Clinical analysis of germline copy number variation in DMD using a non-conjugate hierarchical Bayesian model.

BACKGROUND: Detection of copy number variants (CNVs) is an important aspect of clinical testing for several disorders, including Duchenne muscular dystrophy, and is often performed using multiplex ligation-dependent probe amplification (MLPA). However, since many genetic carrier screens depend instead on next-generation sequencing (NGS) for wider discovery of small variants, they often do not include CNV analysis. Moreover, most computational techniques developed to detect CNVs from exome sequencing data are not suitable for carrier screening, as they require matched normals, very large cohorts, or extensive gene panels. METHODS: We present a computational software package, geneCNV ( http://github.com/vkozareva/geneCNV ), which can identify exon-level CNVs using exome sequencing data from only a few genes. The tool relies on a hierarchical parametric model trained on a small cohort of reference samples. RESULTS: Using geneCNV, we accurately inferred heterozygous CNVs in the DMD gene across a cohort of 15 test subjects. These results were validated against MLPA, the current standard for clinical CNV analysis in DMD. We also benchmarked the tool's performance against other computational techniques and found comparable or improved CNV detection in DMD using data from panels ranging from 4,000 genes to as few as 8 genes. CONCLUSIONS: geneCNV allows for the creation of cost-effective screening panels by allowing NGS sequencing approaches to generate results equivalent to bespoke genotyping assays like MLPA. By using a parametric model to detect CNVs, it also fulfills regulatory requirements to define a reference range for a genetic test. It is freely available and can be incorporated into any Illumina sequencing pipeline to create clinical assays for detection of exon duplications and deletions.

Metabolic profiles of exercise in patients with McArdle disease or mitochondrial myopathy.

McArdle disease and mitochondrial myopathy impair muscle oxidative phosphorylation (OXPHOS) by distinct mechanisms: the former by restricting oxidative substrate availability caused by blocked glycogen breakdown, the latter because of intrinsic respiratory chain defects. We applied metabolic profiling to systematically interrogate these disorders at rest, when muscle symptoms are typically minimal, and with exercise, when symptoms of premature fatigue and potential muscle injury are unmasked. At rest, patients with mitochondrial disease exhibit elevated lactate and reduced uridine; in McArdle disease purine nucleotide metabolites, including xanthine, hypoxanthine, and inosine are elevated. During exercise, glycolytic intermediates, TCA cycle intermediates, and pantothenate expand dramatically in both mitochondrial disease and control subjects. In contrast, in McArdle disease, these metabolites remain unchanged from rest; but urea cycle intermediates are increased, likely attributable to increased ammonia production as a result of exaggerated purine degradation. Our results establish skeletal muscle glycogen as the source of TCA cycle expansion that normally accompanies exercise and imply that impaired TCA cycle flux is a central mechanism of restricted oxidative capacity in this disorder. Finally, we report that resting levels of long-chain triacylglycerols in mitochondrial myopathy correlate with the severity of OXPHOS dysfunction, as indicated by the level of impaired O2 extraction from arterial blood during peak exercise. Our integrated analysis of exercise and metabolism provides unique insights into the biochemical basis of these muscle oxidative defects, with potential implications for their clinical management.

Effects of sodium benzoate, a widely used food preservative, on glucose homeostasis and metabolic profiles in humans.

Sodium benzoate is a widely used preservative found in many foods and soft drinks. It is metabolized within mitochondria to produce hippurate, which is then cleared by the kidneys. We previously reported that ingestion of sodium benzoate at the generally regarded as safe (GRAS) dose leads to a robust excursion in the plasma hippurate level [1]. Since previous reports demonstrated adverse effects of benzoate and hippurate on glucose homeostasis in cells and in animal models, we hypothesized that benzoate might represent a widespread and underappreciated diabetogenic dietary exposure in humans. Here, we evaluated whether acute exposure to GRAS levels of sodium benzoate alters insulin and glucose homeostasis through a randomized, controlled, cross-over study of 14 overweight subjects. Serial blood samples were collected following an oral glucose challenge, in the presence or absence of sodium benzoate. Outcome measurements included glucose, insulin, glucagon, as well as temporal mass spectrometry-based metabolic profiles. We did not find a statistically significant effect of an acute oral exposure to sodium benzoate on glucose homeostasis. Of the 146 metabolites targeted, four changed significantly in response to benzoate, including the expected rise in benzoate and hippurate. In addition, anthranilic acid, a tryptophan metabolite, exhibited a robust rise, while acetylglycine dropped. Although our study shows that GRAS doses of benzoate do not have an acute, adverse effect on glucose homeostasis, future studies will be necessary to explore the metabolic impact of chronic benzoate exposure.

