Biology subjects

Petrov, D.

Publications and source records attributed to Petrov, D..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Prolonged delays in human microbiota transmission after a controlled antibiotic perturbation

Humans constantly encounter new microbes, but few become long-term residents of the adult gut microbiome. Classical theories predict that colonization is determined by the availability of open niches, but it remains unclear whether other ecological barriers limit commensal colonization in natural settings. To disentangle these effects, we used a controlled perturbation with the antibiotic ciprofloxacin to investigate the dynamics of gut microbiome transmission in 22 households of healthy, cohabiting adults. Colonization was rare in three-quarters of antibiotic-taking subjects, whose resident strains rapidly recovered in the week after antibiotics ended. In contrast, the remaining antibiotic-taking subjects exhibited lasting responses, with extensive species losses and transient expansions of potential opportunistic pathogens. These subjects experienced elevated rates of commensal colonization, but only after long delays: many new colonizers underwent sudden, correlated expansions months after the antibiotic perturbation. Furthermore, strains that had previously transmitted between cohabiting partners rarely recolonized after antibiotic disruptions, showing that colonization displays substantial historical contingency. This work demonstrates that there remain substantial ecological barriers to colonization even after major microbiome disruptions, suggesting that dispersal interactions and priority effects limit the pace of community change.

microbiology↗

bioRxiv2023

Strong environmental memory revealed by experimental evolution in static and fluctuating environments

Evolution in a static environment, such as a laboratory setting with constant and uniform conditions, often proceeds via large-effect beneficial mutations that may become maladaptive in other environments. Conversely, natural settings require populations to endure environmental fluctuations. A sensible assumption is that the fitness of a lineage in a fluctuating environment is the time-average of its fitness over the sequence of static conditions it encounters. However, transitions between conditions may pose entirely new challenges, which could cause deviations from this time-average. To test this, we tracked hundreds of thousands of barcoded yeast lineages evolving in static and fluctuating conditions and subsequently isolated 900 mutants for pooled fitness assays in 15 environments. We find that fitness in fluctuating environments indeed often deviates from the expectation based on static components, leading to fitness non-additivity. Moreover, closer examination reveals that fitness in one component of a fluctuating environment is often strongly influenced by the previous component. We show that this environmental memory is especially common for mutants with high variance in fitness across tested environments, even if the components of the focal fluctuating environment are excluded from this variance. We employ a simple mathematical model and whole-genome sequencing to propose mechanisms underlying this effect, including lag time evolution and sensing mutations. Our results demonstrate that environmental fluctuations have large impacts on fitness and suggest that variance in static environments can explain these impacts.

evolutionary biology↗

bioRxiv2023

Far From Home: Evolution of haploid and diploid populations reveals common, strong, and variable pleiotropic effects in non-home environments

Adaptation is driven by the selection for beneficial mutations that provide a fitness advantage in the specific environment in which a population is evolving. However, environments are rarely constant or predictable. When an organism well adapted to one environment finds itself in another, pleiotropic effects of mutations that made it well adapted to its former environment will affect its success. To better understand such pleiotropic effects, we evolved both haploid and diploid barcoded budding yeast populations in multiple environments, isolated adaptive clones, and then determined the fitness effects of adaptive mutations in "non-home" environments in which they were not selected. We find that pleiotropy is common, with most adaptive evolved lineages showing fitness effects in non-home environments. Consistent with other studies, we find that these pleiotropic effects are unpredictable: they are beneficial in some environments and deleterious in others. However, we do find that lineages with adaptive mutations in the same genes tend to show similar pleiotropic effects. We also find that ploidy influences the observed adaptive mutational spectra in a condition-specific fashion. In some conditions, haploids and diploids are selected with adaptive mutations in identical genes, while in others they accumulate mutations in almost completely disjoint sets of genes.

evolutionary biology↗

bioRxiv2022

Extreme sensitivity of fitness to environmental conditions; lessons from #1BigBatch

The phrase "survival of the fittest" has become an iconic descriptor of how natural selection works. And yet, precisely measuring fitness, even for single-celled microbial populations growing in controlled laboratory conditions, remains a challenge. While numerous methods exist to perform these measurements, including recently developed methods utilizing DNA barcoding, all methods seem limited in their precision to differentiate strains with small fitness differences. This limit on precision is relevant in many fields, including the field of experimental evolution. In this study, we hone in on the factors that contribute to noisy fitness measurements and suggest solutions to avoid certain sources of noise. Surprisingly, even when common sources of technical noise are controlled for, we find that fitness measurements are still very noisy. Our data suggest that subtle environmental differences among replicates create substantial variation across fitness measurements. We conclude by providing best practices for obtaining precise fitness measurements and by discussing how these measurements should be interpreted given their extreme context dependence. This work was inspired by the scientific community who followed us and gave us tips as we live-tweeted a high-replicate fitness measurement experiment at #1BigBatch.

