Biology subjects

Desai, M. M.

Publications and source records attributed to Desai, M. M..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

The landscape of antibody binding affinity in SARS-CoV-2 Omicron BA.1 evolution

The Omicron BA.1 variant of SARS-CoV-2 escapes convalescent sera and monoclonal antibodies that are effective against earlier strains of the virus. This immune evasion is largely a consequence of mutations in the BA.1 receptor binding domain (RBD), the major antigenic target of SARS-CoV-2. Previous studies have identified several key RBD mutations leading to escape from most antibodies. However, little is known about how these escape mutations interact with each other and with other mutations in the RBD. Here, we systematically map these interactions by measuring the binding affinity of all possible combinations of these 15 RBD mutations (215 = 32,768 genotypes) to four monoclonal antibodies (LY-CoV016, LY-CoV555, REGN10987, and S309) with distinct epitopes. We find that BA.1 can lose affinity to diverse antibodies by acquiring a few large-effect mutations and can reduce affinity to others through several small-effect mutations. However, our results also reveal alternative pathways to antibody escape that do not include every large-effect mutation. Moreover, epistatic interactions are shown to constrain affinity decline in S309 but only modestly shape the affinity landscapes of other antibodies. Together with previous work on the ACE2 affinity landscape, our results suggest that escape of each antibody is mediated by distinct groups of mutations, whose deleterious effects on ACE2 affinity are compensated by another distinct group of mutations (most notably Q498R and N501Y).

evolutionary biology↗

bioRxiv2022

Compensatory epistasis maintains ACE2 affinity in SARS-CoV-2 Omicron BA.1

The Omicron BA.1 variant emerged in late 2021 and quickly spread across the world. Compared to the ancestral Wuhan Hu-1 strain and other pre-Omicron SARS-CoV-2 variants, BA.1 has many mutations, a number of which are known to enable antibody escape 1-3. Many of these antibody-escape mutations individually decrease the spike receptor-binding domain (RBD) affinity for ACE2 in the background of early SARS-CoV-2 variants 4, but BA.1 still binds ACE2 with high affinity 5,6. The fitness and evolution of the BA.1 lineage is therefore driven by the combined effects of numerous mutations. Here, we systematically map the epistatic interactions between the 15 mutations in the RBD of BA.1 relative to the Wuhan Hu-1 strain. Specifically, we measure the ACE2 affinity of all possible combinations of these 15 mutations (2 15 = 32,768 genotypes), spanning all possible evolutionary intermediates from the ancestral Wuhan Hu-1 strain to BA.1. We find that immune escape mutations in BA.1 individually reduce ACE2 affinity but are compensated by epistatic interactions with other affinity-enhancing mutations, including Q498R and N501Y. Thus, the ability of BA.1 to evade immunity while maintaining ACE2 affinity is contingent on acquiring multiple interacting mutations. Our results implicate compensatory epistasis as a key factor driving substantial evolutionary change for SARS-CoV-2 and are consistent with Omicron BA.1 arising from a chronic infection.

evolutionary biology↗

bioRxiv2022

Spatial structure alters the site frequency spectrum produced by hitchhiking

The reduction of genetic diversity due to genetic hitchhiking is widely used to find past selective sweeps from sequencing data, but very little is known about how spatial structure affects hitchhiking. We use mathematical modeling and simulations to find the unfolded site frequency spectrum (SFS) left by hitchhiking in the genomic region of a sweep in a population occupying a one-dimensional range. For such populations, sweeps spread as Fisher waves, rather than logistically. We find that this leaves a characteristic three-part SFS at loci very close to the swept locus. Very low frequencies are dominated by recent mutations that occurred after the sweep and are unaffected by hitchhiking. At moderately low frequencies, there is a transition zone primarily composed of alleles that briefly "surfed" on the wave of the sweep before falling out of the wavefront, leaving a spectrum close to that expected in well-mixed populations. However, for moderate-to-high frequencies, there is a distinctive scaling regime of the SFS produced by alleles that drifted to fixation in the wavefront and then were carried throughout the population. For loci slightly farther away from the swept locus on the genome, recombination is much more effective at restoring diversity in one-dimensional populations than it is in well-mixed ones. We find that these signatures of space can be strong even in apparently well-mixed populations with negligible spatial genetic differentiation, suggesting that spatial structure may frequently distort the signatures of hitchhiking in natural populations.