Mapping the fitness landscape of gene expression uncovers the cause of antagonism and sign epistasis between adaptive mutations.

How do adapting populations navigate the tensions between the costs of gene expression and the benefits of gene products to optimize the levels of many genes at once? Here we combined independently-arising beneficial mutations that altered enzyme levels in the central metabolism of Methylobacterium extorquens to uncover the fitness landscape defined by gene expression levels. We found strong antagonism and sign epistasis between these beneficial mutations. Mutations with the largest individual benefit interacted the most antagonistically with other mutations, a trend we also uncovered through analyses of datasets from other model systems. However, these beneficial mutations interacted multiplicatively (i.e., no epistasis) at the level of enzyme expression. By generating a model that predicts fitness from enzyme levels we could explain the observed sign epistasis as a result of overshooting the optimum defined by a balance between enzyme catalysis benefits and fitness costs. Knowledge of the phenotypic landscape also illuminated that, although the fitness peak was phenotypically far from the ancestral state, it was not genetically distant. Single beneficial mutations jumped straight toward the global optimum rather than being constrained to change the expression phenotypes in the correlated fashion expected by the genetic architecture. Given that adaptation in nature often results from optimizing gene expression, these conclusions can be widely applicable to other organisms and selective conditions. Poor interactions between individually beneficial alleles affecting gene expression may thus compromise the benefit of sex during adaptation and promote genetic differentiation.

The ability of flux balance analysis to predict evolution of central metabolism scales with the initial distance to the optimum.

The most powerful genome-scale framework to model metabolism, flux balance analysis (FBA), is an evolutionary optimality model. It hypothesizes selection upon a proposed optimality criterion in order to predict the set of internal fluxes that would maximize fitness. Here we present a direct test of the optimality assumption underlying FBA by comparing the central metabolic fluxes predicted by multiple criteria to changes measurable by a (13)C-labeling method for experimentally-evolved strains. We considered datasets for three Escherichia coli evolution experiments that varied in their length, consistency of environment, and initial optimality. For ten populations that were evolved for 50,000 generations in glucose minimal medium, we observed modest changes in relative fluxes that led to small, but significant decreases in optimality and increased the distance to the predicted optimal flux distribution. In contrast, seven populations evolved on the poor substrate lactate for 900 generations collectively became more optimal and had flux distributions that moved toward predictions. For three pairs of central metabolic knockouts evolved on glucose for 600-800 generations, there was a balance between cases where optimality and flux patterns moved toward or away from FBA predictions. Despite this variation in predictability of changes in central metabolism, two generalities emerged. First, improved growth largely derived from evolved increases in the rate of substrate use. Second, FBA predictions bore out well for the two experiments initiated with ancestors with relatively sub-optimal yield, whereas those begun already quite optimal tended to move somewhat away from predictions. These findings suggest that the tradeoff between rate and yield is surprisingly modest. The observed positive correlation between rate and yield when adaptation initiated further from the optimum resulted in the ability of FBA to use stoichiometric constraints to predict the evolution of metabolism despite selection for rate.

Development of an optimized medium, strain and high-throughput culturing methods for Methylobacterium extorquens.

Methylobacterium extorquens strains are the best-studied methylotrophic model system, and their metabolism of single carbon compounds has been studied for over 50 years. Here we develop a new system for high-throughput batch culture of M. extorquens in microtiter plates by jointly optimizing the properties of the organism, the growth media and the culturing system. After removing cellulose synthase genes in M. extorquens strains AM1 and PA1 to prevent biofilm formation, we found that currently available lab automation equipment, integrated and managed by open source software, makes possible reliable estimates of the exponential growth rate. Using this system, we developed an optimized growth medium for M. extorquens using response surface methodologies. We found that media that used EDTA as a metal chelator inhibited growth and led to inconsistent culture conditions. In contrast, the new medium we developed with a PIPES buffer and metals chelated by citrate allowed for fast and more consistent growth rates. This new Methylobacterium PIPES ('MP') medium was also robust to large deviations in its component ingredients which avoided batch effects from experiments that used media prepared at different times. MP medium allows for faster and more consistent growth than other media used for M. extorquens.

Clarity: an open-source manager for laboratory automation.

Software to manage automated laboratories, when interfaced with hardware instruments, gives users a way to specify experimental protocols and schedule activities to avoid hardware conflicts. In addition to these basics, modern laboratories need software that can run multiple different protocols in parallel and that can be easily extended to interface with a constantly growing diversity of techniques and instruments. We present Clarity, a laboratory automation manager that is hardware agnostic, portable, extensible, and open source. Clarity provides critical features including remote monitoring, robust error reporting by phone or email, and full state recovery in the event of a system crash. We discuss the basic organization of Clarity, demonstrate an example of its implementation for the automated analysis of bacterial growth, and describe how the program can be extended to manage new hardware. Clarity is mature, well documented, actively developed, written in C# for the Common Language Infrastructure, and is free and open-source software. These advantages set Clarity apart from currently available laboratory automation programs. The source code and documentation for Clarity is available at http://code.google.com/p/osla/.

