1 1H/1H mice, we performed histological analysis to ascertain whether differences in brain histology underlied these behaviours. Data and cohort details are given in Supplementary Table S3 . Analysis of hematoxylin and eosin stained brain sections revealed that, compared to wildtype littermates, Katnal1 1H/1H animals had less tightly packed pyramidal cell layers in the hippocampus (Figures 3a and b) and a narrower cortical layer 1 and wider cortical layer 6 (Figures 3c-e) . To confirm these cortical layer differences, immunofluorescence was performed using the (Figures 3l and m) . Quantification of fluorescence intensity demonstrated that in Katnal1 1H/1H cortex both calbindin and CUX1 labelling was more intense closer to the cortical surface, which is consistent with the reduction in the size of layer 1 (two-way analysis of variance (ANOVA), interaction factors 'genotype X distance of fluorescence from cortical surface', calbindin: F(75,988) = 16.8, P o 0.0005; CUX1: F(93,372 = 2.17, P = 0.001; Figures 3h and k) . Similar quantification revealed that FOXP2 labelling extended further from layer 6b (as labelled by CTGF) in the Katnal1 1H/1H cortex, which is consistent with an increase in the size of layer 6 (two-way ANOVA, interaction factors 'genotype X distance of fluorescence from CTGF labelling:' F(93,372) = 1.32, P = 0.038; Figure 3n ). Finally, three dimensional models of the ventricular system were constructed from brain micro-computed tomography scans (Figures 3o and p) . Volumetric analysis revealed that Katnal1 1H/1H mice had substantially larger ventricles than wild types (Figure 3q ).
Neuronal migration and morphology defects in Katnal1 1H/1H brains The histological phenotypes of Katnal1 1H/1H mouse brains described above are suggestive of neuronal migration defects. 18 We therefore investigated whether Katnal1 1H/1H mice showed abnormal neuronal migration using BrdU labelling of E13 and E15 embryos and quantified labelled cells in the cortex of P9 pups (described in reference 18). At both ages Katnal1 1H/1H animals had greater numbers of labelled neurons in bins close to the cortical surface neurons positioned closer to the cortical surface compared to wild type. To confirm these results we used a Boyden chamber 19 and performed in vitro neuronal migration analysis in E13.5 primary cortical neuronal cultures. Here we found that a greater proportion of Katnal1 1H/1H cortical neurons migrated to the base of the cell culture insert compared to wildtype controls (Supplementary Figure S3) .
Since in both BrdU labelling and the Boyden assay neurons from Katnal1 1H/1H animals migrated further than those of wild-type littermates, these results suggest that Katnal1 1H/1H cortical neurons show defects in the termination of cortical neuronal migration. Given its role in cytoskeletal organisation, we also hypothesised that neuronal morphology is modulated by Katnal1. Analysis of golgi stained neurons from layers 2-3 of the cortex (Figures 4g and i) demonstrated that, compared to wild-type littermates, Katnal1 1H/1H neurons had larger soma (Figure 4k) , and shorter and thinner axons (Figures 4l and m) (data and cohort details are given in Supplementary Table S3 ). Furthermore, analysis at higher magnification (Figures 4h and j) , demonstrated that the number of synaptic spines on Katnal1 1H/1H neurons was significantly reduced compared to wild type (Figure 4n ).
Recent studies have demonstrated that mutations in some microtubule severing enzymes can cause defects in cilia. 5 Since such ciliary defects could underlie the phenotypes described above we studied the motile cilia of the ependymal lining of the lateral ventricle in sections of postnatal day 2 mouse brains from both Katnal1 1H/1H (n = 4) and wild-type animals (n = 3). We found that the ciliary beat frequency (CBF) of Katnal1 1H/1H animals was significantly attenuated compared to wild-type (CBF: wildtype = 22.39 ± 0.94 Hz, Katnal1 1H/1H = 14.25 ± 0.92 Hz, P = 0.0001; Figure 5a , Supplementary Movies S1). This reduction in CBF in Katnal1 1H/1H animals was also associated with an increased proportion of cilia with an abnormal beat pattern (ciliary dyskinesia) (proportion of dyskinetic cilia: wild type = 17%, Katnal1 1H/1H = 75%) (Figure 5b and Supplementary Movies S1). Visual inspection of the cilia identified a number of ciliary abnormalities such as a swollen ciliary tip (Supplementary Movie S3) or extremely long cilia (Supplementary Movie S4) scattered throughout the field of cilia in Katnal1 1H/1H ventricles. These abnormalities were observed in approximately 25% of Katnal1 1H/1H brain slices. The abnormal cilia always showed a dyskinetic beat pattern and lower beat frequency. To further investigate ciliary morphology we performed scanning electron microscopy upon the ependymal lining of the lateral ventricles of both Katnal1 1H/1H (n = 3) and wild-type animals (n = 3; Figures 5c and d) . Cilia measurements showed no significant differences in average cilia length between genotypes (average cilia length: wild type = 6.22 ± 0.86 μm, Katnal1 1H/1H = 6.54 ± 0.94 Hz, P = 0.303). However in Katnal1 1H/1H samples we noted the presence of both long and short cilia (Figures 5e and f ; defined as two standard deviations longer or shorter than the average cilia length) that were not present in wild-type samples. In addition, inspection of Katnal1 1H/1H cilia identified ciliary abnormalities including bifurcated cilia (Figure 5g) , abnormal kinks and bends in the cilia (Figure 5h ) and swellings along the length of the cilia (Figure 5i ). Transmission electron microscopy of ependymal cilia found that vesicular aggre- Katnal1 disruption affects CNS functions G Banks et al gates were present within the ciliary swellings described above (Figure 5j ). Although these abnormalities were present in only a small proportion (o1%) of Katnal1 1H/1H cilia, they were notably absent from wild-type cilia.
Microtubule severing enzymes play diverse roles in the nervous system. 1, 2 However, at present the microtubule severing enzyme Katnal1 is poorly defined in the context of CNS development and function. Here we present a detailed phenotypic analysis of Katnal1 1H and show that the mutation is associated with changes in circadian rhythms, sleep and behaviour. Furthermore we demonstrate that defects in brain histopathology, neuronal migration and neuronal morphology underlie these phenotypes. Finally we also demonstrate that Katnal1 1H causes a range of defects in the motile cilia of ventricular ependymal cells. The data we present here are the first to associate KATNAL1 with such dysfunctions with important implications for clinical association studies.
The Katnal1 1H mutation was initially identified with a circadian deficit including a short free-running period and advanced activity onset. However subsequent ex vivo experiments using SCN slices of animals carrying the PER2::LUC reporter gene demonstrated no defects in SCN cellular rhythms, suggesting that the core circadian clock was unperturbed by the mutation. Phenotypes in circadian running wheel rhythms that are not associated with changes to the core clock mechanism have also been reported in mouse models of schizophrenia. 25 Here it has been suggested that the wheel running changes observed are the result in defects in output pathways from the SCN circadian clock. Similarly, in Katnal1 1H/1H mice we hypothesise that the defects we demonstrate in neuronal anatomy and neuronal morphology may disrupt output signals from the SCN. Alternatively given that various neuropeptides such as oxytocin are secreted in a circadian manner from ependymal cells lining the third ventricle of the brain, 26 altered ventricular morphology and ciliary function in Katnal1 1H/1H mice may disrupt the circulation of factors secreted by the ciliated ventricular ependymal cells and contribute to the disruption of the behavioural rhythms observed.
The behavioural consequences of microtubule severing enzyme dysfunction in mouse models have been poorly characterised. Currently the phenotypes described are limited to motor dysfunction in mice lacking the Spg4 gene 27 and head shaking and circling in the Fign mutant. 7, 28, 29 In contrast, here we demonstrate that loss of function of Katnal1 is associated with a range of behavioural phenotypes, including changes in circadian activity, poor learning and memory, hyperactivity in a novel environment (the open field) and deficits in USVs. Notably the learning and memory, anxiety and vocalisation phenotypes reprise the clinical symptoms of ID, increased anxiety in novel situations and delays in language acquisition reported in human patients who carry microdeletions incorporating haploinsufficiency of KATNAL1. 8, 9 While it is also worth noting that mutant mice spend more time the centre of the open field than wild types (implying that Katnal1 1H/1H animals show reduced anxiety), we suggest that this result is confounded by the hyperactivity in novel environments phenotype we also describe in mutant mice. This observation is backed up by the fact that mutant animals showed increased activity in all regions of the open field rather than just the anxiolytic periphery. Here we also highlight defects in Katnal1 1H/1H mice such as compromised neuronal migration and morphology which may underpin such phenotypes. In Drosophila, the homologue of Katnal1 (kat-60L1) has been demonstrated to play a critical role in neuronal morphology during development, 30 however the data that we present here is the first to demonstrate a similar phenotype in mammals and furthermore suggests how subtle perturbations to KATNAL1 function may contribute to specific neural and behavioural conditions. For example, defects in neuronal migration, synaptic spines and neuronal morphology such as those we have demonstrated here, have been suggested to underpin ID in conditions such as lissencephaly, 18 Down's syndrome 31 and Rett syndrome. 32 While we are not suggesting that Katnal1 is causative for these conditions, similarities in symptoms and neuronal phenotypes between these conditions and those linked to Katnal1 dysfunction should be appreciated. Furthermore a rare mutation in KATNAL1 has been associated with schizophrenia 10 (http://atgu.mgh.harvard.edu/~spurcell/gene book/genebook.cgi?user = guest&cmd = verb-gene&tbox = KATNAL1) and KATNAL1 has been shown to interact with the schizophrenia associated gene DISC1. 33 In line with these observations we note that increases in ventricular volume and reductions in synaptic spines have been reported in schizophrenic patients 34, 35 and our data demonstrates the same phenotypes in Katnal1 1H/1H mice. Thus the range of phenotypes associated with defects in the function of Katnal1 strongly suggests that the gene should be considered in the pathology of disorders such as ID and schizophrenia.
We do note one key genetic difference between the human patients and Katnal1 1H/1H animals. While the human patients were all heterozygous for the Katnal1 deletion, we found no phenotype in heterozygous mutant mice (data not shown) suggesting that while haploinsufficiency is causative for phenotypes in humans, mice require complete loss of KATNAL1 function to show similar effects. A similar discrepancy between humans and mice has also been noted for the intellectual disability candidate gene CTNNB1. 17 While heterozygous loss of function mutations in CTNNB1 are causative for intellectual disability in humans, conditional knock outs for CTNNB1 have no reported behavioural or craniofacial phenotypes. 36, 37 These differences demonstrate that while mouse models of intellectual disability are of great use in our understanding of the causative mechanisms which underlie the condition, there are still genetic and neurodevelopmental differences between species which also must be taken into account. We also note that while the Katnal1 1H mutation shows a loss of catalytic function in both HEK293 cells and Sertoli cells, 23 this loss of function has not been verified in neuronal cells. However, given that our data demonstrates that the Katnal1 1H mutation lies in an essential catalytic domain and that we show neuronal phenotypes in Katnal1 1H/1H mice, we would expect to see the same loss of catalytic function in neurons.
The data we present here also demonstrate defects in motile cilia in Katnal1 1H/1H mice. Ciliary disruptions in humans (ciliopathies) include Bardet-Biedl and Joubert syndrome. 38 While there is currently limited data available regarding the behavioural phenotypes of mouse models of ciliopathies, we note that ciliary dysfunction in mice has been linked with learning and memory 39 and vocalisation phenotypes, 40 both of which were disturbed in the Katnal1 1H/1H mice described here. It is also notable that the neuronal migration and enlarged ventricle phenotypes that we describe in Katnal1 1H/1H mice recapitulate features associated with known ciliopathy gene mutations. [41] [42] [43] [44] Furthermore in Bardet-Biedl syndrome mouse models ciliary defects such as reduced CBF 45 and structural defects such as abnormal lengthening and swellings along their length 41 have been described, that are similar to those we describe in Katnal1 1H/1H mice. There is strong evidence that ciliopathy associated genes play a number of roles in neuronal development by affecting processes such as progenitor proliferation or maintenance of the radial glia scaffold. 43 However it is also clear that defects in microtubule organisation also affect synaptic structure. 2 At present it is difficult to disentangle the relative contributions of defects in microtubule severing and ciliary abnormalities to the overall phenotypes we observe in Katnal1 1H/1H mice. Further investigations are required to clarify the impacts of these two processes. However it is notable that while defects in cilia structure may contribute to the phenotypes we describe in Katnal1 1H/1H mice, they are far less prominent in Katnal1 1H/1H mice than in other mouse ciliopathy models, 41 suggesting that the ciliary component of KATNAL1 dysfunction may be mild compared to other ciliopathies. Similarly while hydrocephalus has been suggested to be a component of some ciliopathy mouse models, 46 Katnal1 1H/1H mice showed only increased ventricle size rather than an increased incidence of hydrocephalus, further suggesting the ciliary defects in these animals are mild compared to other ciliopathies.
In summary the data presented here clearly demonstrate that KATNAL1 plays an important role in a variety of neuronal processes including neuronal migration, neuronal morphology and ependymal ciliary function. The downstream effect of these defects leads in turn to a number of behavioural changes including in learning and memory, reaction to anxiogenic situations and circadian rhythms. These data therefore highlight how perturbations in KATNAL1 may play a role in neuronal dysfunction and demonstrates that the enzyme is a novel candidate in the study of behavioural and neurodevelopmental disorders.
The authors declare no conflict of interest. | What are microtubule severing enzymes? | false | 924 | {
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2,634 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What are the chacateristics of the S2 subunit? | false | 3,718 | {
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"S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV"
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2,683 | Estimating the number of infections and the impact of non-
pharmaceutical interventions on COVID-19 in 11 European countries
30 March 2020 Imperial College COVID-19 Response Team
Seth Flaxmani Swapnil Mishra*, Axel Gandy*, H JulietteT Unwin, Helen Coupland, Thomas A Mellan, Harrison
Zhu, Tresnia Berah, Jeffrey W Eaton, Pablo N P Guzman, Nora Schmit, Lucia Cilloni, Kylie E C Ainslie, Marc
Baguelin, Isobel Blake, Adhiratha Boonyasiri, Olivia Boyd, Lorenzo Cattarino, Constanze Ciavarella, Laura Cooper,
Zulma Cucunuba’, Gina Cuomo—Dannenburg, Amy Dighe, Bimandra Djaafara, Ilaria Dorigatti, Sabine van Elsland,
Rich FitzJohn, Han Fu, Katy Gaythorpe, Lily Geidelberg, Nicholas Grassly, Wi|| Green, Timothy Hallett, Arran
Hamlet, Wes Hinsley, Ben Jeffrey, David Jorgensen, Edward Knock, Daniel Laydon, Gemma Nedjati—Gilani, Pierre
Nouvellet, Kris Parag, Igor Siveroni, Hayley Thompson, Robert Verity, Erik Volz, Caroline Walters, Haowei Wang,
Yuanrong Wang, Oliver Watson, Peter Winskill, Xiaoyue Xi, Charles Whittaker, Patrick GT Walker, Azra Ghani,
Christl A. Donnelly, Steven Riley, Lucy C Okell, Michaela A C Vollmer, NeilM.Ferguson1and Samir Bhatt*1
Department of Infectious Disease Epidemiology, Imperial College London
Department of Mathematics, Imperial College London
WHO Collaborating Centre for Infectious Disease Modelling
MRC Centre for Global Infectious Disease Analysis
Abdul LatifJameeI Institute for Disease and Emergency Analytics, Imperial College London
Department of Statistics, University of Oxford
*Contributed equally 1Correspondence: nei|[email protected], [email protected]
Summary
Following the emergence of a novel coronavirus (SARS-CoV-Z) and its spread outside of China, Europe
is now experiencing large epidemics. In response, many European countries have implemented
unprecedented non-pharmaceutical interventions including case isolation, the closure of schools and
universities, banning of mass gatherings and/or public events, and most recently, widescale social
distancing including local and national Iockdowns.
In this report, we use a semi-mechanistic Bayesian hierarchical model to attempt to infer the impact
of these interventions across 11 European countries. Our methods assume that changes in the
reproductive number— a measure of transmission - are an immediate response to these interventions
being implemented rather than broader gradual changes in behaviour. Our model estimates these
changes by calculating backwards from the deaths observed over time to estimate transmission that
occurred several weeks prior, allowing for the time lag between infection and death.
One of the key assumptions of the model is that each intervention has the same effect on the
reproduction number across countries and over time. This allows us to leverage a greater amount of
data across Europe to estimate these effects. It also means that our results are driven strongly by the
data from countries with more advanced epidemics, and earlier interventions, such as Italy and Spain.
We find that the slowing growth in daily reported deaths in Italy is consistent with a significant impact
of interventions implemented several weeks earlier. In Italy, we estimate that the effective
reproduction number, Rt, dropped to close to 1 around the time of Iockdown (11th March), although
with a high level of uncertainty.
Overall, we estimate that countries have managed to reduce their reproduction number. Our
estimates have wide credible intervals and contain 1 for countries that have implemented a||
interventions considered in our analysis. This means that the reproduction number may be above or
below this value. With current interventions remaining in place to at least the end of March, we
estimate that interventions across all 11 countries will have averted 59,000 deaths up to 31 March
[95% credible interval 21,000-120,000]. Many more deaths will be averted through ensuring that
interventions remain in place until transmission drops to low levels. We estimate that, across all 11
countries between 7 and 43 million individuals have been infected with SARS-CoV-Z up to 28th March,
representing between 1.88% and 11.43% ofthe population. The proportion of the population infected
to date — the attack rate - is estimated to be highest in Spain followed by Italy and lowest in Germany
and Norway, reflecting the relative stages of the epidemics.
Given the lag of 2-3 weeks between when transmission changes occur and when their impact can be
observed in trends in mortality, for most of the countries considered here it remains too early to be
certain that recent interventions have been effective. If interventions in countries at earlier stages of
their epidemic, such as Germany or the UK, are more or less effective than they were in the countries
with advanced epidemics, on which our estimates are largely based, or if interventions have improved
or worsened over time, then our estimates of the reproduction number and deaths averted would
change accordingly. It is therefore critical that the current interventions remain in place and trends in
cases and deaths are closely monitored in the coming days and weeks to provide reassurance that
transmission of SARS-Cov-Z is slowing.
SUGGESTED CITATION
Seth Flaxman, Swapnil Mishra, Axel Gandy et 0/. Estimating the number of infections and the impact of non—
pharmaceutical interventions on COVID—19 in 11 European countries. Imperial College London (2020), doi:
https://doi.org/10.25561/77731
1 Introduction
Following the emergence of a novel coronavirus (SARS-CoV-Z) in Wuhan, China in December 2019 and
its global spread, large epidemics of the disease, caused by the virus designated COVID-19, have
emerged in Europe. In response to the rising numbers of cases and deaths, and to maintain the
capacity of health systems to treat as many severe cases as possible, European countries, like those in
other continents, have implemented or are in the process of implementing measures to control their
epidemics. These large-scale non-pharmaceutical interventions vary between countries but include
social distancing (such as banning large gatherings and advising individuals not to socialize outside
their households), border closures, school closures, measures to isolate symptomatic individuals and
their contacts, and large-scale lockdowns of populations with all but essential internal travel banned.
Understanding firstly, whether these interventions are having the desired impact of controlling the
epidemic and secondly, which interventions are necessary to maintain control, is critical given their
large economic and social costs.
The key aim ofthese interventions is to reduce the effective reproduction number, Rt, ofthe infection,
a fundamental epidemiological quantity representing the average number of infections, at time t, per
infected case over the course of their infection. Ith is maintained at less than 1, the incidence of new
infections decreases, ultimately resulting in control of the epidemic. If Rt is greater than 1, then
infections will increase (dependent on how much greater than 1 the reproduction number is) until the
epidemic peaks and eventually declines due to acquisition of herd immunity.
In China, strict movement restrictions and other measures including case isolation and quarantine
began to be introduced from 23rd January, which achieved a downward trend in the number of
confirmed new cases during February, resulting in zero new confirmed indigenous cases in Wuhan by
March 19th. Studies have estimated how Rt changed during this time in different areas ofChina from
around 2-4 during the uncontrolled epidemic down to below 1, with an estimated 7-9 fold decrease
in the number of daily contacts per person.1'2 Control measures such as social distancing, intensive
testing, and contact tracing in other countries such as Singapore and South Korea have successfully
reduced case incidence in recent weeks, although there is a riskthe virus will spread again once control
measures are relaxed.3'4
The epidemic began slightly laterin Europe, from January or later in different regions.5 Countries have
implemented different combinations of control measures and the level of adherence to government
recommendations on social distancing is likely to vary between countries, in part due to different
levels of enforcement.
Estimating reproduction numbers for SARS-CoV-Z presents challenges due to the high proportion of
infections not detected by health systems”7 and regular changes in testing policies, resulting in
different proportions of infections being detected over time and between countries. Most countries
so far only have the capacity to test a small proportion of suspected cases and tests are reserved for
severely ill patients or for high-risk groups (e.g. contacts of cases). Looking at case data, therefore,
gives a systematically biased view of trends.
An alternative way to estimate the course of the epidemic is to back-calculate infections from
observed deaths. Reported deaths are likely to be more reliable, although the early focus of most
surveillance systems on cases with reported travel histories to China may mean that some early deaths
will have been missed. Whilst the recent trends in deaths will therefore be informative, there is a time
lag in observing the effect of interventions on deaths since there is a 2-3-week period between
infection, onset of symptoms and outcome.
In this report, we fit a novel Bayesian mechanistic model of the infection cycle to observed deaths in
11 European countries, inferring plausible upper and lower bounds (Bayesian credible intervals) of the
total populations infected (attack rates), case detection probabilities, and the reproduction number
over time (Rt). We fit the model jointly to COVID-19 data from all these countries to assess whether
there is evidence that interventions have so far been successful at reducing Rt below 1, with the strong
assumption that particular interventions are achieving a similar impact in different countries and that
the efficacy of those interventions remains constant over time. The model is informed more strongly
by countries with larger numbers of deaths and which implemented interventions earlier, therefore
estimates of recent Rt in countries with more recent interventions are contingent on similar
intervention impacts. Data in the coming weeks will enable estimation of country-specific Rt with
greater precision.
Model and data details are presented in the appendix, validation and sensitivity are also presented in
the appendix, and general limitations presented below in the conclusions.
2 Results
The timing of interventions should be taken in the context of when an individual country’s epidemic
started to grow along with the speed with which control measures were implemented. Italy was the
first to begin intervention measures, and other countries followed soon afterwards (Figure 1). Most
interventions began around 12th-14th March. We analyzed data on deaths up to 28th March, giving a
2-3-week window over which to estimate the effect of interventions. Currently, most countries in our
study have implemented all major non-pharmaceutical interventions.
For each country, we model the number of infections, the number of deaths, and Rt, the effective
reproduction number over time, with Rt changing only when an intervention is introduced (Figure 2-
12). Rt is the average number of secondary infections per infected individual, assuming that the
interventions that are in place at time t stay in place throughout their entire infectious period. Every
country has its own individual starting reproduction number Rt before interventions take place.
Specific interventions are assumed to have the same relative impact on Rt in each country when they
were introduced there and are informed by mortality data across all countries.
Figure l: Intervention timings for the 11 European countries included in the analysis. For further
details see Appendix 8.6.
2.1 Estimated true numbers of infections and current attack rates
In all countries, we estimate there are orders of magnitude fewer infections detected (Figure 2) than
true infections, mostly likely due to mild and asymptomatic infections as well as limited testing
capacity. In Italy, our results suggest that, cumulatively, 5.9 [1.9-15.2] million people have been
infected as of March 28th, giving an attack rate of 9.8% [3.2%-25%] of the population (Table 1). Spain
has recently seen a large increase in the number of deaths, and given its smaller population, our model
estimates that a higher proportion of the population, 15.0% (7.0 [18-19] million people) have been
infected to date. Germany is estimated to have one of the lowest attack rates at 0.7% with 600,000
[240,000-1,500,000] people infected.
Imperial College COVID-19 Response Team
Table l: Posterior model estimates of percentage of total population infected as of 28th March 2020.
Country % of total population infected (mean [95% credible intervall)
Austria 1.1% [0.36%-3.1%]
Belgium 3.7% [1.3%-9.7%]
Denmark 1.1% [0.40%-3.1%]
France 3.0% [1.1%-7.4%]
Germany 0.72% [0.28%-1.8%]
Italy 9.8% [3.2%-26%]
Norway 0.41% [0.09%-1.2%]
Spain 15% [3.7%-41%]
Sweden 3.1% [0.85%-8.4%]
Switzerland 3.2% [1.3%-7.6%]
United Kingdom 2.7% [1.2%-5.4%]
2.2 Reproduction numbers and impact of interventions
Averaged across all countries, we estimate initial reproduction numbers of around 3.87 [3.01-4.66],
which is in line with other estimates.1'8 These estimates are informed by our choice of serial interval
distribution and the initial growth rate of observed deaths. A shorter assumed serial interval results in
lower starting reproduction numbers (Appendix 8.4.2, Appendix 8.4.6). The initial reproduction
numbers are also uncertain due to (a) importation being the dominant source of new infections early
in the epidemic, rather than local transmission (b) possible under-ascertainment in deaths particularly
before testing became widespread.
We estimate large changes in Rt in response to the combined non-pharmaceutical interventions. Our
results, which are driven largely by countries with advanced epidemics and larger numbers of deaths
(e.g. Italy, Spain), suggest that these interventions have together had a substantial impact on
transmission, as measured by changes in the estimated reproduction number Rt. Across all countries
we find current estimates of Rt to range from a posterior mean of 0.97 [0.14-2.14] for Norway to a
posterior mean of2.64 [1.40-4.18] for Sweden, with an average of 1.43 across the 11 country posterior
means, a 64% reduction compared to the pre-intervention values. We note that these estimates are
contingent on intervention impact being the same in different countries and at different times. In all
countries but Sweden, under the same assumptions, we estimate that the current reproduction
number includes 1 in the uncertainty range. The estimated reproduction number for Sweden is higher,
not because the mortality trends are significantly different from any other country, but as an artefact
of our model, which assumes a smaller reduction in Rt because no full lockdown has been ordered so
far. Overall, we cannot yet conclude whether current interventions are sufficient to drive Rt below 1
(posterior probability of being less than 1.0 is 44% on average across the countries). We are also
unable to conclude whether interventions may be different between countries or over time.
There remains a high level of uncertainty in these estimates. It is too early to detect substantial
intervention impact in many countries at earlier stages of their epidemic (e.g. Germany, UK, Norway).
Many interventions have occurred only recently, and their effects have not yet been fully observed
due to the time lag between infection and death. This uncertainty will reduce as more data become
available. For all countries, our model fits observed deaths data well (Bayesian goodness of fit tests).
We also found that our model can reliably forecast daily deaths 3 days into the future, by withholding
the latest 3 days of data and comparing model predictions to observed deaths (Appendix 8.3).
The close spacing of interventions in time made it statistically impossible to determine which had the
greatest effect (Figure 1, Figure 4). However, when doing a sensitivity analysis (Appendix 8.4.3) with
uninformative prior distributions (where interventions can increase deaths) we find similar impact of
Imperial College COVID-19 Response Team
interventions, which shows that our choice of prior distribution is not driving the effects we see in the
main analysis.
Figure 2: Country-level estimates of infections, deaths and Rt. Left: daily number of infections, brown
bars are reported infections, blue bands are predicted infections, dark blue 50% credible interval (CI),
light blue 95% CI. The number of daily infections estimated by our model drops immediately after an
intervention, as we assume that all infected people become immediately less infectious through the
intervention. Afterwards, if the Rt is above 1, the number of infections will starts growing again.
Middle: daily number of deaths, brown bars are reported deaths, blue bands are predicted deaths, CI
as in left plot. Right: time-varying reproduction number Rt, dark green 50% CI, light green 95% CI.
Icons are interventions shown at the time they occurred.
Imperial College COVID-19 Response Team
Table 2: Totalforecasted deaths since the beginning of the epidemic up to 31 March in our model
and in a counterfactual model (assuming no intervention had taken place). Estimated averted deaths
over this time period as a result of the interventions. Numbers in brackets are 95% credible intervals.
2.3 Estimated impact of interventions on deaths
Table 2 shows total forecasted deaths since the beginning of the epidemic up to and including 31
March under ourfitted model and under the counterfactual model, which predicts what would have
happened if no interventions were implemented (and R, = R0 i.e. the initial reproduction number
estimated before interventions). Again, the assumption in these predictions is that intervention
impact is the same across countries and time. The model without interventions was unable to capture
recent trends in deaths in several countries, where the rate of increase had clearly slowed (Figure 3).
Trends were confirmed statistically by Bayesian leave-one-out cross-validation and the widely
applicable information criterion assessments —WA|C).
By comparing the deaths predicted under the model with no interventions to the deaths predicted in
our intervention model, we calculated the total deaths averted up to the end of March. We find that,
across 11 countries, since the beginning of the epidemic, 59,000 [21,000-120,000] deaths have been
averted due to interventions. In Italy and Spain, where the epidemic is advanced, 38,000 [13,000-
84,000] and 16,000 [5,400-35,000] deaths have been averted, respectively. Even in the UK, which is
much earlier in its epidemic, we predict 370 [73-1,000] deaths have been averted.
These numbers give only the deaths averted that would have occurred up to 31 March. lfwe were to
include the deaths of currently infected individuals in both models, which might happen after 31
March, then the deaths averted would be substantially higher.
Figure 3: Daily number of confirmed deaths, predictions (up to 28 March) and forecasts (after) for (a)
Italy and (b) Spain from our model with interventions (blue) and from the no interventions
counterfactual model (pink); credible intervals are shown one week into the future. Other countries
are shown in Appendix 8.6.
03/0 25% 50% 753% 100%
(no effect on transmissibility) (ends transmissibility
Relative % reduction in R.
Figure 4: Our model includes five covariates for governmental interventions, adjusting for whether
the intervention was the first one undertaken by the government in response to COVID-19 (red) or
was subsequent to other interventions (green). Mean relative percentage reduction in Rt is shown
with 95% posterior credible intervals. If 100% reduction is achieved, Rt = 0 and there is no more
transmission of COVID-19. No effects are significantly different from any others, probably due to the
fact that many interventions occurred on the same day or within days of each other as shown in
Figure l.
3 Discussion
During this early phase of control measures against the novel coronavirus in Europe, we analyze trends
in numbers of deaths to assess the extent to which transmission is being reduced. Representing the
COVlD-19 infection process using a semi-mechanistic, joint, Bayesian hierarchical model, we can
reproduce trends observed in the data on deaths and can forecast accurately over short time horizons.
We estimate that there have been many more infections than are currently reported. The high level
of under-ascertainment of infections that we estimate here is likely due to the focus on testing in
hospital settings rather than in the community. Despite this, only a small minority of individuals in
each country have been infected, with an attack rate on average of 4.9% [l.9%-ll%] with considerable
variation between countries (Table 1). Our estimates imply that the populations in Europe are not
close to herd immunity ("50-75% if R0 is 2-4). Further, with Rt values dropping substantially, the rate
of acquisition of herd immunity will slow down rapidly. This implies that the virus will be able to spread
rapidly should interventions be lifted. Such estimates of the attack rate to date urgently need to be
validated by newly developed antibody tests in representative population surveys, once these become
available.
We estimate that major non-pharmaceutical interventions have had a substantial impact on the time-
varying reproduction numbers in countries where there has been time to observe intervention effects
on trends in deaths (Italy, Spain). lfadherence in those countries has changed since that initial period,
then our forecast of future deaths will be affected accordingly: increasing adherence over time will
have resulted in fewer deaths and decreasing adherence in more deaths. Similarly, our estimates of
the impact ofinterventions in other countries should be viewed with caution if the same interventions
have achieved different levels of adherence than was initially the case in Italy and Spain.
Due to the implementation of interventions in rapid succession in many countries, there are not
enough data to estimate the individual effect size of each intervention, and we discourage attributing
associations to individual intervention. In some cases, such as Norway, where all interventions were
implemented at once, these individual effects are by definition unidentifiable. Despite this, while
individual impacts cannot be determined, their estimated joint impact is strongly empirically justified
(see Appendix 8.4 for sensitivity analysis). While the growth in daily deaths has decreased, due to the
lag between infections and deaths, continued rises in daily deaths are to be expected for some time.
To understand the impact of interventions, we fit a counterfactual model without the interventions
and compare this to the actual model. Consider Italy and the UK - two countries at very different stages
in their epidemics. For the UK, where interventions are very recent, much of the intervention strength
is borrowed from countries with older epidemics. The results suggest that interventions will have a
large impact on infections and deaths despite counts of both rising. For Italy, where far more time has
passed since the interventions have been implemented, it is clear that the model without
interventions does not fit well to the data, and cannot explain the sub-linear (on the logarithmic scale)
reduction in deaths (see Figure 10).
The counterfactual model for Italy suggests that despite mounting pressure on health systems,
interventions have averted a health care catastrophe where the number of new deaths would have
been 3.7 times higher (38,000 deaths averted) than currently observed. Even in the UK, much earlier
in its epidemic, the recent interventions are forecasted to avert 370 total deaths up to 31 of March.
4 Conclusion and Limitations
Modern understanding of infectious disease with a global publicized response has meant that
nationwide interventions could be implemented with widespread adherence and support. Given
observed infection fatality ratios and the epidemiology of COVlD-19, major non-pharmaceutical
interventions have had a substantial impact in reducing transmission in countries with more advanced
epidemics. It is too early to be sure whether similar reductions will be seen in countries at earlier
stages of their epidemic. While we cannot determine which set of interventions have been most
successful, taken together, we can already see changes in the trends of new deaths. When forecasting
3 days and looking over the whole epidemic the number of deaths averted is substantial. We note that
substantial innovation is taking place, and new more effective interventions or refinements of current
interventions, alongside behavioral changes will further contribute to reductions in infections. We
cannot say for certain that the current measures have controlled the epidemic in Europe; however, if
current trends continue, there is reason for optimism.
Our approach is semi-mechanistic. We propose a plausible structure for the infection process and then
estimate parameters empirically. However, many parameters had to be given strong prior
distributions or had to be fixed. For these assumptions, we have provided relevant citations to
previous studies. As more data become available and better estimates arise, we will update these in
weekly reports. Our choice of serial interval distribution strongly influences the prior distribution for
starting R0. Our infection fatality ratio, and infection-to-onset-to-death distributions strongly
influence the rate of death and hence the estimated number of true underlying cases.
We also assume that the effect of interventions is the same in all countries, which may not be fully
realistic. This assumption implies that countries with early interventions and more deaths since these
interventions (e.g. Italy, Spain) strongly influence estimates of intervention impact in countries at
earlier stages of their epidemic with fewer deaths (e.g. Germany, UK).
We have tried to create consistent definitions of all interventions and document details of this in
Appendix 8.6. However, invariably there will be differences from country to country in the strength of
their intervention — for example, most countries have banned gatherings of more than 2 people when
implementing a lockdown, whereas in Sweden the government only banned gatherings of more than
10 people. These differences can skew impacts in countries with very little data. We believe that our
uncertainty to some degree can cover these differences, and as more data become available,
coefficients should become more reliable.
However, despite these strong assumptions, there is sufficient signal in the data to estimate changes
in R, (see the sensitivity analysis reported in Appendix 8.4.3) and this signal will stand to increase with
time. In our Bayesian hierarchical framework, we robustly quantify the uncertainty in our parameter
estimates and posterior predictions. This can be seen in the very wide credible intervals in more recent
days, where little or no death data are available to inform the estimates. Furthermore, we predict
intervention impact at country-level, but different trends may be in place in different parts of each
country. For example, the epidemic in northern Italy was subject to controls earlier than the rest of
the country.
5 Data
Our model utilizes daily real-time death data from the ECDC (European Centre of Disease Control),
where we catalogue case data for 11 European countries currently experiencing the epidemic: Austria,
Belgium, Denmark, France, Germany, Italy, Norway, Spain, Sweden, Switzerland and the United
Kingdom. The ECDC provides information on confirmed cases and deaths attributable to COVID-19.
However, the case data are highly unrepresentative of the incidence of infections due to
underreporting as well as systematic and country-specific changes in testing.
We, therefore, use only deaths attributable to COVID-19 in our model; we do not use the ECDC case
estimates at all. While the observed deaths still have some degree of unreliability, again due to
changes in reporting and testing, we believe the data are ofsufficient fidelity to model. For population
counts, we use UNPOP age-stratified counts.10
We also catalogue data on the nature and type of major non-pharmaceutical interventions. We looked
at the government webpages from each country as well as their official public health
division/information webpages to identify the latest advice/laws being issued by the government and
public health authorities. We collected the following:
School closure ordered: This intervention refers to nationwide extraordinary school closures which in
most cases refer to both primary and secondary schools closing (for most countries this also includes
the closure of otherforms of higher education or the advice to teach remotely). In the case of Denmark
and Sweden, we allowed partial school closures of only secondary schools. The date of the school
closure is taken to be the effective date when the schools started to be closed (ifthis was on a Monday,
the date used was the one of the previous Saturdays as pupils and students effectively stayed at home
from that date onwards).
Case-based measures: This intervention comprises strong recommendations or laws to the general
public and primary care about self—isolation when showing COVID-19-like symptoms. These also
include nationwide testing programs where individuals can be tested and subsequently self—isolated.
Our definition is restricted to nationwide government advice to all individuals (e.g. UK) or to all primary
care and excludes regional only advice. These do not include containment phase interventions such
as isolation if travelling back from an epidemic country such as China.
Public events banned: This refers to banning all public events of more than 100 participants such as
sports events.
Social distancing encouraged: As one of the first interventions against the spread of the COVID-19
pandemic, many governments have published advice on social distancing including the
recommendation to work from home wherever possible, reducing use ofpublictransport and all other
non-essential contact. The dates used are those when social distancing has officially been
recommended by the government; the advice may include maintaining a recommended physical
distance from others.
Lockdown decreed: There are several different scenarios that the media refers to as lockdown. As an
overall definition, we consider regulations/legislations regarding strict face-to-face social interaction:
including the banning of any non-essential public gatherings, closure of educational and
public/cultural institutions, ordering people to stay home apart from exercise and essential tasks. We
include special cases where these are not explicitly mentioned on government websites but are
enforced by the police (e.g. France). The dates used are the effective dates when these legislations
have been implemented. We note that lockdown encompasses other interventions previously
implemented.
First intervention: As Figure 1 shows, European governments have escalated interventions rapidly,
and in some examples (Norway/Denmark) have implemented these interventions all on a single day.
Therefore, given the temporal autocorrelation inherent in government intervention, we include a
binary covariate for the first intervention, which can be interpreted as a government decision to take
major action to control COVID-19.
A full list of the timing of these interventions and the sources we have used can be found in Appendix
8.6.
6 Methods Summary
A Visual summary of our model is presented in Figure 5 (details in Appendix 8.1 and 8.2). Replication
code is available at https://github.com/|mperia|CollegeLondon/covid19model/releases/tag/vl.0
We fit our model to observed deaths according to ECDC data from 11 European countries. The
modelled deaths are informed by an infection-to-onset distribution (time from infection to the onset
of symptoms), an onset-to-death distribution (time from the onset of symptoms to death), and the
population-averaged infection fatality ratio (adjusted for the age structure and contact patterns of
each country, see Appendix). Given these distributions and ratios, modelled deaths are a function of
the number of infections. The modelled number of infections is informed by the serial interval
distribution (the average time from infection of one person to the time at which they infect another)
and the time-varying reproduction number. Finally, the time-varying reproduction number is a
function of the initial reproduction number before interventions and the effect sizes from
interventions.
Figure 5: Summary of model components.
Following the hierarchy from bottom to top gives us a full framework to see how interventions affect
infections, which can result in deaths. We use Bayesian inference to ensure our modelled deaths can
reproduce the observed deaths as closely as possible. From bottom to top in Figure 5, there is an
implicit lag in time that means the effect of very recent interventions manifest weakly in current
deaths (and get stronger as time progresses). To maximise the ability to observe intervention impact
on deaths, we fit our model jointly for all 11 European countries, which results in a large data set. Our
model jointly estimates the effect sizes of interventions. We have evaluated the effect ofour Bayesian
prior distribution choices and evaluate our Bayesian posterior calibration to ensure our results are
statistically robust (Appendix 8.4).
7 Acknowledgements
Initial research on covariates in Appendix 8.6 was crowdsourced; we thank a number of people
across the world for help with this. This work was supported by Centre funding from the UK Medical
Research Council under a concordat with the UK Department for International Development, the
NIHR Health Protection Research Unit in Modelling Methodology and CommunityJameel.
8 Appendix: Model Specifics, Validation and Sensitivity Analysis
8.1 Death model
We observe daily deaths Dam for days t E 1, ...,n and countries m E 1, ...,p. These daily deaths are
modelled using a positive real-Valued function dam = E(Dam) that represents the expected number
of deaths attributed to COVID-19. Dam is assumed to follow a negative binomial distribution with
The expected number of deaths (1 in a given country on a given day is a function of the number of
infections C occurring in previous days.
At the beginning of the epidemic, the observed deaths in a country can be dominated by deaths that
result from infection that are not locally acquired. To avoid biasing our model by this, we only include
observed deaths from the day after a country has cumulatively observed 10 deaths in our model.
To mechanistically link ourfunction for deaths to infected cases, we use a previously estimated COVID-
19 infection-fatality-ratio ifr (probability of death given infection)9 together with a distribution oftimes
from infection to death TE. The ifr is derived from estimates presented in Verity et al11 which assumed
homogeneous attack rates across age-groups. To better match estimates of attack rates by age
generated using more detailed information on country and age-specific mixing patterns, we scale
these estimates (the unadjusted ifr, referred to here as ifr’) in the following way as in previous work.4
Let Ca be the number of infections generated in age-group a, Na the underlying size of the population
in that age group and AR“ 2 Ca/Na the age-group-specific attack rate. The adjusted ifr is then given
by: ifra = fififié, where AR50_59 is the predicted attack-rate in the 50-59 year age-group after
incorporating country-specific patterns of contact and mixing. This age-group was chosen as the
reference as it had the lowest predicted level of underreporting in previous analyses of data from the
Chinese epidemic“. We obtained country-specific estimates of attack rate by age, AR“, for the 11
European countries in our analysis from a previous study which incorporates information on contact
between individuals of different ages in countries across Europe.12 We then obtained overall ifr
estimates for each country adjusting for both demography and age-specific attack rates.
Using estimated epidemiological information from previous studies,“'11 we assume TE to be the sum of
two independent random times: the incubation period (infection to onset of symptoms or infection-
to-onset) distribution and the time between onset of symptoms and death (onset-to-death). The
infection-to-onset distribution is Gamma distributed with mean 5.1 days and coefficient of variation
0.86. The onset-to-death distribution is also Gamma distributed with a mean of 18.8 days and a
coefficient of va riation 0.45. ifrm is population averaged over the age structure of a given country. The
infection-to-death distribution is therefore given by:
um ~ ifrm ~ (Gamma(5.1,0.86) + Gamma(18.8,0.45))
Figure 6 shows the infection-to-death distribution and the resulting survival function that integrates
to the infection fatality ratio.
Figure 6: Left, infection-to-death distribution (mean 23.9 days). Right, survival probability of infected
individuals per day given the infection fatality ratio (1%) and the infection-to-death distribution on
the left.
Using the probability of death distribution, the expected number of deaths dam, on a given day t, for
country, m, is given by the following discrete sum:
The number of deaths today is the sum of the past infections weighted by their probability of death,
where the probability of death depends on the number of days since infection.
8.2 Infection model
The true number of infected individuals, C, is modelled using a discrete renewal process. This approach
has been used in numerous previous studies13'16 and has a strong theoretical basis in stochastic
individual-based counting processes such as Hawkes process and the Bellman-Harris process.”18 The
renewal model is related to the Susceptible-Infected-Recovered model, except the renewal is not
expressed in differential form. To model the number ofinfections over time we need to specify a serial
interval distribution g with density g(T), (the time between when a person gets infected and when
they subsequently infect another other people), which we choose to be Gamma distributed:
g ~ Gamma (6.50.62).
The serial interval distribution is shown below in Figure 7 and is assumed to be the same for all
countries.
Figure 7: Serial interval distribution g with a mean of 6.5 days.
Given the serial interval distribution, the number of infections Eamon a given day t, and country, m,
is given by the following discrete convolution function:
_ t—1
Cam — Ram ZT=0 Cr,mgt—‘r r
where, similarto the probability ofdeath function, the daily serial interval is discretized by
fs+0.5
1.5
gs = T=s—0.Sg(T)dT fors = 2,3, and 91 = fT=Og(T)dT.
Infections today depend on the number of infections in the previous days, weighted by the discretized
serial interval distribution. This weighting is then scaled by the country-specific time-Varying
reproduction number, Ram, that models the average number of secondary infections at a given time.
The functional form for the time-Varying reproduction number was chosen to be as simple as possible
to minimize the impact of strong prior assumptions: we use a piecewise constant function that scales
Ram from a baseline prior R0,m and is driven by known major non-pharmaceutical interventions
occurring in different countries and times. We included 6 interventions, one of which is constructed
from the other 5 interventions, which are timings of school and university closures (k=l), self—isolating
if ill (k=2), banning of public events (k=3), any government intervention in place (k=4), implementing
a partial or complete lockdown (k=5) and encouraging social distancing and isolation (k=6). We denote
the indicator variable for intervention k E 1,2,3,4,5,6 by IkI’m, which is 1 if intervention k is in place
in country m at time t and 0 otherwise. The covariate ”any government intervention” (k=4) indicates
if any of the other 5 interventions are in effect,i.e.14’t’m equals 1 at time t if any of the interventions
k E 1,2,3,4,5 are in effect in country m at time t and equals 0 otherwise. Covariate 4 has the
interpretation of indicating the onset of major government intervention. The effect of each
intervention is assumed to be multiplicative. Ram is therefore a function ofthe intervention indicators
Ik’t’m in place at time t in country m:
Ram : R0,m eXp(— 212:1 O(Rheum)-
The exponential form was used to ensure positivity of the reproduction number, with R0,m
constrained to be positive as it appears outside the exponential. The impact of each intervention on
Ram is characterised by a set of parameters 0(1, ...,OL6, with independent prior distributions chosen
to be
ock ~ Gamma(. 5,1).
The impacts ock are shared between all m countries and therefore they are informed by all available
data. The prior distribution for R0 was chosen to be
R0,m ~ Normal(2.4, IKI) with K ~ Normal(0,0.5),
Once again, K is the same among all countries to share information.
We assume that seeding of new infections begins 30 days before the day after a country has
cumulatively observed 10 deaths. From this date, we seed our model with 6 sequential days of
infections drawn from cl’m,...,66’m~EXponential(T), where T~Exponential(0.03). These seed
infections are inferred in our Bayesian posterior distribution.
We estimated parameters jointly for all 11 countries in a single hierarchical model. Fitting was done
in the probabilistic programming language Stan,19 using an adaptive Hamiltonian Monte Carlo (HMC)
sampler. We ran 8 chains for 4000 iterations with 2000 iterations of warmup and a thinning factor 4
to obtain 2000 posterior samples. Posterior convergence was assessed using the Rhat statistic and by
diagnosing divergent transitions of the HMC sampler. Prior-posterior calibrations were also performed
(see below).
8.3 Validation
We validate accuracy of point estimates of our model using cross-Validation. In our cross-validation
scheme, we leave out 3 days of known death data (non-cumulative) and fit our model. We forecast
what the model predicts for these three days. We present the individual forecasts for each day, as
well as the average forecast for those three days. The cross-validation results are shown in the Figure
8.
Figure 8: Cross-Validation results for 3-day and 3-day aggregatedforecasts
Figure 8 provides strong empirical justification for our model specification and mechanism. Our
accurate forecast over a three-day time horizon suggests that our fitted estimates for Rt are
appropriate and plausible.
Along with from point estimates we all evaluate our posterior credible intervals using the Rhat
statistic. The Rhat statistic measures whether our Markov Chain Monte Carlo (MCMC) chains have
converged to the equilibrium distribution (the correct posterior distribution). Figure 9 shows the Rhat
statistics for all of our parameters
Figure 9: Rhat statistics - values close to 1 indicate MCMC convergence.
Figure 9 indicates that our MCMC have converged. In fitting we also ensured that the MCMC sampler
experienced no divergent transitions - suggesting non pathological posterior topologies.
8.4 SensitivityAnalysis
8.4.1 Forecasting on log-linear scale to assess signal in the data
As we have highlighted throughout in this report, the lag between deaths and infections means that
it ta kes time for information to propagate backwa rds from deaths to infections, and ultimately to Rt.
A conclusion of this report is the prediction of a slowing of Rt in response to major interventions. To
gain intuition that this is data driven and not simply a consequence of highly constrained model
assumptions, we show death forecasts on a log-linear scale. On this scale a line which curves below a
linear trend is indicative of slowing in the growth of the epidemic. Figure 10 to Figure 12 show these
forecasts for Italy, Spain and the UK. They show this slowing down in the daily number of deaths. Our
model suggests that Italy, a country that has the highest death toll of COVID-19, will see a slowing in
the increase in daily deaths over the coming week compared to the early stages of the epidemic.
We investigated the sensitivity of our estimates of starting and final Rt to our assumed serial interval
distribution. For this we considered several scenarios, in which we changed the serial interval
distribution mean, from a value of 6.5 days, to have values of 5, 6, 7 and 8 days.
In Figure 13, we show our estimates of R0, the starting reproduction number before interventions, for
each of these scenarios. The relative ordering of the Rt=0 in the countries is consistent in all settings.
However, as expected, the scale of Rt=0 is considerably affected by this change — a longer serial
interval results in a higher estimated Rt=0. This is because to reach the currently observed size of the
epidemics, a longer assumed serial interval is compensated by a higher estimated R0.
Additionally, in Figure 14, we show our estimates of Rt at the most recent model time point, again for
each ofthese scenarios. The serial interval mean can influence Rt substantially, however, the posterior
credible intervals of Rt are broadly overlapping.
Figure 13: Initial reproduction number R0 for different serial interval (SI) distributions (means
between 5 and 8 days). We use 6.5 days in our main analysis.
Figure 14: Rt on 28 March 2020 estimated for all countries, with serial interval (SI) distribution means
between 5 and 8 days. We use 6.5 days in our main analysis.
8.4.3 Uninformative prior sensitivity on or
We ran our model using implausible uninformative prior distributions on the intervention effects,
allowing the effect of an intervention to increase or decrease Rt. To avoid collinearity, we ran 6
separate models, with effects summarized below (compare with the main analysis in Figure 4). In this
series of univariate analyses, we find (Figure 15) that all effects on their own serve to decrease Rt.
This gives us confidence that our choice of prior distribution is not driving the effects we see in the
main analysis. Lockdown has a very large effect, most likely due to the fact that it occurs after other
interventions in our dataset. The relatively large effect sizes for the other interventions are most likely
due to the coincidence of the interventions in time, such that one intervention is a proxy for a few
others.
Figure 15: Effects of different interventions when used as the only covariate in the model.
8.4.4
To assess prior assumptions on our piecewise constant functional form for Rt we test using a
nonparametric function with a Gaussian process prior distribution. We fit a model with a Gaussian
process prior distribution to data from Italy where there is the largest signal in death data. We find
that the Gaussian process has a very similartrend to the piecewise constant model and reverts to the
mean in regions of no data. The correspondence of a completely nonparametric function and our
piecewise constant function suggests a suitable parametric specification of Rt.
Nonparametric fitting of Rf using a Gaussian process:
8.4.5 Leave country out analysis
Due to the different lengths of each European countries’ epidemic, some countries, such as Italy have
much more data than others (such as the UK). To ensure that we are not leveraging too much
information from any one country we perform a ”leave one country out” sensitivity analysis, where
we rerun the model without a different country each time. Figure 16 and Figure 17 are examples for
results for the UK, leaving out Italy and Spain. In general, for all countries, we observed no significant
dependence on any one country.
Figure 16: Model results for the UK, when not using data from Italy for fitting the model. See the
Figure 17: Model results for the UK, when not using data from Spain for fitting the model. See caption
of Figure 2 for an explanation of the plots.
8.4.6 Starting reproduction numbers vs theoretical predictions
To validate our starting reproduction numbers, we compare our fitted values to those theoretically
expected from a simpler model assuming exponential growth rate, and a serial interval distribution
mean. We fit a linear model with a Poisson likelihood and log link function and extracting the daily
growth rate r. For well-known theoretical results from the renewal equation, given a serial interval
distribution g(r) with mean m and standard deviation 5, given a = mZ/S2 and b = m/SZ, and
a
subsequently R0 = (1 + %) .Figure 18 shows theoretically derived R0 along with our fitted
estimates of Rt=0 from our Bayesian hierarchical model. As shown in Figure 18 there is large
correspondence between our estimated starting reproduction number and the basic reproduction
number implied by the growth rate r.
R0 (red) vs R(FO) (black)
Figure 18: Our estimated R0 (black) versus theoretically derived Ru(red) from a log-linear
regression fit.
8.5 Counterfactual analysis — interventions vs no interventions
Figure 19: Daily number of confirmed deaths, predictions (up to 28 March) and forecasts (after) for
all countries except Italy and Spain from our model with interventions (blue) and from the no
interventions counterfactual model (pink); credible intervals are shown one week into the future.
DOI: https://doi.org/10.25561/77731
Page 28 of 35
30 March 2020 Imperial College COVID-19 Response Team
8.6 Data sources and Timeline of Interventions
Figure 1 and Table 3 display the interventions by the 11 countries in our study and the dates these
interventions became effective.
Table 3: Timeline of Interventions.
Country Type Event Date effective
School closure
ordered Nationwide school closures.20 14/3/2020
Public events
banned Banning of gatherings of more than 5 people.21 10/3/2020
Banning all access to public spaces and gatherings
Lockdown of more than 5 people. Advice to maintain 1m
ordered distance.22 16/3/2020
Social distancing
encouraged Recommendation to maintain a distance of 1m.22 16/3/2020
Case-based
Austria measures Implemented at lockdown.22 16/3/2020
School closure
ordered Nationwide school closures.23 14/3/2020
Public events All recreational activities cancelled regardless of
banned size.23 12/3/2020
Citizens are required to stay at home except for
Lockdown work and essential journeys. Going outdoors only
ordered with household members or 1 friend.24 18/3/2020
Public transport recommended only for essential
Social distancing journeys, work from home encouraged, all public
encouraged places e.g. restaurants closed.23 14/3/2020
Case-based Everyone should stay at home if experiencing a
Belgium measures cough or fever.25 10/3/2020
School closure Secondary schools shut and universities (primary
ordered schools also shut on 16th).26 13/3/2020
Public events Bans of events >100 people, closed cultural
banned institutions, leisure facilities etc.27 12/3/2020
Lockdown Bans of gatherings of >10 people in public and all
ordered public places were shut.27 18/3/2020
Limited use of public transport. All cultural
Social distancing institutions shut and recommend keeping
encouraged appropriate distance.28 13/3/2020
Case-based Everyone should stay at home if experiencing a
Denmark measures cough or fever.29 12/3/2020
School closure
ordered Nationwide school closures.30 14/3/2020
Public events
banned Bans of events >100 people.31 13/3/2020
Lockdown Everybody has to stay at home. Need a self-
ordered authorisation form to leave home.32 17/3/2020
Social distancing
encouraged Advice at the time of lockdown.32 16/3/2020
Case-based
France measures Advice at the time of lockdown.32 16/03/2020
School closure
ordered Nationwide school closures.33 14/3/2020
Public events No gatherings of >1000 people. Otherwise
banned regional restrictions only until lockdown.34 22/3/2020
Lockdown Gatherings of > 2 people banned, 1.5 m
ordered distance.35 22/3/2020
Social distancing Avoid social interaction wherever possible
encouraged recommended by Merkel.36 12/3/2020
Advice for everyone experiencing symptoms to
Case-based contact a health care agency to get tested and
Germany measures then self—isolate.37 6/3/2020
School closure
ordered Nationwide school closures.38 5/3/2020
Public events
banned The government bans all public events.39 9/3/2020
Lockdown The government closes all public places. People
ordered have to stay at home except for essential travel.40 11/3/2020
A distance of more than 1m has to be kept and
Social distancing any other form of alternative aggregation is to be
encouraged excluded.40 9/3/2020
Case-based Advice to self—isolate if experiencing symptoms
Italy measures and quarantine if tested positive.41 9/3/2020
Norwegian Directorate of Health closes all
School closure educational institutions. Including childcare
ordered facilities and all schools.42 13/3/2020
Public events The Directorate of Health bans all non-necessary
banned social contact.42 12/3/2020
Lockdown Only people living together are allowed outside
ordered together. Everyone has to keep a 2m distance.43 24/3/2020
Social distancing The Directorate of Health advises against all
encouraged travelling and non-necessary social contacts.42 16/3/2020
Case-based Advice to self—isolate for 7 days if experiencing a
Norway measures cough or fever symptoms.44 15/3/2020
ordered Nationwide school closures.45 13/3/2020
Public events
banned Banning of all public events by lockdown.46 14/3/2020
Lockdown
ordered Nationwide lockdown.43 14/3/2020
Social distancing Advice on social distancing and working remotely
encouraged from home.47 9/3/2020
Case-based Advice to self—isolate for 7 days if experiencing a
Spain measures cough or fever symptoms.47 17/3/2020
School closure
ordered Colleges and upper secondary schools shut.48 18/3/2020
Public events
banned The government bans events >500 people.49 12/3/2020
Lockdown
ordered No lockdown occurred. NA
People even with mild symptoms are told to limit
Social distancing social contact, encouragement to work from
encouraged home.50 16/3/2020
Case-based Advice to self—isolate if experiencing a cough or
Sweden measures fever symptoms.51 10/3/2020
School closure
ordered No in person teaching until 4th of April.52 14/3/2020
Public events
banned The government bans events >100 people.52 13/3/2020
Lockdown
ordered Gatherings of more than 5 people are banned.53 2020-03-20
Advice on keeping distance. All businesses where
Social distancing this cannot be realised have been closed in all
encouraged states (kantons).54 16/3/2020
Case-based Advice to self—isolate if experiencing a cough or
Switzerland measures fever symptoms.55 2/3/2020
Nationwide school closure. Childminders,
School closure nurseries and sixth forms are told to follow the
ordered guidance.56 21/3/2020
Public events
banned Implemented with lockdown.57 24/3/2020
Gatherings of more than 2 people not from the
Lockdown same household are banned and police
ordered enforceable.57 24/3/2020
Social distancing Advice to avoid pubs, clubs, theatres and other
encouraged public institutions.58 16/3/2020
Case-based Advice to self—isolate for 7 days if experiencing a
UK measures cough or fever symptoms.59 12/3/2020
9 References
1. Li, R. et al. Substantial undocumented infection facilitates the rapid dissemination of novel
coronavirus (SARS-CoV2). Science (2020) doi:10.1126/science.abb3221.
2. Zhang, J. et al. Patterns of human social contact and contact with animals in Shanghai, China.
5cLRep.9,1—11(2019)
3. Worldometers.info. Hong Kong: coronavirus cases.
https://www.wo rldometers.info/co ronavirus/country/china-hong-kong-sar/.
4. Ferguson, N. et al. Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19
mortality and healthcare demand (Report 9). https://www.imperial.ac.uk/mrc-global-infectious-
disease-analysis/news--wuhan-coronavirus/.
5. Cereda, D. et al. The early phase of the COVID-19 outbreak in Lombardy, Italy. arXiv (2020).
6. Zhao, A. J. et al. Title: Antibody responses to SARS-CoV-2 in patients of novel coronavirus
disease 2019 Brief Title : Antibody responses in COVID-19 patients. (2020).
7. Jombart, T. et al. Inferring the number of COVID-19 cases from recently reported deaths.
medRXiV 2020.03.10.20033761(2020)doi:10.1101/2020.03.10.20033761.
8. Zhang, J. et al. Age profile of susceptibility, mixing, and social distancing shape the dynamics
of the novel coronavirus disease 2019 outbreak in China. (2020) doi:10.1101/2020.03.19.20039107.
9. Lourenco, J. et al. Fundamental principles of epidemic spread highlight the immediate need
for large-scale serological surveys to assess the stage of the SARS-CoV-2 epidemic.
doi:10.1101/2020.03.24.20042291
10. United Nations, Department of Economic and Social Affairs, Population Division. World
Population Prospects 2019: Data Booket. ST/ESA/SER.A/424. (2019).
11. Verity, R. et al. Estimates ofthe severity of COVID-19 disease. Lancet Infect Dis in press, (2020).
12. Walker, P. G. T. et al. Report 12: The Global Impact of COVID-19 and Strategies for Mitigation
and Suppression.
13. Fraser, C. Estimating Individual and Household Reproduction Numbers in an Emerging
Epidemic. PL05 ONE 2, e758 (2007).
14. Cori, A., Ferguson, N. M., Fraser, C. & Cauchemez, S. A New Framework and Software to
Estimate Time-Varying Reproduction Numbers During Epidemics. Am. J. Epidemiol. 178, 1505—1512
(20131
15. Nouvellet, P. et al. A simple approach to measure transmissibility and forecast incidence.
Epidemics 22, 29—35 (2018).
16. Cauchemez, 8., Valleron, A. J., Boelle, P. Y., Flahault, A. & Ferguson, N. M. Estimating the
impact of school closure on influenza transmission from Sentinel data. Nature 452, 750—754 (2008).
17. Bellman, R. & Harris, T. On Age-Dependent Binary Branching Processes. Ann. Math. 55, 280—
295(19521
18. Bellman, R. & Harris, T. E. On the Theory of Age-Dependent Stochastic Branching Processes.
Proc. Natl. Acad. Sci. 34, 601—604 (1948).
19. Stan Development Team. 2018. The Stan Core Library, Version 2.18.0. http://mc-stan.org.
20. Bundesministerium. Coronavirus (COVID-19): Status quo — Schulen, Hochschulen,
Universitaten und Forschungsinstitutionen.
https://www.bmbwf.gv.at/Ministerium/Informationspflicht/corona/corona_status.html.
21. Henley, J. Coronavirus: EU states enact tough measures to stem spread. The Guardian
https://www.theguardian.com/world/2020/mar/10/coronavirus-several-eu-states-ban-mass-events-
after-italian-lockdown (2020).
22. Bundesministerium. Coronavirus - Aktuelle MaBnahmen.
https://www.sozialministerium.at/Informationen-zum-Coronavirus/Coronavirus—Aktuelle-
MaBnahmen.html (2020).
23. Federal Public Service. Coronavirus : Phase 2 maintained, transition to the federal phase and
additional measures. https://www.info-coronavirus.be/en/2020/03/12/phase-2-maintained-
transition-to-the-federal-phase-and-additional-measures/ (2020).
24. Belgium.be. Coronavirus: reinforced measures | Belgium.be.
https://www.belgium.be/en/news/2020/coronavirus_reinforced_measures (2020).
25. Federal Public Service. Protect yourself and protect the others. https://www.info-
coronavirus.be/en/2020/03/10/protect-yourself—and-protect-the-others/ (2020).
26. Wikipedia. 2020 coronavirus pandemic in Denmark. Wikimedia Foundation
https://en.wikipedia.org/wiki/2020_coronavirus_pandemic_in_Denmark.
27. Stephensen, Emma K|inker; Hansen, T. S. Danmark lukker ned: Her er regeringens nye tiltag.
TV2 https://nyheder.tv2.dk/samfund/2020-03-11-danmark-lukker-ned-her-er-regeringens-nye-tiltag
(20201
28. Politi. Nye tiltag mod covid-19. Politi https://politi.dk/coronavirus-i-danmark/seneste-nyt-fra-
myndighederne/nye-tiltag-mod-covid-19 (2020).
29. Styrelsen for Patientsikkerhed. Indberetning om covid-19zlnformation om mulighed for
p\aabud til enkeltpersoner (coronavirus/covid-19). https://stps.dk/da/ansvar-og-
retningslinjer/vejledning/indberetning-om-covid-19/#.
30. Wikipedia. 2020 coronavirus pandemic in France. Wikimedia Foundation
https://en.wikipedia.org/wiki/2020_coronavirus_pandemic_in_France.
31. The Local. France bans gatherings of more than 100 people as coronavirus death toll rises -
The Local. The Local https://www.thelocal.fr/20200313/france-bans-gatherings-of—over-100-people-
to-fight-coronavirus-pandemic (2020).
32. Henley, Jon; Willsher, Kim; Kassam, A. Coronavirus: France imposes lockdown as EU calls for
30-day travel ban. The Guardian https://www.theguardian.com/world/2020/mar/16/coronavirus-
spain-takes-over-private-healthcare-amid-more-european-lockdowns (2020).
33. Wikipedia. 2020 coronavirus pandemic in Germany. Wikimedia Foundation
https://en.wikipedia.org/wiki/2020_coronavirus_pandemic_in_Germany.
34. BMI. Coronavirus: Fragen und Antworten. Bundesministerium des Innern,fur Bau und Heimat
https://web.archive.org/web/20200317073042/https://www.bmi.bund.de/SharedDocs/faqs/DE/the
men/bevoelkerungsschutz/coronavirus/coronavirus-faqs.htmI#doc13738352bodyText7.
35. BBC News. Coronavirus: Germany tightens curbs and bans meetings of more than two. BBC
News https://www.bbc.co.uk/news/world-europe-51999080 (2020).
36. Bundesregierung. Kanzlerin trifft Regierungschefs der Lander Sozialkontakte vermeiden,
Ausbreitung verlangsamen. https://www.bundesregierung.de/breg-de/themen/coronavirus/mpk-
1730186(2020)
37. Robert Koch Institut. Antworten auf haufig gestellte Fragen zum Coronavirus SARS-CoV-2.
Robert Koch Institut
https://web.archive.org/web/20200312004624/https://www.rki.de/SharedDocs/FAQ/NCOV2019/F
AQ_Liste.html (2020).
38. Ministero della Salute. Governo annuncia sospensione dell’attivita didattica dal 5 a|15 marzo.
Ministero della Salute
http://www.salute.gov.it/portale/nuovocoronavirus/dettaglioVideoNuovoCoronavirus.jsp?lingua=ita
liano&menu=multimedia&p=video&id=2052 (2020).
39. CNN. Italy prohibits travel and cancels all public events in its northern region. CNN
https://edition.cnn.com/2020/03/08/europe/italy-coronavirus-lockdown-europe-intl/index.html
(2020).
40. Attualita. Coronavirus: stop a pub, cinema, teatro e discoteche anche a Roma. Ecco cosa
prevede il nuovo decreto. Roma Today https://www.romatoday.it/attualita/coronavirus-pub-cinema-
teatri-locali-chiusi-nuovo-decreto.html (2020).
41. Gazzetta Ufficiale. DECRETO DEL PRESIDENTE DEL CONSIGLIO DEl MINISTRI. Gazzetta Ufflclale
https://www.gazzettaufficiale.it/eli/id/2020/03/08/20A01522/sg (2020).
42. Helsedirektoratet. The Norwegian Directorate of Health has issued a decision to close schools
and other educational institutions. Helsedirektoratet https://www.helsedirektoratet.no/nyheter/the-
norwegian-directorate-of—health-has-issued-a-decision-to-close-schools-and-other-educationa|-
institutions (2020).
43. Krostensen, Mette; Hellem-Hansen, Viktoria L.; Tandstad, B. Folkehelseinstituttet mener
23.000 kan vaere smittet. NRK https://www.nrk.no/norge/folkehelseinstituttet-mener-23.000-kan-
vaere-smittet-1.14958149 (2020).
44. Norweigen Government. The Government is establishing clear quarantine and isolation rules.
regjeringen.no https://www.regjeringen.no/en/aktuelt/the-government-is-establishing-clear-
quarantine-and-isolation-rules/id2693647/ (2020).
45. Wikipedia. 2020 coronavirus pandemic in Spain. Wikimedia Foundation
https://en.wikipedia.org/wiki/2020_coronavirus_pandemic_in_Spain.
46. Gabinete de Prensa. El Gobierno anuncia nuevas medidas para evitar la extension del nuevo
coronavirus COVID-19. Gobierno de Espana
https://www.mscbs.gob.es/gabinete/notasPrensa.do?id=4807 (2020).
47. Gabinete de Prensa. El Consejo Interterritorial del SNS acuerda medidas concretas para zonas
con transmision comunitaria significativa de coronavirus. Gobierno de Espana
https://www.mscbs.gob.es/gabinete/notasPrensa.do?id=4806 (2020).
48. Folkhalsomyndigheten. Larosaten och gymnasieskolor uppmanas nu att bedriva
distansundervisning. Folkhdlsomyndigheten https://www.folkhalsomyndigheten.se/nyheter-och-
press/nyhetsarkiv/2020/mars/larosaten-och-gymnasieskolor-uppmanas-nu-att-bedriva-
distansundervisning(2020).
49. The Local. Sweden bans large events to halt coronavirus spread. The Local
https://www.theloca|.se/20200311/sweden-to-ban-large-public-gatherings-over-coronavirus (2020).
50. Radosevich. Stockholmers urged to work from home as COVID-19 community spread
confirmed. Sveriges Radio
https://sverigesradio.se/sida/artikel.aspx?programid=2054&artikel=7430511(2020).
51. Folkhalsomyndigheten. Flera tecken p\aa samhallsspridning av covid-19 i Sverige.
Folkhdlsomyndigheten https://www.folkhalsomyndigheten.se/nyheter-och-
press/nyhetsarkiv/2020/mars/flera-tecken-pa-samhallsspridning-av-covid-19-i-sverige/ (2020).
52. Bundesamt fur Gesendheit BAG. Bundesrat verscharft Massnahmen gegen das Coronavirus
zum Schutz der Gesundheit und unterstUtzt betroffene Branchen. Schweizerische Eidgenossenschaft
https://www.bag.admin.ch/bag/de/home/das-bag/aktuell/medienmitteilungen.msg-id-78437.html
(20201
53. Bundesamt fur Gesundheit BAG. Coronavirus: Bundesrat verbietet Ansammlungen von mehr
als fUnf Personen. Schweizerische Eidgenossenschaft https://www.bag.admin.ch/bag/de/home/das-
bag/aktuell/medienmitteilungen.msg-id-78513.html (2020).
54. Bundesamt fur Gesundheit BAG. Coronavirus: Bundesrat erklart die «ausserordentliche Lage»
und verscharft die Massnahmen. Schweizerische Eidgenossenschaft
https://www.bag.admin.ch/bag/de/home/das-bag/aktuell/medienmitteilungen.msg-id-78454.html
(20201
55. Bundesamt fur Gesundheit BAG. Neue Hygiene- und Verhaltensregeln zum Schutz gegen das
neue Coronavirus. Schweizerische Eidgenossenschaft https://www.bag.admin.ch/bag/de/home/das-
bag/a ktuell/medienmitteilungen.msg-id-78304.html (2020).
56. UK Government, D. for E. Schools, colleges and early years settings to close. UK Government
https://www.gov.uk/government/news/schools-colleges-and-early-years-settings-to-close (2020).
57. UK Government. PM address to the nation on coronavirus: 23 March 2020. UK Government
https://www.gov.uk/government/speeches/pm-address-to-the-nation-on-coronavirus-23-march-
2020(20201
58. Boycott-Owen, Mason; Bowman, Verity; Kelly-Linden, Jordan; Gartner, A. G. H. S. T.
Coronavirus: Boris Johnson puts UK in lockdown as death tolls reaches 55. The Telegraph
https://www.telegraph.co.uk/global-health/science-and-disease/coronavirus-news-uk-latest-
update-covid-19-death-toll-cases/ (2020).
59. BBC News. Coronavirus: People with fever or ’continuous’ cough told to self—isolate. BBC News
https://www.bbc.co.uk/news/uk-51857856 (2020). | What is a lockdown? | false | 1,083 | {
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1,660 | Hantaviruses in the Americas and Their Role as Emerging Pathogens
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3185593/
SHA: efe13a8d42b60ef9f7387ea539a1b2eeb5f80101
Authors: Hjelle, Brian; Torres-Pérez, Fernando
Date: 2010-11-25
DOI: 10.3390/v2122559
License: cc-by
Abstract: The continued emergence and re-emergence of pathogens represent an ongoing, sometimes major, threat to populations. Hantaviruses (family Bunyaviridae) and their associated human diseases were considered to be confined to Eurasia, but the occurrence of an outbreak in 1993–94 in the southwestern United States led to a great increase in their study among virologists worldwide. Well over 40 hantaviral genotypes have been described, the large majority since 1993, and nearly half of them pathogenic for humans. Hantaviruses cause persistent infections in their reservoir hosts, and in the Americas, human disease is manifest as a cardiopulmonary compromise, hantavirus cardiopulmonary syndrome (HCPS), with case-fatality ratios, for the most common viral serotypes, between 30% and 40%. Habitat disturbance and larger-scale ecological disturbances, perhaps including climate change, are among the factors that may have increased the human caseload of HCPS between 1993 and the present. We consider here the features that influence the structure of host population dynamics that may lead to viral outbreaks, as well as the macromolecular determinants of hantaviruses that have been regarded as having potential contribution to pathogenicity.
Text: Emerging pathogens cause new or previously unrecognized diseases, and among them, emerging zoonotic diseases are a major concern among scientists studying infectious diseases at different spatial and temporal scales [1, 2] . Changes in biotic and abiotic conditions may alter population disease dynamics and lead to the emergence of zoonotic infections [3] [4] [5] [6] . During the last decades, several outbreaks of emerging and re-emerging viral pathogens have occurred, affecting both purely-local and worldwide/pandemic involvement of human populations. Among the conspicuous examples are influenza A, Ebola virus, hepatitis C virus, severe adult respiratory distress (SARS), coronavirus, and human immunodeficiency virus, which challenge prevention and control measures of public health systems [7] . In the Americas, the recent outbreak of pandemic influenza A subtype H1N1 became a major target for control due to its rapid spread, and uncertainties in virulence and transmissibility, yet vaccine availability was limited when significant activity occurred in advance of the traditional influenza season [8] . However, in the last century outbreaks of several viral-related diseases have emerged or re-emerged involving arenaviruses and dengue viruses, and more recently, hantaviruses, and the expansion of the geographic range of West Nile virus. Among zoonotic diseases, small mammals are hosts of several pathogenic RNA viruses, especially Arenaviridae and Bunyaviridae: Hantavirus [9] [10] [11] .
Hantavirus infections became a concern in the Americas after the description of an outbreak of acute respiratory distress occurred in the Four Corners area in 1993 [12] . The newly recognized disease, hantavirus cardiopulmonary syndrome, HCPS (or hantavirus pulmonary syndrome), was linked to infection by the newly-discovered Sin Nombre virus (SNV), and the rodent Peromyscus maniculatus (deer mouse) was identified as the reservoir [13] . However, hantavirus infections have a much longer history. A review of ancient Chinese writings, dating back to approximately 960 AD, revealed descriptions closely resembling hemorrhagic fever with renal syndrome (HFRS), the syndrome caused by Old World hantaviruses [14] . During the twentieth century, cases of acute febrile disease with renal compromise were described from several Eurasian countries and Japan, often in association with military engagements [15] . HFRS as a distinct syndrome, however, was first brought to the attention of western medicine in association with an outbreak that occurred among United Nations troops during the Korean conflict between 1951 and 1954, where more than 3,200 soldiers were afflicted [16] . It took more than two decades until the etiologic agent, Hantaan virus (HTNV), was isolated from the striped field mouse Apodemus agrarius, detected in part by the binding of antibodies from patient serum samples to the lung tissues of healthy, wild-caught field mice [17, 18] . The virus was later found to represent the type species of a new genus Hantavirus of the family Bunyaviridae, although it was later apparent that the first hantavirus to be isolated was the shrew-borne Thottapalayam virus [19] . The categorization of hantaviruses as belonging to the family Bunyaviridae is due in part to the consistent presence of three RNA genomes that are circularized in vivo as a result of the presence of terminal complementary nucleotides that help fold the genome into a -hairpin‖ morphology, first described for the Uukuniemi phlebovirus [19, 20] . Table 1 is a list of the predominant, serologically distinct pathogenic hantaviruses. Many other named genotypes are described, but such other pathogenic forms are generally closely related to Andes or, in some cases, Sin Nombre virus.
During virus maturation, the precursor form GPC is processed using a membrane -bound protease into Gn and Gc, a cleavage that occurs, and appears to be signaled, after the conserved peptide signal WAASA at the C-terminal of Gn [24] . Although the two proteins can be expressed independently through transfection, they can be retained in the wrong cellular compartment (ER or aggresome); they thus must be co-expressed to allow them stability so that the two can be assembled correctly in the Golgi [25, [27] [28] [29] .
A number of activities and properties have been identified for the hantavirus envelope glycoproteins, including some features that are suspected to be involved in the pathogenicity of the disease-causing serotypes, a possibility that has engendered experimental attention. The glycoproteins are the known or presumed ligands for at least two distinct cellular receptors, the 3 integrin chain and decay accelerating factor, or DAF [30, 31] ; with gC1qR/p32 also identified as another potential entry receptor [32] . Comparisons with the tick-borne encephalitis virus E protein, led Tischler et al. to consider the Gc glycoprotein as a potential class II fusion protein, perhaps imparting fusion activity to the virion, and this hypothesis has gained support in other studies [33, 34] .
Additional activities have been identified with, or claimed to be related to, Gn. For many of these studies, an underlying premise has held that there are differences between the glycoproteins of -pathogenic‖ hantaviruses relative to viruses in the genus that are dubbed to be -non-pathogenic‖. While it is true that it has not yet been possible to link Prospect Hill virus (PHV) to human disease, the absence of evidence for its pathogenicity should perhaps not be equated with the evidence of its absence. One might only consider that the level of disease (e.g., lethargy, fever, proteinuria, and azotemia) associated with infection of nonhuman primates by PHV is not significantly different from that recorded for nonhuman primate models using the known-pathogen Puumala virus (PUUV) [35, 36] . For the purpose of this discussion we will presume that apathogenic hantaviruses are indeed apathogenic.
While some studies have suggested that Gn glycoproteins are directed more rapidly into the ubiquitin-proteosome pathway than are apathogenic forms, others have interpreted differences in the handling of Gn glycoproteins across hantavirus species by the ubiquitin-proteosomal system as independent of pathogenicity [37] [38] [39] . Some investigators have directed their efforts toward identifying a differential capacity, either kinetic or in absolute magnitude, in the ability of pathogenic and apathogenic hantaviruses to elicit an interferon response in cells. One premise that emerges is that apathogenic forms would tend to induce an earlier innate response that would render it more likely that the virus would be quickly cleared or rendered less competent in its replication so as to blunt any pathological response in the host [40] [41] [42] . The anti-hantavirus innate response can in some cases be attributed to viral interaction as a ligand of TLR-3, but not in others, and in endothelial cells, it appears not to require more than the viral particle itself, even when introduced in replication-incompetent form [43, 44] . Proteins and mRNAs prominently induced by hantaviruses include MxA and IFIT-1 (ISG-56) and others including some with known or suspected anti-viral activity. Those hantaviruses, often highly pathogenic strains, that fail to induce a potent antiviral response, are suspected or presumed to have a (more) potent interferon-pathway antagonism mechanism relative to other viruses, a mechanism that acts positively to prevent an effective innate response from forming, at least early in infection [42, 45] . Yet some instances are reported wherein highly pathogenic hantaviruses, such as SNV, are also able to induce expression of interferon-stimulated gene mRNAs, even very early in infection, with ISG proteins, as expected, taking longer to appear in the cell [44] . Anti-interferon activities have also been attributed to the NSs protein that may be elaborated in cells infected by serotypes that encode this protein [46] . Other investigators have examined the activities of hantavirus glycoproteins and other proteins that might themselves directly affect some aspects of the pathogenic progression associated with hantavirus infection of humans, such as vascular permeability changes. While early attempts to directly cause increases in permeability of endothelial monolayers with viral particles or viral infection were largely disappointing, hantaviruses have been identified as adversely affecting endothelial migration over substrata and in potentiating VEG-F-induced endothelial permeability [47, 48] .
The shorter (50-kD) nucleocapsid or N protein is a structural component of the viral nucleocapsid, along with the genomic viral RNA segments. As an RNA-binding protein that engages the hairpin termini of the genomic segments with high affinity [49, 50] , it limits the access of the RNA to host nucleases and helps to render viral replication a closed process within the cytoplasm. It also acts as a peripheral membrane protein, as does the L protein [51] , an activity that could play a role in its presumed, but not yet demonstrated function as matrix [52] . Until recently, it had not been appreciated that N has a wide variety of other activities, some of which can be linked, not only to fundamental requirements of replication, but also to the interference with an array of the intracellular processes of the normal cell. Thus, an interaction between the amino terminus of the hantavirus N protein and the cellular protein Daxx has been proposed, with the suggestion of potential pro-apoptotic consequences [51] . N is also reported to interact with actin microfilaments, and the SUMO-1 protein [53, 54] . Using reporter-gene based assays, Connie Schmaljohn and her colleagues have reported that Hantaan virus' nucleocapsid protein has an inhibitory role in inflammatory responses mediated by NF kappa B (NF-B). The effects on NF-B expression appeared to be confined to prevention of its nuclear translocation after its attempted activation with lipopolysaccharide, LPS [55] . In the cytoplasm of infected cells, N protein can be found in cellular P bodies where it sequesters and protects 5' caps. It may locate the caps through its interaction with DCP1, a key constituent of P bodies. During hantavirus infection, the viral RNAs become concentrated in P bodies, through their interaction with N and DCP1. The N protein demonstrates preferential protection of mRNAs engineered to prematurely terminate their encoded protein in comparison to native mRNAs [56] . N protein has been increasingly linked to viral replication and translation, sometimes in previously unanticipated ways. It is among a growing family of diverse viral proteins that can serve as a nonspecific -RNA chaperone‖, an activity that should facilitate the L polymerase's access to vRNA for transcription and replication, in that it can transiently dissociate misfolded RNA structures [57] . Some of N protein's effects on translation might not immediately be recognized to be adaptive in nature. It can replace the entire EIF4F translational initiation complex, simultaneously presenting the ribosome with a replacement for the cap-binding activity of eIF 4E, binding to the 43S pre-initiation complex as does eIF 4G, while replacing the helicase activity of eIF 4A, which is presumed to be needed to dissociate higher-order RNA structure [56, 58] . These three factors normally work together to achieve translational initiation. In P bodies, N protein's ability to bind at high affinity to capped native cellular oligoribonucleotides, along with its activity in protecting capped RNAs from degradation likely facilitates the access of capped oligonucleotides for use in transcriptional initiation by L polymerase (-cap snatching‖).
Trafficking of N for viral assembly: Classically, N protein in infected cells appears to be clustered or particulate in nature, with a heavy concentration at a single perinuclear location, widely considered to be the Golgi [27] . The N proteins of hantaviruses are found in association with particulate fractions, and confocal microscopy and biochemical-inhibitor studies have shown that N tracks along microtubules but not with actin filaments [52] . The ultimate destination for N, for its assembly into viral particles is the Golgi, and it traffics there via the endoplasmic reticulum-Golgi intermediate complex (ERGIC), also known as vesicular-tubular cluster [52] . A dominant negative inhibitor, dynamitin, associated with dynein-mediated transport, reduced N's accumulation in the Golgi. Later studies suggested that the specific dependence on microtubular transport is specific to Old World hantaviruses such as HTNV, but that the New World hantavirus ANDV is instead associated with actin filaments [59] . However, recent data indicates that microtubular transport is indeed utilized for the New World hantavirus SNV [60] .
Hantavirus diseases of man have long been suspected of having an immunopathogenic basis in part because of their relatively long incubation period of 2-3 weeks and the observed temporal association between immunologic derangements and the first appearance of signs and symptoms of hantavirus illness. HFRS and HCPS share many clinical features, leading many investigators to consider them to be, in essence, different manifestations of a similar pathogenic process, differing mainly in the primary target organs of disease expression ( Table 2 ). The pathogenesis of hantavirus infections is the topic of a continuously-updated review in the series UpToDate [61] .
By the time symptoms appear in HCPS, both strong antiviral responses, and, for the more virulent viral genotypes, viral RNA can be detected in blood plasma or nucleated blood cells respectively [63, 64] . At least three studies have correlated plasma viral RNA with disease severity for HCPS and HFRS, suggesting that the replication of the virus plays an ongoing and real-time role in viral pathogenesis [65] [66] [67] . Several hallmark pathologic changes have been identified that occur in both HFRS and HCPS. A critical feature of both is a transient (~ 1-5 days) capillary leak involving the kidney and retroperitoneal space in HFRS and the lungs in HCPS. The resulting leakage is exudative in character, with chemical composition high in protein and resembling plasma.
The continued experience indicating the strong tissue tropism for endothelial cells, specifically, is among the several factors that make β3 integrin an especially attractive candidate as an important in vivo receptor for hantaviruses. It is likely that hantaviruses arrive at their target tissues through uptake by regional lymph nodes, perhaps with or within an escorting lung histiocyte. The virus seeds local endothelium, where the first few infected cells give rise, ultimately, to a primary viremia, a process that appears to take a long time for hantavirus infections [62, 63] . By the time that secondary viremia emerges, the agents of the more severe forms of HFRS and HCPS have begun to achieve sufficient mass as to induce, through PAMP-PRR interactions and other means, the expression of proinflammatory cytokines [64] . For HCPS, that expression favors the pulmonary bed and lymphoid organs, yet, for unknown reasons, spares the retroperitoneum and, in general, the kidney. In HFRS the situation is reversed, and yet it is often not appreciated that the expected preferential tissue tropism of HFRS-associated viruses and their HCPS-associated counterparts for the renal and pulmonary beds, respectively, is not as one would predict through the manifestations of the two diseases.
Local elaboration of inflammatory and chemotactic mediators is considered to be a requirement for the development of systemic disease symptoms, with those abnormalities sometimes culminating in shock and death. Yet it is not hypoxemia, due to the prominent pulmonary edema, that leads to death in most fatal cases of HCPS, but rather intoxication of the heart by as-yet-undefined mediators that leads to the low cardiac output state and the associated shock syndrome [64, 65] . It is tempting to speculate that mediators produced in the lung in connection with the inflammatory infiltrate can percolate through the coronary circulation with minimal dilution in HCPS, a disadvantageous consequence of the close anatomic juxtaposition of the two organs. Thus, at least three classes of potential mechanisms, some overlapping and all certainly nonexclusive of the others, could be presumed to underlie the pathogenesis of HCPS. These include:
(1) Innate immune mechanisms. The nature of interactions between hantavirus pathogen-associated molecular patterns (PAMP) with the pattern recognition receptors (PRR) of susceptible endothelial cells are beginning to be clarified. The prototypical HTNV appears to be recognized by TLR-3 [43] . Such an infection has consequences such as increased expression of HLA-DR in dendritic cells [66] and differentiation of monocytes toward dendritic cells [67] .
(2) Direct viral effects. The observed correlation between viral load and disease severity leaves the possibility open that hantavirus particles or RNA can themselves have toxic effects on cells or on signaling. Some investigators have favored direct viral toxicity, acting through the inhibition of endothelial cell barrier function, as an explanation for much of the capillary leak, although there is widespread agreement that multiple mechanisms that mediate pathogenesis likely operate simultaneously in the affected patient [68] . A potentially important clue toward the mechanism by which hantavirus infections deplete blood platelets and, in some cases cause hemorrhagic manifestations, was advanced by the recent discovery that pathogenic hantaviruses are able to recruit platelets to adhere to endothelial cell surfaces, with β3 integrin used as a critical binding element [69] .
(3) Pathogenic effects caused by the activities of specific viral macromolecules. We have reviewed some of the activities associated with the Gn, Gc and N, virally-encoded polypeptides in previous sections.
Testing models of pathogenesis can be done more effectively when there is an animal model that mimics key aspects of the disease. There is no such model that closely mimics HFRS, but animal models exist for both the asymptomatic carriage of PUUV and SNV by their native carrier rodents, the bank vole Myodes glareolus and the deer mouse P. maniculatus; as well as a Syrian hamster model using ANDV or the related Maporal virus from Venezuela, for which an HCPS-mimetic disease is observed [70] [71] [72] [73] .
The ANDV-Syrian hamster model has a number of features in common with the human disease, as well as some differences. Unlike the neurologic diseases that have been possible to elicit with HTNV, the hamster model for HCPS appears to be caused by capillary leak that results in pulmonary edema and the production of a pleural effusion with exudative characteristics. Typically the hamsters die between 11 and 14-d post-inoculation, reflecting a slightly accelerated incubation period in comparison to human infections. As with human HCPS, the microscopic examination of the lung reveals abundant fibrin deposition, thickened alveolar septa, and viral antigen expressed abundantly in the microvascular endothelium. ANDV-infected hamsters fitted with physiologic monitoring devices exhibited diminished pulse pressures, tachycardia, and hypotension that appear to closely mimic the shock that is believed to be the proximate cause of demise in patients who succumb to HCPS [65, 74] .
Compared to the human disease, ANDV-infected hamsters exhibit exceptionally high titers of live ANDV in their tissues, with much of the viral replication occurring in hepatocytes, which are spared in the human disease. Titers of live ANDV in some cases exceed 10 8 /g, whereas hantavirus isolates from human tissues have been notoriously difficult to obtain. Despite the universal occurrence of mildly-elevated hepatic enzymes in patients with HCPS, hepatic enzymes do not appear to be present at elevated levels in the blood of diseased hamsters even immediately before death [75] .
The protracted incubation period associated with hantavirus disease gives the host considerable time to mount a mature immune response against the virus. Thus, in contradistinction to infections of comparable severity and related symptomatology associated with arenaviruses and filoviruses, hantavirus infections of humans are associated with antibody responses of significant titer by the time symptoms commence. Despite this observation, it appears to be possible that natural variation in individual neutralizing antibody responses among patients with SNV infections can be linked to disease severity, suggesting that administration of antiviral antibodies could prove effective therapeutically [76] . In the case of ANDV infection, new evidence has emerged indicating that the apparent clearance of the virus from the blood does not result in the complete removal of antigenic stimulus by the virus, suggesting that the virus may persist, perhaps in some as-yet undetermined immunologically privileged site [77] .
A role for T cell-mediated pathological responses in HFRS and HCPS has been the source of speculation for a variety of reasons. The severity of SNV-associated HCPS may have made it more apparent that the onset of pulmonary edema, tachycardia and hypertension seemed to be all but universally temporally associated with the appearance of a spectrum of highly-activated cells of the lymphoid lineage in the peripheral blood. Cells with a close morphologic similarity to these -immunoblasts‖ were detected in the congested, heavy lungs of patients who came to autopsy, as well as in lymphoid organs and in the portal triads [63, [78] [79] [80] . These observations led to speculation that some component of hantavirus pathogenesis could be linked to the appearance of antiviral T cells that could stimulate or contribute to the appearance of a -storm‖ of mediators and the associated capillary leak phenotype. Subsequent studies have borne out the expectation that a significant fraction of the immunoblast population in patients with HCPS are T cells with specificity for specific class I HLA-presented epitopes of viral antigens, including Gn, Gc and N [77, [81] [82] [83] . Presumably, the antiviral activities of such cells, manifested in part through their elaboration of mediators in the affected interstitium, can contribute to the endothelial/capillary leak that lies at the heart of hantavirus pathogenesis.
Because early cases of HCPS often came to autopsy, it became possible to examine necropsied tissues for expression of cytokines. The study by Mori et al. (1999) revealed high relative expression of proinflammatory cytokines including TNF, IL-1, IL-6, providing evidence in favor of a -cytokine storm‖ model for pathogenesis [64] . The authors believed, based on the morphology of cytokine-secreting cells, that both monocytes and lymphocytes were contributing to the production of cytokines. That proinflammatory mediators are found in elevated levels in the plasma as well as the renal interstitium of patients with acute hantaviral illness has been recognized for some time as well [84, 85] .
While diagnosis of HCPS as well as HFRS is best accomplished with IgM serology, in the acute stage of SNV infection, RT-PCR can also be used if blood cells or blood clot are used instead of plasma or serum, where sensitivity even using nested PCR primers drops to about 70% [86] [87] [88] . In a facility at which many cases of HCPS are treated, the University of New Mexico medical center in Albuquerque, a diagnostic service has long been offered in which the patient's hematologic findings are analyzed to establish the probability that a patient has HCPS. The combination of thrombocytopenia, elevated abundance of -immunoblast‖ lymphocytes, left-shifted polymorphonuclear cell population without strong morphologic evidence for their activation, and elevated hemoglobin or hematocrit values is highly specific for HCPS and allows clinicians the ability to put presumptive-HCPS patients on extracorporeal membrane oxygenation (ECMO), which is believed to have saved many patients from a lethal outcome [89] .
Human infection by hantaviruses is thought to follow contact with secretions or excretions produced by infected rodents. In the United States, 538 human infections by hantavirus were reported through late December 2009 [90] , with New Mexico, Arizona and Colorado exhibiting the highest case-loads. While the prototypical central American hantavirus in central America was Rio Segundo virus of Reithrodontomys mexicanus from Costa Rica, the first human disease appeared some years later in Panama, where Choclo virus (CHOV) arose as the etiologic agent and is believed to be responsible for all known cases of HCPS. The fulvous pygmy rice rat Oligoryzomys fulvescens has been identified as the rodent reservoir [91] . In Panama, the first cases of HCPS, albeit with little or no evident cardiac involvement, were reported in 1999, and since then, 106 human infections have occurred with a 26% mortality rate [92] . Serosurveys of mammals in Mexico and Costa Rica have found anti-hantavirus antibodies [93] [94] [95] [96] , and seroprevalences ranging between 0.6 to 1.6% in human populations were reported despite the absence of known HCPS cases [97] . In South America, HCPS cases have been indentified in Argentina, Bolivia, Brazil, Chile, Paraguay and Uruguay, and evidence for human exposure to hantaviruses have also been reported in Venezuela [98] and Perú [99] . In southern South America, ANDV is the main etiologic agent with cases in Chile and Argentina reported since 1995. In Chile, 671 cases of HCPS due to ANDV have occurred during the period 2001-2009 [100] . Since 1995, more than 1,000 HCPS cases have been reported in Argentina [101] ; in Brazil, approximately 1,100 HCPS cases have been identified between 1993 and 2008 [102] . Case-fatality ratios in those three countries have been similar, ranging from 30% (Argentina), 36% (Chile) and 39% (Brazil).
Hantavirus infections occur more frequently in men than women, although the male/female ratio is highly variable. For example, Panamanian communities showed a ratio of 55 men to 45 women [103] , while in Chile the ratio is more biased to males (71%) [104] . In the Paraguayan Chaco the male-female ratio approaches 50% [105] . In North America, by December 2009 63% of case-patients were males [90] . All ethnic and racial groups seem to be susceptible to hantavirus infections, and the differences between certain groups (as indigenous and non-indigenous) are more likely correlated with the type habitat where the population resides (e.g., rural versus urban areas). In fact, rural communities account for the highest hantavirus incidences overall and are therefore at higher risk [92, [105] [106] [107] [108] [109] [110] [111] , although the importance of peridomestic settings as a major area of exposure has also been emphasized [112, 113] .
The main mechanism by which humans acquire hantavirus infection is by exposure to aerosols of contaminated rodent feces, urine, and saliva [114, 115] . This can occur when humans reside in areas in close proximity to those that rodents inhabit, live in areas infested with rodents, or when rodents invade human settings, which are more frequent in rural habitats. There is a long history of human co-existence with rodents, raising questions about the apparent recent increases in hantavirus-related illnesses, especially HCPS. Other than an apparent association with El Niño southern oscillation (ENSO) events in some regions [116, 117] , the recent increases in incidence of HCPS do not seem to follow a readily-defined temporal or spatial pattern. However, some landscape features such as habitat fragmentation or human-disturbed areas may influence rodent population dynamics and impact viral incidence [118] [119] [120] [121] . Despite the stochasticity associated with contraction of hantavirus infection, certain scenarios have been recognized as posing higher risk. Human activities in poorly ventilated buildings that aerosolize particulates that are then inhaled (i.e., cleaning, shaking rugs, dusting) are frequently identified among patients admitted for HCPS [11, 122] . Outdoor activities are thought to convey lower risk due to lability of hantaviruses to UV radiation and the presumed tendency to be dispersed in wind, although certain environmental conditions seem to maintain the virus for longer periods outside its natural host allowing for indirect transmission [123] . An alternative but uncommon route of virus transmission is by rodent bites [124] [125] [126] . Field workers handling mammals are potentially at higher risk of exposure with hantavirus infections, although when quantified through serosurveys the absolute risk appears rather slight [127] . A new study in Colorado suggests the possibility that a rodent bite may have been the proximate vehicle for outdoor transmission of SNV [128] , which re-emphasizes the use of personal protective equipment during field work activities [129] . As a particular case within hantaviruses, person-to-person transmission has exclusively been documented for the South American Andes virus [130] [131] [132] [133] [134] [135] . The identification of this transmission route has been made using both molecular tools and epidemiological surveys, but the mechanism of interpersonal transmission is not well established. Recent findings show that family clusters and specifically sexual partners share the greater risk of interpersonal transmission, although sexual transmission per se can be neither inferred nor refuted presently [130, 135] . Interestingly, ANDV may also be shed by humans through other biological fluids such as urine [136] , illustrating the particular properties that differentiate this virus from other hantaviruses. Although interpersonal transmission seems to be unique for ANDV, viral RNA of PUUV has been detected in saliva of patients with HFRS, and some patients with SNV-HCPS have viral RNA in tracheal secretions [88, 137] .
Hantaviruses in the Americas are naturally hosted by rodents (Muridae and Cricetidae) as well as shrews (Soricidae) and moles (Talpidae) (Figure 1) . Three shrew and one mole species have been reported to host hantaviruses and their pathogenicity for humans remains unknown [22, 138, 139] . At least 15 rodent species have been identified as carriers of different pathogenic hantaviruses, with some South American genotypes such as Castelo do Sonhos (CDSV) or Hu39694 only identified after human infections (Figure 1 ). Hantaviruses typically show high species-specificity and no intermediate host [140] . However, some hantavirus genotypes have been described in the same rodent species. Such is the case of Playa de Oro (OROV) and Catacamas (CATV) identified in Oryzomys couesi [141, 142] , or Maporal (MAPV) and Choclo (CHOV) hosted by O. fulvescens [91, 143] . In North America both Muleshoe and Black Creek Canal hantaviruses have been detected in geographically-distant Sigmodon hispidus [144, 145] . Also, one hantavirus genotype (e.g., Juquitiba-like virus) may be carried by more than one rodent species (O. nigripes, Oxymycterus judex, Akodon montesis). Another example is Laguna Negra virus (LANV) which after being identified in Calomys laucha [146] has also been reported in C. callosus [147] . The rapid increase in the discovery of new hantaviruses and the identification of their hosts does not seem likely to end soon as new small mammal species are screened [95] . This subject is complicated by continued controversy in the criteria for the classification of distinct hantaviruses [148, 149] , which is also tied to host taxonomic classification and taxonomic rearrangements.
Cross-species transmission is a major process during spread, emergence, and evolution of RNA viruses [6, 150] . Particularly within hantaviruses, spillover to secondary hosts are increasingly identified as more extensive studies are performed [151] [152] [153] [154] [155] [156] . For example, ANDV is the predominant etiologic agent of HCPS in South America, and O. longicaudatus the main rodent reservoir. Spillover in at least four other rodent species that co-occur with the reservoir have been identified, with Abrothrix longipilis showing the second higher prevalence to ANDV-antibodies, and there is presently no question that the virus is extremely similar genetically between the two host rodents [157, 158] . In North America, spillover of Bayou virus (BAYV) may have occurred from the main reservoir O. palustris to S. hispidus, R. fulvescens, P. leucopus, and B. taylori [159] [160] [161] . Hantavirus spillover is more likely to occur with host populations inhabiting sympatric or syntopic regions [151, 162] , and cross-species transmission would presumably have greater chances of success if the host species are closely related [163] . An interesting exception is found between Oxbow virus (OXBV) and Asama virus (ASAV) in which a host-switch process seemed to have occurred between mammals belonging to two families (Talpidae and Soricidae), likely as a result of alternating and recurrent co-divergence of certain taxa through evolutionary time [138] .
Hantaviruses are horizontally transmitted between rodents and are not transmitted by arthropods (unlike other viruses of the family Bunyaviridae). Spillover infection to nonhuman mammals usually results in no onward (or -dead-end‖) transmission, but if humans are infected may result in high morbidity and mortality [122, 164] . During the spring of 1993, an outbreak of patients with HCPS due to SNV occurred in the Four Corners states resulting in more than 60% case-fatality among the initial cases, many involving members of the Navajo tribe [12, 121] . In Panama, an outbreak was reported during 1999-2000 in Los Santos, and 12 cases where identified with three fatalities [165, 166] . This represented the first report of human hantavirus infections in Central America. In South America, the first largest identified outbreak occurred in the Chaco region in northwestern Paraguay during 1995-1996. Seventeen individuals were identified with SNV antibody (ELISA) or were antigen (IHC) positive out of 52 suspected cases [167] . Major outbreaks due to ANDV occurred in 1996 in southern Argentina [131, 134] ; in southern Chile clusters of patients presented with hantavirus illness in 1997 [158] . In Brazil, the first outbreak was identified in the Brazilian Amazon (Maranhão State) in 2000, and involved small villages that resulted in a 13.3% prevalence of those tested (398 total residents) [168] .
The factors that trigger hantavirus outbreaks are still poorly understood, probably because they result from several interacting biotic and abiotic features whose key parameters are difficult to model. However, the use of new modeling approaches that involve geographical and environmental features seem to be promising in predicting potential hantavirus outbreaks and/or areas of higher risk [169] [170] [171] [172] . Because hantaviruses are known to be directly transmitted from infected to susceptible hosts, the first natural approach is to relate outbreaks to the ecology of the viral hosts. Hantavirus transmission and persistence in rodent populations depends on several factors that interact to affect ecological dynamics of the host, which in turn is strongly influenced by the behavioral characteristics of individual rodent species, to landscape structure, and environmental features [173, 174] . Viral transmission depends on contact rates among susceptible hosts, and despite the prevailing notion that a higher density increases encounters and hence secondary infected hosts, contrasting patterns relating rodent population size and virus prevalence can be found [175] . In addition, it has been shown that SNV transmission follows a contact heterogeneity pattern, where individuals in the population have different probability of transmitting the infection [176] . The understanding of viral transmission proves to be far more complex when species other than the main reservoir host are incorporated in the model. In fact, recent studies have shown that higher hosts species diversity is correlated with lower infection prevalence in North America for P. maniculatus [177] , in Central America for O. fulvescens (reservoir of Choclo virus) and Zygodontomys brevicauda (reservoir of Calabazo virus) [178] , and in South America for Akodon montensis (reservoir of Jabora virus) [162] . Contact rates vary according to the spatial distribution of populations and seem to be strongly influenced by landscape structure. For example, SNV prevalence in P. maniculatus was higher in landscapes with a higher level of fragmentation of the preferred habitat [179] . In addition, certain properties of the landscape such as elevation, slope, and land cover seem to be useful in detecting areas with persistent SNV infections, and therefore thought to be refugial areas where the virus can be maintained for years [169] . Changes in the natural environment of reservoir species, such as forest fragmentation and habitat loss, may alter population abundance and distribution and lead to hantavirus outbreaks, as observed in the Azurero Peninsula of Panama [118, 119] . Also, differences in the microhabitat, including overstory cover, may lead to differences in the ecological dynamics within populations and affect the rate of exposure to the virus [180] . Differences in hantavirus infections through contrasting landscapes in the latitudinal span have been found in rodent populations of O. longicaudatus in Chile, suggesting that humans are differentially exposed to the virus [107, 181] .
Rodent population dynamics are affected by seasonal changes of weather and climate [182, 183] . In the case of the ENSO-associated outbreaks, a complex cascade of events triggered by highly unusual rains in the precedent year have been postulated to result in an increase of primary production and rodent densities, also increasing the likelihood of transmission of the virus to humans, but it has proved difficult to precisely demonstrate the suggested intermediate events such as increased rodent densities in the increased caseload [116, 121, 184] . In South America, effects of climate change and hantavirus outbreaks have not been well studied, despite the knowledge that several rodents species that are reservoirs of emerging diseases have dramatically been affected by events like El Niño [185] . Changes in host population dynamics are also affected by seasonality, which may lead to disease outbreaks when processes that equilibrate rodent populations from season to season are interrupted [186] .
Viral emergence may continue to be promoted as human-introduced changes continue to increase in the environment at different geographical scales. Human incursions into previously uncultivated environments may lead to new contacts between rodent reservoirs and humans, increasing the likelihood of contracting infections [187] . These changes may also alter rodent's population structure and dynamics and interspecies interactions creating conditions that may lead to viral outbreaks, viral establishment in new hosts, and emergence of HCPS [102, 162] , even with seemingly slight ecological disturbance to the virus-host system [188] .
Certain pathophysiologic characteristics, including thrombocytopenia and shock, of hantavirus diseases of humans, bear substantial similarity to the hemorrhagic fevers induced by other viruses such arenaviruses, filoviruses and flaviviruses, despite sharing essentially no sequence similarities therewith. Such observations raise questions about whether such commonalities in pathogenesis are chance similarities of phenotype, or instead report the presence of common molecular mechanisms among the viruses.
In this review we discuss the general properties, discoveries and epidemiology/ecology of the New World forms of pathogenic hantaviruses, and also seek to identify some of the characteristics of the viral macromolecules and immunologic mechanisms that have been proposed as potential direct mediators of the pathogenic events that characterize the human disease HCPS. While it is unlikely that expression of any particular viral protein or RNAs in isolation can be relied upon to replicate key phenotypes of infection by the complete virus, some of the findings have been sufficiently consistent with what is known of the pathogenesis in vivo that they offer plausible first-pass leads in the search for therapeutic targets. We look forward to the mechanistic revelations that will follow the inevitably expanded usage of powerful methods such as deep sequencing, ever-more advanced imaging, and microscopic methods, and animal models that can at last be said to be close mimics of human hantavirus disease. | Which pathogenic RNA viruses are hosted by small mammals? | false | 4,458 | {
"text": [
"Arenaviridae and Bunyaviridae: Hantavirus"
],
"answer_start": [
2977
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1,741 | MERS coronavirus: diagnostics, epidemiology and transmission
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4687373/
SHA: f6fcf1a99cbd073c5821d1c4ffa3f2c6daf8ae29
Authors: Mackay, Ian M.; Arden, Katherine E.
Date: 2015-12-22
DOI: 10.1186/s12985-015-0439-5
License: cc-by
Abstract: The first known cases of Middle East respiratory syndrome (MERS), associated with infection by a novel coronavirus (CoV), occurred in 2012 in Jordan but were reported retrospectively. The case first to be publicly reported was from Jeddah, in the Kingdom of Saudi Arabia (KSA). Since then, MERS-CoV sequences have been found in a bat and in many dromedary camels (DC). MERS-CoV is enzootic in DC across the Arabian Peninsula and in parts of Africa, causing mild upper respiratory tract illness in its camel reservoir and sporadic, but relatively rare human infections. Precisely how virus transmits to humans remains unknown but close and lengthy exposure appears to be a requirement. The KSA is the focal point of MERS, with the majority of human cases. In humans, MERS is mostly known as a lower respiratory tract (LRT) disease involving fever, cough, breathing difficulties and pneumonia that may progress to acute respiratory distress syndrome, multiorgan failure and death in 20 % to 40 % of those infected. However, MERS-CoV has also been detected in mild and influenza-like illnesses and in those with no signs or symptoms. Older males most obviously suffer severe disease and MERS patients often have comorbidities. Compared to severe acute respiratory syndrome (SARS), another sometimes- fatal zoonotic coronavirus disease that has since disappeared, MERS progresses more rapidly to respiratory failure and acute kidney injury (it also has an affinity for growth in kidney cells under laboratory conditions), is more frequently reported in patients with underlying disease and is more often fatal. Most human cases of MERS have been linked to lapses in infection prevention and control (IPC) in healthcare settings, with approximately 20 % of all virus detections reported among healthcare workers (HCWs) and higher exposures in those with occupations that bring them into close contact with camels. Sero-surveys have found widespread evidence of past infection in adult camels and limited past exposure among humans. Sensitive, validated reverse transcriptase real-time polymerase chain reaction (RT-rtPCR)-based diagnostics have been available almost from the start of the emergence of MERS. While the basic virology of MERS-CoV has advanced over the past three years, understanding of the interplay between camel, environment, and human remains limited. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12985-015-0439-5) contains supplementary material, which is available to authorized users.
Text: An email from Dr Ali Mohamed Zaki, an Egyptian virologist working at the Dr Soliman Fakeeh Hospital in Jeddah in the Kingdom of Saudi Arabia (KSA) announced the first culture of a new coronavirus to the world. The email was published on the website of the professional emerging diseases (ProMED) network on 20 th September 2012 [1] (Fig. 1) and described the first reported case, a 60 year old man from Bisha in the KSA. This information led to the rapid discovery of a second case of the virus, this time in an ill patient in the United Kingdom, who had been transferred from Qatar for care [2] . The new virus was initially called novel coronavirus (nCoV) and subsequentlty entitled the Middle East respiratoy syndrome coronavirus (MERS-CoV). As of 2 nd of September 2015, there have been 1,493 detections of viral RNA or virus-specific antibodies across 26 countries (Additional file 1: Figure S1 ) confirmed by the World Health Organization (WHO), with over a third of the positive people dying (at least 527, 35 %) [3] .
Since that first report, a slow discovery process over the following two to three years revealed a virus that had infected over 90 % of adult dromedary camels (DC; Camelus dromedarius) in the KSA [4] , also DCs across the Arabian Peninsula and parts of Africa that are a source of DC imports for the KSA [5] . To date, MERS-CoV has not been detected in DCs tested in zoos or herds from other parts of the world [6] [7] [8] [9] . Occasionally, virus is transmitted from infected DCs to exposed humans. Subsequent transmission to other humans requires relatively close and prolonged exposure [10] .
The first viral isolate was patented and concerns were raised that this would restrict access to both the virus and to viral diagnostics [11, 12] . However, sensitive, validated reverse transcriptase real-time polymerase chain reaction (RT-rtPCR)-based diagnostics were quickly described and virus was made freely available subject to routine biosafety considerations [13] . Subsequent epidemiology and research has identified the cell receptor as exopeptidase dipeptidyl peptidase 4 (DPP4; also called CD26); that MERS-CoV has a broad tropism, replicating better in some cells lines and eliciting a more proinflammatory response than SARS-CoV; is widespread in DCs; has the potential to infect other animals and that MERS kills its human host more often than SARS did (20-40 % versus 9 % for SARS [14] ) [15] [16] [17] [18] [19] .
In humans, overt disease was given the name Middle East respiratory syndrome, with the acronym MERS. From intermittent animal-to-human spill-over events, the MERS-CoV spreads sporadically among people, causing more severe disease among older adults, especially males, with pre-existing diseases. The spread of MERS-CoV among humans has often been associated with outbreaks in hospitals, with around 20 % of all cases to date involving healthcare workers (HCWs).
Although DCs appear to suffer the equivalent of a 'common cold' from MERS-CoV infection, in humans, the virus can be a more serious and opportunistic pathogen associated with the death of up to 40 % of reported cases. It has yet to be established whether infections thought to have been acquired from an animal source produce a more severe outcome than those spread between humans [20] . Studies have established that the mean incubation period for MERS is five to six days, ranging from two to 16 days, with 13 to 14 days between when illness begins in one person and subsequently spreads to another [21] [22] [23] [24] . Among those with progressive illness, the median time to death is 11 to 13 days, ranging from five to 27 days [23, 24] . Fever and gastrointestinal symptoms may form a prodrome, after which symptoms decline, only to be followed by a more severe systemic and respiratory syndrome [25, 26] .
The first WHO case definition [27] defined probable cases of MERS based on the presence of febrile illness, cough and requirement for hospitalization with suspicion of lower respiratory tract (LRT) involvement. It also included roles for contact with a probable or confirmed case or for travel or residence within the Arabian Peninsula. If strictly adhered to, only the severe syndrome would be subject to laboratory testing, which was the paradigm early on [21] . From July 2013, the revised WHO case definition included the importance of seeking out and understanding the role of asymptomatic cases and from June 2014, the WHO definition more clearly stated that a confirmed case included any person whose sample was RT-PCR positive for MERS-CoV, or who produced a seroconversion, irrespective of clinical signs and symptoms. [28] [29] [30] Apart from the WHO and the KSA Ministry of Health reports, asymptomatic or subclinical cases of MERS-CoV infection were documented in the scientific literature although not always as often as occurred early on [31, 32] . The KSA definition of a case became more strict on 13 th May 2014, relying on the presence of both clinical features and laboratory confirmation [33] . Testing of asymptomatic people was recommended against from December 2014 [34] , reinforced by a case definition released by the KSA Ministry of Health in June 2015 [35] . The KSA has been the source of 79 % of human cases. Severe MERS is notable for its impact among older men with comorbid diseases including diabetes mellitus, cirrhosis and various lung, renal and cardiac conditions [36] [37] [38] . Interestingly in June 2015, an outbreak in South Korea followed a similar distribution [39, 40] . Among laboratory confirmed cases, fever, cough and upper respiratory tract (URT) signs and symptoms usually occur first, followed within a week by progressive LRT distress and lymphopaenia [37] . Patients often present to a hospital with pneumonia, or worse, and secondary bacterial infections have been reported [37, 41] . Disease can progress to acute respiratory distress syndrome and multiorgan system failure [37] . MERS has reportedly killed approximately 35 % of all reported cases, 42 % of cases in the KSA, yet only 19 % of cases in South Korea, where mortality ranged from 7 % among younger age groups to 40 % among those aged 60 years and above [42] ; all may be inflated values with asymptomatic or mild infections sometimes not sought or not reported [34] . General supportive care is key to managing severe cases [43] . Children under the age of 14 years are rarely reported to be positive for MERS-CoV, comprising only 1.1 % (n = 16) of total reported cases. Between 1 st September 2012 and 2 nd December 2013, a study described the then tally of paediatric cases in the KSA, which stood at 11 (two to 16 years of age; median 13 years); nine were asymptomatic (72 %) and one infant died [44] . In Amman, Jordan, 1,005 samples from hospitalized children under the age of two years with fever and/or respiratory signs and symptoms were tested but none were positive for MERS-CoV RNA, despite being collected at a similar time to the first known outbreak of MERS-CoV in the neighbouring town of Al-Zarqa [45] . A second trimester stillbirth occurred in a pregnant woman during an acute respiratory illness and while not RT-rtPCR positive, the mother did subsequently develop antibodies to MERS-CoV, suggestive of recent infection [46] . Her exposure history to a MERS-CoV RT-rtPCR positive relative and an antibody-reactive husband, her incubation period and her symptom history met the WHO criteria for being a probable MERS-CoV case [46] .
Diagnostic methods were published within days of the ProMED email announcing the first MERS case [47] , including several now gold standard in-house RT-rtPCR assays (Fig. 2 ) as well as virus culture in Vero and LLC-MK2 cells [18, 47, 48] . A colorectal adenocarcinoma (Caco-2) epithelial cell line has since been recommended for isolation of infections MERS-CoV [49] . We previously [18] .). Open reading frames are indicated as yellow rectangles bracketed by terminal untranslated regions (UTR; grey rectangles). FS-frame-shift. Predicted regions encompassing recombination break-points are indicated by orange pills. Created using Geneious v8.1 [211] and annotated using Adobe Illustrator. Beneath this is a schematic depicting the location of RT-PCR primers (blue arrows indicate direction) and oligoprobes (green rectangles) used in the earliest RT-rtPCR screening assays and conventional, semi-nested (three primers) RT-PCR confirmatory sequencing assays [47, 48] . Publication order is noted by first [27 th September 2012; red] and second [6 th December 2012; orange] coloured rectangles; both from Corman et al. [47, 48] Those assays recommended by the WHO are highlighted underneath by yellow dots [53] . The NSeq reverse primer has consistently contained one sequence mismatch with some MERS-CoV variants. An altered version of that from Mackay IM, Arden KE. Middle East respiratory syndrome: An emerging coronavirus infection tracked by the crowd. Virus Res 2015 Vol 202:60-88 with permission from Elsevier [5] reviewed the broad tropism of MERS-CoV [5] . However, as is well described, cell culture is a slow, specialised and insensitive method [50] while PCR-based techniques are the preferred method for MERS-CoV detection.
The first open reading frames (ORF 1a and 1b; Fig. 2 ) have become a key diagnostic and taxonomic target for CoV species identification. With less than 80 % identity between the amino acid sequence of MERS ORF 1ab and betacoronavirus relatives, Tylonycteris bat HKU4 and Pipistrellus bat HKU5, it can be concluded that it is a novel and distinct virus. MERS-CoV is predicted to encode ten open reading frames with 5' and 3' untranslated regions [51] . The structural proteins include the spike (S), envelope (E), membrane (M) and nucleocapsid (N) [52] . The products of ORF1a and ORF1b are predicted to encode nonstructural proteins.
The majority of specimen testing to date has employed validated RT-rtPCR assays shown to be sensitive and specific [47, 48, 53] . The RealStar® kit uses these WHOrecommended assays [54] . The target sequences of these screening assays have not changed among genomes examined until at least mid-2015 (IMM observation). Other RT-rtPCR assays have been developed and validated for use as laboratory-based diagnostic tools [55] [56] [57] . Additionally, loop-mediated [58, 59] or recombinase polymerase [60] isothermal assays have been designed for field deployment.
The detection of MERS-CoV antigen has not been common to date but the combination of short turnaround time from test to result, high throughput and identification of viral proteins makes this an attractive option. Detection of viral proteins rather than viral RNA indicates the likely presence of infectious virus. The first rapid immunochromatographic tool described could detect recombinant MERS-CoV nucleocapsid protein from DC nasal swabs with 94 % sensitivity and 100 % specificity compared to RT-rtPCR [61] . A different approach used a monoclonal antibody-based capture ELISA targeting the MERS-CoV nucleocapsid protein with a sensitivity of 10 3 TCID 50 and 100 % specificity [62] .
Demonstration of a seroconversion to a MERS-CoV infection meets the current WHO definition of a case so optimized and thoroughly validated sero-assays employed alongside good clinical histories are useful to both identify prior MERS-CoV infection and help support transmission studies. Because serology testing is, by its nature, retrospective, it is usual to detect a viral footprint, in the form of antibodies, in the absence of any signs or symptoms of disease and often in the absence of any viral RNA [63] .
Strategic, widespread sero-surveys of humans using samples collected after 2012 are infrequent. Much of the Arabian Peninsula and all of the Horn of Africa lack baseline data describing the proportion of the community who may have been infected by a MERS-CoV. However, sero-surveys have had widespread use in elucidating the role of DCs as a transmission source for MERS-CoV. Because of the identity shared between DC and human MERS-CoV (see Molecular epidemiology: using genomes to understand outbreaks), serological assays for DC sero-surveys should be transferrable to human screening with minimal re-configuration. Also, no diagnostically relevant variation in neutralization activity have been found from among a range of circulating tested MERS-CoV isolates and sera, so whole virus or specific protein-based sero-assays should perform equivalently in detecting serological responses to the single MERS-CoV serotype [49] . The development of robust serological assays requires reliable panels of wellcharacterized animal or human sera, including those positive for antibodies specific to MERS-CoV, as well as to likely sources of cross-reaction [64] . Obtaining these materials was problematic and slowed the development and commercialization of antibody detection assays for human testing [64] . A number of commercial ELISA kits, immunofluorescent assays (IFA) kits, recombinant proteins and monoclonal antibodies have been released [31, [65] [66] [67] [68] . Initially, conventional IFAs were used for human sero-surveys. These relied on MERS-CoV-infected cell culture as an antigen source, detecting the presence of human anti-MERS-CoV IgG, IgM or neutralizing antibodies in human samples [18, 48, 69] . No sign of MERS-CoV antibodies was found among 2,400 sera from patients visiting Hospital in Jeddah, from 2010 through 2012, prior to the description of MERS-CoV [18] . Nor did IFA methods detect any sign of prior MERS-CoV infection among a small sample of 130 healthy blood donors from another Hospital in Jeddah (collected between Jan and Dec 2012) [70] . Of 226 slaughterhouse workers, only eight (3.5 %) were positive by IFA, and those sera could not be confirmed by virus neutralization (NT) test. The study indicated that HCoV-HKU1 was a likely source of crossreactive antigen in the whole virus IFA [70] . Whole virus MERS-CoV IFA also suffered from some cross-reactivity with convalescent SARS patient sera and this could not be resolved by an NT test which was also cross-reactive [71] . IFA using recombinant proteins instead of whole-virus IFA, has been shown to be a more specific tool [31] . Since asymptomatic zoonoses have been posited [72] , an absence of antibodies to MERS-CoV among some humans who have regular and close contact with camels may reflect the rarity of actively infected animals at butcheries, a limited transmission risk associated with slaughtering DCs [70] , a pre-existing cross-protective immune status or some other factor(s) resulting in a low risk of disease and concurrent seroconversion developing after exposure in this group. IFA using recombinant proteins instead.
Some sero-assays have bypassed the risks of working with infectious virus by creating transfected cells expressing recombinant portions of the MERS-CoV nucleocapsid and spike proteins [48, 73] , or using a recombinant lentivirus expressing MERS-CoV spike protein and luciferase [74, 75] . A pseudo particle neutralization (ppNT) assay has seen widespread used in animal studies and was at least as sensitive as the traditional microneutralization (MNT) test. [10, 74, [76] [77] [78] ] Studies using small sample numbers and ppNT found no evidence of MERS-CoV neutralizing antibody in sera from 158 children with LRT infections between May 2010 and May 2011, 110 sera from 19 to 52 year old male blood donors and 300 selfidentified animal workers from the Jazan Region of the KSA during 2012 [79, 80] . Similarly, a study of four herdsmen in contact with an infected DC herd in Al-Ahsa, eight people who had intermittent contact with the herd, 30 veterinary surgeons and support staff who were not exposed to the herd, three unprotected abattoir workers in Al-Ahsa and 146 controls who were not exposed to DCs in any professional role, found none with serological evidence of past MERS-CoV infection using the ppNT assay [10] . A delay in the neutralizing antibody response to MERS-CoV infection was associated with increased disease severity in South Korea cases with most responses detectable by week three of illness while others, even though disease was severe, did not respond for four or more weeks [81] . The implications for our ability to detect any response in mild or asymptomatic cases was not explored but may be a signifcant factor in understanding exposure in the wider community.
A Jordanian outbreak of acute LRT disease in a hospital in 2012 was retrospectively found to be associated with MERS-CoV infection, initially using RT-rtPCR, but subsequently, and on a larger scale, through positivity by ELISA and IFA or MNT test. [46, 82, 83] This outbreak predated the first case of MERS in the KSA. The ELISA used a recombinant nucleocapsid protein from the group 2 betacoronavirus bat-CoV HKU5 to identify antibodies against the equivalent crossreactive MERS-CoV protein [71] . It was validated using 545 sera collected from people with prior HCoV-OC43, HCoV-229E, SARS-CoV, HCoV-NL63, HRV, HMPV or influenza A(H1N1) infections but was reportedly less specific than the recombinant IFA discussed above. It was still considered an applicable tool for screening large sample numbers [82] . A protein microarray expressing the S1 protein subunit has also been validated and widely used for DC testing [5, 84] . Detection of MERS-CoV infection using ELISA or S1 subunit protein microarray [84] is usually followed by confirmatory IFA and/ or a plaque-reduction neutralization (PRNT) [69, 70, 85] or MNT test. [74, 85, 86] This confirmatory process aims toensure the antibodies detected are able to specifically neutralize the intended virus and are not more broadly reactive to other coronaviruses found in DCs (bovine CoV, BCoV) or humans (HCoV-OC43, HCoV-229E, HCoV-NL63, HCoV-HKU1, SARS-CoV). In the largest study of human sera, a tiered diagnostic process assigned both recombinant IFA and recombinant ELISA positive sera to 'stage 1' seropositivity. A stage 2 seropositive result additionally required a suitably titred PRNT result [87] . The study found 15 sera collected in 2012 to 2013 from 10,009 (0.2 %) people in 13 KSA provinces contained MERS-CoV antibodies, but significantly higher proportions in occurred in camel shepherds (two of 87; 2.3 %) and slaughterhouse workers (five of 140; 3.6 %) [87] . Contemporary surveys are needed.
MERS-CoV does not appear to be easily transmitted from DCs to humans, or perhaps it is [72] , but generally does not trigger a detectable immune response if only mild disease or asymptomatic infection results. Serology assays are in need of further validation in this area so care is required when moving newly developed diagnostic serology algorithms from a research setting to one that informs public health decisions. This was reinforced when a false positive US case, purported to have been infected after a handshake and two face-to-face meetings, did not withstand further confirmatory analysis using a more specific, NT assay and was subsequently retracted [88, 89] .
The WHO recommends sampling from the LRT for MERS-CoV RT-rtPCR testing, especially when sample collection is delayed by a week or more after onset of symptoms. [53] LRT samples are also best for attempting isolation of infectious virus, although the success of culture is reduced when disease persists [49] . Recommended sample types include bronchoalveolar lavage (BAL), tracheal/tracheobronchial aspirate, pleural fluid and sputum [53, 90] . Fresh samples yield better diagnostic results than refrigerated material [69] and if delays in testing of ≥72 h are likely, samples (except for blood) should be frozen at −70°C [90] . If available, lung biopsy or autopsy tissues can also be tested [53] . The URT is a less invasive and more convenient sampling site however, and an oropharyngeal and throat swab or a nasopharyngeal aspirate/wash are recommended when URT sampling is to be conducted [90] . Paired sera, collected two to three weeks apart are preferable for serological testing while a single sample is suggested to be sufficient if collected two weeks after onset of disease or a single serum collected during the first 10-12 days if conducting RT-rtPCR [53, 90] . Human urine and stool have been found to contain MERS-CoV RNA 12 to 26 days after symptom onset [25, 69, 91] and are listed as samples that should be considered [53, 90] . In two cases that arrived in the Netherlands, urine was RT-rtPCR negative but faeces was weakly positive and sera were RT-rtPCR positive for five days or more [25] . The finding of MERS-CoV viral RNA in serum provides an avenue for retrospective PCR-based studies if respiratory samples are unavailable [83] . RNAaemia may also correlate with disease severity; signs of virus were cleared from the serum of a recovered patient, yet lingered until the death of another [92] .
Clinically suspected MERS cases may return negative results by RT-rtPCR. Data have shown one or more negative URT samples may be contradicted by further URT sampling or the use of LRT samples, which is preferred [2, 43, 93] . Higher viral loads occur in the LRT compared to the URT. [22, 69, 88, 94] This fits with the observation that the majority of disease symptoms are reported to manifest as systemic and LRT disease [21] . However, on occasion, even LRT specimens from MERS cases may initially be negative, only to later become positive by RT-PCR [95] . This may be due to poor sampling when a cough is absent or non-productive or because the viral load is low [95] . Despite this both the largest human MERS-CoV studies [32, [96] [97] [98] and smaller ones [22, 25, 99] , use samples from the URT. It is then noteworthy that one study reported an association between higher loads in the URT and worse clinical outcome including intensive care and death [94] . At writing, no human data exist to define whether the virus replicates solely or preferentially in the LRT or URT, or replicates in other human tissues in vivo although MERS-CoV RNA has been detected from both the URT and LRT in a macaque monkey model [100] .The distribution of DPP4 in the human upper airways is also not well described.
Individual human case studies report long periods of viral shedding, sometimes intermittently and not necessarily linked to the presence of disease symptoms. [25, 69, 99, 101] In one instance, a HCW shed viral RNA for 42 days in the absence of disease [99] . It is an area of high priority to better understand whether such cases are able to infect others. Over three quarters of MERS cases shed viral RNA in their LRT specimens (tracheal aspirates and sputum) for at least 30 days, while only 30 % of contacts were still shedding RNA in their URT specimens [91, 102] .
In the only study to examine the effect of sample type on molecular analysis, 64 nasopharyngeal aspirates (NPA; an URT sample), 30 tracheal aspirates, 13 sputa and three BAL were examined. The tracheal aspirates and BAL returned the highest viral load values followed by NPA and sputum. Unsurprisingly, higher viral loads generally paralleled whole genome sequencing and culture success and, in NPA testing, were significantly correlated with severe disease and death [49, 94, 103] . This study demonstrated the importance of LRT sampling for whole genome sequencing.
When tested, samples positive for MERS-CoV are often negative for other pathogens [2, 25, 93, 104] . However, many studies make no mention of additional testing for endemic human respiratory viruses [21, 23, 73, 105] . When viruses are sought, they have included human herpesvirus (HHV), rhinoviruses (HRV), enteroviruses (EV), respiratory syncytial virus (RSV), parainfluenzavirus types 1, 2 and 3 (PIVs),influenzaviruses (IFVs), endemic HCoVs, adenoviruses (AdVs) metapneumovirus (MPV) and influenza A\H1N1 virus; co-detections with MERS-CoV have been found on occasion [2, 22, 37, 69, 97] . Bacterial testing is sometimes included (for example, for Legionella and Pneumococcus) but the impact of bacterial co-presence is also unclear [22, [104] [105] [106] . Further testing of the LRT sample from the first MERS case used IFA to screen for some viruses (negative for IFV, PIVs, RSV and AdVs) and RT-PCR for others (negative for AdV, EVs, MPV and HHVs) [18] . RT-PCR also detected MERS-CoV. The WHO strongly recommends testing for other respiratory pathogens [53] but with this recommendation often discounted, there are limited data to address the occurrence and impact of co-infections or alternative viral diagnoses among both MERS cases and their contacts. Little is known of other causes of MERS-like pneumonia in the KSA or of the general burden of disease due to the known classical respiratory viruses.
Testing of adult pilgrims performing the Hajj in 2012 to 2014 has not detected any MERS-CoV. In 2012, nasal swabs from 154 pilgrims collected prior to leaving for or departing from the KSA were tested [47] . In 2013, testing was significantly scaled up with 5,235 nasopharyngeal swabs from 3,210 incoming pilgrims and 2,025 swabs from outgoing pilgrims tested [98] . It should be noted that most pilgrims arrived from MERS-free countries. A further 114 swabs were taken from pilgrims with influenza-like illness [96, 107] . In earlier Hajj gatherings, it was found that influenza viruses circulated widely, whilst other viruses, often rhinoviruses, circulated more selectively, interpreted as indicating their importation along with foreign pilgrims. [107] [108] [109] Over time, increased influenza vaccination has been credited for a fall in the prevalence of influenza like illnesses among Hajj pilgrims. [110] A LRT sample is often not collected for these studies [98, 107, 109] , so false negative findings are a possibility although little is known about the initial site of MERS-CoV infection and replication; it may have been assumed it was the LRT because disease was first noticed there but the URT may be the site of the earliest replication.
In Jeddah between March and July 2014 (hereafter called the Jeddah-2014 outbreak; Fig. 3 ), there was a rapid increase in MERS cases, accompanied by intense screening; approximately 5,000 samples from in and around the region were tested in a month yielding around 140 MERS-CoV detections (~3 % prevalence) [111] . Among 5,065 individuals sampled and tested across the KSA between October 2012 and September 2013,108 (2.1 %) detections were made in a hospital-centric population which included hospitalized cases (n = 2,908; 57.4 %), their families (n = 462; 9.1 %) and associated HCWs (n = 1,695; 33.5 %) [32] . Among the detections, 19 (17.8 %) were HCWs and 10 (9.3 %) were family contacts [32] .
The 2-3 % prevalence of active MERS-CoV infections is not dissimilar to the hospital-based prevalence of other human CoVs. [112] However, the proportion of deaths among those infected with MERS-CoV is much higher than that known for the HCoVs NL63, HKU1, 229E or OC43 in other countries, and even above that for SARS-CoV; it is not a virus that could reasonably be described as a "storm in a teacup". It is the low transmission rate that has prevented worldwide spread, despite many "opportunities".
Very early in the MERS outbreak, some animals were highly regarded as either the reservoir or intermediate host(s) of MERS-CoV with three of the first five cases having contact with DCs [73, 113, 114] . Today, animal MERS-CoV infections must be reported to the world organization for animal health as an emerging disease [115] . A summary of the first MERS cases reported by the WHO defined animal contact with humans as being direct and within 10 days prior to symptom onset [20] . This definition made no specific allowance for acquisition from DCs through a droplet-based route, which is very likely route for acquisition of a virus that initially and predominantly causes respiratory disease [23] . Camels are known to produce high levels of MERS-CoV RNA in their URT and lungs [116] . Providing support for a droplet transmission route and perhaps indicating the presence of RNA in smaller, drier droplet nuclei, MERS-CoV RNA was identified in a high volume air sample collected from a barn housing an infected DC [117] . The precise source from which humans acquire MERS-CoV remains poorly studied but it seems likely that animal and human behavioural factors may play roles (Fig. 3) [118] . These factors may prove important for human cases who do not describe any DC contact [119] nor any contact with a confirmed case. Whether the WHO definition of animal contact is sufficient to identify exposure to this respiratory virus remains unclear. Wording focuses on consumption of DC products but does not specifically ascribe risk to a droplet route for acquisition of MERS-CoV from DC [120] . Some MERS patients are listed in WHO disease notices as being in proximity to DCs or farms, but the individuals have not described coming into contact with the animals. No alternative path for acquiring infection is reported in many of these instances. What constitutes a definition of "contact" during these interviews has been defined for one study [72] . Despite this lack of clarity, the WHO consider that evidence linking MERS-CoV transmission between DCs to humans is irrefutable (Fig. 4) [120] .
The possibility that bats were an animal host of MERS-CoV was initially widely discussed because of the existing diversity of coronaviruses known to reside among them [121] [122] [123] [124] . Conclusive evidence supporting bats as a source for human infections by MERS-CoV has yet to be found, but bats do appear to host ancestral representatives [53, 125] . However, these are not variants of the same virus nor always within the same phylogenetic lineage as MERS-CoV; they are each a genetically distinct virus. Bat-to-human infection by MERS-CoV is a purely speculative event. The only piece of MERS-CoV-specific evidence pointing to bats originates from amplification of a 190 nt fragment of the RNAdependent RNA polymerase gene of the MERS-CoV genome, identified in a faecal pellet from an insectivorous Emballonuridae bat, Taphozous perforatus found in Bisha, the KSA [121] . While very short, the sequence of the fragment defined it as a diagnostic discovery. Subsequently a link to DCs was reported [85] and that link has matured into a verified association [38, 126] (Fig. 4) .
(See figure on previous page.) Fig. 3 Monthly detections of MERS-CoV (blue bars) and of cases who died (red bars) with some dates of interest marked for 2012 to 4 th September 2015. An approximation of when DC calving season [128] and when recently born DCs are weaned is indicated. Spring (green) and summer (orange) in the Arabian Peninsula are also shaded. Note the left-hand y-axis scale for 2014 and 2015 which is greater than for 2012/13. Sources of these public data include the WHO, Ministries of Health and FluTrackers [207] [208] [209] . Earlier and subsequent versions of this chart are maintained on a personal blog [210] . Modified and reprinted from Mackay IM, Arden KE. Middle East respiratory syndrome: An emerging coronavirus infection tracked by the crowd. Virus Res 2015 Vol 202:60-88 with permission from Elsevier [5] DCs, which make up 95 % of all camels, have a central presence in the Arabian Peninsula where human-DC contact ranges from little to close [119] . Contact may be commonplace and could occur in variety of ways (Fig. 4a) . There are several large well-attended festivals, races, sales and parades which feature DCs and DCs are also kept and bred close to populated areas in the KSA [127, 128] . DC milk and meat are widely consumed and the older DC is an animal of ritual significance after the Hajj pilgrimage [129] . However, MERS-CoV infection frequency is reportedly much lower than is the widespread and frequent habit of eating, drinking and preparing DC products. Daily ingestion of fresh unpasteurized DC milk is common among the desert Bedouin and many others in the KSA. DC urine is also consumed or used for supposed health benefits. Despite camel butchery being a local occupation, neither butchers nor other at-risk groups are identifiable among MERS cases; this may simply be a reporting issue rather than an unexplainable absence of MERS. A small case-control study published in 2015 identified direct DC contact, and not ingestion of products, to be associated with onset of MERS [38] .
The first sero-survey of livestock living in the Middle East region was conducted during 2012-2013 [85] . DCs were sampled from a mostly Canary Island-born herd and from Omani DCs (originally imported from the Horn of Africa) [85] . A neutralising antibody assay found only 10 % of strongly seropositive Canary Island [5] . b Camel-to-human infections appear to be infrequent, while human-to-human spread of infection is regularly facilitated by poor IPC in healthcare settings where transmission is amplified, accounting for the bulk of cases. There are human MERS cases that do not fall into either category of source and it is unclear if these acquired infection through some entirely separate route, or from cases that escaped diagnosis. c Hypothetical ways in which subclinical (when infection may not meet a previously defined clinical threshold of signs and/or symptoms) or asymptomatic (no obvious signs or measured, noticed or recalled symptoms of illness) MERS-CoV infection may be implicated in transmission DC sera could neutralise MERS-CoV while all Omani DC sera had high levels of specific MERS-CoV neutralizing antibody [85] . This indicated that DCs had in the past been infected by MERS-CoV, or a very similar virus.
Since this study, a host of peer-reviewed reports have looked at both DCs and other animals, and the possibility that they may host MERS-CoV infection. Seropositive DCs have been found throughout the Arabian Peninsula including Oman, the KSA, Qatar, Jordan, the United Arab Emirates (UAE), Kuwait as well as Sudan, Somalia, Egypt, Tunisia, Nigeria, Kenya and Ethiopia in Africa and the Canary Islands [85, [130] [131] [132] [133] [134] . Other animals tested include sheep, cows, pigs, horses, donkeys, mules, birds, water buffalo, goats, Bactrian camels, llamas and guanaco (south American camelids) but none had detectable neutralising antibody against MERS-CoV [4, 74, 78, 85, 86, 135, 136] . No virology or serology studies of human samples from areas in Africa where there are camels with a history of MERS-CoV have been reported to date. However,an absence of unexplained pneumonia that may be attributable to MERS-CoV infection may not signal the absence of virus among humans in each country but simply reflect a lack of expensive epidemiology studies conducted by resource-poor countries. It is thus unclear whether MERS-CoV, or an antigenically related CoV, is an unrecognized pathogen in these regions, perhaps circulating for even longer than it has been known in the Arabian Peninsula [133] .
MERS-CoV RNA has also been detected in DC samples, and recovery of infectious virus has also been achieved from DC samples [4, 77, 117, 132, [137] [138] [139] [140] [141] . From some of these, full or majority length genomes of MERS-CoV have been sequenced [77, 137, 138] . DC versions of MERS-CoV were found to be as similar to each other, as were variants detected from different humans over time and across distance.
Antibody screening assays have also detected crossreactive antibodies in sera. These were identified as such by screening sera against similar viruses, for example BCoV or HCoV-OC43 (as an antigenic facsimile for BCoV). It is possible that other MERS-CoV-like viruses also reside within DCs, but this does not detract from the definitive finding of MERS-CoV genetic sequences in both DCs and humans [117, 142, 143] .
Screening studies have shown that juvenile DCs are more often positive for virus or viral RNA while older DCs are more likely to be seropositive and RNA or virus negative [76, 77, 144] . In adult DCs, MERS-CoV RNA has been detected among animals with pre-existing antibody, suggesting re-infection is possible [77, 144] . Viral loads among positive DCs can be very high [4, 76, 77, 139, 144] and DCs have been found positive both when ill with URT respiratory signs [77, 117, 142, 145] or when apparently healthy [137] . These findings indicate DCs host natural MERS-CoV infections. Furthermore, stored DC sera have revealed signs of MERS-CoV in DCs which date back over three decades (the earliest collected in 1983) [4, 133, 135] . Older sera have not been tested and so precisely how long DCs have been afflicted by MERS-CoV, whether the virus is enzootic among them, introduced to them decades or centuries ago from bats in Africa or the Arabian Peninsula, or they are the subject of regular but short-lived viral incursions from an as yet unknown host, cannot be answered.
Researchers sought to determine a direction for infection; were DCs transmitting virus to humans or were humans infecting DCs? At a Qatari site, a farm owner and his employee became ill in mid-October 2013 and tested positive for MERS-CoV RNA in a sputum and throat swab sample, respectively. RT-rtPCRs found MERS-CoV RNA in 11 of 14 positive DC nasal swabs at the farm; six (43 %) positive by two or more assays [138] . The results indicated a recent outbreak had occurred in this herd; the first indication of MERS-CoV RNA found within DCs with a temporal association to human infections. Three positive DC samples were confirmed by sequencing a 358 nt portion of the spike gene; these sequences were identical to each other, again with close homology to other human and DC MERS-CoV sequences [138] . The DCs and human contacts yielded ORF1a and ORF4b sequences differing by only a single nucleotide each, clustering closely with the Hafr-Al-Batin_1_2013 variant [138] . Subsequent case studies found evidence of a concurrent human and DC infection and the direction of that infection was inferred to be from the ill DCs and to their human owners [117, 142, 146] . Partial genome sequences indicated that a human and a MERS-CoV RT-rtPCR positive DC had been infected by a variant of the same virus, harbouring the same distinct pattern of nucleotide polymorphisms. [142] All nine DC in the owner's herd, serially sampled, reacted in a recombinant S1 antigen ELISA, with the two animals that had been RT-rtPCR positive showing a small, verifiable rise in antibody titre [142] . A rise in titre theoretically begins 10 to 21 days after DC infection [142] . The authors suggested that the rise in titre in DC sera which occurred alongside a declining RNA load, while the patient was actively ill and hospitalized, indicated that the DCs were infected first followed by the owner [117, 142] . BCoV antibodies were also present, and rising in one of the two RT-rtPCR positive animals but no animal's antibodies could neutralise BCoV infection [142] .
Camel calving season occurs in the winter months (between late October and late February; Fig. 3 ) and this may be a time when there is increased risk to humans of spill-over due to new infections among naïve DC populations [128] . What role maternal camel antibody might play in delaying infection of calves remains unknown [128, 142] . Juvenile DCs appear to host active infection more often than adult DCs and thus the sacrificial slaughter of DCs, which must be five years of age or older (termed a thane), may not be accompanied by significant risk of exposure to infection. In contrast to earlier results, slaughterhouse workers who kill both younger and older DCs, may be an occupational group with significantly higher incidence of seropositivity to MERS-CoV when animals have active MERS-CoV infections [129, 139, [147] [148] [149] . Expanded virological investigations of African DCs may lead to more seropositive animals and geographic areas in which humans may be at risk. It is possible that there are areas where humans already harbour MERS-CoV infections that have not been identified because of an absence of laboratory surveillance. Virological investigations of bats may lead to findings of ancestral viruses and viral 'missing links' and identifying any other animal sources of zoonotic spread is important to inform options for reducing human exposures [56, 76] .
Infectious MERS-CoV added to DC, goat or cow milk and stored at 4°C could be recovered at least 72 h later and, if stored at 22°C, recovery was possible for up to 48 h [150] . MERS-CoV titre decreased somewhat when recovered from milk at 22°C but pasteurization completely ablated MERS-CoV infectivity [150] . In a subsequent study, MERS-CoV RNA was identified in the milk, nasal secretion and faeces of DCs from Qatar [151] .
A single study has examined the ability of MERS-CoV to survive in the environment [150] . Plastic or steel surfaces were inoculated with 10 6 TCID 50 of MERS-CoV at different temperature and relative humidity (RH) and virus recovery was attempted in cell culture. At high ambient temperature (30°C) and low RH (30 %) MERS-CoV remained viable for 24 h [150] . By comparison, a well known and efficently transmitted respiratory virus, influenza A virus, could not be recovered in culture beyond four hours under any conditions [150] . Aerosol experiments found MERS-CoV viability only decreased 7 % at low RH at 20°C. In comparison, influenza A virus decreased by 95 % [150] . MERS-CoV survival is inferior to that previously demonstrated for SARS-CoV [152] . For context, pathogenic bacteria can remain viable and airborne for 45 min in a coughed aerosol and can spread 4 m. MERS-CoV's ability to remain viable over long time periods gives it the capacity to thoroughly contaminate a room's surfaces when occupied by an infected and symptomatic patient [153] . Whether MERS-CoV can remain adrift and infectious for extended periods (truly airborne) remains unknown. Such findings expand our understanding of the possibilities for droplets to transmit respiratory viruses in many settings, including hospital waiting rooms, emergency departments, treatment rooms, open intensive care facilities and private patient rooms. The nature and quality of air exchange, circulation and filtration are important variables in risk measurement and reduction as is the use of negative pressure rooms to contain known cases. Droplet spread between humans is considered the mechanism of human-to-human transmission and the need for droplet precautions was emphasized after the Al-Ahsa hospital, the KSA and the South Korean outbreaks [21, 23, 154, 155] . By extrapolation, aerosol-generating events involving DCs (urination, defecation, and preparation and consumption of DC products) should be factored into risk measurement and reduction efforts and messaged using appropriate context. The provision of evidence supporting the best formulation of personal protective equipment to be worn by HCWs who receive, manage or conduct procedures on infectious cases remains a priority.
MERS-CoV was found and characterized because of its apparent association with severe, and therefore more obvious, illness in humans; we were the canaries in the coal mine. Sero-assays and prospective cohort studies have yet to determine the extent to which milder or asymptomatic cases contribute to MERS-CoV transmission chains. However, transmission of MERS-CoV is defined as sporadic (not sustained), intra-familial, often healthcare associated, inefficient and requiring close and prolonged contact [22, 31, 63, 93, 97, 102, 156] In a household study, 14 of 280 (5 %) contacts of 26 MERS-CoV positive index patients were RNA or antibody positive; the rate of general transmission, even in outbreaks is around 3 % [31] . It seems that the majority of human cases of MERS-CoV, even when numbers appear to increase suddenly, do not readily transmit to more than one other human so to date, the localized epidemic of MERS-CoV has not been self-sustaining [157] [158] [159] [160] [161] . That is to say, the basic reproduction number (R 0 ) -the average number of infections caused by one infected individual in a fully susceptible populationhas been close to one throughout various clusters and outbreaks. If R 0 was greater than 1, a sustained increase in case numbers would be expected. Some R o calculations may be affected by incomplete case contact tracing, limited community testing and how a case is defined. That MERS has had a constant presence in the Arabian Peninsula since 2012 is due to ongoing, sporadic spill-over events from DCs amplified by poorly controlled hospital outbreaks.
The first known MERS human-to-human transmission event was one characterized by acute LRT disease in a healthcare setting in Jordan. In stark contrast, a sero-survey of HCW who were sometimes in close and prolonged contact with the first, fatal MERS-CoV case in 2012 [162] , found none of the HCW had seroconverted four months later, despite an absence of eye protection and variable compliance with required PPE standards [162] .
Early on in the MERS story, samples for testing were mostly collected from patients with severe illness and not those with milder acute respiratory tract infections. Contacts of confirmed MERS cases were often observed for clinical illness, but not tested. These omissions may have confounded our understanding of MERS-CoV transmission and biased early data towards higher numbers of seriously ill and hospitalized patients, inflating the apparent proportion of fatal cases. Case-control studies were not a focus. As testing paradigms changed and contacts were increasingly tested, more asymptomatic and mild infections were recognized [163] .
A rise in the cases termed asymptomatic (which enlarge the denominator for calculations of the proportion of fatal cases, defined in [164] ) resulted in a drop in the proportion of fatal cases during the Jeddah-2014 outbreak. Historically, such rises are consistent with changing definitions and laboratory responses and clinical management of a newly discovered virus infection that was first noted only among the severely ill. Upon follow-up, over three-quarters of such MERS-CoV RNA positive people did recall having one or more symptoms at the time, despite being reported as asymptomatic [165] raising some question over the reliability of other reported data.
The proportion of fatal MERS cases within the KSA compared to outside the KSA, as well as the age, and sex distribution change in different ways when comparing MERS outbreaks. Approximately 43 % of MERS cases (549 of 1277) in the KSA were fatal betwen 2012 and December 2015 while 21 % (72 of 330) died among those occurring outside of the KSA. The total number of male cases always outnumber females and the proportion of male deaths is always greater than the proportion of females who die. However the proportion of male deaths from total males with MERS is a similar figure to that for females. In the KSA, there is a greater proportion of younger males among cases and deaths than were observed from the 2015 South Korean or the Jeddah-2014 outbreaks (Additional file 2: Figure S2 ). Why these aspects have differed may be due to differences in the time to presentation and diagnosis, the nature and quality of supportive care, the way a person became infected (habits, exposure to a human or zoonotic source, viral load, route of infection) or the extent to which different populations are burdened by underlying diseases [40] .
As a group, HCWs comprised 16 % of MERS cases in the KSA and South Korea. It is apparent that the weekly proportion of infected HCWs increases alongside each steep rise in overall detections (Fig. 5) . In May 2013, the WHO published guidelines for IPC during care of probable or confirmed cases of MERS-CoV infection in a healthcare setting [166] . This is explainable because to date, each case rise has been intimately associated with healthcare-facility related outbreaks [118] . These rises in MERS-CoV detections can decrease the average age during each event because HCWs are usually younger than inpatients with MERS. Healthcare facilities have been a regular target for suggested improvements aimed at improving infection prevention and control (IPC) procedures [115, 118] .
Most of the analysis of MERS-CoV genetics has been performed using high throughput or "deep" sequencing methods for complete genome deduction [167] [168] [169] . MERS-CoV was the first subject of such widespread use of deep sequencing to study an emerging viral outbreak with global reach. The technique can produce genomic [207] [208] [209] . Earlier and subsequent versions of this chart are maintained on a personal blog [210] length coverage in a single experiment with highly repetitious measurement of each nucleotide position [52, 140] . Despite assays having been published early on, subgenomic sequencing, once the mainstay of viral outbreak studies, has less often been published during MERS-CoV characterization [48] . As more genomes from both humans and DCs have been characterized, two clades have become apparent; A and B (Fig. 6) . Clade A contains only human-derived MERS-CoV genomes from Jordan, while Clade B comprises the majority of human and camel genomes deduced thus far [168] .
Two studies during 2015, one looking at Jeddah-2014 MERS-CoV variants and another looking at a variant exported from South Korea to China, have now identified signs of genetic recombination among MERS-CoV variants. While human and camel whole genome sequences have retained >99 % identity with each other, members of genetically distinct lineages can and do swap genetic material when suitable conditions and coinfections co-occur [170] [171] [172] . Shared identity implies that the major source for human acquisition is the DC, rather than another animal, although more testing of other animal species is needed to confirm that conclusion. Over a month, a DC virus sequenced on different occasions did not change at all indicating a degree of genomic stability in its host, supporting that DCs are the natural, rather than intermediate, host for the MERS-CoV we know today [77] . To date, recombination has been localised to breakpoints near the boundary between ORF1a and ORF1b regions, within the spike gene [170] and in the ORF1b region (Fig. 2) [172] . It is not unexpected that recombination should occur since it is well known among other CoVs [124] and because the majority of MERS-CoV whole genomes collected from samples spanning three years (2012-2015) and from humans, camels and different countries have shown close genetic identity to each other, with just enough subtle variation to support outbreak investigations so long as whole genome sequencing is applied [52, 77, 135, 138, 168, [173] [174] [175] .
Changes in genome sequence may herald alterations to virus transmissibility, replication, persistence, lethality or response to future drugs. If we have prior knowledge of the impact of genetic changes because of thorough characterization studies, we can closely Fig. 6 The genetic relationship between MERS-CoV nucleotide sequences (downloaded from GenBank using the listed accession numbers and from virological.org [212] ). This neighbour joining tree was created in MEGA v6 using an alignment of human and DCderived MERS-CoV sequences (Geneious v8.1 [211] ). Clades are indicated next to dark (Clade A) or pale (Clade B) blue vertical bars. Camel icons denote genomes from DCs. Healthcare or community outbreaks are boxed and labelled using previously described schemes [212, 213] monitor the genomic regions and better understand any changes in transmission or disease patterns as they occur. Genetic mutations noted during the largest of human outbreaks, Jeddah-2014, did not impart any major replicative or immunomodulatory changes when compared to earlier viral variants in vitro [156, 176] . However, we understand very little of the phenotypic outcomes that result from subtle genetic change in MERS-CoV genomes. To date no clinical relevance or obvious in vivo changes to viral replication, shedding or transmission has been reported or attributed to mutations or to new recombinant viruses [156] . But vigilance and larger, more contemporary and in vivo studies are needed.
Genome sequence located to a distinct clade were identified from an Egyptian DC that was probably imported from Sudan. This does not fit into either of the current clades [125, 168, 177] . A virus sequenced from a Neoromicia capensis bat was more closely related to MERS-CoV than other large bat-derived sequences had been to that point, but the genome of a variant of a MERS-CoV has yet to be discovered and deduced from any bat [125] .
Analyses of MERS-CoV genomes have shown that most single nucleotide differences among variants were located in the last third of the genome (Fig. 2) , which encodes the spike protein and accessory proteins [168] . At least nine MERS-CoV genomes contained amino acid substitutions in the receptor binding domain (RBD) of the spike protein and codons 158 (N-terminal region), 460 (RBD), 1020 (in heptad repeat 1), 1202 and 1208 bear investigation as markers of adaptive change [140, 169] . The spike protein had not changed in the recombinant MERS-CoV genome identified in China in 2015 but was reported to have varied at a higher rate than that for complete MERS-CoV genomes, among South Korean variants [172, 178] . This highlights that subgenomic regions may not always contain enough genetic diversity to prove useful for differentiating viral variants. Despite this, one assay amplifying a 615 nucleotide fragment of the spike S2 domain gene for Sanger sequencing agreed with the results generated by the sequencing of a some full genomes and was useful to define additional sequence groupings [177] .
Genomic sequence can also be used to define the geographic boundaries of a cluster or outbreak and monitor its progress, based on the similarity of the variants found among infected humans and animals when occurring together, or between different sites and times (Fig. 6 ) [169] . This approach was employed when defining the geographically constrained MERS hospital outbreak in Al-Ahsa, which occurred between 1 st April and 23 rd May 2013, as well as clusters in Buraidah and a community outbreak in Hafr Al-Batin, the KSA. Genomic sequencing identified that approximately 12 MERS-CoV detections from a community outbreak in Hafr Al-Batin between June and August 2013 may have been triggered by an index case becoming infected through DC contact [175] . Sequencing MERS-CoV genomes from the 2013 Al-Ahsa hospital outbreak indicated that multiple viral variants contributed to the cases but that most were similar enough to each other to be consistent with human-tohuman transmission. Molecular epidemiology has revealed otherwise hidden links in transmission chains encompassing a period of up to five months [179] . However, most outbreaks have not continued for longer than two to three months and so opportunities for the virus to adapt further to humans through co-infection and sustained serial passage have been rare [169] . In Riyadh-2014, genetic evidence supported the likelihood of multiple external introductions of virus, implicating a range of healthcare facilities in an event that otherwise looked contiguous [23, 168, 179] . Riyadh is a nexus for camel and human travel and has had more MERS cases than any other region of the KSA to date but also harbours a wide range of MERS-CoV variants [128, 167, 179] . However the South Korean outbreak originated from a single infected person, resulting in three to four generations of cases [180, 181] . Studies of this apparently recombinant viral variant did not find an increased evolutionary rate and no sign of virus adaptation thus the outbreak seems to have been driven by circumstance rather than circumstance together with mutation [181] .
For many MERS cases detected outside the Arabian Peninsula, extensive contact tracing has been performed and the results described in detail. Contact tracing is essential to contain the emergence and transmission of a new virus and today it is supported by molecular epidemiology. Although it is an expensive and time consuming process, contact tracing can identify potential new infections and through active or passive monitoring, react more rapidly if disease does develop. Results of contact tracing to date have found that onward transmission among humans is an infrequent event. For example, there were 83 contacts, both symptomatic and asymptomatic, of a case treated in Germany who travelled from the UAE but no sign of virus or antibody were found in any of them [73] . The very first MERS case had made contact with 56 HCWs and 48 others, but none developed any indication of infection [162] . In a study of 123 contacts of a case treated in France, only seven matched the definition for a possible case and were tested; one who had shared a 20 m 2 hospital room while in a bed 1.5 m away from the index case for a prolonged period was positive [26] . None of the contacts of the first two MERS cases imported into the USA in 2014 contained any MERS-CoV footprint [182] and none of the 131 contacts of two travellers returning to the Netherlands developed MERS-CoV antibodies or tested RNA positive [25, 183] . Analyses of public data reveal many likely instances of nosocomial acquisition of infection in the Arabian Peninsula and these data may be accompanied by some details noting contact with a known case or facility. One example identified the likely role of a patient with a subclinical infection, present in a hospital during their admission for other reasons, as the likeliest index case triggering a family cluster [93] . Contact tracing was a significant factor in the termination of a 2015 outbreak involving multiple South Korean hospitals [184] . Such studies demonstrate the necessity of finding and understanding a role for mild and asymptomatic cases, together with restricting close contact or prolonged exposure of infected people to others, especially older family members and friends with underlying disease (Fig. 4c) .
The hospital-associated outbreak in Jeddah in 2014 was the largest and most rapid accumulation of MERS-CoV detections to date. The greatest number of MERS-CoV detections of any month on record occurred in Jeddah in April. The outbreak was mostly (>60 % of cases) associated with human-to-human spread within hospital environments and resulted from a lack of, or breakdown in, infection prevention and control [37, 185, 186] . A rise in fatalities followed the rapid increase in case numbers.
In 2015 two large outbreaks occurred. South Korea was the site of the first large scale outbreak outside the Arabian Peninsula and produced the first cases in both South Korea and China, occurring between May and July 2015. This was closely followed by a distinct outbreak in Ar Riyad province in the KSA which appeared to come under control in early November.
After staying in Bahrain for two weeks, a 68 year old male (68 M) travelled home to South Korea via Qatar, arriving free of symptoms on the 4 th May 2015 [187] . He developed fever, myalgia and a cough nearly a week later (11 th ). He visited a clinic as an outpatient between the 12 th and 15 th of May and was admitted to Hospital A on the 15 th [188] . He was discharged from Hospital A on the 17 th then visited and was admitted to the emergency department of Hospital B on the 18 th . During this second stay, a sputum sample was taken and tested positive for MERS-CoV on the 20 th [187, 188] , triggering transfer to the designated isolation treatment facility. Over a period of 10 days, the index case was seen at three different hospitals, demonstrating a key feature of "hospital shopping" that shaped the South Korean outbreak. Approximately 34 people were infected during this time [187] . In total 186 cases were generated in this outbreak, all linked through a single transmission chain to 68 M; 37 cases died [189] . In South Korea, the national health insurance system provides for relatively low cost medical care, defraying some costs by making family members responsible for a portion of the ministration of the sick, resulting in them sometimes staying for long periods in the rooms that often have more than four beds in them [24] . Other factors thought to have enabled this outbreak included unfamiliarity of local clinicians with MERS, ease with which the public can visit and be treated by tertiary hospitals, the custom of visiting sick friends and relatives in hospitals, the hierarchical nature of Korean society, crowded emergency rooms, poor IPC measures, a lack of negative pressure isolation rooms and poor inter-hospital communication of patient disease histories [24, [190] [191] [192] . All of the reported transmission occurred across three or four generations and apart from one unknown source, were all hospital-acquired [24, 120, 181, [193] [194] [195] . Few clinical details about these cases have been reported to date and detail on transmission and contact tracing is minimal. The hospitals involved were initially not identified, governmental guidance and actions produced confusing messages and there was very limited communication at all early on which resulted in unnecessary concern, distrust and a distinct economic impact [191, [196] [197] [198] . Early in the outbreak, a infected traveller, the son of an identified case in South Korea, passed through Hong Kong on his way to China where he was located, isolated and cared for in China [91, 199, 200] . No contacts became ill. The outbreak was brought under control in late July/ early August [201] after improved IPC measures were employed, strong contact tracing monitoring and quarantine, expanded laboratory testing, hospitals were better secured, specialized personnel were dispatched to manage cases and international cooperation increased [202, 203] . A review of public data showed that, as for MERS in the KSA, older age and the presence of underlying disease were significantly associated with a fatal outcome in South Korea. [40] Even though R 0 is <1, super-spreading events facilitated by circumstances created in healthcare settings and characterized by cluster sizes over 150, such as this one, are not unexpected from MERS-CoV infection [204] . The dynamic of an outbreak depends on the R 0 and an individual's viral shedding patterns, contact type and frequency, hospital procedures and population structure and density [204] .
In the region of Ar Riyad, including the capital city of Riyadh, a hospital based cluster began, within a single hospital, from late June 2015 [205] . By mid-September there had been approximately170 cases reported but the outbreak appeared to been brought under control in November.
It became apparent early on that MERS-CoV spread relatively ineffectively from human-to-human. Despite ongoing and possibly seasonal introduction of virus to the human population via infected DCs and perhaps other animals yet to be identified, the vast majority of MERS-CoV transmission has occurred from infected to uninfected humans in close and prolonged contact through circumstances created by poor infection control in health care settings. This opportunistic virus has had its greatest impact on those with underlying diseases and such vulnerable people, sometimes suffering multiple comorbidities, have been most often associated with hospitals, creating a perfect storm of exposure, transmission and mortality. It remains unclear if this group are uniquely affected by MERS-CoV or if other respiratory virus infections, including those from HCoVs, produce a similarly serious impact. In South Korea, a single imported case created an outbreak of 185 cases and 36 deaths that had a disproportionate impact on economic performance, community behaviour and trust in government and the health care system. Household human-to human transmission occurs but is also limited. Educational programs will be essential tools for combatting the spread of MERS-CoV both within urban and regional communities and for the health care setting.
Vigilance remains important for containment since MERS-CoV is a virus with a genetic makeup that has been observed for only three years and is not stable. Among all humans reported to be infected, nearly 40 % have died. Continued laboratory testing, sequencing, analysis, timely data sharing and clear communication are essential for such vigilance to be effective. Global alignment of case definitions would further aid accurate calculation of a case fatality ratio by including subclinical case numbers. Whole genome sequencing has been used extensively to study MERS-CoV travel and variation and although it remains a tool for experts, it appears to be the best tool for the job.
MERS and SARS have some clinical similarities but they also diverge significantly [206] . Defining characteristics include the higher PFC among MERS cases (above 50 % in 2013 and currently at 30-40 %; well above the 9 % of SARS) and the higher association between fatal MERS and older males with underlying comorbidities. For the viruses, MERS-CoV has a broader tropism, grows more rapidly in vitro, more rapidly induces cytopathogenic change, triggers distinct transcriptional responses, makes use of a different receptor, induces a more proinflammatory state and has a delayed innate antiviral response compared to SARS-CoV.
There appears to be a 2-3 % prevalence of MERS-CoV in the KSA with a 5 % chance of secondary transmission within the household. There is an increased risk of infection through certain occupations at certain times and a much greater chance for spread to other humans during circumstances created by humans, which drives more effective transmission than any R 0 would predict on face value. Nonetheless, despite multiple mass gatherings that have afforded the virus many millions of opportunities to spread, there have remarkably been no reported outbreaks of MERS or MERS-CoV during or immediately after these events. There is no evidence that MERS-CoV is a virus of pandemic concern. Nonetheless, hospital settings continue to describe MERS cases and outbreaks in the Arabian Peninsula. As long as we facilitate the spread of MERS-CoV among our most vulnerable populations, the world must remain on alert for cases which may be exported more frequently when a host country with infected camel reservoirs is experiencing human clusters or outbreaks.
The MERS-CoV appears to be an enzootic virus infecting the DC URT with evidence of recent genetic recombination. It may once have had its origins among bats, but evidence is lacking and the relevance of that to today's ongoing epidemic is academic. Thanks to quick action, the sensitive and rapid molecular diagnostic tools required to achieve rapid and sensitive detection goal have been in place and made widely available since the virus was reported in 2012. RT-PCR testing of LRT samples remains the gold standard for MERS-CoV confirmation. Serological tools continue to emerge but they are in need of further validation using samples from mild and asymptomatic infections and a densely sampled cohort study to follow contacts of new cases may address this need. Similarly, the important question of whether those who do shed MERS-CoV RNA for extended periods are infectious while appearing well, continues to go unanswered. It is even unclear just how many 'asymptomatic' infections have been described and reported correctly which in turn raises questions about the reliability of other clinical data collection to date. While the basic virology of MERS-CoV has advanced over the course of the past three years, understanding what is happening in, and the interplay between, camel, environment and human is still in its infancy.
Additional file 1: Figure S1 . The | What percentage of all reported cases has MERS reportedly killed ? | false | 4,225 | {
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1,671 | Host resilience to emerging coronaviruses
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7079962/
SHA: f7cfc37ea164f16393d7f4f3f2b32214dea1ded4
Authors: Jamieson, Amanda M
Date: 2016-07-01
DOI: 10.2217/fvl-2016-0060
License: cc-by
Abstract: Recently, two coronaviruses, severe acute respiratory syndrome coronavirus and Middle East respiratory syndrome coronavirus, have emerged to cause unusually severe respiratory disease in humans. Currently, there is a lack of effective antiviral treatment options or vaccine available. Given the severity of these outbreaks, and the possibility of additional zoonotic coronaviruses emerging in the near future, the exploration of different treatment strategies is necessary. Disease resilience is the ability of a given host to tolerate an infection, and to return to a state of health. This review focuses on exploring various host resilience mechanisms that could be exploited for treatment of severe acute respiratory syndrome coronavirus, Middle East respiratory syndrome coronavirus and other respiratory viruses that cause acute lung injury and acute respiratory distress syndrome.
Text: The 21st century was heralded with the emergence of two novel coronaviruses (CoV) that have unusually high pathogenicity and mortality [1] [2] [3] [4] [5] . Severe acute respiratory syndrome coronavirus (SARS-Cov) was first identified in 2003 [6] [7] [8] [9] . While there was initially great concern about SARS-CoV, once no new cases emerged, funding and research decreased. However, a decade later Middle East respiratory syndrome coronavirus (MERS-CoV), also known as HCoV-EMC, emerged initially in Saudi Arabia [3, 10] . SARS-CoV infected about 8000 people, and resulted in the deaths of approximately 10% of those infected [11] . While MERS-CoV is not as widespread as SARS-CoV, it appears to have an even higher mortality rate, with 35-50% of diagnosed infections resulting in death [3, [12] [13] . These deadly betacoronavirus viruses existed in animal reservoirs [4] [5] 9, [14] [15] . Recently, other CoVs have been detected in animal populations raising the possibility that we will see a repeat of these types of outbreaks in the near future [11, [16] [17] [18] [19] [20] . Both these zoonotic viruses cause a much more severe disease than what is typically seen for CoVs, making them a global health concern. Both SARS-CoV and MERS-CoV result in severe lung pathology. Many infected patients have acute lung injury (ALI), a condition that is diagnosed based on the presence of pulmonary edema and respiratory failure without a cardiac cause. In some patients there is a progression to the more severe form of ALI, acute respiratory distress syndrome (ARDS) [21] [22] [23] .
In order to survive a given infection, a successful host must not only be able to clear the pathogen, but tolerate damage caused by the pathogen itself and also by the host's immune response [24] [25] [26] . We refer to resilience as the ability of a host to tolerate the effects of pathogens and the immune response to pathogens. A resilient host is able to return to a state of health after responding to an infection [24, [27] [28] . Most currently available treatment options for infectious diseases are antimicrobials, For reprint orders, please contact: [email protected] REviEW Jamieson future science group and thus target the pathogen itself. Given the damage that pathogens can cause this focus on rapid pathogen clearance is understandable. However, an equally important medical intervention is to increase the ability of the host to tolerate the direct and indirect effects of the pathogen, and this is an area that is just beginning to be explored [29] . Damage to the lung epithelium by respiratory pathogens is a common cause of decreased resilience [30] [31] [32] . This review explores some of the probable host resilience pathways to viral infections, with a particular focus on the emerging coronaviruses. We will also examine factors that make some patients disease tolerant and other patients less tolerant to the viral infection. These factors can serve as a guide to new potential therapies for improved patient care.
Both SARS-CoV and MERS-CoV are typified by a rapid progression to ARDS, however, there are some distinct differences in the infectivity and pathogenicity. The two viruses have different receptors leading to different cellular tropism, and SARS-CoV is more ubiquitous in the cell type and species it can infect. SARS-CoV uses the ACE2 receptor to gain entry to cells, while MERS-CoV uses the ectopeptidase DPP4 [33] [34] [35] [36] . Unlike SARS-CoV infection, which causes primarily a severe respiratory syndrome, MERS-CoV infection can also lead to kidney failure [37, 38] . SARS-CoV also spreads more rapidly between hosts, while MERS-CoV has been more easily contained, but it is unclear if this is due to the affected patient populations and regions [3] [4] 39 ]. Since MERS-CoV is a very recently discovered virus, [40, 41] more research has been done on SARS-CoV. However, given the similarities it is hoped that some of these findings can also be applied to MERS-CoV, and other potential emerging zoonotic coronaviruses.
Both viral infections elicit a very strong inflammatory response, and are also able to circumvent the immune response. There appears to be several ways that these viruses evade and otherwise redirect the immune response [1, [42] [43] [44] [45] . The pathways that lead to the induction of the antiviral type I interferon (IFN) response are common targets of many viruses, and coronaviruses are no exception. SARS-CoV and MERS-CoV are contained in double membrane vesicles (DMVs), that prevents sensing of its genome [1, 46] . As with most coronaviruses several viral proteins suppress the type I IFN response, and other aspects of innate antiviral immunity [47] . These alterations of the type I IFN response appear to play a role in immunopathology in more than one way. In patients with high initial viral titers there is a poor prognosis [39, 48] . This indicates that reduction of the antiviral response may lead to direct viral-induced pathology. There is also evidence that the delayed type I IFN response can lead to misregulation of the immune response that can cause immunopathology. In a mouse model of SARS-CoV infection, the type I IFN response is delayed [49] . The delay of this potent antiviral response leads to decreased viral clearance, at the same time there is an increase in inflammatory cells of the immune system that cause excessive immunopathology [49] . In this case, the delayed antiviral response not only causes immunopathology, it also fails to properly control the viral replication. While more research is needed, it appears that MERS has a similar effect on the innate immune response [5, 50] .
The current treatment and prevention options for SARS-CoV and MERS-CoV are limited. So far there are no licensed vaccines for SAR-CoV or MERS-CoV, although several strategies have been tried in animal models [51, 52] . There are also no antiviral strategies that are clearly effective in controlled trials. During outbreaks several antiviral strategies were empirically tried, but these uncontrolled studies gave mixed results [5, 39] . The main antivirals used were ribavirin, lopinavir and ritonavir [38, 53] . These were often used in combination with IFN therapy [54] . However, retrospective analysis of these data has not led to clear conclusions of the efficacy of these treatment options. Research in this area is still ongoing and it is hoped that we will soon have effective strategies to treat novel CoV [3,36,38,40, [55] [56] [57] [58] [59] [60] [61] [62] [63] [64] .
The lack of effective antivirals makes it necessary to examine other potential treatments for SARS-CoV and MERS-CoV. Even if there were effective strategies to decrease viral burden, for these viruses, the potential for new emerging zoonotic CoVs presents additional complications. Vaccines cannot be produced in time to stop the spread of an emerging virus. In addition, as was demonstrated during SARS-CoV and MERS-CoV outbreaks, there is always a challenge during a crisis situation to know which Host resilience to emerging coronaviruses REviEW future science group www.futuremedicine.com antiviral will work on a given virus. One method of addressing this is to develop broad-spectrum antivirals that target conserved features of a given class of virus [65] . However, given the fast mutation rates of viruses there are several challenges to this strategy. Another method is to increase the ability of a given patient to tolerate the disease, i.e., target host resilience mechanisms. So far this has largely been in the form of supportive care, which relies on mechanical ventilation and oxygenation [29, 39, 66] .
Since SARS-CoV and MERS-CoV were discovered relatively recently there is a lack of both patient and experimental data. However, many other viruses cause ALI and ARDS, including influenza A virus (IAV). By looking at data from other high pathology viruses we can extrapolate various pathways that could be targeted during infection with these emerging CoVs. This can add to our understanding of disease resilience mechanisms that we have learned from direct studies of SARS-CoV and MERS-CoV. Increased understanding of host resilience mechanisms can lead to future host-based therapies that could increase patient survival [29] .
One common theme that emerges in many respiratory viruses including SARS-CoV and MERS-CoV is that much of the pathology is due to an excessive inflammatory response. A study from Josset et al. examines the cell host response to both MERS-CoV and SARS-CoV, and discovered that MERS-CoV dysregulates the host transcriptome to a much greater extent than SARS-CoV [67] . It demonstrates that glucocorticoids may be a potential way of altering the changes in the host transcriptome at late time points after infection. If host gene responses are maintained this may increase disease resilience. Given the severe disease that manifested during the SARS-CoV outbreak, many different treatment options were empirically tried on human patients. One immunomodulatory treatment that was tried during the SARS-CoV outbreak was systemic corticosteroids. This was tried with and without the use of type I IFNs and other therapies that could directly target the virus [68] . Retrospective analysis revealed that, when given at the correct time and to the appropriate patients, corticosteroid use could decrease mortality and also length of hospital stays [68] . In addition, there is some evidence that simultaneous treatment with IFNs could increase the potential benefits [69] . Although these treatments are not without complications, and there has been a lack of a randomized controlled trial [5, 39] .
Corticosteroids are broadly immunosuppressive and have many physiological effects [5, 39] . Several recent studies have suggested that other compounds could be useful in increasing host resilience to viral lung infections. A recent paper demonstrates that topoisomerase I can protect against inflammation-induced death from a variety of viral infections including IAV [70] . Blockade of C5a complement signaling has also been suggested as a possible option in decreasing inflammation during IAV infection [71] . Other immunomodulators include celecoxib, mesalazine and eritoran [72, 73] . Another class of drugs that have been suggested are statins. They act to stabilize the activation of aspects of the innate immune response and prevent excessive inflammation [74] . However, decreasing immunopathology by immunomodulation is problematic because it can lead to increased pathogen burden, and thus increase virus-induced pathology [75, 76] . Another potential treatment option is increasing tissue repair pathways to increase host resilience to disease. This has been shown by bioinformatics [77] , as well as in several animal models [30-31,78-79]. These therapies have been shown in cell culture model systems or animal models to be effective, but have not been demonstrated in human patients. The correct timing of the treatments is essential. Early intervention has been shown to be the most effective in some cases, but other therapies work better when given slightly later during the course of the infection. As the onset of symptoms varies slightly from patient to patient the need for precise timing will be a challenge.
Examination of potential treatment options for SARS-CoV and MERS-CoV should include consideration of host resilience [29] . In addition to the viral effects, and the pathology caused by the immune response, there are various comorbidities associated with SARS-CoV and MERS-CoV that lead to adverse outcomes. Interestingly, these additional risk factors that lead to a more severe disease are different between the two viruses. It is unclear if these differences are due to distinct populations affected by the viruses, because of properties of the virus themselves, or both. Understanding these factors could be a key to increasing host resilience to the infections. MERS-CoV patients had increased morbidity and mortality if they were obese, immunocompromised, diabetic or had cardiac disease [4, 12] .
REviEW Jamieson future science group Risk factors for SARS-CoV patients included an older age and male [39] . Immune factors that increased mortality for SARS-CoV were a higher neutrophil count and low T-cell counts [5, 39, 77] . One factor that increased disease for patients infected with SARS-CoV and MERS-CoV was infection with other viruses or bacteria [5, 39] . This is similar to what is seen with many other respiratory infections. A recent study looking at malaria infections in animal models and human patients demonstrated that resilient hosts can be predicted [28] . Clinical studies have started to correlate specific biomarkers with disease outcomes in ARDS patients [80] . By understanding risk factors for disease severity we can perhaps predict if a host may be nonresilient and tailor the treatment options appropriately.
A clear advantage of targeting host resilience pathways is that these therapies can be used to treat a variety of different infections. In addition, there is no need to develop a vaccine or understand the antiviral susceptibility of a new virus. Toward this end, understanding why some patients or patient populations have increased susceptibility is of paramount importance. In addition, a need for good model systems to study responses to these new emerging coronaviruses is essential. Research into both these subjects will lead us toward improved treatment of emerging viruses that cause ALI, such as SARS-CoV and MERS-CoV.
The author has no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
No writing assistance was utilized in the production of this manuscript.
• Severe acute respiratory syndrome coronavirus and Middle East respiratory syndrome coronavirus are zoonotic coronaviruses that cause acute lung injury and acute respiratory distress syndrome.
• Antivirals have limited effects on the course of the infection with these coronaviruses.
• There is currently no vaccine for either severe acute respiratory syndrome coronavirus or Middle East respiratory syndrome coronavirus.
• Host resilience is the ability of a host to tolerate the effects of an infection and return to a state of health.
• Several pathways, including control of inflammation, metabolism and tissue repair may be targeted to increase host resilience.
• The future challenge is to target host resilience pathways in such a way that there are limited effects on pathogen clearance pathways. Future studies should determine the safety of these types of treatments for human patients.
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1,686 | Nucleolar Protein Trafficking in Response to HIV-1 Tat: Rewiring the Nucleolus
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3499507/
SHA: efa871aeaf22cbd0ce30e8bd1cb3d1afff2a98f9
Authors: Jarboui, Mohamed Ali; Bidoia, Carlo; Woods, Elena; Roe, Barbara; Wynne, Kieran; Elia, Giuliano; Hall, William W.; Gautier, Virginie W.
Date: 2012-11-15
DOI: 10.1371/journal.pone.0048702
License: cc-by
Abstract: The trans-activator Tat protein is a viral regulatory protein essential for HIV-1 replication. Tat trafficks to the nucleoplasm and the nucleolus. The nucleolus, a highly dynamic and structured membrane-less sub-nuclear compartment, is the site of rRNA and ribosome biogenesis and is involved in numerous cellular functions including transcriptional regulation, cell cycle control and viral infection. Importantly, transient nucleolar trafficking of both Tat and HIV-1 viral transcripts are critical in HIV-1 replication, however, the role(s) of the nucleolus in HIV-1 replication remains unclear. To better understand how the interaction of Tat with the nucleolar machinery contributes to HIV-1 pathogenesis, we investigated the quantitative changes in the composition of the nucleolar proteome of Jurkat T-cells stably expressing HIV-1 Tat fused to a TAP tag. Using an organellar proteomic approach based on mass spectrometry, coupled with Stable Isotope Labelling in Cell culture (SILAC), we quantified 520 proteins, including 49 proteins showing significant changes in abundance in Jurkat T-cell nucleolus upon Tat expression. Numerous proteins exhibiting a fold change were well characterised Tat interactors and/or known to be critical for HIV-1 replication. This suggests that the spatial control and subcellular compartimentaliation of these cellular cofactors by Tat provide an additional layer of control for regulating cellular machinery involved in HIV-1 pathogenesis. Pathway analysis and network reconstruction revealed that Tat expression specifically resulted in the nucleolar enrichment of proteins collectively participating in ribosomal biogenesis, protein homeostasis, metabolic pathways including glycolytic, pentose phosphate, nucleotides and amino acids biosynthetic pathways, stress response, T-cell signaling pathways and genome integrity. We present here the first differential profiling of the nucleolar proteome of T-cells expressing HIV-1 Tat. We discuss how these proteins collectively participate in interconnected networks converging to adapt the nucleolus dynamic activities, which favor host biosynthetic activities and may contribute to create a cellular environment supporting robust HIV-1 production.
Text: The nucleolus is a highly ordered subnuclear compartment organised around genetic loci called nucleolar-organising regions (NORs) formed by clusters of hundreds of rDNA gene repeats organised in tandem head-to-tail repeat [1, 2] . A membrane-less organelle originally described as the ''Ribosome Factory'', the nucleolus is dedicated to RNA-polymerase-I-directed rDNA transcription, rRNA processing mediated by small nucleolar ribonucleoproteins (soRNPs) and ribosome assembly. Ribosome biogenesis is essential for protein synthesis and cell viability [2] and ultimately results in the separate large (60S) and small (40S) ribosomal subunits, which are subsequently exported to the cytoplasm. This fundamental cellular process, to which the cell dedicates most of its energy resources, is tightly regulated to match dynamic changes in cell proliferation, growth rate and metabolic activities [3] .
The nucleolus is the site of additional RNA processing, including mRNA export and degradation, the maturation of uridine-rich small nuclear RNPs (U snRNPs), which form the core of the spliceosome, biogenesis of t-RNA and microRNAs (miRNAs) [4] . The nucleolus is also involved in other cellular processes including cell cycle control, oncogenic processes, cellular stress responses and translation [4] .
The concept of a multifunctional and highly dynamic nucleolus has been substantiated by several studies combining organellar proteomic approaches and quantitative mass spectrometry, and describing thousands of proteins transiting through the nucleolus in response to various metabolic conditions, stress and cellular environments [5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16] . Collectively, the aforementioned studies represent landmarks in understanding the functional complexity of the nucleolus, and demonstrated that nucleolar proteins are in continuous exchange with other nuclear and cellular compartments in response to specific cellular conditions.
Of importance, the nucleolus is also the target of viruses including HIV-1, hCMV, HSV and KSHV, as part of their replication strategy [2, 17] . Proteomics studies analysing the nucleoli of cells infected with Human respiratory syncytial virus (HRSV), influenza A virus, avian coronavirus infectious bronchitis virus (IBV) or adenovirus highlighted how viruses can distinctively disrupt the distribution of nucleolar proteins [2, 17, 18, 19, 20, 21, 22, 23, 24] . Interestingly, both HIV-1 regulatory proteins Tat and Rev localise to the nucleoplasm and nucleolus. Both their sequences encompass a nucleolar localisation signal (NoLS) overlapping with their nuclear localisation signal (NLS), which governs their nucleolar localisation [25, 26, 27, 28, 29, 30, 31] . Furthermore, Tat and Rev interact with the nucleolar antigen B23, which is essential for their nucleolar localisation [25, 26, 27, 28, 29, 30] . Nevertheless, a recent study described that in contrast to Jurkat T-cells and other transformed cell lines where Tat is associated with the nucleus and nucleolus, in primary T-cells Tat primarily accumulates at the plasma membrane, while trafficking via the nucleus where it functions [32] . While the regulation of their active nuclear import and/or export, as mediated by the karyopherin/importin family have been well described, the mechanisms distributing Tat and Rev between the cytoplasm, nucleoplasm and the nucleolus remains elusive [33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48] . Importantly, two major studies by Machienzi et al. have revealed important functional links between HIV-1 replication and the nucleolus [49, 50] . First, they could inhibit HIV-1 replication and Tat transactivation function employing a TAR decoy specifically directed to the nucleolus. Furthermore, using a similar approach, with an anti-HIV-1 hammerhead ribozyme fused to the U16 small nucleolar RNA and therefore targeted to the nucleolus, they could dramatically suppress HIV-1 replication. Collectively, these findings strongly suggest that HIV-1 transcripts and Tat nucleolar trafficking are critical for HIV-1 replication. However the nature of these contributions remains to be elucidated.
In this report, we systematically analysed the nucleolar proteome perturbations occurring in Jurkat T-cells constitutively expressing HIV-1 Tat, using a quantitative mass spectrometry approach. Following the detailed annotation of the quantitative abundance changes in the nucleolar protein composition upon Tat expression, we focussed on the Tat-affected cellular complexes and signalling pathways associated with ribosome biogenesis, spliceosome, molecular chaperones, DNA replication and repair and metabolism and discuss their potential involvement in HIV-1 pathogenesis.
In this study, we investigated the quantitative changes in the nucleolar proteome of Jurkat T cells constitutively expressing HIV-1 Tat (86aa) versus their Tat-negative counterpart, using stable isotope labelling with amino acids in cell culture (SILAC) technology, followed by ESI tandem mass spectrometry and implemented the experimental approach described in Figure 1A . First, using retroviral gene delivery, we transduced HIV-1 Tat fused to a tandem affinity purification (TAP) tag (consisting of two protein G and a streptavidin binding peptide) or TAP tag alone (control vector) in Jurkat leukemia T cell clone E6-1 and sorted the transduced cells (GFP positive) by FACS. This resulted in a highly enriched population of polyclonal transduced cells presenting different expression levels of the transgene ( Figure 1B) . The functionality of TAP-Tat was confirmed by transfecting Jurkat TAP-Tat and TAP cells with a luciferase reporter gene vector under the control of the HIV-1 LTR (pGL3-LTR) [36] . TAP-Tat up regulated gene expression from the HIV-1 LTR by up to 28 fold compared to control ( Figure 1C ). To further address the functionality of Tat fused to TAP, we compared Jurkat TAP-Tat with Jurkat-tat, a cell line stably expressing untagged Tat [51] . Both cell line exhibited comparable HIV-1 LTR activity following transfection with pGL3-LTR ( Figure S1 ). Next, Tat expression and subcellular localization was verified by subcellular fractionation followed by WB analysis ( Figure 1E ). TAP-Tat displayed a prominent nuclear/nucleolar localization but could also be detected in the cytoplasm. These observations were further validated by immunofluorescence microscopy ( Figure 1E ). Of note, Jurkat-tat presented similar patterns for Tat subcellular distribution as shown by immunofluorescence microscopy and subcellular fractionation followed by WB analysis (Figure S2 and S3). We next compared the growth rate and proliferation of the Jurkat TAP and TAP-Tat cell lines (Materials and Methods S1), which were equivalent ( Figure S4A ). Similarly, FACS analysis confirmed that the relative populations in G1, S, and G2/M were similar for Jurkat TAP-Tat and TAP cells ( Figure S4B ).
We labeled Jurkat TAP-Tat and Jurkat TAP cells with light (R0K0) and heavy (R6K6) isotope containing arginine and lysine, respectively. Following five passages in their respective SILAC medium, 85 million cells from each culture were harvested, pooled and their nucleoli were isolated as previously described ( Figure 1A ) [52] . Each step of the procedure was closely monitored by microscopic examination. To assess the quality of our fractionation procedure, specific enrichment of known nucleolar antigens was investigated by Western Blot analysis ( Figure 1D ). Nucleolin (110 kDa) and Fibrillarin (FBL) (34 kDa), two major nucleolar proteins known to localise to the granular component of the nucleolus, were found to be highly enriched in the mixed nucleolar fraction. Of note, nucleolin was equally distributed between the nuclear and cytoplasmic fractions. This distribution pattern for nucleolin appears to be specific for Jurkat T-cells as show previously [52, 53] . The nuclear protein PARP-1 (Poly ADPribose polymerase 1) (113 kDa) was present in the nuclear and nucleoplasmic fraction but was depleted in the nucleolar fraction. Alpha-tubulin (50 kDa) was highly abundant in the cytoplasmic fraction and weakly detected in the nuclear fractions. Collectively, these results confirmed that our methods produced a highly enriched nucleolar fraction without significant cross contamination.
Subsequently, the nucleolar protein mixture was trypsindigested and the resulting peptides were analysed by mass spectrometry. Comparative quantitative proteomic analysis was performed using MaxQuant to analyse the ratios in isotopes for each peptide identified. A total of 2427 peptides were quantified, representing 520 quantified nucleolar proteins. The fully annotated list of the quantified nucleolar proteins is available in Table S1 and the raw data from the mass spectrometry analysis was deposited in the Tranche repository database (https:// proteomecommons.org/tranche/), which can be accessed using the hash keys described in materials and methods. We annotated the quantified proteins using the ToppGene Suite tools [54] and extracted Gene Ontology (GO) and InterPro annotations [55] . The analysis of GO biological processes ( Figure 1F ) revealed that the best-represented biological processes included transcription (24%), RNA processing (23%), cell cycle process (13%) and chromosome organisation (15%), which reflects nucleolar associated functions and is comparable to our previous characterisation of Jurkat T-cell nucleolar proteome [52] . Subcellular distribution analysis ( Figure 1F ) revealed that our dataset contained proteins known to localise in the nucleolus (49%), in the nucleus (24%) while 15% of proteins were previously described to reside exclusively in the cytoplasm. The subcellular distribution was similar to our previous analysis of the Jurkat T-cell nucleolar proteome [52] . Table S1 . The distribution of protein ratios are represented in Figure 1G as log 2 (abundance change). The SILAC ratios indicate changes in protein abundance in the nucleolar fraction of Jurkat TAP-Tat cells in comparison with Jurkat TAP cells. The distribution of the quantified proteins followed a Gaussian distribution ( Figure 1G ). A total of 49 nucleolar proteins exhibited a 1.5 fold or greater significant change (p,0.05) upon Tat expression (Table 1) . Of these, 30 proteins were enriched, whereas 19 proteins were depleted. Cells displayed no changes in the steady state content of some of the major and abundant constituents of the nucleolus, including nucleophosmin (NPM1/ B23), C23, FBL, nucleolar protein P120 (NOL1), and nucleolar protein 5A (NOL5A). The distinct ratios of protein changes upon Tat expression could reflect specific nucleolar reorganization and altered activities of the nucleolus.
We performed WB analysis to validate the SILAC-based results obtained by our quantitative proteomic approach ( Figure 2 ). 15 selected proteins displayed differential intensity in the nucleolar fractions upon Tat expression, including 9 enriched (HSP90b, STAT3, pRb, CK2a, CK2a', HSP90a, Transportin, ZAP70, DDX3), and 3 depleted (ILF3, BOP1, and SSRP1) proteins. In addition, we also tested by WB analysis, protein abundance not affected by Tat expression (Importin beta, FBL, B23, C23). These results highlight the concordance in the trend of the corresponding SILAC ratios, despite some differences in the quantitative ranges. Of note, using WB, we could observe a change of intensity for protein with a SILAC fold change as low as 1.25-fold.
Of note, the question remains as to which fold change magnitude might constitute a biologically relevant consequence. On the one hand, the threshold of protein abundance changes can be determined statistically and would then highlight the larger abundance changes as illustrated in Table 1 . Alternatively, the coordinated enrichment or depletion of a majority of proteins belonging to a distinct cellular complex or pathway would allow the definition of a group of proteins of interest and potential significance. Therefore, we next focused on both enriched or depleted individual proteins with activities associated with HIV-1 or Tat molecular pathogenesis, and on clustered modifications affecting entire cellular signaling pathways and macromolecular complexes.
We initially focused on signaling proteins interacting with Tat and/or associated HIV-1 molecular pathogenesis and whose abundance in the nucleolus was modulated by Tat expression.
Phospho-protein phosphatases. Phospho-protein phosphatase PP1 and PP2A are essential serine/threonine phosphatases [56, 57] . Importantly, PP1 accounts for 80% of the Ser/Thr phosphatase activity within the nucleolus. In our study, PP1 was found to be potentially enriched by 1.52-fold in the nucleolus of Jurkat cells expressing Tat, which supports previous studies describing the nuclear and nucleolar targeting of PP1a by HIV-1 Tat and how PP1 upregulates HIV-1 transcription [58, 59, 60, 61, 62] . PP1 c was also identified as part of the in vitro nuclear interactome [63] . Similarly, PPP2CA, the PP2A catalytic subunit (1.29-fold) and its regulatory subunit PP2R1A (1.27-fold) were similarly enriched upon Tat expression. Interestingly, Tat association with the PP2A subunit promoters results in the overexpression and up regulation of PP2A activity in lymphocytes [64, 65] . Furthermore, PP2A contributes to the regulation of HIV-1 transcription and replication [61, 66] .
Retinoblastoma Protein. The tumour suppressor gene pRb protein displayed a 1.4-fold change in the nucleolus upon Tat expression [67] . Furthermore, WB analysis confirmed the distinct translocation of pRb from the nucleoplasm to the nucleolus by Tat ( Figure 2 ). Depending on the cell type, pRb can be hyperphosphorylated or hypophosphorylated upon Tat expression and can negatively or positively regulate Tat-mediated transcription respectively [68, 69, 70] . Interestingly, the hyperphosphorylation of pRB triggers in its translocation into the nucleolus [71] . Phosphorylation of pRB is also associated with an increase in ribosomal biogenesis and cell growth [72] .
STAT3. The transcription factor signal transducer and activator of transcription 3 (STAT3) was significantly enriched (1.86-fold) in the nucleolar fraction by Tat constitutive expression. Furthermore, WB analysis indicated that Tat expression could promote the relocalisation of STAT3 from the cytoplasm to the nucleus, with a distinct enrichment in the nucleolus ( Figure 2) . Interestingly, previous studies have demonstrated Tat-mediated activation of STAT3 signaling, as shown by its phosphorylation status [73] . Interestingly, STAT3 phosphorylation induced dimerisation of the protein followed its translocation to the nucleus [74] .
YBX1. YBX1, the DNA/RNA binding multifunctional protein was enriched by 1.38-fold in the nucleolus of Jurkat cells upon Tat expression. Interestingly, YBX1 interacts with Tat and TAR and modulates HIV-1 gene expression [63, 75] .
ZAP70. The protein tyrosine kinase ZAP70 (Zeta-chainassociated protein kinase 70) was enriched by 1.24-fold in the nucleolus of Jurkat cells expressing Tat [76] . Furthermore, WB analysis revealed that Tat expression could promote the relocalisation of ZAP70 from the cytoplasm to the nucleus, with a distinct enrichment in the nucleolus ( Figure 2 ). Of note, ZAP70 is part of the in vitro nuclear Tat interactome [63] .
Matrin 3. The inner nuclear matrix protein, Matrin 3 (MATR3), presented a 1.39-fold change in the nucleolus of Jurkat cells expressing Tat. It localizes in the nucleolasm with a diffuse pattern excluded from the nucleoli [77] . Matrin 3 has been identified as part of the in vitro HIV-1 Tat nuclear interactome [63] . Two recent studies have described Matrin 3 as part of ribonucleoprotein complexes also including HIV-1 Rev and (Rev Response Element) RRE-containing HIV-1 RNA, and promoting HIV-1 post-transcriptional regulation [78, 79, 80] .
CASP10. The pro-apototic signaling molecule, Caspase 10 (CASP10), was significantly depleted from the nucleolus of Jurkat-Tat cells (0.82-fold) [81] . Importantly, Tat expression downregulates CASP10 expression and activity in Jurkat cells [82] .
ADAR1. Adenosine deaminase acting on RNA (ADAR1), which converts adenosines to inosines in double-stranded RNA, was significantly depleted from the nucleolus of Jurkat-Tat cells (0.78-fold). Interestingly, ADAR1 over-expression up-regulates HIV-1 replication via an RNA editing mechanism [83, 84, 85, 86, 87, 88] . Furthermore, ADAR1 belongs to the in vitro HIV-1 Tat nuclear interactome [63] .
To underline the structural and functional relationships of the nucleolar proteins affected by HIV-1 Tat, we constructed a network representation of our dataset. We employed Cytoscape version 2.6.3 [89] and using the MiMI plugin [90] to map previously characterised interactions, extracted from protein interaction databases (BIND, DIP, HPRD, CCSB, Reactome, IntAct and MINT). This resulted in a highly dense and connected network comprising 416 proteins (nodes) out of the 536 proteins, linked by 5060 undirected interactions (edges) ( Figure 3A ). Centrality analysis revealed a threshold of 23.7 interactions per protein. Topology analysis using the CentiScaPe plugin [91] showed that the node degree distribution follows a power law ( Figure S5 ), characteristic of a scale-free network. Importantly, when we analysed the clustering coefficient distribution ( Figure S6 ) we found that the network is organised in a hierarchical architecture [92] , where connected nodes are part of highly clustered areas maintained by few hubs organised around HIV-1 Tat. Furthermore, node degree connection analysis of our network identified HIV-1 Tat as the most connected protein ( Figure S6 ). Specifically, the topology analysis indicated that the values for Tat centralities were the highest (Node degree, stress, radiality, closeness, betweeness and centroid), characterising Tat as the main hub protein of the nucleolar network. Indeed, a total of 146 proteins have been previously described to interact with Tat ( Figure 3B , Table S2 ). These proteins are involved in a wide range of cellular processes including chromosomal organization, DNA and RNA processing and cell cycle control. Importantly, aver the third of these proteins exhibit an increase in fold ratio change (59 proteins with a ratio .1.2 fold).
In parallel, we characterised the magnitude of the related protein abundance changes observed in distinct cellular pathways ( Figure 4) .
Ribosomal biogenesis. We initially focused on ribosome biogenesis, the primary function of the nucleolus. We could observe a general and coordinated increase in the abundance of ribosomal proteins in the nucleolus by Tat expression (Figure 4 ). While some ribosomal proteins remained unaffected, Tat caused the nucleolar accumulation of several distinct large and small ribosomal proteins, except RPL35A, for which Tat expression caused a marked decrease at the nucleolar level (0.29-fold). Similarly, several proteins involved in rRNA processing exhibited an overall increase in nucleolar accumulation upon Tat expression. These include human canonical members of the L7ae family together with members participating in Box C/D, H/ACA and U3 snoRNPs ( Figure 4) . Conversely, BOP1, a component of the PeBoW (Pescadillo Bop1 WDR12) complex essential for maturation of the large ribosomal subunit, was significantly depleted from the nucleolus of Jurkat TAP-Tat cells (0.81-fold) and this was confirmed by WB analysis (Figure 2 ) [93] . Nevertheless, the other PeBoW complex components, Pes1 (0.94-fold) and WDR12 (1.1fold), were not affected by Tat expression. Of note, we did not detect change in the abundance of protein participating in rDNA transcription such as RNAPOLI, UBF.
Spliceosome. We identified and quantified in our dataset 55 proteins out of the 108 known spliceosomal proteins [94] . These proteins include the small nuclear ribonucleoproteins U1, U2 and U5, Sm D1, D2, D3, F and B, and the heterogeneous nuclear ribonucleoproteins. Our data suggested a distinct increase in the abundance of specific spliceosome complex proteins upon expression of HIV-1 Tat in Jurkat T-cells (Figure 3 and 4) . The only three proteins that were significantly depleted from the nucleolus upon expression of HIV-1 Tat were RBMX (0.89-fold), HNRNPA2B1 (0.84-fold) and SNRPA (0.81-fold). Several investigations showed expression alteration in cellular splicing factors in HIV-1 infected cells [95, 96] .
Molecular chaperones. We have identified several molecular chaperones, co-chaperones and other factors involved into proteostasis to be highly enriched in the nucleolus of T-cells upon Tat expression (Figure 3 and 4) , many of which were previously characterised as part of the Tat nuclear interactome [63] . Several heat-shock proteins including DNAJs, specific HSP90, HSP70 and HSP40 isoforms and their co-factors were distinctively enriched in the nucleolar fraction of Jurkat cells expressing Tat ( Figure 4 ). As shown by WB, while HSP90a and b are mostly cytoplasmic, Tat expression triggers their relocalisation to the nucleus and nucleolus, corroborating our proteomic quantitative approach (Figure 2) . Similarly, heat-shock can cause the HSP90 and HSP70 to relocalise to the nucleolus [97, 98, 99, 100, 101] . In a recent study, Fassati's group has shown that HSP90 is present at the HIV-1 promoter and may directly regulate viral gene expression [102] . We also observed the coordinated increased abundance of class I (GroEL and GroES) and class II (chaperonin containing TCP-1 (CTT)) chaperonin molecules (Figure 3 and 4) upon Tat expression.
Ubiquitin-proteasome pathway. The ubiquitin-proteasome pathway is the major proteolytic system of eukaryotic cells [103] . Importantly, the nuclear ubiquitin-proteasome pathway controls the supply of ribosomal proteins and is important to ribosome biogenesis [104, 105] . The 26S proteasome is composed of the 20S core particle (CP) and the 19S regulatory particle (RP). Alternatively, CP can associate with the 11S RP to form the immunoproteasome. All the quantified proteins in our study are part of the 19S regulatory complex and include PSMD2 (1.5-fold), PSMD3 (1.32-fold), PSMD11 (1.25-fold) and PSMD13 (0.72-fold), the only proteasome component significantly depleted from the nucleolus in the presence of Tat (Figure 4) . Interestingly, Tat interacts with distinct subunits of the proteasome system, including the 19S, 20S and 11S subunits. The consequences of these interactions include the competition of Tat with 11S RP or 19S RP for binding to the 20S CP, which resulted in the inhibition of the 20S peptidase activity [106, 107, 108, 109, 110, 111] . Furthermore, Tat was shown to modify the proteasome composition and activity, which affects the generation of peptide antigens recognized by cytotoxic T-lymphocytes [112] . Importantly, a recent study demonstrated that in the absence of Tat, proteasome components are associated to the HIV-1 promoter and proteasome activity limits transcription [113] . Addition of Tat promoted the dissociation of the 19S subunit from the 20S proteasome, followed by the distinct enrichment of the 19S-like complex in nuclear extracts together with the Tat-mediated recruitment of the 19S subunits to the HIV-1 promoter, which facilitated its transcriptional elongation [113] . We also quantified UBA1 (1.36-fold), the E3 ubiquitin-protein ligase UHRF1 (1.13-fold), UBC (1-fold) and two Ubiquitinspecific-peptidases, USP30 (1.28-fold) and USP20 (0.06-fold) (Figure 4) .
DNA replication and repair. Upon HIV-1 Tat expression, we observed the coordinated nucleolar enrichment of several cellular factors associated with DNA replication and repairs pathways (Figure 4) .
Tat induced the coordinated enrichment of the miniature chromosome maintenance MCM2-7 complex (from 1.23-to 3.30fold, respectively) [114] . MCM7, 6 and 3 were identified as part of the in vitro nuclear interactome of HIV-1 Tat [63] . The structural maintenance of chromosomes 2, SMC2, was enriched (1.35-fold) in the nucleolar fraction by Tat expression. SMC2 was identified as part of the in vitro nuclear interactome of HIV-1 Tat [63] . While replication factor C1 (RFC1) and RFC2 (1.31-and 1.28-fold respectively) displayed an increased fold change and RFC5/3 were not affected, RFC4 was severely depleted (0.69-fold) from the nucleolar fraction upon Tat expression [115] . RFC1 and RFC2 were identified as part of the in vitro nuclear interactome of HIV-1 Tat [63] . Tat induced the enrichment of XRCC6 (1.27-fold) and XRCC5 (1.36-fold) in the nucleolus, which are involved in the repair of non-homologous DNA end joining (NHEJ) [116] . XRCC6 associates with viral preintegration complexes containing HIV-1 Integrase and also interact with Tat and TAR [117, 118, 119] . Furthermore, in a ribozyme-based screen, XRCC5 (Ku80) knockdown decreased both retroviral integration and Tatmediated transcription [120] . As part of the base excision repair (BER), we have identified a major apurinic/apyrimidinic endonuclease 1 (APEX1) (1.29-fold) . Importantly, in a siRNA screen targeting DNA repair factors, APEX1 knockdown was found to inhibit HIV-1 infection by more 60% [121] . The high mobility group (HMG) protein, HMGA1 (1.30-fold), was enriched in the nucleolus following Tat expression [122] . HMGA1 interact with HIV-1 Integrase and is part of the HIV-1 pre-integration complex [123, 124] . Importantly, HMGA1 has been identified in a proteomic screen, as a cellular cofactor interacting with the HIV-1 59leader [125] .
Metabolism. Our proteomic data suggest that Tat induces perturbations in glycolysis, the pentose phosphate pathway, and nucleotide and amino acid biosynthesis (Figure 4 and Figure S7 ). Notably, in T cells expressing Tat, we detected co-ordinated changes in the abundance of proteins not previously known to be associated with Tat pathogenesis, which revealed unexpected connections with with glycolysis and the pentose phosphate pathway, including the following glycolitic enzymes, lactate dehydrogenase B (LDHB) (1.37-fold), glyceraldehyde 3-phosphate dehydrogenase (GAPDH) (1.17-fold) and phosphoglyceric acid mutase (PGAM1) (0.89-fold) ( Figure 4 and Figure S7 ). Briefly, GPI catalyzes the reversible isomerization of glucose-6-phosphate in fructose-6-phosphate. Subsequently, PFKP catalyzes the irreversible conversion of fructose-6-phosphate to fructose-1,6-bisphosphate and is a key regulatory enzyme in glycolysis. At the end of the glycolytic pathway, PKM2, in its tetrameric form, is known to generate ATP and pyruvate, while LDHB diverts the majority of the pyruvate to lactate production and regeneration of NAD+ in support to continued glycolysis, a phenomenon described for proliferative Tcells [126] . Of note, in highly proliferating cells, PKM2 can be found in its dimeric form and its activity is altered. This upregulates the availibility of glucose intermediates, which are rerouted to the pentose phosphate and serine biosynthesis pathways for the production of biosynthetic precursors of nucleotides, phospholipids and amino acids. As part of the pentose phosphate pathway, we have characterised the significant enrichment of glucose-6-phosphate dehydrogenase (G6PD) (2.11-fold), which branches of the glycolysis pathway to generate NADPH, ribose-5phosphate an important precursor for the synthesis of nucleotides. Consistent with this, we detected the coordinated increase in the abundance of enzymes which plays a central role in the synthesis of purines and pyrimidines. More specifically, IMPDH2 (1.66fold), a rate-limiting enzyme at the branch point of purine nucleotide biosynthesis, leading to the generation of guanine nucleotides, phosphoribosyl pyrophosphate synthetase 2 (PRPS2) (1.41-fold), cytidine-5-prime-triphosphate synthetase (CTPS) (1.74-fold) which catalyses the conversion of UTP to CTP and the ribonucleotide reductase large subunit (RRM1) (1.56-fold). In parralel, we noted the increased abundance of the phosphoserine aminotransferase PSAT1 (1.90-fold), an enzyme implicated in serine biosynthesis, which has been linked with cell proliferation in vitro.
The host-virus interface is a fundamental aspect in defining the molecular pathogenesis of HIV-1 [127, 128, 129, 130, 131, 132, 133] . Indeed, with its limited repertoire of viral proteins, HIV-1 relies extensively on the host cell machinery for its replication. Several recent studies have capitalized on the recent advances in the ''OMICS'' technologies, and have revealed important insights into this finely tuned molecular dialogue [132, 134] . HIV-1 Tat is essential for viral replication and orchestrates HIV-1 gene expression. The viral regulatory protein is known to interact with an extensive array of cellular proteins and to modulate cellular gene expression and signaling pathway [135, 136] . We and others have employed system-level approaches to investigate Tat interplay with the host cell machinery, which have characterised HIV-1 Tat as a critical mediator of the host-viral interface [137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149] . Here, we have investigated the nucleolar proteins trafficking in response to HIV-1 Tat expression in T-cells, with the view to provide unique and novel insights on the role of proteins compartimentalisation by Tat in the fine-tuning of protein availability and function.
We have developed for this study, a cellular model using Jurkat T-cells stably expressing Tat fused in its N-ternminal to TAP-tag.
Jurkat T-cells are robust and present the advantage to grow without stimulations and are easely transduced using retroviral gene delivery. Importantly, they have been widely employed to evaluate Tat-mediated pathogenesis using system-wide approaches and to analyse T-cell key cellular signaling pathways and functions [144, 150, 151, 152] . Indeed, we have found them particularly suited for prolongued in vitro culture in SILAC medium and subsequent isolation of their nucleolus followed by MS analysis, which requires up to 85 millions of cells. We fused Tat to the TAP tag to enable future downstream applications such as Tandem affinity purification or Chromatin IP analysis. Importantly, we have confirm that N-terminal TAP-tag did not interfere with Tat function nor its localisation in Jurkat cells, when compared to untagged-Tat. Of note, Tat subcellular distribution can vary according to the cell type employed. While Tat is known to accumulate in the nucleus and nucleolus in Jurkat cells and other transformed cell lines, in primary T-cells, Tat was described to primarily accumulate at the plasma membrane, while trafficking via the nucleus where it functions [32] . These differences remain to be characterised but could be related to different expression levels of transport factors in transformed cell lines versus primary cells, as recently described by Kuusisto et al. [39] . Furthermore, Stauber and Pavlakis have suggested that Tat nucleolar localisation could be the results of Tat overexpression [31] . Here, we have selected and employed a polyclonal population of Jurkat T-cells expressing Tat at different levels. We propose that this heterogeneity in Tat expression levels might reflect Tat stochastic expression described during viral replication [153] .
Using a quantitative proteomic strategy based on an organellar approach, we quantified over 520 nucleolar proteins, including 49 proteins exhibiting a significant fold change. The extent to which the induced variations in the abundance of nucleolar proteins are biologically relevant and can affect cellular and/or viral processes remains to be determined. Nevertheless, the biological nature of the pathways and macromolecular complexes affected enable us to discuss their potential associations with HIV-1 pathogenesis.
HIV-1 Tat is expressed early following HIV-1 genome integration and mediates the shift to the viral production phase, associated with robust proviral gene expression, viral proteins assembly and ultimately, virions budding and release. In this context and based on our results, we propose that Tat could participate in shaping the intracellular environment and metabolic profile of T cells to favor host biosynthetic activities supporting robust virions production. Indeed, we observed the distinct nucleolar enrichment of ribosomal proteins and enzymes associated with ribosomal biogenesis, which could be indicative of an increase in protein synthesis. With the notable exeption of RPL35A nucleolar depletion, ribosomal proteins and enzymes associated with ribosomal biogenesis were in the top 20 most enriched nucleolar proteins (NHP2L1, RLP14, RPL17, RPL27, RPS2, RPL13). Furthermore, this effect appears to be specific to HIV-1 Tat since transcription inhibition by Actinomycin D resulted in the overall depletion of ribosomal proteins in the nucleolus [9] . Moreover, quantitative proteomics analysis of the nucleous in adenovirus-infected cells showed a mild decrease in ribosomal proteins [24] . Whether this reflect a shift in ribosome biogenesis and/or a change in the composition of the ribosomal subunits remains to be determined. Nevertheless, the adapted need for elevated ribosome production is intuitive for a system that needs to support the increased demand for new viral proteins synthesis. In parralel, we observed the concordant modulation of pathways regulating protein homeostasis. We noted the significant nucleolar accumulation of multiple molecular chaperones including the HSPs, the TCP-1 complex, and CANX/CALR molecules and the disrupted nucleolar abundance of proteins belonging to the ubiquitin-proteasome pathway, which controls the supply of ribosomal proteins [104, 105] . These observations further support previous studies describibing the modulation of the proteasomal activity by Tat, which affect the expression, assembly, and localization of specific subunits of the proteasomal complexes [106, 107, 108, 109, 110, 111, 113] . We also observed the concomitant depletion of CASP10 in the nucleolus of Jurkat TAP-Tat. It has been suggested that CASP10 could be targeted to the nucleolus to inhibit protein synthesis [154] . Interestingly, the presence and potential roles of molecular chaperones in the nucleolus have been highlighted by Banski et al, who elaborate on how the chaperone network could regulate ribosome biogenesis, cell signaling, and stress response [97, 155] . As viral production progresses into the late phase and cellular stress increases, nucleolar enrichment of molecular chaperones by Tat could not only enable adequat folding of newly synthetised viral proteins but could also promote tolerance of infected cells to stress and maintain cell viability.
Coincidentally, we observed the marked nucleolar enrichment of enzymes belonging to metabolic pathways including glycolysis, pentose phosphate, nucleotide and amino acid biosynthetic pathways. Similarly, these pathways are elevated in proliferative T-cells or in cancer cells following a metabolic shift to aerobic glycolysis, also known as the Warburg effect [156, 157, 158, 159] . There, glucose intermediates from the glycolysis pathway are not only commited to energy production and broke-down into pyruvate for the TCA cycle, but are redirected to alternative pathways, including the pentose phosphate pathway, and used as metabolic precursors to produce nucleotides, amino acids, acetyl CoA and NADPH for redox homeostasis. Consistently, we also noted the concomittant nucleolar enrichment of enzymes belonging to the nucleotide synthesis pathway, including IMPH2, a rate limiting enzyme known to control the pool of GTP. Similarly, we noted the nucleolar enrichment of PSAT1, an enzyme involved in serine and threonin metabolism, which is associated with cellular proliferation [160] . Collectively, we propose that by controlling protein homeostasis and metabolic pathways, Tat could meet both the energetic and biosynthetic demand of HIV-1 productive infection.
Of note, while nucleotide metabolism enzymes are associated with the nucleus, glycolysis takes place in the cytoplasm. Nevertheless, glycolytic enzymes have been detected in both the nuclear and nucleolar fractions by proteomic analyses [8, 161] . Furthermore glycolytic enzymes, such as PKM2, LDH, phosphoglycerate kinase, GAPDH, and aldolase, also have been reported to display nuclear localization and bind to DNA [162] . More specifically, PKM2 is known to associate with promoter and participate in the regulation of gene expression as a transcriptional coactivator [163] .
HIV-1 Tat has previously been described as an immunoregulator and more specifically, has been reported both to inhibit or to promote TCR signaling [164] . We have observed the nucleolar enrichment by Tat of key proximal or downstream components of T-cell signaling pathways, including ZAP70, ILF3 and STAT3, which play crucial roles in T-cell development and activation. We had previously identified them as T-cell specific components of the nucleolus, and IF studies suggested that their association with the nucleolus could be regulated by specific conditions [165] . Our results further support that Tat could contribute to the dysregulation of TCR-derived signals and that the nucleolus could represent an important spatial link for TCR signaling molecules.
We observed the coordinated nucleolar enrichment of key components of the DNA replication, recombination and repair pathways by Tat. These include XRCC5 and XRCC6, HMGA1, APEX1, MCM2-7, SMC2, RFC1 and RFC2, while RFC4 was found to be significantly depleted. Interestingly, these cofactors have been associated with the efficiency of retroviral DNA integration into the host DNA or the integrity of integrated provirus [166] . Whether the increased abundance of these factors within the nucleolus could be associated with their potential participation in the integration and maintenance of provirus gene integrity, remains to be determined.
The mechanisms of Tat-mediated segregation and compartimentalisation of proteins in or out of the nucleolus may depend on factor(s) inherent for each protein and the nature of their relationship with Tat, since subcellular fractionation combined with WB analysis showed that the pattern and extent of subcellular redistribution between proteins varied. We could observe cases where Tat upregulated the expression of proteins which resulted in a general increase of theses proteins throughout the cellular compartments including the nucleolus (DDX3, TNPO1). Alternatively, Tat could trigger the nucleolar translocation of proteins directly from the cytoplasm or the nucleoplasm (pRb). Additionally, we observed cytoplasmic proteins redistributed to both the nucleoplasm and nucleolus upon Tat expression (STAT3, ZAP70 and HSP90). Finally, we also noted protein depletion in the nucleolar fraction accompanied by an increase in the nucleoplasm (SSRP1). It remains difficult at this stage, to appreciate whether the accumulation of specific proteins would result in their activation or inhibition by sequestering them away from their site of action. Conversely, the depletion of a protein from the nucleolus could either result in the down-regulation of its activity in this location or could be the result of its mobilization from its storage site, the nucleolus, to the nucleoplasm or cytoplasm where it can perform its function. Remarkably, we identified several known HIV-1 Tat partners involved in HIV-1 pathogenesis, which suggests that Tat could physically modulate their nucleolar targeting or their recruitment to specific site in the nucleoplasm or cytoplasm. Tat could also promote post-translational modifications, which could mediate the targeting of specific proteins to the nucleolus. This is exemplified by the following enriched proteins, pRb, PP1 and STAT3, for which phosphorylation is induced by Tat. Importantly, their phosphorylation status determines their subcellular distribution, thus providing a potential mechanism for their redistribution by Tat. Moreover, our data indicates that serine/threonine kinases (CK2 a') and phosphatases (PP1) were significantly enriched in the nucleolar fractions of Jurkat TAP-Tat. These enzymes account for the majority of the phosphorylation/ dephosphorylation activity in the nucleolus and can act as regulators of nucleolar protein trafficking. In addition, Tat significantly decreased the levels of SUMO-2 in the nucleolus. Similarly, SUMO-mediated post-translational modifications are known to modulate nucleolar protein localization [104] . Given the potential importance of post-translational modifications, including phosphorylation in the Tat-mediated change of abundance of nucleolar proteins, a more targeted proteomic approach such as the enrichment for phosphopetides, would extend the resolution of our screening approach.
The control of protein turnover is also an important mean to modulate the abundance of nucleolar proteins. Ribosomal proteins are degraded by the Ubiquitin-Proteasome pathway to ensure their abundance matches up with rRNA transcription levels. Conversely, heat shock proteins HSP90s protect them from degradation. Interestingly, our data showing that Tat modulation the abundance proteins associated with the Ubiquitin-proteasome and heat-shock pathway. This could contribute to the observed enrichment of ribosomal proteins by Tat. Nevertheless, we cannot exclude that the increased abundance of ribosomal proteins in the nucleolus could be the result of Tat-mediated prevention of their export to the cytoplasm. Interestingly, using a different cellular system, a drosophila melanogaster Tat transgenic strain, Ponti et al, analysed the effects of Tat on ribosome biogenesis, following 3 days heat shock treatment to induce Tat expression under the control of the hsp70 promoter [167] . Following Tat expression, they observed a defect in pre-rRNA processing associated with a decrease in the level of 80S ribosomes [167] . Nevertheless, the different cellular system employed combined with the 3 days heatshock induction make their results difficult to compare with ours.
While previous system-level studies have monitored the effects of HIV-1 Tat expression on T cells, to our knowledge, we have presented here the first proteomic analysis of dynamic composition of the nucleolus in response to HIV-1 Tat expression. Using quantitative proteomics, we have underlined the changes in abundance of specific nucleolar proteins and have highlighted the extensive and coordinated nucleolar reorganization in response to Tat constitutive expression. Our findings underscore that Tat expressing T-cells exhibit a unique nucleolar proteomic profile, which may reflect a viral strategy to facilitate the progression to robust viral production. Importantly, we noted the functional relationship of nucleolar proteins of our dataset with HIV-1 pathogenesis and HIV-1 Tat in particular. This further increases our confidence in our experimental strategy and suggests a role for Tat in the spatial control and subcellular compartimentaliation of these cellular cofactors. Ultimatly, our study provides new insights on the importance of Tat in the cross talk between nucleolar functions and viral pathogenesis. Importantly, we have also identified changes in nucleolar protein abundance that were not previously associated with HIV-1 pathogenesis, including proteins associated with metabolic pathways, which provide new potential targets and cellular pathways for therapeutic intervention.
Jurkat T-cells, clone E6.1 (ATCC), Jurkat NTAP-Tat and Jurkat NTAP were maintained in RPMI-1640 medium supplemented with 10% (v/v) foetal bovine serum (Gibco, EU approved), and antibiotics. Phoenix-GP cells (G.P. Nolan; www.stanford.edu/ group/nolan/), were maintained in DMEM medium supplemented with 10% (v/v) foetal bovine serum (GIBCO, EU approved). Cells were counted using Scepter TM 2.0 Cell Counter (Millipore).
The sequence of HIV-1 Tat (HIV-1 HXB2, 86 amino acids) was sub-cloned into pENTR 2B vector (Invitrogen, A10463). Using the Gateway technology (Invitrogen), we introduced the HIV-1 Tat sequence into the plasmid pCeMM-NTAP(GS)-Gw [168] . Phoenix cells (G.P. Nolan; www.stanford.edu/group/ nolan/), were transfected using Fugene 6 (Roche) with 5 mg of the plasmid NTAP-Tat or NTAP and 3 mg of the pMDG-VSVG. Viral supernatants were collected after 48 h, filtered and used to transduce the Jurkat cell lines. The construct is termed NTAP-Tat, the empty vector was termed NTAP. Using retroviral gene delivery, we stably transduced Jurkat cells (clone E6.1 (ATCC)). The positive clones named Jurkat NTAP-Tat and Jurkat NTAP were sorted to enrich the population of cells expressing GFP using the BC MoFlo XDP cell sorter (Beckman Coulter).
Sub-cellular fractions (10 mg) were resolved by SDS-PAGE and transferred onto BioTrace PVDF membranes (Pall corporation). The following primary antibodies were used: a-Tubulin (Sc 5286), C23 (Sc 6013), and Fibrillarin (Sc 25397) were from Santa Cruz Biotechnology, and PARP (AM30) from Calbiochem, mouse anti-ZAP 70 (05-253, Millipore), rabbit anti-STAT3 (06-596, Millipore), rabbit anti-ILF3 (ab92355, Abcam), rabbit anti-HSP90 beta (ab32568, Abcam), mouse anti-ADAR1 (ab88574, Abcam), rabbit anti-HDAC1 (ab19845, Abcam), rabbit anti-SSRP1 (ab21584, Abcam) rabbit anti-BOP1 (ab86982, Abcam), mouse anti-KpNB1 (ab10303, Abcam), rabbit anti-HIV-1 Tat (ab43014, Abcam), rabbit anti-CK2A (ab10466, Abcam), rabbit anti-DDX3X (ab37160, Abcam), mouse anti-TNPO1 (ab2811, Abcam), mouse anti-HSP90A (CA1023, MERCK), and rabbit-anti RB1 (sc-102, Santa Cruz).The following secondary antibodies were used ECL: Anti-mouse IgG and ECL Anti-rabbit IgG (GE Healthcare), and Donkey anti-goat IgG (Sc 2020) (Santa Cruz Biotechnology).
For SILAC analysis SILAC-RPMI R0K0 and SILAC-RPMI R6K6 (Dundee cells) media supplemented with 10% dialyzed FBS (GIBCO, 26400-036) were used. The Jurkat cells expressing NTAP-Tat and NTAP were serially passaged and grown for five doublings to ensure full incorporation of the labelled amino acids. Cells viability was checked with Trypan Blue (0.4% solution, SIGMA) and further confirmed using PI staining and FACS analysis. Cells were mixed to the ratio 1:1 to obtain 140610 6 cells. Nucleoli were isolated from the mixed cell population as previously described in Jarboui et al., [165] .
Nucleolar extracts (100 mg) were resuspended in 50 mM ammonium bicarbonate and in solution trypsin digested as previously described in Jarboui et al. [165] . Sample was run on a Thermo Scientific LTQ ORBITRAP XL mass spectrometer connected to an Eksigent NANO LC.1DPLUS chromatography system incorporating an auto-sampler. Sample was loaded onto a Biobasic C18 PicofritTM column (100 mm length, 75 mm ID) and was separated by an increasing acetonitrile gradient, using a 142 min reverse phase gradient (0-40% acetonitrile for 110 min) at a flow rate of 300 nL min-1. The mass spectrometer was operated in positive ion mode with a capillary temperature of 200uC, a capillary voltage of 46V, a tube lens voltage of 140V and with a potential of 1800 V applied to the frit. All data was acquired with the mass spectrometer operating in automatic data dependent switching mode. A high resolution MS scan was performed using the Orbitrap to select the 5 most intense ions prior to MS/MS analysis using the Ion trap.
The incorporation efficiency of labelled amino-acids was determined by analysing the peptides identified in isolated nucleoli from cell population maintained in ''Heavy'' medium as described in [169] . Our analysis showed that we had an incorporation efficiency .95% (data not shown).
The MS/MS spectra were searched for peptides identification and quantification using the MaxQuant software [170] (version 1.1.1.36), the Human IPI Database (version 3.83) and the Andromeda search engine associated to MaxQuant [171] . Standard settings were used for MaxQuant with the Acetyl (Protein N-term) as variable modification and Carbamidomethyl (Cys) as fixed modification, 2 missed cleavage were allowed, except that the filtering of labelled amino acids was prohibited. Initial mass deviation of precursor ion and fragment ions were 7 ppm and 0.5 Da, respectively. Each protein ratio was calculated as the intensity-weighted average of the individual peptides ratios. Proteins were identified with the minimum of one peptide with a false discovery rate less than 1%.
Gene ontology, KEGG pathway and Pfam terms were extracted from UNIPROT entries using Perseus, a software from the MaxQuant Data analysis package (http://www.maxquant.org ), and the ToppGene suite tools [54] .
The Jurkat NTAP-Tat and Jurkat NTAP were transfected using the Amaxa electroporation system (Amaxa biosystem) with the pGL3 (pGL3-LTR) (Promega) as recommended by Amaxa Biosystem. Dual-luciferase assays (Promega) were performed according to the manufacturer's instructions. Luciferase activity was measured and normalized against the total amount of proteins as quantified by the BCA protein quantification kit (Pierce, Thermo Scientific).
To preserve their original shape, we performed immunostaining of Jurkat cells in suspension. Cells were fixed in 2% PFA for 10 min at RT, permeabilised in 0.5% Triton X-100 for 15 min at RT and blocked with 5% FCS. Cells were incubated with the rabbit HIV-1 Tat antibody (ab43014, Abcam) followed by the secondary antibody anti-Rabbit alexa fluor 647 (A-21246, Invitrogen). Cells were allowed to attach to Cell-Tak (BD) coated Silanised Slides (DaoCytomation), and stained with DAPI. Images were captured with a Carl Zeiss Confocal Microscope equipped with a Plan-Apochromat 63X/1.4 oil DIC objective.
The proteomics RAW Data file from the mass spectrometry analysis was deposited to the Tranche repository(https:// proteomecommons.org/tranche/) [172] . The file can be accessed and downloaded using the following hash key:
(R3O5SV5Z6HvWqrBNDhp21tXFetluDWYxvwMIfU-h6e1kMgarauCSq4dlNcxeUvFOHDEzLeDcg4X5Y8reSb6-MUA6wM1kIAAAAAAAAB/w = = ). Materials and Methods S1 Description of the methods employed to examine cell cycle, cell viability and cell proliferation analysis.
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2,642 | First cases of coronavirus disease 2019 (COVID-19) in the WHO European Region, 24 January to 21 February 2020
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7068164/
SHA: ce358c18aac69fc83c7b2e9a7dca4a43b0f60e2e
Authors: Spiteri, Gianfranco; Fielding, James; Diercke, Michaela; Campese, Christine; Enouf, Vincent; Gaymard, Alexandre; Bella, Antonino; Sognamiglio, Paola; Sierra Moros, Maria José; Riutort, Antonio Nicolau; Demina, Yulia V.; Mahieu, Romain; Broas, Markku; Bengnér, Malin; Buda, Silke; Schilling, Julia; Filleul, Laurent; Lepoutre, Agnès; Saura, Christine; Mailles, Alexandra; Levy-Bruhl, Daniel; Coignard, Bruno; Bernard-Stoecklin, Sibylle; Behillil, Sylvie; van der Werf, Sylvie; Valette, Martine; Lina, Bruno; Riccardo, Flavia; Nicastri, Emanuele; Casas, Inmaculada; Larrauri, Amparo; Salom Castell, Magdalena; Pozo, Francisco; Maksyutov, Rinat A.; Martin, Charlotte; Van Ranst, Marc; Bossuyt, Nathalie; Siira, Lotta; Sane, Jussi; Tegmark-Wisell, Karin; Palmérus, Maria; Broberg, Eeva K.; Beauté, Julien; Jorgensen, Pernille; Bundle, Nick; Pereyaslov, Dmitriy; Adlhoch, Cornelia; Pukkila, Jukka; Pebody, Richard; Olsen, Sonja; Ciancio, Bruno Christian
Date: 2020-03-05
DOI: 10.2807/1560-7917.es.2020.25.9.2000178
License: cc-by
Abstract: In the WHO European Region, COVID-19 surveillance was implemented 27 January 2020. We detail the first European cases. As at 21 February, nine European countries reported 47 cases. Among 38 cases studied, 21 were linked to two clusters in Germany and France, 14 were infected in China. Median case age was 42 years; 25 were male. Late detection of the clusters’ index cases delayed isolation of further local cases. As at 5 March, there were 4,250 cases.
Text: In the WHO European Region, COVID-19 surveillance was implemented 27 January 2020. We detail the first European cases. As at 21 February, nine European countries reported 47 cases. Among 38 cases studied, 21 were linked to two clusters in Germany and France, 14 were infected in China. Median case age was 42 years; 25 were male. Late detection of the clusters' index cases delayed isolation of further local cases. As at 5 March, there were 4,250 cases.
A cluster of pneumonia of unknown origin was identified in Wuhan, China, in December 2019 [1] . On 12 January 2020, Chinese authorities shared the sequence of a novel coronavirus termed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) isolated from some clustered cases [2] . Since then, the disease caused by SARS-CoV-2 has been named coronavirus disease 2019 (COVID -19) . As at 21 February 2020, the virus had spread rapidly mostly within China but also to 28 other countries, including in the World Health Organization (WHO) European Region [3] [4] [5] .
Here we describe the epidemiology of the first cases of COVID-19 in this region, excluding cases reported in the United Kingdom (UK), as at 21 February 2020. The study includes a comparison between cases detected among travellers from China and cases whose infection was acquired due to subsequent local transmission.
On 27 January 2020, the European Centre for Disease Prevention and Control (ECDC) and the WHO Regional Office for Europe asked countries to complete a WHO standard COVID-19 case report form for all confirmed and probable cases according to WHO criteria [6] [7] [8] . The overall aim of surveillance at this time was to support the global strategy of containment of COVID-19 with rapid identification and follow-up of cases linked to affected countries in order to minimise onward transmission. The surveillance objectives were to: describe the key epidemiological and clinical characteristics of COVID-19 cases detected in Europe; inform country preparedness; and improve further case detection and management. Data collected included demographics, history of recent travel to affected areas, close contact with a probable or confirmed COVID-19 case, underlying conditions, signs and symptoms of disease at onset, type of specimens from which the virus was detected, and clinical outcome. The WHO case definition was adopted for surveillance: a confirmed case was a person with laboratory confirmation of SARS-CoV-2 infection (ECDC recommended two separate SARS-CoV-2 RT-PCR tests), irrespective of clinical signs and symptoms, whereas a probable case was a suspect case for whom testing for SARS-CoV-2 was inconclusive or positive using a pan-coronavirus assay [8] . By 31 January 2020, 47 laboratories in 31 countries, including 38 laboratories in 24 European Union and European Economic Area (EU/EEA) countries, had diagnostic capability for SARS-CoV-2 available (close to 60% of countries in the WHO European Region), with cross-border shipment arrangements in place for many of those lacking domestic testing capacity. The remaining six EU/EEA countries were expected to have diagnostic testing available by mid-February [9] .
As at 09:00 on 21 February 2020, 47 confirmed cases of COVID-19 were reported in the WHO European Region and one of these cases had died [4] . Data on 38 of these cases (i.e. all except the nine reported in the UK) are included in this analysis.
The first three cases detected were reported in France on 24 January 2020 and had onset of symptoms on 17, 19 and 23 January respectively [10] . The first death was reported on 15 February in France. As at 21 February, nine countries had reported cases ( Figure) : Belgium (1), Finland (1), France (12), Germany (16), Italy (3), Russia (2), Spain (2), Sweden (1) and the UK (9 -not included further).
The place of infection (assessed at national level based on an incubation period presumed to be up to 14 days [11] , travel history and contact with probable or confirmed cases as per the case definition) was reported for 35 cases (missing for three cases), of whom 14 were infected in China (Hubei province: 10 cases; Shandong province: one case; province not reported for three cases). The remaining 21 cases were infected in Europe. Of these, 14 were linked to a cluster in Bavaria, Germany, and seven to a cluster in Haute-Savoie, France [12, 13] . Cases from the Bavarian cluster were reported from Germany and Spain, whereas cases from the Haute-Savoie cluster were reported from France All but two cases were hospitalised (35 of 37 where information on hospitalisation was reported), although it is likely that most were hospitalised to isolate the person rather than because of severe disease. The time from onset of symptoms to hospitalisation (and isolation) ranged between 0 and 10 days with a mean of 3.7 days (reported for 29 cases). The mean number of days to hospitalisation was 2.5 days for cases imported from China, but 4.6 days for those infected in Europe. This was mostly a result of delays in identifying the index cases of the two clusters in France and Germany. In the German cluster, for example, the first three cases detected locally were hospitalised in a mean of 5.7 days, whereas the following six took only a mean of 2 days to be hospitalised.
Symptoms at the point of diagnosis were reported for 31 cases. Two cases were asymptomatic and remained so until tested negative. The asymptomatic cases were tested as part of screening following repatriation and during contact tracing respectively. Of the remaining 29, 20 reported fever, 14 reported cough and eight reported weakness. Additional symptoms reported included headaches (6 cases), sore throat (2), rhinorrhoea (2), shortness of breath (2), myalgia (1), diarrhoea (1) and nausea (1). Fever was reported as the sole symptom for nine cases. In 16 of 29 symptomatic cases, the symptoms at diagnosis were consistent with the case definition for acute respiratory infection [16] , although it is possible that cases presented additional symptoms after diagnosis and these were not reported.
Data on pre-existing conditions were reported for seven cases; five had no pre-existing conditions while one was reported to be obese and one had pre-existing cardiac disease. No data on clinical signs e.g. dyspnea etc. were reported for any of the 38 cases.
All hospitalised cases had a benign clinical evolution except four, two reported in Italy and two reported in France, all of whom developed viral pneumonia. All three cases who were aged 65 years or over were admitted to intensive care and required respiratory support and one French case died. The case who died was hospitalised for 21 days and required intensive care and mechanical ventilation for 19 days. The duration of hospitalisation was reported for 16 cases with a median of 13 days (range: 8-23 days). As at 21 February 2020, four cases were still hospitalised.
All cases were confirmed according to specific assays targeting at least two separate genes (envelope (E) gene as a screening test and RNA-dependent RNA polymerase (RdRp) gene or nucleoprotein (N) gene for confirmation) [8, 17] . The specimen types tested were reported for 27 cases: 15 had positive nasopharyngeal swabs, nine had positive throat swabs, three cases had positive sputum, two had a positive nasal swab, one case had a positive nasopharyngeal aspirate and one a positive endotracheal aspirate.
As at 09:00 on 21 February, few COVID-19 cases had been detected in Europe compared with Asia. However the situation is rapidly developing, with a large outbreak recently identified in northern Italy, with transmission in several municipalities and at least two deaths [18] . As at 5 March 2020, there are 4,250 cases including 113 deaths reported among 38 countries in the WHO European region [19] .
In our analysis of early cases, we observed transmission in two broad contexts: sporadic cases among travellers from China (14 cases) and cases who acquired infection due to subsequent local transmission in Europe (21 cases). Our analysis shows that the time from symptom onset to hospitalisation/case isolation was about 3 days longer for locally acquired cases than for imported cases. People returning from affected areas are likely to have a low threshold to seek care and be tested when symptomatic, however delays in identifying the index cases of the two clusters in France and Germany meant that locally acquired cases took longer to be detected and isolated. Once the exposure is determined and contacts identified and quarantined (171 contacts in France and 200 in Germany for the clusters in Haute-Savoie and Bavaria, respectively), further cases are likely to be rapidly detected and isolated when they develop symptoms [15, 20] . In the German cluster, for example, the first three cases detected locally were hospitalised in a mean of 5.7 days, whereas the following six were hospitalised after a mean of 2 days. Locally acquired cases require significant resources for contact tracing and quarantine, and countries should be prepared to allocate considerable public health resources during the containment phase, should local clusters emerge in their population. In addition, prompt sharing of information on cases and contacts through international notification systems such as the International Health Regulations (IHR) mechanism and the European Commission's European Early Warning and Response System is essential to contain international spread of infection.
All of the imported cases had a history of travel to China. This was consistent with the epidemiological situation in Asia, and supported the recommendation for testing of suspected cases with travel history to China and potentially other areas of presumed ongoing community transmission. The situation has evolved rapidly since then, however, and the number of countries reporting COVID-19 transmission increased rapidly, notably with a large outbreak in northern Italy with 3,089 cases reported as at 5 March [18, 19] . Testing of suspected cases based on geographical risk of importation needs to be complemented with additional approaches to ensure early detection of local circulation of COVID-19, including through testing of severe acute respiratory infections in hospitals irrespectively of travel history as recommended in the WHO case definition updated on 27 February 2020 [21] .
The clinical presentation observed in the cases in Europe is that of an acute respiratory infection. However, of the 31 cases with information on symptoms, 20 cases presented with fever and nine cases presented only with fever and no other symptoms. These findings, which are consistent with other published case series, have prompted ECDC to include fever among several clinical signs or symptoms indicative for the suspected case definition.
Three cases were aged 65 years or over. All required admission to intensive care and were tourists (imported cases). These findings could reflect the average older age of the tourist population compared with the local contacts exposed to infection in Europe and do not allow us to draw any conclusion on the proportion of severe cases that we could expect in the general population of Europe. Despite this, the finding of older individuals being at higher risk of a severe clinical course is consistent with the evidence from Chinese case series published so far although the majority of infections in China have been mild [22, 23] .
This preliminary analysis is based on the first reported cases of COVID-19 cases in the WHO European Region. Given the small sample size, and limited completeness for some variables, all the results presented should be interpreted with caution.
With increasing numbers of cases in Europe, data from surveillance and investigations in the region can build on the evidence from countries in Asia experiencing more widespread transmission particularly on disease spectrum and the proportion of infections with severe outcome [22] . Understanding the infection-severity is critical to help plan for the impact on the healthcare system and the wider population. Serological studies are vital to understand the proportion of cases who are asymptomatic. Hospital-based surveillance could help estimate the incidence of severe cases and identify risk factors for severity and death. Established hospital surveillance systems that are in place for influenza and other diseases in Europe may be expanded for this purpose. In addition, a number of countries in Europe are adapting and, in some cases, already using existing sentinel primary care based surveillance systems for influenza to detect community transmission of SARS-CoV-2. This approach will be used globally to help identify evidence of widespread community transmission and, should the virus spread and containment no longer be deemed feasible, to monitor intensity of disease transmission, trends and its geographical spread.
Additional research is needed to complement surveillance data to build knowledge on the infectious period, modes of transmission, basic and effective reproduction numbers, and effectiveness of prevention and case management options also in settings outside of China. Such special studies are being conducted globally, including a cohort study on citizens repatriated from China to Europe, with the aim to extrapolate disease incidence and risk factors for infection in areas with community transmission. Countries together with ECDC and WHO, should use all opportunities to address these questions in a coordinated fashion at the European and global level.
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1,698 | Accelerated viral dynamics in bat cell lines, with implications for zoonotic emergence
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7064339/
SHA: f2cc0d63ff2c4aaa127c4caae21d8f3a0067e3d5
Authors: Brook, Cara E; Boots, Mike; Chandran, Kartik; Dobson, Andrew P; Drosten, Christian; Graham, Andrea L; Grenfell, Bryan T; Müller, Marcel A; Ng, Melinda; Wang, Lin-Fa; van Leeuwen, Anieke
Date: 2020-02-03
DOI: 10.7554/elife.48401
License: cc-by
Abstract: Bats host virulent zoonotic viruses without experiencing disease. A mechanistic understanding of the impact of bats’ virus hosting capacities, including uniquely constitutive immune pathways, on cellular-scale viral dynamics is needed to elucidate zoonotic emergence. We carried out virus infectivity assays on bat cell lines expressing induced and constitutive immune phenotypes, then developed a theoretical model of our in vitro system, which we fit to empirical data. Best fit models recapitulated expected immune phenotypes for representative cell lines, supporting robust antiviral defenses in bat cells that correlated with higher estimates for within-host viral propagation rates. In general, heightened immune responses limit pathogen-induced cellular morbidity, which can facilitate the establishment of rapidly-propagating persistent infections within-host. Rapidly-transmitting viruses that have evolved with bat immune systems will likely cause enhanced virulence following emergence into secondary hosts with immune systems that diverge from those unique to bats.
Text: Bats have received much attention in recent years for their role as reservoir hosts for emerging viral zoonoses, including rabies and related lyssaviruses, Hendra and Nipah henipaviruses, Ebola and Marburg filoviruses, and SARS coronavirus (Calisher et al., 2006; Wang and Anderson, 2019) . In most non-Chiropteran mammals, henipaviruses, filoviruses, and coronaviruses induce substantial morbidity and mortality, display short durations of infection, and elicit robust, long-term immunity in hosts surviving infection (Nicholls et al., 2003; Hooper et al., 2001; Mahanty and Bray, 2004) . Bats, by contrast, demonstrate no obvious disease symptoms upon infection with pathogens that are highly virulent in non-volant mammals (Schountz et al., 2017) but may, instead, support viruses as longterm persistent infections, rather than transient, immunizing pathologies (Plowright et al., 2016) .
Recent research advances are beginning to shed light on the molecular mechanisms by which bats avoid pathology from these otherwise virulent pathogens (Brook and Dobson, 2015) . Bats leverage a suite of species-specific mechanisms to limit viral load, which include host receptor sequence incompatibilities for some bat-virus combinations (Ng et al., 2015; Takadate et al., 2020) and constitutive expression of the antiviral cytokine, IFN-a, for others (Zhou et al., 2016) . Typically, the presence of viral RNA or DNA in the cytoplasm of mammalian cells will induce secretion of type I interferon proteins (IFN-a and IFN-b), which promote expression and translation of interferon-stimulated genes (ISGs) in neighboring cells and render them effectively antiviral (Stetson and Medzhitov, 2006) . In some bat cells, the transcriptomic blueprints for this IFN response are expressed constitutively, even in the absence of stimulation by viral RNA or DNA (Zhou et al., 2016) . In non-flying mammals, constitutive IFN expression would likely elicit widespread inflammation and concomitant immunopathology upon viral infection, but bats support unique adaptations to combat inflammation (Zhang et al., 2013; Ahn et al., 2019; Xie et al., 2018; Pavlovich et al., 2018) that may have evolved to mitigate metabolic damage induced during flight (Kacprzyk et al., 2017) . The extent to which constitutive IFN-a expression signifies constitutive antiviral defense in the form of functional IFN-a protein remains unresolved. In bat cells constitutively expressing IFN-a, some protein-stimulated, downstream ISGs appear to be also constitutively expressed, but additional ISG induction is nonetheless possible following viral challenge and stimulation of IFN-b (Zhou et al., 2016; Xie et al., 2018) . Despite recent advances in molecular understanding of bat viral tolerance, the consequences of this unique bat immunity on within-host virus dynamics-and its implications for understanding zoonotic emergence-have yet to be elucidated.
The field of 'virus dynamics' was first developed to describe the mechanistic underpinnings of long-term patterns of steady-state viral load exhibited by patients in chronic phase infections with HIV, who appeared to produce and clear virus at equivalent rates (Nowak and May, 2000; Ho et al., 1995) . Models of simple target cell depletion, in which viral load is dictated by a bottom-eLife digest Bats can carry viruses that are deadly to other mammals without themselves showing serious symptoms. In fact, bats are natural reservoirs for viruses that have some of the highest fatality rates of any viruses that people acquire from wild animals -including rabies, Ebola and the SARS coronavirus.
Bats have a suite of antiviral defenses that keep the amount of virus in check. For example, some bats have an antiviral immune response called the interferon pathway perpetually switched on. In most other mammals, having such a hyper-vigilant immune response would cause harmful inflammation. Bats, however, have adapted anti-inflammatory traits that protect them from such harm, include the loss of certain genes that normally promote inflammation. However, no one has previously explored how these unique antiviral defenses of bats impact the viruses themselves. Now, Brook et al. have studied this exact question using bat cells grown in the laboratory. The experiments made use of cells from one bat species -the black flying fox -in which the interferon pathway is always on, and another -the Egyptian fruit bat -in which this pathway is only activated during an infection. The bat cells were infected with three different viruses, and then Brook et al. observed how the interferon pathway helped keep the infections in check, before creating a computer model of this response. The experiments and model helped reveal that the bats' defenses may have a potential downside for other animals, including humans. In both bat species, the strongest antiviral responses were countered by the virus spreading more quickly from cell to cell. This suggests that bat immune defenses may drive the evolution of faster transmitting viruses, and while bats are well protected from the harmful effects of their own prolific viruses, other creatures like humans are not.
The findings may help to explain why bats are often the source for viruses that are deadly in humans. Learning more about bats' antiviral defenses and how they drive virus evolution may help scientists develop better ways to predict, prevent or limit the spread of viruses from bats to humans. More studies are needed in bats to help these efforts. In the meantime, the experiments highlight the importance of warning people to avoid direct contact with wild bats. up resource supply of infection-susceptible host cells, were first developed for HIV (Perelson, 2002) but have since been applied to other chronic infections, including hepatitis-C virus (Neumann et al., 1998) , hepatitis-B virus (Nowak et al., 1996) and cytomegalovirus (Emery et al., 1999) . Recent work has adopted similar techniques to model the within-host dynamics of acute infections, such as influenza A and measles, inspiring debate over the extent to which explicit modeling of top-down immune control can improve inference beyond the basic resource limitation assumptions of the target cell model (Baccam et al., 2006; Pawelek et al., 2012; Saenz et al., 2010; Morris et al., 2018) .
To investigate the impact of unique bat immune processes on in vitro viral kinetics, we first undertook a series of virus infection experiments on bat cell lines expressing divergent interferon phenotypes, then developed a theoretical model elucidating the dynamics of within-host viral spread. We evaluated our theoretical model analytically independent of the data, then fit the model to data recovered from in vitro experimental trials in order to estimate rates of within-host virus transmission and cellular progression to antiviral status under diverse assumptions of absent, induced, and constitutive immunity. Finally, we confirmed our findings in spatially-explicit stochastic simulations of fitted time series from our mean field model. We hypothesized that top-down immune processes would overrule classical resource-limitation in bat cell lines described as constitutively antiviral in the literature, offering a testable prediction for models fit to empirical data. We further predicted that the most robust antiviral responses would be associated with the most rapid within-host virus propagation rates but also protect cells against virus-induced mortality to support the longest enduring infections in tissue culture.
We first explored the influence of innate immune phenotype on within-host viral propagation in a series of infection experiments in cell culture. We conducted plaque assays on six-well plate monolayers of three immortalized mammalian kidney cell lines: [1] Vero (African green monkey) cells, which are IFN-defective and thus limited in antiviral capacity (Desmyter et al., 1968) ; [2] RoNi/7.1 (Rousettus aegyptiacus) cells which demonstrate idiosyncratic induced interferon responses upon viral challenge (Kuzmin et al., 2017; Arnold et al., 2018; Biesold et al., 2011; Pavlovich et al., 2018) ; and [3] PaKiT01 (Pteropus alecto) cells which constitutively express IFN-a (Zhou et al., 2016; Crameri et al., 2009) . To intensify cell line-specific differences in constitutive immunity, we carried out infectivity assays with GFP-tagged, replication-competent vesicular stomatitis Indiana viruses: rVSV-G, rVSV-EBOV, and rVSV-MARV, which have been previously described (Miller et al., 2012; Wong et al., 2010) . Two of these viruses, rVSV-EBOV and rVSV-MARV, are recombinants for which cell entry is mediated by the glycoprotein of the bat-evolved filoviruses, Ebola (EBOV) and Marburg (MARV), thus allowing us to modulate the extent of structural, as well as immunological, antiviral defense at play in each infection. Previous work in this lab has demonstrated incompatibilities in the NPC1 filovirus receptor which render PaKiT01 cells refractory to infection with rVSV-MARV (Ng and Chandrab, 2018, Unpublished results) , making them structurally antiviral, over and above their constitutive expression of IFN-a. All three cell lines were challenged with all three viruses at two multiplicities of infection (MOI): 0.001 and 0.0001. Between 18 and 39 trials were run at each cell-virus-MOI combination, excepting rVSV-MARV infections on PaKiT01 cells at MOI = 0.001, for which only eight trials were run (see Materials and methods; Figure 1 -figure supplements 1-3, Supplementary file 1).
Because plaque assays restrict viral transmission neighbor-to-neighbor in two-dimensional cellular space (Howat et al., 2006) , we were able to track the spread of GFP-expressing virus-infected cells across tissue monolayers via inverted fluorescence microscopy. For each infection trial, we monitored and re-imaged plates for up to 200 hr of observations or until total monolayer destruction, processed resulting images, and generated a time series of the proportion of infectious-cell occupied plate space across the duration of each trial (see Materials and methods). We used generalized additive models to infer the time course of all cell culture replicates and construct the multi-trial dataset to which we eventually fit our mechanistic transmission model for each cell line-virus-specific combination ( Figure 1; Figure 1 -figure supplements 1-5).
All three recombinant vesicular stomatitis viruses (rVSV-G, rVSV-EBOV, and rVSV-MARV) infected Vero, RoNi/7.1, and PaKiT01 tissue cultures at both focal MOIs. Post-invasion, virus spread rapidly across most cell monolayers, resulting in virus-induced epidemic extinction. Epidemics were less severe in bat cell cultures, especially when infected with the recombinant filoviruses, rVSV-EBOV and rVSV-MARV. Monolayer destruction was avoided in the case of rVSV-EBOV and rVSV-MARV infections on PaKiT01 cells: in the former, persistent viral infection was maintained throughout the 200 hr duration of each experiment, while, in the latter, infection was eliminated early in the time series, preserving a large proportion of live, uninfectious cells across the duration of the experiment. We assumed this pattern to be the result of immune-mediated epidemic extinction (Figure 1) . Patterns from MOI = 0.001 were largely recapitulated at MOI = 0.0001, though at somewhat reduced total proportions (Figure 1-figure supplement 5 ).
A theoretical model fit to in vitro data recapitulates expected immune phenotypes for bat cells We next developed a within-host model to fit to these data to elucidate the effects of induced and constitutive immunity on the dynamics of viral spread in host tissue ( Figure 1 ). The compartmental within-host system mimicked our two-dimensional cell culture monolayer, with cells occupying five distinct infection states: susceptible (S), antiviral (A), exposed (E), infectious (I), and dead (D). We modeled exposed cells as infected but not yet infectious, capturing the 'eclipse phase' of viral integration into a host cell which precedes viral replication. Antiviral cells were immune to viral infection, in accordance with the 'antiviral state' induced from interferon stimulation of ISGs in tissues adjacent to infection (Stetson and Medzhitov, 2006) . Because we aimed to translate available data into modeled processes, we did not explicitly model interferon dynamics but instead scaled the rate of cell progression from susceptible to antiviral (r) by the proportion of exposed cells (globally) in the system. In systems permitting constitutive immunity, a second rate of cellular acquisition of antiviral status (") additionally scaled with the global proportion of susceptible cells in the model. Compared with virus, IFN particles are small and highly diffusive, justifying this global signaling assumption at the limited spatial extent of a six-well plate and maintaining consistency with previous modeling approximations of IFN signaling in plaque assay (Howat et al., 2006) .
To best represent our empirical monolayer system, we expressed our state variables as proportions (P S , P A , P E , P I , and P D ), under assumptions of frequency-dependent transmission in a wellmixed population (Keeling and Rohani, 2008) , though note that the inclusion of P D (representing the proportion of dead space in the modeled tissue) had the functional effect of varying transmission with infectious cell density. This resulted in the following system of ordinary differential equations:
We defined 'induced immunity' as complete, modeling all cells as susceptible to viral invasion at disease-free equilibrium, with defenses induced subsequent to viral exposure through the term r. By contrast, we allowed the extent of constitutive immunity to vary across the parameter range of " > 0, defining a 'constitutive' system as one containing any antiviral cells at disease-free equilibrium. In fitting this model to tissue culture data, we independently estimated both r and "; as well as the cell-to-cell transmission rate, b, for each cell-virus combination. Since the extent to which constitutively-expressed IFN-a is constitutively translated into functional protein is not yet known for bat hosts (Zhou et al., 2016) , this approach permitted our tissue culture data to drive modeling inference: even in PaKiT01 cell lines known to constitutively express IFN-a, the true constitutive extent of the system (i.e. the quantity of antiviral cells present at disease-free equilibrium) was allowed to vary through estimation of ": For the purposes of model-fitting, we fixed the value of c, the return rate of antiviral cells to susceptible status, at 0. The small spatial scale and short time course (max 200 hours) of our experiments likely prohibited any return of antiviral cells to susceptible status in our empirical system; nonetheless, we retained the term c in analytical evaluations of our model because regression from antiviral to susceptible status is possible over long time periods in vitro and at the scale of a complete organism (Radke et al., 1974; Rasmussen and Farley, 1975; Samuel and Knutson, 1982) .
Before fitting to empirical time series, we undertook bifurcation analysis of our theoretical model and generated testable hypotheses on the basis of model outcomes. From our within-host model system (Equation 1-5), we derived the following expression for R 0 , the pathogen basic reproduction number (Supplementary file 2):
Pathogens can invade a host tissue culture when R 0 >1. Rapid rates of constitutive antiviral acquisition (") will drive R 0 <1: tissue cultures with highly constitutive antiviral immunity will be therefore resistant to virus invasion from the outset. Since, by definition, induced immunity is stimulated following initial virus invasion, the rate of induced antiviral acquisition (r) is not incorporated into the equation for R 0 ; while induced immune processes can control virus after initial invasion, they cannot prevent it from occurring to begin with. In cases of fully induced or absent immunity (" ¼ 0), the R 0 equation thus reduces to a form typical of the classic SEIR model:
At equilibrium, the theoretical, mean field model demonstrates one of three infection states: endemic equilibrium, stable limit cycles, or no infection ( Figure 2) . Respectively, these states approximate the persistent infection, virus-induced epidemic extinction, and immune-mediated epidemic extinction phenotypes previously witnessed in tissue culture experiments ( Figure 1 ). Theoretically, endemic equilibrium is maintained when new infections are generated at the same rate at which infections are lost, while limit cycles represent parameter space under which infectious and susceptible populations are locked in predictable oscillations. Endemic equilibria resulting from cellular regeneration (i.e. births) have been described in vivo for HIV (Coffin, 1995) and in vitro for herpesvirus plaque assays (Howat et al., 2006) , but, because they so closely approach zero, true limit cycles likely only occur theoretically, instead yielding stochastic extinctions in empirical time series.
Bifurcation analysis of our mean field model revealed that regions of no infection (pathogen extinction) were bounded at lower threshold (Branch point) values for b, below which the pathogen was unable to invade. We found no upper threshold to invasion for b under any circumstances (i.e. b high enough to drive pathogen-induced extinction), but high b values resulted in Hopf bifurcations, which delineate regions of parameter space characterized by limit cycles. Since limit cycles so closely approach zero, high bs recovered in this range would likely produce virus-induced epidemic extinctions under experimental conditions. Under more robust representations of immunity, with higher values for either or both induced (r) and constitutive (") rates of antiviral acquisition, Hopf bifurcations occurred at increasingly higher values for b, meaning that persistent infections could establish at higher viral transmission rates ( Figure 2 ). Consistent with our derivation for R 0 , we found that the Branch point threshold for viral invasion was independent of changes to the induced immune parameter (r) but saturated at high values of " that characterize highly constitutive immunity ( Figure 3) .
We next fit our theoretical model by least squares to each cell line-virus combination, under absent, induced, and constitutive assumptions of immunity. In general, best fit models recapitulated expected outcomes based on the immune phenotype of the cell line in question, as described in the general literature (Table 1 Ironically, the induced immune model offered a slightly better fit than the constitutive to rVSV-MARV infections on the PaKiT01 cell line (the one cell line-virus combination for which we know a constitutively antiviral cell-receptor incompatibility to be at play). Because constitutive immune assumptions can prohibit pathogen invasion (R 0 <1), model fits to this time series under constitutive assumptions were handicapped by overestimations of ", which prohibited pathogen invasion. Only by incorporating an exceedingly rapid rate of induced antiviral acquisition could the model guarantee that initial infection would be permitted and then rapidly controlled. In all panel (A) plots, the rate of induced immune antiviral acquisition (r) was fixed at 0.01. Panel (B) depicts dynamics under variably induced immunity, ranging from absent (left: r=0) to high (right: r=1). In all panel (B) plots, the rate of constitutive antiviral acquisition (") was fixed at 0.0001 Branch point curves are represented as solid lines and Hopf curves as dashed lines. White space indicates endemic equilibrium (persistence), gray space indicates limit cycles, and black space indicates no infection (extinction). Other parameter values for equilibrium analysis were fixed at: b = .025, m = .001, s = 1/6, c = 0. Special points from bifurcations analyses are listed in Supplementary file 3.
In fitting our theoretical model to in vitro data, we estimated the within-host virus transmission rate (b) and the rate(s) of cellular acquisition to antiviral status (r or r + ") ( Table 1 ; Supplementary file 4). Under absent immune assumptions, r and " were fixed at 0 while b was estimated; under induced immune assumptions, " was fixed at 0 while r and b were estimated; and under constitutive immune assumptions, all three parameters (r, ", and b) were simultaneously estimated for each cell-virus combination. Best fit parameter estimates for MOI=0.001 data are visualized in conjunction with br and b -" bifurcations in (r) and (B) the constitutive immunity rate of antiviral acquisition ("). Panels show variation in the extent of immunity, from absent (left) to high (right). Branch point curves are represented as solid lines and Hopf curves as dashed lines. White space indicates endemic equilibrium (persistence), gray space indicates limit cycling, and black space indicates no infection (extinction). Other parameter values for equilibrium analysis were fixed at: b = .025, m = .001, s = 1/6, a = 1/6, c = 0. Special points from bifurcations analyses are listed in Supplementary file 3. space corresponding to theoretical limit cycles, consistent with observed virus-induced epidemic extinctions in stochastic tissue cultures.
In contrast to Vero cells, the induced immunity model offered the best fit to all RoNi/7.1 data, consistent with reported patterns in the literature and our own validation by qPCR ( Table 1; Arnold et al., 2018; Kuzmin et al., 2017; Biesold et al., 2011; Pavlovich et al., 2018) . As in Vero cell trials, we estimated highest b values for rVSV-G infections on RoNi/7.1 cell lines but here recovered higher b estimates for rVSV-MARV than for rVSV-EBOV. This reversal was balanced by a higher estimated rate of acquisition to antiviral status (r) for rVSV-EBOV versus rVSV-MARV. In general, we observed that more rapid rates of antiviral acquisition (either induced, r, constitutive, ", or both) correlated with higher transmission rates (b). When offset by r, b values estimated for RoNi/7.1 infections maintained the same amplitude as those estimated for immune-absent Vero cell lines but caused gentler epidemics and reduced cellular mortality (Figure 1) . RoNi/7.1 parameter estimates localized in the region corresponding to endemic equilibrium for the deterministic, theoretical model (Figure 4) , yielding less acute epidemics which nonetheless went extinct in stochastic experiments.
Finally, rVSV-G and rVSV-EBOV trials on PaKiT01 cells were best fit by models assuming constitutive immunity, while rVSV-MARV infections on PaKiT01 were matched equivalently by models assuming either induced or constitutive immunity-with induced models favored over constitutive in AIC comparisons because one fewer parameter was estimated (Figure 1-figure supplements 4-5; Supplementary file 4). For all virus infections, PaKiT01 cell lines yielded b estimates a full order of magnitude higher than Vero or RoNi/7.1 cells, with each b balanced by an immune response (either r, or r combined with ") also an order of magnitude higher than that recovered for the other cell lines ( Figure 4 ; Table 1 ). As in RoNi/7.1 cells, PaKiT01 parameter fits localized in the region corresponding to endemic equilibrium for the deterministic theoretical model. Because constitutive immune processes can actually prohibit initial pathogen invasion, constitutive immune fits to rVSV-MARV infections on PaKiT01 cell lines consistently localized at or below the Branch point threshold for virus invasion (R 0 ¼ 1). During model fitting for optimization of ", any parameter tests of " values producing R 0 <1 resulted in no infection and, consequently, produced an exceedingly poor fit to infectious time series data. In all model fits assuming constitutive immunity, across all cell lines, antiviral contributions from " prohibited virus from invading at all. The induced immune model thus produced a more parsimonious recapitulation of these data because virus invasion was always permitted, then rapidly controlled.
In order to compare the relative contributions of each cell line's disparate immune processes to epidemic dynamics, we next used our mean field parameter estimates to calculate the initial 'antiviral rate'-the initial accumulation rate of antiviral cells upon virus invasion for each cell-virus-MOI combination-based on the following equation:
where P E was calculated from the initial infectious dose (MOI) of each infection experiment and P S was estimated at disease-free equilibrium:
Because and " both contribute to this initial antiviral rate, induced and constitutive immune assumptions are capable of yielding equally rapid rates, depending on parameter fits. Indeed, under fully induced immune assumptions, the induced antiviral acquisition rate (r) estimated for rVSV-MARV infection on PaKiT01 cells was so high that the initial antiviral rate exceeded even that estimated under constitutive assumptions for this cell-virus combination (Supplementary file 4) . In reality, we know that NPC1 receptor incompatibilities make PaKiT01 cell lines constitutively refractory to rVSV-MARV infection (Ng and Chandrab, 2018, Unpublished results) and that PaKiT01 cells also constitutively express the antiviral cytokine, IFN-a. Model fitting results suggest that this constitutive expression of IFN-a may act more as a rapidly inducible immune response following virus invasion than as a constitutive secretion of functional IFN-a protein. Nonetheless, as hypothesized, PaKiT01 cell lines were by far the most antiviral of any in our study-with initial antiviral rates estimated several orders of magnitude higher than any others in our study, under either induced or constitutive assumptions ( Table 1 ; Supplementary file 4). RoNi/7.1 cells displayed the second-most-pronounced signature of immunity, followed by Vero cells, for which the initial antiviral rate was essentially zero even under forced assumptions of induced or constitutive immunity ( Table 1 ; Supplementary file 4).
Using fitted parameters for b and ", we additionally calculated R 0 , the basic reproduction number for the virus, for each cell line-virus-MOI combination ( Table 1 ; Supplementary file 4). We found that R 0 was essentially unchanged across differing immune assumptions for RoNi/7.1 and Vero cells, for which the initial antiviral rate was low. In the case of PaKiT01 cells, a high initial antiviral rate under either induced or constitutive immunity resulted in a correspondingly high estimation of b (and, consequently, R 0 ) which still produced the same epidemic curve that resulted from the much lower estimates for b and R 0 paired with absent immunity. These findings suggest that antiviral immune responses protect host tissues against virus-induced cell mortality and may facilitate the establishment of more rapid within-host transmission rates.
Total monolayer destruction occurred in all cell-virus combinations excepting rVSV-EBOV infections on RoNi/7.1 cells and rVSV-EBOV and rVSV-MARV infections on PaKiT01 cells. Monolayer destruction corresponded to susceptible cell depletion and epidemic turnover where R-effective (the product of R 0 and the proportion susceptible) was reduced below one ( Figure 5) . For rVSV-EBOV infections on RoNi/7.1, induced antiviral cells safeguarded remnant live cells, which birthed new susceptible cells late in the time series. In rVSV-EBOV and rVSV-MARV infections on PaKiT01 cells, this antiviral protection halted the epidemic ( Figure 5 ; R-effective <1) before susceptibles fully declined. In the case of rVSV-EBOV on PaKiT01, the birth of new susceptibles from remnant live cells protected by antiviral status maintained late-stage transmission to facilitate long-term epidemic persistence. Importantly, under fixed parameter values for the infection incubation rate (s) and infectioninduced mortality rate (a), models were unable to reproduce the longer-term infectious time series captured in data from rVSV-EBOV infections on PaKiT01 cell lines without incorporation of cell births, an assumption adopted in previous modeling representations of IFN-mediated viral dynamics in tissue culture (Howat et al., 2006) . In our experiments, we observed that cellular reproduction took place as plaque assays achieved confluency. Finally, because the protective effect of antiviral cells is more clearly observable spatially, we confirmed our results by simulating fitted time series in a spatially-explicit, stochastic reconstruction of our mean field model. In spatial simulations, rates of antiviral acquisition were fixed at fitted values for r and " derived from mean field estimates, while transmission rates (b) were fixed at values ten times greater than those estimated under mean field conditions, accounting for the intensification of parameter thresholds permitting pathogen invasion in local spatial interactions (see Materials and methods; Videos 1-3; Figure 5-figure supplement 3; Supplementary file 5; Webb et al., 2007) . In immune capable time series, spatial antiviral cells acted as 'refugia' which protected live cells from infection as each initial epidemic wave 'washed' across a cell monolayer. Eventual birth of new susceptibles from these living refugia allowed for sustained epidemic transmission in cases where some infectious cells persisted at later timepoints in simulation (Videos 1-3; Figure 5-figure supplement 3 ).
Bats are reservoirs for several important emerging zoonoses but appear not to experience disease from otherwise virulent viral pathogens. Though the molecular biological literature has made great progress in elucidating the mechanisms by which bats tolerate viral infections (Zhou et al., 2016; Ahn et al., 2019; Xie et al., 2018; Pavlovich et al., 2018; Zhang et al., 2013) , the impact of unique bat immunity on virus dynamics within-host has not been well-elucidated. We used an innovative combination of in vitro experimentation and within-host modeling to explore the impact of unique bat immunity on virus dynamics. Critically, we found that bat cell lines demonstrated a signature of enhanced interferon-mediated immune response, of either constitutive or induced form, which allowed for establishment of rapid within-host, cell-to-cell virus transmission rates (b). These results were supported by both data-independent bifurcation analysis of our mean field theoretical model, as well as fitting of this model to viral infection time series established in bat cell culture. Additionally, we demonstrated that the antiviral state induced by the interferon pathway protects live cells from mortality in tissue culture, resulting in in vitro epidemics of extended duration that enhance the probability of establishing a long-term persistent infection. Our findings suggest that viruses evolved in bat reservoirs possessing enhanced IFN capabilities could achieve more rapid within-host transmission rates without causing pathology to their hosts. Such rapidly-reproducing viruses would likely generate extreme virulence upon spillover to hosts lacking similar immune capacities to bats.
To achieve these results, we first developed a novel, within-host, theoretical model elucidating the effects of unique bat immunity, then undertook bifurcation analysis of the model's equilibrium properties under immune absent, induced, and constitutive assumptions. We considered a cell line to be constitutively immune if possessing any number of antiviral cells at disease-free equilibrium but allowed the extent of constitutive immunity to vary across the parameter range for ", the constitutive rate of antiviral acquisition. In deriving the equation for R 0 , the basic reproduction number, which defines threshold conditions for virus invasion of a tissue (R 0 >1), we demonstrated how the invasion threshold is elevated at high values of constitutive antiviral acquisition, ". Constitutive immune processes can thus prohibit pathogen invasion, while induced responses, by definition, can only control infections post-hoc. Once thresholds for pathogen invasion have been met, assumptions of constitutive immunity will limit the cellular mortality (virulence) incurred at high transmission rates. Regardless of mechanism (induced or constitutive), interferon-stimulated antiviral cells appear to play a key role in maintaining longer term or persistent infections by safeguarding susceptible cells from rapid infection and concomitant cell death. Fitting of our model to in vitro data supported expected immune phenotypes for different bat cell lines as described in the literature. Simple target cell models that ignore the effects of immunity best recapitulated infectious time series derived from IFN-deficient Vero cells, while models assuming induced immune processes most accurately reproduced trials derived from RoNi/7.1 (Rousettus aegyptiacus) cells, which possess a standard virusinduced IFN-response. In most cases, models assuming constitutive immune processes best recreated virus epidemics produced on PaKiT01 (Pteropus alecto) cells, which are known to constitutively express the antiviral cytokine, IFN-a (Zhou et al., 2016) . Model support for induced immune assumptions in fits to rVSV-MARV infections on PaKiT01 cells suggests that the constitutive IFN-a expression characteristic of P. alecto cells may represent more of a constitutive immune priming process than a perpetual, functional, antiviral defense. Results from mean field model fitting were additionally confirmed in spatially explicit stochastic simulations of each time series.
As previously demonstrated in within-host models for HIV (Coffin, 1995; Perelson et al., 1996; Nowak et al., 1995; Bonhoeffer et al., 1997; Ho et al., 1995) , assumptions of simple target-cell depletion can often provide satisfactory approximations of viral dynamics, especially those reproduced in simple in vitro systems. Critically, our model fitting emphasizes the need for incorporation of top-down effects of immune control in order to accurately reproduce infectious time series derived from bat cell tissue cultures, especially those resulting from the robustly antiviral PaKiT01 P. alecto cell line. These findings indicate that enhanced IFN-mediated immune pathways in bat reservoirs may promote elevated within-host virus replication rates prior to cross-species emergence. We nonetheless acknowledge the limitations imposed by in vitro experiments in tissue culture, especially involving recombinant viruses and immortalized cell lines. Future work should extend these cell culture studies to include measurements of multiple state variables (i.e. antiviral cells) to enhance epidemiological inference.
The continued recurrence of Ebola epidemics across central Africa highlights the importance of understanding bats' roles as reservoirs for virulent zoonotic disease. The past decade has born witness to emerging consensus regarding the unique pathways by which bats resist and tolerate highly virulent infections (Brook and Dobson, 2015; Xie et al., 2018; Zhang et al., 2013; Ahn et al., 2019; Zhou et al., 2016; Ng et al., 2015; Pavlovich et al., 2018) . Nonetheless, an understanding of the mechanisms by which bats support endemic pathogens at the population level, or promote the evolution of virulent pathogens at the individual level, remains elusive. Endemic maintenance of infection is a defining characteristic of a pathogen reservoir (Haydon et al., 2002) , and bats appear to merit such a title, supporting long-term persistence of highly transmissible viral infections in isolated island populations well below expected critical community sizes (Peel et al., 2012) . Researchers debate the relative influence of population-level and within-host mechanisms which might explain these trends (Plowright et al., 2016) , but increasingly, field data are difficult to reconcile without acknowledgement of a role for persistent infections (Peel et al., 2018; Brook et al., 2019) . We present general methods to study cross-scale viral dynamics, which suggest that within-host persistence is supported by robust antiviral responses characteristic of bat immune processes. Viruses which evolve rapid replication rates under these robust antiviral defenses may pose the greatest hazard for cross-species pathogen emergence into spillover hosts with immune systems that differ from those unique to bats.
All experiments were carried out on three immortalized mammalian kidney cell lines: Vero (African green monkey), RoNi/7.1 (Rousettus aegyptiacus) (Kühl et al., 2011; Biesold et al., 2011) and PaKiT01 (Pteropus alecto) (Crameri et al., 2009) . The species identifications of all bat cell lines was confirmed morphologically and genetically in the publications in which they were originally described (Kühl et al., 2011; Biesold et al., 2011; Crameri et al., 2009) . Vero cells were obtained from ATCC.
Monolayers of each cell line were grown to 90% confluency (~9Â10 5 cells) in 6-well plates. Cells were maintained in a humidified 37˚C, 5% CO 2 incubator and cultured in Dulbecco's modified Eagle medium (DMEM) (Life Technologies, Grand Island, NY), supplemented with 2% fetal bovine serum (FBS) (Gemini Bio Products, West Sacramento, CA), and 1% penicillin-streptomycin (Life Technologies). Cells were tested monthly for mycoplasma contamination while experiments were taking place; all cells assayed negative for contamination at every testing.
Previous work has demonstrated that all cell lines used are capable of mounting a type I IFN response upon viral challenge, with the exception of Vero cells, which possess an IFN-b deficiency (Desmyter et al., 1968; Rhim et al., 1969; Emeny and Morgan, 1979) . RoNi/7.1 cells have been shown to mount idiosyncratic induced IFN defenses upon viral infection (Pavlovich et al., 2018; Kuzmin et al., 2017; Arnold et al., 2018; Kühl et al., 2011; Biesold et al., 2011) , while PaKiT01 cells are known to constitutively express the antiviral cytokine, IFN-a (Zhou et al., 2016) . This work is the first documentation of IFN signaling induced upon challenge with the particular recombinant VSVs outlined below. We verified known antiviral immune phenotypes via qPCR. Results were consistent with the literature, indicating a less pronounced role for interferon defense against viral infection in RoNi/7.1 versus PaKiT01 cells.
Replication-capable recombinant vesicular stomatitis Indiana viruses, expressing filovirus glycoproteins in place of wild type G (rVSV-G, rVSV-EBOV, and rVSV-MARV) have been previously described (Wong et al., 2010; Miller et al., 2012) . Viruses were selected to represent a broad range of anticipated antiviral responses from host cells, based on a range of past evolutionary histories between the virus glycoprotein mediating cell entry and the host cell's entry receptor. These interactions ranged from the total absence of evolutionary history in the case of rVSV-G infections on all cell lines to a known receptor-level cell entry incompatibility in the case of rVSV-MARV infections on PaKiT01 cell lines.
To measure infectivities of rVSVs on each of the cell lines outlined above, so as to calculate the correct viral dose for each MOI, NH 4 Cl (20 mM) was added to infected cell cultures at 1-2 hr postinfection to block viral spread, and individual eGFP-positive cells were manually counted at 12-14 hr post-infection.
Previously published work indicates that immortalized kidney cell lines of Rousettus aegyptiacus (RoNi/7.1) and Pteropus alecto (PaKiT01) exhibit different innate antiviral immune phenotypes through, respectively, induced (Biesold et al., 2011; Pavlovich et al., 2018; Kühl et al., 2011; Arnold et al., 2018) and constitutive (Zhou et al., 2016 ) expression of type I interferon genes. We verified these published phenotypes on our own cell lines infected with rVSV-G, rVSV-EBOV, and rVSV-MARV via qPCR of IFN-a and IFN-b genes across a longitudinal time series of infection.
Specifically, we carried out multiple time series of infection of each cell line with each of the viruses described above, under mock infection conditions and at MOIs of 0.0001 and 0.001-with the exception of rVSV-MARV on PaKiT01 cell lines, for which infection was only performed at MOI = 0.0001 due to limited viral stocks and the extremely low infectivity of this virus on this cell line (thus requiring high viral loads for initial infection). All experiments were run in duplicate on 6well plates, such that a typical plate for any of the three viruses had two control (mock) wells, two MOI = 0.0001 wells and two MOI = 0.001 wells, excepting PaKiT01 plates, which had two control and four MOI = 0.0001 wells at a given time. We justify this PaKiT01 exemption through the expectation that IFN-a expression is constitutive for these cells, and by the assumption that any expression exhibited at the lower MOI should also be present at the higher MOI.
For these gene expression time series, four 6-well plates for each cell line-virus combination were incubated with virus for one hour at 37˚C. Following incubation, virus was aspirated off, and cell monolayers were washed in PBS, then covered with an agar plaque assay overlay to mimic conditions under which infection trials were run. Plates were then harvested sequentially at timepoints of roughly 5, 10, 15, and 20 hr post-infection (exact timing varied as multiple trials were running simultaneously). Upon harvest of each plate, agar overlay was removed, and virus was lysed and RNA extracted from cells using the Zymo Quick RNA Mini Prep kit, according to the manufacturer's instructions and including the step for cellular DNA digestion. Post-extraction, RNA quality was verified via nanodrop, and RNA was converted to cDNA using the Invitrogen Superscript III cDNA synthesis kit, according to the manufacturer's instructions. cDNA was then stored at 4˚C and as a frozen stock at À20˚C to await qPCR.
We undertook qPCR of cDNA to assess expression of the type I interferon genes, IFN-a and IFNb, and the housekeeping gene, b-Actin, using primers previously reported in the literature (Supplementary file 6) . For qPCR, 2 ml of each cDNA sample was incubated with 7 ml of deionized water, 1 ml of 5 UM forward/reverse primer mix and 10 ml of iTaq Universal SYBR Green, then cycled on a QuantStudio3 Real-Time PCR machine under the following conditions: initial denaturation at 94 C for 2 min followed by 40 cycles of: denaturation at 95˚C (5 s), annealing at 58˚C (15 s), and extension at 72˚C (10 s).
We report simple d-Ct values for each run, with raw Ct of the target gene of interest (IFN-a or IFN-b) subtracted from raw Ct of the b-Actin housekeeping gene in Figure 1 -figure supplement 6. Calculation of fold change upon viral infection in comparison to mock using the d-d-Ct method (Livak and Schmittgen, 2001) was inappropriate in this case, as we wished to demonstrate constitutive expression of IFN-a in PaKiT01 cells, whereby data from mock cells was identical to that produced from infected cells.
After being grown to~90% confluency, cells were incubated with pelleted rVSVs expressing eGFP (rVSV-G, rVSV-EBOV, rVSV-MARV). Cell lines were challenged with both a low (0.0001) and high (0.001) multiplicity of infection (MOI) for each virus. In a cell monolayer infected at a given MOI (m), the proportion of cells (P), infected by k viral particles can be described by the Poisson distribution: P k ð Þ ¼ e Àm m k k! , such that the number of initially infected cells in an experiment equals: 1 À e Àm . We assumed that a~90% confluent culture at each trial's origin was comprised of~9x10 5 cells and conducted all experiments at MOIs of 0.0001 and 0.001, meaning that we began each trial by introducing virus to, respectively,~81 or 810 cells, representing the state variable 'E' in our theoretical model. Low MOIs were selected to best approximate the dynamics of mean field infection and limit artifacts of spatial structuring, such as premature epidemic extinction when growing plaques collide with plate walls in cell culture.
Six-well plates were prepared with each infection in duplicate or triplicate, such that a control well (no virus) and 2-3 wells each at MOI 0.001 and 0.0001 were incubated simultaneously on the same plate. In total, we ran between 18 and 39 trials at each cell-virus-MOI combination, excepting r-VSV-MARV infections on PaKiT01 cells at MOI = 0.001, for which we ran only eight trials due to the low infectivity of this virus on this cell line, which required high viral loads for initial infection. Cells were incubated with virus for one hour at 37˚C. Following incubation, virus was aspirated off, and cell monolayers were washed in PBS, then covered with a molten viscous overlay (50% 2X MEM/Lglutamine; 5% FBS; 3% HEPES; 42% agarose), cooled for 20 min, and re-incubated in their original humidified 37˚C, 5% CO 2 environment.
After application of the overlay, plates were monitored periodically using an inverted fluorescence microscope until the first signs of GFP expression were witnessed (~6-9.5 hr post-infection, depending on the cell line and virus under investigation). From that time forward, a square subset of the center of each well (comprised of either 64-or 36-subframes and corresponding to roughly 60% and 40% of the entire well space) was imaged periodically, using a CellInsight CX5 High Content Screening (HCS) Platform with a 4X air objective (ThermoFisher, Inc, Waltham, MA). Microscope settings were held standard across all trials, with exposure time fixed at 0.0006 s for each image. One color channel was imaged, such that images produced show GFP-expressing cells in white and non-GFP-expressing cells in black (Figure 1-figure supplement 1) .
Wells were photographed in rotation, as frequently as possible, from the onset of GFP expression until the time that the majority of cells in the well were surmised to be dead, GFP expression could no longer be detected, or early termination was desired to permit Hoechst staining.
In the case of PaKiT01 cells infected with rVSV-EBOV, where an apparently persistent infection established, the assay was terminated after 200+ hours (8+ days) of continuous observation. Upon termination of all trials, cells were fixed in formaldehyde (4% for 15 min), incubated with Hoechst stain (0.0005% for 15 min) (ThermoFisher, Inc, Waltham, MA), then imaged at 4X on the CellInsight CX5 High Content Screening (HCS) Platform. The machine was allowed to find optimal focus for each Hoechst stain image. One color channel was permitted such that images produced showed live nuclei in white and dead cells in black.
Hoechst stain colors cellular DNA, and viral infection is thought to interfere with the clarity of the stain (Dembowski and DeLuca, 2015) . As such, infection termination, cell fixation, and Hoechst staining enables generation of a rough time series of uninfectious live cells (i.e. susceptible + antiviral cells) to complement the images which produced time series of proportions infectious. Due to uncertainty over the exact epidemic state of Hoechst-stained cells (i.e. exposed but not yet infectious cells may still stain), we elected to fit our models only to the infectious time series derived from GFPexpressing images and used Hoechst stain images as a post hoc visual check on our fit only ( Figure 5 ; Figure 5 -figure supplements 1-2).
Images recovered from the time series above were processed into binary ('infectious' vs. 'non-infectious' or, for Hoechst-stained images, 'live' vs. 'dead') form using the EBImage package (Pau et al., 2010) in R version 3.6 for MacIntosh, after methods further detailed in Supplementary file 7. Binary images were then further processed into time series of infectious or, for Hoechst-stained images, live cells using a series of cell counting scripts. Because of logistical constraints (i.e. many plates of simultaneously running infection trials and only one available imaging microscope), the time course of imaging across the duration of each trial was quite variable. As such, we fitted a series of statistical models to our processed image data to reconstruct reliable values of the infectious proportion of each well per hour for each distinct trial in all cell line-virus-MOI combinations (Figure 1
To derive the expression for R 0 , the basic pathogen reproductive number in vitro, we used Next Generation Matrix (NGM) techniques (Diekmann et al., 1990; Heffernan et al., 2005) , employing Wolfram Mathematica (version 11.2) as an analytical tool. R 0 describes the number of new infections generated by an existing infection in a completely susceptible host population; a pathogen will invade a population when R 0 >1 (Supplementary file 2). We then analyzed stability properties of the system, exploring dynamics across a range of parameter spaces, using MatCont (version 2.2) (Dhooge et al., 2008) for Matlab (version R2018a) (Supplementary file 3).
The birth rate, b, and natural mortality rate, m, balance to yield a population-level growth rate, such that it is impossible to estimate both b and m simultaneously from total population size data alone. As such, we fixed b at. 025 and estimated m by fitting an infection-absent version of our mean field model to the susceptible time series derived via Hoechst staining of control wells for each of the three cell lines (Figure 1-figure supplement 7) . This yielded a natural mortality rate, m, corresponding to a lifespan of approximately 121, 191, and 84 hours, respectively, for Vero, RoNi/7.1, and PaKiT01 cell lines (Figure 1-figure supplement 7) . We then fixed the virus incubation rate, s, as the inverse of the shortest observed duration of time from initial infection to the observation of the first infectious cells via fluorescent microscope for all nine cell line -virus combinations (ranging 6 to 9.5 hours). We fixed a, the infection-induced mortality rate, at 1/6, an accepted standard for general viral kinetics (Howat et al., 2006) , and held c, the rate of antiviral cell regression to susceptible status, at 0 for the timespan (<200 hours) of the experimental cell line infection trials.
We estimated cell line-virus-MOI-specific values for b, r, and " by fitting the deterministic output of infectious proportions in our mean field model to the full suite of statistical outputs of all trials for each infected cell culture time series (Figure 1-figure supplements 2-3) . Fitting was performed by minimizing the sum of squared differences between the deterministic model output and cell linevirus-MOI-specific infectious proportion of the data at each timestep. We optimized parameters for MOI = 0.001 and 0.0001 simultaneously to leverage statistical power across the two datasets, estimating a different transmission rate, b, for trials run at each infectious dose but, where applicable, estimating the same rates of r and " across the two time series. We used the differential equation solver lsoda() in the R package deSolve (Soetaert et al., 2010) to obtain numerical solutions for the mean field model and carried out minimization using the 'Nelder-Mead' algorithm of the optim() function in base R. All model fits were conducted using consistent starting guesses for the parameters, b (b = 3), and where applicable, r (r = 0.001) and " (" = 0.001). In the case of failed fits or indefinite hessians, we generated a series of random guesses around the starting conditions and continued estimation until successful fits were achieved.
All eighteen cell line-virus-MOI combinations of data were fit by an immune absent (" = r = 0) version of the theoretical model and, subsequently, an induced immunity (" = 0; r >0) and constitutive immunity (" >0; r >0) version of the model. Finally, we compared fits across each cell line-virus-MOI combination via AIC. In calculating AIC, the number of fitted parameters in each model (k) varied across the immune phenotypes, with one parameter (b) estimated for absent immune assumptions, two (b and r) for induced immune assumptions, and three (b, r, and ") for constitutive immune assumptions. The sample size (n) corresponded to the number of discrete time steps across all empirical infectious trials to which the model was fitted for each cell-line virus combination. All fitting and model comparison scripts are freely available for download at the following FigShare repository: DOI: 10.6084/m9.figshare.8312807.
Finally, we verified all mean field fits in a spatial context, in order to more thoroughly elucidate the role of antiviral cells in each time series. We constructed our spatial model in C++ implemented in R using the packages Rcpp and RcppArmadillo (Eddelbuettel and Francois, 2011; Eddelbuettel and Sanderson, 2017) . Following Nagai and Honda (2001) and Howat et al. (2006) , we modeled this system on a two-dimensional hexagonal lattice, using a ten-minute epidemic timestep for cell state transitions. At the initialization of each simulation, we randomly assigned a duration of natural lifespan, incubation period, infectivity period, and time from antiviral to susceptible status to all cells in a theoretical monolayer. Parameter durations were drawn from a normal distribution centered at the inverse of the respective fixed rates of m, s, a, and c, as reported with our mean field model. Transitions involving the induced (r) and constitutive (") rates of antiviral acquisition were governed probabilistically and adjusted dynamically at each timestep based on the global environment. As such, we fixed these parameters at the same values estimated in the mean field model, and multiplied both r and " by the global proportion of, respectively, exposed and susceptible cells at a given timestep.
In contrast to antiviral acquisition rates, transitions involving the birth rate (b) and the transmission rate (b) occurred probabilistically based on each cell's local environment. The birth rate, b, was multiplied by the proportion of susceptible cells within a six-neighbor circumference of a focal dead cell, while b was multiplied by the proportion of infectious cells within a thirty-six neighbor vicinity of a focal susceptible cell, thus allowing viral transmission to extend beyond the immediate nearestneighbor boundaries of an infectious cell. To compensate for higher thresholds to cellular persistence and virus invasion which occur under local spatial conditions (Webb et al., 2007) , we increased the birth rate, b, and the cell-to-cell transmission rate, b, respectively, to six and ten times the values used in the mean field model (Supplementary file 4) . We derived these increases based on the assumption that births took place exclusively based on pairwise nearest-neighbor interactions (the six immediately adjacent cells to a focal dead cell), while viral transmission was locally concentrated but included a small (7.5%) global contribution, representing the thirty-six cell surrounding vicinity of a focal susceptible. We justify these increases and derive their origins further in Supplementary file 5.
We simulated ten stochastic spatial time series for all cell-virus combinations under all three immune assumptions at a population size of 10,000 cells and compared model output with data in . Transparent reporting form Data availability All data generated or analysed during this study are included in the manuscript and supporting files. All images and code used in this study have been made available for download at the following Figshare | What is an example of anti-viral defense in bats? | false | 2,730 | {
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"some bats have an antiviral immune response called the interferon pathway perpetually switched on"
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1,628 | Evidence for the Convergence Model: The Emergence of Highly Pathogenic Avian Influenza (H5N1) in Viet Nam
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4580613/
SHA: ee5b43d20a640664510cb7a540caaae4a8e19933
Authors: Saksena, Sumeet; Fox, Jefferson; Epprecht, Michael; Tran, Chinh C.; Nong, Duong H.; Spencer, James H.; Nguyen, Lam; Finucane, Melissa L.; Tran, Vien D.; Wilcox, Bruce A.
Date: 2015-09-23
DOI: 10.1371/journal.pone.0138138
License: cc-by
Abstract: Building on a series of ground breaking reviews that first defined and drew attention to emerging infectious diseases (EID), the ‘convergence model’ was proposed to explain the multifactorial causality of disease emergence. The model broadly hypothesizes disease emergence is driven by the co-incidence of genetic, physical environmental, ecological, and social factors. We developed and tested a model of the emergence of highly pathogenic avian influenza (HPAI) H5N1 based on suspected convergence factors that are mainly associated with land-use change. Building on previous geospatial statistical studies that identified natural and human risk factors associated with urbanization, we added new factors to test whether causal mechanisms and pathogenic landscapes could be more specifically identified. Our findings suggest that urbanization spatially combines risk factors to produce particular types of peri-urban landscapes with significantly higher HPAI H5N1 emergence risk. The work highlights that peri-urban areas of Viet Nam have higher levels of chicken densities, duck and geese flock size diversities, and fraction of land under rice or aquaculture than rural and urban areas. We also found that land-use diversity, a surrogate measure for potential mixing of host populations and other factors that likely influence viral transmission, significantly improves the model’s predictability. Similarly, landscapes where intensive and extensive forms of poultry production overlap were found at greater risk. These results support the convergence hypothesis in general and demonstrate the potential to improve EID prevention and control by combing geospatial monitoring of these factors along with pathogen surveillance programs.
Text: Two decades after the Institute of Medicine's seminal report [1] recognized novel and reemerging diseases as a new category of microbial threats, the perpetual and unexpected nature of the emergence of infectious diseases remains a challenge in spite of significant clinical and biomedical research advances [2] . Highly Pathogenic Avian Influenza (HPAI) (subtype H5N1) is the most significant newly emerging pandemic disease since HIV/AIDS. Its eruption in Southeast Asia in 2003-4 and subsequent spread globally to more than 60 countries fits the complex systems definition of "surprise" [3] . In this same year that IOM had published its final report on microbial threats which highlighted H5N1's successful containment in Hong Kong in 1997 [4] , massive outbreaks occurred in Southeast Asia where it remains endemic, along with Egypt's Nile Delta. Since 2003, HPAI H5N1 has killed millions of poultry in countries throughout Asia, Europe, and Africa, and 402 humans have died from it in sixteen countries according to WHO data as of January 2015. The threat of a pandemic resulting in millions of human cases worldwide remains a possibility [5] .
Lederberg et al. [1] first pointed to the multiplicity of factors driving disease emergence, which later were elaborated and described in terms of 'the convergence model' [6] . The model proposes emergence events are precipitated by the intensifying of biological, environmental, ecological, and socioeconomic drivers. Microbial "adaptation and change," along with "changing ecosystems" and "economic development and land use" form major themes. Joshua Lederberg, the major intellectual force behind the studies summed-up saying "Ecological instabilities arise from the ways we alter the physical and biological environment, the microbial and animal tenants (humans included) of these environments, and our interactions (including hygienic and therapeutic interventions) with the parasites" [6] .
Combining such disparate factors and associated concepts from biomedicine, ecology, and social sciences in a single framework remains elusive. One approach suggested has been to employ social-ecological systems theory that attempts to capture the behavior of so-called 'coupled natural-human systems', including the inevitable unexpected appearance of new diseases, themselves one of the "emerging properties" of complex adaptive systems (CAS) [7, 8] . The convergence model can be so adapted by incorporating the dynamics of urban, agricultural, and natural ecosystem transformations proposed with this framework. These associated multifaceted interactions including feedbacks that affect ecological communities, hosts and pathogen populations, are the proximate drivers of disease emergence.
The initial HPAI H5N1 outbreaks in Vietnam represent an ideal opportunity to adapt and test a CAS-convergence model. Emergence risk should be highest in the most rapidly transforming urban areas, peri-urban zones where mixes of urban-rural, modern-traditional land uses and poultry husbandry coincide most intensely. Specifically we hypothesized a positive association between the presence of HPAI outbreaks in poultry at the commune level and: 1) peri-urban areas, as defined by Saksena et al. [9] , 2) land-use diversity, and 3) co-location of intensive and extensive systems of poultry.
We used the presence or absence at the commune level of HPAI H5N1 outbreaks in poultry as the dependent variable. Vietnam experienced its first HPAI H5N1 outbreak in late 2003, since then, there have been five waves and sporadic outbreaks recorded over the years [10, 11] . We chose to study the first wave (Wave 1) that ended in February 2004 and the second wave (Wave 2) that occurred between December 2004 and April 2005. We used data from the Viet Nam 2006 Agricultural Census to develop an urbanicity classification that used data collected at a single point in time (2006) but across space (10,820 communes) to infer processes of change (urbanization, land-use diversification, and poultry intensification) [9] . The 58 provinces in Vietnam (not counting the 5 urban provinces that are governed centrally) are divided into rural districts, provincial towns, and provincial cities. Rural districts are further divided into communes (rural areas) and towns, and provincial towns and cities are divided into wards (urban subdistricts) and communes. A commune in Viet Nam is thus the third level administrative subdivision, consisting of villages/hamlets. For the purpose of simplicity we will henceforth use the term "commune" to refer to the smallest administrative unit whether it is a commune, town, or ward. We included risk factors documented in previous work. We also aimed to understand the differences, if any, in risk dynamics at different scales; comparing risks at the national scale to those at two sub-national agro-ecological zones. For this purpose we chose to study the Red River and Mekong River deltas, well known hot spots of the disease. Hence we conducted two sets of analyses (waves 1 and 2) for three places (nation, Red River Delta, and Mekong Delta) producing a total of 6 wave-place analyses. Data on outbreaks were obtained from the publicly available database of Viet Nam's Department of Animal Health. Given the highly complex dynamics of the epidemics and in keeping with recent methodological trends, we used multiple modeling approaches-parametric and non-parametric-with a focus on spatial analysis. We used both 'place' oriented models that can take into account variations in factors such as policies and administration as well as 'space' oriented models that recognize the importance of physical proximity in natural phenomenon [12] .
Very few empirical studies have attempted to determine whether urbanization is related to EID outbreaks or whether urbanization is associated primarily with other factors related to EID outbreaks. One immediate problem researchers face is defining what is rural, urban, and transitional (i.e., peri-urban). Some studies have used official administrative definitions of urban and rural areas, but this approach is limited in its bluntness [13] . Other studies prioritized human population density as a satisfactory surrogate [11, [14] [15] [16] [17] [18] [19] [20] , but this approach ignores the important fact that density is not a risk factor if it is accompanied by sufficient infrastructure to handle the population. Spencer [21] examined urbanization as a non-linear characteristic, using household-level variables such as water and sanitation services. He found evidence that increased diversity in water supply sources and sanitation infrastructure were associated with higher incidences of HPAI. These studies employed a limited definition of urbanization that lacked a well-defined characterization of peri-urbanization.
Still other studies have mapped the relative urban nature of a place, a broad concept that is often referred to as 'urbanicity' [22] [23] [24] [25] . While these studies show differences in the rural/ urban nature of communities across space and time, they have been limited to small-to medium-scale observational studies; and they have failed to distinguish between different levels of "ruralness". Perhaps the best known model of peri-urbanization is McGee's concept of desakota (Indonesian for "village-town") [26] . McGee identified six characteristics of desakota regions: 1) a large population of smallholder cultivators; 2) an increase in non-agricultural activities; 3) extreme fluidity and mobility of population; 4) a mixture of land uses, agriculture, cottage industries, suburban development; 5) increased participation of the female labor force; and 6) "grey-zones", where informal and illegal activities group [26] . Saksena et al. [9] built on McGee's desakota concepts and data from the 2006 Viet Nam Agricultural Census to establish an urbanicity classification. That study identified and mapped the 10,820 communes, the smallest administrative unit for which data are collected, as being rural, peri-urban, urban, or urban core. This project used the Saksena classification to assess associations between urbanicity classes, other risks factors, and HPAI outbreaks.
Researchers have estimated that almost 75% of zoonotic diseases are associated with landcover and land-use changes (LCLUC) [27, 28] . LCLUC such as peri-urbanization and agricultural diversification frequently result in more diverse and fragmented landscapes (number of land covers or land uses per unit of land). The importance of landscape pattern, including diversity and associated processes, which equate to host species' habitat size and distribution, and thus pathogen transmission dynamics is axiomatic though the specific mechanisms depend on the disease [29, 30] . Landscape fragmentation produces ecotones, defined as abrupt edges or transitions zones between different ecological systems, thought to facilitate disease emergence by increasing the intensity and frequency of contact between host species [31] Furthermore, fragmentation of natural habitat tends to interrupt and degrade natural processes, including interspecies interactions that regulate densities of otherwise opportunistic species that may serve as competent hosts [32] , although it is not clear if reduced species diversity necessarily increases pathogen transmission [33] . Rarely has research connected land-use diversification to final health endpoints in humans or livestock; this study attempts to link land-use diversity with HPAI H5N1 outbreaks.
Human populations in the rapidly urbanizing cities of the developing world require access to vegetables, fruits, meat, etc. typically produced elsewhere. As theorized by von Thünen in 1826 [34] , much of this demand is met by farms near cities [35] , many in areas undergoing processes of peri-urbanization [26] . Due to the globalization of poultry trade, large-scale chicken farms raising thousands of birds have expanded rapidly in Southeast Asia and compete with existing small backyard farmers [36] . Large, enterprise-scale (15,000-100,000 birds) operations are still rare in Viet Nam (only 33 communes have such a facility). On the other hand, domestic and multinational companies frequently contract farmers to raise between 2,000 and 15,000 birds.
Recent studies have examined the relative role of extensive (backyard) systems and intensive systems [15, [17] [18] [19] 37] . In much of Asia there is often a mix of commercial and backyard farming at any one location [36] . Experts have suggested that from a biosecurity perspective the co-location of extensive and intensive systems is a potential risk factor [38] . Intensive systems allow for virus evolution (e.g. Low Pathogenic Avian Influenza to HPAI) and transformation, while extensive systems allow for environmental persistence and circulation [39] . Previous studies of chicken populations as a risk factor have distinguished between production systems-native chickens, backyard chickens; flock density; commercial chickens, broilers and layers density, etc. [15, [17] [18] [19] 37] . In isolation, however, none of these number and/or density based poultry metrics adequately measures the extent of co-location of intensive and extensive systems in any given place. Intensive and extensive systems in Viet Nam have their own fairly well defined flock sizes. A diversity index of the relative number of intensive and extensive systems of poultry-raising can better estimate the effect of such co-location; this study attempts to link a livestock diversity index with the presence or absence of HPAI H5N1 outbreaks at the commune level.
This study investigated for the 10,820 communes of Viet Nam a wide suite of socio-economic, agricultural, climatic and ecological variables relevant to poultry management and the transmission and persistence of the HPAI virus. Many of these variables were identified based on earlier studies of HPAI (as reviewed in Gilbert and Pfeiffer [40] ). Three novel variables were included based on hypotheses generated by this project. All variables were measured or aggregated to the commune level. The novel variables were:
• Degree of urbanization: We used the urbanicity classification developed by Saksena et al. [9] to define the urban character of each commune. The classification framework is based on four characteristics: 1) percentage of households whose main income is from agriculture, aquaculture and forestry, 2) percentage of households with modern forms of toilets, 3) percentage of land under agriculture, aquaculture and forestry and 4) the Normalized Differentiated Vegetation Index (NDVI). The three-way classification enabled testing for non-linear and non-monotonous responses.
• Land-use diversity: We measured land-use diversity using the Gini-Simpson Diversity Index [41] . The Gini-Simpson Diversity Index is given by 1-λ, where λ equals the probability that two entities taken at random from the dataset of interest represent the same type. In situations with only one class (complete homogeneity) the Gini-Simpson index would have a value equal to zero. Such diversity indices have been used to measure land-use diversity [42] . We used the following five land-use classes: annual crops, perennial crops, forests, aquaculture and built-up land (including miscellaneous uses) for which data were collected in the 2006 Agricultural Census. The area under the last class was calculated as the difference between the total area and the sum of the first four classes.
The following variables are listed according to their role in disease introduction, transmission and persistence, though some of these factors may have multiple roles.
• Human population related transmission.
Human population density [11, 14-16, 18, 19, 44, 45] .
• Poultry trade and market.
Towns and cities were assumed to be active trading places [10, 18, 37, 44, 46] . So, the distance to the nearest town/city was used as indicator of poultry trade.
Trade is facilitated by access to transportation infrastructure [37, 47, 48] . So, the distance to the nearest a) national highway and b) provincial highway was used as indicator of transportation infrastructure.
• Disease introduction and amplification.
The densities of chicken were calculated based on commune area [15, 19, 37, 49] .
• Intermediate hosts.
Duck and geese densities were calculated using total commune area [11, 19, 49] .
As previous studies have shown a link between scavenging in rice fields by ducks and outbreaks, we also calculated duck density using only the area under rice.
• Agro-ecological and environmental risk factors.
Previous studies have shown that the extent of rice cultivation is a risk factor, mainly due its association with free ranging ducks acting as scavengers [10] . We used percentage of land under rice cultivation as a measure of extent.
Rice cropping intensity is also a known risk factor [11, 17, 37] . We used the mean number of rice crops per year as a measure of intensity.
The extent of aquaculture is a known risk factor [10] , possibly because water bodies offer routes for transmission and persistence of the virus. The percentage of land under aquaculture was used as a metric.
Proximity to water bodies increases the risk of outbreaks [47, [50] [51] [52] , possibly by increasing the chance of contact between wild water birds and domestic poultry. We measured the distance between the commune and the nearest: a) lake and b) river.
Climatic variables-annual mean temperature and annual precipitation-have been associated with significant changes in risk [48, 53] .
Elevation, which is associated with types of land cover and agriculture, has been shown to be a significant risk factor in Vietnam [10] .
Compound Topographical Index (CTI, also known as Topographical Wetness Index) is a measure of the tendency for water to pool. Studies in Thailand and elsewhere [54] have shown that the extent of surface water is a strong risk factor, possibly due to the role of water in long-range transmission and persistence of the virus. In the absence of reliable and inexpensive data on the extent of surface water we used CTI as a proxy. CTI has been used in Ecological Niche Models (ENM) of HPAI H5N1 [55, 56] . However, given the nature of ENM studies, the effect of CTI as a risk factor has been unknown so far. CTI has been used as a risk factor in the study of other infectious and non-infectious diseases [57] . Some studies have shown that at local scales, the slope of the terrain (a component of CTI) was significantly correlated with reservoir species dominance [58] . CTI is a function of both the slope and the upstream contributing area per unit width orthogonal to the flow direction. CTI is computed as follows: CTI = ln (A s / (tan (β)) where; A s = Area Value calculated as ((flow accumulation + 1) Ã (pixel area in m 2 )) and β is the slope expressed in radians [59] .
Though previous studies have indicated that Normalized Difference Vegetation Index (NDVI) is a risk factor [10, 20, 55, 60, 61], we did not include it explicitly in our models, as the urban classification index we used included NDVI [9] .
We obtained commune level data on HPAI H5N1 outbreaks from the publicly available database of the Department of Animal Health [10] . Viet Nam experienced its first major epidemic waves between December 2003 and February 2006 [10] . We chose to study the first wave (Wave 1) that ended in February 2004 and the second wave (Wave 2) that occurred between December 2004 and April 2005. In Wave 1, 21% of the communes and in Wave 2, 6% of the communes experienced outbreaks. We used data from the 1999 Population Census of Viet Nam to estimate human population per commune. We relied on data from two Agriculture Censuses of Viet Nam. This survey is conducted every five years covering all rural households and those peri-urban households that own farms. Thus about three-fourths of all of the country's households are included. The contents of the survey include number of households in major production activities, population, labor classified by sex, age, qualification, employment and major income source; agriculture, forestry and aquaculture land used by households classified by source, type, cultivation area for by crop type; and farming equipment by purpose. Commune level surveys include information on rural infrastructure, namely electricity, transportation, medical stations, schools; fresh water source, communication, markets, etc. Detailed economic data are collected for large farms. We used the 2006 Agriculture Census for most variables because the first three epidemic waves occurred between the Agricultural Censuses of 2001 and 2006 but were closer in time to the 2006 census [10] . However, for data on poultry numbers we used the 2001 Agriculture Census data set because between 1991 and 2003 the poultry population grew at an average rate of 7% annually. However, in 2004, after the first wave of the H5N1 epidemic, the poultry population fell 15%. Only by mid-2008 did the poultry population return close to pre-epidemic levels. Thus, we considered the poultry population data from the 2001 census to be more representative. We aggregated census household data to the commune level. A three-way classification of the rural-to-urban transition was based on a related study [9] .
Raster data on annual mean temperature and precipitation were obtained from the World-Clim database and converted to commune level data. The bioclimatic variables were compiled from the monthly temperature and precipitation values and interpolated to surfaces at 90m spatial resolution [62] . This public database provides data on the average climatic conditions of the period 1950-2000.
Elevation was generated from SRTM 90 meter Digital Elevation Models (DEM) acquired from the Consortium for Spatial Information (CGIAR-CSI). Compound Topographical Index (CTI) data were generated using the Geomorphometry and Gradient Metrics Toolbox for Arc-GIS 10.1.
Prior to risk factor analysis we cleaned the data by identifying illogical values for all variables and then either assigning a missing value to them or adjusting the values. Illogical values occurred mainly (less than 1% of the cases) for land-related variables such as percentage of commune land under a particular type of land use. Next we tested each variable for normality using the BestFit software (Palisade Corporation). Most of the variables were found to follow a log-normal distribution and a log-transform was used on them. We then examined the bi-variate correlations between all the risk factors (or their log-transform, as the case may be). Correlations were analyzed separately for each place. Certain risk factors were then eliminated from consideration when |r| ! 0.5 (r is the Pearson correlation coefficient). When two risk factors were highly correlated, we chose to include the one which had not been adequately studied explicitly in previously published risk models. Notably, we excluded a) elevation (correlated with human population density, chicken density, duck density, percentage land under paddy, annual temperature and compound topographical index), b) human population density (correlated with elevation and CTI), c) chicken density (only at national level, correlated with CTI), d) duck and goose density (correlated with elevation, chicken density, percentage land under paddy, land use diversity index and CTI), e) annual temperature (correlated with elevation and CTI) and f) cropping intensity (correlated with percentage land under paddy).
Considering the importance of spatial autocorrelation in such epidemics, we used two modeling approaches: 1) multi-level Generalized Linear Mixed Model (GLMM) and 2) Boosted Regression trees (BRT) [63, 64] with an autoregressive term [65] . GLMM is a 'place' oriented approach that is well suited to analyzing the effect of administrative groupings, while BRT is a 'space' oriented approach that accounts for the effects of physical proximity. We began by deriving an autoregressive term by averaging the presence/absence among a set of neighbors defined by the limit of autocorrelation, weighted by the inverse of the Euclidean distance [65] .
The limit of the autocorrelation of the response variable was obtained from the range of the spatial correlogram ρ (h) [66] . To determine which predictor variables to include in the two models, we conducted logistic regression modeling separately for each of them one by one but included the autoregressive term each time. We finally included only those variables whose coefficient had a significance value p 0.2 (in at least one wave-place combination) and we noted the sign of the coefficient. This choice of p value for screening risk factors is common in similar studies [15, 18, 45, 67] . We used a two-level GLMM (communes nested under districts) to take account of random effects for an area influenced by its neighbors, and thus, we studied the effect of spatial autocorrelation. We used robust standard errors for tests of fixed effects. Boosted regression trees, also known as stochastic gradient boosting, was performed to predict the probability of HPAI H5N1 occurrence and determine the relative influence of each risk factor to the HPAI H5N1 occurrence. This method was developed recently and applied widely for distribution prediction in various fields of ecology [63, 64] . It is widely used for species distribution modeling where only the sites of occurrence of the species are known [68] . The method has been applied in numerous studies for predicting the distribution of HPAI H5N1 disease [16, 51, [69] [70] [71] . BRT utilizes regression trees and boosting algorithms to fit several models and combines them for improving prediction by performing iterative loop throughout the model [63, 64] .
The advantage of BRT is that it applies stochastic processes that include probabilistic components to improve predictive performance. We used regression trees to select relevant predictor variables and boosting to improve accuracy in a single tree. The sequential process allows trees to be fitted iteratively through a forward stage-wise procedure in the boosting model. Two important parameters specified in the BRT model are learning rate (lr) and tree complexity (tc) to determine the number of trees for optimal prediction [63, 64] . In our model we used 10 sets of training and test points for cross-validation, a tree complexity of 5, a learning rate of 0.01, and a bag fraction of 0.5. Other advantages of BRT include its insensitivity to co-linearity and non-linear responses. However, for the sake of consistency with the GLMM method, we chose to eliminate predictors that were highly correlated with other predictors and to make log-transforms where needed. In the GLMM models we used p 0.05 to identify significant risk factors.
The predictive performances of the models were assessed by the area under the curve (AUC) of the receiver operation characteristic (ROC) curve. AUC is a measure of the overall fit of the model that varies from 0.5 (chance event) to 1.0 (perfect fit) [72] . A comparison of AUC with other accuracy metrics concluded that it is the most robust measure of model performance because it remained constant over a wide range of prevalence rates [73] . We used the corrected Akaike Information Criteria (AICc) to compare each GLMM model with and without its respective suite of fixed predictors.
We used SPSS version 21 (IBM Corp., New York, 2012) for GLMM and R version 3.1.0 (The R Foundation for Statistical Computing, 2014) for the BRT. For calculating the spatial correlogram we used the spdep package of R.
The fourteen predictor variables we modeled (see tables) were all found to be significantly associated with HPAI H5N1 outbreaks (p 0.2) in at least one wave-place combination based on univariate analysis (but including the autoregressive term) ( Table 1) . Land-use diversity, chicken density, poultry flock size diversity and distance to national highway were found to have significant associations across five of the six wave-place combinations.
power of the GLMM models, as measured by the AUC, is very good with AUC values ranging from 0.802 to 0.952 (Tables 2-7 ). The predictive power of the national models was higher than that of the delta models. The predictive power of the BRT models is good, with AUCs ranging from 0.737 to 0.914. The BRT models also had a better predictive power at the national level than at the delta level. These values are higher than those reported for Wave 1 (AUC = 0.69) and Wave 2 (AUC = 0.77) by Gilbert et al. [11] . Both Gilbert et al. [11] and this study found that at the national level the predictive performance for Wave 2 was higher than that for Wave 1. Wave 2 mainly affected the Mekong River Delta. Previous studies indicated the duck density was an important predictor [11] ; our results, however, indicated that the diversity of duck flock size was a more important predictor than duck density.
Both the GLMM and BRT models found annual precipitation to be a significant factor. The GLMM model indicated a negative association; similar to what was found by studies in China [51] and in the Red River Delta [53] . A global study of human cases also found occurrence to be higher under drier conditions [74] . Generally, the role of precipitation was found to be far more significant in the deltas than for the country as a whole.
The unadjusted Relative Risk (RR) of peri-urban areas in comparison with non-peri-urban areas was 1.41 and 1.60 for Waves 1 and 2, respectively. In terms of urbanicity, we found that chicken density, percentage of land under rice, percentage of land under aquaculture, flock size diversity for duck and geese, and the Compound Topographical Index (CTI) to be highest in peri-urban areas (Fig 1a-1e) . We also found that land-use diversity was higher in rural areas, but peri-urban areas had diversity levels only marginally lower (Fig 1f) . The urbanicity variable alone, however, was not found to be significantly associated with HPAI H5N1 in any place according to the GLMM model except for the urban level in Red River Delta for Wave 2 and in the Mekong River Delta for Wave 1. The BRT model ranked urbanicity as one of the least influential variables. Land-use diversity was found to be significantly associated with HPAI H5N1 in both waves for Viet Nam according to the GLMM model, but at the delta level the association was significant only for Wave 2 in the Mekong River Delta. The BRT model indicated that land-use diversity highly influenced HPAI H5N1 at the national level in Wave 2. For the remaining waveplace combinations land-use diversity had middle to below-middle rank of influence.
Both the GLMM and BRT models indicated that the diversity of chicken flock-size had a strong association with HPAI H5N1 for both waves at the national level. This was generally found to be true at the delta levels with some exceptions. The diversity of duck and goose flock size was also significantly associated with HPAI H5N1 in all places, but the associations were much stronger in Wave 2 than in Wave 1.
The GLMM model indicated that the CTI had a very strong association with HPAI H5N1 at the national level in both waves although this was not true in the two deltas. The CTI is a steady state wetness index commonly used to quantify topographic control on hydrological processes. Accumulation numbers in flat areas, like deltas, are very large; hence the CTI was not a relevant variable in the GLMM model in these areas. The BRT model however indicated that CTI had middle to low influence in all waves and places. We found very high spatial clustering effects as indicated by the fact that in all waves and places the BRT model found the spatial autocorrelation term to have the highest rank of influence. As expected, the relative influence of the autocorrelation term at the national level was higher (60-78%) than at the delta levels (14-35%). In the GLMM models we found the Akaike Information Criterion (AIC) using the entire set of 14 variables to be much lower than the AICs of a GLMM model without fixed effects. This indicated that though clustering effects were significant, our theory driven predictor variables improved model performance.
A limitation of using surveillance methods for the dependent variable (poultry outbreaks) is that the data may have reporting/detection biases [11] . Under-reporting/detection in rural areas as compared to peri-urban areas is possible. We believe that the urbanicity and the shortest distance to nearest town risk factors serve as rough proxies for reporting/detection efficiency. Previous studies have tended to use human population density as a proxy for this purpose. In our study we found a strong association between human population density and urbanicity. But we acknowledge that a categorical variable such as urbanicity may provide less sensitivity than a continuous variable such as human population density in this specific context.
This study explored the validity of a general model for disease emergence that combined the IOM 'convergence model' [6] and the social-ecological systems model [7, 8] , for investigating the specific case of HPAI in Vietnam. We sought to test the hypotheses that measures of urbanization, land-use diversification, and poultry intensification are correlated with outbreaks in poultry. Our results generally support the hypothesis that social-ecological system transformations are associated with H5NI outbreaks in poultry.
The results presented here highlight three main findings: 1) when relevant risk factors are taken into account, urbanization is generally not a significant independent risk factor; but in peri-urban landscapes emergence factors converge, including higher levels of chicken densities, duck and geese flock size diversities, and fraction of land under rice or aquaculture; 2) high land-use diversity landscapes, a variable not previously considered in spatial studies of HPAI H5N1, are at significantly greater risk for HPAI H5N1 outbreaks; as are 3) landscapes where intensive and extensive forms of poultry production are co-located.
Only one other study has explicitly examined urbanicity in the context of HPAI H5N1. Loth et al. [17] found peri-urban areas in Indonesia were significantly associated with HPAI H5N1 cases, even based on multivariate models. Our study, however, attempted both to associate HPAI H5N1 with degree of urbanicity and to determine the features of peri-urban areas that place them at risk. When those features (i.e., chicken densities, duck and geese flock size diversities, and the fraction of land under rice or aquaculture) are included in multivariate models, the role of the urbanization variable per se diminishes. We found in the main river deltas in Viet Nam (Red River and Mekong), urbanization had no significant association with HPAI H5N1. This may be due to the fact that the deltas are more homogenous, in terms of urbanization, than the country as a whole. This is the first study to examine land-use diversity as a risk factor for HPAI H5N1. Measured by the Gini-Simpson Diversity Index of the five land-use classes on which data were collected in the 2006 Viet Nam Agricultural Census, and the presence or absence of HPAI outbreaks at the commune level, our results indicate a strong association between land-use diversity and HPAI H5N1 at the national level and in the Mekong River Delta. This metric captures both the variety of habitats and of the complexity of geospatial patterning likely associated with transmission intensity. Our results are similar to what has been observed by studies of other EIDs using fragmentation metrics (e.g. [75] [76] [77] . This is one of the few studies, however, to link landscape fragmentation to an EID disease in poultry and not just to the vector and/or hosts of the EID.
Previous studies have focused on poultry production factors such as type of species, size of flocks, and extent of commercialization (e.g. [15, [17] [18] [19] . This study expands on those findings by providing evidence that when intensive and extensive systems of chicken and/or duck and geese production co-exist in the same commune, the commune experiences higher risk of disease outbreak. Future studies need to examine the biological causal mechanisms in this context.
We suggest that national census data (particularly agricultural censuses) compiled at local levels of administration provide valuable information that are not available from remotely sensed data (such as poultry densities) or require a large amount of labor to map at national to larger scales (land-use diversity). Mapping land-use classes at the national scale for local administrative units (i.e., the 10,820 communes in Viet Nam) is not an insignificant task. Future studies, however, could examine the correlation between a census-based metric with metrics derived from remote sensing used to measure proportional abundance of each landcover type within a landscape [78] . Vietnam is relatively advanced in making digital national population and agricultural census data available in a format that can be linked to administrative boundaries. While other nations are beginning to develop similar capacities, in the short term the application of this method to other countries may be limited. Ultimately, both census and remotely sensed data can be used independently to map the urban transition and diversity of land use; these tools, however, may provide their greatest insights when used together.
Another important contribution of this study was the discovery of the importance of CTI. So far CTI had been used only in ecological niche modeling studies of HPAI H5N1; the specific role and direction of influence of CTI had has so far been unknown. Our study, the first to use CTI as a risk factor, found it had a large positive influence on HPAI H5N1 risk at the national level. Previous studies have highlighted the role of surface water extent in the persistence and transmission of the HPAI H5N1 virus. These studies measured surface water extent as area covered by water, magnitude of seasonal flooding, distance to the nearest body of water, or other variables that are often difficult to map using remotely sensed data, especially for large area studies. CTI on the other hand has the potential to serve as an excellent surrogate which can easily be measured in a GIS database. The national and regional (delta) models differed quite considerably, both in terms of performance and significant risk factors. In the deltas we commonly found only chicken density, duck flock size diversity and annual precipitation to be significant. This suggests dynamics of risk at the commune level are strongly dependent on the spatial range of analysis, consistent with another study in the Mekong Delta [61] . Though that study's model initially included three dozen commonly known risk factors, the significant risk factors were limited to poultry flock density, proportion households with electricity, re-scaled NDVI median May-October, buffalo density and sweet potato yield. Another study in the Red River Delta [79] found that in addition to the typical poultry density metrics, only the presence of poultry traders was significant. We speculate that for smaller regions, especially for known hot-spots, the relevant risk factors are those that reflect short-range, short-term driving forces such as poultry trading, presence of live bird markets and wet markets etc. Improving model performance for smaller regions would require highly refined and nuanced metrics for poultry trading, road infrastructure, water bodies, etc.-data that are typically not available through census surveys. The differences between the national and regional models suggest that our results can inform planners making decisions at different hierarchical levels of jurisdiction: national, region and local.
Our study has the potential to inform the design of future research related to the epidemiology of other EIDs in Viet Nam and elsewhere. For example, we speculate that in Southeast Asia, Japanese encephalitis, the transmission of which is associated with rice cultivation and flood irrigation [80] , may also show a strong association with peri-urbanization. In some areas of Asia these ecological conditions occur near, or occasionally within, urban centers. Likewise, Hantaan virus, the cause of Korean hemorrhagic fever, is associated with the field mouse Apodemus agrarius and rice harvesting in fields where the rodents are present [80] . Our work has demonstrated that the percentage of land under rice in peri-urban areas and rural areas is similar. Hence diseases associated with rice production are likely to peak in peri-urban areas given other risk factors such as land-use diversity, CTI, and distance to infrastructure. Our poultry flock-size diversity findings may also be relevant to understanding the dynamics of other poultry related infections such as Newcastle disease. Finally, these results suggest the validity of a general model of zoonotic disease emergence that integrates IOM's convergence model with the subsequently proposed social-ecological systems and EID framework. Thus, convergence represents the coalescence in time and space of processes associated with land-cover and land-use changes. Project results question whether the urban/rural land-use dichotomy is useful when large areas and parts of the population are caught between the two. Planners need better tools for mapping the rural-urban transition, and for understanding how the specific nature of peri-urban environments creates elevated health risk that require adaptation of existing planning, land use, and development practices. | Where is the highest risk of HPAI H5N1 like disease emergence? | false | 589 | {
"text": [
"Emergence risk should be highest in the most rapidly transforming urban areas, peri-urban zones where mixes of urban-rural, modern-traditional land uses and poultry husbandry coincide most intensely."
],
"answer_start": [
5073
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} |
1,690 | Viruses and Evolution – Viruses First? A Personal Perspective
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6433886/
SHA: f3b9fc0f8e0a431366196d3e835e1ec368b379d1
Authors: Moelling, Karin; Broecker, Felix
Date: 2019-03-19
DOI: 10.3389/fmicb.2019.00523
License: cc-by
Abstract: The discovery of exoplanets within putative habitable zones revolutionized astrobiology in recent years. It stimulated interest in the question about the origin of life and its evolution. Here, we discuss what the roles of viruses might have been at the beginning of life and during evolution. Viruses are the most abundant biological entities on Earth. They are present everywhere, in our surrounding, the oceans, the soil and in every living being. Retroviruses contributed to about half of our genomic sequences and to the evolution of the mammalian placenta. Contemporary viruses reflect evolution ranging from the RNA world to the DNA-protein world. How far back can we trace their contribution? Earliest replicating and evolving entities are the ribozymes or viroids fulfilling several criteria of life. RNA can perform many aspects of life and influences our gene expression until today. The simplest structures with non-protein-coding information may represent models of life built on structural, not genetic information. Viruses today are obligatory parasites depending on host cells. Examples of how an independent lifestyle might have been lost include mitochondria, chloroplasts, Rickettsia and others, which used to be autonomous bacteria and became intracellular parasites or endosymbionts, thereby losing most of their genes. Even in vitro the loss of genes can be recapitulated all the way from coding to non-coding RNA. Furthermore, the giant viruses may indicate that there is no sharp border between living and non-living entities but an evolutionary continuum. Here, it is discussed how viruses can lose and gain genes, and that they are essential drivers of evolution. This discussion may stimulate the thinking about viruses as early possible forms of life. Apart from our view “viruses first”, there are others such as “proteins first” and “metabolism first.”
Text: Mycoplasma mycoides by systematic deletion of individual genes resulted in a synthetic minimal genome of 473 genes (Hutchison et al., 2016) . Can one consider simpler living entities?
There are elements with zero genes that fulfill many criteria for early life: ribozymes, catalytic RNAs closely related to viroids. They were recovered in vitro from 10 15 molecules (aptamers), 220 nucleotides in length, by 10 rounds of selection. Among the many RNA species present in this collection of quasispecies RNAs were catalytically active members, enzymatically active ribozymes. The sequence space for 220-mer RNAs is about 3 × 10 132 (Eigen, 1971; Wilson and Szostak, 1999; Brackett and Dieckmann, 2006) .
The selected ribozymes were able to replicate, cleave, join, and form peptide bonds. They can polymerize progeny chemically, allow for mutations to occur and can evolve. One molecule serves as catalyst, the other one as substrate. Replication of ribozymes was demonstrated in the test tube (Lincoln and Joyce, 2009) . Ribozymes can form peptide bonds between amino acids (Zhang and Cech, 1997) . Thus, small peptides were available by ribozyme activity. Consequently, an RNA modification has been proposed as peptide nucleic acid (PNA), with more stable peptide bonds instead of phosphodiester bonds (Zhang and Cech, 1997; Joyce, 2002) . Replication of RNA molecules can be performed chemically from RNA without polymerase enzymes. In addition, deoxyribozymes can form from ribonucleotides (Wilson and Szostak, 1999) . Thus, DNA can arise from RNA chemically, without the key protein enzyme, the reverse transcriptase.
An entire living world is possible from non-coding RNA (ncRNA) before evolution of the genetic code and protein enzymes. Ribozymes naturally consist of circular single-stranded RNAs (Orgel, 2004) . They lack the genetic triplet code and do not encode proteins. Instead, they exhibit structural information by hairpin-loops that form hydrogen bonds between incomplete double strands, and loops free to interact with other molecules. They represent a quasispecies in which many species of RNA may form, such as ribozymes, tRNA-like molecules, and other ncRNAs. RNAs within such a pool can bind amino acids. Ninety different amino acids have been identified on the Murchison meteorite found in Australia, while on Earth only about 20 of them are used for protein synthesis (Meierhenrich, 2008) . Where formation of ribozymes occurred on the early Earth is a matter of speculation. The hydrothermal vents such as black smokers in the deep ocean are possibilities where life may have started (Martin et al., 2008) . There, temperature gradients and clay containing minerals such as magnesium or manganese are available. Pores or niches offer possibilities for concentration of building blocks, which is required for chemical reactions to occur. Interestingly, also ice is a candidate for ribozyme formation and chemical reactions. Ice crystals displace the biomolecules into the liquid phase, which leads to concentration, creating a quasicellular compartmentalization where de novo synthesis of nucleotide precursors is promoted. There, RNA and ribozymes can emerge, which are capable of self-replication (Attwater et al., 2010) .
tRNA-amino acid complexes can find RNAs as "mRNAs." Such interactions could have contributed to the evolution of the genetic code. This sequence of events can lead to primitive ribosome precursors. Ribozymes are the essential catalytic elements in ribosomes: "The ribosome is a ribozyme" (Cech, 2000) , supplemented with about a hundred scaffold proteins later during evolution. The proteins have structural functions and contribute indirectly to enzymatic activity. Are these ribosomebound ribozymes fossils from the early Earth? Small peptides can be formed by ribozymes before ribosomes evolved, whereby single or dimeric amino acids may originate from the universe (Meierhenrich, 2008) .
Small peptides with basic amino acids can increase the catalytic activity of ribozymes as shown in vitro (Müller et al., 1994) . Such proteins are known as RNA-binding proteins from RNA viruses that protect the RNA genome, with motifs such as RAPRKKG of the nucleocapsid NCp7 of HIV (Schmalzbauer et al., 1996) . Peptides can enhance the catalytic activity of ribozymes up to a 100-fold (Müller et al., 1994) . Such peptides of RNA viruses serve as chaperones that remove higher ordered RNA structures, allowing for more efficient interaction of RNA molecules and increasing transcription rates of RNA polymerases (Müller et al., 1994) . Ribonucleoproteins may have also been functionally important during the evolution of ribosomes (Harish and Caetano-Anolles, 2012) .
These pre-ribosomal structures are also similar to precursorlike structures of retroviruses. Reverse transcription can be performed by ribozymes chemically. This action does not necessarily require a protein polymerase such as the reverse transcriptase. Similarly, deoxyribonucleotides can arise by removal of an oxygen without the need of a protein enzyme (a reductase) as today, and allow for DNA polymerization (Wilson and Szostak, 1999; Joyce, 2002) . The same elements of the precursors for ribosomes are also building blocks of retroviruses, which may have a similar evolutionary origin (Moelling, 2012 (Moelling, , 2013 . tRNAs serve as primers for the reverse transcriptase, and the sequence of promoters of transposable elements are derived from tRNAs (Lander et al., 2001) . The ribozymes developed into more complex self-cleaving group II introns with insertion of genes encoding a reverse transcriptase and additional proteins (Moelling and Broecker, 2015; Moelling et al., 2017) (Figure 1) .
It came as a surprise that the genomes of almost all species are rich in ncDNA, transcribed into ncRNAs but not encoding proteins, as evidenced, for instance, by the "Encyclopedia of DNA Elements" (ENCODE) project. ncDNA amounts to more than 98% of the human DNA genome (Deveson et al., 2017) . Higher organisms tend to have more non-coding information, which allows for more complex modes of gene regulation. The ncRNAs are regulators of the protein-coding sequences. Highly complex organisms such as humans typically have a high number of ncRNA and regulatory mechanisms. ncRNA can range from close to zero in the smallest bacteria such as Pelagibacter ubique to about 98% in the human genome.
RNA viruses such as the retrovirus HIV harbor ncRNAs for gene regulation such as the trans-activating response element (TAR), the binding site for the Tat protein for early viral gene expression. Tat has a highly basic domain comprising mostly Lys and Arg residues, resembling other RNA binding proteins. ncRNA also serves on viral RNA genomes as ribosomal entry sites, primer binding sites or packaging signals. DNA synthesis depends on RNA synthesis as initial event, with RNA primers as starters for DNA replication, inside of cells as FIGURE 1 | A compartment is shown with essential components of life as discussed in the text. Non-coding RNA (ncRNA), ribozymes or viroids, can perform many steps for life without protein-coding genes but only by structural information. Individual amino acids are indicated as black dots and may be available on Earth from the universe. DNA may have existed before retroviruses. The compartment can be interpreted as pre-virus or pre-cell. Viroid, green; RNA, red; DNA, black.
well as during retroviral replication, proving a requirement of RNA (Flint, 2015) .
The number of mammalian protein-coding genes is about 20,000. Surprisingly, this is only a fifth of the number of genes of bread wheat (Appels et al., 2018) . Tulips, maize and other plants also have larger genomes, indicating that the number of genes does not necessarily reflect the complexity of an organism. What makes these plant genomes so large, is still an open question. Could the giant genomes possibly be the result to breeding of plants by farmers or gardeners?
According to Szostak there are molecules which appear like relics from the RNA world such as acetyl-CoA or vitamin B12, both of which are bound to a ribonucleotide for no obvious reason -was it "forgotten" to be removed? (Roberts and Szostak, 1997; Szostak et al., 2001; Szostak, 2011) . Perhaps the connected RNA serves as structural stabilizer. Lipid vesicles could have formed the first compartments and enclosed ribozymes, tRNAs with selected amino acids, and RNA which became mRNA. Is this a pre-cell or pre-virus (Figure 1) ? Patel et al. (2015) demonstrated that the building blocks of life, ribonucleotides, lipids and amino acids, can be formed from C, H, O, P, N, S in a "one pot" synthesis. This study can be regarded as a follow-up study of the classical Urey-Miller in vitro synthesis of biomolecules (Miller, 1953; Miller and Urey, 1959) . Transition from the RNA to the DNA world was promoted by the formation of the reverse transcriptase. The enzyme was first described in retroviruses but it is almost ubiquitous and found in numerous cellular species, many of which with unknown functions (Simon and Zimmerly, 2008; Lescot et al., 2016) . It is an important link between the RNA and the DNA worlds. The name reverse transcriptase is historical and irritating because it is the "real" transcriptase during the transition from the RNA to the DNA world. Similarly, the ribonuclease H (RNase H) is an essential enzyme of retroviruses (Mölling et al., 1971) . The RNase H turned out to be one of the five most frequent and ancient proteins (Ma et al., 2008 ) that belongs to a superfamily of more than sixty different unique representatives and 152 families with numerous functions (Majorek et al., 2014) .
Some of the many tRNAs can become loaded with amino acids. There are viruses containing tRNA-like structures (TLS), resembling these early RNAs (Dreher, 2009) . The TLS of these viruses typically bind to a single amino acid. TLS-viruses include plant viruses, such as Turnip yellow mosaic virus, in Peanut clump virus, Tobacco mosaic virus (TMV), and Brome mosaic virus. Only half a tRNA is found in Narnaviruses of fungi. The amino acids known to be components of tRNA-like viruses are valine, histidine and tyrosine. The structures were also designated as "mimicry, " enhancing translation (Dreher, 2009 (Dreher, , 2010 . They look like "frozen" precursor-like elements for protein synthesis. This combination of a partial tRNA linked to one amino acid can be interpreted as an evolutionary early step toward protein synthesis, trapped in a viral element.
Ribozymes are related to the protein-free viroids. Viroids are virus-like elements that belong to the virosphere, the world of viruses (Chela-Flores, 1994) . Viroids lack protein coats and therefore were initially not designated as viruses but virus-like viroids when they were discovered in 1971 by Theodor Diener. He described viroids as "living fossils" (Diener, 2016) (Figure 2) .
From infected potatoes, Diener isolated the Potato spindle tuber viroid (PSTVd) whose genome was about a 100-fold smaller than those of viruses known at that time. The viroids known today are ranging from 246 to 467 nucleotides. They contain circular single-stranded RNA, are protein-free and self-replicating with no genetic information, but only structural FIGURE 2 | Viroids are hairpin-loop structures and are shown schematically and as electron micrograph. Viroids are, like ribozymes, without genetic information and play major biological roles today in plant diseases, in carnation flowers, in liver cancer, as catalyst of protein synthesis in ribosomes and as circular regulatory RNAs, as "sponges" for other regulatory RNAs.
information in the form of hairpin-loops (Riesner et al., 1979) . They can generate copies of themselves in the appropriate environment. They were designated as the "frontiers of life" (Flores et al., 2014) .
The knowledge of virus composition was based on TMV and its crystallization by Wendell Stanley in 1935 (Pennazio and Roggero, 2000) . The genome of TMV is protein-coding singlestranded RNA of about 6,400 nucleotides that is enclosed by a rod-like protein coat. Viroids, in contrast, do not encode proteins and lack coats but they are closely related to viruses. Viroids can lose their autonomy and rely on host RNA polymerases to replicate, are capable of infecting plants and many are economically important pathogens. There are two families, the nucleus-replicating Pospiviroidae such as PSTVd and the chloroplast-replicating Avsunviroidae like the Avocado sunblotch viroid (ASBVd). Their replication requires host enzymes. Thus, autonomy is replaced by dependence on host enzymes and an intracellular lifestyle.
Most viroids are often enzymatically active ribozymes -yet they are examples that this trait can get lost as a result of changing environmental conditions. Loss of ribozyme activity is a functional, not a genetic loss. Only the nuclear variants, the Pospiviroidae, can lose their ribozyme activity and use the cellular RNase III enzyme for their replication. In contrast, the Avsunviroidae are still active hammerhead ribozymes. Thus, inside the nucleus of a host cell, the enzymatic RNA function can become unnecessary. Not genes, but a function, the catalytic activity, gets lost.
Viroids did apparently not gain genes but cooperated for a more complex lifestyle. For example, Carnation small viroid-like RNA (CarSV RNA) cooperates with a retrovirus and is accompanied by a homologous DNA generated by a reverse transcriptase. This enzyme presumably originates from a pararetrovirus of plants. Pararetroviruses package virus particles at a different stage during replication than retroviruses, the DNA, not the RNA. This unique combination between two viral elements has so far only been detected with CarSV in carnation flowers (Flores et al., 2005 (Flores et al., , 2014 . Why did such a cooperation evolve -perhaps by breeding gardeners? RNA is sensitive to degradation; therefore, genetic increase and growth of the genome may not be favorable energetically -at least not in plants. Gain of function is, in this case, cooperation.
The circular RNA (circRNA) is related to ribozymes/viroids as a chief regulator of other regulatory RNAs, a "sponge" absorbing small RNAs. Micro RNAs (miRNAs) are post-transcriptional regulators that are affected by the presence of circRNAs. circRNAs were detected in human and mouse brains and testes as well as in plants. They can bind 70 conserved miRNAs in a cell and amount up to 25,000 molecules (Hansen et al., 2013) . Their structure is reminiscent of catalytically active ribozymes.
There is an exceptional viroid that gained coding information and entered the human liver (Taylor, 2009) . The viroid is known as hepatitis delta virus (HDV). It has the smallest genome of any known animal virus of about 1,680 nucleotides. It has properties typical of viroids, since it contains circRNA, forms similar hairpin-loops and replicates in the nucleus using host enzymes. Two polymerases have to redirect their specificity from DNA to RNA to generate the HDV genome and antigenome. Both of them have ribozyme activity. In contrast to other ribozymes, HDV encodes a protein, the hepatitis delta antigen (HDVAg) that occurs in two forms, the small-HDVAg (24 kDa) supporting replication and the large-HDVAg (27 kDa) that helps virion assembly. The gene was presumably picked up from the host cell by recombination of HDV's mRNA intermediate with a host mRNA. Transmission depends on a helper virus, the Hepatitis B virus (HBV), which delivers the coat (Taylor, 2009 ) Does packaging by a helper virus protect the genome and thereby allow for a larger viroid to exist?
In plants, viroids may not be able to become bigger possibly due to their sensitivity to degradation -but they cannot become much smaller either. Only a single viroid is known that is completely composed of protein-coding RNA with triplets (AbouHaidar et al., 2014). Viroids and related replicating RNAs are error-prone replicating units and the error frequency imposes a certain minimal size onto them, as they would otherwise become extinct. This mechanism has been described as "error catastrophe, " which prevents survival (Eigen, 1971 (Eigen, , 2013 . The viroids and related RNAs are the smallest known replicons. Smaller ones would become extinct in the absence of repair systems.
In summary, RNA can catalyze many reactions. Protein enzymes which may have evolved later have higher catalytic activities. Ribozymes are carriers of information, but do not require coding genes. Information is stored in their sequence and structure. Thus, replication of an initial RNA is followed by flow of information, from DNA to RNA to protein, as described the Central Dogma (Crick, 1968) . Even an information flow from protein to DNA has been described for some archaeal proteins (Béguin et al., 2015) . The DNA-protein world contains numerous ncRNAs with key functions. ncRNA may serve as a model compound for the origin of life on other planets. Hereby not the chemical composition of this molecule is of prime relevance, but its simplicity and multifunctionality. Furthermore, RNA is software and hardware in a single molecule, which makes it unique in our world. There are other scenarios besides the here discussed "virus-first, " such as "protein-first", "metabolism-fist" or the "lipid world" (Segré et al., 2001; Andras and Andras, 2005; Vasas et al., 2010; Moelling, 2012) . Some of these alternative concepts were built on phylogenomics, the reconstruction of the tree of life by genome sequencing (Delsuc et al., 2005) . Surprisingly, it was Sir Francis Crick, one of the discoverers of the DNA double-helix, who stated that he would not be surprised about a world completely built of RNA. A similar prediction was made by Walter Gilbert (Crick, 1968; Gilbert, 1986) . What a vision! Our world was almost 50 years later defined as "RNAprotein" world (Altman, 2013) . One can speculate our world was built of ribozymes or viroids, which means "viruses first."
ncRNAs appear as relics from the past RNA world, before DNA, the genetic code and proteins evolved. However, ncRNA is essential in our biological DNA world today. It is possible to produce such ncRNA today in the test tube by loss of genic information from protein-coding RNA. This reduction to ncRNA was demonstrated in vitro with phage RNA. Phage Qβ genomic RNA, 4,217 nucleotides in length, was incubated in the presence of Qβ replicase, free nucleotides and salts, a rich milieu in the test tube. The RNA was allowed to replicate by means of the Qβ replicase. Serial transfer of aliquots to fresh medium led to ever faster replication rates and reduction of genomic size, down to 218 nucleotides of ncRNA in 74 generations. This study demonstrated that, depending on environmental conditions, an extreme gene reduction can take place. This experiment performed in 1965 was designated as "Spiegelman's Monster." Coding RNA became replicating ncRNA (Spiegelman et al., 1965; Kacian et al., 1972) ! Manfred Eigen extended this experiment and demonstrated further that a mixture containing no RNA to start with but only ribonucleotides and the Qβ replicase can under the right conditions in a test tube spontaneously generate self-replicating ncRNA. This evolved into a form similar to Spiegelman's Monster. The presence of the replicase enzyme was still necessary in these studies. Furthermore, a change in enzyme concentration and addition of short RNAs or an RNA intercalator influenced the arising RNA population (Sumper and Luce, 1975; Eigen, 2013) . Thus, the complexity of genomes depends on the environment: poor conditions lead to increased complexity and rich environments to reduced complexity.
The process demonstrated in this experiment with viral components indicates that reversion to simplicity, reduction in size, loss of genetic information and speed in replication can be major forces of life, even though this appears to be like a reversion of evolution. The experiment can perhaps be generalized from the test tube to a principle, that the most successful survivors on our planet are the viruses and microorganisms, which became the most abundant entities. Perhaps life can start from there again.
These studies raise the question of how RNA molecules can become longer, if the small polymers become smaller and smaller, replicate faster and outcompete longer ones. This may be overcome by heat flow across an open pore in submerged rocks, which concentrates replicating oligonucleotides from a constant feeding flow and selection for longer strands. This has been described for an increase from 100 to 1,000 nucleotides in vitro. RNA molecules shorter than 75 nucleotides will die out (Kreysing et al., 2015) . Could a poor environment lead to an increase of complexity? This could be tested. Ribozymes were shown to grow in size by uptake of genes, as demonstrated for HDV (Taylor, 2009 ).
An interesting recent unexpected example supporting the notion that environmental conditions influence genetic complexity, is the human gut microbiome. Its complexity increases with diverse food, while uniform rich food reduces its diversity and may lead to diseases such as obesity. Colonization of the human intestinal tract starts at birth. A few dozen bacterial and viral/phage species are conserved between individuals (core sequences) as a stable composition (Broecker et al., 2016c . Dysbiosis has been observed in several chronic diseases and in obesity, a loss of bacterial richness and diversity. Nutrition under affluent conditions with sugar-rich food contributes to obesity, which results in a significant reduction of the complexity of the microbiome. This reduction is difficult to revert (Cotillard et al., 2013; Le Chatelier et al., 2013) . The gut microbiome in human patients with obesity is reminiscent of the gene reduction described in the Spiegelman's Monster experiment: reduction of genes in a rich environment.
