Biology subjects

Markin, A.

Publications and source records attributed to Markin, A..

13 recordsLinked to original sources

bioRxiv2026

Host type governs influenza evolutionary strategy across reservoir and spillover hosts

Despite its high propensity for host switching, the evolutionary mechanisms underlying influenza host adaptation remain unclear. H3Nx influenza viruses are uniquely generalist, with long-term lineages that circulate in avian, human, swine, equine, and canine hosts. Using 13,295 H3Nx sequences, we quantified host-specific adaptive evolution and developed a pipeline to map reassortment events onto trees with measures of statistical uncertainty. We find that while H3Nx viruses in mammals undergo adaptive evolution in HA and NA, viruses in birds experience very little directional selection. Instead, avian lineages exhibit high rates of reassortment, frequently generating novel reassortant lineages that persist transiently and turn over rapidly. 29.8-47.4% of all avian reassortant lineages are purged within the first year of circulation, and reassortment shows no fitness benefit in birds. In contrast, reassorted lineages in swine are more likely to persist long-term, suggesting that reassortment in swine may be broadly beneficial. Segment-specific reassortment patterns were also distinct between avian and mammalian viruses, with NA reassorting more frequently than expected in birds, but less frequently than expected in swine. Reassortment events are enriched between mammalian, but not avian, host switches, suggesting that reassortment may be most beneficial for mediating host switches among mammalian species. Together, our data suggest that host differences drive fundamentally different evolutionary outcomes for influenza viruses, transitioning from reassortment-dominant evolution in their avian reservoir, to varying degrees of adaptation upon establishment in mammals.

evolutionary biology↗

bioRxiv2026

Quantifying Asymmetric Coevolutionary Dynamics using Normalized Phylogenetic Costs

AO_SCPLOWBSTRACTC_SCPLOWCoevolutionary studies aim to characterize associations, such as virus-host relationships, by using phylogenetic distances to quantify the topological concordance between the phylogenies of interacting taxa. However, phylogenetic distances cannot capture asymmetrical relationships that arise from differences in sampling, evolutionary rates, or characterizations between datasets. Furthermore, a lack of accurate normalization complicates the interpretation and validation of coevolutionary analyses. To address these limitations, we employed the Asymmetric Cluster Affinity and Cluster Support costs as a general framework to quantify coevolutionary patterns across multiple biological scales. We benchmarked the precision of these costs by reanalyzing a curated dataset documenting interspecies transmission frequencies across nineteen virus-host phylogenies. Our results corroborate prior findings showing that all virus families under study can cross species boundaries; however, the asymmetric costs provide a more granular representation, demonstrating that the frequency of such events varies significantly across families. We then applied the Asymmetric Cluster Support cost to quantify preferential gene segment pairings within the Bluetongue virus genome. This analysis revealed a close phylogenetic association between the outer capsid proteins VP2 and VP5, likely reflecting shared selective pressures due to their critical roles in cell entry and exit. In contrast, gene segments encoding nonstructural proteins exhibited discordant evolutionary histories relative to other segments. Finally, we demonstrated that the Asymmetric Cluster Support cost can detect coevolutionary dynamics in swine influenza A virus, identifying novel gene pairings indicative of major viral reassortment events. Overall, our approach demonstrates that normalized asymmetric phylogenetic costs accurately capture complex biological relationships and provide a robust framework for quantifying fine-scale coevolutionary dynamics in rapidly evolving pathogens.

bioinformatics↗

bioRxiv2026

A multivalent mRNA-lipid nanoparticle vaccine containing eight hemagglutinin antigens elicited broad neutralizing antibody responses and protected against influenza A virus challenge in swine.

