abstract: Magnetic resonance spectroscopy offers a broad range of noninvasive analytical methods for investigating metabolism in vivo. Of these, the magnetization-transfer (MT) techniques permit the estimation of the unidirectional fluxes associated with metabolic exchange reactions. Phosphorus (^31^P) MT measurements can be used to examine the bioenergetic reactions of the creatine-kinase system and the ATP synthesis/hydrolysis cycle. Observations from our group and others suggest that the inorganic phosphate (P~i~) → ATP flux in skeletal muscle may be modulated by certain conditions, including aging, insulin resistance, and diabetes, and may reflect inherent alterations in mitochondrial metabolism. However, such effects on the P~i~ → ATP flux are not universally observed under conditions in which mitochondrial function, assessed by other techniques, is impaired, and recent articles have raised concerns about the absolute magnitude of the measured reaction rates. As the application of ^31^P-MT techniques becomes more widespread, this article reviews the methodology and outlines our experience with its implementation in a variety of models in vivo. Also discussed are potential limitations of the technique, complementary methods for assessing oxidative metabolism, and whether the P~i~ → ATP flux is a viable biomarker of metabolic function in vivo*.*
author: Douglas E. Befroy; Douglas L. Rothman; Kitt Falk Petersen; Gerald I. ShulmanCorresponding author: Douglas E. Befroy, <firstname.lastname@example.com>.
date: 2012-11
references:
title: ^31^P-Magnetization Transfer Magnetic Resonance Spectroscopy Measurements of In Vivo Metabolism

Because of its versatility, magnetic resonance spectroscopy (MRS) has emerged as a powerful modality for studying tissue-specific intracellular metabolism in vivo. Several metabolically relevant nuclei, including hydrogen (^1^H), carbon (^13^C), and phosphorus (^31^P), are magnetic resonance (MR)-visible, permitting the detection of a range of metabolites in a variety of tissues. The noninvasive nature of the technique allows repeated measurements from the same location, so that the response to an acute intervention (e.g., exercise, insulin stimulation) or longer-term treatment (e.g., diet manipulation, drug therapy) can be assessed. Using more sophisticated MRS techniques, discrete reaction rates can also be estimated using ^13^C-MRS to monitor the metabolic fate of ^13^C-labeled substrates or by using magnetization-transfer (MT) techniques to monitor the unidirectional fluxes associated with metabolic exchange reactions. Of these, ^31^P-MT methods offer the ability to examine the key bioenergetic reactions of the creatine kinase (CK) equilibrium (ATP ⇆ phosphocreatine \[PCr\] exchange) and the ATP synthesis/hydrolysis cycle (ATP ⇆ inorganic phosphate \[P~i~\] exchange). Particular interest has been generated by the observations from our group and others that unidirectional P~i~ → ATP flux in muscle may be modulated in certain disease states, including insulin resistance and diabetes, that may reflect alterations in mitochondrial metabolism. However, disparate results have been reported by different groups, and recent articles have raised concerns about the absolute magnitude of the measured reaction rates. Given that many clinical MR scanners now have the capability of performing ^31^P-MT experiments and the implementation of the method is becoming more widespread, we would like to offer our perspective on the application of the technique in vivo. In this article, we review our experience using the ^31^P-MT technique to measure P~i~ → ATP flux in a variety of models, describe limitations of the methodology, assess alternative and complementary methods of estimating cellular bioenergetics, and discuss the validity of using the technique as a biomarker of metabolic function in vivo.

# THE MT TECHNIQUE

The MT techniques work on the principle that if the MR signal of an exchanging metabolite is perturbed, the transfer of this effect to its exchange partner can be detected, while leaving the underlying chemical equilibrium unaffected. The perturbation may either eliminate (saturate) or invert the signal of the initial metabolite of interest and is accomplished by applying a frequency-selective saturation or inversion pulse prior to acquiring the MR spectrum. These approaches give rise to the saturation-transfer (ST) and inversion-transfer techniques, respectively. For in vivo studies, the ST technique is typically used because of ease of calibration of an effective frequency-selective saturation pulse. On in vivo MR systems, particularly those used for human studies, the accurate, short-duration inversion pulses required for the inversion-transfer technique are difficult to implement due to inherent limitations in radiofrequency field homogeneity and the high-power requirements of such pulses. The ST effect from the terminal (γ) phosphate group of ATP to PCr due to the CK equilibrium and to P~i~ due to ATP synthesis/hydrolysis in skeletal muscle is shown in the ^31^P spectra in Fig. 1. The magnitude of the effect (e.g., ΔPCr or ΔP~i~) is proportional to the kinetics of exchange. Underlying assumptions for the application of the technique are that the metabolites of interest have distinct peaks in the MR spectrum, that exchange is at steady state (i.e., that the metabolite concentrations do not change during the experiment), and that exchange is rapid with respect to the lifetime of the MR signal.

The ATP synthesis/hydrolysis cycle is a phosphate-exchange reaction under the chemical equilibrium shown in Eq. 1, where *k*~f~ and *k*~r~ are the forward and reverse rate constants. From simple reaction kinetics, the forward reaction (P~i~ → ATP flux) rate is equivalent to the forward rate constant multiplied by the concentrations of ADP and P~i~ (Eq. 2). At steady state, the tissue concentration of ADP remains constant, and this relationship can be simplified to generate a pseudo–first-order rate constant of exchange for P~i~ (*k*′~f~) that incorporates the effects of the ADP concentration (Eq. 3). During the ST experiment (Fig. 1), γATP saturation causes a reduction in the observed P~i~ signal (M′) from its equilibrium value (M~0~) due to the effects of phosphate exchange (i.e., *k*′~f~) and the influence of the effective MR relaxation time (T~1~′) of P~i~ (Eq. 4).

Equation 4 requires that the following conditions are met: that there is full equilibration between the sites of ATP utilization (i.e., in the cytosol) and ATP production (mitochondria and cytosol); that across this system, ATP production ≡ utilization; that the saturation pulse fully nulls the γATP signal and has minimal off-resonance effects; and that the detected compartment (i.e., cytosolic P~i~) is fully MR-visible and not participating in competing reactions. A more detailed description of the effects of chemical exchange on the observed MR signal and the derivation of these equations is beyond the scope of this article but can be found in the classic articles describing MT from McConnell (1) and Forsen and Hoffman (2).

From a practical perspective, the estimation of P~i~ → ATP flux therefore requires the determination of three parameters: *1*) calculation of the ST effect (M′/M~0~) from γATP to P~i~; *2*) calibration of the T~1~ of P~i~ under conditions of γ-ATP saturation (T~1~′); and *3*) determination of the intracellular P~i~ concentration. The unidirectional (P~i~ → ATP) flux that contributes to the exchange can then be calculated according to Eq. 3. To ensure that a study is fully described, we recommend that all of these parameters are reported when publishing data acquired using the ^31^P-ST technique. Two experimental approaches are possible: in the progressive saturation experiment, M′ and T~1~′ are determined simultaneously by acquiring a series of spectra in which the duration of the saturation pulse is gradually lengthened, and the extent of the ST effect increases until steady state is achieved. Alternatively, M′ can be determined from a single spectrum in which the duration of the saturation pulse is sufficient (i.e., several times T~1~′) to establish the new steady-state MR equilibrium, with T~1~′ determined by a separate experiment. An inversion-recovery calibration with γATP saturation during the repetition time (T~R~) and throughout the inversion delay will typically be performed to estimate T~1~′. The intracellular concentration of P~i~ can be determined from a fully relaxed ^31^P spectrum (where T~R~ \>\> T~1~, and all metabolites are detected with equal sensitivity) with reference to ATP as an internal standard. Imperfections in the frequency specificity of the saturation pulse can lead to off-resonance effects modulating the intensity of the peak of interest. Therefore, M~0~ is usually determined under control saturation conditions with the saturation pulse irradiating a downfield frequency from P~i~ that mirrors the separation between the γATP and P~i~ peaks. These effects can be significant, particularly at lower MR field strengths in which the frequency separation between the exchanging metabolites is relatively small (3,4). The performance and off-resonance effects of a saturation pulse are also influenced by its duration and therefore may not be consistent between the variable saturation pulse lengths of the progressive saturation experiment. We have found that this tends to lead to an underestimate of T~1~′ and prefer the steady-state style experiment, in which pulse performance is equivalent among all scans.