The reduction of the complexity of the microbiome is in part attributed to the action of phages, which under such conditions, defined as stress, lyse the bacteria. Fecal microbiota transplantation can even be replaced by soluble fractions containing phages or metabolites from the donor without bacteria (Ott et al., 2017) . Analogously, the most highly complex microbiomes are found in indigenous human tribes in Africa, which live on a broad variety of different nutrients. It is a slow process, though, to increase gut microbiota complexity by diverse nutrition. The obesity-associated microbiota that survive are fitter and more difficult to counteract. Urbanization and westernization of the diet is associated with a loss of microbial biodiversity, loss of microbial organisms and genes (Segata, 2015) .
To understand the mechanism and driving force for genome reduction, deletion rates were tested by insertion of an indicator gene into the Salmonella enterica genome. The loss of the indicator gene was monitored by serial passage in rich medium. After 1,000 generations about 25% of the deletions caused increased bacterial fitness. Deletions resulted in smaller genomes with reduced or absence of DNA repair genes (Koskiniemi et al., 2012) . Gene loss conferred a higher fitness to the bacteria under these experimental conditions.
The recently discovered mimiviruses and other giant viruses are worth considering for understanding the evolution of life with respect to the contribution of viruses. Their hosts are, for example, Acanthamoeba, Chlorella, and Coccolithus algae (Emiliania huxleyi), but also corals or sponges as discussed more recently. Mimiviruses were first discovered in cooling water towers in Bradford, United Kingdom in 2003 with about 1,000 genes, most of which unrelated to previously known genes. Mimiviruses have received attention because they contain elements that were considered hallmarks of living cells, not of viruses, such as elements required for protein synthesis, tRNAs and amino acid transferases. The mimiviruses harbor these building blocks as incomplete sets not sufficient for independent protein synthesis as bacteria or archaea can perform, preventing them from leading an autonomous life (La Scola et al., 2003 Scola et al., , 2008 . They are larger than some bacteria. Giant viruses can be looked at as being on an evolutionary path toward a cellular organism. Alternatively, they may have evolved from a cellular organism by loss of genetic information (Nasir and Caetano-Anolles, 2015) . Giant viruses have frequently taken up genes from their hosts by horizontal gene transfer (HGT) (La Scola et al., 2008; Nasir and Caetano-Anolles, 2015; Colson et al., 2018) . A graph on genome sizes shows that mimiviruses and bacteria overlap in size, indicating a continuous transition between viruses and bacteria and between living and non-living worlds (based on Holmes, 2011) (Figure 3) . Other giant viruses, such as megaviruses, were discovered in the ocean of Chile with 1,120 genes. Most recently the Klosneuvirus was identified in the sewage of the monastery Klosterneuburg in Austria in 2017 with 1.57 million (mio) basepairs (Mitch, 2017) . Pithovirus sibericum is the largest among giant viruses discovered to date with a diameter of 1.5 microns, a genome of 470,000 bp with 467 putative genes, 1.6 microns in length, and it is presumably 30,000 years old as it was recovered from permafrost in Siberia (Legendre et al., 2014) . The smaller Pandoraviruses with 1 micron in length have five times larger genomes, 2,500,000 bp (Philippe et al., 2013) (Figure 3) .
The giant viruses can even be hosts to smaller viruses, the virophages, reminiscent of bacteriophages, the viruses of bacteria. These virophages such as Sputnik are only 50 nm in size with 18,343 bp of circular dsDNA and 21 predicted proteincoding genes. They replicate in viral factories and consume the resources of the mimivirus, thereby destroying it. Some, virophages can even integrate into the genome of the cellular host and can be reactivated when the host is infected by giant viruses. Thus, giant viruses suggest that viruses are close to living entities or may have been alive (La Scola et al., 2008; Fischer and Hackl, 2016) . In biology it is common to distinguish between living and dead matter by the ability to synthesize proteins and replicate autonomously. The giant viruses may be considered as missing link between the two, because they harbor "almost" the protein synthesis apparatus. The transition from living to the non-living world is continuous, not separated by a sharp borderline (Figure 3) .
Viruses are not considered alive by most of the scientific community and as written in textbooks, because they cannot replicate autonomously. Yet some of the giant viruses are equipped with almost all components of the protein synthesis machinery close to bacteria suggesting that they belong to the living matter (Schulz et al., 2017) . The ribozymes may have been the earliest replicating entity. Perhaps also other viruses were initially more independent of the early Earth than they are today. As described in Figure 1 there may have been initially no major difference between an early virus or an early cell. Only later viruses may have given up their autonomous replication and became parasites -as has been described for some bacteria (see below).
Efforts have been made to identify the smallest living cell that is still autonomously replicating. Among the presumably smallest naturally occurring bacteria is Pelagibacter ubique of the SAR11 clade of bacteria (Giovannoni, 2017) , which was discovered in 1990. It is an alpha-proteobacterium with 1,389 genes present ubiquitously in all oceans. It can reach up to 10 28 free living cells in total and represents about 25% of microbial plankton cells. Very little of its DNA is non-coding. It harbors podophage-type phages, designated as "pelagiphage" (Zhao et al., 2013) . This small bacterium was designated as the most common organism on the planet. Why is it so successful? This autonomous bacterium is smaller than some parasitic giant viruses. Craig Venter, who first succeeded in sequencing the human genome, tried to minimize the putative smallest genome of a living species, from Mycoplasma mycoides, a parasitic bacterium that lives in ruminants (Gibson et al., 2008 (Gibson et al., , 2010 . His group synthesized a genome of 531,000 bp with 473 genes, 149 of them (32%) with unknown functions (Hutchison et al., 2016) . Among the smallest parasitic living organisms is Nanoarchaeum equitans. It is a thermophile archaeon which lives at 80 • C and at pH 6 with 2% salt (Huber et al., 2003) . Its genome has a size of 490,000 bp and encodes 540 genes. N. equitans is an obligate symbiont of a bigger archaeon, Ignicoccus riding on it as on a horse, hence the name (Huber et al., 2003) .
The world of viruses covers a range of three logs in size of their genomes: from zero genes to about 2,500 genes amounting to about 2,500,000 bp of DNA. The zero-gene viroids are about 300 bases in length (Figure 3) .
The virosphere is the most successful reservoir of biological entities on our planet in terms of numbers of particles, speed of replication, growth rates, and sequence space. There are about 10 33 viruses on our planet and they are present in every single existing species (Suttle, 2005) .
There is no living species without viruses! Viruses also occur freely in the oceans, in the soil, in clouds up to the stratosphere and higher, to at least 300 km in altitude. They populate the human intestine, birth canal, and the outside of the body as protective layer against microbial populations. Microbes contain phages that are activated during stress conditions such as lack of nutrients, change in temperatures, lack of space and other changes of environmental conditions.
One of the most earth-shaking papers of this century was the publication of the human genome sequence (Lander et al., 2001) . About half, possibly even two-thirds of the sequence are composed of more or less complete endogenous retroviruses (ERVs) and related retroelements (REs) (de Koning et al., 2011) . REs amplify via copy-and-paste mechanisms involving a reverse transcriptase step from an RNA intermediate into DNA. In addition, DNA transposable elements (TEs) move by a cutand-paste mechanism. The origin of REs is being discussed as remnants of ancient retroviral germline infections that became evolutionarily fixed in the genome. About 450,000 human ERV (HERV) elements constitute about 8% of the human genome consisting of hallmark retroviral elements like the gag, pol, env genes and flanking long terminal repeats (LTR) that act as promoters (Lander et al., 2001) . Howard Temin, one of the discoverers of the reverse transcriptase, in 1985 already described endogenous retrovirus-like elements, which he estimated to about 10% of the human and mouse genome sequence (Temin, 1985) . The actual number is about 45% as estimated today (Lander et al., 2001) . In some genes such as the Protein Kinase Inhibitor B (PKIB) gene we determined about 70% retrovirusrelated sequences (Moelling and Broecker, 2015) . Is there a limit? Could it have been 100%? Retroviruses are estimated to have entered the lineage of the mammalian genome 550 million years ago (MYA) (Hayward, 2017) . Older ERV sequences may exist but are unrecognizable today due to the accumulation of mutations.
ERVs undergo mutations, deletions or homologous recombination events with large deletions and can become as short as solo LTR elements, which are a few hundred bp in length -the left-overs from full-length retroviral genomes of about 10,000 bp. The LTR promoters can deregulate neighboring genes. Homologous recombination events may be considered as gene loss or gene reduction events. It is the assumption that the ERVs, which were no longer needed for host cell defense, were no longer selected for by evolution and consequently deleted as unnecessary consumers of energy.
Eugene Koonin points out that infection and integration are unique events occurring at a fast pace, while loss and gene reduction may take much longer time frames (Wolf and Koonin, 2013) .
A frequent gene reduction of eukaryotic genomes is the loss of the viral envelope protein encoded by the env gene. Without a coat, retroviruses can no longer leave the cell and infect other cells. They lose mobility and become obligatory intracellular elements. Helper viruses can supply envelope proteins in trans and mobilize the viruses. TEs or REs can be regarded as examples of coat-free intracellular virus relics -or could it have been the other way round, perhaps precursors of full-length retroviruses?
These elements can be amplified intracellularly and modify the host genomes by integration with the potential danger of gene disruption and genetic changes. REs can lead to gene duplications and pseudogene development, with one copy for stable conservation of acquired functions and the other one for innovations (Cotton and Page, 2005) . Such duplications constitute large amounts of mammalian genomes (Zhang, 2003) . Retroviruses have an RNase H moiety duplication, one of which serves as a catalytically inactive linker between the RT polymerase and the enzymatically active RNase H (Xiong and Eickbush, 1990; Malik and Eickbush, 2001; Moelling and Broecker, 2015; Moelling et al., 2017) . This gene duplication dates back to 500 mio years (Cotton and Page, 2005) .
Gene duplications are a common cause of cancer, which often occurs only in the genome of the cancer cell itself, less affecting offsprings. Myc, Myb, ErbB2, Ras, and Raf are oncogenes amplified in diverse types of human cancers (Vogelstein and Kinzler, 2002) . The ability of retroviruses to integrate makes them distinct from endosymbionts which stay separate. Yet the net result is very similar, acquisition of new genetic information, which is transmitted to the next generation, if the germline is infected and endogenization of the virus occurred.
Viral integration is not limited to eukaryotic cells but also a mechanism in prokaryotes for maintenance of the lysogenic state of phages inside bacteria.
Also, for other eukaryotic viruses such as HBV, the envelope surface antigen BHsAg can be deleted, which leads to an obligatory intracellular life style for the virus, which especially in the presence of HCV promotes cancer (Yang et al., 2016) .
HIV has been shown to rapidly lose one of its auxiliary genes, nef, originally for negative factor. The gene was lost within a rather low number of passages of the virus grown under tissue culture conditions by selection for high virus titer producing cells. Deletion of nef resulted in a significant increase of the virus titer in culture -hence the name. The nef gene product was of no need inside tissue culture cells, rather it was inhibitory for replication. However, it is essential for pathogenicity in animals, and subsequently nef was reinterpreted as "necessary factor" (Flint, 2015) .
Also, the human hosts of HIV can lose a significant terminal portion of a seven transmembrane receptor in lymphocytes, the primary target cell for HIV entry and for virus uptake. This molecule, the CCR5 cytokine receptor is truncated by 32 carboxy-terminal amino acids (CCR5-32), disabling the receptor functionally. The allele frequency of the mutant CCR5-32 mutant is about 10% in the European population, making these people resistant to HIV infections (Solloch et al., 2017) . This gene loss in Europeans has been shown to make the individuals resistant not only against HIV infection but also against malaria. This may have been the selective pressure in the past before HIV/AIDS arose. No side effect for humans lacking this gene has been described (Galvani and Slatkin, 2003) .
Viruses have been proven to be drivers of evolution (Villarreal and Witzany, 2010) , including the human genome, which by at least 45% is composed of sequences related to retroviruses. In addition, endogenized retroviruses supplied the syncytin genes that are essential for the development of the mammalian placenta, and allowed the growth of embryos without its rejection by the maternal immune system (Dupressoir et al., 2012) . Thus, the same property which causes immunodeficiency in HIV-infected patients and leads to AIDS causes syncytia formation, cell fusion after infection by a retrovirus. Viruses have also been proposed to be at the origin of the evolution of adaptive immunity (Villarreal, 2009 ). Thus, viruses shaped genomes by supplying essential genes and mechanisms.
Endogenization of retroviruses has occurred in the mammalian genomes for at least 550 mio years (Hayward, 2017) . If the integrated ERVs did not provide any selective advantage, they deteriorated and accumulated mutations with loss of function. This was directly proven by reconstruction of an infectious retrovirus from the consensus sequence of 9 defective endogenous virus sequences, designated as Phoenix. The virus was expressed from a constructed synthetic DNA clone in cell culture and formed virus particles identified by high resolution microscopic analysis (Dewannieux and Heidmann, 2013) .
The koalas in Australia are currently undergoing endogenization of a retrovirus (koala retrovirus, KoRV) in "real time" and demonstrate possible consequences for immunity. In the early 1900s, some individuals were transferred to islands, including Kangaroo Island, close to the Australian mainland for repopulation purposes, as koalas were threatened to become extinct. Today, the majority of the koala population is infected by KoRV, which is closely related to the Gibbon ape leukemia virus (GALV). Yet, koalas isolated on Kangaroo Island are KoRV negative, which allows dating the introduction of KoRV into the koala population to about one hundred years ago. Many of the infected koalas fell ill and died, yet some populations became resistant within about 100 years, corresponding to about 10 generations. The koalas likely developed resistance due to the integrated DNA proviruses. The retrovirus is transmitted as exogenous as well as endogenous virus, similar to the Jaagsiekte sheep retrovirus (JSRV), whereby the endogenized viruses protect with a viral gene product, such as Env, against de novo infections by "superinfection exclusion" (Tarlinton, 2012) . The contribution of retroviruses to the antiviral defense is striking, since all retroviral genes have analogous genes in the siRNA/RNAi defense mechanism of eukaryotic cells (Moelling et al., 2006) .
Retroviruses can protect against infection by other related viruses, for example, by expressing Env proteins that block cellsurface receptors (Villarreal, 2011) . A comparable mechanism protects bacterial cells against DNA phages, by integrated phage DNA fragments that are transcribed into mRNA and hybridize to incoming new DNA phages and thereby lead to their destruction by hybrid-specific nucleases, CRISPR/Cas immunity (Charpentier and Doudna, 2013) . It is often not realized that immunity acquisition in bacteria and mammalian cells follow analogous mechanisms (Figure 4) .
Integration of retroviruses normally occurs in somatic cells after infection as an obligatory step during the viral life cycle. Infection of germline cells can lead to transmission to the next generation and ultimately result in inherited resistance. Endogenized retroviruses likely caused resistance FIGURE 4 | Viruses protect against viruses: retroviruses protect a cell against a new infection by a similar virus designated as "superinfection exclusion" or viral interference. This is mediated by viral gene products such as proteins or nucleic acids. Similarly, phages protect against phages: superinfection of bacteria is prevented by CRISPR/Cas RNA originating from previous infections. The mechanisms of defense against viruses and phages are analogous. Protection by viruses or phages against superinfections represents cellular defense and acquired immunity. The four examples are discussed in the text.
to the exogenous counterparts. Similarly, resistance to Simian Immune Deficiency virus (SIV) in some monkey species may be explained by endogenization (Li et al., 2017 (Li et al., , 2018 . In the case of phages and their prokaryotic hosts the mechanism is described as CRISPR/Cas, which follow analogous principles of "endogenization" of incoming genetic material for subsequent exclusion.
One may speculate that HIV may also eventually become endogenized into the human genome. There is some evidence that HIV can infect human germline cells and can be transmitted to the embryonic genome (Wang et al., 2011) . How long this may take is not known -10 generations?
The loss of function of ERVs can occur by mutations, deletions of the env or other genes and ultimately all coding genes by homologous recombination, leaving behind only one LTR. The number of retrovirus-like elements add up to about 450,000, corresponding to 8% of the human genome (Lander et al., 2001; Cordaux and Batzer, 2009 ). The promoter regions were analyzed for their contribution to cancer by activating neighboring genes -as a consequence of a former retrovirus infection. Indeed, activated cellular genes by "downstream promotion" were identified in animal studies with activation of the myc gene as one of many examples, leading to chronic, not acute development of cancer (Ott et al., 2013) . As a general mechanism for human cancer today the LTRs are, however, not identified as a major culprit. Most of the ERVs we find today have been integrated during evolution in introns or other regions where their presence is relatively harmless. Did the other ones result in death of the carriers which disappeared? The effects of LTRs on the expression levels of neighboring host genes was studied with the endogenous human virus, HERV-K, as a possible cause of cancer, but this appears not to be a general phenomenon (Broecker et al., 2016b) . As shown for the koalas, ERVs can confer immunity to viral infections (Feschotte and Gilbert, 2012) .
A related ERV, HERV-H, was shown to produce an RNA that keeps early embryonic cells pluripotent and even revert adult cells to regain pluripotency (Grow et al., 2015) . Thus, the role of ERVs may be more complex than we presently know.
Transposable elements and REs that lost the ability of cellular transmission by deletion of the coat protein majorly contribute to genetic complexity of host cells. They are "locked" inside the cells and are major drivers of the increase of genetic complexity (Cordaux and Batzer, 2009 ). One could speculate that these intracellular elements are replicationincompetent retroviruses lacking coats (Lander et al., 2001) . Bats transmit viruses such as Ebola and SARS coronavirus without suffering from disease (Beltz, 2018) . Even RNA viruses such as Bornaviruses have been shown to integrate by illegitimate reverse transcription, possibly also supplying immunity against superinfection (Katzourakis and Gifford, 2010) .
There are two prominent events that significantly contributed to the success of life and the formation of cells. Both of them are associated with gene reduction. This phenomenon may play a role for the evolution of viruses from autonomous to parasitic lifestyles. In the 1960s Lynn Margulis proposed an extracellular origin for mitochondria (Margulis, 1970 (Margulis, , 1993 ). An ancestral cell, perhaps an archaeon, was infected by an anaerobic bacterium, which gave rise to mitochondria. Similarly, cyanobacteria formed the chloroplasts in modern plant cells. Mitochondria arose around 1.45 billion years ago (BYA) (Embley and Martin, 2006) . Mitochondria and chloroplasts are the most striking examples for a change in lifestyle from autonomous bacteria to endosymbionts. This transition is often considered as extremely rare and a hallmark of evolution of life on our planet. However, there are many other obligate intracellular parasites such as Rickettsia, Chlamydia trachomatis, Coxiella burnetii (the causative agent of Q fever), Mycobacterium leprae, M. tuberculosis, and M. mycoides (Beare et al., 2006) .
The change of lifestyle of the endosymbionts in the two cases of mitochondria and chloroplasts is striking. Both of them drastically reduced their genetic make-up. Mitochondria contain less than 37 genes, left from the original about 3,000 genes. Is endogenization of retroviruses, the ERVs, which are integrated into germline cells, related to endosymbiosis? Are these endosymbionts models for the transition from autonomous lifestyle to a parasitic life-which may have taken place with viruses? A more recent typical example for a reductive evolution are Rickettsia. These bacteria were assumed for some time to be viruses because of their obligatory intracellular parasitic existence. Rickettsia have evolved from autonomously replicating bacteria. Reductive evolution of endosymbionts can yield bacteria with tiny genomes on the expense of autonomous extracellular life. Their genomes are 1.11 mio bp in length with about 834 protein-coding genes, and loss of 24% by reductive evolution (Ogata et al., 2001) . Rickettsia may have some relationship with cyanobacteria, which are considered as the major symbionts.
Can one speculate that viruses may have been autonomous entities initially? Viroids may have undergone transition from autonomy to parasites, just as shown for mitochondria, chloroplasts or Rickettsia? To which extent have viruses been autonomous and independent of cellular metabolisms originally -and contributed to the origin of cells? Could they only later have lost their autonomy and become parasitic?
Viruses are minimalistic in their composition and must have undergone stringent gene reductions (Flint, 2015) . How small can their genomes become? Most coding RNA viruses still contain regulatory elements, ncRNA at the 3 and 5 terminal regions for ribosomal entry, protein synthesis, transcriptional regulation, and others.
A subgroup of retroviruses is an interesting example in respect to simultaneous loss and gain of genetic information. The oncogenic retroviruses or tumorviruses can recombine with cellular genes which under the promoters of retroviruses can become oncogenes and drivers of cancer. About a hundred oncogenes have been selected for in the laboratories and studied over decades for understanding the molecular mechanisms of cancer. Selection for growth advantages of the host cells led to the discovery of the fastest growth-promoting oncogenes we know today, such as Ras, Raf, ErbB or Myc, which are in part successful targets for anticancer drugs (Moelling et al., 1984) .
These oncogenes were in most cases taken up by the retroviruses at the expense of structural (gag), replicating (pol) or envelope (env) genes, and are often expressed as fusion proteins with Gag. Thus, oncogenic retroviruses are obligatory intracellular defective viruses and were selected for in the laboratory by researchers for the oncogenes with the most potent growth promoting ability. They need the supply of replicatory genes in trans from co-infecting helper viruses to infect other cells (Flint, 2015) . Retroviruses are able to pick up cellular genes, transfer and integrate them into neighboring cells. Some strains of Rous sarcoma virus maintain replication competent when carrying the cell-derived src (for sarcoma) oncogene encoding a protein of 536 amino acids that apparently can fit into the retroviral particle along with the full-size viral genome (Broecker et al., 2016a) . Spatial reasons may have influenced the formation of oncogenic retroviruses and limited their size and thereby led to their defective phenotypes.
There are indications that the uncontrolled activity of (retro)transposons in germline cells can result in diseases such as male infertility -presumably by "error catastrophe, " caused by too many transposition events. In mammals, piRNAs tame transposon activity by means of the RNase H activity of PIWI proteins during spermatogenesis (Girard et al., 2006) .
Only a minority of viruses are pathogens; most of them do not cause diseases. On the contrary, they are most important as drivers of evolution, as transmitters of genetic material, as innovative agents. In particular, the RNA viruses are the most innovative ones. Some of them are pathogenic and dangerous, such as HIV or influenza virus, or viroids in plants. RNA viruses are able to change so rapidly that the host immune system is unable to counteract the infection. Pathogenicity arises when environmental conditions change, for instance, when a virus enters a new organism or species.
Increase of cellular complexity by viruses is an important feature of evolution. Such major evolutionary changes are recently taken as arguments against the evolutionary theory by Charles Darwin who considered gradual changes, small increments by mutations as the main basis for selection and evolution. New criticism is addressing this thinking, considering larger changes as evolutionary drivers. Such changes arise by many complex phenomena such as endosymbiosis, infection by prokaryotes, viruses and fungi, recombination of genes, HGT, infections, sex. Dramatic changes such as endosymbiosis or pathogen infections extend Darwin's concept of evolution.
There are numerous examples for the contribution of viruses to the evolution of life since at least as long as 550 MYA (Hayward, 2017) . But genetic noise through random mutations does not allow us to go back to the origin of life. It may not be impossible that the earliest compartment was indistinguishable, either a pre-cell or a pre-virus. By analogy one may speculate that at some point autonomous viruses gave up independence for an obligatory intracellular life -as has been described for mitochondria and chloroplasts but also intracellular bacteria such as Rickettsia. This speculation is based on the concept that early life must have started simple and with high genetic variability and then became more complex. But complexity can be given up for a less energy consuming lifestyle with small genomes and high speed of replication (Moelling, 2012 (Moelling, , 2013 . Therefore, the question may be repeated: "Are viruses our oldest ancestors?" Some fossil life can be partially reproduced in vitro by Spiegelman's Monster and Eigen's follow-up experiments, explaining the great surviving potential of simple ncRNA.
Viruses can be pathogens, but their recognition as primarily causing diseases is wrong. This notion is based on the history of viruses in medicine, as explained in a book entitled "Viruses: More Friends Than Foes" (Moelling, 2017) . The scenario described here focuses on viruses as drivers of evolution.
The early RNA world gained interest 20-30 years ago as evidenced by the references provided above. Surprisingly, there are scientists who still believe in the "pansperm hypothesis" and think that retroviruses are of extraterrestric origin (Steele et al., 2018) . The recent interest in the origin of life arose from the newly discovered exoplanets whose number increases daily -and which may be as numerous as 10 25 . Thus, pure statistics make some people believe that there is extraterrestrial life.
The extraterrestric life is mimicked in laboratories on Earth with many assumptions -perhaps this overview stimulates some thinking. The discussion presented here should be taken as concept about simple replicating and evolving entities possibly arising from different building blocks in other environments, with structure being more relevant than sequence. | How can DNA arise chemically from RNA? | false | 1,183 | {
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"deoxyribozymes can form from ribonucleotides (Wilson and Szostak, 1999) . Thus, DNA can arise from RNA chemically, without the key protein enzyme, the reverse transcriptase."
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2,504 | Respiratory Viral Infections in Exacerbation of Chronic Airway Inflammatory Diseases: Novel Mechanisms and Insights From the Upper Airway Epithelium
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7052386/
SHA: 45a566c71056ba4faab425b4f7e9edee6320e4a4
Authors: Tan, Kai Sen; Lim, Rachel Liyu; Liu, Jing; Ong, Hsiao Hui; Tan, Vivian Jiayi; Lim, Hui Fang; Chung, Kian Fan; Adcock, Ian M.; Chow, Vincent T.; Wang, De Yun
Date: 2020-02-25
DOI: 10.3389/fcell.2020.00099
License: cc-by
Abstract: Respiratory virus infection is one of the major sources of exacerbation of chronic airway inflammatory diseases. These exacerbations are associated with high morbidity and even mortality worldwide. The current understanding on viral-induced exacerbations is that viral infection increases airway inflammation which aggravates disease symptoms. Recent advances in in vitro air-liquid interface 3D cultures, organoid cultures and the use of novel human and animal challenge models have evoked new understandings as to the mechanisms of viral exacerbations. In this review, we will focus on recent novel findings that elucidate how respiratory viral infections alter the epithelial barrier in the airways, the upper airway microbial environment, epigenetic modifications including miRNA modulation, and other changes in immune responses throughout the upper and lower airways. First, we reviewed the prevalence of different respiratory viral infections in causing exacerbations in chronic airway inflammatory diseases. Subsequently we also summarized how recent models have expanded our appreciation of the mechanisms of viral-induced exacerbations. Further we highlighted the importance of the virome within the airway microbiome environment and its impact on subsequent bacterial infection. This review consolidates the understanding of viral induced exacerbation in chronic airway inflammatory diseases and indicates pathways that may be targeted for more effective management of chronic inflammatory diseases.
Text: The prevalence of chronic airway inflammatory disease is increasing worldwide especially in developed nations (GBD 2015 Chronic Respiratory Disease Collaborators, 2017 Guan et al., 2018) . This disease is characterized by airway inflammation leading to complications such as coughing, wheezing and shortness of breath. The disease can manifest in both the upper airway (such as chronic rhinosinusitis, CRS) and lower airway (such as asthma and chronic obstructive pulmonary disease, COPD) which greatly affect the patients' quality of life (Calus et al., 2012; Bao et al., 2015) . Treatment and management vary greatly in efficacy due to the complexity and heterogeneity of the disease. This is further complicated by the effect of episodic exacerbations of the disease, defined as worsening of disease symptoms including wheeze, cough, breathlessness and chest tightness (Xepapadaki and Papadopoulos, 2010) . Such exacerbations are due to the effect of enhanced acute airway inflammation impacting upon and worsening the symptoms of the existing disease (Hashimoto et al., 2008; Viniol and Vogelmeier, 2018) . These acute exacerbations are the main cause of morbidity and sometimes mortality in patients, as well as resulting in major economic burdens worldwide. However, due to the complex interactions between the host and the exacerbation agents, the mechanisms of exacerbation may vary considerably in different individuals under various triggers. Acute exacerbations are usually due to the presence of environmental factors such as allergens, pollutants, smoke, cold or dry air and pathogenic microbes in the airway (Gautier and Charpin, 2017; Viniol and Vogelmeier, 2018) . These agents elicit an immune response leading to infiltration of activated immune cells that further release inflammatory mediators that cause acute symptoms such as increased mucus production, cough, wheeze and shortness of breath. Among these agents, viral infection is one of the major drivers of asthma exacerbations accounting for up to 80-90% and 45-80% of exacerbations in children and adults respectively (Grissell et al., 2005; Xepapadaki and Papadopoulos, 2010; Jartti and Gern, 2017; Adeli et al., 2019) . Viral involvement in COPD exacerbation is also equally high, having been detected in 30-80% of acute COPD exacerbations (Kherad et al., 2010; Jafarinejad et al., 2017; Stolz et al., 2019) . Whilst the prevalence of viral exacerbations in CRS is still unclear, its prevalence is likely to be high due to the similar inflammatory nature of these diseases (Rowan et al., 2015; Tan et al., 2017) . One of the reasons for the involvement of respiratory viruses' in exacerbations is their ease of transmission and infection (Kutter et al., 2018) . In addition, the high diversity of the respiratory viruses may also contribute to exacerbations of different nature and severity (Busse et al., 2010; Costa et al., 2014; Jartti and Gern, 2017) . Hence, it is important to identify the exact mechanisms underpinning viral exacerbations in susceptible subjects in order to properly manage exacerbations via supplementary treatments that may alleviate the exacerbation symptoms or prevent severe exacerbations.
While the lower airway is the site of dysregulated inflammation in most chronic airway inflammatory diseases, the upper airway remains the first point of contact with sources of exacerbation. Therefore, their interaction with the exacerbation agents may directly contribute to the subsequent responses in the lower airway, in line with the "United Airway" hypothesis. To elucidate the host airway interaction with viruses leading to exacerbations, we thus focus our review on recent findings of viral interaction with the upper airway. We compiled how viral induced changes to the upper airway may contribute to chronic airway inflammatory disease exacerbations, to provide a unified elucidation of the potential exacerbation mechanisms initiated from predominantly upper airway infections.
Despite being a major cause of exacerbation, reports linking respiratory viruses to acute exacerbations only start to emerge in the late 1950s (Pattemore et al., 1992) ; with bacterial infections previously considered as the likely culprit for acute exacerbation (Stevens, 1953; Message and Johnston, 2002) . However, with the advent of PCR technology, more viruses were recovered during acute exacerbations events and reports implicating their role emerged in the late 1980s (Message and Johnston, 2002) . Rhinovirus (RV) and respiratory syncytial virus (RSV) are the predominant viruses linked to the development and exacerbation of chronic airway inflammatory diseases (Jartti and Gern, 2017) . Other viruses such as parainfluenza virus (PIV), influenza virus (IFV) and adenovirus (AdV) have also been implicated in acute exacerbations but to a much lesser extent (Johnston et al., 2005; Oliver et al., 2014; Ko et al., 2019) . More recently, other viruses including bocavirus (BoV), human metapneumovirus (HMPV), certain coronavirus (CoV) strains, a specific enterovirus (EV) strain EV-D68, human cytomegalovirus (hCMV) and herpes simplex virus (HSV) have been reported as contributing to acute exacerbations . The common feature these viruses share is that they can infect both the upper and/or lower airway, further increasing the inflammatory conditions in the diseased airway (Mallia and Johnston, 2006; Britto et al., 2017) .
Respiratory viruses primarily infect and replicate within airway epithelial cells . During the replication process, the cells release antiviral factors and cytokines that alter local airway inflammation and airway niche (Busse et al., 2010) . In a healthy airway, the inflammation normally leads to type 1 inflammatory responses consisting of activation of an antiviral state and infiltration of antiviral effector cells. This eventually results in the resolution of the inflammatory response and clearance of the viral infection (Vareille et al., 2011; Braciale et al., 2012) . However, in a chronically inflamed airway, the responses against the virus may be impaired or aberrant, causing sustained inflammation and erroneous infiltration, resulting in the exacerbation of their symptoms (Mallia and Johnston, 2006; Dougherty and Fahy, 2009; Busse et al., 2010; Britto et al., 2017; Linden et al., 2019) . This is usually further compounded by the increased susceptibility of chronic airway inflammatory disease patients toward viral respiratory infections, thereby increasing the frequency of exacerbation as a whole (Dougherty and Fahy, 2009; Busse et al., 2010; Linden et al., 2019) . Furthermore, due to the different replication cycles and response against the myriad of respiratory viruses, each respiratory virus may also contribute to exacerbations via different mechanisms that may alter their severity. Hence, this review will focus on compiling and collating the current known mechanisms of viral-induced exacerbation of chronic airway inflammatory diseases; as well as linking the different viral infection pathogenesis to elucidate other potential ways the infection can exacerbate the disease. The review will serve to provide further understanding of viral induced exacerbation to identify potential pathways and pathogenesis mechanisms that may be targeted as supplementary care for management and prevention of exacerbation. Such an approach may be clinically significant due to the current scarcity of antiviral drugs for the management of viral-induced exacerbations. This will improve the quality of life of patients with chronic airway inflammatory diseases.
Once the link between viral infection and acute exacerbations of chronic airway inflammatory disease was established, there have been many reports on the mechanisms underlying the exacerbation induced by respiratory viral infection. Upon infecting the host, viruses evoke an inflammatory response as a means of counteracting the infection. Generally, infected airway epithelial cells release type I (IFNα/β) and type III (IFNλ) interferons, cytokines and chemokines such as IL-6, IL-8, IL-12, RANTES, macrophage inflammatory protein 1α (MIP-1α) and monocyte chemotactic protein 1 (MCP-1) (Wark and Gibson, 2006; Matsukura et al., 2013) . These, in turn, enable infiltration of innate immune cells and of professional antigen presenting cells (APCs) that will then in turn release specific mediators to facilitate viral targeting and clearance, including type II interferon (IFNγ), IL-2, IL-4, IL-5, IL-9, and IL-12 (Wark and Gibson, 2006; Singh et al., 2010; Braciale et al., 2012) . These factors heighten local inflammation and the infiltration of granulocytes, T-cells and B-cells (Wark and Gibson, 2006; Braciale et al., 2012) . The increased inflammation, in turn, worsens the symptoms of airway diseases.
Additionally, in patients with asthma and patients with CRS with nasal polyp (CRSwNP), viral infections such as RV and RSV promote a Type 2-biased immune response (Becker, 2006; Jackson et al., 2014; Jurak et al., 2018) . This amplifies the basal type 2 inflammation resulting in a greater release of IL-4, IL-5, IL-13, RANTES and eotaxin and a further increase in eosinophilia, a key pathological driver of asthma and CRSwNP (Wark and Gibson, 2006; Singh et al., 2010; Chung et al., 2015; Dunican and Fahy, 2015) . Increased eosinophilia, in turn, worsens the classical symptoms of disease and may further lead to life-threatening conditions due to breathing difficulties. On the other hand, patients with COPD and patients with CRS without nasal polyp (CRSsNP) are more neutrophilic in nature due to the expression of neutrophil chemoattractants such as CXCL9, CXCL10, and CXCL11 (Cukic et al., 2012; Brightling and Greening, 2019) . The pathology of these airway diseases is characterized by airway remodeling due to the presence of remodeling factors such as matrix metalloproteinases (MMPs) released from infiltrating neutrophils (Linden et al., 2019) . Viral infections in such conditions will then cause increase neutrophilic activation; worsening the symptoms and airway remodeling in the airway thereby exacerbating COPD, CRSsNP and even CRSwNP in certain cases (Wang et al., 2009; Tacon et al., 2010; Linden et al., 2019) .
An epithelial-centric alarmin pathway around IL-25, IL-33 and thymic stromal lymphopoietin (TSLP), and their interaction with group 2 innate lymphoid cells (ILC2) has also recently been identified (Nagarkar et al., 2012; Hong et al., 2018; Allinne et al., 2019) . IL-25, IL-33 and TSLP are type 2 inflammatory cytokines expressed by the epithelial cells upon injury to the epithelial barrier (Gabryelska et al., 2019; Roan et al., 2019) . ILC2s are a group of lymphoid cells lacking both B and T cell receptors but play a crucial role in secreting type 2 cytokines to perpetuate type 2 inflammation when activated (Scanlon and McKenzie, 2012; Li and Hendriks, 2013) . In the event of viral infection, cell death and injury to the epithelial barrier will also induce the expression of IL-25, IL-33 and TSLP, with heighten expression in an inflamed airway (Allakhverdi et al., 2007; Goldsmith et al., 2012; Byers et al., 2013; Shaw et al., 2013; Beale et al., 2014; Jackson et al., 2014; Uller and Persson, 2018; Ravanetti et al., 2019) . These 3 cytokines then work in concert to activate ILC2s to further secrete type 2 cytokines IL-4, IL-5, and IL-13 which further aggravate the type 2 inflammation in the airway causing acute exacerbation (Camelo et al., 2017) . In the case of COPD, increased ILC2 activation, which retain the capability of differentiating to ILC1, may also further augment the neutrophilic response and further aggravate the exacerbation (Silver et al., 2016) . Interestingly, these factors are not released to any great extent and do not activate an ILC2 response during viral infection in healthy individuals (Yan et al., 2016; Tan et al., 2018a) ; despite augmenting a type 2 exacerbation in chronically inflamed airways (Jurak et al., 2018) . These classical mechanisms of viral induced acute exacerbations are summarized in Figure 1 .
As integration of the virology, microbiology and immunology of viral infection becomes more interlinked, additional factors and FIGURE 1 | Current understanding of viral induced exacerbation of chronic airway inflammatory diseases. Upon virus infection in the airway, antiviral state will be activated to clear the invading pathogen from the airway. Immune response and injury factors released from the infected epithelium normally would induce a rapid type 1 immunity that facilitates viral clearance. However, in the inflamed airway, the cytokines and chemokines released instead augmented the inflammation present in the chronically inflamed airway, strengthening the neutrophilic infiltration in COPD airway, and eosinophilic infiltration in the asthmatic airway. The effect is also further compounded by the participation of Th1 and ILC1 cells in the COPD airway; and Th2 and ILC2 cells in the asthmatic airway.
Frontiers in Cell and Developmental Biology | www.frontiersin.org mechanisms have been implicated in acute exacerbations during and after viral infection (Murray et al., 2006) . Murray et al. (2006) has underlined the synergistic effect of viral infection with other sensitizing agents in causing more severe acute exacerbations in the airway. This is especially true when not all exacerbation events occurred during the viral infection but may also occur well after viral clearance (Kim et al., 2008; Stolz et al., 2019) in particular the late onset of a bacterial infection (Singanayagam et al., 2018 (Singanayagam et al., , 2019a . In addition, viruses do not need to directly infect the lower airway to cause an acute exacerbation, as the nasal epithelium remains the primary site of most infections. Moreover, not all viral infections of the airway will lead to acute exacerbations, suggesting a more complex interplay between the virus and upper airway epithelium which synergize with the local airway environment in line with the "united airway" hypothesis (Kurai et al., 2013) . On the other hand, viral infections or their components persist in patients with chronic airway inflammatory disease (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Hence, their presence may further alter the local environment and contribute to current and future exacerbations. Future studies should be performed using metagenomics in addition to PCR analysis to determine the contribution of the microbiome and mycobiome to viral infections. In this review, we highlight recent data regarding viral interactions with the airway epithelium that could also contribute to, or further aggravate, acute exacerbations of chronic airway inflammatory diseases.
Patients with chronic airway inflammatory diseases have impaired or reduced ability of viral clearance (Hammond et al., 2015; McKendry et al., 2016; Akbarshahi et al., 2018; Gill et al., 2018; Wang et al., 2018; Singanayagam et al., 2019b) . Their impairment stems from a type 2-skewed inflammatory response which deprives the airway of important type 1 responsive CD8 cells that are responsible for the complete clearance of virusinfected cells (Becker, 2006; McKendry et al., 2016) . This is especially evident in weak type 1 inflammation-inducing viruses such as RV and RSV (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Additionally, there are also evidence of reduced type I (IFNβ) and III (IFNλ) interferon production due to type 2-skewed inflammation, which contributes to imperfect clearance of the virus resulting in persistence of viral components, or the live virus in the airway epithelium (Contoli et al., 2006; Hwang et al., 2019; Wark, 2019) . Due to the viral components remaining in the airway, antiviral genes such as type I interferons, inflammasome activating factors and cytokines remained activated resulting in prolong airway inflammation (Wood et al., 2011; Essaidi-Laziosi et al., 2018) . These factors enhance granulocyte infiltration thus prolonging the exacerbation symptoms. Such persistent inflammation may also be found within DNA viruses such as AdV, hCMV and HSV, whose infections generally persist longer (Imperiale and Jiang, 2015) , further contributing to chronic activation of inflammation when they infect the airway (Yang et al., 2008; Morimoto et al., 2009; Imperiale and Jiang, 2015; Lan et al., 2016; Tan et al., 2016; Kowalski et al., 2017) . With that note, human papilloma virus (HPV), a DNA virus highly associated with head and neck cancers and respiratory papillomatosis, is also linked with the chronic inflammation that precedes the malignancies (de Visser et al., 2005; Gillison et al., 2012; Bonomi et al., 2014; Fernandes et al., 2015) . Therefore, the role of HPV infection in causing chronic inflammation in the airway and their association to exacerbations of chronic airway inflammatory diseases, which is scarcely explored, should be investigated in the future. Furthermore, viral persistence which lead to continuous expression of antiviral genes may also lead to the development of steroid resistance, which is seen with RV, RSV, and PIV infection (Chi et al., 2011; Ford et al., 2013; Papi et al., 2013) . The use of steroid to suppress the inflammation may also cause the virus to linger longer in the airway due to the lack of antiviral clearance (Kim et al., 2008; Hammond et al., 2015; Hewitt et al., 2016; McKendry et al., 2016; Singanayagam et al., 2019b) . The concomitant development of steroid resistance together with recurring or prolong viral infection thus added considerable burden to the management of acute exacerbation, which should be the future focus of research to resolve the dual complications arising from viral infection.
On the other end of the spectrum, viruses that induce strong type 1 inflammation and cell death such as IFV (Yan et al., 2016; Guibas et al., 2018) and certain CoV (including the recently emerged COVID-19 virus) (Tao et al., 2013; Yue et al., 2018; Zhu et al., 2020) , may not cause prolonged inflammation due to strong induction of antiviral clearance. These infections, however, cause massive damage and cell death to the epithelial barrier, so much so that areas of the epithelium may be completely absent post infection (Yan et al., 2016; Tan et al., 2019) . Factors such as RANTES and CXCL10, which recruit immune cells to induce apoptosis, are strongly induced from IFV infected epithelium (Ampomah et al., 2018; Tan et al., 2019) . Additionally, necroptotic factors such as RIP3 further compounds the cell deaths in IFV infected epithelium . The massive cell death induced may result in worsening of the acute exacerbation due to the release of their cellular content into the airway, further evoking an inflammatory response in the airway (Guibas et al., 2018) . Moreover, the destruction of the epithelial barrier may cause further contact with other pathogens and allergens in the airway which may then prolong exacerbations or results in new exacerbations. Epithelial destruction may also promote further epithelial remodeling during its regeneration as viral infection induces the expression of remodeling genes such as MMPs and growth factors . Infections that cause massive destruction of the epithelium, such as IFV, usually result in severe acute exacerbations with non-classical symptoms of chronic airway inflammatory diseases. Fortunately, annual vaccines are available to prevent IFV infections (Vasileiou et al., 2017; Zheng et al., 2018) ; and it is recommended that patients with chronic airway inflammatory disease receive their annual influenza vaccination as the best means to prevent severe IFV induced exacerbation.
Another mechanism that viral infections may use to drive acute exacerbations is the induction of vasodilation or tight junction opening factors which may increase the rate of infiltration. Infection with a multitude of respiratory viruses causes disruption of tight junctions with the resulting increased rate of viral infiltration. This also increases the chances of allergens coming into contact with airway immune cells. For example, IFV infection was found to induce oncostatin M (OSM) which causes tight junction opening (Pothoven et al., 2015; Tian et al., 2018) . Similarly, RV and RSV infections usually cause tight junction opening which may also increase the infiltration rate of eosinophils and thus worsening of the classical symptoms of chronic airway inflammatory diseases (Sajjan et al., 2008; Kast et al., 2017; Kim et al., 2018) . In addition, the expression of vasodilating factors and fluid homeostatic factors such as angiopoietin-like 4 (ANGPTL4) and bactericidal/permeabilityincreasing fold-containing family member A1 (BPIFA1) are also associated with viral infections and pneumonia development, which may worsen inflammation in the lower airway Akram et al., 2018) . These factors may serve as targets to prevent viral-induced exacerbations during the management of acute exacerbation of chronic airway inflammatory diseases.
Another recent area of interest is the relationship between asthma and COPD exacerbations and their association with the airway microbiome. The development of chronic airway inflammatory diseases is usually linked to specific bacterial species in the microbiome which may thrive in the inflamed airway environment (Diver et al., 2019) . In the event of a viral infection such as RV infection, the effect induced by the virus may destabilize the equilibrium of the microbiome present (Molyneaux et al., 2013; Kloepfer et al., 2014; Kloepfer et al., 2017; Jubinville et al., 2018; van Rijn et al., 2019) . In addition, viral infection may disrupt biofilm colonies in the upper airway (e.g., Streptococcus pneumoniae) microbiome to be release into the lower airway and worsening the inflammation (Marks et al., 2013; Chao et al., 2014) . Moreover, a viral infection may also alter the nutrient profile in the airway through release of previously inaccessible nutrients that will alter bacterial growth (Siegel et al., 2014; Mallia et al., 2018) . Furthermore, the destabilization is further compounded by impaired bacterial immune response, either from direct viral influences, or use of corticosteroids to suppress the exacerbation symptoms (Singanayagam et al., 2018 (Singanayagam et al., , 2019a Wang et al., 2018; Finney et al., 2019) . All these may gradually lead to more far reaching effect when normal flora is replaced with opportunistic pathogens, altering the inflammatory profiles (Teo et al., 2018) . These changes may in turn result in more severe and frequent acute exacerbations due to the interplay between virus and pathogenic bacteria in exacerbating chronic airway inflammatory diseases (Wark et al., 2013; Singanayagam et al., 2018) . To counteract these effects, microbiome-based therapies are in their infancy but have shown efficacy in the treatments of irritable bowel syndrome by restoring the intestinal microbiome (Bakken et al., 2011) . Further research can be done similarly for the airway microbiome to be able to restore the microbiome following disruption by a viral infection.
Viral infections can cause the disruption of mucociliary function, an important component of the epithelial barrier. Ciliary proteins FIGURE 2 | Changes in the upper airway epithelium contributing to viral exacerbation in chronic airway inflammatory diseases. The upper airway epithelium is the primary contact/infection site of most respiratory viruses. Therefore, its infection by respiratory viruses may have far reaching consequences in augmenting and synergizing current and future acute exacerbations. The destruction of epithelial barrier, mucociliary function and cell death of the epithelial cells serves to increase contact between environmental triggers with the lower airway and resident immune cells. The opening of tight junction increasing the leakiness further augments the inflammation and exacerbations. In addition, viral infections are usually accompanied with oxidative stress which will further increase the local inflammation in the airway. The dysregulation of inflammation can be further compounded by modulation of miRNAs and epigenetic modification such as DNA methylation and histone modifications that promote dysregulation in inflammation. Finally, the change in the local airway environment and inflammation promotes growth of pathogenic bacteria that may replace the airway microbiome. Furthermore, the inflammatory environment may also disperse upper airway commensals into the lower airway, further causing inflammation and alteration of the lower airway environment, resulting in prolong exacerbation episodes following viral infection.
Viral specific trait contributing to exacerbation mechanism (with literature evidence) Oxidative stress ROS production (RV, RSV, IFV, HSV)
As RV, RSV, and IFV were the most frequently studied viruses in chronic airway inflammatory diseases, most of the viruses listed are predominantly these viruses. However, the mechanisms stated here may also be applicable to other viruses but may not be listed as they were not implicated in the context of chronic airway inflammatory diseases exacerbation (see text for abbreviations).
that aid in the proper function of the motile cilia in the airways are aberrantly expressed in ciliated airway epithelial cells which are the major target for RV infection (Griggs et al., 2017) . Such form of secondary cilia dyskinesia appears to be present with chronic inflammations in the airway, but the exact mechanisms are still unknown (Peng et al., , 2019 Qiu et al., 2018) . Nevertheless, it was found that in viral infection such as IFV, there can be a change in the metabolism of the cells as well as alteration in the ciliary gene expression, mostly in the form of down-regulation of the genes such as dynein axonemal heavy chain 5 (DNAH5) and multiciliate differentiation And DNA synthesis associated cell cycle protein (MCIDAS) (Tan et al., 2018b . The recently emerged Wuhan CoV was also found to reduce ciliary beating in infected airway epithelial cell model (Zhu et al., 2020) . Furthermore, viral infections such as RSV was shown to directly destroy the cilia of the ciliated cells and almost all respiratory viruses infect the ciliated cells (Jumat et al., 2015; Yan et al., 2016; Tan et al., 2018a) . In addition, mucus overproduction may also disrupt the equilibrium of the mucociliary function following viral infection, resulting in symptoms of acute exacerbation (Zhu et al., 2009) . Hence, the disruption of the ciliary movement during viral infection may cause more foreign material and allergen to enter the airway, aggravating the symptoms of acute exacerbation and making it more difficult to manage. The mechanism of the occurrence of secondary cilia dyskinesia can also therefore be explored as a means to limit the effects of viral induced acute exacerbation.
MicroRNAs (miRNAs) are short non-coding RNAs involved in post-transcriptional modulation of biological processes, and implicated in a number of diseases (Tan et al., 2014) . miRNAs are found to be induced by viral infections and may play a role in the modulation of antiviral responses and inflammation (Gutierrez et al., 2016; Deng et al., 2017; Feng et al., 2018) . In the case of chronic airway inflammatory diseases, circulating miRNA changes were found to be linked to exacerbation of the diseases (Wardzynska et al., 2020) . Therefore, it is likely that such miRNA changes originated from the infected epithelium and responding immune cells, which may serve to further dysregulate airway inflammation leading to exacerbations. Both IFV and RSV infections has been shown to increase miR-21 and augmented inflammation in experimental murine asthma models, which is reversed with a combination treatment of anti-miR-21 and corticosteroids (Kim et al., 2017) . IFV infection is also shown to increase miR-125a and b, and miR-132 in COPD epithelium which inhibits A20 and MAVS; and p300 and IRF3, respectively, resulting in increased susceptibility to viral infections (Hsu et al., 2016 (Hsu et al., , 2017 . Conversely, miR-22 was shown to be suppressed in asthmatic epithelium in IFV infection which lead to aberrant epithelial response, contributing to exacerbations (Moheimani et al., 2018) . Other than these direct evidence of miRNA changes in contributing to exacerbations, an increased number of miRNAs and other non-coding RNAs responsible for immune modulation are found to be altered following viral infections (Globinska et al., 2014; Feng et al., 2018; Hasegawa et al., 2018) . Hence non-coding RNAs also presents as targets to modulate viral induced airway changes as a means of managing exacerbation of chronic airway inflammatory diseases. Other than miRNA modulation, other epigenetic modification such as DNA methylation may also play a role in exacerbation of chronic airway inflammatory diseases. Recent epigenetic studies have indicated the association of epigenetic modification and chronic airway inflammatory diseases, and that the nasal methylome was shown to be a sensitive marker for airway inflammatory changes (Cardenas et al., 2019; Gomez, 2019) . At the same time, it was also shown that viral infections such as RV and RSV alters DNA methylation and histone modifications in the airway epithelium which may alter inflammatory responses, driving chronic airway inflammatory diseases and exacerbations (McErlean et al., 2014; Pech et al., 2018; Caixia et al., 2019) . In addition, Spalluto et al. (2017) also showed that antiviral factors such as IFNγ epigenetically modifies the viral resistance of epithelial cells. Hence, this may indicate that infections such as RV and RSV that weakly induce antiviral responses may result in an altered inflammatory state contributing to further viral persistence and exacerbation of chronic airway inflammatory diseases (Spalluto et al., 2017) .
Finally, viral infection can result in enhanced production of reactive oxygen species (ROS), oxidative stress and mitochondrial dysfunction in the airway epithelium (Kim et al., 2018; Mishra et al., 2018; Wang et al., 2018) . The airway epithelium of patients with chronic airway inflammatory diseases are usually under a state of constant oxidative stress which sustains the inflammation in the airway (Barnes, 2017; van der Vliet et al., 2018) . Viral infections of the respiratory epithelium by viruses such as IFV, RV, RSV and HSV may trigger the further production of ROS as an antiviral mechanism Aizawa et al., 2018; Wang et al., 2018) . Moreover, infiltrating cells in response to the infection such as neutrophils will also trigger respiratory burst as a means of increasing the ROS in the infected region. The increased ROS and oxidative stress in the local environment may serve as a trigger to promote inflammation thereby aggravating the inflammation in the airway (Tiwari et al., 2002) . A summary of potential exacerbation mechanisms and the associated viruses is shown in Figure 2 and Table 1 .
While the mechanisms underlying the development and acute exacerbation of chronic airway inflammatory disease is extensively studied for ways to manage and control the disease, a viral infection does more than just causing an acute exacerbation in these patients. A viral-induced acute exacerbation not only induced and worsens the symptoms of the disease, but also may alter the management of the disease or confer resistance toward treatments that worked before. Hence, appreciation of the mechanisms of viral-induced acute exacerbations is of clinical significance to devise strategies to correct viral induce changes that may worsen chronic airway inflammatory disease symptoms. Further studies in natural exacerbations and in viral-challenge models using RNA-sequencing (RNA-seq) or single cell RNA-seq on a range of time-points may provide important information regarding viral pathogenesis and changes induced within the airway of chronic airway inflammatory disease patients to identify novel targets and pathway for improved management of the disease. Subsequent analysis of functions may use epithelial cell models such as the air-liquid interface, in vitro airway epithelial model that has been adapted to studying viral infection and the changes it induced in the airway (Yan et al., 2016; Boda et al., 2018; Tan et al., 2018a) . Animal-based diseased models have also been developed to identify systemic mechanisms of acute exacerbation (Shin, 2016; Gubernatorova et al., 2019; Tanner and Single, 2019) . Furthermore, the humanized mouse model that possess human immune cells may also serves to unravel the immune profile of a viral infection in healthy and diseased condition (Ito et al., 2019; Li and Di Santo, 2019) . For milder viruses, controlled in vivo human infections can be performed for the best mode of verification of the associations of the virus with the proposed mechanism of viral induced acute exacerbations . With the advent of suitable diseased models, the verification of the mechanisms will then provide the necessary continuation of improving the management of viral induced acute exacerbations.
In conclusion, viral-induced acute exacerbation of chronic airway inflammatory disease is a significant health and economic burden that needs to be addressed urgently. In view of the scarcity of antiviral-based preventative measures available for only a few viruses and vaccines that are only available for IFV infections, more alternative measures should be explored to improve the management of the disease. Alternative measures targeting novel viral-induced acute exacerbation mechanisms, especially in the upper airway, can serve as supplementary treatments of the currently available management strategies to augment their efficacy. New models including primary human bronchial or nasal epithelial cell cultures, organoids or precision cut lung slices from patients with airways disease rather than healthy subjects can be utilized to define exacerbation mechanisms. These mechanisms can then be validated in small clinical trials in patients with asthma or COPD. Having multiple means of treatment may also reduce the problems that arise from resistance development toward a specific treatment. | What is consolidated in this review? | false | 3,861 | {
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185 | CDC Summary 21 MAR 2020,
https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/summary.html
This is a rapidly evolving situation and CDC will provide updated information and guidance as it becomes available.
Updated March 21, 2020
CDC is responding to a pandemic of respiratory disease spreading from person-to-person caused by a novel (new) coronavirus. The disease has been named “coronavirus disease 2019” (abbreviated “COVID-19”). This situation poses a serious public health risk. The federal government is working closely with state, local, tribal, and territorial partners, as well as public health partners, to respond to this situation. COVID-19 can cause mild to severe illness; most severe illness occurs in older adults.
Situation in U.S.
Different parts of the country are seeing different levels of COVID-19 activity. The United States nationally is in the initiation phase of the pandemic. States in which community spread is occurring are in the acceleration phase. The duration and severity of each pandemic phase can vary depending on the characteristics of the virus and the public health response.
CDC and state and local public health laboratories are testing for the virus that causes COVID-19. View CDC’s Public Health Laboratory Testing map.
All 50 states have reported cases of COVID-19 to CDC.
U.S. COVID-19 cases include:
Imported cases in travelers
Cases among close contacts of a known case
Community-acquired cases where the source of the infection is unknown.
Twenty-seven U.S. states are reporting some community spread of COVID-19.
View latest case counts, deaths, and a map of states with reported cases.
CDC Recommends
Everyone can do their part to help us respond to this emerging public health threat:
On March 16, the White House announced a program called “15 Days to Slow the Spread,”pdf iconexternal icon which is a nationwide effort to slow the spread of COVID-19 through the implementation of social distancing at all levels of society.
Older people and people with severe chronic conditions should take special precautions because they are at higher risk of developing serious COVID-19 illness.
If you are a healthcare provider, use your judgment to determine if a patient has signs and symptoms compatible with COVID-19 and whether the patient should be tested. Factors to consider in addition to clinical symptoms may include:
Does the patient have recent travel from an affected area?
Has the patient been in close contact with someone with COVID-19 or with patients with pneumonia of unknown cause?
Does the patient reside in an area where there has been community spread of COVID-19?
If you are a healthcare provider or a public health responder caring for a COVID-19 patient, please take care of yourself and follow recommended infection control procedures.
People who get a fever or cough should consider whether they might have COVID-19, depending on where they live, their travel history or other exposures. More than half of the U.S. is seeing some level of community spread of COVID-19. Testing for COVID-19 may be accessed through medical providers or public health departments, but there is no treatment for this virus. Most people have mild illness and are able to recover at home without medical care.
For people who are ill with COVID-19, but are not sick enough to be hospitalized, please follow CDC guidance on how to reduce the risk of spreading your illness to others. People who are mildly ill with COVID-19 are able to isolate at home during their illness.
If you have been in China or another affected area or have been exposed to someone sick with COVID-19 in the last 14 days, you will face some limitations on your movement and activity. Please follow instructions during this time. Your cooperation is integral to the ongoing public health response to try to slow spread of this virus.
COVID-19 Emergence
COVID-19 is caused by a coronavirus. Coronaviruses are a large family of viruses that are common in people and many different species of animals, including camels, cattle, cats, and bats. Rarely, animal coronaviruses can infect people and then spread between people such as with MERS-CoV, SARS-CoV, and now with this new virus (named SARS-CoV-2).
The SARS-CoV-2 virus is a betacoronavirus, like MERS-CoV and SARS-CoV. All three of these viruses have their origins in bats. The sequences from U.S. patients are similar to the one that China initially posted, suggesting a likely single, recent emergence of this virus from an animal reservoir.
Early on, many of the patients at the epicenter of the outbreak in Wuhan, Hubei Province, China had some link to a large seafood and live animal market, suggesting animal-to-person spread. Later, a growing number of patients reportedly did not have exposure to animal markets, indicating person-to-person spread. Person-to-person spread was subsequently reported outside Hubei and in countries outside China, including in the United States. Some international destinations now have ongoing community spread with the virus that causes COVID-19, as do some parts of the United States. Community spread means some people have been infected and it is not known how or where they became exposed. Learn more about the spread of this newly emerged coronavirus.
Severity
The complete clinical picture with regard to COVID-19 is not fully known. Reported illnesses have ranged from very mild (including some with no reported symptoms) to severe, including illness resulting in death. While information so far suggests that most COVID-19 illness is mild, a reportexternal icon out of China suggests serious illness occurs in 16% of cases. Older people and people of all ages with severe chronic medical conditions — like heart disease, lung disease and diabetes, for example — seem to be at higher risk of developing serious COVID-19 illness. A CDC Morbidity & Mortality Weekly Report that looked at severity of disease among COVID-19 cases in the United States by age group found that 80% of deaths were among adults 65 years and older with the highest percentage of severe outcomes occurring in people 85 years and older.
Learn more about the symptoms associated with COVID-19.
COVID-19 Pandemic
A pandemic is a global outbreak of disease. Pandemics happen when a new virus emerges to infect people and can spread between people sustainably. Because there is little to no pre-existing immunity against the new virus, it spreads worldwide.
The virus that causes COVID-19 is infecting people and spreading easily from person-to-person. Cases have been detected in most countries worldwide and community spread is being detected in a growing number of countries. On March 11, the COVID-19 outbreak was characterized as a pandemic by the WHOexternal icon.
This is the first pandemic known to be caused by the emergence of a new coronavirus. In the past century, there have been four pandemics caused by the emergence of novel influenza viruses. As a result, most research and guidance around pandemics is specific to influenza, but the same premises can be applied to the current COVID-19 pandemic. Pandemics of respiratory disease follow a certain progression outlined in a “Pandemic Intervals Framework.” Pandemics begin with an investigation phase, followed by recognition, initiation, and acceleration phases. The peak of illnesses occurs at the end of the acceleration phase, which is followed by a deceleration phase, during which there is a decrease in illnesses. Different countries can be in different phases of the pandemic at any point in time and different parts of the same country can also be in different phases of a pandemic.
There are ongoing investigations to learn more. This is a rapidly evolving situation and information will be updated as it becomes available.
Risk Assessment
Risk depends on characteristics of the virus, including how well it spreads between people; the severity of resulting illness; and the medical or other measures available to control the impact of the virus (for example, vaccines or medications that can treat the illness) and the relative success of these. In the absence of vaccine or treatment medications, nonpharmaceutical interventions become the most important response strategy. These are community interventions that can reduce the impact of disease.
The risk from COVID-19 to Americans can be broken down into risk of exposure versus risk of serious illness and death.
Risk of exposure:
The immediate risk of being exposed to this virus is still low for most Americans, but as the outbreak expands, that risk will increase. Cases of COVID-19 and instances of community spread are being reported in a growing number of states.
People in places where ongoing community spread of the virus that causes COVID-19 has been reported are at elevated risk of exposure, with the level of risk dependent on the location.
Healthcare workers caring for patients with COVID-19 are at elevated risk of exposure.
Close contacts of persons with COVID-19 also are at elevated risk of exposure.
Travelers returning from affected international locations where community spread is occurring also are at elevated risk of exposure, with level of risk dependent on where they traveled.
Risk of Severe Illness:
Early information out of China, where COVID-19 first started, shows that some people are at higher risk of getting very sick from this illness. This includes:
Older adults, with risk increasing by age.
People who have serious chronic medical conditions like:
Heart disease
Diabetes
Lung disease
CDC has developed guidance to help in the risk assessment and management of people with potential exposures to COVID-19.
What May Happen
More cases of COVID-19 are likely to be identified in the United States in the coming days, including more instances of community spread. CDC expects that widespread transmission of COVID-19 in the United States will occur. In the coming months, most of the U.S. population will be exposed to this virus.
Widespread transmission of COVID-19 could translate into large numbers of people needing medical care at the same time. Schools, childcare centers, and workplaces, may experience more absenteeism. Mass gatherings may be sparsely attended or postponed. Public health and healthcare systems may become overloaded, with elevated rates of hospitalizations and deaths. Other critical infrastructure, such as law enforcement, emergency medical services, and sectors of the transportation industry may also be affected. Healthcare providers and hospitals may be overwhelmed. At this time, there is no vaccine to protect against COVID-19 and no medications approved to treat it. Nonpharmaceutical interventions will be the most important response strategy to try to delay the spread of the virus and reduce the impact of disease.
CDC Response
Global efforts at this time are focused concurrently on lessening the spread and impact of this virus. The federal government is working closely with state, local, tribal, and territorial partners, as well as public health partners, to respond to this public health threat.
Highlights of CDC’s Response
CDC established a COVID-19 Incident Management System on January 7, 2020. On January 21, CDC activated its Emergency Operations Center to better provide ongoing support to the COVID-19 response.
The U.S. government has taken unprecedented steps with respect to travel in response to the growing public health threat posed by this new coronavirus:
Foreign nationals who have been in China, Iran, the United Kingdom, Ireland and any one of the 26 European countries in the Schengen Area within the past 14 days cannot enter the United States.
U.S. citizens, residents, and their immediate family members who have been any one of those countries within in the past 14 days can enter the United States, but they are subject to health monitoring and possible quarantine for up to 14 days.
People at higher risk of serious COVID-19 illness avoid cruise travel and non-essential air travel.
CDC has issued additional specific travel guidance related to COVID-19.
CDC has issued clinical guidance, including:
Clinical Guidance for Management of Patients with Confirmed Coronavirus Disease (COVID-19).
Infection Prevention and Control Recommendations for Patients, including guidance on the use of personal protective equipment (PPE) during a shortage.
CDC also has issued guidance for other settings, including:
Preparing for COVID-19: Long-term Care Facilities, Nursing Homes
Discontinuation of Home Isolation for Persons with COVID-19
CDC has deployed multidisciplinary teams to support state health departments in case identification, contact tracing, clinical management, and public communications.
CDC has worked with federal partners to support the safe return of Americans overseas who have been affected by COVID-19.
An important part of CDC’s role during a public health emergency is to develop a test for the pathogen and equip state and local public health labs with testing capacity.
CDC developed an rRT-PCR test to diagnose COVID-19.
As of the evening of March 17, 89 state and local public health labs in 50 states, the District of Columbia, Guam, and Puerto Rico have successfully verified and are currently using CDC COVID-19 diagnostic tests.
Commercial manufacturers are now producing their own tests.
CDC has grown the COVID-19 virus in cell culture, which is necessary for further studies, including for additional genetic characterization. The cell-grown virus was sent to NIH’s BEI Resources Repositoryexternal icon for use by the broad scientific community.
CDC also is developing a serology test for COVID-19.
Other Available Resources
The following resources are available with information on COVID-19
World Health Organization, Coronavirusexternal icon | What should mildly-ill patients do? | false | 230 | {
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2,504 | Respiratory Viral Infections in Exacerbation of Chronic Airway Inflammatory Diseases: Novel Mechanisms and Insights From the Upper Airway Epithelium
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7052386/
SHA: 45a566c71056ba4faab425b4f7e9edee6320e4a4
Authors: Tan, Kai Sen; Lim, Rachel Liyu; Liu, Jing; Ong, Hsiao Hui; Tan, Vivian Jiayi; Lim, Hui Fang; Chung, Kian Fan; Adcock, Ian M.; Chow, Vincent T.; Wang, De Yun
Date: 2020-02-25
DOI: 10.3389/fcell.2020.00099
License: cc-by
Abstract: Respiratory virus infection is one of the major sources of exacerbation of chronic airway inflammatory diseases. These exacerbations are associated with high morbidity and even mortality worldwide. The current understanding on viral-induced exacerbations is that viral infection increases airway inflammation which aggravates disease symptoms. Recent advances in in vitro air-liquid interface 3D cultures, organoid cultures and the use of novel human and animal challenge models have evoked new understandings as to the mechanisms of viral exacerbations. In this review, we will focus on recent novel findings that elucidate how respiratory viral infections alter the epithelial barrier in the airways, the upper airway microbial environment, epigenetic modifications including miRNA modulation, and other changes in immune responses throughout the upper and lower airways. First, we reviewed the prevalence of different respiratory viral infections in causing exacerbations in chronic airway inflammatory diseases. Subsequently we also summarized how recent models have expanded our appreciation of the mechanisms of viral-induced exacerbations. Further we highlighted the importance of the virome within the airway microbiome environment and its impact on subsequent bacterial infection. This review consolidates the understanding of viral induced exacerbation in chronic airway inflammatory diseases and indicates pathways that may be targeted for more effective management of chronic inflammatory diseases.
Text: The prevalence of chronic airway inflammatory disease is increasing worldwide especially in developed nations (GBD 2015 Chronic Respiratory Disease Collaborators, 2017 Guan et al., 2018) . This disease is characterized by airway inflammation leading to complications such as coughing, wheezing and shortness of breath. The disease can manifest in both the upper airway (such as chronic rhinosinusitis, CRS) and lower airway (such as asthma and chronic obstructive pulmonary disease, COPD) which greatly affect the patients' quality of life (Calus et al., 2012; Bao et al., 2015) . Treatment and management vary greatly in efficacy due to the complexity and heterogeneity of the disease. This is further complicated by the effect of episodic exacerbations of the disease, defined as worsening of disease symptoms including wheeze, cough, breathlessness and chest tightness (Xepapadaki and Papadopoulos, 2010) . Such exacerbations are due to the effect of enhanced acute airway inflammation impacting upon and worsening the symptoms of the existing disease (Hashimoto et al., 2008; Viniol and Vogelmeier, 2018) . These acute exacerbations are the main cause of morbidity and sometimes mortality in patients, as well as resulting in major economic burdens worldwide. However, due to the complex interactions between the host and the exacerbation agents, the mechanisms of exacerbation may vary considerably in different individuals under various triggers. Acute exacerbations are usually due to the presence of environmental factors such as allergens, pollutants, smoke, cold or dry air and pathogenic microbes in the airway (Gautier and Charpin, 2017; Viniol and Vogelmeier, 2018) . These agents elicit an immune response leading to infiltration of activated immune cells that further release inflammatory mediators that cause acute symptoms such as increased mucus production, cough, wheeze and shortness of breath. Among these agents, viral infection is one of the major drivers of asthma exacerbations accounting for up to 80-90% and 45-80% of exacerbations in children and adults respectively (Grissell et al., 2005; Xepapadaki and Papadopoulos, 2010; Jartti and Gern, 2017; Adeli et al., 2019) . Viral involvement in COPD exacerbation is also equally high, having been detected in 30-80% of acute COPD exacerbations (Kherad et al., 2010; Jafarinejad et al., 2017; Stolz et al., 2019) . Whilst the prevalence of viral exacerbations in CRS is still unclear, its prevalence is likely to be high due to the similar inflammatory nature of these diseases (Rowan et al., 2015; Tan et al., 2017) . One of the reasons for the involvement of respiratory viruses' in exacerbations is their ease of transmission and infection (Kutter et al., 2018) . In addition, the high diversity of the respiratory viruses may also contribute to exacerbations of different nature and severity (Busse et al., 2010; Costa et al., 2014; Jartti and Gern, 2017) . Hence, it is important to identify the exact mechanisms underpinning viral exacerbations in susceptible subjects in order to properly manage exacerbations via supplementary treatments that may alleviate the exacerbation symptoms or prevent severe exacerbations.
While the lower airway is the site of dysregulated inflammation in most chronic airway inflammatory diseases, the upper airway remains the first point of contact with sources of exacerbation. Therefore, their interaction with the exacerbation agents may directly contribute to the subsequent responses in the lower airway, in line with the "United Airway" hypothesis. To elucidate the host airway interaction with viruses leading to exacerbations, we thus focus our review on recent findings of viral interaction with the upper airway. We compiled how viral induced changes to the upper airway may contribute to chronic airway inflammatory disease exacerbations, to provide a unified elucidation of the potential exacerbation mechanisms initiated from predominantly upper airway infections.
Despite being a major cause of exacerbation, reports linking respiratory viruses to acute exacerbations only start to emerge in the late 1950s (Pattemore et al., 1992) ; with bacterial infections previously considered as the likely culprit for acute exacerbation (Stevens, 1953; Message and Johnston, 2002) . However, with the advent of PCR technology, more viruses were recovered during acute exacerbations events and reports implicating their role emerged in the late 1980s (Message and Johnston, 2002) . Rhinovirus (RV) and respiratory syncytial virus (RSV) are the predominant viruses linked to the development and exacerbation of chronic airway inflammatory diseases (Jartti and Gern, 2017) . Other viruses such as parainfluenza virus (PIV), influenza virus (IFV) and adenovirus (AdV) have also been implicated in acute exacerbations but to a much lesser extent (Johnston et al., 2005; Oliver et al., 2014; Ko et al., 2019) . More recently, other viruses including bocavirus (BoV), human metapneumovirus (HMPV), certain coronavirus (CoV) strains, a specific enterovirus (EV) strain EV-D68, human cytomegalovirus (hCMV) and herpes simplex virus (HSV) have been reported as contributing to acute exacerbations . The common feature these viruses share is that they can infect both the upper and/or lower airway, further increasing the inflammatory conditions in the diseased airway (Mallia and Johnston, 2006; Britto et al., 2017) .
Respiratory viruses primarily infect and replicate within airway epithelial cells . During the replication process, the cells release antiviral factors and cytokines that alter local airway inflammation and airway niche (Busse et al., 2010) . In a healthy airway, the inflammation normally leads to type 1 inflammatory responses consisting of activation of an antiviral state and infiltration of antiviral effector cells. This eventually results in the resolution of the inflammatory response and clearance of the viral infection (Vareille et al., 2011; Braciale et al., 2012) . However, in a chronically inflamed airway, the responses against the virus may be impaired or aberrant, causing sustained inflammation and erroneous infiltration, resulting in the exacerbation of their symptoms (Mallia and Johnston, 2006; Dougherty and Fahy, 2009; Busse et al., 2010; Britto et al., 2017; Linden et al., 2019) . This is usually further compounded by the increased susceptibility of chronic airway inflammatory disease patients toward viral respiratory infections, thereby increasing the frequency of exacerbation as a whole (Dougherty and Fahy, 2009; Busse et al., 2010; Linden et al., 2019) . Furthermore, due to the different replication cycles and response against the myriad of respiratory viruses, each respiratory virus may also contribute to exacerbations via different mechanisms that may alter their severity. Hence, this review will focus on compiling and collating the current known mechanisms of viral-induced exacerbation of chronic airway inflammatory diseases; as well as linking the different viral infection pathogenesis to elucidate other potential ways the infection can exacerbate the disease. The review will serve to provide further understanding of viral induced exacerbation to identify potential pathways and pathogenesis mechanisms that may be targeted as supplementary care for management and prevention of exacerbation. Such an approach may be clinically significant due to the current scarcity of antiviral drugs for the management of viral-induced exacerbations. This will improve the quality of life of patients with chronic airway inflammatory diseases.
Once the link between viral infection and acute exacerbations of chronic airway inflammatory disease was established, there have been many reports on the mechanisms underlying the exacerbation induced by respiratory viral infection. Upon infecting the host, viruses evoke an inflammatory response as a means of counteracting the infection. Generally, infected airway epithelial cells release type I (IFNα/β) and type III (IFNλ) interferons, cytokines and chemokines such as IL-6, IL-8, IL-12, RANTES, macrophage inflammatory protein 1α (MIP-1α) and monocyte chemotactic protein 1 (MCP-1) (Wark and Gibson, 2006; Matsukura et al., 2013) . These, in turn, enable infiltration of innate immune cells and of professional antigen presenting cells (APCs) that will then in turn release specific mediators to facilitate viral targeting and clearance, including type II interferon (IFNγ), IL-2, IL-4, IL-5, IL-9, and IL-12 (Wark and Gibson, 2006; Singh et al., 2010; Braciale et al., 2012) . These factors heighten local inflammation and the infiltration of granulocytes, T-cells and B-cells (Wark and Gibson, 2006; Braciale et al., 2012) . The increased inflammation, in turn, worsens the symptoms of airway diseases.
Additionally, in patients with asthma and patients with CRS with nasal polyp (CRSwNP), viral infections such as RV and RSV promote a Type 2-biased immune response (Becker, 2006; Jackson et al., 2014; Jurak et al., 2018) . This amplifies the basal type 2 inflammation resulting in a greater release of IL-4, IL-5, IL-13, RANTES and eotaxin and a further increase in eosinophilia, a key pathological driver of asthma and CRSwNP (Wark and Gibson, 2006; Singh et al., 2010; Chung et al., 2015; Dunican and Fahy, 2015) . Increased eosinophilia, in turn, worsens the classical symptoms of disease and may further lead to life-threatening conditions due to breathing difficulties. On the other hand, patients with COPD and patients with CRS without nasal polyp (CRSsNP) are more neutrophilic in nature due to the expression of neutrophil chemoattractants such as CXCL9, CXCL10, and CXCL11 (Cukic et al., 2012; Brightling and Greening, 2019) . The pathology of these airway diseases is characterized by airway remodeling due to the presence of remodeling factors such as matrix metalloproteinases (MMPs) released from infiltrating neutrophils (Linden et al., 2019) . Viral infections in such conditions will then cause increase neutrophilic activation; worsening the symptoms and airway remodeling in the airway thereby exacerbating COPD, CRSsNP and even CRSwNP in certain cases (Wang et al., 2009; Tacon et al., 2010; Linden et al., 2019) .
An epithelial-centric alarmin pathway around IL-25, IL-33 and thymic stromal lymphopoietin (TSLP), and their interaction with group 2 innate lymphoid cells (ILC2) has also recently been identified (Nagarkar et al., 2012; Hong et al., 2018; Allinne et al., 2019) . IL-25, IL-33 and TSLP are type 2 inflammatory cytokines expressed by the epithelial cells upon injury to the epithelial barrier (Gabryelska et al., 2019; Roan et al., 2019) . ILC2s are a group of lymphoid cells lacking both B and T cell receptors but play a crucial role in secreting type 2 cytokines to perpetuate type 2 inflammation when activated (Scanlon and McKenzie, 2012; Li and Hendriks, 2013) . In the event of viral infection, cell death and injury to the epithelial barrier will also induce the expression of IL-25, IL-33 and TSLP, with heighten expression in an inflamed airway (Allakhverdi et al., 2007; Goldsmith et al., 2012; Byers et al., 2013; Shaw et al., 2013; Beale et al., 2014; Jackson et al., 2014; Uller and Persson, 2018; Ravanetti et al., 2019) . These 3 cytokines then work in concert to activate ILC2s to further secrete type 2 cytokines IL-4, IL-5, and IL-13 which further aggravate the type 2 inflammation in the airway causing acute exacerbation (Camelo et al., 2017) . In the case of COPD, increased ILC2 activation, which retain the capability of differentiating to ILC1, may also further augment the neutrophilic response and further aggravate the exacerbation (Silver et al., 2016) . Interestingly, these factors are not released to any great extent and do not activate an ILC2 response during viral infection in healthy individuals (Yan et al., 2016; Tan et al., 2018a) ; despite augmenting a type 2 exacerbation in chronically inflamed airways (Jurak et al., 2018) . These classical mechanisms of viral induced acute exacerbations are summarized in Figure 1 .
As integration of the virology, microbiology and immunology of viral infection becomes more interlinked, additional factors and FIGURE 1 | Current understanding of viral induced exacerbation of chronic airway inflammatory diseases. Upon virus infection in the airway, antiviral state will be activated to clear the invading pathogen from the airway. Immune response and injury factors released from the infected epithelium normally would induce a rapid type 1 immunity that facilitates viral clearance. However, in the inflamed airway, the cytokines and chemokines released instead augmented the inflammation present in the chronically inflamed airway, strengthening the neutrophilic infiltration in COPD airway, and eosinophilic infiltration in the asthmatic airway. The effect is also further compounded by the participation of Th1 and ILC1 cells in the COPD airway; and Th2 and ILC2 cells in the asthmatic airway.
Frontiers in Cell and Developmental Biology | www.frontiersin.org mechanisms have been implicated in acute exacerbations during and after viral infection (Murray et al., 2006) . Murray et al. (2006) has underlined the synergistic effect of viral infection with other sensitizing agents in causing more severe acute exacerbations in the airway. This is especially true when not all exacerbation events occurred during the viral infection but may also occur well after viral clearance (Kim et al., 2008; Stolz et al., 2019) in particular the late onset of a bacterial infection (Singanayagam et al., 2018 (Singanayagam et al., , 2019a . In addition, viruses do not need to directly infect the lower airway to cause an acute exacerbation, as the nasal epithelium remains the primary site of most infections. Moreover, not all viral infections of the airway will lead to acute exacerbations, suggesting a more complex interplay between the virus and upper airway epithelium which synergize with the local airway environment in line with the "united airway" hypothesis (Kurai et al., 2013) . On the other hand, viral infections or their components persist in patients with chronic airway inflammatory disease (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Hence, their presence may further alter the local environment and contribute to current and future exacerbations. Future studies should be performed using metagenomics in addition to PCR analysis to determine the contribution of the microbiome and mycobiome to viral infections. In this review, we highlight recent data regarding viral interactions with the airway epithelium that could also contribute to, or further aggravate, acute exacerbations of chronic airway inflammatory diseases.
Patients with chronic airway inflammatory diseases have impaired or reduced ability of viral clearance (Hammond et al., 2015; McKendry et al., 2016; Akbarshahi et al., 2018; Gill et al., 2018; Wang et al., 2018; Singanayagam et al., 2019b) . Their impairment stems from a type 2-skewed inflammatory response which deprives the airway of important type 1 responsive CD8 cells that are responsible for the complete clearance of virusinfected cells (Becker, 2006; McKendry et al., 2016) . This is especially evident in weak type 1 inflammation-inducing viruses such as RV and RSV (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Additionally, there are also evidence of reduced type I (IFNβ) and III (IFNλ) interferon production due to type 2-skewed inflammation, which contributes to imperfect clearance of the virus resulting in persistence of viral components, or the live virus in the airway epithelium (Contoli et al., 2006; Hwang et al., 2019; Wark, 2019) . Due to the viral components remaining in the airway, antiviral genes such as type I interferons, inflammasome activating factors and cytokines remained activated resulting in prolong airway inflammation (Wood et al., 2011; Essaidi-Laziosi et al., 2018) . These factors enhance granulocyte infiltration thus prolonging the exacerbation symptoms. Such persistent inflammation may also be found within DNA viruses such as AdV, hCMV and HSV, whose infections generally persist longer (Imperiale and Jiang, 2015) , further contributing to chronic activation of inflammation when they infect the airway (Yang et al., 2008; Morimoto et al., 2009; Imperiale and Jiang, 2015; Lan et al., 2016; Tan et al., 2016; Kowalski et al., 2017) . With that note, human papilloma virus (HPV), a DNA virus highly associated with head and neck cancers and respiratory papillomatosis, is also linked with the chronic inflammation that precedes the malignancies (de Visser et al., 2005; Gillison et al., 2012; Bonomi et al., 2014; Fernandes et al., 2015) . Therefore, the role of HPV infection in causing chronic inflammation in the airway and their association to exacerbations of chronic airway inflammatory diseases, which is scarcely explored, should be investigated in the future. Furthermore, viral persistence which lead to continuous expression of antiviral genes may also lead to the development of steroid resistance, which is seen with RV, RSV, and PIV infection (Chi et al., 2011; Ford et al., 2013; Papi et al., 2013) . The use of steroid to suppress the inflammation may also cause the virus to linger longer in the airway due to the lack of antiviral clearance (Kim et al., 2008; Hammond et al., 2015; Hewitt et al., 2016; McKendry et al., 2016; Singanayagam et al., 2019b) . The concomitant development of steroid resistance together with recurring or prolong viral infection thus added considerable burden to the management of acute exacerbation, which should be the future focus of research to resolve the dual complications arising from viral infection.
On the other end of the spectrum, viruses that induce strong type 1 inflammation and cell death such as IFV (Yan et al., 2016; Guibas et al., 2018) and certain CoV (including the recently emerged COVID-19 virus) (Tao et al., 2013; Yue et al., 2018; Zhu et al., 2020) , may not cause prolonged inflammation due to strong induction of antiviral clearance. These infections, however, cause massive damage and cell death to the epithelial barrier, so much so that areas of the epithelium may be completely absent post infection (Yan et al., 2016; Tan et al., 2019) . Factors such as RANTES and CXCL10, which recruit immune cells to induce apoptosis, are strongly induced from IFV infected epithelium (Ampomah et al., 2018; Tan et al., 2019) . Additionally, necroptotic factors such as RIP3 further compounds the cell deaths in IFV infected epithelium . The massive cell death induced may result in worsening of the acute exacerbation due to the release of their cellular content into the airway, further evoking an inflammatory response in the airway (Guibas et al., 2018) . Moreover, the destruction of the epithelial barrier may cause further contact with other pathogens and allergens in the airway which may then prolong exacerbations or results in new exacerbations. Epithelial destruction may also promote further epithelial remodeling during its regeneration as viral infection induces the expression of remodeling genes such as MMPs and growth factors . Infections that cause massive destruction of the epithelium, such as IFV, usually result in severe acute exacerbations with non-classical symptoms of chronic airway inflammatory diseases. Fortunately, annual vaccines are available to prevent IFV infections (Vasileiou et al., 2017; Zheng et al., 2018) ; and it is recommended that patients with chronic airway inflammatory disease receive their annual influenza vaccination as the best means to prevent severe IFV induced exacerbation.
Another mechanism that viral infections may use to drive acute exacerbations is the induction of vasodilation or tight junction opening factors which may increase the rate of infiltration. Infection with a multitude of respiratory viruses causes disruption of tight junctions with the resulting increased rate of viral infiltration. This also increases the chances of allergens coming into contact with airway immune cells. For example, IFV infection was found to induce oncostatin M (OSM) which causes tight junction opening (Pothoven et al., 2015; Tian et al., 2018) . Similarly, RV and RSV infections usually cause tight junction opening which may also increase the infiltration rate of eosinophils and thus worsening of the classical symptoms of chronic airway inflammatory diseases (Sajjan et al., 2008; Kast et al., 2017; Kim et al., 2018) . In addition, the expression of vasodilating factors and fluid homeostatic factors such as angiopoietin-like 4 (ANGPTL4) and bactericidal/permeabilityincreasing fold-containing family member A1 (BPIFA1) are also associated with viral infections and pneumonia development, which may worsen inflammation in the lower airway Akram et al., 2018) . These factors may serve as targets to prevent viral-induced exacerbations during the management of acute exacerbation of chronic airway inflammatory diseases.
Another recent area of interest is the relationship between asthma and COPD exacerbations and their association with the airway microbiome. The development of chronic airway inflammatory diseases is usually linked to specific bacterial species in the microbiome which may thrive in the inflamed airway environment (Diver et al., 2019) . In the event of a viral infection such as RV infection, the effect induced by the virus may destabilize the equilibrium of the microbiome present (Molyneaux et al., 2013; Kloepfer et al., 2014; Kloepfer et al., 2017; Jubinville et al., 2018; van Rijn et al., 2019) . In addition, viral infection may disrupt biofilm colonies in the upper airway (e.g., Streptococcus pneumoniae) microbiome to be release into the lower airway and worsening the inflammation (Marks et al., 2013; Chao et al., 2014) . Moreover, a viral infection may also alter the nutrient profile in the airway through release of previously inaccessible nutrients that will alter bacterial growth (Siegel et al., 2014; Mallia et al., 2018) . Furthermore, the destabilization is further compounded by impaired bacterial immune response, either from direct viral influences, or use of corticosteroids to suppress the exacerbation symptoms (Singanayagam et al., 2018 (Singanayagam et al., , 2019a Wang et al., 2018; Finney et al., 2019) . All these may gradually lead to more far reaching effect when normal flora is replaced with opportunistic pathogens, altering the inflammatory profiles (Teo et al., 2018) . These changes may in turn result in more severe and frequent acute exacerbations due to the interplay between virus and pathogenic bacteria in exacerbating chronic airway inflammatory diseases (Wark et al., 2013; Singanayagam et al., 2018) . To counteract these effects, microbiome-based therapies are in their infancy but have shown efficacy in the treatments of irritable bowel syndrome by restoring the intestinal microbiome (Bakken et al., 2011) . Further research can be done similarly for the airway microbiome to be able to restore the microbiome following disruption by a viral infection.
Viral infections can cause the disruption of mucociliary function, an important component of the epithelial barrier. Ciliary proteins FIGURE 2 | Changes in the upper airway epithelium contributing to viral exacerbation in chronic airway inflammatory diseases. The upper airway epithelium is the primary contact/infection site of most respiratory viruses. Therefore, its infection by respiratory viruses may have far reaching consequences in augmenting and synergizing current and future acute exacerbations. The destruction of epithelial barrier, mucociliary function and cell death of the epithelial cells serves to increase contact between environmental triggers with the lower airway and resident immune cells. The opening of tight junction increasing the leakiness further augments the inflammation and exacerbations. In addition, viral infections are usually accompanied with oxidative stress which will further increase the local inflammation in the airway. The dysregulation of inflammation can be further compounded by modulation of miRNAs and epigenetic modification such as DNA methylation and histone modifications that promote dysregulation in inflammation. Finally, the change in the local airway environment and inflammation promotes growth of pathogenic bacteria that may replace the airway microbiome. Furthermore, the inflammatory environment may also disperse upper airway commensals into the lower airway, further causing inflammation and alteration of the lower airway environment, resulting in prolong exacerbation episodes following viral infection.
Viral specific trait contributing to exacerbation mechanism (with literature evidence) Oxidative stress ROS production (RV, RSV, IFV, HSV)
As RV, RSV, and IFV were the most frequently studied viruses in chronic airway inflammatory diseases, most of the viruses listed are predominantly these viruses. However, the mechanisms stated here may also be applicable to other viruses but may not be listed as they were not implicated in the context of chronic airway inflammatory diseases exacerbation (see text for abbreviations).
that aid in the proper function of the motile cilia in the airways are aberrantly expressed in ciliated airway epithelial cells which are the major target for RV infection (Griggs et al., 2017) . Such form of secondary cilia dyskinesia appears to be present with chronic inflammations in the airway, but the exact mechanisms are still unknown (Peng et al., , 2019 Qiu et al., 2018) . Nevertheless, it was found that in viral infection such as IFV, there can be a change in the metabolism of the cells as well as alteration in the ciliary gene expression, mostly in the form of down-regulation of the genes such as dynein axonemal heavy chain 5 (DNAH5) and multiciliate differentiation And DNA synthesis associated cell cycle protein (MCIDAS) (Tan et al., 2018b . The recently emerged Wuhan CoV was also found to reduce ciliary beating in infected airway epithelial cell model (Zhu et al., 2020) . Furthermore, viral infections such as RSV was shown to directly destroy the cilia of the ciliated cells and almost all respiratory viruses infect the ciliated cells (Jumat et al., 2015; Yan et al., 2016; Tan et al., 2018a) . In addition, mucus overproduction may also disrupt the equilibrium of the mucociliary function following viral infection, resulting in symptoms of acute exacerbation (Zhu et al., 2009) . Hence, the disruption of the ciliary movement during viral infection may cause more foreign material and allergen to enter the airway, aggravating the symptoms of acute exacerbation and making it more difficult to manage. The mechanism of the occurrence of secondary cilia dyskinesia can also therefore be explored as a means to limit the effects of viral induced acute exacerbation.
MicroRNAs (miRNAs) are short non-coding RNAs involved in post-transcriptional modulation of biological processes, and implicated in a number of diseases (Tan et al., 2014) . miRNAs are found to be induced by viral infections and may play a role in the modulation of antiviral responses and inflammation (Gutierrez et al., 2016; Deng et al., 2017; Feng et al., 2018) . In the case of chronic airway inflammatory diseases, circulating miRNA changes were found to be linked to exacerbation of the diseases (Wardzynska et al., 2020) . Therefore, it is likely that such miRNA changes originated from the infected epithelium and responding immune cells, which may serve to further dysregulate airway inflammation leading to exacerbations. Both IFV and RSV infections has been shown to increase miR-21 and augmented inflammation in experimental murine asthma models, which is reversed with a combination treatment of anti-miR-21 and corticosteroids (Kim et al., 2017) . IFV infection is also shown to increase miR-125a and b, and miR-132 in COPD epithelium which inhibits A20 and MAVS; and p300 and IRF3, respectively, resulting in increased susceptibility to viral infections (Hsu et al., 2016 (Hsu et al., , 2017 . Conversely, miR-22 was shown to be suppressed in asthmatic epithelium in IFV infection which lead to aberrant epithelial response, contributing to exacerbations (Moheimani et al., 2018) . Other than these direct evidence of miRNA changes in contributing to exacerbations, an increased number of miRNAs and other non-coding RNAs responsible for immune modulation are found to be altered following viral infections (Globinska et al., 2014; Feng et al., 2018; Hasegawa et al., 2018) . Hence non-coding RNAs also presents as targets to modulate viral induced airway changes as a means of managing exacerbation of chronic airway inflammatory diseases. Other than miRNA modulation, other epigenetic modification such as DNA methylation may also play a role in exacerbation of chronic airway inflammatory diseases. Recent epigenetic studies have indicated the association of epigenetic modification and chronic airway inflammatory diseases, and that the nasal methylome was shown to be a sensitive marker for airway inflammatory changes (Cardenas et al., 2019; Gomez, 2019) . At the same time, it was also shown that viral infections such as RV and RSV alters DNA methylation and histone modifications in the airway epithelium which may alter inflammatory responses, driving chronic airway inflammatory diseases and exacerbations (McErlean et al., 2014; Pech et al., 2018; Caixia et al., 2019) . In addition, Spalluto et al. (2017) also showed that antiviral factors such as IFNγ epigenetically modifies the viral resistance of epithelial cells. Hence, this may indicate that infections such as RV and RSV that weakly induce antiviral responses may result in an altered inflammatory state contributing to further viral persistence and exacerbation of chronic airway inflammatory diseases (Spalluto et al., 2017) .
Finally, viral infection can result in enhanced production of reactive oxygen species (ROS), oxidative stress and mitochondrial dysfunction in the airway epithelium (Kim et al., 2018; Mishra et al., 2018; Wang et al., 2018) . The airway epithelium of patients with chronic airway inflammatory diseases are usually under a state of constant oxidative stress which sustains the inflammation in the airway (Barnes, 2017; van der Vliet et al., 2018) . Viral infections of the respiratory epithelium by viruses such as IFV, RV, RSV and HSV may trigger the further production of ROS as an antiviral mechanism Aizawa et al., 2018; Wang et al., 2018) . Moreover, infiltrating cells in response to the infection such as neutrophils will also trigger respiratory burst as a means of increasing the ROS in the infected region. The increased ROS and oxidative stress in the local environment may serve as a trigger to promote inflammation thereby aggravating the inflammation in the airway (Tiwari et al., 2002) . A summary of potential exacerbation mechanisms and the associated viruses is shown in Figure 2 and Table 1 .
While the mechanisms underlying the development and acute exacerbation of chronic airway inflammatory disease is extensively studied for ways to manage and control the disease, a viral infection does more than just causing an acute exacerbation in these patients. A viral-induced acute exacerbation not only induced and worsens the symptoms of the disease, but also may alter the management of the disease or confer resistance toward treatments that worked before. Hence, appreciation of the mechanisms of viral-induced acute exacerbations is of clinical significance to devise strategies to correct viral induce changes that may worsen chronic airway inflammatory disease symptoms. Further studies in natural exacerbations and in viral-challenge models using RNA-sequencing (RNA-seq) or single cell RNA-seq on a range of time-points may provide important information regarding viral pathogenesis and changes induced within the airway of chronic airway inflammatory disease patients to identify novel targets and pathway for improved management of the disease. Subsequent analysis of functions may use epithelial cell models such as the air-liquid interface, in vitro airway epithelial model that has been adapted to studying viral infection and the changes it induced in the airway (Yan et al., 2016; Boda et al., 2018; Tan et al., 2018a) . Animal-based diseased models have also been developed to identify systemic mechanisms of acute exacerbation (Shin, 2016; Gubernatorova et al., 2019; Tanner and Single, 2019) . Furthermore, the humanized mouse model that possess human immune cells may also serves to unravel the immune profile of a viral infection in healthy and diseased condition (Ito et al., 2019; Li and Di Santo, 2019) . For milder viruses, controlled in vivo human infections can be performed for the best mode of verification of the associations of the virus with the proposed mechanism of viral induced acute exacerbations . With the advent of suitable diseased models, the verification of the mechanisms will then provide the necessary continuation of improving the management of viral induced acute exacerbations.
In conclusion, viral-induced acute exacerbation of chronic airway inflammatory disease is a significant health and economic burden that needs to be addressed urgently. In view of the scarcity of antiviral-based preventative measures available for only a few viruses and vaccines that are only available for IFV infections, more alternative measures should be explored to improve the management of the disease. Alternative measures targeting novel viral-induced acute exacerbation mechanisms, especially in the upper airway, can serve as supplementary treatments of the currently available management strategies to augment their efficacy. New models including primary human bronchial or nasal epithelial cell cultures, organoids or precision cut lung slices from patients with airways disease rather than healthy subjects can be utilized to define exacerbation mechanisms. These mechanisms can then be validated in small clinical trials in patients with asthma or COPD. Having multiple means of treatment may also reduce the problems that arise from resistance development toward a specific treatment. | What further can viral persistence lead to? | false | 3,978 | {
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1,691 | RNA sequencing-based analysis of the spleen transcriptome following infectious bronchitis virus infection of chickens selected for different mannose-binding lectin serum concentrations
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4729133/
SHA: f5f1cd43740b5b6eca8b3cf2714fc0854a746519
Authors: Hamzić, Edin; Kjærup, Rikke Brødsgaard; Mach, Núria; Minozzi, Guilietta; Strozzi, Francesco; Gualdi, Valentina; Williams, John L.; Chen, Jun; Wattrang, Eva; Buitenhuis, Bart; Juul-Madsen, Helle Risdahl; Dalgaard, Tina Sørensen
Date: 2016-01-27
DOI: 10.1186/s12864-016-2403-1
License: cc-by
Abstract: BACKGROUND: Avian infectious bronchitis is a highly contagious disease of the upper-respiratory tract caused by infectious bronchitis virus (IBV). Understanding the molecular mechanisms involved in the interaction between innate and adaptive immune responses to IBV infection is a crucial element for further improvements in strategies to control IB. To this end, two chicken lines, selected for high (L10H line) and low (L10L line) serum concentration of mannose-binding lectin (MBL) were studied. In total, 32 birds from each line were used. Sixteen birds from each line were infected with IBV and sixteen were left uninfected. Eight uninfected and infected birds from each line were euthanized at 1 and 3 weeks post infection. RNA sequencing was performed on spleen samples from all 64 birds and differential gene expression analysis was performed for four comparisons: L10L line versus L10H line for uninfected birds at weeks 1 and 3, respectively, and in the same way for infected birds. Functional analysis was performed using Gene Ontology (GO) Immune System Process terms specific for Gallus gallus. RESULTS: Comparing uninfected L10H and L10L birds, we identified 1698 and 1424 differentially expressed (DE) genes at weeks 1 and 3, respectively. For the IBV-infected birds, 1934 and 866 DE genes were identified between the two lines at weeks 1 and 3, respectively. The two most enriched GO terms emerging from the comparison of uninfected birds between the two lines were “Lymphocyte activation involved in immune response” and “Somatic recombination of immunoglobulin genes involved in immune response” at weeks 1 and 3, respectively. When comparing IBV-infected birds between the two lines, the most enriched GO terms were “Alpha-beta T cell activation” and “Positive regulation of leukocyte activation” at weeks 1 and 3, respectively. CONCLUSIONS: Healthy birds from the two lines showed significant differences in expression profiles for subsets of adaptive and innate immunity-related genes, whereas comparison of the IBV-infected birds from the two lines showed differences in expression of immunity-related genes involved in T cell activation and proliferation. The observed transcriptome differences between the two lines indicate that selection for MBL had influenced innate as well as adaptive immunity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2403-1) contains supplementary material, which is available to authorized users.
Text: Conclusions: Healthy birds from the two lines showed significant differences in expression profiles for subsets of adaptive and innate immunity-related genes, whereas comparison of the IBV-infected birds from the two lines showed differences in expression of immunity-related genes involved in T cell activation and proliferation. The observed transcriptome differences between the two lines indicate that selection for MBL had influenced innate as well as adaptive immunity.
Keywords: IBV, Coronavirus, Infectious bronchitis, Chicken, RNA sequencing, Transcriptome, Spleen, Mannose-binding lectin, Immune response Background Avian infectious bronchitis (IB) is an acute and highly contagious disease of the upper-respiratory tract caused by the infectious bronchitis virus (IBV). The virus is a member of the Coronaviridae family and has numerous serotypes and strains. Rapid replication combined with high mutation rate and recombination are the main causes of the observed high diversity [1] . The respiratory tract is the primary target organ and entry point for the virus, before further spread to kidneys and gonads. The most common symptoms of IB are related to the respiratory tract and include gasping, coughing, sneezing, tracheal rales, and nasal discharge [2] . Feed conversion and average daily gain are affected in broilers, and infection is often followed by secondary bacterial infections. In layers, IBV causes a reduction in egg production and egg quality. Today, IB is one of the most economically important diseases in the poultry industry [2] . Infection outbreaks are controlled by a combination of strict management practices and vaccination. The strict management practices, which include the maintenance of the housing temperature and ventilation, are essential, because IBV is highly contagious and spreads very fast. Live attenuated and inactivated vaccines are widely used for control and prevention of IBV infection [3, 4] . As there is little or no cross-protection between different serotypes/variants of the virus, hence vaccines should contain serotypes present in a particular area in order to induce adequate protection [1] . New multi-strain vaccines with the optimal antigen combination and optimal adjuvants are therefore required for future IBV control. Understanding the molecular mechanisms involved in the interaction between innate and adaptive immune responses to IBV infection is a crucial element for further improvements of the vaccines.
IBV infection induces a wide range of immune responses in chickens. An innate immune response is activated during the initial stages of infection in the mucosal lining of the trachea following binding of IBV virions to receptors on epithelial cells [5] . Activation of this innate immune response may be initiated by Toll-like receptor (TLR) signaling upon IBV recognition [6, 7] . In addition, rapid activation of natural killer (NK) cells has been observed one day after IBV infection [8] as well as increased macrophage numbers in lungs and trachea after primary IBV infection [9] . In the case of the adaptive immune responses, T lymphocyte subpopulations are actively involved in the early stages of IBV clearance [7, 10] exhibiting rapid activation upon IBV infection [6] . Furthermore, studies have shown that cytotoxic T lymphocytes (CTL) play an important role in responding to primary infections with IBV [10, 11] . In addition to T cell responses, IBV specific antibodies, of all three antibody classes present in chickens, have been reported [12] [13] [14] . A specific local antibody response in avian infectious bronchitis is characteristic for the response to a secondary infection [15] . The innate and adaptive immune systems are strongly interconnected, which is also seen in the response to IBV infection, and the connection possibly involves the serum collectin, mannose-binding lectin (MBL) as a key player [16] .
Two chicken lines which were selected for high and low MBL serum concentrations (designated L10H and L10L, respectively), were used in the present study. Selective breeding has been performed for 14 generations using the combination of two strains (67.5 % UM-B19 chickens and 33.5 % White Cornish) as a starting population, as described by Juul-Madsen et al. [17] . The final result was two divergent lines, with mean MBL serum concentrations of 33.4 μg/ml for the L10H line and 7.6 μg/ml for the L10L line, respectively [18, 19] . The mean MBL serum concentration for 14 different chicken lines representing both broilers and layers is around 6 μg/ml, but varies from 0.4 to 37.8 μg/ml in normal healthy chickens with protein produced in the liver as the main source of circulating MBL [17] . In chickens, a positive correlation between MBL serum concentrations and the severity of several infections, such as infections caused by IBV [19] , Escherichia coli [20] and Pasteurella multocida [21] , has been observed. Chicken MBL binds to IBV [16, 22] , therefore it is possible that MBL facilitates innate responses such as opsono-phagocytosis, complement activation or virus neutralization, in the early stages of IBV infection. In mammals MBL has also been shown to influence induction of adaptive immunity [23] . In support of the role of MBL in response to IBV, Kjaerup et al. [18] observed considerable differences in cellular adaptive immune parameters in response to an IBV infection between lines L10L and L10H. Furthermore, birds from L10H line exhibited lower viral loads and less severe damage of tracheal cilia following the IBV infection in comparison to birds from the L10L line.
The aim of this study was to characterize the spleen transcriptome of healthy birds from the two lines selected for serum MBL, and to investigate differences in molecular mechanisms behind the development of systemic adaptive immunity between the L10L and L10H lines infected with IBV.
The experimental timeline and sampling time points are as illustrated in Fig. 1 and a full description of the experimental infection is reported by Kjaerup et al. [18] . The birds were infected at 3 weeks of age and from day 2 post-infection (p.i.), showed clinical signs characteristic of IBV infection, including sneezing and labored breathing. Viral loads in tracheal swabs were assessed for all birds as reported in the previous paper published on the experimental infection study [18] . No virus was detected in the uninfected birds at any time point throughout the experiment. Viral genomes were detected in swabs from infected birds from day 1 to 8 p.i. Notably, significantly lower viral loads (p < 0.03) were observed in birds from line L10H in comparison to infected birds from line L10L [18] .
Detection and quantification of splenic gene expression RNA sequencing data were produced from eight infected and eight uninfected birds from each of the two lines at two sampling occasions, as described in the materials and methods section. All samples passed quality control measures for raw and trimmed sequenced reads except for individual no. 46, which was removed due to a very low number of sequenced reads. For the remaining birds, an average of over 37 million reads were obtained per sample for the 63 samples analyzed, with 81 % of the reads mapping to the chicken genome reference sequence, as described in the materials and methods section (See summary statistics with the number of mapped and total reads is presented in Additional file 1: Table S1 ). In total, 17,113 expressed genes were identified. After filtering genes with fewer than one read per million in eight samples [24] (genes which would not achieve statistical significance for differential expression), the final list contained 11,292 expressed genes. Before performing the differential gene expression analysis, further multivariate analysis was carried out on the raw and normalized gene count data to identify any discrepancies.
Multi-dimensional scaling (MDS) plot on expressed genes between the two lines, L10H and L10L, showed that they differ considerably in their transcriptome profiles for both uninfected and IBV-infected birds [See Additional file 2: Figure S1 ]. Moreover, inter-individual variation in gene expression at week 1 was considerably higher than that observed at week 3 for both uninfected and IBV-infected birds [See Additional file 2: Figure S1 ].
Birds 22 and 47 were separated from the rest on the MDS plot [See Additional file 2: Figure S1 ]. However, inspection of raw sequence data and mapping parameters did not identify any technical problems which would explain the observed out-grouping of these birds. In addition an interclass principal component analysis (PCA) was performed using raw and normalized gene counts. The interclass PCA revealed that the birds 22 and 47 were placed outside the 95 % confidence intervals of their respective treatments [See Additional file 3: Figure S2 ]. However, the PCA did not identify any gene having extreme count profiles which may have contributed to the transcriptome dispersion of birds 22 and 47 with respect to their treatment groups. Although there was no clear technical or biological explanation for their out-grouping, these samples were removed from further analysis.
Differential gene expression analysis was performed to compare the two chicken lines (L10L and L10H) at two time points for uninfected (C1 and C2, see Fig. 1 ) and IBV-infected birds (C3 and C4, see Fig. 1 ). A large number of genes were differentially expressed (DE) between L10L and L10H lines at weeks 1 and 3, for both uninfected and IBV-infected birds (see Table 1 , see Fig. 1 ).
We identified 1,698 and 1,424 DE genes for the uninfected birds between lines L10L and L10H at weeks 1 and 3, respectively (see Table 1 ). In total 692 genes had higher expression in L10H line and 1,006 had higher expression in line L10L for the uninfected birds at week 1 [See Additional file 4: Table S2 ] and 774 genes had higher expression in L10H line and 650 genes had higher expression in L10L line for uninfected birds at week 3 [See Additional file 5: Table S3 ].
Comparing IBV-infected L10H and L10L birds, we identified 1,934 and 866 DE genes at weeks 1 and 3, respectively (see Table 1 ). In total 931 genes had higher expression in line L10H and 1,003 had higher expression in line L10L at week 1 and at week 3, 508 had higher expression in line L10H and 358 had higher expression in line L10L (Table 1 , Additional file 6: Table S4 and Additional file 7: Table S5 ).
There were also status-related changes in gene expression as shown in the Venn diagram ( Fig. 2) . At week 1, the total number of DE genes in uninfected birds Fig. 2 ). Out of 3,011 (1077 + 621 + 1313) DE genes for both uninfected and infected birds between the two lines only 621 (~20 %) were common for two comparisons (Fig. 2 ). At week 3, the total number of DE genes in uninfected birds between the two lines was 1424 (883 + 541) ( Table 1 , Fig. 2 ) which was higher comparing to 866 (541 + 325) in infected birds between the two lines ( Table 1 , Fig. 2 ). When comparing the uninfected and infected birds between the two lines, 541 (~30 %) genes were common out of total of 1749 (883 + 541+ 325) DE genes for both comparisons (Fig. 2) .
Moreover, we also performed differential gene expression analysis to compare two time points (week 1 and week 3) in the two chicken lines (L10L and L10H) for uninfected (C5 and C6, see Fig. 1 ) and IBV-infected birds (C7 and C8, see Fig. 1 ). Finally, differential gene expression analysis was also conducted to compare the two infection states (uninfected and IBV-infected) at two time points for the L10L chicken line (C9 and C10, see Table S6 , Additional file 9: Table S7 , Additional file 10: Table S8 , Additional file 11: Table S9 , Additional file 12: Table S10 , Additional file 13: Table S11 , Additional file 14: Table S12 and Additional file 15: Table S13 ].
An enrichment gene set analysis was carried out to identify over-represented Gene Ontology (GO) "Immune System Process" terms using the lists of DE genes from comparisons between uninfected and infected birds from the two lines at 1 and 3 weeks p.i. The most enriched GO Immune System terms between the two lines when comparing uninfected birds from the two lines and then infected from the two lines are shown in Fig. 3 .
GO Immune System terms associated with genes that were differentially expressed between the two lines for uninfected birds at week 1 were "Lymphocyte activation involved in immune response" (GO:0002285), "Activation of innate immune response" (GO:0002218), "Lymphocyte mediated immunity" (GO:0002449), and "Leukocyte Comparison between the two lines, L10H and L10L, uninfected and infected birds at two time points (weeks 1 and 3). Comparisons C1 -C4 correspond to differential gene expression comparisons presented in Fig. 1 For uninfected birds at week 3, the most enriched GO Immune System terms were "Somatic recombination of immunoglobulin genes involved in immune response" (GO:0002204) and the "Adaptive immune response based on somatic recombination of immune receptors built from immunoglobulin superfamily" (GO:0002460) [See Fig. 3 , See Additional file 17: Figure S4 ]. In total, 47 DE genes mapped to GO Immune System terms in this comparison (Fig. 4) . Among the DE genes that had a higher expression in the line L10H at week 3, in the uninfected group, were IL7, FKBP1B, FAS and PTPN22, which were also seen differentially expressed between lines at week 1 [See Fig. 4 , Additional file 17: Figure S4 ].
Comparing infected birds from the two lines, at week 1, "Alpha-beta T cell activation" (GO:0046631), "Activation of innate immune response" (GO:0002218) and "Leukocyte differentiation" (GO:0002521) functions were the three most enriched GO Immune System terms (Fig. 3) . CXCR4 (Chemokine receptor 4), PTPN22 and FAS were among the most highly expressed genes in L10H [See Fig. 4 , Additional file 18: Figure S5 ].
The major GO Immune System term that was strongly enriched for in the infected birds at week 3 was "Positive regulation of leukocyte activation" (GO:0002696) [See Figure S6 ].
The present study used two lines, L10L and L10H, which have been divergently selected for high and low MBL serum concentration for 14 generations, Fig. 3 Functional map of differentially expressed genes enriched for GO Immune System terms. The top categories of the GO Immune System terms associated with differentially expressed (DE) genes. All categories were statistically significant (adjusted p-value < 0.001). The chart fragments represent the number of genes associated with the terms as a proportion of the total number of genes within the respective GO term. Terms which have not been grouped are shown in grey respectively. These two lines have earlier been extensively used for immunological studies and exhibit differences in immunological parameters after being challenged with several pathogens [18, 22, 25] .
The spleen is a secondary lymphoid organ where innate and adaptive immune responses can be efficiently mounted. In addition, the avian spleen is considered to play a very important immunological role because avian lymphatic vessels and lymph nodes are poorly developed [26] . The transcriptome differences in the spleen between the two lines, L10L and L10H, for uninfected (healthy) and IBV-infected birds were investigated, focusing on the differential expression of immune-related genes within significantly enriched immune-related GO terms. Large differences in transcriptome profiles were observed between birds from the two lines, both uninfected (healthy) and following the experimental IBV challenge [See Additional file 2: Figure S1 ]. This suggests Fig. 4 Differentially expressed genes associated with the GO Immune System term. Heatmap representation of the differentially expressed (DE) genes associated with the GO Immune System terms for the four comparisons between the two lines, L10H and L10L, uninfected and infected groups at two time points, weeks 1 and 3. The heat map is constructed using the average values of counts per millions for each group that selection for MBL serum levels in the two lines had a much wider effect which goes beyond the expression of the MBL gene [27] . The observed transcriptome differences can probably be attributed to correlated response to selection [28] or random genetic drift [29] . Correlated selection occurs when a trait is affected by selection on a another trait and is dependent on a genetic correlation between the two traits, which is well known in animal breeding [30] . Alternatively, random genetic drift could contribute to the observed differences, considering that the founder population of the two lines was small [17] .
Focusing on the expression of immune-related genes: at week 1, the uninfected birds showed differences in the expression of genes involved in both adaptive immunity and innate immunity-related pathways [See Additional file 16: Figure S3 ]. In addition, the line L10H had a lower expression for the subset of the innate immune genes, TYRO3, TRAF3 and TLR7 at week 1 [See Additional file 16: Figure S3 and Fig. 4 ]. TYRO3 encodes tyrosineprotein kinase receptor 3 (TYRO3) which is involved in inhibition of TLR signaling pathways and TLR-induced cytokine signaling pathways. These two pathways influence immune-related processes, including cell proliferation/survival, cell adhesion and migration and inhibits the innate inflammatory response to pathogens [31] . TRAF3 encodes a cytoplasmic signaling protein, which plays a critical role in the regulation of antiviral response and viral evasion [32] [33] [34] . TLR7 was also among the DE innate immunity-related genes with higher expression in the line L10H. Chicken TLR7 has been shown to play a part in the response to IBV infections [9, 35] .
In addition to the differences in the expression profiles for a subset of innate immune genes, the two lines also differed in their expression of adaptive immune genes. Uninfected birds from L10H had a higher gene expression compared to the line L10L, for TGFB3, IL7, FKBP1B, FAS and PTPN22. These genes are known to be involved in a wide range of adaptive immune processes. In humans, reducing the TGF-β signaling on T cells has been shown to increase the function of CD8 T cells in an indirect way which results in the rapid elimination of viruses, enabling the creation of an effective memory response [36] . Similarly, human IL-7 plays a key role in the survival of both naïve [37] and memory [38, 39] CD4 and CD8 T cells. Moreover, an in vitro study showed that inhibition of FKBP1B and other cyclophilins blocked the replication of different Coronaviruses, including IBV [40] . In analogy, uninfected birds from the L10H line had a higher expression of IL7, FKBP1B, FAS and PTPN22.
Generally the uninfected (healthy) birds from the two lines exhibit different expression profiles for this subset of innate and adaptive immune genes probably resulting from the divergent selection for the MBL serum concentration. Selection in animal breeding have been shown to have an extensive effect on a variety of traits including immunological [30] . Moreover, correlated response to selection has been observed in the case where selection was performed on less complex traits such as testosterone levels [41] . Finally, different expression profiles for the subset of innate and adaptive immune in the uninfected birds from the two lines might be due to the balance in the effect of MBL serum levels. High levels of human MBL have been mostly reported as beneficial while in case of intracellular parasitic disease the effect of MBL serum level might be opposite [42] . The results indicate that selection for MBL serum levels might lead to favoring specific modes of immune responses depending on the MBL function.
Large differences in the expression patterns were seen between the two lines following infection with IBV and these differences involved adaptive immunity-related pathways which are associated with "Alpha-beta T cell activation" (GO:0046631), and "Activation of innate immune response" (GO:0002218) [See Additional file 18: Figure S5 ]. The observed enrichment for GO terms related to T cell activation is in accordance with a previous study of these lines that showed that the IBV-specific T cells are present in large numbers in the spleen after IBV infection [43] . At week 1 post infection CXCR4, FAS and PTPN22 showed higher expression in line L10H. The CXC chemokine receptors are expressed on both effector and memory T cells and play a key role in the homeostasis of memory T cells [44] . FAS has been shown to be upregulated in the kidney of chickens challenged with IBV [45] . The Fas/FasL pathway is an important pathway of killing for cytotoxic T cells [46] . Similarly, PTPN22 has been shown to be differentially expressed in chickens following pathogen challenge, and in particular following infection with Escherichia coli [47] .
Additionally VCAM1 and JMJD6 were among the adaptive immunity-related genes DE between lines at week 3 [See Fig. 4 , Additional file 19: Figure S6 ]. The VCAM1 gene is known to be involved in the activation of T cells [48] . Furthermore, a recent study demonstrated that JMJD6 regulates proliferation of memory T cells during a viral infection [49] which is of great interest considering that had higher expression in the IBVinfected birds from L10H line at week 3.
The results show that the two lines differ greatly in the expression of adaptive immunity-related genes following infection, which may imply the presence of different modes of gene regulation. The sampling times were chosen to access responses both in the effector phase (week 1) and memory phase (week 3) of the adaptive immune response to IBV. In accordance, at 1 week, post infection subsets of genes actively involved in T cell proliferation show differences between the lines. Also, at week 3 immune-related gene expression profiles in response to IBV infection that differ between the lines are more related to maintenance of T cell memory. MBL is known to be involved in regulation of dendritic cell maturation as well as cytokine production [50] . Dendritic cells, which are the main antigen presenting cells and are actively involved in regulation of adaptive immune responses, possess the receptors for MBL in mammals [23] . Therefore, the two lines selected for different MBL serum concentration may display differences in adaptive immune responses and development of adaptive immunity as a result of differences in response to cytokine signaling from dendritic cells. Other studies of the two lines, L10L and L10H, have shown that they differ in disease response parameters after being challenged with different pathogens. The L10L line has been associated with increased viral replication in the airway after an infectious bronchitis virus (IBV) infection [18] , reduced growth rate after an Escherichia coli infection [20] and greater intestinal colonization after Salmonella Infantis infection [51] . In the present experiment, significantly lower viral loads (p < 0.03) were observed in birds from line L10H in comparison to infected birds from line L10L [18] . Furthermore, L10H birds in the present study exhibited a less severe damage of tracheal cilia following the IBV infection in comparison to the L10L line (unpublished data). In the current experiment phenotypic differences in additional traits connected to adaptive immunity were observed, including numbers of circulating B cells and cytotoxic T cells [18] . Based on these observations it seems that selection for high MBL serum concentration allows birds to cope better after being infected with a range of pathogens. Therefore, the observed differences in the expression profiles for the adaptive and innate immune-related genes are a reflection of differences in disease resistance and immune responses between the lines L10L and L10H.
In conclusion, large differences in the spleen transcriptome between the two chicken lines, L10L and L10H, were observed in both uninfected (healthy) and IBVinfected birds. The uninfected birds from the two lines showed differences in expression profiles for a subset of both adaptive and innate immunity-related genes, which may represent differences in preparedness to respond to an infection. Following infection with IBV, the two lines showed large differences in expression of genes involved in the adaptive cellular immune response such as T cell activation and proliferation pathways and hence their ability to respond to the infection, which is reflected in the difference in pathogen load seen between the two lines.
This study is a follow-up of the experiment performed by Kjaerup et al. [18] which characterized the cellular and humoral immune response of the two chicken lines, L10H and L10L, divergently selected for MBL serum concentrations following IBV infection. In total, 96 birds were used in the experimental study originating from the two Aarhus University inbred lines, L10H and L10L [19] . All 96 birds were reared together in a biosecure IBV-free environment until they were 3 weeks of age and then allocated to two different groups with 24 birds from each line in each group (uninfected and infected). The birds were transferred to a biosafety level 2 facility and placed in isolators. Two isolators contained uninfected chickens and two isolators contained infected chickens. Each isolator having an equal mix of the two lines as described by Kjaerup et al. [18] .
The virulent IBV-M41 strain was used for the infection (a kind gift from Dr. med. vet. Hans C. Philipp at the Lohmann Animal Health GmbH, Cuxhaven, Germany). The virus had been passaged twice in specific pathogen-free embryonated eggs. The IBV inocula were prepared in phosphate-buffered saline (PBS) immediately before use and contained 2 × 10 5.2 EID 50 /200 μl of IBV-M41 virus. The first and the second group (the uninfected groups) were mock-infected with 200 μl PBS per bird. The third and fourth groups (the infected groups) received 200 μL of IBV-M41. The inocula were given half nasally and half orally to mimic the natural infection routes of IBV in the chicken. Chickens were fed diets that met or exceeded the National Research Council requirements. Feed and water were provided ad libitum. The birds were monitored daily for clinical signs of disease and disease parameters were measured as reported by Kjaerup et al. [18] . None of the individuals received antibiotic therapy during the experimental period. The study was carried out under strict ethical approval and monitoring (see the statement at the end of the Materials and Methods section).
For this study 64 spleen samples were harvested and used for RNA sequencing. The birds were sacrificed 1 and 3 weeks post infection by cervical dislocation and spleen samples were collected. At both time points, eight samples from the two lines, L10H and line L10L, from each group (uninfected and infected) were collected as illustrated in Fig. 1 . After collection, spleens were sectioned (triangular cross-sectional slice from upper part) and identical samples from each chicken were immediately placed in RNAlater® Stabilization Solution (Ambion Inc., Austin, Texas) that were incubated at 4°C overnight and then transferred to -20°C the following day.
Tissue samples were homogenized on a TissueLyzer LT (Qiagen, Hilden, Germany). Total RNA was extracted with the Qiagen RNAeasy Kit (Catalog ID 74104, Qiagen, Venlo, Netherlands) according to the manufacturer's instructions. The quality of the 64 total RNA samples was verified using a 2200 TapeStation RNA Screen Tape device (Agilent, Santa Clara, CA, USA) and the concentration ascertained using an ND-1000 spectrophotometer (Nano-Drop, Wilmington, DE).
Libraries were prepared with the Illumina TruseqRNA sample prep kit (Catalog ID FC-122-1001, Illumina, San Diego, USA) following the manufacturer's protocol and evaluated with the Agilent Tape Station 2200. Libraries were quantified by Picogreen and then normalized to 10 nM as recommended by Illumina for cluster generation on the Hiseq2000. Equimolar amounts of each library were mixed before NaOH denaturation.
The Illumina Truseq PE cluster kit v3 (Catalog ID PE-401-3001) was used to generate clusters on the grafted Illumina Flowcell and the hybridized libraries were sequenced on six lines of a Flowcell on the Hiseq2000 with 100 cycles of a paired-end sequencing module using the Truseq SBS kit v3 (Catalog ID FC-401-3001).
Quality control, mapping of RNA sequencing reads and counting mapped reads Initial control quality was assessed by the FastQC software version 0.11.3 [52] . Raw reads were than trimmed for low quality bases using the Trimmomatic tool version 0.32 [53] applying minimum Phred quality score >10 averaged across the sliding window of five bases. Furthermore, all reads with the length below 40 bp were removed.
The trimmed reads were mapped to the Gallus gallus reference genome (Gallus_gallus-4.0, release 80 [54] ) using a spliced aligner TopHat2 version 2.014 [55] . The Gallus gallus gene annotation used for mapping was retrieved from Ensembl database version 80 (www.ensembl.org). The mapping quality was assessed using a set of Python scripts within the RSeQC toolkit [56] . The quality control assessment included inspection of the read coverage over the full gene body in order to assess if reads coverage was uniform and if there was any 5' or 3' bias as well as how the mapped reads were distributed over genome features.
Gene count estimation was performed using the HTSeq-count tool in 'union' mode. The HTSeq-count is a Python script within the HTSeq framework, version 0.7.1, which is an open source toolkit that allows the input of raw counts from aligned reads to be annotated with gene names based on genomic features [57] .
The read counts obtained were used to estimate gene expression and identify differentially expressed (DE) genes. This was achieved using Bioconductor package edgeR version 3.10.0 [58] and limma version 3.24.5 [59] following a previously described protocol [24] . Before performing statistical analysis, genes with low levels of expression were filtered out using a threshold of least one read per million in n of the samples, where n is the size of the smallest group of replicates, which in this case was eight.
In order to account for technical and biological effects reads counts were normalized using the "calc-NormFactors" function implemented in the edgeR package. This function normalizes the data by finding a set of scaling factors for the library sizes that minimizes the log-fold changes between the samples. The scale factors were computed using the trimmed mean of M-values (TMM) between samples [58] . Common and tag-wise dispersion estimates were calculated with the Cox-Reid profile adjusted likelihood method in order to correct for the technical and biological variation when fitting the multivariate negative binomial model [60] .
Multidimensional scaling (MDS) was implemented in the edgeR package, to assess similarity of the samples visually. The MDS plot was created in order to visualize the relationship between samples and identify possible outliers [58] . MDS is based on comparing the relationship between all pairs of samples by applying a countspecific pairwise distance measure [58] . Possible outliers were further investigated using principal component analysis (PCA) to remove samples which fell outside a 95 % confidence ellipse.
A design matrix was created in order to specify the factors that were expected to affect the expression level. The matrix was constructed to fit the saturated model where each treatment combination was considered separately. Eight treatment combinations were considered as illustrated in Fig. 1 : uninfected birds from the line L10H at week 1, uninfected birds from the line L10L at week 1, infected birds from the line L10H at week 1, infected birds from the line L10L at week 1, uninfected birds from the line L10H at week 3, uninfected birds from the line L10L at week 3, infected birds from the line L10H at week 3, infected birds from the line L10L at week 3.
A generalized linear model likelihood ratio test, specifying the difference of interest, was used to test for differential expression between these treatment combinations. The differential expression analysis was performed comparing the log-fold differences in gene counts between two lines (L10H and L10L) at different time points (weeks 1 and 3) and for different status (uninfected and infected) separately (Fig. 1 ). Benjamini Hochberg false discovery rates (FDR) for a transcriptome-wide experiment were calculated to correct for multiple testing [61] . All genes with an FDR-adjusted p-value <0.05 were considered individual genes of interest and were retained for further analysis.
Functional analysis of the DE genes was performed using the Cytoscape version 3.2.1 [62, 63] with the ClueGo version 2.1.7 plug-in [64] to enrich the annotation and enrichment of the differentially expressed (DE) genes for four comparisons (C1-C4, see Fig. 1 ). ClueGO determines the distribution of the target genes across the GO (Gene Ontology) terms and pathways: this study focused on. The p-value was calculated using right-sided hypergeometric tests and Benjamini-Hochberg adjustment was used for multiple test correction. An adjusted pvalue of 0.001 indicated a statistically significant deviation from the expected distribution, and that the corresponding GO terms and pathways were enriched for the target genes. The association strength between the terms was calculated using a corrected kappa statistic of 0.4. The network created represented the terms as nodes which were linked based on a 0.4 kappa score level. The size of the nodes reflected the enrichment significance of the terms. The network was automatically laid out using the Organic layout algorithm supported by Cytoscape. The functional groups were created by iterative merging of initially defined groups based on the predefined kappa score threshold. Only functional groups represented by their most significant term were visualized in the network providing an insightful view of their interrelations [64] .
The experimental procedures were conducted under the protocols approved by the Danish Animal Experiments Inspectorate and complied with the Danish Ministry of Justice Law no. 382 (June 10, 1987) and Acts 739 (December 6, 1988) and 333 (May 19, 1990) concerning animal experimentation and care of experimental animals. The license to conduct the animal experiment was obtained by Helle R. Juul-Madsen. comparison between uninfected birds at week 1. The GO Immune System terms were identified as nodes and linked based on their kappa score level (> = 0.4) and p-value < 0.001. Functionally related groups partially overlapped. The GO terms are labelled in colors according to hierarchical clustering of GO terms. Terms which have not been grouped are shown in grey. The colour pie charts of the GO Immune system nodes show the gene proportion associated with the respective term. (PDF 60 kb)
Additional file 17: Figure S4 . Network representation of enriched GO Immune System terms of differentially expressed (DE) genes for comparison between uninfected birds at week 3. The GO Immune System terms were identified as nodes and linked based on their kappa score level (> = 0.4) and p-value < 0.001. Functionally related groups partially overlapped. The GO terms are labelled in colours according to hierarchical clustering of GO terms. Terms which have not been grouped are shown in grey. The color pie charts of the GO Immune system nodes show the gene proportion associated with the respective term. (PDF 55 kb) Additional file 18: Figure S5 . Network representation of enriched GO Immune System terms of differentially expressed (DE) genes for comparison between infected birds at week 1. The GO Immune System terms were identified as nodes and linked based on their kappa score level (> = 0.4) and p-value < 0.001. Functionally related groups partially overlapped. The GO terms are labelled in colors according to hierarchical clustering of GO terms. Terms which have not been grouped are shown in grey. The color pie charts of the GO Immune system nodes show the gene proportion associated with the respective term. (PDF 70 kb) Additional file 19: Figure S6 . Network representation of enriched GO Immune System terms of differentially expressed (DE) genes for comparison between infected birds at week 3. The GO Immune System terms were identified as nodes and linked based on their kappa score level (> = 0.4) and p-value < 0.001. Functionally related groups partially overlapped. The GO terms are labelled in colors according to hierarchical clustering of GO terms. Terms which have not been grouped are shown in grey. The color pie charts of the GO Immune system nodes show the gene proportion associated with the respective term. (PDF 30 kb) | What differentiated the two chicken lines used in this study? | false | 5,161 | {
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"serum concentration of mannose-binding lectin (MBL)"
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1,684 | A novel anti-mycobacterial function of mitogen-activated protein kinase phosphatase-1
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2804704/
SHA: f6ed1f1e9999e57793addb1c9c54f61c7861a995
Authors: Cheung, Benny KW; Yim, Howard CH; Lee, Norris CM; Lau, Allan SY
Date: 2009-12-17
DOI: 10.1186/1471-2172-10-64
License: cc-by
Abstract: BACKGROUND: Mycobacterium tuberculosis (MTB) is a major cause of morbidity and mortality in the world. To combat against this pathogen, immune cells release cytokines including tumor necrosis factor-α (TNF-α), which is pivotal in the development of protective granulomas. Our previous results showed that Bacillus Calmette Guerin (BCG), a mycobacterium used as a model to investigate the immune response against MTB, stimulates the induction of TNF-α via mitogen-activated protein kinase (MAPK) in human blood monocytes. Since MAPK phosphatase-1 (MKP-1) is known to regulate MAPK activities, we examined whether MKP-1 plays a role in BCG-induced MAPK activation and cytokine expression. RESULTS: Primary human blood monocytes were treated with BCG and assayed for MKP-1 expression. Our results demonstrated that following exposure to BCG, there was an increase in the expression of MKP-1. Additionally, the induction of MKP-1 was regulated by p38 MAPK and extracellular signal-regulated kinase 1 and 2 (ERK1/2). Surprisingly, when MKP-1 expression was blocked by its specific siRNA, there was a significant decrease in the levels of phospho-MAPK (p38 MAPK and ERK1/2) and TNF-α inducible by BCG. CONCLUSIONS: Since TNF-α is pivotal in granuloma formation, the results indicated an unexpected positive function of MKP-1 against mycobacterial infection as opposed to its usual phosphatase activity.
Text: Tuberculosis (TB) remains a major cause of morbidity and mortality in the world, especially in the developing countries [1] . The disease is caused by Mycobacterium tuberculosis (MTB) and approximately one third of the world's population has been infected by this pathogen. In a recent report, World Health Organization (WHO) estimated that there are 9.2 million new TB cases around the world in 2006 [1] .
In response to MTB infection, induction of cytokines by immune cells is an important defense mechanism. The infected macrophages secrete intercellular signaling factors, proinflammatory cytokines, to mediate the inflammatory response leading to the formation of granuloma and induction of T-cell mediated immunity [2] . In order to understand TB pathogenesis, signaling pathways induced by mycobacteria have long been a subject of interest. Mitogen activated protein kinases (MAPKs) including extracellular signal-regulated kinase 1 and 2 (ERK1/2), p38 MAPK, and c-Jun N-terminal kinase (JNK) have been implicated as important cellular signaling molecules activated by mycobacteria [3] . Previous reports have shown that p38 MAPK and ERK1/2 are required in the induction of TNF-α expression in human monocytes infected with M. tuberculosis H37Rv [4] . We have further revealed the significant role of MAPKs in the signal transduction events of mycobacterial activation of primary human blood monocytes (PBMo) leading to cytokine expressions via the interaction with PKR [5] . However, the subsequent events as to how MAPK is regulated and how such regulation affects cytokine production in response to mycobacteria remain to be elucidated.
Since MAPKs are activated by phosphorylation, dephosphorylation of MAPKs seems to be an efficient process to inactivate their activities. It can be achieved by specific protein kinase phosphatases which can remove the phosphate group from MAPKs. Examples of these phosphatases include tyrosine phosphatases, serine/threonine phosphatases, and dual-specificity phosphatases (DUSPs). Some DUSPs are also known as MAPK phosphatases (MKPs) [6] [7] [8] . Currently, there are at least 10 MKPs identified, while MKP-1 is the most studied member of the family. The regulatory role of MKP-1 on cytokine induction is best demonstrated by MKP-1 knockout (KO) macrophages in response to lipopolysaccharide (LPS), a cell wall component of Gram-negative bacteria. MKP-1 KO macrophages showed prolonged phosphorylation of p38 MAPK and JNK as well as increased production of TNF-α in response to LPS treatment [9] . Consistent with these results, another group further revealed that LPS-treated MKP-1 KO bone marrow-derived macrophages show increased AP-1 DNA-binding activity [10] . Also, they showed that LPS-induced MKP-1 expression is dependent on myeloid differentiation factor 88 (MyD88) and TIR domain-containing adaptor inducing IFN-β (TRIF) [10] , thus demonstrating the role of MKP-1 in signal transduction.
Not only LPS, other TLR inducers including CpG, peptidoglycan, poly IC, and Pam 3 Cys can regulate cytokine expressions including TNF-α, IL-10 via MKP-1 activities [10, 11] . In these processes, MKP-1 serves to mitigate the undesirable effects of septic shock and maintain organ functions by restraining the inflammatory responses following bacterial infection. Another example of MKP-1 function is the immune response to Staphylococcus aureus (S. aureus), a Gram positive bacteria. There are higher levels of cytokine production including TNF-α, IL-6, and MIP-1α in MKP-1 KO mice infected with S. aureus [12] . Also, the mice would have a rapid development of multiorgan dysfunction as well as faster mortality rate upon challenge with heat-killed S. aureus [12] . Taken together, these results suggest that MKP-1 protects the host from overactivation of the immune system in response to Gram negative or Gram positive bacteria.
In the past, it was believed that different MKP/DUSP family members have overlapping functions. However, the emergence of DUSP2 turned the concept up side down [13] . It was shown that DUSP2 behaves differently and is opposite to the function as stated above. In DUSP2 KO cells, they produced less inflammatory mediators, implying that DUSP2 may play a role in mediating instead of limiting inflammation. For instances, when DUSP2 KO macrophages were treated with LPS, there were less TNF, IL-6, nitric oxide, IL-12-producing cells when compared to those of the wild type counterparts [13] . When the DUSP2 KO bone marrow-derived mast cells were first sensitized with immunoglobulin E (IgE) receptor (FcεRI) and then stimulated with dinitrophenol-heat stable antigen, they produced lower TNF mRNA levels, diminished IL-6 production, less phosphorylation of ERK1/2, p38 MAPK, and less transcriptional activities by Elk1 and NFAT-AP-1 [13] .
These unexpected positive regulations of immune cell functions by DUSP2 have been hypothesized to be due to crosstalks between MAPKs [13] . Stimulation of KO mast cells and macrophages showed increases in phosphorylation of JNK. Moreover, inhibition of JNK by small molecule inhibitors showed increases in phosphorylation of ERK [13] . The authors also showed that there were physical interactions of DUSP2 with ERK2, DUSP2 with JNK2, as well as DUSP2 and p38 MAPK after stimulation of the cells with dinitrophenol-heat stable antigen. Nevertheless, the details of the crosstalks between MAPKs and phosphatases need further investigation. Thus, the MKP family plays a critical role in the regulation of immune responses.
Innate immune response protects the host from MTB infection by secretion of cytokines including TNF-α in immune cells. Meanwhile, MAPK is one of the critical proteins in the regulation of immunity and cytokine expression. Since MAPK is regulated by MKP-1 in response to LPS and the activation of MAPK is important in BCGinduced cytokine expression, we hypothesize that MKP-1 plays a critical role in the immune regulation of BCG in human monocytes. We examined the involvement of MKP-1 in BCG-induced MAPK activation and its consequent cytokine expression. Here, we present evidences that MKP-1 plays an unexpected role in the regulation of cytokine induction by BCG through its control of MAPK phosphorylation.
It has been reported that many inducers including growth factors, LPS, peptidoglycan, and dexamethasone can stimulate the expression of MKP-1 in human macrophages, microglia, mast cells or fibroblasts [6] . To investigate the role of different TLR inducers in MKP-1 induction process in human blood monocytes, the level of MKP-1 mRNA was measured by quantitative polymerase chain reaction (QPCR) method. PBMo were isolated from primary human blood mononuclear cells and stimulated with Pam 3 Cys (TLR2 agonist), poly IC (TLR3 agonist), or LPS (TLR4 agonist) for 1 and 3 hours. Following exposure to Pam 3 Cys or LPS, there were significant inductions of MKP-1 mRNA levels within 1 hour of treatment ( Figure 1A ). These effects on MKP-1 induction continued for 3 hours post-treatment with Pam 3 Cys ( Figure 1A ). In contrast, poly IC did not induce MKP-1 ( Figure 1A ). The results indicate that different inducers showed differential up-regulation of MKP-1 expression.
LPS has been extensively used to demonstrate the role of MKP-1 in immune response both in vivo and in vitro [9, 12] . To establish a foundation for interpretation of subsequent experimental results, LPS was used as a positive control for the induction of MKP-1 expression. To determine the levels of MKP-1 in response to LPS, kinetics of MKP-1 transcription were determined by QPCR. There was a significant induction of MKP-1 mRNA, which peaked as early as 1 hour upon LPS stimulation, and the levels gradually decreased over a course of 6 hours. These results showed that LPS induced MKP-1 expression (Figure 1B) .
Next, to demonstrate the induction of specific phosphatases by BCG, kinetics of MKP-1 expression in PBMo was studied by using QPCR during BCG treatment. Similar to the results produced by LPS, upon the addition of BCG (MOI = 1 CFU/cell), there was a significant induction of MKP-1 mRNA within 1 hour of BCG treatment as determined by Taqman probe specific for MKP-1 ( Figure 2A ). The effects lasted for at least 6 hours ( Figure 2A ).
To examine whether the changes of protein production were in parallel to that of the mRNA levels, the protein levels of MKP-1 were measured by Western blotting. In response to BCG, PBMo produced the MKP-1 protein as early as 30 minutes after treatment. The protein levels were maintained for 2 hours and dropped to basal levels at 3 hours ( Figure 2B ). The results demonstrated that there was MKP-1 induction in response to BCG activation in human monocytes.
It has been shown that inhibition of p38 MAPK either by specific inhibitor or siRNA reduced the expression of MKP-1 in LPS-or peptidoglycan-treated macrophages [14] . To determine the mechanisms involved in the BCGinduced MKP-1 expression, PBMo were pretreated with several inhibitors including PD98059 (inhibitor for MAP kinase kinase [MEK] or ERK1/2), SB203580 (inhibitor for p38 MAPK), SP600125 (inhibitor for JNK), and CAPE (inhibitor for NF-κB) for 1 hour. A range of concentrations of each inhibitor was used to test their optimal concentrations and effects on cell viability and kinase inhibitions. BCG was added afterwards and total RNA was harvested. The results demonstrated that, with the inhibition of ERK1/2 and p38 MAPK activities by their corresponding relatively specific inhibitors, MKP-1 expressions were significantly reduced ( Figure 3 ). In addition, using higher dose of SB203580, we showed that the inhibition is increased further (data not shown). On the contrary, pretreatment of the cells with CAPE and SP600125 did not affect the induction of MKP-1 by BCG ( Figure 3 ). These results suggest that BCG-induced MKP-1 expression is dependent on both p38 MAPK and ERK1/2.
Throughout the above experiments, the primary goal was to examine the induction of MKP-1 by BCG in human monocytes. Thus, to further examine the role of MKP-1 in BCG-induced signaling, transfection of siRNA into PBMo was used to knockdown the activity of MKP-1. To demonstrate that the MKP-1 siRNA can indeed knockdown the target gene, PBMo were first transfected with control or MKP-1 siRNA and then treated with BCG for 3 hours. Levels of MKP-1 mRNA were measured by RT-PCR method.
In Figure 4A , BCG stimulated MKP-1 expression (lanes 1 and 2). In MKP-1 siRNA transfected monocytes, induction of MKP-1 by BCG was significantly decreased (lanes 2 and 4). The results showed that the siRNA does abrogate the levels of MKP-1 mRNA.
To further determine whether MKP-1 siRNA affects BCGinduced MKP-1 at protein levels, PBMo were treated as above and MKP-1 proteins were measured by Western blotting. The results showed that BCG could induce MKP-1 proteins as usual for cells transfected with control siRNA ( Figure 4B , lanes 1-3). However, the levels of BCGinduced MKP-1 protein expression were reduced in cells transfected with MKP-1 siRNA ( Figure 4B , lanes 4-6). Together, the results suggest that MKP-1 siRNA not only reduced the MKP-1 mRNA in BCG treatment but also abrogated the BCG-induced MKP-1 protein.
As stated in the literature [9] , MKP-1 KO mice showed increased TNF-α production in response to LPS. On the basis of the above MKP-1 siRNA results, LPS was then used as a control to demonstrate the effects of this MKP-1 siRNA system. cytokine expression induced by LPS in MKP-1 siRNA transfected cells suggest that the siRNA system is effective in knocking down the MKP-1 expression and MKP-1 acts as a negative regulator in LPS-induced TNF-α expression.
To investigate the effect of MKP-1 siRNA on BCG-induced cytokine expression, the levels of TNF-α, IL-6 and IL-10 mRNA were measured by QPCR method. PBMo were transfected with either control or MKP-1 siRNA. Following exposure to BCG with control siRNA, there were significant inductions of TNF-α, IL-6 and IL-10 mRNA levels for 3 hours after treatment as previously reported ( [5] and data not shown). Next, the effects of MKP-1 siRNA were examined on the cytokine expression induced by BCG. Surprisingly, there was a significant abrogation of BCGinduced TNF-α expression by MKP-1 siRNA ( Figure 4D ). With the knockdown of MKP-1, the level of BCG-induced TNF-α was only 60% compared to that of the control cells, while BCG-induced IL-6 and IL-10 were unchanged in MKP-1 siRNA transfected cells. The results revealed that MKP-1 plays a role in the induction of TNF-α expression upon BCG stimulation, which may be different from that of its conventional functions in which MKP-1 acts as a negative regulator in LPS-induced signaling pathways [7] .
The unexpected observations in cytokine expression lead to the investigation on the effects of MKP-1 siRNA on BCG-induced MAPK activation. MKP-1 was found to have a preferential substrate binding to p38 MAPK and JNK than ERK1/2 [7] . The phosphorylation status of MAPKs was assessed in control or MKP-1 siRNA transfected PBMo. Western blotting results demonstrated that BCGinduced both p38 MAPK and ERK1/2 phosphorylation in 15 minutes (data not shown) and peaked at 30 minutes, and then returned to basal levels in cells treated with the control siRNA ( Figure 5 ). Similar to the results of cytokine expression, phosphorylation of both p38 MAPK and ERK1/2 in response to BCG was decreased in monocytes transfected with MKP-1 siRNA instead of the expected increase in phosphorylation ( Figure 5 ). The results suggest that MKP-1 knockdown would result in reduced MAPK phosphorylation by BCG, implying that the reduced level of TNF-α production in BCG stimulated monocytes is due to reduced phosphorylation of MAPKs by MKP-1 siRNA.
This report presented evidences that a novel function of MKP-1 is uncovered in cytokine regulation in response to mycobacterial infection. BCG induces MKP-1 as a rapid response (Figure 2) . The induction mechanism of MKP-1 by BCG is dependent on both ERK1/2 and p38 MAPK ( Figure 3 ). Using siRNA approach, the functions of MKP-1 can be examined in primary human monocytes. The results showed that the BCG-induced MAPKs activation as well as cytokine expression are downstream of MKP-1 ( Figures 4D and 5) . Thus, MKP-1 is a critical signaling molecule that is involved in BCG-induced cytokine expression.
Previous reports have shown that MKP-1 induced by LPS or peptidoglycan is dependent on p38 MAPK [14] . Accordingly, BCG-induced MKP-1 can be inhibited by both p38 MAPK and ERK1/2 inhibitors. Interestingly, it has been shown that degradation of MKP-1 is reduced after ERK1/2 phosphorylation [15] . It can be hypothesized that BCG-induced MKP-1 proteins can be stabilized by ERK1/2 and the detailed mechanisms involved require more exploration. Also, since the inhibition of MKP-1 expression by both inhibitors (for p38 MAPK and ERK1/ 2) was not complete, it is believed that other proteins may be involved in the BCG-induced MKP-1 expression.
On the basis of the literature results on LPS effects ( Figure 6 ), the original expectation for this project is that MKP-1 acts as a negative regulator. LPS-stimulated MKP-1 KO peritoneal macrophages showed prolonged phosphorylation of p38 MAPK and JNK as well as increased production of TNF-α [9] . In doing so, LPS-induced MKP-1 could BCG-induced MAPK phosphorylation is decreased by MKP-1 siRNA prevent prolonged TNF-α production as in sepsis which may lead to severe damage to the host. It was expected that BCG induces MKP-1 and its induction would correlate with the dephosphorylation of MAPKs including p38 MAPK. By blocking the MKP-1 using siRNA, it was expected to have increased p38 MAPK phosphorylation and prolonged TNF-α production in response to BCG. Nevertheless, our results shown here are diametrically opposite. One possibility for the unexpected results may be due to non-specific effects of transfection or siRNA. However, this was not the case since there was a prolonged and increased TNF-α expression after the MKP-1 siRNA-transfected monocytes were treated with LPS (Figure 4C ).
There is now a new hypothesis to explain such paradoxical effects of MKP-1 in TNF-α regulation in which the phosphatase plays a role in positive regulation of TNF-α production in response to BCG as in the case of DUSP2 [13] . The structures of MKP-1 and DUSP2 are similar, with which they both contain a MAPK-interacting domain and a phosphatase catalytic site. By contrast, other DUSP may have extra domains, e.g., PEST [6] . Here, we postulate that the function of MKP-1 in BCG-induced signaling is similar to that of the DUSP2/PAC1.
Actually, the discovery of DUSP2 has initially created some paradoxical questions. As described, DUSP2 behaves differently from other MKP family members [13] . In DUSP2 KO macrophages treated with LPS, they produced less inflammatory mediators including less TNF, IL-6, nitric oxide, and IL-12-producing cells, when compared to that of the wild type counterparts [13] . Indeed, the results of these published studies on DUSP2 studies are quite similar to that of our reported results here.
It is plausible that these unexpected positive regulations of immune cell functions by DUSP2 were due to crosstalks between MAPKs [13] . It was shown that there are interactions between JNK and ERK1/2 pathways [16] .
Here, we showed that the sustained activation of JNK blocks ERK activation ( Figure 6 ). In the DUSP2 situation, stimulation of KO mast cells and macrophages shows increased phosphorylation of JNK, and inhibition of JNK by its own specific inhibitor restores phosphorylation of ERK1/2 [13] .
In the BCG-MKP-1 situation, there is an early phosphorylation of p38 MAPK and ERK1/2. Therefore, it is possible that JNK may play a role in the crosstalk interaction of MAPK. However, our preliminary data suggest that the level of phosphorylated JNK was not increased in PBMo MKP-1 plays a critical role in the regulation of cytokine expression upon mycobacterial infection Figure 6 MKP-1 plays a critical role in the regulation of cytokine expression upon mycobacterial infection. LPS model was provided according to literature findings (Left). In this scenario, LPS activates MKP-1, which in turn dephosphorylates and deactivates phospho-p38 MAPK, resulting in less TNF-α induction. However, the situation in DHP-HSA activation of DUSP2 is more complicated (Middle), since the phosphatase activity causes subsequent inhibition of phospho-JNK which leads to the derepression of phospho-p38 MAPK. Consequently, the combined effects of this cascade results in more TNF-α expression. The unexpected antimycobacterial role of MKP-1 (Right) may be explained by events similar to the DUSP2 effects. In this case (Right), there was an inhibition of unknown pathways or kinases downstream of MKP-1, and the unknown factor in turn inhibits MAPKs activation leading to more TNF-α induction. The details and kinase targets are yet to be identified. transfected with MKP-1 siRNA (data not shown). Thus, the details of the crosstalk between MAPKs need further investigation. Here, we present a model to summarize the results and to hypothesize the existence of an as yet unidentified intermediary factor or factors in the pathways downstream of MKP-1 effects in the BCG-induced signaling cascade. The unexpected antimycobacterial role of MKP-1 ( Figure 6 ) may be explained by events similar to the DUSP2 effects. In this case, BCG induces MKP-1 expression while also activates MAPKs including p38 MAPK and ERK1/2. Downstream of MKP-1, there is an inhibition of unknown pathways or kinases. The unknown factor in turn inhibits MAPKs activation, which ultimately leads to more TNF-α induction ( Figure 6 ).
In summary, MKP-1 plays a critical role in the regulation of cytokine expression upon mycobacterial infection. Inhibition of unknown pathways or kinases downstream of MKP-1, which in turn inhibits MAPKs activation, may be used to explain the novel function of MKP-1 in enhancing MAPK activity and consequent TNF-α expression following BCG treatment ( Figure 6 ). Taken together, the role of MAPK crosstalks need further exploration. (3) TNF-α, 30 cycles (TM = 56°C), upstream, 5'-GGCTCCAGGCGGTGCTTGTTC-3', downstream, 5'-AGACGGCGATGCGGCTGATG-3'. PCR products were analyzed on a 1% agarose gel with ethidium bromide and visualized under ultraviolet light. In order to check the size of the PCR products, 1 kb Plus DNA Lad-der™ (Invitrogen, USA) was run along with the PCR products.
To perform QPCR, the levels of MKP-1, and TNF-α mRNA as well as the reference gene GAPDH (as internal control) were assayed by the gene-specific Assays-on-Demand reagent kits (Applied Biosystems, USA). All samples were run in duplicates or triplicates and with no template controls on an ABI Prism 7700 Sequence Detector. The analysis method of QPCR was the comparative cycle number to threshold (C T ) method as described in user bulletin no. 2 of the ABI Prism 7700 Sequence Detection System. The number of C T of the targeted genes was normalized to that of GAPDH in each sample (ΔC T ). The C T value of the treated cells was compared with that of the untreated or mock-treated cells (ΔΔCT). The relative gene expression of the targeted genes (fold induction) was calculated as 2 -ΔΔCT .
Total cellular proteins were extracted by lysing cells in lysis buffer containing 1% Triton X-100, 0.5% NP-40, 150 mM NaCl, 10 mM Tris-HCl (pH 7.4), 1 mM EDTA, 1 mM EGTA (pH 8.0), 1% SDS, 0.2 mg/ml PMSF, 1 μg/ml aprotinin, 1 mM sodium orthovanadate, 2 μg/ml pepstatin, 2 μg/ml leupeptin, and 50 mM sodium fluoride for 5 minutes. The homogenate was then boiled for 10 minutes and stored at -70°C until use. The concentrations of total protein in cell extracts were determined by BCA™ Protein Assay Kit (Pierce, IL, USA).
Western blot was done as described [20] . Equal amounts of protein were separated by 10% SDS-PAGE, electroblotted onto nitrocellulose membranes (Schleicher & Schuell), and followed by probing with specific antibod-ies for Actin, MKP-1 (Santa Cruz Biotech., USA), phospho-p38 MAPK, phospho-ERK1/2 (Cell Signaling, USA). After three washes, the membranes were incubated with the corresponding secondary antibodies. The bands were detected using the Enhanced Chemiluminescence System (Amersham Pharmacia Biotech) as per the manufacturer's instructions.
Transfection of siRNA into human monocytes was done as described [21] . MKP-1 siRNA included (i) MKP1-HSS102982, AAACGCUUCGUAUCCUCCUUUGAGG; (ii) MKP1-HSS102983, UUAUGCCCAAGGCAUCCAG-CAUGUC; and (iii) MKP1-HSS102984, UGAUG-GAGUCUAUGAAGUCAAUGGC. MKP-1 knockdown in PBMo was conducted by using MKP1-HSS102983 only or a pool of the above three different MKP-1 Stealth™ Select RNAi (ratio = 1:1:1, 200 nM, Invitrogen, USA). Stealth™ RNAi Negative Control Duplex (200 nM) was used as a control for sequence independent effects for the siRNA transfection. Transfection of monocytes was done by using jetPEI™ DNA transfection reagent (Polyplus Transfection, USA) according to the manufacturer's instructions. After transfecting the cells for 24 h, the transfectants were treated with different inducers as described above.
Statistical analysis was performed by Student's t test. Differences were considered statistically significant when p values were less than 0.05. | What percentage of the world has been infected by tuberculosis? | false | 891 | {
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1,671 | Host resilience to emerging coronaviruses
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7079962/
SHA: f7cfc37ea164f16393d7f4f3f2b32214dea1ded4
Authors: Jamieson, Amanda M
Date: 2016-07-01
DOI: 10.2217/fvl-2016-0060
License: cc-by
Abstract: Recently, two coronaviruses, severe acute respiratory syndrome coronavirus and Middle East respiratory syndrome coronavirus, have emerged to cause unusually severe respiratory disease in humans. Currently, there is a lack of effective antiviral treatment options or vaccine available. Given the severity of these outbreaks, and the possibility of additional zoonotic coronaviruses emerging in the near future, the exploration of different treatment strategies is necessary. Disease resilience is the ability of a given host to tolerate an infection, and to return to a state of health. This review focuses on exploring various host resilience mechanisms that could be exploited for treatment of severe acute respiratory syndrome coronavirus, Middle East respiratory syndrome coronavirus and other respiratory viruses that cause acute lung injury and acute respiratory distress syndrome.
Text: The 21st century was heralded with the emergence of two novel coronaviruses (CoV) that have unusually high pathogenicity and mortality [1] [2] [3] [4] [5] . Severe acute respiratory syndrome coronavirus (SARS-Cov) was first identified in 2003 [6] [7] [8] [9] . While there was initially great concern about SARS-CoV, once no new cases emerged, funding and research decreased. However, a decade later Middle East respiratory syndrome coronavirus (MERS-CoV), also known as HCoV-EMC, emerged initially in Saudi Arabia [3, 10] . SARS-CoV infected about 8000 people, and resulted in the deaths of approximately 10% of those infected [11] . While MERS-CoV is not as widespread as SARS-CoV, it appears to have an even higher mortality rate, with 35-50% of diagnosed infections resulting in death [3, [12] [13] . These deadly betacoronavirus viruses existed in animal reservoirs [4] [5] 9, [14] [15] . Recently, other CoVs have been detected in animal populations raising the possibility that we will see a repeat of these types of outbreaks in the near future [11, [16] [17] [18] [19] [20] . Both these zoonotic viruses cause a much more severe disease than what is typically seen for CoVs, making them a global health concern. Both SARS-CoV and MERS-CoV result in severe lung pathology. Many infected patients have acute lung injury (ALI), a condition that is diagnosed based on the presence of pulmonary edema and respiratory failure without a cardiac cause. In some patients there is a progression to the more severe form of ALI, acute respiratory distress syndrome (ARDS) [21] [22] [23] .
In order to survive a given infection, a successful host must not only be able to clear the pathogen, but tolerate damage caused by the pathogen itself and also by the host's immune response [24] [25] [26] . We refer to resilience as the ability of a host to tolerate the effects of pathogens and the immune response to pathogens. A resilient host is able to return to a state of health after responding to an infection [24, [27] [28] . Most currently available treatment options for infectious diseases are antimicrobials, For reprint orders, please contact: [email protected] REviEW Jamieson future science group and thus target the pathogen itself. Given the damage that pathogens can cause this focus on rapid pathogen clearance is understandable. However, an equally important medical intervention is to increase the ability of the host to tolerate the direct and indirect effects of the pathogen, and this is an area that is just beginning to be explored [29] . Damage to the lung epithelium by respiratory pathogens is a common cause of decreased resilience [30] [31] [32] . This review explores some of the probable host resilience pathways to viral infections, with a particular focus on the emerging coronaviruses. We will also examine factors that make some patients disease tolerant and other patients less tolerant to the viral infection. These factors can serve as a guide to new potential therapies for improved patient care.
Both SARS-CoV and MERS-CoV are typified by a rapid progression to ARDS, however, there are some distinct differences in the infectivity and pathogenicity. The two viruses have different receptors leading to different cellular tropism, and SARS-CoV is more ubiquitous in the cell type and species it can infect. SARS-CoV uses the ACE2 receptor to gain entry to cells, while MERS-CoV uses the ectopeptidase DPP4 [33] [34] [35] [36] . Unlike SARS-CoV infection, which causes primarily a severe respiratory syndrome, MERS-CoV infection can also lead to kidney failure [37, 38] . SARS-CoV also spreads more rapidly between hosts, while MERS-CoV has been more easily contained, but it is unclear if this is due to the affected patient populations and regions [3] [4] 39 ]. Since MERS-CoV is a very recently discovered virus, [40, 41] more research has been done on SARS-CoV. However, given the similarities it is hoped that some of these findings can also be applied to MERS-CoV, and other potential emerging zoonotic coronaviruses.
Both viral infections elicit a very strong inflammatory response, and are also able to circumvent the immune response. There appears to be several ways that these viruses evade and otherwise redirect the immune response [1, [42] [43] [44] [45] . The pathways that lead to the induction of the antiviral type I interferon (IFN) response are common targets of many viruses, and coronaviruses are no exception. SARS-CoV and MERS-CoV are contained in double membrane vesicles (DMVs), that prevents sensing of its genome [1, 46] . As with most coronaviruses several viral proteins suppress the type I IFN response, and other aspects of innate antiviral immunity [47] . These alterations of the type I IFN response appear to play a role in immunopathology in more than one way. In patients with high initial viral titers there is a poor prognosis [39, 48] . This indicates that reduction of the antiviral response may lead to direct viral-induced pathology. There is also evidence that the delayed type I IFN response can lead to misregulation of the immune response that can cause immunopathology. In a mouse model of SARS-CoV infection, the type I IFN response is delayed [49] . The delay of this potent antiviral response leads to decreased viral clearance, at the same time there is an increase in inflammatory cells of the immune system that cause excessive immunopathology [49] . In this case, the delayed antiviral response not only causes immunopathology, it also fails to properly control the viral replication. While more research is needed, it appears that MERS has a similar effect on the innate immune response [5, 50] .
The current treatment and prevention options for SARS-CoV and MERS-CoV are limited. So far there are no licensed vaccines for SAR-CoV or MERS-CoV, although several strategies have been tried in animal models [51, 52] . There are also no antiviral strategies that are clearly effective in controlled trials. During outbreaks several antiviral strategies were empirically tried, but these uncontrolled studies gave mixed results [5, 39] . The main antivirals used were ribavirin, lopinavir and ritonavir [38, 53] . These were often used in combination with IFN therapy [54] . However, retrospective analysis of these data has not led to clear conclusions of the efficacy of these treatment options. Research in this area is still ongoing and it is hoped that we will soon have effective strategies to treat novel CoV [3,36,38,40, [55] [56] [57] [58] [59] [60] [61] [62] [63] [64] .
The lack of effective antivirals makes it necessary to examine other potential treatments for SARS-CoV and MERS-CoV. Even if there were effective strategies to decrease viral burden, for these viruses, the potential for new emerging zoonotic CoVs presents additional complications. Vaccines cannot be produced in time to stop the spread of an emerging virus. In addition, as was demonstrated during SARS-CoV and MERS-CoV outbreaks, there is always a challenge during a crisis situation to know which Host resilience to emerging coronaviruses REviEW future science group www.futuremedicine.com antiviral will work on a given virus. One method of addressing this is to develop broad-spectrum antivirals that target conserved features of a given class of virus [65] . However, given the fast mutation rates of viruses there are several challenges to this strategy. Another method is to increase the ability of a given patient to tolerate the disease, i.e., target host resilience mechanisms. So far this has largely been in the form of supportive care, which relies on mechanical ventilation and oxygenation [29, 39, 66] .
Since SARS-CoV and MERS-CoV were discovered relatively recently there is a lack of both patient and experimental data. However, many other viruses cause ALI and ARDS, including influenza A virus (IAV). By looking at data from other high pathology viruses we can extrapolate various pathways that could be targeted during infection with these emerging CoVs. This can add to our understanding of disease resilience mechanisms that we have learned from direct studies of SARS-CoV and MERS-CoV. Increased understanding of host resilience mechanisms can lead to future host-based therapies that could increase patient survival [29] .
One common theme that emerges in many respiratory viruses including SARS-CoV and MERS-CoV is that much of the pathology is due to an excessive inflammatory response. A study from Josset et al. examines the cell host response to both MERS-CoV and SARS-CoV, and discovered that MERS-CoV dysregulates the host transcriptome to a much greater extent than SARS-CoV [67] . It demonstrates that glucocorticoids may be a potential way of altering the changes in the host transcriptome at late time points after infection. If host gene responses are maintained this may increase disease resilience. Given the severe disease that manifested during the SARS-CoV outbreak, many different treatment options were empirically tried on human patients. One immunomodulatory treatment that was tried during the SARS-CoV outbreak was systemic corticosteroids. This was tried with and without the use of type I IFNs and other therapies that could directly target the virus [68] . Retrospective analysis revealed that, when given at the correct time and to the appropriate patients, corticosteroid use could decrease mortality and also length of hospital stays [68] . In addition, there is some evidence that simultaneous treatment with IFNs could increase the potential benefits [69] . Although these treatments are not without complications, and there has been a lack of a randomized controlled trial [5, 39] .
Corticosteroids are broadly immunosuppressive and have many physiological effects [5, 39] . Several recent studies have suggested that other compounds could be useful in increasing host resilience to viral lung infections. A recent paper demonstrates that topoisomerase I can protect against inflammation-induced death from a variety of viral infections including IAV [70] . Blockade of C5a complement signaling has also been suggested as a possible option in decreasing inflammation during IAV infection [71] . Other immunomodulators include celecoxib, mesalazine and eritoran [72, 73] . Another class of drugs that have been suggested are statins. They act to stabilize the activation of aspects of the innate immune response and prevent excessive inflammation [74] . However, decreasing immunopathology by immunomodulation is problematic because it can lead to increased pathogen burden, and thus increase virus-induced pathology [75, 76] . Another potential treatment option is increasing tissue repair pathways to increase host resilience to disease. This has been shown by bioinformatics [77] , as well as in several animal models [30-31,78-79]. These therapies have been shown in cell culture model systems or animal models to be effective, but have not been demonstrated in human patients. The correct timing of the treatments is essential. Early intervention has been shown to be the most effective in some cases, but other therapies work better when given slightly later during the course of the infection. As the onset of symptoms varies slightly from patient to patient the need for precise timing will be a challenge.
Examination of potential treatment options for SARS-CoV and MERS-CoV should include consideration of host resilience [29] . In addition to the viral effects, and the pathology caused by the immune response, there are various comorbidities associated with SARS-CoV and MERS-CoV that lead to adverse outcomes. Interestingly, these additional risk factors that lead to a more severe disease are different between the two viruses. It is unclear if these differences are due to distinct populations affected by the viruses, because of properties of the virus themselves, or both. Understanding these factors could be a key to increasing host resilience to the infections. MERS-CoV patients had increased morbidity and mortality if they were obese, immunocompromised, diabetic or had cardiac disease [4, 12] .
REviEW Jamieson future science group Risk factors for SARS-CoV patients included an older age and male [39] . Immune factors that increased mortality for SARS-CoV were a higher neutrophil count and low T-cell counts [5, 39, 77] . One factor that increased disease for patients infected with SARS-CoV and MERS-CoV was infection with other viruses or bacteria [5, 39] . This is similar to what is seen with many other respiratory infections. A recent study looking at malaria infections in animal models and human patients demonstrated that resilient hosts can be predicted [28] . Clinical studies have started to correlate specific biomarkers with disease outcomes in ARDS patients [80] . By understanding risk factors for disease severity we can perhaps predict if a host may be nonresilient and tailor the treatment options appropriately.
A clear advantage of targeting host resilience pathways is that these therapies can be used to treat a variety of different infections. In addition, there is no need to develop a vaccine or understand the antiviral susceptibility of a new virus. Toward this end, understanding why some patients or patient populations have increased susceptibility is of paramount importance. In addition, a need for good model systems to study responses to these new emerging coronaviruses is essential. Research into both these subjects will lead us toward improved treatment of emerging viruses that cause ALI, such as SARS-CoV and MERS-CoV.
The author has no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
No writing assistance was utilized in the production of this manuscript.
• Severe acute respiratory syndrome coronavirus and Middle East respiratory syndrome coronavirus are zoonotic coronaviruses that cause acute lung injury and acute respiratory distress syndrome.
• Antivirals have limited effects on the course of the infection with these coronaviruses.
• There is currently no vaccine for either severe acute respiratory syndrome coronavirus or Middle East respiratory syndrome coronavirus.
• Host resilience is the ability of a host to tolerate the effects of an infection and return to a state of health.
• Several pathways, including control of inflammation, metabolism and tissue repair may be targeted to increase host resilience.
• The future challenge is to target host resilience pathways in such a way that there are limited effects on pathogen clearance pathways. Future studies should determine the safety of these types of treatments for human patients.
Papers of special note have been highlighted as: | What is the relationship between SARS-CoV and acute respiratory distress syndrome (ARDS)? | false | 1,263 | {
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2,669 | Frontiers in antiviral therapy and immunotherapy
https://doi.org/10.1002/cti2.1115
SHA: facbfdfa7189ca9ff83dc30e5d241ab22e962dbf
Authors: Heaton, Steven M
Date: 2020
DOI: 10.1002/cti2.1115
License: cc-by
Abstract: nan
Text: Globally, recent decades have witnessed a growing disjunction, a 'Valley of Death' 1,2 no less, between broadening strides in fundamental biomedical research and their incommensurate reach into the clinic. Plumbing work on research funding and development pipelines through recent changes in the structure of government funding, 2 new public and private joint ventures and specialist undergraduate and postgraduate courses now aim to incorporate pathways to translation at the earliest stages. Reflecting this shift, the number of biomedical research publications targeting 'translational' concepts has increased exponentially, up 1800% between 2003 and 2014 3 and continuing to rise rapidly up to the present day. Fuelled by the availability of new research technologies, as well as changing disease, cost and other pressing issues of our time, further growth in this exciting space will undoubtedly continue. Despite recent advances in the therapeutic control of immune function and viral infection, current therapies are often challenging to develop, expensive to deploy and readily select for resistance-conferring mutants. Shaped by the hostvirus immunological 'arms race' and tempered in the forge of deep time, the biodiversity of our world is increasingly being harnessed for new biotechnologies and therapeutics. Simultaneously, a shift towards host-oriented antiviral therapies is currently underway. In this Clinical & Translational Immunology Special Feature, I illustrate a strategic vision integrating these themes to create new, effective, economical and robust antiviral therapies and immunotherapies, with both the realities and the opportunities afforded to researchers working in our changing world squarely in mind.
Opening this CTI Special Feature, I outline ways these issues may be solved by creatively leveraging the so-called 'strengths' of viruses. Viral RNA polymerisation and reverse transcription enable resistance to treatment by conferring extraordinary genetic diversity. However, these exact processes ultimately restrict viral infectivity by strongly limiting virus genome sizes and their incorporation of new information. I coin this evolutionary dilemma the 'information economy paradox'. Many viruses attempt to resolve this by manipulating multifunctional or multitasking host cell proteins (MMHPs), thereby maximising host subversion and viral infectivity at minimal informational cost. 4 I argue this exposes an 'Achilles Heel' that may be safely targeted via host-oriented therapies to impose devastating informational and fitness barriers on escape mutant selection. Furthermore, since MMHPs are often conserved targets within and between virus families, MMHP-targeting therapies may exhibit both robust and broadspectrum antiviral efficacy. Achieving this through drug repurposing will break the vicious cycle of escalating therapeutic development costs and trivial escape mutant selection, both quickly and in multiple places. I also discuss alternative posttranslational and RNA-based antiviral approaches, designer vaccines, immunotherapy and the emerging field of neo-virology. 4 I anticipate international efforts in these areas over the coming decade will enable the tapping of useful new biological functions and processes, methods for controlling infection, and the deployment of symbiotic or subclinical viruses in new therapies and biotechnologies that are so crucially needed.
Upon infection, pathogens stimulate expression of numerous host inflammatory factors that support recruitment and activation of immune cells. On the flip side, this same process also causes immunopathology when prolonged or deregulated. 5 In their contribution to this Special Feature, Yoshinaga and Takeuchi review endogenous RNA-binding proteins (RBPs) that post-transcriptionally control expression of crucial inflammatory factors in various tissues and their potential therapeutic applications. 6 These RBPs include tristetraprolin and AUF1, which promote degradation of AU-rich element (ARE)-containing mRNA; members of the Roquin and Regnase families, which respectively promote or effect degradation of mRNAs harbouring stem-loop structures; and the increasingly apparent role of the RNA methylation machinery in controlling inflammatory mRNA stability. These activities take place in various subcellular compartments and are differentially regulated during infection. In this way, mRNA-destabilising RBPs constitute a 'brake' on the immune system, which may ultimately be toggled therapeutically. I anticipate continued efforts in this area will lead to new methods of regaining control over inflammation in autoimmunity, selectively enhancing immunity in immunotherapy, and modulating RNA synthesis and virus replication during infection.
Another mRNA under post-transcriptional regulation by Regnase-1 and Roquin is Furin, which encodes a conserved proprotein convertase crucial in human health and disease. Furin, along with other PCSK family members, is widely implicated in immune regulation, cancer and the entry, maturation or release of a broad array of evolutionarily diverse viruses including human papillomavirus (HPV), influenza (IAV), Ebola (EboV), dengue (DenV) and human immunodeficiency virus (HIV). Here, Braun and Sauter review the roles of furin in these processes, as well as the history and future of furin-targeting therapeutics. 7 They also discuss their recent work revealing how two IFN-cinducible factors exhibit broad-spectrum inhibition of IAV, measles (MV), zika (ZikV) and HIV by suppressing furin activity. 8 Over the coming decade, I expect to see an ever-finer spatiotemporal resolution of host-oriented therapies to achieve safe, effective and broad-spectrum yet costeffective therapies for clinical use.
The increasing abundance of affordable, sensitive, high-throughput genome sequencing technologies has led to a recent boom in metagenomics and the cataloguing of the microbiome of our world. The MinION nanopore sequencer is one of the latest innovations in this space, enabling direct sequencing in a miniature form factor with only minimal sample preparation and a consumer-grade laptop computer. Nakagawa and colleagues here report on their latest experiments using this system, further improving its performance for use in resource-poor contexts for meningitis diagnoses. 9 While direct sequencing of viral genomic RNA is challenging, this system was recently used to directly sequence an RNA virus genome (IAV) for the first time. 10 I anticipate further improvements in the performance of such devices over the coming decade will transform virus surveillance efforts, the importance of which was underscored by the recent EboV and novel coronavirus (nCoV / COVID-19) outbreaks, enabling rapid deployment of antiviral treatments that take resistance-conferring mutations into account.
Decades of basic immunology research have provided a near-complete picture of the main armaments in the human antiviral arsenal. Nevertheless, this focus on mammalian defences and pathologies has sidelined examination of the types and roles of viruses and antiviral defences that exist throughout our biosphere. One case in point is the CRISPR/Cas antiviral immune system of prokaryotes, which is now repurposed as a revolutionary gene-editing biotechnology in plants and animals. 11 Another is the ancient lineage of nucleocytosolic large DNA viruses (NCLDVs), which are emerging human pathogens that possess enormous genomes of up to several megabases in size encoding hundreds of proteins with unique and unknown functions. 12 Moreover, hundreds of human-and avian-infective viruses such as IAV strain H5N1 are known, but recent efforts indicate the true number may be in the millions and many harbour zoonotic potential. 13 It is increasingly clear that host-virus interactions have generated truly vast yet poorly understood and untapped biodiversity. Closing this Special Feature, Watanabe and Kawaoka elaborate on neo-virology, an emerging field engaged in cataloguing and characterising this biodiversity through a global consortium. 14 I predict these efforts will unlock a vast wealth of currently unexplored biodiversity, leading to biotechnologies and treatments that leverage the host-virus interactions developed throughout evolution.
When biomedical innovations fall into the 'Valley of Death', patients who are therefore not reached all too often fall with them. Being entrusted with the resources and expectation to conceive, deliver and communicate dividends to society is both cherished and eagerly pursued at every stage of our careers. Nevertheless, the road to research translation is winding and is built on a foundation of basic research. Supporting industry-academia collaboration and nurturing talent and skills in the Indo-Pacific region are two of the four pillars of the National Innovation and Science Agenda. 2 These frame Australia's Medical Research and Innovation Priorities, which include antimicrobial resistance, global health and health security, drug repurposing and translational research infrastructure, 15 capturing many of the key elements of this CTI Special Feature. Establishing durable international relationships that integrate diverse expertise is essential to delivering these outcomes. To this end, NHMRC has recently taken steps under the International Engagement Strategy 16 to increase cooperation with its counterparts overseas. These include the Japan Agency for Medical Research and Development (AMED), tasked with translating the biomedical research output of that country. Given the reciprocal efforts at accelerating bilateral engagement currently underway, 17 the prospects for new areas of international cooperation and mobility have never been more exciting nor urgent. With the above in mind, all contributions to this CTI Special Feature I have selected from research presented by fellow invitees to the 2018 Awaji International Forum on Infection and Immunity (AIFII) and 2017 Consortium of Biological Sciences (ConBio) conferences in Japan. Both Australia and Japan have strong traditions in immunology and related disciplines, and I predict that the quantity, quality and importance of our bilateral cooperation will accelerate rapidly over the short to medium term. By expanding and cooperatively leveraging our respective research strengths, our efforts may yet solve the many pressing disease, cost and other sustainability issues of our time. | How do these exact processes ultimately restrict viral infectivity? | false | 4,127 | {
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1,713 | Ebola Virus Maintenance: If Not (Only) Bats, What Else?
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6213544/
SHA: f16da7cf7a952fb981dfc0d77280aac9c3ab933a
Authors: Caron, Alexandre; Bourgarel, Mathieu; Cappelle, Julien; Liégeois, Florian; De Nys, Hélène M.; Roger, François
Date: 2018-10-09
DOI: 10.3390/v10100549
License: cc-by
Abstract: The maintenance mechanisms of ebolaviruses in African forest ecosystems are still unknown, but indirect evidences point at the involvement of some bat species. Despite intense research, the main bat-maintenance hypothesis has not been confirmed yet. The alternative hypotheses of a non-bat maintenance host or a maintenance community including, or not, several bat and other species, deserves more investigation. However, African forest ecosystems host a large biodiversity and abound in potential maintenance hosts. How does one puzzle out? Since recent studies have revealed that several bat species have been exposed to ebolaviruses, the common denominator to these hypotheses is that within the epidemiological cycle, some bats species must be exposed to the viruses and infected by these potential alternative hosts. Under this constraint, and given the peculiar ecology of bats (roosting behaviour, habitat utilisation, and flight mode), we review the hosts and transmission pathways that can lead to bat exposure and infection to ebolaviruses. In contrast to the capacity of bats to transmit ebolaviruses and other pathogens to many hosts, our results indicate that only a limited number of hosts and pathways can lead to the transmission of ebolaviruses to bats, and that the alternative maintenance host, if it exists, must be amongst them. A list of these pathways is provided, along with protocols to prioritise and investigate these alternative hypotheses. In conclusion, taking into account the ecology of bats and their known involvement in ebolaviruses ecology drastically reduces the list of potential alternative maintenance hosts for ebolaviruses. Understanding the natural history of ebolaviruses is a health priority, and investigating these alternative hypotheses could complete the current effort focused on the role of bats.
Text: Ebolaviruses (EBVs), according to Kuhn et al. classification [1] ) are single-strand RNA filoviruses that can induce a high mortality in some hosts, including apes and humans [2, 3] . The different ebolaviruses have caused localised but dramatic human outbreaks, mainly in Central Africa, in the last 40 years. The recent West African outbreak in 2013-2016 gave an outline of the pandemic potential of these pathogens [4, 5] .
Disentangling the complexity of maintenance hosts or communities in multi-host systems at the wildlife/livestock/human interface is a difficult task [16] [17] [18] . The maintenance of EBV in equatorial forests is yet to be understood. Some mammal species played a major role in triggering human outbreaks: apes such as chimpanzees (Pan troglodytes troglodytes and P. t. verus) and western lowland gorillas (Gorilla gorilla gorilla) were at the origin of several human outbreaks [10] [11] [12] , but have been found to be highly susceptible to EBV with potential drastic impact for their populations [12, 19] . EBOV PCR positive duiker carcasses (Cephalophus sp.) have also been found [20] . One would not expect such a high mortality (relative to their population density) of EBOV in maintenance hosts. However, these data indicate their possible involvement in the transmission function of EBOV, bridging the maintenance host with human populations during a spillover event [18] (Figure 1 ). The EBOV susceptibility and exposure (tested by virology, serology and/or PCR) of many other potential forest hosts, including invertebrates, birds, bats, monkeys, rodents, and other small mammals, have been tested in the field or experimentally with an interestingly large amount of negative results (e.g., [12, [21] [22] [23] [24] [25] [26] ). A few monkey and bat individuals serologically positive to EBV antigen represent the only exceptions [12] .
Today, African bats are considered by many as the best candidates for acting as maintenance hosts for EBOV. Partial vRNA was sequenced from living specimens of three different bat species in Central Africa [23] , and antibodies against ebolavirus antigen have been detected in 9 bat species (8 frugivorous and 1 insectivorous) [3, 23, [27] [28] [29] [30] . Recently, a new ebolavirus species with an unknown pathogenic risk has also been isolated from two insectivorous bat species roosting inside a house [31] . Moreover, Swanepoel et al. showed that EBOV replicated in three species of experimentally infected bats (Tadarida condylura, Tadarida pumila, and Epomophorus wahlbergi), including virus isolated from faeces 21 days after experimental infection [22] . In addition, some bat species have been shown to act as maintenance hosts for multiple RNA viruses, including filoviruses (e.g., [32] [33] [34] ). However, to date, no EBOV replicative strain has been isolated from healthy wild bats despite thousands of individuals tested [14, [23] [24] [25] 28, 34, 35] . Given the current knowledge, the main hypotheses for EBOV maintenance are a single bat species as Rousettus aegyptiacus is considered the maintenance host for Marburg virus ( Figure 1A1 ); or a network of interacting bat species creating a maintenance community for EBOV ( Figure 1A2 ).
The bat system is complex. First, for its diversity: globally, they represent over 20% of the mammal diversity, forming the second largest mammalian order after rodents, and Africa hosts 317 known living species, 25% of the global bat diversity [36] . Secondly, bats have exceptional lifestyles that have already been reviewed, especially in relation to their role in disease ecology [33, [37] [38] [39] [40] [41] [42] [43] . They are unique mammal species regrouping such peculiar life history traits as their aerial life mode, their longevity, their gregarious and migration patterns, as well as their immune system. bridging the maintenance host with human populations during a spillover event [18] (Figure 1 ). The EBOV susceptibility and exposure (tested by virology, serology and/or PCR) of many other potential forest hosts, including invertebrates, birds, bats, monkeys, rodents, and other small mammals, have been tested in the field or experimentally with an interestingly large amount of negative results (e.g., [12, [21] [22] [23] [24] [25] [26] ). A few monkey and bat individuals serologically positive to EBV antigen represent the only exceptions [12] .
Potential maintenance mechanisms of ebolaviruses in wildlife, according to current knowledge. Circles (plain or dotted) indicate a maintenance function play by the host(s); arrows represent infectious transmission pathways between hosts. Humans, non-human primates, and duikers are examples of known non-maintenance hosts, exposed occasionally to ebolavirus directly or indirectly through the main maintenance host. (A1) Main maintenance hypothesis: there is one bat Figure 1 . Potential maintenance mechanisms of ebolaviruses in wildlife, according to current knowledge. Circles (plain or dotted) indicate a maintenance function play by the host(s); arrows represent infectious transmission pathways between hosts. Humans, non-human primates, and duikers are examples of known non-maintenance hosts, exposed occasionally to ebolavirus directly or indirectly through the main maintenance host. (A1) Main maintenance hypothesis: there is one bat species maintaining each ebolavirus alone. Currently this is logically the most investigated hypothesis given the available data, and represents the maintenance mechanism for another filovirus, the Marburg virus, as currently understood. (A2) Several bat species are needed to create a maintenance community for Zaire ebolavirus (EBOV); each bat species cannot complete EBOV maintenance alone, as it requires interactions with the other species. (B) Alternate non-bat maintenance host hypothesis: if it exists, it is known that it can transmit ebolaviruses to some bat species. In this article, we review the potential hosts and associated transmission pathways that link this host to bat species (red arrow). (C) The maintenance community hypothesis, in which several hosts are needed to maintain ebolaviruses (ellipses represent different scenarios of community maintenance). This could be one or more alternative hosts involving possibly bat species. By definition, if such an alternative host exists, there are infectious transmission pathways from this host towards bats that are reviewed here (red arrows).
Proving that a bat species maintains EBOV (e.g., [44, 45] ), or that interconnected populations of different bat species create the cradle for EBOV maintenance in a specific ecosystem, is a difficult task. Finding a live virus in a healthy bat specimen would constitute a great step in proving that this particular species is part or the totality of the EBOV maintenance. However, this finding would also trigger new questions: does this species act alone to maintain EBOV, or do other sympatric bat species' populations create a maintenance community for EBOV? Is this EBOV maintenance system unique or ecosystem specific? Additionally, are other non-bat species involved in the maintenance? The road to identifying the maintenance host(s) of EBOV is still long.
The gaps in knowledge concerning the maintenance of EBOV and other EBV are therefore still significant. Available data indicates a systematic but weak signal in some bat species, a pattern in line with the main bat maintenance hypotheses, but not excluding as well alternative hypotheses as presented in Figure 1B ,C. If those alternative scenarios do not necessarily agree with the Occam's razor principle, they still cannot be ignored by the scientific community. African forest ecosystems host a high diversity of organisms relative to other ecosystems, and provide a rich pool of candidate species for playing a role in EBOV maintenance. EBOV specialists agree in calling for more integrated efforts across scientific fields, notably epidemiology, ecology, molecular biology, remote sensing modelling, and social sciences to test new hypotheses [39] . We provide, here, an ecological perspective on the EBOV multi-host system to provide a hypothesis-driven framework for future work. There is still a possibility that bats are not part of or that non-bat species are involved in the EBOV maintenance system and alternative scenarios should be considered and explored ( Figure 1 ) [46] . These scenarios should be investigated, when possible, alongside bat-centred protocols, to confirm or invalidate the case for bats as EBOV maintenance hosts.
When a probability P is difficult or impossible to estimate, it is sometimes easier to estimate its inverse probability (1-P), the probability that it does not happen. It would be tedious to quantitatively estimate probabilities in the case of ebolavirus maintenance given the current lack of information, but trying to define the components of this probability could help. Hence, instead of proving that bats are the maintenance host for EBOV, what if we consider that "bats are not the (only) maintenance host for EBOV"?
Here, we consider the scenario presented in Figure 1B ,C, namely, that bats are not the maintenance host for EBOV or that bat species are involved with alternative host(s) in the EBOV maintenance community. Current data and knowledge support both scenarios. Some bats are sometimes in contact with the virus and experience waves of exposure during outbreaks [27] . Once infected, bats could either be dead-end hosts, as some experimental studies suggest that some bat species cannot excrete the virus [47] ); or they could transmit viruses to other hosts, such as primates including humans [6, 48, 49] as a bridge host, linking the maintenance host with humans. This means based on the definition of a bridge host [18] , that these bats must have been in contact, at some point in the epidemiological cycle, with the maintenance host (or another bridge host) to get the EBOV infection. Here, "contact" means infectious contact, and can be direct (e.g., physical) or indirect (e.g., through the environment). The search for alternative maintenance hosts for EBOV should, therefore, concentrate on hosts that can transmit the virus to bats. In other words, any host that could not transmit the virus to bats would be ineligible to be a maintenance host for EBOV. This holds for any host found exposed to EBOV (e.g., some duiker sp.) but the focus on bats is justified in the following section.
The ecology of most African bat species is largely unknown. It can still be summarised as follows: roosting in trees (hanging or in holes) or caves, flying, eating insects while flying (insectivorous bats)/eating fruits in trees (fruit bat), flying back and roosting in trees or caves; with biannual long-range migration or nomadic movements for some species [50] . A single bat can cover a large variety of habitats and even regions for those migrating. Therefore, the transmission pathways from bats to other animals through urine, saliva, birthing fluids, and placental material and/or guano could be important (see review on Ebola isolated from body tissues and fluids [51] ). Predation is also a less known but potential transmission pathway from bats to predators [48, 52] . The range of potential species at risk of infection from bats is thus large [53] . However, the range of potential transmission pathways available for the maintenance or bridge host (under scenario B and C in Figure 1 ) to infect bats seems to be much more limited. For example, bats seldom use the ground floor: transmission routes requiring direct contact or environmental transmission on the ground do not expose bats. In other terms, direct contacts with strictly ground-dwelling animals would be very unlikely. Four habitat types structure the various transmission pathways from the alternative host to bats (and each bat species will frequent only a fraction of these habitats: (i) open air while flying, for insectivorous bats also while feeding; (ii) surface water when drinking; (iii) cave roofs and walls as roost habitat; (iv) tree canopy for roosting or feeding. From these four habitats, potential transmission routes to infect bats from other hosts can be inferred (Table 1 ). In the following sections, the different transmission pathways that can link potential alternative hosts to bats are listed and discussed, along with examples of these alternative hosts.
Firstly, EBOV transmission to bats could occur through aerosol transmission in all four habitats. This means that the maintenance host would release, in bats' airspace, enough EBOV to contaminate bats. In theory, this would be possible in most bat environments, but we have discarded open-air transmission (e.g., in-flight bird to bat transmission) as the load of virus in the air cannot reach the levels that ensure infection. However, in the confined atmosphere of caves, bat to human transmission of rabies has been suspected [54] [55] [56] . EBOV and other filovirus particles seem to be able to persist for at least 90 min as aerosol [57, 71] , and experimental studies conducted on non-human primates (NHPs) by inoculating EBOV via the aerosol route were able to induce fatal disease 5 to 12 days post-inoculation [58] . Experimental airborne transmission of EBOV between animals from different species, e.g., from pigs to non-human primates, also seems possible [74] . In caves, the aerosol route might thus be possible. However, as bats tend to roost aggregated in groups and sometimes in large colonies, the ambient air may be saturated by bats' aerosols, rather than an alternative host. Air screening could be attempted in bat habitats but experimental aerosol transmission trials from alternative hosts to bats would be more efficient.
Bats are exposed to ectoparasitism [61] . If the biting invertebrate has previously bitten the alternative maintenance host, it could, in principle, infect bats. Hematophagous insects have been screened for EBOV during or after outbreaks with no conclusive results [26, 75] . However, absence of exposure during an outbreak does not mean that the host is not involved in the maintenance of the virus in-between outbreaks. For example, the process of amplification in disease ecology can involve different hosts than maintenance hosts. Little information is available on ticks in bats. Ticks have been suggested to be involved in the transmission of Crimean-Congo haemorrhagic fever-like viruses to bats [76] , and are seriously considered as potential hosts for the transmission of other pathogens from non-bat hosts to bats. Mosquitos could also be a vessel for a vector-borne transmission of EBOV. Studies on mosquito blood meals have revealed that mosquito could feed on bats and other mammals [62, 63] . Bat flies appear to be highly bat-specific, adapted to their lifestyle [77] [78] [79] [80] and are involved in the transmission of pathogens [64] . However, this specificity would preclude interspecies pathogen transmission. Ectoparasitism provides a potential solid source of indirect contacts between the alternative maintenance host and bats. This transmission pathway should be explored much further, and ecological insights, including insect and bat behavioural ecology, will be necessary to target the right insect species within the diversity of available biting species, in the right habitat (e.g., tree canopy level, caves' roofs, when bats are immobile) at a proper time (e.g., nocturnal behaviour of bats) and season, when both hosts (i.e., the maintenance host and bats) can be fed upon by the vector. To our knowledge, such targeted protocols have not been implemented so far.
Insectivorous bats feed on insects that could be a source of EBOV [61] . This food-borne route has been little investigated as well. A recent study pointed out the role of insect-specific viruses in the evolution of numerous viral families, including mononegaviruses, which infect vertebrates [81] . There is a possibility that prey-insects are the maintenance host for EBOV [61] . Insect vectors, such as blood feeding insects (e.g., mosquitos) could also, in theory, transport viruses in their blood meal after a bite on an infected host. They have been suspected in other filovirus outbreaks in the past [82] . In theory, these insects preyed upon by bats could also link bats to any type of maintenance host they could feed on. Bats actively search for prey in many different habitats hosting hematophagous insects that feed on habitat-specific fauna. Moreover, Reiskind et al. suggested that blood fed female mosquitos are more susceptible to predation [66] . Leendertz et al. also suggested that the population dynamics of mayflies may act as a driver of EBOV emergence in mammals and humans [46] . Insectivorous bat diet analysis could, therefore, indicate the relative proportion of hematophagous insect fed upon by bats and their identity, in order to subsequently target these insect species for sampling.
The EBOV maintenance host could shed viable viruses in the environment where bats could get infected by environmental exposure. The most likely habitats where this can happen are tree canopies and holes, and cave roofs/walls used only by a fraction of hosts inhabiting forests. The probability of infection will be dependent on the capacity of the virus to survive in the environmental conditions available in the specific habitat. Therefore, a better understanding of the capacity of EBOV to survive under different biotic and abiotic conditions is important to explore further (e.g., [71, 73] ). These experimental approaches should consider the specific environmental conditions occurring in the tree canopy and cave roofs in terms of substrate, temperature, humidity and light properties.
One particular mechanism that has been put forward in the literature is the fruit-borne route concerning frugivorous bats in the tree canopy. The availability of fruits attracts fruit-eating animals, including birds, tree-dwelling mammals, and invertebrates. This behaviour can create a network of contacts between hosts, leading to several transmission pathways, and this interaction network can be denser during seasons with food resource limitations [23, 27] . Indirect contacts through faecal material, urine, or saliva left on fruits or branches could link the maintenance host with bats, in the same way that bats have been shown to be able to transmit other viruses (e.g., henipaviruses) through body fluids on fruit [33, 70, 83] . EBOV and filoviruses have been shown to persist for some time (3 to 7 days) in the environment, depending on the biotic and abiotic conditions [71] [72] [73] . In addition, EBV can be shed in some bat faeces [22] (but not all, [47] ), and have been cultured from human urine and saliva [51] , hence, could also be transmitted from faeces, urine, and saliva from other species. This transmission route is therefore possible, but restrained to the fauna feeding at the same height as bats (or, technically, above). The hypothesis of fruits soiled with infected body fluids falling on the ground and opening a transmission pathway towards other ground-level foraging hosts (e.g., duikers) does not expose bats to the alternative maintenance hosts (e.g., [83] ).
A relation between river systems and EBOV outbreaks has been suggested in Central Africa, with tributaries influencing the spatial distribution of cases [84] . If river systems can harbour specific biotic communities with potential alternative hosts, such as water-dependent vectors [46] , they can also represent, in remote forest ecosystems, the main transport pathways for people, providing a means for pathogens to spread through infected people or their hunted animals. Of course, in principle, while drinking, bats could get infected if the virus is present at the surface of the water. The capacity of EBOV to survive in the water has been the focus of a recent experimental study reporting an EBOV survival in water of 4 to 7 days between 21 and 27 • C [72] . Bats usually drink in open water, and not on the shores where viruses could be more concentrated by the presence of the maintenance host, for example. A dilution effect expected in open water, relative to some shallow water near the shores, would not favour such a transmission route a priori.
Tree and cave roosts could expose hanging and resting bats to direct contact with a potential maintenance host. However, as a first observation, the upside-down vertical position of bat roosting does not really favour disease transmission from an alternative host. For bat species roosting in tree-holes, the situation can be different as they can share temporally or directly their nest space with other animals [85] . Secondly, the density of bats roosting in caves prevents the presence of many other potential hosts in the cave roof (but, for example, snakes can predate on bats in caves). During their feeding behaviour, frugivorous bats could be in direct contact with other hosts attracted by the fruits. Their nocturnal habits will limit the diversity of host they can interact with. We are not aware of any extensive study on the network of potential contacts between bats and other animals during their roosting and feeding behaviour. The majority of studies investigated potential of infectious contact from bats to other organisms [53] . Novel technologies, such as camera traps equipped with nocturnal vision, could provide opportunities for more research on this topic.
As the ecology of most Africa bats is unknown, other opportunities exposing bat to potential maintenance hosts may be discovered in the future. For example, some bat species feed on fish [86] and, more recently, using stable isotopes of carbon and nitrogen as dietary tracers, it was demonstrated that a bat species, Nyctalus lasiopterus, was seasonally feeding on migrating Palearctic birds [87] , a feeding behaviour unknown until now. Failed predation on bats could also be a rare opportunity for infectious transmission [52] .
Considering the scenario B and C in Figure 1 , that bats are not the maintenance hosts of EBOV or that they are not the only host involved in the maintenance of EBOV, helps in focusing EBOV research protocols on a reduced range of potential transmission routes and potential alternative hosts interacting with bats in their specific and limited habitats. This means that if bats are not the maintenance hosts for EBOV, then there is only a limited number of candidate species to play the role of alternative maintenance hosts. This limited number of alternative maintenance hosts is defined by the ecology of bats that imposes on those alternative maintenance hosts only a few possible EBOV transmission pathways towards bats. From the biodiversity of African forest and the full web of interactions between species, a set of secondary hypotheses indicated in Table 1 can be tested through protocols presented to further investigate the role of different maintenance host candidates for EBOV. The observation of this limited number of hosts calls for testing them, even if only to exclude them from the list of hypotheses and strengthen the main hypothesis. As warned above, the EBOV multi-host maintenance system could include a complex network of interacting bat species ( Figure 1A2 ) and to proceed by elimination of alternative hypotheses may be a way to zoom-in on the maintenance community. The hypothesis of human playing a role in ebolavirus maintenance has not been addressed here, even if persistence of EBOV in previously infected humans has been recently proven [51] . This scenario would be more indicating of a change in the evolutionary trajectory of the pathogen (as moving from Step 4 to 5 in Figure 1 of Wolfe et al. [88] ) than of the natural maintenance of ebolaviruses that is considered here.
In order for these protocols to be efficient and well designed, insights from behavioural ecology, plant phenology, and molecular biology (amongst other disciplines) will be necessary. Integrated approaches to health have been proposed recently and, in EBOV ecology, they should promote the integration of ecological sciences into health sciences that are usually at the forefront of epidemiological investigations. For example, a lot of sampling of potential alternative hosts has been undertaken during ebolaviruses outbreaks (e.g., [12, [21] [22] [23] [24] [25] [26] ). These investigations concerned mainly the search for "what transmits ebolaviruses to people" as they were implemented during a human (or great ape) outbreak, and in the vicinity of outbreaks. This does not mean that they can automatically inform on "what maintains ebolaviruses". When looking for the maintenance host, investigations should also target the same and other alternative hosts during inter-outbreak periods with ecologically driven hypotheses. This is what is currently done for bats following the main maintenance hypothesis (e.g., [30] ), but not often for alternative hosts. Experimental trials should also concentrate on the environmental conditions occurring in bat-specific habitats, which can be very different from human outbreak conditions.
The transmission routes towards bats represent interhost contacts of unknown intensity and frequency, and it would be difficult to compare their relative importance. However, one can prioritize some transmission routes based on the current knowledge. The insect food-borne and vector-borne routes of transmission need, surely, to be further investigated, as they can expose bats to numerous other hosts. Previous works on insects have mainly concentrated on sampling insects in the human outbreaks' surroundings (e.g., [26] ). When searching for a maintenance host that can transmit EBOV to bats, protocols should concentrate on insects in interaction with known-exposed bat species. This would mean combining bat behavioural ecology and arthropod capture protocols to detect their potential carriage of EBOV, as well as protocols exploring bat feeding habits (e.g., molecular detection of prey DNA in bat's guano) [65, 67] . For example, insect captures should be targeted where insects can bite bats, in caves or at canopy level, and not at ground level where bats may not occur. Studying host interaction networks at fruit feeding sites is also an interesting avenue to explore direct, environmental, and fruit-borne routes of transmission. Behavioural ecology could inform and help targeting protocols. Chimpanzees and monkeys can feed at the same height as bats. Some rodent species feed on fruits, but the selection of the arboricolous species feeding at the same height as bats can reduce the list drastically. Camera trap protocols could inform host interaction networks placing bat species in symmetric or asymmetric interactions with other potential alternative hosts.
Under field reality, and especially in rainforests, this list of protocols will need a carefully designed programme to be successful, rooted in interdisciplinarity. As bats, and especially those species that have been exposed to ebolaviruses, are the entry point of most of these alternative hypotheses (i.e., alternative host need to be in contact with bats), the behavioural and community ecology of targeted bat species will need to be locally understood. Data recorders, such as vector or camera traps, will need to be deployed where bats are currently roosting or feeding. This can be a difficult task. Understanding which feeding resources attract bats at a specific season requires a good understanding of indigenous and domesticated tree phenology (e.g., [89] ). Prior to this work, a guano-based dietary analysis of the feeding behaviour of bats could help to map locally where and when bats will be present. Then, simultaneous protocols on bats and sympatric alternative hosts can be implemented, and a biological search for antibodies or antigens can be implemented. Combining protocols to test the main and alternative hypotheses could provide cost-effective and synergetic options.
To conclude, alternative hypotheses presented here should be explored alongside efforts to confirm bat species as maintenance hosts for EBOV. The ecology of those bat species already known to be exposed should be used to design protocols in order to target relevant alternative maintenance hosts. Given the number of species already involved/exposed to EBOV, the ecology of EBOV and its maintenance system can be expected to be complex, ecosystem dependent [46] , and dynamic, due to global changes [90] . The Ebola maintenance system, once isolated in the forests, is now interacting with humans and their modified environments and will adapt to it. Aiming at this moving target will require out-of-the-box thinking and interdisciplinary collaboration. | What do circles indicate in Figure 1? | false | 5,318 | {
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2,450 | Safe patient transport for COVID-19
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7079436/
SHA: 3ec1eb120d6bcca31ddc69832be05988c0952e60
Authors: Liew, Mei Fong; Siow, Wen Ting; Yau, Ying Wei; See, Kay Choong
Date: 2020-03-18
DOI: 10.1186/s13054-020-2828-4
License: cc-by
Abstract: nan
Text: Mei Fong Liew 1,2* , Wen Ting Siow 1,2 , Ying Wei Yau 3 and Kay Choong See 1
Dear Editor, Although COVID-19 has not been officially labelled as a pandemic yet, the global burden of disease is significant and continues to rise. The virus has a high humanto-human transmissibility via airborne, droplet and contact routes [1] . Patient numbers can surge, and hospitals should be ready not just with the infrastructure, but also staff to be familiar with workflows. Kain and Fowler [2] have eloquently detailed influenza pandemic preparations for hospitals and intensive care units, and we feel the principles described in the article are relevant to COVID-19. Staff must consider patient transfers in between wards, as COVID-19 patients are admitted in isolation facilities to contain infected cases and to avoid nosocomial spread [1] .
Infectious cases may be intentionally brought out of isolation rooms for various reasons. Intra-hospital transfer may be required from emergency departments to the wards, from the general floor to the intensive care unit and from the wards to radiology suites. Inter-hospital transfer may be required for extracorporeal membrane oxygenation (ECMO) if patients with COVID-19 develop severe acute respiratory distress syndrome within hospitals with only basic ventilation facilities. During episodes of patient transport outside of isolation, potential breaches of infection control can occur. At the same time, when COVID-19 patients turn ill during transport, their management is exceptionally challenging as accompanying staff would be wearing cumbersome personal protective equipment (PPE) [3] .
Mitigating the spread of COVID-19 is a national priority in Singapore [4] , and part of this effort involves planning and conducting safe patient transport for suspected or confirmed cases. HCWs who handle the transport of COVID-19 patients must consider the following principles (see Table 1 ): firstly, early recognition of the deteriorating patient; secondly, HCW safety; thirdly, bystander safety; fourthly, contingency plans for medical emergencies during transport; fifthly, post-transport decontamination. Specific action steps require designated zones for transport [5] , sufficient supplies of PPE, staff training and support personnel like security officers and cleaning crews. Powered air-purifying respirators add a layer of safety on top of N95 respirators [3] and should be used if possible for high-risk cases, such as those requiring ambulance transport to ECMO centres.
Given the continued global spread of COVID-19, we expect that more hospitals will need to deal with this disease. Haphazard transport of infected cases leading to nosocomial spread can stymie efforts to break the chains of transmission. We hope that our suggestions can aid others in ensuring safe patient transport for COVID-19 and reduce nosocomial spread.
Not applicable.
Availability of data and materials Not applicable.
Ethics approval and consent to participate Not applicable.
Not applicable.
The authors declare that they have no competing interests. prior to embarking on the same ambulance • Staff to doff PPE in the nearest clinical area, for example ambulance bay, upon arrival • Terminal cleaning of ambulance upon arrival when back at primary hospital BVM bag-valve-mask, CO2 carbon dioxide, ECMO extracorporeal membrane oxygenation, EMD emergency, GW general ward, HEPA high-efficiency particulate air, ICU intensive care unit, PAPR powered air-purifying respirator, PPE personal protective equipment | What are main steps for mitigating the COVID -19 transmission during transport of suspected and confirmed patients? | false | 641 | {
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2,459 | No credible evidence supporting claims of the laboratory engineering of SARS-CoV-2
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7054935/
SHA: 5a9154aee79901dd8fecd58b7bcd9b7351102d24
Authors: Liu, Shan-Lu; Saif, Linda J.; Weiss, Susan R.; Su, Lishan
Date: 2020-02-26
DOI: 10.1080/22221751.2020.1733440
License: cc-by
Abstract: nan
Text: The emergence and outbreak of a newly discovered acute respiratory disease in Wuhan, China, has affected greater than 40,000 people, and killed more than 1,000 as of Feb. 10, 2020. A new human coronavirus, SARS-CoV-2, was quickly identified, and the associated disease is now referred to as coronavirus disease discovered in 2019 (COVID-19) (https://globalbiodefense. com/novel-coronavirus-covid-19-portal/).
According to what has been reported [1] [2] [3] , COVID-2019 seems to have similar clinical manifestations to that of the severe acute respiratory syndrome (SARS) caused by SARS-CoV. The SARS-CoV-2 genome sequence also has ∼80% identity with SARS-CoV, but it is most similar to some bat beta-coronaviruses, with the highest being >96% identity [4, 5] .
Currently, there are speculations, rumours and conspiracy theories that SARS-CoV-2 is of laboratory origin. Some people have alleged that the human SARS-CoV-2 was leaked directly from a laboratory in Wuhan where a bat CoV (RaTG13) was recently reported, which shared ∼96% homology with the SARS-CoV-2 [4] . However, as we know, the human SARS-CoV and intermediate host palm civet SARSlike CoV shared 99.8% homology, with a total of 202 single-nucleotide (nt) variations (SNVs) identified across the genome [6] . Given that there are greater than 1,100 nt differences between the human SARS-CoV-2 and the bat RaTG13-CoV [4] , which are distributed throughout the genome in a naturally occurring pattern following the evolutionary characteristics typical of CoVs, it is highly unlikely that RaTG13 CoV is the immediate source of SARS-CoV-2. The absence of a logical targeted pattern in the new viral sequences and a close relative in a wildlife species (bats) are the most revealing signs that SARS-CoV-2 evolved by natural evolution. A search for an intermediate animal host between bats and humans is needed to identify animal CoVs more closely related to human SARS-CoV-2. There is speculation that pangolins might carry CoVs closely related to SARS-CoV-2, but the data to substantiate this is not yet published (https:// www.nature.com/articles/d41586-020-00364-2).
Another claim in Chinese social media points to a Nature Medicine paper published in 2015 [7] , which reports the construction of a chimeric CoV with a bat CoV S gene (SHC014) in the backbone of a SARS CoV that has adapted to infect mice (MA15) and is capable of infecting human cells [8] . However, this claim lacks any scientific basis and must be discounted because of significant divergence in the genetic sequence of this construct with the new SARS-CoV-2 (>5,000 nucleotides).
The mouse-adapted SARS virus (MA15) [9] was generated by serial passage of an infectious wildtype SARS CoV clone in the respiratory tract of BALB/c mice. After 15 passages in mice, the SARS-CoV gained elevated replication and lung pathogenesis in aged mice (hence M15), due to six coding genetic mutations associated with mouse adaptation. It is likely that MA15 is highly attenuated to replicate in human cells or patients due to the mouse adaptation.
It was proposed that the S gene from bat-derived CoV, unlike that from human patients-or civetsderived viruses, was unable to use human ACE2 as a receptor for entry into human cells [10, 11] . Civets were proposed to be an intermediate host of the bat-CoVs, capable of spreading SARS CoV to humans [6, 12] . However, in 2013 several novel bat coronaviruses were isolated from Chinese horseshoe bats and the bat SARS-like or SL-CoV-WIV1 was able to use ACE2 from humans, civets and Chinese horseshoe bats for entry [8] . Combined with evolutionary evidence that the bat ACE2 gene has been positively selected at the same contact sites as the human ACE2 gene for interacting with SARS CoV [13] , it was proposed that an intermediate host may not be necessary and that some bat SL-CoVs may be able to directly infect human hosts. To directly address this possibility, the exact S gene from bat coronavirus SL-SHC014 was synthesized and used to generate a chimeric virus in the mouse adapted MA15 SARS-CoV backbone. The resultant SL-SHC014-MA15 virus could indeed efficiently use human ACE2 and replicate in primary human airway cells to similar titres as epidemic strains of SARS-CoV. While SL-SHC014-MA15 can replicate efficiently in young and aged mouse lungs, infection was attenuated, and less virus antigen was present in the airway epithelium as compared to SARS MA15, which causes lethal outcomes in aged mice [7] .
Due to the elevated pathogenic activity of the SHC014-MA15 chimeric virus relative to MA15 chimeric virus with the original human SARS S gene in mice, such experiments with SL-SHC014-MA15 chimeric virus were later restricted as gain of function (GOF) studies under the US government-mandated pause policy (https://www.nih.gov/about-nih/who-weare/nih-director/statements/nih-lifts-funding-pausegain-function-research). The current COVID-2019 epidemic has restarted the debate over the risks of constructing such viruses that could have pandemic potential, irrespective of the finding that these bat CoVs already exist in nature. Regardless, upon careful phylogenetic analyses by multiple international groups [5, 14] , the SARS-CoV-2 is undoubtedly distinct from SL-SHC014-MA15, with >6,000 nucleotide differences across the whole genome. Therefore, once again there is no credible evidence to support the claim that the SARS-CoV-2 is derived from the chimeric SL-SHC014-MA15 virus.
There are also rumours that the SARS-CoV-2 was artificially, or intentionally, made by humans in the lab, and this is highlighted in one manuscript submitted to BioRxiv (a manuscript sharing site prior to any peer review), claiming that SARS-CoV-2 has HIV sequence in it and was thus likely generated in the laboratory. In a rebuttal paper led by an HIV-1 virologist Dr. Feng Gao, they used careful bioinformatics analyses to demonstrate that the original claim of multiple HIV insertions into the SARS-CoV-2 is not HIV-1 specific but random [15] . Because of the many concerns raised by the international community, the authors who made the initial claim have already withdrawn this report.
Evolution is stepwise and accrues mutations gradually over time, whereas synthetic constructs would typically use a known backbone and introduce logical or targeted changes instead of the randomly occurring mutations that are present in naturally isolated viruses such as bat CoV RaTG13. In our view, there is currently no credible evidence to support the claim that SARS-CoV-2 originated from a laboratory-engineered CoV. It is more likely that SARS-CoV-2 is a recombinant CoV generated in nature between a bat CoV and another coronavirus in an intermediate animal host. More studies are needed to explore this possibility and resolve the natural origin of SARS-CoV-2. We should emphasize that, although SARS-CoV-2 shows no evidence of laboratory origin, viruses with such great public health threats must be handled properly in the laboratory and also properly regulated by the scientific community and governments.
No potential conflict of interest was reported by the author(s).
Susan R. Weiss http://orcid.org/0000-0002-8155-4528 | What is the conclusion of this report? | false | 3,616 | {
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"More studies are needed to explore this possibility and resolve the natural origin of SARS-CoV-2. We should emphasize that, although SARS-CoV-2 shows no evidence of laboratory origin, viruses with such great public health threats must be handled properly in the laboratory and also properly regulated by the scientific community and governments."
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1,741 | MERS coronavirus: diagnostics, epidemiology and transmission
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4687373/
SHA: f6fcf1a99cbd073c5821d1c4ffa3f2c6daf8ae29
Authors: Mackay, Ian M.; Arden, Katherine E.
Date: 2015-12-22
DOI: 10.1186/s12985-015-0439-5
License: cc-by
Abstract: The first known cases of Middle East respiratory syndrome (MERS), associated with infection by a novel coronavirus (CoV), occurred in 2012 in Jordan but were reported retrospectively. The case first to be publicly reported was from Jeddah, in the Kingdom of Saudi Arabia (KSA). Since then, MERS-CoV sequences have been found in a bat and in many dromedary camels (DC). MERS-CoV is enzootic in DC across the Arabian Peninsula and in parts of Africa, causing mild upper respiratory tract illness in its camel reservoir and sporadic, but relatively rare human infections. Precisely how virus transmits to humans remains unknown but close and lengthy exposure appears to be a requirement. The KSA is the focal point of MERS, with the majority of human cases. In humans, MERS is mostly known as a lower respiratory tract (LRT) disease involving fever, cough, breathing difficulties and pneumonia that may progress to acute respiratory distress syndrome, multiorgan failure and death in 20 % to 40 % of those infected. However, MERS-CoV has also been detected in mild and influenza-like illnesses and in those with no signs or symptoms. Older males most obviously suffer severe disease and MERS patients often have comorbidities. Compared to severe acute respiratory syndrome (SARS), another sometimes- fatal zoonotic coronavirus disease that has since disappeared, MERS progresses more rapidly to respiratory failure and acute kidney injury (it also has an affinity for growth in kidney cells under laboratory conditions), is more frequently reported in patients with underlying disease and is more often fatal. Most human cases of MERS have been linked to lapses in infection prevention and control (IPC) in healthcare settings, with approximately 20 % of all virus detections reported among healthcare workers (HCWs) and higher exposures in those with occupations that bring them into close contact with camels. Sero-surveys have found widespread evidence of past infection in adult camels and limited past exposure among humans. Sensitive, validated reverse transcriptase real-time polymerase chain reaction (RT-rtPCR)-based diagnostics have been available almost from the start of the emergence of MERS. While the basic virology of MERS-CoV has advanced over the past three years, understanding of the interplay between camel, environment, and human remains limited. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12985-015-0439-5) contains supplementary material, which is available to authorized users.
Text: An email from Dr Ali Mohamed Zaki, an Egyptian virologist working at the Dr Soliman Fakeeh Hospital in Jeddah in the Kingdom of Saudi Arabia (KSA) announced the first culture of a new coronavirus to the world. The email was published on the website of the professional emerging diseases (ProMED) network on 20 th September 2012 [1] (Fig. 1) and described the first reported case, a 60 year old man from Bisha in the KSA. This information led to the rapid discovery of a second case of the virus, this time in an ill patient in the United Kingdom, who had been transferred from Qatar for care [2] . The new virus was initially called novel coronavirus (nCoV) and subsequentlty entitled the Middle East respiratoy syndrome coronavirus (MERS-CoV). As of 2 nd of September 2015, there have been 1,493 detections of viral RNA or virus-specific antibodies across 26 countries (Additional file 1: Figure S1 ) confirmed by the World Health Organization (WHO), with over a third of the positive people dying (at least 527, 35 %) [3] .
Since that first report, a slow discovery process over the following two to three years revealed a virus that had infected over 90 % of adult dromedary camels (DC; Camelus dromedarius) in the KSA [4] , also DCs across the Arabian Peninsula and parts of Africa that are a source of DC imports for the KSA [5] . To date, MERS-CoV has not been detected in DCs tested in zoos or herds from other parts of the world [6] [7] [8] [9] . Occasionally, virus is transmitted from infected DCs to exposed humans. Subsequent transmission to other humans requires relatively close and prolonged exposure [10] .
The first viral isolate was patented and concerns were raised that this would restrict access to both the virus and to viral diagnostics [11, 12] . However, sensitive, validated reverse transcriptase real-time polymerase chain reaction (RT-rtPCR)-based diagnostics were quickly described and virus was made freely available subject to routine biosafety considerations [13] . Subsequent epidemiology and research has identified the cell receptor as exopeptidase dipeptidyl peptidase 4 (DPP4; also called CD26); that MERS-CoV has a broad tropism, replicating better in some cells lines and eliciting a more proinflammatory response than SARS-CoV; is widespread in DCs; has the potential to infect other animals and that MERS kills its human host more often than SARS did (20-40 % versus 9 % for SARS [14] ) [15] [16] [17] [18] [19] .
In humans, overt disease was given the name Middle East respiratory syndrome, with the acronym MERS. From intermittent animal-to-human spill-over events, the MERS-CoV spreads sporadically among people, causing more severe disease among older adults, especially males, with pre-existing diseases. The spread of MERS-CoV among humans has often been associated with outbreaks in hospitals, with around 20 % of all cases to date involving healthcare workers (HCWs).
Although DCs appear to suffer the equivalent of a 'common cold' from MERS-CoV infection, in humans, the virus can be a more serious and opportunistic pathogen associated with the death of up to 40 % of reported cases. It has yet to be established whether infections thought to have been acquired from an animal source produce a more severe outcome than those spread between humans [20] . Studies have established that the mean incubation period for MERS is five to six days, ranging from two to 16 days, with 13 to 14 days between when illness begins in one person and subsequently spreads to another [21] [22] [23] [24] . Among those with progressive illness, the median time to death is 11 to 13 days, ranging from five to 27 days [23, 24] . Fever and gastrointestinal symptoms may form a prodrome, after which symptoms decline, only to be followed by a more severe systemic and respiratory syndrome [25, 26] .
The first WHO case definition [27] defined probable cases of MERS based on the presence of febrile illness, cough and requirement for hospitalization with suspicion of lower respiratory tract (LRT) involvement. It also included roles for contact with a probable or confirmed case or for travel or residence within the Arabian Peninsula. If strictly adhered to, only the severe syndrome would be subject to laboratory testing, which was the paradigm early on [21] . From July 2013, the revised WHO case definition included the importance of seeking out and understanding the role of asymptomatic cases and from June 2014, the WHO definition more clearly stated that a confirmed case included any person whose sample was RT-PCR positive for MERS-CoV, or who produced a seroconversion, irrespective of clinical signs and symptoms. [28] [29] [30] Apart from the WHO and the KSA Ministry of Health reports, asymptomatic or subclinical cases of MERS-CoV infection were documented in the scientific literature although not always as often as occurred early on [31, 32] . The KSA definition of a case became more strict on 13 th May 2014, relying on the presence of both clinical features and laboratory confirmation [33] . Testing of asymptomatic people was recommended against from December 2014 [34] , reinforced by a case definition released by the KSA Ministry of Health in June 2015 [35] . The KSA has been the source of 79 % of human cases. Severe MERS is notable for its impact among older men with comorbid diseases including diabetes mellitus, cirrhosis and various lung, renal and cardiac conditions [36] [37] [38] . Interestingly in June 2015, an outbreak in South Korea followed a similar distribution [39, 40] . Among laboratory confirmed cases, fever, cough and upper respiratory tract (URT) signs and symptoms usually occur first, followed within a week by progressive LRT distress and lymphopaenia [37] . Patients often present to a hospital with pneumonia, or worse, and secondary bacterial infections have been reported [37, 41] . Disease can progress to acute respiratory distress syndrome and multiorgan system failure [37] . MERS has reportedly killed approximately 35 % of all reported cases, 42 % of cases in the KSA, yet only 19 % of cases in South Korea, where mortality ranged from 7 % among younger age groups to 40 % among those aged 60 years and above [42] ; all may be inflated values with asymptomatic or mild infections sometimes not sought or not reported [34] . General supportive care is key to managing severe cases [43] . Children under the age of 14 years are rarely reported to be positive for MERS-CoV, comprising only 1.1 % (n = 16) of total reported cases. Between 1 st September 2012 and 2 nd December 2013, a study described the then tally of paediatric cases in the KSA, which stood at 11 (two to 16 years of age; median 13 years); nine were asymptomatic (72 %) and one infant died [44] . In Amman, Jordan, 1,005 samples from hospitalized children under the age of two years with fever and/or respiratory signs and symptoms were tested but none were positive for MERS-CoV RNA, despite being collected at a similar time to the first known outbreak of MERS-CoV in the neighbouring town of Al-Zarqa [45] . A second trimester stillbirth occurred in a pregnant woman during an acute respiratory illness and while not RT-rtPCR positive, the mother did subsequently develop antibodies to MERS-CoV, suggestive of recent infection [46] . Her exposure history to a MERS-CoV RT-rtPCR positive relative and an antibody-reactive husband, her incubation period and her symptom history met the WHO criteria for being a probable MERS-CoV case [46] .
Diagnostic methods were published within days of the ProMED email announcing the first MERS case [47] , including several now gold standard in-house RT-rtPCR assays (Fig. 2 ) as well as virus culture in Vero and LLC-MK2 cells [18, 47, 48] . A colorectal adenocarcinoma (Caco-2) epithelial cell line has since been recommended for isolation of infections MERS-CoV [49] . We previously [18] .). Open reading frames are indicated as yellow rectangles bracketed by terminal untranslated regions (UTR; grey rectangles). FS-frame-shift. Predicted regions encompassing recombination break-points are indicated by orange pills. Created using Geneious v8.1 [211] and annotated using Adobe Illustrator. Beneath this is a schematic depicting the location of RT-PCR primers (blue arrows indicate direction) and oligoprobes (green rectangles) used in the earliest RT-rtPCR screening assays and conventional, semi-nested (three primers) RT-PCR confirmatory sequencing assays [47, 48] . Publication order is noted by first [27 th September 2012; red] and second [6 th December 2012; orange] coloured rectangles; both from Corman et al. [47, 48] Those assays recommended by the WHO are highlighted underneath by yellow dots [53] . The NSeq reverse primer has consistently contained one sequence mismatch with some MERS-CoV variants. An altered version of that from Mackay IM, Arden KE. Middle East respiratory syndrome: An emerging coronavirus infection tracked by the crowd. Virus Res 2015 Vol 202:60-88 with permission from Elsevier [5] reviewed the broad tropism of MERS-CoV [5] . However, as is well described, cell culture is a slow, specialised and insensitive method [50] while PCR-based techniques are the preferred method for MERS-CoV detection.
The first open reading frames (ORF 1a and 1b; Fig. 2 ) have become a key diagnostic and taxonomic target for CoV species identification. With less than 80 % identity between the amino acid sequence of MERS ORF 1ab and betacoronavirus relatives, Tylonycteris bat HKU4 and Pipistrellus bat HKU5, it can be concluded that it is a novel and distinct virus. MERS-CoV is predicted to encode ten open reading frames with 5' and 3' untranslated regions [51] . The structural proteins include the spike (S), envelope (E), membrane (M) and nucleocapsid (N) [52] . The products of ORF1a and ORF1b are predicted to encode nonstructural proteins.
The majority of specimen testing to date has employed validated RT-rtPCR assays shown to be sensitive and specific [47, 48, 53] . The RealStar® kit uses these WHOrecommended assays [54] . The target sequences of these screening assays have not changed among genomes examined until at least mid-2015 (IMM observation). Other RT-rtPCR assays have been developed and validated for use as laboratory-based diagnostic tools [55] [56] [57] . Additionally, loop-mediated [58, 59] or recombinase polymerase [60] isothermal assays have been designed for field deployment.
The detection of MERS-CoV antigen has not been common to date but the combination of short turnaround time from test to result, high throughput and identification of viral proteins makes this an attractive option. Detection of viral proteins rather than viral RNA indicates the likely presence of infectious virus. The first rapid immunochromatographic tool described could detect recombinant MERS-CoV nucleocapsid protein from DC nasal swabs with 94 % sensitivity and 100 % specificity compared to RT-rtPCR [61] . A different approach used a monoclonal antibody-based capture ELISA targeting the MERS-CoV nucleocapsid protein with a sensitivity of 10 3 TCID 50 and 100 % specificity [62] .
Demonstration of a seroconversion to a MERS-CoV infection meets the current WHO definition of a case so optimized and thoroughly validated sero-assays employed alongside good clinical histories are useful to both identify prior MERS-CoV infection and help support transmission studies. Because serology testing is, by its nature, retrospective, it is usual to detect a viral footprint, in the form of antibodies, in the absence of any signs or symptoms of disease and often in the absence of any viral RNA [63] .
Strategic, widespread sero-surveys of humans using samples collected after 2012 are infrequent. Much of the Arabian Peninsula and all of the Horn of Africa lack baseline data describing the proportion of the community who may have been infected by a MERS-CoV. However, sero-surveys have had widespread use in elucidating the role of DCs as a transmission source for MERS-CoV. Because of the identity shared between DC and human MERS-CoV (see Molecular epidemiology: using genomes to understand outbreaks), serological assays for DC sero-surveys should be transferrable to human screening with minimal re-configuration. Also, no diagnostically relevant variation in neutralization activity have been found from among a range of circulating tested MERS-CoV isolates and sera, so whole virus or specific protein-based sero-assays should perform equivalently in detecting serological responses to the single MERS-CoV serotype [49] . The development of robust serological assays requires reliable panels of wellcharacterized animal or human sera, including those positive for antibodies specific to MERS-CoV, as well as to likely sources of cross-reaction [64] . Obtaining these materials was problematic and slowed the development and commercialization of antibody detection assays for human testing [64] . A number of commercial ELISA kits, immunofluorescent assays (IFA) kits, recombinant proteins and monoclonal antibodies have been released [31, [65] [66] [67] [68] . Initially, conventional IFAs were used for human sero-surveys. These relied on MERS-CoV-infected cell culture as an antigen source, detecting the presence of human anti-MERS-CoV IgG, IgM or neutralizing antibodies in human samples [18, 48, 69] . No sign of MERS-CoV antibodies was found among 2,400 sera from patients visiting Hospital in Jeddah, from 2010 through 2012, prior to the description of MERS-CoV [18] . Nor did IFA methods detect any sign of prior MERS-CoV infection among a small sample of 130 healthy blood donors from another Hospital in Jeddah (collected between Jan and Dec 2012) [70] . Of 226 slaughterhouse workers, only eight (3.5 %) were positive by IFA, and those sera could not be confirmed by virus neutralization (NT) test. The study indicated that HCoV-HKU1 was a likely source of crossreactive antigen in the whole virus IFA [70] . Whole virus MERS-CoV IFA also suffered from some cross-reactivity with convalescent SARS patient sera and this could not be resolved by an NT test which was also cross-reactive [71] . IFA using recombinant proteins instead of whole-virus IFA, has been shown to be a more specific tool [31] . Since asymptomatic zoonoses have been posited [72] , an absence of antibodies to MERS-CoV among some humans who have regular and close contact with camels may reflect the rarity of actively infected animals at butcheries, a limited transmission risk associated with slaughtering DCs [70] , a pre-existing cross-protective immune status or some other factor(s) resulting in a low risk of disease and concurrent seroconversion developing after exposure in this group. IFA using recombinant proteins instead.
Some sero-assays have bypassed the risks of working with infectious virus by creating transfected cells expressing recombinant portions of the MERS-CoV nucleocapsid and spike proteins [48, 73] , or using a recombinant lentivirus expressing MERS-CoV spike protein and luciferase [74, 75] . A pseudo particle neutralization (ppNT) assay has seen widespread used in animal studies and was at least as sensitive as the traditional microneutralization (MNT) test. [10, 74, [76] [77] [78] ] Studies using small sample numbers and ppNT found no evidence of MERS-CoV neutralizing antibody in sera from 158 children with LRT infections between May 2010 and May 2011, 110 sera from 19 to 52 year old male blood donors and 300 selfidentified animal workers from the Jazan Region of the KSA during 2012 [79, 80] . Similarly, a study of four herdsmen in contact with an infected DC herd in Al-Ahsa, eight people who had intermittent contact with the herd, 30 veterinary surgeons and support staff who were not exposed to the herd, three unprotected abattoir workers in Al-Ahsa and 146 controls who were not exposed to DCs in any professional role, found none with serological evidence of past MERS-CoV infection using the ppNT assay [10] . A delay in the neutralizing antibody response to MERS-CoV infection was associated with increased disease severity in South Korea cases with most responses detectable by week three of illness while others, even though disease was severe, did not respond for four or more weeks [81] . The implications for our ability to detect any response in mild or asymptomatic cases was not explored but may be a signifcant factor in understanding exposure in the wider community.
A Jordanian outbreak of acute LRT disease in a hospital in 2012 was retrospectively found to be associated with MERS-CoV infection, initially using RT-rtPCR, but subsequently, and on a larger scale, through positivity by ELISA and IFA or MNT test. [46, 82, 83] This outbreak predated the first case of MERS in the KSA. The ELISA used a recombinant nucleocapsid protein from the group 2 betacoronavirus bat-CoV HKU5 to identify antibodies against the equivalent crossreactive MERS-CoV protein [71] . It was validated using 545 sera collected from people with prior HCoV-OC43, HCoV-229E, SARS-CoV, HCoV-NL63, HRV, HMPV or influenza A(H1N1) infections but was reportedly less specific than the recombinant IFA discussed above. It was still considered an applicable tool for screening large sample numbers [82] . A protein microarray expressing the S1 protein subunit has also been validated and widely used for DC testing [5, 84] . Detection of MERS-CoV infection using ELISA or S1 subunit protein microarray [84] is usually followed by confirmatory IFA and/ or a plaque-reduction neutralization (PRNT) [69, 70, 85] or MNT test. [74, 85, 86] This confirmatory process aims toensure the antibodies detected are able to specifically neutralize the intended virus and are not more broadly reactive to other coronaviruses found in DCs (bovine CoV, BCoV) or humans (HCoV-OC43, HCoV-229E, HCoV-NL63, HCoV-HKU1, SARS-CoV). In the largest study of human sera, a tiered diagnostic process assigned both recombinant IFA and recombinant ELISA positive sera to 'stage 1' seropositivity. A stage 2 seropositive result additionally required a suitably titred PRNT result [87] . The study found 15 sera collected in 2012 to 2013 from 10,009 (0.2 %) people in 13 KSA provinces contained MERS-CoV antibodies, but significantly higher proportions in occurred in camel shepherds (two of 87; 2.3 %) and slaughterhouse workers (five of 140; 3.6 %) [87] . Contemporary surveys are needed.
MERS-CoV does not appear to be easily transmitted from DCs to humans, or perhaps it is [72] , but generally does not trigger a detectable immune response if only mild disease or asymptomatic infection results. Serology assays are in need of further validation in this area so care is required when moving newly developed diagnostic serology algorithms from a research setting to one that informs public health decisions. This was reinforced when a false positive US case, purported to have been infected after a handshake and two face-to-face meetings, did not withstand further confirmatory analysis using a more specific, NT assay and was subsequently retracted [88, 89] .
The WHO recommends sampling from the LRT for MERS-CoV RT-rtPCR testing, especially when sample collection is delayed by a week or more after onset of symptoms. [53] LRT samples are also best for attempting isolation of infectious virus, although the success of culture is reduced when disease persists [49] . Recommended sample types include bronchoalveolar lavage (BAL), tracheal/tracheobronchial aspirate, pleural fluid and sputum [53, 90] . Fresh samples yield better diagnostic results than refrigerated material [69] and if delays in testing of ≥72 h are likely, samples (except for blood) should be frozen at −70°C [90] . If available, lung biopsy or autopsy tissues can also be tested [53] . The URT is a less invasive and more convenient sampling site however, and an oropharyngeal and throat swab or a nasopharyngeal aspirate/wash are recommended when URT sampling is to be conducted [90] . Paired sera, collected two to three weeks apart are preferable for serological testing while a single sample is suggested to be sufficient if collected two weeks after onset of disease or a single serum collected during the first 10-12 days if conducting RT-rtPCR [53, 90] . Human urine and stool have been found to contain MERS-CoV RNA 12 to 26 days after symptom onset [25, 69, 91] and are listed as samples that should be considered [53, 90] . In two cases that arrived in the Netherlands, urine was RT-rtPCR negative but faeces was weakly positive and sera were RT-rtPCR positive for five days or more [25] . The finding of MERS-CoV viral RNA in serum provides an avenue for retrospective PCR-based studies if respiratory samples are unavailable [83] . RNAaemia may also correlate with disease severity; signs of virus were cleared from the serum of a recovered patient, yet lingered until the death of another [92] .
Clinically suspected MERS cases may return negative results by RT-rtPCR. Data have shown one or more negative URT samples may be contradicted by further URT sampling or the use of LRT samples, which is preferred [2, 43, 93] . Higher viral loads occur in the LRT compared to the URT. [22, 69, 88, 94] This fits with the observation that the majority of disease symptoms are reported to manifest as systemic and LRT disease [21] . However, on occasion, even LRT specimens from MERS cases may initially be negative, only to later become positive by RT-PCR [95] . This may be due to poor sampling when a cough is absent or non-productive or because the viral load is low [95] . Despite this both the largest human MERS-CoV studies [32, [96] [97] [98] and smaller ones [22, 25, 99] , use samples from the URT. It is then noteworthy that one study reported an association between higher loads in the URT and worse clinical outcome including intensive care and death [94] . At writing, no human data exist to define whether the virus replicates solely or preferentially in the LRT or URT, or replicates in other human tissues in vivo although MERS-CoV RNA has been detected from both the URT and LRT in a macaque monkey model [100] .The distribution of DPP4 in the human upper airways is also not well described.
Individual human case studies report long periods of viral shedding, sometimes intermittently and not necessarily linked to the presence of disease symptoms. [25, 69, 99, 101] In one instance, a HCW shed viral RNA for 42 days in the absence of disease [99] . It is an area of high priority to better understand whether such cases are able to infect others. Over three quarters of MERS cases shed viral RNA in their LRT specimens (tracheal aspirates and sputum) for at least 30 days, while only 30 % of contacts were still shedding RNA in their URT specimens [91, 102] .
In the only study to examine the effect of sample type on molecular analysis, 64 nasopharyngeal aspirates (NPA; an URT sample), 30 tracheal aspirates, 13 sputa and three BAL were examined. The tracheal aspirates and BAL returned the highest viral load values followed by NPA and sputum. Unsurprisingly, higher viral loads generally paralleled whole genome sequencing and culture success and, in NPA testing, were significantly correlated with severe disease and death [49, 94, 103] . This study demonstrated the importance of LRT sampling for whole genome sequencing.
When tested, samples positive for MERS-CoV are often negative for other pathogens [2, 25, 93, 104] . However, many studies make no mention of additional testing for endemic human respiratory viruses [21, 23, 73, 105] . When viruses are sought, they have included human herpesvirus (HHV), rhinoviruses (HRV), enteroviruses (EV), respiratory syncytial virus (RSV), parainfluenzavirus types 1, 2 and 3 (PIVs),influenzaviruses (IFVs), endemic HCoVs, adenoviruses (AdVs) metapneumovirus (MPV) and influenza A\H1N1 virus; co-detections with MERS-CoV have been found on occasion [2, 22, 37, 69, 97] . Bacterial testing is sometimes included (for example, for Legionella and Pneumococcus) but the impact of bacterial co-presence is also unclear [22, [104] [105] [106] . Further testing of the LRT sample from the first MERS case used IFA to screen for some viruses (negative for IFV, PIVs, RSV and AdVs) and RT-PCR for others (negative for AdV, EVs, MPV and HHVs) [18] . RT-PCR also detected MERS-CoV. The WHO strongly recommends testing for other respiratory pathogens [53] but with this recommendation often discounted, there are limited data to address the occurrence and impact of co-infections or alternative viral diagnoses among both MERS cases and their contacts. Little is known of other causes of MERS-like pneumonia in the KSA or of the general burden of disease due to the known classical respiratory viruses.
Testing of adult pilgrims performing the Hajj in 2012 to 2014 has not detected any MERS-CoV. In 2012, nasal swabs from 154 pilgrims collected prior to leaving for or departing from the KSA were tested [47] . In 2013, testing was significantly scaled up with 5,235 nasopharyngeal swabs from 3,210 incoming pilgrims and 2,025 swabs from outgoing pilgrims tested [98] . It should be noted that most pilgrims arrived from MERS-free countries. A further 114 swabs were taken from pilgrims with influenza-like illness [96, 107] . In earlier Hajj gatherings, it was found that influenza viruses circulated widely, whilst other viruses, often rhinoviruses, circulated more selectively, interpreted as indicating their importation along with foreign pilgrims. [107] [108] [109] Over time, increased influenza vaccination has been credited for a fall in the prevalence of influenza like illnesses among Hajj pilgrims. [110] A LRT sample is often not collected for these studies [98, 107, 109] , so false negative findings are a possibility although little is known about the initial site of MERS-CoV infection and replication; it may have been assumed it was the LRT because disease was first noticed there but the URT may be the site of the earliest replication.
In Jeddah between March and July 2014 (hereafter called the Jeddah-2014 outbreak; Fig. 3 ), there was a rapid increase in MERS cases, accompanied by intense screening; approximately 5,000 samples from in and around the region were tested in a month yielding around 140 MERS-CoV detections (~3 % prevalence) [111] . Among 5,065 individuals sampled and tested across the KSA between October 2012 and September 2013,108 (2.1 %) detections were made in a hospital-centric population which included hospitalized cases (n = 2,908; 57.4 %), their families (n = 462; 9.1 %) and associated HCWs (n = 1,695; 33.5 %) [32] . Among the detections, 19 (17.8 %) were HCWs and 10 (9.3 %) were family contacts [32] .
The 2-3 % prevalence of active MERS-CoV infections is not dissimilar to the hospital-based prevalence of other human CoVs. [112] However, the proportion of deaths among those infected with MERS-CoV is much higher than that known for the HCoVs NL63, HKU1, 229E or OC43 in other countries, and even above that for SARS-CoV; it is not a virus that could reasonably be described as a "storm in a teacup". It is the low transmission rate that has prevented worldwide spread, despite many "opportunities".
Very early in the MERS outbreak, some animals were highly regarded as either the reservoir or intermediate host(s) of MERS-CoV with three of the first five cases having contact with DCs [73, 113, 114] . Today, animal MERS-CoV infections must be reported to the world organization for animal health as an emerging disease [115] . A summary of the first MERS cases reported by the WHO defined animal contact with humans as being direct and within 10 days prior to symptom onset [20] . This definition made no specific allowance for acquisition from DCs through a droplet-based route, which is very likely route for acquisition of a virus that initially and predominantly causes respiratory disease [23] . Camels are known to produce high levels of MERS-CoV RNA in their URT and lungs [116] . Providing support for a droplet transmission route and perhaps indicating the presence of RNA in smaller, drier droplet nuclei, MERS-CoV RNA was identified in a high volume air sample collected from a barn housing an infected DC [117] . The precise source from which humans acquire MERS-CoV remains poorly studied but it seems likely that animal and human behavioural factors may play roles (Fig. 3) [118] . These factors may prove important for human cases who do not describe any DC contact [119] nor any contact with a confirmed case. Whether the WHO definition of animal contact is sufficient to identify exposure to this respiratory virus remains unclear. Wording focuses on consumption of DC products but does not specifically ascribe risk to a droplet route for acquisition of MERS-CoV from DC [120] . Some MERS patients are listed in WHO disease notices as being in proximity to DCs or farms, but the individuals have not described coming into contact with the animals. No alternative path for acquiring infection is reported in many of these instances. What constitutes a definition of "contact" during these interviews has been defined for one study [72] . Despite this lack of clarity, the WHO consider that evidence linking MERS-CoV transmission between DCs to humans is irrefutable (Fig. 4) [120] .
The possibility that bats were an animal host of MERS-CoV was initially widely discussed because of the existing diversity of coronaviruses known to reside among them [121] [122] [123] [124] . Conclusive evidence supporting bats as a source for human infections by MERS-CoV has yet to be found, but bats do appear to host ancestral representatives [53, 125] . However, these are not variants of the same virus nor always within the same phylogenetic lineage as MERS-CoV; they are each a genetically distinct virus. Bat-to-human infection by MERS-CoV is a purely speculative event. The only piece of MERS-CoV-specific evidence pointing to bats originates from amplification of a 190 nt fragment of the RNAdependent RNA polymerase gene of the MERS-CoV genome, identified in a faecal pellet from an insectivorous Emballonuridae bat, Taphozous perforatus found in Bisha, the KSA [121] . While very short, the sequence of the fragment defined it as a diagnostic discovery. Subsequently a link to DCs was reported [85] and that link has matured into a verified association [38, 126] (Fig. 4) .
(See figure on previous page.) Fig. 3 Monthly detections of MERS-CoV (blue bars) and of cases who died (red bars) with some dates of interest marked for 2012 to 4 th September 2015. An approximation of when DC calving season [128] and when recently born DCs are weaned is indicated. Spring (green) and summer (orange) in the Arabian Peninsula are also shaded. Note the left-hand y-axis scale for 2014 and 2015 which is greater than for 2012/13. Sources of these public data include the WHO, Ministries of Health and FluTrackers [207] [208] [209] . Earlier and subsequent versions of this chart are maintained on a personal blog [210] . Modified and reprinted from Mackay IM, Arden KE. Middle East respiratory syndrome: An emerging coronavirus infection tracked by the crowd. Virus Res 2015 Vol 202:60-88 with permission from Elsevier [5] DCs, which make up 95 % of all camels, have a central presence in the Arabian Peninsula where human-DC contact ranges from little to close [119] . Contact may be commonplace and could occur in variety of ways (Fig. 4a) . There are several large well-attended festivals, races, sales and parades which feature DCs and DCs are also kept and bred close to populated areas in the KSA [127, 128] . DC milk and meat are widely consumed and the older DC is an animal of ritual significance after the Hajj pilgrimage [129] . However, MERS-CoV infection frequency is reportedly much lower than is the widespread and frequent habit of eating, drinking and preparing DC products. Daily ingestion of fresh unpasteurized DC milk is common among the desert Bedouin and many others in the KSA. DC urine is also consumed or used for supposed health benefits. Despite camel butchery being a local occupation, neither butchers nor other at-risk groups are identifiable among MERS cases; this may simply be a reporting issue rather than an unexplainable absence of MERS. A small case-control study published in 2015 identified direct DC contact, and not ingestion of products, to be associated with onset of MERS [38] .
The first sero-survey of livestock living in the Middle East region was conducted during 2012-2013 [85] . DCs were sampled from a mostly Canary Island-born herd and from Omani DCs (originally imported from the Horn of Africa) [85] . A neutralising antibody assay found only 10 % of strongly seropositive Canary Island [5] . b Camel-to-human infections appear to be infrequent, while human-to-human spread of infection is regularly facilitated by poor IPC in healthcare settings where transmission is amplified, accounting for the bulk of cases. There are human MERS cases that do not fall into either category of source and it is unclear if these acquired infection through some entirely separate route, or from cases that escaped diagnosis. c Hypothetical ways in which subclinical (when infection may not meet a previously defined clinical threshold of signs and/or symptoms) or asymptomatic (no obvious signs or measured, noticed or recalled symptoms of illness) MERS-CoV infection may be implicated in transmission DC sera could neutralise MERS-CoV while all Omani DC sera had high levels of specific MERS-CoV neutralizing antibody [85] . This indicated that DCs had in the past been infected by MERS-CoV, or a very similar virus.
Since this study, a host of peer-reviewed reports have looked at both DCs and other animals, and the possibility that they may host MERS-CoV infection. Seropositive DCs have been found throughout the Arabian Peninsula including Oman, the KSA, Qatar, Jordan, the United Arab Emirates (UAE), Kuwait as well as Sudan, Somalia, Egypt, Tunisia, Nigeria, Kenya and Ethiopia in Africa and the Canary Islands [85, [130] [131] [132] [133] [134] . Other animals tested include sheep, cows, pigs, horses, donkeys, mules, birds, water buffalo, goats, Bactrian camels, llamas and guanaco (south American camelids) but none had detectable neutralising antibody against MERS-CoV [4, 74, 78, 85, 86, 135, 136] . No virology or serology studies of human samples from areas in Africa where there are camels with a history of MERS-CoV have been reported to date. However,an absence of unexplained pneumonia that may be attributable to MERS-CoV infection may not signal the absence of virus among humans in each country but simply reflect a lack of expensive epidemiology studies conducted by resource-poor countries. It is thus unclear whether MERS-CoV, or an antigenically related CoV, is an unrecognized pathogen in these regions, perhaps circulating for even longer than it has been known in the Arabian Peninsula [133] .
MERS-CoV RNA has also been detected in DC samples, and recovery of infectious virus has also been achieved from DC samples [4, 77, 117, 132, [137] [138] [139] [140] [141] . From some of these, full or majority length genomes of MERS-CoV have been sequenced [77, 137, 138] . DC versions of MERS-CoV were found to be as similar to each other, as were variants detected from different humans over time and across distance.
Antibody screening assays have also detected crossreactive antibodies in sera. These were identified as such by screening sera against similar viruses, for example BCoV or HCoV-OC43 (as an antigenic facsimile for BCoV). It is possible that other MERS-CoV-like viruses also reside within DCs, but this does not detract from the definitive finding of MERS-CoV genetic sequences in both DCs and humans [117, 142, 143] .
Screening studies have shown that juvenile DCs are more often positive for virus or viral RNA while older DCs are more likely to be seropositive and RNA or virus negative [76, 77, 144] . In adult DCs, MERS-CoV RNA has been detected among animals with pre-existing antibody, suggesting re-infection is possible [77, 144] . Viral loads among positive DCs can be very high [4, 76, 77, 139, 144] and DCs have been found positive both when ill with URT respiratory signs [77, 117, 142, 145] or when apparently healthy [137] . These findings indicate DCs host natural MERS-CoV infections. Furthermore, stored DC sera have revealed signs of MERS-CoV in DCs which date back over three decades (the earliest collected in 1983) [4, 133, 135] . Older sera have not been tested and so precisely how long DCs have been afflicted by MERS-CoV, whether the virus is enzootic among them, introduced to them decades or centuries ago from bats in Africa or the Arabian Peninsula, or they are the subject of regular but short-lived viral incursions from an as yet unknown host, cannot be answered.
Researchers sought to determine a direction for infection; were DCs transmitting virus to humans or were humans infecting DCs? At a Qatari site, a farm owner and his employee became ill in mid-October 2013 and tested positive for MERS-CoV RNA in a sputum and throat swab sample, respectively. RT-rtPCRs found MERS-CoV RNA in 11 of 14 positive DC nasal swabs at the farm; six (43 %) positive by two or more assays [138] . The results indicated a recent outbreak had occurred in this herd; the first indication of MERS-CoV RNA found within DCs with a temporal association to human infections. Three positive DC samples were confirmed by sequencing a 358 nt portion of the spike gene; these sequences were identical to each other, again with close homology to other human and DC MERS-CoV sequences [138] . The DCs and human contacts yielded ORF1a and ORF4b sequences differing by only a single nucleotide each, clustering closely with the Hafr-Al-Batin_1_2013 variant [138] . Subsequent case studies found evidence of a concurrent human and DC infection and the direction of that infection was inferred to be from the ill DCs and to their human owners [117, 142, 146] . Partial genome sequences indicated that a human and a MERS-CoV RT-rtPCR positive DC had been infected by a variant of the same virus, harbouring the same distinct pattern of nucleotide polymorphisms. [142] All nine DC in the owner's herd, serially sampled, reacted in a recombinant S1 antigen ELISA, with the two animals that had been RT-rtPCR positive showing a small, verifiable rise in antibody titre [142] . A rise in titre theoretically begins 10 to 21 days after DC infection [142] . The authors suggested that the rise in titre in DC sera which occurred alongside a declining RNA load, while the patient was actively ill and hospitalized, indicated that the DCs were infected first followed by the owner [117, 142] . BCoV antibodies were also present, and rising in one of the two RT-rtPCR positive animals but no animal's antibodies could neutralise BCoV infection [142] .
Camel calving season occurs in the winter months (between late October and late February; Fig. 3 ) and this may be a time when there is increased risk to humans of spill-over due to new infections among naïve DC populations [128] . What role maternal camel antibody might play in delaying infection of calves remains unknown [128, 142] . Juvenile DCs appear to host active infection more often than adult DCs and thus the sacrificial slaughter of DCs, which must be five years of age or older (termed a thane), may not be accompanied by significant risk of exposure to infection. In contrast to earlier results, slaughterhouse workers who kill both younger and older DCs, may be an occupational group with significantly higher incidence of seropositivity to MERS-CoV when animals have active MERS-CoV infections [129, 139, [147] [148] [149] . Expanded virological investigations of African DCs may lead to more seropositive animals and geographic areas in which humans may be at risk. It is possible that there are areas where humans already harbour MERS-CoV infections that have not been identified because of an absence of laboratory surveillance. Virological investigations of bats may lead to findings of ancestral viruses and viral 'missing links' and identifying any other animal sources of zoonotic spread is important to inform options for reducing human exposures [56, 76] .
Infectious MERS-CoV added to DC, goat or cow milk and stored at 4°C could be recovered at least 72 h later and, if stored at 22°C, recovery was possible for up to 48 h [150] . MERS-CoV titre decreased somewhat when recovered from milk at 22°C but pasteurization completely ablated MERS-CoV infectivity [150] . In a subsequent study, MERS-CoV RNA was identified in the milk, nasal secretion and faeces of DCs from Qatar [151] .
A single study has examined the ability of MERS-CoV to survive in the environment [150] . Plastic or steel surfaces were inoculated with 10 6 TCID 50 of MERS-CoV at different temperature and relative humidity (RH) and virus recovery was attempted in cell culture. At high ambient temperature (30°C) and low RH (30 %) MERS-CoV remained viable for 24 h [150] . By comparison, a well known and efficently transmitted respiratory virus, influenza A virus, could not be recovered in culture beyond four hours under any conditions [150] . Aerosol experiments found MERS-CoV viability only decreased 7 % at low RH at 20°C. In comparison, influenza A virus decreased by 95 % [150] . MERS-CoV survival is inferior to that previously demonstrated for SARS-CoV [152] . For context, pathogenic bacteria can remain viable and airborne for 45 min in a coughed aerosol and can spread 4 m. MERS-CoV's ability to remain viable over long time periods gives it the capacity to thoroughly contaminate a room's surfaces when occupied by an infected and symptomatic patient [153] . Whether MERS-CoV can remain adrift and infectious for extended periods (truly airborne) remains unknown. Such findings expand our understanding of the possibilities for droplets to transmit respiratory viruses in many settings, including hospital waiting rooms, emergency departments, treatment rooms, open intensive care facilities and private patient rooms. The nature and quality of air exchange, circulation and filtration are important variables in risk measurement and reduction as is the use of negative pressure rooms to contain known cases. Droplet spread between humans is considered the mechanism of human-to-human transmission and the need for droplet precautions was emphasized after the Al-Ahsa hospital, the KSA and the South Korean outbreaks [21, 23, 154, 155] . By extrapolation, aerosol-generating events involving DCs (urination, defecation, and preparation and consumption of DC products) should be factored into risk measurement and reduction efforts and messaged using appropriate context. The provision of evidence supporting the best formulation of personal protective equipment to be worn by HCWs who receive, manage or conduct procedures on infectious cases remains a priority.
MERS-CoV was found and characterized because of its apparent association with severe, and therefore more obvious, illness in humans; we were the canaries in the coal mine. Sero-assays and prospective cohort studies have yet to determine the extent to which milder or asymptomatic cases contribute to MERS-CoV transmission chains. However, transmission of MERS-CoV is defined as sporadic (not sustained), intra-familial, often healthcare associated, inefficient and requiring close and prolonged contact [22, 31, 63, 93, 97, 102, 156] In a household study, 14 of 280 (5 %) contacts of 26 MERS-CoV positive index patients were RNA or antibody positive; the rate of general transmission, even in outbreaks is around 3 % [31] . It seems that the majority of human cases of MERS-CoV, even when numbers appear to increase suddenly, do not readily transmit to more than one other human so to date, the localized epidemic of MERS-CoV has not been self-sustaining [157] [158] [159] [160] [161] . That is to say, the basic reproduction number (R 0 ) -the average number of infections caused by one infected individual in a fully susceptible populationhas been close to one throughout various clusters and outbreaks. If R 0 was greater than 1, a sustained increase in case numbers would be expected. Some R o calculations may be affected by incomplete case contact tracing, limited community testing and how a case is defined. That MERS has had a constant presence in the Arabian Peninsula since 2012 is due to ongoing, sporadic spill-over events from DCs amplified by poorly controlled hospital outbreaks.
The first known MERS human-to-human transmission event was one characterized by acute LRT disease in a healthcare setting in Jordan. In stark contrast, a sero-survey of HCW who were sometimes in close and prolonged contact with the first, fatal MERS-CoV case in 2012 [162] , found none of the HCW had seroconverted four months later, despite an absence of eye protection and variable compliance with required PPE standards [162] .
Early on in the MERS story, samples for testing were mostly collected from patients with severe illness and not those with milder acute respiratory tract infections. Contacts of confirmed MERS cases were often observed for clinical illness, but not tested. These omissions may have confounded our understanding of MERS-CoV transmission and biased early data towards higher numbers of seriously ill and hospitalized patients, inflating the apparent proportion of fatal cases. Case-control studies were not a focus. As testing paradigms changed and contacts were increasingly tested, more asymptomatic and mild infections were recognized [163] .
A rise in the cases termed asymptomatic (which enlarge the denominator for calculations of the proportion of fatal cases, defined in [164] ) resulted in a drop in the proportion of fatal cases during the Jeddah-2014 outbreak. Historically, such rises are consistent with changing definitions and laboratory responses and clinical management of a newly discovered virus infection that was first noted only among the severely ill. Upon follow-up, over three-quarters of such MERS-CoV RNA positive people did recall having one or more symptoms at the time, despite being reported as asymptomatic [165] raising some question over the reliability of other reported data.
The proportion of fatal MERS cases within the KSA compared to outside the KSA, as well as the age, and sex distribution change in different ways when comparing MERS outbreaks. Approximately 43 % of MERS cases (549 of 1277) in the KSA were fatal betwen 2012 and December 2015 while 21 % (72 of 330) died among those occurring outside of the KSA. The total number of male cases always outnumber females and the proportion of male deaths is always greater than the proportion of females who die. However the proportion of male deaths from total males with MERS is a similar figure to that for females. In the KSA, there is a greater proportion of younger males among cases and deaths than were observed from the 2015 South Korean or the Jeddah-2014 outbreaks (Additional file 2: Figure S2 ). Why these aspects have differed may be due to differences in the time to presentation and diagnosis, the nature and quality of supportive care, the way a person became infected (habits, exposure to a human or zoonotic source, viral load, route of infection) or the extent to which different populations are burdened by underlying diseases [40] .
As a group, HCWs comprised 16 % of MERS cases in the KSA and South Korea. It is apparent that the weekly proportion of infected HCWs increases alongside each steep rise in overall detections (Fig. 5) . In May 2013, the WHO published guidelines for IPC during care of probable or confirmed cases of MERS-CoV infection in a healthcare setting [166] . This is explainable because to date, each case rise has been intimately associated with healthcare-facility related outbreaks [118] . These rises in MERS-CoV detections can decrease the average age during each event because HCWs are usually younger than inpatients with MERS. Healthcare facilities have been a regular target for suggested improvements aimed at improving infection prevention and control (IPC) procedures [115, 118] .
Most of the analysis of MERS-CoV genetics has been performed using high throughput or "deep" sequencing methods for complete genome deduction [167] [168] [169] . MERS-CoV was the first subject of such widespread use of deep sequencing to study an emerging viral outbreak with global reach. The technique can produce genomic [207] [208] [209] . Earlier and subsequent versions of this chart are maintained on a personal blog [210] length coverage in a single experiment with highly repetitious measurement of each nucleotide position [52, 140] . Despite assays having been published early on, subgenomic sequencing, once the mainstay of viral outbreak studies, has less often been published during MERS-CoV characterization [48] . As more genomes from both humans and DCs have been characterized, two clades have become apparent; A and B (Fig. 6) . Clade A contains only human-derived MERS-CoV genomes from Jordan, while Clade B comprises the majority of human and camel genomes deduced thus far [168] .
Two studies during 2015, one looking at Jeddah-2014 MERS-CoV variants and another looking at a variant exported from South Korea to China, have now identified signs of genetic recombination among MERS-CoV variants. While human and camel whole genome sequences have retained >99 % identity with each other, members of genetically distinct lineages can and do swap genetic material when suitable conditions and coinfections co-occur [170] [171] [172] . Shared identity implies that the major source for human acquisition is the DC, rather than another animal, although more testing of other animal species is needed to confirm that conclusion. Over a month, a DC virus sequenced on different occasions did not change at all indicating a degree of genomic stability in its host, supporting that DCs are the natural, rather than intermediate, host for the MERS-CoV we know today [77] . To date, recombination has been localised to breakpoints near the boundary between ORF1a and ORF1b regions, within the spike gene [170] and in the ORF1b region (Fig. 2) [172] . It is not unexpected that recombination should occur since it is well known among other CoVs [124] and because the majority of MERS-CoV whole genomes collected from samples spanning three years (2012-2015) and from humans, camels and different countries have shown close genetic identity to each other, with just enough subtle variation to support outbreak investigations so long as whole genome sequencing is applied [52, 77, 135, 138, 168, [173] [174] [175] .
Changes in genome sequence may herald alterations to virus transmissibility, replication, persistence, lethality or response to future drugs. If we have prior knowledge of the impact of genetic changes because of thorough characterization studies, we can closely Fig. 6 The genetic relationship between MERS-CoV nucleotide sequences (downloaded from GenBank using the listed accession numbers and from virological.org [212] ). This neighbour joining tree was created in MEGA v6 using an alignment of human and DCderived MERS-CoV sequences (Geneious v8.1 [211] ). Clades are indicated next to dark (Clade A) or pale (Clade B) blue vertical bars. Camel icons denote genomes from DCs. Healthcare or community outbreaks are boxed and labelled using previously described schemes [212, 213] monitor the genomic regions and better understand any changes in transmission or disease patterns as they occur. Genetic mutations noted during the largest of human outbreaks, Jeddah-2014, did not impart any major replicative or immunomodulatory changes when compared to earlier viral variants in vitro [156, 176] . However, we understand very little of the phenotypic outcomes that result from subtle genetic change in MERS-CoV genomes. To date no clinical relevance or obvious in vivo changes to viral replication, shedding or transmission has been reported or attributed to mutations or to new recombinant viruses [156] . But vigilance and larger, more contemporary and in vivo studies are needed.
Genome sequence located to a distinct clade were identified from an Egyptian DC that was probably imported from Sudan. This does not fit into either of the current clades [125, 168, 177] . A virus sequenced from a Neoromicia capensis bat was more closely related to MERS-CoV than other large bat-derived sequences had been to that point, but the genome of a variant of a MERS-CoV has yet to be discovered and deduced from any bat [125] .
Analyses of MERS-CoV genomes have shown that most single nucleotide differences among variants were located in the last third of the genome (Fig. 2) , which encodes the spike protein and accessory proteins [168] . At least nine MERS-CoV genomes contained amino acid substitutions in the receptor binding domain (RBD) of the spike protein and codons 158 (N-terminal region), 460 (RBD), 1020 (in heptad repeat 1), 1202 and 1208 bear investigation as markers of adaptive change [140, 169] . The spike protein had not changed in the recombinant MERS-CoV genome identified in China in 2015 but was reported to have varied at a higher rate than that for complete MERS-CoV genomes, among South Korean variants [172, 178] . This highlights that subgenomic regions may not always contain enough genetic diversity to prove useful for differentiating viral variants. Despite this, one assay amplifying a 615 nucleotide fragment of the spike S2 domain gene for Sanger sequencing agreed with the results generated by the sequencing of a some full genomes and was useful to define additional sequence groupings [177] .
Genomic sequence can also be used to define the geographic boundaries of a cluster or outbreak and monitor its progress, based on the similarity of the variants found among infected humans and animals when occurring together, or between different sites and times (Fig. 6 ) [169] . This approach was employed when defining the geographically constrained MERS hospital outbreak in Al-Ahsa, which occurred between 1 st April and 23 rd May 2013, as well as clusters in Buraidah and a community outbreak in Hafr Al-Batin, the KSA. Genomic sequencing identified that approximately 12 MERS-CoV detections from a community outbreak in Hafr Al-Batin between June and August 2013 may have been triggered by an index case becoming infected through DC contact [175] . Sequencing MERS-CoV genomes from the 2013 Al-Ahsa hospital outbreak indicated that multiple viral variants contributed to the cases but that most were similar enough to each other to be consistent with human-tohuman transmission. Molecular epidemiology has revealed otherwise hidden links in transmission chains encompassing a period of up to five months [179] . However, most outbreaks have not continued for longer than two to three months and so opportunities for the virus to adapt further to humans through co-infection and sustained serial passage have been rare [169] . In Riyadh-2014, genetic evidence supported the likelihood of multiple external introductions of virus, implicating a range of healthcare facilities in an event that otherwise looked contiguous [23, 168, 179] . Riyadh is a nexus for camel and human travel and has had more MERS cases than any other region of the KSA to date but also harbours a wide range of MERS-CoV variants [128, 167, 179] . However the South Korean outbreak originated from a single infected person, resulting in three to four generations of cases [180, 181] . Studies of this apparently recombinant viral variant did not find an increased evolutionary rate and no sign of virus adaptation thus the outbreak seems to have been driven by circumstance rather than circumstance together with mutation [181] .
For many MERS cases detected outside the Arabian Peninsula, extensive contact tracing has been performed and the results described in detail. Contact tracing is essential to contain the emergence and transmission of a new virus and today it is supported by molecular epidemiology. Although it is an expensive and time consuming process, contact tracing can identify potential new infections and through active or passive monitoring, react more rapidly if disease does develop. Results of contact tracing to date have found that onward transmission among humans is an infrequent event. For example, there were 83 contacts, both symptomatic and asymptomatic, of a case treated in Germany who travelled from the UAE but no sign of virus or antibody were found in any of them [73] . The very first MERS case had made contact with 56 HCWs and 48 others, but none developed any indication of infection [162] . In a study of 123 contacts of a case treated in France, only seven matched the definition for a possible case and were tested; one who had shared a 20 m 2 hospital room while in a bed 1.5 m away from the index case for a prolonged period was positive [26] . None of the contacts of the first two MERS cases imported into the USA in 2014 contained any MERS-CoV footprint [182] and none of the 131 contacts of two travellers returning to the Netherlands developed MERS-CoV antibodies or tested RNA positive [25, 183] . Analyses of public data reveal many likely instances of nosocomial acquisition of infection in the Arabian Peninsula and these data may be accompanied by some details noting contact with a known case or facility. One example identified the likely role of a patient with a subclinical infection, present in a hospital during their admission for other reasons, as the likeliest index case triggering a family cluster [93] . Contact tracing was a significant factor in the termination of a 2015 outbreak involving multiple South Korean hospitals [184] . Such studies demonstrate the necessity of finding and understanding a role for mild and asymptomatic cases, together with restricting close contact or prolonged exposure of infected people to others, especially older family members and friends with underlying disease (Fig. 4c) .
The hospital-associated outbreak in Jeddah in 2014 was the largest and most rapid accumulation of MERS-CoV detections to date. The greatest number of MERS-CoV detections of any month on record occurred in Jeddah in April. The outbreak was mostly (>60 % of cases) associated with human-to-human spread within hospital environments and resulted from a lack of, or breakdown in, infection prevention and control [37, 185, 186] . A rise in fatalities followed the rapid increase in case numbers.
In 2015 two large outbreaks occurred. South Korea was the site of the first large scale outbreak outside the Arabian Peninsula and produced the first cases in both South Korea and China, occurring between May and July 2015. This was closely followed by a distinct outbreak in Ar Riyad province in the KSA which appeared to come under control in early November.
After staying in Bahrain for two weeks, a 68 year old male (68 M) travelled home to South Korea via Qatar, arriving free of symptoms on the 4 th May 2015 [187] . He developed fever, myalgia and a cough nearly a week later (11 th ). He visited a clinic as an outpatient between the 12 th and 15 th of May and was admitted to Hospital A on the 15 th [188] . He was discharged from Hospital A on the 17 th then visited and was admitted to the emergency department of Hospital B on the 18 th . During this second stay, a sputum sample was taken and tested positive for MERS-CoV on the 20 th [187, 188] , triggering transfer to the designated isolation treatment facility. Over a period of 10 days, the index case was seen at three different hospitals, demonstrating a key feature of "hospital shopping" that shaped the South Korean outbreak. Approximately 34 people were infected during this time [187] . In total 186 cases were generated in this outbreak, all linked through a single transmission chain to 68 M; 37 cases died [189] . In South Korea, the national health insurance system provides for relatively low cost medical care, defraying some costs by making family members responsible for a portion of the ministration of the sick, resulting in them sometimes staying for long periods in the rooms that often have more than four beds in them [24] . Other factors thought to have enabled this outbreak included unfamiliarity of local clinicians with MERS, ease with which the public can visit and be treated by tertiary hospitals, the custom of visiting sick friends and relatives in hospitals, the hierarchical nature of Korean society, crowded emergency rooms, poor IPC measures, a lack of negative pressure isolation rooms and poor inter-hospital communication of patient disease histories [24, [190] [191] [192] . All of the reported transmission occurred across three or four generations and apart from one unknown source, were all hospital-acquired [24, 120, 181, [193] [194] [195] . Few clinical details about these cases have been reported to date and detail on transmission and contact tracing is minimal. The hospitals involved were initially not identified, governmental guidance and actions produced confusing messages and there was very limited communication at all early on which resulted in unnecessary concern, distrust and a distinct economic impact [191, [196] [197] [198] . Early in the outbreak, a infected traveller, the son of an identified case in South Korea, passed through Hong Kong on his way to China where he was located, isolated and cared for in China [91, 199, 200] . No contacts became ill. The outbreak was brought under control in late July/ early August [201] after improved IPC measures were employed, strong contact tracing monitoring and quarantine, expanded laboratory testing, hospitals were better secured, specialized personnel were dispatched to manage cases and international cooperation increased [202, 203] . A review of public data showed that, as for MERS in the KSA, older age and the presence of underlying disease were significantly associated with a fatal outcome in South Korea. [40] Even though R 0 is <1, super-spreading events facilitated by circumstances created in healthcare settings and characterized by cluster sizes over 150, such as this one, are not unexpected from MERS-CoV infection [204] . The dynamic of an outbreak depends on the R 0 and an individual's viral shedding patterns, contact type and frequency, hospital procedures and population structure and density [204] .
In the region of Ar Riyad, including the capital city of Riyadh, a hospital based cluster began, within a single hospital, from late June 2015 [205] . By mid-September there had been approximately170 cases reported but the outbreak appeared to been brought under control in November.
It became apparent early on that MERS-CoV spread relatively ineffectively from human-to-human. Despite ongoing and possibly seasonal introduction of virus to the human population via infected DCs and perhaps other animals yet to be identified, the vast majority of MERS-CoV transmission has occurred from infected to uninfected humans in close and prolonged contact through circumstances created by poor infection control in health care settings. This opportunistic virus has had its greatest impact on those with underlying diseases and such vulnerable people, sometimes suffering multiple comorbidities, have been most often associated with hospitals, creating a perfect storm of exposure, transmission and mortality. It remains unclear if this group are uniquely affected by MERS-CoV or if other respiratory virus infections, including those from HCoVs, produce a similarly serious impact. In South Korea, a single imported case created an outbreak of 185 cases and 36 deaths that had a disproportionate impact on economic performance, community behaviour and trust in government and the health care system. Household human-to human transmission occurs but is also limited. Educational programs will be essential tools for combatting the spread of MERS-CoV both within urban and regional communities and for the health care setting.
Vigilance remains important for containment since MERS-CoV is a virus with a genetic makeup that has been observed for only three years and is not stable. Among all humans reported to be infected, nearly 40 % have died. Continued laboratory testing, sequencing, analysis, timely data sharing and clear communication are essential for such vigilance to be effective. Global alignment of case definitions would further aid accurate calculation of a case fatality ratio by including subclinical case numbers. Whole genome sequencing has been used extensively to study MERS-CoV travel and variation and although it remains a tool for experts, it appears to be the best tool for the job.
MERS and SARS have some clinical similarities but they also diverge significantly [206] . Defining characteristics include the higher PFC among MERS cases (above 50 % in 2013 and currently at 30-40 %; well above the 9 % of SARS) and the higher association between fatal MERS and older males with underlying comorbidities. For the viruses, MERS-CoV has a broader tropism, grows more rapidly in vitro, more rapidly induces cytopathogenic change, triggers distinct transcriptional responses, makes use of a different receptor, induces a more proinflammatory state and has a delayed innate antiviral response compared to SARS-CoV.
There appears to be a 2-3 % prevalence of MERS-CoV in the KSA with a 5 % chance of secondary transmission within the household. There is an increased risk of infection through certain occupations at certain times and a much greater chance for spread to other humans during circumstances created by humans, which drives more effective transmission than any R 0 would predict on face value. Nonetheless, despite multiple mass gatherings that have afforded the virus many millions of opportunities to spread, there have remarkably been no reported outbreaks of MERS or MERS-CoV during or immediately after these events. There is no evidence that MERS-CoV is a virus of pandemic concern. Nonetheless, hospital settings continue to describe MERS cases and outbreaks in the Arabian Peninsula. As long as we facilitate the spread of MERS-CoV among our most vulnerable populations, the world must remain on alert for cases which may be exported more frequently when a host country with infected camel reservoirs is experiencing human clusters or outbreaks.
The MERS-CoV appears to be an enzootic virus infecting the DC URT with evidence of recent genetic recombination. It may once have had its origins among bats, but evidence is lacking and the relevance of that to today's ongoing epidemic is academic. Thanks to quick action, the sensitive and rapid molecular diagnostic tools required to achieve rapid and sensitive detection goal have been in place and made widely available since the virus was reported in 2012. RT-PCR testing of LRT samples remains the gold standard for MERS-CoV confirmation. Serological tools continue to emerge but they are in need of further validation using samples from mild and asymptomatic infections and a densely sampled cohort study to follow contacts of new cases may address this need. Similarly, the important question of whether those who do shed MERS-CoV RNA for extended periods are infectious while appearing well, continues to go unanswered. It is even unclear just how many 'asymptomatic' infections have been described and reported correctly which in turn raises questions about the reliability of other clinical data collection to date. While the basic virology of MERS-CoV has advanced over the course of the past three years, understanding what is happening in, and the interplay between, camel, environment and human is still in its infancy.
Additional file 1: Figure S1 . The | What appears to be a requirement for transmission? | false | 4,180 | {
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1,661 | Neutralization Interfering Antibodies: A “Novel” Example of Humoral Immune Dysfunction Facilitating Viral Escape?
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3499828/
SHA: f4f75af02b7226c5b2363de1a75821a4b9b20412
Authors: Nicasio, Mancini; Sautto, Giuseppe; Clementi, Nicola; Diotti, Roberta A.; Criscuolo, Elena; Castelli, Matteo; Solforosi, Laura; Clementi, Massimo; Burioni, Roberto
Date: 2012-09-24
DOI: 10.3390/v4091731
License: cc-by
Abstract: The immune response against some viral pathogens, in particular those causing chronic infections, is often ineffective notwithstanding a robust humoral neutralizing response. Several evasion mechanisms capable of subverting the activity of neutralizing antibodies (nAbs) have been described. Among them, the elicitation of non-neutralizing and interfering Abs has been hypothesized. Recently, this evasion mechanism has acquired an increasing interest given its possible impact on novel nAb-based antiviral therapeutic and prophylactic approaches. In this review, we illustrate the mechanisms of Ab-mediated interference and the viral pathogens described in literature as able to adopt this “novel” evasion strategy.
Text: Hypervariable viruses adopt several mechanisms to cope with the host humoral immune response. The most studied mechanism is the accumulation of point mutations on immunodominant regions of surface proteins, making them no longer recognizable by previously generated neutralizing antibodies (nAbs) [1] [2] [3] [4] . Other escape mechanisms involving surface proteins include glycosylation of functionally pivotal residues (the glycan shield) or their association with host serum components (e.g., lipoproteins) in order to mask them from the immune system [5] [6] [7] [8] [9] (Figure 1A ). Other known escape mechanisms are (i) a sort of protected route of virus spreading, such as cell-to-cell transmission [10, 11] ; (ii) the molecular mimicry between viral proteins and host self-antigens or (iii) the viral-induced stimulation of subfamily-restricted antibodies (Abs), both with obvious implications in viral-induced autoimmune diseases such as cryoglobulinemia for HCV [12] [13] [14] . The possible interfering effect of non-neutralizing Abs (non-nAbs) was originally proposed by Dulbecco et al. in 1956 [15] , to explain the apparent inhibition of virus neutralization exerted by some serum samples. Recently, this proposed immune escape mechanism has re-acquired a relevant interest, especially considering the potential clinical use of neutralizing anti-infectious nAbs or the design of epitope-based vaccinal approaches [16] . To date, two main mechanisms have been proposed for the interfering effects of non-nAbs: (i) direct binding interference by steric hindrance, (ii) inhibition of binding following conformational changes of the viral antigen bound by interfering non-nAbs. Moreover, it has been speculated that, even when not directly interfering with nAbs binding, non-nAbs may also lead to the enhancement of viral infection through interaction with Fc receptors or complement receptors [17] .
Overall, possibly elicited non-nAbs in infected or vaccinated individuals may interfere with the neutralizing potential of nAbs. In more detail, these interfering Abs are able to bind viral proteins at the level of immunodominant but functionally irrelevant regions of viral proteins, decreasing or blocking the binding of nAbs to crucial viral epitopes (e.g., receptor-binding domains) ( Figure 1B ) [18] . A candidate antiviral monoclonal antibody (mAb) or polyclonal preparation should not be subjected to this mechanism of interference, or to the other escape mechanisms previously mentioned. Similarly, novel vaccinal approaches should avoid the elicitation of interfering Abs that could even worsen the disease in case of a real infection.
In the following paragraphs we discuss these mechanisms with specific examples of their role in the course of the viral infections where they have been described.
Hepatitis C virus (HCV) is a positive-sense single stranded RNA enveloped virus causing chronic hepatitis in most untreated patients (about 80%), with the consequent risk of developing cirrhosis and hepatocellular carcinoma. More than 170 million people (2%-3% of the world population) are infected worldwide, and a protective vaccine is not yet available, whereas therapeutic options are still limited and not completely effective [19] . For these reasons chronic HCV infection represents the major indication for liver transplantation in Europe and United States. Moreover, transplanted recipients are subject to high risk of graft re-infection and to a more severe and rapid progression of the liver disease [20] .
Schematic representation of viral escape mechanisms from humoral immune response against surface viral proteins: point mutations on immunodominant regions, glycosylation of functionally pivotal residues (glycan shield) of the viral surface proteins and virus association with host serum components (e.g., lipoproteins) (B) Mechanisms of interference on nAb-mediated virus neutralization by the binding of interfering non-nAbs: non-neutralizing/interfering Abs might interfere with the binding of nAbs by steric hindrance following a spatial occupancy of their epitope or a competition for the binding; otherwise the binding of non-neutralizing/interfering Abs may induce conformational changes on the viral protein, thus affecting nAb binding to the antigen. Non-neutralizing/interfering Abs are depicted in black while nAbs in yellow.
The HCV genome encodes a single polyprotein of about 3,000 aminoacids that is processed by host and viral proteases into at least 3 structural (core, E1 and E2) and 7 non-structural (p7, NS2, NS3, NS4A, NS4B, NS5A and NS5B) proteins [21, 22] . In particular, the envelope type I membrane glycoproteins E1 and E2 form non-covalent heterodimers on the surface of the HCV envelope and allow clathrin-mediated virus endocytosis interacting consecutively with several entry cellular factors such as glycosaminoglycans [23] [24] [25] , low-density lipoprotein receptor [26, 27] , scavenger receptor class B type I [28] , the tetraspanin CD81 [29] , the tight-junction proteins claudin-1 and occludin, and the recently described Niemann-Pick C1-like 1 cholesterol absorption receptor [30] [31] [32] [33] [34] . The development of effective prophylactic and therapeutic approaches against this virus has been hindered mainly by its high mutation rate that gives rise to highly diversified viral variants, even within a single patient (quasispecies) [35] . Indeed, seven major genotypes, varying by up to 30% in nucleotide sequence, and several subtypes are recognized, each characterized by different clinical features such as different evolutionary rates to chronic liver diseases or different response to available antiviral therapies [21, 36, 37] .
The development and use of anti-HCV mAbs capable of targeting structurally and functionally conserved regions of the highly variable viral particles are being considered as novel therapeutic tools [38] [39] [40] [41] [42] [43] . In particular, the production of potent nAbs in acute infections has been shown to correlate with viral clearance in a single-source outbreak cohort [44] . Moreover, in vaccinated chimpanzees, a sustained Ab response to envelope glycoproteins E1 and E2 correlates with reduced viremia [45] , while the passive administration of neutralizing mAbs in a uPA-SCID chimeric mouse model of infection was able to protect against challenge with a HCV quasispecies inoculum [46] . Broadly cross-neutralizing human mAbs directed against the surface E2 glycoprotein of HCV (HCV/E2) are typically directed against functionally important regions within the CD81 binding site [47] [48] [49] [50] [51] [52] [53] [54] , as well as against other critical residues highly conserved among different genotypes [55, 56] . This aspect is crucial for the possible therapeutic in vivo use of such mAbs, but it may not be sufficient since it has been recently supposed that other non-nAb populations may interfere with their neutralizing activity [39, [57] [58] [59] [60] [61] . In fact, in persistently infected individuals anti-HCV/E2 cross-nAbs are generally elicited at low titer and in a late stage of the infection, leading to a poor control of viremia, whereas quasispecies-specific neutralizing or high titer non-nAbs are elicited earlier [53, [58] [59] [60] [61] [62] . Moreover, the in vivo use of anti-HCV polyclonal immunoglobulin preparations in both chimpanzees and humans has been disappointing, and clinical studies have shown that these preparations fail to prevent recurrent infections in patients after liver transplantation [63] .
At this regard, a recent paper has suggested that the effect of some of these nAbs, directed against functionally important residues involved in the viral binding to CD81 (within epitope I, encompassing aminoacid residues 412-426), could be hindered by the presence of non-nAbs binding residues within epitope II on HCV/E2 (aminoacid residues 434-446) [58] . In particular, blocking of these interfering epitope II-specific Abs not only raised the neutralizing titer of serum containing both epitope I-and epitope II-specific Abs, but also uncovered a broader cross-genotype neutralizing response [58] . However, the role (and the existence itself) of these interfering Abs in influencing HCV infection is still controversial. Some authors recently corroborated the data of Zhang et al. by in vitro neutralization assays using serum-derived HCV of genotype 4a and polyclonal Abs derived from immunized goats with different conserved peptides spanning aminoacid residues 412-419, 430-447 and 517-531 of HCV/E2 glycoprotein [64] . In particular, this group found an interfering activity exerted by the weakly neutralizing 430-447-elicited Abs on the neutralizing activity of both the 412-419 and the 517-531-elicited Abs [64] . Interestingly, according to the putative model for E2 folding, all the three aforementioned regions would lie next to each other on the glycoprotein [48] . Therefore, this structural prediction possibly supports the interfering effect of epitope II-directed Abs. However, while this predicted structure is currently the best model available, these conclusions cannot be absolutely ascertained. For this purpose, the availability of E1-E2 crystal will certainly accelerate the fine elucidation of the spatial proximities of neutralizing and interfering mAbs on the E1-E2 structure and, consequently, structure-based vaccine progress.
Moreover, it is noteworthy that individuals with Abs that target the region of E2 encompassing epitope I frequently harbor Abs that recognize the region containing epitope II, thus confirming the co-immunogenicity of these epitopes [58] . Finally, it has been shown both a low prevalence (less than 2.5%) and a low titer of epitope I-reactive Abs in sera from both chronic and acute resolved infections thus supporting the hypothesis of a conformational masking by adjacent regions such as that containing epitope II [65] . In fact, Zhang et al. originally put forward the idea that once epitope II is bound to an Ab, the site of epitope I becomes masked and can no longer be recognized by specific nAbs. Indeed, depletion of Abs to epitope II in plasma from a chronically infected HCV patient and vaccinated chimpanzees recovered an otherwise undetectable cross-genotype neutralizing activity [58] . Another possibility is that the initial binding of interfering Abs to the region containing epitope II may induce conformational changes on E2 that inhibit the binding by epitope I-directed Abs, as recently suggested by Lapierre et al. for other anti-HCV/E2 Abs [66] .
Conversely, these conclusions were not supported in a recent study by Tarr et al. using murine (AP33) and rat (2/69a) mAbs, as well as human immunoglobulin fractions affinity-purified on linear peptides representing distinct HCV/E2 domains clustering within the regions 412-426 and 434-446 [67] . Although confirming the previously reported co-immunogenicity of these two regions, the authors failed to demonstrate any inhibition between these two groups of Abs. Considering their results, the authors indeed suggested that interference by non-nAbs, at least to the region encompassing residues 434-446, is not a possible mechanism for HCV persistence in chronically infected individuals, as it had been originally proposed by Zhang et al. In accordance with the findings of Tarr and colleagues, Keck et al. described anti-HCV/E2 human mAbs binding conformation-sensitive epitopes encompassing also some residues within the 434-446 interfering region [56] . These mAbs are broadly neutralizing and do not lead to viral escape mutants, demonstrating the functional importance of their epitopes. The authors conclude that not all Abs directed against epitope II are interfering, but they also speculate that the interfering activity could be limited to Abs recognizing linear epitopes within it [56] .
Recently, we have partly confirmed the observations of Zhang et al. using a panel of anti-HCV/E2 mAbs: the well characterized mouse anti-HCV/E2 mAb AP33, whose epitope encompasses epitope I (aminoacid residues 412-423), and a weakly neutralizing human anti-HCV/E2 mAb (named e509), whose epitope encompasses epitope II [68] . In particular, we found that e509 is able to interfere with the neutralizing activity of AP33 on genotype 1a virus (strain H77). Instead, we found that e509 does not minimally interfere with the activity of two other broadly cross-neutralizing human anti-HCV/E2 mAbs, named e20 and e137 [49, 69] . Interestingly, we found that both e20 and e137 bind also residues within epitope II, at a higher affinity compared to e509, thus displacing it from the interfering epitope and, therefore, keeping unaltered their neutralizing activity. Thus, in our opinion, the described divergent observations reported above may depend on the different Ab specificities present in the polyclonal preparations used and, probably, also on the different HCV genotypes infecting the studied patients [68] . Moreover, the different strategies adopted in isolating epitope I-and epitope II-directed Abs followed in the studies above could explain the different data obtained. In fact, immunoglobulins purified on peptides representing distinct HCV/E2 regions [67] are obviously directed against linear epitopes; these preparations are certainly different from mAbs cloned using a full-length HCV/E2 glycoprotein, which are more probably directed against conformational epitopes including also residues outside the investigated linear regions [54] .
To summarize, in the HCV field several works support the existence of interfering Ab populations and hypothesize their possible role in HCV persistence, as demonstrated using human plasma-derived immunoglobulin preparations, human mAbs, and sera of animals vaccinated with recombinant HCV/E2 peptides. The possible mechanism leading to the interference is still controversial, but both direct steric hindrance and induced antigen conformational changes have been hypothesized. On the other hand, other papers do not confirm these findings, suggesting that the putative interfering epitope II may be targeted by Abs endowed with a broadly neutralizing activity. Our recent paper, using well characterized mAbs [68] , shows that the interfering Abs do exist but that their overall effect may be biased by the presence of nAbs with different binding features and by the infecting HCV genotype. Future works investigating the in vivo role of these interfering Ab subpopulations in HCV persistence will certainly be very useful.
The influenza viruses circulate worldwide in animal reservoirs, especially water fowl, potentially affecting humans of any age group. Influenza viruses are classified into types A, B or C based on antigenic differences of their nucleoprotein and matrix protein. The most clinically relevant and variable type is influenza A which is divided in several subtypes, according to the antigenic characteristic of the two envelope glycoproteins, and causes epidemic and pandemic infections [70] . The yearly recurring influenza epidemics are associated with significant morbidity and mortality, particularly among risk groups (such as elderly people or those with chronic medical conditions, pregnant women and children) [71] ; the global spread of pandemic influenza viruses can cause millions of deaths [72] .
Within the enveloped influenza virion eight segments of negative single-stranded RNA are protected by the nucleocapsid protein, forming the ribonucleoprotein (RNP). The first six RNA segments each code for a single protein: PB2, PB1, and PA (all constituting the RNA-dependent RNA polymerase), the hemagglutinin (HA), the nucleoprotein (NP), the neuraminidase (NA). The last two segments each code for two different proteins: the matrix proteins (M1 and M2) and the non-structural proteins (NS1 and NS2). Three different proteins (HA, NA and M2) are present on the viral envelope. The HA glycoprotein is the most abundant and it is the major target of the humoral immune response. Together with the NA transmembrane glycoprotein, HA is capable of eliciting a subtype-specific immune responses which is fully protective within, but only partially protective across different subtypes [73] . HA is synthesized as inactive precursor that transits into its active form upon cleavage by host cell proteases, and which is present on the viral membrane as homotrimers. HA trimers bind to 2,6-linked sialic acid molecules on cell membrane proteins or lipids through domains located in the globular head of each monomer. Subsequently, the viral envelope fuses by clathrin-dependent and -independent mechanisms with the endocytic vesicle membrane through the HA fusion peptide located in the stem region of each monomer. As a consequence, viral components are released into the host cell and can subvert the synthetic capabilities of the host cell for production and release of progeny particles [74] .
The humoral immunity plays an important role in the host defense against influenza virus infection as most of Abs neutralize influenza viruses and, hence, limit infection [75] [76] [77] [78] . In fact, a large body of experimental works suggests that occlusion of the receptor-binding site on HA by Abs is the main mechanism of influenza viral neutralization. Less common, but more broadly nAbs may neutralize influenza virus by inhibiting fusion of the viral envelope with the endocytic-vesicle membrane [50, [79] [80] [81] [82] [83] . Aminoacid changes on HA, more frequent on the immunodominant globular head, have complex effects on viral neutralization by Abs, usually allowing the mutated variants to escape from previously generated nAbs [84] . Classical studies using neutralizing mouse mAbs identified five distinct antigenic sites (A-E) on the HA1 globular head region in the three-dimensional structure of the H3 HA molecule (A/Hong Kong/1/68) [85] [86] [87] as well as in H1 [88] and H2 subtypes [89] .
During the first few days of an infection, the nAb titer is often low, while the titer of non-nAbs is higher and may play a role in the outcome of an infection, as recently observed for influenza A/2009 H1N1 pandemic virus infected patients by To et al. [90] . In particular, this group found that the amount, as well as the avidity, of non-nAbs were higher for patients with severe disease than for those with mild disease. The authors concluded that an exaggerated non-nAb response during the early stage of infection was associated with severe disease [90] . Moreover, the authors speculated that non-nAbs present in patients' sera during the early stage of infection were likely to be either preexisting or the result of a secondary heterosubtypic humoral immune response against more conserved epitopes on several influenza proteins [91] . This early humoral response can be elicited within a few days after infection, because of immune priming by previous exposure to shared viral epitopes. In fact, the matrix proteins and nucleoprotein have conserved aminoacid sequences, and therefore Abs against these proteins from previous seasonal influenza virus infection or vaccination could be induced [92] . Indeed, upon infection with influenza virus, memory B-cells can proliferate rapidly and generate a large amount of these high avidity non-nAbs, especially in patients with severe disease. This is consistent with the observation that the number of peripheral blood B-cells is higher in patients with severe disease than in those with mild disease during the early stage of infection.
The mechanism of Ab neutralization interference has been indirectly speculated also by Ndifon et al., who observed that some aminoacid changes on HA actually increase the efficiency of neutralization of escape variants by previously generated Abs, even if not directly influencing their binding [93] . In detail, this group suggested that the increase in neutralizing activity after HA mutation could be the resultant of a lesser steric interference between Abs. Specifically, if there is a steric competition for binding to HA by Abs with different neutralization efficiency, then a mutation that reduces the binding of Abs with low neutralizing activity could increase the overall viral neutralization. Indeed, similarly to what has been speculated for HCV, Abs that bind to HA epitopes located at a distance from the receptor-binding site may therefore fail to occupy this site efficiently, thereby leading to a decreased viral neutralization. Moreover, it has been shown that Abs that bind to a certain HA epitope can prevent further binding of Abs to other epitopes of the same HA protein, and even to epitopes found on adjacent HA proteins. The above observations suggest that Abs that bind to low-neutralization efficiency epitopes of HA might interfere with the binding of nAbs to close high-neutralization efficiency epitopes, thereby impeding the neutralization of influenza viruses. Considering the HA structure, the binding of the interfering Abs would lie at the level of epitope C and E located far from the receptor-binding site on the globular head of the HA. However, the binding of these Abs may influence the binding of nAbs to epitopes A, B and D, located closer to the receptorbinding site [93] . At this regard changes to epitope A, B and D could be highly favored by natural selection, whereas changes to epitopes C and E could be disadvantageous to influenza viruses [93] .
Similarly to HCV, but with a sounder confirm due to the availability of the crystal structure, these speculations raise the intriguing possibility that the influenza viruses may have evolved by favoring the preferential elicitation of Abs recognizing epitopes with a low-neutralization profile. Indeed, steric hindrance by Abs that bind these epitopes could greatly reduce the extent of mutation required for a virus to evade neutralization by host Abs. Consequently, a decrease in the affinity of Abs for epitopes with low-neutralization efficiency could lead to an increase in viral neutralization. This suggests a possible approach to design "low-interference" vaccines that could greatly diminish the impact of Ab interference. These immunogens are genetically modified from viral target only at the level of low-neutralization efficiency epitopes. Indeed, vaccine-induced Abs only recognize high-neutralization efficiency epitopes of the target and Abs induced by low-interference vaccine strain have low affinity for low-neutralization efficiency epitopes of the target circulating virus strain. Therefore, they do not interfere with Abs to high-neutralization efficiency epitopes, implying an improved neutralization. Consequently, limiting Ab-mediated interference, the target virus cannot escape from vaccine-induced Abs through small epitope changes. Alternatively, vaccines could be designed to include only those regions that correspond to epitopes with high-neutralization efficiency.
Furthermore, antiviral drugs could be designed to include viral proteins carrying modifications at the level of high-neutralization efficiency epitopes; these "decoy" proteins would compete with virus for binding to low-neutralization efficiency Abs in a manner similar to that played by neuraminidase inhibitors.
In synthesis, the availability of HA crystal structure has helped to confirm the existence and to explain the mechanisms of interference by non-or weakly-neutralizing anti-HA Abs. The recent work by To et al. [90] evidencing that a non-nAb response during the early stage of infection is associated with a severe disease, may be the first proof of the role of these interfering Abs in the course of a natural infection.
The [94] . More than 8,000 cases, including almost 800 deaths, were reported during the outbreak period and increasing age and comorbidity were risk factors for severe disease and death [95] . Since 2003, only sporadic cases have been reported; however, the possibility that SARS outbreaks could reemerge naturally or be deliberately released is a public health concern. Like influenza viruses, SARS-CoV circulates in animal reservoirs, with bats that are thought to transmit the virus to small mammals with exposure to these small animals as the source of human infections [96] . The clinical disease is similar to other severe acute respiratory infections, including influenza, and the SARS case definition includes clinical, epidemiologic, and laboratory criteria [97, 98] .
The basic genome organization and replicative cycle is similar for all CoVs. Gene 1 encodes all predicted replicase/transcriptase proteins, which are translated from input genomic RNA, while genes 2-9 encode structural and accessory proteins, including the envelope spike (S) protein, which are translated from separate subgenomic mRNAs. CoVs use a unique discontinuous mechanism to transcribe a series of progressively larger subgenomic mRNAs, and each contains a leader RNA sequence that is derived from the 5' end of the genome [99] .
The S protein of CoVs is inserted in the envelope of the virion mediating binding and fusion events necessary for infection, and it is the major target of the humoral protective immunity [100] . Although the S protein of SARS-CoV (SARS-S) shares little aminoacid identity (approximately 20%-27%), it shares common structural features with S proteins of the other members of the Coronaviridae family. SARS-S protein is a type I transmembrane glycoprotein of approximately 1,255 amino acids in length and divided into two functional domains: S1 (aminoacid residues 15-680) and S2 (aminoacid residues 681-1,255) [101] . In many CoVs, the S protein is cleaved during biogenesis and these two functional domains are held together non-covalently; however, as in the case of human CoV 229E, the S protein is not cleaved in SARS-CoV [102] . The S1 domain forms a globular structure that mediates interaction of the S protein with its main receptor, angiotensin-converting enzyme 2 (ACE2), while the S2 domain mediates fusion and contains the putative fusion peptide and two conserved helical regions (HR1 and HR2) that upon cleavage by the endosomal protease cathepsin L form the six helix bundle fusion core [103] .
Vaccine strategies aiming at blocking/limiting infection by SARS-CoV mainly focus on targeting the SARS-S viral glycoprotein [100] . Nonetheless, such a strategy poses a singular dilemma for CoVs, as previous vaccination protocols have highlighted the possibility of immune-mediated enhancement of the disease [104] .
At this regard, the group of Zhong et al. investigated the role of non-neutralizing interfering Abs also in the case of SARS-CoV infection [105] . In particular, they found that two mAbs directed against the region encompassing aminoacid residues 491-510 of SARS-S (341C and 540C) act synergistically to inhibit SARS-CoV infection in vitro, while a non-neutralizing mAb (240C) whose epitope encompasses the above mentioned region, disrupted the neutralizing activity of both 341C and 540C [105, 106] . By analyzing the crystal structure of the SARS-S protein, the authors proposed a possible explanation to what observed, evidencing that the epitopes of all the mAbs are closely packed and proximal to each other but distal from the ACE2 receptor binding site [105] . Moreover, the epitope of the non-neutralizing mAb 240C partially overlaps by at least 2 aminoacids (P507 and A508) with that of the neutralizing mAb 341C. As a consequence, mAb 240C could inhibit mAb 341C binding in an equilibrium-related manner. On the other hand, the authors found that the 240C mAb could sterically interfere with the binding of the 540C mAb through the proposed mechanism of spatial occupancy ( Figure 1B) . In fact, the accessibility of mAb 540C to its epitope may be blocked by the mAb 240C binding that masks the surface area containing it. In fact, as speculated by Davies and Cohen, the buried area of an Ab can range from 500 Å 2 to more than 800 Å 2 corresponding to 21-32 aminoacids, although only 9-20 aminoacid residues (the real epitope) make direct contacts with the Ab [107] . In fact, as previously observed for HCV, influenza and other human and animal viruses [108] , one of the possible mechanisms is that the steric block by non-nAbs reduces the binding of nAbs on the SARS-S protein disabling neutralization. Conversely, notwithstanding the epitopes of mAbs 341C and 540C are located on a single loop; they are spatially separated thereby providing distinct interfaces for independent Ab binding.
To conclude, SARS-CoV can elicit potentially interfering non-nAbs by presenting on its surface closely packed regions with different biological features. On the other hand, the host can mount a vigorous neutralizing humoral response by producing Abs that recognize distinct epitopes and act synergistically. In particular, these results suggest that a cocktail of neutralizing human mAb that can bind to unique epitopes and have different mechanisms of action might be of clinical utility against SARS-CoV infection, and indicate that a similar approach may be applied to treat other viral infections [109] .
The human immunodeficiency virus (HIV) is a positive single-stranded RNA retrovirus, causing substantial morbidity and mortality across the globe, particularly in developing countries. Human immunodeficiency viruses type 1 and 2 (HIV-1 and HIV-2) are the results of multi-interspecies transmissions from simian virus to humans. HIV-2 prevalence is low and there is an higher proportion of HIV-2 infected individuals that do not progress to acquired immunodeficiency disease syndrome (AIDS) compared with those infected with HIV-1 [110] . HIV-1 viruses are very divergent and are classified in four groups: M, N, O and P. In particular, the group M is subdivided in nine subtypes and numerous circulating recombinant forms [111] .
The genome of all retroviruses encode the Gag, Pol and Env structural proteins. Among the HIV structural proteins, gp120 and gp41 surface envelope glycoproteins form heterodimers that are organized as trimers on the surface of the viral membrane. HIV-1 entry into target cells is initiated by the interaction of these surface envelope glycoproteins with CD4 and a co-receptor (typically CCR5 or CXCR4) on target cells [112] . The gp120 portion binds the target cell receptors, while gp41 promotes fusion of viral and cellular membranes [113] . Upon binding to the CD4 receptor, gp120 undergoes a conformational change, resulting in the exposure of epitopes that can be bound by co-receptor molecules and in the eventual formation of the transient pre-hairpin intermediate conformation [114] [115] [116] . In the pre-hairpin intermediate, the gp41 molecules reorganize so that the N-terminal peptides form a trimer of helices that expose the fusion peptide to the target cell, while the C-terminal helices remain anchored to the viral membrane [113] . This stage is vulnerable to a number of nAbs and peptides capable of binding either the N-or C-terminal peptides [117, 118] . Upon fusion with the target cell membrane, further gp41 reorganization results in the association of N-and C-terminal peptides to create a six-helix post-fusion bundle [119] . After fusion and delivery of the viral capsid in the cytoplasm, uncoating leads to the release of viral enzymes, proteins, and genomic RNA inside the cell.
Reverse transcription of the viral genomic single-stranded positive RNA is then initiated to yield a double-stranded proviral DNA to be imported in the nucleus and integrated into host chromosome. Active transcription from the integrated proviral DNA occurs in the presence of NF-κB and viral Tat. Splicing of viral mRNA yields early accessory proteins like Tat, Rev, and Nef, which help in transcription, splicing, and modification of the cellular machinery, respectively. Accumulation of Rev protects the viral mRNA from splicing, thus yielding increasingly longer mRNAs able to code for structural and envelope proteins, and finally viral genomic RNAs is ready to be encapsidated [111] . Antiretroviral drug therapy for HIV is highly effective in controlling the infection; however, the eradication of this virus is currently not practicable and the treatment is therefore lifelong and burdened by considerable toxicity and drug resistance. A vaccine is widely viewed as being crucial for the control of the epidemic but several advanced efforts to develop an effective prophylaxis resulted unsuccessful [120, 121] . One of the greatest challenges in developing a vaccine against HIV is to overcome its ability to constantly mutate and escape anti-HIV immune responses [122] . This high mutation rate is a direct result of the presence of the virus' low fidelity RNA polymerase as well as the high levels of recombination it undergoes and the constantly evolving glycan shield of the envelope glycoproteins [123] [124] [125] . At this regard, both cytotoxic T lymphocytes and nAbs have long been reported to select for immune escape variants during the course of HIV-1 infection [126] [127] [128] .
A candidate passive immunotherapy could consist, as previously suggested for SARS-CoV infection, in the administration of a cocktail of broadly neutralizing mAbs, that could minimize the onset of viral escape mutants [129] . Various combinations of human mAbs have been studied over the past several years which have shown additive, synergistic, or antagonistic effects on the neutralization of HIV-1 [130] [131] [132] [133] [134] [135] . Antagonistic effect in HIV-1 neutralization has been previously reported with a pair of anti-gp120 mAbs directed against the V3-loop and the CD4 binding site, respectively [136] . The molecular mechanisms determining the antagonism have not been further studied in details.
The only study describing for the first time at the molecular level a possible mechanism of interference also for HIV was performed using pair combinations of anti-gp41 mAbs [137] . More in details, the authors noted an antagonistic effect when the anti-gp41 neutralizing mAbs 2F5 or 50-69 were combined with the non-neutralizing anti-gp41 mAb 98-6 [137] . In particular mAbs 50-69 and 98-6 recognize different gp41 epitopes located within cluster I (aminoacid residues 579-613) and cluster II (aminoacid residues 644-667), respectively. On the other hand mAb 2F5 recognize a different epitope from mAb 98-6, within the gp41 membrane-proximal external region (MPER), in a portion adjacent to the cluster II region of gp41. Moreover, there is some overlap between cluster II epitopes and the epitope recognized by mAb 2F5 [138] , explaining the inhibition of mAb 2F5 binding by mAb 98-6 [137, 139] .
Thus, in the case of the antagonism between mAbs 2F5 and 98-6 the author hypothesized a mechanism of steric hindrance between the two mAbs as they could bind peptides and peptide complexes representing the pre-fusogenic and fusogenic forms of gp41 [140] . In particular, mAb 98-6 had a higher affinity for the peptide complexes representing the fusogenic form, than did 2F5. Thus, the binding of 98-6, which fails to neutralize the HIV-1 isolate 89.6 (HIV-1 89.6 ), could interfere with the binding of 2F5, leading to the neutralization antagonism. In contrast, mAbs 50-69 and 2F5 recognize distinct epitopes on gp41, and display independent (additive) reactivity against HIV-1 89.6 in combination with most of the other anti-gp41 and anti-gp120 mAbs tested [137] .
To conclude, anti-gp120 and anti-gp41 Abs are induced in HIV-1-infected individuals but are predominantly non-neutralizing, since the functionally important regions of HIV surface proteins are almost completely hidden to the immune system [139] . An intriguing hypothesis is that, together with other HIV escape mechanisms, the effect of the extremely rare anti-gp41 and anti-gp120 nAbs may be also hindered by the overwhelming amount of interfering non-nAbs. To date, the existence of interfering non-nAbs has been clearly evidenced only using anti-gp41 mAbs with different biological features, whereas no data have been generated using anti-gp120 mAbs. The possible role of non-nAbmediated interference in facilitating HIV escape in the course of the natural infection certainly deserves future studies.
Immunoprophylactic or immunotherapeutic approaches with mAbs are still considered a possible supporting tool in the management of infectious diseases. In particular, the availability of broadly neutralizing mAbs directed against viral pathogens, whose actual prophylactic and therapeutic approaches are far from effective, has led to many ongoing clinical trials. However, the evidence reported in this review suggest that candidate mAbs to be possibly used in antiviral passive immunization approaches, or to be elicited by future vaccine strategies, have not only to be highly cross-neutralizing molecules [141, 142] , but also tailored molecules whose activity is not influenced by possible interfering Abs produced in the course of infection. To this end, they must either be directed against highly neutralizing epitopes not subjected to the mechanism of interference, or must feature high affinity for the antigen in order to displace the binding of possible interfering Abs [51, 68] . | Which type of influenza causes epidemics and pandemics? | false | 5,170 | {
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2,675 | Knowledge, Attitudes and Practices (KAP) related to the Pandemic (H1N1) 2009 among Chinese General Population: a Telephone Survey
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3112099/
SHA: fe954b75ed45c02d47090ee70d25c726b24b081c
Authors: Lin, Yilan; Huang, Lijuan; Nie, Shaofa; Liu, Zengyan; Yu, Hongjie; Yan, Weirong; Xu, Yihua
Date: 2011-05-16
DOI: 10.1186/1471-2334-11-128
License: cc-by
Abstract: BACKGROUND: China is at greatest risk of the Pandemic (H1N1) 2009 due to its huge population and high residential density. The unclear comprehension and negative attitudes towards the emerging infectious disease among general population may lead to unnecessary worry and even panic. The objective of this study was to investigate the Chinese public response to H1N1 pandemic and provide baseline data to develop public education campaigns in response to future outbreaks. METHODS: A close-ended questionnaire developed by the Chinese Center for Disease Control and Prevention was applied to assess the knowledge, attitudes and practices (KAP) of pandemic (H1N1) 2009 among 10,669 responders recruited from seven urban and two rural areas of China sampled by using the probability proportional to size (PPS) method. RESULTS: 30.0% respondents were not clear whether food spread H1N1 virusand. 65.7% reported that the pandemic had no impact on their life. The immunization rates of the seasonal flu and H1N1vaccine were 7.5% and 10.8%, respectively. Farmers and those with lower education level were less likely to know the main transmission route (cough or talk face to face). Female and those with college and above education had higher perception of risk and more compliance with preventive behaviors. Relationships between knowledge and risk perception (OR = 1.69; 95%CI 1.54-1.86), and knowledge and practices (OR = 1.57; 95%CI 1.42-1.73) were found among the study subjects. With regard to the behavior of taking up A/H1N1 vaccination, there are several related factors found in the current study population, including the perception of life disturbed (OR = 1.29; 95%CI 1.11-1.50), the safety of A/H1N1 vaccine (OR = 0.07; 95%CI 0.04-0.11), the knowledge of free vaccination policy (OR = 7.20; 95%CI 5.91-8.78), the state's priority vaccination strategy(OR = 1.33; 95%CI 1.08-1.64), and taking up seasonal influenza vaccine behavior (OR = 4.69; 95%CI 3.53-6.23). CONCLUSIONS: This A/H1N1 epidemic has not caused public panic yet, but the knowledge of A/H1N1 in residents is not optimistic. Public education campaign may take the side effects of vaccine and the knowledge about the state's vaccination strategy into account.
Text: At the end of March 2009, an outbreak of novel influenza A (H1N1) (here after called A/H1N1) infection occurred in Mexico, followed by ongoing spread to all over the world in a short period [1] . On June 11 2009, the World Health Organization raised its pandemic alert level to the highest level, phase 6 [2] , meaning that the A/H1N1 flu had spread in more than two continents and reached pandemic proportions. As of June 13, 2010, it had caused over 18,172 deaths in more than 214 countries and overseas territories or communities [3] . Most illness, especially the severe illness and deaths, had occurred among healthy young adults, which was markedly different from the disease pattern seen during epidemics of seasonal influenza [4, 5] .
China is highly susceptible to A/H1N1 because of its huge population and high residential density, besides the high infectiousness of this novel influenza virus. After the first imported case reported on May 11, 2009 , the confirmed cases were reported in various provinces of China [6] . By the late of October 2009, A/H1N1 cases had increased dramatically, with 44,981 cases and 6 deaths confirmed at the end of October 2009. The A/ H1N1 infection rate peaked in November 2009, when approximately 1500 new cases of A/H1N1 were being confirmed each day. By the end of this month, a total of 92,904 cases and 200 deaths had resulted from A/ H1N1-related causes [7] . The Chinese government has taken a series of preventive measures according to WHO guidelines, including the promotion of public knowledge about flu through mass media, patient isolation, quarantine of close contact person, and free vaccinations to population at high risk (e.g. young children, healthcare workers, and people with chronic disease) [8] . However, there were few public reports on the assessment of the effect of these policies and the level of knowledge, attitude and practice (KAP) associating with A/H1N1 among general population.
It is well-known that confused comprehension and negative attitude towards the emerging communicable disease may lead to unnecessary worry and chaos, even excessive panic which would aggravate the disease epidemic [9] . For instance, during SARS epidemic from 2002 to 2004, the misconceptions and the excessive panic of Chinese public to SARS led the public resistant to comply with the suggested preventive measures such as avoiding public transportation, going to hospital when they were sick, which contributed to the rapid spread of SARS and resulted in a more serious epidemic situation, making China one of the worst affected countries with over 5327 cases and 439 deaths [10, 11] . In addition, the panic of infectious disease outbreak could cause huge economic loss, for example the economic loss of SARS has been estimated at $30-$100 billion in US, though less than 10,000 persons were infected [12] . SARS experience has demonstrated the importance of monitoring the public perception in disease epidemic control, which may affect the compliance of community to the precautionary strategies. Understanding related factors affecting people to undertake precautionary behavior may also help decision-makers take appropriate measures to promote individual or community health. Therefore, it is important to monitor and analyze the public response to the emerging disease.
To investigate community responses to A/H1N1 in China, we conducted this telephone survey to describe the knowledge, attitudes and practices of A/H1N1 among general population in China and put forward policy recommendations to government in case of future similar conditions.
This study was performed in seven urban regions (Beijing, Shanghai, Wuhan, Jingzhou, Xi'an, Zhengzhou, Shenzhen cities) and two rural areas (Jingzhou and Zhengzhou counties) of China with over one million people in each region. Regarding the urban sites, Beijing as the capital of China locates in the northeast; Shanghai is a municipality in the east of China; Wuhan (the provincial capital of Hubei) and Zhengzhou (the provincial capital of Henan province) are both in the centre of China; Xi'an in the northwest of China is the provincial capital of Shanxi province; and Shenzhen of the Guangdong province is in the southeast of China. As for the rural sites, Jingzhou county and Zhengzhou county, from Hubei and Henan provinces, respectively, both locate in the centre of China.
This current study was carried out in three phases during the pandemic peak season of A/H1N1. The first phase was from 30 November 2009 to 27 December 2009, the second from 4 January 2010 to 24 January 2010, and the third from 24 February to 25 March in 2010.
A two-stage proportional probability to size (PPS) sampling method was used in each phase. In stage І, about 30% of administrative regions in each study site were selected as primary sample units (PSUs) for cluster sampling. In stage II, telephone numbers were sampled randomly, of which the first four digitals were obtained from each PSU's post office as initial number and the other three or four digitals were obtained from random number generated by Excel 2003. Then each family was chosen as per unit (excluding school, hotel public or cell phone etc.) and at least 400 families in each site at each phase were selected finally. If the family was selected repeatedly or refused to answer the questionnaire, we added one to the last digit of phone number and dial again. If the line was busy or of no response, we would dial three times and then give up this phone number if there was still no respondent.
Anonymous telephone interviews were conducted from 6:30 pm to 10:00 pm so as to avoid over-presenting the non-work population by well-trained interviewers with Bachelor degree of Epidemiology. The Questionnaire to Survey the Level of Knowledge, Attitude and Practice in Different Stages of A/H1N1 Pandemic by Telephone was designed by the Chinese Centre for Disease Control and Prevention (China CDC, Beijing). The majority of the questions were closed-ended and variables in the questionnaire were categorical, except age. The inclusion criteria of subjects were: age≥18 and proper communication skills. There were seven questions related to the knowledge of A/H1N1, four referred to the attitude, and five concerning about the practice in this questionnaire (See additional file 1: The Questionnaire to Survey the Level of Knowledge, Attitude and Practice in Different Stages of H1N1 Pandemic by Telephone in China).
This study was approved by the institutional review board of the Tongji Medical College of Huazhong University of Science and Technology. All respondents were informed consent. We respected their wishes whether to accept our survey and promised to protect their secrets.
All data were entered into computer using Epidata V.3.1 and were analyzed in SPSS statistical software V.12. Chi-square test was applied to compare the immunization rates of the seasonal flu and A/H1N1 vaccine. The associations between the socio-demographic factors and the KAP regarding A/H1N1 were firstly investigated by using univariate odds ratios (OR) and then stepwise logistic regression modeling applied. Adjusting for such background variables including gender, age, level of education, occupation, region, and survey wave, stepwise multivariate logistic regression models were applied to investigate the impact factors associated with the risk perception of A/H1N1, A/H1N1 vaccination uptake and the compliance with suggested preventive measures (avoid crowd places/wash hand frequently/keep distance from people with influenza-like symptoms). For the purposes of analysis, the factor knowledge about the main modes of transmission was divided into two groups according to whether the respondents knew both cough and talk faceto-face can spread A/H1N1. Odds ratios and respective 95% confidence intervals (CI) were obtained from the logistic regression analysis. P values lower than 0.05 were judged to be statistically significant.
A total of 88541 telephone numbers were dialed. Except 65323 invalid calls (including vacant numbers, fax numbers, busy tone numbers and non-qualified respondents whose age <18 and whose phones were from school, hotel or other public places), 23218 eligible respondents were identified. Among these respondents, 12360 completed the interview. Therefore, the response rate was 46.8%. Excluding missing, and logical erroneous data, 10669 questionnaires in total were eligible for analysis. The baseline characteristics of the respondents were presented in Table1. The mean age of all respondents was 41.47 years (over range: 18-90 year) . Of all respondents, 54.4% were female, and 42.4% had received college or above education (Table 1) .
The overall KAP related to A/H1N1 was reported in Table 2 . As to knowledge, 75.6% of all respondents knew that influenza could be transmitted by coughing and sneezing, and 61.9% thought that talking face-to-face was the transmission route, whereas 30.0% believed the transmission could be through food. Less than one third of respondents knew that virus could be transmitted by handshaking and indirect hand contact (26.8% and 22.3%, respectively). Multiple logistic regression analysis showed that those with middle school (OR = 1.71; 95%CI 1.48-1.98), or having an education level of college and above (OR = 2.16; 95%CI 1.83-2.54) were more likely to know the transmission routes comparing with other people. Comparing with students, teachers (OR = 1.46; 95%CI 1.09-1.96) were more likely to answer the above questions Table 3 and Table 4 ). Regarding the A/H1N1vaccination, 69.9% respondents believed that the occurrence rate of adverse reactions caused by A/H1N1 vaccination was fairly low and they were not afraid of taking up vaccination. Most residents (96.1%) thought that the state's vaccination strategy was reasonable.
About half of the respondents (42.9%) had avoided going to crowded places during the past two weeks of our survey. In case people nearby held influenza-like symptoms such as fever or cough, 56.9% increased the frequency of hand-washing and 57.4% would stay away from them. Multiple logistic regression analysis indicated compliance with the preventive practices were more likely to be taken by those who were females (OR = 1. Table 3 and Table 4 ). The immunization rates of the seasonal flu and A/ H1N1 in respondents were 7.5% and 10.8% respectively. The multivariate stepwise models further showed that except the health care workers (OR = 1.52; 95%CI 1.09-2.11), residents in other occupations (OR = 0.06-0.67) were less likely to take up the A/H1N1 vaccination comparing with students (in Table 3 ). Adjusting for the background covariates the knowledge about the free vaccination policy (OR = 7.20; 95%CI 5.91-8.78) and the state's initial vaccination strategy(OR = 1.33; 95%CI 1.08-1.64), perception of daily life disturbed (OR = 1.29; 95% CI 1.11-1.50), practice of injecting the seasonal influenza vaccine (OR = 4.69; 95%CI 3.53-6.23) were significantly associated with behavior of taking up the A/H1N1 vaccination positively (in Table 5 ), and the adverse reaction of A/H1N1 vaccine negatively influenced people's practice (OR = 0.07; 95%CI 0.04-0.11).
Novel A/H1N1 has caused pandemic in this century. It is important to encourage the public to adopt precautionary behaviors, which is based on the correct knowledge of the epidemic and appropriate response among residents. Many studies have examined the various levels of KAP about infectious disease outbreaks, such as SARS, avian influenza [13] [14] [15] . Some studies have been reported specifically on community responses to A/H1N1 in Australia and Europe [16, 17] . But through literature search, we haven't found any public reports on KAP regarding A/H1N1 among Chinese population until now. Therefore, we conducted this large population-based survey (10669 respondents) to investigate community responses to A/H1N1 and to provide baseline data to government for preventive measures in case of future outbreaks.
Unless people have basic knowledge about the modes of transmission, they respond appropriately during an outbreak [16] . It has been proved that influenza is transmitted through person to person via respiratory secretions [18] . Most residents in our survey recognized that OR m : odds ratio obtained from stepwise multivariate logistics regression analysis using univariately significant variables as candidate variables and adjusting for region; NU: not significant in the univariate analysis; *: P < 0.05; †: P < 0.01; ‡: P < 0.0001.
the risk of getting infected would increase when an infected person coughed or sneezed in close distance. This may be due to the previous experience of SARS and avian flu. Multivariate analysis results showed that workers and farmers with lower education level were less likely to have this knowledge, which indicated that the contents and forms of propaganda should be more understandable and acceptable. A large proportion of residents in our survey overlooked the indirect hand contact and hand-shaking transmission route and about one third of public misconceived that A/H1N1 was food borne, which was associated with the previous knowledge of avian flu and the new A/H1N1 flu in the general population. The confusion with avian flu might mislead some residents to believe that the A/H1N1 virus is fatal and cause public panic [19] . Therefore, it is important for the government and health authorities to provide continuously updated information of the emerging disease through televisions, newspapers, radios, and Internet. There are regional differences in the perception of A/H1N1. For example, the public in Hong Kong did not perceive a high likelihood of having a local A/H1N1 outbreak [19] , but Malaysians were particularly anxious about the pandemic [20] . The current study shows that emotional distress was relatively mild in China as few residents worried about being infected (25.1%). This phenomenon may also be related to the previous experience of the SARS epidemic, as well as the open epidemic information. A survey in Korean university showed that women perceived higher illness severity and personal susceptibility to A/ H1N1 infection, which had been reconfirmed in our study [21] . Logistic regression analysis results suggested that women with higher educational level had higher perception of risk. As time went by, the knowledge about the main transmission route increased, but the risk perception of being infected in residents decreased, suggesting the positive effect of government policy regarding A/H1N1 infection prevention, as well as the promotion of the media.
The previous study presented various results of influencing factors on the the compliance with the preventive practices. The study in Saudi showed that older men with better education were more likely to take preventive practices [9] ; female students in Korean washed hands more frequently during the peak pandemic period of A/ H1N1 [21] ; in another pandemic study in USA, younger people was found to have greater uptake of recommended behaviors but not for gender [16] . We found female with higher education took more precautionary behaviors, but office staffs and farmers took less comparing with students. While such differences could result from study population demographics, profound differences may also exist in the knowledge of A/H1N1 and the perceptions of recommended behaviors in those countries. Adjusting for the background factors, the multivariate logistic regression showed the possible relationship between knowledge and risk perception, knowledge and practices (odd ratios were 1.57 and 2.09, respectively), which indicated that good knowledge is important to enable individuals to have better attitudes and practices in influenza risk reduction. Similar findings were observed in other studies performed during A/ H1N1 pandemic in Singapore [22] and during SARS pandemic in Hong Kong [13] . Therefore, it is important to focus on inculcating the correct knowledge to individuals as it will influence both attitudes and practices. Injecting vaccination is an effective measure to prevent infectious disease [23] . In China, the seasonal influenza vaccination is not included in the national immunization program and must be purchased by recipients. Those who are above 60 years old, the pupil and children in kindergarten, and people with chronic diseases are recommended to get inoculation. Data provided by China CDC in 2009 showed that the immunization rate of the seasonal flu in Chinese population was below 2% [24] , which was much lower than 7.5% in our study (P < 0.0001). This phenomenon is partly due to the state's prior vaccination strategy for population at high risk such as students, teachers, healthcare workers and people with chronic disease, as well as the confusion between seasonal flu vaccine and A/H1N1 vaccine in residents. People who couldn't access the A/H1N1 vaccine may take up seasonal flu vaccine as preventive behaviors. The A/ H1N1 vaccine was not available in China until the middle of September 2009. All populations at high risk above three years old were invited for vaccination free of charge [25] . A survey among 868 European travelers showed 14.2% participants were vaccinated against pandemic influenza A/H1N1 [26] , higher than 10.8% in our study (P < 0.01). Our study also showed students and health care workers were more likely to take up, which may be due to the prior vaccination strategy. Multivariate stepwise logistic regression analysis, which allowed us to adjust for background factors, further showed the perceived risk of infection and the knowledge about the main modes of transmission related to A/H1N1 vaccination were insignificantly, similar results seen in Lau's study [8] . Therefore, the vaccination rate of A/H1N1 is not expected to increase even if the virus becomes more prevalent or the knowledge of its transmission mode improved. Additionally, the behavior of taking up A/H1N1 vaccine was associated with perceptions of vaccine's safety and influence on daily life by A/H1N1 as well as the knowledge about the free vaccination policy and the state's initial vaccination strategy. This suggests that improving the safety of vaccine, the acceptability of side effect and the knowledge about the state's strategy related to A/H1N1 vaccination in residents may be helpful to promote A/H1N1 vaccination in the general population. The cross-sectional telephone survey adopted in the study has some limitations. We were unable to interview the people who did not have phones and the depth of the questionnaire was largely limited because questions and pre-existing answers could not be too long and complex. In addition, the telephone response rate was 46.8%, which means more than half of the interviewees rejected or didn't finish the survey. It was impossible to compare the difference between respondents and nonrespondents due to the lack of their basic information.
This A/H1N1 epidemic has not caused public panic yet, but the knowledge of A/H1N1 in residents is not optimistic as most of them confused the transmission route of A/H1N1. There are many factors influencing the KAP related to A/H1N1. Female with higher educational level had higher perceived risk of infection and took more precautionary behaviors. Public education campaign may take the side effects of vaccine and the knowledge about the state's vaccination strategy into account. The data collected in this survey could be used as baseline data to monitor public perceives and behaviors in the event of future outbreak of infectious disease in China.
Additional file 1: Questionnaire. The Questionnaire to Survey the Level of Knowledge, Attitude and Practice in Different Stages of H1N1 Pandemic by Telephone in China. | What was the estimated economic impact in the U.S. from the 2009 SARS pandemic? | false | 528 | {
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1,571 | Community-acquired pneumonia in children — a changing spectrum of disease
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5608782/
SHA: eecb946b106a94f26a79a964f0160e8e16f79f42
Authors: le Roux, David M.; Zar, Heather J.
Date: 2017-09-21
DOI: 10.1007/s00247-017-3827-8
License: cc-by
Abstract: Pneumonia remains the leading cause of death in children outside the neonatal period, despite advances in prevention and management. Over the last 20 years, there has been a substantial decrease in the incidence of childhood pneumonia and pneumonia-associated mortality. New conjugate vaccines against Haemophilus influenzae type b and Streptococcus pneumoniae have contributed to decreases in radiologic, clinical and complicated pneumonia cases and have reduced hospitalization and mortality. The importance of co-infections with multiple pathogens and the predominance of viral-associated disease are emerging. Better access to effective preventative and management strategies is needed in low- and middle-income countries, while new strategies are needed to address the residual burden of disease once these have been implemented.
Text: Pneumonia has been the leading cause of death in children younger than 5 years for decades. Although there have been substantial decreases in overall child mortality and in pneumonia-specific mortality, pneumonia remains the major single cause of death in children outside the neonatal period, causing approximately 900,000 of the estimated 6.3 million child deaths in 2013 [1] . Substantial advances have occurred in the understanding of risk factors and etiology of pneumonia, in development of standardized case definitions, and in prevention with the production of improved vaccines and in treatment. Such advances have led to changes in the epidemiology, etiology and mortality from childhood pneumonia. However in many areas access to these interventions remains sub-optimal, with large inequities between and within countries and regions. In this paper we review the impact of recent preventative and management advances in pneumonia epidemiology, etiology, radiologic presentation and outcome in children.
The overall burden of childhood pneumonia has been reduced substantially over the last decade, despite an increase in the global childhood population from 605 million in 2000 to 664 million in 2015 [2] . Recent data suggest that there has been a 25% decrease in the incidence of pneumonia, from 0.29 episodes per child year in low-and middle-income countries in 2000, to 0.22 episodes per child year in 2010 [3] . This is substantiated by a 58% decrease in pneumonia-associated disability-adjusted life years between 1990 and 2013, from 186 million to 78 million as estimated in the Global Burden of Disease study [1] . Pneumonia deaths decreased from 1.8 million in 2000 to 900,000 in 2013 [1] . These data do not reflect the full impact of increasingly widespread use of pneumococcal conjugate vaccine in low-and middle-income countries because the incidence of pneumonia and number of deaths are likely to decrease still further as a result of this widespread intervention [4] .
Notwithstanding this progress, there remains a disproportionate burden of disease in low-and middle-income countries, where more than 90% of pneumonia cases and deaths occur. The incidence in high-income countries is estimated at 0.015 episodes per child year, compared to 0.22 episodes per child year in low-and middle-income countries [3] . On average, 1 in 66 children in high-income countries is affected by pneumonia per year, compared to 1 in 5 children in low-and middle-income countries. Even within low-and middleincome countries there are regional inequities and challenges with access to health care services: up to 81% of severe pneumonia deaths occur outside a hospital [5] . In addition to a higher incidence of pneumonia, the case fatality rate is estimated to be almost 10-fold higher in low-and middle-income countries as compared to high-income countries [3, 5] .
Childhood pneumonia can also lead to significant morbidity and chronic disease. Early life pneumonia can impair longterm lung health by decreasing lung function [6] . Severe or recurrent pneumonia can have a worse effect on lung function; increasing evidence suggests that chronic obstructive pulmonary disease might be related to early childhood pneumonia [7, 8] . A meta-analysis of the risk of long-term outcomes after childhood pneumonia categorized chronic respiratory sequelae into major (restrictive lung disease, obstructive lung disease, bronchiectasis) and minor (chronic bronchitis, asthma, abnormal pulmonary function) groups [9] . The risk of developing at least one of the major sequelae was estimated as 6% after an ambulatory pneumonia event and 14% after an episode of hospitalized pneumonia. Because respiratory diseases affect almost 1 billion people globally and are a major cause of mortality and morbidity [10] , childhood pneumonia might contribute to substantial morbidity across the life course.
Chest radiologic changes have been considered the gold standard for defining a pneumonia event [11] because clinical findings can be subjective and clinical definitions of pneumonia can be nonspecific. In 2005, to aid in defining outcomes of pneumococcal vaccine studies, the World Health Organization's (WHO) standardized chest radiograph description defined a group of children who were considered most likely to have pneumococcal pneumonia [12] . The term "end-point consolidation" was described as a dense or fluffy opacity that occupies a portion or whole of a lobe, or the entire lung. "Other infiltrate" included linear and patchy densities, peribronchial thickening, minor patchy infiltrates that are not of sufficient magnitude to constitute primary end-point consolidation, and small areas of atelectasis that in children can be difficult to distinguish from consolidation. "Primary end-point pneumonia" included either end-point consolidation or a pleural effusion associated with a pulmonary parenchymal infiltrate (including "other" infiltrate).
Widespread use of pneumococcal conjugate vaccination and Haemophilus influenzae type B conjugate vaccination has decreased the incidence of radiologic pneumonia. In a review of four randomized controlled trials and two case-control studies of Haemophilus influenzae type B conjugate vaccination in high-burden communities, the vaccination was associated with an 18% decrease in radiologic pneumonia [13] . Introduction of pneumococcal conjugate vaccination was associated with a 26% decrease in radiologic pneumonia in California between 1995 and 1998 [14] . In vaccine efficacy trials in low-and middle-income countries, pneumococcal conjugate vaccination reduced radiologic pneumonia by 37% in the Gambia [15] , 25% in South Africa [16] and 26% in the Philippines [17] .
The WHO radiologic case definition was not intended to distinguish bacterial from viral etiology but rather to define a sub-set of pneumonia cases in which pneumococcal infection was considered more likely and to provide a set of standardized definitions through which researchers could achieve broad agreement in reporting chest radiographs. However, despite widespread field utilization, there are concerns regarding inter-observer repeatability. There has been good consensus for the description of lobar consolidation but significant disagreement on the description of patchy and perihilar infiltrates [18, 19] . In addition, many children with clinically severe lung disease do not have primary end-point pneumonia: in one pre-pneumococcal conjugate vaccination study, only 34% of children hospitalized with pneumonia had primary end-point pneumonia [20] . A revised case definition of "presumed bacterial pneumonia" has been introduced, and this definition includes pneumonia cases with WHO-defined alveolar consolidation, as well as those with other abnormal chest radiograph infiltrates and a serum C-reactive protein of at least 40 mg/L [21, 22] . This definition has been shown to have greater sensitivity than the original WHO radiologic definition of primary end-point pneumonia for detecting the burden of pneumonia prevented by pneumococcal conjugate vaccination [23] . Using the revised definition, the 10-valent pneumococcal conjugate vaccine (pneumococcal conjugate vaccination-10), had a vaccine efficacy of 22% in preventing presumed bacterial pneumonia in young children in South America [22] , and pneumococcal conjugate vaccination-13 had a vaccine efficacy of 39% in preventing presumed bacterial pneumonia in children older than 16 weeks who were not infected with human immunodeficiency virus (HIV) in South Africa [21] . Thus there is convincing evidence that pneumococcal conjugate vaccination decreases the incidence of radiologic pneumonia; however there is no evidence to suggest that pneumococcal conjugate vaccination modifies the radiologic appearance of pneumococcal pneumonia.
Empyema is a rare complication of pneumonia. An increased incidence of empyema in children was noted in some high-income countries following pneumococcal conjugate vaccination-7 introduction, and this was attributed to pneumococcal serotypes not included in pneumococcal conjugate vaccination-7, especially 3 and 19A [24] . In the United States, evidence from a national hospital database suggests that the incidence of empyema increased 1.9-fold between 1996 and 2008 [25] . In Australia, the incidence rate ratio increased by 1.4 times when comparing the pre-pneumococcal conjugate vaccination-7 period (1998 to 2004) to the post-pneumococcal conjugate vaccination-7 period (2005 to 2010) [26] . In Scotland, incidence of empyema in children rose from 6.5 per million between 1981 and 1998, to 66 per million in 2005 [27] . These trends have been reversed since the introduction of pneumococcal conjugate vaccination-13. Data from the United States suggest that empyema decreased by 50% in children younger than 5 years [28] ; similarly, data from the United Kingdom and Scotland showed substantial reduction in pediatric empyema following pneumococcal conjugate vaccination-13 introduction [29, 30] .
Several national guidelines from high-income countries, as well as the WHO recommendations for low-and middleincome countries, recommend that chest radiography should not be routinely performed in children with ambulatory pneumonia [31] [32] [33] . Indications for chest radiography include hospitalization, severe hypoxemia or respiratory distress, failed initial antibiotic therapy, or suspicion for other diseases (tuberculosis, inhaled foreign body) or complications. However, point-of-care lung ultrasound is emerging as a promising modality for diagnosing childhood pneumonia [34] .
In addition to the effect on radiologic pneumonia, pneumococcal conjugate vaccination reduces the risk of hospitalization from viral-associated pneumonia, probably by reducing bacterial-viral co-infections resulting in severe disease and hospitalization [35] . An analysis of ecological and observational studies of pneumonia incidence in different age groups soon after introduction of pneumococcal conjugate vaccination-7 in Canada, Italy, Australia, Poland and the United States showed decreases in all-cause pneumonia hospitalizations ranging from 15% to 65% [36] . In the United States after pneumococcal conjugate vaccination-13 replaced pneumococcal conjugate vaccination-7, there was a further 17% decrease in hospitalizations for pneumonia among children eligible for the vaccination, and a further 12% decrease among unvaccinated adults [28] .
A systematic review of etiology studies prior to availability of new conjugate vaccines confirmed S. pneumoniae and H. influenzae type B as the most important bacterial causes of pneumonia, with Staphylococcus aureus and Klebsiella pneumoniae associated with some severe cases. Respiratory syncytial virus was the leading viral cause, identified in 15-40% of pneumonia cases, followed by influenza A and B, parainfluenza, human metapneumovirus and adenovirus [37] .
More recent meta-analyses of etiology data suggest a changing pathogen profile, with increasing recognition that clinical pneumonia is caused by the sequential or concurrent interaction of more than one organism. Severe disease in particular is often caused by multiple pathogens. With high coverage of pneumococcal conjugate vaccination and Haemophilus influenzae type B conjugate vaccination, viral pathogens increasingly predominate [38] . In recent case-control studies, at least one virus was detected in 87% of clinical pneumonia cases in South Africa [39] , while viruses were detected in 81% of radiologic pneumonia cases in Sweden [40] . In a large multi-center study in the United States, viral pathogens were detected in 73% of children hospitalized with radiologic pneumonia, while bacteria were detected in only 15% of cases [41] . A meta-analysis of 23 case-control studies of viral etiology in radiologically confirmed pneumonia in children, completed up to 2014, reported good evidence of causal attribution for respiratory syncytial virus, influenza, metapneumovirus and parainfluenza virus [42] . However there was no consistent evidence that many other commonly described viruses, including rhinovirus, adenovirus, bocavirus and coronavirus, were more commonly isolated from cases than from controls. Further attribution of bacterial etiology is difficult because it is often not possible to distinguish colonizing from pathogenic bacteria when they are isolated from nasal specimens [43] .
Another etiology is pertussis. In the last decade there has also been a resurgence in pertussis cases, especially in highincome countries [44] . Because pertussis immunity after acellular pertussis vaccination is less long-lasting than immunity after wild-type infection or whole-cell vaccination, many women of child-bearing age have waning pertussis antibody levels. Their infants might therefore be born with low transplacental anti-pertussis immunoglobulin G levels, making them susceptible to pertussis infection before completion of the primary vaccination series [45] . In 2014, more than 40,000 pertussis cases were reported to the Centers for Disease Control and Prevention in the United States; in some states, population-based incidence rates are higher than at any time in the last 70 years [44] . In contrast, most low-and middleincome countries use whole-cell pertussis vaccines and the numbers of pertussis cases in those countries were stable or decreasing until 2015 [46] . However recent evidence from South Africa (where the acellular vaccine is used) shows an appreciable incidence of pertussis among infants presenting with acute pneumonia: 2% of clinical pneumonia cases among infants enrolled in a birth cohort were caused by pertussis [39] , and 3.7% of infants and young children presenting to a tertiary academic hospital had evidence of pertussis infection [47] .
Similarly, childhood tuberculosis is a major cause of morbidity and mortality in many low-and middle-income countries, and Mycobacterium tuberculosis has increasingly been recognized as a pathogen in acute pneumonia in children living in high tuberculosis-prevalence settings. Postmortem studies of children dying from acute respiratory illness have commonly reported M. tuberculosis [48, 49] . A recent systematic review of tuberculosis as a comorbidity of childhood pneumonia reported culture-confirmed disease in about 8% of cases [50] . Because intrathoracic tuberculosis disease is only culture-confirmed in a minority of cases, the true burden could be even higher; tuberculosis could therefore be an important contributor to childhood pneumonia incidence and mortality in high-prevalence areas.
Childhood pneumonia and clinically severe disease result from a complex interaction of host and environmental risk factors [37] . Because of the effectiveness of pneumococcal conjugate vaccination and Haemophilus influenzae type B conjugate vaccination for prevention of radiologic and clinical pneumonia, incomplete or inadequate vaccination must be considered as a major preventable risk factor for childhood pneumonia. Other risk factors include low birth weight, which is associated with 3.2 times increased odds of severe pneumonia in low-and middle-income countries, and 1.8 times increased odds in high-income countries [51] . Similarly, lack of exclusive breastfeeding for the first 4 months of life increases odds of severe pneumonia by 2.7 times in low-and middle-income countries and 1.3 times in highincome countries. Markers of undernutrition are strong risk factors for pneumonia in low-and middle-income countries only, with highly significant odds ratios for underweight for age (4.5), stunting (2.6) and wasting (2.8) . Household crowding has uniform risk, with odds ratios between 1.9 and 2.3 in both low-and middle-income countries and high-income countries. Indoor air pollution from use of solid or biomass fuels increases odds of pneumonia by 1.6 times; lack of measles vaccination by the end of the first year of age increases odds of pneumonia by 1.8 times [51] . It is estimated that the prevalence of these critical risk factors in low-and middle-income countries decreased by 25% between 2000 and 2010, contributing to reductions in pneumonia incidence and mortality in low-and middle-income countries, even in countries where conjugate vaccines have not been available [3] .
The single strongest risk factor for pneumonia is HIV infection, which is especially prevalent in children in sub-Saharan Africa. HIV-infected children have 6 times increased odds of developing severe pneumonia or of death compared to HIV-uninfected children [52] . Since the effective prevention of mother-to-child transmission of HIV, there is a growing population of HIV-exposed children who are uninfected; their excess risk of pneumonia, compared to HIV unexposed children, has been described as 1.3-to 3.4-fold higher [53] [54] [55] [56] [57] .
The pneumococcal conjugate vaccination and Haemophilus influenzae type B conjugate vaccination have been effective tools to decrease pneumonia incidence, severity and mortality [58, 59] . However, equitable coverage and access to vaccines remains sub-optimal. By the end of 2015, Haemophilus influenzae type B conjugate vaccination had been introduced in 73 countries, with global coverage estimated at 68%. However, inequities are still apparent among regions: in the Americas coverage is estimated at 90%, while in the Western Pacific it is only 25%. By 2015, pneumococcal conjugate vaccination had been introduced into 54 countries, with global coverage of 35% for three doses of pneumococcal conjugate vaccination for infant populations [60] . To address this issue, the WHO's Global Vaccine Access Plan initiative was launched to make life-saving vaccines more equitably available. In addition to securing guarantees for financing of vaccines, the program objectives include building political will in low-and middle-income countries to commit to immunization as a priority, social marketing to individuals and communities, strengthening health systems and promoting relevant local research and development innovations [61] .
Maternal vaccination to prevent disease in the youngest infants has been shown to be effective for tetanus, influenza and pertussis [62] . Influenza vaccination during pregnancy is safe, provides reasonable maternal protection against influenza, and also protects infants for a limited period from confirmed influenza infection (vaccine efficacy 63% in Bangladesh [63] and 50.4% in South Africa [64] ). However as antibody levels drop sharply after birth, infant protection does not persist much beyond 8 weeks [65] . Recently respiratory syncytial virus vaccination in pregnancy has been shown to be safe and immunogenic, and a phase-3 clinical trial of efficacy at preventing respiratory syncytial virus disease in infants is under way [66] . Within a decade, respiratory syncytial virus in infancy might be vaccine-preventable, with further decreases in pneumonia incidence, morbidity and mortality [67] .
Improved access to health care, better nutrition and improved living conditions might contribute to further decreases in childhood pneumonia burden. The WHO Integrated Global Action Plan for diarrhea and pneumonia highlights many opportunities to protect, prevent and treat children [68] . Breastfeeding rates can be improved by programs that combine education and counseling interventions in homes, communities and health facilities, and by promotion of baby-friendly hospitals [69] . Improved home ventilation, cleaner cooking fuels and reduction in exposure to cigarette smoke are essential interventions to reduce the incidence and severity of pneumonia [70, 71] . Prevention of pediatric HIV is possible by providing interventions to prevent mother-to-child transmission [72] . Early infant HIV testing and early initiation of antiretroviral therapy and cotrimoxazole prophylaxis can substantially reduce the incidence of community-acquired pneumonia among HIV-infected children [73] . Community-based interventions reduce pneumonia mortality and have the indirect effect of improved-careseeking behavior [58] . If these cost-effective interventions were scaled up, it is estimated that 67% of pneumonia deaths in lowand middle-income countries could be prevented by 2025 [58] .
Case management of pneumonia is a strategy by which severity of disease is classified as severe or non-severe. All children receive early, appropriate oral antibiotics, and severe cases are referred for parenteral antibiotics. When implemented in highburden areas before the availability of conjugate vaccines, case management as part of Integrated Management of Childhood Illness was associated with a 27% decrease in overall child mortality, and 42% decrease in pneumonia-specific mortality [74] . However the predominance of viral causes of pneumonia and low case fatality have prompted concern about overuse of antibiotics. Several randomized controlled trials comparing oral antibiotics to placebo for non-severe pneumonia have been performed [75] [76] [77] and others are ongoing [78] . In two studies, performed in Denmark and in India, outcomes of antibiotic and placebo treatments were equivalent [76, 77] . In the third study, in Pakistan, there was a non-significant 24% vs. 20% rate of failure in the placebo group, which was deemed to be non-equivalent to the antibiotic group [75] . Furthermore, because WHO-classified non-severe pneumonia and bronchiolitis might be considered within a spectrum of lower respiratory disease, many children with clinical pneumonia could actually have viral bronchiolitis, for which antibiotics are not beneficial [79] . This has been reflected in British [33] and Spanish [31] national pneumonia guidelines, which do not recommend routine antibiotic treatment for children younger than 2 years with evidence of pneumococcal conjugate vaccination who present with non-severe pneumonia. The United States' national guidelines recommend withholding antibiotics in children up to age 5 years presenting with non-severe pneumonia [32] . However, given the high mortality from pneumonia in low-and middle-income countries, the lack of easy access to care, and the high prevalence of risk factors for severe disease, revised World Health Organization pneumonia guidelines still recommend antibiotic treatment for all children who meet the WHO pneumonia case definitions [80] .
Use of supplemental oxygen is life-saving, but this is not universally available in low-and middle-income countries; it is estimated that use of supplemental oxygen systems could reduce mortality of children with hypoxic pneumonia by 20% [81] . Identifying systems capacity to increase availability of oxygen in health facilities, and identifying barriers to further implementation are among the top 15 priorities for future childhood pneumonia research [82] . However, up to 81% of pneumonia deaths in 2010 occurred outside health facilities [5] , so there are major challenges with access to health services and health-seeking behavior of vulnerable populations. Identifying and changing the barriers to accessing health care is an important area with the potential to impact the survival and health of the most vulnerable children [82] .