evolutionary biology↗

bioRxiv2021

Mutational robustness changes during long-term adaptation in laboratory budding yeast populations

As an adapting population traverses the fitness landscape, its local neighborhood (i.e., the collection of fitness effects of single-step mutations) can change shape because of interactions with mutations acquired during evolution. These changes to the distribution of fitness effects can affect both the rate of adaptation and the accumulation of deleterious mutations. However, while numerous models of fitness landscapes have been proposed in the literature, empirical data on how this distribution changes during evolution remains limited. In this study, we directly measure how the fitness landscape neighborhood changes during laboratory adaptation. Using a barcode-based mutagenesis system, we measure the fitness effects of 91 specific gene disruption mutations in genetic backgrounds spanning 8,000-10,000 generations of evolution in two constant environments. We find that the mean of the distribution of fitness effects decreases in one environment, indicating a reduction in mutational robustness, but does not change in the other. We show that these distribution-level patterns result from biases in variable patterns of epistasis at the level of individual mutations, including fitness-correlated and idiosyncratic epistasis.

evolutionary biology↗

bioRxiv2021

Idiosyncratic epistasis leads to global fitness-correlated trends

Epistasis can dramatically affect evolutionary trajectories. In recent decades, protein-level fitness landscapes have revealed extensive idiosyncratic epistasis among specific mutations. In contrast, other work has found ubiquitous and apparently non-specific patterns of global diminishing-returns and increasing-costs epistasis among mutations across the genome. Here, we use a hierarchical CRISPR gene drive system to construct all combinations of 10 missense mutations from across the genome in budding yeast, and measure their fitness in six environments. We show that the resulting fitness landscapes exhibit global fitness-correlated trends, but that these trends emerge from specific idiosyncratic interactions. This provides the first experimental validation of recent theoretical work that has argued that fitness-correlated trends can emerge as the generic consequence of idiosyncratic epistasis. One-Sentence SummaryA genome-spanning fitness landscape reveals how idiosyncratic genetic interactions lead to global epistatic patterns.

evolutionary biology↗

bioRxiv2021

Barcoded bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast

Mapping the genetic basis of complex traits is critical to uncovering the biological mechanisms that underlie disease and other phenotypes. Genome-wide association studies (GWAS) in humans and quantitative trait locus (QTL) mapping in model organisms can now explain much of the observed heritability in many traits, allowing us to predict phenotype from genotype. However, constraints on power due to statistical confounders in large GWAS and smaller sample sizes in QTL studies still limit our ability to resolve numerous small-effect variants, map them to causal genes, identify pleiotropic effects across multiple traits, and infer non-additive interactions between loci (epistasis). Here, we introduce barcoded bulk quantitative trait locus (BB-QTL) mapping, which allows us to construct, genotype, and phenotype 100,000 offspring of a budding yeast cross, two orders of magnitude larger than the previous state of the art. We use this panel to map the genetic basis of eighteen complex traits, finding that the genetic architecture of these traits involves hundreds of small-effect loci densely spaced throughout the genome, many with widespread pleiotropic effects across multiple traits. Epistasis plays a central role, with thousands of interactions that provide insight into genetic networks. By dramatically increasing sample size, BB-QTL mapping demonstrates the potential of natural variants in high-powered QTL studies to reveal the highly polygenic, pleiotropic, and epistatic architecture of complex traits. Significance statementUnderstanding the genetic basis of important phenotypes is a central goal of genetics. However, the highly polygenic architectures of complex traits inferred by large-scale genome-wide association studies (GWAS) in humans stand in contrast to the results of quantitative trait locus (QTL) mapping studies in model organisms. Here, we use a barcoding approach to conduct QTL mapping in budding yeast at a scale two orders of magnitude larger than the previous state of the art. The resulting increase in power reveals the polygenic nature of complex traits in yeast, and offers insight into widespread patterns of pleiotropy and epistasis. Our data and analysis methods offer opportunities for future work in systems biology, and have implications for large-scale GWAS in human populations.