FREQ-Seq: a rapid, cost-effective, sequencing-based method to determine allele frequencies directly from mixed populations.

Understanding evolutionary dynamics within microbial populations requires the ability to accurately follow allele frequencies through time. Here we present a rapid, cost-effective method (FREQ-Seq) that leverages Illumina next-generation sequencing for localized, quantitative allele frequency detection. Analogous to RNA-Seq, FREQ-Seq relies upon counts from the >10(5) reads generated per locus per time-point to determine allele frequencies. Loci of interest are directly amplified from a mixed population via two rounds of PCR using inexpensive, user-designed oligonucleotides and a bar-coded bridging primer system that can be regenerated in-house. The resulting bar-coded PCR products contain the adapters needed for Illumina sequencing, eliminating further library preparation. We demonstrate the utility of FREQ-Seq by determining the order and dynamics of beneficial alleles that arose as a microbial population, founded with an engineered strain of Methylobacterium, evolved to grow on methanol. Quantifying allele frequencies with minimal bias down to 1% abundance allowed effective analysis of SNPs, small in-dels and insertions of transposable elements. Our data reveal large-scale clonal interference during the early stages of adaptation and illustrate the utility of FREQ-Seq as a cost-effective tool for tracking allele frequencies in populations.

Ultrafast evolution and loss of CRISPRs following a host shift in a novel wildlife pathogen, Mycoplasma gallisepticum.

Measureable rates of genome evolution are well documented in human pathogens but are less well understood in bacterial pathogens in the wild, particularly during and after host switches. Mycoplasma gallisepticum (MG) is a pathogenic bacterium that has evolved predominantly in poultry and recently jumped to wild house finches (Carpodacus mexicanus), a common North American songbird. For the first time we characterize the genome and measure rates of genome evolution in House Finch isolates of MG, as well as in poultry outgroups. Using whole-genome sequences of 12 House Finch isolates across a 13-year serial sample and an additional four newly sequenced poultry strains, we estimate a nucleotide diversity in House Finch isolates of only ∼2% of ancestral poultry strains and a nucleotide substitution rate of 0.8-1.2×10(-5) per site per year both in poultry and in House Finches, an exceptionally fast rate rivaling some of the highest estimates reported thus far for bacteria. We also found high diversity and complete turnover of CRISPR arrays in poultry MG strains prior to the switch to the House Finch host, but after the invasion of House Finches there is progressive loss of CRISPR repeat diversity, and recruitment of novel CRISPR repeats ceases. Recent (2007) House Finch MG strains retain only ∼50% of the CRISPR repertoire founding (1994-95) strains and have lost the CRISPR-associated genes required for CRISPR function. Our results suggest that genome evolution in bacterial pathogens of wild birds can be extremely rapid and in this case is accompanied by apparent functional loss of CRISPRs.

Diminishing returns epistasis among beneficial mutations decelerates adaptation.

Epistasis has substantial impacts on evolution, in particular, the rate of adaptation. We generated combinations of beneficial mutations that arose in a lineage during rapid adaptation of a bacterium whose growth depended on a newly introduced metabolic pathway. The proportional selective benefit for three of the four loci consistently decreased when they were introduced onto more fit backgrounds. These three alleles all reduced morphological defects caused by expression of the foreign pathway. A simple theoretical model segregating the apparent contribution of individual alleles to benefits and costs effectively predicted the interactions between them. These results provide the first evidence that patterns of epistasis may differ for within- and between-gene interactions during adaptation and that diminishing returns epistasis contributes to the consistent observation of decelerating fitness gains during adaptation.

Darwinian evolution can follow only very few mutational paths to fitter proteins.

Five point mutations in a particular beta-lactamase allele jointly increase bacterial resistance to a clinically important antibiotic by a factor of approximately 100,000. In principle, evolution to this high-resistance beta-lactamase might follow any of the 120 mutational trajectories linking these alleles. However, we demonstrate that 102 trajectories are inaccessible to Darwinian selection and that many of the remaining trajectories have negligible probabilities of realization, because four of these five mutations fail to increase drug resistance in some combinations. Pervasive biophysical pleiotropy within the beta-lactamase seems to be responsible, and because such pleiotropy appears to be a general property of missense mutations, we conclude that much protein evolution will be similarly constrained. This implies that the protein tape of life may be largely reproducible and even predictable.