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Kosakovsky Pond, S. L.

Publications and source records attributed to Kosakovsky Pond, S. L..

32 records · Page 2Linked to original sources
bioRxiv2021

Recent zoonotic spillover and tropism shift of a Canine Coronavirus is associated with relaxed selection and putative loss of function in NTD subdomain of spike protein.

A recent study reported the occurrence of Canine Coronavirus (CCoV) in nasopharyngeal swabs from a small number of patients hospitalized with pneumonia during a 2017-18 period in Sarawak, Malaysia. Because the genome sequence for one of these isolates is available, we conducted comparative evolutionary analyses of the spike gene of this strain (CCoV-HuPn-2018), with other available Alphacoronavirus 1 spike sequences. The most N-terminus subdomain (0-domain) of the CCoV-HuPn-2018 spike protein has sequence similarity to Transmissible Gastroenteritis Virus (TGEV) and CCoV2b strains, but not to other members of the type II Alphacoronaviruses (i.e., CCoV2a and Feline CoV2-FCoV2). This 0-domain in CCoV-HuPn-2018 has evidence for relaxed selection pressure, an increased rate of molecular evolution, and a number of unique amino acid substitutions relative to CCoV2b and TGEV sequences. A region of the 0-domain determined to be key to sialic acid binding and pathogenesis in TGEV had clear differences in amino acid sequences in CCoV-HuPn-2018 relative to both CCoV2b (enteric) and TGEV (enteric and respiratory). The 0-domain of CCoV-HuPn-2018 also had several sites inferred to be under positive diversifying selection, including sites within the signal peptide. Downstream of the 0-domain, FCoV2 shared sequence similarity to the CCoV2b and TGEV sequences, with analyses of this larger alignment identifying positively selected sites in the putative Receptor Binding Domain (RBD) and Connector Domain (CD). Recombination analyses strongly implicated a particular FCoV2 strain in the recombinant history of CCoV-HuPn-2018 with molecular divergence times estimated at around 60 years ago. We hypothesize that CCoV-HuPn-2018 had an enteric origin, but that it has lost that particular tropism, because of mutations in the sialic acid binding region of the spike 0-domain. As selection pressure on this region was reduced, the virus evolved a respiratory tropism, analogous to other Alphacoronavirus 1, such as Porcine Respiratory Coronavirus (PRCV), that have lost this region entirely. We also suggest that signals of positive selection in the signal peptide as well as other changes in the 0-domain of CCoV-HuPn-2018 could represent an adaptive role in this new host and that this could be in part due to the different spatial distribution of the N-linked glycan repertoire for this strain.

evolutionary biology↗
bioRxiv2021

Identification of site-specific evolutionary trajectories shared across human betacoronaviruses

Comparing the evolution of distantly related viruses can provide insights into common adaptive processes related to shared ecological niches. Phylogenetic approaches, coupled with other molecular evolution tools, can help identify mutations informative on adaptation, whilst the structural contextualization of these to functional sites of proteins may help gain insight into their biological properties. Two zoonotic betacoronaviruses capable of sustained human-to-human transmission have caused pandemics in recent times (SARS-CoV-1 and SARS-CoV-2), whilst a third virus (MERS-CoV) is responsible for sporadic outbreaks linked to animal infections. Moreover, two other betacoronaviruses have circulated endemically in humans for decades (HKU1 and OC43). To search for evidence of adaptive convergence between established and emerging betacoronaviruses capable of sustained human-to-human transmission (HKU1, OC43, SARS-CoV-1 and SARS-CoV-2), we developed a methodological pipeline to classify shared non-synonymous mutations as putatively denoting homoplasy (repeated mutations that do not share direct common ancestry) or stepwise evolution (sequential mutations leading towards a novel genotype). In parallel, we look for evidence of positive selection, and draw upon protein structure data to identify potential biological implications. We find 30 mutations, with four of these [codon sites 18121 (nsp14/residue 28), 21623 (spike/21), 21635 (spike/25) and 23948 (spike/796); SARS-CoV-2 genome numbering] displaying evolution under positive selection and proximity to functional protein regions. Our findings shed light on potential mechanisms underlying betacoronavirus adaptation to the human host and pinpoint common mutational pathways that may occur during establishment of human endemicity.

evolutionary biology↗
bioRxiv2020

An evolutionary portrait of the progenitor SARS-CoV-2 and its dominant offshoots in COVID-19 pandemic