evolutionary biology↗

bioRxiv2022

Cancers adapt to their mutational load by buffering protein misfolding stress

In asexual populations that dont undergo recombination, such as cancer, deleterious mutations are expected to accrue readily due to genome-wide linkage between mutations. Despite this mutational load of often thousands of deleterious mutations, many tumors thrive. How tumors survive the damaging consequences of this mutational load is not well understood. Here, we investigate the functional consequences of mutational load in 10,295 human tumors by quantifying their phenotypic response through changes in gene expression. Using a generalized linear mixed model (GLMM), we find that high mutational load tumors up-regulate proteostasis machinery related to the mitigation and prevention of protein misfolding. We replicate these expression responses in cancer cell lines and show that the viability in high mutational load cancer cells is strongly dependent on complexes that degrade and refold proteins. This indicates that upregulation of proteostasis machinery is causally important for high mutational burden tumors and uncovers new therapeutic vulnerabilities. Statement of SignificanceCancers can successfully survive an accumulation of thousands of protein-damaging mutations. Here, we show that high mutational load tumors mitigate these damaging consequences by up-regulating complexes that buffer against protein misfolding stress - providing novel therapeutic vulnerabilities and suggesting that disruption of proteostasis is a hallmark of somatic evolution.

cancer biology↗

bioRxiv2021

Multiplexed identification of RAS paralog imbalance as a driver of lung cancer growth

Oncogenic KRAS mutations occur in approximately 30% of lung adenocarcinoma. Despite several decades of effort, oncogenic KRAS-driven lung cancer remains difficult to treat, and our understanding of the positive and negative regulators of RAS signaling is incomplete. To uncover the functional impact of diverse KRAS-interacting proteins on lung cancer growth in vivo, we used multiplexed somatic CRISPR/Cas9-based genome editing in genetically engineered mouse models with tumor barcoding and high-throughput barcode sequencing. Through a series of CRISPR/Cas9 screens in autochthonous lung tumors, we identified HRAS and NRAS as key suppressors of KRASG12D-driven tumor growth in vivo and confirmed these effects in oncogenic KRAS-driven human lung cancer cell lines. Mechanistically, RAS paralogs interact with oncogenic KRAS, suppress KRAS-KRAS interactions, and reduce downstream ERK signaling. HRAS mutations identified in KRAS-driven human tumors partially abolished this effect. Comparison of the tumor-suppressive effects of HRAS and NRAS in KRAS- and BRAF-driven lung cancer models confirmed that RAS paralogs are specific suppressors of oncogenic KRAS-driven lung cancer in vivo. Our study outlines a technological avenue to uncover positive and negative regulators of oncogenic KRAS-driven cancer in a multiplexed manner in vivo and highlights the role of RAS paralog imbalance in oncogenic KRAS-driven lung cancer.

cancer biology↗

bioRxiv2021

Note: Updating the metadata of four misidentified samples in the DrosRTEC dataset

This note details the consortiums rationale behind its decision to modify the metadata for putatively misidentified European samples in the DrosRTEC dataset. In brief, we use PCA on published datasets from North America and Europe to generate phylogeographic clusters reflective of worldwide D. melanogaster demography. We used this PCA to train a DAPC model in order the predict the group membership. Our results indicate that 4 out of 73 samples were misclassified and the metadata was updated accordingly. These samples are a spring-fall pair from Spain and Austria.

genomics↗

bioRxiv2020

Widespread introgression across a phylogeny of 155 Drosophila genomes

Genome-scale sequence data have invigorated the study of hybridization and introgression, particularly in animals. However, outside of a few notable cases, we lack systematic tests for introgression at a larger phylogenetic scale across entire clades. Here we leverage 155 genome assemblies, from 149 species, to generate a fossil-calibrated phylogeny and conduct multilocus tests for introgression across nine monophyletic radiations within the genus Drosophila. Using complementary phylogenomic approaches, we identify widespread introgression across the evolutionary history of Drosophila. Mapping gene-tree discordance onto the phylogeny revealed that both ancient and recent introgression has occurred across most of the nine clades that we examined. Our results provide the first evidence of introgression occurring across the evolutionary history of Drosophila and highlight the need to continue to study the evolutionary consequences of hybridization and introgression in this genus and across the Tree of Life.