# PRACTICAL CONSIDERATIONS FOR THE IMPLEMENTATION OF ^31^P-ST IN VIVO

Because rates of P~i~ → ATP flux determined using the ^31^P-ST experiment incorporate the measurement of three independent parameters (M′/M~0,~ T~1~′, and \[P~i~\]), it is important to estimate these parameters as accurately as possible. High signal/noise ^31^P spectra are required, particularly for the determination of M′/M~0~, in which a relatively small decrement (∼20%) in the magnitude of the P~i~ resonance, present in relatively low concentration (∼2 mmol/L) compared with the other ^31^P metabolites, is detected. Therefore, a stable experimental setup is required that minimizes or eliminates movement of the region of interest. Inadvertent contractions may perturb the maintenance of metabolic steady state in muscle and should be prevented. For animal experiments, these conditions are best satisfied by performing the ST experiment under light anesthesia. To ensure precision in the estimate of M′/ M~0~ in our studies, we repeat the measurement multiple times to confirm experimental stability.

The duration of the experiment will be dependent on the tissue of interest, species, and field strength of the MR system used. Our ^31^P-ST experiments in human muscle take ∼60 min on a 4 Tesla system, whereas 4–6 h are required for an ST experiment in mouse hindlimb at 9.4 Tesla due to the relatively small mass of muscle tissue available. The overall length of the ST experiment is dominated by the estimation of T~1~′, which requires the acquisition of several spectra to characterize the evolution of the MR signal. This calibration can be shortened by obtaining fewer points, although this will also decrease the accuracy of the calibration. Faster methods are available that allow the estimation of T~1~ by varying the extent to which the MR signal is excited (variable flip-angle methods) (5); however, the implementation of these methods in vivo can be problematic because very accurate excitation pulses are required for precise estimation of the T~1~ relaxation time.

# BIOLOGICAL APPLICATIONS OF ^31^P-ST TO MEASURE P~i~ → ATP FLUX

The biological feasibility of using the ST technique to assess P~i~ → ATP flux was initially demonstrated in cell suspensions of *Escherichia coli* (6). Subsequent experiments in yeast cell suspensions (7) and implementation of the technique in the isolated perfused heart (8,9) and perfused liver (10) preparations demonstrated the applicability of the technique in a variety of in vitro systems. Translation of the methodology to in vivo applications was first performed in rat brain (11) followed by studies in the exercising rat hindlimb in vivo (12) and semi-invasive studies of dog (13) and lamb heart (14). We sought to add in vivo estimates of P~i~ → ATP flux by ^31^P-ST to complement ^13^C-MRS methods we were developing to assess rates of substrate oxidation via the tricarboxylic acid cycle (TCA cycle flux) in resting skeletal muscle. We initially performed proof-of-principle studies in rat hindlimb (15,16) followed by studies in human muscle to validate the methods (17) and examine how these metabolic fluxes were modulated by aging (18), insulin resistance (19,20), and endurance exercise training (21). We have also taken advantage of transgenic mouse models to examine how overt genetic modulations of mitochondrial content (22) and metabolism may influence the flux measured by the ^31^P-ST technique (23; D.E.B. and G.I.S., unpublished observations). More recently, there has been a rapid expansion in the number of studies using the ^31^P-ST technique in vivo, with applications examining the effects of insulin stimulation (24,25), insulin resistance (26–28), diabetes (29,30), MELAS (mitochondrial encephalopathy, lactic acidosis, and stroke-like episodes) syndrome (31), and acromegaly (32) on resting muscle P~i~ → ATP flux. Pilot studies have been reported in human liver (33,34), and validation experiments have been performed in human (35,36) and rat (37) brain.

# LIMITATIONS OF THE ^31^P-ST TECHNIQUE

The early studies examining the applications of the ^31^P-ST technique in vitro observed that under certain conditions, the measured P~i~ → ATP flux was significantly greater than that predicted from oxygen consumption measurements, assuming the theoretical phosphate-to-oxygen (P:O) ratio for mitochondrial oxidative phosphorylation of ∼3. This phenomenon was demonstrated not only in yeast (7,38) but also in isolated perfused heart (39) and liver (10). The study by Alger et al. (7) noted that an appreciable P~i~ → ATP flux could be detected in yeast under anaerobic conditions that was insensitive to the mitochondrial inhibitor oligomycin, suggesting that ATP synthesis via glycolysis was also detected by ^31^P-ST and may augment the flux observed under aerobic conditions. Studies using glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and phosphoglycerate kinase (PGK) in solution at concentrations and conditions designed to mimic those found in the Langendorff perfused heart confirmed that these enzymes could catalyze a significant P~i~ → ATP flux (40). Subsequent experiments using iodoacetate to inhibit ATP generation via the GAPDH/PGK enzyme couple demonstrated that these enzymes were contributing significantly to the measured P~i~ → ATP flux rates in these systems (10,38,39) potentially via catalyzing P~i~ ⇆ ATP exchange. With the GAPDH/PGK contribution eliminated, the apparent P:O ratio was normalized to ∼2 to 3, below the theoretical limit (38,39). It has also been demonstrated using radiolabeled phosphate that near equilibrium P~i~ ⇆ ATP exchange can occur within isolated mitochondria at low respiration rates (41), either at the level of the ATP synthase complex or the adenine-nucleotide translocase (ANT). At higher respiration rates, the reverse flux (ATP → P~i~) was significantly decreased, leading to a switch from reversible P~i~ ⇆ ATP exchange to unidirectional ATP production by the mitochondrion. This observation is consistent with the normalization of P:O at higher workloads in heart (14,39) and exercising rat muscle in vivo (12). Overexpression of the F~1~F~0~ ATP synthase in *E. coli* had no effect on the P~i~ → ATP flux measured by ^31^P-ST (42) under aerobic conditions. In contrast, overexpression of the ANT in yeast oxidizing glucose led to a significant increase in P~i~ → ATP flux (43), indicating a role for the ANT in catalyzing P~i~ ⇆ ATP exchange.

# INFLUENCE OF NEAR-EQUILIBRIUM P~i~ ⇆ ATP EXCHANGE ON IN VIVO STUDIES USING ^31^P-ST

Recent articles have expressed concern over the contribution of unidentified P~i~ ⇆ ATP exchange mechanisms to absolute rates of P~i~ → ATP flux measured in vivo using ^31^P-ST, highlighting the discrepancy between estimated P:O ratios and querying whether this unidirectional flux reflects mitochondrial activity (44–46). In addition to putative contributions from exchange via GAPDH/PGK (45) and at the mitochondrion, Balaban and Koretsky (46) suggest that small metabolite pools, undetectable in the ^31^P-MR spectrum due to their low concentration, could be irradiated during the ST experiment, undergo exchange with P~i~, and contribute to the observed MT effect. These concerns are certainly valid in terms of deconvoluting the specific mechanisms that contribute to the P~i~ → ATP flux and quantifying absolute rates of net (i.e., forward flux minus reverse flux) mitochondrial ATP synthesis.

