In response to COVID-19, the Government of Ethiopia has been taking a series of policy actions beyond public health initiatives alone. Therefore, this study was aimed to assess the applicability of basic preventive measures of the pandemic COVID-19 and associated factors among the residents of Guraghe Zone from 18th to 29th September, 2020. Systematic random sampling method was applied among the predetermined 634 samples. Variables which had p-value less than 0.25 in bivariate analysis were considered as candidate for multivariable logistic regression model. P-value <0.05 was used as a cutoff point to determine statistical significance in multiple logistic regressions for the final model.Community based cross sectional study was conducted at Guraghe Zone from 18In this study, 17.7%  of the respondents apply the basic preventive measures towards the prevention of the pandemic COVID-19. In addition, being rural resident , being studied grade 1–8 , being a farmer , currently not married , having family size 1-3, have no diagnosed medical illness  and having poor knowledge  were factors which are statistically significant in multivariable logistic regression model.Despite the application of preventive measures and vaccine delivery, the applicability of the pandemic COVID-19 preventive measures was too low, which indicate that the Zone is at risk for the infection. Rural residents, those who have lower educational level, farmers, non-marrieds, those who have lower family size, those who have diagnosed medical illnesses and those who have poor knowledge were prone to the infection with the pandemic COVID-19 due to the lower practice of applying the basic preventive measures. In addition, awareness creation should be in practice at all levels of the community especially lower educational classes and rural residents. The pandemic of coronavirus disease 2019 (COVID-19) started in December 2019 in Wuhan, China Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: YesReviewer #2: YesReviewer #3: No**********2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: NoReviewer #2: YesReviewer #3: No**********3. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********4. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: NoReviewer #2: YesReviewer #3: Yes**********5. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: 1. The manuscript has a lot of typo errors grammatical, spelling, punctuation, and consistency in word usage like; COVID-19, COVID-2019 and COVID 19, Guraghe zone and Gurage zone, dyed instead of died.2. High knowledge: If the respondent answers 11 of the 14 knowledge assessment questions correctly (10). What if the respondent answer 12, 13, and 14 of 14 knowledge assessment questions correctly????3. Moderate knowledge: If the respondent answers nine of the 14 knowledge assessment questions correctly (10). What if the respondent answers 10 of 14 knowledge assessment questions correctly????4. Poor or low knowledge: If the respondent responds below nine knowledge assessment questions correctly (10).5. Good knowledge: If the respondent responds above nine knowledge assessment questions correctly6. How did you measure attitude is not operationalized7. The maximum total score ranged from 0–13, with a higher score indicating better knowledge about COVID-19. How can it be the maximum score of 13 if one individual answers all 14 questions correctly the maximum score will be 14? So, how do you justify it?8. Data were cleaned, edited, coded, and entered into Epi-data version 3.1 and exported to SPSS version 25 for Windows. How can you cleaned, edited, and coded before data entry?9. Television is not social media?10. How do you manage the multicollinearity between being a rural residence and a lower educational level?11. Should supply the basic preventive measures such as mask and sanitizers for financially poor individuals: You didn’t assess the availability of these preventive accessories so how can you recommend.12. Those independent variables that had p-value less than 0.25 in bivariate analysis were entered in to the multivariable logistic regressions model. What is your justification to use 0.25 as cut off points?Reviewer #2: In this manuscript, the authors conducted a community based cross-sectional study to assess The applicability of basic preventive measures of the pandemic COVID-19 and associated factors among residents in Guraghe Zone. The study is well written, is easy to follow and covers a hot topic, but some issues should be improved before publication.Comments1.The study is well thought off. I believed that the topic and the content of the manuscript was different. So, it will be advisable to modify the title like KAP2.In the method section, replace Method by Method and material3.There are many language mistakes, please revisit the manuscript for correction.4. Reference for your operational definition?5.Please give some explanations about the current availability of the vaccine6.Please complete all necessary information on the title of each Table7. Discussion section: Will be useful to the reader to add some interesting recent literature about the updates against COVID-19 outbreak and related tools to counteract the same8.Used very few reference, which results poor interpretation of your result, please use the following reference 9.Conclusion Section: The paragraph requires a general revision to eliminate redundant sentences and please refine and don’t repeat it in the abstract part.Reviewer #3: major3 why use design effect 1.5? , is there scientifically recommended to use design effect 1.5minor1, there is sentence and paragraph without reference on introduction part2, study are description part, please use recent data not more than 5 years3, the sampling procedure is multistage , it is better represent graphically that makes easily understand to readers4. on table 5 there is missing data , please incorporate this data5, it is better to exclude those data are not significant on multi-variate regression6, please include the p-value for those factors that are significant at multi-variant**********what does this mean?). If published, this will include your full peer review and any attached files.6. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool, AttachmentPONE-D-21-05518_reviewer comment.pdfSubmitted filename: Click here for additional data file. 16 Apr 2021Response to the Reviewers1. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.Reviewer #1: YesReviewer #2: YesReviewer #3: NoResponse; Thank you and certain revision were made.________________________________________2. Has the statistical analysis been performed appropriately and rigorously?Reviewer #1: NoReviewer #2: YesReviewer #3: NoResponse: Thank you and it was revised in detail.________________________________________3. Have the authors made all data underlying the findings in their manuscript fully available?The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.Reviewer #1: YesReviewer #2: YesReviewer #3: YesResponse: Thank you________________________________________4. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: NoReviewer #2: YesReviewer #3: YesResponse: Thank you and it was revised by a language expert. ________________________________________5. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Response: It was revised and we have responded point by point for each raised concerns and corrected as highlighted in the revised version.Reviewer #1: 1. The manuscript has a lot of typo errors grammatical, spelling, punctuation, and consistency in word usage like; COVID-19, COVID-2019 and COVID 19, Guraghe zone and Gurage zone, dyed instead of died.• Response: Thank you. All the inconsistencies were resolved and the whole manuscript was revised by language expert. ________________________________________2. High knowledge: If the respondent answers 11 of the 14 knowledge assessment questions correctly (10). What if the respondent answer 12, 13, and 14 of 14 knowledge assessment questions correctly????Response: Thank you and it was revised and it was to mean at least 11 of the 14 assessment questions. ________________________________________3. Moderate knowledge: If the respondent answers nine of the 14 knowledge assessment questions correctly (10). What if the respondent answers 10 of 14 knowledge assessment questions correctly????• Response: It was revised and which was to mean at least nine of the knowledge assessment questions. ________________________________________4. Poor knowledge: If the respondent responds below nine knowledge assessment questions correctly (10).• Response: It was revised as:- “Poor knowledge: If the respondent responds < 8 knowledge assessment questions correctly”. ________________________________________5. Good knowledge: If the respondent responds above nine knowledge assessment questions correctly• Response: It was revised as: - “Good knowledge: If the respondent responds > 9 knowledge assessment questions correctly”.