The diversity within H1 and H3 subtype influenza A viruses (IAV) in swine prevents effective vaccine control approaches with inactivated whole-virus vaccines. We addressed the challenge of controlling co-circulating hemagglutinin (HA) clades of swine IAV with the development of a multivalent mRNA-lipid nanoparticle (LNP) vaccine expressing 8 HA proteins to maximize genetic coverage. We applied a computational approach to select eight HA genes that represented 95% of the observed IAV detected in the United States between 2022 and 2025. Piglets were vaccinated and boosted intramuscularly with either individual HA mRNA-LNP or an 8-HA multivalent mRNA-LNP. Serum was collected to evaluate systemic antibody levels. Twenty-one days post-boost, pigs were challenged with a field relevant H1 1A.3.3.3-c3 IAV strain. The 8-HA multivalent mRNA-LNP vaccine induced neutralizing antibodies against all eight antigens and vaccinees were protected against lung lesions, with lesion scores similar to non-challenged animals. Homologous monovalent vaccination significantly reduced IAV detection in nasal secretions and in the lungs. Heterologous monovalent vaccination was not cross-protective but did not induce vaccine-associated enhanced respiratory disease. We provide evidence that monovalent and multivalent mRNA-LNP influenza vaccines elicited neutralizing antibody responses in pigs and protected against viral challenge. The versatility and capacity for rapidly updating the mRNA-LNP vaccine platform make it an appealing tool to improve animal health and minimize the circulation and diversity of IAV in swine. ImportanceInfluenza A virus is an important respiratory pathogen in swine, and zoonotic transmission of swine strains to humans remains a public health risk. Control strategies against IAV in swine herds rely heavily on biosecurity measures and vaccination. However, the antigenic diversity of IAV circulating in swine challenges current vaccination programs, and there is a need for broadly protective vaccines or platforms that can rapidly update components to reflect circulating diversity. mRNA-LNP vaccines have emerged as promising vaccine platforms, offering simultaneous delivery of multiple antigens, rapid development, scalable manufacturing, and potent immunogenicity. In this study, we assessed the immunogenicity and protective capacity of monovalent and multivalent mRNA-LNP vaccines encoding eight representative IAV HA antigens. To our knowledge, this is the first study to objectively select multiple representative endemic swine IAV strains by quantifying genetic diversity within the phylogeny and to apply this selection to rationally design and evaluate a multivalent HA mRNA-based influenza vaccine in the swine model.

microbiology↗

bioRxiv2026

Splicer: Phylogenetic Placement in Sub-Linear Time

MotivationPhylogenetic placement is an established approach for rapidly classifying new genetic sequences and updating a phylogeny without fully recomputing it. Popular maximum-likelihood placement methods, such as pplacer and EPA-ng, tend to struggle computationally when the size of the reference tree increases to tens or hundreds of thousands of sequences. As a more scalable alternative, distance-based and parsimony-based placement methods were introduced such as UShER. These methods, in principle, scale linearly as the size of the reference tree grows. However, as the scale of genetic and genomic sequences continues to grow nearly exponentially, developing algorithms that can perform placement in sub-linear time while maintaining accuracy becomes more crucial. ResultsHere, we develop Splicer, the first such algorithm that can perform placement in guaranteed [Formula] time. To achieve this performance, Splicer first decomposes the original reference tree into blobs and constructs a phylogenetic scaffold tree linking representatives from different blobs. Every blob in such decomposition has at most [Formula] taxa, and the scaffold tree has at most [Formula] leaves, where c is any constant. Then, given the query sequences for placement, they are first placed onto a scaffold tree using pplacer or EPA-ng, and then placed more precisely within the respective blobs. We demonstrate the high accuracy of Splicer on an empirical influenza A virus dataset that has sparse coverage due to limited genomic surveillance. We also show that Splicer can, for the first time, apply maximum-likelihood placement to COVID-19 pandemic-scale data using a dataset with over 12 million SARS-CoV-2 reference genomes. Splicer scales the highly accurate maximum-likelihood approaches implemented in pplacer and EPA-ng to trees with millions of taxa and eliminates the necessity to curate and subsample genomic datasets for real-time classifications. Availability and implementationSplicer tool and source code are freely available at https://github.com/flu-crew/splicer.

bioinformatics↗

bioRxiv2026

On the correctness of gene tree tagging and the consistency of ASTRAL-pro under a unified model of gene duplication, loss, and coalescence

AO_SCPLOWBSTRACTC_SCPLOWASTRAL-pro is the leading method for reconstructing species trees under complex evolutionary scenarios involving gene duplication, loss, and coalescence, commonly modeled by DLCoal. A unique aspect of A-pro is that it utilizes rooted gene trees, with internal vertices labeled as duplications or speciations, to modify its objective function compared to the traditional ASTRAL method. Although there is a natural event-based definition of correct tagging when genes evolve with only gene duplications and losses, it cannot be applied when there is deep coalescence. Here, we introduce a definition of correct tagging that is broadly applicable, proposing that a gene tree vertex is correctly tagged as a duplication if it is the most recent common ancestor of at least one pair of gene copies related via a duplication event. Using this definition, we study some statistical properties of ASTRAL-pros objective function under the DLCoal model and evaluate the accuracy of ASTRAL-pros tagging algorithm in simulations.