Much progress has been made in decreasing deaths caused by childhood pneumonia. Improved socioeconomic status and vaccinations, primarily the conjugate vaccines (against Haemophilus influenzae and pneumococcus), have led to substantial reductions in the incidence and severity of childhood pneumonia. Stronger strategies to prevent and manage HIV have reduced HIV-associated pneumonia deaths. However, despite the substantial changes in incidence, etiology and radiology globally, there remain inequities in access to care and availability of effective interventions, especially in low-and middle-income countries. Effective interventions need to be more widely available and new interventions developed for the residual burden of childhood pneumonia. | What is the reduction in the number of childhood pneumonia cases? | false | 511 | {
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2,683 | Estimating the number of infections and the impact of non-
pharmaceutical interventions on COVID-19 in 11 European countries
30 March 2020 Imperial College COVID-19 Response Team
Seth Flaxmani Swapnil Mishra*, Axel Gandy*, H JulietteT Unwin, Helen Coupland, Thomas A Mellan, Harrison
Zhu, Tresnia Berah, Jeffrey W Eaton, Pablo N P Guzman, Nora Schmit, Lucia Cilloni, Kylie E C Ainslie, Marc
Baguelin, Isobel Blake, Adhiratha Boonyasiri, Olivia Boyd, Lorenzo Cattarino, Constanze Ciavarella, Laura Cooper,
Zulma Cucunuba’, Gina Cuomo—Dannenburg, Amy Dighe, Bimandra Djaafara, Ilaria Dorigatti, Sabine van Elsland,
Rich FitzJohn, Han Fu, Katy Gaythorpe, Lily Geidelberg, Nicholas Grassly, Wi|| Green, Timothy Hallett, Arran
Hamlet, Wes Hinsley, Ben Jeffrey, David Jorgensen, Edward Knock, Daniel Laydon, Gemma Nedjati—Gilani, Pierre
Nouvellet, Kris Parag, Igor Siveroni, Hayley Thompson, Robert Verity, Erik Volz, Caroline Walters, Haowei Wang,
Yuanrong Wang, Oliver Watson, Peter Winskill, Xiaoyue Xi, Charles Whittaker, Patrick GT Walker, Azra Ghani,
Christl A. Donnelly, Steven Riley, Lucy C Okell, Michaela A C Vollmer, NeilM.Ferguson1and Samir Bhatt*1
Department of Infectious Disease Epidemiology, Imperial College London
Department of Mathematics, Imperial College London
WHO Collaborating Centre for Infectious Disease Modelling
MRC Centre for Global Infectious Disease Analysis
Abdul LatifJameeI Institute for Disease and Emergency Analytics, Imperial College London
Department of Statistics, University of Oxford
*Contributed equally 1Correspondence: nei|[email protected], [email protected]
Summary
Following the emergence of a novel coronavirus (SARS-CoV-Z) and its spread outside of China, Europe
is now experiencing large epidemics. In response, many European countries have implemented
unprecedented non-pharmaceutical interventions including case isolation, the closure of schools and
universities, banning of mass gatherings and/or public events, and most recently, widescale social
distancing including local and national Iockdowns.
In this report, we use a semi-mechanistic Bayesian hierarchical model to attempt to infer the impact
of these interventions across 11 European countries. Our methods assume that changes in the
reproductive number— a measure of transmission - are an immediate response to these interventions
being implemented rather than broader gradual changes in behaviour. Our model estimates these
changes by calculating backwards from the deaths observed over time to estimate transmission that
occurred several weeks prior, allowing for the time lag between infection and death.
One of the key assumptions of the model is that each intervention has the same effect on the
reproduction number across countries and over time. This allows us to leverage a greater amount of
data across Europe to estimate these effects. It also means that our results are driven strongly by the
data from countries with more advanced epidemics, and earlier interventions, such as Italy and Spain.
We find that the slowing growth in daily reported deaths in Italy is consistent with a significant impact
of interventions implemented several weeks earlier. In Italy, we estimate that the effective
reproduction number, Rt, dropped to close to 1 around the time of Iockdown (11th March), although
with a high level of uncertainty.
Overall, we estimate that countries have managed to reduce their reproduction number. Our
estimates have wide credible intervals and contain 1 for countries that have implemented a||
interventions considered in our analysis. This means that the reproduction number may be above or
below this value. With current interventions remaining in place to at least the end of March, we
estimate that interventions across all 11 countries will have averted 59,000 deaths up to 31 March
[95% credible interval 21,000-120,000]. Many more deaths will be averted through ensuring that
interventions remain in place until transmission drops to low levels. We estimate that, across all 11
countries between 7 and 43 million individuals have been infected with SARS-CoV-Z up to 28th March,
representing between 1.88% and 11.43% ofthe population. The proportion of the population infected
to date — the attack rate - is estimated to be highest in Spain followed by Italy and lowest in Germany
and Norway, reflecting the relative stages of the epidemics.
Given the lag of 2-3 weeks between when transmission changes occur and when their impact can be
observed in trends in mortality, for most of the countries considered here it remains too early to be
certain that recent interventions have been effective. If interventions in countries at earlier stages of
their epidemic, such as Germany or the UK, are more or less effective than they were in the countries
with advanced epidemics, on which our estimates are largely based, or if interventions have improved
or worsened over time, then our estimates of the reproduction number and deaths averted would
change accordingly. It is therefore critical that the current interventions remain in place and trends in
cases and deaths are closely monitored in the coming days and weeks to provide reassurance that
transmission of SARS-Cov-Z is slowing.
SUGGESTED CITATION
Seth Flaxman, Swapnil Mishra, Axel Gandy et 0/. Estimating the number of infections and the impact of non—
pharmaceutical interventions on COVID—19 in 11 European countries. Imperial College London (2020), doi:
https://doi.org/10.25561/77731
1 Introduction
Following the emergence of a novel coronavirus (SARS-CoV-Z) in Wuhan, China in December 2019 and
its global spread, large epidemics of the disease, caused by the virus designated COVID-19, have
emerged in Europe. In response to the rising numbers of cases and deaths, and to maintain the
capacity of health systems to treat as many severe cases as possible, European countries, like those in
other continents, have implemented or are in the process of implementing measures to control their
epidemics. These large-scale non-pharmaceutical interventions vary between countries but include
social distancing (such as banning large gatherings and advising individuals not to socialize outside
their households), border closures, school closures, measures to isolate symptomatic individuals and
their contacts, and large-scale lockdowns of populations with all but essential internal travel banned.
Understanding firstly, whether these interventions are having the desired impact of controlling the
epidemic and secondly, which interventions are necessary to maintain control, is critical given their
large economic and social costs.
The key aim ofthese interventions is to reduce the effective reproduction number, Rt, ofthe infection,
a fundamental epidemiological quantity representing the average number of infections, at time t, per
infected case over the course of their infection. Ith is maintained at less than 1, the incidence of new
infections decreases, ultimately resulting in control of the epidemic. If Rt is greater than 1, then
infections will increase (dependent on how much greater than 1 the reproduction number is) until the
epidemic peaks and eventually declines due to acquisition of herd immunity.
In China, strict movement restrictions and other measures including case isolation and quarantine
began to be introduced from 23rd January, which achieved a downward trend in the number of
confirmed new cases during February, resulting in zero new confirmed indigenous cases in Wuhan by
March 19th. Studies have estimated how Rt changed during this time in different areas ofChina from
around 2-4 during the uncontrolled epidemic down to below 1, with an estimated 7-9 fold decrease
in the number of daily contacts per person.1'2 Control measures such as social distancing, intensive
testing, and contact tracing in other countries such as Singapore and South Korea have successfully
reduced case incidence in recent weeks, although there is a riskthe virus will spread again once control
measures are relaxed.3'4
The epidemic began slightly laterin Europe, from January or later in different regions.5 Countries have
implemented different combinations of control measures and the level of adherence to government
recommendations on social distancing is likely to vary between countries, in part due to different
levels of enforcement.
Estimating reproduction numbers for SARS-CoV-Z presents challenges due to the high proportion of
infections not detected by health systems”7 and regular changes in testing policies, resulting in
different proportions of infections being detected over time and between countries. Most countries
so far only have the capacity to test a small proportion of suspected cases and tests are reserved for
severely ill patients or for high-risk groups (e.g. contacts of cases). Looking at case data, therefore,
gives a systematically biased view of trends.
An alternative way to estimate the course of the epidemic is to back-calculate infections from
observed deaths. Reported deaths are likely to be more reliable, although the early focus of most
surveillance systems on cases with reported travel histories to China may mean that some early deaths
will have been missed. Whilst the recent trends in deaths will therefore be informative, there is a time
lag in observing the effect of interventions on deaths since there is a 2-3-week period between
infection, onset of symptoms and outcome.
In this report, we fit a novel Bayesian mechanistic model of the infection cycle to observed deaths in
11 European countries, inferring plausible upper and lower bounds (Bayesian credible intervals) of the
total populations infected (attack rates), case detection probabilities, and the reproduction number
over time (Rt). We fit the model jointly to COVID-19 data from all these countries to assess whether
there is evidence that interventions have so far been successful at reducing Rt below 1, with the strong
assumption that particular interventions are achieving a similar impact in different countries and that
the efficacy of those interventions remains constant over time. The model is informed more strongly
by countries with larger numbers of deaths and which implemented interventions earlier, therefore
estimates of recent Rt in countries with more recent interventions are contingent on similar
intervention impacts. Data in the coming weeks will enable estimation of country-specific Rt with
greater precision.
Model and data details are presented in the appendix, validation and sensitivity are also presented in
the appendix, and general limitations presented below in the conclusions.
2 Results
The timing of interventions should be taken in the context of when an individual country’s epidemic
started to grow along with the speed with which control measures were implemented. Italy was the
first to begin intervention measures, and other countries followed soon afterwards (Figure 1). Most
interventions began around 12th-14th March. We analyzed data on deaths up to 28th March, giving a
2-3-week window over which to estimate the effect of interventions. Currently, most countries in our
study have implemented all major non-pharmaceutical interventions.
For each country, we model the number of infections, the number of deaths, and Rt, the effective
reproduction number over time, with Rt changing only when an intervention is introduced (Figure 2-
12). Rt is the average number of secondary infections per infected individual, assuming that the
interventions that are in place at time t stay in place throughout their entire infectious period. Every
country has its own individual starting reproduction number Rt before interventions take place.
Specific interventions are assumed to have the same relative impact on Rt in each country when they
were introduced there and are informed by mortality data across all countries.
Figure l: Intervention timings for the 11 European countries included in the analysis. For further
details see Appendix 8.6.
2.1 Estimated true numbers of infections and current attack rates
In all countries, we estimate there are orders of magnitude fewer infections detected (Figure 2) than
true infections, mostly likely due to mild and asymptomatic infections as well as limited testing
capacity. In Italy, our results suggest that, cumulatively, 5.9 [1.9-15.2] million people have been
infected as of March 28th, giving an attack rate of 9.8% [3.2%-25%] of the population (Table 1). Spain
has recently seen a large increase in the number of deaths, and given its smaller population, our model
estimates that a higher proportion of the population, 15.0% (7.0 [18-19] million people) have been
infected to date. Germany is estimated to have one of the lowest attack rates at 0.7% with 600,000
[240,000-1,500,000] people infected.
Imperial College COVID-19 Response Team
Table l: Posterior model estimates of percentage of total population infected as of 28th March 2020.
Country % of total population infected (mean [95% credible intervall)
Austria 1.1% [0.36%-3.1%]
Belgium 3.7% [1.3%-9.7%]
Denmark 1.1% [0.40%-3.1%]
France 3.0% [1.1%-7.4%]
Germany 0.72% [0.28%-1.8%]
Italy 9.8% [3.2%-26%]
Norway 0.41% [0.09%-1.2%]
Spain 15% [3.7%-41%]
Sweden 3.1% [0.85%-8.4%]
Switzerland 3.2% [1.3%-7.6%]
United Kingdom 2.7% [1.2%-5.4%]
2.2 Reproduction numbers and impact of interventions
Averaged across all countries, we estimate initial reproduction numbers of around 3.87 [3.01-4.66],
which is in line with other estimates.1'8 These estimates are informed by our choice of serial interval
distribution and the initial growth rate of observed deaths. A shorter assumed serial interval results in
lower starting reproduction numbers (Appendix 8.4.2, Appendix 8.4.6). The initial reproduction
numbers are also uncertain due to (a) importation being the dominant source of new infections early
in the epidemic, rather than local transmission (b) possible under-ascertainment in deaths particularly
before testing became widespread.
We estimate large changes in Rt in response to the combined non-pharmaceutical interventions. Our
results, which are driven largely by countries with advanced epidemics and larger numbers of deaths
(e.g. Italy, Spain), suggest that these interventions have together had a substantial impact on
transmission, as measured by changes in the estimated reproduction number Rt. Across all countries
we find current estimates of Rt to range from a posterior mean of 0.97 [0.14-2.14] for Norway to a
posterior mean of2.64 [1.40-4.18] for Sweden, with an average of 1.43 across the 11 country posterior
means, a 64% reduction compared to the pre-intervention values. We note that these estimates are
contingent on intervention impact being the same in different countries and at different times. In all
countries but Sweden, under the same assumptions, we estimate that the current reproduction
number includes 1 in the uncertainty range. The estimated reproduction number for Sweden is higher,
not because the mortality trends are significantly different from any other country, but as an artefact
of our model, which assumes a smaller reduction in Rt because no full lockdown has been ordered so
far. Overall, we cannot yet conclude whether current interventions are sufficient to drive Rt below 1
(posterior probability of being less than 1.0 is 44% on average across the countries). We are also
unable to conclude whether interventions may be different between countries or over time.
There remains a high level of uncertainty in these estimates. It is too early to detect substantial
intervention impact in many countries at earlier stages of their epidemic (e.g. Germany, UK, Norway).
Many interventions have occurred only recently, and their effects have not yet been fully observed
due to the time lag between infection and death. This uncertainty will reduce as more data become
available. For all countries, our model fits observed deaths data well (Bayesian goodness of fit tests).
We also found that our model can reliably forecast daily deaths 3 days into the future, by withholding
the latest 3 days of data and comparing model predictions to observed deaths (Appendix 8.3).
The close spacing of interventions in time made it statistically impossible to determine which had the
greatest effect (Figure 1, Figure 4). However, when doing a sensitivity analysis (Appendix 8.4.3) with
uninformative prior distributions (where interventions can increase deaths) we find similar impact of
Imperial College COVID-19 Response Team
interventions, which shows that our choice of prior distribution is not driving the effects we see in the
main analysis.
Figure 2: Country-level estimates of infections, deaths and Rt. Left: daily number of infections, brown
bars are reported infections, blue bands are predicted infections, dark blue 50% credible interval (CI),
light blue 95% CI. The number of daily infections estimated by our model drops immediately after an
intervention, as we assume that all infected people become immediately less infectious through the
intervention. Afterwards, if the Rt is above 1, the number of infections will starts growing again.
Middle: daily number of deaths, brown bars are reported deaths, blue bands are predicted deaths, CI
as in left plot. Right: time-varying reproduction number Rt, dark green 50% CI, light green 95% CI.
Icons are interventions shown at the time they occurred.
Imperial College COVID-19 Response Team
Table 2: Totalforecasted deaths since the beginning of the epidemic up to 31 March in our model
and in a counterfactual model (assuming no intervention had taken place). Estimated averted deaths
over this time period as a result of the interventions. Numbers in brackets are 95% credible intervals.
2.3 Estimated impact of interventions on deaths
Table 2 shows total forecasted deaths since the beginning of the epidemic up to and including 31
March under ourfitted model and under the counterfactual model, which predicts what would have
happened if no interventions were implemented (and R, = R0 i.e. the initial reproduction number
estimated before interventions). Again, the assumption in these predictions is that intervention
impact is the same across countries and time. The model without interventions was unable to capture
recent trends in deaths in several countries, where the rate of increase had clearly slowed (Figure 3).
Trends were confirmed statistically by Bayesian leave-one-out cross-validation and the widely
applicable information criterion assessments —WA|C).
By comparing the deaths predicted under the model with no interventions to the deaths predicted in
our intervention model, we calculated the total deaths averted up to the end of March. We find that,
across 11 countries, since the beginning of the epidemic, 59,000 [21,000-120,000] deaths have been
averted due to interventions. In Italy and Spain, where the epidemic is advanced, 38,000 [13,000-
84,000] and 16,000 [5,400-35,000] deaths have been averted, respectively. Even in the UK, which is
much earlier in its epidemic, we predict 370 [73-1,000] deaths have been averted.
These numbers give only the deaths averted that would have occurred up to 31 March. lfwe were to
include the deaths of currently infected individuals in both models, which might happen after 31
March, then the deaths averted would be substantially higher.
Figure 3: Daily number of confirmed deaths, predictions (up to 28 March) and forecasts (after) for (a)
Italy and (b) Spain from our model with interventions (blue) and from the no interventions
counterfactual model (pink); credible intervals are shown one week into the future. Other countries
are shown in Appendix 8.6.
03/0 25% 50% 753% 100%
(no effect on transmissibility) (ends transmissibility
Relative % reduction in R.
Figure 4: Our model includes five covariates for governmental interventions, adjusting for whether
the intervention was the first one undertaken by the government in response to COVID-19 (red) or
was subsequent to other interventions (green). Mean relative percentage reduction in Rt is shown
with 95% posterior credible intervals. If 100% reduction is achieved, Rt = 0 and there is no more
transmission of COVID-19. No effects are significantly different from any others, probably due to the
fact that many interventions occurred on the same day or within days of each other as shown in
Figure l.
3 Discussion
During this early phase of control measures against the novel coronavirus in Europe, we analyze trends
in numbers of deaths to assess the extent to which transmission is being reduced. Representing the
COVlD-19 infection process using a semi-mechanistic, joint, Bayesian hierarchical model, we can
reproduce trends observed in the data on deaths and can forecast accurately over short time horizons.
We estimate that there have been many more infections than are currently reported. The high level
of under-ascertainment of infections that we estimate here is likely due to the focus on testing in
hospital settings rather than in the community. Despite this, only a small minority of individuals in
each country have been infected, with an attack rate on average of 4.9% [l.9%-ll%] with considerable
variation between countries (Table 1). Our estimates imply that the populations in Europe are not
close to herd immunity ("50-75% if R0 is 2-4). Further, with Rt values dropping substantially, the rate
of acquisition of herd immunity will slow down rapidly. This implies that the virus will be able to spread
rapidly should interventions be lifted. Such estimates of the attack rate to date urgently need to be
validated by newly developed antibody tests in representative population surveys, once these become
available.
We estimate that major non-pharmaceutical interventions have had a substantial impact on the time-
varying reproduction numbers in countries where there has been time to observe intervention effects
on trends in deaths (Italy, Spain). lfadherence in those countries has changed since that initial period,
then our forecast of future deaths will be affected accordingly: increasing adherence over time will
have resulted in fewer deaths and decreasing adherence in more deaths. Similarly, our estimates of
the impact ofinterventions in other countries should be viewed with caution if the same interventions
have achieved different levels of adherence than was initially the case in Italy and Spain.
Due to the implementation of interventions in rapid succession in many countries, there are not
enough data to estimate the individual effect size of each intervention, and we discourage attributing
associations to individual intervention. In some cases, such as Norway, where all interventions were
implemented at once, these individual effects are by definition unidentifiable. Despite this, while
individual impacts cannot be determined, their estimated joint impact is strongly empirically justified
(see Appendix 8.4 for sensitivity analysis). While the growth in daily deaths has decreased, due to the
lag between infections and deaths, continued rises in daily deaths are to be expected for some time.
To understand the impact of interventions, we fit a counterfactual model without the interventions
and compare this to the actual model. Consider Italy and the UK - two countries at very different stages
in their epidemics. For the UK, where interventions are very recent, much of the intervention strength
is borrowed from countries with older epidemics. The results suggest that interventions will have a
large impact on infections and deaths despite counts of both rising. For Italy, where far more time has
passed since the interventions have been implemented, it is clear that the model without
interventions does not fit well to the data, and cannot explain the sub-linear (on the logarithmic scale)
reduction in deaths (see Figure 10).
The counterfactual model for Italy suggests that despite mounting pressure on health systems,
interventions have averted a health care catastrophe where the number of new deaths would have
been 3.7 times higher (38,000 deaths averted) than currently observed. Even in the UK, much earlier
in its epidemic, the recent interventions are forecasted to avert 370 total deaths up to 31 of March.
4 Conclusion and Limitations
Modern understanding of infectious disease with a global publicized response has meant that
nationwide interventions could be implemented with widespread adherence and support. Given
observed infection fatality ratios and the epidemiology of COVlD-19, major non-pharmaceutical
interventions have had a substantial impact in reducing transmission in countries with more advanced
epidemics. It is too early to be sure whether similar reductions will be seen in countries at earlier
stages of their epidemic. While we cannot determine which set of interventions have been most
successful, taken together, we can already see changes in the trends of new deaths. When forecasting
3 days and looking over the whole epidemic the number of deaths averted is substantial. We note that
substantial innovation is taking place, and new more effective interventions or refinements of current
interventions, alongside behavioral changes will further contribute to reductions in infections. We
cannot say for certain that the current measures have controlled the epidemic in Europe; however, if
current trends continue, there is reason for optimism.
Our approach is semi-mechanistic. We propose a plausible structure for the infection process and then
estimate parameters empirically. However, many parameters had to be given strong prior
distributions or had to be fixed. For these assumptions, we have provided relevant citations to
previous studies. As more data become available and better estimates arise, we will update these in
weekly reports. Our choice of serial interval distribution strongly influences the prior distribution for
starting R0. Our infection fatality ratio, and infection-to-onset-to-death distributions strongly
influence the rate of death and hence the estimated number of true underlying cases.
We also assume that the effect of interventions is the same in all countries, which may not be fully
realistic. This assumption implies that countries with early interventions and more deaths since these
interventions (e.g. Italy, Spain) strongly influence estimates of intervention impact in countries at
earlier stages of their epidemic with fewer deaths (e.g. Germany, UK).
We have tried to create consistent definitions of all interventions and document details of this in
Appendix 8.6. However, invariably there will be differences from country to country in the strength of
their intervention — for example, most countries have banned gatherings of more than 2 people when
implementing a lockdown, whereas in Sweden the government only banned gatherings of more than
10 people. These differences can skew impacts in countries with very little data. We believe that our
uncertainty to some degree can cover these differences, and as more data become available,
coefficients should become more reliable.
However, despite these strong assumptions, there is sufficient signal in the data to estimate changes
in R, (see the sensitivity analysis reported in Appendix 8.4.3) and this signal will stand to increase with
time. In our Bayesian hierarchical framework, we robustly quantify the uncertainty in our parameter
estimates and posterior predictions. This can be seen in the very wide credible intervals in more recent
days, where little or no death data are available to inform the estimates. Furthermore, we predict
intervention impact at country-level, but different trends may be in place in different parts of each
country. For example, the epidemic in northern Italy was subject to controls earlier than the rest of
the country.
5 Data
Our model utilizes daily real-time death data from the ECDC (European Centre of Disease Control),
where we catalogue case data for 11 European countries currently experiencing the epidemic: Austria,
Belgium, Denmark, France, Germany, Italy, Norway, Spain, Sweden, Switzerland and the United
Kingdom. The ECDC provides information on confirmed cases and deaths attributable to COVID-19.
However, the case data are highly unrepresentative of the incidence of infections due to
underreporting as well as systematic and country-specific changes in testing.
We, therefore, use only deaths attributable to COVID-19 in our model; we do not use the ECDC case
estimates at all. While the observed deaths still have some degree of unreliability, again due to
changes in reporting and testing, we believe the data are ofsufficient fidelity to model. For population
counts, we use UNPOP age-stratified counts.10
We also catalogue data on the nature and type of major non-pharmaceutical interventions. We looked
at the government webpages from each country as well as their official public health
division/information webpages to identify the latest advice/laws being issued by the government and
public health authorities. We collected the following:
School closure ordered: This intervention refers to nationwide extraordinary school closures which in
most cases refer to both primary and secondary schools closing (for most countries this also includes
the closure of otherforms of higher education or the advice to teach remotely). In the case of Denmark
and Sweden, we allowed partial school closures of only secondary schools. The date of the school
closure is taken to be the effective date when the schools started to be closed (ifthis was on a Monday,
the date used was the one of the previous Saturdays as pupils and students effectively stayed at home
from that date onwards).
Case-based measures: This intervention comprises strong recommendations or laws to the general
public and primary care about self—isolation when showing COVID-19-like symptoms. These also
include nationwide testing programs where individuals can be tested and subsequently self—isolated.
Our definition is restricted to nationwide government advice to all individuals (e.g. UK) or to all primary
care and excludes regional only advice. These do not include containment phase interventions such
as isolation if travelling back from an epidemic country such as China.
Public events banned: This refers to banning all public events of more than 100 participants such as
sports events.
Social distancing encouraged: As one of the first interventions against the spread of the COVID-19
pandemic, many governments have published advice on social distancing including the
recommendation to work from home wherever possible, reducing use ofpublictransport and all other
non-essential contact. The dates used are those when social distancing has officially been
recommended by the government; the advice may include maintaining a recommended physical
distance from others.
Lockdown decreed: There are several different scenarios that the media refers to as lockdown. As an
overall definition, we consider regulations/legislations regarding strict face-to-face social interaction:
including the banning of any non-essential public gatherings, closure of educational and
public/cultural institutions, ordering people to stay home apart from exercise and essential tasks. We
include special cases where these are not explicitly mentioned on government websites but are
enforced by the police (e.g. France). The dates used are the effective dates when these legislations
have been implemented. We note that lockdown encompasses other interventions previously
implemented.
First intervention: As Figure 1 shows, European governments have escalated interventions rapidly,
and in some examples (Norway/Denmark) have implemented these interventions all on a single day.
Therefore, given the temporal autocorrelation inherent in government intervention, we include a
binary covariate for the first intervention, which can be interpreted as a government decision to take
major action to control COVID-19.
A full list of the timing of these interventions and the sources we have used can be found in Appendix
8.6.
6 Methods Summary
A Visual summary of our model is presented in Figure 5 (details in Appendix 8.1 and 8.2). Replication
code is available at https://github.com/|mperia|CollegeLondon/covid19model/releases/tag/vl.0
We fit our model to observed deaths according to ECDC data from 11 European countries. The
modelled deaths are informed by an infection-to-onset distribution (time from infection to the onset
of symptoms), an onset-to-death distribution (time from the onset of symptoms to death), and the
population-averaged infection fatality ratio (adjusted for the age structure and contact patterns of
each country, see Appendix). Given these distributions and ratios, modelled deaths are a function of
the number of infections. The modelled number of infections is informed by the serial interval
distribution (the average time from infection of one person to the time at which they infect another)
and the time-varying reproduction number. Finally, the time-varying reproduction number is a
function of the initial reproduction number before interventions and the effect sizes from
interventions.
Figure 5: Summary of model components.
Following the hierarchy from bottom to top gives us a full framework to see how interventions affect
infections, which can result in deaths. We use Bayesian inference to ensure our modelled deaths can
reproduce the observed deaths as closely as possible. From bottom to top in Figure 5, there is an
implicit lag in time that means the effect of very recent interventions manifest weakly in current
deaths (and get stronger as time progresses). To maximise the ability to observe intervention impact
on deaths, we fit our model jointly for all 11 European countries, which results in a large data set. Our
model jointly estimates the effect sizes of interventions. We have evaluated the effect ofour Bayesian
prior distribution choices and evaluate our Bayesian posterior calibration to ensure our results are
statistically robust (Appendix 8.4).
7 Acknowledgements
Initial research on covariates in Appendix 8.6 was crowdsourced; we thank a number of people
across the world for help with this. This work was supported by Centre funding from the UK Medical
Research Council under a concordat with the UK Department for International Development, the
NIHR Health Protection Research Unit in Modelling Methodology and CommunityJameel.
8 Appendix: Model Specifics, Validation and Sensitivity Analysis
8.1 Death model
We observe daily deaths Dam for days t E 1, ...,n and countries m E 1, ...,p. These daily deaths are
modelled using a positive real-Valued function dam = E(Dam) that represents the expected number
of deaths attributed to COVID-19. Dam is assumed to follow a negative binomial distribution with
The expected number of deaths (1 in a given country on a given day is a function of the number of
infections C occurring in previous days.
At the beginning of the epidemic, the observed deaths in a country can be dominated by deaths that
result from infection that are not locally acquired. To avoid biasing our model by this, we only include
observed deaths from the day after a country has cumulatively observed 10 deaths in our model.
To mechanistically link ourfunction for deaths to infected cases, we use a previously estimated COVID-
19 infection-fatality-ratio ifr (probability of death given infection)9 together with a distribution oftimes
from infection to death TE. The ifr is derived from estimates presented in Verity et al11 which assumed
homogeneous attack rates across age-groups. To better match estimates of attack rates by age
generated using more detailed information on country and age-specific mixing patterns, we scale
these estimates (the unadjusted ifr, referred to here as ifr’) in the following way as in previous work.4
Let Ca be the number of infections generated in age-group a, Na the underlying size of the population
in that age group and AR“ 2 Ca/Na the age-group-specific attack rate. The adjusted ifr is then given
by: ifra = fififié, where AR50_59 is the predicted attack-rate in the 50-59 year age-group after
incorporating country-specific patterns of contact and mixing. This age-group was chosen as the
reference as it had the lowest predicted level of underreporting in previous analyses of data from the
Chinese epidemic“. We obtained country-specific estimates of attack rate by age, AR“, for the 11
European countries in our analysis from a previous study which incorporates information on contact
between individuals of different ages in countries across Europe.12 We then obtained overall ifr
estimates for each country adjusting for both demography and age-specific attack rates.
Using estimated epidemiological information from previous studies,“'11 we assume TE to be the sum of
two independent random times: the incubation period (infection to onset of symptoms or infection-
to-onset) distribution and the time between onset of symptoms and death (onset-to-death). The
infection-to-onset distribution is Gamma distributed with mean 5.1 days and coefficient of variation
0.86. The onset-to-death distribution is also Gamma distributed with a mean of 18.8 days and a
coefficient of va riation 0.45. ifrm is population averaged over the age structure of a given country. The
infection-to-death distribution is therefore given by:
um ~ ifrm ~ (Gamma(5.1,0.86) + Gamma(18.8,0.45))
Figure 6 shows the infection-to-death distribution and the resulting survival function that integrates
to the infection fatality ratio.
Figure 6: Left, infection-to-death distribution (mean 23.9 days). Right, survival probability of infected
individuals per day given the infection fatality ratio (1%) and the infection-to-death distribution on
the left.
Using the probability of death distribution, the expected number of deaths dam, on a given day t, for
country, m, is given by the following discrete sum:
The number of deaths today is the sum of the past infections weighted by their probability of death,
where the probability of death depends on the number of days since infection.
8.2 Infection model
The true number of infected individuals, C, is modelled using a discrete renewal process. This approach
has been used in numerous previous studies13'16 and has a strong theoretical basis in stochastic
individual-based counting processes such as Hawkes process and the Bellman-Harris process.”18 The
renewal model is related to the Susceptible-Infected-Recovered model, except the renewal is not
expressed in differential form. To model the number ofinfections over time we need to specify a serial
interval distribution g with density g(T), (the time between when a person gets infected and when
they subsequently infect another other people), which we choose to be Gamma distributed:
g ~ Gamma (6.50.62).
The serial interval distribution is shown below in Figure 7 and is assumed to be the same for all
countries.
Figure 7: Serial interval distribution g with a mean of 6.5 days.
Given the serial interval distribution, the number of infections Eamon a given day t, and country, m,
is given by the following discrete convolution function:
_ t—1
Cam — Ram ZT=0 Cr,mgt—‘r r
where, similarto the probability ofdeath function, the daily serial interval is discretized by
fs+0.5
1.5
gs = T=s—0.Sg(T)dT fors = 2,3, and 91 = fT=Og(T)dT.
Infections today depend on the number of infections in the previous days, weighted by the discretized
serial interval distribution. This weighting is then scaled by the country-specific time-Varying
reproduction number, Ram, that models the average number of secondary infections at a given time.
The functional form for the time-Varying reproduction number was chosen to be as simple as possible
to minimize the impact of strong prior assumptions: we use a piecewise constant function that scales
Ram from a baseline prior R0,m and is driven by known major non-pharmaceutical interventions
occurring in different countries and times. We included 6 interventions, one of which is constructed
from the other 5 interventions, which are timings of school and university closures (k=l), self—isolating
if ill (k=2), banning of public events (k=3), any government intervention in place (k=4), implementing
a partial or complete lockdown (k=5) and encouraging social distancing and isolation (k=6). We denote
the indicator variable for intervention k E 1,2,3,4,5,6 by IkI’m, which is 1 if intervention k is in place
in country m at time t and 0 otherwise. The covariate ”any government intervention” (k=4) indicates
if any of the other 5 interventions are in effect,i.e.14’t’m equals 1 at time t if any of the interventions
k E 1,2,3,4,5 are in effect in country m at time t and equals 0 otherwise. Covariate 4 has the
interpretation of indicating the onset of major government intervention. The effect of each
intervention is assumed to be multiplicative. Ram is therefore a function ofthe intervention indicators
Ik’t’m in place at time t in country m:
Ram : R0,m eXp(— 212:1 O(Rheum)-
The exponential form was used to ensure positivity of the reproduction number, with R0,m
constrained to be positive as it appears outside the exponential. The impact of each intervention on
Ram is characterised by a set of parameters 0(1, ...,OL6, with independent prior distributions chosen
to be
ock ~ Gamma(. 5,1).
The impacts ock are shared between all m countries and therefore they are informed by all available
data. The prior distribution for R0 was chosen to be
R0,m ~ Normal(2.4, IKI) with K ~ Normal(0,0.5),
Once again, K is the same among all countries to share information.
We assume that seeding of new infections begins 30 days before the day after a country has
cumulatively observed 10 deaths. From this date, we seed our model with 6 sequential days of
infections drawn from cl’m,...,66’m~EXponential(T), where T~Exponential(0.03). These seed
infections are inferred in our Bayesian posterior distribution.
We estimated parameters jointly for all 11 countries in a single hierarchical model. Fitting was done
in the probabilistic programming language Stan,19 using an adaptive Hamiltonian Monte Carlo (HMC)
sampler. We ran 8 chains for 4000 iterations with 2000 iterations of warmup and a thinning factor 4
to obtain 2000 posterior samples. Posterior convergence was assessed using the Rhat statistic and by
diagnosing divergent transitions of the HMC sampler. Prior-posterior calibrations were also performed
(see below).
8.3 Validation
We validate accuracy of point estimates of our model using cross-Validation. In our cross-validation
scheme, we leave out 3 days of known death data (non-cumulative) and fit our model. We forecast
what the model predicts for these three days. We present the individual forecasts for each day, as
well as the average forecast for those three days. The cross-validation results are shown in the Figure
8.
Figure 8: Cross-Validation results for 3-day and 3-day aggregatedforecasts
Figure 8 provides strong empirical justification for our model specification and mechanism. Our
accurate forecast over a three-day time horizon suggests that our fitted estimates for Rt are
appropriate and plausible.
Along with from point estimates we all evaluate our posterior credible intervals using the Rhat
statistic. The Rhat statistic measures whether our Markov Chain Monte Carlo (MCMC) chains have
converged to the equilibrium distribution (the correct posterior distribution). Figure 9 shows the Rhat
statistics for all of our parameters
Figure 9: Rhat statistics - values close to 1 indicate MCMC convergence.
Figure 9 indicates that our MCMC have converged. In fitting we also ensured that the MCMC sampler
experienced no divergent transitions - suggesting non pathological posterior topologies.
8.4 SensitivityAnalysis
8.4.1 Forecasting on log-linear scale to assess signal in the data
As we have highlighted throughout in this report, the lag between deaths and infections means that
it ta kes time for information to propagate backwa rds from deaths to infections, and ultimately to Rt.
A conclusion of this report is the prediction of a slowing of Rt in response to major interventions. To
gain intuition that this is data driven and not simply a consequence of highly constrained model
assumptions, we show death forecasts on a log-linear scale. On this scale a line which curves below a
linear trend is indicative of slowing in the growth of the epidemic. Figure 10 to Figure 12 show these
forecasts for Italy, Spain and the UK. They show this slowing down in the daily number of deaths. Our
model suggests that Italy, a country that has the highest death toll of COVID-19, will see a slowing in
the increase in daily deaths over the coming week compared to the early stages of the epidemic.
We investigated the sensitivity of our estimates of starting and final Rt to our assumed serial interval
distribution. For this we considered several scenarios, in which we changed the serial interval
distribution mean, from a value of 6.5 days, to have values of 5, 6, 7 and 8 days.
In Figure 13, we show our estimates of R0, the starting reproduction number before interventions, for
each of these scenarios. The relative ordering of the Rt=0 in the countries is consistent in all settings.
However, as expected, the scale of Rt=0 is considerably affected by this change — a longer serial
interval results in a higher estimated Rt=0. This is because to reach the currently observed size of the
epidemics, a longer assumed serial interval is compensated by a higher estimated R0.
Additionally, in Figure 14, we show our estimates of Rt at the most recent model time point, again for
each ofthese scenarios. The serial interval mean can influence Rt substantially, however, the posterior
credible intervals of Rt are broadly overlapping.
Figure 13: Initial reproduction number R0 for different serial interval (SI) distributions (means
between 5 and 8 days). We use 6.5 days in our main analysis.
Figure 14: Rt on 28 March 2020 estimated for all countries, with serial interval (SI) distribution means
between 5 and 8 days. We use 6.5 days in our main analysis.
8.4.3 Uninformative prior sensitivity on or
We ran our model using implausible uninformative prior distributions on the intervention effects,
allowing the effect of an intervention to increase or decrease Rt. To avoid collinearity, we ran 6
separate models, with effects summarized below (compare with the main analysis in Figure 4). In this
series of univariate analyses, we find (Figure 15) that all effects on their own serve to decrease Rt.
This gives us confidence that our choice of prior distribution is not driving the effects we see in the
main analysis. Lockdown has a very large effect, most likely due to the fact that it occurs after other
interventions in our dataset. The relatively large effect sizes for the other interventions are most likely
due to the coincidence of the interventions in time, such that one intervention is a proxy for a few
others.
Figure 15: Effects of different interventions when used as the only covariate in the model.
8.4.4
To assess prior assumptions on our piecewise constant functional form for Rt we test using a
nonparametric function with a Gaussian process prior distribution. We fit a model with a Gaussian
process prior distribution to data from Italy where there is the largest signal in death data. We find
that the Gaussian process has a very similartrend to the piecewise constant model and reverts to the
mean in regions of no data. The correspondence of a completely nonparametric function and our
piecewise constant function suggests a suitable parametric specification of Rt.
Nonparametric fitting of Rf using a Gaussian process:
8.4.5 Leave country out analysis
Due to the different lengths of each European countries’ epidemic, some countries, such as Italy have
much more data than others (such as the UK). To ensure that we are not leveraging too much
information from any one country we perform a ”leave one country out” sensitivity analysis, where
we rerun the model without a different country each time. Figure 16 and Figure 17 are examples for
results for the UK, leaving out Italy and Spain. In general, for all countries, we observed no significant
dependence on any one country.
Figure 16: Model results for the UK, when not using data from Italy for fitting the model. See the
Figure 17: Model results for the UK, when not using data from Spain for fitting the model. See caption
of Figure 2 for an explanation of the plots.
8.4.6 Starting reproduction numbers vs theoretical predictions
To validate our starting reproduction numbers, we compare our fitted values to those theoretically
expected from a simpler model assuming exponential growth rate, and a serial interval distribution
mean. We fit a linear model with a Poisson likelihood and log link function and extracting the daily
growth rate r. For well-known theoretical results from the renewal equation, given a serial interval
distribution g(r) with mean m and standard deviation 5, given a = mZ/S2 and b = m/SZ, and
a
subsequently R0 = (1 + %) .Figure 18 shows theoretically derived R0 along with our fitted
estimates of Rt=0 from our Bayesian hierarchical model. As shown in Figure 18 there is large
correspondence between our estimated starting reproduction number and the basic reproduction
number implied by the growth rate r.
R0 (red) vs R(FO) (black)
Figure 18: Our estimated R0 (black) versus theoretically derived Ru(red) from a log-linear
regression fit.
8.5 Counterfactual analysis — interventions vs no interventions
Figure 19: Daily number of confirmed deaths, predictions (up to 28 March) and forecasts (after) for
all countries except Italy and Spain from our model with interventions (blue) and from the no
interventions counterfactual model (pink); credible intervals are shown one week into the future.
DOI: https://doi.org/10.25561/77731
Page 28 of 35
30 March 2020 Imperial College COVID-19 Response Team
8.6 Data sources and Timeline of Interventions
Figure 1 and Table 3 display the interventions by the 11 countries in our study and the dates these
interventions became effective.
Table 3: Timeline of Interventions.
Country Type Event Date effective
School closure
ordered Nationwide school closures.20 14/3/2020
Public events
banned Banning of gatherings of more than 5 people.21 10/3/2020
Banning all access to public spaces and gatherings
Lockdown of more than 5 people. Advice to maintain 1m
ordered distance.22 16/3/2020
Social distancing
encouraged Recommendation to maintain a distance of 1m.22 16/3/2020
Case-based
Austria measures Implemented at lockdown.22 16/3/2020
School closure
ordered Nationwide school closures.23 14/3/2020
Public events All recreational activities cancelled regardless of
banned size.23 12/3/2020
Citizens are required to stay at home except for
Lockdown work and essential journeys. Going outdoors only
ordered with household members or 1 friend.24 18/3/2020
Public transport recommended only for essential
Social distancing journeys, work from home encouraged, all public
encouraged places e.g. restaurants closed.23 14/3/2020
Case-based Everyone should stay at home if experiencing a
Belgium measures cough or fever.25 10/3/2020
School closure Secondary schools shut and universities (primary
ordered schools also shut on 16th).26 13/3/2020
Public events Bans of events >100 people, closed cultural
banned institutions, leisure facilities etc.27 12/3/2020
Lockdown Bans of gatherings of >10 people in public and all
ordered public places were shut.27 18/3/2020
Limited use of public transport. All cultural
Social distancing institutions shut and recommend keeping
encouraged appropriate distance.28 13/3/2020
Case-based Everyone should stay at home if experiencing a
Denmark measures cough or fever.29 12/3/2020
School closure
ordered Nationwide school closures.30 14/3/2020
Public events
banned Bans of events >100 people.31 13/3/2020
Lockdown Everybody has to stay at home. Need a self-
ordered authorisation form to leave home.32 17/3/2020
Social distancing
encouraged Advice at the time of lockdown.32 16/3/2020
Case-based
France measures Advice at the time of lockdown.32 16/03/2020
School closure
ordered Nationwide school closures.33 14/3/2020
Public events No gatherings of >1000 people. Otherwise
banned regional restrictions only until lockdown.34 22/3/2020
Lockdown Gatherings of > 2 people banned, 1.5 m
ordered distance.35 22/3/2020
Social distancing Avoid social interaction wherever possible
encouraged recommended by Merkel.36 12/3/2020
Advice for everyone experiencing symptoms to
Case-based contact a health care agency to get tested and
Germany measures then self—isolate.37 6/3/2020
School closure
ordered Nationwide school closures.38 5/3/2020
Public events
banned The government bans all public events.39 9/3/2020
Lockdown The government closes all public places. People
ordered have to stay at home except for essential travel.40 11/3/2020
A distance of more than 1m has to be kept and
Social distancing any other form of alternative aggregation is to be
encouraged excluded.40 9/3/2020
Case-based Advice to self—isolate if experiencing symptoms
Italy measures and quarantine if tested positive.41 9/3/2020
Norwegian Directorate of Health closes all
School closure educational institutions. Including childcare
ordered facilities and all schools.42 13/3/2020
Public events The Directorate of Health bans all non-necessary
banned social contact.42 12/3/2020
Lockdown Only people living together are allowed outside
ordered together. Everyone has to keep a 2m distance.43 24/3/2020
Social distancing The Directorate of Health advises against all
encouraged travelling and non-necessary social contacts.42 16/3/2020
Case-based Advice to self—isolate for 7 days if experiencing a
Norway measures cough or fever symptoms.44 15/3/2020
ordered Nationwide school closures.45 13/3/2020
Public events
banned Banning of all public events by lockdown.46 14/3/2020
Lockdown
ordered Nationwide lockdown.43 14/3/2020
Social distancing Advice on social distancing and working remotely
encouraged from home.47 9/3/2020
Case-based Advice to self—isolate for 7 days if experiencing a
Spain measures cough or fever symptoms.47 17/3/2020
School closure
ordered Colleges and upper secondary schools shut.48 18/3/2020
Public events
banned The government bans events >500 people.49 12/3/2020
Lockdown
ordered No lockdown occurred. NA
People even with mild symptoms are told to limit
Social distancing social contact, encouragement to work from
encouraged home.50 16/3/2020
Case-based Advice to self—isolate if experiencing a cough or
Sweden measures fever symptoms.51 10/3/2020
School closure
ordered No in person teaching until 4th of April.52 14/3/2020
Public events
banned The government bans events >100 people.52 13/3/2020
Lockdown
ordered Gatherings of more than 5 people are banned.53 2020-03-20
Advice on keeping distance. All businesses where
Social distancing this cannot be realised have been closed in all
encouraged states (kantons).54 16/3/2020
Case-based Advice to self—isolate if experiencing a cough or
Switzerland measures fever symptoms.55 2/3/2020
Nationwide school closure. Childminders,
School closure nurseries and sixth forms are told to follow the
ordered guidance.56 21/3/2020
Public events
banned Implemented with lockdown.57 24/3/2020
Gatherings of more than 2 people not from the
Lockdown same household are banned and police
ordered enforceable.57 24/3/2020
Social distancing Advice to avoid pubs, clubs, theatres and other
encouraged public institutions.58 16/3/2020
Case-based Advice to self—isolate for 7 days if experiencing a
UK measures cough or fever symptoms.59 12/3/2020
9 References
1. Li, R. et al. Substantial undocumented infection facilitates the rapid dissemination of novel
coronavirus (SARS-CoV2). Science (2020) doi:10.1126/science.abb3221.
2. Zhang, J. et al. Patterns of human social contact and contact with animals in Shanghai, China.
5cLRep.9,1—11(2019)
3. Worldometers.info. Hong Kong: coronavirus cases.
https://www.wo rldometers.info/co ronavirus/country/china-hong-kong-sar/.
4. Ferguson, N. et al. Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19
mortality and healthcare demand (Report 9). https://www.imperial.ac.uk/mrc-global-infectious-
disease-analysis/news--wuhan-coronavirus/.
5. Cereda, D. et al. The early phase of the COVID-19 outbreak in Lombardy, Italy. arXiv (2020).
6. Zhao, A. J. et al. Title: Antibody responses to SARS-CoV-2 in patients of novel coronavirus
disease 2019 Brief Title : Antibody responses in COVID-19 patients. (2020).
7. Jombart, T. et al. Inferring the number of COVID-19 cases from recently reported deaths.
medRXiV 2020.03.10.20033761(2020)doi:10.1101/2020.03.10.20033761.
8. Zhang, J. et al. Age profile of susceptibility, mixing, and social distancing shape the dynamics
of the novel coronavirus disease 2019 outbreak in China. (2020) doi:10.1101/2020.03.19.20039107.
9. Lourenco, J. et al. Fundamental principles of epidemic spread highlight the immediate need
for large-scale serological surveys to assess the stage of the SARS-CoV-2 epidemic.
doi:10.1101/2020.03.24.20042291
10. United Nations, Department of Economic and Social Affairs, Population Division. World
Population Prospects 2019: Data Booket. ST/ESA/SER.A/424. (2019).
11. Verity, R. et al. Estimates ofthe severity of COVID-19 disease. Lancet Infect Dis in press, (2020).
12. Walker, P. G. T. et al. Report 12: The Global Impact of COVID-19 and Strategies for Mitigation
and Suppression.
13. Fraser, C. Estimating Individual and Household Reproduction Numbers in an Emerging
Epidemic. PL05 ONE 2, e758 (2007).
14. Cori, A., Ferguson, N. M., Fraser, C. & Cauchemez, S. A New Framework and Software to
Estimate Time-Varying Reproduction Numbers During Epidemics. Am. J. Epidemiol. 178, 1505—1512
(20131
15. Nouvellet, P. et al. A simple approach to measure transmissibility and forecast incidence.
Epidemics 22, 29—35 (2018).
16. Cauchemez, 8., Valleron, A. J., Boelle, P. Y., Flahault, A. & Ferguson, N. M. Estimating the
impact of school closure on influenza transmission from Sentinel data. Nature 452, 750—754 (2008).
17. Bellman, R. & Harris, T. On Age-Dependent Binary Branching Processes. Ann. Math. 55, 280—
295(19521
18. Bellman, R. & Harris, T. E. On the Theory of Age-Dependent Stochastic Branching Processes.
Proc. Natl. Acad. Sci. 34, 601—604 (1948).
19. Stan Development Team. 2018. The Stan Core Library, Version 2.18.0. http://mc-stan.org.
20. Bundesministerium. Coronavirus (COVID-19): Status quo — Schulen, Hochschulen,
Universitaten und Forschungsinstitutionen.
https://www.bmbwf.gv.at/Ministerium/Informationspflicht/corona/corona_status.html.
21. Henley, J. Coronavirus: EU states enact tough measures to stem spread. The Guardian
https://www.theguardian.com/world/2020/mar/10/coronavirus-several-eu-states-ban-mass-events-
after-italian-lockdown (2020).
22. Bundesministerium. Coronavirus - Aktuelle MaBnahmen.
https://www.sozialministerium.at/Informationen-zum-Coronavirus/Coronavirus—Aktuelle-
MaBnahmen.html (2020).
23. Federal Public Service. Coronavirus : Phase 2 maintained, transition to the federal phase and
additional measures. https://www.info-coronavirus.be/en/2020/03/12/phase-2-maintained-
transition-to-the-federal-phase-and-additional-measures/ (2020).
24. Belgium.be. Coronavirus: reinforced measures | Belgium.be.
https://www.belgium.be/en/news/2020/coronavirus_reinforced_measures (2020).
25. Federal Public Service. Protect yourself and protect the others. https://www.info-
coronavirus.be/en/2020/03/10/protect-yourself—and-protect-the-others/ (2020).
26. Wikipedia. 2020 coronavirus pandemic in Denmark. Wikimedia Foundation
https://en.wikipedia.org/wiki/2020_coronavirus_pandemic_in_Denmark.
27. Stephensen, Emma K|inker; Hansen, T. S. Danmark lukker ned: Her er regeringens nye tiltag.
TV2 https://nyheder.tv2.dk/samfund/2020-03-11-danmark-lukker-ned-her-er-regeringens-nye-tiltag
(20201
28. Politi. Nye tiltag mod covid-19. Politi https://politi.dk/coronavirus-i-danmark/seneste-nyt-fra-
myndighederne/nye-tiltag-mod-covid-19 (2020).
29. Styrelsen for Patientsikkerhed. Indberetning om covid-19zlnformation om mulighed for
p\aabud til enkeltpersoner (coronavirus/covid-19). https://stps.dk/da/ansvar-og-
retningslinjer/vejledning/indberetning-om-covid-19/#.
30. Wikipedia. 2020 coronavirus pandemic in France. Wikimedia Foundation
https://en.wikipedia.org/wiki/2020_coronavirus_pandemic_in_France.
31. The Local. France bans gatherings of more than 100 people as coronavirus death toll rises -
The Local. The Local https://www.thelocal.fr/20200313/france-bans-gatherings-of—over-100-people-
to-fight-coronavirus-pandemic (2020).
32. Henley, Jon; Willsher, Kim; Kassam, A. Coronavirus: France imposes lockdown as EU calls for
30-day travel ban. The Guardian https://www.theguardian.com/world/2020/mar/16/coronavirus-
spain-takes-over-private-healthcare-amid-more-european-lockdowns (2020).
33. Wikipedia. 2020 coronavirus pandemic in Germany. Wikimedia Foundation
https://en.wikipedia.org/wiki/2020_coronavirus_pandemic_in_Germany.
34. BMI. Coronavirus: Fragen und Antworten. Bundesministerium des Innern,fur Bau und Heimat
https://web.archive.org/web/20200317073042/https://www.bmi.bund.de/SharedDocs/faqs/DE/the
men/bevoelkerungsschutz/coronavirus/coronavirus-faqs.htmI#doc13738352bodyText7.
35. BBC News. Coronavirus: Germany tightens curbs and bans meetings of more than two. BBC
News https://www.bbc.co.uk/news/world-europe-51999080 (2020).
36. Bundesregierung. Kanzlerin trifft Regierungschefs der Lander Sozialkontakte vermeiden,
Ausbreitung verlangsamen. https://www.bundesregierung.de/breg-de/themen/coronavirus/mpk-
1730186(2020)
37. Robert Koch Institut. Antworten auf haufig gestellte Fragen zum Coronavirus SARS-CoV-2.
Robert Koch Institut
https://web.archive.org/web/20200312004624/https://www.rki.de/SharedDocs/FAQ/NCOV2019/F
AQ_Liste.html (2020).
38. Ministero della Salute. Governo annuncia sospensione dell’attivita didattica dal 5 a|15 marzo.
Ministero della Salute
http://www.salute.gov.it/portale/nuovocoronavirus/dettaglioVideoNuovoCoronavirus.jsp?lingua=ita
liano&menu=multimedia&p=video&id=2052 (2020).
39. CNN. Italy prohibits travel and cancels all public events in its northern region. CNN
https://edition.cnn.com/2020/03/08/europe/italy-coronavirus-lockdown-europe-intl/index.html
(2020).
40. Attualita. Coronavirus: stop a pub, cinema, teatro e discoteche anche a Roma. Ecco cosa
prevede il nuovo decreto. Roma Today https://www.romatoday.it/attualita/coronavirus-pub-cinema-
teatri-locali-chiusi-nuovo-decreto.html (2020).
41. Gazzetta Ufficiale. DECRETO DEL PRESIDENTE DEL CONSIGLIO DEl MINISTRI. Gazzetta Ufflclale
https://www.gazzettaufficiale.it/eli/id/2020/03/08/20A01522/sg (2020).
42. Helsedirektoratet. The Norwegian Directorate of Health has issued a decision to close schools
and other educational institutions. Helsedirektoratet https://www.helsedirektoratet.no/nyheter/the-
norwegian-directorate-of—health-has-issued-a-decision-to-close-schools-and-other-educationa|-
institutions (2020).
43. Krostensen, Mette; Hellem-Hansen, Viktoria L.; Tandstad, B. Folkehelseinstituttet mener
23.000 kan vaere smittet. NRK https://www.nrk.no/norge/folkehelseinstituttet-mener-23.000-kan-
vaere-smittet-1.14958149 (2020).
44. Norweigen Government. The Government is establishing clear quarantine and isolation rules.
regjeringen.no https://www.regjeringen.no/en/aktuelt/the-government-is-establishing-clear-
quarantine-and-isolation-rules/id2693647/ (2020).
45. Wikipedia. 2020 coronavirus pandemic in Spain. Wikimedia Foundation
https://en.wikipedia.org/wiki/2020_coronavirus_pandemic_in_Spain.
46. Gabinete de Prensa. El Gobierno anuncia nuevas medidas para evitar la extension del nuevo
coronavirus COVID-19. Gobierno de Espana
https://www.mscbs.gob.es/gabinete/notasPrensa.do?id=4807 (2020).
47. Gabinete de Prensa. El Consejo Interterritorial del SNS acuerda medidas concretas para zonas
con transmision comunitaria significativa de coronavirus. Gobierno de Espana
https://www.mscbs.gob.es/gabinete/notasPrensa.do?id=4806 (2020).
48. Folkhalsomyndigheten. Larosaten och gymnasieskolor uppmanas nu att bedriva
distansundervisning. Folkhdlsomyndigheten https://www.folkhalsomyndigheten.se/nyheter-och-
press/nyhetsarkiv/2020/mars/larosaten-och-gymnasieskolor-uppmanas-nu-att-bedriva-
distansundervisning(2020).
49. The Local. Sweden bans large events to halt coronavirus spread. The Local
https://www.theloca|.se/20200311/sweden-to-ban-large-public-gatherings-over-coronavirus (2020).
50. Radosevich. Stockholmers urged to work from home as COVID-19 community spread
confirmed. Sveriges Radio
https://sverigesradio.se/sida/artikel.aspx?programid=2054&artikel=7430511(2020).
51. Folkhalsomyndigheten. Flera tecken p\aa samhallsspridning av covid-19 i Sverige.
Folkhdlsomyndigheten https://www.folkhalsomyndigheten.se/nyheter-och-
press/nyhetsarkiv/2020/mars/flera-tecken-pa-samhallsspridning-av-covid-19-i-sverige/ (2020).
52. Bundesamt fur Gesendheit BAG. Bundesrat verscharft Massnahmen gegen das Coronavirus
zum Schutz der Gesundheit und unterstUtzt betroffene Branchen. Schweizerische Eidgenossenschaft
https://www.bag.admin.ch/bag/de/home/das-bag/aktuell/medienmitteilungen.msg-id-78437.html
(20201
53. Bundesamt fur Gesundheit BAG. Coronavirus: Bundesrat verbietet Ansammlungen von mehr
als fUnf Personen. Schweizerische Eidgenossenschaft https://www.bag.admin.ch/bag/de/home/das-
bag/aktuell/medienmitteilungen.msg-id-78513.html (2020).
54. Bundesamt fur Gesundheit BAG. Coronavirus: Bundesrat erklart die «ausserordentliche Lage»
und verscharft die Massnahmen. Schweizerische Eidgenossenschaft
https://www.bag.admin.ch/bag/de/home/das-bag/aktuell/medienmitteilungen.msg-id-78454.html
(20201
55. Bundesamt fur Gesundheit BAG. Neue Hygiene- und Verhaltensregeln zum Schutz gegen das
neue Coronavirus. Schweizerische Eidgenossenschaft https://www.bag.admin.ch/bag/de/home/das-
bag/a ktuell/medienmitteilungen.msg-id-78304.html (2020).
56. UK Government, D. for E. Schools, colleges and early years settings to close. UK Government
https://www.gov.uk/government/news/schools-colleges-and-early-years-settings-to-close (2020).
57. UK Government. PM address to the nation on coronavirus: 23 March 2020. UK Government
https://www.gov.uk/government/speeches/pm-address-to-the-nation-on-coronavirus-23-march-
2020(20201
58. Boycott-Owen, Mason; Bowman, Verity; Kelly-Linden, Jordan; Gartner, A. G. H. S. T.
Coronavirus: Boris Johnson puts UK in lockdown as death tolls reaches 55. The Telegraph
https://www.telegraph.co.uk/global-health/science-and-disease/coronavirus-news-uk-latest-
update-covid-19-death-toll-cases/ (2020).
59. BBC News. Coronavirus: People with fever or ’continuous’ cough told to self—isolate. BBC News
https://www.bbc.co.uk/news/uk-51857856 (2020). | What is Spain's estimated mean percentage [95% credible interval] of total population infected as of 28th March? | false | 855 | {
"text": [
"3.1% [0.85%-8.4%]"
],
"answer_start": [
13284
]
} |
2,683 | Estimating the number of infections and the impact of non-
pharmaceutical interventions on COVID-19 in 11 European countries
30 March 2020 Imperial College COVID-19 Response Team
Seth Flaxmani Swapnil Mishra*, Axel Gandy*, H JulietteT Unwin, Helen Coupland, Thomas A Mellan, Harrison
Zhu, Tresnia Berah, Jeffrey W Eaton, Pablo N P Guzman, Nora Schmit, Lucia Cilloni, Kylie E C Ainslie, Marc
Baguelin, Isobel Blake, Adhiratha Boonyasiri, Olivia Boyd, Lorenzo Cattarino, Constanze Ciavarella, Laura Cooper,
Zulma Cucunuba’, Gina Cuomo—Dannenburg, Amy Dighe, Bimandra Djaafara, Ilaria Dorigatti, Sabine van Elsland,
Rich FitzJohn, Han Fu, Katy Gaythorpe, Lily Geidelberg, Nicholas Grassly, Wi|| Green, Timothy Hallett, Arran
Hamlet, Wes Hinsley, Ben Jeffrey, David Jorgensen, Edward Knock, Daniel Laydon, Gemma Nedjati—Gilani, Pierre
Nouvellet, Kris Parag, Igor Siveroni, Hayley Thompson, Robert Verity, Erik Volz, Caroline Walters, Haowei Wang,
Yuanrong Wang, Oliver Watson, Peter Winskill, Xiaoyue Xi, Charles Whittaker, Patrick GT Walker, Azra Ghani,
Christl A. Donnelly, Steven Riley, Lucy C Okell, Michaela A C Vollmer, NeilM.Ferguson1and Samir Bhatt*1
Department of Infectious Disease Epidemiology, Imperial College London
Department of Mathematics, Imperial College London
WHO Collaborating Centre for Infectious Disease Modelling
MRC Centre for Global Infectious Disease Analysis
Abdul LatifJameeI Institute for Disease and Emergency Analytics, Imperial College London
Department of Statistics, University of Oxford
*Contributed equally 1Correspondence: nei|[email protected], [email protected]
Summary
Following the emergence of a novel coronavirus (SARS-CoV-Z) and its spread outside of China, Europe
is now experiencing large epidemics. In response, many European countries have implemented
unprecedented non-pharmaceutical interventions including case isolation, the closure of schools and
universities, banning of mass gatherings and/or public events, and most recently, widescale social
distancing including local and national Iockdowns.
In this report, we use a semi-mechanistic Bayesian hierarchical model to attempt to infer the impact
of these interventions across 11 European countries. Our methods assume that changes in the
reproductive number— a measure of transmission - are an immediate response to these interventions
being implemented rather than broader gradual changes in behaviour. Our model estimates these
changes by calculating backwards from the deaths observed over time to estimate transmission that
occurred several weeks prior, allowing for the time lag between infection and death.
One of the key assumptions of the model is that each intervention has the same effect on the
reproduction number across countries and over time. This allows us to leverage a greater amount of
data across Europe to estimate these effects. It also means that our results are driven strongly by the
data from countries with more advanced epidemics, and earlier interventions, such as Italy and Spain.
We find that the slowing growth in daily reported deaths in Italy is consistent with a significant impact
of interventions implemented several weeks earlier. In Italy, we estimate that the effective
reproduction number, Rt, dropped to close to 1 around the time of Iockdown (11th March), although
with a high level of uncertainty.
Overall, we estimate that countries have managed to reduce their reproduction number. Our
estimates have wide credible intervals and contain 1 for countries that have implemented a||
interventions considered in our analysis. This means that the reproduction number may be above or
below this value. With current interventions remaining in place to at least the end of March, we
estimate that interventions across all 11 countries will have averted 59,000 deaths up to 31 March
[95% credible interval 21,000-120,000]. Many more deaths will be averted through ensuring that
interventions remain in place until transmission drops to low levels. We estimate that, across all 11
countries between 7 and 43 million individuals have been infected with SARS-CoV-Z up to 28th March,
representing between 1.88% and 11.43% ofthe population. The proportion of the population infected
to date — the attack rate - is estimated to be highest in Spain followed by Italy and lowest in Germany
and Norway, reflecting the relative stages of the epidemics.
Given the lag of 2-3 weeks between when transmission changes occur and when their impact can be
observed in trends in mortality, for most of the countries considered here it remains too early to be
certain that recent interventions have been effective. If interventions in countries at earlier stages of
their epidemic, such as Germany or the UK, are more or less effective than they were in the countries
with advanced epidemics, on which our estimates are largely based, or if interventions have improved
or worsened over time, then our estimates of the reproduction number and deaths averted would
change accordingly. It is therefore critical that the current interventions remain in place and trends in
cases and deaths are closely monitored in the coming days and weeks to provide reassurance that
transmission of SARS-Cov-Z is slowing.
SUGGESTED CITATION
Seth Flaxman, Swapnil Mishra, Axel Gandy et 0/. Estimating the number of infections and the impact of non—
pharmaceutical interventions on COVID—19 in 11 European countries. Imperial College London (2020), doi:
https://doi.org/10.25561/77731
1 Introduction
Following the emergence of a novel coronavirus (SARS-CoV-Z) in Wuhan, China in December 2019 and
its global spread, large epidemics of the disease, caused by the virus designated COVID-19, have
emerged in Europe. In response to the rising numbers of cases and deaths, and to maintain the
capacity of health systems to treat as many severe cases as possible, European countries, like those in
other continents, have implemented or are in the process of implementing measures to control their
epidemics. These large-scale non-pharmaceutical interventions vary between countries but include
social distancing (such as banning large gatherings and advising individuals not to socialize outside
their households), border closures, school closures, measures to isolate symptomatic individuals and
their contacts, and large-scale lockdowns of populations with all but essential internal travel banned.
Understanding firstly, whether these interventions are having the desired impact of controlling the
epidemic and secondly, which interventions are necessary to maintain control, is critical given their
large economic and social costs.
The key aim ofthese interventions is to reduce the effective reproduction number, Rt, ofthe infection,
a fundamental epidemiological quantity representing the average number of infections, at time t, per
infected case over the course of their infection. Ith is maintained at less than 1, the incidence of new
infections decreases, ultimately resulting in control of the epidemic. If Rt is greater than 1, then
infections will increase (dependent on how much greater than 1 the reproduction number is) until the
epidemic peaks and eventually declines due to acquisition of herd immunity.
In China, strict movement restrictions and other measures including case isolation and quarantine
began to be introduced from 23rd January, which achieved a downward trend in the number of
confirmed new cases during February, resulting in zero new confirmed indigenous cases in Wuhan by
March 19th. Studies have estimated how Rt changed during this time in different areas ofChina from
around 2-4 during the uncontrolled epidemic down to below 1, with an estimated 7-9 fold decrease
in the number of daily contacts per person.1'2 Control measures such as social distancing, intensive
testing, and contact tracing in other countries such as Singapore and South Korea have successfully
reduced case incidence in recent weeks, although there is a riskthe virus will spread again once control
measures are relaxed.3'4
The epidemic began slightly laterin Europe, from January or later in different regions.5 Countries have
implemented different combinations of control measures and the level of adherence to government
recommendations on social distancing is likely to vary between countries, in part due to different
levels of enforcement.
Estimating reproduction numbers for SARS-CoV-Z presents challenges due to the high proportion of
infections not detected by health systems”7 and regular changes in testing policies, resulting in
different proportions of infections being detected over time and between countries. Most countries
so far only have the capacity to test a small proportion of suspected cases and tests are reserved for
severely ill patients or for high-risk groups (e.g. contacts of cases). Looking at case data, therefore,
gives a systematically biased view of trends.
An alternative way to estimate the course of the epidemic is to back-calculate infections from
observed deaths. Reported deaths are likely to be more reliable, although the early focus of most
surveillance systems on cases with reported travel histories to China may mean that some early deaths
will have been missed. Whilst the recent trends in deaths will therefore be informative, there is a time
lag in observing the effect of interventions on deaths since there is a 2-3-week period between
infection, onset of symptoms and outcome.
In this report, we fit a novel Bayesian mechanistic model of the infection cycle to observed deaths in
11 European countries, inferring plausible upper and lower bounds (Bayesian credible intervals) of the
total populations infected (attack rates), case detection probabilities, and the reproduction number
over time (Rt). We fit the model jointly to COVID-19 data from all these countries to assess whether
there is evidence that interventions have so far been successful at reducing Rt below 1, with the strong
assumption that particular interventions are achieving a similar impact in different countries and that
the efficacy of those interventions remains constant over time. The model is informed more strongly
by countries with larger numbers of deaths and which implemented interventions earlier, therefore
estimates of recent Rt in countries with more recent interventions are contingent on similar
intervention impacts. Data in the coming weeks will enable estimation of country-specific Rt with
greater precision.
Model and data details are presented in the appendix, validation and sensitivity are also presented in
the appendix, and general limitations presented below in the conclusions.
2 Results
The timing of interventions should be taken in the context of when an individual country’s epidemic
started to grow along with the speed with which control measures were implemented. Italy was the
first to begin intervention measures, and other countries followed soon afterwards (Figure 1). Most
interventions began around 12th-14th March. We analyzed data on deaths up to 28th March, giving a
2-3-week window over which to estimate the effect of interventions. Currently, most countries in our
study have implemented all major non-pharmaceutical interventions.
For each country, we model the number of infections, the number of deaths, and Rt, the effective
reproduction number over time, with Rt changing only when an intervention is introduced (Figure 2-
12). Rt is the average number of secondary infections per infected individual, assuming that the
interventions that are in place at time t stay in place throughout their entire infectious period. Every
country has its own individual starting reproduction number Rt before interventions take place.
Specific interventions are assumed to have the same relative impact on Rt in each country when they
were introduced there and are informed by mortality data across all countries.
Figure l: Intervention timings for the 11 European countries included in the analysis. For further
details see Appendix 8.6.
2.1 Estimated true numbers of infections and current attack rates
In all countries, we estimate there are orders of magnitude fewer infections detected (Figure 2) than
true infections, mostly likely due to mild and asymptomatic infections as well as limited testing
capacity. In Italy, our results suggest that, cumulatively, 5.9 [1.9-15.2] million people have been
infected as of March 28th, giving an attack rate of 9.8% [3.2%-25%] of the population (Table 1). Spain
has recently seen a large increase in the number of deaths, and given its smaller population, our model
estimates that a higher proportion of the population, 15.0% (7.0 [18-19] million people) have been
infected to date. Germany is estimated to have one of the lowest attack rates at 0.7% with 600,000
[240,000-1,500,000] people infected.
Imperial College COVID-19 Response Team
Table l: Posterior model estimates of percentage of total population infected as of 28th March 2020.
Country % of total population infected (mean [95% credible intervall)
Austria 1.1% [0.36%-3.1%]
Belgium 3.7% [1.3%-9.7%]
Denmark 1.1% [0.40%-3.1%]
France 3.0% [1.1%-7.4%]
Germany 0.72% [0.28%-1.8%]
Italy 9.8% [3.2%-26%]
Norway 0.41% [0.09%-1.2%]
Spain 15% [3.7%-41%]
Sweden 3.1% [0.85%-8.4%]
Switzerland 3.2% [1.3%-7.6%]
United Kingdom 2.7% [1.2%-5.4%]
2.2 Reproduction numbers and impact of interventions
Averaged across all countries, we estimate initial reproduction numbers of around 3.87 [3.01-4.66],
which is in line with other estimates.1'8 These estimates are informed by our choice of serial interval
distribution and the initial growth rate of observed deaths. A shorter assumed serial interval results in
lower starting reproduction numbers (Appendix 8.4.2, Appendix 8.4.6). The initial reproduction
numbers are also uncertain due to (a) importation being the dominant source of new infections early
in the epidemic, rather than local transmission (b) possible under-ascertainment in deaths particularly
before testing became widespread.
We estimate large changes in Rt in response to the combined non-pharmaceutical interventions. Our
results, which are driven largely by countries with advanced epidemics and larger numbers of deaths
(e.g. Italy, Spain), suggest that these interventions have together had a substantial impact on
transmission, as measured by changes in the estimated reproduction number Rt. Across all countries
we find current estimates of Rt to range from a posterior mean of 0.97 [0.14-2.14] for Norway to a
posterior mean of2.64 [1.40-4.18] for Sweden, with an average of 1.43 across the 11 country posterior
means, a 64% reduction compared to the pre-intervention values. We note that these estimates are
contingent on intervention impact being the same in different countries and at different times. In all
countries but Sweden, under the same assumptions, we estimate that the current reproduction
number includes 1 in the uncertainty range. The estimated reproduction number for Sweden is higher,
not because the mortality trends are significantly different from any other country, but as an artefact
of our model, which assumes a smaller reduction in Rt because no full lockdown has been ordered so
far. Overall, we cannot yet conclude whether current interventions are sufficient to drive Rt below 1
(posterior probability of being less than 1.0 is 44% on average across the countries). We are also
unable to conclude whether interventions may be different between countries or over time.
There remains a high level of uncertainty in these estimates. It is too early to detect substantial
intervention impact in many countries at earlier stages of their epidemic (e.g. Germany, UK, Norway).
Many interventions have occurred only recently, and their effects have not yet been fully observed
due to the time lag between infection and death. This uncertainty will reduce as more data become
available. For all countries, our model fits observed deaths data well (Bayesian goodness of fit tests).
We also found that our model can reliably forecast daily deaths 3 days into the future, by withholding
the latest 3 days of data and comparing model predictions to observed deaths (Appendix 8.3).
The close spacing of interventions in time made it statistically impossible to determine which had the
greatest effect (Figure 1, Figure 4). However, when doing a sensitivity analysis (Appendix 8.4.3) with
uninformative prior distributions (where interventions can increase deaths) we find similar impact of
Imperial College COVID-19 Response Team
interventions, which shows that our choice of prior distribution is not driving the effects we see in the
main analysis.
Figure 2: Country-level estimates of infections, deaths and Rt. Left: daily number of infections, brown
bars are reported infections, blue bands are predicted infections, dark blue 50% credible interval (CI),
light blue 95% CI. The number of daily infections estimated by our model drops immediately after an
intervention, as we assume that all infected people become immediately less infectious through the
intervention. Afterwards, if the Rt is above 1, the number of infections will starts growing again.
Middle: daily number of deaths, brown bars are reported deaths, blue bands are predicted deaths, CI
as in left plot. Right: time-varying reproduction number Rt, dark green 50% CI, light green 95% CI.
Icons are interventions shown at the time they occurred.
Imperial College COVID-19 Response Team
Table 2: Totalforecasted deaths since the beginning of the epidemic up to 31 March in our model
and in a counterfactual model (assuming no intervention had taken place). Estimated averted deaths
over this time period as a result of the interventions. Numbers in brackets are 95% credible intervals.
2.3 Estimated impact of interventions on deaths
Table 2 shows total forecasted deaths since the beginning of the epidemic up to and including 31
March under ourfitted model and under the counterfactual model, which predicts what would have
happened if no interventions were implemented (and R, = R0 i.e. the initial reproduction number
estimated before interventions). Again, the assumption in these predictions is that intervention
impact is the same across countries and time. The model without interventions was unable to capture
recent trends in deaths in several countries, where the rate of increase had clearly slowed (Figure 3).
Trends were confirmed statistically by Bayesian leave-one-out cross-validation and the widely
applicable information criterion assessments —WA|C).
By comparing the deaths predicted under the model with no interventions to the deaths predicted in
our intervention model, we calculated the total deaths averted up to the end of March. We find that,
across 11 countries, since the beginning of the epidemic, 59,000 [21,000-120,000] deaths have been
averted due to interventions. In Italy and Spain, where the epidemic is advanced, 38,000 [13,000-
84,000] and 16,000 [5,400-35,000] deaths have been averted, respectively. Even in the UK, which is
much earlier in its epidemic, we predict 370 [73-1,000] deaths have been averted.
These numbers give only the deaths averted that would have occurred up to 31 March. lfwe were to
include the deaths of currently infected individuals in both models, which might happen after 31
March, then the deaths averted would be substantially higher.
Figure 3: Daily number of confirmed deaths, predictions (up to 28 March) and forecasts (after) for (a)
Italy and (b) Spain from our model with interventions (blue) and from the no interventions
counterfactual model (pink); credible intervals are shown one week into the future. Other countries
are shown in Appendix 8.6.
03/0 25% 50% 753% 100%
(no effect on transmissibility) (ends transmissibility
Relative % reduction in R.
Figure 4: Our model includes five covariates for governmental interventions, adjusting for whether
the intervention was the first one undertaken by the government in response to COVID-19 (red) or
was subsequent to other interventions (green). Mean relative percentage reduction in Rt is shown
with 95% posterior credible intervals. If 100% reduction is achieved, Rt = 0 and there is no more
transmission of COVID-19. No effects are significantly different from any others, probably due to the
fact that many interventions occurred on the same day or within days of each other as shown in
Figure l.
3 Discussion
During this early phase of control measures against the novel coronavirus in Europe, we analyze trends
in numbers of deaths to assess the extent to which transmission is being reduced. Representing the
COVlD-19 infection process using a semi-mechanistic, joint, Bayesian hierarchical model, we can
reproduce trends observed in the data on deaths and can forecast accurately over short time horizons.
We estimate that there have been many more infections than are currently reported. The high level
of under-ascertainment of infections that we estimate here is likely due to the focus on testing in
hospital settings rather than in the community. Despite this, only a small minority of individuals in
each country have been infected, with an attack rate on average of 4.9% [l.9%-ll%] with considerable
variation between countries (Table 1). Our estimates imply that the populations in Europe are not
close to herd immunity ("50-75% if R0 is 2-4). Further, with Rt values dropping substantially, the rate
of acquisition of herd immunity will slow down rapidly. This implies that the virus will be able to spread
rapidly should interventions be lifted. Such estimates of the attack rate to date urgently need to be
validated by newly developed antibody tests in representative population surveys, once these become
available.
We estimate that major non-pharmaceutical interventions have had a substantial impact on the time-
varying reproduction numbers in countries where there has been time to observe intervention effects
on trends in deaths (Italy, Spain). lfadherence in those countries has changed since that initial period,
then our forecast of future deaths will be affected accordingly: increasing adherence over time will
have resulted in fewer deaths and decreasing adherence in more deaths. Similarly, our estimates of
the impact ofinterventions in other countries should be viewed with caution if the same interventions
have achieved different levels of adherence than was initially the case in Italy and Spain.
Due to the implementation of interventions in rapid succession in many countries, there are not
enough data to estimate the individual effect size of each intervention, and we discourage attributing
associations to individual intervention. In some cases, such as Norway, where all interventions were
implemented at once, these individual effects are by definition unidentifiable. Despite this, while
individual impacts cannot be determined, their estimated joint impact is strongly empirically justified
(see Appendix 8.4 for sensitivity analysis). While the growth in daily deaths has decreased, due to the
lag between infections and deaths, continued rises in daily deaths are to be expected for some time.
To understand the impact of interventions, we fit a counterfactual model without the interventions
and compare this to the actual model. Consider Italy and the UK - two countries at very different stages
in their epidemics. For the UK, where interventions are very recent, much of the intervention strength
is borrowed from countries with older epidemics. The results suggest that interventions will have a
large impact on infections and deaths despite counts of both rising. For Italy, where far more time has
passed since the interventions have been implemented, it is clear that the model without
interventions does not fit well to the data, and cannot explain the sub-linear (on the logarithmic scale)
reduction in deaths (see Figure 10).
The counterfactual model for Italy suggests that despite mounting pressure on health systems,
interventions have averted a health care catastrophe where the number of new deaths would have
been 3.7 times higher (38,000 deaths averted) than currently observed. Even in the UK, much earlier
in its epidemic, the recent interventions are forecasted to avert 370 total deaths up to 31 of March.
4 Conclusion and Limitations
Modern understanding of infectious disease with a global publicized response has meant that
nationwide interventions could be implemented with widespread adherence and support. Given
observed infection fatality ratios and the epidemiology of COVlD-19, major non-pharmaceutical
interventions have had a substantial impact in reducing transmission in countries with more advanced
epidemics. It is too early to be sure whether similar reductions will be seen in countries at earlier
stages of their epidemic. While we cannot determine which set of interventions have been most
successful, taken together, we can already see changes in the trends of new deaths. When forecasting
3 days and looking over the whole epidemic the number of deaths averted is substantial. We note that
substantial innovation is taking place, and new more effective interventions or refinements of current
interventions, alongside behavioral changes will further contribute to reductions in infections. We
cannot say for certain that the current measures have controlled the epidemic in Europe; however, if
current trends continue, there is reason for optimism.
Our approach is semi-mechanistic. We propose a plausible structure for the infection process and then
estimate parameters empirically. However, many parameters had to be given strong prior
distributions or had to be fixed. For these assumptions, we have provided relevant citations to
previous studies. As more data become available and better estimates arise, we will update these in
weekly reports. Our choice of serial interval distribution strongly influences the prior distribution for
starting R0. Our infection fatality ratio, and infection-to-onset-to-death distributions strongly
influence the rate of death and hence the estimated number of true underlying cases.
We also assume that the effect of interventions is the same in all countries, which may not be fully
realistic. This assumption implies that countries with early interventions and more deaths since these
interventions (e.g. Italy, Spain) strongly influence estimates of intervention impact in countries at
earlier stages of their epidemic with fewer deaths (e.g. Germany, UK).
We have tried to create consistent definitions of all interventions and document details of this in
Appendix 8.6. However, invariably there will be differences from country to country in the strength of
their intervention — for example, most countries have banned gatherings of more than 2 people when
implementing a lockdown, whereas in Sweden the government only banned gatherings of more than
10 people. These differences can skew impacts in countries with very little data. We believe that our
uncertainty to some degree can cover these differences, and as more data become available,
coefficients should become more reliable.
However, despite these strong assumptions, there is sufficient signal in the data to estimate changes
in R, (see the sensitivity analysis reported in Appendix 8.4.3) and this signal will stand to increase with
time. In our Bayesian hierarchical framework, we robustly quantify the uncertainty in our parameter
estimates and posterior predictions. This can be seen in the very wide credible intervals in more recent
days, where little or no death data are available to inform the estimates. Furthermore, we predict
intervention impact at country-level, but different trends may be in place in different parts of each
country. For example, the epidemic in northern Italy was subject to controls earlier than the rest of
the country.
5 Data
Our model utilizes daily real-time death data from the ECDC (European Centre of Disease Control),
where we catalogue case data for 11 European countries currently experiencing the epidemic: Austria,
Belgium, Denmark, France, Germany, Italy, Norway, Spain, Sweden, Switzerland and the United
Kingdom. The ECDC provides information on confirmed cases and deaths attributable to COVID-19.
However, the case data are highly unrepresentative of the incidence of infections due to
underreporting as well as systematic and country-specific changes in testing.
We, therefore, use only deaths attributable to COVID-19 in our model; we do not use the ECDC case
estimates at all. While the observed deaths still have some degree of unreliability, again due to
changes in reporting and testing, we believe the data are ofsufficient fidelity to model. For population
counts, we use UNPOP age-stratified counts.10
We also catalogue data on the nature and type of major non-pharmaceutical interventions. We looked
at the government webpages from each country as well as their official public health
division/information webpages to identify the latest advice/laws being issued by the government and
public health authorities. We collected the following:
School closure ordered: This intervention refers to nationwide extraordinary school closures which in
most cases refer to both primary and secondary schools closing (for most countries this also includes
the closure of otherforms of higher education or the advice to teach remotely). In the case of Denmark
and Sweden, we allowed partial school closures of only secondary schools. The date of the school
closure is taken to be the effective date when the schools started to be closed (ifthis was on a Monday,
the date used was the one of the previous Saturdays as pupils and students effectively stayed at home
from that date onwards).
Case-based measures: This intervention comprises strong recommendations or laws to the general
public and primary care about self—isolation when showing COVID-19-like symptoms. These also
include nationwide testing programs where individuals can be tested and subsequently self—isolated.
Our definition is restricted to nationwide government advice to all individuals (e.g. UK) or to all primary
care and excludes regional only advice. These do not include containment phase interventions such
as isolation if travelling back from an epidemic country such as China.
Public events banned: This refers to banning all public events of more than 100 participants such as
sports events.
Social distancing encouraged: As one of the first interventions against the spread of the COVID-19
pandemic, many governments have published advice on social distancing including the
recommendation to work from home wherever possible, reducing use ofpublictransport and all other
non-essential contact. The dates used are those when social distancing has officially been
recommended by the government; the advice may include maintaining a recommended physical
distance from others.
Lockdown decreed: There are several different scenarios that the media refers to as lockdown. As an
overall definition, we consider regulations/legislations regarding strict face-to-face social interaction:
including the banning of any non-essential public gatherings, closure of educational and
public/cultural institutions, ordering people to stay home apart from exercise and essential tasks. We
include special cases where these are not explicitly mentioned on government websites but are
enforced by the police (e.g. France). The dates used are the effective dates when these legislations
have been implemented. We note that lockdown encompasses other interventions previously
implemented.
First intervention: As Figure 1 shows, European governments have escalated interventions rapidly,
and in some examples (Norway/Denmark) have implemented these interventions all on a single day.
Therefore, given the temporal autocorrelation inherent in government intervention, we include a
binary covariate for the first intervention, which can be interpreted as a government decision to take
major action to control COVID-19.
A full list of the timing of these interventions and the sources we have used can be found in Appendix
8.6.
6 Methods Summary
A Visual summary of our model is presented in Figure 5 (details in Appendix 8.1 and 8.2). Replication
code is available at https://github.com/|mperia|CollegeLondon/covid19model/releases/tag/vl.0
We fit our model to observed deaths according to ECDC data from 11 European countries. The
modelled deaths are informed by an infection-to-onset distribution (time from infection to the onset
of symptoms), an onset-to-death distribution (time from the onset of symptoms to death), and the
population-averaged infection fatality ratio (adjusted for the age structure and contact patterns of
each country, see Appendix). Given these distributions and ratios, modelled deaths are a function of
the number of infections. The modelled number of infections is informed by the serial interval
distribution (the average time from infection of one person to the time at which they infect another)
and the time-varying reproduction number. Finally, the time-varying reproduction number is a
function of the initial reproduction number before interventions and the effect sizes from
interventions.
Figure 5: Summary of model components.
Following the hierarchy from bottom to top gives us a full framework to see how interventions affect
infections, which can result in deaths. We use Bayesian inference to ensure our modelled deaths can
reproduce the observed deaths as closely as possible. From bottom to top in Figure 5, there is an
implicit lag in time that means the effect of very recent interventions manifest weakly in current
deaths (and get stronger as time progresses). To maximise the ability to observe intervention impact
on deaths, we fit our model jointly for all 11 European countries, which results in a large data set. Our
model jointly estimates the effect sizes of interventions. We have evaluated the effect ofour Bayesian
prior distribution choices and evaluate our Bayesian posterior calibration to ensure our results are
statistically robust (Appendix 8.4).
7 Acknowledgements
Initial research on covariates in Appendix 8.6 was crowdsourced; we thank a number of people
across the world for help with this. This work was supported by Centre funding from the UK Medical
Research Council under a concordat with the UK Department for International Development, the
NIHR Health Protection Research Unit in Modelling Methodology and CommunityJameel.
8 Appendix: Model Specifics, Validation and Sensitivity Analysis
8.1 Death model
We observe daily deaths Dam for days t E 1, ...,n and countries m E 1, ...,p. These daily deaths are
modelled using a positive real-Valued function dam = E(Dam) that represents the expected number
of deaths attributed to COVID-19. Dam is assumed to follow a negative binomial distribution with
The expected number of deaths (1 in a given country on a given day is a function of the number of
infections C occurring in previous days.
At the beginning of the epidemic, the observed deaths in a country can be dominated by deaths that
result from infection that are not locally acquired. To avoid biasing our model by this, we only include
observed deaths from the day after a country has cumulatively observed 10 deaths in our model.
To mechanistically link ourfunction for deaths to infected cases, we use a previously estimated COVID-
19 infection-fatality-ratio ifr (probability of death given infection)9 together with a distribution oftimes
from infection to death TE. The ifr is derived from estimates presented in Verity et al11 which assumed
homogeneous attack rates across age-groups. To better match estimates of attack rates by age
generated using more detailed information on country and age-specific mixing patterns, we scale
these estimates (the unadjusted ifr, referred to here as ifr’) in the following way as in previous work.4
Let Ca be the number of infections generated in age-group a, Na the underlying size of the population
in that age group and AR“ 2 Ca/Na the age-group-specific attack rate. The adjusted ifr is then given
by: ifra = fififié, where AR50_59 is the predicted attack-rate in the 50-59 year age-group after
incorporating country-specific patterns of contact and mixing. This age-group was chosen as the
reference as it had the lowest predicted level of underreporting in previous analyses of data from the
Chinese epidemic“. We obtained country-specific estimates of attack rate by age, AR“, for the 11
European countries in our analysis from a previous study which incorporates information on contact
between individuals of different ages in countries across Europe.12 We then obtained overall ifr
estimates for each country adjusting for both demography and age-specific attack rates.
Using estimated epidemiological information from previous studies,“'11 we assume TE to be the sum of
two independent random times: the incubation period (infection to onset of symptoms or infection-
to-onset) distribution and the time between onset of symptoms and death (onset-to-death). The
infection-to-onset distribution is Gamma distributed with mean 5.1 days and coefficient of variation
0.86. The onset-to-death distribution is also Gamma distributed with a mean of 18.8 days and a
coefficient of va riation 0.45. ifrm is population averaged over the age structure of a given country. The
infection-to-death distribution is therefore given by:
um ~ ifrm ~ (Gamma(5.1,0.86) + Gamma(18.8,0.45))
Figure 6 shows the infection-to-death distribution and the resulting survival function that integrates
to the infection fatality ratio.
Figure 6: Left, infection-to-death distribution (mean 23.9 days). Right, survival probability of infected
individuals per day given the infection fatality ratio (1%) and the infection-to-death distribution on
the left.
Using the probability of death distribution, the expected number of deaths dam, on a given day t, for
country, m, is given by the following discrete sum:
The number of deaths today is the sum of the past infections weighted by their probability of death,
where the probability of death depends on the number of days since infection.
8.2 Infection model
The true number of infected individuals, C, is modelled using a discrete renewal process. This approach
has been used in numerous previous studies13'16 and has a strong theoretical basis in stochastic
individual-based counting processes such as Hawkes process and the Bellman-Harris process.”18 The
renewal model is related to the Susceptible-Infected-Recovered model, except the renewal is not
expressed in differential form. To model the number ofinfections over time we need to specify a serial
interval distribution g with density g(T), (the time between when a person gets infected and when
they subsequently infect another other people), which we choose to be Gamma distributed:
g ~ Gamma (6.50.62).
The serial interval distribution is shown below in Figure 7 and is assumed to be the same for all
countries.
Figure 7: Serial interval distribution g with a mean of 6.5 days.
Given the serial interval distribution, the number of infections Eamon a given day t, and country, m,
is given by the following discrete convolution function:
_ t—1
Cam — Ram ZT=0 Cr,mgt—‘r r
where, similarto the probability ofdeath function, the daily serial interval is discretized by
fs+0.5
1.5
gs = T=s—0.Sg(T)dT fors = 2,3, and 91 = fT=Og(T)dT.
Infections today depend on the number of infections in the previous days, weighted by the discretized
serial interval distribution. This weighting is then scaled by the country-specific time-Varying
reproduction number, Ram, that models the average number of secondary infections at a given time.
The functional form for the time-Varying reproduction number was chosen to be as simple as possible
to minimize the impact of strong prior assumptions: we use a piecewise constant function that scales
Ram from a baseline prior R0,m and is driven by known major non-pharmaceutical interventions
occurring in different countries and times. We included 6 interventions, one of which is constructed
from the other 5 interventions, which are timings of school and university closures (k=l), self—isolating
if ill (k=2), banning of public events (k=3), any government intervention in place (k=4), implementing
a partial or complete lockdown (k=5) and encouraging social distancing and isolation (k=6). We denote
the indicator variable for intervention k E 1,2,3,4,5,6 by IkI’m, which is 1 if intervention k is in place
in country m at time t and 0 otherwise. The covariate ”any government intervention” (k=4) indicates
if any of the other 5 interventions are in effect,i.e.14’t’m equals 1 at time t if any of the interventions
k E 1,2,3,4,5 are in effect in country m at time t and equals 0 otherwise. Covariate 4 has the
interpretation of indicating the onset of major government intervention. The effect of each
intervention is assumed to be multiplicative. Ram is therefore a function ofthe intervention indicators
Ik’t’m in place at time t in country m:
Ram : R0,m eXp(— 212:1 O(Rheum)-
The exponential form was used to ensure positivity of the reproduction number, with R0,m
constrained to be positive as it appears outside the exponential. The impact of each intervention on
Ram is characterised by a set of parameters 0(1, ...,OL6, with independent prior distributions chosen
to be
ock ~ Gamma(. 5,1).
The impacts ock are shared between all m countries and therefore they are informed by all available
data. The prior distribution for R0 was chosen to be
R0,m ~ Normal(2.4, IKI) with K ~ Normal(0,0.5),
Once again, K is the same among all countries to share information.
We assume that seeding of new infections begins 30 days before the day after a country has
cumulatively observed 10 deaths. From this date, we seed our model with 6 sequential days of
infections drawn from cl’m,...,66’m~EXponential(T), where T~Exponential(0.03). These seed
infections are inferred in our Bayesian posterior distribution.
We estimated parameters jointly for all 11 countries in a single hierarchical model. Fitting was done
in the probabilistic programming language Stan,19 using an adaptive Hamiltonian Monte Carlo (HMC)
sampler. We ran 8 chains for 4000 iterations with 2000 iterations of warmup and a thinning factor 4
to obtain 2000 posterior samples. Posterior convergence was assessed using the Rhat statistic and by
diagnosing divergent transitions of the HMC sampler. Prior-posterior calibrations were also performed
(see below).
8.3 Validation
We validate accuracy of point estimates of our model using cross-Validation. In our cross-validation
scheme, we leave out 3 days of known death data (non-cumulative) and fit our model. We forecast
what the model predicts for these three days. We present the individual forecasts for each day, as
well as the average forecast for those three days. The cross-validation results are shown in the Figure
8.
Figure 8: Cross-Validation results for 3-day and 3-day aggregatedforecasts
Figure 8 provides strong empirical justification for our model specification and mechanism. Our
accurate forecast over a three-day time horizon suggests that our fitted estimates for Rt are
appropriate and plausible.
Along with from point estimates we all evaluate our posterior credible intervals using the Rhat
statistic. The Rhat statistic measures whether our Markov Chain Monte Carlo (MCMC) chains have
converged to the equilibrium distribution (the correct posterior distribution). Figure 9 shows the Rhat
statistics for all of our parameters
Figure 9: Rhat statistics - values close to 1 indicate MCMC convergence.
Figure 9 indicates that our MCMC have converged. In fitting we also ensured that the MCMC sampler
experienced no divergent transitions - suggesting non pathological posterior topologies.
8.4 SensitivityAnalysis
8.4.1 Forecasting on log-linear scale to assess signal in the data
As we have highlighted throughout in this report, the lag between deaths and infections means that
it ta kes time for information to propagate backwa rds from deaths to infections, and ultimately to Rt.
A conclusion of this report is the prediction of a slowing of Rt in response to major interventions. To
gain intuition that this is data driven and not simply a consequence of highly constrained model
assumptions, we show death forecasts on a log-linear scale. On this scale a line which curves below a
linear trend is indicative of slowing in the growth of the epidemic. Figure 10 to Figure 12 show these
forecasts for Italy, Spain and the UK. They show this slowing down in the daily number of deaths. Our
model suggests that Italy, a country that has the highest death toll of COVID-19, will see a slowing in
the increase in daily deaths over the coming week compared to the early stages of the epidemic.
We investigated the sensitivity of our estimates of starting and final Rt to our assumed serial interval
distribution. For this we considered several scenarios, in which we changed the serial interval
distribution mean, from a value of 6.5 days, to have values of 5, 6, 7 and 8 days.
In Figure 13, we show our estimates of R0, the starting reproduction number before interventions, for
each of these scenarios. The relative ordering of the Rt=0 in the countries is consistent in all settings.
However, as expected, the scale of Rt=0 is considerably affected by this change — a longer serial
interval results in a higher estimated Rt=0. This is because to reach the currently observed size of the
epidemics, a longer assumed serial interval is compensated by a higher estimated R0.
Additionally, in Figure 14, we show our estimates of Rt at the most recent model time point, again for
each ofthese scenarios. The serial interval mean can influence Rt substantially, however, the posterior
credible intervals of Rt are broadly overlapping.
Figure 13: Initial reproduction number R0 for different serial interval (SI) distributions (means
between 5 and 8 days). We use 6.5 days in our main analysis.
Figure 14: Rt on 28 March 2020 estimated for all countries, with serial interval (SI) distribution means
between 5 and 8 days. We use 6.5 days in our main analysis.
8.4.3 Uninformative prior sensitivity on or
We ran our model using implausible uninformative prior distributions on the intervention effects,
allowing the effect of an intervention to increase or decrease Rt. To avoid collinearity, we ran 6
separate models, with effects summarized below (compare with the main analysis in Figure 4). In this
series of univariate analyses, we find (Figure 15) that all effects on their own serve to decrease Rt.
This gives us confidence that our choice of prior distribution is not driving the effects we see in the
main analysis. Lockdown has a very large effect, most likely due to the fact that it occurs after other
interventions in our dataset. The relatively large effect sizes for the other interventions are most likely
due to the coincidence of the interventions in time, such that one intervention is a proxy for a few
others.
Figure 15: Effects of different interventions when used as the only covariate in the model.
8.4.4
To assess prior assumptions on our piecewise constant functional form for Rt we test using a
nonparametric function with a Gaussian process prior distribution. We fit a model with a Gaussian
process prior distribution to data from Italy where there is the largest signal in death data. We find
that the Gaussian process has a very similartrend to the piecewise constant model and reverts to the
mean in regions of no data. The correspondence of a completely nonparametric function and our
piecewise constant function suggests a suitable parametric specification of Rt.
Nonparametric fitting of Rf using a Gaussian process:
8.4.5 Leave country out analysis
Due to the different lengths of each European countries’ epidemic, some countries, such as Italy have
much more data than others (such as the UK). To ensure that we are not leveraging too much
information from any one country we perform a ”leave one country out” sensitivity analysis, where
we rerun the model without a different country each time. Figure 16 and Figure 17 are examples for
results for the UK, leaving out Italy and Spain. In general, for all countries, we observed no significant
dependence on any one country.
Figure 16: Model results for the UK, when not using data from Italy for fitting the model. See the
Figure 17: Model results for the UK, when not using data from Spain for fitting the model. See caption
of Figure 2 for an explanation of the plots.
8.4.6 Starting reproduction numbers vs theoretical predictions
To validate our starting reproduction numbers, we compare our fitted values to those theoretically
expected from a simpler model assuming exponential growth rate, and a serial interval distribution
mean. We fit a linear model with a Poisson likelihood and log link function and extracting the daily
growth rate r. For well-known theoretical results from the renewal equation, given a serial interval
distribution g(r) with mean m and standard deviation 5, given a = mZ/S2 and b = m/SZ, and
a
subsequently R0 = (1 + %) .Figure 18 shows theoretically derived R0 along with our fitted
estimates of Rt=0 from our Bayesian hierarchical model. As shown in Figure 18 there is large
correspondence between our estimated starting reproduction number and the basic reproduction
number implied by the growth rate r.
R0 (red) vs R(FO) (black)
Figure 18: Our estimated R0 (black) versus theoretically derived Ru(red) from a log-linear
regression fit.
8.5 Counterfactual analysis — interventions vs no interventions
Figure 19: Daily number of confirmed deaths, predictions (up to 28 March) and forecasts (after) for
all countries except Italy and Spain from our model with interventions (blue) and from the no
interventions counterfactual model (pink); credible intervals are shown one week into the future.
DOI: https://doi.org/10.25561/77731
Page 28 of 35
30 March 2020 Imperial College COVID-19 Response Team
8.6 Data sources and Timeline of Interventions
Figure 1 and Table 3 display the interventions by the 11 countries in our study and the dates these
interventions became effective.
Table 3: Timeline of Interventions.
Country Type Event Date effective
School closure
ordered Nationwide school closures.20 14/3/2020
Public events
banned Banning of gatherings of more than 5 people.21 10/3/2020
Banning all access to public spaces and gatherings
Lockdown of more than 5 people. Advice to maintain 1m
ordered distance.22 16/3/2020
Social distancing
encouraged Recommendation to maintain a distance of 1m.22 16/3/2020
Case-based
Austria measures Implemented at lockdown.22 16/3/2020
School closure
ordered Nationwide school closures.23 14/3/2020
Public events All recreational activities cancelled regardless of
banned size.23 12/3/2020
Citizens are required to stay at home except for
Lockdown work and essential journeys. Going outdoors only
ordered with household members or 1 friend.24 18/3/2020
Public transport recommended only for essential
Social distancing journeys, work from home encouraged, all public
encouraged places e.g. restaurants closed.23 14/3/2020
Case-based Everyone should stay at home if experiencing a
Belgium measures cough or fever.25 10/3/2020
School closure Secondary schools shut and universities (primary
ordered schools also shut on 16th).26 13/3/2020
Public events Bans of events >100 people, closed cultural
banned institutions, leisure facilities etc.27 12/3/2020
Lockdown Bans of gatherings of >10 people in public and all
ordered public places were shut.27 18/3/2020
Limited use of public transport. All cultural
Social distancing institutions shut and recommend keeping
encouraged appropriate distance.28 13/3/2020
Case-based Everyone should stay at home if experiencing a
Denmark measures cough or fever.29 12/3/2020
School closure
ordered Nationwide school closures.30 14/3/2020
Public events
banned Bans of events >100 people.31 13/3/2020
Lockdown Everybody has to stay at home. Need a self-
ordered authorisation form to leave home.32 17/3/2020
Social distancing
encouraged Advice at the time of lockdown.32 16/3/2020
Case-based
France measures Advice at the time of lockdown.32 16/03/2020
School closure
ordered Nationwide school closures.33 14/3/2020
Public events No gatherings of >1000 people. Otherwise
banned regional restrictions only until lockdown.34 22/3/2020
Lockdown Gatherings of > 2 people banned, 1.5 m
ordered distance.35 22/3/2020
Social distancing Avoid social interaction wherever possible
encouraged recommended by Merkel.36 12/3/2020
Advice for everyone experiencing symptoms to
Case-based contact a health care agency to get tested and
Germany measures then self—isolate.37 6/3/2020
School closure
ordered Nationwide school closures.38 5/3/2020
Public events
banned The government bans all public events.39 9/3/2020
Lockdown The government closes all public places. People
ordered have to stay at home except for essential travel.40 11/3/2020
A distance of more than 1m has to be kept and
Social distancing any other form of alternative aggregation is to be
encouraged excluded.40 9/3/2020
Case-based Advice to self—isolate if experiencing symptoms
Italy measures and quarantine if tested positive.41 9/3/2020
Norwegian Directorate of Health closes all
School closure educational institutions. Including childcare
ordered facilities and all schools.42 13/3/2020
Public events The Directorate of Health bans all non-necessary
banned social contact.42 12/3/2020
Lockdown Only people living together are allowed outside
ordered together. Everyone has to keep a 2m distance.43 24/3/2020
Social distancing The Directorate of Health advises against all
encouraged travelling and non-necessary social contacts.42 16/3/2020
Case-based Advice to self—isolate for 7 days if experiencing a
Norway measures cough or fever symptoms.44 15/3/2020
ordered Nationwide school closures.45 13/3/2020
Public events
banned Banning of all public events by lockdown.46 14/3/2020
Lockdown
ordered Nationwide lockdown.43 14/3/2020
Social distancing Advice on social distancing and working remotely
encouraged from home.47 9/3/2020
Case-based Advice to self—isolate for 7 days if experiencing a
Spain measures cough or fever symptoms.47 17/3/2020
School closure
ordered Colleges and upper secondary schools shut.48 18/3/2020
Public events
banned The government bans events >500 people.49 12/3/2020
Lockdown
ordered No lockdown occurred. NA
People even with mild symptoms are told to limit
Social distancing social contact, encouragement to work from
encouraged home.50 16/3/2020
Case-based Advice to self—isolate if experiencing a cough or
Sweden measures fever symptoms.51 10/3/2020
School closure
ordered No in person teaching until 4th of April.52 14/3/2020
Public events
banned The government bans events >100 people.52 13/3/2020
Lockdown
ordered Gatherings of more than 5 people are banned.53 2020-03-20
Advice on keeping distance. All businesses where
Social distancing this cannot be realised have been closed in all
encouraged states (kantons).54 16/3/2020
Case-based Advice to self—isolate if experiencing a cough or
Switzerland measures fever symptoms.55 2/3/2020
Nationwide school closure. Childminders,
School closure nurseries and sixth forms are told to follow the
ordered guidance.56 21/3/2020
Public events
banned Implemented with lockdown.57 24/3/2020
Gatherings of more than 2 people not from the
Lockdown same household are banned and police
ordered enforceable.57 24/3/2020
Social distancing Advice to avoid pubs, clubs, theatres and other
encouraged public institutions.58 16/3/2020
Case-based Advice to self—isolate for 7 days if experiencing a
UK measures cough or fever symptoms.59 12/3/2020
9 References
1. Li, R. et al. Substantial undocumented infection facilitates the rapid dissemination of novel
coronavirus (SARS-CoV2). Science (2020) doi:10.1126/science.abb3221.
2. Zhang, J. et al. Patterns of human social contact and contact with animals in Shanghai, China.
5cLRep.9,1—11(2019)
3. Worldometers.info. Hong Kong: coronavirus cases.
https://www.wo rldometers.info/co ronavirus/country/china-hong-kong-sar/.
4. Ferguson, N. et al. Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19
mortality and healthcare demand (Report 9). https://www.imperial.ac.uk/mrc-global-infectious-
disease-analysis/news--wuhan-coronavirus/.
5. Cereda, D. et al. The early phase of the COVID-19 outbreak in Lombardy, Italy. arXiv (2020).
6. Zhao, A. J. et al. Title: Antibody responses to SARS-CoV-2 in patients of novel coronavirus
disease 2019 Brief Title : Antibody responses in COVID-19 patients. (2020).
7. Jombart, T. et al. Inferring the number of COVID-19 cases from recently reported deaths.
medRXiV 2020.03.10.20033761(2020)doi:10.1101/2020.03.10.20033761.
8. Zhang, J. et al. Age profile of susceptibility, mixing, and social distancing shape the dynamics
of the novel coronavirus disease 2019 outbreak in China. (2020) doi:10.1101/2020.03.19.20039107.
9. Lourenco, J. et al. Fundamental principles of epidemic spread highlight the immediate need
for large-scale serological surveys to assess the stage of the SARS-CoV-2 epidemic.
doi:10.1101/2020.03.24.20042291
10. United Nations, Department of Economic and Social Affairs, Population Division. World
Population Prospects 2019: Data Booket. ST/ESA/SER.A/424. (2019).
11. Verity, R. et al. Estimates ofthe severity of COVID-19 disease. Lancet Infect Dis in press, (2020).
12. Walker, P. G. T. et al. Report 12: The Global Impact of COVID-19 and Strategies for Mitigation
and Suppression.
13. Fraser, C. Estimating Individual and Household Reproduction Numbers in an Emerging
Epidemic. PL05 ONE 2, e758 (2007).
14. Cori, A., Ferguson, N. M., Fraser, C. & Cauchemez, S. A New Framework and Software to
Estimate Time-Varying Reproduction Numbers During Epidemics. Am. J. Epidemiol. 178, 1505—1512
(20131
15. Nouvellet, P. et al. A simple approach to measure transmissibility and forecast incidence.
Epidemics 22, 29—35 (2018).
16. Cauchemez, 8., Valleron, A. J., Boelle, P. Y., Flahault, A. & Ferguson, N. M. Estimating the
impact of school closure on influenza transmission from Sentinel data. Nature 452, 750—754 (2008).
17. Bellman, R. & Harris, T. On Age-Dependent Binary Branching Processes. Ann. Math. 55, 280—
295(19521
18. Bellman, R. & Harris, T. E. On the Theory of Age-Dependent Stochastic Branching Processes.
Proc. Natl. Acad. Sci. 34, 601—604 (1948).
19. Stan Development Team. 2018. The Stan Core Library, Version 2.18.0. http://mc-stan.org.
20. Bundesministerium. Coronavirus (COVID-19): Status quo — Schulen, Hochschulen,
Universitaten und Forschungsinstitutionen.
https://www.bmbwf.gv.at/Ministerium/Informationspflicht/corona/corona_status.html.
21. Henley, J. Coronavirus: EU states enact tough measures to stem spread. The Guardian
https://www.theguardian.com/world/2020/mar/10/coronavirus-several-eu-states-ban-mass-events-
after-italian-lockdown (2020).
22. Bundesministerium. Coronavirus - Aktuelle MaBnahmen.
https://www.sozialministerium.at/Informationen-zum-Coronavirus/Coronavirus—Aktuelle-
MaBnahmen.html (2020).
23. Federal Public Service. Coronavirus : Phase 2 maintained, transition to the federal phase and
additional measures. https://www.info-coronavirus.be/en/2020/03/12/phase-2-maintained-
transition-to-the-federal-phase-and-additional-measures/ (2020).
24. Belgium.be. Coronavirus: reinforced measures | Belgium.be.
https://www.belgium.be/en/news/2020/coronavirus_reinforced_measures (2020).
25. Federal Public Service. Protect yourself and protect the others. https://www.info-
coronavirus.be/en/2020/03/10/protect-yourself—and-protect-the-others/ (2020).
26. Wikipedia. 2020 coronavirus pandemic in Denmark. Wikimedia Foundation
https://en.wikipedia.org/wiki/2020_coronavirus_pandemic_in_Denmark.
27. Stephensen, Emma K|inker; Hansen, T. S. Danmark lukker ned: Her er regeringens nye tiltag.
TV2 https://nyheder.tv2.dk/samfund/2020-03-11-danmark-lukker-ned-her-er-regeringens-nye-tiltag
(20201
28. Politi. Nye tiltag mod covid-19. Politi https://politi.dk/coronavirus-i-danmark/seneste-nyt-fra-
myndighederne/nye-tiltag-mod-covid-19 (2020).
29. Styrelsen for Patientsikkerhed. Indberetning om covid-19zlnformation om mulighed for
p\aabud til enkeltpersoner (coronavirus/covid-19). https://stps.dk/da/ansvar-og-
retningslinjer/vejledning/indberetning-om-covid-19/#.
30. Wikipedia. 2020 coronavirus pandemic in France. Wikimedia Foundation
https://en.wikipedia.org/wiki/2020_coronavirus_pandemic_in_France.
31. The Local. France bans gatherings of more than 100 people as coronavirus death toll rises -
The Local. The Local https://www.thelocal.fr/20200313/france-bans-gatherings-of—over-100-people-
to-fight-coronavirus-pandemic (2020).
32. Henley, Jon; Willsher, Kim; Kassam, A. Coronavirus: France imposes lockdown as EU calls for
30-day travel ban. The Guardian https://www.theguardian.com/world/2020/mar/16/coronavirus-
spain-takes-over-private-healthcare-amid-more-european-lockdowns (2020).
33. Wikipedia. 2020 coronavirus pandemic in Germany. Wikimedia Foundation
https://en.wikipedia.org/wiki/2020_coronavirus_pandemic_in_Germany.
34. BMI. Coronavirus: Fragen und Antworten. Bundesministerium des Innern,fur Bau und Heimat
https://web.archive.org/web/20200317073042/https://www.bmi.bund.de/SharedDocs/faqs/DE/the
men/bevoelkerungsschutz/coronavirus/coronavirus-faqs.htmI#doc13738352bodyText7.
35. BBC News. Coronavirus: Germany tightens curbs and bans meetings of more than two. BBC
News https://www.bbc.co.uk/news/world-europe-51999080 (2020).
36. Bundesregierung. Kanzlerin trifft Regierungschefs der Lander Sozialkontakte vermeiden,
Ausbreitung verlangsamen. https://www.bundesregierung.de/breg-de/themen/coronavirus/mpk-
1730186(2020)
37. Robert Koch Institut. Antworten auf haufig gestellte Fragen zum Coronavirus SARS-CoV-2.
Robert Koch Institut
https://web.archive.org/web/20200312004624/https://www.rki.de/SharedDocs/FAQ/NCOV2019/F
AQ_Liste.html (2020).
38. Ministero della Salute. Governo annuncia sospensione dell’attivita didattica dal 5 a|15 marzo.
Ministero della Salute
http://www.salute.gov.it/portale/nuovocoronavirus/dettaglioVideoNuovoCoronavirus.jsp?lingua=ita
liano&menu=multimedia&p=video&id=2052 (2020).
39. CNN. Italy prohibits travel and cancels all public events in its northern region. CNN
https://edition.cnn.com/2020/03/08/europe/italy-coronavirus-lockdown-europe-intl/index.html
(2020).
40. Attualita. Coronavirus: stop a pub, cinema, teatro e discoteche anche a Roma. Ecco cosa
prevede il nuovo decreto. Roma Today https://www.romatoday.it/attualita/coronavirus-pub-cinema-
teatri-locali-chiusi-nuovo-decreto.html (2020).
41. Gazzetta Ufficiale. DECRETO DEL PRESIDENTE DEL CONSIGLIO DEl MINISTRI. Gazzetta Ufflclale
https://www.gazzettaufficiale.it/eli/id/2020/03/08/20A01522/sg (2020).
42. Helsedirektoratet. The Norwegian Directorate of Health has issued a decision to close schools
and other educational institutions. Helsedirektoratet https://www.helsedirektoratet.no/nyheter/the-
norwegian-directorate-of—health-has-issued-a-decision-to-close-schools-and-other-educationa|-
institutions (2020).
43. Krostensen, Mette; Hellem-Hansen, Viktoria L.; Tandstad, B. Folkehelseinstituttet mener
23.000 kan vaere smittet. NRK https://www.nrk.no/norge/folkehelseinstituttet-mener-23.000-kan-
vaere-smittet-1.14958149 (2020).
44. Norweigen Government. The Government is establishing clear quarantine and isolation rules.
regjeringen.no https://www.regjeringen.no/en/aktuelt/the-government-is-establishing-clear-
quarantine-and-isolation-rules/id2693647/ (2020).
45. Wikipedia. 2020 coronavirus pandemic in Spain. Wikimedia Foundation
https://en.wikipedia.org/wiki/2020_coronavirus_pandemic_in_Spain.
46. Gabinete de Prensa. El Gobierno anuncia nuevas medidas para evitar la extension del nuevo
coronavirus COVID-19. Gobierno de Espana
https://www.mscbs.gob.es/gabinete/notasPrensa.do?id=4807 (2020).
47. Gabinete de Prensa. El Consejo Interterritorial del SNS acuerda medidas concretas para zonas
con transmision comunitaria significativa de coronavirus. Gobierno de Espana
https://www.mscbs.gob.es/gabinete/notasPrensa.do?id=4806 (2020).
48. Folkhalsomyndigheten. Larosaten och gymnasieskolor uppmanas nu att bedriva
distansundervisning. Folkhdlsomyndigheten https://www.folkhalsomyndigheten.se/nyheter-och-
press/nyhetsarkiv/2020/mars/larosaten-och-gymnasieskolor-uppmanas-nu-att-bedriva-
distansundervisning(2020).
49. The Local. Sweden bans large events to halt coronavirus spread. The Local
https://www.theloca|.se/20200311/sweden-to-ban-large-public-gatherings-over-coronavirus (2020).
50. Radosevich. Stockholmers urged to work from home as COVID-19 community spread
confirmed. Sveriges Radio
https://sverigesradio.se/sida/artikel.aspx?programid=2054&artikel=7430511(2020).
51. Folkhalsomyndigheten. Flera tecken p\aa samhallsspridning av covid-19 i Sverige.
Folkhdlsomyndigheten https://www.folkhalsomyndigheten.se/nyheter-och-
press/nyhetsarkiv/2020/mars/flera-tecken-pa-samhallsspridning-av-covid-19-i-sverige/ (2020).
52. Bundesamt fur Gesendheit BAG. Bundesrat verscharft Massnahmen gegen das Coronavirus
zum Schutz der Gesundheit und unterstUtzt betroffene Branchen. Schweizerische Eidgenossenschaft
https://www.bag.admin.ch/bag/de/home/das-bag/aktuell/medienmitteilungen.msg-id-78437.html
(20201
53. Bundesamt fur Gesundheit BAG. Coronavirus: Bundesrat verbietet Ansammlungen von mehr
als fUnf Personen. Schweizerische Eidgenossenschaft https://www.bag.admin.ch/bag/de/home/das-
bag/aktuell/medienmitteilungen.msg-id-78513.html (2020).
54. Bundesamt fur Gesundheit BAG. Coronavirus: Bundesrat erklart die «ausserordentliche Lage»
und verscharft die Massnahmen. Schweizerische Eidgenossenschaft
https://www.bag.admin.ch/bag/de/home/das-bag/aktuell/medienmitteilungen.msg-id-78454.html
(20201
55. Bundesamt fur Gesundheit BAG. Neue Hygiene- und Verhaltensregeln zum Schutz gegen das
neue Coronavirus. Schweizerische Eidgenossenschaft https://www.bag.admin.ch/bag/de/home/das-
bag/a ktuell/medienmitteilungen.msg-id-78304.html (2020).
56. UK Government, D. for E. Schools, colleges and early years settings to close. UK Government
https://www.gov.uk/government/news/schools-colleges-and-early-years-settings-to-close (2020).
57. UK Government. PM address to the nation on coronavirus: 23 March 2020. UK Government
https://www.gov.uk/government/speeches/pm-address-to-the-nation-on-coronavirus-23-march-
2020(20201
58. Boycott-Owen, Mason; Bowman, Verity; Kelly-Linden, Jordan; Gartner, A. G. H. S. T.
Coronavirus: Boris Johnson puts UK in lockdown as death tolls reaches 55. The Telegraph
https://www.telegraph.co.uk/global-health/science-and-disease/coronavirus-news-uk-latest-
update-covid-19-death-toll-cases/ (2020).
59. BBC News. Coronavirus: People with fever or ’continuous’ cough told to self—isolate. BBC News
https://www.bbc.co.uk/news/uk-51857856 (2020). | What term describes when a majority of the population has built an immunity to a virus? | false | 819 | {
"text": [
"herd immunity"
],
"answer_start": [
7235
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} |
188 | The Battle Against Coronavirus Disease 2019 (COVID-19): Emergency Management
and Infection Control in a Radiology Department
https://www.jacr.org/article/S1546-1440(20)30285-4/pdf
Journal Pre-proof
Zixing Huang, Shuang Zhao, Zhenlin Li, Weixia Chen, Lihong Zhao, Lipeng Deng, Bin
Song
PII: S1546-1440(20)30285-4
DOI: https://doi.org/10.1016/j.jacr.2020.03.011
Reference: JACR 5139
To appear in: Journal of the American College of Radiology
Received Date: 24 February 2020
Revised Date: 13 March 2020
Accepted Date: 15 March 2020
Please cite this article as: Huang Z, Zhao S, Li Z, Chen W, Zhao L, Deng L, Song B, The Battle Against
Coronavirus Disease 2019 (COVID-19): Emergency Management and Infection Control in a Radiology
Department, Journal of the American College of Radiology (2020), doi: https://doi.org/10.1016/
j.jacr.2020.03.011.
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition
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© 2020 Published by Elsevier Inc. on behalf of American College of Radiology
The Battle Against Coronavirus Disease 2019 (COVID-19): Emergency Management
and Infection Control in a Radiology Department
Zixing Huang*, Shuang Zhao*, Zhenlin Li, Weixia Chen, Lihong Zhao, Lipeng Deng,
Bin Song
Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
*Zixing Huang and Shuang Zhao contributed equally to this work as co-first author.
Corresponding Author: Bin Song, MD
Address: Department of Radiology, West China Hospital, Sichuan University.
No. 37, GUOXUE Alley, Chengdu, 610041, China
Tel.: (+86)28 85423680, Fax: (+86)28 85582944
Email: [email protected].
Authors’ contributions
ZXH: conceived the study and drafted the manuscript.
ZS: conceived the study and drafted the manuscript.
ZLL: The member of the emergency management and infection control team (EMICT)
and was involved in the formulation of the measures.
WXC: The member of the EMICT and was involved in the formulation of the
measures.
LHZ: The member of the EMICT and was involved in the formulation of the
measures.
LPD: The member of the EMICT and was involved in the formulation of the
measures.
BS: Leader of the EMICT, conceived the study and reviewed the manuscript.
All authors read and approved the final manuscript.
The authors declare no conflict of interest.
The authors declare that they had full access to all of the data in this study and the
authors take complete responsibility for the integrity of the data and the accuracy of
the data analysis
1
The Battle Against Novel Coronavirus Pneumonia (COVID-19): Emergency
Management and Infection Control in a Radiology Department
Abstract
Objective: To describe the strategy and the emergency management and infection control
procedure of our radiology department during the COVID-19 outbreak.
Methods: We set up emergency management and sensing control teams. The team formulated
various measures: reconfiguration of the radiology department, personal protection and training
of staff, examination procedures for patients suspected of or confirmed with COVID-19 as well
as patients without an exposure history or symptoms. Those with suspected or confirmed
COVID-19 infection were scanned in the designated fever-CT unit.
Results: From January 21, 2020 to March 9, 2020, 3,083 people suspected of or confirmed with
COVID-19 underwent fever-CT examinations. Including initial examinations and
reexaminations, the total number of fever-CT examinations numbered 3,340. As a result of our
precautions, none of the staff of the radiology department were infected with COVID-19.
Conclusion: Strategic planning and adequate protections can help protect patients and staff
against a highly infectious disease while maintaining function at a high volume capacity.
Keywords: Coronavirus, COVID-19, novel coronavirus pneumonia, infection control
2
Introduction
The whole world has been closely focusing on an outbreak of respiratory disease caused by a
novel coronavirus that was first reported in Wuhan, China, on December 31, 2019, and that
continues to spread. On February 11, 2020, the World Health Organization (WHO) named the
disease “coronavirus disease 2019” (COVID-19).
As of 24:00 on March 11, 2020, the National Health Commission (NHC) had received reports
of 80,793 confirmed cases and 3,169 deaths on the Chinese mainland. There remain 14,831
confirmed cases (including 4,257 in serious condition) and 253 suspected cases still
hospitalized. To date, 677,243 people have been identified as having had close contact with
infected patients of whom13,701 are under medical observation [1]. Outside China, 44,067
laboratory-confirmed cases and 1,440 deaths have occurred in 117 countries /territories/areas
according to the WHO [2]. COVID-19 poses significant threats to international health. Like the
flu, COVID-19 is thought to spread mainly from person-to-person between people who are in
close contact with one another through respiratory droplets produced when an infected person
coughs or sneezes. In light of the infectious nature of this disease, healthcare workers are at
high risk of infection of COVID-19. In China, healthcare workers account for 1,716 confirmed
cases of COVID-19, including six deaths [3].
Computed tomography (CT) can play a role in both diagnosing and categorizing
COVID-19 on the basis of case definitions issued by the WHO and the treatment guidelines
from the NHC [4]. Suspected patients having the virus may undergo chest CT. Isolation and
barrier procedures are necessary to protect both the department staff and other patients in the
hospital. Note should be made that due to overlap of imaging findings with other respiratory
3
diseases, CT is not helpful as a screening tool. But it can help identify the degree of pulmonary
involvement and disease course.
Our hospital is a national regional medical center with 4,300 beds and a tertiary referral
center in Sichuan province. The initial response started on January 21, 2020, after transmission
of COVID-19 was confirmed to be human-to-human on January 20, 2020. The first suspected
case of COVID-19 in Sichuan province was reported on January 21, 2020. The Sichuan
provincial government immediately launched the first-level response to major public health
emergencies. On the same day, our hospital was designated to care for Sichuan province
patients with COVID-19.
This article describes the emergency management procedure of our radiology department
for situations involving severe infectious diseases, such as COVID-19, and the
infection-protection experience of the department staff.
Methods
The hospital provided personal protective equipment (medical protective clothing,
surgical cap, N95 mask, gloves, face shields, and goggles) to all its healthcare staff, erected
three medical tents (fever tents) for screening of fever cases in the parking lot of the emergency
department, planned an examination route and examination area for patients suspected of
harboring the virus, and placed confirmed patients in an isolation ward. “Fever” was the
colloquial term used to designate suspected COVID-19 based on symptoms such as a fever or
with an epidemiological history of a potential exposure as well as those with confirmed
COVID-19 referred for treatment. Further, during outbreak, emergency and outpatient patients
4
without fever were asked for information such as epidemiological history and sent to fever tents
as long as they met suspected criteria.
The radiology department has 65 diagnostic radiologists and 161 other staff members
(trained technologists, nurses, engineers, and support staff). The equipment of the radiology
department includes 12 magnetic resonance (MR) scanners, 14 CT scanners, 15 digital
subtraction angiography (DSA) systems, 32 sets of digital radiography (DR) systems
(including nine mobile bedside DR sets), and 130 imaging diagnostic workstations for picture
archiving and communication systems (PACS). Most of the equipment is distributed among
four buildings at the hospital main campus. 4 CT scanners, 4 MR scanners, 1 DR are located on
the first floor of the first inpatient building, and 9 DR and 8 DSA are located on the second
floor. 1 CT and 1 MR scanner are located in the third inpatient building. 1 CT and 1 MR scanner
are located in the sixth inpatient building. 2 CT scanners, 2 MR scanners and 7 DSA are located
in the technical building. The rest of the equipment is located in the seventh inpatient building
in the branch campus.
The first inpatient building, located next to the emergency department, was reconfigured to
handle cases of COVID-19. Fever tents were set up by the emergency department in the
emergency department parking lot to separate normal emergency patients from patients with
symptoms or exposure history suspicious of COVID-19. We established separate means of
access between fever tents and between the fever examination area of the radiology department
to avoid cross-contamination.
The emergency management and infection control measures, as described below and
implemented in the radiology department during the outbreak, have been approved by the
5
infection control committee of hospital. These measures are in accordance with relevant laws
and regulations, in order to protect patients as well as the staff.
Radiology Emergency Management and Infection Control Team (EMICT)
The radiology department director chaired the EMICT. Its members include the deputy
director, chief technologist, head nurse, equipment engineer supervisor, and infection control
nurse of the radiology department. Team responsibilities included (1) coordination between the
hospital’s management and planning of infection control and radiology departments; (2)
collection of the most up-to-date protection-related information to educate and train staff in the
department; (3) reallocation of staff according to the actual situation; (4) establishment of the
CT procedures for patients with COVID-19; and (5) establishment of an emergency
management plan for the radiology department to ensure that the department would run
normally.
Suspected patients
The suspected patients were identified according to the Diagnosis and Treatment Program of
the Novel Coronavirus Pneumonia of the NHC [5], mainly based on epidemiological history.
Reconfiguration of the radiology department
The radiology department was divided into four areas [6]: contaminated, semicontaminated,
buffer, and clean areas (Figure 1). The contaminated area is connected to the fever clinic and
includes the fever accessway, the CT examination room, and the DR examination room for
6
confirmed and suspected cases. One CT scanner and one DR system closest to the emergency
department are designated the fever-CT and fever-DR to examine patients with suspected and
confirmed COVID-19. There is a separate dedicated access between the contaminated area and
the fever screening tents. The semicontaminated area includes the fever-CT control room,
fever-DR control room, and other patient examination access areas. The buffer zone includes
access areas for medical personnel and a dressing area for technologists. The clean area
includes the administrative office and the diagnostic room.
The contaminated area was isolated from other areas using physical barricades.
Directional signs were newly installed to guide patients and staff.
Personal protection and training of staff
For providing care for patients with confirmed and suspected COVID-19, all hospital staff
are required to wear complete personal protective equipment [7]: medical protective clothing,
surgical cap, N95 mask, gloves, face shields, and goggles. Wearing and removing of the
equipment must be performed in accordance with the procedures and under the supervision of
the infection control nurse.
Because staff members working in the contaminated area are under much situational
pressure, periodically taking time off could lower their physical and mental stress levels. The
technologists on fever-CT duty shifts are provided a break once a week for four hours. In
addition, the health of staff in the contaminated area must be monitored closely for the
symptoms of COVID-19. Pregnant staff must be assigned to the clean area.
7
The EMICT formulates and continually updates guidelines and educates all staff for West
China Hospital of Sichuan University. The EMICT training for staff is mainly involves
documents regarding infection control and CT findings of COVID-19 and maintains an EMICT
WeChat group for West China Hospital of Sichuan University. WeChat is the most widely used
social media app in China. The EMICT releases the latest national and hospital-based
information regarding COVID-19, guidance documents, and other notices from the hospital
and radiology department in the WeChat group on a daily basis. Staff can also report to the
EMICT in the WeChat group any time. Protocols for each modality and infection control
instructions are posted on the walls in all examination rooms. The EMICT periodically reminds
staff to undertake personal measures to reduce infection, such as wearing masks at all instances
in the radiology department and N95 masks if working in the contaminated area; not touching
the mask and the eyes; practicing hand hygiene; facing away from colleagues when eating,
drinking, and talking; and not using personal cell phones while on duty.
In addition, the chief thoracic radiologist provided lectures on all radiologists and
technologists on typical CT findings of COVID-19 infection using materials developed in
Wuhan, the epicenter of the outbreak in China.
CT examination procedures
There are two sets of procedures for CT examination: the fever-CT procedure and routine CT
procedure for those not suspected of COVID-19.
The fever-CT procedure for suspected or confirmed COVID-19 (Figure 2)
8
Before the fever-CT technologist operates the equipment, he or she should wear personal
protective equipment according to three-level protection standard [8]. Before the CT
examination of patients with suspected and confirmed COVID-19 begins, the fever tent or
isolation ward notifies the radiologist in advance. The fever-CT technologist checks the
equipment and prepares to disinfect the imaging equipment immediately after the examination.
The patient enters the fever-CT waiting area through the fever access area. If the patient
can get onto and off the examination table by themselves, the patient is allowed to do so. If the
patient cannot get onto or off the examination table independently, the person accompanying
the patient assists the patient, rather than the technologist. The technologist checks the patient
information and, using an intercom system in the examination room, asks the patient to remove
any metal ornaments on the neck and chest. Also, by intercom, the technologist trains the
patient to hold his or her breath during the examination.
The technologist uses a low-dose chest CT protocol to scan the patient. After scanning, the
original images are reconstructed as 1 mm-thick layers. The technologist browses the images to
ensure that their quality meets the diagnostic requirements and then guides the patient to leave
through the fever access area. The disposable sheets for patient examination are changed after
each patient. The equipment is disinfected according to the procedure below.
To protect themselves, the technologists assigned to the fever-CT wear N95 mask and
other personal protection as established by the EMICT.
The CT procedure for regular patients (figure.3)
9
Some patients with COVID-19 have no symptoms, and they may call at the general clinic for
other reasons. The following CT procedure is applicable under these circumstances:
When the patient makes an appointment for examination, the staff asks the patient about
their epidemiological history, symptoms, and signs. If suspected criteria are met, the patient
will be sent to the fever tent for further screening. When a patient presents to the radiology
department entrance, his/her temperature is measured. If the temperature is higher than 37.2 , ℃
the patient is sent to the fever tent for further investigation.
Those with no exposure history, suspicious symptoms or fever are screened in one of the
non-contaminated CT scanners. The technologists assigned to these scanners wear surgical
masks. All patients and the person accompanying them are required to wear surgical masks.
After the CT examination, the technologist browses the images quickly. If the CT appearance is
typical of lung infection, the technologist immediately reports it to the chest radiologist on duty
and asks the patient to wait in the CT examination room. If the chest radiologist does not
suspect COVID-19 infection, the patient can leave the CT examination room. If the chest
radiologist does suspect COVID-19 infection, the technologist immediately reports it to the
EMICT and sends the patient to the fever tent. The floor and equipment in the CT examination
room are disinfected according to regulations, and air disinfection is conducted for 30 min
before examining other patients. These CT scanners are considered noncontaminated (not
fever-CTs) after these sterilization procedures.
Fever-DR examination procedure
10
The COVID-19 guideline of the NHC does not recommend chest DR because its ability in
diagnosing COVID-19 is limited. At our hospital, we only use mobile DR units to provide
bedside examination for critically ill patients. The technologist operating the mobile DR
wears personal protective equipment according to the three-level protection standard and
sterilizes the mobile DR according to the ward management requirements as described below.
Equipment and environment disinfection procedures
Routine disinfection procedure [9]
1) Object surface disinfection: Object surface is wiped with 1000mg/L chlorine-containing
disinfectant, wipe twice with 75% ethanol for non-corrosion resistance, once /4 hours.
2) Equipment disinfection: The equipment in the contaminated area are wiped with
2000mg/L chlorine-containing disinfectant. The DR and CT gantry in the contaminated
area are wiped with 75% ethanol. The equipment in the buffer area is wiped with
500-1000mg/L chlorine-containing disinfectant or alcohol-containing disposable
disinfectant wipes twice a day.
3) Air disinfection: Turning off all central air conditioners to prevent air contamination with
each other. Polluted area: open the door for ventilation, each time more than 30 minutes,
once /4 hours; The air sterilizer is continuously sterilized or the ultraviolet ray is
continuously used in the unmanned state for 60 minutes, four times a day, remembered to
close the inner shielding door when air disinfection. Other ambient air is sprayed with
1000mg/L chlorine-containing disinfectant and ventilated twice a day
4) Ground disinfection: The ground is wiped with 1000mg/L chlorine-containing
disinfectant, once /4 hours.
5) When contaminated, disinfect at any time. In case of visible contamination, disposable
absorbent materials should be used first to completely remove the pollutants, and then a
cloth soaked with 2000mg/L chlorine-containing disinfectant should be used for 30
minutes before wiping.
11
Fever-CT disinfection procedures after examination
In addition to the above, disinfect the examination bed and ground with chlorinated disinfectant
containing 2000mg/L [10].
Noncontaminated CT disinfection procedures after suspected COVID-19 case examination
In addition to the above routine disinfection procedure, air disinfection is conducted for 30 min
before examining other patients.
Results
From January 21, 2020 when screening for epidemiological history or symptoms
suspicious for COVID-19, to March 9, 2020, our hospital screened a total of 7,203 individuals
and confirmed 24 cases of COVID-19. Of these, 3,083 people underwent fever-CT
examinations. Including the initial examination and reexamination, the total number of fever
CT examination numbered 3,340. The fever-CT scanned a patient approximately every 21.5
minutes. As a result of our precautions, none of the staff of the radiology department developed
symptoms suspicious for COVID-19. The fever-CT technologist, with the highest probability
of exposure, remains PCR negative.
Discussion
It has been 17 years since the severe acute respiratory syndrome (SARS) epidemic, the last
national spread of severe infectious disease, broke out. Currently, the Chinese people are
panicking again. The speed and extent by which COVID-19 has spread in 2 months are
12
unprecedented, beyond those of SARS, and this has been aided by its contagious nature and
rapid spread via droplets and contact. The droplet mode of transmission means that a person can
be infected easily by means of casual contact or even fomites on contaminated environmental
surfaces. Another theory has yet to be proved: aerosol propagation.
How radiology departments respond to any infectious disease outbreak is determined
primarily by the estimated risk of cross-infection to the staff and other patients. Appropriate
precautions taken only by staff in direct contact with patients may be adequate when the risk is
low. The strongest measures need to be implemented to limit the spread of the disease when the
risk is high. With severe infectious diseases such as COVID-19, the highest level of infection
control measures must be implemented; these include providing adequate standard protective
equipment, training staff, and instituting proper emergency plans.
Once a contagious infectious disease has been identified, the EMICT must consider four
main areas of response: data gathering, collaboration, needs assessment, and expert advice [10].
Data gathering includes dissemination of up-to-date case definitions and information about
confirmatory tests to all staff with direct patient contact to allow appropriate barrier precautions
to be taken. All typical and atypical imaging features of the disease should be made known to
all radiologists to assist in recognition of the disease on images and to allow accurate reporting
of these findings. We have stored images of all probable cases of COVID-19 in the PACS so
that these images were readily available for any radiologist to review, and images from
previous imaging studies are also available for comparison.
Collaboration with the radiology departments of other hospitals is very important because
patients may initially present to different centers, depending on geographic location and travel
13
distance. These patients may be few in number at a single hospital, but if data from patients at
several hospitals are available, a more accurate overall understanding of both imaging features
and epidemiology can be achieved. Dissemination of this information to all healthcare facilities
will also lead to early recognition of the disease, and appropriate isolation measures may be
instituted.
The Internet and social media apps, especially WeChat, have been used for distribution of
medical information, and because the exchange of information regarding infectious disease
outbreaks is almost instantaneous, it is an indispensable tool for radiologists. In fact, within a
month of the outbreak, the hospital that received the most infected patients from the source of
the outbreak made a PowerPoint presentation of the CT manifestations of COVID-19, which
was shared via WeChat and disseminated across the country in a very short time. Subsequently,
COVID-19-teaching PowerPoint presentations from various hospitals appeared and were
quickly shared via WeChat.
Our diagnostic process is limited as chest CT along is not diagnostic of COVID-19
because of lack of imaging specificity. But when combined with other epidemiological,
clinical, laboratory and virus nucleic acid information, typical chest CT imaging findings are
helpful for making the diagnosis. In our opinion, the major role of chest CT is to understand the
extent and dynamic evolution of lung lesions induced by COVID-19. The reasons why we
adopted the low-dose chest CT scan protocol are as follows: low-dose chest CT has been
widely used in the screening of early lung cancer. It is well known that many early lung cancers
are ground-glass opacities (GGO), so we believe that low-dose screening is also applicable for
COVID-19. In addition, considering the rapid development of COVID-19, many CT
14
examinations may be conducted in the same individual to monitor disease progress. Low-dose
scanning can reduce the radiation damage to patients.
Although the processes we established minimized the exposure of hospital staff, ancillary
personnel and other patients, it remains limited as follows. Sichuan province is not the center of
the epidemic. The number of patients with COVID-19 whom we have treated has not been
high, and most cases are from other provinces of China. However, we believe that our
experience in management, the reconfiguration of our radiology department, and the workflow
changes implemented in the current COVID-19 situation are useful for other radiology
departments that must prepare for dealing with patients with COVID-19. While no radiology
personnel developed symptoms suspicious for or were confirmed as having COVID-19, there
may be asymptomatic personnel.
REFERENCES
1. National Health Commission of the People’s Republic of China.(2020). March 12: Daily briefing
on novel coronavirus cases in China. Retrieved from
http://en.nhc.gov.cn/2020-03/12/c_77618.htm. Accessed March 11, 2020.
2. World Health Organization. (2020). Coronavirus disease 2019 (COVID-19) Situation Report-52.
Retrieved from
https://www.who.int/docs/default-source/coronaviruse/20200312-sitrep-52-covid-19.pdf?sfvrsn=e
2bfc9c0_2 9. Accessed March 11, 2020.
3. National Health Commission of the People’s Republic of China.(2020). Latest developments in
epidemic control on Feb 15. Retrieved from http://en.nhc.gov.cn/2020-02/16/c_76622. Accessed
March 11, 2020.
15
4. Health Commission of the People’s Republic of China.(2020). The notification of the trial
operation based on the guideline version 6 in the coronavirus disease diagnosis and treatment.
Retrieved from
http://www.nhc.gov.cn/xcs/zhengcwj/202002/8334a8326dd94d329df351d7da8aefc2.shtml.
Accessed March 11, 2020
5. Health Commission of the People’s Republic of China.(2020). The notification of the trial
operation based on the guideline version 6 in the coronavirus disease diagnosis and treatment.
Retrieved from
http://www.nhc.gov.cn/xcs/zhengcwj/202002/8334a8326dd94d329df351d7da8aefc2.shtml.
Accessed March 11, 2020.
6. Health Commission of the People’s Republic of China.(2009). The guideline for pathogens
isolated operations in hospital. Retrieved from
http://www.nhc.gov.cn/wjw/s9496/200904/40116.shtml. Accessed March 11, 2020.
7. Health Commission of the People’s Republic of China.(2017). The guideline for prevention and
control of hospital acquired infections of airborne pathogens. Retrieved from
http://www.nhc.gov.cn/wjw/s9496/201701/7e0e8fc6725843aabba8f841f2f585d2.shtml. Accessed
March 11, 2020.
8. Health Commission of the People’s Republic of China.(2017). The guideline for prevention and
control of hospital acquired infections of airborne pathogens. Retrieved from
http://www.nhc.gov.cn/wjw/s9496/201701/7e0e8fc6725843aabba8f841f2f585d2.shtml. Accessed
March 11, 2020.
9. Health Commission of the People’s Republic of China.(2012). The standardization for
sterilization techniques in hospital. Retrieved from
http://www.nhc.gov.cn/wjw/s9496/201204/54510.shtml. Accessed March 11, 2020.
10. Health Commission of the People’s Republic of China.(2012). The standardization for
sterilization techniques in hospital. Retrieved from
http://www.nhc.gov.cn/wjw/s9496/201204/54510.shtml. Accessed March 11, 2020.
11. Katona P. Bioterrorism Preparedness: Generic Blueprint for Health Departments, Hospitals, and
Physicians. Infectious Diseases in Clinical Practice. 2002;11(3):115-122. Accessed March 11,
2020.
16
Figure Legends
Figure 1. Diagram of the layout of our radiology department was divided into four areas: contaminated
(shaded in black), semicontaminated (shaded in dark gray), buffer (shaded in light gray), and clean areas
(shaded in white). The contaminated area was separated from other areas by barriers.
Figure 2. Diagram shows CT protocol for suspected and confirmed patients with COVID-19.
Figure 3. Diagram shows CT protocol for regular patients.
Abbreviations:
COVID-19: coronavirus disease 2019
CT: computed tomography
DR: digital radiography
EMICT: emergency management and infection control team
NHC: National Health Commission
PACS: picture archiving and communication system
SARS: severe acute respiratory syndrome
Sentence Summary
With severe infectious diseases such as COVID-19, the highest level of infection control
measures must be implemented, collaboration with the radiology departments of other
hospitals be needed, and social media be employed.
Take-home points
1. To response to a community infection emergency, a special emergency management team
needs to be setup at the departmental level to implement infection containment and
control procedures that continues to allow the imaging examination and imaging
diagnosis of those with suspected infection, and to prevent intra-departmental spreading
of infection (EMICT).
2. Infection control measures, such as reconfiguration of department areas, personal
protection and anti-infection training of all staff, standardized procedures including
contact minimization for chest CT and DR examinations, and timely disinfection of CT
and DR examination rooms, should be implemented properly.
3. If there are more than one scanner in a hospital, only one of them should be assigned to
suspected cases. | Who must be assigned to the clean area? | false | 2,456 | {
"text": [
"Pregnant staff"
],
"answer_start": [
12636
]
} |
2,486 | Potential Rapid Diagnostics, Vaccine and Therapeutics for 2019 Novel Coronavirus (2019-nCoV): A Systematic Review
https://doi.org/10.3390/jcm9030623
SHA: 9b0c87f808b1b66f2937d7a7acb524a756b6113b
Authors: Pang, Junxiong; Wang, Min Xian; Ang, Ian Yi Han; Tan, Sharon Hui Xuan; Lewis, Ruth Frances; Chen, Jacinta I. Pei; Gutierrez, Ramona A.; Gwee, Sylvia Xiao Wei; Chua, Pearleen Ee Yong; Yang, Qian; Ng, Xian Yi; Yap, Rowena K. S.; Tan, Hao Yi; Teo, Yik Ying; Tan, Chorh Chuan; Cook, Alex R.; Yap, Jason Chin-Huat; Hsu, Li Yang
Date: 2020
DOI: 10.3390/jcm9030623
License: cc-by
Abstract: Rapid diagnostics, vaccines and therapeutics are important interventions for the management of the 2019 novel coronavirus (2019-nCoV) outbreak. It is timely to systematically review the potential of these interventions, including those for Middle East respiratory syndrome-Coronavirus (MERS-CoV) and severe acute respiratory syndrome (SARS)-CoV, to guide policymakers globally on their prioritization of resources for research and development. A systematic search was carried out in three major electronic databases (PubMed, Embase and Cochrane Library) to identify published studies in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Supplementary strategies through Google Search and personal communications were used. A total of 27 studies fulfilled the criteria for review. Several laboratory protocols for confirmation of suspected 2019-nCoV cases using real-time reverse transcription polymerase chain reaction (RT-PCR) have been published. A commercial RT-PCR kit developed by the Beijing Genomic Institute is currently widely used in China and likely in Asia. However, serological assays as well as point-of-care testing kits have not been developed but are likely in the near future. Several vaccine candidates are in the pipeline. The likely earliest Phase 1 vaccine trial is a synthetic DNA-based candidate. A number of novel compounds as well as therapeutics licensed for other conditions appear to have in vitro efficacy against the 2019-nCoV. Some are being tested in clinical trials against MERS-CoV and SARS-CoV, while others have been listed for clinical trials against 2019-nCoV. However, there are currently no effective specific antivirals or drug combinations supported by high-level evidence.
Text: Since mid-December 2019 and as of early February 2020, the 2019 novel coronavirus (2019-nCoV) originating from Wuhan (Hubei Province, China) has infected over 25,000 laboratory-confirmed cases across 28 countries with about 500 deaths (a case-fatality rate of about 2%). More than 90% of the cases and deaths were in China [1] . Based on the initial reported surge of cases in Wuhan, the majority were males with a median age of 55 years and linked to the Huanan Seafood Wholesale Market [2] . Most of the reported cases had similar symptoms at the onset of illness such as fever, cough, and myalgia or fatigue. Most cases developed pneumonia and some severe and even fatal respiratory diseases such as acute respiratory distress syndrome [3] .
The 2019 novel coronavirus (2019-nCoV), a betacoronavirus, forms a clade within the subgenus sarbecovirus of the Orthocoronavirinae subfamily [4] . The severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) are also betacoronaviruses that are zoonotic in origin and have been linked to potential fatal illness during the outbreaks in 2003 and 2012, respectively [5, 6] . Based on current evidence, pathogenicity for 2019-nCoV is about 3%, which is significantly lower than SARS-CoV (10%) and MERS-CoV (40%) [7] . However, 2019-nCoV has potentially higher transmissibility (R0: 1.4-5.5) than both SARS-CoV (R0: [2] [3] [4] [5] and MERS-CoV (R0: <1) [7] .
With the possible expansion of 2019-nCoV globally [8] and the declaration of the 2019-nCoV outbreak as a Public Health Emergency of International Concern by the World Health Organization, there is an urgent need for rapid diagnostics, vaccines and therapeutics to detect, prevent and contain 2019-nCoV promptly. There is however currently a lack of understanding of what is available in the early phase of 2019-nCoV outbreak. The systematic review describes and assesses the potential rapid diagnostics, vaccines and therapeutics for 2019-nCoV, based in part on the developments for MERS-CoV and SARS-CoV.
A systematic search was carried out in three major electronic databases (PubMed, Embase and Cochrane Library) to identify published studies examining the diagnosis, therapeutic drugs and vaccines for Severe Acute Respiratory Syndrome (SARS), Middle East Respiratory Syndrome (MERS) and the 2019 novel coronavirus (2019-nCoV), in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.
There were two independent reviewers each focusing on SARS, MERS, and 2019-nCoV, respectively. A third independent reviewer was engaged to resolve any conflicting article of interest. We used the key words "SARS", "coronavirus", "MERS", "2019 Novel coronavirus", "Wuhan virus" to identify the diseases in the search strategy. The systematic searches for diagnosis, therapeutic drugs and vaccines were carried out independently and the key words "drug", "therapy", "vaccine", "diagnosis", "point of care testing" and "rapid diagnostic test" were used in conjunction with the disease key words for the respective searches.
Examples of search strings can be found in Table S1 . We searched for randomized controlled trials (RCTs) and validation trials (for diagnostics test) published in English, that measured (a) the sensitivity and/or specificity of a rapid diagnostic test or a point-of-care testing kit, (b) the impact of drug therapy or (c) vaccine efficacy against either of these diseases with no date restriction applied. For the 2019-nCoV, we searched for all in vitro, animal, or human studies published in English between 1 December 2019 and 6 February 2020, on the same outcomes of interest. In addition, we reviewed the references of retrieved articles in order to identify additional studies or reports not retrieved by the initial searches. Studies that examined the mechanisms of diagnostic tests, drug therapy or vaccine efficacy against SARS, MERS and 2019-nCoV were excluded. A Google search for 2019-nCoV diagnostics (as of 6 February 2020; Table S2 ) yielded five webpage links from government and international bodies with official information and guidelines (WHO, Europe CDC, US CDC, US FDA), three webpage links on diagnostic protocols and scientific commentaries, and five webpage links on market news and press releases. Six protocols for diagnostics using reverse transcriptase polymerase chain reaction (RT-PCR) from six countries were published on WHO's website [9] . Google search for 2019-nCoV vaccines yielded 19 relevant articles.
With the emergence of 2019-nCoV, real time RT-PCR remains the primary means for diagnosing the new virus strain among the many diagnostic platforms available ( [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] ; Table S3 ). Among the 16 diagnostics studies selected, one study discussed the use of RT-PCR in diagnosing patients with 2019-nCoV [11] ( Table 1 ). The period and type of specimen collected for RT-PCR play an important role in the diagnosis of 2019-nCoV. It was found that the respiratory specimens were positive for the virus while serum was negative in the early period. It has also suggested that in the early days of illness, patients have high levels of virus despite the mild symptoms.
Apart from the commonly used RT-PCR in diagnosing MERS-CoV, four studies identified various diagnostic methods such as reverse transcription loop-mediated isothermal amplification (RT-LAMP), RT-insulated isothermal PCR (RT-iiPCR) and a one-step rRT-PCR assay based on specific TaqMan probes. RT-LAMP has similar sensitivity as real time RT-PCR. It is also highly specific and is used to detect MERS-CoV. It is comparable to the usual diagnostic tests and is rapid, simple and convenient. Likewise, RT-iiPCR and a one-step rRT-PCR assay have also shown similar sensitivity and high specificity for MER-CoV. Lastly, one study focused on the validation of the six commercial real RT-PCR kits, with high accuracy. Although real time RT-PCR is a primary method for diagnosing MERS-CoV, high levels of PCR inhibition may hinder PCR sensitivity (Table 1) .
There are eleven studies that focus on SARS-CoV diagnostic testing (Table 1) . These papers described diagnostic methods to detect the virus with the majority of them using molecular testing for diagnosis. Comparison between the molecular test (i.e RT-PCR) and serological test (i.e., ELISA) showed that the molecular test has better sensitivity and specificity. Hence, enhancements to the current molecular test were conducted to improve the diagnosis. Studies looked at using nested PCR to include a pre-amplification step or incorporating N gene as an additional sensitive molecular marker to improve on the sensitivity (Table 1 ).
In addition, there are seven potential rapid diagnostic kits (as of 24 January 2020; Table 2 ) available on the market for 2019-nCoV. Six of these are only for research purposes. Only one kit from Beijing Genome Institute (BGI) is approved for use in the clinical setting for rapid diagnosis. Most of the kits are for RT-PCR. There were two kits (BGI, China and Veredus, Singapore) with the capability to detect multiple pathogens using sequencing and microarray technologies, respectively. The limit of detection of the enhanced realtime PCR method was 10 2 -fold higher than the standard real-time PCR assay and 10 7fold higher than conventional PCR methods In the clinical aspect, the enhanced realtime PCR method was able to detect 6 cases of SARS-CoV positive samples that were not confirmed by any other assay [25] • The real time PCR has a threshold sensitivity of 10 genome equivalents per reaction and it has a good reproducibility with the inter-assay coefficients of variation of 1.73 to 2.72%. • 13 specimens from 6 patients were positive with viral load range from 362 to 36,240,000 genome equivalents/mL. The real-time RT-PCR reaction was more sensitive than the nested PCR reaction, as the detection limit for the nested PCR reaction was about 10 3 genome equivalents in the standard cDNA control. [34] Real-time reverse-transcription PCR (rRT-PCR); RNA-dependent RNA polymerase (RdRp); open reading frame 1a (ORF1a); Loop-mediated isothermal amplification (LAMP); enzyme-linked immunosorbent assay (ELISA); immunofluorescent assay (IFA); immunochromatographic test (ICT); nasopharyngeal aspirate (NPA).
With the emergence of 2019-nCoV, there are about 15 potential vaccine candidates in the pipeline globally (Table 3 ), in which a wide range of technology (such as messenger RNA, DNA-based, nanoparticle, synthetic and modified virus-like particle) was applied. It will likely take about a year for most candidates to start phase 1 clinical trials except for those funded by Coalition for Epidemic Preparedness Innovations (CEPI). However, the kit developed by the BGI have passed emergency approval procedure of the National Medical Products Administration, and are currently used in clinical and surveillance centers of China [40] .
Of the total of 570 unique studies on 2019-nCoV, SARS CoV or MERS-CoV vaccines screened, only four were eventually included in the review. Most studies on SARS and MERS vaccines were excluded as they were performed in cell or animal models ( Figure 1 ). The four studies included in this review were Phase I clinical trials on SARS or MERS vaccines (Table 4 ) [44] [45] [46] [47] . There were no studies of any population type (cell, animal, human) on the 2019-nCoV at the point of screening. The published clinical trials were mostly done in United States except for one on the SARS vaccine done in China [44] . All vaccine candidates for SARS and MERS were reported to be safe, well-tolerated and able to trigger the relevant and appropriate immune responses in the participants. In addition, we highlight six ongoing Phase I clinical trials identified in the ClinicalTrials.gov register ( [48, 49] ); Table S4 ) [50] [51] [52] . These trials are all testing the safety and immunogenicity of their respective MERS-CoV vaccine candidates but were excluded as there are no results published yet. The trials are projected to complete in December 2020 (two studies in Russia [50, 51] ) and December 2021 (in Germany [52] ).
Existing literature search did not return any results on completed 2019-nCoV trials at the time of writing. Among 23 trials found from the systematic review (Table 5) , there are nine clinical trials registered under the clinical trials registry (ClinicalTrials.gov) for 2019-nCoV therapeutics [53] [54] [55] [56] [57] [58] [59] [60] [61] . Of which five studies on hydroxychloroquine, lopinavir plus ritonavir and arbidol, mesenchymal stem cells, traditional Chinese medicine and glucocorticoid therapy usage have commenced recruitment. The remaining four studies encompass investigation of antivirals, interferon atomization, darunavir and cobicistat, arbidol, and remdesivir usage for 2019-nCoV patients (Table 5) . Seroconversion measured by S1-ELISA occurred in 86% and 94% participants after 2 and 3 doses, respectively, and was maintained in 79% participants up to study end at week 60. Neutralising antibodies were detected in 50% participants at one or more time points during the study, but only 3% maintained neutralisation activity to end of study. T-cell responses were detected in 71% and 76% participants after 2 and 3 doses, respectively. There were no differences in immune responses between dose groups after 6 weeks and vaccine-induced humoral and cellular responses were respectively detected in 77% and 64% participants at week 60.
[47] Molecules developed by the university scientists inhibit two coronavirus enzymes and prevent its replication. The discovered drug targets are said to be more than 95% similar to enzyme targets found on the SARS virus. Researchers note that identified drugs may not be available to address the ongoing outbreak but they hope to make it accessible for future outbreaks.
[85] Besides the six completed randomized controlled trials (RCT) selected from the systematic review (Table 6) , there is only one ongoing randomized controlled trial targeted at SARS therapeutics [92] . The studies found from ClinicalTrials.gov have not been updated since 2013. While many prospective and retrospective cohort studies conducted during the epidemic centered on usage of ribavirin with lopinavir/ritonavir or ribavirin only, there has yet to be well-designed clinical trials investigating their usage. Three completed randomized controlled trials were conducted during the SARS epidemic-3 in China, 1 in Taiwan and 2 in Hong Kong [93] [94] [95] [96] [97] . The studies respectively investigated antibiotic usage involving 190 participants, combination of western and Chinese treatment vs. Chinese treatment in 123 participants, integrative Chinese and Western treatment in 49 patients, usage of a specific Chinese medicine in four participants and early use of corticosteroid in 16 participants. Another notable study was an open non-randomized study investigating ribavirin/lopinavir/ritonavir usage in 152 participants [98] . One randomized controlled trial investigating integrative western and Chinese treatment during the SARS epidemic was excluded as it was a Chinese article [94] .
There is only one ongoing randomized controlled trial targeted at MERS therapeutics [99] . It investigates the usage of Lopinavir/Ritonavir and Interferon Beta 1B. Likewise, many prospective and retrospective cohort studies conducted during the epidemic centered on usage of ribavirin with lopinavir/ritonavir/ribavirin, interferon, and convalescent plasma usage. To date, only one trial has been completed. One phase 1 clinical trial investigating the safety and tolerability of a fully human polyclonal IgG immunoglobulin (SAB-301) was found in available literature [46] . The trial conducted in the United States in 2017 demonstrated SAB-301 to be safe and well-tolerated at single doses. Another trial on MERS therapeutics was found on ClinicalTrials.gov-a phase 2/3 trial in the United States evaluating the safety, tolerability, pharmacokinetics (PK), and immunogenicity on coadministered MERS-CoV antibodies REGN3048 & REGN3051 [100].
Rapid diagnostics plays an important role in disease and outbreak management. The fast and accurate diagnosis of a specific viral infection enables prompt and accurate public health surveillance, prevention and control measures. Local transmission and clusters can be prevented or delayed by isolation of laboratory-confirmed cases and their close contacts quarantined and monitored at home. Rapid diagnostic also facilitates other specific public health interventions such as closure of high-risk facilities and areas associated with the confirmed cases for prompt infection control and environmental decontamination [11, 101] .
Laboratory diagnosis can be performed by: (a) detecting the genetic material of the virus, (b) detecting the antibodies that neutralize the viral particles of interest, (c) detecting the viral epitopes of interest with antibodies (serological testing), or (d) culture and isolation of viable virus particles.
The key limitations of genetic material detection are the lack of knowledge of the presence of viable virus, the potential cross-reactivity with non-specific genetic regions and the short timeframe for accurate detection during the acute infection phase. The key limitations of serological testing is the need to collect paired serum samples (in the acute and convalescent phases) from cases under investigation for confirmation to eliminate potential cross-reactivity from non-specific antibodies from past exposure and/or infection by other coronaviruses. The limitation of virus culture and isolation is the long duration and the highly specialized skills required of the technicians to process the samples. All patients recovered.
Significantly shorted time from the disease onset to the symptom improvement in treatment (5.10 ± 2.83 days) compared to control group (7.62 ± 2.27 days) (p < 0.05) No significant difference in blood routine improvement, pulmonary chest shadow in chest film improvement and corticosteroid usgae between the 2 groups. However, particularly in the respect of improving clinical symptoms, elevating quality of life, promoting immune function recovery, promoting absorption of pulmonary inflammation, reducing the dosage of cortisteroid and shortening the therapeutic course, treatment with integrative chinese and western medicine treatment had obvious superiority compared with using control treatment alone. Single infusions of SAB-301 up to 50 mg/kg appear to be safe and well-tolerated in healthy participants. [46] Where the biological samples are taken from also play a role in the sensitivity of these tests. For SARS-CoV and MERS-CoV, specimens collected from the lower respiratory tract such as sputum and tracheal aspirates have higher and more prolonged levels of viral RNA because of the tropism of the virus. MERS-CoV viral loads are also higher for severe cases and have longer viral shedding compared to mild cases. Although upper respiratory tract specimens such as nasopharyngeal or oropharyngeal swabs can be used, they have potentially lower viral loads and may have higher risk of false-negatives among the mild MERS and SARS cases [102, 103] , and likely among the 2019-nCoV cases.
The existing practices in detecting genetic material of coronaviruses such as SARS-CoV and MERS-CoV include (a) reverse transcription-polymerase chain reaction (RT-PCR), (b) real-time RT-PCR (rRT-PCR), (c) reverse transcription loop-mediated isothermal amplification (RT-LAMP) and (d) real-time RT-LAMP [104] . Nucleic amplification tests (NAAT) are usually preferred as in the case of MERS-CoV diagnosis as it has the highest sensitivity at the earliest time point in the acute phase of infection [102] . Chinese health authorities have recently posted the full genome of 2019-nCoV in the GenBank and in GISAID portal to facilitate in the detection of the virus [11] . Several laboratory assays have been developed to detect the novel coronavirus in Wuhan, as highlighted in WHO's interim guidance on nCoV laboratory testing of suspected cases. These include protocols from other countries such as Thailand, Japan and China [105] .
The first validated diagnostic test was designed in Germany. Corman et al. had initially designed a candidate diagnostic RT-PCR assay based on the SARS or SARS-related coronavirus as it was suggested that circulating virus was SARS-like. Upon the release of the sequence, assays were selected based on the match against 2019-nCoV upon inspection of the sequence alignment. Two assays were used for the RNA dependent RNA polymerase (RdRP) gene and E gene where E gene assay acts as the first-line screening tool and RdRp gene assay as the confirmatory testing. All assays were highly sensitive and specific in that they did not cross-react with other coronavirus and also human clinical samples that contained respiratory viruses [11] .
The Hong Kong University used two monoplex assays which were reactive with coronaviruses under the subgenus Sarbecovirus (consisting of 2019-nCoV, SARS-CoV and SARS-like coronavirus). Viral RNA extracted from SARS-CoV can be used as the positive control for the suggested protocol assuming that SARS has been eradicated. It is proposed that the N gene RT-PCR can be used as a screening assay while the Orf1b assay acts as a confirmatory test. However, this protocol has only been evaluated with a panel of controls with the only positive control SARS-CoV RNA. Synthetic oligonucleotide positive control or 2019-nCoV have yet to be tested [106] .
The US CDC shared the protocol on the real time RT-PCR assay for the detection of the 2019-nCoV with the primers and probes designed for the universal detection of SARS-like coronavirus and the specific detection of 2019-nCoV. However, the protocol has not been validated on other platforms or chemistries apart from the protocol described. There are some limitations for the assay. Analysts engaged have to be trained and familiar with the testing procedure and result interpretation. False negative results may occur due to insufficient organisms in the specimen resulting from improper collection, transportation or handling. Also, RNA viruses may show substantial genetic variability. This could result in mismatch between the primer and probes with the target sequence which can diminish the assay performance or result in false negative results [107] . Point-of-care test kit can potentially minimize these limitations, which should be highly prioritized for research and development in the next few months.
Serological testing such as ELISA, IIFT and neutralization tests are effective in determining the extent of infection, including estimating asymptomatic and attack rate. Compared to the detection of viral genome through molecular methods, serological testing detects antibodies and antigens. There would be a lag period as antibodies specifically targeting the virus would normally appear between 14 and 28 days after the illness onset [108] . Furthermore, studies suggest that low antibody titers in the second week or delayed antibody production could be associated with mortality with a high viral load. Hence, serological diagnoses are likely used when nucleic amplification tests (NAAT) are not available or accessible [102] .
Vaccines can prevent and protect against infection and disease occurrence when exposed to the specific pathogen of interest, especially in vulnerable populations who are more prone to severe outcomes. In the context of the current 2019-nCoV outbreak, vaccines will help control and reduce disease transmission by creating herd immunity in addition to protecting healthy individuals from infection. This decreases the effective R0 value of the disease. Nonetheless, there are social, clinical and economic hurdles for vaccine and vaccination programmes, including (a) the willingness of the public to undergo vaccination with a novel vaccine, (b) the side effects and severe adverse reactions of vaccination, (c) the potential difference and/or low efficacy of the vaccine in populations different from the clinical trials' populations and (d) the accessibility of the vaccines to a given population (including the cost and availability of the vaccine).
Vaccines against the 2019-nCoV are currently in development and none are in testing (at the time of writing). On 23 January 2020, the Coalition for Epidemic Preparedness Innovations (CEPI) announced that they will fund vaccine development programmes with Inovio, The University of Queensland and Moderna, Inc respectively, with the aim to test the experimental vaccines clinically in 16 weeks (By June 2020). The vaccine candidates will be developed by the DNA, recombinant and mRNA vaccine platforms from these organizations [109] .
Based on the most recent MERS-CoV outbreak, there are already a number of vaccine candidates being developed but most are still in the preclinical testing stage. The vaccines in development include viral vector-based vaccine, DNA vaccine, subunit vaccine, virus-like particles (VLPs)-based vaccine, inactivated whole-virus (IWV) vaccine and live attenuated vaccine. The latest findings for these vaccines arebased on the review by Yong et al. (2019) in August 2019 [110] . As of the date of reporting, there is only one published clinical study on the MERS-CoV vaccine by GeneOne Life Science & Inovio Pharmaceuticals [47] . There was one SARS vaccine trial conducted by the US National Institute of Allergy and Infectious Diseases. Both Phase I clinical trials reported positive results, but only one has announced plans to proceed to Phase 2 trial [111] .
Due to the close genetic relatedness of SARS-CoV (79%) with 2019-nCoV [112] , there may be potential cross-protective effect of using a safe SARS-CoV vaccine while awaiting the 2019-nCoV vaccine. However, this would require small scale phase-by-phase implementation and close monitoring of vaccinees before any large scale implementation.
Apart from the timely diagnosis of cases, the achievement of favorable clinical outcomes depends on the timely treatment administered. ACE2 has been reported to be the same cell entry receptor used by 2019-nCoV to infect humans as SARS-CoV [113] . Hence, clinical similarity between the two viruses is expected, particularly in severe cases. In addition, most of those who have died from MERS-CoV, SARS-CoV and 2019-nCoV were advance in age and had underlying health conditions such as hypertension, diabetes or cardiovascular disease that compromised their immune systems [114] . Coronaviruses have error-prone RNA-dependent RNA polymerases (RdRP), which result in frequent mutations and recombination events. This results in quasispecies diversity that is closely associated with adaptive evolution and the capacity to enhance viral-cell entry to cause disease over time in a specific population at-risk [115] . Since ACE2 is abundantly present in humans in the epithelia of the lung and small intestine, coronaviruses are likely to infect the upper respiratory and gastrointestinal tract and this may influence the type of therapeutics against 2019-nCoV, similarly to SAR-CoV.
However, in the years following two major coronavirus outbreaks SARS-CoV in 2003 and MERS-CoV in 2012, there remains no consensus on the optimal therapy for either disease [116, 117] . Well-designed clinical trials that provide the gold standard for assessing the therapeutic measures are scarce. No coronavirus protease inhibitors have successfully completed a preclinical development program despite large efforts exploring SARS-CoV inhibitors. The bulk of potential therapeutic strategies remain in the experimental phase, with only a handful crossing the in vitro hurdle. Stronger efforts are required in the research for treatment options for major coronaviruses given their pandemic potential. Effective treatment options are essential to maximize the restoration of affected populations to good health following infections. Clinical trials have commenced in China to identify effective treatments for 2019-nCoV based on the treatment evidence from SARS and MERS. There is currently no effective specific antiviral with high-level evidence; any specific antiviral therapy should be provided in the context of a clinical study/trial. Few treatments have shown real curative action against SARS and MERS and the literature generally describes isolated cases or small case series.
Many interferons from the three classes have been tested for their antiviral activities against SARS-CoV both in vitro and in animal models. Interferon β has consistently been shown to be the most active, followed by interferon α. The use of corticosteroids with interferon alfacon-1 (synthetic interferon α) appeared to have improved oxygenation and faster resolution of chest radiograph abnormalities in observational studies with untreated controls. Interferon has been used in multiple observational studies to treat SARS-CoV and MERS-CoV patients [116, 117] . Interferons, with or without ribavirin, and lopinavir/ritonavir are most likely to be beneficial and are being trialed in China for 2019-nCoV. This drug treatment appears to be the most advanced. Timing of treatment is likely an important factor in effectiveness. A combination of ribavirin and lopinavir/ritonavir was used as a post-exposure prophylaxis in health care workers and may have reduced the risk of infection. Ribavirin alone is unlikely to have substantial antiviral activities at clinically used dosages. Hence, ribavirin with or without corticosteroids and with lopinavir and ritonavir are among the combinations employed. This was the most common agent reported in the available literature. Its efficacy has been assessed in observational studies, retrospective case series, retrospective cohort study, a prospective observational study, a prospective cohort study and randomized controlled trial ranging from seven to 229 participants [117] . Lopinavir/ritonavir (Kaletra) was the earliest protease inhibitor combination introduced for the treatment of SARS-CoV. Its efficacy was documented in several studies, causing notably lower incidence of adverse outcomes than with ribavirin alone. Combined usage with ribavirin was also associated with lower incidence of acute respiratory distress syndrome, nosocomial infection and death, amongst other favorable outcomes. Recent in vitro studies have shown another HIV protease inhibitor, nelfinavir, to have antiviral capacity against SARS-CoV, although it has yet to show favorable outcomes in animal studies [118] . Remdesivir (Gilead Sciences, GS-5734) nucleoside analogue in vitro and in vivo data support GS-5734 development as a potential pan-coronavirus antiviral based on results against several coronaviruses (CoVs), including highly pathogenic CoVs and potentially emergent BatCoVs. The use of remdesivir may be a good candidate as an investigational treatment.
Improved mortality following receipt of convalescent plasma in various doses was consistently reported in several observational studies involving cases with severe acute respiratory infections (SARIs) of viral etiology. A significant reduction in the pooled odds of mortality following treatment of 0.25 compared to placebo or no therapy was observed [119] . Studies were however at moderate to high risk of bias given their small sample sizes, allocation of treatment based on the physician's discretion, and the availability of plasma. Factors like concomitant treatment may have also confounded the results. Associations between convalescent plasma and hospital length of stay, viral antibody levels, and viral load respectively were similarly inconsistent across available literature. Convalescent plasma, while promising, is likely not yet feasible, given the limited pool of potential donors and issues of scalability. Monoclonal antibody treatment is progressing. SARS-CoV enters host cells through the binding of their spike (S) protein to angiotensin converting enzyme 2 (ACE2) and CD209L [118] . Human monoclonal antibodies to the S protein have been shown to significantly reduce the severity of lung pathology in non-human primates following MERS-CoV infection [120] . Such neutralizing antibodies can be elicited by active or passive immunization using vaccines or convalescent plasma respectively. While such neutralizing antibodies can theoretically be harvested from individuals immunized with vaccines, there is uncertainty over the achievement of therapeutic levels of antibodies.
Other therapeutic agents have also been reported. A known antimalarial agent, chloroquine, elicits antiviral effects against multiple viruses including HIV type 1, hepatitis B and HCoV-229E. Chloroquine is also immunomodulatory, capable of suppressing the production and release of factors which mediate the inflammatory complications of viral diseases (tumor necrosis factor and interleukin 6) [121] . It is postulated that chloroquine works by altering ACE2 glycosylation and endosomal pH. Its anti-inflammatory properties may be beneficial for the treatment of SARS. Niclosamide as a known drug used in antihelminthic treatment. The efficacy of niclosamide as an inhibitor of virus replication was proven in several assays. In both immunoblot analysis and immunofluorescence assays, niclosamide treatment was observed to completely inhibit viral antigen synthesis. Reduction of virus yield in infected cells was dose dependent. Niclosamide likely does not interfere in the early stages of virus attachment and entry into cells, nor does it function as a protease inhibitor. Mechanisms of niclosamide activity warrant further investigation [122] . Glycyrrhizin also reportedly inhibits virus adsorption and penetration in the early steps of virus replication. Glycyrrhizin was a significantly potent inhibitor with a low selectivity index when tested against several pathogenic flaviviruses. While preliminary results suggest production of nitrous oxide (which inhibits virus replication) through induction of nitrous oxide synthase, the mechanism of Glycyrrhizin against SARS-CoV remains unclear. The compound also has relatively lower toxicity compared to protease inhibitors like ribavirin [123] . Inhibitory activity was also detected in baicalin [124] , extracted from another herb used in the treatment of SARS in China and Hong Kong. Findings on these compounds are limited to in vitro studies [121] [122] [123] [124] .
Due to the rapidly evolving situation of the 2019-nCoV, there will be potential limitations to the systematic review. The systematic review is likely to have publication bias as some developments have yet to be reported while for other developments there is no intention to report publicly (or in scientific platforms) due to confidentiality concerns. However, this may be limited to only a few developments for review as publicity does help in branding to some extent for the company and/or the funder. Furthermore, due to the rapid need to share the status of these developments, there may be reporting bias in some details provided by authors of the scientific articles or commentary articles in traditional media. Lastly, while it is not viable for any form of quality assessment and metaanalysis of the selected articles due to the limited data provided and the heterogeneous style of reporting by different articles, this paper has provided a comprehensive overview of the potential developments of these pharmaceutical interventions during the early phase of the outbreak. This systematic review would be useful for cross-check when the quality assessment and meta-analysis of these developments are performed as a follow-up study.
Rapid diagnostics, vaccines and therapeutics are key pharmaceutical interventions to limit transmission of respiratory infectious diseases. Many potential developments on these pharmaceutical interventions for 2019-nCoV are ongoing in the containment phase of this outbreak, potentially due to better pandemic preparedness than before. However, lessons from MERS-CoV and SARS-CoV have shown that the journeys for these developments can still be challenging moving ahead.
Supplementary Materials: The following are available online at www.mdpi.com/xxx/s1, Table S1 : Example of full search strategy in Pubmed, Table S2 : Google Search: 2019-nCoV diagnostics, Table S3 : Summary of diagnostic assays developed for 2019-nCoV, Table S4 | What work has been carried out this study? | false | 3,617 | {
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650 | Role of S-Palmitoylation on IFITM5 for the Interaction with FKBP11 in Osteoblast Cells
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3776769/
Tsukamoto, Takashi; Li, Xianglan; Morita, Hiromi; Minowa, Takashi; Aizawa, Tomoyasu; Hanagata, Nobutaka; Demura, Makoto
2013-09-18
DOI:10.1371/journal.pone.0075831
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Abstract: Recently, one of the interferon-induced transmembrane (IFITM) family proteins, IFITM3, has become an important target for the activity against influenza A (H1N1) virus infection. In this protein, a post-translational modification by fatty acids covalently attached to cysteine, termed S-palmitoylation, plays a crucial role for the antiviral activity. IFITM3 possesses three cysteine residues for the S-palmitoylation in the first transmembrane (TM1) domain and in the cytoplasmic (CP) loop. Because these cysteines are well conserved in the mammalian IFITM family proteins, the S-palmitoylation on these cysteines is significant for their functions. IFITM5 is another IFITM family protein and interacts with the FK506-binding protein 11 (FKBP11) to form a higher-order complex in osteoblast cells, which induces the expression of immunologically relevant genes. In this study, we investigated the role played by S-palmitoylation of IFITM5 in its interaction with FKBP11 in the cells, because this interaction is a key process for the gene expression. Our investigations using an established reporter, 17-octadecynoic acid (17-ODYA), and an inhibitor for the S-palmitoylation, 2-bromopalmitic acid (2BP), revealed that IFITM5 was S-palmitoylated in addition to IFITM3. Specifically, we found that cysteine residues in the TM1 domain and in the CP loop were S-palmitoylated in IFITM5. Then, we revealed by immunoprecipitation and western blot analyses that the interaction of IFITM5 with FKBP11 was inhibited in the presence of 2BP. The mutant lacking the S-palmitoylation site in the TM1 domain lost the interaction with FKBP11. These results indicate that the S-palmitoylation on IFITM5 promotes the interaction with FKBP11. Finally, we investigated bone nodule formation in osteoblast cells in the presence of 2BP, because IFITM5 was originally identified as a bone formation factor. The experiment resulted in a morphological aberration of the bone nodule. This also indicated that the S-palmitoylation contributes to bone formation.
Text: The interferon-induced transmembrane (IFITM) protein family (also known as the Fragilis family in mice) is a part of the dispanin family [1] and is composed of double-transmembrane α-helices connected by a cytoplasmic (CP) loop and extracellular (EC) amino-and carboxyl-terminal polypeptide sequences (Figure 1-A) . The IFITM proteins are evolutionarily conserved in vertebrates [2] . Recent genomic research has revealed that there are 5 IFITM members in humans (IFITM1, 2, 3, 5 and 10) and 7 members in mice (IFITM1, 2, 3, 5, 6, 7, and 10). These proteins play roles in diverse biological processes, such as germ cell maturation during gastrulation (IFITM1-3) [3] [4] [5] , cell-to-cell adhesion (IFITM1) [6] [7] [8] , antiviral activity (IFITM1-3) [9] [10] [11] [12] [13] [14] [15] [16] [17] , and bone formation (IFITM5) [18] [19] [20] [21] [22] , although the detailed functions of IFITM6, 7, and 10 are unknown at present. In particular, IFITM3 has been a target of intensive studies on its activity against influenza A (H1N1) virus infection and internalization [9] [10] [11] [12] [13] [14] .
In 2010, Dr. Yount and co-workers reported that the antiviral activity of IFITM3 is dependent on S-palmitoylation on the protein [10] . The S-palmitoylation [23] is a post-translational modification on proteins by C 16 saturated-fatty acids (palmitic acids) covalently attached to certain cysteine residues via a thioester linkage (Figure 1-B) . The modification is reversibly catalyzed by protein acyltransferases and acylprotein thioesterases, and confers unique properties to the protein, such as membrane binding and targeting, immunoreactivity,
Amino-acid sequence alignment of IFITM5, IFITM1, IFITM2, and IFITM3 derived from mice. The conserved residues are highlighted in black. The three conserved cysteines are highlighted in red and numbered based on the sequence of IFITM5 (top) and IFITM3 (bottom). The residues unique in IFITM5 are highlighted in gray. The first and the second transmembrane domains, the extracellular sequences, and the cytoplasmic loop are indicated by arrows and denoted as TM1 and TM2, EC, and the CP loop, respectively. The TM domains were predicted by SOSUI. The aspartates at the C-terminal region in IFITM5 are shown in blue. B) The schematic illustration of the protein S-palmitoylation. The C 16 -palmitic acid is attached to cysteine via a thioester linkage. The palmitoylation and depalmitoylation are catalyzed by protein acyltransferases and acylprotein thioesterases, respectively. In this study, hydroxylamine, NH 2 OH, was used to reduce the thioester linkage. C) The amino acid sequence identity (similarity) among IFITM5, IFITM1, IFITM2, and IFITM3 is summarized. doi: 10.1371/journal.pone.0075831.g001 and protein-protein interaction. The authors revealed that IFITM3 is S-palmitoylated on three membrane proximal cysteines, Cys71 and Cys72 in the first transmembrane (TM1) domain, and Cys105 in the CP loop (Figure 1-A) [10] . In addition, IFITM3 lacking the S-palmitoylation is not clustered in the cell membrane and significantly diminishes the antiviral activity. Moreover, the cysteines in IFITM2, Cys70, Cys71, and Cys104 are also palmitoylated in the same manner, which affects the intracellular localization [24] . A resent study has revealed that murine IFITM1 has four cysteine residues (Cys49, Cys50, Cys83, and Cys103) for the S-palmitoylation, which is required for the antiviral activity and the protein stability [25] . The other IFITM family members also possess these cysteines (Figure 1-A) , and thus the role of the Spalmitoylation on the cysteines should be significant for the functions of IFITM proteins.
Here, we focused on IFITM5, which is also known as bonerestricted IFITM-like (BRIL) protein [18] . Among the IFITM family proteins, IFITM5 is unique. (i) Expression of IFITM5: Unlike the other IFITM family proteins, the expression of IFITM5 is not induced by interferons because the region upstream of the ifitm5 gene lacks the interferon regulatory elements [26] . Furthermore, the expression of IFITM5 is mostly restricted to osteoblast cells [18, 19, 27] , while the other IFITM proteins are expressed ubiquitously (ii). Amino-acid sequence similarity: The amino acid sequence of IFITM5 is relatively dissimilar to IFITM1-3 proteins (~ 65% similarity), while IFITM1-3 proteins share ~ 85% similarity with each other (Figure 1 -C). In addition, IFITM5 has an aspartate-rich domain in the C-terminal region, which could be involved in calcium binding (Figure 1 -A) [26] . (iii) Role of IFITM5 in bone formation: The expression of IFITM5 is associated with mineralization during the bone formation process in osteoblast cells [18] [19] [20] [21] . Previous studies have confirmed the expression of IFITM5 in bone tissues in mice, rats, humans and tammar wallabies [2] . The ifitm5-gene knockout mice have smaller bones [19] . Moreover, the knockdown of the ifitm5 gene by small hairpin RNA induces a decrease in bone nodule formation, whereas overexpression of the gene in UMR106 cells has been shown to increase calcium uptake and bone nodule formation [18] . (iv) Role of IFITM5 for immune activity: Recent studies have revealed that IFITM5 interacts with the FK506-binding protein 11 (FKBP11) to form IFITM5-FKBP11-CD81-the prostaglandin F2 receptor negative regulator (FPRP) complex [28] . When the complex is formed, the expressions of 5 interferon-induced genes are induced, including bone marrow stromal cell antigen 2 (Bst2), interferon inducible protein 1 (Irgm), interferoninduced protein with tetratricopeptide repeats 3 (Ifit3), b(2)microglobulin (B2m), and MHC class I antigen gene. Consequently, these results indicate that IFITM5 is involved not only in the bone formation but also in the immune system activity.
In this study, we investigated the S-palmitoylation of IFITM5 and its role in the interaction with FKBP11 in mouse osteoblast cells. Cells transfected by a plasmid DNA encoding mouse IFITM5 were grown in the presence of an established chemical reporter, 17-octadecynoic acid (17-ODYA) [29, 30] , or an inhibitor for the S-palmitoylation, 2-bromopalmitic acid (2BP) [31] . The biochemical assays using these compounds revealed that the wild-type IFITM5 is S-palmitoylated. To identify the Spalmitoylation site in IFITM5, we prepared cysteine-substituted mutants, IFITM5-C86A, -C52A/C53A, and -C52A/53A/86A (Cys-less). The chemical reporter assay suggested that at least two out of three cysteines in IFITM5 are S-palmitoylated. The interaction of IFITM5 with FKBP11 was examined by immunoprecipitation assay, resulting in the loss of the interaction in the presence of 2BP. The same result was obtained in the two mutants, C52A/C53A and Cys-less. These results suggested that the S-palmitoylation on Cys52 and/or Cys53 in the TM1 domain of IFITM5 is necessary for the interaction with FKBP11. On the other hand, Cys86 in the CP loop of IFITM5 was S-palmitoylated but not involved in the interaction. Because this interaction is important for the immunologically relevant gene expression, it was indicated that the role of the S-palmitoylation is to promote the interaction of IFITM5 with FKBP11 and to regulate the immune activity in the osteoblast cells. The possible interaction mechanism and the effect of the S-palmitoylation on the bone nodule formation will be discussed.
For mammalian cell expression, plasmid vectors of wild-type IFITM5 (IFITM5-WT) and FLAG-fused FKBP11 (FKBP11-FLAG) were constructed by inserting the cloned genes into a pBApo-CMV Neo expression vector (Takara Bio, Shiga, Japan). The details of the recombinant DNA constructs were the same as described previously [19] . The genes of IFITM5 mutants (IFITM5-C86A, -C52A/53A, and -C52A/C53A/C86A (Cys-less)) were prepared using a QuikChange site-directed mutagenesis kit (Stratagene, La Jolla, CA). The plasmid vectors of FLAG-fused IFITM5-WT, -C52A/53A, and Cys-less were constructed by inserting the cloned genes into the pBApo-CMV Neo expression vector. For E. coli cell expression, the plasmid vector of IFITM5-WT was constructed by inserting the cloned gene into a pET22b (Novagen, Madison, WI) expression vector. The forward primer 5'-GGAATTCCATATGGACACTTCATATCCCCGTG-3' and the reverse primer 5'-CCGCTCGAGGTTATAGTCCTCCTCATCAAACTTGG-3' were used to amplify the gene encoding the entire IFITM5 from the plasmid vector for mammalian cell expression described above. The underlined letters denote an NdeI and an XhoI cleavage site, respectively. The plasmids of IFITM5 mutants were prepared using a QuikChange site-directed mutagenesis kit. The sense and anti-sense primers used were 5'-GGCAGTATGGCTCCAAAGCCAAGGCGTACAACATCCTGG CTGC-3' and 5'-GCAGCCAGGATGTTGTACGCCTTGGCTTTGGAGCCATACT GCC-3' for IFITM5-C86A; and 5'-GCACGATGTACCTGAATCTGGCGGCGCTTGGATTCCTGG CGC-3' and 5'-GCGCCAGGAATCCAAGCGCCGCCAGATTCAGGTACATCG TGC-3' for IFITM5-C52A/C53A, respectively (Sigma-Aldrich, St. Louis, MO).
Osteoblast-like MC3T3 cells were provided by the RIKEN, Cell Bank (RCB 1126). The procedures for cell culture, transfection, and protein expression were the same as reported previously. When necessary, 2-bromopalmitic acid (2BP; Wako, Osaka, Japan) and 17-octadecynoic acid (17-ODYA; Sigma-Aldrich) were dissolved in 99.5% dimethyl sulfoxide (DMSO; Wako) and added to differentiation medium at concentrations of 100 μM and 50 μM in less than 0.1% DMSO, respectively [30, 31] .
Wild-type and mutant IFITM5 proteins were also produced using an E. coli recombinant expression system. E. coli BL21(DE3) cells transformed by the expression plasmid were grown at 37°C in LB medium containing 50 μg/mL ampicillin. After four-hour induction by 1 mM isopropyl β-Dthiogalactopyranoside (IPTG), cells were harvested by centrifugation (6,400 × g for 10 min at 4°C). The cells were suspended in 50 mM Tris-HCl buffer (pH 8) and disrupted by a French press (Ohtake, Tokyo, Japan) (100 MPa × 4 times). The crude membrane fraction was collected by ultracentrifugation (178,000 × g for 90 min at 4°C). The collected fraction was solubilized with 1.5% n-dodecyl-β-Dmaltopyranoside (DDM) (Dojindo Lab, Kumamoto, Japan) in 50 mM Tris-HCl, pH 8, containing 0.3 M NaCl and 5 mM imidazole. After the ultracentrifugation, the supernatant was incubated with Ni 2+ -NTA agarose resin (Qiagen, Hilden, Germany). The resin was applied to a chromatography column and washed with 50 mM imidazole containing 50 mM Tris-HCl (pH 8), 0.3 M NaCl and 0.1% DDM. The DDM-solubilized IFITM5 was collected by elution with the same buffer containing 0.3 M imidazole. The sample media were replaced by the appropriate buffer solution by two passages over a PD-10 column (GE Healthcare UK, Ltd., Amersham Place, England).
The experimental details are described in previous reports [19, 28] . Briefly, total proteins were extracted from the osteoblast cells which co-expressed IFITM5 and FKBP11-FLAG using a total protein extraction kit (BioChain Institute Inc., Newark, CA). Then, the cell lysate was incubated with anti-FLAG M2 agarose gel (Sigma-Aldrich) at 4°C for 2 h. To recover FKBP11-FLAG, 500 ng/μL 3 × FLAG peptide (Sigma-Aldrich) dissolved in Tris-buffered saline was added to the collected gel at 4°C for 1 h. The recovered proteins and the cell lysate containing total proteins were analyzed by SDS-PAGE (15% ePAGEL; ATTO, Tokyo, Japan) and western blot. The anti-IFITM5 polyclonal antibody, which was prepared from the amino-terminal peptide sequence (TSYPREDPRAPSSRC), and anti-FLAG monoclonal antibody (Sigma-Aldrich) were used as primary antibodies. The HRP-conjugated goat anti-rabbit IgG (H+L) (Zymed Laboratories, San Francisco, CA) and goat anti-mouse IgG (H+L) (Sigma-Aldrich) antibodies were used as secondary antibodies for the anti-IFITM5 and anti-FLAG primary antibodies, respectively. The proteins were detected by chemiluminescent reaction (MercK-Millipore, Billerica, MA).
The cell lysate extracted from the osteoblast cells metabolically labeled by 17-ODYA was incubated with anti-FLAG M2 agarose gel to obtain purified FLAG-fused IFITM5 proteins. The 17-ODYA-labeled proteins were chemically labeled with azide-PEG 3 -5(6)-carboxytetramethylrhodamine (TAMRA-azide; Click Chemistry Tools, Scottsdale, AZ) with reference to previous studies [10, 29, 30, 32] and the manufacturer's guide. The proteins separated by SDS-PAGE were visualized using a 532-nm laser for excitation and the fluorescence by TAMRA (565 nm) was detected using a 575nm long-path filter (Typhoon FLA 9000; GE Healthcare).
The subcultured osteoblast MC3T3 cells were seeded at a density of 5,000 cells/cm 2 in 40 mm dishes and cultured in α-Modified Eagle's Medium (α-MEM; Sigma-Aldrich) containing 10% (v/v) fetal bovine serum (FBS; Nichirei Biosciences Inc., Tokyo, Japan). On the next day, this was replaced with differentiation medium, containing 2 mM glycerophosphate and 50 μg/mL sodium ascorbate at final concentrations, to induce osteoblast differentiation. When necessary, 100 μM 2BP in less than 0.1% DMSO, or 0.1% DMSO alone was added to the differentiation medium at final concentrations. All cultures were incubated at 37°C in a humidified atmosphere containing 5% CO 2 for 27 days. Mineralized nodules were stained with Alizarin Red S (Sigma-Aldrich). The standard staining procedure was used. The mineralized nodules were checked every three days.
To identify the S-palmitoylation on IFITM5, the osteoblast cells harboring the plasmid DNA encoding IFITM5-WT were cultured in the absence and presence of 2BP, which inhibits the S-palmitoylation (Figure 2-A) [31] . Then, the cell lysate containing total protein was extracted for use in the SDS-PAGE and western blot analyses. For purposes of comparison, E. coli cells were also cultured in the absence of 2BP and the cell lysate was extracted. Figure 2 -B shows the results of the western blot assay for IFITM5-WT expressed in the osteoblast and the E. coli cells. In the osteoblast cells, IFITM5-WT exhibited a single band near the 17.4 kDa molecular-mass marker (see lane 1) in the absence of 2BP. However, in the presence of 2BP (see lane 4), the band appeared at a lower position than that in the absence of 2BP (lane 1). These results suggested that IFITM5-WT has high and low molecular-mass forms in the absence and presence of 2BP, respectively. The S-palmitoylation is a reversible reaction, and therefore is depalmitoylated by a strong reductant such as hydroxylamine [10] . Following hydroxylamine treatment (see lane 2), the band appeared at the same position as in the presence of 2BP (lane 4). In prokaryote E. coli cells, the post-translational modification S-Palmitoylation on IFITM5 PLOS ONE | www.plosone.org does not occur. Hence, the band was also observed at the same lower position (see lane 3). In the case of IFITM3, the palmitoylation was also reported to induce a change in mobility on electrophoresis, just as in our present results [10] .
For direct observation of the S-palmitoylation, an established chemical reporter, 17-ODYA (Figure 2-C) , was used. The osteoblast cells harboring the plasmid encoding IFITM5-WT were cultured in the presence of 17-ODYA to label the protein metabolically. Following the extraction and the purification of the cell lysate, the labeled IFITM5-WT was ligated with TAMRA-azide according to the Cu(I)-catalyzed [3+2] azidealkyne cycloaddition method [10, 29, 30, 32 ]. An in-gel fluorescence image of the 17-ODYA-TAMRA-labeled IFITM5-WT (see lane 2 in Figure 2 -D) showed that IFITM5 was Spalmitoylated in the osteoblast cells. The FLAG-tag attached to IFITM5 has no influence on the modification and chemical labeling (lanes 1 and 5). In addition, after the hydroxylamine treatment (see lane 6), the fluorescence became weak because of the dissociation of 17-ODYA from IFITM5, which was the same mechanism as the dissociation of the palmitic acid from IFITM5 by reduction as described above (lane 2 of Figure 2-B) .
Therefore, we concluded that the IFITM5 expressed in the native osteoblast cells is S-palmitoylated. In addition, the bands corresponding to the high and the low molecular-mass forms shown in western blot analysis were tentatively assigned to the S-palmitoylated and the depalmitoylated forms, respectively.
As described above in the Introduction, cysteine residues are the substrate for S-palmitoylation. IFITM5 possesses three cysteines, Cys52 and Cys53 in the TM1 domain, and Cys86 in the CP loop (Figure 1-A) . All of these cysteines are highly conserved among the mammalian IFITM family proteins (Figure 3-A) . To identify the modification site in IFITM5, we prepared cysteine-substituted mutants, IFITM5-C52A/C53A, -C86A, and -C52A/C53A/C86A (Cys-less). The osteoblast cells harboring each plasmid were cultured in the absence of 2BP, and then the cell lysate was extracted. Figure 3 -B shows the results of the western blot detecting the expression of all the mutants in the osteoblast cells. In the C52A/C53A and Cys-less mutants (see lanes 2 and 4), the low molecular-mass form was detected. This result indicates that either Cys52 or Cys53 is involved in the S-palmitoylation. In addition, as shown in Figure 2 -D, strong and weak fluorescence were detected in the C52A/ C53A mutant in the absence and presence of hydroxylamine (lanes 3 and 7) , respectively, but not in the Cys-less mutant (lanes 4 and 8) . These results suggested that the rest of the cysteine in the C52A/C53A mutant, Cys86, is S-palmitoylated and the Cys-less mutant completely lost the S-palmitoylation because all the cysteines were substituted. Therefore, we concluded that Cys86, plus one or two other cysteine residues in IFITM5, i.e., Cys52 and/or Cys53, are S-palmitoylated. In addition, it was found that the S-palmitoylation on the TM1 domain has a major effect on the mobility in the gel (lower panel of Figure 2 -D and Figure 3-B) . Therefore, we hereafter refer to the high and low molecular-mass forms as the TM1palmitoylated and the TM1-depalmitoylated forms, respectively. Finally, we reassigned the bands shown in the western blot analysis as follows: IFITM5-WT is fully palmitoylated, the C86A mutant is partially palmitoylated at Cys52 and/or Cys53, the C52A/C53A mutant is partially palmitoylated at Cys86, and the Cys-less mutant is completely depalmitoylated.
Previous studies have revealed that IFITM5 interacts with FKBP11 [19] . FKBP11 belongs to the FK506-binding protein family and has a transmembrane domain. The interaction between IFITM5 and FKBP11 is important for the immune activity because formation of the IFITM5-FKBP11-CD81-FPRP complex induces the expression of interferon-induced genesnamely, the Bst2, Irgm, Ifit3, B2m, and MHC class I antigen gene [28] . To investigate the effect of the S-palmitoylation on the interaction of IFITM5 with FKBP11, we carried out an immunoprecipitation assay. The osteoblast cells co-transfected by the plasmids encoding IFITM5-WT and FKBP11-FLAG were cultured in the absence and the presence of 2BP. Then, the extracted cell-lysate was incubated with anti-FLAG agarose gel. The gel was washed several times. Finally, the proteins were competitively eluted by the addition of FLAG peptide. If IFITM5 interacted with FKBP11, it was expected that IFITM5 The conserved cysteines are highlighted in orange and numbered. In the lower panel, the numbers given in parenthesis correspond to the residual number for IFITM2. For the calculation of probability, a total of 23 IFITM2, 23 IFITM3, and 17 IFITM5 sequences derived from mammalian species in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database were used. Sequence alignment was carried out using CLUSTALW. Sequence logos were generated using WEBLOGO 3. B) Western blot for the wild-type and cysteine-substituted mutants of IFITM5 expressed in the osteoblast cells. For detection, the anti-IFITM5 antibody was used as a primary antibody. The upper arrow indicates that C52 and/or C53 in the TM1 domain is Spalmitoylated (lanes 1 and 3) . The C52A/C53A (lane 2) and Cys-less (lane 4) mutants are partially and completely depalmitoylated. The experiment was carried out 2 times. doi: 10.1371/journal.pone.0075831.g003 would be obtained during this step and detected by immunoblotting. Figure 4 -A shows the results of the western blot for the co-immunoprecipitation of IFITM5-WT with FKBP-FLAG. The band corresponding to FKBP11 appeared in all the lanes (upper panel). Lanes 1 and 2 are controls to ensure that IFITM5 and FKBP11 are both contained in the cell lysate before the immunoprecipitation. The controls also ensured that IFITM5 was S-palmitoylated in the absence of 2BP (see lane 1), whereas IFITM5 was not S-palmitoylated in the presence of 2BP (see lane 2). After the immunoprecipitation, a single band corresponding to the S-palmitoylated IFITM5 appeared in the absence of 2BP (see lane 3), indicating the interaction of the Spalmitoylated IFITM5 with FKBP11. However, in the presence of 2BP, no band corresponding to IFITM5 appeared (see lane 4) , indicating that the two molecules do not interact with each other. These results suggest that the S-palmitoylation on IFITM5 contributes to the interaction with FKBP11.
Next, we further investigated the relationship between the Spalmitoylation and the interaction with FKBP11 by using the IFITM5 mutants described above. The osteoblast cells cotransfected by the plasmids encoding IFITM5 mutants (C52A/ C53A, C86A, and Cys-less) and FKBP11-FLAG were cultured. The immunoprecipitation assay was carried out in the same way as described above. Figure 4 -B shows the results of the western blot for the co-immunoprecipitation of the wild-type and the IFITM5 mutants with FKBP11. Figure 4 -C shows the results of the control experiment using the cell lysate before the immunoprecipitation. As described in the previous section 3-3, the band corresponding to FKBP11 appeared in all the lanes (upper panels) because the immunoprecipitation was carried out using the anti-FLAG agarose gel. In the lower panel of Figure 4 -B, single bands were observed for the IFITM5-WT and -C86A mutant (lanes 1 and 3) but not for the -C52A/C53A and Cys-less mutants (lanes 2 and 4) . This result indicates that the wild-type and the C86A mutant interact with FKBP11, whereas the other two mutants do not. Interestingly, this tendency mirrored the trend for the S-palmitoylation profiles, which means that Cys52 and/or Cys53 in the TM1 domain of the IFITM5-WT and -C86A mutants is S-palmitoylated, whereas these residues are not S-palmitoylated in the C52A/C53A and Cys-less mutants (see Figures 2-D, 3 -B and the lower panel of Figure 4 -C). Because the S-palmitoylation contributes to the IFITM5-FKBP11 interaction, as described in the previous section 3-3 (also in Figure 4-A) , the results of Figure 4 -B suggest that the mutants which lost the S-palmitoylation site(s), Cys52 and/or Cys53, are not able to interact with FKBP11. In other words, the S-palmitoylation on these cysteines is necessary for the interaction of IFITM5 with FKBP11.
As described above in the Introduction, previous studies have revealed that IFITM5 also contributes to bone formation [18] [19] [20] [21] . Therefore, we investigated the influence of Spalmitoylation on the bone nodule formation in osteoblast cells, in which native IFITM5 is expressed. Figure 5 shows the time-dependent nodule formation in the absence and the presence of 2BP ( Figure 5-A and -B) . Figure 5 -C shows the results of the control trial to verify the effect of DMSO, which was used as the solvent for 2BP, on the nodule formation. The mineralized nodule was stained with Alizarin Red, which reacts with deposited calcium. In Figure 5 -D, the area of the mineralized nodule was plotted against experimental time. In the absence of 2BP (Figure 5-A, -C, and -D) , the mineralization was started 15 days after the initiation of the cell differentiation (Day 0). On the other hand, in the presence of 2BP ( Figure 5-B and -D) , the nodule was formed on Day 12. The halftime for the maximum mineralization in the presence of 2BP was estimated to be 7 days earlier than that in the absence of 2BP (Figure 5-D) . In addition, differences in the form of the mineralized nodules were observed. Figure 5 -E shows an enlarged view of each nodule on Day 21. The stained nodules were diffused in the presence of 2BP (panel b), whereas in the absence of 2BP the nodules formed a large cluster (panels a and c). Therefore, our observations in this study suggested that the S-palmitoylation affects the bone nodule formation in the osteoblast cells.
In this study, we confirmed the S-palmitoylation on IFITM5 in the osteoblast cells, which was the same as that previously reported for IFITM3 and IFITM2. As reported previously, in IFITM3 and IFITM2, which share 85% sequence similarity (Figure 1-C) , two cysteines in the TM1 domain (Cys71 and Cys72 for IFITM3, Cys70 and Cys71 for IFITM2) and one cysteine in the CP loop (Cys105 for IFITM3, Cys104 for IFITM2) are all S-palmitoylated in cells [10, 24] . On the other hand, although IFITM5 shares 68% and 66% sequence similarity to IFITM3 and IFITM2, respectively, more than one cysteine in the TM1 domain (Cys52 or Cys53) and one cysteine in the CP loop (Cys86) are S-palmitoylated. Taking into account the high conservation of three cysteines in the IFITM proteins (Figures 1-A and 3-A) , all the cysteines in IFITM5 may be involved in the S-palmitoylation just as in the case of IFITM3 and IFITM2 [10, 24] .
The roles of the S-palmitoylation on IFITM3 have been studied intensively, and the S-palmitoylation has been shown to be crucial for the correct positioning in the membrane and the resistance to viral infection and internalization [10] (the roles are summarized in Figure 6 -A and discussed in detail below). A recent study has revealed that the S-palmitoylation on IFITM2 is also important for the protein clustering in the membrane [24] . However, we do not know the role of the Spalmitoylation of IFITM5 for the clustering in the membrane at present because we have not yet succeeded in obtaining a proper antibody for immunohistochemistry, despite our allocating much time to the search and considering a considerable number of antibodies.
Dr. Hanagata and co-workers previously reported that IFITM5 lacking the TM1 domain and the CP loop, which and IFITM5 (lower panels), the anti-FLAG and the anti-IFITM5 antibodies were used as primary antibodies, respectively. Arrows indicate the existence of each protein and the S-palmitoylation on IFITM5. A) Western blot for the co-immunoprecipitation of the wild-type IFITM5 with the FLAG-fused FKBP11 (FKBP11-FLAG) in the osteoblast cells in the absence and the presence of 2BP (denoted as "-" and "+", respectively). Lanes 1 and 2 are the results for the control trials used to verify the existence of IFITM5 and FKBP11 before the immunoprecipitation, and Lanes 3 and 4 show the results after the immunoprecipitation. The experiment was repeated 3 times. B) Western blot for the co-immunoprecipitation of the wild-type and the cysteine-substituted mutants of IFITM5 with FKBP11-FLAG in the osteoblast cells. The band corresponding to FLAG peptide is not shown because of the smaller molecular-mass of FLAG peptide relative to FKBP11-FLAG. C) The control experiment of Figure 4 -B used to verify that IFITM5 and FKBP11 were both present in the cell lysate before the immunoprecipitation. The experiment was repeated 2 times. A) The functional mechanism of IFITM3 is summarized from previous studies. (i) IFITM3 is S-palmitoylated at Cys71, Cys72, and Cys105, (ii) which induces clustering and correct positioning in the membrane, (iii) resulting in the antiviral activity against influenza virus. B) The functional mechanism of IFITM5 is summarized by combining the results from the present and the previous studies. (i) Cys86, plus one or two other cysteine residues in IFITM5, i.e., Cys52 and/or Cys53, are S-palmitoylated (ii). The S-palmitoylation allows IFITM5 to interact with FKBP11 in the osteoblast cells (iii). The dissociation of CD9 from the FKBP11-CD81-FPRP/CD9 complex is induced by formation of the IFITM5-FKBP11-CD81-FPRP complex and leads to the immunologically relevant gene expression. IFITM5 also contributes to the bone formation, but it is unknown which states as described in (i)-(iii) are important for the bone formation at present.At present, no interactive protein has been identified in IFITM3 and IFITM2. On the other hand, IFITM5 interacts with the partner protein, FKBP11, and the S-palmitoylation clearly makes a significant contribution to the interaction. Therefore, IFITM5 forms a hetero-oligomer in the cell membrane for its physiological function.
contain the relevant modification sites, lost the ability to interact with FKBP11 [19] . In the present study, we determined that the S-palmitoylation on Cys52 and/or Cys53 in the TM1 domain is necessary for the interaction. From these results, we speculate that Cys52 and Cys53 face toward the interaction surface with FKBP11, and therefore IFITM5 and FKBP11 interact with each other through the palmitic acid(s) attached to the cysteine(s) (summarized in Figure 6 -B, discussed in detail later). Our investigation revealed that Cys86 is involved in the Spalmitoylation but does not contribute to the interaction with FKBP11. We speculate that some other residues in the CP loop located near the TM1 domain make some contribution to the interaction.
Previous investigations also revealed that IFITM5 expressed in the heterologous fibroblast NIH3T3 cells exhibited direct interactions with CD81, the B cell receptor-associated protein 31 (BCAP31), and the hydroxysteroid (17-beta) dehydrogenase 7 (HSD17b7). These three proteins bind to the IFITM5 without the S-palmitoylation (low molecular-mass form; see Figure 3 -b in ref [19] . and Figure 1 -B in ref [28] .). In the fibroblast cells, the S-palmitoylation on IFITM5 is insufficient [19] . These interactions are not observed in the native osteoblast cells, and therefore are nonspecific. Taking these facts into consideration, we speculate that the S-palmitoylation on IFITM5 promotes the specific interaction with FKBP11 in the osteoblast cells.
The role played by the S-palmitoylation of IFITM5 in immune activity of the osteoblast cells will be discussed by combining the results from the present and the previous studies. A specific interaction between IFITM5 and FKBP11 should be necessary to form the IFITM5-FKBP11-CD81-FPRP complex. CD81, also known as TAPA-1, is a member of the tetraspanin membrane protein family and a component of the B-cell coreceptor complex which mediates the B-cell signaling for immune responses. When forming this complex, CD9, a partner protein with CD81, dissociates from the FKBP11-CD81-FPRP/CD9 complex and consequently induces the osteoblastspecific expression of the interferon-induced genes, Bst2, Irgm, Ifit3, B2m, and the MHC class I antigen gene [28] . If the Spalmitoylation-mediated specific interaction of IFITM5 with FKBP11 were lost, the IFITM5-FKBP11-CD81-FPRP complex would not be formed, and consequently the interferon-induced gene expression would be inhibited because CD9 would remain associated with the FKBP11-CD81-FPRP/CD9 complex. In this respect, we speculate that IFITM5 is involved in the immune system activity in the osteoblast cells and the interaction of the S-palmitoylated IFITM5 with FKBP11 regulates the immune activity.
In addition, it was suggested that the S-palmitoylation on IFITM5 contributes to the bone nodule formation, including morphology and time for mineralization, in the osteoblast cells ( Figure 5 ). It is difficult to conclude at present that the lack of the S-palmitoylation on IFITM5 causes the diffusion of the bone nodules (panel b of Figure 5 -E); we can say, however, that IFITM5 will probably not be S-palmitoylated in the cells in the presence of 2BP. While 2BP is commonly used as an inhibitor of palmitoylation, it also targets many metabolic enzymes [33, 34] . Thus, it is also difficult to interpret the results of the long-term incubation of the osteoblast cells in the presence of 2BP. In any case, these are interesting and key observations in terms of clarifying the role played by the S-palmitoylation of IFITM5 in bone formation, and further studies are required. Figure 6 describes a possible mechanism of the interaction of IFITM5 with FKBP11 and the role of IFITM5 in the osteoblast cell function by means of a comparison with IFITM3. In the case of IFITM3, as shown in Figure 6 -A, the following are observed. (i) The three cysteines are all S-palmitoylated (ii). The S-palmitoylation leads to the clustering and the correct positioning of IFITM3 molecules in the membrane (iii). The Spalmitoylation and the following clustering are crucial for the resistance to the influenza virus. When IFITM3 lacks the Spalmitoylation, the IFITM3 molecules do not cluster, which leads to the significant decrease in the antiviral activity.
On the other hand, Figure 6 -B shows that the following observations are made in the case of IFITM5. (i) Cys86, plus one or two other cysteine residues in IFITM5, i.e., Cys52 and/or Cys53, are S-palmitoylated (ii). The S-palmitoylated IFITM5 is able to interact specifically with FKBP11. The interaction is presumed to be mediated by the palmitic acid(s) attached to the cysteine(s) facing toward the interaction surface on FKBP11. Cys86 is involved in the S-palmitoylation but not in the interaction of IFITM5 with FKBP11. At present, however, little is known about the role of the S-palmitoylation of IFITM5 for the localization in the membrane. When the S-palmitoylation affects the localization of IFITM5 as in the case of IFITM3 [10] , the S-palmitoylated IFITM5 molecules should be localized in the membrane or the depalmitoylated molecules should be delocalized. The loss of the interaction between IFITM5 and FKBP11 could be due to a relocalization of the depalmitoylated IFITM5 that prevents its association with FKBP11 (iii). The Spalmitoylated IFITM5 interacts with the FKBP11-CD81-FPRP/CD9 complex through FKBP11, which induces the dissociation of CD9 from the complex and the expression of 5 immunologically relevant genes. Finally, IFITM5 forms the IFITM5-FKBP11-CD81-FPRP complex. It is unknown at present which of the three states (i)~(iii) illustrated in Figure 6 -B is important for the bone mineralization of the osteoblast cells. The lack of the S-palmitoylation influences the interaction with FKBP11, which could account for the following complex formation and gene expression. In addition, the bone nodule formation is also affected. Note that the role of the Spalmitoylation has been involved in the bone formation [35] . It is indicated that the S-palmitoylation on IFITM5 plays roles not only for the regulation of the immune activity but also for the bone formation.
In conclusion, we have revealed the S-palmitoylation on IFITM5 and its role in the interaction with FKBP11. Not only the immune activity but also the bone mineralization in the osteoblast cells is affected by the S-palmitoylation. In general, the functional role of the S-palmitoylation is different for each protein [36] . For many proteins, the palmitoylation and depalmitoylation cycle is constitutive and regulated by enzymes. Based on the present results, it is difficult to address (i) whether the S-palmitoylation on IFITM5 is constitutive or regulated, or (ii) when and where IFITM5 is S-palmitoylated in the osteoblast cells. Further studies are required and are currently underway. | How many cysteine residues are contained in the first transmembrane domain of IFITM3? | false | 569 | {
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2,486 | Potential Rapid Diagnostics, Vaccine and Therapeutics for 2019 Novel Coronavirus (2019-nCoV): A Systematic Review
https://doi.org/10.3390/jcm9030623
SHA: 9b0c87f808b1b66f2937d7a7acb524a756b6113b
Authors: Pang, Junxiong; Wang, Min Xian; Ang, Ian Yi Han; Tan, Sharon Hui Xuan; Lewis, Ruth Frances; Chen, Jacinta I. Pei; Gutierrez, Ramona A.; Gwee, Sylvia Xiao Wei; Chua, Pearleen Ee Yong; Yang, Qian; Ng, Xian Yi; Yap, Rowena K. S.; Tan, Hao Yi; Teo, Yik Ying; Tan, Chorh Chuan; Cook, Alex R.; Yap, Jason Chin-Huat; Hsu, Li Yang
Date: 2020
DOI: 10.3390/jcm9030623
License: cc-by
Abstract: Rapid diagnostics, vaccines and therapeutics are important interventions for the management of the 2019 novel coronavirus (2019-nCoV) outbreak. It is timely to systematically review the potential of these interventions, including those for Middle East respiratory syndrome-Coronavirus (MERS-CoV) and severe acute respiratory syndrome (SARS)-CoV, to guide policymakers globally on their prioritization of resources for research and development. A systematic search was carried out in three major electronic databases (PubMed, Embase and Cochrane Library) to identify published studies in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Supplementary strategies through Google Search and personal communications were used. A total of 27 studies fulfilled the criteria for review. Several laboratory protocols for confirmation of suspected 2019-nCoV cases using real-time reverse transcription polymerase chain reaction (RT-PCR) have been published. A commercial RT-PCR kit developed by the Beijing Genomic Institute is currently widely used in China and likely in Asia. However, serological assays as well as point-of-care testing kits have not been developed but are likely in the near future. Several vaccine candidates are in the pipeline. The likely earliest Phase 1 vaccine trial is a synthetic DNA-based candidate. A number of novel compounds as well as therapeutics licensed for other conditions appear to have in vitro efficacy against the 2019-nCoV. Some are being tested in clinical trials against MERS-CoV and SARS-CoV, while others have been listed for clinical trials against 2019-nCoV. However, there are currently no effective specific antivirals or drug combinations supported by high-level evidence.
Text: Since mid-December 2019 and as of early February 2020, the 2019 novel coronavirus (2019-nCoV) originating from Wuhan (Hubei Province, China) has infected over 25,000 laboratory-confirmed cases across 28 countries with about 500 deaths (a case-fatality rate of about 2%). More than 90% of the cases and deaths were in China [1] . Based on the initial reported surge of cases in Wuhan, the majority were males with a median age of 55 years and linked to the Huanan Seafood Wholesale Market [2] . Most of the reported cases had similar symptoms at the onset of illness such as fever, cough, and myalgia or fatigue. Most cases developed pneumonia and some severe and even fatal respiratory diseases such as acute respiratory distress syndrome [3] .
The 2019 novel coronavirus (2019-nCoV), a betacoronavirus, forms a clade within the subgenus sarbecovirus of the Orthocoronavirinae subfamily [4] . The severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) are also betacoronaviruses that are zoonotic in origin and have been linked to potential fatal illness during the outbreaks in 2003 and 2012, respectively [5, 6] . Based on current evidence, pathogenicity for 2019-nCoV is about 3%, which is significantly lower than SARS-CoV (10%) and MERS-CoV (40%) [7] . However, 2019-nCoV has potentially higher transmissibility (R0: 1.4-5.5) than both SARS-CoV (R0: [2] [3] [4] [5] and MERS-CoV (R0: <1) [7] .
With the possible expansion of 2019-nCoV globally [8] and the declaration of the 2019-nCoV outbreak as a Public Health Emergency of International Concern by the World Health Organization, there is an urgent need for rapid diagnostics, vaccines and therapeutics to detect, prevent and contain 2019-nCoV promptly. There is however currently a lack of understanding of what is available in the early phase of 2019-nCoV outbreak. The systematic review describes and assesses the potential rapid diagnostics, vaccines and therapeutics for 2019-nCoV, based in part on the developments for MERS-CoV and SARS-CoV.
A systematic search was carried out in three major electronic databases (PubMed, Embase and Cochrane Library) to identify published studies examining the diagnosis, therapeutic drugs and vaccines for Severe Acute Respiratory Syndrome (SARS), Middle East Respiratory Syndrome (MERS) and the 2019 novel coronavirus (2019-nCoV), in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.
There were two independent reviewers each focusing on SARS, MERS, and 2019-nCoV, respectively. A third independent reviewer was engaged to resolve any conflicting article of interest. We used the key words "SARS", "coronavirus", "MERS", "2019 Novel coronavirus", "Wuhan virus" to identify the diseases in the search strategy. The systematic searches for diagnosis, therapeutic drugs and vaccines were carried out independently and the key words "drug", "therapy", "vaccine", "diagnosis", "point of care testing" and "rapid diagnostic test" were used in conjunction with the disease key words for the respective searches.
Examples of search strings can be found in Table S1 . We searched for randomized controlled trials (RCTs) and validation trials (for diagnostics test) published in English, that measured (a) the sensitivity and/or specificity of a rapid diagnostic test or a point-of-care testing kit, (b) the impact of drug therapy or (c) vaccine efficacy against either of these diseases with no date restriction applied. For the 2019-nCoV, we searched for all in vitro, animal, or human studies published in English between 1 December 2019 and 6 February 2020, on the same outcomes of interest. In addition, we reviewed the references of retrieved articles in order to identify additional studies or reports not retrieved by the initial searches. Studies that examined the mechanisms of diagnostic tests, drug therapy or vaccine efficacy against SARS, MERS and 2019-nCoV were excluded. A Google search for 2019-nCoV diagnostics (as of 6 February 2020; Table S2 ) yielded five webpage links from government and international bodies with official information and guidelines (WHO, Europe CDC, US CDC, US FDA), three webpage links on diagnostic protocols and scientific commentaries, and five webpage links on market news and press releases. Six protocols for diagnostics using reverse transcriptase polymerase chain reaction (RT-PCR) from six countries were published on WHO's website [9] . Google search for 2019-nCoV vaccines yielded 19 relevant articles.
With the emergence of 2019-nCoV, real time RT-PCR remains the primary means for diagnosing the new virus strain among the many diagnostic platforms available ( [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] ; Table S3 ). Among the 16 diagnostics studies selected, one study discussed the use of RT-PCR in diagnosing patients with 2019-nCoV [11] ( Table 1 ). The period and type of specimen collected for RT-PCR play an important role in the diagnosis of 2019-nCoV. It was found that the respiratory specimens were positive for the virus while serum was negative in the early period. It has also suggested that in the early days of illness, patients have high levels of virus despite the mild symptoms.
Apart from the commonly used RT-PCR in diagnosing MERS-CoV, four studies identified various diagnostic methods such as reverse transcription loop-mediated isothermal amplification (RT-LAMP), RT-insulated isothermal PCR (RT-iiPCR) and a one-step rRT-PCR assay based on specific TaqMan probes. RT-LAMP has similar sensitivity as real time RT-PCR. It is also highly specific and is used to detect MERS-CoV. It is comparable to the usual diagnostic tests and is rapid, simple and convenient. Likewise, RT-iiPCR and a one-step rRT-PCR assay have also shown similar sensitivity and high specificity for MER-CoV. Lastly, one study focused on the validation of the six commercial real RT-PCR kits, with high accuracy. Although real time RT-PCR is a primary method for diagnosing MERS-CoV, high levels of PCR inhibition may hinder PCR sensitivity (Table 1) .
There are eleven studies that focus on SARS-CoV diagnostic testing (Table 1) . These papers described diagnostic methods to detect the virus with the majority of them using molecular testing for diagnosis. Comparison between the molecular test (i.e RT-PCR) and serological test (i.e., ELISA) showed that the molecular test has better sensitivity and specificity. Hence, enhancements to the current molecular test were conducted to improve the diagnosis. Studies looked at using nested PCR to include a pre-amplification step or incorporating N gene as an additional sensitive molecular marker to improve on the sensitivity (Table 1 ).
In addition, there are seven potential rapid diagnostic kits (as of 24 January 2020; Table 2 ) available on the market for 2019-nCoV. Six of these are only for research purposes. Only one kit from Beijing Genome Institute (BGI) is approved for use in the clinical setting for rapid diagnosis. Most of the kits are for RT-PCR. There were two kits (BGI, China and Veredus, Singapore) with the capability to detect multiple pathogens using sequencing and microarray technologies, respectively. The limit of detection of the enhanced realtime PCR method was 10 2 -fold higher than the standard real-time PCR assay and 10 7fold higher than conventional PCR methods In the clinical aspect, the enhanced realtime PCR method was able to detect 6 cases of SARS-CoV positive samples that were not confirmed by any other assay [25] • The real time PCR has a threshold sensitivity of 10 genome equivalents per reaction and it has a good reproducibility with the inter-assay coefficients of variation of 1.73 to 2.72%. • 13 specimens from 6 patients were positive with viral load range from 362 to 36,240,000 genome equivalents/mL. The real-time RT-PCR reaction was more sensitive than the nested PCR reaction, as the detection limit for the nested PCR reaction was about 10 3 genome equivalents in the standard cDNA control. [34] Real-time reverse-transcription PCR (rRT-PCR); RNA-dependent RNA polymerase (RdRp); open reading frame 1a (ORF1a); Loop-mediated isothermal amplification (LAMP); enzyme-linked immunosorbent assay (ELISA); immunofluorescent assay (IFA); immunochromatographic test (ICT); nasopharyngeal aspirate (NPA).
With the emergence of 2019-nCoV, there are about 15 potential vaccine candidates in the pipeline globally (Table 3 ), in which a wide range of technology (such as messenger RNA, DNA-based, nanoparticle, synthetic and modified virus-like particle) was applied. It will likely take about a year for most candidates to start phase 1 clinical trials except for those funded by Coalition for Epidemic Preparedness Innovations (CEPI). However, the kit developed by the BGI have passed emergency approval procedure of the National Medical Products Administration, and are currently used in clinical and surveillance centers of China [40] .
Of the total of 570 unique studies on 2019-nCoV, SARS CoV or MERS-CoV vaccines screened, only four were eventually included in the review. Most studies on SARS and MERS vaccines were excluded as they were performed in cell or animal models ( Figure 1 ). The four studies included in this review were Phase I clinical trials on SARS or MERS vaccines (Table 4 ) [44] [45] [46] [47] . There were no studies of any population type (cell, animal, human) on the 2019-nCoV at the point of screening. The published clinical trials were mostly done in United States except for one on the SARS vaccine done in China [44] . All vaccine candidates for SARS and MERS were reported to be safe, well-tolerated and able to trigger the relevant and appropriate immune responses in the participants. In addition, we highlight six ongoing Phase I clinical trials identified in the ClinicalTrials.gov register ( [48, 49] ); Table S4 ) [50] [51] [52] . These trials are all testing the safety and immunogenicity of their respective MERS-CoV vaccine candidates but were excluded as there are no results published yet. The trials are projected to complete in December 2020 (two studies in Russia [50, 51] ) and December 2021 (in Germany [52] ).
Existing literature search did not return any results on completed 2019-nCoV trials at the time of writing. Among 23 trials found from the systematic review (Table 5) , there are nine clinical trials registered under the clinical trials registry (ClinicalTrials.gov) for 2019-nCoV therapeutics [53] [54] [55] [56] [57] [58] [59] [60] [61] . Of which five studies on hydroxychloroquine, lopinavir plus ritonavir and arbidol, mesenchymal stem cells, traditional Chinese medicine and glucocorticoid therapy usage have commenced recruitment. The remaining four studies encompass investigation of antivirals, interferon atomization, darunavir and cobicistat, arbidol, and remdesivir usage for 2019-nCoV patients (Table 5) . Seroconversion measured by S1-ELISA occurred in 86% and 94% participants after 2 and 3 doses, respectively, and was maintained in 79% participants up to study end at week 60. Neutralising antibodies were detected in 50% participants at one or more time points during the study, but only 3% maintained neutralisation activity to end of study. T-cell responses were detected in 71% and 76% participants after 2 and 3 doses, respectively. There were no differences in immune responses between dose groups after 6 weeks and vaccine-induced humoral and cellular responses were respectively detected in 77% and 64% participants at week 60.
[47] Molecules developed by the university scientists inhibit two coronavirus enzymes and prevent its replication. The discovered drug targets are said to be more than 95% similar to enzyme targets found on the SARS virus. Researchers note that identified drugs may not be available to address the ongoing outbreak but they hope to make it accessible for future outbreaks.
[85] Besides the six completed randomized controlled trials (RCT) selected from the systematic review (Table 6) , there is only one ongoing randomized controlled trial targeted at SARS therapeutics [92] . The studies found from ClinicalTrials.gov have not been updated since 2013. While many prospective and retrospective cohort studies conducted during the epidemic centered on usage of ribavirin with lopinavir/ritonavir or ribavirin only, there has yet to be well-designed clinical trials investigating their usage. Three completed randomized controlled trials were conducted during the SARS epidemic-3 in China, 1 in Taiwan and 2 in Hong Kong [93] [94] [95] [96] [97] . The studies respectively investigated antibiotic usage involving 190 participants, combination of western and Chinese treatment vs. Chinese treatment in 123 participants, integrative Chinese and Western treatment in 49 patients, usage of a specific Chinese medicine in four participants and early use of corticosteroid in 16 participants. Another notable study was an open non-randomized study investigating ribavirin/lopinavir/ritonavir usage in 152 participants [98] . One randomized controlled trial investigating integrative western and Chinese treatment during the SARS epidemic was excluded as it was a Chinese article [94] .
There is only one ongoing randomized controlled trial targeted at MERS therapeutics [99] . It investigates the usage of Lopinavir/Ritonavir and Interferon Beta 1B. Likewise, many prospective and retrospective cohort studies conducted during the epidemic centered on usage of ribavirin with lopinavir/ritonavir/ribavirin, interferon, and convalescent plasma usage. To date, only one trial has been completed. One phase 1 clinical trial investigating the safety and tolerability of a fully human polyclonal IgG immunoglobulin (SAB-301) was found in available literature [46] . The trial conducted in the United States in 2017 demonstrated SAB-301 to be safe and well-tolerated at single doses. Another trial on MERS therapeutics was found on ClinicalTrials.gov-a phase 2/3 trial in the United States evaluating the safety, tolerability, pharmacokinetics (PK), and immunogenicity on coadministered MERS-CoV antibodies REGN3048 & REGN3051 [100].
Rapid diagnostics plays an important role in disease and outbreak management. The fast and accurate diagnosis of a specific viral infection enables prompt and accurate public health surveillance, prevention and control measures. Local transmission and clusters can be prevented or delayed by isolation of laboratory-confirmed cases and their close contacts quarantined and monitored at home. Rapid diagnostic also facilitates other specific public health interventions such as closure of high-risk facilities and areas associated with the confirmed cases for prompt infection control and environmental decontamination [11, 101] .
Laboratory diagnosis can be performed by: (a) detecting the genetic material of the virus, (b) detecting the antibodies that neutralize the viral particles of interest, (c) detecting the viral epitopes of interest with antibodies (serological testing), or (d) culture and isolation of viable virus particles.
The key limitations of genetic material detection are the lack of knowledge of the presence of viable virus, the potential cross-reactivity with non-specific genetic regions and the short timeframe for accurate detection during the acute infection phase. The key limitations of serological testing is the need to collect paired serum samples (in the acute and convalescent phases) from cases under investigation for confirmation to eliminate potential cross-reactivity from non-specific antibodies from past exposure and/or infection by other coronaviruses. The limitation of virus culture and isolation is the long duration and the highly specialized skills required of the technicians to process the samples. All patients recovered.
Significantly shorted time from the disease onset to the symptom improvement in treatment (5.10 ± 2.83 days) compared to control group (7.62 ± 2.27 days) (p < 0.05) No significant difference in blood routine improvement, pulmonary chest shadow in chest film improvement and corticosteroid usgae between the 2 groups. However, particularly in the respect of improving clinical symptoms, elevating quality of life, promoting immune function recovery, promoting absorption of pulmonary inflammation, reducing the dosage of cortisteroid and shortening the therapeutic course, treatment with integrative chinese and western medicine treatment had obvious superiority compared with using control treatment alone. Single infusions of SAB-301 up to 50 mg/kg appear to be safe and well-tolerated in healthy participants. [46] Where the biological samples are taken from also play a role in the sensitivity of these tests. For SARS-CoV and MERS-CoV, specimens collected from the lower respiratory tract such as sputum and tracheal aspirates have higher and more prolonged levels of viral RNA because of the tropism of the virus. MERS-CoV viral loads are also higher for severe cases and have longer viral shedding compared to mild cases. Although upper respiratory tract specimens such as nasopharyngeal or oropharyngeal swabs can be used, they have potentially lower viral loads and may have higher risk of false-negatives among the mild MERS and SARS cases [102, 103] , and likely among the 2019-nCoV cases.
The existing practices in detecting genetic material of coronaviruses such as SARS-CoV and MERS-CoV include (a) reverse transcription-polymerase chain reaction (RT-PCR), (b) real-time RT-PCR (rRT-PCR), (c) reverse transcription loop-mediated isothermal amplification (RT-LAMP) and (d) real-time RT-LAMP [104] . Nucleic amplification tests (NAAT) are usually preferred as in the case of MERS-CoV diagnosis as it has the highest sensitivity at the earliest time point in the acute phase of infection [102] . Chinese health authorities have recently posted the full genome of 2019-nCoV in the GenBank and in GISAID portal to facilitate in the detection of the virus [11] . Several laboratory assays have been developed to detect the novel coronavirus in Wuhan, as highlighted in WHO's interim guidance on nCoV laboratory testing of suspected cases. These include protocols from other countries such as Thailand, Japan and China [105] .
The first validated diagnostic test was designed in Germany. Corman et al. had initially designed a candidate diagnostic RT-PCR assay based on the SARS or SARS-related coronavirus as it was suggested that circulating virus was SARS-like. Upon the release of the sequence, assays were selected based on the match against 2019-nCoV upon inspection of the sequence alignment. Two assays were used for the RNA dependent RNA polymerase (RdRP) gene and E gene where E gene assay acts as the first-line screening tool and RdRp gene assay as the confirmatory testing. All assays were highly sensitive and specific in that they did not cross-react with other coronavirus and also human clinical samples that contained respiratory viruses [11] .
The Hong Kong University used two monoplex assays which were reactive with coronaviruses under the subgenus Sarbecovirus (consisting of 2019-nCoV, SARS-CoV and SARS-like coronavirus). Viral RNA extracted from SARS-CoV can be used as the positive control for the suggested protocol assuming that SARS has been eradicated. It is proposed that the N gene RT-PCR can be used as a screening assay while the Orf1b assay acts as a confirmatory test. However, this protocol has only been evaluated with a panel of controls with the only positive control SARS-CoV RNA. Synthetic oligonucleotide positive control or 2019-nCoV have yet to be tested [106] .
The US CDC shared the protocol on the real time RT-PCR assay for the detection of the 2019-nCoV with the primers and probes designed for the universal detection of SARS-like coronavirus and the specific detection of 2019-nCoV. However, the protocol has not been validated on other platforms or chemistries apart from the protocol described. There are some limitations for the assay. Analysts engaged have to be trained and familiar with the testing procedure and result interpretation. False negative results may occur due to insufficient organisms in the specimen resulting from improper collection, transportation or handling. Also, RNA viruses may show substantial genetic variability. This could result in mismatch between the primer and probes with the target sequence which can diminish the assay performance or result in false negative results [107] . Point-of-care test kit can potentially minimize these limitations, which should be highly prioritized for research and development in the next few months.
Serological testing such as ELISA, IIFT and neutralization tests are effective in determining the extent of infection, including estimating asymptomatic and attack rate. Compared to the detection of viral genome through molecular methods, serological testing detects antibodies and antigens. There would be a lag period as antibodies specifically targeting the virus would normally appear between 14 and 28 days after the illness onset [108] . Furthermore, studies suggest that low antibody titers in the second week or delayed antibody production could be associated with mortality with a high viral load. Hence, serological diagnoses are likely used when nucleic amplification tests (NAAT) are not available or accessible [102] .
Vaccines can prevent and protect against infection and disease occurrence when exposed to the specific pathogen of interest, especially in vulnerable populations who are more prone to severe outcomes. In the context of the current 2019-nCoV outbreak, vaccines will help control and reduce disease transmission by creating herd immunity in addition to protecting healthy individuals from infection. This decreases the effective R0 value of the disease. Nonetheless, there are social, clinical and economic hurdles for vaccine and vaccination programmes, including (a) the willingness of the public to undergo vaccination with a novel vaccine, (b) the side effects and severe adverse reactions of vaccination, (c) the potential difference and/or low efficacy of the vaccine in populations different from the clinical trials' populations and (d) the accessibility of the vaccines to a given population (including the cost and availability of the vaccine).
Vaccines against the 2019-nCoV are currently in development and none are in testing (at the time of writing). On 23 January 2020, the Coalition for Epidemic Preparedness Innovations (CEPI) announced that they will fund vaccine development programmes with Inovio, The University of Queensland and Moderna, Inc respectively, with the aim to test the experimental vaccines clinically in 16 weeks (By June 2020). The vaccine candidates will be developed by the DNA, recombinant and mRNA vaccine platforms from these organizations [109] .
Based on the most recent MERS-CoV outbreak, there are already a number of vaccine candidates being developed but most are still in the preclinical testing stage. The vaccines in development include viral vector-based vaccine, DNA vaccine, subunit vaccine, virus-like particles (VLPs)-based vaccine, inactivated whole-virus (IWV) vaccine and live attenuated vaccine. The latest findings for these vaccines arebased on the review by Yong et al. (2019) in August 2019 [110] . As of the date of reporting, there is only one published clinical study on the MERS-CoV vaccine by GeneOne Life Science & Inovio Pharmaceuticals [47] . There was one SARS vaccine trial conducted by the US National Institute of Allergy and Infectious Diseases. Both Phase I clinical trials reported positive results, but only one has announced plans to proceed to Phase 2 trial [111] .
Due to the close genetic relatedness of SARS-CoV (79%) with 2019-nCoV [112] , there may be potential cross-protective effect of using a safe SARS-CoV vaccine while awaiting the 2019-nCoV vaccine. However, this would require small scale phase-by-phase implementation and close monitoring of vaccinees before any large scale implementation.
Apart from the timely diagnosis of cases, the achievement of favorable clinical outcomes depends on the timely treatment administered. ACE2 has been reported to be the same cell entry receptor used by 2019-nCoV to infect humans as SARS-CoV [113] . Hence, clinical similarity between the two viruses is expected, particularly in severe cases. In addition, most of those who have died from MERS-CoV, SARS-CoV and 2019-nCoV were advance in age and had underlying health conditions such as hypertension, diabetes or cardiovascular disease that compromised their immune systems [114] . Coronaviruses have error-prone RNA-dependent RNA polymerases (RdRP), which result in frequent mutations and recombination events. This results in quasispecies diversity that is closely associated with adaptive evolution and the capacity to enhance viral-cell entry to cause disease over time in a specific population at-risk [115] . Since ACE2 is abundantly present in humans in the epithelia of the lung and small intestine, coronaviruses are likely to infect the upper respiratory and gastrointestinal tract and this may influence the type of therapeutics against 2019-nCoV, similarly to SAR-CoV.
However, in the years following two major coronavirus outbreaks SARS-CoV in 2003 and MERS-CoV in 2012, there remains no consensus on the optimal therapy for either disease [116, 117] . Well-designed clinical trials that provide the gold standard for assessing the therapeutic measures are scarce. No coronavirus protease inhibitors have successfully completed a preclinical development program despite large efforts exploring SARS-CoV inhibitors. The bulk of potential therapeutic strategies remain in the experimental phase, with only a handful crossing the in vitro hurdle. Stronger efforts are required in the research for treatment options for major coronaviruses given their pandemic potential. Effective treatment options are essential to maximize the restoration of affected populations to good health following infections. Clinical trials have commenced in China to identify effective treatments for 2019-nCoV based on the treatment evidence from SARS and MERS. There is currently no effective specific antiviral with high-level evidence; any specific antiviral therapy should be provided in the context of a clinical study/trial. Few treatments have shown real curative action against SARS and MERS and the literature generally describes isolated cases or small case series.
Many interferons from the three classes have been tested for their antiviral activities against SARS-CoV both in vitro and in animal models. Interferon β has consistently been shown to be the most active, followed by interferon α. The use of corticosteroids with interferon alfacon-1 (synthetic interferon α) appeared to have improved oxygenation and faster resolution of chest radiograph abnormalities in observational studies with untreated controls. Interferon has been used in multiple observational studies to treat SARS-CoV and MERS-CoV patients [116, 117] . Interferons, with or without ribavirin, and lopinavir/ritonavir are most likely to be beneficial and are being trialed in China for 2019-nCoV. This drug treatment appears to be the most advanced. Timing of treatment is likely an important factor in effectiveness. A combination of ribavirin and lopinavir/ritonavir was used as a post-exposure prophylaxis in health care workers and may have reduced the risk of infection. Ribavirin alone is unlikely to have substantial antiviral activities at clinically used dosages. Hence, ribavirin with or without corticosteroids and with lopinavir and ritonavir are among the combinations employed. This was the most common agent reported in the available literature. Its efficacy has been assessed in observational studies, retrospective case series, retrospective cohort study, a prospective observational study, a prospective cohort study and randomized controlled trial ranging from seven to 229 participants [117] . Lopinavir/ritonavir (Kaletra) was the earliest protease inhibitor combination introduced for the treatment of SARS-CoV. Its efficacy was documented in several studies, causing notably lower incidence of adverse outcomes than with ribavirin alone. Combined usage with ribavirin was also associated with lower incidence of acute respiratory distress syndrome, nosocomial infection and death, amongst other favorable outcomes. Recent in vitro studies have shown another HIV protease inhibitor, nelfinavir, to have antiviral capacity against SARS-CoV, although it has yet to show favorable outcomes in animal studies [118] . Remdesivir (Gilead Sciences, GS-5734) nucleoside analogue in vitro and in vivo data support GS-5734 development as a potential pan-coronavirus antiviral based on results against several coronaviruses (CoVs), including highly pathogenic CoVs and potentially emergent BatCoVs. The use of remdesivir may be a good candidate as an investigational treatment.
Improved mortality following receipt of convalescent plasma in various doses was consistently reported in several observational studies involving cases with severe acute respiratory infections (SARIs) of viral etiology. A significant reduction in the pooled odds of mortality following treatment of 0.25 compared to placebo or no therapy was observed [119] . Studies were however at moderate to high risk of bias given their small sample sizes, allocation of treatment based on the physician's discretion, and the availability of plasma. Factors like concomitant treatment may have also confounded the results. Associations between convalescent plasma and hospital length of stay, viral antibody levels, and viral load respectively were similarly inconsistent across available literature. Convalescent plasma, while promising, is likely not yet feasible, given the limited pool of potential donors and issues of scalability. Monoclonal antibody treatment is progressing. SARS-CoV enters host cells through the binding of their spike (S) protein to angiotensin converting enzyme 2 (ACE2) and CD209L [118] . Human monoclonal antibodies to the S protein have been shown to significantly reduce the severity of lung pathology in non-human primates following MERS-CoV infection [120] . Such neutralizing antibodies can be elicited by active or passive immunization using vaccines or convalescent plasma respectively. While such neutralizing antibodies can theoretically be harvested from individuals immunized with vaccines, there is uncertainty over the achievement of therapeutic levels of antibodies.
Other therapeutic agents have also been reported. A known antimalarial agent, chloroquine, elicits antiviral effects against multiple viruses including HIV type 1, hepatitis B and HCoV-229E. Chloroquine is also immunomodulatory, capable of suppressing the production and release of factors which mediate the inflammatory complications of viral diseases (tumor necrosis factor and interleukin 6) [121] . It is postulated that chloroquine works by altering ACE2 glycosylation and endosomal pH. Its anti-inflammatory properties may be beneficial for the treatment of SARS. Niclosamide as a known drug used in antihelminthic treatment. The efficacy of niclosamide as an inhibitor of virus replication was proven in several assays. In both immunoblot analysis and immunofluorescence assays, niclosamide treatment was observed to completely inhibit viral antigen synthesis. Reduction of virus yield in infected cells was dose dependent. Niclosamide likely does not interfere in the early stages of virus attachment and entry into cells, nor does it function as a protease inhibitor. Mechanisms of niclosamide activity warrant further investigation [122] . Glycyrrhizin also reportedly inhibits virus adsorption and penetration in the early steps of virus replication. Glycyrrhizin was a significantly potent inhibitor with a low selectivity index when tested against several pathogenic flaviviruses. While preliminary results suggest production of nitrous oxide (which inhibits virus replication) through induction of nitrous oxide synthase, the mechanism of Glycyrrhizin against SARS-CoV remains unclear. The compound also has relatively lower toxicity compared to protease inhibitors like ribavirin [123] . Inhibitory activity was also detected in baicalin [124] , extracted from another herb used in the treatment of SARS in China and Hong Kong. Findings on these compounds are limited to in vitro studies [121] [122] [123] [124] .
Due to the rapidly evolving situation of the 2019-nCoV, there will be potential limitations to the systematic review. The systematic review is likely to have publication bias as some developments have yet to be reported while for other developments there is no intention to report publicly (or in scientific platforms) due to confidentiality concerns. However, this may be limited to only a few developments for review as publicity does help in branding to some extent for the company and/or the funder. Furthermore, due to the rapid need to share the status of these developments, there may be reporting bias in some details provided by authors of the scientific articles or commentary articles in traditional media. Lastly, while it is not viable for any form of quality assessment and metaanalysis of the selected articles due to the limited data provided and the heterogeneous style of reporting by different articles, this paper has provided a comprehensive overview of the potential developments of these pharmaceutical interventions during the early phase of the outbreak. This systematic review would be useful for cross-check when the quality assessment and meta-analysis of these developments are performed as a follow-up study.
Rapid diagnostics, vaccines and therapeutics are key pharmaceutical interventions to limit transmission of respiratory infectious diseases. Many potential developments on these pharmaceutical interventions for 2019-nCoV are ongoing in the containment phase of this outbreak, potentially due to better pandemic preparedness than before. However, lessons from MERS-CoV and SARS-CoV have shown that the journeys for these developments can still be challenging moving ahead.
Supplementary Materials: The following are available online at www.mdpi.com/xxx/s1, Table S1 : Example of full search strategy in Pubmed, Table S2 : Google Search: 2019-nCoV diagnostics, Table S3 : Summary of diagnostic assays developed for 2019-nCoV, Table S4 | What are the symptoms at the onset? | false | 3,621 | {
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2,634 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What was done for the prediction of protein secondary structures? | false | 3,712 | {
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1,741 | MERS coronavirus: diagnostics, epidemiology and transmission
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4687373/
SHA: f6fcf1a99cbd073c5821d1c4ffa3f2c6daf8ae29
Authors: Mackay, Ian M.; Arden, Katherine E.
Date: 2015-12-22
DOI: 10.1186/s12985-015-0439-5
License: cc-by
Abstract: The first known cases of Middle East respiratory syndrome (MERS), associated with infection by a novel coronavirus (CoV), occurred in 2012 in Jordan but were reported retrospectively. The case first to be publicly reported was from Jeddah, in the Kingdom of Saudi Arabia (KSA). Since then, MERS-CoV sequences have been found in a bat and in many dromedary camels (DC). MERS-CoV is enzootic in DC across the Arabian Peninsula and in parts of Africa, causing mild upper respiratory tract illness in its camel reservoir and sporadic, but relatively rare human infections. Precisely how virus transmits to humans remains unknown but close and lengthy exposure appears to be a requirement. The KSA is the focal point of MERS, with the majority of human cases. In humans, MERS is mostly known as a lower respiratory tract (LRT) disease involving fever, cough, breathing difficulties and pneumonia that may progress to acute respiratory distress syndrome, multiorgan failure and death in 20 % to 40 % of those infected. However, MERS-CoV has also been detected in mild and influenza-like illnesses and in those with no signs or symptoms. Older males most obviously suffer severe disease and MERS patients often have comorbidities. Compared to severe acute respiratory syndrome (SARS), another sometimes- fatal zoonotic coronavirus disease that has since disappeared, MERS progresses more rapidly to respiratory failure and acute kidney injury (it also has an affinity for growth in kidney cells under laboratory conditions), is more frequently reported in patients with underlying disease and is more often fatal. Most human cases of MERS have been linked to lapses in infection prevention and control (IPC) in healthcare settings, with approximately 20 % of all virus detections reported among healthcare workers (HCWs) and higher exposures in those with occupations that bring them into close contact with camels. Sero-surveys have found widespread evidence of past infection in adult camels and limited past exposure among humans. Sensitive, validated reverse transcriptase real-time polymerase chain reaction (RT-rtPCR)-based diagnostics have been available almost from the start of the emergence of MERS. While the basic virology of MERS-CoV has advanced over the past three years, understanding of the interplay between camel, environment, and human remains limited. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12985-015-0439-5) contains supplementary material, which is available to authorized users.
Text: An email from Dr Ali Mohamed Zaki, an Egyptian virologist working at the Dr Soliman Fakeeh Hospital in Jeddah in the Kingdom of Saudi Arabia (KSA) announced the first culture of a new coronavirus to the world. The email was published on the website of the professional emerging diseases (ProMED) network on 20 th September 2012 [1] (Fig. 1) and described the first reported case, a 60 year old man from Bisha in the KSA. This information led to the rapid discovery of a second case of the virus, this time in an ill patient in the United Kingdom, who had been transferred from Qatar for care [2] . The new virus was initially called novel coronavirus (nCoV) and subsequentlty entitled the Middle East respiratoy syndrome coronavirus (MERS-CoV). As of 2 nd of September 2015, there have been 1,493 detections of viral RNA or virus-specific antibodies across 26 countries (Additional file 1: Figure S1 ) confirmed by the World Health Organization (WHO), with over a third of the positive people dying (at least 527, 35 %) [3] .
Since that first report, a slow discovery process over the following two to three years revealed a virus that had infected over 90 % of adult dromedary camels (DC; Camelus dromedarius) in the KSA [4] , also DCs across the Arabian Peninsula and parts of Africa that are a source of DC imports for the KSA [5] . To date, MERS-CoV has not been detected in DCs tested in zoos or herds from other parts of the world [6] [7] [8] [9] . Occasionally, virus is transmitted from infected DCs to exposed humans. Subsequent transmission to other humans requires relatively close and prolonged exposure [10] .
The first viral isolate was patented and concerns were raised that this would restrict access to both the virus and to viral diagnostics [11, 12] . However, sensitive, validated reverse transcriptase real-time polymerase chain reaction (RT-rtPCR)-based diagnostics were quickly described and virus was made freely available subject to routine biosafety considerations [13] . Subsequent epidemiology and research has identified the cell receptor as exopeptidase dipeptidyl peptidase 4 (DPP4; also called CD26); that MERS-CoV has a broad tropism, replicating better in some cells lines and eliciting a more proinflammatory response than SARS-CoV; is widespread in DCs; has the potential to infect other animals and that MERS kills its human host more often than SARS did (20-40 % versus 9 % for SARS [14] ) [15] [16] [17] [18] [19] .
In humans, overt disease was given the name Middle East respiratory syndrome, with the acronym MERS. From intermittent animal-to-human spill-over events, the MERS-CoV spreads sporadically among people, causing more severe disease among older adults, especially males, with pre-existing diseases. The spread of MERS-CoV among humans has often been associated with outbreaks in hospitals, with around 20 % of all cases to date involving healthcare workers (HCWs).
Although DCs appear to suffer the equivalent of a 'common cold' from MERS-CoV infection, in humans, the virus can be a more serious and opportunistic pathogen associated with the death of up to 40 % of reported cases. It has yet to be established whether infections thought to have been acquired from an animal source produce a more severe outcome than those spread between humans [20] . Studies have established that the mean incubation period for MERS is five to six days, ranging from two to 16 days, with 13 to 14 days between when illness begins in one person and subsequently spreads to another [21] [22] [23] [24] . Among those with progressive illness, the median time to death is 11 to 13 days, ranging from five to 27 days [23, 24] . Fever and gastrointestinal symptoms may form a prodrome, after which symptoms decline, only to be followed by a more severe systemic and respiratory syndrome [25, 26] .
The first WHO case definition [27] defined probable cases of MERS based on the presence of febrile illness, cough and requirement for hospitalization with suspicion of lower respiratory tract (LRT) involvement. It also included roles for contact with a probable or confirmed case or for travel or residence within the Arabian Peninsula. If strictly adhered to, only the severe syndrome would be subject to laboratory testing, which was the paradigm early on [21] . From July 2013, the revised WHO case definition included the importance of seeking out and understanding the role of asymptomatic cases and from June 2014, the WHO definition more clearly stated that a confirmed case included any person whose sample was RT-PCR positive for MERS-CoV, or who produced a seroconversion, irrespective of clinical signs and symptoms. [28] [29] [30] Apart from the WHO and the KSA Ministry of Health reports, asymptomatic or subclinical cases of MERS-CoV infection were documented in the scientific literature although not always as often as occurred early on [31, 32] . The KSA definition of a case became more strict on 13 th May 2014, relying on the presence of both clinical features and laboratory confirmation [33] . Testing of asymptomatic people was recommended against from December 2014 [34] , reinforced by a case definition released by the KSA Ministry of Health in June 2015 [35] . The KSA has been the source of 79 % of human cases. Severe MERS is notable for its impact among older men with comorbid diseases including diabetes mellitus, cirrhosis and various lung, renal and cardiac conditions [36] [37] [38] . Interestingly in June 2015, an outbreak in South Korea followed a similar distribution [39, 40] . Among laboratory confirmed cases, fever, cough and upper respiratory tract (URT) signs and symptoms usually occur first, followed within a week by progressive LRT distress and lymphopaenia [37] . Patients often present to a hospital with pneumonia, or worse, and secondary bacterial infections have been reported [37, 41] . Disease can progress to acute respiratory distress syndrome and multiorgan system failure [37] . MERS has reportedly killed approximately 35 % of all reported cases, 42 % of cases in the KSA, yet only 19 % of cases in South Korea, where mortality ranged from 7 % among younger age groups to 40 % among those aged 60 years and above [42] ; all may be inflated values with asymptomatic or mild infections sometimes not sought or not reported [34] . General supportive care is key to managing severe cases [43] . Children under the age of 14 years are rarely reported to be positive for MERS-CoV, comprising only 1.1 % (n = 16) of total reported cases. Between 1 st September 2012 and 2 nd December 2013, a study described the then tally of paediatric cases in the KSA, which stood at 11 (two to 16 years of age; median 13 years); nine were asymptomatic (72 %) and one infant died [44] . In Amman, Jordan, 1,005 samples from hospitalized children under the age of two years with fever and/or respiratory signs and symptoms were tested but none were positive for MERS-CoV RNA, despite being collected at a similar time to the first known outbreak of MERS-CoV in the neighbouring town of Al-Zarqa [45] . A second trimester stillbirth occurred in a pregnant woman during an acute respiratory illness and while not RT-rtPCR positive, the mother did subsequently develop antibodies to MERS-CoV, suggestive of recent infection [46] . Her exposure history to a MERS-CoV RT-rtPCR positive relative and an antibody-reactive husband, her incubation period and her symptom history met the WHO criteria for being a probable MERS-CoV case [46] .
Diagnostic methods were published within days of the ProMED email announcing the first MERS case [47] , including several now gold standard in-house RT-rtPCR assays (Fig. 2 ) as well as virus culture in Vero and LLC-MK2 cells [18, 47, 48] . A colorectal adenocarcinoma (Caco-2) epithelial cell line has since been recommended for isolation of infections MERS-CoV [49] . We previously [18] .). Open reading frames are indicated as yellow rectangles bracketed by terminal untranslated regions (UTR; grey rectangles). FS-frame-shift. Predicted regions encompassing recombination break-points are indicated by orange pills. Created using Geneious v8.1 [211] and annotated using Adobe Illustrator. Beneath this is a schematic depicting the location of RT-PCR primers (blue arrows indicate direction) and oligoprobes (green rectangles) used in the earliest RT-rtPCR screening assays and conventional, semi-nested (three primers) RT-PCR confirmatory sequencing assays [47, 48] . Publication order is noted by first [27 th September 2012; red] and second [6 th December 2012; orange] coloured rectangles; both from Corman et al. [47, 48] Those assays recommended by the WHO are highlighted underneath by yellow dots [53] . The NSeq reverse primer has consistently contained one sequence mismatch with some MERS-CoV variants. An altered version of that from Mackay IM, Arden KE. Middle East respiratory syndrome: An emerging coronavirus infection tracked by the crowd. Virus Res 2015 Vol 202:60-88 with permission from Elsevier [5] reviewed the broad tropism of MERS-CoV [5] . However, as is well described, cell culture is a slow, specialised and insensitive method [50] while PCR-based techniques are the preferred method for MERS-CoV detection.
The first open reading frames (ORF 1a and 1b; Fig. 2 ) have become a key diagnostic and taxonomic target for CoV species identification. With less than 80 % identity between the amino acid sequence of MERS ORF 1ab and betacoronavirus relatives, Tylonycteris bat HKU4 and Pipistrellus bat HKU5, it can be concluded that it is a novel and distinct virus. MERS-CoV is predicted to encode ten open reading frames with 5' and 3' untranslated regions [51] . The structural proteins include the spike (S), envelope (E), membrane (M) and nucleocapsid (N) [52] . The products of ORF1a and ORF1b are predicted to encode nonstructural proteins.
The majority of specimen testing to date has employed validated RT-rtPCR assays shown to be sensitive and specific [47, 48, 53] . The RealStar® kit uses these WHOrecommended assays [54] . The target sequences of these screening assays have not changed among genomes examined until at least mid-2015 (IMM observation). Other RT-rtPCR assays have been developed and validated for use as laboratory-based diagnostic tools [55] [56] [57] . Additionally, loop-mediated [58, 59] or recombinase polymerase [60] isothermal assays have been designed for field deployment.
The detection of MERS-CoV antigen has not been common to date but the combination of short turnaround time from test to result, high throughput and identification of viral proteins makes this an attractive option. Detection of viral proteins rather than viral RNA indicates the likely presence of infectious virus. The first rapid immunochromatographic tool described could detect recombinant MERS-CoV nucleocapsid protein from DC nasal swabs with 94 % sensitivity and 100 % specificity compared to RT-rtPCR [61] . A different approach used a monoclonal antibody-based capture ELISA targeting the MERS-CoV nucleocapsid protein with a sensitivity of 10 3 TCID 50 and 100 % specificity [62] .
Demonstration of a seroconversion to a MERS-CoV infection meets the current WHO definition of a case so optimized and thoroughly validated sero-assays employed alongside good clinical histories are useful to both identify prior MERS-CoV infection and help support transmission studies. Because serology testing is, by its nature, retrospective, it is usual to detect a viral footprint, in the form of antibodies, in the absence of any signs or symptoms of disease and often in the absence of any viral RNA [63] .
Strategic, widespread sero-surveys of humans using samples collected after 2012 are infrequent. Much of the Arabian Peninsula and all of the Horn of Africa lack baseline data describing the proportion of the community who may have been infected by a MERS-CoV. However, sero-surveys have had widespread use in elucidating the role of DCs as a transmission source for MERS-CoV. Because of the identity shared between DC and human MERS-CoV (see Molecular epidemiology: using genomes to understand outbreaks), serological assays for DC sero-surveys should be transferrable to human screening with minimal re-configuration. Also, no diagnostically relevant variation in neutralization activity have been found from among a range of circulating tested MERS-CoV isolates and sera, so whole virus or specific protein-based sero-assays should perform equivalently in detecting serological responses to the single MERS-CoV serotype [49] . The development of robust serological assays requires reliable panels of wellcharacterized animal or human sera, including those positive for antibodies specific to MERS-CoV, as well as to likely sources of cross-reaction [64] . Obtaining these materials was problematic and slowed the development and commercialization of antibody detection assays for human testing [64] . A number of commercial ELISA kits, immunofluorescent assays (IFA) kits, recombinant proteins and monoclonal antibodies have been released [31, [65] [66] [67] [68] . Initially, conventional IFAs were used for human sero-surveys. These relied on MERS-CoV-infected cell culture as an antigen source, detecting the presence of human anti-MERS-CoV IgG, IgM or neutralizing antibodies in human samples [18, 48, 69] . No sign of MERS-CoV antibodies was found among 2,400 sera from patients visiting Hospital in Jeddah, from 2010 through 2012, prior to the description of MERS-CoV [18] . Nor did IFA methods detect any sign of prior MERS-CoV infection among a small sample of 130 healthy blood donors from another Hospital in Jeddah (collected between Jan and Dec 2012) [70] . Of 226 slaughterhouse workers, only eight (3.5 %) were positive by IFA, and those sera could not be confirmed by virus neutralization (NT) test. The study indicated that HCoV-HKU1 was a likely source of crossreactive antigen in the whole virus IFA [70] . Whole virus MERS-CoV IFA also suffered from some cross-reactivity with convalescent SARS patient sera and this could not be resolved by an NT test which was also cross-reactive [71] . IFA using recombinant proteins instead of whole-virus IFA, has been shown to be a more specific tool [31] . Since asymptomatic zoonoses have been posited [72] , an absence of antibodies to MERS-CoV among some humans who have regular and close contact with camels may reflect the rarity of actively infected animals at butcheries, a limited transmission risk associated with slaughtering DCs [70] , a pre-existing cross-protective immune status or some other factor(s) resulting in a low risk of disease and concurrent seroconversion developing after exposure in this group. IFA using recombinant proteins instead.
Some sero-assays have bypassed the risks of working with infectious virus by creating transfected cells expressing recombinant portions of the MERS-CoV nucleocapsid and spike proteins [48, 73] , or using a recombinant lentivirus expressing MERS-CoV spike protein and luciferase [74, 75] . A pseudo particle neutralization (ppNT) assay has seen widespread used in animal studies and was at least as sensitive as the traditional microneutralization (MNT) test. [10, 74, [76] [77] [78] ] Studies using small sample numbers and ppNT found no evidence of MERS-CoV neutralizing antibody in sera from 158 children with LRT infections between May 2010 and May 2011, 110 sera from 19 to 52 year old male blood donors and 300 selfidentified animal workers from the Jazan Region of the KSA during 2012 [79, 80] . Similarly, a study of four herdsmen in contact with an infected DC herd in Al-Ahsa, eight people who had intermittent contact with the herd, 30 veterinary surgeons and support staff who were not exposed to the herd, three unprotected abattoir workers in Al-Ahsa and 146 controls who were not exposed to DCs in any professional role, found none with serological evidence of past MERS-CoV infection using the ppNT assay [10] . A delay in the neutralizing antibody response to MERS-CoV infection was associated with increased disease severity in South Korea cases with most responses detectable by week three of illness while others, even though disease was severe, did not respond for four or more weeks [81] . The implications for our ability to detect any response in mild or asymptomatic cases was not explored but may be a signifcant factor in understanding exposure in the wider community.
A Jordanian outbreak of acute LRT disease in a hospital in 2012 was retrospectively found to be associated with MERS-CoV infection, initially using RT-rtPCR, but subsequently, and on a larger scale, through positivity by ELISA and IFA or MNT test. [46, 82, 83] This outbreak predated the first case of MERS in the KSA. The ELISA used a recombinant nucleocapsid protein from the group 2 betacoronavirus bat-CoV HKU5 to identify antibodies against the equivalent crossreactive MERS-CoV protein [71] . It was validated using 545 sera collected from people with prior HCoV-OC43, HCoV-229E, SARS-CoV, HCoV-NL63, HRV, HMPV or influenza A(H1N1) infections but was reportedly less specific than the recombinant IFA discussed above. It was still considered an applicable tool for screening large sample numbers [82] . A protein microarray expressing the S1 protein subunit has also been validated and widely used for DC testing [5, 84] . Detection of MERS-CoV infection using ELISA or S1 subunit protein microarray [84] is usually followed by confirmatory IFA and/ or a plaque-reduction neutralization (PRNT) [69, 70, 85] or MNT test. [74, 85, 86] This confirmatory process aims toensure the antibodies detected are able to specifically neutralize the intended virus and are not more broadly reactive to other coronaviruses found in DCs (bovine CoV, BCoV) or humans (HCoV-OC43, HCoV-229E, HCoV-NL63, HCoV-HKU1, SARS-CoV). In the largest study of human sera, a tiered diagnostic process assigned both recombinant IFA and recombinant ELISA positive sera to 'stage 1' seropositivity. A stage 2 seropositive result additionally required a suitably titred PRNT result [87] . The study found 15 sera collected in 2012 to 2013 from 10,009 (0.2 %) people in 13 KSA provinces contained MERS-CoV antibodies, but significantly higher proportions in occurred in camel shepherds (two of 87; 2.3 %) and slaughterhouse workers (five of 140; 3.6 %) [87] . Contemporary surveys are needed.
MERS-CoV does not appear to be easily transmitted from DCs to humans, or perhaps it is [72] , but generally does not trigger a detectable immune response if only mild disease or asymptomatic infection results. Serology assays are in need of further validation in this area so care is required when moving newly developed diagnostic serology algorithms from a research setting to one that informs public health decisions. This was reinforced when a false positive US case, purported to have been infected after a handshake and two face-to-face meetings, did not withstand further confirmatory analysis using a more specific, NT assay and was subsequently retracted [88, 89] .
The WHO recommends sampling from the LRT for MERS-CoV RT-rtPCR testing, especially when sample collection is delayed by a week or more after onset of symptoms. [53] LRT samples are also best for attempting isolation of infectious virus, although the success of culture is reduced when disease persists [49] . Recommended sample types include bronchoalveolar lavage (BAL), tracheal/tracheobronchial aspirate, pleural fluid and sputum [53, 90] . Fresh samples yield better diagnostic results than refrigerated material [69] and if delays in testing of ≥72 h are likely, samples (except for blood) should be frozen at −70°C [90] . If available, lung biopsy or autopsy tissues can also be tested [53] . The URT is a less invasive and more convenient sampling site however, and an oropharyngeal and throat swab or a nasopharyngeal aspirate/wash are recommended when URT sampling is to be conducted [90] . Paired sera, collected two to three weeks apart are preferable for serological testing while a single sample is suggested to be sufficient if collected two weeks after onset of disease or a single serum collected during the first 10-12 days if conducting RT-rtPCR [53, 90] . Human urine and stool have been found to contain MERS-CoV RNA 12 to 26 days after symptom onset [25, 69, 91] and are listed as samples that should be considered [53, 90] . In two cases that arrived in the Netherlands, urine was RT-rtPCR negative but faeces was weakly positive and sera were RT-rtPCR positive for five days or more [25] . The finding of MERS-CoV viral RNA in serum provides an avenue for retrospective PCR-based studies if respiratory samples are unavailable [83] . RNAaemia may also correlate with disease severity; signs of virus were cleared from the serum of a recovered patient, yet lingered until the death of another [92] .
Clinically suspected MERS cases may return negative results by RT-rtPCR. Data have shown one or more negative URT samples may be contradicted by further URT sampling or the use of LRT samples, which is preferred [2, 43, 93] . Higher viral loads occur in the LRT compared to the URT. [22, 69, 88, 94] This fits with the observation that the majority of disease symptoms are reported to manifest as systemic and LRT disease [21] . However, on occasion, even LRT specimens from MERS cases may initially be negative, only to later become positive by RT-PCR [95] . This may be due to poor sampling when a cough is absent or non-productive or because the viral load is low [95] . Despite this both the largest human MERS-CoV studies [32, [96] [97] [98] and smaller ones [22, 25, 99] , use samples from the URT. It is then noteworthy that one study reported an association between higher loads in the URT and worse clinical outcome including intensive care and death [94] . At writing, no human data exist to define whether the virus replicates solely or preferentially in the LRT or URT, or replicates in other human tissues in vivo although MERS-CoV RNA has been detected from both the URT and LRT in a macaque monkey model [100] .The distribution of DPP4 in the human upper airways is also not well described.
Individual human case studies report long periods of viral shedding, sometimes intermittently and not necessarily linked to the presence of disease symptoms. [25, 69, 99, 101] In one instance, a HCW shed viral RNA for 42 days in the absence of disease [99] . It is an area of high priority to better understand whether such cases are able to infect others. Over three quarters of MERS cases shed viral RNA in their LRT specimens (tracheal aspirates and sputum) for at least 30 days, while only 30 % of contacts were still shedding RNA in their URT specimens [91, 102] .
In the only study to examine the effect of sample type on molecular analysis, 64 nasopharyngeal aspirates (NPA; an URT sample), 30 tracheal aspirates, 13 sputa and three BAL were examined. The tracheal aspirates and BAL returned the highest viral load values followed by NPA and sputum. Unsurprisingly, higher viral loads generally paralleled whole genome sequencing and culture success and, in NPA testing, were significantly correlated with severe disease and death [49, 94, 103] . This study demonstrated the importance of LRT sampling for whole genome sequencing.
When tested, samples positive for MERS-CoV are often negative for other pathogens [2, 25, 93, 104] . However, many studies make no mention of additional testing for endemic human respiratory viruses [21, 23, 73, 105] . When viruses are sought, they have included human herpesvirus (HHV), rhinoviruses (HRV), enteroviruses (EV), respiratory syncytial virus (RSV), parainfluenzavirus types 1, 2 and 3 (PIVs),influenzaviruses (IFVs), endemic HCoVs, adenoviruses (AdVs) metapneumovirus (MPV) and influenza A\H1N1 virus; co-detections with MERS-CoV have been found on occasion [2, 22, 37, 69, 97] . Bacterial testing is sometimes included (for example, for Legionella and Pneumococcus) but the impact of bacterial co-presence is also unclear [22, [104] [105] [106] . Further testing of the LRT sample from the first MERS case used IFA to screen for some viruses (negative for IFV, PIVs, RSV and AdVs) and RT-PCR for others (negative for AdV, EVs, MPV and HHVs) [18] . RT-PCR also detected MERS-CoV. The WHO strongly recommends testing for other respiratory pathogens [53] but with this recommendation often discounted, there are limited data to address the occurrence and impact of co-infections or alternative viral diagnoses among both MERS cases and their contacts. Little is known of other causes of MERS-like pneumonia in the KSA or of the general burden of disease due to the known classical respiratory viruses.
Testing of adult pilgrims performing the Hajj in 2012 to 2014 has not detected any MERS-CoV. In 2012, nasal swabs from 154 pilgrims collected prior to leaving for or departing from the KSA were tested [47] . In 2013, testing was significantly scaled up with 5,235 nasopharyngeal swabs from 3,210 incoming pilgrims and 2,025 swabs from outgoing pilgrims tested [98] . It should be noted that most pilgrims arrived from MERS-free countries. A further 114 swabs were taken from pilgrims with influenza-like illness [96, 107] . In earlier Hajj gatherings, it was found that influenza viruses circulated widely, whilst other viruses, often rhinoviruses, circulated more selectively, interpreted as indicating their importation along with foreign pilgrims. [107] [108] [109] Over time, increased influenza vaccination has been credited for a fall in the prevalence of influenza like illnesses among Hajj pilgrims. [110] A LRT sample is often not collected for these studies [98, 107, 109] , so false negative findings are a possibility although little is known about the initial site of MERS-CoV infection and replication; it may have been assumed it was the LRT because disease was first noticed there but the URT may be the site of the earliest replication.
In Jeddah between March and July 2014 (hereafter called the Jeddah-2014 outbreak; Fig. 3 ), there was a rapid increase in MERS cases, accompanied by intense screening; approximately 5,000 samples from in and around the region were tested in a month yielding around 140 MERS-CoV detections (~3 % prevalence) [111] . Among 5,065 individuals sampled and tested across the KSA between October 2012 and September 2013,108 (2.1 %) detections were made in a hospital-centric population which included hospitalized cases (n = 2,908; 57.4 %), their families (n = 462; 9.1 %) and associated HCWs (n = 1,695; 33.5 %) [32] . Among the detections, 19 (17.8 %) were HCWs and 10 (9.3 %) were family contacts [32] .
The 2-3 % prevalence of active MERS-CoV infections is not dissimilar to the hospital-based prevalence of other human CoVs. [112] However, the proportion of deaths among those infected with MERS-CoV is much higher than that known for the HCoVs NL63, HKU1, 229E or OC43 in other countries, and even above that for SARS-CoV; it is not a virus that could reasonably be described as a "storm in a teacup". It is the low transmission rate that has prevented worldwide spread, despite many "opportunities".
Very early in the MERS outbreak, some animals were highly regarded as either the reservoir or intermediate host(s) of MERS-CoV with three of the first five cases having contact with DCs [73, 113, 114] . Today, animal MERS-CoV infections must be reported to the world organization for animal health as an emerging disease [115] . A summary of the first MERS cases reported by the WHO defined animal contact with humans as being direct and within 10 days prior to symptom onset [20] . This definition made no specific allowance for acquisition from DCs through a droplet-based route, which is very likely route for acquisition of a virus that initially and predominantly causes respiratory disease [23] . Camels are known to produce high levels of MERS-CoV RNA in their URT and lungs [116] . Providing support for a droplet transmission route and perhaps indicating the presence of RNA in smaller, drier droplet nuclei, MERS-CoV RNA was identified in a high volume air sample collected from a barn housing an infected DC [117] . The precise source from which humans acquire MERS-CoV remains poorly studied but it seems likely that animal and human behavioural factors may play roles (Fig. 3) [118] . These factors may prove important for human cases who do not describe any DC contact [119] nor any contact with a confirmed case. Whether the WHO definition of animal contact is sufficient to identify exposure to this respiratory virus remains unclear. Wording focuses on consumption of DC products but does not specifically ascribe risk to a droplet route for acquisition of MERS-CoV from DC [120] . Some MERS patients are listed in WHO disease notices as being in proximity to DCs or farms, but the individuals have not described coming into contact with the animals. No alternative path for acquiring infection is reported in many of these instances. What constitutes a definition of "contact" during these interviews has been defined for one study [72] . Despite this lack of clarity, the WHO consider that evidence linking MERS-CoV transmission between DCs to humans is irrefutable (Fig. 4) [120] .
The possibility that bats were an animal host of MERS-CoV was initially widely discussed because of the existing diversity of coronaviruses known to reside among them [121] [122] [123] [124] . Conclusive evidence supporting bats as a source for human infections by MERS-CoV has yet to be found, but bats do appear to host ancestral representatives [53, 125] . However, these are not variants of the same virus nor always within the same phylogenetic lineage as MERS-CoV; they are each a genetically distinct virus. Bat-to-human infection by MERS-CoV is a purely speculative event. The only piece of MERS-CoV-specific evidence pointing to bats originates from amplification of a 190 nt fragment of the RNAdependent RNA polymerase gene of the MERS-CoV genome, identified in a faecal pellet from an insectivorous Emballonuridae bat, Taphozous perforatus found in Bisha, the KSA [121] . While very short, the sequence of the fragment defined it as a diagnostic discovery. Subsequently a link to DCs was reported [85] and that link has matured into a verified association [38, 126] (Fig. 4) .
(See figure on previous page.) Fig. 3 Monthly detections of MERS-CoV (blue bars) and of cases who died (red bars) with some dates of interest marked for 2012 to 4 th September 2015. An approximation of when DC calving season [128] and when recently born DCs are weaned is indicated. Spring (green) and summer (orange) in the Arabian Peninsula are also shaded. Note the left-hand y-axis scale for 2014 and 2015 which is greater than for 2012/13. Sources of these public data include the WHO, Ministries of Health and FluTrackers [207] [208] [209] . Earlier and subsequent versions of this chart are maintained on a personal blog [210] . Modified and reprinted from Mackay IM, Arden KE. Middle East respiratory syndrome: An emerging coronavirus infection tracked by the crowd. Virus Res 2015 Vol 202:60-88 with permission from Elsevier [5] DCs, which make up 95 % of all camels, have a central presence in the Arabian Peninsula where human-DC contact ranges from little to close [119] . Contact may be commonplace and could occur in variety of ways (Fig. 4a) . There are several large well-attended festivals, races, sales and parades which feature DCs and DCs are also kept and bred close to populated areas in the KSA [127, 128] . DC milk and meat are widely consumed and the older DC is an animal of ritual significance after the Hajj pilgrimage [129] . However, MERS-CoV infection frequency is reportedly much lower than is the widespread and frequent habit of eating, drinking and preparing DC products. Daily ingestion of fresh unpasteurized DC milk is common among the desert Bedouin and many others in the KSA. DC urine is also consumed or used for supposed health benefits. Despite camel butchery being a local occupation, neither butchers nor other at-risk groups are identifiable among MERS cases; this may simply be a reporting issue rather than an unexplainable absence of MERS. A small case-control study published in 2015 identified direct DC contact, and not ingestion of products, to be associated with onset of MERS [38] .
The first sero-survey of livestock living in the Middle East region was conducted during 2012-2013 [85] . DCs were sampled from a mostly Canary Island-born herd and from Omani DCs (originally imported from the Horn of Africa) [85] . A neutralising antibody assay found only 10 % of strongly seropositive Canary Island [5] . b Camel-to-human infections appear to be infrequent, while human-to-human spread of infection is regularly facilitated by poor IPC in healthcare settings where transmission is amplified, accounting for the bulk of cases. There are human MERS cases that do not fall into either category of source and it is unclear if these acquired infection through some entirely separate route, or from cases that escaped diagnosis. c Hypothetical ways in which subclinical (when infection may not meet a previously defined clinical threshold of signs and/or symptoms) or asymptomatic (no obvious signs or measured, noticed or recalled symptoms of illness) MERS-CoV infection may be implicated in transmission DC sera could neutralise MERS-CoV while all Omani DC sera had high levels of specific MERS-CoV neutralizing antibody [85] . This indicated that DCs had in the past been infected by MERS-CoV, or a very similar virus.
Since this study, a host of peer-reviewed reports have looked at both DCs and other animals, and the possibility that they may host MERS-CoV infection. Seropositive DCs have been found throughout the Arabian Peninsula including Oman, the KSA, Qatar, Jordan, the United Arab Emirates (UAE), Kuwait as well as Sudan, Somalia, Egypt, Tunisia, Nigeria, Kenya and Ethiopia in Africa and the Canary Islands [85, [130] [131] [132] [133] [134] . Other animals tested include sheep, cows, pigs, horses, donkeys, mules, birds, water buffalo, goats, Bactrian camels, llamas and guanaco (south American camelids) but none had detectable neutralising antibody against MERS-CoV [4, 74, 78, 85, 86, 135, 136] . No virology or serology studies of human samples from areas in Africa where there are camels with a history of MERS-CoV have been reported to date. However,an absence of unexplained pneumonia that may be attributable to MERS-CoV infection may not signal the absence of virus among humans in each country but simply reflect a lack of expensive epidemiology studies conducted by resource-poor countries. It is thus unclear whether MERS-CoV, or an antigenically related CoV, is an unrecognized pathogen in these regions, perhaps circulating for even longer than it has been known in the Arabian Peninsula [133] .
MERS-CoV RNA has also been detected in DC samples, and recovery of infectious virus has also been achieved from DC samples [4, 77, 117, 132, [137] [138] [139] [140] [141] . From some of these, full or majority length genomes of MERS-CoV have been sequenced [77, 137, 138] . DC versions of MERS-CoV were found to be as similar to each other, as were variants detected from different humans over time and across distance.
Antibody screening assays have also detected crossreactive antibodies in sera. These were identified as such by screening sera against similar viruses, for example BCoV or HCoV-OC43 (as an antigenic facsimile for BCoV). It is possible that other MERS-CoV-like viruses also reside within DCs, but this does not detract from the definitive finding of MERS-CoV genetic sequences in both DCs and humans [117, 142, 143] .
Screening studies have shown that juvenile DCs are more often positive for virus or viral RNA while older DCs are more likely to be seropositive and RNA or virus negative [76, 77, 144] . In adult DCs, MERS-CoV RNA has been detected among animals with pre-existing antibody, suggesting re-infection is possible [77, 144] . Viral loads among positive DCs can be very high [4, 76, 77, 139, 144] and DCs have been found positive both when ill with URT respiratory signs [77, 117, 142, 145] or when apparently healthy [137] . These findings indicate DCs host natural MERS-CoV infections. Furthermore, stored DC sera have revealed signs of MERS-CoV in DCs which date back over three decades (the earliest collected in 1983) [4, 133, 135] . Older sera have not been tested and so precisely how long DCs have been afflicted by MERS-CoV, whether the virus is enzootic among them, introduced to them decades or centuries ago from bats in Africa or the Arabian Peninsula, or they are the subject of regular but short-lived viral incursions from an as yet unknown host, cannot be answered.
Researchers sought to determine a direction for infection; were DCs transmitting virus to humans or were humans infecting DCs? At a Qatari site, a farm owner and his employee became ill in mid-October 2013 and tested positive for MERS-CoV RNA in a sputum and throat swab sample, respectively. RT-rtPCRs found MERS-CoV RNA in 11 of 14 positive DC nasal swabs at the farm; six (43 %) positive by two or more assays [138] . The results indicated a recent outbreak had occurred in this herd; the first indication of MERS-CoV RNA found within DCs with a temporal association to human infections. Three positive DC samples were confirmed by sequencing a 358 nt portion of the spike gene; these sequences were identical to each other, again with close homology to other human and DC MERS-CoV sequences [138] . The DCs and human contacts yielded ORF1a and ORF4b sequences differing by only a single nucleotide each, clustering closely with the Hafr-Al-Batin_1_2013 variant [138] . Subsequent case studies found evidence of a concurrent human and DC infection and the direction of that infection was inferred to be from the ill DCs and to their human owners [117, 142, 146] . Partial genome sequences indicated that a human and a MERS-CoV RT-rtPCR positive DC had been infected by a variant of the same virus, harbouring the same distinct pattern of nucleotide polymorphisms. [142] All nine DC in the owner's herd, serially sampled, reacted in a recombinant S1 antigen ELISA, with the two animals that had been RT-rtPCR positive showing a small, verifiable rise in antibody titre [142] . A rise in titre theoretically begins 10 to 21 days after DC infection [142] . The authors suggested that the rise in titre in DC sera which occurred alongside a declining RNA load, while the patient was actively ill and hospitalized, indicated that the DCs were infected first followed by the owner [117, 142] . BCoV antibodies were also present, and rising in one of the two RT-rtPCR positive animals but no animal's antibodies could neutralise BCoV infection [142] .
Camel calving season occurs in the winter months (between late October and late February; Fig. 3 ) and this may be a time when there is increased risk to humans of spill-over due to new infections among naïve DC populations [128] . What role maternal camel antibody might play in delaying infection of calves remains unknown [128, 142] . Juvenile DCs appear to host active infection more often than adult DCs and thus the sacrificial slaughter of DCs, which must be five years of age or older (termed a thane), may not be accompanied by significant risk of exposure to infection. In contrast to earlier results, slaughterhouse workers who kill both younger and older DCs, may be an occupational group with significantly higher incidence of seropositivity to MERS-CoV when animals have active MERS-CoV infections [129, 139, [147] [148] [149] . Expanded virological investigations of African DCs may lead to more seropositive animals and geographic areas in which humans may be at risk. It is possible that there are areas where humans already harbour MERS-CoV infections that have not been identified because of an absence of laboratory surveillance. Virological investigations of bats may lead to findings of ancestral viruses and viral 'missing links' and identifying any other animal sources of zoonotic spread is important to inform options for reducing human exposures [56, 76] .
Infectious MERS-CoV added to DC, goat or cow milk and stored at 4°C could be recovered at least 72 h later and, if stored at 22°C, recovery was possible for up to 48 h [150] . MERS-CoV titre decreased somewhat when recovered from milk at 22°C but pasteurization completely ablated MERS-CoV infectivity [150] . In a subsequent study, MERS-CoV RNA was identified in the milk, nasal secretion and faeces of DCs from Qatar [151] .
A single study has examined the ability of MERS-CoV to survive in the environment [150] . Plastic or steel surfaces were inoculated with 10 6 TCID 50 of MERS-CoV at different temperature and relative humidity (RH) and virus recovery was attempted in cell culture. At high ambient temperature (30°C) and low RH (30 %) MERS-CoV remained viable for 24 h [150] . By comparison, a well known and efficently transmitted respiratory virus, influenza A virus, could not be recovered in culture beyond four hours under any conditions [150] . Aerosol experiments found MERS-CoV viability only decreased 7 % at low RH at 20°C. In comparison, influenza A virus decreased by 95 % [150] . MERS-CoV survival is inferior to that previously demonstrated for SARS-CoV [152] . For context, pathogenic bacteria can remain viable and airborne for 45 min in a coughed aerosol and can spread 4 m. MERS-CoV's ability to remain viable over long time periods gives it the capacity to thoroughly contaminate a room's surfaces when occupied by an infected and symptomatic patient [153] . Whether MERS-CoV can remain adrift and infectious for extended periods (truly airborne) remains unknown. Such findings expand our understanding of the possibilities for droplets to transmit respiratory viruses in many settings, including hospital waiting rooms, emergency departments, treatment rooms, open intensive care facilities and private patient rooms. The nature and quality of air exchange, circulation and filtration are important variables in risk measurement and reduction as is the use of negative pressure rooms to contain known cases. Droplet spread between humans is considered the mechanism of human-to-human transmission and the need for droplet precautions was emphasized after the Al-Ahsa hospital, the KSA and the South Korean outbreaks [21, 23, 154, 155] . By extrapolation, aerosol-generating events involving DCs (urination, defecation, and preparation and consumption of DC products) should be factored into risk measurement and reduction efforts and messaged using appropriate context. The provision of evidence supporting the best formulation of personal protective equipment to be worn by HCWs who receive, manage or conduct procedures on infectious cases remains a priority.
MERS-CoV was found and characterized because of its apparent association with severe, and therefore more obvious, illness in humans; we were the canaries in the coal mine. Sero-assays and prospective cohort studies have yet to determine the extent to which milder or asymptomatic cases contribute to MERS-CoV transmission chains. However, transmission of MERS-CoV is defined as sporadic (not sustained), intra-familial, often healthcare associated, inefficient and requiring close and prolonged contact [22, 31, 63, 93, 97, 102, 156] In a household study, 14 of 280 (5 %) contacts of 26 MERS-CoV positive index patients were RNA or antibody positive; the rate of general transmission, even in outbreaks is around 3 % [31] . It seems that the majority of human cases of MERS-CoV, even when numbers appear to increase suddenly, do not readily transmit to more than one other human so to date, the localized epidemic of MERS-CoV has not been self-sustaining [157] [158] [159] [160] [161] . That is to say, the basic reproduction number (R 0 ) -the average number of infections caused by one infected individual in a fully susceptible populationhas been close to one throughout various clusters and outbreaks. If R 0 was greater than 1, a sustained increase in case numbers would be expected. Some R o calculations may be affected by incomplete case contact tracing, limited community testing and how a case is defined. That MERS has had a constant presence in the Arabian Peninsula since 2012 is due to ongoing, sporadic spill-over events from DCs amplified by poorly controlled hospital outbreaks.
The first known MERS human-to-human transmission event was one characterized by acute LRT disease in a healthcare setting in Jordan. In stark contrast, a sero-survey of HCW who were sometimes in close and prolonged contact with the first, fatal MERS-CoV case in 2012 [162] , found none of the HCW had seroconverted four months later, despite an absence of eye protection and variable compliance with required PPE standards [162] .
Early on in the MERS story, samples for testing were mostly collected from patients with severe illness and not those with milder acute respiratory tract infections. Contacts of confirmed MERS cases were often observed for clinical illness, but not tested. These omissions may have confounded our understanding of MERS-CoV transmission and biased early data towards higher numbers of seriously ill and hospitalized patients, inflating the apparent proportion of fatal cases. Case-control studies were not a focus. As testing paradigms changed and contacts were increasingly tested, more asymptomatic and mild infections were recognized [163] .
A rise in the cases termed asymptomatic (which enlarge the denominator for calculations of the proportion of fatal cases, defined in [164] ) resulted in a drop in the proportion of fatal cases during the Jeddah-2014 outbreak. Historically, such rises are consistent with changing definitions and laboratory responses and clinical management of a newly discovered virus infection that was first noted only among the severely ill. Upon follow-up, over three-quarters of such MERS-CoV RNA positive people did recall having one or more symptoms at the time, despite being reported as asymptomatic [165] raising some question over the reliability of other reported data.
The proportion of fatal MERS cases within the KSA compared to outside the KSA, as well as the age, and sex distribution change in different ways when comparing MERS outbreaks. Approximately 43 % of MERS cases (549 of 1277) in the KSA were fatal betwen 2012 and December 2015 while 21 % (72 of 330) died among those occurring outside of the KSA. The total number of male cases always outnumber females and the proportion of male deaths is always greater than the proportion of females who die. However the proportion of male deaths from total males with MERS is a similar figure to that for females. In the KSA, there is a greater proportion of younger males among cases and deaths than were observed from the 2015 South Korean or the Jeddah-2014 outbreaks (Additional file 2: Figure S2 ). Why these aspects have differed may be due to differences in the time to presentation and diagnosis, the nature and quality of supportive care, the way a person became infected (habits, exposure to a human or zoonotic source, viral load, route of infection) or the extent to which different populations are burdened by underlying diseases [40] .
As a group, HCWs comprised 16 % of MERS cases in the KSA and South Korea. It is apparent that the weekly proportion of infected HCWs increases alongside each steep rise in overall detections (Fig. 5) . In May 2013, the WHO published guidelines for IPC during care of probable or confirmed cases of MERS-CoV infection in a healthcare setting [166] . This is explainable because to date, each case rise has been intimately associated with healthcare-facility related outbreaks [118] . These rises in MERS-CoV detections can decrease the average age during each event because HCWs are usually younger than inpatients with MERS. Healthcare facilities have been a regular target for suggested improvements aimed at improving infection prevention and control (IPC) procedures [115, 118] .
Most of the analysis of MERS-CoV genetics has been performed using high throughput or "deep" sequencing methods for complete genome deduction [167] [168] [169] . MERS-CoV was the first subject of such widespread use of deep sequencing to study an emerging viral outbreak with global reach. The technique can produce genomic [207] [208] [209] . Earlier and subsequent versions of this chart are maintained on a personal blog [210] length coverage in a single experiment with highly repetitious measurement of each nucleotide position [52, 140] . Despite assays having been published early on, subgenomic sequencing, once the mainstay of viral outbreak studies, has less often been published during MERS-CoV characterization [48] . As more genomes from both humans and DCs have been characterized, two clades have become apparent; A and B (Fig. 6) . Clade A contains only human-derived MERS-CoV genomes from Jordan, while Clade B comprises the majority of human and camel genomes deduced thus far [168] .
Two studies during 2015, one looking at Jeddah-2014 MERS-CoV variants and another looking at a variant exported from South Korea to China, have now identified signs of genetic recombination among MERS-CoV variants. While human and camel whole genome sequences have retained >99 % identity with each other, members of genetically distinct lineages can and do swap genetic material when suitable conditions and coinfections co-occur [170] [171] [172] . Shared identity implies that the major source for human acquisition is the DC, rather than another animal, although more testing of other animal species is needed to confirm that conclusion. Over a month, a DC virus sequenced on different occasions did not change at all indicating a degree of genomic stability in its host, supporting that DCs are the natural, rather than intermediate, host for the MERS-CoV we know today [77] . To date, recombination has been localised to breakpoints near the boundary between ORF1a and ORF1b regions, within the spike gene [170] and in the ORF1b region (Fig. 2) [172] . It is not unexpected that recombination should occur since it is well known among other CoVs [124] and because the majority of MERS-CoV whole genomes collected from samples spanning three years (2012-2015) and from humans, camels and different countries have shown close genetic identity to each other, with just enough subtle variation to support outbreak investigations so long as whole genome sequencing is applied [52, 77, 135, 138, 168, [173] [174] [175] .
Changes in genome sequence may herald alterations to virus transmissibility, replication, persistence, lethality or response to future drugs. If we have prior knowledge of the impact of genetic changes because of thorough characterization studies, we can closely Fig. 6 The genetic relationship between MERS-CoV nucleotide sequences (downloaded from GenBank using the listed accession numbers and from virological.org [212] ). This neighbour joining tree was created in MEGA v6 using an alignment of human and DCderived MERS-CoV sequences (Geneious v8.1 [211] ). Clades are indicated next to dark (Clade A) or pale (Clade B) blue vertical bars. Camel icons denote genomes from DCs. Healthcare or community outbreaks are boxed and labelled using previously described schemes [212, 213] monitor the genomic regions and better understand any changes in transmission or disease patterns as they occur. Genetic mutations noted during the largest of human outbreaks, Jeddah-2014, did not impart any major replicative or immunomodulatory changes when compared to earlier viral variants in vitro [156, 176] . However, we understand very little of the phenotypic outcomes that result from subtle genetic change in MERS-CoV genomes. To date no clinical relevance or obvious in vivo changes to viral replication, shedding or transmission has been reported or attributed to mutations or to new recombinant viruses [156] . But vigilance and larger, more contemporary and in vivo studies are needed.
Genome sequence located to a distinct clade were identified from an Egyptian DC that was probably imported from Sudan. This does not fit into either of the current clades [125, 168, 177] . A virus sequenced from a Neoromicia capensis bat was more closely related to MERS-CoV than other large bat-derived sequences had been to that point, but the genome of a variant of a MERS-CoV has yet to be discovered and deduced from any bat [125] .
Analyses of MERS-CoV genomes have shown that most single nucleotide differences among variants were located in the last third of the genome (Fig. 2) , which encodes the spike protein and accessory proteins [168] . At least nine MERS-CoV genomes contained amino acid substitutions in the receptor binding domain (RBD) of the spike protein and codons 158 (N-terminal region), 460 (RBD), 1020 (in heptad repeat 1), 1202 and 1208 bear investigation as markers of adaptive change [140, 169] . The spike protein had not changed in the recombinant MERS-CoV genome identified in China in 2015 but was reported to have varied at a higher rate than that for complete MERS-CoV genomes, among South Korean variants [172, 178] . This highlights that subgenomic regions may not always contain enough genetic diversity to prove useful for differentiating viral variants. Despite this, one assay amplifying a 615 nucleotide fragment of the spike S2 domain gene for Sanger sequencing agreed with the results generated by the sequencing of a some full genomes and was useful to define additional sequence groupings [177] .
Genomic sequence can also be used to define the geographic boundaries of a cluster or outbreak and monitor its progress, based on the similarity of the variants found among infected humans and animals when occurring together, or between different sites and times (Fig. 6 ) [169] . This approach was employed when defining the geographically constrained MERS hospital outbreak in Al-Ahsa, which occurred between 1 st April and 23 rd May 2013, as well as clusters in Buraidah and a community outbreak in Hafr Al-Batin, the KSA. Genomic sequencing identified that approximately 12 MERS-CoV detections from a community outbreak in Hafr Al-Batin between June and August 2013 may have been triggered by an index case becoming infected through DC contact [175] . Sequencing MERS-CoV genomes from the 2013 Al-Ahsa hospital outbreak indicated that multiple viral variants contributed to the cases but that most were similar enough to each other to be consistent with human-tohuman transmission. Molecular epidemiology has revealed otherwise hidden links in transmission chains encompassing a period of up to five months [179] . However, most outbreaks have not continued for longer than two to three months and so opportunities for the virus to adapt further to humans through co-infection and sustained serial passage have been rare [169] . In Riyadh-2014, genetic evidence supported the likelihood of multiple external introductions of virus, implicating a range of healthcare facilities in an event that otherwise looked contiguous [23, 168, 179] . Riyadh is a nexus for camel and human travel and has had more MERS cases than any other region of the KSA to date but also harbours a wide range of MERS-CoV variants [128, 167, 179] . However the South Korean outbreak originated from a single infected person, resulting in three to four generations of cases [180, 181] . Studies of this apparently recombinant viral variant did not find an increased evolutionary rate and no sign of virus adaptation thus the outbreak seems to have been driven by circumstance rather than circumstance together with mutation [181] .
For many MERS cases detected outside the Arabian Peninsula, extensive contact tracing has been performed and the results described in detail. Contact tracing is essential to contain the emergence and transmission of a new virus and today it is supported by molecular epidemiology. Although it is an expensive and time consuming process, contact tracing can identify potential new infections and through active or passive monitoring, react more rapidly if disease does develop. Results of contact tracing to date have found that onward transmission among humans is an infrequent event. For example, there were 83 contacts, both symptomatic and asymptomatic, of a case treated in Germany who travelled from the UAE but no sign of virus or antibody were found in any of them [73] . The very first MERS case had made contact with 56 HCWs and 48 others, but none developed any indication of infection [162] . In a study of 123 contacts of a case treated in France, only seven matched the definition for a possible case and were tested; one who had shared a 20 m 2 hospital room while in a bed 1.5 m away from the index case for a prolonged period was positive [26] . None of the contacts of the first two MERS cases imported into the USA in 2014 contained any MERS-CoV footprint [182] and none of the 131 contacts of two travellers returning to the Netherlands developed MERS-CoV antibodies or tested RNA positive [25, 183] . Analyses of public data reveal many likely instances of nosocomial acquisition of infection in the Arabian Peninsula and these data may be accompanied by some details noting contact with a known case or facility. One example identified the likely role of a patient with a subclinical infection, present in a hospital during their admission for other reasons, as the likeliest index case triggering a family cluster [93] . Contact tracing was a significant factor in the termination of a 2015 outbreak involving multiple South Korean hospitals [184] . Such studies demonstrate the necessity of finding and understanding a role for mild and asymptomatic cases, together with restricting close contact or prolonged exposure of infected people to others, especially older family members and friends with underlying disease (Fig. 4c) .
The hospital-associated outbreak in Jeddah in 2014 was the largest and most rapid accumulation of MERS-CoV detections to date. The greatest number of MERS-CoV detections of any month on record occurred in Jeddah in April. The outbreak was mostly (>60 % of cases) associated with human-to-human spread within hospital environments and resulted from a lack of, or breakdown in, infection prevention and control [37, 185, 186] . A rise in fatalities followed the rapid increase in case numbers.
In 2015 two large outbreaks occurred. South Korea was the site of the first large scale outbreak outside the Arabian Peninsula and produced the first cases in both South Korea and China, occurring between May and July 2015. This was closely followed by a distinct outbreak in Ar Riyad province in the KSA which appeared to come under control in early November.
After staying in Bahrain for two weeks, a 68 year old male (68 M) travelled home to South Korea via Qatar, arriving free of symptoms on the 4 th May 2015 [187] . He developed fever, myalgia and a cough nearly a week later (11 th ). He visited a clinic as an outpatient between the 12 th and 15 th of May and was admitted to Hospital A on the 15 th [188] . He was discharged from Hospital A on the 17 th then visited and was admitted to the emergency department of Hospital B on the 18 th . During this second stay, a sputum sample was taken and tested positive for MERS-CoV on the 20 th [187, 188] , triggering transfer to the designated isolation treatment facility. Over a period of 10 days, the index case was seen at three different hospitals, demonstrating a key feature of "hospital shopping" that shaped the South Korean outbreak. Approximately 34 people were infected during this time [187] . In total 186 cases were generated in this outbreak, all linked through a single transmission chain to 68 M; 37 cases died [189] . In South Korea, the national health insurance system provides for relatively low cost medical care, defraying some costs by making family members responsible for a portion of the ministration of the sick, resulting in them sometimes staying for long periods in the rooms that often have more than four beds in them [24] . Other factors thought to have enabled this outbreak included unfamiliarity of local clinicians with MERS, ease with which the public can visit and be treated by tertiary hospitals, the custom of visiting sick friends and relatives in hospitals, the hierarchical nature of Korean society, crowded emergency rooms, poor IPC measures, a lack of negative pressure isolation rooms and poor inter-hospital communication of patient disease histories [24, [190] [191] [192] . All of the reported transmission occurred across three or four generations and apart from one unknown source, were all hospital-acquired [24, 120, 181, [193] [194] [195] . Few clinical details about these cases have been reported to date and detail on transmission and contact tracing is minimal. The hospitals involved were initially not identified, governmental guidance and actions produced confusing messages and there was very limited communication at all early on which resulted in unnecessary concern, distrust and a distinct economic impact [191, [196] [197] [198] . Early in the outbreak, a infected traveller, the son of an identified case in South Korea, passed through Hong Kong on his way to China where he was located, isolated and cared for in China [91, 199, 200] . No contacts became ill. The outbreak was brought under control in late July/ early August [201] after improved IPC measures were employed, strong contact tracing monitoring and quarantine, expanded laboratory testing, hospitals were better secured, specialized personnel were dispatched to manage cases and international cooperation increased [202, 203] . A review of public data showed that, as for MERS in the KSA, older age and the presence of underlying disease were significantly associated with a fatal outcome in South Korea. [40] Even though R 0 is <1, super-spreading events facilitated by circumstances created in healthcare settings and characterized by cluster sizes over 150, such as this one, are not unexpected from MERS-CoV infection [204] . The dynamic of an outbreak depends on the R 0 and an individual's viral shedding patterns, contact type and frequency, hospital procedures and population structure and density [204] .
In the region of Ar Riyad, including the capital city of Riyadh, a hospital based cluster began, within a single hospital, from late June 2015 [205] . By mid-September there had been approximately170 cases reported but the outbreak appeared to been brought under control in November.
It became apparent early on that MERS-CoV spread relatively ineffectively from human-to-human. Despite ongoing and possibly seasonal introduction of virus to the human population via infected DCs and perhaps other animals yet to be identified, the vast majority of MERS-CoV transmission has occurred from infected to uninfected humans in close and prolonged contact through circumstances created by poor infection control in health care settings. This opportunistic virus has had its greatest impact on those with underlying diseases and such vulnerable people, sometimes suffering multiple comorbidities, have been most often associated with hospitals, creating a perfect storm of exposure, transmission and mortality. It remains unclear if this group are uniquely affected by MERS-CoV or if other respiratory virus infections, including those from HCoVs, produce a similarly serious impact. In South Korea, a single imported case created an outbreak of 185 cases and 36 deaths that had a disproportionate impact on economic performance, community behaviour and trust in government and the health care system. Household human-to human transmission occurs but is also limited. Educational programs will be essential tools for combatting the spread of MERS-CoV both within urban and regional communities and for the health care setting.
Vigilance remains important for containment since MERS-CoV is a virus with a genetic makeup that has been observed for only three years and is not stable. Among all humans reported to be infected, nearly 40 % have died. Continued laboratory testing, sequencing, analysis, timely data sharing and clear communication are essential for such vigilance to be effective. Global alignment of case definitions would further aid accurate calculation of a case fatality ratio by including subclinical case numbers. Whole genome sequencing has been used extensively to study MERS-CoV travel and variation and although it remains a tool for experts, it appears to be the best tool for the job.
MERS and SARS have some clinical similarities but they also diverge significantly [206] . Defining characteristics include the higher PFC among MERS cases (above 50 % in 2013 and currently at 30-40 %; well above the 9 % of SARS) and the higher association between fatal MERS and older males with underlying comorbidities. For the viruses, MERS-CoV has a broader tropism, grows more rapidly in vitro, more rapidly induces cytopathogenic change, triggers distinct transcriptional responses, makes use of a different receptor, induces a more proinflammatory state and has a delayed innate antiviral response compared to SARS-CoV.
There appears to be a 2-3 % prevalence of MERS-CoV in the KSA with a 5 % chance of secondary transmission within the household. There is an increased risk of infection through certain occupations at certain times and a much greater chance for spread to other humans during circumstances created by humans, which drives more effective transmission than any R 0 would predict on face value. Nonetheless, despite multiple mass gatherings that have afforded the virus many millions of opportunities to spread, there have remarkably been no reported outbreaks of MERS or MERS-CoV during or immediately after these events. There is no evidence that MERS-CoV is a virus of pandemic concern. Nonetheless, hospital settings continue to describe MERS cases and outbreaks in the Arabian Peninsula. As long as we facilitate the spread of MERS-CoV among our most vulnerable populations, the world must remain on alert for cases which may be exported more frequently when a host country with infected camel reservoirs is experiencing human clusters or outbreaks.
The MERS-CoV appears to be an enzootic virus infecting the DC URT with evidence of recent genetic recombination. It may once have had its origins among bats, but evidence is lacking and the relevance of that to today's ongoing epidemic is academic. Thanks to quick action, the sensitive and rapid molecular diagnostic tools required to achieve rapid and sensitive detection goal have been in place and made widely available since the virus was reported in 2012. RT-PCR testing of LRT samples remains the gold standard for MERS-CoV confirmation. Serological tools continue to emerge but they are in need of further validation using samples from mild and asymptomatic infections and a densely sampled cohort study to follow contacts of new cases may address this need. Similarly, the important question of whether those who do shed MERS-CoV RNA for extended periods are infectious while appearing well, continues to go unanswered. It is even unclear just how many 'asymptomatic' infections have been described and reported correctly which in turn raises questions about the reliability of other clinical data collection to date. While the basic virology of MERS-CoV has advanced over the course of the past three years, understanding what is happening in, and the interplay between, camel, environment and human is still in its infancy.
Additional file 1: Figure S1 . The | What samples returned the highest MERS viral load values? | false | 4,265 | {
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650 | Role of S-Palmitoylation on IFITM5 for the Interaction with FKBP11 in Osteoblast Cells
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3776769/
Tsukamoto, Takashi; Li, Xianglan; Morita, Hiromi; Minowa, Takashi; Aizawa, Tomoyasu; Hanagata, Nobutaka; Demura, Makoto
2013-09-18
DOI:10.1371/journal.pone.0075831
License:cc-by
Abstract: Recently, one of the interferon-induced transmembrane (IFITM) family proteins, IFITM3, has become an important target for the activity against influenza A (H1N1) virus infection. In this protein, a post-translational modification by fatty acids covalently attached to cysteine, termed S-palmitoylation, plays a crucial role for the antiviral activity. IFITM3 possesses three cysteine residues for the S-palmitoylation in the first transmembrane (TM1) domain and in the cytoplasmic (CP) loop. Because these cysteines are well conserved in the mammalian IFITM family proteins, the S-palmitoylation on these cysteines is significant for their functions. IFITM5 is another IFITM family protein and interacts with the FK506-binding protein 11 (FKBP11) to form a higher-order complex in osteoblast cells, which induces the expression of immunologically relevant genes. In this study, we investigated the role played by S-palmitoylation of IFITM5 in its interaction with FKBP11 in the cells, because this interaction is a key process for the gene expression. Our investigations using an established reporter, 17-octadecynoic acid (17-ODYA), and an inhibitor for the S-palmitoylation, 2-bromopalmitic acid (2BP), revealed that IFITM5 was S-palmitoylated in addition to IFITM3. Specifically, we found that cysteine residues in the TM1 domain and in the CP loop were S-palmitoylated in IFITM5. Then, we revealed by immunoprecipitation and western blot analyses that the interaction of IFITM5 with FKBP11 was inhibited in the presence of 2BP. The mutant lacking the S-palmitoylation site in the TM1 domain lost the interaction with FKBP11. These results indicate that the S-palmitoylation on IFITM5 promotes the interaction with FKBP11. Finally, we investigated bone nodule formation in osteoblast cells in the presence of 2BP, because IFITM5 was originally identified as a bone formation factor. The experiment resulted in a morphological aberration of the bone nodule. This also indicated that the S-palmitoylation contributes to bone formation.
Text: The interferon-induced transmembrane (IFITM) protein family (also known as the Fragilis family in mice) is a part of the dispanin family [1] and is composed of double-transmembrane α-helices connected by a cytoplasmic (CP) loop and extracellular (EC) amino-and carboxyl-terminal polypeptide sequences (Figure 1-A) . The IFITM proteins are evolutionarily conserved in vertebrates [2] . Recent genomic research has revealed that there are 5 IFITM members in humans (IFITM1, 2, 3, 5 and 10) and 7 members in mice (IFITM1, 2, 3, 5, 6, 7, and 10). These proteins play roles in diverse biological processes, such as germ cell maturation during gastrulation (IFITM1-3) [3] [4] [5] , cell-to-cell adhesion (IFITM1) [6] [7] [8] , antiviral activity (IFITM1-3) [9] [10] [11] [12] [13] [14] [15] [16] [17] , and bone formation (IFITM5) [18] [19] [20] [21] [22] , although the detailed functions of IFITM6, 7, and 10 are unknown at present. In particular, IFITM3 has been a target of intensive studies on its activity against influenza A (H1N1) virus infection and internalization [9] [10] [11] [12] [13] [14] .
In 2010, Dr. Yount and co-workers reported that the antiviral activity of IFITM3 is dependent on S-palmitoylation on the protein [10] . The S-palmitoylation [23] is a post-translational modification on proteins by C 16 saturated-fatty acids (palmitic acids) covalently attached to certain cysteine residues via a thioester linkage (Figure 1-B) . The modification is reversibly catalyzed by protein acyltransferases and acylprotein thioesterases, and confers unique properties to the protein, such as membrane binding and targeting, immunoreactivity,
Amino-acid sequence alignment of IFITM5, IFITM1, IFITM2, and IFITM3 derived from mice. The conserved residues are highlighted in black. The three conserved cysteines are highlighted in red and numbered based on the sequence of IFITM5 (top) and IFITM3 (bottom). The residues unique in IFITM5 are highlighted in gray. The first and the second transmembrane domains, the extracellular sequences, and the cytoplasmic loop are indicated by arrows and denoted as TM1 and TM2, EC, and the CP loop, respectively. The TM domains were predicted by SOSUI. The aspartates at the C-terminal region in IFITM5 are shown in blue. B) The schematic illustration of the protein S-palmitoylation. The C 16 -palmitic acid is attached to cysteine via a thioester linkage. The palmitoylation and depalmitoylation are catalyzed by protein acyltransferases and acylprotein thioesterases, respectively. In this study, hydroxylamine, NH 2 OH, was used to reduce the thioester linkage. C) The amino acid sequence identity (similarity) among IFITM5, IFITM1, IFITM2, and IFITM3 is summarized. doi: 10.1371/journal.pone.0075831.g001 and protein-protein interaction. The authors revealed that IFITM3 is S-palmitoylated on three membrane proximal cysteines, Cys71 and Cys72 in the first transmembrane (TM1) domain, and Cys105 in the CP loop (Figure 1-A) [10] . In addition, IFITM3 lacking the S-palmitoylation is not clustered in the cell membrane and significantly diminishes the antiviral activity. Moreover, the cysteines in IFITM2, Cys70, Cys71, and Cys104 are also palmitoylated in the same manner, which affects the intracellular localization [24] . A resent study has revealed that murine IFITM1 has four cysteine residues (Cys49, Cys50, Cys83, and Cys103) for the S-palmitoylation, which is required for the antiviral activity and the protein stability [25] . The other IFITM family members also possess these cysteines (Figure 1-A) , and thus the role of the Spalmitoylation on the cysteines should be significant for the functions of IFITM proteins.
Here, we focused on IFITM5, which is also known as bonerestricted IFITM-like (BRIL) protein [18] . Among the IFITM family proteins, IFITM5 is unique. (i) Expression of IFITM5: Unlike the other IFITM family proteins, the expression of IFITM5 is not induced by interferons because the region upstream of the ifitm5 gene lacks the interferon regulatory elements [26] . Furthermore, the expression of IFITM5 is mostly restricted to osteoblast cells [18, 19, 27] , while the other IFITM proteins are expressed ubiquitously (ii). Amino-acid sequence similarity: The amino acid sequence of IFITM5 is relatively dissimilar to IFITM1-3 proteins (~ 65% similarity), while IFITM1-3 proteins share ~ 85% similarity with each other (Figure 1 -C). In addition, IFITM5 has an aspartate-rich domain in the C-terminal region, which could be involved in calcium binding (Figure 1 -A) [26] . (iii) Role of IFITM5 in bone formation: The expression of IFITM5 is associated with mineralization during the bone formation process in osteoblast cells [18] [19] [20] [21] . Previous studies have confirmed the expression of IFITM5 in bone tissues in mice, rats, humans and tammar wallabies [2] . The ifitm5-gene knockout mice have smaller bones [19] . Moreover, the knockdown of the ifitm5 gene by small hairpin RNA induces a decrease in bone nodule formation, whereas overexpression of the gene in UMR106 cells has been shown to increase calcium uptake and bone nodule formation [18] . (iv) Role of IFITM5 for immune activity: Recent studies have revealed that IFITM5 interacts with the FK506-binding protein 11 (FKBP11) to form IFITM5-FKBP11-CD81-the prostaglandin F2 receptor negative regulator (FPRP) complex [28] . When the complex is formed, the expressions of 5 interferon-induced genes are induced, including bone marrow stromal cell antigen 2 (Bst2), interferon inducible protein 1 (Irgm), interferoninduced protein with tetratricopeptide repeats 3 (Ifit3), b(2)microglobulin (B2m), and MHC class I antigen gene. Consequently, these results indicate that IFITM5 is involved not only in the bone formation but also in the immune system activity.
In this study, we investigated the S-palmitoylation of IFITM5 and its role in the interaction with FKBP11 in mouse osteoblast cells. Cells transfected by a plasmid DNA encoding mouse IFITM5 were grown in the presence of an established chemical reporter, 17-octadecynoic acid (17-ODYA) [29, 30] , or an inhibitor for the S-palmitoylation, 2-bromopalmitic acid (2BP) [31] . The biochemical assays using these compounds revealed that the wild-type IFITM5 is S-palmitoylated. To identify the Spalmitoylation site in IFITM5, we prepared cysteine-substituted mutants, IFITM5-C86A, -C52A/C53A, and -C52A/53A/86A (Cys-less). The chemical reporter assay suggested that at least two out of three cysteines in IFITM5 are S-palmitoylated. The interaction of IFITM5 with FKBP11 was examined by immunoprecipitation assay, resulting in the loss of the interaction in the presence of 2BP. The same result was obtained in the two mutants, C52A/C53A and Cys-less. These results suggested that the S-palmitoylation on Cys52 and/or Cys53 in the TM1 domain of IFITM5 is necessary for the interaction with FKBP11. On the other hand, Cys86 in the CP loop of IFITM5 was S-palmitoylated but not involved in the interaction. Because this interaction is important for the immunologically relevant gene expression, it was indicated that the role of the S-palmitoylation is to promote the interaction of IFITM5 with FKBP11 and to regulate the immune activity in the osteoblast cells. The possible interaction mechanism and the effect of the S-palmitoylation on the bone nodule formation will be discussed.
For mammalian cell expression, plasmid vectors of wild-type IFITM5 (IFITM5-WT) and FLAG-fused FKBP11 (FKBP11-FLAG) were constructed by inserting the cloned genes into a pBApo-CMV Neo expression vector (Takara Bio, Shiga, Japan). The details of the recombinant DNA constructs were the same as described previously [19] . The genes of IFITM5 mutants (IFITM5-C86A, -C52A/53A, and -C52A/C53A/C86A (Cys-less)) were prepared using a QuikChange site-directed mutagenesis kit (Stratagene, La Jolla, CA). The plasmid vectors of FLAG-fused IFITM5-WT, -C52A/53A, and Cys-less were constructed by inserting the cloned genes into the pBApo-CMV Neo expression vector. For E. coli cell expression, the plasmid vector of IFITM5-WT was constructed by inserting the cloned gene into a pET22b (Novagen, Madison, WI) expression vector. The forward primer 5'-GGAATTCCATATGGACACTTCATATCCCCGTG-3' and the reverse primer 5'-CCGCTCGAGGTTATAGTCCTCCTCATCAAACTTGG-3' were used to amplify the gene encoding the entire IFITM5 from the plasmid vector for mammalian cell expression described above. The underlined letters denote an NdeI and an XhoI cleavage site, respectively. The plasmids of IFITM5 mutants were prepared using a QuikChange site-directed mutagenesis kit. The sense and anti-sense primers used were 5'-GGCAGTATGGCTCCAAAGCCAAGGCGTACAACATCCTGG CTGC-3' and 5'-GCAGCCAGGATGTTGTACGCCTTGGCTTTGGAGCCATACT GCC-3' for IFITM5-C86A; and 5'-GCACGATGTACCTGAATCTGGCGGCGCTTGGATTCCTGG CGC-3' and 5'-GCGCCAGGAATCCAAGCGCCGCCAGATTCAGGTACATCG TGC-3' for IFITM5-C52A/C53A, respectively (Sigma-Aldrich, St. Louis, MO).
Osteoblast-like MC3T3 cells were provided by the RIKEN, Cell Bank (RCB 1126). The procedures for cell culture, transfection, and protein expression were the same as reported previously. When necessary, 2-bromopalmitic acid (2BP; Wako, Osaka, Japan) and 17-octadecynoic acid (17-ODYA; Sigma-Aldrich) were dissolved in 99.5% dimethyl sulfoxide (DMSO; Wako) and added to differentiation medium at concentrations of 100 μM and 50 μM in less than 0.1% DMSO, respectively [30, 31] .
Wild-type and mutant IFITM5 proteins were also produced using an E. coli recombinant expression system. E. coli BL21(DE3) cells transformed by the expression plasmid were grown at 37°C in LB medium containing 50 μg/mL ampicillin. After four-hour induction by 1 mM isopropyl β-Dthiogalactopyranoside (IPTG), cells were harvested by centrifugation (6,400 × g for 10 min at 4°C). The cells were suspended in 50 mM Tris-HCl buffer (pH 8) and disrupted by a French press (Ohtake, Tokyo, Japan) (100 MPa × 4 times). The crude membrane fraction was collected by ultracentrifugation (178,000 × g for 90 min at 4°C). The collected fraction was solubilized with 1.5% n-dodecyl-β-Dmaltopyranoside (DDM) (Dojindo Lab, Kumamoto, Japan) in 50 mM Tris-HCl, pH 8, containing 0.3 M NaCl and 5 mM imidazole. After the ultracentrifugation, the supernatant was incubated with Ni 2+ -NTA agarose resin (Qiagen, Hilden, Germany). The resin was applied to a chromatography column and washed with 50 mM imidazole containing 50 mM Tris-HCl (pH 8), 0.3 M NaCl and 0.1% DDM. The DDM-solubilized IFITM5 was collected by elution with the same buffer containing 0.3 M imidazole. The sample media were replaced by the appropriate buffer solution by two passages over a PD-10 column (GE Healthcare UK, Ltd., Amersham Place, England).
The experimental details are described in previous reports [19, 28] . Briefly, total proteins were extracted from the osteoblast cells which co-expressed IFITM5 and FKBP11-FLAG using a total protein extraction kit (BioChain Institute Inc., Newark, CA). Then, the cell lysate was incubated with anti-FLAG M2 agarose gel (Sigma-Aldrich) at 4°C for 2 h. To recover FKBP11-FLAG, 500 ng/μL 3 × FLAG peptide (Sigma-Aldrich) dissolved in Tris-buffered saline was added to the collected gel at 4°C for 1 h. The recovered proteins and the cell lysate containing total proteins were analyzed by SDS-PAGE (15% ePAGEL; ATTO, Tokyo, Japan) and western blot. The anti-IFITM5 polyclonal antibody, which was prepared from the amino-terminal peptide sequence (TSYPREDPRAPSSRC), and anti-FLAG monoclonal antibody (Sigma-Aldrich) were used as primary antibodies. The HRP-conjugated goat anti-rabbit IgG (H+L) (Zymed Laboratories, San Francisco, CA) and goat anti-mouse IgG (H+L) (Sigma-Aldrich) antibodies were used as secondary antibodies for the anti-IFITM5 and anti-FLAG primary antibodies, respectively. The proteins were detected by chemiluminescent reaction (MercK-Millipore, Billerica, MA).
The cell lysate extracted from the osteoblast cells metabolically labeled by 17-ODYA was incubated with anti-FLAG M2 agarose gel to obtain purified FLAG-fused IFITM5 proteins. The 17-ODYA-labeled proteins were chemically labeled with azide-PEG 3 -5(6)-carboxytetramethylrhodamine (TAMRA-azide; Click Chemistry Tools, Scottsdale, AZ) with reference to previous studies [10, 29, 30, 32] and the manufacturer's guide. The proteins separated by SDS-PAGE were visualized using a 532-nm laser for excitation and the fluorescence by TAMRA (565 nm) was detected using a 575nm long-path filter (Typhoon FLA 9000; GE Healthcare).
The subcultured osteoblast MC3T3 cells were seeded at a density of 5,000 cells/cm 2 in 40 mm dishes and cultured in α-Modified Eagle's Medium (α-MEM; Sigma-Aldrich) containing 10% (v/v) fetal bovine serum (FBS; Nichirei Biosciences Inc., Tokyo, Japan). On the next day, this was replaced with differentiation medium, containing 2 mM glycerophosphate and 50 μg/mL sodium ascorbate at final concentrations, to induce osteoblast differentiation. When necessary, 100 μM 2BP in less than 0.1% DMSO, or 0.1% DMSO alone was added to the differentiation medium at final concentrations. All cultures were incubated at 37°C in a humidified atmosphere containing 5% CO 2 for 27 days. Mineralized nodules were stained with Alizarin Red S (Sigma-Aldrich). The standard staining procedure was used. The mineralized nodules were checked every three days.
To identify the S-palmitoylation on IFITM5, the osteoblast cells harboring the plasmid DNA encoding IFITM5-WT were cultured in the absence and presence of 2BP, which inhibits the S-palmitoylation (Figure 2-A) [31] . Then, the cell lysate containing total protein was extracted for use in the SDS-PAGE and western blot analyses. For purposes of comparison, E. coli cells were also cultured in the absence of 2BP and the cell lysate was extracted. Figure 2 -B shows the results of the western blot assay for IFITM5-WT expressed in the osteoblast and the E. coli cells. In the osteoblast cells, IFITM5-WT exhibited a single band near the 17.4 kDa molecular-mass marker (see lane 1) in the absence of 2BP. However, in the presence of 2BP (see lane 4), the band appeared at a lower position than that in the absence of 2BP (lane 1). These results suggested that IFITM5-WT has high and low molecular-mass forms in the absence and presence of 2BP, respectively. The S-palmitoylation is a reversible reaction, and therefore is depalmitoylated by a strong reductant such as hydroxylamine [10] . Following hydroxylamine treatment (see lane 2), the band appeared at the same position as in the presence of 2BP (lane 4). In prokaryote E. coli cells, the post-translational modification S-Palmitoylation on IFITM5 PLOS ONE | www.plosone.org does not occur. Hence, the band was also observed at the same lower position (see lane 3). In the case of IFITM3, the palmitoylation was also reported to induce a change in mobility on electrophoresis, just as in our present results [10] .
For direct observation of the S-palmitoylation, an established chemical reporter, 17-ODYA (Figure 2-C) , was used. The osteoblast cells harboring the plasmid encoding IFITM5-WT were cultured in the presence of 17-ODYA to label the protein metabolically. Following the extraction and the purification of the cell lysate, the labeled IFITM5-WT was ligated with TAMRA-azide according to the Cu(I)-catalyzed [3+2] azidealkyne cycloaddition method [10, 29, 30, 32 ]. An in-gel fluorescence image of the 17-ODYA-TAMRA-labeled IFITM5-WT (see lane 2 in Figure 2 -D) showed that IFITM5 was Spalmitoylated in the osteoblast cells. The FLAG-tag attached to IFITM5 has no influence on the modification and chemical labeling (lanes 1 and 5). In addition, after the hydroxylamine treatment (see lane 6), the fluorescence became weak because of the dissociation of 17-ODYA from IFITM5, which was the same mechanism as the dissociation of the palmitic acid from IFITM5 by reduction as described above (lane 2 of Figure 2-B) .
Therefore, we concluded that the IFITM5 expressed in the native osteoblast cells is S-palmitoylated. In addition, the bands corresponding to the high and the low molecular-mass forms shown in western blot analysis were tentatively assigned to the S-palmitoylated and the depalmitoylated forms, respectively.
As described above in the Introduction, cysteine residues are the substrate for S-palmitoylation. IFITM5 possesses three cysteines, Cys52 and Cys53 in the TM1 domain, and Cys86 in the CP loop (Figure 1-A) . All of these cysteines are highly conserved among the mammalian IFITM family proteins (Figure 3-A) . To identify the modification site in IFITM5, we prepared cysteine-substituted mutants, IFITM5-C52A/C53A, -C86A, and -C52A/C53A/C86A (Cys-less). The osteoblast cells harboring each plasmid were cultured in the absence of 2BP, and then the cell lysate was extracted. Figure 3 -B shows the results of the western blot detecting the expression of all the mutants in the osteoblast cells. In the C52A/C53A and Cys-less mutants (see lanes 2 and 4), the low molecular-mass form was detected. This result indicates that either Cys52 or Cys53 is involved in the S-palmitoylation. In addition, as shown in Figure 2 -D, strong and weak fluorescence were detected in the C52A/ C53A mutant in the absence and presence of hydroxylamine (lanes 3 and 7) , respectively, but not in the Cys-less mutant (lanes 4 and 8) . These results suggested that the rest of the cysteine in the C52A/C53A mutant, Cys86, is S-palmitoylated and the Cys-less mutant completely lost the S-palmitoylation because all the cysteines were substituted. Therefore, we concluded that Cys86, plus one or two other cysteine residues in IFITM5, i.e., Cys52 and/or Cys53, are S-palmitoylated. In addition, it was found that the S-palmitoylation on the TM1 domain has a major effect on the mobility in the gel (lower panel of Figure 2 -D and Figure 3-B) . Therefore, we hereafter refer to the high and low molecular-mass forms as the TM1palmitoylated and the TM1-depalmitoylated forms, respectively. Finally, we reassigned the bands shown in the western blot analysis as follows: IFITM5-WT is fully palmitoylated, the C86A mutant is partially palmitoylated at Cys52 and/or Cys53, the C52A/C53A mutant is partially palmitoylated at Cys86, and the Cys-less mutant is completely depalmitoylated.
Previous studies have revealed that IFITM5 interacts with FKBP11 [19] . FKBP11 belongs to the FK506-binding protein family and has a transmembrane domain. The interaction between IFITM5 and FKBP11 is important for the immune activity because formation of the IFITM5-FKBP11-CD81-FPRP complex induces the expression of interferon-induced genesnamely, the Bst2, Irgm, Ifit3, B2m, and MHC class I antigen gene [28] . To investigate the effect of the S-palmitoylation on the interaction of IFITM5 with FKBP11, we carried out an immunoprecipitation assay. The osteoblast cells co-transfected by the plasmids encoding IFITM5-WT and FKBP11-FLAG were cultured in the absence and the presence of 2BP. Then, the extracted cell-lysate was incubated with anti-FLAG agarose gel. The gel was washed several times. Finally, the proteins were competitively eluted by the addition of FLAG peptide. If IFITM5 interacted with FKBP11, it was expected that IFITM5 The conserved cysteines are highlighted in orange and numbered. In the lower panel, the numbers given in parenthesis correspond to the residual number for IFITM2. For the calculation of probability, a total of 23 IFITM2, 23 IFITM3, and 17 IFITM5 sequences derived from mammalian species in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database were used. Sequence alignment was carried out using CLUSTALW. Sequence logos were generated using WEBLOGO 3. B) Western blot for the wild-type and cysteine-substituted mutants of IFITM5 expressed in the osteoblast cells. For detection, the anti-IFITM5 antibody was used as a primary antibody. The upper arrow indicates that C52 and/or C53 in the TM1 domain is Spalmitoylated (lanes 1 and 3) . The C52A/C53A (lane 2) and Cys-less (lane 4) mutants are partially and completely depalmitoylated. The experiment was carried out 2 times. doi: 10.1371/journal.pone.0075831.g003 would be obtained during this step and detected by immunoblotting. Figure 4 -A shows the results of the western blot for the co-immunoprecipitation of IFITM5-WT with FKBP-FLAG. The band corresponding to FKBP11 appeared in all the lanes (upper panel). Lanes 1 and 2 are controls to ensure that IFITM5 and FKBP11 are both contained in the cell lysate before the immunoprecipitation. The controls also ensured that IFITM5 was S-palmitoylated in the absence of 2BP (see lane 1), whereas IFITM5 was not S-palmitoylated in the presence of 2BP (see lane 2). After the immunoprecipitation, a single band corresponding to the S-palmitoylated IFITM5 appeared in the absence of 2BP (see lane 3), indicating the interaction of the Spalmitoylated IFITM5 with FKBP11. However, in the presence of 2BP, no band corresponding to IFITM5 appeared (see lane 4) , indicating that the two molecules do not interact with each other. These results suggest that the S-palmitoylation on IFITM5 contributes to the interaction with FKBP11.
Next, we further investigated the relationship between the Spalmitoylation and the interaction with FKBP11 by using the IFITM5 mutants described above. The osteoblast cells cotransfected by the plasmids encoding IFITM5 mutants (C52A/ C53A, C86A, and Cys-less) and FKBP11-FLAG were cultured. The immunoprecipitation assay was carried out in the same way as described above. Figure 4 -B shows the results of the western blot for the co-immunoprecipitation of the wild-type and the IFITM5 mutants with FKBP11. Figure 4 -C shows the results of the control experiment using the cell lysate before the immunoprecipitation. As described in the previous section 3-3, the band corresponding to FKBP11 appeared in all the lanes (upper panels) because the immunoprecipitation was carried out using the anti-FLAG agarose gel. In the lower panel of Figure 4 -B, single bands were observed for the IFITM5-WT and -C86A mutant (lanes 1 and 3) but not for the -C52A/C53A and Cys-less mutants (lanes 2 and 4) . This result indicates that the wild-type and the C86A mutant interact with FKBP11, whereas the other two mutants do not. Interestingly, this tendency mirrored the trend for the S-palmitoylation profiles, which means that Cys52 and/or Cys53 in the TM1 domain of the IFITM5-WT and -C86A mutants is S-palmitoylated, whereas these residues are not S-palmitoylated in the C52A/C53A and Cys-less mutants (see Figures 2-D, 3 -B and the lower panel of Figure 4 -C). Because the S-palmitoylation contributes to the IFITM5-FKBP11 interaction, as described in the previous section 3-3 (also in Figure 4-A) , the results of Figure 4 -B suggest that the mutants which lost the S-palmitoylation site(s), Cys52 and/or Cys53, are not able to interact with FKBP11. In other words, the S-palmitoylation on these cysteines is necessary for the interaction of IFITM5 with FKBP11.
As described above in the Introduction, previous studies have revealed that IFITM5 also contributes to bone formation [18] [19] [20] [21] . Therefore, we investigated the influence of Spalmitoylation on the bone nodule formation in osteoblast cells, in which native IFITM5 is expressed. Figure 5 shows the time-dependent nodule formation in the absence and the presence of 2BP ( Figure 5-A and -B) . Figure 5 -C shows the results of the control trial to verify the effect of DMSO, which was used as the solvent for 2BP, on the nodule formation. The mineralized nodule was stained with Alizarin Red, which reacts with deposited calcium. In Figure 5 -D, the area of the mineralized nodule was plotted against experimental time. In the absence of 2BP (Figure 5-A, -C, and -D) , the mineralization was started 15 days after the initiation of the cell differentiation (Day 0). On the other hand, in the presence of 2BP ( Figure 5-B and -D) , the nodule was formed on Day 12. The halftime for the maximum mineralization in the presence of 2BP was estimated to be 7 days earlier than that in the absence of 2BP (Figure 5-D) . In addition, differences in the form of the mineralized nodules were observed. Figure 5 -E shows an enlarged view of each nodule on Day 21. The stained nodules were diffused in the presence of 2BP (panel b), whereas in the absence of 2BP the nodules formed a large cluster (panels a and c). Therefore, our observations in this study suggested that the S-palmitoylation affects the bone nodule formation in the osteoblast cells.
In this study, we confirmed the S-palmitoylation on IFITM5 in the osteoblast cells, which was the same as that previously reported for IFITM3 and IFITM2. As reported previously, in IFITM3 and IFITM2, which share 85% sequence similarity (Figure 1-C) , two cysteines in the TM1 domain (Cys71 and Cys72 for IFITM3, Cys70 and Cys71 for IFITM2) and one cysteine in the CP loop (Cys105 for IFITM3, Cys104 for IFITM2) are all S-palmitoylated in cells [10, 24] . On the other hand, although IFITM5 shares 68% and 66% sequence similarity to IFITM3 and IFITM2, respectively, more than one cysteine in the TM1 domain (Cys52 or Cys53) and one cysteine in the CP loop (Cys86) are S-palmitoylated. Taking into account the high conservation of three cysteines in the IFITM proteins (Figures 1-A and 3-A) , all the cysteines in IFITM5 may be involved in the S-palmitoylation just as in the case of IFITM3 and IFITM2 [10, 24] .
The roles of the S-palmitoylation on IFITM3 have been studied intensively, and the S-palmitoylation has been shown to be crucial for the correct positioning in the membrane and the resistance to viral infection and internalization [10] (the roles are summarized in Figure 6 -A and discussed in detail below). A recent study has revealed that the S-palmitoylation on IFITM2 is also important for the protein clustering in the membrane [24] . However, we do not know the role of the Spalmitoylation of IFITM5 for the clustering in the membrane at present because we have not yet succeeded in obtaining a proper antibody for immunohistochemistry, despite our allocating much time to the search and considering a considerable number of antibodies.
Dr. Hanagata and co-workers previously reported that IFITM5 lacking the TM1 domain and the CP loop, which and IFITM5 (lower panels), the anti-FLAG and the anti-IFITM5 antibodies were used as primary antibodies, respectively. Arrows indicate the existence of each protein and the S-palmitoylation on IFITM5. A) Western blot for the co-immunoprecipitation of the wild-type IFITM5 with the FLAG-fused FKBP11 (FKBP11-FLAG) in the osteoblast cells in the absence and the presence of 2BP (denoted as "-" and "+", respectively). Lanes 1 and 2 are the results for the control trials used to verify the existence of IFITM5 and FKBP11 before the immunoprecipitation, and Lanes 3 and 4 show the results after the immunoprecipitation. The experiment was repeated 3 times. B) Western blot for the co-immunoprecipitation of the wild-type and the cysteine-substituted mutants of IFITM5 with FKBP11-FLAG in the osteoblast cells. The band corresponding to FLAG peptide is not shown because of the smaller molecular-mass of FLAG peptide relative to FKBP11-FLAG. C) The control experiment of Figure 4 -B used to verify that IFITM5 and FKBP11 were both present in the cell lysate before the immunoprecipitation. The experiment was repeated 2 times. A) The functional mechanism of IFITM3 is summarized from previous studies. (i) IFITM3 is S-palmitoylated at Cys71, Cys72, and Cys105, (ii) which induces clustering and correct positioning in the membrane, (iii) resulting in the antiviral activity against influenza virus. B) The functional mechanism of IFITM5 is summarized by combining the results from the present and the previous studies. (i) Cys86, plus one or two other cysteine residues in IFITM5, i.e., Cys52 and/or Cys53, are S-palmitoylated (ii). The S-palmitoylation allows IFITM5 to interact with FKBP11 in the osteoblast cells (iii). The dissociation of CD9 from the FKBP11-CD81-FPRP/CD9 complex is induced by formation of the IFITM5-FKBP11-CD81-FPRP complex and leads to the immunologically relevant gene expression. IFITM5 also contributes to the bone formation, but it is unknown which states as described in (i)-(iii) are important for the bone formation at present.At present, no interactive protein has been identified in IFITM3 and IFITM2. On the other hand, IFITM5 interacts with the partner protein, FKBP11, and the S-palmitoylation clearly makes a significant contribution to the interaction. Therefore, IFITM5 forms a hetero-oligomer in the cell membrane for its physiological function.
contain the relevant modification sites, lost the ability to interact with FKBP11 [19] . In the present study, we determined that the S-palmitoylation on Cys52 and/or Cys53 in the TM1 domain is necessary for the interaction. From these results, we speculate that Cys52 and Cys53 face toward the interaction surface with FKBP11, and therefore IFITM5 and FKBP11 interact with each other through the palmitic acid(s) attached to the cysteine(s) (summarized in Figure 6 -B, discussed in detail later). Our investigation revealed that Cys86 is involved in the Spalmitoylation but does not contribute to the interaction with FKBP11. We speculate that some other residues in the CP loop located near the TM1 domain make some contribution to the interaction.
Previous investigations also revealed that IFITM5 expressed in the heterologous fibroblast NIH3T3 cells exhibited direct interactions with CD81, the B cell receptor-associated protein 31 (BCAP31), and the hydroxysteroid (17-beta) dehydrogenase 7 (HSD17b7). These three proteins bind to the IFITM5 without the S-palmitoylation (low molecular-mass form; see Figure 3 -b in ref [19] . and Figure 1 -B in ref [28] .). In the fibroblast cells, the S-palmitoylation on IFITM5 is insufficient [19] . These interactions are not observed in the native osteoblast cells, and therefore are nonspecific. Taking these facts into consideration, we speculate that the S-palmitoylation on IFITM5 promotes the specific interaction with FKBP11 in the osteoblast cells.
The role played by the S-palmitoylation of IFITM5 in immune activity of the osteoblast cells will be discussed by combining the results from the present and the previous studies. A specific interaction between IFITM5 and FKBP11 should be necessary to form the IFITM5-FKBP11-CD81-FPRP complex. CD81, also known as TAPA-1, is a member of the tetraspanin membrane protein family and a component of the B-cell coreceptor complex which mediates the B-cell signaling for immune responses. When forming this complex, CD9, a partner protein with CD81, dissociates from the FKBP11-CD81-FPRP/CD9 complex and consequently induces the osteoblastspecific expression of the interferon-induced genes, Bst2, Irgm, Ifit3, B2m, and the MHC class I antigen gene [28] . If the Spalmitoylation-mediated specific interaction of IFITM5 with FKBP11 were lost, the IFITM5-FKBP11-CD81-FPRP complex would not be formed, and consequently the interferon-induced gene expression would be inhibited because CD9 would remain associated with the FKBP11-CD81-FPRP/CD9 complex. In this respect, we speculate that IFITM5 is involved in the immune system activity in the osteoblast cells and the interaction of the S-palmitoylated IFITM5 with FKBP11 regulates the immune activity.
In addition, it was suggested that the S-palmitoylation on IFITM5 contributes to the bone nodule formation, including morphology and time for mineralization, in the osteoblast cells ( Figure 5 ). It is difficult to conclude at present that the lack of the S-palmitoylation on IFITM5 causes the diffusion of the bone nodules (panel b of Figure 5 -E); we can say, however, that IFITM5 will probably not be S-palmitoylated in the cells in the presence of 2BP. While 2BP is commonly used as an inhibitor of palmitoylation, it also targets many metabolic enzymes [33, 34] . Thus, it is also difficult to interpret the results of the long-term incubation of the osteoblast cells in the presence of 2BP. In any case, these are interesting and key observations in terms of clarifying the role played by the S-palmitoylation of IFITM5 in bone formation, and further studies are required. Figure 6 describes a possible mechanism of the interaction of IFITM5 with FKBP11 and the role of IFITM5 in the osteoblast cell function by means of a comparison with IFITM3. In the case of IFITM3, as shown in Figure 6 -A, the following are observed. (i) The three cysteines are all S-palmitoylated (ii). The S-palmitoylation leads to the clustering and the correct positioning of IFITM3 molecules in the membrane (iii). The Spalmitoylation and the following clustering are crucial for the resistance to the influenza virus. When IFITM3 lacks the Spalmitoylation, the IFITM3 molecules do not cluster, which leads to the significant decrease in the antiviral activity.
On the other hand, Figure 6 -B shows that the following observations are made in the case of IFITM5. (i) Cys86, plus one or two other cysteine residues in IFITM5, i.e., Cys52 and/or Cys53, are S-palmitoylated (ii). The S-palmitoylated IFITM5 is able to interact specifically with FKBP11. The interaction is presumed to be mediated by the palmitic acid(s) attached to the cysteine(s) facing toward the interaction surface on FKBP11. Cys86 is involved in the S-palmitoylation but not in the interaction of IFITM5 with FKBP11. At present, however, little is known about the role of the S-palmitoylation of IFITM5 for the localization in the membrane. When the S-palmitoylation affects the localization of IFITM5 as in the case of IFITM3 [10] , the S-palmitoylated IFITM5 molecules should be localized in the membrane or the depalmitoylated molecules should be delocalized. The loss of the interaction between IFITM5 and FKBP11 could be due to a relocalization of the depalmitoylated IFITM5 that prevents its association with FKBP11 (iii). The Spalmitoylated IFITM5 interacts with the FKBP11-CD81-FPRP/CD9 complex through FKBP11, which induces the dissociation of CD9 from the complex and the expression of 5 immunologically relevant genes. Finally, IFITM5 forms the IFITM5-FKBP11-CD81-FPRP complex. It is unknown at present which of the three states (i)~(iii) illustrated in Figure 6 -B is important for the bone mineralization of the osteoblast cells. The lack of the S-palmitoylation influences the interaction with FKBP11, which could account for the following complex formation and gene expression. In addition, the bone nodule formation is also affected. Note that the role of the Spalmitoylation has been involved in the bone formation [35] . It is indicated that the S-palmitoylation on IFITM5 plays roles not only for the regulation of the immune activity but also for the bone formation.
In conclusion, we have revealed the S-palmitoylation on IFITM5 and its role in the interaction with FKBP11. Not only the immune activity but also the bone mineralization in the osteoblast cells is affected by the S-palmitoylation. In general, the functional role of the S-palmitoylation is different for each protein [36] . For many proteins, the palmitoylation and depalmitoylation cycle is constitutive and regulated by enzymes. Based on the present results, it is difficult to address (i) whether the S-palmitoylation on IFITM5 is constitutive or regulated, or (ii) when and where IFITM5 is S-palmitoylated in the osteoblast cells. Further studies are required and are currently underway. | Why is the expression of IFITM5 not promoted by interferons? | false | 575 | {
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1,689 | Chikungunya: A Potentially Emerging Epidemic?
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2860491/
SHA: f7c3160bef4169d29e2a8bdd79dd6e9056d4774c
Authors: Thiboutot, Michelle M.; Kannan, Senthil; Kawalekar, Omkar U.; Shedlock, Devon J.; Khan, Amir S.; Sarangan, Gopalsamy; Srikanth, Padma; Weiner, David B.; Muthumani, Karuppiah
Date: 2010-04-27
DOI: 10.1371/journal.pntd.0000623
License: cc-by
Abstract: Chikungunya virus is a mosquito-borne emerging pathogen that has a major health impact in humans and causes fever disease, headache, rash, nausea, vomiting, myalgia, and arthralgia. Indigenous to tropical Africa, recent large outbreaks have been reported in parts of South East Asia and several of its neighboring islands in 2005–07 and in Europe in 2007. Furthermore, positive cases have been confirmed in the United States in travelers returning from known outbreak areas. Currently, there is no vaccine or antiviral treatment. With the threat of an emerging global pandemic, the peculiar problems associated with the more immediate and seasonal epidemics warrant the development of an effective vaccine. In this review, we summarize the evidence supporting these concepts.
Text: Chikungunya virus (CHIKV), a mosquito-borne pathogen listed by National Institute of Allergy and Infectious Diseases (NIAID) as a Category C Priority Pathogen that causes Chikungunya fever (CHIKF), has been spreading throughout Asia, Africa, and parts of Europe in recent times [1, 2, 3] . CHIKV is an arthropod-borne virus (arbovirus) and is transmitted to humans primarily by Aedes aegypti, the infamous yellow fever propagator [4, 5] . CHIKV infection is marked by severe joint pain, contorting its victims into unusual postures [6] . The disease gets its name from the Kimakonde vernacular language of Tanzania and Mozambique, and the word chikungunya means ''that which contorts or bends up'' and translates in Swahili to ''the illness of the bended walker'' [7, 8, 9] . In Africa, CHIKV is maintained in a sylvatic cycle among forest-dwelling Aedes spp. mosquitoes, wild primates, squirrels, birds, and rodents ( Figure 1 ) [10] . In Asia, the disease is vectored by Ae. aegypti and Ae. albopictus [11] . Transmission in Asia occurs in an urban cycle whereby the mosquito spreads the disease from an infected human to an uninfected human, following an epidemiological pattern similar to dengue fever [12] .
The 2005-2006 epidemic of CHIKV in La Reunion islands in the Indian Ocean, spurred the discovery of a new vector species, Ae. albopictus [5] . Wrecking over one-third of the island's population, this epidemic peaked its devastation between January and February 2006, when over 46,000 cases came into light every week, including 284 deaths [5, 13] . Ae. albopictus is common in urban areas of the United States and is already flourishing in 36 states, raising grave concerns to the immunologically naive populace of the United States [14] .
Accordingly, this review elaborately details the epidemiology and global expansion of CHIKV, describes its clinical features and pathogenesis and its symptoms and complications, and finally nominates a possible vaccine approach against CHIKV infection.
CHIKV has been isolated into three genotypes based on phylogenetic studies. These genotypes, based on the gene sequences of an Envelope protein (E1), are Asian, East/Central/ South African, and West African [4, 11, 15] . Using phylogenetic models, Cherian et al. estimate that the Asian genotype of CHIKV emerged between 50 and 310 y ago, and the West and East African genotypes diverged between 100 and 840 y ago [15] . Since then, CHIKV has come a long way, with several mutations incorporated, and has continued to wreak epidemics in several regions. Recent activities of CHIKV include the Indian epidemic in 2005-2006, which was followed by a sudden explosion of cases in 2007. An estimated 1.3 million people across 13 states were reported to be infected in India [12, 16] , and CHIKV was also widespread in Malaysia, Sri Lanka, and Indonesia [17] . In July-August of 2007, CHIKV was reported in Italy, probably brought in by travelers from CHIKV-prone regions of India, Africa, and Indian Ocean islands such as Mauritius, Madagascar, and Seychelles. Few of the Italian isolates were found to have evolved from the Kerala isolate, which was associated with a A226V shift in E1 gene that represents a successful evolutionary adaptation in the mosquito vector similar to the ones observed in Reunion Island [2, 18, 19] .
In recent times, with an increase in global travel, the risk for spreading CHIKV to non-endemic regions has heightened [1] . Several travelers have brought CHIKV home with them after visiting areas with actively infected populations [12, 20] . Such cases have been documented in European countries, Australia, Asia, and the United States [8, 21] . The United States has already reported at least twelve cases of travel-associated CHIKV, while France has reported 850 cases, and the United Kingdom 93 [8, 14] . Beyond this, CHIKV-infected travelers have also been diagnosed in Australia, Belgium, Canada, Czech Republic, French Guiana, Germany, Hong Kong, Italy, Japan, Kenya, Malaysia, Martinique, Norway, Switzerland, and Sri Lanka [21] . Some travelers were viremic, worrying public health officials about the spread of CHIKV to new areas [1, 8] .
The incubation time for CHIKV is relatively short, requiring only 2-6 d with symptoms usually appearing 4-7 d post-infection [22] . Vazeille et al. detected CHIKV in the salivary glands of Ae. albopictus only 2 d after infection [5] . Upon infection, CHIKF tends to present itself in two phases. The first stage is acute, while the second stage, experienced by most but not all, is persistent, causing disabling polyarthritis. Characteristics of the acute phase include an abrupt onset of fever, arthralgia, and in some cases, maculopapular rash [6, 23] . The acute phase causes such intense joint and muscular pain that makes movement very difficult and prostrates its victims [6, 20] .