________________________________________6. How did you measure attitude is not operationalized• Response: It was mentioned at the end of data collection tool and procedure but no we have stated at the subtitle, operational definition. ________________________________________7. The maximum total score ranged from 0–13, with a higher score indicating better knowledge about COVID-19. How can it be the maximum score of 13 if one individual answers all 14 questions correctly the maximum score will be 14? So, how do you justify it?• Response: Thank you. It was a typing error, which was to mean 14. If a respondent answers all the knowledge assessment questions correctly, stated as scored 14 of the 14 questions. ________________________________________8. Data were cleaned, edited, coded, and entered into Epi-data version 3.1 and exported to SPSS version 25 for Windows. How can you cleaned, edited, and coded before data entry?Response: The statement was rephrased and stated as:- “Data were entered into Epi-data version 3.1 and exported to SPSS version 25 for Windows, then cleaned, edited, coded and exploratory data analysis was carried out to check the levels of missing values, presence of influential outliers, multi-co linearity”.________________________________________9. Television is not social media?Response: It was revised and which was to mean mass media.________________________________________10. How do you manage the multicollinearity between being a rural residence and a lower educational level?Response: All the variables were checked for multicholinearity but multicholinearity was not existed. Therefore; no any management is required unless multicholinearity was observed. ________________________________________11. Should supply the basic preventive measures such as mask and sanitizers for financially poor individuals: You didn’t assess the availability of these preventive accessories so how can you recommend.Response: It was missed during manuscript preparation and incorporated now. This study was conducted as a baseline for further studies and for conducting community service across the study area. This study was presented within the university and community service was delivered through delivering the sanitizers, mask and health information dissemination. ________________________________________12. Those independent variables that had p-value less than 0.25 in bivariate analysis were entered in to the multivariable logistic regressions model. What is your justification to use 0.25 as cut off points?Response: In this study, we had used 12 independent variables. If we had sufficient variables, we can minimize the cutoff point but if the number of variables were not much we can increase the cutoff point. In addition; increasing the cutoff point will keep the marginally significant variables. Therefore; we have used the cutoff point 0.25 to select the candidate variable for multivariable analysis. ________________________________________Reviewer #2: In this manuscript, the authors conducted a community based cross-sectional study to assess The applicability of basic preventive measures of the pandemic COVID-19 and associated factors among residents in Guraghe Zone. The study is well written, is easy to follow and covers a hot topic, but some issues should be improved before publication.1) The study is well thought off. I believed that the topic and the content of the manuscript was different. So, it will be advisable to modify the title like KAPResponse: It was not aimed to investigate the knowledge and attitude but both of them were independent variables. They were described and as independent factors associated with the applicability of the basic preventive measures of COVID-19. As you have seen in the introduction part, it was focused to show the gap in the applicability of the basic preventive measures. In addition, as you have seen the outcome variable is the applicability of the basic preventive measures of the pandemic COVID-19, not KAP. ________________________________________2) In the method section, replace Method by Method and materialResponse: It was replaced accordingly.________________________________________3) There are many language mistakes, please revisit the manuscript for correction.Response: The whole manuscript was revised by a language expert. ________________________________________4) Reference for your operational definition?Response: Thank you all the operational definitions were cited. ________________________________________5) Please give some explanations about the current availability of the vaccineResponse; It was incorporated at the introduction section.________________________________________6) Please complete all necessary information on the title of each TableResponse: Thank you. It was revised and all the necessary information was incorporated. ________________________________________7) Discussion section: Will be useful to the reader to add some interesting recent literature about the updates against COVID-19 outbreak and related tools to counteract the sameResponse: Certain updated recent articles were cited. ________________________________________8) Used very few reference, which results poor interpretation of your result, please use the following reference Response: Thank you. All of them were cited. ________________________________________9) Conclusion Section: The paragraph requires a general revision to eliminate redundant sentences and please refine and don’t repeat it in the abstract part.Response: The conclusion was revised and certain amendments were made.________________________________________Response to Reviewer #3Why use design effect 1.5? , is there scientifically recommended to use design effect 1.5• Response: Design effect is determined by the researcher in considering the heterogeneity of the population. Most researchers use design effect 2 but it is possible to use also 1.5. We have decided to use it 1.5 in considering, the heterogeneity of the populations  and the cost that we have afford. ________________________________________Minor1. There is sentence and paragraph without reference on introduction partResponse: Thank you. All the statements were cited. ________________________________________2. On table 5 there is missing data , please incorporate this dataResponse: It was not a missing data, which was for the variables which were not statistically significant in multivariable analysis but to resolve this, we have the table in to two (table 5 & 6). ________________________________________3. It is better to exclude those data are not significant on multi-variate regressionResponse: It was revised and removed. ________________________________________4. Please include the p-value for those factors that are significant at multi-variantResponse: Thank you, it was included. ________________________________________AttachmentResponse to reviewers.docxSubmitted filename: Click here for additional data file. 15 Jun 2021PONE-D-21-05518R1The applicability of basic preventive measures of the pandemic COVID-19 and associated factors among residents in Guraghe ZonePLOS ONEDear Dr. Dessu,Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.Please address second reviewer concern and rephrase sentences in the abstract and conclusion to minimize repetition. plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.Please submit your revised manuscript by Jul 30 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at Please include the following items when submitting your revised manuscript:A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: We look forward to receiving your revised manuscript.Kind regards,Enamul KabirAcademic EditorPLOS ONEJournal Requirements:Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.[Note: HTML markup is below. Please do not edit.]Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.Reviewer #1: All comments have been addressedReviewer #2: All comments have been addressedReviewer #3: All comments have been addressed**********2. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********4. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********5. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********6. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: Line space in abstract part is not consistent. So make it consistent the line space for the conclusion part is not consistent with the other parts`Reviewer #2: The author addresses all comments, however, still they did not understood one of my comment regarding redundancy of sentence the conclusion in both the abstract and main body. Therefore, please rephrase and rewrite the conclusion to minimize repetitionReviewer #3: (No Response)**********what does this mean?). If published, this will include your full peer review and any attached files.7. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool,  15 Jun 2021Both concdrns were addressed and corrected.AttachmentResponse to reviewers.docxSubmitted filename: Click here for additional data file. 21 Jul 2021PONE-D-21-05518R2The applicability of basic preventive measures of the pandemic COVID-19 and associated factors among residents in Guraghe ZonePLOS ONEDear Dr. Dessu,Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.One of the reviewers raised some minor issues those need to be fixed before taking final decision.plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.Please submit your revised manuscript by Sep 04 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at Please include the following items when submitting your revised manuscript:A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: We look forward to receiving your revised manuscript.Kind regards,Enamul KabirAcademic EditorPLOS ONEJournal Requirements:Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.Additional Editor Comments (if provided):[Note: HTML markup is below. Please do not edit.]Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.Reviewer #1: All comments have been addressedReviewer #2: All comments have been addressedReviewer #3: All comments have been addressed**********2. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********4. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********5. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********6. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: CommentsThe authors have carefully addressed almost all the issues raised by reviewers in the first review process. However, the additional comments below should be addressed to enhance the quality of the paper.On Abstract, data processing and analysis, and result session better to address these comments which are highlighted in the main manuscript:• P-value ≤0.05 better to change <0.05• All prevalence, proportion, and magnitude are better to be in one decimal point including its confidence intervals. For instance, 21.9%  of the respondents have good knowledge, 94.2%  had a favorable attitude, and 17.7%  apply basic preventive measures …………• The odds ratio and its respective confidence interval better to be in two decimal points. For example, • As a principle; the prevalence, proportion, magnitude, odds, and its respective confidence interval should have a similar decimal points which means one decimal point for prevalence, proportion, and magnitude and two decimal points for odds.• All the recommendations have no owner it doesn’t tell anything about for whom you are going to recommend. So, it is better to indicate the specific stakeholders for each of your recommendations.Reviewer #2: The author addressed all comments provided by me and all other reviewers. Therefore, I confirmed that it is accepted.Reviewer #3: the author addressed all comments adequately and proper statically analysis and technically good and I recommend for publication**********what does this mean?). If published, this will include your full peer review and any attached files.7. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool, AttachmentPONE-D-21-05518_R2 with comments.pdfSubmitted filename: Click here for additional data file.AttachmentComments to Autor.docxSubmitted filename: Click here for additional data file. 22 Jul 2021Response to reviewers• P-value ≤0.05 better to change <0.05 Response: It was revised and corrected as “P-value <0.05 was used as a cutoff point to determine statistical significance in multiple logistic regressions for the final model”. • All prevalence, proportion, and magnitude are better to be in one decimal point including its confidence intervals. For instance, 21.9%  of the respondents have good knowledge, 94.2%  had a favorable attitude, and 17.7%  apply basic preventive measures …………Response: It was revised and corrected all over the manuscript as:- “In this study, 17.7%  of the respondents apply the basic preventive measures towards the prevention of the pandemic COVID-19”. • The odds ratio and its respective confidence interval better to be in two decimal points. For example, o Response: It was revised and corrected as:- “In addition, being rural resident , being studied grade 1-8 , being a farmer , currently not married , having family size 1-3, have no diagnosed medical illness  and having poor knowledge  were factors which are statistically significant in multivariable logistic regression model”.• As a principle; the prevalence, proportion, magnitude, odds, and its respective confidence interval should have a similar decimal points which means one decimal point for prevalence, proportion, and magnitude and two decimal points for odds. o Response: It was revised and corrected as per your recommendations.• All the recommendations have no owner it doesn’t tell anything about for whom you are going to recommend. So, it is better to indicate the specific stakeholders for each of your recommendations.o Response: It was revised and the recommendations were given for the specific bodies.AttachmentResponse to reviewers.docxSubmitted filename: Click here for additional data file. 11 Aug 2021The applicability of basic preventive measures of the pandemic COVID-19 and associated factors among residents in Guraghe ZonePONE-D-21-05518R3Dear Dr. Dessu,We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at onepress@plos.org.If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact Kind regards,Enamul KabirAcademic EditorPLOS ONEAdditional Editor Comments :Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.Reviewer #1: All comments have been addressedReviewer #2: All comments have been addressed**********2. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: YesReviewer #2: Yes**********3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: YesReviewer #2: Yes**********4. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: YesReviewer #2: Yes**********5. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: Yes**********6. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: All comments have been addressed; The language, typographic errors, analysis, and overall the paper addressed scientific writeup formats. And all my concerns are addressed and it is fit to be accepted for possible publication.Reviewer #2: All comments are well addressed and incorporated in the main body of the manuscript. So, please do not submit again more for revision**********what does this mean?). If published, this will include your full peer review and any attached files.7. PLOS authors have the option to publish the peer review history of their article (If you choose “no”, your identity will remain anonymous but your review may still be made public.Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.Reviewer #1: NoReviewer #2: No 16 Aug 2021PONE-D-21-05518R3 The applicability of basic preventive measures of the pandemic COVID-19 and associated factors among residents in Guraghe Zone Dear Dr. Dessu:I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. 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Nature Communications 10.1038/s41467-021-25534-2, published online 6 September 2021.Correction to: In the original PDF version of this Article, there was an error in the code within the 'Methods' subsection ‘scETM software’. The original text read:“from scETM import scETM,UnsupervisedTrainermodel = scETMtrainer = UnsupervisedTrainertrainer.trainmodel.get_all_embeddings_and_nll(adata)”The correct format is:“from scETM import scETM, UnsupervisedTrainermodel = scETMtrainer = UnsupervisedTrainertrainer.trainmodel.get_all_embeddings_and_nll(adata)”This has been corrected in the PDF version of the Article; the HTML version was correct at the time of publication.


Manihot esculenta) is an important clonally propagated food crop in tropical and subtropical regions worldwide. Genetic gain by molecular breeding has been limited, partially because cassava is a highly heterozygous crop with a repetitive and difficult-to-assemble genome.Cassava  differences. ASE bias was often tissue specific and inconsistent across different tissues. Direction-shifting was observed in <2% of the ASE transcripts. Despite high gene synteny, the HiFi genome assembly revealed extensive chromosome rearrangements and abundant intra-genomic and inter-genomic divergent sequences, with large structural variations mostly related to LTR retrotransposons. We use the reference-quality assemblies to build a cassava pan-genome and demonstrate its importance in representing the genetic diversity of cassava for downstream reference-guided omics analysis and breeding.Here we demonstrate that Pacific Biosciences high-fidelity (HiFi) sequencing reads, in combination with the assembler hifiasm, produced genome assemblies at near complete haplotype resolution with higher continuity and accuracy compared to conventional long sequencing reads. We present 2 chromosome-scale haploid genomes phased with Hi-C technology for the diploid African cassava variety TME204. With consensus accuracy >QV46, contig N50 >18 Mb, BUSCO completeness of 99%, and 35k phased gene loci, it is the most accurate, continuous, complete, and haplotype-resolved cassava genome assembly so far. The phased and annotated chromosome pairs allow a systematic view of the heterozygous diploid genome organization in cassava with improved accuracy, completeness, and haplotype resolution. They will be a valuable resource for cassava breeding and research. Our study may also provide insights into developing cost-effective and efficient strategies for resolving complex genomes with high resolution, accuracy, and continuity. Manihot esculenta, NCBI:txid3983) genome has a haploid genome