When considering the extent to which glycolytic ATP production or GAPDH/PGK exchange may contribute to the observed rates of P~i~ → ATP flux measured by the ^31^P-ST experiment in vivo, it is worth noting that observations from these in vitro studies may not translate directly to those in an intact organisms due to several factors. Firstly, absolute rates of P~i~ → ATP flux measured in vitro in both cell preparations and isolated organs are significantly higher than those measured in vivo (Table 1). These in vitro systems are often studied under conditions in which glucose is the sole or primary substrate, which may enhance the contribution of glycolytic metabolism to the measured P~i~ → ATP flux and play a role in the erroneously high P:O ratios observed in these preparations. Furthermore, there are substantial differences in the expression of glycolytic enzymes between tissues and different species. The expression/activity levels for PGK, which exhibits a high flux control coefficient for ATP ⇆ P~i~ exchange (47), can vary by an order of magnitude among human tissues and between the same tissue in humans and rodents (Table 2). Resting skeletal muscle, for example, derives most of its energy from fat oxidation rather than glycolysis, and this is reflected in the relative PGK activity where heart ≈ brain \>\> liver \> muscle. PGK activity in most human tissues is significantly lower than in the counterpart tissue in rats and substantially lower than that in mice, reflecting the greater reliance on glycolytic metabolism in rodents. In brain, despite the high PGK activity and significant role for glycolysis, close to theoretical P:O ratios have been reported (35,37). The extrapolation of metabolic mechanisms between in vitro and in vivo preparations, from one tissue to another or between different species, is therefore not straightforward, and we urge caution when interpreting the ramifications of an observation in a particular preparation.

Absolute P~i~ → ATP flux rates reported in the literature for different in vitro and in vivo preparations

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Protein expression/activity (arbitrary units) of PGK1 isoform between different tissues and species

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In the following section, we will describe our experiences with the ^31^P-ST technique in a variety of systems, which along with studies from other laboratories, support the notion that P~i~ → ATP flux responds to perturbations in oxidative metabolism and, when supported by complementary methods, can be used as a biomarker of in vivo mitochondrial activity. Detailed descriptions of the experimental procedures we have used can be found in the cited literature. It is worth noting that although different MR systems were used, we implemented comparable ^31^P-ST protocols for all of our human and rodent studies. Saturation-pulse lengths, sequence repetition times, and the delays for the inversion-recovery calibration were optimized according to the inherent T~1~′ of P~i~ on each MR system, and appropriate coil geometries were chosen for the region of interest.

The most compelling evidence we have obtained that demonstrates that the P~i~ → ATP flux measured by ^31^P-ST responds to perturbations in skeletal muscle oxidative function is from transgenic mouse models with direct manipulation of genes that modulate mitochondrial content and metabolism. Mice with muscle-specific overexpression of peroxisome proliferator–activated receptor γ (PPARγ) coactivator 1α (PGC1α), a regulator of oxidative metabolism, exhibit increased mitochondrial density and enhanced expression and protein content of genes involved in oxidative phosphorylation. P~i~ → ATP flux in the muscle of these mice was increased ∼40% (Fig. 2), and a concomitant increase in fatty-acid oxidation was detected in isolated soleus muscle strips (22). It is interesting to note that short-term (3 weeks) high-fat feeding enhanced muscle P~i~ → ATP flux in both wild-type and PGC1α overexpressing mice (22) (Fig. 3). This phenomenon is supported by data obtained from rats fed a high-fat diet for 2.5 weeks in which the in vivo oxidative capacity of muscle (assessed using the ^31^P-MRS PCr recovery method) was increased as well as mitochondrial DNA content and the oxidative capacity of isolated mitochondria (48), presumably to increase the ability to oxidize the excess of available lipid. Significantly, this enhancement in mitochondrial capacity had dissipated after 25 weeks of high-fat feeding, despite a sustained elevation in mitochondrial DNA, which corresponds with the decreased muscle P~i~ → ATP flux observed in rats fed a high-fat diet for longer (10-week) duration (49). Uncoupling protein 3 (UCP3) is a mitochondrial membrane protein found in skeletal muscle that has high homology with UCP1, which is found in brown adipose tissue and mediates thermogenesis by dissipating the H^+^ electrochemical gradient across the inner mitochondrial membrane. We observed that in vivo skeletal muscle P~i~ → ATP flux was increased in UCP3 knockout mice (23); conversely, muscle-specific overexpression of UCP3 led to a decreased flux (D.E.B. and G.I.S., unpublished observations) \[Fig. 2, data were acquired using the same MR protocols as described in Choi et al. (22)\]. These observations are supported by in vitro data. The ATP/ADP ratio was increased in mitochondria isolated from the muscle of UCP3-knockout mice, and State III (ADP-stimulated) respiration rates were increased (50). Palmitate and pyruvate oxidation have been observed to be elevated in soleus muscle strips isolated from UCP3 overexpressing mice (51) accompanied by an increased in State IV (nonstimulated) respiration rates in mitochondria (52) and whole-body energy expenditure (53).

To more fully characterize mitochondrial oxidative function in skeletal muscle in vivo, we use estimates of P~i~ → ATP flux assessed by ^31^P-ST in conjunction with direct measurements of substrate oxidation via the TCA cycle using dynamic ^13^C-MRS. A thorough analysis of this technique is beyond the scope of this article and can be found in the literature (20,54), but a brief description is warranted. Rates of TCA cycle flux in muscle can be estimated by infusing ^13^C-labeled acetate and using ^13^C-MRS to monitor ^13^C-label incorporation into the muscle glutamate pool, which acts as a surrogate for the intermediates of the TCA cycle. Kinetic analysis of the time courses of ^13^C glutamate enrichment can be accomplished using computer-modeling techniques to fit the data to a metabolic model of the TCA cycle, and rates of acetate oxidation and total TCA cycle flux can be estimated. These studies use pharmacy-prepared, sterile infusates of acetate, a naturally occurring endogenous substrate, that have been positionally enriched with the MR-visible stable isotope of carbon (^13^C). Concentrations of plasma acetate during the infusion remain relatively low (∼1 mmol/L) to avoid mass action effects of the substrate that could otherwise influence metabolism. As such, these studies can be accomplished under conditions that minimize the perturbation of resting muscle metabolism, are minimally invasive, and very safe.

We found that both P~i~ → ATP flux, measured by ^31^P-ST, and TCA cycle flux, measured by ^13^C-MRS, were both reduced by ∼40% in the calf muscles of healthy, lean, elderly individuals (∼70 years of age) with respect to healthy, young (∼27 years), control subjects who were matched for BMI and physical activity (Fig. 4) (18). Similarly, using the same ^13^C- and ^31^P-MRS methods, both TCA cycle and P~i~ → ATP flux were reduced by ∼30% in healthy, young, lean, insulin-resistant (IR) offspring of type 2 diabetic patients (IR offspring) compared with age-BMI-activity–matched insulin-sensitive (IS) control subjects (IS subjects) (19,20) (Fig. 5). In vitro analysis of muscle biopsy samples from a similar cohort of IR offspring (55) revealed a comparable ∼35% reduction in mitochondrial density, as assessed by electron microscopy, as well as decreased content of proteins associated with oxidative phosphorylation (cytochrome *c* oxidase-1, succinate dehydrogenase, and pyruvate dehydrogenase) compared with matched IS subjects. This reduction in mitochondrial content and function in the young, lean IR offspring was consistent with a reduction in the ratio of slow-twitch (oxidative) muscle fibers to fast-twitch (glycolytic) fibers (19).