Ninety-five percent of infected adults are symptomatic after infection, and of these, most become disabled for weeks to months as a result of decreased dexterity, loss of mobility, and delayed reaction. Eighteen months after disease onset, 40% of patients are found to still have anti-CHIKV IgM [6, 18, 23, 24] . The chronic stage of CHIKF is characterized by polyarthralgia that can last from weeks to years beyond the acute stage [6] . CHIKV has been shown to attack fibroblasts, explaining the involvement of muscles, joints, and skin connective tissues. The high number of nociceptive nerve endings found within the joints and muscle connective tissues can explain pain associated with CHIKF [25, 26] .
More than 50% of patients who suffer from severe CHIKF are over 65 y old, and more than 33% of them die. Most adults who suffer from severe CHIKF have underlying medical conditions [6, 24, 27] . The other group that is disproportionately affected by severe CHIKV is children. Other complications associated with CHIKV, from most common to least common, include respiratory failure, cardiovascular decompensation, meningoencephalitis, severe acute hepatitis, severe cutaneous effects, other central nervous system problems, and kidney failure [6, 18, 20, 23, 24, 26, 27] .
CHIKV undertakes a complex replication cycle upon host infection (Figure 2 ), which makes its genome susceptible to mutations [28, 29] . For instance, Ae. aegypti, responsible for epidemics in Kenya, Comoros, and Seychelles, carried CHIKV with an alanine in the 226 position of the E1 gene (E1-A226) [4, 18] . However, when the virus struck La Reunion Islands, a decline in population of Ae. aegypti, due to massive dichlorodiphenyltrichloroethane usage and dearth of Ae. albopictus species' www.plosntds.org population, resulted in an ecological pressure, favoring replacement of alanine at position 226 with valine (E1-A226V) [5] . This mutation allowed CHIKV's secondary vector species, Ae. albopictus, to supplement Ae. aegypti as its primary vector [5] .
Within a year, the E1-A226V mutation was present in La Reunion Island, and Ae. albopictus apparently vectored the large epidemic infecting 34% of La Reunion Island's population [5] . All of the CHIKV strains isolated from Mayotte carried the E1-A226V mutation, and the mutation was also found in Madagascar in 2007 [5] . The E1-A226V mutation was not present at the beginning of the Indian Ocean Islands outbreak (before September 2005). However, more than 90% of later viral strains found there had incorporated the mutation (December-March 2006), indicating a genotype switch during the winter season [5, 18, 20] .
The E1-A226V mutation also enabled an increase in infectivity of Ae. albopictus when compared to its infectivity of Ae. aegypti [4, 11, 18, 30] , and with several factors taken together, Ae. albopictus has become the new preferred and more lethal vector for CHIKV [4, 5, 11] . In fact, Tsetsarkin et al. found that a Green Fluorescent Protein tagged E1-A226V virus was 100 times more infective to Ae. albopictus than it was to Ae. aegypti [4] . In all the Indian Ocean Islands, Ae. albopictus became the main vector for CHIKV within 1-2 y after CHIKV was introduced to the region [31] .
Of note is that Ae. aegypti has most likely been established in North America for over 300 y, while Ae. albopictus has been in many areas of the US, since 1985, primarily in Florida [32] and since then has expanded its range in the country. Reiskind et al. set out to determine if Ae. aegypti and Ae. albopictus mosquitoes captured in Florida were susceptible to CHIKV infection by a La Reunion isolate [32] . Each mosquito tested was highly susceptible to infection by a full-length infectious clone of the La Réunion Island isolate, CHIKV LR2006 OPY1 strain. Even though the Ae. albopictus strains were more susceptible to infection, overall ecology and differences in human biting patterns need to be studied further Characteristically, there are two rounds of translation: (+) sense genomic RNA (49S9 = 11.7 kb) acts directly as mRNA and is partially translated (59 end) to produce non-structural proteins (nsp's). These proteins are responsible for replication and formation of a complementary (2) strand, the template for further (+) strand synthesis. Subgenomic mRNA (26 S = 4.1 kb) replication occurs through the synthesis of full-length (2) intermediate RNA, which is regulated by nsp4 and p123 precursor in early infection and later by mature nsp's. Translation of the newly synthesized sub-genomic RNA results in production of structural proteins such as Capsid and protein E2-6k-E1 (from 39 end of genome). Assembly occurs at the cell surface, and the envelope is acquired as the virus buds from the cell and release and maturation almost simultaneous occurred. Replication occurs in the cytoplasm and is very rapid (,4 h) [28, 29] . doi:10.1371/journal.pntd.0000623.g002 www.plosntds.org to gain a more accurate understanding of a potential CHIKV epidemic in the US [32] .
During the 7 d preceding birth, no human mother has been reported to transmit the disease vertically. However, about 50% of newborns delivered while the mother was infected with CHIKV contracted the disease from their mother, despite the method of delivery. Furthermore, there have been instances of CHIKV transmission from mother to fetus causing congenital illness and fetal death [33] .
During the 2005-2006 La Reunion Island outbreaks, Ramful et al. discovered that mothers could transmit CHIKV to their progeny during the perinatal period (Day 24 to Day +1) [33, 34] , and it is associated with a high degree of morbidity. By mean Day 4 of life, all of the neonates were symptomatic for CHIKV, exhibiting common CHIKF symptoms. Six neonates were confirmed to have contracted CHIKV and developed mengoencephalitis. Of those mothers who, during the La Reunion Island epidemic, were infected long before delivery, only three fetal deaths were reported [12, 33] . Ramful et al. theorized that motherto-child transmission most likely happens transplacentally shortly before delivery [33] . A similar study by Gerardin et al. reported nineteen cases of neonatal infection associated with intrapartum maternal viremia that progressed to develop encephalitis owing to vertical transmission from infected mothers [34] .
Clinical and epidemiological similarities with dengue fever make CHIKV diagnosis difficult, which may lead physicians to misdiagnose CHIKV as dengue fever; therefore, the incidence of CHIKV may actually be higher than currently believed (Table 1 ) [6, 12, 35] .
The amount of time elapsed since disease onset is the most critical parameter when choosing a diagnostic test. CHIKV can be detected and isolated by culturing with mosquito cells (C6/36), Vero cells (mammalian), or in mice [26] . However, this method can take at least a week and only achieves a high sensitivity during the viremic phase, which usually only lasts up to 48 h after the bite. Five days post-infection, the viral isolation approach has a low sensitivity but is still the preferred method for detecting the CHIKV strain [12, 26, 31, 35] . RT-PCR on the other hand is a faster and more sensitive method that can be used within the first week of disease onset [26] , and it is currently the most sensitive method for detecting and quantifying viral mRNA [4, 36] .
Classic serological detection, by assays such as ELISA [37] , immunofluorescence [5, 38] , complement binding, and haemagglutination inhibition [39] , constitutes the second diagnostic tool used for biological diagnosis of CHIKV infection. These proven techniques are useful for detection of Antigen in mosquitoes during epidemiological studies. These assays detect virus-specific IgM and IgG, however the sensitivity and specificity of these assays has been poorly characterized. Viral competence, or the potential of viral infection and transmission, is an important parameter that can be quantified by ELISA, viral culture, and PCR.
A study by Ng et al. showed biomarkers indicative of severe CHIKV infection [40] . They found decreased levels of RANTES and increased levels of Interleukin-6 (IL-6) and Interleukin-1b (IL-1b) that could be sued for CHIKV detection in patients as indicators of CHIKV-driven cytokine storm. Couderc et al. demonstrate another cytokine, type-I IFN, as a key player in the progression to CHIKV infection [26] . Using an IFN-a/b null mouse model, they demonstrated evidence of muscles, joints, and skin as privileged CHIKV targets, which is consistent with human pathology. Although Ng et al. concluded that RANTES levels were significantly suppressed in severe CHIKF patients [40] , interestingly, an increase in levels of RANTES has been observed in dengue infection [41] . Since the symptoms of CHIKF mimic those of dengue fever, results obtained from this study strongly suggest that RANTES could be a potential distinctive biomarker that differentiates between these two clinically similar diseases.
There are no approved antiviral treatments currently available for CHIKV [1, 3, 12, 42] . Currently, CHIKF is treated symptomatically, usually with non-steroidal anti-inflammatory drugs or steroids, bed rest, and fluids. Movement and mild exercise are thought to decrease stiffness and morning arthralgia, but heavy exercise may exacerbate rheumatic symptoms. Corticosteroids may be used in cases of debilitating chronic CHIKV infection. There is a debate about the appropriateness of chloroquine as treatment for unresolved, non-steroidal anti-inflammatory drugresistant arthritis [43] . A study showed that viral production was www.plosntds.org drastically reduced at 16 h post-infection after treatment with 100 mM dec-RVKR-cmk (Decanoyl-Arg-Val-Lys-Arg-chloromethylketone), a furine inhibitor [42, 44] . Chloroquine acted by raising the pH, blocking low pH-dependent entry of virus into the cell. It is important to note that dec-RVKR-cmk or chloroquine only inhibited viral spreading from cell to cell, not CHIKV replication once it had entered the cell [43] . However, most would agree that the best weapon against CHIKV is prevention. A live CHIKV vaccine developed by the United States reached phase II clinical trial encompassing 59 healthy volunteers [45] . Eight percent of the volunteers experienced transient arthralgia, while 98% of the volunteers had seroconversion [45] . However, live CHIKV vaccines are still questionable. One cannot discount the risk of a live vaccine possibly inducing chronic rheumatism. Also, there is the question as to whether widespread use among the public could trigger mosquito transmission or lead to chronic infection or viral reversion [1] .
An alternative approach would be to produce a chimeric vaccine against CHIKV. Wang et al. developed a chimeric alphavirus vaccine that is uniformly attenuated and does not cause reactogenicity in mice [3] . Three different versions of this vaccine were made using three different backbone vectors: Venezuelan equine encephalitis virus (VEEV) attenuated vaccine strain T-83, naturally attenuated eastern equine encephalitis virus (EEEV), and attenuated Sindbis virus (SINV). In short, CHIKV structural proteins were engineered into the backbones of the aforementioned vaccines to produce the chimeras [3] . These chimeras were found to stimulate a strong humoral immunity, and even at doses of 5.3-5.8 log 10 PFU, they did not trigger reactogenicity. When vaccinated mice were challenged with CHIKV, neither adult nor neonatal mice gained weight, had fever, or displayed signs of neurological illness. Upon comparison of the chimeras with the Army181/25 vaccine, the Army vaccine resulted in higher levels of viremia and replication in the joints of neonatal mice. Because the joints are known targets of CHIKV, Wang et al. noted their vaccine might avoid the negative reactogenic side effects of the Army vaccine. After being subcutaneously vaccinated with 5.3-5.8 log 10 PFU of the chimeric vaccines, mice produced strong neutralizing antibody titers. The VEEV and EEEV chimeras yielded higher neutralizing antibody titers than the SINV chimera without being more virulent. On top of this, the VEEV and EEEV CHIKV chimeras seemed to be more immunogenic than the Army vaccine despite the chimeras' lower viremia and replication in the joints of neonatal mice [3] .
Tiwari et al. [46] adopted a different strategy using formalin inactivated CHIKV in combination with alhydrogel (Aluminum Hydroxide) as an adjuvant. This study clearly suggests that this vaccine elicits both humoral and cell-mediated immune responses in mice, providing its immunogenic potential. A recent study by Couderc et al. [47] showed passive immunization as a potential treatment for CHIKV infection. Using purified immunoglobulin extracted from convalescent CHIKV patients, they demonstrated effective neutralizing activity against CHIKV infection both in vitro and in vivo. This thereby establishes a potential preventive and therapeutic approach to combat CHIKV infection. Pathogenesis studies conducted with related alpha virus, like RRV, have shown the role of macrophages in persistence on infection [48] . They also demonstrated the role of RRV-specific CD8 T cells in clearing viral load in infected patients, thereby warranting similar investigations with CHIKV and the importance of investigating a cell-mediated immune response-based vaccine against CHIKV [49] .
There are always certain risks associated with live attenuated or inactivated viral vaccines [50] . One way to avoid these potential problems is to construct a consensus-based DNA vaccine. DNA based vaccines have an improved safety profile as compared to live or attenuated vaccines [51, 52] . A consequence of CHIKV's rapid evolution is difficulty in constructing a vaccine that will be able to Figure 3 . Levels of CHIKV-specific IgG in mice immunized with CHIKV vaccines. Each group of C57BL/6 mice (n = 5) was immunized with 12.5 mg of pVax1 control vector or CHIKV vaccine plasmids as indicated at 0 and 2 wk. Mice were bled 2 wk after each immunization, and each group's serum pool was diluted to 1:100 and 1:500 for reaction with specific vaccine constructs. Serum was incubated for 1 h at 37uC on 96-well plates coated with 2 mg/ml of respective CHIKV peptides, and antibody was detected using anti-mouse IgG-HRP and OD was measured at 405 nm. doi:10.1371/journal.pntd.0000623.g003 www.plosntds.org effectively protect large populations from multiple strains of the virus. One of the strengths of DNA consensus vaccines is its ability to induce cross-reactive immune responses against the three distinct phylogenetic groups of CHIKV. Also DNA-based vaccines can be produced more rapidly than protein-based vaccines.
Recently, Muthumani et al. constructed a vaccine that was shown to induce both humoral and cellular immunity in vivo in 3-4-wk-old female C57/BL6 mice [49] . These mice were immunized using an in vivo electroporation method to deliver the vaccine into the quadriceps muscle. The consensus construct was designed against E1, E2, and the core protein capsid. To design the construct, they aligned 21 sequences of CHIKV isolated between 1952 and 2006, using strains from differing countries, including La Reunion Island. The most common nucleotide among the sequences was chosen at each position to be used in the consensus construct, taking care not to alter the reading frame. They conducted codon and RNA optimization, added a strong Kozak sequence, and substituted signal peptide with an immunoglobulin E leader sequence to improve vaccine efficacy.
After immunizing the mice, spleens were harvested along with serum and tested to determine antibody titer. After three immunizations, consensus E1, E2, and C vaccines were shown to induce T-cell immune responses leading to strong IFN-c responses and proliferation in C57/BL6 mice. Furthermore, when compared with control mice, immunized mice had higher total IgG levels as well as higher anti-E1 specific, anti-E2 specific, and anti-C specific IgG antibodies, suggesting a strong humoral immune response ( Figure 3 ) and also specificity for the antigens encoded in the vaccine constructs ( Figure 4 ). Because of its promising results and the need for a safer vaccine, this consensus DNA vaccine deserves further investigation. Determining longevity of protective effects of the vaccine and persistence of antibody and IFN-c responses could be the next step of investigation. Challenged studies of immunized mice must also be carried out.
CHIKV mosquito-borne disease has caused massive outbreaks for at least half a century but is no longer confined to the www.plosntds.org developing nations. It began to encroach into the boundaries of the developing world. As a result, the NIAID has designated CHIKV as a Category C pathogen alongside the influenza and SARS-CoV viruses [3] . Realization of the potential severity of this disease is exigent; for instance, if used as a biological weapon, the world economy could be severely crippled; if enough members of the armed forces were to become infected during a military deployment, military operations could be significantly affected. Efforts to monitor the disease will only provide minimal warning in a global society, and steps to prevent the morbidity and mortality associated with pandemic are imperative [21, 31] . Despite the gravity of its infectious potency and the fear of it being a potential biological weapon, there is currently no vaccine for CHIKV infections. Live attenuated vaccine trials were carried out in 2000, but funding for the project was discontinued. Newer approaches such as DNA vaccines appear promising over conventional strategies like live attenuated or inactivated virus and thus call for further investigation. Recent advances such electroporation delivery and incorporation of adjuvants has boosted DNA vaccine efficacy [51, 53] . Despite the low antibody response to DNA vaccines, other numerous advantages have overshadowed these minor drawbacks (Table 2) , the most important one being the ability to induce both humoral and cellular immune responses [51, 54] .
Judging by recent success, such as the immunogenic construct developed by Muthumani et al., DNA vaccines could play a major role in combating CHIKV [49] . Vaccines are literally a critical component of CHIKV disease control and therefore research in this area is highly encouraged. The dramatic spread of dengue viruses (DENV) throughout tropical America since 1980 via the same vectors and human hosts underscores the risk to public health in the Americas. The adverse events associated with the current live vaccine are well documented [55] . Realizing these drawbacks, earnest efforts should be taken to develop new strategies to forestall further spread and complications. | What percentage die? | false | 2,504 | {
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1,571 | Community-acquired pneumonia in children — a changing spectrum of disease
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5608782/
SHA: eecb946b106a94f26a79a964f0160e8e16f79f42
Authors: le Roux, David M.; Zar, Heather J.
Date: 2017-09-21
DOI: 10.1007/s00247-017-3827-8
License: cc-by
Abstract: Pneumonia remains the leading cause of death in children outside the neonatal period, despite advances in prevention and management. Over the last 20 years, there has been a substantial decrease in the incidence of childhood pneumonia and pneumonia-associated mortality. New conjugate vaccines against Haemophilus influenzae type b and Streptococcus pneumoniae have contributed to decreases in radiologic, clinical and complicated pneumonia cases and have reduced hospitalization and mortality. The importance of co-infections with multiple pathogens and the predominance of viral-associated disease are emerging. Better access to effective preventative and management strategies is needed in low- and middle-income countries, while new strategies are needed to address the residual burden of disease once these have been implemented.
Text: Pneumonia has been the leading cause of death in children younger than 5 years for decades. Although there have been substantial decreases in overall child mortality and in pneumonia-specific mortality, pneumonia remains the major single cause of death in children outside the neonatal period, causing approximately 900,000 of the estimated 6.3 million child deaths in 2013 [1] . Substantial advances have occurred in the understanding of risk factors and etiology of pneumonia, in development of standardized case definitions, and in prevention with the production of improved vaccines and in treatment. Such advances have led to changes in the epidemiology, etiology and mortality from childhood pneumonia. However in many areas access to these interventions remains sub-optimal, with large inequities between and within countries and regions. In this paper we review the impact of recent preventative and management advances in pneumonia epidemiology, etiology, radiologic presentation and outcome in children.
The overall burden of childhood pneumonia has been reduced substantially over the last decade, despite an increase in the global childhood population from 605 million in 2000 to 664 million in 2015 [2] . Recent data suggest that there has been a 25% decrease in the incidence of pneumonia, from 0.29 episodes per child year in low-and middle-income countries in 2000, to 0.22 episodes per child year in 2010 [3] . This is substantiated by a 58% decrease in pneumonia-associated disability-adjusted life years between 1990 and 2013, from 186 million to 78 million as estimated in the Global Burden of Disease study [1] . Pneumonia deaths decreased from 1.8 million in 2000 to 900,000 in 2013 [1] . These data do not reflect the full impact of increasingly widespread use of pneumococcal conjugate vaccine in low-and middle-income countries because the incidence of pneumonia and number of deaths are likely to decrease still further as a result of this widespread intervention [4] .
Notwithstanding this progress, there remains a disproportionate burden of disease in low-and middle-income countries, where more than 90% of pneumonia cases and deaths occur. The incidence in high-income countries is estimated at 0.015 episodes per child year, compared to 0.22 episodes per child year in low-and middle-income countries [3] . On average, 1 in 66 children in high-income countries is affected by pneumonia per year, compared to 1 in 5 children in low-and middle-income countries. Even within low-and middleincome countries there are regional inequities and challenges with access to health care services: up to 81% of severe pneumonia deaths occur outside a hospital [5] . In addition to a higher incidence of pneumonia, the case fatality rate is estimated to be almost 10-fold higher in low-and middle-income countries as compared to high-income countries [3, 5] .
Childhood pneumonia can also lead to significant morbidity and chronic disease. Early life pneumonia can impair longterm lung health by decreasing lung function [6] . Severe or recurrent pneumonia can have a worse effect on lung function; increasing evidence suggests that chronic obstructive pulmonary disease might be related to early childhood pneumonia [7, 8] . A meta-analysis of the risk of long-term outcomes after childhood pneumonia categorized chronic respiratory sequelae into major (restrictive lung disease, obstructive lung disease, bronchiectasis) and minor (chronic bronchitis, asthma, abnormal pulmonary function) groups [9] . The risk of developing at least one of the major sequelae was estimated as 6% after an ambulatory pneumonia event and 14% after an episode of hospitalized pneumonia. Because respiratory diseases affect almost 1 billion people globally and are a major cause of mortality and morbidity [10] , childhood pneumonia might contribute to substantial morbidity across the life course.
Chest radiologic changes have been considered the gold standard for defining a pneumonia event [11] because clinical findings can be subjective and clinical definitions of pneumonia can be nonspecific. In 2005, to aid in defining outcomes of pneumococcal vaccine studies, the World Health Organization's (WHO) standardized chest radiograph description defined a group of children who were considered most likely to have pneumococcal pneumonia [12] . The term "end-point consolidation" was described as a dense or fluffy opacity that occupies a portion or whole of a lobe, or the entire lung. "Other infiltrate" included linear and patchy densities, peribronchial thickening, minor patchy infiltrates that are not of sufficient magnitude to constitute primary end-point consolidation, and small areas of atelectasis that in children can be difficult to distinguish from consolidation. "Primary end-point pneumonia" included either end-point consolidation or a pleural effusion associated with a pulmonary parenchymal infiltrate (including "other" infiltrate).
Widespread use of pneumococcal conjugate vaccination and Haemophilus influenzae type B conjugate vaccination has decreased the incidence of radiologic pneumonia. In a review of four randomized controlled trials and two case-control studies of Haemophilus influenzae type B conjugate vaccination in high-burden communities, the vaccination was associated with an 18% decrease in radiologic pneumonia [13] . Introduction of pneumococcal conjugate vaccination was associated with a 26% decrease in radiologic pneumonia in California between 1995 and 1998 [14] . In vaccine efficacy trials in low-and middle-income countries, pneumococcal conjugate vaccination reduced radiologic pneumonia by 37% in the Gambia [15] , 25% in South Africa [16] and 26% in the Philippines [17] .
The WHO radiologic case definition was not intended to distinguish bacterial from viral etiology but rather to define a sub-set of pneumonia cases in which pneumococcal infection was considered more likely and to provide a set of standardized definitions through which researchers could achieve broad agreement in reporting chest radiographs. However, despite widespread field utilization, there are concerns regarding inter-observer repeatability. There has been good consensus for the description of lobar consolidation but significant disagreement on the description of patchy and perihilar infiltrates [18, 19] . In addition, many children with clinically severe lung disease do not have primary end-point pneumonia: in one pre-pneumococcal conjugate vaccination study, only 34% of children hospitalized with pneumonia had primary end-point pneumonia [20] . A revised case definition of "presumed bacterial pneumonia" has been introduced, and this definition includes pneumonia cases with WHO-defined alveolar consolidation, as well as those with other abnormal chest radiograph infiltrates and a serum C-reactive protein of at least 40 mg/L [21, 22] . This definition has been shown to have greater sensitivity than the original WHO radiologic definition of primary end-point pneumonia for detecting the burden of pneumonia prevented by pneumococcal conjugate vaccination [23] . Using the revised definition, the 10-valent pneumococcal conjugate vaccine (pneumococcal conjugate vaccination-10), had a vaccine efficacy of 22% in preventing presumed bacterial pneumonia in young children in South America [22] , and pneumococcal conjugate vaccination-13 had a vaccine efficacy of 39% in preventing presumed bacterial pneumonia in children older than 16 weeks who were not infected with human immunodeficiency virus (HIV) in South Africa [21] . Thus there is convincing evidence that pneumococcal conjugate vaccination decreases the incidence of radiologic pneumonia; however there is no evidence to suggest that pneumococcal conjugate vaccination modifies the radiologic appearance of pneumococcal pneumonia.
Empyema is a rare complication of pneumonia. An increased incidence of empyema in children was noted in some high-income countries following pneumococcal conjugate vaccination-7 introduction, and this was attributed to pneumococcal serotypes not included in pneumococcal conjugate vaccination-7, especially 3 and 19A [24] . In the United States, evidence from a national hospital database suggests that the incidence of empyema increased 1.9-fold between 1996 and 2008 [25] . In Australia, the incidence rate ratio increased by 1.4 times when comparing the pre-pneumococcal conjugate vaccination-7 period (1998 to 2004) to the post-pneumococcal conjugate vaccination-7 period (2005 to 2010) [26] . In Scotland, incidence of empyema in children rose from 6.5 per million between 1981 and 1998, to 66 per million in 2005 [27] . These trends have been reversed since the introduction of pneumococcal conjugate vaccination-13. Data from the United States suggest that empyema decreased by 50% in children younger than 5 years [28] ; similarly, data from the United Kingdom and Scotland showed substantial reduction in pediatric empyema following pneumococcal conjugate vaccination-13 introduction [29, 30] .
Several national guidelines from high-income countries, as well as the WHO recommendations for low-and middleincome countries, recommend that chest radiography should not be routinely performed in children with ambulatory pneumonia [31] [32] [33] . Indications for chest radiography include hospitalization, severe hypoxemia or respiratory distress, failed initial antibiotic therapy, or suspicion for other diseases (tuberculosis, inhaled foreign body) or complications. However, point-of-care lung ultrasound is emerging as a promising modality for diagnosing childhood pneumonia [34] .
In addition to the effect on radiologic pneumonia, pneumococcal conjugate vaccination reduces the risk of hospitalization from viral-associated pneumonia, probably by reducing bacterial-viral co-infections resulting in severe disease and hospitalization [35] . An analysis of ecological and observational studies of pneumonia incidence in different age groups soon after introduction of pneumococcal conjugate vaccination-7 in Canada, Italy, Australia, Poland and the United States showed decreases in all-cause pneumonia hospitalizations ranging from 15% to 65% [36] . In the United States after pneumococcal conjugate vaccination-13 replaced pneumococcal conjugate vaccination-7, there was a further 17% decrease in hospitalizations for pneumonia among children eligible for the vaccination, and a further 12% decrease among unvaccinated adults [28] .
A systematic review of etiology studies prior to availability of new conjugate vaccines confirmed S. pneumoniae and H. influenzae type B as the most important bacterial causes of pneumonia, with Staphylococcus aureus and Klebsiella pneumoniae associated with some severe cases. Respiratory syncytial virus was the leading viral cause, identified in 15-40% of pneumonia cases, followed by influenza A and B, parainfluenza, human metapneumovirus and adenovirus [37] .
More recent meta-analyses of etiology data suggest a changing pathogen profile, with increasing recognition that clinical pneumonia is caused by the sequential or concurrent interaction of more than one organism. Severe disease in particular is often caused by multiple pathogens. With high coverage of pneumococcal conjugate vaccination and Haemophilus influenzae type B conjugate vaccination, viral pathogens increasingly predominate [38] . In recent case-control studies, at least one virus was detected in 87% of clinical pneumonia cases in South Africa [39] , while viruses were detected in 81% of radiologic pneumonia cases in Sweden [40] . In a large multi-center study in the United States, viral pathogens were detected in 73% of children hospitalized with radiologic pneumonia, while bacteria were detected in only 15% of cases [41] . A meta-analysis of 23 case-control studies of viral etiology in radiologically confirmed pneumonia in children, completed up to 2014, reported good evidence of causal attribution for respiratory syncytial virus, influenza, metapneumovirus and parainfluenza virus [42] . However there was no consistent evidence that many other commonly described viruses, including rhinovirus, adenovirus, bocavirus and coronavirus, were more commonly isolated from cases than from controls. Further attribution of bacterial etiology is difficult because it is often not possible to distinguish colonizing from pathogenic bacteria when they are isolated from nasal specimens [43] .
Another etiology is pertussis. In the last decade there has also been a resurgence in pertussis cases, especially in highincome countries [44] . Because pertussis immunity after acellular pertussis vaccination is less long-lasting than immunity after wild-type infection or whole-cell vaccination, many women of child-bearing age have waning pertussis antibody levels. Their infants might therefore be born with low transplacental anti-pertussis immunoglobulin G levels, making them susceptible to pertussis infection before completion of the primary vaccination series [45] . In 2014, more than 40,000 pertussis cases were reported to the Centers for Disease Control and Prevention in the United States; in some states, population-based incidence rates are higher than at any time in the last 70 years [44] . In contrast, most low-and middleincome countries use whole-cell pertussis vaccines and the numbers of pertussis cases in those countries were stable or decreasing until 2015 [46] . However recent evidence from South Africa (where the acellular vaccine is used) shows an appreciable incidence of pertussis among infants presenting with acute pneumonia: 2% of clinical pneumonia cases among infants enrolled in a birth cohort were caused by pertussis [39] , and 3.7% of infants and young children presenting to a tertiary academic hospital had evidence of pertussis infection [47] .
Similarly, childhood tuberculosis is a major cause of morbidity and mortality in many low-and middle-income countries, and Mycobacterium tuberculosis has increasingly been recognized as a pathogen in acute pneumonia in children living in high tuberculosis-prevalence settings. Postmortem studies of children dying from acute respiratory illness have commonly reported M. tuberculosis [48, 49] . A recent systematic review of tuberculosis as a comorbidity of childhood pneumonia reported culture-confirmed disease in about 8% of cases [50] . Because intrathoracic tuberculosis disease is only culture-confirmed in a minority of cases, the true burden could be even higher; tuberculosis could therefore be an important contributor to childhood pneumonia incidence and mortality in high-prevalence areas.
Childhood pneumonia and clinically severe disease result from a complex interaction of host and environmental risk factors [37] . Because of the effectiveness of pneumococcal conjugate vaccination and Haemophilus influenzae type B conjugate vaccination for prevention of radiologic and clinical pneumonia, incomplete or inadequate vaccination must be considered as a major preventable risk factor for childhood pneumonia. Other risk factors include low birth weight, which is associated with 3.2 times increased odds of severe pneumonia in low-and middle-income countries, and 1.8 times increased odds in high-income countries [51] . Similarly, lack of exclusive breastfeeding for the first 4 months of life increases odds of severe pneumonia by 2.7 times in low-and middle-income countries and 1.3 times in highincome countries. Markers of undernutrition are strong risk factors for pneumonia in low-and middle-income countries only, with highly significant odds ratios for underweight for age (4.5), stunting (2.6) and wasting (2.8) . Household crowding has uniform risk, with odds ratios between 1.9 and 2.3 in both low-and middle-income countries and high-income countries. Indoor air pollution from use of solid or biomass fuels increases odds of pneumonia by 1.6 times; lack of measles vaccination by the end of the first year of age increases odds of pneumonia by 1.8 times [51] . It is estimated that the prevalence of these critical risk factors in low-and middle-income countries decreased by 25% between 2000 and 2010, contributing to reductions in pneumonia incidence and mortality in low-and middle-income countries, even in countries where conjugate vaccines have not been available [3] .
The single strongest risk factor for pneumonia is HIV infection, which is especially prevalent in children in sub-Saharan Africa. HIV-infected children have 6 times increased odds of developing severe pneumonia or of death compared to HIV-uninfected children [52] . Since the effective prevention of mother-to-child transmission of HIV, there is a growing population of HIV-exposed children who are uninfected; their excess risk of pneumonia, compared to HIV unexposed children, has been described as 1.3-to 3.4-fold higher [53] [54] [55] [56] [57] .
The pneumococcal conjugate vaccination and Haemophilus influenzae type B conjugate vaccination have been effective tools to decrease pneumonia incidence, severity and mortality [58, 59] . However, equitable coverage and access to vaccines remains sub-optimal. By the end of 2015, Haemophilus influenzae type B conjugate vaccination had been introduced in 73 countries, with global coverage estimated at 68%. However, inequities are still apparent among regions: in the Americas coverage is estimated at 90%, while in the Western Pacific it is only 25%. By 2015, pneumococcal conjugate vaccination had been introduced into 54 countries, with global coverage of 35% for three doses of pneumococcal conjugate vaccination for infant populations [60] . To address this issue, the WHO's Global Vaccine Access Plan initiative was launched to make life-saving vaccines more equitably available. In addition to securing guarantees for financing of vaccines, the program objectives include building political will in low-and middle-income countries to commit to immunization as a priority, social marketing to individuals and communities, strengthening health systems and promoting relevant local research and development innovations [61] .
Maternal vaccination to prevent disease in the youngest infants has been shown to be effective for tetanus, influenza and pertussis [62] . Influenza vaccination during pregnancy is safe, provides reasonable maternal protection against influenza, and also protects infants for a limited period from confirmed influenza infection (vaccine efficacy 63% in Bangladesh [63] and 50.4% in South Africa [64] ). However as antibody levels drop sharply after birth, infant protection does not persist much beyond 8 weeks [65] . Recently respiratory syncytial virus vaccination in pregnancy has been shown to be safe and immunogenic, and a phase-3 clinical trial of efficacy at preventing respiratory syncytial virus disease in infants is under way [66] . Within a decade, respiratory syncytial virus in infancy might be vaccine-preventable, with further decreases in pneumonia incidence, morbidity and mortality [67] .
Improved access to health care, better nutrition and improved living conditions might contribute to further decreases in childhood pneumonia burden. The WHO Integrated Global Action Plan for diarrhea and pneumonia highlights many opportunities to protect, prevent and treat children [68] . Breastfeeding rates can be improved by programs that combine education and counseling interventions in homes, communities and health facilities, and by promotion of baby-friendly hospitals [69] . Improved home ventilation, cleaner cooking fuels and reduction in exposure to cigarette smoke are essential interventions to reduce the incidence and severity of pneumonia [70, 71] . Prevention of pediatric HIV is possible by providing interventions to prevent mother-to-child transmission [72] . Early infant HIV testing and early initiation of antiretroviral therapy and cotrimoxazole prophylaxis can substantially reduce the incidence of community-acquired pneumonia among HIV-infected children [73] . Community-based interventions reduce pneumonia mortality and have the indirect effect of improved-careseeking behavior [58] . If these cost-effective interventions were scaled up, it is estimated that 67% of pneumonia deaths in lowand middle-income countries could be prevented by 2025 [58] .
Case management of pneumonia is a strategy by which severity of disease is classified as severe or non-severe. All children receive early, appropriate oral antibiotics, and severe cases are referred for parenteral antibiotics. When implemented in highburden areas before the availability of conjugate vaccines, case management as part of Integrated Management of Childhood Illness was associated with a 27% decrease in overall child mortality, and 42% decrease in pneumonia-specific mortality [74] . However the predominance of viral causes of pneumonia and low case fatality have prompted concern about overuse of antibiotics. Several randomized controlled trials comparing oral antibiotics to placebo for non-severe pneumonia have been performed [75] [76] [77] and others are ongoing [78] . In two studies, performed in Denmark and in India, outcomes of antibiotic and placebo treatments were equivalent [76, 77] . In the third study, in Pakistan, there was a non-significant 24% vs. 20% rate of failure in the placebo group, which was deemed to be non-equivalent to the antibiotic group [75] . Furthermore, because WHO-classified non-severe pneumonia and bronchiolitis might be considered within a spectrum of lower respiratory disease, many children with clinical pneumonia could actually have viral bronchiolitis, for which antibiotics are not beneficial [79] . This has been reflected in British [33] and Spanish [31] national pneumonia guidelines, which do not recommend routine antibiotic treatment for children younger than 2 years with evidence of pneumococcal conjugate vaccination who present with non-severe pneumonia. The United States' national guidelines recommend withholding antibiotics in children up to age 5 years presenting with non-severe pneumonia [32] . However, given the high mortality from pneumonia in low-and middle-income countries, the lack of easy access to care, and the high prevalence of risk factors for severe disease, revised World Health Organization pneumonia guidelines still recommend antibiotic treatment for all children who meet the WHO pneumonia case definitions [80] .
Use of supplemental oxygen is life-saving, but this is not universally available in low-and middle-income countries; it is estimated that use of supplemental oxygen systems could reduce mortality of children with hypoxic pneumonia by 20% [81] . Identifying systems capacity to increase availability of oxygen in health facilities, and identifying barriers to further implementation are among the top 15 priorities for future childhood pneumonia research [82] . However, up to 81% of pneumonia deaths in 2010 occurred outside health facilities [5] , so there are major challenges with access to health services and health-seeking behavior of vulnerable populations. Identifying and changing the barriers to accessing health care is an important area with the potential to impact the survival and health of the most vulnerable children [82] .
Much progress has been made in decreasing deaths caused by childhood pneumonia. Improved socioeconomic status and vaccinations, primarily the conjugate vaccines (against Haemophilus influenzae and pneumococcus), have led to substantial reductions in the incidence and severity of childhood pneumonia. Stronger strategies to prevent and manage HIV have reduced HIV-associated pneumonia deaths. However, despite the substantial changes in incidence, etiology and radiology globally, there remain inequities in access to care and availability of effective interventions, especially in low-and middle-income countries. Effective interventions need to be more widely available and new interventions developed for the residual burden of childhood pneumonia. | How can childhood pneumonia affect the subsequent health of a person? | false | 516 | {
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776 | It is Unlikely That Influenza Viruses Will Cause a Pandemic Again Like What Happened in 1918 and 1919
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4019839/
Song, Liting
2014-05-07
DOI:10.3389/fpubh.2014.00039
License:cc-by
Abstract: nan
Text: Influenza and influenza viruses are wellknown popular topics to medical professionals and the general public. Influenza viruses had caused a pandemic globally during 1918 and 1919, and that influenza pandemic had taken away more than 20 million people's lives in the world. However, in my opinion, it is unlikely that influenza viruses will again cause a pandemic on a level (both of the morbidity rate and the mortality rate) comparable to what happened in 1918 and 1919.
Influenza viruses very easily reassort, recombine, and point mutate in nature due to their segmented RNA genome structures, however, unlike highly pathogenic (virulent) viruses like rabies virus, Lassa fever virus, smallpox virus, eastern equine encephalitis virus, Ebola virus, Marburg virus, and human immunodeficiency virus 1 (HIV-1); most influenza viruses (wild types and mutants) are moderately pathogenic. The case fatality rates of some highly virulent viruses and related references are listed in Table 1 .
On November 11, 1918 , the fighting of World War I was stopped, and World War I was officially ended on June 28, 1919 with the signing of the Versailles Treaty. It is estimated that around 8.5-10 million soldiers lost their lives in World War I due to battle. The war also directly caused more than 6 million civilian deaths. Millions of people suffered from hunger and malnutrition during the war. Malnutrition weakened the human immune system and made a person more vulnerable to infectious diseases like tuberculosis and influenza, therefore, hunger and malnutrition were indirectly responsible for millions of deaths in the world in that period of time. For example, about 700,000 Germans died from malnutrition-related diseases in the years of 1914-1918. During the 1918-1919 influenza pandemic, between 21 and 25 million people died of influenza worldwide. Those people were killed both directly and indirectly by influenza virus infections. Many families were too poor to buy food and coal, and to afford health care expenses when their family members were ill. Influenza virus could infect all members of a family, and this could result in no one left to feed the fires, and to prepare food for the whole family, even if they had firewood, coal, and food left in their homes. Sadly, a large number of people died of influenza virus infections along with starvation, cold, and poor living conditions (8) .
In recent years, while hunger and malnutrition are not major and serious problems in some developed countries anymore, they are still very difficult to overcome in many developing countries. In these less-developed countries, there were approximately 925 million people who suffered from hunger; 125 million children were underweight; and 195 million children were stunted each year (9) . Nevertheless, in comparison to 1918 and 1919, currently, we have much better social and economic conditions and public health systems globally; and generally speaking, the majority of people in the world have better nutritional and educational statuses; better living and working conditions; therefore, better general health and immunity. Furthermore, in 1918 and 1919, physicians and nurses almost had nothing in their hands to help individuals who were infected by influenza viruses. Today, although we still do not have very effective, powerful, and practical anti-influenza drugs available, we at least have some improved, useful, and helpful anti-viral drugs like zanamivir, and effective, convenient anti-cold medicines like Tylenol or Advil. We do not have a universal vaccine to prevent all influenza virus infections, but we can make effective vaccines to a specific influenza virus strain in a short time. Actually, in the United States of America, the influenza classed mortality rate declined from 10.2/100,000 in the 1940s to 0.56/100,000 in the 1990s; and the classed mortality rates of 1957-1958 and 1968-1969 influenza pandemics were not remarkably different from the non-pandemic seasons (10) .
Because of the above reasons, we can optimistically assume that even the same strain of influenza virus, which caused pandemic in 1918 and 1919, would not be able to kill millions of people and cause a pandemic comparable to the 1918-1919 pandemic again in the future.
Additionally, a significant number of viruses can cause influenza-like syndromes, such as rhinovirus, parainfluenza virus, adenovirus, coronavirus, respiratory syncytial virus, Coxsackie B virus, echovirus, and metapneumovirus (11, 12) . Some of the above-mentioned viruses like adenovirus and mutated coronavirus could cause problems that are comparable to influenza viruses (13, 14) .
The World Health Organization (WHO) mistakenly raised the level of influenza pandemic alert from phase 5 to the highest phase 6 on June 11, 2009 (15) . However, the truth was that most cases of H1N1 influenza A virus infections were mild, the symptomatic case fatality rate was only 0.005% in New Zealand (16) ; and in New York City, the case fatality rate was 0.0094-0.0147% for persons ≥65 years old, and for those of 0-17 years old, the case fatality rate was 0.0008-0.0012% (17) . Some researchers argued that it should not have been called an influenza pandemic in the first place if the clinical severity was considered (15, (18) (19) (20) . I believe it was unwise that we had paid too much www.frontiersin.org 23) . Not surprisingly, every year there would be some influenza patients and a few of them would die from the infections, as it is almost impossible to eliminate influenza viruses from the natural environment in many years. The severity of a viral infection is determined by both of the viral virulence (pathogenicity) and the host immunity. Some researchers' opinions on H7N9 avian influenza virus were incorrect and/or inadequate. They mainly focused on influenza viruses and worried about viral mutations, viral pathogenicity, viral adaptation, and transmission. They overestimated the negative part of socio-economic factors of the present east China: overcrowded population in the epidemic region; very busy national and international transportation and travel; a large number of live poultry markets . . . but they underestimated the currently changed, developed, and improved positive part of socio-economic factors in China. The following factors might be used to explain why that H7N9 influenza A virus epidemic was limited and controlled in China, and only a few immunocompromised patients were killed by H7N9 influenza A virus. First, China has a relatively organized and effective public health system, there are four levels of (national, provincial, prefectural-level city, and county) centers for disease control and prevention all over China (24) . Second, physicians and nurses in China were prepared and knowledgeable of influenza virus infections. Third, samples from patients with suspected influenza virus infections were collected and sent to the local and national centers for disease control and prevention promptly. H7N9 influenza A viruses were isolated and identified very quickly. Thereby, they were able to diagnose, confirm, and report three cases of H7N9 influenza patients in the early stage of the epidemic (24, 25) . Fourth, health care and public health workers were protected properly. Consequently, none of the health professionals was infected by H7N9 influenza A virus in 2013. However, a surgeon died of H7N9 influenza in Shanghai, China in January of 2014 (26) . Fifth, they detected H7N9 influenza A viruses from the samples of chickens, pigeons, and the environment of live poultry markets in Shanghai (27) ; and closed the live poultry markets of the involved epidemic region quickly. Sixth, patients were isolated and treated timely in hospitals, 74% (1251/1689) of those close contacts of H7N9 influenza patients were monitored and observed. Thus, H7N9 influenza A virus could not spread to a bigger population (24) . Last but not least, we are connected to the Internet now, and it seems that our planet is much smaller today than the earlier days when we did not have the Internet, because communication and information exchange have become so fast, easy, and convenient presently. During that avian influenza epidemic, some influenza experts in the world shared/exchanged H7N9 influenza A virus information and provided professional consultations and suggestions efficiently and rapidly. All these public health routine practices and measures resulted in that H7N9 influenza epidemic being controlled and stopped in China (24) . I have to point out that the cases of diagnosed H7N9 avian influenza A virus infection might only be the tip of the iceberg. Aside from one laboratory confirmed asymptotic case of H7N9 influenza A virus infection in Beijing (22), there were probably many undetected mild or asymptotic cases of influenza A H7N9 infection. The reason is that most people usually think a common cold is a very common and normal occurrence, and they don't take flu-like illnesses seriously. In most situations, they would just stay home and take some medicines. Only those who have very severe flu-like symptoms would see doctors, and thereby be detected and diagnosed, accordingly the real case fatality rate should be much lower than the detected 32.14% (45/140, one case from Taiwan, and one case from Hong Kong) (22, 23).
Nowadays, we travel faster, and we travel more frequently and globally, and we have more complicated social activities and lifestyles, thereby increasing the chances of viral mutation; and we realize that influenza viruses are even easier to reassort, recombine, and mutate in nature than many other RNA viruses. However, we are now living in a technologically, economically, and socially much better and advanced society. I believe influenza virus infections are controllable and preventable, with the increased population health and immunity, with the WHO Global Influenza Surveillance and Response System, and with standard/routine epidemiological practices, and with new effective anti-viral agents and vaccines in production in the future. Now, I first predict that influenza viruses will unlikely again cause a pandemic on a level comparable to what happened in 1918 and 1919. Hopefully, one day we could consider a strategy to produce a universal vaccine that can prevent people from infections of all influenza virus strains, or we could produce some very effective anti-influenza virus drugs; then influenza would not be a problem anymore. We should learn lessons from the mistakes we made in the past. It is reasonable and necessary to be cautious about influenza viruses, but overreactions or catastrophic reactions should be avoided in the future. My opinion is anti-traditional; the purpose of this article is to influence public health policy, and to save some of the limited resources and money for more important diseases like heart diseases, cancer, diabetes, AIDS, hepatitises, and tuberculosis (15) .
Liting Song: conception of manuscript, drafting of manuscript, critical revision of manuscript, and final approval of manuscript.
The author would like to recognize the contributions of the reviewers and editors of this manuscript for their corrections and editing, and Dr. Emanuel Goldman for correcting errors related to grammar and syntax of the final manuscript. | What was the detected fatality rate of H7N9 Avian flu? | false | 303 | {
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2,669 | Frontiers in antiviral therapy and immunotherapy
https://doi.org/10.1002/cti2.1115
SHA: facbfdfa7189ca9ff83dc30e5d241ab22e962dbf
Authors: Heaton, Steven M
Date: 2020
DOI: 10.1002/cti2.1115
License: cc-by
Abstract: nan
Text: Globally, recent decades have witnessed a growing disjunction, a 'Valley of Death' 1,2 no less, between broadening strides in fundamental biomedical research and their incommensurate reach into the clinic. Plumbing work on research funding and development pipelines through recent changes in the structure of government funding, 2 new public and private joint ventures and specialist undergraduate and postgraduate courses now aim to incorporate pathways to translation at the earliest stages. Reflecting this shift, the number of biomedical research publications targeting 'translational' concepts has increased exponentially, up 1800% between 2003 and 2014 3 and continuing to rise rapidly up to the present day. Fuelled by the availability of new research technologies, as well as changing disease, cost and other pressing issues of our time, further growth in this exciting space will undoubtedly continue. Despite recent advances in the therapeutic control of immune function and viral infection, current therapies are often challenging to develop, expensive to deploy and readily select for resistance-conferring mutants. Shaped by the hostvirus immunological 'arms race' and tempered in the forge of deep time, the biodiversity of our world is increasingly being harnessed for new biotechnologies and therapeutics. Simultaneously, a shift towards host-oriented antiviral therapies is currently underway. In this Clinical & Translational Immunology Special Feature, I illustrate a strategic vision integrating these themes to create new, effective, economical and robust antiviral therapies and immunotherapies, with both the realities and the opportunities afforded to researchers working in our changing world squarely in mind.
Opening this CTI Special Feature, I outline ways these issues may be solved by creatively leveraging the so-called 'strengths' of viruses. Viral RNA polymerisation and reverse transcription enable resistance to treatment by conferring extraordinary genetic diversity. However, these exact processes ultimately restrict viral infectivity by strongly limiting virus genome sizes and their incorporation of new information. I coin this evolutionary dilemma the 'information economy paradox'. Many viruses attempt to resolve this by manipulating multifunctional or multitasking host cell proteins (MMHPs), thereby maximising host subversion and viral infectivity at minimal informational cost. 4 I argue this exposes an 'Achilles Heel' that may be safely targeted via host-oriented therapies to impose devastating informational and fitness barriers on escape mutant selection. Furthermore, since MMHPs are often conserved targets within and between virus families, MMHP-targeting therapies may exhibit both robust and broadspectrum antiviral efficacy. Achieving this through drug repurposing will break the vicious cycle of escalating therapeutic development costs and trivial escape mutant selection, both quickly and in multiple places. I also discuss alternative posttranslational and RNA-based antiviral approaches, designer vaccines, immunotherapy and the emerging field of neo-virology. 4 I anticipate international efforts in these areas over the coming decade will enable the tapping of useful new biological functions and processes, methods for controlling infection, and the deployment of symbiotic or subclinical viruses in new therapies and biotechnologies that are so crucially needed.
Upon infection, pathogens stimulate expression of numerous host inflammatory factors that support recruitment and activation of immune cells. On the flip side, this same process also causes immunopathology when prolonged or deregulated. 5 In their contribution to this Special Feature, Yoshinaga and Takeuchi review endogenous RNA-binding proteins (RBPs) that post-transcriptionally control expression of crucial inflammatory factors in various tissues and their potential therapeutic applications. 6 These RBPs include tristetraprolin and AUF1, which promote degradation of AU-rich element (ARE)-containing mRNA; members of the Roquin and Regnase families, which respectively promote or effect degradation of mRNAs harbouring stem-loop structures; and the increasingly apparent role of the RNA methylation machinery in controlling inflammatory mRNA stability. These activities take place in various subcellular compartments and are differentially regulated during infection. In this way, mRNA-destabilising RBPs constitute a 'brake' on the immune system, which may ultimately be toggled therapeutically. I anticipate continued efforts in this area will lead to new methods of regaining control over inflammation in autoimmunity, selectively enhancing immunity in immunotherapy, and modulating RNA synthesis and virus replication during infection.
Another mRNA under post-transcriptional regulation by Regnase-1 and Roquin is Furin, which encodes a conserved proprotein convertase crucial in human health and disease. Furin, along with other PCSK family members, is widely implicated in immune regulation, cancer and the entry, maturation or release of a broad array of evolutionarily diverse viruses including human papillomavirus (HPV), influenza (IAV), Ebola (EboV), dengue (DenV) and human immunodeficiency virus (HIV). Here, Braun and Sauter review the roles of furin in these processes, as well as the history and future of furin-targeting therapeutics. 7 They also discuss their recent work revealing how two IFN-cinducible factors exhibit broad-spectrum inhibition of IAV, measles (MV), zika (ZikV) and HIV by suppressing furin activity. 8 Over the coming decade, I expect to see an ever-finer spatiotemporal resolution of host-oriented therapies to achieve safe, effective and broad-spectrum yet costeffective therapies for clinical use.
The increasing abundance of affordable, sensitive, high-throughput genome sequencing technologies has led to a recent boom in metagenomics and the cataloguing of the microbiome of our world. The MinION nanopore sequencer is one of the latest innovations in this space, enabling direct sequencing in a miniature form factor with only minimal sample preparation and a consumer-grade laptop computer. Nakagawa and colleagues here report on their latest experiments using this system, further improving its performance for use in resource-poor contexts for meningitis diagnoses. 9 While direct sequencing of viral genomic RNA is challenging, this system was recently used to directly sequence an RNA virus genome (IAV) for the first time. 10 I anticipate further improvements in the performance of such devices over the coming decade will transform virus surveillance efforts, the importance of which was underscored by the recent EboV and novel coronavirus (nCoV / COVID-19) outbreaks, enabling rapid deployment of antiviral treatments that take resistance-conferring mutations into account.
Decades of basic immunology research have provided a near-complete picture of the main armaments in the human antiviral arsenal. Nevertheless, this focus on mammalian defences and pathologies has sidelined examination of the types and roles of viruses and antiviral defences that exist throughout our biosphere. One case in point is the CRISPR/Cas antiviral immune system of prokaryotes, which is now repurposed as a revolutionary gene-editing biotechnology in plants and animals. 11 Another is the ancient lineage of nucleocytosolic large DNA viruses (NCLDVs), which are emerging human pathogens that possess enormous genomes of up to several megabases in size encoding hundreds of proteins with unique and unknown functions. 12 Moreover, hundreds of human-and avian-infective viruses such as IAV strain H5N1 are known, but recent efforts indicate the true number may be in the millions and many harbour zoonotic potential. 13 It is increasingly clear that host-virus interactions have generated truly vast yet poorly understood and untapped biodiversity. Closing this Special Feature, Watanabe and Kawaoka elaborate on neo-virology, an emerging field engaged in cataloguing and characterising this biodiversity through a global consortium. 14 I predict these efforts will unlock a vast wealth of currently unexplored biodiversity, leading to biotechnologies and treatments that leverage the host-virus interactions developed throughout evolution.
When biomedical innovations fall into the 'Valley of Death', patients who are therefore not reached all too often fall with them. Being entrusted with the resources and expectation to conceive, deliver and communicate dividends to society is both cherished and eagerly pursued at every stage of our careers. Nevertheless, the road to research translation is winding and is built on a foundation of basic research. Supporting industry-academia collaboration and nurturing talent and skills in the Indo-Pacific region are two of the four pillars of the National Innovation and Science Agenda. 2 These frame Australia's Medical Research and Innovation Priorities, which include antimicrobial resistance, global health and health security, drug repurposing and translational research infrastructure, 15 capturing many of the key elements of this CTI Special Feature. Establishing durable international relationships that integrate diverse expertise is essential to delivering these outcomes. To this end, NHMRC has recently taken steps under the International Engagement Strategy 16 to increase cooperation with its counterparts overseas. These include the Japan Agency for Medical Research and Development (AMED), tasked with translating the biomedical research output of that country. Given the reciprocal efforts at accelerating bilateral engagement currently underway, 17 the prospects for new areas of international cooperation and mobility have never been more exciting nor urgent. With the above in mind, all contributions to this CTI Special Feature I have selected from research presented by fellow invitees to the 2018 Awaji International Forum on Infection and Immunity (AIFII) and 2017 Consortium of Biological Sciences (ConBio) conferences in Japan. Both Australia and Japan have strong traditions in immunology and related disciplines, and I predict that the quantity, quality and importance of our bilateral cooperation will accelerate rapidly over the short to medium term. By expanding and cooperatively leveraging our respective research strengths, our efforts may yet solve the many pressing disease, cost and other sustainability issues of our time. | What do RBPs include? | false | 4,143 | {
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1,607 | A Schiff Base-Derived Copper (II) Complex Is a Potent Inducer of Apoptosis in Colon Cancer Cells by Activating the Intrinsic Pathway
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3967396/
SHA: f1f24521928f5d8565a15a17bd7f79239a3d4116
Authors: Hajrezaie, Maryam; Paydar, Mohammadjavad; Zorofchian Moghadamtousi, Soheil; Hassandarvish, Pouya; Gwaram, Nura Suleiman; Zahedifard, Maryam; Rouhollahi, Elham; Karimian, Hamed; Looi, Chung Yeng; Ali, Hapipah Mohd; Abdul Majid, Nazia; Abdulla, Mahmood Ameen
Date: 2014-03-05
DOI: 10.1155/2014/540463
License: cc-by
Abstract: Metal-based drugs with extensive clinical applications hold great promise for the development of cancer chemotherapeutic agents. In the last few decades, Schiff bases and their complexes have become well known for their extensive biological potential. In the present study, we examined the antiproliferative effect of a copper (II) complex on HT-29 colon cancer cells. The Cu(BrHAP)(2 ) Schiff base compound demonstrated a potent antiproliferative effect in HT-29 cells, with an IC(50 )value of 2.87 μg/ml after 72 h of treatment. HT-29 cells treated with Cu (II) complexes underwent apoptosis death, as exhibited by a progressive elevation in the proportion of the G(1 ) cell population. At a concentration of 6.25 μg/ml, the Cu(BrHAP)(2 ) compound caused significant elevation in ROS production following perturbation of mitochondrial membrane potential and cytochrome c release, as assessed by the measurement of fluorescence intensity in stained cells. Furthermore, the activation of caspases 3/7 and 9 was part of the Cu (II) complex-induced apoptosis, which confirmed the involvement of mitochondrial-mediated apoptosis. Meanwhile, there was no significant activation of caspase-8. Taken together, these results imply that the Cu(BrHAP)(2 ) compound is a potential candidate for further in vivo and clinical colon cancer studies to develop novel chemotherapeutic agents derived from metal-based agents.
Text: Cancer is a debilitating disease that afflicts a substantial portion of the world population in all generations and is a major health problem of global concern [1] . Among the various types of cancer, colorectal cancer is the second and third most prevalent cancer among males and females in the United States, respectively. In spite of all the considerable progress in protective methods and recent improvements in screening techniques and chemotherapy, the 1-year and 5-year relative survival rates for patients suffering from colorectal cancer are 83.2% and 64.3%, respectively [2] . In addition, due to bitter controversy over optimal methods for early detection, full compliance of patients with screening recommendations remains a major hindrance for diagnosis at the early stages of cancer development. Development of resistance to chemotherapy also represents a critical issue for which simultaneous treatment with various classes of therapeutics to reduce the resistance has yielded some success [3] . Moreover, the numerous side effects of chemotherapeutic drugs on cancer patients, including hair loss, diarrhea, bleeding, and immunosuppression, have made the process 2
The Scientific World Journal of treatment more complicated [4] . The highly regulated programmed cell death process of apoptosis is a matter of great interest in oncology and cancer therapy and represents a common molecular pathway for drug resistance and carcinogenesis [5] .
Maintenance of a constant cell number in the colonic mucosa is highly regulated through the balance between apoptosis and cell proliferation. The perturbation in this balance leads to an escape from normal cell number homeostasis and is associated with the progression of cancer cells [6, 7] . Thus, suppression of proliferation and elevation of apoptosis in these aberrant cells are suggested to be the essential mechanism for the inhibition of colon cancer. Furthermore, apoptosis and the factors involved in its mechanism of action also present a window that can be exploited for the improvement of potential therapeutic agents with high effectiveness and less adverse side effects [8] . Hence, screening for novel compounds capable of inducing apoptosis in colon cancer cells that can be used alone or in combination with other chemotherapeutic drugs is a significant need and represents a critical challenge in medicinal chemistry.
Metal complexes have been extensively utilized in clinics for centuries and have attracted numerous inorganic chemists to analyze them, with the main focus being medical applications [9, 10] . Copper, an essential trace element with an oxidative nature and bioessential activity in human metabolism, does not exist in an ionic form in biological systems. Thus, measurement of copper in the body is evaluated in the form of complexes with organic compounds [11] . Schiff bases are a critical class of compounds in medical chemistry that have demonstrated significant chemotherapeutic and antibacterial application [12, 13] . Schiff base Cu(II) complexes revealed great potential for antiproliferative, antibacterial, and gastroprotective activity [14] [15] [16] [17] [18] . This study evaluated the anticancer potential of a copper (II) complex derived from N,N -dimethyl ethylene diamine and 2-hydroxyacetophenone Schiff base ligand, Cu(BrHAP) 2 . Furthermore, the possible apoptotic mechanism underlying this activity was also examined. Dulbecco's Modified Eagle Medium (DMEM, Life Technologies, Inc., Rockville, MD) containing 10% fetal bovine serum, 100 g/mL streptomycin, and 100 U/mL penicillin G at 37 ∘ C in a humidified atmosphere of 5% CO 2 /95% air. The cells were plated at a fitting density in tissue culture flasks (Corning, USA) according to each experimental scale. Cell viability was measured by a conventional MTT [3-(4,5-dimethylthiazol-2yl)-2,5-diphenyltetrazolium bromide] reduction assay. After 48 h exposure to six concentrations of Cu(BrHAP) 2 , cells were treated with MTT solution (2 mg/mL) for 2 h. The dark formazan crystals formed in intact cells were dissolved in DMSO, and the absorbance was measured at 570 nm and 650 nm as a background using a microplate reader (Hidex, Turku, Finland). The IC 50 value was determined as the concentration of Cu(BrHAP) 2 required to reduce the absorbance of treated cells to 50% of the DMSO-treated control cells. All samples were prepared in triplicates.
Assay. Measurement of lactate dehydrogenase (LDH) release is a biomarker for determining the cytotoxicity of a compound. Briefly, HT-29 cells were treated with different concentrations of Cu(BrHAP) 2 and Triton X-100 (positive control) for 48 h, and the supernatants of the untreated and treated cells were transferred to a new 96-well plate for LDH activity analysis. Next, 100 L of LDH reaction solution was added to each well, the plate was incubated at room temperature for 30 min, and the absorbance was read at 490 nm using a Tecan Infinite 200 Pro (Tecan, Männedorf, Switzerland) microplate reader. The amount of formazan salt and intensity of red color in treated and untreated samples were represented as the LDH activity of cells. The LDH release level in cells treated with Cu(BrHAP) 2 was expressed as a percentage of the positive control.
A propidium iodide (PI) and acridine orange (AO) double staining assay were carried out for detection of apoptosis in the treated cells using a fluorescent microscope (Leica attached with Q-Floro software) according to a standard procedure. HT-29 cells (5 × 10 4 cells/mL in a 25 mL culture flask) were plated, treated with Cu(BrHAP) 2 at the IC 50 concentration, and incubated for 24, 48, and 72 h. After harvesting the cells, they were stained with fluorescent dyes and observed under a UV-fluorescent microscope (Olympus BX51) within 30 min.
In brief, HT-29 cells (1 × 10 4 cells/well in 96-well plate) were supplemented with Cu(BrHAP) 2 (2 g/mL) or DMSO (negative control) for 24 h. The live cells were then incubated with BrdU and Phospho-Histone H3 dyes for 30 min. After the cells were fixed and stained as described by the manufacturer's instructions, they were visualized and analyzed using the Cellomics ArrayScan HCS reader (Thermo Scientific). The fluorescence intensities of the dyes were measured using a target activation bioapplication module.
To confirm the result of the fluorescence cell cycle analysis, HT-29 cells (5 × 10 4 cells/mL) were treated with Cu(BrHAP) 2 for 24, 48, and 72 h for flow cytometry analysis. After incubation, HT-29 cells were spun down at 1800 rpm for 5 min. Next, fixation of a cell population for flow cytometry analysis was carried out to restore integrity. In brief, the cell pellets were fixed by mixing them with 700 L of cold ethanol (90%) and were then kept at 4 ∘ C overnight. Treated HT-29 cells were spun down, and the ethanol was discarded. After washing and suspending the cells in PBS, 25 L of RNase A (10 mg/mL) and 50 L of propidium iodide (PI) (1 mg/mL) were added to the fixed cells for 1 h at 37 ∘ C. The added RNase A limited the ability of PI to bind to only DNA molecules. At the end, the DNA content of the cells was analyzed by a flow cytometer (BD FACSCanto II).
The oxygen radical antioxidant capacity (ORAC) assay was carried out based on the protocols described in detail previously [19] . In brief, Cu(BrHAP) 2 at the concentration of 100 g/mL was used for this assay in a total reaction volume of 200 L. The experiment was performed in a black 96-well microplate with 25 L of compound, blank (solvent/PBS), standard (trolox), or positive control (quercetin). The plate was then supplemented with the working fluorescein solution (150 L), followed by a 5 min incubation at 37 ∘ . The total volume of 200 L was made up by adding 25 L of AAPH working solution. Fluorescence intensity was measured at an excitation wavelength of 485 nm and an emission wavelength of 538 nm every 2 min for 2 h. The result was quantified by calculating the differences of area under the fluorescence decay curve (AUC) of samples and blank. The values were Trolox equivalents (TE).
In brief, HT-29 cells (1 × 10 4 cells/mL) were seeded in 96-well plates and treated with different concentrations of Cu(BrHAP) 2 and DMSO (negative control) for 24 h. After 30 min treatment with dihydroethidium (DHE) dye, cells were fixed and washed with wash buffer as described by the manufacturer's instructions. In the presence of superoxides, DHE dye is oxidized to ethidium. The fluorescence intensity was determined by a fluorescent plate reader at an extension wavelength of 520 nm and an emission wavelength of 620 nm.
The critical factors for monitoring the cell health, namely, cell loss, changes in cell permeability, cytochrome release, mitochondrial membrane potential changes, nuclear size, and morphological changes, were studied using a Cellomics Multiparameter Cytotoxicity 3 Kit as described in detail previously [20] . Plates with stained cells were analyzed using the ArrayScan HCS system (Cellomics, PA, USA).
Caspases 3/7, -8, and 9 activities were determined using the commercial caspase-Glo 3/7, 8, and 9 assay kit (Promega, Madison, WI). HT-29 cells (1.0 × 10 4 cells/well) were seeded overnight in white-walled 96-well plates and treated with different concentrations of Cu(BrHAP) 2 for 24 h. According to the manufacturer's protocol, the treated cells were supplemented with caspase-Glo reagent (100 L) and incubated at room temperature for 30 min. The active caspases from apoptotic cells caused the cleavage of aminoluciferin-labeled synthetic tetrapeptide, leading to the release of substrate for the luciferase enzyme. Caspase activities were analyzed using a Tecan Infinite 200 Pro (Tecan, Männedorf, Switzerland) microplate reader.
In brief, HT-29 cells (1.0 × 10 4 cells/well in a 96-well plate) were treated with different concentrations of Cu(BrHAP) 2 for 3 h, followed by stimulation with TNF-(1 ng/mL) for 30 min. After discarding the medium, cells were fixed and stained using a Cellomics nucleus factor-B (NF-B) activation kit (Thermo Scientific) according to the manufacturer's instructions. Next, an Array Scan HCS Reader was used for evaluation of the plate. Cytoplasmic and nuclear NF-B intensity ratios were calculated using Cytoplasm to Nucleus Translocation Bioapplication software. The average intensity of 200 cells/well was determined. The ratios for untreated, treated, and TNF-stimulated cells were compared.
All the experiments were performed at least three times independently. The results were presented as the mean ± standard deviation (SD) of the number of experiments shown in the legends. An analysis of variance (ANOVA) was carried out using the prism statistical package (GraphPad Software, USA). < 0.05 was considered statistically significant.
Cells of the Colon. Initially, the cytotoxicity of Cu(BrHAP) 2 was tested on HT-29 and CCD 841 cell lines. The IC 50 values of the Schiff base compound were determined based on the result collected from three independent MTT experiments. As indicated in Table 1 , Cu(BrHAP) 2 elicited a significant cytotoxicity and cell inhibitory effect after 24, 48, and 72 h of treatment on HT-29 cell. 2 -Induced LDH Release. Lactate dehydrogenase (LDH) release in the medium is a marker that shows the loss of membrane integrity, apoptosis, or necrosis. The cytotoxicity of the Cu(BrHAP) 2 compound, as determined by the LDH release assay, was quantified on HT-29 cells treated with various concentrations of the Schiff base compound for 48 h. Cu(BrHAP) 2 induced a significant elevation in LDH release, demonstrating cytotoxicity at the 6.25 and 12.5 g/mL concentrations compared to the control cells ( Figure 2 ).
Microscopy and AO/PI Double Staining. Morphological changes in HT-29 cells treated with Cu(BrHAP) 2 compound were observed under a fluorescent microscope at 24, 48, and 72 h. The cells were scored under a fluorescent microscope to analyze viable cells, early apoptosis, and late apoptosis. Early apoptosis, defined as intervening AO within the fragmented DNA, was observed under bright green fluorescence. At the same time, control cells were visualized with a green intact nuclear structure. After 24 and 48 h of treatment with Cu(BrHAP) 2 , moderate apoptosis was observed in the form of blebbing and nuclear chromatin condensation. Furthermore, in the late stage of apoptosis, changes, such as the presence of a reddish-orange color due to binding of PI to denatured DNA, were observed after 72 h of treatment ( Figure 3) . The results showed that the Cu(BrHAP) 2 compound induced morphological features of apoptosis in a time-dependent manner. Figure 4 , demonstrated that there is no cell cycle arrest in the S/M phases. The lack of cell cycle arrest in the S/M phases suggested possible cell cycle arrest in the G 1 /G 2 phases. To determine the exact arrested phase, treated HT-29 cells were analyzed for cell cycle progression using flow cytometry. As expected, there was no significant arrest in the S/M phases. Meanwhile, significant cell cycle arrest in the G 1 phase was observed for HT-29 cells after 24 and 48 h of treatment ( Figure 5 ).
Assay. Antioxidant capacity was measured by ORAC assay, which is the only assay that involves the use of peroxyl radical as a prooxidant and quantifies activity via the area under the curve (AUC) technique. In our experiment, quercetin was used as a positive control. The result demonstrated that Cu(BrHAP) 2 exhibited low to moderate antioxidant activity compared to quercetin ( Table 2) .
Formation. HT-29 cells were treated with different concentrations of Cu(BrHAP) 2 for 24 h and stained with DHE dye to determine the influence of the Schiff base compound on ROS production. The fluorescence intensities of DHE oxidization by ROS were quantified using a fluorescence microplate reader. As depicted in Figure 6 , exposure to the Schiff base compound caused a significant elevation in the ROS levels of treated HT-29 cells at the 6.25 g/mL concentration.
To investigate the induction of apoptosis by Cu(BrHAP) 2 , nuclear morphological changes in HT-29 cells were analyzed by detection of nuclear condensation. As shown in Figure 7 , Hoechst 33342 staining demonstrated that nuclear condensation, which is directly related to apoptotic chromatin changes, emerged in some cells after treatment with Cu(BrHAP) 2 . Meanwhile, the permeability of treated cells was also elevated. Mitochondria are the main source for the production of ROS and adenosine triphosphate (ATP) and are critical in controlling the death and survival of cells. The reduction in fluorescence intensity depicted in Figure 6 Cu(BrHAP) 2 triggered the translocation of cytochrome from mitochondria into the cytosol during apoptosis in HT-29 cells.
Activation. The elevation in ROS production associated with a collapse in MMP may lead to the activation of the caspase cascade. To investigate caspase activation, the bioluminescent intensities representing caspases 3/7, 8, and 9 activities were quantified in HT-29 cells treated with different concentrations of Cu(BrHAP) 2 for 24 h. As shown in Figure 8 , significant elevation in the activity of caspase-3/7 at the 6.25 g/mL concentration and caspase-9 at the 6.25 and 12.5 g/mL concentrations was observed in Cu(BrHAP) 2treated cells, while no significant change in the activity of caspase-8 was detected between treated and untreated HT-29 cells. Thus, the apoptosis induced by the Schiff base compound in HT-29 cells is possibly mediated via the intrinsic pathway, but not the extrinsic pathway.
is a transcription factor that has a critical role in cytokine gene expression. NF-B activation and translocation to the nucleus to enable DNA-binding activity and facilitate target gene expression are mediated by inflammatory cytokines such as tumor necrosis factor-(TNF-). The Cu(BrHAP) 2 Schiff base compound did not exhibit any inhibitory effect on translocation of TNF--stimulated NF-B in HT-29 treated cells, and TNF--stimulation led to NF-B translocation from the cytoplasm to the nucleus (Figure 9 ).
Carcinogenesis is a multistage process in which unregulated cell proliferation as well as a reduction in apoptosis incidence serves as initial characterizations for its progression [21] . One of the defense procedures in multicellular organisms is the destruction of undesirable cell development, which is defined as programmed cell death. Apoptosis is the most noticed programmed cell death mechanism and is characterized by distinct morphological changes such as membrane permeability, cell shrinkage, disruption of the mitochondrial membrane, and chromatin condensation [22, 23]. The disruption of cellular homeostasis between cell death and cell proliferation leads to cancer incidence [24] , and agents that can induce apoptosis are known to have potential anticancer effects [25, 26] . Apoptosis pathways are effective targets for cancer therapy as well as chemoprevention. Numerous chemopreventive drugs have been determined to regulate key events or molecules in apoptosis-inducing signal transduction pathways [27] . In the present study, the Cu(BrHAP) 2 Schiff base compound was evaluated for its ability to inhibit the growth of HT-29 cells using an MTT assay. HT-29 cells have recently been characterized as a suitable model for colon cancer studies [28] [29] [30] . human colon cancer cells in a time-and dose-dependent manner. Meanwhile, the nontumorigenic colon cell line (CCD 841) showed no cytotoxicity after treatment with the compound. The cytotoxic effect of the Cu(II) compound was also confirmed by measuring the level of LDH release from treated cells. Considerably elevated LDH release showed that the cytotoxicity of the Cu(BrHAP) 2 compound possibly occurred via the loss of membrane integrity, whether through activation of apoptosis or the necrosis pathway [31] . The observation of early apoptosis and late apoptosis by fluorescent microscopy analysis and AO/PI double staining following treatment of HT-29 cells with the compound included some signs of apoptosis, namely, cytoplasmic shrinkage, membrane blebbing, and DNA fragmentation [32, 33] . We found that the number of cells with early apoptosis features was higher at earlier stages of treatment. However, when treatment time increased to 72 h, late apoptosis or necrosis characterizations were dominant among treated HT-29 cells. Concurrent detection of late apoptosis or necrosis is scientifically possible because treated HT-29 cells undergoing apoptosis may have progressed into necrosis due to the prolonged incubation with the Schiff base compound.
To elucidate the mechanisms underlying the observed antiproliferative effect of the Cu(II) complex on cancer cells, cell cycle distribution was analyzed using BrdU and Phospho-Histone H3 staining along with flow cytometry [34] [35] [36] . BrdU dye can attach to the synthesized DNA of replicating cells during the S phase of the cell cycle, while Phospho-Histone H3 dye stains cells in different mitotic stages. The cell cycle results from the BrdU and Phospho-Histone H3 double staining assay indicated that there were no significant changes in the number of cells in the S/M phases after the exposure of HT-29 cells to the Schiff base compound. This result suggests the possibility that the cells were arrested in the G 1 or G 2 phase of the cell cycle. Thus, the flow cytometry analysis of the cell cycle was performed to determine the exact arrested phase, and the results demonstrated significant cell cycle arrest at G 1 after 24 and 48 h of treatment, suggesting proliferative suppression via induction of apoptosis [37, 38] .
Perturbation of mitochondrial membrane potential is one of the earliest intracellular events that occur following the induction of apoptosis [39] . As the main source of cellular ROS and adenosine triphosphate (ATP), mitochondria are the key regulators of mechanisms controlling the survival or death of cells. After confirming that the Cu(BrHAP) 2 Schiff base compound did not have significant antioxidant capacity in HT-29 cancer cells using the ORAC assay, the induction of ROS production in treated cells was analyzed. According to our study, after exposing the Cu(II) compound to HT-29 cells and analyzing the levels of ROS, it was demonstrated that the level of ROS in treated HT-29 cells was significantly elevated at a compound concentration of 6.25 g/mL.
In metal-induced apoptosis, the mitochondria have the crucial role in mediating apoptosis through metal-induced ROS [40] . The intrinsic or mitochondrial-dependent signaling pathway involves different factors of nonreceptor-mediated stimuli that induce intracellular signals. These signals, mainly through the p53 protein, act on the mitochondrialinitiated events. Excessive ROS production is a negative signal that can result in the failure of suppression of antiapoptotic factors, thereby triggering apoptosis. Therefore, we used mitochondrial membrane potential (MMP) fluorescent probes to examine the effect of elevated ROS production on the function of mitochondria in treated HT-29 cells. As shown in Figure 7 , changes in MMP after treatment with the Cu(BrHAP) 2 Schiff base compound leading to the membrane depolarization of the mitochondria were demonstrated by Rhodamine 123 release to the cytoplasm from the mitochondria matrix. The result implies that the induction of apoptosis by Cu(II) Schiff base complexes may be associated with the mitochondrial pathway [26, 41, 42] . One of the important signals to initiate the procedure of apoptosis is cytosolic cytochrome . The release of cytochrome into the cytosol and reduction of its levels in the mitochondria have been shown to occur as a result of changes in MMP [30] . As the result illustrated, the synthetic Schiff base compound also led to an increase in the level of cytochrome in the cytosol compared to the control.
The excessive production of ROS from mitochondria and the collapse of MMP may activate the downstream caspase molecules and consequently lead to apoptotic cell death. After the binding of cytochrome to apoptotic activating factor-1, caspase-9 is activated via apoptosome formation, which leads to active caspase-3/7, the most effective caspase with many cellular targets [43] . In the extrinsic pathway, apoptosis is mediated by death receptors. As an example, FAS ligand interacts with the FAS receptor, leading to the activation of caspase-8 [44] . Caspase-8 activation cleaves and activates downstream executioner caspases such as caspase-3/7 [45, 46] . In our study, the Cu(BrHAP) 2 schiff base compound induced significant elevation in the caspases 3/7 and 9 activities compared to the control. Meanwhile, there was no activation of caspase-8, suggesting that the apoptosis induced in HT-29 cells was mediated via the intrinsic mitochondrial pathway but not the extrinsic, death receptor-linked caspase-8 pathway.
The supporting evidence of LDH release, ROS production, MMP suppression, elevation in the level of cytochrome , and activation of caspases 3/7 and 9 demonstrated the promising anticancer activity of the Cu(BrHAP) 2 Schiff base compound against the HT-29 colon cancer cell line via the intrinsic mitochondrial pathway. | What is the 5-year survival rate for colorectal cancer patients? | false | 5,280 | {
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1,674 | Beyond phage display: non-traditional applications of the filamentous bacteriophage as a vaccine carrier, therapeutic biologic, and bioconjugation scaffold
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4523942/
SHA: f00f183d0bce0091a02349ec1eab44a76dad9bc4
Authors: Henry, Kevin A.; Arbabi-Ghahroudi, Mehdi; Scott, Jamie K.
Date: 2015-08-04
DOI: 10.3389/fmicb.2015.00755
License: cc-by
Abstract: For the past 25 years, phage display technology has been an invaluable tool for studies of protein–protein interactions. However, the inherent biological, biochemical, and biophysical properties of filamentous bacteriophage, as well as the ease of its genetic manipulation, also make it an attractive platform outside the traditional phage display canon. This review will focus on the unique properties of the filamentous bacteriophage and highlight its diverse applications in current research. Particular emphases are placed on: (i) the advantages of the phage as a vaccine carrier, including its high immunogenicity, relative antigenic simplicity and ability to activate a range of immune responses, (ii) the phage’s potential as a prophylactic and therapeutic agent for infectious and chronic diseases, (iii) the regularity of the virion major coat protein lattice, which enables a variety of bioconjugation and surface chemistry applications, particularly in nanomaterials, and (iv) the phage’s large population sizes and fast generation times, which make it an excellent model system for directed protein evolution. Despite their ubiquity in the biosphere, metagenomics work is just beginning to explore the ecology of filamentous and non-filamentous phage, and their role in the evolution of bacterial populations. Thus, the filamentous phage represents a robust, inexpensive, and versatile microorganism whose bioengineering applications continue to expand in new directions, although its limitations in some spheres impose obstacles to its widespread adoption and use.
Text: The filamentous bacteriophage (genera Inovirus and Plectrovirus) are non-enveloped, rod-shaped viruses of Escherichia coli whose long helical capsids encapsulate a single-stranded circular DNA genome. Subsequent to the independent discovery of bacteriophage by Twort (1915) and d 'Hérelle (1917) , the first filamentous phage, f1, was isolated in Loeb (1960) and later characterized as a member of a larger group of phage (Ff, including f1, M13, and fd phage) specific for the E. coli conjugative F pilus (Hofschneider and Mueller-Jensen, 1963; Marvin and Hoffmann-Berling, 1963; Zinder et al., 1963; Salivar et al., 1964) . Soon thereafter, filamentous phage were discovered that do not use F-pili for entry (If and Ike; Meynell and Lawn, 1968; Khatoon et al., 1972) , and over time the list of known filamentous phage has expanded to over 60 members (Fauquet et al., 2005) , including temperate and Gram-positivetropic species. Work by multiple groups over the past 50 years has contributed to a relatively sophisticated understanding of filamentous phage structure, biology and life cycle (reviewed in Marvin, 1998; Rakonjac et al., 2011; Rakonjac, 2012) .
In the mid-1980s, the principle of modifying the filamentous phage genome to display polypeptides as fusions to coat proteins on the virion surface was invented by Smith and colleagues (Smith, 1985; Parmley and Smith, 1988) . Based on the ideas described in Parmley and Smith (1988) , groups in California, Germany, and the UK developed phage-display platforms to create and screen libraries of peptide and folded-protein variants (Bass et al., 1990; Devlin et al., 1990; McCafferty et al., 1990; Scott and Smith, 1990; Breitling et al., 1991; Kang et al., 1991) . This technology allowed, for the first time, the ability to seamlessly connect genetic information with protein function for a large number of protein variants simultaneously, and has been widely and productively exploited in studies of proteinprotein interactions. Many excellent reviews are available on phage-display libraries and their applications (Kehoe and Kay, 2005; Bratkovic, 2010; Pande et al., 2010) . However, the phage also has a number of unique structural and biological properties that make it highly useful in areas of research that have received far less attention.
Thus, the purpose of this review is to highlight recent and current work using filamentous phage in novel and nontraditional applications. Specifically, we refer to projects that rely on the filamentous phage as a key element, but whose primary purpose is not the generation or screening of phagedisplayed libraries to obtain binding polypeptide ligands. These tend to fall into four major categories of use: (i) filamentous phage as a vaccine carrier; (ii) engineered filamentous phage as a therapeutic biologic agent in infectious and chronic diseases; (iii) filamentous phage as a scaffold for bioconjugation and surface chemistry; and (iv) filamentous phage as an engine for evolving variants of displayed proteins with novel functions. A final section is dedicated to recent developments in filamentous phage ecology and phage-host interactions. Common themes shared amongst all these applications include the unique biological, immunological, and physicochemical properties of the phage, its ability to display a variety of biomolecules in modular fashion, and its relative simplicity and ease of manipulation.
Nearly all applications of the filamentous phage depend on its ability to display polypeptides on the virion's surface as fusions to phage coat proteins ( Table 1) . The display mode determines the maximum tolerated size of the fused polypeptide, its copy number on the phage, and potentially, the structure of the displayed polypeptide. Display may be achieved by fusing DNA encoding a polypeptide of interest directly to the gene encoding a coat protein within the phage genome (type 8 display on pVIII, type 3 display on pIII, etc.), resulting in fully recombinant phage. Much more commonly, however, only one copy of the coat protein is modified in the presence of a second, wild-type copy (e.g., type 88 display if both recombinant and wild-type pVIII genes are on the phage genome, type 8+8 display if the Parmley and Smith (1988), McConnell et al. (1994) , Rondot et al. (2001) Hybrid (type 33 and 3+3 systems) Type 3+3 system <1 2 Smith and Scott (1993) , Smith and Petrenko (1997) pVI Hybrid (type 6+6 system) Yes <1 2 >25 kDa Hufton et al. (1999) pVII Fully recombinant (type 7 system) No ∼5 >25 kDa Kwasnikowski et al. (2005) Hybrid (type 7+7 system) Yes <1 2 Gao et al. (1999) pVIII Fully recombinant (landscape phage; type 8 system)
No 2700 3 ∼5-8 residues Kishchenko et al. (1994) , Petrenko et al. (1996) Hybrid (type 88 and 8+8 systems) Type 8+8 system ∼1-300 2 >50 kDa Scott and Smith (1990) , Greenwood et al. (1991) , Smith and Fernandez (2004) pIX Fully recombinant (type 9+9 * system) Yes ∼5 >25 kDa Gao et al. (2002) Hybrid (type 9+9 system) No <1 2 Gao et al. (1999) , Shi et al. (2010) , Tornetta et al. (2010) 1 Asterisks indicate non-functional copies of the coat protein are present in the genome of the helper phage used to rescue a phagemid whose coat protein has been fused to a recombinant polypeptide. 2 The copy number depends on polypeptide size; typically <1 copy per phage particle but for pVIII peptide display can be up to ∼15% of pVIII molecules in hybrid virions. 3 The total number of pVIII molecules depends on the phage genome size; one pVIII molecule is added for every 2.3 nucleotides in the viral genome. recombinant gene 8 is on a plasmid with a phage origin of replication) resulting in a hybrid virion bearing two different types of a given coat protein. Multivalent display on some coat proteins can also be enforced using helper phage bearing nonfunctional copies of the relevant coat protein gene (e.g., type 3 * +3 display). By far the most commonly used coat proteins for display are the major coat protein, pVIII, and the minor coat protein, pIII, with the major advantage of the former being higher copy number display (up to ∼15% of recombinant pVIII molecules in a hybrid virion, at least for short peptide fusions), and of the latter being the ability to display some folded proteins at an appreciable copy number (1-5 per phage particle). While pVIII display of folded proteins on hybrid phage is possible, it typically results in a copy number of much less than 1 per virion (Sidhu et al., 2000) . For the purposes of this review, we use the term "phage display" to refer to a recombinant filamentous phage displaying a single polypeptide sequence on its surface (or more rarely, bispecific display achieved via fusion of polypeptides to two different capsid proteins), and the term "phage-displayed library" to refer to a diverse pool of recombinant filamentous phage displaying an array of polypeptide variants (e.g., antibody fragments; peptides). Such libraries are typically screened by iterative cycles of panning against an immobilized protein of interest (e.g., antigen for phage-displayed antibody libraries; antibody for phage-displayed peptide libraries) followed by amplification of the bound phage in E. coli cells.
Early work with anti-phage antisera generated for species classification purposes demonstrated that the filamentous phage virion is highly immunogenic in the absence of adjuvants (Meynell and Lawn, 1968 ) and that only the major coat protein, pVIII, and the minor coat protein, pIII, are targeted by antibodies (Pratt et al., 1969; Woolford et al., 1977) . Thus, the idea of using the phage as carrier to elicit antibodies against poorly immunogenic haptens or polypeptide was a natural extension of the ability to display recombinant exogenous sequences on its surface, which was first demonstrated by de la Cruz et al. (1988) . The phage particle's low cost of production, high stability and potential for high valency display of foreign antigen (via pVIII display) also made it attractive as a vaccine carrier, especially during the early stages of development of recombinant protein technology.
Building upon existing peptide-carrier technology, the first filamentous phage-based vaccine immunogens displayed short amino acid sequences derived directly from proteins of interest as recombinant fusions to pVIII or pIII (de la Cruz et al., 1988) . As library technology was developed and refined, phage-based antigens displaying peptide ligands of monoclonal antibodies (selected from random peptide libraries using the antibody, thus simulating with varying degrees of success the antibody's folded epitope on its cognate antigen; Geysen et al., 1986; Knittelfelder et al., 2009) were also generated for immunization purposes, with the goal of eliciting anti-peptide antibodies that also recognize the native protein. Some of the pioneering work in this area used peptides derived from infectious disease antigens (or peptide ligands of antibodies against these antigens; Table 2) , including malaria and human immunodeficiency virus type 1 (HIV-1). When displayed on phage, peptides encoding the repeat regions of the malarial circumsporozoite protein and merozoite surface protein 1 were immunogenic in mice and rabbits (de la Cruz et al., 1988; Greenwood et al., 1991; Willis et al., 1993; Demangel et al., 1996) , and antibodies raised against the latter cross-reacted with the full-length protein. Various peptide determinants (or mimics thereof) of HIV-1 gp120, gp41, gag, and reverse transcriptase were immunogenic when displayed on or conjugated to phage coat proteins (Minenkova et al., 1993; di Marzo Veronese et al., 1994; De Berardinis et al., 1999; Scala et al., 1999; Chen et al., 2001; van Houten et al., 2006 van Houten et al., , 2010 , and in some cases elicited antibodies that were able to weakly neutralize lab-adapted viruses (di Marzo Veronese et al., 1994; Scala et al., 1999) . The list of animal and human infections for which phage-displayed peptide immunogens have been developed as vaccine leads continues to expand and includes bacterial, fungal, viral, and parasitic pathogens ( Table 2) . While in some cases the results of these studies have been promising, antibody epitope-based peptide vaccines are no longer an area of active research for several reasons: (i) in many cases, peptides incompletely or inadequately mimic epitopes on folded proteins (Irving et al., 2010 ; see below); (ii) antibodies against a single epitope may be of limited utility, especially for highly variable pathogens (Van Regenmortel, 2012); and (iii) for pathogens for which protective immune responses are generated efficiently during natural infection, peptide vaccines offer few advantages over recombinant subunit and live vector vaccines, which have become easier to produce over time.
More recently, peptide-displaying phage have been used in attempts to generate therapeutic antibody responses for chronic diseases, cancer, immunotherapy, and immunocontraception. Immunization with phage displaying Alzheimer's disease β-amyloid fibril peptides elicited anti-aggregating antibodies in mice and guinea pigs (Frenkel et al., 2000 (Frenkel et al., , 2003 Esposito et al., 2008; Tanaka et al., 2011) , possibly reduced amyloid plaque formation in mice (Frenkel et al., 2003; Solomon, 2005; Esposito et al., 2008) , and may have helped maintain cognitive abilities in a transgenic mouse model of Alzheimer's disease (Lavie et al., 2004) ; however, it remains unclear how such antibodies are proposed to cross the blood-brain barrier. Yip et al. (2001) found that antibodies raised in mice against an ERBB2/HER2 peptide could inhibit breast-cancer cell proliferation. Phage displaying peptide ligands of an anti-IgE antibody elicited antibodies that bound purified IgE molecules (Rudolf et al., 1998) , which may be useful in allergy immunotherapy. Several strategies for phage-based contraceptive vaccines have been proposed for control of animal populations. For example, immunization with phage displaying follicle-stimulating hormone peptides on pVIII elicited antibodies that impaired the fertility of mice and ewes (Abdennebi et al., 1999) . Phage displaying or chemically Rubinchik and Chow (2000) conjugated to sperm antigen peptides or peptide mimics (Samoylova et al., 2012a,b) and gonadotropin-releasing hormone (Samoylov et al., 2012) are also in development.
For the most part, peptides displayed on phage elicit antibodies in experimental animals ( Table 2) , although this depends on characteristics of the peptide and the method of its display: pIII fusions tend toward lower immunogenicity than pVIII fusions (Greenwood et al., 1991) possibly due to copy number differences (pIII: 1-5 copies vs. pVIII: estimated at several hundred copies; Malik et al., 1996) . In fact, the phage is at least as immunogenic as traditional carrier proteins such as bovine serum albumin (BSA) and keyhole limpet hemocyanin (KLH; Melzer et al., 2003; Su et al., 2007) , and has comparatively few endogenous B-cell epitopes to divert the antibody response from its intended target (Henry et al., 2011) . Excepting small epitopes that can be accurately represented by a contiguous short amino acid sequence, however, it has been extremely difficult to elicit antibody responses that cross-react with native protein epitopes using peptides. The overall picture is considerably bleaker than that painted by Table 2 , since in several studies either: (i) peptide ligands selected from phage-displayed libraries were classified by the authors as mimics of discontinuous epitopes if they bore no obvious sequence homology to the native protein, which is weak evidence of non-linearity, or (ii) the evidence for cross-reactivity of antibodies elicited by immunization with phage-displayed peptides with native protein was uncompelling. Irving et al. (2010) describe at least one reason for this lack of success: it seems that peptide antigens elicit a set of topologically restricted antibodies that are largely unable to recognize discontinuous or complex epitopes on larger biomolecules. While the peptide may mimic the chemistry of a given epitope on a folded protein (allowing it to crossreact with a targeted antibody), being a smaller molecule, it cannot mimic the topology of that antibody's full epitope.
Despite this, the filamentous phage remains highly useful as a carrier for peptides with relatively simple secondary structures, which may be stablilized via anchoring to the coat proteins (Henry et al., 2011) . This may be especially true of peptides with poor inherent immunogenicity, which may be increased by high-valency display and phage-associated adjuvanticity (see Immunological Mechanisms of Vaccination with Filamentous Phage below).
The filamentous phage has been used to a lesser extent as a carrier for T-cell peptide epitopes, primarily as fusion proteins with pVIII ( Table 3) . Early work, showing that immunization with phage elicited T-cell help (Kölsch et al., 1971; Willis et al., 1993) , was confirmed by several subsequent studies (De Berardinis et al., 1999; Ulivieri et al., 2008) . From the perspective of vaccination against infectious disease, De Berardinis et al. (2000) showed that a cytotoxic T-cell (CTL) epitope from HIV-1 reverse transcriptase could elicit antigen-specific CTLs in vitro and in vivo without addition of exogenous helper T-cell epitopes, presumably since these are already present in the phage coat proteins (Mascolo et al., 2007) . Similarly, efficient priming of CTLs was observed against phage-displayed T-cell epitopes from Hepatitis B virus (Wan et al., 2001) and Candida albicans (Yang et al., 2005a; Wang et al., 2006 Wang et al., , 2014d , which, together with other types of immune responses, protected mice against systemic candidiasis. Vaccination with a combination of phagedisplayed peptides elicited antigen-specific CTLs that proved effective in reducing porcine cysticercosis in a randomized controlled trial (Manoutcharian et al., 2004; Morales et al., 2008) .
While the correlates of vaccine-induced immune protection for infectious diseases, where they are known, are almost exclusively serum or mucosal antibodies (Plotkin, 2010) ,
In certain vaccine applications, the filamentous phage has been used as a carrier for larger molecules that would be immunogenic even in isolation. Initially, the major advantages to phage display of such antigens were speed, ease of purification and low cost of production (Gram et al., 1993) . E. coli F17a-G adhesin (Van Gerven et al., 2008) , hepatitis B core antigen (Bahadir et al., 2011) , and hepatitis B surface antigen (Balcioglu et al., 2014) all elicited antibody responses when displayed on pIII, although none of these studies compared the immunogenicity of the phage-displayed proteins with that of the purified protein alone. Phage displaying Schistosoma mansoni glutathione S-transferase on pIII elicited an antibody response that was both higher in titer and of different isotypes compared to immunization with the protein alone (Rao et al., 2003) . Two studies of antiidiotypic vaccines have used the phage as a carrier for antibody fragments bearing immunogenic idiotypes. Immunization with phage displaying the 1E10 idiotype scFv (mimicking a Vibrio anguillarum surface epitope) elicited antibodies that protected flounder fish from Vibrio anguillarum challenge (Xia et al., 2005) . A chemically linked phage-BCL1 tumor-specific idiotype vaccine was weakly immunogenic in mice but extended survival time in a B-cell lymphoma model (Roehnisch et al., 2013) , and was welltolerated and immunogenic in patients with multiple myeloma (Roehnisch et al., 2014) . One study of DNA vaccination with an anti-laminarin scFv found that DNA encoding a pIII-scFv fusion protein elicited stronger humoral and cell-mediated immune responses than DNA encoding the scFv alone (Cuesta et al., 2006) , suggesting that under some circumstances, endogenous phage T-cell epitopes can enhance the immunogenicity of associated proteins. Taken together, the results of these studies show that as a particulate virus-like particle, the filamentous phage likely triggers different types of immune responses than recombinant protein antigens, and provide additional T-cell help to displayed or conjugated proteins. However, the low copy number of pIII-displayed proteins, as well as potentially unwanted phage-associated adjuvanticity, can make display of recombinant proteins by phage a suboptimal vaccine choice.
Although our understanding of the immune response against the filamentous phage pales in comparison to classical model antigens such as ovalbumin, recent work has begun to shed light on the immune mechanisms activated in response to phage vaccination (Figure 1) . The phage particle is immunogenic without adjuvant in all species tested to date, including mice (Willis et al., 1993) , rats (Dente et al., 1994) , rabbits (de la Cruz et al., 1988) , guinea pigs (Frenkel et al., 2000; Kim et al., 2004) , fish (Coull et al., 1996; Xia et al., 2005) , non-human primates (Chen et al., 2001) , and humans (Roehnisch et al., 2014) . Various routes of immunization have been employed, including oral administration (Delmastro et al., 1997) as well as subcutaneous (Grabowska et al., 2000) , intraperitoneal (van Houten et al., 2006) , intramuscular (Samoylova et al., 2012a) , intravenous (Vaks and Benhar, 2011) , and intradermal injection (Roehnisch et al., 2013) ; no published study has directly compared the effect of administration route on filamentous phage immunogenicity. Antibodies are generated against only three major sites on the virion: (i) the surface-exposed N-terminal ∼12 residues of the pVIII monomer lattice (Terry et al., 1997; Kneissel et al., 1999) ; (ii) the N-terminal N1 and N2 domains of pIII (van Houten et al., 2010) ; and (iii) bacterial lipopolysaccharide (LPS) embedded in the phage coat (Henry et al., 2011) . In mice, serum antibody titers against the phage typically reach 1:10 5 -1:10 6 after 2-3 immunizations, and are maintained for at least 1 year postimmunization (Frenkel et al., 2000) . Primary antibody responses against the phage appear to be composed of a mixture of IgM and IgG2b isotypes in C57BL/6 mice, while secondary antibody responses are composed primarily of IgG1 and IgG2b isotypes, with a lesser contribution of IgG2c and IgG3 isotypes (Hashiguchi et al., 2010) . Deletion of the surface-exposed N1 and N2 domains of pIII produces a truncated form of this protein that does not elicit antibodies, but also results in a non-infective phage particle with lower overall immunogenicity (van Houten et al., 2010) .
FIGURE 1 | Types of immune responses elicited in response to immunization with filamentous bacteriophage. As a virus-like particle, the filamentous phage engages multiple arms of the immune system, beginning with cellular effectors of innate immunity (macrophages, neutrophils, and possibly natural killer cells), which are recruited to tumor sites by phage displaying tumor-targeting moieties. The phage likely
activates T-cell independent antibody responses, either via phage-associated TLR ligands or cross-linking by the pVIII lattice. After processing by antigen-presenting cells, phage-derived peptides are presented on MHC class II and cross-presented on MHC class I, resulting in activation of short-lived CTLs and an array of helper T-cell types, which help prime memory CTL and high-affinity B-cell responses.
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Although serum anti-phage antibody titers appear to be at least partially T-cell dependent (Kölsch et al., 1971; Willis et al., 1993; De Berardinis et al., 1999; van Houten et al., 2010) , many circulating pVIII-specific B cells in the blood are devoid of somatic mutation even after repeated biweekly immunizations, suggesting that under these conditions, the phage activates T-cell-independent B-cell responses in addition to highaffinity T-cell-dependent responses (Murira, 2014) . Filamentous phage particles can be processed by antigen-presenting cells and presented on MHC class II molecules (Gaubin et al., 2003; Ulivieri et al., 2008) and can activate T H 1, T H 2, and T H 17 helper T cells (Yang et al., 2005a; Wang et al., 2014d) . Anti-phage T H 2 responses were enhanced through display of CTLA-4 peptides fused to pIII (Kajihara et al., 2000) . Phage proteins can also be cross-presented on MHC class I molecules (Wan et al., 2005) and can prime two waves of CTL responses, consisting first of short-lived CTLs and later of long-lived memory CTLs that require CD4 + T-cell help (Del Pozzo et al., 2010) . The latter CTLs mediate a delayed-type hypersensitivity reaction (Fang et al., 2005; Del Pozzo et al., 2010) .
The phage particle is self-adjuvanting through multiple mechanisms. Host cell wall-derived LPS enhances the virion's immunogenicity, and its removal by polymyxin B chromatography reduces antibody titers against phage coat proteins (Grabowska et al., 2000) . The phage's singlestranded DNA genome contains CpG motifs and may also have an adjuvant effect. The antibody response against the phage is entirely dependent on MyD88 signaling and is modulated by stimulation of several Toll-like receptors (Hashiguchi et al., 2010) , indicating that innate immunity plays an important but largely uncharacterized role in the activation of anti-phage adaptive immune responses. Biodistribution studies of the phage after intravenous injection show that it is cleared from the blood within hours through the reticuloendothelial system (Molenaar et al., 2002) , particularly of the liver and spleen, where it is retained for days (Zou et al., 2004) , potentially activating marginal-zone B-cell responses. Thus, the filamentous phage is not only a highly immunogenic carrier, but by virtue of activating a range of innate and adaptive immune responses, serves as an excellent model virus-like particle antigen.
Long before the identification of filamentous phage, other types of bacteriophage were already being used for antibacterial therapy in the former Soviet Union and Eastern Europe (reviewed in Sulakvelidze et al., 2001) . The filamentous phage, with its nonlytic life cycle, has less obvious clinical uses, despite the fact that the host specificity of Inovirus and Plectrovirus includes many pathogens of medical importance, including Salmonella, E. coli, Shigella, Pseudomonas, Clostridium, and Mycoplasma species.
In an effort to enhance their bactericidal activity, genetically modified filamentous phage have been used as a "Trojan horse" to introduce various antibacterial agents into cells. M13 and Pf3 phage engineered to express either BglII restriction endonuclease (Hagens and Blasi, 2003; Hagens et al., 2004) , lambda phage S holin (Hagens and Blasi, 2003) or a lethal catabolite gene activator protein (Moradpour et al., 2009) effectively killed E. coli and Pseudomonas aeruginosa cells, respectively, with no concomitant release of LPS (Hagens and Blasi, 2003; Hagens et al., 2004) . Unfortunately, the rapid emergence of resistant bacteria with modified F pili represents a major and possibly insurmountable obstacle to this approach. However, there are some indications that filamentous phage can exert useful but more subtle effects upon their bacterial hosts that may not result in the development of resistance to infection. Several studies have reported increased antibiotic sensitivity in bacterial populations simultaneously infected with either wild type filamentous phage (Hagens et al., 2006) or phage engineered to repress the cellular SOS response (Lu and Collins, 2009) . Filamentous phage f1 infection inhibited early stage, but not mature, biofilm formation in E. coli (May et al., 2011) . Thus, unmodified filamentous phage may be of future interest as elements of combination therapeutics against certain drug-resistant infections.
More advanced therapeutic applications of the filamentous phage emerge when it is modified to express a targeting moiety specific for pathogenic cells and/or proteins for the treatment of infectious diseases, cancer and autoimmunity (Figure 2) . The first work in this area showed as proof-of-concept that phage encoding a GFP expression cassette and displaying a HER2specific scFv on all copies of pIII were internalized into breast tumor cells, resulting in GFP expression (Poul and Marks, 1999) . M13 or fd phage displaying either a targeting peptide or antibody fragment and tethered to chloramphenicol by a labile crosslinker were more potent inhibitors of Staphylococcus aureus growth than high-concentration free chloramphenicol (Yacoby et al., 2006; Vaks and Benhar, 2011) . M13 phage loaded with doxorubicin and displaying a targeting peptide on pIII specifically killed prostate cancer cells in vitro (Ghosh et al., 2012a) . Tumorspecific peptide:pVIII fusion proteins selected from "landscape" phage (Romanov et al., 2001; Abbineni et al., 2010; Fagbohun et al., 2012 Fagbohun et al., , 2013 Lang et al., 2014; Wang et al., 2014a) were able to target and deliver siRNA-, paclitaxel-, and doxorubicincontaining liposomes to tumor cells (Jayanna et al., 2010a; Wang et al., 2010a Wang et al., ,b,c, 2014b Bedi et al., 2011 Bedi et al., , 2013 Bedi et al., , 2014 ; they were non-toxic and increased tumor remission rates in mouse models (Jayanna et al., 2010b; Wang et al., 2014b,c) . Using the B16-OVA tumor model, Eriksson et al. (2007) showed that phage displaying peptides and/or Fabs specific for tumor antigens delayed tumor growth and improved survival, owing in large part to activation of tumor-associated macrophages and recruitment of neutrophils to the tumor site (Eriksson et al., 2009) . Phage displaying an scFv against β-amyloid fibrils showed promise as a diagnostic (Frenkel and Solomon, 2002) and therapeutic (Solomon, 2008) reagent for Alzheimer's disease and Parkinson's disease due to the unanticipated ability of the phage to penetrate into brain tissue (Ksendzovsky et al., 2012) . Similarly, phage displaying an immunodominant peptide epitope derived from myelin oligodendrocyte glycoprotein depleted pathogenic demyelinating antibodies in brain tissue in the murine experimental autoimmune encephalomyelitis model of multiple sclerosis (Rakover et al., 2010) . The advantages of the filamentous phage in this context over traditional antibody-drug or protein-peptide conjugates are (i) its ability to carry very high amounts of drug or peptide, and (ii) its ability to access anatomical compartments that cannot generally be reached by systemic administration of a protein.
Unlike most therapeutic biologics, the filamentous phage's production in bacteria complicates its use in humans in several ways. First and foremost, crude preparations of filamentous phage typically contain very high levels of contaminating LPS, in the range of ∼10 2 -10 4 endotoxin units (EU)/mL (Boratynski et al., 2004; Branston et al., 2015) , which have the potential to cause severe adverse reactions. LPS is not completely removed by polyethylene glycol precipitation or cesium chloride density gradient centrifugation (Smith and Gingrich, 2005; Branston et al., 2015) , but its levels can be reduced dramatically using additional purification steps such as size exclusion chromatography (Boratynski et al., 2004; Zakharova et al., 2005) , polymyxin B chromatography (Grabowska et al., 2000) , and treatment with detergents such as Triton X-100 or Triton X-114 (Roehnisch et al., 2014; Branston et al., 2015) . These strategies routinely achieve endotoxin levels of <1 EU/mL as measured by the limulus amebocyte lysate (LAL) assay, well below the FDA limit for parenteral administration of 5 EU/kg body weight/dose, although concerns remain regarding the presence of residual virion-associated LPS which may be undetectable. A second and perhaps unavoidable consequence of the filamentous phage's bacterial production is inherent heterogeneity of particle size and the spectrum of host cellderived virion-associated and soluble contaminants, which may be cause for safety concerns and restrict its use to high-risk groups.
Many types of bacteriophage and engineered phage variants, including filamentous phage, have been proposed for prophylactic use ex vivo in food safety, either in the production pipeline (reviewed in Dalmasso et al., 2014) or for detection of foodborne pathogens post-production (reviewed in Schmelcher and Loessner, 2014) . Filamentous phage displaying a tetracysteine tag on pIII were used to detect E. coli cells through staining with biarsenical dye . M13 phage functionalized with metallic silver were highly bactericidal against E. coli and Staphylococcus epidermidis . Biosensors based on surface plasmon resonance (Nanduri et al., 2007) , piezoelectric transducers (Olsen et al., 2006) , linear dichroism (Pacheco-Gomez et al., 2012) , and magnetoelastic sensor technology (Lakshmanan et al., 2007; Huang et al., 2009) were devised using filamentous phage displaying scFv or conjugated to whole IgG against E. coli, Listeria monocytogenes, Salmonella typhimurium, and Bacillus anthracis with limits of detection on the order of 10 2 -10 6 bacterial cells/mL. Proof of concept has been demonstrated for use of such phage-based biosensors to detect bacterial contamination of live produce (Li et al., 2010b) and eggs (Chai et al., 2012) .
The filamentous phage particle is enclosed by a rod-like protein capsid, ∼1000 nm long and 5 nm wide, made up almost entirely of overlapping pVIII monomers, each of which lies ∼27 angstroms from its nearest neighbor and exposes two amine groups as well as at least three carboxyl groups (Henry et al., 2011) . The regularity of the phage pVIII lattice and its diversity of chemically addressable groups make it an ideal scaffold for bioconjugation (Figure 3) . The most commonly used approach is functionalization of amine groups with NHS esters (van Houten et al., 2006 (van Houten et al., , 2010 Yacoby et al., 2006) , although this can result in unwanted acylation of pIII and any displayed biomolecules. Carboxyl groups and tyrosine residues can also be functionalized using carbodiimide coupling and diazonium coupling, respectively (Li et al., 2010a) . Carrico et al. (2012) developed methods to specifically label pVIII N-termini without modification of exposed lysine residues through a two-step transamination-oxime formation reaction. Specific modification of phage coat proteins is even more easily accomplished using genetically modified phage displaying peptides (Ng et al., 2012) or enzymes (Chen et al., 2007; Hess et al., 2012) , but this can be cumbersome and is less general in application.
For more than a decade, interest in the filamentous phage as a building block for nanomaterials has been growing because of its unique physicochemical properties, with emerging applications in magnetics, optics, and electronics. It has long been known that above a certain concentration threshold, phage can form ordered crystalline suspensions (Welsh et al., 1996) . Lee et al. (2002) engineered M13 phage to display a ZnS-binding peptide on pIII and showed that, in the presence of ZnS nanoparticles, they selfassemble into highly ordered film biomaterials that can be aligned using magnetic fields. Taking advantage of the ability to display substrate-specific peptides at known locations on the phage filament Hess et al., 2012) , this pioneering FIGURE 3 | Chemically addressable groups of the filamentous bacteriophage major coat protein lattice. The filamentous phage virion is made up of ∼2,500-4,000 overlapping copies of the 50-residue major coat protein, pVIII, arranged in a shingle-type lattice. Each monomer has an array of chemically addressable groups available for bioorthogonal conjugation, including two primary amine groups (shown in red), three carboxyl groups (show in blue) and two hydroxyl groups (show in green). The 12 N-terminal residues generally exposed to the immune system for antibody binding are in bold underline. Figure adapted from structural data of Marvin, 1990 , freely available in PDB and SCOPe databases.
work became the basis for construction of two-and threedimensional nanomaterials with more advanced architectures, including semiconducting nanowires (Mao et al., 2003 (Mao et al., , 2004 , nanoparticles , and nanocomposites (Oh et al., 2012; Chen et al., 2014) . Using hybrid M13 phage displaying Co 3 O 4 -and gold-binding peptides on pVIII as a scaffold to assemble nanowires on polyelectrolyte multilayers, Nam et al. (2006) produced a thin, flexible lithium ion battery, which could be stamped onto platinum microband current collectors (Nam et al., 2008) . The electrochemical properties of such batteries were further improved through pIII-display of single-walled carbon nanotube-binding peptides (Lee et al., 2009) , offering an approach for sustainable production of nanostructured electrodes from poorly conductive starting materials. Phagebased nanomaterials have found applications in cancer imaging (Ghosh et al., 2012b; Yi et al., 2012) , photocatalytic water splitting (Nam et al., 2010a; Neltner et al., 2010) , light harvesting (Nam et al., 2010b; Chen et al., 2013) , photoresponsive technologies (Murugesan et al., 2013) , neural electrodes (Kim et al., 2014) , and piezoelectric energy generation (Murugesan et al., 2013) .
Thus, the unique physicochemical properties of the phage, in combination with modular display of peptides and proteins with known binding specificity, have spawned wholly novel materials with diverse applications. It is worth noting that the unusual biophysical properties of the filamentous phage can also be exploited in the study of structures of other macromolecules. Magnetic alignment of high-concentration filamentous phage in solution can partially order DNA, RNA, proteins, and other biomolecules for measurement of dipolar coupling interactions (Hansen et al., 1998 (Hansen et al., , 2000 Dahlke Ojennus et al., 1999) in NMR spectroscopy.
Because of their large population sizes, short generation times, small genome sizes and ease of manipulation, various filamentous and non-filamentous bacteriophages have been used as models of experimental evolution (reviewed in Husimi, 1989; Wichman and Brown, 2010; Kawecki et al., 2012; Hall et al., 2013) . The filamentous phage has additional practical uses in protein engineering and directed protein evolution, due to its unique tolerance of genetic modifications that allow biomolecules to be displayed on the virion surface. First and foremost among these applications is in vitro affinity maturation of antibody fragments displayed on pIII. Libraries of variant Fabs and single chain antibodies can be generated via random or sitedirected mutagenesis and selected on the basis of improved or altered binding, roughly mimicking the somatic evolution strategy of the immune system (Marks et al., 1992; Bradbury et al., 2011) . However, other in vitro display systems, such as yeast display, have important advantages over the filamentous phage for affinity maturation (although each display technology has complementary strengths; Koide and Koide, 2012) , and regardless of the display method, selection of "improved" variants can be slow and cumbersome. Iterative methods have been developed to combine computationally designed mutations (Lippow et al., 2007) and circumvent the screening of combinatorial libraries, but these have had limited success to date.
Recently, Esvelt et al. (2011) developed a novel strategy for directed evolution of filamentous phage-displayed proteins, called phage-assisted continuous evolution (PACE), which allows multiple rounds of evolution per day with little experimental intervention. The authors engineered M13 phage to encode an exogenous protein (the subject for directed evolution), whose functional activity triggers gene III expression from an accessory plasmid; variants of the exogenous protein arise by random mutagenesis during phage replication, the rate of which can be increased by inducible expression of error-prone DNA polymerases. By supplying limiting amounts of receptive E. coli cells to the engineered phage variants, Esvelt et al. (2011) elegantly linked phage infectivity and production of offspring with the presence of a desired protein phenotype. Carlson et al. (2014) later showed that PACE selection stringency could be modulated by providing small amounts of pIII independently of protein phenotype, and undesirable protein functions negatively selected by linking them to expression of a truncated pIII variant that impairs infectivity in a dominant negative fashion. PACE is currently limited to protein functions that can be linked in some way to the expression of a gene III reporter, such as protein-protein interaction, recombination, DNA or RNA binding, and enzymatic catalysis (Meyer and Ellington, 2011) . This approach represents a promising avenue for both basic research in molecular evolution (Dickinson et al., 2013) and synthetic biology, including antibody engineering.
Filamentous bacteriophage have been recovered from diverse environmental sources, including soil (Murugaiyan et al., 2011) , coastal fresh water (Xue et al., 2012) , alpine lakes (Hofer and Sommaruga, 2001) and deep sea bacteria (Jian et al., 2012) , but not, perhaps surprisingly, the human gut (Kim et al., 2011) . The environmental "phageome" in soil and water represent the largest source of replicating DNA on the planet, and is estimated to contain upward of 10 30 viral particles (Ashelford et al., 2003; Chibani-Chennoufi et al., 2004; Suttle, 2005) . The few studies attempting to investigate filamentous phage environmental ecology using classical environmental microbiology techniques (typically direct observation by electron microscopy) found that filamentous phage made up anywhere from 0 to 100% of all viral particles (Demuth et al., 1993; Pina et al., 1998; Hofer and Sommaruga, 2001) . There was some evidence of seasonal fluctuation of filamentous phage populations in tandem with the relative abundance of free-living heterotrophic bacteria (Hofer and Sommaruga, 2001) . Environmental metagenomics efforts are just beginning to unravel the composition of viral ecosystems. The existing data suggest that filamentous phage comprise minor constituents of viral communities in freshwater (Roux et al., 2012) and reclaimed and potable water (Rosario et al., 2009) but have much higher frequencies in wastewater and sewage (Cantalupo et al., 2011; Alhamlan et al., 2013) , with the caveat that biases inherent to the methodologies for ascertaining these data (purification of viral particles, sequencing biases) have not been not well validated. There are no data describing the population dynamics of filamentous phage and their host species in the natural environment.
At the individual virus-bacterium level, it is clear that filamentous phage can modulate host phenotype, including the virulence of important human and crop pathogens. This can occur either through direct effects of phage replication on cell growth and physiology, or, more typically, by horizontal transfer of genetic material contained within episomes and/or chromosomally integrated prophage. Temperate filamentous phage may also play a role in genome evolution (reviewed in Canchaya et al., 2003) . Perhaps the best-studied example of virulence modulation by filamentous phage is that of Vibrio cholerae, whose full virulence requires lysogenic conversion by the cholera toxin-encoding CTXφ phage (Waldor and Mekalanos, 1996) . Integration of CTXφ phage occurs at specific sites in the genome; these sequences are introduced through the combined action of another filamentous phage, fs2φ, and a satellite filamentous phage, TLC-Knφ1 (Hassan et al., 2010) . Thus, filamentous phage species interact and coevolve with each other in addition to their hosts. Infection by filamentous phage has been implicated in the virulence of Yersinia pestis (Derbise et al., 2007) , Neisseria meningitidis (Bille et al., 2005 (Bille et al., , 2008 , Vibrio parahaemolyticus (Iida et al., 2001) , E. coli 018:K1:H7 (Gonzalez et al., 2002) , Xanthomonas campestris (Kamiunten and Wakimoto, 1982) , and P. aeruginosa (Webb et al., 2004) , although in most of these cases, the specific mechanisms modulating virulence are unclear. Phage infection can both enhance or repress virulence depending on the characteristics of the phage, the host bacterium, and the environmental milieu, as is the case for the bacterial wilt pathogen Ralstonia solanacearum (Yamada, 2013) . Since infection results in downregulation of the pili used for viral entry, filamentous phage treatment has been proposed as a hypothetical means of inhibiting bacterial conjugation and horizontal gene transfer, so as to prevent the spread of antibiotic resistance genes (Lin et al., 2011) .
Finally, the filamentous phage may also play a future role in the preservation of biodiversity of other organisms in at-risk ecosystems. Engineered phage have been proposed for use in bioremediation, either displaying antibody fragments of desired specificity for filtration of toxins and environmental contaminants (Petrenko and Makowski, 1993) , or as biodegradable polymers displaying peptides selected for their ability to aggregate pollutants, such as oil sands tailings (Curtis et al., 2011 (Curtis et al., , 2013 . Engineered phage displaying peptides that specifically bind inorganic materials have also been proposed for use in more advanced and less intrusive mineral separation technologies (Curtis et al., 2009 ).
The filamentous phage represents a highly versatile organism whose uses extend far beyond traditional phage display and affinity selection of antibodies and polypeptides of desired specificity. Its high immunogenicity and ability to display a variety of surface antigens make the phage an excellent particulate vaccine carrier, although its bacterial production and preparation heterogeneity likely limits its applications in human vaccines at present, despite being apparently safe and well-tolerated in animals and people. Unanticipated characteristics of the phage particle, such as crossing of the blood-brain barrier and formation of highly ordered liquid crystalline phases, have opened up entirely new avenues of research in therapeutics for chronic disease and the design of nanomaterials. Our comparatively detailed understanding of the interactions of model filamentous phage with their bacterial hosts has allowed researchers to harness the phage life cycle to direct protein evolution in the lab. Hopefully, deeper knowledge of phage-host interactions at an ecological level may produce novel strategies to control bacterial pathogenesis. While novel applications of the filamentous phage continue to be developed, the phage is likely to retain its position as a workhorse for therapeutic antibody discovery for many years to come, even with the advent of competing technologies.
KH and JS conceived and wrote the manuscript. MA-G read the manuscript and commented on the text. | What trials have been done to demonstrate the potential of phage in applications for nanomaterials? | false | 1,764 | {
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2,440 | Optimization Method for Forecasting Confirmed Cases of COVID-19 in China
https://doi.org/10.3390/jcm9030674
SHA: 1d7f8850c5244fdc9b387038e7eeae9bcbbde6d2
Authors: Al-Qaness, Mohammed A. A.; Ewees, Ahmed A.; Fan, Hong; Abd El Aziz, Mohamed
Date: 2020
DOI: 10.3390/jcm9030674
License: cc-by
Abstract: In December 2019, a novel coronavirus, called COVID-19, was discovered in Wuhan, China, and has spread to different cities in China as well as to 24 other countries. The number of confirmed cases is increasing daily and reached 34,598 on 8 February 2020. In the current study, we present a new forecasting model to estimate and forecast the number of confirmed cases of COVID-19 in the upcoming ten days based on the previously confirmed cases recorded in China. The proposed model is an improved adaptive neuro-fuzzy inference system (ANFIS) using an enhanced flower pollination algorithm (FPA) by using the salp swarm algorithm (SSA). In general, SSA is employed to improve FPA to avoid its drawbacks (i.e., getting trapped at the local optima). The main idea of the proposed model, called FPASSA-ANFIS, is to improve the performance of ANFIS by determining the parameters of ANFIS using FPASSA. The FPASSA-ANFIS model is evaluated using the World Health Organization (WHO) official data of the outbreak of the COVID-19 to forecast the confirmed cases of the upcoming ten days. More so, the FPASSA-ANFIS model is compared to several existing models, and it showed better performance in terms of Mean Absolute Percentage Error (MAPE), Root Mean Squared Relative Error (RMSRE), Root Mean Squared Relative Error (RMSRE), coefficient of determination ( R 2 ), and computing time. Furthermore, we tested the proposed model using two different datasets of weekly influenza confirmed cases in two countries, namely the USA and China. The outcomes also showed good performances.
Text: A large family of viruses, called coronaviruses, are severe pathogens for human beings, which infect respiratory, hepatic, gastrointestinal, and neurologic diseases. They are distributed among humans, birds, livestock, mice, bats, and other wild animals [1] [2] [3] . The outbreaks of two previous coronaviruses, SARS-CoV and MERS-CoV in 2003 and 2012, respectively, have approved the transmission from animal to animal, and human to human [4] . In December 2019, the World Health Organization (WHO) received notifications from China for many cases of respiratory illness that were linked to some people who had visited a seafood market in Wuhan [5] . Currently, Wuhan city suffers from the spreading of a novel coronavirus, called COVID-19 (previously, it was called 2019-nCoV). In [6] , the authors concluded that COVID-19 likely originated in bats, because it is more similar to two bat-derived coronavirus strains. However, the source of the COVID-19 is not confirmed yet, and it communities, Hong Kong and Toronto, were 1.2 and 1.32, respectively. Ong et al. [20] proposed a monitoring and forecasting model for influenza A (H1N1-2009). Furthermore, Nah et al. [21] proposed a probability-based model to predict the spread of the MERS.
The Adaptive Neuro-Fuzzy Inference System (ANFIS) [22] is widely applied in time series prediction and forecasting problems, and it showed good performance in many existing applications. It offers flexibility in determining nonlinearity in the time series data, as well as combining the properties of both artificial neural networks (ANN) and fuzzy logic systems. It has been applied in various forecasting applications, for example, in [23] , a stock price forecasting model was proposed using ANFIS and empirical mode decomposition. Chen et al. [24] proposed a TAIEX time series forecasting model based on a hybrid of ANFIS and ordered weighted averaging (OWA). In [25] , another time series forecasting method was presented for electricity prices based on ANFIS. Svalina et al. [26] proposed an ANFIS based forecasting model for close price indices for a stock market for five days. Ekici and Aksoy [27] presented an ANFIS based building energy consumption forecasting model. More so, ANFIS is also applied to forecast electricity loads [28] . Kumar et al. [29] proposed an ANFIS based model to forecast return products. Ho and Tsai [30] applied ANFIS to forecast product development performance. However, estimating ANFIS parameters is a challenge that needs to be improved. Therefore, in previous studies, some individual swarm intelligence (SI) methods have been applied to the ANFIS parameters to enhance time series forecasting because these parameters have a significant effect on the performance of ANFIS. The SI methods include the particle swarm optimization (PSO) [31, 32] , social-spider optimization [33] , sine-cosine algorithm (SCA) [34] , and multi-verse optimizer (MVO) [35] . For example, in [34] SCA algorithm was applied to improve the ANFIS model to forecast oil consumption in three countries, namely, Canada, Germany, and Japan. In the same context, in [35] , The MVO algorithm was used to enhance the ANFIS model to forecast oil consumption in two countries. In addition, in [36] the PSO was used with ANFIS to predict biochar yield. However, individual SI algorithms may stock at local optima. Therefore, one solution is to apply hybrid SI algorithms to avoid this problem. In [37] , a hybrid of two SI algorithms, namely GA and SSA, was presented to improve the ANFIS model. The proposed new model called GA-SSA-ANFIS was applied to forecast crude oil prices for long-term time series data. However, the previously mentioned methods suffer from some limitations that can affect the performance of the forecasting output such as slow convergence and the ability to balance between exploration and exploitation phases can influence the quality of the final output. This motivated us to propose an alternative forecasting method dependent on the hybridization concept. This concept avoids the limitations of traditional SI techniques by combining the strengths of different techniques, and this produces new SI techniques that are better than traditional ones.
In the current study, we propose an improved ANFIS model based on a modified flower pollination algorithm (FPA) using the salp swarm algorithm (SSA). The FPA is an optimization algorithm proposed by Yang [38] , which was inspired by the flow pollination process of the flowering plants. The FPA was employed in various optimization applications, for example to estimate solar PV parameter [39, 40] , solving sudoku puzzles [41] , feature selection [42] , antenna design [43] , and other applications [44] [45] [46] [47] . Moreover, SSA is also an optimization algorithm proposed by Mirjalili et al. [48] inspired by the behavior of salp chains. In recent years, the SSA was utilized to solve different optimization problems, such as feature selection [49, 50] , data classification [51] , image segmentation [52] , and others [53, 54] .
The proposed method called FPASSA is a hybrid of FPA and SSA, in which the SSA is applied as a local search method for FPA. The proposed FPASSA starts by receiving the historical COVID-19 dataset. Then a set of solutions is generated where each of them represents the value for the parameters of the ANFIS model. Then the quality of each solution is calculated using the fitness value, and the solution that has the best fitness value is chosen to represent the best solution. Then the probability of each solution is computed. Then the current solution will be updated, either using global or local strategy in FPA. However, in the case of local strategy, the operators of SSA or FPA will be used according to the probability of the fitness value for each solution. The process of updating the solutions is repeated until reaching the stop condition, and the best parameter configurations are used to forecast the number of confirmed cases of COVID-19.
The main contribution points of the current study are as follows:
1.
We propose an efficient forecasting model to forecast the confirmed cases of the COVID-19 in China for the upcoming ten days based on previously confirmed cases.
An improved ANFIS model is proposed using a modified FPA algorithm, using SSA.
We compare the proposed model with the original ANFIS and existing modified ANFIS models, such as PSO, GA, ABC, and FPA.
The rest of this study is organized as follows. The preliminaries of ANFIS, FPA, and SSA are described in Section 2. Section 3 presents the proposed FPASSA, and Section 4 presents the experimental setup and results. We conclude this study in Section 5.
The principles of the ANFIS are given in this section. The ANFIS model links the fuzzy logic and neural networks [22] . It generates a mapping between the input and output by applying IF-THEN rules (it is also called Takagi-Sugeno inference model). Figure 1 illustrates the ANFIS model where, y and x define the inputs to Layer 1 whereas, O 1i is its output of node i that is computed as follows:
where µ denotes the generalized Gaussian membership functions. A i and B i define the membership values of µ. α i and ρ i denote the premise parameters set. The output of Layer 2 (it is also known as the firing strength of a rule) is calculated as follows:
Meanwhile, the output of Layer 3 (it is also known as the normalized firing strength) is calculated as follows:
The output of Layer 4 (it is also known as an adaptive node) is calculated as follows:
where r i , q i , and p i define the consequent parameters of the node i. Layer 5 contains only one node; its output is computed as:
Flower Pollination Algorithm is an optimization method proposed by Yang [38] . It simulates the transfer of flowers' pollen by pollinators in nature. This algorithm utilizes the two types of pollination (i.e., self-pollination and cross-pollination). In self-pollination, the pollination occurs with no pollinators, whereas, in cross-pollination, the pollens are moved between different plants. In more detail, the self-pollination can be represented as a local pollination while the cross-pollination can be called global pollination.
The global pollination or cross-pollination can be mathematically formed as follows:
where x t i defines the pollen i at iteration t. L denotes the pollination's strength or the step size. F * is the target position or best solution. In some cases, insects can fly with different distance steps for a long space; therefore, Levy fly distribution is applied to simulate this movement.
where λ = 1.5. Γ(λ) denotes the gamma function. This distribution is available for large steps s > 0. The self-pollination or local pollination can be mathematically formed as follows:
where x t i and x k i represent pollens from different flower in the same plant. in the range [0,1] The process of pollination can be done using cross-pollination or self-pollination. Therefore, the random variable p, in the range [0, 1], is used to determine this process.
SSA is an optimization technique introduced by [48] . It simulates the Salps' behavior in nature. This behavior is called salp chain. The mathematical model of SSA begins by splinting its population into a leader group and followers group. The leader is the front salp, whereas, the followers are the other salps. The search space is determined in n-dimensions with n variables. Equation (10) works to update the salps' positions.
where x 1 j denotes the leader's position in j-th dimension. F j is the target position. ub j and lb j represent the max and min bounds, respectively. c 2 and c 3 denote random numbers in [0, 1]. c 1 is an important parameter; it balances between the exploration and exploitation phases. It is computed as follows:
where the current loop number is t and the max loop' number is t max . Then, the followers' position is updated as follows:
where x i j defines the i-th position of the follower in j-th dimension. i > 1.
This section explains the proposed FPASSA-ANFIS method. It is a time series method for forecasting the confirmed cases of the COVID-19, as given in Figure 2 . The FPASSA-ANFIS utilizes the improved FPA to train the ANFIS model by optimizing its parameters. The FPASSA-ANFIS contains five layers as the classic ANFIS model. Layer 1 contains the input variables (the historical COVID-19 confirmed cases). Whereas Layer 5 produces the forecasted values. In the learning phase, the FPASSA is used to select the best weights between Layer 4 and Layer 5.
The FPASSA-ANFIS starts by formatting the input data in a time series form. In our case, the autocorrelation function (ACF) was considered. ACF is one of the methods applied to find patterns in the data; it presents information about the correlation between points separated by various time lags. Therefore, in this paper, the variables with ACF greater than 0.2 are considered i.e., 5-lags.
Besides, the training data contains 75% of the dataset, whereas the testing data contains 25% of them. The number of clusters is defined by the fuzzy c-mean (FCM) method to construct the ANFIS model.
The parameters of the ANFIS model are prepared by the FPASSA algorithm. In the training phase, the calculation error (as in Equation (13)) between the real data and the predicted data is used to evaluate the parameters' quality.
where T is the real data, and P is the predicted data. N s is the sample length. The smaller values of the objective function indicate good ANFIS's parameter.
On the other hand, the updating phase of the followers' positions in the SSA algorithm is applied to improve the global pollination phase in the FPA algorithm. In this improvement, there is a random variable (r) used to switch between both phases. If r > 0.5, then the operators of the SSA is used; otherwise, the operators of the FPA are used. In general, The FPASSA starts by constructing the population (X); afterward, the objective function is calculated for each solution. The solution with the lowest error value is saved to the next iteration. This sequence is repeated until meeting the stop condition, which in this paper, is the maximum number of iterations. Then the best solution is passed to train the parameters of the ANFIS model.
After finishing the training phase, the testing phase is started with the best solution to compute the final output. The performance of the proposed method is evaluated by comparing the real data with the predicted data using the performance measures. Finally, the FPASSA produces a foretasted value for confirmed cases of COVID-19 in China in the next day. The steps of the proposed FPASSA are presented in Algorithm 1.
Input: Historical COVID-19 dataset, size of population N, total number of iterations t max .
Divide the data into training and testing sets.
Using Fuzzy c-mean method to determine the number of membership functions.
Constructing the ANFIS network.
Set the initial value for N solutions (X). Return the best solution that represents the best configuration for ANFIS.
Apply the testing set to the best ANFIS model.
Forecasting the COVID-19 for the next ten days.
This section presents the description of the used dataset, the performance measures, the parameter setting for all methods, the experiment results, and discussions.
The main dataset of this study is COVID-19 dataset. It was collected from the WHO website (https: //www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports/). It contains the daily confirmed cases in China from 21 January 2020 to 18 February 2020, as shown in Table 1 . We used 75% from the dataset to train the model while the rest is used to test it.
Moreover, we evaluated the performance of the proposed method using two datasets of weekly influenza confirmed cases. The first one is called DS1; it was collected from the Centers for Disease Control and Prevention (CDC) (https://www.cdc.gov/flu/weekly/). It starts from week number 40 in 2015 and continues until week number 6 in 2020. Whereas, the second one is called DS2. It was collected from the WHO website (https://www.who.int/influenza). It contains the data of weekly influenza confirmed cases in China from week number 1 in 2016 to week number 8 in 2020.
The quality of the proposed method is evaluated using a set of performance metrics as follows:
• Root Mean Square Error (RMSE):
where Yp and Y are the predicted and original values, respectively. • Mean Absolute Error (MAE):
• Mean Absolute Percentage Error (MAPE):
• Root Mean Squared Relative Error (RMSRE):
N s represents the sample size of the data. • Coefficient of Determination (R 2 ):
where Y represents the average of Y.
The lowest value of RMSE, MAE, MAPE, and RMSRE refers to the best method. The higher value of R 2 indicates better correlation for the method.
This paper aims to assess the ability of the FPASSA to forecast the COVID-19 by comparing its performance with other methods, namely the ANFIS and the trained ANFIS models using PSO, GA, ABC, FPA, and FPASSA. The parameters' setting for these models is listed in Table 2 .
The common parameters, such as population size, are set to 25 and 100 iterations are applied. Besides, each algorithm is performed for 30 independent runs to fair comparisons. The selected parameters are chosen because they produced good behavior in previous experiments, such as [34, 35, 55, 56] . Table 2 . Parameters' setting.
Parameters Setting
Max. epochs = 100, Error goal = 0, Initial step = 0.01, Decrease rate = 0.9, Increase rate = 1.
In this section, the performance of the proposed FPASSA to predict the DS1 and DS2 is discussed. It can be concluded from Table 3 that the performance of FPASSA outperformed the compared methods in all measures, whereas the FPA is ranked second. The results of DS2 indicate that the FPASSA is ranked first in terms of RMSE, MAPE, R 2 , and the CPU time. Whereas, the PSO is ranked second, followed by the FPA, GA, then ABC. These results denote that the proposed method can optimize the parameters of the ANFIS model effectively and produce good results in terms of the performance measures. Comparison results between the proposed FPASSA and other models to forecast COVID-19 are given in Table 4 . It can be concluded that the FPASSA outperforms other models. For example, by analyzing the results of RMSE, MAE, MAPE, RMSRE, and CPU time(s) it can be observed that the FPASSA achieves the smallest value among the comparison algorithms, and this indicates the high quality of the FPASSA. Meanwhile, the FPA allocates the second rank, which provides better results than the rest of the methods.
Moreover, the value of R 2 refers to the high correlation between the prediction obtained by the proposed FPASSA method and the original COVID-19, which has nearly 0.97. This can also be noticed from Figure 3 , which depicts the training of the algorithms using the historical data of the COVID-19 as well as their forecasting values for ten days. Table 5 depicts the forecasting value for the confirmed cases of the COVID-19 in China from 19/2/2020 to 28/2/2020. From these results, it can be noticed that the outbreak will reach its highest level on the day 28/2/2020. The average percentage of the increase over the forecasted period is 10%, the highest percentage is 12% on 28/2/2020, and the lowest percentage is 8.7% on 19/2/2020. From the previous results, it can be concluded that the proposed FPASSA-ANFIS has a high ability to forecast the COVID-19 dataset. These results avoid the limitations of traditional ANFIS because of the combination with the modified FPA method. Moreover, the operators of SSA are combined with the local strategy of FPA to enhance their exploitation ability. However, the time computational of the proposed FPASSA method still requires more improvements.
This paper proposed a modified version for the flower pollination algorithm (FPA) using the salp swarm algorithm (SSA). This modified version, called FPASSA, is applied to improve the performance of the ANFIS through determining the optimal value for its parameters. The developed FPASSA-ANFIS model is applied as a forecasting technique for a novel coronavirus, called COVID-19, that was discovered in Wuhan, China at the end of last year and January of the current year. The proposed FPASSA-ANFIS model has a high ability to predict the number of confirmed cases within ten days. Besides, FPASSA-ANFIS outperforms other forecasting models in terms of RMSE, MAE, MAPE, RMSRE, and R 2 . Furthermore, two datasets of weekly influenza confirmed cases in the USA and China were used to evaluate the proposed method, and the evaluation outcomes showed its good performance. According to the promising results obtained by the proposed FPASSA-ANFIS, it can be applied in different forecasting applications. | Among whom are the coronaviruses distributed? | false | 4,405 | {
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2,486 | Potential Rapid Diagnostics, Vaccine and Therapeutics for 2019 Novel Coronavirus (2019-nCoV): A Systematic Review
https://doi.org/10.3390/jcm9030623
SHA: 9b0c87f808b1b66f2937d7a7acb524a756b6113b
Authors: Pang, Junxiong; Wang, Min Xian; Ang, Ian Yi Han; Tan, Sharon Hui Xuan; Lewis, Ruth Frances; Chen, Jacinta I. Pei; Gutierrez, Ramona A.; Gwee, Sylvia Xiao Wei; Chua, Pearleen Ee Yong; Yang, Qian; Ng, Xian Yi; Yap, Rowena K. S.; Tan, Hao Yi; Teo, Yik Ying; Tan, Chorh Chuan; Cook, Alex R.; Yap, Jason Chin-Huat; Hsu, Li Yang
Date: 2020
DOI: 10.3390/jcm9030623
License: cc-by
Abstract: Rapid diagnostics, vaccines and therapeutics are important interventions for the management of the 2019 novel coronavirus (2019-nCoV) outbreak. It is timely to systematically review the potential of these interventions, including those for Middle East respiratory syndrome-Coronavirus (MERS-CoV) and severe acute respiratory syndrome (SARS)-CoV, to guide policymakers globally on their prioritization of resources for research and development. A systematic search was carried out in three major electronic databases (PubMed, Embase and Cochrane Library) to identify published studies in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Supplementary strategies through Google Search and personal communications were used. A total of 27 studies fulfilled the criteria for review. Several laboratory protocols for confirmation of suspected 2019-nCoV cases using real-time reverse transcription polymerase chain reaction (RT-PCR) have been published. A commercial RT-PCR kit developed by the Beijing Genomic Institute is currently widely used in China and likely in Asia. However, serological assays as well as point-of-care testing kits have not been developed but are likely in the near future. Several vaccine candidates are in the pipeline. The likely earliest Phase 1 vaccine trial is a synthetic DNA-based candidate. A number of novel compounds as well as therapeutics licensed for other conditions appear to have in vitro efficacy against the 2019-nCoV. Some are being tested in clinical trials against MERS-CoV and SARS-CoV, while others have been listed for clinical trials against 2019-nCoV. However, there are currently no effective specific antivirals or drug combinations supported by high-level evidence.
Text: Since mid-December 2019 and as of early February 2020, the 2019 novel coronavirus (2019-nCoV) originating from Wuhan (Hubei Province, China) has infected over 25,000 laboratory-confirmed cases across 28 countries with about 500 deaths (a case-fatality rate of about 2%). More than 90% of the cases and deaths were in China [1] . Based on the initial reported surge of cases in Wuhan, the majority were males with a median age of 55 years and linked to the Huanan Seafood Wholesale Market [2] . Most of the reported cases had similar symptoms at the onset of illness such as fever, cough, and myalgia or fatigue. Most cases developed pneumonia and some severe and even fatal respiratory diseases such as acute respiratory distress syndrome [3] .
The 2019 novel coronavirus (2019-nCoV), a betacoronavirus, forms a clade within the subgenus sarbecovirus of the Orthocoronavirinae subfamily [4] . The severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) are also betacoronaviruses that are zoonotic in origin and have been linked to potential fatal illness during the outbreaks in 2003 and 2012, respectively [5, 6] . Based on current evidence, pathogenicity for 2019-nCoV is about 3%, which is significantly lower than SARS-CoV (10%) and MERS-CoV (40%) [7] . However, 2019-nCoV has potentially higher transmissibility (R0: 1.4-5.5) than both SARS-CoV (R0: [2] [3] [4] [5] and MERS-CoV (R0: <1) [7] .
With the possible expansion of 2019-nCoV globally [8] and the declaration of the 2019-nCoV outbreak as a Public Health Emergency of International Concern by the World Health Organization, there is an urgent need for rapid diagnostics, vaccines and therapeutics to detect, prevent and contain 2019-nCoV promptly. There is however currently a lack of understanding of what is available in the early phase of 2019-nCoV outbreak. The systematic review describes and assesses the potential rapid diagnostics, vaccines and therapeutics for 2019-nCoV, based in part on the developments for MERS-CoV and SARS-CoV.
A systematic search was carried out in three major electronic databases (PubMed, Embase and Cochrane Library) to identify published studies examining the diagnosis, therapeutic drugs and vaccines for Severe Acute Respiratory Syndrome (SARS), Middle East Respiratory Syndrome (MERS) and the 2019 novel coronavirus (2019-nCoV), in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.
There were two independent reviewers each focusing on SARS, MERS, and 2019-nCoV, respectively. A third independent reviewer was engaged to resolve any conflicting article of interest. We used the key words "SARS", "coronavirus", "MERS", "2019 Novel coronavirus", "Wuhan virus" to identify the diseases in the search strategy. The systematic searches for diagnosis, therapeutic drugs and vaccines were carried out independently and the key words "drug", "therapy", "vaccine", "diagnosis", "point of care testing" and "rapid diagnostic test" were used in conjunction with the disease key words for the respective searches.
Examples of search strings can be found in Table S1 . We searched for randomized controlled trials (RCTs) and validation trials (for diagnostics test) published in English, that measured (a) the sensitivity and/or specificity of a rapid diagnostic test or a point-of-care testing kit, (b) the impact of drug therapy or (c) vaccine efficacy against either of these diseases with no date restriction applied. For the 2019-nCoV, we searched for all in vitro, animal, or human studies published in English between 1 December 2019 and 6 February 2020, on the same outcomes of interest. In addition, we reviewed the references of retrieved articles in order to identify additional studies or reports not retrieved by the initial searches. Studies that examined the mechanisms of diagnostic tests, drug therapy or vaccine efficacy against SARS, MERS and 2019-nCoV were excluded. A Google search for 2019-nCoV diagnostics (as of 6 February 2020; Table S2 ) yielded five webpage links from government and international bodies with official information and guidelines (WHO, Europe CDC, US CDC, US FDA), three webpage links on diagnostic protocols and scientific commentaries, and five webpage links on market news and press releases. Six protocols for diagnostics using reverse transcriptase polymerase chain reaction (RT-PCR) from six countries were published on WHO's website [9] . Google search for 2019-nCoV vaccines yielded 19 relevant articles.
With the emergence of 2019-nCoV, real time RT-PCR remains the primary means for diagnosing the new virus strain among the many diagnostic platforms available ( [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] ; Table S3 ). Among the 16 diagnostics studies selected, one study discussed the use of RT-PCR in diagnosing patients with 2019-nCoV [11] ( Table 1 ). The period and type of specimen collected for RT-PCR play an important role in the diagnosis of 2019-nCoV. It was found that the respiratory specimens were positive for the virus while serum was negative in the early period. It has also suggested that in the early days of illness, patients have high levels of virus despite the mild symptoms.
Apart from the commonly used RT-PCR in diagnosing MERS-CoV, four studies identified various diagnostic methods such as reverse transcription loop-mediated isothermal amplification (RT-LAMP), RT-insulated isothermal PCR (RT-iiPCR) and a one-step rRT-PCR assay based on specific TaqMan probes. RT-LAMP has similar sensitivity as real time RT-PCR. It is also highly specific and is used to detect MERS-CoV. It is comparable to the usual diagnostic tests and is rapid, simple and convenient. Likewise, RT-iiPCR and a one-step rRT-PCR assay have also shown similar sensitivity and high specificity for MER-CoV. Lastly, one study focused on the validation of the six commercial real RT-PCR kits, with high accuracy. Although real time RT-PCR is a primary method for diagnosing MERS-CoV, high levels of PCR inhibition may hinder PCR sensitivity (Table 1) .
There are eleven studies that focus on SARS-CoV diagnostic testing (Table 1) . These papers described diagnostic methods to detect the virus with the majority of them using molecular testing for diagnosis. Comparison between the molecular test (i.e RT-PCR) and serological test (i.e., ELISA) showed that the molecular test has better sensitivity and specificity. Hence, enhancements to the current molecular test were conducted to improve the diagnosis. Studies looked at using nested PCR to include a pre-amplification step or incorporating N gene as an additional sensitive molecular marker to improve on the sensitivity (Table 1 ).
In addition, there are seven potential rapid diagnostic kits (as of 24 January 2020; Table 2 ) available on the market for 2019-nCoV. Six of these are only for research purposes. Only one kit from Beijing Genome Institute (BGI) is approved for use in the clinical setting for rapid diagnosis. Most of the kits are for RT-PCR. There were two kits (BGI, China and Veredus, Singapore) with the capability to detect multiple pathogens using sequencing and microarray technologies, respectively. The limit of detection of the enhanced realtime PCR method was 10 2 -fold higher than the standard real-time PCR assay and 10 7fold higher than conventional PCR methods In the clinical aspect, the enhanced realtime PCR method was able to detect 6 cases of SARS-CoV positive samples that were not confirmed by any other assay [25] • The real time PCR has a threshold sensitivity of 10 genome equivalents per reaction and it has a good reproducibility with the inter-assay coefficients of variation of 1.73 to 2.72%. • 13 specimens from 6 patients were positive with viral load range from 362 to 36,240,000 genome equivalents/mL. The real-time RT-PCR reaction was more sensitive than the nested PCR reaction, as the detection limit for the nested PCR reaction was about 10 3 genome equivalents in the standard cDNA control. [34] Real-time reverse-transcription PCR (rRT-PCR); RNA-dependent RNA polymerase (RdRp); open reading frame 1a (ORF1a); Loop-mediated isothermal amplification (LAMP); enzyme-linked immunosorbent assay (ELISA); immunofluorescent assay (IFA); immunochromatographic test (ICT); nasopharyngeal aspirate (NPA).
With the emergence of 2019-nCoV, there are about 15 potential vaccine candidates in the pipeline globally (Table 3 ), in which a wide range of technology (such as messenger RNA, DNA-based, nanoparticle, synthetic and modified virus-like particle) was applied. It will likely take about a year for most candidates to start phase 1 clinical trials except for those funded by Coalition for Epidemic Preparedness Innovations (CEPI). However, the kit developed by the BGI have passed emergency approval procedure of the National Medical Products Administration, and are currently used in clinical and surveillance centers of China [40] .
Of the total of 570 unique studies on 2019-nCoV, SARS CoV or MERS-CoV vaccines screened, only four were eventually included in the review. Most studies on SARS and MERS vaccines were excluded as they were performed in cell or animal models ( Figure 1 ). The four studies included in this review were Phase I clinical trials on SARS or MERS vaccines (Table 4 ) [44] [45] [46] [47] . There were no studies of any population type (cell, animal, human) on the 2019-nCoV at the point of screening. The published clinical trials were mostly done in United States except for one on the SARS vaccine done in China [44] . All vaccine candidates for SARS and MERS were reported to be safe, well-tolerated and able to trigger the relevant and appropriate immune responses in the participants. In addition, we highlight six ongoing Phase I clinical trials identified in the ClinicalTrials.gov register ( [48, 49] ); Table S4 ) [50] [51] [52] . These trials are all testing the safety and immunogenicity of their respective MERS-CoV vaccine candidates but were excluded as there are no results published yet. The trials are projected to complete in December 2020 (two studies in Russia [50, 51] ) and December 2021 (in Germany [52] ).
Existing literature search did not return any results on completed 2019-nCoV trials at the time of writing. Among 23 trials found from the systematic review (Table 5) , there are nine clinical trials registered under the clinical trials registry (ClinicalTrials.gov) for 2019-nCoV therapeutics [53] [54] [55] [56] [57] [58] [59] [60] [61] . Of which five studies on hydroxychloroquine, lopinavir plus ritonavir and arbidol, mesenchymal stem cells, traditional Chinese medicine and glucocorticoid therapy usage have commenced recruitment. The remaining four studies encompass investigation of antivirals, interferon atomization, darunavir and cobicistat, arbidol, and remdesivir usage for 2019-nCoV patients (Table 5) . Seroconversion measured by S1-ELISA occurred in 86% and 94% participants after 2 and 3 doses, respectively, and was maintained in 79% participants up to study end at week 60. Neutralising antibodies were detected in 50% participants at one or more time points during the study, but only 3% maintained neutralisation activity to end of study. T-cell responses were detected in 71% and 76% participants after 2 and 3 doses, respectively. There were no differences in immune responses between dose groups after 6 weeks and vaccine-induced humoral and cellular responses were respectively detected in 77% and 64% participants at week 60.
[47] Molecules developed by the university scientists inhibit two coronavirus enzymes and prevent its replication. The discovered drug targets are said to be more than 95% similar to enzyme targets found on the SARS virus. Researchers note that identified drugs may not be available to address the ongoing outbreak but they hope to make it accessible for future outbreaks.
[85] Besides the six completed randomized controlled trials (RCT) selected from the systematic review (Table 6) , there is only one ongoing randomized controlled trial targeted at SARS therapeutics [92] . The studies found from ClinicalTrials.gov have not been updated since 2013. While many prospective and retrospective cohort studies conducted during the epidemic centered on usage of ribavirin with lopinavir/ritonavir or ribavirin only, there has yet to be well-designed clinical trials investigating their usage. Three completed randomized controlled trials were conducted during the SARS epidemic-3 in China, 1 in Taiwan and 2 in Hong Kong [93] [94] [95] [96] [97] . The studies respectively investigated antibiotic usage involving 190 participants, combination of western and Chinese treatment vs. Chinese treatment in 123 participants, integrative Chinese and Western treatment in 49 patients, usage of a specific Chinese medicine in four participants and early use of corticosteroid in 16 participants. Another notable study was an open non-randomized study investigating ribavirin/lopinavir/ritonavir usage in 152 participants [98] . One randomized controlled trial investigating integrative western and Chinese treatment during the SARS epidemic was excluded as it was a Chinese article [94] .
There is only one ongoing randomized controlled trial targeted at MERS therapeutics [99] . It investigates the usage of Lopinavir/Ritonavir and Interferon Beta 1B. Likewise, many prospective and retrospective cohort studies conducted during the epidemic centered on usage of ribavirin with lopinavir/ritonavir/ribavirin, interferon, and convalescent plasma usage. To date, only one trial has been completed. One phase 1 clinical trial investigating the safety and tolerability of a fully human polyclonal IgG immunoglobulin (SAB-301) was found in available literature [46] . The trial conducted in the United States in 2017 demonstrated SAB-301 to be safe and well-tolerated at single doses. Another trial on MERS therapeutics was found on ClinicalTrials.gov-a phase 2/3 trial in the United States evaluating the safety, tolerability, pharmacokinetics (PK), and immunogenicity on coadministered MERS-CoV antibodies REGN3048 & REGN3051 [100].
Rapid diagnostics plays an important role in disease and outbreak management. The fast and accurate diagnosis of a specific viral infection enables prompt and accurate public health surveillance, prevention and control measures. Local transmission and clusters can be prevented or delayed by isolation of laboratory-confirmed cases and their close contacts quarantined and monitored at home. Rapid diagnostic also facilitates other specific public health interventions such as closure of high-risk facilities and areas associated with the confirmed cases for prompt infection control and environmental decontamination [11, 101] .
Laboratory diagnosis can be performed by: (a) detecting the genetic material of the virus, (b) detecting the antibodies that neutralize the viral particles of interest, (c) detecting the viral epitopes of interest with antibodies (serological testing), or (d) culture and isolation of viable virus particles.
The key limitations of genetic material detection are the lack of knowledge of the presence of viable virus, the potential cross-reactivity with non-specific genetic regions and the short timeframe for accurate detection during the acute infection phase. The key limitations of serological testing is the need to collect paired serum samples (in the acute and convalescent phases) from cases under investigation for confirmation to eliminate potential cross-reactivity from non-specific antibodies from past exposure and/or infection by other coronaviruses. The limitation of virus culture and isolation is the long duration and the highly specialized skills required of the technicians to process the samples. All patients recovered.
Significantly shorted time from the disease onset to the symptom improvement in treatment (5.10 ± 2.83 days) compared to control group (7.62 ± 2.27 days) (p < 0.05) No significant difference in blood routine improvement, pulmonary chest shadow in chest film improvement and corticosteroid usgae between the 2 groups. However, particularly in the respect of improving clinical symptoms, elevating quality of life, promoting immune function recovery, promoting absorption of pulmonary inflammation, reducing the dosage of cortisteroid and shortening the therapeutic course, treatment with integrative chinese and western medicine treatment had obvious superiority compared with using control treatment alone. Single infusions of SAB-301 up to 50 mg/kg appear to be safe and well-tolerated in healthy participants. [46] Where the biological samples are taken from also play a role in the sensitivity of these tests. For SARS-CoV and MERS-CoV, specimens collected from the lower respiratory tract such as sputum and tracheal aspirates have higher and more prolonged levels of viral RNA because of the tropism of the virus. MERS-CoV viral loads are also higher for severe cases and have longer viral shedding compared to mild cases. Although upper respiratory tract specimens such as nasopharyngeal or oropharyngeal swabs can be used, they have potentially lower viral loads and may have higher risk of false-negatives among the mild MERS and SARS cases [102, 103] , and likely among the 2019-nCoV cases.
The existing practices in detecting genetic material of coronaviruses such as SARS-CoV and MERS-CoV include (a) reverse transcription-polymerase chain reaction (RT-PCR), (b) real-time RT-PCR (rRT-PCR), (c) reverse transcription loop-mediated isothermal amplification (RT-LAMP) and (d) real-time RT-LAMP [104] . Nucleic amplification tests (NAAT) are usually preferred as in the case of MERS-CoV diagnosis as it has the highest sensitivity at the earliest time point in the acute phase of infection [102] . Chinese health authorities have recently posted the full genome of 2019-nCoV in the GenBank and in GISAID portal to facilitate in the detection of the virus [11] . Several laboratory assays have been developed to detect the novel coronavirus in Wuhan, as highlighted in WHO's interim guidance on nCoV laboratory testing of suspected cases. These include protocols from other countries such as Thailand, Japan and China [105] .
The first validated diagnostic test was designed in Germany. Corman et al. had initially designed a candidate diagnostic RT-PCR assay based on the SARS or SARS-related coronavirus as it was suggested that circulating virus was SARS-like. Upon the release of the sequence, assays were selected based on the match against 2019-nCoV upon inspection of the sequence alignment. Two assays were used for the RNA dependent RNA polymerase (RdRP) gene and E gene where E gene assay acts as the first-line screening tool and RdRp gene assay as the confirmatory testing. All assays were highly sensitive and specific in that they did not cross-react with other coronavirus and also human clinical samples that contained respiratory viruses [11] .
The Hong Kong University used two monoplex assays which were reactive with coronaviruses under the subgenus Sarbecovirus (consisting of 2019-nCoV, SARS-CoV and SARS-like coronavirus). Viral RNA extracted from SARS-CoV can be used as the positive control for the suggested protocol assuming that SARS has been eradicated. It is proposed that the N gene RT-PCR can be used as a screening assay while the Orf1b assay acts as a confirmatory test. However, this protocol has only been evaluated with a panel of controls with the only positive control SARS-CoV RNA. Synthetic oligonucleotide positive control or 2019-nCoV have yet to be tested [106] .
The US CDC shared the protocol on the real time RT-PCR assay for the detection of the 2019-nCoV with the primers and probes designed for the universal detection of SARS-like coronavirus and the specific detection of 2019-nCoV. However, the protocol has not been validated on other platforms or chemistries apart from the protocol described. There are some limitations for the assay. Analysts engaged have to be trained and familiar with the testing procedure and result interpretation. False negative results may occur due to insufficient organisms in the specimen resulting from improper collection, transportation or handling. Also, RNA viruses may show substantial genetic variability. This could result in mismatch between the primer and probes with the target sequence which can diminish the assay performance or result in false negative results [107] . Point-of-care test kit can potentially minimize these limitations, which should be highly prioritized for research and development in the next few months.
Serological testing such as ELISA, IIFT and neutralization tests are effective in determining the extent of infection, including estimating asymptomatic and attack rate. Compared to the detection of viral genome through molecular methods, serological testing detects antibodies and antigens. There would be a lag period as antibodies specifically targeting the virus would normally appear between 14 and 28 days after the illness onset [108] . Furthermore, studies suggest that low antibody titers in the second week or delayed antibody production could be associated with mortality with a high viral load. Hence, serological diagnoses are likely used when nucleic amplification tests (NAAT) are not available or accessible [102] .
Vaccines can prevent and protect against infection and disease occurrence when exposed to the specific pathogen of interest, especially in vulnerable populations who are more prone to severe outcomes. In the context of the current 2019-nCoV outbreak, vaccines will help control and reduce disease transmission by creating herd immunity in addition to protecting healthy individuals from infection. This decreases the effective R0 value of the disease. Nonetheless, there are social, clinical and economic hurdles for vaccine and vaccination programmes, including (a) the willingness of the public to undergo vaccination with a novel vaccine, (b) the side effects and severe adverse reactions of vaccination, (c) the potential difference and/or low efficacy of the vaccine in populations different from the clinical trials' populations and (d) the accessibility of the vaccines to a given population (including the cost and availability of the vaccine).
Vaccines against the 2019-nCoV are currently in development and none are in testing (at the time of writing). On 23 January 2020, the Coalition for Epidemic Preparedness Innovations (CEPI) announced that they will fund vaccine development programmes with Inovio, The University of Queensland and Moderna, Inc respectively, with the aim to test the experimental vaccines clinically in 16 weeks (By June 2020). The vaccine candidates will be developed by the DNA, recombinant and mRNA vaccine platforms from these organizations [109] .
Based on the most recent MERS-CoV outbreak, there are already a number of vaccine candidates being developed but most are still in the preclinical testing stage. The vaccines in development include viral vector-based vaccine, DNA vaccine, subunit vaccine, virus-like particles (VLPs)-based vaccine, inactivated whole-virus (IWV) vaccine and live attenuated vaccine. The latest findings for these vaccines arebased on the review by Yong et al. (2019) in August 2019 [110] . As of the date of reporting, there is only one published clinical study on the MERS-CoV vaccine by GeneOne Life Science & Inovio Pharmaceuticals [47] . There was one SARS vaccine trial conducted by the US National Institute of Allergy and Infectious Diseases. Both Phase I clinical trials reported positive results, but only one has announced plans to proceed to Phase 2 trial [111] .
Due to the close genetic relatedness of SARS-CoV (79%) with 2019-nCoV [112] , there may be potential cross-protective effect of using a safe SARS-CoV vaccine while awaiting the 2019-nCoV vaccine. However, this would require small scale phase-by-phase implementation and close monitoring of vaccinees before any large scale implementation.
Apart from the timely diagnosis of cases, the achievement of favorable clinical outcomes depends on the timely treatment administered. ACE2 has been reported to be the same cell entry receptor used by 2019-nCoV to infect humans as SARS-CoV [113] . Hence, clinical similarity between the two viruses is expected, particularly in severe cases. In addition, most of those who have died from MERS-CoV, SARS-CoV and 2019-nCoV were advance in age and had underlying health conditions such as hypertension, diabetes or cardiovascular disease that compromised their immune systems [114] . Coronaviruses have error-prone RNA-dependent RNA polymerases (RdRP), which result in frequent mutations and recombination events. This results in quasispecies diversity that is closely associated with adaptive evolution and the capacity to enhance viral-cell entry to cause disease over time in a specific population at-risk [115] . Since ACE2 is abundantly present in humans in the epithelia of the lung and small intestine, coronaviruses are likely to infect the upper respiratory and gastrointestinal tract and this may influence the type of therapeutics against 2019-nCoV, similarly to SAR-CoV.
However, in the years following two major coronavirus outbreaks SARS-CoV in 2003 and MERS-CoV in 2012, there remains no consensus on the optimal therapy for either disease [116, 117] . Well-designed clinical trials that provide the gold standard for assessing the therapeutic measures are scarce. No coronavirus protease inhibitors have successfully completed a preclinical development program despite large efforts exploring SARS-CoV inhibitors. The bulk of potential therapeutic strategies remain in the experimental phase, with only a handful crossing the in vitro hurdle. Stronger efforts are required in the research for treatment options for major coronaviruses given their pandemic potential. Effective treatment options are essential to maximize the restoration of affected populations to good health following infections. Clinical trials have commenced in China to identify effective treatments for 2019-nCoV based on the treatment evidence from SARS and MERS. There is currently no effective specific antiviral with high-level evidence; any specific antiviral therapy should be provided in the context of a clinical study/trial. Few treatments have shown real curative action against SARS and MERS and the literature generally describes isolated cases or small case series.
Many interferons from the three classes have been tested for their antiviral activities against SARS-CoV both in vitro and in animal models. Interferon β has consistently been shown to be the most active, followed by interferon α. The use of corticosteroids with interferon alfacon-1 (synthetic interferon α) appeared to have improved oxygenation and faster resolution of chest radiograph abnormalities in observational studies with untreated controls. Interferon has been used in multiple observational studies to treat SARS-CoV and MERS-CoV patients [116, 117] . Interferons, with or without ribavirin, and lopinavir/ritonavir are most likely to be beneficial and are being trialed in China for 2019-nCoV. This drug treatment appears to be the most advanced. Timing of treatment is likely an important factor in effectiveness. A combination of ribavirin and lopinavir/ritonavir was used as a post-exposure prophylaxis in health care workers and may have reduced the risk of infection. Ribavirin alone is unlikely to have substantial antiviral activities at clinically used dosages. Hence, ribavirin with or without corticosteroids and with lopinavir and ritonavir are among the combinations employed. This was the most common agent reported in the available literature. Its efficacy has been assessed in observational studies, retrospective case series, retrospective cohort study, a prospective observational study, a prospective cohort study and randomized controlled trial ranging from seven to 229 participants [117] . Lopinavir/ritonavir (Kaletra) was the earliest protease inhibitor combination introduced for the treatment of SARS-CoV. Its efficacy was documented in several studies, causing notably lower incidence of adverse outcomes than with ribavirin alone. Combined usage with ribavirin was also associated with lower incidence of acute respiratory distress syndrome, nosocomial infection and death, amongst other favorable outcomes. Recent in vitro studies have shown another HIV protease inhibitor, nelfinavir, to have antiviral capacity against SARS-CoV, although it has yet to show favorable outcomes in animal studies [118] . Remdesivir (Gilead Sciences, GS-5734) nucleoside analogue in vitro and in vivo data support GS-5734 development as a potential pan-coronavirus antiviral based on results against several coronaviruses (CoVs), including highly pathogenic CoVs and potentially emergent BatCoVs. The use of remdesivir may be a good candidate as an investigational treatment.
Improved mortality following receipt of convalescent plasma in various doses was consistently reported in several observational studies involving cases with severe acute respiratory infections (SARIs) of viral etiology. A significant reduction in the pooled odds of mortality following treatment of 0.25 compared to placebo or no therapy was observed [119] . Studies were however at moderate to high risk of bias given their small sample sizes, allocation of treatment based on the physician's discretion, and the availability of plasma. Factors like concomitant treatment may have also confounded the results. Associations between convalescent plasma and hospital length of stay, viral antibody levels, and viral load respectively were similarly inconsistent across available literature. Convalescent plasma, while promising, is likely not yet feasible, given the limited pool of potential donors and issues of scalability. Monoclonal antibody treatment is progressing. SARS-CoV enters host cells through the binding of their spike (S) protein to angiotensin converting enzyme 2 (ACE2) and CD209L [118] . Human monoclonal antibodies to the S protein have been shown to significantly reduce the severity of lung pathology in non-human primates following MERS-CoV infection [120] . Such neutralizing antibodies can be elicited by active or passive immunization using vaccines or convalescent plasma respectively. While such neutralizing antibodies can theoretically be harvested from individuals immunized with vaccines, there is uncertainty over the achievement of therapeutic levels of antibodies.
Other therapeutic agents have also been reported. A known antimalarial agent, chloroquine, elicits antiviral effects against multiple viruses including HIV type 1, hepatitis B and HCoV-229E. Chloroquine is also immunomodulatory, capable of suppressing the production and release of factors which mediate the inflammatory complications of viral diseases (tumor necrosis factor and interleukin 6) [121] . It is postulated that chloroquine works by altering ACE2 glycosylation and endosomal pH. Its anti-inflammatory properties may be beneficial for the treatment of SARS. Niclosamide as a known drug used in antihelminthic treatment. The efficacy of niclosamide as an inhibitor of virus replication was proven in several assays. In both immunoblot analysis and immunofluorescence assays, niclosamide treatment was observed to completely inhibit viral antigen synthesis. Reduction of virus yield in infected cells was dose dependent. Niclosamide likely does not interfere in the early stages of virus attachment and entry into cells, nor does it function as a protease inhibitor. Mechanisms of niclosamide activity warrant further investigation [122] . Glycyrrhizin also reportedly inhibits virus adsorption and penetration in the early steps of virus replication. Glycyrrhizin was a significantly potent inhibitor with a low selectivity index when tested against several pathogenic flaviviruses. While preliminary results suggest production of nitrous oxide (which inhibits virus replication) through induction of nitrous oxide synthase, the mechanism of Glycyrrhizin against SARS-CoV remains unclear. The compound also has relatively lower toxicity compared to protease inhibitors like ribavirin [123] . Inhibitory activity was also detected in baicalin [124] , extracted from another herb used in the treatment of SARS in China and Hong Kong. Findings on these compounds are limited to in vitro studies [121] [122] [123] [124] .
Due to the rapidly evolving situation of the 2019-nCoV, there will be potential limitations to the systematic review. The systematic review is likely to have publication bias as some developments have yet to be reported while for other developments there is no intention to report publicly (or in scientific platforms) due to confidentiality concerns. However, this may be limited to only a few developments for review as publicity does help in branding to some extent for the company and/or the funder. Furthermore, due to the rapid need to share the status of these developments, there may be reporting bias in some details provided by authors of the scientific articles or commentary articles in traditional media. Lastly, while it is not viable for any form of quality assessment and metaanalysis of the selected articles due to the limited data provided and the heterogeneous style of reporting by different articles, this paper has provided a comprehensive overview of the potential developments of these pharmaceutical interventions during the early phase of the outbreak. This systematic review would be useful for cross-check when the quality assessment and meta-analysis of these developments are performed as a follow-up study.
Rapid diagnostics, vaccines and therapeutics are key pharmaceutical interventions to limit transmission of respiratory infectious diseases. Many potential developments on these pharmaceutical interventions for 2019-nCoV are ongoing in the containment phase of this outbreak, potentially due to better pandemic preparedness than before. However, lessons from MERS-CoV and SARS-CoV have shown that the journeys for these developments can still be challenging moving ahead.
Supplementary Materials: The following are available online at www.mdpi.com/xxx/s1, Table S1 : Example of full search strategy in Pubmed, Table S2 : Google Search: 2019-nCoV diagnostics, Table S3 : Summary of diagnostic assays developed for 2019-nCoV, Table S4 | How many confirmed cases were identified in February 2020? | false | 3,618 | {
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2,504 | Respiratory Viral Infections in Exacerbation of Chronic Airway Inflammatory Diseases: Novel Mechanisms and Insights From the Upper Airway Epithelium
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7052386/
SHA: 45a566c71056ba4faab425b4f7e9edee6320e4a4
Authors: Tan, Kai Sen; Lim, Rachel Liyu; Liu, Jing; Ong, Hsiao Hui; Tan, Vivian Jiayi; Lim, Hui Fang; Chung, Kian Fan; Adcock, Ian M.; Chow, Vincent T.; Wang, De Yun
Date: 2020-02-25
DOI: 10.3389/fcell.2020.00099
License: cc-by
Abstract: Respiratory virus infection is one of the major sources of exacerbation of chronic airway inflammatory diseases. These exacerbations are associated with high morbidity and even mortality worldwide. The current understanding on viral-induced exacerbations is that viral infection increases airway inflammation which aggravates disease symptoms. Recent advances in in vitro air-liquid interface 3D cultures, organoid cultures and the use of novel human and animal challenge models have evoked new understandings as to the mechanisms of viral exacerbations. In this review, we will focus on recent novel findings that elucidate how respiratory viral infections alter the epithelial barrier in the airways, the upper airway microbial environment, epigenetic modifications including miRNA modulation, and other changes in immune responses throughout the upper and lower airways. First, we reviewed the prevalence of different respiratory viral infections in causing exacerbations in chronic airway inflammatory diseases. Subsequently we also summarized how recent models have expanded our appreciation of the mechanisms of viral-induced exacerbations. Further we highlighted the importance of the virome within the airway microbiome environment and its impact on subsequent bacterial infection. This review consolidates the understanding of viral induced exacerbation in chronic airway inflammatory diseases and indicates pathways that may be targeted for more effective management of chronic inflammatory diseases.
Text: The prevalence of chronic airway inflammatory disease is increasing worldwide especially in developed nations (GBD 2015 Chronic Respiratory Disease Collaborators, 2017 Guan et al., 2018) . This disease is characterized by airway inflammation leading to complications such as coughing, wheezing and shortness of breath. The disease can manifest in both the upper airway (such as chronic rhinosinusitis, CRS) and lower airway (such as asthma and chronic obstructive pulmonary disease, COPD) which greatly affect the patients' quality of life (Calus et al., 2012; Bao et al., 2015) . Treatment and management vary greatly in efficacy due to the complexity and heterogeneity of the disease. This is further complicated by the effect of episodic exacerbations of the disease, defined as worsening of disease symptoms including wheeze, cough, breathlessness and chest tightness (Xepapadaki and Papadopoulos, 2010) . Such exacerbations are due to the effect of enhanced acute airway inflammation impacting upon and worsening the symptoms of the existing disease (Hashimoto et al., 2008; Viniol and Vogelmeier, 2018) . These acute exacerbations are the main cause of morbidity and sometimes mortality in patients, as well as resulting in major economic burdens worldwide. However, due to the complex interactions between the host and the exacerbation agents, the mechanisms of exacerbation may vary considerably in different individuals under various triggers. Acute exacerbations are usually due to the presence of environmental factors such as allergens, pollutants, smoke, cold or dry air and pathogenic microbes in the airway (Gautier and Charpin, 2017; Viniol and Vogelmeier, 2018) . These agents elicit an immune response leading to infiltration of activated immune cells that further release inflammatory mediators that cause acute symptoms such as increased mucus production, cough, wheeze and shortness of breath. Among these agents, viral infection is one of the major drivers of asthma exacerbations accounting for up to 80-90% and 45-80% of exacerbations in children and adults respectively (Grissell et al., 2005; Xepapadaki and Papadopoulos, 2010; Jartti and Gern, 2017; Adeli et al., 2019) . Viral involvement in COPD exacerbation is also equally high, having been detected in 30-80% of acute COPD exacerbations (Kherad et al., 2010; Jafarinejad et al., 2017; Stolz et al., 2019) . Whilst the prevalence of viral exacerbations in CRS is still unclear, its prevalence is likely to be high due to the similar inflammatory nature of these diseases (Rowan et al., 2015; Tan et al., 2017) . One of the reasons for the involvement of respiratory viruses' in exacerbations is their ease of transmission and infection (Kutter et al., 2018) . In addition, the high diversity of the respiratory viruses may also contribute to exacerbations of different nature and severity (Busse et al., 2010; Costa et al., 2014; Jartti and Gern, 2017) . Hence, it is important to identify the exact mechanisms underpinning viral exacerbations in susceptible subjects in order to properly manage exacerbations via supplementary treatments that may alleviate the exacerbation symptoms or prevent severe exacerbations.
While the lower airway is the site of dysregulated inflammation in most chronic airway inflammatory diseases, the upper airway remains the first point of contact with sources of exacerbation. Therefore, their interaction with the exacerbation agents may directly contribute to the subsequent responses in the lower airway, in line with the "United Airway" hypothesis. To elucidate the host airway interaction with viruses leading to exacerbations, we thus focus our review on recent findings of viral interaction with the upper airway. We compiled how viral induced changes to the upper airway may contribute to chronic airway inflammatory disease exacerbations, to provide a unified elucidation of the potential exacerbation mechanisms initiated from predominantly upper airway infections.
Despite being a major cause of exacerbation, reports linking respiratory viruses to acute exacerbations only start to emerge in the late 1950s (Pattemore et al., 1992) ; with bacterial infections previously considered as the likely culprit for acute exacerbation (Stevens, 1953; Message and Johnston, 2002) . However, with the advent of PCR technology, more viruses were recovered during acute exacerbations events and reports implicating their role emerged in the late 1980s (Message and Johnston, 2002) . Rhinovirus (RV) and respiratory syncytial virus (RSV) are the predominant viruses linked to the development and exacerbation of chronic airway inflammatory diseases (Jartti and Gern, 2017) . Other viruses such as parainfluenza virus (PIV), influenza virus (IFV) and adenovirus (AdV) have also been implicated in acute exacerbations but to a much lesser extent (Johnston et al., 2005; Oliver et al., 2014; Ko et al., 2019) . More recently, other viruses including bocavirus (BoV), human metapneumovirus (HMPV), certain coronavirus (CoV) strains, a specific enterovirus (EV) strain EV-D68, human cytomegalovirus (hCMV) and herpes simplex virus (HSV) have been reported as contributing to acute exacerbations . The common feature these viruses share is that they can infect both the upper and/or lower airway, further increasing the inflammatory conditions in the diseased airway (Mallia and Johnston, 2006; Britto et al., 2017) .
Respiratory viruses primarily infect and replicate within airway epithelial cells . During the replication process, the cells release antiviral factors and cytokines that alter local airway inflammation and airway niche (Busse et al., 2010) . In a healthy airway, the inflammation normally leads to type 1 inflammatory responses consisting of activation of an antiviral state and infiltration of antiviral effector cells. This eventually results in the resolution of the inflammatory response and clearance of the viral infection (Vareille et al., 2011; Braciale et al., 2012) . However, in a chronically inflamed airway, the responses against the virus may be impaired or aberrant, causing sustained inflammation and erroneous infiltration, resulting in the exacerbation of their symptoms (Mallia and Johnston, 2006; Dougherty and Fahy, 2009; Busse et al., 2010; Britto et al., 2017; Linden et al., 2019) . This is usually further compounded by the increased susceptibility of chronic airway inflammatory disease patients toward viral respiratory infections, thereby increasing the frequency of exacerbation as a whole (Dougherty and Fahy, 2009; Busse et al., 2010; Linden et al., 2019) . Furthermore, due to the different replication cycles and response against the myriad of respiratory viruses, each respiratory virus may also contribute to exacerbations via different mechanisms that may alter their severity. Hence, this review will focus on compiling and collating the current known mechanisms of viral-induced exacerbation of chronic airway inflammatory diseases; as well as linking the different viral infection pathogenesis to elucidate other potential ways the infection can exacerbate the disease. The review will serve to provide further understanding of viral induced exacerbation to identify potential pathways and pathogenesis mechanisms that may be targeted as supplementary care for management and prevention of exacerbation. Such an approach may be clinically significant due to the current scarcity of antiviral drugs for the management of viral-induced exacerbations. This will improve the quality of life of patients with chronic airway inflammatory diseases.
Once the link between viral infection and acute exacerbations of chronic airway inflammatory disease was established, there have been many reports on the mechanisms underlying the exacerbation induced by respiratory viral infection. Upon infecting the host, viruses evoke an inflammatory response as a means of counteracting the infection. Generally, infected airway epithelial cells release type I (IFNα/β) and type III (IFNλ) interferons, cytokines and chemokines such as IL-6, IL-8, IL-12, RANTES, macrophage inflammatory protein 1α (MIP-1α) and monocyte chemotactic protein 1 (MCP-1) (Wark and Gibson, 2006; Matsukura et al., 2013) . These, in turn, enable infiltration of innate immune cells and of professional antigen presenting cells (APCs) that will then in turn release specific mediators to facilitate viral targeting and clearance, including type II interferon (IFNγ), IL-2, IL-4, IL-5, IL-9, and IL-12 (Wark and Gibson, 2006; Singh et al., 2010; Braciale et al., 2012) . These factors heighten local inflammation and the infiltration of granulocytes, T-cells and B-cells (Wark and Gibson, 2006; Braciale et al., 2012) . The increased inflammation, in turn, worsens the symptoms of airway diseases.
Additionally, in patients with asthma and patients with CRS with nasal polyp (CRSwNP), viral infections such as RV and RSV promote a Type 2-biased immune response (Becker, 2006; Jackson et al., 2014; Jurak et al., 2018) . This amplifies the basal type 2 inflammation resulting in a greater release of IL-4, IL-5, IL-13, RANTES and eotaxin and a further increase in eosinophilia, a key pathological driver of asthma and CRSwNP (Wark and Gibson, 2006; Singh et al., 2010; Chung et al., 2015; Dunican and Fahy, 2015) . Increased eosinophilia, in turn, worsens the classical symptoms of disease and may further lead to life-threatening conditions due to breathing difficulties. On the other hand, patients with COPD and patients with CRS without nasal polyp (CRSsNP) are more neutrophilic in nature due to the expression of neutrophil chemoattractants such as CXCL9, CXCL10, and CXCL11 (Cukic et al., 2012; Brightling and Greening, 2019) . The pathology of these airway diseases is characterized by airway remodeling due to the presence of remodeling factors such as matrix metalloproteinases (MMPs) released from infiltrating neutrophils (Linden et al., 2019) . Viral infections in such conditions will then cause increase neutrophilic activation; worsening the symptoms and airway remodeling in the airway thereby exacerbating COPD, CRSsNP and even CRSwNP in certain cases (Wang et al., 2009; Tacon et al., 2010; Linden et al., 2019) .
An epithelial-centric alarmin pathway around IL-25, IL-33 and thymic stromal lymphopoietin (TSLP), and their interaction with group 2 innate lymphoid cells (ILC2) has also recently been identified (Nagarkar et al., 2012; Hong et al., 2018; Allinne et al., 2019) . IL-25, IL-33 and TSLP are type 2 inflammatory cytokines expressed by the epithelial cells upon injury to the epithelial barrier (Gabryelska et al., 2019; Roan et al., 2019) . ILC2s are a group of lymphoid cells lacking both B and T cell receptors but play a crucial role in secreting type 2 cytokines to perpetuate type 2 inflammation when activated (Scanlon and McKenzie, 2012; Li and Hendriks, 2013) . In the event of viral infection, cell death and injury to the epithelial barrier will also induce the expression of IL-25, IL-33 and TSLP, with heighten expression in an inflamed airway (Allakhverdi et al., 2007; Goldsmith et al., 2012; Byers et al., 2013; Shaw et al., 2013; Beale et al., 2014; Jackson et al., 2014; Uller and Persson, 2018; Ravanetti et al., 2019) . These 3 cytokines then work in concert to activate ILC2s to further secrete type 2 cytokines IL-4, IL-5, and IL-13 which further aggravate the type 2 inflammation in the airway causing acute exacerbation (Camelo et al., 2017) . In the case of COPD, increased ILC2 activation, which retain the capability of differentiating to ILC1, may also further augment the neutrophilic response and further aggravate the exacerbation (Silver et al., 2016) . Interestingly, these factors are not released to any great extent and do not activate an ILC2 response during viral infection in healthy individuals (Yan et al., 2016; Tan et al., 2018a) ; despite augmenting a type 2 exacerbation in chronically inflamed airways (Jurak et al., 2018) . These classical mechanisms of viral induced acute exacerbations are summarized in Figure 1 .
As integration of the virology, microbiology and immunology of viral infection becomes more interlinked, additional factors and FIGURE 1 | Current understanding of viral induced exacerbation of chronic airway inflammatory diseases. Upon virus infection in the airway, antiviral state will be activated to clear the invading pathogen from the airway. Immune response and injury factors released from the infected epithelium normally would induce a rapid type 1 immunity that facilitates viral clearance. However, in the inflamed airway, the cytokines and chemokines released instead augmented the inflammation present in the chronically inflamed airway, strengthening the neutrophilic infiltration in COPD airway, and eosinophilic infiltration in the asthmatic airway. The effect is also further compounded by the participation of Th1 and ILC1 cells in the COPD airway; and Th2 and ILC2 cells in the asthmatic airway.
Frontiers in Cell and Developmental Biology | www.frontiersin.org mechanisms have been implicated in acute exacerbations during and after viral infection (Murray et al., 2006) . Murray et al. (2006) has underlined the synergistic effect of viral infection with other sensitizing agents in causing more severe acute exacerbations in the airway. This is especially true when not all exacerbation events occurred during the viral infection but may also occur well after viral clearance (Kim et al., 2008; Stolz et al., 2019) in particular the late onset of a bacterial infection (Singanayagam et al., 2018 (Singanayagam et al., , 2019a . In addition, viruses do not need to directly infect the lower airway to cause an acute exacerbation, as the nasal epithelium remains the primary site of most infections. Moreover, not all viral infections of the airway will lead to acute exacerbations, suggesting a more complex interplay between the virus and upper airway epithelium which synergize with the local airway environment in line with the "united airway" hypothesis (Kurai et al., 2013) . On the other hand, viral infections or their components persist in patients with chronic airway inflammatory disease (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Hence, their presence may further alter the local environment and contribute to current and future exacerbations. Future studies should be performed using metagenomics in addition to PCR analysis to determine the contribution of the microbiome and mycobiome to viral infections. In this review, we highlight recent data regarding viral interactions with the airway epithelium that could also contribute to, or further aggravate, acute exacerbations of chronic airway inflammatory diseases.
Patients with chronic airway inflammatory diseases have impaired or reduced ability of viral clearance (Hammond et al., 2015; McKendry et al., 2016; Akbarshahi et al., 2018; Gill et al., 2018; Wang et al., 2018; Singanayagam et al., 2019b) . Their impairment stems from a type 2-skewed inflammatory response which deprives the airway of important type 1 responsive CD8 cells that are responsible for the complete clearance of virusinfected cells (Becker, 2006; McKendry et al., 2016) . This is especially evident in weak type 1 inflammation-inducing viruses such as RV and RSV (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Additionally, there are also evidence of reduced type I (IFNβ) and III (IFNλ) interferon production due to type 2-skewed inflammation, which contributes to imperfect clearance of the virus resulting in persistence of viral components, or the live virus in the airway epithelium (Contoli et al., 2006; Hwang et al., 2019; Wark, 2019) . Due to the viral components remaining in the airway, antiviral genes such as type I interferons, inflammasome activating factors and cytokines remained activated resulting in prolong airway inflammation (Wood et al., 2011; Essaidi-Laziosi et al., 2018) . These factors enhance granulocyte infiltration thus prolonging the exacerbation symptoms. Such persistent inflammation may also be found within DNA viruses such as AdV, hCMV and HSV, whose infections generally persist longer (Imperiale and Jiang, 2015) , further contributing to chronic activation of inflammation when they infect the airway (Yang et al., 2008; Morimoto et al., 2009; Imperiale and Jiang, 2015; Lan et al., 2016; Tan et al., 2016; Kowalski et al., 2017) . With that note, human papilloma virus (HPV), a DNA virus highly associated with head and neck cancers and respiratory papillomatosis, is also linked with the chronic inflammation that precedes the malignancies (de Visser et al., 2005; Gillison et al., 2012; Bonomi et al., 2014; Fernandes et al., 2015) . Therefore, the role of HPV infection in causing chronic inflammation in the airway and their association to exacerbations of chronic airway inflammatory diseases, which is scarcely explored, should be investigated in the future. Furthermore, viral persistence which lead to continuous expression of antiviral genes may also lead to the development of steroid resistance, which is seen with RV, RSV, and PIV infection (Chi et al., 2011; Ford et al., 2013; Papi et al., 2013) . The use of steroid to suppress the inflammation may also cause the virus to linger longer in the airway due to the lack of antiviral clearance (Kim et al., 2008; Hammond et al., 2015; Hewitt et al., 2016; McKendry et al., 2016; Singanayagam et al., 2019b) . The concomitant development of steroid resistance together with recurring or prolong viral infection thus added considerable burden to the management of acute exacerbation, which should be the future focus of research to resolve the dual complications arising from viral infection.
On the other end of the spectrum, viruses that induce strong type 1 inflammation and cell death such as IFV (Yan et al., 2016; Guibas et al., 2018) and certain CoV (including the recently emerged COVID-19 virus) (Tao et al., 2013; Yue et al., 2018; Zhu et al., 2020) , may not cause prolonged inflammation due to strong induction of antiviral clearance. These infections, however, cause massive damage and cell death to the epithelial barrier, so much so that areas of the epithelium may be completely absent post infection (Yan et al., 2016; Tan et al., 2019) . Factors such as RANTES and CXCL10, which recruit immune cells to induce apoptosis, are strongly induced from IFV infected epithelium (Ampomah et al., 2018; Tan et al., 2019) . Additionally, necroptotic factors such as RIP3 further compounds the cell deaths in IFV infected epithelium . The massive cell death induced may result in worsening of the acute exacerbation due to the release of their cellular content into the airway, further evoking an inflammatory response in the airway (Guibas et al., 2018) . Moreover, the destruction of the epithelial barrier may cause further contact with other pathogens and allergens in the airway which may then prolong exacerbations or results in new exacerbations. Epithelial destruction may also promote further epithelial remodeling during its regeneration as viral infection induces the expression of remodeling genes such as MMPs and growth factors . Infections that cause massive destruction of the epithelium, such as IFV, usually result in severe acute exacerbations with non-classical symptoms of chronic airway inflammatory diseases. Fortunately, annual vaccines are available to prevent IFV infections (Vasileiou et al., 2017; Zheng et al., 2018) ; and it is recommended that patients with chronic airway inflammatory disease receive their annual influenza vaccination as the best means to prevent severe IFV induced exacerbation.
Another mechanism that viral infections may use to drive acute exacerbations is the induction of vasodilation or tight junction opening factors which may increase the rate of infiltration. Infection with a multitude of respiratory viruses causes disruption of tight junctions with the resulting increased rate of viral infiltration. This also increases the chances of allergens coming into contact with airway immune cells. For example, IFV infection was found to induce oncostatin M (OSM) which causes tight junction opening (Pothoven et al., 2015; Tian et al., 2018) . Similarly, RV and RSV infections usually cause tight junction opening which may also increase the infiltration rate of eosinophils and thus worsening of the classical symptoms of chronic airway inflammatory diseases (Sajjan et al., 2008; Kast et al., 2017; Kim et al., 2018) . In addition, the expression of vasodilating factors and fluid homeostatic factors such as angiopoietin-like 4 (ANGPTL4) and bactericidal/permeabilityincreasing fold-containing family member A1 (BPIFA1) are also associated with viral infections and pneumonia development, which may worsen inflammation in the lower airway Akram et al., 2018) . These factors may serve as targets to prevent viral-induced exacerbations during the management of acute exacerbation of chronic airway inflammatory diseases.
Another recent area of interest is the relationship between asthma and COPD exacerbations and their association with the airway microbiome. The development of chronic airway inflammatory diseases is usually linked to specific bacterial species in the microbiome which may thrive in the inflamed airway environment (Diver et al., 2019) . In the event of a viral infection such as RV infection, the effect induced by the virus may destabilize the equilibrium of the microbiome present (Molyneaux et al., 2013; Kloepfer et al., 2014; Kloepfer et al., 2017; Jubinville et al., 2018; van Rijn et al., 2019) . In addition, viral infection may disrupt biofilm colonies in the upper airway (e.g., Streptococcus pneumoniae) microbiome to be release into the lower airway and worsening the inflammation (Marks et al., 2013; Chao et al., 2014) . Moreover, a viral infection may also alter the nutrient profile in the airway through release of previously inaccessible nutrients that will alter bacterial growth (Siegel et al., 2014; Mallia et al., 2018) . Furthermore, the destabilization is further compounded by impaired bacterial immune response, either from direct viral influences, or use of corticosteroids to suppress the exacerbation symptoms (Singanayagam et al., 2018 (Singanayagam et al., , 2019a Wang et al., 2018; Finney et al., 2019) . All these may gradually lead to more far reaching effect when normal flora is replaced with opportunistic pathogens, altering the inflammatory profiles (Teo et al., 2018) . These changes may in turn result in more severe and frequent acute exacerbations due to the interplay between virus and pathogenic bacteria in exacerbating chronic airway inflammatory diseases (Wark et al., 2013; Singanayagam et al., 2018) . To counteract these effects, microbiome-based therapies are in their infancy but have shown efficacy in the treatments of irritable bowel syndrome by restoring the intestinal microbiome (Bakken et al., 2011) . Further research can be done similarly for the airway microbiome to be able to restore the microbiome following disruption by a viral infection.
Viral infections can cause the disruption of mucociliary function, an important component of the epithelial barrier. Ciliary proteins FIGURE 2 | Changes in the upper airway epithelium contributing to viral exacerbation in chronic airway inflammatory diseases. The upper airway epithelium is the primary contact/infection site of most respiratory viruses. Therefore, its infection by respiratory viruses may have far reaching consequences in augmenting and synergizing current and future acute exacerbations. The destruction of epithelial barrier, mucociliary function and cell death of the epithelial cells serves to increase contact between environmental triggers with the lower airway and resident immune cells. The opening of tight junction increasing the leakiness further augments the inflammation and exacerbations. In addition, viral infections are usually accompanied with oxidative stress which will further increase the local inflammation in the airway. The dysregulation of inflammation can be further compounded by modulation of miRNAs and epigenetic modification such as DNA methylation and histone modifications that promote dysregulation in inflammation. Finally, the change in the local airway environment and inflammation promotes growth of pathogenic bacteria that may replace the airway microbiome. Furthermore, the inflammatory environment may also disperse upper airway commensals into the lower airway, further causing inflammation and alteration of the lower airway environment, resulting in prolong exacerbation episodes following viral infection.
Viral specific trait contributing to exacerbation mechanism (with literature evidence) Oxidative stress ROS production (RV, RSV, IFV, HSV)
As RV, RSV, and IFV were the most frequently studied viruses in chronic airway inflammatory diseases, most of the viruses listed are predominantly these viruses. However, the mechanisms stated here may also be applicable to other viruses but may not be listed as they were not implicated in the context of chronic airway inflammatory diseases exacerbation (see text for abbreviations).
that aid in the proper function of the motile cilia in the airways are aberrantly expressed in ciliated airway epithelial cells which are the major target for RV infection (Griggs et al., 2017) . Such form of secondary cilia dyskinesia appears to be present with chronic inflammations in the airway, but the exact mechanisms are still unknown (Peng et al., , 2019 Qiu et al., 2018) . Nevertheless, it was found that in viral infection such as IFV, there can be a change in the metabolism of the cells as well as alteration in the ciliary gene expression, mostly in the form of down-regulation of the genes such as dynein axonemal heavy chain 5 (DNAH5) and multiciliate differentiation And DNA synthesis associated cell cycle protein (MCIDAS) (Tan et al., 2018b . The recently emerged Wuhan CoV was also found to reduce ciliary beating in infected airway epithelial cell model (Zhu et al., 2020) . Furthermore, viral infections such as RSV was shown to directly destroy the cilia of the ciliated cells and almost all respiratory viruses infect the ciliated cells (Jumat et al., 2015; Yan et al., 2016; Tan et al., 2018a) . In addition, mucus overproduction may also disrupt the equilibrium of the mucociliary function following viral infection, resulting in symptoms of acute exacerbation (Zhu et al., 2009) . Hence, the disruption of the ciliary movement during viral infection may cause more foreign material and allergen to enter the airway, aggravating the symptoms of acute exacerbation and making it more difficult to manage. The mechanism of the occurrence of secondary cilia dyskinesia can also therefore be explored as a means to limit the effects of viral induced acute exacerbation.
MicroRNAs (miRNAs) are short non-coding RNAs involved in post-transcriptional modulation of biological processes, and implicated in a number of diseases (Tan et al., 2014) . miRNAs are found to be induced by viral infections and may play a role in the modulation of antiviral responses and inflammation (Gutierrez et al., 2016; Deng et al., 2017; Feng et al., 2018) . In the case of chronic airway inflammatory diseases, circulating miRNA changes were found to be linked to exacerbation of the diseases (Wardzynska et al., 2020) . Therefore, it is likely that such miRNA changes originated from the infected epithelium and responding immune cells, which may serve to further dysregulate airway inflammation leading to exacerbations. Both IFV and RSV infections has been shown to increase miR-21 and augmented inflammation in experimental murine asthma models, which is reversed with a combination treatment of anti-miR-21 and corticosteroids (Kim et al., 2017) . IFV infection is also shown to increase miR-125a and b, and miR-132 in COPD epithelium which inhibits A20 and MAVS; and p300 and IRF3, respectively, resulting in increased susceptibility to viral infections (Hsu et al., 2016 (Hsu et al., , 2017 . Conversely, miR-22 was shown to be suppressed in asthmatic epithelium in IFV infection which lead to aberrant epithelial response, contributing to exacerbations (Moheimani et al., 2018) . Other than these direct evidence of miRNA changes in contributing to exacerbations, an increased number of miRNAs and other non-coding RNAs responsible for immune modulation are found to be altered following viral infections (Globinska et al., 2014; Feng et al., 2018; Hasegawa et al., 2018) . Hence non-coding RNAs also presents as targets to modulate viral induced airway changes as a means of managing exacerbation of chronic airway inflammatory diseases. Other than miRNA modulation, other epigenetic modification such as DNA methylation may also play a role in exacerbation of chronic airway inflammatory diseases. Recent epigenetic studies have indicated the association of epigenetic modification and chronic airway inflammatory diseases, and that the nasal methylome was shown to be a sensitive marker for airway inflammatory changes (Cardenas et al., 2019; Gomez, 2019) . At the same time, it was also shown that viral infections such as RV and RSV alters DNA methylation and histone modifications in the airway epithelium which may alter inflammatory responses, driving chronic airway inflammatory diseases and exacerbations (McErlean et al., 2014; Pech et al., 2018; Caixia et al., 2019) . In addition, Spalluto et al. (2017) also showed that antiviral factors such as IFNγ epigenetically modifies the viral resistance of epithelial cells. Hence, this may indicate that infections such as RV and RSV that weakly induce antiviral responses may result in an altered inflammatory state contributing to further viral persistence and exacerbation of chronic airway inflammatory diseases (Spalluto et al., 2017) .
Finally, viral infection can result in enhanced production of reactive oxygen species (ROS), oxidative stress and mitochondrial dysfunction in the airway epithelium (Kim et al., 2018; Mishra et al., 2018; Wang et al., 2018) . The airway epithelium of patients with chronic airway inflammatory diseases are usually under a state of constant oxidative stress which sustains the inflammation in the airway (Barnes, 2017; van der Vliet et al., 2018) . Viral infections of the respiratory epithelium by viruses such as IFV, RV, RSV and HSV may trigger the further production of ROS as an antiviral mechanism Aizawa et al., 2018; Wang et al., 2018) . Moreover, infiltrating cells in response to the infection such as neutrophils will also trigger respiratory burst as a means of increasing the ROS in the infected region. The increased ROS and oxidative stress in the local environment may serve as a trigger to promote inflammation thereby aggravating the inflammation in the airway (Tiwari et al., 2002) . A summary of potential exacerbation mechanisms and the associated viruses is shown in Figure 2 and Table 1 .
While the mechanisms underlying the development and acute exacerbation of chronic airway inflammatory disease is extensively studied for ways to manage and control the disease, a viral infection does more than just causing an acute exacerbation in these patients. A viral-induced acute exacerbation not only induced and worsens the symptoms of the disease, but also may alter the management of the disease or confer resistance toward treatments that worked before. Hence, appreciation of the mechanisms of viral-induced acute exacerbations is of clinical significance to devise strategies to correct viral induce changes that may worsen chronic airway inflammatory disease symptoms. Further studies in natural exacerbations and in viral-challenge models using RNA-sequencing (RNA-seq) or single cell RNA-seq on a range of time-points may provide important information regarding viral pathogenesis and changes induced within the airway of chronic airway inflammatory disease patients to identify novel targets and pathway for improved management of the disease. Subsequent analysis of functions may use epithelial cell models such as the air-liquid interface, in vitro airway epithelial model that has been adapted to studying viral infection and the changes it induced in the airway (Yan et al., 2016; Boda et al., 2018; Tan et al., 2018a) . Animal-based diseased models have also been developed to identify systemic mechanisms of acute exacerbation (Shin, 2016; Gubernatorova et al., 2019; Tanner and Single, 2019) . Furthermore, the humanized mouse model that possess human immune cells may also serves to unravel the immune profile of a viral infection in healthy and diseased condition (Ito et al., 2019; Li and Di Santo, 2019) . For milder viruses, controlled in vivo human infections can be performed for the best mode of verification of the associations of the virus with the proposed mechanism of viral induced acute exacerbations . With the advent of suitable diseased models, the verification of the mechanisms will then provide the necessary continuation of improving the management of viral induced acute exacerbations.
In conclusion, viral-induced acute exacerbation of chronic airway inflammatory disease is a significant health and economic burden that needs to be addressed urgently. In view of the scarcity of antiviral-based preventative measures available for only a few viruses and vaccines that are only available for IFV infections, more alternative measures should be explored to improve the management of the disease. Alternative measures targeting novel viral-induced acute exacerbation mechanisms, especially in the upper airway, can serve as supplementary treatments of the currently available management strategies to augment their efficacy. New models including primary human bronchial or nasal epithelial cell cultures, organoids or precision cut lung slices from patients with airways disease rather than healthy subjects can be utilized to define exacerbation mechanisms. These mechanisms can then be validated in small clinical trials in patients with asthma or COPD. Having multiple means of treatment may also reduce the problems that arise from resistance development toward a specific treatment. | Why may the mechanisms of exacerbation vary considerably? | false | 3,868 | {
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2,504 | Respiratory Viral Infections in Exacerbation of Chronic Airway Inflammatory Diseases: Novel Mechanisms and Insights From the Upper Airway Epithelium
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7052386/
SHA: 45a566c71056ba4faab425b4f7e9edee6320e4a4
Authors: Tan, Kai Sen; Lim, Rachel Liyu; Liu, Jing; Ong, Hsiao Hui; Tan, Vivian Jiayi; Lim, Hui Fang; Chung, Kian Fan; Adcock, Ian M.; Chow, Vincent T.; Wang, De Yun
Date: 2020-02-25
DOI: 10.3389/fcell.2020.00099
License: cc-by
Abstract: Respiratory virus infection is one of the major sources of exacerbation of chronic airway inflammatory diseases. These exacerbations are associated with high morbidity and even mortality worldwide. The current understanding on viral-induced exacerbations is that viral infection increases airway inflammation which aggravates disease symptoms. Recent advances in in vitro air-liquid interface 3D cultures, organoid cultures and the use of novel human and animal challenge models have evoked new understandings as to the mechanisms of viral exacerbations. In this review, we will focus on recent novel findings that elucidate how respiratory viral infections alter the epithelial barrier in the airways, the upper airway microbial environment, epigenetic modifications including miRNA modulation, and other changes in immune responses throughout the upper and lower airways. First, we reviewed the prevalence of different respiratory viral infections in causing exacerbations in chronic airway inflammatory diseases. Subsequently we also summarized how recent models have expanded our appreciation of the mechanisms of viral-induced exacerbations. Further we highlighted the importance of the virome within the airway microbiome environment and its impact on subsequent bacterial infection. This review consolidates the understanding of viral induced exacerbation in chronic airway inflammatory diseases and indicates pathways that may be targeted for more effective management of chronic inflammatory diseases.
Text: The prevalence of chronic airway inflammatory disease is increasing worldwide especially in developed nations (GBD 2015 Chronic Respiratory Disease Collaborators, 2017 Guan et al., 2018) . This disease is characterized by airway inflammation leading to complications such as coughing, wheezing and shortness of breath. The disease can manifest in both the upper airway (such as chronic rhinosinusitis, CRS) and lower airway (such as asthma and chronic obstructive pulmonary disease, COPD) which greatly affect the patients' quality of life (Calus et al., 2012; Bao et al., 2015) . Treatment and management vary greatly in efficacy due to the complexity and heterogeneity of the disease. This is further complicated by the effect of episodic exacerbations of the disease, defined as worsening of disease symptoms including wheeze, cough, breathlessness and chest tightness (Xepapadaki and Papadopoulos, 2010) . Such exacerbations are due to the effect of enhanced acute airway inflammation impacting upon and worsening the symptoms of the existing disease (Hashimoto et al., 2008; Viniol and Vogelmeier, 2018) . These acute exacerbations are the main cause of morbidity and sometimes mortality in patients, as well as resulting in major economic burdens worldwide. However, due to the complex interactions between the host and the exacerbation agents, the mechanisms of exacerbation may vary considerably in different individuals under various triggers. Acute exacerbations are usually due to the presence of environmental factors such as allergens, pollutants, smoke, cold or dry air and pathogenic microbes in the airway (Gautier and Charpin, 2017; Viniol and Vogelmeier, 2018) . These agents elicit an immune response leading to infiltration of activated immune cells that further release inflammatory mediators that cause acute symptoms such as increased mucus production, cough, wheeze and shortness of breath. Among these agents, viral infection is one of the major drivers of asthma exacerbations accounting for up to 80-90% and 45-80% of exacerbations in children and adults respectively (Grissell et al., 2005; Xepapadaki and Papadopoulos, 2010; Jartti and Gern, 2017; Adeli et al., 2019) . Viral involvement in COPD exacerbation is also equally high, having been detected in 30-80% of acute COPD exacerbations (Kherad et al., 2010; Jafarinejad et al., 2017; Stolz et al., 2019) . Whilst the prevalence of viral exacerbations in CRS is still unclear, its prevalence is likely to be high due to the similar inflammatory nature of these diseases (Rowan et al., 2015; Tan et al., 2017) . One of the reasons for the involvement of respiratory viruses' in exacerbations is their ease of transmission and infection (Kutter et al., 2018) . In addition, the high diversity of the respiratory viruses may also contribute to exacerbations of different nature and severity (Busse et al., 2010; Costa et al., 2014; Jartti and Gern, 2017) . Hence, it is important to identify the exact mechanisms underpinning viral exacerbations in susceptible subjects in order to properly manage exacerbations via supplementary treatments that may alleviate the exacerbation symptoms or prevent severe exacerbations.
While the lower airway is the site of dysregulated inflammation in most chronic airway inflammatory diseases, the upper airway remains the first point of contact with sources of exacerbation. Therefore, their interaction with the exacerbation agents may directly contribute to the subsequent responses in the lower airway, in line with the "United Airway" hypothesis. To elucidate the host airway interaction with viruses leading to exacerbations, we thus focus our review on recent findings of viral interaction with the upper airway. We compiled how viral induced changes to the upper airway may contribute to chronic airway inflammatory disease exacerbations, to provide a unified elucidation of the potential exacerbation mechanisms initiated from predominantly upper airway infections.
Despite being a major cause of exacerbation, reports linking respiratory viruses to acute exacerbations only start to emerge in the late 1950s (Pattemore et al., 1992) ; with bacterial infections previously considered as the likely culprit for acute exacerbation (Stevens, 1953; Message and Johnston, 2002) . However, with the advent of PCR technology, more viruses were recovered during acute exacerbations events and reports implicating their role emerged in the late 1980s (Message and Johnston, 2002) . Rhinovirus (RV) and respiratory syncytial virus (RSV) are the predominant viruses linked to the development and exacerbation of chronic airway inflammatory diseases (Jartti and Gern, 2017) . Other viruses such as parainfluenza virus (PIV), influenza virus (IFV) and adenovirus (AdV) have also been implicated in acute exacerbations but to a much lesser extent (Johnston et al., 2005; Oliver et al., 2014; Ko et al., 2019) . More recently, other viruses including bocavirus (BoV), human metapneumovirus (HMPV), certain coronavirus (CoV) strains, a specific enterovirus (EV) strain EV-D68, human cytomegalovirus (hCMV) and herpes simplex virus (HSV) have been reported as contributing to acute exacerbations . The common feature these viruses share is that they can infect both the upper and/or lower airway, further increasing the inflammatory conditions in the diseased airway (Mallia and Johnston, 2006; Britto et al., 2017) .
Respiratory viruses primarily infect and replicate within airway epithelial cells . During the replication process, the cells release antiviral factors and cytokines that alter local airway inflammation and airway niche (Busse et al., 2010) . In a healthy airway, the inflammation normally leads to type 1 inflammatory responses consisting of activation of an antiviral state and infiltration of antiviral effector cells. This eventually results in the resolution of the inflammatory response and clearance of the viral infection (Vareille et al., 2011; Braciale et al., 2012) . However, in a chronically inflamed airway, the responses against the virus may be impaired or aberrant, causing sustained inflammation and erroneous infiltration, resulting in the exacerbation of their symptoms (Mallia and Johnston, 2006; Dougherty and Fahy, 2009; Busse et al., 2010; Britto et al., 2017; Linden et al., 2019) . This is usually further compounded by the increased susceptibility of chronic airway inflammatory disease patients toward viral respiratory infections, thereby increasing the frequency of exacerbation as a whole (Dougherty and Fahy, 2009; Busse et al., 2010; Linden et al., 2019) . Furthermore, due to the different replication cycles and response against the myriad of respiratory viruses, each respiratory virus may also contribute to exacerbations via different mechanisms that may alter their severity. Hence, this review will focus on compiling and collating the current known mechanisms of viral-induced exacerbation of chronic airway inflammatory diseases; as well as linking the different viral infection pathogenesis to elucidate other potential ways the infection can exacerbate the disease. The review will serve to provide further understanding of viral induced exacerbation to identify potential pathways and pathogenesis mechanisms that may be targeted as supplementary care for management and prevention of exacerbation. Such an approach may be clinically significant due to the current scarcity of antiviral drugs for the management of viral-induced exacerbations. This will improve the quality of life of patients with chronic airway inflammatory diseases.
Once the link between viral infection and acute exacerbations of chronic airway inflammatory disease was established, there have been many reports on the mechanisms underlying the exacerbation induced by respiratory viral infection. Upon infecting the host, viruses evoke an inflammatory response as a means of counteracting the infection. Generally, infected airway epithelial cells release type I (IFNα/β) and type III (IFNλ) interferons, cytokines and chemokines such as IL-6, IL-8, IL-12, RANTES, macrophage inflammatory protein 1α (MIP-1α) and monocyte chemotactic protein 1 (MCP-1) (Wark and Gibson, 2006; Matsukura et al., 2013) . These, in turn, enable infiltration of innate immune cells and of professional antigen presenting cells (APCs) that will then in turn release specific mediators to facilitate viral targeting and clearance, including type II interferon (IFNγ), IL-2, IL-4, IL-5, IL-9, and IL-12 (Wark and Gibson, 2006; Singh et al., 2010; Braciale et al., 2012) . These factors heighten local inflammation and the infiltration of granulocytes, T-cells and B-cells (Wark and Gibson, 2006; Braciale et al., 2012) . The increased inflammation, in turn, worsens the symptoms of airway diseases.
Additionally, in patients with asthma and patients with CRS with nasal polyp (CRSwNP), viral infections such as RV and RSV promote a Type 2-biased immune response (Becker, 2006; Jackson et al., 2014; Jurak et al., 2018) . This amplifies the basal type 2 inflammation resulting in a greater release of IL-4, IL-5, IL-13, RANTES and eotaxin and a further increase in eosinophilia, a key pathological driver of asthma and CRSwNP (Wark and Gibson, 2006; Singh et al., 2010; Chung et al., 2015; Dunican and Fahy, 2015) . Increased eosinophilia, in turn, worsens the classical symptoms of disease and may further lead to life-threatening conditions due to breathing difficulties. On the other hand, patients with COPD and patients with CRS without nasal polyp (CRSsNP) are more neutrophilic in nature due to the expression of neutrophil chemoattractants such as CXCL9, CXCL10, and CXCL11 (Cukic et al., 2012; Brightling and Greening, 2019) . The pathology of these airway diseases is characterized by airway remodeling due to the presence of remodeling factors such as matrix metalloproteinases (MMPs) released from infiltrating neutrophils (Linden et al., 2019) . Viral infections in such conditions will then cause increase neutrophilic activation; worsening the symptoms and airway remodeling in the airway thereby exacerbating COPD, CRSsNP and even CRSwNP in certain cases (Wang et al., 2009; Tacon et al., 2010; Linden et al., 2019) .
An epithelial-centric alarmin pathway around IL-25, IL-33 and thymic stromal lymphopoietin (TSLP), and their interaction with group 2 innate lymphoid cells (ILC2) has also recently been identified (Nagarkar et al., 2012; Hong et al., 2018; Allinne et al., 2019) . IL-25, IL-33 and TSLP are type 2 inflammatory cytokines expressed by the epithelial cells upon injury to the epithelial barrier (Gabryelska et al., 2019; Roan et al., 2019) . ILC2s are a group of lymphoid cells lacking both B and T cell receptors but play a crucial role in secreting type 2 cytokines to perpetuate type 2 inflammation when activated (Scanlon and McKenzie, 2012; Li and Hendriks, 2013) . In the event of viral infection, cell death and injury to the epithelial barrier will also induce the expression of IL-25, IL-33 and TSLP, with heighten expression in an inflamed airway (Allakhverdi et al., 2007; Goldsmith et al., 2012; Byers et al., 2013; Shaw et al., 2013; Beale et al., 2014; Jackson et al., 2014; Uller and Persson, 2018; Ravanetti et al., 2019) . These 3 cytokines then work in concert to activate ILC2s to further secrete type 2 cytokines IL-4, IL-5, and IL-13 which further aggravate the type 2 inflammation in the airway causing acute exacerbation (Camelo et al., 2017) . In the case of COPD, increased ILC2 activation, which retain the capability of differentiating to ILC1, may also further augment the neutrophilic response and further aggravate the exacerbation (Silver et al., 2016) . Interestingly, these factors are not released to any great extent and do not activate an ILC2 response during viral infection in healthy individuals (Yan et al., 2016; Tan et al., 2018a) ; despite augmenting a type 2 exacerbation in chronically inflamed airways (Jurak et al., 2018) . These classical mechanisms of viral induced acute exacerbations are summarized in Figure 1 .
As integration of the virology, microbiology and immunology of viral infection becomes more interlinked, additional factors and FIGURE 1 | Current understanding of viral induced exacerbation of chronic airway inflammatory diseases. Upon virus infection in the airway, antiviral state will be activated to clear the invading pathogen from the airway. Immune response and injury factors released from the infected epithelium normally would induce a rapid type 1 immunity that facilitates viral clearance. However, in the inflamed airway, the cytokines and chemokines released instead augmented the inflammation present in the chronically inflamed airway, strengthening the neutrophilic infiltration in COPD airway, and eosinophilic infiltration in the asthmatic airway. The effect is also further compounded by the participation of Th1 and ILC1 cells in the COPD airway; and Th2 and ILC2 cells in the asthmatic airway.
Frontiers in Cell and Developmental Biology | www.frontiersin.org mechanisms have been implicated in acute exacerbations during and after viral infection (Murray et al., 2006) . Murray et al. (2006) has underlined the synergistic effect of viral infection with other sensitizing agents in causing more severe acute exacerbations in the airway. This is especially true when not all exacerbation events occurred during the viral infection but may also occur well after viral clearance (Kim et al., 2008; Stolz et al., 2019) in particular the late onset of a bacterial infection (Singanayagam et al., 2018 (Singanayagam et al., , 2019a . In addition, viruses do not need to directly infect the lower airway to cause an acute exacerbation, as the nasal epithelium remains the primary site of most infections. Moreover, not all viral infections of the airway will lead to acute exacerbations, suggesting a more complex interplay between the virus and upper airway epithelium which synergize with the local airway environment in line with the "united airway" hypothesis (Kurai et al., 2013) . On the other hand, viral infections or their components persist in patients with chronic airway inflammatory disease (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Hence, their presence may further alter the local environment and contribute to current and future exacerbations. Future studies should be performed using metagenomics in addition to PCR analysis to determine the contribution of the microbiome and mycobiome to viral infections. In this review, we highlight recent data regarding viral interactions with the airway epithelium that could also contribute to, or further aggravate, acute exacerbations of chronic airway inflammatory diseases.
Patients with chronic airway inflammatory diseases have impaired or reduced ability of viral clearance (Hammond et al., 2015; McKendry et al., 2016; Akbarshahi et al., 2018; Gill et al., 2018; Wang et al., 2018; Singanayagam et al., 2019b) . Their impairment stems from a type 2-skewed inflammatory response which deprives the airway of important type 1 responsive CD8 cells that are responsible for the complete clearance of virusinfected cells (Becker, 2006; McKendry et al., 2016) . This is especially evident in weak type 1 inflammation-inducing viruses such as RV and RSV (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Additionally, there are also evidence of reduced type I (IFNβ) and III (IFNλ) interferon production due to type 2-skewed inflammation, which contributes to imperfect clearance of the virus resulting in persistence of viral components, or the live virus in the airway epithelium (Contoli et al., 2006; Hwang et al., 2019; Wark, 2019) . Due to the viral components remaining in the airway, antiviral genes such as type I interferons, inflammasome activating factors and cytokines remained activated resulting in prolong airway inflammation (Wood et al., 2011; Essaidi-Laziosi et al., 2018) . These factors enhance granulocyte infiltration thus prolonging the exacerbation symptoms. Such persistent inflammation may also be found within DNA viruses such as AdV, hCMV and HSV, whose infections generally persist longer (Imperiale and Jiang, 2015) , further contributing to chronic activation of inflammation when they infect the airway (Yang et al., 2008; Morimoto et al., 2009; Imperiale and Jiang, 2015; Lan et al., 2016; Tan et al., 2016; Kowalski et al., 2017) . With that note, human papilloma virus (HPV), a DNA virus highly associated with head and neck cancers and respiratory papillomatosis, is also linked with the chronic inflammation that precedes the malignancies (de Visser et al., 2005; Gillison et al., 2012; Bonomi et al., 2014; Fernandes et al., 2015) . Therefore, the role of HPV infection in causing chronic inflammation in the airway and their association to exacerbations of chronic airway inflammatory diseases, which is scarcely explored, should be investigated in the future. Furthermore, viral persistence which lead to continuous expression of antiviral genes may also lead to the development of steroid resistance, which is seen with RV, RSV, and PIV infection (Chi et al., 2011; Ford et al., 2013; Papi et al., 2013) . The use of steroid to suppress the inflammation may also cause the virus to linger longer in the airway due to the lack of antiviral clearance (Kim et al., 2008; Hammond et al., 2015; Hewitt et al., 2016; McKendry et al., 2016; Singanayagam et al., 2019b) . The concomitant development of steroid resistance together with recurring or prolong viral infection thus added considerable burden to the management of acute exacerbation, which should be the future focus of research to resolve the dual complications arising from viral infection.
On the other end of the spectrum, viruses that induce strong type 1 inflammation and cell death such as IFV (Yan et al., 2016; Guibas et al., 2018) and certain CoV (including the recently emerged COVID-19 virus) (Tao et al., 2013; Yue et al., 2018; Zhu et al., 2020) , may not cause prolonged inflammation due to strong induction of antiviral clearance. These infections, however, cause massive damage and cell death to the epithelial barrier, so much so that areas of the epithelium may be completely absent post infection (Yan et al., 2016; Tan et al., 2019) . Factors such as RANTES and CXCL10, which recruit immune cells to induce apoptosis, are strongly induced from IFV infected epithelium (Ampomah et al., 2018; Tan et al., 2019) . Additionally, necroptotic factors such as RIP3 further compounds the cell deaths in IFV infected epithelium . The massive cell death induced may result in worsening of the acute exacerbation due to the release of their cellular content into the airway, further evoking an inflammatory response in the airway (Guibas et al., 2018) . Moreover, the destruction of the epithelial barrier may cause further contact with other pathogens and allergens in the airway which may then prolong exacerbations or results in new exacerbations. Epithelial destruction may also promote further epithelial remodeling during its regeneration as viral infection induces the expression of remodeling genes such as MMPs and growth factors . Infections that cause massive destruction of the epithelium, such as IFV, usually result in severe acute exacerbations with non-classical symptoms of chronic airway inflammatory diseases. Fortunately, annual vaccines are available to prevent IFV infections (Vasileiou et al., 2017; Zheng et al., 2018) ; and it is recommended that patients with chronic airway inflammatory disease receive their annual influenza vaccination as the best means to prevent severe IFV induced exacerbation.
Another mechanism that viral infections may use to drive acute exacerbations is the induction of vasodilation or tight junction opening factors which may increase the rate of infiltration. Infection with a multitude of respiratory viruses causes disruption of tight junctions with the resulting increased rate of viral infiltration. This also increases the chances of allergens coming into contact with airway immune cells. For example, IFV infection was found to induce oncostatin M (OSM) which causes tight junction opening (Pothoven et al., 2015; Tian et al., 2018) . Similarly, RV and RSV infections usually cause tight junction opening which may also increase the infiltration rate of eosinophils and thus worsening of the classical symptoms of chronic airway inflammatory diseases (Sajjan et al., 2008; Kast et al., 2017; Kim et al., 2018) . In addition, the expression of vasodilating factors and fluid homeostatic factors such as angiopoietin-like 4 (ANGPTL4) and bactericidal/permeabilityincreasing fold-containing family member A1 (BPIFA1) are also associated with viral infections and pneumonia development, which may worsen inflammation in the lower airway Akram et al., 2018) . These factors may serve as targets to prevent viral-induced exacerbations during the management of acute exacerbation of chronic airway inflammatory diseases.
Another recent area of interest is the relationship between asthma and COPD exacerbations and their association with the airway microbiome. The development of chronic airway inflammatory diseases is usually linked to specific bacterial species in the microbiome which may thrive in the inflamed airway environment (Diver et al., 2019) . In the event of a viral infection such as RV infection, the effect induced by the virus may destabilize the equilibrium of the microbiome present (Molyneaux et al., 2013; Kloepfer et al., 2014; Kloepfer et al., 2017; Jubinville et al., 2018; van Rijn et al., 2019) . In addition, viral infection may disrupt biofilm colonies in the upper airway (e.g., Streptococcus pneumoniae) microbiome to be release into the lower airway and worsening the inflammation (Marks et al., 2013; Chao et al., 2014) . Moreover, a viral infection may also alter the nutrient profile in the airway through release of previously inaccessible nutrients that will alter bacterial growth (Siegel et al., 2014; Mallia et al., 2018) . Furthermore, the destabilization is further compounded by impaired bacterial immune response, either from direct viral influences, or use of corticosteroids to suppress the exacerbation symptoms (Singanayagam et al., 2018 (Singanayagam et al., , 2019a Wang et al., 2018; Finney et al., 2019) . All these may gradually lead to more far reaching effect when normal flora is replaced with opportunistic pathogens, altering the inflammatory profiles (Teo et al., 2018) . These changes may in turn result in more severe and frequent acute exacerbations due to the interplay between virus and pathogenic bacteria in exacerbating chronic airway inflammatory diseases (Wark et al., 2013; Singanayagam et al., 2018) . To counteract these effects, microbiome-based therapies are in their infancy but have shown efficacy in the treatments of irritable bowel syndrome by restoring the intestinal microbiome (Bakken et al., 2011) . Further research can be done similarly for the airway microbiome to be able to restore the microbiome following disruption by a viral infection.
Viral infections can cause the disruption of mucociliary function, an important component of the epithelial barrier. Ciliary proteins FIGURE 2 | Changes in the upper airway epithelium contributing to viral exacerbation in chronic airway inflammatory diseases. The upper airway epithelium is the primary contact/infection site of most respiratory viruses. Therefore, its infection by respiratory viruses may have far reaching consequences in augmenting and synergizing current and future acute exacerbations. The destruction of epithelial barrier, mucociliary function and cell death of the epithelial cells serves to increase contact between environmental triggers with the lower airway and resident immune cells. The opening of tight junction increasing the leakiness further augments the inflammation and exacerbations. In addition, viral infections are usually accompanied with oxidative stress which will further increase the local inflammation in the airway. The dysregulation of inflammation can be further compounded by modulation of miRNAs and epigenetic modification such as DNA methylation and histone modifications that promote dysregulation in inflammation. Finally, the change in the local airway environment and inflammation promotes growth of pathogenic bacteria that may replace the airway microbiome. Furthermore, the inflammatory environment may also disperse upper airway commensals into the lower airway, further causing inflammation and alteration of the lower airway environment, resulting in prolong exacerbation episodes following viral infection.
Viral specific trait contributing to exacerbation mechanism (with literature evidence) Oxidative stress ROS production (RV, RSV, IFV, HSV)
As RV, RSV, and IFV were the most frequently studied viruses in chronic airway inflammatory diseases, most of the viruses listed are predominantly these viruses. However, the mechanisms stated here may also be applicable to other viruses but may not be listed as they were not implicated in the context of chronic airway inflammatory diseases exacerbation (see text for abbreviations).
that aid in the proper function of the motile cilia in the airways are aberrantly expressed in ciliated airway epithelial cells which are the major target for RV infection (Griggs et al., 2017) . Such form of secondary cilia dyskinesia appears to be present with chronic inflammations in the airway, but the exact mechanisms are still unknown (Peng et al., , 2019 Qiu et al., 2018) . Nevertheless, it was found that in viral infection such as IFV, there can be a change in the metabolism of the cells as well as alteration in the ciliary gene expression, mostly in the form of down-regulation of the genes such as dynein axonemal heavy chain 5 (DNAH5) and multiciliate differentiation And DNA synthesis associated cell cycle protein (MCIDAS) (Tan et al., 2018b . The recently emerged Wuhan CoV was also found to reduce ciliary beating in infected airway epithelial cell model (Zhu et al., 2020) . Furthermore, viral infections such as RSV was shown to directly destroy the cilia of the ciliated cells and almost all respiratory viruses infect the ciliated cells (Jumat et al., 2015; Yan et al., 2016; Tan et al., 2018a) . In addition, mucus overproduction may also disrupt the equilibrium of the mucociliary function following viral infection, resulting in symptoms of acute exacerbation (Zhu et al., 2009) . Hence, the disruption of the ciliary movement during viral infection may cause more foreign material and allergen to enter the airway, aggravating the symptoms of acute exacerbation and making it more difficult to manage. The mechanism of the occurrence of secondary cilia dyskinesia can also therefore be explored as a means to limit the effects of viral induced acute exacerbation.
MicroRNAs (miRNAs) are short non-coding RNAs involved in post-transcriptional modulation of biological processes, and implicated in a number of diseases (Tan et al., 2014) . miRNAs are found to be induced by viral infections and may play a role in the modulation of antiviral responses and inflammation (Gutierrez et al., 2016; Deng et al., 2017; Feng et al., 2018) . In the case of chronic airway inflammatory diseases, circulating miRNA changes were found to be linked to exacerbation of the diseases (Wardzynska et al., 2020) . Therefore, it is likely that such miRNA changes originated from the infected epithelium and responding immune cells, which may serve to further dysregulate airway inflammation leading to exacerbations. Both IFV and RSV infections has been shown to increase miR-21 and augmented inflammation in experimental murine asthma models, which is reversed with a combination treatment of anti-miR-21 and corticosteroids (Kim et al., 2017) . IFV infection is also shown to increase miR-125a and b, and miR-132 in COPD epithelium which inhibits A20 and MAVS; and p300 and IRF3, respectively, resulting in increased susceptibility to viral infections (Hsu et al., 2016 (Hsu et al., , 2017 . Conversely, miR-22 was shown to be suppressed in asthmatic epithelium in IFV infection which lead to aberrant epithelial response, contributing to exacerbations (Moheimani et al., 2018) . Other than these direct evidence of miRNA changes in contributing to exacerbations, an increased number of miRNAs and other non-coding RNAs responsible for immune modulation are found to be altered following viral infections (Globinska et al., 2014; Feng et al., 2018; Hasegawa et al., 2018) . Hence non-coding RNAs also presents as targets to modulate viral induced airway changes as a means of managing exacerbation of chronic airway inflammatory diseases. Other than miRNA modulation, other epigenetic modification such as DNA methylation may also play a role in exacerbation of chronic airway inflammatory diseases. Recent epigenetic studies have indicated the association of epigenetic modification and chronic airway inflammatory diseases, and that the nasal methylome was shown to be a sensitive marker for airway inflammatory changes (Cardenas et al., 2019; Gomez, 2019) . At the same time, it was also shown that viral infections such as RV and RSV alters DNA methylation and histone modifications in the airway epithelium which may alter inflammatory responses, driving chronic airway inflammatory diseases and exacerbations (McErlean et al., 2014; Pech et al., 2018; Caixia et al., 2019) . In addition, Spalluto et al. (2017) also showed that antiviral factors such as IFNγ epigenetically modifies the viral resistance of epithelial cells. Hence, this may indicate that infections such as RV and RSV that weakly induce antiviral responses may result in an altered inflammatory state contributing to further viral persistence and exacerbation of chronic airway inflammatory diseases (Spalluto et al., 2017) .
Finally, viral infection can result in enhanced production of reactive oxygen species (ROS), oxidative stress and mitochondrial dysfunction in the airway epithelium (Kim et al., 2018; Mishra et al., 2018; Wang et al., 2018) . The airway epithelium of patients with chronic airway inflammatory diseases are usually under a state of constant oxidative stress which sustains the inflammation in the airway (Barnes, 2017; van der Vliet et al., 2018) . Viral infections of the respiratory epithelium by viruses such as IFV, RV, RSV and HSV may trigger the further production of ROS as an antiviral mechanism Aizawa et al., 2018; Wang et al., 2018) . Moreover, infiltrating cells in response to the infection such as neutrophils will also trigger respiratory burst as a means of increasing the ROS in the infected region. The increased ROS and oxidative stress in the local environment may serve as a trigger to promote inflammation thereby aggravating the inflammation in the airway (Tiwari et al., 2002) . A summary of potential exacerbation mechanisms and the associated viruses is shown in Figure 2 and Table 1 .
While the mechanisms underlying the development and acute exacerbation of chronic airway inflammatory disease is extensively studied for ways to manage and control the disease, a viral infection does more than just causing an acute exacerbation in these patients. A viral-induced acute exacerbation not only induced and worsens the symptoms of the disease, but also may alter the management of the disease or confer resistance toward treatments that worked before. Hence, appreciation of the mechanisms of viral-induced acute exacerbations is of clinical significance to devise strategies to correct viral induce changes that may worsen chronic airway inflammatory disease symptoms. Further studies in natural exacerbations and in viral-challenge models using RNA-sequencing (RNA-seq) or single cell RNA-seq on a range of time-points may provide important information regarding viral pathogenesis and changes induced within the airway of chronic airway inflammatory disease patients to identify novel targets and pathway for improved management of the disease. Subsequent analysis of functions may use epithelial cell models such as the air-liquid interface, in vitro airway epithelial model that has been adapted to studying viral infection and the changes it induced in the airway (Yan et al., 2016; Boda et al., 2018; Tan et al., 2018a) . Animal-based diseased models have also been developed to identify systemic mechanisms of acute exacerbation (Shin, 2016; Gubernatorova et al., 2019; Tanner and Single, 2019) . Furthermore, the humanized mouse model that possess human immune cells may also serves to unravel the immune profile of a viral infection in healthy and diseased condition (Ito et al., 2019; Li and Di Santo, 2019) . For milder viruses, controlled in vivo human infections can be performed for the best mode of verification of the associations of the virus with the proposed mechanism of viral induced acute exacerbations . With the advent of suitable diseased models, the verification of the mechanisms will then provide the necessary continuation of improving the management of viral induced acute exacerbations.
In conclusion, viral-induced acute exacerbation of chronic airway inflammatory disease is a significant health and economic burden that needs to be addressed urgently. In view of the scarcity of antiviral-based preventative measures available for only a few viruses and vaccines that are only available for IFV infections, more alternative measures should be explored to improve the management of the disease. Alternative measures targeting novel viral-induced acute exacerbation mechanisms, especially in the upper airway, can serve as supplementary treatments of the currently available management strategies to augment their efficacy. New models including primary human bronchial or nasal epithelial cell cultures, organoids or precision cut lung slices from patients with airways disease rather than healthy subjects can be utilized to define exacerbation mechanisms. These mechanisms can then be validated in small clinical trials in patients with asthma or COPD. Having multiple means of treatment may also reduce the problems that arise from resistance development toward a specific treatment. | What is highlighted by the authors? | false | 3,860 | {
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2,669 | Frontiers in antiviral therapy and immunotherapy
https://doi.org/10.1002/cti2.1115
SHA: facbfdfa7189ca9ff83dc30e5d241ab22e962dbf
Authors: Heaton, Steven M
Date: 2020
DOI: 10.1002/cti2.1115
License: cc-by
Abstract: nan
Text: Globally, recent decades have witnessed a growing disjunction, a 'Valley of Death' 1,2 no less, between broadening strides in fundamental biomedical research and their incommensurate reach into the clinic. Plumbing work on research funding and development pipelines through recent changes in the structure of government funding, 2 new public and private joint ventures and specialist undergraduate and postgraduate courses now aim to incorporate pathways to translation at the earliest stages. Reflecting this shift, the number of biomedical research publications targeting 'translational' concepts has increased exponentially, up 1800% between 2003 and 2014 3 and continuing to rise rapidly up to the present day. Fuelled by the availability of new research technologies, as well as changing disease, cost and other pressing issues of our time, further growth in this exciting space will undoubtedly continue. Despite recent advances in the therapeutic control of immune function and viral infection, current therapies are often challenging to develop, expensive to deploy and readily select for resistance-conferring mutants. Shaped by the hostvirus immunological 'arms race' and tempered in the forge of deep time, the biodiversity of our world is increasingly being harnessed for new biotechnologies and therapeutics. Simultaneously, a shift towards host-oriented antiviral therapies is currently underway. In this Clinical & Translational Immunology Special Feature, I illustrate a strategic vision integrating these themes to create new, effective, economical and robust antiviral therapies and immunotherapies, with both the realities and the opportunities afforded to researchers working in our changing world squarely in mind.
Opening this CTI Special Feature, I outline ways these issues may be solved by creatively leveraging the so-called 'strengths' of viruses. Viral RNA polymerisation and reverse transcription enable resistance to treatment by conferring extraordinary genetic diversity. However, these exact processes ultimately restrict viral infectivity by strongly limiting virus genome sizes and their incorporation of new information. I coin this evolutionary dilemma the 'information economy paradox'. Many viruses attempt to resolve this by manipulating multifunctional or multitasking host cell proteins (MMHPs), thereby maximising host subversion and viral infectivity at minimal informational cost. 4 I argue this exposes an 'Achilles Heel' that may be safely targeted via host-oriented therapies to impose devastating informational and fitness barriers on escape mutant selection. Furthermore, since MMHPs are often conserved targets within and between virus families, MMHP-targeting therapies may exhibit both robust and broadspectrum antiviral efficacy. Achieving this through drug repurposing will break the vicious cycle of escalating therapeutic development costs and trivial escape mutant selection, both quickly and in multiple places. I also discuss alternative posttranslational and RNA-based antiviral approaches, designer vaccines, immunotherapy and the emerging field of neo-virology. 4 I anticipate international efforts in these areas over the coming decade will enable the tapping of useful new biological functions and processes, methods for controlling infection, and the deployment of symbiotic or subclinical viruses in new therapies and biotechnologies that are so crucially needed.
Upon infection, pathogens stimulate expression of numerous host inflammatory factors that support recruitment and activation of immune cells. On the flip side, this same process also causes immunopathology when prolonged or deregulated. 5 In their contribution to this Special Feature, Yoshinaga and Takeuchi review endogenous RNA-binding proteins (RBPs) that post-transcriptionally control expression of crucial inflammatory factors in various tissues and their potential therapeutic applications. 6 These RBPs include tristetraprolin and AUF1, which promote degradation of AU-rich element (ARE)-containing mRNA; members of the Roquin and Regnase families, which respectively promote or effect degradation of mRNAs harbouring stem-loop structures; and the increasingly apparent role of the RNA methylation machinery in controlling inflammatory mRNA stability. These activities take place in various subcellular compartments and are differentially regulated during infection. In this way, mRNA-destabilising RBPs constitute a 'brake' on the immune system, which may ultimately be toggled therapeutically. I anticipate continued efforts in this area will lead to new methods of regaining control over inflammation in autoimmunity, selectively enhancing immunity in immunotherapy, and modulating RNA synthesis and virus replication during infection.
Another mRNA under post-transcriptional regulation by Regnase-1 and Roquin is Furin, which encodes a conserved proprotein convertase crucial in human health and disease. Furin, along with other PCSK family members, is widely implicated in immune regulation, cancer and the entry, maturation or release of a broad array of evolutionarily diverse viruses including human papillomavirus (HPV), influenza (IAV), Ebola (EboV), dengue (DenV) and human immunodeficiency virus (HIV). Here, Braun and Sauter review the roles of furin in these processes, as well as the history and future of furin-targeting therapeutics. 7 They also discuss their recent work revealing how two IFN-cinducible factors exhibit broad-spectrum inhibition of IAV, measles (MV), zika (ZikV) and HIV by suppressing furin activity. 8 Over the coming decade, I expect to see an ever-finer spatiotemporal resolution of host-oriented therapies to achieve safe, effective and broad-spectrum yet costeffective therapies for clinical use.
The increasing abundance of affordable, sensitive, high-throughput genome sequencing technologies has led to a recent boom in metagenomics and the cataloguing of the microbiome of our world. The MinION nanopore sequencer is one of the latest innovations in this space, enabling direct sequencing in a miniature form factor with only minimal sample preparation and a consumer-grade laptop computer. Nakagawa and colleagues here report on their latest experiments using this system, further improving its performance for use in resource-poor contexts for meningitis diagnoses. 9 While direct sequencing of viral genomic RNA is challenging, this system was recently used to directly sequence an RNA virus genome (IAV) for the first time. 10 I anticipate further improvements in the performance of such devices over the coming decade will transform virus surveillance efforts, the importance of which was underscored by the recent EboV and novel coronavirus (nCoV / COVID-19) outbreaks, enabling rapid deployment of antiviral treatments that take resistance-conferring mutations into account.
Decades of basic immunology research have provided a near-complete picture of the main armaments in the human antiviral arsenal. Nevertheless, this focus on mammalian defences and pathologies has sidelined examination of the types and roles of viruses and antiviral defences that exist throughout our biosphere. One case in point is the CRISPR/Cas antiviral immune system of prokaryotes, which is now repurposed as a revolutionary gene-editing biotechnology in plants and animals. 11 Another is the ancient lineage of nucleocytosolic large DNA viruses (NCLDVs), which are emerging human pathogens that possess enormous genomes of up to several megabases in size encoding hundreds of proteins with unique and unknown functions. 12 Moreover, hundreds of human-and avian-infective viruses such as IAV strain H5N1 are known, but recent efforts indicate the true number may be in the millions and many harbour zoonotic potential. 13 It is increasingly clear that host-virus interactions have generated truly vast yet poorly understood and untapped biodiversity. Closing this Special Feature, Watanabe and Kawaoka elaborate on neo-virology, an emerging field engaged in cataloguing and characterising this biodiversity through a global consortium. 14 I predict these efforts will unlock a vast wealth of currently unexplored biodiversity, leading to biotechnologies and treatments that leverage the host-virus interactions developed throughout evolution.
When biomedical innovations fall into the 'Valley of Death', patients who are therefore not reached all too often fall with them. Being entrusted with the resources and expectation to conceive, deliver and communicate dividends to society is both cherished and eagerly pursued at every stage of our careers. Nevertheless, the road to research translation is winding and is built on a foundation of basic research. Supporting industry-academia collaboration and nurturing talent and skills in the Indo-Pacific region are two of the four pillars of the National Innovation and Science Agenda. 2 These frame Australia's Medical Research and Innovation Priorities, which include antimicrobial resistance, global health and health security, drug repurposing and translational research infrastructure, 15 capturing many of the key elements of this CTI Special Feature. Establishing durable international relationships that integrate diverse expertise is essential to delivering these outcomes. To this end, NHMRC has recently taken steps under the International Engagement Strategy 16 to increase cooperation with its counterparts overseas. These include the Japan Agency for Medical Research and Development (AMED), tasked with translating the biomedical research output of that country. Given the reciprocal efforts at accelerating bilateral engagement currently underway, 17 the prospects for new areas of international cooperation and mobility have never been more exciting nor urgent. With the above in mind, all contributions to this CTI Special Feature I have selected from research presented by fellow invitees to the 2018 Awaji International Forum on Infection and Immunity (AIFII) and 2017 Consortium of Biological Sciences (ConBio) conferences in Japan. Both Australia and Japan have strong traditions in immunology and related disciplines, and I predict that the quantity, quality and importance of our bilateral cooperation will accelerate rapidly over the short to medium term. By expanding and cooperatively leveraging our respective research strengths, our efforts may yet solve the many pressing disease, cost and other sustainability issues of our time. | What ways to solve the issues are outlined? | false | 4,126 | {
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1,584 | Viral and bacterial co-infection in severe pneumonia triggers innate immune responses and specifically enhances IP-10: a translational study
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5138590/
SHA: ef3d6cabc804e5eb587b34249b539c1b5efa4cc4
Authors: Hoffmann, Jonathan; Machado, Daniela; Terrier, Olivier; Pouzol, Stephane; Messaoudi, Mélina; Basualdo, Wilma; Espínola, Emilio E; Guillen, Rosa M.; Rosa-Calatrava, Manuel; Picot, Valentina; Bénet, Thomas; Endtz, Hubert; Russomando, Graciela; Paranhos-Baccalà, Gláucia
Date: 2016-12-06
DOI: 10.1038/srep38532
License: cc-by
Abstract: Mixed viral and bacterial infections are widely described in community-acquired pneumonia; however, the clinical implications of co-infection on the associated immunopathology remain poorly studied. In this study, microRNA, mRNA and cytokine/chemokine secretion profiling were investigated for human monocyte-derived macrophages infected in-vitro with Influenza virus A/H1N1 and/or Streptococcus pneumoniae. We observed that the in-vitro co-infection synergistically increased interferon-γ-induced protein-10 (CXCL10, IP-10) expression compared to the singly-infected cells conditions. We demonstrated that endogenous miRNA-200a-3p, whose expression was synergistically induced following co-infection, indirectly regulates CXCL10 expression by targeting suppressor of cytokine signaling-6 (SOCS-6), a well-known regulator of the JAK-STAT signaling pathway. Additionally, in a subsequent clinical pilot study, immunomodulators levels were evaluated in samples from 74 children (≤5 years-old) hospitalized with viral and/or bacterial community-acquired pneumonia. Clinically, among the 74 cases of pneumonia, patients with identified mixed-detection had significantly higher (3.6-fold) serum IP-10 levels than those with a single detection (P = 0.03), and were significantly associated with severe pneumonia (P < 0.01). This study demonstrates that viral and bacterial co-infection modulates the JAK-STAT signaling pathway and leads to exacerbated IP-10 expression, which could play a major role in the pathogenesis of pneumonia.
Text: Scientific RepoRts | 6:38532 | DOI: 10 .1038/srep38532 pathogenesis of several diseases and has been suggested as a potential biomarker of viral infection 10, 11 , late-onset bacterial infection in premature infants 12 , and a promising biomarker of sepsis and septic shock 13, 14 . Combined analysis of IP-10 and IFN-γ has also been reported as a useful biomarker for diagnosis and monitoring therapeutic efficacy in patients with active tuberculosis [15] [16] [17] , and both remain detectable in the urine of patients with pulmonary diseases in the absence of renal dysfunction 18 .
With airway epithelial cells 19 , resident alveolar macrophages (AMs) and blood monocytes-derived macrophages (recruited into tissues under inflammatory conditions 20, 21 ) represent a major line of defense against both pneumococcal (through their high phagocytic capacity [22] [23] [24] ) and influenza infection 25, 26 . So far, no studies have yet focused on the intracellular mechanisms that regulate IP-10 in human blood leukocytes during mixed IAV and SP infection. Several studies indicated that host non-coding small RNAs (including microRNAs) may function as immunomodulators by regulating several pivotal intracellular processes, such as the innate immune response 27 and antiviral activity 28, 29 ; both of these processes are closely related to toll-like receptor (TLR) signaling pathways.
In this study, we firstly investigated the in vitro intracellular mechanisms that mediate the innate immune response in IAV and/or SP infected human monocyte-derived macrophages (MDMs). Using this approach, we observed that mixed-infection of MDMs induces a synergistic production of IP-10 which can be related to a miRNA-200a/JAK-STAT/SOCS-6 regulatory pathway. Subsequently, in a retrospective analysis of clinical samples collected from children ≤ 5 years-old hospitalized with pneumonia, we confirmed that serum IP-10 level could be related to both viral and/or bacterial etiologies and disease severity.
Characteristics of MDMs infected by IAV and/or SP. Initially, we investigated in vitro the impact of single and mixed IAV and SP infection on MDMs. Firstly, active replication of IAV was assessed by qRT-PCR and quantification of new infectious viral particles in the cell supernatants ( Fig. 1a,b ). IAV titer increased over time after single infection with IAV and correlated with increased production of negative-strand IAV RNA. Maximum viral replication was observed at 18-24 hours post-infection, after which time both RNA replication and the quantity of infectious particles decreased. In this in vitro model, subsequent challenge of IAV-infected MDMs with SP had no significant impact on the production of new infectious viral particles (Fig. 1b) . Together, these results indicate permissive and productive infection of MDMs by IAV. Secondly, we evaluated whether MDMs are permissive for both IAV and SP infection. The presence of pneumococci within IAV-and SP-infected primary MDMs was confirmed at 8 h post-infection (Fig. 1c) , suggesting that MDMs are permissive for viral and bacterial co-infection in the early steps of infection. Importantly, confocal co-detection of mixed IAV and SP was only effective following 8 h post-infection due to the bactericidal impact of SP internalization within human macrophages (after 24 h, data not shown). Thirdly, we evaluated the impact of single and mixed infection with IAV and SP on MDM viability. Mixed infection significantly decreased cell viability (65.2 ± 4.5% total cell death at 48 hours post-infection; P < 0.0001) compared to single SP and IAV infection (39.6 ± 1.7% and 17.4 ± 1.1% total cell death, respectively; Fig. 1d ). Taken together, these results confirmed human MDMs are permissive to mixed viral and bacterial infection. mRNA, microRNA and protein expression profiling reveal an overall induction of the host innate immune response following IAV and/or SP infection of MDMs. To investigate the innate immune response orchestrated by IAV-and SP-infected human MDMs, we firstly evaluated the expression of 84 genes involved in the innate and adaptive immune responses (Table S1) ; the major differentially-expressed genes are summarized in Fig. 2a . Expression profiling indicated an overall induction of genes related to the JAK-STAT, NF-Κ β and TLR signaling pathways. Indeed, all interferon-stimulated genes (ISGs) screened, including CXCL10 (fold-change [FC] = 240.9), CCL-2 (FC = 34.2) and MX-1 (FC = 151.4) were upregulated following mixed infection compared to uninfected cells, most of which are closely related to STAT-1 (FC = 52.3), IRF-7 (FC = 6.8) and IFNB1 (FC = 5.2) also found upregulated in mixed infected cells. Secondly, we investigated the endogenous microRNA expression profiles of IAV-and SP-infected MDMs. A selection of microRNAs that were found to be differentially-expressed under different infection conditions are shown in Fig. 2b and Table S2 . MiRNA-200a-3p was overexpressed after both single IAV (FC = 6.9), single SP (FC = 3.7) and mixed IAV/SP infection (FC = 7.3), indicating this miRNA may play a role in the innate immune response to viral and bacterial co-infection. Similar miRNA-200a-3p dysregulation profiles were obtained following IAV and/or SP infections of human macrophages-like (THP-1 monocytes-derived macrophages) or primary MDMs (data not shown). Thirdly, the secreted levels of various antiviral, pro-inflammatory and immunomodulatory cytokines/chemokines were assayed in IAV-and SP-infected-THP-1 and primary MDM cell supernatants. We observed a remarkable correlation between the mRNA and protein expression profiles of single or mixed infected MDMs especially regarding CXCL-10 and IP-10 expression. Indeed, the level of IP-10 was synergistically increased in the supernatant of IAV-infected THP-1 MDMs exposed to SP (mean: 30,589 ± 16,484 pg ml −1 ) compared to single IAV infection (1,439 ± 566.5 pg ml −1 ) and single SP infection (4,472 ± 2,001 pg ml −1 ; P≤ 0.05; Fig. 2c ) at 24 hours after infection. In those cells, IP-10 expression reduced over time (48 to 72 hours), coinciding with a significant higher proportion of necrotic and apoptotic cells (Fig. 1d) . The synergistic expression of IP-10 was similarly observed at 24 hours post-infection using primary MDMs (Fig. 2d) . Significantly increased secretion of the other tested cytokines and chemokines was not observed post-infection, even in mixed infected MDMs (Fig. S1 ). Interestingly, a significant production of IP-10 was also observed in supernatants of primary human airway epithelial cells (HAEC) mixed-infected by IAV and SP compared to the single infections (Fig. 2e) . Taken together, the mRNA and protein profiling results suggested that mixed viral and bacterial infection of MDMs induces a synergistic pro-inflammatory response related to the type-1 interferon and JAK-STAT signaling pathways, with IP-10 as signature of IAV/SP co-infection. Among all microRNAs screened, miR-200a-3p was the most Scientific RepoRts | 6:38532 | DOI: 10.1038/srep38532 overexpressed in IAV/SP co-infection of human MDMs. In the remainder of this study, we decided to investigate the interconnection between miR-200a-3p expression and the innate immune response.
Endogenous miRNA-200a-3p expression correlates with CXCL10 (IP-10) induction following mixed IAV and SP infection of human MDMs. Using a specific Taqman probe assay targeting miR-200a-3p, we confirmed a significant upregulation of miR-200a-3p following mixed IAV and SP infection of human MDMs (Fig. 3a) . In this experiment, a more marked up-regulation of miR-200a-3p was observed following IAV+ SP compared to results obtained previously (Fig. 2b) . This discrepancy has been attributed to the use of two different approaches to quantify miR-200a-3p expression. The use of a target-specific stem-loop reverse transcription primer in Fig. 3a allows a better sensitivity of miR-200a-3p detection compared to the non-specific fluorescent dye used in Fig. 2b . As the general trend was suggestive of a synergistic induction of miR-200a-3p in response to mixed infection (Fig. 3a) , we hypothesized microRNA-200a-3p may play a role in the regulation of CXCL10 (IP-10), which was also synergistically upregulated in mixed-infected MDMs ( Fig. 2c and d) and primary HAEC ( Statistical analyses were performed using two-way ANOVA with Tukey's post-hoc test; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.
Scientific RepoRts | 6:38532 | DOI: 10.1038/srep38532 CXCL10 (Fig. 3d) . These results suggested miR-200a-3p indirectly regulates CXCL10 and led us to hypothesize that miR-200a-3p controls a potential repressor of the JAK-STAT signaling pathway. . At 18 h after transfection, the MDMs were singly or mixed infected as described previously. At 8 h post-IAV and/or SP infection, total mRNA was extracted and amplified by PCR using specific primers for the indicated genes. Values represent median ± IQR (a, c) or mean ± SEM (d, e) of three biological replicates. Statistical analyses were performed using a Kruskal-Wallis test (non-parametric, one-way ANOVA with Dunn's post-hoc test) for data presented in (a, c). An ordinary two-way ANOVA (with Tukey's post-hoc multiple comparison test) was used for data presented in (d, e). *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001. MiRNA-200a-3p indirectly regulates IP-10 expression by targeting SOCS6. As shown in Fig. 2a , several JAK-STAT signaling pathway genes were deregulated in mixed IAV-and SP-infected human MDMs; therefore, we hypothesized that miR-200a-3p directly regulates a regulator of the JAK-STAT signaling pathway. Predictive target analysis indicated that the 3' UTR of suppressor of cytokine signaling-6 (SOCS6) may be targeted by miR-200a-3p (Fig. 3b) . SOCS proteins constitute a class of negative regulators of JAK-STAT signaling pathways that are induced by both cytokines and TLR signaling. MiRNA-200a-3p was not predicted to target any of the other six members of the SOCS gene family. Transfection of human MDMs with MIM-200a downregulated SOCS6 (FC = 0.57) while inhibition of miR-200a-3p (INH-200a) upregulated SOCS6 (FC = 1.55), confirming that miR-200a-3p effectively regulates the expression of SOCS6 (Fig. 3e) . Moreover, SOCS6 was synergistically downregulated in IAV-or IAV/SP-infected MDMs overexpressing miRNA-200a (Fig. 3e) , suggesting that both infection and miR-200a-3p negatively regulate the expression of SOCS6. Finally, western blotting confirmed that expression of SOCS-6 sharply reduced following infection, especially after mixed IAV and SP infection (Fig. 3f) .
These results indicate miR-200a-3p is strongly induced in response to mixed viral and bacterial co-infection, which in turn leads to downregulation of the JAK-STAT regulator SOCS-6 at both the mRNA and protein levels and subsequent upregulation of IP-10.
analyses demonstrated mixed IAV and SP infection of human MDMs and HAEC induced significant production of IP-10. As blood leukocytes and respiratory tract epithelial cells actively contribute to inflammation during pneumonia, we hypothesized the level of IP-10 in serum of patient with pneumonia may be both indicative of mixed respiratory infection and disease severity. As part of a prospective, hospital-based, multicenter case-control study on the etiology of pneumonia among children under 5-years-old, a total of 74 patients (44 male, 30 female) were included in this pilot evaluation. According to WHO guidelines, retrospective analysis indicated 44 (59.5%) children had clinical signs of non-severe pneumonia and 30 (40.5%) children had signs of severe pneumonia. The main patient characteristics at inclusion are shown in Table 1 . Patients with severe pneumonia had significant more recorded episodes of dyspnea (P < 0.001), cyanosis (P = 0.03), lower chest indrawing (P < 0.001), dullness to percussion (P < 0.001) and lethargy (P < 0.001) during chest examination than patient with non-severe pneumonia. Moreover, pleural effusions were significantly more observed among critically ill patients and the duration of hospitalization was significantly longer for the children with severe pneumonia than for those with non-severe pneumonia (P = 0.0015). Two deaths occurred within the group of children retrospectively defined with severe pneumonia. Evaluation of the systemic inflammatory response of the 74 cases is shown in Table 2 . Serum level of CRP, IP-10, PCT, G-CSF, IL-6, IL-8 and MIP-1β were significantly more elevated in serum samples from critically ill patients. Patients with severe pneumonia had significantly higher (4.2-fold) serum IP-10 levels than those with a non-severe pneumonia (P < 0.001) suggesting IP-10 as a promising prognostic marker in pneumonia. Diagnostic accuracy measures for predicting pneumonia severity using blood-based biomarkers are summarized in Table S3 . Briefly, in this study, the optimal IP-10 cut-off value for identifying patient with severe pneumonia was 4,240 pg ml −1 , with an area under the receiver operating characteristic curve of 0.69 (95% CI, 0.57 to 0.82, P < 0.001). Defining as positive a serum IP-10 level above this cut-off resulted in a sensitivity of 63.3%, specificity of 63.6% and a positive likelihood ratio of 1.74. Prognostic values of IP-10 were closed to procalcitonin (PCT; AUC = 0.70; 95% IC, 0.58 to 0.82, P < 0.001) and IL-6 (AUC = 0.70; 95% IC, 0.58-0.83, P < 0.001).
Multiplex PCR-based screening of respiratory and blood samples reveal a high variety of pathogen associations (Table 3) . Respiratory viruses were detected in the nasal aspirates (NAs) of 63/74 patients (85.1%). Etiological bacteria of pneumonia (S. pneumoniae, n = 19; S. aureus, n = 1; or H. influenzae type B, n = 7) were identified via real-time PCR in the blood samples of 27/74 (36.5%) of the patients. Multiplex PCR assays allowed the identification of respiratory bacteria in the blood of 19 patients with negative blood culture results. Among the 74 cases PCR-positive for respiratory pathogens, a single virus or bacteria were detected in the NAs of 7 (9.4%) and 3 (4.0%) patients, respectively; these 10/74 (13.5%) cases were defined as the single infection group. The mixed infection group included the 62/74 (83.8%) cases in which (1) multiple viruses and/or bacteria were identified in NAs (38/74; 51.3%) without any bacteria identified in blood samples or (2) one or more viruses and/or bacteria were identified in NAs and associated with a blood bacteremia (24/74; 32.4%). We evaluated whether IP-10 serum level could correlate with the viral and bacterial etiologies of pneumonia. Patients with mixed infection had significant higher (3.6-fold) IP-10 serum level than patient with single detection (P = 0.03; Table 4 ). A stratified analysis reveals that the highest IP-10 serum level was observed among patients with both several respiratory pathogens identified (mixed-detection group) and severe pneumonia (14,427 pg ml −1 , IQR (3,981-82,994). In detail, a remarkable IP-10 serum level (142,531 pg ml −1 ), representing 33-fold higher above cut-off value predicting pneumonia severity was observed in patient with hRV in NA co-detected with S. pneumoniae (serotype 14) in pleural effusion and blood. In concordance with our in-vitro model of co-infection, a significant IP-10 level (90,338 pg ml −1 ) was quantified in blood sample of patient with severe bacteremic pneumococcal (serotype 14) pneumonia with a positive co-detection of Influenza B virus in NA. Taken together, these results suggest that high serum IP-10 levels are significantly associated with mixed viral and bacterial detection and also related to pneumonia pathogenesis.
This study provides additional in vitro and clinical data to improve our understanding of the immunopathology of mixed viral and bacterial pneumonia (Fig. 4) .
The in vitro model of influenza and pneumococcal superinfection of human MDMs demonstrated that mixed infection synergistically induced release of the pro-inflammatory chemokine IP-10, strongly suggesting human Scientific RepoRts | 6:38532 | DOI: 10.1038/srep38532 blood leukocytes contribute to the immunopathology of pneumonia. Additionally, transcriptomics and omics analyses provided new data on the inflammatory pathways that are activated during mixed infection and related to synergistic induction of the pro-inflammatory chemokine IP-10 in mixed infected cells. Our observations are consistent with a recent study describing IP-10 induction as host-proteome signature of both viral and bacterial infections 30 . Of the differentially-expressed genes observed in mixed infected MDMs, the transcription factors STAT-1 and IRF-7 appear to play crucial roles in the regulation of interferon-stimulated genes including CXCL10 (IP-10). By focusing on the intracellular mechanisms that regulate inflammatory pathways, we demonstrated a novel role for miRNA-200a-3p in the regulation of CXCL10 (IP-10). These observations are consistent with previous reports showing that RNA virus infection upregulates miR-155 in macrophages and dendritic cells and also regulates suppressor of cytokine signaling 1 (SOCS1), suggesting the existence of a miRNA/JAK-STAT/SOCS regulatory pathway during viral infection 29 . Our study suggests co-infection leads to overexpression of miR-200a-3p, which in turn targets and downregulates the JAK-STAT regulator SOCS-6 and consequently increases CXCL10 (IP-10) expression. Interestingly, a complementary in-silico approach reveals that several microRNAs that were found dysregulated in our experiments of IAV and SP co-infection of MDMs or HAEC, might target several genes of SOCS family and play similar role than miR-200a-3p. Indeed, miRNA-142-3p might target SOCS4, 5, 6 mRNA while miRNA-194-5p might target SOCS2, 3, 4, 5 and 7 mRNA. These observations underline that intra-cellular regulation of IP-10 is not limited to the contribution of a sole microRNA. A complex inter-relationship between numerous host microRNAs and inhibitors of the JAK-STAT signaling pathway occur to control host innate inflammatory response against viral and/or bacterial infections. Clinically, the majority of pediatric CAP cases in this study were associated with both positive viral and/or bacterial detection. Respiratory microorganisms were detected in 97% of cases; 51.3% of which were viral-viral, viral-bacterial or bacterial-bacterial co-detected only in nasal aspirates, 32.4% of which co-detected in both nasal aspirates and blood samples. These data are consistent with previous etiological studies of pediatric CAP 3,31-33 . S. pneumoniae was the major bacteria identified in blood (19/74; 25.7%) and mainly co-detected with respiratory viruses in NAs (16/19; 84.2%). We observed a very high diversity of viral and bacterial associations in biological samples from children with pneumonia. In comparison with IAV and SP14 combination evaluated in-vitro, no pneumonia cases were singly influenza and pneumococcus infected, and no similar co-detection with those two pathogens has been clinically observed. Nevertheless, Influenza B (IVB) virus was identified in 5 patients and two of them had a positive SP co-detection in blood (one non-typable strain and one serotype 14 using our molecular typing test). IVB and SP14 combination seems to be the nearest pathogen co-detection to that in-vitro investigated. Clinically, this co-detection was associated with both a very high IP-10 expression and a very severe pneumonia case definition. Interestingly, our translational pilot evaluation reveals IP-10 expression can be induced by several different viral and/or bacterial combinations. As immune response to each pathogen is different, further in-vitro investigations using different pathogens associations are needed to better characterize the mechanisms involved in the immunopathology of pneumonia.
In this cohort, highest serum IP-10 levels were identified among patients with both several pathogen detected and severe pneumonia, suggesting a significant role of IP-10 on pneumonia pathogenesis. Indeed, high plasma levels of IP-10 have previously been reported in patients with sepsis 12 , and were associated with high mortality rate, especially among patients with CAP 34 . Additionally, the IP-10-CXCR3 axis has been related to acute immune lung injury and lymphocyte apoptosis during the development of severe acute respiratory syndrome (SARS) 35, 36 . Moreover, an in vivo study that modeled influenza and pneumococcal superinfection in mice indicated that pro-inflammatory chemokines, including IP-10, play a crucial role in influenza-induced susceptibility to lung neutrophilia, severe immunopathology and mortality 37 . In this study, markedly elevated IP-10 (92,809 pg ml −1 ) combined with the highest PCT level (74.4 pg ml −1 ) were quantified in the serum sample of a child who died, in whom S. pneumoniae (serotype 9 V) was identified in the blood (PCR and blood culture) and co-detected with Haemophilus influenzae type B in nasal aspirate. These observations suggest an interrelationship between co-detection, elevated serum IP-10 and the pathogenesis of pneumonia.
Several limitations of this pilot translational study need to be acknowledged before concluding mixed infection is related to elevated IP-10 and disease severity. Indeed, although viral shedding (e.g., of HRV and HBoV) is common in asymptomatic children, we were unable to evaluate the levels of immunomodulators in the serum samples of a control group. Moreover, although the samples were collected within the first 24 hours after admission, only a single blood sample was processed for each patient. Therefore, a larger, longitudinal study on the etiology and severity of pneumonia will be necessary to confirm these results. In conclusion, the present findings suggest that mixed respiratory infections and IP-10 may play major, interconnected roles in the pathogenesis of pneumonia. Clinically, assessment and monitoring of induced IP-10 serum level may assist clinicians to improve diagnosis and patient management of severe community-acquired pneumonia.
Viral and bacterial strains. The 10 ng ml −1 M-CSF (Miltenyi Biotec). THP− 1 MDMs were obtained by culturing cells with 10 ng ml -1 phorbol myristate acetate (PMA; Invivogen, Toulouse, France) for 72 hours. Human airway epithelial cells (HAEC, bronchial cell type) originated from a 54-years old woman with no pathology reported (batch number MD056501) were provided by Mucilair (Epithelix, Geneva, Switzerland). Sterility, tissue integrity (TEER), mucus production and cilia beating frequency have been certified by the company. Gene expression profiling. Total cellular mRNA was purified using the RNeasy kit (Qiagen, Hilden, Germany). Reverse-transcription of total mRNA was performed using the RT 2 First Strand Kit (SABiosciences, Hilden, Germany). The expression of 84 genes involved in the human innate and adaptive immune responses was evaluated using the RT 2 profiler ™ PCR Array (SABiosciences) according to the manufacturer's recommendations. The Δ Δ Ct method was applied to calculate the fold changes in gene expression for each gene relative to uninfected control cells using the web-based RT 2 profiler PCR Array Data Analysis software (SABiosciences).
MicroRNA profiling array. Total cellular microRNAs were purified using the miRNeasy Mini kit (Qiagen) and reverse-transcribed using the miScript Reverse Transcription kit (Qiagen). The profiling of 84 miRNAs was performed using the Human Immunopathology miScript miRNA PCR Array kit (Qiagen) according to the manufacturer's instructions. Data were analyzed using the miScript miRNA PCR array data analysis web portal.
In silico miRNA target prediction. MiRNA target genes were retrieved and compiled using TargetScan 38 and microRNA.org resource 39 . The interactions between miRNAs and intracellular pathways were predicted using DIANA-miRPath v2.0 40 .
THP-1 MDMs were seeded in 24-well plates (0.5 × 10 6 per well) in triplicate, exposed to Influenza A H1N1 (A/Solomon islands/3/2006) virus (IAV) under serum-free conditions for 1 hour and then cultured for 3 hours in fresh RPMI-1640 containing 2% FBS. Streptococcus pneumoniae (SP) serotype 14 was added at 4 hours after IAV infection. Gentamicin (10 μ g ml −1 ) was added 2 hours after SP infection (i.e. 6 hours post-influenza infection) and maintained in the culture media throughout the experiment to kill extracellular bacteria and limit bacterial growth. Cell viability was determined by flow-cytometry using the FITC/Annexin V apoptosis detection kit (BD Biosciences), according to the manufacturer's instructions. #4427975) . In this assay, fold changes have been defined by the Δ Δ Ct method using control RNU-44 and -48 as reference microRNAs. Total mRNA was purified from transfected and infected MDMs using the RNeasy kit (Qiagen) and specific primers were used to amplify transforming growth factor beta-2 (TGFB2; F: 5′ -CCATCCCGCCCACTTTCTAC-3′ , R: 5′ -AGCTCAATCCGTTGTTCAGGC-3′ ), SOCS6 (F: 5′ -AAGAATTCATCCCTTGGATTAGGTAAC-3′ , R: 5′ -CAGACTGGAGGTCGTGGAA-3′ ) 41 43 , and 3) absence of wheezing at auscultation, and, 4) first symptoms appearing within the last 14 days, and 5) radiological confirmation of pneumonia as per WHO guidelines 44 . Based on these primary criteria defining pneumonia cases, all 74 cases were retrospectively re-evaluated according to the WHO "Pocket book of hospital care for children" 45 criteria to evaluate pneumonia severity. Cases that died during the study, or who had at least one additional clinical signs including central cyanosis, dullness to percussion during chest examination, prostration/lethargy, pleural effusion observed on chest radiography were retrospectively included in the severe pneumonia group. Patients without any of these additional clinical signs were included in the non-severe pneumonia group. Table 4 . a IP-10 values are expressed in pg ml -1 . IP-10 concentration differences between groups were compared using unpaired Mann-Whitney tests; significant changes (P < 0.05) are in bold. Clinical and molecular analysis. Nasopharyngeal aspirates (NAs) and whole blood samples were collected from children within 24 hours of admission. Whole blood samples were used for complete blood counts, blood culture and multiplex real-time PCR to identify Staphylococcus aureus, Streptococcus pneumoniae and Haemophilus influenzae type B 46 . S. pneumoniae serotypes were defined using a 11 multiplex real-time PCR assay targeting the 40 most frequently represented serotypes or serogroups according to protocol developed by Messaoudi et al. 47 . Serum C-reactive protein (CRP; AssayPro, St. Charles, Missouri, United States) and Procalcitonin (PCT; VIDAS B.R.A.H.M.S; bioMérieux) were quantified from whole-blood samples. Multiplex real-time non quantitative PCR (Fast-Track Diagnostic, Sliema, Malta) was used to detect 19 viruses and five bacteria in the respiratory specimens (NAs and pleural effusions). Mixed detection was defined as 1) PCR-positive for multiple viruses in NAs, 2) positive blood culture or PCR-positive for multiple bacteria in blood or 3) PCR-positive for one or multiple viruses in NAs and one or multiple bacteria in blood (identified by PCR and blood culture).
Ethical approval. The study protocol, informed consent statement, clinical research form, any amendments and all other study documents were submitted to and approved by the Ethical Committee of the Instituto de Investigaciones en Ciencias de la Salud, the Universidad Nacional de Asunción (IICS-UNA) and the Hospital Pediátrico Niños de Acosta Ñu. Informed consent was obtained from all subjects involved in this study. The clinical investigation was conducted according to the principles expressed in the Declaration of Helsinki.
Statistical analysis. The Chi-square test and Fisher's exact test were used to compare categorical variables; continuous variables and non-normally distributed data were compared using the Mann-Whitney U-test; normally distributed data were compared using unpaired t-tests. Comparative analyses between experimental conditions (i.e., MOCK, IAV, SP or IAV + SP) were performed using one-way ANOVA with Tukey's post-hoc test or Kruskal-Wallis analysis with Dunn's post-hoc tests. Receiver operating curve (ROC) analysis was used to determine the optimal cut-off value for IP-10 to differentiate between non-severe and severe pneumonia cases. P < 0.05 was considered statistically significant. All statistical analyses were performed using GraphPad Prism (La Jolla, California, United States). | What cell types help prevent pneumococcal and influenza infection in the lungs? | false | 5,216 | {
"text": [
"airway epithelial cells 19 , resident alveolar macrophages (AMs) and blood monocytes-derived macrophages"
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2,628 | Haunted with and hunting for viruses
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7089303/
SHA: c51c4f6146d0c636bc4dc3839c16b9e3ef52849a
Authors: Gao, George Fu; Wu, Ying
Date: 2013-08-07
DOI: 10.1007/s11427-013-4525-x
License: cc-by
Abstract: nan
Text: pecially with next-generation sequencing (NGS) for new virus genome discovery, e.g., Ruben Donis et al. [10] sequenced a bat-derived influenza virus genome by using NGS in 2012, raising a serious question as to whether or not our seasonal or pandemic flu might have another reservoir host. Chen and colleagues [11] confirmed the SFTSV independently by using NGS. Indeed, metagenomics analysis has yielded a great deal of new viruses, especially from the environment. Our actively hunting for new viruses has made some significant contributions for our understanding of virus ecology, pathogenesis and interspecies transmission.
Science China Life Sciences has focused on this hot topic in the event of the H7N9 outbreak after a comprehensive overview of the topic addressing HPAIV H5N1 in 2009 in the journal [12] [13] [14] . In this issue, six groups have been invited to present their recent findings on the emerging viruses, in addition to a previous report on H7N9 [3] .
Shi [15] reviewed recent discoveries of new viruses or virus genomes from bat. Bat is believed to harbor many more viruses than we ever thought as a reservoir host or even a susceptible host [16] . After the SARS-CoV virus, we have been actively seeking for new coronaviruses from bat and have yielded many of them, including potential human infecting HKU-1, 4, 5 and 9 [17, 18] . Recent MERS-CoV infection is another example for severe disease caused by used-to-be-less pathogenic coronaviruses. Shi and colleagues [19] by using NGS have discovered many unknown animal viruses from bat, especially some important paramyxoviruses and reoviruses. Filovirus has also been identified in bat with potential severe outcomes. Lyssaviruses (with many genotypes, including rabies virus) in the Rhabdoviridae family have been linked with severe fatal human cases, even in the developed countries, including Australia, with the bites of bats in the city [20, 21] . The potential roles of these viruses in bats for interspecies transmission are yet to be elucidated.
Tan and colleagues [22] specifically focused on the newly-emerged MERS-CoV. The virus was identified in 2012 in the Middle East with some exported cases to Europe. In 2013 the virus has been re-emerging and expanding its borders to more European countries. In the initial diagnosis, the pan-coronavirus real-time reverse transcription polymerase chain reaction (RT-PCR) assay played a very important role for the identification of the causative agents. By using this method, scientists detected an expected-size PCR fragment for the corresponding conserved region of ORF1b of the replicase gene of a coronavirus. This is another example that molecular biology methods played for the discovery of new pathogens. Soon the receptor used by MERS-CoV to enter the host cells was identified [23] and the molecular basis of the receptor binding to the virus was also elucidated recently [8] .
Enterovirus has been known as serious human pathogens for a long time but their significance to the public health has been emphasized by the emergence of enterovirus 71 in 1998 as a serious pathogenic agents for children in Taiwan [24] and re-emerged in mainland China in 2008 [25] . In this issue, Duan and colleagues [26] summarized the findings of new enteroviruses by using NGS. Because of the application of new NGS technology they also challenged the Koch's postulates. A new model of Koch's postulates, named the metagenomic Koch's postulates, has provided guidance for the study of the pathogenicity of novel viruses. The review also provided a detailed description of the NGS and related molecular methods for the virus discovery followed by a list of new enteroviruses found in human feces. These include viruses in the family of Piconaviridae, Parvoviridae, Circoviridae, Astroviridae and Polyomaviridae.
Yu Xue-Jie and colleagues [27] reviewed the new bunyavirus, SFTSV, identified in China. As the virus discoverers, they have overviewed the whole process of the discovery, which is helpful and meaningful for the new virus discoveries in the future. The disease caused by SFTSV, with a CFR of 12%, had been in China for a couple of years before the causative agent was finally identified. There are still a lot of questions remained unknown for this new virus and vigorous studies are in great need. The transmission route of the virus has not been clarified but tick as vector is suspected. Domestic and wild animals, e.g., goats, boars, cattle and dogs, are believed to be the virus-amplifying hosts. Therefore the effective control measures are still under evaluation. Vaccines protecting the SFTSV infection are under its way in Chinese Center for Disease Control and Prevention. Recently a similar virus has been identified in both Japan and USA (a new name of Heartland virus was proposed for the US virus) [9] .
In addition to new viruses infecting human beings, some new viruses infecting animals but their public health significance needing to be further evaluated, have also been discovered. The new flavivirus, duck egg-drop syndrome virus (DEDSV), is a good example. Su and colleagues [28] reviewed the characterization of the DEDSV and its disease form in this issue. The virus was found closely-related to a long-time-known virus, Tembusu virus [29, 30] . Initially, the disease was only found in egg-raising ducks but soon it was found in pigeons, chickens and geese [31, 32] . Yet the transmission vector, though mosquitoes are suspected, has not been identified. Due to the public health concerns of its related viruses, potential human infection of DEDSV should be evaluated.
Research on insect viruses is reviving in recent years. In this issue, Zhou and colleagues [33] reviewed the newly-identified insect viruses in China. Insects are the largest group of animals on the Earth therefore they also carry many more viruses. Studies on these viruses can provide useful knowledge for our understanding about animal or human infecting viruses. More importantly, modification and application of insect-infecting viruses can be used as effective biologicals for the control of insect pest. The new viruses identified include Wuhan nodavirus (WhNV), a member of family Nodaviridae; Dendrolimus punctatus tetravirus (DpTV), a new member of the genus Omegatetravirus of the family Alphatetravirida; Ectropis obliqua picorna-like virus (EoV), a positive-strand RNA virus causing a lethal granulosis infection in the larvae of the tea looper (Ectropis obliqua), the virus a member of the Flaviridae family.
While we are enjoying ourselves with the civilization of modern societies, the ecology has ever been changing. Human beings encounter more ecology-climate-changing problems, including the zoonotic pathogens. We have to face some unknown pathogenic agents passively. To get ourselves well prepared we also ought to actively hunt for unknown pathogens. Prediction and pre-warning can only be realized by knowing more about the unknown. This is especially true for infectious agents. | Which bat virus have been found to be linked with diseases? | false | 3,849 | {
"text": [
"potential human infecting HKU-1, 4, 5 and 9 [17, 18] . Recent MERS-CoV infection is another example for severe disease caused by used-to-be-less pathogenic coronaviruses. Shi and colleagues [19] by using NGS have discovered many unknown animal viruses from bat, especially some important paramyxoviruses and reoviruses. Filovirus has also been identified in bat with potential severe outcomes. Lyssaviruses (with many genotypes, including rabies virus) in the Rhabdoviridae family have been linked with severe fatal human cases, even in the developed countries, including Australia, with the bites of bats in the city [20, 21] ."
],
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1,548 | The First Detection of Equine Coronavirus in Adult Horses and Foals in Ireland
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6832964/
SHA: eee5a9068ade4c6776f189045115a90a5785e983
Authors: Nemoto, Manabu; Schofield, Warren; Cullinane, Ann
Date: 2019-10-14
DOI: 10.3390/v11100946
License: cc-by
Abstract: The objective of this study was to investigate the presence of equine coronavirus (ECoV) in clinical samples submitted to a diagnostic laboratory in Ireland. A total of 424 clinical samples were examined from equids with enteric disease in 24 Irish counties between 2011 and 2015. A real-time reverse transcription polymerase chain reaction was used to detect ECoV RNA. Nucleocapsid, spike and the region from the p4.7 to p12.7 genes of positive samples were sequenced, and sequence and phylogenetic analyses were conducted. Five samples (1.2%) collected in 2011 and 2013 tested positive for ECoV. Positive samples were collected from adult horses, Thoroughbred foals and a donkey foal. Sequence and/or phylogenetic analysis showed that nucleocapsid, spike and p12.7 genes were highly conserved and were closely related to ECoVs identified in other countries. In contrast, the region from p4.7 and the non-coding region following the p4.7 gene had deletions or insertions. The differences in the p4.7 region between the Irish ECoVs and other ECoVs indicated that the Irish viruses were distinguishable from those circulating in other countries. This is the first report of ECoV detected in both foals and adult horses in Ireland.
Text: Equine coronavirus (ECoV) is a positive-stranded RNA virus and belongs to the species Betacoronavirus 1 in the genus Betacoronavirus [1, 2] . The clinical signs associated with ECoV infection during outbreaks in the USA [3] and Japan [4] [5] [6] were fever, anorexia, lethargy and diarrhoea. The same clinical signs were also recorded in an experimental challenge study using Japanese draft horses [7] . The main transmission route is considered to be faecal-oral [7] and ECoV is usually detected in faecal samples. However, the molecular detection of ECoV in faeces from horses with diarrhoea, does not prove causation. Coronaviruses can cause both enteric and respiratory disease in many avian and mammalian species but ECoV is less likely to be found in respiratory secretions than in faeces [8, 9] .
Both molecular and seroepidemiology studies suggest that ECoV may be more prevalent in the USA than in other countries [10] . ECoV was detected in samples collected from equids in 48 states of the USA [11] . In central Kentucky, approximately 30% of both healthy and diarrheic Thoroughbred foals were infected with ECoV [12] . All of the qPCR positive foals with diarrhoea were co-infected with other pathogens such as rotavirus or Clostridium perfringens, suggesting that there was potential for ECoV to be over-diagnosed as a causative agent in complex diseases. In contrast in Japan, although an outbreak of diarrhoea occurred among ECoV-infected draft horses at one racecourse [4] [5] [6] , there have been no similar outbreaks subsequently, and all rectal swabs collected from diarrheic Thoroughbred foals were negative. Furthermore, only 2.5% of the rectal swabs collected from healthy foals in the largest Thoroughbred horse breeding region in Japan were positive for ECoV [13] . In France, 2.8% of 395 faecal samples and 0.5% of 200 respiratory samples collected in 58 counties tested positive for ECoV [9] . Similar to the reports from Japan and France, a low prevalence of ECoV was also observed in the UK [14] , Saudi Arabia and Oman [15] . The objective of this study was to investigate the presence of ECoV in clinical samples submitted to a diagnostic laboratory in Ireland. The samples were tested by real-time reverse transcription polymerase chain reaction (rRT-PCR) as it has been shown to be the most sensitive diagnostic method for ECoV [16] and is routinely employed as an alternative to virus isolation in diagnostic laboratories worldwide, both for timely diagnosis and in epidemiological studies [9, 10] . Virus isolation and biological characterisation were beyond the capacity of this study, which was similar in scope to that of the studies in horse populations in the USA, Europe and Asia [8, 9, 13, 14] . The rRT-PCR assay was performed as previously described using a primer set targeting the nucleocapsid (N) gene (ECoV-380f, ECoV-522r and ECoV-436p) [3] (Table 1) and AgPath-ID One-Step RT-PCR Kit (Thermo Fisher Scientific, MA, USA) according to the manufacturer's instructions. To prove that the extraction was successful and that there was no inhibition during rRT-PCR amplification, an internal positive control primer/probe (PrimerDesign, Southampton, UK) was added to the master mix. Thermal cycling conditions were; 48 • C for 10 min and 95 • C for 10 min, followed by 40 cycles at 94 • C for 15 s and 60 • C for 45 s. The SuperScript III One-Step RT-PCR System with Platinum Taq High Fidelity (Thermo Fisher Scientific, MA, USA) was used for sequencing analysis of two of the five ECoV samples identified. There was inadequate viral nucleic acid in the other three samples for sequencing. The primer sets used to amplify the nucleocapsid (N) gene [4] , the partial spike (S) gene [9] , and the region from the p4.7 to p12.7 genes of non-structural proteins (Oue, personal communication) are shown in Table 1 . The RT-PCR products were sequenced commercially by GATC Biotech (Cologne, Germany). Sequence analysis was performed using the BLAST and CLUSTALW programs, and Vector NTI Advance 11.5 software (Thermo Fisher Scientific, MA, USA). Phylogenetic analysis of nucleotide sequences was conducted with MEGA software Version 5.2 [17] . A phylogenetic tree was constructed based on nucleotide sequences of the K2+G (N gene) and TN93 (S gene) using the maximum likelihood method. MEGA software was used to select the optimal substitution models. Statistical analysis of the tree was performed with the bootstrap test (1000 replicates) for multiple alignments. The complete genome sequences of NC99 (EF446615) [2] , Tokachi09 (LC061272), Obihiro12-1 (LC061273) and Obihiro12-2 (LC061274) [1] , the N (AB671298) and S (AB671299) genes of Obihiro2004, the N gene of Hidaka-No.61/2012 (LC054263) and Hidaka-No.119/2012 (LC054264) [13] , the S gene of ECoV_FRA_2011/1 (KC178705), ECoV_FRA_2011/2 (KC178704), ECoV_FRA_2012/1 (KC178703), ECoV_FRA_2012/2 (KC178702) and ECoV_FRA_2012/3 (KC178701) [9] were used in sequence and/or phylogenetic analysis.
The accession numbers registered in GenBank/EMBL/DDBJ are as follows: the complete sequences of the N gene; 11V11708/IRL (LC149485) and 13V08313/IRL (LC149486), the partial sequences of the S gene; 11V11708/IRL (LC149487) and13V08313/IRL (LC149488) and the complete sequences from the p4.7 to p12.7 genes; 11V11708/IRL (LC149489) and13V08313/IRL (LC149490). One six-week-old foal was the only clinical case on a public Thoroughbred stud farm with approximately 30 mares when it presented with diarrhoea. Recovery took over three weeks during which it received fluid therapy, probiotics, antiulcer medication and antibiotics. The second foal was a 14-day-old filly, which had been hospitalised with diarrhoea two days prior to sample collection. The foal responded well to supportive treatment and at the time of sample collection, the diarrhoea had resolved. The five ECoV positive samples tested negative for equine rotavirus.
The nucleotide sequences of the complete N gene, the partial S gene and the region from the p4.7 to p12.7 genes of two positive samples (11V11708/IRL/2011 and 13V08313/IRL/2013) were determined. The nucleotide identities of the N and S genes of the two Irish ECoVs were 99.8% (1338/1341 nucleotides) and 99.5% (650/653 nucleotides), respectively. The nucleotide identities of the N gene of the two Irish ECoVs and the ECoVs from other continents are summarised in Table 2 .
Phylogenetic analysis was performed for the nucleotide sequences of the complete N and partial S genes (Figure 1 ). The analysis for the N gene showed that Irish ECoVs were independently clustered although they were closely related to Japanese viruses identified after 2009. In the phylogenetic tree of the S gene, Irish ECoVs were closely related to all other ECoVs analysed.
The length of the region from the p4.7 to p12.7 genes in the two viruses was 544 base pairs. Compared with NC99, Irish ECoVs, had a total of 37 nucleotide deletions within p4.7 and the non-coding region following the p4.7 gene. Compared with Obihiro 12-1 and 12-2, Irish ECoVs had a three-nucleotide insertion. When compared with Tokachi09, the Irish ECoVs had a 148-nucleotide insertion (see Figure S1 ). The p12.7 gene of the two Irish ECoVs did not have deletions or insertions, and the nucleotide identities were 98.8-99.7% between these viruses and the other ECoVs (NC99, Tokachi09, Obihiro12-1 and Obihiro12-2).
This study provides the first report of ECoV circulating in Ireland, the third European country with a significant horse industry where the virus has been detected in horses with enteric disease. However, detection of ECoV in faeces samples from horses with enteric disease does not prove
This study provides the first report of ECoV circulating in Ireland, the third European country with a significant horse industry where the virus has been detected in horses with enteric disease. However, detection of ECoV in faeces samples from horses with enteric disease does not prove causation. In this study, 424 samples collected between 2011 and 2015 from equids with enteric disease were tested, and only five samples (1.2%) were positive for ECoV. The inclusion of an internal positive control in the rRT-PCR eliminated the possibility of false negative results due to the presence of PCR inhibitors but the high content of nucleases associated with faeces samples may have caused some RNA degradation. However, this low prevalence of ECoV is similar to that identified in France [9] and among Thoroughbred foals in Japan [13] .
Although ECoV has been identified on three continents, little is known about the genetic and pathogenic diversity in field viruses. In this study, sequence and phylogenetic analysis (Figure 1 ) demonstrated a high level of homology between viruses detected in a donkey and a horse in two provinces in Ireland in different years. This suggests that Irish ECoVs may have low genetic diversity. Compared with the ECoVs of other countries, the N, S and p12.7 genes of the two Irish viruses were highly conserved. In contrast, the region from p4.7 and the non-coding region following the p4.7 gene had deletions or insertions ( Figure S1 ). Because of polymorphism in this region, this region could be useful for epidemiological investigation [5] . The differences in the p4.7 region between the Irish ECoVs and other ECoVs indicated that the viruses in Ireland may be distinguishable from those circulating in other countries. The positive samples were collected in November (1), March (1) and April (3) in this study. Higher case numbers are identified in the USA during the colder months (October to April) [11] , and our results were consistent with the circulation period in USA. It has been reported that outbreaks mainly occurred among adult riding, racing and show horses in USA [11] . The choice of cases to include in the current study may not have been optimal for detection of ECoV as the majority of samples were from foals. However, two positive samples were collected from adult horses in a combined riding school/show jumping yard in the West of Ireland. At the time of sample collection in April 2013, the monthly mean temperatures were below long-term average and in parts of the West, were the coldest in 24 years [18] . Cold weather may have been a predisposing factor to the ECoV infection on the farm.
Two positive samples were collected from Thoroughbred foals. A faeces sample collected from one foal with severe watery diarrhoea and inappetance was positive for ECoV but a sample collected three days later tested negative. A potential difficulty in detecting ECoV from naturally infected horses has been noted previously as serial samples from seven sick horses in the USA suggested that ECoV only persisted for three to nine days in faeces [3] . In both cases, the diarrhoea may have been caused by other unidentified coinfecting pathogens as has been suggested by investigators in the USA [12] . This is the first report of ECoV detection in faeces samples from both foals and adult horses in Ireland. The viruses identified in Ireland are genetically closely related to the Japanese viruses and the results of this study give no indication of significant genetic or phenotypic diversity. In recent years, there has been an increase in awareness and testing for ECoV in the USA and elsewhere [10] . Horse breeding and racing activities in Ireland are the most prominent and important of any country on a per capita basis. There are over 50 Thoroughbred horses per 10,000 of population in Ireland, compared to between three and five for Great Britain, France and the USA [19] . Thus, an investigation of ECoV in Ireland is pertinent not only to increase awareness nationally of the epidemiology of the virus and promote discussion on its clinical importance, but also to inform the industry globally of the health status of Irish horses. Ireland exports horses all over the world. By illustration, in 2016 the country was the second biggest seller of bloodstock at public auctions second only to the USA [19] .
Many questions remain with regard to the clinical significance of ECoV. The outbreak at a draft-horse racetrack in Japan in 2009 affected 132 of approximately 600 horses and resulted in non-starters and the implementation of movement restrictions [4] . However, draft horses appear to have a higher infection rate than other breeds and an outbreak of similar severity has not been reported in Thoroughbred racehorses [10, 20] . The much higher incidence of ECoV positive Thoroughbred foals identified in Kentucky compared to similar populations internationally suggests an increased susceptibility to ECoV infection in that population. In the past, specific environmental factors were associated with extensive reproductive loss in the Kentucky area and to a lesser extent in other states [21] , but predisposing regional factors such as differences in management, environment or husbandry have not been identified for ECoV. It has been suggested that ECoV is a coinfecting agent in foals with diarrhoea and clinical infections have predominantly been reported in adult horses with a mono-infection with EcoV [10] . There was no indication from the results of this study that coronavirus is a major cause of diarrhoea in Irish horses but the introduction of rRT-PCR as a routine diagnostic test will assist in elucidating the significance of this virus to the Irish breeding, racing and sports industries. The primary focus in future will be on testing adult horses that present with anorexia, lethargy, fever and changes in faecal character as a significant association has been demonstrated between this clinical status and molecular detection of ECoV in faeces [11] . | Where have most outbreaks of equine coronavirus occurred in the United States? | false | 2,128 | {
"text": [
"adult riding, racing and show horses"
],
"answer_start": [
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} |
1,629 | The Intranasal Application of Zanamivir and Carrageenan Is Synergistically Active against Influenza A Virus in the Murine Model
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4459876/
SHA: f0b1fa4036434b57c8307d43c39a4193f7e8053a
Authors: Morokutti-Kurz, Martina; König-Schuster, Marielle; Koller, Christiane; Graf, Christine; Graf, Philipp; Kirchoff, Norman; Reutterer, Benjamin; Seifert, Jan-Marcus; Unger, Hermann; Grassauer, Andreas; Prieschl-Grassauer, Eva; Nakowitsch, Sabine
Date: 2015-06-08
DOI: 10.1371/journal.pone.0128794
License: cc-by
Abstract: BACKGROUND: Carrageenan is a clinically proven and marketed compound for the treatment of viral upper respiratory tract infections. As infections caused by influenza virus are often accompanied by infections with other respiratory viruses the combination of a specific anti-influenza compound with the broadly active antiviral polymer has huge potential for the treatment of respiratory infections. Thus, the combination of the specific anti-influenza drug Zanamivir together with carrageenan in a formulation suitable for intranasal application was evaluated in-vitro and in-vivo. PRINCIPAL FINDINGS: We show in-vitro that carrageenan and Zanamivir act synergistically against several influenza A virus strains (H1N1(09)pdm, H3N2, H5N1, H7N7). Moreover, we demonstrate in a lethal influenza model with a low pathogenic H7N7 virus (HA closely related to the avian influenza A(H7N9) virus) and a H1N1(09)pdm influenza virus in C57BL/6 mice that the combined use of both compounds significantly increases survival of infected animals in comparison with both mono-therapies or placebo. Remarkably, this benefit is maintained even when the treatment starts up to 72 hours post infection. CONCLUSION: A nasal spray containing carrageenan and Zanamivir should therefore be tested for prevention and treatment of uncomplicated influenza in clinical trials.
Text: The periodic appearance of new influenza variants poses a worldwide pandemic threat. Since the emergence of the new A(H7N9) virus, more than 400 human cases were reported to the WHO with a mortality rate of more than 35%. Most patients with A(H7N9) infections had contact with poultry or visited live animal markets. However, some sporadic cases seemed to be a result of human to human transmissions [1, 2] . In contrast to pandemic viruses which fulminantly enter the human population and cause high mortality rates, seasonal influenza viruses generally cause uncomplicated and transient infections in humans, with virus replication localized to the upper respiratory tract [3, 4] . However, in its fully developed form influenza is an acute respiratory disease resulting in hospitalizations and deaths mainly among high-risk groups. Worldwide, annual epidemics result in about three to five million cases of severe illness, and about 250,000 to 500,000 deaths [5] . For this reason WHO [6] and CDC [7] recommend antiviral treatment for any patient with suspected influenza who is at risk for influenza complications without previous laboratory confirmation.
It is known that influenza virus infections are often accompanied by other viral pathogens [8] . Depending on the detection method (qRT-PCR or immunofluorescence) different ratios of co-infections have been found. Analysis by qRT-PCR revealed that 54.5-83.3% of influenza A or B positive patients were found to have at least one concomitant respiratory viral infection [9] [10] [11] [12] . The detection frequency with immunofluorescence was found to be even higher (90-100%) [13, 14] . Potential concomitant viral pathogens of influenza virus infections include human rhinovirus (hRV), respiratory syncytial virus, adenovirus, human coronavirus, human metapneumovirus and parainfluenza virus [14, 15] .
As a result of the multiple infections, a specific anti-influenza mono-therapy treats the influenza virus infection only, but not the infection with the concomitant viral pathogen. Hence, the therapy often fails to sufficiently resolve symptoms. This is also reflected by the fact that neuraminidase inhibitors (NI) are highly efficacious in animal models investigating influenza mono-infections [16, 17] but show lower efficacy against influenza symptoms in clinical trials in adults with natural infections [18] . Therefore, there is a high medical need for a broadly acting antiviral therapy in combination with a specific anti-influenza therapy for treatment of patients suffering from upper respiratory tract symptoms. Ideally, the substances present in the combination complement each other by different modes of action, leading to a treatment that provides full protection against a broad range of different respiratory viruses as well as different influenza strains with a low probability to induce escape mutations.
One approach for a broad antiviral therapy is the creation of a protective physical barrier in the nasal cavity using carrageenan. Carrageenan is a high molecular weight sulfated polymer derived from red seaweed (Rhodophyceae) that has been extensively used in food, cosmetic and pharmaceutical industry and is generally recognized as safe by the FDA (GRAS) (reviewed in [19] ). Three main forms of carrageenans are commercially used: kappa, iota and lambda. They differ from each other in the degree of sulfation, solubility and gelling properties [20] . The antiviral mechanism of carrageenan is based on the interference with viral attachment; as a consequence, viral entry is inhibited [21, 22] . Its antiviral activity is dependent on the type of polymer as well as the virus and the host cells [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] and has been reviewed in [33] [34] [35] . We published that iota-carrageenan is a potent inhibitor of hRV [36] and influenza A [37] replication and demonstrated the antiviral efficacy of iota-carrageenan against common cold viruses by intranasal application in several randomized, double-blind, parallel group, placebo-controlled clinical trials [38] [39] [40] . The pooled analysis of two studies conducted in 153 children and 203 adults revealed that patients infected with any respiratory virus, who were intranasally treated with iota-carrageenan showed a 1.9 day faster recovery from common cold symptoms than placebo treated patients in the intention-to-treat population [41, 42] . The anti-influenza activity was shown by subgroup analysis of 49 influenza infected patients who benefited from a 3.3 days faster recovery from symptoms. The use of carrageenan nasal spray was associated with a significant reduction of the influenza viral load in nasal fluids and a significant increase in the number of virus free patients within the treatment period of 7 days. In good accordance Prieschl-Grassauer are co-founders of Marinomed Biotechnologie GmbH. Marinomed Biotechnologie GmbH had a role in study design, data collection and analysis, decision to publish, preparation of the manuscript and is financing the processing charge of the manuscript. with the literature [9] [10] [11] [12] [13] [14] we observed that the majority of influenza virus infected patients suffered from a concomitant respiratory viral infection (66%) as determined by real-time PCR. Carrageenan containing nasal sprays are already marketed for the treatment of respiratory viral infections under different brand names in 18 countries.
At present the only available effective drugs for treatment and post exposure prevention of influenza are the NI (Oseltamivir and Zanamivir worldwide; Peramivir in Japan and South Korea). Since the large-scale use of M2 blockers for prophylaxis and treatment in humans [43] and farming [44] , the currently circulating influenza viruses already lack sensitivity to this drug group [45] .
We have already shown an additive therapeutic effect of a combination therapy with intranasally applied iota-carrageenan and orally administered Oseltamivir in lethally H1N1 A/PR/ 8/34 infected mice and a treatment start 48 hours post infection (hpi) [37] .
Due to these very promising results we further developed the concept of combining carrageenan with an NI therapy. In contrast to Oseltamivir, which needs to be activated by metabolic conversion, Zanamivir is directly applied as active drug and can also be administered intranasally [46] [47] [48] [49] [50] [51] [52] . The potential of an intranasal administration of Zanamivir was investigated by GlaxoSmithKline. In seven clinical challenge trials 66 volunteers were infected with influenza B/Yamagata/16/88 and 213 with influenza A/Texas/36/91 (H1N1). 156 of these participants got intranasally applied Zanamivir at different doses (daily dose levels from 6.4 mg to 96 mg) for prophylaxis or therapy [46, 47, 53, 54] . These challenge trials showed that treatment starting before and up to 36 hours post virus inoculation was associated with prevention of laboratory confirmed influenza and febrile illness as well as a reduction in viral titers, duration of shedding and symptoms. In total, safety data from 1092 patients after intranasal application of Zanamivir were published and no evidence for Zanamivir induced adverse events or increased frequencies of local nasal intolerance in comparison to placebo groups was found [46, 49, 52] .
Taken together, the combination of a carrageenan nasal spray that provides broad antiviral activity against upper respiratory infections-including influenza-with Zanamivir, a specific anti-influenza drug, meets the existing medical need to treat multiple viral infections. In the present work we investigate the therapeutic effect of a combination of carrageenan and Zanamivir in-vitro and in an animal model.
Kappa-carrageenan and iota-carrageenan were purchased from FMC Biopolymers (Philadelphia, PA). The identity, purity (>95%) of carrageenan subtypes and the molecular weight (>100,000) was confirmed by NMR analysis as described elsewhere [55] and the presence of lambda-carrageenan was below the detection limit of 3%. The dry polymer powders were dissolved in aqua bidest (Fresenius Kabi, Austria) to a final concentration of 2.4 mg/ml iota-and 0.8 mg/ml kappa-carrageenan. This 2x stock solution was sterile filtered through a 0.22 μm filter (PAA, Switzerland) and stored at room temperature until use. For further testing the stock solution was diluted to a mixture containing 1.2 mg/ml iota-carrageenan and 0.4 mg/ml kappa-carrageenan (hereinafter referred to as "carrageenan").
Zanamivir was purchased as powder (Haosun Pharma, China) and the identity and purity was confirmed by NMR analysis. Zanamivir was either dissolved in carrageenan or placebo solutions, followed by sterile filtration through a 0.22 μm filter (Sarstedt, Germany). For in-vivo studies all Zanamivir containing solutions were freshly prepared.
Madin-Darby canine kidney (MDCK) cells were obtained from the American Type Culture Collection (ATCC, Manassas, VA) and cultivated in a 37°C incubator (Sanyo, Japan; CO 2 : 5%, relative humidity: >95%). MDCK cells were grown in Dulbecco's minimal essential (DMEM) high glucose medium (PAA, Austria) supplemented with 10% fetal bovine serum (FBS; PAA, Austria; heat inactivated).
Influenza virus A/Hansa Hamburg/01/09 (H1N1(09)pdm) was kindly provided by Peter Staeheli Department of Virology, University of Freiburg, Germany and previously described in [56] ; A/Teal/Germany/Wv632/05 (H5N1) previously published in [57] (accession numbers CY061882-9) and A/Turkey/Germany/R11/01 (H7N7) (taxonomy ID 278191, accession number AEZ68716) were supplied by courtesy of Martin Beer, Institute of Diagnostic Virology, Friedrich-Loeffler-Institute, Riems, Germany; A/Aichi/2/68 (H3N2) was purchased from the ATCC. All influenza viruses were propagated in MDCK cells at 37°C and 5% CO 2 in influenza medium [Opti-Pro serum free medium (Gibco, Austria) supplemented with 4 mM L-glutamine (PAA, Austria), 1% antibiotic-antimycotic mix (PAA, Austria) and 5 μg/ml trypsin (Sigma Aldrich, Austria)].
To determine the 50% inhibitory concentration (IC 50 ) and the combination effect of carrageenan and Zanamivir, a semi-liquid plaque assay was developed. Into 96 well tissue culture plates 1.7x10 4 MDCK cells/well were seeded and infected at 90% confluence (24-28 hours later). Serial dilutions of carrageenan and Zanamivir were prepared in assay medium (influenza medium without trypsin). For infection, viruses were diluted to an MOI of 0.003 (H1N1(09)pdm and H3N2 Aichi), 0.015 (H5N1) or 0.004 (H7N7), respectively, in assay medium and incubated at room temperature (RT) for 10 min with the serial dilutions of carrageenan and/or Zanamivir, respectively. For evaluation of the combination effect of carrageenan and Zanamivir, viruses were diluted in assay medium containing constant concentrations of either carrageenan or Zanamivir. The other substance was serially diluted and used for virus incubation. Cells were infected in 6 replicates/compound dilution, respectively, and incubated at RT for 45 min before inoculum removal. Cells were further incubated with the respective concentration of the investigated substances present in the overlay [influenza medium with 2.25% Carboxymethylcellulose (CMC, Fluka, Austria)] for 30-42 hours at 37°C. Evolving plaques were evaluated after methanol/acetone cell fixation by immune staining with antibodies either directed against the influenza A nucleoprotein (AbD Serotec, Germany) (for H1N1(09)pdm, H5N1 and H7N7) or the hemagglutinin (AbD Serotec, Germany) (for H3N2). Analysis was done with a HRP labeled detection antibody (Thermo Scientific, Germany) using TMB (Biolegend, Germany) as substrate and a microplate reader at 450 nm. The reduction of detected signal represents a reduction in the number and size of plaques and indicates suppression of viral replication during infection and cultivation.
After the immunostaining cells were stained with 0.005% crystal violet solution to assess the condition of the cell layer and the toxicity of the compounds. IC 50 values and standard deviations were calculated for a sigmoidal dose response model using XLfit Excel add-in version 5.3.1.3.
All animal experiments were carried out according to the guidelines of the "European Convention for the Protection of Vertebrate Animals used for Experimental and other Scientific Purposes" and the Austrian law for animal experiments. All animal experiments were approved by the Veterinary University of Vienna institutional ethics committee and performed under the Austrian Federal Ministry of Science and Research experimental animal license numbers BMWF-68.205/0262-II/3b/2011 and BMWF-68.205/0142-II/3b2012. C57BL/6 mice were purchased from Janvier Labs, France and maintained under standard laboratory conditions in the animal facilities of the Veterinary University of Vienna. For euthanasia and anesthesia asphyxiation through CO 2 was used and all efforts were made to minimize suffering.
For infection experiments, 3-5 weeks old female mice were intranasally inoculated with 50 μl influenza virus solution (25 μl/nostril) containing 2.27x10 3 or 1.65x10 3 plaque-forming unit of H1N1(09)pdm or H7N7, respectively. Subsequently, treatment started 24, 48 or 72 hpi, as indicated for the different experiments. Treatment was performed intranasally either with 50 μl therapeutic solution or placebo twice per day for 5 days. As therapy either carrageenan (containing 1.2 mg/ml iota-carrageenan and 0.4 mg/ml kappa-carrageenan to provide a daily dose of 12 mg/kg body weight (BW)), Zanamivir (containing either 130 μg/ml or 390 μg/ml Zanamivir, to provide a daily dose of 1 or 3 mg/kg BW, respectively) or a combination of carrageenan and Zanamivir were used. Carrageenan and Zanamivir are used at non-toxic concentrations as shown by [58] and [59] . Mice were monitored twice daily for 15 days for survival and weight loss. Mortality also includes mice that were sacrificed for ethical considerations when they had lost more than 25% of their initial body weight. We confirm the viral infection in these animals by necropsy and scoring of the lung inflammation.
As the mechanisms underlying the antiviral activity of NI and carrageenans are fundamentally distinct, they are likely to exhibit different activities towards the individual influenza virus strains. As a result, in combination they could complement each other to provide protection against a broader spectrum of influenza virus strains than the individual compounds.
To test this hypothesis, we investigated the sensitivity of various influenza virus strains to Zanamivir and carrageenan in an adapted plaque reduction assay with semi-liquid overlay in MDCK cells [60, 61] . Using this method, we determined the IC 50 of Zanamivir and carrageenan against influenza A viruses of human and animal origin, namely H1N1(09)pdm (A/Hansa Hamburg/01/09), H3N2 (A/Aichi/2/68), low pathogenic (LP) H5N1 (A/Teal/Germany/ Wv632/05) and LP H7N7 (A/Turkey/Germany/R11/01) ( Table 1) . Both substances were nontoxic at the highest tested concentration (400 μM Zanamivir and 533 μg/ml carrageenan), neither was their combination. Furthermore, CMC in the overlay did not show any virus inhibitory effect (data not shown). Inhibition of viral replication of all tested influenza strains was achieved with both substances. However, the IC 50 values varied widely depending on the influenza virus strain. The IC 50 values of Zanamivir ranged between 0.18 μM for H5N1 and 22.97 μM for H7N7 and that of carrageenan from 0.39 μg/ml to 118.48 μg/ml for H1N1(09)pdm and H7N7, respectively (see Table 1 ). These results demonstrate that carrageenan and Zanamivir target individual influenza strains to different extents so that they may complement each other to provide broader anti-influenza activity.
The type of compound interaction was characterized by employing isobolograms (Fig 1) . As described in [62] , isobolograms graphically compare the doses of two compounds needed to reach 50% inhibition to the predicted doses calculated based on a model of drug additivity. A curve linearity of~1 is expected for an additive compound interaction whereas a curve progression <1 argue for synergistic and >1 for an antagonistic compound interaction.
Two virus strains were selected for those experiments, one being the most sensitive to carrageenan (H1N1(09)pdm) and one being the least sensitive (H7N7). In both cases the isobolograms show a synergistic interaction of carrageenan and Zanamivir (Fig 1) . Thus, it was shown that Zanamivir and carrageenan target individual influenza viruses with different efficiencies, most probably due to their different antiviral strategies. As a result, the combination provides synergistic activity with higher protection against a broader spectrum of influenza virus strains than the individual compounds.
In the influenza animal model, C57Bl/6 mice are challenged with a lethal dose of the respective virus and treated with different regimens in comparison to a vehicle control (placebo). Infection and treatment (twice a day for 5 days) are done intranasally without anesthesia. We investigated whether the combination of Zanamivir and carrageenan is more efficacious in reducing mortality than the corresponding mono-therapies.
First, we determined the minimal effective dose of a Zanamivir mono-therapy that significantly improved survival time of H1N1 and H7N7 infected mice. For the H7N7 lethal infection the minimal effective dose of Zanamivir as mono-therapy ranged between 1 and 3 mg/kg BW/ day (data not shown). Next, we compared the antiviral activity of carrageenan (12 mg/kg BW/ day) and Zanamivir (1 and 3 mg/kg BW/day) mono-therapies with the respective combination versus placebo treatment. Survival rates of mice with treatment starting 24 hpi are shown in Fig 2A. All placebo treated mice died between day 7 and 9 and also in all mono-therapy groups 100% lethality was observed until day 15. In contrast, the combination therapies led to 50% and 90% survival, depending on the Zanamivir concentration. Statistical analysis showed that the Zanamivir mono-therapy 1 mg/kg BW/day did not show a significant benefit (p = 0.1810), whereas the mono-therapy with 3 mg/kg BW/day significantly increased the survival rate compared with placebo treated mice (p = 0.0016). Both Zanamivir concentrations experienced significant benefit in survival by the combination with carrageenan (p<0.0001). Similarly, the combination therapies resulted in remarkably increased survival (p = 0.0421 for 1 mg and p<0.0001 for 3 mg/kg BW/day) when compared to the carrageenan mono-therapy. No statistically significant difference was observed between the combination containing 3 mg/kg BW/day Zanamivir and that containing 1 mg/kg BW/day (p = 0.0525). However, a trend for an increased survival rate with the higher Zanamivir concentration was evident. Therefore, for further investigation the combination therapy containing 3 mg/kg BW/day Zanamivir was evaluated in lethally H7N7 infected mice.
Next, the therapeutic potential of the combination with a delayed therapy start 48 or 72 hpi versus placebo treatment was explored. The survival rates of mice are shown in Fig 2B. All placebo treated mice died until day 10 and also in the group with the treatment start 72 hpi 100% lethality was found. In contrast, the combination therapy starting 48 hpi provided a statistically significant enhanced survival rate in comparison to placebo-treated mice (p = 0.0010).
In summary, the combination of two effective, established mono-therapies resulted in a significantly enhanced survival in lethally H7N7 infected mice. Additionally, the combination therapy was highly efficient in comparison to placebo treatment even after a treatment onset up to 48 hpi.
Intranasal therapy with carrageenan and Zanamivir starting 72 hpi significantly protects lethally influenza H1N1(09)pdm infected mice Next, the minimal effective dose of Zanamivir used as mono-therapy was evaluated in a lethal H1N1(09)pdm mouse model, following the same scheme as described in the H7N7 experiments. The lowest effective dose of Zanamivir after a treatment start 24 hpi was 1 mg/kg BW/ day and its combination with carrageenan was highly effective (data not shown). In the following experiment the therapeutic potential of the combination with a therapy start 48 or 72 hpi was investigated in comparison with the respective placebo treatment.
As shown in Fig 3, the survival rates of mice treated with the combination therapy were highly significantly increased in comparison to the placebo group (p<0.0001). There was no difference in survival between the two therapy starting points, 48 or 72 hpi, which both resulted
We investigated the antiviral effect of a combination of carrageenan with the NI Zanamivir in cell culture studies and in mouse influenza infection models. We have previously shown that a combined therapy of iota-carrageenan with the NI Oseltamivir led to significantly enhanced survival in mice infected with H1N1 PR/8/34 in comparison with the respective mono-therapies [37] . However, Oseltamivir is an orally administered prodrug, which has to be converted into its active form by metabolic processing. Therefore, a further development of a combination nasal spray was not possible with Oseltamivir. Instead Zanamivir-a NI that is applied as active drug-was chosen for the development of a compound combination.
During the evaluation process we found that the binding efficiency of different carrageenan subtypes on different influenza strains varies. The combined use of iota-and kappa-carrageenan for the treatment of lethally influenza infected C57Bl/6 mice revealed a better therapeutic effect than the use of iota-carrageenan alone (S1 Fig). Thus, to provide a broader spectrum of activity against different influenza virus strains, a mixture of iota-and kappa-carrageenan (designated as carrageenan) was used for further evaluation.
For investigation of the effect of a compound combination of carrageenan and Zanamivir, we examined their inhibition efficiency, individually and in combination, against influenza viruses in an adapted plaque reduction assay with semi-liquid overlay in MDCK cells. The combination showed a synergistic inhibition of virus replication in in-vitro assays with all tested influenza viruses (Fig 1) . This indicates that the physical interaction of the polymer with the virus does not disturb the inhibition of the neuraminidase by Zanamivir. This was confirmed in in-vitro tests examining a potential influence of the polymer on the neuraminidase inhibiting activity of Zanamivir (data not shown). Hence, the observed synergistic effect is based on the combination of two distinct underlying mechanisms. As a result, in the proposed combination both mechanisms would complement each other to provide more efficient protection against a broader spectrum of influenza virus strains than the individual compounds.
The synergistic effect was also shown in lethal mice models (Fig 2 and Fig 3) . The pathogenicity of influenza viruses in mice varies and is dependent on the strain and its adaptation to the host. Depending on virus dose and strain, influenza viruses can induce lethal infections in certain mouse strains usually within two weeks [37, 63] . In our model, C57Bl/6 mice are challenged intranasally with a lethal dose of the respective virus and treated with different regimens in comparison to a vehicle control (placebo). In such a model, early virus replication takes place in the upper respiratory tract. From there, virus spreads to the lung and causes lethal pneumonia. The effect of the treatment on mortality is assessed in comparison to placebotreated control mice. Of all in-vitro tested influenza strains the H1N1(09)pdm and the LP H7N7 are particularly interesting for two reasons. First, they are highly relevant pathogens, as placebo or with the mono-therapies consisting of carrageenan (12 mg/kg BW/day) or Zanamivir (1 and 3 mg/ kg BW/day) or a combination thereof. Treatment started 24 hpi and continued for 5 days. (B) Mice (n = 20 per group) were lethally intranasally infected without anesthesia on day 0 and intranasally treated twice per day either with placebo or a combination of carrageenan with Zanamivir (3 mg/kg BW/day). Treatment started either 48 hpi or 72 hpi and continued for 5 days. On the y-axis the survival of mice [%] and on the x-axis the time post infection [days] is given. Placebo treated uninfected control mice showed 100% survival in both experiments (data not shown). Statistical analyses were conducted using log rank test and are shown beneath the graphs. Values of p<0.05 were considered statistically significant; non-significance (n.s.) was obtained with p-values >0.05. both are involved in recent influenza outbreaks. The H1N1(09)pdm is associated with more than 18,400 deaths in the season 2009/2010 while the LP H7N7 carries an HA closely related to that of the avian influenza H7N9 virus which has caused more than 175 deaths until October 2014 [64] . Second, they are of special interest for the carrageenan/Zanamivir combination approach. They have shown to differ in in-vitro susceptibility to carrageenan, Zanamivir (Table 1 ) and the combination thereof (Fig 1) . While H1N1(09)pdm was highly sensitive to inhibition by both substances alone, H7N7 required much higher concentrations of carrageenan and Zanamivir, respectively, to achieve similar inhibition efficiencies. Therefore, both virus strains were chosen to further explore the efficiency of the combination therapy in a mouse model.
We established lethal mouse models with both viruses that resulted in 6.8 and 8.5 mean survival days for LP H7N7 and H1N1(09)pdm, respectively. These results are in good accordance to similar already published lethal influenza models [65] [66] [67] . In our models the lowest effective dose for Zanamivir at a treatment start 24 hpi was found to be between 1 to 3 mg/kg BW/day for both viruses. This concentration range is relatively high in comparison to other published studies. However, these studies were done under anesthesia with different viruses and a prophylactic therapy start [65, 66] . The fact that a higher dose of NI is needed for an effective treatment when the therapy starts 24 hpi is already known for Oseltamivir [68] . Nonetheless, also data with much higher effective concentrations (10 mg/kg BW/day [69] ) and with similar concentrations of Zanamivir (2.5 mg/kg BW/day [67] ) were published as well.
We found that the combination of carrageenan with 3 mg/kg BW/day Zanamivir used for treatment of H7N7 infected mice resulted in significantly enhanced survival of mice in comparison to both mono-therapies (Fig 2) . The significantly enhanced survival compared to the placebo treated group was also found after a delayed treatment start 48 hpi. Furthermore, in the H1N1(09)pdm model the combination of carrageenan with 1 mg/kg BW/day Zanamivir showed statistically significant enhanced survival in comparison to placebo treatment even after a treatment start 72 hpi. This is a remarkable finding since NIs are normally not effective when applied 72 hpi.
The finding supports the development of the Zanamivir and carrageenan combination approach. As the intranasal treatment regime is incapable to effectively treat virus infections of the lung, the primary target of such a product is the prophylaxis and therapy of uncomplicated influenza. Since the majority of influenza infections causes uncomplicated illnesses and practically all cases of influenza start with an infection of the nasal cavity or the upper respiratory tract, the therapeutic potential is huge. However, clinical studies are required to elucidate and demonstrate the potential of the proposed combination therapy.
Combination of antiviral strategies has led to impressive achievements in the combat against other viral disease like HIV. In particular the problem of antiviral resistance could be addressed with this strategy. In the last decade concerns have been raised about the increased emergence of Oseltamivir resistant influenza viruses. The augmented appearance of viruses carrying the mutation H275Y in the neuraminidase of H1N1(09)pdm viruses that confers resistance to Oseltamivir left Zanamivir as only treatment option for symptomatic patients infected with an Oseltamivir resistant influenza strain [70] . In contrast to Oseltamivir, resistance to Zanamivir is less frequent. To date, Zanamivir resistant influenza has been detected only once, in an immunocompromised patient [71, 72] . However, lessons should be learned from previous anti-influenza interventions which resulted in occurrence of resistance against currently approved drugs [73] . Therefore, concerns are comprehensible that an increased Zanamivir use may also lead to the rapid emergence of resistances [74] . To overcome this threat, a combination of antivirals which inhibits virus replication by distinct mechanisms is a valid strategy. We checked for the possibility of generating double compound escape mutant viruses while passaging viruses in the presence of increasing concentrations of compound combinations. After 10 passages in MDCK cells no resistance to the compound combination for any tested influenza virus could be found (data not shown). However, this finding does not guarantee that emergence of Zanamivir escape mutants can be completely halted.
In summary, we demonstrated that the anti-influenza mechanisms of both single compounds complement each other. The combination provides synergistically better protection against a broader spectrum of influenza viruses than the individual compounds.
A nasal spray containing carrageenan together with Zanamivir provides an easy to apply treatment of upper respiratory tract infections in patients under suspicion to be influenza infected. Patients would benefit from the fast and efficient treatment of uncomplicated influenza in the upper respiratory tract. Due to the faster influenza virus clearance from the upper respiratory tract and the independent antiviral mechanism of carrageenan and Zanamivir the likelihood to develop escape mutations against Zanamivir will be reduced. Both individual compounds are able to reduce severity and/or duration of the influenza illness and a combination is expected to work similarly. Additionally, due to the broad antiviral effectiveness of carrageenan, patients will receive in parallel a treatment of concomitant viral infections. Therefore, patients will benefit from a decreased probability to develop complications. In consideration of the complications known to accompany an influenza virus illness this combinational therapy meets an urgent medical need.
A second scope of this combination is the protection against newly emerging pandemic viruses during the time until identification of the virus followed by manufacturing and distribution of vaccines [43] . Even if, due to new reverse genetic techniques, less time for production of vaccines is needed, it still takes months before large quantities of vaccine are available [75] . During this time the human population should be protected to decelerate viral spread. At the moment the only available opportunities for personal protection are hygiene measures and the use of Tamiflu (brand name of Oseltamivir).
Novel protection and treatment options for influenza are desperately needed. Based on our encouraging results in mice we suggest testing a nasal spray containing carrageenan in combination with the neuraminidase inhibitor Zanamivir in clinical trials for prevention or treatment of uncomplicated influenza infections.
Supporting Information S1 Fig. Therapeutic efficacy of iota-carrageenan solely or together with kappa-carrageenan in influenza H7N7 lethal infected mice. Mice (n = 20 per group) were lethally intranasally infected without anesthesia on day 0 and accordingly intranasally treated twice per day either with placebo or with iota-carrageenan or with a mixture of iota-and kappa-carrageenan. Treatment started 24 hpi and continued for 5 days. On the y-axis the survival of mice [%] and on the x-axis the time post infection [days] is given. Placebo treated, uninfected control mice showed 100% survival (data not shown). Statistical analyses were conducted using log rank test and are shown beneath the graphs. Values of p<0.05 were considered statistically significant; non-significance (n.s.) was obtained with p-values >0.05. (TIFF) | Is coinfection common in influenza infection? | false | 2,151 | {
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1,676 | Viruses Causing Gastroenteritis: The Known, The New and Those Beyond
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4776197/
SHA: f7b30ee89775bc82607cc6bc87feb5934b47625f
Authors: Oude Munnink, Bas B.; van der Hoek, Lia
Date: 2016-02-19
DOI: 10.3390/v8020042
License: cc-by
Abstract: The list of recently discovered gastrointestinal viruses is expanding rapidly. Whether these agents are actually involved in a disease such as diarrhea is the essential question, yet difficult to answer. In this review a summary of all viruses found in diarrhea is presented, together with the current knowledge about their connection to disease.
Text: The gastrointestinal tract is a vulnerable organ for infections as there is constant contact with the outside, mainly via the oral route. Inflammation of the stomach and the intestines (gastroenteritis) can cause nausea, vomiting and diarrhea. Gastroenteritis is responsible for two to three million deaths each year, making it one of the most common causes of mortality [1] . Mainly children in developing countries, but also immuno-compromised individuals in developed countries, suffer from diarrhea. While bacterial and parasitic gastrointestinal infections are declining as a result of proper disposal of sewage and safe drinking water, viral gastroenteritis is not declining in developing countries [2] . In the developed world, viruses are already the most common pathogens causing diarrhea [3] .
Although viruses infecting humans had already been described since 1901 [4] and viruses were suspected to play a role in diarrhea, it lasted until 1972, when the first virus causing gastroenteritis (norovirus) was identified in an outbreak of diarrhea in Norwalk (California, United States) [5] . Shortly after the discovery of norovirus several other viruses causing gastroenteritis were discovered: rotavirus in epithelial cells of children with gastroenteritis [6] , astrovirus in infantile diarrhea cases [7] , enteric adenoviruses in the feces of children with acute diarrhea [8] , and sapovirus during an outbreak of gastroenteritis in an orphanage in Sapporo, Japan [9] . All these viruses spread via the fecal-oral route through person-to-person transmission and are described in more detail below.
Noroviruses are part of the family Caliciviridae and outbreaks of norovirus gastroenteritis have been reported in cruise ships, health care settings, schools, and in the military, but norovirus is also responsible for around 60% of all sporadic diarrhea cases (diarrhea cases where an enteropathogen could be found), reviewed in the literature [10, 11] . The pathogenesis of norovirus infection has been tested in vivo. Filtrated norovirus was given to healthy volunteers after which most of them developed diarrhea [12] . Culturing of the virus, however, has been a problem since its discovery, yet one study has recently described the cultivation of norovirus in B cells, and has revealed that co-factors, such as histo-blood antigen expressing enteric bacteria, are probably needed before enteric viruses can be cultured in vitro [13] . Sapoviruses are also members of the Caliciviridae. There are five human genogroups of sapovirus described [14] which account for 2.2%-12.7% of all gastroenteritis cases around the globe [14, 15] . Sapovirus outbreaks occur throughout the year and can be foodborne [16] . For sapoviruses it has been described that the virus was not found before onset of an outbreak, and that it was found in 95% of the patients during an outbreak, while it declined to 50% after an outbreak, indicating that the virus introduces disease in a naturally infected host [17] .
Rotavirus infection is the most common cause of viral gastroenteritis among children; however, parents of infected children also often become ill and as a result rotavirus is the second most common cause of gastroenteritis in adults [18] . Studies in human volunteers have shown that infection with rotavirus causes diarrhea, results in shedding of the virus and a rise in antibody anti-virus titer after infection [19] . Additionally, astroviruses infections are common, accounting for about 10% of all sporadic diarrhea cases [20] . Astrovirus has been isolated from diseased people, filtrated and administered to healthy individuals after which in some of the volunteers diarrheal disease was observed and astrovirus was shed in their stools [21] . The virus can replicate in human embryonic kidney cells and was detected by electron microscopy (EM) [21] . Adenoviruses are responsible for around 1.5%-5.4% of the diarrhea cases in children under the age of 2 years, reviewed in the literature [22] . Of the 57 identified adenovirus types [23] , only adenoviruses type 40 and 41 are associated with diarrhea [24] . Next to these two types, adenovirus type 52 can also cause gastroenteritis [25] , although it has been argued whether type 52 is actually a separate type since there is not sufficient distance to adenovirus type 41 [26] . Adenoviruses can generally be propagated in cell lines; however, enteric adenovirus 40/41 are difficult to culture, reviewed in the literature [27] .
In the 1980s and 1990s some viral agents were identified for which the direct association with disease is less clear. Aichi viruses are members of the Picornaviridae identified in fecal samples of patients with gastroenteritis [28] . Aichi virus infection has been shown to elicit an immune response [29] . Since their discovery, two case-control studies were performed, but, although both studies only found Aichi virus in stools of diarrheic patients, the prevalence of Aichi virus (0.5% and 1.8%) was too low to find a significant association with diarrhea [30, 31] . In immuno-compromised hosts the virus is found in higher quantities and is not associated with diarrhea [32] . Toroviruses, part of the Coronaviridae, were first identified in 1984 in stools of children and adults with gastroenteritis [33] . Torovirus infection is associated with diarrhea [34] and is more frequently observed in immuno-compromised patients and in nosocomial infected individuals [34] . Retrospective analysis of nosocomial viral gastroenteritis in a pediatric hospital revealed that in 67% of the cases torovirus could be detected [35] . However, only a limited number of studies report the detection of torovirus and therefore the true pathogenesis and prevalence of this virus remains elusive. Picobirnaviruses belong to the Picobirnaviridae and were first detected in the feces of children with gastroenteritis [36] . Since the initial discovery, the virus has been detected in fecal samples of several animal species, and it has been shown that the viruses are genetically highly diverse without a clear species clustering, reviewed in the literature [37] . This high sequence diversity has also been observed within particular outbreaks of gastroenteritis [38, 39] , limiting the likelihood that picobirnaviruses are actually causing outbreaks, as no distinct single source of infection can be identified.
In 1907 the first tissue culture system was developed which was regarded as the golden standard for virus detection for a long time, reviewed in the literature [40] . In the 1930's serology and electron microscopy were introduced which boosted the discovery of new viruses. During these years, these methods developed fruitfully but viruses infecting the gastrointestinal tract were especially difficult to culture. Throughout the last several decades, several DNA-based techniques have been developed for virus discovery that boosted the identification of novel viruses in stool samples. The four most used methods are: 1. Universal primer-PCR [41] ; 2. Random priming-based PCR [42] ; 3. Virus Discovery cDNA, Amplified Fragment Length Polymorphism (VIDISCA) [43] ; and 4. Sequence-Independent Single Primer Amplification (SISPA) [44] . Universal primer-PCR is a virus discovery technique that uses universal primers designed on conserved parts of a specific viral family, which can be used to detect novel variants of this viral family. Random priming-based PCR is a technique that randomly amplifies all nucleic acids present in samples, after which the resulting PCR products can be cloned and sequenced. SISPA and VIDISCA are virus discovery techniques that are based on digestion with restriction enzymes, after which adaptors can be ligated. These methods have been successful in the discovery of novel viruses, but there are some limitations. Universal primers are useful for discovering novel viruses of a chosen family, but the primers, based on our present knowledge of the viral family, may not fit on all unknown variants. Random priming PCR, SISPA and VIDISCA are sequence independent amplification techniques. The disadvantage of random priming PCR, SISPA and VIDISCA is that the virus needs to be present at a high concentration, while the host background DNA and/or RNA should be minimal and preferably not complex.
In recent years, sequence independent amplification techniques improved considerably by coupling these techniques to next-generation sequencing platforms and as a result several novel viruses have been described in gastroenteritis cases, such as cosavirus [45] , Saffold virus [46] , klassevirus/salivirus [47, 48] , polyomavirus [49] , bufavirus [50] , tusavirus [51] , and recovirus [52] . Although these viruses are found in individuals with diarrhea, for most of them the degree of circulation (prevalence) and the ability to cause morbid conditions or disease (pathogenesis) remains to be determined, as described below (also see Table 1 ). Only found in low prevalence; **: Only limited data is available about this virus; ***: Antibodies against astrovirus HMO-C were observed whereas no antibodies against astrovirus HMO-A were found (HMO = human-mink-ovine-like astrovirus); -No published data available;ˆPicobirnavirus, tusavirus and recovirus were identified in the gastrointestinal tract after next-generation sequencing, but no information regarding antibody response or association with diarrhea is available.
In the last decade, two novel clades of astroviruses have been discovered in stool samples from patients with diarrhea that are genetically far distinct from the classical astroviruses. The first clade consists of the VA-1, VA-2, VA-3, VA-4, and VA-5 astroviruses, which are genetically related to feline and porcine astroviruses, while the second clade consists of the MLB1, MLB2 and MLB3 astroviruses and form a separate cluster [55, 57, [74] [75] [76] [77] [78] . For these novel clades the pathogenesis remains to be determined since the viruses have been identified in patients with and without diarrhea, and in some studies the viruses were associated with diarrhea whilst in others no association could be found [55] [56] [57] . In addition an antibody response was observed against some but not all novel astrovirus types [54, 58] . Recently, astrovirus MLB2 has also been detected in blood plasma of a febrile child [79] and astrovirus VA1 in a frontal cortex biopsy specimen from a patient with encephalitis [80] , suggesting that astrovirus infection may not be limited to the gastrointestinal tract.
In 2008, Saffold virus was detected in a stool sample from a pediatric patient with fever of unknown origin [46] . Although Saffold virus type 3 was cultured on a human epithelial cervical carcinoma (HeLa) cell line, cytopathic effects were observed and neutralizing antibodies have been found in serum samples [59] , subsequent case-control studies showed that the virus was not significantly associated with diarrhea [53, 60, 61] . Additionally, in 2008 cosavirus was identified in a patient with diarrhea [45] . However, a case-control study showed that this virus was also detected in a substantial amount of individuals without diarrhea and is not associated with diarrhea [32, 62, 63] . Klassevirus/salivirus was identified in 2009 in two fecal samples from infants with gastrointestinal disorders [47, 48] . In two studies the detection of this virus was associated with diarrhea [48, 53] , while in another study no association with disease was found [65] . Serological evidence of human klassevirus infection was obtained, suggesting that the virus infects human cells [64] .
With the use of next-generation sequencing techniques, three novel polyomaviruses were also identified in human fecal samples. MW polyomavirus was identified in the stool of a healthy child from Malawi in 2012 [49] , and in the same year MX polyomavirus was found in stool samples of patients with and without diarrhea from Mexico, United States and Chili [68] . One year later, STL polyomavirus was found in the stool of a healthy child from Malawi [71] . An antibody response against MX polyomavirus [66] and MW polyomavirus [69] was observed, although MW polyomavirus [67] and STL polyomavirus [70] were not significantly associated with diarrhea in two independent case-control studies.
Bufavirus is a member of the Parvoviridae and was first described in 2012 [50] . Two case-controls in Thailand and in Turkey showed that the virus was only found in patients with diarrhea and not in controls [72, 73] ; however, because of the low prevalence (respectively 0.3% in Thailand and 1.4% in Turkey), no significant association with disease was found. Tusavirus, another recently described member of the Parvoviridae, was identified in the feces of a child from Tunisia with unexplained diarrhea [51] , and thus far this is the only study describing this virus. Recovirus is a novel member of the Caliciviridae and was found in diarrhea samples from Bangladesh [52] . Similar to tusavirus, this is the only study describing this virus thus far.
The identification of the above-mentioned novel viruses certainly increased our knowledge about viruses that can be found in the gastrointestinal tract of humans, yet it is unknown how many of these novel viruses are actually enteropathogens. Human stool contains a wide variety of viruses which can be derived from different hosts: Besides genuine human viruses, plant dietary viruses [32, 81] and animal dietary viruses [82] can also be found in human stool, as well as bacteriophages and viruses infecting protozoa [32] . Even viruses derived from other parts of the body can be found in fecal samples, such as the John Cunningham Polyoma virus originating from the kidney ending up in feces via urine [83] , and rhinoviruses [84] , bocaviruses [85] and coronaviruses [86] originating from the respiratory tract and probably swallowed. Furthermore, viruses infecting blood cells such as human immunodeficiency virus (HIV)-1 can also be detected in fecal samples [87] . Therefore, once a novel virus has been identified in human stool samples it is does not indicate that this virus is replicating in human intestinal cells.
Koch recognized as early as 1891 that associating the presence of a certain agent with a certain disease is complex, and he therefore postulated guidelines that should be followed before an agent can be classified as a pathogen [88] . His postulates can be summarized in three points: (1) The microbe occurs in every case of the disease in question and under circumstances which can account for the pathological changes and clinical course of the disease; (2) the microbe occurs in no other disease as a fortuitous and nonpathogenic parasite; and (3), after being fully isolated from the body and repeatedly grown in pure culture, the microbe can induce the disease anew. If a microbe has fulfilled these three postulates it can be stated that "the occurrence of the microbe in the disease can no longer be accidental, but in this case no other relation between it and the disease except that the microbe is the cause of the disease can be considered". For enteric viruses, however, these postulates are not applicable. Firstly, the enteric viruses are not easily cultured [89] [90] [91] , and, secondly, prolonged sheading of viral agents and asymptomatic infection have been described [92] , reviewed in the literature [93] . Although attempts have been made to adjust the Koch's postulates specifically for viruses and the current methodologies deployed [94] [95] [96] , fulfilling these postulates is still not feasible on most occasions due to the lack of an efficient cell culture system, difficulties in antigen synthesis and high levels of viral genetic diversity within viral groups, reviewed in the literature [97] .
Several approaches have been made to develop a methodology that adds more significance to the discovery of a novel virus. One approach is based on the enrichment of immunogenic viruses before next-generation sequencing by making use of autologous antibody capture prior to sequencing. This method was tested and validated on several fecal samples containing adenovirus, sapovirus and norovirus, and has shown to enrich immunogenic viruses, while plant viruses and bacteriophages were not enriched after antibody capture [98] . Another method to enrich for relevant viruses prior to next-generation sequencing is the so-called virome capture sequencing platform for vertebrate viruses (VirCapSeq-VERT) which uses~2 million probes which cover the genomes of all members of the viral taxa known to infect vertebrates [99] . However, both methods have limitations: For the antibody capture method, viruses need to be present in high viral loads, and convalescent blood, serum or plasma needs to be available. A disadvantage of the VirCapSeq-VERT technique is that completely novel viruses, e.g., viruses from a novel virus family, will not be identified.
The most straightforward method to demonstrate association with disease is using case-control studies. In order to perform such studies, matched stool samples have to be collected in case and control groups from the same geographical locations in the same period of the year. Additionally, whereas in recent years case-control studies have been performed using conventional real-time PCRs (RT-PCR), in the future, sequence independent next-generation sequencing techniques can be used for such case-control studies. Since it allows detection of virtually all nucleic acids, next-generation sequencing has several advantages compared to specific RT-PCRs. Next-generation sequencing prevents the necessity to perform numerous RT-PCRs to screen for all viruses suspected to be associated with disease, and novel variants of currently known viral families or novel virus species can be detected which can be particularly beneficial if only few reference genomes are available. The major benefit of such a database is that in the immediate future the most important question can be answered if a novel virus is identified in diarrhea cases: Is the virus likely to cause disease?
In conclusion, the long list of viruses identified in the gastrointestinal tract is most probably not final yet. It is to be expected that several novel viruses will be described in the near future, since detection of these agents using the current next-generation sequence technologies is no longer a difficulty. Therefore, adding relevance to the discovery of novel viruses should be the main goal for future studies. | What is Koch's third postulate? | false | 909 | {
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187 | Preparation for Possible Sustained Transmission of 2019 Novel Coronavirus
Lessons From Previous Epidemics
https://jamanetwork.com/journals/jama/fullarticle/2761285
February 11, 2020
David L. Swerdlow, MD1; Lyn Finelli, DrPH, MS2
Author Affiliations Article Information
JAMA. 2020;323(12):1129-1130. doi:10.1001/jama.2020.1960
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Transmissibility and severity are the 2 most critical factors that determine the effect of an epidemic. Neither the 2009 pandemic influenza A(H1N1) virus ([H1N1]pdm09) pandemic or the severe acute respiratory syndrome coronavirus (SARS-CoV) or the Middle East respiratory syndrome coronavirus (MERS-CoV) epidemics had the combination of both high transmissibility and severity. Control strategies are driven by this combination. R0, the basic reproduction number, is a commonly used measure of transmissibility and is defined as the number of additional persons one case infects over the course of their illness. An R0 of less than 1 indicates the infection will die out “eventually.” An R0 of greater than 1 indicates the infection has the potential for sustained transmission.
For example, influenza A(H1N1)pdm09, first identified in southern California on April 15, 2009, was highly transmissible. By May 5, 2009, influenza A(H1N1)pdm09 had spread to 41 US states and 21 countries.1 While influenza A(H1N1)pdm09 was highly transmissible, it was not severe. Initial estimates of the R0 of influenza A(H1N1)pdm09 were 1.7.2 Although an estimated 201 200 respiratory deaths due to influenza A(H1N1)pdm09 occurred during the first year of the pandemic, the number of deaths per population was 30 times lower than that seen during the 1968 influenza pandemic, 1000 times less than the 1918 pandemic, and even less than typical seasonal influenza epidemics (estimated by the World Health Organization [WHO] to be 250 000 to 500 000 per year, although estimation methods differ).3 Influenza A(H1N1)pdm09 was highly transmissible but not severe.
SARS-CoV (2003) and MERS-CoV (2012-current) cause severe disease, but despite the initial R0 estimations of greater than 2.0 for SARS-CoV (indicating sustained and even worldwide transmission could occur), and some large outbreaks, neither were as transmissible as initial concerns suggested. SARS-CoV caused 8098 reported cases and 774 deaths (case-fatality rate, 9.6%) in 37 countries before the epidemic was controlled. Control was thought to have been possible because a high proportion of cases were severe, making it easier to rapidly identify and isolate infected individuals. In addition, the virus was present at lower levels in upper airway secretions. There was no secondary transmission in the United States from the 8 imported cases, although in Toronto, Canada, a single importation is thought to have led to about 400 cases and 44 deaths. Later estimates of R0 were less than 1, indicating that SARS-CoV may not have been capable of sustained transmission, especially in the setting of control measures.4
Similarly, MERS-CoV appears to have high severity and low transmissibility. Since 2012, MERS-CoV has caused 2494 reported cases and 858 deaths (case-fatality rate, 34%) in 27 countries. MERS-CoV has also caused some rapid outbreaks, mainly in hospitals in Saudi Arabia, Jordan, and South Korea, but estimates of MERS-CoV R0 are less than 1, and thus far it has been contained.5
Can a respiratory virus that is both transmissible and severe be contained? In preparation for an influenza pandemic, the US Department of Health and Human Services’ Pandemic Influenza Plan included a combination of nonpharmaceutical (border and school closing, infection control measures) and pharmaceutical (antiviral prophylaxis, vaccines) interventions meant to be used in combination to interrupt or slow influenza transmission. Despite implementation of some of these interventions, influenza A(H1N1)pdm09 spread to 120 countries in 3 months.
With the emergence of MERS-CoV in the Middle East, a preparedness plan was developed that included a surveillance plan, laboratory testing, and contact tracing guidance. Infection control guidance was developed for use in health care settings and traveler guidance was developed for the public.6 The US Centers for Disease Control and Prevention (CDC) distributed MERS-CoV polymerase chain reaction test kits to state health departments. Two cases were imported into the United States. Contacts were traced, including household, hospital, and airline contacts. No secondary cases were identified in the United States. MERS-CoV was thought to be severe and control measures relied on recognition of suspect cases. However, during a hospital outbreak in Jeddah, Saudi Arabia, among hospitalized patients only 5 of 53 (9%) health care–associated cases had documented presence in the same room as a patient with MERS.5 Despite the high case-fatality rate (an important measure of severity), MERS cases can be asymptomatic and mild (25% in one outbreak). Although it is not known how often asymptomatic or mildly symptomatic patients transmit MERS, initiating comprehensive measures such as isolating patients suspected of having or having been exposed to the virus and using personal protective equipment when caring for them may be extremely difficult because so many patients have mild and nonspecific symptoms.
Is the world ready for a respiratory virus with high transmissibility and severity? After a new influenza virus (H7N9) was identified in China in 2013, a series of modeling articles described the effect of, and level of preparedness for, a severe, single-wave pandemic in the United States.7 In scenarios that used clinical attack rates (the proportion of individuals who become ill with or die from a disease in a population initially uninfected) of 20% to 30% (for comparison the clinical attack rate was 20% in the first year of the 2009 H1N1 pandemic), depending on severity there would be an estimated 669 000 to 4.3 million hospitalizations and an estimated 54 000 to 538 000 deaths without any interventions in the United States. The models suggested that without a vaccine, school closures would be unlikely to affect the pandemic, an estimated 35 000 to 60 000 ventilators would be needed, up to an estimated 7.3 billion surgical masks or respirators would be required, and perhaps most important, if vaccine development did not start before the virus was introduced, it was unlikely that a significant number of hospitalizations and deaths could be averted due to the time it takes to develop, test, manufacture, and distribute a vaccine.
It is impossible to know what will happen so early in this novel 2019 coronavirus (2019-nCoV) epidemic. The scope, morbidity, and mortality will depend on the combination of severity and transmissibility. Numerous experts have “nowcasted” how many cases have occurred and forecasted how many cases will likely occur. A recent study suggests rapid person to person transmission can occur.8 Disease modelers have estimated R0 to be 2.2.9 The University of Hong Kong estimates the outbreak could infect more than 150 000 persons per day in China at its peak.
Is 2019-nCoV infection severe? To date approximately 14% of cases of 2019-nCoV have been described as severe by WHO, with a case-fatality rate of 2.1%.10 Estimates of severity are usually higher in the beginning of an epidemic due to the identification of the most severely affected cases and decline as the epidemic progresses. However, because many infected persons have not yet recovered and may still die, the case-fatality rate and severity could be underestimated. On January 30, 2020, WHO officially declared the 2019-nCoV epidemic as a Public Health Emergency of International Concern, indicating its concern that countries aside from China could be affected by 2019-nCoV.
In preparing for possible sustained transmission of 2019-nCoV beyond China, applicable lessons from previous experiences with epidemics/pandemics of respiratory viruses should be carefully considered to better control and mitigate potential consequences. Influenza preparedness plans have been developed that aim to stop, slow, or limit the spread of an influenza pandemic to the United States. These plans address limiting domestic spread and mitigating disease but also sustaining infrastructure and reducing the adverse effects of the pandemic on the economy and society. These plans would be useful to enact during the 2019-nCoV epidemic should the United States experience sustained transmission. Countries have been successful in the past and there is nothing yet to predict that this time it is likely to be worse. Effective prevention and control will not be easy if there is sustained transmission and will require the full attention of public health, federal and local governments, the private sector, and every citizen.
Back to topArticle Information
Corresponding Author: David L. Swerdlow, MD, Clinical Epidemiology Lead, Medical Development and Scientific/Clinical Affairs, Pfizer Vaccines, 500 Arcola Rd, Collegeville, PA 19426 ([email protected]).
Published Online: February 11, 2020. doi:10.1001/jama.2020.1960
Conflict of Interest Disclosures: Dr Swerdlow reports owning stock and stock options in Pfizer Inc. Dr Swerdlow also reports providing a one-time consultation consisting of an overview of SARS and MERS epidemiology to GLG Consulting and receiving an honorarium. Dr Finelli reports owning stock in Merck and Co.
Funding/Support: Pfizer Inc provided salary support for Dr Swerdlow.
Role of the Funder/Sponsor: Pfizer Inc reviewed the manuscript and approved the decision to submit the manuscript for publication.
References
1.
Swerdlow DL, Finelli L, Bridges CB. 2009 H1N1 influenza pandemic: field and epidemiologic investigations in the United States at the start of the first pandemic of the 21st century. Clin Infect Dis. 2011;52(suppl 1):S1-S3. doi:10.1093/cid/ciq005PubMedGoogle ScholarCrossref
2.
Balcan D, Hu H, Goncalves B, et al. Seasonal transmission potential and activity peaks of the new influenza A(H1N1): a Monte Carlo likelihood analysis based on human mobility. BMC Medicine. 2009;7(45). doi:10.1186/1741-7015-7-45
3.
Dawood FS, Iuliano AD, Reed C, et al. Estimated global mortality associated with the first 12 months of 2009 pandemic influenza A H1N1 virus circulation: a modelling study. Lancet Infect Dis. 2012;12(9):687-695. doi:10.1016/S1473-3099(12)70121-4PubMedGoogle ScholarCrossref
4.
Chowell G, Castillo-Chavez C, Fenimore PW, Kribs-Zaleta CM, Arriola L, Hyman JM. Model parameters and outbreak control for SARS. Emerg Infect Dis. 2004;10(7):1258-1263. doi:10.3201/eid1007.030647PubMedGoogle ScholarCrossref
5.
Killerby ME, Biggs HM, Midgley CM, Gerber SI, Watson JT. Middle East respiratory syndrome coronavirus transmission. Emerg Infect Dis. 2020;26(2):191-198. doi:10.3201/eid2602.190697PubMedGoogle ScholarCrossref
6.
Rasmussen SA, Watson AK, Swerdlow DL. Middle East respiratory syndrome (MERS). Microbiol Spectr. 2016;4(3). doi:10.1128/microbiolspec.EI10-0020-2016PubMedGoogle Scholar
7.
Swerdlow DL, Pillai SK, Meltzer MI, eds. CDC modeling efforts in response to a potential public health emergency: influenza A(H7N9) as an example. Clin Infect Dis. 2015;60(suppl):S1-S63. https://academic.oup.com/cid/issue/60/suppl_1.Google Scholar
8.
Wang D, Hu B, Hu C, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus–infected pneumonia in Wuhan, China. JAMA. Published online February 7, 2020. doi:10.1001/jama.2020.1585
ArticlePubMedGoogle Scholar
9.