genetics↗

bioRxiv2021

Population genetics of polymorphism and divergence in rapidly evolving populations

In rapidly evolving populations, numerous beneficial and deleterious mutations can arise and segregate within a population at the same time. In this regime, evolutionary dynamics cannot be analyzed using traditional population genetic approaches that assume that sites evolve independently. Instead, the dynamics of many loci must be analyzed simultaneously. Recent work has made progress by first analyzing the fitness variation within a population, and then studying how individual lineages interact with this traveling fitness wave. However, these "traveling wave" models have previously been restricted to extreme cases where selection on individual mutations is either much faster or much slower than the typical coalescent timescale Tc. In this work, we show how the traveling wave framework can be extended to intermediate regimes in which the scaled fitness effects of mutations (Tcs) are neither large nor small compared to one. This enables us to describe the dynamics of populations subject to a wide range of fitness effects, and in particular, in cases where it is not immediately clear which mutations are most important in shaping the dynamics and statistics of genetic diversity. We use this approach to derive new expressions for the fixation probabilities and site frequency spectra of mutations as a function of their scaled fitness effects, along with related results for the coalescent timescale Tc and the rate of adaptation or Mullers ratchet. We find that competition between linked mutations can have a dramatic impact on the proportions of neutral and selected polymorphisms, which is not simply summarized by the scaled selection coefficient Tcs. We conclude by discussing the implications of these results for population genetic inferences.

evolutionary biology↗

bioRxiv2021

Dynamics and variability in the pleiotropic effects of adaptation in laboratory budding yeast populations

Evolutionary adaptation to a constant environment is driven by the accumulation of mutations which can have a range of unrealized pleiotropic effects in other environments. These pleiotropic consequences of adaptation can influence the emergence of specialists or generalists, and are critical for evolution in temporally or spatially fluctuating environments. While many experiments have examined the pleiotropic effects of adaptation at a snapshot in time, very few have observed the dynamics by which these effects emerge and evolve. Here, we propagated hundreds of diploid and haploid laboratory budding yeast populations in each of three environments, and then assayed their fitness in multiple environments over 1000 generations of evolution. We find that replicate populations evolved in the same condition share common patterns of pleiotropic effects across other environments, which emerge within the first several hundred generations of evolution. However, we also find dynamic and environment-specific variability within these trends: variability in pleiotropic effects tends to increase over time, with the extent of variability depending on the evolution environment. These results suggest shifting and overlapping contributions of chance and contingency to the pleiotropic effects of adaptation, which could influence evolutionary trajectories in complex environments that fluctuate across space and time.

evolutionary biology↗

bioRxiv2021

Binding affinity landscapes constrain the evolution of broadly neutralizing anti-influenza antibodies

Over the past two decades, several broadly neutralizing antibodies (bnAbs) that confer protection against diverse influenza strains have been isolated1,2. Structural and biochemical characterization of these bnAbs has provided molecular insight into how they bind distinct antigens1. However, our understanding of the evolutionary pathways leading to bnAbs, and thus how best to elicit them, remains limited. Here, we measure equilibrium dissociation constants of combinatorially complete mutational libraries for two naturally isolated influenza bnAbs3-5 (CR-9114, 16 mutations; CR-6261, 11 mutations), reconstructing all possible intermediates back to the unmutated germline sequences. We find that these two libraries exhibit strikingly different patterns of breadth: while many variants of CR-6261 display moderate affinity to diverse antigens, those of CR-9114 display appreciable affinity only in specific, nested combinations. By examining the extensive pairwise and higher-order epistasis between mutations, we find key sites with strong synergistic interactions that are highly similar across antigens for CR-6261 and different for CR-9114. Together, these features of the binding affinity landscapes strongly favor sequential acquisition of affinity to diverse antigens for CR-9114, while the acquisition of breadth to more similar antigens for CR-6261 is less constrained. These results, if generalizable to other bnAbs, may explain the molecular basis for the widespread observation that sequential exposure favors greater breadth6-8, and such mechanistic insight will be essential for predicting and eliciting broadly protective immune responses.

evolutionary biology↗

bioRxiv2021

The Genetic Basis of Differential Autodiploidization in Evolving Yeast Populations