We have also examined muscle-specific P~i~ → ATP flux in different muscle groups of the calf using a localized version of the ^31^P-ST method to restrict the measurement to either the gastrocnemius or soleus muscle compartments (Fig. 6). Muscle-specific P~i~ → ATP flux, measured in healthy volunteers, was significantly faster in the soleus muscle compared with the gastrocnemius (*V*~Pi\ →\ ATP~ = 8.12 ± 0.86 vs. 4.97 ± 1.08 mmol/g/min) (56). This disparity in P~i~ → ATP flux is consistent with the differences in mitochondrial number, oxidative enzyme content, and oxygen consumption expected for the more oxidative phenotype of the soleus than the gastrocnemius (57–61).

We have used the combination of ^31^P-ST assessment of P~i~ → ATP flux and ^13^C-MRS measurement of TCA cycle flux to noninvasively assess energetic efficiency in skeletal muscle in both humans and rodents (16,17). Mitochondrial uncoupling stimulated by acute 2,4-dinitrophenol (DNP) or chronic thyroid hormone (T3) administration are known to lead to an increase in oxygen consumption (16,62–66). Consistent with this mechanism of action, DNP and T3 treatment in rats caused substantial increases in muscle TCA cycle flux, yet the P~i~ → ATP flux was unaffected, reflecting decreased mitochondrial efficiency (16). This observation was supported by a lack of effect of either T3 or DNP on the ATPase activity of isolated mitochondria or any detectable differences in muscle GAPDH/PGK exchange rates assessed by the deuterated glucose technique. Similar decreases in mitochondrial energetic efficiency using the same in vivo ^13^C-/^31^P-MRS methods have also been observed in human skeletal muscle in response to T3 treatment (17).

These data indicate that rates of resting muscle P~i~ → ATP flux and substrate oxidation via the TCA cycle determined using ^31^P- and ^13^C-MRS techniques appear to track qualitatively with modulations in mitochondrial content and the extent of mitochondrial uncoupling. Assuming that three molecules of O~2~ are ultimately consumed per C~2~ unit oxidized by the TCA cycle and that the P:O ratio is ∼3 (these approximations hold whether the substrate source is fatty acids or glucose), rates of muscle P~i~ → ATP flux are estimated to be ∼1.6 μmol/g/min. Therefore, absolute rates of ATP production measured using the ^31^P-ST technique (∼7.5 μmol/g/min) are still significantly higher than those calculated from TCA cycle activity. It is worth noting that this discrepancy in ATP production (∼4.7-fold) is far lower than that estimated from measurements of oxygen consumption by arterio/venous (A/V) difference, near infrared spectroscopy (NIRS), and ^15^O~2~ positron emission tomography (44). This is because rates of oxygen consumption calculated from TCA cycle flux data (∼0.29 μmol(O~2~)/g/min) exceed those calculated by NIRS and positron emission tomography by 3–10-fold and are at the upper limit of literature values reported using A/V difference methods. We believe that phenotypic differences in the muscle group(s) examined using the different techniques contribute, in part, to these discrepancies in rates of O~2~ consumption and may be exacerbated by experimental considerations for each method. For example, A/V difference methods tend to sample blood-oxygen concentration across an entire limb in which other tissues may contribute to the measured O~2~ consumption. Accurate estimates of muscle mass/volume are also required to determination rates of O~2~ utilization. NIRS techniques sample from a relatively superficial region of interest that may not exhibit comparable rates of O~2~ consumption to the bulk of the tissue. We feel that the most relevant methodological comparison is between the TCA cycle flux and ^31^P-ST because both ^13^C and ^31^P data were acquired from comparable regions of interest in the calf muscles. As discussed above, we believe that the disparity in absolute rates of ATP production estimated by these methods in resting muscle is likely because of near equilibrium P~i~ ⇆ ATP exchange at the level of the mitochondria, with only a minor contribution from exchange catalyzed by GAPDH/PGK.

Data from other groups also support the notion that in vivo estimates of P~i~ → ATP flux correlate with tissue oxidative metabolism. Brindle et al. (12) examined the effects of electrically stimulated contractions on rat muscle using ^31^P-ST and observed a linear response of P~i~ → ATP flux to increases in muscle workload. An earlier study in perfused muscle established that muscle oxygen consumption is also proportional to workload (67). Comparing the data from these studies, despite P~i~ ⇆ ATP exchange contributing to the measured unidirectional P~i~ → ATP flux at rest and leading to an overestimation in the P:O ratio in quiescent muscle, at higher workloads the P:O ratio trended toward the theoretical value. Although the increases in P~i~ → ATP flux and oxygen consumption due to muscle contraction were not directly proportional, the ^31^P-ST measurement appeared to track oxygen utilization and therefore respond to increases in mitochondrial activity. In the rat brain, by modulating the depth of anesthesia, P~i~ → ATP flux was found to be tightly correlated with the cerebral activity level and the extent of energy demand (37). Similarly, rates of P~i~ → ATP flux measured in the human visual cortex (35) and monkey brain (68) agree well with predicted values calculated from cerebral metabolic rates of glucose or oxygen consumption or from MRS measurements of TCA cycle flux.

# METABOLIC IMPLICATIONS OF DIFFERENCES IN RESTING MUSCLE P~i~ → ATP FLUX

In contracting muscle, numerous studies have demonstrated that mitochondrial ATP production is likely to be demand-driven and regulated through substrate-level feedback via ADP and P~i~, both of which increase in response to contractile activity. The factors that regulate mitochondrial activity in resting muscle in vivo are less clear, in which any underlying metabolic perturbations are likely to be more subtle (and therefore difficult to detect experimentally). In this section, we discuss the metabolic implications that stem from our observations of reduced rates of basal P~i~ → ATP flux in the muscle of elderly individuals and IR offspring.

Under basal conditions, protein synthesis and the maintenance of ion homeostasis are likely to be the major cellular processes that consume ATP. There is evidence to suggest that rates of protein synthesis are decreased in the muscle of elderly subjects (69,70) and that pH and ion homeostasis may be disrupted (71,72). Although blunted increases in protein synthesis in response to insulin stimulation have been reported in individuals with type 2 diabetes (73), basal rates of muscle protein synthesis appear to be unaffected (74). Decreased content and activity of the Na^+^/K^+^-ATPase, a transmembrane ion pump that maintains the cellular membrane homeostasis, has been reported in type 2 diabetic patients (75), obese IR individuals (76), and in response to high-fat feeding (77). The activity of this protein may contribute significantly to basal energy requirements in muscle as well as other tissues (78). These observations match with the decreases in TCA cycle and ATP flux that we observe in the muscle of elderly and IR offspring; however, the implication of cause and effect is unclear. Although a mechanism of demand-driven regulation of resting ATP flux is plausible, it is also feasible that protein synthesis may have been downregulated and/or ion homeostasis disrupted due to the decreased availability of ATP.

Interestingly, under resting conditions in which intracellular concentrations of both ADP and P~i~ are low, it has been suggested that the cellular redox potential (i.e., availability of NADH) may also exert respiratory control (79,80). Our observations of decreased P~i~ → ATP flux in the muscle of elderly and IR individuals may be a result of the decreased TCA cycle activity, which reduces the availability of NADH for oxidation by the electron transport chain.

A recent study by Lim et al. (30) has suggested that the decreased rates of muscle ATP turnover observed in type 2 diabetic subjects may be due to reduced rates of glucose uptake and glycogen synthesis. We do not believe that such effects are likely to play a significant role in our studies of the elderly or IR offspring because glucose disposal in resting muscle under fasting conditions will be very low and of insufficient magnitude to exert an effect on oxidative rates.