size ∼750 Mb dCTP) probes. DNA was extracted from individual clones using Nucleobond Xtra midi kit (Macherey-Nagel) and used for PacBio library preparation by the French Plant Genomic Resources Center (CNRGV) of the French National Research Institute for Agriculture, Food and Environment (INRAE). PacBio sequencing was performed on the Sequel II system with a movie time of 30 hours with 120-min pre-extension step by Gentyane Genomic Platform (INRAE). Circular consensus sequence (CCS) reads per BAC clone were generated using SMRT Analysis Software SMRT Link v9.0.0  and FastQ Screen v0.11.1 , respectively. The technical quality of PacBio raw data was checked using the “QC module” in the PacBio SMRT Analysis Software SMRT Link version 8.0 . Iso-Seq reads were clustered into high-quality  transcripts using the “Iso-Seq Analysis” Application in PacBio SMRT Analysis Software (SMRT Link v10.1.0.119588). The technical quality of Hi-C data was checked using HiCUP v0.8.0  [The technical quality and potential sample contamination in Illumina PE reads were evaluated using FastQC v0.11.8  .k-mers in the Illumina PE reads using Preqc in SGA v0.10.15  [Genome complexities such as repeat content and the level of heterozygosity were evaluated with _001982) ,54. Anal_001982) , cassavaRRID:SCR_016089) [RRID:SCR_021069) [RRID:SCR_015880) [PacBio CLR reads were assembled using Falcon   in pb-as_016089) , hifiasm_021069) , and HiCRRID:SCR_001228) [k-mer–based method Merqury (v1.1) [Assembly statistics were collected using QUAST v4.5  . NG50 [5_001228)  was calck-mer analysis results were first used to compute false duplication rates, where k-mers that appeared more than twice in each haploid assembly were used to identify artificial duplications. PacBio CLR reads were then aligned to each haploid genome and the coverage was analyzed using Asset software [For evaluation of structural accuracy, Merqury software . AssemblRRID:SCR_015008) completeness of single-copy orthologs discovered in plants (Viridiplantae Odb10) [RRID:SCR_018550) [Functional completeness was measured using BUSCO v5  , and alie Odb10)  were dowe Odb10) . Referen_018550) . The “as_018550)  were cal_018550) .RRID:SCR_011919) [Two sets of haplotype-resolved, phased contig (haplotig) assemblies were generated using hifiasm (v0.15.3) with a combination of HiFi reads and PE Hi-C reads. Haplotigs were first validated against the high-density genetic map of cassava , which c_011919) . For eacRRID:SCR_021171) [Hi-C reads were mapped back to each set of haplotigs independently using the Arima mapping pipeline  and were_021171)  was used_021171) . Given tRRID:SCR_015027), with dependency on TRF (v4.09) [RRID:SCR_021170) [RRID:SCR_014653) [RRID:SCR_012954) [RRID:SCR_016120) [RRID:SCR_017623) [RRID:SCR_011811) [RRID:SCR_007105) [Starting with the assembly of all resolved alleles , repeat elements were predicted using RepeatModeler v2.0.1  , RECON v_021170) , RepeatS_014653) , and Rep_016120) , LTR_Ret_017623) , Ninja (_017623) , MAFFT v_011811) , and CD-_007105) . Among t_007105) , and eacGenome annotation was first performed by transferring reference gene models from AM560 v8.1 to TME204 haplotype assemblies using liftoff (v1.6.1) . Findingab initio gene prediction was performed using AUGUSTUS  [RRID:SCR_006646). Predicted protein sequences were compared against AM560 v8.1 protein sequences and Uniprot/Swiss-Prot (release 2021_03) using blastp v2.10.1+  and InterPro using InterProScan v5.52–86.0 . The best protein matches from AM560 v8.1, Uniprot/Swiss-Prot, and InterPro, plus Gene Ontology (GO) terms and pathways, were used to functionally annotate predicted genes.Complementary to the transferred reference gene models, _008417)  with expRRID:SCR_016582) [RRID:SCR_015687) [2|FC| > 2 and adjusted P < 0.00001.Transcripts annotated in TME204 H1 and H2 were pooled and de-duplicated using cd-hit-est (v4.8.1)  to gener_015687)  as thoseRRID:SCR_001598) comparison of H1 and H2 transcripts. A unique, bi-directional best-matched transcript pair was considered as allele A and B. Expression values for bi-allelic transcripts were a subset from the master quantification table including all resolved alleles. ASE was determined using the same package DEseq2, with adjusted P < 0.05. ASE transcripts overlapped between tissues and haplotypes were analyzed using upsetR [For ASE, bi-allelic transcripts were identified by reciprocal blastn (v2.10.0)  [For alignment-based sequence similarity analysis, the cassava reference genome AM560 v8.0 was first disassembled into contig sequences using the utility function “split_scaffold” in IDBA (v1.1.3) . Each se_018171) , which r_018171)  and Asse_018171)  for idenRRID:SCR_018550) [For SV analysis using HiFi reads, TME204 HiFi reads were aligned to reference contigs of AM560 and TME204 haplotigs using minimap2 v2.15r905  . SVs wer_018550) . Summary_018550) .For chromosome-level comparisons, the alignment-free method smash++ (v20.04)  was usedPan-genomes were constructed using minigraph (v0.15-r426) . Large SRRID:SCR_014798) [P-value cut-off set to 0.00001. The only exception was for the 141 homozygous DETs, where the P-value cut-off was set to 0.001. GO annotation of the ab initio predicted gene models were used as the background gene set.For all selected gene sets, GO enrichment analysis was performed using topGO v2.44.0  ,90 with MZ959795, MZ959796, MZ959797, and MZ959798. All supporting data and materials are available in the GigaScience GigaDB database [Raw sequencing read data from PacBio  and Illumina (Hi-C and shotgun) underlying this article are available in the European Nucleotide Archive (ENA) database and can be accessed with accession No. PRJEB43673 (or ERP127652 as the secondary accession number in ENA). Assembled genome sequences of TME204 H1 and H2 are available in the NCBI database and can be accessed with accession No. PRJNA758616 and PRJNA758615, respectively. Assembled BAC clone sequences are available in the NCBI GenBank database and can be accessed with accession Nos. database .ASE: allele-specific expression; BAC: bacterial artificial chromosome; BP: biological process; bp: base pairs; CCS: circular consensus sequence; CDS: coding sequence; CLR: continuous long reads; CMD: Cassava Mosaic Diseases; CPU: central processing unit; DE: differentially expressed/differential expression; DET: differentially expressed transcript; ENA: European Nucleotide Archive; GO: gene ontology; HiFi: high-fidelity; HMW: high molecular weight; Indel: insertion and deletion; IPA: Improved Phased Assembler; kb: kilobase pairs; Mb: megabase pairs; MF: molecular function; NCBI: National Center for Biotechnology Information; numt's: nuclear mitochondrial pseudogene regions; PacBio: Pacific Biosciences; PE: paired-end; QV: quality value; RAM: root apical meristem; SAM: shoot apical meristem; SMRT: Single Molecule Real-Time; SNP: single-nucleotide polymorphism; SV: structural variation; TPM: transcript per million; VGP: the Vertebrate Genome Project.The cassava TME204  cultivar used in our study was obtained by ETH Zurich from the International Institute of Tropical Agriculture (IITA) in Nigeria in 2003 prior to the implementation of the International Treaty on Plant Genetic Resources for Food and Agriculture . TME204 The authors declare that they have no competing interests.This work was supported by the Bill & Melinda Gates Foundation (INV-008213), ETH Zurich, and the Functional Genomics Center Zurich (FGCZ). D.P. is funded by national funds through FCT  under the Institutional Call to Scientific Employment Stimulus (reference CEECINST/00026/2018). W.G. is supported by a Yushan Scholarship of the Ministry of Education in Taiwan.W.Q., Y.L., A.P., R.S., and W.G. designed the study. Y.L. and C.C. prepared DNA and RNA samples for sequencing. A.P., S.G., and A.B. prepared CLR, HiFi, and Iso-Seq libraries and performed PacBio sequencing. Y.L., N.R., E.P., S.V., and M.F. generated the BAC sequences. W.Q., Y.L., P.S., D.P., and W.G. analyzed data. W.Q., Y.L., A.P., A.B., P.S., and W.G. wrote the manuscript. All authors reviewed the final manuscript before submission.giac028_GIGA-D-21-00333_Original_SubmissionClick here for additional data file.giac028_GIGA-D-21-00333_Revision_1Click here for additional data file.giac028_GIGA-D-21-00333_Revision_2Click here for additional data file.giac028_GIGA-D-21-00333_Revision_3Click here for additional data file.giac028_Response_to_Reviewer_Comments_Revision_1Click here for additional data file.giac028_Response_to_Reviewer_Comments_Revision_2Click here for additional data file.giac028_Response_to_Reviewer_Comments_Revision_3Click here for additional data file.giac028_Reviewer_1_Report_Original_SubmissionZehong Ding -- 11/11/2021 ReviewedClick here for additional data file.giac028_Reviewer_1_Report_Revision_1Zehong Ding -- 1/16/2022 ReviewedClick here for additional data file.giac028_Reviewer_2_Report_Original_SubmissionC Robin Buell -- 11/17/2021 ReviewedClick here for additional data file.giac028_Reviewer_2_Report_Revision_1C Robin Buell -- 1/16/2022 ReviewedClick here for additional data file.giac028_Supplemental_FileClick here for additional data file.