evolutionary biology↗

bioRxiv2020

A genotype-phenotype-fitness map reveals local modularity and global pleiotropy of adaptation

Building a genotype-phenotype-fitness map of adaptation is a central goal in evolutionary biology. It is notoriously difficult even when the adaptive mutations are known because it is hard to enumerate which phenotypes make these mutations adaptive. We address this problem by first quantifying how the fitness of hundreds of adaptive yeast mutants responds to subtle environmental shifts and then modeling the number of phenotypes they must collectively influence by decomposing these patterns of fitness variation. We find that a small number of phenotypes predicts fitness of the adaptive mutations near their original glucose-limited evolution condition. Importantly, phenotypes that matter little to fitness at or near the evolution condition can matter strongly in distant environments. This suggests that adaptive mutations are locally modular--affecting a small number of phenotypes that matter to fitness in the environment where they evolved--yet globally pleiotropic--affecting additional phenotypes that may reduce or improve fitness in new environments.

evolutionary biology↗

bioRxiv2020

Genetic determinants of EGFR-Driven Lung Cancer Growth and Therapeutic Response In Vivo

Cancer genome sequencing has uncovered substantial complexity in the mutational landscape of tumors. Given this complexity, experimental approaches are necessary to establish the impact of combinations of genetic alterations on tumor biology and to uncover genotype-dependent effects on drug sensitivity. In lung adenocarcinoma, EGFR mutations co-occur with many putative tumor suppressor gene alterations, however the extent to which these alterations contribute to tumor growth and their response to therapy in vivo has not been explored experimentally. By integrating a novel mouse model of oncogenic EGFR-driven Trp53-deficient lung adenocarcinoma with multiplexed CRISPR-Cas9-mediated genome editing and tumor barcode sequencing, we quantified the effects of inactivation of ten putative tumor suppressor genes. Inactivation of Apc, Rb1, or Rbm10 most strongly promoted tumor growth. Unexpectedly, inactivation of Lkb1 or Setd2 - which are the strongest drivers of tumor growth in an oncogenic Kras-driven model - reduced EGFR-driven tumor growth. These results are consistent with the relative frequency of these tumor suppressor gene alterations in human EGFR- and KRAS-driven lung adenocarcinomas. Furthermore, Keap1 inactivation reduces the sensitivity of EGFR-driven Trp53-deficient tumors to the EGFR inhibitor osimertinib. Importantly, in human EGFR/TP53 mutant lung adenocarcinomas, mutations in the KEAP1 pathway correlated with decreased time on tyrosine kinase inhibitor treatment. Our study highlights how genetic alterations can have dramatically different biological consequences depending on the oncogenic context and that the fitness landscape can shift upon drug treatment.

cancer biology↗

bioRxiv2020

Ancient RNA virus epidemics through the lens of recent adaptation in human genomes

Over the course of the last several million years of evolution, humans likely have been plagued by hundreds or perhaps thousands of epidemics. Little is known about such ancient epidemics and a deep evolutionary perspective on current pathogenic threats is lacking. The study of past epidemics has typically been limited in temporal scope to recorded history, and in physical scope to pathogens that left sufficient DNA behind, such as Yersinia pestis during the Great Plague. Host genomes however offer an indirect way to detect ancient epidemics beyond the current temporal and physical limits. Arms races with pathogens have shaped the genomes of the hosts by driving a large number of adaptations at many genes, and these signals can be used to detect and further characterize ancient epidemics. Here, we detect the genomic footprints left by ancient viral epidemics that took place in the past ~50,000 years in the 26 human populations represented in the 1,000 Genomes Project. By using the enrichment in signals of adaptation at ~4,500 host loci that interact with specific types of viruses, we provide evidence that RNA viruses have driven a particularly large number of adaptive events across diverse human populations. These results suggest that different types of viruses may have exerted different selective pressures during human evolution. Knowledge of these past selective pressures will provide a deeper evolutionary perspective on current pathogenic threats.

evolutionary biology↗

bioRxiv2020

Quantitative in vivo analyses reveal a complex pharmacogenomic landscape in lung adenocarcinoma