We report the likely most recent common ancestor of SARS-CoV-2 - the coronavirus that causes COVID-19. This progenitor SARS-CoV-2 genome was recovered through a novel application and advancement of computational methods initially developed to reconstruct the mutational history of tumor cells in a patient. The progenitor differs from the earliest coronaviruses sampled in China by three variants, implying that none of the earliest patients represent the index case or gave rise to all the human infections. However, multiple coronavirus infections in China and the USA harbored the progenitor genetic fingerprint in January 2020 and later, suggesting that the progenitor was spreading worldwide as soon as weeks after the first reported cases of COVID-19. Mutations of the progenitor and its offshoots have produced many dominant coronavirus strains, which have spread episodically over time. Fingerprinting based on common mutations reveals that the same coronavirus lineage has dominated North America for most of the pandemic. There have been multiple replacements of predominant coronavirus strains in Europe and Asia and the continued presence of multiple high-frequency strains in Asia and North America. We provide a continually updating dashboard of global evolution and spatiotemporal trends of SARS-CoV-2 spread (http://sars2evo.datamonkey.org/).

evolutionary biology↗
bioRxiv2020

Genomics of a killifish from the Seychelles islands supports transoceanic island colonization and reveals relaxed selection of developmental genes

How freshwater fish colonize remote islands remains an evolutionary puzzle. Tectonic drift and trans-oceanic dispersal models have been proposed as possible alternative mechanisms. Integrating dating of known tectonic events with population genetics and experimental test of salinity tolerance in the Seychelles islands golden panchax (Pachypanchax playfairii), we found support for trans-oceanic dispersal being the most likely scenario. At the macroevolutionary scale, the non-annual killifish golden panchax shows stronger genome-wide purifying selection compared to annual killifishes from continental Africa. Reconstructing past demographies in isolated golden panchax populations provides support for decline in effective population size, which could have allowed slightly deleterious mutations to segregate in the population. Unlike annual killifishes, where relaxed selection preferentially targets aging-related genes, relaxation of purifying selection in golden panchax affects genes involved in developmental processes, including fgf10.

evolutionary biology↗
bioRxiv2020

Evidence of significant natural selection in the evolution of SARS-CoV-2 in bats, not humans

RNA viruses are proficient at switching host species, and evolving adaptations to exploit the new hosts cells efficiently. Surprisingly, SARS-CoV-2 has apparently required no significant adaptation to humans since the start of the COVID-19 pandemic, with no observed selective sweeps since genome sampling began. Here we assess the types of natural selection taking place in Sarbecoviruses in horseshoe bats versus SARS-CoV-2 evolution in humans. While there is moderate evidence of diversifying positive selection in SARS-CoV-2 in humans, it is limited to the early phase of the pandemic, and purifying selection is much weaker in SARS-CoV-2 than in related bat Sarbecoviruses. In contrast, our analysis detects significant positive episodic diversifying selection acting on the bat virus lineage SARS-CoV-2 emerged from, accompanied by an adaptive depletion in CpG composition presumed to be linked to the action of antiviral mechanisms in ancestral hosts. The closest bat virus to SARS-CoV-2, RmYN02 (sharing an ancestor [~]1976), is a recombinant with a structure that includes differential CpG content in Spike; clear evidence of coinfection and evolution in bats without involvement of other species. Collectively our results demonstrate the progenitor of SARS-CoV-2 was capable of near immediate human-human transmission as a consequence of its adaptive evolutionary history in bats, not humans.

evolutionary biology↗
bioRxiv2020

Contrast-FEL: a test for differences in selective pressures at individual sites among clades and sets of branches.

A number of evolutionary hypotheses can be tested by comparing selective pressures among sets of branches in a phylogenetic tree. When the question of interest is to identify specific sites within genes that may be evolving differently, a common approach is to perform separate analyses on subsets of sequences, and compare parameter estimates in a post hoc fashion. This approach is statistically suboptimal, and not always applicable. Here, we develop a simple extension of a popular fixed effects likelihood method in the context of codon-based evolutionary phylogenetic maximum likelihood testing, Contrast-FEL. It is suitable for identifying individual alignment sites where any among the K [≥] 2 sets of branches in a phylogenetic tree have detectably different dN/dS ratios, indicative of different selective regimes. Using extensive simulations, we show that Contrast-FEL delivers good power, exceeding 90% for sufficiently large differences, while maintaining tight control over false positive rates. We conclude by applying Contrast-FEL to data from five previously published studies spanning a diverse range of organisms and focusing on different evolutionary questions.