Li Q, Guan X, Wu P, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus–infected pneumonia. N Engl J Med. Published online January 29, 2020. doi:10.1056/NEJMoa2001316PubMedGoogle Scholar
10.
World Health Organization. Novel coronavirus (2019-nCoV) situation reports. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports/. Accessed February 4, 2020.
Comment
2 Comments for this articleEXPAND ALL
February 12, 2020
Understanding R and Disease Control
Oz Mansoor | Public Health Physician, Wellington
The message, that we need to prepare for a pandemic is vital. But the article misreports some key ideas. Firstly, SARS was not controlled "because a high proportion of cases were severe." While that helped , it was because cases were not infectious before some days after symptom onset (usually in the second week of illness). This gave more time for case identification and isolation. And most cases did not pass on infection to anybody, but a few spread to many. When all such individuals were identified and isolated, spread stopped.
Unfortunately, the new virusappears to be spreading from people much earlier in the course of illness, and even with mild symptoms - which was never documented for SARS. However, it is not clear that it is any different or better at spread between people, and perhaps with the same pattern of most cases not causing further spread.
Secondly, the R0, the basic reproduction number, is correctly described as the average number of infections each case causes. But it lacks two key ideas: 1) the 0 after the R implies the native state, which is a fully susceptible population and without any control measures. R is the effectiive number and can include the impact of control measures.
To claim that it was the lack of transmissibility, rather than the control measures that ended SARS, is not based on any evidence. And it ignores the heroic efforts of affected countries.
Elimination of SARS demonstrated the potential of globally coordinated collective action, as well as the damage caused by ignorance and prejudice. Most seem to have already forgotten the lessons of SARS.CONFLICT OF INTEREST: Worked for WHO/WPRO in SARS responseREAD MORE
February 24, 2020
COVID 19: a global presence and not only a new pathogen?
Giuliano Ramadori, Professor of Medicine | University Clinic, Göttingen, Germany
In the winter season there comes the time of upper and lower respiratory tract infections characterised by cough, dyspnea and eventually fever (influenza-like illness).Some of the patients, especially older people living alone affected by the disease ,may need hospitalization and eventually intensive care. In many of the cases who are hospitalized nasal and/or tracheal fluid are examined for viral or bacterial agents. Only in less than 50% of the cases influenza viruses are considered to be the cause of the disease.In the rest of the cases diagnostic procedure for human coronaviruses is not performed routinely. One of the fourdifferent Human Coronaviruses (HuCoV: 229E,NL 63,0C43 and HKU1) can however be found in up to 30% ofpatients negative for influenza viruses (1). Chinese scientists in Wuhan, who had to deal with an increasing number of acute respiratory tract diseases resembling viral pneumonia, performed deep sequencing analysis from samples taken from the lower respiratory tract and found a "novel" coronavirus. The sequence of the complete genome was made public. At the same time, however, the notice from Wuhan brought to mind the SARS- and MERS-epidemics. The measures taken by the Chinese- and WHO-authorities are now well known.
Recently about 150 new cases have been identified in northern Italy and health authorities are still looking for case 0 (the source). Is it possible that COVID-19 was already existent in Italy -- and not only in Italy but possibly everywhere in the world -- and that newly available nucleotide sequence allows now to find the cause of previously undefined influenza-like illness?
REFERENCE
1. Benezit F et al.:Non-influenza respiratory viruses in adult patients admitted with influenza-like illness:a 3- year prospective multicenter study.Infection, 13 february 2020, https://doi.org/10.1007/s15010-019-01388-1).CONFLICT OF INTEREST: None ReportedREAD MORE
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Silverchair Logo | What influenza virus was identified in China in 2013? | false | 251 | {
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1,687 | Interactome analysis of the lymphocytic choriomeningitis virus nucleoprotein in infected cells reveals ATPase Na(+)/K(+) transporting subunit Alpha 1 and prohibitin as host-cell factors involved in the life cycle of mammarenaviruses
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5834214/
SHA: efbd0dfc426da5dd25ce29411d6fa37571623773
Authors: Iwasaki, Masaharu; Minder, Petra; Caì, Yíngyún; Kuhn, Jens H.; Yates, John R.; Torbett, Bruce E.; de la Torre, Juan C.
Date: 2018-02-20
DOI: 10.1371/journal.ppat.1006892
License: cc0
Abstract: Several mammalian arenaviruses (mammarenaviruses) cause hemorrhagic fevers in humans and pose serious public health concerns in their endemic regions. Additionally, mounting evidence indicates that the worldwide-distributed, prototypic mammarenavirus, lymphocytic choriomeningitis virus (LCMV), is a neglected human pathogen of clinical significance. Concerns about human-pathogenic mammarenaviruses are exacerbated by of the lack of licensed vaccines, and current anti-mammarenavirus therapy is limited to off-label use of ribavirin that is only partially effective. Detailed understanding of virus/host-cell interactions may facilitate the development of novel anti-mammarenavirus strategies by targeting components of the host-cell machinery that are required for efficient virus multiplication. Here we document the generation of a recombinant LCMV encoding a nucleoprotein (NP) containing an affinity tag (rLCMV/Strep-NP) and its use to capture the NP-interactome in infected cells. Our proteomic approach combined with genetics and pharmacological validation assays identified ATPase Na(+)/K(+) transporting subunit alpha 1 (ATP1A1) and prohibitin (PHB) as pro-viral factors. Cell-based assays revealed that ATP1A1 and PHB are involved in different steps of the virus life cycle. Accordingly, we observed a synergistic inhibitory effect on LCMV multiplication with a combination of ATP1A1 and PHB inhibitors. We show that ATP1A1 inhibitors suppress multiplication of Lassa virus and Candid#1, a live-attenuated vaccine strain of Junín virus, suggesting that the requirement of ATP1A1 in virus multiplication is conserved among genetically distantly related mammarenaviruses. Our findings suggest that clinically approved inhibitors of ATP1A1, like digoxin, could be repurposed to treat infections by mammarenaviruses pathogenic for humans.
Text: Introduction Mammarenaviruses (Arenaviridae: Mammarenavirus) cause chronic infections of rodents worldwide [1] . Invasion of human dwellings by infected rodents can result in human infections through mucosal exposure to aerosols or by direct contact of abraded skin with infectious material. Several mammarenaviruses cause viral hemorrhagic fevers (VHFs) in humans and pose important public health problems in their endemic areas [2] [3] [4] [5] [6] . Mammarenaviruses are classified into two main groups, Old World (OW) and New World (NW) [1] . The OW Lassa virus (LASV), causative agent of Lassa fever (LF), is the most significant OW mammarenaviral pathogen. LASV is estimated to infect several hundred thousand individuals annually in Western Africa, resulting in a high number of LF cases associated with high morbidity and lethality. Moreover, LASV endemic regions are expanding [7] , and the association of the recently identified mammarenavirus Lujo virus with a VHF outbreak in Southern Africa [8, 9] has raised concerns about the emergence of novel VHF-causing mammarenaviruses. The most significant NW mammarenavirus is Junín virus (JUNV), which causes Argentinian hemorrhagic fever [10] . The worldwide-distributed OW mammarenavirus lymphocytic choriomeningitis virus (LCMV) is a neglected human pathogen of clinical significance especially in congenital infections [11] [12] [13] [14] [15] . Moreover, LCMV poses a particular threat to immunocompromised individuals, as has been illustrated by fatal cases of LCMV infection associated with organ transplants [16, 17] . However, LCMV research can be safely performed at BSL-2 containment, rather than the BSL-4 containment necessary for live LASV or JUNV research [18] .
No US Food and Drug Administration (FDA)-licensed vaccines are available for the treatment of arenavirus infections, although a live attenuated vaccine strain of JUNV, Candid#1, is licensed in Argentina. Likewise, current anti-mammarenavirus therapy is limited to an offlabel use of the nucleoside analogue ribavirin that is only partially effective and can cause significant side effects [19] [20] [21] . Development of effective anti-mammarenavirus drugs has been hampered by the lack of detailed understanding of virus/host-cell interactions required for mammarenavirus multiplication that could represent amenable targets for antiviral therapy. the potential problem that overexpression of a single viral gene product may potentiate PPI interactions that are not relevant during the course of a natural virus infection. To overcome this issue, we designed a recombinant LCMV (rLCMV) encoding a tandem [WSHPQFEK (GGGS) 3 WSHPQFEK] Strep-tag fused to the amino-terminus of NP (rLCMV/Strep-NP) (Fig 1A and 1B) . To facilitate the identification of specific PPI between NP and host cell proteins, we used our mammarenavirus tri-segmented (r3) platform [30] to design an r3LCMV expressing a C-terminus Strep-tag version of enhanced green fluorescent protein (r3LCMV/eGFP-Strep) that we used as a negative control (Fig 1A and 1B) . We rescued rLCMV/Strep-NP and r3LCMV/eGFP-Strep and confirmed the expression of strep-tagged NP and eGFP in rLCMV/ Strep-NP-and r3LCMV/eGFP-Strep-infected cells, respectively (Fig 1C) . Next, we examined the growth properties of rLCMV/Strep-NP and r3LCMV/eGFP-Strep in three different cells lines from hamsters, humans, and nonhuman primates (BHK-21, A549, and Vero E6 cells, respectively) (Fig 1D) . The fitness of rLCMV/Strep-NP and r3LCMV/eGFP-Strep was modestly decreased compared to that observed with wild-type (WT) Armstrong (rLCMV ARM) and Clone 13 (rLCMV Cl-13) strains of LCMV. However, both rLCMV/Strep-NP and r3LCMV/eGFP-Strep had WT-like growth kinetics and reached high titers. As with WT LCMV, infection with rLCMV/Strep-NP prevented production of bioactive IFN-I by cells in response to Sendai virus (SeV) infection as determined using an IFN bioassay based on protection against the cytopathic effect (CPE) induced by infection with vesicular stomatitis virus (VSV) (Fig 1E) . Vero cells treated for 16 h with tissue cultured supernatants (TCS) from A549 cells infected first with WT LCMV or rLCMV/Strep, followed by 24 h infection with SeV, remained fully susceptible to VSV-induced CPE. In contrast, Vero cells treated with TCS from A549 cells infected with rLCMV/NP(D382A), a mutant unable to prevent induction of IFN-I [30] , and subsequently with SeV, were protected against VSV induced CPE.
We selected the human A549 cell line because lung epithelial cells are one of the initial cell targets of humans following inhalation of mammarenavirions. We infected A549 cells (multiplicity of infection [MOI] = 0.1) with either rLCMV/Strep-NP or r3LCMV/eGFP-Strep (Fig 2A) . At 48 h post-inoculation (pi), we prepared total cell lysates for pull-down (PD) assays using a sepharose resin coated with strep-tactin. Aliquots of the protein complexes present in the PD samples were fractionated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) (Fig 2B) followed by SYPRO Ruby protein gel staining. We compared the pattern of stained protein bands detected between rLCMV/Strep-NP-and r3LCMV/eGFP-Strepinfected samples and confirmed the presence of Strep-NP and eGFP-Strep in pertinent samples (Fig 2B) . Protein complexes in the rest of eluates from the PD samples were concentrated by trichloroacetic acid (TCA) precipitation and subjected to trypsin digestion (Fig 2A) . Digested peptides were subjected to liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis using a hybrid mass spectrometer consisting of linear quadrupole ion dual cell trap (LTQ) Velos and an Orbitrap analyser.
We classified host-cell proteins identified by LC-MS/MS analysis from two independent biological replicates into two groups: 1) proteins found only in Strep-NP PD samples with at least five spectral counts ( Table 1) , and 2) proteins found in both Strep-NP and eGFP-Strep PD samples with five or higher spectral counts in Strep-NP samples and at least 2-fold higher spectral counts in Strep-NP PD compared to eGFP PD samples ( Table 2) . Filtering the data using these criteria resulted in identification of 139 candidate host-cell proteins as NP-interacting partners. Among 53 proteins found present in both NP-and eGFP-PD samples, 36 had spectral counts in the NP-PD sample that were less than two-fold higher than their corresponding spectral counts in the eGFP-PD sample (Fig 2C and S1 Table) . Based on the criteria we described above, we considered these proteins to be highly unlikely specific NPinteractors with an involvement in the LCMV life cycle, and therefore we did not consider these hits for further analysis. However, we acknowledge that we cannot formally rule out that some of these hits could still play a role on the life cycle of LCMV.
The protein annotation through evolutionary relationship (PANTHER) protein family classification (Biological Process) of the NP-interacting protein candidates revealed that a large number of proteins were involved in metabolic and cellular processes (Fig 2D) . We also analyzed the molecular functions of the NP-interacting protein candidates according to the PAN-THER protein profile classification (Fig 2E) , which revealed diversified biochemical functions enriched for nucleic acid-binding proteins and chaperones.
To initially assess pro-or anti-viral roles of NP-interacting host-cell proteins identified by LC-MS/MS, we examined the effect of small interfering RNA (siRNA)-mediated knockdown (kd) of each of the corresponding genes on multiplication of rLCMV expressing reporter gene ZsGreen (ZsG) in A549 cells (Fig 3A) . The siRNAs we used were from the genome-wide ON TARGET-Plus (OTP) Human siRNA library (18,301 genes, 4 siRNAs/gene). OTPs are latest generation of siRNAs and offer significant advantages over previous generations. Off-target effects are primarily driven by antisense strand microRNA (miR)-like seed activity. In OTPs, the sense strand is modified to favor antisense strand uptake whereas the antisense strand seed region is modified to drastically reduce seed-related off-targeting [33] . In addition, OTPs are designed on the foundation of the SMARTselection algorithm (Dharmacon), widely considered to be the best algorithm for rational siRNA design strategy. Numerous host-cell factors showed an anti-LCMV effect (increased ZsG expression by kd of the genes), including microtubule-associated protein 1B (MAP1B) [ [38] , dengue virus 2 (DENV-2) [39] , and chikungunya virus (CHIKV) [40] .
To begin assessing the potential biological implications of the identified NP-host cell protein interactions, we selected ATP1A1 and PHB given the availability of reagents, existing knowledge about their roles in cell physiology, and evidence of participation in multiplication of other viruses. We confirmed that cells transfected with siRNA specific to ATP1A1 and PHB exhibited the predicted reduced levels in ATP1A1 and PHB protein expression (Fig 3B) . Likewise, we examined whether siRNA-mediated reduced expression levels of ZsGreen correlated with reduced LCMV progeny titers. For this, we transfected A549 cells with siRNA targeting Expression of Strep-tagged proteins. A549 cells seeded (5.0 x 10 5 cells/well) in a 6-well plate and cultured overnight were infected (MOI = 0.1) with the indicated rLCMVs. At 48 h pi, total cell lysates were prepared, and protein expression was analyzed by western blotting. (D) Growth properties of rLCMV expressing Strep-tagged proteins. BHK-21 (1.75 x 10 5 cells/well), A549 (1.25 x 10 5 cells/well), or Vero E6 (1.25 x 10 5 cells/well) cells seeded in 24-well plates and cultured overnight were infected (MOI = 0.01) with the indicated rLCMVs. At the indicated times pi, TCSs were collected and virus titers determined by IFFA. Results represent means ± SD of the results of three independent experiments. (E) Lack of induction of IFN-I in cells infected with rLCMV/Strep-NP. A549 cells were infected (MOI = 0.1) with the indicated rLCMV or mock-infected, and 36 h later infected with SeV (MOI = 1). At 24 h pi with SeV, TCS were collected and used, following virus inactivation by U.V., to treat Vero E6 cells for 16 h, followed by infection with rVSV (MOI = 0.1) [rVSV(+)] or mockinfection [rVSV (-) ]. At 24 h pi with rVSV, cells were fixed with 4% PFA and stained with crystal violet to assess rVSV-induced cytopathic effect. We used as control rLCMV/NP(D382A) that contains mutation D382A within NP, which has been shown to abrogate the NP's ability to counteract the induction of IFN-I production.
https://doi.org/10.1371/journal.ppat.1006892.g001 ATP1A1 or with NC siRNA 72 h prior to infection with rLCMV/ZsG. We found that siRNAmediated kd of ATP1A1 dramatically inhibited ZsGreen expression (Fig 3Ci) , which was associated with a significant reduction of infectious LCMV progeny (Fig 3Cii) . Our attempts to see interaction between NP and ATP1A1 or NP and PHB by co-immunoprecipitation were unsuccessful. Several possibilities could account for this, including interactions of low affinity or high on/off rate or both. Another consideration is that only a minor fraction of NP might be engaged in the interaction with a given host cell protein, and therefore, detection of these interactions would require highly sensitive methods such as LC-MS/MS. To overcome this problem we used confocal microscopy to examine the co-localization of NP with ATP1A1 and PHB in LCMV-infected cells. Weighted co-localization coefficients (CC), determined by taking into consideration the brightness of each channel signal, were significantly higher than non-weighted CC, indicating the presence of brighter pixels in the co-localized regions compared to the non-co-localized regions (Fig 4) .
The cardiac glycoside ouabain is an inhibitor of ATP1A1 that has been used to treat congestive heart failure in European countries [41] . The PHB inhibitor rocaglamide is a flavagline from an Aglaia tree used in traditional Chinese medicine [42] that has potent anticancer activity [43] . To examine whether pharmacological inhibition of ATP1A1 or PHB inhibited LCMV multiplication, we pretreated human (A549 and HEK 293T), nonhuman primate (Vero E6), and rodent (murine L929 and hamster BHK-21) cells with ouabain or rocaglamide and infected them with rLCMV/eGFP (S1 Fig). Ouabain treatment resulted in a strong dosedependent inhibition of eGFP expression in infected human-and nonhuman primate cells, but did not affect eGFP expression intensity in infected rodent cells (S1A Fig) . This finding is consistent with rodents expressing an ATP1A1 allele that is resistant to ouabain inhibition [44] .
Likewise, we observed a dose-dependent rocaglamide inhibition of eGFP expression in all cell lines infected with rLCMV/eGFP (S1B Fig) . Consistent with these findings, production of infectious LCMV progeny was reduced by treatment with either ouabain or rocaglamide ( Fig 5A) within a concentration range that had minimal impact on cell viability (Fig 5B) . To examine the correlation between efficacy and cytotoxicity of these compounds, we determined their therapeutic index (TI = CC 50 /IC 50 (Fig 5Bi) ; whereas rocaglamide had TIs of >105 (CC 50 > 1000 nM, IC 50 = 9.51 nM) and 10.3 (CC 50 = 100 nM, IC 50 = 9.75 nM) in A549 and Vero E6 cells, respectively (Fig 5Bii) . Moreover, the ATP1A1 antagonist inhibitor, bufalin, also exhibited robust anti-LCMV activity with TIs of 8.92 (CC 50 Heat shock protein HSP 90-alpha HSP90AA1 P07900 8 10 9
Endoplasmin HSP90B1 P14625 9 9 9
Large neutral amino acids transporter small subunit 1 SLC7A5 Q01650 6 12 9
Keratin, type II cuticular Hb1 KRT81 Q14533 10 8 9
Putative helicase MOV-10 MOV10 Q9HCE1 8 10 9
Microtubule-associated protein 1B MAP1B P46821 6 11 8.5
Spectrin beta chain, rocaglamide (100 nM) (Fig 5C) , further supporting a specific anti-LCMV activity of ouabain and rocaglamide that was not due to reduced cell viability.
To gain insights about the mechanisms by which ouabain and rocaglamide exert their anti-LCMV activity, we examined effects of these compounds on distinct steps of the LCMV life cycle. First, we asked whether ouabain and rocaglamide affected cell entry of LCMV. We conducted time-of-addition experiments in which we treated cells with ouabain or rocaglamide prior to virus inoculation (-1.5 h), at the time of inoculation (0 h), or 1.5 h pi (+1.5 h) (Fig 6A) .
In some samples, we used ammonium chloride starting at 4 h pi to block multiple rounds of virus infection. The timing of compound addition did not significantly change the number of eGFP-positive cells, indicating that neither ouabain nor rocaglamide inhibited cell entry of LCMV. The number of eGFP + cells in ouabain-treated cells was reduced at all time-of-addition points compared to vehicle dimethyl sulfoxide (DMSO)-treated cells, but was similar to that observed in ammonium chloride-treated cells. Thus, ouabain did not inhibit LCMV RNA replication and gene expression, but rather a late step of the LCMV life cycle. In contrast, rocaglamide treatment resulted in a negligible number of eGFP + cells, indicating that rocaglamide inhibited virus RNA replication and gene transcription.
To further investigate the effect of ouabain and rocaglamide on virus RNA synthesis, we infected A549 cells with a recombinant single-cycle infectious LCMV expressing eGFP (rLCMVΔGPC/eGFP) and treated cells with either ouabain or rocaglamide. Seventy-two hours later, we determined percent normalized eGFP expression in infected cells (Fig 6B) . Consistent with our results from the time-of-addition experiment, ouabain did not affect reporter eGFP expression. However, rocaglamide reduced eGFP expression, confirming inhibitory effect of rocaglamide on virus RNA synthesis.
We also examined the effect of ouabain and rocaglamide on the late step of the arenavirus life cycle, Z-mediated budding. For this experiment, we transfected cells with Z-Strep-and Z-FLAG (DYKDDDDK epitope)-expressing plasmids from LCMV and LASV, respectively. At 24 h post-transfection, we removed the tissue culture supernatant (TCS) and washed extensively transfected cells to eliminate already budded Z. We cultured the transfected cells in the presence or absence of ouabain or rocaglamide. At 24 h, we determined by WB levels of Z protein in both whole cell lysates and associated with virus-like particles (VLPs) collected from TCS. Treatment with rocaglamide, but not with ouabain, caused a reduction in both LCMV and LASV Z budding efficiency (Fig 6C and 6D) . The reproducibility of these findings was confirmed based on results from four independent experiments (Fig 6E) . We also examined whether ouabain could interfere with a step of assembly of infectious progeny that was not captured by the Z budding assay through two additional experiments. The first experiment involved the use of a newly generated single-cycle infectious recombinant LCMV expressing the reporter gene ZsGreen (scrLCMV/ZsG-P2A-NP) to infect (MOI = 0.1) A549 cells (1 st infection). These cells were subsequently transfected with a plasmid expressing LCMV GPC. After 24 h, we used TCS to infect a fresh cell monolayer (2 nd infection) and identified infected cells based on ZsGreen expression. To assess the effect of ouabain on de novo assembly of infectious progeny we determined normalized ratios (2 nd /1 st infection) of ZsGreen + cells (Fig 6F) . The second experiment involved infection (MOI = 0.1) of cells with WT LCMV, and 48 h later we washed infected cells three times to remove the extracellular infectious progeny produced during the first 48 h of infection. Then, fresh media containing ouabain or DMSO vehicle control were added, and 24 h later we determined virus titers in TCS (Fig 6G) . Results from both experiments consistently showed that ouabain did not inhibit assembly de novo of extracellular infectious virus.
Combination therapy can significantly alleviate the problem posed by the rapid emergence of drug-resistant variants commonly observed during monotherapy strategies to control RNA virus infections. Since ouabain and rocaglamide inhibited different steps of the LCMV life cycle, we examined whether their use in combination results in a synergistic anti-LCMV effect. For this experiment, we infected A549 cells with rLCMV/eGFP and treated them with ouabain and rocaglamide using different concentrations and combinations. At 48 h pi, we determined percent eGFP expression (Fig 7) . Combination treatment with ouabain and rocaglamide resulted in synergistic anti-LCMV activity that was enhanced under conditions using higher concentrations of ouabain and lower concentrations of rocaglamide.
We next asked whether the ATP1A1 and PHB host-cell factors contributed also to multiplication of viral hemorrhagic fever-causing LASV. We treated A549 cells with ouabain, bufalin, or rocaglamide and inoculated the treated cells with recombinant LASV expressing eGFP (rLASV/eGFP). eGFP expression was examined 48 h later. Similar to rLCMV infection, LASV multiplication was restricted in ouabain-, bufalin-, or rocaglamide-treated cells at concentrations minimally impacting cell viability, although their IC 50 values were slightly higher than those found with the LCMV infection system (Fig 5B and S2 Fig) as ouabain had IC 50 of 9.34 nM, bufalin had IC 50 of 1.66 nM and rocaglamide had IC 50 of 37.0 nM (Fig 8) . We also tested the effect of compounds targeting ATP1A1 and PHB on multiplication of JUNV. Consistent with our results obtained with LCMV and LASV, ouabain, bufalin, and rocaglamide strongly suppressed JUNV multiplication (S3 Fig). These findings indicate that ATP1A1 and PHB function as pro-viral factors of a range of mammarenaviruses.
We identified ATP1A1 and PHB as novel host-cell proteins that contribute to efficient multiplication of mammarenaviruses. Our approach using a recombinant LCMV expressing NP with an affinity tag facilitated defining the NP interactome in the context of LCMV infection. Recently, using an NP-specific monoclonal antibody (mAb) to precipitate NP and associated cellular protein partners in a mammarenavirus NP interactome, King et al. identified 348 host proteins that associated with LCMV NP [45] . We found 99 common proteins between our filtered LCMV NP interactome of 171 proteins and the LCMV NP interactome documented by King et al. Differences in both experimental conditions and analysis methodologies used to generate the LCMV NP interactome documented by King et al. and ours likely h post-transfection, cells were washed with fresh media to eliminate Z-mediated production of VLPs in the absence of compound treatment, and cultured for another 24 h in fresh media in the presence of ouabain or Roc-A at the indicated concentrations. VLPs present in TCS were collected by ultracentrifugation, and cell lysates were prepared. Z protein expression in VLPs and cell lysates were determined by western blots using antibodies to Strep-tag (C) and FLAG-tag (D). Budding efficiency for each sample was estimated by dividing the signal intensity of the Z protein associated with VLPs by that of Z detected in the cell lysate. Numbers on the bottom of panel C correspond to LCMV Z budding efficiencies determined in a representative experiment. Results shown in panel E correspond to the average and SD from four independent experiments including the one shown in panel D. The mean budding efficiency of DMSO treatedsamples was set to 100%. Data represent mean ± SD of four independent experiments. (F) Effect of ouabain on incorporation of viral glycoprotein into virions. 293T cells seeded (4.0 x 10 5 cells/well) in a 12-well plate and cultured overnight were infected (MOI = 0.1) with scrLCMV/ZsG (1 st infection) for 2 h and subsequently transfected with 0.5 μg of pC-GPC. At 24 h pi, cells were washed with fresh medium to eliminate infectious virus particle produced in the absence of compound treatment, and cultured for another 24 h in fresh media in the presence of ouabain at 40 nM (OUA). At 48 h pi, TCS was collected and used to infect fresh monolayer of BHK-21 cells (2 nd infection) seeded (4.0 x 10 5 cells/well) in a 12-well plate 1 day before the infection, and 293T cell lysate was prepared. 24 h later, BHK-21 cell lysate was prepared. ZsGreen signal intensity was measured by a fluorescent plate reader. GP-incorporation efficiency was estimated by dividing ZsGreen signal intensity in BHK-21 cell lysate (2 nd ) by that in 293T cell lysate (1 st ). The mean GP-incorporation efficiency of DMSO treated samples was set to 100%. Data represent means ± SD from three independent experiments. contributed to the observed differences between data sets. Despite progress in the implementation of global proteomics-based screens to identify virus-host protein-protein interactions, overlap between datasets for the same viral system is usually limited. However, the substantial overlap of 99 of the 171 NP-interacting proteins from both studies supports the overall reliability of both systems. We used results of the eGFP-Strep interactome, determined in r3LCMV/eGFP-Strep-infected cells, as a control to filter out non-specific NP interactions, which may have resulted in a higher degree of stringency than in the study by King et al for selection of NP-interacting candidates. The combined information provided by the NP interactome reported by King et al. and the one we present in this work, will facilitate future studies to further characterize the functional and biological implications of NP-host cell interacting proteins.
All tested mammarenavirus NPs, with exception of the NP from TCRV, blocked IRF-3-dependent IFN-I induction [25, 46] . The anti-IFN activity of NP was mapped to its C-terminal part and linked to the 3'-5' exonuclease domain present with the NP C-terminal part [30] . Inhibitor-B kinase ε (IKKε) was identified as an NP-binding protein using plasmid-mediated overexpression in transfected cells [47] , and the NP-IKKε binding affinity correlated with NP's ability to inhibit IFN-I induction [47] . We, as well as the work by King et al. [45] , did not detect this NP-IKKε interaction. This discrepancy may have been caused by very low expression of IKKε in LCMV-infected cells, which prevented detection of IKKε by LC-MS/MS. Alternatively, NP-IKKε interaction could possibility be temporarily regulated and take place at early times pi, but could be mostly absent at 48 h pi, the time at which we prepared the cell lysates for our proteomics studies. Future studies comparing the NP interactome at different times during infection will contribute to a better understanding of the dynamics of NP/hostcell protein interactions.
Na + /K + -ATPase is a well-characterized membrane ion transporter and is composed of two functional subunits (α and β) and one regulatory γ subunit [48] . ATP1A1 represents one of four α subunits [49, 50] . Recent evidence has suggested that the Na + /K + -ATPase is involved in multiple cell signaling pathways that are independent of its ion-pumping function [51] . Cardiac glycoside inhibitors of the Na + /K + -ATPase (NKA), so-called cardiotonic steroids (CST; e.g., ouabain, bufalin), have been shown to inhibit multiplication of different viruses including Ebola virus [35], coronaviruses [36], herpes simplex virus 1 [52, 53] , CHIKV [54] , human immunodeficiency virus 1 (HIV-1) [55] , adenovirus [56] and porcine reproductive and respiratory syndrome virus 1 [57] .
Different mechanisms are likely to contribute to the antiviral activity of CSTs, including altered cell functions modulated by the signaling activity of Na + /K + -ATPase [58] . Thus, a low concentration of ouabain induces a conformational change in ATP1A1 that results in activation and release of proto-oncogene tyrosine protein kinase, Src, from ATP1A1, followed by activation of as yet unknown downstream signaling that inhibits, for instance, cell entry of murine hepatitis virus (MHV) [59] . However, our results indicated that ouabain did not interfere with LCMV cell entry. In addition, treatment with the Src inhibitor 4-amino-5-(4-methylphenyl)-7-(t-butyl)pyrazolo [3,4-d] pyrimidine (PP1) did not counteract the anti-LCMV activity of ouabain (S4 Fig). Nevertheless, ATP1A1-mediated Src signaling could plausibly contribute to the inhibitory effect of ouabain on JUNV multiplication as similarly to that observed with MHV. Moreover, cell entry of JUNV occurs also by clathrin-mediated endocytosis [60] , a process affected by Src signaling. Ouabain has been clinically used in several European countries for the management of congestive heart failure, whereas bufalin has been tested in clinical trials for cancer treatments [61] , and the CST digoxin has been FDA-approved since 1997 to treat heart failure and atrial fibrillation. Hence, opportunities for the repurposing CSTs have potential as therapeutics to treat infections caused by viral hemorrhagic fever-causing arenaviruses.
The PHB inhibitor, rocaglamide, appeared to interfere with LCMV RNA synthesis and budding, but did not affect LCMV cell entry. In contrast, PHB was reported to be a cell entry receptor for DENV-2 [39] and CHIKV [40] . On the other hand, PHB did not act as a virus cell entry receptor for HCV. Rather, PHB contributed to HCV cell entry through binding to cellular RAF (c-Raf; proto-oncogene serine/threonine-protein kinase) and subsequent Harvey rat sarcoma proto-oncogene (HRas) activation that induces a signal transduction pathway required for epidermal growth factor receptor (EGFR)-mediated HCV cell entry [37] . In addition, siRNA-mediated kd of PHB decreased production of H5N1 FLUAV [38] . These findings indicate that PHB is involved in different steps of the life cycle of a variety of viruses, and thereby an attractive target for the development of broad-spectrum antiviral drugs.
Rocaglate is a group of natural compounds, which includes rocaglamide, that inhibits protein synthesis by targeting the ATP-dependent DEAD-box RNA helicase eukaryotic initiation factor 4A (eIF4A) and exerts anti-tumor activity [62, 63] . The rocaglate compound, silvestrol, inhibits Ebola virus multiplication likely by interfering with the role of eIF4A in viral protein translation [64] .
While we focused on two host proteins, ATP1A1 and PHB, in this study, our proteomics approach also identified several NP-interacting host-cell proteins whose kd expression via siRNA resulted in increased LCMV multiplication. These proteins, which included MAP1B, might have anti-LCMV activity. MAP1B has been shown to bind to nonstructural proteins 1 (NS1) and 2 (NS2) of human respiratory syncytial virus (HRSV) [34] . NS1 and NS2 of HRSV antagonizes host IFN-I response by reducing the levels of TNF receptor associated factor (TRAF3), IKKε (NS1), and STAT2 (NS2) [65] . NS2-MAP1B interaction interfered with HRSV NS2's ability to reduce levels of STAT2, whereas the role of NS1-MAP1B interaction remains to be determined [34] . Examining the role of NP-MAP1B interaction in modulating NP's ability to inhibit induction of type I IFN is of interest.
We identified among the NP-interacting host cell proteins the RNA helicase Moloney leukemia virus 10 (MOV10), which has been reported to be an antiviral factor for FLUAV [66] , retroviruses [67] [68] [69] [70] [71] , and DENV-2 [72] . We did not observe increased LCMV multiplication in cells subjected to siRNA-mediated kd of MOV10, a finding that would question an anti-LCMV activity of MOV10. However, we consider that LCMV has already optimal multiplication in A549 cells and further increases may occur only under rather unique conditions. MOV10 was shown to enhance IRF-3-mediated IFN-I induction following SeV infection through a tank binding kinase 1 (TBK1)-independent and IKKε-dependent manner. This finding was further supported by demonstrating MOV10-IKKε interaction by co-immunoprecipitation studies [73] . We documented that the anti-IFN activity of mammarenavirus NP correlated with its ability to interact with IKKε [47] . Whether NP-MOV10 interaction prevents MOV10 from enhancing IRF-3-mediated IFN-I induction remains to be determined.
Several members of the mammalian chaperonin-containing T-complex (CCT) were identified as prominent hits in our NP interactome. The mammalian CCT is critical for folding of many proteins with important functions in diverse cellular processes [74] , and may protect complex protein topologies within its central cavity during biosynthesis and folding [75] . The contribution of CCT members to NP assembly into a nucleocapsid structure could account for their presence in the NP, but not eGFP, interactome. Interestingly, members of the CCT have been implicated in multiplication of different viruses including rabies virus [76, 77] , HCV [78] and FLUAV [79] . However, the role of these CCT proteins in virus multiplication remains unknown and may involve functions other than acting as molecular chaperones.
Previous studies documented the presence of several components of the of eIF4F, including 4A, within viral replication-transcription complexes (RTC) detected in cells infected with LCMV [80] and TCRV [81] . These findings, together with the detection of a number of ribosomal proteins in the NP interactome, suggest that translation of viral mRNAs may take place within RTC. However, rocaglamide interference with the activity of eIF4A within the viral RTC might contribute to its anti-LCMV activity.
In this work, we documented the generation of rLCMV/Strep-NP and its use to define the NP-interactome in infected cells. We presented evidence that ATP1A1 and PHB contribute to efficient multiplication of mammarenaviruses using genetics and pharmacological inhibition of the genes. Consistent with our findings, bioinformatic analysis revealed that the protein network associated with ATP1A1 and PHB involves host cell proteins with functions in biological processes that have been implicated in virus multiplication (S5 Fig). The overall experimental approach described here can facilitate the identification of biologically relevant NP-interacting host-cell proteins. Future studies elucidating the roles of pro-and antiviral host-cell factors identified in this study in mammarenavirus multiplication will advance our understanding of the multiple functions of NP and uncover novel cellular targets for the development of antimammarenaviral drugs. In addition, by identifying proviral host-cell factors, drugs that are already approved can be repurposing as therapeutics to combat human pathogenic mammarenavirus infections.
Baby hamster kidney BHK-21 (American Type Culture Collection, ATCC, CCL-10), house mouse L929 (ATCC CCL-1), grivet Vero E6 (ATCC CRL-1586), human A549 (ATCC CCL-185), and human HEK 293T (ATCC CRL-3216) cells were grown in Dulbecco's modified Eagle's medium (Thermo Fisher Scientific, Waltham, MA) containing 10% heat-inactivated fetal bovine serum, 2 mM of L-glutamine, 100 mg/ml of streptomycin, and 100 U/ml of penicillin at 37˚C and 5% CO 2 .
WT recombinant LCMVs, Armstrong (rLCMV ARM) and clone-13 (rLCMV Cl-13) strains, were generated as described [30, 82, 83] . Generation of rLCMV/NP(D382A) and SeV, strain Cantell, was described [30, 82, 83 ]. An rLCMV lacking GPC and expressing eGFP (rLCMVΔGPC/eGFP) was generated by reverse genetics using procedures previously described [84] . rLCMV/Strep-NP and r3LCMV/eGFP-Strep were generated by reverse genetics using similar procedures to generate WT rLCMV and tri-segmented LCMV (r3LCMV) expressing eGFP [30] . For the generation of these novel rLCMVs, we created pol1S Cl-13 plasmids that directed Pol1-mediated intracellular synthesis of recombinant LCMV S genome RNA species coding for Strep-tagged NP or eGFP, respectively (Fig 1A and 1B) . The rLCMV expressing eGFP (rLCMV/eGFP) was generated as described [85] , and the rLCMV expressing ZsGreen (rLCMV/ZsG) instead of eGFP was generated by reverse genetics using similar procedures to generate rLCMV/eGFP. Generation of rLASV expressing eGFP (rLASV/eGFP) will be described elsewhere. A tri-segmented recombinant live-attenuated Candid #1 strain of JUNV expressing eGFP (r3JUNV/eGFP) was generated as described [86] . For the generation of a novel single cycle rLCMV expressing ZsGreen (scrLCMV/ZsG-P2A-NP), a pol1S plasmid was created by omitting GPC open reading frame (ORF) from pol1S plasmid used for the generation of rLCMV/ZsG. scrLCMV/ZsG-P2A-NP was rescued by reverse genetics using similar procedures to generate rLCMVΔGPC/eGFP [84] .
LCMV titers were determined by immunofocus forming assay (IFFA) as described [87] . Briefly, 10-fold serial virus dilutions were used to infect Vero E6 cell monolayers in a 96-well plate, and at 20 h pi, cells were fixed with 4% paraformaldehyde (PFA) in phosphate-buffered saline (PBS). After cell permeabilization by treatment with dilution buffer (DB) (0.3% Triton X-100 in PBS-containing 3% bovine serum albumin [BSA]), cells were stained with a rat mAb to NP (VL-4, Bio X Cell, West Lebanon, NH) conjugated with Alexa Fluor 488 (VL-4-AF488, Protein Labeling Kit, Life Technologies, Carlsbad, CA). VSV titers were determined by a plaque assay.
Total cell lysates were prepared in PD lysis buffer (+) (250 mM of NaCl, 50 mM of Tris-HCl [pH = 7.5], 0.5% TritonX-100, 10% glycerol, 1 mM of MgCl 2 , 1 μM of CaCl 2 , 1 μM of ZnCl 2 ) and clarified by centrifugation at 21,130 x g at 4˚C for 10 min. Clarified lysates were mixed at a 1:1 ratio with loading buffer (100 mM of Tris [pH 6.8], 20% 2-mercaptoethanol, 4% SDS, 0.2% bromophenol blue, 20% glycerol) and boiled for 5 min. Proteins samples were fractionated by SDS-PAGE using 4-20% gradient polyacrylamide gels (Mini-PROTEAN TGX gels 4-20%, Bio-Rad, Hercules, CA), and proteins were transferred by electroblotting onto polyvinylidene difluoride membranes (Immobilin Transfer Membranes, Millipore, Billerica, MA). To detect Strep-tagged proteins, membranes were reacted with mouse monoclonal antibodies to Strep (QIAGEN, Germantown, MD), eGFP (Takara Bio USA, Mountain View, CA), GP 2 (We33/ 36), ATP1A1 (TehrmoFisher Scientific, Rockford, IL), PHB (Abcam, Cambridge, MA) or rabbit polyclonal antibodies to α-tubulin (Cell Signaling Technologies, Danvers, MA) or glyceraldehyde-3-phosphate dehydrogenase (GAPDH, Millipore), respectively, followed by incubation with appropriate horseradish peroxidase-conjugated anti-mouse or anti-rabbit immunoglobulin G (IgG) antibodies (Jackson ImmunoResearch Laboratories, West Grove, PA). SuperSignal West Pico or Femto chemiluminescent substrate (Thermo Fisher Scientific) was used to elicit chemiluminescent signals that were visualized using ImageQuant LAS 4000 Imager (GE Healthcare Bio-Sciences, Pittsburgh, PA).
Pull down of strep-tagged proteins from infected cell lysate. A549 cells prepared in six 15-cm dishes (approximately 1.0 x 10 8 cells in total) were infected with either rLCMV/Strep-NP or r3LCMV/eGFP at an MOI of 0.1. At 48 h pi, cells were washed three times with ice-cold PBS, scraped into fresh ice-cold PBS, and centrifuged at 400 x g at 4˚C for 10 min. Supernatant was removed, and cells were lysed with 12 ml of PD lysis buffer (+) supplemented with halt protease and phosphatase inhibitor cocktail (Thermo Fisher Scientific) and 5 μg/ml of deoxyribonuclease I (Worthington Biochemical Corporation, Lakewood, NJ). Lysate was clarified by centrifugation at 3,900 x g at 4˚C for 30 min to remove cell debris. Clarified cell lysate was then incubated with strep-tactin sepharose resin (QIAGEN) at 4˚C. After 2 h of incubation, the resin was washed three times with PD lysis buffer (+) and once with PD lysis buffer without TritonX-100 (PD lysis buffer [-] ). After the centrifugation at 1,600 x g and 4˚C for 5 min, the last wash buffer was removed, and protein complexes associated with the resin were eluted into 2 ml of PD lysis buffer (-) containing 2.5 mM of desthiobiotin. The eluate was then subjected to TCA precipitation followed by trypsin digestion.
Multidimensional protein identification technology microcolumn. A MudPIT microcolumn was prepared by first creating a Kasil frit at one end of an un-deactivated 250-μm outside diameter (OD) capillary tube (interior diameter of 360 μm)(Agilent Technologies, Inc., Santa Clara, CA). The Kasil frit was prepared by briefly dipping a 20-30-cm capillary tube in 300 μl of Kasil 1624 potassium silicate well-mixed solution (PQ Corporation, Malvern, PA) and 100 μl of formamide, curing at 100˚C for 4 h, and cutting the frit to a length of %2 mm. Strong cation exchange particles (SCX Luna, 5-μm diameter, 125 Å pores, Phenomenex, Torrance, CA) were packed in-house from particle slurries in methanol to 2.5 cm. Reversed phase particles (2 cm, C18 Aqua, 3-μm diameter, 125 Å pores, Phenomenex) were then successively packed onto the capillary tube using the same method as SCX loading.
MudPIT analysis. An analytical reversed-phase liquid chromatography column was generated by pulling a 100-μm (interior diameter (ID) of 360 μm) OD capillary tube (Polymicro Technologies, Phoenix, AZ) to 5-μm ID tip. Reversed-phase particles (Luna C18, 3-μm diameter, 125 Å pores, Phenomenex) were packed directly into the pulled column at 5.5 mPa until 15 cm long. The column was further packed, washed, and equilibrated at 10 mPa with buffer B (80% acetonitrile, 0.1% formic acid) followed by buffer A (5% acetonitrile and 0.1% formic acid). MudPIT and analytical columns were assembled using a zero-dead volume union (Upchurch Scientific, Oak Harbor, WA). LC-MS/MS analysis was performed with an Agilent high-pressure LC pump (Agilent) and linear quadrupole ion dual cell trap Orbitrap Velos (Thermo) using an in-house built electrospray stage. Electrospray was performed directly from the analytical column by applying the electrospray ionization (ESI) voltage at a tee (150 μm ID, Upchurch Scientific) directly downstream of a 1:1,000 split flow to reduce the flow rate to 300 nl/min through the columns. MudPIT experiments (10-step) were performed in which each step corresponds to 0, 10, 20, 40, 50, 60, 70, 80, 90 , and 100% buffer C (500 mM of ammonium acetate, 0.1% formic acid, and 5% acetonitrile) and was run for 3 min at the beginning of a 110-min gradient.
Data analysis. Protein and peptide identification were performed with Integrated Proteomics Pipeline-IP2 (Integrated Proteomics Applications, San Diego, CA. http://www. integratedproteomics.com/) using ProLuCID and DTASelect2 algorithms. DTASelect parameters were-p 2 -y 1-trypstat-pfp .01 -extra-pI-DB-dm-in. Spectrum raw files were extracted into ms2 files from raw files using open source RawExtract 1.9.9 (Scripps Research Institute, La Jolla, CA; http://fields.scripps.edu/downloads.php), and the tandem mass spectra were searched against a human protein database (UniprotKB). To accurately estimate peptide probabilities and false discovery rates, we used a decoy database containing the reversed sequences of all the proteins appended to the target database. Tandem mass spectra were matched to sequences using the ProLuCID algorithm with a 600-ppm peptide mass tolerance. ProLuCID searches were done on an Intel Xeon cluster processor running under the Linux operating system. The search space included half and fully tryptic peptide candidates that fell within the mass tolerance window with no miscleavage constraint. Carbamidomethylation (+57.02146 Da) of cysteine was considered as a static modification. siRNA screening A549 cells (1,000 cells/well) in a 384-well plate were reverse transfected with 0.5 pmol of siRNA pool (S2 Table) targeting each gene using 0.1 μl of Lipofectamine RNAiMAX (Thermo Fisher Scientific) (final siRNA concentration was 10 nM), followed by incubation at 37˚C and 5% CO 2 . At 72 h post-transfection, cells were infected (MOI = 0.05) with rLCMV/ZsG. siRNA target host-cell proteins were selected based on availability of validated siRNA sequences. The siRNAs we used to examine the effects on LCMV multiplication of knockdown expression of NP-interacting host cell protein candidate hits corresponded to the Genome-wide ON TAR-GET-Plus (OTP) Human siRNA library (18,301 genes, 4 siRNAs/gene; Dharmacon, Lafayette, CO).
A549 cells (3.0 x 10 4 cells/well) were reverse transfected in a 24-well plate with 6 pmol of siRNA pools targeting each gene using 1 μl of Lipofectamine RNAiMAX (final siRNA concentration is 10 nM). At 72 h post-transfection, total cell lysate was prepared in modified lysis A buffer (25 mM Tris-HCl [pH = 8.0], 50 mM NaCl, 1%Triton X-100, 1.25% sodium deoxycholate) and clarified by centrifugation at 21,130 x g at 4˚C for 10 min. The total protein concentration of clarified cell lysate was measured by Pierce BCA Protein Assay Kit (Thermo Fisher Scientific). The same amount of protein from each sample was subjected to SDS-PAGE, and the protein expression of siRNA-targeted genes was analyzed by western blots.
Cells infected with eGFP-or ZsGreen-expressing rLCMV were fixed with 4% PFA in PBS. After cell permeabilization by treatment with DB, cells were stained with 4',6-diamidino-2-phenylindole (DAPI). Green fluorescence (eGFP or ZsGreen) and DAPI signals were measured by a fluorescent plate reader (Synergy H4 Hybrid Multi-Mode Microplate Reader, Bio-Tek, Winooski, VT).
Mock-and virus-infected cells were fixed with 4% PFA. After cell permeabilization and blocking by treatment with DB containing 1% normal goat serum, cells were incubated with primary mouse anti ATP1A1 or PHB antibody followed by secondary anti-mouse IgG antibody conjugated with Alexa Fluore 568 (anti-mouse IgG-AF568). Subsequently, cells were stained with VL-4-AF488. In some samples, primary antibody against ATP1A1 or PHB was omitted to determine background fluorescence. To visualize nuclei, DAPI Fluoromount-G (SouthernBiotech, Birmingham, AL) was used to mount coverslips on a slide glass. Stained cells were observed under a confocal microscope (LSM 710, Zeiss) and data analyzed by ZEN software (Zeiss). Co-localization analysis was performed on a pixel by pixel basis using Zen software (Zeiss). Eight green (NP-positive) cells were marked and every pixel in the marked area was plotted in the scatter diagram based on its intensity level from each channel. Thresholds for green and red channels were determined using mock-infected cells stained with VL-4-AF488 (anti-NP) and anti-mouse IgG antibody conjugated with Alexa Fluor 568, without using anti-ATP1A1 or -PHB antibodies. Each pixel was assigned a value of 1. Co-localization coefficients (CC) (or non-weighted CC) were determined by dividing the sum of both green-and red-positive pixels by the sum of green positive pixels. This calculation was repeated for eight individual cells. To assess the specificity of co-localization, we determined weighted CC by taking into consideration the brightness of each channel signal. Comparison of non-weighted and weighted CC allowed us to determine whether brighter pixels were present in the co-localized regions compared to the non-co-localized regions. p values were determined by a two-tailed paired t test using GraphPad Prism software.
A549 or Vero E6 cells seeded (2.0 x 10 4 cells/well) in a 96-well plate and cultured overnight were treated with 3-fold serial compound dilutions at 37˚C and 5% CO 2 for 2 h, followed by infection with rLCMV/eGFP (MOI = 0.01). Compounds were present to study endpoint. At 48 h pi, cells were fixed with 4% PFA in PBS, and eGFP expression was examined by a fluorescent plate reader (Synergy H4 Hybrid Multi-Mode Microplate Reader, BioTek). Mean values obtained with DMSO-treated and rLCMV/eGFP-infected cells were set to 100%. The IC 50 concentrations were determined using GraphPad Prism.
A549 or Vero E6 cells seeded in a 96-well plate (2.0 x 10 4 cells/well) and cultured overnight were treated with 3-fold serial compound dilutions and cultured at 37˚C and 5% CO 2 for 48 h. Then, CellTiter 96 AQ ueous one solution reagent (Promega, Madison, WI) was added. Thereafter, the assay was performed according to the manufacturer's recommendations, and the absorbance (490 nm) was obtained using an enzyme-linked immunosorbent assay (ELISA) reader (SPECTRA max plus 384; Molecular Devices, Sunnyvale, CA). Mean values obtained with DMSO-treated cells were set to 100%. The CC 50 concentrations were determined using GraphPad Prism.
A plasmid expressing C-terminus Strep-tagged Z protein (pC-LCMV-Z-Strep) was generated using similar procedure to generate a plasmid expressing C-terminus FLAG-tagged LASV Z protein (pC-LASV-Z-FLAG), and the budding assay was performed as previously described [88] . Cells (HEK 293T) in a 12-well plate were transfected with 0.5 μg of empty pCAGGS vector or pC-LCMV-Z-Strep or pC-LASV-Z-FLAG using Lipofectamine 2000. At 5 h post-transfection, media were replaced with fresh media and incubated at 37˚C and 5% CO 2 for 19 h. Then the cells were three times washed with fresh medium. After the removal of the last wash medium, cells were cultured in fresh medium containing ouabain (30 or 40 nM) or rocaglamide (50 or 100 nM) or equivalent concentration of DMSO, and 24 h later, virion-like particle (VLP)-containing TCS and cells were collected. Total cell lysate was prepared by lysing the cells with lysis buffer (1% NP-40, 50 mM of Tris-HCl [pH 8.0], 62.5 mM NaCl, 0.4% sodium deoxycholate). After clarification of TCS from cell debris by centrifugation at 400 x g and 4˚C for 10 min, VLPs were collected by ultracentrifugation at 100,000 x g and 4˚C for 30 min through a 20% sucrose cushion. VLPs were resuspended in PBS, and Z expression in total cell lysate and TCS (containing VLPs) were analyzed by western blots.
A549 cells infected with rLCMV/eGFP were harvested using Accutase cell detachment solution (Innovative Cell Technologies, San Diego, CA) and fixed with 4% PFA in PBS. eGFP expression was examined by flow cytometry using a BD LSR II (Becton Dickson), and data were analyzed with FlowJo (Tree Star, Inc., Ashland, OR).
293T cells seeded (4.0 x 10 5 cells/well) in a 12-well plate and cultured overnight were infected with scrLCMV/ZsG-P2A-NP for 2 h and subsequently transfected with 0.5 μg of pC-GPC. At 24 h pi, cells were three times washed with fresh media to eliminate infectious virus particle produced in the absence of compound treatment, and cultured for another 24 h in fresh media in the presence of 40 nM of ouabain or vehicle control (DMSO). At 48 h pi, TCS was collected and used to infect fresh monolayers of BHK-21 cells seeded (4.0 x 10 5 cells/well) in a 12-well plate 1 day before the infection, and 293T cell lysate was prepared. 24 h later, BHK-21 cell lysate was prepared. Total cell lysate was prepared in cell lysis buffer (150 mM of NaCl, 50 mM of Tris-HCl [pH = 7.5], 0.5% [NP-40], 1 mM of EDTA] and clarified by centrifugation at 21,130 x g at 4˚C for 10 min. ZsGreen signal intensity in clarified cell lysate was measured by a fluorescent plate reader (Synergy H4 Hybrid Multi-Mode Microplate Reader, BioTek).
A549 cells seeded (2 x 10 5 cells/well) in a 96-well plate and cultured overnight were treated with combinations of different concentrations of ouabain and rocaglamide for 2 h and then infected (MOI = 0.01) with rLCMV/eGFP. Compounds were present in the culture medium throughout the experiment. At 48 h pi, cells were fixed, permeabilized by treatment with DB, and stained with DAPI. eGFP and DAPI signals were measured by a fluorescent plate reader (Synergy H4 Hybrid Multi-Mode Microplate Reader, BioTek). eGFP readouts were normalized by DAPI readouts, and normalized data were used to analyze synergistic effect of the two compounds by the MacSynergy II program [89] .
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2,504 | Respiratory Viral Infections in Exacerbation of Chronic Airway Inflammatory Diseases: Novel Mechanisms and Insights From the Upper Airway Epithelium
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7052386/
SHA: 45a566c71056ba4faab425b4f7e9edee6320e4a4
Authors: Tan, Kai Sen; Lim, Rachel Liyu; Liu, Jing; Ong, Hsiao Hui; Tan, Vivian Jiayi; Lim, Hui Fang; Chung, Kian Fan; Adcock, Ian M.; Chow, Vincent T.; Wang, De Yun
Date: 2020-02-25
DOI: 10.3389/fcell.2020.00099
License: cc-by
Abstract: Respiratory virus infection is one of the major sources of exacerbation of chronic airway inflammatory diseases. These exacerbations are associated with high morbidity and even mortality worldwide. The current understanding on viral-induced exacerbations is that viral infection increases airway inflammation which aggravates disease symptoms. Recent advances in in vitro air-liquid interface 3D cultures, organoid cultures and the use of novel human and animal challenge models have evoked new understandings as to the mechanisms of viral exacerbations. In this review, we will focus on recent novel findings that elucidate how respiratory viral infections alter the epithelial barrier in the airways, the upper airway microbial environment, epigenetic modifications including miRNA modulation, and other changes in immune responses throughout the upper and lower airways. First, we reviewed the prevalence of different respiratory viral infections in causing exacerbations in chronic airway inflammatory diseases. Subsequently we also summarized how recent models have expanded our appreciation of the mechanisms of viral-induced exacerbations. Further we highlighted the importance of the virome within the airway microbiome environment and its impact on subsequent bacterial infection. This review consolidates the understanding of viral induced exacerbation in chronic airway inflammatory diseases and indicates pathways that may be targeted for more effective management of chronic inflammatory diseases.
Text: The prevalence of chronic airway inflammatory disease is increasing worldwide especially in developed nations (GBD 2015 Chronic Respiratory Disease Collaborators, 2017 Guan et al., 2018) . This disease is characterized by airway inflammation leading to complications such as coughing, wheezing and shortness of breath. The disease can manifest in both the upper airway (such as chronic rhinosinusitis, CRS) and lower airway (such as asthma and chronic obstructive pulmonary disease, COPD) which greatly affect the patients' quality of life (Calus et al., 2012; Bao et al., 2015) . Treatment and management vary greatly in efficacy due to the complexity and heterogeneity of the disease. This is further complicated by the effect of episodic exacerbations of the disease, defined as worsening of disease symptoms including wheeze, cough, breathlessness and chest tightness (Xepapadaki and Papadopoulos, 2010) . Such exacerbations are due to the effect of enhanced acute airway inflammation impacting upon and worsening the symptoms of the existing disease (Hashimoto et al., 2008; Viniol and Vogelmeier, 2018) . These acute exacerbations are the main cause of morbidity and sometimes mortality in patients, as well as resulting in major economic burdens worldwide. However, due to the complex interactions between the host and the exacerbation agents, the mechanisms of exacerbation may vary considerably in different individuals under various triggers. Acute exacerbations are usually due to the presence of environmental factors such as allergens, pollutants, smoke, cold or dry air and pathogenic microbes in the airway (Gautier and Charpin, 2017; Viniol and Vogelmeier, 2018) . These agents elicit an immune response leading to infiltration of activated immune cells that further release inflammatory mediators that cause acute symptoms such as increased mucus production, cough, wheeze and shortness of breath. Among these agents, viral infection is one of the major drivers of asthma exacerbations accounting for up to 80-90% and 45-80% of exacerbations in children and adults respectively (Grissell et al., 2005; Xepapadaki and Papadopoulos, 2010; Jartti and Gern, 2017; Adeli et al., 2019) . Viral involvement in COPD exacerbation is also equally high, having been detected in 30-80% of acute COPD exacerbations (Kherad et al., 2010; Jafarinejad et al., 2017; Stolz et al., 2019) . Whilst the prevalence of viral exacerbations in CRS is still unclear, its prevalence is likely to be high due to the similar inflammatory nature of these diseases (Rowan et al., 2015; Tan et al., 2017) . One of the reasons for the involvement of respiratory viruses' in exacerbations is their ease of transmission and infection (Kutter et al., 2018) . In addition, the high diversity of the respiratory viruses may also contribute to exacerbations of different nature and severity (Busse et al., 2010; Costa et al., 2014; Jartti and Gern, 2017) . Hence, it is important to identify the exact mechanisms underpinning viral exacerbations in susceptible subjects in order to properly manage exacerbations via supplementary treatments that may alleviate the exacerbation symptoms or prevent severe exacerbations.
While the lower airway is the site of dysregulated inflammation in most chronic airway inflammatory diseases, the upper airway remains the first point of contact with sources of exacerbation. Therefore, their interaction with the exacerbation agents may directly contribute to the subsequent responses in the lower airway, in line with the "United Airway" hypothesis. To elucidate the host airway interaction with viruses leading to exacerbations, we thus focus our review on recent findings of viral interaction with the upper airway. We compiled how viral induced changes to the upper airway may contribute to chronic airway inflammatory disease exacerbations, to provide a unified elucidation of the potential exacerbation mechanisms initiated from predominantly upper airway infections.
Despite being a major cause of exacerbation, reports linking respiratory viruses to acute exacerbations only start to emerge in the late 1950s (Pattemore et al., 1992) ; with bacterial infections previously considered as the likely culprit for acute exacerbation (Stevens, 1953; Message and Johnston, 2002) . However, with the advent of PCR technology, more viruses were recovered during acute exacerbations events and reports implicating their role emerged in the late 1980s (Message and Johnston, 2002) . Rhinovirus (RV) and respiratory syncytial virus (RSV) are the predominant viruses linked to the development and exacerbation of chronic airway inflammatory diseases (Jartti and Gern, 2017) . Other viruses such as parainfluenza virus (PIV), influenza virus (IFV) and adenovirus (AdV) have also been implicated in acute exacerbations but to a much lesser extent (Johnston et al., 2005; Oliver et al., 2014; Ko et al., 2019) . More recently, other viruses including bocavirus (BoV), human metapneumovirus (HMPV), certain coronavirus (CoV) strains, a specific enterovirus (EV) strain EV-D68, human cytomegalovirus (hCMV) and herpes simplex virus (HSV) have been reported as contributing to acute exacerbations . The common feature these viruses share is that they can infect both the upper and/or lower airway, further increasing the inflammatory conditions in the diseased airway (Mallia and Johnston, 2006; Britto et al., 2017) .
Respiratory viruses primarily infect and replicate within airway epithelial cells . During the replication process, the cells release antiviral factors and cytokines that alter local airway inflammation and airway niche (Busse et al., 2010) . In a healthy airway, the inflammation normally leads to type 1 inflammatory responses consisting of activation of an antiviral state and infiltration of antiviral effector cells. This eventually results in the resolution of the inflammatory response and clearance of the viral infection (Vareille et al., 2011; Braciale et al., 2012) . However, in a chronically inflamed airway, the responses against the virus may be impaired or aberrant, causing sustained inflammation and erroneous infiltration, resulting in the exacerbation of their symptoms (Mallia and Johnston, 2006; Dougherty and Fahy, 2009; Busse et al., 2010; Britto et al., 2017; Linden et al., 2019) . This is usually further compounded by the increased susceptibility of chronic airway inflammatory disease patients toward viral respiratory infections, thereby increasing the frequency of exacerbation as a whole (Dougherty and Fahy, 2009; Busse et al., 2010; Linden et al., 2019) . Furthermore, due to the different replication cycles and response against the myriad of respiratory viruses, each respiratory virus may also contribute to exacerbations via different mechanisms that may alter their severity. Hence, this review will focus on compiling and collating the current known mechanisms of viral-induced exacerbation of chronic airway inflammatory diseases; as well as linking the different viral infection pathogenesis to elucidate other potential ways the infection can exacerbate the disease. The review will serve to provide further understanding of viral induced exacerbation to identify potential pathways and pathogenesis mechanisms that may be targeted as supplementary care for management and prevention of exacerbation. Such an approach may be clinically significant due to the current scarcity of antiviral drugs for the management of viral-induced exacerbations. This will improve the quality of life of patients with chronic airway inflammatory diseases.
Once the link between viral infection and acute exacerbations of chronic airway inflammatory disease was established, there have been many reports on the mechanisms underlying the exacerbation induced by respiratory viral infection. Upon infecting the host, viruses evoke an inflammatory response as a means of counteracting the infection. Generally, infected airway epithelial cells release type I (IFNα/β) and type III (IFNλ) interferons, cytokines and chemokines such as IL-6, IL-8, IL-12, RANTES, macrophage inflammatory protein 1α (MIP-1α) and monocyte chemotactic protein 1 (MCP-1) (Wark and Gibson, 2006; Matsukura et al., 2013) . These, in turn, enable infiltration of innate immune cells and of professional antigen presenting cells (APCs) that will then in turn release specific mediators to facilitate viral targeting and clearance, including type II interferon (IFNγ), IL-2, IL-4, IL-5, IL-9, and IL-12 (Wark and Gibson, 2006; Singh et al., 2010; Braciale et al., 2012) . These factors heighten local inflammation and the infiltration of granulocytes, T-cells and B-cells (Wark and Gibson, 2006; Braciale et al., 2012) . The increased inflammation, in turn, worsens the symptoms of airway diseases.
Additionally, in patients with asthma and patients with CRS with nasal polyp (CRSwNP), viral infections such as RV and RSV promote a Type 2-biased immune response (Becker, 2006; Jackson et al., 2014; Jurak et al., 2018) . This amplifies the basal type 2 inflammation resulting in a greater release of IL-4, IL-5, IL-13, RANTES and eotaxin and a further increase in eosinophilia, a key pathological driver of asthma and CRSwNP (Wark and Gibson, 2006; Singh et al., 2010; Chung et al., 2015; Dunican and Fahy, 2015) . Increased eosinophilia, in turn, worsens the classical symptoms of disease and may further lead to life-threatening conditions due to breathing difficulties. On the other hand, patients with COPD and patients with CRS without nasal polyp (CRSsNP) are more neutrophilic in nature due to the expression of neutrophil chemoattractants such as CXCL9, CXCL10, and CXCL11 (Cukic et al., 2012; Brightling and Greening, 2019) . The pathology of these airway diseases is characterized by airway remodeling due to the presence of remodeling factors such as matrix metalloproteinases (MMPs) released from infiltrating neutrophils (Linden et al., 2019) . Viral infections in such conditions will then cause increase neutrophilic activation; worsening the symptoms and airway remodeling in the airway thereby exacerbating COPD, CRSsNP and even CRSwNP in certain cases (Wang et al., 2009; Tacon et al., 2010; Linden et al., 2019) .
An epithelial-centric alarmin pathway around IL-25, IL-33 and thymic stromal lymphopoietin (TSLP), and their interaction with group 2 innate lymphoid cells (ILC2) has also recently been identified (Nagarkar et al., 2012; Hong et al., 2018; Allinne et al., 2019) . IL-25, IL-33 and TSLP are type 2 inflammatory cytokines expressed by the epithelial cells upon injury to the epithelial barrier (Gabryelska et al., 2019; Roan et al., 2019) . ILC2s are a group of lymphoid cells lacking both B and T cell receptors but play a crucial role in secreting type 2 cytokines to perpetuate type 2 inflammation when activated (Scanlon and McKenzie, 2012; Li and Hendriks, 2013) . In the event of viral infection, cell death and injury to the epithelial barrier will also induce the expression of IL-25, IL-33 and TSLP, with heighten expression in an inflamed airway (Allakhverdi et al., 2007; Goldsmith et al., 2012; Byers et al., 2013; Shaw et al., 2013; Beale et al., 2014; Jackson et al., 2014; Uller and Persson, 2018; Ravanetti et al., 2019) . These 3 cytokines then work in concert to activate ILC2s to further secrete type 2 cytokines IL-4, IL-5, and IL-13 which further aggravate the type 2 inflammation in the airway causing acute exacerbation (Camelo et al., 2017) . In the case of COPD, increased ILC2 activation, which retain the capability of differentiating to ILC1, may also further augment the neutrophilic response and further aggravate the exacerbation (Silver et al., 2016) . Interestingly, these factors are not released to any great extent and do not activate an ILC2 response during viral infection in healthy individuals (Yan et al., 2016; Tan et al., 2018a) ; despite augmenting a type 2 exacerbation in chronically inflamed airways (Jurak et al., 2018) . These classical mechanisms of viral induced acute exacerbations are summarized in Figure 1 .
As integration of the virology, microbiology and immunology of viral infection becomes more interlinked, additional factors and FIGURE 1 | Current understanding of viral induced exacerbation of chronic airway inflammatory diseases. Upon virus infection in the airway, antiviral state will be activated to clear the invading pathogen from the airway. Immune response and injury factors released from the infected epithelium normally would induce a rapid type 1 immunity that facilitates viral clearance. However, in the inflamed airway, the cytokines and chemokines released instead augmented the inflammation present in the chronically inflamed airway, strengthening the neutrophilic infiltration in COPD airway, and eosinophilic infiltration in the asthmatic airway. The effect is also further compounded by the participation of Th1 and ILC1 cells in the COPD airway; and Th2 and ILC2 cells in the asthmatic airway.
Frontiers in Cell and Developmental Biology | www.frontiersin.org mechanisms have been implicated in acute exacerbations during and after viral infection (Murray et al., 2006) . Murray et al. (2006) has underlined the synergistic effect of viral infection with other sensitizing agents in causing more severe acute exacerbations in the airway. This is especially true when not all exacerbation events occurred during the viral infection but may also occur well after viral clearance (Kim et al., 2008; Stolz et al., 2019) in particular the late onset of a bacterial infection (Singanayagam et al., 2018 (Singanayagam et al., , 2019a . In addition, viruses do not need to directly infect the lower airway to cause an acute exacerbation, as the nasal epithelium remains the primary site of most infections. Moreover, not all viral infections of the airway will lead to acute exacerbations, suggesting a more complex interplay between the virus and upper airway epithelium which synergize with the local airway environment in line with the "united airway" hypothesis (Kurai et al., 2013) . On the other hand, viral infections or their components persist in patients with chronic airway inflammatory disease (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Hence, their presence may further alter the local environment and contribute to current and future exacerbations. Future studies should be performed using metagenomics in addition to PCR analysis to determine the contribution of the microbiome and mycobiome to viral infections. In this review, we highlight recent data regarding viral interactions with the airway epithelium that could also contribute to, or further aggravate, acute exacerbations of chronic airway inflammatory diseases.
Patients with chronic airway inflammatory diseases have impaired or reduced ability of viral clearance (Hammond et al., 2015; McKendry et al., 2016; Akbarshahi et al., 2018; Gill et al., 2018; Wang et al., 2018; Singanayagam et al., 2019b) . Their impairment stems from a type 2-skewed inflammatory response which deprives the airway of important type 1 responsive CD8 cells that are responsible for the complete clearance of virusinfected cells (Becker, 2006; McKendry et al., 2016) . This is especially evident in weak type 1 inflammation-inducing viruses such as RV and RSV (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Additionally, there are also evidence of reduced type I (IFNβ) and III (IFNλ) interferon production due to type 2-skewed inflammation, which contributes to imperfect clearance of the virus resulting in persistence of viral components, or the live virus in the airway epithelium (Contoli et al., 2006; Hwang et al., 2019; Wark, 2019) . Due to the viral components remaining in the airway, antiviral genes such as type I interferons, inflammasome activating factors and cytokines remained activated resulting in prolong airway inflammation (Wood et al., 2011; Essaidi-Laziosi et al., 2018) . These factors enhance granulocyte infiltration thus prolonging the exacerbation symptoms. Such persistent inflammation may also be found within DNA viruses such as AdV, hCMV and HSV, whose infections generally persist longer (Imperiale and Jiang, 2015) , further contributing to chronic activation of inflammation when they infect the airway (Yang et al., 2008; Morimoto et al., 2009; Imperiale and Jiang, 2015; Lan et al., 2016; Tan et al., 2016; Kowalski et al., 2017) . With that note, human papilloma virus (HPV), a DNA virus highly associated with head and neck cancers and respiratory papillomatosis, is also linked with the chronic inflammation that precedes the malignancies (de Visser et al., 2005; Gillison et al., 2012; Bonomi et al., 2014; Fernandes et al., 2015) . Therefore, the role of HPV infection in causing chronic inflammation in the airway and their association to exacerbations of chronic airway inflammatory diseases, which is scarcely explored, should be investigated in the future. Furthermore, viral persistence which lead to continuous expression of antiviral genes may also lead to the development of steroid resistance, which is seen with RV, RSV, and PIV infection (Chi et al., 2011; Ford et al., 2013; Papi et al., 2013) . The use of steroid to suppress the inflammation may also cause the virus to linger longer in the airway due to the lack of antiviral clearance (Kim et al., 2008; Hammond et al., 2015; Hewitt et al., 2016; McKendry et al., 2016; Singanayagam et al., 2019b) . The concomitant development of steroid resistance together with recurring or prolong viral infection thus added considerable burden to the management of acute exacerbation, which should be the future focus of research to resolve the dual complications arising from viral infection.
On the other end of the spectrum, viruses that induce strong type 1 inflammation and cell death such as IFV (Yan et al., 2016; Guibas et al., 2018) and certain CoV (including the recently emerged COVID-19 virus) (Tao et al., 2013; Yue et al., 2018; Zhu et al., 2020) , may not cause prolonged inflammation due to strong induction of antiviral clearance. These infections, however, cause massive damage and cell death to the epithelial barrier, so much so that areas of the epithelium may be completely absent post infection (Yan et al., 2016; Tan et al., 2019) . Factors such as RANTES and CXCL10, which recruit immune cells to induce apoptosis, are strongly induced from IFV infected epithelium (Ampomah et al., 2018; Tan et al., 2019) . Additionally, necroptotic factors such as RIP3 further compounds the cell deaths in IFV infected epithelium . The massive cell death induced may result in worsening of the acute exacerbation due to the release of their cellular content into the airway, further evoking an inflammatory response in the airway (Guibas et al., 2018) . Moreover, the destruction of the epithelial barrier may cause further contact with other pathogens and allergens in the airway which may then prolong exacerbations or results in new exacerbations. Epithelial destruction may also promote further epithelial remodeling during its regeneration as viral infection induces the expression of remodeling genes such as MMPs and growth factors . Infections that cause massive destruction of the epithelium, such as IFV, usually result in severe acute exacerbations with non-classical symptoms of chronic airway inflammatory diseases. Fortunately, annual vaccines are available to prevent IFV infections (Vasileiou et al., 2017; Zheng et al., 2018) ; and it is recommended that patients with chronic airway inflammatory disease receive their annual influenza vaccination as the best means to prevent severe IFV induced exacerbation.
Another mechanism that viral infections may use to drive acute exacerbations is the induction of vasodilation or tight junction opening factors which may increase the rate of infiltration. Infection with a multitude of respiratory viruses causes disruption of tight junctions with the resulting increased rate of viral infiltration. This also increases the chances of allergens coming into contact with airway immune cells. For example, IFV infection was found to induce oncostatin M (OSM) which causes tight junction opening (Pothoven et al., 2015; Tian et al., 2018) . Similarly, RV and RSV infections usually cause tight junction opening which may also increase the infiltration rate of eosinophils and thus worsening of the classical symptoms of chronic airway inflammatory diseases (Sajjan et al., 2008; Kast et al., 2017; Kim et al., 2018) . In addition, the expression of vasodilating factors and fluid homeostatic factors such as angiopoietin-like 4 (ANGPTL4) and bactericidal/permeabilityincreasing fold-containing family member A1 (BPIFA1) are also associated with viral infections and pneumonia development, which may worsen inflammation in the lower airway Akram et al., 2018) . These factors may serve as targets to prevent viral-induced exacerbations during the management of acute exacerbation of chronic airway inflammatory diseases.
Another recent area of interest is the relationship between asthma and COPD exacerbations and their association with the airway microbiome. The development of chronic airway inflammatory diseases is usually linked to specific bacterial species in the microbiome which may thrive in the inflamed airway environment (Diver et al., 2019) . In the event of a viral infection such as RV infection, the effect induced by the virus may destabilize the equilibrium of the microbiome present (Molyneaux et al., 2013; Kloepfer et al., 2014; Kloepfer et al., 2017; Jubinville et al., 2018; van Rijn et al., 2019) . In addition, viral infection may disrupt biofilm colonies in the upper airway (e.g., Streptococcus pneumoniae) microbiome to be release into the lower airway and worsening the inflammation (Marks et al., 2013; Chao et al., 2014) . Moreover, a viral infection may also alter the nutrient profile in the airway through release of previously inaccessible nutrients that will alter bacterial growth (Siegel et al., 2014; Mallia et al., 2018) . Furthermore, the destabilization is further compounded by impaired bacterial immune response, either from direct viral influences, or use of corticosteroids to suppress the exacerbation symptoms (Singanayagam et al., 2018 (Singanayagam et al., , 2019a Wang et al., 2018; Finney et al., 2019) . All these may gradually lead to more far reaching effect when normal flora is replaced with opportunistic pathogens, altering the inflammatory profiles (Teo et al., 2018) . These changes may in turn result in more severe and frequent acute exacerbations due to the interplay between virus and pathogenic bacteria in exacerbating chronic airway inflammatory diseases (Wark et al., 2013; Singanayagam et al., 2018) . To counteract these effects, microbiome-based therapies are in their infancy but have shown efficacy in the treatments of irritable bowel syndrome by restoring the intestinal microbiome (Bakken et al., 2011) . Further research can be done similarly for the airway microbiome to be able to restore the microbiome following disruption by a viral infection.
Viral infections can cause the disruption of mucociliary function, an important component of the epithelial barrier. Ciliary proteins FIGURE 2 | Changes in the upper airway epithelium contributing to viral exacerbation in chronic airway inflammatory diseases. The upper airway epithelium is the primary contact/infection site of most respiratory viruses. Therefore, its infection by respiratory viruses may have far reaching consequences in augmenting and synergizing current and future acute exacerbations. The destruction of epithelial barrier, mucociliary function and cell death of the epithelial cells serves to increase contact between environmental triggers with the lower airway and resident immune cells. The opening of tight junction increasing the leakiness further augments the inflammation and exacerbations. In addition, viral infections are usually accompanied with oxidative stress which will further increase the local inflammation in the airway. The dysregulation of inflammation can be further compounded by modulation of miRNAs and epigenetic modification such as DNA methylation and histone modifications that promote dysregulation in inflammation. Finally, the change in the local airway environment and inflammation promotes growth of pathogenic bacteria that may replace the airway microbiome. Furthermore, the inflammatory environment may also disperse upper airway commensals into the lower airway, further causing inflammation and alteration of the lower airway environment, resulting in prolong exacerbation episodes following viral infection.
Viral specific trait contributing to exacerbation mechanism (with literature evidence) Oxidative stress ROS production (RV, RSV, IFV, HSV)
As RV, RSV, and IFV were the most frequently studied viruses in chronic airway inflammatory diseases, most of the viruses listed are predominantly these viruses. However, the mechanisms stated here may also be applicable to other viruses but may not be listed as they were not implicated in the context of chronic airway inflammatory diseases exacerbation (see text for abbreviations).
that aid in the proper function of the motile cilia in the airways are aberrantly expressed in ciliated airway epithelial cells which are the major target for RV infection (Griggs et al., 2017) . Such form of secondary cilia dyskinesia appears to be present with chronic inflammations in the airway, but the exact mechanisms are still unknown (Peng et al., , 2019 Qiu et al., 2018) . Nevertheless, it was found that in viral infection such as IFV, there can be a change in the metabolism of the cells as well as alteration in the ciliary gene expression, mostly in the form of down-regulation of the genes such as dynein axonemal heavy chain 5 (DNAH5) and multiciliate differentiation And DNA synthesis associated cell cycle protein (MCIDAS) (Tan et al., 2018b . The recently emerged Wuhan CoV was also found to reduce ciliary beating in infected airway epithelial cell model (Zhu et al., 2020) . Furthermore, viral infections such as RSV was shown to directly destroy the cilia of the ciliated cells and almost all respiratory viruses infect the ciliated cells (Jumat et al., 2015; Yan et al., 2016; Tan et al., 2018a) . In addition, mucus overproduction may also disrupt the equilibrium of the mucociliary function following viral infection, resulting in symptoms of acute exacerbation (Zhu et al., 2009) . Hence, the disruption of the ciliary movement during viral infection may cause more foreign material and allergen to enter the airway, aggravating the symptoms of acute exacerbation and making it more difficult to manage. The mechanism of the occurrence of secondary cilia dyskinesia can also therefore be explored as a means to limit the effects of viral induced acute exacerbation.
MicroRNAs (miRNAs) are short non-coding RNAs involved in post-transcriptional modulation of biological processes, and implicated in a number of diseases (Tan et al., 2014) . miRNAs are found to be induced by viral infections and may play a role in the modulation of antiviral responses and inflammation (Gutierrez et al., 2016; Deng et al., 2017; Feng et al., 2018) . In the case of chronic airway inflammatory diseases, circulating miRNA changes were found to be linked to exacerbation of the diseases (Wardzynska et al., 2020) . Therefore, it is likely that such miRNA changes originated from the infected epithelium and responding immune cells, which may serve to further dysregulate airway inflammation leading to exacerbations. Both IFV and RSV infections has been shown to increase miR-21 and augmented inflammation in experimental murine asthma models, which is reversed with a combination treatment of anti-miR-21 and corticosteroids (Kim et al., 2017) . IFV infection is also shown to increase miR-125a and b, and miR-132 in COPD epithelium which inhibits A20 and MAVS; and p300 and IRF3, respectively, resulting in increased susceptibility to viral infections (Hsu et al., 2016 (Hsu et al., , 2017 . Conversely, miR-22 was shown to be suppressed in asthmatic epithelium in IFV infection which lead to aberrant epithelial response, contributing to exacerbations (Moheimani et al., 2018) . Other than these direct evidence of miRNA changes in contributing to exacerbations, an increased number of miRNAs and other non-coding RNAs responsible for immune modulation are found to be altered following viral infections (Globinska et al., 2014; Feng et al., 2018; Hasegawa et al., 2018) . Hence non-coding RNAs also presents as targets to modulate viral induced airway changes as a means of managing exacerbation of chronic airway inflammatory diseases. Other than miRNA modulation, other epigenetic modification such as DNA methylation may also play a role in exacerbation of chronic airway inflammatory diseases. Recent epigenetic studies have indicated the association of epigenetic modification and chronic airway inflammatory diseases, and that the nasal methylome was shown to be a sensitive marker for airway inflammatory changes (Cardenas et al., 2019; Gomez, 2019) . At the same time, it was also shown that viral infections such as RV and RSV alters DNA methylation and histone modifications in the airway epithelium which may alter inflammatory responses, driving chronic airway inflammatory diseases and exacerbations (McErlean et al., 2014; Pech et al., 2018; Caixia et al., 2019) . In addition, Spalluto et al. (2017) also showed that antiviral factors such as IFNγ epigenetically modifies the viral resistance of epithelial cells. Hence, this may indicate that infections such as RV and RSV that weakly induce antiviral responses may result in an altered inflammatory state contributing to further viral persistence and exacerbation of chronic airway inflammatory diseases (Spalluto et al., 2017) .
Finally, viral infection can result in enhanced production of reactive oxygen species (ROS), oxidative stress and mitochondrial dysfunction in the airway epithelium (Kim et al., 2018; Mishra et al., 2018; Wang et al., 2018) . The airway epithelium of patients with chronic airway inflammatory diseases are usually under a state of constant oxidative stress which sustains the inflammation in the airway (Barnes, 2017; van der Vliet et al., 2018) . Viral infections of the respiratory epithelium by viruses such as IFV, RV, RSV and HSV may trigger the further production of ROS as an antiviral mechanism Aizawa et al., 2018; Wang et al., 2018) . Moreover, infiltrating cells in response to the infection such as neutrophils will also trigger respiratory burst as a means of increasing the ROS in the infected region. The increased ROS and oxidative stress in the local environment may serve as a trigger to promote inflammation thereby aggravating the inflammation in the airway (Tiwari et al., 2002) . A summary of potential exacerbation mechanisms and the associated viruses is shown in Figure 2 and Table 1 .
While the mechanisms underlying the development and acute exacerbation of chronic airway inflammatory disease is extensively studied for ways to manage and control the disease, a viral infection does more than just causing an acute exacerbation in these patients. A viral-induced acute exacerbation not only induced and worsens the symptoms of the disease, but also may alter the management of the disease or confer resistance toward treatments that worked before. Hence, appreciation of the mechanisms of viral-induced acute exacerbations is of clinical significance to devise strategies to correct viral induce changes that may worsen chronic airway inflammatory disease symptoms. Further studies in natural exacerbations and in viral-challenge models using RNA-sequencing (RNA-seq) or single cell RNA-seq on a range of time-points may provide important information regarding viral pathogenesis and changes induced within the airway of chronic airway inflammatory disease patients to identify novel targets and pathway for improved management of the disease. Subsequent analysis of functions may use epithelial cell models such as the air-liquid interface, in vitro airway epithelial model that has been adapted to studying viral infection and the changes it induced in the airway (Yan et al., 2016; Boda et al., 2018; Tan et al., 2018a) . Animal-based diseased models have also been developed to identify systemic mechanisms of acute exacerbation (Shin, 2016; Gubernatorova et al., 2019; Tanner and Single, 2019) . Furthermore, the humanized mouse model that possess human immune cells may also serves to unravel the immune profile of a viral infection in healthy and diseased condition (Ito et al., 2019; Li and Di Santo, 2019) . For milder viruses, controlled in vivo human infections can be performed for the best mode of verification of the associations of the virus with the proposed mechanism of viral induced acute exacerbations . With the advent of suitable diseased models, the verification of the mechanisms will then provide the necessary continuation of improving the management of viral induced acute exacerbations.
In conclusion, viral-induced acute exacerbation of chronic airway inflammatory disease is a significant health and economic burden that needs to be addressed urgently. In view of the scarcity of antiviral-based preventative measures available for only a few viruses and vaccines that are only available for IFV infections, more alternative measures should be explored to improve the management of the disease. Alternative measures targeting novel viral-induced acute exacerbation mechanisms, especially in the upper airway, can serve as supplementary treatments of the currently available management strategies to augment their efficacy. New models including primary human bronchial or nasal epithelial cell cultures, organoids or precision cut lung slices from patients with airways disease rather than healthy subjects can be utilized to define exacerbation mechanisms. These mechanisms can then be validated in small clinical trials in patients with asthma or COPD. Having multiple means of treatment may also reduce the problems that arise from resistance development toward a specific treatment. | Who has impaired or reduced ability of viral clearance ? | false | 3,970 | {
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1,719 | Virus-Vectored Influenza Virus Vaccines
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147686/
SHA: f6d2afb2ec44d8656972ea79f8a833143bbeb42b
Authors: Tripp, Ralph A.; Tompkins, S. Mark
Date: 2014-08-07
DOI: 10.3390/v6083055
License: cc-by
Abstract: Despite the availability of an inactivated vaccine that has been licensed for >50 years, the influenza virus continues to cause morbidity and mortality worldwide. Constant evolution of circulating influenza virus strains and the emergence of new strains diminishes the effectiveness of annual vaccines that rely on a match with circulating influenza strains. Thus, there is a continued need for new, efficacious vaccines conferring cross-clade protection to avoid the need for biannual reformulation of seasonal influenza vaccines. Recombinant virus-vectored vaccines are an appealing alternative to classical inactivated vaccines because virus vectors enable native expression of influenza antigens, even from virulent influenza viruses, while expressed in the context of the vector that can improve immunogenicity. In addition, a vectored vaccine often enables delivery of the vaccine to sites of inductive immunity such as the respiratory tract enabling protection from influenza virus infection. Moreover, the ability to readily manipulate virus vectors to produce novel influenza vaccines may provide the quickest path toward a universal vaccine protecting against all influenza viruses. This review will discuss experimental virus-vectored vaccines for use in humans, comparing them to licensed vaccines and the hurdles faced for licensure of these next-generation influenza virus vaccines.
Text: Seasonal influenza is a worldwide health problem causing high mobility and substantial mortality [1] [2] [3] [4] . Moreover, influenza infection often worsens preexisting medical conditions [5] [6] [7] . Vaccines against circulating influenza strains are available and updated annually, but many issues are still present, including low efficacy in the populations at greatest risk of complications from influenza virus infection, i.e., the young and elderly [8, 9] . Despite increasing vaccination rates, influenza-related hospitalizations are increasing [8, 10] , and substantial drug resistance has developed to two of the four currently approved anti-viral drugs [11, 12] . While adjuvants have the potential to improve efficacy and availability of current inactivated vaccines, live-attenuated and virus-vectored vaccines are still considered one of the best options for the induction of broad and efficacious immunity to the influenza virus [13] .
The general types of influenza vaccines available in the United States are trivalent inactivated influenza vaccine (TIV), quadrivalent influenza vaccine (QIV), and live attenuated influenza vaccine (LAIV; in trivalent and quadrivalent forms). There are three types of inactivated vaccines that include whole virus inactivated, split virus inactivated, and subunit vaccines. In split virus vaccines, the virus is disrupted by a detergent. In subunit vaccines, HA and NA have been further purified by removal of other viral components. TIV is administered intramuscularly and contains three or four inactivated viruses, i.e., two type A strains (H1 and H3) and one or two type B strains. TIV efficacy is measured by induction of humoral responses to the hemagglutinin (HA) protein, the major surface and attachment glycoprotein on influenza. Serum antibody responses to HA are measured by the hemagglutination-inhibition (HI) assay, and the strain-specific HI titer is considered the gold-standard correlate of immunity to influenza where a four-fold increase in titer post-vaccination, or a HI titer of ≥1:40 is considered protective [4, 14] . Protection against clinical disease is mainly conferred by serum antibodies; however, mucosal IgA antibodies also may contribute to resistance against infection. Split virus inactivated vaccines can induce neuraminidase (NA)-specific antibody responses [15] [16] [17] , and anti-NA antibodies have been associated with protection from infection in humans [18] [19] [20] [21] [22] . Currently, NA-specific antibody responses are not considered a correlate of protection [14] . LAIV is administered as a nasal spray and contains the same three or four influenza virus strains as inactivated vaccines but on an attenuated vaccine backbone [4] . LAIV are temperature-sensitive and cold-adapted so they do not replicate effectively at core body temperature, but replicate in the mucosa of the nasopharynx [23] . LAIV immunization induces serum antibody responses, mucosal antibody responses (IgA), and T cell responses. While robust serum antibody and nasal wash (mucosal) antibody responses are associated with protection from infection, other immune responses, such as CD8 + cytotoxic lymphocyte (CTL) responses may contribute to protection and there is not a clear correlate of immunity for LAIV [4, 14, 24] .
Currently licensed influenza virus vaccines suffer from a number of issues. The inactivated vaccines rely on specific antibody responses to the HA, and to a lesser extent NA proteins for protection. The immunodominant portions of the HA and NA molecules undergo a constant process of antigenic drift, a natural accumulation of mutations, enabling virus evasion from immunity [9, 25] . Thus, the circulating influenza A and B strains are reviewed annually for antigenic match with current vaccines, Replacement of vaccine strains may occur regularly, and annual vaccination is recommended to assure protection [4, 26, 27] . For the northern hemisphere, vaccine strain selection occurs in February and then manufacturers begin production, taking at least six months to produce the millions of vaccine doses required for the fall [27] . If the prediction is imperfect, or if manufacturers have issues with vaccine production, vaccine efficacy or availability can be compromised [28] . LAIV is not recommended for all populations; however, it is generally considered to be as effective as inactivated vaccines and may be more efficacious in children [4, 9, 24] . While LAIV relies on antigenic match and the HA and NA antigens are replaced on the same schedule as the TIV [4, 9] , there is some suggestion that LAIV may induce broader protection than TIV due to the diversity of the immune response consistent with inducing virus-neutralizing serum and mucosal antibodies, as well as broadly reactive T cell responses [9, 23, 29] . While overall both TIV and LAIV are considered safe and effective, there is a recognized need for improved seasonal influenza vaccines [26] . Moreover, improved understanding of immunity to conserved influenza virus antigens has raised the possibility of a universal vaccine, and these universal antigens will likely require novel vaccines for effective delivery [30] [31] [32] .
Virus-vectored vaccines share many of the advantages of LAIV, as well as those unique to the vectors. Recombinant DNA systems exist that allow ready manipulation and modification of the vector genome. This in turn enables modification of the vectors to attenuate the virus or enhance immunogenicity, in addition to adding and manipulating the influenza virus antigens. Many of these vectors have been extensively studied or used as vaccines against wild type forms of the virus. Finally, each of these vaccine vectors is either replication-defective or causes a self-limiting infection, although like LAIV, safety in immunocompromised individuals still remains a concern [4, 13, [33] [34] [35] . Table 1 summarizes the benefits and concerns of each of the virus-vectored vaccines discussed here.
There are 53 serotypes of adenovirus, many of which have been explored as vaccine vectors. A live adenovirus vaccine containing serotypes 4 and 7 has been in use by the military for decades, suggesting adenoviruses may be safe for widespread vaccine use [36] . However, safety concerns have led to the majority of adenovirus-based vaccine development to focus on replication-defective vectors. Adenovirus 5 (Ad5) is the most-studied serotype, having been tested for gene delivery and anti-cancer agents, as well as for infectious disease vaccines.
Adenovirus vectors are attractive as vaccine vectors because their genome is very stable and there are a variety of recombinant systems available which can accommodate up to 10 kb of recombinant genetic material [37] . Adenovirus is a non-enveloped virus which is relatively stable and can be formulated for long-term storage at 4 °C, or even storage up to six months at room temperature [33] . Adenovirus vaccines can be grown to high titers, exceeding 10 1° plaque forming units (PFU) per mL when cultured on 293 or PER.C6 cells [38] , and the virus can be purified by simple methods [39] . Adenovirus vaccines can also be delivered via multiple routes, including intramuscular injection, subcutaneous injection, intradermal injection, oral delivery using a protective capsule, and by intranasal delivery. Importantly, the latter two delivery methods induce robust mucosal immune responses and may bypass preexisting vector immunity [33] . Even replication-defective adenovirus vectors are naturally immunostimulatory and effective adjuvants to the recombinant antigen being delivered. Adenovirus has been extensively studied as a vaccine vector for human disease. The first report using adenovirus as a vaccine vector for influenza demonstrated immunogenicity of recombinant adenovirus 5 (rAd5) expressing the HA of a swine influenza virus, A/Swine/Iowa/1999 (H3N2). Intramuscular immunization of mice with this construct induced robust neutralizing antibody responses and protected mice from challenge with a heterologous virus, A/Hong Kong/1/1968 (H3N2) [40] . Replication defective rAd5 vaccines expressing influenza HA have also been tested in humans. A rAd5-HA expressing the HA from A/Puerto Rico/8/1934 (H1N1; PR8) was delivered to humans epicutaneously or intranasally and assayed for safety and immunogenicity. The vaccine was well tolerated and induced seroconversion with the intranasal administration had a higher conversion rate and higher geometric meant HI titers [41] . While clinical trials with rAd vectors have overall been successful, demonstrating safety and some level of efficacy, rAd5 as a vector has been negatively overshadowed by two clinical trial failures. The first trial was a gene therapy examination where high-dose intravenous delivery of an Ad vector resulted in the death of an 18-year-old male [42, 43] . The second clinical failure was using an Ad5-vectored HIV vaccine being tested as a part of a Step Study, a phase 2B clinical trial. In this study, individuals were vaccinated with the Ad5 vaccine vector expressing HIV-1 gag, pol, and nef genes. The vaccine induced HIV-specific T cell responses; however, the study was stopped after interim analysis suggested the vaccine did not achieve efficacy and individuals with high preexisting Ad5 antibody titers might have an increased risk of acquiring HIV-1 [44] [45] [46] . Subsequently, the rAd5 vaccine-associated risk was confirmed [47] . While these two instances do not suggest Ad-vector vaccines are unsafe or inefficacious, the umbra cast by the clinical trials notes has affected interest for all adenovirus vaccines, but interest still remains.
Immunization with adenovirus vectors induces potent cellular and humoral immune responses that are initiated through toll-like receptor-dependent and independent pathways which induce robust pro-inflammatory cytokine responses. Recombinant Ad vaccines expressing HA antigens from pandemic H1N1 (pH1N1), H5 and H7 highly pathogenic avian influenza (HPAI) virus (HPAIV), and H9 avian influenza viruses have been tested for efficacy in a number of animal models, including chickens, mice, and ferrets, and been shown to be efficacious and provide protection from challenge [48, 49] . Several rAd5 vectors have been explored for delivery of non-HA antigens, influenza nucleoprotein (NP) and matrix 2 (M2) protein [29, [50] [51] [52] . The efficacy of non-HA antigens has led to their inclusion with HA-based vaccines to improve immunogenicity and broaden breadth of both humoral and cellular immunity [53, 54] . However, as both CD8 + T cell and neutralizing antibody responses are generated by the vector and vaccine antigens, immunological memory to these components can reduce efficacy and limit repeated use [48] .
One drawback of an Ad5 vector is the potential for preexisting immunity, so alternative adenovirus serotypes have been explored as vectors, particularly non-human and uncommon human serotypes. Non-human adenovirus vectors include those from non-human primates (NHP), dogs, sheep, pigs, cows, birds and others [48, 55] . These vectors can infect a variety of cell types, but are generally attenuated in humans avoiding concerns of preexisting immunity. Swine, NHP and bovine adenoviruses expressing H5 HA antigens have been shown to induce immunity comparable to human rAd5-H5 vaccines [33, 56] . Recombinant, replication-defective adenoviruses from low-prevalence serotypes have also been shown to be efficacious. Low prevalence serotypes such as adenovirus types 3, 7, 11, and 35 can evade anti-Ad5 immune responses while maintaining effective antigen delivery and immunogenicity [48, 57] . Prime-boost strategies, using DNA or protein immunization in conjunction with an adenovirus vaccine booster immunization have also been explored as a means to avoided preexisting immunity [52] .
Adeno-associated viruses (AAV) were first explored as gene therapy vectors. Like rAd vectors, rAAV have broad tropism infecting a variety of hosts, tissues, and proliferating and non-proliferating cell types [58] . AAVs had been generally not considered as vaccine vectors because they were widely considered to be poorly immunogenic. A seminal study using AAV-2 to express a HSV-2 glycoprotein showed this virus vaccine vector effectively induced potent CD8 + T cell and serum antibody responses, thereby opening the door to other rAAV vaccine-associated studies [59, 60] .
AAV vector systems have a number of engaging properties. The wild type viruses are non-pathogenic and replication incompetent in humans and the recombinant AAV vector systems are even further attenuated [61] . As members of the parvovirus family, AAVs are small non-enveloped viruses that are stable and amenable to long-term storage without a cold chain. While there is limited preexisting immunity, availability of non-human strains as vaccine candidates eliminates these concerns. Modifications to the vector have increased immunogenicity, as well [60] .
There are limited studies using AAVs as vaccine vectors for influenza. An AAV expressing an HA antigen was first shown to induce protective in 2001 [62] . Later, a hybrid AAV derived from two non-human primate isolates (AAVrh32.33) was used to express influenza NP and protect against PR8 challenge in mice [63] . Most recently, following the 2009 H1N1 influenza virus pandemic, rAAV vectors were generated expressing the HA, NP and matrix 1 (M1) proteins of A/Mexico/4603/2009 (pH1N1), and in murine immunization and challenge studies, the rAAV-HA and rAAV-NP were shown to be protective; however, mice vaccinated with rAAV-HA + NP + M1 had the most robust protection. Also, mice vaccinated with rAAV-HA + rAAV-NP + rAAV-M1 were also partially protected against heterologous (PR8, H1N1) challenge [63] . Most recently, an AAV vector was used to deliver passive immunity to influenza [64, 65] . In these studies, AAV (AAV8 and AAV9) was used to deliver an antibody transgene encoding a broadly cross-protective anti-influenza monoclonal antibody for in vivo expression. Both intramuscular and intranasal delivery of the AAVs was shown to protect against a number of influenza virus challenges in mice and ferrets, including H1N1 and H5N1 viruses [64, 65] . These studies suggest that rAAV vectors are promising vaccine and immunoprophylaxis vectors. To this point, while approximately 80 phase I, I/II, II, or III rAAV clinical trials are open, completed, or being reviewed, these have focused upon gene transfer studies and so there is as yet limited safety data for use of rAAV as vaccines [66] .
Alphaviruses are positive-sense, single-stranded RNA viruses of the Togaviridae family. A variety of alphaviruses have been developed as vaccine vectors, including Semliki Forest virus (SFV), Sindbis (SIN) virus, Venezuelan equine encephalitis (VEE) virus, as well as chimeric viruses incorporating portions of SIN and VEE viruses. The replication defective vaccines or replicons do not encode viral structural proteins, having these portions of the genome replaces with transgenic material.
The structural proteins are provided in cell culture production systems. One important feature of the replicon systems is the self-replicating nature of the RNA. Despite the partial viral genome, the RNAs are self-replicating and can express transgenes at very high levels [67] .
SIN, SFV, and VEE have all been tested for efficacy as vaccine vectors for influenza virus [68] [69] [70] [71] . A VEE-based replicon system encoding the HA from PR8 was demonstrated to induce potent HA-specific immune response and protected from challenge in a murine model, despite repeated immunization with the vector expressing a control antigen, suggesting preexisting immunity may not be an issue for the replicon vaccine [68] . A separate study developed a VEE replicon system expressing the HA from A/Hong Kong/156/1997 (H5N1) and demonstrated varying efficacy after in ovo vaccination or vaccination of 1-day-old chicks [70] . A recombinant SIN virus was use as a vaccine vector to deliver a CD8 + T cell epitope only. The well-characterized NP epitope was transgenically expressed in the SIN system and shown to be immunogenic in mice, priming a robust CD8 + T cell response and reducing influenza virus titer after challenge [69] . More recently, a VEE replicon system expressing the HA protein of PR8 was shown to protect young adult (8-week-old) and aged (12-month-old) mice from lethal homologous challenge [72] .
The VEE replicon systems are particularly appealing as the VEE targets antigen-presenting cells in the lymphatic tissues, priming rapid and robust immune responses [73] . VEE replicon systems can induce robust mucosal immune responses through intranasal or subcutaneous immunization [72] [73] [74] , and subcutaneous immunization with virus-like replicon particles (VRP) expressing HA-induced antigen-specific systemic IgG and fecal IgA antibodies [74] . VRPs derived from VEE virus have been developed as candidate vaccines for cytomegalovirus (CMV). A phase I clinical trial with the CMV VRP showed the vaccine was immunogenic, inducing CMV-neutralizing antibody responses and potent T cell responses. Moreover, the vaccine was well tolerated and considered safe [75] . A separate clinical trial assessed efficacy of repeated immunization with a VRP expressing a tumor antigen. The vaccine was safe and despite high vector-specific immunity after initial immunization, continued to boost transgene-specific immune responses upon boost [76] . While additional clinical data is needed, these reports suggest alphavirus replicon systems or VRPs may be safe and efficacious, even in the face of preexisting immunity.
Baculovirus has been extensively used to produce recombinant proteins. Recently, a baculovirus-derived recombinant HA vaccine was approved for human use and was first available for use in the United States for the 2013-2014 influenza season [4] . Baculoviruses have also been explored as vaccine vectors. Baculoviruses have a number of advantages as vaccine vectors. The viruses have been extensively studied for protein expression and for pesticide use and so are readily manipulated. The vectors can accommodate large gene insertions, show limited cytopathic effect in mammalian cells, and have been shown to infect and express genes of interest in a spectrum of mammalian cells [77] . While the insect promoters are not effective for mammalian gene expression, appropriate promoters can be cloned into the baculovirus vaccine vectors.
Baculovirus vectors have been tested as influenza vaccines, with the first reported vaccine using Autographa californica nuclear polyhedrosis virus (AcNPV) expressing the HA of PR8 under control of the CAG promoter (AcCAG-HA) [77] . Intramuscular, intranasal, intradermal, and intraperitoneal immunization or mice with AcCAG-HA elicited HA-specific antibody responses, however only intranasal immunization provided protection from lethal challenge. Interestingly, intranasal immunization with the wild type AcNPV also resulted in protection from PR8 challenge. The robust innate immune response to the baculovirus provided non-specific protection from subsequent influenza virus infection [78] . While these studies did not demonstrate specific protection, there were antigen-specific immune responses and potential adjuvant effects by the innate response.
Baculovirus pseudotype viruses have also been explored. The G protein of vesicular stomatitis virus controlled by the insect polyhedron promoter and the HA of A/Chicken/Hubei/327/2004 (H5N1) HPAIV controlled by a CMV promoter were used to generate the BV-G-HA. Intramuscular immunization of mice or chickens with BV-G-HA elicited strong HI and VN serum antibody responses, IFN-γ responses, and protected from H5N1 challenge [79] . A separate study demonstrated efficacy using a bivalent pseudotyped baculovirus vector [80] .
Baculovirus has also been used to generate an inactivated particle vaccine. The HA of A/Indonesia/CDC669/2006(H5N1) was incorporated into a commercial baculovirus vector controlled by the e1 promoter from White Spot Syndrome Virus. The resulting recombinant virus was propagated in insect (Sf9) cells and inactivated as a particle vaccine [81, 82] . Intranasal delivery with cholera toxin B as an adjuvant elicited robust HI titers and protected from lethal challenge [81] . Oral delivery of this encapsulated vaccine induced robust serum HI titers and mucosal IgA titers in mice, and protected from H5N1 HPAIV challenge. More recently, co-formulations of inactivated baculovirus vectors have also been shown to be effective in mice [83] .
While there is growing data on the potential use of baculovirus or pseudotyped baculovirus as a vaccine vector, efficacy data in mammalian animal models other than mice is lacking. There is also no data on the safety in humans, reducing enthusiasm for baculovirus as a vaccine vector for influenza at this time.
Newcastle disease virus (NDV) is a single-stranded, negative-sense RNA virus that causes disease in poultry. NDV has a number of appealing qualities as a vaccine vector. As an avian virus, there is little or no preexisting immunity to NDV in humans and NDV propagates to high titers in both chicken eggs and cell culture. As a paramyxovirus, there is no DNA phase in the virus lifecycle reducing concerns of integration events, and the levels of gene expression are driven by the proximity to the leader sequence at the 3' end of the viral genome. This gradient of gene expression enables attenuation through rearrangement of the genome, or by insertion of transgenes within the genome. Finally, pathogenicity of NDV is largely determined by features of the fusion protein enabling ready attenuation of the vaccine vector [84] .
Reverse genetics, a method that allows NDV to be rescued from plasmids expressing the viral RNA polymerase and nucleocapsid proteins, was first reported in 1999 [85, 86] . This process has enabled manipulation of the NDV genome as well as incorporation of transgenes and the development of NDV vectors. Influenza was the first infectious disease targeted with a recombinant NDV (rNDV) vector. The HA protein of A/WSN/1933 (H1N1) was inserted into the Hitchner B1 vaccine strain. The HA protein was expressed on infected cells and was incorporated into infectious virions. While the virus was attenuated compared to the parental vaccine strain, it induced a robust serum antibody response and protected against homologous influenza virus challenge in a murine model of infection [87] . Subsequently, rNDV was tested as a vaccine vector for HPAIV having varying efficacy against H5 and H7 influenza virus infections in poultry [88] [89] [90] [91] [92] [93] [94] . These vaccines have the added benefit of potentially providing protection against both the influenza virus and NDV infection.
NDV has also been explored as a vaccine vector for humans. Two NHP studies assessed the immunogenicity and efficacy of an rNDV expressing the HA or NA of A/Vietnam/1203/2004 (H5N1; VN1203) [95, 96] . Intranasal and intratracheal delivery of the rNDV-HA or rNDV-NA vaccines induced both serum and mucosal antibody responses and protected from HPAIV challenge [95, 96] . NDV has limited clinical data; however, phase I and phase I/II clinical trials have shown that the NDV vector is well-tolerated, even at high doses delivered intravenously [44, 97] . While these results are promising, additional studies are needed to advance NDV as a human vaccine vector for influenza.
Parainfluenza virus type 5 (PIV5) is a paramyxovirus vaccine vector being explored for delivery of influenza and other infectious disease vaccine antigens. PIV5 has only recently been described as a vaccine vector [98] . Similar to other RNA viruses, PIV5 has a number of features that make it an attractive vaccine vector. For example, PIV5 has a stable RNA genome and no DNA phase in virus replication cycle reducing concerns of host genome integration or modification. PIV5 can be grown to very high titers in mammalian vaccine cell culture substrates and is not cytopathic allowing for extended culture and harvest of vaccine virus [98, 99] . Like NDV, PIV5 has a 3'-to 5' gradient of gene expression and insertion of transgenes at different locations in the genome can variably attenuate the virus and alter transgene expression [100] . PIV5 has broad tropism, infecting many cell types, tissues, and species without causing clinical disease, although PIV5 has been associated with -kennel cough‖ in dogs [99] . A reverse genetics system for PIV5 was first used to insert the HA gene from A/Udorn/307/72 (H3N2) into the PIV5 genome between the hemagglutinin-neuraminidase (HN) gene and the large (L) polymerase gene. Similar to NDV, the HA was expressed at high levels in infected cells and replicated similarly to the wild type virus, and importantly, was not pathogenic in immunodeficient mice [98] . Additionally, a single intranasal immunization in a murine model of influenza infection was shown to induce neutralizing antibody responses and protect against a virus expressing homologous HA protein [98] . PIV5 has also been explored as a vaccine against HPAIV. Recombinant PIV5 vaccines expressing the HA or NP from VN1203 were tested for efficacy in a murine challenge model. Mice intranasally vaccinated with a single dose of PIV5-H5 vaccine had robust serum and mucosal antibody responses, and were protected from lethal challenge. Notably, although cellular immune responses appeared to contribute to protection, serum antibody was sufficient for protection from challenge [100, 101] . Intramuscular immunization with PIV5-H5 was also shown to be effective at inducing neutralizing antibody responses and protecting against lethal influenza virus challenge [101] . PIV5 expressing the NP protein of HPAIV was also efficacious in the murine immunization and challenge model, where a single intranasal immunization induced robust CD8 + T cell responses and protected against homologous (H5N1) and heterosubtypic (H1N1) virus challenge [102] .
Currently there is no clinical safety data for use of PIV5 in humans. However, live PIV5 has been a component of veterinary vaccines for -kennel cough‖ for >30 years, and veterinarians and dog owners are exposed to live PIV5 without reported disease [99] . This combined with preclinical data from a variety of animal models suggests that PIV5 as a vector is likely to be safe in humans. As preexisting immunity is a concern for all virus-vectored vaccines, it should be noted that there is no data on the levels of preexisting immunity to PIV5 in humans. However, a study evaluating the efficacy of a PIV5-H3 vaccine in canines previously vaccinated against PIV5 (kennel cough) showed induction of robust anti-H3 serum antibody responses as well as high serum antibody levels to the PIV5 vaccine, suggesting preexisting immunity to the PIV5 vector may not affect immunogenicity of vaccines even with repeated use [99] .
Poxvirus vaccines have a long history and the notable hallmark of being responsible for eradication of smallpox. The termination of the smallpox virus vaccination program has resulted in a large population of poxvirus-naï ve individuals that provides the opportunity for the use of poxviruses as vectors without preexisting immunity concerns [103] . Poxvirus-vectored vaccines were first proposed for use in 1982 with two reports of recombinant vaccinia viruses encoding and expressing functional thymidine kinase gene from herpes virus [104, 105] . Within a year, a vaccinia virus encoding the HA of an H2N2 virus was shown to express a functional HA protein (cleaved in the HA1 and HA2 subunits) and be immunogenic in rabbits and hamsters [106] . Subsequently, all ten of the primary influenza proteins have been expressed in vaccine virus [107] .
Early work with intact vaccinia virus vectors raised safety concerns, as there was substantial reactogenicity that hindered recombinant vaccine development [108] . Two vaccinia vectors were developed to address these safety concerns. The modified vaccinia virus Ankara (MVA) strain was attenuated by passage 530 times in chick embryo fibroblasts cultures. The second, New York vaccinia virus (NYVAC) was a plaque-purified clone of the Copenhagen vaccine strain rationally attenuated by deletion of 18 open reading frames [109] [110] [111] .
Modified vaccinia virus Ankara (MVA) was developed prior to smallpox eradication to reduce or prevent adverse effects of other smallpox vaccines [109] . Serial tissue culture passage of MVA resulted in loss of 15% of the genome, and established a growth restriction for avian cells. The defects affected late stages in virus assembly in non-avian cells, a feature enabling use of the vector as single-round expression vector in non-permissive hosts. Interestingly, over two decades ago, recombinant MVA expressing the HA and NP of influenza virus was shown to be effective against lethal influenza virus challenge in a murine model [112] . Subsequently, MVA expressing various antigens from seasonal, pandemic (A/California/04/2009, pH1N1), equine (A/Equine/Kentucky/1/81 H3N8), and HPAI (VN1203) viruses have been shown to be efficacious in murine, ferret, NHP, and equine challenge models [113] . MVA vaccines are very effective stimulators of both cellular and humoral immunity. For example, abortive infection provides native expression of the influenza antigens enabling robust antibody responses to native surface viral antigens. Concurrently, the intracellular influenza peptides expressed by the pox vector enter the class I MHC antigen processing and presentation pathway enabling induction of CD8 + T cell antiviral responses. MVA also induces CD4 + T cell responses further contributing to the magnitude of the antigen-specific effector functions [107, [112] [113] [114] [115] . MVA is also a potent activator of early innate immune responses further enhancing adaptive immune responses [116] . Between early smallpox vaccine development and more recent vaccine vector development, MVA has undergone extensive safety testing and shown to be attenuated in severely immunocompromised animals and safe for use in children, adults, elderly, and immunocompromised persons. With extensive pre-clinical data, recombinant MVA vaccines expressing influenza antigens have been tested in clinical trials and been shown to be safe and immunogenic in humans [117] [118] [119] . These results combined with data from other (non-influenza) clinical and pre-clinical studies support MVA as a leading viral-vectored candidate vaccine.
The NYVAC vector is a highly attenuated vaccinia virus strain. NYVAC is replication-restricted; however, it grows in chick embryo fibroblasts and Vero cells enabling vaccine-scale production. In non-permissive cells, critical late structural proteins are not produced stopping replication at the immature virion stage [120] . NYVAC is very attenuated and considered safe for use in humans of all ages; however, it predominantly induces a CD4 + T cell response which is different compared to MVA [114] . Both MVA and NYVAC provoke robust humoral responses, and can be delivered mucosally to induce mucosal antibody responses [121] . There has been only limited exploration of NYVAC as a vaccine vector for influenza virus; however, a vaccine expressing the HA from A/chicken/Indonesia/7/2003 (H5N1) was shown to induce potent neutralizing antibody responses and protect against challenge in swine [122] .
While there is strong safety and efficacy data for use of NYVAC or MVA-vectored influenza vaccines, preexisting immunity remains a concern. Although the smallpox vaccination campaign has resulted in a population of poxvirus-naï ve people, the initiation of an MVA or NYVAC vaccination program for HIV, influenza or other pathogens will rapidly reduce this susceptible population. While there is significant interest in development of pox-vectored influenza virus vaccines, current influenza vaccination strategies rely upon regular immunization with vaccines matched to circulating strains. This would likely limit the use and/or efficacy of poxvirus-vectored influenza virus vaccines for regular and seasonal use [13] . Intriguingly, NYVAC may have an advantage for use as an influenza vaccine vector, because immunization with this vector induces weaker vaccine-specific immune responses compared to other poxvirus vaccines, a feature that may address the concerns surrounding preexisting immunity [123] .
While poxvirus-vectored vaccines have not yet been approved for use in humans, there is a growing list of licensed poxvirus for veterinary use that include fowlpox-and canarypox-vectored vaccines for avian and equine influenza viruses, respectively [124, 125] . The fowlpox-vectored vaccine expressing the avian influenza virus HA antigen has the added benefit of providing protection against fowlpox infection. Currently, at least ten poxvirus-vectored vaccines have been licensed for veterinary use [126] . These poxvirus vectors have the potential for use as vaccine vectors in humans, similar to the first use of cowpox for vaccination against smallpox [127] . The availability of these non-human poxvirus vectors with extensive animal safety and efficacy data may address the issues with preexisting immunity to the human vaccine strains, although the cross-reactivity originally described with cowpox could also limit use.
Influenza vaccines utilizing vesicular stomatitis virus (VSV), a rhabdovirus, as a vaccine vector have a number of advantages shared with other RNA virus vaccine vectors. Both live and replication-defective VSV vaccine vectors have been shown to be immunogenic [128, 129] , and like Paramyxoviridae, the Rhabdoviridae genome has a 3'-to-5' gradient of gene expression enabling attention by selective vaccine gene insertion or genome rearrangement [130] . VSV has a number of other advantages including broad tissue tropism, and the potential for intramuscular or intranasal immunization. The latter delivery method enables induction of mucosal immunity and elimination of needles required for vaccination. Also, there is little evidence of VSV seropositivity in humans eliminating concerns of preexisting immunity, although repeated use may be a concern. Also, VSV vaccine can be produced using existing mammalian vaccine manufacturing cell lines.
Influenza antigens were first expressed in a VSV vector in 1997. Both the HA and NA were shown to be expressed as functional proteins and incorporated into the recombinant VSV particles [131] . Subsequently, VSV-HA, expressing the HA protein from A/WSN/1933 (H1N1) was shown to be immunogenic and protect mice from lethal influenza virus challenge [129] . To reduce safety concerns, attenuated VSV vectors were developed. One candidate vaccine had a truncated VSV G protein, while a second candidate was deficient in G protein expression and relied on G protein expressed by a helper vaccine cell line to the provide the virus receptor. Both vectors were found to be attenuated in mice, but maintained immunogenicity [128] . More recently, single-cycle replicating VSV vaccines have been tested for efficacy against H5N1 HPAIV. VSV vectors expressing the HA from A/Hong Kong/156/97 (H5N1) were shown to be immunogenic and induce cross-reactive antibody responses and protect against challenge with heterologous H5N1 challenge in murine and NHP models [132] [133] [134] .
VSV vectors are not without potential concerns. VSV can cause disease in a number of species, including humans [135] . The virus is also potentially neuroinvasive in some species [136] , although NHP studies suggest this is not a concern in humans [137] . Also, while the incorporation of the influenza antigen in to the virion may provide some benefit in immunogenicity, changes in tropism or attenuation could arise from incorporation of different influenza glycoproteins. There is no evidence for this, however [134] . Currently, there is no human safety data for VSV-vectored vaccines. While experimental data is promising, additional work is needed before consideration for human influenza vaccination.
Current influenza vaccines rely on matching the HA antigen of the vaccine with circulating strains to provide strain-specific neutralizing antibody responses [4, 14, 24] . There is significant interest in developing universal influenza vaccines that would not require annual reformulation to provide protective robust and durable immunity. These vaccines rely on generating focused immune responses to highly conserved portions of the virus that are refractory to mutation [30] [31] [32] . Traditional vaccines may not be suitable for these vaccination strategies; however, vectored vaccines that have the ability to be readily modified and to express transgenes are compatible for these applications.
The NP and M2 proteins have been explored as universal vaccine antigens for decades. Early work with recombinant viral vectors demonstrated that immunization with vaccines expressing influenza antigens induced potent CD8 + T cell responses [107, [138] [139] [140] [141] . These responses, even to the HA antigen, could be cross-protective [138] . A number of studies have shown that immunization with NP expressed by AAV, rAd5, alphavirus vectors, MVA, or other vector systems induces potent CD8 + T cell responses and protects against influenza virus challenge [52, 63, 69, 102, 139, 142] . As the NP protein is highly conserved across influenza A viruses, NP-specific T cells can protect against heterologous and even heterosubtypic virus challenges [30] .
The M2 protein is also highly conserved and expressed on the surface of infected cells, although to a lesser extent on the surface of virus particles [30] . Much of the vaccine work in this area has focused on virus-like or subunit particles expressing the M2 ectodomain; however, studies utilizing a DNA-prime, rAd-boost strategies to vaccinate against the entire M2 protein have shown the antigen to be immunogenic and protective [50] . In these studies, antibodies to the M2 protein protected against homologous and heterosubtypic challenge, including a H5N1 HPAIV challenge. More recently, NP and M2 have been combined to induce broadly cross-reactive CD8 + T cell and antibody responses, and rAd5 vaccines expressing these antigens have been shown to protect against pH1N1 and H5N1 challenges [29, 51] .
Historically, the HA has not been widely considered as a universal vaccine antigen. However, the recent identification of virus neutralizing monoclonal antibodies that cross-react with many subtypes of influenza virus [143] has presented the opportunity to design vaccine antigens to prime focused antibody responses to the highly conserved regions recognized by these monoclonal antibodies. The majority of these broadly cross-reactive antibodies recognize regions on the stalk of the HA protein [143] . The HA stalk is generally less immunogenic compared to the globular head of the HA protein so most approaches have utilized -headless‖ HA proteins as immunogens. HA stalk vaccines have been designed using DNA and virus-like particles [144] and MVA [142] ; however, these approaches are amenable to expression in any of the viruses vectors described here.
The goal of any vaccine is to protect against infection and disease, while inducing population-based immunity to reduce or eliminate virus transmission within the population. It is clear that currently licensed influenza vaccines have not fully met these goals, nor those specific to inducing long-term, robust immunity. There are a number of vaccine-related issues that must be addressed before population-based influenza vaccination strategies are optimized. The concept of a -one size fits all‖ vaccine needs to be updated, given the recent ability to probe the virus-host interface through RNA interference approaches that facilitate the identification of host genes affecting virus replication, immunity, and disease. There is also a need for revision of the current influenza virus vaccine strategies for at-risk populations, particularly those at either end of the age spectrum. An example of an improved vaccine regime might include the use of a vectored influenza virus vaccine that expresses the HA, NA and M and/or NP proteins for the two currently circulating influenza A subtypes and both influenza B strains so that vaccine take and vaccine antigen levels are not an issue in inducing protective immunity. Recombinant live-attenuated or replication-deficient influenza viruses may offer an advantage for this and other approaches.
Vectored vaccines can be constructed to express full-length influenza virus proteins, as well as generate conformationally restricted epitopes, features critical in generating appropriate humoral protection. Inclusion of internal influenza antigens in a vectored vaccine can also induce high levels of protective cellular immunity. To generate sustained immunity, it is an advantage to induce immunity at sites of inductive immunity to natural infection, in this case the respiratory tract. Several vectored vaccines target the respiratory tract. Typically, vectored vaccines generate antigen for weeks after immunization, in contrast to subunit vaccination. This increased presence and level of vaccine antigen contributes to and helps sustain a durable memory immune response, even augmenting the selection of higher affinity antibody secreting cells. The enhanced memory response is in part linked to the intrinsic augmentation of immunity induced by the vector. Thus, for weaker antigens typical of HA, vectored vaccines have the capacity to overcome real limitations in achieving robust and durable protection.
Meeting the mandates of seasonal influenza vaccine development is difficult, and to respond to a pandemic strain is even more challenging. Issues with influenza vaccine strain selection based on recently circulating viruses often reflect recommendations by the World Health Organization (WHO)-a process that is cumbersome. The strains of influenza A viruses to be used in vaccine manufacture are not wild-type viruses but rather reassortants that are hybrid viruses containing at least the HA and NA gene segments from the target strains and other gene segments from the master strain, PR8, which has properties of high growth in fertilized hen's eggs. This additional process requires more time and quality control, and specifically for HPAI viruses, it is a process that may fail because of the nature of those viruses. In contrast, viral-vectored vaccines are relatively easy to manipulate and produce, and have well-established safety profiles. There are several viral-based vectors currently employed as antigen delivery systems, including poxviruses, adenoviruses baculovirus, paramyxovirus, rhabdovirus, and others; however, the majority of human clinical trials assessing viral-vectored influenza vaccines use poxvirus and adenovirus vectors. While each of these vector approaches has unique features and is in different stages of development, the combined successes of these approaches supports the virus-vectored vaccine approach as a whole. Issues such as preexisting immunity and cold chain requirements, and lingering safety concerns will have to be overcome; however, each approach is making progress in addressing these issues, and all of the approaches are still viable. Virus-vectored vaccines hold particular promise for vaccination with universal or focused antigens where traditional vaccination methods are not suited to efficacious delivery of these antigens. The most promising approaches currently in development are arguably those targeting conserved HA stalk region epitopes. Given the findings to date, virus-vectored vaccines hold great promise and may overcome the current limitations of influenza vaccines. | What does the TIV contain? | false | 1,259 | {
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1,741 | MERS coronavirus: diagnostics, epidemiology and transmission
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4687373/
SHA: f6fcf1a99cbd073c5821d1c4ffa3f2c6daf8ae29
Authors: Mackay, Ian M.; Arden, Katherine E.
Date: 2015-12-22
DOI: 10.1186/s12985-015-0439-5
License: cc-by
Abstract: The first known cases of Middle East respiratory syndrome (MERS), associated with infection by a novel coronavirus (CoV), occurred in 2012 in Jordan but were reported retrospectively. The case first to be publicly reported was from Jeddah, in the Kingdom of Saudi Arabia (KSA). Since then, MERS-CoV sequences have been found in a bat and in many dromedary camels (DC). MERS-CoV is enzootic in DC across the Arabian Peninsula and in parts of Africa, causing mild upper respiratory tract illness in its camel reservoir and sporadic, but relatively rare human infections. Precisely how virus transmits to humans remains unknown but close and lengthy exposure appears to be a requirement. The KSA is the focal point of MERS, with the majority of human cases. In humans, MERS is mostly known as a lower respiratory tract (LRT) disease involving fever, cough, breathing difficulties and pneumonia that may progress to acute respiratory distress syndrome, multiorgan failure and death in 20 % to 40 % of those infected. However, MERS-CoV has also been detected in mild and influenza-like illnesses and in those with no signs or symptoms. Older males most obviously suffer severe disease and MERS patients often have comorbidities. Compared to severe acute respiratory syndrome (SARS), another sometimes- fatal zoonotic coronavirus disease that has since disappeared, MERS progresses more rapidly to respiratory failure and acute kidney injury (it also has an affinity for growth in kidney cells under laboratory conditions), is more frequently reported in patients with underlying disease and is more often fatal. Most human cases of MERS have been linked to lapses in infection prevention and control (IPC) in healthcare settings, with approximately 20 % of all virus detections reported among healthcare workers (HCWs) and higher exposures in those with occupations that bring them into close contact with camels. Sero-surveys have found widespread evidence of past infection in adult camels and limited past exposure among humans. Sensitive, validated reverse transcriptase real-time polymerase chain reaction (RT-rtPCR)-based diagnostics have been available almost from the start of the emergence of MERS. While the basic virology of MERS-CoV has advanced over the past three years, understanding of the interplay between camel, environment, and human remains limited. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12985-015-0439-5) contains supplementary material, which is available to authorized users.
Text: An email from Dr Ali Mohamed Zaki, an Egyptian virologist working at the Dr Soliman Fakeeh Hospital in Jeddah in the Kingdom of Saudi Arabia (KSA) announced the first culture of a new coronavirus to the world. The email was published on the website of the professional emerging diseases (ProMED) network on 20 th September 2012 [1] (Fig. 1) and described the first reported case, a 60 year old man from Bisha in the KSA. This information led to the rapid discovery of a second case of the virus, this time in an ill patient in the United Kingdom, who had been transferred from Qatar for care [2] . The new virus was initially called novel coronavirus (nCoV) and subsequentlty entitled the Middle East respiratoy syndrome coronavirus (MERS-CoV). As of 2 nd of September 2015, there have been 1,493 detections of viral RNA or virus-specific antibodies across 26 countries (Additional file 1: Figure S1 ) confirmed by the World Health Organization (WHO), with over a third of the positive people dying (at least 527, 35 %) [3] .
Since that first report, a slow discovery process over the following two to three years revealed a virus that had infected over 90 % of adult dromedary camels (DC; Camelus dromedarius) in the KSA [4] , also DCs across the Arabian Peninsula and parts of Africa that are a source of DC imports for the KSA [5] . To date, MERS-CoV has not been detected in DCs tested in zoos or herds from other parts of the world [6] [7] [8] [9] . Occasionally, virus is transmitted from infected DCs to exposed humans. Subsequent transmission to other humans requires relatively close and prolonged exposure [10] .
The first viral isolate was patented and concerns were raised that this would restrict access to both the virus and to viral diagnostics [11, 12] . However, sensitive, validated reverse transcriptase real-time polymerase chain reaction (RT-rtPCR)-based diagnostics were quickly described and virus was made freely available subject to routine biosafety considerations [13] . Subsequent epidemiology and research has identified the cell receptor as exopeptidase dipeptidyl peptidase 4 (DPP4; also called CD26); that MERS-CoV has a broad tropism, replicating better in some cells lines and eliciting a more proinflammatory response than SARS-CoV; is widespread in DCs; has the potential to infect other animals and that MERS kills its human host more often than SARS did (20-40 % versus 9 % for SARS [14] ) [15] [16] [17] [18] [19] .
In humans, overt disease was given the name Middle East respiratory syndrome, with the acronym MERS. From intermittent animal-to-human spill-over events, the MERS-CoV spreads sporadically among people, causing more severe disease among older adults, especially males, with pre-existing diseases. The spread of MERS-CoV among humans has often been associated with outbreaks in hospitals, with around 20 % of all cases to date involving healthcare workers (HCWs).
Although DCs appear to suffer the equivalent of a 'common cold' from MERS-CoV infection, in humans, the virus can be a more serious and opportunistic pathogen associated with the death of up to 40 % of reported cases. It has yet to be established whether infections thought to have been acquired from an animal source produce a more severe outcome than those spread between humans [20] . Studies have established that the mean incubation period for MERS is five to six days, ranging from two to 16 days, with 13 to 14 days between when illness begins in one person and subsequently spreads to another [21] [22] [23] [24] . Among those with progressive illness, the median time to death is 11 to 13 days, ranging from five to 27 days [23, 24] . Fever and gastrointestinal symptoms may form a prodrome, after which symptoms decline, only to be followed by a more severe systemic and respiratory syndrome [25, 26] .
The first WHO case definition [27] defined probable cases of MERS based on the presence of febrile illness, cough and requirement for hospitalization with suspicion of lower respiratory tract (LRT) involvement. It also included roles for contact with a probable or confirmed case or for travel or residence within the Arabian Peninsula. If strictly adhered to, only the severe syndrome would be subject to laboratory testing, which was the paradigm early on [21] . From July 2013, the revised WHO case definition included the importance of seeking out and understanding the role of asymptomatic cases and from June 2014, the WHO definition more clearly stated that a confirmed case included any person whose sample was RT-PCR positive for MERS-CoV, or who produced a seroconversion, irrespective of clinical signs and symptoms. [28] [29] [30] Apart from the WHO and the KSA Ministry of Health reports, asymptomatic or subclinical cases of MERS-CoV infection were documented in the scientific literature although not always as often as occurred early on [31, 32] . The KSA definition of a case became more strict on 13 th May 2014, relying on the presence of both clinical features and laboratory confirmation [33] . Testing of asymptomatic people was recommended against from December 2014 [34] , reinforced by a case definition released by the KSA Ministry of Health in June 2015 [35] . The KSA has been the source of 79 % of human cases. Severe MERS is notable for its impact among older men with comorbid diseases including diabetes mellitus, cirrhosis and various lung, renal and cardiac conditions [36] [37] [38] . Interestingly in June 2015, an outbreak in South Korea followed a similar distribution [39, 40] . Among laboratory confirmed cases, fever, cough and upper respiratory tract (URT) signs and symptoms usually occur first, followed within a week by progressive LRT distress and lymphopaenia [37] . Patients often present to a hospital with pneumonia, or worse, and secondary bacterial infections have been reported [37, 41] . Disease can progress to acute respiratory distress syndrome and multiorgan system failure [37] . MERS has reportedly killed approximately 35 % of all reported cases, 42 % of cases in the KSA, yet only 19 % of cases in South Korea, where mortality ranged from 7 % among younger age groups to 40 % among those aged 60 years and above [42] ; all may be inflated values with asymptomatic or mild infections sometimes not sought or not reported [34] . General supportive care is key to managing severe cases [43] . Children under the age of 14 years are rarely reported to be positive for MERS-CoV, comprising only 1.1 % (n = 16) of total reported cases. Between 1 st September 2012 and 2 nd December 2013, a study described the then tally of paediatric cases in the KSA, which stood at 11 (two to 16 years of age; median 13 years); nine were asymptomatic (72 %) and one infant died [44] . In Amman, Jordan, 1,005 samples from hospitalized children under the age of two years with fever and/or respiratory signs and symptoms were tested but none were positive for MERS-CoV RNA, despite being collected at a similar time to the first known outbreak of MERS-CoV in the neighbouring town of Al-Zarqa [45] . A second trimester stillbirth occurred in a pregnant woman during an acute respiratory illness and while not RT-rtPCR positive, the mother did subsequently develop antibodies to MERS-CoV, suggestive of recent infection [46] . Her exposure history to a MERS-CoV RT-rtPCR positive relative and an antibody-reactive husband, her incubation period and her symptom history met the WHO criteria for being a probable MERS-CoV case [46] .
Diagnostic methods were published within days of the ProMED email announcing the first MERS case [47] , including several now gold standard in-house RT-rtPCR assays (Fig. 2 ) as well as virus culture in Vero and LLC-MK2 cells [18, 47, 48] . A colorectal adenocarcinoma (Caco-2) epithelial cell line has since been recommended for isolation of infections MERS-CoV [49] . We previously [18] .). Open reading frames are indicated as yellow rectangles bracketed by terminal untranslated regions (UTR; grey rectangles). FS-frame-shift. Predicted regions encompassing recombination break-points are indicated by orange pills. Created using Geneious v8.1 [211] and annotated using Adobe Illustrator. Beneath this is a schematic depicting the location of RT-PCR primers (blue arrows indicate direction) and oligoprobes (green rectangles) used in the earliest RT-rtPCR screening assays and conventional, semi-nested (three primers) RT-PCR confirmatory sequencing assays [47, 48] . Publication order is noted by first [27 th September 2012; red] and second [6 th December 2012; orange] coloured rectangles; both from Corman et al. [47, 48] Those assays recommended by the WHO are highlighted underneath by yellow dots [53] . The NSeq reverse primer has consistently contained one sequence mismatch with some MERS-CoV variants. An altered version of that from Mackay IM, Arden KE. Middle East respiratory syndrome: An emerging coronavirus infection tracked by the crowd. Virus Res 2015 Vol 202:60-88 with permission from Elsevier [5] reviewed the broad tropism of MERS-CoV [5] . However, as is well described, cell culture is a slow, specialised and insensitive method [50] while PCR-based techniques are the preferred method for MERS-CoV detection.
The first open reading frames (ORF 1a and 1b; Fig. 2 ) have become a key diagnostic and taxonomic target for CoV species identification. With less than 80 % identity between the amino acid sequence of MERS ORF 1ab and betacoronavirus relatives, Tylonycteris bat HKU4 and Pipistrellus bat HKU5, it can be concluded that it is a novel and distinct virus. MERS-CoV is predicted to encode ten open reading frames with 5' and 3' untranslated regions [51] . The structural proteins include the spike (S), envelope (E), membrane (M) and nucleocapsid (N) [52] . The products of ORF1a and ORF1b are predicted to encode nonstructural proteins.
The majority of specimen testing to date has employed validated RT-rtPCR assays shown to be sensitive and specific [47, 48, 53] . The RealStar® kit uses these WHOrecommended assays [54] . The target sequences of these screening assays have not changed among genomes examined until at least mid-2015 (IMM observation). Other RT-rtPCR assays have been developed and validated for use as laboratory-based diagnostic tools [55] [56] [57] . Additionally, loop-mediated [58, 59] or recombinase polymerase [60] isothermal assays have been designed for field deployment.
The detection of MERS-CoV antigen has not been common to date but the combination of short turnaround time from test to result, high throughput and identification of viral proteins makes this an attractive option. Detection of viral proteins rather than viral RNA indicates the likely presence of infectious virus. The first rapid immunochromatographic tool described could detect recombinant MERS-CoV nucleocapsid protein from DC nasal swabs with 94 % sensitivity and 100 % specificity compared to RT-rtPCR [61] . A different approach used a monoclonal antibody-based capture ELISA targeting the MERS-CoV nucleocapsid protein with a sensitivity of 10 3 TCID 50 and 100 % specificity [62] .
Demonstration of a seroconversion to a MERS-CoV infection meets the current WHO definition of a case so optimized and thoroughly validated sero-assays employed alongside good clinical histories are useful to both identify prior MERS-CoV infection and help support transmission studies. Because serology testing is, by its nature, retrospective, it is usual to detect a viral footprint, in the form of antibodies, in the absence of any signs or symptoms of disease and often in the absence of any viral RNA [63] .
Strategic, widespread sero-surveys of humans using samples collected after 2012 are infrequent. Much of the Arabian Peninsula and all of the Horn of Africa lack baseline data describing the proportion of the community who may have been infected by a MERS-CoV. However, sero-surveys have had widespread use in elucidating the role of DCs as a transmission source for MERS-CoV. Because of the identity shared between DC and human MERS-CoV (see Molecular epidemiology: using genomes to understand outbreaks), serological assays for DC sero-surveys should be transferrable to human screening with minimal re-configuration. Also, no diagnostically relevant variation in neutralization activity have been found from among a range of circulating tested MERS-CoV isolates and sera, so whole virus or specific protein-based sero-assays should perform equivalently in detecting serological responses to the single MERS-CoV serotype [49] . The development of robust serological assays requires reliable panels of wellcharacterized animal or human sera, including those positive for antibodies specific to MERS-CoV, as well as to likely sources of cross-reaction [64] . Obtaining these materials was problematic and slowed the development and commercialization of antibody detection assays for human testing [64] . A number of commercial ELISA kits, immunofluorescent assays (IFA) kits, recombinant proteins and monoclonal antibodies have been released [31, [65] [66] [67] [68] . Initially, conventional IFAs were used for human sero-surveys. These relied on MERS-CoV-infected cell culture as an antigen source, detecting the presence of human anti-MERS-CoV IgG, IgM or neutralizing antibodies in human samples [18, 48, 69] . No sign of MERS-CoV antibodies was found among 2,400 sera from patients visiting Hospital in Jeddah, from 2010 through 2012, prior to the description of MERS-CoV [18] . Nor did IFA methods detect any sign of prior MERS-CoV infection among a small sample of 130 healthy blood donors from another Hospital in Jeddah (collected between Jan and Dec 2012) [70] . Of 226 slaughterhouse workers, only eight (3.5 %) were positive by IFA, and those sera could not be confirmed by virus neutralization (NT) test. The study indicated that HCoV-HKU1 was a likely source of crossreactive antigen in the whole virus IFA [70] . Whole virus MERS-CoV IFA also suffered from some cross-reactivity with convalescent SARS patient sera and this could not be resolved by an NT test which was also cross-reactive [71] . IFA using recombinant proteins instead of whole-virus IFA, has been shown to be a more specific tool [31] . Since asymptomatic zoonoses have been posited [72] , an absence of antibodies to MERS-CoV among some humans who have regular and close contact with camels may reflect the rarity of actively infected animals at butcheries, a limited transmission risk associated with slaughtering DCs [70] , a pre-existing cross-protective immune status or some other factor(s) resulting in a low risk of disease and concurrent seroconversion developing after exposure in this group. IFA using recombinant proteins instead.
Some sero-assays have bypassed the risks of working with infectious virus by creating transfected cells expressing recombinant portions of the MERS-CoV nucleocapsid and spike proteins [48, 73] , or using a recombinant lentivirus expressing MERS-CoV spike protein and luciferase [74, 75] . A pseudo particle neutralization (ppNT) assay has seen widespread used in animal studies and was at least as sensitive as the traditional microneutralization (MNT) test. [10, 74, [76] [77] [78] ] Studies using small sample numbers and ppNT found no evidence of MERS-CoV neutralizing antibody in sera from 158 children with LRT infections between May 2010 and May 2011, 110 sera from 19 to 52 year old male blood donors and 300 selfidentified animal workers from the Jazan Region of the KSA during 2012 [79, 80] . Similarly, a study of four herdsmen in contact with an infected DC herd in Al-Ahsa, eight people who had intermittent contact with the herd, 30 veterinary surgeons and support staff who were not exposed to the herd, three unprotected abattoir workers in Al-Ahsa and 146 controls who were not exposed to DCs in any professional role, found none with serological evidence of past MERS-CoV infection using the ppNT assay [10] . A delay in the neutralizing antibody response to MERS-CoV infection was associated with increased disease severity in South Korea cases with most responses detectable by week three of illness while others, even though disease was severe, did not respond for four or more weeks [81] . The implications for our ability to detect any response in mild or asymptomatic cases was not explored but may be a signifcant factor in understanding exposure in the wider community.
A Jordanian outbreak of acute LRT disease in a hospital in 2012 was retrospectively found to be associated with MERS-CoV infection, initially using RT-rtPCR, but subsequently, and on a larger scale, through positivity by ELISA and IFA or MNT test. [46, 82, 83] This outbreak predated the first case of MERS in the KSA. The ELISA used a recombinant nucleocapsid protein from the group 2 betacoronavirus bat-CoV HKU5 to identify antibodies against the equivalent crossreactive MERS-CoV protein [71] . It was validated using 545 sera collected from people with prior HCoV-OC43, HCoV-229E, SARS-CoV, HCoV-NL63, HRV, HMPV or influenza A(H1N1) infections but was reportedly less specific than the recombinant IFA discussed above. It was still considered an applicable tool for screening large sample numbers [82] . A protein microarray expressing the S1 protein subunit has also been validated and widely used for DC testing [5, 84] . Detection of MERS-CoV infection using ELISA or S1 subunit protein microarray [84] is usually followed by confirmatory IFA and/ or a plaque-reduction neutralization (PRNT) [69, 70, 85] or MNT test. [74, 85, 86] This confirmatory process aims toensure the antibodies detected are able to specifically neutralize the intended virus and are not more broadly reactive to other coronaviruses found in DCs (bovine CoV, BCoV) or humans (HCoV-OC43, HCoV-229E, HCoV-NL63, HCoV-HKU1, SARS-CoV). In the largest study of human sera, a tiered diagnostic process assigned both recombinant IFA and recombinant ELISA positive sera to 'stage 1' seropositivity. A stage 2 seropositive result additionally required a suitably titred PRNT result [87] . The study found 15 sera collected in 2012 to 2013 from 10,009 (0.2 %) people in 13 KSA provinces contained MERS-CoV antibodies, but significantly higher proportions in occurred in camel shepherds (two of 87; 2.3 %) and slaughterhouse workers (five of 140; 3.6 %) [87] . Contemporary surveys are needed.
MERS-CoV does not appear to be easily transmitted from DCs to humans, or perhaps it is [72] , but generally does not trigger a detectable immune response if only mild disease or asymptomatic infection results. Serology assays are in need of further validation in this area so care is required when moving newly developed diagnostic serology algorithms from a research setting to one that informs public health decisions. This was reinforced when a false positive US case, purported to have been infected after a handshake and two face-to-face meetings, did not withstand further confirmatory analysis using a more specific, NT assay and was subsequently retracted [88, 89] .
The WHO recommends sampling from the LRT for MERS-CoV RT-rtPCR testing, especially when sample collection is delayed by a week or more after onset of symptoms. [53] LRT samples are also best for attempting isolation of infectious virus, although the success of culture is reduced when disease persists [49] . Recommended sample types include bronchoalveolar lavage (BAL), tracheal/tracheobronchial aspirate, pleural fluid and sputum [53, 90] . Fresh samples yield better diagnostic results than refrigerated material [69] and if delays in testing of ≥72 h are likely, samples (except for blood) should be frozen at −70°C [90] . If available, lung biopsy or autopsy tissues can also be tested [53] . The URT is a less invasive and more convenient sampling site however, and an oropharyngeal and throat swab or a nasopharyngeal aspirate/wash are recommended when URT sampling is to be conducted [90] . Paired sera, collected two to three weeks apart are preferable for serological testing while a single sample is suggested to be sufficient if collected two weeks after onset of disease or a single serum collected during the first 10-12 days if conducting RT-rtPCR [53, 90] . Human urine and stool have been found to contain MERS-CoV RNA 12 to 26 days after symptom onset [25, 69, 91] and are listed as samples that should be considered [53, 90] . In two cases that arrived in the Netherlands, urine was RT-rtPCR negative but faeces was weakly positive and sera were RT-rtPCR positive for five days or more [25] . The finding of MERS-CoV viral RNA in serum provides an avenue for retrospective PCR-based studies if respiratory samples are unavailable [83] . RNAaemia may also correlate with disease severity; signs of virus were cleared from the serum of a recovered patient, yet lingered until the death of another [92] .
Clinically suspected MERS cases may return negative results by RT-rtPCR. Data have shown one or more negative URT samples may be contradicted by further URT sampling or the use of LRT samples, which is preferred [2, 43, 93] . Higher viral loads occur in the LRT compared to the URT. [22, 69, 88, 94] This fits with the observation that the majority of disease symptoms are reported to manifest as systemic and LRT disease [21] . However, on occasion, even LRT specimens from MERS cases may initially be negative, only to later become positive by RT-PCR [95] . This may be due to poor sampling when a cough is absent or non-productive or because the viral load is low [95] . Despite this both the largest human MERS-CoV studies [32, [96] [97] [98] and smaller ones [22, 25, 99] , use samples from the URT. It is then noteworthy that one study reported an association between higher loads in the URT and worse clinical outcome including intensive care and death [94] . At writing, no human data exist to define whether the virus replicates solely or preferentially in the LRT or URT, or replicates in other human tissues in vivo although MERS-CoV RNA has been detected from both the URT and LRT in a macaque monkey model [100] .The distribution of DPP4 in the human upper airways is also not well described.
Individual human case studies report long periods of viral shedding, sometimes intermittently and not necessarily linked to the presence of disease symptoms. [25, 69, 99, 101] In one instance, a HCW shed viral RNA for 42 days in the absence of disease [99] . It is an area of high priority to better understand whether such cases are able to infect others. Over three quarters of MERS cases shed viral RNA in their LRT specimens (tracheal aspirates and sputum) for at least 30 days, while only 30 % of contacts were still shedding RNA in their URT specimens [91, 102] .
In the only study to examine the effect of sample type on molecular analysis, 64 nasopharyngeal aspirates (NPA; an URT sample), 30 tracheal aspirates, 13 sputa and three BAL were examined. The tracheal aspirates and BAL returned the highest viral load values followed by NPA and sputum. Unsurprisingly, higher viral loads generally paralleled whole genome sequencing and culture success and, in NPA testing, were significantly correlated with severe disease and death [49, 94, 103] . This study demonstrated the importance of LRT sampling for whole genome sequencing.
When tested, samples positive for MERS-CoV are often negative for other pathogens [2, 25, 93, 104] . However, many studies make no mention of additional testing for endemic human respiratory viruses [21, 23, 73, 105] . When viruses are sought, they have included human herpesvirus (HHV), rhinoviruses (HRV), enteroviruses (EV), respiratory syncytial virus (RSV), parainfluenzavirus types 1, 2 and 3 (PIVs),influenzaviruses (IFVs), endemic HCoVs, adenoviruses (AdVs) metapneumovirus (MPV) and influenza A\H1N1 virus; co-detections with MERS-CoV have been found on occasion [2, 22, 37, 69, 97] . Bacterial testing is sometimes included (for example, for Legionella and Pneumococcus) but the impact of bacterial co-presence is also unclear [22, [104] [105] [106] . Further testing of the LRT sample from the first MERS case used IFA to screen for some viruses (negative for IFV, PIVs, RSV and AdVs) and RT-PCR for others (negative for AdV, EVs, MPV and HHVs) [18] . RT-PCR also detected MERS-CoV. The WHO strongly recommends testing for other respiratory pathogens [53] but with this recommendation often discounted, there are limited data to address the occurrence and impact of co-infections or alternative viral diagnoses among both MERS cases and their contacts. Little is known of other causes of MERS-like pneumonia in the KSA or of the general burden of disease due to the known classical respiratory viruses.
Testing of adult pilgrims performing the Hajj in 2012 to 2014 has not detected any MERS-CoV. In 2012, nasal swabs from 154 pilgrims collected prior to leaving for or departing from the KSA were tested [47] . In 2013, testing was significantly scaled up with 5,235 nasopharyngeal swabs from 3,210 incoming pilgrims and 2,025 swabs from outgoing pilgrims tested [98] . It should be noted that most pilgrims arrived from MERS-free countries. A further 114 swabs were taken from pilgrims with influenza-like illness [96, 107] . In earlier Hajj gatherings, it was found that influenza viruses circulated widely, whilst other viruses, often rhinoviruses, circulated more selectively, interpreted as indicating their importation along with foreign pilgrims. [107] [108] [109] Over time, increased influenza vaccination has been credited for a fall in the prevalence of influenza like illnesses among Hajj pilgrims. [110] A LRT sample is often not collected for these studies [98, 107, 109] , so false negative findings are a possibility although little is known about the initial site of MERS-CoV infection and replication; it may have been assumed it was the LRT because disease was first noticed there but the URT may be the site of the earliest replication.
In Jeddah between March and July 2014 (hereafter called the Jeddah-2014 outbreak; Fig. 3 ), there was a rapid increase in MERS cases, accompanied by intense screening; approximately 5,000 samples from in and around the region were tested in a month yielding around 140 MERS-CoV detections (~3 % prevalence) [111] . Among 5,065 individuals sampled and tested across the KSA between October 2012 and September 2013,108 (2.1 %) detections were made in a hospital-centric population which included hospitalized cases (n = 2,908; 57.4 %), their families (n = 462; 9.1 %) and associated HCWs (n = 1,695; 33.5 %) [32] . Among the detections, 19 (17.8 %) were HCWs and 10 (9.3 %) were family contacts [32] .
The 2-3 % prevalence of active MERS-CoV infections is not dissimilar to the hospital-based prevalence of other human CoVs. [112] However, the proportion of deaths among those infected with MERS-CoV is much higher than that known for the HCoVs NL63, HKU1, 229E or OC43 in other countries, and even above that for SARS-CoV; it is not a virus that could reasonably be described as a "storm in a teacup". It is the low transmission rate that has prevented worldwide spread, despite many "opportunities".
Very early in the MERS outbreak, some animals were highly regarded as either the reservoir or intermediate host(s) of MERS-CoV with three of the first five cases having contact with DCs [73, 113, 114] . Today, animal MERS-CoV infections must be reported to the world organization for animal health as an emerging disease [115] . A summary of the first MERS cases reported by the WHO defined animal contact with humans as being direct and within 10 days prior to symptom onset [20] . This definition made no specific allowance for acquisition from DCs through a droplet-based route, which is very likely route for acquisition of a virus that initially and predominantly causes respiratory disease [23] . Camels are known to produce high levels of MERS-CoV RNA in their URT and lungs [116] . Providing support for a droplet transmission route and perhaps indicating the presence of RNA in smaller, drier droplet nuclei, MERS-CoV RNA was identified in a high volume air sample collected from a barn housing an infected DC [117] . The precise source from which humans acquire MERS-CoV remains poorly studied but it seems likely that animal and human behavioural factors may play roles (Fig. 3) [118] . These factors may prove important for human cases who do not describe any DC contact [119] nor any contact with a confirmed case. Whether the WHO definition of animal contact is sufficient to identify exposure to this respiratory virus remains unclear. Wording focuses on consumption of DC products but does not specifically ascribe risk to a droplet route for acquisition of MERS-CoV from DC [120] . Some MERS patients are listed in WHO disease notices as being in proximity to DCs or farms, but the individuals have not described coming into contact with the animals. No alternative path for acquiring infection is reported in many of these instances. What constitutes a definition of "contact" during these interviews has been defined for one study [72] . Despite this lack of clarity, the WHO consider that evidence linking MERS-CoV transmission between DCs to humans is irrefutable (Fig. 4) [120] .
The possibility that bats were an animal host of MERS-CoV was initially widely discussed because of the existing diversity of coronaviruses known to reside among them [121] [122] [123] [124] . Conclusive evidence supporting bats as a source for human infections by MERS-CoV has yet to be found, but bats do appear to host ancestral representatives [53, 125] . However, these are not variants of the same virus nor always within the same phylogenetic lineage as MERS-CoV; they are each a genetically distinct virus. Bat-to-human infection by MERS-CoV is a purely speculative event. The only piece of MERS-CoV-specific evidence pointing to bats originates from amplification of a 190 nt fragment of the RNAdependent RNA polymerase gene of the MERS-CoV genome, identified in a faecal pellet from an insectivorous Emballonuridae bat, Taphozous perforatus found in Bisha, the KSA [121] . While very short, the sequence of the fragment defined it as a diagnostic discovery. Subsequently a link to DCs was reported [85] and that link has matured into a verified association [38, 126] (Fig. 4) .
(See figure on previous page.) Fig. 3 Monthly detections of MERS-CoV (blue bars) and of cases who died (red bars) with some dates of interest marked for 2012 to 4 th September 2015. An approximation of when DC calving season [128] and when recently born DCs are weaned is indicated. Spring (green) and summer (orange) in the Arabian Peninsula are also shaded. Note the left-hand y-axis scale for 2014 and 2015 which is greater than for 2012/13. Sources of these public data include the WHO, Ministries of Health and FluTrackers [207] [208] [209] . Earlier and subsequent versions of this chart are maintained on a personal blog [210] . Modified and reprinted from Mackay IM, Arden KE. Middle East respiratory syndrome: An emerging coronavirus infection tracked by the crowd. Virus Res 2015 Vol 202:60-88 with permission from Elsevier [5] DCs, which make up 95 % of all camels, have a central presence in the Arabian Peninsula where human-DC contact ranges from little to close [119] . Contact may be commonplace and could occur in variety of ways (Fig. 4a) . There are several large well-attended festivals, races, sales and parades which feature DCs and DCs are also kept and bred close to populated areas in the KSA [127, 128] . DC milk and meat are widely consumed and the older DC is an animal of ritual significance after the Hajj pilgrimage [129] . However, MERS-CoV infection frequency is reportedly much lower than is the widespread and frequent habit of eating, drinking and preparing DC products. Daily ingestion of fresh unpasteurized DC milk is common among the desert Bedouin and many others in the KSA. DC urine is also consumed or used for supposed health benefits. Despite camel butchery being a local occupation, neither butchers nor other at-risk groups are identifiable among MERS cases; this may simply be a reporting issue rather than an unexplainable absence of MERS. A small case-control study published in 2015 identified direct DC contact, and not ingestion of products, to be associated with onset of MERS [38] .
The first sero-survey of livestock living in the Middle East region was conducted during 2012-2013 [85] . DCs were sampled from a mostly Canary Island-born herd and from Omani DCs (originally imported from the Horn of Africa) [85] . A neutralising antibody assay found only 10 % of strongly seropositive Canary Island [5] . b Camel-to-human infections appear to be infrequent, while human-to-human spread of infection is regularly facilitated by poor IPC in healthcare settings where transmission is amplified, accounting for the bulk of cases. There are human MERS cases that do not fall into either category of source and it is unclear if these acquired infection through some entirely separate route, or from cases that escaped diagnosis. c Hypothetical ways in which subclinical (when infection may not meet a previously defined clinical threshold of signs and/or symptoms) or asymptomatic (no obvious signs or measured, noticed or recalled symptoms of illness) MERS-CoV infection may be implicated in transmission DC sera could neutralise MERS-CoV while all Omani DC sera had high levels of specific MERS-CoV neutralizing antibody [85] . This indicated that DCs had in the past been infected by MERS-CoV, or a very similar virus.
Since this study, a host of peer-reviewed reports have looked at both DCs and other animals, and the possibility that they may host MERS-CoV infection. Seropositive DCs have been found throughout the Arabian Peninsula including Oman, the KSA, Qatar, Jordan, the United Arab Emirates (UAE), Kuwait as well as Sudan, Somalia, Egypt, Tunisia, Nigeria, Kenya and Ethiopia in Africa and the Canary Islands [85, [130] [131] [132] [133] [134] . Other animals tested include sheep, cows, pigs, horses, donkeys, mules, birds, water buffalo, goats, Bactrian camels, llamas and guanaco (south American camelids) but none had detectable neutralising antibody against MERS-CoV [4, 74, 78, 85, 86, 135, 136] . No virology or serology studies of human samples from areas in Africa where there are camels with a history of MERS-CoV have been reported to date. However,an absence of unexplained pneumonia that may be attributable to MERS-CoV infection may not signal the absence of virus among humans in each country but simply reflect a lack of expensive epidemiology studies conducted by resource-poor countries. It is thus unclear whether MERS-CoV, or an antigenically related CoV, is an unrecognized pathogen in these regions, perhaps circulating for even longer than it has been known in the Arabian Peninsula [133] .
MERS-CoV RNA has also been detected in DC samples, and recovery of infectious virus has also been achieved from DC samples [4, 77, 117, 132, [137] [138] [139] [140] [141] . From some of these, full or majority length genomes of MERS-CoV have been sequenced [77, 137, 138] . DC versions of MERS-CoV were found to be as similar to each other, as were variants detected from different humans over time and across distance.
Antibody screening assays have also detected crossreactive antibodies in sera. These were identified as such by screening sera against similar viruses, for example BCoV or HCoV-OC43 (as an antigenic facsimile for BCoV). It is possible that other MERS-CoV-like viruses also reside within DCs, but this does not detract from the definitive finding of MERS-CoV genetic sequences in both DCs and humans [117, 142, 143] .
Screening studies have shown that juvenile DCs are more often positive for virus or viral RNA while older DCs are more likely to be seropositive and RNA or virus negative [76, 77, 144] . In adult DCs, MERS-CoV RNA has been detected among animals with pre-existing antibody, suggesting re-infection is possible [77, 144] . Viral loads among positive DCs can be very high [4, 76, 77, 139, 144] and DCs have been found positive both when ill with URT respiratory signs [77, 117, 142, 145] or when apparently healthy [137] . These findings indicate DCs host natural MERS-CoV infections. Furthermore, stored DC sera have revealed signs of MERS-CoV in DCs which date back over three decades (the earliest collected in 1983) [4, 133, 135] . Older sera have not been tested and so precisely how long DCs have been afflicted by MERS-CoV, whether the virus is enzootic among them, introduced to them decades or centuries ago from bats in Africa or the Arabian Peninsula, or they are the subject of regular but short-lived viral incursions from an as yet unknown host, cannot be answered.
Researchers sought to determine a direction for infection; were DCs transmitting virus to humans or were humans infecting DCs? At a Qatari site, a farm owner and his employee became ill in mid-October 2013 and tested positive for MERS-CoV RNA in a sputum and throat swab sample, respectively. RT-rtPCRs found MERS-CoV RNA in 11 of 14 positive DC nasal swabs at the farm; six (43 %) positive by two or more assays [138] . The results indicated a recent outbreak had occurred in this herd; the first indication of MERS-CoV RNA found within DCs with a temporal association to human infections. Three positive DC samples were confirmed by sequencing a 358 nt portion of the spike gene; these sequences were identical to each other, again with close homology to other human and DC MERS-CoV sequences [138] . The DCs and human contacts yielded ORF1a and ORF4b sequences differing by only a single nucleotide each, clustering closely with the Hafr-Al-Batin_1_2013 variant [138] . Subsequent case studies found evidence of a concurrent human and DC infection and the direction of that infection was inferred to be from the ill DCs and to their human owners [117, 142, 146] . Partial genome sequences indicated that a human and a MERS-CoV RT-rtPCR positive DC had been infected by a variant of the same virus, harbouring the same distinct pattern of nucleotide polymorphisms. [142] All nine DC in the owner's herd, serially sampled, reacted in a recombinant S1 antigen ELISA, with the two animals that had been RT-rtPCR positive showing a small, verifiable rise in antibody titre [142] . A rise in titre theoretically begins 10 to 21 days after DC infection [142] . The authors suggested that the rise in titre in DC sera which occurred alongside a declining RNA load, while the patient was actively ill and hospitalized, indicated that the DCs were infected first followed by the owner [117, 142] . BCoV antibodies were also present, and rising in one of the two RT-rtPCR positive animals but no animal's antibodies could neutralise BCoV infection [142] .
Camel calving season occurs in the winter months (between late October and late February; Fig. 3 ) and this may be a time when there is increased risk to humans of spill-over due to new infections among naïve DC populations [128] . What role maternal camel antibody might play in delaying infection of calves remains unknown [128, 142] . Juvenile DCs appear to host active infection more often than adult DCs and thus the sacrificial slaughter of DCs, which must be five years of age or older (termed a thane), may not be accompanied by significant risk of exposure to infection. In contrast to earlier results, slaughterhouse workers who kill both younger and older DCs, may be an occupational group with significantly higher incidence of seropositivity to MERS-CoV when animals have active MERS-CoV infections [129, 139, [147] [148] [149] . Expanded virological investigations of African DCs may lead to more seropositive animals and geographic areas in which humans may be at risk. It is possible that there are areas where humans already harbour MERS-CoV infections that have not been identified because of an absence of laboratory surveillance. Virological investigations of bats may lead to findings of ancestral viruses and viral 'missing links' and identifying any other animal sources of zoonotic spread is important to inform options for reducing human exposures [56, 76] .
Infectious MERS-CoV added to DC, goat or cow milk and stored at 4°C could be recovered at least 72 h later and, if stored at 22°C, recovery was possible for up to 48 h [150] . MERS-CoV titre decreased somewhat when recovered from milk at 22°C but pasteurization completely ablated MERS-CoV infectivity [150] . In a subsequent study, MERS-CoV RNA was identified in the milk, nasal secretion and faeces of DCs from Qatar [151] .
A single study has examined the ability of MERS-CoV to survive in the environment [150] . Plastic or steel surfaces were inoculated with 10 6 TCID 50 of MERS-CoV at different temperature and relative humidity (RH) and virus recovery was attempted in cell culture. At high ambient temperature (30°C) and low RH (30 %) MERS-CoV remained viable for 24 h [150] . By comparison, a well known and efficently transmitted respiratory virus, influenza A virus, could not be recovered in culture beyond four hours under any conditions [150] . Aerosol experiments found MERS-CoV viability only decreased 7 % at low RH at 20°C. In comparison, influenza A virus decreased by 95 % [150] . MERS-CoV survival is inferior to that previously demonstrated for SARS-CoV [152] . For context, pathogenic bacteria can remain viable and airborne for 45 min in a coughed aerosol and can spread 4 m. MERS-CoV's ability to remain viable over long time periods gives it the capacity to thoroughly contaminate a room's surfaces when occupied by an infected and symptomatic patient [153] . Whether MERS-CoV can remain adrift and infectious for extended periods (truly airborne) remains unknown. Such findings expand our understanding of the possibilities for droplets to transmit respiratory viruses in many settings, including hospital waiting rooms, emergency departments, treatment rooms, open intensive care facilities and private patient rooms. The nature and quality of air exchange, circulation and filtration are important variables in risk measurement and reduction as is the use of negative pressure rooms to contain known cases. Droplet spread between humans is considered the mechanism of human-to-human transmission and the need for droplet precautions was emphasized after the Al-Ahsa hospital, the KSA and the South Korean outbreaks [21, 23, 154, 155] . By extrapolation, aerosol-generating events involving DCs (urination, defecation, and preparation and consumption of DC products) should be factored into risk measurement and reduction efforts and messaged using appropriate context. The provision of evidence supporting the best formulation of personal protective equipment to be worn by HCWs who receive, manage or conduct procedures on infectious cases remains a priority.
MERS-CoV was found and characterized because of its apparent association with severe, and therefore more obvious, illness in humans; we were the canaries in the coal mine. Sero-assays and prospective cohort studies have yet to determine the extent to which milder or asymptomatic cases contribute to MERS-CoV transmission chains. However, transmission of MERS-CoV is defined as sporadic (not sustained), intra-familial, often healthcare associated, inefficient and requiring close and prolonged contact [22, 31, 63, 93, 97, 102, 156] In a household study, 14 of 280 (5 %) contacts of 26 MERS-CoV positive index patients were RNA or antibody positive; the rate of general transmission, even in outbreaks is around 3 % [31] . It seems that the majority of human cases of MERS-CoV, even when numbers appear to increase suddenly, do not readily transmit to more than one other human so to date, the localized epidemic of MERS-CoV has not been self-sustaining [157] [158] [159] [160] [161] . That is to say, the basic reproduction number (R 0 ) -the average number of infections caused by one infected individual in a fully susceptible populationhas been close to one throughout various clusters and outbreaks. If R 0 was greater than 1, a sustained increase in case numbers would be expected. Some R o calculations may be affected by incomplete case contact tracing, limited community testing and how a case is defined. That MERS has had a constant presence in the Arabian Peninsula since 2012 is due to ongoing, sporadic spill-over events from DCs amplified by poorly controlled hospital outbreaks.
The first known MERS human-to-human transmission event was one characterized by acute LRT disease in a healthcare setting in Jordan. In stark contrast, a sero-survey of HCW who were sometimes in close and prolonged contact with the first, fatal MERS-CoV case in 2012 [162] , found none of the HCW had seroconverted four months later, despite an absence of eye protection and variable compliance with required PPE standards [162] .
Early on in the MERS story, samples for testing were mostly collected from patients with severe illness and not those with milder acute respiratory tract infections. Contacts of confirmed MERS cases were often observed for clinical illness, but not tested. These omissions may have confounded our understanding of MERS-CoV transmission and biased early data towards higher numbers of seriously ill and hospitalized patients, inflating the apparent proportion of fatal cases. Case-control studies were not a focus. As testing paradigms changed and contacts were increasingly tested, more asymptomatic and mild infections were recognized [163] .
A rise in the cases termed asymptomatic (which enlarge the denominator for calculations of the proportion of fatal cases, defined in [164] ) resulted in a drop in the proportion of fatal cases during the Jeddah-2014 outbreak. Historically, such rises are consistent with changing definitions and laboratory responses and clinical management of a newly discovered virus infection that was first noted only among the severely ill. Upon follow-up, over three-quarters of such MERS-CoV RNA positive people did recall having one or more symptoms at the time, despite being reported as asymptomatic [165] raising some question over the reliability of other reported data.
The proportion of fatal MERS cases within the KSA compared to outside the KSA, as well as the age, and sex distribution change in different ways when comparing MERS outbreaks. Approximately 43 % of MERS cases (549 of 1277) in the KSA were fatal betwen 2012 and December 2015 while 21 % (72 of 330) died among those occurring outside of the KSA. The total number of male cases always outnumber females and the proportion of male deaths is always greater than the proportion of females who die. However the proportion of male deaths from total males with MERS is a similar figure to that for females. In the KSA, there is a greater proportion of younger males among cases and deaths than were observed from the 2015 South Korean or the Jeddah-2014 outbreaks (Additional file 2: Figure S2 ). Why these aspects have differed may be due to differences in the time to presentation and diagnosis, the nature and quality of supportive care, the way a person became infected (habits, exposure to a human or zoonotic source, viral load, route of infection) or the extent to which different populations are burdened by underlying diseases [40] .
As a group, HCWs comprised 16 % of MERS cases in the KSA and South Korea. It is apparent that the weekly proportion of infected HCWs increases alongside each steep rise in overall detections (Fig. 5) . In May 2013, the WHO published guidelines for IPC during care of probable or confirmed cases of MERS-CoV infection in a healthcare setting [166] . This is explainable because to date, each case rise has been intimately associated with healthcare-facility related outbreaks [118] . These rises in MERS-CoV detections can decrease the average age during each event because HCWs are usually younger than inpatients with MERS. Healthcare facilities have been a regular target for suggested improvements aimed at improving infection prevention and control (IPC) procedures [115, 118] .
Most of the analysis of MERS-CoV genetics has been performed using high throughput or "deep" sequencing methods for complete genome deduction [167] [168] [169] . MERS-CoV was the first subject of such widespread use of deep sequencing to study an emerging viral outbreak with global reach. The technique can produce genomic [207] [208] [209] . Earlier and subsequent versions of this chart are maintained on a personal blog [210] length coverage in a single experiment with highly repetitious measurement of each nucleotide position [52, 140] . Despite assays having been published early on, subgenomic sequencing, once the mainstay of viral outbreak studies, has less often been published during MERS-CoV characterization [48] . As more genomes from both humans and DCs have been characterized, two clades have become apparent; A and B (Fig. 6) . Clade A contains only human-derived MERS-CoV genomes from Jordan, while Clade B comprises the majority of human and camel genomes deduced thus far [168] .
Two studies during 2015, one looking at Jeddah-2014 MERS-CoV variants and another looking at a variant exported from South Korea to China, have now identified signs of genetic recombination among MERS-CoV variants. While human and camel whole genome sequences have retained >99 % identity with each other, members of genetically distinct lineages can and do swap genetic material when suitable conditions and coinfections co-occur [170] [171] [172] . Shared identity implies that the major source for human acquisition is the DC, rather than another animal, although more testing of other animal species is needed to confirm that conclusion. Over a month, a DC virus sequenced on different occasions did not change at all indicating a degree of genomic stability in its host, supporting that DCs are the natural, rather than intermediate, host for the MERS-CoV we know today [77] . To date, recombination has been localised to breakpoints near the boundary between ORF1a and ORF1b regions, within the spike gene [170] and in the ORF1b region (Fig. 2) [172] . It is not unexpected that recombination should occur since it is well known among other CoVs [124] and because the majority of MERS-CoV whole genomes collected from samples spanning three years (2012-2015) and from humans, camels and different countries have shown close genetic identity to each other, with just enough subtle variation to support outbreak investigations so long as whole genome sequencing is applied [52, 77, 135, 138, 168, [173] [174] [175] .
Changes in genome sequence may herald alterations to virus transmissibility, replication, persistence, lethality or response to future drugs. If we have prior knowledge of the impact of genetic changes because of thorough characterization studies, we can closely Fig. 6 The genetic relationship between MERS-CoV nucleotide sequences (downloaded from GenBank using the listed accession numbers and from virological.org [212] ). This neighbour joining tree was created in MEGA v6 using an alignment of human and DCderived MERS-CoV sequences (Geneious v8.1 [211] ). Clades are indicated next to dark (Clade A) or pale (Clade B) blue vertical bars. Camel icons denote genomes from DCs. Healthcare or community outbreaks are boxed and labelled using previously described schemes [212, 213] monitor the genomic regions and better understand any changes in transmission or disease patterns as they occur. Genetic mutations noted during the largest of human outbreaks, Jeddah-2014, did not impart any major replicative or immunomodulatory changes when compared to earlier viral variants in vitro [156, 176] . However, we understand very little of the phenotypic outcomes that result from subtle genetic change in MERS-CoV genomes. To date no clinical relevance or obvious in vivo changes to viral replication, shedding or transmission has been reported or attributed to mutations or to new recombinant viruses [156] . But vigilance and larger, more contemporary and in vivo studies are needed.
Genome sequence located to a distinct clade were identified from an Egyptian DC that was probably imported from Sudan. This does not fit into either of the current clades [125, 168, 177] . A virus sequenced from a Neoromicia capensis bat was more closely related to MERS-CoV than other large bat-derived sequences had been to that point, but the genome of a variant of a MERS-CoV has yet to be discovered and deduced from any bat [125] .
Analyses of MERS-CoV genomes have shown that most single nucleotide differences among variants were located in the last third of the genome (Fig. 2) , which encodes the spike protein and accessory proteins [168] . At least nine MERS-CoV genomes contained amino acid substitutions in the receptor binding domain (RBD) of the spike protein and codons 158 (N-terminal region), 460 (RBD), 1020 (in heptad repeat 1), 1202 and 1208 bear investigation as markers of adaptive change [140, 169] . The spike protein had not changed in the recombinant MERS-CoV genome identified in China in 2015 but was reported to have varied at a higher rate than that for complete MERS-CoV genomes, among South Korean variants [172, 178] . This highlights that subgenomic regions may not always contain enough genetic diversity to prove useful for differentiating viral variants. Despite this, one assay amplifying a 615 nucleotide fragment of the spike S2 domain gene for Sanger sequencing agreed with the results generated by the sequencing of a some full genomes and was useful to define additional sequence groupings [177] .
Genomic sequence can also be used to define the geographic boundaries of a cluster or outbreak and monitor its progress, based on the similarity of the variants found among infected humans and animals when occurring together, or between different sites and times (Fig. 6 ) [169] . This approach was employed when defining the geographically constrained MERS hospital outbreak in Al-Ahsa, which occurred between 1 st April and 23 rd May 2013, as well as clusters in Buraidah and a community outbreak in Hafr Al-Batin, the KSA. Genomic sequencing identified that approximately 12 MERS-CoV detections from a community outbreak in Hafr Al-Batin between June and August 2013 may have been triggered by an index case becoming infected through DC contact [175] . Sequencing MERS-CoV genomes from the 2013 Al-Ahsa hospital outbreak indicated that multiple viral variants contributed to the cases but that most were similar enough to each other to be consistent with human-tohuman transmission. Molecular epidemiology has revealed otherwise hidden links in transmission chains encompassing a period of up to five months [179] . However, most outbreaks have not continued for longer than two to three months and so opportunities for the virus to adapt further to humans through co-infection and sustained serial passage have been rare [169] . In Riyadh-2014, genetic evidence supported the likelihood of multiple external introductions of virus, implicating a range of healthcare facilities in an event that otherwise looked contiguous [23, 168, 179] . Riyadh is a nexus for camel and human travel and has had more MERS cases than any other region of the KSA to date but also harbours a wide range of MERS-CoV variants [128, 167, 179] . However the South Korean outbreak originated from a single infected person, resulting in three to four generations of cases [180, 181] . Studies of this apparently recombinant viral variant did not find an increased evolutionary rate and no sign of virus adaptation thus the outbreak seems to have been driven by circumstance rather than circumstance together with mutation [181] .
For many MERS cases detected outside the Arabian Peninsula, extensive contact tracing has been performed and the results described in detail. Contact tracing is essential to contain the emergence and transmission of a new virus and today it is supported by molecular epidemiology. Although it is an expensive and time consuming process, contact tracing can identify potential new infections and through active or passive monitoring, react more rapidly if disease does develop. Results of contact tracing to date have found that onward transmission among humans is an infrequent event. For example, there were 83 contacts, both symptomatic and asymptomatic, of a case treated in Germany who travelled from the UAE but no sign of virus or antibody were found in any of them [73] . The very first MERS case had made contact with 56 HCWs and 48 others, but none developed any indication of infection [162] . In a study of 123 contacts of a case treated in France, only seven matched the definition for a possible case and were tested; one who had shared a 20 m 2 hospital room while in a bed 1.5 m away from the index case for a prolonged period was positive [26] . None of the contacts of the first two MERS cases imported into the USA in 2014 contained any MERS-CoV footprint [182] and none of the 131 contacts of two travellers returning to the Netherlands developed MERS-CoV antibodies or tested RNA positive [25, 183] . Analyses of public data reveal many likely instances of nosocomial acquisition of infection in the Arabian Peninsula and these data may be accompanied by some details noting contact with a known case or facility. One example identified the likely role of a patient with a subclinical infection, present in a hospital during their admission for other reasons, as the likeliest index case triggering a family cluster [93] . Contact tracing was a significant factor in the termination of a 2015 outbreak involving multiple South Korean hospitals [184] . Such studies demonstrate the necessity of finding and understanding a role for mild and asymptomatic cases, together with restricting close contact or prolonged exposure of infected people to others, especially older family members and friends with underlying disease (Fig. 4c) .
The hospital-associated outbreak in Jeddah in 2014 was the largest and most rapid accumulation of MERS-CoV detections to date. The greatest number of MERS-CoV detections of any month on record occurred in Jeddah in April. The outbreak was mostly (>60 % of cases) associated with human-to-human spread within hospital environments and resulted from a lack of, or breakdown in, infection prevention and control [37, 185, 186] . A rise in fatalities followed the rapid increase in case numbers.
In 2015 two large outbreaks occurred. South Korea was the site of the first large scale outbreak outside the Arabian Peninsula and produced the first cases in both South Korea and China, occurring between May and July 2015. This was closely followed by a distinct outbreak in Ar Riyad province in the KSA which appeared to come under control in early November.
After staying in Bahrain for two weeks, a 68 year old male (68 M) travelled home to South Korea via Qatar, arriving free of symptoms on the 4 th May 2015 [187] . He developed fever, myalgia and a cough nearly a week later (11 th ). He visited a clinic as an outpatient between the 12 th and 15 th of May and was admitted to Hospital A on the 15 th [188] . He was discharged from Hospital A on the 17 th then visited and was admitted to the emergency department of Hospital B on the 18 th . During this second stay, a sputum sample was taken and tested positive for MERS-CoV on the 20 th [187, 188] , triggering transfer to the designated isolation treatment facility. Over a period of 10 days, the index case was seen at three different hospitals, demonstrating a key feature of "hospital shopping" that shaped the South Korean outbreak. Approximately 34 people were infected during this time [187] . In total 186 cases were generated in this outbreak, all linked through a single transmission chain to 68 M; 37 cases died [189] . In South Korea, the national health insurance system provides for relatively low cost medical care, defraying some costs by making family members responsible for a portion of the ministration of the sick, resulting in them sometimes staying for long periods in the rooms that often have more than four beds in them [24] . Other factors thought to have enabled this outbreak included unfamiliarity of local clinicians with MERS, ease with which the public can visit and be treated by tertiary hospitals, the custom of visiting sick friends and relatives in hospitals, the hierarchical nature of Korean society, crowded emergency rooms, poor IPC measures, a lack of negative pressure isolation rooms and poor inter-hospital communication of patient disease histories [24, [190] [191] [192] . All of the reported transmission occurred across three or four generations and apart from one unknown source, were all hospital-acquired [24, 120, 181, [193] [194] [195] . Few clinical details about these cases have been reported to date and detail on transmission and contact tracing is minimal. The hospitals involved were initially not identified, governmental guidance and actions produced confusing messages and there was very limited communication at all early on which resulted in unnecessary concern, distrust and a distinct economic impact [191, [196] [197] [198] . Early in the outbreak, a infected traveller, the son of an identified case in South Korea, passed through Hong Kong on his way to China where he was located, isolated and cared for in China [91, 199, 200] . No contacts became ill. The outbreak was brought under control in late July/ early August [201] after improved IPC measures were employed, strong contact tracing monitoring and quarantine, expanded laboratory testing, hospitals were better secured, specialized personnel were dispatched to manage cases and international cooperation increased [202, 203] . A review of public data showed that, as for MERS in the KSA, older age and the presence of underlying disease were significantly associated with a fatal outcome in South Korea. [40] Even though R 0 is <1, super-spreading events facilitated by circumstances created in healthcare settings and characterized by cluster sizes over 150, such as this one, are not unexpected from MERS-CoV infection [204] . The dynamic of an outbreak depends on the R 0 and an individual's viral shedding patterns, contact type and frequency, hospital procedures and population structure and density [204] .
In the region of Ar Riyad, including the capital city of Riyadh, a hospital based cluster began, within a single hospital, from late June 2015 [205] . By mid-September there had been approximately170 cases reported but the outbreak appeared to been brought under control in November.
It became apparent early on that MERS-CoV spread relatively ineffectively from human-to-human. Despite ongoing and possibly seasonal introduction of virus to the human population via infected DCs and perhaps other animals yet to be identified, the vast majority of MERS-CoV transmission has occurred from infected to uninfected humans in close and prolonged contact through circumstances created by poor infection control in health care settings. This opportunistic virus has had its greatest impact on those with underlying diseases and such vulnerable people, sometimes suffering multiple comorbidities, have been most often associated with hospitals, creating a perfect storm of exposure, transmission and mortality. It remains unclear if this group are uniquely affected by MERS-CoV or if other respiratory virus infections, including those from HCoVs, produce a similarly serious impact. In South Korea, a single imported case created an outbreak of 185 cases and 36 deaths that had a disproportionate impact on economic performance, community behaviour and trust in government and the health care system. Household human-to human transmission occurs but is also limited. Educational programs will be essential tools for combatting the spread of MERS-CoV both within urban and regional communities and for the health care setting.
Vigilance remains important for containment since MERS-CoV is a virus with a genetic makeup that has been observed for only three years and is not stable. Among all humans reported to be infected, nearly 40 % have died. Continued laboratory testing, sequencing, analysis, timely data sharing and clear communication are essential for such vigilance to be effective. Global alignment of case definitions would further aid accurate calculation of a case fatality ratio by including subclinical case numbers. Whole genome sequencing has been used extensively to study MERS-CoV travel and variation and although it remains a tool for experts, it appears to be the best tool for the job.
MERS and SARS have some clinical similarities but they also diverge significantly [206] . Defining characteristics include the higher PFC among MERS cases (above 50 % in 2013 and currently at 30-40 %; well above the 9 % of SARS) and the higher association between fatal MERS and older males with underlying comorbidities. For the viruses, MERS-CoV has a broader tropism, grows more rapidly in vitro, more rapidly induces cytopathogenic change, triggers distinct transcriptional responses, makes use of a different receptor, induces a more proinflammatory state and has a delayed innate antiviral response compared to SARS-CoV.
There appears to be a 2-3 % prevalence of MERS-CoV in the KSA with a 5 % chance of secondary transmission within the household. There is an increased risk of infection through certain occupations at certain times and a much greater chance for spread to other humans during circumstances created by humans, which drives more effective transmission than any R 0 would predict on face value. Nonetheless, despite multiple mass gatherings that have afforded the virus many millions of opportunities to spread, there have remarkably been no reported outbreaks of MERS or MERS-CoV during or immediately after these events. There is no evidence that MERS-CoV is a virus of pandemic concern. Nonetheless, hospital settings continue to describe MERS cases and outbreaks in the Arabian Peninsula. As long as we facilitate the spread of MERS-CoV among our most vulnerable populations, the world must remain on alert for cases which may be exported more frequently when a host country with infected camel reservoirs is experiencing human clusters or outbreaks.
The MERS-CoV appears to be an enzootic virus infecting the DC URT with evidence of recent genetic recombination. It may once have had its origins among bats, but evidence is lacking and the relevance of that to today's ongoing epidemic is academic. Thanks to quick action, the sensitive and rapid molecular diagnostic tools required to achieve rapid and sensitive detection goal have been in place and made widely available since the virus was reported in 2012. RT-PCR testing of LRT samples remains the gold standard for MERS-CoV confirmation. Serological tools continue to emerge but they are in need of further validation using samples from mild and asymptomatic infections and a densely sampled cohort study to follow contacts of new cases may address this need. Similarly, the important question of whether those who do shed MERS-CoV RNA for extended periods are infectious while appearing well, continues to go unanswered. It is even unclear just how many 'asymptomatic' infections have been described and reported correctly which in turn raises questions about the reliability of other clinical data collection to date. While the basic virology of MERS-CoV has advanced over the course of the past three years, understanding what is happening in, and the interplay between, camel, environment and human is still in its infancy.
Additional file 1: Figure S1 . The | What does subsequent transmission of MERS-CoV to other humans require? | false | 4,198 | {
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2,504 | Respiratory Viral Infections in Exacerbation of Chronic Airway Inflammatory Diseases: Novel Mechanisms and Insights From the Upper Airway Epithelium
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7052386/
SHA: 45a566c71056ba4faab425b4f7e9edee6320e4a4
Authors: Tan, Kai Sen; Lim, Rachel Liyu; Liu, Jing; Ong, Hsiao Hui; Tan, Vivian Jiayi; Lim, Hui Fang; Chung, Kian Fan; Adcock, Ian M.; Chow, Vincent T.; Wang, De Yun
Date: 2020-02-25
DOI: 10.3389/fcell.2020.00099
License: cc-by
Abstract: Respiratory virus infection is one of the major sources of exacerbation of chronic airway inflammatory diseases. These exacerbations are associated with high morbidity and even mortality worldwide. The current understanding on viral-induced exacerbations is that viral infection increases airway inflammation which aggravates disease symptoms. Recent advances in in vitro air-liquid interface 3D cultures, organoid cultures and the use of novel human and animal challenge models have evoked new understandings as to the mechanisms of viral exacerbations. In this review, we will focus on recent novel findings that elucidate how respiratory viral infections alter the epithelial barrier in the airways, the upper airway microbial environment, epigenetic modifications including miRNA modulation, and other changes in immune responses throughout the upper and lower airways. First, we reviewed the prevalence of different respiratory viral infections in causing exacerbations in chronic airway inflammatory diseases. Subsequently we also summarized how recent models have expanded our appreciation of the mechanisms of viral-induced exacerbations. Further we highlighted the importance of the virome within the airway microbiome environment and its impact on subsequent bacterial infection. This review consolidates the understanding of viral induced exacerbation in chronic airway inflammatory diseases and indicates pathways that may be targeted for more effective management of chronic inflammatory diseases.
Text: The prevalence of chronic airway inflammatory disease is increasing worldwide especially in developed nations (GBD 2015 Chronic Respiratory Disease Collaborators, 2017 Guan et al., 2018) . This disease is characterized by airway inflammation leading to complications such as coughing, wheezing and shortness of breath. The disease can manifest in both the upper airway (such as chronic rhinosinusitis, CRS) and lower airway (such as asthma and chronic obstructive pulmonary disease, COPD) which greatly affect the patients' quality of life (Calus et al., 2012; Bao et al., 2015) . Treatment and management vary greatly in efficacy due to the complexity and heterogeneity of the disease. This is further complicated by the effect of episodic exacerbations of the disease, defined as worsening of disease symptoms including wheeze, cough, breathlessness and chest tightness (Xepapadaki and Papadopoulos, 2010) . Such exacerbations are due to the effect of enhanced acute airway inflammation impacting upon and worsening the symptoms of the existing disease (Hashimoto et al., 2008; Viniol and Vogelmeier, 2018) . These acute exacerbations are the main cause of morbidity and sometimes mortality in patients, as well as resulting in major economic burdens worldwide. However, due to the complex interactions between the host and the exacerbation agents, the mechanisms of exacerbation may vary considerably in different individuals under various triggers. Acute exacerbations are usually due to the presence of environmental factors such as allergens, pollutants, smoke, cold or dry air and pathogenic microbes in the airway (Gautier and Charpin, 2017; Viniol and Vogelmeier, 2018) . These agents elicit an immune response leading to infiltration of activated immune cells that further release inflammatory mediators that cause acute symptoms such as increased mucus production, cough, wheeze and shortness of breath. Among these agents, viral infection is one of the major drivers of asthma exacerbations accounting for up to 80-90% and 45-80% of exacerbations in children and adults respectively (Grissell et al., 2005; Xepapadaki and Papadopoulos, 2010; Jartti and Gern, 2017; Adeli et al., 2019) . Viral involvement in COPD exacerbation is also equally high, having been detected in 30-80% of acute COPD exacerbations (Kherad et al., 2010; Jafarinejad et al., 2017; Stolz et al., 2019) . Whilst the prevalence of viral exacerbations in CRS is still unclear, its prevalence is likely to be high due to the similar inflammatory nature of these diseases (Rowan et al., 2015; Tan et al., 2017) . One of the reasons for the involvement of respiratory viruses' in exacerbations is their ease of transmission and infection (Kutter et al., 2018) . In addition, the high diversity of the respiratory viruses may also contribute to exacerbations of different nature and severity (Busse et al., 2010; Costa et al., 2014; Jartti and Gern, 2017) . Hence, it is important to identify the exact mechanisms underpinning viral exacerbations in susceptible subjects in order to properly manage exacerbations via supplementary treatments that may alleviate the exacerbation symptoms or prevent severe exacerbations.
While the lower airway is the site of dysregulated inflammation in most chronic airway inflammatory diseases, the upper airway remains the first point of contact with sources of exacerbation. Therefore, their interaction with the exacerbation agents may directly contribute to the subsequent responses in the lower airway, in line with the "United Airway" hypothesis. To elucidate the host airway interaction with viruses leading to exacerbations, we thus focus our review on recent findings of viral interaction with the upper airway. We compiled how viral induced changes to the upper airway may contribute to chronic airway inflammatory disease exacerbations, to provide a unified elucidation of the potential exacerbation mechanisms initiated from predominantly upper airway infections.
Despite being a major cause of exacerbation, reports linking respiratory viruses to acute exacerbations only start to emerge in the late 1950s (Pattemore et al., 1992) ; with bacterial infections previously considered as the likely culprit for acute exacerbation (Stevens, 1953; Message and Johnston, 2002) . However, with the advent of PCR technology, more viruses were recovered during acute exacerbations events and reports implicating their role emerged in the late 1980s (Message and Johnston, 2002) . Rhinovirus (RV) and respiratory syncytial virus (RSV) are the predominant viruses linked to the development and exacerbation of chronic airway inflammatory diseases (Jartti and Gern, 2017) . Other viruses such as parainfluenza virus (PIV), influenza virus (IFV) and adenovirus (AdV) have also been implicated in acute exacerbations but to a much lesser extent (Johnston et al., 2005; Oliver et al., 2014; Ko et al., 2019) . More recently, other viruses including bocavirus (BoV), human metapneumovirus (HMPV), certain coronavirus (CoV) strains, a specific enterovirus (EV) strain EV-D68, human cytomegalovirus (hCMV) and herpes simplex virus (HSV) have been reported as contributing to acute exacerbations . The common feature these viruses share is that they can infect both the upper and/or lower airway, further increasing the inflammatory conditions in the diseased airway (Mallia and Johnston, 2006; Britto et al., 2017) .
Respiratory viruses primarily infect and replicate within airway epithelial cells . During the replication process, the cells release antiviral factors and cytokines that alter local airway inflammation and airway niche (Busse et al., 2010) . In a healthy airway, the inflammation normally leads to type 1 inflammatory responses consisting of activation of an antiviral state and infiltration of antiviral effector cells. This eventually results in the resolution of the inflammatory response and clearance of the viral infection (Vareille et al., 2011; Braciale et al., 2012) . However, in a chronically inflamed airway, the responses against the virus may be impaired or aberrant, causing sustained inflammation and erroneous infiltration, resulting in the exacerbation of their symptoms (Mallia and Johnston, 2006; Dougherty and Fahy, 2009; Busse et al., 2010; Britto et al., 2017; Linden et al., 2019) . This is usually further compounded by the increased susceptibility of chronic airway inflammatory disease patients toward viral respiratory infections, thereby increasing the frequency of exacerbation as a whole (Dougherty and Fahy, 2009; Busse et al., 2010; Linden et al., 2019) . Furthermore, due to the different replication cycles and response against the myriad of respiratory viruses, each respiratory virus may also contribute to exacerbations via different mechanisms that may alter their severity. Hence, this review will focus on compiling and collating the current known mechanisms of viral-induced exacerbation of chronic airway inflammatory diseases; as well as linking the different viral infection pathogenesis to elucidate other potential ways the infection can exacerbate the disease. The review will serve to provide further understanding of viral induced exacerbation to identify potential pathways and pathogenesis mechanisms that may be targeted as supplementary care for management and prevention of exacerbation. Such an approach may be clinically significant due to the current scarcity of antiviral drugs for the management of viral-induced exacerbations. This will improve the quality of life of patients with chronic airway inflammatory diseases.
Once the link between viral infection and acute exacerbations of chronic airway inflammatory disease was established, there have been many reports on the mechanisms underlying the exacerbation induced by respiratory viral infection. Upon infecting the host, viruses evoke an inflammatory response as a means of counteracting the infection. Generally, infected airway epithelial cells release type I (IFNα/β) and type III (IFNλ) interferons, cytokines and chemokines such as IL-6, IL-8, IL-12, RANTES, macrophage inflammatory protein 1α (MIP-1α) and monocyte chemotactic protein 1 (MCP-1) (Wark and Gibson, 2006; Matsukura et al., 2013) . These, in turn, enable infiltration of innate immune cells and of professional antigen presenting cells (APCs) that will then in turn release specific mediators to facilitate viral targeting and clearance, including type II interferon (IFNγ), IL-2, IL-4, IL-5, IL-9, and IL-12 (Wark and Gibson, 2006; Singh et al., 2010; Braciale et al., 2012) . These factors heighten local inflammation and the infiltration of granulocytes, T-cells and B-cells (Wark and Gibson, 2006; Braciale et al., 2012) . The increased inflammation, in turn, worsens the symptoms of airway diseases.
Additionally, in patients with asthma and patients with CRS with nasal polyp (CRSwNP), viral infections such as RV and RSV promote a Type 2-biased immune response (Becker, 2006; Jackson et al., 2014; Jurak et al., 2018) . This amplifies the basal type 2 inflammation resulting in a greater release of IL-4, IL-5, IL-13, RANTES and eotaxin and a further increase in eosinophilia, a key pathological driver of asthma and CRSwNP (Wark and Gibson, 2006; Singh et al., 2010; Chung et al., 2015; Dunican and Fahy, 2015) . Increased eosinophilia, in turn, worsens the classical symptoms of disease and may further lead to life-threatening conditions due to breathing difficulties. On the other hand, patients with COPD and patients with CRS without nasal polyp (CRSsNP) are more neutrophilic in nature due to the expression of neutrophil chemoattractants such as CXCL9, CXCL10, and CXCL11 (Cukic et al., 2012; Brightling and Greening, 2019) . The pathology of these airway diseases is characterized by airway remodeling due to the presence of remodeling factors such as matrix metalloproteinases (MMPs) released from infiltrating neutrophils (Linden et al., 2019) . Viral infections in such conditions will then cause increase neutrophilic activation; worsening the symptoms and airway remodeling in the airway thereby exacerbating COPD, CRSsNP and even CRSwNP in certain cases (Wang et al., 2009; Tacon et al., 2010; Linden et al., 2019) .
An epithelial-centric alarmin pathway around IL-25, IL-33 and thymic stromal lymphopoietin (TSLP), and their interaction with group 2 innate lymphoid cells (ILC2) has also recently been identified (Nagarkar et al., 2012; Hong et al., 2018; Allinne et al., 2019) . IL-25, IL-33 and TSLP are type 2 inflammatory cytokines expressed by the epithelial cells upon injury to the epithelial barrier (Gabryelska et al., 2019; Roan et al., 2019) . ILC2s are a group of lymphoid cells lacking both B and T cell receptors but play a crucial role in secreting type 2 cytokines to perpetuate type 2 inflammation when activated (Scanlon and McKenzie, 2012; Li and Hendriks, 2013) . In the event of viral infection, cell death and injury to the epithelial barrier will also induce the expression of IL-25, IL-33 and TSLP, with heighten expression in an inflamed airway (Allakhverdi et al., 2007; Goldsmith et al., 2012; Byers et al., 2013; Shaw et al., 2013; Beale et al., 2014; Jackson et al., 2014; Uller and Persson, 2018; Ravanetti et al., 2019) . These 3 cytokines then work in concert to activate ILC2s to further secrete type 2 cytokines IL-4, IL-5, and IL-13 which further aggravate the type 2 inflammation in the airway causing acute exacerbation (Camelo et al., 2017) . In the case of COPD, increased ILC2 activation, which retain the capability of differentiating to ILC1, may also further augment the neutrophilic response and further aggravate the exacerbation (Silver et al., 2016) . Interestingly, these factors are not released to any great extent and do not activate an ILC2 response during viral infection in healthy individuals (Yan et al., 2016; Tan et al., 2018a) ; despite augmenting a type 2 exacerbation in chronically inflamed airways (Jurak et al., 2018) . These classical mechanisms of viral induced acute exacerbations are summarized in Figure 1 .
As integration of the virology, microbiology and immunology of viral infection becomes more interlinked, additional factors and FIGURE 1 | Current understanding of viral induced exacerbation of chronic airway inflammatory diseases. Upon virus infection in the airway, antiviral state will be activated to clear the invading pathogen from the airway. Immune response and injury factors released from the infected epithelium normally would induce a rapid type 1 immunity that facilitates viral clearance. However, in the inflamed airway, the cytokines and chemokines released instead augmented the inflammation present in the chronically inflamed airway, strengthening the neutrophilic infiltration in COPD airway, and eosinophilic infiltration in the asthmatic airway. The effect is also further compounded by the participation of Th1 and ILC1 cells in the COPD airway; and Th2 and ILC2 cells in the asthmatic airway.
Frontiers in Cell and Developmental Biology | www.frontiersin.org mechanisms have been implicated in acute exacerbations during and after viral infection (Murray et al., 2006) . Murray et al. (2006) has underlined the synergistic effect of viral infection with other sensitizing agents in causing more severe acute exacerbations in the airway. This is especially true when not all exacerbation events occurred during the viral infection but may also occur well after viral clearance (Kim et al., 2008; Stolz et al., 2019) in particular the late onset of a bacterial infection (Singanayagam et al., 2018 (Singanayagam et al., , 2019a . In addition, viruses do not need to directly infect the lower airway to cause an acute exacerbation, as the nasal epithelium remains the primary site of most infections. Moreover, not all viral infections of the airway will lead to acute exacerbations, suggesting a more complex interplay between the virus and upper airway epithelium which synergize with the local airway environment in line with the "united airway" hypothesis (Kurai et al., 2013) . On the other hand, viral infections or their components persist in patients with chronic airway inflammatory disease (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Hence, their presence may further alter the local environment and contribute to current and future exacerbations. Future studies should be performed using metagenomics in addition to PCR analysis to determine the contribution of the microbiome and mycobiome to viral infections. In this review, we highlight recent data regarding viral interactions with the airway epithelium that could also contribute to, or further aggravate, acute exacerbations of chronic airway inflammatory diseases.
Patients with chronic airway inflammatory diseases have impaired or reduced ability of viral clearance (Hammond et al., 2015; McKendry et al., 2016; Akbarshahi et al., 2018; Gill et al., 2018; Wang et al., 2018; Singanayagam et al., 2019b) . Their impairment stems from a type 2-skewed inflammatory response which deprives the airway of important type 1 responsive CD8 cells that are responsible for the complete clearance of virusinfected cells (Becker, 2006; McKendry et al., 2016) . This is especially evident in weak type 1 inflammation-inducing viruses such as RV and RSV (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Additionally, there are also evidence of reduced type I (IFNβ) and III (IFNλ) interferon production due to type 2-skewed inflammation, which contributes to imperfect clearance of the virus resulting in persistence of viral components, or the live virus in the airway epithelium (Contoli et al., 2006; Hwang et al., 2019; Wark, 2019) . Due to the viral components remaining in the airway, antiviral genes such as type I interferons, inflammasome activating factors and cytokines remained activated resulting in prolong airway inflammation (Wood et al., 2011; Essaidi-Laziosi et al., 2018) . These factors enhance granulocyte infiltration thus prolonging the exacerbation symptoms. Such persistent inflammation may also be found within DNA viruses such as AdV, hCMV and HSV, whose infections generally persist longer (Imperiale and Jiang, 2015) , further contributing to chronic activation of inflammation when they infect the airway (Yang et al., 2008; Morimoto et al., 2009; Imperiale and Jiang, 2015; Lan et al., 2016; Tan et al., 2016; Kowalski et al., 2017) . With that note, human papilloma virus (HPV), a DNA virus highly associated with head and neck cancers and respiratory papillomatosis, is also linked with the chronic inflammation that precedes the malignancies (de Visser et al., 2005; Gillison et al., 2012; Bonomi et al., 2014; Fernandes et al., 2015) . Therefore, the role of HPV infection in causing chronic inflammation in the airway and their association to exacerbations of chronic airway inflammatory diseases, which is scarcely explored, should be investigated in the future. Furthermore, viral persistence which lead to continuous expression of antiviral genes may also lead to the development of steroid resistance, which is seen with RV, RSV, and PIV infection (Chi et al., 2011; Ford et al., 2013; Papi et al., 2013) . The use of steroid to suppress the inflammation may also cause the virus to linger longer in the airway due to the lack of antiviral clearance (Kim et al., 2008; Hammond et al., 2015; Hewitt et al., 2016; McKendry et al., 2016; Singanayagam et al., 2019b) . The concomitant development of steroid resistance together with recurring or prolong viral infection thus added considerable burden to the management of acute exacerbation, which should be the future focus of research to resolve the dual complications arising from viral infection.
On the other end of the spectrum, viruses that induce strong type 1 inflammation and cell death such as IFV (Yan et al., 2016; Guibas et al., 2018) and certain CoV (including the recently emerged COVID-19 virus) (Tao et al., 2013; Yue et al., 2018; Zhu et al., 2020) , may not cause prolonged inflammation due to strong induction of antiviral clearance. These infections, however, cause massive damage and cell death to the epithelial barrier, so much so that areas of the epithelium may be completely absent post infection (Yan et al., 2016; Tan et al., 2019) . Factors such as RANTES and CXCL10, which recruit immune cells to induce apoptosis, are strongly induced from IFV infected epithelium (Ampomah et al., 2018; Tan et al., 2019) . Additionally, necroptotic factors such as RIP3 further compounds the cell deaths in IFV infected epithelium . The massive cell death induced may result in worsening of the acute exacerbation due to the release of their cellular content into the airway, further evoking an inflammatory response in the airway (Guibas et al., 2018) . Moreover, the destruction of the epithelial barrier may cause further contact with other pathogens and allergens in the airway which may then prolong exacerbations or results in new exacerbations. Epithelial destruction may also promote further epithelial remodeling during its regeneration as viral infection induces the expression of remodeling genes such as MMPs and growth factors . Infections that cause massive destruction of the epithelium, such as IFV, usually result in severe acute exacerbations with non-classical symptoms of chronic airway inflammatory diseases. Fortunately, annual vaccines are available to prevent IFV infections (Vasileiou et al., 2017; Zheng et al., 2018) ; and it is recommended that patients with chronic airway inflammatory disease receive their annual influenza vaccination as the best means to prevent severe IFV induced exacerbation.
Another mechanism that viral infections may use to drive acute exacerbations is the induction of vasodilation or tight junction opening factors which may increase the rate of infiltration. Infection with a multitude of respiratory viruses causes disruption of tight junctions with the resulting increased rate of viral infiltration. This also increases the chances of allergens coming into contact with airway immune cells. For example, IFV infection was found to induce oncostatin M (OSM) which causes tight junction opening (Pothoven et al., 2015; Tian et al., 2018) . Similarly, RV and RSV infections usually cause tight junction opening which may also increase the infiltration rate of eosinophils and thus worsening of the classical symptoms of chronic airway inflammatory diseases (Sajjan et al., 2008; Kast et al., 2017; Kim et al., 2018) . In addition, the expression of vasodilating factors and fluid homeostatic factors such as angiopoietin-like 4 (ANGPTL4) and bactericidal/permeabilityincreasing fold-containing family member A1 (BPIFA1) are also associated with viral infections and pneumonia development, which may worsen inflammation in the lower airway Akram et al., 2018) . These factors may serve as targets to prevent viral-induced exacerbations during the management of acute exacerbation of chronic airway inflammatory diseases.
Another recent area of interest is the relationship between asthma and COPD exacerbations and their association with the airway microbiome. The development of chronic airway inflammatory diseases is usually linked to specific bacterial species in the microbiome which may thrive in the inflamed airway environment (Diver et al., 2019) . In the event of a viral infection such as RV infection, the effect induced by the virus may destabilize the equilibrium of the microbiome present (Molyneaux et al., 2013; Kloepfer et al., 2014; Kloepfer et al., 2017; Jubinville et al., 2018; van Rijn et al., 2019) . In addition, viral infection may disrupt biofilm colonies in the upper airway (e.g., Streptococcus pneumoniae) microbiome to be release into the lower airway and worsening the inflammation (Marks et al., 2013; Chao et al., 2014) . Moreover, a viral infection may also alter the nutrient profile in the airway through release of previously inaccessible nutrients that will alter bacterial growth (Siegel et al., 2014; Mallia et al., 2018) . Furthermore, the destabilization is further compounded by impaired bacterial immune response, either from direct viral influences, or use of corticosteroids to suppress the exacerbation symptoms (Singanayagam et al., 2018 (Singanayagam et al., , 2019a Wang et al., 2018; Finney et al., 2019) . All these may gradually lead to more far reaching effect when normal flora is replaced with opportunistic pathogens, altering the inflammatory profiles (Teo et al., 2018) . These changes may in turn result in more severe and frequent acute exacerbations due to the interplay between virus and pathogenic bacteria in exacerbating chronic airway inflammatory diseases (Wark et al., 2013; Singanayagam et al., 2018) . To counteract these effects, microbiome-based therapies are in their infancy but have shown efficacy in the treatments of irritable bowel syndrome by restoring the intestinal microbiome (Bakken et al., 2011) . Further research can be done similarly for the airway microbiome to be able to restore the microbiome following disruption by a viral infection.
Viral infections can cause the disruption of mucociliary function, an important component of the epithelial barrier. Ciliary proteins FIGURE 2 | Changes in the upper airway epithelium contributing to viral exacerbation in chronic airway inflammatory diseases. The upper airway epithelium is the primary contact/infection site of most respiratory viruses. Therefore, its infection by respiratory viruses may have far reaching consequences in augmenting and synergizing current and future acute exacerbations. The destruction of epithelial barrier, mucociliary function and cell death of the epithelial cells serves to increase contact between environmental triggers with the lower airway and resident immune cells. The opening of tight junction increasing the leakiness further augments the inflammation and exacerbations. In addition, viral infections are usually accompanied with oxidative stress which will further increase the local inflammation in the airway. The dysregulation of inflammation can be further compounded by modulation of miRNAs and epigenetic modification such as DNA methylation and histone modifications that promote dysregulation in inflammation. Finally, the change in the local airway environment and inflammation promotes growth of pathogenic bacteria that may replace the airway microbiome. Furthermore, the inflammatory environment may also disperse upper airway commensals into the lower airway, further causing inflammation and alteration of the lower airway environment, resulting in prolong exacerbation episodes following viral infection.
Viral specific trait contributing to exacerbation mechanism (with literature evidence) Oxidative stress ROS production (RV, RSV, IFV, HSV)
As RV, RSV, and IFV were the most frequently studied viruses in chronic airway inflammatory diseases, most of the viruses listed are predominantly these viruses. However, the mechanisms stated here may also be applicable to other viruses but may not be listed as they were not implicated in the context of chronic airway inflammatory diseases exacerbation (see text for abbreviations).
that aid in the proper function of the motile cilia in the airways are aberrantly expressed in ciliated airway epithelial cells which are the major target for RV infection (Griggs et al., 2017) . Such form of secondary cilia dyskinesia appears to be present with chronic inflammations in the airway, but the exact mechanisms are still unknown (Peng et al., , 2019 Qiu et al., 2018) . Nevertheless, it was found that in viral infection such as IFV, there can be a change in the metabolism of the cells as well as alteration in the ciliary gene expression, mostly in the form of down-regulation of the genes such as dynein axonemal heavy chain 5 (DNAH5) and multiciliate differentiation And DNA synthesis associated cell cycle protein (MCIDAS) (Tan et al., 2018b . The recently emerged Wuhan CoV was also found to reduce ciliary beating in infected airway epithelial cell model (Zhu et al., 2020) . Furthermore, viral infections such as RSV was shown to directly destroy the cilia of the ciliated cells and almost all respiratory viruses infect the ciliated cells (Jumat et al., 2015; Yan et al., 2016; Tan et al., 2018a) . In addition, mucus overproduction may also disrupt the equilibrium of the mucociliary function following viral infection, resulting in symptoms of acute exacerbation (Zhu et al., 2009) . Hence, the disruption of the ciliary movement during viral infection may cause more foreign material and allergen to enter the airway, aggravating the symptoms of acute exacerbation and making it more difficult to manage. The mechanism of the occurrence of secondary cilia dyskinesia can also therefore be explored as a means to limit the effects of viral induced acute exacerbation.
MicroRNAs (miRNAs) are short non-coding RNAs involved in post-transcriptional modulation of biological processes, and implicated in a number of diseases (Tan et al., 2014) . miRNAs are found to be induced by viral infections and may play a role in the modulation of antiviral responses and inflammation (Gutierrez et al., 2016; Deng et al., 2017; Feng et al., 2018) . In the case of chronic airway inflammatory diseases, circulating miRNA changes were found to be linked to exacerbation of the diseases (Wardzynska et al., 2020) . Therefore, it is likely that such miRNA changes originated from the infected epithelium and responding immune cells, which may serve to further dysregulate airway inflammation leading to exacerbations. Both IFV and RSV infections has been shown to increase miR-21 and augmented inflammation in experimental murine asthma models, which is reversed with a combination treatment of anti-miR-21 and corticosteroids (Kim et al., 2017) . IFV infection is also shown to increase miR-125a and b, and miR-132 in COPD epithelium which inhibits A20 and MAVS; and p300 and IRF3, respectively, resulting in increased susceptibility to viral infections (Hsu et al., 2016 (Hsu et al., , 2017 . Conversely, miR-22 was shown to be suppressed in asthmatic epithelium in IFV infection which lead to aberrant epithelial response, contributing to exacerbations (Moheimani et al., 2018) . Other than these direct evidence of miRNA changes in contributing to exacerbations, an increased number of miRNAs and other non-coding RNAs responsible for immune modulation are found to be altered following viral infections (Globinska et al., 2014; Feng et al., 2018; Hasegawa et al., 2018) . Hence non-coding RNAs also presents as targets to modulate viral induced airway changes as a means of managing exacerbation of chronic airway inflammatory diseases. Other than miRNA modulation, other epigenetic modification such as DNA methylation may also play a role in exacerbation of chronic airway inflammatory diseases. Recent epigenetic studies have indicated the association of epigenetic modification and chronic airway inflammatory diseases, and that the nasal methylome was shown to be a sensitive marker for airway inflammatory changes (Cardenas et al., 2019; Gomez, 2019) . At the same time, it was also shown that viral infections such as RV and RSV alters DNA methylation and histone modifications in the airway epithelium which may alter inflammatory responses, driving chronic airway inflammatory diseases and exacerbations (McErlean et al., 2014; Pech et al., 2018; Caixia et al., 2019) . In addition, Spalluto et al. (2017) also showed that antiviral factors such as IFNγ epigenetically modifies the viral resistance of epithelial cells. Hence, this may indicate that infections such as RV and RSV that weakly induce antiviral responses may result in an altered inflammatory state contributing to further viral persistence and exacerbation of chronic airway inflammatory diseases (Spalluto et al., 2017) .
Finally, viral infection can result in enhanced production of reactive oxygen species (ROS), oxidative stress and mitochondrial dysfunction in the airway epithelium (Kim et al., 2018; Mishra et al., 2018; Wang et al., 2018) . The airway epithelium of patients with chronic airway inflammatory diseases are usually under a state of constant oxidative stress which sustains the inflammation in the airway (Barnes, 2017; van der Vliet et al., 2018) . Viral infections of the respiratory epithelium by viruses such as IFV, RV, RSV and HSV may trigger the further production of ROS as an antiviral mechanism Aizawa et al., 2018; Wang et al., 2018) . Moreover, infiltrating cells in response to the infection such as neutrophils will also trigger respiratory burst as a means of increasing the ROS in the infected region. The increased ROS and oxidative stress in the local environment may serve as a trigger to promote inflammation thereby aggravating the inflammation in the airway (Tiwari et al., 2002) . A summary of potential exacerbation mechanisms and the associated viruses is shown in Figure 2 and Table 1 .
While the mechanisms underlying the development and acute exacerbation of chronic airway inflammatory disease is extensively studied for ways to manage and control the disease, a viral infection does more than just causing an acute exacerbation in these patients. A viral-induced acute exacerbation not only induced and worsens the symptoms of the disease, but also may alter the management of the disease or confer resistance toward treatments that worked before. Hence, appreciation of the mechanisms of viral-induced acute exacerbations is of clinical significance to devise strategies to correct viral induce changes that may worsen chronic airway inflammatory disease symptoms. Further studies in natural exacerbations and in viral-challenge models using RNA-sequencing (RNA-seq) or single cell RNA-seq on a range of time-points may provide important information regarding viral pathogenesis and changes induced within the airway of chronic airway inflammatory disease patients to identify novel targets and pathway for improved management of the disease. Subsequent analysis of functions may use epithelial cell models such as the air-liquid interface, in vitro airway epithelial model that has been adapted to studying viral infection and the changes it induced in the airway (Yan et al., 2016; Boda et al., 2018; Tan et al., 2018a) . Animal-based diseased models have also been developed to identify systemic mechanisms of acute exacerbation (Shin, 2016; Gubernatorova et al., 2019; Tanner and Single, 2019) . Furthermore, the humanized mouse model that possess human immune cells may also serves to unravel the immune profile of a viral infection in healthy and diseased condition (Ito et al., 2019; Li and Di Santo, 2019) . For milder viruses, controlled in vivo human infections can be performed for the best mode of verification of the associations of the virus with the proposed mechanism of viral induced acute exacerbations . With the advent of suitable diseased models, the verification of the mechanisms will then provide the necessary continuation of improving the management of viral induced acute exacerbations.
In conclusion, viral-induced acute exacerbation of chronic airway inflammatory disease is a significant health and economic burden that needs to be addressed urgently. In view of the scarcity of antiviral-based preventative measures available for only a few viruses and vaccines that are only available for IFV infections, more alternative measures should be explored to improve the management of the disease. Alternative measures targeting novel viral-induced acute exacerbation mechanisms, especially in the upper airway, can serve as supplementary treatments of the currently available management strategies to augment their efficacy. New models including primary human bronchial or nasal epithelial cell cultures, organoids or precision cut lung slices from patients with airways disease rather than healthy subjects can be utilized to define exacerbation mechanisms. These mechanisms can then be validated in small clinical trials in patients with asthma or COPD. Having multiple means of treatment may also reduce the problems that arise from resistance development toward a specific treatment. | What can be used unravel the immune profile of a viral infection in healthy and diseased condition? | false | 4,031 | {
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2,565 | Interferon-Induced Transmembrane Protein 3 Inhibits Hantaan Virus Infection, and Its Single Nucleotide Polymorphism rs12252 Influences the Severity of Hemorrhagic Fever with Renal Syndrome
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5206578/
SHA: 4328e18bdf9b52875c87f3f5ddb1911636a192d2
Authors: Xu-yang, Zheng; Pei-yu, Bian; Chuan-tao, Ye; Wei, Ye; Hong-wei, Ma; Kang, Tang; Chun-mei, Zhang; Ying-feng, Lei; Xin, Wei; Ping-zhong, Wang; Chang-xing, Huang; Xue-fan, Bai; Ying, Zhang; Zhan-sheng, Jia
Date: 2017-01-03
DOI: 10.3389/fimmu.2016.00535
License: cc-by
Abstract: Hantaan virus (HTNV) causes hemorrhagic fever with renal syndrome (HFRS). Previous studies have identified interferon-induced transmembrane proteins (IFITMs) as an interferon-stimulated gene family. However, the role of IFITMs in HTNV infection is unclear. In this study, we observed that IFITM3 single nucleotide polymorphisms (SNP) rs12252 C allele and CC genotype associated with the disease severity and HTNV load in the plasma of HFRS patients. In vitro experiments showed that the truncated protein produced by the rs12252 C allele exhibited an impaired anti-HTNV activity. We also proved that IFITM3 was able to inhibit HTNV infection in both HUVEC and A549 cells by overexpression and RNAi assays, likely via a mechanism of inhibiting virus entry demonstrated by binding and entry assay. Localization of IFITM3 in late endosomes was also observed. In addition, we demonstrated that the transcription of IFITM3 is negatively regulated by an lncRNA negative regulator of interferon response (NRIR). Taken together, we conclude that IFITM3, negatively regulated by NRIR, inhibits HTNV infection, and its SNP rs12252 correlates with the plasma HTNV load and the disease severity of patients with HFRS.
Text: associates with the severity of disease, indicating the importance of viremia in the pathogenesis of HFRS (2) . Therefore, further studies of host factors limiting HTNV infection and influencing antiviral response as well as disease progression are clinically significant and timely. The human family of interferon-induced transmembrane proteins (IFITMs) was discovered 25 years ago to consist of interferon-stimulated genes (ISGs) (3) . This family includes five members, namely, IFITM1, 2, 3, 5, and 10, among which IFITM1, 2, and 3 possess antiviral activity (4) . Different IFITM proteins have different antiviral spectrum (5) . For example, IFITM3 has been shown to prevent influenza virus infection in vitro and in mice (6, 7) , and it also inhibits multiple viruses, including filoviruses, rhabdoviruses, flaviviruses, and even Ebola and Zika virus (7) (8) (9) (10) (11) . The antiviral mechanism of IFITM3 is thought to be the restriction of viral entry into cells (4, 12) . Single nucleotide polymorphisms (SNPs) are single nucleotide variations in a genetic sequence that occur at an appreciable frequency in the population. Several SNPs has been identified in IFITM3, among which the rs12252 site with C allele results in a N-terminal truncation of IFITM3 protein, leading to impaired inhibition of influenza virus in vitro (13, 14) . Notably, the frequencies of rs12252 C allele and CC genotype correlate with disease severity in patients infected with influenza virus (13, 15) . HTNV has been shown to induce a type I interferon response (though in later time postinfection) (16, 17) . While overexpression of IFITM1, 2, and 3 in Vero E6 cells has been reported to inhibit HTNV infection (18) , however, the effect of IFITMs on HTNV infection in human cell lines and its role in HFRS still remain unknown.
LncRNA comprises a group of non-coding RNAs longer than 200 nt that function as gene regulators. Some lncRNAs have been shown to play a role in innate immunity (19) . Among them, negative regulator of interferon response (NRIR) (lncRNA NRIR, also known as lncRNA-CMPK2) is a non-coding ISG that negatively regulates IFITM1 and Mx1 expression in HCV infection (20) . Notably, IFITM3 is largely homologous to IFITM1, but the role of NRIR in the regulation of IFITM3 in HTNV infection remains unclear.
In the present study, we investigate the effect of IFTTM3 on the replication of HTNV and its role in the development of HFRS in humans. We provide primary evidence suggesting that IFITM3, regulated by NRIR, can inhibit HTNV infection and its SNP rs12252 correlates with the disease severity and viral load in patients with HFRS. This study expands our understanding of the antiviral activity of IFITM3 and enriches our knowledge of innate immune responses to HTNV infection.
This study was conducted in accordance with the recommendations of the biomedical research guidelines involving human participants established by the National Health and Family Planning Commission of China. The Institutional Ethics Committee of Tangdu Hospital approved this study. All subjects gave written informed consent in accordance with the Declaration of Helsinki. Before inclusion, all participants were informed of the study objectives and signed the consent form before blood samples and medical records were obtained.
Sixty-nine HFRS patients admitted into the Department of Infectious Diseases, Tangdu Hospital between October 2014 and March 2016 were enrolled in this study. All patients were Han Chinese. The diagnosis of HFRS was made based on typical symptoms and signs as well as positive IgM and IgG antibodies against HTNV in the serum assessed by enzyme linked immunosorbent assay (ELISA) in our department. The classification of HFRS severity and the exclusion criteria were described as follows (21) : white blood cells (WBC), platelets (PLT), blood urea nitrogen (BUN), serum creatinine (Scr), and heteromorphic lymphocytes that were tested by the Department of Clinical Laboratory (shown in Table 1 ).
According to clinical symptoms and signs, such as fever, effusion, hemorrhage, edema, and renal function, the severity of HFRS can be classified as previously described (21): (1) mild patients were identified with mild renal failure without an obvious oliguric stage; (2) moderate patients were those with obvious symptoms of uremia, effusion (bulbar conjunctiva), hemorrhage (skin and mucous membrane), and renal failure with a typical oliguric stage; (3) severe patients had severe uremia, effusion (bulbar conjunctiva and either peritoneum or pleura), hemorrhage (skin and mucous membrane), and renal failure with oliguria (urine output, 50-500 ml/day) for ≤5 days or anuria (urine output, <50 ml/day) for ≤2 days; and (4) critical patients exhibited ≥1 of the following signs during the illness: refractory shock, visceral hemorrhage, heart failure, pulmonary edema, brain edema, severe secondary infection, and severe renal failure with oliguria (urine output, 50-500 ml/day) for >5 days, anuria (urine output, <50 ml/day) for >2 days, or a BUN level of >42.84 mmol/l. Due to the sample quantity required for SNP typing, the mild and moderate patients were assessed together in the mild group, and we combined severe and critical patients as severe group.
The exclusion criteria for this study were patients with: (1) any other kidney disease, (2) diabetes mellitus, (3) autoimmune disease, (4) hematological disease, (5) cardiovascular disease, (6) viral hepatitis (types A, B, C, D, or E), or (7) any other liver disease. In addition, no patients received corticosteroids or other immunomodulatory drugs during the study period (21) .
Genomic DNA was extracted from the peripheral blood of patients using the PureGene DNA Isolation kit (Gentra Systems, Minneapolis, MN, USA). The region encompassing the human IFITM3 rs12252 were amplified by PCR (forward primer, 5′-GGAAACTGTTGAGAAACCGAA-3′ and reverse primer, 5′-CATACGCACCTTCACGGAGT-3′). The PCR products were purified and sequenced using an Applied Biosystems 3730xl DNA Analyzer (Thermo Scientific, Waltham, MA, USA). The allele frequencies and genotypes of healthy Han Chinese and other groups were obtained from the 1,000 genomes project (http:// www.1000genomes.org).
The HTNV load in plasma samples (collected during the acute phase) from 24 age-and sex-matched HFRS patients with different genotypes were measured using previously reported methods (2) . Briefly, viral RNA was extracted from the plasma of HFRS patients using Purelink Viral RNA/DNA Kits (Invitrogen, Carlsbad, CA, USA). The SuperScript III Platinum One-Step Quantitative RT-PCR System kit (Invitrogen, Carlsbad, CA, USA) was employed for the real-time RT-PCR assay. The primers and probe (provided by Sangon Biotech, Shanghai, China) were as follows: forward, 5′-TACAGAGGGAAATCAATGCC-3′, reverse, 5′-TGTTCAACTCATCTGGATCCTT-3′, and probe, 5′-(FAM) ATCCCTCACCTTCTGCCTGGCTATC (TAMRA)-3′. The synthetic S segment of the HTNV standard strain 76-118 RNA transcript was used as the quantitative calibrator. The external standard was the culture supernatant of Vero E6 cells infected with HTNV 76-118, which was quantified using synthetic quantitative calibrators. For each experiment, one aliquot of calibrated 76-118 standard was extracted in parallel with the clinical samples and serially 10-fold diluted with concentrations ranging from 10.56 to 2.56 log10 copies/ml. PCR was performed using an iQ5 Cycler (Bio-Rad, Hercules, CA, USA) with following conditions: 42°C for 15 min, 95°C for 2 min, and 50 cycles of 15 s at 95°C, 30 s at 53°C, and 30 s at 72°C. Fluorescence was read during the 72°C step of the final segment of every cycling program.
HUVEC cells (ScienCell Research Laboratories, Carlsbad, CA, USA) were grown in ECM BulletKit (ScienCell Research Laboratories, Carlsbad, CA, USA) in a 5% CO2 incubator. A549 cells (ATCC Cat# CRM-CCL-185, RRID:CVCL_0023) were grown in our laboratory in DMEM with 10% FBS (Thermo Scientific, Waltham, MA, USA) in a 5% CO2 incubator. Cells were used within passage 10 after primary culture. HTNV strain 76-118 was cultured in Vero E6 cells (ATCC Cat# CRL-1586, RRID:CVCL_0574) in our laboratory and titrated using an immunofluorescence staining assay for HTNV nucleocapsid protein (NP) as previously described (22) . The TCID50 was 10 5 /ml, which was calculated using the Reed-Muench method.
The recombinant human IFN-α2a was obtained from PBL Interferon Source (Piscataway, NJ, USA) and dissolved in the buffer provided by the manufacturer (composition not disclosed). HUVEC and A549 cells were infected by incubation with HTNV as indicated moi at 37°C for 60 mins. Subsequently, the virus solution was removed and fresh medium added to the cell culture.
Cells were transfected with lentiviral vectors of c-myc-tagged IFITM1, IFITM2, IFITM3, and IFITM3 NΔ21 (purchased from GENECHEM, Shanghai, China) at a moi of 10. Puromycin (2 μg/ ml for HUVEC and 6 μg/ml for A549 cells) was used to create cell lines stably expressing IFITMs. Cells were transfected with control (scrambled) short interfering RNA (siRNA), IFITM1 siRNA, IFITM2 siRNA, or IFITM3 siRNA (10 nM) using Lipofectamine 3000 transfection reagent (Invitrogen, Carlsbad, CA, USA). SiRNAs were purchased from Origene (Rockville, MD, USA), and the sequences were not disclosed.
Total RNA was extracted using TRIzol reagent (Invitrogen, Carlsbad, CA, USA), and cDNA was synthesized using the K1622 kit (Thermo Scientific, Waltham, MA, USA). Quantitative realtime PCR (qPCR) was performed using SYBR Premix Ex Taq II (Takara Biotechnology Co., Dalian, China) with a Bio-Rad iQ5 cycler (Bio-Rad, Hercules, CA, USA). β-actin was used as the reference gene. The primers (Sangon Biotech, Shanghai, China) were as follows: IFITM1 (forward, 5′-ACTCCGTGAAGTCTAGGGACA-3′ and reverse, 5′-TGTCACAGAGCCGAATACCAG-3′); IFITM2 (forward, 5′-ATCCCGGTAACCCGATCAC-3′ and reverse, 5′-CTTCCTGTCCCTAGACTTCAC-3′); IFITM3 (forward, 5′-GGTCTTCGCTGGACACCAT-3′ and reverse, 5′-TGTCCCTAGACTTCACGGAGTA-3′); IFITM3 pre-mRNA (forward, 5′-CATAGCACGCGGCTCT CAG-3′ and reverse, 5′-CGTCGCCAACCATCTTCCTG-3′); HTNV S segment (forward, 5′-GCCTGGAGACCATCTGA AAG-3′ and reverse, 5′-AGTATCGGGACGACAAAGGA-3′); β-actin (forward, 5′-GCTACGTCGCCCTGGACTTC-3′ and reverse, 5′-GTCATAGTCCGCCTAGAAGC-3′); NRIR (forward, 5′-ATGGTTTTCTGGTGCCTTG-3′ and reverse, 5′-GGAGGTTAGAGGTGTCTGCTG-3′); NRAV (forward, 5′-TCACTACTGCCCCAGGATCA-3′ and reverse, 5′-GGTGGTCACAGGACTCATGG-3′).
For detection of miR-130a, cDNA was synthesized using the TaqMan microRNA reverse transcription kit (Invitrogen, Carlsbad, CA, USA) with a specific primer in gene-specific TaqMan assay kit (000454, Invitrogen, Carlsbad, CA, USA). MiR-130a level was determined using the gene-specific TaqMan assay kit (000454, Invitrogen, Carlsbad, CA, USA). U6 (001973, Invitrogen, Carlsbad, CA, USA) was used as an endogenous control (23) . Because the pre-mRNA levels can represent the initial transcription rate (24) , the primers used to detect the pre-mRNA of IFITM3 were designed targeting the intron of IFITM3 as previously described (25) . IFITM3 has two exons and one intron. For qPCR of IFITM3 pre-mRNA, the forward primers were positioned in the intron, and the reverse primer was positioned at the beginning of the second exon. For qPCR of IFITM3 mRNA, the forward primers were positioned in the first exon, and the reverse primer was positioned at the beginning of the second exon (24) . Because the basal expression of IFITM3 is low in A549 cells, we detected IFITM3 mRNA and pre-mRNA in A549 cells following IFN-α2a treatment (20 IU/ml for 12 h) after the overexpression of NRIR.
Cell lysates were prepared using Radio Immunoprecipitation Assay (RIPA) buffer (Sigma-Aldrich, St. Louis, MO, USA). Equal amounts of protein (20 μg protein/lane) were electrophoresed on a 10%-SDS-polyacrylamide gel and electrophoretically transferred to a polyvinylidene difluoride membrane (Millipore, Billerica, MA, USA). After blocking with 5% bovine serum albumin in Trisbuffered saline at room temperature for 1 h, the membranes were incubated with antibodies against IFITM1 (Proteintech Group Cat# 60074-1-Ig Lot# RRID:AB_2233405), IFITM2, IFITM3 (Proteintech Group Cat# 66081-1-Ig Lot# RRID:AB_11182821), and β-actin (Proteintech, Wuhan, Hubei, China) or HTNV NP (provided by the Department of Microbiology, The Fourth Military Medical University) overnight at 4°C. The membranes were then washed and incubated with HRP-conjugated IgG antibody (Cell Signaling Technology, Danvers, MA, USA) for 1 h at room temperature. The blots were developed using an enhanced chemiluminescence detection kit (Millipore, Billerica, MA, USA) and visualized using X-ray film. The blot densities were analyzed using the Quantity One software (Bio-Rad, Hercules, CA, USA). In addition, the RIPA buffer contains 50mM Tris (pH = 7.4), 150 mM NaCl, 1% Triton X-100, 1% sodium deoxycholate, 0.1% SDS. Protease inhibitor cocktail (Roche, Basel, Switzerland) was added before use.
The cells were cultured on glass coverslips (Millipore, Billerica, MA, USA) until they were semi-confluence and then incubated with HTNV for 60 min (moi = 1). At the indicated times post-HTNV infection, the cells were fixed with 4% PFA, incubated with 0.3% Triton X-100 (Sigma-Aldrich, St. Louis, MO, USA), and blocked with 5% BSA for 1 h. Following incubation with a mouse monoclonal antibody against c-myc-tag (Sigma-Aldrich, St. Louis, MO, USA, Sigma-Aldrich Cat# M5546), IFITM3, lysosome-associated membrane glycoprotein 1 (LAMP1, Cell Signaling Technology, Danvers, MA, USA), or HTNV NP at 37°C for 2 h, the cells were washed and incubated with anti-rabbit Ig conjugated to Alexa 555 and anti-mouse Ig conjugated to Alexa 488 (Abcam, Cambridge, MA, USA) secondary antibodies at room temperature for 1 h. The nuclei were counterstained with DAPI. An Olympus BX51 fluorescence microscope system and FV1000 confocal microscopy system (Olympus, Tokyo, Japan) were used to capture the images. hTnV binding and entry assay Cells transduced with IFITM3 or the empty vector were detached and washed extensively with cold PBS. The cells and HTNV were pre-chilled on ice for 30 min, mixed at a moi of 1 and incubated at 4°C for 1 h with rotation. Part of cells were washed extensively with ice-cold PBS and harvested for binding assay. Another part of cells were switched to 37°C for 2 h to allow HTNV entry. The HTNV that remained on the cell surface was removed by treatment with proteinase K (0.1 mg/ml, Thermo Scientific, Waltham, MA, USA). To achieve direct entry of HTNV into cells by virus-plasma membrane fusion as a positive control, cells were pre-chilled on ice for 10 min with 20 mM NH4Cl. Adsorption of HTNV (moi = 1) was performed at 4°C for 1 h. The cells were then washed, and fusion of the virus with the plasma membrane was triggered by incubation in low pH medium (20 mM sodium succinate, pH = 5.5) for 10 min at 37°C. Infection was followed by incubation for 2 h at 37°C in the presence of 20 mM NH4Cl (26) . qPCR analysis of the HTNV S segment was conducted to evaluate the influence of IFITMs on HTNV cell adhesion and HTNV entry.
All data were expressed as the mean ± SEM. Statistical analyses were performed using GraphPad Prism 5 (GraphPad Software, La Jolla, CA, USA). For association analysis of the rs12252 allele and genotype, Fisher's exact test was used. Independent samples t-tests were used for normally distributed data. Differences among groups were determined by one-way analysis of variance (ANOVA) with repeated measures, followed by Bonferroni's post hoc test. P < 0.05 was considered statistically significant.
The iFiTM3 snP rs12252 c allele and cc genotype associated with severe hFrs Disease and a higher Plasma hTnV load
To determine the clinical significance of IFITM3 SNP in HTNV infection, the relationship between rs12252 SNP and the severity of HFRS in 69 patients were examined. We sequenced 300 bp of the IFITM3 locus encompassing SNP rs12252 in all enrolled patients. Then, we stratified these patients into mild and severe, based on the clinical assessment as described in Section "Material and Methods. " We found a significantly higher frequency of the C allele among severe HFRS patients compared with the healthy Han Chinese in the 1,000 genomes sequence database (68.29 vs. 52.16%, P = 0.0076). The frequency of rs12252 C in severe patients was also higher than those mild patients (68.29 vs. 46.43%, P = 0.013, Figures 1A,B; Table 2 ). These data suggest that harboring rs12252 C allele increases the risk of suffering severe disease in HTNV-infected individuals, with an odds ratio (95% CI) of 2.124 (1.067-4.230). For genotypes, 43.90% of the severe patients carried the CC genotype, a significantly higher frequency than the control Han Chinese per 1,000 genomes sequence database (26.92% CC genotype, P = 0.03) as well as mildly infected patients (14.29%, P = 0.02, Figures 1A,B ; Table 2 ). However, mildly ill individuals did not exhibit a Fisher's exact test was used to test the association between rs12252 allele/genotype and HFRS severity. (c) The plasma HTNV load in CC genotype patients and CT/TT genotype patients, tested by qRCR analysis. Each symbol represents one individual patient. Independent samples t-test was used to test the difference of HTNV load between groups. *P < 0.05, **P < 0.01. significantly different genotype frequencies compared with the Han Chinese population. In addition, we also found that patients with CC genotype had higher plasma viral load in acute phase ( Figure 1C) . These results support the notion that the normal function of IFITM3 plays a critical role in the immune response to HTNV infection in vivo, which has a substantial influence on the clinical manifestation of HFRS.
Previous studies reveal that the truncated IFITM3 protein produced by SNP rs12252 C allele (Figure 2A , the missing part stands for the truncated 21 amino acids from N-terminal of IFITM3, the intramembrane helix, and transmembrane helix was presented as boxes) leads to an impaired anti-influenza activity (14) . To test the functional significance of this polymorphism in HTNV infection, we transfected the majority T or minority C variant IFITM3 alleles that produce full-length or N-terminally truncated (NΔ21) proteins (Figure 2A ) with c-myc-tag to HUVEC and A549 cell using lentivirus vectors ( Figure 2B) . Then, we challenged the cells with HTNV at moi = 1 for 24 h and found that cells with the minority C variant were more susceptible to HTNV infection with higher expression of HTNV S segment ( Figure 2C ) and more positive of HTNV NP ( Figure S3 in Supplementary Material). Indeed, compared with the mock (empty vector)-infected control, the NΔ21 protein almost lost the ability to inhibit HTNV infection in both HUVEC and A549 cells (Figures 2C,D ; Figure S3 in Supplementary Material).
To determine the role of HTNV infection in inducing IFITMs, qPCR as well as Western blot of IFITMs were conducted in HUVEC and A549 cells (Figures 3A,B ; Figure S1 in Supplementary Material). While we observed only a moderate upregulation of IFITM1, 2, and 3 mRNA and protein in HUVECs after more than 24 h postinfection; IFITM1, 2, and 3 mRNA, however, were only transiently upregulated in A549 cells and caused no significant change in protein level.
We knocked down the IFITM1, 2, and 3 expression by transfection of their siRNAs individually. The effect of siRNAs on the expression of target IFITMs was tested by qPCR in HUVECs ( Figure S2 in Supplementary Material), and the effect of the best oligo against each IFITMs (IFITM1C, IFITM2A, IFITM3B) was tested by Western blot in A549 ( Figure 4A ) and HUVEC cells ( Figure 4B) . To assess the role of IFITMs in anti-HTNV effect of IFN-α2a, IFITM1, 2, and 3 were knocked down respectively by transfecting the above-tested oligoes for 12 h, followed by IFN-α2a treatment (20 IU/ml for another 12 h). The cells were then challenged with HTNV (moi = 1) for 24 h. The HTNV S segment and NP levels were significantly suppressed in both HUVEC and A549 cells in response to IFN-α2a treatment.
Notably, knockdown of IFITM3 significantly restored the levels of HTNV S segment and NP in HUVEC and A549 cells. Knockdown of IFITM1 also partially restored the HTNV level in A549 cells (Figures 4C,D) . These results demonstrate that
To assess the anti-HTNV effects of IFITMs, we tested the effect of overexpressed IFITM1, 2, and 3 on HTNV infection. c-myc-tagged IFITM1, 2, and 3 were expressed in both HUVEC and A549 cells (Figure 5A) , and the cells were then challenged with HTNV (moi = 1) for 24 h. The HTNV S segment and NP levels were suppressed by IFITM3 overexpression in HUVEC cells (Figures 5B-D) . They were also suppressed by expressing IFITM1 and IFITM3 in A549 cells (Figures 5B-D) .
The inhibitory effect of IFITM3 was further confirmed by immunofluorescence analysis of HTNV NP ( Figure S3 in Supplementary Material). These results were in accordance with the above-described RNAi results. To determine whether IFITM3 inhibited HTNV binding or entry, HUVEC and A549 cells were incubated with HTNV (moi = 1) at 4°C for 1 h, unbound virus was washed away, and HTNV RNA collected at this time point represents HTNV bound to the cell surface. After virus binding, the cells were shifted to 37°C for 2 h to allow HTNV internalization, and HTNV RNA collected at this time point represents cell-internalized virus. As a positive control for inhibition of virus entry, we incubated a parallel group of cells with HTNV at pH = 5.5 as described in Section "Materials and Methods." Expression of IFITM3 did not affect HTNV binding ( Figure 6A ) but significantly suppressed HTNV entry in both HUVEC and A549 cells (Figure 6B ). iFiTM3 Was Partially localized to laMP1 + late endosomes in the host cells
To elucidate the mechanism of IFITM3 function, we investigated the subcellular localization of IFTIM3 in the host cells. IFITM3 was found partially localized to LAMP1 + late endosomes in HUVECs analyzed by confocal microscopy (Figure 6C) . The co-localization of IFITM3 and LAMP1 + late endosomes had also been found in A549 cells (27) . Because the transfer into LAMP1 + late endosomes is a necessary step for HTNV entry (28) , this result provides an evidence for the anti-HTNV mechanism of IFITM3.
LncRNA-and microRNA-mediated regulation of IFITM3 has been reported in several studies. We tested the change of previously reported regulators of IFITMs, such as NRAV, NRIR, and miR-130a after HTNV infection, among which NRIR was the only changed one (downregulated) after HTNV infection ( Figure 7A ; Figure S4 in Supplementary Material) in HUVEC. However, the expression of NRIR was unchanged in A549 cells. We overexpressed NRIR in HUVEC and A549 cells using the pcDNA3.1 vector ( Figure 7B) . Importantly, overexpression of NRIR significantly suppressed IFITM3 mRNA and pre-mRNA levels and facilitated HTNV infection in HUVEC and A549 cells (Figures 7C-E) . These data suggest that lncRNA NRIR is a negative regulator of IFITM3 transcription.
Hantaan virus is an enveloped, negative-sense RNA virus from the genus Hantavirus within the family Bunyaviridae. It causes HFRS, which is an important threat to public health worldwide. It is also a potential weapon for biological terrorism. Reservoir animals, usually rodents, are asymptomatic during persistent infection. Unlike in rodents, Hantavirus infection leads to HFRS and Hantavirus pulmonary syndrome (HPS) in humans (21) . The major clinical characteristics of HFRS include fever, hemorrhage, hypotension, and renal injury (1, 21) , causing severe manifestations and death in some cases. The current standard of care for HFRS relies on symptomatic and supportive treatment. It has been confirmed that the plasma viral load is associated with the severity of HFRS, implicating the importance of viremia in the pathogenesis of HFRS (2). However, no direct antiviral medications are currently available for this illness. Interferon is the key molecule for the antiviral response and has been used as an antiviral medicine in many diseases. It has been reported that HTNV infection induces a late type I interferon response (16) . However, the set of ISGs required for IFN-mediated inhibition of HTNV has not yet been identified. Therefore, identification of ISGs that are effective against HTNV is an attractive strategy to identify novel therapeutic targets.
In this study, we demonstrated a significantly high frequency of the rs12252 C allele and CC genotype among HFRS patients with severe illness compared with mildly infected individuals and the healthy Han Chinese. The rs12252 C allele and CC genotype are also found to be associated with higher plasma viral load in the early stage of HFRS. We also discovered that HTNV infection induces IFITMs, and the truncated IFITM3 produced by rs12252 C allele exhibits significantly decreased anti-HTNV activity. Interestingly, IFITM3 is found to restrict HTNV infection with a mechanism of cellular entry inhibition. Indeed, IFITM3 is localized to the late endosome in the host cells, which is a necessary structure for HTNV entry. In addition, we find that HTNV infection downregulated lncRNA NRIR 48 h post infection, which negatively regulates the transcription of IFITM3. Collectively, these results suggest that IFITM3, regulated by NRIR, inhibits HTNV infection, and its SNP rs12252 correlates with the disease severity and viral load in patients with HFRS.
The antiviral properties of IFITM proteins were identified in 2009 in an RNAi screen for host factors that influence influenza virus replication (29) . IFITM1, 2, and 3 have been demonstrated to possess antiviral activity in several studies. Everitt et al. demonstrated that the severity of influenza virus infection was greatly increased in IFITM3-knockout mice compared with wild-type animals (15) . Different IFITM members have also been confirmed to inhibit the cellular entry of multiple virus families (including filoviruses, rhabdoviruses, and flaviviruses) (7, (9) (10) (11) 30) . For example, HIV-1 and HCV infection are inhibited by IFITM1 (31) (32) (33) (34) . It is commonly believed that IFITMs restrict viral infection at the stage of cellular entry (12) . Recent studies suggested that the cellular location of different IFITMs may influence the range of viruses restricted by each protein (5) . IFITM1 prevents HCV entry because it colocalizes with CD81 on the cell membrane, interrupting the endocytosis of HCV particles (32) , whereas IFITM3 confines influenza virus in acidified endosomal compartments (27) . Notably, retrovirus subvirus particles (ISVPs), which do not require endosomal acidification for entry, are not inhibited by IFITM3 expression, suggesting that IFITM3 may function at the stage of endosomal entry (35) . Studies utilizing cell-cell fusion assays have suggested that IFITM3 blocks the entry of enveloped virus by preventing the fusion of the viral membrane with a limiting membrane of the host cell, either the plasma membrane and/or the endosomal membranes. The results obtained using two-photon laser scanning and fluorescence lifetime imaging (FLIM) suggest that IFITM proteins may reduce membrane fluidity and increase the spontaneous positive curvature in the outer leaflet of membranes (36) . In the present study, we demonstrated that IFN-α2a (20 U/ ml) significantly inhibited HTNV infection, siRNA-mediated depletion of IFITM3 alone significantly mitigated the antiviral effect of IFN-α2a in both HUVEC and A549 cells, whereas depletion of IFITM1 alone alleviated the antiviral effect of IFN-α2a in A549 cells. Overexpression of IFITM3 inhibited HTNV infection to HUVEC and A549 cells. IFITM1 overexpression was also effective in inhibition of HTNV in A549 cells. All these results suggest that IFITM3 is an important control factor under natural infection of HTNV. Our results also demonstrate that the effectiveness of IFITM3 is cell type-independent, which is in accordance with the results from similar viruses, such as RVFV (18) . Binding and entry assays, conducted by controlling the temperature and pH, showed that IFITM3 did not significantly influence HTNV binding but inhibited HTNV entry into HUVEC and A549 cells. Indeed, IFITM3 partially localizes to the late endosome of the host cells, which is a necessary site for the HTNV entry. However, we failed in tracking the transportation of HTNV in infected cells possibly due to the lack of fluorescence-labeled virus. In addition, IFITM1 also suppressed HTNV infection in A549 cells. The mechanism underlying anti-HTNV effect of IFITM1 remains undetermined and deserves to be further explored.
According to a recent study on the three-dimensional structure of IFITM3, there is a C-terminal transmembrane α-helix and a two-N-terminal intramembrane α-helices (shown in Figure 2A as black boxes) in IFITM3 (14) . There are two splice variants that differ by the presence or absence of the first N-terminal 21 amino acids (deleted part, shown in Figure 2A as red dotted line). Several SNPs including 13 non-synonymous, 13 synonymous, 1 in-frame stop, and 1 splice site acceptoraltering have been reported in the translated IFITM3 sequence (15, 29) . Among them, the rare SNP rs12252C allele of IFITM3 truncates the protein as described above, leading to a reduced inhibition of influenza virus infection in A549 cells (15) . We demonstrated that truncated IFITM3 protein also loses the ability to inhibit HTNV infection in vitro. In Northern European patients hospitalized with seasonal influenza or pandemic influenza A virus, increased homozygosity of the minor C allele of SNP rs12252 in IFITM3 was observed (37) . In Chinese patients infected with influenza A (H1N1) virus, there was also an increased frequency of the C allele and CC genotype of SNP rs12252 (13) . In the present study, we observed an increased frequency of the C allele and CC genotype of SNP rs12252 in severely infected HFRS patients compared with healthy control and mildly affected patients. Patients carrying the CC genotype also had higher plasma viral loads compared with those with the CT/TT genotype. Given the impaired function of the IFITM3 protein produced by the C mutation, and the fact that enrichment of the rs12252 C allele in patients with severe disease and the higher viral load in patients with the CC genotype, this founding suggests that IFITM3 plays a pivotal role in the anti-HTNV response in vivo. We speculate that the much higher level of CC allele at healthy population of Han Chinese compared with Caucasians may place the Chinese at a higher risk for developing severe illness upon HTNV infection, which needs further investigation.
LncRNAs are a group of non-coding RNAs longer than 200 nt that function as gene regulators, playing a role in regulating multiple cellular functions, including the innate immunity. For example, lncRNA NEAT1 is reported to be upregulated by influenza virus or PolyI:C stimulation, which promotes IL-8 expression (38) . lncRNA NRAV has been shown to negatively regulate the initial transcription of IFITM3 and Mx1 by affecting the histone modification of these genes (25) . lncRNA NRIR is a non-coding ISG, which has been reported to negatively regulate IFITM1 and Mx1 expression in HCV infection (20) . Mir-130a was also reported as a regulator of IFITM1 (23) . In this analysis, lncRNA NRIR was downregulated in HUVECs after HTNV infection for 48 h, overexpression of NRIR negatively regulates the initial transcription of IFITM3, evidenced by the decreased pre-mRNA as well as mRNA levels. NRIR overexpression also facilitated HTNV infection. These results indicate that the downregulation of NRIR after HTNV infection is possibly involved in the activation of innate immune responses against HTNV infection. We have also evaluated other potential regulators of IFITM3 before we choose NRIR for further study. Another lncRNA that can regulate IFITM3, i.e., NRAV (NR_038854), remained unchanged after HTNV infection ( Figures S4A,B in Supplementary Material). Additionally, miR-130a, which potentially regulate IFITM3, was also unaltered after HTNV infection ( Figures S4C,D in Supplementary Material).
In conclusion, this study revealed a critical role for IFITM3 in HTNV infection. We demonstrated, for the first time to our knowledge, that IFITM3 is a newly identified anti-HTNV ISG; its expression is negatively regulated by NRIR; and its antiviral activity seems via a mechanism of inhibiting virus entry into the host cells. In addition, we discovered that the IFITM3 SNP rs12252 C allele and CC genotype correlates with the plasma HTNV load and the severity of HFRS; and the rs12252 C allele produces a truncated IFITM3 protein (NΔ21) that attenuates its anti-HTNV function. These results provide new insights into the role of IFITM3 in regulating innate immunity against HTNV infection, which is the basis for identifying new targets to develop novel agent against this worldwide infectious disease. aUThOr cOnTribUTiOns ZX-y, BP-y, YC-t, and MH-w performed the experiments; WP-z, BX-f, LY-f, ZY, and JZ-s designed the research; HC-x, YW, and WX analyzed the data; TK and ZC-m provided clinical data; ZX-y and BP-y wrote the paper. | How is Interferon used in practice? | false | 551 | {
"text": [
"an antiviral medicine"
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2,466 | Critical care response to a hospital outbreak of the 2019-nCoV infection in Shenzhen, China
https://doi.org/10.1186/s13054-020-2786-x
SHA: 6a93283b499ae5bc6aaf29f14e701dc8f25138ea
Authors: Liu, Yong; Li, Jinxiu; Feng, Yongwen
Date: 2020
DOI: 10.1186/s13054-020-2786-x
License: cc-by
Abstract: nan
Text: The main challenge may include (1) early identification of outbreak, (2) rapid expansion of patients, (3) high risk of nosocomial transmission, (4) unpredictability of size impacted, and (5) lack of backup resource. These challenges have caused severe shortage of healthcare workers, medical materials, and beds with isolation. The Spring Festival holiday has greatly aggravated the shortage of human resources and heavy traffic flow due to the vacation of healthy workers and factory workers, which further magnified the risk of transmission. The key point is to discriminate the infectious disease outbreak from regular clustering cases of flu-like diseases at early stage. There is a trade-off between false alarm causing population panic and delayed identification leading to social crisis.
Early identification of 2019-nCoV infection presents a major challenge for the frontline clinicians. Its clinical symptoms largely overlap with those of common acute respiratory illnesses, including fever (98%), cough (76%), and diarrhea (3%), often more severe in older adults with pre-existing chronic comorbidities [1] . Usually, the laboratory abnormalities include lymphocytopenia and hypoxemia [1] . The initial chest radiographs may vary from minimal abnormality to bilateral ground-glass opacity or subsegmental areas of consolidation [1] . In addition, asymptomatic cases and lack of diagnosis kits result in delayed or even missed diagnosis inevitable and makes many other patients, visitors, and healthcare workers exposed to the 2019-nCoV infection.
Critical care response to the outbreak of coronavirus should happen not only at the level of hospital, but also at the level of the city which is dominated by the government. At the early stage, the size of the patients' population is not beyond the capability of local infectious diseases hospital (IDH). The general hospital is responsible for fever triage, identifying suspected cases, and transferring to the local IDH. Such a plan is mandatory for every hospital. Shenzhen city has established a preexisting Infectious Disease Epidemic Plan (IDEP), which has facilitated managing and containing local outbreak of the 2019-nCoV. In case the patient load exceeds the hospital capability of the IDH, new IDHs should be considered either by building a temporary new IDH or reconstructing an existing hospital. Wuhan, the epicenter of the outbreak, is racing against time to build two specialized hospitals for nCoV patients, namely Huoshenshan and Leishenshan hospital, whereas a different strategy has been undertaken in Shenzhen city by reconstructing an existing hospital to become an IDH with capability of 800 beds.
2019-nCoV patients should be admitted to singlebedded, negative pressure rooms in isolated units with intensive care and monitoring [2] . Clinical engineering should have plans to reconstruct standard rooms [2] . Retrofitting the rooms with externally exhausted HEPA filters may be an expedient solution. Also, the general hospital may consider procedures such as suspending elective surgeries, canceling ambulatory clinics and outpatient diagnostic procedures, transferring patients to other institutions, and restricting hospital visitors [2] . More importantly, because the hospitals' ability to respond to the outbreak largely depends on their available ICU beds, the plan to increase ICU bed capacity needs to be determined.
Caring for 2019-nCoV patients represents a substantial exposure risk for ICU staff because of the following reasons: highly contagious with multiple transmission route, high exposure dose, long daily contact hours, and ICU stay. The basic reproductive number was estimated to be 2.2 (95% CI, 1.4 to 3.9) [3] , or as high as between 3.6 and 4.0 [4] . The 2019-nCoV is proved to be transmitted by respiratory droplets, contact, and fecal-oral, even transmission through the eye is possible [5, 6] . The higher viral load and aerosol-generating procedures, such as noninvasive ventilation, magnify the exposure and transmission risk [2, 7, 8] . Moreover, virus shedding can be prolonged and last for > 3 weeks according to some literature and our unpublished data [2] . Healthcare providers and those in contact with infected patients should utilize contact, droplet, and airborne precautions with N95 respirator. Strict infection prevention and control practices have been implemented and audited in our units following the infection prevention and control plan published by China's National Health Committee (CNHC). In addition, wellequipped fever clinic as triage station with trained staff knowing 2019-nCoV case definitions is established. For suspected 2019-nCoV infection, several key points are crucial procedures: recording a detailed history, standardizing pneumonia workup, obtaining lower respiratory tract specimens [2, 8] , and implementing droplet isolation to break the transmission chain in the healthcare setting [2] .
The risk of 2019-nCoV exposure may cause significant psychosocial stress on healthcare workers [2] . The death of a retired ENT physician from a 2019-nCoV infection has added to fears in January 2020. Psychotherapists have also been invited to join medical teams to evaluate and deal with potential stress and depression for the safety of the healthcare workers.
Critical management 2019-nCoV management was largely supportive, including intubation, early prone positioning, neuromuscular blockade, and extracorporeal membrane oxygenation (ECMO) according to the recommendations updated by CNHC. Low-dose systematic corticosteroids, lopinavir/ritonavir, and atomization inhalation of interferon were encouraged. These critical managements have worked well so far, as our 2019-nCoV patients had zero mortality. On the contrary, the previously reported mortality of 2019-nCoV patients in Wuhan ranged from 11 to 15% [1, 9] . | What are the steps that a hospital should take after COVID-19 outbreak? | false | 644 | {
"text": [
"2019-nCoV patients should be admitted"
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187 | Preparation for Possible Sustained Transmission of 2019 Novel Coronavirus
Lessons From Previous Epidemics
https://jamanetwork.com/journals/jama/fullarticle/2761285
February 11, 2020
David L. Swerdlow, MD1; Lyn Finelli, DrPH, MS2
Author Affiliations Article Information
JAMA. 2020;323(12):1129-1130. doi:10.1001/jama.2020.1960
COVID-19 Resource Center
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Transmissibility and severity are the 2 most critical factors that determine the effect of an epidemic. Neither the 2009 pandemic influenza A(H1N1) virus ([H1N1]pdm09) pandemic or the severe acute respiratory syndrome coronavirus (SARS-CoV) or the Middle East respiratory syndrome coronavirus (MERS-CoV) epidemics had the combination of both high transmissibility and severity. Control strategies are driven by this combination. R0, the basic reproduction number, is a commonly used measure of transmissibility and is defined as the number of additional persons one case infects over the course of their illness. An R0 of less than 1 indicates the infection will die out “eventually.” An R0 of greater than 1 indicates the infection has the potential for sustained transmission.
For example, influenza A(H1N1)pdm09, first identified in southern California on April 15, 2009, was highly transmissible. By May 5, 2009, influenza A(H1N1)pdm09 had spread to 41 US states and 21 countries.1 While influenza A(H1N1)pdm09 was highly transmissible, it was not severe. Initial estimates of the R0 of influenza A(H1N1)pdm09 were 1.7.2 Although an estimated 201 200 respiratory deaths due to influenza A(H1N1)pdm09 occurred during the first year of the pandemic, the number of deaths per population was 30 times lower than that seen during the 1968 influenza pandemic, 1000 times less than the 1918 pandemic, and even less than typical seasonal influenza epidemics (estimated by the World Health Organization [WHO] to be 250 000 to 500 000 per year, although estimation methods differ).3 Influenza A(H1N1)pdm09 was highly transmissible but not severe.
SARS-CoV (2003) and MERS-CoV (2012-current) cause severe disease, but despite the initial R0 estimations of greater than 2.0 for SARS-CoV (indicating sustained and even worldwide transmission could occur), and some large outbreaks, neither were as transmissible as initial concerns suggested. SARS-CoV caused 8098 reported cases and 774 deaths (case-fatality rate, 9.6%) in 37 countries before the epidemic was controlled. Control was thought to have been possible because a high proportion of cases were severe, making it easier to rapidly identify and isolate infected individuals. In addition, the virus was present at lower levels in upper airway secretions. There was no secondary transmission in the United States from the 8 imported cases, although in Toronto, Canada, a single importation is thought to have led to about 400 cases and 44 deaths. Later estimates of R0 were less than 1, indicating that SARS-CoV may not have been capable of sustained transmission, especially in the setting of control measures.4
Similarly, MERS-CoV appears to have high severity and low transmissibility. Since 2012, MERS-CoV has caused 2494 reported cases and 858 deaths (case-fatality rate, 34%) in 27 countries. MERS-CoV has also caused some rapid outbreaks, mainly in hospitals in Saudi Arabia, Jordan, and South Korea, but estimates of MERS-CoV R0 are less than 1, and thus far it has been contained.5
Can a respiratory virus that is both transmissible and severe be contained? In preparation for an influenza pandemic, the US Department of Health and Human Services’ Pandemic Influenza Plan included a combination of nonpharmaceutical (border and school closing, infection control measures) and pharmaceutical (antiviral prophylaxis, vaccines) interventions meant to be used in combination to interrupt or slow influenza transmission. Despite implementation of some of these interventions, influenza A(H1N1)pdm09 spread to 120 countries in 3 months.
With the emergence of MERS-CoV in the Middle East, a preparedness plan was developed that included a surveillance plan, laboratory testing, and contact tracing guidance. Infection control guidance was developed for use in health care settings and traveler guidance was developed for the public.6 The US Centers for Disease Control and Prevention (CDC) distributed MERS-CoV polymerase chain reaction test kits to state health departments. Two cases were imported into the United States. Contacts were traced, including household, hospital, and airline contacts. No secondary cases were identified in the United States. MERS-CoV was thought to be severe and control measures relied on recognition of suspect cases. However, during a hospital outbreak in Jeddah, Saudi Arabia, among hospitalized patients only 5 of 53 (9%) health care–associated cases had documented presence in the same room as a patient with MERS.5 Despite the high case-fatality rate (an important measure of severity), MERS cases can be asymptomatic and mild (25% in one outbreak). Although it is not known how often asymptomatic or mildly symptomatic patients transmit MERS, initiating comprehensive measures such as isolating patients suspected of having or having been exposed to the virus and using personal protective equipment when caring for them may be extremely difficult because so many patients have mild and nonspecific symptoms.
Is the world ready for a respiratory virus with high transmissibility and severity? After a new influenza virus (H7N9) was identified in China in 2013, a series of modeling articles described the effect of, and level of preparedness for, a severe, single-wave pandemic in the United States.7 In scenarios that used clinical attack rates (the proportion of individuals who become ill with or die from a disease in a population initially uninfected) of 20% to 30% (for comparison the clinical attack rate was 20% in the first year of the 2009 H1N1 pandemic), depending on severity there would be an estimated 669 000 to 4.3 million hospitalizations and an estimated 54 000 to 538 000 deaths without any interventions in the United States. The models suggested that without a vaccine, school closures would be unlikely to affect the pandemic, an estimated 35 000 to 60 000 ventilators would be needed, up to an estimated 7.3 billion surgical masks or respirators would be required, and perhaps most important, if vaccine development did not start before the virus was introduced, it was unlikely that a significant number of hospitalizations and deaths could be averted due to the time it takes to develop, test, manufacture, and distribute a vaccine.
It is impossible to know what will happen so early in this novel 2019 coronavirus (2019-nCoV) epidemic. The scope, morbidity, and mortality will depend on the combination of severity and transmissibility. Numerous experts have “nowcasted” how many cases have occurred and forecasted how many cases will likely occur. A recent study suggests rapid person to person transmission can occur.8 Disease modelers have estimated R0 to be 2.2.9 The University of Hong Kong estimates the outbreak could infect more than 150 000 persons per day in China at its peak.
Is 2019-nCoV infection severe? To date approximately 14% of cases of 2019-nCoV have been described as severe by WHO, with a case-fatality rate of 2.1%.10 Estimates of severity are usually higher in the beginning of an epidemic due to the identification of the most severely affected cases and decline as the epidemic progresses. However, because many infected persons have not yet recovered and may still die, the case-fatality rate and severity could be underestimated. On January 30, 2020, WHO officially declared the 2019-nCoV epidemic as a Public Health Emergency of International Concern, indicating its concern that countries aside from China could be affected by 2019-nCoV.
In preparing for possible sustained transmission of 2019-nCoV beyond China, applicable lessons from previous experiences with epidemics/pandemics of respiratory viruses should be carefully considered to better control and mitigate potential consequences. Influenza preparedness plans have been developed that aim to stop, slow, or limit the spread of an influenza pandemic to the United States. These plans address limiting domestic spread and mitigating disease but also sustaining infrastructure and reducing the adverse effects of the pandemic on the economy and society. These plans would be useful to enact during the 2019-nCoV epidemic should the United States experience sustained transmission. Countries have been successful in the past and there is nothing yet to predict that this time it is likely to be worse. Effective prevention and control will not be easy if there is sustained transmission and will require the full attention of public health, federal and local governments, the private sector, and every citizen.
Back to topArticle Information
Corresponding Author: David L. Swerdlow, MD, Clinical Epidemiology Lead, Medical Development and Scientific/Clinical Affairs, Pfizer Vaccines, 500 Arcola Rd, Collegeville, PA 19426 ([email protected]).
Published Online: February 11, 2020. doi:10.1001/jama.2020.1960
Conflict of Interest Disclosures: Dr Swerdlow reports owning stock and stock options in Pfizer Inc. Dr Swerdlow also reports providing a one-time consultation consisting of an overview of SARS and MERS epidemiology to GLG Consulting and receiving an honorarium. Dr Finelli reports owning stock in Merck and Co.
Funding/Support: Pfizer Inc provided salary support for Dr Swerdlow.
Role of the Funder/Sponsor: Pfizer Inc reviewed the manuscript and approved the decision to submit the manuscript for publication.
References
1.
Swerdlow DL, Finelli L, Bridges CB. 2009 H1N1 influenza pandemic: field and epidemiologic investigations in the United States at the start of the first pandemic of the 21st century. Clin Infect Dis. 2011;52(suppl 1):S1-S3. doi:10.1093/cid/ciq005PubMedGoogle ScholarCrossref
2.
Balcan D, Hu H, Goncalves B, et al. Seasonal transmission potential and activity peaks of the new influenza A(H1N1): a Monte Carlo likelihood analysis based on human mobility. BMC Medicine. 2009;7(45). doi:10.1186/1741-7015-7-45
3.
Dawood FS, Iuliano AD, Reed C, et al. Estimated global mortality associated with the first 12 months of 2009 pandemic influenza A H1N1 virus circulation: a modelling study. Lancet Infect Dis. 2012;12(9):687-695. doi:10.1016/S1473-3099(12)70121-4PubMedGoogle ScholarCrossref
4.
Chowell G, Castillo-Chavez C, Fenimore PW, Kribs-Zaleta CM, Arriola L, Hyman JM. Model parameters and outbreak control for SARS. Emerg Infect Dis. 2004;10(7):1258-1263. doi:10.3201/eid1007.030647PubMedGoogle ScholarCrossref
5.
Killerby ME, Biggs HM, Midgley CM, Gerber SI, Watson JT. Middle East respiratory syndrome coronavirus transmission. Emerg Infect Dis. 2020;26(2):191-198. doi:10.3201/eid2602.190697PubMedGoogle ScholarCrossref
6.
Rasmussen SA, Watson AK, Swerdlow DL. Middle East respiratory syndrome (MERS). Microbiol Spectr. 2016;4(3). doi:10.1128/microbiolspec.EI10-0020-2016PubMedGoogle Scholar
7.
Swerdlow DL, Pillai SK, Meltzer MI, eds. CDC modeling efforts in response to a potential public health emergency: influenza A(H7N9) as an example. Clin Infect Dis. 2015;60(suppl):S1-S63. https://academic.oup.com/cid/issue/60/suppl_1.Google Scholar
8.
Wang D, Hu B, Hu C, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus–infected pneumonia in Wuhan, China. JAMA. Published online February 7, 2020. doi:10.1001/jama.2020.1585
ArticlePubMedGoogle Scholar
9.
Li Q, Guan X, Wu P, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus–infected pneumonia. N Engl J Med. Published online January 29, 2020. doi:10.1056/NEJMoa2001316PubMedGoogle Scholar
10.
World Health Organization. Novel coronavirus (2019-nCoV) situation reports. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports/. Accessed February 4, 2020.
Comment
2 Comments for this articleEXPAND ALL
February 12, 2020
Understanding R and Disease Control
Oz Mansoor | Public Health Physician, Wellington
The message, that we need to prepare for a pandemic is vital. But the article misreports some key ideas. Firstly, SARS was not controlled "because a high proportion of cases were severe." While that helped , it was because cases were not infectious before some days after symptom onset (usually in the second week of illness). This gave more time for case identification and isolation. And most cases did not pass on infection to anybody, but a few spread to many. When all such individuals were identified and isolated, spread stopped.
Unfortunately, the new virusappears to be spreading from people much earlier in the course of illness, and even with mild symptoms - which was never documented for SARS. However, it is not clear that it is any different or better at spread between people, and perhaps with the same pattern of most cases not causing further spread.
Secondly, the R0, the basic reproduction number, is correctly described as the average number of infections each case causes. But it lacks two key ideas: 1) the 0 after the R implies the native state, which is a fully susceptible population and without any control measures. R is the effectiive number and can include the impact of control measures.
To claim that it was the lack of transmissibility, rather than the control measures that ended SARS, is not based on any evidence. And it ignores the heroic efforts of affected countries.
Elimination of SARS demonstrated the potential of globally coordinated collective action, as well as the damage caused by ignorance and prejudice. Most seem to have already forgotten the lessons of SARS.CONFLICT OF INTEREST: Worked for WHO/WPRO in SARS responseREAD MORE
February 24, 2020
COVID 19: a global presence and not only a new pathogen?
Giuliano Ramadori, Professor of Medicine | University Clinic, Göttingen, Germany
In the winter season there comes the time of upper and lower respiratory tract infections characterised by cough, dyspnea and eventually fever (influenza-like illness).Some of the patients, especially older people living alone affected by the disease ,may need hospitalization and eventually intensive care. In many of the cases who are hospitalized nasal and/or tracheal fluid are examined for viral or bacterial agents. Only in less than 50% of the cases influenza viruses are considered to be the cause of the disease.In the rest of the cases diagnostic procedure for human coronaviruses is not performed routinely. One of the fourdifferent Human Coronaviruses (HuCoV: 229E,NL 63,0C43 and HKU1) can however be found in up to 30% ofpatients negative for influenza viruses (1). Chinese scientists in Wuhan, who had to deal with an increasing number of acute respiratory tract diseases resembling viral pneumonia, performed deep sequencing analysis from samples taken from the lower respiratory tract and found a "novel" coronavirus. The sequence of the complete genome was made public. At the same time, however, the notice from Wuhan brought to mind the SARS- and MERS-epidemics. The measures taken by the Chinese- and WHO-authorities are now well known.
Recently about 150 new cases have been identified in northern Italy and health authorities are still looking for case 0 (the source). Is it possible that COVID-19 was already existent in Italy -- and not only in Italy but possibly everywhere in the world -- and that newly available nucleotide sequence allows now to find the cause of previously undefined influenza-like illness?
REFERENCE
1. Benezit F et al.:Non-influenza respiratory viruses in adult patients admitted with influenza-like illness:a 3- year prospective multicenter study.Infection, 13 february 2020, https://doi.org/10.1007/s15010-019-01388-1).CONFLICT OF INTEREST: None ReportedREAD MORE
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Silverchair Logo | What is the estimated R0 of COVID-19? | false | 255 | {
"text": [
"2.2"
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7158
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2,440 | Optimization Method for Forecasting Confirmed Cases of COVID-19 in China
https://doi.org/10.3390/jcm9030674
SHA: 1d7f8850c5244fdc9b387038e7eeae9bcbbde6d2
Authors: Al-Qaness, Mohammed A. A.; Ewees, Ahmed A.; Fan, Hong; Abd El Aziz, Mohamed
Date: 2020
DOI: 10.3390/jcm9030674
License: cc-by
Abstract: In December 2019, a novel coronavirus, called COVID-19, was discovered in Wuhan, China, and has spread to different cities in China as well as to 24 other countries. The number of confirmed cases is increasing daily and reached 34,598 on 8 February 2020. In the current study, we present a new forecasting model to estimate and forecast the number of confirmed cases of COVID-19 in the upcoming ten days based on the previously confirmed cases recorded in China. The proposed model is an improved adaptive neuro-fuzzy inference system (ANFIS) using an enhanced flower pollination algorithm (FPA) by using the salp swarm algorithm (SSA). In general, SSA is employed to improve FPA to avoid its drawbacks (i.e., getting trapped at the local optima). The main idea of the proposed model, called FPASSA-ANFIS, is to improve the performance of ANFIS by determining the parameters of ANFIS using FPASSA. The FPASSA-ANFIS model is evaluated using the World Health Organization (WHO) official data of the outbreak of the COVID-19 to forecast the confirmed cases of the upcoming ten days. More so, the FPASSA-ANFIS model is compared to several existing models, and it showed better performance in terms of Mean Absolute Percentage Error (MAPE), Root Mean Squared Relative Error (RMSRE), Root Mean Squared Relative Error (RMSRE), coefficient of determination ( R 2 ), and computing time. Furthermore, we tested the proposed model using two different datasets of weekly influenza confirmed cases in two countries, namely the USA and China. The outcomes also showed good performances.
Text: A large family of viruses, called coronaviruses, are severe pathogens for human beings, which infect respiratory, hepatic, gastrointestinal, and neurologic diseases. They are distributed among humans, birds, livestock, mice, bats, and other wild animals [1] [2] [3] . The outbreaks of two previous coronaviruses, SARS-CoV and MERS-CoV in 2003 and 2012, respectively, have approved the transmission from animal to animal, and human to human [4] . In December 2019, the World Health Organization (WHO) received notifications from China for many cases of respiratory illness that were linked to some people who had visited a seafood market in Wuhan [5] . Currently, Wuhan city suffers from the spreading of a novel coronavirus, called COVID-19 (previously, it was called 2019-nCoV). In [6] , the authors concluded that COVID-19 likely originated in bats, because it is more similar to two bat-derived coronavirus strains. However, the source of the COVID-19 is not confirmed yet, and it communities, Hong Kong and Toronto, were 1.2 and 1.32, respectively. Ong et al. [20] proposed a monitoring and forecasting model for influenza A (H1N1-2009). Furthermore, Nah et al. [21] proposed a probability-based model to predict the spread of the MERS.
The Adaptive Neuro-Fuzzy Inference System (ANFIS) [22] is widely applied in time series prediction and forecasting problems, and it showed good performance in many existing applications. It offers flexibility in determining nonlinearity in the time series data, as well as combining the properties of both artificial neural networks (ANN) and fuzzy logic systems. It has been applied in various forecasting applications, for example, in [23] , a stock price forecasting model was proposed using ANFIS and empirical mode decomposition. Chen et al. [24] proposed a TAIEX time series forecasting model based on a hybrid of ANFIS and ordered weighted averaging (OWA). In [25] , another time series forecasting method was presented for electricity prices based on ANFIS. Svalina et al. [26] proposed an ANFIS based forecasting model for close price indices for a stock market for five days. Ekici and Aksoy [27] presented an ANFIS based building energy consumption forecasting model. More so, ANFIS is also applied to forecast electricity loads [28] . Kumar et al. [29] proposed an ANFIS based model to forecast return products. Ho and Tsai [30] applied ANFIS to forecast product development performance. However, estimating ANFIS parameters is a challenge that needs to be improved. Therefore, in previous studies, some individual swarm intelligence (SI) methods have been applied to the ANFIS parameters to enhance time series forecasting because these parameters have a significant effect on the performance of ANFIS. The SI methods include the particle swarm optimization (PSO) [31, 32] , social-spider optimization [33] , sine-cosine algorithm (SCA) [34] , and multi-verse optimizer (MVO) [35] . For example, in [34] SCA algorithm was applied to improve the ANFIS model to forecast oil consumption in three countries, namely, Canada, Germany, and Japan. In the same context, in [35] , The MVO algorithm was used to enhance the ANFIS model to forecast oil consumption in two countries. In addition, in [36] the PSO was used with ANFIS to predict biochar yield. However, individual SI algorithms may stock at local optima. Therefore, one solution is to apply hybrid SI algorithms to avoid this problem. In [37] , a hybrid of two SI algorithms, namely GA and SSA, was presented to improve the ANFIS model. The proposed new model called GA-SSA-ANFIS was applied to forecast crude oil prices for long-term time series data. However, the previously mentioned methods suffer from some limitations that can affect the performance of the forecasting output such as slow convergence and the ability to balance between exploration and exploitation phases can influence the quality of the final output. This motivated us to propose an alternative forecasting method dependent on the hybridization concept. This concept avoids the limitations of traditional SI techniques by combining the strengths of different techniques, and this produces new SI techniques that are better than traditional ones.
In the current study, we propose an improved ANFIS model based on a modified flower pollination algorithm (FPA) using the salp swarm algorithm (SSA). The FPA is an optimization algorithm proposed by Yang [38] , which was inspired by the flow pollination process of the flowering plants. The FPA was employed in various optimization applications, for example to estimate solar PV parameter [39, 40] , solving sudoku puzzles [41] , feature selection [42] , antenna design [43] , and other applications [44] [45] [46] [47] . Moreover, SSA is also an optimization algorithm proposed by Mirjalili et al. [48] inspired by the behavior of salp chains. In recent years, the SSA was utilized to solve different optimization problems, such as feature selection [49, 50] , data classification [51] , image segmentation [52] , and others [53, 54] .
The proposed method called FPASSA is a hybrid of FPA and SSA, in which the SSA is applied as a local search method for FPA. The proposed FPASSA starts by receiving the historical COVID-19 dataset. Then a set of solutions is generated where each of them represents the value for the parameters of the ANFIS model. Then the quality of each solution is calculated using the fitness value, and the solution that has the best fitness value is chosen to represent the best solution. Then the probability of each solution is computed. Then the current solution will be updated, either using global or local strategy in FPA. However, in the case of local strategy, the operators of SSA or FPA will be used according to the probability of the fitness value for each solution. The process of updating the solutions is repeated until reaching the stop condition, and the best parameter configurations are used to forecast the number of confirmed cases of COVID-19.
The main contribution points of the current study are as follows:
1.
We propose an efficient forecasting model to forecast the confirmed cases of the COVID-19 in China for the upcoming ten days based on previously confirmed cases.
An improved ANFIS model is proposed using a modified FPA algorithm, using SSA.
We compare the proposed model with the original ANFIS and existing modified ANFIS models, such as PSO, GA, ABC, and FPA.
The rest of this study is organized as follows. The preliminaries of ANFIS, FPA, and SSA are described in Section 2. Section 3 presents the proposed FPASSA, and Section 4 presents the experimental setup and results. We conclude this study in Section 5.
The principles of the ANFIS are given in this section. The ANFIS model links the fuzzy logic and neural networks [22] . It generates a mapping between the input and output by applying IF-THEN rules (it is also called Takagi-Sugeno inference model). Figure 1 illustrates the ANFIS model where, y and x define the inputs to Layer 1 whereas, O 1i is its output of node i that is computed as follows:
where µ denotes the generalized Gaussian membership functions. A i and B i define the membership values of µ. α i and ρ i denote the premise parameters set. The output of Layer 2 (it is also known as the firing strength of a rule) is calculated as follows:
Meanwhile, the output of Layer 3 (it is also known as the normalized firing strength) is calculated as follows:
The output of Layer 4 (it is also known as an adaptive node) is calculated as follows:
where r i , q i , and p i define the consequent parameters of the node i. Layer 5 contains only one node; its output is computed as:
Flower Pollination Algorithm is an optimization method proposed by Yang [38] . It simulates the transfer of flowers' pollen by pollinators in nature. This algorithm utilizes the two types of pollination (i.e., self-pollination and cross-pollination). In self-pollination, the pollination occurs with no pollinators, whereas, in cross-pollination, the pollens are moved between different plants. In more detail, the self-pollination can be represented as a local pollination while the cross-pollination can be called global pollination.
The global pollination or cross-pollination can be mathematically formed as follows:
where x t i defines the pollen i at iteration t. L denotes the pollination's strength or the step size. F * is the target position or best solution. In some cases, insects can fly with different distance steps for a long space; therefore, Levy fly distribution is applied to simulate this movement.
where λ = 1.5. Γ(λ) denotes the gamma function. This distribution is available for large steps s > 0. The self-pollination or local pollination can be mathematically formed as follows:
where x t i and x k i represent pollens from different flower in the same plant. in the range [0,1] The process of pollination can be done using cross-pollination or self-pollination. Therefore, the random variable p, in the range [0, 1], is used to determine this process.
SSA is an optimization technique introduced by [48] . It simulates the Salps' behavior in nature. This behavior is called salp chain. The mathematical model of SSA begins by splinting its population into a leader group and followers group. The leader is the front salp, whereas, the followers are the other salps. The search space is determined in n-dimensions with n variables. Equation (10) works to update the salps' positions.
where x 1 j denotes the leader's position in j-th dimension. F j is the target position. ub j and lb j represent the max and min bounds, respectively. c 2 and c 3 denote random numbers in [0, 1]. c 1 is an important parameter; it balances between the exploration and exploitation phases. It is computed as follows:
where the current loop number is t and the max loop' number is t max . Then, the followers' position is updated as follows:
where x i j defines the i-th position of the follower in j-th dimension. i > 1.
This section explains the proposed FPASSA-ANFIS method. It is a time series method for forecasting the confirmed cases of the COVID-19, as given in Figure 2 . The FPASSA-ANFIS utilizes the improved FPA to train the ANFIS model by optimizing its parameters. The FPASSA-ANFIS contains five layers as the classic ANFIS model. Layer 1 contains the input variables (the historical COVID-19 confirmed cases). Whereas Layer 5 produces the forecasted values. In the learning phase, the FPASSA is used to select the best weights between Layer 4 and Layer 5.
The FPASSA-ANFIS starts by formatting the input data in a time series form. In our case, the autocorrelation function (ACF) was considered. ACF is one of the methods applied to find patterns in the data; it presents information about the correlation between points separated by various time lags. Therefore, in this paper, the variables with ACF greater than 0.2 are considered i.e., 5-lags.
Besides, the training data contains 75% of the dataset, whereas the testing data contains 25% of them. The number of clusters is defined by the fuzzy c-mean (FCM) method to construct the ANFIS model.
The parameters of the ANFIS model are prepared by the FPASSA algorithm. In the training phase, the calculation error (as in Equation (13)) between the real data and the predicted data is used to evaluate the parameters' quality.
where T is the real data, and P is the predicted data. N s is the sample length. The smaller values of the objective function indicate good ANFIS's parameter.
On the other hand, the updating phase of the followers' positions in the SSA algorithm is applied to improve the global pollination phase in the FPA algorithm. In this improvement, there is a random variable (r) used to switch between both phases. If r > 0.5, then the operators of the SSA is used; otherwise, the operators of the FPA are used. In general, The FPASSA starts by constructing the population (X); afterward, the objective function is calculated for each solution. The solution with the lowest error value is saved to the next iteration. This sequence is repeated until meeting the stop condition, which in this paper, is the maximum number of iterations. Then the best solution is passed to train the parameters of the ANFIS model.
After finishing the training phase, the testing phase is started with the best solution to compute the final output. The performance of the proposed method is evaluated by comparing the real data with the predicted data using the performance measures. Finally, the FPASSA produces a foretasted value for confirmed cases of COVID-19 in China in the next day. The steps of the proposed FPASSA are presented in Algorithm 1.
Input: Historical COVID-19 dataset, size of population N, total number of iterations t max .
Divide the data into training and testing sets.
Using Fuzzy c-mean method to determine the number of membership functions.
Constructing the ANFIS network.
Set the initial value for N solutions (X). Return the best solution that represents the best configuration for ANFIS.
Apply the testing set to the best ANFIS model.
Forecasting the COVID-19 for the next ten days.
This section presents the description of the used dataset, the performance measures, the parameter setting for all methods, the experiment results, and discussions.
The main dataset of this study is COVID-19 dataset. It was collected from the WHO website (https: //www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports/). It contains the daily confirmed cases in China from 21 January 2020 to 18 February 2020, as shown in Table 1 . We used 75% from the dataset to train the model while the rest is used to test it.
Moreover, we evaluated the performance of the proposed method using two datasets of weekly influenza confirmed cases. The first one is called DS1; it was collected from the Centers for Disease Control and Prevention (CDC) (https://www.cdc.gov/flu/weekly/). It starts from week number 40 in 2015 and continues until week number 6 in 2020. Whereas, the second one is called DS2. It was collected from the WHO website (https://www.who.int/influenza). It contains the data of weekly influenza confirmed cases in China from week number 1 in 2016 to week number 8 in 2020.
The quality of the proposed method is evaluated using a set of performance metrics as follows:
• Root Mean Square Error (RMSE):
where Yp and Y are the predicted and original values, respectively. • Mean Absolute Error (MAE):
• Mean Absolute Percentage Error (MAPE):
• Root Mean Squared Relative Error (RMSRE):
N s represents the sample size of the data. • Coefficient of Determination (R 2 ):
where Y represents the average of Y.
The lowest value of RMSE, MAE, MAPE, and RMSRE refers to the best method. The higher value of R 2 indicates better correlation for the method.
This paper aims to assess the ability of the FPASSA to forecast the COVID-19 by comparing its performance with other methods, namely the ANFIS and the trained ANFIS models using PSO, GA, ABC, FPA, and FPASSA. The parameters' setting for these models is listed in Table 2 .
The common parameters, such as population size, are set to 25 and 100 iterations are applied. Besides, each algorithm is performed for 30 independent runs to fair comparisons. The selected parameters are chosen because they produced good behavior in previous experiments, such as [34, 35, 55, 56] . Table 2 . Parameters' setting.
Parameters Setting
Max. epochs = 100, Error goal = 0, Initial step = 0.01, Decrease rate = 0.9, Increase rate = 1.
In this section, the performance of the proposed FPASSA to predict the DS1 and DS2 is discussed. It can be concluded from Table 3 that the performance of FPASSA outperformed the compared methods in all measures, whereas the FPA is ranked second. The results of DS2 indicate that the FPASSA is ranked first in terms of RMSE, MAPE, R 2 , and the CPU time. Whereas, the PSO is ranked second, followed by the FPA, GA, then ABC. These results denote that the proposed method can optimize the parameters of the ANFIS model effectively and produce good results in terms of the performance measures. Comparison results between the proposed FPASSA and other models to forecast COVID-19 are given in Table 4 . It can be concluded that the FPASSA outperforms other models. For example, by analyzing the results of RMSE, MAE, MAPE, RMSRE, and CPU time(s) it can be observed that the FPASSA achieves the smallest value among the comparison algorithms, and this indicates the high quality of the FPASSA. Meanwhile, the FPA allocates the second rank, which provides better results than the rest of the methods.
Moreover, the value of R 2 refers to the high correlation between the prediction obtained by the proposed FPASSA method and the original COVID-19, which has nearly 0.97. This can also be noticed from Figure 3 , which depicts the training of the algorithms using the historical data of the COVID-19 as well as their forecasting values for ten days. Table 5 depicts the forecasting value for the confirmed cases of the COVID-19 in China from 19/2/2020 to 28/2/2020. From these results, it can be noticed that the outbreak will reach its highest level on the day 28/2/2020. The average percentage of the increase over the forecasted period is 10%, the highest percentage is 12% on 28/2/2020, and the lowest percentage is 8.7% on 19/2/2020. From the previous results, it can be concluded that the proposed FPASSA-ANFIS has a high ability to forecast the COVID-19 dataset. These results avoid the limitations of traditional ANFIS because of the combination with the modified FPA method. Moreover, the operators of SSA are combined with the local strategy of FPA to enhance their exploitation ability. However, the time computational of the proposed FPASSA method still requires more improvements.
This paper proposed a modified version for the flower pollination algorithm (FPA) using the salp swarm algorithm (SSA). This modified version, called FPASSA, is applied to improve the performance of the ANFIS through determining the optimal value for its parameters. The developed FPASSA-ANFIS model is applied as a forecasting technique for a novel coronavirus, called COVID-19, that was discovered in Wuhan, China at the end of last year and January of the current year. The proposed FPASSA-ANFIS model has a high ability to predict the number of confirmed cases within ten days. Besides, FPASSA-ANFIS outperforms other forecasting models in terms of RMSE, MAE, MAPE, RMSRE, and R 2 . Furthermore, two datasets of weekly influenza confirmed cases in the USA and China were used to evaluate the proposed method, and the evaluation outcomes showed its good performance. According to the promising results obtained by the proposed FPASSA-ANFIS, it can be applied in different forecasting applications. | What were the outcomes of the test? | false | 4,403 | {
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1,719 | Virus-Vectored Influenza Virus Vaccines
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147686/
SHA: f6d2afb2ec44d8656972ea79f8a833143bbeb42b
Authors: Tripp, Ralph A.; Tompkins, S. Mark
Date: 2014-08-07
DOI: 10.3390/v6083055
License: cc-by
Abstract: Despite the availability of an inactivated vaccine that has been licensed for >50 years, the influenza virus continues to cause morbidity and mortality worldwide. Constant evolution of circulating influenza virus strains and the emergence of new strains diminishes the effectiveness of annual vaccines that rely on a match with circulating influenza strains. Thus, there is a continued need for new, efficacious vaccines conferring cross-clade protection to avoid the need for biannual reformulation of seasonal influenza vaccines. Recombinant virus-vectored vaccines are an appealing alternative to classical inactivated vaccines because virus vectors enable native expression of influenza antigens, even from virulent influenza viruses, while expressed in the context of the vector that can improve immunogenicity. In addition, a vectored vaccine often enables delivery of the vaccine to sites of inductive immunity such as the respiratory tract enabling protection from influenza virus infection. Moreover, the ability to readily manipulate virus vectors to produce novel influenza vaccines may provide the quickest path toward a universal vaccine protecting against all influenza viruses. This review will discuss experimental virus-vectored vaccines for use in humans, comparing them to licensed vaccines and the hurdles faced for licensure of these next-generation influenza virus vaccines.
Text: Seasonal influenza is a worldwide health problem causing high mobility and substantial mortality [1] [2] [3] [4] . Moreover, influenza infection often worsens preexisting medical conditions [5] [6] [7] . Vaccines against circulating influenza strains are available and updated annually, but many issues are still present, including low efficacy in the populations at greatest risk of complications from influenza virus infection, i.e., the young and elderly [8, 9] . Despite increasing vaccination rates, influenza-related hospitalizations are increasing [8, 10] , and substantial drug resistance has developed to two of the four currently approved anti-viral drugs [11, 12] . While adjuvants have the potential to improve efficacy and availability of current inactivated vaccines, live-attenuated and virus-vectored vaccines are still considered one of the best options for the induction of broad and efficacious immunity to the influenza virus [13] .
The general types of influenza vaccines available in the United States are trivalent inactivated influenza vaccine (TIV), quadrivalent influenza vaccine (QIV), and live attenuated influenza vaccine (LAIV; in trivalent and quadrivalent forms). There are three types of inactivated vaccines that include whole virus inactivated, split virus inactivated, and subunit vaccines. In split virus vaccines, the virus is disrupted by a detergent. In subunit vaccines, HA and NA have been further purified by removal of other viral components. TIV is administered intramuscularly and contains three or four inactivated viruses, i.e., two type A strains (H1 and H3) and one or two type B strains. TIV efficacy is measured by induction of humoral responses to the hemagglutinin (HA) protein, the major surface and attachment glycoprotein on influenza. Serum antibody responses to HA are measured by the hemagglutination-inhibition (HI) assay, and the strain-specific HI titer is considered the gold-standard correlate of immunity to influenza where a four-fold increase in titer post-vaccination, or a HI titer of ≥1:40 is considered protective [4, 14] . Protection against clinical disease is mainly conferred by serum antibodies; however, mucosal IgA antibodies also may contribute to resistance against infection. Split virus inactivated vaccines can induce neuraminidase (NA)-specific antibody responses [15] [16] [17] , and anti-NA antibodies have been associated with protection from infection in humans [18] [19] [20] [21] [22] . Currently, NA-specific antibody responses are not considered a correlate of protection [14] . LAIV is administered as a nasal spray and contains the same three or four influenza virus strains as inactivated vaccines but on an attenuated vaccine backbone [4] . LAIV are temperature-sensitive and cold-adapted so they do not replicate effectively at core body temperature, but replicate in the mucosa of the nasopharynx [23] . LAIV immunization induces serum antibody responses, mucosal antibody responses (IgA), and T cell responses. While robust serum antibody and nasal wash (mucosal) antibody responses are associated with protection from infection, other immune responses, such as CD8 + cytotoxic lymphocyte (CTL) responses may contribute to protection and there is not a clear correlate of immunity for LAIV [4, 14, 24] .
Currently licensed influenza virus vaccines suffer from a number of issues. The inactivated vaccines rely on specific antibody responses to the HA, and to a lesser extent NA proteins for protection. The immunodominant portions of the HA and NA molecules undergo a constant process of antigenic drift, a natural accumulation of mutations, enabling virus evasion from immunity [9, 25] . Thus, the circulating influenza A and B strains are reviewed annually for antigenic match with current vaccines, Replacement of vaccine strains may occur regularly, and annual vaccination is recommended to assure protection [4, 26, 27] . For the northern hemisphere, vaccine strain selection occurs in February and then manufacturers begin production, taking at least six months to produce the millions of vaccine doses required for the fall [27] . If the prediction is imperfect, or if manufacturers have issues with vaccine production, vaccine efficacy or availability can be compromised [28] . LAIV is not recommended for all populations; however, it is generally considered to be as effective as inactivated vaccines and may be more efficacious in children [4, 9, 24] . While LAIV relies on antigenic match and the HA and NA antigens are replaced on the same schedule as the TIV [4, 9] , there is some suggestion that LAIV may induce broader protection than TIV due to the diversity of the immune response consistent with inducing virus-neutralizing serum and mucosal antibodies, as well as broadly reactive T cell responses [9, 23, 29] . While overall both TIV and LAIV are considered safe and effective, there is a recognized need for improved seasonal influenza vaccines [26] . Moreover, improved understanding of immunity to conserved influenza virus antigens has raised the possibility of a universal vaccine, and these universal antigens will likely require novel vaccines for effective delivery [30] [31] [32] .
Virus-vectored vaccines share many of the advantages of LAIV, as well as those unique to the vectors. Recombinant DNA systems exist that allow ready manipulation and modification of the vector genome. This in turn enables modification of the vectors to attenuate the virus or enhance immunogenicity, in addition to adding and manipulating the influenza virus antigens. Many of these vectors have been extensively studied or used as vaccines against wild type forms of the virus. Finally, each of these vaccine vectors is either replication-defective or causes a self-limiting infection, although like LAIV, safety in immunocompromised individuals still remains a concern [4, 13, [33] [34] [35] . Table 1 summarizes the benefits and concerns of each of the virus-vectored vaccines discussed here.
There are 53 serotypes of adenovirus, many of which have been explored as vaccine vectors. A live adenovirus vaccine containing serotypes 4 and 7 has been in use by the military for decades, suggesting adenoviruses may be safe for widespread vaccine use [36] . However, safety concerns have led to the majority of adenovirus-based vaccine development to focus on replication-defective vectors. Adenovirus 5 (Ad5) is the most-studied serotype, having been tested for gene delivery and anti-cancer agents, as well as for infectious disease vaccines.
Adenovirus vectors are attractive as vaccine vectors because their genome is very stable and there are a variety of recombinant systems available which can accommodate up to 10 kb of recombinant genetic material [37] . Adenovirus is a non-enveloped virus which is relatively stable and can be formulated for long-term storage at 4 °C, or even storage up to six months at room temperature [33] . Adenovirus vaccines can be grown to high titers, exceeding 10 1° plaque forming units (PFU) per mL when cultured on 293 or PER.C6 cells [38] , and the virus can be purified by simple methods [39] . Adenovirus vaccines can also be delivered via multiple routes, including intramuscular injection, subcutaneous injection, intradermal injection, oral delivery using a protective capsule, and by intranasal delivery. Importantly, the latter two delivery methods induce robust mucosal immune responses and may bypass preexisting vector immunity [33] . Even replication-defective adenovirus vectors are naturally immunostimulatory and effective adjuvants to the recombinant antigen being delivered. Adenovirus has been extensively studied as a vaccine vector for human disease. The first report using adenovirus as a vaccine vector for influenza demonstrated immunogenicity of recombinant adenovirus 5 (rAd5) expressing the HA of a swine influenza virus, A/Swine/Iowa/1999 (H3N2). Intramuscular immunization of mice with this construct induced robust neutralizing antibody responses and protected mice from challenge with a heterologous virus, A/Hong Kong/1/1968 (H3N2) [40] . Replication defective rAd5 vaccines expressing influenza HA have also been tested in humans. A rAd5-HA expressing the HA from A/Puerto Rico/8/1934 (H1N1; PR8) was delivered to humans epicutaneously or intranasally and assayed for safety and immunogenicity. The vaccine was well tolerated and induced seroconversion with the intranasal administration had a higher conversion rate and higher geometric meant HI titers [41] . While clinical trials with rAd vectors have overall been successful, demonstrating safety and some level of efficacy, rAd5 as a vector has been negatively overshadowed by two clinical trial failures. The first trial was a gene therapy examination where high-dose intravenous delivery of an Ad vector resulted in the death of an 18-year-old male [42, 43] . The second clinical failure was using an Ad5-vectored HIV vaccine being tested as a part of a Step Study, a phase 2B clinical trial. In this study, individuals were vaccinated with the Ad5 vaccine vector expressing HIV-1 gag, pol, and nef genes. The vaccine induced HIV-specific T cell responses; however, the study was stopped after interim analysis suggested the vaccine did not achieve efficacy and individuals with high preexisting Ad5 antibody titers might have an increased risk of acquiring HIV-1 [44] [45] [46] . Subsequently, the rAd5 vaccine-associated risk was confirmed [47] . While these two instances do not suggest Ad-vector vaccines are unsafe or inefficacious, the umbra cast by the clinical trials notes has affected interest for all adenovirus vaccines, but interest still remains.
Immunization with adenovirus vectors induces potent cellular and humoral immune responses that are initiated through toll-like receptor-dependent and independent pathways which induce robust pro-inflammatory cytokine responses. Recombinant Ad vaccines expressing HA antigens from pandemic H1N1 (pH1N1), H5 and H7 highly pathogenic avian influenza (HPAI) virus (HPAIV), and H9 avian influenza viruses have been tested for efficacy in a number of animal models, including chickens, mice, and ferrets, and been shown to be efficacious and provide protection from challenge [48, 49] . Several rAd5 vectors have been explored for delivery of non-HA antigens, influenza nucleoprotein (NP) and matrix 2 (M2) protein [29, [50] [51] [52] . The efficacy of non-HA antigens has led to their inclusion with HA-based vaccines to improve immunogenicity and broaden breadth of both humoral and cellular immunity [53, 54] . However, as both CD8 + T cell and neutralizing antibody responses are generated by the vector and vaccine antigens, immunological memory to these components can reduce efficacy and limit repeated use [48] .
One drawback of an Ad5 vector is the potential for preexisting immunity, so alternative adenovirus serotypes have been explored as vectors, particularly non-human and uncommon human serotypes. Non-human adenovirus vectors include those from non-human primates (NHP), dogs, sheep, pigs, cows, birds and others [48, 55] . These vectors can infect a variety of cell types, but are generally attenuated in humans avoiding concerns of preexisting immunity. Swine, NHP and bovine adenoviruses expressing H5 HA antigens have been shown to induce immunity comparable to human rAd5-H5 vaccines [33, 56] . Recombinant, replication-defective adenoviruses from low-prevalence serotypes have also been shown to be efficacious. Low prevalence serotypes such as adenovirus types 3, 7, 11, and 35 can evade anti-Ad5 immune responses while maintaining effective antigen delivery and immunogenicity [48, 57] . Prime-boost strategies, using DNA or protein immunization in conjunction with an adenovirus vaccine booster immunization have also been explored as a means to avoided preexisting immunity [52] .
Adeno-associated viruses (AAV) were first explored as gene therapy vectors. Like rAd vectors, rAAV have broad tropism infecting a variety of hosts, tissues, and proliferating and non-proliferating cell types [58] . AAVs had been generally not considered as vaccine vectors because they were widely considered to be poorly immunogenic. A seminal study using AAV-2 to express a HSV-2 glycoprotein showed this virus vaccine vector effectively induced potent CD8 + T cell and serum antibody responses, thereby opening the door to other rAAV vaccine-associated studies [59, 60] .
AAV vector systems have a number of engaging properties. The wild type viruses are non-pathogenic and replication incompetent in humans and the recombinant AAV vector systems are even further attenuated [61] . As members of the parvovirus family, AAVs are small non-enveloped viruses that are stable and amenable to long-term storage without a cold chain. While there is limited preexisting immunity, availability of non-human strains as vaccine candidates eliminates these concerns. Modifications to the vector have increased immunogenicity, as well [60] .
There are limited studies using AAVs as vaccine vectors for influenza. An AAV expressing an HA antigen was first shown to induce protective in 2001 [62] . Later, a hybrid AAV derived from two non-human primate isolates (AAVrh32.33) was used to express influenza NP and protect against PR8 challenge in mice [63] . Most recently, following the 2009 H1N1 influenza virus pandemic, rAAV vectors were generated expressing the HA, NP and matrix 1 (M1) proteins of A/Mexico/4603/2009 (pH1N1), and in murine immunization and challenge studies, the rAAV-HA and rAAV-NP were shown to be protective; however, mice vaccinated with rAAV-HA + NP + M1 had the most robust protection. Also, mice vaccinated with rAAV-HA + rAAV-NP + rAAV-M1 were also partially protected against heterologous (PR8, H1N1) challenge [63] . Most recently, an AAV vector was used to deliver passive immunity to influenza [64, 65] . In these studies, AAV (AAV8 and AAV9) was used to deliver an antibody transgene encoding a broadly cross-protective anti-influenza monoclonal antibody for in vivo expression. Both intramuscular and intranasal delivery of the AAVs was shown to protect against a number of influenza virus challenges in mice and ferrets, including H1N1 and H5N1 viruses [64, 65] . These studies suggest that rAAV vectors are promising vaccine and immunoprophylaxis vectors. To this point, while approximately 80 phase I, I/II, II, or III rAAV clinical trials are open, completed, or being reviewed, these have focused upon gene transfer studies and so there is as yet limited safety data for use of rAAV as vaccines [66] .
Alphaviruses are positive-sense, single-stranded RNA viruses of the Togaviridae family. A variety of alphaviruses have been developed as vaccine vectors, including Semliki Forest virus (SFV), Sindbis (SIN) virus, Venezuelan equine encephalitis (VEE) virus, as well as chimeric viruses incorporating portions of SIN and VEE viruses. The replication defective vaccines or replicons do not encode viral structural proteins, having these portions of the genome replaces with transgenic material.
The structural proteins are provided in cell culture production systems. One important feature of the replicon systems is the self-replicating nature of the RNA. Despite the partial viral genome, the RNAs are self-replicating and can express transgenes at very high levels [67] .
SIN, SFV, and VEE have all been tested for efficacy as vaccine vectors for influenza virus [68] [69] [70] [71] . A VEE-based replicon system encoding the HA from PR8 was demonstrated to induce potent HA-specific immune response and protected from challenge in a murine model, despite repeated immunization with the vector expressing a control antigen, suggesting preexisting immunity may not be an issue for the replicon vaccine [68] . A separate study developed a VEE replicon system expressing the HA from A/Hong Kong/156/1997 (H5N1) and demonstrated varying efficacy after in ovo vaccination or vaccination of 1-day-old chicks [70] . A recombinant SIN virus was use as a vaccine vector to deliver a CD8 + T cell epitope only. The well-characterized NP epitope was transgenically expressed in the SIN system and shown to be immunogenic in mice, priming a robust CD8 + T cell response and reducing influenza virus titer after challenge [69] . More recently, a VEE replicon system expressing the HA protein of PR8 was shown to protect young adult (8-week-old) and aged (12-month-old) mice from lethal homologous challenge [72] .
The VEE replicon systems are particularly appealing as the VEE targets antigen-presenting cells in the lymphatic tissues, priming rapid and robust immune responses [73] . VEE replicon systems can induce robust mucosal immune responses through intranasal or subcutaneous immunization [72] [73] [74] , and subcutaneous immunization with virus-like replicon particles (VRP) expressing HA-induced antigen-specific systemic IgG and fecal IgA antibodies [74] . VRPs derived from VEE virus have been developed as candidate vaccines for cytomegalovirus (CMV). A phase I clinical trial with the CMV VRP showed the vaccine was immunogenic, inducing CMV-neutralizing antibody responses and potent T cell responses. Moreover, the vaccine was well tolerated and considered safe [75] . A separate clinical trial assessed efficacy of repeated immunization with a VRP expressing a tumor antigen. The vaccine was safe and despite high vector-specific immunity after initial immunization, continued to boost transgene-specific immune responses upon boost [76] . While additional clinical data is needed, these reports suggest alphavirus replicon systems or VRPs may be safe and efficacious, even in the face of preexisting immunity.
Baculovirus has been extensively used to produce recombinant proteins. Recently, a baculovirus-derived recombinant HA vaccine was approved for human use and was first available for use in the United States for the 2013-2014 influenza season [4] . Baculoviruses have also been explored as vaccine vectors. Baculoviruses have a number of advantages as vaccine vectors. The viruses have been extensively studied for protein expression and for pesticide use and so are readily manipulated. The vectors can accommodate large gene insertions, show limited cytopathic effect in mammalian cells, and have been shown to infect and express genes of interest in a spectrum of mammalian cells [77] . While the insect promoters are not effective for mammalian gene expression, appropriate promoters can be cloned into the baculovirus vaccine vectors.
Baculovirus vectors have been tested as influenza vaccines, with the first reported vaccine using Autographa californica nuclear polyhedrosis virus (AcNPV) expressing the HA of PR8 under control of the CAG promoter (AcCAG-HA) [77] . Intramuscular, intranasal, intradermal, and intraperitoneal immunization or mice with AcCAG-HA elicited HA-specific antibody responses, however only intranasal immunization provided protection from lethal challenge. Interestingly, intranasal immunization with the wild type AcNPV also resulted in protection from PR8 challenge. The robust innate immune response to the baculovirus provided non-specific protection from subsequent influenza virus infection [78] . While these studies did not demonstrate specific protection, there were antigen-specific immune responses and potential adjuvant effects by the innate response.
Baculovirus pseudotype viruses have also been explored. The G protein of vesicular stomatitis virus controlled by the insect polyhedron promoter and the HA of A/Chicken/Hubei/327/2004 (H5N1) HPAIV controlled by a CMV promoter were used to generate the BV-G-HA. Intramuscular immunization of mice or chickens with BV-G-HA elicited strong HI and VN serum antibody responses, IFN-γ responses, and protected from H5N1 challenge [79] . A separate study demonstrated efficacy using a bivalent pseudotyped baculovirus vector [80] .
Baculovirus has also been used to generate an inactivated particle vaccine. The HA of A/Indonesia/CDC669/2006(H5N1) was incorporated into a commercial baculovirus vector controlled by the e1 promoter from White Spot Syndrome Virus. The resulting recombinant virus was propagated in insect (Sf9) cells and inactivated as a particle vaccine [81, 82] . Intranasal delivery with cholera toxin B as an adjuvant elicited robust HI titers and protected from lethal challenge [81] . Oral delivery of this encapsulated vaccine induced robust serum HI titers and mucosal IgA titers in mice, and protected from H5N1 HPAIV challenge. More recently, co-formulations of inactivated baculovirus vectors have also been shown to be effective in mice [83] .
While there is growing data on the potential use of baculovirus or pseudotyped baculovirus as a vaccine vector, efficacy data in mammalian animal models other than mice is lacking. There is also no data on the safety in humans, reducing enthusiasm for baculovirus as a vaccine vector for influenza at this time.
Newcastle disease virus (NDV) is a single-stranded, negative-sense RNA virus that causes disease in poultry. NDV has a number of appealing qualities as a vaccine vector. As an avian virus, there is little or no preexisting immunity to NDV in humans and NDV propagates to high titers in both chicken eggs and cell culture. As a paramyxovirus, there is no DNA phase in the virus lifecycle reducing concerns of integration events, and the levels of gene expression are driven by the proximity to the leader sequence at the 3' end of the viral genome. This gradient of gene expression enables attenuation through rearrangement of the genome, or by insertion of transgenes within the genome. Finally, pathogenicity of NDV is largely determined by features of the fusion protein enabling ready attenuation of the vaccine vector [84] .
Reverse genetics, a method that allows NDV to be rescued from plasmids expressing the viral RNA polymerase and nucleocapsid proteins, was first reported in 1999 [85, 86] . This process has enabled manipulation of the NDV genome as well as incorporation of transgenes and the development of NDV vectors. Influenza was the first infectious disease targeted with a recombinant NDV (rNDV) vector. The HA protein of A/WSN/1933 (H1N1) was inserted into the Hitchner B1 vaccine strain. The HA protein was expressed on infected cells and was incorporated into infectious virions. While the virus was attenuated compared to the parental vaccine strain, it induced a robust serum antibody response and protected against homologous influenza virus challenge in a murine model of infection [87] . Subsequently, rNDV was tested as a vaccine vector for HPAIV having varying efficacy against H5 and H7 influenza virus infections in poultry [88] [89] [90] [91] [92] [93] [94] . These vaccines have the added benefit of potentially providing protection against both the influenza virus and NDV infection.
NDV has also been explored as a vaccine vector for humans. Two NHP studies assessed the immunogenicity and efficacy of an rNDV expressing the HA or NA of A/Vietnam/1203/2004 (H5N1; VN1203) [95, 96] . Intranasal and intratracheal delivery of the rNDV-HA or rNDV-NA vaccines induced both serum and mucosal antibody responses and protected from HPAIV challenge [95, 96] . NDV has limited clinical data; however, phase I and phase I/II clinical trials have shown that the NDV vector is well-tolerated, even at high doses delivered intravenously [44, 97] . While these results are promising, additional studies are needed to advance NDV as a human vaccine vector for influenza.
Parainfluenza virus type 5 (PIV5) is a paramyxovirus vaccine vector being explored for delivery of influenza and other infectious disease vaccine antigens. PIV5 has only recently been described as a vaccine vector [98] . Similar to other RNA viruses, PIV5 has a number of features that make it an attractive vaccine vector. For example, PIV5 has a stable RNA genome and no DNA phase in virus replication cycle reducing concerns of host genome integration or modification. PIV5 can be grown to very high titers in mammalian vaccine cell culture substrates and is not cytopathic allowing for extended culture and harvest of vaccine virus [98, 99] . Like NDV, PIV5 has a 3'-to 5' gradient of gene expression and insertion of transgenes at different locations in the genome can variably attenuate the virus and alter transgene expression [100] . PIV5 has broad tropism, infecting many cell types, tissues, and species without causing clinical disease, although PIV5 has been associated with -kennel cough‖ in dogs [99] . A reverse genetics system for PIV5 was first used to insert the HA gene from A/Udorn/307/72 (H3N2) into the PIV5 genome between the hemagglutinin-neuraminidase (HN) gene and the large (L) polymerase gene. Similar to NDV, the HA was expressed at high levels in infected cells and replicated similarly to the wild type virus, and importantly, was not pathogenic in immunodeficient mice [98] . Additionally, a single intranasal immunization in a murine model of influenza infection was shown to induce neutralizing antibody responses and protect against a virus expressing homologous HA protein [98] . PIV5 has also been explored as a vaccine against HPAIV. Recombinant PIV5 vaccines expressing the HA or NP from VN1203 were tested for efficacy in a murine challenge model. Mice intranasally vaccinated with a single dose of PIV5-H5 vaccine had robust serum and mucosal antibody responses, and were protected from lethal challenge. Notably, although cellular immune responses appeared to contribute to protection, serum antibody was sufficient for protection from challenge [100, 101] . Intramuscular immunization with PIV5-H5 was also shown to be effective at inducing neutralizing antibody responses and protecting against lethal influenza virus challenge [101] . PIV5 expressing the NP protein of HPAIV was also efficacious in the murine immunization and challenge model, where a single intranasal immunization induced robust CD8 + T cell responses and protected against homologous (H5N1) and heterosubtypic (H1N1) virus challenge [102] .
Currently there is no clinical safety data for use of PIV5 in humans. However, live PIV5 has been a component of veterinary vaccines for -kennel cough‖ for >30 years, and veterinarians and dog owners are exposed to live PIV5 without reported disease [99] . This combined with preclinical data from a variety of animal models suggests that PIV5 as a vector is likely to be safe in humans. As preexisting immunity is a concern for all virus-vectored vaccines, it should be noted that there is no data on the levels of preexisting immunity to PIV5 in humans. However, a study evaluating the efficacy of a PIV5-H3 vaccine in canines previously vaccinated against PIV5 (kennel cough) showed induction of robust anti-H3 serum antibody responses as well as high serum antibody levels to the PIV5 vaccine, suggesting preexisting immunity to the PIV5 vector may not affect immunogenicity of vaccines even with repeated use [99] .
Poxvirus vaccines have a long history and the notable hallmark of being responsible for eradication of smallpox. The termination of the smallpox virus vaccination program has resulted in a large population of poxvirus-naï ve individuals that provides the opportunity for the use of poxviruses as vectors without preexisting immunity concerns [103] . Poxvirus-vectored vaccines were first proposed for use in 1982 with two reports of recombinant vaccinia viruses encoding and expressing functional thymidine kinase gene from herpes virus [104, 105] . Within a year, a vaccinia virus encoding the HA of an H2N2 virus was shown to express a functional HA protein (cleaved in the HA1 and HA2 subunits) and be immunogenic in rabbits and hamsters [106] . Subsequently, all ten of the primary influenza proteins have been expressed in vaccine virus [107] .
Early work with intact vaccinia virus vectors raised safety concerns, as there was substantial reactogenicity that hindered recombinant vaccine development [108] . Two vaccinia vectors were developed to address these safety concerns. The modified vaccinia virus Ankara (MVA) strain was attenuated by passage 530 times in chick embryo fibroblasts cultures. The second, New York vaccinia virus (NYVAC) was a plaque-purified clone of the Copenhagen vaccine strain rationally attenuated by deletion of 18 open reading frames [109] [110] [111] .
Modified vaccinia virus Ankara (MVA) was developed prior to smallpox eradication to reduce or prevent adverse effects of other smallpox vaccines [109] . Serial tissue culture passage of MVA resulted in loss of 15% of the genome, and established a growth restriction for avian cells. The defects affected late stages in virus assembly in non-avian cells, a feature enabling use of the vector as single-round expression vector in non-permissive hosts. Interestingly, over two decades ago, recombinant MVA expressing the HA and NP of influenza virus was shown to be effective against lethal influenza virus challenge in a murine model [112] . Subsequently, MVA expressing various antigens from seasonal, pandemic (A/California/04/2009, pH1N1), equine (A/Equine/Kentucky/1/81 H3N8), and HPAI (VN1203) viruses have been shown to be efficacious in murine, ferret, NHP, and equine challenge models [113] . MVA vaccines are very effective stimulators of both cellular and humoral immunity. For example, abortive infection provides native expression of the influenza antigens enabling robust antibody responses to native surface viral antigens. Concurrently, the intracellular influenza peptides expressed by the pox vector enter the class I MHC antigen processing and presentation pathway enabling induction of CD8 + T cell antiviral responses. MVA also induces CD4 + T cell responses further contributing to the magnitude of the antigen-specific effector functions [107, [112] [113] [114] [115] . MVA is also a potent activator of early innate immune responses further enhancing adaptive immune responses [116] . Between early smallpox vaccine development and more recent vaccine vector development, MVA has undergone extensive safety testing and shown to be attenuated in severely immunocompromised animals and safe for use in children, adults, elderly, and immunocompromised persons. With extensive pre-clinical data, recombinant MVA vaccines expressing influenza antigens have been tested in clinical trials and been shown to be safe and immunogenic in humans [117] [118] [119] . These results combined with data from other (non-influenza) clinical and pre-clinical studies support MVA as a leading viral-vectored candidate vaccine.
The NYVAC vector is a highly attenuated vaccinia virus strain. NYVAC is replication-restricted; however, it grows in chick embryo fibroblasts and Vero cells enabling vaccine-scale production. In non-permissive cells, critical late structural proteins are not produced stopping replication at the immature virion stage [120] . NYVAC is very attenuated and considered safe for use in humans of all ages; however, it predominantly induces a CD4 + T cell response which is different compared to MVA [114] . Both MVA and NYVAC provoke robust humoral responses, and can be delivered mucosally to induce mucosal antibody responses [121] . There has been only limited exploration of NYVAC as a vaccine vector for influenza virus; however, a vaccine expressing the HA from A/chicken/Indonesia/7/2003 (H5N1) was shown to induce potent neutralizing antibody responses and protect against challenge in swine [122] .
While there is strong safety and efficacy data for use of NYVAC or MVA-vectored influenza vaccines, preexisting immunity remains a concern. Although the smallpox vaccination campaign has resulted in a population of poxvirus-naï ve people, the initiation of an MVA or NYVAC vaccination program for HIV, influenza or other pathogens will rapidly reduce this susceptible population. While there is significant interest in development of pox-vectored influenza virus vaccines, current influenza vaccination strategies rely upon regular immunization with vaccines matched to circulating strains. This would likely limit the use and/or efficacy of poxvirus-vectored influenza virus vaccines for regular and seasonal use [13] . Intriguingly, NYVAC may have an advantage for use as an influenza vaccine vector, because immunization with this vector induces weaker vaccine-specific immune responses compared to other poxvirus vaccines, a feature that may address the concerns surrounding preexisting immunity [123] .
While poxvirus-vectored vaccines have not yet been approved for use in humans, there is a growing list of licensed poxvirus for veterinary use that include fowlpox-and canarypox-vectored vaccines for avian and equine influenza viruses, respectively [124, 125] . The fowlpox-vectored vaccine expressing the avian influenza virus HA antigen has the added benefit of providing protection against fowlpox infection. Currently, at least ten poxvirus-vectored vaccines have been licensed for veterinary use [126] . These poxvirus vectors have the potential for use as vaccine vectors in humans, similar to the first use of cowpox for vaccination against smallpox [127] . The availability of these non-human poxvirus vectors with extensive animal safety and efficacy data may address the issues with preexisting immunity to the human vaccine strains, although the cross-reactivity originally described with cowpox could also limit use.
Influenza vaccines utilizing vesicular stomatitis virus (VSV), a rhabdovirus, as a vaccine vector have a number of advantages shared with other RNA virus vaccine vectors. Both live and replication-defective VSV vaccine vectors have been shown to be immunogenic [128, 129] , and like Paramyxoviridae, the Rhabdoviridae genome has a 3'-to-5' gradient of gene expression enabling attention by selective vaccine gene insertion or genome rearrangement [130] . VSV has a number of other advantages including broad tissue tropism, and the potential for intramuscular or intranasal immunization. The latter delivery method enables induction of mucosal immunity and elimination of needles required for vaccination. Also, there is little evidence of VSV seropositivity in humans eliminating concerns of preexisting immunity, although repeated use may be a concern. Also, VSV vaccine can be produced using existing mammalian vaccine manufacturing cell lines.
Influenza antigens were first expressed in a VSV vector in 1997. Both the HA and NA were shown to be expressed as functional proteins and incorporated into the recombinant VSV particles [131] . Subsequently, VSV-HA, expressing the HA protein from A/WSN/1933 (H1N1) was shown to be immunogenic and protect mice from lethal influenza virus challenge [129] . To reduce safety concerns, attenuated VSV vectors were developed. One candidate vaccine had a truncated VSV G protein, while a second candidate was deficient in G protein expression and relied on G protein expressed by a helper vaccine cell line to the provide the virus receptor. Both vectors were found to be attenuated in mice, but maintained immunogenicity [128] . More recently, single-cycle replicating VSV vaccines have been tested for efficacy against H5N1 HPAIV. VSV vectors expressing the HA from A/Hong Kong/156/97 (H5N1) were shown to be immunogenic and induce cross-reactive antibody responses and protect against challenge with heterologous H5N1 challenge in murine and NHP models [132] [133] [134] .
VSV vectors are not without potential concerns. VSV can cause disease in a number of species, including humans [135] . The virus is also potentially neuroinvasive in some species [136] , although NHP studies suggest this is not a concern in humans [137] . Also, while the incorporation of the influenza antigen in to the virion may provide some benefit in immunogenicity, changes in tropism or attenuation could arise from incorporation of different influenza glycoproteins. There is no evidence for this, however [134] . Currently, there is no human safety data for VSV-vectored vaccines. While experimental data is promising, additional work is needed before consideration for human influenza vaccination.
Current influenza vaccines rely on matching the HA antigen of the vaccine with circulating strains to provide strain-specific neutralizing antibody responses [4, 14, 24] . There is significant interest in developing universal influenza vaccines that would not require annual reformulation to provide protective robust and durable immunity. These vaccines rely on generating focused immune responses to highly conserved portions of the virus that are refractory to mutation [30] [31] [32] . Traditional vaccines may not be suitable for these vaccination strategies; however, vectored vaccines that have the ability to be readily modified and to express transgenes are compatible for these applications.
The NP and M2 proteins have been explored as universal vaccine antigens for decades. Early work with recombinant viral vectors demonstrated that immunization with vaccines expressing influenza antigens induced potent CD8 + T cell responses [107, [138] [139] [140] [141] . These responses, even to the HA antigen, could be cross-protective [138] . A number of studies have shown that immunization with NP expressed by AAV, rAd5, alphavirus vectors, MVA, or other vector systems induces potent CD8 + T cell responses and protects against influenza virus challenge [52, 63, 69, 102, 139, 142] . As the NP protein is highly conserved across influenza A viruses, NP-specific T cells can protect against heterologous and even heterosubtypic virus challenges [30] .
The M2 protein is also highly conserved and expressed on the surface of infected cells, although to a lesser extent on the surface of virus particles [30] . Much of the vaccine work in this area has focused on virus-like or subunit particles expressing the M2 ectodomain; however, studies utilizing a DNA-prime, rAd-boost strategies to vaccinate against the entire M2 protein have shown the antigen to be immunogenic and protective [50] . In these studies, antibodies to the M2 protein protected against homologous and heterosubtypic challenge, including a H5N1 HPAIV challenge. More recently, NP and M2 have been combined to induce broadly cross-reactive CD8 + T cell and antibody responses, and rAd5 vaccines expressing these antigens have been shown to protect against pH1N1 and H5N1 challenges [29, 51] .
Historically, the HA has not been widely considered as a universal vaccine antigen. However, the recent identification of virus neutralizing monoclonal antibodies that cross-react with many subtypes of influenza virus [143] has presented the opportunity to design vaccine antigens to prime focused antibody responses to the highly conserved regions recognized by these monoclonal antibodies. The majority of these broadly cross-reactive antibodies recognize regions on the stalk of the HA protein [143] . The HA stalk is generally less immunogenic compared to the globular head of the HA protein so most approaches have utilized -headless‖ HA proteins as immunogens. HA stalk vaccines have been designed using DNA and virus-like particles [144] and MVA [142] ; however, these approaches are amenable to expression in any of the viruses vectors described here.
The goal of any vaccine is to protect against infection and disease, while inducing population-based immunity to reduce or eliminate virus transmission within the population. It is clear that currently licensed influenza vaccines have not fully met these goals, nor those specific to inducing long-term, robust immunity. There are a number of vaccine-related issues that must be addressed before population-based influenza vaccination strategies are optimized. The concept of a -one size fits all‖ vaccine needs to be updated, given the recent ability to probe the virus-host interface through RNA interference approaches that facilitate the identification of host genes affecting virus replication, immunity, and disease. There is also a need for revision of the current influenza virus vaccine strategies for at-risk populations, particularly those at either end of the age spectrum. An example of an improved vaccine regime might include the use of a vectored influenza virus vaccine that expresses the HA, NA and M and/or NP proteins for the two currently circulating influenza A subtypes and both influenza B strains so that vaccine take and vaccine antigen levels are not an issue in inducing protective immunity. Recombinant live-attenuated or replication-deficient influenza viruses may offer an advantage for this and other approaches.
Vectored vaccines can be constructed to express full-length influenza virus proteins, as well as generate conformationally restricted epitopes, features critical in generating appropriate humoral protection. Inclusion of internal influenza antigens in a vectored vaccine can also induce high levels of protective cellular immunity. To generate sustained immunity, it is an advantage to induce immunity at sites of inductive immunity to natural infection, in this case the respiratory tract. Several vectored vaccines target the respiratory tract. Typically, vectored vaccines generate antigen for weeks after immunization, in contrast to subunit vaccination. This increased presence and level of vaccine antigen contributes to and helps sustain a durable memory immune response, even augmenting the selection of higher affinity antibody secreting cells. The enhanced memory response is in part linked to the intrinsic augmentation of immunity induced by the vector. Thus, for weaker antigens typical of HA, vectored vaccines have the capacity to overcome real limitations in achieving robust and durable protection.
Meeting the mandates of seasonal influenza vaccine development is difficult, and to respond to a pandemic strain is even more challenging. Issues with influenza vaccine strain selection based on recently circulating viruses often reflect recommendations by the World Health Organization (WHO)-a process that is cumbersome. The strains of influenza A viruses to be used in vaccine manufacture are not wild-type viruses but rather reassortants that are hybrid viruses containing at least the HA and NA gene segments from the target strains and other gene segments from the master strain, PR8, which has properties of high growth in fertilized hen's eggs. This additional process requires more time and quality control, and specifically for HPAI viruses, it is a process that may fail because of the nature of those viruses. In contrast, viral-vectored vaccines are relatively easy to manipulate and produce, and have well-established safety profiles. There are several viral-based vectors currently employed as antigen delivery systems, including poxviruses, adenoviruses baculovirus, paramyxovirus, rhabdovirus, and others; however, the majority of human clinical trials assessing viral-vectored influenza vaccines use poxvirus and adenovirus vectors. While each of these vector approaches has unique features and is in different stages of development, the combined successes of these approaches supports the virus-vectored vaccine approach as a whole. Issues such as preexisting immunity and cold chain requirements, and lingering safety concerns will have to be overcome; however, each approach is making progress in addressing these issues, and all of the approaches are still viable. Virus-vectored vaccines hold particular promise for vaccination with universal or focused antigens where traditional vaccination methods are not suited to efficacious delivery of these antigens. The most promising approaches currently in development are arguably those targeting conserved HA stalk region epitopes. Given the findings to date, virus-vectored vaccines hold great promise and may overcome the current limitations of influenza vaccines. | How is the TIV efficacy measured? | false | 1,261 | {
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1,620 | A missense mutation in Katnal1 underlies behavioural, neurological and ciliary anomalies
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5761721/
SHA: f4cebabd74b16e710fb41a737d8ef84b7d565d8d
Authors: Banks, G; Lassi, G; Hoerder-Suabedissen, A; Tinarelli, F; Simon, M M; Wilcox, A; Lau, P; Lawson, T N; Johnson, S; Rutman, A; Sweeting, M; Chesham, J E; Barnard, A R; Horner, N; Westerberg, H; Smith, L B; Molnár, Z; Hastings, M H; Hirst, R A; Tucci, V; Nolan, P M
Date: 2017-04-04
DOI: 10.1038/mp.2017.54
License: cc-by
Abstract: Microtubule severing enzymes implement a diverse range of tissue-specific molecular functions throughout development and into adulthood. Although microtubule severing is fundamental to many dynamic neural processes, little is known regarding the role of the family member Katanin p60 subunit A-like 1, KATNAL1, in central nervous system (CNS) function. Recent studies reporting that microdeletions incorporating the KATNAL1 locus in humans result in intellectual disability and microcephaly suggest that KATNAL1 may play a prominent role in the CNS; however, such associations lack the functional data required to highlight potential mechanisms which link the gene to disease symptoms. Here we identify and characterise a mouse line carrying a loss of function allele in Katnal1. We show that mutants express behavioural deficits including in circadian rhythms, sleep, anxiety and learning/memory. Furthermore, in the brains of Katnal1 mutant mice we reveal numerous morphological abnormalities and defects in neuronal migration and morphology. Furthermore we demonstrate defects in the motile cilia of the ventricular ependymal cells of mutants, suggesting a role for Katnal1 in the development of ciliary function. We believe the data we present here are the first to associate KATNAL1 with such phenotypes, demonstrating that the protein plays keys roles in a number of processes integral to the development of neuronal function and behaviour.
Text: Microtubule severing enzymes are a family of AAA-ATPase proteins that participate in fundamental cellular processes such as mitosis, ciliary biogenesis and growth cone motility. In neurons this family is known to control such processes as axonal elongation 1 and synaptic development. 2 In addition, mutations in microtubule severing enzyme genes SPG4, KATNB1 and KATNAL2 are associated with hereditary spastic paraplegia, cerebral malformations and autism, respectively, [3] [4] [5] [6] and mutations in Fign cause a range of phenotypes in mice. 7 Currently the microtubule severing enzyme KATNAL1 is poorly characterised and it is not yet understood how the enzyme functions in the nervous system. Recent evidence from genetic characterisation of human patients suggests that haploinsufficiency of KATNAL1 is linked with a number of symptoms including intellectual disability (ID) and craniofacial dysmorphologies. 8, 9 It is also notable that a very rare KATNAL1 mutation has been associated with schizophrenia 10 (http://atgu.mgh.harvard.edu/~spurcell/genebook/gene book.cgi?user = guest&cmd = verb-gene&tbox = KATNAL1) and that Peters syndrome and autism have both been associated with the chromosomal region containing the KATNAL1 locus. 11, 12 Although such association studies strongly suggest that KATNAL1 plays a fundamental role in the central nervous system (CNS), additional studies using cellular or animals models are required to understand how the gene may be causative for disease. Here we present the first study describing neural and behavioural deficits associated with a loss of function allele of Katnal1 in the mouse. This mutant mouse line was independently identified in two parallel phenotyping screens, which demonstrated that mutant mice showed both male sterility and circadian phenotypes. Subsequent behavioural investigations demonstrated that this mutation is associated with anxiety and memory deficits. Underlying these behavioural phenotypes, we identified histopathological abnormalities in the brains of Katnal1 1H/1H mutants, including disordered cellular layers in the hippocampus and cortex and substantially larger ventricles. Further investigations demonstrated that Katnal1 1H/1H mice show neuronal migration and ciliary function deficits suggesting KATNAL1 plays an essential role in these processes. These findings are the first to our knowledge to conclusively show that mutations in Katnal1 lead to behavioural and neuronal disturbances and provide insight regarding the clinical associations that have been linked to the gene. performed on mouse cohorts that were partially or completely congenic on the C57BL/6 J background.
Circadian wheel running was performed as previously described. 14 Sleep assessment by electroencephalography and electromyography Electroencephalography and electromyography was performed as previously described. 15 Behavioural phenotyping Spontaneous alternation. Mice were placed in a walled T-maze (black polyvinyl chloride, lined with sawdust; stem = 88 × 13 cm; arms = 32 × 13 cm) and allowed to enter a goal arm of their choice. The mouse was confined in the goal arm for 30 s, before being allowed a second free choice of goal arm. An alternation was recorded if the second choice differed from that of the first. One trial was performed per day for 10 days.
Open field behaviour. Mice were placed into a walled arena (grey polyvinyl chloride; 45 × 45 cm) and allowed to explore for 20 min. Animals were monitored by EthoVision XT analysis software (Noldus, Wageningen, Netherlands).
Video tracking in the home cage. Activity in the home cage was recorded by video tracking as previously described. 16 Morris water maze and ultrasonic vocalisation. These tests were performed as previously described. 17 Brain histology and immunofluorescence Brains were mounted in OCT (VWR) and 12 μm coronal sections taken. Sections were stained with hematoxylin and eosin, or immunolabelled following standard protocols.
In vivo neuronal migration assessment was performed as previously described 18 using embryos at either E13 or E15 (three mothers per age group) and pups at P9. Cell counts were performed using ImageJ (NIH, Bethesda, MD, USA).
In vitro neuronal migration assessment was performed using a Boyden chamber migration protocol as previously described. 19 Micro-computed tomography scanning Micro-computed tomography was performed using a Skyscan 1172 at 90 kV, 112 μA using an aluminium and copper filter, a rotation step of 0.250 degrees and a pixel size of 4.96 μm.
Segmentation, volume calculation and 3D modelling was performed using ITK-SNAP version 3.0.0 (ref. 20) and 3DSlicer. 21 Golgi-Cox staining of neurons Golgi-Cox neuronal staining was performed using the FD Rapid GolgiStain Kit (FD NeuroTechnologies, Columbia, MD, USA). Neurons were analysed using ImageJ.
Brains from P2 mice were dissected, and the dorsal cerebral half was sectioned (250 μm) through the floor of the lateral and 3rd ventricle using a vibratome. Ciliary beat frequency and pattern was analysed as previously described. 22 Electron microscopy For Scanning Electron Microscopy the ependymal lining of the lateral ventricle was fixed in 2.5% glutaraldehyde, 2% paraformaldehyde in 0.1 M phosphate buffer, incubated in 2% osmium tetroxide, and dehydrated through ethanol solutions. Samples were critical point dried using an Emitech K850 (Quorum Technologies, East Sussex, UK), coated with platinum using a Quorom Q150R S sputter coater (Quorum Technologies). and visualised using a JEOL LSM-6010 scanning electron microscope (Jeol, Herts, UK).
Transmission electron microscopy was performed as previously described. 22 Statistical analysis Data was analysed using two-tailed students T test or AVOVA using SPSS (IBM) or GraphPad Prism 5.0 (GraphPad Software, La Jolla, CA, USA). Significance level for all analysis was set at Po 0.05. All graphs are presented showing mean ± s.e.m.
Additional and more detailed methods can be found in supplementary information.
Identification and cloning of the Katnal1 1H mutation To identify novel gene mutations affecting circadian behaviour we undertook a circadian running wheel screen of pedigrees of N-ethyl-N-nitrosourea mutagenised mice. 13 In one pedigree 17.65% of animals showed a short circadian period in constant darkness (o 23 h observed in 12 out of 68 animals screened). An outcross using an affected female produced no affected animals (33 animals screened). In subsequent intercross screens 15.5% of animals were affected (53 out of 342 animals screened), suggesting that the pedigree carries a mutation causing a recessive circadian phenotype which is 60% penetrant. We found no gender bias in affected animals (proportion of affected animals: male = 47.2%; female = 52.8%).
Concurrently a male sterility phenotype was identified within the same pedigree. 23 Genome-wide SNP linkage analysis mapped the circadian and sterility phenotypes to the same region on chromosome 5 and subsequent sequencing identified the causative mutation as a T to G single point mutation within exon seven of the Katnal1 gene. For full details of mapping and identification of the mutation see reference 23. This mutant allele was designated Katnal1 1H , and results in a leucine to valine substitution at residue 286 of the protein. In vitro functional analysis demonstrated that the mutation is a recessive loss-offunction allele. 23 3D modelling of the protein suggests that this loss of function is due to hydrophobic changes in the AAA domain of the enzyme (Supplementary Figure S1 ). Genotyping confirmed that the mutation was homozygous in affected circadian animals and wild type or heterozygous in unaffected animals, confirming that Katnal1 1H was causative for the circadian phenotype.
Circadian and sleep anomalies in Katnal1 1H/1H mice More extensive circadian phenotyping conducted on Katnal1 homozygotes (Katnal1 1H/1H ) and wild-type littermates (Katnal1 +/+ ) confirmed that Katnal1 1H/1H mice had a shorter free-running circadian period (Figures 1a-c) and furthermore revealed that Katnal1 1H/1H animals were more active in the light phase of the light/dark cycle (Figure 1d ), showed increased anticipation of light to dark transitions and greater shift in activity onset when released from light/dark cycles to constant darkness ( Figure 1e ). Data and cohort details are given in Supplementary Table S1 . Bioluminescence recordings performed using PER2::LUCIFERASE reporter mice carrying the Katnal1 1H mutation revealed that these circadian changes were not due to changes to the core molecular clock of the suprachiasmatic nucleus (the site of the master circadian clock in the brain; Supplementary Figure S2 ).
Circadian disruptions are often associated with deficits in sleep homeostasis. Therefore to complement our circadian studies we conducted wireless electroencephalography recordings over a baseline period of 24 h and following a 6 h period of sleep deprivation. A detailed summary of electroencephalography analysis is given in Supplementary Table S1. Compared to wildtype littermates, the non-REM delta power of Katnal1 1H/1H mice was higher in the dark phase of baseline sleep (mixed ANOVA, interaction factors 'genotype X time, F(1,88) = 8.91, P = 0.0175) ( Figure 1f ) and in both the light and dark phases of recovery sleep (mixed ANOVA, interaction factors 'genotype X time', F(1,136) = 11.93, P = 0.0086; Figure 1g ). All other sleep parameters were unaffected in Katnal1 1H/1H animals.
Katnal1 1H/1H mice display a spectrum of behavioural deficits Human patients carrying a heterozygous deletion incorporating the Katnal1 locus show a number of cognitive deficits including ID and a delay in language acquisition. 8, 9 We therefore investigated whether these deficits were modelled in Katnal1 1H/1H mice by subjecting animal cohorts to a battery of behavioural tests. Data and cohort details are given in Supplementary Table S2 .
Both working memory and spatial memory were significantly poorer in Katnal1 1H/1H mice, as evidenced by reduced spontaneous alternations in a T-maze ( Figure 2a ) and in the Morris water maze where mutants take longer to find the platform in acquisition trials (Figure 2b Compared to wild-type littermates, Katnal1 1H/1H animals have a shorter period (c), are more active in the light phase of the light/dark cycle (d) and show an earlier onset of activity in light/dark transitions and in the transition from light/dark cycles to constant darkness (e). In EEG recordings during sleep, Katnal1 1H/1H mice show increased non-REM delta power in the dark phase of the light/dark cycle (f) and following sleep deprivation (g). *P ⩽ 0.05; **P ⩽ 0.01; ***P ⩽ 0.001. EEG, electroencephalography; DD, constant darkness; LD, light/dark cycle. type = 164 ± 12 m, Katnal1 1H/1H = 243 ± 20 m, P = 0.02; distance travelled in periphery of open field: wild type = 4.3 ± 0.2 m, Katnal1 1H/1H = 6 ± 0.3 m, P = 0.004). Conversely when mouse activity was recorded in the home cage, we found no difference between genotypes (distance travelled over 24 h: wild type = 399 ± 77 m, Katnal1 1H/1H = 418 ± 41 m, P = 0.833) suggesting that the former activity differences were due to the novel environment of the open field rather than generalised hyperactivity in Katnal1 1H/1H animals. Finally, in certain conditions (such as maternal separation) mice emit ultrasonic vocalisations (USVs). To test whether Katnal1 1H/1H animals vocalised differently to wild types, we separated pups at postnatal days 7-8 (the age at which mice show peak of USV emission 24 ) and recorded their USVs. In these tests, compared to wild types, Katnal1 1H/1H pups produced fewer ( Figure 2g ) and shorter (Figure 2h ) vocalisations, containing fewer phrases (Figure 2i ). Gross brain morphological abnormalities in Katnal1 1H/1H mice Since we observed a number of behavioural phenotypes in Katnal1 1H/1H mice, we performed histological analysis to ascertain whether differences in brain histology underlied these behaviours. Data and cohort details are given in Supplementary Table S3 . Analysis of hematoxylin and eosin stained brain sections revealed that, compared to wildtype littermates, Katnal1 1H/1H animals had less tightly packed pyramidal cell layers in the hippocampus (Figures 3a and b) and a narrower cortical layer 1 and wider cortical layer 6 (Figures 3c-e) . To confirm these cortical layer differences, immunofluorescence was performed using the (Figures 3l and m) . Quantification of fluorescence intensity demonstrated that in Katnal1 1H/1H cortex both calbindin and CUX1 labelling was more intense closer to the cortical surface, which is consistent with the reduction in the size of layer 1 (two-way analysis of variance (ANOVA), interaction factors 'genotype X distance of fluorescence from cortical surface', calbindin: F(75,988) = 16.8, P o 0.0005; CUX1: F(93,372 = 2.17, P = 0.001; Figures 3h and k) . Similar quantification revealed that FOXP2 labelling extended further from layer 6b (as labelled by CTGF) in the Katnal1 1H/1H cortex, which is consistent with an increase in the size of layer 6 (two-way ANOVA, interaction factors 'genotype X distance of fluorescence from CTGF labelling:' F(93,372) = 1.32, P = 0.038; Figure 3n ). Finally, three dimensional models of the ventricular system were constructed from brain micro-computed tomography scans (Figures 3o and p) . Volumetric analysis revealed that Katnal1 1H/1H mice had substantially larger ventricles than wild types (Figure 3q ).
Neuronal migration and morphology defects in Katnal1 1H/1H brains The histological phenotypes of Katnal1 1H/1H mouse brains described above are suggestive of neuronal migration defects. 18 We therefore investigated whether Katnal1 1H/1H mice showed abnormal neuronal migration using BrdU labelling of E13 and E15 embryos and quantified labelled cells in the cortex of P9 pups (described in reference 18). At both ages Katnal1 1H/1H animals had greater numbers of labelled neurons in bins close to the cortical surface neurons positioned closer to the cortical surface compared to wild type. To confirm these results we used a Boyden chamber 19 and performed in vitro neuronal migration analysis in E13.5 primary cortical neuronal cultures. Here we found that a greater proportion of Katnal1 1H/1H cortical neurons migrated to the base of the cell culture insert compared to wildtype controls (Supplementary Figure S3) .
Since in both BrdU labelling and the Boyden assay neurons from Katnal1 1H/1H animals migrated further than those of wild-type littermates, these results suggest that Katnal1 1H/1H cortical neurons show defects in the termination of cortical neuronal migration. Given its role in cytoskeletal organisation, we also hypothesised that neuronal morphology is modulated by Katnal1. Analysis of golgi stained neurons from layers 2-3 of the cortex (Figures 4g and i) demonstrated that, compared to wild-type littermates, Katnal1 1H/1H neurons had larger soma (Figure 4k) , and shorter and thinner axons (Figures 4l and m) (data and cohort details are given in Supplementary Table S3 ). Furthermore, analysis at higher magnification (Figures 4h and j) , demonstrated that the number of synaptic spines on Katnal1 1H/1H neurons was significantly reduced compared to wild type (Figure 4n ).
Recent studies have demonstrated that mutations in some microtubule severing enzymes can cause defects in cilia. 5 Since such ciliary defects could underlie the phenotypes described above we studied the motile cilia of the ependymal lining of the lateral ventricle in sections of postnatal day 2 mouse brains from both Katnal1 1H/1H (n = 4) and wild-type animals (n = 3). We found that the ciliary beat frequency (CBF) of Katnal1 1H/1H animals was significantly attenuated compared to wild-type (CBF: wildtype = 22.39 ± 0.94 Hz, Katnal1 1H/1H = 14.25 ± 0.92 Hz, P = 0.0001; Figure 5a , Supplementary Movies S1). This reduction in CBF in Katnal1 1H/1H animals was also associated with an increased proportion of cilia with an abnormal beat pattern (ciliary dyskinesia) (proportion of dyskinetic cilia: wild type = 17%, Katnal1 1H/1H = 75%) (Figure 5b and Supplementary Movies S1). Visual inspection of the cilia identified a number of ciliary abnormalities such as a swollen ciliary tip (Supplementary Movie S3) or extremely long cilia (Supplementary Movie S4) scattered throughout the field of cilia in Katnal1 1H/1H ventricles. These abnormalities were observed in approximately 25% of Katnal1 1H/1H brain slices. The abnormal cilia always showed a dyskinetic beat pattern and lower beat frequency. To further investigate ciliary morphology we performed scanning electron microscopy upon the ependymal lining of the lateral ventricles of both Katnal1 1H/1H (n = 3) and wild-type animals (n = 3; Figures 5c and d) . Cilia measurements showed no significant differences in average cilia length between genotypes (average cilia length: wild type = 6.22 ± 0.86 μm, Katnal1 1H/1H = 6.54 ± 0.94 Hz, P = 0.303). However in Katnal1 1H/1H samples we noted the presence of both long and short cilia (Figures 5e and f ; defined as two standard deviations longer or shorter than the average cilia length) that were not present in wild-type samples. In addition, inspection of Katnal1 1H/1H cilia identified ciliary abnormalities including bifurcated cilia (Figure 5g) , abnormal kinks and bends in the cilia (Figure 5h ) and swellings along the length of the cilia (Figure 5i ). Transmission electron microscopy of ependymal cilia found that vesicular aggre- Katnal1 disruption affects CNS functions G Banks et al gates were present within the ciliary swellings described above (Figure 5j ). Although these abnormalities were present in only a small proportion (o1%) of Katnal1 1H/1H cilia, they were notably absent from wild-type cilia.
Microtubule severing enzymes play diverse roles in the nervous system. 1, 2 However, at present the microtubule severing enzyme Katnal1 is poorly defined in the context of CNS development and function. Here we present a detailed phenotypic analysis of Katnal1 1H and show that the mutation is associated with changes in circadian rhythms, sleep and behaviour. Furthermore we demonstrate that defects in brain histopathology, neuronal migration and neuronal morphology underlie these phenotypes. Finally we also demonstrate that Katnal1 1H causes a range of defects in the motile cilia of ventricular ependymal cells. The data we present here are the first to associate KATNAL1 with such dysfunctions with important implications for clinical association studies.