AbstractThe lack of knowledge about the relationship between tumor genotypes and therapeutic responses remains one of the most important gaps in enabling the effective use of cancer therapies. Here, we couple a multiplexed and quantitative platform with robust statistical methods to enable pharmacogenomic mapping of lung cancer treatment responses in vivo. We uncover a surprisingly complex map of genotype-specific therapeutic responses, with over 20% of possible interactions showing significant resistance or sensitivity. We validate one of these interactions - the resistance of Keap1 mutant tumors to platinum therapy - using a large patient response dataset. Our results highlight the importance of understanding the genetic determinants of treatment responses in the development of precision therapies and define a strategy to identify such determinants.

cancer biology↗

bioRxiv2019

Most cancers carry a substantial deleterious load due to Hill-Robertson interference

Cancer genomes exhibit surprisingly weak signatures of negative selection1,2. This may be because selective pressures are relaxed or because genome-wide linkage prevents deleterious mutations from being removed (Hill-Robertson interference)3. By stratifying tumors by their genome-wide mutational burden, we observe negative selection (dN/dS ~ 0.47) in low mutational burden tumors, while remaining cancers exhibit dN/dS ratios ~1. This suggests that most tumors do not remove deleterious passengers. To buffer against deleterious passengers, tumors upregulate heat shock pathways as their mutational burden increases. Finally, evolutionary modeling finds that Hill-Robertson interference alone can reproduce patterns of attenuated selection and estimates the total fitness cost of passengers to be 40% per cell on average. Collectively, our findings suggest that the lack of observed negative selection in most tumors is not due to relaxed selective pressures, but rather the inability of selection to remove deleterious mutations in the presence of genome-wide linkage.

evolutionary biology↗

bioRxiv2019

Long live the king: chromosome-level assembly of the lion (Panthera leo) using linked-read, Hi-C, and long read data

The lion (Panthera leo) is one of the most popular and iconic feline species on the planet, yet in spite of its popularity, the last century has seen massive declines for lion populations worldwide. Genomic resources for endangered species represent an important way forward for the field of conservation, enabling high-resolution studies of demography, disease, and population dynamics. Here, we present a chromosome-level assembly for the captive African lion from the Exotic Feline Rescue Center as a resource for current and subsequent genetic work of the sole social species of the Panthera clade. Our assembly is composed of 10x Genomics Chromium data, Dovetail Hi-C, and Oxford Nanopore long-read data. Synteny is highly conserved between the lion, other Panthera genomes, and the domestic cat. We find variability in the length and levels of homozygosity across the genomes of the lion sequenced here and other previous published resequence data, indicating contrasting histories of recent and ancient small population sizes and/or inbreeding. Demographic analyses reveal similar histories across all individuals except the Asiatic lion, which shows a more rapid decline in population size. This high-quality genome will greatly aid in the continuing research and conservation efforts for the lion.

genomics↗

bioRxiv2019

Recent evolutionary history of tigers highlights contrasting roles of genetic drift and selection

Formulating strategies for species conservation requires knowledge of evolutionary and genetic history. Tigers are among the most charismatic of endangered species and garner significant conservation attention. However, the evolutionary history and genomic variation of tigers remain poorly known. With 70% of the worlds wild tigers living in India, such knowledge is critical for tiger conservation. We re-sequenced 65 individual tiger genomes across their extant geographic range, representing most extant subspecies with a specific focus on tigers from India. As suggested by earlier studies, we found strong genetic differentiation between the putative tiger subspecies. Despite high total genomic diversity in India, individual tigers host longer runs of homozygosity, potentially suggesting recent inbreeding, possibly because of small and fragmented protected areas. Surprisingly, demographic models suggest recent divergence (within the last 10,000 years) between populations, and strong population bottlenecks. Amur tiger genomes revealed the strongest signals of selection mainly related to metabolic adaptation to cold, while Sumatran tigers show evidence of evolving under weak selection for genes involved in body size regulation. Depending on conservation objectives, our results support the isolation of Amur and Sumatran tigers, while geneflow between Malayan and South Asian tigers may be considered. Further, the impacts of ongoing connectivity loss on the health and persistence of tigers in India should be closely monitored.