bioinformatics↗
bioRxiv2020

Extra base hits: widespread empirical support for instantaneous multiple-nucleotide changes

Despite many attempts to introduce evolutionary models that permit substitutions that instantly alter more than one nucleotide in a codon, the prevailing wisdom remains that such changes are rare and generally negligible (or are reflective of non-biological artifacts, such as alignment errors), and codon models continue to posit that only single nucleotide change have non-zero rates. We develop and test a simple hierarchy of codon-substitution models with non-zero evolutionary rates for only one-nucleotide (1H), one- and two-nucleotide (2H), or any (3H) codon substitutions. Using 35,000 empirical alignments, we find widespread statistical support for multiple hits: 58% of alignments prefer models with 2H allowed, and 22% - with 3H allowed. Analyses of simulated data suggest that these results are not likely to be due to simple artifacts such as model misclassification or alignment errors. Further modeling revealed that synonymous codon island jumping among codons encoding serine, especially along short branches, contributes significantly to this 3H signal. While serine codons were prominently involved in multiple-hit substitutions, there were other common exchanges contributing to better model fit. It appears that a small subset of sites in most alignments have unusual evolutionary dynamics not well explained by existing model formalisms, and that commonly estimated quantities, such as dN/dS ratios may be biased by model misspecification. Our findings highlight the need for continued evaluation of assumptions underlying workhorse evolutionary models and subsequent evolutionary inference techniques. We provide a software implementation for evolutionary biologists to assess the potential impact of extra base hits in their data in the HyPhy package.

bioinformatics↗
bioRxiv2020

No more business as usual: agile and effective responses to emerging pathogen threats require open data and open analytics

The current state of much of the Wuhan pneumonia virus (COVID-19) research shows a regrettable lack of data sharing and considerable analytical obfuscation. This impedes global research cooperation, which is essential for tackling public health emergencies, and requires unimpeded access to data, analysis tools, and computational infrastructure. Here we show that community efforts in developing open analytical software tools over the past ten years, combined with national investments into scientific computational infrastructure, can overcome these deficiencies and provide an accessible platform for tackling global health emergencies in an open and transparent manner. Specifically, we use all COVID-19 genomic data available in the public domain so far to (1) underscore the importance of access to raw data and to (2) demonstrate that existing community efforts in curation and deployment of biomedical software can reliably support rapid, reproducible research during global health crises. All our analyses are fully documented at https://github.com/galaxyproject/SARS-CoV-2.

evolutionary biology↗
bioRxiv2020

Deep Sequencing Reveals Compartmentalized HIV-1 in the Semen of Men with and without STI-associated Urethritis

Concurrent sexually transmitted infections (STI) can increase the probability of HIV-1 transmission primarily by increasing the viral load present in semen. In this study, we explored the relationship of HIV-1 in blood and seminal plasma in the presence and absence of urethritis and after treatment of the concurrent STI. Primer ID deep sequencing of the V1/V3 region of the HIV-1 env gene was done for paired blood and semen samples from ART-naive men living in Malawi with (n = 19) and without (n = 5) STI-associated urethritis; for a subset of samples full length env genes were generated for sequence analysis and to test entry phenotype. Cytokine concentrations in the blood and semen were also measured, and a reduction in the levels of pro-inflammatory cytokines was observed following STI treatment. We observed no difference in the prevalence of diverse compartmentalized semen-derived lineages in men with or without STI-associated urethritis, and these viral populations were largely stable during STI treatment. Clonal amplification of one or a few viral sequences accounted for nearly 50% of the viral population indicating a recent bottleneck followed by limited viral replication. We documented a case of superinfection where the new strain was restricted to the genital tract. We conclude that the male genital tract is a site where virus can be brought in from the blood, where localized sustained replication can occur, where a superinfecting strain can persist, and where specific genotypes can be amplified perhaps initially by cellular proliferation but further by limited viral replication. ImportanceHIV-1 is a sexually transmitted infection that co-exists with other STIs. Here we examine the impact of a concurrent STI resulting in urethritis on the HIV-1 population within the male genital tract. We found that viral populations remain largely stable even with treatment of the STI. These results show that viral populations within the male genital tract are defined by factors beyond transient inflammation associated with a concurrent STI.

microbiology↗
bioRxiv2019

Analysis of unusual and signature APOBEC-mutations in HIV-1 pol next-generation sequences