With the emergence of new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants and the acquisition of novel mutations in existing lineages, the need to implement methods capable of monitoring viral dynamics arises. We report the emergence and spread of a new SARS-CoV-2 variant within the B.1.575 lineage, containing the E484K mutation in the spike protein (named B.1.575.2), in a region in northern Spain in May and June 2021. SARS-CoV-2-positive samples with cycle threshold values of ≤30 were selected to screen for presumptive variants using the TaqPath coronavirus disease 2019 (COVID-19) reverse transcription (RT)-PCR kit and the TaqMan SARS-CoV-2 mutation panel. Confirmation of variants was performed by whole-genome sequencing. Of the 200 samples belonging to the B.1.575 lineage, 194 (97%) corresponded to the B.1.575.2 sublineage, which was related to the presence of the E484K mutation. Of 197 cases registered in the Global Initiative on Sharing Avian Influenza Data (GISAID) EpiCoV database as lineage B.1.575.2, 194 (99.5%) were identified in Pamplona, Spain. This report emphasizes the importance of complementing surveillance of SARS-CoV-2 with sequencing for the rapid control of emerging viral variants. During the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, several variants that were catalogued as variants of concern (VOCs) or variants of interest (VOIs) by the European Centre for Disease Prevention and Control have emerged in different countries. As of 23 June 2021, the four important lineages with evident impact on transmissibility, severity, and immunity are lineages B.1.1.7 (Alpha), B.1.351 (Beta), B.1.617.2 (Delta), and P.1 (Gamma) 14. LineagThe lineage B.1.575 emerged in the United States, and since its emergence two new sublineages have been identified. The B.1.575.1 sublineage was classified in the Phylogenetic Assignment of Named Global Outbreak (PANGO) lineage system as a Spanish sublineage of B.1.575 with spike mutations P681H, S494P, and T716I, and the B.1.575.2 sublineage, whose main characteristic is the presence of the E484K spike mutation, also originated in Spain  screening and whole-genome sequencing.TC) value of ≤30. Occasionally, targeted samples are also included according to epidemiological criteria.The Microbiology Department of the Complejo Hospitalario de Navarra, which is located in Pamplona, the capital city of Navarra, Spain , is the reference laboratory of the public health system for SARS-CoV-2. Upper respiratory specimens for SARS-CoV-2 detection are routinely collected at hospitals and primary care centers and processed by commercial RT-qPCR methods. Since the end of 2020, when variant B.1.1.7 became predominant in the United Kingdom, prospective sample-based surveillance has been conducted in our community to identify novel emerging SARS-CoV-2 variants. A two-step laboratory procedure includes all positive SARS-CoV-2 samples from hospital patients and community settings with a cycle threshold (Screening of presumptive SARS-CoV-2 variants carrying the ΔH69/ΔV70 deletion was performed using the TaqPath coronavirus disease 2019 (COVID-19) RT-PCR kit , following the manufacturer’s instructions. Then, all samples of non-B.1.1.7 variants were subjected to a second RT-qPCR assay with the TaqMan SARS-CoV-2 mutation panel (Thermo Fisher Scientific). At that time, we customized the TaqMan assay to detect SARS-CoV-2 spike protein with the N501Y, E484K, K417N, and K417T mutations. All samples were sequenced.https://www.gisaid.org), Nextstrain (https://nextstrain.org), and the PANGO lineage system (https://cov-lineages.org)  on the Illumina NovaSeq 6000 system located in the public company NASERTIC, following the manufacturer’s instructions. The viral lineage classifications were performed with the Global Initiative on Sharing Avian Influenza Data (GISAID) EpiCoV database (ges.org) –11.http://gisaid.org) under accession numbers EPI_ISL_2510533, EPI_ISL_2510585 to EPI_ISL_2510589, EPI_ISL_2510592, EPI_ISL_2516620, EPI_ISL_2516686 to EPI_ISL_2516689, EPI_ISL_2516691, EPI_ISL_2516698 to EPI_ISL_2516704, EPI_ISL_2516709, EPI_ISL_2516710 to EPI_ISL_2516715, EPI_ISL_2516717 to EPI_ISL_2516721, EPI_ISL_2516723, EPI_ISL_2516724, EPI_ISL_2516726 to EPI_ISL_2516728, EPI_ISL_2516731, EPI_ISL_2516732, EPI_ISL_2516734 to EPI_ISL_2516749, EPI_ISL_2516753, EPI_ISL_2516754, EPI_ISL_2516756, EPI_ISL_2516757, EPI_ISL_2516759 to EPI_ISL_2516761, EPI_ISL_2516855 to EPI_ISL_2516857, EPI_ISL_2516861 to EPI_ISL_2516877, EPI_ISL_2516879, EPI_ISL_2516881, EPI_ISL_2516934, EPI_ISL_2516937 to EPI_ISL_2516940, EPI_ISL_2934576 to EPI_ISL_2934590, EPI_ISL_2934594, EPI_ISL_2934597, EPI_ISL_2934599 to EPI_ISL_2934603, EPI_ISL_2934617 to EPI_ISL_2934623, EPI_ISL_2934625, EPI_ISL_2934626, EPI_ISL_2934629 to EPI_ISL_2934635, EPI_ISL_2934638 to EPI_ISL_2934640, EPI_ISL_2934642, EPI_ISL_2934645 to EPI_ISL_2934651, EPI_ISL_2934656 to EPI_ISL_2934659, EPI_ISL_2934661, EPI_ISL_2934662, EPI_ISL_2934665 to EPI_ISL_2934669, EPI_ISL_2934672, EPI_ISL_2934673, EPI_ISL_2934676 to EPI_ISL_2934681, EPI_ISL_2934684 to EPI_ISL_2934686, EPI_ISL_2934699, EPI_ISL_2934703 to EPI_ISL_2934722, EPI_ISL_2934728 to EPI_ISL_2934730, EPI_ISL_2934844, EPI_ISL_2934846 to EPI_ISL_2934848, EPI_ISL_2934852, EPI_ISL_2934853, EPI_ISL_2934897, EPI_ISL_2934905, EPI_ISL_2934906, EPI_ISL_2934910, and EPI_ISL_2934917 (B.1.575.2), EPI_ISL_1392993 and EPI_ISL_1393347 (B.1.575.1), and EPI_ISL_1622537, EPI_ISL_1622538, EPI_ISL_1622541, and EPI_ISL_1622850 (B.1.575).All genomes generated in this work were deposited in the GISAID EpiCoV database  related to the B.1.575 lineage, i.e., 4 (2%) B.1.575, 2 (1%) B.1.575.1, and 194 (97%) B.1.575.2. Among the common substitutions present in these lineages, four occurred in the spike protein  . All samThe first case with the B.1.575 lineage to be identified in Pamplona dates back to 20 January 2021; after that date, no other case was identified until 15 March 2021, when three isolates showing mutations common to the B.1.575 lineage were recorded. Between week 20 and week 26 of 2021, we identified 194 cases with lineage B.1.575, which had acquired another S mutation, E484K, classified in the GISAID EpiCoV and Pangolin databases as representing sublineage B.1.575.2. The first case with the B.1.575.2 lineage was identified in a sample isolated on 19 May 2021 (week 20 of 2021); the number of cases grew to 48 cases in weeks 23 and 24 and declined suddenly at the end of June due to the emergence of the Delta (B.1.617.2) variant . This vaTo determine the distribution of the SARS-CoV-2 B.1.575 lineage, we searched in the GISAID EpiCoV and PANGO lineage databases. From May to July, the lineage and sublineages of B.1.575 have increased exponentially in different countries. The B.1.575 lineage was predominant in the United States (90%), while the B.1.575.1 and B.1.575.2 sublineages dominated in Spain .The B.1.575.2 sublineage was predominant in Navarra, since 99.5% of the cases (194/197 cases) registered in the GISAID EpiCoV database were identified in this region. In contrast, we did not identify any genomes of the B.1.575 or B.1.575.1 lineage carrying the E484K mutation.In this study, we observed the emergence of lineage B.1.575.2 with the spike E484K mutation, circulating in Pamplona in association with an outbreak. Pamplona is a small city located in the north of Spain, near France, and it could serve as a spread model for other cities in the world. The new lineage displayed a low prevalence (4.10%) among SARS-CoV-2 genomes analyzed between 23 March 2020 and 30 June 2021. Still, it was already dispersed in our city and represented 97% of the B.1.575 sequences detected during that period. The E484K mutation is considered one of the most important substitutions associated with reduced antibody neutralization potency and efficacy of the SARS-CoV-2 vaccine –15. The –1–Screening PCR is a useful tool for detecting mutations, mainly because of its rapidity. Future identification with this method, including new mutations characteristic of the lineage, could serve as a rapid method of variant identification. However, whole-genome sequencing remains the gold standard technique for pandemic control.To our knowledge, this is the first study that describes the emergence of the lineage B.1.575.2. This genetic variant includes a mutation in the spike protein (E484K). This SARS-CoV-2 genetic variant was discovered in Pamplona in association with an outbreak, demonstrating the importance of genetic sequencing, especially for new community outbreaks.This brief report emphasizes the importance of exhaustive surveillance for circulating variants of SARS-CoV-2, to reduce community transmission, to assess the COVID-19 vaccine effectiveness, and to prevent the emergence of more transmissible variants that could further increase the severity of the epidemic in the country.