The Katnal1 1H mutation was initially identified with a circadian deficit including a short free-running period and advanced activity onset. However subsequent ex vivo experiments using SCN slices of animals carrying the PER2::LUC reporter gene demonstrated no defects in SCN cellular rhythms, suggesting that the core circadian clock was unperturbed by the mutation. Phenotypes in circadian running wheel rhythms that are not associated with changes to the core clock mechanism have also been reported in mouse models of schizophrenia. 25 Here it has been suggested that the wheel running changes observed are the result in defects in output pathways from the SCN circadian clock. Similarly, in Katnal1 1H/1H mice we hypothesise that the defects we demonstrate in neuronal anatomy and neuronal morphology may disrupt output signals from the SCN. Alternatively given that various neuropeptides such as oxytocin are secreted in a circadian manner from ependymal cells lining the third ventricle of the brain, 26 altered ventricular morphology and ciliary function in Katnal1 1H/1H mice may disrupt the circulation of factors secreted by the ciliated ventricular ependymal cells and contribute to the disruption of the behavioural rhythms observed.
The behavioural consequences of microtubule severing enzyme dysfunction in mouse models have been poorly characterised. Currently the phenotypes described are limited to motor dysfunction in mice lacking the Spg4 gene 27 and head shaking and circling in the Fign mutant. 7, 28, 29 In contrast, here we demonstrate that loss of function of Katnal1 is associated with a range of behavioural phenotypes, including changes in circadian activity, poor learning and memory, hyperactivity in a novel environment (the open field) and deficits in USVs. Notably the learning and memory, anxiety and vocalisation phenotypes reprise the clinical symptoms of ID, increased anxiety in novel situations and delays in language acquisition reported in human patients who carry microdeletions incorporating haploinsufficiency of KATNAL1. 8, 9 While it is also worth noting that mutant mice spend more time the centre of the open field than wild types (implying that Katnal1 1H/1H animals show reduced anxiety), we suggest that this result is confounded by the hyperactivity in novel environments phenotype we also describe in mutant mice. This observation is backed up by the fact that mutant animals showed increased activity in all regions of the open field rather than just the anxiolytic periphery. Here we also highlight defects in Katnal1 1H/1H mice such as compromised neuronal migration and morphology which may underpin such phenotypes. In Drosophila, the homologue of Katnal1 (kat-60L1) has been demonstrated to play a critical role in neuronal morphology during development, 30 however the data that we present here is the first to demonstrate a similar phenotype in mammals and furthermore suggests how subtle perturbations to KATNAL1 function may contribute to specific neural and behavioural conditions. For example, defects in neuronal migration, synaptic spines and neuronal morphology such as those we have demonstrated here, have been suggested to underpin ID in conditions such as lissencephaly, 18 Down's syndrome 31 and Rett syndrome. 32 While we are not suggesting that Katnal1 is causative for these conditions, similarities in symptoms and neuronal phenotypes between these conditions and those linked to Katnal1 dysfunction should be appreciated. Furthermore a rare mutation in KATNAL1 has been associated with schizophrenia 10 (http://atgu.mgh.harvard.edu/~spurcell/gene book/genebook.cgi?user = guest&cmd = verb-gene&tbox = KATNAL1) and KATNAL1 has been shown to interact with the schizophrenia associated gene DISC1. 33 In line with these observations we note that increases in ventricular volume and reductions in synaptic spines have been reported in schizophrenic patients 34, 35 and our data demonstrates the same phenotypes in Katnal1 1H/1H mice. Thus the range of phenotypes associated with defects in the function of Katnal1 strongly suggests that the gene should be considered in the pathology of disorders such as ID and schizophrenia.
We do note one key genetic difference between the human patients and Katnal1 1H/1H animals. While the human patients were all heterozygous for the Katnal1 deletion, we found no phenotype in heterozygous mutant mice (data not shown) suggesting that while haploinsufficiency is causative for phenotypes in humans, mice require complete loss of KATNAL1 function to show similar effects. A similar discrepancy between humans and mice has also been noted for the intellectual disability candidate gene CTNNB1. 17 While heterozygous loss of function mutations in CTNNB1 are causative for intellectual disability in humans, conditional knock outs for CTNNB1 have no reported behavioural or craniofacial phenotypes. 36, 37 These differences demonstrate that while mouse models of intellectual disability are of great use in our understanding of the causative mechanisms which underlie the condition, there are still genetic and neurodevelopmental differences between species which also must be taken into account. We also note that while the Katnal1 1H mutation shows a loss of catalytic function in both HEK293 cells and Sertoli cells, 23 this loss of function has not been verified in neuronal cells. However, given that our data demonstrates that the Katnal1 1H mutation lies in an essential catalytic domain and that we show neuronal phenotypes in Katnal1 1H/1H mice, we would expect to see the same loss of catalytic function in neurons.
The data we present here also demonstrate defects in motile cilia in Katnal1 1H/1H mice. Ciliary disruptions in humans (ciliopathies) include Bardet-Biedl and Joubert syndrome. 38 While there is currently limited data available regarding the behavioural phenotypes of mouse models of ciliopathies, we note that ciliary dysfunction in mice has been linked with learning and memory 39 and vocalisation phenotypes, 40 both of which were disturbed in the Katnal1 1H/1H mice described here. It is also notable that the neuronal migration and enlarged ventricle phenotypes that we describe in Katnal1 1H/1H mice recapitulate features associated with known ciliopathy gene mutations. [41] [42] [43] [44] Furthermore in Bardet-Biedl syndrome mouse models ciliary defects such as reduced CBF 45 and structural defects such as abnormal lengthening and swellings along their length 41 have been described, that are similar to those we describe in Katnal1 1H/1H mice. There is strong evidence that ciliopathy associated genes play a number of roles in neuronal development by affecting processes such as progenitor proliferation or maintenance of the radial glia scaffold. 43 However it is also clear that defects in microtubule organisation also affect synaptic structure. 2 At present it is difficult to disentangle the relative contributions of defects in microtubule severing and ciliary abnormalities to the overall phenotypes we observe in Katnal1 1H/1H mice. Further investigations are required to clarify the impacts of these two processes. However it is notable that while defects in cilia structure may contribute to the phenotypes we describe in Katnal1 1H/1H mice, they are far less prominent in Katnal1 1H/1H mice than in other mouse ciliopathy models, 41 suggesting that the ciliary component of KATNAL1 dysfunction may be mild compared to other ciliopathies. Similarly while hydrocephalus has been suggested to be a component of some ciliopathy mouse models, 46 Katnal1 1H/1H mice showed only increased ventricle size rather than an increased incidence of hydrocephalus, further suggesting the ciliary defects in these animals are mild compared to other ciliopathies.
In summary the data presented here clearly demonstrate that KATNAL1 plays an important role in a variety of neuronal processes including neuronal migration, neuronal morphology and ependymal ciliary function. The downstream effect of these defects leads in turn to a number of behavioural changes including in learning and memory, reaction to anxiogenic situations and circadian rhythms. These data therefore highlight how perturbations in KATNAL1 may play a role in neuronal dysfunction and demonstrates that the enzyme is a novel candidate in the study of behavioural and neurodevelopmental disorders.
The authors declare no conflict of interest. | What genetic mutation is associated with cerebral malformations? | false | 927 | {
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1,560 | Relationship between hepcidin and oxidant/antioxidant status in calves with suspected neonatal septicemia
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5146304/
SHA: efcd7d171bb51acf2ef0a631901900497957a3be
Authors: Erkilic, E. E.; Erdogan, H. M.; Ogun, M.; Kirmizigul, A. H.; Gokce, E.; Kuru, M.; Kukurt, A.
Date: 2016-11-14
DOI: 10.14202/vetworld.2016.1238-1241
License: cc-by
Abstract: AIM: This study has been conducted for the purpose of determining serum hepcidin, total antioxidant status (TAS), total oxidant status (TOS), and Fe levels in calves with suspected neonatal septicemia before and after treatment and the clinical significance of hepcidin in calves with suspected neonatal septicemia. MATERIALS AND METHODS: The study material consisted of 15 calves of different ages and sexes brought to the Training, Research and Application Center at the Kafkas University Faculty of Veterinary Medicine with suspected neonatal septicemia. 8.5 mL of blood was drawn from the jugular vein of each animal into coagulant tubes before and after treatment for one-off biochemical analyses and centrifuged. After this, the serum was separated. Hepcidin, TAS, TOS, and Fe levels in the serum were measured. RESULTS: While pre-treatment hepcidin levels were 58.42±3.46 ng/mL, post-treatment levels were 46.87±2.98 ng/mL (p<0.05). Pre-treatment Fe levels were 60.13±7.27 µg/dl, while post-treatment levels were 83.1±8.09 µg/dl (p<0.05). The changes in the TAS and TOS levels were also found to be statistically significant. CONCLUSION: In light of the fact that hepcidin plays a role function in the regulation of Fe as well as the fact that Fe is a significant nutritional source for many microorganisms, it was concluded that hepcidin may play a significant role in nutritional immunity and the pathogenesis of diseases.
Text: Neonatal calf septicemia causes high morbidity and mortality and is one of the leading and most significant difficulties in raising cattle. Calf septicemia is the main cause of death in the neonatal period [1] . Its etiology involves bacteria (commonly Escherichia coli), viruses (rota and coronavirus), parasites, and other factors. As the disease progresses quickly and is lethal, diagnosis and treatment should be initiated as quickly as possible [2] .
Hepcidin is a low molecular weight, antimicrobial peptide hormone and was first discovered in human urine [3] . It is produced by the liver as a firstline response to inflammatory reactions and high Fe concentrations [4, 5] . Hepcidin plays a fundamental role in the regulation of Fe metabolism [6] , which is a part of foundational cellular functions and thus of vital importance. On the other hand, by participating in redox reactions leading to the production of reactive oxygen species (ROSs), Fe also causes oxidative stress. Therefore, Fe has been regarded as a potentially toxic element to cells [7] . Fe also plays an important role in pathogenesis of bacterial infections as bacteria utilize Fe for survival, growth and proliferation; therefore, it is of paramount importance to control the Fe metabolism [6] . It is well known that the abundance of Fe suppresses defense system leading host vulnerable to infections. There is a significant relationship between Hepcidin, Fe metabolism, inflammation, and the immune system. The fact that hepcidin plays an active role in the regulation of Fe release from macrophages and in the control of excessive Fe absorption from the duodenum is well documented [6] . Hepcidin is a part of the natural defense mechanism, thus it limits the amount of Fe that can be utilized by pathogens [8] . In inflammatory conditions, hypoferremia is an important first-line protective mechanism in response to infections [9] . Fe also participates in redox reactions, causing the production of ROS, and thus leading to oxidative stress [7] . Free radicals play a significant role in the pathogenesis of many diseases [10] . Newborns are subject to oxidative stress during birth. It is also reported that in livestock diseases, especially enteritis and pneumonia, antioxidant capacity is efficacious [11] .
This study was designed to determine the clinical significance of hepcidin in calves with suspected neonatal septicemia by evaluating serum hepcidin, total antioxidant status (TAS), total oxidant status (TOS), and Fe levels in calves suspected of neonatal septicemia before and after treatment.
This study was conducted after obtaining approval from the Mehmet Akif Ersoy University Animal Experiments Local Ethics Committee (MAKU-HADYEK-Submission: 2014/77).
The study consisted of 15 calves with suspected neonatal septicemia aged between 1 and 10 days old admitted to the Teaching Hospital of Veterinary Medicine. Suspected septicemia was diagnosed based on clinical (diarrhea, weakness in or absence of sucking reflex, the calf being in a supine position on the ground or being unable to stand, severe dehydration, abnormal rectal temperature [hypo-or hyperthermia], mucosal hyperemia, and full sclera) and hematological (increase in white blood cell [WBC] count) examinations; the animals were suspected to have septicemia [12, 13] . The animals were given standard treatment (antibiotic, nonsteroidal anti-inflammatory drugs, vitamin C, fluid therapy, and intestinal astringent). For determination of serum hepcidin, TAS, TOS, Fe levels, and hematological parameters; blood samples were taken before and after treatment in all cases. 8.5 mL of blood was taken from the jugular vein of each animal into coagulant tubes for biochemical analysis, and 3 mL blood was taken into ETDA tubes for hematological analysis. Samples were centrifuged at 3000 rpm for 10 min, and the serum was harvested and kept at −20°C until the analysis. Serum hepcidin (Mybiosource ® ), TAS (Rel Assay Diagnostics ® ), and TOS (Rel Assay Diagnostics ® ) were determined using commercial ELISA kits, and Fe value was measured spectrophotometrically. Hematological (WBC, lymphocyte [LYM], red blood cells [RBC], mean corpuscular volume (MCV), and hematocrit [HCT]) analysis was performed on blood counter (VG-MS4e ® , Melet Schloesıng, France).
The results were evaluated using the t-test in the SPSS ® (SPSS 20, USA) statistical package program to determine the differences between values before and after treatment.
Calves with suspected septicemia exhibited clinical signs of loss of appetite, fatigue, indifference to surroundings, reduced/absence of sucking reflex, cool extremities, inability to stand, diarrhea, eye sinking into their sockets, and hyperemia in the conjunctiva. The average body temperature, heart rate, and respiratory rates of the animals were 37.18±0.13°C, 104±4.33/min, and 28.86±0.75/min pre-treatment; and 38.54±0.1°C, 107.53±2.20/min and 26.40±0.36/min post-treatment, respectively.
The changes in hepcidin, TAS, TOS and Fe levels in the calves with suspected septicemia before and after treatment are given in Table- 1. After treatment, serum hepcidin and TOS levels were significantly lower than before treatment in calves. On contrary, serum TAS and Fe levels were significantly higher than before treatment (Table-1 ).
The treatment of calves resulted in significant changes in the hematological parameters that were examined except for RBC. The WBC count, LYM count, MCV and HCT significantly changed after treatment when compared to values obtained before treatment (Table-2 ).
This study aimed to determine the clinical importance or use of hepcidin by comparing the values of serum hepcidin, TAS, TOS and Fe levels in calves with suspected neonatal septicemia before and after treatment.
Clinicians rely on clinical and laboratory examinations of patients to form a working diagnosis, so hematological and serum biochemical parameters are usually used for this purpose [14] . The hematological parameters (WBC, HCT, LYM, and MCV) evaluated in this study were comparable with those reported by others in neonatal calves with diarrhea and suspected septicemia [15] [16] [17] . Treatment significantly corrected to normal values the hematological parameters that were examined with the exception of RBC. Pretreatment leukocyte count was high because of the inflammation that occurred in the organism, and that the HCT levels were high due to the dehydration that occurred due to diarrhea. Hepcidin is controlled by the presence of inflammation in the body, Fe storage, and erythropoietic activity in the bone marrow and plays a primary role in the homeostasis of Fe [4] . The increase in tissue and plasma Fe levels stimulates the synthesis of hepcidin and reduces Fe release and enteric Fe absorption from macrophages and hepatocytes [18] . Increased hepcidin concentrations during inflammation and infection reduce serum Fe levels by decreasing Fe release from macrophages and hepatocytes, and thus Fe required for microorganisms and tumor cells is restricted [19] .
Serum hepcidin levels in calves with suspected septicemia were significantly high before treatment when compared to after treatment; also Fe levels were lower before treatment when compared to after treatment in this study. This situation could be related to the interaction between hepcidin and Fe and also gives credence to the role of hepcidin in the hemostasis of Fe during inflammation and infection. As in our study, Fe levels are well known to decrease in diarrheic calves when compared to healthy calves [20, 21] . Although no study exists reporting hepcidin concentration in diseased calves, studies in human subjects show that cord blood hepcidin levels might be an important indicator in diagnosing early-onset of neonatal sepsis. The cord blood hepcidin levels of neonatal infants with sepsis varied between 118.1 and 8400 ng/mL and were significantly higher than the healthy infants [22] . A similar result was reported that hepcidin concentrations in neonatal infants with sepsis were significantly higher than in healthy infants [23] . These findings along with our results add credence to the idea that hepcidin-Fe interaction may play a role in the pathogenesis of septicemia.
The production of free oxygen species causes alterations in protein, lipid, and DNA during oxidative stress and leads to the development of lesions in the organs [24] . Free iron has toxic characteristics as it catalyses the production of ROSs [25] and thus causes oxidative stress [26] . The role of Fe in the development of oxidative stress may once more show the importance of hepcidin, as an important Fe regulator, with regard to enhancing antioxidant capacity through inhibiting utilization of Fe by the organism as well as the host cells.
The antioxidant and oxidative system are in a constant state of balance in the organism. Any event breaking up this balance in favor of the oxidative stress molecules will cause cell damage [27, 28] . The host cells initiate the antioxidant system in case of exposure to oxidative stress [27] . Kabu et al. [16] reported TOS and TAS values in neonatal calves with diarrhea as 13.47±0.81 μmol H 2 O 2 /L and 0.51±0.02 mmol Trolox-equivalent/L, respectively, and treatment of these calves caused changes in these values of 11.21±0.26 μmol H 2 O 2 /L and 0.55±0.02 mmol Troloxequivalent/L, respectively. Studies also reported that parameters used for oxidative stress (malondialdehyde) were higher [29] and antioxidant parameters (superoxide dismutase [21] , TAS) were lower in diarrheic calves [29] . Similarly, in our study, TAS level was significantly lower and TOS level was significantly higher in diarrheic calves before treatment, and treatment caused corrections in these parameters. Decrease in TAS and increase in TOS levels demonstrated that oxidative stress was evident in the diseased calves in our study. Increased TOS and hepcidin levels before treatment are thought that associated with inflammation. After treatment increased TAS and decreased hepcidin levels support this opinion.
Hepcidin may play an important part in non-specific immunity and is a key molecule that plays a role in the pathogenesis of diseases by enhancing the development of antioxidant system. However, more detailed studies are needed on the role of hepcidin in the pathogenesis of septicemia.
This work was carried out in collaboration between all authors. EEE, HME and AHK: Designed the experimental procedures. EEE, EG and MK: Conducted the research work. EEE, AHK, MO and AK: Helped in laboratory analysis. All authors read and approved the final manuscript. | What stimulates the release of hepcidin? | false | 2,133 | {
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2,504 | Respiratory Viral Infections in Exacerbation of Chronic Airway Inflammatory Diseases: Novel Mechanisms and Insights From the Upper Airway Epithelium
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7052386/
SHA: 45a566c71056ba4faab425b4f7e9edee6320e4a4
Authors: Tan, Kai Sen; Lim, Rachel Liyu; Liu, Jing; Ong, Hsiao Hui; Tan, Vivian Jiayi; Lim, Hui Fang; Chung, Kian Fan; Adcock, Ian M.; Chow, Vincent T.; Wang, De Yun
Date: 2020-02-25
DOI: 10.3389/fcell.2020.00099
License: cc-by
Abstract: Respiratory virus infection is one of the major sources of exacerbation of chronic airway inflammatory diseases. These exacerbations are associated with high morbidity and even mortality worldwide. The current understanding on viral-induced exacerbations is that viral infection increases airway inflammation which aggravates disease symptoms. Recent advances in in vitro air-liquid interface 3D cultures, organoid cultures and the use of novel human and animal challenge models have evoked new understandings as to the mechanisms of viral exacerbations. In this review, we will focus on recent novel findings that elucidate how respiratory viral infections alter the epithelial barrier in the airways, the upper airway microbial environment, epigenetic modifications including miRNA modulation, and other changes in immune responses throughout the upper and lower airways. First, we reviewed the prevalence of different respiratory viral infections in causing exacerbations in chronic airway inflammatory diseases. Subsequently we also summarized how recent models have expanded our appreciation of the mechanisms of viral-induced exacerbations. Further we highlighted the importance of the virome within the airway microbiome environment and its impact on subsequent bacterial infection. This review consolidates the understanding of viral induced exacerbation in chronic airway inflammatory diseases and indicates pathways that may be targeted for more effective management of chronic inflammatory diseases.
Text: The prevalence of chronic airway inflammatory disease is increasing worldwide especially in developed nations (GBD 2015 Chronic Respiratory Disease Collaborators, 2017 Guan et al., 2018) . This disease is characterized by airway inflammation leading to complications such as coughing, wheezing and shortness of breath. The disease can manifest in both the upper airway (such as chronic rhinosinusitis, CRS) and lower airway (such as asthma and chronic obstructive pulmonary disease, COPD) which greatly affect the patients' quality of life (Calus et al., 2012; Bao et al., 2015) . Treatment and management vary greatly in efficacy due to the complexity and heterogeneity of the disease. This is further complicated by the effect of episodic exacerbations of the disease, defined as worsening of disease symptoms including wheeze, cough, breathlessness and chest tightness (Xepapadaki and Papadopoulos, 2010) . Such exacerbations are due to the effect of enhanced acute airway inflammation impacting upon and worsening the symptoms of the existing disease (Hashimoto et al., 2008; Viniol and Vogelmeier, 2018) . These acute exacerbations are the main cause of morbidity and sometimes mortality in patients, as well as resulting in major economic burdens worldwide. However, due to the complex interactions between the host and the exacerbation agents, the mechanisms of exacerbation may vary considerably in different individuals under various triggers. Acute exacerbations are usually due to the presence of environmental factors such as allergens, pollutants, smoke, cold or dry air and pathogenic microbes in the airway (Gautier and Charpin, 2017; Viniol and Vogelmeier, 2018) . These agents elicit an immune response leading to infiltration of activated immune cells that further release inflammatory mediators that cause acute symptoms such as increased mucus production, cough, wheeze and shortness of breath. Among these agents, viral infection is one of the major drivers of asthma exacerbations accounting for up to 80-90% and 45-80% of exacerbations in children and adults respectively (Grissell et al., 2005; Xepapadaki and Papadopoulos, 2010; Jartti and Gern, 2017; Adeli et al., 2019) . Viral involvement in COPD exacerbation is also equally high, having been detected in 30-80% of acute COPD exacerbations (Kherad et al., 2010; Jafarinejad et al., 2017; Stolz et al., 2019) . Whilst the prevalence of viral exacerbations in CRS is still unclear, its prevalence is likely to be high due to the similar inflammatory nature of these diseases (Rowan et al., 2015; Tan et al., 2017) . One of the reasons for the involvement of respiratory viruses' in exacerbations is their ease of transmission and infection (Kutter et al., 2018) . In addition, the high diversity of the respiratory viruses may also contribute to exacerbations of different nature and severity (Busse et al., 2010; Costa et al., 2014; Jartti and Gern, 2017) . Hence, it is important to identify the exact mechanisms underpinning viral exacerbations in susceptible subjects in order to properly manage exacerbations via supplementary treatments that may alleviate the exacerbation symptoms or prevent severe exacerbations.
While the lower airway is the site of dysregulated inflammation in most chronic airway inflammatory diseases, the upper airway remains the first point of contact with sources of exacerbation. Therefore, their interaction with the exacerbation agents may directly contribute to the subsequent responses in the lower airway, in line with the "United Airway" hypothesis. To elucidate the host airway interaction with viruses leading to exacerbations, we thus focus our review on recent findings of viral interaction with the upper airway. We compiled how viral induced changes to the upper airway may contribute to chronic airway inflammatory disease exacerbations, to provide a unified elucidation of the potential exacerbation mechanisms initiated from predominantly upper airway infections.
Despite being a major cause of exacerbation, reports linking respiratory viruses to acute exacerbations only start to emerge in the late 1950s (Pattemore et al., 1992) ; with bacterial infections previously considered as the likely culprit for acute exacerbation (Stevens, 1953; Message and Johnston, 2002) . However, with the advent of PCR technology, more viruses were recovered during acute exacerbations events and reports implicating their role emerged in the late 1980s (Message and Johnston, 2002) . Rhinovirus (RV) and respiratory syncytial virus (RSV) are the predominant viruses linked to the development and exacerbation of chronic airway inflammatory diseases (Jartti and Gern, 2017) . Other viruses such as parainfluenza virus (PIV), influenza virus (IFV) and adenovirus (AdV) have also been implicated in acute exacerbations but to a much lesser extent (Johnston et al., 2005; Oliver et al., 2014; Ko et al., 2019) . More recently, other viruses including bocavirus (BoV), human metapneumovirus (HMPV), certain coronavirus (CoV) strains, a specific enterovirus (EV) strain EV-D68, human cytomegalovirus (hCMV) and herpes simplex virus (HSV) have been reported as contributing to acute exacerbations . The common feature these viruses share is that they can infect both the upper and/or lower airway, further increasing the inflammatory conditions in the diseased airway (Mallia and Johnston, 2006; Britto et al., 2017) .
Respiratory viruses primarily infect and replicate within airway epithelial cells . During the replication process, the cells release antiviral factors and cytokines that alter local airway inflammation and airway niche (Busse et al., 2010) . In a healthy airway, the inflammation normally leads to type 1 inflammatory responses consisting of activation of an antiviral state and infiltration of antiviral effector cells. This eventually results in the resolution of the inflammatory response and clearance of the viral infection (Vareille et al., 2011; Braciale et al., 2012) . However, in a chronically inflamed airway, the responses against the virus may be impaired or aberrant, causing sustained inflammation and erroneous infiltration, resulting in the exacerbation of their symptoms (Mallia and Johnston, 2006; Dougherty and Fahy, 2009; Busse et al., 2010; Britto et al., 2017; Linden et al., 2019) . This is usually further compounded by the increased susceptibility of chronic airway inflammatory disease patients toward viral respiratory infections, thereby increasing the frequency of exacerbation as a whole (Dougherty and Fahy, 2009; Busse et al., 2010; Linden et al., 2019) . Furthermore, due to the different replication cycles and response against the myriad of respiratory viruses, each respiratory virus may also contribute to exacerbations via different mechanisms that may alter their severity. Hence, this review will focus on compiling and collating the current known mechanisms of viral-induced exacerbation of chronic airway inflammatory diseases; as well as linking the different viral infection pathogenesis to elucidate other potential ways the infection can exacerbate the disease. The review will serve to provide further understanding of viral induced exacerbation to identify potential pathways and pathogenesis mechanisms that may be targeted as supplementary care for management and prevention of exacerbation. Such an approach may be clinically significant due to the current scarcity of antiviral drugs for the management of viral-induced exacerbations. This will improve the quality of life of patients with chronic airway inflammatory diseases.
Once the link between viral infection and acute exacerbations of chronic airway inflammatory disease was established, there have been many reports on the mechanisms underlying the exacerbation induced by respiratory viral infection. Upon infecting the host, viruses evoke an inflammatory response as a means of counteracting the infection. Generally, infected airway epithelial cells release type I (IFNα/β) and type III (IFNλ) interferons, cytokines and chemokines such as IL-6, IL-8, IL-12, RANTES, macrophage inflammatory protein 1α (MIP-1α) and monocyte chemotactic protein 1 (MCP-1) (Wark and Gibson, 2006; Matsukura et al., 2013) . These, in turn, enable infiltration of innate immune cells and of professional antigen presenting cells (APCs) that will then in turn release specific mediators to facilitate viral targeting and clearance, including type II interferon (IFNγ), IL-2, IL-4, IL-5, IL-9, and IL-12 (Wark and Gibson, 2006; Singh et al., 2010; Braciale et al., 2012) . These factors heighten local inflammation and the infiltration of granulocytes, T-cells and B-cells (Wark and Gibson, 2006; Braciale et al., 2012) . The increased inflammation, in turn, worsens the symptoms of airway diseases.
Additionally, in patients with asthma and patients with CRS with nasal polyp (CRSwNP), viral infections such as RV and RSV promote a Type 2-biased immune response (Becker, 2006; Jackson et al., 2014; Jurak et al., 2018) . This amplifies the basal type 2 inflammation resulting in a greater release of IL-4, IL-5, IL-13, RANTES and eotaxin and a further increase in eosinophilia, a key pathological driver of asthma and CRSwNP (Wark and Gibson, 2006; Singh et al., 2010; Chung et al., 2015; Dunican and Fahy, 2015) . Increased eosinophilia, in turn, worsens the classical symptoms of disease and may further lead to life-threatening conditions due to breathing difficulties. On the other hand, patients with COPD and patients with CRS without nasal polyp (CRSsNP) are more neutrophilic in nature due to the expression of neutrophil chemoattractants such as CXCL9, CXCL10, and CXCL11 (Cukic et al., 2012; Brightling and Greening, 2019) . The pathology of these airway diseases is characterized by airway remodeling due to the presence of remodeling factors such as matrix metalloproteinases (MMPs) released from infiltrating neutrophils (Linden et al., 2019) . Viral infections in such conditions will then cause increase neutrophilic activation; worsening the symptoms and airway remodeling in the airway thereby exacerbating COPD, CRSsNP and even CRSwNP in certain cases (Wang et al., 2009; Tacon et al., 2010; Linden et al., 2019) .
An epithelial-centric alarmin pathway around IL-25, IL-33 and thymic stromal lymphopoietin (TSLP), and their interaction with group 2 innate lymphoid cells (ILC2) has also recently been identified (Nagarkar et al., 2012; Hong et al., 2018; Allinne et al., 2019) . IL-25, IL-33 and TSLP are type 2 inflammatory cytokines expressed by the epithelial cells upon injury to the epithelial barrier (Gabryelska et al., 2019; Roan et al., 2019) . ILC2s are a group of lymphoid cells lacking both B and T cell receptors but play a crucial role in secreting type 2 cytokines to perpetuate type 2 inflammation when activated (Scanlon and McKenzie, 2012; Li and Hendriks, 2013) . In the event of viral infection, cell death and injury to the epithelial barrier will also induce the expression of IL-25, IL-33 and TSLP, with heighten expression in an inflamed airway (Allakhverdi et al., 2007; Goldsmith et al., 2012; Byers et al., 2013; Shaw et al., 2013; Beale et al., 2014; Jackson et al., 2014; Uller and Persson, 2018; Ravanetti et al., 2019) . These 3 cytokines then work in concert to activate ILC2s to further secrete type 2 cytokines IL-4, IL-5, and IL-13 which further aggravate the type 2 inflammation in the airway causing acute exacerbation (Camelo et al., 2017) . In the case of COPD, increased ILC2 activation, which retain the capability of differentiating to ILC1, may also further augment the neutrophilic response and further aggravate the exacerbation (Silver et al., 2016) . Interestingly, these factors are not released to any great extent and do not activate an ILC2 response during viral infection in healthy individuals (Yan et al., 2016; Tan et al., 2018a) ; despite augmenting a type 2 exacerbation in chronically inflamed airways (Jurak et al., 2018) . These classical mechanisms of viral induced acute exacerbations are summarized in Figure 1 .
As integration of the virology, microbiology and immunology of viral infection becomes more interlinked, additional factors and FIGURE 1 | Current understanding of viral induced exacerbation of chronic airway inflammatory diseases. Upon virus infection in the airway, antiviral state will be activated to clear the invading pathogen from the airway. Immune response and injury factors released from the infected epithelium normally would induce a rapid type 1 immunity that facilitates viral clearance. However, in the inflamed airway, the cytokines and chemokines released instead augmented the inflammation present in the chronically inflamed airway, strengthening the neutrophilic infiltration in COPD airway, and eosinophilic infiltration in the asthmatic airway. The effect is also further compounded by the participation of Th1 and ILC1 cells in the COPD airway; and Th2 and ILC2 cells in the asthmatic airway.
Frontiers in Cell and Developmental Biology | www.frontiersin.org mechanisms have been implicated in acute exacerbations during and after viral infection (Murray et al., 2006) . Murray et al. (2006) has underlined the synergistic effect of viral infection with other sensitizing agents in causing more severe acute exacerbations in the airway. This is especially true when not all exacerbation events occurred during the viral infection but may also occur well after viral clearance (Kim et al., 2008; Stolz et al., 2019) in particular the late onset of a bacterial infection (Singanayagam et al., 2018 (Singanayagam et al., , 2019a . In addition, viruses do not need to directly infect the lower airway to cause an acute exacerbation, as the nasal epithelium remains the primary site of most infections. Moreover, not all viral infections of the airway will lead to acute exacerbations, suggesting a more complex interplay between the virus and upper airway epithelium which synergize with the local airway environment in line with the "united airway" hypothesis (Kurai et al., 2013) . On the other hand, viral infections or their components persist in patients with chronic airway inflammatory disease (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Hence, their presence may further alter the local environment and contribute to current and future exacerbations. Future studies should be performed using metagenomics in addition to PCR analysis to determine the contribution of the microbiome and mycobiome to viral infections. In this review, we highlight recent data regarding viral interactions with the airway epithelium that could also contribute to, or further aggravate, acute exacerbations of chronic airway inflammatory diseases.
Patients with chronic airway inflammatory diseases have impaired or reduced ability of viral clearance (Hammond et al., 2015; McKendry et al., 2016; Akbarshahi et al., 2018; Gill et al., 2018; Wang et al., 2018; Singanayagam et al., 2019b) . Their impairment stems from a type 2-skewed inflammatory response which deprives the airway of important type 1 responsive CD8 cells that are responsible for the complete clearance of virusinfected cells (Becker, 2006; McKendry et al., 2016) . This is especially evident in weak type 1 inflammation-inducing viruses such as RV and RSV (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Additionally, there are also evidence of reduced type I (IFNβ) and III (IFNλ) interferon production due to type 2-skewed inflammation, which contributes to imperfect clearance of the virus resulting in persistence of viral components, or the live virus in the airway epithelium (Contoli et al., 2006; Hwang et al., 2019; Wark, 2019) . Due to the viral components remaining in the airway, antiviral genes such as type I interferons, inflammasome activating factors and cytokines remained activated resulting in prolong airway inflammation (Wood et al., 2011; Essaidi-Laziosi et al., 2018) . These factors enhance granulocyte infiltration thus prolonging the exacerbation symptoms. Such persistent inflammation may also be found within DNA viruses such as AdV, hCMV and HSV, whose infections generally persist longer (Imperiale and Jiang, 2015) , further contributing to chronic activation of inflammation when they infect the airway (Yang et al., 2008; Morimoto et al., 2009; Imperiale and Jiang, 2015; Lan et al., 2016; Tan et al., 2016; Kowalski et al., 2017) . With that note, human papilloma virus (HPV), a DNA virus highly associated with head and neck cancers and respiratory papillomatosis, is also linked with the chronic inflammation that precedes the malignancies (de Visser et al., 2005; Gillison et al., 2012; Bonomi et al., 2014; Fernandes et al., 2015) . Therefore, the role of HPV infection in causing chronic inflammation in the airway and their association to exacerbations of chronic airway inflammatory diseases, which is scarcely explored, should be investigated in the future. Furthermore, viral persistence which lead to continuous expression of antiviral genes may also lead to the development of steroid resistance, which is seen with RV, RSV, and PIV infection (Chi et al., 2011; Ford et al., 2013; Papi et al., 2013) . The use of steroid to suppress the inflammation may also cause the virus to linger longer in the airway due to the lack of antiviral clearance (Kim et al., 2008; Hammond et al., 2015; Hewitt et al., 2016; McKendry et al., 2016; Singanayagam et al., 2019b) . The concomitant development of steroid resistance together with recurring or prolong viral infection thus added considerable burden to the management of acute exacerbation, which should be the future focus of research to resolve the dual complications arising from viral infection.
On the other end of the spectrum, viruses that induce strong type 1 inflammation and cell death such as IFV (Yan et al., 2016; Guibas et al., 2018) and certain CoV (including the recently emerged COVID-19 virus) (Tao et al., 2013; Yue et al., 2018; Zhu et al., 2020) , may not cause prolonged inflammation due to strong induction of antiviral clearance. These infections, however, cause massive damage and cell death to the epithelial barrier, so much so that areas of the epithelium may be completely absent post infection (Yan et al., 2016; Tan et al., 2019) . Factors such as RANTES and CXCL10, which recruit immune cells to induce apoptosis, are strongly induced from IFV infected epithelium (Ampomah et al., 2018; Tan et al., 2019) . Additionally, necroptotic factors such as RIP3 further compounds the cell deaths in IFV infected epithelium . The massive cell death induced may result in worsening of the acute exacerbation due to the release of their cellular content into the airway, further evoking an inflammatory response in the airway (Guibas et al., 2018) . Moreover, the destruction of the epithelial barrier may cause further contact with other pathogens and allergens in the airway which may then prolong exacerbations or results in new exacerbations. Epithelial destruction may also promote further epithelial remodeling during its regeneration as viral infection induces the expression of remodeling genes such as MMPs and growth factors . Infections that cause massive destruction of the epithelium, such as IFV, usually result in severe acute exacerbations with non-classical symptoms of chronic airway inflammatory diseases. Fortunately, annual vaccines are available to prevent IFV infections (Vasileiou et al., 2017; Zheng et al., 2018) ; and it is recommended that patients with chronic airway inflammatory disease receive their annual influenza vaccination as the best means to prevent severe IFV induced exacerbation.
Another mechanism that viral infections may use to drive acute exacerbations is the induction of vasodilation or tight junction opening factors which may increase the rate of infiltration. Infection with a multitude of respiratory viruses causes disruption of tight junctions with the resulting increased rate of viral infiltration. This also increases the chances of allergens coming into contact with airway immune cells. For example, IFV infection was found to induce oncostatin M (OSM) which causes tight junction opening (Pothoven et al., 2015; Tian et al., 2018) . Similarly, RV and RSV infections usually cause tight junction opening which may also increase the infiltration rate of eosinophils and thus worsening of the classical symptoms of chronic airway inflammatory diseases (Sajjan et al., 2008; Kast et al., 2017; Kim et al., 2018) . In addition, the expression of vasodilating factors and fluid homeostatic factors such as angiopoietin-like 4 (ANGPTL4) and bactericidal/permeabilityincreasing fold-containing family member A1 (BPIFA1) are also associated with viral infections and pneumonia development, which may worsen inflammation in the lower airway Akram et al., 2018) . These factors may serve as targets to prevent viral-induced exacerbations during the management of acute exacerbation of chronic airway inflammatory diseases.
Another recent area of interest is the relationship between asthma and COPD exacerbations and their association with the airway microbiome. The development of chronic airway inflammatory diseases is usually linked to specific bacterial species in the microbiome which may thrive in the inflamed airway environment (Diver et al., 2019) . In the event of a viral infection such as RV infection, the effect induced by the virus may destabilize the equilibrium of the microbiome present (Molyneaux et al., 2013; Kloepfer et al., 2014; Kloepfer et al., 2017; Jubinville et al., 2018; van Rijn et al., 2019) . In addition, viral infection may disrupt biofilm colonies in the upper airway (e.g., Streptococcus pneumoniae) microbiome to be release into the lower airway and worsening the inflammation (Marks et al., 2013; Chao et al., 2014) . Moreover, a viral infection may also alter the nutrient profile in the airway through release of previously inaccessible nutrients that will alter bacterial growth (Siegel et al., 2014; Mallia et al., 2018) . Furthermore, the destabilization is further compounded by impaired bacterial immune response, either from direct viral influences, or use of corticosteroids to suppress the exacerbation symptoms (Singanayagam et al., 2018 (Singanayagam et al., , 2019a Wang et al., 2018; Finney et al., 2019) . All these may gradually lead to more far reaching effect when normal flora is replaced with opportunistic pathogens, altering the inflammatory profiles (Teo et al., 2018) . These changes may in turn result in more severe and frequent acute exacerbations due to the interplay between virus and pathogenic bacteria in exacerbating chronic airway inflammatory diseases (Wark et al., 2013; Singanayagam et al., 2018) . To counteract these effects, microbiome-based therapies are in their infancy but have shown efficacy in the treatments of irritable bowel syndrome by restoring the intestinal microbiome (Bakken et al., 2011) . Further research can be done similarly for the airway microbiome to be able to restore the microbiome following disruption by a viral infection.
Viral infections can cause the disruption of mucociliary function, an important component of the epithelial barrier. Ciliary proteins FIGURE 2 | Changes in the upper airway epithelium contributing to viral exacerbation in chronic airway inflammatory diseases. The upper airway epithelium is the primary contact/infection site of most respiratory viruses. Therefore, its infection by respiratory viruses may have far reaching consequences in augmenting and synergizing current and future acute exacerbations. The destruction of epithelial barrier, mucociliary function and cell death of the epithelial cells serves to increase contact between environmental triggers with the lower airway and resident immune cells. The opening of tight junction increasing the leakiness further augments the inflammation and exacerbations. In addition, viral infections are usually accompanied with oxidative stress which will further increase the local inflammation in the airway. The dysregulation of inflammation can be further compounded by modulation of miRNAs and epigenetic modification such as DNA methylation and histone modifications that promote dysregulation in inflammation. Finally, the change in the local airway environment and inflammation promotes growth of pathogenic bacteria that may replace the airway microbiome. Furthermore, the inflammatory environment may also disperse upper airway commensals into the lower airway, further causing inflammation and alteration of the lower airway environment, resulting in prolong exacerbation episodes following viral infection.
Viral specific trait contributing to exacerbation mechanism (with literature evidence) Oxidative stress ROS production (RV, RSV, IFV, HSV)
As RV, RSV, and IFV were the most frequently studied viruses in chronic airway inflammatory diseases, most of the viruses listed are predominantly these viruses. However, the mechanisms stated here may also be applicable to other viruses but may not be listed as they were not implicated in the context of chronic airway inflammatory diseases exacerbation (see text for abbreviations).
that aid in the proper function of the motile cilia in the airways are aberrantly expressed in ciliated airway epithelial cells which are the major target for RV infection (Griggs et al., 2017) . Such form of secondary cilia dyskinesia appears to be present with chronic inflammations in the airway, but the exact mechanisms are still unknown (Peng et al., , 2019 Qiu et al., 2018) . Nevertheless, it was found that in viral infection such as IFV, there can be a change in the metabolism of the cells as well as alteration in the ciliary gene expression, mostly in the form of down-regulation of the genes such as dynein axonemal heavy chain 5 (DNAH5) and multiciliate differentiation And DNA synthesis associated cell cycle protein (MCIDAS) (Tan et al., 2018b . The recently emerged Wuhan CoV was also found to reduce ciliary beating in infected airway epithelial cell model (Zhu et al., 2020) . Furthermore, viral infections such as RSV was shown to directly destroy the cilia of the ciliated cells and almost all respiratory viruses infect the ciliated cells (Jumat et al., 2015; Yan et al., 2016; Tan et al., 2018a) . In addition, mucus overproduction may also disrupt the equilibrium of the mucociliary function following viral infection, resulting in symptoms of acute exacerbation (Zhu et al., 2009) . Hence, the disruption of the ciliary movement during viral infection may cause more foreign material and allergen to enter the airway, aggravating the symptoms of acute exacerbation and making it more difficult to manage. The mechanism of the occurrence of secondary cilia dyskinesia can also therefore be explored as a means to limit the effects of viral induced acute exacerbation.
MicroRNAs (miRNAs) are short non-coding RNAs involved in post-transcriptional modulation of biological processes, and implicated in a number of diseases (Tan et al., 2014) . miRNAs are found to be induced by viral infections and may play a role in the modulation of antiviral responses and inflammation (Gutierrez et al., 2016; Deng et al., 2017; Feng et al., 2018) . In the case of chronic airway inflammatory diseases, circulating miRNA changes were found to be linked to exacerbation of the diseases (Wardzynska et al., 2020) . Therefore, it is likely that such miRNA changes originated from the infected epithelium and responding immune cells, which may serve to further dysregulate airway inflammation leading to exacerbations. Both IFV and RSV infections has been shown to increase miR-21 and augmented inflammation in experimental murine asthma models, which is reversed with a combination treatment of anti-miR-21 and corticosteroids (Kim et al., 2017) . IFV infection is also shown to increase miR-125a and b, and miR-132 in COPD epithelium which inhibits A20 and MAVS; and p300 and IRF3, respectively, resulting in increased susceptibility to viral infections (Hsu et al., 2016 (Hsu et al., , 2017 . Conversely, miR-22 was shown to be suppressed in asthmatic epithelium in IFV infection which lead to aberrant epithelial response, contributing to exacerbations (Moheimani et al., 2018) . Other than these direct evidence of miRNA changes in contributing to exacerbations, an increased number of miRNAs and other non-coding RNAs responsible for immune modulation are found to be altered following viral infections (Globinska et al., 2014; Feng et al., 2018; Hasegawa et al., 2018) . Hence non-coding RNAs also presents as targets to modulate viral induced airway changes as a means of managing exacerbation of chronic airway inflammatory diseases. Other than miRNA modulation, other epigenetic modification such as DNA methylation may also play a role in exacerbation of chronic airway inflammatory diseases. Recent epigenetic studies have indicated the association of epigenetic modification and chronic airway inflammatory diseases, and that the nasal methylome was shown to be a sensitive marker for airway inflammatory changes (Cardenas et al., 2019; Gomez, 2019) . At the same time, it was also shown that viral infections such as RV and RSV alters DNA methylation and histone modifications in the airway epithelium which may alter inflammatory responses, driving chronic airway inflammatory diseases and exacerbations (McErlean et al., 2014; Pech et al., 2018; Caixia et al., 2019) . In addition, Spalluto et al. (2017) also showed that antiviral factors such as IFNγ epigenetically modifies the viral resistance of epithelial cells. Hence, this may indicate that infections such as RV and RSV that weakly induce antiviral responses may result in an altered inflammatory state contributing to further viral persistence and exacerbation of chronic airway inflammatory diseases (Spalluto et al., 2017) .
Finally, viral infection can result in enhanced production of reactive oxygen species (ROS), oxidative stress and mitochondrial dysfunction in the airway epithelium (Kim et al., 2018; Mishra et al., 2018; Wang et al., 2018) . The airway epithelium of patients with chronic airway inflammatory diseases are usually under a state of constant oxidative stress which sustains the inflammation in the airway (Barnes, 2017; van der Vliet et al., 2018) . Viral infections of the respiratory epithelium by viruses such as IFV, RV, RSV and HSV may trigger the further production of ROS as an antiviral mechanism Aizawa et al., 2018; Wang et al., 2018) . Moreover, infiltrating cells in response to the infection such as neutrophils will also trigger respiratory burst as a means of increasing the ROS in the infected region. The increased ROS and oxidative stress in the local environment may serve as a trigger to promote inflammation thereby aggravating the inflammation in the airway (Tiwari et al., 2002) . A summary of potential exacerbation mechanisms and the associated viruses is shown in Figure 2 and Table 1 .
While the mechanisms underlying the development and acute exacerbation of chronic airway inflammatory disease is extensively studied for ways to manage and control the disease, a viral infection does more than just causing an acute exacerbation in these patients. A viral-induced acute exacerbation not only induced and worsens the symptoms of the disease, but also may alter the management of the disease or confer resistance toward treatments that worked before. Hence, appreciation of the mechanisms of viral-induced acute exacerbations is of clinical significance to devise strategies to correct viral induce changes that may worsen chronic airway inflammatory disease symptoms. Further studies in natural exacerbations and in viral-challenge models using RNA-sequencing (RNA-seq) or single cell RNA-seq on a range of time-points may provide important information regarding viral pathogenesis and changes induced within the airway of chronic airway inflammatory disease patients to identify novel targets and pathway for improved management of the disease. Subsequent analysis of functions may use epithelial cell models such as the air-liquid interface, in vitro airway epithelial model that has been adapted to studying viral infection and the changes it induced in the airway (Yan et al., 2016; Boda et al., 2018; Tan et al., 2018a) . Animal-based diseased models have also been developed to identify systemic mechanisms of acute exacerbation (Shin, 2016; Gubernatorova et al., 2019; Tanner and Single, 2019) . Furthermore, the humanized mouse model that possess human immune cells may also serves to unravel the immune profile of a viral infection in healthy and diseased condition (Ito et al., 2019; Li and Di Santo, 2019) . For milder viruses, controlled in vivo human infections can be performed for the best mode of verification of the associations of the virus with the proposed mechanism of viral induced acute exacerbations . With the advent of suitable diseased models, the verification of the mechanisms will then provide the necessary continuation of improving the management of viral induced acute exacerbations.
In conclusion, viral-induced acute exacerbation of chronic airway inflammatory disease is a significant health and economic burden that needs to be addressed urgently. In view of the scarcity of antiviral-based preventative measures available for only a few viruses and vaccines that are only available for IFV infections, more alternative measures should be explored to improve the management of the disease. Alternative measures targeting novel viral-induced acute exacerbation mechanisms, especially in the upper airway, can serve as supplementary treatments of the currently available management strategies to augment their efficacy. New models including primary human bronchial or nasal epithelial cell cultures, organoids or precision cut lung slices from patients with airways disease rather than healthy subjects can be utilized to define exacerbation mechanisms. These mechanisms can then be validated in small clinical trials in patients with asthma or COPD. Having multiple means of treatment may also reduce the problems that arise from resistance development toward a specific treatment. | What is another mechanism that viral infections use to drive acute exacerbations? | false | 3,987 | {
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2,642 | First cases of coronavirus disease 2019 (COVID-19) in the WHO European Region, 24 January to 21 February 2020
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7068164/
SHA: ce358c18aac69fc83c7b2e9a7dca4a43b0f60e2e
Authors: Spiteri, Gianfranco; Fielding, James; Diercke, Michaela; Campese, Christine; Enouf, Vincent; Gaymard, Alexandre; Bella, Antonino; Sognamiglio, Paola; Sierra Moros, Maria José; Riutort, Antonio Nicolau; Demina, Yulia V.; Mahieu, Romain; Broas, Markku; Bengnér, Malin; Buda, Silke; Schilling, Julia; Filleul, Laurent; Lepoutre, Agnès; Saura, Christine; Mailles, Alexandra; Levy-Bruhl, Daniel; Coignard, Bruno; Bernard-Stoecklin, Sibylle; Behillil, Sylvie; van der Werf, Sylvie; Valette, Martine; Lina, Bruno; Riccardo, Flavia; Nicastri, Emanuele; Casas, Inmaculada; Larrauri, Amparo; Salom Castell, Magdalena; Pozo, Francisco; Maksyutov, Rinat A.; Martin, Charlotte; Van Ranst, Marc; Bossuyt, Nathalie; Siira, Lotta; Sane, Jussi; Tegmark-Wisell, Karin; Palmérus, Maria; Broberg, Eeva K.; Beauté, Julien; Jorgensen, Pernille; Bundle, Nick; Pereyaslov, Dmitriy; Adlhoch, Cornelia; Pukkila, Jukka; Pebody, Richard; Olsen, Sonja; Ciancio, Bruno Christian
Date: 2020-03-05
DOI: 10.2807/1560-7917.es.2020.25.9.2000178
License: cc-by
Abstract: In the WHO European Region, COVID-19 surveillance was implemented 27 January 2020. We detail the first European cases. As at 21 February, nine European countries reported 47 cases. Among 38 cases studied, 21 were linked to two clusters in Germany and France, 14 were infected in China. Median case age was 42 years; 25 were male. Late detection of the clusters’ index cases delayed isolation of further local cases. As at 5 March, there were 4,250 cases.
Text: In the WHO European Region, COVID-19 surveillance was implemented 27 January 2020. We detail the first European cases. As at 21 February, nine European countries reported 47 cases. Among 38 cases studied, 21 were linked to two clusters in Germany and France, 14 were infected in China. Median case age was 42 years; 25 were male. Late detection of the clusters' index cases delayed isolation of further local cases. As at 5 March, there were 4,250 cases.
A cluster of pneumonia of unknown origin was identified in Wuhan, China, in December 2019 [1] . On 12 January 2020, Chinese authorities shared the sequence of a novel coronavirus termed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) isolated from some clustered cases [2] . Since then, the disease caused by SARS-CoV-2 has been named coronavirus disease 2019 (COVID -19) . As at 21 February 2020, the virus had spread rapidly mostly within China but also to 28 other countries, including in the World Health Organization (WHO) European Region [3] [4] [5] .
Here we describe the epidemiology of the first cases of COVID-19 in this region, excluding cases reported in the United Kingdom (UK), as at 21 February 2020. The study includes a comparison between cases detected among travellers from China and cases whose infection was acquired due to subsequent local transmission.
On 27 January 2020, the European Centre for Disease Prevention and Control (ECDC) and the WHO Regional Office for Europe asked countries to complete a WHO standard COVID-19 case report form for all confirmed and probable cases according to WHO criteria [6] [7] [8] . The overall aim of surveillance at this time was to support the global strategy of containment of COVID-19 with rapid identification and follow-up of cases linked to affected countries in order to minimise onward transmission. The surveillance objectives were to: describe the key epidemiological and clinical characteristics of COVID-19 cases detected in Europe; inform country preparedness; and improve further case detection and management. Data collected included demographics, history of recent travel to affected areas, close contact with a probable or confirmed COVID-19 case, underlying conditions, signs and symptoms of disease at onset, type of specimens from which the virus was detected, and clinical outcome. The WHO case definition was adopted for surveillance: a confirmed case was a person with laboratory confirmation of SARS-CoV-2 infection (ECDC recommended two separate SARS-CoV-2 RT-PCR tests), irrespective of clinical signs and symptoms, whereas a probable case was a suspect case for whom testing for SARS-CoV-2 was inconclusive or positive using a pan-coronavirus assay [8] . By 31 January 2020, 47 laboratories in 31 countries, including 38 laboratories in 24 European Union and European Economic Area (EU/EEA) countries, had diagnostic capability for SARS-CoV-2 available (close to 60% of countries in the WHO European Region), with cross-border shipment arrangements in place for many of those lacking domestic testing capacity. The remaining six EU/EEA countries were expected to have diagnostic testing available by mid-February [9] .
As at 09:00 on 21 February 2020, 47 confirmed cases of COVID-19 were reported in the WHO European Region and one of these cases had died [4] . Data on 38 of these cases (i.e. all except the nine reported in the UK) are included in this analysis.
The first three cases detected were reported in France on 24 January 2020 and had onset of symptoms on 17, 19 and 23 January respectively [10] . The first death was reported on 15 February in France. As at 21 February, nine countries had reported cases ( Figure) : Belgium (1), Finland (1), France (12), Germany (16), Italy (3), Russia (2), Spain (2), Sweden (1) and the UK (9 -not included further).
The place of infection (assessed at national level based on an incubation period presumed to be up to 14 days [11] , travel history and contact with probable or confirmed cases as per the case definition) was reported for 35 cases (missing for three cases), of whom 14 were infected in China (Hubei province: 10 cases; Shandong province: one case; province not reported for three cases). The remaining 21 cases were infected in Europe. Of these, 14 were linked to a cluster in Bavaria, Germany, and seven to a cluster in Haute-Savoie, France [12, 13] . Cases from the Bavarian cluster were reported from Germany and Spain, whereas cases from the Haute-Savoie cluster were reported from France All but two cases were hospitalised (35 of 37 where information on hospitalisation was reported), although it is likely that most were hospitalised to isolate the person rather than because of severe disease. The time from onset of symptoms to hospitalisation (and isolation) ranged between 0 and 10 days with a mean of 3.7 days (reported for 29 cases). The mean number of days to hospitalisation was 2.5 days for cases imported from China, but 4.6 days for those infected in Europe. This was mostly a result of delays in identifying the index cases of the two clusters in France and Germany. In the German cluster, for example, the first three cases detected locally were hospitalised in a mean of 5.7 days, whereas the following six took only a mean of 2 days to be hospitalised.
Symptoms at the point of diagnosis were reported for 31 cases. Two cases were asymptomatic and remained so until tested negative. The asymptomatic cases were tested as part of screening following repatriation and during contact tracing respectively. Of the remaining 29, 20 reported fever, 14 reported cough and eight reported weakness. Additional symptoms reported included headaches (6 cases), sore throat (2), rhinorrhoea (2), shortness of breath (2), myalgia (1), diarrhoea (1) and nausea (1). Fever was reported as the sole symptom for nine cases. In 16 of 29 symptomatic cases, the symptoms at diagnosis were consistent with the case definition for acute respiratory infection [16] , although it is possible that cases presented additional symptoms after diagnosis and these were not reported.
Data on pre-existing conditions were reported for seven cases; five had no pre-existing conditions while one was reported to be obese and one had pre-existing cardiac disease. No data on clinical signs e.g. dyspnea etc. were reported for any of the 38 cases.
All hospitalised cases had a benign clinical evolution except four, two reported in Italy and two reported in France, all of whom developed viral pneumonia. All three cases who were aged 65 years or over were admitted to intensive care and required respiratory support and one French case died. The case who died was hospitalised for 21 days and required intensive care and mechanical ventilation for 19 days. The duration of hospitalisation was reported for 16 cases with a median of 13 days (range: 8-23 days). As at 21 February 2020, four cases were still hospitalised.
All cases were confirmed according to specific assays targeting at least two separate genes (envelope (E) gene as a screening test and RNA-dependent RNA polymerase (RdRp) gene or nucleoprotein (N) gene for confirmation) [8, 17] . The specimen types tested were reported for 27 cases: 15 had positive nasopharyngeal swabs, nine had positive throat swabs, three cases had positive sputum, two had a positive nasal swab, one case had a positive nasopharyngeal aspirate and one a positive endotracheal aspirate.
As at 09:00 on 21 February, few COVID-19 cases had been detected in Europe compared with Asia. However the situation is rapidly developing, with a large outbreak recently identified in northern Italy, with transmission in several municipalities and at least two deaths [18] . As at 5 March 2020, there are 4,250 cases including 113 deaths reported among 38 countries in the WHO European region [19] .
In our analysis of early cases, we observed transmission in two broad contexts: sporadic cases among travellers from China (14 cases) and cases who acquired infection due to subsequent local transmission in Europe (21 cases). Our analysis shows that the time from symptom onset to hospitalisation/case isolation was about 3 days longer for locally acquired cases than for imported cases. People returning from affected areas are likely to have a low threshold to seek care and be tested when symptomatic, however delays in identifying the index cases of the two clusters in France and Germany meant that locally acquired cases took longer to be detected and isolated. Once the exposure is determined and contacts identified and quarantined (171 contacts in France and 200 in Germany for the clusters in Haute-Savoie and Bavaria, respectively), further cases are likely to be rapidly detected and isolated when they develop symptoms [15, 20] . In the German cluster, for example, the first three cases detected locally were hospitalised in a mean of 5.7 days, whereas the following six were hospitalised after a mean of 2 days. Locally acquired cases require significant resources for contact tracing and quarantine, and countries should be prepared to allocate considerable public health resources during the containment phase, should local clusters emerge in their population. In addition, prompt sharing of information on cases and contacts through international notification systems such as the International Health Regulations (IHR) mechanism and the European Commission's European Early Warning and Response System is essential to contain international spread of infection.
All of the imported cases had a history of travel to China. This was consistent with the epidemiological situation in Asia, and supported the recommendation for testing of suspected cases with travel history to China and potentially other areas of presumed ongoing community transmission. The situation has evolved rapidly since then, however, and the number of countries reporting COVID-19 transmission increased rapidly, notably with a large outbreak in northern Italy with 3,089 cases reported as at 5 March [18, 19] . Testing of suspected cases based on geographical risk of importation needs to be complemented with additional approaches to ensure early detection of local circulation of COVID-19, including through testing of severe acute respiratory infections in hospitals irrespectively of travel history as recommended in the WHO case definition updated on 27 February 2020 [21] .
The clinical presentation observed in the cases in Europe is that of an acute respiratory infection. However, of the 31 cases with information on symptoms, 20 cases presented with fever and nine cases presented only with fever and no other symptoms. These findings, which are consistent with other published case series, have prompted ECDC to include fever among several clinical signs or symptoms indicative for the suspected case definition.
Three cases were aged 65 years or over. All required admission to intensive care and were tourists (imported cases). These findings could reflect the average older age of the tourist population compared with the local contacts exposed to infection in Europe and do not allow us to draw any conclusion on the proportion of severe cases that we could expect in the general population of Europe. Despite this, the finding of older individuals being at higher risk of a severe clinical course is consistent with the evidence from Chinese case series published so far although the majority of infections in China have been mild [22, 23] .
This preliminary analysis is based on the first reported cases of COVID-19 cases in the WHO European Region. Given the small sample size, and limited completeness for some variables, all the results presented should be interpreted with caution.
With increasing numbers of cases in Europe, data from surveillance and investigations in the region can build on the evidence from countries in Asia experiencing more widespread transmission particularly on disease spectrum and the proportion of infections with severe outcome [22] . Understanding the infection-severity is critical to help plan for the impact on the healthcare system and the wider population. Serological studies are vital to understand the proportion of cases who are asymptomatic. Hospital-based surveillance could help estimate the incidence of severe cases and identify risk factors for severity and death. Established hospital surveillance systems that are in place for influenza and other diseases in Europe may be expanded for this purpose. In addition, a number of countries in Europe are adapting and, in some cases, already using existing sentinel primary care based surveillance systems for influenza to detect community transmission of SARS-CoV-2. This approach will be used globally to help identify evidence of widespread community transmission and, should the virus spread and containment no longer be deemed feasible, to monitor intensity of disease transmission, trends and its geographical spread.
Additional research is needed to complement surveillance data to build knowledge on the infectious period, modes of transmission, basic and effective reproduction numbers, and effectiveness of prevention and case management options also in settings outside of China. Such special studies are being conducted globally, including a cohort study on citizens repatriated from China to Europe, with the aim to extrapolate disease incidence and risk factors for infection in areas with community transmission. Countries together with ECDC and WHO, should use all opportunities to address these questions in a coordinated fashion at the European and global level.
provided input to the outline, multiple versions of the manuscript and gave approval to the final draft. | For how many cases Fever reported as the sole symptom? | false | 3,821 | {
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1,741 | MERS coronavirus: diagnostics, epidemiology and transmission
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4687373/
SHA: f6fcf1a99cbd073c5821d1c4ffa3f2c6daf8ae29
Authors: Mackay, Ian M.; Arden, Katherine E.
Date: 2015-12-22
DOI: 10.1186/s12985-015-0439-5
License: cc-by
Abstract: The first known cases of Middle East respiratory syndrome (MERS), associated with infection by a novel coronavirus (CoV), occurred in 2012 in Jordan but were reported retrospectively. The case first to be publicly reported was from Jeddah, in the Kingdom of Saudi Arabia (KSA). Since then, MERS-CoV sequences have been found in a bat and in many dromedary camels (DC). MERS-CoV is enzootic in DC across the Arabian Peninsula and in parts of Africa, causing mild upper respiratory tract illness in its camel reservoir and sporadic, but relatively rare human infections. Precisely how virus transmits to humans remains unknown but close and lengthy exposure appears to be a requirement. The KSA is the focal point of MERS, with the majority of human cases. In humans, MERS is mostly known as a lower respiratory tract (LRT) disease involving fever, cough, breathing difficulties and pneumonia that may progress to acute respiratory distress syndrome, multiorgan failure and death in 20 % to 40 % of those infected. However, MERS-CoV has also been detected in mild and influenza-like illnesses and in those with no signs or symptoms. Older males most obviously suffer severe disease and MERS patients often have comorbidities. Compared to severe acute respiratory syndrome (SARS), another sometimes- fatal zoonotic coronavirus disease that has since disappeared, MERS progresses more rapidly to respiratory failure and acute kidney injury (it also has an affinity for growth in kidney cells under laboratory conditions), is more frequently reported in patients with underlying disease and is more often fatal. Most human cases of MERS have been linked to lapses in infection prevention and control (IPC) in healthcare settings, with approximately 20 % of all virus detections reported among healthcare workers (HCWs) and higher exposures in those with occupations that bring them into close contact with camels. Sero-surveys have found widespread evidence of past infection in adult camels and limited past exposure among humans. Sensitive, validated reverse transcriptase real-time polymerase chain reaction (RT-rtPCR)-based diagnostics have been available almost from the start of the emergence of MERS. While the basic virology of MERS-CoV has advanced over the past three years, understanding of the interplay between camel, environment, and human remains limited. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12985-015-0439-5) contains supplementary material, which is available to authorized users.
Text: An email from Dr Ali Mohamed Zaki, an Egyptian virologist working at the Dr Soliman Fakeeh Hospital in Jeddah in the Kingdom of Saudi Arabia (KSA) announced the first culture of a new coronavirus to the world. The email was published on the website of the professional emerging diseases (ProMED) network on 20 th September 2012 [1] (Fig. 1) and described the first reported case, a 60 year old man from Bisha in the KSA. This information led to the rapid discovery of a second case of the virus, this time in an ill patient in the United Kingdom, who had been transferred from Qatar for care [2] . The new virus was initially called novel coronavirus (nCoV) and subsequentlty entitled the Middle East respiratoy syndrome coronavirus (MERS-CoV). As of 2 nd of September 2015, there have been 1,493 detections of viral RNA or virus-specific antibodies across 26 countries (Additional file 1: Figure S1 ) confirmed by the World Health Organization (WHO), with over a third of the positive people dying (at least 527, 35 %) [3] .
Since that first report, a slow discovery process over the following two to three years revealed a virus that had infected over 90 % of adult dromedary camels (DC; Camelus dromedarius) in the KSA [4] , also DCs across the Arabian Peninsula and parts of Africa that are a source of DC imports for the KSA [5] . To date, MERS-CoV has not been detected in DCs tested in zoos or herds from other parts of the world [6] [7] [8] [9] . Occasionally, virus is transmitted from infected DCs to exposed humans. Subsequent transmission to other humans requires relatively close and prolonged exposure [10] .
The first viral isolate was patented and concerns were raised that this would restrict access to both the virus and to viral diagnostics [11, 12] . However, sensitive, validated reverse transcriptase real-time polymerase chain reaction (RT-rtPCR)-based diagnostics were quickly described and virus was made freely available subject to routine biosafety considerations [13] . Subsequent epidemiology and research has identified the cell receptor as exopeptidase dipeptidyl peptidase 4 (DPP4; also called CD26); that MERS-CoV has a broad tropism, replicating better in some cells lines and eliciting a more proinflammatory response than SARS-CoV; is widespread in DCs; has the potential to infect other animals and that MERS kills its human host more often than SARS did (20-40 % versus 9 % for SARS [14] ) [15] [16] [17] [18] [19] .
In humans, overt disease was given the name Middle East respiratory syndrome, with the acronym MERS. From intermittent animal-to-human spill-over events, the MERS-CoV spreads sporadically among people, causing more severe disease among older adults, especially males, with pre-existing diseases. The spread of MERS-CoV among humans has often been associated with outbreaks in hospitals, with around 20 % of all cases to date involving healthcare workers (HCWs).
Although DCs appear to suffer the equivalent of a 'common cold' from MERS-CoV infection, in humans, the virus can be a more serious and opportunistic pathogen associated with the death of up to 40 % of reported cases. It has yet to be established whether infections thought to have been acquired from an animal source produce a more severe outcome than those spread between humans [20] . Studies have established that the mean incubation period for MERS is five to six days, ranging from two to 16 days, with 13 to 14 days between when illness begins in one person and subsequently spreads to another [21] [22] [23] [24] . Among those with progressive illness, the median time to death is 11 to 13 days, ranging from five to 27 days [23, 24] . Fever and gastrointestinal symptoms may form a prodrome, after which symptoms decline, only to be followed by a more severe systemic and respiratory syndrome [25, 26] .
The first WHO case definition [27] defined probable cases of MERS based on the presence of febrile illness, cough and requirement for hospitalization with suspicion of lower respiratory tract (LRT) involvement. It also included roles for contact with a probable or confirmed case or for travel or residence within the Arabian Peninsula. If strictly adhered to, only the severe syndrome would be subject to laboratory testing, which was the paradigm early on [21] . From July 2013, the revised WHO case definition included the importance of seeking out and understanding the role of asymptomatic cases and from June 2014, the WHO definition more clearly stated that a confirmed case included any person whose sample was RT-PCR positive for MERS-CoV, or who produced a seroconversion, irrespective of clinical signs and symptoms. [28] [29] [30] Apart from the WHO and the KSA Ministry of Health reports, asymptomatic or subclinical cases of MERS-CoV infection were documented in the scientific literature although not always as often as occurred early on [31, 32] . The KSA definition of a case became more strict on 13 th May 2014, relying on the presence of both clinical features and laboratory confirmation [33] . Testing of asymptomatic people was recommended against from December 2014 [34] , reinforced by a case definition released by the KSA Ministry of Health in June 2015 [35] . The KSA has been the source of 79 % of human cases. Severe MERS is notable for its impact among older men with comorbid diseases including diabetes mellitus, cirrhosis and various lung, renal and cardiac conditions [36] [37] [38] . Interestingly in June 2015, an outbreak in South Korea followed a similar distribution [39, 40] . Among laboratory confirmed cases, fever, cough and upper respiratory tract (URT) signs and symptoms usually occur first, followed within a week by progressive LRT distress and lymphopaenia [37] . Patients often present to a hospital with pneumonia, or worse, and secondary bacterial infections have been reported [37, 41] . Disease can progress to acute respiratory distress syndrome and multiorgan system failure [37] . MERS has reportedly killed approximately 35 % of all reported cases, 42 % of cases in the KSA, yet only 19 % of cases in South Korea, where mortality ranged from 7 % among younger age groups to 40 % among those aged 60 years and above [42] ; all may be inflated values with asymptomatic or mild infections sometimes not sought or not reported [34] . General supportive care is key to managing severe cases [43] . Children under the age of 14 years are rarely reported to be positive for MERS-CoV, comprising only 1.1 % (n = 16) of total reported cases. Between 1 st September 2012 and 2 nd December 2013, a study described the then tally of paediatric cases in the KSA, which stood at 11 (two to 16 years of age; median 13 years); nine were asymptomatic (72 %) and one infant died [44] . In Amman, Jordan, 1,005 samples from hospitalized children under the age of two years with fever and/or respiratory signs and symptoms were tested but none were positive for MERS-CoV RNA, despite being collected at a similar time to the first known outbreak of MERS-CoV in the neighbouring town of Al-Zarqa [45] . A second trimester stillbirth occurred in a pregnant woman during an acute respiratory illness and while not RT-rtPCR positive, the mother did subsequently develop antibodies to MERS-CoV, suggestive of recent infection [46] . Her exposure history to a MERS-CoV RT-rtPCR positive relative and an antibody-reactive husband, her incubation period and her symptom history met the WHO criteria for being a probable MERS-CoV case [46] .
Diagnostic methods were published within days of the ProMED email announcing the first MERS case [47] , including several now gold standard in-house RT-rtPCR assays (Fig. 2 ) as well as virus culture in Vero and LLC-MK2 cells [18, 47, 48] . A colorectal adenocarcinoma (Caco-2) epithelial cell line has since been recommended for isolation of infections MERS-CoV [49] . We previously [18] .). Open reading frames are indicated as yellow rectangles bracketed by terminal untranslated regions (UTR; grey rectangles). FS-frame-shift. Predicted regions encompassing recombination break-points are indicated by orange pills. Created using Geneious v8.1 [211] and annotated using Adobe Illustrator. Beneath this is a schematic depicting the location of RT-PCR primers (blue arrows indicate direction) and oligoprobes (green rectangles) used in the earliest RT-rtPCR screening assays and conventional, semi-nested (three primers) RT-PCR confirmatory sequencing assays [47, 48] . Publication order is noted by first [27 th September 2012; red] and second [6 th December 2012; orange] coloured rectangles; both from Corman et al. [47, 48] Those assays recommended by the WHO are highlighted underneath by yellow dots [53] . The NSeq reverse primer has consistently contained one sequence mismatch with some MERS-CoV variants. An altered version of that from Mackay IM, Arden KE. Middle East respiratory syndrome: An emerging coronavirus infection tracked by the crowd. Virus Res 2015 Vol 202:60-88 with permission from Elsevier [5] reviewed the broad tropism of MERS-CoV [5] . However, as is well described, cell culture is a slow, specialised and insensitive method [50] while PCR-based techniques are the preferred method for MERS-CoV detection.
The first open reading frames (ORF 1a and 1b; Fig. 2 ) have become a key diagnostic and taxonomic target for CoV species identification. With less than 80 % identity between the amino acid sequence of MERS ORF 1ab and betacoronavirus relatives, Tylonycteris bat HKU4 and Pipistrellus bat HKU5, it can be concluded that it is a novel and distinct virus. MERS-CoV is predicted to encode ten open reading frames with 5' and 3' untranslated regions [51] . The structural proteins include the spike (S), envelope (E), membrane (M) and nucleocapsid (N) [52] . The products of ORF1a and ORF1b are predicted to encode nonstructural proteins.
The majority of specimen testing to date has employed validated RT-rtPCR assays shown to be sensitive and specific [47, 48, 53] . The RealStar® kit uses these WHOrecommended assays [54] . The target sequences of these screening assays have not changed among genomes examined until at least mid-2015 (IMM observation). Other RT-rtPCR assays have been developed and validated for use as laboratory-based diagnostic tools [55] [56] [57] . Additionally, loop-mediated [58, 59] or recombinase polymerase [60] isothermal assays have been designed for field deployment.
The detection of MERS-CoV antigen has not been common to date but the combination of short turnaround time from test to result, high throughput and identification of viral proteins makes this an attractive option. Detection of viral proteins rather than viral RNA indicates the likely presence of infectious virus. The first rapid immunochromatographic tool described could detect recombinant MERS-CoV nucleocapsid protein from DC nasal swabs with 94 % sensitivity and 100 % specificity compared to RT-rtPCR [61] . A different approach used a monoclonal antibody-based capture ELISA targeting the MERS-CoV nucleocapsid protein with a sensitivity of 10 3 TCID 50 and 100 % specificity [62] .
Demonstration of a seroconversion to a MERS-CoV infection meets the current WHO definition of a case so optimized and thoroughly validated sero-assays employed alongside good clinical histories are useful to both identify prior MERS-CoV infection and help support transmission studies. Because serology testing is, by its nature, retrospective, it is usual to detect a viral footprint, in the form of antibodies, in the absence of any signs or symptoms of disease and often in the absence of any viral RNA [63] .
Strategic, widespread sero-surveys of humans using samples collected after 2012 are infrequent. Much of the Arabian Peninsula and all of the Horn of Africa lack baseline data describing the proportion of the community who may have been infected by a MERS-CoV. However, sero-surveys have had widespread use in elucidating the role of DCs as a transmission source for MERS-CoV. Because of the identity shared between DC and human MERS-CoV (see Molecular epidemiology: using genomes to understand outbreaks), serological assays for DC sero-surveys should be transferrable to human screening with minimal re-configuration. Also, no diagnostically relevant variation in neutralization activity have been found from among a range of circulating tested MERS-CoV isolates and sera, so whole virus or specific protein-based sero-assays should perform equivalently in detecting serological responses to the single MERS-CoV serotype [49] . The development of robust serological assays requires reliable panels of wellcharacterized animal or human sera, including those positive for antibodies specific to MERS-CoV, as well as to likely sources of cross-reaction [64] . Obtaining these materials was problematic and slowed the development and commercialization of antibody detection assays for human testing [64] . A number of commercial ELISA kits, immunofluorescent assays (IFA) kits, recombinant proteins and monoclonal antibodies have been released [31, [65] [66] [67] [68] . Initially, conventional IFAs were used for human sero-surveys. These relied on MERS-CoV-infected cell culture as an antigen source, detecting the presence of human anti-MERS-CoV IgG, IgM or neutralizing antibodies in human samples [18, 48, 69] . No sign of MERS-CoV antibodies was found among 2,400 sera from patients visiting Hospital in Jeddah, from 2010 through 2012, prior to the description of MERS-CoV [18] . Nor did IFA methods detect any sign of prior MERS-CoV infection among a small sample of 130 healthy blood donors from another Hospital in Jeddah (collected between Jan and Dec 2012) [70] . Of 226 slaughterhouse workers, only eight (3.5 %) were positive by IFA, and those sera could not be confirmed by virus neutralization (NT) test. The study indicated that HCoV-HKU1 was a likely source of crossreactive antigen in the whole virus IFA [70] . Whole virus MERS-CoV IFA also suffered from some cross-reactivity with convalescent SARS patient sera and this could not be resolved by an NT test which was also cross-reactive [71] . IFA using recombinant proteins instead of whole-virus IFA, has been shown to be a more specific tool [31] . Since asymptomatic zoonoses have been posited [72] , an absence of antibodies to MERS-CoV among some humans who have regular and close contact with camels may reflect the rarity of actively infected animals at butcheries, a limited transmission risk associated with slaughtering DCs [70] , a pre-existing cross-protective immune status or some other factor(s) resulting in a low risk of disease and concurrent seroconversion developing after exposure in this group. IFA using recombinant proteins instead.
Some sero-assays have bypassed the risks of working with infectious virus by creating transfected cells expressing recombinant portions of the MERS-CoV nucleocapsid and spike proteins [48, 73] , or using a recombinant lentivirus expressing MERS-CoV spike protein and luciferase [74, 75] . A pseudo particle neutralization (ppNT) assay has seen widespread used in animal studies and was at least as sensitive as the traditional microneutralization (MNT) test. [10, 74, [76] [77] [78] ] Studies using small sample numbers and ppNT found no evidence of MERS-CoV neutralizing antibody in sera from 158 children with LRT infections between May 2010 and May 2011, 110 sera from 19 to 52 year old male blood donors and 300 selfidentified animal workers from the Jazan Region of the KSA during 2012 [79, 80] . Similarly, a study of four herdsmen in contact with an infected DC herd in Al-Ahsa, eight people who had intermittent contact with the herd, 30 veterinary surgeons and support staff who were not exposed to the herd, three unprotected abattoir workers in Al-Ahsa and 146 controls who were not exposed to DCs in any professional role, found none with serological evidence of past MERS-CoV infection using the ppNT assay [10] . A delay in the neutralizing antibody response to MERS-CoV infection was associated with increased disease severity in South Korea cases with most responses detectable by week three of illness while others, even though disease was severe, did not respond for four or more weeks [81] . The implications for our ability to detect any response in mild or asymptomatic cases was not explored but may be a signifcant factor in understanding exposure in the wider community.
A Jordanian outbreak of acute LRT disease in a hospital in 2012 was retrospectively found to be associated with MERS-CoV infection, initially using RT-rtPCR, but subsequently, and on a larger scale, through positivity by ELISA and IFA or MNT test. [46, 82, 83] This outbreak predated the first case of MERS in the KSA. The ELISA used a recombinant nucleocapsid protein from the group 2 betacoronavirus bat-CoV HKU5 to identify antibodies against the equivalent crossreactive MERS-CoV protein [71] . It was validated using 545 sera collected from people with prior HCoV-OC43, HCoV-229E, SARS-CoV, HCoV-NL63, HRV, HMPV or influenza A(H1N1) infections but was reportedly less specific than the recombinant IFA discussed above. It was still considered an applicable tool for screening large sample numbers [82] . A protein microarray expressing the S1 protein subunit has also been validated and widely used for DC testing [5, 84] . Detection of MERS-CoV infection using ELISA or S1 subunit protein microarray [84] is usually followed by confirmatory IFA and/ or a plaque-reduction neutralization (PRNT) [69, 70, 85] or MNT test. [74, 85, 86] This confirmatory process aims toensure the antibodies detected are able to specifically neutralize the intended virus and are not more broadly reactive to other coronaviruses found in DCs (bovine CoV, BCoV) or humans (HCoV-OC43, HCoV-229E, HCoV-NL63, HCoV-HKU1, SARS-CoV). In the largest study of human sera, a tiered diagnostic process assigned both recombinant IFA and recombinant ELISA positive sera to 'stage 1' seropositivity. A stage 2 seropositive result additionally required a suitably titred PRNT result [87] . The study found 15 sera collected in 2012 to 2013 from 10,009 (0.2 %) people in 13 KSA provinces contained MERS-CoV antibodies, but significantly higher proportions in occurred in camel shepherds (two of 87; 2.3 %) and slaughterhouse workers (five of 140; 3.6 %) [87] . Contemporary surveys are needed.
MERS-CoV does not appear to be easily transmitted from DCs to humans, or perhaps it is [72] , but generally does not trigger a detectable immune response if only mild disease or asymptomatic infection results. Serology assays are in need of further validation in this area so care is required when moving newly developed diagnostic serology algorithms from a research setting to one that informs public health decisions. This was reinforced when a false positive US case, purported to have been infected after a handshake and two face-to-face meetings, did not withstand further confirmatory analysis using a more specific, NT assay and was subsequently retracted [88, 89] .
The WHO recommends sampling from the LRT for MERS-CoV RT-rtPCR testing, especially when sample collection is delayed by a week or more after onset of symptoms. [53] LRT samples are also best for attempting isolation of infectious virus, although the success of culture is reduced when disease persists [49] . Recommended sample types include bronchoalveolar lavage (BAL), tracheal/tracheobronchial aspirate, pleural fluid and sputum [53, 90] . Fresh samples yield better diagnostic results than refrigerated material [69] and if delays in testing of ≥72 h are likely, samples (except for blood) should be frozen at −70°C [90] . If available, lung biopsy or autopsy tissues can also be tested [53] . The URT is a less invasive and more convenient sampling site however, and an oropharyngeal and throat swab or a nasopharyngeal aspirate/wash are recommended when URT sampling is to be conducted [90] . Paired sera, collected two to three weeks apart are preferable for serological testing while a single sample is suggested to be sufficient if collected two weeks after onset of disease or a single serum collected during the first 10-12 days if conducting RT-rtPCR [53, 90] . Human urine and stool have been found to contain MERS-CoV RNA 12 to 26 days after symptom onset [25, 69, 91] and are listed as samples that should be considered [53, 90] . In two cases that arrived in the Netherlands, urine was RT-rtPCR negative but faeces was weakly positive and sera were RT-rtPCR positive for five days or more [25] . The finding of MERS-CoV viral RNA in serum provides an avenue for retrospective PCR-based studies if respiratory samples are unavailable [83] . RNAaemia may also correlate with disease severity; signs of virus were cleared from the serum of a recovered patient, yet lingered until the death of another [92] .
Clinically suspected MERS cases may return negative results by RT-rtPCR. Data have shown one or more negative URT samples may be contradicted by further URT sampling or the use of LRT samples, which is preferred [2, 43, 93] . Higher viral loads occur in the LRT compared to the URT. [22, 69, 88, 94] This fits with the observation that the majority of disease symptoms are reported to manifest as systemic and LRT disease [21] . However, on occasion, even LRT specimens from MERS cases may initially be negative, only to later become positive by RT-PCR [95] . This may be due to poor sampling when a cough is absent or non-productive or because the viral load is low [95] . Despite this both the largest human MERS-CoV studies [32, [96] [97] [98] and smaller ones [22, 25, 99] , use samples from the URT. It is then noteworthy that one study reported an association between higher loads in the URT and worse clinical outcome including intensive care and death [94] . At writing, no human data exist to define whether the virus replicates solely or preferentially in the LRT or URT, or replicates in other human tissues in vivo although MERS-CoV RNA has been detected from both the URT and LRT in a macaque monkey model [100] .The distribution of DPP4 in the human upper airways is also not well described.
Individual human case studies report long periods of viral shedding, sometimes intermittently and not necessarily linked to the presence of disease symptoms. [25, 69, 99, 101] In one instance, a HCW shed viral RNA for 42 days in the absence of disease [99] . It is an area of high priority to better understand whether such cases are able to infect others. Over three quarters of MERS cases shed viral RNA in their LRT specimens (tracheal aspirates and sputum) for at least 30 days, while only 30 % of contacts were still shedding RNA in their URT specimens [91, 102] .
In the only study to examine the effect of sample type on molecular analysis, 64 nasopharyngeal aspirates (NPA; an URT sample), 30 tracheal aspirates, 13 sputa and three BAL were examined. The tracheal aspirates and BAL returned the highest viral load values followed by NPA and sputum. Unsurprisingly, higher viral loads generally paralleled whole genome sequencing and culture success and, in NPA testing, were significantly correlated with severe disease and death [49, 94, 103] . This study demonstrated the importance of LRT sampling for whole genome sequencing.
When tested, samples positive for MERS-CoV are often negative for other pathogens [2, 25, 93, 104] . However, many studies make no mention of additional testing for endemic human respiratory viruses [21, 23, 73, 105] . When viruses are sought, they have included human herpesvirus (HHV), rhinoviruses (HRV), enteroviruses (EV), respiratory syncytial virus (RSV), parainfluenzavirus types 1, 2 and 3 (PIVs),influenzaviruses (IFVs), endemic HCoVs, adenoviruses (AdVs) metapneumovirus (MPV) and influenza A\H1N1 virus; co-detections with MERS-CoV have been found on occasion [2, 22, 37, 69, 97] . Bacterial testing is sometimes included (for example, for Legionella and Pneumococcus) but the impact of bacterial co-presence is also unclear [22, [104] [105] [106] . Further testing of the LRT sample from the first MERS case used IFA to screen for some viruses (negative for IFV, PIVs, RSV and AdVs) and RT-PCR for others (negative for AdV, EVs, MPV and HHVs) [18] . RT-PCR also detected MERS-CoV. The WHO strongly recommends testing for other respiratory pathogens [53] but with this recommendation often discounted, there are limited data to address the occurrence and impact of co-infections or alternative viral diagnoses among both MERS cases and their contacts. Little is known of other causes of MERS-like pneumonia in the KSA or of the general burden of disease due to the known classical respiratory viruses.
Testing of adult pilgrims performing the Hajj in 2012 to 2014 has not detected any MERS-CoV. In 2012, nasal swabs from 154 pilgrims collected prior to leaving for or departing from the KSA were tested [47] . In 2013, testing was significantly scaled up with 5,235 nasopharyngeal swabs from 3,210 incoming pilgrims and 2,025 swabs from outgoing pilgrims tested [98] . It should be noted that most pilgrims arrived from MERS-free countries. A further 114 swabs were taken from pilgrims with influenza-like illness [96, 107] . In earlier Hajj gatherings, it was found that influenza viruses circulated widely, whilst other viruses, often rhinoviruses, circulated more selectively, interpreted as indicating their importation along with foreign pilgrims. [107] [108] [109] Over time, increased influenza vaccination has been credited for a fall in the prevalence of influenza like illnesses among Hajj pilgrims. [110] A LRT sample is often not collected for these studies [98, 107, 109] , so false negative findings are a possibility although little is known about the initial site of MERS-CoV infection and replication; it may have been assumed it was the LRT because disease was first noticed there but the URT may be the site of the earliest replication.
In Jeddah between March and July 2014 (hereafter called the Jeddah-2014 outbreak; Fig. 3 ), there was a rapid increase in MERS cases, accompanied by intense screening; approximately 5,000 samples from in and around the region were tested in a month yielding around 140 MERS-CoV detections (~3 % prevalence) [111] . Among 5,065 individuals sampled and tested across the KSA between October 2012 and September 2013,108 (2.1 %) detections were made in a hospital-centric population which included hospitalized cases (n = 2,908; 57.4 %), their families (n = 462; 9.1 %) and associated HCWs (n = 1,695; 33.5 %) [32] . Among the detections, 19 (17.8 %) were HCWs and 10 (9.3 %) were family contacts [32] .
The 2-3 % prevalence of active MERS-CoV infections is not dissimilar to the hospital-based prevalence of other human CoVs. [112] However, the proportion of deaths among those infected with MERS-CoV is much higher than that known for the HCoVs NL63, HKU1, 229E or OC43 in other countries, and even above that for SARS-CoV; it is not a virus that could reasonably be described as a "storm in a teacup". It is the low transmission rate that has prevented worldwide spread, despite many "opportunities".
Very early in the MERS outbreak, some animals were highly regarded as either the reservoir or intermediate host(s) of MERS-CoV with three of the first five cases having contact with DCs [73, 113, 114] . Today, animal MERS-CoV infections must be reported to the world organization for animal health as an emerging disease [115] . A summary of the first MERS cases reported by the WHO defined animal contact with humans as being direct and within 10 days prior to symptom onset [20] . This definition made no specific allowance for acquisition from DCs through a droplet-based route, which is very likely route for acquisition of a virus that initially and predominantly causes respiratory disease [23] . Camels are known to produce high levels of MERS-CoV RNA in their URT and lungs [116] . Providing support for a droplet transmission route and perhaps indicating the presence of RNA in smaller, drier droplet nuclei, MERS-CoV RNA was identified in a high volume air sample collected from a barn housing an infected DC [117] . The precise source from which humans acquire MERS-CoV remains poorly studied but it seems likely that animal and human behavioural factors may play roles (Fig. 3) [118] . These factors may prove important for human cases who do not describe any DC contact [119] nor any contact with a confirmed case. Whether the WHO definition of animal contact is sufficient to identify exposure to this respiratory virus remains unclear. Wording focuses on consumption of DC products but does not specifically ascribe risk to a droplet route for acquisition of MERS-CoV from DC [120] . Some MERS patients are listed in WHO disease notices as being in proximity to DCs or farms, but the individuals have not described coming into contact with the animals. No alternative path for acquiring infection is reported in many of these instances. What constitutes a definition of "contact" during these interviews has been defined for one study [72] . Despite this lack of clarity, the WHO consider that evidence linking MERS-CoV transmission between DCs to humans is irrefutable (Fig. 4) [120] .
The possibility that bats were an animal host of MERS-CoV was initially widely discussed because of the existing diversity of coronaviruses known to reside among them [121] [122] [123] [124] . Conclusive evidence supporting bats as a source for human infections by MERS-CoV has yet to be found, but bats do appear to host ancestral representatives [53, 125] . However, these are not variants of the same virus nor always within the same phylogenetic lineage as MERS-CoV; they are each a genetically distinct virus. Bat-to-human infection by MERS-CoV is a purely speculative event. The only piece of MERS-CoV-specific evidence pointing to bats originates from amplification of a 190 nt fragment of the RNAdependent RNA polymerase gene of the MERS-CoV genome, identified in a faecal pellet from an insectivorous Emballonuridae bat, Taphozous perforatus found in Bisha, the KSA [121] . While very short, the sequence of the fragment defined it as a diagnostic discovery. Subsequently a link to DCs was reported [85] and that link has matured into a verified association [38, 126] (Fig. 4) .
(See figure on previous page.) Fig. 3 Monthly detections of MERS-CoV (blue bars) and of cases who died (red bars) with some dates of interest marked for 2012 to 4 th September 2015. An approximation of when DC calving season [128] and when recently born DCs are weaned is indicated. Spring (green) and summer (orange) in the Arabian Peninsula are also shaded. Note the left-hand y-axis scale for 2014 and 2015 which is greater than for 2012/13. Sources of these public data include the WHO, Ministries of Health and FluTrackers [207] [208] [209] . Earlier and subsequent versions of this chart are maintained on a personal blog [210] . Modified and reprinted from Mackay IM, Arden KE. Middle East respiratory syndrome: An emerging coronavirus infection tracked by the crowd. Virus Res 2015 Vol 202:60-88 with permission from Elsevier [5] DCs, which make up 95 % of all camels, have a central presence in the Arabian Peninsula where human-DC contact ranges from little to close [119] . Contact may be commonplace and could occur in variety of ways (Fig. 4a) . There are several large well-attended festivals, races, sales and parades which feature DCs and DCs are also kept and bred close to populated areas in the KSA [127, 128] . DC milk and meat are widely consumed and the older DC is an animal of ritual significance after the Hajj pilgrimage [129] . However, MERS-CoV infection frequency is reportedly much lower than is the widespread and frequent habit of eating, drinking and preparing DC products. Daily ingestion of fresh unpasteurized DC milk is common among the desert Bedouin and many others in the KSA. DC urine is also consumed or used for supposed health benefits. Despite camel butchery being a local occupation, neither butchers nor other at-risk groups are identifiable among MERS cases; this may simply be a reporting issue rather than an unexplainable absence of MERS. A small case-control study published in 2015 identified direct DC contact, and not ingestion of products, to be associated with onset of MERS [38] .
The first sero-survey of livestock living in the Middle East region was conducted during 2012-2013 [85] . DCs were sampled from a mostly Canary Island-born herd and from Omani DCs (originally imported from the Horn of Africa) [85] . A neutralising antibody assay found only 10 % of strongly seropositive Canary Island [5] . b Camel-to-human infections appear to be infrequent, while human-to-human spread of infection is regularly facilitated by poor IPC in healthcare settings where transmission is amplified, accounting for the bulk of cases. There are human MERS cases that do not fall into either category of source and it is unclear if these acquired infection through some entirely separate route, or from cases that escaped diagnosis. c Hypothetical ways in which subclinical (when infection may not meet a previously defined clinical threshold of signs and/or symptoms) or asymptomatic (no obvious signs or measured, noticed or recalled symptoms of illness) MERS-CoV infection may be implicated in transmission DC sera could neutralise MERS-CoV while all Omani DC sera had high levels of specific MERS-CoV neutralizing antibody [85] . This indicated that DCs had in the past been infected by MERS-CoV, or a very similar virus.
Since this study, a host of peer-reviewed reports have looked at both DCs and other animals, and the possibility that they may host MERS-CoV infection. Seropositive DCs have been found throughout the Arabian Peninsula including Oman, the KSA, Qatar, Jordan, the United Arab Emirates (UAE), Kuwait as well as Sudan, Somalia, Egypt, Tunisia, Nigeria, Kenya and Ethiopia in Africa and the Canary Islands [85, [130] [131] [132] [133] [134] . Other animals tested include sheep, cows, pigs, horses, donkeys, mules, birds, water buffalo, goats, Bactrian camels, llamas and guanaco (south American camelids) but none had detectable neutralising antibody against MERS-CoV [4, 74, 78, 85, 86, 135, 136] . No virology or serology studies of human samples from areas in Africa where there are camels with a history of MERS-CoV have been reported to date. However,an absence of unexplained pneumonia that may be attributable to MERS-CoV infection may not signal the absence of virus among humans in each country but simply reflect a lack of expensive epidemiology studies conducted by resource-poor countries. It is thus unclear whether MERS-CoV, or an antigenically related CoV, is an unrecognized pathogen in these regions, perhaps circulating for even longer than it has been known in the Arabian Peninsula [133] .
MERS-CoV RNA has also been detected in DC samples, and recovery of infectious virus has also been achieved from DC samples [4, 77, 117, 132, [137] [138] [139] [140] [141] . From some of these, full or majority length genomes of MERS-CoV have been sequenced [77, 137, 138] . DC versions of MERS-CoV were found to be as similar to each other, as were variants detected from different humans over time and across distance.
Antibody screening assays have also detected crossreactive antibodies in sera. These were identified as such by screening sera against similar viruses, for example BCoV or HCoV-OC43 (as an antigenic facsimile for BCoV). It is possible that other MERS-CoV-like viruses also reside within DCs, but this does not detract from the definitive finding of MERS-CoV genetic sequences in both DCs and humans [117, 142, 143] .
Screening studies have shown that juvenile DCs are more often positive for virus or viral RNA while older DCs are more likely to be seropositive and RNA or virus negative [76, 77, 144] . In adult DCs, MERS-CoV RNA has been detected among animals with pre-existing antibody, suggesting re-infection is possible [77, 144] . Viral loads among positive DCs can be very high [4, 76, 77, 139, 144] and DCs have been found positive both when ill with URT respiratory signs [77, 117, 142, 145] or when apparently healthy [137] . These findings indicate DCs host natural MERS-CoV infections. Furthermore, stored DC sera have revealed signs of MERS-CoV in DCs which date back over three decades (the earliest collected in 1983) [4, 133, 135] . Older sera have not been tested and so precisely how long DCs have been afflicted by MERS-CoV, whether the virus is enzootic among them, introduced to them decades or centuries ago from bats in Africa or the Arabian Peninsula, or they are the subject of regular but short-lived viral incursions from an as yet unknown host, cannot be answered.
Researchers sought to determine a direction for infection; were DCs transmitting virus to humans or were humans infecting DCs? At a Qatari site, a farm owner and his employee became ill in mid-October 2013 and tested positive for MERS-CoV RNA in a sputum and throat swab sample, respectively. RT-rtPCRs found MERS-CoV RNA in 11 of 14 positive DC nasal swabs at the farm; six (43 %) positive by two or more assays [138] . The results indicated a recent outbreak had occurred in this herd; the first indication of MERS-CoV RNA found within DCs with a temporal association to human infections. Three positive DC samples were confirmed by sequencing a 358 nt portion of the spike gene; these sequences were identical to each other, again with close homology to other human and DC MERS-CoV sequences [138] . The DCs and human contacts yielded ORF1a and ORF4b sequences differing by only a single nucleotide each, clustering closely with the Hafr-Al-Batin_1_2013 variant [138] . Subsequent case studies found evidence of a concurrent human and DC infection and the direction of that infection was inferred to be from the ill DCs and to their human owners [117, 142, 146] . Partial genome sequences indicated that a human and a MERS-CoV RT-rtPCR positive DC had been infected by a variant of the same virus, harbouring the same distinct pattern of nucleotide polymorphisms. [142] All nine DC in the owner's herd, serially sampled, reacted in a recombinant S1 antigen ELISA, with the two animals that had been RT-rtPCR positive showing a small, verifiable rise in antibody titre [142] . A rise in titre theoretically begins 10 to 21 days after DC infection [142] . The authors suggested that the rise in titre in DC sera which occurred alongside a declining RNA load, while the patient was actively ill and hospitalized, indicated that the DCs were infected first followed by the owner [117, 142] . BCoV antibodies were also present, and rising in one of the two RT-rtPCR positive animals but no animal's antibodies could neutralise BCoV infection [142] .
Camel calving season occurs in the winter months (between late October and late February; Fig. 3 ) and this may be a time when there is increased risk to humans of spill-over due to new infections among naïve DC populations [128] . What role maternal camel antibody might play in delaying infection of calves remains unknown [128, 142] . Juvenile DCs appear to host active infection more often than adult DCs and thus the sacrificial slaughter of DCs, which must be five years of age or older (termed a thane), may not be accompanied by significant risk of exposure to infection. In contrast to earlier results, slaughterhouse workers who kill both younger and older DCs, may be an occupational group with significantly higher incidence of seropositivity to MERS-CoV when animals have active MERS-CoV infections [129, 139, [147] [148] [149] . Expanded virological investigations of African DCs may lead to more seropositive animals and geographic areas in which humans may be at risk. It is possible that there are areas where humans already harbour MERS-CoV infections that have not been identified because of an absence of laboratory surveillance. Virological investigations of bats may lead to findings of ancestral viruses and viral 'missing links' and identifying any other animal sources of zoonotic spread is important to inform options for reducing human exposures [56, 76] .
Infectious MERS-CoV added to DC, goat or cow milk and stored at 4°C could be recovered at least 72 h later and, if stored at 22°C, recovery was possible for up to 48 h [150] . MERS-CoV titre decreased somewhat when recovered from milk at 22°C but pasteurization completely ablated MERS-CoV infectivity [150] . In a subsequent study, MERS-CoV RNA was identified in the milk, nasal secretion and faeces of DCs from Qatar [151] .
A single study has examined the ability of MERS-CoV to survive in the environment [150] . Plastic or steel surfaces were inoculated with 10 6 TCID 50 of MERS-CoV at different temperature and relative humidity (RH) and virus recovery was attempted in cell culture. At high ambient temperature (30°C) and low RH (30 %) MERS-CoV remained viable for 24 h [150] . By comparison, a well known and efficently transmitted respiratory virus, influenza A virus, could not be recovered in culture beyond four hours under any conditions [150] . Aerosol experiments found MERS-CoV viability only decreased 7 % at low RH at 20°C. In comparison, influenza A virus decreased by 95 % [150] . MERS-CoV survival is inferior to that previously demonstrated for SARS-CoV [152] . For context, pathogenic bacteria can remain viable and airborne for 45 min in a coughed aerosol and can spread 4 m. MERS-CoV's ability to remain viable over long time periods gives it the capacity to thoroughly contaminate a room's surfaces when occupied by an infected and symptomatic patient [153] . Whether MERS-CoV can remain adrift and infectious for extended periods (truly airborne) remains unknown. Such findings expand our understanding of the possibilities for droplets to transmit respiratory viruses in many settings, including hospital waiting rooms, emergency departments, treatment rooms, open intensive care facilities and private patient rooms. The nature and quality of air exchange, circulation and filtration are important variables in risk measurement and reduction as is the use of negative pressure rooms to contain known cases. Droplet spread between humans is considered the mechanism of human-to-human transmission and the need for droplet precautions was emphasized after the Al-Ahsa hospital, the KSA and the South Korean outbreaks [21, 23, 154, 155] . By extrapolation, aerosol-generating events involving DCs (urination, defecation, and preparation and consumption of DC products) should be factored into risk measurement and reduction efforts and messaged using appropriate context. The provision of evidence supporting the best formulation of personal protective equipment to be worn by HCWs who receive, manage or conduct procedures on infectious cases remains a priority.
MERS-CoV was found and characterized because of its apparent association with severe, and therefore more obvious, illness in humans; we were the canaries in the coal mine. Sero-assays and prospective cohort studies have yet to determine the extent to which milder or asymptomatic cases contribute to MERS-CoV transmission chains. However, transmission of MERS-CoV is defined as sporadic (not sustained), intra-familial, often healthcare associated, inefficient and requiring close and prolonged contact [22, 31, 63, 93, 97, 102, 156] In a household study, 14 of 280 (5 %) contacts of 26 MERS-CoV positive index patients were RNA or antibody positive; the rate of general transmission, even in outbreaks is around 3 % [31] . It seems that the majority of human cases of MERS-CoV, even when numbers appear to increase suddenly, do not readily transmit to more than one other human so to date, the localized epidemic of MERS-CoV has not been self-sustaining [157] [158] [159] [160] [161] . That is to say, the basic reproduction number (R 0 ) -the average number of infections caused by one infected individual in a fully susceptible populationhas been close to one throughout various clusters and outbreaks. If R 0 was greater than 1, a sustained increase in case numbers would be expected. Some R o calculations may be affected by incomplete case contact tracing, limited community testing and how a case is defined. That MERS has had a constant presence in the Arabian Peninsula since 2012 is due to ongoing, sporadic spill-over events from DCs amplified by poorly controlled hospital outbreaks.
The first known MERS human-to-human transmission event was one characterized by acute LRT disease in a healthcare setting in Jordan. In stark contrast, a sero-survey of HCW who were sometimes in close and prolonged contact with the first, fatal MERS-CoV case in 2012 [162] , found none of the HCW had seroconverted four months later, despite an absence of eye protection and variable compliance with required PPE standards [162] .
Early on in the MERS story, samples for testing were mostly collected from patients with severe illness and not those with milder acute respiratory tract infections. Contacts of confirmed MERS cases were often observed for clinical illness, but not tested. These omissions may have confounded our understanding of MERS-CoV transmission and biased early data towards higher numbers of seriously ill and hospitalized patients, inflating the apparent proportion of fatal cases. Case-control studies were not a focus. As testing paradigms changed and contacts were increasingly tested, more asymptomatic and mild infections were recognized [163] .
A rise in the cases termed asymptomatic (which enlarge the denominator for calculations of the proportion of fatal cases, defined in [164] ) resulted in a drop in the proportion of fatal cases during the Jeddah-2014 outbreak. Historically, such rises are consistent with changing definitions and laboratory responses and clinical management of a newly discovered virus infection that was first noted only among the severely ill. Upon follow-up, over three-quarters of such MERS-CoV RNA positive people did recall having one or more symptoms at the time, despite being reported as asymptomatic [165] raising some question over the reliability of other reported data.
The proportion of fatal MERS cases within the KSA compared to outside the KSA, as well as the age, and sex distribution change in different ways when comparing MERS outbreaks. Approximately 43 % of MERS cases (549 of 1277) in the KSA were fatal betwen 2012 and December 2015 while 21 % (72 of 330) died among those occurring outside of the KSA. The total number of male cases always outnumber females and the proportion of male deaths is always greater than the proportion of females who die. However the proportion of male deaths from total males with MERS is a similar figure to that for females. In the KSA, there is a greater proportion of younger males among cases and deaths than were observed from the 2015 South Korean or the Jeddah-2014 outbreaks (Additional file 2: Figure S2 ). Why these aspects have differed may be due to differences in the time to presentation and diagnosis, the nature and quality of supportive care, the way a person became infected (habits, exposure to a human or zoonotic source, viral load, route of infection) or the extent to which different populations are burdened by underlying diseases [40] .
As a group, HCWs comprised 16 % of MERS cases in the KSA and South Korea. It is apparent that the weekly proportion of infected HCWs increases alongside each steep rise in overall detections (Fig. 5) . In May 2013, the WHO published guidelines for IPC during care of probable or confirmed cases of MERS-CoV infection in a healthcare setting [166] . This is explainable because to date, each case rise has been intimately associated with healthcare-facility related outbreaks [118] . These rises in MERS-CoV detections can decrease the average age during each event because HCWs are usually younger than inpatients with MERS. Healthcare facilities have been a regular target for suggested improvements aimed at improving infection prevention and control (IPC) procedures [115, 118] .
Most of the analysis of MERS-CoV genetics has been performed using high throughput or "deep" sequencing methods for complete genome deduction [167] [168] [169] . MERS-CoV was the first subject of such widespread use of deep sequencing to study an emerging viral outbreak with global reach. The technique can produce genomic [207] [208] [209] . Earlier and subsequent versions of this chart are maintained on a personal blog [210] length coverage in a single experiment with highly repetitious measurement of each nucleotide position [52, 140] . Despite assays having been published early on, subgenomic sequencing, once the mainstay of viral outbreak studies, has less often been published during MERS-CoV characterization [48] . As more genomes from both humans and DCs have been characterized, two clades have become apparent; A and B (Fig. 6) . Clade A contains only human-derived MERS-CoV genomes from Jordan, while Clade B comprises the majority of human and camel genomes deduced thus far [168] .
Two studies during 2015, one looking at Jeddah-2014 MERS-CoV variants and another looking at a variant exported from South Korea to China, have now identified signs of genetic recombination among MERS-CoV variants. While human and camel whole genome sequences have retained >99 % identity with each other, members of genetically distinct lineages can and do swap genetic material when suitable conditions and coinfections co-occur [170] [171] [172] . Shared identity implies that the major source for human acquisition is the DC, rather than another animal, although more testing of other animal species is needed to confirm that conclusion. Over a month, a DC virus sequenced on different occasions did not change at all indicating a degree of genomic stability in its host, supporting that DCs are the natural, rather than intermediate, host for the MERS-CoV we know today [77] . To date, recombination has been localised to breakpoints near the boundary between ORF1a and ORF1b regions, within the spike gene [170] and in the ORF1b region (Fig. 2) [172] . It is not unexpected that recombination should occur since it is well known among other CoVs [124] and because the majority of MERS-CoV whole genomes collected from samples spanning three years (2012-2015) and from humans, camels and different countries have shown close genetic identity to each other, with just enough subtle variation to support outbreak investigations so long as whole genome sequencing is applied [52, 77, 135, 138, 168, [173] [174] [175] .
Changes in genome sequence may herald alterations to virus transmissibility, replication, persistence, lethality or response to future drugs. If we have prior knowledge of the impact of genetic changes because of thorough characterization studies, we can closely Fig. 6 The genetic relationship between MERS-CoV nucleotide sequences (downloaded from GenBank using the listed accession numbers and from virological.org [212] ). This neighbour joining tree was created in MEGA v6 using an alignment of human and DCderived MERS-CoV sequences (Geneious v8.1 [211] ). Clades are indicated next to dark (Clade A) or pale (Clade B) blue vertical bars. Camel icons denote genomes from DCs. Healthcare or community outbreaks are boxed and labelled using previously described schemes [212, 213] monitor the genomic regions and better understand any changes in transmission or disease patterns as they occur. Genetic mutations noted during the largest of human outbreaks, Jeddah-2014, did not impart any major replicative or immunomodulatory changes when compared to earlier viral variants in vitro [156, 176] . However, we understand very little of the phenotypic outcomes that result from subtle genetic change in MERS-CoV genomes. To date no clinical relevance or obvious in vivo changes to viral replication, shedding or transmission has been reported or attributed to mutations or to new recombinant viruses [156] . But vigilance and larger, more contemporary and in vivo studies are needed.
Genome sequence located to a distinct clade were identified from an Egyptian DC that was probably imported from Sudan. This does not fit into either of the current clades [125, 168, 177] . A virus sequenced from a Neoromicia capensis bat was more closely related to MERS-CoV than other large bat-derived sequences had been to that point, but the genome of a variant of a MERS-CoV has yet to be discovered and deduced from any bat [125] .
Analyses of MERS-CoV genomes have shown that most single nucleotide differences among variants were located in the last third of the genome (Fig. 2) , which encodes the spike protein and accessory proteins [168] . At least nine MERS-CoV genomes contained amino acid substitutions in the receptor binding domain (RBD) of the spike protein and codons 158 (N-terminal region), 460 (RBD), 1020 (in heptad repeat 1), 1202 and 1208 bear investigation as markers of adaptive change [140, 169] . The spike protein had not changed in the recombinant MERS-CoV genome identified in China in 2015 but was reported to have varied at a higher rate than that for complete MERS-CoV genomes, among South Korean variants [172, 178] . This highlights that subgenomic regions may not always contain enough genetic diversity to prove useful for differentiating viral variants. Despite this, one assay amplifying a 615 nucleotide fragment of the spike S2 domain gene for Sanger sequencing agreed with the results generated by the sequencing of a some full genomes and was useful to define additional sequence groupings [177] .
Genomic sequence can also be used to define the geographic boundaries of a cluster or outbreak and monitor its progress, based on the similarity of the variants found among infected humans and animals when occurring together, or between different sites and times (Fig. 6 ) [169] . This approach was employed when defining the geographically constrained MERS hospital outbreak in Al-Ahsa, which occurred between 1 st April and 23 rd May 2013, as well as clusters in Buraidah and a community outbreak in Hafr Al-Batin, the KSA. Genomic sequencing identified that approximately 12 MERS-CoV detections from a community outbreak in Hafr Al-Batin between June and August 2013 may have been triggered by an index case becoming infected through DC contact [175] . Sequencing MERS-CoV genomes from the 2013 Al-Ahsa hospital outbreak indicated that multiple viral variants contributed to the cases but that most were similar enough to each other to be consistent with human-tohuman transmission. Molecular epidemiology has revealed otherwise hidden links in transmission chains encompassing a period of up to five months [179] . However, most outbreaks have not continued for longer than two to three months and so opportunities for the virus to adapt further to humans through co-infection and sustained serial passage have been rare [169] . In Riyadh-2014, genetic evidence supported the likelihood of multiple external introductions of virus, implicating a range of healthcare facilities in an event that otherwise looked contiguous [23, 168, 179] . Riyadh is a nexus for camel and human travel and has had more MERS cases than any other region of the KSA to date but also harbours a wide range of MERS-CoV variants [128, 167, 179] . However the South Korean outbreak originated from a single infected person, resulting in three to four generations of cases [180, 181] . Studies of this apparently recombinant viral variant did not find an increased evolutionary rate and no sign of virus adaptation thus the outbreak seems to have been driven by circumstance rather than circumstance together with mutation [181] .
For many MERS cases detected outside the Arabian Peninsula, extensive contact tracing has been performed and the results described in detail. Contact tracing is essential to contain the emergence and transmission of a new virus and today it is supported by molecular epidemiology. Although it is an expensive and time consuming process, contact tracing can identify potential new infections and through active or passive monitoring, react more rapidly if disease does develop. Results of contact tracing to date have found that onward transmission among humans is an infrequent event. For example, there were 83 contacts, both symptomatic and asymptomatic, of a case treated in Germany who travelled from the UAE but no sign of virus or antibody were found in any of them [73] . The very first MERS case had made contact with 56 HCWs and 48 others, but none developed any indication of infection [162] . In a study of 123 contacts of a case treated in France, only seven matched the definition for a possible case and were tested; one who had shared a 20 m 2 hospital room while in a bed 1.5 m away from the index case for a prolonged period was positive [26] . None of the contacts of the first two MERS cases imported into the USA in 2014 contained any MERS-CoV footprint [182] and none of the 131 contacts of two travellers returning to the Netherlands developed MERS-CoV antibodies or tested RNA positive [25, 183] . Analyses of public data reveal many likely instances of nosocomial acquisition of infection in the Arabian Peninsula and these data may be accompanied by some details noting contact with a known case or facility. One example identified the likely role of a patient with a subclinical infection, present in a hospital during their admission for other reasons, as the likeliest index case triggering a family cluster [93] . Contact tracing was a significant factor in the termination of a 2015 outbreak involving multiple South Korean hospitals [184] . Such studies demonstrate the necessity of finding and understanding a role for mild and asymptomatic cases, together with restricting close contact or prolonged exposure of infected people to others, especially older family members and friends with underlying disease (Fig. 4c) .
The hospital-associated outbreak in Jeddah in 2014 was the largest and most rapid accumulation of MERS-CoV detections to date. The greatest number of MERS-CoV detections of any month on record occurred in Jeddah in April. The outbreak was mostly (>60 % of cases) associated with human-to-human spread within hospital environments and resulted from a lack of, or breakdown in, infection prevention and control [37, 185, 186] . A rise in fatalities followed the rapid increase in case numbers.
In 2015 two large outbreaks occurred. South Korea was the site of the first large scale outbreak outside the Arabian Peninsula and produced the first cases in both South Korea and China, occurring between May and July 2015. This was closely followed by a distinct outbreak in Ar Riyad province in the KSA which appeared to come under control in early November.
After staying in Bahrain for two weeks, a 68 year old male (68 M) travelled home to South Korea via Qatar, arriving free of symptoms on the 4 th May 2015 [187] . He developed fever, myalgia and a cough nearly a week later (11 th ). He visited a clinic as an outpatient between the 12 th and 15 th of May and was admitted to Hospital A on the 15 th [188] . He was discharged from Hospital A on the 17 th then visited and was admitted to the emergency department of Hospital B on the 18 th . During this second stay, a sputum sample was taken and tested positive for MERS-CoV on the 20 th [187, 188] , triggering transfer to the designated isolation treatment facility. Over a period of 10 days, the index case was seen at three different hospitals, demonstrating a key feature of "hospital shopping" that shaped the South Korean outbreak. Approximately 34 people were infected during this time [187] . In total 186 cases were generated in this outbreak, all linked through a single transmission chain to 68 M; 37 cases died [189] . In South Korea, the national health insurance system provides for relatively low cost medical care, defraying some costs by making family members responsible for a portion of the ministration of the sick, resulting in them sometimes staying for long periods in the rooms that often have more than four beds in them [24] . Other factors thought to have enabled this outbreak included unfamiliarity of local clinicians with MERS, ease with which the public can visit and be treated by tertiary hospitals, the custom of visiting sick friends and relatives in hospitals, the hierarchical nature of Korean society, crowded emergency rooms, poor IPC measures, a lack of negative pressure isolation rooms and poor inter-hospital communication of patient disease histories [24, [190] [191] [192] . All of the reported transmission occurred across three or four generations and apart from one unknown source, were all hospital-acquired [24, 120, 181, [193] [194] [195] . Few clinical details about these cases have been reported to date and detail on transmission and contact tracing is minimal. The hospitals involved were initially not identified, governmental guidance and actions produced confusing messages and there was very limited communication at all early on which resulted in unnecessary concern, distrust and a distinct economic impact [191, [196] [197] [198] . Early in the outbreak, a infected traveller, the son of an identified case in South Korea, passed through Hong Kong on his way to China where he was located, isolated and cared for in China [91, 199, 200] . No contacts became ill. The outbreak was brought under control in late July/ early August [201] after improved IPC measures were employed, strong contact tracing monitoring and quarantine, expanded laboratory testing, hospitals were better secured, specialized personnel were dispatched to manage cases and international cooperation increased [202, 203] . A review of public data showed that, as for MERS in the KSA, older age and the presence of underlying disease were significantly associated with a fatal outcome in South Korea. [40] Even though R 0 is <1, super-spreading events facilitated by circumstances created in healthcare settings and characterized by cluster sizes over 150, such as this one, are not unexpected from MERS-CoV infection [204] . The dynamic of an outbreak depends on the R 0 and an individual's viral shedding patterns, contact type and frequency, hospital procedures and population structure and density [204] .
In the region of Ar Riyad, including the capital city of Riyadh, a hospital based cluster began, within a single hospital, from late June 2015 [205] . By mid-September there had been approximately170 cases reported but the outbreak appeared to been brought under control in November.
It became apparent early on that MERS-CoV spread relatively ineffectively from human-to-human. Despite ongoing and possibly seasonal introduction of virus to the human population via infected DCs and perhaps other animals yet to be identified, the vast majority of MERS-CoV transmission has occurred from infected to uninfected humans in close and prolonged contact through circumstances created by poor infection control in health care settings. This opportunistic virus has had its greatest impact on those with underlying diseases and such vulnerable people, sometimes suffering multiple comorbidities, have been most often associated with hospitals, creating a perfect storm of exposure, transmission and mortality. It remains unclear if this group are uniquely affected by MERS-CoV or if other respiratory virus infections, including those from HCoVs, produce a similarly serious impact. In South Korea, a single imported case created an outbreak of 185 cases and 36 deaths that had a disproportionate impact on economic performance, community behaviour and trust in government and the health care system. Household human-to human transmission occurs but is also limited. Educational programs will be essential tools for combatting the spread of MERS-CoV both within urban and regional communities and for the health care setting.
Vigilance remains important for containment since MERS-CoV is a virus with a genetic makeup that has been observed for only three years and is not stable. Among all humans reported to be infected, nearly 40 % have died. Continued laboratory testing, sequencing, analysis, timely data sharing and clear communication are essential for such vigilance to be effective. Global alignment of case definitions would further aid accurate calculation of a case fatality ratio by including subclinical case numbers. Whole genome sequencing has been used extensively to study MERS-CoV travel and variation and although it remains a tool for experts, it appears to be the best tool for the job.
MERS and SARS have some clinical similarities but they also diverge significantly [206] . Defining characteristics include the higher PFC among MERS cases (above 50 % in 2013 and currently at 30-40 %; well above the 9 % of SARS) and the higher association between fatal MERS and older males with underlying comorbidities. For the viruses, MERS-CoV has a broader tropism, grows more rapidly in vitro, more rapidly induces cytopathogenic change, triggers distinct transcriptional responses, makes use of a different receptor, induces a more proinflammatory state and has a delayed innate antiviral response compared to SARS-CoV.
There appears to be a 2-3 % prevalence of MERS-CoV in the KSA with a 5 % chance of secondary transmission within the household. There is an increased risk of infection through certain occupations at certain times and a much greater chance for spread to other humans during circumstances created by humans, which drives more effective transmission than any R 0 would predict on face value. Nonetheless, despite multiple mass gatherings that have afforded the virus many millions of opportunities to spread, there have remarkably been no reported outbreaks of MERS or MERS-CoV during or immediately after these events. There is no evidence that MERS-CoV is a virus of pandemic concern. Nonetheless, hospital settings continue to describe MERS cases and outbreaks in the Arabian Peninsula. As long as we facilitate the spread of MERS-CoV among our most vulnerable populations, the world must remain on alert for cases which may be exported more frequently when a host country with infected camel reservoirs is experiencing human clusters or outbreaks.
The MERS-CoV appears to be an enzootic virus infecting the DC URT with evidence of recent genetic recombination. It may once have had its origins among bats, but evidence is lacking and the relevance of that to today's ongoing epidemic is academic. Thanks to quick action, the sensitive and rapid molecular diagnostic tools required to achieve rapid and sensitive detection goal have been in place and made widely available since the virus was reported in 2012. RT-PCR testing of LRT samples remains the gold standard for MERS-CoV confirmation. Serological tools continue to emerge but they are in need of further validation using samples from mild and asymptomatic infections and a densely sampled cohort study to follow contacts of new cases may address this need. Similarly, the important question of whether those who do shed MERS-CoV RNA for extended periods are infectious while appearing well, continues to go unanswered. It is even unclear just how many 'asymptomatic' infections have been described and reported correctly which in turn raises questions about the reliability of other clinical data collection to date. While the basic virology of MERS-CoV has advanced over the course of the past three years, understanding what is happening in, and the interplay between, camel, environment and human is still in its infancy.
Additional file 1: Figure S1 . The | What is the duration between when illness begins in one person and subsequently spreads to another? | false | 4,211 | {
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2,592 | A mathematical model for simulating the phase-based transmissibility of a novel coronavirus
https://doi.org/10.1186/s40249-020-00640-3
SHA: 018269476cd191365d6b8bed046078aea07c8c01
Authors: Yin, Tian-Mu Chen; Jia, Rui; Qiu-Peng, Wang; Ze-Yu, Zhao; Jing-An, Cui; Ling
Date: 2020
DOI: 10.1186/s40249-020-00640-3
License: cc-by
Abstract: Background As reported by the World Health Organization, a novel coronavirus (2019-nCoV) was identified as the causative virus of Wuhan pneumonia of unknown etiology by Chinese authorities on 7 January, 2020. The virus was named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by International Committee on Taxonomy of Viruses on 11 February, 2020. This study aimed to develop a mathematical model for calculating the transmissibility of the virus. Methods In this study, we developed a Bats-Hosts-Reservoir-People transmission network model for simulating the potential transmission from the infection source (probably be bats) to the human infection. Since the Bats-Hosts-Reservoir network was hard to explore clearly and public concerns were focusing on the transmission from Huanan Seafood Wholesale Market (reservoir) to people, we simplified the model as Reservoir-People (RP) transmission network model. The next generation matrix approach was adopted to calculate the basic reproduction number (R 0) from the RP model to assess the transmissibility of the SARS-CoV-2. Results The value of R 0 was estimated of 2.30 from reservoir to person and 3.58 from person to person which means that the expected number of secondary infections that result from introducing a single infected individual into an otherwise susceptible population was 3.58. Conclusions Our model showed that the transmissibility of SARS-CoV-2 was higher than the Middle East respiratory syndrome in the Middle East countries, similar to severe acute respiratory syndrome, but lower than MERS in the Republic of Korea.
Text: On 31 December 2019, the World Health Organization (WHO) China Country Office was informed of cases of pneumonia of unknown etiology (unknown cause) detected in Wuhan City, Hubei Province of China, and WHO reported that a novel coronavirus (2019-nCoV), which was named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by International Committee on Taxonomy of Viruses on 11 February, 2020, was identified as the causative virus by Chinese authorities on 7 January [1] . It is reported that the virus might be bat origin [2] , and the transmission of the virus might related to a seafood market (Huanan Seafood Wholesale Market) exposure [3, 4] . The genetic features and some clinical findings of the infection have been reported recently [4] [5] [6] . Potentials for international spread via commercial air travel had been assessed [7] . Public health concerns are being paid globally on how many people are infected and suspected.
Therefore, it is urgent to develop a mathematical model to estimate the transmissibility and dynamic of the transmission of the virus. There were several researches focusing on mathematical modelling [3, 8] . These researches focused on calculating the basic reproduction number (R 0 ) by using the serial intervals and intrinsic growth rate [3, 9, 10] , or using ordinary differential equations and Markov Chain Monte Carlo methods [8] . However, the bat origin and the transmission route form the seafood market to people were not considered in the published models.
In this study, we developed a Bats-Hosts-Reservoir-People (BHRP) transmission network model for simulating the potential transmission from the infection source (probably be bats) to the human infection. Since the Bats-Hosts-Reservoir network was hard to explore clearly and public concerns were focusing on the transmission from Huanan Seafood Wholesale Market (reservoir) to people, we simplified the model as Reservoir-People (RP) transmission network model, and R 0 was calculated based on the RP model to assess the transmissibility of the SARS-CoV-2.
The reported cases of SARS-CoV-2, which have been named as COVID-19, were collected for the modelling study from a published literature [3] . As reported by Li et al. [3] , the onset date of the first case was on 7 December, 2020, and the seafood market was closed on 1 January, 2020 [11] . The epidemic curve from 7 December, 2019 to 1 January, 2020 was collected for our study, and the simulation time step was 1 day. fourth-order Runge-Kutta method, with tolerance set at 0.001, was used to perform curve fitting. While the curve fitting is in progress, Berkeley Madonna displays the root mean square deviation between the data and best run so far. The coefficient of determination (R 2 ) was employed to assess the goodness-of-fit. SPSS 13.0 (IBM Corp., Armonk, NY, USA) was employed to calculate the R 2 .
The Bats-Hosts-Reservoir-People (BHRP) transmission network model
The BHRP transmission network model was posted to bioRxiv on 19 January, 2020 [12] . We assumed that the virus transmitted among the bats, and then transmitted to unknown hosts (probably some wild animals). The hosts were hunted and sent to the seafood market which was defined as the reservoir of the virus. People exposed to the market got the risks of the infection (Fig. 1) . The BHRP transmission network model was based on the following assumptions or facts:
a) The bats were divided into four compartments: susceptible bats (S B ), exposed bats (E B ), infected bats (I B ), and removed bats (R B ). The birth rate and death rate of bats were defined as n B and m B . In this model, we set Ʌ B = n B × N B as the number of the newborn bats where N B refer to the total number of bats. The incubation period of bat infection was defined as 1/ω B and the infectious period of bat infection was defined as 1/γ B . The S B will be infected through sufficient contact with I B , and the transmission rate was defined as β B . b) The hosts were also divided into four compartments: susceptible hosts (S H ), exposed hosts (E H ), infected hosts (I H ), and removed hosts (R H ). The birth rate and death rate of hosts were defined as n H and m H . In this model, we set Ʌ H = n H × N H where N H refer to the total number of hosts. The incubation period of host infection was defined as 1/ω H and the infectious period of host infection was defined as 1/γ H . The S H will be infected through sufficient contact with I B and I H , and the transmission rates were defined as β BH and β H , respectively. c) The SARS-CoV-2 in reservoir (the seafood market) was denoted as W. We assumed that the retail purchases rate of the hosts in the market was a, and that the prevalence of SARS-CoV-2 in the purchases was I H /N H , therefore, the rate of the SARS-CoV-2 in W imported form the hosts was aWI H /N H where N H was the total number of hosts. We also assumed that symptomatic infected people and asymptomatic infected people could export the virus into W with the rate of μ P and μ' P , although this assumption might occur in a low probability. The virus in W will subsequently leave the W compartment at a rate of εW, where 1/ε is the lifetime of the virus. d) The people were divided into five compartments:
susceptible people (S P ), exposed people (E P ), symptomatic infected people (I P ), asymptomatic infected people (A P ), and removed people (R P ) including recovered and death people. The birth rate and death rate of people were defined as n P and m P . In this model, we set Ʌ P = n P × N P where N P refer to the total number of people. The incubation period and latent period of human infection was defined as 1/ω P and 1/ω' P . The infectious period of I P and A P was defined as 1/γ P and 1/γ' P . The proportion of asymptomatic infection was defined as δ P . The S P will be infected through sufficient contact with W and I P , and the transmission rates were defined as β W and β P , respectively. We also assumed that the transmissibility of A P was κ times that of I P , where 0 ≤ κ ≤ 1.
The parameters of the BHRP model were shown in Table 1 .
We assumed that the SARS-CoV-2 might be imported to the seafood market in a short time. Therefore, we added the further assumptions as follows:
a) The transmission network of Bats-Host was ignored. b) Based on our previous studies on simulating importation [13, 14] , we set the initial value of W as following impulse function:
In the function, n, t 0 and t i refer to imported volume of the SARS-CoV-2 to the market, start time of the simulation, and the interval of the importation.
Therefore, the BHRP model was simplified as RP model and is shown as follows:
During the outbreak period, the natural birth rate and death rate in the population was in a relative low level. However, people would commonly travel into and out from Wuhan City mainly due to the Chinese New Year holiday. Therefore, n P and m P refer to the rate of people traveling into Wuhan City and traveling out from Wuhan City, respectively.
In the model, people and viruses have different dimensions. Based on our previous research [15] , we therefore used the following sets to perform the normalization:
In the normalization, parameter c refers to the relative shedding coefficient of A P compared to I P . The normalized RP model is changed as follows:
The transmissibility of the SARS-CoV-2 based on the RP model
In this study, we used the R 0 to assess the transmissibility of the SARS-CoV-2. Commonly, R 0 was defined as the expected number of secondary infections that result from introducing a single infected individual into an otherwise susceptible population [13, 16, 17] . If R 0 > 1, the outbreak will occur. If R 0 < 1, the outbreak will toward an end. In this study, R 0 was deduced from the RP model by the next generation matrix approach [18] . The multiple of the transmissibility of A P to that of I P .
The parameters were estimated based on the following facts and assumptions:
a) The mean incubation period was 5.2 days (95% confidence interval [CI]: 4.1-7.0) [3] . We set the same value (5.2 days) of the incubation period and the latent period in this study. Thus, ω P = ω' P = 0.1923. b) There is a mean 5-day delay from symptom onset to detection/hospitalization of a case (the cases detected in Thailand and Japan were hospitalized from 3 to 7 days after onset, respectively) [19] [20] [21] . The duration from illness onset to first medical visit for the 45 patients with illness onset before January 1 was estimated to have a mean of 5.8 days (95% CI: 4.3-7.5) [3] . In our model, we set the infectious period of the cases as 5.8 days. Therefore, γ P = 0.1724. c) Since there was no data on the proportion of asymptomatic infection of the virus, we simulated the baseline value of proportion of 0.5 (δ P = 0.5). d) Since there was no evidence about the transmissibility of asymptomatic infection, we assumed that the transmissibility of asymptomatic infection was 0.5 times that of symptomatic infection (κ = 0.5), which was the similar value as influenza [22] . We assumed that the relative shedding rate of A P compared to I P was 0.5. Thus, c = 0.5. e) Since 14 January, 2020, Wuhan City has strengthened the body temperature detection of passengers leaving Wuhan at airports, railway stations, long-distance bus stations and passenger terminals. As of January 17, a total of nearly 0.3 million people had been tested for body temperature [23] . In Wuhan, there are about 2.87 million mobile population [24] . We assumed that there was 0.1 million people moving out to Wuhan City per day since January 10, 2020, and we believe that this number would increase (mainly due to the winter vacation and the Chinese New Year holiday) until 24 January, 2020. This means that the 2.87 million would move out from Wuhan City in about 14 days. Therefore, we set the moving volume of 0.2 million per day in our model. Since the population of Wuhan was about 11 million at the end of 2018 [25] , the rate of people traveling out from Wuhan City would be 0.018 (0.2/11) per day. However, we assumed that the normal population mobility before January 1 was 0.1 times as that after January 10. Therefore, we set the rate of people moving into and moving out from Wuhan City as 0.0018 per day (n P = m P = 0.0018).
f) The parameters b P and b W were estimated by fitting the model with the collected data. g) At the beginning of the simulation, we assumed that the prevalence of the virus in the market was 1/100000. h) Since the SARS-CoV-2 is an RNA virus, we assumed that it could be died in the environment in a short time, but it could be stay for a longer time (10 days) in the unknown hosts in the market. We set ε = 0.1.
In this study, we assumed that the incubation period (1/ ω P ) was the same as latent period (1/ω' P ) of human infection, thus ω P = ω' P . Based on the equations of RP model, we can get the disease free equilibrium point as: In the matrix:
By the next generation matrix approach, we can get the next generation matrix and R 0 for the RP model:
The R 0 of the normalized RP model is shown as follows:
Our modelling results showed that the normalized RP model fitted well to the reported SARS-CoV-2 cases data (R 2 = 0.512, P < 0.001) (Fig. 2) . The value of R 0 was estimated of 2.30 from reservoir to person, and from person to person and 3.58 from person to person which means that the expected number of secondary infections that result from introducing a single infected individual into an otherwise susceptible population was 3.58.
In this study, we developed RP transmission model, which considering the routes from reservoir to person and from person to person of SARS-CoV-2 respectively. We used the models to fit the reported data in Wuhan City, China from published literature [3] . The simulation results showed that the R 0 of SARS-CoV-2 was 3.58 from person to person. There was a research showed that the R 0 of SARS-CoV-2 was 2.68 (95% CI: 2.47-2.86) [8] . Another research showed that the R 0 of SARS-CoV-2 was 2.2 (95% CI: 1.4-3.9) [3] . The different values might be due to the different methods. The methods which Li et al. employed were based on the epidemic growth rate of the epidemic curve and the serial interval [3] . Our previous study showed that several methods could be used to calculate the R 0 based on the epidemic growth rate of the epidemic curve and the serial interval, and different methods might result in different values of R 0 [26] . Our results also showed that the R 0 of SARS-CoV-2 was 2.30 from reservoir to person which was lower than that of person to person. This means that the transmission route was mainly from person to person rather than from reservoir to person in the early stage of the transmission in Wuhan City. However, this result was based on the limited data from a published literature, and it might not show the real situation at the early stage of the transmission.
Researches showed that the R 0 of severe acute respiratory syndrome (SARS) was about 2.7-3.4 or 2-4 in Hong Kong, China [27, 28] . Another research found that the R 0 of SARS was about 2.1 in Hong Kong, China, 2.7 in Singapore, and 3.8 in Beijing, China [29] . Therefore, we believe that the commonly acceptable average value of the R 0 of SARS might be 2.9 [30] . The transmissibility of the Middle East respiratory syndrome (MERS) is much lower than SARS. The reported value of the R 0 of MERS was about 0.8-1.3 [31] , with the inter-human transmissibility of the disease was about 0.6 or 0.9 in Middle East countries [32] . However, MERS had a high transmissibility in the outbreak in the Republic of Korea with the R 0 of 2.5-7.2 [33, 34] . Therefore, the transmissibility of SARS-CoV-2 might be higher than MERS in the Middle East countries, similar to SARS, but lower than MERS transmitted in the Republic of Korea.
To contain the transmission of the virus, it is important to decrease R 0 . According to the equation of R 0 deduced from the simplified RP model, R 0 is related to many parameters. The mainly parameters which could be changed were b P , b W , and γ. Interventions such as wearing masks and increasing social distance could decrease the b P , the intervention that close the seafood market could decrease the b W , and shorten the duration form symptoms onset to be diagnosed could decrease 1/γ. All these interventions could decrease the effective reproduction number and finally be helpful to control the transmission.
Since there are too many parameters in our model, several limitations exist in this study. Firstly, we did not use the detailed data of the SARS-CoV-2 to perform the estimation instead of using the data from literatures [3] . We simulated the natural history of the infection that the proportion of asymptomatic infection was 50%, and the transmissibility of asymptomatic infection was half of that of symptomatic infection, which were different to those of MERS and SARS. It is known that the proportion of asymptomatic infection of MERS and SARS was lower than 10%. Secondly, the parameters of population mobility were not from an accurate dataset. Thirdly, since there was no data of the initial prevalence of the virus in the seafood market, we assumed the initial value of 1/100 000. This assumption might lead to the simulation been under-or over-estimated. In addition, since we did not consider the changing rate of the individual's activity (such as wearing masks, increasing social distance, and not to travel to Wuhan City), the estimation of importation of the virus might not be correct. All these limitations will lead to the uncertainty of our results. Therefore, the accuracy and the validity of the estimation would be better if the models fit the first-hand data on the population mobility and the data on the natural history, the epidemiological characteristics, and the transmission mechanism of the virus.
By calculating the published data, our model showed that the transmissibility of SARS-CoV-2 might be higher than MERS in the Middle East countries, similar to SARS, but lower than MERS in the Republic of Korea. Since the objective of this study was to provide a mathematical model for calculating the transmissibility of SARS-CoV-2, the R 0 was estimated based on limited data which published in a literature. More data were needed to estimate the transmissibility accurately. | What is the reported value of R0 for MERS? | false | 2,773 | {
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2,642 | First cases of coronavirus disease 2019 (COVID-19) in the WHO European Region, 24 January to 21 February 2020
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7068164/
SHA: ce358c18aac69fc83c7b2e9a7dca4a43b0f60e2e
Authors: Spiteri, Gianfranco; Fielding, James; Diercke, Michaela; Campese, Christine; Enouf, Vincent; Gaymard, Alexandre; Bella, Antonino; Sognamiglio, Paola; Sierra Moros, Maria José; Riutort, Antonio Nicolau; Demina, Yulia V.; Mahieu, Romain; Broas, Markku; Bengnér, Malin; Buda, Silke; Schilling, Julia; Filleul, Laurent; Lepoutre, Agnès; Saura, Christine; Mailles, Alexandra; Levy-Bruhl, Daniel; Coignard, Bruno; Bernard-Stoecklin, Sibylle; Behillil, Sylvie; van der Werf, Sylvie; Valette, Martine; Lina, Bruno; Riccardo, Flavia; Nicastri, Emanuele; Casas, Inmaculada; Larrauri, Amparo; Salom Castell, Magdalena; Pozo, Francisco; Maksyutov, Rinat A.; Martin, Charlotte; Van Ranst, Marc; Bossuyt, Nathalie; Siira, Lotta; Sane, Jussi; Tegmark-Wisell, Karin; Palmérus, Maria; Broberg, Eeva K.; Beauté, Julien; Jorgensen, Pernille; Bundle, Nick; Pereyaslov, Dmitriy; Adlhoch, Cornelia; Pukkila, Jukka; Pebody, Richard; Olsen, Sonja; Ciancio, Bruno Christian
Date: 2020-03-05
DOI: 10.2807/1560-7917.es.2020.25.9.2000178
License: cc-by
Abstract: In the WHO European Region, COVID-19 surveillance was implemented 27 January 2020. We detail the first European cases. As at 21 February, nine European countries reported 47 cases. Among 38 cases studied, 21 were linked to two clusters in Germany and France, 14 were infected in China. Median case age was 42 years; 25 were male. Late detection of the clusters’ index cases delayed isolation of further local cases. As at 5 March, there were 4,250 cases.
Text: In the WHO European Region, COVID-19 surveillance was implemented 27 January 2020. We detail the first European cases. As at 21 February, nine European countries reported 47 cases. Among 38 cases studied, 21 were linked to two clusters in Germany and France, 14 were infected in China. Median case age was 42 years; 25 were male. Late detection of the clusters' index cases delayed isolation of further local cases. As at 5 March, there were 4,250 cases.
A cluster of pneumonia of unknown origin was identified in Wuhan, China, in December 2019 [1] . On 12 January 2020, Chinese authorities shared the sequence of a novel coronavirus termed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) isolated from some clustered cases [2] . Since then, the disease caused by SARS-CoV-2 has been named coronavirus disease 2019 (COVID -19) . As at 21 February 2020, the virus had spread rapidly mostly within China but also to 28 other countries, including in the World Health Organization (WHO) European Region [3] [4] [5] .
Here we describe the epidemiology of the first cases of COVID-19 in this region, excluding cases reported in the United Kingdom (UK), as at 21 February 2020. The study includes a comparison between cases detected among travellers from China and cases whose infection was acquired due to subsequent local transmission.
On 27 January 2020, the European Centre for Disease Prevention and Control (ECDC) and the WHO Regional Office for Europe asked countries to complete a WHO standard COVID-19 case report form for all confirmed and probable cases according to WHO criteria [6] [7] [8] . The overall aim of surveillance at this time was to support the global strategy of containment of COVID-19 with rapid identification and follow-up of cases linked to affected countries in order to minimise onward transmission. The surveillance objectives were to: describe the key epidemiological and clinical characteristics of COVID-19 cases detected in Europe; inform country preparedness; and improve further case detection and management. Data collected included demographics, history of recent travel to affected areas, close contact with a probable or confirmed COVID-19 case, underlying conditions, signs and symptoms of disease at onset, type of specimens from which the virus was detected, and clinical outcome. The WHO case definition was adopted for surveillance: a confirmed case was a person with laboratory confirmation of SARS-CoV-2 infection (ECDC recommended two separate SARS-CoV-2 RT-PCR tests), irrespective of clinical signs and symptoms, whereas a probable case was a suspect case for whom testing for SARS-CoV-2 was inconclusive or positive using a pan-coronavirus assay [8] . By 31 January 2020, 47 laboratories in 31 countries, including 38 laboratories in 24 European Union and European Economic Area (EU/EEA) countries, had diagnostic capability for SARS-CoV-2 available (close to 60% of countries in the WHO European Region), with cross-border shipment arrangements in place for many of those lacking domestic testing capacity. The remaining six EU/EEA countries were expected to have diagnostic testing available by mid-February [9] .
As at 09:00 on 21 February 2020, 47 confirmed cases of COVID-19 were reported in the WHO European Region and one of these cases had died [4] . Data on 38 of these cases (i.e. all except the nine reported in the UK) are included in this analysis.
The first three cases detected were reported in France on 24 January 2020 and had onset of symptoms on 17, 19 and 23 January respectively [10] . The first death was reported on 15 February in France. As at 21 February, nine countries had reported cases ( Figure) : Belgium (1), Finland (1), France (12), Germany (16), Italy (3), Russia (2), Spain (2), Sweden (1) and the UK (9 -not included further).
The place of infection (assessed at national level based on an incubation period presumed to be up to 14 days [11] , travel history and contact with probable or confirmed cases as per the case definition) was reported for 35 cases (missing for three cases), of whom 14 were infected in China (Hubei province: 10 cases; Shandong province: one case; province not reported for three cases). The remaining 21 cases were infected in Europe. Of these, 14 were linked to a cluster in Bavaria, Germany, and seven to a cluster in Haute-Savoie, France [12, 13] . Cases from the Bavarian cluster were reported from Germany and Spain, whereas cases from the Haute-Savoie cluster were reported from France All but two cases were hospitalised (35 of 37 where information on hospitalisation was reported), although it is likely that most were hospitalised to isolate the person rather than because of severe disease. The time from onset of symptoms to hospitalisation (and isolation) ranged between 0 and 10 days with a mean of 3.7 days (reported for 29 cases). The mean number of days to hospitalisation was 2.5 days for cases imported from China, but 4.6 days for those infected in Europe. This was mostly a result of delays in identifying the index cases of the two clusters in France and Germany. In the German cluster, for example, the first three cases detected locally were hospitalised in a mean of 5.7 days, whereas the following six took only a mean of 2 days to be hospitalised.
Symptoms at the point of diagnosis were reported for 31 cases. Two cases were asymptomatic and remained so until tested negative. The asymptomatic cases were tested as part of screening following repatriation and during contact tracing respectively. Of the remaining 29, 20 reported fever, 14 reported cough and eight reported weakness. Additional symptoms reported included headaches (6 cases), sore throat (2), rhinorrhoea (2), shortness of breath (2), myalgia (1), diarrhoea (1) and nausea (1). Fever was reported as the sole symptom for nine cases. In 16 of 29 symptomatic cases, the symptoms at diagnosis were consistent with the case definition for acute respiratory infection [16] , although it is possible that cases presented additional symptoms after diagnosis and these were not reported.
Data on pre-existing conditions were reported for seven cases; five had no pre-existing conditions while one was reported to be obese and one had pre-existing cardiac disease. No data on clinical signs e.g. dyspnea etc. were reported for any of the 38 cases.
All hospitalised cases had a benign clinical evolution except four, two reported in Italy and two reported in France, all of whom developed viral pneumonia. All three cases who were aged 65 years or over were admitted to intensive care and required respiratory support and one French case died. The case who died was hospitalised for 21 days and required intensive care and mechanical ventilation for 19 days. The duration of hospitalisation was reported for 16 cases with a median of 13 days (range: 8-23 days). As at 21 February 2020, four cases were still hospitalised.
All cases were confirmed according to specific assays targeting at least two separate genes (envelope (E) gene as a screening test and RNA-dependent RNA polymerase (RdRp) gene or nucleoprotein (N) gene for confirmation) [8, 17] . The specimen types tested were reported for 27 cases: 15 had positive nasopharyngeal swabs, nine had positive throat swabs, three cases had positive sputum, two had a positive nasal swab, one case had a positive nasopharyngeal aspirate and one a positive endotracheal aspirate.
As at 09:00 on 21 February, few COVID-19 cases had been detected in Europe compared with Asia. However the situation is rapidly developing, with a large outbreak recently identified in northern Italy, with transmission in several municipalities and at least two deaths [18] . As at 5 March 2020, there are 4,250 cases including 113 deaths reported among 38 countries in the WHO European region [19] .
In our analysis of early cases, we observed transmission in two broad contexts: sporadic cases among travellers from China (14 cases) and cases who acquired infection due to subsequent local transmission in Europe (21 cases). Our analysis shows that the time from symptom onset to hospitalisation/case isolation was about 3 days longer for locally acquired cases than for imported cases. People returning from affected areas are likely to have a low threshold to seek care and be tested when symptomatic, however delays in identifying the index cases of the two clusters in France and Germany meant that locally acquired cases took longer to be detected and isolated. Once the exposure is determined and contacts identified and quarantined (171 contacts in France and 200 in Germany for the clusters in Haute-Savoie and Bavaria, respectively), further cases are likely to be rapidly detected and isolated when they develop symptoms [15, 20] . In the German cluster, for example, the first three cases detected locally were hospitalised in a mean of 5.7 days, whereas the following six were hospitalised after a mean of 2 days. Locally acquired cases require significant resources for contact tracing and quarantine, and countries should be prepared to allocate considerable public health resources during the containment phase, should local clusters emerge in their population. In addition, prompt sharing of information on cases and contacts through international notification systems such as the International Health Regulations (IHR) mechanism and the European Commission's European Early Warning and Response System is essential to contain international spread of infection.
All of the imported cases had a history of travel to China. This was consistent with the epidemiological situation in Asia, and supported the recommendation for testing of suspected cases with travel history to China and potentially other areas of presumed ongoing community transmission. The situation has evolved rapidly since then, however, and the number of countries reporting COVID-19 transmission increased rapidly, notably with a large outbreak in northern Italy with 3,089 cases reported as at 5 March [18, 19] . Testing of suspected cases based on geographical risk of importation needs to be complemented with additional approaches to ensure early detection of local circulation of COVID-19, including through testing of severe acute respiratory infections in hospitals irrespectively of travel history as recommended in the WHO case definition updated on 27 February 2020 [21] .
The clinical presentation observed in the cases in Europe is that of an acute respiratory infection. However, of the 31 cases with information on symptoms, 20 cases presented with fever and nine cases presented only with fever and no other symptoms. These findings, which are consistent with other published case series, have prompted ECDC to include fever among several clinical signs or symptoms indicative for the suspected case definition.
Three cases were aged 65 years or over. All required admission to intensive care and were tourists (imported cases). These findings could reflect the average older age of the tourist population compared with the local contacts exposed to infection in Europe and do not allow us to draw any conclusion on the proportion of severe cases that we could expect in the general population of Europe. Despite this, the finding of older individuals being at higher risk of a severe clinical course is consistent with the evidence from Chinese case series published so far although the majority of infections in China have been mild [22, 23] .
This preliminary analysis is based on the first reported cases of COVID-19 cases in the WHO European Region. Given the small sample size, and limited completeness for some variables, all the results presented should be interpreted with caution.
With increasing numbers of cases in Europe, data from surveillance and investigations in the region can build on the evidence from countries in Asia experiencing more widespread transmission particularly on disease spectrum and the proportion of infections with severe outcome [22] . Understanding the infection-severity is critical to help plan for the impact on the healthcare system and the wider population. Serological studies are vital to understand the proportion of cases who are asymptomatic. Hospital-based surveillance could help estimate the incidence of severe cases and identify risk factors for severity and death. Established hospital surveillance systems that are in place for influenza and other diseases in Europe may be expanded for this purpose. In addition, a number of countries in Europe are adapting and, in some cases, already using existing sentinel primary care based surveillance systems for influenza to detect community transmission of SARS-CoV-2. This approach will be used globally to help identify evidence of widespread community transmission and, should the virus spread and containment no longer be deemed feasible, to monitor intensity of disease transmission, trends and its geographical spread.
Additional research is needed to complement surveillance data to build knowledge on the infectious period, modes of transmission, basic and effective reproduction numbers, and effectiveness of prevention and case management options also in settings outside of China. Such special studies are being conducted globally, including a cohort study on citizens repatriated from China to Europe, with the aim to extrapolate disease incidence and risk factors for infection in areas with community transmission. Countries together with ECDC and WHO, should use all opportunities to address these questions in a coordinated fashion at the European and global level.
provided input to the outline, multiple versions of the manuscript and gave approval to the final draft. | What were the asymptomatic cases tested as? | false | 3,819 | {
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2,504 | Respiratory Viral Infections in Exacerbation of Chronic Airway Inflammatory Diseases: Novel Mechanisms and Insights From the Upper Airway Epithelium
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7052386/
SHA: 45a566c71056ba4faab425b4f7e9edee6320e4a4
Authors: Tan, Kai Sen; Lim, Rachel Liyu; Liu, Jing; Ong, Hsiao Hui; Tan, Vivian Jiayi; Lim, Hui Fang; Chung, Kian Fan; Adcock, Ian M.; Chow, Vincent T.; Wang, De Yun
Date: 2020-02-25
DOI: 10.3389/fcell.2020.00099
License: cc-by
Abstract: Respiratory virus infection is one of the major sources of exacerbation of chronic airway inflammatory diseases. These exacerbations are associated with high morbidity and even mortality worldwide. The current understanding on viral-induced exacerbations is that viral infection increases airway inflammation which aggravates disease symptoms. Recent advances in in vitro air-liquid interface 3D cultures, organoid cultures and the use of novel human and animal challenge models have evoked new understandings as to the mechanisms of viral exacerbations. In this review, we will focus on recent novel findings that elucidate how respiratory viral infections alter the epithelial barrier in the airways, the upper airway microbial environment, epigenetic modifications including miRNA modulation, and other changes in immune responses throughout the upper and lower airways. First, we reviewed the prevalence of different respiratory viral infections in causing exacerbations in chronic airway inflammatory diseases. Subsequently we also summarized how recent models have expanded our appreciation of the mechanisms of viral-induced exacerbations. Further we highlighted the importance of the virome within the airway microbiome environment and its impact on subsequent bacterial infection. This review consolidates the understanding of viral induced exacerbation in chronic airway inflammatory diseases and indicates pathways that may be targeted for more effective management of chronic inflammatory diseases.
Text: The prevalence of chronic airway inflammatory disease is increasing worldwide especially in developed nations (GBD 2015 Chronic Respiratory Disease Collaborators, 2017 Guan et al., 2018) . This disease is characterized by airway inflammation leading to complications such as coughing, wheezing and shortness of breath. The disease can manifest in both the upper airway (such as chronic rhinosinusitis, CRS) and lower airway (such as asthma and chronic obstructive pulmonary disease, COPD) which greatly affect the patients' quality of life (Calus et al., 2012; Bao et al., 2015) . Treatment and management vary greatly in efficacy due to the complexity and heterogeneity of the disease. This is further complicated by the effect of episodic exacerbations of the disease, defined as worsening of disease symptoms including wheeze, cough, breathlessness and chest tightness (Xepapadaki and Papadopoulos, 2010) . Such exacerbations are due to the effect of enhanced acute airway inflammation impacting upon and worsening the symptoms of the existing disease (Hashimoto et al., 2008; Viniol and Vogelmeier, 2018) . These acute exacerbations are the main cause of morbidity and sometimes mortality in patients, as well as resulting in major economic burdens worldwide. However, due to the complex interactions between the host and the exacerbation agents, the mechanisms of exacerbation may vary considerably in different individuals under various triggers. Acute exacerbations are usually due to the presence of environmental factors such as allergens, pollutants, smoke, cold or dry air and pathogenic microbes in the airway (Gautier and Charpin, 2017; Viniol and Vogelmeier, 2018) . These agents elicit an immune response leading to infiltration of activated immune cells that further release inflammatory mediators that cause acute symptoms such as increased mucus production, cough, wheeze and shortness of breath. Among these agents, viral infection is one of the major drivers of asthma exacerbations accounting for up to 80-90% and 45-80% of exacerbations in children and adults respectively (Grissell et al., 2005; Xepapadaki and Papadopoulos, 2010; Jartti and Gern, 2017; Adeli et al., 2019) . Viral involvement in COPD exacerbation is also equally high, having been detected in 30-80% of acute COPD exacerbations (Kherad et al., 2010; Jafarinejad et al., 2017; Stolz et al., 2019) . Whilst the prevalence of viral exacerbations in CRS is still unclear, its prevalence is likely to be high due to the similar inflammatory nature of these diseases (Rowan et al., 2015; Tan et al., 2017) . One of the reasons for the involvement of respiratory viruses' in exacerbations is their ease of transmission and infection (Kutter et al., 2018) . In addition, the high diversity of the respiratory viruses may also contribute to exacerbations of different nature and severity (Busse et al., 2010; Costa et al., 2014; Jartti and Gern, 2017) . Hence, it is important to identify the exact mechanisms underpinning viral exacerbations in susceptible subjects in order to properly manage exacerbations via supplementary treatments that may alleviate the exacerbation symptoms or prevent severe exacerbations.
While the lower airway is the site of dysregulated inflammation in most chronic airway inflammatory diseases, the upper airway remains the first point of contact with sources of exacerbation. Therefore, their interaction with the exacerbation agents may directly contribute to the subsequent responses in the lower airway, in line with the "United Airway" hypothesis. To elucidate the host airway interaction with viruses leading to exacerbations, we thus focus our review on recent findings of viral interaction with the upper airway. We compiled how viral induced changes to the upper airway may contribute to chronic airway inflammatory disease exacerbations, to provide a unified elucidation of the potential exacerbation mechanisms initiated from predominantly upper airway infections.
Despite being a major cause of exacerbation, reports linking respiratory viruses to acute exacerbations only start to emerge in the late 1950s (Pattemore et al., 1992) ; with bacterial infections previously considered as the likely culprit for acute exacerbation (Stevens, 1953; Message and Johnston, 2002) . However, with the advent of PCR technology, more viruses were recovered during acute exacerbations events and reports implicating their role emerged in the late 1980s (Message and Johnston, 2002) . Rhinovirus (RV) and respiratory syncytial virus (RSV) are the predominant viruses linked to the development and exacerbation of chronic airway inflammatory diseases (Jartti and Gern, 2017) . Other viruses such as parainfluenza virus (PIV), influenza virus (IFV) and adenovirus (AdV) have also been implicated in acute exacerbations but to a much lesser extent (Johnston et al., 2005; Oliver et al., 2014; Ko et al., 2019) . More recently, other viruses including bocavirus (BoV), human metapneumovirus (HMPV), certain coronavirus (CoV) strains, a specific enterovirus (EV) strain EV-D68, human cytomegalovirus (hCMV) and herpes simplex virus (HSV) have been reported as contributing to acute exacerbations . The common feature these viruses share is that they can infect both the upper and/or lower airway, further increasing the inflammatory conditions in the diseased airway (Mallia and Johnston, 2006; Britto et al., 2017) .
Respiratory viruses primarily infect and replicate within airway epithelial cells . During the replication process, the cells release antiviral factors and cytokines that alter local airway inflammation and airway niche (Busse et al., 2010) . In a healthy airway, the inflammation normally leads to type 1 inflammatory responses consisting of activation of an antiviral state and infiltration of antiviral effector cells. This eventually results in the resolution of the inflammatory response and clearance of the viral infection (Vareille et al., 2011; Braciale et al., 2012) . However, in a chronically inflamed airway, the responses against the virus may be impaired or aberrant, causing sustained inflammation and erroneous infiltration, resulting in the exacerbation of their symptoms (Mallia and Johnston, 2006; Dougherty and Fahy, 2009; Busse et al., 2010; Britto et al., 2017; Linden et al., 2019) . This is usually further compounded by the increased susceptibility of chronic airway inflammatory disease patients toward viral respiratory infections, thereby increasing the frequency of exacerbation as a whole (Dougherty and Fahy, 2009; Busse et al., 2010; Linden et al., 2019) . Furthermore, due to the different replication cycles and response against the myriad of respiratory viruses, each respiratory virus may also contribute to exacerbations via different mechanisms that may alter their severity. Hence, this review will focus on compiling and collating the current known mechanisms of viral-induced exacerbation of chronic airway inflammatory diseases; as well as linking the different viral infection pathogenesis to elucidate other potential ways the infection can exacerbate the disease. The review will serve to provide further understanding of viral induced exacerbation to identify potential pathways and pathogenesis mechanisms that may be targeted as supplementary care for management and prevention of exacerbation. Such an approach may be clinically significant due to the current scarcity of antiviral drugs for the management of viral-induced exacerbations. This will improve the quality of life of patients with chronic airway inflammatory diseases.
Once the link between viral infection and acute exacerbations of chronic airway inflammatory disease was established, there have been many reports on the mechanisms underlying the exacerbation induced by respiratory viral infection. Upon infecting the host, viruses evoke an inflammatory response as a means of counteracting the infection. Generally, infected airway epithelial cells release type I (IFNα/β) and type III (IFNλ) interferons, cytokines and chemokines such as IL-6, IL-8, IL-12, RANTES, macrophage inflammatory protein 1α (MIP-1α) and monocyte chemotactic protein 1 (MCP-1) (Wark and Gibson, 2006; Matsukura et al., 2013) . These, in turn, enable infiltration of innate immune cells and of professional antigen presenting cells (APCs) that will then in turn release specific mediators to facilitate viral targeting and clearance, including type II interferon (IFNγ), IL-2, IL-4, IL-5, IL-9, and IL-12 (Wark and Gibson, 2006; Singh et al., 2010; Braciale et al., 2012) . These factors heighten local inflammation and the infiltration of granulocytes, T-cells and B-cells (Wark and Gibson, 2006; Braciale et al., 2012) . The increased inflammation, in turn, worsens the symptoms of airway diseases.
Additionally, in patients with asthma and patients with CRS with nasal polyp (CRSwNP), viral infections such as RV and RSV promote a Type 2-biased immune response (Becker, 2006; Jackson et al., 2014; Jurak et al., 2018) . This amplifies the basal type 2 inflammation resulting in a greater release of IL-4, IL-5, IL-13, RANTES and eotaxin and a further increase in eosinophilia, a key pathological driver of asthma and CRSwNP (Wark and Gibson, 2006; Singh et al., 2010; Chung et al., 2015; Dunican and Fahy, 2015) . Increased eosinophilia, in turn, worsens the classical symptoms of disease and may further lead to life-threatening conditions due to breathing difficulties. On the other hand, patients with COPD and patients with CRS without nasal polyp (CRSsNP) are more neutrophilic in nature due to the expression of neutrophil chemoattractants such as CXCL9, CXCL10, and CXCL11 (Cukic et al., 2012; Brightling and Greening, 2019) . The pathology of these airway diseases is characterized by airway remodeling due to the presence of remodeling factors such as matrix metalloproteinases (MMPs) released from infiltrating neutrophils (Linden et al., 2019) . Viral infections in such conditions will then cause increase neutrophilic activation; worsening the symptoms and airway remodeling in the airway thereby exacerbating COPD, CRSsNP and even CRSwNP in certain cases (Wang et al., 2009; Tacon et al., 2010; Linden et al., 2019) .
An epithelial-centric alarmin pathway around IL-25, IL-33 and thymic stromal lymphopoietin (TSLP), and their interaction with group 2 innate lymphoid cells (ILC2) has also recently been identified (Nagarkar et al., 2012; Hong et al., 2018; Allinne et al., 2019) . IL-25, IL-33 and TSLP are type 2 inflammatory cytokines expressed by the epithelial cells upon injury to the epithelial barrier (Gabryelska et al., 2019; Roan et al., 2019) . ILC2s are a group of lymphoid cells lacking both B and T cell receptors but play a crucial role in secreting type 2 cytokines to perpetuate type 2 inflammation when activated (Scanlon and McKenzie, 2012; Li and Hendriks, 2013) . In the event of viral infection, cell death and injury to the epithelial barrier will also induce the expression of IL-25, IL-33 and TSLP, with heighten expression in an inflamed airway (Allakhverdi et al., 2007; Goldsmith et al., 2012; Byers et al., 2013; Shaw et al., 2013; Beale et al., 2014; Jackson et al., 2014; Uller and Persson, 2018; Ravanetti et al., 2019) . These 3 cytokines then work in concert to activate ILC2s to further secrete type 2 cytokines IL-4, IL-5, and IL-13 which further aggravate the type 2 inflammation in the airway causing acute exacerbation (Camelo et al., 2017) . In the case of COPD, increased ILC2 activation, which retain the capability of differentiating to ILC1, may also further augment the neutrophilic response and further aggravate the exacerbation (Silver et al., 2016) . Interestingly, these factors are not released to any great extent and do not activate an ILC2 response during viral infection in healthy individuals (Yan et al., 2016; Tan et al., 2018a) ; despite augmenting a type 2 exacerbation in chronically inflamed airways (Jurak et al., 2018) . These classical mechanisms of viral induced acute exacerbations are summarized in Figure 1 .
As integration of the virology, microbiology and immunology of viral infection becomes more interlinked, additional factors and FIGURE 1 | Current understanding of viral induced exacerbation of chronic airway inflammatory diseases. Upon virus infection in the airway, antiviral state will be activated to clear the invading pathogen from the airway. Immune response and injury factors released from the infected epithelium normally would induce a rapid type 1 immunity that facilitates viral clearance. However, in the inflamed airway, the cytokines and chemokines released instead augmented the inflammation present in the chronically inflamed airway, strengthening the neutrophilic infiltration in COPD airway, and eosinophilic infiltration in the asthmatic airway. The effect is also further compounded by the participation of Th1 and ILC1 cells in the COPD airway; and Th2 and ILC2 cells in the asthmatic airway.
Frontiers in Cell and Developmental Biology | www.frontiersin.org mechanisms have been implicated in acute exacerbations during and after viral infection (Murray et al., 2006) . Murray et al. (2006) has underlined the synergistic effect of viral infection with other sensitizing agents in causing more severe acute exacerbations in the airway. This is especially true when not all exacerbation events occurred during the viral infection but may also occur well after viral clearance (Kim et al., 2008; Stolz et al., 2019) in particular the late onset of a bacterial infection (Singanayagam et al., 2018 (Singanayagam et al., , 2019a . In addition, viruses do not need to directly infect the lower airway to cause an acute exacerbation, as the nasal epithelium remains the primary site of most infections. Moreover, not all viral infections of the airway will lead to acute exacerbations, suggesting a more complex interplay between the virus and upper airway epithelium which synergize with the local airway environment in line with the "united airway" hypothesis (Kurai et al., 2013) . On the other hand, viral infections or their components persist in patients with chronic airway inflammatory disease (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Hence, their presence may further alter the local environment and contribute to current and future exacerbations. Future studies should be performed using metagenomics in addition to PCR analysis to determine the contribution of the microbiome and mycobiome to viral infections. In this review, we highlight recent data regarding viral interactions with the airway epithelium that could also contribute to, or further aggravate, acute exacerbations of chronic airway inflammatory diseases.
Patients with chronic airway inflammatory diseases have impaired or reduced ability of viral clearance (Hammond et al., 2015; McKendry et al., 2016; Akbarshahi et al., 2018; Gill et al., 2018; Wang et al., 2018; Singanayagam et al., 2019b) . Their impairment stems from a type 2-skewed inflammatory response which deprives the airway of important type 1 responsive CD8 cells that are responsible for the complete clearance of virusinfected cells (Becker, 2006; McKendry et al., 2016) . This is especially evident in weak type 1 inflammation-inducing viruses such as RV and RSV (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Additionally, there are also evidence of reduced type I (IFNβ) and III (IFNλ) interferon production due to type 2-skewed inflammation, which contributes to imperfect clearance of the virus resulting in persistence of viral components, or the live virus in the airway epithelium (Contoli et al., 2006; Hwang et al., 2019; Wark, 2019) . Due to the viral components remaining in the airway, antiviral genes such as type I interferons, inflammasome activating factors and cytokines remained activated resulting in prolong airway inflammation (Wood et al., 2011; Essaidi-Laziosi et al., 2018) . These factors enhance granulocyte infiltration thus prolonging the exacerbation symptoms. Such persistent inflammation may also be found within DNA viruses such as AdV, hCMV and HSV, whose infections generally persist longer (Imperiale and Jiang, 2015) , further contributing to chronic activation of inflammation when they infect the airway (Yang et al., 2008; Morimoto et al., 2009; Imperiale and Jiang, 2015; Lan et al., 2016; Tan et al., 2016; Kowalski et al., 2017) . With that note, human papilloma virus (HPV), a DNA virus highly associated with head and neck cancers and respiratory papillomatosis, is also linked with the chronic inflammation that precedes the malignancies (de Visser et al., 2005; Gillison et al., 2012; Bonomi et al., 2014; Fernandes et al., 2015) . Therefore, the role of HPV infection in causing chronic inflammation in the airway and their association to exacerbations of chronic airway inflammatory diseases, which is scarcely explored, should be investigated in the future. Furthermore, viral persistence which lead to continuous expression of antiviral genes may also lead to the development of steroid resistance, which is seen with RV, RSV, and PIV infection (Chi et al., 2011; Ford et al., 2013; Papi et al., 2013) . The use of steroid to suppress the inflammation may also cause the virus to linger longer in the airway due to the lack of antiviral clearance (Kim et al., 2008; Hammond et al., 2015; Hewitt et al., 2016; McKendry et al., 2016; Singanayagam et al., 2019b) . The concomitant development of steroid resistance together with recurring or prolong viral infection thus added considerable burden to the management of acute exacerbation, which should be the future focus of research to resolve the dual complications arising from viral infection.
On the other end of the spectrum, viruses that induce strong type 1 inflammation and cell death such as IFV (Yan et al., 2016; Guibas et al., 2018) and certain CoV (including the recently emerged COVID-19 virus) (Tao et al., 2013; Yue et al., 2018; Zhu et al., 2020) , may not cause prolonged inflammation due to strong induction of antiviral clearance. These infections, however, cause massive damage and cell death to the epithelial barrier, so much so that areas of the epithelium may be completely absent post infection (Yan et al., 2016; Tan et al., 2019) . Factors such as RANTES and CXCL10, which recruit immune cells to induce apoptosis, are strongly induced from IFV infected epithelium (Ampomah et al., 2018; Tan et al., 2019) . Additionally, necroptotic factors such as RIP3 further compounds the cell deaths in IFV infected epithelium . The massive cell death induced may result in worsening of the acute exacerbation due to the release of their cellular content into the airway, further evoking an inflammatory response in the airway (Guibas et al., 2018) . Moreover, the destruction of the epithelial barrier may cause further contact with other pathogens and allergens in the airway which may then prolong exacerbations or results in new exacerbations. Epithelial destruction may also promote further epithelial remodeling during its regeneration as viral infection induces the expression of remodeling genes such as MMPs and growth factors . Infections that cause massive destruction of the epithelium, such as IFV, usually result in severe acute exacerbations with non-classical symptoms of chronic airway inflammatory diseases. Fortunately, annual vaccines are available to prevent IFV infections (Vasileiou et al., 2017; Zheng et al., 2018) ; and it is recommended that patients with chronic airway inflammatory disease receive their annual influenza vaccination as the best means to prevent severe IFV induced exacerbation.
Another mechanism that viral infections may use to drive acute exacerbations is the induction of vasodilation or tight junction opening factors which may increase the rate of infiltration. Infection with a multitude of respiratory viruses causes disruption of tight junctions with the resulting increased rate of viral infiltration. This also increases the chances of allergens coming into contact with airway immune cells. For example, IFV infection was found to induce oncostatin M (OSM) which causes tight junction opening (Pothoven et al., 2015; Tian et al., 2018) . Similarly, RV and RSV infections usually cause tight junction opening which may also increase the infiltration rate of eosinophils and thus worsening of the classical symptoms of chronic airway inflammatory diseases (Sajjan et al., 2008; Kast et al., 2017; Kim et al., 2018) . In addition, the expression of vasodilating factors and fluid homeostatic factors such as angiopoietin-like 4 (ANGPTL4) and bactericidal/permeabilityincreasing fold-containing family member A1 (BPIFA1) are also associated with viral infections and pneumonia development, which may worsen inflammation in the lower airway Akram et al., 2018) . These factors may serve as targets to prevent viral-induced exacerbations during the management of acute exacerbation of chronic airway inflammatory diseases.
Another recent area of interest is the relationship between asthma and COPD exacerbations and their association with the airway microbiome. The development of chronic airway inflammatory diseases is usually linked to specific bacterial species in the microbiome which may thrive in the inflamed airway environment (Diver et al., 2019) . In the event of a viral infection such as RV infection, the effect induced by the virus may destabilize the equilibrium of the microbiome present (Molyneaux et al., 2013; Kloepfer et al., 2014; Kloepfer et al., 2017; Jubinville et al., 2018; van Rijn et al., 2019) . In addition, viral infection may disrupt biofilm colonies in the upper airway (e.g., Streptococcus pneumoniae) microbiome to be release into the lower airway and worsening the inflammation (Marks et al., 2013; Chao et al., 2014) . Moreover, a viral infection may also alter the nutrient profile in the airway through release of previously inaccessible nutrients that will alter bacterial growth (Siegel et al., 2014; Mallia et al., 2018) . Furthermore, the destabilization is further compounded by impaired bacterial immune response, either from direct viral influences, or use of corticosteroids to suppress the exacerbation symptoms (Singanayagam et al., 2018 (Singanayagam et al., , 2019a Wang et al., 2018; Finney et al., 2019) . All these may gradually lead to more far reaching effect when normal flora is replaced with opportunistic pathogens, altering the inflammatory profiles (Teo et al., 2018) . These changes may in turn result in more severe and frequent acute exacerbations due to the interplay between virus and pathogenic bacteria in exacerbating chronic airway inflammatory diseases (Wark et al., 2013; Singanayagam et al., 2018) . To counteract these effects, microbiome-based therapies are in their infancy but have shown efficacy in the treatments of irritable bowel syndrome by restoring the intestinal microbiome (Bakken et al., 2011) . Further research can be done similarly for the airway microbiome to be able to restore the microbiome following disruption by a viral infection.
Viral infections can cause the disruption of mucociliary function, an important component of the epithelial barrier. Ciliary proteins FIGURE 2 | Changes in the upper airway epithelium contributing to viral exacerbation in chronic airway inflammatory diseases. The upper airway epithelium is the primary contact/infection site of most respiratory viruses. Therefore, its infection by respiratory viruses may have far reaching consequences in augmenting and synergizing current and future acute exacerbations. The destruction of epithelial barrier, mucociliary function and cell death of the epithelial cells serves to increase contact between environmental triggers with the lower airway and resident immune cells. The opening of tight junction increasing the leakiness further augments the inflammation and exacerbations. In addition, viral infections are usually accompanied with oxidative stress which will further increase the local inflammation in the airway. The dysregulation of inflammation can be further compounded by modulation of miRNAs and epigenetic modification such as DNA methylation and histone modifications that promote dysregulation in inflammation. Finally, the change in the local airway environment and inflammation promotes growth of pathogenic bacteria that may replace the airway microbiome. Furthermore, the inflammatory environment may also disperse upper airway commensals into the lower airway, further causing inflammation and alteration of the lower airway environment, resulting in prolong exacerbation episodes following viral infection.
Viral specific trait contributing to exacerbation mechanism (with literature evidence) Oxidative stress ROS production (RV, RSV, IFV, HSV)
As RV, RSV, and IFV were the most frequently studied viruses in chronic airway inflammatory diseases, most of the viruses listed are predominantly these viruses. However, the mechanisms stated here may also be applicable to other viruses but may not be listed as they were not implicated in the context of chronic airway inflammatory diseases exacerbation (see text for abbreviations).
that aid in the proper function of the motile cilia in the airways are aberrantly expressed in ciliated airway epithelial cells which are the major target for RV infection (Griggs et al., 2017) . Such form of secondary cilia dyskinesia appears to be present with chronic inflammations in the airway, but the exact mechanisms are still unknown (Peng et al., , 2019 Qiu et al., 2018) . Nevertheless, it was found that in viral infection such as IFV, there can be a change in the metabolism of the cells as well as alteration in the ciliary gene expression, mostly in the form of down-regulation of the genes such as dynein axonemal heavy chain 5 (DNAH5) and multiciliate differentiation And DNA synthesis associated cell cycle protein (MCIDAS) (Tan et al., 2018b . The recently emerged Wuhan CoV was also found to reduce ciliary beating in infected airway epithelial cell model (Zhu et al., 2020) . Furthermore, viral infections such as RSV was shown to directly destroy the cilia of the ciliated cells and almost all respiratory viruses infect the ciliated cells (Jumat et al., 2015; Yan et al., 2016; Tan et al., 2018a) . In addition, mucus overproduction may also disrupt the equilibrium of the mucociliary function following viral infection, resulting in symptoms of acute exacerbation (Zhu et al., 2009) . Hence, the disruption of the ciliary movement during viral infection may cause more foreign material and allergen to enter the airway, aggravating the symptoms of acute exacerbation and making it more difficult to manage. The mechanism of the occurrence of secondary cilia dyskinesia can also therefore be explored as a means to limit the effects of viral induced acute exacerbation.
MicroRNAs (miRNAs) are short non-coding RNAs involved in post-transcriptional modulation of biological processes, and implicated in a number of diseases (Tan et al., 2014) . miRNAs are found to be induced by viral infections and may play a role in the modulation of antiviral responses and inflammation (Gutierrez et al., 2016; Deng et al., 2017; Feng et al., 2018) . In the case of chronic airway inflammatory diseases, circulating miRNA changes were found to be linked to exacerbation of the diseases (Wardzynska et al., 2020) . Therefore, it is likely that such miRNA changes originated from the infected epithelium and responding immune cells, which may serve to further dysregulate airway inflammation leading to exacerbations. Both IFV and RSV infections has been shown to increase miR-21 and augmented inflammation in experimental murine asthma models, which is reversed with a combination treatment of anti-miR-21 and corticosteroids (Kim et al., 2017) . IFV infection is also shown to increase miR-125a and b, and miR-132 in COPD epithelium which inhibits A20 and MAVS; and p300 and IRF3, respectively, resulting in increased susceptibility to viral infections (Hsu et al., 2016 (Hsu et al., , 2017 . Conversely, miR-22 was shown to be suppressed in asthmatic epithelium in IFV infection which lead to aberrant epithelial response, contributing to exacerbations (Moheimani et al., 2018) . Other than these direct evidence of miRNA changes in contributing to exacerbations, an increased number of miRNAs and other non-coding RNAs responsible for immune modulation are found to be altered following viral infections (Globinska et al., 2014; Feng et al., 2018; Hasegawa et al., 2018) . Hence non-coding RNAs also presents as targets to modulate viral induced airway changes as a means of managing exacerbation of chronic airway inflammatory diseases. Other than miRNA modulation, other epigenetic modification such as DNA methylation may also play a role in exacerbation of chronic airway inflammatory diseases. Recent epigenetic studies have indicated the association of epigenetic modification and chronic airway inflammatory diseases, and that the nasal methylome was shown to be a sensitive marker for airway inflammatory changes (Cardenas et al., 2019; Gomez, 2019) . At the same time, it was also shown that viral infections such as RV and RSV alters DNA methylation and histone modifications in the airway epithelium which may alter inflammatory responses, driving chronic airway inflammatory diseases and exacerbations (McErlean et al., 2014; Pech et al., 2018; Caixia et al., 2019) . In addition, Spalluto et al. (2017) also showed that antiviral factors such as IFNγ epigenetically modifies the viral resistance of epithelial cells. Hence, this may indicate that infections such as RV and RSV that weakly induce antiviral responses may result in an altered inflammatory state contributing to further viral persistence and exacerbation of chronic airway inflammatory diseases (Spalluto et al., 2017) .
Finally, viral infection can result in enhanced production of reactive oxygen species (ROS), oxidative stress and mitochondrial dysfunction in the airway epithelium (Kim et al., 2018; Mishra et al., 2018; Wang et al., 2018) . The airway epithelium of patients with chronic airway inflammatory diseases are usually under a state of constant oxidative stress which sustains the inflammation in the airway (Barnes, 2017; van der Vliet et al., 2018) . Viral infections of the respiratory epithelium by viruses such as IFV, RV, RSV and HSV may trigger the further production of ROS as an antiviral mechanism Aizawa et al., 2018; Wang et al., 2018) . Moreover, infiltrating cells in response to the infection such as neutrophils will also trigger respiratory burst as a means of increasing the ROS in the infected region. The increased ROS and oxidative stress in the local environment may serve as a trigger to promote inflammation thereby aggravating the inflammation in the airway (Tiwari et al., 2002) . A summary of potential exacerbation mechanisms and the associated viruses is shown in Figure 2 and Table 1 .
While the mechanisms underlying the development and acute exacerbation of chronic airway inflammatory disease is extensively studied for ways to manage and control the disease, a viral infection does more than just causing an acute exacerbation in these patients. A viral-induced acute exacerbation not only induced and worsens the symptoms of the disease, but also may alter the management of the disease or confer resistance toward treatments that worked before. Hence, appreciation of the mechanisms of viral-induced acute exacerbations is of clinical significance to devise strategies to correct viral induce changes that may worsen chronic airway inflammatory disease symptoms. Further studies in natural exacerbations and in viral-challenge models using RNA-sequencing (RNA-seq) or single cell RNA-seq on a range of time-points may provide important information regarding viral pathogenesis and changes induced within the airway of chronic airway inflammatory disease patients to identify novel targets and pathway for improved management of the disease. Subsequent analysis of functions may use epithelial cell models such as the air-liquid interface, in vitro airway epithelial model that has been adapted to studying viral infection and the changes it induced in the airway (Yan et al., 2016; Boda et al., 2018; Tan et al., 2018a) . Animal-based diseased models have also been developed to identify systemic mechanisms of acute exacerbation (Shin, 2016; Gubernatorova et al., 2019; Tanner and Single, 2019) . Furthermore, the humanized mouse model that possess human immune cells may also serves to unravel the immune profile of a viral infection in healthy and diseased condition (Ito et al., 2019; Li and Di Santo, 2019) . For milder viruses, controlled in vivo human infections can be performed for the best mode of verification of the associations of the virus with the proposed mechanism of viral induced acute exacerbations . With the advent of suitable diseased models, the verification of the mechanisms will then provide the necessary continuation of improving the management of viral induced acute exacerbations.
In conclusion, viral-induced acute exacerbation of chronic airway inflammatory disease is a significant health and economic burden that needs to be addressed urgently. In view of the scarcity of antiviral-based preventative measures available for only a few viruses and vaccines that are only available for IFV infections, more alternative measures should be explored to improve the management of the disease. Alternative measures targeting novel viral-induced acute exacerbation mechanisms, especially in the upper airway, can serve as supplementary treatments of the currently available management strategies to augment their efficacy. New models including primary human bronchial or nasal epithelial cell cultures, organoids or precision cut lung slices from patients with airways disease rather than healthy subjects can be utilized to define exacerbation mechanisms. These mechanisms can then be validated in small clinical trials in patients with asthma or COPD. Having multiple means of treatment may also reduce the problems that arise from resistance development toward a specific treatment. | Where might such miRNA changes have originated from? | false | 4,013 | {
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1,686 | Nucleolar Protein Trafficking in Response to HIV-1 Tat: Rewiring the Nucleolus
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3499507/
SHA: efa871aeaf22cbd0ce30e8bd1cb3d1afff2a98f9
Authors: Jarboui, Mohamed Ali; Bidoia, Carlo; Woods, Elena; Roe, Barbara; Wynne, Kieran; Elia, Giuliano; Hall, William W.; Gautier, Virginie W.
Date: 2012-11-15
DOI: 10.1371/journal.pone.0048702
License: cc-by
Abstract: The trans-activator Tat protein is a viral regulatory protein essential for HIV-1 replication. Tat trafficks to the nucleoplasm and the nucleolus. The nucleolus, a highly dynamic and structured membrane-less sub-nuclear compartment, is the site of rRNA and ribosome biogenesis and is involved in numerous cellular functions including transcriptional regulation, cell cycle control and viral infection. Importantly, transient nucleolar trafficking of both Tat and HIV-1 viral transcripts are critical in HIV-1 replication, however, the role(s) of the nucleolus in HIV-1 replication remains unclear. To better understand how the interaction of Tat with the nucleolar machinery contributes to HIV-1 pathogenesis, we investigated the quantitative changes in the composition of the nucleolar proteome of Jurkat T-cells stably expressing HIV-1 Tat fused to a TAP tag. Using an organellar proteomic approach based on mass spectrometry, coupled with Stable Isotope Labelling in Cell culture (SILAC), we quantified 520 proteins, including 49 proteins showing significant changes in abundance in Jurkat T-cell nucleolus upon Tat expression. Numerous proteins exhibiting a fold change were well characterised Tat interactors and/or known to be critical for HIV-1 replication. This suggests that the spatial control and subcellular compartimentaliation of these cellular cofactors by Tat provide an additional layer of control for regulating cellular machinery involved in HIV-1 pathogenesis. Pathway analysis and network reconstruction revealed that Tat expression specifically resulted in the nucleolar enrichment of proteins collectively participating in ribosomal biogenesis, protein homeostasis, metabolic pathways including glycolytic, pentose phosphate, nucleotides and amino acids biosynthetic pathways, stress response, T-cell signaling pathways and genome integrity. We present here the first differential profiling of the nucleolar proteome of T-cells expressing HIV-1 Tat. We discuss how these proteins collectively participate in interconnected networks converging to adapt the nucleolus dynamic activities, which favor host biosynthetic activities and may contribute to create a cellular environment supporting robust HIV-1 production.
Text: The nucleolus is a highly ordered subnuclear compartment organised around genetic loci called nucleolar-organising regions (NORs) formed by clusters of hundreds of rDNA gene repeats organised in tandem head-to-tail repeat [1, 2] . A membrane-less organelle originally described as the ''Ribosome Factory'', the nucleolus is dedicated to RNA-polymerase-I-directed rDNA transcription, rRNA processing mediated by small nucleolar ribonucleoproteins (soRNPs) and ribosome assembly. Ribosome biogenesis is essential for protein synthesis and cell viability [2] and ultimately results in the separate large (60S) and small (40S) ribosomal subunits, which are subsequently exported to the cytoplasm. This fundamental cellular process, to which the cell dedicates most of its energy resources, is tightly regulated to match dynamic changes in cell proliferation, growth rate and metabolic activities [3] .
The nucleolus is the site of additional RNA processing, including mRNA export and degradation, the maturation of uridine-rich small nuclear RNPs (U snRNPs), which form the core of the spliceosome, biogenesis of t-RNA and microRNAs (miRNAs) [4] . The nucleolus is also involved in other cellular processes including cell cycle control, oncogenic processes, cellular stress responses and translation [4] .
The concept of a multifunctional and highly dynamic nucleolus has been substantiated by several studies combining organellar proteomic approaches and quantitative mass spectrometry, and describing thousands of proteins transiting through the nucleolus in response to various metabolic conditions, stress and cellular environments [5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16] . Collectively, the aforementioned studies represent landmarks in understanding the functional complexity of the nucleolus, and demonstrated that nucleolar proteins are in continuous exchange with other nuclear and cellular compartments in response to specific cellular conditions.
Of importance, the nucleolus is also the target of viruses including HIV-1, hCMV, HSV and KSHV, as part of their replication strategy [2, 17] . Proteomics studies analysing the nucleoli of cells infected with Human respiratory syncytial virus (HRSV), influenza A virus, avian coronavirus infectious bronchitis virus (IBV) or adenovirus highlighted how viruses can distinctively disrupt the distribution of nucleolar proteins [2, 17, 18, 19, 20, 21, 22, 23, 24] . Interestingly, both HIV-1 regulatory proteins Tat and Rev localise to the nucleoplasm and nucleolus. Both their sequences encompass a nucleolar localisation signal (NoLS) overlapping with their nuclear localisation signal (NLS), which governs their nucleolar localisation [25, 26, 27, 28, 29, 30, 31] . Furthermore, Tat and Rev interact with the nucleolar antigen B23, which is essential for their nucleolar localisation [25, 26, 27, 28, 29, 30] . Nevertheless, a recent study described that in contrast to Jurkat T-cells and other transformed cell lines where Tat is associated with the nucleus and nucleolus, in primary T-cells Tat primarily accumulates at the plasma membrane, while trafficking via the nucleus where it functions [32] . While the regulation of their active nuclear import and/or export, as mediated by the karyopherin/importin family have been well described, the mechanisms distributing Tat and Rev between the cytoplasm, nucleoplasm and the nucleolus remains elusive [33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48] . Importantly, two major studies by Machienzi et al. have revealed important functional links between HIV-1 replication and the nucleolus [49, 50] . First, they could inhibit HIV-1 replication and Tat transactivation function employing a TAR decoy specifically directed to the nucleolus. Furthermore, using a similar approach, with an anti-HIV-1 hammerhead ribozyme fused to the U16 small nucleolar RNA and therefore targeted to the nucleolus, they could dramatically suppress HIV-1 replication. Collectively, these findings strongly suggest that HIV-1 transcripts and Tat nucleolar trafficking are critical for HIV-1 replication. However the nature of these contributions remains to be elucidated.
In this report, we systematically analysed the nucleolar proteome perturbations occurring in Jurkat T-cells constitutively expressing HIV-1 Tat, using a quantitative mass spectrometry approach. Following the detailed annotation of the quantitative abundance changes in the nucleolar protein composition upon Tat expression, we focussed on the Tat-affected cellular complexes and signalling pathways associated with ribosome biogenesis, spliceosome, molecular chaperones, DNA replication and repair and metabolism and discuss their potential involvement in HIV-1 pathogenesis.
In this study, we investigated the quantitative changes in the nucleolar proteome of Jurkat T cells constitutively expressing HIV-1 Tat (86aa) versus their Tat-negative counterpart, using stable isotope labelling with amino acids in cell culture (SILAC) technology, followed by ESI tandem mass spectrometry and implemented the experimental approach described in Figure 1A . First, using retroviral gene delivery, we transduced HIV-1 Tat fused to a tandem affinity purification (TAP) tag (consisting of two protein G and a streptavidin binding peptide) or TAP tag alone (control vector) in Jurkat leukemia T cell clone E6-1 and sorted the transduced cells (GFP positive) by FACS. This resulted in a highly enriched population of polyclonal transduced cells presenting different expression levels of the transgene ( Figure 1B) . The functionality of TAP-Tat was confirmed by transfecting Jurkat TAP-Tat and TAP cells with a luciferase reporter gene vector under the control of the HIV-1 LTR (pGL3-LTR) [36] . TAP-Tat up regulated gene expression from the HIV-1 LTR by up to 28 fold compared to control ( Figure 1C ). To further address the functionality of Tat fused to TAP, we compared Jurkat TAP-Tat with Jurkat-tat, a cell line stably expressing untagged Tat [51] . Both cell line exhibited comparable HIV-1 LTR activity following transfection with pGL3-LTR ( Figure S1 ). Next, Tat expression and subcellular localization was verified by subcellular fractionation followed by WB analysis ( Figure 1E ). TAP-Tat displayed a prominent nuclear/nucleolar localization but could also be detected in the cytoplasm. These observations were further validated by immunofluorescence microscopy ( Figure 1E ). Of note, Jurkat-tat presented similar patterns for Tat subcellular distribution as shown by immunofluorescence microscopy and subcellular fractionation followed by WB analysis (Figure S2 and S3). We next compared the growth rate and proliferation of the Jurkat TAP and TAP-Tat cell lines (Materials and Methods S1), which were equivalent ( Figure S4A ). Similarly, FACS analysis confirmed that the relative populations in G1, S, and G2/M were similar for Jurkat TAP-Tat and TAP cells ( Figure S4B ).
We labeled Jurkat TAP-Tat and Jurkat TAP cells with light (R0K0) and heavy (R6K6) isotope containing arginine and lysine, respectively. Following five passages in their respective SILAC medium, 85 million cells from each culture were harvested, pooled and their nucleoli were isolated as previously described ( Figure 1A ) [52] . Each step of the procedure was closely monitored by microscopic examination. To assess the quality of our fractionation procedure, specific enrichment of known nucleolar antigens was investigated by Western Blot analysis ( Figure 1D ). Nucleolin (110 kDa) and Fibrillarin (FBL) (34 kDa), two major nucleolar proteins known to localise to the granular component of the nucleolus, were found to be highly enriched in the mixed nucleolar fraction. Of note, nucleolin was equally distributed between the nuclear and cytoplasmic fractions. This distribution pattern for nucleolin appears to be specific for Jurkat T-cells as show previously [52, 53] . The nuclear protein PARP-1 (Poly ADPribose polymerase 1) (113 kDa) was present in the nuclear and nucleoplasmic fraction but was depleted in the nucleolar fraction. Alpha-tubulin (50 kDa) was highly abundant in the cytoplasmic fraction and weakly detected in the nuclear fractions. Collectively, these results confirmed that our methods produced a highly enriched nucleolar fraction without significant cross contamination.
Subsequently, the nucleolar protein mixture was trypsindigested and the resulting peptides were analysed by mass spectrometry. Comparative quantitative proteomic analysis was performed using MaxQuant to analyse the ratios in isotopes for each peptide identified. A total of 2427 peptides were quantified, representing 520 quantified nucleolar proteins. The fully annotated list of the quantified nucleolar proteins is available in Table S1 and the raw data from the mass spectrometry analysis was deposited in the Tranche repository database (https:// proteomecommons.org/tranche/), which can be accessed using the hash keys described in materials and methods. We annotated the quantified proteins using the ToppGene Suite tools [54] and extracted Gene Ontology (GO) and InterPro annotations [55] . The analysis of GO biological processes ( Figure 1F ) revealed that the best-represented biological processes included transcription (24%), RNA processing (23%), cell cycle process (13%) and chromosome organisation (15%), which reflects nucleolar associated functions and is comparable to our previous characterisation of Jurkat T-cell nucleolar proteome [52] . Subcellular distribution analysis ( Figure 1F ) revealed that our dataset contained proteins known to localise in the nucleolus (49%), in the nucleus (24%) while 15% of proteins were previously described to reside exclusively in the cytoplasm. The subcellular distribution was similar to our previous analysis of the Jurkat T-cell nucleolar proteome [52] . Table S1 . The distribution of protein ratios are represented in Figure 1G as log 2 (abundance change). The SILAC ratios indicate changes in protein abundance in the nucleolar fraction of Jurkat TAP-Tat cells in comparison with Jurkat TAP cells. The distribution of the quantified proteins followed a Gaussian distribution ( Figure 1G ). A total of 49 nucleolar proteins exhibited a 1.5 fold or greater significant change (p,0.05) upon Tat expression (Table 1) . Of these, 30 proteins were enriched, whereas 19 proteins were depleted. Cells displayed no changes in the steady state content of some of the major and abundant constituents of the nucleolus, including nucleophosmin (NPM1/ B23), C23, FBL, nucleolar protein P120 (NOL1), and nucleolar protein 5A (NOL5A). The distinct ratios of protein changes upon Tat expression could reflect specific nucleolar reorganization and altered activities of the nucleolus.
We performed WB analysis to validate the SILAC-based results obtained by our quantitative proteomic approach ( Figure 2 ). 15 selected proteins displayed differential intensity in the nucleolar fractions upon Tat expression, including 9 enriched (HSP90b, STAT3, pRb, CK2a, CK2a', HSP90a, Transportin, ZAP70, DDX3), and 3 depleted (ILF3, BOP1, and SSRP1) proteins. In addition, we also tested by WB analysis, protein abundance not affected by Tat expression (Importin beta, FBL, B23, C23). These results highlight the concordance in the trend of the corresponding SILAC ratios, despite some differences in the quantitative ranges. Of note, using WB, we could observe a change of intensity for protein with a SILAC fold change as low as 1.25-fold.
Of note, the question remains as to which fold change magnitude might constitute a biologically relevant consequence. On the one hand, the threshold of protein abundance changes can be determined statistically and would then highlight the larger abundance changes as illustrated in Table 1 . Alternatively, the coordinated enrichment or depletion of a majority of proteins belonging to a distinct cellular complex or pathway would allow the definition of a group of proteins of interest and potential significance. Therefore, we next focused on both enriched or depleted individual proteins with activities associated with HIV-1 or Tat molecular pathogenesis, and on clustered modifications affecting entire cellular signaling pathways and macromolecular complexes.
We initially focused on signaling proteins interacting with Tat and/or associated HIV-1 molecular pathogenesis and whose abundance in the nucleolus was modulated by Tat expression.
Phospho-protein phosphatases. Phospho-protein phosphatase PP1 and PP2A are essential serine/threonine phosphatases [56, 57] . Importantly, PP1 accounts for 80% of the Ser/Thr phosphatase activity within the nucleolus. In our study, PP1 was found to be potentially enriched by 1.52-fold in the nucleolus of Jurkat cells expressing Tat, which supports previous studies describing the nuclear and nucleolar targeting of PP1a by HIV-1 Tat and how PP1 upregulates HIV-1 transcription [58, 59, 60, 61, 62] . PP1 c was also identified as part of the in vitro nuclear interactome [63] . Similarly, PPP2CA, the PP2A catalytic subunit (1.29-fold) and its regulatory subunit PP2R1A (1.27-fold) were similarly enriched upon Tat expression. Interestingly, Tat association with the PP2A subunit promoters results in the overexpression and up regulation of PP2A activity in lymphocytes [64, 65] . Furthermore, PP2A contributes to the regulation of HIV-1 transcription and replication [61, 66] .
Retinoblastoma Protein. The tumour suppressor gene pRb protein displayed a 1.4-fold change in the nucleolus upon Tat expression [67] . Furthermore, WB analysis confirmed the distinct translocation of pRb from the nucleoplasm to the nucleolus by Tat ( Figure 2 ). Depending on the cell type, pRb can be hyperphosphorylated or hypophosphorylated upon Tat expression and can negatively or positively regulate Tat-mediated transcription respectively [68, 69, 70] . Interestingly, the hyperphosphorylation of pRB triggers in its translocation into the nucleolus [71] . Phosphorylation of pRB is also associated with an increase in ribosomal biogenesis and cell growth [72] .
STAT3. The transcription factor signal transducer and activator of transcription 3 (STAT3) was significantly enriched (1.86-fold) in the nucleolar fraction by Tat constitutive expression. Furthermore, WB analysis indicated that Tat expression could promote the relocalisation of STAT3 from the cytoplasm to the nucleus, with a distinct enrichment in the nucleolus ( Figure 2) . Interestingly, previous studies have demonstrated Tat-mediated activation of STAT3 signaling, as shown by its phosphorylation status [73] . Interestingly, STAT3 phosphorylation induced dimerisation of the protein followed its translocation to the nucleus [74] .
YBX1. YBX1, the DNA/RNA binding multifunctional protein was enriched by 1.38-fold in the nucleolus of Jurkat cells upon Tat expression. Interestingly, YBX1 interacts with Tat and TAR and modulates HIV-1 gene expression [63, 75] .
ZAP70. The protein tyrosine kinase ZAP70 (Zeta-chainassociated protein kinase 70) was enriched by 1.24-fold in the nucleolus of Jurkat cells expressing Tat [76] . Furthermore, WB analysis revealed that Tat expression could promote the relocalisation of ZAP70 from the cytoplasm to the nucleus, with a distinct enrichment in the nucleolus ( Figure 2 ). Of note, ZAP70 is part of the in vitro nuclear Tat interactome [63] .
Matrin 3. The inner nuclear matrix protein, Matrin 3 (MATR3), presented a 1.39-fold change in the nucleolus of Jurkat cells expressing Tat. It localizes in the nucleolasm with a diffuse pattern excluded from the nucleoli [77] . Matrin 3 has been identified as part of the in vitro HIV-1 Tat nuclear interactome [63] . Two recent studies have described Matrin 3 as part of ribonucleoprotein complexes also including HIV-1 Rev and (Rev Response Element) RRE-containing HIV-1 RNA, and promoting HIV-1 post-transcriptional regulation [78, 79, 80] .
CASP10. The pro-apototic signaling molecule, Caspase 10 (CASP10), was significantly depleted from the nucleolus of Jurkat-Tat cells (0.82-fold) [81] . Importantly, Tat expression downregulates CASP10 expression and activity in Jurkat cells [82] .
ADAR1. Adenosine deaminase acting on RNA (ADAR1), which converts adenosines to inosines in double-stranded RNA, was significantly depleted from the nucleolus of Jurkat-Tat cells (0.78-fold). Interestingly, ADAR1 over-expression up-regulates HIV-1 replication via an RNA editing mechanism [83, 84, 85, 86, 87, 88] . Furthermore, ADAR1 belongs to the in vitro HIV-1 Tat nuclear interactome [63] .
To underline the structural and functional relationships of the nucleolar proteins affected by HIV-1 Tat, we constructed a network representation of our dataset. We employed Cytoscape version 2.6.3 [89] and using the MiMI plugin [90] to map previously characterised interactions, extracted from protein interaction databases (BIND, DIP, HPRD, CCSB, Reactome, IntAct and MINT). This resulted in a highly dense and connected network comprising 416 proteins (nodes) out of the 536 proteins, linked by 5060 undirected interactions (edges) ( Figure 3A ). Centrality analysis revealed a threshold of 23.7 interactions per protein. Topology analysis using the CentiScaPe plugin [91] showed that the node degree distribution follows a power law ( Figure S5 ), characteristic of a scale-free network. Importantly, when we analysed the clustering coefficient distribution ( Figure S6 ) we found that the network is organised in a hierarchical architecture [92] , where connected nodes are part of highly clustered areas maintained by few hubs organised around HIV-1 Tat. Furthermore, node degree connection analysis of our network identified HIV-1 Tat as the most connected protein ( Figure S6 ). Specifically, the topology analysis indicated that the values for Tat centralities were the highest (Node degree, stress, radiality, closeness, betweeness and centroid), characterising Tat as the main hub protein of the nucleolar network. Indeed, a total of 146 proteins have been previously described to interact with Tat ( Figure 3B , Table S2 ). These proteins are involved in a wide range of cellular processes including chromosomal organization, DNA and RNA processing and cell cycle control. Importantly, aver the third of these proteins exhibit an increase in fold ratio change (59 proteins with a ratio .1.2 fold).
In parallel, we characterised the magnitude of the related protein abundance changes observed in distinct cellular pathways ( Figure 4) .
Ribosomal biogenesis. We initially focused on ribosome biogenesis, the primary function of the nucleolus. We could observe a general and coordinated increase in the abundance of ribosomal proteins in the nucleolus by Tat expression (Figure 4 ). While some ribosomal proteins remained unaffected, Tat caused the nucleolar accumulation of several distinct large and small ribosomal proteins, except RPL35A, for which Tat expression caused a marked decrease at the nucleolar level (0.29-fold). Similarly, several proteins involved in rRNA processing exhibited an overall increase in nucleolar accumulation upon Tat expression. These include human canonical members of the L7ae family together with members participating in Box C/D, H/ACA and U3 snoRNPs ( Figure 4) . Conversely, BOP1, a component of the PeBoW (Pescadillo Bop1 WDR12) complex essential for maturation of the large ribosomal subunit, was significantly depleted from the nucleolus of Jurkat TAP-Tat cells (0.81-fold) and this was confirmed by WB analysis (Figure 2 ) [93] . Nevertheless, the other PeBoW complex components, Pes1 (0.94-fold) and WDR12 (1.1fold), were not affected by Tat expression. Of note, we did not detect change in the abundance of protein participating in rDNA transcription such as RNAPOLI, UBF.
Spliceosome. We identified and quantified in our dataset 55 proteins out of the 108 known spliceosomal proteins [94] . These proteins include the small nuclear ribonucleoproteins U1, U2 and U5, Sm D1, D2, D3, F and B, and the heterogeneous nuclear ribonucleoproteins. Our data suggested a distinct increase in the abundance of specific spliceosome complex proteins upon expression of HIV-1 Tat in Jurkat T-cells (Figure 3 and 4) . The only three proteins that were significantly depleted from the nucleolus upon expression of HIV-1 Tat were RBMX (0.89-fold), HNRNPA2B1 (0.84-fold) and SNRPA (0.81-fold). Several investigations showed expression alteration in cellular splicing factors in HIV-1 infected cells [95, 96] .
Molecular chaperones. We have identified several molecular chaperones, co-chaperones and other factors involved into proteostasis to be highly enriched in the nucleolus of T-cells upon Tat expression (Figure 3 and 4) , many of which were previously characterised as part of the Tat nuclear interactome [63] . Several heat-shock proteins including DNAJs, specific HSP90, HSP70 and HSP40 isoforms and their co-factors were distinctively enriched in the nucleolar fraction of Jurkat cells expressing Tat ( Figure 4 ). As shown by WB, while HSP90a and b are mostly cytoplasmic, Tat expression triggers their relocalisation to the nucleus and nucleolus, corroborating our proteomic quantitative approach (Figure 2) . Similarly, heat-shock can cause the HSP90 and HSP70 to relocalise to the nucleolus [97, 98, 99, 100, 101] . In a recent study, Fassati's group has shown that HSP90 is present at the HIV-1 promoter and may directly regulate viral gene expression [102] . We also observed the coordinated increased abundance of class I (GroEL and GroES) and class II (chaperonin containing TCP-1 (CTT)) chaperonin molecules (Figure 3 and 4) upon Tat expression.
Ubiquitin-proteasome pathway. The ubiquitin-proteasome pathway is the major proteolytic system of eukaryotic cells [103] . Importantly, the nuclear ubiquitin-proteasome pathway controls the supply of ribosomal proteins and is important to ribosome biogenesis [104, 105] . The 26S proteasome is composed of the 20S core particle (CP) and the 19S regulatory particle (RP). Alternatively, CP can associate with the 11S RP to form the immunoproteasome. All the quantified proteins in our study are part of the 19S regulatory complex and include PSMD2 (1.5-fold), PSMD3 (1.32-fold), PSMD11 (1.25-fold) and PSMD13 (0.72-fold), the only proteasome component significantly depleted from the nucleolus in the presence of Tat (Figure 4) . Interestingly, Tat interacts with distinct subunits of the proteasome system, including the 19S, 20S and 11S subunits. The consequences of these interactions include the competition of Tat with 11S RP or 19S RP for binding to the 20S CP, which resulted in the inhibition of the 20S peptidase activity [106, 107, 108, 109, 110, 111] . Furthermore, Tat was shown to modify the proteasome composition and activity, which affects the generation of peptide antigens recognized by cytotoxic T-lymphocytes [112] . Importantly, a recent study demonstrated that in the absence of Tat, proteasome components are associated to the HIV-1 promoter and proteasome activity limits transcription [113] . Addition of Tat promoted the dissociation of the 19S subunit from the 20S proteasome, followed by the distinct enrichment of the 19S-like complex in nuclear extracts together with the Tat-mediated recruitment of the 19S subunits to the HIV-1 promoter, which facilitated its transcriptional elongation [113] . We also quantified UBA1 (1.36-fold), the E3 ubiquitin-protein ligase UHRF1 (1.13-fold), UBC (1-fold) and two Ubiquitinspecific-peptidases, USP30 (1.28-fold) and USP20 (0.06-fold) (Figure 4) .
DNA replication and repair. Upon HIV-1 Tat expression, we observed the coordinated nucleolar enrichment of several cellular factors associated with DNA replication and repairs pathways (Figure 4) .
Tat induced the coordinated enrichment of the miniature chromosome maintenance MCM2-7 complex (from 1.23-to 3.30fold, respectively) [114] . MCM7, 6 and 3 were identified as part of the in vitro nuclear interactome of HIV-1 Tat [63] . The structural maintenance of chromosomes 2, SMC2, was enriched (1.35-fold) in the nucleolar fraction by Tat expression. SMC2 was identified as part of the in vitro nuclear interactome of HIV-1 Tat [63] . While replication factor C1 (RFC1) and RFC2 (1.31-and 1.28-fold respectively) displayed an increased fold change and RFC5/3 were not affected, RFC4 was severely depleted (0.69-fold) from the nucleolar fraction upon Tat expression [115] . RFC1 and RFC2 were identified as part of the in vitro nuclear interactome of HIV-1 Tat [63] . Tat induced the enrichment of XRCC6 (1.27-fold) and XRCC5 (1.36-fold) in the nucleolus, which are involved in the repair of non-homologous DNA end joining (NHEJ) [116] . XRCC6 associates with viral preintegration complexes containing HIV-1 Integrase and also interact with Tat and TAR [117, 118, 119] . Furthermore, in a ribozyme-based screen, XRCC5 (Ku80) knockdown decreased both retroviral integration and Tatmediated transcription [120] . As part of the base excision repair (BER), we have identified a major apurinic/apyrimidinic endonuclease 1 (APEX1) (1.29-fold) . Importantly, in a siRNA screen targeting DNA repair factors, APEX1 knockdown was found to inhibit HIV-1 infection by more 60% [121] . The high mobility group (HMG) protein, HMGA1 (1.30-fold), was enriched in the nucleolus following Tat expression [122] . HMGA1 interact with HIV-1 Integrase and is part of the HIV-1 pre-integration complex [123, 124] . Importantly, HMGA1 has been identified in a proteomic screen, as a cellular cofactor interacting with the HIV-1 59leader [125] .
Metabolism. Our proteomic data suggest that Tat induces perturbations in glycolysis, the pentose phosphate pathway, and nucleotide and amino acid biosynthesis (Figure 4 and Figure S7 ). Notably, in T cells expressing Tat, we detected co-ordinated changes in the abundance of proteins not previously known to be associated with Tat pathogenesis, which revealed unexpected connections with with glycolysis and the pentose phosphate pathway, including the following glycolitic enzymes, lactate dehydrogenase B (LDHB) (1.37-fold), glyceraldehyde 3-phosphate dehydrogenase (GAPDH) (1.17-fold) and phosphoglyceric acid mutase (PGAM1) (0.89-fold) ( Figure 4 and Figure S7 ). Briefly, GPI catalyzes the reversible isomerization of glucose-6-phosphate in fructose-6-phosphate. Subsequently, PFKP catalyzes the irreversible conversion of fructose-6-phosphate to fructose-1,6-bisphosphate and is a key regulatory enzyme in glycolysis. At the end of the glycolytic pathway, PKM2, in its tetrameric form, is known to generate ATP and pyruvate, while LDHB diverts the majority of the pyruvate to lactate production and regeneration of NAD+ in support to continued glycolysis, a phenomenon described for proliferative Tcells [126] . Of note, in highly proliferating cells, PKM2 can be found in its dimeric form and its activity is altered. This upregulates the availibility of glucose intermediates, which are rerouted to the pentose phosphate and serine biosynthesis pathways for the production of biosynthetic precursors of nucleotides, phospholipids and amino acids. As part of the pentose phosphate pathway, we have characterised the significant enrichment of glucose-6-phosphate dehydrogenase (G6PD) (2.11-fold), which branches of the glycolysis pathway to generate NADPH, ribose-5phosphate an important precursor for the synthesis of nucleotides. Consistent with this, we detected the coordinated increase in the abundance of enzymes which plays a central role in the synthesis of purines and pyrimidines. More specifically, IMPDH2 (1.66fold), a rate-limiting enzyme at the branch point of purine nucleotide biosynthesis, leading to the generation of guanine nucleotides, phosphoribosyl pyrophosphate synthetase 2 (PRPS2) (1.41-fold), cytidine-5-prime-triphosphate synthetase (CTPS) (1.74-fold) which catalyses the conversion of UTP to CTP and the ribonucleotide reductase large subunit (RRM1) (1.56-fold). In parralel, we noted the increased abundance of the phosphoserine aminotransferase PSAT1 (1.90-fold), an enzyme implicated in serine biosynthesis, which has been linked with cell proliferation in vitro.
The host-virus interface is a fundamental aspect in defining the molecular pathogenesis of HIV-1 [127, 128, 129, 130, 131, 132, 133] . Indeed, with its limited repertoire of viral proteins, HIV-1 relies extensively on the host cell machinery for its replication. Several recent studies have capitalized on the recent advances in the ''OMICS'' technologies, and have revealed important insights into this finely tuned molecular dialogue [132, 134] . HIV-1 Tat is essential for viral replication and orchestrates HIV-1 gene expression. The viral regulatory protein is known to interact with an extensive array of cellular proteins and to modulate cellular gene expression and signaling pathway [135, 136] . We and others have employed system-level approaches to investigate Tat interplay with the host cell machinery, which have characterised HIV-1 Tat as a critical mediator of the host-viral interface [137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149] . Here, we have investigated the nucleolar proteins trafficking in response to HIV-1 Tat expression in T-cells, with the view to provide unique and novel insights on the role of proteins compartimentalisation by Tat in the fine-tuning of protein availability and function.
We have developed for this study, a cellular model using Jurkat T-cells stably expressing Tat fused in its N-ternminal to TAP-tag.
Jurkat T-cells are robust and present the advantage to grow without stimulations and are easely transduced using retroviral gene delivery. Importantly, they have been widely employed to evaluate Tat-mediated pathogenesis using system-wide approaches and to analyse T-cell key cellular signaling pathways and functions [144, 150, 151, 152] . Indeed, we have found them particularly suited for prolongued in vitro culture in SILAC medium and subsequent isolation of their nucleolus followed by MS analysis, which requires up to 85 millions of cells. We fused Tat to the TAP tag to enable future downstream applications such as Tandem affinity purification or Chromatin IP analysis. Importantly, we have confirm that N-terminal TAP-tag did not interfere with Tat function nor its localisation in Jurkat cells, when compared to untagged-Tat. Of note, Tat subcellular distribution can vary according to the cell type employed. While Tat is known to accumulate in the nucleus and nucleolus in Jurkat cells and other transformed cell lines, in primary T-cells, Tat was described to primarily accumulate at the plasma membrane, while trafficking via the nucleus where it functions [32] . These differences remain to be characterised but could be related to different expression levels of transport factors in transformed cell lines versus primary cells, as recently described by Kuusisto et al. [39] . Furthermore, Stauber and Pavlakis have suggested that Tat nucleolar localisation could be the results of Tat overexpression [31] . Here, we have selected and employed a polyclonal population of Jurkat T-cells expressing Tat at different levels. We propose that this heterogeneity in Tat expression levels might reflect Tat stochastic expression described during viral replication [153] .
Using a quantitative proteomic strategy based on an organellar approach, we quantified over 520 nucleolar proteins, including 49 proteins exhibiting a significant fold change. The extent to which the induced variations in the abundance of nucleolar proteins are biologically relevant and can affect cellular and/or viral processes remains to be determined. Nevertheless, the biological nature of the pathways and macromolecular complexes affected enable us to discuss their potential associations with HIV-1 pathogenesis.
HIV-1 Tat is expressed early following HIV-1 genome integration and mediates the shift to the viral production phase, associated with robust proviral gene expression, viral proteins assembly and ultimately, virions budding and release. In this context and based on our results, we propose that Tat could participate in shaping the intracellular environment and metabolic profile of T cells to favor host biosynthetic activities supporting robust virions production. Indeed, we observed the distinct nucleolar enrichment of ribosomal proteins and enzymes associated with ribosomal biogenesis, which could be indicative of an increase in protein synthesis. With the notable exeption of RPL35A nucleolar depletion, ribosomal proteins and enzymes associated with ribosomal biogenesis were in the top 20 most enriched nucleolar proteins (NHP2L1, RLP14, RPL17, RPL27, RPS2, RPL13). Furthermore, this effect appears to be specific to HIV-1 Tat since transcription inhibition by Actinomycin D resulted in the overall depletion of ribosomal proteins in the nucleolus [9] . Moreover, quantitative proteomics analysis of the nucleous in adenovirus-infected cells showed a mild decrease in ribosomal proteins [24] . Whether this reflect a shift in ribosome biogenesis and/or a change in the composition of the ribosomal subunits remains to be determined. Nevertheless, the adapted need for elevated ribosome production is intuitive for a system that needs to support the increased demand for new viral proteins synthesis. In parralel, we observed the concordant modulation of pathways regulating protein homeostasis. We noted the significant nucleolar accumulation of multiple molecular chaperones including the HSPs, the TCP-1 complex, and CANX/CALR molecules and the disrupted nucleolar abundance of proteins belonging to the ubiquitin-proteasome pathway, which controls the supply of ribosomal proteins [104, 105] . These observations further support previous studies describibing the modulation of the proteasomal activity by Tat, which affect the expression, assembly, and localization of specific subunits of the proteasomal complexes [106, 107, 108, 109, 110, 111, 113] . We also observed the concomitant depletion of CASP10 in the nucleolus of Jurkat TAP-Tat. It has been suggested that CASP10 could be targeted to the nucleolus to inhibit protein synthesis [154] . Interestingly, the presence and potential roles of molecular chaperones in the nucleolus have been highlighted by Banski et al, who elaborate on how the chaperone network could regulate ribosome biogenesis, cell signaling, and stress response [97, 155] . As viral production progresses into the late phase and cellular stress increases, nucleolar enrichment of molecular chaperones by Tat could not only enable adequat folding of newly synthetised viral proteins but could also promote tolerance of infected cells to stress and maintain cell viability.
Coincidentally, we observed the marked nucleolar enrichment of enzymes belonging to metabolic pathways including glycolysis, pentose phosphate, nucleotide and amino acid biosynthetic pathways. Similarly, these pathways are elevated in proliferative T-cells or in cancer cells following a metabolic shift to aerobic glycolysis, also known as the Warburg effect [156, 157, 158, 159] . There, glucose intermediates from the glycolysis pathway are not only commited to energy production and broke-down into pyruvate for the TCA cycle, but are redirected to alternative pathways, including the pentose phosphate pathway, and used as metabolic precursors to produce nucleotides, amino acids, acetyl CoA and NADPH for redox homeostasis. Consistently, we also noted the concomittant nucleolar enrichment of enzymes belonging to the nucleotide synthesis pathway, including IMPH2, a rate limiting enzyme known to control the pool of GTP. Similarly, we noted the nucleolar enrichment of PSAT1, an enzyme involved in serine and threonin metabolism, which is associated with cellular proliferation [160] . Collectively, we propose that by controlling protein homeostasis and metabolic pathways, Tat could meet both the energetic and biosynthetic demand of HIV-1 productive infection.
Of note, while nucleotide metabolism enzymes are associated with the nucleus, glycolysis takes place in the cytoplasm. Nevertheless, glycolytic enzymes have been detected in both the nuclear and nucleolar fractions by proteomic analyses [8, 161] . Furthermore glycolytic enzymes, such as PKM2, LDH, phosphoglycerate kinase, GAPDH, and aldolase, also have been reported to display nuclear localization and bind to DNA [162] . More specifically, PKM2 is known to associate with promoter and participate in the regulation of gene expression as a transcriptional coactivator [163] .
HIV-1 Tat has previously been described as an immunoregulator and more specifically, has been reported both to inhibit or to promote TCR signaling [164] . We have observed the nucleolar enrichment by Tat of key proximal or downstream components of T-cell signaling pathways, including ZAP70, ILF3 and STAT3, which play crucial roles in T-cell development and activation. We had previously identified them as T-cell specific components of the nucleolus, and IF studies suggested that their association with the nucleolus could be regulated by specific conditions [165] . Our results further support that Tat could contribute to the dysregulation of TCR-derived signals and that the nucleolus could represent an important spatial link for TCR signaling molecules.
We observed the coordinated nucleolar enrichment of key components of the DNA replication, recombination and repair pathways by Tat. These include XRCC5 and XRCC6, HMGA1, APEX1, MCM2-7, SMC2, RFC1 and RFC2, while RFC4 was found to be significantly depleted. Interestingly, these cofactors have been associated with the efficiency of retroviral DNA integration into the host DNA or the integrity of integrated provirus [166] . Whether the increased abundance of these factors within the nucleolus could be associated with their potential participation in the integration and maintenance of provirus gene integrity, remains to be determined.
The mechanisms of Tat-mediated segregation and compartimentalisation of proteins in or out of the nucleolus may depend on factor(s) inherent for each protein and the nature of their relationship with Tat, since subcellular fractionation combined with WB analysis showed that the pattern and extent of subcellular redistribution between proteins varied. We could observe cases where Tat upregulated the expression of proteins which resulted in a general increase of theses proteins throughout the cellular compartments including the nucleolus (DDX3, TNPO1). Alternatively, Tat could trigger the nucleolar translocation of proteins directly from the cytoplasm or the nucleoplasm (pRb). Additionally, we observed cytoplasmic proteins redistributed to both the nucleoplasm and nucleolus upon Tat expression (STAT3, ZAP70 and HSP90). Finally, we also noted protein depletion in the nucleolar fraction accompanied by an increase in the nucleoplasm (SSRP1). It remains difficult at this stage, to appreciate whether the accumulation of specific proteins would result in their activation or inhibition by sequestering them away from their site of action. Conversely, the depletion of a protein from the nucleolus could either result in the down-regulation of its activity in this location or could be the result of its mobilization from its storage site, the nucleolus, to the nucleoplasm or cytoplasm where it can perform its function. Remarkably, we identified several known HIV-1 Tat partners involved in HIV-1 pathogenesis, which suggests that Tat could physically modulate their nucleolar targeting or their recruitment to specific site in the nucleoplasm or cytoplasm. Tat could also promote post-translational modifications, which could mediate the targeting of specific proteins to the nucleolus. This is exemplified by the following enriched proteins, pRb, PP1 and STAT3, for which phosphorylation is induced by Tat. Importantly, their phosphorylation status determines their subcellular distribution, thus providing a potential mechanism for their redistribution by Tat. Moreover, our data indicates that serine/threonine kinases (CK2 a') and phosphatases (PP1) were significantly enriched in the nucleolar fractions of Jurkat TAP-Tat. These enzymes account for the majority of the phosphorylation/ dephosphorylation activity in the nucleolus and can act as regulators of nucleolar protein trafficking. In addition, Tat significantly decreased the levels of SUMO-2 in the nucleolus. Similarly, SUMO-mediated post-translational modifications are known to modulate nucleolar protein localization [104] . Given the potential importance of post-translational modifications, including phosphorylation in the Tat-mediated change of abundance of nucleolar proteins, a more targeted proteomic approach such as the enrichment for phosphopetides, would extend the resolution of our screening approach.
The control of protein turnover is also an important mean to modulate the abundance of nucleolar proteins. Ribosomal proteins are degraded by the Ubiquitin-Proteasome pathway to ensure their abundance matches up with rRNA transcription levels. Conversely, heat shock proteins HSP90s protect them from degradation. Interestingly, our data showing that Tat modulation the abundance proteins associated with the Ubiquitin-proteasome and heat-shock pathway. This could contribute to the observed enrichment of ribosomal proteins by Tat. Nevertheless, we cannot exclude that the increased abundance of ribosomal proteins in the nucleolus could be the result of Tat-mediated prevention of their export to the cytoplasm. Interestingly, using a different cellular system, a drosophila melanogaster Tat transgenic strain, Ponti et al, analysed the effects of Tat on ribosome biogenesis, following 3 days heat shock treatment to induce Tat expression under the control of the hsp70 promoter [167] . Following Tat expression, they observed a defect in pre-rRNA processing associated with a decrease in the level of 80S ribosomes [167] . Nevertheless, the different cellular system employed combined with the 3 days heatshock induction make their results difficult to compare with ours.
While previous system-level studies have monitored the effects of HIV-1 Tat expression on T cells, to our knowledge, we have presented here the first proteomic analysis of dynamic composition of the nucleolus in response to HIV-1 Tat expression. Using quantitative proteomics, we have underlined the changes in abundance of specific nucleolar proteins and have highlighted the extensive and coordinated nucleolar reorganization in response to Tat constitutive expression. Our findings underscore that Tat expressing T-cells exhibit a unique nucleolar proteomic profile, which may reflect a viral strategy to facilitate the progression to robust viral production. Importantly, we noted the functional relationship of nucleolar proteins of our dataset with HIV-1 pathogenesis and HIV-1 Tat in particular. This further increases our confidence in our experimental strategy and suggests a role for Tat in the spatial control and subcellular compartimentaliation of these cellular cofactors. Ultimatly, our study provides new insights on the importance of Tat in the cross talk between nucleolar functions and viral pathogenesis. Importantly, we have also identified changes in nucleolar protein abundance that were not previously associated with HIV-1 pathogenesis, including proteins associated with metabolic pathways, which provide new potential targets and cellular pathways for therapeutic intervention.
Jurkat T-cells, clone E6.1 (ATCC), Jurkat NTAP-Tat and Jurkat NTAP were maintained in RPMI-1640 medium supplemented with 10% (v/v) foetal bovine serum (Gibco, EU approved), and antibiotics. Phoenix-GP cells (G.P. Nolan; www.stanford.edu/ group/nolan/), were maintained in DMEM medium supplemented with 10% (v/v) foetal bovine serum (GIBCO, EU approved). Cells were counted using Scepter TM 2.0 Cell Counter (Millipore).
The sequence of HIV-1 Tat (HIV-1 HXB2, 86 amino acids) was sub-cloned into pENTR 2B vector (Invitrogen, A10463). Using the Gateway technology (Invitrogen), we introduced the HIV-1 Tat sequence into the plasmid pCeMM-NTAP(GS)-Gw [168] . Phoenix cells (G.P. Nolan; www.stanford.edu/group/ nolan/), were transfected using Fugene 6 (Roche) with 5 mg of the plasmid NTAP-Tat or NTAP and 3 mg of the pMDG-VSVG. Viral supernatants were collected after 48 h, filtered and used to transduce the Jurkat cell lines. The construct is termed NTAP-Tat, the empty vector was termed NTAP. Using retroviral gene delivery, we stably transduced Jurkat cells (clone E6.1 (ATCC)). The positive clones named Jurkat NTAP-Tat and Jurkat NTAP were sorted to enrich the population of cells expressing GFP using the BC MoFlo XDP cell sorter (Beckman Coulter).
Sub-cellular fractions (10 mg) were resolved by SDS-PAGE and transferred onto BioTrace PVDF membranes (Pall corporation). The following primary antibodies were used: a-Tubulin (Sc 5286), C23 (Sc 6013), and Fibrillarin (Sc 25397) were from Santa Cruz Biotechnology, and PARP (AM30) from Calbiochem, mouse anti-ZAP 70 (05-253, Millipore), rabbit anti-STAT3 (06-596, Millipore), rabbit anti-ILF3 (ab92355, Abcam), rabbit anti-HSP90 beta (ab32568, Abcam), mouse anti-ADAR1 (ab88574, Abcam), rabbit anti-HDAC1 (ab19845, Abcam), rabbit anti-SSRP1 (ab21584, Abcam) rabbit anti-BOP1 (ab86982, Abcam), mouse anti-KpNB1 (ab10303, Abcam), rabbit anti-HIV-1 Tat (ab43014, Abcam), rabbit anti-CK2A (ab10466, Abcam), rabbit anti-DDX3X (ab37160, Abcam), mouse anti-TNPO1 (ab2811, Abcam), mouse anti-HSP90A (CA1023, MERCK), and rabbit-anti RB1 (sc-102, Santa Cruz).The following secondary antibodies were used ECL: Anti-mouse IgG and ECL Anti-rabbit IgG (GE Healthcare), and Donkey anti-goat IgG (Sc 2020) (Santa Cruz Biotechnology).
For SILAC analysis SILAC-RPMI R0K0 and SILAC-RPMI R6K6 (Dundee cells) media supplemented with 10% dialyzed FBS (GIBCO, 26400-036) were used. The Jurkat cells expressing NTAP-Tat and NTAP were serially passaged and grown for five doublings to ensure full incorporation of the labelled amino acids. Cells viability was checked with Trypan Blue (0.4% solution, SIGMA) and further confirmed using PI staining and FACS analysis. Cells were mixed to the ratio 1:1 to obtain 140610 6 cells. Nucleoli were isolated from the mixed cell population as previously described in Jarboui et al., [165] .
Nucleolar extracts (100 mg) were resuspended in 50 mM ammonium bicarbonate and in solution trypsin digested as previously described in Jarboui et al. [165] . Sample was run on a Thermo Scientific LTQ ORBITRAP XL mass spectrometer connected to an Eksigent NANO LC.1DPLUS chromatography system incorporating an auto-sampler. Sample was loaded onto a Biobasic C18 PicofritTM column (100 mm length, 75 mm ID) and was separated by an increasing acetonitrile gradient, using a 142 min reverse phase gradient (0-40% acetonitrile for 110 min) at a flow rate of 300 nL min-1. The mass spectrometer was operated in positive ion mode with a capillary temperature of 200uC, a capillary voltage of 46V, a tube lens voltage of 140V and with a potential of 1800 V applied to the frit. All data was acquired with the mass spectrometer operating in automatic data dependent switching mode. A high resolution MS scan was performed using the Orbitrap to select the 5 most intense ions prior to MS/MS analysis using the Ion trap.
The incorporation efficiency of labelled amino-acids was determined by analysing the peptides identified in isolated nucleoli from cell population maintained in ''Heavy'' medium as described in [169] . Our analysis showed that we had an incorporation efficiency .95% (data not shown).
The MS/MS spectra were searched for peptides identification and quantification using the MaxQuant software [170] (version 1.1.1.36), the Human IPI Database (version 3.83) and the Andromeda search engine associated to MaxQuant [171] . Standard settings were used for MaxQuant with the Acetyl (Protein N-term) as variable modification and Carbamidomethyl (Cys) as fixed modification, 2 missed cleavage were allowed, except that the filtering of labelled amino acids was prohibited. Initial mass deviation of precursor ion and fragment ions were 7 ppm and 0.5 Da, respectively. Each protein ratio was calculated as the intensity-weighted average of the individual peptides ratios. Proteins were identified with the minimum of one peptide with a false discovery rate less than 1%.
Gene ontology, KEGG pathway and Pfam terms were extracted from UNIPROT entries using Perseus, a software from the MaxQuant Data analysis package (http://www.maxquant.org ), and the ToppGene suite tools [54] .
The Jurkat NTAP-Tat and Jurkat NTAP were transfected using the Amaxa electroporation system (Amaxa biosystem) with the pGL3 (pGL3-LTR) (Promega) as recommended by Amaxa Biosystem. Dual-luciferase assays (Promega) were performed according to the manufacturer's instructions. Luciferase activity was measured and normalized against the total amount of proteins as quantified by the BCA protein quantification kit (Pierce, Thermo Scientific).
To preserve their original shape, we performed immunostaining of Jurkat cells in suspension. Cells were fixed in 2% PFA for 10 min at RT, permeabilised in 0.5% Triton X-100 for 15 min at RT and blocked with 5% FCS. Cells were incubated with the rabbit HIV-1 Tat antibody (ab43014, Abcam) followed by the secondary antibody anti-Rabbit alexa fluor 647 (A-21246, Invitrogen). Cells were allowed to attach to Cell-Tak (BD) coated Silanised Slides (DaoCytomation), and stained with DAPI. Images were captured with a Carl Zeiss Confocal Microscope equipped with a Plan-Apochromat 63X/1.4 oil DIC objective.
The proteomics RAW Data file from the mass spectrometry analysis was deposited to the Tranche repository(https:// proteomecommons.org/tranche/) [172] . The file can be accessed and downloaded using the following hash key:
(R3O5SV5Z6HvWqrBNDhp21tXFetluDWYxvwMIfU-h6e1kMgarauCSq4dlNcxeUvFOHDEzLeDcg4X5Y8reSb6-MUA6wM1kIAAAAAAAAB/w = = ). Materials and Methods S1 Description of the methods employed to examine cell cycle, cell viability and cell proliferation analysis.
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1,686 | Nucleolar Protein Trafficking in Response to HIV-1 Tat: Rewiring the Nucleolus
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3499507/
SHA: efa871aeaf22cbd0ce30e8bd1cb3d1afff2a98f9
Authors: Jarboui, Mohamed Ali; Bidoia, Carlo; Woods, Elena; Roe, Barbara; Wynne, Kieran; Elia, Giuliano; Hall, William W.; Gautier, Virginie W.
Date: 2012-11-15
DOI: 10.1371/journal.pone.0048702
License: cc-by
Abstract: The trans-activator Tat protein is a viral regulatory protein essential for HIV-1 replication. Tat trafficks to the nucleoplasm and the nucleolus. The nucleolus, a highly dynamic and structured membrane-less sub-nuclear compartment, is the site of rRNA and ribosome biogenesis and is involved in numerous cellular functions including transcriptional regulation, cell cycle control and viral infection. Importantly, transient nucleolar trafficking of both Tat and HIV-1 viral transcripts are critical in HIV-1 replication, however, the role(s) of the nucleolus in HIV-1 replication remains unclear. To better understand how the interaction of Tat with the nucleolar machinery contributes to HIV-1 pathogenesis, we investigated the quantitative changes in the composition of the nucleolar proteome of Jurkat T-cells stably expressing HIV-1 Tat fused to a TAP tag. Using an organellar proteomic approach based on mass spectrometry, coupled with Stable Isotope Labelling in Cell culture (SILAC), we quantified 520 proteins, including 49 proteins showing significant changes in abundance in Jurkat T-cell nucleolus upon Tat expression. Numerous proteins exhibiting a fold change were well characterised Tat interactors and/or known to be critical for HIV-1 replication. This suggests that the spatial control and subcellular compartimentaliation of these cellular cofactors by Tat provide an additional layer of control for regulating cellular machinery involved in HIV-1 pathogenesis. Pathway analysis and network reconstruction revealed that Tat expression specifically resulted in the nucleolar enrichment of proteins collectively participating in ribosomal biogenesis, protein homeostasis, metabolic pathways including glycolytic, pentose phosphate, nucleotides and amino acids biosynthetic pathways, stress response, T-cell signaling pathways and genome integrity. We present here the first differential profiling of the nucleolar proteome of T-cells expressing HIV-1 Tat. We discuss how these proteins collectively participate in interconnected networks converging to adapt the nucleolus dynamic activities, which favor host biosynthetic activities and may contribute to create a cellular environment supporting robust HIV-1 production.
Text: The nucleolus is a highly ordered subnuclear compartment organised around genetic loci called nucleolar-organising regions (NORs) formed by clusters of hundreds of rDNA gene repeats organised in tandem head-to-tail repeat [1, 2] . A membrane-less organelle originally described as the ''Ribosome Factory'', the nucleolus is dedicated to RNA-polymerase-I-directed rDNA transcription, rRNA processing mediated by small nucleolar ribonucleoproteins (soRNPs) and ribosome assembly. Ribosome biogenesis is essential for protein synthesis and cell viability [2] and ultimately results in the separate large (60S) and small (40S) ribosomal subunits, which are subsequently exported to the cytoplasm. This fundamental cellular process, to which the cell dedicates most of its energy resources, is tightly regulated to match dynamic changes in cell proliferation, growth rate and metabolic activities [3] .
The nucleolus is the site of additional RNA processing, including mRNA export and degradation, the maturation of uridine-rich small nuclear RNPs (U snRNPs), which form the core of the spliceosome, biogenesis of t-RNA and microRNAs (miRNAs) [4] . The nucleolus is also involved in other cellular processes including cell cycle control, oncogenic processes, cellular stress responses and translation [4] .
The concept of a multifunctional and highly dynamic nucleolus has been substantiated by several studies combining organellar proteomic approaches and quantitative mass spectrometry, and describing thousands of proteins transiting through the nucleolus in response to various metabolic conditions, stress and cellular environments [5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16] . Collectively, the aforementioned studies represent landmarks in understanding the functional complexity of the nucleolus, and demonstrated that nucleolar proteins are in continuous exchange with other nuclear and cellular compartments in response to specific cellular conditions.
Of importance, the nucleolus is also the target of viruses including HIV-1, hCMV, HSV and KSHV, as part of their replication strategy [2, 17] . Proteomics studies analysing the nucleoli of cells infected with Human respiratory syncytial virus (HRSV), influenza A virus, avian coronavirus infectious bronchitis virus (IBV) or adenovirus highlighted how viruses can distinctively disrupt the distribution of nucleolar proteins [2, 17, 18, 19, 20, 21, 22, 23, 24] . Interestingly, both HIV-1 regulatory proteins Tat and Rev localise to the nucleoplasm and nucleolus. Both their sequences encompass a nucleolar localisation signal (NoLS) overlapping with their nuclear localisation signal (NLS), which governs their nucleolar localisation [25, 26, 27, 28, 29, 30, 31] . Furthermore, Tat and Rev interact with the nucleolar antigen B23, which is essential for their nucleolar localisation [25, 26, 27, 28, 29, 30] . Nevertheless, a recent study described that in contrast to Jurkat T-cells and other transformed cell lines where Tat is associated with the nucleus and nucleolus, in primary T-cells Tat primarily accumulates at the plasma membrane, while trafficking via the nucleus where it functions [32] . While the regulation of their active nuclear import and/or export, as mediated by the karyopherin/importin family have been well described, the mechanisms distributing Tat and Rev between the cytoplasm, nucleoplasm and the nucleolus remains elusive [33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48] . Importantly, two major studies by Machienzi et al. have revealed important functional links between HIV-1 replication and the nucleolus [49, 50] . First, they could inhibit HIV-1 replication and Tat transactivation function employing a TAR decoy specifically directed to the nucleolus. Furthermore, using a similar approach, with an anti-HIV-1 hammerhead ribozyme fused to the U16 small nucleolar RNA and therefore targeted to the nucleolus, they could dramatically suppress HIV-1 replication. Collectively, these findings strongly suggest that HIV-1 transcripts and Tat nucleolar trafficking are critical for HIV-1 replication. However the nature of these contributions remains to be elucidated.
In this report, we systematically analysed the nucleolar proteome perturbations occurring in Jurkat T-cells constitutively expressing HIV-1 Tat, using a quantitative mass spectrometry approach. Following the detailed annotation of the quantitative abundance changes in the nucleolar protein composition upon Tat expression, we focussed on the Tat-affected cellular complexes and signalling pathways associated with ribosome biogenesis, spliceosome, molecular chaperones, DNA replication and repair and metabolism and discuss their potential involvement in HIV-1 pathogenesis.
In this study, we investigated the quantitative changes in the nucleolar proteome of Jurkat T cells constitutively expressing HIV-1 Tat (86aa) versus their Tat-negative counterpart, using stable isotope labelling with amino acids in cell culture (SILAC) technology, followed by ESI tandem mass spectrometry and implemented the experimental approach described in Figure 1A . First, using retroviral gene delivery, we transduced HIV-1 Tat fused to a tandem affinity purification (TAP) tag (consisting of two protein G and a streptavidin binding peptide) or TAP tag alone (control vector) in Jurkat leukemia T cell clone E6-1 and sorted the transduced cells (GFP positive) by FACS. This resulted in a highly enriched population of polyclonal transduced cells presenting different expression levels of the transgene ( Figure 1B) . The functionality of TAP-Tat was confirmed by transfecting Jurkat TAP-Tat and TAP cells with a luciferase reporter gene vector under the control of the HIV-1 LTR (pGL3-LTR) [36] . TAP-Tat up regulated gene expression from the HIV-1 LTR by up to 28 fold compared to control ( Figure 1C ). To further address the functionality of Tat fused to TAP, we compared Jurkat TAP-Tat with Jurkat-tat, a cell line stably expressing untagged Tat [51] . Both cell line exhibited comparable HIV-1 LTR activity following transfection with pGL3-LTR ( Figure S1 ). Next, Tat expression and subcellular localization was verified by subcellular fractionation followed by WB analysis ( Figure 1E ). TAP-Tat displayed a prominent nuclear/nucleolar localization but could also be detected in the cytoplasm. These observations were further validated by immunofluorescence microscopy ( Figure 1E ). Of note, Jurkat-tat presented similar patterns for Tat subcellular distribution as shown by immunofluorescence microscopy and subcellular fractionation followed by WB analysis (Figure S2 and S3). We next compared the growth rate and proliferation of the Jurkat TAP and TAP-Tat cell lines (Materials and Methods S1), which were equivalent ( Figure S4A ). Similarly, FACS analysis confirmed that the relative populations in G1, S, and G2/M were similar for Jurkat TAP-Tat and TAP cells ( Figure S4B ).
We labeled Jurkat TAP-Tat and Jurkat TAP cells with light (R0K0) and heavy (R6K6) isotope containing arginine and lysine, respectively. Following five passages in their respective SILAC medium, 85 million cells from each culture were harvested, pooled and their nucleoli were isolated as previously described ( Figure 1A ) [52] . Each step of the procedure was closely monitored by microscopic examination. To assess the quality of our fractionation procedure, specific enrichment of known nucleolar antigens was investigated by Western Blot analysis ( Figure 1D ). Nucleolin (110 kDa) and Fibrillarin (FBL) (34 kDa), two major nucleolar proteins known to localise to the granular component of the nucleolus, were found to be highly enriched in the mixed nucleolar fraction. Of note, nucleolin was equally distributed between the nuclear and cytoplasmic fractions. This distribution pattern for nucleolin appears to be specific for Jurkat T-cells as show previously [52, 53] . The nuclear protein PARP-1 (Poly ADPribose polymerase 1) (113 kDa) was present in the nuclear and nucleoplasmic fraction but was depleted in the nucleolar fraction. Alpha-tubulin (50 kDa) was highly abundant in the cytoplasmic fraction and weakly detected in the nuclear fractions. Collectively, these results confirmed that our methods produced a highly enriched nucleolar fraction without significant cross contamination.
Subsequently, the nucleolar protein mixture was trypsindigested and the resulting peptides were analysed by mass spectrometry. Comparative quantitative proteomic analysis was performed using MaxQuant to analyse the ratios in isotopes for each peptide identified. A total of 2427 peptides were quantified, representing 520 quantified nucleolar proteins. The fully annotated list of the quantified nucleolar proteins is available in Table S1 and the raw data from the mass spectrometry analysis was deposited in the Tranche repository database (https:// proteomecommons.org/tranche/), which can be accessed using the hash keys described in materials and methods. We annotated the quantified proteins using the ToppGene Suite tools [54] and extracted Gene Ontology (GO) and InterPro annotations [55] . The analysis of GO biological processes ( Figure 1F ) revealed that the best-represented biological processes included transcription (24%), RNA processing (23%), cell cycle process (13%) and chromosome organisation (15%), which reflects nucleolar associated functions and is comparable to our previous characterisation of Jurkat T-cell nucleolar proteome [52] . Subcellular distribution analysis ( Figure 1F ) revealed that our dataset contained proteins known to localise in the nucleolus (49%), in the nucleus (24%) while 15% of proteins were previously described to reside exclusively in the cytoplasm. The subcellular distribution was similar to our previous analysis of the Jurkat T-cell nucleolar proteome [52] . Table S1 . The distribution of protein ratios are represented in Figure 1G as log 2 (abundance change). The SILAC ratios indicate changes in protein abundance in the nucleolar fraction of Jurkat TAP-Tat cells in comparison with Jurkat TAP cells. The distribution of the quantified proteins followed a Gaussian distribution ( Figure 1G ). A total of 49 nucleolar proteins exhibited a 1.5 fold or greater significant change (p,0.05) upon Tat expression (Table 1) . Of these, 30 proteins were enriched, whereas 19 proteins were depleted. Cells displayed no changes in the steady state content of some of the major and abundant constituents of the nucleolus, including nucleophosmin (NPM1/ B23), C23, FBL, nucleolar protein P120 (NOL1), and nucleolar protein 5A (NOL5A). The distinct ratios of protein changes upon Tat expression could reflect specific nucleolar reorganization and altered activities of the nucleolus.
We performed WB analysis to validate the SILAC-based results obtained by our quantitative proteomic approach ( Figure 2 ). 15 selected proteins displayed differential intensity in the nucleolar fractions upon Tat expression, including 9 enriched (HSP90b, STAT3, pRb, CK2a, CK2a', HSP90a, Transportin, ZAP70, DDX3), and 3 depleted (ILF3, BOP1, and SSRP1) proteins. In addition, we also tested by WB analysis, protein abundance not affected by Tat expression (Importin beta, FBL, B23, C23). These results highlight the concordance in the trend of the corresponding SILAC ratios, despite some differences in the quantitative ranges. Of note, using WB, we could observe a change of intensity for protein with a SILAC fold change as low as 1.25-fold.
Of note, the question remains as to which fold change magnitude might constitute a biologically relevant consequence. On the one hand, the threshold of protein abundance changes can be determined statistically and would then highlight the larger abundance changes as illustrated in Table 1 . Alternatively, the coordinated enrichment or depletion of a majority of proteins belonging to a distinct cellular complex or pathway would allow the definition of a group of proteins of interest and potential significance. Therefore, we next focused on both enriched or depleted individual proteins with activities associated with HIV-1 or Tat molecular pathogenesis, and on clustered modifications affecting entire cellular signaling pathways and macromolecular complexes.
We initially focused on signaling proteins interacting with Tat and/or associated HIV-1 molecular pathogenesis and whose abundance in the nucleolus was modulated by Tat expression.
Phospho-protein phosphatases. Phospho-protein phosphatase PP1 and PP2A are essential serine/threonine phosphatases [56, 57] . Importantly, PP1 accounts for 80% of the Ser/Thr phosphatase activity within the nucleolus. In our study, PP1 was found to be potentially enriched by 1.52-fold in the nucleolus of Jurkat cells expressing Tat, which supports previous studies describing the nuclear and nucleolar targeting of PP1a by HIV-1 Tat and how PP1 upregulates HIV-1 transcription [58, 59, 60, 61, 62] . PP1 c was also identified as part of the in vitro nuclear interactome [63] . Similarly, PPP2CA, the PP2A catalytic subunit (1.29-fold) and its regulatory subunit PP2R1A (1.27-fold) were similarly enriched upon Tat expression. Interestingly, Tat association with the PP2A subunit promoters results in the overexpression and up regulation of PP2A activity in lymphocytes [64, 65] . Furthermore, PP2A contributes to the regulation of HIV-1 transcription and replication [61, 66] .
Retinoblastoma Protein. The tumour suppressor gene pRb protein displayed a 1.4-fold change in the nucleolus upon Tat expression [67] . Furthermore, WB analysis confirmed the distinct translocation of pRb from the nucleoplasm to the nucleolus by Tat ( Figure 2 ). Depending on the cell type, pRb can be hyperphosphorylated or hypophosphorylated upon Tat expression and can negatively or positively regulate Tat-mediated transcription respectively [68, 69, 70] . Interestingly, the hyperphosphorylation of pRB triggers in its translocation into the nucleolus [71] . Phosphorylation of pRB is also associated with an increase in ribosomal biogenesis and cell growth [72] .
STAT3. The transcription factor signal transducer and activator of transcription 3 (STAT3) was significantly enriched (1.86-fold) in the nucleolar fraction by Tat constitutive expression. Furthermore, WB analysis indicated that Tat expression could promote the relocalisation of STAT3 from the cytoplasm to the nucleus, with a distinct enrichment in the nucleolus ( Figure 2) . Interestingly, previous studies have demonstrated Tat-mediated activation of STAT3 signaling, as shown by its phosphorylation status [73] . Interestingly, STAT3 phosphorylation induced dimerisation of the protein followed its translocation to the nucleus [74] .
YBX1. YBX1, the DNA/RNA binding multifunctional protein was enriched by 1.38-fold in the nucleolus of Jurkat cells upon Tat expression. Interestingly, YBX1 interacts with Tat and TAR and modulates HIV-1 gene expression [63, 75] .
ZAP70. The protein tyrosine kinase ZAP70 (Zeta-chainassociated protein kinase 70) was enriched by 1.24-fold in the nucleolus of Jurkat cells expressing Tat [76] . Furthermore, WB analysis revealed that Tat expression could promote the relocalisation of ZAP70 from the cytoplasm to the nucleus, with a distinct enrichment in the nucleolus ( Figure 2 ). Of note, ZAP70 is part of the in vitro nuclear Tat interactome [63] .
Matrin 3. The inner nuclear matrix protein, Matrin 3 (MATR3), presented a 1.39-fold change in the nucleolus of Jurkat cells expressing Tat. It localizes in the nucleolasm with a diffuse pattern excluded from the nucleoli [77] . Matrin 3 has been identified as part of the in vitro HIV-1 Tat nuclear interactome [63] . Two recent studies have described Matrin 3 as part of ribonucleoprotein complexes also including HIV-1 Rev and (Rev Response Element) RRE-containing HIV-1 RNA, and promoting HIV-1 post-transcriptional regulation [78, 79, 80] .
CASP10. The pro-apototic signaling molecule, Caspase 10 (CASP10), was significantly depleted from the nucleolus of Jurkat-Tat cells (0.82-fold) [81] . Importantly, Tat expression downregulates CASP10 expression and activity in Jurkat cells [82] .
ADAR1. Adenosine deaminase acting on RNA (ADAR1), which converts adenosines to inosines in double-stranded RNA, was significantly depleted from the nucleolus of Jurkat-Tat cells (0.78-fold). Interestingly, ADAR1 over-expression up-regulates HIV-1 replication via an RNA editing mechanism [83, 84, 85, 86, 87, 88] . Furthermore, ADAR1 belongs to the in vitro HIV-1 Tat nuclear interactome [63] .
To underline the structural and functional relationships of the nucleolar proteins affected by HIV-1 Tat, we constructed a network representation of our dataset. We employed Cytoscape version 2.6.3 [89] and using the MiMI plugin [90] to map previously characterised interactions, extracted from protein interaction databases (BIND, DIP, HPRD, CCSB, Reactome, IntAct and MINT). This resulted in a highly dense and connected network comprising 416 proteins (nodes) out of the 536 proteins, linked by 5060 undirected interactions (edges) ( Figure 3A ). Centrality analysis revealed a threshold of 23.7 interactions per protein. Topology analysis using the CentiScaPe plugin [91] showed that the node degree distribution follows a power law ( Figure S5 ), characteristic of a scale-free network. Importantly, when we analysed the clustering coefficient distribution ( Figure S6 ) we found that the network is organised in a hierarchical architecture [92] , where connected nodes are part of highly clustered areas maintained by few hubs organised around HIV-1 Tat. Furthermore, node degree connection analysis of our network identified HIV-1 Tat as the most connected protein ( Figure S6 ). Specifically, the topology analysis indicated that the values for Tat centralities were the highest (Node degree, stress, radiality, closeness, betweeness and centroid), characterising Tat as the main hub protein of the nucleolar network. Indeed, a total of 146 proteins have been previously described to interact with Tat ( Figure 3B , Table S2 ). These proteins are involved in a wide range of cellular processes including chromosomal organization, DNA and RNA processing and cell cycle control. Importantly, aver the third of these proteins exhibit an increase in fold ratio change (59 proteins with a ratio .1.2 fold).
In parallel, we characterised the magnitude of the related protein abundance changes observed in distinct cellular pathways ( Figure 4) .
Ribosomal biogenesis. We initially focused on ribosome biogenesis, the primary function of the nucleolus. We could observe a general and coordinated increase in the abundance of ribosomal proteins in the nucleolus by Tat expression (Figure 4 ). While some ribosomal proteins remained unaffected, Tat caused the nucleolar accumulation of several distinct large and small ribosomal proteins, except RPL35A, for which Tat expression caused a marked decrease at the nucleolar level (0.29-fold). Similarly, several proteins involved in rRNA processing exhibited an overall increase in nucleolar accumulation upon Tat expression. These include human canonical members of the L7ae family together with members participating in Box C/D, H/ACA and U3 snoRNPs ( Figure 4) . Conversely, BOP1, a component of the PeBoW (Pescadillo Bop1 WDR12) complex essential for maturation of the large ribosomal subunit, was significantly depleted from the nucleolus of Jurkat TAP-Tat cells (0.81-fold) and this was confirmed by WB analysis (Figure 2 ) [93] . Nevertheless, the other PeBoW complex components, Pes1 (0.94-fold) and WDR12 (1.1fold), were not affected by Tat expression. Of note, we did not detect change in the abundance of protein participating in rDNA transcription such as RNAPOLI, UBF.
Spliceosome. We identified and quantified in our dataset 55 proteins out of the 108 known spliceosomal proteins [94] . These proteins include the small nuclear ribonucleoproteins U1, U2 and U5, Sm D1, D2, D3, F and B, and the heterogeneous nuclear ribonucleoproteins. Our data suggested a distinct increase in the abundance of specific spliceosome complex proteins upon expression of HIV-1 Tat in Jurkat T-cells (Figure 3 and 4) . The only three proteins that were significantly depleted from the nucleolus upon expression of HIV-1 Tat were RBMX (0.89-fold), HNRNPA2B1 (0.84-fold) and SNRPA (0.81-fold). Several investigations showed expression alteration in cellular splicing factors in HIV-1 infected cells [95, 96] .
Molecular chaperones. We have identified several molecular chaperones, co-chaperones and other factors involved into proteostasis to be highly enriched in the nucleolus of T-cells upon Tat expression (Figure 3 and 4) , many of which were previously characterised as part of the Tat nuclear interactome [63] . Several heat-shock proteins including DNAJs, specific HSP90, HSP70 and HSP40 isoforms and their co-factors were distinctively enriched in the nucleolar fraction of Jurkat cells expressing Tat ( Figure 4 ). As shown by WB, while HSP90a and b are mostly cytoplasmic, Tat expression triggers their relocalisation to the nucleus and nucleolus, corroborating our proteomic quantitative approach (Figure 2) . Similarly, heat-shock can cause the HSP90 and HSP70 to relocalise to the nucleolus [97, 98, 99, 100, 101] . In a recent study, Fassati's group has shown that HSP90 is present at the HIV-1 promoter and may directly regulate viral gene expression [102] . We also observed the coordinated increased abundance of class I (GroEL and GroES) and class II (chaperonin containing TCP-1 (CTT)) chaperonin molecules (Figure 3 and 4) upon Tat expression.
Ubiquitin-proteasome pathway. The ubiquitin-proteasome pathway is the major proteolytic system of eukaryotic cells [103] . Importantly, the nuclear ubiquitin-proteasome pathway controls the supply of ribosomal proteins and is important to ribosome biogenesis [104, 105] . The 26S proteasome is composed of the 20S core particle (CP) and the 19S regulatory particle (RP). Alternatively, CP can associate with the 11S RP to form the immunoproteasome. All the quantified proteins in our study are part of the 19S regulatory complex and include PSMD2 (1.5-fold), PSMD3 (1.32-fold), PSMD11 (1.25-fold) and PSMD13 (0.72-fold), the only proteasome component significantly depleted from the nucleolus in the presence of Tat (Figure 4) . Interestingly, Tat interacts with distinct subunits of the proteasome system, including the 19S, 20S and 11S subunits. The consequences of these interactions include the competition of Tat with 11S RP or 19S RP for binding to the 20S CP, which resulted in the inhibition of the 20S peptidase activity [106, 107, 108, 109, 110, 111] . Furthermore, Tat was shown to modify the proteasome composition and activity, which affects the generation of peptide antigens recognized by cytotoxic T-lymphocytes [112] . Importantly, a recent study demonstrated that in the absence of Tat, proteasome components are associated to the HIV-1 promoter and proteasome activity limits transcription [113] . Addition of Tat promoted the dissociation of the 19S subunit from the 20S proteasome, followed by the distinct enrichment of the 19S-like complex in nuclear extracts together with the Tat-mediated recruitment of the 19S subunits to the HIV-1 promoter, which facilitated its transcriptional elongation [113] . We also quantified UBA1 (1.36-fold), the E3 ubiquitin-protein ligase UHRF1 (1.13-fold), UBC (1-fold) and two Ubiquitinspecific-peptidases, USP30 (1.28-fold) and USP20 (0.06-fold) (Figure 4) .
DNA replication and repair. Upon HIV-1 Tat expression, we observed the coordinated nucleolar enrichment of several cellular factors associated with DNA replication and repairs pathways (Figure 4) .
Tat induced the coordinated enrichment of the miniature chromosome maintenance MCM2-7 complex (from 1.23-to 3.30fold, respectively) [114] . MCM7, 6 and 3 were identified as part of the in vitro nuclear interactome of HIV-1 Tat [63] . The structural maintenance of chromosomes 2, SMC2, was enriched (1.35-fold) in the nucleolar fraction by Tat expression. SMC2 was identified as part of the in vitro nuclear interactome of HIV-1 Tat [63] . While replication factor C1 (RFC1) and RFC2 (1.31-and 1.28-fold respectively) displayed an increased fold change and RFC5/3 were not affected, RFC4 was severely depleted (0.69-fold) from the nucleolar fraction upon Tat expression [115] . RFC1 and RFC2 were identified as part of the in vitro nuclear interactome of HIV-1 Tat [63] . Tat induced the enrichment of XRCC6 (1.27-fold) and XRCC5 (1.36-fold) in the nucleolus, which are involved in the repair of non-homologous DNA end joining (NHEJ) [116] . XRCC6 associates with viral preintegration complexes containing HIV-1 Integrase and also interact with Tat and TAR [117, 118, 119] . Furthermore, in a ribozyme-based screen, XRCC5 (Ku80) knockdown decreased both retroviral integration and Tatmediated transcription [120] . As part of the base excision repair (BER), we have identified a major apurinic/apyrimidinic endonuclease 1 (APEX1) (1.29-fold) . Importantly, in a siRNA screen targeting DNA repair factors, APEX1 knockdown was found to inhibit HIV-1 infection by more 60% [121] . The high mobility group (HMG) protein, HMGA1 (1.30-fold), was enriched in the nucleolus following Tat expression [122] . HMGA1 interact with HIV-1 Integrase and is part of the HIV-1 pre-integration complex [123, 124] . Importantly, HMGA1 has been identified in a proteomic screen, as a cellular cofactor interacting with the HIV-1 59leader [125] .
Metabolism. Our proteomic data suggest that Tat induces perturbations in glycolysis, the pentose phosphate pathway, and nucleotide and amino acid biosynthesis (Figure 4 and Figure S7 ). Notably, in T cells expressing Tat, we detected co-ordinated changes in the abundance of proteins not previously known to be associated with Tat pathogenesis, which revealed unexpected connections with with glycolysis and the pentose phosphate pathway, including the following glycolitic enzymes, lactate dehydrogenase B (LDHB) (1.37-fold), glyceraldehyde 3-phosphate dehydrogenase (GAPDH) (1.17-fold) and phosphoglyceric acid mutase (PGAM1) (0.89-fold) ( Figure 4 and Figure S7 ). Briefly, GPI catalyzes the reversible isomerization of glucose-6-phosphate in fructose-6-phosphate. Subsequently, PFKP catalyzes the irreversible conversion of fructose-6-phosphate to fructose-1,6-bisphosphate and is a key regulatory enzyme in glycolysis. At the end of the glycolytic pathway, PKM2, in its tetrameric form, is known to generate ATP and pyruvate, while LDHB diverts the majority of the pyruvate to lactate production and regeneration of NAD+ in support to continued glycolysis, a phenomenon described for proliferative Tcells [126] . Of note, in highly proliferating cells, PKM2 can be found in its dimeric form and its activity is altered. This upregulates the availibility of glucose intermediates, which are rerouted to the pentose phosphate and serine biosynthesis pathways for the production of biosynthetic precursors of nucleotides, phospholipids and amino acids. As part of the pentose phosphate pathway, we have characterised the significant enrichment of glucose-6-phosphate dehydrogenase (G6PD) (2.11-fold), which branches of the glycolysis pathway to generate NADPH, ribose-5phosphate an important precursor for the synthesis of nucleotides. Consistent with this, we detected the coordinated increase in the abundance of enzymes which plays a central role in the synthesis of purines and pyrimidines. More specifically, IMPDH2 (1.66fold), a rate-limiting enzyme at the branch point of purine nucleotide biosynthesis, leading to the generation of guanine nucleotides, phosphoribosyl pyrophosphate synthetase 2 (PRPS2) (1.41-fold), cytidine-5-prime-triphosphate synthetase (CTPS) (1.74-fold) which catalyses the conversion of UTP to CTP and the ribonucleotide reductase large subunit (RRM1) (1.56-fold). In parralel, we noted the increased abundance of the phosphoserine aminotransferase PSAT1 (1.90-fold), an enzyme implicated in serine biosynthesis, which has been linked with cell proliferation in vitro.
The host-virus interface is a fundamental aspect in defining the molecular pathogenesis of HIV-1 [127, 128, 129, 130, 131, 132, 133] . Indeed, with its limited repertoire of viral proteins, HIV-1 relies extensively on the host cell machinery for its replication. Several recent studies have capitalized on the recent advances in the ''OMICS'' technologies, and have revealed important insights into this finely tuned molecular dialogue [132, 134] . HIV-1 Tat is essential for viral replication and orchestrates HIV-1 gene expression. The viral regulatory protein is known to interact with an extensive array of cellular proteins and to modulate cellular gene expression and signaling pathway [135, 136] . We and others have employed system-level approaches to investigate Tat interplay with the host cell machinery, which have characterised HIV-1 Tat as a critical mediator of the host-viral interface [137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149] . Here, we have investigated the nucleolar proteins trafficking in response to HIV-1 Tat expression in T-cells, with the view to provide unique and novel insights on the role of proteins compartimentalisation by Tat in the fine-tuning of protein availability and function.
We have developed for this study, a cellular model using Jurkat T-cells stably expressing Tat fused in its N-ternminal to TAP-tag.
Jurkat T-cells are robust and present the advantage to grow without stimulations and are easely transduced using retroviral gene delivery. Importantly, they have been widely employed to evaluate Tat-mediated pathogenesis using system-wide approaches and to analyse T-cell key cellular signaling pathways and functions [144, 150, 151, 152] . Indeed, we have found them particularly suited for prolongued in vitro culture in SILAC medium and subsequent isolation of their nucleolus followed by MS analysis, which requires up to 85 millions of cells. We fused Tat to the TAP tag to enable future downstream applications such as Tandem affinity purification or Chromatin IP analysis. Importantly, we have confirm that N-terminal TAP-tag did not interfere with Tat function nor its localisation in Jurkat cells, when compared to untagged-Tat. Of note, Tat subcellular distribution can vary according to the cell type employed. While Tat is known to accumulate in the nucleus and nucleolus in Jurkat cells and other transformed cell lines, in primary T-cells, Tat was described to primarily accumulate at the plasma membrane, while trafficking via the nucleus where it functions [32] . These differences remain to be characterised but could be related to different expression levels of transport factors in transformed cell lines versus primary cells, as recently described by Kuusisto et al. [39] . Furthermore, Stauber and Pavlakis have suggested that Tat nucleolar localisation could be the results of Tat overexpression [31] . Here, we have selected and employed a polyclonal population of Jurkat T-cells expressing Tat at different levels. We propose that this heterogeneity in Tat expression levels might reflect Tat stochastic expression described during viral replication [153] .
Using a quantitative proteomic strategy based on an organellar approach, we quantified over 520 nucleolar proteins, including 49 proteins exhibiting a significant fold change. The extent to which the induced variations in the abundance of nucleolar proteins are biologically relevant and can affect cellular and/or viral processes remains to be determined. Nevertheless, the biological nature of the pathways and macromolecular complexes affected enable us to discuss their potential associations with HIV-1 pathogenesis.
HIV-1 Tat is expressed early following HIV-1 genome integration and mediates the shift to the viral production phase, associated with robust proviral gene expression, viral proteins assembly and ultimately, virions budding and release. In this context and based on our results, we propose that Tat could participate in shaping the intracellular environment and metabolic profile of T cells to favor host biosynthetic activities supporting robust virions production. Indeed, we observed the distinct nucleolar enrichment of ribosomal proteins and enzymes associated with ribosomal biogenesis, which could be indicative of an increase in protein synthesis. With the notable exeption of RPL35A nucleolar depletion, ribosomal proteins and enzymes associated with ribosomal biogenesis were in the top 20 most enriched nucleolar proteins (NHP2L1, RLP14, RPL17, RPL27, RPS2, RPL13). Furthermore, this effect appears to be specific to HIV-1 Tat since transcription inhibition by Actinomycin D resulted in the overall depletion of ribosomal proteins in the nucleolus [9] . Moreover, quantitative proteomics analysis of the nucleous in adenovirus-infected cells showed a mild decrease in ribosomal proteins [24] . Whether this reflect a shift in ribosome biogenesis and/or a change in the composition of the ribosomal subunits remains to be determined. Nevertheless, the adapted need for elevated ribosome production is intuitive for a system that needs to support the increased demand for new viral proteins synthesis. In parralel, we observed the concordant modulation of pathways regulating protein homeostasis. We noted the significant nucleolar accumulation of multiple molecular chaperones including the HSPs, the TCP-1 complex, and CANX/CALR molecules and the disrupted nucleolar abundance of proteins belonging to the ubiquitin-proteasome pathway, which controls the supply of ribosomal proteins [104, 105] . These observations further support previous studies describibing the modulation of the proteasomal activity by Tat, which affect the expression, assembly, and localization of specific subunits of the proteasomal complexes [106, 107, 108, 109, 110, 111, 113] . We also observed the concomitant depletion of CASP10 in the nucleolus of Jurkat TAP-Tat. It has been suggested that CASP10 could be targeted to the nucleolus to inhibit protein synthesis [154] . Interestingly, the presence and potential roles of molecular chaperones in the nucleolus have been highlighted by Banski et al, who elaborate on how the chaperone network could regulate ribosome biogenesis, cell signaling, and stress response [97, 155] . As viral production progresses into the late phase and cellular stress increases, nucleolar enrichment of molecular chaperones by Tat could not only enable adequat folding of newly synthetised viral proteins but could also promote tolerance of infected cells to stress and maintain cell viability.
Coincidentally, we observed the marked nucleolar enrichment of enzymes belonging to metabolic pathways including glycolysis, pentose phosphate, nucleotide and amino acid biosynthetic pathways. Similarly, these pathways are elevated in proliferative T-cells or in cancer cells following a metabolic shift to aerobic glycolysis, also known as the Warburg effect [156, 157, 158, 159] . There, glucose intermediates from the glycolysis pathway are not only commited to energy production and broke-down into pyruvate for the TCA cycle, but are redirected to alternative pathways, including the pentose phosphate pathway, and used as metabolic precursors to produce nucleotides, amino acids, acetyl CoA and NADPH for redox homeostasis. Consistently, we also noted the concomittant nucleolar enrichment of enzymes belonging to the nucleotide synthesis pathway, including IMPH2, a rate limiting enzyme known to control the pool of GTP. Similarly, we noted the nucleolar enrichment of PSAT1, an enzyme involved in serine and threonin metabolism, which is associated with cellular proliferation [160] . Collectively, we propose that by controlling protein homeostasis and metabolic pathways, Tat could meet both the energetic and biosynthetic demand of HIV-1 productive infection.
Of note, while nucleotide metabolism enzymes are associated with the nucleus, glycolysis takes place in the cytoplasm. Nevertheless, glycolytic enzymes have been detected in both the nuclear and nucleolar fractions by proteomic analyses [8, 161] . Furthermore glycolytic enzymes, such as PKM2, LDH, phosphoglycerate kinase, GAPDH, and aldolase, also have been reported to display nuclear localization and bind to DNA [162] . More specifically, PKM2 is known to associate with promoter and participate in the regulation of gene expression as a transcriptional coactivator [163] .
HIV-1 Tat has previously been described as an immunoregulator and more specifically, has been reported both to inhibit or to promote TCR signaling [164] . We have observed the nucleolar enrichment by Tat of key proximal or downstream components of T-cell signaling pathways, including ZAP70, ILF3 and STAT3, which play crucial roles in T-cell development and activation. We had previously identified them as T-cell specific components of the nucleolus, and IF studies suggested that their association with the nucleolus could be regulated by specific conditions [165] . Our results further support that Tat could contribute to the dysregulation of TCR-derived signals and that the nucleolus could represent an important spatial link for TCR signaling molecules.
We observed the coordinated nucleolar enrichment of key components of the DNA replication, recombination and repair pathways by Tat. These include XRCC5 and XRCC6, HMGA1, APEX1, MCM2-7, SMC2, RFC1 and RFC2, while RFC4 was found to be significantly depleted. Interestingly, these cofactors have been associated with the efficiency of retroviral DNA integration into the host DNA or the integrity of integrated provirus [166] . Whether the increased abundance of these factors within the nucleolus could be associated with their potential participation in the integration and maintenance of provirus gene integrity, remains to be determined.
The mechanisms of Tat-mediated segregation and compartimentalisation of proteins in or out of the nucleolus may depend on factor(s) inherent for each protein and the nature of their relationship with Tat, since subcellular fractionation combined with WB analysis showed that the pattern and extent of subcellular redistribution between proteins varied. We could observe cases where Tat upregulated the expression of proteins which resulted in a general increase of theses proteins throughout the cellular compartments including the nucleolus (DDX3, TNPO1). Alternatively, Tat could trigger the nucleolar translocation of proteins directly from the cytoplasm or the nucleoplasm (pRb). Additionally, we observed cytoplasmic proteins redistributed to both the nucleoplasm and nucleolus upon Tat expression (STAT3, ZAP70 and HSP90). Finally, we also noted protein depletion in the nucleolar fraction accompanied by an increase in the nucleoplasm (SSRP1). It remains difficult at this stage, to appreciate whether the accumulation of specific proteins would result in their activation or inhibition by sequestering them away from their site of action. Conversely, the depletion of a protein from the nucleolus could either result in the down-regulation of its activity in this location or could be the result of its mobilization from its storage site, the nucleolus, to the nucleoplasm or cytoplasm where it can perform its function. Remarkably, we identified several known HIV-1 Tat partners involved in HIV-1 pathogenesis, which suggests that Tat could physically modulate their nucleolar targeting or their recruitment to specific site in the nucleoplasm or cytoplasm. Tat could also promote post-translational modifications, which could mediate the targeting of specific proteins to the nucleolus. This is exemplified by the following enriched proteins, pRb, PP1 and STAT3, for which phosphorylation is induced by Tat. Importantly, their phosphorylation status determines their subcellular distribution, thus providing a potential mechanism for their redistribution by Tat. Moreover, our data indicates that serine/threonine kinases (CK2 a') and phosphatases (PP1) were significantly enriched in the nucleolar fractions of Jurkat TAP-Tat. These enzymes account for the majority of the phosphorylation/ dephosphorylation activity in the nucleolus and can act as regulators of nucleolar protein trafficking. In addition, Tat significantly decreased the levels of SUMO-2 in the nucleolus. Similarly, SUMO-mediated post-translational modifications are known to modulate nucleolar protein localization [104] . Given the potential importance of post-translational modifications, including phosphorylation in the Tat-mediated change of abundance of nucleolar proteins, a more targeted proteomic approach such as the enrichment for phosphopetides, would extend the resolution of our screening approach.
The control of protein turnover is also an important mean to modulate the abundance of nucleolar proteins. Ribosomal proteins are degraded by the Ubiquitin-Proteasome pathway to ensure their abundance matches up with rRNA transcription levels. Conversely, heat shock proteins HSP90s protect them from degradation. Interestingly, our data showing that Tat modulation the abundance proteins associated with the Ubiquitin-proteasome and heat-shock pathway. This could contribute to the observed enrichment of ribosomal proteins by Tat. Nevertheless, we cannot exclude that the increased abundance of ribosomal proteins in the nucleolus could be the result of Tat-mediated prevention of their export to the cytoplasm. Interestingly, using a different cellular system, a drosophila melanogaster Tat transgenic strain, Ponti et al, analysed the effects of Tat on ribosome biogenesis, following 3 days heat shock treatment to induce Tat expression under the control of the hsp70 promoter [167] . Following Tat expression, they observed a defect in pre-rRNA processing associated with a decrease in the level of 80S ribosomes [167] . Nevertheless, the different cellular system employed combined with the 3 days heatshock induction make their results difficult to compare with ours.
While previous system-level studies have monitored the effects of HIV-1 Tat expression on T cells, to our knowledge, we have presented here the first proteomic analysis of dynamic composition of the nucleolus in response to HIV-1 Tat expression. Using quantitative proteomics, we have underlined the changes in abundance of specific nucleolar proteins and have highlighted the extensive and coordinated nucleolar reorganization in response to Tat constitutive expression. Our findings underscore that Tat expressing T-cells exhibit a unique nucleolar proteomic profile, which may reflect a viral strategy to facilitate the progression to robust viral production. Importantly, we noted the functional relationship of nucleolar proteins of our dataset with HIV-1 pathogenesis and HIV-1 Tat in particular. This further increases our confidence in our experimental strategy and suggests a role for Tat in the spatial control and subcellular compartimentaliation of these cellular cofactors. Ultimatly, our study provides new insights on the importance of Tat in the cross talk between nucleolar functions and viral pathogenesis. Importantly, we have also identified changes in nucleolar protein abundance that were not previously associated with HIV-1 pathogenesis, including proteins associated with metabolic pathways, which provide new potential targets and cellular pathways for therapeutic intervention.
Jurkat T-cells, clone E6.1 (ATCC), Jurkat NTAP-Tat and Jurkat NTAP were maintained in RPMI-1640 medium supplemented with 10% (v/v) foetal bovine serum (Gibco, EU approved), and antibiotics. Phoenix-GP cells (G.P. Nolan; www.stanford.edu/ group/nolan/), were maintained in DMEM medium supplemented with 10% (v/v) foetal bovine serum (GIBCO, EU approved). Cells were counted using Scepter TM 2.0 Cell Counter (Millipore).
The sequence of HIV-1 Tat (HIV-1 HXB2, 86 amino acids) was sub-cloned into pENTR 2B vector (Invitrogen, A10463). Using the Gateway technology (Invitrogen), we introduced the HIV-1 Tat sequence into the plasmid pCeMM-NTAP(GS)-Gw [168] . Phoenix cells (G.P. Nolan; www.stanford.edu/group/ nolan/), were transfected using Fugene 6 (Roche) with 5 mg of the plasmid NTAP-Tat or NTAP and 3 mg of the pMDG-VSVG. Viral supernatants were collected after 48 h, filtered and used to transduce the Jurkat cell lines. The construct is termed NTAP-Tat, the empty vector was termed NTAP. Using retroviral gene delivery, we stably transduced Jurkat cells (clone E6.1 (ATCC)). The positive clones named Jurkat NTAP-Tat and Jurkat NTAP were sorted to enrich the population of cells expressing GFP using the BC MoFlo XDP cell sorter (Beckman Coulter).
Sub-cellular fractions (10 mg) were resolved by SDS-PAGE and transferred onto BioTrace PVDF membranes (Pall corporation). The following primary antibodies were used: a-Tubulin (Sc 5286), C23 (Sc 6013), and Fibrillarin (Sc 25397) were from Santa Cruz Biotechnology, and PARP (AM30) from Calbiochem, mouse anti-ZAP 70 (05-253, Millipore), rabbit anti-STAT3 (06-596, Millipore), rabbit anti-ILF3 (ab92355, Abcam), rabbit anti-HSP90 beta (ab32568, Abcam), mouse anti-ADAR1 (ab88574, Abcam), rabbit anti-HDAC1 (ab19845, Abcam), rabbit anti-SSRP1 (ab21584, Abcam) rabbit anti-BOP1 (ab86982, Abcam), mouse anti-KpNB1 (ab10303, Abcam), rabbit anti-HIV-1 Tat (ab43014, Abcam), rabbit anti-CK2A (ab10466, Abcam), rabbit anti-DDX3X (ab37160, Abcam), mouse anti-TNPO1 (ab2811, Abcam), mouse anti-HSP90A (CA1023, MERCK), and rabbit-anti RB1 (sc-102, Santa Cruz).The following secondary antibodies were used ECL: Anti-mouse IgG and ECL Anti-rabbit IgG (GE Healthcare), and Donkey anti-goat IgG (Sc 2020) (Santa Cruz Biotechnology).
For SILAC analysis SILAC-RPMI R0K0 and SILAC-RPMI R6K6 (Dundee cells) media supplemented with 10% dialyzed FBS (GIBCO, 26400-036) were used. The Jurkat cells expressing NTAP-Tat and NTAP were serially passaged and grown for five doublings to ensure full incorporation of the labelled amino acids. Cells viability was checked with Trypan Blue (0.4% solution, SIGMA) and further confirmed using PI staining and FACS analysis. Cells were mixed to the ratio 1:1 to obtain 140610 6 cells. Nucleoli were isolated from the mixed cell population as previously described in Jarboui et al., [165] .
Nucleolar extracts (100 mg) were resuspended in 50 mM ammonium bicarbonate and in solution trypsin digested as previously described in Jarboui et al. [165] . Sample was run on a Thermo Scientific LTQ ORBITRAP XL mass spectrometer connected to an Eksigent NANO LC.1DPLUS chromatography system incorporating an auto-sampler. Sample was loaded onto a Biobasic C18 PicofritTM column (100 mm length, 75 mm ID) and was separated by an increasing acetonitrile gradient, using a 142 min reverse phase gradient (0-40% acetonitrile for 110 min) at a flow rate of 300 nL min-1. The mass spectrometer was operated in positive ion mode with a capillary temperature of 200uC, a capillary voltage of 46V, a tube lens voltage of 140V and with a potential of 1800 V applied to the frit. All data was acquired with the mass spectrometer operating in automatic data dependent switching mode. A high resolution MS scan was performed using the Orbitrap to select the 5 most intense ions prior to MS/MS analysis using the Ion trap.
The incorporation efficiency of labelled amino-acids was determined by analysing the peptides identified in isolated nucleoli from cell population maintained in ''Heavy'' medium as described in [169] . Our analysis showed that we had an incorporation efficiency .95% (data not shown).
The MS/MS spectra were searched for peptides identification and quantification using the MaxQuant software [170] (version 1.1.1.36), the Human IPI Database (version 3.83) and the Andromeda search engine associated to MaxQuant [171] . Standard settings were used for MaxQuant with the Acetyl (Protein N-term) as variable modification and Carbamidomethyl (Cys) as fixed modification, 2 missed cleavage were allowed, except that the filtering of labelled amino acids was prohibited. Initial mass deviation of precursor ion and fragment ions were 7 ppm and 0.5 Da, respectively. Each protein ratio was calculated as the intensity-weighted average of the individual peptides ratios. Proteins were identified with the minimum of one peptide with a false discovery rate less than 1%.
Gene ontology, KEGG pathway and Pfam terms were extracted from UNIPROT entries using Perseus, a software from the MaxQuant Data analysis package (http://www.maxquant.org ), and the ToppGene suite tools [54] .
The Jurkat NTAP-Tat and Jurkat NTAP were transfected using the Amaxa electroporation system (Amaxa biosystem) with the pGL3 (pGL3-LTR) (Promega) as recommended by Amaxa Biosystem. Dual-luciferase assays (Promega) were performed according to the manufacturer's instructions. Luciferase activity was measured and normalized against the total amount of proteins as quantified by the BCA protein quantification kit (Pierce, Thermo Scientific).
To preserve their original shape, we performed immunostaining of Jurkat cells in suspension. Cells were fixed in 2% PFA for 10 min at RT, permeabilised in 0.5% Triton X-100 for 15 min at RT and blocked with 5% FCS. Cells were incubated with the rabbit HIV-1 Tat antibody (ab43014, Abcam) followed by the secondary antibody anti-Rabbit alexa fluor 647 (A-21246, Invitrogen). Cells were allowed to attach to Cell-Tak (BD) coated Silanised Slides (DaoCytomation), and stained with DAPI. Images were captured with a Carl Zeiss Confocal Microscope equipped with a Plan-Apochromat 63X/1.4 oil DIC objective.
The proteomics RAW Data file from the mass spectrometry analysis was deposited to the Tranche repository(https:// proteomecommons.org/tranche/) [172] . The file can be accessed and downloaded using the following hash key:
(R3O5SV5Z6HvWqrBNDhp21tXFetluDWYxvwMIfU-h6e1kMgarauCSq4dlNcxeUvFOHDEzLeDcg4X5Y8reSb6-MUA6wM1kIAAAAAAAAB/w = = ). Materials and Methods S1 Description of the methods employed to examine cell cycle, cell viability and cell proliferation analysis.
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1,557 | Changes in pulmonary tuberculosis prevalence: evidence from the 2010 population survey in a populous province of China
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3890533/
SHA: eef61bdfa49b8652fd660b5b8b7e74cf51922505
Authors: Wei, Xiaolin; Zhang, Xiulei; Yin, Jia; Walley, John; Beanland, Rachel; Zou, Guanyang; Zhang, Hongmei; Li, Fang; Liu, Zhimin; Zee, Benny CY; Griffiths, Sian M
Date: 2014-01-11
DOI: 10.1186/1471-2334-14-21
License: cc-by
Abstract: BACKGROUND: This paper reports findings from the prevalence survey conducted in Shandong China in 2010, a province with a population of 94 million. This study aimed to estimate TB prevalence of the province in 2010 in comparison with the 2000 survey; and to compare yields of TB cases from different case finding approaches. METHODS: A population based, cross-sectional survey was conducted using multi-stage random cluster sampling. 54,279 adults participated in the survey with a response rate of 96%. Doctors interviewed and classified participants as suspected TB cases if they presented with persistent cough, abnormal chest X-ray (CXRAY), or both. Three sputum specimens of all suspected cases were collected and sent for smear microscopy and culture. RESULTS: Adjusted prevalence rate of bacteriologically confirmed cases was 34 per 100,000 for adults in Shandong in 2010. Compared to the 2000 survey, TB prevalence has declined by 80%. 53% of bacteriologically confirmed cases did not present persistent cough. The yield of bacteriologically confirmed cases was 47% by symptom screening and 95% by CXRAY. Over 50% of TB cases were among over 65’s. CONCLUSIONS: The prevalence rate of bacteriologically confirmed cases was significantly reduced compared with 2000. The survey raised challenges to identify TB cases without clear symptoms.
Text: China, with an estimated prevalence of all TB cases of 108 per 100,000 in 2010, has the second highest TB burden in the world, accounting for 13% of all cases worldwide [1] . The World Health organization (WHO) estimated that China had reached the targets of 85% treatment success by 1993 and 70% case detection rate by 2005 [2] . National TB prevalence surveys were conducted in China in 1979 China in , 1990 China in , 2000 , and 2010 [4] . Survey results provide more accurate estimates for TB prevalence rates than the WHO estimates and can be used to assess the likelihood of China achieving global targets for TB prevalence.
Shandong province has a population of 94 million. It is a relatively developed province with a per capita GDP 1.6 times of the national average in 2010 [5] . The prevalence rate of TB in Shandong was lower compared with the average rate of China in 2000 [3] . Population representative samples were drawn in Shandong in the surveys of 2000 and 2010 using similar methods. The study aimed to estimate the TB prevalence in Shandong based on the 2010 survey, and compare results of the two cross sectional surveys.
The target population of the TB prevalence survey was residents of 15 years old or above who had lived in the selected clusters for more than 6 months. A population based, cross-sectional survey was conducted using multistage random cluster sampling method.
The survey employed the same sampling methods as the China national survey in 2010, which was similar to the sampling methods used in 2000 [6] . The design of the surveys was in accordance with WHO recommendations [7] . The design effect factor due to cluster sampling was estimated at 1.28 [8] . A sample size of 52500 adults (≧15 years old), in 35 clusters, was calculated based on detecting a change of 20% in prevalence rate of TB smear positive cases compared with the rate of the 2000 survey (95 per 100,000), with a probability greater than 95% and 95% power, accounting for 90% response rate of participants [9] .
A stratified multi stage random sampling was used to select the 35 clusters within 17 prefectures in Shandong province. The number of clusters was randomly allocated in proportion to the provincial population at the prefectural, county/district and township levels. A cluster was defined as a community (a village in the rural area or a resident community in an urban area) with a population of 1250 to 1750 adults (i.e., those of 15 years or older). If the community contained less than 1250 adult residents, the neighboring community to the north was annexed. If the community or combined communities containing more than 1750 adults, we randomly selected households and then included all adults in the household for the survey until the total number of selected adults reached 1750. Military barracks and prisons located in the cluster were excluded [7] .
The survey was conducted from March to June 2010 by survey teams consisting of clinicians, public health doctors, radiologists, laboratory technicians and nurses. Local media was used to promote awareness of the survey. Community workers conducted a house-to-house census to update the database of residents, inform survey participants and obtain informed consent. The study did not involve children under 15 years old. Written informed consent was obtained from all participants of 16 years old or above. While from those of 15 years old, written informed consents were obtained from their parents or guardians. All documents were properly stored in the Shandong Chest Hospital. Ethical approvals for the study and consent procedures were obtained from the Institutional Review Board (IRB) of Shandong Chest Hospital (NIH register numberIRB00006010).
Those who agreed to participate in the survey were invited to the county TB dispensary, where they completed a consultation with a trained clinical TB doctor regarding any symptoms suggestive of TB, such as persistent cough (lasting two weeks or longer), haemoptysis, weight loss and fever. All participants had a chest X-ray (CXRAY) taken that then were reviewed by a panel of radiologists. Those with symptoms or CXRAY films suggestive of TB were classified as suspected TB cases. All suspected cases were asked to produce three sputum samples, one at the time of consultation, another at night and the third in the early morning of the following day. Identified suspects completed an additional questionnaire regarding their social-economic situation, smoking status, and the presence of TB related symptoms in the preceding six months (cough, fever, weight loss, chest pain and haemoptysis).
Sputum smears were conducted in local TB dispensaries. All sputum samples were cultured using the Löwenstein-Jensen medium in the provincial laboratory within 24 hours using cold chain transportation. Samples were excluded from TB when non-tuberculosis bacilli were identified from the culture. All sputum smear and culture were conducted strictly according the national TB laboratory external quality control measure, which is in consistent with the WHO TB prevalence survey guideline [7] . TB classification was made according to the China national TB guideline [10] . A positive smear had at least one acid fast bacillus identified during examination of at least 100 fields. Participants with positive sputum smear specimens were classified as sputum positive cases. Those with positive smear or culture sputum specimens were classified as sputum bacteriologically confirmed cases. Those being culture negative with abnormal CXRAY suggestive of TB and having been ruled out from other diseases by clinicians and radiologists were classified as CXRAY suggestive bacteriologically negative cases. Due to resource limitations the recommendation of broad-spectrum antimicrobial agents to confirm the diagnosis of negative TB cases was not applied in this survey [11] . Newly diagnosed cases were distinguished from previously diagnosed cases through checks during the interviews and against the TB registration system. Initial diagnosis was made by a group of local clinicians and radiologists. Subsequently, samples and CXRAY films of all suspected and confirmed cases were re-assessed by a group of senior clinicians and radiologists at provincial and national levels. CXRAY films of 100% of those scored as abnormal and 10% random sampling of those scored as normal were transferred for independent reading. The provincial laboratory team randomly examined one slide from the three samples of sputum positive cases, all three samples of CXRAY suggestive TB cases, and randomly selected 10% of the non-TB cases.
Prevalence estimates of sputum positive, bacteriologically confirmed and all TB cases were calculated. In all analyses, population weightings were employed to adjust for the stratified multi-stage sampling design effect [8] . The survey results in 2010 and 2000 were standardized against the age structures of China's census population in 2010. The 2000 TB prevalence survey included all age groups [12] . The WHO recommended method was used to enable comparison between the two surveys that prevalence rates of child TB were assumed to reduce to the same extent as adult TB from 2000 to 2010 [13] . Subgroup analysis in gender, age groups and urban/rural residence were conducted. Case identification rate was calculated as the number of cases identified by a screening method over all suspected cases found by the method. Yields of the symptom consultation and CXRAY were calculated as a proportion of the total number of bacteriologically confirmed cases.
The survey selected 17 urban clusters and 18 rural clusters. It covered a total population of 89,093, of which 56,671 were eligible for the survey (Figure 1 ). The response rate ranged from 95% to 97% in different clusters. 54,279 participants attended clinical consultation and were examined by CXRAY. Among them, 47% were males. The average age was 46 years with 14% of 65 years and older. A total of 572 suspected TB cases were found. Of these, 264 (46%) were identified based on CXRAY abnormalities, 228 (40%) were based on persistent cough, 80 (14%) were based on both. The survey diagnosed 172 new cases, including 19 new bacteriologically confirmed cases (including 11 sputum and culture positive cases, and 8 sputum negative but culture positive cases) and 153 CXRAY suggestive bacteriologically negative cases. The survey also identified 11 existing cases registered on the national TB program. In addition, the survey found four cases with culture positive non-tuberculosis bacilli, and excluded them from TB patients.
All participants of the survey were first screened by symptoms and CXRAY. Those who had symptoms of consistent cough or haemoptysis, or CXRAY abnormalities were then screened by smear and culture. Case identification rates of new bacteriologically confirmed cases from the suspected cases were significantly higher with CXRAY as a primary tool (Figure 1 , 3.8%, P = 0.012) and further increased by both symptom screen of persistent cough and CXRAY (10%, P < 0.001) compared with symptom screen alone (0.4%). The same pattern of case identification rate was observed in the sputum positive cases (7.5%, 1.9% and 0% respectively). The proportion reporting persistent cough was not significantly higher among bacteriologically confirmed cases compared with other suspects (P = 0.565). The symptom consultation alone identified 308 suspects, including 6 (1.9%) sputum smear positive TB and 9 (2.9%) bacteriologically confirmed TB. Among the 344 suspects with CXRAY abnormalities, 11 (3.2%) had sputum positive TB and 18 (5.2%) had bacteriologically confirmed TB. The yield of bacteriologically confirmed cases was 47.4% by screening consultation and 94.7% by CXRAY. In the population of over 65 years old, symptom consultation and the CXRAY identified 174 and 182 suspected cases respectively, yielding5 (2.9%) and 9 (4.9%) of bacteriologically confirmed cases. Yields of bacteriologically confirmed cases were 55.6% by symptom consultation and 100% by CXRAY among over 65's.
Of the 512 suspected cases that completed the additional questionnaire, 42% were farmers and 31% were current smokers (Table 1) . Per capita household income of bacteriologically confirmed cases was less than 50% of that of the non-TB cases (P < 0.05). Though smoking rate was higher among TB cases compared with non-TB cases, no significant differences were found (P > 0.05). Of the ten bacteriologically confirmed cases not presenting with persistent cough at the prevalence survey, one coughed for two days, one had chest pain, and the other eight had no symptoms of TB in the last six months.
The crude prevalence rate in Shandong in 2010 of sputum positive cases was 22.1 (95% CI: 9.6-34.6), bacteriologically confirmed cases was 36.8 (95% CI: 17.8-55.8), and all cases were 337.1 (95% CI: 254.1-420.0) per 100,000 in adult population ( Table 2 ). The adjusted prevalence rates of the whole population in Shandong were17.8 (95% CI: 8.3-17.5), 27.8 (95% CI: 14.8-28.0) and 239.4 (95% CI: 179.9-298.9) per 100,000 in 2010. A remarkable decline of 82.0%, 80.2% and 31.4% was observed in TB prevalence rates of sputum positive, bacteriologically confirmed, and all cases, respectively, compared to the adjusted rates in 2000 [12] . Large declines were observed in males between 40 and 65 years old, and in females over 60 years old ( Figure 2) .
The adjusted prevalence rates in the adult population were 21.4 (95% CI: 10.0-32.8), 33.5 (95% CI: 17.8-49.2) and 285.8 (95% CI: 254.2-356.4) for sputum positive cases, bacteriologically confirmed cases and all cases, respectively. Significant differences regarding adjusted TB prevalence rates were observed between males and females, over 65's and 15 to 64 years old, in rural and urban areas ( Table 2 , P < 0.001). The male to female ratios were 5.5 in sputum positive cases and 2.8 in bacteriologically confirmed cases, while the ratios climbed to 6.0 and 4.1, respectively, among those over 65 years. The majority of TB patients, 54.5% of sputum positive cases and 47.3% of bacteriologically confirmed cases, were from people 65 years or older. The ratio between over 65's and 15 to 64 years old was 8.4 in sputum positive cases and 5.9 in bacteriologically confirmed cases. The ratio between rural and urban areas was 2.7 in sputum positive cases and 4.8 in bacteriologically confirmed cases.
The most striking finding was that a large proportion of TB patients did not present consistent cough. Passive case finding is the routine practice in developing countries where sputum microscopy is performed to identify TB cases among people with persistent cough. A large proportion of TB cases may be missed using this method as 53% of bacteriologically confirmed cases and 45% sputum positive cases in this study had no persistent cough but were identified through abnormal CXRAY. Nearly half of bacteriologically confirmed cases reported no symptoms in the last six months. This finding, although initially surprising, is consistent with reports from Vietnam (47% of bacteriologically confirmed cases not presenting persistent cough) [14] , Myanmar (38%) and Ethiopia (48%) [13] . CXRAY was sensitive in detecting TB cases, as yields of bacteriologically confirmed cases were much higher by CXRAY compared with by symptom screening, as reported in Vietnam [15] and some high HIV prevalence settings [16, 17] . CXRAY, though expensive at the initial installment, may improve TB case finding due to its short turnover time and high throughput [18] . Our findings suggest that the strategy of case finding using CXRAY followed by sputum or culture as the primary and secondary screening tests could be more effective, especially among the population of over 65 year olds, as the yields were higher in over 65's compared with the general Table 2 Prevalence rates of sputum positive TB cases, bacteriologically confirmed TB cases and all cases in Shandong, China, 2010 No population. Although using CXRAY to examine everyone is not feasible, it can be used in routine elder physical examinations. The China public health package now covers free CXRAY for elders, as well annual employee body examinations provided free CXRAY.
In this survey, only one sputum positive patient had been detected and treated by the national program, though specific clinical consultation was conducted to identify any patients who have been diagnosed and treated for TB before. This may reflect the difference between the active case finding approach in the survey and the passive casing finding approach in practice. Nevertheless, it indicated that a large proportion of bacteriologically confirmed TB cases are missed by the national TB program.
Another notable change is the sharp decline of the proportion of sputum positive cases, which accounted for 30.5% of all cases in the 2000 survey but was reduced to 6.6% in the 2010 survey. The proportion of notified sputum cases out of all TB cases in Shandong also declined from 80.9% in 2005 to 64.6% in 2010 [19] .
The prevalence rate of bacteriologically confirmed cases has reduced by 80% in the last decade in Shandong, compared with a national decline of 45% (from 216/ 100,000 in 2000 to 119/ 100,000 in 2010) [4] . The rapid decline of TB prevalence rate of bacteriologically confirmed cases in the recent decade may be attributed to China's strengthened public health system following the outbreak of severe acute respiratory syndrome in 2003 [2] . Another reason may be due to improved reporting of TB cases in the online communicable disease reporting system, and the improved collaboration between public hospitals and TB dispensaries [20] . Other factors such as social economic development may also have played an important role in the reduction of TB prevalence, as found in a study of TB notification rates trends in 134 countries [21] .
The adjusted prevalence rate of bacteriologically confirmed cases in Shandong was lower than the WHO estimates for China in 2010 [1] . But the national prevalence rates of bacteriologically confirmed cases, 119/100,000 in 2010 [4] , was higher than the WHO estimate, 108/ 100,000, even the survey did not collect negative and extra-pulmonary TB cases. Vietnam reported similar findings in its 2006 survey [14] . One reason is that prevalence surveys results are based on active case finding while WHO estimates are based on notification rates from passive case finding. A re-evaluation of the reported TB prevalence in China is needed based on the recent survey.
CXRAY suggestive bacteriologically negative cases may be smear or culture negative TB cases if they had any TB symptoms, while some may be caused by suboptimal smear or culture. As reported in China's previous surveys [3, 22] , including these cases as TB cases may result in an over-estimate of all pulmonary cases [23] .
The survey revealed that over half of the TB patients were 65 years and older in Shandong, while the over 65's were more likely to present with abnormal CXRAY and persistent cough. Similar trends have been documented in other developed cities such as Hong Kong and Singapore [24] . These high rates may reflect the higher TB rates in the past and decline in immunity in the over 65's. How to treat elders with TB and other complications such as diabetes remains an ongoing challenge in China and similar settings.
The survey results can be generalized to the Shandong population of 94 million or similar international settings with middle income and middle TB prevalence levels. The patterns of the TB epidemic found in Shandong, i.e., the proportion of patients with symptoms, ratios between urban and rural areas, men and women, were similar to those found in the national survey [4] . However, the prevalence rates cannot be extrapolated to western provinces in China with a higher TB prevalence. For logistical reasons, the eligible population did not include adults staying in the sampled clusters less than 6 months, which was the same practice in the 2000 survey. However, shortterm migrants may have a potentially higher prevalence of TB than the general population [25] . This may result in a lower estimate of the true prevalence rate. The survey did not collect social-economic indicators, smoking status and HIV status of all participants, so comparisons between TB cases and all non-TB patients are not available. However, the HIV prevalence in Shandong China is below 0.01%, and would not significantly alter the TB prevalence rate. In addition, the survey did not evaluate child TB and extra pulmonary TB. Discussions of using CXRAY as a screening tool was on the technical aspect, but not on costing side as we did not conduct any cost effectiveness analysis or the social willingness to pay for such a strategy in similar settings.
This study has shown that the prevalence of bacteriologically confirmed TB in Shandong has reduced substantially over the last decade. Importantly, the majority of these cases did not present with persistent cough and the proportion of sputum positive cases has declined sharply. Further studies are recommended to assess the feasibility of adopting CXRAY in the existing health care services to detect TB cases and the cost effectiveness of such intervention.
The authors declare that they have no competing interests. | When was the study conducted? | false | 3,023 | {
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1,571 | Community-acquired pneumonia in children — a changing spectrum of disease
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5608782/
SHA: eecb946b106a94f26a79a964f0160e8e16f79f42
Authors: le Roux, David M.; Zar, Heather J.
Date: 2017-09-21
DOI: 10.1007/s00247-017-3827-8
License: cc-by
Abstract: Pneumonia remains the leading cause of death in children outside the neonatal period, despite advances in prevention and management. Over the last 20 years, there has been a substantial decrease in the incidence of childhood pneumonia and pneumonia-associated mortality. New conjugate vaccines against Haemophilus influenzae type b and Streptococcus pneumoniae have contributed to decreases in radiologic, clinical and complicated pneumonia cases and have reduced hospitalization and mortality. The importance of co-infections with multiple pathogens and the predominance of viral-associated disease are emerging. Better access to effective preventative and management strategies is needed in low- and middle-income countries, while new strategies are needed to address the residual burden of disease once these have been implemented.
Text: Pneumonia has been the leading cause of death in children younger than 5 years for decades. Although there have been substantial decreases in overall child mortality and in pneumonia-specific mortality, pneumonia remains the major single cause of death in children outside the neonatal period, causing approximately 900,000 of the estimated 6.3 million child deaths in 2013 [1] . Substantial advances have occurred in the understanding of risk factors and etiology of pneumonia, in development of standardized case definitions, and in prevention with the production of improved vaccines and in treatment. Such advances have led to changes in the epidemiology, etiology and mortality from childhood pneumonia. However in many areas access to these interventions remains sub-optimal, with large inequities between and within countries and regions. In this paper we review the impact of recent preventative and management advances in pneumonia epidemiology, etiology, radiologic presentation and outcome in children.
The overall burden of childhood pneumonia has been reduced substantially over the last decade, despite an increase in the global childhood population from 605 million in 2000 to 664 million in 2015 [2] . Recent data suggest that there has been a 25% decrease in the incidence of pneumonia, from 0.29 episodes per child year in low-and middle-income countries in 2000, to 0.22 episodes per child year in 2010 [3] . This is substantiated by a 58% decrease in pneumonia-associated disability-adjusted life years between 1990 and 2013, from 186 million to 78 million as estimated in the Global Burden of Disease study [1] . Pneumonia deaths decreased from 1.8 million in 2000 to 900,000 in 2013 [1] . These data do not reflect the full impact of increasingly widespread use of pneumococcal conjugate vaccine in low-and middle-income countries because the incidence of pneumonia and number of deaths are likely to decrease still further as a result of this widespread intervention [4] .
Notwithstanding this progress, there remains a disproportionate burden of disease in low-and middle-income countries, where more than 90% of pneumonia cases and deaths occur. The incidence in high-income countries is estimated at 0.015 episodes per child year, compared to 0.22 episodes per child year in low-and middle-income countries [3] . On average, 1 in 66 children in high-income countries is affected by pneumonia per year, compared to 1 in 5 children in low-and middle-income countries. Even within low-and middleincome countries there are regional inequities and challenges with access to health care services: up to 81% of severe pneumonia deaths occur outside a hospital [5] . In addition to a higher incidence of pneumonia, the case fatality rate is estimated to be almost 10-fold higher in low-and middle-income countries as compared to high-income countries [3, 5] .
Childhood pneumonia can also lead to significant morbidity and chronic disease. Early life pneumonia can impair longterm lung health by decreasing lung function [6] . Severe or recurrent pneumonia can have a worse effect on lung function; increasing evidence suggests that chronic obstructive pulmonary disease might be related to early childhood pneumonia [7, 8] . A meta-analysis of the risk of long-term outcomes after childhood pneumonia categorized chronic respiratory sequelae into major (restrictive lung disease, obstructive lung disease, bronchiectasis) and minor (chronic bronchitis, asthma, abnormal pulmonary function) groups [9] . The risk of developing at least one of the major sequelae was estimated as 6% after an ambulatory pneumonia event and 14% after an episode of hospitalized pneumonia. Because respiratory diseases affect almost 1 billion people globally and are a major cause of mortality and morbidity [10] , childhood pneumonia might contribute to substantial morbidity across the life course.
Chest radiologic changes have been considered the gold standard for defining a pneumonia event [11] because clinical findings can be subjective and clinical definitions of pneumonia can be nonspecific. In 2005, to aid in defining outcomes of pneumococcal vaccine studies, the World Health Organization's (WHO) standardized chest radiograph description defined a group of children who were considered most likely to have pneumococcal pneumonia [12] . The term "end-point consolidation" was described as a dense or fluffy opacity that occupies a portion or whole of a lobe, or the entire lung. "Other infiltrate" included linear and patchy densities, peribronchial thickening, minor patchy infiltrates that are not of sufficient magnitude to constitute primary end-point consolidation, and small areas of atelectasis that in children can be difficult to distinguish from consolidation. "Primary end-point pneumonia" included either end-point consolidation or a pleural effusion associated with a pulmonary parenchymal infiltrate (including "other" infiltrate).
Widespread use of pneumococcal conjugate vaccination and Haemophilus influenzae type B conjugate vaccination has decreased the incidence of radiologic pneumonia. In a review of four randomized controlled trials and two case-control studies of Haemophilus influenzae type B conjugate vaccination in high-burden communities, the vaccination was associated with an 18% decrease in radiologic pneumonia [13] . Introduction of pneumococcal conjugate vaccination was associated with a 26% decrease in radiologic pneumonia in California between 1995 and 1998 [14] . In vaccine efficacy trials in low-and middle-income countries, pneumococcal conjugate vaccination reduced radiologic pneumonia by 37% in the Gambia [15] , 25% in South Africa [16] and 26% in the Philippines [17] .
The WHO radiologic case definition was not intended to distinguish bacterial from viral etiology but rather to define a sub-set of pneumonia cases in which pneumococcal infection was considered more likely and to provide a set of standardized definitions through which researchers could achieve broad agreement in reporting chest radiographs. However, despite widespread field utilization, there are concerns regarding inter-observer repeatability. There has been good consensus for the description of lobar consolidation but significant disagreement on the description of patchy and perihilar infiltrates [18, 19] . In addition, many children with clinically severe lung disease do not have primary end-point pneumonia: in one pre-pneumococcal conjugate vaccination study, only 34% of children hospitalized with pneumonia had primary end-point pneumonia [20] . A revised case definition of "presumed bacterial pneumonia" has been introduced, and this definition includes pneumonia cases with WHO-defined alveolar consolidation, as well as those with other abnormal chest radiograph infiltrates and a serum C-reactive protein of at least 40 mg/L [21, 22] . This definition has been shown to have greater sensitivity than the original WHO radiologic definition of primary end-point pneumonia for detecting the burden of pneumonia prevented by pneumococcal conjugate vaccination [23] . Using the revised definition, the 10-valent pneumococcal conjugate vaccine (pneumococcal conjugate vaccination-10), had a vaccine efficacy of 22% in preventing presumed bacterial pneumonia in young children in South America [22] , and pneumococcal conjugate vaccination-13 had a vaccine efficacy of 39% in preventing presumed bacterial pneumonia in children older than 16 weeks who were not infected with human immunodeficiency virus (HIV) in South Africa [21] . Thus there is convincing evidence that pneumococcal conjugate vaccination decreases the incidence of radiologic pneumonia; however there is no evidence to suggest that pneumococcal conjugate vaccination modifies the radiologic appearance of pneumococcal pneumonia.
Empyema is a rare complication of pneumonia. An increased incidence of empyema in children was noted in some high-income countries following pneumococcal conjugate vaccination-7 introduction, and this was attributed to pneumococcal serotypes not included in pneumococcal conjugate vaccination-7, especially 3 and 19A [24] . In the United States, evidence from a national hospital database suggests that the incidence of empyema increased 1.9-fold between 1996 and 2008 [25] . In Australia, the incidence rate ratio increased by 1.4 times when comparing the pre-pneumococcal conjugate vaccination-7 period (1998 to 2004) to the post-pneumococcal conjugate vaccination-7 period (2005 to 2010) [26] . In Scotland, incidence of empyema in children rose from 6.5 per million between 1981 and 1998, to 66 per million in 2005 [27] . These trends have been reversed since the introduction of pneumococcal conjugate vaccination-13. Data from the United States suggest that empyema decreased by 50% in children younger than 5 years [28] ; similarly, data from the United Kingdom and Scotland showed substantial reduction in pediatric empyema following pneumococcal conjugate vaccination-13 introduction [29, 30] .
Several national guidelines from high-income countries, as well as the WHO recommendations for low-and middleincome countries, recommend that chest radiography should not be routinely performed in children with ambulatory pneumonia [31] [32] [33] . Indications for chest radiography include hospitalization, severe hypoxemia or respiratory distress, failed initial antibiotic therapy, or suspicion for other diseases (tuberculosis, inhaled foreign body) or complications. However, point-of-care lung ultrasound is emerging as a promising modality for diagnosing childhood pneumonia [34] .
In addition to the effect on radiologic pneumonia, pneumococcal conjugate vaccination reduces the risk of hospitalization from viral-associated pneumonia, probably by reducing bacterial-viral co-infections resulting in severe disease and hospitalization [35] . An analysis of ecological and observational studies of pneumonia incidence in different age groups soon after introduction of pneumococcal conjugate vaccination-7 in Canada, Italy, Australia, Poland and the United States showed decreases in all-cause pneumonia hospitalizations ranging from 15% to 65% [36] . In the United States after pneumococcal conjugate vaccination-13 replaced pneumococcal conjugate vaccination-7, there was a further 17% decrease in hospitalizations for pneumonia among children eligible for the vaccination, and a further 12% decrease among unvaccinated adults [28] .
A systematic review of etiology studies prior to availability of new conjugate vaccines confirmed S. pneumoniae and H. influenzae type B as the most important bacterial causes of pneumonia, with Staphylococcus aureus and Klebsiella pneumoniae associated with some severe cases. Respiratory syncytial virus was the leading viral cause, identified in 15-40% of pneumonia cases, followed by influenza A and B, parainfluenza, human metapneumovirus and adenovirus [37] .
More recent meta-analyses of etiology data suggest a changing pathogen profile, with increasing recognition that clinical pneumonia is caused by the sequential or concurrent interaction of more than one organism. Severe disease in particular is often caused by multiple pathogens. With high coverage of pneumococcal conjugate vaccination and Haemophilus influenzae type B conjugate vaccination, viral pathogens increasingly predominate [38] . In recent case-control studies, at least one virus was detected in 87% of clinical pneumonia cases in South Africa [39] , while viruses were detected in 81% of radiologic pneumonia cases in Sweden [40] . In a large multi-center study in the United States, viral pathogens were detected in 73% of children hospitalized with radiologic pneumonia, while bacteria were detected in only 15% of cases [41] . A meta-analysis of 23 case-control studies of viral etiology in radiologically confirmed pneumonia in children, completed up to 2014, reported good evidence of causal attribution for respiratory syncytial virus, influenza, metapneumovirus and parainfluenza virus [42] . However there was no consistent evidence that many other commonly described viruses, including rhinovirus, adenovirus, bocavirus and coronavirus, were more commonly isolated from cases than from controls. Further attribution of bacterial etiology is difficult because it is often not possible to distinguish colonizing from pathogenic bacteria when they are isolated from nasal specimens [43] .
Another etiology is pertussis. In the last decade there has also been a resurgence in pertussis cases, especially in highincome countries [44] . Because pertussis immunity after acellular pertussis vaccination is less long-lasting than immunity after wild-type infection or whole-cell vaccination, many women of child-bearing age have waning pertussis antibody levels. Their infants might therefore be born with low transplacental anti-pertussis immunoglobulin G levels, making them susceptible to pertussis infection before completion of the primary vaccination series [45] . In 2014, more than 40,000 pertussis cases were reported to the Centers for Disease Control and Prevention in the United States; in some states, population-based incidence rates are higher than at any time in the last 70 years [44] . In contrast, most low-and middleincome countries use whole-cell pertussis vaccines and the numbers of pertussis cases in those countries were stable or decreasing until 2015 [46] . However recent evidence from South Africa (where the acellular vaccine is used) shows an appreciable incidence of pertussis among infants presenting with acute pneumonia: 2% of clinical pneumonia cases among infants enrolled in a birth cohort were caused by pertussis [39] , and 3.7% of infants and young children presenting to a tertiary academic hospital had evidence of pertussis infection [47] .
Similarly, childhood tuberculosis is a major cause of morbidity and mortality in many low-and middle-income countries, and Mycobacterium tuberculosis has increasingly been recognized as a pathogen in acute pneumonia in children living in high tuberculosis-prevalence settings. Postmortem studies of children dying from acute respiratory illness have commonly reported M. tuberculosis [48, 49] . A recent systematic review of tuberculosis as a comorbidity of childhood pneumonia reported culture-confirmed disease in about 8% of cases [50] . Because intrathoracic tuberculosis disease is only culture-confirmed in a minority of cases, the true burden could be even higher; tuberculosis could therefore be an important contributor to childhood pneumonia incidence and mortality in high-prevalence areas.
Childhood pneumonia and clinically severe disease result from a complex interaction of host and environmental risk factors [37] . Because of the effectiveness of pneumococcal conjugate vaccination and Haemophilus influenzae type B conjugate vaccination for prevention of radiologic and clinical pneumonia, incomplete or inadequate vaccination must be considered as a major preventable risk factor for childhood pneumonia. Other risk factors include low birth weight, which is associated with 3.2 times increased odds of severe pneumonia in low-and middle-income countries, and 1.8 times increased odds in high-income countries [51] . Similarly, lack of exclusive breastfeeding for the first 4 months of life increases odds of severe pneumonia by 2.7 times in low-and middle-income countries and 1.3 times in highincome countries. Markers of undernutrition are strong risk factors for pneumonia in low-and middle-income countries only, with highly significant odds ratios for underweight for age (4.5), stunting (2.6) and wasting (2.8) . Household crowding has uniform risk, with odds ratios between 1.9 and 2.3 in both low-and middle-income countries and high-income countries. Indoor air pollution from use of solid or biomass fuels increases odds of pneumonia by 1.6 times; lack of measles vaccination by the end of the first year of age increases odds of pneumonia by 1.8 times [51] . It is estimated that the prevalence of these critical risk factors in low-and middle-income countries decreased by 25% between 2000 and 2010, contributing to reductions in pneumonia incidence and mortality in low-and middle-income countries, even in countries where conjugate vaccines have not been available [3] .
The single strongest risk factor for pneumonia is HIV infection, which is especially prevalent in children in sub-Saharan Africa. HIV-infected children have 6 times increased odds of developing severe pneumonia or of death compared to HIV-uninfected children [52] . Since the effective prevention of mother-to-child transmission of HIV, there is a growing population of HIV-exposed children who are uninfected; their excess risk of pneumonia, compared to HIV unexposed children, has been described as 1.3-to 3.4-fold higher [53] [54] [55] [56] [57] .
The pneumococcal conjugate vaccination and Haemophilus influenzae type B conjugate vaccination have been effective tools to decrease pneumonia incidence, severity and mortality [58, 59] . However, equitable coverage and access to vaccines remains sub-optimal. By the end of 2015, Haemophilus influenzae type B conjugate vaccination had been introduced in 73 countries, with global coverage estimated at 68%. However, inequities are still apparent among regions: in the Americas coverage is estimated at 90%, while in the Western Pacific it is only 25%. By 2015, pneumococcal conjugate vaccination had been introduced into 54 countries, with global coverage of 35% for three doses of pneumococcal conjugate vaccination for infant populations [60] . To address this issue, the WHO's Global Vaccine Access Plan initiative was launched to make life-saving vaccines more equitably available. In addition to securing guarantees for financing of vaccines, the program objectives include building political will in low-and middle-income countries to commit to immunization as a priority, social marketing to individuals and communities, strengthening health systems and promoting relevant local research and development innovations [61] .
Maternal vaccination to prevent disease in the youngest infants has been shown to be effective for tetanus, influenza and pertussis [62] . Influenza vaccination during pregnancy is safe, provides reasonable maternal protection against influenza, and also protects infants for a limited period from confirmed influenza infection (vaccine efficacy 63% in Bangladesh [63] and 50.4% in South Africa [64] ). However as antibody levels drop sharply after birth, infant protection does not persist much beyond 8 weeks [65] . Recently respiratory syncytial virus vaccination in pregnancy has been shown to be safe and immunogenic, and a phase-3 clinical trial of efficacy at preventing respiratory syncytial virus disease in infants is under way [66] . Within a decade, respiratory syncytial virus in infancy might be vaccine-preventable, with further decreases in pneumonia incidence, morbidity and mortality [67] .
Improved access to health care, better nutrition and improved living conditions might contribute to further decreases in childhood pneumonia burden. The WHO Integrated Global Action Plan for diarrhea and pneumonia highlights many opportunities to protect, prevent and treat children [68] . Breastfeeding rates can be improved by programs that combine education and counseling interventions in homes, communities and health facilities, and by promotion of baby-friendly hospitals [69] . Improved home ventilation, cleaner cooking fuels and reduction in exposure to cigarette smoke are essential interventions to reduce the incidence and severity of pneumonia [70, 71] . Prevention of pediatric HIV is possible by providing interventions to prevent mother-to-child transmission [72] . Early infant HIV testing and early initiation of antiretroviral therapy and cotrimoxazole prophylaxis can substantially reduce the incidence of community-acquired pneumonia among HIV-infected children [73] . Community-based interventions reduce pneumonia mortality and have the indirect effect of improved-careseeking behavior [58] . If these cost-effective interventions were scaled up, it is estimated that 67% of pneumonia deaths in lowand middle-income countries could be prevented by 2025 [58] .
Case management of pneumonia is a strategy by which severity of disease is classified as severe or non-severe. All children receive early, appropriate oral antibiotics, and severe cases are referred for parenteral antibiotics. When implemented in highburden areas before the availability of conjugate vaccines, case management as part of Integrated Management of Childhood Illness was associated with a 27% decrease in overall child mortality, and 42% decrease in pneumonia-specific mortality [74] . However the predominance of viral causes of pneumonia and low case fatality have prompted concern about overuse of antibiotics. Several randomized controlled trials comparing oral antibiotics to placebo for non-severe pneumonia have been performed [75] [76] [77] and others are ongoing [78] . In two studies, performed in Denmark and in India, outcomes of antibiotic and placebo treatments were equivalent [76, 77] . In the third study, in Pakistan, there was a non-significant 24% vs. 20% rate of failure in the placebo group, which was deemed to be non-equivalent to the antibiotic group [75] . Furthermore, because WHO-classified non-severe pneumonia and bronchiolitis might be considered within a spectrum of lower respiratory disease, many children with clinical pneumonia could actually have viral bronchiolitis, for which antibiotics are not beneficial [79] . This has been reflected in British [33] and Spanish [31] national pneumonia guidelines, which do not recommend routine antibiotic treatment for children younger than 2 years with evidence of pneumococcal conjugate vaccination who present with non-severe pneumonia. The United States' national guidelines recommend withholding antibiotics in children up to age 5 years presenting with non-severe pneumonia [32] . However, given the high mortality from pneumonia in low-and middle-income countries, the lack of easy access to care, and the high prevalence of risk factors for severe disease, revised World Health Organization pneumonia guidelines still recommend antibiotic treatment for all children who meet the WHO pneumonia case definitions [80] .
Use of supplemental oxygen is life-saving, but this is not universally available in low-and middle-income countries; it is estimated that use of supplemental oxygen systems could reduce mortality of children with hypoxic pneumonia by 20% [81] . Identifying systems capacity to increase availability of oxygen in health facilities, and identifying barriers to further implementation are among the top 15 priorities for future childhood pneumonia research [82] . However, up to 81% of pneumonia deaths in 2010 occurred outside health facilities [5] , so there are major challenges with access to health services and health-seeking behavior of vulnerable populations. Identifying and changing the barriers to accessing health care is an important area with the potential to impact the survival and health of the most vulnerable children [82] .
Much progress has been made in decreasing deaths caused by childhood pneumonia. Improved socioeconomic status and vaccinations, primarily the conjugate vaccines (against Haemophilus influenzae and pneumococcus), have led to substantial reductions in the incidence and severity of childhood pneumonia. Stronger strategies to prevent and manage HIV have reduced HIV-associated pneumonia deaths. However, despite the substantial changes in incidence, etiology and radiology globally, there remain inequities in access to care and availability of effective interventions, especially in low-and middle-income countries. Effective interventions need to be more widely available and new interventions developed for the residual burden of childhood pneumonia. | How has the childhood population grown in the last two decades? | false | 510 | {
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1,698 | Accelerated viral dynamics in bat cell lines, with implications for zoonotic emergence
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7064339/
SHA: f2cc0d63ff2c4aaa127c4caae21d8f3a0067e3d5
Authors: Brook, Cara E; Boots, Mike; Chandran, Kartik; Dobson, Andrew P; Drosten, Christian; Graham, Andrea L; Grenfell, Bryan T; Müller, Marcel A; Ng, Melinda; Wang, Lin-Fa; van Leeuwen, Anieke
Date: 2020-02-03
DOI: 10.7554/elife.48401
License: cc-by
Abstract: Bats host virulent zoonotic viruses without experiencing disease. A mechanistic understanding of the impact of bats’ virus hosting capacities, including uniquely constitutive immune pathways, on cellular-scale viral dynamics is needed to elucidate zoonotic emergence. We carried out virus infectivity assays on bat cell lines expressing induced and constitutive immune phenotypes, then developed a theoretical model of our in vitro system, which we fit to empirical data. Best fit models recapitulated expected immune phenotypes for representative cell lines, supporting robust antiviral defenses in bat cells that correlated with higher estimates for within-host viral propagation rates. In general, heightened immune responses limit pathogen-induced cellular morbidity, which can facilitate the establishment of rapidly-propagating persistent infections within-host. Rapidly-transmitting viruses that have evolved with bat immune systems will likely cause enhanced virulence following emergence into secondary hosts with immune systems that diverge from those unique to bats.
Text: Bats have received much attention in recent years for their role as reservoir hosts for emerging viral zoonoses, including rabies and related lyssaviruses, Hendra and Nipah henipaviruses, Ebola and Marburg filoviruses, and SARS coronavirus (Calisher et al., 2006; Wang and Anderson, 2019) . In most non-Chiropteran mammals, henipaviruses, filoviruses, and coronaviruses induce substantial morbidity and mortality, display short durations of infection, and elicit robust, long-term immunity in hosts surviving infection (Nicholls et al., 2003; Hooper et al., 2001; Mahanty and Bray, 2004) . Bats, by contrast, demonstrate no obvious disease symptoms upon infection with pathogens that are highly virulent in non-volant mammals (Schountz et al., 2017) but may, instead, support viruses as longterm persistent infections, rather than transient, immunizing pathologies (Plowright et al., 2016) .
Recent research advances are beginning to shed light on the molecular mechanisms by which bats avoid pathology from these otherwise virulent pathogens (Brook and Dobson, 2015) . Bats leverage a suite of species-specific mechanisms to limit viral load, which include host receptor sequence incompatibilities for some bat-virus combinations (Ng et al., 2015; Takadate et al., 2020) and constitutive expression of the antiviral cytokine, IFN-a, for others (Zhou et al., 2016) . Typically, the presence of viral RNA or DNA in the cytoplasm of mammalian cells will induce secretion of type I interferon proteins (IFN-a and IFN-b), which promote expression and translation of interferon-stimulated genes (ISGs) in neighboring cells and render them effectively antiviral (Stetson and Medzhitov, 2006) . In some bat cells, the transcriptomic blueprints for this IFN response are expressed constitutively, even in the absence of stimulation by viral RNA or DNA (Zhou et al., 2016) . In non-flying mammals, constitutive IFN expression would likely elicit widespread inflammation and concomitant immunopathology upon viral infection, but bats support unique adaptations to combat inflammation (Zhang et al., 2013; Ahn et al., 2019; Xie et al., 2018; Pavlovich et al., 2018) that may have evolved to mitigate metabolic damage induced during flight (Kacprzyk et al., 2017) . The extent to which constitutive IFN-a expression signifies constitutive antiviral defense in the form of functional IFN-a protein remains unresolved. In bat cells constitutively expressing IFN-a, some protein-stimulated, downstream ISGs appear to be also constitutively expressed, but additional ISG induction is nonetheless possible following viral challenge and stimulation of IFN-b (Zhou et al., 2016; Xie et al., 2018) . Despite recent advances in molecular understanding of bat viral tolerance, the consequences of this unique bat immunity on within-host virus dynamics-and its implications for understanding zoonotic emergence-have yet to be elucidated.
The field of 'virus dynamics' was first developed to describe the mechanistic underpinnings of long-term patterns of steady-state viral load exhibited by patients in chronic phase infections with HIV, who appeared to produce and clear virus at equivalent rates (Nowak and May, 2000; Ho et al., 1995) . Models of simple target cell depletion, in which viral load is dictated by a bottom-eLife digest Bats can carry viruses that are deadly to other mammals without themselves showing serious symptoms. In fact, bats are natural reservoirs for viruses that have some of the highest fatality rates of any viruses that people acquire from wild animals -including rabies, Ebola and the SARS coronavirus.
Bats have a suite of antiviral defenses that keep the amount of virus in check. For example, some bats have an antiviral immune response called the interferon pathway perpetually switched on. In most other mammals, having such a hyper-vigilant immune response would cause harmful inflammation. Bats, however, have adapted anti-inflammatory traits that protect them from such harm, include the loss of certain genes that normally promote inflammation. However, no one has previously explored how these unique antiviral defenses of bats impact the viruses themselves. Now, Brook et al. have studied this exact question using bat cells grown in the laboratory. The experiments made use of cells from one bat species -the black flying fox -in which the interferon pathway is always on, and another -the Egyptian fruit bat -in which this pathway is only activated during an infection. The bat cells were infected with three different viruses, and then Brook et al. observed how the interferon pathway helped keep the infections in check, before creating a computer model of this response. The experiments and model helped reveal that the bats' defenses may have a potential downside for other animals, including humans. In both bat species, the strongest antiviral responses were countered by the virus spreading more quickly from cell to cell. This suggests that bat immune defenses may drive the evolution of faster transmitting viruses, and while bats are well protected from the harmful effects of their own prolific viruses, other creatures like humans are not.
The findings may help to explain why bats are often the source for viruses that are deadly in humans. Learning more about bats' antiviral defenses and how they drive virus evolution may help scientists develop better ways to predict, prevent or limit the spread of viruses from bats to humans. More studies are needed in bats to help these efforts. In the meantime, the experiments highlight the importance of warning people to avoid direct contact with wild bats. up resource supply of infection-susceptible host cells, were first developed for HIV (Perelson, 2002) but have since been applied to other chronic infections, including hepatitis-C virus (Neumann et al., 1998) , hepatitis-B virus (Nowak et al., 1996) and cytomegalovirus (Emery et al., 1999) . Recent work has adopted similar techniques to model the within-host dynamics of acute infections, such as influenza A and measles, inspiring debate over the extent to which explicit modeling of top-down immune control can improve inference beyond the basic resource limitation assumptions of the target cell model (Baccam et al., 2006; Pawelek et al., 2012; Saenz et al., 2010; Morris et al., 2018) .
To investigate the impact of unique bat immune processes on in vitro viral kinetics, we first undertook a series of virus infection experiments on bat cell lines expressing divergent interferon phenotypes, then developed a theoretical model elucidating the dynamics of within-host viral spread. We evaluated our theoretical model analytically independent of the data, then fit the model to data recovered from in vitro experimental trials in order to estimate rates of within-host virus transmission and cellular progression to antiviral status under diverse assumptions of absent, induced, and constitutive immunity. Finally, we confirmed our findings in spatially-explicit stochastic simulations of fitted time series from our mean field model. We hypothesized that top-down immune processes would overrule classical resource-limitation in bat cell lines described as constitutively antiviral in the literature, offering a testable prediction for models fit to empirical data. We further predicted that the most robust antiviral responses would be associated with the most rapid within-host virus propagation rates but also protect cells against virus-induced mortality to support the longest enduring infections in tissue culture.
We first explored the influence of innate immune phenotype on within-host viral propagation in a series of infection experiments in cell culture. We conducted plaque assays on six-well plate monolayers of three immortalized mammalian kidney cell lines: [1] Vero (African green monkey) cells, which are IFN-defective and thus limited in antiviral capacity (Desmyter et al., 1968) ; [2] RoNi/7.1 (Rousettus aegyptiacus) cells which demonstrate idiosyncratic induced interferon responses upon viral challenge (Kuzmin et al., 2017; Arnold et al., 2018; Biesold et al., 2011; Pavlovich et al., 2018) ; and [3] PaKiT01 (Pteropus alecto) cells which constitutively express IFN-a (Zhou et al., 2016; Crameri et al., 2009) . To intensify cell line-specific differences in constitutive immunity, we carried out infectivity assays with GFP-tagged, replication-competent vesicular stomatitis Indiana viruses: rVSV-G, rVSV-EBOV, and rVSV-MARV, which have been previously described (Miller et al., 2012; Wong et al., 2010) . Two of these viruses, rVSV-EBOV and rVSV-MARV, are recombinants for which cell entry is mediated by the glycoprotein of the bat-evolved filoviruses, Ebola (EBOV) and Marburg (MARV), thus allowing us to modulate the extent of structural, as well as immunological, antiviral defense at play in each infection. Previous work in this lab has demonstrated incompatibilities in the NPC1 filovirus receptor which render PaKiT01 cells refractory to infection with rVSV-MARV (Ng and Chandrab, 2018, Unpublished results) , making them structurally antiviral, over and above their constitutive expression of IFN-a. All three cell lines were challenged with all three viruses at two multiplicities of infection (MOI): 0.001 and 0.0001. Between 18 and 39 trials were run at each cell-virus-MOI combination, excepting rVSV-MARV infections on PaKiT01 cells at MOI = 0.001, for which only eight trials were run (see Materials and methods; Figure 1 -figure supplements 1-3, Supplementary file 1).
Because plaque assays restrict viral transmission neighbor-to-neighbor in two-dimensional cellular space (Howat et al., 2006) , we were able to track the spread of GFP-expressing virus-infected cells across tissue monolayers via inverted fluorescence microscopy. For each infection trial, we monitored and re-imaged plates for up to 200 hr of observations or until total monolayer destruction, processed resulting images, and generated a time series of the proportion of infectious-cell occupied plate space across the duration of each trial (see Materials and methods). We used generalized additive models to infer the time course of all cell culture replicates and construct the multi-trial dataset to which we eventually fit our mechanistic transmission model for each cell line-virus-specific combination ( Figure 1; Figure 1 -figure supplements 1-5).
All three recombinant vesicular stomatitis viruses (rVSV-G, rVSV-EBOV, and rVSV-MARV) infected Vero, RoNi/7.1, and PaKiT01 tissue cultures at both focal MOIs. Post-invasion, virus spread rapidly across most cell monolayers, resulting in virus-induced epidemic extinction. Epidemics were less severe in bat cell cultures, especially when infected with the recombinant filoviruses, rVSV-EBOV and rVSV-MARV. Monolayer destruction was avoided in the case of rVSV-EBOV and rVSV-MARV infections on PaKiT01 cells: in the former, persistent viral infection was maintained throughout the 200 hr duration of each experiment, while, in the latter, infection was eliminated early in the time series, preserving a large proportion of live, uninfectious cells across the duration of the experiment. We assumed this pattern to be the result of immune-mediated epidemic extinction (Figure 1) . Patterns from MOI = 0.001 were largely recapitulated at MOI = 0.0001, though at somewhat reduced total proportions (Figure 1-figure supplement 5 ).
A theoretical model fit to in vitro data recapitulates expected immune phenotypes for bat cells We next developed a within-host model to fit to these data to elucidate the effects of induced and constitutive immunity on the dynamics of viral spread in host tissue ( Figure 1 ). The compartmental within-host system mimicked our two-dimensional cell culture monolayer, with cells occupying five distinct infection states: susceptible (S), antiviral (A), exposed (E), infectious (I), and dead (D). We modeled exposed cells as infected but not yet infectious, capturing the 'eclipse phase' of viral integration into a host cell which precedes viral replication. Antiviral cells were immune to viral infection, in accordance with the 'antiviral state' induced from interferon stimulation of ISGs in tissues adjacent to infection (Stetson and Medzhitov, 2006) . Because we aimed to translate available data into modeled processes, we did not explicitly model interferon dynamics but instead scaled the rate of cell progression from susceptible to antiviral (r) by the proportion of exposed cells (globally) in the system. In systems permitting constitutive immunity, a second rate of cellular acquisition of antiviral status (") additionally scaled with the global proportion of susceptible cells in the model. Compared with virus, IFN particles are small and highly diffusive, justifying this global signaling assumption at the limited spatial extent of a six-well plate and maintaining consistency with previous modeling approximations of IFN signaling in plaque assay (Howat et al., 2006) .
To best represent our empirical monolayer system, we expressed our state variables as proportions (P S , P A , P E , P I , and P D ), under assumptions of frequency-dependent transmission in a wellmixed population (Keeling and Rohani, 2008) , though note that the inclusion of P D (representing the proportion of dead space in the modeled tissue) had the functional effect of varying transmission with infectious cell density. This resulted in the following system of ordinary differential equations:
We defined 'induced immunity' as complete, modeling all cells as susceptible to viral invasion at disease-free equilibrium, with defenses induced subsequent to viral exposure through the term r. By contrast, we allowed the extent of constitutive immunity to vary across the parameter range of " > 0, defining a 'constitutive' system as one containing any antiviral cells at disease-free equilibrium. In fitting this model to tissue culture data, we independently estimated both r and "; as well as the cell-to-cell transmission rate, b, for each cell-virus combination. Since the extent to which constitutively-expressed IFN-a is constitutively translated into functional protein is not yet known for bat hosts (Zhou et al., 2016) , this approach permitted our tissue culture data to drive modeling inference: even in PaKiT01 cell lines known to constitutively express IFN-a, the true constitutive extent of the system (i.e. the quantity of antiviral cells present at disease-free equilibrium) was allowed to vary through estimation of ": For the purposes of model-fitting, we fixed the value of c, the return rate of antiviral cells to susceptible status, at 0. The small spatial scale and short time course (max 200 hours) of our experiments likely prohibited any return of antiviral cells to susceptible status in our empirical system; nonetheless, we retained the term c in analytical evaluations of our model because regression from antiviral to susceptible status is possible over long time periods in vitro and at the scale of a complete organism (Radke et al., 1974; Rasmussen and Farley, 1975; Samuel and Knutson, 1982) .
Before fitting to empirical time series, we undertook bifurcation analysis of our theoretical model and generated testable hypotheses on the basis of model outcomes. From our within-host model system (Equation 1-5), we derived the following expression for R 0 , the pathogen basic reproduction number (Supplementary file 2):
Pathogens can invade a host tissue culture when R 0 >1. Rapid rates of constitutive antiviral acquisition (") will drive R 0 <1: tissue cultures with highly constitutive antiviral immunity will be therefore resistant to virus invasion from the outset. Since, by definition, induced immunity is stimulated following initial virus invasion, the rate of induced antiviral acquisition (r) is not incorporated into the equation for R 0 ; while induced immune processes can control virus after initial invasion, they cannot prevent it from occurring to begin with. In cases of fully induced or absent immunity (" ¼ 0), the R 0 equation thus reduces to a form typical of the classic SEIR model:
At equilibrium, the theoretical, mean field model demonstrates one of three infection states: endemic equilibrium, stable limit cycles, or no infection ( Figure 2) . Respectively, these states approximate the persistent infection, virus-induced epidemic extinction, and immune-mediated epidemic extinction phenotypes previously witnessed in tissue culture experiments ( Figure 1 ). Theoretically, endemic equilibrium is maintained when new infections are generated at the same rate at which infections are lost, while limit cycles represent parameter space under which infectious and susceptible populations are locked in predictable oscillations. Endemic equilibria resulting from cellular regeneration (i.e. births) have been described in vivo for HIV (Coffin, 1995) and in vitro for herpesvirus plaque assays (Howat et al., 2006) , but, because they so closely approach zero, true limit cycles likely only occur theoretically, instead yielding stochastic extinctions in empirical time series.
Bifurcation analysis of our mean field model revealed that regions of no infection (pathogen extinction) were bounded at lower threshold (Branch point) values for b, below which the pathogen was unable to invade. We found no upper threshold to invasion for b under any circumstances (i.e. b high enough to drive pathogen-induced extinction), but high b values resulted in Hopf bifurcations, which delineate regions of parameter space characterized by limit cycles. Since limit cycles so closely approach zero, high bs recovered in this range would likely produce virus-induced epidemic extinctions under experimental conditions. Under more robust representations of immunity, with higher values for either or both induced (r) and constitutive (") rates of antiviral acquisition, Hopf bifurcations occurred at increasingly higher values for b, meaning that persistent infections could establish at higher viral transmission rates ( Figure 2 ). Consistent with our derivation for R 0 , we found that the Branch point threshold for viral invasion was independent of changes to the induced immune parameter (r) but saturated at high values of " that characterize highly constitutive immunity ( Figure 3) .
We next fit our theoretical model by least squares to each cell line-virus combination, under absent, induced, and constitutive assumptions of immunity. In general, best fit models recapitulated expected outcomes based on the immune phenotype of the cell line in question, as described in the general literature (Table 1 Ironically, the induced immune model offered a slightly better fit than the constitutive to rVSV-MARV infections on the PaKiT01 cell line (the one cell line-virus combination for which we know a constitutively antiviral cell-receptor incompatibility to be at play). Because constitutive immune assumptions can prohibit pathogen invasion (R 0 <1), model fits to this time series under constitutive assumptions were handicapped by overestimations of ", which prohibited pathogen invasion. Only by incorporating an exceedingly rapid rate of induced antiviral acquisition could the model guarantee that initial infection would be permitted and then rapidly controlled. In all panel (A) plots, the rate of induced immune antiviral acquisition (r) was fixed at 0.01. Panel (B) depicts dynamics under variably induced immunity, ranging from absent (left: r=0) to high (right: r=1). In all panel (B) plots, the rate of constitutive antiviral acquisition (") was fixed at 0.0001 Branch point curves are represented as solid lines and Hopf curves as dashed lines. White space indicates endemic equilibrium (persistence), gray space indicates limit cycles, and black space indicates no infection (extinction). Other parameter values for equilibrium analysis were fixed at: b = .025, m = .001, s = 1/6, c = 0. Special points from bifurcations analyses are listed in Supplementary file 3.
In fitting our theoretical model to in vitro data, we estimated the within-host virus transmission rate (b) and the rate(s) of cellular acquisition to antiviral status (r or r + ") ( Table 1 ; Supplementary file 4). Under absent immune assumptions, r and " were fixed at 0 while b was estimated; under induced immune assumptions, " was fixed at 0 while r and b were estimated; and under constitutive immune assumptions, all three parameters (r, ", and b) were simultaneously estimated for each cell-virus combination. Best fit parameter estimates for MOI=0.001 data are visualized in conjunction with br and b -" bifurcations in (r) and (B) the constitutive immunity rate of antiviral acquisition ("). Panels show variation in the extent of immunity, from absent (left) to high (right). Branch point curves are represented as solid lines and Hopf curves as dashed lines. White space indicates endemic equilibrium (persistence), gray space indicates limit cycling, and black space indicates no infection (extinction). Other parameter values for equilibrium analysis were fixed at: b = .025, m = .001, s = 1/6, a = 1/6, c = 0. Special points from bifurcations analyses are listed in Supplementary file 3. space corresponding to theoretical limit cycles, consistent with observed virus-induced epidemic extinctions in stochastic tissue cultures.
In contrast to Vero cells, the induced immunity model offered the best fit to all RoNi/7.1 data, consistent with reported patterns in the literature and our own validation by qPCR ( Table 1; Arnold et al., 2018; Kuzmin et al., 2017; Biesold et al., 2011; Pavlovich et al., 2018) . As in Vero cell trials, we estimated highest b values for rVSV-G infections on RoNi/7.1 cell lines but here recovered higher b estimates for rVSV-MARV than for rVSV-EBOV. This reversal was balanced by a higher estimated rate of acquisition to antiviral status (r) for rVSV-EBOV versus rVSV-MARV. In general, we observed that more rapid rates of antiviral acquisition (either induced, r, constitutive, ", or both) correlated with higher transmission rates (b). When offset by r, b values estimated for RoNi/7.1 infections maintained the same amplitude as those estimated for immune-absent Vero cell lines but caused gentler epidemics and reduced cellular mortality (Figure 1) . RoNi/7.1 parameter estimates localized in the region corresponding to endemic equilibrium for the deterministic, theoretical model (Figure 4) , yielding less acute epidemics which nonetheless went extinct in stochastic experiments.
Finally, rVSV-G and rVSV-EBOV trials on PaKiT01 cells were best fit by models assuming constitutive immunity, while rVSV-MARV infections on PaKiT01 were matched equivalently by models assuming either induced or constitutive immunity-with induced models favored over constitutive in AIC comparisons because one fewer parameter was estimated (Figure 1-figure supplements 4-5; Supplementary file 4). For all virus infections, PaKiT01 cell lines yielded b estimates a full order of magnitude higher than Vero or RoNi/7.1 cells, with each b balanced by an immune response (either r, or r combined with ") also an order of magnitude higher than that recovered for the other cell lines ( Figure 4 ; Table 1 ). As in RoNi/7.1 cells, PaKiT01 parameter fits localized in the region corresponding to endemic equilibrium for the deterministic theoretical model. Because constitutive immune processes can actually prohibit initial pathogen invasion, constitutive immune fits to rVSV-MARV infections on PaKiT01 cell lines consistently localized at or below the Branch point threshold for virus invasion (R 0 ¼ 1). During model fitting for optimization of ", any parameter tests of " values producing R 0 <1 resulted in no infection and, consequently, produced an exceedingly poor fit to infectious time series data. In all model fits assuming constitutive immunity, across all cell lines, antiviral contributions from " prohibited virus from invading at all. The induced immune model thus produced a more parsimonious recapitulation of these data because virus invasion was always permitted, then rapidly controlled.
In order to compare the relative contributions of each cell line's disparate immune processes to epidemic dynamics, we next used our mean field parameter estimates to calculate the initial 'antiviral rate'-the initial accumulation rate of antiviral cells upon virus invasion for each cell-virus-MOI combination-based on the following equation:
where P E was calculated from the initial infectious dose (MOI) of each infection experiment and P S was estimated at disease-free equilibrium:
Because and " both contribute to this initial antiviral rate, induced and constitutive immune assumptions are capable of yielding equally rapid rates, depending on parameter fits. Indeed, under fully induced immune assumptions, the induced antiviral acquisition rate (r) estimated for rVSV-MARV infection on PaKiT01 cells was so high that the initial antiviral rate exceeded even that estimated under constitutive assumptions for this cell-virus combination (Supplementary file 4) . In reality, we know that NPC1 receptor incompatibilities make PaKiT01 cell lines constitutively refractory to rVSV-MARV infection (Ng and Chandrab, 2018, Unpublished results) and that PaKiT01 cells also constitutively express the antiviral cytokine, IFN-a. Model fitting results suggest that this constitutive expression of IFN-a may act more as a rapidly inducible immune response following virus invasion than as a constitutive secretion of functional IFN-a protein. Nonetheless, as hypothesized, PaKiT01 cell lines were by far the most antiviral of any in our study-with initial antiviral rates estimated several orders of magnitude higher than any others in our study, under either induced or constitutive assumptions ( Table 1 ; Supplementary file 4). RoNi/7.1 cells displayed the second-most-pronounced signature of immunity, followed by Vero cells, for which the initial antiviral rate was essentially zero even under forced assumptions of induced or constitutive immunity ( Table 1 ; Supplementary file 4).
Using fitted parameters for b and ", we additionally calculated R 0 , the basic reproduction number for the virus, for each cell line-virus-MOI combination ( Table 1 ; Supplementary file 4). We found that R 0 was essentially unchanged across differing immune assumptions for RoNi/7.1 and Vero cells, for which the initial antiviral rate was low. In the case of PaKiT01 cells, a high initial antiviral rate under either induced or constitutive immunity resulted in a correspondingly high estimation of b (and, consequently, R 0 ) which still produced the same epidemic curve that resulted from the much lower estimates for b and R 0 paired with absent immunity. These findings suggest that antiviral immune responses protect host tissues against virus-induced cell mortality and may facilitate the establishment of more rapid within-host transmission rates.
Total monolayer destruction occurred in all cell-virus combinations excepting rVSV-EBOV infections on RoNi/7.1 cells and rVSV-EBOV and rVSV-MARV infections on PaKiT01 cells. Monolayer destruction corresponded to susceptible cell depletion and epidemic turnover where R-effective (the product of R 0 and the proportion susceptible) was reduced below one ( Figure 5) . For rVSV-EBOV infections on RoNi/7.1, induced antiviral cells safeguarded remnant live cells, which birthed new susceptible cells late in the time series. In rVSV-EBOV and rVSV-MARV infections on PaKiT01 cells, this antiviral protection halted the epidemic ( Figure 5 ; R-effective <1) before susceptibles fully declined. In the case of rVSV-EBOV on PaKiT01, the birth of new susceptibles from remnant live cells protected by antiviral status maintained late-stage transmission to facilitate long-term epidemic persistence. Importantly, under fixed parameter values for the infection incubation rate (s) and infectioninduced mortality rate (a), models were unable to reproduce the longer-term infectious time series captured in data from rVSV-EBOV infections on PaKiT01 cell lines without incorporation of cell births, an assumption adopted in previous modeling representations of IFN-mediated viral dynamics in tissue culture (Howat et al., 2006) . In our experiments, we observed that cellular reproduction took place as plaque assays achieved confluency. Finally, because the protective effect of antiviral cells is more clearly observable spatially, we confirmed our results by simulating fitted time series in a spatially-explicit, stochastic reconstruction of our mean field model. In spatial simulations, rates of antiviral acquisition were fixed at fitted values for r and " derived from mean field estimates, while transmission rates (b) were fixed at values ten times greater than those estimated under mean field conditions, accounting for the intensification of parameter thresholds permitting pathogen invasion in local spatial interactions (see Materials and methods; Videos 1-3; Figure 5-figure supplement 3; Supplementary file 5; Webb et al., 2007) . In immune capable time series, spatial antiviral cells acted as 'refugia' which protected live cells from infection as each initial epidemic wave 'washed' across a cell monolayer. Eventual birth of new susceptibles from these living refugia allowed for sustained epidemic transmission in cases where some infectious cells persisted at later timepoints in simulation (Videos 1-3; Figure 5-figure supplement 3 ).
Bats are reservoirs for several important emerging zoonoses but appear not to experience disease from otherwise virulent viral pathogens. Though the molecular biological literature has made great progress in elucidating the mechanisms by which bats tolerate viral infections (Zhou et al., 2016; Ahn et al., 2019; Xie et al., 2018; Pavlovich et al., 2018; Zhang et al., 2013) , the impact of unique bat immunity on virus dynamics within-host has not been well-elucidated. We used an innovative combination of in vitro experimentation and within-host modeling to explore the impact of unique bat immunity on virus dynamics. Critically, we found that bat cell lines demonstrated a signature of enhanced interferon-mediated immune response, of either constitutive or induced form, which allowed for establishment of rapid within-host, cell-to-cell virus transmission rates (b). These results were supported by both data-independent bifurcation analysis of our mean field theoretical model, as well as fitting of this model to viral infection time series established in bat cell culture. Additionally, we demonstrated that the antiviral state induced by the interferon pathway protects live cells from mortality in tissue culture, resulting in in vitro epidemics of extended duration that enhance the probability of establishing a long-term persistent infection. Our findings suggest that viruses evolved in bat reservoirs possessing enhanced IFN capabilities could achieve more rapid within-host transmission rates without causing pathology to their hosts. Such rapidly-reproducing viruses would likely generate extreme virulence upon spillover to hosts lacking similar immune capacities to bats.