IntroductionAt low mutation-detection thresholds, next generation sequencing (NGS) for HIV-1 genotypic resistance testing is susceptible to artifactual detection of mutations arising from PCR error and APOBEC-mediated G-to-A hypermutation.\n\nMethodsWe analyzed published HIV-1 pol Illumina NGS data to characterize the distribution of mutations at eight NGS thresholds: 20%, 10%, 5%, 2%, 1%, 0.5%, 0.2%, and 0.1%. At each threshold, we determined the proportion of amino acid mutations that were unusual (defined as having a prevalence <0.01% in HIV-1 group M sequences) or were signature APOBEC mutations.\n\nResultsEight studies, containing 855 samples, in the NCBI Sequence Read Archive were analyzed. As detection thresholds were lowered, there was a progressive increase in the proportion of positions with both usual and unusual mutations and in the proportion of all mutations that were unusual. The median proportion of positions with an unusual mutation increased gradually from 0% at the 20% threshold to 0.3% at the 1% threshold and then exponentially to 1.3% (0.5% threshold), 6.9% (0.2% threshold), and 23.2% (0.1% threshold). In two of three studies with available plasma HIV-1 RNA levels, the proportion of positions with unusual mutations was negatively associated with virus levels. Although the complete set of signature APOBEC mutations was much smaller than that of unusual mutations, the former outnumbered the latter in one-sixth of the samples at the 0.5%, 1%, and 2% thresholds.\n\nConclusionsThe marked increase in the proportion of positions with unusual mutations at thresholds below 1% and in samples with lower virus loads suggests that, at low thresholds, many unusual mutations are artifactual, reflecting PCR error or G-to-A hypermutation. Profiling the numbers of unusual and signature APOBEC pol mutations at different NGS thresholds may be useful to avoid selecting a threshold that is too low and poses an unacceptable risk of identifying artifactual mutations.

bioinformatics↗
bioRxiv2019

A new method for inferring timetrees from temporally sampled molecular sequences

Pathogen timetrees are phylogenies scaled to time. They reveal the temporal history of a pathogen spread through the populations as captured in the evolutionary history of strains. These timetrees are inferred by using molecular sequences of pathogenic strains sampled at different times. That is, temporally sampled sequences enable the inference of sequence divergence times. Here, we present a new approach (RelTime with Dated Tips [RTDT]) to estimating pathogen timetrees based on the relative rate framework underlying the RelTime approach. RTDT does not require many of the priors demanded by Bayesian approaches, and it has light computing requirements. We found RTDT to be accurate on simulated datasets evolved under a variety of branch rates models. Interestingly, we found two non-Bayesian methods (RTDT and Least Squares Dating [LSD]) to perform similar to or better than the Bayesian approaches available in BEAST and MCMCTree programs. RTDT method was found to generally outperform all other methods for phylogenies in with autocorrelated evolutionary rates. In analyses of empirical datasets, RTDT produced dates that were similar to those from Bayesian analyses. Speed and accuracy of the new method, as compared to the alternatives, makes it appealing for analyzing growing datasets of pathogenic strains. Cross-platform MEGA X software, freely available from http://www.megasoftware.net, now contains the new method for use through a friendly graphical user interface and in high-throughput settings.\n\nAUTHOR SUMMARYPathogen timetrees trace the origins and evolutionary histories of strains in populations, hosts, and outbreaks. The tips of these molecular phylogenies often contain sampling time information because the sequences were generally obtained at different times during the disease outbreaks and propagation. We have developed a new method for inferring timetrees for phylogenies with tip dates, which improves on widely-used Bayesian methods (e.g., BEAST) in computational efficiency and does not require prior specification of population parameters, branch rate model, or clock model. We performed extensive computer simulation and found that RTDT performed better than the other methods for the estimation of divergence times at deep node in phylogenies where evolutionary rates were autocorrelated. The new method is available in the cross-platform MEGA software package that provides a graphical user interface, and allows use via a command line in scripting and high throughput analysis (www.megasoftware.net).