bioinformatics↗

bioRxiv2025

Phylo-rs: an extensible phylogenetic analysis library in Rust

We introduce Phylo-rs: a fast, extensible, general-purpose library for phylogenetic analysis and inference written in the Rust programming language. Phylo-rs leverages a combination of speed, memory-safety, and native WebAssembly support offered by Rust to provide a robust set of memory-efficient data structures and elementary phylogenetic algorithms. Phylo-rs is focused on efficient and convenient deployment of software aimed at large-scale phylogenetic analysis and inference. Phylo-rs is available under an open-source license on GitHub at https://github.com/sriram98v/phylo-rs, with documentation available at https://docs.rs/phylo/latest/phylo/.

bioinformatics↗

bioRxiv2024

Revealing reassortment in influenza A viruses with TreeSort

Reassortment among influenza A viruses (IAV) facilitates genomic evolution and has been associated with interspecies transmission and pandemics. We introduce a novel tool called TreeSort that accurately identifies recent and ancestral reassortment events on datasets with thousands of IAV whole genomes. The algorithm has immediate relevance to modern large-scale surveillance studies that generate thousands of whole genomes. TreeSort uses the phylogeny of a selected IAV segment as a reference and finds the branches on the phylogeny where reassortment has occurred with high probability by incorporating information from other gene segments. The tool reports the particular gene segments that were involved in reassortment and how different they are from prior gene pairings. Using TreeSort, we studied reassortment patterns of different IAV subtypes isolated in avian, swine, and human hosts. Avian IAV demonstrated more reassortment than human and swine IAV, with the avian H7 subtype displaying the most frequent reassortment. Reassortment in the swine and human H3 subtypes was more frequent than in the swine and human H1 subtypes, respectively. The highly pathogenic avian influenza H5N1 clade 2.3.4.4b had elevated reassortment rates in the 2020-2023 period; however, the surface protein-encoding genes (HA, NA, and MP) co-evolved together with almost no reassortment among these genes. We observed similar co-evolutionary patterns with very low rates of reassortment among the surface proteins for the human H1 and H3 lineages, suggesting that strong co-evolution and preferential pairings among surface proteins are a consequence of high viral fitness. Our algorithm enables real-time tracking of IAV reassortment within and across different hosts, can be applied to determine how specific genes evolve in response to reassortment events, and can identify novel viruses for pandemic risk assessment. TreeSort is available at https://github.com/flu-crew/TreeSort.

microbiology↗

bioRxiv2024

Experimental reproduction of viral replication and disease in dairy calves and lactating cows inoculated with highly pathogenic avian influenza H5N1 clade 2.3.4.4b

Highly pathogenic avian influenza (HPAI) H5N1 of the hemagglutinin clade 2.3.4.4b was detected in the United States in late 2021 and continues to circulate in all four North American flyways to date. In addition to impacting poultry, these HPAI viruses caused mortality events in wild bird species and wild mammals. Transmission in multiple host species raises the concern for mammalian adaptation. On March 25, 2024, HPAI H5N1 clade 2.3.4.4b was confirmed in a dairy cow in Texas in response to a multi-state investigation into milk production losses. Over one hundred positive herds were rapidly identified in Texas and eleven other U.S. states. The case description included reduced feed intake and rumen motility in lactating cows, decreased milk production, and thick yellow milk. The diagnostic investigation revealed detections of viral RNA in milk and mammary tissue with alveolar epithelial degeneration and necrosis, and positive immunoreactivity of glandular epithelium by immunohistochemistry. A single transmission event, likely from avian species to dairy cattle, followed by limited local transmission preceded the onward lateral transmission of H5N1 clade 2.3.4.4b genotype B3.13. We sought to experimentally reproduce infection with genotype B3.13 in Holstein yearling heifers and lactating cows. The heifers were inoculated by an aerosol respiratory route and the cows by an intramammary route. Clinical disease was mild in the heifers, but infection was confirmed by virus detection, lesions, and seroconversion. Clinical disease in lactating cows included decreased rumen motility, changes to milk appearance, and production losses consistent with field reports of viral mastitis. Infection was confirmed by high levels of viral RNA detected in milk, virus isolation, lesions in mammary tissue, and seroconversion. This study provides the foundation to investigate additional routes of infection, transmission, and intervention strategies.