Spontaneous whole-genome duplication, or autodiploidization, is a common route to adaptation in experimental evolution of haploid budding yeast populations. The rate at which autodiploids fix in these populations appears to vary across strain backgrounds, but the genetic basis of these differences remains poorly characterized. Here we show that the frequency of autodiploidization differs dramatically between two closely related laboratory strains of Saccharomyces cerevisiae, BY4741 and W303. To investigate the genetic basis of this difference, we crossed these strains to generate hundreds of unique F1 segregants and tested the tendency of each segregant to autodiplodize across hundreds of generations of laboratory evolution. We find that variants in the SSD1 gene are the primary genetic determinant of differences in autodiploidization. We then used multiple laboratory and wild strains of S. cerevisiae to show that clonal populations of strains with a functional copy of SSD1 autodiploidize more frequently in evolution experiments, while knocking out this gene or replacing it with the W303 allele reduces autodiploidization propensity across all genetic backgrounds tested. These results suggest a potential strategy for modifying rates of spontaneous whole-genome duplications in laboratory evolution experiments in haploid budding yeast. They may also have relevance to other settings in which eukaryotic genome stability plays an important role, such as biomanufacturing and the treatment of pathogenic fungal diseases and cancers.

evolutionary biology↗

bioRxiv2020

Phenotypic and molecular evolution across 10,000 generations in laboratory budding yeast populations

Laboratory experimental evolution provides a window into the details of the evolutionary process. To investigate the consequences of long-term adaptation, we evolved 205 S. cerevisiae populations (124 haploid and 81 diploid) for [~]10,000 generations in three environments. We measured the dynamics of fitness changes over time, finding repeatable patterns of declining adaptability. Sequencing revealed that this phenotypic adaptation is coupled with a steady accumulation of mutations, widespread genetic parallelism, and historical contingency. In contrast to long-term evolution in E. coli, we do not observe long-term coexistence or populations with highly elevated mutation rates. We find that evolution in diploid populations involves both fixation of heterozygous mutations and frequent loss-of-heterozygosity events. Together, these results help distinguish aspects of evolutionary dynamics that are likely to be general features of adaptation across many systems from those that are specific to individual organisms and environmental conditions.

evolutionary biology↗

bioRxiv2020

Global epistasis emerges from a generic model of a complex trait

Epistasis between mutations can make adaptation contingent on evolutionary history. Yet despite widespread "microscopic" epistasis between the mutations involved, microbial evolution experiments show consistent patterns of fitness increase between replicate lines. Recent work shows that this consistency is driven in part by global patterns of diminishing-returns and increasing-costs epistasis, which make mutations systematically less beneficial (or more deleterious) on fitter genetic backgrounds. However, the mechanistic basis of this "global" epistasis remains unknown. Here we show that diminishing-returns and increasing-costs epistasis emerge generically as a consequence of pervasive microscopic epistasis. Our model predicts a specific quantitative relationship between the magnitude of global epistasis and the stochastic effects of microscopic epistasis, which we confirm by re-analyzing existing data. We further show that the distribution of fitness effects takes on a universal form when epistasis is widespread, and introduce a novel fitness landscape model to show how phenotypic evolution can be repeatable despite sequence-level stochasticity.

evolutionary biology↗

bioRxiv2019

Chance and Necessity in the Pleiotropic Consequences of Adaptation for Budding Yeast

Mutations that a population accumulates during evolution in one ("home") environment may cause fitness gains or losses in other conditions. Such pleiotropic fitness effects determine the evolutionary fate of the population in variable environments and can lead to ecological specialization. It is unclear how the pleiotropic outcomes of evolution are shaped by the intrinsic randomness of the evolutionary process and by the deterministic variation in selection pressures across environments. To address this question, we evolved 20 replicate populations of the yeast Saccharomyces cerevisiae in 11 laboratory environments and measured their fitness across multiple other conditions. We found that evolution in all home environments led to a diversity of patterns of pleiotropic fitness gains and losses, driven by multiple types of mutations. Approximately 60% percent of this variation are explained by clones home environment and the most common parallel genetic changes, while about 40% are attributed to the stochastic accumulation of mutations whose pleiotropic effects are unpredictable. On average, populations specialized to their home environment, but generalists also evolved in almost all conditions. Our results suggest that the mutations accumulating in a home environment incur a variety of pleiotropic effects, from costs to benefits, with different probabilities. Therefore, whether a population evolves towards a specialist or a generalist phenotype is heavily influenced by chance.