# COMPARISON OF ^31^P-ST WITH OTHER METHODS FOR ESTIMATING IN VIVO MITOCHONDRIAL METABOLISM IN SKELETAL MUSCLE

As described above, we have implemented ^31^P-ST measurements of P~i~ → ATP flux in conjunction with ^13^C-MRS estimates of TCA cycle flux to assess muscle mitochondrial metabolism in vivo. Other groups have complemented their ^31^P-ST measurements with dynamic ^31^P-MRS to estimate muscle mitochondrial oxidative capacity from the kinetics of PCr repletion following a bout of exercise, a method that has been validated in humans and rat models (81). This functional estimate of oxidative capacity has been shown to correlate well with whole-body maximal oxygen consumption (*V*o~2max~) and estimates of mitochondrial capacity, enzyme expression/content and respiratory function of isolated mitochondria, determined in vitro using biopsy samples (82–85). Muscle oxidative capacity determined by PCr recovery has been demonstrated to be reduced in type 2 diabetic patients (86,87), although this finding is not universal (88,89). Interestingly, in a rat model of mitochondrial dysfunction, induced by chronic inhibition of complex 1 of the electron transport chain, hindlimb muscle oxidative capacity determined by PCr recovery was significantly decreased, whereas resting P~i~ → ATP flux was unaffected (90). Similarly, in human subjects with a genetic defect in insulin-receptor signaling, oxidative capacity of the vastus lateralis was decreased versus healthy controls, whereas resting P~i~ → ATP in the calf muscle was unchanged (26). However, it is unclear whether valid comparisons of the methods can be made in this study because each technique was performed in different muscle compartments where the metabolic phenotype is likely to differ significantly. The disagreement between findings with PCr recovery and ^31^P ST in these studies has been used to query the ST method and whether it reflects oxidative activity in skeletal muscle. However, an alternate interpretation, which we support, is that the two measurements assess different aspects of mitochondrial function: total muscle oxidative capacity versus resting energy production, that are not necessarily proportional due to intracellular regulation of mitochondrial function.

Although the PCr recovery method seems to provide an excellent estimate of functional mitochondrial/oxidative capacity, several factors concerning the effective application of the method should be considered for those unfamiliar with the technique. The kinetics of PCr repletion following exercise are usually characterized by fitting the recovery to a monoexponential and assuming the postexercise ATP generation is entirely oxidative (91). However, bi- or multiexponential behavior has been observed in response to high-intensity exercise. This response may be a consequence of tissue heterogeneity or differences in fiber recruitment during exercise, although a contribution of glycolytic ATP production has also been suggested (92,93). Intracellular acidification, typically encountered during high-intensity exercise protocols, appears to slow the rate of PCr recovery potentially due to direct effects on mitochondrial respiration (94,95), the use of ATP for H^+^ pumping to restore pH (84,96), or via modulating the CK equilibrium (97–99). The pH dependence of PCr recovery rates may also reflect selective recruitment of muscle fibers for low- versus high-intensity contractions (100).

The rate of muscle PCr depletion monitored by ^31^P-MRS during limb ischemia induced by circulatory occlusion has also been used as an estimate of resting ATP use. A comparison of the ^31^P-MRS methods has been performed in the calf muscles by Schmid et al. (101), who observed correlations among muscle P~i~ → ATP flux, the decline in PCr induced by cuff ischemia, and the time constant of PCr recovery (τ~PCr~) following exercise protocol during ischemia. The correlation among these parameters would seem to suggest that each reflects oxidative activity; however, we urge caution over the interpretation of these data due to methodological uncertainties in this study. Reservations include the lack of control over end-exercise pH, which, as described above, has been demonstrated to modulate the kinetics of PCr recovery, and the use of a plantar flexion exercise protocol in combination with a relatively large diameter coil for ^31^P signal detection. Plantar flexion involves preferential activation of the gastrocnemius muscle groups, which will exhibit enhanced PCr depletion compared with the soleus and influence the observed PCr recovery kinetics. In contrast, the region of interest for the P~i~ → ATP flux and ischemic PCr utilization measurements performed in resting muscle will correspond to a weighted average of the soleus and gastrocnemius muscle groups. The relative contribution of deeper lying muscle groups in this study will be particularly exacerbated by the relatively large-diameter coil (10 cm) used for ^31^P signal detection. The use of a smaller-diameter ^31^P coil would act as a rudimentary method of signal localization by confining signal detection to the superficial muscle groups and ensure that the sampled volume was equivalent for each ^31^P technique. Finally, we also have concerns over whether ischemic conditions are a valid metabolic environment in which to assess resting ATP turnover.

In vitro analyses of muscle biopsy samples may also offer additional insight into mitochondrial metabolism. Mitochondrial density, mitochondrial DNA copy number, the expression and content of mitochondrial proteins, as well as the respiratory function of isolated mitochondria or skinned muscle fibers provide a theoretical estimate of the maximal mitochondrial capacity and have been used as indirect markers of mitochondrial function. As mentioned above, the functional estimate of mitochondrial metabolism determined using the PCr recovery technique correlates with many of these theoretical estimates (82–85), reflecting that these methods are all biomarkers of mitochondrial capacity rather than resting or intermediate mitochondrial function. Taken together, these studies highlight that these techniques are likely measuring different aspects of mitochondrial metabolism, resting activity versus maximal capacity, and to more fully characterize the metabolic effects of an intervention or disease, multiple parameters of oxidative function, ideally a combination of resting function, maximal capacity, and the response to an intermediate metabolic demand, should be assessed.

Performing in vitro analyses of mitochondrial metabolism from muscle biopsy samples therefore enables an array of parameters to be assessed, and the experimental procedures involved are highly sensitive and can typically be accomplished in most laboratories. However, a number of caveats should be considered: the biopsy itself is an invasive measurement and is extracted from a small region of tissue that may not accurately represent the entire muscle. Repeated sampling, although feasible, will occur from slightly different regions of tissue that may not contain the same muscle fiber-type composition. The integrated network of metabolic processes that exist in vivo are no longer present, and assays usually provide an estimate of the theoretical maximal capacity without the limitations imposed by regulatory mechanisms, substrate availability, or product inhibition. Normalization of data can also be problematic because different internal reference standards (total protein content, total mitochondrial protein content, specific mitochondrial proteins) are often used. The MR methods described in this article offer the ability to estimate mitochondrial function in vivo, in which regulatory mechanisms remain intact and the same region of tissue can be sampled noninvasively and repeatedly, although this is obviously constrained by the availability of an MR system. The PCr recovery method is relatively straightforward to implement on many scanners and can yield estimates of functional muscle mitochondrial capacity, provided an appropriate contraction protocol is selected, particularly when studying populations that may have impaired muscle metabolism. The TCA cycle flux measurement using ^13^C-MRS to monitor the oxidation of ^13^C-labeled substrates is considerably more complex to implement and generally requires customized MR hardware/software as well as specialized metabolic modeling analyses. Additional constraints are provided by the length of the study (∼2 to 3 h within the scanner), which may be prohibitive for certain subjects, and the overall cost of the experiment due to the need for ^13^C-labeled substrates, extensive MR system time, and personnel. However, this method probably provides the most accurate estimate of resting mitochondrial activity in vivo.