G3 Genes|Genomes|Genetics, 2021, 11(3)., DOI: https://doi.org/10.1093/g3journal/jkaa029https://doi.org/10.25387/g3.12813299”. This should have been “https://figshare.com/articles/figure/Supplemental_Material_for_Shweta_Basargekar_and_Ratnaparkhi_2020/12813299?file=25392737”. This has now been corrected online.When this paper first published, in the data availability section, the location of supplementary data was erroneously given as “figshare DOI:


This protocol tracks engaged transcription complexes across functional genomic regions demonstrated in human K562 erythroleukemia cells.Nascent RNA-sequencing tracks transcription at nucleotide resolution. The genomic distribution of engaged transcription complexes, in turn, uncovers functional genomic regions. Here, we provide analytical steps to (1) identify transcribed regulatory elements For complete details on the use and execution of this protocol, please refer to   •de novo genome-wideIdentification of transcribed regulatory elements •Quantification of engaged transcription complexes at functional genomic regions•Measuring distribution of transcription regulators across the functional genomic regions•Revealing functional genomic regions from nascent transcription data de novo genome-wide, (2) quantify engaged transcription complexes at enhancers, promoter-proximal regions, divergent transcripts, gene bodies, and termination windows, and (3) measure distribution of transcription machineries and regulatory proteins across functional genomic regions. This protocol tracks engaged transcription complexes across functional genomic regions demonstrated in human K562 erythroleukemia cells.Nascent RNA-sequencing tracks transcription at nucleotide resolution. The genomic distribution of engaged transcription complexes, in turn, uncovers functional genomic regions. Here, we provide analytical steps to (1) identify transcribed regulatory elements  Transcription is a fundamental process in every organism, and its coordination defines RNA synthesis in the cell. A plethora of transcription factors, cofactors, chromatin remodelers and RNA-processing complexes orchestrate the process of RNA synthesis  complexes, and the three-dimensional architecture of the linear DNA molecules  for PRO-seq have been reported. Here, we begin with sequenced and mapped PRO-seq reads in bed format (https://www.ncbi.nlm.nih.gov/geo/) using accession code GSE181161.Wet-lab protocols  and compd format B and strd format C. The bed format C and unrd format , remappehttp://hgdownload.soe.ucsc.edu/goldenPath/. Here, the human hg38 file (2020-08-17) is downloaded in step 4 using wget (https://www.gnu.org/software/wget/).We derive functional genomic regions from the profile of active transcription and the refGene-annotated coordinates of gene transcripts. The refGene list of transcripts can be downloaded from the UCSC genome golden path: de novo using the pattern of divergent transcription (via the web interface (https://django.dreg.scigap.org/) or installed locally (https://github.com/Danko-Lab/dREG). For broad accessibility, the web-based tool is used here. Unnormalized bigWig files are generally provided with PRO-seq data. If needed, the code below converts a bed file reporting the whole read (https://www.encodeproject.org/software/bedgraphtobigwig/). The required chrSizes.txt file is a two-column data frame that contains the chromosome names and the sizes , obtainable for the appropriate genome from http://hgdownload.cse.ucsc.edu/goldenpath/.awk ‘$6 == "+"’ PROseq.bed | genomeCoverageBed -i stdin -3 -bg -g chrSizes.txt > PROseq_pl.bedgraphawk ‘$6 == "-"’ PROseq.bed | genomeCoverageBed -i stdin -3 -bg -g chrSizes.txt > PROseq_temp.bedgraphawk ‘{$4=$4∗-1; print}’ PROseq_temp.bedgraph > PROseq_mn.bedgraphbedgraphToBigWig PROseq_pl.bedgraph chrSizes.txt PROseq_pl.bigWigbedgraphToBigWig PROseq_mn.bedgraph chrSizes.txt PROseq_mn.bigWigEnhancers can be identified cription . In thiscription . dREG inole read C. One ofhttps://github.com/Vihervaara/ChIP-seq_analyses).Regulatory proteins coordinate every step of transcription. In this protocol, the functional genomic regions are first identified and color-coded to show enhancer regions in green, sites of divergent transcription (div) in purple, promoter-proximal regions (pp) in orange, gene body (gb) in black, region around CPS in light blue and termination window (tw) in pink A and 3B.https://www.r-project.org) and coordinates of functional genomic regions are compared to active sites of nascent transcription using bedtools ((https://bedtools.readthedocs.io/en/latest/).The data-analyses reported here are conducted in the command line environment of the Apple OS X operating system. Lists of genomic coordinates are processed in R  de novo A. Subseqde novo A. Sites de novo . For simvia GitHub .Enhancer coordinates reported here are the dREG-identified sites of divergent transcription that do not overlap with any annotated promoter of a gene. Active genes, instead, are further divided into distinct regions B. A browTiming: 1–3 hThis section identifies transcribed regulatory elements in the investigated cell line and condition.1.https://django.dreg.scigap.org/. Log in.a.Choose dREG peak calling.b.plus strand file to the correct box.Upload the unnormalized 3′-coverage bigWig c.minus strand file to the correct box.Upload the unnormalized 3′-coverage bigWig plus strand and -1 for the minus strand).Please note that the bigWig files need to be unnormalized  to describe your run and press Launch. The run time depends on the size of the file and available processing capacity, commonly ranging 1–3h.Create an account at 2.When the run is complete, download the prefix.dREG.peak.full.bed.gz file and gunzip it.3.Move the downloaded file to the working directory and rename it to a simpler form:mv ∼/Downloads/K562_hg38.dREG.peak.full.bed /pathToWorkingDirectory/dREGcalls_hg38_K562.bedTiming: 30 minThese steps (4–6) divide genes into functional regions.4.Download RefGene datafile, gunzip it and open it in R.http://hgdownload.soe.ucsc.edu/goldenPath/hg38/database/refGene.txt.gzwget -c -O hg38.refGene.txt.gz gunzip hg38.refGene.txt.gzRrefGene = read.table#gives the number of rows and columns in the refGene dataframedim(refGene) #shows the first six rows of the dataframehead(refGene)  #shows information on each dimensionstr(refGene) 5.Name the refGene columns and remove unnecessary columns and chromosome entries.names(refGene) =c#maintains chromosomes 1-22, X, Y and M.refGene = refGene  #drops the extra levels removed above.refGene$chr = factor(refGene$chr)  refGene = refGene#look at the dataframe againhead(refGene)  6.Generate coordinates of functional regions for every annotated gene transcript.