evolutionary biology↗

bioRxiv2019

Higher fitness yeast genotypes are less robust to deleterious mutations

Natural selection drives populations towards higher fitness, but second-order selection for adaptability and mutational robustness can also influence the dynamics of adaptation. In many microbial systems, diminishing returns epistasis contributes to a tendency for more-fit genotypes to be less adaptable, but no analogous patterns for robustness are known. To understand how robustness varies across genotypes, we measure the fitness effects of hundreds of individual insertion mutations in a panel of yeast strains. We find that more-fit strains are less robust: they have distributions of fitness effects (DFEs) with lower mean and higher variance. These shifts in the DFE arise because many mutations have more strongly deleterious effects in faster-growing strains. This negative correlation between fitness and robustness implies that second-order selection for robustness will tend to conflict with first-order selection for fitness.

evolutionary biology↗

bioRxiv2018

Distinguishing multiple-merger from Kingman coalescence using two-site frequency spectra

Demographic inference methods in population genetics typically assume that the ancestry of a sample can be modeled by the Kingman coalescent. A defining feature of this stochastic process is that it generates genealogies that are binary trees: no more than two ancestral lineages may coalesce at the same time. However, this assumption breaks down under several scenarios. For example, pervasive natural selection and extreme variation in offspring number can both generate genealogies with "multiple-merger" events in which more than two lineages coalesce instantaneously. Therefore, detecting multiple mergers (and other violations of the Kingman assumptions) is important both for understanding which forces have shaped the diversity of a population and for avoiding fitting misspecified models to data. Current methods to detect multiple mergers in genomic data rely primarily on the site frequency spectrum (SFS). However, the signatures of multiple mergers in the SFS are also consistent with a Kingman coalescent with a time-varying population size. Here, we present a new statistical test for determining whether the Kingman coalescent with any population size history is consistent with population data. Our approach is based on information contained in the two-site joint frequency spectrum (2-SFS) for pairs of linked sites, which has a different dependence on the topologies of genealogies than the SFS. Our statistical test is global in the sense that it can detect when the genome-wide genetic diversity is inconsistent with the Kingman model, rather than detecting outlier regions, as in selection scan methods. We validate this test using simulations, and then apply it to demonstrate that genomic diversity data from Drosophila melanogaster is inconsistent with the Kingman coalescent.

evolutionary biology↗

bioRxiv2017

The effect of strong purifying selection on genetic diversity

Purifying selection reduces genetic diversity, both at sites under direct selection and at linked neutral sites. This process, known as background selection, is thought to play an important role in shaping genomic diversity in natural populations. Yet despite its importance, the effects of background selection are not fully understood. Previous theoretical analyses of this process have taken a backwards-time approach based on the structured coalescent. While they provide some insight, these methods are either limited to very small samples or are computationally prohibitive. Here, we present a new forward-time analysis of the trajectories of both neutral and deleterious mutations at a nonrecombining locus. We find that strong purifying selection leads to remarkably rich dynamics: neutral mutations can exhibit sweep-like behavior, and deleterious mutations can reach substantial frequencies even when they are guaranteed to eventually go extinct. Our analysis of these dynamics allows us to calculate analytical expressions for the full site frequency spectrum. We find that whenever background selection is strong enough to lead to a reduction in genetic diversity, it also results in substantial distortions to the site frequency spectrum, which can mimic the effects of population expansions or positive selection. Because these distortions are most pronounced in the low and high frequency ends of the spectrum, they become particularly important in larger samples, but may have small effects in smaller samples. We also apply our forward-time framework to calculate other quantities, such as the ultimate fates of polymorphisms or the fitnesses of their ancestral backgrounds.

evolutionary biology↗

bioRxiv2017

Novel Magnetic Resonance Imaging strategy targeting Neurotensin Receptors in detection of Prostate Cancer

