Biology subjects

Soni, V.

Publications and source records attributed to Soni, V..

4 recordsLinked to original sources

bioRxiv2021

Site level factors that affect the rate of adaptive evolution in humans and chimpanzees; the effect of contracting population size.

It has previously been shown in other species that the rate of adaptive evolution is higher at sites that are more exposed in a protein structure and lower between amino acid pairs that are more dissimilar. We have investigated whether these patterns are found in the divergence between humans and chimpanzees using an extension of the MacDonald-Kreitman test. We confirm previous findings and find that the rate of adaptive evolution, relative to the rate of mutation, is higher for more exposed amino acids, lower for amino acid pairs that are more dissimilar in terms of their polarity, volume and lower for amino acid pairs that are subject to stronger purifying selection, as measured by the ratio of the numbers of non-synonymous to synonymous polymorphisms (pN /pS). However, the slope of this latter relationship is significantly shallower than in Drosophila species. We suggest that this is due to the population contraction that has occurred since humans and chimpanzees diverged. We demonstrate theoretically that population size reduction can generate an artefactual positive correlation between the rate of adaptive evolution and any factor that is correlated to the mean strength of selection acting against deleterious mutations, even if there has been no adaptive evolution (the converse is also expected). Our measure of selective constraint, pN /pS, is negatively correlated to the mean strength of selection, and hence we would expect the correlation between the rate of adaptive evolution to also be negatively correlated to pN /pS, if there is no adaptive evolution. The fact that our rate of adaptive evolution is positively correlated to pN /pS suggests that the correlation does genuinely exist, but that is has been attenuated by population size contraction.

evolutionary biology↗

bioRxiv2021

Factors that affect the rates of adaptive and non-adaptive evolution at the gene level in humans and chimpanzees

The rate of amino acid substitution has been shown to be correlated to a number of factors including the rate of recombination, the age of the gene, the length of the protein, mean expression level and gene function. However, the extent to which these correlations are due to adaptive and non-adaptive evolution has not been studied in detail, at least not in hominids. We find that the rate of adaptive evolution is significantly positively correlated to the rate of recombination, protein length and gene expression level, and negatively correlated to gene age. The correlations remain significant when each factor is controlled for in turn, except when controlling for expression in an analysis of protein length; and they also remain significant, or marginally significant, when biased gene conversion is controlled for. However, the positive correlations could be an artefact of population size contraction. We also find that the rate of non-adaptive evolution is negatively correlated to each factor, and all these correlations survive controlling for each other and biased gene conversion. Finally, we examine the effect of gene function on rates of adaptive and non-adaptive evolution; we confirm that virus interacting proteins (VIPs) have higher rates of adaptive and lower rates of non-adaptive evolution, but we also demonstrate that there is significant variation in the rate of adaptive and non-adaptive evolution between GO categories when removing VIPs. We estimate that the VIP/non-VIP axis explains about 5-8x more of the variance in evolutionary rate than GO categories.

evolutionary biology↗

bioRxiv2021

Chemical-genetic interaction mapping links carbon metabolism and cell wall structure to tuberculosis drug efficacy

Current chemotherapy against Mycobacterium tuberculosis (Mtb), an important human pathogen, requires a multidrug regimen lasting several months. While efforts have been made to optimize therapy by exploiting drug-drug synergies, testing new drug combinations in relevant host environments remains arduous. In particular, host environments profoundly affect the bacterial metabolic state and drug efficacy, limiting the accuracy of predictions based on in vitro assays alone. In this study, we utilize conditional Mtb knockdown mutants of essential genes as an experimentally-tractable surrogate for drug treatment, and probe the relationship between Mtb carbon metabolism and chemical-genetic interactions (CGI). We examined the anti-tubercular drugs isoniazid, rifampicin and moxifloxacin, and found that CGI are differentially responsive to the metabolic state, defining both environment-independent and -dependent interactions. Specifically, growth on the in vivo-relevant carbon source, cholesterol, reduced rifampicin efficacy by altering mycobacterial cell surface lipid composition. We report that a variety of perturbations in cell wall synthesis pathways restore rifampicin efficacy during growth on cholesterol, and that both environment-independent and cholesterol-dependent in vitro CGI could be leveraged to enhance bacterial clearance in the mouse infection model. Our findings present an atlas of novel chemical-genetic-environmental interactions that can be used to optimize drug-drug interactions as well as provide a framework for understanding in vitro correlates of in vivo efficacy. SignificanceEfforts to improve tuberculosis therapy include optimizing multi-drug regimens to take advantage of drug-drug synergies. However, the complex host environment has a profound effect on bacterial metabolic state and drug activity, making predictions of optimal drug combinations difficult. In this study, we leverage a newly developed library of conditional knockdown Mycobacterium tuberculosis mutants in which genetic depletion of essential genes mimics the effect of drug therapy. This tractable system allowed us to assess the effect of growth condition on predicted drug-drug interactions. We found that these interactions can be differentially sensitive to the metabolic state and select in vitro-defined interactions can be leveraged to accelerate bacterial killing during infection. These findings suggest new strategies for optimizing tuberculosis therapy.

microbiology↗

bioRxiv2021

A new test suggests that balancing selection maintains hundreds of non-synonymous polymorphisms in the human genome

The role that balancing selection plays in the maintenance of genetic diversity remains unresolved. Here we introduce a new test, based on the McDonald-Kreitman test, in which the number of polymorphisms that are shared between populations is contrasted to those that are private at selected and neutral sites. We show that this simple test is robust to a variety of demographic changes, and that it can also give a direct estimate of the number of shared polymorphisms that are directly maintained by balancing selection. We apply our method to population genomic data from humans and conclude that more than a thousand non-synonymous polymorphisms are subject to balancing selection.

evolutionary biology↗