### Subset the genes based on the strand:refGene_pl = subsetrefGene_mn = subsetplus strand:### Genes on the # TSSrefGene_pl$TSS = refGene_pl$txStart # CPSrefGene_pl$CPS = refGene_pl$txEnd  # region of divergent transcriptionrefGene_pl$DIVs = refGene_pl$txStart-750 refGene_pl$DIVe = refGene_pl$txStart-251# promoter-proximal regionrefGene_pl$PPs = refGene_pl$TSS-250  refGene_pl$PPe = refGene_pl$TSS+249# genebodyrefGene_pl$GBs = refGene_pl$TSS+250  refGene_pl$GBe = refGene_pl$CPS-501# CPS regionrefGene_pl$CPSs = refGene_pl$CPS-500  refGene_pl$CPSe = refGene_pl$CPS+499# termination windowrefGene_pl$TWs = refGene_pl$CPS+500  refGene_pl$TWe = refGene_pl$CPS+10499minus strand:#### Genes on the # TSSrefGene_mn$TSS = refGene_mn$txEnd  # CPSrefGene_mn$CPS = refGene_mn$txStart  # divergent transcription regionrefGene_mn$DIVs = refGene_mn$txEnd+251  refGene_mn$DIVe = refGene_mn$txEnd+750# promoter-proximal regionrefGene_mn$PPs = refGene_mn$TSS-249  refGene_mn$PPe = refGene_mn$TSS+250# genebodyrefGene_mn$GBs = refGene_mn$CPS+501  refGene_mn$GBe = refGene_mn$TSS-250# CPS regionrefGene_mn$CPSs = refGene_mn$CPS-499  refGene_mn$CPSe = refGene_mn$CPS+500# termination windowrefGene_mn$TWs = refGene_mn$CPS-10499  refGene_mn$TWe = refGene_mn$CPS-500#### combine the data of plus and minus stands:refGene = rbindrefGene$promC1 = refGene$TSS-500refGene$promC2 = refGene$TSS+500#### generate data files:write.tablewrite.table], file="hg38_refGenes_TSSpm500.txt", col.names=F, row.names=F, quote=F, sep="\t")save.image      # saves the above entries in the Rq       # exits Ry        # answers ‘yes’ for saving the workspace imageIn the RefGene data file, the ‘txStart’ is smaller than the same transcript’s ‘txEnd’. This is convenient when working with the coordinates of genes, but it leads to different columns reporting different functional sites depending on whether the plus or the minus strand encodes the gene. For example, the annotated TSS for genes on the plus strand is reported as txStart, while the TSS for genes on the minus strand is reported as txEnd. In the following steps, we add a column ‘TSS’ that reports the annotated TSS for each transcript. We then output a file that reports a 1000-nt window around the TSS. These windows of 1000 nt are intersected with the coordinates of dREG-identified sites of divergent transcription in step 7 to identify genes with active transcription and distal sites of divergent transcription, i.e., enhancers. We also obtain transcript-specific coordinates of promoter-proximal region (PP), divergent transcription (DIV), gene body (GB), CPS, and termination window (TW) according to the scheme in https://github.com/Vihervaara/functionalGenomicRegions).Please note that an R script comprising the steps from reading the refGene file in step 4 to the end of step 6 is provided in GitHub 9.Generate a new data frame in R that contains only actively transcribed genes. In essence, the ‘refGene’ data frame generated in step 6 is reduced here to contain only gene transcripts which initiate transcription. The ‘txID’ column contains an individual identification code for each transcript variant.refGeneAct = subset10.Write files that contain the coordinates of promoter-proximal and divergent transcription regions. These coordinates were generated in step 6.write.table], file="ppPolII.txt", col.names=F, row.names=F, quote=F, sep="\t")write.table], file="divTx.txt", col.names=F, row.names=F, quote=F, sep="\t")11.Remove short genes before generating files with the gene body coordinates. This stage is needed to omit gene transcripts, where, due to shortness of the gene, the gene body would overlap with the promoter-proximal region (stretching to +500 from TSS) and CPS (starting from −500 from CPS) windows.shortGenes = subsetrefGeneAct_ = subset#in K562 cells mapped against hg38, 351 active genes are removed at this stage.12.Write the files for the CPSs, gene body coordinates and transcription windows.write.table], file="CPS.txt", col.names=F, row.names=F, quote=F, sep="\t")write.table], file="TW.txt", col.names=F, row.names=F, quote=F, sep="\t")refGeneAct_ = subset #ensuring no negative gene body lengths remain.write.table], file="geneBody.txt", col.names=F, row.names=F, quote=F, sep="\t")save.imageqyOf note: In the RefGen for hg38 file, short genes constitute 3,575 transcripts. Of these, only 351 genes were uniquely mappable, identified as ‘Active’ and, therefore, removed from our list of active gene transcripts in K562 cells.The steps 8–12 can also be run via an R script provided in GitHub .Timing: 20 minIn steps 13 and 14, active sites of transcription are allocated to individual functional genomic regions. The active sites of transcription are derived from the nascent transcription sequencing data.13.a.echo retaining 3prime most coordinate of the bed file awk ‘$6 == "+"’ PROseq_K562_hg38.bed > tempPL.bed awk ‘$6 == "-"’ PROseq_K562_hg38.bed > tempMN.bedSplit the file based on the strand of the mapped readb. awk ‘{$2 = $3; print}’ tempPL.bed > tempPL_3p.bed awk ‘{$3 = $2; print}’ tempMN.bed > tempMN_3p.bedActive site of transcription (3′-most nt) is the coordinate given in the third column of plus strand reads and the second column for minus strand reads. In this step, the active site of transcription (single nt) will be placed both to the second and the third column.c. cat tempPL_3p.bed tempMN_3p.bed | tr ‘ ‘ ‘\t‘ > temp_3p.bed sortBed -i temp_3p.bed > PROseq_K562_hg38_3pnt.bed rm ∗temp∗The reads from plus and minus strands are combined, the data is converted to tab-delimited, and the reads sorted based on genomic coordinates. Intermediary files are removed.Generate a bed file that only contains the 3′-nucleotide (active site of transcription) of each read B. In the14.Intersect the coordinates of nascent transcription with the coordinates of functional genomic regions.Note: To allocate each engaged Pol II complex only once, we use the -u option in the bedtools intersect command and sequentially allocate the coordinates of active transcription to the distinct genomic categories. In each round, two different files are generated: File 1 retains active sites that localize to the given functional category (options -u and -wa). File 2 reports the active sites that do not localize to the given functional category (controlled with option -v). The file 2 will be used in the subsequent round to ensure that each engaged Pol II is allocated only to one genomic region. The order of the intersections is: i) promoter-proximal regions, ii) sites of divergent transcription, iii) enhancers, iv) CPSs, v) gene bodies, and vi) termination windows. In this order, promoter-associated Pol II molecules are not counted into enhancer transcription. Furthermore, transcription at intragenic enhancers is allocated to enhancers instead of gene bodies. Finally, termination windows can be relatively short or extend over several kilobases  are allocated to distinct functional categories.Timing: 10 minThe code in step 15 calculates engaged Pol II molecules in each category of functional genomic regions . Engaged Pol II that does not occur in any of the categories is indicated as unannotated. Step 15 further analyses the distribution of engaged Pol II across the functional genomic regions  in the dataset. Here, we only have a single sample and, therefore, focus on the distribution (proportions) of active sites across the genomic regions. With PRO-seq data, a normalization factor that accounts for differences in data handling and sequencing depth can be computed. Detailed description of normalization factors is out of the scope of this study. In brief, invariant whole-genome spike-in from a distinct organism can be added to all samples before the run-on reaction. This equal amount of foreign chromatin provides a count of nascent transcription against which the samples can be normalized . If desired, the color-code for each category of functional genomic regions can be adjusted here by changing the rgb values.awk -F ‘\t’ -v OFS=‘\t’ ‘{ $(NF+1) ="243,132,0"; print }’ ppPolCounts.tmp > ppPolCounts.bedawk -F ‘\t’ -v OFS=‘\t’ ‘{ $(NF+1) ="178,59,212"; print }’ ppDivCounts.tmp > ppDivCounts.bedawk -F ‘\t’ -v OFS=‘\t’ ‘{ $(NF+1) ="115,212,122"; print }’ enhancerCounts.tmp > enhancerCounts.bedawk -F ‘\t’ -v OFS=‘\t’ ‘{ $(NF+1) ="0,0,0"; print }’ geneBodyCounts.tmp > geneBodyCounts.bedawk -F ‘\t’ -v OFS=‘\t’ ‘{ $(NF+1) ="103,200,249"; print }’ CPSCounts.tmp > CPSCounts.bedawk -F ‘\t’ -v OFS=‘\t’ ‘{ $(NF+1) ="255,54,98"; print }’ TerminationWinCounts.tmp > TerminationWinCounts.bed18.Combine the files. Add an extra column "." to obtain a genome browser compatible bed file for visualization.cat ppPolCounts.bed ppDivCounts.bed enhancerCounts.bed geneBodyCounts.bed CPSCounts.bed TerminationWinCounts.bed > catRegions.tempawk -F ‘\t’ -v OFS=‘\t’ ‘{ $(NF+1) ="."; print }’ catRegions.temp > catRegions2.temp19.Reorganize the columns