evolutionary biology↗
bioRxiv2018

Monocyte Infection Dynamics Shape HIV-1 Phyloanatomy in the Peripheral Blood

Human immunodeficiency virus (HIV) RNA and DNA have been isolated from patient monocytes, an immune cell population that is quite different in several aspects from the canonical T-cell viral target. Because monocytes are migratory and resilient to both natural and synthetic antiviral defenses, knowledge of the contribution of monocyte infection to ongoing viral evolution and spread in vivo is of significant interest for drug development and treatment strategies. Using single viral genome sequencing from different peripheral blood compartments and phyloanatomic statistical inference, we demonstrate that productively infected monocytes follow an evolutionary trajectory that is distinct from peripheral T cells during multiple stages of disease progression. Gene flow and selection analysis reveal plasticity in the source of monocyte infection and in the region of the HIV envelope glycoprotein that experiences selection pressure across individuals. The findings, thus, point to a potential reservoir showing a range of infection and transmission dynamics, for which the current universal, T cell-targeted treatment strategies would be inadequate.\n\nAuthor summaryHuman immunodeficiency virus is a rapidly evolving virus, allowing its genetic material to act as a fingerprint for epidemiological processes among, as well as within, individual infected hosts. In this study, sampling of viral RNA from plasma and differing infected immune cell populations from the peripheral blood was undertaken for three separate individuals in order to infer such processes. The results revealed a productively infected monocyte cell population, for which distinct selection pressures were linked to differing spatiotemporal origins of infection. In light of previous evidence of the migratory nature of these cells and resilience to both natural and synthetic antiviral defenses, this study underscores the importance of further investigation into the role of monocytes, and monocyte-rich tissues, as viral reservoirs during treatment of HIV with antiretroviral therapy.

evolutionary biology↗
bioRxiv2018

Relative evolutionary rates in proteins are largely insensitive to the substitution model

The relative evolutionary rates at individual sites in proteins are informative measures of conservation or adaptation. Often used as evolutionarily-aware conservation scores, relative rates reveal key functional or strongly-selected residues. Estimating rates in a phylogenetic context requires specifying a protein substitution model, which is typically a phenomenological model trained on a large empirical dataset. A strong emphasis has traditionally been placed on selecting the \"best-fit\" model, with the implicit understanding that suboptimal or otherwise ill-fitting models can potentially bias inferences. However, the pervasiveness and degree of such bias has not been systematically examined. We investigated how model choice impacts site-wise relative rates from a large set of empirical protein alignments. We compared models designed for use on any general protein, models designed for specific domains of life, and the simple equal-rates Jukes Cantor-style model (JC). As expected, information theoretic measures showed overwhelming evidence that some models fit the data decidedly better than others. By contrast, estimates of site-specific evolutionary rates were impressively insensitive to the substitution model used, revealing an unexpected degree of robustness to potential model misspecification. A deeper examination of the fewer than 5% of sites for which model inferences differed in a meaningful way showed that the JC model can uniquely identify rapidly-evolving sites that models with empirically-derived exchangeabilities fail to detect. We conclude that relative protein rates appear robust to the applied substitution model, and any sensible model of protein evolution, regardless of its fit to the data, should produce broadly consistent evolutionary rates.

evolutionary biology↗
bioRxiv2017

Full-Length Envelope Analyzer (FLEA): A tool for longitudinal analysis of viral amplicons

Next generation sequencing of viral populations has advanced our understanding of viral population dynamics, the development of drug resistance, and escape from host immune responses. Many applications require complete gene sequences, which can be impossible to reconstruct from short reads. HIV-1 env, the protein of interest for HIV vaccine studies, is exceptionally challenging for long-read sequencing and analysis due to its length, high substitution rate, and extensive indel variation. While long-read sequencing is attractive in this setting, the analysis of such data is not well handled by existing methods. To address this, we introduce FLEA (Full-Length Envelope Analyzer), which performs end-to-end analysis and visualization of long-read sequencing data.\n\nFLEA consists of both a pipeline (optionally run on a high-performance cluster), and a client-side web application that provides interactive results. The pipeline transforms FASTQ reads into high-quality consensus sequences (HQCSs) and uses them to build a codon-aware multiple sequence alignment. The resulting alignment is then used to infer phylogenies, selection pressure, and evolutionary dynamics. The web application provides publication-quality plots and interactive visualizations, including an annotated viral alignment browser, time series plots of evolutionary dynamics, visualizations of gene-wide selective pressures (such as dN /dS) across time and across protein structure, and a phylogenetic tree browser.\n\nWe demonstrate how FLEA may be used to process Pacific Biosciences HIV-1 env data and describe recent examples of its use. Simulations show how FLEA dramatically reduces the error rate of this sequencing platform, providing an accurate portrait of complex and variable HIV-1 env populations.\n\nA public instance of FLEA is hosted at http://flea.datamonkey.org. The Python source code for the FLEA pipeline can be found at https://github.com/veg/flea-pipeline. The client-side application is available at https://github.com/veg/flea-web-app. A live demo of the P018 results can be found at http://flea.murrell.group/view/P018.

bioinformatics↗