# CONCLUSION

In conclusion, MT MRS techniques offer a unique ability to examine the unidirectional fluxes that contribute to metabolic exchange reactions. The P~i~ → ATP flux associated with the ATP synthesis/hydrolysis cycle is of particular interest because it is a key bioenergetic process supporting the energy demands of a tissue. Although the ^31^P-ST experiment measures all metabolic contributions to the P~i~ → ATP flux, including glycolytic ATP production and near-equilibrium exchange at the level of GAPDH/PGK and/or the mitochondrion, experiments in a variety of in vivo systems suggest that the flux does respond to perturbations in mitochondrial metabolism. Different experimental techniques to assess muscle metabolism in vivo (e.g. P~i~ → ATP flux by ^31^P-ST, oxidative capacity by PCr recovery using dynamic ^31^P-MRS, and substrate oxidation by dynamic ^13^C-MRS) likely assess different parameters of mitochondrial function. Therefore, to more fully characterize oxidative function in vivo, we recommend the use of complementary analytical techniques to obtain a multiparametric assessment of mitochondrial metabolism.

## ACKNOWLEDGMENTS

This work was supported by grants from the U.S. Public Health Service (R01-DK-49230, R01-DK-40936, R24-DK-085638, U24-DK-059635, P30-DK-45735, and R01-AG-23686) and a Distinguished Clinical Scientist Award (to K.F.P.) from the American Diabetes Association.

No potential conflicts of interest relevant to this article were reported.

D.E.B., D.L.R., K.F.P., and G.I.S. contributed to the writing of this article. D.E.B. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

# REFERENCES


author: Philip E BournePhilip E. Bourne is Editor-in-Chief of *PLoS Computational Biology*. E-mail: <email@example.com>
date: 2005-10
title: Ten Simple Rules for Getting Published

The student council (<http://www.iscbsc.org/>) of the International Society for Computational Biology asked me to present my thoughts on getting published in the field of computational biology at the Intelligent Systems in Molecular Biology conference held in Detroit in late June of 2005. Close to 200 bright young souls (and a few not so young) crammed into a small room for what proved to be a wonderful interchange among a group of whom approximately one-half had yet to publish their first paper. The advice I gave that day I have modified and present as ten rules for getting published.

# Rule 1: Read many papers, and learn from both the good and the bad work of others.

It is never too early to become a critic. Journal clubs, where you critique a paper as a group, are excellent for having this kind of dialogue. Reading at least two papers a day in detail (not just in your area of research) and thinking about their quality will also help. Being well read has another potential major benefit—it facilitates a more objective view of one's own work. It is too easy after many late nights spent in front of a computer screen and/or laboratory bench to convince yourself that your work is the best invention since sliced bread. More than likely it is not, and your mentor is prone to falling into the same trap, hence rule 2.

# Rule 2: The more objective you can be about your work, the better that work will ultimately become.

Alas, some scientists will never be objective about their own work, and will never make the best scientists—learn objectivity early, the editors and reviewers have.

# Rule 3: Good editors and reviewers will be objective about your work.

The quality of the editorial board is an early indicator of the review process. Look at the masthead of the journal in which you plan to publish. Outstanding editors demand and get outstanding reviews. Put your energy into improving the quality of the manuscript *before submission*. Ideally, the reviews will improve your paper. But they will not get to imparting that advice if there are fundamental flaws.

# Rule 4: If you do not write well in the English language, take lessons early; it will be invaluable later.

This is not just about grammar, but more importantly comprehension. The best papers are those in which complex ideas are expressed in a way that those who are less than immersed in the field can understand. Have you noticed that the most renowned scientists often give the most logical and simply stated yet stimulating lectures? This extends to their written work as well. Note that writing clearly is valuable, even if your ultimate career does not hinge on producing good scientific papers in English language journals. Submitted papers that are not clearly written in good English, unless the science is truly outstanding, are often rejected or at best slow to publish since they require extensive copyediting.

# Rule 5: Learn to live with rejection.

A failure to be objective can make rejection harder to take, and you will be rejected. Scientific careers are full of rejection, even for the best scientists. The correct response to a paper being rejected or requiring major revision is to listen to the reviewers and respond in an objective, not subjective, manner. Reviews reflect how your paper is being judged—learn to live with it. If reviewers are unanimous about the poor quality of the paper, move on—in virtually all cases, they are right. If they request a major revision, do it and address every point they raise both in your cover letter and through obvious revisions to the text. Multiple rounds of revision are painful for all those concerned and slow the publishing process.

# Rule 6: The ingredients of good science are obvious—novelty of research topic, comprehensive coverage of the relevant literature, good data, good analysis including strong statistical support, and a thought-provoking discussion. The ingredients of good science reporting are obvious—good organization, the appropriate use of tables and figures, the right length, writing to the intended audience—do not ignore the obvious.

Be objective about these ingredients when you review the first draft, and do not rely on your mentor. Get a candid opinion by having the paper read by colleagues without a vested interest in the work, including those not directly involved in the topic area.

# Rule 7: Start writing the paper the day you have the idea of what questions to pursue.

Some would argue that this places too much emphasis on publishing, but it could also be argued that it helps define scope and facilitates hypothesis-driven science. The temptation of novice authors is to try to include everything they know in a paper. Your thesis is/was your kitchen sink. Your papers should be concise, and impart as much information as possible in the least number of words. Be familiar with the guide to authors and follow it, the editors and reviewers do. Maintain a good bibliographic database as you go, and read the papers in it.

# Rule 8: Become a reviewer early in your career.

Reviewing other papers will help you write better papers. To start, work with your mentors; have them give you papers they are reviewing and do the first cut at the review (most mentors will be happy to do this). Then, go through the final review that gets sent in by your mentor, and where allowed, as is true of this journal, look at the reviews others have written. This will provide an important perspective on the quality of your reviews and, hopefully, allow you to see your own work in a more objective way. You will also come to understand the review process and the quality of reviews, which is an important ingredient in deciding where to send your paper.

# Rule 9: Decide early on where to try to publish your paper.

This will define the form and level of detail and assumed novelty of the work you are doing. Many journals have a presubmission enquiry system available—use it. Even before the paper is written, get a sense of the novelty of the work, and whether a specific journal will be interested.

# Rule 10: Quality is everything.

It is better to publish one paper in a quality journal than multiple papers in lesser journals. Increasingly, it is harder to hide the impact of your papers; tools like Google Scholar and the ISI Web of Science are being used by tenure committees and employers to define metrics for the quality of your work. It used to be that just the journal name was used as a metric. In the digital world, everyone knows if a paper has little impact. Try to publish in journals that have high impact factors; chances are your paper will have high impact, too, if accepted.

When you are long gone, your scientific legacy is, in large part, the literature you left behind and the impact it represents. I hope these ten simple rules can help you leave behind something future generations of scientists will admire.


author: F Barone; M Bombardieri; J Spencer; P Isaacson; F Humby; P Morgan; S Challacombe; G Valesini; C Pitzalis
date: 2007
institute: 1Department of Rheumatology, GKT School of Medicine, London, UK; 2Department of Immunology, GKT School of Medicine, London, UK; 3Department of Immunology, UCL, London, UK; 4Department of Oral Pathology and Medicine, GKT School of Medicine, London, UK; 5Department of Reumatologia, La Sapienza, Roma, Italy
title: CXCL13, CCL21 and CXCL12 are upregulated in mucosal-associated lymphoid tissue lymphomas in patients with Sjorgen's syndrome and cooperate in the maintenance of the immune response and malignant cell survival

# Background

We previously demonstrated in minor salivary glands of patients with Sjogren's syndrome (SS-mSGs) that a true phenomenon of ectopic lymphoneogenesis takes places, with the formation of germinal centres (GCs), in association with the ectopic expression of the lymphoid chemokines (CKs) CXCL13 and CCL21. In Sjogren's syndrome major salivary glands (SS-MSGs) these structures are known to support clonal immunoglobulin heavy chain gene rearrangements and somatic hypermutation, favouring expansion and selection of autoreactive B-cell clones, clonally related to lymphomatous B-cell clones (responsible for lymphoma development in Sjogren's syndrome (SS)). The involvement of lymphoid CKs and CXCL12 in the development of lymphoid malignancies has been demonstrated. At present, however, no data on the expression of these CKs nor their cellular source within SS-MSGs and mucosal-associated lymphoid tissue lymphomas (MALT-Ls) from patients with SS have been described.