microbiology↗

bioRxiv2024

Emergence and interstate spread of highly pathogenic avian influenza A(H5N1) in dairy cattle

Highly pathogenic avian influenza (HPAI) viruses cross species barriers and have the potential to cause pandemics. In North America, HPAI A(H5N1) viruses related to the goose/Guangdong 2.3.4.4b hemagglutinin phylogenetic clade have infected wild birds, poultry, and mammals. Our genomic analysis and epidemiological investigation showed that a reassortment event in wild bird populations preceded a single wild bird-to-cattle transmission episode. The movement of asymptomatic cattle has likely played a role in the spread of HPAI within the United States dairy herd. Some molecular markers in virus populations were detected at low frequency that may lead to changes in transmission efficiency and phenotype after evolution in dairy cattle. Continued transmission of H5N1 HPAI within dairy cattle increases the risk for infection and subsequent spread of the virus to human populations.

microbiology↗

bioRxiv2022

Reverse-zoonoses of 2009 H1N1 pandemic influenza A viruses and evolution in United States swine results in viruses with zoonotic potential

The 2009 H1N1 pandemic (pdm09) lineage of influenza A virus (IAV) crosses interspecies barriers with frequent human-to-swine spillovers each year. These spillovers reassort and drift within swine populations, leading to genetically and antigenically novel IAV that represent a zoonotic threat. We quantified interspecies transmission of the pdm09 lineage, persistence in swine, and identified how evolution in swine impacted zoonotic risk. Human and swine pdm09 case counts between 2010 and 2020 were correlated and human pdm09 burden and circulation directly impacted the detection of pdm09 in pigs. However, there was a relative absence of pdm09 circulation in humans during the 2020-21 season that was not reflected in swine. During the 2020-21 season, most swine pdm09 detections originated from human-to-swine spillovers from the 2018-19 and 2019-20 seasons that persisted in swine. We identified contemporary swine pdm09 representatives of each persistent spillover and quantified cross-reactivity between human seasonal H1 vaccine strains and the swine strains using a panel of monovalent ferret antisera in hemagglutination inhibition (HI) assays. The swine pdm09s had variable antigenic reactivity to vaccine antisera, but each swine pdm09 clade exhibited significant reduction in cross-reactivity to one or more of the human seasonal vaccine strains. Further supporting zoonotic risk, we showed phylogenetic evidence for 17 swine-to-human transmission events of pdm09 from 2010 to 2021, 11 of which were not previously classified as variants, with each of the zoonotic cases associated with persistent circulation of pdm09 in pigs. These data demonstrate that reverse-zoonoses and evolution of pdm09 in swine results in viruses that are capable of zoonotic transmission and represent a potential pandemic threat. Author SummaryThe diversity and evolution of influenza A virus (IAV) in pigs is linked to the emergence of IAV with pandemic potential. Human-to-swine transmission of the 2009 H1N1 pandemic (pdm09) IAV lineage repeatedly occurred across the past decade and has increased genetic diversity in pigs: sporadic swine-to-human cases are associated with these viruses. We measured the frequency of human-to-swine transmission of the H1N1 pandemic IAV lineage between 2009 and 2021 and determined how this affected the diversity of IAV in swine and zoonotic risk. We detected 371 separate human-to-swine spillovers, with the frequency of interspecies transmission increasing when the burden of IAV was highest in the human population. Most spillovers were single events without sustained transmission, but a small subset resulted in the emergence, persistence, and cocirculation of different pdm09 genetic clades in US pigs. Each of the pdm09 representative of different persistent spillovers was genetically and antigenically different from human seasonal vaccine strains. The persistence of pdm09 within pigs resulted in at least five recent swine-to-human transmission events. These data suggest that controlling IAV infection in humans working with swine can minimize spillover into pigs, reduce resulting genetic diversity of IAV in pigs, and proactively reduce the potential for swine-to-human transmission of IAV with pandemic potential.