and add a header track.awk ‘{print $1 "\t" $2 "\t" $3 "\t" $7 "\t" $5 "\t" $6 "\t" $2 "\t" $3 "\t" $8}’ catRegions2.temp > catRegions3.tempawk ‘!seen++’ catRegions3.temp | sortBed > catRegions4.temptouch headerLine.txtecho track name="functional_genomic_regions" itemRgb="On" >> headerLine.txtcat headerLine.txt catRegions4.temp > functionalGenomicRegions.bedrm ∗.temprm headerLine.txtNote: As mentioned above, the number of engaged Pol II complexes at the distinct genomic regions generated in this protocol originates from raw read counts of the data. This count depends on the sequencing depth. To get a normalized count of engaged Pol II, the column 4 (reporting raw count) in the ’functionalGenomicregions.bed’ file can be multiplied with a normalization factor.The generated ’functionalGenomicregions.bed’ file can be read in genome browsers to show the identified functional genomic regions as well as the count of engaged Pol II at each indicated region . As starting material, please use a file that reports the summit coordinate of each peak, named with '_summits.bed', for example: K562_TBP_summits.bed, K562_GATA1_summits.bed, K562_CTCF_summits.bed, K562_H3K36me3_summits.bed .Obtain or generate datasets of interest. Place them in the folder of your working directory. Here, we used TBP, GATA1, CTCF, H3K36me3, NELFe, p300 and RAD21 ChIP-seq data . We remab.for x in the code below. In the loop, the ${x} will be replaced with the factor name, one listed factor after another.The peak summits for each given chromatin-associated factor are intersected with the distinct genomic regions. The strategy described in step 14 is used to ensure that each identified enrichment of a factor at the genome (peak) is counted once. For efficiency, we use a loop function that takes one bed file of mapped peak summits at a time. To define which datasets are analyzed in the loop function, please place names of factors in quotation marks, separated by a space, after the c.Run the code below using the factors of your choice. Please, ensure that the files are placed in the correct folder (working directory) and that the file names correspond to the names in the code. The files listing the coordinates of functional genomic regions were generated in steps 1–12.Count genome-associating factors at distinct functional genomic regions.for x in "TBP" "GATA1" "CTCF" "H3K36me3"do## Factor-derived reads at promoter-proximal regionsbedtools intersect -u -wa -a K562_${x}_summits.bed -b ppPolII.txt > ${x}_K562_ppPolII.bedbedtools intersect -v -a K562_${x}_summits.bed -b ppPolII.txt > ${x}_ppRemoved.bed## Factor-derived reads at the sites of divergent transcriptionbedtools intersect -u -wa -a ${x}_ppRemoved.bed -b divTx.txt > ${x}_K562_ppDiv.bedbedtools intersect -v -a ${x}_ppRemoved.bed -b divTx.txt > ${x}_ppdivRemoved.bed## Factor-derived reads at enhancersbedtools intersect -u -wa -a ${x}_ppdivRemoved.bed -b enhancers.bed > ${x}_K562_enhancers.bedbedtools intersect -v -a ${x}_ppdivRemoved.bed -b enhancers.bed > ${x}_ppdivEnhRemoved.bed## Factor-derived reads at CPSbedtools intersect -u -wa -a ${x}_ppdivEnhRemoved.bed -b CPS.txt > ${x}_K562_CPS.bedbedtools intersect -v -a ${x}_ppdivEnhRemoved.bed -b CPS.txt > ${x}_ppdivEnhCPSRemoved.bed## Factor-derived reads at GBbedtools intersect -u -wa -a ${x}_ppdivEnhCPSRemoved.bed -b geneBody.txt > ${x}_K562_GB.bedbedtools intersect -v -a ${x}_ppdivEnhCPSRemoved.bed -b geneBody.txt > ${x}_ppdivEnhCPSgbRemoved.bed## Factor-derived reads at termination windowsbedtools intersect -u -wa -a ${x}_ppdivEnhCPSgbRemoved.bed -b TW.txt > ${x}_K562_TW.bedbedtools intersect -v -a ${x}_ppdivEnhCPSgbRemoved.bed -b TW.txt > ${x}_K562_noGene_noEnh.bedrm ∗Removed.beddone21.a.script Factor_counts_at_functional_regions.txtInitiate the script that collects factor counts at the functional genomic regions.b.Plot the counts of rows in each intersected bed file.c.control + D in the terminal window.Terminate the log script by pressing Plot the counts of chromatin-associated factors at distinct categories of functional regions.22.The file ‘Factor_peaks_at_functional_regions.txt’ reports the number of ChIP-seq peaks at each functional category. ined see E and 4C.functional_genomic_regions.bed file, each block represents the coordinates of an individual functional genomic region. The block color codes for the category of the region . In UBET2 and PPP1R12B genes are shown, and two intergenic enhancer candidates identified on the longer isoform of PPP1R12B. Furthermore, the protocol counts engaged Pol II complexes that localize to each identified functional genomic region. The raw count of active sites of transcription is given in column 4 of the functional_genomic_regions.bed file, appearing above the color-coded block when visualized in a genome browser (HBE1 gene to the region’s upstream locus control element (LCR). In PRO-seq used here :https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"/bin/bash -c "$. Likewise, the names of the files in the scripts should be updated to match the user-specific input files.Please find the code as shell and R script files in the GitHub repository viher@kth.se).Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Anniina Vihervaara (This study did not generate new unique reagents.


Escherichia coli (EHEC) isolates of serotype O157:H7 are serious foodborne zoonotic pathogens and prime targets for biocontrol using bacteriophages. We report on the complete genome sequences of 11 novel lytic bacteriophages, representing three viral genera, isolated from cattle in Hungary that target E. coli O157 strains.Enterohemorrhagic  Escherichia coli (EHEC) isolates of serotype O157:H7 are serious foodborne zoonotic pathogens and prime targets for biocontrol using bacteriophages. We report on the complete genome sequences of 11 novel lytic bacteriophages, representing three viral genera, isolated from cattle in Hungary that target E. coli O157 strains.Enterohemorrhagic  Escherichia coli (EHEC) strains, particularly of the O157:H7 serotype, are serious foodborne zoonotic pathogens, and several phages which show effective lysis of these have previously been characterized , and atypical pathotypes isolated earlier in Hungary, as well , FastQ Screen (https://www.bioinformatics.babraham.ac.uk/projects/fastq_screen), and Trimmomatic , genome sizes of 166,440 and 166,441 bp, respectively, and a GC content of 35.4%. Phages vb_EcoM_bov10K2, vb_EcoM_bov11CS3, vb_EcoM_bov22_2, and vb_EcoM_bov25_3 are rV5-like phages belonging to the Vequintavirus genus of the Vequintavirinae subfamily, having a >96% nucleotide identity to the type phage rV5 (DQ832317.1). Their genome sizes were between 135,960 and 135,961 bp, with a 43.7% GC content. Phages vb_EcoS_bov11C2, vb_EcoS_bov15_1, vb_EcoS_bov16_1, vb_EcoS_bov22_1, and vb_EcoS_bov25_1D represent HK578-like phages, officially the Dhillonvirus genus from the Siphoviridae family, with 86% genome coverage and >90% nucleotide identity to phage HK578 (JQ086375.1). Their genome sizes were between 44,612 and 44,747 bp, and their GC content was 54.5%.Phages vb_EcoM_bov9_1 and vb_EcoM_bov10K1 proved to be T4-like phages, representing the Phages within the same genus were very uniform. The T4-like phages differed in only a 1-bp gap. Of the rV5-like phages, vb_EcoM_bov10K2, vb_EcoM_bov11CS3, and vb_EcoM_bov25_3 were 100% identical except for a 1-bp gap, while vb_EcoM_bov22_2 differed from them in only 2 single nucleotide polymorphisms (SNPs). The dhillonviruses differed at most by 11 SNPs, with a gap of 30 or 89 bp. The genome of vb_EcoS_bov22_1 was assembled as a partial genome sequence, with a different start position compared to the other dhillonviruses.MT884006 through MT884015 and MT951623.The nucleotide sequences of the phages are deposited in GenBank under the accession numbers