# Objective

To assess the specific contribution of lymphoid CKs in the organization of lymphoid proliferation within SS-MSGs and SS-MALT-Ls.

# Methods

We studied 12 SS-mSGs, four SS-MSGs with lympho-epithelial lesion and 20 SS-MSGs with non-Hodgkin B-cell MALT-Ls. In order to define the histological organization of the lymphoid infiltrate (reactive versus malignant areas) and identify the B-cell subpopulations infiltrating the glands, immunohistochemistry was carried out for cellular (CD21, bcl-2, bcl-6, IgD, CD20, CD3, CD68) and vascular markers (CD31, PNAd). On sequential sections, digital images for CXCL13, CCL21 and CXCL12 were analysed by thresholding positive staining in detected areas of interest. Digital image analysis estimated CK's volume fraction areas as a ratio between CXCL13, CCL21 and CXCL12 positive areas over malignant or reactive areas. CK's producing cells were identified by double staining on sequential sections. Mononuclear cells were isolated from two SS-MALT-L parotids following enzymatic digestion and stained for CD19, CD38, CD27, CD24, IgM, IgD, CD10, CD5, CD3, CD4, CD69, CD45RO, CXCR5, CXCR4 and CCR7. Finally, mRNA from total SS-MSGs and MALT-Ls and isolated B cells and T cells from MALT-Ls were analysed by RT-PCR for the transcript levels of CXCL13, CCL21 and CXCL12.

# Results

Reactive areas, characterized by T-cell/B-cell segregation, CD20^+^IgD^+^bcl-2^+^ follicular B cells, presence of follicular dendritic cell networks in GCs and high endothelial venule formation were detected in 100% of MALT-Ls. A B-cell population (CD20^+^IgD^-^bcl-2^+^) characterized by nuclear abnormalities and monocytoid appearance was consistently observed within the proliferating ducts and identified as the B-cell malignant component. FACS analysis on isolated MALT-L mononuclear cells showed B cells in diverse maturative stages (transitional, mature and memory B cells) and a B-cell population CD19^pos^IgD^low^CD24^neg^CD27^low/neg^CD5^neg^CD10^neg^ not detectable in the controls. Ectopic expression of CXCL13 and CCL21 was observed in 100% of SS-MSGs and MALT-Ls. A significant increase in CXCL13's volume fraction analysis was observed both in SS-MSGs and SS-MALT-L reactive areas, as compared with SS-mSG follicular areas (*P* \< 0.05 and *P* \< 0.05, respectively). A strong difference in CXCL13 within the MALT-L reactive area compared with malignant areas was detected (*P* \< 0.001). CCL21 was significantly increased in MALT-Ls compared with both SS-mSGs and SS-MSGs and was mainly confined to the T-cell area. CXCL12 was strongly expressed by ductal epithelial cells, vessels and reactive areas in SS-mSGs, SS-MSGs and MALT-Ls. Interestingly a significant increase in CXCL12 expression on MALT-L malignant areas as compared with reactive areas in SS-mSGs and SS-MSGs was detected (*P* \< 0.01 and *P* \< 0.05). RT-PCR analysis showed increased CXCL13 and CCL21 level in SS-MSGs compared with MALT-Ls and SS-mSGs, while strong upregulation in CXCL12 transcript in MALT-Ls as compared with SS-mSGs and SS-MSGs was detected.

CXCL13, CCL21 and CXCL12 were detected on CD68^+^ cells by immunohistochemistry, while CD20 and CD3, CXCL13 and CCL21 double staining and mRNA analysis on MALT-extracted T and B lymphocytes showed negligible expression of the two CKs in MALT-L-extracted lymphocytes. Interestingly we identified strong CXCL12 expression on CD19^+^ MALT-L isolated cells both at the protein and mRNA level and on ductal epithelial cells in close contact with the malignant B-cell infiltration. In agreement with this increase, we demonstrated a significant downregulation of CXCR4 on MALT-L-isolated B cells, likely to be the result of CXCR4 internalization upon CXCL12 ligation.

# Conclusion

In SS-MALT-Ls a strong upregulation of the lymphoid CKs CXCL13 and CCL21 takes place and is associated with the organization of the reactive areas involved in the maintenance of the autoimmune process within the malignancy. These findings support a contributory role for CXCL13 and CCL21 in the pathogenesis of MALT lymphomas in SS. These results imply that the CK/CK^-^ receptor axis is functional in MALT-L malignant cells, and suggest that the glandular microenvironment, B-cell receptor signalling upon antigen engagement and autocrine signals from the same malignant population concur in MALT lymphomagenesis, triggering local activation of malignant B cells and favouring their survival and expansion.


abstract: A report on the 2004 Keystone Symposium 'Human Genome Sequence Variation and the Inherited Basis of Common Disease', Breckenridge, USA, 8-13 January 2004.
author: Evan E Eichler; Kelly A Frazer
date: 2004
institute: 1Department of Genetics, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA; 2Perlegen Sciences, 2021 Stierlin Court, Mountain View, CA 94043, USA
title: The nature, pattern and function of human sequence variation

The Keystone Symposia on Human Genome Sequence Variation and the Inherited Basis of Common Disease and Quantitative Genetics in Model Organisms were held concurrently at the Beaver Run Resort this year. The dual nature of the meeting created a unique atmosphere in which participants were encouraged to cross-attend sessions. Indeed, several sessions were held jointly between the two meetings, creating the opportunity for interaction among a larger body of scientists than typically attend a Keystone meeting. This unusual format encouraged cross-fertilization of ideas among population, quantitative and human geneticists as well as epidemiologists and genome scientists. This report is dedicated primarily to the proceedings within the Human Sequence Variation sessions.

# Polymorphisms and haplotype mapping

Two presentations confronted the prevailing hypothesis that common diseases are likely to be due solely to common genetic variants, such as those that can be identified by mapping frequent polymorphisms. Aravinda Chakravarti (Johns Hopkins University, Baltimore, USA) challenged the community by raising, once again, the unsettling specter that rare variants might in fact underlie a significant fraction of common disease. He presented data from his longstanding work on the complex genetics of Hirschsprung Disease. The data strongly suggest that both common and rare single-nucleotide polymorphisms (SNPs) should be considered if the true nature of a complex genetic disease is to be understood. Similarly, David Altshuler (Massachusetts General Hospital, Boston, USA) described a genetic analysis of diabetes. He showed preliminary results suggesting that mitochondrial DNA is involved in type II diabetes and hypothesized that primary alterations in mitochondrial oxidative phosphorylation pathways contribute to type II diabetes. Both common and rare variants are equally important in this case.