To achieve these results, we first developed a novel, within-host, theoretical model elucidating the effects of unique bat immunity, then undertook bifurcation analysis of the model's equilibrium properties under immune absent, induced, and constitutive assumptions. We considered a cell line to be constitutively immune if possessing any number of antiviral cells at disease-free equilibrium but allowed the extent of constitutive immunity to vary across the parameter range for ", the constitutive rate of antiviral acquisition. In deriving the equation for R 0 , the basic reproduction number, which defines threshold conditions for virus invasion of a tissue (R 0 >1), we demonstrated how the invasion threshold is elevated at high values of constitutive antiviral acquisition, ". Constitutive immune processes can thus prohibit pathogen invasion, while induced responses, by definition, can only control infections post-hoc. Once thresholds for pathogen invasion have been met, assumptions of constitutive immunity will limit the cellular mortality (virulence) incurred at high transmission rates. Regardless of mechanism (induced or constitutive), interferon-stimulated antiviral cells appear to play a key role in maintaining longer term or persistent infections by safeguarding susceptible cells from rapid infection and concomitant cell death. Fitting of our model to in vitro data supported expected immune phenotypes for different bat cell lines as described in the literature. Simple target cell models that ignore the effects of immunity best recapitulated infectious time series derived from IFN-deficient Vero cells, while models assuming induced immune processes most accurately reproduced trials derived from RoNi/7.1 (Rousettus aegyptiacus) cells, which possess a standard virusinduced IFN-response. In most cases, models assuming constitutive immune processes best recreated virus epidemics produced on PaKiT01 (Pteropus alecto) cells, which are known to constitutively express the antiviral cytokine, IFN-a (Zhou et al., 2016) . Model support for induced immune assumptions in fits to rVSV-MARV infections on PaKiT01 cells suggests that the constitutive IFN-a expression characteristic of P. alecto cells may represent more of a constitutive immune priming process than a perpetual, functional, antiviral defense. Results from mean field model fitting were additionally confirmed in spatially explicit stochastic simulations of each time series.
As previously demonstrated in within-host models for HIV (Coffin, 1995; Perelson et al., 1996; Nowak et al., 1995; Bonhoeffer et al., 1997; Ho et al., 1995) , assumptions of simple target-cell depletion can often provide satisfactory approximations of viral dynamics, especially those reproduced in simple in vitro systems. Critically, our model fitting emphasizes the need for incorporation of top-down effects of immune control in order to accurately reproduce infectious time series derived from bat cell tissue cultures, especially those resulting from the robustly antiviral PaKiT01 P. alecto cell line. These findings indicate that enhanced IFN-mediated immune pathways in bat reservoirs may promote elevated within-host virus replication rates prior to cross-species emergence. We nonetheless acknowledge the limitations imposed by in vitro experiments in tissue culture, especially involving recombinant viruses and immortalized cell lines. Future work should extend these cell culture studies to include measurements of multiple state variables (i.e. antiviral cells) to enhance epidemiological inference.
The continued recurrence of Ebola epidemics across central Africa highlights the importance of understanding bats' roles as reservoirs for virulent zoonotic disease. The past decade has born witness to emerging consensus regarding the unique pathways by which bats resist and tolerate highly virulent infections (Brook and Dobson, 2015; Xie et al., 2018; Zhang et al., 2013; Ahn et al., 2019; Zhou et al., 2016; Ng et al., 2015; Pavlovich et al., 2018) . Nonetheless, an understanding of the mechanisms by which bats support endemic pathogens at the population level, or promote the evolution of virulent pathogens at the individual level, remains elusive. Endemic maintenance of infection is a defining characteristic of a pathogen reservoir (Haydon et al., 2002) , and bats appear to merit such a title, supporting long-term persistence of highly transmissible viral infections in isolated island populations well below expected critical community sizes (Peel et al., 2012) . Researchers debate the relative influence of population-level and within-host mechanisms which might explain these trends (Plowright et al., 2016) , but increasingly, field data are difficult to reconcile without acknowledgement of a role for persistent infections (Peel et al., 2018; Brook et al., 2019) . We present general methods to study cross-scale viral dynamics, which suggest that within-host persistence is supported by robust antiviral responses characteristic of bat immune processes. Viruses which evolve rapid replication rates under these robust antiviral defenses may pose the greatest hazard for cross-species pathogen emergence into spillover hosts with immune systems that differ from those unique to bats.
All experiments were carried out on three immortalized mammalian kidney cell lines: Vero (African green monkey), RoNi/7.1 (Rousettus aegyptiacus) (Kühl et al., 2011; Biesold et al., 2011) and PaKiT01 (Pteropus alecto) (Crameri et al., 2009) . The species identifications of all bat cell lines was confirmed morphologically and genetically in the publications in which they were originally described (Kühl et al., 2011; Biesold et al., 2011; Crameri et al., 2009) . Vero cells were obtained from ATCC.
Monolayers of each cell line were grown to 90% confluency (~9Â10 5 cells) in 6-well plates. Cells were maintained in a humidified 37˚C, 5% CO 2 incubator and cultured in Dulbecco's modified Eagle medium (DMEM) (Life Technologies, Grand Island, NY), supplemented with 2% fetal bovine serum (FBS) (Gemini Bio Products, West Sacramento, CA), and 1% penicillin-streptomycin (Life Technologies). Cells were tested monthly for mycoplasma contamination while experiments were taking place; all cells assayed negative for contamination at every testing.
Previous work has demonstrated that all cell lines used are capable of mounting a type I IFN response upon viral challenge, with the exception of Vero cells, which possess an IFN-b deficiency (Desmyter et al., 1968; Rhim et al., 1969; Emeny and Morgan, 1979) . RoNi/7.1 cells have been shown to mount idiosyncratic induced IFN defenses upon viral infection (Pavlovich et al., 2018; Kuzmin et al., 2017; Arnold et al., 2018; Kühl et al., 2011; Biesold et al., 2011) , while PaKiT01 cells are known to constitutively express the antiviral cytokine, IFN-a (Zhou et al., 2016) . This work is the first documentation of IFN signaling induced upon challenge with the particular recombinant VSVs outlined below. We verified known antiviral immune phenotypes via qPCR. Results were consistent with the literature, indicating a less pronounced role for interferon defense against viral infection in RoNi/7.1 versus PaKiT01 cells.
Replication-capable recombinant vesicular stomatitis Indiana viruses, expressing filovirus glycoproteins in place of wild type G (rVSV-G, rVSV-EBOV, and rVSV-MARV) have been previously described (Wong et al., 2010; Miller et al., 2012) . Viruses were selected to represent a broad range of anticipated antiviral responses from host cells, based on a range of past evolutionary histories between the virus glycoprotein mediating cell entry and the host cell's entry receptor. These interactions ranged from the total absence of evolutionary history in the case of rVSV-G infections on all cell lines to a known receptor-level cell entry incompatibility in the case of rVSV-MARV infections on PaKiT01 cell lines.
To measure infectivities of rVSVs on each of the cell lines outlined above, so as to calculate the correct viral dose for each MOI, NH 4 Cl (20 mM) was added to infected cell cultures at 1-2 hr postinfection to block viral spread, and individual eGFP-positive cells were manually counted at 12-14 hr post-infection.
Previously published work indicates that immortalized kidney cell lines of Rousettus aegyptiacus (RoNi/7.1) and Pteropus alecto (PaKiT01) exhibit different innate antiviral immune phenotypes through, respectively, induced (Biesold et al., 2011; Pavlovich et al., 2018; Kühl et al., 2011; Arnold et al., 2018) and constitutive (Zhou et al., 2016 ) expression of type I interferon genes. We verified these published phenotypes on our own cell lines infected with rVSV-G, rVSV-EBOV, and rVSV-MARV via qPCR of IFN-a and IFN-b genes across a longitudinal time series of infection.
Specifically, we carried out multiple time series of infection of each cell line with each of the viruses described above, under mock infection conditions and at MOIs of 0.0001 and 0.001-with the exception of rVSV-MARV on PaKiT01 cell lines, for which infection was only performed at MOI = 0.0001 due to limited viral stocks and the extremely low infectivity of this virus on this cell line (thus requiring high viral loads for initial infection). All experiments were run in duplicate on 6well plates, such that a typical plate for any of the three viruses had two control (mock) wells, two MOI = 0.0001 wells and two MOI = 0.001 wells, excepting PaKiT01 plates, which had two control and four MOI = 0.0001 wells at a given time. We justify this PaKiT01 exemption through the expectation that IFN-a expression is constitutive for these cells, and by the assumption that any expression exhibited at the lower MOI should also be present at the higher MOI.
For these gene expression time series, four 6-well plates for each cell line-virus combination were incubated with virus for one hour at 37˚C. Following incubation, virus was aspirated off, and cell monolayers were washed in PBS, then covered with an agar plaque assay overlay to mimic conditions under which infection trials were run. Plates were then harvested sequentially at timepoints of roughly 5, 10, 15, and 20 hr post-infection (exact timing varied as multiple trials were running simultaneously). Upon harvest of each plate, agar overlay was removed, and virus was lysed and RNA extracted from cells using the Zymo Quick RNA Mini Prep kit, according to the manufacturer's instructions and including the step for cellular DNA digestion. Post-extraction, RNA quality was verified via nanodrop, and RNA was converted to cDNA using the Invitrogen Superscript III cDNA synthesis kit, according to the manufacturer's instructions. cDNA was then stored at 4˚C and as a frozen stock at À20˚C to await qPCR.
We undertook qPCR of cDNA to assess expression of the type I interferon genes, IFN-a and IFNb, and the housekeeping gene, b-Actin, using primers previously reported in the literature (Supplementary file 6) . For qPCR, 2 ml of each cDNA sample was incubated with 7 ml of deionized water, 1 ml of 5 UM forward/reverse primer mix and 10 ml of iTaq Universal SYBR Green, then cycled on a QuantStudio3 Real-Time PCR machine under the following conditions: initial denaturation at 94 C for 2 min followed by 40 cycles of: denaturation at 95˚C (5 s), annealing at 58˚C (15 s), and extension at 72˚C (10 s).
We report simple d-Ct values for each run, with raw Ct of the target gene of interest (IFN-a or IFN-b) subtracted from raw Ct of the b-Actin housekeeping gene in Figure 1 -figure supplement 6. Calculation of fold change upon viral infection in comparison to mock using the d-d-Ct method (Livak and Schmittgen, 2001) was inappropriate in this case, as we wished to demonstrate constitutive expression of IFN-a in PaKiT01 cells, whereby data from mock cells was identical to that produced from infected cells.
After being grown to~90% confluency, cells were incubated with pelleted rVSVs expressing eGFP (rVSV-G, rVSV-EBOV, rVSV-MARV). Cell lines were challenged with both a low (0.0001) and high (0.001) multiplicity of infection (MOI) for each virus. In a cell monolayer infected at a given MOI (m), the proportion of cells (P), infected by k viral particles can be described by the Poisson distribution: P k ð Þ ¼ e Àm m k k! , such that the number of initially infected cells in an experiment equals: 1 À e Àm . We assumed that a~90% confluent culture at each trial's origin was comprised of~9x10 5 cells and conducted all experiments at MOIs of 0.0001 and 0.001, meaning that we began each trial by introducing virus to, respectively,~81 or 810 cells, representing the state variable 'E' in our theoretical model. Low MOIs were selected to best approximate the dynamics of mean field infection and limit artifacts of spatial structuring, such as premature epidemic extinction when growing plaques collide with plate walls in cell culture.
Six-well plates were prepared with each infection in duplicate or triplicate, such that a control well (no virus) and 2-3 wells each at MOI 0.001 and 0.0001 were incubated simultaneously on the same plate. In total, we ran between 18 and 39 trials at each cell-virus-MOI combination, excepting r-VSV-MARV infections on PaKiT01 cells at MOI = 0.001, for which we ran only eight trials due to the low infectivity of this virus on this cell line, which required high viral loads for initial infection. Cells were incubated with virus for one hour at 37˚C. Following incubation, virus was aspirated off, and cell monolayers were washed in PBS, then covered with a molten viscous overlay (50% 2X MEM/Lglutamine; 5% FBS; 3% HEPES; 42% agarose), cooled for 20 min, and re-incubated in their original humidified 37˚C, 5% CO 2 environment.
After application of the overlay, plates were monitored periodically using an inverted fluorescence microscope until the first signs of GFP expression were witnessed (~6-9.5 hr post-infection, depending on the cell line and virus under investigation). From that time forward, a square subset of the center of each well (comprised of either 64-or 36-subframes and corresponding to roughly 60% and 40% of the entire well space) was imaged periodically, using a CellInsight CX5 High Content Screening (HCS) Platform with a 4X air objective (ThermoFisher, Inc, Waltham, MA). Microscope settings were held standard across all trials, with exposure time fixed at 0.0006 s for each image. One color channel was imaged, such that images produced show GFP-expressing cells in white and non-GFP-expressing cells in black (Figure 1-figure supplement 1) .
Wells were photographed in rotation, as frequently as possible, from the onset of GFP expression until the time that the majority of cells in the well were surmised to be dead, GFP expression could no longer be detected, or early termination was desired to permit Hoechst staining.
In the case of PaKiT01 cells infected with rVSV-EBOV, where an apparently persistent infection established, the assay was terminated after 200+ hours (8+ days) of continuous observation. Upon termination of all trials, cells were fixed in formaldehyde (4% for 15 min), incubated with Hoechst stain (0.0005% for 15 min) (ThermoFisher, Inc, Waltham, MA), then imaged at 4X on the CellInsight CX5 High Content Screening (HCS) Platform. The machine was allowed to find optimal focus for each Hoechst stain image. One color channel was permitted such that images produced showed live nuclei in white and dead cells in black.
Hoechst stain colors cellular DNA, and viral infection is thought to interfere with the clarity of the stain (Dembowski and DeLuca, 2015) . As such, infection termination, cell fixation, and Hoechst staining enables generation of a rough time series of uninfectious live cells (i.e. susceptible + antiviral cells) to complement the images which produced time series of proportions infectious. Due to uncertainty over the exact epidemic state of Hoechst-stained cells (i.e. exposed but not yet infectious cells may still stain), we elected to fit our models only to the infectious time series derived from GFPexpressing images and used Hoechst stain images as a post hoc visual check on our fit only ( Figure 5 ; Figure 5 -figure supplements 1-2).
Images recovered from the time series above were processed into binary ('infectious' vs. 'non-infectious' or, for Hoechst-stained images, 'live' vs. 'dead') form using the EBImage package (Pau et al., 2010) in R version 3.6 for MacIntosh, after methods further detailed in Supplementary file 7. Binary images were then further processed into time series of infectious or, for Hoechst-stained images, live cells using a series of cell counting scripts. Because of logistical constraints (i.e. many plates of simultaneously running infection trials and only one available imaging microscope), the time course of imaging across the duration of each trial was quite variable. As such, we fitted a series of statistical models to our processed image data to reconstruct reliable values of the infectious proportion of each well per hour for each distinct trial in all cell line-virus-MOI combinations (Figure 1
To derive the expression for R 0 , the basic pathogen reproductive number in vitro, we used Next Generation Matrix (NGM) techniques (Diekmann et al., 1990; Heffernan et al., 2005) , employing Wolfram Mathematica (version 11.2) as an analytical tool. R 0 describes the number of new infections generated by an existing infection in a completely susceptible host population; a pathogen will invade a population when R 0 >1 (Supplementary file 2). We then analyzed stability properties of the system, exploring dynamics across a range of parameter spaces, using MatCont (version 2.2) (Dhooge et al., 2008) for Matlab (version R2018a) (Supplementary file 3).
The birth rate, b, and natural mortality rate, m, balance to yield a population-level growth rate, such that it is impossible to estimate both b and m simultaneously from total population size data alone. As such, we fixed b at. 025 and estimated m by fitting an infection-absent version of our mean field model to the susceptible time series derived via Hoechst staining of control wells for each of the three cell lines (Figure 1-figure supplement 7) . This yielded a natural mortality rate, m, corresponding to a lifespan of approximately 121, 191, and 84 hours, respectively, for Vero, RoNi/7.1, and PaKiT01 cell lines (Figure 1-figure supplement 7) . We then fixed the virus incubation rate, s, as the inverse of the shortest observed duration of time from initial infection to the observation of the first infectious cells via fluorescent microscope for all nine cell line -virus combinations (ranging 6 to 9.5 hours). We fixed a, the infection-induced mortality rate, at 1/6, an accepted standard for general viral kinetics (Howat et al., 2006) , and held c, the rate of antiviral cell regression to susceptible status, at 0 for the timespan (<200 hours) of the experimental cell line infection trials.
We estimated cell line-virus-MOI-specific values for b, r, and " by fitting the deterministic output of infectious proportions in our mean field model to the full suite of statistical outputs of all trials for each infected cell culture time series (Figure 1-figure supplements 2-3) . Fitting was performed by minimizing the sum of squared differences between the deterministic model output and cell linevirus-MOI-specific infectious proportion of the data at each timestep. We optimized parameters for MOI = 0.001 and 0.0001 simultaneously to leverage statistical power across the two datasets, estimating a different transmission rate, b, for trials run at each infectious dose but, where applicable, estimating the same rates of r and " across the two time series. We used the differential equation solver lsoda() in the R package deSolve (Soetaert et al., 2010) to obtain numerical solutions for the mean field model and carried out minimization using the 'Nelder-Mead' algorithm of the optim() function in base R. All model fits were conducted using consistent starting guesses for the parameters, b (b = 3), and where applicable, r (r = 0.001) and " (" = 0.001). In the case of failed fits or indefinite hessians, we generated a series of random guesses around the starting conditions and continued estimation until successful fits were achieved.
All eighteen cell line-virus-MOI combinations of data were fit by an immune absent (" = r = 0) version of the theoretical model and, subsequently, an induced immunity (" = 0; r >0) and constitutive immunity (" >0; r >0) version of the model. Finally, we compared fits across each cell line-virus-MOI combination via AIC. In calculating AIC, the number of fitted parameters in each model (k) varied across the immune phenotypes, with one parameter (b) estimated for absent immune assumptions, two (b and r) for induced immune assumptions, and three (b, r, and ") for constitutive immune assumptions. The sample size (n) corresponded to the number of discrete time steps across all empirical infectious trials to which the model was fitted for each cell-line virus combination. All fitting and model comparison scripts are freely available for download at the following FigShare repository: DOI: 10.6084/m9.figshare.8312807.
Finally, we verified all mean field fits in a spatial context, in order to more thoroughly elucidate the role of antiviral cells in each time series. We constructed our spatial model in C++ implemented in R using the packages Rcpp and RcppArmadillo (Eddelbuettel and Francois, 2011; Eddelbuettel and Sanderson, 2017) . Following Nagai and Honda (2001) and Howat et al. (2006) , we modeled this system on a two-dimensional hexagonal lattice, using a ten-minute epidemic timestep for cell state transitions. At the initialization of each simulation, we randomly assigned a duration of natural lifespan, incubation period, infectivity period, and time from antiviral to susceptible status to all cells in a theoretical monolayer. Parameter durations were drawn from a normal distribution centered at the inverse of the respective fixed rates of m, s, a, and c, as reported with our mean field model. Transitions involving the induced (r) and constitutive (") rates of antiviral acquisition were governed probabilistically and adjusted dynamically at each timestep based on the global environment. As such, we fixed these parameters at the same values estimated in the mean field model, and multiplied both r and " by the global proportion of, respectively, exposed and susceptible cells at a given timestep.
In contrast to antiviral acquisition rates, transitions involving the birth rate (b) and the transmission rate (b) occurred probabilistically based on each cell's local environment. The birth rate, b, was multiplied by the proportion of susceptible cells within a six-neighbor circumference of a focal dead cell, while b was multiplied by the proportion of infectious cells within a thirty-six neighbor vicinity of a focal susceptible cell, thus allowing viral transmission to extend beyond the immediate nearestneighbor boundaries of an infectious cell. To compensate for higher thresholds to cellular persistence and virus invasion which occur under local spatial conditions (Webb et al., 2007) , we increased the birth rate, b, and the cell-to-cell transmission rate, b, respectively, to six and ten times the values used in the mean field model (Supplementary file 4) . We derived these increases based on the assumption that births took place exclusively based on pairwise nearest-neighbor interactions (the six immediately adjacent cells to a focal dead cell), while viral transmission was locally concentrated but included a small (7.5%) global contribution, representing the thirty-six cell surrounding vicinity of a focal susceptible. We justify these increases and derive their origins further in Supplementary file 5.
We simulated ten stochastic spatial time series for all cell-virus combinations under all three immune assumptions at a population size of 10,000 cells and compared model output with data in . Transparent reporting form Data availability All data generated or analysed during this study are included in the manuscript and supporting files. All images and code used in this study have been made available for download at the following Figshare | What is a conclusion of the modeling? | false | 2,748 | {
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1,623 | Etiology of Influenza-Like Illnesses from Sentinel Network Practitioners in Réunion Island, 2011-2012
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5031398/
SHA: f5ff89ebfdd0375d034c112c6c1c7e163fa69a0c
Authors: Brottet, Elise; Jaffar-Bandjee, Marie-Christine; Li-Pat-Yuen, Ghislaine; Filleul, Laurent
Date: 2016-09-21
DOI: 10.1371/journal.pone.0163377
License: cc-by
Abstract: In Réunion Island, despite an influenza surveillance established since 1996 by the sentinel general practitioner’s network, little is known about the etiology of Influenza like-illness (ILI) that differs from influenza viruses in a tropical area. We set up a retrospective study using nasal swabs collected by sentinel GPs from ILI patients in 2011 and 2012. A total of 250 swabs were randomly selected and analyzed by multiplex reverse transcriptase polymerase chain reaction (RT-PCR) including research of 18 viruses and 4 bacteria. We detected respiratory viruses in 169/222 (76.1%) samples, mostly rhinovirus (23.4%), influenza A virus (21.2%), influenza B virus (12.6%), coronavirus (4.9%) and Human metapneumovirus (3.6%). Nine swabs (5.3% of positive swabs) revealed co-infections with two viruses identified, among which six concerned co-infections with influenza viruses. We observed important seasonal differences, with circulation of Human Metapneumoviruses, RSV A and B and coronavirus only during summer; whereas parainfluenza viruses were identified only during winter. In conclusion, this study highlights a substantial circulation of multiple respiratory pathogens in Réunion Island throughout the year. It shows that ILI are not only attributable to influenza and underlines the need for biological surveillance. As the use of multiplex RT-PCR showed its efficacy, it is now used routinely in the surveillance of ILI.
Text: Influenza like-illness (ILI) or acute respiratory infections can be caused by several types of respiratory viruses or bacteria in humans [1] . Influenza viruses, Respiratory Syncytial viruses (RSV) and Parainfluenza viruses are identified as major viruses mostly responsible for ILI and pneumonia in several studies [2] . However practitioners cannot diagnose the infection without a biological test confirmation. Unfortunately, these infections causes are identified in less than 50% [3] .
Réunion Island, a French overseas territory with 850,000 inhabitants, is located in the southern hemisphere between Madagascar and Mauritius in the Indian Ocean (Latitude: 21°05.2920 S Longitude: 55°36.4380 E.). The island benefits from a healthcare system similar to mainland France and epidemiological surveillance has been developed by the regional office of the French Institute for Public Health Surveillance (Cire OI), based on the surveillance system of mainland France [4] . Influenza activity generally increases during austral winter, corresponding to summer in Europe [5] . Since 2011, influenza vaccination campaign in Reunion Island starts in April and the vaccine used corresponds to World Health Organization recommendations for the southern hemisphere.
Since 1996, clinical and biological influenza surveillance has been based on a sentinel practitioner's network [6] . In 2014, this network was composed of 58 general practitioners (GPs) spread over the island and represented around 7% of all Réunion Island GPs. Nasal swabs are randomly collected all along the year and are tested by RT-PCR for influenza viruses. Among these surveillance samples, 40 to 50% are tested positive for influenza A virus, A(H1N1)pdm09 or B virus by the virological laboratory of the University Hospital Center of Réunion. Thus ILI samples tested negative for influenza are of unknown etiology.
Several biological tools allow identifying respiratory pathogens from nasal swab. In recent years, multiplex reverse transcriptase polymerase chain reaction (RT-PCR) has been developed to identify several viruses simultaneously [7] [8] [9] [10] . We therefore used this new method to set up a retrospective study using swabs collected by sentinel GPs from 2011 to 2012.
The main objective of our study was to characterize respiratory pathogens responsible for ILI consultations in sentinel GPs in 2011 and 2012. Secondary objectives were to highlight seasonal trends on respiratory pathogens circulation and to describe occurrence of co-infections, especially during the flu season.
ILI was defined as a sudden onset of fever more than 38 degrees Celsius and cough, associated or not with other symptoms such as breathing difficulty, headache, etc. Every week, all GPs of the sentinel network were encouraged to collect a nasal swab from the first two patients who presented ILI since less than three days. After being tested for influenza viruses, the 994 swabs collected in 2011 and 2012 are frozen at -80°C at the university hospital center (CHU) laboratory.
Based on the budget, a season-stratified sample of 250 swabs was randomly selected in order to describe circulating viruses including outside flu season. Random sampling was performed with Excel 1 using the anonymized surveillance database of the Cire OI. The sampling frame contained identification number of swab assigned by Cire OI, laboratory identification number, sex, age, date of onset of symptoms, date of swab collection and result of influenza RT-PCR.
We used Respifinder 1 Smart 22 kits a multiplex RT-PCR (PathoFinder, Maastricht, The Netherlands) which can detect 22 respiratory pathogens. This assay is based on the multiplex ligation-dependent probe amplification (MLPA) technology. The reverse transcription and preamplification steps were performed on the epgradient Mastercycler 1 (Eppendorf) and the hybridization, ligation and detection steps on the LightCycler 1 480 system (Roche Applied Science). This method was chosen because of its high specificity, compared to other same methods (78% versus 33%) [3, 11] . Multiplex analysis allows for rapid production of diagnostic results. It thus allows highlighted the possible presence of eighteen respiratory viruses and four bacteria in one reaction by melt curve analysis: Influenza A not (H1N1
Statistical analyses were performed with Stata 1 and Excel 1 . Two seasons were defined to identify possible seasonal trends in circulation of the viruses: winter season during weeks 23 to 39 between June and September and summer season during the rest of the year.
Data and swabs result from a surveillance system that received regulatory approvals, including the CNIL (National Commission for Information Technology and Civil Liberties Number 1592205) approval in July 2012. All the patients have received oral information and gave their consent for swab and data collection. Data were collected for surveillance purpose and are totally anonymous.
Among the 250 randomly-selected swabs, 26 were not available anymore as they were sent to Influenza Reference Center for confirmation and characterization of the pathogenic agent. According to the sensitivity of the assay two samples could be discordant results between Influenza PCR initially realized and Multiplex PCR. Thus they were deleted from the analysis: one is positive for Influenza in singleplex and negative for all tested pathogens in multiplex and one is positive for Influenza in singleplex and positive for PIV2 in multiplex. In total, 222 analyses were considered. Moreover, 53 samples were negative for all analyzed respiratory pathogens (23.9%) and 169 samples had at least one detected pathogen (76.1%), finally a total of 178 pathogens was identified.
During the study period, a minority of the weeks (21 i.e. 20%) did not include any sampled swab, mainly outside flu season.
Patients' sex-ratio was 0.63 (86 men and 136 women) and mean age was 28.4 years [min 0; max 81]. Ten percent had less than 5 years, 24% 5-15 years, 63% 15-65 years and only 3% were 65 and older.
The respiratory pathogens most frequently identified in ILI swabs were rhinovirus (23.4%), influenza A not H1N1 (21.2%) and influenza B (12.6%) ( Table 1) .
Among the 22 respiratory pathogens tested by the multiplex, only three were not found in any analyzed sample: Parainfluenza3, Legionella pneumophila and Bordetella pertussis.
Regarding co-infections, nine swabs revealed the presence of two viruses, among which6 involved influenza viruses (Table 2) .
Analyses showed that some viruses are possibly seasonal and were circulating during a specific period of the year. They are detected only in summer for Human Metapneumovirus, RSV A and B, and influenza A(H1N1)pdm09. For the latter, it is specific to the studied period since the influenza A(H1N1)pdm09 virus reappeared in Réunion Island in October 2012 and was no longer circulating since late 2010. On the opposite, Parainfluenza 1,2 and 4 viruses were identified only in winter. For other pathogens, no specific period of detection was observed.
A weekly description of samples was realized to study the distribution of respiratory pathogens in 2011 and 2012 (Fig 1) . Results of biological analyses were compared with data of ILI consultations declared by sentinel GPs in 2011 and 2012. We observed in 2011, after a first wave in June mainly due to influenza A not H1N1 virus, a second wave of ILI consultations with mainly identification of Parainfluenza viruses and not influenza viruses. In 2012, the second epidemic wave at the end of austral winter coincided with Influenza viruses and Rhinovirus circulation.
Regarding negative swabs (Fig 2) , we observed no seasonality during the study period with a similar proportion whatever the season.
This retrospective study based on a sentinel GPs network showed that not only influenza viruses are responsible for ILI consultations. Indeed, an important circulation of multiple pathogens was observed throughout the year, with 12 different types of pathogens identified in 2011 and 2012. Respiratory viral pathogens were present in 76.1% of samples, which is largely above results from annual influenza surveillance [12] . After influenza viruses, Rhinovirus and Coronavirus were the most common respiratory viruses in Réunion Island. Although samples were not taken every week, sample was representative of ILI activity and consistent with flu season. Nevertheless, according to the low number of samples, it is difficult to conclude about seasonality. However in our study, RSV was circulating in summer season which is hot and rainy, which is confirmed by other studies in tropical region [13] .
This study also highlighted several co-infections, showing that concomitant the multiple etiology of ILI. Co-circulation was already observed in Réunion Island during the A(H1N1) pdm09 pandemic in addition to influenza virus, with identification of other respiratory viruses such as Rhinovirus or Coronavirus [14] . In mainland France, during this pandemic, circulation of major respiratory viruses was found, such as Rhinovirus, Parainfluenza, Coronavirus, Human Metapneumovirus, like in our publication [15] [16] . In our study, only 5.3% of positive swabs were co-infections whereas in two studies in Madagascar co-infections represented 27.3% and 29.4% [17] [18] .
Despite the distance of 9,300 km between Réunion and France, the island is directly connected to Europe with four daily flights to France. These exchanges can impact respiratory pathogens circulation in southern and northern hemisphere. Results of this study can therefore be of interest to both Indian Ocean and Europe countries.
Among the 148 swabs initially negative for influenza because not previously tested for any other viruses, the study found an etiology for 95 swabs. In total, only 53 swabs, representing 24% of the sample, remained without etiology with negative multiplex PCR results all along the year. Multiple hypotheses can explain this result: a poor quality of swabs, preventing from identifying a pathogen, noninfectious causes or other pathogens not included in the multiplex PCR. However, we couldn't test the negative swabs for RNAse P, a marker of human cells, which could provide a modicum of assurance that the swab contained human cells.
Concerning the two samples divergent for influenza identification between the multiplex and singleplex PCR, we discarded them for the analysis; one was positive in Influenza with singleplex and positive in PIV with multiplex. It could be a false positive result from singleplex. Indeed, as the multiplex PCR assay has a good sensitivity and is considered as a gold-standard, we decided to keep seven negative results for Influenza in singleplex and positive in Influenza in multiplex [7] [8] [9] [10] .
No case of Bordetella pertussis which causes whooping cough and Legionella pneumophila which causes Legionnaires' disease was identified in this study. However, these diseases are rare in Réunion Island, around three cases of Legionnaires' disease are declared each year.
A limit of the study is that no clinical data were available in the virological surveillance system of influenza in Réunion Island. It was impossible to compare clinical symptoms according to each pathogen and to know if there are different pathogens which cause for instance rhinitis, laryngitis or bronchitis (diseases included in ILI). A specific prospective study including clinical data might provide useful elements in the semiotics of diseases.
In conclusion, this study highlighted an important circulation of multiple pathogens in Réunion Island throughout the year. It shows that ILI is not specific to influenza and so it is essential to have biological results in order to establish the differential diagnosis and thus explain the etiology of symptoms. For a better understanding of respiratory pathogens circulating in Réunion Island, information from this study may also be useful to practitioners who see many patients in consultation with ILI. As the use of multiplex RT-PCR showed its efficacy in the ILI surveillance and allowed to highlight the circulation of other viruses and bacterial causes of respiratory infections, it is now used routinely in the surveillance of ILI. Moreover, it would be interesting to repeat this study every 3 or 5 years adding clinical data to monitor the evolution of respiratory pathogens in Réunion Island over time. | How many swabs remained without etiology? | false | 4,113 | {
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2,504 | Respiratory Viral Infections in Exacerbation of Chronic Airway Inflammatory Diseases: Novel Mechanisms and Insights From the Upper Airway Epithelium
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7052386/
SHA: 45a566c71056ba4faab425b4f7e9edee6320e4a4
Authors: Tan, Kai Sen; Lim, Rachel Liyu; Liu, Jing; Ong, Hsiao Hui; Tan, Vivian Jiayi; Lim, Hui Fang; Chung, Kian Fan; Adcock, Ian M.; Chow, Vincent T.; Wang, De Yun
Date: 2020-02-25
DOI: 10.3389/fcell.2020.00099
License: cc-by
Abstract: Respiratory virus infection is one of the major sources of exacerbation of chronic airway inflammatory diseases. These exacerbations are associated with high morbidity and even mortality worldwide. The current understanding on viral-induced exacerbations is that viral infection increases airway inflammation which aggravates disease symptoms. Recent advances in in vitro air-liquid interface 3D cultures, organoid cultures and the use of novel human and animal challenge models have evoked new understandings as to the mechanisms of viral exacerbations. In this review, we will focus on recent novel findings that elucidate how respiratory viral infections alter the epithelial barrier in the airways, the upper airway microbial environment, epigenetic modifications including miRNA modulation, and other changes in immune responses throughout the upper and lower airways. First, we reviewed the prevalence of different respiratory viral infections in causing exacerbations in chronic airway inflammatory diseases. Subsequently we also summarized how recent models have expanded our appreciation of the mechanisms of viral-induced exacerbations. Further we highlighted the importance of the virome within the airway microbiome environment and its impact on subsequent bacterial infection. This review consolidates the understanding of viral induced exacerbation in chronic airway inflammatory diseases and indicates pathways that may be targeted for more effective management of chronic inflammatory diseases.
Text: The prevalence of chronic airway inflammatory disease is increasing worldwide especially in developed nations (GBD 2015 Chronic Respiratory Disease Collaborators, 2017 Guan et al., 2018) . This disease is characterized by airway inflammation leading to complications such as coughing, wheezing and shortness of breath. The disease can manifest in both the upper airway (such as chronic rhinosinusitis, CRS) and lower airway (such as asthma and chronic obstructive pulmonary disease, COPD) which greatly affect the patients' quality of life (Calus et al., 2012; Bao et al., 2015) . Treatment and management vary greatly in efficacy due to the complexity and heterogeneity of the disease. This is further complicated by the effect of episodic exacerbations of the disease, defined as worsening of disease symptoms including wheeze, cough, breathlessness and chest tightness (Xepapadaki and Papadopoulos, 2010) . Such exacerbations are due to the effect of enhanced acute airway inflammation impacting upon and worsening the symptoms of the existing disease (Hashimoto et al., 2008; Viniol and Vogelmeier, 2018) . These acute exacerbations are the main cause of morbidity and sometimes mortality in patients, as well as resulting in major economic burdens worldwide. However, due to the complex interactions between the host and the exacerbation agents, the mechanisms of exacerbation may vary considerably in different individuals under various triggers. Acute exacerbations are usually due to the presence of environmental factors such as allergens, pollutants, smoke, cold or dry air and pathogenic microbes in the airway (Gautier and Charpin, 2017; Viniol and Vogelmeier, 2018) . These agents elicit an immune response leading to infiltration of activated immune cells that further release inflammatory mediators that cause acute symptoms such as increased mucus production, cough, wheeze and shortness of breath. Among these agents, viral infection is one of the major drivers of asthma exacerbations accounting for up to 80-90% and 45-80% of exacerbations in children and adults respectively (Grissell et al., 2005; Xepapadaki and Papadopoulos, 2010; Jartti and Gern, 2017; Adeli et al., 2019) . Viral involvement in COPD exacerbation is also equally high, having been detected in 30-80% of acute COPD exacerbations (Kherad et al., 2010; Jafarinejad et al., 2017; Stolz et al., 2019) . Whilst the prevalence of viral exacerbations in CRS is still unclear, its prevalence is likely to be high due to the similar inflammatory nature of these diseases (Rowan et al., 2015; Tan et al., 2017) . One of the reasons for the involvement of respiratory viruses' in exacerbations is their ease of transmission and infection (Kutter et al., 2018) . In addition, the high diversity of the respiratory viruses may also contribute to exacerbations of different nature and severity (Busse et al., 2010; Costa et al., 2014; Jartti and Gern, 2017) . Hence, it is important to identify the exact mechanisms underpinning viral exacerbations in susceptible subjects in order to properly manage exacerbations via supplementary treatments that may alleviate the exacerbation symptoms or prevent severe exacerbations.
While the lower airway is the site of dysregulated inflammation in most chronic airway inflammatory diseases, the upper airway remains the first point of contact with sources of exacerbation. Therefore, their interaction with the exacerbation agents may directly contribute to the subsequent responses in the lower airway, in line with the "United Airway" hypothesis. To elucidate the host airway interaction with viruses leading to exacerbations, we thus focus our review on recent findings of viral interaction with the upper airway. We compiled how viral induced changes to the upper airway may contribute to chronic airway inflammatory disease exacerbations, to provide a unified elucidation of the potential exacerbation mechanisms initiated from predominantly upper airway infections.
Despite being a major cause of exacerbation, reports linking respiratory viruses to acute exacerbations only start to emerge in the late 1950s (Pattemore et al., 1992) ; with bacterial infections previously considered as the likely culprit for acute exacerbation (Stevens, 1953; Message and Johnston, 2002) . However, with the advent of PCR technology, more viruses were recovered during acute exacerbations events and reports implicating their role emerged in the late 1980s (Message and Johnston, 2002) . Rhinovirus (RV) and respiratory syncytial virus (RSV) are the predominant viruses linked to the development and exacerbation of chronic airway inflammatory diseases (Jartti and Gern, 2017) . Other viruses such as parainfluenza virus (PIV), influenza virus (IFV) and adenovirus (AdV) have also been implicated in acute exacerbations but to a much lesser extent (Johnston et al., 2005; Oliver et al., 2014; Ko et al., 2019) . More recently, other viruses including bocavirus (BoV), human metapneumovirus (HMPV), certain coronavirus (CoV) strains, a specific enterovirus (EV) strain EV-D68, human cytomegalovirus (hCMV) and herpes simplex virus (HSV) have been reported as contributing to acute exacerbations . The common feature these viruses share is that they can infect both the upper and/or lower airway, further increasing the inflammatory conditions in the diseased airway (Mallia and Johnston, 2006; Britto et al., 2017) .
Respiratory viruses primarily infect and replicate within airway epithelial cells . During the replication process, the cells release antiviral factors and cytokines that alter local airway inflammation and airway niche (Busse et al., 2010) . In a healthy airway, the inflammation normally leads to type 1 inflammatory responses consisting of activation of an antiviral state and infiltration of antiviral effector cells. This eventually results in the resolution of the inflammatory response and clearance of the viral infection (Vareille et al., 2011; Braciale et al., 2012) . However, in a chronically inflamed airway, the responses against the virus may be impaired or aberrant, causing sustained inflammation and erroneous infiltration, resulting in the exacerbation of their symptoms (Mallia and Johnston, 2006; Dougherty and Fahy, 2009; Busse et al., 2010; Britto et al., 2017; Linden et al., 2019) . This is usually further compounded by the increased susceptibility of chronic airway inflammatory disease patients toward viral respiratory infections, thereby increasing the frequency of exacerbation as a whole (Dougherty and Fahy, 2009; Busse et al., 2010; Linden et al., 2019) . Furthermore, due to the different replication cycles and response against the myriad of respiratory viruses, each respiratory virus may also contribute to exacerbations via different mechanisms that may alter their severity. Hence, this review will focus on compiling and collating the current known mechanisms of viral-induced exacerbation of chronic airway inflammatory diseases; as well as linking the different viral infection pathogenesis to elucidate other potential ways the infection can exacerbate the disease. The review will serve to provide further understanding of viral induced exacerbation to identify potential pathways and pathogenesis mechanisms that may be targeted as supplementary care for management and prevention of exacerbation. Such an approach may be clinically significant due to the current scarcity of antiviral drugs for the management of viral-induced exacerbations. This will improve the quality of life of patients with chronic airway inflammatory diseases.
Once the link between viral infection and acute exacerbations of chronic airway inflammatory disease was established, there have been many reports on the mechanisms underlying the exacerbation induced by respiratory viral infection. Upon infecting the host, viruses evoke an inflammatory response as a means of counteracting the infection. Generally, infected airway epithelial cells release type I (IFNα/β) and type III (IFNλ) interferons, cytokines and chemokines such as IL-6, IL-8, IL-12, RANTES, macrophage inflammatory protein 1α (MIP-1α) and monocyte chemotactic protein 1 (MCP-1) (Wark and Gibson, 2006; Matsukura et al., 2013) . These, in turn, enable infiltration of innate immune cells and of professional antigen presenting cells (APCs) that will then in turn release specific mediators to facilitate viral targeting and clearance, including type II interferon (IFNγ), IL-2, IL-4, IL-5, IL-9, and IL-12 (Wark and Gibson, 2006; Singh et al., 2010; Braciale et al., 2012) . These factors heighten local inflammation and the infiltration of granulocytes, T-cells and B-cells (Wark and Gibson, 2006; Braciale et al., 2012) . The increased inflammation, in turn, worsens the symptoms of airway diseases.
Additionally, in patients with asthma and patients with CRS with nasal polyp (CRSwNP), viral infections such as RV and RSV promote a Type 2-biased immune response (Becker, 2006; Jackson et al., 2014; Jurak et al., 2018) . This amplifies the basal type 2 inflammation resulting in a greater release of IL-4, IL-5, IL-13, RANTES and eotaxin and a further increase in eosinophilia, a key pathological driver of asthma and CRSwNP (Wark and Gibson, 2006; Singh et al., 2010; Chung et al., 2015; Dunican and Fahy, 2015) . Increased eosinophilia, in turn, worsens the classical symptoms of disease and may further lead to life-threatening conditions due to breathing difficulties. On the other hand, patients with COPD and patients with CRS without nasal polyp (CRSsNP) are more neutrophilic in nature due to the expression of neutrophil chemoattractants such as CXCL9, CXCL10, and CXCL11 (Cukic et al., 2012; Brightling and Greening, 2019) . The pathology of these airway diseases is characterized by airway remodeling due to the presence of remodeling factors such as matrix metalloproteinases (MMPs) released from infiltrating neutrophils (Linden et al., 2019) . Viral infections in such conditions will then cause increase neutrophilic activation; worsening the symptoms and airway remodeling in the airway thereby exacerbating COPD, CRSsNP and even CRSwNP in certain cases (Wang et al., 2009; Tacon et al., 2010; Linden et al., 2019) .
An epithelial-centric alarmin pathway around IL-25, IL-33 and thymic stromal lymphopoietin (TSLP), and their interaction with group 2 innate lymphoid cells (ILC2) has also recently been identified (Nagarkar et al., 2012; Hong et al., 2018; Allinne et al., 2019) . IL-25, IL-33 and TSLP are type 2 inflammatory cytokines expressed by the epithelial cells upon injury to the epithelial barrier (Gabryelska et al., 2019; Roan et al., 2019) . ILC2s are a group of lymphoid cells lacking both B and T cell receptors but play a crucial role in secreting type 2 cytokines to perpetuate type 2 inflammation when activated (Scanlon and McKenzie, 2012; Li and Hendriks, 2013) . In the event of viral infection, cell death and injury to the epithelial barrier will also induce the expression of IL-25, IL-33 and TSLP, with heighten expression in an inflamed airway (Allakhverdi et al., 2007; Goldsmith et al., 2012; Byers et al., 2013; Shaw et al., 2013; Beale et al., 2014; Jackson et al., 2014; Uller and Persson, 2018; Ravanetti et al., 2019) . These 3 cytokines then work in concert to activate ILC2s to further secrete type 2 cytokines IL-4, IL-5, and IL-13 which further aggravate the type 2 inflammation in the airway causing acute exacerbation (Camelo et al., 2017) . In the case of COPD, increased ILC2 activation, which retain the capability of differentiating to ILC1, may also further augment the neutrophilic response and further aggravate the exacerbation (Silver et al., 2016) . Interestingly, these factors are not released to any great extent and do not activate an ILC2 response during viral infection in healthy individuals (Yan et al., 2016; Tan et al., 2018a) ; despite augmenting a type 2 exacerbation in chronically inflamed airways (Jurak et al., 2018) . These classical mechanisms of viral induced acute exacerbations are summarized in Figure 1 .
As integration of the virology, microbiology and immunology of viral infection becomes more interlinked, additional factors and FIGURE 1 | Current understanding of viral induced exacerbation of chronic airway inflammatory diseases. Upon virus infection in the airway, antiviral state will be activated to clear the invading pathogen from the airway. Immune response and injury factors released from the infected epithelium normally would induce a rapid type 1 immunity that facilitates viral clearance. However, in the inflamed airway, the cytokines and chemokines released instead augmented the inflammation present in the chronically inflamed airway, strengthening the neutrophilic infiltration in COPD airway, and eosinophilic infiltration in the asthmatic airway. The effect is also further compounded by the participation of Th1 and ILC1 cells in the COPD airway; and Th2 and ILC2 cells in the asthmatic airway.
Frontiers in Cell and Developmental Biology | www.frontiersin.org mechanisms have been implicated in acute exacerbations during and after viral infection (Murray et al., 2006) . Murray et al. (2006) has underlined the synergistic effect of viral infection with other sensitizing agents in causing more severe acute exacerbations in the airway. This is especially true when not all exacerbation events occurred during the viral infection but may also occur well after viral clearance (Kim et al., 2008; Stolz et al., 2019) in particular the late onset of a bacterial infection (Singanayagam et al., 2018 (Singanayagam et al., , 2019a . In addition, viruses do not need to directly infect the lower airway to cause an acute exacerbation, as the nasal epithelium remains the primary site of most infections. Moreover, not all viral infections of the airway will lead to acute exacerbations, suggesting a more complex interplay between the virus and upper airway epithelium which synergize with the local airway environment in line with the "united airway" hypothesis (Kurai et al., 2013) . On the other hand, viral infections or their components persist in patients with chronic airway inflammatory disease (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Hence, their presence may further alter the local environment and contribute to current and future exacerbations. Future studies should be performed using metagenomics in addition to PCR analysis to determine the contribution of the microbiome and mycobiome to viral infections. In this review, we highlight recent data regarding viral interactions with the airway epithelium that could also contribute to, or further aggravate, acute exacerbations of chronic airway inflammatory diseases.
Patients with chronic airway inflammatory diseases have impaired or reduced ability of viral clearance (Hammond et al., 2015; McKendry et al., 2016; Akbarshahi et al., 2018; Gill et al., 2018; Wang et al., 2018; Singanayagam et al., 2019b) . Their impairment stems from a type 2-skewed inflammatory response which deprives the airway of important type 1 responsive CD8 cells that are responsible for the complete clearance of virusinfected cells (Becker, 2006; McKendry et al., 2016) . This is especially evident in weak type 1 inflammation-inducing viruses such as RV and RSV (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Additionally, there are also evidence of reduced type I (IFNβ) and III (IFNλ) interferon production due to type 2-skewed inflammation, which contributes to imperfect clearance of the virus resulting in persistence of viral components, or the live virus in the airway epithelium (Contoli et al., 2006; Hwang et al., 2019; Wark, 2019) . Due to the viral components remaining in the airway, antiviral genes such as type I interferons, inflammasome activating factors and cytokines remained activated resulting in prolong airway inflammation (Wood et al., 2011; Essaidi-Laziosi et al., 2018) . These factors enhance granulocyte infiltration thus prolonging the exacerbation symptoms. Such persistent inflammation may also be found within DNA viruses such as AdV, hCMV and HSV, whose infections generally persist longer (Imperiale and Jiang, 2015) , further contributing to chronic activation of inflammation when they infect the airway (Yang et al., 2008; Morimoto et al., 2009; Imperiale and Jiang, 2015; Lan et al., 2016; Tan et al., 2016; Kowalski et al., 2017) . With that note, human papilloma virus (HPV), a DNA virus highly associated with head and neck cancers and respiratory papillomatosis, is also linked with the chronic inflammation that precedes the malignancies (de Visser et al., 2005; Gillison et al., 2012; Bonomi et al., 2014; Fernandes et al., 2015) . Therefore, the role of HPV infection in causing chronic inflammation in the airway and their association to exacerbations of chronic airway inflammatory diseases, which is scarcely explored, should be investigated in the future. Furthermore, viral persistence which lead to continuous expression of antiviral genes may also lead to the development of steroid resistance, which is seen with RV, RSV, and PIV infection (Chi et al., 2011; Ford et al., 2013; Papi et al., 2013) . The use of steroid to suppress the inflammation may also cause the virus to linger longer in the airway due to the lack of antiviral clearance (Kim et al., 2008; Hammond et al., 2015; Hewitt et al., 2016; McKendry et al., 2016; Singanayagam et al., 2019b) . The concomitant development of steroid resistance together with recurring or prolong viral infection thus added considerable burden to the management of acute exacerbation, which should be the future focus of research to resolve the dual complications arising from viral infection.
On the other end of the spectrum, viruses that induce strong type 1 inflammation and cell death such as IFV (Yan et al., 2016; Guibas et al., 2018) and certain CoV (including the recently emerged COVID-19 virus) (Tao et al., 2013; Yue et al., 2018; Zhu et al., 2020) , may not cause prolonged inflammation due to strong induction of antiviral clearance. These infections, however, cause massive damage and cell death to the epithelial barrier, so much so that areas of the epithelium may be completely absent post infection (Yan et al., 2016; Tan et al., 2019) . Factors such as RANTES and CXCL10, which recruit immune cells to induce apoptosis, are strongly induced from IFV infected epithelium (Ampomah et al., 2018; Tan et al., 2019) . Additionally, necroptotic factors such as RIP3 further compounds the cell deaths in IFV infected epithelium . The massive cell death induced may result in worsening of the acute exacerbation due to the release of their cellular content into the airway, further evoking an inflammatory response in the airway (Guibas et al., 2018) . Moreover, the destruction of the epithelial barrier may cause further contact with other pathogens and allergens in the airway which may then prolong exacerbations or results in new exacerbations. Epithelial destruction may also promote further epithelial remodeling during its regeneration as viral infection induces the expression of remodeling genes such as MMPs and growth factors . Infections that cause massive destruction of the epithelium, such as IFV, usually result in severe acute exacerbations with non-classical symptoms of chronic airway inflammatory diseases. Fortunately, annual vaccines are available to prevent IFV infections (Vasileiou et al., 2017; Zheng et al., 2018) ; and it is recommended that patients with chronic airway inflammatory disease receive their annual influenza vaccination as the best means to prevent severe IFV induced exacerbation.
Another mechanism that viral infections may use to drive acute exacerbations is the induction of vasodilation or tight junction opening factors which may increase the rate of infiltration. Infection with a multitude of respiratory viruses causes disruption of tight junctions with the resulting increased rate of viral infiltration. This also increases the chances of allergens coming into contact with airway immune cells. For example, IFV infection was found to induce oncostatin M (OSM) which causes tight junction opening (Pothoven et al., 2015; Tian et al., 2018) . Similarly, RV and RSV infections usually cause tight junction opening which may also increase the infiltration rate of eosinophils and thus worsening of the classical symptoms of chronic airway inflammatory diseases (Sajjan et al., 2008; Kast et al., 2017; Kim et al., 2018) . In addition, the expression of vasodilating factors and fluid homeostatic factors such as angiopoietin-like 4 (ANGPTL4) and bactericidal/permeabilityincreasing fold-containing family member A1 (BPIFA1) are also associated with viral infections and pneumonia development, which may worsen inflammation in the lower airway Akram et al., 2018) . These factors may serve as targets to prevent viral-induced exacerbations during the management of acute exacerbation of chronic airway inflammatory diseases.
Another recent area of interest is the relationship between asthma and COPD exacerbations and their association with the airway microbiome. The development of chronic airway inflammatory diseases is usually linked to specific bacterial species in the microbiome which may thrive in the inflamed airway environment (Diver et al., 2019) . In the event of a viral infection such as RV infection, the effect induced by the virus may destabilize the equilibrium of the microbiome present (Molyneaux et al., 2013; Kloepfer et al., 2014; Kloepfer et al., 2017; Jubinville et al., 2018; van Rijn et al., 2019) . In addition, viral infection may disrupt biofilm colonies in the upper airway (e.g., Streptococcus pneumoniae) microbiome to be release into the lower airway and worsening the inflammation (Marks et al., 2013; Chao et al., 2014) . Moreover, a viral infection may also alter the nutrient profile in the airway through release of previously inaccessible nutrients that will alter bacterial growth (Siegel et al., 2014; Mallia et al., 2018) . Furthermore, the destabilization is further compounded by impaired bacterial immune response, either from direct viral influences, or use of corticosteroids to suppress the exacerbation symptoms (Singanayagam et al., 2018 (Singanayagam et al., , 2019a Wang et al., 2018; Finney et al., 2019) . All these may gradually lead to more far reaching effect when normal flora is replaced with opportunistic pathogens, altering the inflammatory profiles (Teo et al., 2018) . These changes may in turn result in more severe and frequent acute exacerbations due to the interplay between virus and pathogenic bacteria in exacerbating chronic airway inflammatory diseases (Wark et al., 2013; Singanayagam et al., 2018) . To counteract these effects, microbiome-based therapies are in their infancy but have shown efficacy in the treatments of irritable bowel syndrome by restoring the intestinal microbiome (Bakken et al., 2011) . Further research can be done similarly for the airway microbiome to be able to restore the microbiome following disruption by a viral infection.
Viral infections can cause the disruption of mucociliary function, an important component of the epithelial barrier. Ciliary proteins FIGURE 2 | Changes in the upper airway epithelium contributing to viral exacerbation in chronic airway inflammatory diseases. The upper airway epithelium is the primary contact/infection site of most respiratory viruses. Therefore, its infection by respiratory viruses may have far reaching consequences in augmenting and synergizing current and future acute exacerbations. The destruction of epithelial barrier, mucociliary function and cell death of the epithelial cells serves to increase contact between environmental triggers with the lower airway and resident immune cells. The opening of tight junction increasing the leakiness further augments the inflammation and exacerbations. In addition, viral infections are usually accompanied with oxidative stress which will further increase the local inflammation in the airway. The dysregulation of inflammation can be further compounded by modulation of miRNAs and epigenetic modification such as DNA methylation and histone modifications that promote dysregulation in inflammation. Finally, the change in the local airway environment and inflammation promotes growth of pathogenic bacteria that may replace the airway microbiome. Furthermore, the inflammatory environment may also disperse upper airway commensals into the lower airway, further causing inflammation and alteration of the lower airway environment, resulting in prolong exacerbation episodes following viral infection.
Viral specific trait contributing to exacerbation mechanism (with literature evidence) Oxidative stress ROS production (RV, RSV, IFV, HSV)
As RV, RSV, and IFV were the most frequently studied viruses in chronic airway inflammatory diseases, most of the viruses listed are predominantly these viruses. However, the mechanisms stated here may also be applicable to other viruses but may not be listed as they were not implicated in the context of chronic airway inflammatory diseases exacerbation (see text for abbreviations).
that aid in the proper function of the motile cilia in the airways are aberrantly expressed in ciliated airway epithelial cells which are the major target for RV infection (Griggs et al., 2017) . Such form of secondary cilia dyskinesia appears to be present with chronic inflammations in the airway, but the exact mechanisms are still unknown (Peng et al., , 2019 Qiu et al., 2018) . Nevertheless, it was found that in viral infection such as IFV, there can be a change in the metabolism of the cells as well as alteration in the ciliary gene expression, mostly in the form of down-regulation of the genes such as dynein axonemal heavy chain 5 (DNAH5) and multiciliate differentiation And DNA synthesis associated cell cycle protein (MCIDAS) (Tan et al., 2018b . The recently emerged Wuhan CoV was also found to reduce ciliary beating in infected airway epithelial cell model (Zhu et al., 2020) . Furthermore, viral infections such as RSV was shown to directly destroy the cilia of the ciliated cells and almost all respiratory viruses infect the ciliated cells (Jumat et al., 2015; Yan et al., 2016; Tan et al., 2018a) . In addition, mucus overproduction may also disrupt the equilibrium of the mucociliary function following viral infection, resulting in symptoms of acute exacerbation (Zhu et al., 2009) . Hence, the disruption of the ciliary movement during viral infection may cause more foreign material and allergen to enter the airway, aggravating the symptoms of acute exacerbation and making it more difficult to manage. The mechanism of the occurrence of secondary cilia dyskinesia can also therefore be explored as a means to limit the effects of viral induced acute exacerbation.
MicroRNAs (miRNAs) are short non-coding RNAs involved in post-transcriptional modulation of biological processes, and implicated in a number of diseases (Tan et al., 2014) . miRNAs are found to be induced by viral infections and may play a role in the modulation of antiviral responses and inflammation (Gutierrez et al., 2016; Deng et al., 2017; Feng et al., 2018) . In the case of chronic airway inflammatory diseases, circulating miRNA changes were found to be linked to exacerbation of the diseases (Wardzynska et al., 2020) . Therefore, it is likely that such miRNA changes originated from the infected epithelium and responding immune cells, which may serve to further dysregulate airway inflammation leading to exacerbations. Both IFV and RSV infections has been shown to increase miR-21 and augmented inflammation in experimental murine asthma models, which is reversed with a combination treatment of anti-miR-21 and corticosteroids (Kim et al., 2017) . IFV infection is also shown to increase miR-125a and b, and miR-132 in COPD epithelium which inhibits A20 and MAVS; and p300 and IRF3, respectively, resulting in increased susceptibility to viral infections (Hsu et al., 2016 (Hsu et al., , 2017 . Conversely, miR-22 was shown to be suppressed in asthmatic epithelium in IFV infection which lead to aberrant epithelial response, contributing to exacerbations (Moheimani et al., 2018) . Other than these direct evidence of miRNA changes in contributing to exacerbations, an increased number of miRNAs and other non-coding RNAs responsible for immune modulation are found to be altered following viral infections (Globinska et al., 2014; Feng et al., 2018; Hasegawa et al., 2018) . Hence non-coding RNAs also presents as targets to modulate viral induced airway changes as a means of managing exacerbation of chronic airway inflammatory diseases. Other than miRNA modulation, other epigenetic modification such as DNA methylation may also play a role in exacerbation of chronic airway inflammatory diseases. Recent epigenetic studies have indicated the association of epigenetic modification and chronic airway inflammatory diseases, and that the nasal methylome was shown to be a sensitive marker for airway inflammatory changes (Cardenas et al., 2019; Gomez, 2019) . At the same time, it was also shown that viral infections such as RV and RSV alters DNA methylation and histone modifications in the airway epithelium which may alter inflammatory responses, driving chronic airway inflammatory diseases and exacerbations (McErlean et al., 2014; Pech et al., 2018; Caixia et al., 2019) . In addition, Spalluto et al. (2017) also showed that antiviral factors such as IFNγ epigenetically modifies the viral resistance of epithelial cells. Hence, this may indicate that infections such as RV and RSV that weakly induce antiviral responses may result in an altered inflammatory state contributing to further viral persistence and exacerbation of chronic airway inflammatory diseases (Spalluto et al., 2017) .
Finally, viral infection can result in enhanced production of reactive oxygen species (ROS), oxidative stress and mitochondrial dysfunction in the airway epithelium (Kim et al., 2018; Mishra et al., 2018; Wang et al., 2018) . The airway epithelium of patients with chronic airway inflammatory diseases are usually under a state of constant oxidative stress which sustains the inflammation in the airway (Barnes, 2017; van der Vliet et al., 2018) . Viral infections of the respiratory epithelium by viruses such as IFV, RV, RSV and HSV may trigger the further production of ROS as an antiviral mechanism Aizawa et al., 2018; Wang et al., 2018) . Moreover, infiltrating cells in response to the infection such as neutrophils will also trigger respiratory burst as a means of increasing the ROS in the infected region. The increased ROS and oxidative stress in the local environment may serve as a trigger to promote inflammation thereby aggravating the inflammation in the airway (Tiwari et al., 2002) . A summary of potential exacerbation mechanisms and the associated viruses is shown in Figure 2 and Table 1 .
While the mechanisms underlying the development and acute exacerbation of chronic airway inflammatory disease is extensively studied for ways to manage and control the disease, a viral infection does more than just causing an acute exacerbation in these patients. A viral-induced acute exacerbation not only induced and worsens the symptoms of the disease, but also may alter the management of the disease or confer resistance toward treatments that worked before. Hence, appreciation of the mechanisms of viral-induced acute exacerbations is of clinical significance to devise strategies to correct viral induce changes that may worsen chronic airway inflammatory disease symptoms. Further studies in natural exacerbations and in viral-challenge models using RNA-sequencing (RNA-seq) or single cell RNA-seq on a range of time-points may provide important information regarding viral pathogenesis and changes induced within the airway of chronic airway inflammatory disease patients to identify novel targets and pathway for improved management of the disease. Subsequent analysis of functions may use epithelial cell models such as the air-liquid interface, in vitro airway epithelial model that has been adapted to studying viral infection and the changes it induced in the airway (Yan et al., 2016; Boda et al., 2018; Tan et al., 2018a) . Animal-based diseased models have also been developed to identify systemic mechanisms of acute exacerbation (Shin, 2016; Gubernatorova et al., 2019; Tanner and Single, 2019) . Furthermore, the humanized mouse model that possess human immune cells may also serves to unravel the immune profile of a viral infection in healthy and diseased condition (Ito et al., 2019; Li and Di Santo, 2019) . For milder viruses, controlled in vivo human infections can be performed for the best mode of verification of the associations of the virus with the proposed mechanism of viral induced acute exacerbations . With the advent of suitable diseased models, the verification of the mechanisms will then provide the necessary continuation of improving the management of viral induced acute exacerbations.
In conclusion, viral-induced acute exacerbation of chronic airway inflammatory disease is a significant health and economic burden that needs to be addressed urgently. In view of the scarcity of antiviral-based preventative measures available for only a few viruses and vaccines that are only available for IFV infections, more alternative measures should be explored to improve the management of the disease. Alternative measures targeting novel viral-induced acute exacerbation mechanisms, especially in the upper airway, can serve as supplementary treatments of the currently available management strategies to augment their efficacy. New models including primary human bronchial or nasal epithelial cell cultures, organoids or precision cut lung slices from patients with airways disease rather than healthy subjects can be utilized to define exacerbation mechanisms. These mechanisms can then be validated in small clinical trials in patients with asthma or COPD. Having multiple means of treatment may also reduce the problems that arise from resistance development toward a specific treatment. | What is an example of this? | false | 3,989 | {
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2,526 | Epidemiological research priorities for public health control of the ongoing global novel coronavirus (2019-nCoV) outbreak
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7029449/
SHA: 90de2d957e1960b948b8c38c9877f9eca983f9eb
Authors: Cowling, Benjamin J; Leung, Gabriel M
Date: 2020-02-13
DOI: 10.2807/1560-7917.es.2020.25.6.2000110
License: cc-by
Abstract: Infections with 2019-nCoV can spread from person to person, and in the earliest phase of the outbreak the basic reproductive number was estimated to be around 2.2, assuming a mean serial interval of 7.5 days [2]. The serial interval was not precisely estimated, and a potentially shorter mean serial interval would have corresponded to a slightly lower basic reproductive number. Control measures and changes in population behaviour later in January should have reduced the effective reproductive number. However, it is too early to estimate whether the effective reproductive number has been reduced to below the critical threshold of 1 because cases currently being detected and reported would have mostly been infected in mid- to late-January. Average delays between infection and illness onset have been estimated at around 5–6 days, with an upper limit of around 11-14 days [2,5], and delays from illness onset to laboratory confirmation added a further 10 days on average [2].
Text: It is now 6 weeks since Chinese health authorities announced the discovery of a novel coronavirus (2019-nCoV) [1] causing a cluster of pneumonia cases in Wuhan, the major transport hub of central China. The earliest human infections had occurred by early December 2019, and a large wet market in central Wuhan was linked to most, but not all, of the initial cases [2] . While evidence from the initial outbreak investigations seemed to suggest that 2019-nCoV could not easily spread between humans [3] , it is now very clear that infections have been spreading from person to person [2] . We recently estimated that more than 75,000 infections may have occurred in Wuhan as at 25 January 2020 [4] , and increasing numbers of infections continue to be detected in other cities in mainland China and around the world. A number of important characteristics of 2019-nCoV infection have already been identified, but in order to calibrate public health responses we need improved information on transmission dynamics, severity of the disease, immunity, and the impact of control and mitigation measures that have been applied to date.
Infections with 2019-nCoV can spread from person to person, and in the earliest phase of the outbreak the basic reproductive number was estimated to be around 2.2, assuming a mean serial interval of 7.5 days [2] . The serial interval was not precisely estimated, and a potentially shorter mean serial interval would have corresponded to a slightly lower basic reproductive number. Control measures and changes in population behaviour later in January should have reduced the effective reproductive number. However, it is too early to estimate whether the effective reproductive number has been reduced to below the critical threshold of 1 because cases currently being detected and reported would have mostly been infected in mid-to late-January. Average delays between infection and illness onset have been estimated at around 5-6 days, with an upper limit of around 11-14 days [2, 5] , and delays from illness onset to laboratory confirmation added a further 10 days on average [2] .
Chains of transmission have now been reported in a number of locations outside of mainland China. Within the coming days or weeks it will become clear whether sustained local transmission has been occurring in other cities outside of Hubei province in China, or in other countries. If sustained transmission does occur in other locations, it would be valuable to determine whether there is variation in transmissibility by location, for example because of different behaviours or control measures, or because of different environmental conditions. To address the latter, virus survival studies can be done in the laboratory to confirm whether there are preferred ranges of temperature or humidity for 2019-nCoV transmission to occur.
In an analysis of the first 425 confirmed cases of infection, 73% of cases with illness onset between 12 and 22 January reported no exposure to either a wet market or another person with symptoms of a respiratory illness [2] . The lack of reported exposure to another ill person could be attributed to lack of awareness or recall bias, but China's health minister publicly warned that pre-symptomatic transmission could be occurring [6] . Determining the extent to which asymptomatic or pre-symptomatic transmission might be occurring is an urgent priority, because it has direct implications for public health and hospital infection control. Data on viral shedding dynamics could help in assessing duration of infectiousness. For severe acute respiratory syndrome-related coronavirus (SARS-CoV), infectivity peaked at around 10 days after illness onset [7] , consistent with the peak in viral load at around that time [8] . This allowed control of the SARS epidemic through prompt detection of cases and strict isolation. For influenza virus infections, virus shedding is highest on the day of illness onset and relatively higher from shortly before symptom onset until a few days after onset [9] . To date, transmission patterns of 2019-nCoV appear more similar to influenza, with contagiousness occurring around the time of symptom onset, rather than SARS.
Transmission of respiratory viruses generally happens through large respiratory droplets, but some respiratory viruses can spread through fine particle aerosols [10] , and indirect transmission via fomites can also play a role. Coronaviruses can also infect the human gastrointestinal tract [11, 12] , and faecal-oral transmission might also play a role in this instance. The SARS-CoV superspreading event at Amoy Gardens where more than 300 cases were infected was attributed to faecal-oral, then airborne, spread through pressure differentials between contaminated effluent pipes, bathroom floor drains and flushing toilets [13] . The first large identifiable superspreading event during the present 2019-nCoV outbreak has apparently taken place on the Diamond Princess cruise liner quarantined off the coast of Yokohama, Japan, with at least 130 passengers tested positive for 2019-nCoV as at 10 February 2020 [14] . Identifying which modes are important for 2019-nCoV transmission would inform the importance of personal protective measures such as face masks (and specifically which types) and hand hygiene.
The first human infections were identified through a surveillance system for pneumonia of unknown aetiology, and all of the earliest infections therefore had Modelling studies incorporating healthcare capacity and processes pneumonia. It is well established that some infections can be severe, particularly in older adults with underlying medical conditions [15, 16] , but based on the generally mild clinical presentation of 2019-nCoV cases detected outside China, it appears that there could be many more mild infections than severe infections. Determining the spectrum of clinical manifestations of 2019-nCoV infections is perhaps the most urgent research priority, because it determines the strength of public health response required. If the seriousness of infection is similar to the 1918/19 Spanish influenza, and therefore at the upper end of severity scales in influenza pandemic plans, the same responses would be warranted for 2019-nCoV as for the most severe influenza pandemics. If, however, the seriousness of infection is similar to seasonal influenza, especially during milder seasons, mitigation measures could be tuned accordingly.
Beyond a robust assessment of overall severity, it is also important to determine high risk groups. Infections would likely be more severe in older adults, obese individuals or those with underlying medical conditions, but there have not yet been reports of severity of infections in pregnant women, and very few cases have been reported in children [2] .
Those under 18 years are a critical group to study in order to tease out the relative roles of susceptibility vs severity as possible underlying causes for the very rare recorded instances of infection in this age group. Are children protected from infection or do they not fall ill after infection? If they are naturally immune, which is unlikely, we should understand why; otherwise, even if they do not show symptoms, it is important to know if they shed the virus. Obviously, the question about virus shedding of those being infected but asymptomatic leads to the crucial question of infectivity. Answers to these questions are especially pertinent as basis for decisions on school closure as a social distancing intervention, which can be hugely disruptive not only for students but also because of its knock-on effect for child care and parental duties. Very few children have been confirmed 2019-nCoV cases so far but that does not necessarily mean that they are less susceptible or that they could not be latent carriers. Serosurveys in affected locations could inform this, in addition to truly assessing the clinical severity spectrum.
Another question on susceptibility is regarding whether 2019-nCoV infection confers neutralising immunity, usually but not always, indicated by the presence of neutralising antibodies in convalescent sera. Some experts already questioned whether the 2019-nCoV may behave similarly to MERS-CoV in cases exhibiting mild symptoms without eliciting neutralising antibodies [17] . A separate question pertains to the possibility of antibody-dependent enhancement of infection or of disease [18, 19] . If either of these were to be relevant, the transmission dynamics could become more complex.
A wide range of control measures can be considered to contain or mitigate an emerging infection such as 2019-nCoV. Internationally, the past week has seen an increasing number of countries issue travel advisories or outright entry bans on persons from Hubei province or China as a whole, as well as substantial cuts in flights to and from affected areas out of commercial considerations. Evaluation of these mobility restrictions can confirm their potential effectiveness in delaying local epidemics [20] , and can also inform when as well as how to lift these restrictions.
If and when local transmission begins in a particular location, a variety of community mitigation measures can be implemented by health authorities to reduce transmission and thus reduce the growth rate of an epidemic, reduce the height of the epidemic peak and the peak demand on healthcare services, as well as reduce the total number of infected persons [21] . A number of social distancing measures have already been implemented in Chinese cities in the past few weeks including school and workplace closures. It should now be an urgent priority to quantify the effects of these measures and specifically whether they can reduce the effective reproductive number below 1, because this will guide the response strategies in other locations. During the 1918/19 influenza pandemic, cities in the United States, which implemented the most aggressive and sustained community measures were the most successful ones in mitigating the impact of that pandemic [22] .
Similarly to international travel interventions, local social distancing measures should be assessed for their impact and when they could be safely discontinued, albeit in a coordinated and deliberate manner across China such that recrudescence in the epidemic curve is minimised. Mobile telephony global positioning system (GPS) data and location services data from social media providers such as Baidu and Tencent in China could become the first occasion when these data inform outbreak control in real time.
At the individual level, surgical face masks have often been a particularly visible image from affected cities in China. Face masks are essential components of personal protective equipment in healthcare settings, and should be recommended for ill persons in the community or for those who care for ill persons. However, there is now a shortage of supply of masks in China and elsewhere, and debates are ongoing about their protective value for uninfected persons in the general community.
The Table summarises research gaps to guide the public health response identified.
In conclusion, there are a number of urgent research priorities to inform the public health response to the global spread of 2019-nCoV infections. Establishing robust estimates of the clinical severity of infections is probably the most pressing, because flattening out the surge in hospital admissions would be essential if there is a danger of hospitals becoming overwhelmed with patients who require inpatient care, not only for those infected with 2019-nCoV but also for urgent acute care of patients with other conditions including those scheduled for procedures and operations. In addressing the research gaps identified here, there is a need for strong collaboration of a competent corps of epidemiological scientists and public health workers who have the flexibility to cope with the surge capacity required, as well as support from laboratories that can deliver on the ever rising demand for diagnostic tests for 2019-nCoV and related sequelae. The readiness survey by Reusken et al. in this issue of Eurosurveillance testifies to the rapid response and capabilities of laboratories across Europe should the outbreak originating in Wuhan reach this continent [23] .
In the medium term, we look towards the identification of efficacious pharmaceutical agents to prevent and treat what may likely become an endemic infection globally. Beyond the first year, one interesting possibility in the longer term, perhaps borne of wishful hope, is that after the first few epidemic waves, the subsequent endemic re-infections could be of milder severity. Particularly if children are being infected and are developing immunity hereafter, 2019-nCoV could optimistically become the fifth human coronavirus causing the common cold.
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1,687 | Interactome analysis of the lymphocytic choriomeningitis virus nucleoprotein in infected cells reveals ATPase Na(+)/K(+) transporting subunit Alpha 1 and prohibitin as host-cell factors involved in the life cycle of mammarenaviruses
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5834214/
SHA: efbd0dfc426da5dd25ce29411d6fa37571623773
Authors: Iwasaki, Masaharu; Minder, Petra; Caì, Yíngyún; Kuhn, Jens H.; Yates, John R.; Torbett, Bruce E.; de la Torre, Juan C.
Date: 2018-02-20
DOI: 10.1371/journal.ppat.1006892
License: cc0
Abstract: Several mammalian arenaviruses (mammarenaviruses) cause hemorrhagic fevers in humans and pose serious public health concerns in their endemic regions. Additionally, mounting evidence indicates that the worldwide-distributed, prototypic mammarenavirus, lymphocytic choriomeningitis virus (LCMV), is a neglected human pathogen of clinical significance. Concerns about human-pathogenic mammarenaviruses are exacerbated by of the lack of licensed vaccines, and current anti-mammarenavirus therapy is limited to off-label use of ribavirin that is only partially effective. Detailed understanding of virus/host-cell interactions may facilitate the development of novel anti-mammarenavirus strategies by targeting components of the host-cell machinery that are required for efficient virus multiplication. Here we document the generation of a recombinant LCMV encoding a nucleoprotein (NP) containing an affinity tag (rLCMV/Strep-NP) and its use to capture the NP-interactome in infected cells. Our proteomic approach combined with genetics and pharmacological validation assays identified ATPase Na(+)/K(+) transporting subunit alpha 1 (ATP1A1) and prohibitin (PHB) as pro-viral factors. Cell-based assays revealed that ATP1A1 and PHB are involved in different steps of the virus life cycle. Accordingly, we observed a synergistic inhibitory effect on LCMV multiplication with a combination of ATP1A1 and PHB inhibitors. We show that ATP1A1 inhibitors suppress multiplication of Lassa virus and Candid#1, a live-attenuated vaccine strain of Junín virus, suggesting that the requirement of ATP1A1 in virus multiplication is conserved among genetically distantly related mammarenaviruses. Our findings suggest that clinically approved inhibitors of ATP1A1, like digoxin, could be repurposed to treat infections by mammarenaviruses pathogenic for humans.
Text: Introduction Mammarenaviruses (Arenaviridae: Mammarenavirus) cause chronic infections of rodents worldwide [1] . Invasion of human dwellings by infected rodents can result in human infections through mucosal exposure to aerosols or by direct contact of abraded skin with infectious material. Several mammarenaviruses cause viral hemorrhagic fevers (VHFs) in humans and pose important public health problems in their endemic areas [2] [3] [4] [5] [6] . Mammarenaviruses are classified into two main groups, Old World (OW) and New World (NW) [1] . The OW Lassa virus (LASV), causative agent of Lassa fever (LF), is the most significant OW mammarenaviral pathogen. LASV is estimated to infect several hundred thousand individuals annually in Western Africa, resulting in a high number of LF cases associated with high morbidity and lethality. Moreover, LASV endemic regions are expanding [7] , and the association of the recently identified mammarenavirus Lujo virus with a VHF outbreak in Southern Africa [8, 9] has raised concerns about the emergence of novel VHF-causing mammarenaviruses. The most significant NW mammarenavirus is Junín virus (JUNV), which causes Argentinian hemorrhagic fever [10] . The worldwide-distributed OW mammarenavirus lymphocytic choriomeningitis virus (LCMV) is a neglected human pathogen of clinical significance especially in congenital infections [11] [12] [13] [14] [15] . Moreover, LCMV poses a particular threat to immunocompromised individuals, as has been illustrated by fatal cases of LCMV infection associated with organ transplants [16, 17] . However, LCMV research can be safely performed at BSL-2 containment, rather than the BSL-4 containment necessary for live LASV or JUNV research [18] .
No US Food and Drug Administration (FDA)-licensed vaccines are available for the treatment of arenavirus infections, although a live attenuated vaccine strain of JUNV, Candid#1, is licensed in Argentina. Likewise, current anti-mammarenavirus therapy is limited to an offlabel use of the nucleoside analogue ribavirin that is only partially effective and can cause significant side effects [19] [20] [21] . Development of effective anti-mammarenavirus drugs has been hampered by the lack of detailed understanding of virus/host-cell interactions required for mammarenavirus multiplication that could represent amenable targets for antiviral therapy. the potential problem that overexpression of a single viral gene product may potentiate PPI interactions that are not relevant during the course of a natural virus infection. To overcome this issue, we designed a recombinant LCMV (rLCMV) encoding a tandem [WSHPQFEK (GGGS) 3 WSHPQFEK] Strep-tag fused to the amino-terminus of NP (rLCMV/Strep-NP) (Fig 1A and 1B) . To facilitate the identification of specific PPI between NP and host cell proteins, we used our mammarenavirus tri-segmented (r3) platform [30] to design an r3LCMV expressing a C-terminus Strep-tag version of enhanced green fluorescent protein (r3LCMV/eGFP-Strep) that we used as a negative control (Fig 1A and 1B) . We rescued rLCMV/Strep-NP and r3LCMV/eGFP-Strep and confirmed the expression of strep-tagged NP and eGFP in rLCMV/ Strep-NP-and r3LCMV/eGFP-Strep-infected cells, respectively (Fig 1C) . Next, we examined the growth properties of rLCMV/Strep-NP and r3LCMV/eGFP-Strep in three different cells lines from hamsters, humans, and nonhuman primates (BHK-21, A549, and Vero E6 cells, respectively) (Fig 1D) . The fitness of rLCMV/Strep-NP and r3LCMV/eGFP-Strep was modestly decreased compared to that observed with wild-type (WT) Armstrong (rLCMV ARM) and Clone 13 (rLCMV Cl-13) strains of LCMV. However, both rLCMV/Strep-NP and r3LCMV/eGFP-Strep had WT-like growth kinetics and reached high titers. As with WT LCMV, infection with rLCMV/Strep-NP prevented production of bioactive IFN-I by cells in response to Sendai virus (SeV) infection as determined using an IFN bioassay based on protection against the cytopathic effect (CPE) induced by infection with vesicular stomatitis virus (VSV) (Fig 1E) . Vero cells treated for 16 h with tissue cultured supernatants (TCS) from A549 cells infected first with WT LCMV or rLCMV/Strep, followed by 24 h infection with SeV, remained fully susceptible to VSV-induced CPE. In contrast, Vero cells treated with TCS from A549 cells infected with rLCMV/NP(D382A), a mutant unable to prevent induction of IFN-I [30] , and subsequently with SeV, were protected against VSV induced CPE.
We selected the human A549 cell line because lung epithelial cells are one of the initial cell targets of humans following inhalation of mammarenavirions. We infected A549 cells (multiplicity of infection [MOI] = 0.1) with either rLCMV/Strep-NP or r3LCMV/eGFP-Strep (Fig 2A) . At 48 h post-inoculation (pi), we prepared total cell lysates for pull-down (PD) assays using a sepharose resin coated with strep-tactin. Aliquots of the protein complexes present in the PD samples were fractionated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) (Fig 2B) followed by SYPRO Ruby protein gel staining. We compared the pattern of stained protein bands detected between rLCMV/Strep-NP-and r3LCMV/eGFP-Strepinfected samples and confirmed the presence of Strep-NP and eGFP-Strep in pertinent samples (Fig 2B) . Protein complexes in the rest of eluates from the PD samples were concentrated by trichloroacetic acid (TCA) precipitation and subjected to trypsin digestion (Fig 2A) . Digested peptides were subjected to liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis using a hybrid mass spectrometer consisting of linear quadrupole ion dual cell trap (LTQ) Velos and an Orbitrap analyser.
We classified host-cell proteins identified by LC-MS/MS analysis from two independent biological replicates into two groups: 1) proteins found only in Strep-NP PD samples with at least five spectral counts ( Table 1) , and 2) proteins found in both Strep-NP and eGFP-Strep PD samples with five or higher spectral counts in Strep-NP samples and at least 2-fold higher spectral counts in Strep-NP PD compared to eGFP PD samples ( Table 2) . Filtering the data using these criteria resulted in identification of 139 candidate host-cell proteins as NP-interacting partners. Among 53 proteins found present in both NP-and eGFP-PD samples, 36 had spectral counts in the NP-PD sample that were less than two-fold higher than their corresponding spectral counts in the eGFP-PD sample (Fig 2C and S1 Table) . Based on the criteria we described above, we considered these proteins to be highly unlikely specific NPinteractors with an involvement in the LCMV life cycle, and therefore we did not consider these hits for further analysis. However, we acknowledge that we cannot formally rule out that some of these hits could still play a role on the life cycle of LCMV.
The protein annotation through evolutionary relationship (PANTHER) protein family classification (Biological Process) of the NP-interacting protein candidates revealed that a large number of proteins were involved in metabolic and cellular processes (Fig 2D) . We also analyzed the molecular functions of the NP-interacting protein candidates according to the PAN-THER protein profile classification (Fig 2E) , which revealed diversified biochemical functions enriched for nucleic acid-binding proteins and chaperones.
To initially assess pro-or anti-viral roles of NP-interacting host-cell proteins identified by LC-MS/MS, we examined the effect of small interfering RNA (siRNA)-mediated knockdown (kd) of each of the corresponding genes on multiplication of rLCMV expressing reporter gene ZsGreen (ZsG) in A549 cells (Fig 3A) . The siRNAs we used were from the genome-wide ON TARGET-Plus (OTP) Human siRNA library (18,301 genes, 4 siRNAs/gene). OTPs are latest generation of siRNAs and offer significant advantages over previous generations. Off-target effects are primarily driven by antisense strand microRNA (miR)-like seed activity. In OTPs, the sense strand is modified to favor antisense strand uptake whereas the antisense strand seed region is modified to drastically reduce seed-related off-targeting [33] . In addition, OTPs are designed on the foundation of the SMARTselection algorithm (Dharmacon), widely considered to be the best algorithm for rational siRNA design strategy. Numerous host-cell factors showed an anti-LCMV effect (increased ZsG expression by kd of the genes), including microtubule-associated protein 1B (MAP1B) [ [38] , dengue virus 2 (DENV-2) [39] , and chikungunya virus (CHIKV) [40] .
To begin assessing the potential biological implications of the identified NP-host cell protein interactions, we selected ATP1A1 and PHB given the availability of reagents, existing knowledge about their roles in cell physiology, and evidence of participation in multiplication of other viruses. We confirmed that cells transfected with siRNA specific to ATP1A1 and PHB exhibited the predicted reduced levels in ATP1A1 and PHB protein expression (Fig 3B) . Likewise, we examined whether siRNA-mediated reduced expression levels of ZsGreen correlated with reduced LCMV progeny titers. For this, we transfected A549 cells with siRNA targeting Expression of Strep-tagged proteins. A549 cells seeded (5.0 x 10 5 cells/well) in a 6-well plate and cultured overnight were infected (MOI = 0.1) with the indicated rLCMVs. At 48 h pi, total cell lysates were prepared, and protein expression was analyzed by western blotting. (D) Growth properties of rLCMV expressing Strep-tagged proteins. BHK-21 (1.75 x 10 5 cells/well), A549 (1.25 x 10 5 cells/well), or Vero E6 (1.25 x 10 5 cells/well) cells seeded in 24-well plates and cultured overnight were infected (MOI = 0.01) with the indicated rLCMVs. At the indicated times pi, TCSs were collected and virus titers determined by IFFA. Results represent means ± SD of the results of three independent experiments. (E) Lack of induction of IFN-I in cells infected with rLCMV/Strep-NP. A549 cells were infected (MOI = 0.1) with the indicated rLCMV or mock-infected, and 36 h later infected with SeV (MOI = 1). At 24 h pi with SeV, TCS were collected and used, following virus inactivation by U.V., to treat Vero E6 cells for 16 h, followed by infection with rVSV (MOI = 0.1) [rVSV(+)] or mockinfection [rVSV (-) ]. At 24 h pi with rVSV, cells were fixed with 4% PFA and stained with crystal violet to assess rVSV-induced cytopathic effect. We used as control rLCMV/NP(D382A) that contains mutation D382A within NP, which has been shown to abrogate the NP's ability to counteract the induction of IFN-I production.
https://doi.org/10.1371/journal.ppat.1006892.g001 ATP1A1 or with NC siRNA 72 h prior to infection with rLCMV/ZsG. We found that siRNAmediated kd of ATP1A1 dramatically inhibited ZsGreen expression (Fig 3Ci) , which was associated with a significant reduction of infectious LCMV progeny (Fig 3Cii) . Our attempts to see interaction between NP and ATP1A1 or NP and PHB by co-immunoprecipitation were unsuccessful. Several possibilities could account for this, including interactions of low affinity or high on/off rate or both. Another consideration is that only a minor fraction of NP might be engaged in the interaction with a given host cell protein, and therefore, detection of these interactions would require highly sensitive methods such as LC-MS/MS. To overcome this problem we used confocal microscopy to examine the co-localization of NP with ATP1A1 and PHB in LCMV-infected cells. Weighted co-localization coefficients (CC), determined by taking into consideration the brightness of each channel signal, were significantly higher than non-weighted CC, indicating the presence of brighter pixels in the co-localized regions compared to the non-co-localized regions (Fig 4) .
The cardiac glycoside ouabain is an inhibitor of ATP1A1 that has been used to treat congestive heart failure in European countries [41] . The PHB inhibitor rocaglamide is a flavagline from an Aglaia tree used in traditional Chinese medicine [42] that has potent anticancer activity [43] . To examine whether pharmacological inhibition of ATP1A1 or PHB inhibited LCMV multiplication, we pretreated human (A549 and HEK 293T), nonhuman primate (Vero E6), and rodent (murine L929 and hamster BHK-21) cells with ouabain or rocaglamide and infected them with rLCMV/eGFP (S1 Fig). Ouabain treatment resulted in a strong dosedependent inhibition of eGFP expression in infected human-and nonhuman primate cells, but did not affect eGFP expression intensity in infected rodent cells (S1A Fig) . This finding is consistent with rodents expressing an ATP1A1 allele that is resistant to ouabain inhibition [44] .
Likewise, we observed a dose-dependent rocaglamide inhibition of eGFP expression in all cell lines infected with rLCMV/eGFP (S1B Fig) . Consistent with these findings, production of infectious LCMV progeny was reduced by treatment with either ouabain or rocaglamide ( Fig 5A) within a concentration range that had minimal impact on cell viability (Fig 5B) . To examine the correlation between efficacy and cytotoxicity of these compounds, we determined their therapeutic index (TI = CC 50 /IC 50 (Fig 5Bi) ; whereas rocaglamide had TIs of >105 (CC 50 > 1000 nM, IC 50 = 9.51 nM) and 10.3 (CC 50 = 100 nM, IC 50 = 9.75 nM) in A549 and Vero E6 cells, respectively (Fig 5Bii) . Moreover, the ATP1A1 antagonist inhibitor, bufalin, also exhibited robust anti-LCMV activity with TIs of 8.92 (CC 50 Heat shock protein HSP 90-alpha HSP90AA1 P07900 8 10 9
Endoplasmin HSP90B1 P14625 9 9 9
Large neutral amino acids transporter small subunit 1 SLC7A5 Q01650 6 12 9
Keratin, type II cuticular Hb1 KRT81 Q14533 10 8 9
Putative helicase MOV-10 MOV10 Q9HCE1 8 10 9
Microtubule-associated protein 1B MAP1B P46821 6 11 8.5
Spectrin beta chain, rocaglamide (100 nM) (Fig 5C) , further supporting a specific anti-LCMV activity of ouabain and rocaglamide that was not due to reduced cell viability.
To gain insights about the mechanisms by which ouabain and rocaglamide exert their anti-LCMV activity, we examined effects of these compounds on distinct steps of the LCMV life cycle. First, we asked whether ouabain and rocaglamide affected cell entry of LCMV. We conducted time-of-addition experiments in which we treated cells with ouabain or rocaglamide prior to virus inoculation (-1.5 h), at the time of inoculation (0 h), or 1.5 h pi (+1.5 h) (Fig 6A) .
In some samples, we used ammonium chloride starting at 4 h pi to block multiple rounds of virus infection. The timing of compound addition did not significantly change the number of eGFP-positive cells, indicating that neither ouabain nor rocaglamide inhibited cell entry of LCMV. The number of eGFP + cells in ouabain-treated cells was reduced at all time-of-addition points compared to vehicle dimethyl sulfoxide (DMSO)-treated cells, but was similar to that observed in ammonium chloride-treated cells. Thus, ouabain did not inhibit LCMV RNA replication and gene expression, but rather a late step of the LCMV life cycle. In contrast, rocaglamide treatment resulted in a negligible number of eGFP + cells, indicating that rocaglamide inhibited virus RNA replication and gene transcription.
To further investigate the effect of ouabain and rocaglamide on virus RNA synthesis, we infected A549 cells with a recombinant single-cycle infectious LCMV expressing eGFP (rLCMVΔGPC/eGFP) and treated cells with either ouabain or rocaglamide. Seventy-two hours later, we determined percent normalized eGFP expression in infected cells (Fig 6B) . Consistent with our results from the time-of-addition experiment, ouabain did not affect reporter eGFP expression. However, rocaglamide reduced eGFP expression, confirming inhibitory effect of rocaglamide on virus RNA synthesis.
We also examined the effect of ouabain and rocaglamide on the late step of the arenavirus life cycle, Z-mediated budding. For this experiment, we transfected cells with Z-Strep-and Z-FLAG (DYKDDDDK epitope)-expressing plasmids from LCMV and LASV, respectively. At 24 h post-transfection, we removed the tissue culture supernatant (TCS) and washed extensively transfected cells to eliminate already budded Z. We cultured the transfected cells in the presence or absence of ouabain or rocaglamide. At 24 h, we determined by WB levels of Z protein in both whole cell lysates and associated with virus-like particles (VLPs) collected from TCS. Treatment with rocaglamide, but not with ouabain, caused a reduction in both LCMV and LASV Z budding efficiency (Fig 6C and 6D) . The reproducibility of these findings was confirmed based on results from four independent experiments (Fig 6E) . We also examined whether ouabain could interfere with a step of assembly of infectious progeny that was not captured by the Z budding assay through two additional experiments. The first experiment involved the use of a newly generated single-cycle infectious recombinant LCMV expressing the reporter gene ZsGreen (scrLCMV/ZsG-P2A-NP) to infect (MOI = 0.1) A549 cells (1 st infection). These cells were subsequently transfected with a plasmid expressing LCMV GPC. After 24 h, we used TCS to infect a fresh cell monolayer (2 nd infection) and identified infected cells based on ZsGreen expression. To assess the effect of ouabain on de novo assembly of infectious progeny we determined normalized ratios (2 nd /1 st infection) of ZsGreen + cells (Fig 6F) . The second experiment involved infection (MOI = 0.1) of cells with WT LCMV, and 48 h later we washed infected cells three times to remove the extracellular infectious progeny produced during the first 48 h of infection. Then, fresh media containing ouabain or DMSO vehicle control were added, and 24 h later we determined virus titers in TCS (Fig 6G) . Results from both experiments consistently showed that ouabain did not inhibit assembly de novo of extracellular infectious virus.
Combination therapy can significantly alleviate the problem posed by the rapid emergence of drug-resistant variants commonly observed during monotherapy strategies to control RNA virus infections. Since ouabain and rocaglamide inhibited different steps of the LCMV life cycle, we examined whether their use in combination results in a synergistic anti-LCMV effect. For this experiment, we infected A549 cells with rLCMV/eGFP and treated them with ouabain and rocaglamide using different concentrations and combinations. At 48 h pi, we determined percent eGFP expression (Fig 7) . Combination treatment with ouabain and rocaglamide resulted in synergistic anti-LCMV activity that was enhanced under conditions using higher concentrations of ouabain and lower concentrations of rocaglamide.
We next asked whether the ATP1A1 and PHB host-cell factors contributed also to multiplication of viral hemorrhagic fever-causing LASV. We treated A549 cells with ouabain, bufalin, or rocaglamide and inoculated the treated cells with recombinant LASV expressing eGFP (rLASV/eGFP). eGFP expression was examined 48 h later. Similar to rLCMV infection, LASV multiplication was restricted in ouabain-, bufalin-, or rocaglamide-treated cells at concentrations minimally impacting cell viability, although their IC 50 values were slightly higher than those found with the LCMV infection system (Fig 5B and S2 Fig) as ouabain had IC 50 of 9.34 nM, bufalin had IC 50 of 1.66 nM and rocaglamide had IC 50 of 37.0 nM (Fig 8) . We also tested the effect of compounds targeting ATP1A1 and PHB on multiplication of JUNV. Consistent with our results obtained with LCMV and LASV, ouabain, bufalin, and rocaglamide strongly suppressed JUNV multiplication (S3 Fig). These findings indicate that ATP1A1 and PHB function as pro-viral factors of a range of mammarenaviruses.
We identified ATP1A1 and PHB as novel host-cell proteins that contribute to efficient multiplication of mammarenaviruses. Our approach using a recombinant LCMV expressing NP with an affinity tag facilitated defining the NP interactome in the context of LCMV infection. Recently, using an NP-specific monoclonal antibody (mAb) to precipitate NP and associated cellular protein partners in a mammarenavirus NP interactome, King et al. identified 348 host proteins that associated with LCMV NP [45] . We found 99 common proteins between our filtered LCMV NP interactome of 171 proteins and the LCMV NP interactome documented by King et al. Differences in both experimental conditions and analysis methodologies used to generate the LCMV NP interactome documented by King et al. and ours likely h post-transfection, cells were washed with fresh media to eliminate Z-mediated production of VLPs in the absence of compound treatment, and cultured for another 24 h in fresh media in the presence of ouabain or Roc-A at the indicated concentrations. VLPs present in TCS were collected by ultracentrifugation, and cell lysates were prepared. Z protein expression in VLPs and cell lysates were determined by western blots using antibodies to Strep-tag (C) and FLAG-tag (D). Budding efficiency for each sample was estimated by dividing the signal intensity of the Z protein associated with VLPs by that of Z detected in the cell lysate. Numbers on the bottom of panel C correspond to LCMV Z budding efficiencies determined in a representative experiment. Results shown in panel E correspond to the average and SD from four independent experiments including the one shown in panel D. The mean budding efficiency of DMSO treatedsamples was set to 100%. Data represent mean ± SD of four independent experiments. (F) Effect of ouabain on incorporation of viral glycoprotein into virions. 293T cells seeded (4.0 x 10 5 cells/well) in a 12-well plate and cultured overnight were infected (MOI = 0.1) with scrLCMV/ZsG (1 st infection) for 2 h and subsequently transfected with 0.5 μg of pC-GPC. At 24 h pi, cells were washed with fresh medium to eliminate infectious virus particle produced in the absence of compound treatment, and cultured for another 24 h in fresh media in the presence of ouabain at 40 nM (OUA). At 48 h pi, TCS was collected and used to infect fresh monolayer of BHK-21 cells (2 nd infection) seeded (4.0 x 10 5 cells/well) in a 12-well plate 1 day before the infection, and 293T cell lysate was prepared. 24 h later, BHK-21 cell lysate was prepared. ZsGreen signal intensity was measured by a fluorescent plate reader. GP-incorporation efficiency was estimated by dividing ZsGreen signal intensity in BHK-21 cell lysate (2 nd ) by that in 293T cell lysate (1 st ). The mean GP-incorporation efficiency of DMSO treated samples was set to 100%. Data represent means ± SD from three independent experiments. contributed to the observed differences between data sets. Despite progress in the implementation of global proteomics-based screens to identify virus-host protein-protein interactions, overlap between datasets for the same viral system is usually limited. However, the substantial overlap of 99 of the 171 NP-interacting proteins from both studies supports the overall reliability of both systems. We used results of the eGFP-Strep interactome, determined in r3LCMV/eGFP-Strep-infected cells, as a control to filter out non-specific NP interactions, which may have resulted in a higher degree of stringency than in the study by King et al for selection of NP-interacting candidates. The combined information provided by the NP interactome reported by King et al. and the one we present in this work, will facilitate future studies to further characterize the functional and biological implications of NP-host cell interacting proteins.
All tested mammarenavirus NPs, with exception of the NP from TCRV, blocked IRF-3-dependent IFN-I induction [25, 46] . The anti-IFN activity of NP was mapped to its C-terminal part and linked to the 3'-5' exonuclease domain present with the NP C-terminal part [30] . Inhibitor-B kinase ε (IKKε) was identified as an NP-binding protein using plasmid-mediated overexpression in transfected cells [47] , and the NP-IKKε binding affinity correlated with NP's ability to inhibit IFN-I induction [47] . We, as well as the work by King et al. [45] , did not detect this NP-IKKε interaction. This discrepancy may have been caused by very low expression of IKKε in LCMV-infected cells, which prevented detection of IKKε by LC-MS/MS. Alternatively, NP-IKKε interaction could possibility be temporarily regulated and take place at early times pi, but could be mostly absent at 48 h pi, the time at which we prepared the cell lysates for our proteomics studies. Future studies comparing the NP interactome at different times during infection will contribute to a better understanding of the dynamics of NP/hostcell protein interactions.
Na + /K + -ATPase is a well-characterized membrane ion transporter and is composed of two functional subunits (α and β) and one regulatory γ subunit [48] . ATP1A1 represents one of four α subunits [49, 50] . Recent evidence has suggested that the Na + /K + -ATPase is involved in multiple cell signaling pathways that are independent of its ion-pumping function [51] . Cardiac glycoside inhibitors of the Na + /K + -ATPase (NKA), so-called cardiotonic steroids (CST; e.g., ouabain, bufalin), have been shown to inhibit multiplication of different viruses including Ebola virus [35], coronaviruses [36], herpes simplex virus 1 [52, 53] , CHIKV [54] , human immunodeficiency virus 1 (HIV-1) [55] , adenovirus [56] and porcine reproductive and respiratory syndrome virus 1 [57] .
Different mechanisms are likely to contribute to the antiviral activity of CSTs, including altered cell functions modulated by the signaling activity of Na + /K + -ATPase [58] . Thus, a low concentration of ouabain induces a conformational change in ATP1A1 that results in activation and release of proto-oncogene tyrosine protein kinase, Src, from ATP1A1, followed by activation of as yet unknown downstream signaling that inhibits, for instance, cell entry of murine hepatitis virus (MHV) [59] . However, our results indicated that ouabain did not interfere with LCMV cell entry. In addition, treatment with the Src inhibitor 4-amino-5-(4-methylphenyl)-7-(t-butyl)pyrazolo [3,4-d] pyrimidine (PP1) did not counteract the anti-LCMV activity of ouabain (S4 Fig). Nevertheless, ATP1A1-mediated Src signaling could plausibly contribute to the inhibitory effect of ouabain on JUNV multiplication as similarly to that observed with MHV. Moreover, cell entry of JUNV occurs also by clathrin-mediated endocytosis [60] , a process affected by Src signaling. Ouabain has been clinically used in several European countries for the management of congestive heart failure, whereas bufalin has been tested in clinical trials for cancer treatments [61] , and the CST digoxin has been FDA-approved since 1997 to treat heart failure and atrial fibrillation. Hence, opportunities for the repurposing CSTs have potential as therapeutics to treat infections caused by viral hemorrhagic fever-causing arenaviruses.
The PHB inhibitor, rocaglamide, appeared to interfere with LCMV RNA synthesis and budding, but did not affect LCMV cell entry. In contrast, PHB was reported to be a cell entry receptor for DENV-2 [39] and CHIKV [40] . On the other hand, PHB did not act as a virus cell entry receptor for HCV. Rather, PHB contributed to HCV cell entry through binding to cellular RAF (c-Raf; proto-oncogene serine/threonine-protein kinase) and subsequent Harvey rat sarcoma proto-oncogene (HRas) activation that induces a signal transduction pathway required for epidermal growth factor receptor (EGFR)-mediated HCV cell entry [37] . In addition, siRNA-mediated kd of PHB decreased production of H5N1 FLUAV [38] . These findings indicate that PHB is involved in different steps of the life cycle of a variety of viruses, and thereby an attractive target for the development of broad-spectrum antiviral drugs.
Rocaglate is a group of natural compounds, which includes rocaglamide, that inhibits protein synthesis by targeting the ATP-dependent DEAD-box RNA helicase eukaryotic initiation factor 4A (eIF4A) and exerts anti-tumor activity [62, 63] . The rocaglate compound, silvestrol, inhibits Ebola virus multiplication likely by interfering with the role of eIF4A in viral protein translation [64] .
While we focused on two host proteins, ATP1A1 and PHB, in this study, our proteomics approach also identified several NP-interacting host-cell proteins whose kd expression via siRNA resulted in increased LCMV multiplication. These proteins, which included MAP1B, might have anti-LCMV activity. MAP1B has been shown to bind to nonstructural proteins 1 (NS1) and 2 (NS2) of human respiratory syncytial virus (HRSV) [34] . NS1 and NS2 of HRSV antagonizes host IFN-I response by reducing the levels of TNF receptor associated factor (TRAF3), IKKε (NS1), and STAT2 (NS2) [65] . NS2-MAP1B interaction interfered with HRSV NS2's ability to reduce levels of STAT2, whereas the role of NS1-MAP1B interaction remains to be determined [34] . Examining the role of NP-MAP1B interaction in modulating NP's ability to inhibit induction of type I IFN is of interest.
We identified among the NP-interacting host cell proteins the RNA helicase Moloney leukemia virus 10 (MOV10), which has been reported to be an antiviral factor for FLUAV [66] , retroviruses [67] [68] [69] [70] [71] , and DENV-2 [72] . We did not observe increased LCMV multiplication in cells subjected to siRNA-mediated kd of MOV10, a finding that would question an anti-LCMV activity of MOV10. However, we consider that LCMV has already optimal multiplication in A549 cells and further increases may occur only under rather unique conditions. MOV10 was shown to enhance IRF-3-mediated IFN-I induction following SeV infection through a tank binding kinase 1 (TBK1)-independent and IKKε-dependent manner. This finding was further supported by demonstrating MOV10-IKKε interaction by co-immunoprecipitation studies [73] . We documented that the anti-IFN activity of mammarenavirus NP correlated with its ability to interact with IKKε [47] . Whether NP-MOV10 interaction prevents MOV10 from enhancing IRF-3-mediated IFN-I induction remains to be determined.
Several members of the mammalian chaperonin-containing T-complex (CCT) were identified as prominent hits in our NP interactome. The mammalian CCT is critical for folding of many proteins with important functions in diverse cellular processes [74] , and may protect complex protein topologies within its central cavity during biosynthesis and folding [75] . The contribution of CCT members to NP assembly into a nucleocapsid structure could account for their presence in the NP, but not eGFP, interactome. Interestingly, members of the CCT have been implicated in multiplication of different viruses including rabies virus [76, 77] , HCV [78] and FLUAV [79] . However, the role of these CCT proteins in virus multiplication remains unknown and may involve functions other than acting as molecular chaperones.
Previous studies documented the presence of several components of the of eIF4F, including 4A, within viral replication-transcription complexes (RTC) detected in cells infected with LCMV [80] and TCRV [81] . These findings, together with the detection of a number of ribosomal proteins in the NP interactome, suggest that translation of viral mRNAs may take place within RTC. However, rocaglamide interference with the activity of eIF4A within the viral RTC might contribute to its anti-LCMV activity.
In this work, we documented the generation of rLCMV/Strep-NP and its use to define the NP-interactome in infected cells. We presented evidence that ATP1A1 and PHB contribute to efficient multiplication of mammarenaviruses using genetics and pharmacological inhibition of the genes. Consistent with our findings, bioinformatic analysis revealed that the protein network associated with ATP1A1 and PHB involves host cell proteins with functions in biological processes that have been implicated in virus multiplication (S5 Fig). The overall experimental approach described here can facilitate the identification of biologically relevant NP-interacting host-cell proteins. Future studies elucidating the roles of pro-and antiviral host-cell factors identified in this study in mammarenavirus multiplication will advance our understanding of the multiple functions of NP and uncover novel cellular targets for the development of antimammarenaviral drugs. In addition, by identifying proviral host-cell factors, drugs that are already approved can be repurposing as therapeutics to combat human pathogenic mammarenavirus infections.
Baby hamster kidney BHK-21 (American Type Culture Collection, ATCC, CCL-10), house mouse L929 (ATCC CCL-1), grivet Vero E6 (ATCC CRL-1586), human A549 (ATCC CCL-185), and human HEK 293T (ATCC CRL-3216) cells were grown in Dulbecco's modified Eagle's medium (Thermo Fisher Scientific, Waltham, MA) containing 10% heat-inactivated fetal bovine serum, 2 mM of L-glutamine, 100 mg/ml of streptomycin, and 100 U/ml of penicillin at 37˚C and 5% CO 2 .
WT recombinant LCMVs, Armstrong (rLCMV ARM) and clone-13 (rLCMV Cl-13) strains, were generated as described [30, 82, 83] . Generation of rLCMV/NP(D382A) and SeV, strain Cantell, was described [30, 82, 83 ]. An rLCMV lacking GPC and expressing eGFP (rLCMVΔGPC/eGFP) was generated by reverse genetics using procedures previously described [84] . rLCMV/Strep-NP and r3LCMV/eGFP-Strep were generated by reverse genetics using similar procedures to generate WT rLCMV and tri-segmented LCMV (r3LCMV) expressing eGFP [30] . For the generation of these novel rLCMVs, we created pol1S Cl-13 plasmids that directed Pol1-mediated intracellular synthesis of recombinant LCMV S genome RNA species coding for Strep-tagged NP or eGFP, respectively (Fig 1A and 1B) . The rLCMV expressing eGFP (rLCMV/eGFP) was generated as described [85] , and the rLCMV expressing ZsGreen (rLCMV/ZsG) instead of eGFP was generated by reverse genetics using similar procedures to generate rLCMV/eGFP. Generation of rLASV expressing eGFP (rLASV/eGFP) will be described elsewhere. A tri-segmented recombinant live-attenuated Candid #1 strain of JUNV expressing eGFP (r3JUNV/eGFP) was generated as described [86] . For the generation of a novel single cycle rLCMV expressing ZsGreen (scrLCMV/ZsG-P2A-NP), a pol1S plasmid was created by omitting GPC open reading frame (ORF) from pol1S plasmid used for the generation of rLCMV/ZsG. scrLCMV/ZsG-P2A-NP was rescued by reverse genetics using similar procedures to generate rLCMVΔGPC/eGFP [84] .
LCMV titers were determined by immunofocus forming assay (IFFA) as described [87] . Briefly, 10-fold serial virus dilutions were used to infect Vero E6 cell monolayers in a 96-well plate, and at 20 h pi, cells were fixed with 4% paraformaldehyde (PFA) in phosphate-buffered saline (PBS). After cell permeabilization by treatment with dilution buffer (DB) (0.3% Triton X-100 in PBS-containing 3% bovine serum albumin [BSA]), cells were stained with a rat mAb to NP (VL-4, Bio X Cell, West Lebanon, NH) conjugated with Alexa Fluor 488 (VL-4-AF488, Protein Labeling Kit, Life Technologies, Carlsbad, CA). VSV titers were determined by a plaque assay.
Total cell lysates were prepared in PD lysis buffer (+) (250 mM of NaCl, 50 mM of Tris-HCl [pH = 7.5], 0.5% TritonX-100, 10% glycerol, 1 mM of MgCl 2 , 1 μM of CaCl 2 , 1 μM of ZnCl 2 ) and clarified by centrifugation at 21,130 x g at 4˚C for 10 min. Clarified lysates were mixed at a 1:1 ratio with loading buffer (100 mM of Tris [pH 6.8], 20% 2-mercaptoethanol, 4% SDS, 0.2% bromophenol blue, 20% glycerol) and boiled for 5 min. Proteins samples were fractionated by SDS-PAGE using 4-20% gradient polyacrylamide gels (Mini-PROTEAN TGX gels 4-20%, Bio-Rad, Hercules, CA), and proteins were transferred by electroblotting onto polyvinylidene difluoride membranes (Immobilin Transfer Membranes, Millipore, Billerica, MA). To detect Strep-tagged proteins, membranes were reacted with mouse monoclonal antibodies to Strep (QIAGEN, Germantown, MD), eGFP (Takara Bio USA, Mountain View, CA), GP 2 (We33/ 36), ATP1A1 (TehrmoFisher Scientific, Rockford, IL), PHB (Abcam, Cambridge, MA) or rabbit polyclonal antibodies to α-tubulin (Cell Signaling Technologies, Danvers, MA) or glyceraldehyde-3-phosphate dehydrogenase (GAPDH, Millipore), respectively, followed by incubation with appropriate horseradish peroxidase-conjugated anti-mouse or anti-rabbit immunoglobulin G (IgG) antibodies (Jackson ImmunoResearch Laboratories, West Grove, PA). SuperSignal West Pico or Femto chemiluminescent substrate (Thermo Fisher Scientific) was used to elicit chemiluminescent signals that were visualized using ImageQuant LAS 4000 Imager (GE Healthcare Bio-Sciences, Pittsburgh, PA).
Pull down of strep-tagged proteins from infected cell lysate. A549 cells prepared in six 15-cm dishes (approximately 1.0 x 10 8 cells in total) were infected with either rLCMV/Strep-NP or r3LCMV/eGFP at an MOI of 0.1. At 48 h pi, cells were washed three times with ice-cold PBS, scraped into fresh ice-cold PBS, and centrifuged at 400 x g at 4˚C for 10 min. Supernatant was removed, and cells were lysed with 12 ml of PD lysis buffer (+) supplemented with halt protease and phosphatase inhibitor cocktail (Thermo Fisher Scientific) and 5 μg/ml of deoxyribonuclease I (Worthington Biochemical Corporation, Lakewood, NJ). Lysate was clarified by centrifugation at 3,900 x g at 4˚C for 30 min to remove cell debris. Clarified cell lysate was then incubated with strep-tactin sepharose resin (QIAGEN) at 4˚C. After 2 h of incubation, the resin was washed three times with PD lysis buffer (+) and once with PD lysis buffer without TritonX-100 (PD lysis buffer [-] ). After the centrifugation at 1,600 x g and 4˚C for 5 min, the last wash buffer was removed, and protein complexes associated with the resin were eluted into 2 ml of PD lysis buffer (-) containing 2.5 mM of desthiobiotin. The eluate was then subjected to TCA precipitation followed by trypsin digestion.
Multidimensional protein identification technology microcolumn. A MudPIT microcolumn was prepared by first creating a Kasil frit at one end of an un-deactivated 250-μm outside diameter (OD) capillary tube (interior diameter of 360 μm)(Agilent Technologies, Inc., Santa Clara, CA). The Kasil frit was prepared by briefly dipping a 20-30-cm capillary tube in 300 μl of Kasil 1624 potassium silicate well-mixed solution (PQ Corporation, Malvern, PA) and 100 μl of formamide, curing at 100˚C for 4 h, and cutting the frit to a length of %2 mm. Strong cation exchange particles (SCX Luna, 5-μm diameter, 125 Å pores, Phenomenex, Torrance, CA) were packed in-house from particle slurries in methanol to 2.5 cm. Reversed phase particles (2 cm, C18 Aqua, 3-μm diameter, 125 Å pores, Phenomenex) were then successively packed onto the capillary tube using the same method as SCX loading.
MudPIT analysis. An analytical reversed-phase liquid chromatography column was generated by pulling a 100-μm (interior diameter (ID) of 360 μm) OD capillary tube (Polymicro Technologies, Phoenix, AZ) to 5-μm ID tip. Reversed-phase particles (Luna C18, 3-μm diameter, 125 Å pores, Phenomenex) were packed directly into the pulled column at 5.5 mPa until 15 cm long. The column was further packed, washed, and equilibrated at 10 mPa with buffer B (80% acetonitrile, 0.1% formic acid) followed by buffer A (5% acetonitrile and 0.1% formic acid). MudPIT and analytical columns were assembled using a zero-dead volume union (Upchurch Scientific, Oak Harbor, WA). LC-MS/MS analysis was performed with an Agilent high-pressure LC pump (Agilent) and linear quadrupole ion dual cell trap Orbitrap Velos (Thermo) using an in-house built electrospray stage. Electrospray was performed directly from the analytical column by applying the electrospray ionization (ESI) voltage at a tee (150 μm ID, Upchurch Scientific) directly downstream of a 1:1,000 split flow to reduce the flow rate to 300 nl/min through the columns. MudPIT experiments (10-step) were performed in which each step corresponds to 0, 10, 20, 40, 50, 60, 70, 80, 90 , and 100% buffer C (500 mM of ammonium acetate, 0.1% formic acid, and 5% acetonitrile) and was run for 3 min at the beginning of a 110-min gradient.
Data analysis. Protein and peptide identification were performed with Integrated Proteomics Pipeline-IP2 (Integrated Proteomics Applications, San Diego, CA. http://www. integratedproteomics.com/) using ProLuCID and DTASelect2 algorithms. DTASelect parameters were-p 2 -y 1-trypstat-pfp .01 -extra-pI-DB-dm-in. Spectrum raw files were extracted into ms2 files from raw files using open source RawExtract 1.9.9 (Scripps Research Institute, La Jolla, CA; http://fields.scripps.edu/downloads.php), and the tandem mass spectra were searched against a human protein database (UniprotKB). To accurately estimate peptide probabilities and false discovery rates, we used a decoy database containing the reversed sequences of all the proteins appended to the target database. Tandem mass spectra were matched to sequences using the ProLuCID algorithm with a 600-ppm peptide mass tolerance. ProLuCID searches were done on an Intel Xeon cluster processor running under the Linux operating system. The search space included half and fully tryptic peptide candidates that fell within the mass tolerance window with no miscleavage constraint. Carbamidomethylation (+57.02146 Da) of cysteine was considered as a static modification. siRNA screening A549 cells (1,000 cells/well) in a 384-well plate were reverse transfected with 0.5 pmol of siRNA pool (S2 Table) targeting each gene using 0.1 μl of Lipofectamine RNAiMAX (Thermo Fisher Scientific) (final siRNA concentration was 10 nM), followed by incubation at 37˚C and 5% CO 2 . At 72 h post-transfection, cells were infected (MOI = 0.05) with rLCMV/ZsG. siRNA target host-cell proteins were selected based on availability of validated siRNA sequences. The siRNAs we used to examine the effects on LCMV multiplication of knockdown expression of NP-interacting host cell protein candidate hits corresponded to the Genome-wide ON TAR-GET-Plus (OTP) Human siRNA library (18,301 genes, 4 siRNAs/gene; Dharmacon, Lafayette, CO).
A549 cells (3.0 x 10 4 cells/well) were reverse transfected in a 24-well plate with 6 pmol of siRNA pools targeting each gene using 1 μl of Lipofectamine RNAiMAX (final siRNA concentration is 10 nM). At 72 h post-transfection, total cell lysate was prepared in modified lysis A buffer (25 mM Tris-HCl [pH = 8.0], 50 mM NaCl, 1%Triton X-100, 1.25% sodium deoxycholate) and clarified by centrifugation at 21,130 x g at 4˚C for 10 min. The total protein concentration of clarified cell lysate was measured by Pierce BCA Protein Assay Kit (Thermo Fisher Scientific). The same amount of protein from each sample was subjected to SDS-PAGE, and the protein expression of siRNA-targeted genes was analyzed by western blots.
Cells infected with eGFP-or ZsGreen-expressing rLCMV were fixed with 4% PFA in PBS. After cell permeabilization by treatment with DB, cells were stained with 4',6-diamidino-2-phenylindole (DAPI). Green fluorescence (eGFP or ZsGreen) and DAPI signals were measured by a fluorescent plate reader (Synergy H4 Hybrid Multi-Mode Microplate Reader, Bio-Tek, Winooski, VT).
Mock-and virus-infected cells were fixed with 4% PFA. After cell permeabilization and blocking by treatment with DB containing 1% normal goat serum, cells were incubated with primary mouse anti ATP1A1 or PHB antibody followed by secondary anti-mouse IgG antibody conjugated with Alexa Fluore 568 (anti-mouse IgG-AF568). Subsequently, cells were stained with VL-4-AF488. In some samples, primary antibody against ATP1A1 or PHB was omitted to determine background fluorescence. To visualize nuclei, DAPI Fluoromount-G (SouthernBiotech, Birmingham, AL) was used to mount coverslips on a slide glass. Stained cells were observed under a confocal microscope (LSM 710, Zeiss) and data analyzed by ZEN software (Zeiss). Co-localization analysis was performed on a pixel by pixel basis using Zen software (Zeiss). Eight green (NP-positive) cells were marked and every pixel in the marked area was plotted in the scatter diagram based on its intensity level from each channel. Thresholds for green and red channels were determined using mock-infected cells stained with VL-4-AF488 (anti-NP) and anti-mouse IgG antibody conjugated with Alexa Fluor 568, without using anti-ATP1A1 or -PHB antibodies. Each pixel was assigned a value of 1. Co-localization coefficients (CC) (or non-weighted CC) were determined by dividing the sum of both green-and red-positive pixels by the sum of green positive pixels. This calculation was repeated for eight individual cells. To assess the specificity of co-localization, we determined weighted CC by taking into consideration the brightness of each channel signal. Comparison of non-weighted and weighted CC allowed us to determine whether brighter pixels were present in the co-localized regions compared to the non-co-localized regions. p values were determined by a two-tailed paired t test using GraphPad Prism software.
A549 or Vero E6 cells seeded (2.0 x 10 4 cells/well) in a 96-well plate and cultured overnight were treated with 3-fold serial compound dilutions at 37˚C and 5% CO 2 for 2 h, followed by infection with rLCMV/eGFP (MOI = 0.01). Compounds were present to study endpoint. At 48 h pi, cells were fixed with 4% PFA in PBS, and eGFP expression was examined by a fluorescent plate reader (Synergy H4 Hybrid Multi-Mode Microplate Reader, BioTek). Mean values obtained with DMSO-treated and rLCMV/eGFP-infected cells were set to 100%. The IC 50 concentrations were determined using GraphPad Prism.
A549 or Vero E6 cells seeded in a 96-well plate (2.0 x 10 4 cells/well) and cultured overnight were treated with 3-fold serial compound dilutions and cultured at 37˚C and 5% CO 2 for 48 h. Then, CellTiter 96 AQ ueous one solution reagent (Promega, Madison, WI) was added. Thereafter, the assay was performed according to the manufacturer's recommendations, and the absorbance (490 nm) was obtained using an enzyme-linked immunosorbent assay (ELISA) reader (SPECTRA max plus 384; Molecular Devices, Sunnyvale, CA). Mean values obtained with DMSO-treated cells were set to 100%. The CC 50 concentrations were determined using GraphPad Prism.
A plasmid expressing C-terminus Strep-tagged Z protein (pC-LCMV-Z-Strep) was generated using similar procedure to generate a plasmid expressing C-terminus FLAG-tagged LASV Z protein (pC-LASV-Z-FLAG), and the budding assay was performed as previously described [88] . Cells (HEK 293T) in a 12-well plate were transfected with 0.5 μg of empty pCAGGS vector or pC-LCMV-Z-Strep or pC-LASV-Z-FLAG using Lipofectamine 2000. At 5 h post-transfection, media were replaced with fresh media and incubated at 37˚C and 5% CO 2 for 19 h. Then the cells were three times washed with fresh medium. After the removal of the last wash medium, cells were cultured in fresh medium containing ouabain (30 or 40 nM) or rocaglamide (50 or 100 nM) or equivalent concentration of DMSO, and 24 h later, virion-like particle (VLP)-containing TCS and cells were collected. Total cell lysate was prepared by lysing the cells with lysis buffer (1% NP-40, 50 mM of Tris-HCl [pH 8.0], 62.5 mM NaCl, 0.4% sodium deoxycholate). After clarification of TCS from cell debris by centrifugation at 400 x g and 4˚C for 10 min, VLPs were collected by ultracentrifugation at 100,000 x g and 4˚C for 30 min through a 20% sucrose cushion. VLPs were resuspended in PBS, and Z expression in total cell lysate and TCS (containing VLPs) were analyzed by western blots.
A549 cells infected with rLCMV/eGFP were harvested using Accutase cell detachment solution (Innovative Cell Technologies, San Diego, CA) and fixed with 4% PFA in PBS. eGFP expression was examined by flow cytometry using a BD LSR II (Becton Dickson), and data were analyzed with FlowJo (Tree Star, Inc., Ashland, OR).
293T cells seeded (4.0 x 10 5 cells/well) in a 12-well plate and cultured overnight were infected with scrLCMV/ZsG-P2A-NP for 2 h and subsequently transfected with 0.5 μg of pC-GPC. At 24 h pi, cells were three times washed with fresh media to eliminate infectious virus particle produced in the absence of compound treatment, and cultured for another 24 h in fresh media in the presence of 40 nM of ouabain or vehicle control (DMSO). At 48 h pi, TCS was collected and used to infect fresh monolayers of BHK-21 cells seeded (4.0 x 10 5 cells/well) in a 12-well plate 1 day before the infection, and 293T cell lysate was prepared. 24 h later, BHK-21 cell lysate was prepared. Total cell lysate was prepared in cell lysis buffer (150 mM of NaCl, 50 mM of Tris-HCl [pH = 7.5], 0.5% [NP-40], 1 mM of EDTA] and clarified by centrifugation at 21,130 x g at 4˚C for 10 min. ZsGreen signal intensity in clarified cell lysate was measured by a fluorescent plate reader (Synergy H4 Hybrid Multi-Mode Microplate Reader, BioTek).
A549 cells seeded (2 x 10 5 cells/well) in a 96-well plate and cultured overnight were treated with combinations of different concentrations of ouabain and rocaglamide for 2 h and then infected (MOI = 0.01) with rLCMV/eGFP. Compounds were present in the culture medium throughout the experiment. At 48 h pi, cells were fixed, permeabilized by treatment with DB, and stained with DAPI. eGFP and DAPI signals were measured by a fluorescent plate reader (Synergy H4 Hybrid Multi-Mode Microplate Reader, BioTek). eGFP readouts were normalized by DAPI readouts, and normalized data were used to analyze synergistic effect of the two compounds by the MacSynergy II program [89] .
Data were analyzed for p values by a two-tailed unpaired t test using GraphPad Prism software. | Why was the human A549 cell line chosen for this study? | false | 5,153 | {
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"lung epithelial cells are one of the initial cell targets of humans following inhalation of mammarenavirions"
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1,719 | Virus-Vectored Influenza Virus Vaccines
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147686/
SHA: f6d2afb2ec44d8656972ea79f8a833143bbeb42b
Authors: Tripp, Ralph A.; Tompkins, S. Mark
Date: 2014-08-07
DOI: 10.3390/v6083055
License: cc-by
Abstract: Despite the availability of an inactivated vaccine that has been licensed for >50 years, the influenza virus continues to cause morbidity and mortality worldwide. Constant evolution of circulating influenza virus strains and the emergence of new strains diminishes the effectiveness of annual vaccines that rely on a match with circulating influenza strains. Thus, there is a continued need for new, efficacious vaccines conferring cross-clade protection to avoid the need for biannual reformulation of seasonal influenza vaccines. Recombinant virus-vectored vaccines are an appealing alternative to classical inactivated vaccines because virus vectors enable native expression of influenza antigens, even from virulent influenza viruses, while expressed in the context of the vector that can improve immunogenicity. In addition, a vectored vaccine often enables delivery of the vaccine to sites of inductive immunity such as the respiratory tract enabling protection from influenza virus infection. Moreover, the ability to readily manipulate virus vectors to produce novel influenza vaccines may provide the quickest path toward a universal vaccine protecting against all influenza viruses. This review will discuss experimental virus-vectored vaccines for use in humans, comparing them to licensed vaccines and the hurdles faced for licensure of these next-generation influenza virus vaccines.
Text: Seasonal influenza is a worldwide health problem causing high mobility and substantial mortality [1] [2] [3] [4] . Moreover, influenza infection often worsens preexisting medical conditions [5] [6] [7] . Vaccines against circulating influenza strains are available and updated annually, but many issues are still present, including low efficacy in the populations at greatest risk of complications from influenza virus infection, i.e., the young and elderly [8, 9] . Despite increasing vaccination rates, influenza-related hospitalizations are increasing [8, 10] , and substantial drug resistance has developed to two of the four currently approved anti-viral drugs [11, 12] . While adjuvants have the potential to improve efficacy and availability of current inactivated vaccines, live-attenuated and virus-vectored vaccines are still considered one of the best options for the induction of broad and efficacious immunity to the influenza virus [13] .
The general types of influenza vaccines available in the United States are trivalent inactivated influenza vaccine (TIV), quadrivalent influenza vaccine (QIV), and live attenuated influenza vaccine (LAIV; in trivalent and quadrivalent forms). There are three types of inactivated vaccines that include whole virus inactivated, split virus inactivated, and subunit vaccines. In split virus vaccines, the virus is disrupted by a detergent. In subunit vaccines, HA and NA have been further purified by removal of other viral components. TIV is administered intramuscularly and contains three or four inactivated viruses, i.e., two type A strains (H1 and H3) and one or two type B strains. TIV efficacy is measured by induction of humoral responses to the hemagglutinin (HA) protein, the major surface and attachment glycoprotein on influenza. Serum antibody responses to HA are measured by the hemagglutination-inhibition (HI) assay, and the strain-specific HI titer is considered the gold-standard correlate of immunity to influenza where a four-fold increase in titer post-vaccination, or a HI titer of ≥1:40 is considered protective [4, 14] . Protection against clinical disease is mainly conferred by serum antibodies; however, mucosal IgA antibodies also may contribute to resistance against infection. Split virus inactivated vaccines can induce neuraminidase (NA)-specific antibody responses [15] [16] [17] , and anti-NA antibodies have been associated with protection from infection in humans [18] [19] [20] [21] [22] . Currently, NA-specific antibody responses are not considered a correlate of protection [14] . LAIV is administered as a nasal spray and contains the same three or four influenza virus strains as inactivated vaccines but on an attenuated vaccine backbone [4] . LAIV are temperature-sensitive and cold-adapted so they do not replicate effectively at core body temperature, but replicate in the mucosa of the nasopharynx [23] . LAIV immunization induces serum antibody responses, mucosal antibody responses (IgA), and T cell responses. While robust serum antibody and nasal wash (mucosal) antibody responses are associated with protection from infection, other immune responses, such as CD8 + cytotoxic lymphocyte (CTL) responses may contribute to protection and there is not a clear correlate of immunity for LAIV [4, 14, 24] .
Currently licensed influenza virus vaccines suffer from a number of issues. The inactivated vaccines rely on specific antibody responses to the HA, and to a lesser extent NA proteins for protection. The immunodominant portions of the HA and NA molecules undergo a constant process of antigenic drift, a natural accumulation of mutations, enabling virus evasion from immunity [9, 25] . Thus, the circulating influenza A and B strains are reviewed annually for antigenic match with current vaccines, Replacement of vaccine strains may occur regularly, and annual vaccination is recommended to assure protection [4, 26, 27] . For the northern hemisphere, vaccine strain selection occurs in February and then manufacturers begin production, taking at least six months to produce the millions of vaccine doses required for the fall [27] . If the prediction is imperfect, or if manufacturers have issues with vaccine production, vaccine efficacy or availability can be compromised [28] . LAIV is not recommended for all populations; however, it is generally considered to be as effective as inactivated vaccines and may be more efficacious in children [4, 9, 24] . While LAIV relies on antigenic match and the HA and NA antigens are replaced on the same schedule as the TIV [4, 9] , there is some suggestion that LAIV may induce broader protection than TIV due to the diversity of the immune response consistent with inducing virus-neutralizing serum and mucosal antibodies, as well as broadly reactive T cell responses [9, 23, 29] . While overall both TIV and LAIV are considered safe and effective, there is a recognized need for improved seasonal influenza vaccines [26] . Moreover, improved understanding of immunity to conserved influenza virus antigens has raised the possibility of a universal vaccine, and these universal antigens will likely require novel vaccines for effective delivery [30] [31] [32] .
Virus-vectored vaccines share many of the advantages of LAIV, as well as those unique to the vectors. Recombinant DNA systems exist that allow ready manipulation and modification of the vector genome. This in turn enables modification of the vectors to attenuate the virus or enhance immunogenicity, in addition to adding and manipulating the influenza virus antigens. Many of these vectors have been extensively studied or used as vaccines against wild type forms of the virus. Finally, each of these vaccine vectors is either replication-defective or causes a self-limiting infection, although like LAIV, safety in immunocompromised individuals still remains a concern [4, 13, [33] [34] [35] . Table 1 summarizes the benefits and concerns of each of the virus-vectored vaccines discussed here.
There are 53 serotypes of adenovirus, many of which have been explored as vaccine vectors. A live adenovirus vaccine containing serotypes 4 and 7 has been in use by the military for decades, suggesting adenoviruses may be safe for widespread vaccine use [36] . However, safety concerns have led to the majority of adenovirus-based vaccine development to focus on replication-defective vectors. Adenovirus 5 (Ad5) is the most-studied serotype, having been tested for gene delivery and anti-cancer agents, as well as for infectious disease vaccines.
Adenovirus vectors are attractive as vaccine vectors because their genome is very stable and there are a variety of recombinant systems available which can accommodate up to 10 kb of recombinant genetic material [37] . Adenovirus is a non-enveloped virus which is relatively stable and can be formulated for long-term storage at 4 °C, or even storage up to six months at room temperature [33] . Adenovirus vaccines can be grown to high titers, exceeding 10 1° plaque forming units (PFU) per mL when cultured on 293 or PER.C6 cells [38] , and the virus can be purified by simple methods [39] . Adenovirus vaccines can also be delivered via multiple routes, including intramuscular injection, subcutaneous injection, intradermal injection, oral delivery using a protective capsule, and by intranasal delivery. Importantly, the latter two delivery methods induce robust mucosal immune responses and may bypass preexisting vector immunity [33] . Even replication-defective adenovirus vectors are naturally immunostimulatory and effective adjuvants to the recombinant antigen being delivered. Adenovirus has been extensively studied as a vaccine vector for human disease. The first report using adenovirus as a vaccine vector for influenza demonstrated immunogenicity of recombinant adenovirus 5 (rAd5) expressing the HA of a swine influenza virus, A/Swine/Iowa/1999 (H3N2). Intramuscular immunization of mice with this construct induced robust neutralizing antibody responses and protected mice from challenge with a heterologous virus, A/Hong Kong/1/1968 (H3N2) [40] . Replication defective rAd5 vaccines expressing influenza HA have also been tested in humans. A rAd5-HA expressing the HA from A/Puerto Rico/8/1934 (H1N1; PR8) was delivered to humans epicutaneously or intranasally and assayed for safety and immunogenicity. The vaccine was well tolerated and induced seroconversion with the intranasal administration had a higher conversion rate and higher geometric meant HI titers [41] . While clinical trials with rAd vectors have overall been successful, demonstrating safety and some level of efficacy, rAd5 as a vector has been negatively overshadowed by two clinical trial failures. The first trial was a gene therapy examination where high-dose intravenous delivery of an Ad vector resulted in the death of an 18-year-old male [42, 43] . The second clinical failure was using an Ad5-vectored HIV vaccine being tested as a part of a Step Study, a phase 2B clinical trial. In this study, individuals were vaccinated with the Ad5 vaccine vector expressing HIV-1 gag, pol, and nef genes. The vaccine induced HIV-specific T cell responses; however, the study was stopped after interim analysis suggested the vaccine did not achieve efficacy and individuals with high preexisting Ad5 antibody titers might have an increased risk of acquiring HIV-1 [44] [45] [46] . Subsequently, the rAd5 vaccine-associated risk was confirmed [47] . While these two instances do not suggest Ad-vector vaccines are unsafe or inefficacious, the umbra cast by the clinical trials notes has affected interest for all adenovirus vaccines, but interest still remains.
Immunization with adenovirus vectors induces potent cellular and humoral immune responses that are initiated through toll-like receptor-dependent and independent pathways which induce robust pro-inflammatory cytokine responses. Recombinant Ad vaccines expressing HA antigens from pandemic H1N1 (pH1N1), H5 and H7 highly pathogenic avian influenza (HPAI) virus (HPAIV), and H9 avian influenza viruses have been tested for efficacy in a number of animal models, including chickens, mice, and ferrets, and been shown to be efficacious and provide protection from challenge [48, 49] . Several rAd5 vectors have been explored for delivery of non-HA antigens, influenza nucleoprotein (NP) and matrix 2 (M2) protein [29, [50] [51] [52] . The efficacy of non-HA antigens has led to their inclusion with HA-based vaccines to improve immunogenicity and broaden breadth of both humoral and cellular immunity [53, 54] . However, as both CD8 + T cell and neutralizing antibody responses are generated by the vector and vaccine antigens, immunological memory to these components can reduce efficacy and limit repeated use [48] .
One drawback of an Ad5 vector is the potential for preexisting immunity, so alternative adenovirus serotypes have been explored as vectors, particularly non-human and uncommon human serotypes. Non-human adenovirus vectors include those from non-human primates (NHP), dogs, sheep, pigs, cows, birds and others [48, 55] . These vectors can infect a variety of cell types, but are generally attenuated in humans avoiding concerns of preexisting immunity. Swine, NHP and bovine adenoviruses expressing H5 HA antigens have been shown to induce immunity comparable to human rAd5-H5 vaccines [33, 56] . Recombinant, replication-defective adenoviruses from low-prevalence serotypes have also been shown to be efficacious. Low prevalence serotypes such as adenovirus types 3, 7, 11, and 35 can evade anti-Ad5 immune responses while maintaining effective antigen delivery and immunogenicity [48, 57] . Prime-boost strategies, using DNA or protein immunization in conjunction with an adenovirus vaccine booster immunization have also been explored as a means to avoided preexisting immunity [52] .
Adeno-associated viruses (AAV) were first explored as gene therapy vectors. Like rAd vectors, rAAV have broad tropism infecting a variety of hosts, tissues, and proliferating and non-proliferating cell types [58] . AAVs had been generally not considered as vaccine vectors because they were widely considered to be poorly immunogenic. A seminal study using AAV-2 to express a HSV-2 glycoprotein showed this virus vaccine vector effectively induced potent CD8 + T cell and serum antibody responses, thereby opening the door to other rAAV vaccine-associated studies [59, 60] .
AAV vector systems have a number of engaging properties. The wild type viruses are non-pathogenic and replication incompetent in humans and the recombinant AAV vector systems are even further attenuated [61] . As members of the parvovirus family, AAVs are small non-enveloped viruses that are stable and amenable to long-term storage without a cold chain. While there is limited preexisting immunity, availability of non-human strains as vaccine candidates eliminates these concerns. Modifications to the vector have increased immunogenicity, as well [60] .
There are limited studies using AAVs as vaccine vectors for influenza. An AAV expressing an HA antigen was first shown to induce protective in 2001 [62] . Later, a hybrid AAV derived from two non-human primate isolates (AAVrh32.33) was used to express influenza NP and protect against PR8 challenge in mice [63] . Most recently, following the 2009 H1N1 influenza virus pandemic, rAAV vectors were generated expressing the HA, NP and matrix 1 (M1) proteins of A/Mexico/4603/2009 (pH1N1), and in murine immunization and challenge studies, the rAAV-HA and rAAV-NP were shown to be protective; however, mice vaccinated with rAAV-HA + NP + M1 had the most robust protection. Also, mice vaccinated with rAAV-HA + rAAV-NP + rAAV-M1 were also partially protected against heterologous (PR8, H1N1) challenge [63] . Most recently, an AAV vector was used to deliver passive immunity to influenza [64, 65] . In these studies, AAV (AAV8 and AAV9) was used to deliver an antibody transgene encoding a broadly cross-protective anti-influenza monoclonal antibody for in vivo expression. Both intramuscular and intranasal delivery of the AAVs was shown to protect against a number of influenza virus challenges in mice and ferrets, including H1N1 and H5N1 viruses [64, 65] . These studies suggest that rAAV vectors are promising vaccine and immunoprophylaxis vectors. To this point, while approximately 80 phase I, I/II, II, or III rAAV clinical trials are open, completed, or being reviewed, these have focused upon gene transfer studies and so there is as yet limited safety data for use of rAAV as vaccines [66] .
Alphaviruses are positive-sense, single-stranded RNA viruses of the Togaviridae family. A variety of alphaviruses have been developed as vaccine vectors, including Semliki Forest virus (SFV), Sindbis (SIN) virus, Venezuelan equine encephalitis (VEE) virus, as well as chimeric viruses incorporating portions of SIN and VEE viruses. The replication defective vaccines or replicons do not encode viral structural proteins, having these portions of the genome replaces with transgenic material.
The structural proteins are provided in cell culture production systems. One important feature of the replicon systems is the self-replicating nature of the RNA. Despite the partial viral genome, the RNAs are self-replicating and can express transgenes at very high levels [67] .
SIN, SFV, and VEE have all been tested for efficacy as vaccine vectors for influenza virus [68] [69] [70] [71] . A VEE-based replicon system encoding the HA from PR8 was demonstrated to induce potent HA-specific immune response and protected from challenge in a murine model, despite repeated immunization with the vector expressing a control antigen, suggesting preexisting immunity may not be an issue for the replicon vaccine [68] . A separate study developed a VEE replicon system expressing the HA from A/Hong Kong/156/1997 (H5N1) and demonstrated varying efficacy after in ovo vaccination or vaccination of 1-day-old chicks [70] . A recombinant SIN virus was use as a vaccine vector to deliver a CD8 + T cell epitope only. The well-characterized NP epitope was transgenically expressed in the SIN system and shown to be immunogenic in mice, priming a robust CD8 + T cell response and reducing influenza virus titer after challenge [69] . More recently, a VEE replicon system expressing the HA protein of PR8 was shown to protect young adult (8-week-old) and aged (12-month-old) mice from lethal homologous challenge [72] .
The VEE replicon systems are particularly appealing as the VEE targets antigen-presenting cells in the lymphatic tissues, priming rapid and robust immune responses [73] . VEE replicon systems can induce robust mucosal immune responses through intranasal or subcutaneous immunization [72] [73] [74] , and subcutaneous immunization with virus-like replicon particles (VRP) expressing HA-induced antigen-specific systemic IgG and fecal IgA antibodies [74] . VRPs derived from VEE virus have been developed as candidate vaccines for cytomegalovirus (CMV). A phase I clinical trial with the CMV VRP showed the vaccine was immunogenic, inducing CMV-neutralizing antibody responses and potent T cell responses. Moreover, the vaccine was well tolerated and considered safe [75] . A separate clinical trial assessed efficacy of repeated immunization with a VRP expressing a tumor antigen. The vaccine was safe and despite high vector-specific immunity after initial immunization, continued to boost transgene-specific immune responses upon boost [76] . While additional clinical data is needed, these reports suggest alphavirus replicon systems or VRPs may be safe and efficacious, even in the face of preexisting immunity.
Baculovirus has been extensively used to produce recombinant proteins. Recently, a baculovirus-derived recombinant HA vaccine was approved for human use and was first available for use in the United States for the 2013-2014 influenza season [4] . Baculoviruses have also been explored as vaccine vectors. Baculoviruses have a number of advantages as vaccine vectors. The viruses have been extensively studied for protein expression and for pesticide use and so are readily manipulated. The vectors can accommodate large gene insertions, show limited cytopathic effect in mammalian cells, and have been shown to infect and express genes of interest in a spectrum of mammalian cells [77] . While the insect promoters are not effective for mammalian gene expression, appropriate promoters can be cloned into the baculovirus vaccine vectors.
Baculovirus vectors have been tested as influenza vaccines, with the first reported vaccine using Autographa californica nuclear polyhedrosis virus (AcNPV) expressing the HA of PR8 under control of the CAG promoter (AcCAG-HA) [77] . Intramuscular, intranasal, intradermal, and intraperitoneal immunization or mice with AcCAG-HA elicited HA-specific antibody responses, however only intranasal immunization provided protection from lethal challenge. Interestingly, intranasal immunization with the wild type AcNPV also resulted in protection from PR8 challenge. The robust innate immune response to the baculovirus provided non-specific protection from subsequent influenza virus infection [78] . While these studies did not demonstrate specific protection, there were antigen-specific immune responses and potential adjuvant effects by the innate response.
Baculovirus pseudotype viruses have also been explored. The G protein of vesicular stomatitis virus controlled by the insect polyhedron promoter and the HA of A/Chicken/Hubei/327/2004 (H5N1) HPAIV controlled by a CMV promoter were used to generate the BV-G-HA. Intramuscular immunization of mice or chickens with BV-G-HA elicited strong HI and VN serum antibody responses, IFN-γ responses, and protected from H5N1 challenge [79] . A separate study demonstrated efficacy using a bivalent pseudotyped baculovirus vector [80] .
Baculovirus has also been used to generate an inactivated particle vaccine. The HA of A/Indonesia/CDC669/2006(H5N1) was incorporated into a commercial baculovirus vector controlled by the e1 promoter from White Spot Syndrome Virus. The resulting recombinant virus was propagated in insect (Sf9) cells and inactivated as a particle vaccine [81, 82] . Intranasal delivery with cholera toxin B as an adjuvant elicited robust HI titers and protected from lethal challenge [81] . Oral delivery of this encapsulated vaccine induced robust serum HI titers and mucosal IgA titers in mice, and protected from H5N1 HPAIV challenge. More recently, co-formulations of inactivated baculovirus vectors have also been shown to be effective in mice [83] .
While there is growing data on the potential use of baculovirus or pseudotyped baculovirus as a vaccine vector, efficacy data in mammalian animal models other than mice is lacking. There is also no data on the safety in humans, reducing enthusiasm for baculovirus as a vaccine vector for influenza at this time.
Newcastle disease virus (NDV) is a single-stranded, negative-sense RNA virus that causes disease in poultry. NDV has a number of appealing qualities as a vaccine vector. As an avian virus, there is little or no preexisting immunity to NDV in humans and NDV propagates to high titers in both chicken eggs and cell culture. As a paramyxovirus, there is no DNA phase in the virus lifecycle reducing concerns of integration events, and the levels of gene expression are driven by the proximity to the leader sequence at the 3' end of the viral genome. This gradient of gene expression enables attenuation through rearrangement of the genome, or by insertion of transgenes within the genome. Finally, pathogenicity of NDV is largely determined by features of the fusion protein enabling ready attenuation of the vaccine vector [84] .
Reverse genetics, a method that allows NDV to be rescued from plasmids expressing the viral RNA polymerase and nucleocapsid proteins, was first reported in 1999 [85, 86] . This process has enabled manipulation of the NDV genome as well as incorporation of transgenes and the development of NDV vectors. Influenza was the first infectious disease targeted with a recombinant NDV (rNDV) vector. The HA protein of A/WSN/1933 (H1N1) was inserted into the Hitchner B1 vaccine strain. The HA protein was expressed on infected cells and was incorporated into infectious virions. While the virus was attenuated compared to the parental vaccine strain, it induced a robust serum antibody response and protected against homologous influenza virus challenge in a murine model of infection [87] . Subsequently, rNDV was tested as a vaccine vector for HPAIV having varying efficacy against H5 and H7 influenza virus infections in poultry [88] [89] [90] [91] [92] [93] [94] . These vaccines have the added benefit of potentially providing protection against both the influenza virus and NDV infection.
NDV has also been explored as a vaccine vector for humans. Two NHP studies assessed the immunogenicity and efficacy of an rNDV expressing the HA or NA of A/Vietnam/1203/2004 (H5N1; VN1203) [95, 96] . Intranasal and intratracheal delivery of the rNDV-HA or rNDV-NA vaccines induced both serum and mucosal antibody responses and protected from HPAIV challenge [95, 96] . NDV has limited clinical data; however, phase I and phase I/II clinical trials have shown that the NDV vector is well-tolerated, even at high doses delivered intravenously [44, 97] . While these results are promising, additional studies are needed to advance NDV as a human vaccine vector for influenza.
Parainfluenza virus type 5 (PIV5) is a paramyxovirus vaccine vector being explored for delivery of influenza and other infectious disease vaccine antigens. PIV5 has only recently been described as a vaccine vector [98] . Similar to other RNA viruses, PIV5 has a number of features that make it an attractive vaccine vector. For example, PIV5 has a stable RNA genome and no DNA phase in virus replication cycle reducing concerns of host genome integration or modification. PIV5 can be grown to very high titers in mammalian vaccine cell culture substrates and is not cytopathic allowing for extended culture and harvest of vaccine virus [98, 99] . Like NDV, PIV5 has a 3'-to 5' gradient of gene expression and insertion of transgenes at different locations in the genome can variably attenuate the virus and alter transgene expression [100] . PIV5 has broad tropism, infecting many cell types, tissues, and species without causing clinical disease, although PIV5 has been associated with -kennel cough‖ in dogs [99] . A reverse genetics system for PIV5 was first used to insert the HA gene from A/Udorn/307/72 (H3N2) into the PIV5 genome between the hemagglutinin-neuraminidase (HN) gene and the large (L) polymerase gene. Similar to NDV, the HA was expressed at high levels in infected cells and replicated similarly to the wild type virus, and importantly, was not pathogenic in immunodeficient mice [98] . Additionally, a single intranasal immunization in a murine model of influenza infection was shown to induce neutralizing antibody responses and protect against a virus expressing homologous HA protein [98] . PIV5 has also been explored as a vaccine against HPAIV. Recombinant PIV5 vaccines expressing the HA or NP from VN1203 were tested for efficacy in a murine challenge model. Mice intranasally vaccinated with a single dose of PIV5-H5 vaccine had robust serum and mucosal antibody responses, and were protected from lethal challenge. Notably, although cellular immune responses appeared to contribute to protection, serum antibody was sufficient for protection from challenge [100, 101] . Intramuscular immunization with PIV5-H5 was also shown to be effective at inducing neutralizing antibody responses and protecting against lethal influenza virus challenge [101] . PIV5 expressing the NP protein of HPAIV was also efficacious in the murine immunization and challenge model, where a single intranasal immunization induced robust CD8 + T cell responses and protected against homologous (H5N1) and heterosubtypic (H1N1) virus challenge [102] .
Currently there is no clinical safety data for use of PIV5 in humans. However, live PIV5 has been a component of veterinary vaccines for -kennel cough‖ for >30 years, and veterinarians and dog owners are exposed to live PIV5 without reported disease [99] . This combined with preclinical data from a variety of animal models suggests that PIV5 as a vector is likely to be safe in humans. As preexisting immunity is a concern for all virus-vectored vaccines, it should be noted that there is no data on the levels of preexisting immunity to PIV5 in humans. However, a study evaluating the efficacy of a PIV5-H3 vaccine in canines previously vaccinated against PIV5 (kennel cough) showed induction of robust anti-H3 serum antibody responses as well as high serum antibody levels to the PIV5 vaccine, suggesting preexisting immunity to the PIV5 vector may not affect immunogenicity of vaccines even with repeated use [99] .
Poxvirus vaccines have a long history and the notable hallmark of being responsible for eradication of smallpox. The termination of the smallpox virus vaccination program has resulted in a large population of poxvirus-naï ve individuals that provides the opportunity for the use of poxviruses as vectors without preexisting immunity concerns [103] . Poxvirus-vectored vaccines were first proposed for use in 1982 with two reports of recombinant vaccinia viruses encoding and expressing functional thymidine kinase gene from herpes virus [104, 105] . Within a year, a vaccinia virus encoding the HA of an H2N2 virus was shown to express a functional HA protein (cleaved in the HA1 and HA2 subunits) and be immunogenic in rabbits and hamsters [106] . Subsequently, all ten of the primary influenza proteins have been expressed in vaccine virus [107] .
Early work with intact vaccinia virus vectors raised safety concerns, as there was substantial reactogenicity that hindered recombinant vaccine development [108] . Two vaccinia vectors were developed to address these safety concerns. The modified vaccinia virus Ankara (MVA) strain was attenuated by passage 530 times in chick embryo fibroblasts cultures. The second, New York vaccinia virus (NYVAC) was a plaque-purified clone of the Copenhagen vaccine strain rationally attenuated by deletion of 18 open reading frames [109] [110] [111] .
Modified vaccinia virus Ankara (MVA) was developed prior to smallpox eradication to reduce or prevent adverse effects of other smallpox vaccines [109] . Serial tissue culture passage of MVA resulted in loss of 15% of the genome, and established a growth restriction for avian cells. The defects affected late stages in virus assembly in non-avian cells, a feature enabling use of the vector as single-round expression vector in non-permissive hosts. Interestingly, over two decades ago, recombinant MVA expressing the HA and NP of influenza virus was shown to be effective against lethal influenza virus challenge in a murine model [112] . Subsequently, MVA expressing various antigens from seasonal, pandemic (A/California/04/2009, pH1N1), equine (A/Equine/Kentucky/1/81 H3N8), and HPAI (VN1203) viruses have been shown to be efficacious in murine, ferret, NHP, and equine challenge models [113] . MVA vaccines are very effective stimulators of both cellular and humoral immunity. For example, abortive infection provides native expression of the influenza antigens enabling robust antibody responses to native surface viral antigens. Concurrently, the intracellular influenza peptides expressed by the pox vector enter the class I MHC antigen processing and presentation pathway enabling induction of CD8 + T cell antiviral responses. MVA also induces CD4 + T cell responses further contributing to the magnitude of the antigen-specific effector functions [107, [112] [113] [114] [115] . MVA is also a potent activator of early innate immune responses further enhancing adaptive immune responses [116] . Between early smallpox vaccine development and more recent vaccine vector development, MVA has undergone extensive safety testing and shown to be attenuated in severely immunocompromised animals and safe for use in children, adults, elderly, and immunocompromised persons. With extensive pre-clinical data, recombinant MVA vaccines expressing influenza antigens have been tested in clinical trials and been shown to be safe and immunogenic in humans [117] [118] [119] . These results combined with data from other (non-influenza) clinical and pre-clinical studies support MVA as a leading viral-vectored candidate vaccine.
The NYVAC vector is a highly attenuated vaccinia virus strain. NYVAC is replication-restricted; however, it grows in chick embryo fibroblasts and Vero cells enabling vaccine-scale production. In non-permissive cells, critical late structural proteins are not produced stopping replication at the immature virion stage [120] . NYVAC is very attenuated and considered safe for use in humans of all ages; however, it predominantly induces a CD4 + T cell response which is different compared to MVA [114] . Both MVA and NYVAC provoke robust humoral responses, and can be delivered mucosally to induce mucosal antibody responses [121] . There has been only limited exploration of NYVAC as a vaccine vector for influenza virus; however, a vaccine expressing the HA from A/chicken/Indonesia/7/2003 (H5N1) was shown to induce potent neutralizing antibody responses and protect against challenge in swine [122] .
While there is strong safety and efficacy data for use of NYVAC or MVA-vectored influenza vaccines, preexisting immunity remains a concern. Although the smallpox vaccination campaign has resulted in a population of poxvirus-naï ve people, the initiation of an MVA or NYVAC vaccination program for HIV, influenza or other pathogens will rapidly reduce this susceptible population. While there is significant interest in development of pox-vectored influenza virus vaccines, current influenza vaccination strategies rely upon regular immunization with vaccines matched to circulating strains. This would likely limit the use and/or efficacy of poxvirus-vectored influenza virus vaccines for regular and seasonal use [13] . Intriguingly, NYVAC may have an advantage for use as an influenza vaccine vector, because immunization with this vector induces weaker vaccine-specific immune responses compared to other poxvirus vaccines, a feature that may address the concerns surrounding preexisting immunity [123] .
While poxvirus-vectored vaccines have not yet been approved for use in humans, there is a growing list of licensed poxvirus for veterinary use that include fowlpox-and canarypox-vectored vaccines for avian and equine influenza viruses, respectively [124, 125] . The fowlpox-vectored vaccine expressing the avian influenza virus HA antigen has the added benefit of providing protection against fowlpox infection. Currently, at least ten poxvirus-vectored vaccines have been licensed for veterinary use [126] . These poxvirus vectors have the potential for use as vaccine vectors in humans, similar to the first use of cowpox for vaccination against smallpox [127] . The availability of these non-human poxvirus vectors with extensive animal safety and efficacy data may address the issues with preexisting immunity to the human vaccine strains, although the cross-reactivity originally described with cowpox could also limit use.
Influenza vaccines utilizing vesicular stomatitis virus (VSV), a rhabdovirus, as a vaccine vector have a number of advantages shared with other RNA virus vaccine vectors. Both live and replication-defective VSV vaccine vectors have been shown to be immunogenic [128, 129] , and like Paramyxoviridae, the Rhabdoviridae genome has a 3'-to-5' gradient of gene expression enabling attention by selective vaccine gene insertion or genome rearrangement [130] . VSV has a number of other advantages including broad tissue tropism, and the potential for intramuscular or intranasal immunization. The latter delivery method enables induction of mucosal immunity and elimination of needles required for vaccination. Also, there is little evidence of VSV seropositivity in humans eliminating concerns of preexisting immunity, although repeated use may be a concern. Also, VSV vaccine can be produced using existing mammalian vaccine manufacturing cell lines.
Influenza antigens were first expressed in a VSV vector in 1997. Both the HA and NA were shown to be expressed as functional proteins and incorporated into the recombinant VSV particles [131] . Subsequently, VSV-HA, expressing the HA protein from A/WSN/1933 (H1N1) was shown to be immunogenic and protect mice from lethal influenza virus challenge [129] . To reduce safety concerns, attenuated VSV vectors were developed. One candidate vaccine had a truncated VSV G protein, while a second candidate was deficient in G protein expression and relied on G protein expressed by a helper vaccine cell line to the provide the virus receptor. Both vectors were found to be attenuated in mice, but maintained immunogenicity [128] . More recently, single-cycle replicating VSV vaccines have been tested for efficacy against H5N1 HPAIV. VSV vectors expressing the HA from A/Hong Kong/156/97 (H5N1) were shown to be immunogenic and induce cross-reactive antibody responses and protect against challenge with heterologous H5N1 challenge in murine and NHP models [132] [133] [134] .
VSV vectors are not without potential concerns. VSV can cause disease in a number of species, including humans [135] . The virus is also potentially neuroinvasive in some species [136] , although NHP studies suggest this is not a concern in humans [137] . Also, while the incorporation of the influenza antigen in to the virion may provide some benefit in immunogenicity, changes in tropism or attenuation could arise from incorporation of different influenza glycoproteins. There is no evidence for this, however [134] . Currently, there is no human safety data for VSV-vectored vaccines. While experimental data is promising, additional work is needed before consideration for human influenza vaccination.
Current influenza vaccines rely on matching the HA antigen of the vaccine with circulating strains to provide strain-specific neutralizing antibody responses [4, 14, 24] . There is significant interest in developing universal influenza vaccines that would not require annual reformulation to provide protective robust and durable immunity. These vaccines rely on generating focused immune responses to highly conserved portions of the virus that are refractory to mutation [30] [31] [32] . Traditional vaccines may not be suitable for these vaccination strategies; however, vectored vaccines that have the ability to be readily modified and to express transgenes are compatible for these applications.
The NP and M2 proteins have been explored as universal vaccine antigens for decades. Early work with recombinant viral vectors demonstrated that immunization with vaccines expressing influenza antigens induced potent CD8 + T cell responses [107, [138] [139] [140] [141] . These responses, even to the HA antigen, could be cross-protective [138] . A number of studies have shown that immunization with NP expressed by AAV, rAd5, alphavirus vectors, MVA, or other vector systems induces potent CD8 + T cell responses and protects against influenza virus challenge [52, 63, 69, 102, 139, 142] . As the NP protein is highly conserved across influenza A viruses, NP-specific T cells can protect against heterologous and even heterosubtypic virus challenges [30] .
The M2 protein is also highly conserved and expressed on the surface of infected cells, although to a lesser extent on the surface of virus particles [30] . Much of the vaccine work in this area has focused on virus-like or subunit particles expressing the M2 ectodomain; however, studies utilizing a DNA-prime, rAd-boost strategies to vaccinate against the entire M2 protein have shown the antigen to be immunogenic and protective [50] . In these studies, antibodies to the M2 protein protected against homologous and heterosubtypic challenge, including a H5N1 HPAIV challenge. More recently, NP and M2 have been combined to induce broadly cross-reactive CD8 + T cell and antibody responses, and rAd5 vaccines expressing these antigens have been shown to protect against pH1N1 and H5N1 challenges [29, 51] .
Historically, the HA has not been widely considered as a universal vaccine antigen. However, the recent identification of virus neutralizing monoclonal antibodies that cross-react with many subtypes of influenza virus [143] has presented the opportunity to design vaccine antigens to prime focused antibody responses to the highly conserved regions recognized by these monoclonal antibodies. The majority of these broadly cross-reactive antibodies recognize regions on the stalk of the HA protein [143] . The HA stalk is generally less immunogenic compared to the globular head of the HA protein so most approaches have utilized -headless‖ HA proteins as immunogens. HA stalk vaccines have been designed using DNA and virus-like particles [144] and MVA [142] ; however, these approaches are amenable to expression in any of the viruses vectors described here.
The goal of any vaccine is to protect against infection and disease, while inducing population-based immunity to reduce or eliminate virus transmission within the population. It is clear that currently licensed influenza vaccines have not fully met these goals, nor those specific to inducing long-term, robust immunity. There are a number of vaccine-related issues that must be addressed before population-based influenza vaccination strategies are optimized. The concept of a -one size fits all‖ vaccine needs to be updated, given the recent ability to probe the virus-host interface through RNA interference approaches that facilitate the identification of host genes affecting virus replication, immunity, and disease. There is also a need for revision of the current influenza virus vaccine strategies for at-risk populations, particularly those at either end of the age spectrum. An example of an improved vaccine regime might include the use of a vectored influenza virus vaccine that expresses the HA, NA and M and/or NP proteins for the two currently circulating influenza A subtypes and both influenza B strains so that vaccine take and vaccine antigen levels are not an issue in inducing protective immunity. Recombinant live-attenuated or replication-deficient influenza viruses may offer an advantage for this and other approaches.
Vectored vaccines can be constructed to express full-length influenza virus proteins, as well as generate conformationally restricted epitopes, features critical in generating appropriate humoral protection. Inclusion of internal influenza antigens in a vectored vaccine can also induce high levels of protective cellular immunity. To generate sustained immunity, it is an advantage to induce immunity at sites of inductive immunity to natural infection, in this case the respiratory tract. Several vectored vaccines target the respiratory tract. Typically, vectored vaccines generate antigen for weeks after immunization, in contrast to subunit vaccination. This increased presence and level of vaccine antigen contributes to and helps sustain a durable memory immune response, even augmenting the selection of higher affinity antibody secreting cells. The enhanced memory response is in part linked to the intrinsic augmentation of immunity induced by the vector. Thus, for weaker antigens typical of HA, vectored vaccines have the capacity to overcome real limitations in achieving robust and durable protection.
Meeting the mandates of seasonal influenza vaccine development is difficult, and to respond to a pandemic strain is even more challenging. Issues with influenza vaccine strain selection based on recently circulating viruses often reflect recommendations by the World Health Organization (WHO)-a process that is cumbersome. The strains of influenza A viruses to be used in vaccine manufacture are not wild-type viruses but rather reassortants that are hybrid viruses containing at least the HA and NA gene segments from the target strains and other gene segments from the master strain, PR8, which has properties of high growth in fertilized hen's eggs. This additional process requires more time and quality control, and specifically for HPAI viruses, it is a process that may fail because of the nature of those viruses. In contrast, viral-vectored vaccines are relatively easy to manipulate and produce, and have well-established safety profiles. There are several viral-based vectors currently employed as antigen delivery systems, including poxviruses, adenoviruses baculovirus, paramyxovirus, rhabdovirus, and others; however, the majority of human clinical trials assessing viral-vectored influenza vaccines use poxvirus and adenovirus vectors. While each of these vector approaches has unique features and is in different stages of development, the combined successes of these approaches supports the virus-vectored vaccine approach as a whole. Issues such as preexisting immunity and cold chain requirements, and lingering safety concerns will have to be overcome; however, each approach is making progress in addressing these issues, and all of the approaches are still viable. Virus-vectored vaccines hold particular promise for vaccination with universal or focused antigens where traditional vaccination methods are not suited to efficacious delivery of these antigens. The most promising approaches currently in development are arguably those targeting conserved HA stalk region epitopes. Given the findings to date, virus-vectored vaccines hold great promise and may overcome the current limitations of influenza vaccines. | What have the studies on NP shown for the protection against influenza challege? | false | 1,647 | {
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1,698 | Accelerated viral dynamics in bat cell lines, with implications for zoonotic emergence
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7064339/
SHA: f2cc0d63ff2c4aaa127c4caae21d8f3a0067e3d5
Authors: Brook, Cara E; Boots, Mike; Chandran, Kartik; Dobson, Andrew P; Drosten, Christian; Graham, Andrea L; Grenfell, Bryan T; Müller, Marcel A; Ng, Melinda; Wang, Lin-Fa; van Leeuwen, Anieke
Date: 2020-02-03
DOI: 10.7554/elife.48401
License: cc-by
Abstract: Bats host virulent zoonotic viruses without experiencing disease. A mechanistic understanding of the impact of bats’ virus hosting capacities, including uniquely constitutive immune pathways, on cellular-scale viral dynamics is needed to elucidate zoonotic emergence. We carried out virus infectivity assays on bat cell lines expressing induced and constitutive immune phenotypes, then developed a theoretical model of our in vitro system, which we fit to empirical data. Best fit models recapitulated expected immune phenotypes for representative cell lines, supporting robust antiviral defenses in bat cells that correlated with higher estimates for within-host viral propagation rates. In general, heightened immune responses limit pathogen-induced cellular morbidity, which can facilitate the establishment of rapidly-propagating persistent infections within-host. Rapidly-transmitting viruses that have evolved with bat immune systems will likely cause enhanced virulence following emergence into secondary hosts with immune systems that diverge from those unique to bats.
Text: Bats have received much attention in recent years for their role as reservoir hosts for emerging viral zoonoses, including rabies and related lyssaviruses, Hendra and Nipah henipaviruses, Ebola and Marburg filoviruses, and SARS coronavirus (Calisher et al., 2006; Wang and Anderson, 2019) . In most non-Chiropteran mammals, henipaviruses, filoviruses, and coronaviruses induce substantial morbidity and mortality, display short durations of infection, and elicit robust, long-term immunity in hosts surviving infection (Nicholls et al., 2003; Hooper et al., 2001; Mahanty and Bray, 2004) . Bats, by contrast, demonstrate no obvious disease symptoms upon infection with pathogens that are highly virulent in non-volant mammals (Schountz et al., 2017) but may, instead, support viruses as longterm persistent infections, rather than transient, immunizing pathologies (Plowright et al., 2016) .
Recent research advances are beginning to shed light on the molecular mechanisms by which bats avoid pathology from these otherwise virulent pathogens (Brook and Dobson, 2015) . Bats leverage a suite of species-specific mechanisms to limit viral load, which include host receptor sequence incompatibilities for some bat-virus combinations (Ng et al., 2015; Takadate et al., 2020) and constitutive expression of the antiviral cytokine, IFN-a, for others (Zhou et al., 2016) . Typically, the presence of viral RNA or DNA in the cytoplasm of mammalian cells will induce secretion of type I interferon proteins (IFN-a and IFN-b), which promote expression and translation of interferon-stimulated genes (ISGs) in neighboring cells and render them effectively antiviral (Stetson and Medzhitov, 2006) . In some bat cells, the transcriptomic blueprints for this IFN response are expressed constitutively, even in the absence of stimulation by viral RNA or DNA (Zhou et al., 2016) . In non-flying mammals, constitutive IFN expression would likely elicit widespread inflammation and concomitant immunopathology upon viral infection, but bats support unique adaptations to combat inflammation (Zhang et al., 2013; Ahn et al., 2019; Xie et al., 2018; Pavlovich et al., 2018) that may have evolved to mitigate metabolic damage induced during flight (Kacprzyk et al., 2017) . The extent to which constitutive IFN-a expression signifies constitutive antiviral defense in the form of functional IFN-a protein remains unresolved. In bat cells constitutively expressing IFN-a, some protein-stimulated, downstream ISGs appear to be also constitutively expressed, but additional ISG induction is nonetheless possible following viral challenge and stimulation of IFN-b (Zhou et al., 2016; Xie et al., 2018) . Despite recent advances in molecular understanding of bat viral tolerance, the consequences of this unique bat immunity on within-host virus dynamics-and its implications for understanding zoonotic emergence-have yet to be elucidated.
The field of 'virus dynamics' was first developed to describe the mechanistic underpinnings of long-term patterns of steady-state viral load exhibited by patients in chronic phase infections with HIV, who appeared to produce and clear virus at equivalent rates (Nowak and May, 2000; Ho et al., 1995) . Models of simple target cell depletion, in which viral load is dictated by a bottom-eLife digest Bats can carry viruses that are deadly to other mammals without themselves showing serious symptoms. In fact, bats are natural reservoirs for viruses that have some of the highest fatality rates of any viruses that people acquire from wild animals -including rabies, Ebola and the SARS coronavirus.
Bats have a suite of antiviral defenses that keep the amount of virus in check. For example, some bats have an antiviral immune response called the interferon pathway perpetually switched on. In most other mammals, having such a hyper-vigilant immune response would cause harmful inflammation. Bats, however, have adapted anti-inflammatory traits that protect them from such harm, include the loss of certain genes that normally promote inflammation. However, no one has previously explored how these unique antiviral defenses of bats impact the viruses themselves. Now, Brook et al. have studied this exact question using bat cells grown in the laboratory. The experiments made use of cells from one bat species -the black flying fox -in which the interferon pathway is always on, and another -the Egyptian fruit bat -in which this pathway is only activated during an infection. The bat cells were infected with three different viruses, and then Brook et al. observed how the interferon pathway helped keep the infections in check, before creating a computer model of this response. The experiments and model helped reveal that the bats' defenses may have a potential downside for other animals, including humans. In both bat species, the strongest antiviral responses were countered by the virus spreading more quickly from cell to cell. This suggests that bat immune defenses may drive the evolution of faster transmitting viruses, and while bats are well protected from the harmful effects of their own prolific viruses, other creatures like humans are not.
The findings may help to explain why bats are often the source for viruses that are deadly in humans. Learning more about bats' antiviral defenses and how they drive virus evolution may help scientists develop better ways to predict, prevent or limit the spread of viruses from bats to humans. More studies are needed in bats to help these efforts. In the meantime, the experiments highlight the importance of warning people to avoid direct contact with wild bats. up resource supply of infection-susceptible host cells, were first developed for HIV (Perelson, 2002) but have since been applied to other chronic infections, including hepatitis-C virus (Neumann et al., 1998) , hepatitis-B virus (Nowak et al., 1996) and cytomegalovirus (Emery et al., 1999) . Recent work has adopted similar techniques to model the within-host dynamics of acute infections, such as influenza A and measles, inspiring debate over the extent to which explicit modeling of top-down immune control can improve inference beyond the basic resource limitation assumptions of the target cell model (Baccam et al., 2006; Pawelek et al., 2012; Saenz et al., 2010; Morris et al., 2018) .
To investigate the impact of unique bat immune processes on in vitro viral kinetics, we first undertook a series of virus infection experiments on bat cell lines expressing divergent interferon phenotypes, then developed a theoretical model elucidating the dynamics of within-host viral spread. We evaluated our theoretical model analytically independent of the data, then fit the model to data recovered from in vitro experimental trials in order to estimate rates of within-host virus transmission and cellular progression to antiviral status under diverse assumptions of absent, induced, and constitutive immunity. Finally, we confirmed our findings in spatially-explicit stochastic simulations of fitted time series from our mean field model. We hypothesized that top-down immune processes would overrule classical resource-limitation in bat cell lines described as constitutively antiviral in the literature, offering a testable prediction for models fit to empirical data. We further predicted that the most robust antiviral responses would be associated with the most rapid within-host virus propagation rates but also protect cells against virus-induced mortality to support the longest enduring infections in tissue culture.
We first explored the influence of innate immune phenotype on within-host viral propagation in a series of infection experiments in cell culture. We conducted plaque assays on six-well plate monolayers of three immortalized mammalian kidney cell lines: [1] Vero (African green monkey) cells, which are IFN-defective and thus limited in antiviral capacity (Desmyter et al., 1968) ; [2] RoNi/7.1 (Rousettus aegyptiacus) cells which demonstrate idiosyncratic induced interferon responses upon viral challenge (Kuzmin et al., 2017; Arnold et al., 2018; Biesold et al., 2011; Pavlovich et al., 2018) ; and [3] PaKiT01 (Pteropus alecto) cells which constitutively express IFN-a (Zhou et al., 2016; Crameri et al., 2009) . To intensify cell line-specific differences in constitutive immunity, we carried out infectivity assays with GFP-tagged, replication-competent vesicular stomatitis Indiana viruses: rVSV-G, rVSV-EBOV, and rVSV-MARV, which have been previously described (Miller et al., 2012; Wong et al., 2010) . Two of these viruses, rVSV-EBOV and rVSV-MARV, are recombinants for which cell entry is mediated by the glycoprotein of the bat-evolved filoviruses, Ebola (EBOV) and Marburg (MARV), thus allowing us to modulate the extent of structural, as well as immunological, antiviral defense at play in each infection. Previous work in this lab has demonstrated incompatibilities in the NPC1 filovirus receptor which render PaKiT01 cells refractory to infection with rVSV-MARV (Ng and Chandrab, 2018, Unpublished results) , making them structurally antiviral, over and above their constitutive expression of IFN-a. All three cell lines were challenged with all three viruses at two multiplicities of infection (MOI): 0.001 and 0.0001. Between 18 and 39 trials were run at each cell-virus-MOI combination, excepting rVSV-MARV infections on PaKiT01 cells at MOI = 0.001, for which only eight trials were run (see Materials and methods; Figure 1 -figure supplements 1-3, Supplementary file 1).
Because plaque assays restrict viral transmission neighbor-to-neighbor in two-dimensional cellular space (Howat et al., 2006) , we were able to track the spread of GFP-expressing virus-infected cells across tissue monolayers via inverted fluorescence microscopy. For each infection trial, we monitored and re-imaged plates for up to 200 hr of observations or until total monolayer destruction, processed resulting images, and generated a time series of the proportion of infectious-cell occupied plate space across the duration of each trial (see Materials and methods). We used generalized additive models to infer the time course of all cell culture replicates and construct the multi-trial dataset to which we eventually fit our mechanistic transmission model for each cell line-virus-specific combination ( Figure 1; Figure 1 -figure supplements 1-5).
All three recombinant vesicular stomatitis viruses (rVSV-G, rVSV-EBOV, and rVSV-MARV) infected Vero, RoNi/7.1, and PaKiT01 tissue cultures at both focal MOIs. Post-invasion, virus spread rapidly across most cell monolayers, resulting in virus-induced epidemic extinction. Epidemics were less severe in bat cell cultures, especially when infected with the recombinant filoviruses, rVSV-EBOV and rVSV-MARV. Monolayer destruction was avoided in the case of rVSV-EBOV and rVSV-MARV infections on PaKiT01 cells: in the former, persistent viral infection was maintained throughout the 200 hr duration of each experiment, while, in the latter, infection was eliminated early in the time series, preserving a large proportion of live, uninfectious cells across the duration of the experiment. We assumed this pattern to be the result of immune-mediated epidemic extinction (Figure 1) . Patterns from MOI = 0.001 were largely recapitulated at MOI = 0.0001, though at somewhat reduced total proportions (Figure 1-figure supplement 5 ).
A theoretical model fit to in vitro data recapitulates expected immune phenotypes for bat cells We next developed a within-host model to fit to these data to elucidate the effects of induced and constitutive immunity on the dynamics of viral spread in host tissue ( Figure 1 ). The compartmental within-host system mimicked our two-dimensional cell culture monolayer, with cells occupying five distinct infection states: susceptible (S), antiviral (A), exposed (E), infectious (I), and dead (D). We modeled exposed cells as infected but not yet infectious, capturing the 'eclipse phase' of viral integration into a host cell which precedes viral replication. Antiviral cells were immune to viral infection, in accordance with the 'antiviral state' induced from interferon stimulation of ISGs in tissues adjacent to infection (Stetson and Medzhitov, 2006) . Because we aimed to translate available data into modeled processes, we did not explicitly model interferon dynamics but instead scaled the rate of cell progression from susceptible to antiviral (r) by the proportion of exposed cells (globally) in the system. In systems permitting constitutive immunity, a second rate of cellular acquisition of antiviral status (") additionally scaled with the global proportion of susceptible cells in the model. Compared with virus, IFN particles are small and highly diffusive, justifying this global signaling assumption at the limited spatial extent of a six-well plate and maintaining consistency with previous modeling approximations of IFN signaling in plaque assay (Howat et al., 2006) .
To best represent our empirical monolayer system, we expressed our state variables as proportions (P S , P A , P E , P I , and P D ), under assumptions of frequency-dependent transmission in a wellmixed population (Keeling and Rohani, 2008) , though note that the inclusion of P D (representing the proportion of dead space in the modeled tissue) had the functional effect of varying transmission with infectious cell density. This resulted in the following system of ordinary differential equations:
We defined 'induced immunity' as complete, modeling all cells as susceptible to viral invasion at disease-free equilibrium, with defenses induced subsequent to viral exposure through the term r. By contrast, we allowed the extent of constitutive immunity to vary across the parameter range of " > 0, defining a 'constitutive' system as one containing any antiviral cells at disease-free equilibrium. In fitting this model to tissue culture data, we independently estimated both r and "; as well as the cell-to-cell transmission rate, b, for each cell-virus combination. Since the extent to which constitutively-expressed IFN-a is constitutively translated into functional protein is not yet known for bat hosts (Zhou et al., 2016) , this approach permitted our tissue culture data to drive modeling inference: even in PaKiT01 cell lines known to constitutively express IFN-a, the true constitutive extent of the system (i.e. the quantity of antiviral cells present at disease-free equilibrium) was allowed to vary through estimation of ": For the purposes of model-fitting, we fixed the value of c, the return rate of antiviral cells to susceptible status, at 0. The small spatial scale and short time course (max 200 hours) of our experiments likely prohibited any return of antiviral cells to susceptible status in our empirical system; nonetheless, we retained the term c in analytical evaluations of our model because regression from antiviral to susceptible status is possible over long time periods in vitro and at the scale of a complete organism (Radke et al., 1974; Rasmussen and Farley, 1975; Samuel and Knutson, 1982) .
Before fitting to empirical time series, we undertook bifurcation analysis of our theoretical model and generated testable hypotheses on the basis of model outcomes. From our within-host model system (Equation 1-5), we derived the following expression for R 0 , the pathogen basic reproduction number (Supplementary file 2):
Pathogens can invade a host tissue culture when R 0 >1. Rapid rates of constitutive antiviral acquisition (") will drive R 0 <1: tissue cultures with highly constitutive antiviral immunity will be therefore resistant to virus invasion from the outset. Since, by definition, induced immunity is stimulated following initial virus invasion, the rate of induced antiviral acquisition (r) is not incorporated into the equation for R 0 ; while induced immune processes can control virus after initial invasion, they cannot prevent it from occurring to begin with. In cases of fully induced or absent immunity (" ¼ 0), the R 0 equation thus reduces to a form typical of the classic SEIR model:
At equilibrium, the theoretical, mean field model demonstrates one of three infection states: endemic equilibrium, stable limit cycles, or no infection ( Figure 2) . Respectively, these states approximate the persistent infection, virus-induced epidemic extinction, and immune-mediated epidemic extinction phenotypes previously witnessed in tissue culture experiments ( Figure 1 ). Theoretically, endemic equilibrium is maintained when new infections are generated at the same rate at which infections are lost, while limit cycles represent parameter space under which infectious and susceptible populations are locked in predictable oscillations. Endemic equilibria resulting from cellular regeneration (i.e. births) have been described in vivo for HIV (Coffin, 1995) and in vitro for herpesvirus plaque assays (Howat et al., 2006) , but, because they so closely approach zero, true limit cycles likely only occur theoretically, instead yielding stochastic extinctions in empirical time series.
Bifurcation analysis of our mean field model revealed that regions of no infection (pathogen extinction) were bounded at lower threshold (Branch point) values for b, below which the pathogen was unable to invade. We found no upper threshold to invasion for b under any circumstances (i.e. b high enough to drive pathogen-induced extinction), but high b values resulted in Hopf bifurcations, which delineate regions of parameter space characterized by limit cycles. Since limit cycles so closely approach zero, high bs recovered in this range would likely produce virus-induced epidemic extinctions under experimental conditions. Under more robust representations of immunity, with higher values for either or both induced (r) and constitutive (") rates of antiviral acquisition, Hopf bifurcations occurred at increasingly higher values for b, meaning that persistent infections could establish at higher viral transmission rates ( Figure 2 ). Consistent with our derivation for R 0 , we found that the Branch point threshold for viral invasion was independent of changes to the induced immune parameter (r) but saturated at high values of " that characterize highly constitutive immunity ( Figure 3) .
We next fit our theoretical model by least squares to each cell line-virus combination, under absent, induced, and constitutive assumptions of immunity. In general, best fit models recapitulated expected outcomes based on the immune phenotype of the cell line in question, as described in the general literature (Table 1 Ironically, the induced immune model offered a slightly better fit than the constitutive to rVSV-MARV infections on the PaKiT01 cell line (the one cell line-virus combination for which we know a constitutively antiviral cell-receptor incompatibility to be at play). Because constitutive immune assumptions can prohibit pathogen invasion (R 0 <1), model fits to this time series under constitutive assumptions were handicapped by overestimations of ", which prohibited pathogen invasion. Only by incorporating an exceedingly rapid rate of induced antiviral acquisition could the model guarantee that initial infection would be permitted and then rapidly controlled. In all panel (A) plots, the rate of induced immune antiviral acquisition (r) was fixed at 0.01. Panel (B) depicts dynamics under variably induced immunity, ranging from absent (left: r=0) to high (right: r=1). In all panel (B) plots, the rate of constitutive antiviral acquisition (") was fixed at 0.0001 Branch point curves are represented as solid lines and Hopf curves as dashed lines. White space indicates endemic equilibrium (persistence), gray space indicates limit cycles, and black space indicates no infection (extinction). Other parameter values for equilibrium analysis were fixed at: b = .025, m = .001, s = 1/6, c = 0. Special points from bifurcations analyses are listed in Supplementary file 3.
In fitting our theoretical model to in vitro data, we estimated the within-host virus transmission rate (b) and the rate(s) of cellular acquisition to antiviral status (r or r + ") ( Table 1 ; Supplementary file 4). Under absent immune assumptions, r and " were fixed at 0 while b was estimated; under induced immune assumptions, " was fixed at 0 while r and b were estimated; and under constitutive immune assumptions, all three parameters (r, ", and b) were simultaneously estimated for each cell-virus combination. Best fit parameter estimates for MOI=0.001 data are visualized in conjunction with br and b -" bifurcations in (r) and (B) the constitutive immunity rate of antiviral acquisition ("). Panels show variation in the extent of immunity, from absent (left) to high (right). Branch point curves are represented as solid lines and Hopf curves as dashed lines. White space indicates endemic equilibrium (persistence), gray space indicates limit cycling, and black space indicates no infection (extinction). Other parameter values for equilibrium analysis were fixed at: b = .025, m = .001, s = 1/6, a = 1/6, c = 0. Special points from bifurcations analyses are listed in Supplementary file 3. space corresponding to theoretical limit cycles, consistent with observed virus-induced epidemic extinctions in stochastic tissue cultures.
In contrast to Vero cells, the induced immunity model offered the best fit to all RoNi/7.1 data, consistent with reported patterns in the literature and our own validation by qPCR ( Table 1; Arnold et al., 2018; Kuzmin et al., 2017; Biesold et al., 2011; Pavlovich et al., 2018) . As in Vero cell trials, we estimated highest b values for rVSV-G infections on RoNi/7.1 cell lines but here recovered higher b estimates for rVSV-MARV than for rVSV-EBOV. This reversal was balanced by a higher estimated rate of acquisition to antiviral status (r) for rVSV-EBOV versus rVSV-MARV. In general, we observed that more rapid rates of antiviral acquisition (either induced, r, constitutive, ", or both) correlated with higher transmission rates (b). When offset by r, b values estimated for RoNi/7.1 infections maintained the same amplitude as those estimated for immune-absent Vero cell lines but caused gentler epidemics and reduced cellular mortality (Figure 1) . RoNi/7.1 parameter estimates localized in the region corresponding to endemic equilibrium for the deterministic, theoretical model (Figure 4) , yielding less acute epidemics which nonetheless went extinct in stochastic experiments.
Finally, rVSV-G and rVSV-EBOV trials on PaKiT01 cells were best fit by models assuming constitutive immunity, while rVSV-MARV infections on PaKiT01 were matched equivalently by models assuming either induced or constitutive immunity-with induced models favored over constitutive in AIC comparisons because one fewer parameter was estimated (Figure 1-figure supplements 4-5; Supplementary file 4). For all virus infections, PaKiT01 cell lines yielded b estimates a full order of magnitude higher than Vero or RoNi/7.1 cells, with each b balanced by an immune response (either r, or r combined with ") also an order of magnitude higher than that recovered for the other cell lines ( Figure 4 ; Table 1 ). As in RoNi/7.1 cells, PaKiT01 parameter fits localized in the region corresponding to endemic equilibrium for the deterministic theoretical model. Because constitutive immune processes can actually prohibit initial pathogen invasion, constitutive immune fits to rVSV-MARV infections on PaKiT01 cell lines consistently localized at or below the Branch point threshold for virus invasion (R 0 ¼ 1). During model fitting for optimization of ", any parameter tests of " values producing R 0 <1 resulted in no infection and, consequently, produced an exceedingly poor fit to infectious time series data. In all model fits assuming constitutive immunity, across all cell lines, antiviral contributions from " prohibited virus from invading at all. The induced immune model thus produced a more parsimonious recapitulation of these data because virus invasion was always permitted, then rapidly controlled.
In order to compare the relative contributions of each cell line's disparate immune processes to epidemic dynamics, we next used our mean field parameter estimates to calculate the initial 'antiviral rate'-the initial accumulation rate of antiviral cells upon virus invasion for each cell-virus-MOI combination-based on the following equation:
where P E was calculated from the initial infectious dose (MOI) of each infection experiment and P S was estimated at disease-free equilibrium:
Because and " both contribute to this initial antiviral rate, induced and constitutive immune assumptions are capable of yielding equally rapid rates, depending on parameter fits. Indeed, under fully induced immune assumptions, the induced antiviral acquisition rate (r) estimated for rVSV-MARV infection on PaKiT01 cells was so high that the initial antiviral rate exceeded even that estimated under constitutive assumptions for this cell-virus combination (Supplementary file 4) . In reality, we know that NPC1 receptor incompatibilities make PaKiT01 cell lines constitutively refractory to rVSV-MARV infection (Ng and Chandrab, 2018, Unpublished results) and that PaKiT01 cells also constitutively express the antiviral cytokine, IFN-a. Model fitting results suggest that this constitutive expression of IFN-a may act more as a rapidly inducible immune response following virus invasion than as a constitutive secretion of functional IFN-a protein. Nonetheless, as hypothesized, PaKiT01 cell lines were by far the most antiviral of any in our study-with initial antiviral rates estimated several orders of magnitude higher than any others in our study, under either induced or constitutive assumptions ( Table 1 ; Supplementary file 4). RoNi/7.1 cells displayed the second-most-pronounced signature of immunity, followed by Vero cells, for which the initial antiviral rate was essentially zero even under forced assumptions of induced or constitutive immunity ( Table 1 ; Supplementary file 4).
Using fitted parameters for b and ", we additionally calculated R 0 , the basic reproduction number for the virus, for each cell line-virus-MOI combination ( Table 1 ; Supplementary file 4). We found that R 0 was essentially unchanged across differing immune assumptions for RoNi/7.1 and Vero cells, for which the initial antiviral rate was low. In the case of PaKiT01 cells, a high initial antiviral rate under either induced or constitutive immunity resulted in a correspondingly high estimation of b (and, consequently, R 0 ) which still produced the same epidemic curve that resulted from the much lower estimates for b and R 0 paired with absent immunity. These findings suggest that antiviral immune responses protect host tissues against virus-induced cell mortality and may facilitate the establishment of more rapid within-host transmission rates.
Total monolayer destruction occurred in all cell-virus combinations excepting rVSV-EBOV infections on RoNi/7.1 cells and rVSV-EBOV and rVSV-MARV infections on PaKiT01 cells. Monolayer destruction corresponded to susceptible cell depletion and epidemic turnover where R-effective (the product of R 0 and the proportion susceptible) was reduced below one ( Figure 5) . For rVSV-EBOV infections on RoNi/7.1, induced antiviral cells safeguarded remnant live cells, which birthed new susceptible cells late in the time series. In rVSV-EBOV and rVSV-MARV infections on PaKiT01 cells, this antiviral protection halted the epidemic ( Figure 5 ; R-effective <1) before susceptibles fully declined. In the case of rVSV-EBOV on PaKiT01, the birth of new susceptibles from remnant live cells protected by antiviral status maintained late-stage transmission to facilitate long-term epidemic persistence. Importantly, under fixed parameter values for the infection incubation rate (s) and infectioninduced mortality rate (a), models were unable to reproduce the longer-term infectious time series captured in data from rVSV-EBOV infections on PaKiT01 cell lines without incorporation of cell births, an assumption adopted in previous modeling representations of IFN-mediated viral dynamics in tissue culture (Howat et al., 2006) . In our experiments, we observed that cellular reproduction took place as plaque assays achieved confluency. Finally, because the protective effect of antiviral cells is more clearly observable spatially, we confirmed our results by simulating fitted time series in a spatially-explicit, stochastic reconstruction of our mean field model. In spatial simulations, rates of antiviral acquisition were fixed at fitted values for r and " derived from mean field estimates, while transmission rates (b) were fixed at values ten times greater than those estimated under mean field conditions, accounting for the intensification of parameter thresholds permitting pathogen invasion in local spatial interactions (see Materials and methods; Videos 1-3; Figure 5-figure supplement 3; Supplementary file 5; Webb et al., 2007) . In immune capable time series, spatial antiviral cells acted as 'refugia' which protected live cells from infection as each initial epidemic wave 'washed' across a cell monolayer. Eventual birth of new susceptibles from these living refugia allowed for sustained epidemic transmission in cases where some infectious cells persisted at later timepoints in simulation (Videos 1-3; Figure 5-figure supplement 3 ).
Bats are reservoirs for several important emerging zoonoses but appear not to experience disease from otherwise virulent viral pathogens. Though the molecular biological literature has made great progress in elucidating the mechanisms by which bats tolerate viral infections (Zhou et al., 2016; Ahn et al., 2019; Xie et al., 2018; Pavlovich et al., 2018; Zhang et al., 2013) , the impact of unique bat immunity on virus dynamics within-host has not been well-elucidated. We used an innovative combination of in vitro experimentation and within-host modeling to explore the impact of unique bat immunity on virus dynamics. Critically, we found that bat cell lines demonstrated a signature of enhanced interferon-mediated immune response, of either constitutive or induced form, which allowed for establishment of rapid within-host, cell-to-cell virus transmission rates (b). These results were supported by both data-independent bifurcation analysis of our mean field theoretical model, as well as fitting of this model to viral infection time series established in bat cell culture. Additionally, we demonstrated that the antiviral state induced by the interferon pathway protects live cells from mortality in tissue culture, resulting in in vitro epidemics of extended duration that enhance the probability of establishing a long-term persistent infection. Our findings suggest that viruses evolved in bat reservoirs possessing enhanced IFN capabilities could achieve more rapid within-host transmission rates without causing pathology to their hosts. Such rapidly-reproducing viruses would likely generate extreme virulence upon spillover to hosts lacking similar immune capacities to bats.
To achieve these results, we first developed a novel, within-host, theoretical model elucidating the effects of unique bat immunity, then undertook bifurcation analysis of the model's equilibrium properties under immune absent, induced, and constitutive assumptions. We considered a cell line to be constitutively immune if possessing any number of antiviral cells at disease-free equilibrium but allowed the extent of constitutive immunity to vary across the parameter range for ", the constitutive rate of antiviral acquisition. In deriving the equation for R 0 , the basic reproduction number, which defines threshold conditions for virus invasion of a tissue (R 0 >1), we demonstrated how the invasion threshold is elevated at high values of constitutive antiviral acquisition, ". Constitutive immune processes can thus prohibit pathogen invasion, while induced responses, by definition, can only control infections post-hoc. Once thresholds for pathogen invasion have been met, assumptions of constitutive immunity will limit the cellular mortality (virulence) incurred at high transmission rates. Regardless of mechanism (induced or constitutive), interferon-stimulated antiviral cells appear to play a key role in maintaining longer term or persistent infections by safeguarding susceptible cells from rapid infection and concomitant cell death. Fitting of our model to in vitro data supported expected immune phenotypes for different bat cell lines as described in the literature. Simple target cell models that ignore the effects of immunity best recapitulated infectious time series derived from IFN-deficient Vero cells, while models assuming induced immune processes most accurately reproduced trials derived from RoNi/7.1 (Rousettus aegyptiacus) cells, which possess a standard virusinduced IFN-response. In most cases, models assuming constitutive immune processes best recreated virus epidemics produced on PaKiT01 (Pteropus alecto) cells, which are known to constitutively express the antiviral cytokine, IFN-a (Zhou et al., 2016) . Model support for induced immune assumptions in fits to rVSV-MARV infections on PaKiT01 cells suggests that the constitutive IFN-a expression characteristic of P. alecto cells may represent more of a constitutive immune priming process than a perpetual, functional, antiviral defense. Results from mean field model fitting were additionally confirmed in spatially explicit stochastic simulations of each time series.
As previously demonstrated in within-host models for HIV (Coffin, 1995; Perelson et al., 1996; Nowak et al., 1995; Bonhoeffer et al., 1997; Ho et al., 1995) , assumptions of simple target-cell depletion can often provide satisfactory approximations of viral dynamics, especially those reproduced in simple in vitro systems. Critically, our model fitting emphasizes the need for incorporation of top-down effects of immune control in order to accurately reproduce infectious time series derived from bat cell tissue cultures, especially those resulting from the robustly antiviral PaKiT01 P. alecto cell line. These findings indicate that enhanced IFN-mediated immune pathways in bat reservoirs may promote elevated within-host virus replication rates prior to cross-species emergence. We nonetheless acknowledge the limitations imposed by in vitro experiments in tissue culture, especially involving recombinant viruses and immortalized cell lines. Future work should extend these cell culture studies to include measurements of multiple state variables (i.e. antiviral cells) to enhance epidemiological inference.
The continued recurrence of Ebola epidemics across central Africa highlights the importance of understanding bats' roles as reservoirs for virulent zoonotic disease. The past decade has born witness to emerging consensus regarding the unique pathways by which bats resist and tolerate highly virulent infections (Brook and Dobson, 2015; Xie et al., 2018; Zhang et al., 2013; Ahn et al., 2019; Zhou et al., 2016; Ng et al., 2015; Pavlovich et al., 2018) . Nonetheless, an understanding of the mechanisms by which bats support endemic pathogens at the population level, or promote the evolution of virulent pathogens at the individual level, remains elusive. Endemic maintenance of infection is a defining characteristic of a pathogen reservoir (Haydon et al., 2002) , and bats appear to merit such a title, supporting long-term persistence of highly transmissible viral infections in isolated island populations well below expected critical community sizes (Peel et al., 2012) . Researchers debate the relative influence of population-level and within-host mechanisms which might explain these trends (Plowright et al., 2016) , but increasingly, field data are difficult to reconcile without acknowledgement of a role for persistent infections (Peel et al., 2018; Brook et al., 2019) . We present general methods to study cross-scale viral dynamics, which suggest that within-host persistence is supported by robust antiviral responses characteristic of bat immune processes. Viruses which evolve rapid replication rates under these robust antiviral defenses may pose the greatest hazard for cross-species pathogen emergence into spillover hosts with immune systems that differ from those unique to bats.
All experiments were carried out on three immortalized mammalian kidney cell lines: Vero (African green monkey), RoNi/7.1 (Rousettus aegyptiacus) (Kühl et al., 2011; Biesold et al., 2011) and PaKiT01 (Pteropus alecto) (Crameri et al., 2009) . The species identifications of all bat cell lines was confirmed morphologically and genetically in the publications in which they were originally described (Kühl et al., 2011; Biesold et al., 2011; Crameri et al., 2009) . Vero cells were obtained from ATCC.
Monolayers of each cell line were grown to 90% confluency (~9Â10 5 cells) in 6-well plates. Cells were maintained in a humidified 37˚C, 5% CO 2 incubator and cultured in Dulbecco's modified Eagle medium (DMEM) (Life Technologies, Grand Island, NY), supplemented with 2% fetal bovine serum (FBS) (Gemini Bio Products, West Sacramento, CA), and 1% penicillin-streptomycin (Life Technologies). Cells were tested monthly for mycoplasma contamination while experiments were taking place; all cells assayed negative for contamination at every testing.
Previous work has demonstrated that all cell lines used are capable of mounting a type I IFN response upon viral challenge, with the exception of Vero cells, which possess an IFN-b deficiency (Desmyter et al., 1968; Rhim et al., 1969; Emeny and Morgan, 1979) . RoNi/7.1 cells have been shown to mount idiosyncratic induced IFN defenses upon viral infection (Pavlovich et al., 2018; Kuzmin et al., 2017; Arnold et al., 2018; Kühl et al., 2011; Biesold et al., 2011) , while PaKiT01 cells are known to constitutively express the antiviral cytokine, IFN-a (Zhou et al., 2016) . This work is the first documentation of IFN signaling induced upon challenge with the particular recombinant VSVs outlined below. We verified known antiviral immune phenotypes via qPCR. Results were consistent with the literature, indicating a less pronounced role for interferon defense against viral infection in RoNi/7.1 versus PaKiT01 cells.
Replication-capable recombinant vesicular stomatitis Indiana viruses, expressing filovirus glycoproteins in place of wild type G (rVSV-G, rVSV-EBOV, and rVSV-MARV) have been previously described (Wong et al., 2010; Miller et al., 2012) . Viruses were selected to represent a broad range of anticipated antiviral responses from host cells, based on a range of past evolutionary histories between the virus glycoprotein mediating cell entry and the host cell's entry receptor. These interactions ranged from the total absence of evolutionary history in the case of rVSV-G infections on all cell lines to a known receptor-level cell entry incompatibility in the case of rVSV-MARV infections on PaKiT01 cell lines.
To measure infectivities of rVSVs on each of the cell lines outlined above, so as to calculate the correct viral dose for each MOI, NH 4 Cl (20 mM) was added to infected cell cultures at 1-2 hr postinfection to block viral spread, and individual eGFP-positive cells were manually counted at 12-14 hr post-infection.
Previously published work indicates that immortalized kidney cell lines of Rousettus aegyptiacus (RoNi/7.1) and Pteropus alecto (PaKiT01) exhibit different innate antiviral immune phenotypes through, respectively, induced (Biesold et al., 2011; Pavlovich et al., 2018; Kühl et al., 2011; Arnold et al., 2018) and constitutive (Zhou et al., 2016 ) expression of type I interferon genes. We verified these published phenotypes on our own cell lines infected with rVSV-G, rVSV-EBOV, and rVSV-MARV via qPCR of IFN-a and IFN-b genes across a longitudinal time series of infection.
Specifically, we carried out multiple time series of infection of each cell line with each of the viruses described above, under mock infection conditions and at MOIs of 0.0001 and 0.001-with the exception of rVSV-MARV on PaKiT01 cell lines, for which infection was only performed at MOI = 0.0001 due to limited viral stocks and the extremely low infectivity of this virus on this cell line (thus requiring high viral loads for initial infection). All experiments were run in duplicate on 6well plates, such that a typical plate for any of the three viruses had two control (mock) wells, two MOI = 0.0001 wells and two MOI = 0.001 wells, excepting PaKiT01 plates, which had two control and four MOI = 0.0001 wells at a given time. We justify this PaKiT01 exemption through the expectation that IFN-a expression is constitutive for these cells, and by the assumption that any expression exhibited at the lower MOI should also be present at the higher MOI.
For these gene expression time series, four 6-well plates for each cell line-virus combination were incubated with virus for one hour at 37˚C. Following incubation, virus was aspirated off, and cell monolayers were washed in PBS, then covered with an agar plaque assay overlay to mimic conditions under which infection trials were run. Plates were then harvested sequentially at timepoints of roughly 5, 10, 15, and 20 hr post-infection (exact timing varied as multiple trials were running simultaneously). Upon harvest of each plate, agar overlay was removed, and virus was lysed and RNA extracted from cells using the Zymo Quick RNA Mini Prep kit, according to the manufacturer's instructions and including the step for cellular DNA digestion. Post-extraction, RNA quality was verified via nanodrop, and RNA was converted to cDNA using the Invitrogen Superscript III cDNA synthesis kit, according to the manufacturer's instructions. cDNA was then stored at 4˚C and as a frozen stock at À20˚C to await qPCR.
We undertook qPCR of cDNA to assess expression of the type I interferon genes, IFN-a and IFNb, and the housekeeping gene, b-Actin, using primers previously reported in the literature (Supplementary file 6) . For qPCR, 2 ml of each cDNA sample was incubated with 7 ml of deionized water, 1 ml of 5 UM forward/reverse primer mix and 10 ml of iTaq Universal SYBR Green, then cycled on a QuantStudio3 Real-Time PCR machine under the following conditions: initial denaturation at 94 C for 2 min followed by 40 cycles of: denaturation at 95˚C (5 s), annealing at 58˚C (15 s), and extension at 72˚C (10 s).
We report simple d-Ct values for each run, with raw Ct of the target gene of interest (IFN-a or IFN-b) subtracted from raw Ct of the b-Actin housekeeping gene in Figure 1 -figure supplement 6. Calculation of fold change upon viral infection in comparison to mock using the d-d-Ct method (Livak and Schmittgen, 2001) was inappropriate in this case, as we wished to demonstrate constitutive expression of IFN-a in PaKiT01 cells, whereby data from mock cells was identical to that produced from infected cells.
After being grown to~90% confluency, cells were incubated with pelleted rVSVs expressing eGFP (rVSV-G, rVSV-EBOV, rVSV-MARV). Cell lines were challenged with both a low (0.0001) and high (0.001) multiplicity of infection (MOI) for each virus. In a cell monolayer infected at a given MOI (m), the proportion of cells (P), infected by k viral particles can be described by the Poisson distribution: P k ð Þ ¼ e Àm m k k! , such that the number of initially infected cells in an experiment equals: 1 À e Àm . We assumed that a~90% confluent culture at each trial's origin was comprised of~9x10 5 cells and conducted all experiments at MOIs of 0.0001 and 0.001, meaning that we began each trial by introducing virus to, respectively,~81 or 810 cells, representing the state variable 'E' in our theoretical model. Low MOIs were selected to best approximate the dynamics of mean field infection and limit artifacts of spatial structuring, such as premature epidemic extinction when growing plaques collide with plate walls in cell culture.
Six-well plates were prepared with each infection in duplicate or triplicate, such that a control well (no virus) and 2-3 wells each at MOI 0.001 and 0.0001 were incubated simultaneously on the same plate. In total, we ran between 18 and 39 trials at each cell-virus-MOI combination, excepting r-VSV-MARV infections on PaKiT01 cells at MOI = 0.001, for which we ran only eight trials due to the low infectivity of this virus on this cell line, which required high viral loads for initial infection. Cells were incubated with virus for one hour at 37˚C. Following incubation, virus was aspirated off, and cell monolayers were washed in PBS, then covered with a molten viscous overlay (50% 2X MEM/Lglutamine; 5% FBS; 3% HEPES; 42% agarose), cooled for 20 min, and re-incubated in their original humidified 37˚C, 5% CO 2 environment.
After application of the overlay, plates were monitored periodically using an inverted fluorescence microscope until the first signs of GFP expression were witnessed (~6-9.5 hr post-infection, depending on the cell line and virus under investigation). From that time forward, a square subset of the center of each well (comprised of either 64-or 36-subframes and corresponding to roughly 60% and 40% of the entire well space) was imaged periodically, using a CellInsight CX5 High Content Screening (HCS) Platform with a 4X air objective (ThermoFisher, Inc, Waltham, MA). Microscope settings were held standard across all trials, with exposure time fixed at 0.0006 s for each image. One color channel was imaged, such that images produced show GFP-expressing cells in white and non-GFP-expressing cells in black (Figure 1-figure supplement 1) .
Wells were photographed in rotation, as frequently as possible, from the onset of GFP expression until the time that the majority of cells in the well were surmised to be dead, GFP expression could no longer be detected, or early termination was desired to permit Hoechst staining.
In the case of PaKiT01 cells infected with rVSV-EBOV, where an apparently persistent infection established, the assay was terminated after 200+ hours (8+ days) of continuous observation. Upon termination of all trials, cells were fixed in formaldehyde (4% for 15 min), incubated with Hoechst stain (0.0005% for 15 min) (ThermoFisher, Inc, Waltham, MA), then imaged at 4X on the CellInsight CX5 High Content Screening (HCS) Platform. The machine was allowed to find optimal focus for each Hoechst stain image. One color channel was permitted such that images produced showed live nuclei in white and dead cells in black.
Hoechst stain colors cellular DNA, and viral infection is thought to interfere with the clarity of the stain (Dembowski and DeLuca, 2015) . As such, infection termination, cell fixation, and Hoechst staining enables generation of a rough time series of uninfectious live cells (i.e. susceptible + antiviral cells) to complement the images which produced time series of proportions infectious. Due to uncertainty over the exact epidemic state of Hoechst-stained cells (i.e. exposed but not yet infectious cells may still stain), we elected to fit our models only to the infectious time series derived from GFPexpressing images and used Hoechst stain images as a post hoc visual check on our fit only ( Figure 5 ; Figure 5 -figure supplements 1-2).
Images recovered from the time series above were processed into binary ('infectious' vs. 'non-infectious' or, for Hoechst-stained images, 'live' vs. 'dead') form using the EBImage package (Pau et al., 2010) in R version 3.6 for MacIntosh, after methods further detailed in Supplementary file 7. Binary images were then further processed into time series of infectious or, for Hoechst-stained images, live cells using a series of cell counting scripts. Because of logistical constraints (i.e. many plates of simultaneously running infection trials and only one available imaging microscope), the time course of imaging across the duration of each trial was quite variable. As such, we fitted a series of statistical models to our processed image data to reconstruct reliable values of the infectious proportion of each well per hour for each distinct trial in all cell line-virus-MOI combinations (Figure 1
To derive the expression for R 0 , the basic pathogen reproductive number in vitro, we used Next Generation Matrix (NGM) techniques (Diekmann et al., 1990; Heffernan et al., 2005) , employing Wolfram Mathematica (version 11.2) as an analytical tool. R 0 describes the number of new infections generated by an existing infection in a completely susceptible host population; a pathogen will invade a population when R 0 >1 (Supplementary file 2). We then analyzed stability properties of the system, exploring dynamics across a range of parameter spaces, using MatCont (version 2.2) (Dhooge et al., 2008) for Matlab (version R2018a) (Supplementary file 3).
The birth rate, b, and natural mortality rate, m, balance to yield a population-level growth rate, such that it is impossible to estimate both b and m simultaneously from total population size data alone. As such, we fixed b at. 025 and estimated m by fitting an infection-absent version of our mean field model to the susceptible time series derived via Hoechst staining of control wells for each of the three cell lines (Figure 1-figure supplement 7) . This yielded a natural mortality rate, m, corresponding to a lifespan of approximately 121, 191, and 84 hours, respectively, for Vero, RoNi/7.1, and PaKiT01 cell lines (Figure 1-figure supplement 7) . We then fixed the virus incubation rate, s, as the inverse of the shortest observed duration of time from initial infection to the observation of the first infectious cells via fluorescent microscope for all nine cell line -virus combinations (ranging 6 to 9.5 hours). We fixed a, the infection-induced mortality rate, at 1/6, an accepted standard for general viral kinetics (Howat et al., 2006) , and held c, the rate of antiviral cell regression to susceptible status, at 0 for the timespan (<200 hours) of the experimental cell line infection trials.
We estimated cell line-virus-MOI-specific values for b, r, and " by fitting the deterministic output of infectious proportions in our mean field model to the full suite of statistical outputs of all trials for each infected cell culture time series (Figure 1-figure supplements 2-3) . Fitting was performed by minimizing the sum of squared differences between the deterministic model output and cell linevirus-MOI-specific infectious proportion of the data at each timestep. We optimized parameters for MOI = 0.001 and 0.0001 simultaneously to leverage statistical power across the two datasets, estimating a different transmission rate, b, for trials run at each infectious dose but, where applicable, estimating the same rates of r and " across the two time series. We used the differential equation solver lsoda() in the R package deSolve (Soetaert et al., 2010) to obtain numerical solutions for the mean field model and carried out minimization using the 'Nelder-Mead' algorithm of the optim() function in base R. All model fits were conducted using consistent starting guesses for the parameters, b (b = 3), and where applicable, r (r = 0.001) and " (" = 0.001). In the case of failed fits or indefinite hessians, we generated a series of random guesses around the starting conditions and continued estimation until successful fits were achieved.
All eighteen cell line-virus-MOI combinations of data were fit by an immune absent (" = r = 0) version of the theoretical model and, subsequently, an induced immunity (" = 0; r >0) and constitutive immunity (" >0; r >0) version of the model. Finally, we compared fits across each cell line-virus-MOI combination via AIC. In calculating AIC, the number of fitted parameters in each model (k) varied across the immune phenotypes, with one parameter (b) estimated for absent immune assumptions, two (b and r) for induced immune assumptions, and three (b, r, and ") for constitutive immune assumptions. The sample size (n) corresponded to the number of discrete time steps across all empirical infectious trials to which the model was fitted for each cell-line virus combination. All fitting and model comparison scripts are freely available for download at the following FigShare repository: DOI: 10.6084/m9.figshare.8312807.
Finally, we verified all mean field fits in a spatial context, in order to more thoroughly elucidate the role of antiviral cells in each time series. We constructed our spatial model in C++ implemented in R using the packages Rcpp and RcppArmadillo (Eddelbuettel and Francois, 2011; Eddelbuettel and Sanderson, 2017) . Following Nagai and Honda (2001) and Howat et al. (2006) , we modeled this system on a two-dimensional hexagonal lattice, using a ten-minute epidemic timestep for cell state transitions. At the initialization of each simulation, we randomly assigned a duration of natural lifespan, incubation period, infectivity period, and time from antiviral to susceptible status to all cells in a theoretical monolayer. Parameter durations were drawn from a normal distribution centered at the inverse of the respective fixed rates of m, s, a, and c, as reported with our mean field model. Transitions involving the induced (r) and constitutive (") rates of antiviral acquisition were governed probabilistically and adjusted dynamically at each timestep based on the global environment. As such, we fixed these parameters at the same values estimated in the mean field model, and multiplied both r and " by the global proportion of, respectively, exposed and susceptible cells at a given timestep.
In contrast to antiviral acquisition rates, transitions involving the birth rate (b) and the transmission rate (b) occurred probabilistically based on each cell's local environment. The birth rate, b, was multiplied by the proportion of susceptible cells within a six-neighbor circumference of a focal dead cell, while b was multiplied by the proportion of infectious cells within a thirty-six neighbor vicinity of a focal susceptible cell, thus allowing viral transmission to extend beyond the immediate nearestneighbor boundaries of an infectious cell. To compensate for higher thresholds to cellular persistence and virus invasion which occur under local spatial conditions (Webb et al., 2007) , we increased the birth rate, b, and the cell-to-cell transmission rate, b, respectively, to six and ten times the values used in the mean field model (Supplementary file 4) . We derived these increases based on the assumption that births took place exclusively based on pairwise nearest-neighbor interactions (the six immediately adjacent cells to a focal dead cell), while viral transmission was locally concentrated but included a small (7.5%) global contribution, representing the thirty-six cell surrounding vicinity of a focal susceptible. We justify these increases and derive their origins further in Supplementary file 5.
We simulated ten stochastic spatial time series for all cell-virus combinations under all three immune assumptions at a population size of 10,000 cells and compared model output with data in . Transparent reporting form Data availability All data generated or analysed during this study are included in the manuscript and supporting files. All images and code used in this study have been made available for download at the following Figshare | What was the conclusion of the study ? | false | 2,734 | {
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"In both bat species, the strongest antiviral responses were countered by the virus spreading more quickly from cell to cell. This suggests that bat immune defenses may drive the evolution of faster transmitting viruses, and while bats are well protected from the harmful effects of their own prolific viruses, other creatures like humans are not."
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1,574 | Population-Based Pertussis Incidence and Risk Factors in Infants Less Than 6 Months in Nepal
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5907881/
SHA: ef821e34873d4752ecae41cd9dfc08a5e6db45e2
Authors: Hughes, Michelle M; Englund, Janet A; Kuypers, Jane; Tielsch, James M; Khatry, Subarna K; Shrestha, Laxman; LeClerq, Steven C; Steinhoff, Mark; Katz, Joanne
Date: 2017-03-01
DOI: 10.1093/jpids/piw079
License: cc-by
Abstract: BACKGROUND: Pertussis is estimated to cause 2 percent of childhood deaths globally and is a growing public health problem in developed countries despite high vaccination coverage. Infants are at greatest risk of morbidity and mortality. Maternal vaccination during pregnancy may be effective to prevent pertussis in young infants, but population-based estimates of disease burden in infants are lacking, particularly in low-income countries. The objective of this study was to estimate the incidence of pertussis in infants less than 6 months of age in Sarlahi District, Nepal. METHODS: Nested within a population-based randomized controlled trial of influenza vaccination during pregnancy, infants were visited weekly from birth through 6 months to assess respiratory illness in the prior week. If any respiratory symptoms had occurred, a nasal swab was collected and tested with a multitarget pertussis polymerase chain reaction (PCR) assay. The prospective cohort study includes infants observed between May 2011 and August 2014. RESULTS: The incidence of PCR-confirmed Bordetella pertussis was 13.3 cases per 1000 infant-years (95% confidence interval, 7.7–21.3) in a cohort of 3483 infants with at least 1 day of follow-up. CONCLUSIONS: In a population-based active home surveillance for respiratory illness, a low risk for pertussis was estimated among infants in rural Nepal. Nepal’s immunization program, which includes a childhood whole cell pertussis vaccine, may be effective in controlling pertussis in infants.
Text: A resurgence of pertussis across age groups has occurred in several countries in recent years [1] . Middle-and high-income countries that use an acellular pertussis vaccine for the primary vaccination series have been particularly affected [2, 3] , and infants and adolescents have experienced the greatest increase [4] . Factors that may contribute to the increased risk of pertussis include rapidly waning immunity from those vaccinated with acellular vaccines [1, 5, 6] , asymptomatic transmission from individuals vaccinated with acellular vaccines [7] , genetic adaption of Bordetella pertussis [8] , vaccination delay or refusal [9] , improved surveillance and laboratory capabilities [2] , and overall increased awareness of the continuing circulation of B pertussis [1] . Some countries experiencing epidemic pertussis, including the United States, United Kingdom, and Argentina, now recommend pertussis immunization in pregnancy and vaccination of close contacts [10, 11] to protect the youngest infants from pertussis before they can be vaccinated themselves [12] . Recent data from maternal vaccination trials demonstrate the ability of antibodies to be transferred from mothers to their infants in pregnancy and their persistence in infants [13] .
Global estimates of pertussis show the highest childhood burden in Southeast Asia [14] . In this region, maternal pertussis vaccination during pregnancy may be a way to protect infants, similar to the approach using tetanus toxoid vaccine. However, globally only 1 population-based estimate of pertussis in infants from birth has been conducted (Senegal) [15] , and surveillance and laboratory capabilities in Asia are lacking [16, 17] . The World Health Organization (WHO) recently recommended that countries using whole cell pertussis vaccines continue to do so in light of recent data indicating that acellular pertussis vaccines are less effective than whole cell pertussis vaccines [18] . Population-based data are needed, especially in low-income settings, to provide a more accurate estimate of the burden of pertussis in infants to inform childhood and maternal immunization policies [19, 20] .
We report on a prospective cohort study following infants weekly in their homes to monitor for pertussis disease from birth to age 6 months. The objective was to provide a population-based estimate of laboratory-confirmed pertussis incidence in infants less than 6 months of age in the Sarlahi District, Nepal.
The study was nested within 2 consecutive randomized controlled trials of maternal influenza vaccination during pregnancy set in the Sarlahi District, located in the central Terai (low-lying plains) region of Nepal [21] . At the start of the trial, prevalent pregnancies were identified through a census of all households in the catchment area. For the duration of the trial, field workers visited all households in the communities, every 5 weeks, where married women (15-40 years) resided, for surveillance of incident pregnancies. Once a pregnancy was identified, women provided consent and were enrolled. From April 25, 2011 through September 9, 2013, women between 17 and 34 weeks gestation were randomized and vaccinated with either an influenza vaccine or placebo. The study was a population-based prospective cohort of infants followed from birth through 6 months postpartum. Approval for the study was obtained from the Institutional Review Boards at the Johns Hopkins Bloomberg School of Public Health, Cincinnati Children's Medical Center, the Institute of Medicine at Tribhuvan University, Kathmandu, and the Nepal Health Research Council. The trials are registered at Clinicaltrials.gov (NCT01034254).
At baseline, information was collected on household structure, socioeconomic status, and demographics. At enrollment, date of last menstrual period and pregnancy history data were collected. As soon as possible after delivery, the mother and infant were visited to collect detailed birth information including infant weight and breastfeeding status. From birth through 6 months, postpartum infants were visited weekly by a field worker, who recorded any infant respiratory symptoms in the past 7 days. If an infant had any of the following symptoms, a mid-nasal nylon flocked swab was collected: fever, cough, wheeze, difficulty breathing, or ear infection. Starting on August 17, 2012, new symptoms, more specific for pertussis, were added to the weekly morbidity visit: apnea, cyanosis, cough with vomit, or whoop/whooping cough. The swabs were stored for up to 1 week at room temperature in PrimeStore Molecular Transport Medium (Longhorn Diagnostics LLC, Bethesda, MD). In addition to these signs, mothers were asked which, if any, infant vaccinations were received in the past 7 days, including pertussis vaccination [22] . Mid-nasal swabs were also collected on a weekly basis from mothers from enrollment through 6 months postpartum who reported fever plus one additional morbidity (cough, sore throat, nasal congestion, or myalgia). All nasal swabs collected from infants were tested for B pertussis, Bordetella parapertussis, and Bordetella bronchispetica. Only the nasal swabs of mothers whose infants tested positive for any of these pathogens were tested for the same pathogens.
Real-time polymerase chain reaction (PCR) testing was conducted at the University of Washington's Molecular Virology Laboratory according to previously published methods [23] . Two-target PCR was used to assess the presence of 3 Bordetella species: B pertussis, B parapertussis, and B bronchiseptica. The amplified targets were chromosomal repeated insertion sequence IS481 (IS) and the polymorphic pertussis toxin ptxA promoter region (PT).
After amplification, the melting points of the amplicons were measured in an iCycler (Bio-Rad). A sample was interpreted as positive when the target(s) had a melting temperature within the species-specific acceptable range and a computed tomography ≤42. A sample was negative if none of the targets tested positive or a single positive target was not reproducible. Maternal nasal swabs were tested for those mothers whose infants tested positive for any Bordetella species
Polymerase chain reaction was also performed for several viral infections (influenza, rhinovirus [RV], respiratory syncytial virus [RSV], bocavirus [BoV], human metapneumovirus, coronavirus, adenovirus, and parainfluenza [1] [2] [3] [4] ) as previously described [21] .
Of 3693 women enrolled, 3646 infants were live born to 3621 women (Supplementary Figure 1 ). Infants were included in this analysis if they were followed for any length of the follow-up period (0 to 180 days); median total follow-up was 146 days per infant (Supplementary Figure 2) . The final dataset consists of 3483 infants, contributing 1280 infant-years of observation, with at least 1 follow-up visit during the first 6 months. This includes infants from the entire trial period, both before and after more pertussis-specific additions to the weekly symptom questionnaire.
At baseline, data on household structure were gathered. At enrollment, women reported their literacy status (binary) and pregnancy history. The field workers identified their ethnicity into 2 broad groups (Pahadi, a group originating from the hills; or Madeshi, a group originating from north India) from names and observation. Women were categorized as nulliparous or multiparous. Responses to 25 questions about household construction, water and sanitation, and household assets were used to develop an index to measure the socioeconomic status of households. Binary variables for each of the 25 questions and a mean SES score were calculated for each household.
Gestational age was measured using a woman's report of date of last menstrual period during pregnancy surveillance. Birth weight was collected as soon as possible after birth using a digital scale (Tanita model BD-585, precision to nearest 10 grams). Birth weights collected >72 hours after birth were excluded from the analysis. Small for gestational age (SGA) was calculated using the sex-specific 10th percentile cutoff described by Alexander et al [24] and the INTERGROWTH-21 standards [25] . Women were asked within how many hours of birth breastfeeding was initiated and binary breastfeeding categories were created (≤1 hour versus >1 hour postdelivery).
Incidence was calculated as the number of pertussis cases per 1000 infant-years at risk. Poisson exact 95% confidence intervals (CIs) were constructed. Characteristics of infant pertussis cases were compared with nonpertussis cases using bivariate Poisson regression. Characteristics of all pertussis respiratory episodes were compared with nonpertussis respiratory episodes; t tests were used for continuous predictors and Fisher's exact tests were used for categorical associations due to the low number of pertussis episodes. All statistical analyses were conducted in Stata/SE 14.1.
A total of 3483 infants had 4283 episodes of respiratory illness between May 18, 2011 and April 30, 2014. Thirty-nine percent (n = 1350) of infants experienced no respiratory episodes. The incidence of respiratory illness was 3.6 episodes per infant-year (95% CI, 3.5-3.7). Mean episode duration was 4.7 days (95% CI, 4.6-4.9). A total of 3930 (92%) episodes were matched to 1 or more pertussis-tested nasal swabs from 2026 infants (Supplementary Figure 1) .
Seventeen cases of B pertussis were identified from 19 nasal swabs (nasal swabs were positive on 2 consecutive weeks for 2 infants). The incidence of PCR-confirmed B pertussis was 13.3 cases per 1000-infant years (95% CI, 7.7-21.3). Five cases of B parapertussis were detected with an incidence of 3.9 cases per 1000 infant-years (95% CI, 1.3-9.1). No cases of B bronchiseptica were identified.
The average pertussis episode duration was 8 days (range, 2-33) ( Table 1 ). Mean age of onset of symptoms was 83 days (range, 19-137) (median, 80; interquartile range, 63-109). The most common symptoms were cough, difficulty breathing, and cough with vomit. None of the additional symptoms related to pertussis that were added in year 2 (cyanosis, apnea, cough with vomit, and whoop) resulted in collection of nasal swabs based solely on these additional symptoms. Pertussis episodes were statistically significantly more likely to include difficulty breathing, cough with vomit, and whoop compared with other respiratory illness. Six infants had at least 1 pertussis vaccination before pertussis disease onset (three <2 weeks and three >2 weeks before pertussis illness) with a mean of 18 days from vaccination to illness compared with 49 days for nonpertussis episodes (P = .03). Five infants received their first pertussis vaccination postpertussis disease onset, whereas 6 infants received no pertussis vaccination in the first 180 days. Three fourths of pertussis episodes were coinfected with at least 1 virus, with RV and BoV the most common. Cases of pertussis were more likely to be infected with BoV than respiratory cases due to causes other than pertussis. The majority of cases occurred between February 2013 and January 2014 (Figure 1) .
No statistically significant differences between risk factors for pertussis and nonpertussis cases ( Table 2) were documented. Given the low number of pertussis cases, the lack of a statistical association is not evidence of nonassociation. No deaths occurred in infants who had pertussis. Of the 8 mothers of B pertussis-positive infants who had a nasal swab collected (14 nasal swabs total) during their own follow-up, none were positive for any pertussis species.
The 5 B parapertussis cases were primarily male whose mothers were primiparous, literate, and Pahadi ethnicity (Supplementary Table 1 ). No mothers of infants who had B parapertussis had a nasal swab collected during follow-up.
The average B parapertussis episode duration was 4 days (Supplementary Table 2 ). Mean age of onset of symptoms was 58 days with a range of 7-95 days. The most common symptoms were cough and wheeze. Rhinovirus and RSV were the only coinfections observed. All B parapertussis cases occurred between September 2011 and February 2012 ( Figure 1 ).
A low incidence of pertussis and generally mild clinical presentation were found in infants <6 months in Nepal. To our knowledge, this represents one of the first population-based active surveillance of PCR-confirmed pertussis among young infants in Asia. Acellular pertussis vaccine trials conducted in the 1990s found the average pertussis incidence in the whole cell vaccine groups ranged from 1 to 37 cases per 1000 infantyears [26] . Our finding of 13 B pertussis cases per 1000 infantyears was on the lower end of this range. In the United States in 2014, the estimated pertussis incidence in infants less than 6 months was 2 cases per 1000 infant-years [27] , much lower than observed in our study; however, this passive surveillance system likely vastly underestimates pertussis incidence. Thus, there is a need for active surveillance data such as ours. Furthermore, given our highly sensitive case detection method, many of our pertussis cases would likely not have been detected in the previous acellular pertussis vaccine trials. More stringent respiratory symptom criteria would have lowered our incidence estimate even further. The low incidence was found in a population where pentavalent vaccine (Pentavac: Diphtheria, Tetanus, Pertussis [Whole Cell], Hepatitis-B and Haemophilus Type b Conjugate Vaccine; Serum Institute of India Pvt. Ltd), scheduled for administration at 6, 10, and 14 weeks, is received with significant delays (7% of infants received all 3 recommended pertussis vaccines by 6 months) [22] . These data support the WHO's recommendation that countries using whole cell pertussis vaccine continue to do so given that the majority of outbreaks have been concentrated in countries using the acellular pertussis vaccine [2] . Recent studies suggest that protection from acellular pertussis vaccine is not as strong or long lasting as that conferred by the whole cell pertussis vaccine [6, 28] .
Another contributing factor to the low pertussis incidence observed could be that surveillance was conducted during a period of low pertussis transmission. Pertussis is a cyclical disease, thought to peak every 2 to 4 years, and we may have captured the burden at a low circulation period [6] . We observed over 70% of our B pertussis cases over a 1-year period. This increase from earlier observation periods could indicate a temporary rise in pertussis consistent with its cyclical pattern or a true increase in the baseline burden. Previous research on pertussis seasonality has in different places and time periods demonstrated various periods of peak transmission or no discernable patterns [29, 30] . Although our data do not support a seasonal pattern, the numbers observed are too low to be conclusive.
Pertussis symptom duration and severity were mild compared with the classic pertussis case presentation. Only 3 of the 17 cases fulfilled the WHO criteria, which requires a minimum of 2 weeks of cough, whoop, or posttussive vomiting [31] . Studies on pertussis in infants have generally been clinic-based, hospital-based, or in an outbreak, which therefore required a certain severity of illness for parents to recognize a need for medical attention [29, 30, 32] . These study designs and passive surveillance efforts therefore may have missed milder pertussis cases [33] . Our study, which required only 1 respiratory symptom for a nasal swab to be collected, had increased sensitivity to detect a range of pertussis case presentations. An alternative explanation for the mild cases seen could be an increase in the proportion of mild compared with severe pertussis cases in Nepal.
Although cough, difficulty breathing, and cough with vomit were the most common symptoms, no symptom was present in all B pertussis cases. During an epidemic period in Washington state, among infants <1 year, who had a minimum of 14 days cough plus an additional symptom, 82% had posttussive emesis, 29% had apnea, 26% had whoop, and 42% had cyanosis [32] . A study of US neonates with pertussis showed the symptom prevalence to be 97% for cough, 91% for cyanosis, 58% for apnea, and 3% for fever [34] . Our study found lower or equal symptom prevalence with the exception of fever. Fever prevalence was higher in our study, similar to that found in Peru [29] .
Although not statistically significant, infants with pertussis were more likely to have been born preterm, low birth weight, and SGA, and their mothers were more likely to be primiparous. These findings are similar to previous studies showing no difference in pertussis cases by sex [29, 35, 36] or crowding [35] but showing differences by birth weight [36] . Coinfections were common, consistent with findings from other hospital-based studies [33] . Codetection of B pertussis and B parapertussis with respiratory viruses may be due to asymptomatic pertussis carriage. The incidence of B parapertussis of 4 cases per 1000 person-years was comparable to that of 2 per 1000 person-years found in the Italian acellular pertussis vaccine trial in 1992-1993 [37] . The duration of illness was shorter for B parapertussis with a maximum duration of 6 days compared with a maximum of 33 days for B pertussis. A milder presentation is consistent with clinical knowledge of B parapertussis infection [37, 38] . Bordetella parapertussis cases occurred only during a 5-month period.
There were several study design limitations. We cannot be certain whether the reported symptoms were caused by pertussis, another organism, or whether symptoms were related to 2 or more etiologic agents. We were unable to perform multivariate regression modeling for characteristics associated with pertussis disease and pertussis cases due to the small number of cases we detected.
Infant respiratory symptoms were reported by parents, who may have missed signs that might have been observed by a healthcare worker. However, the criteria for collection of the nasal swab were broad and did not require sophisticated clinical skills. However, apnea and cyanosis may have been difficult for parents to identify. Although the criteria for specimen collection changed in year 2, no infant experienced a pertussis-specific symptom in isolation without also having one of the originally specified respiratory symptoms. These data support our assumption that we were unlikely to have missed pertussis cases in year 1 with our less sensitive respiratory symptom criteria.
Nasal swabs were collected in the mid-nasal region for influenza virus detection, which may have lowered the sensitivity of pertussis detection. In a field site, the acceptability of an additional nasopharyngeal swab would likely have increased the participant refusal rate. This would have decreased the generalizability of our results to the entire population. Although nasopharyngeal swabs or nasopharyngeal aspirates are the recommended specimen collection method [39] , the nasopharyngeal region was established as the collection area of choice when the diagnostic measure was culture, which has low sensitivity. Recent data demonstrated the comparability of using mid-nasal versus nasopharyngeal swabs in PCR pertussis detection [40] .
Strengths of the study included being a population-based, prospective study, with very low refusal rates. Risk factors, clinical symptoms, and coinfections were prospectively identified without the potential bias that may occur when these data are collected retrospectively or in clinical settings. The community-based design allows generalizability of these results to the entire population and not just those seeking care at a health facility or in an outbreak situation. The Sarlahi District is located in the Terai region where the majority of Nepalese reside, and it has similar demographics to the entire population of Nepal [41] . Sarlahi's location near sea level and on the border with India supports the generalizability of these results to many populations living on the Indian subcontinent. The weekly active surveillance with sensitive criteria for pertussis testing was able to detect mild and atypical pertussis cases, which may have been missed by previous traditional surveillance. The multitarget PCR method allowed highly sensitive and specific detection of 2 additional Bordetella species beyond the primary B pertussis target.
We observed a low incidence of pertussis in infants in a whole cell vaccine environment. Pertussis cases were generally milder than expected compared with traditional pertussis clinical definitions. These data support clinicians considering pertussis in their differential diagnosis of infants with mild respiratory symptoms. Policymakers in Nepal will need to weigh the benefit of an additional prenatal pertussis vaccine or a switch to acellular primary pertussis vaccine with the low burden of pertussis in infants less than 6 months. Our study demonstrated that mid-nasal swabs were able to detect pertussis using a sensitive multitarget PCR. The less invasive mid-nasal nasal swab is an attractive alternative for pertussis nasal swab collection, and further research is needed to compare this collection site with nasopharyngeal swabs. In the future, this method may enhance population-based surveillance efforts. | What type of pertussis vaccine has been recently recommended by the WHO? | false | 2,169 | {
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1,719 | Virus-Vectored Influenza Virus Vaccines
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147686/
SHA: f6d2afb2ec44d8656972ea79f8a833143bbeb42b
Authors: Tripp, Ralph A.; Tompkins, S. Mark
Date: 2014-08-07
DOI: 10.3390/v6083055
License: cc-by
Abstract: Despite the availability of an inactivated vaccine that has been licensed for >50 years, the influenza virus continues to cause morbidity and mortality worldwide. Constant evolution of circulating influenza virus strains and the emergence of new strains diminishes the effectiveness of annual vaccines that rely on a match with circulating influenza strains. Thus, there is a continued need for new, efficacious vaccines conferring cross-clade protection to avoid the need for biannual reformulation of seasonal influenza vaccines. Recombinant virus-vectored vaccines are an appealing alternative to classical inactivated vaccines because virus vectors enable native expression of influenza antigens, even from virulent influenza viruses, while expressed in the context of the vector that can improve immunogenicity. In addition, a vectored vaccine often enables delivery of the vaccine to sites of inductive immunity such as the respiratory tract enabling protection from influenza virus infection. Moreover, the ability to readily manipulate virus vectors to produce novel influenza vaccines may provide the quickest path toward a universal vaccine protecting against all influenza viruses. This review will discuss experimental virus-vectored vaccines for use in humans, comparing them to licensed vaccines and the hurdles faced for licensure of these next-generation influenza virus vaccines.
Text: Seasonal influenza is a worldwide health problem causing high mobility and substantial mortality [1] [2] [3] [4] . Moreover, influenza infection often worsens preexisting medical conditions [5] [6] [7] . Vaccines against circulating influenza strains are available and updated annually, but many issues are still present, including low efficacy in the populations at greatest risk of complications from influenza virus infection, i.e., the young and elderly [8, 9] . Despite increasing vaccination rates, influenza-related hospitalizations are increasing [8, 10] , and substantial drug resistance has developed to two of the four currently approved anti-viral drugs [11, 12] . While adjuvants have the potential to improve efficacy and availability of current inactivated vaccines, live-attenuated and virus-vectored vaccines are still considered one of the best options for the induction of broad and efficacious immunity to the influenza virus [13] .
The general types of influenza vaccines available in the United States are trivalent inactivated influenza vaccine (TIV), quadrivalent influenza vaccine (QIV), and live attenuated influenza vaccine (LAIV; in trivalent and quadrivalent forms). There are three types of inactivated vaccines that include whole virus inactivated, split virus inactivated, and subunit vaccines. In split virus vaccines, the virus is disrupted by a detergent. In subunit vaccines, HA and NA have been further purified by removal of other viral components. TIV is administered intramuscularly and contains three or four inactivated viruses, i.e., two type A strains (H1 and H3) and one or two type B strains. TIV efficacy is measured by induction of humoral responses to the hemagglutinin (HA) protein, the major surface and attachment glycoprotein on influenza. Serum antibody responses to HA are measured by the hemagglutination-inhibition (HI) assay, and the strain-specific HI titer is considered the gold-standard correlate of immunity to influenza where a four-fold increase in titer post-vaccination, or a HI titer of ≥1:40 is considered protective [4, 14] . Protection against clinical disease is mainly conferred by serum antibodies; however, mucosal IgA antibodies also may contribute to resistance against infection. Split virus inactivated vaccines can induce neuraminidase (NA)-specific antibody responses [15] [16] [17] , and anti-NA antibodies have been associated with protection from infection in humans [18] [19] [20] [21] [22] . Currently, NA-specific antibody responses are not considered a correlate of protection [14] . LAIV is administered as a nasal spray and contains the same three or four influenza virus strains as inactivated vaccines but on an attenuated vaccine backbone [4] . LAIV are temperature-sensitive and cold-adapted so they do not replicate effectively at core body temperature, but replicate in the mucosa of the nasopharynx [23] . LAIV immunization induces serum antibody responses, mucosal antibody responses (IgA), and T cell responses. While robust serum antibody and nasal wash (mucosal) antibody responses are associated with protection from infection, other immune responses, such as CD8 + cytotoxic lymphocyte (CTL) responses may contribute to protection and there is not a clear correlate of immunity for LAIV [4, 14, 24] .
Currently licensed influenza virus vaccines suffer from a number of issues. The inactivated vaccines rely on specific antibody responses to the HA, and to a lesser extent NA proteins for protection. The immunodominant portions of the HA and NA molecules undergo a constant process of antigenic drift, a natural accumulation of mutations, enabling virus evasion from immunity [9, 25] . Thus, the circulating influenza A and B strains are reviewed annually for antigenic match with current vaccines, Replacement of vaccine strains may occur regularly, and annual vaccination is recommended to assure protection [4, 26, 27] . For the northern hemisphere, vaccine strain selection occurs in February and then manufacturers begin production, taking at least six months to produce the millions of vaccine doses required for the fall [27] . If the prediction is imperfect, or if manufacturers have issues with vaccine production, vaccine efficacy or availability can be compromised [28] . LAIV is not recommended for all populations; however, it is generally considered to be as effective as inactivated vaccines and may be more efficacious in children [4, 9, 24] . While LAIV relies on antigenic match and the HA and NA antigens are replaced on the same schedule as the TIV [4, 9] , there is some suggestion that LAIV may induce broader protection than TIV due to the diversity of the immune response consistent with inducing virus-neutralizing serum and mucosal antibodies, as well as broadly reactive T cell responses [9, 23, 29] . While overall both TIV and LAIV are considered safe and effective, there is a recognized need for improved seasonal influenza vaccines [26] . Moreover, improved understanding of immunity to conserved influenza virus antigens has raised the possibility of a universal vaccine, and these universal antigens will likely require novel vaccines for effective delivery [30] [31] [32] .
Virus-vectored vaccines share many of the advantages of LAIV, as well as those unique to the vectors. Recombinant DNA systems exist that allow ready manipulation and modification of the vector genome. This in turn enables modification of the vectors to attenuate the virus or enhance immunogenicity, in addition to adding and manipulating the influenza virus antigens. Many of these vectors have been extensively studied or used as vaccines against wild type forms of the virus. Finally, each of these vaccine vectors is either replication-defective or causes a self-limiting infection, although like LAIV, safety in immunocompromised individuals still remains a concern [4, 13, [33] [34] [35] . Table 1 summarizes the benefits and concerns of each of the virus-vectored vaccines discussed here.
There are 53 serotypes of adenovirus, many of which have been explored as vaccine vectors. A live adenovirus vaccine containing serotypes 4 and 7 has been in use by the military for decades, suggesting adenoviruses may be safe for widespread vaccine use [36] . However, safety concerns have led to the majority of adenovirus-based vaccine development to focus on replication-defective vectors. Adenovirus 5 (Ad5) is the most-studied serotype, having been tested for gene delivery and anti-cancer agents, as well as for infectious disease vaccines.
Adenovirus vectors are attractive as vaccine vectors because their genome is very stable and there are a variety of recombinant systems available which can accommodate up to 10 kb of recombinant genetic material [37] . Adenovirus is a non-enveloped virus which is relatively stable and can be formulated for long-term storage at 4 °C, or even storage up to six months at room temperature [33] . Adenovirus vaccines can be grown to high titers, exceeding 10 1° plaque forming units (PFU) per mL when cultured on 293 or PER.C6 cells [38] , and the virus can be purified by simple methods [39] . Adenovirus vaccines can also be delivered via multiple routes, including intramuscular injection, subcutaneous injection, intradermal injection, oral delivery using a protective capsule, and by intranasal delivery. Importantly, the latter two delivery methods induce robust mucosal immune responses and may bypass preexisting vector immunity [33] . Even replication-defective adenovirus vectors are naturally immunostimulatory and effective adjuvants to the recombinant antigen being delivered. Adenovirus has been extensively studied as a vaccine vector for human disease. The first report using adenovirus as a vaccine vector for influenza demonstrated immunogenicity of recombinant adenovirus 5 (rAd5) expressing the HA of a swine influenza virus, A/Swine/Iowa/1999 (H3N2). Intramuscular immunization of mice with this construct induced robust neutralizing antibody responses and protected mice from challenge with a heterologous virus, A/Hong Kong/1/1968 (H3N2) [40] . Replication defective rAd5 vaccines expressing influenza HA have also been tested in humans. A rAd5-HA expressing the HA from A/Puerto Rico/8/1934 (H1N1; PR8) was delivered to humans epicutaneously or intranasally and assayed for safety and immunogenicity. The vaccine was well tolerated and induced seroconversion with the intranasal administration had a higher conversion rate and higher geometric meant HI titers [41] . While clinical trials with rAd vectors have overall been successful, demonstrating safety and some level of efficacy, rAd5 as a vector has been negatively overshadowed by two clinical trial failures. The first trial was a gene therapy examination where high-dose intravenous delivery of an Ad vector resulted in the death of an 18-year-old male [42, 43] . The second clinical failure was using an Ad5-vectored HIV vaccine being tested as a part of a Step Study, a phase 2B clinical trial. In this study, individuals were vaccinated with the Ad5 vaccine vector expressing HIV-1 gag, pol, and nef genes. The vaccine induced HIV-specific T cell responses; however, the study was stopped after interim analysis suggested the vaccine did not achieve efficacy and individuals with high preexisting Ad5 antibody titers might have an increased risk of acquiring HIV-1 [44] [45] [46] . Subsequently, the rAd5 vaccine-associated risk was confirmed [47] . While these two instances do not suggest Ad-vector vaccines are unsafe or inefficacious, the umbra cast by the clinical trials notes has affected interest for all adenovirus vaccines, but interest still remains.
Immunization with adenovirus vectors induces potent cellular and humoral immune responses that are initiated through toll-like receptor-dependent and independent pathways which induce robust pro-inflammatory cytokine responses. Recombinant Ad vaccines expressing HA antigens from pandemic H1N1 (pH1N1), H5 and H7 highly pathogenic avian influenza (HPAI) virus (HPAIV), and H9 avian influenza viruses have been tested for efficacy in a number of animal models, including chickens, mice, and ferrets, and been shown to be efficacious and provide protection from challenge [48, 49] . Several rAd5 vectors have been explored for delivery of non-HA antigens, influenza nucleoprotein (NP) and matrix 2 (M2) protein [29, [50] [51] [52] . The efficacy of non-HA antigens has led to their inclusion with HA-based vaccines to improve immunogenicity and broaden breadth of both humoral and cellular immunity [53, 54] . However, as both CD8 + T cell and neutralizing antibody responses are generated by the vector and vaccine antigens, immunological memory to these components can reduce efficacy and limit repeated use [48] .
One drawback of an Ad5 vector is the potential for preexisting immunity, so alternative adenovirus serotypes have been explored as vectors, particularly non-human and uncommon human serotypes. Non-human adenovirus vectors include those from non-human primates (NHP), dogs, sheep, pigs, cows, birds and others [48, 55] . These vectors can infect a variety of cell types, but are generally attenuated in humans avoiding concerns of preexisting immunity. Swine, NHP and bovine adenoviruses expressing H5 HA antigens have been shown to induce immunity comparable to human rAd5-H5 vaccines [33, 56] . Recombinant, replication-defective adenoviruses from low-prevalence serotypes have also been shown to be efficacious. Low prevalence serotypes such as adenovirus types 3, 7, 11, and 35 can evade anti-Ad5 immune responses while maintaining effective antigen delivery and immunogenicity [48, 57] . Prime-boost strategies, using DNA or protein immunization in conjunction with an adenovirus vaccine booster immunization have also been explored as a means to avoided preexisting immunity [52] .
Adeno-associated viruses (AAV) were first explored as gene therapy vectors. Like rAd vectors, rAAV have broad tropism infecting a variety of hosts, tissues, and proliferating and non-proliferating cell types [58] . AAVs had been generally not considered as vaccine vectors because they were widely considered to be poorly immunogenic. A seminal study using AAV-2 to express a HSV-2 glycoprotein showed this virus vaccine vector effectively induced potent CD8 + T cell and serum antibody responses, thereby opening the door to other rAAV vaccine-associated studies [59, 60] .
AAV vector systems have a number of engaging properties. The wild type viruses are non-pathogenic and replication incompetent in humans and the recombinant AAV vector systems are even further attenuated [61] . As members of the parvovirus family, AAVs are small non-enveloped viruses that are stable and amenable to long-term storage without a cold chain. While there is limited preexisting immunity, availability of non-human strains as vaccine candidates eliminates these concerns. Modifications to the vector have increased immunogenicity, as well [60] .
There are limited studies using AAVs as vaccine vectors for influenza. An AAV expressing an HA antigen was first shown to induce protective in 2001 [62] . Later, a hybrid AAV derived from two non-human primate isolates (AAVrh32.33) was used to express influenza NP and protect against PR8 challenge in mice [63] . Most recently, following the 2009 H1N1 influenza virus pandemic, rAAV vectors were generated expressing the HA, NP and matrix 1 (M1) proteins of A/Mexico/4603/2009 (pH1N1), and in murine immunization and challenge studies, the rAAV-HA and rAAV-NP were shown to be protective; however, mice vaccinated with rAAV-HA + NP + M1 had the most robust protection. Also, mice vaccinated with rAAV-HA + rAAV-NP + rAAV-M1 were also partially protected against heterologous (PR8, H1N1) challenge [63] . Most recently, an AAV vector was used to deliver passive immunity to influenza [64, 65] . In these studies, AAV (AAV8 and AAV9) was used to deliver an antibody transgene encoding a broadly cross-protective anti-influenza monoclonal antibody for in vivo expression. Both intramuscular and intranasal delivery of the AAVs was shown to protect against a number of influenza virus challenges in mice and ferrets, including H1N1 and H5N1 viruses [64, 65] . These studies suggest that rAAV vectors are promising vaccine and immunoprophylaxis vectors. To this point, while approximately 80 phase I, I/II, II, or III rAAV clinical trials are open, completed, or being reviewed, these have focused upon gene transfer studies and so there is as yet limited safety data for use of rAAV as vaccines [66] .
Alphaviruses are positive-sense, single-stranded RNA viruses of the Togaviridae family. A variety of alphaviruses have been developed as vaccine vectors, including Semliki Forest virus (SFV), Sindbis (SIN) virus, Venezuelan equine encephalitis (VEE) virus, as well as chimeric viruses incorporating portions of SIN and VEE viruses. The replication defective vaccines or replicons do not encode viral structural proteins, having these portions of the genome replaces with transgenic material.
The structural proteins are provided in cell culture production systems. One important feature of the replicon systems is the self-replicating nature of the RNA. Despite the partial viral genome, the RNAs are self-replicating and can express transgenes at very high levels [67] .
SIN, SFV, and VEE have all been tested for efficacy as vaccine vectors for influenza virus [68] [69] [70] [71] . A VEE-based replicon system encoding the HA from PR8 was demonstrated to induce potent HA-specific immune response and protected from challenge in a murine model, despite repeated immunization with the vector expressing a control antigen, suggesting preexisting immunity may not be an issue for the replicon vaccine [68] . A separate study developed a VEE replicon system expressing the HA from A/Hong Kong/156/1997 (H5N1) and demonstrated varying efficacy after in ovo vaccination or vaccination of 1-day-old chicks [70] . A recombinant SIN virus was use as a vaccine vector to deliver a CD8 + T cell epitope only. The well-characterized NP epitope was transgenically expressed in the SIN system and shown to be immunogenic in mice, priming a robust CD8 + T cell response and reducing influenza virus titer after challenge [69] . More recently, a VEE replicon system expressing the HA protein of PR8 was shown to protect young adult (8-week-old) and aged (12-month-old) mice from lethal homologous challenge [72] .
The VEE replicon systems are particularly appealing as the VEE targets antigen-presenting cells in the lymphatic tissues, priming rapid and robust immune responses [73] . VEE replicon systems can induce robust mucosal immune responses through intranasal or subcutaneous immunization [72] [73] [74] , and subcutaneous immunization with virus-like replicon particles (VRP) expressing HA-induced antigen-specific systemic IgG and fecal IgA antibodies [74] . VRPs derived from VEE virus have been developed as candidate vaccines for cytomegalovirus (CMV). A phase I clinical trial with the CMV VRP showed the vaccine was immunogenic, inducing CMV-neutralizing antibody responses and potent T cell responses. Moreover, the vaccine was well tolerated and considered safe [75] . A separate clinical trial assessed efficacy of repeated immunization with a VRP expressing a tumor antigen. The vaccine was safe and despite high vector-specific immunity after initial immunization, continued to boost transgene-specific immune responses upon boost [76] . While additional clinical data is needed, these reports suggest alphavirus replicon systems or VRPs may be safe and efficacious, even in the face of preexisting immunity.
Baculovirus has been extensively used to produce recombinant proteins. Recently, a baculovirus-derived recombinant HA vaccine was approved for human use and was first available for use in the United States for the 2013-2014 influenza season [4] . Baculoviruses have also been explored as vaccine vectors. Baculoviruses have a number of advantages as vaccine vectors. The viruses have been extensively studied for protein expression and for pesticide use and so are readily manipulated. The vectors can accommodate large gene insertions, show limited cytopathic effect in mammalian cells, and have been shown to infect and express genes of interest in a spectrum of mammalian cells [77] . While the insect promoters are not effective for mammalian gene expression, appropriate promoters can be cloned into the baculovirus vaccine vectors.
Baculovirus vectors have been tested as influenza vaccines, with the first reported vaccine using Autographa californica nuclear polyhedrosis virus (AcNPV) expressing the HA of PR8 under control of the CAG promoter (AcCAG-HA) [77] . Intramuscular, intranasal, intradermal, and intraperitoneal immunization or mice with AcCAG-HA elicited HA-specific antibody responses, however only intranasal immunization provided protection from lethal challenge. Interestingly, intranasal immunization with the wild type AcNPV also resulted in protection from PR8 challenge. The robust innate immune response to the baculovirus provided non-specific protection from subsequent influenza virus infection [78] . While these studies did not demonstrate specific protection, there were antigen-specific immune responses and potential adjuvant effects by the innate response.
Baculovirus pseudotype viruses have also been explored. The G protein of vesicular stomatitis virus controlled by the insect polyhedron promoter and the HA of A/Chicken/Hubei/327/2004 (H5N1) HPAIV controlled by a CMV promoter were used to generate the BV-G-HA. Intramuscular immunization of mice or chickens with BV-G-HA elicited strong HI and VN serum antibody responses, IFN-γ responses, and protected from H5N1 challenge [79] . A separate study demonstrated efficacy using a bivalent pseudotyped baculovirus vector [80] .
Baculovirus has also been used to generate an inactivated particle vaccine. The HA of A/Indonesia/CDC669/2006(H5N1) was incorporated into a commercial baculovirus vector controlled by the e1 promoter from White Spot Syndrome Virus. The resulting recombinant virus was propagated in insect (Sf9) cells and inactivated as a particle vaccine [81, 82] . Intranasal delivery with cholera toxin B as an adjuvant elicited robust HI titers and protected from lethal challenge [81] . Oral delivery of this encapsulated vaccine induced robust serum HI titers and mucosal IgA titers in mice, and protected from H5N1 HPAIV challenge. More recently, co-formulations of inactivated baculovirus vectors have also been shown to be effective in mice [83] .
While there is growing data on the potential use of baculovirus or pseudotyped baculovirus as a vaccine vector, efficacy data in mammalian animal models other than mice is lacking. There is also no data on the safety in humans, reducing enthusiasm for baculovirus as a vaccine vector for influenza at this time.
Newcastle disease virus (NDV) is a single-stranded, negative-sense RNA virus that causes disease in poultry. NDV has a number of appealing qualities as a vaccine vector. As an avian virus, there is little or no preexisting immunity to NDV in humans and NDV propagates to high titers in both chicken eggs and cell culture. As a paramyxovirus, there is no DNA phase in the virus lifecycle reducing concerns of integration events, and the levels of gene expression are driven by the proximity to the leader sequence at the 3' end of the viral genome. This gradient of gene expression enables attenuation through rearrangement of the genome, or by insertion of transgenes within the genome. Finally, pathogenicity of NDV is largely determined by features of the fusion protein enabling ready attenuation of the vaccine vector [84] .
Reverse genetics, a method that allows NDV to be rescued from plasmids expressing the viral RNA polymerase and nucleocapsid proteins, was first reported in 1999 [85, 86] . This process has enabled manipulation of the NDV genome as well as incorporation of transgenes and the development of NDV vectors. Influenza was the first infectious disease targeted with a recombinant NDV (rNDV) vector. The HA protein of A/WSN/1933 (H1N1) was inserted into the Hitchner B1 vaccine strain. The HA protein was expressed on infected cells and was incorporated into infectious virions. While the virus was attenuated compared to the parental vaccine strain, it induced a robust serum antibody response and protected against homologous influenza virus challenge in a murine model of infection [87] . Subsequently, rNDV was tested as a vaccine vector for HPAIV having varying efficacy against H5 and H7 influenza virus infections in poultry [88] [89] [90] [91] [92] [93] [94] . These vaccines have the added benefit of potentially providing protection against both the influenza virus and NDV infection.
NDV has also been explored as a vaccine vector for humans. Two NHP studies assessed the immunogenicity and efficacy of an rNDV expressing the HA or NA of A/Vietnam/1203/2004 (H5N1; VN1203) [95, 96] . Intranasal and intratracheal delivery of the rNDV-HA or rNDV-NA vaccines induced both serum and mucosal antibody responses and protected from HPAIV challenge [95, 96] . NDV has limited clinical data; however, phase I and phase I/II clinical trials have shown that the NDV vector is well-tolerated, even at high doses delivered intravenously [44, 97] . While these results are promising, additional studies are needed to advance NDV as a human vaccine vector for influenza.
Parainfluenza virus type 5 (PIV5) is a paramyxovirus vaccine vector being explored for delivery of influenza and other infectious disease vaccine antigens. PIV5 has only recently been described as a vaccine vector [98] . Similar to other RNA viruses, PIV5 has a number of features that make it an attractive vaccine vector. For example, PIV5 has a stable RNA genome and no DNA phase in virus replication cycle reducing concerns of host genome integration or modification. PIV5 can be grown to very high titers in mammalian vaccine cell culture substrates and is not cytopathic allowing for extended culture and harvest of vaccine virus [98, 99] . Like NDV, PIV5 has a 3'-to 5' gradient of gene expression and insertion of transgenes at different locations in the genome can variably attenuate the virus and alter transgene expression [100] . PIV5 has broad tropism, infecting many cell types, tissues, and species without causing clinical disease, although PIV5 has been associated with -kennel cough‖ in dogs [99] . A reverse genetics system for PIV5 was first used to insert the HA gene from A/Udorn/307/72 (H3N2) into the PIV5 genome between the hemagglutinin-neuraminidase (HN) gene and the large (L) polymerase gene. Similar to NDV, the HA was expressed at high levels in infected cells and replicated similarly to the wild type virus, and importantly, was not pathogenic in immunodeficient mice [98] . Additionally, a single intranasal immunization in a murine model of influenza infection was shown to induce neutralizing antibody responses and protect against a virus expressing homologous HA protein [98] . PIV5 has also been explored as a vaccine against HPAIV. Recombinant PIV5 vaccines expressing the HA or NP from VN1203 were tested for efficacy in a murine challenge model. Mice intranasally vaccinated with a single dose of PIV5-H5 vaccine had robust serum and mucosal antibody responses, and were protected from lethal challenge. Notably, although cellular immune responses appeared to contribute to protection, serum antibody was sufficient for protection from challenge [100, 101] . Intramuscular immunization with PIV5-H5 was also shown to be effective at inducing neutralizing antibody responses and protecting against lethal influenza virus challenge [101] . PIV5 expressing the NP protein of HPAIV was also efficacious in the murine immunization and challenge model, where a single intranasal immunization induced robust CD8 + T cell responses and protected against homologous (H5N1) and heterosubtypic (H1N1) virus challenge [102] .
Currently there is no clinical safety data for use of PIV5 in humans. However, live PIV5 has been a component of veterinary vaccines for -kennel cough‖ for >30 years, and veterinarians and dog owners are exposed to live PIV5 without reported disease [99] . This combined with preclinical data from a variety of animal models suggests that PIV5 as a vector is likely to be safe in humans. As preexisting immunity is a concern for all virus-vectored vaccines, it should be noted that there is no data on the levels of preexisting immunity to PIV5 in humans. However, a study evaluating the efficacy of a PIV5-H3 vaccine in canines previously vaccinated against PIV5 (kennel cough) showed induction of robust anti-H3 serum antibody responses as well as high serum antibody levels to the PIV5 vaccine, suggesting preexisting immunity to the PIV5 vector may not affect immunogenicity of vaccines even with repeated use [99] .
Poxvirus vaccines have a long history and the notable hallmark of being responsible for eradication of smallpox. The termination of the smallpox virus vaccination program has resulted in a large population of poxvirus-naï ve individuals that provides the opportunity for the use of poxviruses as vectors without preexisting immunity concerns [103] . Poxvirus-vectored vaccines were first proposed for use in 1982 with two reports of recombinant vaccinia viruses encoding and expressing functional thymidine kinase gene from herpes virus [104, 105] . Within a year, a vaccinia virus encoding the HA of an H2N2 virus was shown to express a functional HA protein (cleaved in the HA1 and HA2 subunits) and be immunogenic in rabbits and hamsters [106] . Subsequently, all ten of the primary influenza proteins have been expressed in vaccine virus [107] .
Early work with intact vaccinia virus vectors raised safety concerns, as there was substantial reactogenicity that hindered recombinant vaccine development [108] . Two vaccinia vectors were developed to address these safety concerns. The modified vaccinia virus Ankara (MVA) strain was attenuated by passage 530 times in chick embryo fibroblasts cultures. The second, New York vaccinia virus (NYVAC) was a plaque-purified clone of the Copenhagen vaccine strain rationally attenuated by deletion of 18 open reading frames [109] [110] [111] .
Modified vaccinia virus Ankara (MVA) was developed prior to smallpox eradication to reduce or prevent adverse effects of other smallpox vaccines [109] . Serial tissue culture passage of MVA resulted in loss of 15% of the genome, and established a growth restriction for avian cells. The defects affected late stages in virus assembly in non-avian cells, a feature enabling use of the vector as single-round expression vector in non-permissive hosts. Interestingly, over two decades ago, recombinant MVA expressing the HA and NP of influenza virus was shown to be effective against lethal influenza virus challenge in a murine model [112] . Subsequently, MVA expressing various antigens from seasonal, pandemic (A/California/04/2009, pH1N1), equine (A/Equine/Kentucky/1/81 H3N8), and HPAI (VN1203) viruses have been shown to be efficacious in murine, ferret, NHP, and equine challenge models [113] . MVA vaccines are very effective stimulators of both cellular and humoral immunity. For example, abortive infection provides native expression of the influenza antigens enabling robust antibody responses to native surface viral antigens. Concurrently, the intracellular influenza peptides expressed by the pox vector enter the class I MHC antigen processing and presentation pathway enabling induction of CD8 + T cell antiviral responses. MVA also induces CD4 + T cell responses further contributing to the magnitude of the antigen-specific effector functions [107, [112] [113] [114] [115] . MVA is also a potent activator of early innate immune responses further enhancing adaptive immune responses [116] . Between early smallpox vaccine development and more recent vaccine vector development, MVA has undergone extensive safety testing and shown to be attenuated in severely immunocompromised animals and safe for use in children, adults, elderly, and immunocompromised persons. With extensive pre-clinical data, recombinant MVA vaccines expressing influenza antigens have been tested in clinical trials and been shown to be safe and immunogenic in humans [117] [118] [119] . These results combined with data from other (non-influenza) clinical and pre-clinical studies support MVA as a leading viral-vectored candidate vaccine.
The NYVAC vector is a highly attenuated vaccinia virus strain. NYVAC is replication-restricted; however, it grows in chick embryo fibroblasts and Vero cells enabling vaccine-scale production. In non-permissive cells, critical late structural proteins are not produced stopping replication at the immature virion stage [120] . NYVAC is very attenuated and considered safe for use in humans of all ages; however, it predominantly induces a CD4 + T cell response which is different compared to MVA [114] . Both MVA and NYVAC provoke robust humoral responses, and can be delivered mucosally to induce mucosal antibody responses [121] . There has been only limited exploration of NYVAC as a vaccine vector for influenza virus; however, a vaccine expressing the HA from A/chicken/Indonesia/7/2003 (H5N1) was shown to induce potent neutralizing antibody responses and protect against challenge in swine [122] .
While there is strong safety and efficacy data for use of NYVAC or MVA-vectored influenza vaccines, preexisting immunity remains a concern. Although the smallpox vaccination campaign has resulted in a population of poxvirus-naï ve people, the initiation of an MVA or NYVAC vaccination program for HIV, influenza or other pathogens will rapidly reduce this susceptible population. While there is significant interest in development of pox-vectored influenza virus vaccines, current influenza vaccination strategies rely upon regular immunization with vaccines matched to circulating strains. This would likely limit the use and/or efficacy of poxvirus-vectored influenza virus vaccines for regular and seasonal use [13] . Intriguingly, NYVAC may have an advantage for use as an influenza vaccine vector, because immunization with this vector induces weaker vaccine-specific immune responses compared to other poxvirus vaccines, a feature that may address the concerns surrounding preexisting immunity [123] .
While poxvirus-vectored vaccines have not yet been approved for use in humans, there is a growing list of licensed poxvirus for veterinary use that include fowlpox-and canarypox-vectored vaccines for avian and equine influenza viruses, respectively [124, 125] . The fowlpox-vectored vaccine expressing the avian influenza virus HA antigen has the added benefit of providing protection against fowlpox infection. Currently, at least ten poxvirus-vectored vaccines have been licensed for veterinary use [126] . These poxvirus vectors have the potential for use as vaccine vectors in humans, similar to the first use of cowpox for vaccination against smallpox [127] . The availability of these non-human poxvirus vectors with extensive animal safety and efficacy data may address the issues with preexisting immunity to the human vaccine strains, although the cross-reactivity originally described with cowpox could also limit use.
Influenza vaccines utilizing vesicular stomatitis virus (VSV), a rhabdovirus, as a vaccine vector have a number of advantages shared with other RNA virus vaccine vectors. Both live and replication-defective VSV vaccine vectors have been shown to be immunogenic [128, 129] , and like Paramyxoviridae, the Rhabdoviridae genome has a 3'-to-5' gradient of gene expression enabling attention by selective vaccine gene insertion or genome rearrangement [130] . VSV has a number of other advantages including broad tissue tropism, and the potential for intramuscular or intranasal immunization. The latter delivery method enables induction of mucosal immunity and elimination of needles required for vaccination. Also, there is little evidence of VSV seropositivity in humans eliminating concerns of preexisting immunity, although repeated use may be a concern. Also, VSV vaccine can be produced using existing mammalian vaccine manufacturing cell lines.
Influenza antigens were first expressed in a VSV vector in 1997. Both the HA and NA were shown to be expressed as functional proteins and incorporated into the recombinant VSV particles [131] . Subsequently, VSV-HA, expressing the HA protein from A/WSN/1933 (H1N1) was shown to be immunogenic and protect mice from lethal influenza virus challenge [129] . To reduce safety concerns, attenuated VSV vectors were developed. One candidate vaccine had a truncated VSV G protein, while a second candidate was deficient in G protein expression and relied on G protein expressed by a helper vaccine cell line to the provide the virus receptor. Both vectors were found to be attenuated in mice, but maintained immunogenicity [128] . More recently, single-cycle replicating VSV vaccines have been tested for efficacy against H5N1 HPAIV. VSV vectors expressing the HA from A/Hong Kong/156/97 (H5N1) were shown to be immunogenic and induce cross-reactive antibody responses and protect against challenge with heterologous H5N1 challenge in murine and NHP models [132] [133] [134] .
VSV vectors are not without potential concerns. VSV can cause disease in a number of species, including humans [135] . The virus is also potentially neuroinvasive in some species [136] , although NHP studies suggest this is not a concern in humans [137] . Also, while the incorporation of the influenza antigen in to the virion may provide some benefit in immunogenicity, changes in tropism or attenuation could arise from incorporation of different influenza glycoproteins. There is no evidence for this, however [134] . Currently, there is no human safety data for VSV-vectored vaccines. While experimental data is promising, additional work is needed before consideration for human influenza vaccination.
Current influenza vaccines rely on matching the HA antigen of the vaccine with circulating strains to provide strain-specific neutralizing antibody responses [4, 14, 24] . There is significant interest in developing universal influenza vaccines that would not require annual reformulation to provide protective robust and durable immunity. These vaccines rely on generating focused immune responses to highly conserved portions of the virus that are refractory to mutation [30] [31] [32] . Traditional vaccines may not be suitable for these vaccination strategies; however, vectored vaccines that have the ability to be readily modified and to express transgenes are compatible for these applications.
The NP and M2 proteins have been explored as universal vaccine antigens for decades. Early work with recombinant viral vectors demonstrated that immunization with vaccines expressing influenza antigens induced potent CD8 + T cell responses [107, [138] [139] [140] [141] . These responses, even to the HA antigen, could be cross-protective [138] . A number of studies have shown that immunization with NP expressed by AAV, rAd5, alphavirus vectors, MVA, or other vector systems induces potent CD8 + T cell responses and protects against influenza virus challenge [52, 63, 69, 102, 139, 142] . As the NP protein is highly conserved across influenza A viruses, NP-specific T cells can protect against heterologous and even heterosubtypic virus challenges [30] .
The M2 protein is also highly conserved and expressed on the surface of infected cells, although to a lesser extent on the surface of virus particles [30] . Much of the vaccine work in this area has focused on virus-like or subunit particles expressing the M2 ectodomain; however, studies utilizing a DNA-prime, rAd-boost strategies to vaccinate against the entire M2 protein have shown the antigen to be immunogenic and protective [50] . In these studies, antibodies to the M2 protein protected against homologous and heterosubtypic challenge, including a H5N1 HPAIV challenge. More recently, NP and M2 have been combined to induce broadly cross-reactive CD8 + T cell and antibody responses, and rAd5 vaccines expressing these antigens have been shown to protect against pH1N1 and H5N1 challenges [29, 51] .
Historically, the HA has not been widely considered as a universal vaccine antigen. However, the recent identification of virus neutralizing monoclonal antibodies that cross-react with many subtypes of influenza virus [143] has presented the opportunity to design vaccine antigens to prime focused antibody responses to the highly conserved regions recognized by these monoclonal antibodies. The majority of these broadly cross-reactive antibodies recognize regions on the stalk of the HA protein [143] . The HA stalk is generally less immunogenic compared to the globular head of the HA protein so most approaches have utilized -headless‖ HA proteins as immunogens. HA stalk vaccines have been designed using DNA and virus-like particles [144] and MVA [142] ; however, these approaches are amenable to expression in any of the viruses vectors described here.
The goal of any vaccine is to protect against infection and disease, while inducing population-based immunity to reduce or eliminate virus transmission within the population. It is clear that currently licensed influenza vaccines have not fully met these goals, nor those specific to inducing long-term, robust immunity. There are a number of vaccine-related issues that must be addressed before population-based influenza vaccination strategies are optimized. The concept of a -one size fits all‖ vaccine needs to be updated, given the recent ability to probe the virus-host interface through RNA interference approaches that facilitate the identification of host genes affecting virus replication, immunity, and disease. There is also a need for revision of the current influenza virus vaccine strategies for at-risk populations, particularly those at either end of the age spectrum. An example of an improved vaccine regime might include the use of a vectored influenza virus vaccine that expresses the HA, NA and M and/or NP proteins for the two currently circulating influenza A subtypes and both influenza B strains so that vaccine take and vaccine antigen levels are not an issue in inducing protective immunity. Recombinant live-attenuated or replication-deficient influenza viruses may offer an advantage for this and other approaches.
Vectored vaccines can be constructed to express full-length influenza virus proteins, as well as generate conformationally restricted epitopes, features critical in generating appropriate humoral protection. Inclusion of internal influenza antigens in a vectored vaccine can also induce high levels of protective cellular immunity. To generate sustained immunity, it is an advantage to induce immunity at sites of inductive immunity to natural infection, in this case the respiratory tract. Several vectored vaccines target the respiratory tract. Typically, vectored vaccines generate antigen for weeks after immunization, in contrast to subunit vaccination. This increased presence and level of vaccine antigen contributes to and helps sustain a durable memory immune response, even augmenting the selection of higher affinity antibody secreting cells. The enhanced memory response is in part linked to the intrinsic augmentation of immunity induced by the vector. Thus, for weaker antigens typical of HA, vectored vaccines have the capacity to overcome real limitations in achieving robust and durable protection.
Meeting the mandates of seasonal influenza vaccine development is difficult, and to respond to a pandemic strain is even more challenging. Issues with influenza vaccine strain selection based on recently circulating viruses often reflect recommendations by the World Health Organization (WHO)-a process that is cumbersome. The strains of influenza A viruses to be used in vaccine manufacture are not wild-type viruses but rather reassortants that are hybrid viruses containing at least the HA and NA gene segments from the target strains and other gene segments from the master strain, PR8, which has properties of high growth in fertilized hen's eggs. This additional process requires more time and quality control, and specifically for HPAI viruses, it is a process that may fail because of the nature of those viruses. In contrast, viral-vectored vaccines are relatively easy to manipulate and produce, and have well-established safety profiles. There are several viral-based vectors currently employed as antigen delivery systems, including poxviruses, adenoviruses baculovirus, paramyxovirus, rhabdovirus, and others; however, the majority of human clinical trials assessing viral-vectored influenza vaccines use poxvirus and adenovirus vectors. While each of these vector approaches has unique features and is in different stages of development, the combined successes of these approaches supports the virus-vectored vaccine approach as a whole. Issues such as preexisting immunity and cold chain requirements, and lingering safety concerns will have to be overcome; however, each approach is making progress in addressing these issues, and all of the approaches are still viable. Virus-vectored vaccines hold particular promise for vaccination with universal or focused antigens where traditional vaccination methods are not suited to efficacious delivery of these antigens. The most promising approaches currently in development are arguably those targeting conserved HA stalk region epitopes. Given the findings to date, virus-vectored vaccines hold great promise and may overcome the current limitations of influenza vaccines. | What have the limited NDV human trails shown? | false | 1,588 | {
"text": [
"the NDV vector is well-tolerated, even at high doses delivered intravenously"
],
"answer_start": [
25083
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} |
2,466 | Critical care response to a hospital outbreak of the 2019-nCoV infection in Shenzhen, China
https://doi.org/10.1186/s13054-020-2786-x
SHA: 6a93283b499ae5bc6aaf29f14e701dc8f25138ea
Authors: Liu, Yong; Li, Jinxiu; Feng, Yongwen
Date: 2020
DOI: 10.1186/s13054-020-2786-x
License: cc-by
Abstract: nan
Text: The main challenge may include (1) early identification of outbreak, (2) rapid expansion of patients, (3) high risk of nosocomial transmission, (4) unpredictability of size impacted, and (5) lack of backup resource. These challenges have caused severe shortage of healthcare workers, medical materials, and beds with isolation. The Spring Festival holiday has greatly aggravated the shortage of human resources and heavy traffic flow due to the vacation of healthy workers and factory workers, which further magnified the risk of transmission. The key point is to discriminate the infectious disease outbreak from regular clustering cases of flu-like diseases at early stage. There is a trade-off between false alarm causing population panic and delayed identification leading to social crisis.
Early identification of 2019-nCoV infection presents a major challenge for the frontline clinicians. Its clinical symptoms largely overlap with those of common acute respiratory illnesses, including fever (98%), cough (76%), and diarrhea (3%), often more severe in older adults with pre-existing chronic comorbidities [1] . Usually, the laboratory abnormalities include lymphocytopenia and hypoxemia [1] . The initial chest radiographs may vary from minimal abnormality to bilateral ground-glass opacity or subsegmental areas of consolidation [1] . In addition, asymptomatic cases and lack of diagnosis kits result in delayed or even missed diagnosis inevitable and makes many other patients, visitors, and healthcare workers exposed to the 2019-nCoV infection.
Critical care response to the outbreak of coronavirus should happen not only at the level of hospital, but also at the level of the city which is dominated by the government. At the early stage, the size of the patients' population is not beyond the capability of local infectious diseases hospital (IDH). The general hospital is responsible for fever triage, identifying suspected cases, and transferring to the local IDH. Such a plan is mandatory for every hospital. Shenzhen city has established a preexisting Infectious Disease Epidemic Plan (IDEP), which has facilitated managing and containing local outbreak of the 2019-nCoV. In case the patient load exceeds the hospital capability of the IDH, new IDHs should be considered either by building a temporary new IDH or reconstructing an existing hospital. Wuhan, the epicenter of the outbreak, is racing against time to build two specialized hospitals for nCoV patients, namely Huoshenshan and Leishenshan hospital, whereas a different strategy has been undertaken in Shenzhen city by reconstructing an existing hospital to become an IDH with capability of 800 beds.
2019-nCoV patients should be admitted to singlebedded, negative pressure rooms in isolated units with intensive care and monitoring [2] . Clinical engineering should have plans to reconstruct standard rooms [2] . Retrofitting the rooms with externally exhausted HEPA filters may be an expedient solution. Also, the general hospital may consider procedures such as suspending elective surgeries, canceling ambulatory clinics and outpatient diagnostic procedures, transferring patients to other institutions, and restricting hospital visitors [2] . More importantly, because the hospitals' ability to respond to the outbreak largely depends on their available ICU beds, the plan to increase ICU bed capacity needs to be determined.
Caring for 2019-nCoV patients represents a substantial exposure risk for ICU staff because of the following reasons: highly contagious with multiple transmission route, high exposure dose, long daily contact hours, and ICU stay. The basic reproductive number was estimated to be 2.2 (95% CI, 1.4 to 3.9) [3] , or as high as between 3.6 and 4.0 [4] . The 2019-nCoV is proved to be transmitted by respiratory droplets, contact, and fecal-oral, even transmission through the eye is possible [5, 6] . The higher viral load and aerosol-generating procedures, such as noninvasive ventilation, magnify the exposure and transmission risk [2, 7, 8] . Moreover, virus shedding can be prolonged and last for > 3 weeks according to some literature and our unpublished data [2] . Healthcare providers and those in contact with infected patients should utilize contact, droplet, and airborne precautions with N95 respirator. Strict infection prevention and control practices have been implemented and audited in our units following the infection prevention and control plan published by China's National Health Committee (CNHC). In addition, wellequipped fever clinic as triage station with trained staff knowing 2019-nCoV case definitions is established. For suspected 2019-nCoV infection, several key points are crucial procedures: recording a detailed history, standardizing pneumonia workup, obtaining lower respiratory tract specimens [2, 8] , and implementing droplet isolation to break the transmission chain in the healthcare setting [2] .
The risk of 2019-nCoV exposure may cause significant psychosocial stress on healthcare workers [2] . The death of a retired ENT physician from a 2019-nCoV infection has added to fears in January 2020. Psychotherapists have also been invited to join medical teams to evaluate and deal with potential stress and depression for the safety of the healthcare workers.
Critical management 2019-nCoV management was largely supportive, including intubation, early prone positioning, neuromuscular blockade, and extracorporeal membrane oxygenation (ECMO) according to the recommendations updated by CNHC. Low-dose systematic corticosteroids, lopinavir/ritonavir, and atomization inhalation of interferon were encouraged. These critical managements have worked well so far, as our 2019-nCoV patients had zero mortality. On the contrary, the previously reported mortality of 2019-nCoV patients in Wuhan ranged from 11 to 15% [1, 9] . | Why exposure risk of COVID-19 is very high for ICU staff and what precautions should be taken? | false | 645 | {
"text": [
"substantial exposure risk for ICU staff because of the following reasons"
],
"answer_start": [
3763
]
} |
2,504 | Respiratory Viral Infections in Exacerbation of Chronic Airway Inflammatory Diseases: Novel Mechanisms and Insights From the Upper Airway Epithelium
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7052386/
SHA: 45a566c71056ba4faab425b4f7e9edee6320e4a4
Authors: Tan, Kai Sen; Lim, Rachel Liyu; Liu, Jing; Ong, Hsiao Hui; Tan, Vivian Jiayi; Lim, Hui Fang; Chung, Kian Fan; Adcock, Ian M.; Chow, Vincent T.; Wang, De Yun
Date: 2020-02-25
DOI: 10.3389/fcell.2020.00099
License: cc-by
Abstract: Respiratory virus infection is one of the major sources of exacerbation of chronic airway inflammatory diseases. These exacerbations are associated with high morbidity and even mortality worldwide. The current understanding on viral-induced exacerbations is that viral infection increases airway inflammation which aggravates disease symptoms. Recent advances in in vitro air-liquid interface 3D cultures, organoid cultures and the use of novel human and animal challenge models have evoked new understandings as to the mechanisms of viral exacerbations. In this review, we will focus on recent novel findings that elucidate how respiratory viral infections alter the epithelial barrier in the airways, the upper airway microbial environment, epigenetic modifications including miRNA modulation, and other changes in immune responses throughout the upper and lower airways. First, we reviewed the prevalence of different respiratory viral infections in causing exacerbations in chronic airway inflammatory diseases. Subsequently we also summarized how recent models have expanded our appreciation of the mechanisms of viral-induced exacerbations. Further we highlighted the importance of the virome within the airway microbiome environment and its impact on subsequent bacterial infection. This review consolidates the understanding of viral induced exacerbation in chronic airway inflammatory diseases and indicates pathways that may be targeted for more effective management of chronic inflammatory diseases.
Text: The prevalence of chronic airway inflammatory disease is increasing worldwide especially in developed nations (GBD 2015 Chronic Respiratory Disease Collaborators, 2017 Guan et al., 2018) . This disease is characterized by airway inflammation leading to complications such as coughing, wheezing and shortness of breath. The disease can manifest in both the upper airway (such as chronic rhinosinusitis, CRS) and lower airway (such as asthma and chronic obstructive pulmonary disease, COPD) which greatly affect the patients' quality of life (Calus et al., 2012; Bao et al., 2015) . Treatment and management vary greatly in efficacy due to the complexity and heterogeneity of the disease. This is further complicated by the effect of episodic exacerbations of the disease, defined as worsening of disease symptoms including wheeze, cough, breathlessness and chest tightness (Xepapadaki and Papadopoulos, 2010) . Such exacerbations are due to the effect of enhanced acute airway inflammation impacting upon and worsening the symptoms of the existing disease (Hashimoto et al., 2008; Viniol and Vogelmeier, 2018) . These acute exacerbations are the main cause of morbidity and sometimes mortality in patients, as well as resulting in major economic burdens worldwide. However, due to the complex interactions between the host and the exacerbation agents, the mechanisms of exacerbation may vary considerably in different individuals under various triggers. Acute exacerbations are usually due to the presence of environmental factors such as allergens, pollutants, smoke, cold or dry air and pathogenic microbes in the airway (Gautier and Charpin, 2017; Viniol and Vogelmeier, 2018) . These agents elicit an immune response leading to infiltration of activated immune cells that further release inflammatory mediators that cause acute symptoms such as increased mucus production, cough, wheeze and shortness of breath. Among these agents, viral infection is one of the major drivers of asthma exacerbations accounting for up to 80-90% and 45-80% of exacerbations in children and adults respectively (Grissell et al., 2005; Xepapadaki and Papadopoulos, 2010; Jartti and Gern, 2017; Adeli et al., 2019) . Viral involvement in COPD exacerbation is also equally high, having been detected in 30-80% of acute COPD exacerbations (Kherad et al., 2010; Jafarinejad et al., 2017; Stolz et al., 2019) . Whilst the prevalence of viral exacerbations in CRS is still unclear, its prevalence is likely to be high due to the similar inflammatory nature of these diseases (Rowan et al., 2015; Tan et al., 2017) . One of the reasons for the involvement of respiratory viruses' in exacerbations is their ease of transmission and infection (Kutter et al., 2018) . In addition, the high diversity of the respiratory viruses may also contribute to exacerbations of different nature and severity (Busse et al., 2010; Costa et al., 2014; Jartti and Gern, 2017) . Hence, it is important to identify the exact mechanisms underpinning viral exacerbations in susceptible subjects in order to properly manage exacerbations via supplementary treatments that may alleviate the exacerbation symptoms or prevent severe exacerbations.
While the lower airway is the site of dysregulated inflammation in most chronic airway inflammatory diseases, the upper airway remains the first point of contact with sources of exacerbation. Therefore, their interaction with the exacerbation agents may directly contribute to the subsequent responses in the lower airway, in line with the "United Airway" hypothesis. To elucidate the host airway interaction with viruses leading to exacerbations, we thus focus our review on recent findings of viral interaction with the upper airway. We compiled how viral induced changes to the upper airway may contribute to chronic airway inflammatory disease exacerbations, to provide a unified elucidation of the potential exacerbation mechanisms initiated from predominantly upper airway infections.
Despite being a major cause of exacerbation, reports linking respiratory viruses to acute exacerbations only start to emerge in the late 1950s (Pattemore et al., 1992) ; with bacterial infections previously considered as the likely culprit for acute exacerbation (Stevens, 1953; Message and Johnston, 2002) . However, with the advent of PCR technology, more viruses were recovered during acute exacerbations events and reports implicating their role emerged in the late 1980s (Message and Johnston, 2002) . Rhinovirus (RV) and respiratory syncytial virus (RSV) are the predominant viruses linked to the development and exacerbation of chronic airway inflammatory diseases (Jartti and Gern, 2017) . Other viruses such as parainfluenza virus (PIV), influenza virus (IFV) and adenovirus (AdV) have also been implicated in acute exacerbations but to a much lesser extent (Johnston et al., 2005; Oliver et al., 2014; Ko et al., 2019) . More recently, other viruses including bocavirus (BoV), human metapneumovirus (HMPV), certain coronavirus (CoV) strains, a specific enterovirus (EV) strain EV-D68, human cytomegalovirus (hCMV) and herpes simplex virus (HSV) have been reported as contributing to acute exacerbations . The common feature these viruses share is that they can infect both the upper and/or lower airway, further increasing the inflammatory conditions in the diseased airway (Mallia and Johnston, 2006; Britto et al., 2017) .
Respiratory viruses primarily infect and replicate within airway epithelial cells . During the replication process, the cells release antiviral factors and cytokines that alter local airway inflammation and airway niche (Busse et al., 2010) . In a healthy airway, the inflammation normally leads to type 1 inflammatory responses consisting of activation of an antiviral state and infiltration of antiviral effector cells. This eventually results in the resolution of the inflammatory response and clearance of the viral infection (Vareille et al., 2011; Braciale et al., 2012) . However, in a chronically inflamed airway, the responses against the virus may be impaired or aberrant, causing sustained inflammation and erroneous infiltration, resulting in the exacerbation of their symptoms (Mallia and Johnston, 2006; Dougherty and Fahy, 2009; Busse et al., 2010; Britto et al., 2017; Linden et al., 2019) . This is usually further compounded by the increased susceptibility of chronic airway inflammatory disease patients toward viral respiratory infections, thereby increasing the frequency of exacerbation as a whole (Dougherty and Fahy, 2009; Busse et al., 2010; Linden et al., 2019) . Furthermore, due to the different replication cycles and response against the myriad of respiratory viruses, each respiratory virus may also contribute to exacerbations via different mechanisms that may alter their severity. Hence, this review will focus on compiling and collating the current known mechanisms of viral-induced exacerbation of chronic airway inflammatory diseases; as well as linking the different viral infection pathogenesis to elucidate other potential ways the infection can exacerbate the disease. The review will serve to provide further understanding of viral induced exacerbation to identify potential pathways and pathogenesis mechanisms that may be targeted as supplementary care for management and prevention of exacerbation. Such an approach may be clinically significant due to the current scarcity of antiviral drugs for the management of viral-induced exacerbations. This will improve the quality of life of patients with chronic airway inflammatory diseases.
Once the link between viral infection and acute exacerbations of chronic airway inflammatory disease was established, there have been many reports on the mechanisms underlying the exacerbation induced by respiratory viral infection. Upon infecting the host, viruses evoke an inflammatory response as a means of counteracting the infection. Generally, infected airway epithelial cells release type I (IFNα/β) and type III (IFNλ) interferons, cytokines and chemokines such as IL-6, IL-8, IL-12, RANTES, macrophage inflammatory protein 1α (MIP-1α) and monocyte chemotactic protein 1 (MCP-1) (Wark and Gibson, 2006; Matsukura et al., 2013) . These, in turn, enable infiltration of innate immune cells and of professional antigen presenting cells (APCs) that will then in turn release specific mediators to facilitate viral targeting and clearance, including type II interferon (IFNγ), IL-2, IL-4, IL-5, IL-9, and IL-12 (Wark and Gibson, 2006; Singh et al., 2010; Braciale et al., 2012) . These factors heighten local inflammation and the infiltration of granulocytes, T-cells and B-cells (Wark and Gibson, 2006; Braciale et al., 2012) . The increased inflammation, in turn, worsens the symptoms of airway diseases.
Additionally, in patients with asthma and patients with CRS with nasal polyp (CRSwNP), viral infections such as RV and RSV promote a Type 2-biased immune response (Becker, 2006; Jackson et al., 2014; Jurak et al., 2018) . This amplifies the basal type 2 inflammation resulting in a greater release of IL-4, IL-5, IL-13, RANTES and eotaxin and a further increase in eosinophilia, a key pathological driver of asthma and CRSwNP (Wark and Gibson, 2006; Singh et al., 2010; Chung et al., 2015; Dunican and Fahy, 2015) . Increased eosinophilia, in turn, worsens the classical symptoms of disease and may further lead to life-threatening conditions due to breathing difficulties. On the other hand, patients with COPD and patients with CRS without nasal polyp (CRSsNP) are more neutrophilic in nature due to the expression of neutrophil chemoattractants such as CXCL9, CXCL10, and CXCL11 (Cukic et al., 2012; Brightling and Greening, 2019) . The pathology of these airway diseases is characterized by airway remodeling due to the presence of remodeling factors such as matrix metalloproteinases (MMPs) released from infiltrating neutrophils (Linden et al., 2019) . Viral infections in such conditions will then cause increase neutrophilic activation; worsening the symptoms and airway remodeling in the airway thereby exacerbating COPD, CRSsNP and even CRSwNP in certain cases (Wang et al., 2009; Tacon et al., 2010; Linden et al., 2019) .
An epithelial-centric alarmin pathway around IL-25, IL-33 and thymic stromal lymphopoietin (TSLP), and their interaction with group 2 innate lymphoid cells (ILC2) has also recently been identified (Nagarkar et al., 2012; Hong et al., 2018; Allinne et al., 2019) . IL-25, IL-33 and TSLP are type 2 inflammatory cytokines expressed by the epithelial cells upon injury to the epithelial barrier (Gabryelska et al., 2019; Roan et al., 2019) . ILC2s are a group of lymphoid cells lacking both B and T cell receptors but play a crucial role in secreting type 2 cytokines to perpetuate type 2 inflammation when activated (Scanlon and McKenzie, 2012; Li and Hendriks, 2013) . In the event of viral infection, cell death and injury to the epithelial barrier will also induce the expression of IL-25, IL-33 and TSLP, with heighten expression in an inflamed airway (Allakhverdi et al., 2007; Goldsmith et al., 2012; Byers et al., 2013; Shaw et al., 2013; Beale et al., 2014; Jackson et al., 2014; Uller and Persson, 2018; Ravanetti et al., 2019) . These 3 cytokines then work in concert to activate ILC2s to further secrete type 2 cytokines IL-4, IL-5, and IL-13 which further aggravate the type 2 inflammation in the airway causing acute exacerbation (Camelo et al., 2017) . In the case of COPD, increased ILC2 activation, which retain the capability of differentiating to ILC1, may also further augment the neutrophilic response and further aggravate the exacerbation (Silver et al., 2016) . Interestingly, these factors are not released to any great extent and do not activate an ILC2 response during viral infection in healthy individuals (Yan et al., 2016; Tan et al., 2018a) ; despite augmenting a type 2 exacerbation in chronically inflamed airways (Jurak et al., 2018) . These classical mechanisms of viral induced acute exacerbations are summarized in Figure 1 .
As integration of the virology, microbiology and immunology of viral infection becomes more interlinked, additional factors and FIGURE 1 | Current understanding of viral induced exacerbation of chronic airway inflammatory diseases. Upon virus infection in the airway, antiviral state will be activated to clear the invading pathogen from the airway. Immune response and injury factors released from the infected epithelium normally would induce a rapid type 1 immunity that facilitates viral clearance. However, in the inflamed airway, the cytokines and chemokines released instead augmented the inflammation present in the chronically inflamed airway, strengthening the neutrophilic infiltration in COPD airway, and eosinophilic infiltration in the asthmatic airway. The effect is also further compounded by the participation of Th1 and ILC1 cells in the COPD airway; and Th2 and ILC2 cells in the asthmatic airway.
Frontiers in Cell and Developmental Biology | www.frontiersin.org mechanisms have been implicated in acute exacerbations during and after viral infection (Murray et al., 2006) . Murray et al. (2006) has underlined the synergistic effect of viral infection with other sensitizing agents in causing more severe acute exacerbations in the airway. This is especially true when not all exacerbation events occurred during the viral infection but may also occur well after viral clearance (Kim et al., 2008; Stolz et al., 2019) in particular the late onset of a bacterial infection (Singanayagam et al., 2018 (Singanayagam et al., , 2019a . In addition, viruses do not need to directly infect the lower airway to cause an acute exacerbation, as the nasal epithelium remains the primary site of most infections. Moreover, not all viral infections of the airway will lead to acute exacerbations, suggesting a more complex interplay between the virus and upper airway epithelium which synergize with the local airway environment in line with the "united airway" hypothesis (Kurai et al., 2013) . On the other hand, viral infections or their components persist in patients with chronic airway inflammatory disease (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Hence, their presence may further alter the local environment and contribute to current and future exacerbations. Future studies should be performed using metagenomics in addition to PCR analysis to determine the contribution of the microbiome and mycobiome to viral infections. In this review, we highlight recent data regarding viral interactions with the airway epithelium that could also contribute to, or further aggravate, acute exacerbations of chronic airway inflammatory diseases.
Patients with chronic airway inflammatory diseases have impaired or reduced ability of viral clearance (Hammond et al., 2015; McKendry et al., 2016; Akbarshahi et al., 2018; Gill et al., 2018; Wang et al., 2018; Singanayagam et al., 2019b) . Their impairment stems from a type 2-skewed inflammatory response which deprives the airway of important type 1 responsive CD8 cells that are responsible for the complete clearance of virusinfected cells (Becker, 2006; McKendry et al., 2016) . This is especially evident in weak type 1 inflammation-inducing viruses such as RV and RSV (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Additionally, there are also evidence of reduced type I (IFNβ) and III (IFNλ) interferon production due to type 2-skewed inflammation, which contributes to imperfect clearance of the virus resulting in persistence of viral components, or the live virus in the airway epithelium (Contoli et al., 2006; Hwang et al., 2019; Wark, 2019) . Due to the viral components remaining in the airway, antiviral genes such as type I interferons, inflammasome activating factors and cytokines remained activated resulting in prolong airway inflammation (Wood et al., 2011; Essaidi-Laziosi et al., 2018) . These factors enhance granulocyte infiltration thus prolonging the exacerbation symptoms. Such persistent inflammation may also be found within DNA viruses such as AdV, hCMV and HSV, whose infections generally persist longer (Imperiale and Jiang, 2015) , further contributing to chronic activation of inflammation when they infect the airway (Yang et al., 2008; Morimoto et al., 2009; Imperiale and Jiang, 2015; Lan et al., 2016; Tan et al., 2016; Kowalski et al., 2017) . With that note, human papilloma virus (HPV), a DNA virus highly associated with head and neck cancers and respiratory papillomatosis, is also linked with the chronic inflammation that precedes the malignancies (de Visser et al., 2005; Gillison et al., 2012; Bonomi et al., 2014; Fernandes et al., 2015) . Therefore, the role of HPV infection in causing chronic inflammation in the airway and their association to exacerbations of chronic airway inflammatory diseases, which is scarcely explored, should be investigated in the future. Furthermore, viral persistence which lead to continuous expression of antiviral genes may also lead to the development of steroid resistance, which is seen with RV, RSV, and PIV infection (Chi et al., 2011; Ford et al., 2013; Papi et al., 2013) . The use of steroid to suppress the inflammation may also cause the virus to linger longer in the airway due to the lack of antiviral clearance (Kim et al., 2008; Hammond et al., 2015; Hewitt et al., 2016; McKendry et al., 2016; Singanayagam et al., 2019b) . The concomitant development of steroid resistance together with recurring or prolong viral infection thus added considerable burden to the management of acute exacerbation, which should be the future focus of research to resolve the dual complications arising from viral infection.
On the other end of the spectrum, viruses that induce strong type 1 inflammation and cell death such as IFV (Yan et al., 2016; Guibas et al., 2018) and certain CoV (including the recently emerged COVID-19 virus) (Tao et al., 2013; Yue et al., 2018; Zhu et al., 2020) , may not cause prolonged inflammation due to strong induction of antiviral clearance. These infections, however, cause massive damage and cell death to the epithelial barrier, so much so that areas of the epithelium may be completely absent post infection (Yan et al., 2016; Tan et al., 2019) . Factors such as RANTES and CXCL10, which recruit immune cells to induce apoptosis, are strongly induced from IFV infected epithelium (Ampomah et al., 2018; Tan et al., 2019) . Additionally, necroptotic factors such as RIP3 further compounds the cell deaths in IFV infected epithelium . The massive cell death induced may result in worsening of the acute exacerbation due to the release of their cellular content into the airway, further evoking an inflammatory response in the airway (Guibas et al., 2018) . Moreover, the destruction of the epithelial barrier may cause further contact with other pathogens and allergens in the airway which may then prolong exacerbations or results in new exacerbations. Epithelial destruction may also promote further epithelial remodeling during its regeneration as viral infection induces the expression of remodeling genes such as MMPs and growth factors . Infections that cause massive destruction of the epithelium, such as IFV, usually result in severe acute exacerbations with non-classical symptoms of chronic airway inflammatory diseases. Fortunately, annual vaccines are available to prevent IFV infections (Vasileiou et al., 2017; Zheng et al., 2018) ; and it is recommended that patients with chronic airway inflammatory disease receive their annual influenza vaccination as the best means to prevent severe IFV induced exacerbation.
Another mechanism that viral infections may use to drive acute exacerbations is the induction of vasodilation or tight junction opening factors which may increase the rate of infiltration. Infection with a multitude of respiratory viruses causes disruption of tight junctions with the resulting increased rate of viral infiltration. This also increases the chances of allergens coming into contact with airway immune cells. For example, IFV infection was found to induce oncostatin M (OSM) which causes tight junction opening (Pothoven et al., 2015; Tian et al., 2018) . Similarly, RV and RSV infections usually cause tight junction opening which may also increase the infiltration rate of eosinophils and thus worsening of the classical symptoms of chronic airway inflammatory diseases (Sajjan et al., 2008; Kast et al., 2017; Kim et al., 2018) . In addition, the expression of vasodilating factors and fluid homeostatic factors such as angiopoietin-like 4 (ANGPTL4) and bactericidal/permeabilityincreasing fold-containing family member A1 (BPIFA1) are also associated with viral infections and pneumonia development, which may worsen inflammation in the lower airway Akram et al., 2018) . These factors may serve as targets to prevent viral-induced exacerbations during the management of acute exacerbation of chronic airway inflammatory diseases.
Another recent area of interest is the relationship between asthma and COPD exacerbations and their association with the airway microbiome. The development of chronic airway inflammatory diseases is usually linked to specific bacterial species in the microbiome which may thrive in the inflamed airway environment (Diver et al., 2019) . In the event of a viral infection such as RV infection, the effect induced by the virus may destabilize the equilibrium of the microbiome present (Molyneaux et al., 2013; Kloepfer et al., 2014; Kloepfer et al., 2017; Jubinville et al., 2018; van Rijn et al., 2019) . In addition, viral infection may disrupt biofilm colonies in the upper airway (e.g., Streptococcus pneumoniae) microbiome to be release into the lower airway and worsening the inflammation (Marks et al., 2013; Chao et al., 2014) . Moreover, a viral infection may also alter the nutrient profile in the airway through release of previously inaccessible nutrients that will alter bacterial growth (Siegel et al., 2014; Mallia et al., 2018) . Furthermore, the destabilization is further compounded by impaired bacterial immune response, either from direct viral influences, or use of corticosteroids to suppress the exacerbation symptoms (Singanayagam et al., 2018 (Singanayagam et al., , 2019a Wang et al., 2018; Finney et al., 2019) . All these may gradually lead to more far reaching effect when normal flora is replaced with opportunistic pathogens, altering the inflammatory profiles (Teo et al., 2018) . These changes may in turn result in more severe and frequent acute exacerbations due to the interplay between virus and pathogenic bacteria in exacerbating chronic airway inflammatory diseases (Wark et al., 2013; Singanayagam et al., 2018) . To counteract these effects, microbiome-based therapies are in their infancy but have shown efficacy in the treatments of irritable bowel syndrome by restoring the intestinal microbiome (Bakken et al., 2011) . Further research can be done similarly for the airway microbiome to be able to restore the microbiome following disruption by a viral infection.
Viral infections can cause the disruption of mucociliary function, an important component of the epithelial barrier. Ciliary proteins FIGURE 2 | Changes in the upper airway epithelium contributing to viral exacerbation in chronic airway inflammatory diseases. The upper airway epithelium is the primary contact/infection site of most respiratory viruses. Therefore, its infection by respiratory viruses may have far reaching consequences in augmenting and synergizing current and future acute exacerbations. The destruction of epithelial barrier, mucociliary function and cell death of the epithelial cells serves to increase contact between environmental triggers with the lower airway and resident immune cells. The opening of tight junction increasing the leakiness further augments the inflammation and exacerbations. In addition, viral infections are usually accompanied with oxidative stress which will further increase the local inflammation in the airway. The dysregulation of inflammation can be further compounded by modulation of miRNAs and epigenetic modification such as DNA methylation and histone modifications that promote dysregulation in inflammation. Finally, the change in the local airway environment and inflammation promotes growth of pathogenic bacteria that may replace the airway microbiome. Furthermore, the inflammatory environment may also disperse upper airway commensals into the lower airway, further causing inflammation and alteration of the lower airway environment, resulting in prolong exacerbation episodes following viral infection.
Viral specific trait contributing to exacerbation mechanism (with literature evidence) Oxidative stress ROS production (RV, RSV, IFV, HSV)
As RV, RSV, and IFV were the most frequently studied viruses in chronic airway inflammatory diseases, most of the viruses listed are predominantly these viruses. However, the mechanisms stated here may also be applicable to other viruses but may not be listed as they were not implicated in the context of chronic airway inflammatory diseases exacerbation (see text for abbreviations).
that aid in the proper function of the motile cilia in the airways are aberrantly expressed in ciliated airway epithelial cells which are the major target for RV infection (Griggs et al., 2017) . Such form of secondary cilia dyskinesia appears to be present with chronic inflammations in the airway, but the exact mechanisms are still unknown (Peng et al., , 2019 Qiu et al., 2018) . Nevertheless, it was found that in viral infection such as IFV, there can be a change in the metabolism of the cells as well as alteration in the ciliary gene expression, mostly in the form of down-regulation of the genes such as dynein axonemal heavy chain 5 (DNAH5) and multiciliate differentiation And DNA synthesis associated cell cycle protein (MCIDAS) (Tan et al., 2018b . The recently emerged Wuhan CoV was also found to reduce ciliary beating in infected airway epithelial cell model (Zhu et al., 2020) . Furthermore, viral infections such as RSV was shown to directly destroy the cilia of the ciliated cells and almost all respiratory viruses infect the ciliated cells (Jumat et al., 2015; Yan et al., 2016; Tan et al., 2018a) . In addition, mucus overproduction may also disrupt the equilibrium of the mucociliary function following viral infection, resulting in symptoms of acute exacerbation (Zhu et al., 2009) . Hence, the disruption of the ciliary movement during viral infection may cause more foreign material and allergen to enter the airway, aggravating the symptoms of acute exacerbation and making it more difficult to manage. The mechanism of the occurrence of secondary cilia dyskinesia can also therefore be explored as a means to limit the effects of viral induced acute exacerbation.
MicroRNAs (miRNAs) are short non-coding RNAs involved in post-transcriptional modulation of biological processes, and implicated in a number of diseases (Tan et al., 2014) . miRNAs are found to be induced by viral infections and may play a role in the modulation of antiviral responses and inflammation (Gutierrez et al., 2016; Deng et al., 2017; Feng et al., 2018) . In the case of chronic airway inflammatory diseases, circulating miRNA changes were found to be linked to exacerbation of the diseases (Wardzynska et al., 2020) . Therefore, it is likely that such miRNA changes originated from the infected epithelium and responding immune cells, which may serve to further dysregulate airway inflammation leading to exacerbations. Both IFV and RSV infections has been shown to increase miR-21 and augmented inflammation in experimental murine asthma models, which is reversed with a combination treatment of anti-miR-21 and corticosteroids (Kim et al., 2017) . IFV infection is also shown to increase miR-125a and b, and miR-132 in COPD epithelium which inhibits A20 and MAVS; and p300 and IRF3, respectively, resulting in increased susceptibility to viral infections (Hsu et al., 2016 (Hsu et al., , 2017 . Conversely, miR-22 was shown to be suppressed in asthmatic epithelium in IFV infection which lead to aberrant epithelial response, contributing to exacerbations (Moheimani et al., 2018) . Other than these direct evidence of miRNA changes in contributing to exacerbations, an increased number of miRNAs and other non-coding RNAs responsible for immune modulation are found to be altered following viral infections (Globinska et al., 2014; Feng et al., 2018; Hasegawa et al., 2018) . Hence non-coding RNAs also presents as targets to modulate viral induced airway changes as a means of managing exacerbation of chronic airway inflammatory diseases. Other than miRNA modulation, other epigenetic modification such as DNA methylation may also play a role in exacerbation of chronic airway inflammatory diseases. Recent epigenetic studies have indicated the association of epigenetic modification and chronic airway inflammatory diseases, and that the nasal methylome was shown to be a sensitive marker for airway inflammatory changes (Cardenas et al., 2019; Gomez, 2019) . At the same time, it was also shown that viral infections such as RV and RSV alters DNA methylation and histone modifications in the airway epithelium which may alter inflammatory responses, driving chronic airway inflammatory diseases and exacerbations (McErlean et al., 2014; Pech et al., 2018; Caixia et al., 2019) . In addition, Spalluto et al. (2017) also showed that antiviral factors such as IFNγ epigenetically modifies the viral resistance of epithelial cells. Hence, this may indicate that infections such as RV and RSV that weakly induce antiviral responses may result in an altered inflammatory state contributing to further viral persistence and exacerbation of chronic airway inflammatory diseases (Spalluto et al., 2017) .
Finally, viral infection can result in enhanced production of reactive oxygen species (ROS), oxidative stress and mitochondrial dysfunction in the airway epithelium (Kim et al., 2018; Mishra et al., 2018; Wang et al., 2018) . The airway epithelium of patients with chronic airway inflammatory diseases are usually under a state of constant oxidative stress which sustains the inflammation in the airway (Barnes, 2017; van der Vliet et al., 2018) . Viral infections of the respiratory epithelium by viruses such as IFV, RV, RSV and HSV may trigger the further production of ROS as an antiviral mechanism Aizawa et al., 2018; Wang et al., 2018) . Moreover, infiltrating cells in response to the infection such as neutrophils will also trigger respiratory burst as a means of increasing the ROS in the infected region. The increased ROS and oxidative stress in the local environment may serve as a trigger to promote inflammation thereby aggravating the inflammation in the airway (Tiwari et al., 2002) . A summary of potential exacerbation mechanisms and the associated viruses is shown in Figure 2 and Table 1 .
While the mechanisms underlying the development and acute exacerbation of chronic airway inflammatory disease is extensively studied for ways to manage and control the disease, a viral infection does more than just causing an acute exacerbation in these patients. A viral-induced acute exacerbation not only induced and worsens the symptoms of the disease, but also may alter the management of the disease or confer resistance toward treatments that worked before. Hence, appreciation of the mechanisms of viral-induced acute exacerbations is of clinical significance to devise strategies to correct viral induce changes that may worsen chronic airway inflammatory disease symptoms. Further studies in natural exacerbations and in viral-challenge models using RNA-sequencing (RNA-seq) or single cell RNA-seq on a range of time-points may provide important information regarding viral pathogenesis and changes induced within the airway of chronic airway inflammatory disease patients to identify novel targets and pathway for improved management of the disease. Subsequent analysis of functions may use epithelial cell models such as the air-liquid interface, in vitro airway epithelial model that has been adapted to studying viral infection and the changes it induced in the airway (Yan et al., 2016; Boda et al., 2018; Tan et al., 2018a) . Animal-based diseased models have also been developed to identify systemic mechanisms of acute exacerbation (Shin, 2016; Gubernatorova et al., 2019; Tanner and Single, 2019) . Furthermore, the humanized mouse model that possess human immune cells may also serves to unravel the immune profile of a viral infection in healthy and diseased condition (Ito et al., 2019; Li and Di Santo, 2019) . For milder viruses, controlled in vivo human infections can be performed for the best mode of verification of the associations of the virus with the proposed mechanism of viral induced acute exacerbations . With the advent of suitable diseased models, the verification of the mechanisms will then provide the necessary continuation of improving the management of viral induced acute exacerbations.
In conclusion, viral-induced acute exacerbation of chronic airway inflammatory disease is a significant health and economic burden that needs to be addressed urgently. In view of the scarcity of antiviral-based preventative measures available for only a few viruses and vaccines that are only available for IFV infections, more alternative measures should be explored to improve the management of the disease. Alternative measures targeting novel viral-induced acute exacerbation mechanisms, especially in the upper airway, can serve as supplementary treatments of the currently available management strategies to augment their efficacy. New models including primary human bronchial or nasal epithelial cell cultures, organoids or precision cut lung slices from patients with airways disease rather than healthy subjects can be utilized to define exacerbation mechanisms. These mechanisms can then be validated in small clinical trials in patients with asthma or COPD. Having multiple means of treatment may also reduce the problems that arise from resistance development toward a specific treatment. | What can happen in response to the infection such as neutrophils? | false | 4,026 | {
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2,668 | 2019-nCoV: The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081861/
SHA: f323af9a07cc54faf9bdbabadaacb0e8b46f99a2
Authors: Koenig, Kristi L.; Beÿ, Christian K.; McDonald, Eric C.
Date: 2020-01-31
DOI: 10.5811/westjem.2020.1.46760
License: cc-by
Abstract: 2019 Novel Coronavirus (2019-nCoV) is an emerging infectious disease closely related to MERS-CoV and SARS-CoV that was first reported in Wuhan City, Hubei Province, China in December 2019. As of January 2020, cases of 2019-nCoV are continuing to be reported in other Eastern Asian countries as well as in the United States, Europe, Australia, and numerous other countries. An unusually high volume of domestic and international travel corresponding to the beginning of the 2020 Chinese New Year complicated initial identification and containment of infected persons. Due to the rapidly rising number of cases and reported deaths, all countries should be considered at risk of imported 2019-nCoV. Therefore, it is essential for prehospital, clinic, and emergency department personnel to be able to rapidly assess 2019-nCoV risk and take immediate actions if indicated. The Identify-Isolate-Inform (3I) Tool, originally conceived for the initial detection and management of Ebola virus and later adjusted for other infectious agents, can be adapted for any emerging infectious disease. This paper reports a modification of the 3I Tool for use in the initial detection and management of patients under investigation for 2019-nCoV. After initial assessment for symptoms and epidemiological risk factors, including travel to affected areas and exposure to confirmed 2019-nCoV patients within 14 days, patients are classified in a risk-stratified system. Upon confirmation of a suspected 2019-nCoV case, affected persons must immediately be placed in airborne infection isolation and the appropriate public health agencies notified. This modified 3I Tool will assist emergency and primary care clinicians, as well as out-of-hospital providers, in effectively managing persons with suspected or confirmed 2019-nCoV.
Text: 2019 Novel Coronavirus (2019-nCoV) is a novel respiratory disease first reported in Wuhan, Hubei Province, China in December 2019. 1 Chinese health officials were originally investigating a sudden increase in cases of pneumonia which were later determined to be linked to 2019-nCoV. While most cases originated within mainland China, the disease spread to neighboring countries including Taiwan, Thailand, South Korea, and Japan, and later to the United States, Europe, and Australia. A near real-time updated tracking website for cases and locations worldwide, along with reported deaths is available. 2 Chinese health authorities have sequenced 2019-nCoV and freely shared its genetic profile online. 3, 4 Additionally, on January 28, 2020, an Australian laboratory reported growing the virus from a patient sample. As of January 30, 2020, there have been at least 9,776 persons infected and 213 verified deaths. 2 These numbers are likely underestimates due to the limited information available regarding incubation time, transmissibility, and virus origin. The What was the research question? Investigators adapted the "Identify, Isolate, Inform" (3I) Tool for use in suspected cases of 2019-nCoV.
What was the major finding of the study? A novel 2019-nCoV 3I Tool is designed for frontline clinicians in the management of suspected patients.
This 2019-nCoV 3I adaptation will aid healthcare providers most likely to encounter the disease in the containment and effective treatment of patients.
age distribution of these verified deaths is currently not available.
One preliminary, small-scale study of 41 patients in Wuhan China, reported 6 deaths (15% mortality) with a median age of 49.0 years. 5 Additionally, transmission of the virus has reportedly occurred in healthcare facilities in Wuhan City, raising concerns of spread to healthcare workers, as was seen during prior outbreaks of the novel coronaviruses, Middle Eastern Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Due to the dynamic nature of the outbreak, exposure criteria may change depending on where new cases of 2019-nCoV are detected, the degree of transmissibility, and when additional information regarding the origin of the virus is discovered and reported. On January 15, 2020, the Centers for Disease Control and Prevention (CDC) confirmed the first known imported case of 2019-nCoV in the US state of Washington. The patient had recently returned from Wuhan City, where he likely contracted the disease. Chicago health authorities reported a second US case on January 24, 2020. This was quickly followed by additional imported cases reported in Orange and Los Angeles Counties, California on January 26, 2020. Additional suspected cases continue to be evaluated. On January 30, 2020, the CDC reported the first local transmission in the US between members in a household. On the same day, the World Health Organization declared 2019-nCoV to be a Public Health Emergency of International Concern (PHEIC). 6 On January 31, 2020, the US Department of Health and Human Services declared coronavirus a public health emergency. 7 Healthy individuals and those with mild illness may be asymptomatic, while others may have more pronounced symptoms of fever or lower respiratory illness. Upon identification of a suspected patient, that individual should immediately be isolated with airborne precautions. Further workup and laboratory confirmation can then proceed. Emergency physicians (EPs), emergency medical services (EMS) personnel, and other healthcare workers who encounter patients with suspected 2019-nCoV infection must inform the appropriate authorities, including but not limited to hospital infection control and local or state public health agencies.
Healthcare workers must follow on-going developments related to the outbreak, especially new information concerning detection and management. 8, 9 The 3I Tool outlined in this paper is consistent with current US CDC guidelines and can be applied in a variety of settings such as those in emergency departments, urgent-care clinics, physicians' offices, and prehospital settings. This paper will first briefly review 2019-nCoV and then present the novel 2019-nCoV 3I Tool as modified from its initial conception for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18
Coronavirus 2019-nCoV infection commonly presents with signs and symptoms of pneumonia or as a nonspecific lower respiratory illness, with coughing or difficulty breathing accompanied by fever. 5, 19, 20 Fever and cough constitute the most common presentations. However, patients may have other respiratory symptoms, sore throat, nasal congestion, malaise, myalgia, and headache. Bilateral infiltrates may be seen on chest X-ray. Severe cases may present with sepsis and even shock. Conversely, some patients may present as only mildly ill or asymptomatic altogether. 21 To date, patients with underlying medical conditions and the elderly are more likely to become severely ill, require hospitalization, and ultimately die. 22 Early predictions for incubation time are between 2 and 14 days, based on data from similar coronaviruses. The 14-day criterion for epidemiological risk assumes the longest estimated incubation time. 23 In addition, the World Health Organization (WHO) has created its own interim case definition. 24
By definition, the main features of a novel virus, for example, how it is transmitted, will not be immediately known. However, as with the development of any 3I Tool, it is essential to understand specific characteristics of the disease. In the case of a novel virus such as 2019-CoV, this is challenging since information is rapidly evolving and the science is not yet fully understood. It is possible that the virus will undergo mutations over time that could substantially change its
The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus Koenig et al. features. Nevertheless, an appreciation of the key concepts that drive evidence-based management is beneficial (Table 1) . Management guidance will likely change over time.
With the initial discovery of a new potential public health threat, it will likely be unclear how patients become sick. For example, rather than a contagion, there could be a contaminant or a toxin responsible for signs and symptoms. In this case, the possibility of an environmental toxin in the Wuhan Market was a consideration early on when limited to no human-tohuman transmission was reported. The mode of transmission has implications for the types of personal protective equipment (PPE) needed to protect healthcare providers in the prehospital, clinic, and hospital settings. 25 In addition, patients may need decontamination after exposure to certain toxins. 26 Another important consideration for application of the 3I Tool is whether the disease is contagious prior to symptom onset (like measles) or only after symptoms develop (like Ebola). A January 30, 2020 letter to the New England Journal of Medicine describes a purported confirmed instance of transmission from an asymptomatic individual. Researchers state that, before symptom onset, the primary case infected two individuals, one of which infected two additional colleagues. 27 Subsequent investigation suggested that the source patient did have mild symptoms and had taken an antipyretic, calling this reported asymptomatic transmission into question.
While quarantine may not be feasible and can have unintended consequences, 28, 29, 30 it is a public health tool that can be considered in cases when disease is transmissible before symptom onset. 30 Conversely, if a disease is known not to be transmissible prior to symptom onset, asymptomatic exposed patients must be monitored, but do not require quarantine or isolation unless they develop symptoms.
Initially, it may be unclear whether an infectious agent occurred naturally or was deliberately or accidentally released. In this case, a BSL-4 laboratory studying coronaviruses was located approximately 32 kilometers away from the market where initial exposures were felt to occur. 31 Recall that in 2001, the anthrax letter attacks were initially thought to be naturally occurring. Once determined to be bioterrorism, management of the event was similar to that for a chemical exposure with a sudden impact, defined scene, and need for a rapid response and decontamination on site. This differed from the WHO's modeling predicting an aerosolized release that would result in an incubation period with 100,000 or more persons exposed rather than the 22 people who contracted anthrax in 2001. 32 By understanding the key features of a novel disease, healthcare workers can take evidence-based measures to protect themselves, optimize individual patient management, and prevent further disease spread.
It is currently unclear how 2019-nCoV is spread, but it is suspected to be transmitted through contact with infected respiratory secretions, like other known coronaviruses. There are instances of sustained human-to-human transmission across generations of cases, especially near the epicenter in Wuhan City. 21 Current evidence suggests that close contact with an infected person is a major factor in disease transmission. CDC defines "close contact" 33 as being in or within two meters of an area with a confirmed patient or being directly exposed to infectious secretions without appropriate PPE. Healthcare facilities in China have reported spread from person to person. In addition, some mildly ill or potentially even asymptomatic patients may have a higher chance of spreading the disease to others as they may be less likely to seek medical care. 34 The possibility that patients may be infectious prior to symptom onset further compounds the difficulty of containing the virus and effectively preventing transmission.
The current majority of 2019-nCoV cases have been within China and its bordering countries. 2 Persons with recent travel (within 14 days) to Wuhan City or another region with widespread disease, or exposure to a patient under investigation, are considered to have an epidemiologic risk factor and should be assessed for signs and symptoms of a viral illness such as fever and respiratory symptoms. Coronavirus is a zoonotic virus
The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus that is transmitted to humans via contact with infected animals. Preliminary reports suggest the disease may have originated in a seafood and live animal market in Wuhan City, but it is still unknown how or whether such transmission occurred.
Clinicians working with local public health departments must arrange to have specimens from patients under investigation (PUIs) sent to the CDC laboratory. At this time, the CDC has the only laboratory that can definitively test for 2019-nCoV, though laboratory testing capacity is being rapidly expanded. Polymerase chain reaction (PCR) assays conducted on samples from a patient's upper and lower respiratory tracts will be used to confirm potential cases. In addition, serum antibody titers can be analyzed for confirmation of infection or evidence of immunity. Up-to-date information about the needed specimens and handling requirements to test for 2019-nCoV are available on the CDC website. 35
Like other related coronaviruses, patients with 2019-nCoV frequently present with non-specific symptoms resembling that of influenza. Physicians may consider differential diagnoses related to a wide variety of respiratory infections. In order to relate these symptoms to 2019-nCoV, it is imperative that the identification of a potential exposure event (epidemiologic risk factor) within 14 days of symptom onset is made so that a more focused work-up for 2019-nCoV can be completed. Although the likelihood of coinfection of 2019-nCoV and another respiratory virus is thought to be low, a positive finding of another respiratory pathogen does not exclude the diagnosis of 2019-nCoV. Many commercially available respiratory panels include "coronavirus" in the results, but neither a positive nor a negative finding on these panels should be used to include or exclude a diagnosis of 2019-nCoV.
Supportive care with appropriate infection control is the mainstay of current CDC treatment guidelines for 2019-nCoV. There are not yet any approved antiviral treatments for 2019-nCoV. Emergency Use Authorizations (EUA) for compassionate use cases may be forthcoming from the US federal government for normally unapproved treatments. Supportive treatment predominantly includes respiratory support, hydration, and antipyretics. General treatment for severe cases should focus on the preservation of vital organ function. In the future, antiviral medications may be available. If a secondary bacterial infection such as pneumonia develops, targeted antibiotics are indicated.
Prevention of 2019-nCoV transmission, like any other infectious agent, involves minimizing risk of exposure. Vaccines are under accelerated development and may be useful in the future for post-exposure prophylaxis. Healthcare personnel are at increased risk and should practice standard, droplet, and airborne precautions when encountering an infected person, a PUI, or any symptomatic close contacts. Healthcare workers handling specimens should also adhere to CDC guidelines and should not attempt to perform any virus isolation or characterization.
Fever screening has been implemented at numerous airports, including major international hubs within Asia and the US. The efficacy of this intervention is not well documented, however, as some infected persons may be afebrile and disease transmission might occur prior to symptom onset. 27 In addition, people can artificially lower their temperature readings, e.g., by applying ice to their foreheads.
As outlined above, admission criteria for 2019-nCoV are similar to that of other patients. If patients do not meet medical criteria for hospitalization, they may be discharged home with isolation precautions and continued observation. EPs must notify local public health authorities so appropriate monitoring and community protective measures can be instituted.
The Identify-Isolate-Inform (3I) Tool was initially developed for Ebola virus disease 10,11 and later adapted for measles, 12 MERS, 13 mumps, 14 Zika virus disease, 15 hepatitis A, 16 pertussis, 17 and scabies. 18 This novel tool for suspected 2019-nCoV patients ( Figure 1 ) provides frontline clinicians with a simple algorithm to manage an emerging disease. Identification of exposed patients with an epidemiologic risk factor within 14 days of symptom onset is a crucial first step. An automatic prompt in the electronic health record can be useful in assisting clinicians with early identification of patients at risk. Case definitions promulgated by the WHO 24 and CDC 33 provide useful comprehensive definitions that have been incorporated into the 3I Tool. The 2019-nCoV Tool provides an accurate, summarized algorithm to immediately, and effectively manage suspected patients until additional resources can be consulted.
Patients who do not have an exposure risk or any symptoms may be triaged normally. However, before making patient contact, providers must first apply the Vital Sign Zero concept. 36 Vital Sign Zero is a preliminary, non-contact assessment (i.e., performed prior to touching a patient to take traditional vital signs) to first determine whether specific PPE is indicated before the examination commences. By taking the additional time to complete this assessment, risk of exposure and further transmission can be minimized. while in the treatment facility should be started and maintained to assist with the possibility of contact tracing. Following isolation, physicians should immediately inform the appropriate authorities. Patients who do not meet medical criteria for admission can be isolated at home during the evaluation phase. 37 Health department officials can help prevent transmission in isolated patients by providing in-home monitoring and implementing appropriate exposure-control measures.
Providers in the prehospital setting who have a high likelihood of encountering 2019-nCoV patients, such as those near international ports of entry, should adhere to established exposure control guidelines. 38 Along with appropriate PPE, providers should also carry thermometers to quantify any fever. In the US, providers should contact the appropriate CDC quarantine station upon isolation of infected or suspected patients, especially those from Wuhan, China or other regions with widespread disease, who report symptoms in the last 14 days. As for other infectious diseases, assessing travel history is essential. Dispatch protocols have been instituted to facilitate identification of callers to 911 or the country-equivalent emergency number prior to prehospital personnel arrival. 39 In addition, CDC has promulgated EMS guidelines for prehospital PPE, transportation of PUIs, vehicle decontamination, and 911 Public Safety Answering Points (PSAPs) for 2019-nCoV. 40
2019-nCoV is an emerging infectious disease with rapidly evolving features, the full scope of which will be defined over time. Prior outbreaks of coronaviruses can help inform needed actions in the short term to assist with both treatment of individual patients and prevention of global disease spread. This adaptation of the Identify-Isolate-Inform Tool serves as a resource for healthcare workers who need to make clear, rapid assessments when confronted with potential patients. The concise nature of the 2019-nCoV 3I Tool allows for the rapid and effective management of a novel disease by healthcare providers. | When was the first case of COVID19 confirmed in the USA? | false | 2,187 | {
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1,660 | Hantaviruses in the Americas and Their Role as Emerging Pathogens
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3185593/
SHA: efe13a8d42b60ef9f7387ea539a1b2eeb5f80101
Authors: Hjelle, Brian; Torres-Pérez, Fernando
Date: 2010-11-25
DOI: 10.3390/v2122559
License: cc-by
Abstract: The continued emergence and re-emergence of pathogens represent an ongoing, sometimes major, threat to populations. Hantaviruses (family Bunyaviridae) and their associated human diseases were considered to be confined to Eurasia, but the occurrence of an outbreak in 1993–94 in the southwestern United States led to a great increase in their study among virologists worldwide. Well over 40 hantaviral genotypes have been described, the large majority since 1993, and nearly half of them pathogenic for humans. Hantaviruses cause persistent infections in their reservoir hosts, and in the Americas, human disease is manifest as a cardiopulmonary compromise, hantavirus cardiopulmonary syndrome (HCPS), with case-fatality ratios, for the most common viral serotypes, between 30% and 40%. Habitat disturbance and larger-scale ecological disturbances, perhaps including climate change, are among the factors that may have increased the human caseload of HCPS between 1993 and the present. We consider here the features that influence the structure of host population dynamics that may lead to viral outbreaks, as well as the macromolecular determinants of hantaviruses that have been regarded as having potential contribution to pathogenicity.
Text: Emerging pathogens cause new or previously unrecognized diseases, and among them, emerging zoonotic diseases are a major concern among scientists studying infectious diseases at different spatial and temporal scales [1, 2] . Changes in biotic and abiotic conditions may alter population disease dynamics and lead to the emergence of zoonotic infections [3] [4] [5] [6] . During the last decades, several outbreaks of emerging and re-emerging viral pathogens have occurred, affecting both purely-local and worldwide/pandemic involvement of human populations. Among the conspicuous examples are influenza A, Ebola virus, hepatitis C virus, severe adult respiratory distress (SARS), coronavirus, and human immunodeficiency virus, which challenge prevention and control measures of public health systems [7] . In the Americas, the recent outbreak of pandemic influenza A subtype H1N1 became a major target for control due to its rapid spread, and uncertainties in virulence and transmissibility, yet vaccine availability was limited when significant activity occurred in advance of the traditional influenza season [8] . However, in the last century outbreaks of several viral-related diseases have emerged or re-emerged involving arenaviruses and dengue viruses, and more recently, hantaviruses, and the expansion of the geographic range of West Nile virus. Among zoonotic diseases, small mammals are hosts of several pathogenic RNA viruses, especially Arenaviridae and Bunyaviridae: Hantavirus [9] [10] [11] .
Hantavirus infections became a concern in the Americas after the description of an outbreak of acute respiratory distress occurred in the Four Corners area in 1993 [12] . The newly recognized disease, hantavirus cardiopulmonary syndrome, HCPS (or hantavirus pulmonary syndrome), was linked to infection by the newly-discovered Sin Nombre virus (SNV), and the rodent Peromyscus maniculatus (deer mouse) was identified as the reservoir [13] . However, hantavirus infections have a much longer history. A review of ancient Chinese writings, dating back to approximately 960 AD, revealed descriptions closely resembling hemorrhagic fever with renal syndrome (HFRS), the syndrome caused by Old World hantaviruses [14] . During the twentieth century, cases of acute febrile disease with renal compromise were described from several Eurasian countries and Japan, often in association with military engagements [15] . HFRS as a distinct syndrome, however, was first brought to the attention of western medicine in association with an outbreak that occurred among United Nations troops during the Korean conflict between 1951 and 1954, where more than 3,200 soldiers were afflicted [16] . It took more than two decades until the etiologic agent, Hantaan virus (HTNV), was isolated from the striped field mouse Apodemus agrarius, detected in part by the binding of antibodies from patient serum samples to the lung tissues of healthy, wild-caught field mice [17, 18] . The virus was later found to represent the type species of a new genus Hantavirus of the family Bunyaviridae, although it was later apparent that the first hantavirus to be isolated was the shrew-borne Thottapalayam virus [19] . The categorization of hantaviruses as belonging to the family Bunyaviridae is due in part to the consistent presence of three RNA genomes that are circularized in vivo as a result of the presence of terminal complementary nucleotides that help fold the genome into a -hairpin‖ morphology, first described for the Uukuniemi phlebovirus [19, 20] . Table 1 is a list of the predominant, serologically distinct pathogenic hantaviruses. Many other named genotypes are described, but such other pathogenic forms are generally closely related to Andes or, in some cases, Sin Nombre virus.
During virus maturation, the precursor form GPC is processed using a membrane -bound protease into Gn and Gc, a cleavage that occurs, and appears to be signaled, after the conserved peptide signal WAASA at the C-terminal of Gn [24] . Although the two proteins can be expressed independently through transfection, they can be retained in the wrong cellular compartment (ER or aggresome); they thus must be co-expressed to allow them stability so that the two can be assembled correctly in the Golgi [25, [27] [28] [29] .
A number of activities and properties have been identified for the hantavirus envelope glycoproteins, including some features that are suspected to be involved in the pathogenicity of the disease-causing serotypes, a possibility that has engendered experimental attention. The glycoproteins are the known or presumed ligands for at least two distinct cellular receptors, the 3 integrin chain and decay accelerating factor, or DAF [30, 31] ; with gC1qR/p32 also identified as another potential entry receptor [32] . Comparisons with the tick-borne encephalitis virus E protein, led Tischler et al. to consider the Gc glycoprotein as a potential class II fusion protein, perhaps imparting fusion activity to the virion, and this hypothesis has gained support in other studies [33, 34] .
Additional activities have been identified with, or claimed to be related to, Gn. For many of these studies, an underlying premise has held that there are differences between the glycoproteins of -pathogenic‖ hantaviruses relative to viruses in the genus that are dubbed to be -non-pathogenic‖. While it is true that it has not yet been possible to link Prospect Hill virus (PHV) to human disease, the absence of evidence for its pathogenicity should perhaps not be equated with the evidence of its absence. One might only consider that the level of disease (e.g., lethargy, fever, proteinuria, and azotemia) associated with infection of nonhuman primates by PHV is not significantly different from that recorded for nonhuman primate models using the known-pathogen Puumala virus (PUUV) [35, 36] . For the purpose of this discussion we will presume that apathogenic hantaviruses are indeed apathogenic.
While some studies have suggested that Gn glycoproteins are directed more rapidly into the ubiquitin-proteosome pathway than are apathogenic forms, others have interpreted differences in the handling of Gn glycoproteins across hantavirus species by the ubiquitin-proteosomal system as independent of pathogenicity [37] [38] [39] . Some investigators have directed their efforts toward identifying a differential capacity, either kinetic or in absolute magnitude, in the ability of pathogenic and apathogenic hantaviruses to elicit an interferon response in cells. One premise that emerges is that apathogenic forms would tend to induce an earlier innate response that would render it more likely that the virus would be quickly cleared or rendered less competent in its replication so as to blunt any pathological response in the host [40] [41] [42] . The anti-hantavirus innate response can in some cases be attributed to viral interaction as a ligand of TLR-3, but not in others, and in endothelial cells, it appears not to require more than the viral particle itself, even when introduced in replication-incompetent form [43, 44] . Proteins and mRNAs prominently induced by hantaviruses include MxA and IFIT-1 (ISG-56) and others including some with known or suspected anti-viral activity. Those hantaviruses, often highly pathogenic strains, that fail to induce a potent antiviral response, are suspected or presumed to have a (more) potent interferon-pathway antagonism mechanism relative to other viruses, a mechanism that acts positively to prevent an effective innate response from forming, at least early in infection [42, 45] . Yet some instances are reported wherein highly pathogenic hantaviruses, such as SNV, are also able to induce expression of interferon-stimulated gene mRNAs, even very early in infection, with ISG proteins, as expected, taking longer to appear in the cell [44] . Anti-interferon activities have also been attributed to the NSs protein that may be elaborated in cells infected by serotypes that encode this protein [46] . Other investigators have examined the activities of hantavirus glycoproteins and other proteins that might themselves directly affect some aspects of the pathogenic progression associated with hantavirus infection of humans, such as vascular permeability changes. While early attempts to directly cause increases in permeability of endothelial monolayers with viral particles or viral infection were largely disappointing, hantaviruses have been identified as adversely affecting endothelial migration over substrata and in potentiating VEG-F-induced endothelial permeability [47, 48] .
The shorter (50-kD) nucleocapsid or N protein is a structural component of the viral nucleocapsid, along with the genomic viral RNA segments. As an RNA-binding protein that engages the hairpin termini of the genomic segments with high affinity [49, 50] , it limits the access of the RNA to host nucleases and helps to render viral replication a closed process within the cytoplasm. It also acts as a peripheral membrane protein, as does the L protein [51] , an activity that could play a role in its presumed, but not yet demonstrated function as matrix [52] . Until recently, it had not been appreciated that N has a wide variety of other activities, some of which can be linked, not only to fundamental requirements of replication, but also to the interference with an array of the intracellular processes of the normal cell. Thus, an interaction between the amino terminus of the hantavirus N protein and the cellular protein Daxx has been proposed, with the suggestion of potential pro-apoptotic consequences [51] . N is also reported to interact with actin microfilaments, and the SUMO-1 protein [53, 54] . Using reporter-gene based assays, Connie Schmaljohn and her colleagues have reported that Hantaan virus' nucleocapsid protein has an inhibitory role in inflammatory responses mediated by NF kappa B (NF-B). The effects on NF-B expression appeared to be confined to prevention of its nuclear translocation after its attempted activation with lipopolysaccharide, LPS [55] . In the cytoplasm of infected cells, N protein can be found in cellular P bodies where it sequesters and protects 5' caps. It may locate the caps through its interaction with DCP1, a key constituent of P bodies. During hantavirus infection, the viral RNAs become concentrated in P bodies, through their interaction with N and DCP1. The N protein demonstrates preferential protection of mRNAs engineered to prematurely terminate their encoded protein in comparison to native mRNAs [56] . N protein has been increasingly linked to viral replication and translation, sometimes in previously unanticipated ways. It is among a growing family of diverse viral proteins that can serve as a nonspecific -RNA chaperone‖, an activity that should facilitate the L polymerase's access to vRNA for transcription and replication, in that it can transiently dissociate misfolded RNA structures [57] . Some of N protein's effects on translation might not immediately be recognized to be adaptive in nature. It can replace the entire EIF4F translational initiation complex, simultaneously presenting the ribosome with a replacement for the cap-binding activity of eIF 4E, binding to the 43S pre-initiation complex as does eIF 4G, while replacing the helicase activity of eIF 4A, which is presumed to be needed to dissociate higher-order RNA structure [56, 58] . These three factors normally work together to achieve translational initiation. In P bodies, N protein's ability to bind at high affinity to capped native cellular oligoribonucleotides, along with its activity in protecting capped RNAs from degradation likely facilitates the access of capped oligonucleotides for use in transcriptional initiation by L polymerase (-cap snatching‖).
Trafficking of N for viral assembly: Classically, N protein in infected cells appears to be clustered or particulate in nature, with a heavy concentration at a single perinuclear location, widely considered to be the Golgi [27] . The N proteins of hantaviruses are found in association with particulate fractions, and confocal microscopy and biochemical-inhibitor studies have shown that N tracks along microtubules but not with actin filaments [52] . The ultimate destination for N, for its assembly into viral particles is the Golgi, and it traffics there via the endoplasmic reticulum-Golgi intermediate complex (ERGIC), also known as vesicular-tubular cluster [52] . A dominant negative inhibitor, dynamitin, associated with dynein-mediated transport, reduced N's accumulation in the Golgi. Later studies suggested that the specific dependence on microtubular transport is specific to Old World hantaviruses such as HTNV, but that the New World hantavirus ANDV is instead associated with actin filaments [59] . However, recent data indicates that microtubular transport is indeed utilized for the New World hantavirus SNV [60] .
Hantavirus diseases of man have long been suspected of having an immunopathogenic basis in part because of their relatively long incubation period of 2-3 weeks and the observed temporal association between immunologic derangements and the first appearance of signs and symptoms of hantavirus illness. HFRS and HCPS share many clinical features, leading many investigators to consider them to be, in essence, different manifestations of a similar pathogenic process, differing mainly in the primary target organs of disease expression ( Table 2 ). The pathogenesis of hantavirus infections is the topic of a continuously-updated review in the series UpToDate [61] .
By the time symptoms appear in HCPS, both strong antiviral responses, and, for the more virulent viral genotypes, viral RNA can be detected in blood plasma or nucleated blood cells respectively [63, 64] . At least three studies have correlated plasma viral RNA with disease severity for HCPS and HFRS, suggesting that the replication of the virus plays an ongoing and real-time role in viral pathogenesis [65] [66] [67] . Several hallmark pathologic changes have been identified that occur in both HFRS and HCPS. A critical feature of both is a transient (~ 1-5 days) capillary leak involving the kidney and retroperitoneal space in HFRS and the lungs in HCPS. The resulting leakage is exudative in character, with chemical composition high in protein and resembling plasma.
The continued experience indicating the strong tissue tropism for endothelial cells, specifically, is among the several factors that make β3 integrin an especially attractive candidate as an important in vivo receptor for hantaviruses. It is likely that hantaviruses arrive at their target tissues through uptake by regional lymph nodes, perhaps with or within an escorting lung histiocyte. The virus seeds local endothelium, where the first few infected cells give rise, ultimately, to a primary viremia, a process that appears to take a long time for hantavirus infections [62, 63] . By the time that secondary viremia emerges, the agents of the more severe forms of HFRS and HCPS have begun to achieve sufficient mass as to induce, through PAMP-PRR interactions and other means, the expression of proinflammatory cytokines [64] . For HCPS, that expression favors the pulmonary bed and lymphoid organs, yet, for unknown reasons, spares the retroperitoneum and, in general, the kidney. In HFRS the situation is reversed, and yet it is often not appreciated that the expected preferential tissue tropism of HFRS-associated viruses and their HCPS-associated counterparts for the renal and pulmonary beds, respectively, is not as one would predict through the manifestations of the two diseases.
Local elaboration of inflammatory and chemotactic mediators is considered to be a requirement for the development of systemic disease symptoms, with those abnormalities sometimes culminating in shock and death. Yet it is not hypoxemia, due to the prominent pulmonary edema, that leads to death in most fatal cases of HCPS, but rather intoxication of the heart by as-yet-undefined mediators that leads to the low cardiac output state and the associated shock syndrome [64, 65] . It is tempting to speculate that mediators produced in the lung in connection with the inflammatory infiltrate can percolate through the coronary circulation with minimal dilution in HCPS, a disadvantageous consequence of the close anatomic juxtaposition of the two organs. Thus, at least three classes of potential mechanisms, some overlapping and all certainly nonexclusive of the others, could be presumed to underlie the pathogenesis of HCPS. These include:
(1) Innate immune mechanisms. The nature of interactions between hantavirus pathogen-associated molecular patterns (PAMP) with the pattern recognition receptors (PRR) of susceptible endothelial cells are beginning to be clarified. The prototypical HTNV appears to be recognized by TLR-3 [43] . Such an infection has consequences such as increased expression of HLA-DR in dendritic cells [66] and differentiation of monocytes toward dendritic cells [67] .
(2) Direct viral effects. The observed correlation between viral load and disease severity leaves the possibility open that hantavirus particles or RNA can themselves have toxic effects on cells or on signaling. Some investigators have favored direct viral toxicity, acting through the inhibition of endothelial cell barrier function, as an explanation for much of the capillary leak, although there is widespread agreement that multiple mechanisms that mediate pathogenesis likely operate simultaneously in the affected patient [68] . A potentially important clue toward the mechanism by which hantavirus infections deplete blood platelets and, in some cases cause hemorrhagic manifestations, was advanced by the recent discovery that pathogenic hantaviruses are able to recruit platelets to adhere to endothelial cell surfaces, with β3 integrin used as a critical binding element [69] .
(3) Pathogenic effects caused by the activities of specific viral macromolecules. We have reviewed some of the activities associated with the Gn, Gc and N, virally-encoded polypeptides in previous sections.
Testing models of pathogenesis can be done more effectively when there is an animal model that mimics key aspects of the disease. There is no such model that closely mimics HFRS, but animal models exist for both the asymptomatic carriage of PUUV and SNV by their native carrier rodents, the bank vole Myodes glareolus and the deer mouse P. maniculatus; as well as a Syrian hamster model using ANDV or the related Maporal virus from Venezuela, for which an HCPS-mimetic disease is observed [70] [71] [72] [73] .
The ANDV-Syrian hamster model has a number of features in common with the human disease, as well as some differences. Unlike the neurologic diseases that have been possible to elicit with HTNV, the hamster model for HCPS appears to be caused by capillary leak that results in pulmonary edema and the production of a pleural effusion with exudative characteristics. Typically the hamsters die between 11 and 14-d post-inoculation, reflecting a slightly accelerated incubation period in comparison to human infections. As with human HCPS, the microscopic examination of the lung reveals abundant fibrin deposition, thickened alveolar septa, and viral antigen expressed abundantly in the microvascular endothelium. ANDV-infected hamsters fitted with physiologic monitoring devices exhibited diminished pulse pressures, tachycardia, and hypotension that appear to closely mimic the shock that is believed to be the proximate cause of demise in patients who succumb to HCPS [65, 74] .
Compared to the human disease, ANDV-infected hamsters exhibit exceptionally high titers of live ANDV in their tissues, with much of the viral replication occurring in hepatocytes, which are spared in the human disease. Titers of live ANDV in some cases exceed 10 8 /g, whereas hantavirus isolates from human tissues have been notoriously difficult to obtain. Despite the universal occurrence of mildly-elevated hepatic enzymes in patients with HCPS, hepatic enzymes do not appear to be present at elevated levels in the blood of diseased hamsters even immediately before death [75] .
The protracted incubation period associated with hantavirus disease gives the host considerable time to mount a mature immune response against the virus. Thus, in contradistinction to infections of comparable severity and related symptomatology associated with arenaviruses and filoviruses, hantavirus infections of humans are associated with antibody responses of significant titer by the time symptoms commence. Despite this observation, it appears to be possible that natural variation in individual neutralizing antibody responses among patients with SNV infections can be linked to disease severity, suggesting that administration of antiviral antibodies could prove effective therapeutically [76] . In the case of ANDV infection, new evidence has emerged indicating that the apparent clearance of the virus from the blood does not result in the complete removal of antigenic stimulus by the virus, suggesting that the virus may persist, perhaps in some as-yet undetermined immunologically privileged site [77] .
A role for T cell-mediated pathological responses in HFRS and HCPS has been the source of speculation for a variety of reasons. The severity of SNV-associated HCPS may have made it more apparent that the onset of pulmonary edema, tachycardia and hypertension seemed to be all but universally temporally associated with the appearance of a spectrum of highly-activated cells of the lymphoid lineage in the peripheral blood. Cells with a close morphologic similarity to these -immunoblasts‖ were detected in the congested, heavy lungs of patients who came to autopsy, as well as in lymphoid organs and in the portal triads [63, [78] [79] [80] . These observations led to speculation that some component of hantavirus pathogenesis could be linked to the appearance of antiviral T cells that could stimulate or contribute to the appearance of a -storm‖ of mediators and the associated capillary leak phenotype. Subsequent studies have borne out the expectation that a significant fraction of the immunoblast population in patients with HCPS are T cells with specificity for specific class I HLA-presented epitopes of viral antigens, including Gn, Gc and N [77, [81] [82] [83] . Presumably, the antiviral activities of such cells, manifested in part through their elaboration of mediators in the affected interstitium, can contribute to the endothelial/capillary leak that lies at the heart of hantavirus pathogenesis.
Because early cases of HCPS often came to autopsy, it became possible to examine necropsied tissues for expression of cytokines. The study by Mori et al. (1999) revealed high relative expression of proinflammatory cytokines including TNF, IL-1, IL-6, providing evidence in favor of a -cytokine storm‖ model for pathogenesis [64] . The authors believed, based on the morphology of cytokine-secreting cells, that both monocytes and lymphocytes were contributing to the production of cytokines. That proinflammatory mediators are found in elevated levels in the plasma as well as the renal interstitium of patients with acute hantaviral illness has been recognized for some time as well [84, 85] .