Prostate cancer is the second leading cause of all male cancer deaths. One of the factors present in malignant prostate cells and shown to support its metastatic growth is the neuropeptide neurotensin (NT). The primary goal of the present study was to establish the feasibility of using a newly developed paramagnetic receptor ligand for NT and non-invasive ultrahigh-field magnetic resonance (MR) imaging to visualize prostate cancer in rodents. Orthotropic xenografts were initiated in six-week old male BALB/c nu/nu athymic mice (n = 28) by intra-prostatic (ventral lobe) inoculation of human prostate cancer cells (10L of PC3 cells (106 /100l)). Palpable tumors developed within 30-60 days. A micro-imager utilized in these studies was an actively shielded 9.4T, 89 mm bore, Oxford superconducting magnet with a 100 gauss/cm gradient system. Prior to contrast injection, T2 weighted anatomy scans were done to localize the tumor with a spin-echo multi-slice sequence with TR: 2000 TE: 40 and NEX: 1 in both coronal and axial planes. The paramagnetic ligand data sets were collected with a spin-echo, T1 weighted pulse sequence (MSME): TR 300 msec; TE 5 msec; NEX 4 in both axial and coronal planes. The data sets were taken initially at 5-min intervals post contrast injection for the first half hour and then at 15 min intervals for the next 1.5-2 hours for a time series analyses. The temporal distribution of MR signal intensity in various regions were determined in the absence and presence of NT. Our results confirm that the novel NT molecule was protected from enzymatic degradation and capable of forming a high affinity paramagnetic NT ligand with an extended half-life. During the imaging studies, the signal intensity increased by 200 % in the region of the tumor. This increase in signal intensity approached maximum binding within 30 minutes and remained visible for 1 hour post-injection of the contrast agent. Taken together, these findings suggest that it is feasible to detect and image prostate cancer using a paramagnetic NT ligand and the emergence of the NT receptor ligand that may be used as a diagnostic marker for prostate cancer in humans.

cancer biology↗

bioRxiv2017

Long-term adaptive evolution of genomically recoded Escherichia coli

Efforts are underway to construct several recoded genomes anticipated to exhibit multi-virus resistance, enhanced non-standard amino acid (NSAA) incorporation, and capability for synthetic biocontainment. Though we succeeded in pioneering the first genomically recoded organism (Escherichia coli strain C321.{Delta}A), its fitness is far lower than that of its non-recoded ancestor, particularly in defined media. This fitness deficit severely limits its utility for NSAA-linked applications requiring defined media such as live cell imaging, metabolic engineering, and industrial-scale protein production. Here, we report adaptive evolution of C321.{Delta}A for more than 1,000 generations in independent replicate populations grown in glucose minimal media. Evolved recoded populations significantly exceed the growth rates of both the ancestral C321.{Delta}A and non-recoded strains, permitting use of the recoded chassis in several new contexts. We use next-generation sequencing to identify genes mutated in multiple independent populations, and we reconstruct individual alleles in ancestral strains via multiplex automatable genome engineering (MAGE) to quantify their effects on fitness. Several selective mutations occur only in recoded evolved populations, some of which are associated with altering the translation apparatus in response to recoding, whereas others are not apparently associated with recoding, but instead correct for off-target mutations that occurred during initial genome engineering. This report demonstrates that laboratory evolution can be applied after engineering of recoded genomes to streamline fitness recovery compared to application of additional targeted engineering strategies that may introduce further unintended mutations. In doing so, we provide the most comprehensive insight to date into the physiology of the commonly used C321.{Delta}A strain.\n\nSignificance StatementAfter demonstrating construction of an organism with an altered genetic code, we sought to evolve this organism for many generations to improve its fitness and learn what unique changes natural selection would bestow upon it. Although this organism initially had impaired fitness, we observed that adaptive laboratory evolution resulted in several selective mutations that corrected for insufficient translation termination and for unintended mutations that occurred when originally altering the genetic code. This work further bolsters our understanding of the pliability of the genetic code, it will help guide ongoing and future efforts seeking to recode genomes, and it results in a useful strain for non-standard amino acid incorporation in numerous contexts relevant for research and industry.

evolutionary biology↗