genomics↗

bioRxiv2019

Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia

Active retrotransposons in the human genome (L1, Alu and SVA elements) can create genomic mobile element insertions (MEIs) in both germline and somatic tissue1. Specific somatic MEIs have been detected at high levels in human cancers2, and at lower to medium levels in human brains3. Dysregulation of somatic retrotransposition in the human brain has been hypothesized to contribute to neuropsychiatric diseases4, 5. However, individual somatic MEIs are present in small proportions of cells at a given anatomical location, and thus standard whole-genome sequencing (WGS) presents a difficult signal-to-noise problem, while single-cell approaches suffer from limited scalability and experimental artifacts introduced by enzymatic whole-genome amplification6. Previous studies produced widely differing estimates for the somatic retrotransposition rates in human brain3, 6-8. Here, we present a highly precise machine learning method (RetroSom) to directly identify somatic L1 and Alu insertions in <1% cells from 200x deep WGS, which allows circumventing the restrictions of whole-genome amplification. Using RetroSom we confirmed a lower rate of retrotransposition for individual somatic L1 insertions in human neurons. We discovered that anatomical distribution of somatic L1 insertion is as widespread in glia as in neurons, and across both hemispheres of the brain, indicating retrotransposition occurs during early embryogenesis. We characterized two of the detected brain-specific L1 insertions in great detail in neurons and glia from a donor with schizophrenia. Both insertions are within introns of genes active in brain (CNNM2, FRMD4A) in regions with multiple genetic associations with neuropsychiatric disorders9-11. Gene expression was significantly reduced by both somatic insertions in a reporter assay. Our results provide novel insights into the potential for pathological effects of somatic retrotransposition in the human brain, now including the large glial fraction. RetroSom has broad applicability in all disease states where somatic retrotransposition is expected to play a role, such as autoimmune disorders and cancer.

bioinformatics↗

bioRxiv2019

Reconsidering the management paradigm of fragmented populations

Habitat fragmentation and population declines call for informed management of many endangered species. The dominant paradigm for such management focuses on avoiding deleterious inbreeding effects in separated populations, by facilitating migration to maintain connectivity between them, an approach epitomized by the \"one migrant per generation\" rule. We show that this paradigm fails to take into account two important factors. First, it ignores an inherent trade-off: maintaining within-population genetic diversity is at the expense of maintaining global diversity. Migration increases local within-population genetic diversity, but also homogenizes the meta-population, which may lead to erosion of global genetic diversity. Second, this paradigm does not consider that because many fragmented species have declined in numbers only within the last century, they still carry much of the high genetic diversity characteristic of the historically large population. The conservation of a species global diversity, crucial for evolutionarily adaptation to ecological challenges such as epidemics, industrial pollutants, or climate change, is paramount to a species long-term survival. Here we discuss how consideration of these factors can inform management of fragmented populations and provide a framework to assess the impact on genetic diversity of different management strategies. We also propose two alternative management strategies to replace the \"one migrant per generation\" dogma.

ecology↗

bioRxiv2019

A Porcine Model of Peripheral Nerve Injury Enabling Ultra-Long Regenerative Distances: Surgical Approach, Recovery Kinetics, and Clinical Relevance

Approximately 20 million Americans currently experience residual deficits from traumatic peripheral nerve injury. Despite recent advancements in surgical technique, peripheral nerve repair typically results in poor functional outcomes due to prolonged periods of denervation resulting from long regenerative distances coupled with relatively slow rates of axonal regeneration. Development of novel surgical solutions requires valid preclinical models that adequately replicate the key challenges of clinical peripheral nerve injury. Our team has developed a porcine model using Yucatan minipigs that provides an opportunity to investigate peripheral nerve regeneration using different nerves tailored for a specific mechanism of interest, such as (1) nerve modality: motor, sensory, and mixed-modality; (2) injury length: short versus long gap; and (3) total regenerative distance: proximal versus distal injury. Here, we describe a comprehensive porcine model of two challenging clinically relevant procedures for repair of long segmental lesions ([≥] 5 cm) - the deep peroneal nerve repaired using a sural nerve autograft and the common peroneal nerve repaired using a saphenous nerve autograft - each featuring ultra-long total regenerative distances (up to 20 cm and 27 cm, respectively) to reach distal targets. This paper includes a detailed characterization of the relevant anatomy, surgical approach/technique, functional/electrophysiological outcomes, and nerve morphometry for baseline and autograft repaired nerves. These porcine models of major peripheral nerve injury are suitable as preclinical, translatable models for evaluating the efficacy, safety, and tolerability of next-generation artificial nerve grafts prior to clinical deployment.

neuroscience↗