microbiology↗

bioRxiv2022

PARNAS: Objectively Selecting the Most Representative Taxa on a Phylogeny

The use of next-generation sequencing technology has enabled phylogenetic studies with hundreds of thousands of taxa. Such large-scale phylogenies have become a critical component in genomic epidemiology in pathogens such as SARS-CoV-2 and influenza A virus. However, detailed phenotypic characterization of pathogens or generating a computationally tractable dataset for detailed phylogenetic analyses requires bias free subsampling of taxa. To address this need, we propose parnas, an objective and flexible algorithm to sample and select taxa that best represent observed diversity by solving a generalized k-medoids problem on a phylogenetic tree. parnas solves this problem efficiently and exactly by novel optimizations and adapting algorithms from operations research. For more nuanced selections, taxa can be weighted with metadata or genetic sequence parameters, and the pool of potential representatives can be user-constrained. Motivated by influenza A virus genomic surveillance and vaccine design, parnas can be applied to identify representative taxa that optimally cover the diversity in a phylogeny within a specified distance radius. We demonstrated that parnas is more efficient and flexible than current approaches, and applied it to select representative influenza A virus in swine genes derived from over 5 years of genomic surveillance data. Our objective selection of 4 to 6 strains selected every two years from the 16 distinct genetic clades were sufficient to cover 80% of diversity circulating in US swine. We suggest that this method, through the objective selection of representatives in a phylogeny, provides criteria for rational multivalent vaccine design and for quantifying diversity. PARNAS is available at https://github.com/flu-crew/parnas.

evolutionary biology↗

bioRxiv2021

RF-Net 2: Fast Inference of Virus Reassortment and Hybridization Networks

MotivationA phylogenetic network is a powerful model to represent entangled evolutionary histories with both divergent (speciation) and convergent (e.g., hybridization, reassortment, recombination) evolution. The standard approach to inference of hybridization networks is to (i) reconstruct rooted gene trees and (ii) leverage gene tree discordance for network inference. Recently, we introduced a method called RF-Net for accurate inference of virus reassortment and hybridization networks from input gene trees in the presence of errors commonly found in phylogenetic trees. While RF-Net demonstrated the ability to accurately infer networks with up to four reticulations from erroneous input gene trees, its application was limited by the number of reticulations it could handle in a reasonable amount of time. This limitation is particularly restrictive in the inference of the evolutionary history of segmented RNA viruses such as influenza A virus (IAV), where reassortment is one of the major mechanisms shaping the evolution of these pathogens. ResultsHere we expand the functionality of RF-Net that makes it significantly more applicable in practice. Crucially, we introduce a fast extension to RF-Net, called Fast-RF-Net, that can handle large numbers of reticulations without sacrificing accuracy. Additionally, we develop automatic stopping criteria to select the appropriate number of reticulations heuristically and implement a feature for RF-Net to output error-corrected input gene trees. We then conduct a comprehensive study of the original method and its novel extensions and confirm their efficacy in practice using extensive simulation and empirical influenza A virus evolutionary analyses. AvailabilityRF-Net 2 is available at https://github.com/flu-crew/rf-net-2.

evolutionary biology↗

bioRxiv2019

Robinson-Foulds Reticulation Networks

Phylogenetic (hybridization) networks allow investigation of evolutionary species histories that involve complex phylogenetic events other than speciation, such as reassortment in virus evolution or introgressive hybridization in invertebrates and mammals. Reticulation networks can be inferred by solving the reticulation network problem, typically known as the hybridization network problem. Given a collection of phylogenetic input trees, this problem seeks a minimum reticulation network with the smallest number of reticulation vertices into which the input trees can be embedded exactly. Unfortunately, this problem is limited in practice, since minimum reticulation networks can be easily obfuscated by even small topological errors that typically occur in input trees inferred from biological data. We adapt the reticulation network problem to address erroneous input trees using the classic Robinson-Foulds distance. The RF embedding cost allows trees to be embedded into reticulation networks inexactly, but up to a measurable error. The adapted problem, called the Robinson-Foulds reticulation network (RF-Network) problem is, as we show and like many other problems applied in molecular biology, NP-hard. To address this, we employ local search strategies that have been successfully applied in other NP-hard phylogenetic problems. Our local search method benefits from recent theoretical advancements in this area. Further, we introduce inpractice effective algorithms for the computational challenges involved in our local search approach. Using simulations we experimentally validate the ability of our method, RF-Net, to reconstruct correct phylogenetic networks in the presence of error in input data. Finally, we demonstrate how RF-networks can help identify reassortment in influenza A viruses, and provide insight into the evolutionary history of these viruses. RF-Net was able to estimate a large and credible reassortment network with 164 taxa.

evolutionary biology↗