Several presentations focused on the way that the structure of the human genome can be understood as being made up of haplotype blocks, and on how this may be useful as well as its biological origin and significance. Mark Daly (Massachusetts Institute of Technology, Cambridge, USA) provided insight into the progress and potential early fruits of the human HapMap project, which aims to produce a complete human haplotype map. A central question is how well the current (200,000 genotyped SNPs) and projected (500,000 SNPs by April 2004) haplotype maps recapitulate existing genetic variation within the human population. Extrapolating from existing data, Daly concluded that a density of one SNP marker every 5 kilobases should be sufficient to tag around 80% of human variation. Andy Clark (Cornell University, Ithaca, USA) stressed the need to impute missing genotypes on the basis of flanking SNP information. He presented a powerful Bayesian approach, which used the linkage disequilibrium between SNP pairs from a region of high marker density to infer the genotypes of missing data. He suggested that with a sufficient density of markers, information about the haplotype phase (the paternal or maternal origin) is unnecessary. David Goldstein (University College London, UK) similarly emphasized the need to identify hidden SNPs and further suggested that when the minor allele frequency drops below 7% there would be insufficient power to predict a hidden SNP within a second sample (based on a sample size of 64 individuals). His simulation studies predicted a loss in performance when the SNP density drops below one SNP per 6 kilobases.

One of the highlights of the meeting was the analysis by Peter Donnelly (University of Oxford, UK) of the landscape of fine-scale recombination. He presented a composite likelihood approach with which to estimate rates of recombination between pairs of SNPs. Using polymorphism data to infer properties of fine-scale recombination in a well-studied 10 megabase region of chromosome 20, he showed that the level of recombination varied as much as three orders of magnitude. His results suggest that 80% of all recombination occurs in around 25% of the sequence. While no clear sequence properties of 'hotspots' and 'coldspots' of recombination emerged, in general coldspots were found to be larger than hotspots, and hotspots tend to locate outside genes. There was a general agreement among several speakers that the only convincing correlation with the boundaries of some, but not all, haplotype blocks is increased recombination frequency.

One of the anticipated uses of SNPs and information about haplotype block structure is to improve the power of association studies for human genetic disease. K.F. outlined a strategy to tackle complex genetic traits using high-throughput methods of genotyping. Based on an analysis of a large number of individuals (around 1,000) for genetic variation and plasma concentration of low-density lipoprotein (LDL), the importance of well-characterized case-control samples and replica testing of pooled samples becomes very evident. Richard Lifton (Yale University, New Haven, USA) discussed the genetic determinants of hypertension and metabolic syndrome. He used families at extreme points of the phenotypic range - extreme hypotension and extreme hypertension - to identify 15 genes associated with this disease; 14 of these are involved in the renin-angiotension system, causing either increased or decreased Na^+^ reabsorption. Lifton argued that this is the reason that drugs targeting salt absorption are superior in the treatment of hypertension. A similar success story was echoed by Stephen O'Brien (National Cancer Institute, Frederick, USA) in a detailed study of a cohort of more than 1,000 individuals with acquired immunodeficiency syndrome (AIDS) who have been clinically monitored for over 10 years. His research has identified and/or confirmed 15 genes (including the immune-cell surface molecules CD4, CD5, RANTES, HLA class I, and others) that affect infection with human immunodeficiency virus (HIV-1) and disease progression. Finally, David Hunter (Harvard Medical School, Boston, USA) discussed the role of gene-environment interactions in common disease. He described several examples where dietary and medical advice should be dependent on genotype information, including the finding that the *APOE*4 allele, which has been linked to both Alzheimer's disease and hypertension, is more associated with cognitive decline in individuals with uncontrolled hypertension than in individuals with controlled hypertension.

# Model organisms

In a joint session between the two concurrent meetings, a series of talks focused on how model organisms might be used to move from genotype to phenotype or function. Keith Davies (Paradigm Genetics, Research Triangle Park, North Carolina, USA) described an industrial-level high-throughput transgenic facility that focuses on the systematic collection of phenotype information from *Arabidopsis*. Genotype-phenotype correlation data for over 16,000 *Arabidopsis* genes (including previously unknown genes) is in progress. Using a transposon-tagging system to detect open reading frames (ORFs) in yeast, Michael Snyder (Yale University, New Haven, USA) described the systematic experimental verification of genes in the yeast genome. He emphasized the need to annotate genes, as well as transcription-factor binding sites, experimentally, and not to rely strictly on *in silico* analyses. In contrast, Eric Lander (Whitehead Institute, Cambridge, USA) showed the power of comparative whole-genome sequence analysis of yeast genomes to systematically identify genes, regulatory elements and processes of genome evolution. His analysis of four yeast genomes predicted 5,695 'real' genes. Similar analyses between multiple mammalian genomes are revealing many unexplained conserved elements and "the spectacular state of ignorance" in the area of functional genomics.

A particularly novel aspect of this meeting was the emphasis on inherited patterns of gene expression. Several studies have shown that natural genetic variation can cause significant differences in gene expression, suggesting that phenotypic variation can result not only from coding variation but also from regulatory variation that affects gene expression. To study the genetic architecture of natural variation in gene expression, Leonid Kruglyak (Fred Hutchinson Cancer Research Center, Seattle, USA) conducted a linkage analysis of genome-wide expression patterns in a cross between a laboratory and a wild strain of *Saccharomyces cerevisisae*. Over 1,500 genes were differentially expressed between the parental strains. These loci fell into two categories: *cis*-acting modulators of single genes (around 20%) and *trans*-acting modulators of many genes (around 80%). Surprisingly, analysis of the *trans*-acting loci by molecular function did not show an enrichment of transcription factors. Kevin White (Yale University School of Medicine, New Haven, USA) described the evolution of gene expression in *Drosophila*. He addressed the question, "If evolution was played several times under similar conditions would it repeat itself?" *Drosophila* from 27 inbred strains (with 20 males and 20 females of each strain) were divided into six populations. Three populations were raised in a hypoxic environment and three in a normoxic environment for several generations. When gene expression patterns were compared between strains in the two oxygen levels, 195 (53%) of the 368 genes that showed greater than a two-fold expression difference had evolved in all six populations, suggesting that some genes are more prone to change their expression levels, perhaps due to selective pressures.

Stephanie Monks (University of Washington/Rosetta Inpharmatics, Seattle, USA) discussed the genetics of gene expression in mice. She established a genetic map of expression for 111 F2 mice resulting from a C57BL/J6 × DBA/2J cross. For each of the F2 mice, RNA was isolated from the liver and 23,574 genes were assayed for expression using arrays. The study demonstrated that the distribution of quantitative trait loci (QTLs) controlling gene expression is non-random in the genome. Justin Fay (Washington University, St Louis, USA) addressed the question of whether or not transcriptional variation has functional consequences. Nine isolates of *S. cerevisiae* were grown in rich media in the presence or absence of copper sulfate. Two strains with demonstrated resistance to copper sulfate showed a reduced growth rate, and two different strains produced rust colored colonies. Gene expression differences correlated with resistance were enriched for oxidative stress and the unfolded protein response, while those related to coloration were almost exclusively in the methionine/sulfur assimilation pathway.

In general, the pattern and nature of human genome sequence variation was the primary focus of the meeting, although due diligence was given to insights that could be gleaned from excellent studies from model organisms such as *Drosophila*, mouse, yeast and *Arabidopsis*. The scope of presentations was significantly more 'global' than in past meetings, due in part to the near-completion of the human genome, improvements in genotyping and the amount of analyzed sequence data now available. The wider range of topics appealed to a broader base of biologists. During the course of this meeting, a number of the 'usual' questions emerged. What is the contribution of rare versus common SNPs to the molecular basis for complex genetic disease? What density of SNP markers is sufficient for discriminating disease associations? Is there functional significance to haplotype block structures? How soon will geneticists routinely be able to resolve the genetic basis of complex disease? While there were no final answers to these and other questions, it was clear that significant advances are being made in these directions.