While diagnosis of HCPS as well as HFRS is best accomplished with IgM serology, in the acute stage of SNV infection, RT-PCR can also be used if blood cells or blood clot are used instead of plasma or serum, where sensitivity even using nested PCR primers drops to about 70% [86] [87] [88] . In a facility at which many cases of HCPS are treated, the University of New Mexico medical center in Albuquerque, a diagnostic service has long been offered in which the patient's hematologic findings are analyzed to establish the probability that a patient has HCPS. The combination of thrombocytopenia, elevated abundance of -immunoblast‖ lymphocytes, left-shifted polymorphonuclear cell population without strong morphologic evidence for their activation, and elevated hemoglobin or hematocrit values is highly specific for HCPS and allows clinicians the ability to put presumptive-HCPS patients on extracorporeal membrane oxygenation (ECMO), which is believed to have saved many patients from a lethal outcome [89] .
Human infection by hantaviruses is thought to follow contact with secretions or excretions produced by infected rodents. In the United States, 538 human infections by hantavirus were reported through late December 2009 [90] , with New Mexico, Arizona and Colorado exhibiting the highest case-loads. While the prototypical central American hantavirus in central America was Rio Segundo virus of Reithrodontomys mexicanus from Costa Rica, the first human disease appeared some years later in Panama, where Choclo virus (CHOV) arose as the etiologic agent and is believed to be responsible for all known cases of HCPS. The fulvous pygmy rice rat Oligoryzomys fulvescens has been identified as the rodent reservoir [91] . In Panama, the first cases of HCPS, albeit with little or no evident cardiac involvement, were reported in 1999, and since then, 106 human infections have occurred with a 26% mortality rate [92] . Serosurveys of mammals in Mexico and Costa Rica have found anti-hantavirus antibodies [93] [94] [95] [96] , and seroprevalences ranging between 0.6 to 1.6% in human populations were reported despite the absence of known HCPS cases [97] . In South America, HCPS cases have been indentified in Argentina, Bolivia, Brazil, Chile, Paraguay and Uruguay, and evidence for human exposure to hantaviruses have also been reported in Venezuela [98] and Perú [99] . In southern South America, ANDV is the main etiologic agent with cases in Chile and Argentina reported since 1995. In Chile, 671 cases of HCPS due to ANDV have occurred during the period 2001-2009 [100] . Since 1995, more than 1,000 HCPS cases have been reported in Argentina [101] ; in Brazil, approximately 1,100 HCPS cases have been identified between 1993 and 2008 [102] . Case-fatality ratios in those three countries have been similar, ranging from 30% (Argentina), 36% (Chile) and 39% (Brazil).
Hantavirus infections occur more frequently in men than women, although the male/female ratio is highly variable. For example, Panamanian communities showed a ratio of 55 men to 45 women [103] , while in Chile the ratio is more biased to males (71%) [104] . In the Paraguayan Chaco the male-female ratio approaches 50% [105] . In North America, by December 2009 63% of case-patients were males [90] . All ethnic and racial groups seem to be susceptible to hantavirus infections, and the differences between certain groups (as indigenous and non-indigenous) are more likely correlated with the type habitat where the population resides (e.g., rural versus urban areas). In fact, rural communities account for the highest hantavirus incidences overall and are therefore at higher risk [92, [105] [106] [107] [108] [109] [110] [111] , although the importance of peridomestic settings as a major area of exposure has also been emphasized [112, 113] .
The main mechanism by which humans acquire hantavirus infection is by exposure to aerosols of contaminated rodent feces, urine, and saliva [114, 115] . This can occur when humans reside in areas in close proximity to those that rodents inhabit, live in areas infested with rodents, or when rodents invade human settings, which are more frequent in rural habitats. There is a long history of human co-existence with rodents, raising questions about the apparent recent increases in hantavirus-related illnesses, especially HCPS. Other than an apparent association with El Niño southern oscillation (ENSO) events in some regions [116, 117] , the recent increases in incidence of HCPS do not seem to follow a readily-defined temporal or spatial pattern. However, some landscape features such as habitat fragmentation or human-disturbed areas may influence rodent population dynamics and impact viral incidence [118] [119] [120] [121] . Despite the stochasticity associated with contraction of hantavirus infection, certain scenarios have been recognized as posing higher risk. Human activities in poorly ventilated buildings that aerosolize particulates that are then inhaled (i.e., cleaning, shaking rugs, dusting) are frequently identified among patients admitted for HCPS [11, 122] . Outdoor activities are thought to convey lower risk due to lability of hantaviruses to UV radiation and the presumed tendency to be dispersed in wind, although certain environmental conditions seem to maintain the virus for longer periods outside its natural host allowing for indirect transmission [123] . An alternative but uncommon route of virus transmission is by rodent bites [124] [125] [126] . Field workers handling mammals are potentially at higher risk of exposure with hantavirus infections, although when quantified through serosurveys the absolute risk appears rather slight [127] . A new study in Colorado suggests the possibility that a rodent bite may have been the proximate vehicle for outdoor transmission of SNV [128] , which re-emphasizes the use of personal protective equipment during field work activities [129] . As a particular case within hantaviruses, person-to-person transmission has exclusively been documented for the South American Andes virus [130] [131] [132] [133] [134] [135] . The identification of this transmission route has been made using both molecular tools and epidemiological surveys, but the mechanism of interpersonal transmission is not well established. Recent findings show that family clusters and specifically sexual partners share the greater risk of interpersonal transmission, although sexual transmission per se can be neither inferred nor refuted presently [130, 135] . Interestingly, ANDV may also be shed by humans through other biological fluids such as urine [136] , illustrating the particular properties that differentiate this virus from other hantaviruses. Although interpersonal transmission seems to be unique for ANDV, viral RNA of PUUV has been detected in saliva of patients with HFRS, and some patients with SNV-HCPS have viral RNA in tracheal secretions [88, 137] .
Hantaviruses in the Americas are naturally hosted by rodents (Muridae and Cricetidae) as well as shrews (Soricidae) and moles (Talpidae) (Figure 1) . Three shrew and one mole species have been reported to host hantaviruses and their pathogenicity for humans remains unknown [22, 138, 139] . At least 15 rodent species have been identified as carriers of different pathogenic hantaviruses, with some South American genotypes such as Castelo do Sonhos (CDSV) or Hu39694 only identified after human infections (Figure 1 ). Hantaviruses typically show high species-specificity and no intermediate host [140] . However, some hantavirus genotypes have been described in the same rodent species. Such is the case of Playa de Oro (OROV) and Catacamas (CATV) identified in Oryzomys couesi [141, 142] , or Maporal (MAPV) and Choclo (CHOV) hosted by O. fulvescens [91, 143] . In North America both Muleshoe and Black Creek Canal hantaviruses have been detected in geographically-distant Sigmodon hispidus [144, 145] . Also, one hantavirus genotype (e.g., Juquitiba-like virus) may be carried by more than one rodent species (O. nigripes, Oxymycterus judex, Akodon montesis). Another example is Laguna Negra virus (LANV) which after being identified in Calomys laucha [146] has also been reported in C. callosus [147] . The rapid increase in the discovery of new hantaviruses and the identification of their hosts does not seem likely to end soon as new small mammal species are screened [95] . This subject is complicated by continued controversy in the criteria for the classification of distinct hantaviruses [148, 149] , which is also tied to host taxonomic classification and taxonomic rearrangements.
Cross-species transmission is a major process during spread, emergence, and evolution of RNA viruses [6, 150] . Particularly within hantaviruses, spillover to secondary hosts are increasingly identified as more extensive studies are performed [151] [152] [153] [154] [155] [156] . For example, ANDV is the predominant etiologic agent of HCPS in South America, and O. longicaudatus the main rodent reservoir. Spillover in at least four other rodent species that co-occur with the reservoir have been identified, with Abrothrix longipilis showing the second higher prevalence to ANDV-antibodies, and there is presently no question that the virus is extremely similar genetically between the two host rodents [157, 158] . In North America, spillover of Bayou virus (BAYV) may have occurred from the main reservoir O. palustris to S. hispidus, R. fulvescens, P. leucopus, and B. taylori [159] [160] [161] . Hantavirus spillover is more likely to occur with host populations inhabiting sympatric or syntopic regions [151, 162] , and cross-species transmission would presumably have greater chances of success if the host species are closely related [163] . An interesting exception is found between Oxbow virus (OXBV) and Asama virus (ASAV) in which a host-switch process seemed to have occurred between mammals belonging to two families (Talpidae and Soricidae), likely as a result of alternating and recurrent co-divergence of certain taxa through evolutionary time [138] .
Hantaviruses are horizontally transmitted between rodents and are not transmitted by arthropods (unlike other viruses of the family Bunyaviridae). Spillover infection to nonhuman mammals usually results in no onward (or -dead-end‖) transmission, but if humans are infected may result in high morbidity and mortality [122, 164] . During the spring of 1993, an outbreak of patients with HCPS due to SNV occurred in the Four Corners states resulting in more than 60% case-fatality among the initial cases, many involving members of the Navajo tribe [12, 121] . In Panama, an outbreak was reported during 1999-2000 in Los Santos, and 12 cases where identified with three fatalities [165, 166] . This represented the first report of human hantavirus infections in Central America. In South America, the first largest identified outbreak occurred in the Chaco region in northwestern Paraguay during 1995-1996. Seventeen individuals were identified with SNV antibody (ELISA) or were antigen (IHC) positive out of 52 suspected cases [167] . Major outbreaks due to ANDV occurred in 1996 in southern Argentina [131, 134] ; in southern Chile clusters of patients presented with hantavirus illness in 1997 [158] . In Brazil, the first outbreak was identified in the Brazilian Amazon (Maranhão State) in 2000, and involved small villages that resulted in a 13.3% prevalence of those tested (398 total residents) [168] .
The factors that trigger hantavirus outbreaks are still poorly understood, probably because they result from several interacting biotic and abiotic features whose key parameters are difficult to model. However, the use of new modeling approaches that involve geographical and environmental features seem to be promising in predicting potential hantavirus outbreaks and/or areas of higher risk [169] [170] [171] [172] . Because hantaviruses are known to be directly transmitted from infected to susceptible hosts, the first natural approach is to relate outbreaks to the ecology of the viral hosts. Hantavirus transmission and persistence in rodent populations depends on several factors that interact to affect ecological dynamics of the host, which in turn is strongly influenced by the behavioral characteristics of individual rodent species, to landscape structure, and environmental features [173, 174] . Viral transmission depends on contact rates among susceptible hosts, and despite the prevailing notion that a higher density increases encounters and hence secondary infected hosts, contrasting patterns relating rodent population size and virus prevalence can be found [175] . In addition, it has been shown that SNV transmission follows a contact heterogeneity pattern, where individuals in the population have different probability of transmitting the infection [176] . The understanding of viral transmission proves to be far more complex when species other than the main reservoir host are incorporated in the model. In fact, recent studies have shown that higher hosts species diversity is correlated with lower infection prevalence in North America for P. maniculatus [177] , in Central America for O. fulvescens (reservoir of Choclo virus) and Zygodontomys brevicauda (reservoir of Calabazo virus) [178] , and in South America for Akodon montensis (reservoir of Jabora virus) [162] . Contact rates vary according to the spatial distribution of populations and seem to be strongly influenced by landscape structure. For example, SNV prevalence in P. maniculatus was higher in landscapes with a higher level of fragmentation of the preferred habitat [179] . In addition, certain properties of the landscape such as elevation, slope, and land cover seem to be useful in detecting areas with persistent SNV infections, and therefore thought to be refugial areas where the virus can be maintained for years [169] . Changes in the natural environment of reservoir species, such as forest fragmentation and habitat loss, may alter population abundance and distribution and lead to hantavirus outbreaks, as observed in the Azurero Peninsula of Panama [118, 119] . Also, differences in the microhabitat, including overstory cover, may lead to differences in the ecological dynamics within populations and affect the rate of exposure to the virus [180] . Differences in hantavirus infections through contrasting landscapes in the latitudinal span have been found in rodent populations of O. longicaudatus in Chile, suggesting that humans are differentially exposed to the virus [107, 181] .
Rodent population dynamics are affected by seasonal changes of weather and climate [182, 183] . In the case of the ENSO-associated outbreaks, a complex cascade of events triggered by highly unusual rains in the precedent year have been postulated to result in an increase of primary production and rodent densities, also increasing the likelihood of transmission of the virus to humans, but it has proved difficult to precisely demonstrate the suggested intermediate events such as increased rodent densities in the increased caseload [116, 121, 184] . In South America, effects of climate change and hantavirus outbreaks have not been well studied, despite the knowledge that several rodents species that are reservoirs of emerging diseases have dramatically been affected by events like El Niño [185] . Changes in host population dynamics are also affected by seasonality, which may lead to disease outbreaks when processes that equilibrate rodent populations from season to season are interrupted [186] .
Viral emergence may continue to be promoted as human-introduced changes continue to increase in the environment at different geographical scales. Human incursions into previously uncultivated environments may lead to new contacts between rodent reservoirs and humans, increasing the likelihood of contracting infections [187] . These changes may also alter rodent's population structure and dynamics and interspecies interactions creating conditions that may lead to viral outbreaks, viral establishment in new hosts, and emergence of HCPS [102, 162] , even with seemingly slight ecological disturbance to the virus-host system [188] .
Certain pathophysiologic characteristics, including thrombocytopenia and shock, of hantavirus diseases of humans, bear substantial similarity to the hemorrhagic fevers induced by other viruses such arenaviruses, filoviruses and flaviviruses, despite sharing essentially no sequence similarities therewith. Such observations raise questions about whether such commonalities in pathogenesis are chance similarities of phenotype, or instead report the presence of common molecular mechanisms among the viruses.
In this review we discuss the general properties, discoveries and epidemiology/ecology of the New World forms of pathogenic hantaviruses, and also seek to identify some of the characteristics of the viral macromolecules and immunologic mechanisms that have been proposed as potential direct mediators of the pathogenic events that characterize the human disease HCPS. While it is unlikely that expression of any particular viral protein or RNAs in isolation can be relied upon to replicate key phenotypes of infection by the complete virus, some of the findings have been sufficiently consistent with what is known of the pathogenesis in vivo that they offer plausible first-pass leads in the search for therapeutic targets. We look forward to the mechanistic revelations that will follow the inevitably expanded usage of powerful methods such as deep sequencing, ever-more advanced imaging, and microscopic methods, and animal models that can at last be said to be close mimics of human hantavirus disease. | What have hantaviruses been identified as adversely affect? | false | 4,492 | {
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2,684 | 1918 Influenza: the Mother of All Pandemics
Jeffery K. Taubenberger" and David M. Morens1-
The “Spanish" influenza pandemic of 1918—1919,
which caused :50 million deaths worldwide, remains an
ominous warning to public health. Many questions about its
origins, its unusual epidemiologic features, and the basis of
its pathogenicity remain unanswered. The public health
implications of the pandemic therefore remain in doubt
even as we now grapple with the feared emergence of a
pandemic caused by H5N1 or other virus. However, new
information about the 1918 virus is emerging, for example,
sequencing of the entire genome from archival autopsy tis-
sues. But, the viral genome alone is unlikely to provide
answers to some critical questions. Understanding the
1918 pandemic and its implications for future pandemics
requires careful experimentation and in-depth historical
analysis.
”Curiouser and curiouser/ ” criedAlice
Lewis Carroll, Alice’s Adventures in Wonderland, 1865
An estimated one third of the world’s population (or
z500 million persons) were infected and had clinical-
ly apparent illnesses (1,2) during the 191871919 influenza
pandemic. The disease was exceptionally severe. Case-
fatality rates were >2.5%, compared to <0.1% in other
influenza pandemics (3,4). Total deaths were estimated at
z50 million (577) and were arguably as high as 100 mil-
lion (7).
The impact of this pandemic was not limited to
191871919. All influenza A pandemics since that time, and
indeed almost all cases of influenza A worldwide (except-
ing human infections from avian Viruses such as H5N1 and
H7N7), have been caused by descendants of the 1918
Virus, including “drifted” H1N1 Viruses and reassorted
H2N2 and H3N2 Viruses. The latter are composed of key
genes from the 1918 Virus, updated by subsequently-incor—
porated avian influenza genes that code for novel surface
*Armed Forces Institute of Pathology, Rockville, Maryland, USA;
and TNational Institutes of Health, Bethesda, Maryland, USA
proteins, making the 1918 Virus indeed the “mother” of all
pandemics.
In 1918, the cause of human influenza and its links to
avian and swine influenza were unknown. Despite clinical
and epidemiologic similarities to influenza pandemics of
1889, 1847, and even earlier, many questioned whether
such an explosively fatal disease could be influenza at all.
That question did not begin to be resolved until the 1930s,
when closely related influenza Viruses (now known to be
H1N1 Viruses) were isolated, first from pigs and shortly
thereafter from humans. Seroepidemiologic studies soon
linked both of these viruses to the 1918 pandemic (8).
Subsequent research indicates that descendants of the 1918
Virus still persists enzootically in pigs. They probably also
circulated continuously in humans, undergoing gradual
antigenic drift and causing annual epidemics, until the
1950s. With the appearance of a new H2N2 pandemic
strain in 1957 (“Asian flu”), the direct H1N1 Viral descen-
dants 0f the 1918 pandemic strain disappeared from human
circulation entirely, although the related lineage persisted
enzootically in pigs. But in 1977, human H1N1 Viruses
suddenly “reemerged” from a laboratory freezer (9). They
continue to circulate endemically and epidemically.
Thus in 2006, 2 major descendant lineages of the 1918
H1N1 Virus, as well as 2 additional reassortant lineages,
persist naturally: a human epidemic/endemic H1N1 line-
age, a porcine enzootic H1N1 lineage (so-called classic
swine flu), and the reassorted human H3N2 Virus lineage,
which like the human H1N1 Virus, has led to a porcine
H3N2 lineage. None of these Viral descendants, however,
approaches the pathogenicity of the 1918 parent Virus.
Apparently, the porcine H1N1 and H3N2 lineages uncom-
monly infect humans, and the human H1N1 and H3N2 lin-
eages have both been associated with substantially lower
rates ofillness and death than the virus of 1918. In fact, cur-
rent H1N1 death rates are even lower than those for H3N2
lineage strains (prevalent from 1968 until the present).
H1N1 Viruses descended from the 1918 strain, as well as
H3N2 Viruses, have now been cocirculating worldwide for
29 years and show little evidence of imminent extinction.
Trying To Understand What Happened
By the early 1990s, 75 years of research had failed to
answer a most basic question about the 1918 pandemic:
why was it so fatal? No Virus from 1918 had been isolated,
but all of its apparent descendants caused substantially
milder human disease. Moreover, examination of mortality
data from the 1920s suggests that within a few years after
1918, influenza epidemics had settled into a pattern of
annual epidemicity associated with strain drifting and sub-
stantially lowered death rates. Did some critical Viral genet-
ic event produce a 1918 Virus of remarkable pathogenicity
and then another critical genetic event occur soon after the
1918 pandemic to produce an attenuated H1N1 Virus?
In 1995, a scientific team identified archival influenza
autopsy materials collected in the autumn of 1918 and
began the slow process of sequencing small Viral RNA
fragments to determine the genomic structure of the
causative influenza Virus (10). These efforts have now
determined the complete genomic sequence of 1 Virus and
partial sequences from 4 others. The primary data from the
above studies (11717) and a number of reviews covering
different aspects of the 1918 pandemic have recently been
published ([8720) and confirm that the 1918 Virus is the
likely ancestor of all 4 of the human and swine H1N1 and
H3N2 lineages, as well as the “extinct” H2N2 lineage. No
known mutations correlated with high pathogenicity in
other human or animal influenza Viruses have been found
in the 1918 genome, but ongoing studies to map Virulence
factors are yielding interesting results. The 1918 sequence
data, however, leave unanswered questions about the ori-
gin of the Virus (19) and about the epidemiology of the
pandemic.
When and Where Did the 1918 Influenza
Pandemic Arise?
Before and after 1918, most influenza pandemics
developed in Asia and spread from there to the rest of the
world. Confounding definite assignment of a geographic
point of origin, the 1918 pandemic spread more or less
simultaneously in 3 distinct waves during an z12-month
period in 191871919, in Europe, Asia, and North America
(the first wave was best described in the United States in
March 1918). Historical and epidemiologic data are inade-
quate to identify the geographic origin of the Virus (21),
and recent phylogenetic analysis of the 1918 Viral genome
does not place the Virus in any geographic context ([9).
Although in 1918 influenza was not a nationally
reportable disease and diagnostic criteria for influenza and
pneumonia were vague, death rates from influenza and
pneumonia in the United States had risen sharply in 1915
and 1916 because of a major respiratory disease epidemic
beginning in December 1915 (22). Death rates then dipped
slightly in 1917. The first pandemic influenza wave
appeared in the spring of 1918, followed in rapid succes-
sion by much more fatal second and third waves in the fall
and winter of 191871919, respectively (Figure 1). Is it pos-
sible that a poorly-adapted H1N1 Virus was already begin-
ning to spread in 1915, causing some serious illnesses but
not yet sufficiently fit to initiate a pandemic? Data consis-
tent with this possibility were reported at the time from
European military camps (23), but a counter argument is
that if a strain with a new hemagglutinin (HA) was caus-
ing enough illness to affect the US national death rates
from pneumonia and influenza, it should have caused a
pandemic sooner, and when it eventually did, in 1918,
many people should have been immune or at least partial-
ly immunoprotected. “Herald” events in 1915, 1916, and
possibly even in early 1918, if they occurred, would be dif-
ficult to identify.
The 1918 influenza pandemic had another unique fea-
ture, the simultaneous (or nearly simultaneous) infection
of humans and swine. The Virus of the 1918 pandemic like-
ly expressed an antigenically novel subtype to which most
humans and swine were immunologically naive in 1918
(12,20). Recently published sequence and phylogenetic
analyses suggest that the genes encoding the HA and neu-
raminidase (NA) surface proteins of the 1918 Virus were
derived from an avianlike influenza Virus shortly before
the start of the pandemic and that the precursor Virus had
not circulated widely in humans or swine in the few
decades before (12,15, 24). More recent analyses of the
other gene segments of the Virus also support this conclu-
sion. Regression analyses of human and swine influenza
sequences obtained from 1930 to the present place the ini-
tial circulation of the 1918 precursor Virus in humans at
approximately 191571918 (20). Thus, the precursor was
probably not circulating widely in humans until shortly
before 1918, nor did it appear to have jumped directly
from any species of bird studied to date (19). In summary,
its origin remains puzzling.
Were the 3 Waves in 1918—1 919 Caused
by the Same Virus? If So, How and Why?
Historical records since the 16th century suggest that
new influenza pandemics may appear at any time of year,
not necessarily in the familiar annual winter patterns of
interpandemic years, presumably because newly shifted
influenza Viruses behave differently when they find a uni-
versal or highly susceptible human population. Thereafter,
confronted by the selection pressures of population immu-
nity, these pandemic Viruses begin to drift genetically and
eventually settle into a pattern of annual epidemic recur-
rences caused by the drifted Virus variants.
Figure 1. Three pandemic waves: weekly combined influenza and
pneumonia mortality, United Kingdom, 1918—1919 (21).
In the 1918-1919 pandemic, a first or spring wave
began in March 1918 and spread unevenly through the
United States, Europe, and possibly Asia over the next 6
months (Figure 1). Illness rates were high, but death rates
in most locales were not appreciably above normal. A sec-
ond or fall wave spread globally from September to
November 1918 and was highly fatal. In many nations, a
third wave occurred in early 1919 (21). Clinical similari-
ties led contemporary observers to conclude initially that
they were observing the same disease in the successive
waves. The milder forms of illness in all 3 waves were
identical and typical of influenza seen in the 1889 pandem-
ic and in prior interpandemic years. In retrospect, even the
rapid progressions from uncomplicated influenza infec-
tions to fatal pneumonia, a hallmark of the 191871919 fall
and winter waves, had been noted in the relatively few
severe spring wave cases. The differences between the
waves thus seemed to be primarily in the much higher fre-
quency of complicated, severe, and fatal cases in the last 2
waves.
But 3 extensive pandemic waves of influenza within 1
year, occurring in rapid succession, with only the briefest
of quiescent intervals between them, was unprecedented.
The occurrence, and to some extent the severity, of recur-
rent annual outbreaks, are driven by Viral antigenic drift,
with an antigenic variant Virus emerging to become domi-
nant approximately every 2 to 3 years. Without such drift,
circulating human influenza Viruses would presumably
disappear once herd immunity had reached a critical
threshold at which further Virus spread was sufficiently
limited. The timing and spacing of influenza epidemics in
interpandemic years have been subjects of speculation for
decades. Factors believed to be responsible include partial
herd immunity limiting Virus spread in all but the most
favorable circumstances, which include lower environ-
mental temperatures and human nasal temperatures (bene-
ficial to thermolabile Viruses such as influenza), optimal
humidity, increased crowding indoors, and imperfect ven-
tilation due to closed windows and suboptimal airflow.
However, such factors cannot explain the 3 pandemic
waves of 1918-1919, which occurred in the spring-sum-
mer, summer—fall, and winter (of the Northern
Hemisphere), respectively. The first 2 waves occurred at a
time of year normally unfavorable to influenza Virus
spread. The second wave caused simultaneous outbreaks
in the Northern and Southern Hemispheres from
September to November. Furthermore, the interwave peri-
ods were so brief as to be almost undetectable in some
locales. Reconciling epidemiologically the steep drop in
cases in the first and second waves with the sharp rises in
cases of the second and third waves is difficult. Assuming
even transient postinfection immunity, how could suscep-
tible persons be too few to sustain transmission at 1 point,
and yet enough to start a new explosive pandemic wave a
few weeks later? Could the Virus have mutated profoundly
and almost simultaneously around the world, in the short
periods between the successive waves? Acquiring Viral
drift sufficient to produce new influenza strains capable of
escaping population immunity is believed to take years of
global circulation, not weeks of local circulation. And hav-
ing occurred, such mutated Viruses normally take months
to spread around the world.
At the beginning of other “off season” influenza pan-
demics, successive distinct waves within a year have not
been reported. The 1889 pandemic, for example, began in
the late spring of 1889 and took several months to spread
throughout the world, peaking in northern Europe and the
United States late in 1889 or early in 1890. The second
recurrence peaked in late spring 1891 (more than a year
after the first pandemic appearance) and the third in early
1892 (21 ). As was true for the 1918 pandemic, the second
1891 recurrence produced of the most deaths. The 3 recur-
rences in 1889-1892, however, were spread over >3 years,
in contrast to 191871919, when the sequential waves seen
in individual countries were typically compressed into
z879 months.
What gave the 1918 Virus the unprecedented ability to
generate rapidly successive pandemic waves is unclear.
Because the only 1918 pandemic Virus samples we have
yet identified are from second-wave patients ([6), nothing
can yet be said about whether the first (spring) wave, or for
that matter, the third wave, represented circulation of the
same Virus or variants of it. Data from 1918 suggest that
persons infected in the second wave may have been pro-
tected from influenza in the third wave. But the few data
bearing on protection during the second and third waves
after infection in the first wave are inconclusive and do lit-
tle to resolve the question of whether the first wave was
caused by the same Virus or whether major genetic evolu-
tionary events were occurring even as the pandemic
exploded and progressed. Only influenza RNAipositive
human samples from before 1918, and from all 3 waves,
can answer this question.
What Was the Animal Host
Origin of the Pandemic Virus?
Viral sequence data now suggest that the entire 1918
Virus was novel to humans in, or shortly before, 1918, and
that it thus was not a reassortant Virus produced from old
existing strains that acquired 1 or more new genes, such as
those causing the 1957 and 1968 pandemics. On the con-
trary, the 1918 Virus appears to be an avianlike influenza
Virus derived in toto from an unknown source (17,19), as
its 8 genome segments are substantially different from
contemporary avian influenza genes. Influenza Virus gene
sequences from a number offixed specimens ofwild birds
collected circa 1918 show little difference from avian
Viruses isolated today, indicating that avian Viruses likely
undergo little antigenic change in their natural hosts even
over long periods (24,25).
For example, the 1918 nucleoprotein (NP) gene
sequence is similar to that ofviruses found in wild birds at
the amino acid level but very divergent at the nucleotide
level, which suggests considerable evolutionary distance
between the sources of the 1918 NP and of currently
sequenced NP genes in wild bird strains (13,19). One way
of looking at the evolutionary distance of genes is to com-
pare ratios of synonymous to nonsynonymous nucleotide
substitutions. A synonymous substitution represents a
silent change, a nucleotide change in a codon that does not
result in an amino acid replacement. A nonsynonymous
substitution is a nucleotide change in a codon that results
in an amino acid replacement. Generally, a Viral gene sub-
jected to immunologic drift pressure or adapting to a new
host exhibits a greater percentage of nonsynonymous
mutations, while a Virus under little selective pressure
accumulates mainly synonymous changes. Since little or
no selection pressure is exerted on synonymous changes,
they are thought to reflect evolutionary distance.
Because the 1918 gene segments have more synony-
mous changes from known sequences of wild bird strains
than expected, they are unlikely to have emerged directly
from an avian influenza Virus similar to those that have
been sequenced so far. This is especially apparent when
one examines the differences at 4-fold degenerate codons,
the subset of synonymous changes in which, at the third
codon position, any of the 4 possible nucleotides can be
substituted without changing the resulting amino acid. At
the same time, the 1918 sequences have too few amino acid
difierences from those of wild-bird strains to have spent
many years adapting only in a human or swine intermedi-
ate host. One possible explanation is that these unusual
gene segments were acquired from a reservoir of influenza
Virus that has not yet been identified or sampled. All of
these findings beg the question: where did the 1918 Virus
come from?
In contrast to the genetic makeup of the 1918 pandem-
ic Virus, the novel gene segments of the reassorted 1957
and 1968 pandemic Viruses all originated in Eurasian avian
Viruses (26); both human Viruses arose by the same mech-
anismireassortment of a Eurasian wild waterfowl strain
with the previously circulating human H1N1 strain.
Proving the hypothesis that the Virus responsible for the
1918 pandemic had a markedly different origin requires
samples of human influenza strains circulating before
1918 and samples of influenza strains in the wild that more
closely resemble the 1918 sequences.
What Was the Biological Basis for
1918 Pandemic Virus Pathogenicity?
Sequence analysis alone does not ofier clues to the
pathogenicity of the 1918 Virus. A series of experiments
are under way to model Virulence in Vitro and in animal
models by using Viral constructs containing 1918 genes
produced by reverse genetics.
Influenza Virus infection requires binding of the HA
protein to sialic acid receptors on host cell surface. The HA
receptor-binding site configuration is different for those
influenza Viruses adapted to infect birds and those adapted
to infect humans. Influenza Virus strains adapted to birds
preferentially bind sialic acid receptors with 01 (273) linked
sugars (27729). Human-adapted influenza Viruses are
thought to preferentially bind receptors with 01 (2%) link-
ages. The switch from this avian receptor configuration
requires of the Virus only 1 amino acid change (30), and
the HAs of all 5 sequenced 1918 Viruses have this change,
which suggests that it could be a critical step in human host
adaptation. A second change that greatly augments Virus
binding to the human receptor may also occur, but only 3
of5 1918 HA sequences have it (16).
This means that at least 2 H1N1 receptor-binding vari-
ants cocirculated in 1918: 1 with high—affinity binding to
the human receptor and 1 with mixed-affinity binding to
both avian and human receptors. No geographic or chrono-
logic indication eXists to suggest that one of these variants
was the precursor of the other, nor are there consistent dif-
ferences between the case histories or histopathologic fea-
tures of the 5 patients infected with them. Whether the
Viruses were equally transmissible in 1918, whether they
had identical patterns of replication in the respiratory tree,
and whether one or both also circulated in the first and
third pandemic waves, are unknown.
In a series of in Vivo experiments, recombinant influen-
za Viruses containing between 1 and 5 gene segments of
the 1918 Virus have been produced. Those constructs
bearing the 1918 HA and NA are all highly pathogenic in
mice (31). Furthermore, expression microarray analysis
performed on whole lung tissue of mice infected with the
1918 HA/NA recombinant showed increased upregulation
of genes involved in apoptosis, tissue injury, and oxidative
damage (32). These findings are unexpected because the
Viruses with the 1918 genes had not been adapted to mice;
control experiments in which mice were infected with
modern human Viruses showed little disease and limited
Viral replication. The lungs of animals infected with the
1918 HA/NA construct showed bronchial and alveolar
epithelial necrosis and a marked inflammatory infiltrate,
which suggests that the 1918 HA (and possibly the NA)
contain Virulence factors for mice. The Viral genotypic
basis of this pathogenicity is not yet mapped. Whether
pathogenicity in mice effectively models pathogenicity in
humans is unclear. The potential role of the other 1918 pro-
teins, singularly and in combination, is also unknown.
Experiments to map further the genetic basis of Virulence
of the 1918 Virus in various animal models are planned.
These experiments may help define the Viral component to
the unusual pathogenicity of the 1918 Virus but cannot
address whether specific host factors in 1918 accounted for
unique influenza mortality patterns.
Why Did the 1918 Virus Kill So Many Healthy
Young Ad ults?
The curve of influenza deaths by age at death has histor-
ically, for at least 150 years, been U-shaped (Figure 2),
exhibiting mortality peaks in the very young and the very
old, with a comparatively low frequency of deaths at all
ages in between. In contrast, age-specific death rates in the
1918 pandemic exhibited a distinct pattern that has not been
documented before or since: a “W—shaped” curve, similar to
the familiar U-shaped curve but with the addition of a third
(middle) distinct peak of deaths in young adults z20410
years of age. Influenza and pneumonia death rates for those
1534 years of age in 191871919, for example, were
20 times higher than in previous years (35). Overall, near-
ly half of the influenza—related deaths in the 1918 pandem-
ic were in young adults 20410 years of age, a phenomenon
unique to that pandemic year. The 1918 pandemic is also
unique among influenza pandemics in that absolute risk of
influenza death was higher in those <65 years of age than in
those >65; persons <65 years of age accounted for >99% of
all excess influenza—related deaths in 191871919. In com-
parison, the <65-year age group accounted for 36% of all
excess influenza—related deaths in the 1957 H2N2 pandem-
ic and 48% in the 1968 H3N2 pandemic (33).
A sharper perspective emerges when 1918 age-specific
influenza morbidity rates (21) are used to adj ust the W-
shaped mortality curve (Figure 3, panels, A, B, and C
[35,37]). Persons 65 years of age in 1918 had a dispro-
portionately high influenza incidence (Figure 3, panel A).
But even after adjusting age-specific deaths by age-specif—
ic clinical attack rates (Figure 3, panel B), a W—shaped
curve with a case-fatality peak in young adults remains and
is significantly different from U-shaped age-specific case-
fatality curves typically seen in other influenza years, e.g.,
192871929 (Figure 3, panel C). Also, in 1918 those 5 to 14
years of age accounted for a disproportionate number of
influenza cases, but had a much lower death rate from
influenza and pneumonia than other age groups. To explain
this pattern, we must look beyond properties of the Virus to
host and environmental factors, possibly including
immunopathology (e.g., antibody-dependent infection
enhancement associated with prior Virus exposures [38])
and exposure to risk cofactors such as coinfecting agents,
medications, and environmental agents.
One theory that may partially explain these findings is
that the 1918 Virus had an intrinsically high Virulence, tem-
pered only in those patients who had been born before
1889, e.g., because of exposure to a then-circulating Virus
capable of providing partial immunoprotection against the
1918 Virus strain only in persons old enough (>35 years) to
have been infected during that prior era (35). But this the-
ory would present an additional paradox: an obscure pre-
cursor Virus that left no detectable trace today would have
had to have appeared and disappeared before 1889 and
then reappeared more than 3 decades later.
Epidemiologic data on rates of clinical influenza by
age, collected between 1900 and 1918, provide good evi-
dence for the emergence of an antigenically novel influen-
za Virus in 1918 (21). Jordan showed that from 1900 to
1917, the 5- to 15-year age group accounted for 11% of
total influenza cases, while the >65-year age group
accounted for 6 % of influenza cases. But in 1918, cases in
Figure 2. “U-” and “W—” shaped combined influenza and pneumo-
nia mortality, by age at death, per 100,000 persons in each age
group, United States, 1911—1918. Influenza- and pneumonia-
specific death rates are plotted for the interpandemic years
1911—1917 (dashed line) and for the pandemic year 1918 (solid
line) (33,34).
Incidence male per 1 .nao persunslage group
Mortality per 1.000 persunslige group
+ Case—fataiity rale 1918—1919
Case fatalily par 100 persons ill wilh P&I pel age group
Figure 3. Influenza plus pneumonia (P&l) (combined) age-specific
incidence rates per 1,000 persons per age group (panel A), death
rates per 1,000 persons, ill and well combined (panel B), and
case-fatality rates (panel C, solid line), US Public Health Service
house-to-house surveys, 8 states, 1918 (36). A more typical curve
of age-specific influenza case-fatality (panel C, dotted line) is
taken from US Public Health Service surveys during 1928—1929
(37).
the 5 to 15-year-old group jumped to 25% of influenza
cases (compatible with exposure to an antigenically novel
Virus strain), while the >65-year age group only accounted
for 0.6% of the influenza cases, findings consistent with
previously acquired protective immunity caused by an
identical or closely related Viral protein to which older per-
sons had once been exposed. Mortality data are in accord.
In 1918, persons >75 years had lower influenza and
pneumonia case-fatality rates than they had during the
prepandemic period of 191171917. At the other end of the
age spectrum (Figure 2), a high proportion of deaths in
infancy and early childhood in 1918 mimics the age pat-
tern, if not the mortality rate, of other influenza pandemics.
Could a 1918-like Pandemic Appear Again?
If So, What Could We Do About It?
In its disease course and pathologic features, the 1918
pandemic was different in degree, but not in kind, from
previous and subsequent pandemics. Despite the extraordi-
nary number of global deaths, most influenza cases in
1918 (>95% in most locales in industrialized nations) were
mild and essentially indistinguishable from influenza cases
today. Furthermore, laboratory experiments with recombi-
nant influenza Viruses containing genes from the 1918
Virus suggest that the 1918 and 1918-like Viruses would be
as sensitive as other typical Virus strains to the Food and
Drug Administrationiapproved antiinfluenza drugs riman-
tadine and oseltamivir.
However, some characteristics of the 1918 pandemic
appear unique: most notably, death rates were 5 7 20 times
higher than expected. Clinically and pathologically, these
high death rates appear to be the result of several factors,
including a higher proportion of severe and complicated
infections of the respiratory tract, rather than involvement
of organ systems outside the normal range of the influenza
Virus. Also, the deaths were concentrated in an unusually
young age group. Finally, in 1918, 3 separate recurrences
of influenza followed each other with unusual rapidity,
resulting in 3 explosive pandemic waves within a year’s
time (Figure 1). Each of these unique characteristics may
reflect genetic features of the 1918 Virus, but understand-
ing them will also require examination of host and envi-
ronmental factors.
Until we can ascertain which of these factors gave rise
to the mortality patterns observed and learn more about the
formation of the pandemic, predictions are only educated
guesses. We can only conclude that since it happened once,
analogous conditions could lead to an equally devastating
pandemic.
Like the 1918 Virus, H5N1 is an avian Virus (39),
though a distantly related one. The evolutionary path that
led to pandemic emergence in 1918 is entirely unknown,
but it appears to be different in many respects from the cur-
rent situation with H5N1. There are no historical data,
either in 1918 or in any other pandemic, for establishing
that a pandemic “precursor” Virus caused a highly patho-
genic outbreak in domestic poultry, and no highly patho-
genic avian influenza (HPAI) Virus, including H5N1 and a
number of others, has ever been known to cause a major
human epidemic, let alone a pandemic. While data bearing
on influenza Virus human cell adaptation (e.g., receptor
binding) are beginning to be understood at the molecular
level, the basis for Viral adaptation to efficient human-to-
human spread, the chief prerequisite for pandemic emer-
gence, is unknown for any influenza Virus. The 1918 Virus
acquired this trait, but we do not know how, and we cur-
rently have no way of knowing whether H5N1 Viruses are
now in a parallel process of acquiring human-to-human
transmissibility. Despite an explosion of data on the 1918
Virus during the past decade, we are not much closer to
understanding pandemic emergence in 2006 than we were
in understanding the risk of H1N1 “swine flu” emergence
in 1976.
Even with modern antiviral and antibacterial drugs,
vaccines, and prevention knowledge, the return of a pan-
demic Virus equivalent in pathogenicity to the Virus of
1918 would likely kill >100 million people worldwide. A
pandemic Virus with the (alleged) pathogenic potential of
some recent H5N1 outbreaks could cause substantially
more deaths.
Whether because of Viral, host or environmental fac-
tors, the 1918 Virus causing the first or ‘spring’ wave was
not associated with the exceptional pathogenicity of the
second (fall) and third (winter) waves. Identification of an
influenza RNA-positive case from the first wave could
point to a genetic basis for Virulence by allowing differ-
ences in Viral sequences to be highlighted. Identification of
pre-1918 human influenza RNA samples would help us
understand the timing of emergence of the 1918 Virus.
Surveillance and genomic sequencing of large numbers of
animal influenza Viruses will help us understand the genet-
ic basis of host adaptation and the extent of the natural
reservoir of influenza Viruses. Understanding influenza
pandemics in general requires understanding the 1918 pan-
demic in all its historical, epidemiologic, and biologic
aspects.
Dr Taubenberger is chair of the Department of Molecular
Pathology at the Armed Forces Institute of Pathology, Rockville,
Maryland. His research interests include the molecular patho-
physiology and evolution of influenza Viruses.
Dr Morens is an epidemiologist with a long-standing inter-
est in emerging infectious diseases, Virology, tropical medicine,
and medical history. Since 1999, he has worked at the National
Institute of Allergy and Infectious Diseases.
References
1. Frost WH. Statistics of influenza morbidity. Public Health Rep.
19203558497.
2. Bumet F, Clark E. Influenza: a survey ofthe last 50 years in the light
of modern work on the Virus of epidemic influenza. Melbourne:
MacMillan; 1942.
3. Marks G, Beatty WK. Epidemics. New York: Scribners, 1976.
4. Rosenau MJ, Last JM. Maxcy-Rosenau preventative medicine and
public health. New York: Appleton-Century-Crofts; 1980.
5. Crosby A. America’s forgotten pandemic. Cambridge (UK):
Cambridge University Press;1989.
6. Patterson KD, Pyle GF. The geography and mortality of the 1918
influenza pandemic. Bull Hist Med. 1991;65:4–21.
7. Johnson NPAS, Mueller J. Updating the accounts: global mortality of
the 1918–1920 “Spanish” influenza pandemic. Bull Hist Med
2002;76:105–15.
8. Shope RE. The incidence of neutralizing antibodies for swine
influenza virus in the sera of human beings of different ages. J Exp
Med. 1936;63:669–84.
9. Kendal AP, Noble GR, Skehel JJ, Dowdle WR. Antigenic similarity
of influenza A (H1N1) viruses from epidemics in 1977–1978 to
“Scandinavian” strains isolated in epidemics of 1950–1951. Virology.
1978;89:632–6.
10. Taubenberger JK, Reid AH, Krafft AE, Bijwaard KE, Fanning TG.
Initial genetic characterization of the 1918 “Spanish” influenza virus.
Science. 1997;275:1793–6.
11. Basler CF, Reid AH, Dybing JK, Janczewski TA, Fanning TG, Zheng
H, et al. Sequence of the 1918 pandemic influenza virus nonstructural gene (NS) segment and characterization of recombinant viruses
bearing the 1918 NS genes. Proc Natl Acad Sci U S A
2001;98:2746–51.
12. Reid AH, Fanning TG, Hultin JV, Taubenberger JK. Origin and evolution of the 1918 “Spanish” influenza virus hemagglutinin gene.
Proc Natl Acad Sci U S A 1999;96:1651–6.
13. Reid AH, Fanning TG, Janczewski TA, Lourens RM, and
Taubenberger JK. Novel origin of the 1918 pandemic influenza virus
nucleoprotein gene segment. J Virol. 2004;78:12462–70.
14. Reid AH, Fanning TG, Janczewski TA, McCall S, Taubenberger JK.
Characterization of the 1918 “Spanish” influenza virus matrix gene
segment. J Virol. 2002;76:10717–23.
15. Reid AH, Fanning TG, Janczewski TA, Taubenberger JK.
Characterization of the 1918 “Spanish” influenza virus neuraminidase gene. Proc Natl Acad Sci U S A 2000;97:6785–90.
16. Reid AH, Janczewski TA, Lourens RM, Elliot AJ, Daniels RS, Berry
CL, et al. 1918 influenza pandemic caused by highly conserved viruses with two receptor-binding variants. Emerg Infect Dis.
2003;9:1249–53.
17. Taubenberger JK, Reid AH, Lourens RM, Wang R, Jin G, Fanning
TG. Characterization of the 1918 influenza virus polymerase genes.
Nature. 2005;437:889–93.
18. Reid AH, Taubenberger JK. The 1918 flu and other influenza pandemics: “over there” and back again. Lab Invest. 1999;79:95–101.
19. Reid AH, Taubenberger JK, Fanning TG. Evidence of an absence: the
genetic origins of the 1918 pandemic influenza virus. Nat Rev
Microbiol. 2004;2:909–14.
20. Taubenberger JK, Reid AH, Fanning TG. The 1918 influenza virus: a
killer comes into view. Virology. 2000;274:241–5.
21. Jordan E. Epidemic influenza: a survey. Chicago: American Medical
Association, 1927.
22. Capps J, Moody A. The recent epidemic of grip. JAMA.
1916;67:1349–50.
33. Oxford JS, Sefton A, Jackson R, Innes W, Daniels RS, Johnson NP.
World War I may have allowed the emergence of “Spanish” influenza. Lancet Infect Dis. 2002;2:111–4.
24. Fanning TG, Slemons RD, Reid AH, Janczewski TA, Dean J,
Taubenberger JK. 1917 avian influenza virus sequences suggest that
the 1918 pandemic virus did not acquire its hemagglutinin directly
from birds. J Virol. 2002;76:7860–2.
25. Reid AH, Fanning TG, Slemons RD, Janczewski TA, Dean J,
Taubenberger JK. Relationship of pre-1918 avian influenza HA and
NP sequences to subsequent avian influenza strains. Avian Dis.
2003;47:921–5.
26. Bean W, Schell M, Katz J, Kawaoka Y, Naeve C, Gorman O, et al.
Evolution of the H3 influenza virus hemagglutinin from human and
nonhuman hosts. J Virol. 1992;66:1129–38.
27. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, Wiley DC.
Structure of the influenza virus haemagglutinin complexed with its
receptor, sialic acid. Nature. 1988;333:426–31.
28. Gambaryan AS, Tuzikov AB, Piskarev VE, Yamnikova SS, Lvov DK,
Robertson JS, et al. Specification of receptor-binding phenotypes of
influenza virus isolates from different hosts using synthetic sialylglycopolymers: non-egg-adapted human H1 and H3 influenza A and
influenza B viruses share a common high binding affinity for 6′-sialyl(N-acetyllactosamine). Virology. 1997;232: 345–50.
29. Matrosovich M, Gambaryan A, Teneberg S, Piskarev VE, Yamnikova
SS, Lvov DK, et al. Avian influenza A viruses differ from human
viruses by recognition of sialyloigosaccharides and gangliosides and
by a higher conservation of the HA receptor-binding site. Virology.
1997;233:224–34.
30. Glaser L, Stevens J, Zamarin D, Wilson IA, Garcia-Sastre A, Tumpey
TM, et al. A single amino acid substitution in the 1918 influenza virus
hemagglutinin changes the receptor binding specificity. J Virol.
2005;79:11533–6.
31. Kobasa D, Takada A, Shinya K, Hatta M, Halfmann P, Theriault S, et
al. Enhanced virulence of influenza A viruses with the haemagglutinin of the 1918 pandemic virus. Nature. 2004;431:703–7.
32. Kash JC, Basler CF, Garcia-Sastre A, Carter V, Billharz R, Swayne
DE, et al. Global host immune response: pathogenesis and transcriptional profiling of type A influenza viruses expressing the hemagglutinin and neuraminidase genes from the 1918 pandemic virus. J Virol.
2004;78:9499–511.
33. Grove RD, Hetzel AM. Vital statistics rates in the United States:
1940–1960. Washington: US Government Printing Office, 1968.
34. Linder FE, Grove RD. Vital statistics rates in the United States:
1900–1940. Washington: US Government Printing Office, 1943.
35. Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ,
Fukuda K. Pandemic versus epidemic influenza mortality: a pattern
of changing age distribution. J Infect Dis 1998;178:53–60.
36. Frost WH. The epidemiology of influenza. Public Health Rep.
1919;34:1823–61.
37. Collins SD. Age and sex incidence of influenza and pneumonia morbidity and mortality in the epidemic of 1928-1929 with comparative
data for the epidemic of 1918–1919. Public Health Rep.
1931;46:1909–37.
38. Majde JA. Influenza: Learn from the past. ASM News. 1996;62:514.
39. Peiris JS, Yu WC, Leung CW, Cheung CY, Ng WF, Nicholls JM, et al.
Re-emergence of fatal human influenza A subtype H5N1 disease.
Lancet. 2004;363:617–9.
Address for correspondence: Jeffery K. Taubenberger, Department of
Molecular Pathology, Armed Forces Institute of Pathology, 1413
Research Blvd, Bldg 101, Rm 1057, Rockville, MD 20850-3125, USA;
fax. 301-295-9507; email: [email protected]
The opinions expressed by authors contributing to this journal do
not necessarily reflect the opinions of the Centers for Disease
Control and Prevention or the institutions with which the authors
are affiliated. | Are the descendant H1N1 strains of the 1918 H1N1 swine flu (Spanish Influenza) virus, still prevalent? | false | 1,073 | {
"text": [
"H1N1 Viruses descended from the 1918 strain, as well as \nH3N2 Viruses, have now been cocirculating worldwide for\n29 years and show little evidence of imminent extinction."
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} |
1,674 | Beyond phage display: non-traditional applications of the filamentous bacteriophage as a vaccine carrier, therapeutic biologic, and bioconjugation scaffold
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4523942/
SHA: f00f183d0bce0091a02349ec1eab44a76dad9bc4
Authors: Henry, Kevin A.; Arbabi-Ghahroudi, Mehdi; Scott, Jamie K.
Date: 2015-08-04
DOI: 10.3389/fmicb.2015.00755
License: cc-by
Abstract: For the past 25 years, phage display technology has been an invaluable tool for studies of protein–protein interactions. However, the inherent biological, biochemical, and biophysical properties of filamentous bacteriophage, as well as the ease of its genetic manipulation, also make it an attractive platform outside the traditional phage display canon. This review will focus on the unique properties of the filamentous bacteriophage and highlight its diverse applications in current research. Particular emphases are placed on: (i) the advantages of the phage as a vaccine carrier, including its high immunogenicity, relative antigenic simplicity and ability to activate a range of immune responses, (ii) the phage’s potential as a prophylactic and therapeutic agent for infectious and chronic diseases, (iii) the regularity of the virion major coat protein lattice, which enables a variety of bioconjugation and surface chemistry applications, particularly in nanomaterials, and (iv) the phage’s large population sizes and fast generation times, which make it an excellent model system for directed protein evolution. Despite their ubiquity in the biosphere, metagenomics work is just beginning to explore the ecology of filamentous and non-filamentous phage, and their role in the evolution of bacterial populations. Thus, the filamentous phage represents a robust, inexpensive, and versatile microorganism whose bioengineering applications continue to expand in new directions, although its limitations in some spheres impose obstacles to its widespread adoption and use.
Text: The filamentous bacteriophage (genera Inovirus and Plectrovirus) are non-enveloped, rod-shaped viruses of Escherichia coli whose long helical capsids encapsulate a single-stranded circular DNA genome. Subsequent to the independent discovery of bacteriophage by Twort (1915) and d 'Hérelle (1917) , the first filamentous phage, f1, was isolated in Loeb (1960) and later characterized as a member of a larger group of phage (Ff, including f1, M13, and fd phage) specific for the E. coli conjugative F pilus (Hofschneider and Mueller-Jensen, 1963; Marvin and Hoffmann-Berling, 1963; Zinder et al., 1963; Salivar et al., 1964) . Soon thereafter, filamentous phage were discovered that do not use F-pili for entry (If and Ike; Meynell and Lawn, 1968; Khatoon et al., 1972) , and over time the list of known filamentous phage has expanded to over 60 members (Fauquet et al., 2005) , including temperate and Gram-positivetropic species. Work by multiple groups over the past 50 years has contributed to a relatively sophisticated understanding of filamentous phage structure, biology and life cycle (reviewed in Marvin, 1998; Rakonjac et al., 2011; Rakonjac, 2012) .
In the mid-1980s, the principle of modifying the filamentous phage genome to display polypeptides as fusions to coat proteins on the virion surface was invented by Smith and colleagues (Smith, 1985; Parmley and Smith, 1988) . Based on the ideas described in Parmley and Smith (1988) , groups in California, Germany, and the UK developed phage-display platforms to create and screen libraries of peptide and folded-protein variants (Bass et al., 1990; Devlin et al., 1990; McCafferty et al., 1990; Scott and Smith, 1990; Breitling et al., 1991; Kang et al., 1991) . This technology allowed, for the first time, the ability to seamlessly connect genetic information with protein function for a large number of protein variants simultaneously, and has been widely and productively exploited in studies of proteinprotein interactions. Many excellent reviews are available on phage-display libraries and their applications (Kehoe and Kay, 2005; Bratkovic, 2010; Pande et al., 2010) . However, the phage also has a number of unique structural and biological properties that make it highly useful in areas of research that have received far less attention.
Thus, the purpose of this review is to highlight recent and current work using filamentous phage in novel and nontraditional applications. Specifically, we refer to projects that rely on the filamentous phage as a key element, but whose primary purpose is not the generation or screening of phagedisplayed libraries to obtain binding polypeptide ligands. These tend to fall into four major categories of use: (i) filamentous phage as a vaccine carrier; (ii) engineered filamentous phage as a therapeutic biologic agent in infectious and chronic diseases; (iii) filamentous phage as a scaffold for bioconjugation and surface chemistry; and (iv) filamentous phage as an engine for evolving variants of displayed proteins with novel functions. A final section is dedicated to recent developments in filamentous phage ecology and phage-host interactions. Common themes shared amongst all these applications include the unique biological, immunological, and physicochemical properties of the phage, its ability to display a variety of biomolecules in modular fashion, and its relative simplicity and ease of manipulation.
Nearly all applications of the filamentous phage depend on its ability to display polypeptides on the virion's surface as fusions to phage coat proteins ( Table 1) . The display mode determines the maximum tolerated size of the fused polypeptide, its copy number on the phage, and potentially, the structure of the displayed polypeptide. Display may be achieved by fusing DNA encoding a polypeptide of interest directly to the gene encoding a coat protein within the phage genome (type 8 display on pVIII, type 3 display on pIII, etc.), resulting in fully recombinant phage. Much more commonly, however, only one copy of the coat protein is modified in the presence of a second, wild-type copy (e.g., type 88 display if both recombinant and wild-type pVIII genes are on the phage genome, type 8+8 display if the Parmley and Smith (1988), McConnell et al. (1994) , Rondot et al. (2001) Hybrid (type 33 and 3+3 systems) Type 3+3 system <1 2 Smith and Scott (1993) , Smith and Petrenko (1997) pVI Hybrid (type 6+6 system) Yes <1 2 >25 kDa Hufton et al. (1999) pVII Fully recombinant (type 7 system) No ∼5 >25 kDa Kwasnikowski et al. (2005) Hybrid (type 7+7 system) Yes <1 2 Gao et al. (1999) pVIII Fully recombinant (landscape phage; type 8 system)
No 2700 3 ∼5-8 residues Kishchenko et al. (1994) , Petrenko et al. (1996) Hybrid (type 88 and 8+8 systems) Type 8+8 system ∼1-300 2 >50 kDa Scott and Smith (1990) , Greenwood et al. (1991) , Smith and Fernandez (2004) pIX Fully recombinant (type 9+9 * system) Yes ∼5 >25 kDa Gao et al. (2002) Hybrid (type 9+9 system) No <1 2 Gao et al. (1999) , Shi et al. (2010) , Tornetta et al. (2010) 1 Asterisks indicate non-functional copies of the coat protein are present in the genome of the helper phage used to rescue a phagemid whose coat protein has been fused to a recombinant polypeptide. 2 The copy number depends on polypeptide size; typically <1 copy per phage particle but for pVIII peptide display can be up to ∼15% of pVIII molecules in hybrid virions. 3 The total number of pVIII molecules depends on the phage genome size; one pVIII molecule is added for every 2.3 nucleotides in the viral genome. recombinant gene 8 is on a plasmid with a phage origin of replication) resulting in a hybrid virion bearing two different types of a given coat protein. Multivalent display on some coat proteins can also be enforced using helper phage bearing nonfunctional copies of the relevant coat protein gene (e.g., type 3 * +3 display). By far the most commonly used coat proteins for display are the major coat protein, pVIII, and the minor coat protein, pIII, with the major advantage of the former being higher copy number display (up to ∼15% of recombinant pVIII molecules in a hybrid virion, at least for short peptide fusions), and of the latter being the ability to display some folded proteins at an appreciable copy number (1-5 per phage particle). While pVIII display of folded proteins on hybrid phage is possible, it typically results in a copy number of much less than 1 per virion (Sidhu et al., 2000) . For the purposes of this review, we use the term "phage display" to refer to a recombinant filamentous phage displaying a single polypeptide sequence on its surface (or more rarely, bispecific display achieved via fusion of polypeptides to two different capsid proteins), and the term "phage-displayed library" to refer to a diverse pool of recombinant filamentous phage displaying an array of polypeptide variants (e.g., antibody fragments; peptides). Such libraries are typically screened by iterative cycles of panning against an immobilized protein of interest (e.g., antigen for phage-displayed antibody libraries; antibody for phage-displayed peptide libraries) followed by amplification of the bound phage in E. coli cells.
Early work with anti-phage antisera generated for species classification purposes demonstrated that the filamentous phage virion is highly immunogenic in the absence of adjuvants (Meynell and Lawn, 1968 ) and that only the major coat protein, pVIII, and the minor coat protein, pIII, are targeted by antibodies (Pratt et al., 1969; Woolford et al., 1977) . Thus, the idea of using the phage as carrier to elicit antibodies against poorly immunogenic haptens or polypeptide was a natural extension of the ability to display recombinant exogenous sequences on its surface, which was first demonstrated by de la Cruz et al. (1988) . The phage particle's low cost of production, high stability and potential for high valency display of foreign antigen (via pVIII display) also made it attractive as a vaccine carrier, especially during the early stages of development of recombinant protein technology.
Building upon existing peptide-carrier technology, the first filamentous phage-based vaccine immunogens displayed short amino acid sequences derived directly from proteins of interest as recombinant fusions to pVIII or pIII (de la Cruz et al., 1988) . As library technology was developed and refined, phage-based antigens displaying peptide ligands of monoclonal antibodies (selected from random peptide libraries using the antibody, thus simulating with varying degrees of success the antibody's folded epitope on its cognate antigen; Geysen et al., 1986; Knittelfelder et al., 2009) were also generated for immunization purposes, with the goal of eliciting anti-peptide antibodies that also recognize the native protein. Some of the pioneering work in this area used peptides derived from infectious disease antigens (or peptide ligands of antibodies against these antigens; Table 2) , including malaria and human immunodeficiency virus type 1 (HIV-1). When displayed on phage, peptides encoding the repeat regions of the malarial circumsporozoite protein and merozoite surface protein 1 were immunogenic in mice and rabbits (de la Cruz et al., 1988; Greenwood et al., 1991; Willis et al., 1993; Demangel et al., 1996) , and antibodies raised against the latter cross-reacted with the full-length protein. Various peptide determinants (or mimics thereof) of HIV-1 gp120, gp41, gag, and reverse transcriptase were immunogenic when displayed on or conjugated to phage coat proteins (Minenkova et al., 1993; di Marzo Veronese et al., 1994; De Berardinis et al., 1999; Scala et al., 1999; Chen et al., 2001; van Houten et al., 2006 van Houten et al., , 2010 , and in some cases elicited antibodies that were able to weakly neutralize lab-adapted viruses (di Marzo Veronese et al., 1994; Scala et al., 1999) . The list of animal and human infections for which phage-displayed peptide immunogens have been developed as vaccine leads continues to expand and includes bacterial, fungal, viral, and parasitic pathogens ( Table 2) . While in some cases the results of these studies have been promising, antibody epitope-based peptide vaccines are no longer an area of active research for several reasons: (i) in many cases, peptides incompletely or inadequately mimic epitopes on folded proteins (Irving et al., 2010 ; see below); (ii) antibodies against a single epitope may be of limited utility, especially for highly variable pathogens (Van Regenmortel, 2012); and (iii) for pathogens for which protective immune responses are generated efficiently during natural infection, peptide vaccines offer few advantages over recombinant subunit and live vector vaccines, which have become easier to produce over time.
More recently, peptide-displaying phage have been used in attempts to generate therapeutic antibody responses for chronic diseases, cancer, immunotherapy, and immunocontraception. Immunization with phage displaying Alzheimer's disease β-amyloid fibril peptides elicited anti-aggregating antibodies in mice and guinea pigs (Frenkel et al., 2000 (Frenkel et al., , 2003 Esposito et al., 2008; Tanaka et al., 2011) , possibly reduced amyloid plaque formation in mice (Frenkel et al., 2003; Solomon, 2005; Esposito et al., 2008) , and may have helped maintain cognitive abilities in a transgenic mouse model of Alzheimer's disease (Lavie et al., 2004) ; however, it remains unclear how such antibodies are proposed to cross the blood-brain barrier. Yip et al. (2001) found that antibodies raised in mice against an ERBB2/HER2 peptide could inhibit breast-cancer cell proliferation. Phage displaying peptide ligands of an anti-IgE antibody elicited antibodies that bound purified IgE molecules (Rudolf et al., 1998) , which may be useful in allergy immunotherapy. Several strategies for phage-based contraceptive vaccines have been proposed for control of animal populations. For example, immunization with phage displaying follicle-stimulating hormone peptides on pVIII elicited antibodies that impaired the fertility of mice and ewes (Abdennebi et al., 1999) . Phage displaying or chemically Rubinchik and Chow (2000) conjugated to sperm antigen peptides or peptide mimics (Samoylova et al., 2012a,b) and gonadotropin-releasing hormone (Samoylov et al., 2012) are also in development.
For the most part, peptides displayed on phage elicit antibodies in experimental animals ( Table 2) , although this depends on characteristics of the peptide and the method of its display: pIII fusions tend toward lower immunogenicity than pVIII fusions (Greenwood et al., 1991) possibly due to copy number differences (pIII: 1-5 copies vs. pVIII: estimated at several hundred copies; Malik et al., 1996) . In fact, the phage is at least as immunogenic as traditional carrier proteins such as bovine serum albumin (BSA) and keyhole limpet hemocyanin (KLH; Melzer et al., 2003; Su et al., 2007) , and has comparatively few endogenous B-cell epitopes to divert the antibody response from its intended target (Henry et al., 2011) . Excepting small epitopes that can be accurately represented by a contiguous short amino acid sequence, however, it has been extremely difficult to elicit antibody responses that cross-react with native protein epitopes using peptides. The overall picture is considerably bleaker than that painted by Table 2 , since in several studies either: (i) peptide ligands selected from phage-displayed libraries were classified by the authors as mimics of discontinuous epitopes if they bore no obvious sequence homology to the native protein, which is weak evidence of non-linearity, or (ii) the evidence for cross-reactivity of antibodies elicited by immunization with phage-displayed peptides with native protein was uncompelling. Irving et al. (2010) describe at least one reason for this lack of success: it seems that peptide antigens elicit a set of topologically restricted antibodies that are largely unable to recognize discontinuous or complex epitopes on larger biomolecules. While the peptide may mimic the chemistry of a given epitope on a folded protein (allowing it to crossreact with a targeted antibody), being a smaller molecule, it cannot mimic the topology of that antibody's full epitope.
Despite this, the filamentous phage remains highly useful as a carrier for peptides with relatively simple secondary structures, which may be stablilized via anchoring to the coat proteins (Henry et al., 2011) . This may be especially true of peptides with poor inherent immunogenicity, which may be increased by high-valency display and phage-associated adjuvanticity (see Immunological Mechanisms of Vaccination with Filamentous Phage below).
The filamentous phage has been used to a lesser extent as a carrier for T-cell peptide epitopes, primarily as fusion proteins with pVIII ( Table 3) . Early work, showing that immunization with phage elicited T-cell help (Kölsch et al., 1971; Willis et al., 1993) , was confirmed by several subsequent studies (De Berardinis et al., 1999; Ulivieri et al., 2008) . From the perspective of vaccination against infectious disease, De Berardinis et al. (2000) showed that a cytotoxic T-cell (CTL) epitope from HIV-1 reverse transcriptase could elicit antigen-specific CTLs in vitro and in vivo without addition of exogenous helper T-cell epitopes, presumably since these are already present in the phage coat proteins (Mascolo et al., 2007) . Similarly, efficient priming of CTLs was observed against phage-displayed T-cell epitopes from Hepatitis B virus (Wan et al., 2001) and Candida albicans (Yang et al., 2005a; Wang et al., 2006 Wang et al., , 2014d , which, together with other types of immune responses, protected mice against systemic candidiasis. Vaccination with a combination of phagedisplayed peptides elicited antigen-specific CTLs that proved effective in reducing porcine cysticercosis in a randomized controlled trial (Manoutcharian et al., 2004; Morales et al., 2008) .
While the correlates of vaccine-induced immune protection for infectious diseases, where they are known, are almost exclusively serum or mucosal antibodies (Plotkin, 2010) ,
In certain vaccine applications, the filamentous phage has been used as a carrier for larger molecules that would be immunogenic even in isolation. Initially, the major advantages to phage display of such antigens were speed, ease of purification and low cost of production (Gram et al., 1993) . E. coli F17a-G adhesin (Van Gerven et al., 2008) , hepatitis B core antigen (Bahadir et al., 2011) , and hepatitis B surface antigen (Balcioglu et al., 2014) all elicited antibody responses when displayed on pIII, although none of these studies compared the immunogenicity of the phage-displayed proteins with that of the purified protein alone. Phage displaying Schistosoma mansoni glutathione S-transferase on pIII elicited an antibody response that was both higher in titer and of different isotypes compared to immunization with the protein alone (Rao et al., 2003) . Two studies of antiidiotypic vaccines have used the phage as a carrier for antibody fragments bearing immunogenic idiotypes. Immunization with phage displaying the 1E10 idiotype scFv (mimicking a Vibrio anguillarum surface epitope) elicited antibodies that protected flounder fish from Vibrio anguillarum challenge (Xia et al., 2005) . A chemically linked phage-BCL1 tumor-specific idiotype vaccine was weakly immunogenic in mice but extended survival time in a B-cell lymphoma model (Roehnisch et al., 2013) , and was welltolerated and immunogenic in patients with multiple myeloma (Roehnisch et al., 2014) . One study of DNA vaccination with an anti-laminarin scFv found that DNA encoding a pIII-scFv fusion protein elicited stronger humoral and cell-mediated immune responses than DNA encoding the scFv alone (Cuesta et al., 2006) , suggesting that under some circumstances, endogenous phage T-cell epitopes can enhance the immunogenicity of associated proteins. Taken together, the results of these studies show that as a particulate virus-like particle, the filamentous phage likely triggers different types of immune responses than recombinant protein antigens, and provide additional T-cell help to displayed or conjugated proteins. However, the low copy number of pIII-displayed proteins, as well as potentially unwanted phage-associated adjuvanticity, can make display of recombinant proteins by phage a suboptimal vaccine choice.
Although our understanding of the immune response against the filamentous phage pales in comparison to classical model antigens such as ovalbumin, recent work has begun to shed light on the immune mechanisms activated in response to phage vaccination (Figure 1) . The phage particle is immunogenic without adjuvant in all species tested to date, including mice (Willis et al., 1993) , rats (Dente et al., 1994) , rabbits (de la Cruz et al., 1988) , guinea pigs (Frenkel et al., 2000; Kim et al., 2004) , fish (Coull et al., 1996; Xia et al., 2005) , non-human primates (Chen et al., 2001) , and humans (Roehnisch et al., 2014) . Various routes of immunization have been employed, including oral administration (Delmastro et al., 1997) as well as subcutaneous (Grabowska et al., 2000) , intraperitoneal (van Houten et al., 2006) , intramuscular (Samoylova et al., 2012a) , intravenous (Vaks and Benhar, 2011) , and intradermal injection (Roehnisch et al., 2013) ; no published study has directly compared the effect of administration route on filamentous phage immunogenicity. Antibodies are generated against only three major sites on the virion: (i) the surface-exposed N-terminal ∼12 residues of the pVIII monomer lattice (Terry et al., 1997; Kneissel et al., 1999) ; (ii) the N-terminal N1 and N2 domains of pIII (van Houten et al., 2010) ; and (iii) bacterial lipopolysaccharide (LPS) embedded in the phage coat (Henry et al., 2011) . In mice, serum antibody titers against the phage typically reach 1:10 5 -1:10 6 after 2-3 immunizations, and are maintained for at least 1 year postimmunization (Frenkel et al., 2000) . Primary antibody responses against the phage appear to be composed of a mixture of IgM and IgG2b isotypes in C57BL/6 mice, while secondary antibody responses are composed primarily of IgG1 and IgG2b isotypes, with a lesser contribution of IgG2c and IgG3 isotypes (Hashiguchi et al., 2010) . Deletion of the surface-exposed N1 and N2 domains of pIII produces a truncated form of this protein that does not elicit antibodies, but also results in a non-infective phage particle with lower overall immunogenicity (van Houten et al., 2010) .
FIGURE 1 | Types of immune responses elicited in response to immunization with filamentous bacteriophage. As a virus-like particle, the filamentous phage engages multiple arms of the immune system, beginning with cellular effectors of innate immunity (macrophages, neutrophils, and possibly natural killer cells), which are recruited to tumor sites by phage displaying tumor-targeting moieties. The phage likely
activates T-cell independent antibody responses, either via phage-associated TLR ligands or cross-linking by the pVIII lattice. After processing by antigen-presenting cells, phage-derived peptides are presented on MHC class II and cross-presented on MHC class I, resulting in activation of short-lived CTLs and an array of helper T-cell types, which help prime memory CTL and high-affinity B-cell responses.
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Although serum anti-phage antibody titers appear to be at least partially T-cell dependent (Kölsch et al., 1971; Willis et al., 1993; De Berardinis et al., 1999; van Houten et al., 2010) , many circulating pVIII-specific B cells in the blood are devoid of somatic mutation even after repeated biweekly immunizations, suggesting that under these conditions, the phage activates T-cell-independent B-cell responses in addition to highaffinity T-cell-dependent responses (Murira, 2014) . Filamentous phage particles can be processed by antigen-presenting cells and presented on MHC class II molecules (Gaubin et al., 2003; Ulivieri et al., 2008) and can activate T H 1, T H 2, and T H 17 helper T cells (Yang et al., 2005a; Wang et al., 2014d) . Anti-phage T H 2 responses were enhanced through display of CTLA-4 peptides fused to pIII (Kajihara et al., 2000) . Phage proteins can also be cross-presented on MHC class I molecules (Wan et al., 2005) and can prime two waves of CTL responses, consisting first of short-lived CTLs and later of long-lived memory CTLs that require CD4 + T-cell help (Del Pozzo et al., 2010) . The latter CTLs mediate a delayed-type hypersensitivity reaction (Fang et al., 2005; Del Pozzo et al., 2010) .
The phage particle is self-adjuvanting through multiple mechanisms. Host cell wall-derived LPS enhances the virion's immunogenicity, and its removal by polymyxin B chromatography reduces antibody titers against phage coat proteins (Grabowska et al., 2000) . The phage's singlestranded DNA genome contains CpG motifs and may also have an adjuvant effect. The antibody response against the phage is entirely dependent on MyD88 signaling and is modulated by stimulation of several Toll-like receptors (Hashiguchi et al., 2010) , indicating that innate immunity plays an important but largely uncharacterized role in the activation of anti-phage adaptive immune responses. Biodistribution studies of the phage after intravenous injection show that it is cleared from the blood within hours through the reticuloendothelial system (Molenaar et al., 2002) , particularly of the liver and spleen, where it is retained for days (Zou et al., 2004) , potentially activating marginal-zone B-cell responses. Thus, the filamentous phage is not only a highly immunogenic carrier, but by virtue of activating a range of innate and adaptive immune responses, serves as an excellent model virus-like particle antigen.
Long before the identification of filamentous phage, other types of bacteriophage were already being used for antibacterial therapy in the former Soviet Union and Eastern Europe (reviewed in Sulakvelidze et al., 2001) . The filamentous phage, with its nonlytic life cycle, has less obvious clinical uses, despite the fact that the host specificity of Inovirus and Plectrovirus includes many pathogens of medical importance, including Salmonella, E. coli, Shigella, Pseudomonas, Clostridium, and Mycoplasma species.
In an effort to enhance their bactericidal activity, genetically modified filamentous phage have been used as a "Trojan horse" to introduce various antibacterial agents into cells. M13 and Pf3 phage engineered to express either BglII restriction endonuclease (Hagens and Blasi, 2003; Hagens et al., 2004) , lambda phage S holin (Hagens and Blasi, 2003) or a lethal catabolite gene activator protein (Moradpour et al., 2009) effectively killed E. coli and Pseudomonas aeruginosa cells, respectively, with no concomitant release of LPS (Hagens and Blasi, 2003; Hagens et al., 2004) . Unfortunately, the rapid emergence of resistant bacteria with modified F pili represents a major and possibly insurmountable obstacle to this approach. However, there are some indications that filamentous phage can exert useful but more subtle effects upon their bacterial hosts that may not result in the development of resistance to infection. Several studies have reported increased antibiotic sensitivity in bacterial populations simultaneously infected with either wild type filamentous phage (Hagens et al., 2006) or phage engineered to repress the cellular SOS response (Lu and Collins, 2009) . Filamentous phage f1 infection inhibited early stage, but not mature, biofilm formation in E. coli (May et al., 2011) . Thus, unmodified filamentous phage may be of future interest as elements of combination therapeutics against certain drug-resistant infections.
More advanced therapeutic applications of the filamentous phage emerge when it is modified to express a targeting moiety specific for pathogenic cells and/or proteins for the treatment of infectious diseases, cancer and autoimmunity (Figure 2) . The first work in this area showed as proof-of-concept that phage encoding a GFP expression cassette and displaying a HER2specific scFv on all copies of pIII were internalized into breast tumor cells, resulting in GFP expression (Poul and Marks, 1999) . M13 or fd phage displaying either a targeting peptide or antibody fragment and tethered to chloramphenicol by a labile crosslinker were more potent inhibitors of Staphylococcus aureus growth than high-concentration free chloramphenicol (Yacoby et al., 2006; Vaks and Benhar, 2011) . M13 phage loaded with doxorubicin and displaying a targeting peptide on pIII specifically killed prostate cancer cells in vitro (Ghosh et al., 2012a) . Tumorspecific peptide:pVIII fusion proteins selected from "landscape" phage (Romanov et al., 2001; Abbineni et al., 2010; Fagbohun et al., 2012 Fagbohun et al., , 2013 Lang et al., 2014; Wang et al., 2014a) were able to target and deliver siRNA-, paclitaxel-, and doxorubicincontaining liposomes to tumor cells (Jayanna et al., 2010a; Wang et al., 2010a Wang et al., ,b,c, 2014b Bedi et al., 2011 Bedi et al., , 2013 Bedi et al., , 2014 ; they were non-toxic and increased tumor remission rates in mouse models (Jayanna et al., 2010b; Wang et al., 2014b,c) . Using the B16-OVA tumor model, Eriksson et al. (2007) showed that phage displaying peptides and/or Fabs specific for tumor antigens delayed tumor growth and improved survival, owing in large part to activation of tumor-associated macrophages and recruitment of neutrophils to the tumor site (Eriksson et al., 2009) . Phage displaying an scFv against β-amyloid fibrils showed promise as a diagnostic (Frenkel and Solomon, 2002) and therapeutic (Solomon, 2008) reagent for Alzheimer's disease and Parkinson's disease due to the unanticipated ability of the phage to penetrate into brain tissue (Ksendzovsky et al., 2012) . Similarly, phage displaying an immunodominant peptide epitope derived from myelin oligodendrocyte glycoprotein depleted pathogenic demyelinating antibodies in brain tissue in the murine experimental autoimmune encephalomyelitis model of multiple sclerosis (Rakover et al., 2010) . The advantages of the filamentous phage in this context over traditional antibody-drug or protein-peptide conjugates are (i) its ability to carry very high amounts of drug or peptide, and (ii) its ability to access anatomical compartments that cannot generally be reached by systemic administration of a protein.
Unlike most therapeutic biologics, the filamentous phage's production in bacteria complicates its use in humans in several ways. First and foremost, crude preparations of filamentous phage typically contain very high levels of contaminating LPS, in the range of ∼10 2 -10 4 endotoxin units (EU)/mL (Boratynski et al., 2004; Branston et al., 2015) , which have the potential to cause severe adverse reactions. LPS is not completely removed by polyethylene glycol precipitation or cesium chloride density gradient centrifugation (Smith and Gingrich, 2005; Branston et al., 2015) , but its levels can be reduced dramatically using additional purification steps such as size exclusion chromatography (Boratynski et al., 2004; Zakharova et al., 2005) , polymyxin B chromatography (Grabowska et al., 2000) , and treatment with detergents such as Triton X-100 or Triton X-114 (Roehnisch et al., 2014; Branston et al., 2015) . These strategies routinely achieve endotoxin levels of <1 EU/mL as measured by the limulus amebocyte lysate (LAL) assay, well below the FDA limit for parenteral administration of 5 EU/kg body weight/dose, although concerns remain regarding the presence of residual virion-associated LPS which may be undetectable. A second and perhaps unavoidable consequence of the filamentous phage's bacterial production is inherent heterogeneity of particle size and the spectrum of host cellderived virion-associated and soluble contaminants, which may be cause for safety concerns and restrict its use to high-risk groups.
Many types of bacteriophage and engineered phage variants, including filamentous phage, have been proposed for prophylactic use ex vivo in food safety, either in the production pipeline (reviewed in Dalmasso et al., 2014) or for detection of foodborne pathogens post-production (reviewed in Schmelcher and Loessner, 2014) . Filamentous phage displaying a tetracysteine tag on pIII were used to detect E. coli cells through staining with biarsenical dye . M13 phage functionalized with metallic silver were highly bactericidal against E. coli and Staphylococcus epidermidis . Biosensors based on surface plasmon resonance (Nanduri et al., 2007) , piezoelectric transducers (Olsen et al., 2006) , linear dichroism (Pacheco-Gomez et al., 2012) , and magnetoelastic sensor technology (Lakshmanan et al., 2007; Huang et al., 2009) were devised using filamentous phage displaying scFv or conjugated to whole IgG against E. coli, Listeria monocytogenes, Salmonella typhimurium, and Bacillus anthracis with limits of detection on the order of 10 2 -10 6 bacterial cells/mL. Proof of concept has been demonstrated for use of such phage-based biosensors to detect bacterial contamination of live produce (Li et al., 2010b) and eggs (Chai et al., 2012) .
The filamentous phage particle is enclosed by a rod-like protein capsid, ∼1000 nm long and 5 nm wide, made up almost entirely of overlapping pVIII monomers, each of which lies ∼27 angstroms from its nearest neighbor and exposes two amine groups as well as at least three carboxyl groups (Henry et al., 2011) . The regularity of the phage pVIII lattice and its diversity of chemically addressable groups make it an ideal scaffold for bioconjugation (Figure 3) . The most commonly used approach is functionalization of amine groups with NHS esters (van Houten et al., 2006 (van Houten et al., , 2010 Yacoby et al., 2006) , although this can result in unwanted acylation of pIII and any displayed biomolecules. Carboxyl groups and tyrosine residues can also be functionalized using carbodiimide coupling and diazonium coupling, respectively (Li et al., 2010a) . Carrico et al. (2012) developed methods to specifically label pVIII N-termini without modification of exposed lysine residues through a two-step transamination-oxime formation reaction. Specific modification of phage coat proteins is even more easily accomplished using genetically modified phage displaying peptides (Ng et al., 2012) or enzymes (Chen et al., 2007; Hess et al., 2012) , but this can be cumbersome and is less general in application.
For more than a decade, interest in the filamentous phage as a building block for nanomaterials has been growing because of its unique physicochemical properties, with emerging applications in magnetics, optics, and electronics. It has long been known that above a certain concentration threshold, phage can form ordered crystalline suspensions (Welsh et al., 1996) . Lee et al. (2002) engineered M13 phage to display a ZnS-binding peptide on pIII and showed that, in the presence of ZnS nanoparticles, they selfassemble into highly ordered film biomaterials that can be aligned using magnetic fields. Taking advantage of the ability to display substrate-specific peptides at known locations on the phage filament Hess et al., 2012) , this pioneering FIGURE 3 | Chemically addressable groups of the filamentous bacteriophage major coat protein lattice. The filamentous phage virion is made up of ∼2,500-4,000 overlapping copies of the 50-residue major coat protein, pVIII, arranged in a shingle-type lattice. Each monomer has an array of chemically addressable groups available for bioorthogonal conjugation, including two primary amine groups (shown in red), three carboxyl groups (show in blue) and two hydroxyl groups (show in green). The 12 N-terminal residues generally exposed to the immune system for antibody binding are in bold underline. Figure adapted from structural data of Marvin, 1990 , freely available in PDB and SCOPe databases.
work became the basis for construction of two-and threedimensional nanomaterials with more advanced architectures, including semiconducting nanowires (Mao et al., 2003 (Mao et al., , 2004 , nanoparticles , and nanocomposites (Oh et al., 2012; Chen et al., 2014) . Using hybrid M13 phage displaying Co 3 O 4 -and gold-binding peptides on pVIII as a scaffold to assemble nanowires on polyelectrolyte multilayers, Nam et al. (2006) produced a thin, flexible lithium ion battery, which could be stamped onto platinum microband current collectors (Nam et al., 2008) . The electrochemical properties of such batteries were further improved through pIII-display of single-walled carbon nanotube-binding peptides (Lee et al., 2009) , offering an approach for sustainable production of nanostructured electrodes from poorly conductive starting materials. Phagebased nanomaterials have found applications in cancer imaging (Ghosh et al., 2012b; Yi et al., 2012) , photocatalytic water splitting (Nam et al., 2010a; Neltner et al., 2010) , light harvesting (Nam et al., 2010b; Chen et al., 2013) , photoresponsive technologies (Murugesan et al., 2013) , neural electrodes (Kim et al., 2014) , and piezoelectric energy generation (Murugesan et al., 2013) .
Thus, the unique physicochemical properties of the phage, in combination with modular display of peptides and proteins with known binding specificity, have spawned wholly novel materials with diverse applications. It is worth noting that the unusual biophysical properties of the filamentous phage can also be exploited in the study of structures of other macromolecules. Magnetic alignment of high-concentration filamentous phage in solution can partially order DNA, RNA, proteins, and other biomolecules for measurement of dipolar coupling interactions (Hansen et al., 1998 (Hansen et al., , 2000 Dahlke Ojennus et al., 1999) in NMR spectroscopy.
Because of their large population sizes, short generation times, small genome sizes and ease of manipulation, various filamentous and non-filamentous bacteriophages have been used as models of experimental evolution (reviewed in Husimi, 1989; Wichman and Brown, 2010; Kawecki et al., 2012; Hall et al., 2013) . The filamentous phage has additional practical uses in protein engineering and directed protein evolution, due to its unique tolerance of genetic modifications that allow biomolecules to be displayed on the virion surface. First and foremost among these applications is in vitro affinity maturation of antibody fragments displayed on pIII. Libraries of variant Fabs and single chain antibodies can be generated via random or sitedirected mutagenesis and selected on the basis of improved or altered binding, roughly mimicking the somatic evolution strategy of the immune system (Marks et al., 1992; Bradbury et al., 2011) . However, other in vitro display systems, such as yeast display, have important advantages over the filamentous phage for affinity maturation (although each display technology has complementary strengths; Koide and Koide, 2012) , and regardless of the display method, selection of "improved" variants can be slow and cumbersome. Iterative methods have been developed to combine computationally designed mutations (Lippow et al., 2007) and circumvent the screening of combinatorial libraries, but these have had limited success to date.
Recently, Esvelt et al. (2011) developed a novel strategy for directed evolution of filamentous phage-displayed proteins, called phage-assisted continuous evolution (PACE), which allows multiple rounds of evolution per day with little experimental intervention. The authors engineered M13 phage to encode an exogenous protein (the subject for directed evolution), whose functional activity triggers gene III expression from an accessory plasmid; variants of the exogenous protein arise by random mutagenesis during phage replication, the rate of which can be increased by inducible expression of error-prone DNA polymerases. By supplying limiting amounts of receptive E. coli cells to the engineered phage variants, Esvelt et al. (2011) elegantly linked phage infectivity and production of offspring with the presence of a desired protein phenotype. Carlson et al. (2014) later showed that PACE selection stringency could be modulated by providing small amounts of pIII independently of protein phenotype, and undesirable protein functions negatively selected by linking them to expression of a truncated pIII variant that impairs infectivity in a dominant negative fashion. PACE is currently limited to protein functions that can be linked in some way to the expression of a gene III reporter, such as protein-protein interaction, recombination, DNA or RNA binding, and enzymatic catalysis (Meyer and Ellington, 2011) . This approach represents a promising avenue for both basic research in molecular evolution (Dickinson et al., 2013) and synthetic biology, including antibody engineering.
Filamentous bacteriophage have been recovered from diverse environmental sources, including soil (Murugaiyan et al., 2011) , coastal fresh water (Xue et al., 2012) , alpine lakes (Hofer and Sommaruga, 2001) and deep sea bacteria (Jian et al., 2012) , but not, perhaps surprisingly, the human gut (Kim et al., 2011) . The environmental "phageome" in soil and water represent the largest source of replicating DNA on the planet, and is estimated to contain upward of 10 30 viral particles (Ashelford et al., 2003; Chibani-Chennoufi et al., 2004; Suttle, 2005) . The few studies attempting to investigate filamentous phage environmental ecology using classical environmental microbiology techniques (typically direct observation by electron microscopy) found that filamentous phage made up anywhere from 0 to 100% of all viral particles (Demuth et al., 1993; Pina et al., 1998; Hofer and Sommaruga, 2001) . There was some evidence of seasonal fluctuation of filamentous phage populations in tandem with the relative abundance of free-living heterotrophic bacteria (Hofer and Sommaruga, 2001) . Environmental metagenomics efforts are just beginning to unravel the composition of viral ecosystems. The existing data suggest that filamentous phage comprise minor constituents of viral communities in freshwater (Roux et al., 2012) and reclaimed and potable water (Rosario et al., 2009) but have much higher frequencies in wastewater and sewage (Cantalupo et al., 2011; Alhamlan et al., 2013) , with the caveat that biases inherent to the methodologies for ascertaining these data (purification of viral particles, sequencing biases) have not been not well validated. There are no data describing the population dynamics of filamentous phage and their host species in the natural environment.
At the individual virus-bacterium level, it is clear that filamentous phage can modulate host phenotype, including the virulence of important human and crop pathogens. This can occur either through direct effects of phage replication on cell growth and physiology, or, more typically, by horizontal transfer of genetic material contained within episomes and/or chromosomally integrated prophage. Temperate filamentous phage may also play a role in genome evolution (reviewed in Canchaya et al., 2003) . Perhaps the best-studied example of virulence modulation by filamentous phage is that of Vibrio cholerae, whose full virulence requires lysogenic conversion by the cholera toxin-encoding CTXφ phage (Waldor and Mekalanos, 1996) . Integration of CTXφ phage occurs at specific sites in the genome; these sequences are introduced through the combined action of another filamentous phage, fs2φ, and a satellite filamentous phage, TLC-Knφ1 (Hassan et al., 2010) . Thus, filamentous phage species interact and coevolve with each other in addition to their hosts. Infection by filamentous phage has been implicated in the virulence of Yersinia pestis (Derbise et al., 2007) , Neisseria meningitidis (Bille et al., 2005 (Bille et al., , 2008 , Vibrio parahaemolyticus (Iida et al., 2001) , E. coli 018:K1:H7 (Gonzalez et al., 2002) , Xanthomonas campestris (Kamiunten and Wakimoto, 1982) , and P. aeruginosa (Webb et al., 2004) , although in most of these cases, the specific mechanisms modulating virulence are unclear. Phage infection can both enhance or repress virulence depending on the characteristics of the phage, the host bacterium, and the environmental milieu, as is the case for the bacterial wilt pathogen Ralstonia solanacearum (Yamada, 2013) . Since infection results in downregulation of the pili used for viral entry, filamentous phage treatment has been proposed as a hypothetical means of inhibiting bacterial conjugation and horizontal gene transfer, so as to prevent the spread of antibiotic resistance genes (Lin et al., 2011) .
Finally, the filamentous phage may also play a future role in the preservation of biodiversity of other organisms in at-risk ecosystems. Engineered phage have been proposed for use in bioremediation, either displaying antibody fragments of desired specificity for filtration of toxins and environmental contaminants (Petrenko and Makowski, 1993) , or as biodegradable polymers displaying peptides selected for their ability to aggregate pollutants, such as oil sands tailings (Curtis et al., 2011 (Curtis et al., , 2013 . Engineered phage displaying peptides that specifically bind inorganic materials have also been proposed for use in more advanced and less intrusive mineral separation technologies (Curtis et al., 2009 ).
The filamentous phage represents a highly versatile organism whose uses extend far beyond traditional phage display and affinity selection of antibodies and polypeptides of desired specificity. Its high immunogenicity and ability to display a variety of surface antigens make the phage an excellent particulate vaccine carrier, although its bacterial production and preparation heterogeneity likely limits its applications in human vaccines at present, despite being apparently safe and well-tolerated in animals and people. Unanticipated characteristics of the phage particle, such as crossing of the blood-brain barrier and formation of highly ordered liquid crystalline phases, have opened up entirely new avenues of research in therapeutics for chronic disease and the design of nanomaterials. Our comparatively detailed understanding of the interactions of model filamentous phage with their bacterial hosts has allowed researchers to harness the phage life cycle to direct protein evolution in the lab. Hopefully, deeper knowledge of phage-host interactions at an ecological level may produce novel strategies to control bacterial pathogenesis. While novel applications of the filamentous phage continue to be developed, the phage is likely to retain its position as a workhorse for therapeutic antibody discovery for many years to come, even with the advent of competing technologies.
KH and JS conceived and wrote the manuscript. MA-G read the manuscript and commented on the text. | What is a future potential of filamentous phage? | false | 1,756 | {
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2,504 | Respiratory Viral Infections in Exacerbation of Chronic Airway Inflammatory Diseases: Novel Mechanisms and Insights From the Upper Airway Epithelium
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7052386/
SHA: 45a566c71056ba4faab425b4f7e9edee6320e4a4
Authors: Tan, Kai Sen; Lim, Rachel Liyu; Liu, Jing; Ong, Hsiao Hui; Tan, Vivian Jiayi; Lim, Hui Fang; Chung, Kian Fan; Adcock, Ian M.; Chow, Vincent T.; Wang, De Yun
Date: 2020-02-25
DOI: 10.3389/fcell.2020.00099
License: cc-by
Abstract: Respiratory virus infection is one of the major sources of exacerbation of chronic airway inflammatory diseases. These exacerbations are associated with high morbidity and even mortality worldwide. The current understanding on viral-induced exacerbations is that viral infection increases airway inflammation which aggravates disease symptoms. Recent advances in in vitro air-liquid interface 3D cultures, organoid cultures and the use of novel human and animal challenge models have evoked new understandings as to the mechanisms of viral exacerbations. In this review, we will focus on recent novel findings that elucidate how respiratory viral infections alter the epithelial barrier in the airways, the upper airway microbial environment, epigenetic modifications including miRNA modulation, and other changes in immune responses throughout the upper and lower airways. First, we reviewed the prevalence of different respiratory viral infections in causing exacerbations in chronic airway inflammatory diseases. Subsequently we also summarized how recent models have expanded our appreciation of the mechanisms of viral-induced exacerbations. Further we highlighted the importance of the virome within the airway microbiome environment and its impact on subsequent bacterial infection. This review consolidates the understanding of viral induced exacerbation in chronic airway inflammatory diseases and indicates pathways that may be targeted for more effective management of chronic inflammatory diseases.
Text: The prevalence of chronic airway inflammatory disease is increasing worldwide especially in developed nations (GBD 2015 Chronic Respiratory Disease Collaborators, 2017 Guan et al., 2018) . This disease is characterized by airway inflammation leading to complications such as coughing, wheezing and shortness of breath. The disease can manifest in both the upper airway (such as chronic rhinosinusitis, CRS) and lower airway (such as asthma and chronic obstructive pulmonary disease, COPD) which greatly affect the patients' quality of life (Calus et al., 2012; Bao et al., 2015) . Treatment and management vary greatly in efficacy due to the complexity and heterogeneity of the disease. This is further complicated by the effect of episodic exacerbations of the disease, defined as worsening of disease symptoms including wheeze, cough, breathlessness and chest tightness (Xepapadaki and Papadopoulos, 2010) . Such exacerbations are due to the effect of enhanced acute airway inflammation impacting upon and worsening the symptoms of the existing disease (Hashimoto et al., 2008; Viniol and Vogelmeier, 2018) . These acute exacerbations are the main cause of morbidity and sometimes mortality in patients, as well as resulting in major economic burdens worldwide. However, due to the complex interactions between the host and the exacerbation agents, the mechanisms of exacerbation may vary considerably in different individuals under various triggers. Acute exacerbations are usually due to the presence of environmental factors such as allergens, pollutants, smoke, cold or dry air and pathogenic microbes in the airway (Gautier and Charpin, 2017; Viniol and Vogelmeier, 2018) . These agents elicit an immune response leading to infiltration of activated immune cells that further release inflammatory mediators that cause acute symptoms such as increased mucus production, cough, wheeze and shortness of breath. Among these agents, viral infection is one of the major drivers of asthma exacerbations accounting for up to 80-90% and 45-80% of exacerbations in children and adults respectively (Grissell et al., 2005; Xepapadaki and Papadopoulos, 2010; Jartti and Gern, 2017; Adeli et al., 2019) . Viral involvement in COPD exacerbation is also equally high, having been detected in 30-80% of acute COPD exacerbations (Kherad et al., 2010; Jafarinejad et al., 2017; Stolz et al., 2019) . Whilst the prevalence of viral exacerbations in CRS is still unclear, its prevalence is likely to be high due to the similar inflammatory nature of these diseases (Rowan et al., 2015; Tan et al., 2017) . One of the reasons for the involvement of respiratory viruses' in exacerbations is their ease of transmission and infection (Kutter et al., 2018) . In addition, the high diversity of the respiratory viruses may also contribute to exacerbations of different nature and severity (Busse et al., 2010; Costa et al., 2014; Jartti and Gern, 2017) . Hence, it is important to identify the exact mechanisms underpinning viral exacerbations in susceptible subjects in order to properly manage exacerbations via supplementary treatments that may alleviate the exacerbation symptoms or prevent severe exacerbations.
While the lower airway is the site of dysregulated inflammation in most chronic airway inflammatory diseases, the upper airway remains the first point of contact with sources of exacerbation. Therefore, their interaction with the exacerbation agents may directly contribute to the subsequent responses in the lower airway, in line with the "United Airway" hypothesis. To elucidate the host airway interaction with viruses leading to exacerbations, we thus focus our review on recent findings of viral interaction with the upper airway. We compiled how viral induced changes to the upper airway may contribute to chronic airway inflammatory disease exacerbations, to provide a unified elucidation of the potential exacerbation mechanisms initiated from predominantly upper airway infections.
Despite being a major cause of exacerbation, reports linking respiratory viruses to acute exacerbations only start to emerge in the late 1950s (Pattemore et al., 1992) ; with bacterial infections previously considered as the likely culprit for acute exacerbation (Stevens, 1953; Message and Johnston, 2002) . However, with the advent of PCR technology, more viruses were recovered during acute exacerbations events and reports implicating their role emerged in the late 1980s (Message and Johnston, 2002) . Rhinovirus (RV) and respiratory syncytial virus (RSV) are the predominant viruses linked to the development and exacerbation of chronic airway inflammatory diseases (Jartti and Gern, 2017) . Other viruses such as parainfluenza virus (PIV), influenza virus (IFV) and adenovirus (AdV) have also been implicated in acute exacerbations but to a much lesser extent (Johnston et al., 2005; Oliver et al., 2014; Ko et al., 2019) . More recently, other viruses including bocavirus (BoV), human metapneumovirus (HMPV), certain coronavirus (CoV) strains, a specific enterovirus (EV) strain EV-D68, human cytomegalovirus (hCMV) and herpes simplex virus (HSV) have been reported as contributing to acute exacerbations . The common feature these viruses share is that they can infect both the upper and/or lower airway, further increasing the inflammatory conditions in the diseased airway (Mallia and Johnston, 2006; Britto et al., 2017) .
Respiratory viruses primarily infect and replicate within airway epithelial cells . During the replication process, the cells release antiviral factors and cytokines that alter local airway inflammation and airway niche (Busse et al., 2010) . In a healthy airway, the inflammation normally leads to type 1 inflammatory responses consisting of activation of an antiviral state and infiltration of antiviral effector cells. This eventually results in the resolution of the inflammatory response and clearance of the viral infection (Vareille et al., 2011; Braciale et al., 2012) . However, in a chronically inflamed airway, the responses against the virus may be impaired or aberrant, causing sustained inflammation and erroneous infiltration, resulting in the exacerbation of their symptoms (Mallia and Johnston, 2006; Dougherty and Fahy, 2009; Busse et al., 2010; Britto et al., 2017; Linden et al., 2019) . This is usually further compounded by the increased susceptibility of chronic airway inflammatory disease patients toward viral respiratory infections, thereby increasing the frequency of exacerbation as a whole (Dougherty and Fahy, 2009; Busse et al., 2010; Linden et al., 2019) . Furthermore, due to the different replication cycles and response against the myriad of respiratory viruses, each respiratory virus may also contribute to exacerbations via different mechanisms that may alter their severity. Hence, this review will focus on compiling and collating the current known mechanisms of viral-induced exacerbation of chronic airway inflammatory diseases; as well as linking the different viral infection pathogenesis to elucidate other potential ways the infection can exacerbate the disease. The review will serve to provide further understanding of viral induced exacerbation to identify potential pathways and pathogenesis mechanisms that may be targeted as supplementary care for management and prevention of exacerbation. Such an approach may be clinically significant due to the current scarcity of antiviral drugs for the management of viral-induced exacerbations. This will improve the quality of life of patients with chronic airway inflammatory diseases.
Once the link between viral infection and acute exacerbations of chronic airway inflammatory disease was established, there have been many reports on the mechanisms underlying the exacerbation induced by respiratory viral infection. Upon infecting the host, viruses evoke an inflammatory response as a means of counteracting the infection. Generally, infected airway epithelial cells release type I (IFNα/β) and type III (IFNλ) interferons, cytokines and chemokines such as IL-6, IL-8, IL-12, RANTES, macrophage inflammatory protein 1α (MIP-1α) and monocyte chemotactic protein 1 (MCP-1) (Wark and Gibson, 2006; Matsukura et al., 2013) . These, in turn, enable infiltration of innate immune cells and of professional antigen presenting cells (APCs) that will then in turn release specific mediators to facilitate viral targeting and clearance, including type II interferon (IFNγ), IL-2, IL-4, IL-5, IL-9, and IL-12 (Wark and Gibson, 2006; Singh et al., 2010; Braciale et al., 2012) . These factors heighten local inflammation and the infiltration of granulocytes, T-cells and B-cells (Wark and Gibson, 2006; Braciale et al., 2012) . The increased inflammation, in turn, worsens the symptoms of airway diseases.
Additionally, in patients with asthma and patients with CRS with nasal polyp (CRSwNP), viral infections such as RV and RSV promote a Type 2-biased immune response (Becker, 2006; Jackson et al., 2014; Jurak et al., 2018) . This amplifies the basal type 2 inflammation resulting in a greater release of IL-4, IL-5, IL-13, RANTES and eotaxin and a further increase in eosinophilia, a key pathological driver of asthma and CRSwNP (Wark and Gibson, 2006; Singh et al., 2010; Chung et al., 2015; Dunican and Fahy, 2015) . Increased eosinophilia, in turn, worsens the classical symptoms of disease and may further lead to life-threatening conditions due to breathing difficulties. On the other hand, patients with COPD and patients with CRS without nasal polyp (CRSsNP) are more neutrophilic in nature due to the expression of neutrophil chemoattractants such as CXCL9, CXCL10, and CXCL11 (Cukic et al., 2012; Brightling and Greening, 2019) . The pathology of these airway diseases is characterized by airway remodeling due to the presence of remodeling factors such as matrix metalloproteinases (MMPs) released from infiltrating neutrophils (Linden et al., 2019) . Viral infections in such conditions will then cause increase neutrophilic activation; worsening the symptoms and airway remodeling in the airway thereby exacerbating COPD, CRSsNP and even CRSwNP in certain cases (Wang et al., 2009; Tacon et al., 2010; Linden et al., 2019) .
An epithelial-centric alarmin pathway around IL-25, IL-33 and thymic stromal lymphopoietin (TSLP), and their interaction with group 2 innate lymphoid cells (ILC2) has also recently been identified (Nagarkar et al., 2012; Hong et al., 2018; Allinne et al., 2019) . IL-25, IL-33 and TSLP are type 2 inflammatory cytokines expressed by the epithelial cells upon injury to the epithelial barrier (Gabryelska et al., 2019; Roan et al., 2019) . ILC2s are a group of lymphoid cells lacking both B and T cell receptors but play a crucial role in secreting type 2 cytokines to perpetuate type 2 inflammation when activated (Scanlon and McKenzie, 2012; Li and Hendriks, 2013) . In the event of viral infection, cell death and injury to the epithelial barrier will also induce the expression of IL-25, IL-33 and TSLP, with heighten expression in an inflamed airway (Allakhverdi et al., 2007; Goldsmith et al., 2012; Byers et al., 2013; Shaw et al., 2013; Beale et al., 2014; Jackson et al., 2014; Uller and Persson, 2018; Ravanetti et al., 2019) . These 3 cytokines then work in concert to activate ILC2s to further secrete type 2 cytokines IL-4, IL-5, and IL-13 which further aggravate the type 2 inflammation in the airway causing acute exacerbation (Camelo et al., 2017) . In the case of COPD, increased ILC2 activation, which retain the capability of differentiating to ILC1, may also further augment the neutrophilic response and further aggravate the exacerbation (Silver et al., 2016) . Interestingly, these factors are not released to any great extent and do not activate an ILC2 response during viral infection in healthy individuals (Yan et al., 2016; Tan et al., 2018a) ; despite augmenting a type 2 exacerbation in chronically inflamed airways (Jurak et al., 2018) . These classical mechanisms of viral induced acute exacerbations are summarized in Figure 1 .
As integration of the virology, microbiology and immunology of viral infection becomes more interlinked, additional factors and FIGURE 1 | Current understanding of viral induced exacerbation of chronic airway inflammatory diseases. Upon virus infection in the airway, antiviral state will be activated to clear the invading pathogen from the airway. Immune response and injury factors released from the infected epithelium normally would induce a rapid type 1 immunity that facilitates viral clearance. However, in the inflamed airway, the cytokines and chemokines released instead augmented the inflammation present in the chronically inflamed airway, strengthening the neutrophilic infiltration in COPD airway, and eosinophilic infiltration in the asthmatic airway. The effect is also further compounded by the participation of Th1 and ILC1 cells in the COPD airway; and Th2 and ILC2 cells in the asthmatic airway.
Frontiers in Cell and Developmental Biology | www.frontiersin.org mechanisms have been implicated in acute exacerbations during and after viral infection (Murray et al., 2006) . Murray et al. (2006) has underlined the synergistic effect of viral infection with other sensitizing agents in causing more severe acute exacerbations in the airway. This is especially true when not all exacerbation events occurred during the viral infection but may also occur well after viral clearance (Kim et al., 2008; Stolz et al., 2019) in particular the late onset of a bacterial infection (Singanayagam et al., 2018 (Singanayagam et al., , 2019a . In addition, viruses do not need to directly infect the lower airway to cause an acute exacerbation, as the nasal epithelium remains the primary site of most infections. Moreover, not all viral infections of the airway will lead to acute exacerbations, suggesting a more complex interplay between the virus and upper airway epithelium which synergize with the local airway environment in line with the "united airway" hypothesis (Kurai et al., 2013) . On the other hand, viral infections or their components persist in patients with chronic airway inflammatory disease (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Hence, their presence may further alter the local environment and contribute to current and future exacerbations. Future studies should be performed using metagenomics in addition to PCR analysis to determine the contribution of the microbiome and mycobiome to viral infections. In this review, we highlight recent data regarding viral interactions with the airway epithelium that could also contribute to, or further aggravate, acute exacerbations of chronic airway inflammatory diseases.
Patients with chronic airway inflammatory diseases have impaired or reduced ability of viral clearance (Hammond et al., 2015; McKendry et al., 2016; Akbarshahi et al., 2018; Gill et al., 2018; Wang et al., 2018; Singanayagam et al., 2019b) . Their impairment stems from a type 2-skewed inflammatory response which deprives the airway of important type 1 responsive CD8 cells that are responsible for the complete clearance of virusinfected cells (Becker, 2006; McKendry et al., 2016) . This is especially evident in weak type 1 inflammation-inducing viruses such as RV and RSV (Kling et al., 2005; Wood et al., 2011; Ravi et al., 2019) . Additionally, there are also evidence of reduced type I (IFNβ) and III (IFNλ) interferon production due to type 2-skewed inflammation, which contributes to imperfect clearance of the virus resulting in persistence of viral components, or the live virus in the airway epithelium (Contoli et al., 2006; Hwang et al., 2019; Wark, 2019) . Due to the viral components remaining in the airway, antiviral genes such as type I interferons, inflammasome activating factors and cytokines remained activated resulting in prolong airway inflammation (Wood et al., 2011; Essaidi-Laziosi et al., 2018) . These factors enhance granulocyte infiltration thus prolonging the exacerbation symptoms. Such persistent inflammation may also be found within DNA viruses such as AdV, hCMV and HSV, whose infections generally persist longer (Imperiale and Jiang, 2015) , further contributing to chronic activation of inflammation when they infect the airway (Yang et al., 2008; Morimoto et al., 2009; Imperiale and Jiang, 2015; Lan et al., 2016; Tan et al., 2016; Kowalski et al., 2017) . With that note, human papilloma virus (HPV), a DNA virus highly associated with head and neck cancers and respiratory papillomatosis, is also linked with the chronic inflammation that precedes the malignancies (de Visser et al., 2005; Gillison et al., 2012; Bonomi et al., 2014; Fernandes et al., 2015) . Therefore, the role of HPV infection in causing chronic inflammation in the airway and their association to exacerbations of chronic airway inflammatory diseases, which is scarcely explored, should be investigated in the future. Furthermore, viral persistence which lead to continuous expression of antiviral genes may also lead to the development of steroid resistance, which is seen with RV, RSV, and PIV infection (Chi et al., 2011; Ford et al., 2013; Papi et al., 2013) . The use of steroid to suppress the inflammation may also cause the virus to linger longer in the airway due to the lack of antiviral clearance (Kim et al., 2008; Hammond et al., 2015; Hewitt et al., 2016; McKendry et al., 2016; Singanayagam et al., 2019b) . The concomitant development of steroid resistance together with recurring or prolong viral infection thus added considerable burden to the management of acute exacerbation, which should be the future focus of research to resolve the dual complications arising from viral infection.
On the other end of the spectrum, viruses that induce strong type 1 inflammation and cell death such as IFV (Yan et al., 2016; Guibas et al., 2018) and certain CoV (including the recently emerged COVID-19 virus) (Tao et al., 2013; Yue et al., 2018; Zhu et al., 2020) , may not cause prolonged inflammation due to strong induction of antiviral clearance. These infections, however, cause massive damage and cell death to the epithelial barrier, so much so that areas of the epithelium may be completely absent post infection (Yan et al., 2016; Tan et al., 2019) . Factors such as RANTES and CXCL10, which recruit immune cells to induce apoptosis, are strongly induced from IFV infected epithelium (Ampomah et al., 2018; Tan et al., 2019) . Additionally, necroptotic factors such as RIP3 further compounds the cell deaths in IFV infected epithelium . The massive cell death induced may result in worsening of the acute exacerbation due to the release of their cellular content into the airway, further evoking an inflammatory response in the airway (Guibas et al., 2018) . Moreover, the destruction of the epithelial barrier may cause further contact with other pathogens and allergens in the airway which may then prolong exacerbations or results in new exacerbations. Epithelial destruction may also promote further epithelial remodeling during its regeneration as viral infection induces the expression of remodeling genes such as MMPs and growth factors . Infections that cause massive destruction of the epithelium, such as IFV, usually result in severe acute exacerbations with non-classical symptoms of chronic airway inflammatory diseases. Fortunately, annual vaccines are available to prevent IFV infections (Vasileiou et al., 2017; Zheng et al., 2018) ; and it is recommended that patients with chronic airway inflammatory disease receive their annual influenza vaccination as the best means to prevent severe IFV induced exacerbation.
Another mechanism that viral infections may use to drive acute exacerbations is the induction of vasodilation or tight junction opening factors which may increase the rate of infiltration. Infection with a multitude of respiratory viruses causes disruption of tight junctions with the resulting increased rate of viral infiltration. This also increases the chances of allergens coming into contact with airway immune cells. For example, IFV infection was found to induce oncostatin M (OSM) which causes tight junction opening (Pothoven et al., 2015; Tian et al., 2018) . Similarly, RV and RSV infections usually cause tight junction opening which may also increase the infiltration rate of eosinophils and thus worsening of the classical symptoms of chronic airway inflammatory diseases (Sajjan et al., 2008; Kast et al., 2017; Kim et al., 2018) . In addition, the expression of vasodilating factors and fluid homeostatic factors such as angiopoietin-like 4 (ANGPTL4) and bactericidal/permeabilityincreasing fold-containing family member A1 (BPIFA1) are also associated with viral infections and pneumonia development, which may worsen inflammation in the lower airway Akram et al., 2018) . These factors may serve as targets to prevent viral-induced exacerbations during the management of acute exacerbation of chronic airway inflammatory diseases.
Another recent area of interest is the relationship between asthma and COPD exacerbations and their association with the airway microbiome. The development of chronic airway inflammatory diseases is usually linked to specific bacterial species in the microbiome which may thrive in the inflamed airway environment (Diver et al., 2019) . In the event of a viral infection such as RV infection, the effect induced by the virus may destabilize the equilibrium of the microbiome present (Molyneaux et al., 2013; Kloepfer et al., 2014; Kloepfer et al., 2017; Jubinville et al., 2018; van Rijn et al., 2019) . In addition, viral infection may disrupt biofilm colonies in the upper airway (e.g., Streptococcus pneumoniae) microbiome to be release into the lower airway and worsening the inflammation (Marks et al., 2013; Chao et al., 2014) . Moreover, a viral infection may also alter the nutrient profile in the airway through release of previously inaccessible nutrients that will alter bacterial growth (Siegel et al., 2014; Mallia et al., 2018) . Furthermore, the destabilization is further compounded by impaired bacterial immune response, either from direct viral influences, or use of corticosteroids to suppress the exacerbation symptoms (Singanayagam et al., 2018 (Singanayagam et al., , 2019a Wang et al., 2018; Finney et al., 2019) . All these may gradually lead to more far reaching effect when normal flora is replaced with opportunistic pathogens, altering the inflammatory profiles (Teo et al., 2018) . These changes may in turn result in more severe and frequent acute exacerbations due to the interplay between virus and pathogenic bacteria in exacerbating chronic airway inflammatory diseases (Wark et al., 2013; Singanayagam et al., 2018) . To counteract these effects, microbiome-based therapies are in their infancy but have shown efficacy in the treatments of irritable bowel syndrome by restoring the intestinal microbiome (Bakken et al., 2011) . Further research can be done similarly for the airway microbiome to be able to restore the microbiome following disruption by a viral infection.
Viral infections can cause the disruption of mucociliary function, an important component of the epithelial barrier. Ciliary proteins FIGURE 2 | Changes in the upper airway epithelium contributing to viral exacerbation in chronic airway inflammatory diseases. The upper airway epithelium is the primary contact/infection site of most respiratory viruses. Therefore, its infection by respiratory viruses may have far reaching consequences in augmenting and synergizing current and future acute exacerbations. The destruction of epithelial barrier, mucociliary function and cell death of the epithelial cells serves to increase contact between environmental triggers with the lower airway and resident immune cells. The opening of tight junction increasing the leakiness further augments the inflammation and exacerbations. In addition, viral infections are usually accompanied with oxidative stress which will further increase the local inflammation in the airway. The dysregulation of inflammation can be further compounded by modulation of miRNAs and epigenetic modification such as DNA methylation and histone modifications that promote dysregulation in inflammation. Finally, the change in the local airway environment and inflammation promotes growth of pathogenic bacteria that may replace the airway microbiome. Furthermore, the inflammatory environment may also disperse upper airway commensals into the lower airway, further causing inflammation and alteration of the lower airway environment, resulting in prolong exacerbation episodes following viral infection.
Viral specific trait contributing to exacerbation mechanism (with literature evidence) Oxidative stress ROS production (RV, RSV, IFV, HSV)
As RV, RSV, and IFV were the most frequently studied viruses in chronic airway inflammatory diseases, most of the viruses listed are predominantly these viruses. However, the mechanisms stated here may also be applicable to other viruses but may not be listed as they were not implicated in the context of chronic airway inflammatory diseases exacerbation (see text for abbreviations).
that aid in the proper function of the motile cilia in the airways are aberrantly expressed in ciliated airway epithelial cells which are the major target for RV infection (Griggs et al., 2017) . Such form of secondary cilia dyskinesia appears to be present with chronic inflammations in the airway, but the exact mechanisms are still unknown (Peng et al., , 2019 Qiu et al., 2018) . Nevertheless, it was found that in viral infection such as IFV, there can be a change in the metabolism of the cells as well as alteration in the ciliary gene expression, mostly in the form of down-regulation of the genes such as dynein axonemal heavy chain 5 (DNAH5) and multiciliate differentiation And DNA synthesis associated cell cycle protein (MCIDAS) (Tan et al., 2018b . The recently emerged Wuhan CoV was also found to reduce ciliary beating in infected airway epithelial cell model (Zhu et al., 2020) . Furthermore, viral infections such as RSV was shown to directly destroy the cilia of the ciliated cells and almost all respiratory viruses infect the ciliated cells (Jumat et al., 2015; Yan et al., 2016; Tan et al., 2018a) . In addition, mucus overproduction may also disrupt the equilibrium of the mucociliary function following viral infection, resulting in symptoms of acute exacerbation (Zhu et al., 2009) . Hence, the disruption of the ciliary movement during viral infection may cause more foreign material and allergen to enter the airway, aggravating the symptoms of acute exacerbation and making it more difficult to manage. The mechanism of the occurrence of secondary cilia dyskinesia can also therefore be explored as a means to limit the effects of viral induced acute exacerbation.
MicroRNAs (miRNAs) are short non-coding RNAs involved in post-transcriptional modulation of biological processes, and implicated in a number of diseases (Tan et al., 2014) . miRNAs are found to be induced by viral infections and may play a role in the modulation of antiviral responses and inflammation (Gutierrez et al., 2016; Deng et al., 2017; Feng et al., 2018) . In the case of chronic airway inflammatory diseases, circulating miRNA changes were found to be linked to exacerbation of the diseases (Wardzynska et al., 2020) . Therefore, it is likely that such miRNA changes originated from the infected epithelium and responding immune cells, which may serve to further dysregulate airway inflammation leading to exacerbations. Both IFV and RSV infections has been shown to increase miR-21 and augmented inflammation in experimental murine asthma models, which is reversed with a combination treatment of anti-miR-21 and corticosteroids (Kim et al., 2017) . IFV infection is also shown to increase miR-125a and b, and miR-132 in COPD epithelium which inhibits A20 and MAVS; and p300 and IRF3, respectively, resulting in increased susceptibility to viral infections (Hsu et al., 2016 (Hsu et al., , 2017 . Conversely, miR-22 was shown to be suppressed in asthmatic epithelium in IFV infection which lead to aberrant epithelial response, contributing to exacerbations (Moheimani et al., 2018) . Other than these direct evidence of miRNA changes in contributing to exacerbations, an increased number of miRNAs and other non-coding RNAs responsible for immune modulation are found to be altered following viral infections (Globinska et al., 2014; Feng et al., 2018; Hasegawa et al., 2018) . Hence non-coding RNAs also presents as targets to modulate viral induced airway changes as a means of managing exacerbation of chronic airway inflammatory diseases. Other than miRNA modulation, other epigenetic modification such as DNA methylation may also play a role in exacerbation of chronic airway inflammatory diseases. Recent epigenetic studies have indicated the association of epigenetic modification and chronic airway inflammatory diseases, and that the nasal methylome was shown to be a sensitive marker for airway inflammatory changes (Cardenas et al., 2019; Gomez, 2019) . At the same time, it was also shown that viral infections such as RV and RSV alters DNA methylation and histone modifications in the airway epithelium which may alter inflammatory responses, driving chronic airway inflammatory diseases and exacerbations (McErlean et al., 2014; Pech et al., 2018; Caixia et al., 2019) . In addition, Spalluto et al. (2017) also showed that antiviral factors such as IFNγ epigenetically modifies the viral resistance of epithelial cells. Hence, this may indicate that infections such as RV and RSV that weakly induce antiviral responses may result in an altered inflammatory state contributing to further viral persistence and exacerbation of chronic airway inflammatory diseases (Spalluto et al., 2017) .
Finally, viral infection can result in enhanced production of reactive oxygen species (ROS), oxidative stress and mitochondrial dysfunction in the airway epithelium (Kim et al., 2018; Mishra et al., 2018; Wang et al., 2018) . The airway epithelium of patients with chronic airway inflammatory diseases are usually under a state of constant oxidative stress which sustains the inflammation in the airway (Barnes, 2017; van der Vliet et al., 2018) . Viral infections of the respiratory epithelium by viruses such as IFV, RV, RSV and HSV may trigger the further production of ROS as an antiviral mechanism Aizawa et al., 2018; Wang et al., 2018) . Moreover, infiltrating cells in response to the infection such as neutrophils will also trigger respiratory burst as a means of increasing the ROS in the infected region. The increased ROS and oxidative stress in the local environment may serve as a trigger to promote inflammation thereby aggravating the inflammation in the airway (Tiwari et al., 2002) . A summary of potential exacerbation mechanisms and the associated viruses is shown in Figure 2 and Table 1 .
While the mechanisms underlying the development and acute exacerbation of chronic airway inflammatory disease is extensively studied for ways to manage and control the disease, a viral infection does more than just causing an acute exacerbation in these patients. A viral-induced acute exacerbation not only induced and worsens the symptoms of the disease, but also may alter the management of the disease or confer resistance toward treatments that worked before. Hence, appreciation of the mechanisms of viral-induced acute exacerbations is of clinical significance to devise strategies to correct viral induce changes that may worsen chronic airway inflammatory disease symptoms. Further studies in natural exacerbations and in viral-challenge models using RNA-sequencing (RNA-seq) or single cell RNA-seq on a range of time-points may provide important information regarding viral pathogenesis and changes induced within the airway of chronic airway inflammatory disease patients to identify novel targets and pathway for improved management of the disease. Subsequent analysis of functions may use epithelial cell models such as the air-liquid interface, in vitro airway epithelial model that has been adapted to studying viral infection and the changes it induced in the airway (Yan et al., 2016; Boda et al., 2018; Tan et al., 2018a) . Animal-based diseased models have also been developed to identify systemic mechanisms of acute exacerbation (Shin, 2016; Gubernatorova et al., 2019; Tanner and Single, 2019) . Furthermore, the humanized mouse model that possess human immune cells may also serves to unravel the immune profile of a viral infection in healthy and diseased condition (Ito et al., 2019; Li and Di Santo, 2019) . For milder viruses, controlled in vivo human infections can be performed for the best mode of verification of the associations of the virus with the proposed mechanism of viral induced acute exacerbations . With the advent of suitable diseased models, the verification of the mechanisms will then provide the necessary continuation of improving the management of viral induced acute exacerbations.
In conclusion, viral-induced acute exacerbation of chronic airway inflammatory disease is a significant health and economic burden that needs to be addressed urgently. In view of the scarcity of antiviral-based preventative measures available for only a few viruses and vaccines that are only available for IFV infections, more alternative measures should be explored to improve the management of the disease. Alternative measures targeting novel viral-induced acute exacerbation mechanisms, especially in the upper airway, can serve as supplementary treatments of the currently available management strategies to augment their efficacy. New models including primary human bronchial or nasal epithelial cell cultures, organoids or precision cut lung slices from patients with airways disease rather than healthy subjects can be utilized to define exacerbation mechanisms. These mechanisms can then be validated in small clinical trials in patients with asthma or COPD. Having multiple means of treatment may also reduce the problems that arise from resistance development toward a specific treatment. | How will this review serve? | false | 3,893 | {
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1,719 | Virus-Vectored Influenza Virus Vaccines
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147686/
SHA: f6d2afb2ec44d8656972ea79f8a833143bbeb42b
Authors: Tripp, Ralph A.; Tompkins, S. Mark
Date: 2014-08-07
DOI: 10.3390/v6083055
License: cc-by
Abstract: Despite the availability of an inactivated vaccine that has been licensed for >50 years, the influenza virus continues to cause morbidity and mortality worldwide. Constant evolution of circulating influenza virus strains and the emergence of new strains diminishes the effectiveness of annual vaccines that rely on a match with circulating influenza strains. Thus, there is a continued need for new, efficacious vaccines conferring cross-clade protection to avoid the need for biannual reformulation of seasonal influenza vaccines. Recombinant virus-vectored vaccines are an appealing alternative to classical inactivated vaccines because virus vectors enable native expression of influenza antigens, even from virulent influenza viruses, while expressed in the context of the vector that can improve immunogenicity. In addition, a vectored vaccine often enables delivery of the vaccine to sites of inductive immunity such as the respiratory tract enabling protection from influenza virus infection. Moreover, the ability to readily manipulate virus vectors to produce novel influenza vaccines may provide the quickest path toward a universal vaccine protecting against all influenza viruses. This review will discuss experimental virus-vectored vaccines for use in humans, comparing them to licensed vaccines and the hurdles faced for licensure of these next-generation influenza virus vaccines.
Text: Seasonal influenza is a worldwide health problem causing high mobility and substantial mortality [1] [2] [3] [4] . Moreover, influenza infection often worsens preexisting medical conditions [5] [6] [7] . Vaccines against circulating influenza strains are available and updated annually, but many issues are still present, including low efficacy in the populations at greatest risk of complications from influenza virus infection, i.e., the young and elderly [8, 9] . Despite increasing vaccination rates, influenza-related hospitalizations are increasing [8, 10] , and substantial drug resistance has developed to two of the four currently approved anti-viral drugs [11, 12] . While adjuvants have the potential to improve efficacy and availability of current inactivated vaccines, live-attenuated and virus-vectored vaccines are still considered one of the best options for the induction of broad and efficacious immunity to the influenza virus [13] .
The general types of influenza vaccines available in the United States are trivalent inactivated influenza vaccine (TIV), quadrivalent influenza vaccine (QIV), and live attenuated influenza vaccine (LAIV; in trivalent and quadrivalent forms). There are three types of inactivated vaccines that include whole virus inactivated, split virus inactivated, and subunit vaccines. In split virus vaccines, the virus is disrupted by a detergent. In subunit vaccines, HA and NA have been further purified by removal of other viral components. TIV is administered intramuscularly and contains three or four inactivated viruses, i.e., two type A strains (H1 and H3) and one or two type B strains. TIV efficacy is measured by induction of humoral responses to the hemagglutinin (HA) protein, the major surface and attachment glycoprotein on influenza. Serum antibody responses to HA are measured by the hemagglutination-inhibition (HI) assay, and the strain-specific HI titer is considered the gold-standard correlate of immunity to influenza where a four-fold increase in titer post-vaccination, or a HI titer of ≥1:40 is considered protective [4, 14] . Protection against clinical disease is mainly conferred by serum antibodies; however, mucosal IgA antibodies also may contribute to resistance against infection. Split virus inactivated vaccines can induce neuraminidase (NA)-specific antibody responses [15] [16] [17] , and anti-NA antibodies have been associated with protection from infection in humans [18] [19] [20] [21] [22] . Currently, NA-specific antibody responses are not considered a correlate of protection [14] . LAIV is administered as a nasal spray and contains the same three or four influenza virus strains as inactivated vaccines but on an attenuated vaccine backbone [4] . LAIV are temperature-sensitive and cold-adapted so they do not replicate effectively at core body temperature, but replicate in the mucosa of the nasopharynx [23] . LAIV immunization induces serum antibody responses, mucosal antibody responses (IgA), and T cell responses. While robust serum antibody and nasal wash (mucosal) antibody responses are associated with protection from infection, other immune responses, such as CD8 + cytotoxic lymphocyte (CTL) responses may contribute to protection and there is not a clear correlate of immunity for LAIV [4, 14, 24] .
Currently licensed influenza virus vaccines suffer from a number of issues. The inactivated vaccines rely on specific antibody responses to the HA, and to a lesser extent NA proteins for protection. The immunodominant portions of the HA and NA molecules undergo a constant process of antigenic drift, a natural accumulation of mutations, enabling virus evasion from immunity [9, 25] . Thus, the circulating influenza A and B strains are reviewed annually for antigenic match with current vaccines, Replacement of vaccine strains may occur regularly, and annual vaccination is recommended to assure protection [4, 26, 27] . For the northern hemisphere, vaccine strain selection occurs in February and then manufacturers begin production, taking at least six months to produce the millions of vaccine doses required for the fall [27] . If the prediction is imperfect, or if manufacturers have issues with vaccine production, vaccine efficacy or availability can be compromised [28] . LAIV is not recommended for all populations; however, it is generally considered to be as effective as inactivated vaccines and may be more efficacious in children [4, 9, 24] . While LAIV relies on antigenic match and the HA and NA antigens are replaced on the same schedule as the TIV [4, 9] , there is some suggestion that LAIV may induce broader protection than TIV due to the diversity of the immune response consistent with inducing virus-neutralizing serum and mucosal antibodies, as well as broadly reactive T cell responses [9, 23, 29] . While overall both TIV and LAIV are considered safe and effective, there is a recognized need for improved seasonal influenza vaccines [26] . Moreover, improved understanding of immunity to conserved influenza virus antigens has raised the possibility of a universal vaccine, and these universal antigens will likely require novel vaccines for effective delivery [30] [31] [32] .
Virus-vectored vaccines share many of the advantages of LAIV, as well as those unique to the vectors. Recombinant DNA systems exist that allow ready manipulation and modification of the vector genome. This in turn enables modification of the vectors to attenuate the virus or enhance immunogenicity, in addition to adding and manipulating the influenza virus antigens. Many of these vectors have been extensively studied or used as vaccines against wild type forms of the virus. Finally, each of these vaccine vectors is either replication-defective or causes a self-limiting infection, although like LAIV, safety in immunocompromised individuals still remains a concern [4, 13, [33] [34] [35] . Table 1 summarizes the benefits and concerns of each of the virus-vectored vaccines discussed here.
There are 53 serotypes of adenovirus, many of which have been explored as vaccine vectors. A live adenovirus vaccine containing serotypes 4 and 7 has been in use by the military for decades, suggesting adenoviruses may be safe for widespread vaccine use [36] . However, safety concerns have led to the majority of adenovirus-based vaccine development to focus on replication-defective vectors. Adenovirus 5 (Ad5) is the most-studied serotype, having been tested for gene delivery and anti-cancer agents, as well as for infectious disease vaccines.
Adenovirus vectors are attractive as vaccine vectors because their genome is very stable and there are a variety of recombinant systems available which can accommodate up to 10 kb of recombinant genetic material [37] . Adenovirus is a non-enveloped virus which is relatively stable and can be formulated for long-term storage at 4 °C, or even storage up to six months at room temperature [33] . Adenovirus vaccines can be grown to high titers, exceeding 10 1° plaque forming units (PFU) per mL when cultured on 293 or PER.C6 cells [38] , and the virus can be purified by simple methods [39] . Adenovirus vaccines can also be delivered via multiple routes, including intramuscular injection, subcutaneous injection, intradermal injection, oral delivery using a protective capsule, and by intranasal delivery. Importantly, the latter two delivery methods induce robust mucosal immune responses and may bypass preexisting vector immunity [33] . Even replication-defective adenovirus vectors are naturally immunostimulatory and effective adjuvants to the recombinant antigen being delivered. Adenovirus has been extensively studied as a vaccine vector for human disease. The first report using adenovirus as a vaccine vector for influenza demonstrated immunogenicity of recombinant adenovirus 5 (rAd5) expressing the HA of a swine influenza virus, A/Swine/Iowa/1999 (H3N2). Intramuscular immunization of mice with this construct induced robust neutralizing antibody responses and protected mice from challenge with a heterologous virus, A/Hong Kong/1/1968 (H3N2) [40] . Replication defective rAd5 vaccines expressing influenza HA have also been tested in humans. A rAd5-HA expressing the HA from A/Puerto Rico/8/1934 (H1N1; PR8) was delivered to humans epicutaneously or intranasally and assayed for safety and immunogenicity. The vaccine was well tolerated and induced seroconversion with the intranasal administration had a higher conversion rate and higher geometric meant HI titers [41] . While clinical trials with rAd vectors have overall been successful, demonstrating safety and some level of efficacy, rAd5 as a vector has been negatively overshadowed by two clinical trial failures. The first trial was a gene therapy examination where high-dose intravenous delivery of an Ad vector resulted in the death of an 18-year-old male [42, 43] . The second clinical failure was using an Ad5-vectored HIV vaccine being tested as a part of a Step Study, a phase 2B clinical trial. In this study, individuals were vaccinated with the Ad5 vaccine vector expressing HIV-1 gag, pol, and nef genes. The vaccine induced HIV-specific T cell responses; however, the study was stopped after interim analysis suggested the vaccine did not achieve efficacy and individuals with high preexisting Ad5 antibody titers might have an increased risk of acquiring HIV-1 [44] [45] [46] . Subsequently, the rAd5 vaccine-associated risk was confirmed [47] . While these two instances do not suggest Ad-vector vaccines are unsafe or inefficacious, the umbra cast by the clinical trials notes has affected interest for all adenovirus vaccines, but interest still remains.
Immunization with adenovirus vectors induces potent cellular and humoral immune responses that are initiated through toll-like receptor-dependent and independent pathways which induce robust pro-inflammatory cytokine responses. Recombinant Ad vaccines expressing HA antigens from pandemic H1N1 (pH1N1), H5 and H7 highly pathogenic avian influenza (HPAI) virus (HPAIV), and H9 avian influenza viruses have been tested for efficacy in a number of animal models, including chickens, mice, and ferrets, and been shown to be efficacious and provide protection from challenge [48, 49] . Several rAd5 vectors have been explored for delivery of non-HA antigens, influenza nucleoprotein (NP) and matrix 2 (M2) protein [29, [50] [51] [52] . The efficacy of non-HA antigens has led to their inclusion with HA-based vaccines to improve immunogenicity and broaden breadth of both humoral and cellular immunity [53, 54] . However, as both CD8 + T cell and neutralizing antibody responses are generated by the vector and vaccine antigens, immunological memory to these components can reduce efficacy and limit repeated use [48] .
One drawback of an Ad5 vector is the potential for preexisting immunity, so alternative adenovirus serotypes have been explored as vectors, particularly non-human and uncommon human serotypes. Non-human adenovirus vectors include those from non-human primates (NHP), dogs, sheep, pigs, cows, birds and others [48, 55] . These vectors can infect a variety of cell types, but are generally attenuated in humans avoiding concerns of preexisting immunity. Swine, NHP and bovine adenoviruses expressing H5 HA antigens have been shown to induce immunity comparable to human rAd5-H5 vaccines [33, 56] . Recombinant, replication-defective adenoviruses from low-prevalence serotypes have also been shown to be efficacious. Low prevalence serotypes such as adenovirus types 3, 7, 11, and 35 can evade anti-Ad5 immune responses while maintaining effective antigen delivery and immunogenicity [48, 57] . Prime-boost strategies, using DNA or protein immunization in conjunction with an adenovirus vaccine booster immunization have also been explored as a means to avoided preexisting immunity [52] .
Adeno-associated viruses (AAV) were first explored as gene therapy vectors. Like rAd vectors, rAAV have broad tropism infecting a variety of hosts, tissues, and proliferating and non-proliferating cell types [58] . AAVs had been generally not considered as vaccine vectors because they were widely considered to be poorly immunogenic. A seminal study using AAV-2 to express a HSV-2 glycoprotein showed this virus vaccine vector effectively induced potent CD8 + T cell and serum antibody responses, thereby opening the door to other rAAV vaccine-associated studies [59, 60] .
AAV vector systems have a number of engaging properties. The wild type viruses are non-pathogenic and replication incompetent in humans and the recombinant AAV vector systems are even further attenuated [61] . As members of the parvovirus family, AAVs are small non-enveloped viruses that are stable and amenable to long-term storage without a cold chain. While there is limited preexisting immunity, availability of non-human strains as vaccine candidates eliminates these concerns. Modifications to the vector have increased immunogenicity, as well [60] .
There are limited studies using AAVs as vaccine vectors for influenza. An AAV expressing an HA antigen was first shown to induce protective in 2001 [62] . Later, a hybrid AAV derived from two non-human primate isolates (AAVrh32.33) was used to express influenza NP and protect against PR8 challenge in mice [63] . Most recently, following the 2009 H1N1 influenza virus pandemic, rAAV vectors were generated expressing the HA, NP and matrix 1 (M1) proteins of A/Mexico/4603/2009 (pH1N1), and in murine immunization and challenge studies, the rAAV-HA and rAAV-NP were shown to be protective; however, mice vaccinated with rAAV-HA + NP + M1 had the most robust protection. Also, mice vaccinated with rAAV-HA + rAAV-NP + rAAV-M1 were also partially protected against heterologous (PR8, H1N1) challenge [63] . Most recently, an AAV vector was used to deliver passive immunity to influenza [64, 65] . In these studies, AAV (AAV8 and AAV9) was used to deliver an antibody transgene encoding a broadly cross-protective anti-influenza monoclonal antibody for in vivo expression. Both intramuscular and intranasal delivery of the AAVs was shown to protect against a number of influenza virus challenges in mice and ferrets, including H1N1 and H5N1 viruses [64, 65] . These studies suggest that rAAV vectors are promising vaccine and immunoprophylaxis vectors. To this point, while approximately 80 phase I, I/II, II, or III rAAV clinical trials are open, completed, or being reviewed, these have focused upon gene transfer studies and so there is as yet limited safety data for use of rAAV as vaccines [66] .
Alphaviruses are positive-sense, single-stranded RNA viruses of the Togaviridae family. A variety of alphaviruses have been developed as vaccine vectors, including Semliki Forest virus (SFV), Sindbis (SIN) virus, Venezuelan equine encephalitis (VEE) virus, as well as chimeric viruses incorporating portions of SIN and VEE viruses. The replication defective vaccines or replicons do not encode viral structural proteins, having these portions of the genome replaces with transgenic material.
The structural proteins are provided in cell culture production systems. One important feature of the replicon systems is the self-replicating nature of the RNA. Despite the partial viral genome, the RNAs are self-replicating and can express transgenes at very high levels [67] .
SIN, SFV, and VEE have all been tested for efficacy as vaccine vectors for influenza virus [68] [69] [70] [71] . A VEE-based replicon system encoding the HA from PR8 was demonstrated to induce potent HA-specific immune response and protected from challenge in a murine model, despite repeated immunization with the vector expressing a control antigen, suggesting preexisting immunity may not be an issue for the replicon vaccine [68] . A separate study developed a VEE replicon system expressing the HA from A/Hong Kong/156/1997 (H5N1) and demonstrated varying efficacy after in ovo vaccination or vaccination of 1-day-old chicks [70] . A recombinant SIN virus was use as a vaccine vector to deliver a CD8 + T cell epitope only. The well-characterized NP epitope was transgenically expressed in the SIN system and shown to be immunogenic in mice, priming a robust CD8 + T cell response and reducing influenza virus titer after challenge [69] . More recently, a VEE replicon system expressing the HA protein of PR8 was shown to protect young adult (8-week-old) and aged (12-month-old) mice from lethal homologous challenge [72] .
The VEE replicon systems are particularly appealing as the VEE targets antigen-presenting cells in the lymphatic tissues, priming rapid and robust immune responses [73] . VEE replicon systems can induce robust mucosal immune responses through intranasal or subcutaneous immunization [72] [73] [74] , and subcutaneous immunization with virus-like replicon particles (VRP) expressing HA-induced antigen-specific systemic IgG and fecal IgA antibodies [74] . VRPs derived from VEE virus have been developed as candidate vaccines for cytomegalovirus (CMV). A phase I clinical trial with the CMV VRP showed the vaccine was immunogenic, inducing CMV-neutralizing antibody responses and potent T cell responses. Moreover, the vaccine was well tolerated and considered safe [75] . A separate clinical trial assessed efficacy of repeated immunization with a VRP expressing a tumor antigen. The vaccine was safe and despite high vector-specific immunity after initial immunization, continued to boost transgene-specific immune responses upon boost [76] . While additional clinical data is needed, these reports suggest alphavirus replicon systems or VRPs may be safe and efficacious, even in the face of preexisting immunity.
Baculovirus has been extensively used to produce recombinant proteins. Recently, a baculovirus-derived recombinant HA vaccine was approved for human use and was first available for use in the United States for the 2013-2014 influenza season [4] . Baculoviruses have also been explored as vaccine vectors. Baculoviruses have a number of advantages as vaccine vectors. The viruses have been extensively studied for protein expression and for pesticide use and so are readily manipulated. The vectors can accommodate large gene insertions, show limited cytopathic effect in mammalian cells, and have been shown to infect and express genes of interest in a spectrum of mammalian cells [77] . While the insect promoters are not effective for mammalian gene expression, appropriate promoters can be cloned into the baculovirus vaccine vectors.
Baculovirus vectors have been tested as influenza vaccines, with the first reported vaccine using Autographa californica nuclear polyhedrosis virus (AcNPV) expressing the HA of PR8 under control of the CAG promoter (AcCAG-HA) [77] . Intramuscular, intranasal, intradermal, and intraperitoneal immunization or mice with AcCAG-HA elicited HA-specific antibody responses, however only intranasal immunization provided protection from lethal challenge. Interestingly, intranasal immunization with the wild type AcNPV also resulted in protection from PR8 challenge. The robust innate immune response to the baculovirus provided non-specific protection from subsequent influenza virus infection [78] . While these studies did not demonstrate specific protection, there were antigen-specific immune responses and potential adjuvant effects by the innate response.
Baculovirus pseudotype viruses have also been explored. The G protein of vesicular stomatitis virus controlled by the insect polyhedron promoter and the HA of A/Chicken/Hubei/327/2004 (H5N1) HPAIV controlled by a CMV promoter were used to generate the BV-G-HA. Intramuscular immunization of mice or chickens with BV-G-HA elicited strong HI and VN serum antibody responses, IFN-γ responses, and protected from H5N1 challenge [79] . A separate study demonstrated efficacy using a bivalent pseudotyped baculovirus vector [80] .
Baculovirus has also been used to generate an inactivated particle vaccine. The HA of A/Indonesia/CDC669/2006(H5N1) was incorporated into a commercial baculovirus vector controlled by the e1 promoter from White Spot Syndrome Virus. The resulting recombinant virus was propagated in insect (Sf9) cells and inactivated as a particle vaccine [81, 82] . Intranasal delivery with cholera toxin B as an adjuvant elicited robust HI titers and protected from lethal challenge [81] . Oral delivery of this encapsulated vaccine induced robust serum HI titers and mucosal IgA titers in mice, and protected from H5N1 HPAIV challenge. More recently, co-formulations of inactivated baculovirus vectors have also been shown to be effective in mice [83] .
While there is growing data on the potential use of baculovirus or pseudotyped baculovirus as a vaccine vector, efficacy data in mammalian animal models other than mice is lacking. There is also no data on the safety in humans, reducing enthusiasm for baculovirus as a vaccine vector for influenza at this time.
Newcastle disease virus (NDV) is a single-stranded, negative-sense RNA virus that causes disease in poultry. NDV has a number of appealing qualities as a vaccine vector. As an avian virus, there is little or no preexisting immunity to NDV in humans and NDV propagates to high titers in both chicken eggs and cell culture. As a paramyxovirus, there is no DNA phase in the virus lifecycle reducing concerns of integration events, and the levels of gene expression are driven by the proximity to the leader sequence at the 3' end of the viral genome. This gradient of gene expression enables attenuation through rearrangement of the genome, or by insertion of transgenes within the genome. Finally, pathogenicity of NDV is largely determined by features of the fusion protein enabling ready attenuation of the vaccine vector [84] .
Reverse genetics, a method that allows NDV to be rescued from plasmids expressing the viral RNA polymerase and nucleocapsid proteins, was first reported in 1999 [85, 86] . This process has enabled manipulation of the NDV genome as well as incorporation of transgenes and the development of NDV vectors. Influenza was the first infectious disease targeted with a recombinant NDV (rNDV) vector. The HA protein of A/WSN/1933 (H1N1) was inserted into the Hitchner B1 vaccine strain. The HA protein was expressed on infected cells and was incorporated into infectious virions. While the virus was attenuated compared to the parental vaccine strain, it induced a robust serum antibody response and protected against homologous influenza virus challenge in a murine model of infection [87] . Subsequently, rNDV was tested as a vaccine vector for HPAIV having varying efficacy against H5 and H7 influenza virus infections in poultry [88] [89] [90] [91] [92] [93] [94] . These vaccines have the added benefit of potentially providing protection against both the influenza virus and NDV infection.
NDV has also been explored as a vaccine vector for humans. Two NHP studies assessed the immunogenicity and efficacy of an rNDV expressing the HA or NA of A/Vietnam/1203/2004 (H5N1; VN1203) [95, 96] . Intranasal and intratracheal delivery of the rNDV-HA or rNDV-NA vaccines induced both serum and mucosal antibody responses and protected from HPAIV challenge [95, 96] . NDV has limited clinical data; however, phase I and phase I/II clinical trials have shown that the NDV vector is well-tolerated, even at high doses delivered intravenously [44, 97] . While these results are promising, additional studies are needed to advance NDV as a human vaccine vector for influenza.
Parainfluenza virus type 5 (PIV5) is a paramyxovirus vaccine vector being explored for delivery of influenza and other infectious disease vaccine antigens. PIV5 has only recently been described as a vaccine vector [98] . Similar to other RNA viruses, PIV5 has a number of features that make it an attractive vaccine vector. For example, PIV5 has a stable RNA genome and no DNA phase in virus replication cycle reducing concerns of host genome integration or modification. PIV5 can be grown to very high titers in mammalian vaccine cell culture substrates and is not cytopathic allowing for extended culture and harvest of vaccine virus [98, 99] . Like NDV, PIV5 has a 3'-to 5' gradient of gene expression and insertion of transgenes at different locations in the genome can variably attenuate the virus and alter transgene expression [100] . PIV5 has broad tropism, infecting many cell types, tissues, and species without causing clinical disease, although PIV5 has been associated with -kennel cough‖ in dogs [99] . A reverse genetics system for PIV5 was first used to insert the HA gene from A/Udorn/307/72 (H3N2) into the PIV5 genome between the hemagglutinin-neuraminidase (HN) gene and the large (L) polymerase gene. Similar to NDV, the HA was expressed at high levels in infected cells and replicated similarly to the wild type virus, and importantly, was not pathogenic in immunodeficient mice [98] . Additionally, a single intranasal immunization in a murine model of influenza infection was shown to induce neutralizing antibody responses and protect against a virus expressing homologous HA protein [98] . PIV5 has also been explored as a vaccine against HPAIV. Recombinant PIV5 vaccines expressing the HA or NP from VN1203 were tested for efficacy in a murine challenge model. Mice intranasally vaccinated with a single dose of PIV5-H5 vaccine had robust serum and mucosal antibody responses, and were protected from lethal challenge. Notably, although cellular immune responses appeared to contribute to protection, serum antibody was sufficient for protection from challenge [100, 101] . Intramuscular immunization with PIV5-H5 was also shown to be effective at inducing neutralizing antibody responses and protecting against lethal influenza virus challenge [101] . PIV5 expressing the NP protein of HPAIV was also efficacious in the murine immunization and challenge model, where a single intranasal immunization induced robust CD8 + T cell responses and protected against homologous (H5N1) and heterosubtypic (H1N1) virus challenge [102] .
Currently there is no clinical safety data for use of PIV5 in humans. However, live PIV5 has been a component of veterinary vaccines for -kennel cough‖ for >30 years, and veterinarians and dog owners are exposed to live PIV5 without reported disease [99] . This combined with preclinical data from a variety of animal models suggests that PIV5 as a vector is likely to be safe in humans. As preexisting immunity is a concern for all virus-vectored vaccines, it should be noted that there is no data on the levels of preexisting immunity to PIV5 in humans. However, a study evaluating the efficacy of a PIV5-H3 vaccine in canines previously vaccinated against PIV5 (kennel cough) showed induction of robust anti-H3 serum antibody responses as well as high serum antibody levels to the PIV5 vaccine, suggesting preexisting immunity to the PIV5 vector may not affect immunogenicity of vaccines even with repeated use [99] .
Poxvirus vaccines have a long history and the notable hallmark of being responsible for eradication of smallpox. The termination of the smallpox virus vaccination program has resulted in a large population of poxvirus-naï ve individuals that provides the opportunity for the use of poxviruses as vectors without preexisting immunity concerns [103] . Poxvirus-vectored vaccines were first proposed for use in 1982 with two reports of recombinant vaccinia viruses encoding and expressing functional thymidine kinase gene from herpes virus [104, 105] . Within a year, a vaccinia virus encoding the HA of an H2N2 virus was shown to express a functional HA protein (cleaved in the HA1 and HA2 subunits) and be immunogenic in rabbits and hamsters [106] . Subsequently, all ten of the primary influenza proteins have been expressed in vaccine virus [107] .
Early work with intact vaccinia virus vectors raised safety concerns, as there was substantial reactogenicity that hindered recombinant vaccine development [108] . Two vaccinia vectors were developed to address these safety concerns. The modified vaccinia virus Ankara (MVA) strain was attenuated by passage 530 times in chick embryo fibroblasts cultures. The second, New York vaccinia virus (NYVAC) was a plaque-purified clone of the Copenhagen vaccine strain rationally attenuated by deletion of 18 open reading frames [109] [110] [111] .
Modified vaccinia virus Ankara (MVA) was developed prior to smallpox eradication to reduce or prevent adverse effects of other smallpox vaccines [109] . Serial tissue culture passage of MVA resulted in loss of 15% of the genome, and established a growth restriction for avian cells. The defects affected late stages in virus assembly in non-avian cells, a feature enabling use of the vector as single-round expression vector in non-permissive hosts. Interestingly, over two decades ago, recombinant MVA expressing the HA and NP of influenza virus was shown to be effective against lethal influenza virus challenge in a murine model [112] . Subsequently, MVA expressing various antigens from seasonal, pandemic (A/California/04/2009, pH1N1), equine (A/Equine/Kentucky/1/81 H3N8), and HPAI (VN1203) viruses have been shown to be efficacious in murine, ferret, NHP, and equine challenge models [113] . MVA vaccines are very effective stimulators of both cellular and humoral immunity. For example, abortive infection provides native expression of the influenza antigens enabling robust antibody responses to native surface viral antigens. Concurrently, the intracellular influenza peptides expressed by the pox vector enter the class I MHC antigen processing and presentation pathway enabling induction of CD8 + T cell antiviral responses. MVA also induces CD4 + T cell responses further contributing to the magnitude of the antigen-specific effector functions [107, [112] [113] [114] [115] . MVA is also a potent activator of early innate immune responses further enhancing adaptive immune responses [116] . Between early smallpox vaccine development and more recent vaccine vector development, MVA has undergone extensive safety testing and shown to be attenuated in severely immunocompromised animals and safe for use in children, adults, elderly, and immunocompromised persons. With extensive pre-clinical data, recombinant MVA vaccines expressing influenza antigens have been tested in clinical trials and been shown to be safe and immunogenic in humans [117] [118] [119] . These results combined with data from other (non-influenza) clinical and pre-clinical studies support MVA as a leading viral-vectored candidate vaccine.
The NYVAC vector is a highly attenuated vaccinia virus strain. NYVAC is replication-restricted; however, it grows in chick embryo fibroblasts and Vero cells enabling vaccine-scale production. In non-permissive cells, critical late structural proteins are not produced stopping replication at the immature virion stage [120] . NYVAC is very attenuated and considered safe for use in humans of all ages; however, it predominantly induces a CD4 + T cell response which is different compared to MVA [114] . Both MVA and NYVAC provoke robust humoral responses, and can be delivered mucosally to induce mucosal antibody responses [121] . There has been only limited exploration of NYVAC as a vaccine vector for influenza virus; however, a vaccine expressing the HA from A/chicken/Indonesia/7/2003 (H5N1) was shown to induce potent neutralizing antibody responses and protect against challenge in swine [122] .
While there is strong safety and efficacy data for use of NYVAC or MVA-vectored influenza vaccines, preexisting immunity remains a concern. Although the smallpox vaccination campaign has resulted in a population of poxvirus-naï ve people, the initiation of an MVA or NYVAC vaccination program for HIV, influenza or other pathogens will rapidly reduce this susceptible population. While there is significant interest in development of pox-vectored influenza virus vaccines, current influenza vaccination strategies rely upon regular immunization with vaccines matched to circulating strains. This would likely limit the use and/or efficacy of poxvirus-vectored influenza virus vaccines for regular and seasonal use [13] . Intriguingly, NYVAC may have an advantage for use as an influenza vaccine vector, because immunization with this vector induces weaker vaccine-specific immune responses compared to other poxvirus vaccines, a feature that may address the concerns surrounding preexisting immunity [123] .
While poxvirus-vectored vaccines have not yet been approved for use in humans, there is a growing list of licensed poxvirus for veterinary use that include fowlpox-and canarypox-vectored vaccines for avian and equine influenza viruses, respectively [124, 125] . The fowlpox-vectored vaccine expressing the avian influenza virus HA antigen has the added benefit of providing protection against fowlpox infection. Currently, at least ten poxvirus-vectored vaccines have been licensed for veterinary use [126] . These poxvirus vectors have the potential for use as vaccine vectors in humans, similar to the first use of cowpox for vaccination against smallpox [127] . The availability of these non-human poxvirus vectors with extensive animal safety and efficacy data may address the issues with preexisting immunity to the human vaccine strains, although the cross-reactivity originally described with cowpox could also limit use.
Influenza vaccines utilizing vesicular stomatitis virus (VSV), a rhabdovirus, as a vaccine vector have a number of advantages shared with other RNA virus vaccine vectors. Both live and replication-defective VSV vaccine vectors have been shown to be immunogenic [128, 129] , and like Paramyxoviridae, the Rhabdoviridae genome has a 3'-to-5' gradient of gene expression enabling attention by selective vaccine gene insertion or genome rearrangement [130] . VSV has a number of other advantages including broad tissue tropism, and the potential for intramuscular or intranasal immunization. The latter delivery method enables induction of mucosal immunity and elimination of needles required for vaccination. Also, there is little evidence of VSV seropositivity in humans eliminating concerns of preexisting immunity, although repeated use may be a concern. Also, VSV vaccine can be produced using existing mammalian vaccine manufacturing cell lines.
Influenza antigens were first expressed in a VSV vector in 1997. Both the HA and NA were shown to be expressed as functional proteins and incorporated into the recombinant VSV particles [131] . Subsequently, VSV-HA, expressing the HA protein from A/WSN/1933 (H1N1) was shown to be immunogenic and protect mice from lethal influenza virus challenge [129] . To reduce safety concerns, attenuated VSV vectors were developed. One candidate vaccine had a truncated VSV G protein, while a second candidate was deficient in G protein expression and relied on G protein expressed by a helper vaccine cell line to the provide the virus receptor. Both vectors were found to be attenuated in mice, but maintained immunogenicity [128] . More recently, single-cycle replicating VSV vaccines have been tested for efficacy against H5N1 HPAIV. VSV vectors expressing the HA from A/Hong Kong/156/97 (H5N1) were shown to be immunogenic and induce cross-reactive antibody responses and protect against challenge with heterologous H5N1 challenge in murine and NHP models [132] [133] [134] .
VSV vectors are not without potential concerns. VSV can cause disease in a number of species, including humans [135] . The virus is also potentially neuroinvasive in some species [136] , although NHP studies suggest this is not a concern in humans [137] . Also, while the incorporation of the influenza antigen in to the virion may provide some benefit in immunogenicity, changes in tropism or attenuation could arise from incorporation of different influenza glycoproteins. There is no evidence for this, however [134] . Currently, there is no human safety data for VSV-vectored vaccines. While experimental data is promising, additional work is needed before consideration for human influenza vaccination.
Current influenza vaccines rely on matching the HA antigen of the vaccine with circulating strains to provide strain-specific neutralizing antibody responses [4, 14, 24] . There is significant interest in developing universal influenza vaccines that would not require annual reformulation to provide protective robust and durable immunity. These vaccines rely on generating focused immune responses to highly conserved portions of the virus that are refractory to mutation [30] [31] [32] . Traditional vaccines may not be suitable for these vaccination strategies; however, vectored vaccines that have the ability to be readily modified and to express transgenes are compatible for these applications.
The NP and M2 proteins have been explored as universal vaccine antigens for decades. Early work with recombinant viral vectors demonstrated that immunization with vaccines expressing influenza antigens induced potent CD8 + T cell responses [107, [138] [139] [140] [141] . These responses, even to the HA antigen, could be cross-protective [138] . A number of studies have shown that immunization with NP expressed by AAV, rAd5, alphavirus vectors, MVA, or other vector systems induces potent CD8 + T cell responses and protects against influenza virus challenge [52, 63, 69, 102, 139, 142] . As the NP protein is highly conserved across influenza A viruses, NP-specific T cells can protect against heterologous and even heterosubtypic virus challenges [30] .
The M2 protein is also highly conserved and expressed on the surface of infected cells, although to a lesser extent on the surface of virus particles [30] . Much of the vaccine work in this area has focused on virus-like or subunit particles expressing the M2 ectodomain; however, studies utilizing a DNA-prime, rAd-boost strategies to vaccinate against the entire M2 protein have shown the antigen to be immunogenic and protective [50] . In these studies, antibodies to the M2 protein protected against homologous and heterosubtypic challenge, including a H5N1 HPAIV challenge. More recently, NP and M2 have been combined to induce broadly cross-reactive CD8 + T cell and antibody responses, and rAd5 vaccines expressing these antigens have been shown to protect against pH1N1 and H5N1 challenges [29, 51] .
Historically, the HA has not been widely considered as a universal vaccine antigen. However, the recent identification of virus neutralizing monoclonal antibodies that cross-react with many subtypes of influenza virus [143] has presented the opportunity to design vaccine antigens to prime focused antibody responses to the highly conserved regions recognized by these monoclonal antibodies. The majority of these broadly cross-reactive antibodies recognize regions on the stalk of the HA protein [143] . The HA stalk is generally less immunogenic compared to the globular head of the HA protein so most approaches have utilized -headless‖ HA proteins as immunogens. HA stalk vaccines have been designed using DNA and virus-like particles [144] and MVA [142] ; however, these approaches are amenable to expression in any of the viruses vectors described here.
The goal of any vaccine is to protect against infection and disease, while inducing population-based immunity to reduce or eliminate virus transmission within the population. It is clear that currently licensed influenza vaccines have not fully met these goals, nor those specific to inducing long-term, robust immunity. There are a number of vaccine-related issues that must be addressed before population-based influenza vaccination strategies are optimized. The concept of a -one size fits all‖ vaccine needs to be updated, given the recent ability to probe the virus-host interface through RNA interference approaches that facilitate the identification of host genes affecting virus replication, immunity, and disease. There is also a need for revision of the current influenza virus vaccine strategies for at-risk populations, particularly those at either end of the age spectrum. An example of an improved vaccine regime might include the use of a vectored influenza virus vaccine that expresses the HA, NA and M and/or NP proteins for the two currently circulating influenza A subtypes and both influenza B strains so that vaccine take and vaccine antigen levels are not an issue in inducing protective immunity. Recombinant live-attenuated or replication-deficient influenza viruses may offer an advantage for this and other approaches.
Vectored vaccines can be constructed to express full-length influenza virus proteins, as well as generate conformationally restricted epitopes, features critical in generating appropriate humoral protection. Inclusion of internal influenza antigens in a vectored vaccine can also induce high levels of protective cellular immunity. To generate sustained immunity, it is an advantage to induce immunity at sites of inductive immunity to natural infection, in this case the respiratory tract. Several vectored vaccines target the respiratory tract. Typically, vectored vaccines generate antigen for weeks after immunization, in contrast to subunit vaccination. This increased presence and level of vaccine antigen contributes to and helps sustain a durable memory immune response, even augmenting the selection of higher affinity antibody secreting cells. The enhanced memory response is in part linked to the intrinsic augmentation of immunity induced by the vector. Thus, for weaker antigens typical of HA, vectored vaccines have the capacity to overcome real limitations in achieving robust and durable protection.
Meeting the mandates of seasonal influenza vaccine development is difficult, and to respond to a pandemic strain is even more challenging. Issues with influenza vaccine strain selection based on recently circulating viruses often reflect recommendations by the World Health Organization (WHO)-a process that is cumbersome. The strains of influenza A viruses to be used in vaccine manufacture are not wild-type viruses but rather reassortants that are hybrid viruses containing at least the HA and NA gene segments from the target strains and other gene segments from the master strain, PR8, which has properties of high growth in fertilized hen's eggs. This additional process requires more time and quality control, and specifically for HPAI viruses, it is a process that may fail because of the nature of those viruses. In contrast, viral-vectored vaccines are relatively easy to manipulate and produce, and have well-established safety profiles. There are several viral-based vectors currently employed as antigen delivery systems, including poxviruses, adenoviruses baculovirus, paramyxovirus, rhabdovirus, and others; however, the majority of human clinical trials assessing viral-vectored influenza vaccines use poxvirus and adenovirus vectors. While each of these vector approaches has unique features and is in different stages of development, the combined successes of these approaches supports the virus-vectored vaccine approach as a whole. Issues such as preexisting immunity and cold chain requirements, and lingering safety concerns will have to be overcome; however, each approach is making progress in addressing these issues, and all of the approaches are still viable. Virus-vectored vaccines hold particular promise for vaccination with universal or focused antigens where traditional vaccination methods are not suited to efficacious delivery of these antigens. The most promising approaches currently in development are arguably those targeting conserved HA stalk region epitopes. Given the findings to date, virus-vectored vaccines hold great promise and may overcome the current limitations of influenza vaccines. | What has raised the possibility of universal influenza vaccine? | false | 1,491 | {
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1,586 | In Vitro Bactericidal Activity of 4- and 5-Chloro-2-hydroxy-N-[1-oxo-1-(phenylamino)alkan-2-yl]benzamides against MRSA
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4321674/
SHA: f0e6cef57dbae030aea2f324e21e00945ac659cf
Authors: Zadrazilova, Iveta; Pospisilova, Sarka; Pauk, Karel; Imramovsky, Ales; Vinsova, Jarmila; Cizek, Alois; Jampilek, Josef
Date: 2015-01-15
DOI: 10.1155/2015/349534
License: cc-by
Abstract: A series of nine substituted 2-hydroxy-N-[1-oxo-1-(phenylamino)alkan-2-yl]benzamides was assessed as prospective bactericidal agents against three clinical isolates of methicillin-resistant Staphylococcus aureus (MRSA) and S. aureus ATCC 29213 as the reference and quality control strain. The minimum bactericidal concentration was determined by subculturing aliquots from MIC determination onto substance-free agar plates. The bactericidal kinetics of compounds 5-chloro-2-hydroxy-N-[(2S)-3-methyl-1-oxo-1-{[4-(trifluoromethyl)phenyl]amino}butan-2-yl]benzamide (1f), N-{(2S)-1-[(4-bromophenyl)amino]-3-methyl-1-oxobutan-2-yl}-4-chloro-2-hydroxybenzamide (1g), and 4-chloro-N-{(2S)-1-[(3,4-dichlorophenyl)amino]-3-methyl-1-oxobutan-2-yl}-2-hydroxybenzamide (1h) was established by time-kill assay with a final concentration of the compound equal to 1x, 2x, and 4x MIC; aliquots were removed at 0, 4, 6, 8, and 24 h time points. The most potent bactericidal agent was compound 1f exhibiting remarkable rapid concentration-dependent bactericidal effect even at 2x MIC at 4, 6, and 8 h (with a reduction in bacterial count ranging from 3.08 to 3.75 log(10) CFU/mL) and at 4x MIC at 4, 6, 8, and 24 h (5.30 log(10) CFU/mL reduction in bacterial count) after incubation against MRSA 63718. Reliable bactericidal effect against other strains was maintained at 4x MIC at 24 h.
Text: The antibiotic resistance of invasive pathogens has become one of the most challenging and persistent health problems [1] . Methicillin-resistant Staphylococcus aureus (MRSA) has become the most common clinically relevant multiresistant pathogen [2] causing both healthcare-associated and community-acquired bloodstream infections with mortality rates up to 40% [3] .
The prevalence of MRSA is increasing worldwide and, according to the latest information of the European Centre for Disease Prevention and Control from 2012 [4] , can be considered alarming in some European countries, especially in Portugal and Romania, where ≥50% of all S. aureus isolates from invasive infections were identified as MRSA in 2012 (although, e.g., in Romania the prevalence of MRSA was 25-50% in 2010), followed by Italy, Greece, and Poland with 25-50% isolates being MRSA in 2012 (for comparison, in Poland MRSA isolates constituted 10-25% from all S. aureus isolates in 2010).
The treatment failure of vancomycin, the therapeutic anti-MRSA agent of choice, due to the strains with elevated vancomycin minimum inhibitory concentration (MIC) values (i.e., the lowest concentration of an antimicrobial that will inhibit the visible growth of a microorganism) within the susceptible range was described previously [5, 6] . Thus, the emergence of MRSA (and vancomycin-resistant S. aureus in the recent years as well [7] ) makes the discovery of new molecular scaffolds a priority, and the current situation even necessitates the reengineering and repositioning of some old drug families to achieve adequate control of these bacteria [8] . However, for the treatment of S. aureus bloodstream infections, bactericidal antimicrobial agents are considered to be superior to bacteriostatic drugs [9] . This fact should be considered during the development of effective and safe treatment options for MRSA infections.
The history of clinical usage of salicylanilides (2-hydroxy-N-phenylbenzamides) dates back to the 1940s in therapy of tinea capitis, followed by the discovery of their anthelmintic properties in the mid 1950s [10] . Nowadays, salicylanilides (SALs) are a class of aromatic compounds possessing a wide range of interesting pharmacological activities, such as anthelmintic [11] , antibacterial [12, 13] , antimycobacterial [13] , antifungal [14] , and antiviral [15, 16] , among others. Despite being studied since the 1960s, the mechanism of action responsible for biological activities of these compounds has not been explained so far. SALs have been found to inhibit the two-component regulatory systems (TCS) of bacteria [17] . The latest studies specified them also as selective inhibitors of interleukin-12p40 production that plays a specific role in initiation, expansion, and control of cellular response to tuberculosis [18] . Furthermore, salicylanilides have been recognised as inhibitors of some bacterial enzymes, such as sortase A from S. aureus [19] , d-alanine-d-alanine ligase [20] , or transglycosylases from S. aureus (but not from M. tuberculosis) [12] . These enzymes participate in secretion of various proteins or in biosynthesis of bacterial cell wall. Recently, salicylanilides-like derivatives were described to inhibit two enzymes essential for mycobacteria: (i) methionine aminopeptidase, catalyzing a key step of the posttranslational modification of nascent proteins, and (ii) isocitrate lyase, which is essential for the metabolism of fatty acids [21] . Thus, SALs seem to be promising candidates for development of new antibacterial agents with a novel mechanism of action. Such new agents could be a solution to the resistance challenges.
This study is a follow-up paper to a recently published article [13] . The synthesis of the series of novel derivatives of salicylamides, 4-and 5-chloro-2-hydroxy-N-[1-oxo-1-(phenylamino)alkan-2-yl]benzamides, called diamides due to their skeleton (for general structure see Table 1 ), was described previously [13, 22] , and their antimycobacterial and antibacterial activities against various bacterial species were reported [13] . As these compounds expressed very significant antibacterial activity with low MIC values against clinical isolates of MRSA as representatives of multidrugresistant bacteria, we decided to extend the knowledge about the antibacterial properties of these compounds against MRSA.
The aim of the current study was to assess the overall in vitro bactericidal activity of nine newly synthesized diamides in dependence on time and concentration against clinical isolates of MRSA as representatives of multidrug-resistant bacteria. To the best of our knowledge, this is the first study dealing with the evaluation of novel microbiological characteristics of SAL analogues and revealing their bactericidal effect.
The synthetic pathway of the series of novel diamides was described recently [13, 22] , and their structures (see Table 1 ) were confirmed by IR, NMR, and MS spectrometry, and the purity of the compounds was checked by CHN analysis [13, 22] . [27] ; and MRSA SA 3202 [27] (National Institute of Public Health, Prague, Czech Republic) both of human origin. Suspected colonies were confirmed by PCR; a 108 bp fragment specific for S. aureus was detected [28] . All isolates were tested for the presence of the mecA gene encoding methicillin resistance [29] . These three clinical isolates were classified as vancomycin-susceptible (but with higher MIC of vancomycin equal to 2 g/mL (VA2-MRSA) within the susceptible range for MRSA 63718) methicillinresistant S. aureus (VS-MRSA). For the MICs of vancomycin, see Table 1 . Vancomycin-susceptible methicillin-susceptible Staphylococcus aureus (VS-MSSA) ATCC 29213, obtained from the American Type Culture Collection, was used as the reference and quality control strain. The bacteria were stored at −80 ∘ C and were kept on blood agar plates (Columbia agar base with 5% ovine blood) between experiments. (MBCs) . The MBCs (i.e., the lowest concentrations of antibacterial agents required to kill a particular bacterium) were determined by subculturing aliquots (20 L) from wells with no visible bacterial growth and from control wells of MIC determination onto substance-free Mueller-Hinton agar (MHA) plates. The plates were incubated aerobically at 37 ∘ C for 24 h for colony count. The MBC was defined as the lowest concentration of substance, which produced ≥99.9% killing Table 1 : Chemical structures and in vitro MIC and MBC [ g/mL] values of tested 5-and 4-chloro-2-hydroxy-N-[1-oxo-1-(phenylamino)alkan-2-yl]benzamides (bactericidal effect of individual compounds against particular strains marked in bold). after 24 h of incubation as compared to the colony count of the starting inoculum [30] . To ensure reproducibility, each MBC assay was performed in at least triplicate on separate occasions.
N H O H N O OH 1 2 R 1 R 3 R 2 Comp. R 1 R 2 R 3 MIC [ g/mL] MBC [ g/mL] 1 2 3 4 1 2 3 4 1a 5-Cl 4-CH 3 (S)-CH 3 >256 >256 >256 >256 >256 >256 >256 >256 1b 5-Cl 4-CH 3 (S)-CH(CH 3 ) 2 >256 >256 32 32 >256 >256 128 >256 1c 5-Cl 4-CH 3 (S)-benzyl >256 >256 >256 >256 >256 >256 >256 >256 1d 5-Cl 4-CH 3 (R)-CH 2 -indolyl >256 >256 >256 >256 >256 >256 >256 >256 1e 5-Cl 4-OCH 3 (S)-CH(CH 3 ) 2 >256 >256 >256 >256 >256 >256 >256 >256 1f 5-Cl 4-CF 3 (S)-CH(CH 3 ) 2 4 2 2 2 4 4 8 4 1g 4-Cl 4-Br (S)-CH(CH 3 ) 2 8 4 4 4 1 6 8 8 8 1h 4-Cl 3,4-Cl (S)-CH(CH 3 ) 2 2 1 1 1 4 1 4 2 1i 4-Cl 3,4-Cl (S)-benzyl 1 1 0.5 0.5 8 1 8 1 AMP - - - >16 >16 >16 0.25 >16 >16 >16 0.25 CPX - - - >16 >16 >16 0.5 >16 >16 >16 0.5 VAN - - - 2 1 1 1 2 1 1 1
Time-kill assays were performed by the broth macrodilution method according to previously described methodology [30] with some modifications. Briefly, flasks containing sterile fresh Mueller-Hinton broth (MHB) with the appropriate antimicrobial agent were inoculated with the test organism in logarithmic growth phase to obtain the starting inoculum with the concentration of approximately 7.5 × 10 6 CFU/mL (actual inoculum concentrations ranged from 0.9 × 10 5 to 2.9 × 10 6 CFU/mL) and a final concentration of the antibiotic equal to 1x, 2x, and 4x MIC in 10 mL volume. For the determination of viable counts, aliquots were removed at 0, 4, 6, 8, and 24 h time points after inoculation, serially diluted in sterile phosphate buffered saline, and aliquots (20 L) were plated on MHA plates in duplicate. Colony counts were performed on plates yielding 6 to 60 colonies, and the mean was calculated. Antimicrobial carry-over was controlled by dilution and visual inspection of the distribution of colonies on the plates with observation of possible inhibition of growth at the site of the initial streaks. The plates were incubated at 37 ∘ C for 24 to 48 h, and the number of colonies was determined. To ensure reproducibility, each time-kill experiment was carried out in duplicate on separate occasions with results presented as the mean of all experiments. The growth control without the addition of antimicrobial agents and the control containing DMSO without any antimicrobial agent to exclude antibacterial activity of this solvent were included. Time-kill curves were constructed by plotting the log 10 CFU per millilitre versus time (over 24 h), and the change in bacterial concentration was determined. The results were analysed by evaluating the numbers of strains that yielded Δ(log 10 CFU/mL) values of −1 (corresponding to 90% killing), −2 (99% killing), and −3 (99.9% killing) at 4, 6, 8, and 24 h compared to counts at 0 h. Bactericidal activity was defined as a reduction of at least 99.9% (≥3 log 10 ) of the total count of CFU/mL in the original inoculum.
Diamides seem to be promising candidates for antibacterial agents with very strong anti-MRSA activity, as it was published recently [13] . In the present study the series of nine newly synthesized diamides was evaluated as prospective bactericidal agents against representatives of multidrugresistant bacteria, three clinical isolates of MRSA, and Staphylococcus aureus ATCC 29213 (methicillin-susceptible) as the reference and quality control strain. Since SALs and their analogues are known as compounds with bacteriostatic effect [31] , this is the first study where SAL-like compounds were considered as prospective bactericidal agents and the dependence of bactericidal effect of these compounds on time and concentration was evaluated. Thus, absolutely novel microbiological characteristics of these compounds were revealed in the present study.
Recently MIC values of diamides expressed as molar concentrations in mol/L were published [13] . To allow comparison with MBC values of the present study, MICs in g/mL were calculated and are recorded in Table 1 along with the activity of reference antibacterial drugs, ampicillin, ciprofloxacin, and vancomycin. Potential bactericidal activity of diamides was assessed using MBC assay [26] . MBC values of all tested compounds are recorded in Table 1 as well.
Based on the obtained results, all compounds assessed as active according to MIC values in our previous study (1f-i) showed low or moderate MBC values against all four strains. The MBC values of these compounds did not exceed the highest tested drug concentration and ranged from 1 to 16 g/mL. In all cases, there were comparable MBC values for the clinical isolates of MRSA and the S. aureus reference strain.
Bactericidal activity is defined as a ratio of MBC to MIC of ≤4 [32] . Table 1 bactericidal activity is expressed in bold.
As mentioned above, SALs are known to exhibit a bacteriostatic effect [31] , so it was very interesting to discover that diamides possess bactericidal activity. The amide bond (-CONH-) can cause interactions with a variety of enzymes [33] ; therefore the presence of two amide bonds could be responsible for the bactericidal effect of diamides against MRSA. The activity of SALs and their analogues results from multiple mechanisms, which are still under investigation; for example, it was found that SALs are capable of inhibiting transglycosylases in later stages of S. aureus (including MRSA) cell wall biosynthesis [12] . These enzymes catalyse the step prior to the transpeptidation in the peptidoglycan biosynthesis and are responsible for polymerization of lipid II, which occurs at the outer face of the membrane [12] . Since antibacterial agents targeting cell wall biosynthesis act as bactericidal agents [30, 34] , the failure in the cell wall biosynthesis due to the inhibition of transglycosylases could be responsible for bactericidal activity of diamides against MRSA.
Based on these findings, antibacterial active diamides with bactericidal effect against all four tested strains as prospective bactericidal agents were chosen for subsequent timekill curve studies to determine the real dependence of bactericidal effect on concentration over time.
1-oxobutan-2-yl}-2-hydroxybenzamide (1h) were tested in time-kill studies at 1x, 2x, and 4x MIC against all MRSA isolates and the S. aureus reference strain. The antibacterial effect of DMSO [35] used as the solvent of the tested compounds was excluded in this assay, as time-kill curves of this solvent were identical or very similar to those of the growth control. The extent of bacterial killing was estimated by the number of these strains showing a decrease ranging from 1 to 3 log 10 CFU/mL in viable cell count at different times after incubation. A summary of these data is presented in Table 2 . Based on these data it can be concluded that the bactericidal potency of tested diamides against all four strains decreased as follows: 1f > 1h > 1g. No bactericidal activity (i.e., ≥3 log 10 CFU/mL decrease) was observed at 1x MIC for any strain and time after incubation tested. At 4x MIC from the four strains, compounds 1f, 1 g, and 1h killed 2, 1, and 2 strains, respectively, at 8 h after incubation and 4, 2, and 2 strains, respectively, at 24 h after incubation.
The findings of time-kill studies for each of the four staphylococci strains at exposure to compounds 1f, 1g, and 1h are summarized in Table 3 . Bactericidal activity (i.e., ≥3 log 10 CFU/mL decrease) is expressed in bold.
For compound 1f rapid concentration-dependent antibacterial effect was recorded against clinical isolate of MRSA 63718. Time was not the predictive factor influencing the antibacterial activity because log 10 differences in CFU/mL from the starting inoculum were the same for 4x MIC (with the highest efficiency with a reduction in bacterial count of 5.30 log 10 CFU/mL) or very similar for 2x MIC (with a moderate regrowth after 24 h causing a loss of bactericidal activity) over 24 h. The bactericidal effect was maintained even at 2x MIC at 4 h after incubation for this strain (reduction of 3.08 log 10 CFU/mL). For the remaining strains, clinical isolates of MRSA SA 630, MRSA SA 3202, and S. aureus ATCC 29213, reliable bactericidal effect was recorded at 4x MIC at 24 h after incubation for all these strains with a reduction in bacterial count of 3.22, 3.30, and 3.65 log 10 CFU/mL, respectively.
For compound 1g bactericidal effect against MRSA 63718 was noticed at 2x MIC at 6 and 8 h after incubation and at 4x MIC at 4, 6, and 8 h after incubation with a reduction in bacterial count ranging from 3.10 to 3.58 log 10 CFU/mL. The most effective killing was achieved at 6 h for both concentrations. As in the case of compound 1f, a regrowth was observed after 24 h after incubation. For the remaining isolates of MRSA, SA 630 and SA 3202, bactericidal effect occurred only at 4x MIC at 24 h after incubation with a reduction in bacterial count of 3.38 and 4.01 log 10 CFU/mL, respectively. The highest bactericidal effect was recorded for MRSA SA 3202 at 4x MIC at 24 h after incubation. A reduction consistent with bacteriostatic effect (0.03 to 2.37 log 10 CFU/mL) was observed at other concentrations over time for both isolates. No bactericidal effect was observed for the S. aureus reference strain; compound 1g demonstrated a pattern of bacteriostatic activity against this strain with a reduction in bacterial count ranging from 0.07 to 2.33 log 10 CFU/mL at 4x MIC over time. In other cases, a slight increase in bacterial counts (i.e., overgrowth) compared with the starting inoculum was observed with values ranging from 0.10 to 1.57 log 10 CFU/mL for this reference strain.
For compound 1h bactericidal effect against MRSA 63718 was maintained at 4x MIC at 6 and 8 h after incubation with a reduction in bacterial count of 3.54 and 3.31 log 10 CFU/mL, respectively. The same as for 1g, the most potent bactericidal effect was maintained at 6 h after incubation. Regrowth at 24 h after incubation causing a loss of bactericidal activity was recorded similarly as with previous compounds. The reason for regrowth of the test organism at 24 h in the experiment is unknown. Most probably, selection of resistant mutants is responsible for this phenomenon [30] ; degradation of the drug in the growth medium is not assumed, as regrowth was
Number of strains showing the following log 10 CFU/mL decrease a at the designated incubation time not observed for any other tested strain. For MRSA SA 630 concentration-dependent killing was recorded at 4x MIC at 6, 8, and 24 h after incubation with log 10 differences in CFU/mL from the starting inoculum being very similar over time (ranging from 3.18 to 3.39 log 10 CFU/mL). For MRSA SA 3202 reliable bactericidal effect was maintained only at 4x MIC at 24 h after incubation with a reduction in bacterial count of 3.02 log 10 CFU/mL. As for compound 1g, bacteriostatic activity against S. aureus reference strain was observed with a reduction in bacterial count ranging from 0.34 to 2.62 log 10 CFU/mL at 2x and 4x MIC. Overgrowth (values ranging from 0.04 to 1.43 log 10 CFU/mL) was recorded at 1x MIC for this strain. It is of note that in all staphylococci strains with similar MICs and MBCs for compounds 1g and 1h the responsiveness to antibacterial activity of these compounds varied with clinical strains of MRSA being effectively killed and the reference strain remaining unaffected at 4x MIC.
There is a discrepancy between bactericidal results of MBC assay compared with time-kill kinetics. This difference could be caused by comparing microtiter (MBC assay) to macrobroth (time-kill assay) dilutions [36] . Moreover, although time-kill assays are more labour intensive and time consuming than MBC assays, they are recognised to provide a greater degree of characterisation of the cell eradication potential of antibacterial agents [37] .
Concerning antibacterial effect, it is not generally important if the antibacterial agent is also bactericidal at higher concentrations, because the inhibition of bacterial proliferation usually achieves a therapeutic effect; the patient's immune system is capable of coping with the infection then [34] . However, bactericidal therapy could produce a better treatment result by rapid reduction of the bacterial load [38] . Moreover, in the case of an immune system disorder (e.g., immunosuppressive therapy, AIDS patients, etc.) bactericidal agents are unequivocally indicated. Considering steadily escalating numbers of immunocompromised patients with endocarditis, meningitis, or osteomyelitis in recent years, it is necessary to achieve bacterial killing and broaden the spectrum of antimicrobial agents with bactericidal active compounds [30] .
The clinical outcome of MRSA bacteraemia is significantly influenced by vancomycin MIC. Treatment failure exceeding 60% for S. aureus with vancomycin MIC of 4 g/mL resulted in the change of susceptibility breakpoint from 4 g/mL to 2 g/mL by the Clinical and Laboratory Standards Institute (CLSI) in 2006 [23] as well as by the US Food and Drug Administration (FDA) in 2008 [39] . It has been recommended that for infections caused by MRSA strains with elevated vancomycin MICs (2 g/mL), alternative therapy should be considered [40] . It is of note that based on time-kill assays in the present study, all tested diamides (particularly compound 1f exhibiting rapid bactericidal concentration-dependent effect even at 2x MIC) were most effective against isolate MRSA 63718, which is the strain with elevated vancomycin MIC of 2 g/mL. The activity against the remaining isolates with vancomycin MIC of 1 g/mL was lower.
Considering the emergence of decreasing vancomycin susceptibility of MRSA isolates and thus the therapeutic efficacy of vancomycin therapy, our aim was to determine the potential bactericidal role of novel antibacterial compounds against MRSA in vitro. Based on the obtained results, diamides can be suitable candidates for such novel bactericidal active compounds presenting a promising starting point for further investigations to ascertain real in vivo activity and the exact mechanism of action.
The present study is the first evidence of bactericidal effect of SAL analogues. Against other strains, reliable bactericidal effect was maintained at 4x MIC at 24 h after incubation. Considering the necessity to broaden the spectrum of bactericidal agents, diamides from the current study with a novel mechanism of action could present a very promising and interesting solution to this challenge for the future. | What is the treatment of choice for MRSA infections? | false | 5,227 | {
"text": [
"vancomycin"
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2785
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} |
1,623 | Etiology of Influenza-Like Illnesses from Sentinel Network Practitioners in Réunion Island, 2011-2012
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5031398/
SHA: f5ff89ebfdd0375d034c112c6c1c7e163fa69a0c
Authors: Brottet, Elise; Jaffar-Bandjee, Marie-Christine; Li-Pat-Yuen, Ghislaine; Filleul, Laurent
Date: 2016-09-21
DOI: 10.1371/journal.pone.0163377
License: cc-by
Abstract: In Réunion Island, despite an influenza surveillance established since 1996 by the sentinel general practitioner’s network, little is known about the etiology of Influenza like-illness (ILI) that differs from influenza viruses in a tropical area. We set up a retrospective study using nasal swabs collected by sentinel GPs from ILI patients in 2011 and 2012. A total of 250 swabs were randomly selected and analyzed by multiplex reverse transcriptase polymerase chain reaction (RT-PCR) including research of 18 viruses and 4 bacteria. We detected respiratory viruses in 169/222 (76.1%) samples, mostly rhinovirus (23.4%), influenza A virus (21.2%), influenza B virus (12.6%), coronavirus (4.9%) and Human metapneumovirus (3.6%). Nine swabs (5.3% of positive swabs) revealed co-infections with two viruses identified, among which six concerned co-infections with influenza viruses. We observed important seasonal differences, with circulation of Human Metapneumoviruses, RSV A and B and coronavirus only during summer; whereas parainfluenza viruses were identified only during winter. In conclusion, this study highlights a substantial circulation of multiple respiratory pathogens in Réunion Island throughout the year. It shows that ILI are not only attributable to influenza and underlines the need for biological surveillance. As the use of multiplex RT-PCR showed its efficacy, it is now used routinely in the surveillance of ILI.
Text: Influenza like-illness (ILI) or acute respiratory infections can be caused by several types of respiratory viruses or bacteria in humans [1] . Influenza viruses, Respiratory Syncytial viruses (RSV) and Parainfluenza viruses are identified as major viruses mostly responsible for ILI and pneumonia in several studies [2] . However practitioners cannot diagnose the infection without a biological test confirmation. Unfortunately, these infections causes are identified in less than 50% [3] .
Réunion Island, a French overseas territory with 850,000 inhabitants, is located in the southern hemisphere between Madagascar and Mauritius in the Indian Ocean (Latitude: 21°05.2920 S Longitude: 55°36.4380 E.). The island benefits from a healthcare system similar to mainland France and epidemiological surveillance has been developed by the regional office of the French Institute for Public Health Surveillance (Cire OI), based on the surveillance system of mainland France [4] . Influenza activity generally increases during austral winter, corresponding to summer in Europe [5] . Since 2011, influenza vaccination campaign in Reunion Island starts in April and the vaccine used corresponds to World Health Organization recommendations for the southern hemisphere.
Since 1996, clinical and biological influenza surveillance has been based on a sentinel practitioner's network [6] . In 2014, this network was composed of 58 general practitioners (GPs) spread over the island and represented around 7% of all Réunion Island GPs. Nasal swabs are randomly collected all along the year and are tested by RT-PCR for influenza viruses. Among these surveillance samples, 40 to 50% are tested positive for influenza A virus, A(H1N1)pdm09 or B virus by the virological laboratory of the University Hospital Center of Réunion. Thus ILI samples tested negative for influenza are of unknown etiology.
Several biological tools allow identifying respiratory pathogens from nasal swab. In recent years, multiplex reverse transcriptase polymerase chain reaction (RT-PCR) has been developed to identify several viruses simultaneously [7] [8] [9] [10] . We therefore used this new method to set up a retrospective study using swabs collected by sentinel GPs from 2011 to 2012.
The main objective of our study was to characterize respiratory pathogens responsible for ILI consultations in sentinel GPs in 2011 and 2012. Secondary objectives were to highlight seasonal trends on respiratory pathogens circulation and to describe occurrence of co-infections, especially during the flu season.
ILI was defined as a sudden onset of fever more than 38 degrees Celsius and cough, associated or not with other symptoms such as breathing difficulty, headache, etc. Every week, all GPs of the sentinel network were encouraged to collect a nasal swab from the first two patients who presented ILI since less than three days. After being tested for influenza viruses, the 994 swabs collected in 2011 and 2012 are frozen at -80°C at the university hospital center (CHU) laboratory.
Based on the budget, a season-stratified sample of 250 swabs was randomly selected in order to describe circulating viruses including outside flu season. Random sampling was performed with Excel 1 using the anonymized surveillance database of the Cire OI. The sampling frame contained identification number of swab assigned by Cire OI, laboratory identification number, sex, age, date of onset of symptoms, date of swab collection and result of influenza RT-PCR.
We used Respifinder 1 Smart 22 kits a multiplex RT-PCR (PathoFinder, Maastricht, The Netherlands) which can detect 22 respiratory pathogens. This assay is based on the multiplex ligation-dependent probe amplification (MLPA) technology. The reverse transcription and preamplification steps were performed on the epgradient Mastercycler 1 (Eppendorf) and the hybridization, ligation and detection steps on the LightCycler 1 480 system (Roche Applied Science). This method was chosen because of its high specificity, compared to other same methods (78% versus 33%) [3, 11] . Multiplex analysis allows for rapid production of diagnostic results. It thus allows highlighted the possible presence of eighteen respiratory viruses and four bacteria in one reaction by melt curve analysis: Influenza A not (H1N1
Statistical analyses were performed with Stata 1 and Excel 1 . Two seasons were defined to identify possible seasonal trends in circulation of the viruses: winter season during weeks 23 to 39 between June and September and summer season during the rest of the year.
Data and swabs result from a surveillance system that received regulatory approvals, including the CNIL (National Commission for Information Technology and Civil Liberties Number 1592205) approval in July 2012. All the patients have received oral information and gave their consent for swab and data collection. Data were collected for surveillance purpose and are totally anonymous.
Among the 250 randomly-selected swabs, 26 were not available anymore as they were sent to Influenza Reference Center for confirmation and characterization of the pathogenic agent. According to the sensitivity of the assay two samples could be discordant results between Influenza PCR initially realized and Multiplex PCR. Thus they were deleted from the analysis: one is positive for Influenza in singleplex and negative for all tested pathogens in multiplex and one is positive for Influenza in singleplex and positive for PIV2 in multiplex. In total, 222 analyses were considered. Moreover, 53 samples were negative for all analyzed respiratory pathogens (23.9%) and 169 samples had at least one detected pathogen (76.1%), finally a total of 178 pathogens was identified.
During the study period, a minority of the weeks (21 i.e. 20%) did not include any sampled swab, mainly outside flu season.
Patients' sex-ratio was 0.63 (86 men and 136 women) and mean age was 28.4 years [min 0; max 81]. Ten percent had less than 5 years, 24% 5-15 years, 63% 15-65 years and only 3% were 65 and older.
The respiratory pathogens most frequently identified in ILI swabs were rhinovirus (23.4%), influenza A not H1N1 (21.2%) and influenza B (12.6%) ( Table 1) .
Among the 22 respiratory pathogens tested by the multiplex, only three were not found in any analyzed sample: Parainfluenza3, Legionella pneumophila and Bordetella pertussis.
Regarding co-infections, nine swabs revealed the presence of two viruses, among which6 involved influenza viruses (Table 2) .
Analyses showed that some viruses are possibly seasonal and were circulating during a specific period of the year. They are detected only in summer for Human Metapneumovirus, RSV A and B, and influenza A(H1N1)pdm09. For the latter, it is specific to the studied period since the influenza A(H1N1)pdm09 virus reappeared in Réunion Island in October 2012 and was no longer circulating since late 2010. On the opposite, Parainfluenza 1,2 and 4 viruses were identified only in winter. For other pathogens, no specific period of detection was observed.
A weekly description of samples was realized to study the distribution of respiratory pathogens in 2011 and 2012 (Fig 1) . Results of biological analyses were compared with data of ILI consultations declared by sentinel GPs in 2011 and 2012. We observed in 2011, after a first wave in June mainly due to influenza A not H1N1 virus, a second wave of ILI consultations with mainly identification of Parainfluenza viruses and not influenza viruses. In 2012, the second epidemic wave at the end of austral winter coincided with Influenza viruses and Rhinovirus circulation.
Regarding negative swabs (Fig 2) , we observed no seasonality during the study period with a similar proportion whatever the season.
This retrospective study based on a sentinel GPs network showed that not only influenza viruses are responsible for ILI consultations. Indeed, an important circulation of multiple pathogens was observed throughout the year, with 12 different types of pathogens identified in 2011 and 2012. Respiratory viral pathogens were present in 76.1% of samples, which is largely above results from annual influenza surveillance [12] . After influenza viruses, Rhinovirus and Coronavirus were the most common respiratory viruses in Réunion Island. Although samples were not taken every week, sample was representative of ILI activity and consistent with flu season. Nevertheless, according to the low number of samples, it is difficult to conclude about seasonality. However in our study, RSV was circulating in summer season which is hot and rainy, which is confirmed by other studies in tropical region [13] .
This study also highlighted several co-infections, showing that concomitant the multiple etiology of ILI. Co-circulation was already observed in Réunion Island during the A(H1N1) pdm09 pandemic in addition to influenza virus, with identification of other respiratory viruses such as Rhinovirus or Coronavirus [14] . In mainland France, during this pandemic, circulation of major respiratory viruses was found, such as Rhinovirus, Parainfluenza, Coronavirus, Human Metapneumovirus, like in our publication [15] [16] . In our study, only 5.3% of positive swabs were co-infections whereas in two studies in Madagascar co-infections represented 27.3% and 29.4% [17] [18] .
Despite the distance of 9,300 km between Réunion and France, the island is directly connected to Europe with four daily flights to France. These exchanges can impact respiratory pathogens circulation in southern and northern hemisphere. Results of this study can therefore be of interest to both Indian Ocean and Europe countries.
Among the 148 swabs initially negative for influenza because not previously tested for any other viruses, the study found an etiology for 95 swabs. In total, only 53 swabs, representing 24% of the sample, remained without etiology with negative multiplex PCR results all along the year. Multiple hypotheses can explain this result: a poor quality of swabs, preventing from identifying a pathogen, noninfectious causes or other pathogens not included in the multiplex PCR. However, we couldn't test the negative swabs for RNAse P, a marker of human cells, which could provide a modicum of assurance that the swab contained human cells.
Concerning the two samples divergent for influenza identification between the multiplex and singleplex PCR, we discarded them for the analysis; one was positive in Influenza with singleplex and positive in PIV with multiplex. It could be a false positive result from singleplex. Indeed, as the multiplex PCR assay has a good sensitivity and is considered as a gold-standard, we decided to keep seven negative results for Influenza in singleplex and positive in Influenza in multiplex [7] [8] [9] [10] .
No case of Bordetella pertussis which causes whooping cough and Legionella pneumophila which causes Legionnaires' disease was identified in this study. However, these diseases are rare in Réunion Island, around three cases of Legionnaires' disease are declared each year.
A limit of the study is that no clinical data were available in the virological surveillance system of influenza in Réunion Island. It was impossible to compare clinical symptoms according to each pathogen and to know if there are different pathogens which cause for instance rhinitis, laryngitis or bronchitis (diseases included in ILI). A specific prospective study including clinical data might provide useful elements in the semiotics of diseases.
In conclusion, this study highlighted an important circulation of multiple pathogens in Réunion Island throughout the year. It shows that ILI is not specific to influenza and so it is essential to have biological results in order to establish the differential diagnosis and thus explain the etiology of symptoms. For a better understanding of respiratory pathogens circulating in Réunion Island, information from this study may also be useful to practitioners who see many patients in consultation with ILI. As the use of multiplex RT-PCR showed its efficacy in the ILI surveillance and allowed to highlight the circulation of other viruses and bacterial causes of respiratory infections, it is now used routinely in the surveillance of ILI. Moreover, it would be interesting to repeat this study every 3 or 5 years adding clinical data to monitor the evolution of respiratory pathogens in Réunion Island over time. | Which are identified as major viruses mostly responsible for ILI and pneumonia in several studies? | false | 4,042 | {
"text": [
"Influenza viruses, Respiratory Syncytial viruses (RSV) and Parainfluenza viruses"
],
"answer_start": [
1966
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2,634 | Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067204/
SHA: c097a8a9a543d69c34f10e5c3fd78019e560026a
Authors: Chan, Jasper Fuk-Woo; Kok, Kin-Hang; Zhu, Zheng; Chu, Hin; To, Kelvin Kai-Wang; Yuan, Shuofeng; Yuen, Kwok-Yung
Date: 2020-01-28
DOI: 10.1080/22221751.2020.1719902
License: cc-by
Abstract: A mysterious outbreak of atypical pneumonia in late 2019 was traced to a seafood wholesale market in Wuhan of China. Within a few weeks, a novel coronavirus tentatively named as 2019 novel coronavirus (2019-nCoV) was announced by the World Health Organization. We performed bioinformatics analysis on a virus genome from a patient with 2019-nCoV infection and compared it with other related coronavirus genomes. Overall, the genome of 2019-nCoV has 89% nucleotide identity with bat SARS-like-CoVZXC21 and 82% with that of human SARS-CoV. The phylogenetic trees of their orf1a/b, Spike, Envelope, Membrane and Nucleoprotein also clustered closely with those of the bat, civet and human SARS coronaviruses. However, the external subdomain of Spike’s receptor binding domain of 2019-nCoV shares only 40% amino acid identity with other SARS-related coronaviruses. Remarkably, its orf3b encodes a completely novel short protein. Furthermore, its new orf8 likely encodes a secreted protein with an alpha-helix, following with a beta-sheet(s) containing six strands. Learning from the roles of civet in SARS and camel in MERS, hunting for the animal source of 2019-nCoV and its more ancestral virus would be important for understanding the origin and evolution of this novel lineage B betacoronavirus. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Text: Coronaviruses (CoVs) are enveloped, positive-sense, single-stranded RNA viruses that belong to the subfamily Coronavirinae, family Coronavirdiae, order Nidovirales. There are four genera of CoVs, namely, Alphacoronavirus (αCoV), Betacoronavirus (βCoV), Deltacoronavirus (δCoV), and Gammacoronavirus (γCoV) [1] . Evolutionary analyses have shown that bats and rodents are the gene sources of most αCoVs and βCoVs, while avian species are the gene sources of most δCoVs and γCoVs. CoVs have repeatedly crossed species barriers and some have emerged as important human pathogens. The best-known examples include severe acute respiratory syndrome CoV (SARS-CoV) which emerged in China in 2002-2003 to cause a large-scale epidemic with about 8000 infections and 800 deaths, and Middle East respiratory syndrome CoV (MERS-CoV) which has caused a persistent epidemic in the Arabian Peninsula since 2012 [2, 3] . In both of these epidemics, these viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans.
Prior to December 2019, 6 CoVs were known to infect human, including 2 αCoV (HCoV-229E and HKU-NL63) and 4 βCoV (HCoV-OC43 [
HCoV-OC43 and HCoV-HKU1 usually cause self-limiting upper respiratory infections in immunocompetent hosts and occasionally lower respiratory tract infections in immunocompromised hosts and elderly [4] . In contrast, SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively [5, 6] . On 31 December 2019, the World Health Organization (WHO) was informed of cases of pneumonia of unknown cause in Wuhan City, Hubei Province, China [7] . Subsequent virological testing showed that a novel CoV was detected in these patients. As of 16 January 2020, 43 patients have been diagnosed to have infection with this novel CoV, including two exported cases of mild pneumonia in Thailand and Japan [8, 9] . The earliest date of symptom onset was 1 December 2019 [10] . The symptomatology of these patients included fever, malaise, dry cough, and dyspnea. Among 41 patients admitted to a designated hospital in Wuhan, 13 (32%) required intensive care and 6 (15%) died. All 41 patients had pneumonia with abnormal findings on chest computerized tomography scans [10] . We recently reported a familial cluster of 2019-nCoV infection in a Shenzhen family with travel history to Wuhan [11] . In the present study, we analyzed a 2019-nCoV complete genome from a patient in this familial cluster and compared it with the genomes of related βCoVs to provide insights into the potential source and control strategies.
The complete genome sequence of 2019-nCoV HKU-SZ-005b was available at GenBank (accession no. MN975262) ( Table 1 ). The representative complete genomes of other related βCoVs strains collected from human or mammals were included for comparative analysis. These included strains collected from human, bats, and Himalayan palm civet between 2003 and 2018, with one 229E coronavirus strain as the outgroup.
Phylogenetic tree construction by the neighbour joining method was performed using MEGA X software, with bootstrap values being calculated from 1000 trees [12] . The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) was shown next to the branches [13] . The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site [14] . All ambiguous positions were removed for each sequence pair (pairwise deletion option). Evolutionary analyses were conducted in MEGA X [15] . Multiple alignment was performed using CLUSTAL 2.1 and further visualized using BOX-SHADE 3.21. Structural analysis of orf8 was performed using PSI-blast-based secondary structure PREDiction (PSIPRED) [16] . For the prediction of protein secondary structure including beta sheet, alpha helix, and coil, initial amino acid sequences were input and analysed using neural networking and its own algorithm. Predicted structures were visualized and highlighted on the BOX-SHADE alignment. Prediction of transmembrane domains was performed using the TMHMM 2.0 server (http://www.cbs.dtu.dk/services/TMHMM/). Secondary structure prediction in the 5 ′ -untranslated region (UTR) and 3 ′ -UTR was performed using the RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/ RNAWebSuite/RNAfold.cgi) with minimum free energy (MFE) and partition function in Fold algorithms and Table 2 . Putative functions and proteolytic cleavage sites of 16 nonstructural proteins in orf1a/b as predicted by bioinformatics.
Putative function/domain Amino acid position Putative cleave site
complex with nsp3 and 6: DMV formation
complex with nsp3 and 4: DMV formation
short peptide at the end of orf1a basic options. The human SARS-CoV 5 ′ -and 3 ′ -UTR were used as references to adjust the prediction results.
The single-stranded RNA genome of the 2019-nCoV was 29891 nucleotides in size, encoding 9860 amino acids. The G + C content was 38%. Similar to other (Table 2 ). There are no remarkable differences between the orfs and nsps of 2019-nCoV with those of SARS-CoV (Table 3) . The major distinction between SARSr-CoV and SARS-CoV is in orf3b, Spike and orf8 but especially variable in Spike S1 and orf8 which were previously shown to be recombination hot spots.
Spike glycoprotein comprised of S1 and S2 subunits. The S1 subunit contains a signal peptide, followed by an N-terminal domain (NTD) and receptor-binding domain (RBD), while the S2 subunit contains conserved fusion peptide (FP), heptad repeat (HR) 1 and 2, transmembrane domain (TM), and cytoplasmic domain (CP). We found that the S2 subunit of 2019-nCoV is highly conserved and shares 99% identity with those of the two bat SARS-like CoVs (SL-CoV ZXC21 and ZC45) and human SARS-CoV (Figure 2 ). Thus the broad spectrum antiviral peptides against S2 would be an important preventive and treatment modality for testing in animal models before clinical trials [18] . Though the S1 subunit of 2019-nCoV shares around 70% identity to that of the two bat SARS-like CoVs and human SARS-CoV (Figure 3(A) ), the core domain of RBD (excluding the external subdomain) are highly conserved (Figure 3(B) ). Most of the amino acid differences of RBD are located in the external subdomain, which is responsible for the direct interaction with the host receptor. Further investigation of this soluble variable external subdomain region will reveal its receptor usage, interspecies transmission and pathogenesis. Unlike 2019-nCoV and human SARS-CoV, most known bat SARSr-CoVs have two stretches of deletions in the spike receptor binding domain (RBD) when compared with that of human SARS-CoV. But some Yunnan strains such as the WIV1 had no such deletions and can use human ACE2 as a cellular entry receptor. It is interesting to note that the two bat SARS-related coronavirus ZXC21 and ZC45, being closest to 2019-nCoV, can infect suckling rats and cause inflammation in the brain tissue, and pathological changes in lung & intestine. However, these two viruses could not be isolated in Vero E6 cells and were not investigated further. The two retained deletion sites in the Spike genes of ZXC21 and ZC45 may lessen their likelihood of jumping species barriers imposed by receptor specificity.
A novel short putative protein with 4 helices and no homology to existing SARS-CoV or SARS-r-CoV protein was found within Orf3b ( Figure 4 ). It is notable that SARS-CoV deletion mutants lacking orf3b replicate to levels similar to those of wildtype virus in several cell types [19] , suggesting that orf3b is dispensable for viral replication in vitro. But orf3b may have a role in viral pathogenicity as Vero E6 but not 293T cells transfected with a construct expressing Orf3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time points [20] . Orf3b was also shown to inhibit expression of IFN-β at synthesis and signalling [21] . Subsequently, orf3b homologues identified from three bat SARSrelated-CoV strains were C-terminally truncated and lacked the C-terminal nucleus localization signal of SARS-CoV [22] . IFN antagonist activity analysis demonstrated that one SARS-related-CoV orf3b still possessed IFN antagonist and IRF3-modulating activities. These results indicated that different orf3b proteins display different IFN antagonist activities and this function is independent of the protein's nuclear localization, suggesting a potential link between bat SARS-related-CoV orf3b function and pathogenesis. The importance of this new protein in 2019-nCoV will require further validation and study.
Orf8 orf8 is an accessory protein found in the Betacoronavirus lineage B coronaviruses. Human SARS-CoVs isolated from early-phase patients, all civet SARS-CoVs, and other bat SARS-related CoVs contain fulllength orf8 [23] . However, a 29-nucleotide deletion,
Bat SL-CoV ZXC21 2018
Bat which causes the split of full length of orf8 into putative orf8a and orf8b, has been found in all SARS-CoV isolated from mid-and late-phase human patients [24] . In addition, we have previously identified two bat SARS-related-CoV (Bat-CoV YNLF_31C and YNLF_34C) and proposed that the original SARS-CoV full-length orf8 is acquired from these two bat SARS-related-CoV [25] . Since the SARS-CoV is the closest human pathogenic virus to the 2019-nCoV, we performed phylogenetic analysis and multiple alignments to investigate the orf8 amino acid sequences. The orf8 protein sequences used in the analysis derived from early phase SARS-CoV that includes full-length orf8 (human SARS-CoV GZ02), the mid-and late-phase SARS-CoV that includes the split orf8b (human SARS-CoV Tor2), civet SARS-CoV (paguma SARS-CoV), two bat SARS-related-CoV containing full-length orf8 (bat-CoV YNLF_31C and YNLF_34C), 2019-nCoV, the other two closest bat SARS-related-CoV to 2019-nCoV SL-CoV ZXC21 and ZC45), and bat SARS-related-CoV HKU3-1 ( Figure 5(A) ). As expected, orf8 derived from 2019-nCoV belongs to the group that includes the closest genome sequences of bat SARS-related-CoV ZXC21 and ZC45. Interestingly, the new 2019-nCoV orf8 is distant from the conserved orf8 or Figure 5(B) ) which was shown to trigger intracellular stress pathways and activates NLRP3 inflammasomes [26] , but this is absent in this novel orf8 of 2019-nCoV. Based on a secondary structure prediction, this novel orf8 has a high possibility to form a protein with an alpha-helix, following with a betasheet(s) containing six strands ( Figure 5(C) ).
The genome of 2019-nCoV has overall 89% nucleotide identity with bat SARS-related-CoV SL-CoVZXC21 (MG772934.1), and 82% with human SARS-CoV BJ01 2003 (AY278488) and human SARS-CoV Tor2 (AY274119). The phylogenetic trees constructed using the amino acid sequences of orf1a/b and the 4 structural genes (S, E, M, and N) were shown (Figure 6(A-E) ). For all these 5 genes, the 2019-nCoV was clustered with lineage B βCoVs. It was most closely related to the bat SARS-related CoVs ZXC21 and ZC45 found in Chinese horseshoe
As shown in Figure 7 (A-C), the SARS-CoV 5 ′ -UTR contains SL1, SL2, SL3, SL4, S5, SL5A, SL5B, SL5C, SL6, SL7, and SL8. The SL3 contains trans-cis motif [27] . The SL1, SL2, SL3, SL4, S5, SL5A, SL5B, and SL5C structures were similar among the 2019-nCoV, human SARS-CoV and the bat SARS-related ZC45. In the 2019-nCoV, part of the S5 found was inside Figure 7 Continued the orf1a/b (marked in red), which was similar to SARS-CoV. In bat SARS-related CoV ZC45, the S5 was not found inside orf1a/b. The 2019-nCoV had the same SL6, SL7, and SL8 as SARS-CoV, and an additional stem loop. Bat SARS-related CoV ZC45 did not have the SARS-COV SL6-like stem loop. Instead, it possessed two other stem loops in this region. All three strains had similar SL7 and SL8. The bat SARS-like CoV ZC45 also had an additional stem loop between SL7 and SL8. Overall, the 5 ′ -UTR of 2019-nCoV was more similar to that of SARS-CoV than the bat SARS-related CoV ZC 45. The biological relevance and effects of virulence of the 5 ′ -UTR structures should be investigated further. The 2019-nCoV had various 3 ′ -UTR structures, including BSL, S1, S2, S3, S4, L1, L2, L3, and HVR (Figure 7(D-F) ). The 3 ′ -UTR was conserved among 2019-nCoV, human SARS-CoV and SARS-related CoVs [27] .
In summary, 2019-nCoV is a novel lineage B Betacoronavirus closely related to bat SARS-related coronaviruses. It also has unique genomic features which deserves further investigation to ascertain their roles in viral replication cycle and pathogenesis. More animal sampling to determine its natural animal reservoir and intermediate animal host in the market is important. This will shed light on the evolutionary history of this emerging coronavirus which has jumped into human after the other two zoonotic Betacoroanviruses, SARS-CoV and MERS-CoV. | What is the contrast with SARS-COV and MERS=COV? | false | 3,704 | {
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"SARS-CoV (lineage B βCoV) and MERS-CoV (lineage C βCoV) may cause severe lower respiratory tract infection with acute respiratory distress syndrome and extrapulmonary manifestations, such as diarrhea, lymphopenia, deranged liver and renal function tests, and multiorgan dysfunction syndrome, among both immunocompetent and immunocompromised hosts with mortality rates of ∼10% and ∼35%, respectively"
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1,595 | Severe Acute Respiratory Syndrome Coronavirus Viroporin 3a Activates the NLRP3 Inflammasome
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6361828/
SHA: f02d0c1e8b0109648e578662dc250abe349a033c
Authors: Chen, I-Yin; Moriyama, Miyu; Chang, Ming-Fu; Ichinohe, Takeshi
Date: 2019-01-29
DOI: 10.3389/fmicb.2019.00050
License: cc-by
Abstract: Nod-like receptor family, pyrin domain-containing 3 (NLRP3) regulates the secretion of proinflammatory cytokines interleukin 1 beta (IL-1β) and IL-18. We previously showed that influenza virus M2 or encephalomyocarditis virus (EMCV) 2B proteins stimulate IL-1β secretion following activation of the NLRP3 inflammasome. However, the mechanism by which severe acute respiratory syndrome coronavirus (SARS-CoV) activates the NLRP3 inflammasome remains unknown. Here, we provide direct evidence that SARS-CoV 3a protein activates the NLRP3 inflammasome in lipopolysaccharide-primed macrophages. SARS-CoV 3a was sufficient to cause the NLRP3 inflammasome activation. The ion channel activity of the 3a protein was essential for 3a-mediated IL-1β secretion. While cells uninfected or infected with a lentivirus expressing a 3a protein defective in ion channel activity expressed NLRP3 uniformly throughout the cytoplasm, NLRP3 was redistributed to the perinuclear space in cells infected with a lentivirus expressing the 3a protein. K(+) efflux and mitochondrial reactive oxygen species were important for SARS-CoV 3a-induced NLRP3 inflammasome activation. These results highlight the importance of viroporins, transmembrane pore-forming viral proteins, in virus-induced NLRP3 inflammasome activation.
Text: Severe acute respiratory syndrome coronavirus (SARS-CoV), a member of the genus Betacoronavirus within the family Coronaviridae, is an enveloped virus with a single-stranded positive-sense RNA genome of approximately 30 kb in length. The 5 two-thirds of the genome encodes large polyprotein precursors, open reading frame (ORF) 1 and ORF1b, which are proteolytically cleaved to generate 16 non-structural proteins (Tan et al., 2005) . The 3 one-third of the genome encodes four structural proteins, spike (S), envelope (E), matrix (M) and nucleocapsid (N), and non-structural proteins, along with a set of accessory proteins (3a, 3b, 6, 7a, 7b, 8a, 8b, and 9b) (Perlman and Dandekar, 2005; Tan et al., 2005) . SARS-CoV is the etiological agent of SARS (Drosten et al., 2003; Fouchier et al., 2003; Ksiazek et al., 2003; Kuiken et al., 2003; Peiris et al., 2003) . At least 8,098 laboratory-confirmed cases of human infection, with a fatality rate of 9.6%, were reported to the World Health Organization from November 2002 to July 2003. High levels of proinflammatory cytokines, including tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and IL-6, were detected in autopsy tissues from SARS patients (He et al., 2006) . Although dysregulation of inflammatory cytokines may be involved in lung injury and the pathogenesis of SARS-CoV, the underlying molecular mechanisms are not fully understood.
The innate immune systems utilizes pattern recognition receptors (PRRs) to detect pathogen-associated molecular patterns (Medzhitov, 2001; Kawai and Akira, 2010) . Recognition of virus infection plays an important role in limiting virus replication at the early stages of infection. Nod-like receptor family, pyrin domain-containing 3 (NLRP3) is activated by a wide variety of stimuli, including virus infection (Bauernfeind et al., 2011) . Four models describing activation of the NLRP3 inflammasome have been proposed thus far (Hornung and Latz, 2010; Schroder et al., 2010; Tschopp and Schroder, 2010) . First, the disturbances in intracellular ionic concentrations, including K + efflux and Ca 2+ influx, play an important role (Fernandes-Alnemri et al., 2007; Petrilli et al., 2007; Arlehamn et al., 2010; Ichinohe et al., 2010; Ito et al., 2012; Murakami et al., 2012; Munoz-Planillo et al., 2013) . Second, cathepsin B and L, which are specific lysosomal cysteine proteases, are though to play a role after phagocytosis of cholesterol crystals (Duewell et al., 2010) , fibrillar peptide amyloid-beta , silica crystals, and aluminum salts . Third is the release of reactive oxygen species (ROS) or mitochondrial DNA from damaged mitochondria (Zhou et al., , 2011 Nakahira et al., 2011; Shimada et al., 2012) . Finally, viral RNA or RNA cleavage products generated by RNase L activate the NLRP3 inflammasome via the DExD/H-box helicase, DHX33 (Allen et al., 2009; Mitoma et al., 2013; Chen et al., 2014; Chakrabarti et al., 2015) . Upon activation, the NLRP3 is recruited to the mitochondria via association with mitochondrial antiviral signaling (MAVS) or mitofusin 2 expressed on the outer mitochondrial membrane Subramanian et al., 2013) ; these molecules then recruit the apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC) and pro-caspase-1 to form the NLRP3 inflammasome. This event activates the downstream molecule, caspase-1, which catalyzes the proteolytic processing of pro-IL-1β and pro-IL-18 into their active forms and stimulates their secretion (Kayagaki et al., 2015; Shi et al., 2015) .
It is increasingly evident that NLRP3 detects RNA viruses by sensing the cellular damage or distress induced by viroporins (Ichinohe et al., 2010; Ito et al., 2012; Triantafilou et al., 2013; Nieto-Torres et al., 2015) , transmembrane pore-forming proteins, encoded by certain RNA viruses; these proteins alter membrane permeability to ions by forming membrane channels (Tan et al., 2005; Chen and Ichinohe, 2015) . A recent study shows that the SARS-CoV E protein, which comprise only 76 amino acids, forms Ca 2+ -permeable ion channels and activates the NLRP3 inflammasome (Nieto-Torres et al., 2015) . Although the E and 3a proteins of SARS-CoV, which comprise 274 amino acids and contain three transmembrane domains (Zeng et al., 2004; Lu et al., 2006) , are thought to act as Na + /K + and K + channels, respectively (Wilson et al., 2004; Lu et al., 2006; Torres et al., 2007; Parthasarathy et al., 2008; Pervushin et al., 2009; Wang et al., 2011) , the role of the 3a protein in activating the NLRP3 inflammasome remains unknown. Here, we examined the role of the 3a protein in activating the NLRP3 inflammasome.
Six-week-old female C57BL/6 mice were purchased from The Jackson Laboratory. All animal experiments were approved by the Animal Committees of the Institute of Medical Science (The University of Tokyo).
Bone marrow-derived macrophages (BMMs) were prepared as described previously (Ichinohe et al., 2009) . In brief, bone marrow was obtained from the tibia and femur by flushing with Dulbecco's modified Eagle's medium (DMEM; Nacalai Tesque). Bone marrow cells were cultured for 5 days in DMEM supplemented with 30% L929 cell supernatant containing macrophage colony-stimulating factor, 10% heat-inactivated fetal bovine serum (FBS), and L-glutamine (2 mM) at 37 • C/5% CO 2 . HEK293FT cells (a human embryonic kidney cell line) and HeLa cells (a human epithelial carcinoma cell line) were maintained in DMEM supplemented with 10% FBS, penicillin (100 units/ml), and streptomycin (100 µg/ml) (Nacalai Tesque). MDCK cells (Madin-Darby canine kidney cells) and HT-1080 cells (a human fibrosarcoma cell line) were grown in Eagle's minimal essential medium (E-MEM; Nacalai Tesque) supplemented with 10% FBS, penicillin (100 units/ml), and streptomycin (100 µg/ml) (Nacalai Tesque).
Influenza A virus strain A/PR8 (H1N1) was grown at 35 • C for 2 days in the allantoic cavities of 10-day-old fertile chicken eggs (Ichinohe et al., 2009) . The viral titer was quantified in a standard plaque assay using MDCK cells (Pang et al., 2013) .
Plasmids cDNAs encoding the E and M proteins of SARS-CoV Frankfurt 1 strain (Matsuyama et al., 2005) were obtained by reverse transcription and PCR of total RNA extracted from SARS-CoVinfected Vero cells, followed by PCR amplification using specific primers. pcDNA3.1D-3a-V5His was provided by Ming-Fu Chang (National Taiwan University College of Medicine, Taipei, Taiwan). To generate the plasmids pLenti6-E-V5His, pLenti6-3a-V5His, and pLenti-M-V5His, cDNA fragments of E, 3a, and M were amplified from pcDNA3.1D-E-V5His, pcDNA3.1D-3a-V5His, and pcDNA3.1D-M-V5His using specific primer sets and then ligated into pLenti6-TOPO vectors (Invitrogen). To generate plasmids pCA7-flag-E, pCA7-flag-3a, and pCA7flag-M, pCA7-HA-E, pCA7-HA-3a, and pCA7-HA-M, cDNA fragments of E, 3a, and M were amplified from pcDNA3.1D-E-V5His, pcDNA3.1D-3a-V5His, and pcDNA3.1D-M-V5His using specific primer sets, digested with EcoR I and Not I, and subcloned into the EcoR I-Not I sites of the pCA7-flag-ASC plasmid or pCA7-HA-M2 plasmid, respectively (Ito et al., 2012) . To construct plasmids expressing the E mutant V25F, the mutated E fragments were amplified by inverse PCR with wildtype E-containing plasmids and specific primer sets. The PCR products were cleaved by Dpn I, ligated in a ligase-and T4 kinase-containing reaction and then transformed into DH5α competent cells (TOYOBO). To construct plasmids expressing the 3a mutant 3a-CS, fragments were amplified from wildtype 3a-containing plasmids using 3a-specific primer sets and transformed as described above.
HEK293FT cells were seeded in 24-well cluster plates and transfected with 1 µg pLenti6-E/3a/M-V5His, pLenti-GFP (green fluorescent protein), or pLenti-M2 using polyethylenimine (PEI) Max. At 24 h post-transfection, the cells were lysed with RIPA buffer (50 mM Tris-HCl, 1% NP-40, 0.05% sodium dodecyl sulfate (SDS), 150 mM NaCl and 1 mM EDTA). And the lysates were subjected to SDS-polyacrylamide gel electrophoresis (PAGE) followed by electroblotting onto polyvinylidene difluoride (PVDF) membranes. The membranes were incubated over night with mouse anti-V5-tag (R960-25, Invitrogen), mouse anti-influenza A virus M2 (14C2, Abcam), mouse anti-GFP (GF200, Nacalai Tesque), or rabbit antitubulin (DM1A, Santa Cruz) antibodies, followed by horseradish peroxide-conjugated anti-mouse IgG (Jackson Immuno Research Laboratories) or anti-rabbit IgG (Invitrogen). After washing 3 times with washing buffer (0.05% Tween-20/PBS), the membranes were exposed using Chemi-Lumi One Super (Nacalai Tesque), and the chemiluminescent signals were captured by an ImageQuant LAS-4000 mini apparatus (GE Healthcare).
To generate lentiviruses expressing V5-tagged SARS-CoV E, 3a, and M proteins, the full-length cDNA encoding each viral protein was cloned into the pLenti6.3/V5-TOPO vector (Invitrogen) using the following primers: SARS-CoV E forward, 5 -caccatgtactcattcgtttcgga-3 , and reverse, 5 -gaccagaagatcaggaactc-3 ; SARS-CoV 3a forward, 5caccatggatttgtttatgagatt-3 , and reverse, 5 -caaaggcacgctagtagtcg-3 ; SARS-CoV M forward, 5 -caccatggcagacaacggtactat-3 , and reverse, 5 -ctgtactagcaaagcaatat-3 . Sub-confluent monolayers of HEK293FT cells seeded in a collagen-coated dish (10 cm in diameter) were transfected with 3 µg of pLenti6.3/V5-TOPO vector expressing each viral protein or EGFP together with ViraPower Packaging Mix (Invitrogen) using Lipofectamine 2000 (Invitrogen). The supernatants containing lentiviruses were harvested and filtered through a 0.45 µm filter (Millipore) at 72-96 h post-transfection (Ito et al., 2012) . The lentiviral titer was then quantified using HT-1080 cells as described previously .
Bone marrow-derived macrophages were plated at a density of 8 × 10 5 in 24-well plate and infected with A/PR8 influenza virus or lentivirus at a multiplicity of infection (MOI) of 5 or 0.2 for 1 h, respectively. Then, BMMs were stimulated with 1 µg/ml of LPS and cultured for additional 23 h in complete media. Supernatants were collected at 24 h post-infection and centrifuged to remove cell debris. The amount of IL-1β in the supernatants was measured in an enzyme-linked immunosorbent assay (ELISA) using paired antibodies (eBioscience) (Ichinohe et al., 2010 .
To clarify the cellular localization of the wild-type and mutant 3a proteins of SARS-CoV, HeLa cells were cultured on coverslips and transfected with 1 µg of pCA7-flag-3a or pCD7-flag-3a-CS together with 0.5 µg of ER-mCherry or DsRed-Golgi (Ito et al., 2012) . At 24 h post-transfection, cells were fixed with 4% paraformaldehyde and permeabilized with 1% Triton X-100/PBS. After washing with PBS and blocking with 4% BSA/PBS, the cells were incubated with a mouse anti-flag antibody (M2, Sigma) followed by incubation with Alexa Fluor 488-conjugated goat anti-mouse IgG (H+L) (Life Technologies).
To observe the cellular distribution of NLRP3 in the E-or 3a-expressing cells, HeLa cells were cultured on coverslips and transfected with 1 µg of pCA7-HA-E, pCA7-HA-EV25F, pCA7-HA-3a, pCA7-HA-3a-CS, or pCA7 control vector together with 0.5 µg of pCA7-NLRP3. At 24 h post-transfection, cells were fixed and permeabilized with 4% paraformaldehyde and 1% Triton X-100/PBS. After washing and blocking, the cells were incubated with rabbit anti-HA (561, MBL) and mouse anti-NLRP3 (Cryo-2; AdipoGen) antibodies, followed by Alexa Fluor 488-conjugated goat anti-rabbit IgG (H+L) and Alexa Fluor 568-conjugated goat anti-mouse IgG (H+L) (Life Technologies). Fluorescent signals were observed by confocal microscopy (A1R + , Nikon).
Statistical significance was tested using a two-tailed Student's t-test. P-values < 0.05 were considered statistically significant.
We previously demonstrated that the influenza virus M2 protein (a proton-selective ion channel), its H37G mutant (which has lost its proton selectivity and enables the transport of other cations such as Na + and K + ), and the EMCV 2B protein (a Ca 2+ channel) stimulates NLRP3 inflammasome-mediated IL-1β secretion (Ichinohe et al., 2010; Ito et al., 2012) . In addition, the SARS-CoV E protein acts as a Ca 2+ -permeable ion channels that activates the NLRP3 inflammasome (Nieto- Torres et al., 2015) . The fact that 3a protein of SARS-CoV acts as viroporin prompted us to examine whether it also triggers inflammasome activation. Thus, we first generated lentivirus plasmids expressing V5-tagged proteins and confirmed their expression in HEK293FT cells by immunoblot analysis (Figures 1A-C) . We next transduced lipopolysaccharide (LPS)-primed BMMs with the lentiviruses expressing the SARS-CoV E, 3a, M, influenza virus M2, or EMCV 2B proteins. Consistent with previous reports (Ichinohe et al., Figure 1D) . Similarly, the lentiviruses expressing the SARS-CoV E or 3a proteins stimulated IL-1β release from LPS-primed BMMs ( Figure 1D) . Furthermore, IL-1β secretion from LPSprimed BMMs co-infected with E-and 3a-expressing lentiviruses was significantly higher than that from SARS-CoV E-expressing lentivirus-infected cells ( Figure 1E) . These data indicated that the expression of SARS-CoV viroporin 3a is sufficient to stimulate IL-1β secretion by LPS-primed BMMs.
Previous studies demonstrated that the N-terminal 40 amino acids of the SARS-CoV E protein are important for ion channel formation, and that mutations N15A and V25F [located in the transmembrane domain (from amino acid residues 7-38)] prevent ion conductivity (Wilson et al., 2004; Torres et al., 2007; Verdia-Baguena et al., 2012) . In addition, the SARS-CoV 3a protein contains a cysteine-rich domain (amino acid residues 127-133) that is involved in the formation of a homodimer to generate the ion channel (Lu et al., 2006; Chan et al., 2009) . Thus, mutation of the cysteine-rich domain blocks the ion conductivity by the 3a protein (Chan et al., 2009) . To this end, we substituted amino acids Cys-127, Cys-130, and Cys-133 within the cysteine-rich domain of the SARS-CoV 3a protein with serine to generate a lentivirus expressing the ion channel activity-loss mutant, 3a-CS (Chan et al., 2009; Figure 2A) . To test whether the ion channel activity of the SARS-CoV 3a protein is required to stimulate secretion of IL-1β, we transduced LPSprimed BMMs with lentiviruses expressing the SARS-CoV E, V25F, 3a, 3a-CS, or M proteins. Consistent with a previous report (Nieto -Torres et al., 2015) , we found that the V25F mutant lentivirus failed to stimulate IL-1β release from BMMs ( Figure 2B) . Notably, the 3a-CS mutant completely abrogated IL-1β secretion (Figure 2B) , suggesting that the ion channel activity of the 3a protein is required for SARS-CoV 3a-induced IL-1β secretion.
FIGURE 4 | NLRP3 inflammasome activation by SARS-CoV 3a. HeLa cells were transfected with the expression plasmid encoding NLRP3 and that encoding HA-tagged SARS-CoV 3a, 3a-CS, E, or V25F, and by with a confocal microscope. Scale bars, 10 µm. Data are representative of at least three independent experiments.
Next, we determined the subcellular localization of the SARS-CoV 3a protein using confocal microscopy. When the SARS-CoV Cell-free supernatants were collected at 24 h (lentiviruses) or 6 h (ATP) post-infection or stimulation, and analyzed for IL-1β by ELISA. Data are representative of at least three independent experiments, and indicate the mean ± SD; * * P < 0.01 and * * * P < 0.001.
3a protein was expressed in HeLa cells, we observed two main distribution patterns. Consistent with previous reports (Yu et al., 2004; Yuan et al., 2005) , the 3a protein localized to the Golgi apparatus ( Figure 3A ). In addition, the 3a proteins concentrated in spot structures, which mainly localized to the endoplasmic reticulum (ER) (Figure 3B ). By contrast, the 3a-CS mutant was concentrated in the Golgi apparatus rather than in the ER and did not form spot structures (Figures 3A,B) . We next examined the intracellular localization of NLRP3. Activation of the NLRP3 inflammasome led to a redistribution from the cytosol to the perinuclear space, a process considered as a hallmark of NLRP3 activation (Zhou et al., 2011; Ito et al., 2012; Johnson et al., 2013; Moriyama et al., 2016) . Although cells expressing the ion channel activity-loss mutants 3a-CS or V25F uniformly expressed NLRP3 throughout the cytoplasm, it was redistributed to the perinuclear region in SARS-CoV 3a-or E-expressing cells (Figure 4) . Together, these data provide evidence that the ion channel activity of the SARS-CoV 3a protein is essential for triggering the NLRP3 inflammasome.
Both K + Efflux and ROS Production Are Involved in the IL-1β Release Induced by the SARS-CoV 3a Protein
Finally, we investigated the mechanism by which SARS-CoV 3a triggers NLRP3 inflammasome activation. A previous study showed that the 3a protein of SARS-CoV acts as a K + channel (Lu et al., 2006) . In addition, K + efflux is a well-known activator of the NLRP3 inflammasome (Mariathasan et al., 2006; Petrilli et al., 2007) . These observations prompted us to examine whether K + efflux is required for 3a-mediated IL-1β secretion. To this end, BMMs in K + -rich medium were infected with influenza A virus or lentiviruses expressing the SARS-CoV E or 3a proteins. In agreement with a previous result (Ichinohe et al., 2010) , we found that IL-1β secretion caused by influenza virus was completely blocked when the extracellular K + concentration was increased to 130 mM ( Figure 5A) . The inhibitory effect of the K + -rich medium was also observed when cells were stimulated with lentiviruses expressing the SARS-CoV E or 3a proteins ( Figure 5B ). Since mitochondrial ROS are important for NLRP3 inflammasome activation (Nakahira et al., 2011; Zhou et al., 2011) , we next stimulated BMMs with extracellular ATP or lentiviruses expressing the SARS-CoV E or 3a proteins in the presence or absence of the antioxidant, Mito-TEMPO, a scavenger that is specific for mitochondrial ROS Trnka et al., 2009) . As reported previously (Nakahira et al., 2011; Ito et al., 2012) , treatment of BMMs with Mito-TEMPO completely blocked IL-1β secretion in response to ATP ( Figure 6A) . Similarly, IL-1β release induced by the SARS-CoV E and 3a proteins was significantly inhibited by Mito-TEMPO ( Figure 6B) . These observations indicate that the SARS-CoV 3a protein disrupts intracellular ionic concentrations and causes mitochondrial damages, thereby activating the NLRP3 inflammasome.
In summary, we found that the ion channel activity of SARS-CoV 3a protein is essential for activation of the NLRP3 inflammasome. In addition, both K + efflux and mitochondrial ROS production are required for SARS-CoV 3a-mediated IL-1β secretion.
Thus far, several models have been proposed to explain NLRP3 inflammasome activation by RNA viruses. First, viral RNA or RNA cleavage products generated by RNase L activate the NLRP3 inflammasome via the DExD/H-box helicase, DHX33 (Allen et al., 2009; Mitoma et al., 2013; Chen et al., 2014; Chakrabarti et al., 2015) . Second, viroporins encoded by RNA viruses activates the NLRP3 inflammasome (Ichinohe et al., 2010; Ito et al., 2012; Triantafilou et al., 2013; Nieto-Torres et al., 2015) . In the case of influenza virus, the proton-selective M2 ion channel in the acidic trans-Golgi network activates the NLRP3 inflammasome (Ichinohe et al., 2010) . Interestingly, an M2 mutant in which histidine was substituted with glycine at position 37 (H37G), causing loss of proton selectivity, enables transport of other cations (i.e., Na + and K + ), thereby leading to enhanced secretion of IL-1β from LPS-primed BMMs and dendritic cells when compared with the wild-type M2 protein.
In addition, the 2B proteins of EMCV, poliovirus, enterovirus 71 (EV71), and human rhinovirus (a member of the Picornaviridae family) triggers NLRP3 inflammasome activation by inducing Ca 2+ flux from the ER and Golgi compartments (Ito et al., 2012; Triantafilou et al., 2013) . Furthermore, hepatitis C virus stimulates NLRP3 inflammasome-mediated IL-1β production though its p7 viroporin (Negash et al., 2013; Farag et al., 2017) . Third, a recent study has demonstrated that the 3D protein of EV71 directly interacts with NLRP3 to facilitate the assembly of NLRP3 inflammasome complex (Wang et al., 2017) .
In the case of SARS-CoV, the viroporin E forms forms Ca 2+permeable ion channels and activates the NLRP3 inflammasome (Nieto-Torres et al., 2015) . In addition, another viroporin 3a was found to induce NLRP3 inflammasome activation (Yue et al., 2018) . Although alanine substitution at Cys-133, which is required for dimer or tetramer formation (Lu et al., 2006) , still allows activation of the NLRP3 inflammasome by interacting with caspase-1 (Yue et al., 2018) , the ion channel activity-loss mutant 3a-CS (Cys-to-Ser substitution at positions Cys-127, Cys-130, and Cys-133) (Chan et al., 2009 ) completely abrogated IL-1β secretion from LPS-primed BMMs, suggesting that the 3a protein of SARS-CoV has the ability to induce the NLRP3 inflammasome activation by multiple mechanisms. Previous studies show that the 3a protein of SARS-CoV is localized to the plasma membrane (Minakshi and Padhan, 2014) and acts as a K + channel (Lu et al., 2006) , thereby (presumably) stimulating the K + efflux at the plasma membrane. Indeed, we found that IL-1β secretion caused by the 3a protein was significantly inhibited when the extracellular K + concentration increased to 130 mM. Although it remains unclear whether another viroporin 8a of SARS-CoV (Castano-Rodriguez et al., 2018) activates the NLRP3 inflammasome, these data highlights the importance of viroporins in SARS-CoV-induced NLRP3 inflammasome activation. A better understanding of the mechanism that governs the NLRP3 inflammasome will facilitate the development of more effective interventions for the treatment of infectious diseases and increase our understanding of viral pathogenesis. | What ion channel is essential for 3a-mediated IL-1Beta secretion? | false | 281 | {
"text": [
"ion channel activity of the 3a protein"
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2,519 | Detectable 2019-nCoV viral RNA in blood is a strong indicator for the further clinical severity
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7054964/
SHA: 77b0c98d1a2ca46b219ad090074814c387c80d8f
Authors: Chen, Weilie; Lan, Yun; Yuan, Xiaozhen; Deng, Xilong; Li, Yueping; Cai, Xiaoli; Li, Liya; He, Ruiying; Tan, Yizhou; Deng, Xizi; Gao, Ming; Tang, Guofang; Zhao, Lingzhai; Wang, Jinlin; Fan, Qinghong; Wen, Chunyan; Tong, Yuwei; Tang, Yangbo; Hu, Fengyu; Li, Feng; Tang, Xiaoping
Date: 2020-02-26
DOI: 10.1080/22221751.2020.1732837
License: cc-by
Abstract: The novel coronavirus (2019-nCoV) infection caused pneumonia. we retrospectively analyzed the virus presence in the pharyngeal swab, blood, and the anal swab detected by real-time PCR in the clinical lab. Unexpectedly, the 2109-nCoV RNA was readily detected in the blood (6 of 57 patients) and the anal swabs (11 of 28 patients). Importantly, all of the 6 patients with detectable viral RNA in the blood cohort progressed to severe symptom stage, indicating a strong correlation of serum viral RNA with the disease severity (p-value = 0.0001). Meanwhile, 8 of the 11 patients with annal swab virus-positive was in severe clinical stage. However, the concentration of viral RNA in the anal swab (Ct value = 24 + 39) was higher than in the blood (Ct value = 34 + 39) from patient 2, suggesting that the virus might replicate in the digestive tract. Altogether, our results confirmed the presence of virus RNA in extra-pulmonary sites.
Text: The 2019 novel coronavirus (2019-nCoV), originally outbreaking from Wuhan China, has transmitted in an extremely short period to 25 countries and infected over 31 000 individuals as of Feb 06, 2020, causing an international alarm. Basic scientific research has achieved significantly in the investigation of viral origination [1, 2] , transmission and evolution [3] , and unprecedented public health control actions in China have been activated and effectively prevented the otherwise dramatic spread. The 2019-nCoV virus seems more infectious in its public transmission capacity compared to the well-known 2003 SARS virus in spite of the unavailability of convincingly scientific evidence. The mechanism of viral transmission is still worthy of further exploration.
Currently, one urgent and critical challenge is to treat infected patients and save their lives. Several studies have roughly described the overall clinical features of 2019-nCoV patients [4, 5] . However, the more specific and classified clinical characteristics of the infected patients still require further investigation, particularly for those with severe symptoms, which is roughly estimated to be approximately 15-20 percent of totally confirmed cases based on the local data in our hospital. Clinically, for those severe patients, the main symptoms of 2019-nCoV pneumonia are fever, decreased white blood cell and lymphocyte count, increased C reaction protein and abnormally expressed cytokines [6] .
One remaining question to be resolved is whether the 2019-nCoV virus can replicate in extra-pulmonary sites, which might account for the deteriorated clinical manifestation. In this study, we investigated whether the patients with severe clinical symptoms exhibited special profiles of virus replication or/and distribution compared to those only with mild symptoms.
Patients, who were confirmed to be infected by the 2019-nCoV virus, were firstly enrolled in or transferred to Guangzhou Eighth People's Hospital for treatment purposes. This study followed the guideline of the Ethics Committee of Guangzhou Eighth People's Hospital. All blood, pharyngeal swab, and anal swab samples were collected for diagnostic purposes in the laboratory and our study added no extra burden to patients. Viral RNA was extracted with Nucleic Acid Isolation Kit (Da'an Gene Corporation, Cat: DA0630) on an automatic workstation Smart 32 (Da'an Gene Corporation) following the guidelines. Real-time reverse transcriptional polymerase chain reaction (RT-PCR) reagent (Da'an Gene cooperation, Cat DA0930) was employed for viral detection per the protocol. In brief, two PCR primer and probe sets, which target orf1ab (FAM reporter) and N (VIC reporter) genes separately, were added in the same reaction tube. Positive and negative controls were included for each batch of detection. Samples were considered to be viral positive when either or both set(s) gave a reliable signal(s).
All patients had pneumonia-based diseases but with diversified clinical manifestation. To simplify data analysis, the patients were only classified as either mild or severe clinical symptom groups based on the guideline newly released by Chinese government. Patients who were with at least one of the following symptom should be diagnosed to be severe case, 1) distress of respiratory with respiratory rate > = 30/min; 2) Oxygen saturation < = 93% in the rest state, and 3) arterial oxygen tension (PaO₂) over inspiratory oxygen fraction (FIO₂) of less than 300 mm Hg. In the blood detection cohort (Figure 1 (A)), patients who had at less one serum sample measurement with the PCR method were included. In the 57, 6 cases were detected to be blood positive, all of them (100%) were severe in symptom requiring special care attention, and the blood of the rest 51 cases was without detectable virus in the blood, only 12 of them (23.5%) were severe cases. The ratio of severe symptoms between these two groups was significantly different (p value = 0.0001). In the anal swab cohort (Figure 1 (B)), 11 of 28 cases were detected to be anal swab positive, 8 of them (72.7%) were with severe symptoms, which was significantly higher than that 4 (23.5%) of the rest 17 cases without detectable virus in anal were severe cases.
Fortunately, two cases with detectable virus both in blood and anal swab cohort were recorded. Patient 1 (Figure 2 (A)) was admitted to ICU after enrollment evaluation and was highly suspected infection with 2019-nCoV because of his recent travelling from Wuhan and of confirmed pneumonia by radiographic diagnosis with 5-day fever and 1-day continuous dry coughing. He was then confirmed to be infected by the 2019-nCoV virus on illness day 6 by CDC. High concentrations of the viral RNA were detected in the pharyngeal swabs on illness days 5 (Ct = 17 + 25), 7, 8 (Ct = 25 + 26), and 11 (Ct = 15 + 25). In the blood, no viral RNA was detected on day 5 but the sample on day 6 gave a weak positive signal (Ct = Neg+39), and then the signal was gone again on day 8. On day 9, a low level of viral RNA (Ct = 36 + 41) was detected again in the blood. On day 12, the blood lost signal again. A high concentration of virus RNA (Ct = 23 + 27) was detected in the anal sample on day 13, on the day the 2019-nCoV virus was not detected in the pharyngeal swab. Unfortunately, he was transferred out to another hospital after an emergency expert consultation.
Patient 2 (Figure 2 (B)), who had a clear infection history and started fever 5-day ago and dry coughing 2-day ago, was admitted with clinically highly suspect of 2019-nCoV infection, considering the radiographical diagnosis which indicated clear pneumonia in the bilateral lung lobes. The virus was detected in his blood on illness day 7 (Ct = 34 + 36) and 8 (Ct = 38 + 38). His infection was also informed by the CDC on day 8. Because his disease advanced very fast, he was transferred to the ICU ward for special medical care requirements on day 9, on which day high titers of virus (Ct = 25 + 36) were detected in the pharyngeal sample. Importantly, virus RNA was detected in all pharyngeal (Ct = 23 + 24), blood (Ct = 34 + 39) and anal (Ct = 24 + 29) samples on day 10. He was transferred out to another hospital after an emergency expert consultation.
Finally, we described here the four patients with detectable serum viral RNA. Patient 3 (Figure 3(A) ) was transferred to the ICU directly on illness day 11 because of his severe condition, the 2019-nCoV virus was laboratory detected both in pharyngeal (Ct = 30 + 30) and blood samples (Ct = 37 + 39) on day 12, And his infection was confirmed by CDC on day 13. Pharyngeal samples were PCR positive on days 14 and 17 and became negative on day 22. Patient 4 (Figure 3(B) ) was transferred to the ICU ward on the illness day 6 with a CDC confirmation. His disease advanced pretty fast and became severe on day 7 and he was transferred to ICU after his blood sample was detected to be virus-positive (Ct = 32 + 37). On day 9, he was transferred out. Patient 5 (Figure 3(C) ) was admitted on illness day 4 and his blood sample was virus-positive (Ct = 38 + Neg) on day 6. Her disease progressed rapidly to a severe stage within the next 3 days. Patient 6 ( Figure 3 (D)) with a clear history of virus infection was confirmed to be infected on infection day 7. Viral RNA was detected in his blood sample on day 9, one day ahead of his transfer into ICU. As his condition worsens, he was transferred out on day 13.
In this retrospective study, we analyzed the PCR data of virus detection in different tissues in our laboratory. Firstly, our observation indicated that the presence of viral RNA outside of the respiratory tract might herald the severity of the disease and alarm the requirement of special care. In the blood test cohort, all the 6 infected patients were in (or later progressed to) severe disease stage when serum viral RNA became detectable, which showed a significant difference compared to the blood negative group (p = 0.0001). Patient 2 (Figure 2(B) ), 5 (Figure 3 (C)) and 6 ( Figure 3(D) ) all had detectable viral RNA in the serum before they progressed to the clinical severe symptom stage. Unfortunately, we missed the earlier time points of patient 1 (Figure 2(A) ) and 3 (Figure 3(A) ) who were directly admitted to ICU on transfer to our hospital because of severe condition, of patient 4 (Figure 3(B) ) who had serum sample collected one day post the diagnosis of severe illness. We, fortunately, observed high serum viral load in serum within their severe illness stage. In the anal swab cohort, we found that the presence of virus RNA in the anal digestive tract was also positively correlated with disease severity (p = 0.0102). The 3 patients detected with anal virus RNA but in mild stage should be monitored whether they will progress to the severe stage. We have summarized the information of approximately 70 percent of the patients in Guangzhou city, and the study represented nearly the whole picture of this region. However, the virus outbroke in such an emergence, allowing no delay in waiting for more patients to further confirm the findings.
Secondly, a high concentration of viral RNA in anal swabs suggested the digestive tract might be one extrapulmonary site for virus replication. For patient 1, a high concentration of viral RNA (Ct = 23 + 27, on day 13) was detected in anal swab but not in pharyngeal (the same day) and blood (1 d ahead). For patient 2, higher concentrations of viral RNAs were detected in anal swab (Ct = 24 + 39) and pharyngeal swab (Ct = 23 + 24) than in the blood (Ct = 34 + 39) on the same day. Angiotensin-converting enzyme 2 (ACE2) still is one of the receptors for 2019-nCoV attachment and entry [2] . Intensive structural analysis of the S protein of 2019-nCoV with the SARS-Coronavirus suggested that several critical residues in the viral spike protein might confer favourable interaction with human ACE2 [7] . Of note, ACE2 is also abundantly present in humans in the epithelia of the small intestine besides the respiratory tract and is ubiquitously present in endothelial cells [8] , which might provide possible routes of transmission, and might account for the high transmission capacity of the new virus. We propose that rampant coronavirus replication in pulmonary alveolus results in the breakdown of the alveolar vessel and the subsequent virus leakage into the blood flow, through which the virus is disseminated across the whole body. Then the virus succeeds in establishing reinfection in the digestive tract by using the highly expressed ACE2 receptor, which exacerbated the disease vice versa. Bat originated coronavirus was found to replicate in the swine digestive tract recently, also suggesting the potential replication possibility in the human digestive tract [9] . Nevertheless, confirmation of virus transmission through the digestive tract warrants further virus isolation from the anal swab in high safety level lab.
Unfortunately, in our study, we did not collect stool samples from patients and did not pursue viral RNA in the stool. But we believe the existence of virus RNA in the stool samples from these patients because that a large amount of viral RNA was detected in anal swabs and that viral RNA had also been detected in a case reported from the United States [10] . Also, we didn't collect sputum and bronchoalveolar lavage fluid for virus detection because that the dry coughing characteristic of patients infected with 2019-nCoV prevents producing enough amount of sputum and that bronchoalveolar lavage fluid collection requires a sophisticated operation which increases virus exposure possibility of care providers to high concentrations of virus-containing aerosol.
In summary, we find that the presence of viral RNA in the blood and anal swab is positively correlated with the severe disease stage and that early monitoring of virus RNA in blood and the digestive tract on top of the respiratory tract might benefit the disease prediction. | What test could give an indication for special care for 2019-nCOV patients? | false | 1,171 | {
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1,569 | Techniques to Study Antigen-Specific B Cell Responses
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6667631/
SHA: ee632fa425607e8ff91fc3730bc0782d43ce9c0c
Authors: Boonyaratanakornkit, Jim; Taylor, Justin J.
Date: 2019-07-24
DOI: 10.3389/fimmu.2019.01694
License: cc-by
Abstract: Antibodies against foreign antigens are a critical component of the overall immune response and can facilitate pathogen clearance during a primary infection and also protect against subsequent infections. Dysregulation of the antibody response can lead to an autoimmune disease, malignancy, or enhanced infection. Since the experimental delineation of a distinct B cell lineage in 1965, various methods have been developed to understand antigen-specific B cell responses in the context of autoimmune diseases, primary immunodeficiencies, infection, and vaccination. In this review, we summarize the established techniques and discuss new and emerging technologies for probing the B cell response in vitro and in vivo by taking advantage of the specificity of B cell receptor (BCR)-associated and secreted antibodies. These include ELISPOT, flow cytometry, mass cytometry, and fluorescence microscopy to identify and/or isolate primary antigen-specific B cells. We also present our approach to identify rare antigen-specific B cells using magnetic enrichment followed by flow cytometry. Once these cells are isolated, in vitro proliferation assays and adoptive transfer experiments in mice can be used to further characterize antigen-specific B cell activation, function, and fate. Transgenic mouse models of B cells targeting model antigens and of B cell signaling have also significantly advanced our understanding of antigen-specific B cell responses in vivo.
Text: In his Nobel lecture in 1908, Paul Ehrlich likened the antibody-antigen interaction to a lock and key. He reasoned that antitoxins (antibodies) contained in a solution in the serum of immunized animals must be identical to a cellular receptor "for a really well-made key will not open different locks at the same time" (1) . It took almost five decades before immunofluorescence microscopy was used to confirm the cellular origin of antibodies (2) . Major strides in the B cell and antibody field followed in the 1970s with the development of hybridoma technology to produce monoclonal antibodies and the discovery that somatic rearrangement during B cell differentiation was responsible for antibody diversification (3, 4) . The subsequent explosion of available monoclonal antibodies led to revolutionary diagnostic, therapeutic, and research reagents to distinguish different types of immune cells (5) . Together, these discoveries have allowed us to probe humoral immunity at the level of the antigen-specific B cell.
Methods to probe the antigen-specific B cell response have advanced our understanding of how to harness the remarkable breadth of the B cell repertoire and the exquisite specificity of the individual B cell in developing (1) vaccine candidates that elicit protective antibodies; (2) antibodies that prevent disease when given prophylactically; and (3) antibodies that can be given as therapy after the onset of disease. Many of the vaccines currently available were originally developed empirically either by inactivating, attenuating, or administering a subunit of the pathogen. However, vaccine development against pathogens that are traditionally difficult to vaccinate against may rely on a deeper investigation of the B cell response to the antigens exposed on the surface of these pathogens.
For HIV-1, the discovery of broadly neutralizing antibodies (bnAbs) that protect against infection across diverse viral isolates has intensified efforts to understand the developmental pathway of the rare B cells that produce these antibodies (6) (7) (8) (9) . Insights into the ontogeny of these rare B cells could allow the design of a step-wise vaccine regimen that stimulates the germ-line precursor to expand and mature to produce circulating bnAbs which could protect against HIV acquisition (10, 11) . For RSV, stabilized versions of the fusion (F) protein in the pre-fusion conformation have led to insights in the B cell's response to infection and has generated potentially safer and more efficacious vaccine candidates (12, 13) . Influenza also performs fusion through the stem region of the hemagglutinin protein, and the identification of B cells that target this relatively conserved site has spurred research on the development of a universal influenza vaccine (14) (15) (16) . Like RSV, HIV, and influenza, the fusion proteins of EBV and CMV exist in a pre-fusion conformation, and stabilization in their pre-fusion states could greatly accelerate vaccine development against these pathogens (17-19). Rare memory B cells producing antibodies specific for the EBV fusion machinery have been isolated; these can neutralize both B cell and epithelial cell infection (20). A new paradigm in malaria vaccine development is also emerging with the discovery of IgM+ and IgD+ memory B cells targeting the Merozoite Surface Protein 1, that rapidly respond to malaria re-infection (21). Further, highly potent neutralizing antibodies targeting a novel and conserved site on the Circumsporozoite Protein have been isolated from B cells (22). Together, these examples demonstrate the importance of studying antigen-specific humoral responses to infectious diseases. The solutions to the crystal structures of surface proteins for a variety of pathogens, the conformational stabilization of these antigens, and the application of the methods summarized in this review, to probe antigen-specific B cell responses, have created new opportunities for systematic and rational vaccine design for HIV, RSV, EBV, malaria, and many other pathogens.
The study of B cell responses has not only informed vaccine design but has also advanced our understanding of antibodymediated autoimmune diseases, such as rheumatoid arthritis and systemic lupus erythematosus (23, 24). Up to 20% of mature, naïve B cells have receptors with the capacity to bind self-antigens (25). Although these cells are potentially pathogenic, the deletion of B cells with high affinity to self-antigen through apoptosis, anergy of B cells with low affinity to self-antigen, and the absence of T cell help combine together to protect against autoimmune disease in mice (26). The study of autoantigen-specific B cells and a detailed analysis of B cell subsets with pathogenic potential in humans could lead to a better understanding of how to prevent and treat autoimmune diseases.
Although the term antigen-specific B cell is used throughout this mini-review to denote the analysis of B cells based on binding between the B cell receptor (BCR) and a specific antigen used as bait, it is important to keep in mind that BCRs within the polyclonal B cell repertoire exhibit a spectrum of polyreactivity. On one end of the spectrum, a highly polyreactive BCR is able to bind multiple structurally unrelated antigens with physiologically relevant affinities. The frequency of polyreactivity in the normal adult human B cell repertoire has been estimated to be 4% of naïve B cells, 23% of IgG+ memory B cells, and 26% of intestinal IgA+ and IgG+ plasmablasts (27-29). On the other end of the spectrum, a mono reactive BCR is activated only when it encounters a single cognate antigen. Although there are exceptions, the accumulation of somatic hypermutations within the variable regions of the BCR during the process of affinity maturation is generally thought to lead to increased affinity and specificity for the cognate antigen (30, 31).
Several general techniques are commonly used to identify antigen-specific B cells ( Table 1 ). The B cell enzyme linked immunospot (ELISPOT) technique relies on the principle of capturing the secreted antibody in the vicinity of each cell. In the B cell ELISPOT, antibody secreting B cells (ASCs) present in a sample or differentiated in vitro are added to plates coated with the antigen of interest. Antigen-specific antibodies will bind in close proximity to the location of the individual B cells producing those antibodies. Enzyme or fluorescent labeled secondary antibodies are then used to visualize spots of antibody secretion and binding to plate-bound antigen at the location of the ASCs. Each spot corresponds to antibody produced from a single antigen-specific B cell and therefore the technique is extremely sensitive. Secondary antibodies conjugated to combinatorial colored beads can also be used to detect the antibodies secreted from individual B cells with the advantage of multiplexing the assay (32). One limitation of the assay is its requirement for antibody secretion by B cells thereby limiting the assay to only a subset of B cells in the repertoire, namely ASCs (33). Memory B cells can be stimulated in vitro to differentiate into ASCs prior to addition to the antigen-coated plate (34) . Further, the antigenspecific B cells identified by ELISPOT are generally not available for downstream analysis.
Limiting dilution is another technique that has been used to isolate antigen-specific B cells. In this approach, primary cells can be diluted serially until individual B cells are separated in microwell plates (36) . The B cells can then be cultured and expanded ex vivo and/or immortalized using EBV such that each well contains a monoclonal antibody (3, 37, 38) . Antigen-specific B cells can be selected by screening the culture supernatants for monoclonal antibodies that bind an antigen of interest. Although antibodies can be sequenced and cloned, the requirement for an ex vivo culture prior to selection precludes determination of the transcriptional profile of the original B cell in this approach. This technique can potentially be time-consuming and laborious, but the use of microfluidics and robotics has greatly improved the throughput for selecting antigen-specific B cells (39) . Advances in single cell next generation sequencing technology have allowed high throughput transcriptional profiling and sequencing of paired immunoglobulin heavy and light chains (40) . In this approach, antigen specificity can be tested after monoclonal antibodies are cloned and produced using the sequencing data. This method can be useful in identifying antigen-specific B cells that have undergone clonal expansion after vaccination or acute infection (41) . Flow cytometry is the most common method used for single cell analysis and isolation (39) . Flow cytometry-based analysis of antigen-specific B cells is dependent on labeling antigen with a fluorescent tag to allow detection. Fluorochromes can either be attached covalently via chemical conjugation to the antigen, expressed as a recombinant fusion protein, or attached non-covalently by biotinylating the antigen. After biotinylation, fluorochrome-conjugated streptavidin is added to generate a labeled tetramer of the antigen. Biotinylation of the antigen at a ratio ≤1 biotin to 1 antigen is important, since each streptavidin has the potential to bind four biotins. If the ratio of biotin to antigen is >1:1, then clumping and precipitation of the antigen out of solution can occur as soon as streptavidin is added. Alternatively, site directed biotinylation can be accomplished by adding either an AviTag or BioEase tag to the recombinant antigen prior to expression (77, 78) . When site-specific biotinylation is utilized, researchers must keep in mind that the tag may occlude an epitope from recognition by B cells which can be problematic for vaccine antigens. Further, for proteins that oligomerize, multiple tags may be incorporated, possibly resulting in aggregation.
Another important consideration is the potential for confounding by B cells in the repertoire that bind to the fluorochrome, streptavidin, or any linkers rather than to the antigen of interest. Binding between fluorochromes, linkers, or streptavidin and BCRs from humans and mice never exposed to these antigens are generally of low affinity, and these BCRs are generally expressed by naïve and potentially polyreactive B cells (62, 79, 80) . Dual labeling, in which the same antigen is separately labeled with two different fluorochromes, can be used to identify double positive B cells and remove confounding by B cells that bind the fluorochrome (12, 42) . However, even when tetramers are utilized for dual labeling, streptavidin-specific B cells will contaminate the double positive population. To fully remove confounding from the fluorochrome, streptavidin, and linkers, a "decoy" tetramer can be used to identify these contaminating B cells (21, 26). In this approach, the same fluorochrome used to identify antigen-specific B cells is conjugated to a different fluorochrome such that the emission spectrum is altered by fluorescence resonance energy transfer (FRET) (26). Decoy-binding B cells can therefore be excluded from the true antigen-specific B cells. Notably, it is critical to use the same source of fluorochrome conjugated streptavidin in the tetramer and decoy reagent, because conjugation methods, recombinant streptavidin, and protein fluorochromes like R-phycoerythrin vary enough from company to company to alter some of the epitopes available for B cells to bind.
One weakness of the flow cytometric approach is the reliance on antigens that can be readily conjugated to a fluorochrome or biotinylated. In addition to recombinant proteins and synthesized peptides, labeled polysaccharides, lipids, haptens, virus-like particles, and pseudo viruses have also been used to identify antigen-specific cells by flow cytometry (33, [43] [44] [45] [46] [47] [48] [49] [50] [51] [52] [53] [54] [55] [56] [57] [58] [59] . Further, epitope-specific B cells have been identified by screening bacteriophage-displays or microarray peptide libraries with polyclonal antibodies targeting the native antigen to select conformational epitopes that can be fused to fluorescent proteins for use in flow cytometry (47, 60) .
With technologic advancements increasing the number of simultaneously measurable parameters, antigen-specific B cells can be further characterized by cell surface markers and intracellular staining. Additionally, the immunoglobulin capture assay is a flow cytometry-based adaptation of the ELISPOT assay in which a streptavidin-conjugated anti-CD45 antibody carrying four biotinylated anti-IgG antibodies is used to simultaneously bind plasmablasts and capture secreted antibody followed by fluorescent-labeled antigen to detect antigenspecific plasmablasts (61) . The mean fluorescence intensity measured by flow cytometry and normalized to the level of BCR expression also provides a measure of the relative amount of antigen binding to a B cell and can be used as a rough surrogate for binding affinity (79, 81, 82) . Preincubation of B cells with increasing concentrations of a monomeric antigen prior to labeling with tetrameric antigen can also be used to further quantify binding affinity. Cells expressing high affinity BCRs will bind monomeric antigen at low concentrations, whereas low affinity BCRs will require higher concentrations of monomeric antigen to compete with and inhibit tetramer binding (26). Individual cells can also be isolated by fluorescence activated cell sorting (FACS) for downstream analysis, including BCR sequencing and cloning, BCR affinity measurement, in vitro proliferation, and transcriptional profiling.
Methods have recently been developed to further improve the sensitivity for detecting rare antigen-specific B cells. Magnetic nanoparticles conjugated to antibodies targeting the fluorochrome on the antigen of interest, allow for the enrichment of antigen-specific B cells prior to flow cytometry (20, 26, 80, 83) . This approach is particularly useful for detecting rare antigenspecific naïve B cells, autoreactive B cells, memory B cells, and plasmablasts (21, 26, 47, 50) . The magnetic enrichment strategy allows for the analysis of significantly more cells in a shorter period of time by concentrating the cells of interest prior to flow cytometry (Figure 1) . Notably, as with any method that seeks to identify a population of cells at a very low frequency, the background and noise inherent in the detection system is magnified with respect to the signal of interest, especially when that signal is weak. Therefore, to detect the antigen-specific population of interest, the following considerations are critical: (1) Using decoys to exclude B cells of unwanted specificities;
(2) careful design of flow cytometry panels to avoid emission spillover into the channel for the antigen of interest; and (3) choosing the brightest fluorochromes, like R-phycoerythrin or allophycocyanin.
In vivo methods to probe antigen-specific B cell responses in the presence of other antigen-presenting cells and T cell helpers, have increased our mechanistic understanding of the humoral immune response during vaccination, infection, and autoimmunity. Adoptively transferred B cells can be distinguished from recipient lymphocytes by taking advantage of mouse strains with allelic variations in CD45 or mice devoid of B cells. The adoptively transferred B cells can come from wildtype mice or from mice expressing transgenic BCRs ( Table 2) , and antigen-specific B cells can be analyzed using the techniques described above.
Microscopy is another general technique that has been used to identify antigen-specific cells in vivo and offers the advantage of direct visualization. In the first reported application of this technique to demonstrate the cellular origin of antibodies in 1955, fluorescein-conjugated antibodies against ovalbumin and human immunoglobulin were used to stain tissue sections of the spleen from hyperimmune rabbits (2) . Since then, other groups have fluorescently labeled antigens to localize antigen-specific B cells by microscopy (62, 65) . Advances in laser capture dissection microscopy, already used in the T cell field, also provide an opportunity for isolating individual antigen-specific B cells for downstream analysis, including sequencing and cloning of the BCR or transcriptional profiling (66) . However, antigen staining of BCRs in situ can be challenging depending on the binding of antigens from pathogens to other cellular receptors or an alteration of BCR specificity during tissue fixation or processing. Two-photon or multiphoton microscopy has the ability to resolve images at greater depths and with less photobleaching than confocal microscopy (67, 68) . As a result, this technology has allowed real-time imaging in living, intact lymphoid tissues of mice, permitting the direct in vivo observation of immune cell interactions. The dynamic movements and interactions of antigen-specific B cells can be studied in vivo by combining an adoptive transfer of individual B cells (isolated by limiting dilution or FACS) with two-photon microscopy (63, 69, 70) .
Humanized mouse models are powerful tools for translating experiments in mice to applications in humans. Transgenic mice that produce humanized cytokines by knock-in replacement can be used to support human hematopoietic stem cells (104) . Transgenic mice with complete humanization of the mouse immunoglobulin loci provide an opportunity for recapitulating the breadth of the human B cell repertoire and serve as a valuable tool for therapeutic antibody discovery (71) . However, one caveat is that the allele frequencies found in the B cell repertoires of these mouse models may not necessarily recapitulate those found in humans (72) . Mass cytometry has the potential to provide further high-dimensional analysis of antigen-specific B cells. In this method, heavy metal ion tags rather than fluorochromes are used to label cells. Since data is collected as time-offlight mass spectrometry, up to 42 unique parameters can be simultaneously measured from a single sample without significant spillover between channels or the need for compensation. Mass cytometry with heavy metal-labeled tetramers can be constructed using streptavidin (73) . Mass cytometry with metal-labeled peptide-MHC tetramers has been used successfully to identify and characterize antigen-specific T cells, but to our knowledge has not yet been applied to antigen-specific B cells (73, 74) . One limitation of this approach is that cells are unavailable for downstream analysis since they are vaporized by a plasma torch to atomize the ion tags. However, by simultaneously detecting many more surface markers and intracellular cytokines, transcription factors, and detecting more signaling molecules from individual cells than previously possible with traditional fluorescent labels, the application of mass cytometry with dimensionality reduction algorithms could help dissect the complexity of the B cell compartment, provide a higher resolution view of B cell development, and reveal novel subsets of antigen-specific B cells involved in mediating autoimmune diseases or protection against infection.
On the horizon, single cell RNA-sequencing (RNA-seq) technologies have the potential to revolutionize the study of antigen-specific immune cells (75, 76) . The ability to generate a library of tetramers with unique barcodes could allow the simultaneous examination of gene expression profiles from a large number of cells with different antigen specificities in a single experiment. Combining barcoded tetramers with oligonucleotide-conjugated antibodies and RNA-seq to simultaneously measure the protein and gene expression of antigen-specific cells could further increase the amount of unbiased multi-omic information about individual antigen-specific cells in normal and disease states and aid the rational design of vaccines and therapeutics (105) (106) (107) .
The ongoing analysis of antigen-specific B cell responses has led to the development of new diagnostic, therapeutic, and research reagents. Methods for studying antigen-specific B cell responses are being increasingly applied to tackle diseases like HIV, RSV, and autoimmune diseases, in which the immune response either fails to protect or clear disease, or where it enhances disease or is responsible for the disease itself. Considerable opportunities exist on the horizon for applying these methods to a myriad of diseases in which B cells play an active role.
JB and JT reviewed the literature, generated figures and tables, and wrote the manuscript. | What is the role of antibodies during infection? | false | 465 | {
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2,643 | Responding to the COVID-19 pandemic in complex humanitarian crises
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085188/
SHA: d013e42811c6442b184da3b9bbfd9e334031a975
Authors: Poole, Danielle N.; Escudero, Daniel J.; Gostin, Lawrence O.; Leblang, David; Talbot, Elizabeth A.
Date: 2020-03-21
DOI: 10.1186/s12939-020-01162-y
License: cc-by
Abstract: nan
Text: Over 168 million people across 50 countries are estimated to need humanitarian assistance in 2020 [1] . Response to epidemics in complex humanitarian crisessuch as the recent cholera epidemic in Yemen and the Ebola epidemic in the Democratic Republic of Congois a global health challenge of increasing scale [2] . The thousands of Yemeni and Congolese who have died in these years-long epidemics demonstrate the difficulty of combatting even well-known pathogens in humanitarian settings. The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may represent a still greater threat to those in complex humanitarian crises, which lack the infrastructure, support, and health systems to mount a comprehensive response. Poor governance, public distrust, and political violence may further undermine interventions in these settings.
Populations affected by humanitarian crises are expected to be particularly susceptible to COVID-19, the disease caused by SARS-CoV-2, due to displacement, crowded housing, malnutrition, inadequate water, sanitation, and hygiene (WASH) tools, and stigmatization. Disease outbreaks further reduce access to limited healthcare, which is increasingly disrupted by attacks on health facilities and the persistent overburdening of health systems. These situations escalate both the necessity and the difficulty of delivering accurate and actionable information to potentially affected populations [3] .
As the international community responds to SARS-CoV-2, public health authorities in humanitarian crises begin at a disadvantage to enact appropriate infection control to prevent transmission in healthcare settings, identify infectious cases, administer supportive care and novel treatments for the seriously ill, and trace contacts. These standard public health measures are particularly difficult to perform in humanitarian settings. For example, limited public health, laboratory, and primary care services represent a barrier to testing. Providing the limited healthcare worker cadre with appropriate training and personal protective equipment, and ensuring a continuous supply chain for such, is a challenge in all settings, exacerbated in complex humanitarian crises. Frequent displacement and limited contact information may prevent effective contact tracing. Finally, intractable structural challenges such as overcrowding limit the implementation of both quarantine of those exposed and isolation of those who are ill. Given these increased vulnerabilities, humanitarian crises should be viewed as a priority for national and international bodies that seek to combat this unfolding pandemic. Resources must be identified to protect healthcare workers, develop and deploy rapid testing, improve surveillance, and enact quarantine and isolation of contacts and cases.
To mitigate the impact of COVID-19 on crisesaffected populations, governments and agencies will implement the familiar, global evidence-based approaches for combatting respiratory viruses. Respiratory hygiene is a highly effective public health intervention, supported by evidence demonstrating that the spread of respiratory viruses, such as SARS-CoV-2, can be prevented by hand hygiene, safe cough practice, and social distancing [4] . Hand hygiene is a readily implemented behavior: the distribution of soap to households in humanitarian settings has been shown to increase handwashing by over 30% [5] . Furthermore, hand hygiene is an avenue of agency for protecting one's own health, consistent with the rights to dignity and to fully participate in decisions related to assistance in humanitarian crises. Widespread introduction of alcohol-based hand rubs is also possible in many resource-limited settings, with published protocols for local production [6] .
The Sphere Handbook, a collection of rights-based guidelines for humanitarian response, is the foremost authority on minimum standards for humanitarian assistance [7] . However, despite the indisputable evidence for the efficacy of hand hygiene for reducing both bacterial and viral pathogen transmission, humanitarian WASH standards are based on evidence pertaining to the prevention of illnesses transmitted by the faecal-oral route, with the focus on hand hygiene proximate to latrines [5, 8] . And yet, latrines in crisis settings are often shared and distant from residential shelters, conferring a high risk of gender-based violence [9] . Gender-based violence around latrines is an important deterrent for accessing latrine-adjacent handwashing stations, particularly for hand hygiene to prevent respiratory pathogen transmission.
Evidence-based guidelines alone in complex humanitarian crises may not suffice during the emergence of the current SARS-CoV-2 pandemic. Without the adaptation of existing standards, mitigation plans will fall short of health and human rights obligations in outbreak response. Crisis-affected community engagement is integral in pandemic planning, in order to maximize the real-world effectiveness of efficacious interventions. Transparent and credible information-sharing mechanisms are increasingly essential when pandemics threaten vulnerable populations [10] . Diplomacy bridging long-standing mistrust of public health and biomedical interventions and facilitating engagement with contentious actors is a necessary component of effective health governance in complex crisis settings [2] . Interventions tailored to the needs of crisis-affected populations, delivered with transparent information, in the context of inclusive governance practices, are urgently needed in the global response to the COVID-19 pandemic. | How many people are estimated to need humanitarian assistance in 2020? | false | 1,909 | {
"text": [
"168 million people across 50 countries"
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1,588 | Prediction of lncRNA-protein interactions using HeteSim scores based on heterogeneous networks
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5473862/
SHA: f4f9ea9e0aeb74d3601ee316b84292638c59cc53
Authors: Xiao, Yun; Zhang, Jingpu; Deng, Lei
Date: 2017-06-16
DOI: 10.1038/s41598-017-03986-1
License: cc-by
Abstract: Massive studies have indicated that long non-coding RNAs (lncRNAs) are critical for the regulation of cellular biological processes by binding with RNA-related proteins. However, only a few experimentally supported lncRNA-protein associations have been reported. Existing network-based methods are typically focused on intrinsic features of lncRNA and protein but ignore the information implicit in the topologies of biological networks associated with lncRNAs. Considering the limitations in previous methods, we propose PLPIHS, an effective computational method for Predicting lncRNA-Protein Interactions using HeteSim Scores. PLPIHS uses the HeteSim measure to calculate the relatedness score for each lncRNA-protein pair in the heterogeneous network, which consists of lncRNA-lncRNA similarity network, lncRNA-protein association network and protein-protein interaction network. An SVM classifier to predict lncRNA-protein interactions is built with the HeteSim scores. The results show that PLPIHS performs significantly better than the existing state-of-the-art approaches and achieves an AUC score of 0.97 in the leave-one-out validation test. We also compare the performances of networks with different connectivity density and find that PLPIHS performs well across all the networks. Furthermore, we use the proposed method to identify the related proteins for lncRNA MALAT1. Highly-ranked proteins are verified by the biological studies and demonstrate the effectiveness of our method.
Text: most commonly used approach is guilt-by-association (GBA) 19 , which provides the central top-down principle for analyzing gene networks in functional terms or assessing their quality in encoding functional information. New emerged methods, including the Katz method 20 , Combining dATa Across species using Positive-Unlabeled Learning Techniques(CATAPULT) 19 , Random Walk with Restart (RWR) 21 , and LncRNA-protein Interaction prediction based on Heterogeneous Network model (LPIHN) 22 , have extended the association from just direct protein interactions to more distant connections in various ways. The KATZ measure 20 is a weighted sum of the number of paths in the network that measures the similarity of two nodes. CATAPULT 19 is a supervised machine learning method that uses a biased support vector machine where the features are derived from walks in a heterogeneous gene-trait network. RWR 21 is a method for prioritization of candidate genes by use of a global network distance measure, random walk analysis, for definition of similarities in protein-protein interaction networks and it add weight to the assumption that phenotypically similar diseases are associated with disturbances of subnetworks within the larger protein interactome that extend beyond the disease proteins themselves. LPIHN 22 is a network-based method by implement a random walk on a heterogeneous network. PRINCE is a global method based on formulating constraints on the prioritization function that relate to its smoothness over the network and usage of prior information. Compared with LPIHN and RWR, PRINCE propagates information in a smaller network but contains more connotative meaning when build the initial probability values and has made great performance in gene prioritization 23 and disease identification 24 .
However, many existing network-based methods simply view objects in heterogeneous networks as the same type and do not consider the subtle semantic meanings of different paths. In this paper, we adopt a method named HeteSim, which is a path-based measure to calculate the relevance between objects in heterogeneous network 25 . The basic idea is that similar objects are more likely to be related to some other objects. Considering the relatedness of heterogeneous objects is path-constrained, HeteSim gives a uniform and symmetric measure for arbitrary paths to evaluate the relatedness of heterogeneous object pair (same or different types) with one single score. Due to the relevance path not only captures the semantics information but also constrains the walk path, the score is also a path-based similarity measure.
An example of HeteSim score is illustrated in (Fig. 1 ). The number of paths from A to C and B to C is 3 and 2, respectively. The walk count between A and C is larger than B and C, which might indicate that A is more closer to C than B. But the connectivity between B and C is more intense than A and C in the sight of HeteSim score, since most edges starting from B are connected with C, when A only has a small part of edges connected with C.
Here, we propose a method named PLPIHS (Fig. 2) to predict lncRNA-Protein interactions using HeteSim scores. We first construct a heterogeneous network consisting of a lncRNA-lncRNA similarity network, a lncRNA-protein association network and a protein-protein interaction network. Then, we use the HeteSim measure to calculate the score for each lncRNA-protein pair in the network. A SVM classifier is built based on the scores of different paths. We compare our PLPIHS with PRINCE, RWR and LPIHN and find that PLPIHS outperforms the other methods in many performance measures.
Validation measures. LOOCV(Leave-One-Out Cross Validation) 26 is implemented on the verified lncR-NA-protein associations to evaluate the performance of LPIHN 22 . We leave a known lncRNA-protein pair in turn as the test sample and all the other known lncRNA-protein pairs are regarded as training samples. In order to improve the accuracy of PLPIHS, we remove all connected lncRNAs and proteins while in each validation round. Receiver Operating Characteristic(ROC) curve 27 is used to evaluate the prediction performance, which plots true-positive rate (TPR, sensitivity or recall) versus false-positive rate (FPR, 1-specificity) at different rank cutoffs. When varying the rank cutoffs of successful prediction, we can obtain the corresponding TPR and FPR. In this way, ROC curve is drawn and the area under the curve(AUC) is calculated as well. For a rank threshold, sensitivity(SEN) 28 and specificity(SPE) 29 These measurements are also used to assess the capability of PLPIHS during the preprocessing procedure.
Affection of network preprocessing characteristics. In this paper, we only have two kinds of objects, lncRNA and protein. Thus, the paths from a lncRNA to a protein in our heterogeneous network with length less than six is listed in Table 1 . In order to pick out the most efficient paths, we compared the performances of these 14 paths under different combinations (Fig. 3) . We can see that all paths achieve a favorable status except path 1′~2′. Path 1′~14′ obtains the best performance across all measures, which means that the path with length greater than three contains more significant meanings. The constant factor β is used to control the influence of longer paths. The longer the path length is, the smaller the inhibiting factor is. Path length equals 3 matches with constant β, path length equals 4 matches with constant β*β and path length equals 5 matches with constant β*β*β. Table 2 shows that β has tiny impact on the final results and β = 0.2, 0.4 and 0.7 achieved the best AUC score and the others are not far behind yet.
To further verify the dependability of our method, we compare the three networks of different connectivity density under different cutoff value 0.3, 0.5 and 0.9 (see lncRNA-Protein associations). The results are shown in Fig. 4 . There are tiny performance differences between different sparse networks. The AUC score of the 0.5 network is higher than that of others while the 0.9 network outperforms others in ACC, SEN, MCC and F1-Score. This suggests that PLPIHS performs well across networks with different densities. Table 1 . The paths from a lncRNA to a protein in our heterogeneous network with length less than six.
the RWR method, there is only one restart probability r and it's effects is very slight, which is proved by experiments. The parameter r is set as 0.5 in this comparison. In order to calculate the performance of the different methods, we use a leave-one-out cross validation procedure. We extract 2000 lncRNA-protein associations from the 0.9 network as positive samples, the same number of negative samples are chosen randomly from the 0.3 network as well, avoiding the error caused by imbalance dataset. The gold set which containing 185 lncRNA-protein interactions downloaded from NPinter database has been included in positive pairs as well. In the lncRNA protein prioritization, each lncRNA-protein interaction is utilized as the test set in turn and the remaining associations are used as training data. The whole experiment will be repeated 4000 times to testing each lncRNA-protein pairs in the dataset. ROC curve is drawn based on true positive rate (TPR) and false positive rate (FPR) at different thresholds. The AUC score is utilized to measure the performance. AUC = 1 demonstrates the perfect performance and AUC = 0.5 demonstrates the random performance.The ROC curve of PLPIHS, LPIHS, PRINCE and RWR are plotted in Fig. 5 . The results show that the AUC score of PLPIHS in 0.3 network is 96.8%, which is higher than that of PRINCE, LPIHN and RWR, achieving an AUC value of 81.3%, 88.4% and 79.2%, respectively. Similarly, PLPIHS outperforms other methods in 0.5 network and 0.9 network as well.
Performance evaluation by independent test. For further validation, we also randomly selected 2000 lncRNA-protein associations from the rest of positive samples in 0.9 network and the same number of negative interactions are picked out from the remaining negative samples of 0.3 network to generate the independent test data set. Since the existing network based methods is not suitable for independent test, we only evaluate the performance for the proposed PLPIHS. The independent test results are shown in Fig. 6 , an AUC score of 0.879 is achieved by PLPIHS, illustrating the effectiveness and advantage of the proposed approach. Case Studies. By applying the proposed PLPIHS method, novel candidate lncRNA-related proteins are predicted using LOOCV. We applied PLPIHS onto the 2000 known lncRNA-protein associations, which includes 1511 lncRNAs and 344 proteins to infer novel lncRNA-protein interactions. As a result, an area under the ROC curve of 0.9669, 0.9705 and 0.9703 (Fig. 5) is achieved using the three networks of different connectivity density, which demonstrate that our proposed method is effective in recovering known lncRNA-related proteins.
To further illustrate the application of our approach, a case study of lncRNA MALAT1(ensemble ID: ENSG00000251562) is examined. MALAT1 is a long non-coding RNA which is over-expressed in many human oncogenic tissues and regulates cell cycle and survival 31 . MALAT1 have been identified in multiple types of physiological processes, such as alternative splicing, nuclear organization, epigenetic modulating of gene expression. A large amount of evidence indicates that MALAT1 also closely relates to various pathological processes, including diabetes complications, cancers and so on 32, 33 .
MALAT1 is associated with 68 proteins in NPInter 3.0 34 . We construct the interaction networks of lncRNA MALAT1 by using the prediction results of these four methods (Fig. 7) . Among the 68 known lncRNA-protein interactions, PLPIHS wrongly predicts 6 interactions, while 13 associations are predicted mistakenly by PRINCE and RWR method and 15 lncRNA-protein pairs are falsely predicted by the LPIHN method.
We manually check the top 10 proteins in the ranked list under 0.5 network ( Table 3) .Three of the top 10 predicted proteins have interactions with MALAT1, and most of them had high ranks in the predicted protein lists. For example, In the investigation of colorectal cancer (CRC), MALAT1 could bind to SFPQ, thus releasing PTBP2 from the SFPQ/PTBP2 complex and the interaction between MALAT1 and SFPQ could be a novel therapeutic target for CRC 35 . MALAT1 interacts with SR proteins (SRSF1, SRSF2, SRSF3 and SRSF5) and regulates cellular levels of phosphorylated forms of SR proteins 36 . And it is also as target of TARDBP to play the biological performance and found that TDP-43 bound to long ncRNAs in highly sequence-specific manner in tissue from subjects with or without FTLD-TDP, the MALAT1 ncRNA recruits splicing factors to nuclear speckles and affects phosphorylation of serine/arginine-rich splicing factor proteins 37, 38 . All these results indicate that our proposed method is effective and reliable in identifying novel lncRNA-related proteins.
LncRNAs are involved in a wide range of biological functions through diverse molecular mechanisms often including the interaction with one or more protein partners 12, 13 . Only a small number of lncRNA-protein interactions have been well-characterized. Computational methods can be helpful in suggesting potential interactions for possible experimentation 25 . In this study, we use HeteSim measure to calculate the relevance between lncRNA and protein in a heterogeneous network. The importance of inferring novel lncRNA-protein interactions by considering the subtle semantic meanings of different paths in the heterogeneous network have been verified 39 . We first construct a heterogeneous network consisting of a lncRNA-lncRNA similarity network, a lncRNA-protein association network and a protein-protein interaction network. Then, we use the HeteSim measure to calculate a score for each lncRNA-protein pairs in each path. Finally, a SVM classifier is used to combine the scores of different paths and making predictions. We compare the proposed PLPIHS with PRINCE, RWR and LPIHN and find that PLPIHS obtain an AUC score of 0.9679 in 0.3 network, which is significantly higher than PRINCE, RWR and LPIHN (0.813, 0.884 and 0.7918, respectively). We also compare the performance of these four methods in networks of different connectivity density. As a result, PLPIHS outperforms the other method across all the networks. Moreover, when analysing the predicted proteins interacted with lncRNA MALAT1, PLPIHS successfully predicts 63 out of 68 associations, while PRINCE, RWR and LPIHN retrieve much lower interactions of 57, 57 and 53, respectively. And the top-ranked lncRNA-protein interactions predicted by our method are supported by existing literatures. The results highlight the advantages of our proposed method in predicting possible lncRNA-protein interactions.
Methods lncRNA-Protein associations. All human lncRNA genes and protein-coding genes are downloaded from the GENCODE Release 24 9 . A total of 15941 lncRNA genes and 20284 protein-coding genes are extracted. To obtain genome-wide lncRNA and protein-coding gene associations, we combine three sources of data:
• Co-expression data from COXPRESdb 40 . Three preprocessed co-expression datasets (Hsa.c4-1, Hsa2.c2-0 and Hsa3.c1-0) including pre-calculated pairwise Pearson's correlation coefficients for human were collected from COXPRESdb. The correlations are calculated as follows:
where C(l, p) is the overall correlation between gene l (lncRNA) and protein-coding gene p, C d (l, p) is the correlation score between l and p in dataset d, D is the number of gene pairs (l and p) with positive correlation scores. Gene pairs with negative correlation scores are removed.
• Co-expression data from ArrayExpress 41 and GEO 42 . We obtained the co-expresionn data from the work of Jiang et al. 43 . RNA-Seq raw data of 19 human normal tissues are obtained from ArrayExpress (E-MTAB-513) and GEO (GSE30554). TopHat and Cufflinks with the default parameters are used to calculate the expression values. Pearson's correlation coefficients are used to evaluate the co-expression of lncRNA-protein pairs. • lncRNA-protein interaction data. We download known lncRNA-protein interaction dataset from Protein-protein interactions. We obtain the protein-protein interaction (PPI) data from STRING database V10.0 45 , which contains weighted protein interactions derived from computational prediction methods, high-throughput experiments, and text mining. The confidence scores are computed by combining the probabilities from the different evidence channels, correcting for the probability of randomly observing an interaction.
The HeteSim measure. The HeteSim measure is a uniform and symmetric relevance measure. It can be used to calculate the relatedness of objects with the same or different types in a uniform framework, and it is also a path-constrained measure to estimate the relatedness of object pairs based on the search path that connects two objects through a sequence of node types 39 . Further, the HeteSim score has some good properties (i.e., selfmaximum and symmetric), which have achieved positive performance in many studies 25 . In this study, we use HeteSim scores to measure the similarities between lncRNAs and proteins.
Definition 1 Transition probability matrix 39 L and P are two kinds of object in the heterogeneous network, (I LP ) n*m is an adjacent matrix between L and P, then the normalized matrix of I LP along the row vector is defined as
LP LP k m LP 1 Definition 2 Reachable probability matrix 39 In a heterogeneous network, the reachable probability matrix R for path = + PP P ( ) n 1 2 1 of length n, where P i belongs to any objects in the heterogeneous network, can be expressed as
P P P P P P n n 1 2 2 3 1 Based on the definitions above, the steps of calculating HeteSim scores between two kinds of objects (lncRNA and protein) can be presented as follows:
• Split the path into two parts. When the length n of path is even, we can split it into = P P ( )
Otherwise, if n is odd, the path cannot be divided into two equallength paths. In order to deal with such problem, we need to split the path twice by setting , respectively. Then, we can obtain a HeteSim score for each mid value, the final score will be the average of the two scores.
• Achieve the transition probability matrix and reachable probability matrix under the path L and R . • Calculate the HeteSim score: where − R 1 is the reverse path of R . An example of calculating HeteSim score is indicated in Fig. 8 . We can see that there are three kinds of objects L, T and P in the network. The simplified steps of computing HeteSim score between l3 and p2 under the path = (LTP) is as follows:
• Split the path into two components = LT ( )
• Given the adjacent matrix I LT and I TP below, which means the interactions between lncRNAs and proteins, we can obtain the transition probability matrix T LT and T TP by normalizing the two matrix along the row vector. The PLPIHS method. Among a heterogeneous network, different paths can express different semantic meanings. For instance, a lncRNA and a protein is connected via 'lncRNA-lncRNA-protein' path or 'lncRNA-protein-protein' path representing totally different meanings. The former means that if a lncRNA is associated with a protein, then another lncRNA similar to the lncRNA will be potential associated with the protein. The latter shows that if a protein associated with a lncRNA, then another protein interacted with the protein will be likely associated with the lncRNA. Therefore, the potential information hidden in each path is extraordinary essential to be taken into account during prediction.
The PLPIHS framework is illustrated in Fig. 2 . Firstly, we construct a heterogeneous network consisting of a lncRNA-lncRNA similarity network, a lncRNA-protein association network and a protein-protein interaction network. Three kinds of sparse networks are obtained from the heterogeneous network under different cutoff value 0.3, 0.5 and 0.9 (see lncRNA-Protein associations). The larger cutoff is, the network is more sparse. A total of 15941 lncRNAs genes and 20284 protein-coding genes are extracted as presented in Section 2.3. We randomly take out 1511 lncRNAs and 344 proteins to construct a smaller network for the following experiments in consideration of computing costs. The construction of the smaller heterogeneous networks under different cutoff values are shown in Table 4 , where 'lnc2lnc' denotes the lncRNA-lncRNA network, 'lnc2code' denotes the lncRNA-protein network and 'code2code' denotes the protein-lncRNA network. Table 1 . We use id to indicate the path combination, i.e., 1′~2′ represents path 'LLP' and path 'LPP' . Next, we calculate the heteSim score for each lncRNA-protein pair under each path. The results of different paths are used as different features. And we combine a constant factor β to inhibit the influence of longer paths.The longer the path length is, the smaller the inhibiting factor is. Finally, a SVM classifier is built with these scores to predict potential lncRNA-protein associations. On the account of the HeteSim measure is based on the path-based relevance framework 39 , it can effectively dig out the subtle semantics of each paths. | What are critical to regulate cellular biological processes? | false | 3,687 | {
"text": [
"long non-coding RNAs"
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1,568 | Etiology of respiratory tract infections in the community and clinic in Ilorin, Nigeria
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5719735/
SHA: f2e835d2cde5f42054dbd0c20d4060721135c518
Authors: Kolawole, Olatunji; Oguntoye, Michael; Dam, Tina; Chunara, Rumi
Date: 2017-12-07
DOI: 10.1186/s13104-017-3063-1
License: cc-by
Abstract: OBJECTIVE: Recognizing increasing interest in community disease surveillance globally, the goal of this study was to investigate whether respiratory viruses circulating in the community may be represented through clinical (hospital) surveillance in Nigeria. RESULTS: Children were selected via convenience sampling from communities and a tertiary care center (n = 91) during spring 2017 in Ilorin, Nigeria. Nasal swabs were collected and tested using polymerase chain reaction. The majority (79.1%) of subjects were under 6 years old, of whom 46 were infected (63.9%). A total of 33 of the 91 subjects had one or more respiratory tract virus; there were 10 cases of triple infection and 5 of quadruple. Parainfluenza virus 4, respiratory syncytial virus B and enterovirus were the most common viruses in the clinical sample; present in 93.8% (15/16) of clinical subjects, and 6.7% (5/75) of community subjects (significant difference, p < 0.001). Coronavirus OC43 was the most common virus detected in community members (13.3%, 10/75). A different strain, Coronavirus OC 229 E/NL63 was detected among subjects from the clinic (2/16) and not detected in the community. This pilot study provides evidence that data from the community can potentially represent different information than that sourced clinically, suggesting the need for community surveillance to enhance public health efforts and scientific understanding of respiratory infections.
Text: Acute Respiratory Infections (ARIs) (the cause of both upper respiratory tract infections (URIs) and lower respiratory tract infections (LRIs)) are a major cause of death among children under 5 years old particularly in developing countries where the burden of disease is 2-5 times higher than in developed countries [1] . While these viruses usually cause mild cold-like symptoms and can be self-limiting, in recent years novel coronaviruses such as severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) have evolved and infected humans, causing severe illness, epidemics and pandemics [2] . Currently, the majority of all infectious disease outbreaks as recorded by the World Health Organization (WHO) occur in the continent of Africa where there is high transmission risk [3, 4] . Further, in developing areas (both rural and urban), there are increasing risk factors such as human-animal interfaces (due to residential-proximity to livestock). These changing epidemiological patterns have resulted in calls for improved ARI surveillance, especially in places of high transmission risk [5] .
Nigeria is one such place with high prevalence of many of the risk factors implicated in ARI among children including; age, sex, overcrowding, nutritional status, socio-economic status, and where study of ARIs is currently limited [6] . These broad risk factors alongside limited resources have indicated the need for community-based initiatives for surveillance and interventions [6, 7] . For ARI surveillance in particular, infections in the community are those that do not get reported clinically. Clinical data generally represents the most severe cases, and those from locations with access to healthcare institutions. In Nigeria, hospitals are visited only when symptoms are very severe. Thus, it is hypothesized that viral information from clinical sampling is insufficient to either capture disease incidence in general populations or its predictability from symptoms [8] . Efforts worldwide including in East and Southern Africa have been focused on developing community-based participatory disease surveillance methods [9] [10] [11] [12] [13] . Community-based approaches have been shown useful for learning more about emerging respiratory infections such as assessing under-reporting [14] , types of viruses prevalent in communities [10] , and prediction of epidemics [15] .
Concurrently, advancements in molecular identification methods have enabled studies regarding the emergence and epidemiology of ARI viruses in many locations (e.g. novel polyomaviruses in Australia [16, 17] , human coronavirus Erasmus Medical Center (HCoV-EMC) in the Middle East and United Kingdom [18, 19] , SARS in Canada and China [20] [21] [22] ), yet research regarding the molecular epidemiology of ARI viruses in Nigeria is limited. Diagnostic methods available and other constraints have limited studies there to serological surveys of only a few of these viruses and only in clinical populations [23, 24] . Thus, the utility of community-based surveillance may be appropriate in contexts such as in Nigeria, and the purpose of this pilot study was to investigate if clinical cases may describe the entire picture of ARI among children in Nigeria.
We performed a cross-sectional study in three community centers and one clinical in Ilorin, Nigeria. Ilorin is in Kwara state and is the 6th largest city in Nigeria by population [25] . Three Local Government Areas (Ilorin East, Ilorin South and Ilorin West LGAs) were the community sites and Children's Specialist Hospital, Ilorin the clinical site. Convenience sampling was used for the purposes of this pilot study, and samples were obtained from March 28 to April 5 2017. Inclusion criteria were: children less than 14 years old who had visible symptoms of ARI within the communities or those confirmed at the hospital with ARI. Exclusion criteria were: children who were 14 and above, not showing signs of ARI and subjects whose parents did not give consent. Twenty-five children with symptoms were selected each from the three community locations while 16 symptomatic children were sampled from the hospital. The total sample size (n = 91) was arrived at based on materials and processing cost constraints, as well as to provide enough samples to enable descriptive understanding of viral circulation patterns estimated from other community-based studies [10] .
Disease Surveillance and Notification Officers, who are employed by the State Ministry of Health and familiar with the communities in this study, performed specimen and data collection. Symptoms considered were derived in accordance with other ARI surveillance efforts: sore throat, fever, couch, running nose, vomiting, body ache, leg pain, nausea, chills, shortness of breath [10, 26] . Gender and age, type of residential area (rural/urban), education level, proximity of residence to livestock, proximity to an untarred road and number of people who sleep in same room, were all recorded. The general difference between the two settings was that those from the hospital had severe illnesses, while those from the community were generally "healthy" but exhibiting ARI symptoms (i.e. mild illness).
Nasal swabs were collected from the subjects and stored in DNA/RNA shield (Zymo Research, Irvine, California). Collected samples were spinned and the swab removed. Residues containing the nasal samples were stored at -20 °C prior to molecular analysis.
Viral RNA was isolated using ZR Viral RNA ™ Kit (Zymo Research, Irvine, California) per manufacturer instructions (http://www.zymoresearch.com/downloads/dl/file/ id/147/r1034i.pdf ). Real-time PCR (polymerase chain reaction), commonly used in ARI studies [10, 19, 27] , was then carried out using RV15 One Step ACE Detection Kit, catalogue numbers RV0716K01008007 and RV0717B01008001 (Seegene, Seoul, South Korea) for detection of 15 human viruses: parainfluenza virus 1, 2, 3 and 4 (PIV1-4), respiratory syncytial virus (RSV) A and B, influenza A and B (FLUA, FLUB), rhinovirus type A-C, adenovirus (ADV), coronavirus (OC 229 E/NL63, OC43), enterovirus (HEV), metapneumovirus (hMPV) and bocavirus (BoV).
Reagents were validated in the experimental location using an inbuilt validation protocol to confirm issues of false negative and false positive results were not of concern. Amplification reaction was carried out as described by the manufacturer: reverse transcription 50 °C-30′, initial activation 94°-15′, 45 cycles: denaturation 94°-30″, annealing 60°-1′ 30″, extension 72°-1, final extension 72°-10′, hold 4°. Visualization was performed using electrophoresis on a 2% agarose gel in TBE 1X with EtBr, in presence of RV15 OneStep A/B/C Markers; molecular weight marker. Specimen processing was not blinded as there was no risk of experimental bias. Standardized procedures were used for community and clinic sampling.
All statistical analyses were performed using R version 3.2.4. Univariate statistics [mean and 95% confidence interval (CI)] are described. Bivariate statistics (difference in proportions) were assessed using a two-proportion z-test. A p value < 0.001 was considered significant. No observations used in this study had any missing data for analyses in this study.
Basic participant demographics are summarized in PCR results showed that ten different viruses (influenza A, coronavirus OC 229 E/NL63, RSVA, RSV B, parainfluenza 1-4) were detected. Figure 1 shows how these infections were distributed across virus types as well as in the community versus clinic samples. In sum, a total of 33 of the 91 subjects surveyed had one or more respiratory tract virus (36.3%, 95% CI 26.6-47.0%, Fig. 1 ). Furthermore, 10 of those cases were triple infections and 5 were quadruple infections (illustrated by color of bars in Fig. 1 ). Figure 2 indicates how frequently each pair of viruses were found in the same participant; co-infections were most common among enterovirus and parainfluenza virus 4 (Fig. 2) .
We also compared and contrasted the clinical and community results. Parainfluenza virus 4, respiratory syncytial virus B and enterovirus were the most common viruses found in the clinical sample. These three infections resulted in 41 viruses detected in 15 subjects clinically, and eight infections detected in five people in the community. Together they infected 94% (15/16, 95% CI 67.7-99.7%) of clinical subjects, and 7% (5/75, 95% CI 2.5-15.5%) in the community (significant difference, p < 0.001). The most common virus detected in community samples was Coronavirus OC43; this virus was detected in 13.3% (95% CI 6.9-23.6%) people in the community and not in any of the clinical samples. However a different strain, coronavirus OC 229 E/NL63 was detected in 12.5% of the clinical subjects (2/16, 95% CI 2.2-39.6%) and not detected in the community. Double, triple and quadruple infections were another common feature of note.
We identified ten different respiratory tract viruses among the subjects as shown in Fig. 1 . Samples collected from the Children's specialist hospital showed 100% prevalence rate of infection with one or more viruses. This might not be surprising, as the basic difference between the community and clinic samples was an increased severity of illness in the clinical sample. This may also explain the high level of co-infection found among the clinical subjects. The most prevalent virus in the clinical sample (coronavirus OC43) was not detected in the community sample. Further, there was a significant difference between prevalence of the most common viruses in the clinical sample (parainfluenza virus 4, respiratory syncytial virus B and enterovirus) and their prevalence in the community. Finally, some of the viruses detected in this study have not been detected and implicated with ARIs in Nigeria. There is no report, to the best of our knowledge, implicating coronavirus in ARIs in Nigeria, and it was detected in 12 subjects in this study. Although cases of double and triple infections were observed in a study in Nigeria in 2011 [28] , as far as we are aware, reports of quadruple infections are rare and have not been reported in Nigeria previously.
Due to the unique nature of the data generated in this study and novelty of work in the setting, it is not possible to exactly compare results to other studies. For example, though we found a similar study regarding ARIs in clinical subjects in Burkina Faso [27] , due to the small sample size from this study it would not be feasible to infer or compare prevalence rates. Studies of ARI etiology have mostly been generally focused in areas of the world that are more developed [29] , and it is important to note that the availability of molecular diagnostic methods as employed in this study substantially improve the ability to detect viruses which hitherto have not been detected in Nigeria. Further, findings from this work also add to the growing body of research that shows value of community-data in infectious disease surveillance [8] . As most of the work to-date has been in higher resource areas of the world this study adds perspective from an area where healthcare resources are lower.
In conclusion, results of this study provide evidence for active community surveillance to enhance public health surveillance and scientific understanding of ARIs. This is not only because a minority of children with severe infection are admitted to the hospital in areas such this in Nigeria, but also findings from this pilot study which indicate that viral circulation in the community may not get detected clinically [29] . This pilot study indicates that in areas of Nigeria, etiology of ARIs ascertained from clinical samples may not represent all of the ARIs circulating in the community.
The main limitation of the study is the sample size. In particular, the sample is not equally representative across all ages. However, the sample size was big enough to ascertain significant differences in community and clinic sourced viruses, and provides a qualitative understanding of viral etiology in samples from the community and clinic. Moreover, the sample was largely concentrated on subjects under 6 years, who are amongst the groups at highest risk of ARIs. Despite the small sample size, samples here indicate that circulation patterns in the community may differ from those in the clinic. In addition, this study resulted in unique findings Given that resources are limited for research and practice, we hope these pilot results may motivate further systematic investigations into how community-generated data can best be used in ARI surveillance. Results of this study can inform a larger study, representative across demographic and locations to systematically assess the etiology of infection and differences in clinical and community cohorts. A larger study will also enable accounting for potential confounders such as environmental risk factors. Finally, while it may be intuitive, findings from this pilot study shed light on the scope of differences in ARI patterns including different types and strains of circulating viruses. Also, because PCR was used for viral detection, the study was limited to detection of viruses in the primer sets. Given that these are the most up-to-date and common viruses, this approach was deemed sufficient for this initial investigation.
The study was conceived by RC and OK. RC and OK, MO and TD were involved in the design of the study, which was conducted by MO and TD. RC and OK analyzed the data. RC and OK wrote and revised the manuscript. All authors read and approved the final manuscript. | What was the most common virus detected in community samples in Ilorin, Nigeria? | false | 1,603 | {
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1,679 | Venezuelan Equine Encephalitis Virus Induces Apoptosis through the Unfolded Protein Response Activation of EGR1
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4794670/
SHA: f4aa788ab898b28b00ee103e4d4ab24a2c684caf
Authors: Baer, Alan; Lundberg, Lindsay; Swales, Danielle; Waybright, Nicole; Pinkham, Chelsea; Dinman, Jonathan D.; Jacobs, Jonathan L.; Kehn-Hall, Kylene
Date: 2016-03-11
DOI: 10.1128/jvi.02827-15
License: cc-by
Abstract: Venezuelan equine encephalitis virus (VEEV) is a previously weaponized arthropod-borne virus responsible for causing acute and fatal encephalitis in animal and human hosts. The increased circulation and spread in the Americas of VEEV and other encephalitic arboviruses, such as eastern equine encephalitis virus and West Nile virus, underscore the need for research aimed at characterizing the pathogenesis of viral encephalomyelitis for the development of novel medical countermeasures. The host-pathogen dynamics of VEEV Trinidad donkey-infected human astrocytoma U87MG cells were determined by carrying out RNA sequencing (RNA-Seq) of poly(A) and mRNAs. To identify the critical alterations that take place in the host transcriptome following VEEV infection, samples were collected at 4, 8, and 16 h postinfection and RNA-Seq data were acquired using an Ion Torrent PGM platform. Differential expression of interferon response, stress response factors, and components of the unfolded protein response (UPR) was observed. The protein kinase RNA-like endoplasmic reticulum kinase (PERK) arm of the UPR was activated, as the expression of both activating transcription factor 4 (ATF4) and CHOP (DDIT3), critical regulators of the pathway, was altered after infection. Expression of the transcription factor early growth response 1 (EGR1) was induced in a PERK-dependent manner. EGR1(−/−) mouse embryonic fibroblasts (MEFs) demonstrated lower susceptibility to VEEV-induced cell death than isogenic wild-type MEFs, indicating that EGR1 modulates proapoptotic pathways following VEEV infection. The influence of EGR1 is of great importance, as neuronal damage can lead to long-term sequelae in individuals who have survived VEEV infection. IMPORTANCE Alphaviruses represent a group of clinically relevant viruses transmitted by mosquitoes to humans. In severe cases, viral spread targets neuronal tissue, resulting in significant and life-threatening inflammation dependent on a combination of virus-host interactions. Currently there are no therapeutics for infections cause by encephalitic alphaviruses due to an incomplete understanding of their molecular pathogenesis. Venezuelan equine encephalitis virus (VEEV) is an alphavirus that is prevalent in the Americas and that is capable of infecting horses and humans. Here we utilized next-generation RNA sequencing to identify differential alterations in VEEV-infected astrocytes. Our results indicated that the abundance of transcripts associated with the interferon and the unfolded protein response pathways was altered following infection and demonstrated that early growth response 1 (EGR1) contributed to VEEV-induced cell death.
Text: V enezuelan equine encephalitis virus (VEEV) is a New World alphavirus in the family Togaviridae that is endemic to the Americas. VEEV is a positive-strand RNA virus that is transmitted by mosquitoes and that is naturally present in rodent reservoirs (1) . There are six subtypes that are categorized by their geographic range and pathology in equines and humans. The two epizootic strains, IA/B and IC, arose from mutations among the enzootic strains (2) . The IA/B and IC strains are of particular concern due to increased rates of morbidity and mortality and the risks associated with viral amplification and potential species spillover (2) . In humans, VEEV causes a febrile illness typified by fever, malaise, and vomiting. In some cases, infection progresses to the central nervous system (CNS) and neurological symptoms, such as confusion, ataxia, and seizures, manifest. The mortality rate among cases with neurological symptoms can be as high as 35% in children and 10% in adults, with long-term neurological deficits often being seen in survivors (2) . In 1995, an outbreak of VEEV in Colombia and Venezuela resulted in over 100,000 human cases (3) . In addition to natural outbreaks, VEEV is also a concern from a bioterrorism perspective, as it can be grown to high titers, requires a low infectious dose, and contains multiple serotypes. Both the former Soviet Union and the United States previously weaponized the virus, producing large quantities for their now defunct offensive bioweapons programs (4) . Currently, vaccine strain TC83 is used in horses and for high-risk personnel; however, due to the low rate of seroconversion achieved with this vaccine (5) and its reliance on two single attenuating mutations (6) , it is considered unfit for mass distribution (7) . To date there are no FDA-approved therapeutics for VEEV infection, and further studies are required for clarification of the mechanisms associated with the underlying pathogenesis of VEEV.
Viral and host transcriptomic studies can provide a wealth of information on the underlying pathogenic mechanisms and interactions following the course of an infection. The use of highthroughput next-generation sequencing has led to the discovery of previously uncharacterized viruses and the establishment of numerous novel experimental systems redefining virus-host interactions. To date a number of studies have examined the alterations in the host transcriptome following VEEV infection. A comparative microarray analysis between cells persistently infected with VEEV and cells able to clear VEEV resulted in the identification of PARP12L as an antiviral factor (8) . A molecular comparison utilizing microarrays of host-based responses to the TC83 strain was able to identify biomarkers differentiating between vaccine responder and vaccine nonresponder groups, as well as the involvement of interferon (IFN), interferon-induced pathways, Toll-like receptor (TLR), and interleukin 12 (IL-12)related pathways (9) . A study examining the role of adhesion and inflammatory factors in VEEV-infected CD-1 mice found viral modulation of the expression of extracellular matrix and adhesion genes, such as integrins (Itg␣X, Itg2, 3, and 7), cadherins 1 and 2, vascular cell adhesion molecule 1, and intracellular adhesion molecule 1 (ICAM-1), in the brains of VEEV-infected mice (10) . Follow-up experiments utilizing ICAM-1-knockout mice demonstrated reduced inflammation in the brain and a subsequent delay in the onset of neurological sequelae (10) . A study by Sharma et al. utilized microarrays to analyze gene expression changes in the brain tissue of VEEV-infected mice over the course of an infection, discovering numerous immune pathways involved in antigen presentation, inflammation, apoptosis, and the traditional antiviral response (Cxcl10, CxCl11, Ccl5, Ifr7, Ifi27, Oas1b, Fcerg1, Mif, clusterin, and major histocompatibility complex [MHC] class II) (11) . A second study by the same group identified the regulation of microRNAs (miRNAs) in the brains of VEEV-infected mice, which enabled the correlation of the miRNA changes with earlier mRNA expression data (11, 12) . These analyses suggest that VEEV may be utilizing cellular miRNAs in order to regulate downstream mRNA, which may correspond with the VEEV-induced histological changes to the nervous system (11, 12) .
In the current study, next-generation RNA sequencing (RNA-Seq) was used to identify clinically relevant alterations in the mRNA transcriptome of human astrocytes infected with wildtype (WT) VEEV strain Trinidad donkey (TrD). The analysis of host mRNAs by RNA-Seq provides novel insight into how a host responds to a viral infection through the identification of a wide and dynamic range of transcripts in an unbiased manner. Selective sequencing of mRNAs, specifically, polyadenylated [poly(A)] transcripts, which account for ϳ1% of the entire transcriptome, enhances the detection of the most relevant and low-abundance transcripts (13) . As VEEV has been shown to productively infect astrocytes both in vitro and in vivo (14, 15) , we chose astrocytes as our model of interest. Astrocytes are the most abundant cell in the brain, outnumbering neurons by at least 5-fold (16) , providing an abundant resource for viral replication within the brain. In addition to their well-described structural role in neuronal tissue, as-trocytes play critical roles in other processes, including the regulation of blood flow and of the blood-brain barrier, synapse transmission, and the response to infection (16) . VEEV-infected astrocytes have been shown to produce multiple cytokines, including IL-8, IL-17, interferon gamma (IFN-␥), and gamma interferon-induced protein 10, all of which were found to be associated with viral attenuation (14) .
In order to obtain a dynamic view of the virus-host interactome, RNA-Seq was used to monitor changes in gene expression in VEEV TrD-infected astrocytes at 4, 8, and 16 h postinfection (hpi). By viewing the alterations at multiple early time points using triplicate biological replicates, a robust and dynamic range of information is generated, and this information provides an increase in both the power and the accuracy of detection of differentially expressed transcripts in a highly relevant clinical model (17) . Among VEEV-infected cells, an increase in interferon-regulated genes, including IFIT1, IFIT2, IFIT3, and OASL, was observed. The increased expression of genes involved in the stressinduced unfolded protein response (UPR) pathway was also noted. Interestingly, VEEV infection resulted in an increase in early growth response protein 1 (EGR1), which may serve as a link between the two pathways. The identification of host mRNAs whose expression is altered following VEEV replication, specifically, EGR1 and its interactors up-and downstream, may provide novel host-based therapeutic targets critical for VEEV replication and a greater understanding of the underlying mechanisms underpinning alphavirus replication.
Viral infections and plaque assays. VEEV TrD was obtained from BEI Resources. All experiments with VEEV TrD were performed under biosafety level 3 (BSL-3) conditions. All work involving select agents is registered with the Centers for Disease Control and Prevention and was conducted at George Mason University's Biomedical Research Laboratory, which is registered in accordance with federal select agent regulations. For infections, VEEV was added to supplemented Dulbecco modified Eagle medium (DMEM) to achieve a multiplicity of infection (MOI) of 0.05, 0.5, or 5. Cells were infected for 1 h at 37°C and rotated every 15 min to ensure adequate coverage. The cells were then washed with phosphatebuffered saline (PBS), and complete growth medium was added back to the cells. Viral supernatants and cells were collected at various times postinfection for further analysis. Plaque assays were performed as previously described (18) . mRNA isolation and poly(A) library preparation. RNA from U87MG cells was purified from both VEEV TrD-infected (biosafety level 3) and mock-infected U87MG cells at 4, 8, and 16 hpi utilizing a mirVana isolation kit (Life Technologies). Quality control of purified RNA was then performed using an Agilent 2100 bioanalyzer, and an RNA integrity number (RIN) cutoff of 8 was utilized for all samples. An External RNA Controls Consortium (ERCC) RNA spike-in control mix was then added to the total RNA inputs (10 g RNA) before poly(A) selection using a Life Technologies Dynabeads mRNA Direct kit. Preparation of a whole-transcriptome RNA library from purified mRNA was then performed using an Ion Total RNA-Seq kit (v2; Life Technologies). Quality control of the cDNA libraries was then performed using the Agilent 2100 bioanalyzer along with sterility testing for removal of libraries for sequencing from a BSL-3 to BSL-2 laboratory.
RNA sequencing. Library template preparation was performed on a One Touch 2 platform (Life Technologies). Next-generation RNA sequencing was performed on an Ion Torrent PGM platform and was carried out for each sample to assess the differential gene expression of infected versus uninfected cells over time.
Data filtering and RNA-Seq analysis pipeline. A total of ϳ119 million sequencing reads and an average of 6.6 million reads per sample were used as the input into our analysis pipeline. Unless otherwise noted, downstream RNA-Seq analysis was carried out using the CLC bio Genomics Workbench (v7). Raw RNA-Seq reads were trimmed to remove any residual sequencing adapter fragments that remained on the 5= or 3= ends after sequencing. In addition, end trimming of reads was done using the modified Mott algorithm with a Q20 quality score, and any reads of less than 15 bp were discarded. Following read trimming, the reads were mapped to human genome hg19 with the following RNA-Seq parameters: a 10-hit limit for multiple mapped positions, a similarity fraction of 0.8, a length fraction of 0.8, a mismatch cost of 2, and an indel cost of 3. The expression level of individual genes and transcripts was calculated using the number of reads per kilobase of the exon model per million mapped reads (RPKM) method of Mortazavi et al. (19) . In addition, unmapped reads were also mapped to the ERCC92 synthetic RNA sequence set (20) , as well as to the VEEV reference genome (GenBank accession number L01442). In all samples, the correlation coefficient (R 2 ) between the expected and the mapped number of reads for the ERCC92 spike-in controls was above 0.90. A summary of the overall sequencing results is shown in Table 1 .
Postmapping filtering of all RNA-Seq data was carried out next to include only genes with at least one uniquely mapped read (26,230 genes remained across all data sets) and only those with a nonzero interquartile range across the entire experiment. Principal component analysis of the resulting filtered data set (13,906 genes in total) was carried out using raw counts of uniquely mapped reads (see Fig. 2A ). The remaining RPKM expression values for each gene included in the filtered data set were subjected to quantile normalization with a 5% cutoff. A box plot of log 2transformed RPKM values for each sample before normalization is shown in Fig. 2B . The R 2 value for pairwise sample-to-sample variation within each biological replicate set was observed to range from 0.89 to 0.99, indicating that our biological replicates were consistent and showed no strong bias (data not shown).
Differential gene expression analysis. Differentially expressed genes (DEGs) were identified using two approaches. First, the empirical analysis of differential gene expression algorithm, part of the edgeR Bioconductor package (21) , was applied to the integrated data set of all 18 experiments using the default parameters and a false discovery rate-corrected P value. At each time point, infected and mock-infected samples were compared, and genes whose expression differed by more than 2-fold with a significance with a P value of Յ0.05 were provisionally considered to be differentially expressed.
In addition to the method described above, an orthogonal statistical test of differential expression was applied to the data using a statistical test developed by Baggerly et al. (22) to count the number of expressed sequence tags associated with individual genes, a common feature of both serial analysis of gene expression (SAGE) data and RNA-Seq data. When infected and mock-infected samples were compared, individual genes were provisionally considered differentially expressed when their expression differed by more than 2-fold with a significance with a P value of Յ0.05. Differentially expressed genes found to be in the intersection of the sets of genes identified by both of the methods outlined above were considered high-quality candidates and used as the starting point for further investigation.
Clustering and GSEA. Filtered, normalized expression data were subjected to k-means clustering using a Euclidian distance metric where genes were grouped by means of normalized gene expression (RPKM) values for each experimental condition. Clustering was fitted to 20 distinct clustering groups, and the individual gene expression profiles clustered were further tested for enrichment of gene ontology (GO) terms associated with individual genes. Gene annotations were obtained from Reactome, a database of biological pathway and gene functional annotations (23) . Enrichment analysis was performed using two approaches. First, a hypergeometric test on GO annotations was carried out using an implementation of the GOStats package on each of the individual clusters obtained from k-means clustering (24) . In addition, gene set enrichment analysis (GSEA) was carried out on the entire filtered data set using 100,000 permutations, while duplicates were removed and an analysis of variance was applied. A total of 1,419 categories passed a minimum feature size of 10 and were used for further investigation.
Cohorts of genes with shared patterns of expression over time were identified by k-means clustering. Those found to be enriched for DEGs were subsequently subjected to pathway analysis using the GeneMania system (25) . Using an ad hoc manual approach, relevant pathways and the connections between them were identified on the basis of existing data in the literature coupled with the temporal gene expression data obtained from this study.
qRT-PCR analysis. Purified mRNA was converted to cDNA using a high-capacity RNA-to-cDNA kit (Life Technologies) according to the manufacturer's instructions. Analysis of the viral copy numbers was performed by quantitative reverse transcription-PCR (qRT-PCR) as previously described (26) . Host expression of the following genes was assayed with TaqMan assays (indicated in parentheses): activating transcription factor 3 (ATF3; Hs00231069_m1), ATF4 (Hs00909569_g1), CEBPB (Hs00270923_s1), CEBPD (Hs00270931_s1), DDIT3 (Hs00358796_g1), FOS (Hs04194186_s1), JUN (Hs01103582_s1), EGR1 (Hs00152928_m1), IFI6 (Hs00242571_m1), IFIT1 (Hs01911452_s1), IFIT2 (Hs01922738_s1), IFIT3 (Hs01922738_s1), ISG15 (Hs01921425_s1), ISG20 (Hs00158122_m1), OASL (Hs00984387_m1), BIRC5 (Mm00599749_m1), and XIAP (Mm01311594_mH). Assays for 18S rRNA (Hs99999901_s1 or Mm04277571_s1) were used for normalization. Assays were performed according to the manufacturer's instructions using an ABI StepOne Plus instrument.
Treatment with PERKi and collection for Western blot analysis. U87MG cells were pretreated for 2 h with 10 M the protein kinase RNAlike endoplasmic reticulum (ER) kinase (PERK) inhibitor (PERKi) GSK2606414 (catalog number 516535; EMD Millipore) or dimethyl sulfoxide (DMSO) in DMEM prior to infection with VEEV TrD (MOI, 5). After 1 h, the viral inoculum was removed and cells were washed with sterile PBS (1ϫ). The medium was replaced with medium containing the inhibitor or DMSO. At 16 hpi, the medium was removed, and the cells were washed with PBS and then collected for Western blot analysis.
Knockdown of EGR1 with siRNA. U87MG cells seeded at 6.7 ϫ 10 4 cells per well in a 12-well plate were transfected with 50 nM siGenome Protein lysate preparation and Western blot analysis. Protein lysate preparation and Western blot analysis were performed as previously described (27) . Primary antibodies to the following were used: EGR1 (antibody 44D5; catalog number 4154; Cell Signaling), polyclonal anti-Venezuelan equine encephalitis virus TC83 (subtype IA/B) capsid protein (BEI Resources), CHOP (antibody L63F7; catalog number 2895; Cell Signaling), phosphorylated ␣ subunit of eukaryotic initiation factor 2 (p-eIF2␣; Ser51; antibody D9G8; catalog number 3398; Cell Signaling), ATF4 (antibody D4B8; catalog number 11815; Cell Signaling), activated caspase 3 (antibody Asp175; catalog number 9661; Cell Signaling), and horseradish peroxidase-conjugated -actin (catalog number ab49900-100; Abcam).
Immunofluorescence analysis. U87MG cells were grown on coverslips in a 6-well plate, infected with VEEV TrD as described above, washed with PBS (without Ca and Mg), and then fixed with 4% formaldehyde. Cells were permeabilized with 0.5% Triton X-100 in PBS for 20 min and then washed twice with PBS. The cells were blocked for 10 min at room temperature in 3% bovine serum albumin in PBS. Primary antibodies consisting of a VEEV capsid protein (catalog number NR-9403; BEI Resources) diluted 1:600 and an EGR1 antibody (antibody 44D5; catalog number 4154; Cell Signaling) diluted 1:400 were incubated in fresh blocking buffer at 37°C for 1 h and washed 3 times for 3 min each time in 300 mM NaCl with 0.1% Triton X-100. Alexa Fluor 568 donkey anti-goat secondary antibody (catalog number A11057; Invitrogen) and Alexa Fluor 488 donkey anti-mouse secondary antibody (catalog number A21202; Invitrogen) diluted 1:400 were used as secondary antibodies and treated in the same manner as the primary antibodies. DAPI (4=,6-di- amidino-2-phenylindole) diluted 1:1,000 was used to visualize the nuclei. Coverslips were mounted onto glass slides using 10 l of Fluoromount G mounting medium (catalog number 0100-01; Southern Biotech). A Nikon Eclipse TE2000-U fluorescence microscope was used for fluorescence microscopy. Images were viewed using a 60ϫ objective oil immersion lens. Five images of each sample were obtained, and a representative image of each sample is shown below. All images were subjected to fourline averaging. The images were processed through Nikon NIS-Elements AR Analysis (v3.2) software.
CellTiter Glo and Caspase 3/7 Glo assays. Wild-type and EGR1 Ϫ/Ϫ mouse embryonic fibroblasts (MEFs) were infected with TrD at various MOIs for an hour and then washed with PBS, and the medium was replaced. Cell viability was measured at 24 h postinfection using a Promega CellTiter luminescent cell viability assay (catalog number G7571) according to the manufacturer's protocol. Luminescence was read using a Beckman Coulter DTX 880 multimode detector with an integration time of 100 ms per well. Similarly, caspase activation in infected wildtype and EGR1 Ϫ/Ϫ MEFs was measured at 24 h postinfection using a Promega Caspase 3/7 Glo assay (catalog number G8090) according to the manufacturer's protocol. Luminescence was read using the DTX 880 multimode detector with an integration time of 100 ms per well.
Nucleotide sequence accession numbers. The raw sequencing data for all RNA-Seq runs included in this work are publically available in the NCBI BioProject database under accession number PRJNA300864 (http: //www.ncbi.nlm.nih.gov/bioproject/PRJNA300864).
VEEV replication kinetics in U87MG astrocytes. VEEV replicates in vivo in monocytes, macrophages, neurons, and astrocytes (14) . Common cell lines used to study VEEV infection include Vero and BHK cells; in this study, U87MG astrocytes were chosen as an in vitro model due to their physiological relevance and greater clinical significance. Initial experiments were performed to characterize viral replication in U87MG cells. VEEV replication kinetics in U87MG cells were measured using plaque assays and by monitoring viral protein and RNA expression levels and the cytopathic effect (CPE) on the infected cells (Fig. 1) . Viral release was observed as early as 4 hpi, with ϳ4 log units of virus being observed, followed by a consistent increase in replication at 8 and 16 hpi (Fig. 1A) . Viral replication peaked at 16 hpi, and no additional increase in viral titers was observed at 24 hpi. Viral capsid expression followed a similar pattern, with protein being detected at 8 hpi and expression plateauing at 16 hpi (Fig. 1B) . Among infected U87MG cells, a significant CPE was observed by microscopy at 24 hpi, with little to no CPE being detected at 16 hpi (data not shown). Consistent with these observations, increased caspase 3/7 activity was observed only at 24 hpi (Fig. 1C) . On the basis of these data, times of 4, 8, and 16 hpi, reflecting the early, middle, and late stages of the viral life cycle, respectively, were selected for RNA-Seq analysis in order to provide a dynamic view of the host-pathogen transcriptome profile.
RNA sequencing analysis of VEEV-infected astrocytes. mRNA from triplicate sets of mock-and VEEV-infected U87MG cell cultures was isolated, purified at 4, 8, and 16 hpi, and used to prepare cDNA libraries for downstream RNA-Seq (see Materials and Methods). A high-level summary of the RNA-Seq results is shown in Table 1 . VEEV RNA samples were assayed by quantitative RT-PCR at each time point as a control to demonstrate the increasing viral RNA load over time (Fig. 1D) , consistent with the increasing number of RNA-Seq reads mapped to the VEEV genome at later time points (Table 1) .
For RNA-Seq analysis, individual genes were expressed as the number of reads per kilobase of the exon model per million mapped reads (RPKM) (19) . Log 2 -normalized RPKM expression values for each experimental sample are shown in Fig. 2A and can be found in Data Set S1 in the supplemental material. Minimal sample-to-sample variation in expression values within biological replicates was consistently detected (R 2 Ͼ 0.89 for all replicates; data not shown). In addition, intersample variation was also found to be minimal when it was tested pairwise across the entire experiment by using RPKM values for ERCC97 synthetic spike-in control RNAs (R 2 Ͼ 0.90 for all comparisons; data not shown).
As anticipated, two-component principal component analysis of the RNA-Seq data for mock-infected cells versus VEEV-infected cells showed a clear separation of the samples at 16 hpi from the samples at earlier time points (Fig. 2B) . However, the clustering of VEEV-infected samples with mock-infected samples at earlier time points suggested that the response to viral infection was limited to a narrow subset of early response genes, thus placing a higher burden of proof on identifying differentially expressed genes (DEGs) during the first few hours of infection. Along these lines, two orthogonal methods were used to identify DEGs suitable for further characterization: the edgeR method (21) and the method developed by Baggerly et al. (22) . Genes identified by one method were provisionally considered DEGs, and those identified by both methods were candidate DEGs to be confirmed by qRT-PCR. In addition to comparing individual gene expression values for mock-infected cells and VEEV-infected cells at each time point, gene expression values were also compared serially within each time series of VEEV-infected cells for genes that did not show any statistically significant changes in expression in mock-infected cells. A schematic of the comparative analysis is shown in Fig. 2C . The number of statistically significant DEGs identified by each of these comparisons is shown in Fig. 2D . Furthermore, k-means clustering (against normalized RPKM values) was employed to identify gross changes in gene expression over time for cohorts of genes potentially sharing the same pathway or regulatory triggers ( Fig. 3 ; see also Data Set S2 in the supplemental material). Gene set enrichment analysis (GSEA; see Material and Methods and Data Set S3 in the supplemental material) was carried out on each kmeans cluster. In particular, cluster 20 (Table 2) was significantly enriched for genes involved in translational control, the type I interferon-mediated signaling pathway, and the unfolded protein response (UPR) pathway (GSEA P value Ͻ 0.01). Although there is a well-established connection between translational control and UPR, a novel connection between UPR and the type I interferonmediated response in response to viral replication was suggested by pathway analysis (see Materials and Methods), implicating early growth response 1 (EGR1) as a potential bridge between these two pathways (Fig. 4) . EGR1 belongs to cluster 20 and is strongly induced during VEEV infection, and several other genes associated with the interferon response belong to the same cluster: IRF1, IFIT1, IFIT2, ISG15, and ILF3. EGR1 has been associated with increases in the expression of activating transcription factor 3 (ATF3) (28) , which is a key component of the UPR and which also belongs to cluster 20. This connection represented a potential a Biological process annotations obtained from Reactome for cluster 20. Reactome annotation identifiers are indicated for each annotation. Only traceable author submission (TAS)-classified annotations are considered. TAP, transporter associated with antigen processing; SRP, signal recognition particle. b Full set, the total number of genes in the genome with an annotated biological process; subset, total number of differentially expressed genes with an annotated biological process.
Network of type I interferon response-and UPR-related genes. Large circles, differentially expressed genes; small circles, genes with no significant change in expression; red circles, type I interferon response factors; yellow circles, genes regulating DNA transcription; blue circles, unfolded protein response genes; red lines, genes involved in physical protein-protein interactions; blue lines, genes involved in a common pathway. This network was seeded with k-means clusters 18 and 20, and many ribosomal protein genes were removed.
bridge between the UPR pathway and the interferon response pathway, with EGR1 being one of the potential key transcription factors driving this connection. Consequently, 15 genes from this analysis were selected for further characterization by qRT-PCR (see below): ATF3, activating transcription factor 4 (ATF4), CEBPB, CEBPD, DDIT3/CHOP, EGR1, FOS, IFI6, IFIT1, IFIT2, IFIT3, ISG15, ISG20, JUN, and OASL. The expression values of these genes, as measured by RNA-Seq, are shown in Fig. 5A and B. Confirmatory qRT-PCR analysis indicated concordant gene expression ( Fig. 5C and D) . The interferon response genes induced are in agreement with those detected in previously published studies (11, 29, 30) , and these genes served as an internal positive control. Moreover, the link between EGR1 and the interferon pathway has been demonstrated; EGR1 is induced by IFN-␥ in mouse fibroblasts and by IFN-␣, -, and -␥ in human fibroblasts (31, 32) . EGR1 and the UPR pathway were selected for further analysis, as their role in VEEV infection has not been elucidated.
The RNA-Seq and pathway analysis data indicated that UPR and stress response genes were induced after VEEV infection. During an infection, host cells respond to cellular stresses resulting from increased viral protein translation and secretion by triggering the onset of the UPR pathway. The UPR pathway is an adaptive cellular response activated by endoplasmic reticulum (ER) stress due to protein misfolding. In order to regulate cellular homeostasis during protein folding and secretion, the UPR pathway has developed three classes of sensors to ensure proper cellular regulation: inositolrequiring enzyme 1 (IRE1), protein kinase RNA-like ER kinase (PERK), and activating transcription factor 6 (ATF6) (33, 34) . During VEEV infection, the PERK arm of the UPR appeared to be altered, as two critical regulators of this pathway were differentially expressed: ATF4 and CHOP (DDIT3) (35) . To determine if DEGs altered subsequent protein expression, Western blot analysis was performed for CHOP, ATF4, and phosphorylated eIF2␣ (p-eIF2␣). Tunicamycin, a glycosylation inhibitor and inducer of UPR (36) , was included as a positive control. A time course analysis of U87MG cells treated with 1 M tunicamycin indicated that 8 h of treatment provided the most robust induction of UPR proteins (data not shown). VEEV-infected but not mock-infected or UV-inactivated VEEV (UV-VEEV)-infected cells displayed a dramatic increase in p-eIF2␣ expression and a modest but consistent increase in CHOP and ATF4 expression at 16 hpi (Fig. 6A) . No change in protein expression was observed at 4 hpi (data not shown). Confocal microscopy confirmed CHOP and ATF4 up- regulation, demonstrating a more robust and nuclear staining pattern in VEEV-infected cells than in mock-infected cells (Fig. 6C to E). While ATF4 protein expression levels increased, ATF4 mRNA abundances decreased following VEEV infection ( Fig. 5B and D). These results are consistent with the observation that ATF4 expression is regulated at the translational level upon UPR induction (37) . As eIF2␣ can be phosphorylated by multiple kinases (PERK, protein kinase double-stranded RNA dependent [PKR], general control nonderepressible-2 [GCN2], and hemeregulated inhibitor [HRI]) (38) , the PERK inhibitor (PERKi) GSK2606414 was used to determine if the observed phosphorylation was PERK dependent. Treatment of VEEV-infected cells with PERKi resulted in a marked decrease in eIF2␣ phosphorylation (Fig. 6B) . These results indicate that PERK contributes to eIF2␣ phosphorylation but that there is likely an additional kinase contributing to the phosphorylation event. Collectively, these findings indicate that the PERK arm of the UPR pathway is induced at later time points following VEEV infection.
EGR1 is upregulated in infected cells and localizes to the nucleus. EGR1 is a transcription factor that can be induced by numerous signals, including oxidative stress, hypoxemia, and growth factors (39, 40) . It can also be activated upon infection by both DNA and RNA viruses, including Epstein-Barr virus, mouse hepatitis virus, murine coronavirus, and Japanese encephalitis virus (41) (42) (43) . Treatment of MEFs with the UPR activator thapsigargin has been shown to induce EGR1 expression in a PERK-dependent manner (44) . Given the link between EGR1 and UPR and the robust induction of EGR1 mRNA expression following VEEV infection ( Fig. 4 and 5) , EGR1 was chosen for further study. EGR1 protein expression after VEEV infection was analyzed by Western blot analysis. As previous studies have indicated that EGR1 can be activated by mouse hepatitis virus independently of virus replication (likely due to cellular membrane disruption following entry) (41), a UV-inactivated virus control (UV-VEEV) was included. EGR1 protein levels were increased following VEEV infection compared to those in mock-infected cells and UV-VEEV-infected cells (Fig. 7A; compare lanes 3, 6, and 9 ). The most dramatic upregulation of EGR1 occurred at 16 hpi; this correlates with the highest levels of VEEV capsid production (Fig. 1B) . Following induction, EGR1 has been shown to translocate to the nucleus to induce gene expression through binding to the Egr binding sequence (EBS) [GCG(G/T)GGCG] (40, 45) . Confocal microcopy revealed high levels of EGR1 in the nuclei of infected cells, whereas only low levels of both nuclear and cytoplasmic EGR1 were detected in mock-infected cells (Fig. 7B) . PERKi treatment of VEEV-infected cells resulted in a complete loss of EGR1 induction (Fig. 7C) , indicating that EGR1 was induced in a PERK-dependent fashion. These results demonstrate that EGR1 protein levels and nuclear localization are increased following VEEV infection and that the induction of EGR1 is dependent on PERK.
The loss of EGR1 inhibits VEEV-induced apoptosis but does not alter VEEV replication kinetics. As EGR1 influences cell survival and apoptosis (46) , the impact of EGR1 on VEEV-induced cell death was assessed. Caspase 3 cleavage was observed in WT MEFs at 24 hpi when they were infected at an MOI of 0.5 and started as early as 16 hpi when they were infected at an MOI of 5 (Fig. 8A ). In contrast, EGR1 Ϫ/Ϫ cells showed little to no detectable caspase cleavage following infection with VEEV. Two sets of experiments were performed to quantitatively confirm these results: CellTiter Glo assays to measure total cell viability (ATP production) and Caspase 3/7 Glo assays to measure caspase 3/7 activity. Both WT and EGR1 Ϫ/Ϫ MEFs displayed dose-dependent decreases in cell viability following VEEV infection, with EGR1 Ϫ/Ϫ cells having significantly more viable cells at each MOI examined (Fig. 8B) . Concordantly, a dose-dependent increase in caspase 3/7 activity was observed following VEEV infection, with EGR1 Ϫ/Ϫ cells demonstrating reduced caspase 3 activity at MOIs of 0.5 and 5 (Fig. 8C) . These results were replicated in U87MG cells transfected with siRNA targeting EGR1 (Fig. 8D) . EGR1 has been shown to negatively regulate the transcription of BIRC5 (survivin), an inhibitor of apoptosis (IAP) family member (47) . RNA-Seq data indicated that BIRC5 gene expression was decreased following VEEV infection: log 2 -transformed fold change values of normalized gene expression were Ϫ1.16, Ϫ1.18, and Ϫ1.50 at 4, 8, and 16 hpi, respectively (see Table S1 in the supplemental material and NCBI BioProject accession number PRJNA300864). WT and EGR1 Ϫ/Ϫ MEFs were used to determine if EGR1 influenced BIRC5 gene expression following VEEV infection. BIRC5 expression was significantly decreased at 16 hpi in VEEV-infected WT MEFs, but this reduction was not observed in VEEV-infected EGR1 Ϫ/Ϫ MEFs (Fig. 8E) . Ex-pression of the gene for the X-linked inhibitor of apoptosis (XIAP), another IAP family member, was not significantly differentially altered after infection (data not shown). Collectively, these results demonstrate that EGR1 contributes to VEEV-induced apoptosis.
VEEV replication kinetics were determined for both EGR1 Ϫ/Ϫ and WT MEFs to determine the relevance of EGR1 in viral replication. Cells were infected at two different MOIs (0.5 and 5), and viral supernatants were collected at 4, 8, 16, and 24 hpi and analyzed by plaque assay. The replication kinetics were similar between EGR1 Ϫ/Ϫ and WT MEFs at both MOIs, with titers peaking at 16 hpi (Fig. 9A) . A lack of EGR1 expression was confirmed by Western blotting (Fig. 9B) . These results were replicated in U87MG cells transfected with siRNA targeting EGR1. Transfection of siRNA targeting EGR1 resulted in a Ͼ90% decrease in EGR1 protein expression (Fig. 9D ) without any significant effect on viral replication (Fig. 9C) . These results suggest that the decrease in apoptosis observed in EGR1 Ϫ/Ϫ MEFs was not due to altered VEEV replication kinetics.
Despite being recognized as an emerging threat, relatively little is known about the virulence mechanisms of alphaviruses, largely due to a knowledge gap in the host-pathogen interactome. VEEV infection often results in fatal encephalitis and is known to inhibit both cellular transcription and translation in order to downregulate the innate immune response (1, 48) . In contrast, in the CNS VEEV has been shown to upregulate numerous genes in both the inflammatory response and apoptotic pathways (1, 48) . Specifically, numerous proinflammatory cytokines, including interleu-kin-1 (IL-1), IL-6, IL-12, glycogen synthase kinase 3, inducible nitric oxide synthase, and tumor necrosis factor alpha (TNF-␣), have all been shown to play a role in VEEV pathogenesis (49) (50) (51) (52) (53) . The use of high-throughput next-generation sequencing technologies, such as RNA-Seq, allows an in-depth and unbiased look into the virus-host transcriptome, thus enabling changes in the expression of specific mRNAs to be connected with phenotypic outcomes. To this end, identification of critical differentially expressed transcripts among clinically relevant infected cells will help lead to a greater understanding of viral pathogenesis and may prove beneficial for the identification of therapeutic targets.
In this study, network analysis/RNA-Seq data and the results of protein expression studies revealed that VEEV infection resulted in activation of the PERK arm of the UPR pathway, including the activation of ATF4, CHOP, and eIF2␣ phosphorylation. Several alphaviruses have previously been reported to hijack key components of the UPR pathway in order to promote viral replication, as the reliance of enveloped viruses on the ER for the synthesis of viral envelope-associated glycoproteins and their transport to the plasma membrane often stresses the ER due to rapid viral protein production (54, 55) . Modulation of the UPR is not unique to alphaviruses; rather, it is a shared trait of many positive-sense RNA viruses. Dengue virus has been shown to suppress PERK by inhibiting continued eIF2␣ phosphorylation in order to inhibit immediate apoptosis, increasing viral protein translation and extending the length of productive viral replication (34) . Studies with hepatitis E virus (HEV) have demonstrated that expression of HEV capsid protein open reading frame 2 (ORF2) activates the expression of CHOP and ATF4 (56) . In HEV, ORF2 was shown to stimulate CHOP through both ER stressors and amino acid response elements (AARE) through interaction with ATF4 (56) .
The results shown here indicate that during VEEV infection, initiation of the UPR pathway and subsequent activation of EGR1 play a role in the outcome of virus-induced apoptosis. During the initial detection of ER stress, PERK is able to identify misfolded proteins in the lumen of the ER and phosphorylates eIF2␣ in order to initiate prosurvival pathways in the UPR through the general At 24 hpi caspase 3/7 activity was analyzed using the Caspase 3/7 Glo assay. The fold change values for mock-infected cells were set to a value of 1. **, P Ͻ 0.001. (E) EGR1 Ϫ/Ϫ and WT MEFs were mock or VEEV infected (MOI, 5). RNA was prepared, and gene expression was determined by qRT-PCR using a TaqMan assays for BIRC5 (survivin). The data shown are the values of the fold change of normalized gene expression determined by the ⌬⌬C T threshold cycle (C T ) method. *, P Ͻ 0.005 (comparison of VEEV-infected WT and EGR1 Ϫ/Ϫ cells). inhibition of protein synthesis (33, 34) . VEEV appears to induce the UPR and promote increased eIF2␣ phosphorylation, which results in the translational inhibition of most mRNAs, while UPR selectively increases the translation of ATF4. ATF4 is responsible for the expression of genes that encode proteins involved in apoptosis, redox processes, amino acid metabolism, and ER chaperone recruitment and is a well-known mediator of the PERK pathway and CHOP (33, 34) . CHOP activation facilitates the increased expression of cellular chaperones in order to counteract the buildup of misfolded proteins (57) . Failure to suppress protein misfolding in persistently stressed cells, such as during a viral infection, can then result in activation of the proapoptotic transcription factor CHOP, leading to suppression of the antiapoptotic protein B cell lymphoma-2 (Bcl-2). CHOP can also function as a prosurvival transcription factor by dephosphorylating eIF2␣ through activation of the DNA damage-inducible protein (GADD34) in a self-regulating feedback look (33, 34) . However, the data presented here support a model whereby VEEV infection leads CHOP to function in its proapoptotic role, as no change in GADD34 gene expression was detected by RNA-Seq analysis.
While the UPR was induced following VEEV infection, robust activation was not observed until later time points after infection. This is somewhat surprising, as VEEV infection is expected to induce significant ER stress due to the massive production of viral proteins during the course of an acute robust infection. The structural proteins of VEEV are translated from the viral subgenomic RNA into polyproteins on the rough ER. The E1 and pE2 precur-sor glycoproteins are then assembled as heterodimers in the ER, undergoing conformational changes requiring numerous chaperones (1, 58) . It is possible that VEEV has developed mechanisms to subvert the induction of the UPR. In order to counteract the UPR, the nonstructural proteins (nsPs) of Chikungunya virus (CHIKV) have been shown to inhibit expression of ATF4 and other known UPR target genes, including GRP78/BiP, GRP94, and CHOP (59) . Through nsP activity, CHIKV has developed a means of suppressing the UPR activity resulting from viral glycoprotein-induced ER stress, thus preventing immediate autophagy and apoptotic activation. The VEEV capsid is responsible for interfering with nucleocytoplasmic trafficking and inhibiting rRNA and mRNA transcription and has been implicated in the regulation of type I IFN signaling and the antiviral response through the regulation of both viral RNA and protein production (1, 48, 60) . Therefore, we hypothesize that the ability of the VEEV capsid to inhibit cellular transcription and block nucleocytoplasmic trafficking results in delayed induction of the UPR.
The results of a detailed network analysis based on existing data in the literature, coupled with the temporal gene expression profiles obtained from this study, point toward EGR1 being an important node in the novel link between VEEV activation of the type I interferon response and UPR. EGR1 is known to form a DNA binding complex with C/EBPB, a critical dimerization partner of CHOP (61) . Previous studies have demonstrated that the nuclear localization of CHOP may act as an inducer of EGR1 and that CHOP may act as a transcriptional cofactor for regulation of C/EBPB-EGR1 target genes (61) . The results of the Western blot and microscopy analysis presented in this study support this model, as VEEV infection was found to increase both the overall levels and the nuclear distribution of CHOP along with those of EGR1. Previous studies demonstrated EGR1 mRNA induction by IFN-␥ in mouse fibroblasts and by TNF-␣, TNF-, IL-1, IFN-␣, IFN-, and IFN-␥ in human fibroblasts (31, 32) . EGR1, also known as Zif268 and NGF1-A, is a zinc finger protein and mammalian transcription factor. It has been implicated in cellular proliferation and differentiation, but it may also have proapoptotic functions, depending on the cell type and stimulus (62) . Of particular interest, EGR1 directly controls proliferation when activated by the mitogen-activated protein kinase/extracellular signal-regulated kinase pathway in mitogen-stimulated astrocytes (63) . Virus-induced changes in EGR1 expression have been observed in several in vitro systems. In HIV-1-infected astrocytes, EGR1 upregulation was found to be induced by Tat through transactivation of the EGR1 promoter, leading to cellular dysfunction and Tat-induced neurotoxicity (64) . Increased amounts of EGR1 mRNA have also been demonstrated to act in a region-specific manner, corresponding temporally with viral RNA production in the brain tissues of rats infected with either rabies virus or Borna disease virus (65) .
In summary, the current study demonstrates a potential link between UPR activation and EGR1. EGR1 Ϫ/Ϫ MEFs demonstrated lower levels of susceptibility to VEEV-induced cell death than wild-type MEFs, indicating that EGR1 modulates proapoptotic pathways following infection. Studies are under way to determine if alteration of the UPR through small molecule inhibitors or siRNA interference influences VEEV replication and/or cell death. To date the mechanisms underlying VEEV pathogenesis and subsequent neuronal degeneration have been only partially elucidated. Therefore, determining the role of EGR1 and UPR may play a significant role in the development of a novel therapeutic target resulting in decreased neuronal death and the subsequent neuronal sequelae that result from infection. | What indicators does the UPR pathway use to regulate protein folding and secretion in the cell? | false | 940 | {
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"inositolrequiring enzyme 1 (IRE1), protein kinase RNA-like ER kinase (PERK), and activating transcription factor 6 (ATF6)"
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