Biology subjects

Andersen, K. G.

Publications and source records attributed to Andersen, K. G..

At least 19 recordsLinked to original sources

bioRxiv2026

Dairy cattle movement networks govern the spread and persistence of H5N1 B3.13 in the United States

Avian influenza virus H5N1 is predominantly found in wild and domestic birds. H5N1 genotype B3.13 was first detected in United States dairy cattle in March 2024 and spread through much of the country during 2024 and 2025, resulting in the largest known H5N1 outbreak in domestic mammals. By analysing viral genomic data jointly with historical cattle movement patterns, we find that live cattle movement is the predominant contributor to H5N1 spatial spread, rather than wild or domestic birds. Using phylogeographic methods we estimate that >40% of interstate viral transmissions occurred before B3.13's first detection and >70% occurred before interstate dairy cattle movement restrictions were implemented in April 2024. After this implementation, interstate transmission slowed but within-state spread persisted, driven by local cattle network density and movement volume. Our epidemic simulations demonstrate that the connectivity of counties within and around the Texas Panhandle - where the earliest cases were documented - predisposed the region to become an outbreak epicentre. Counterfactual simulations indicate that interstate restrictions needed to have begun 2-3 months earlier in order to limit the epizootic substantively, given the extent of cryptic spread before detection. Network-informed interventions outperformed geographically-defined containment, but response speed (rather than intervention strength) was the limiting factor in our epidemic models, underscoring the need for surveillance systems capable of detecting pathogen emergence before widespread dissemination.

evolutionary biology↗

bioRxiv2026

The emergence and molecular evolution of H5N1 influenza viruses in United States dairy cattle

Prior to 2024, highly pathogenic avian influenza H5N1 clade 2.3.4.4b viruses circulated predominantly in wild birds and poultry. In 2024 and 2025, 2.3.4.4b genotypes B3.13 and D1.1 were detected in United States dairy cattle. Using whole-genome and segment-specific phylodynamic inference, we estimate that B3.13 and D1.1 spilled over from wild birds into dairy cattle in late 2023 and late 2024, respectively. Spillover occurred shortly after the formation of the reassortant genotypes and was followed by months of cryptic transmission prior to detection. We found that both B3.13 and D1.1 evolved at higher rates in cattle relative to birds, primarily due to relaxed purifying selection. Site-specific analyses identified genomic sites under positive selection in cattle relative to birds, indicating adaptation and likely contributing to improved viral fitness after spillover. Intensified genomic surveillance in dairy cattle is essential as population immunity introduces additional selection pressures, with ever-changing risk for human emergence.

evolutionary biology↗

bioRxiv2025

Delphy: scalable, near-real-time Bayesian phylogenetics for outbreaks

Pathogen genomic analysis is central to tracking, understanding, and containing outbreaks, but complexity and high costs of state-of-the-art (SOTA) phylogenetic tools limit global access and impact. We introduce Delphy, an exact reformulation of Bayesian phylogenetics designed to transform its speed, scalability and accessibility while retaining SOTA accuracy. Delphys central data structure, an Explicit Mutation Annotated Tree, exploits the high sequence similarity in large-scale epidemic datasets for efficient tree exploration and convergence. By reproducing key analyses from recent major epidemics (Ebola, Zika, SARS-CoV-2, mpox, and H5N1), we demonstrate SOTA accuracy with up to 1,000x speedups. Assessing Delphys scalability, we show that a simulated dataset of 100,000 sequences can be analyzed in under a day-the largest such computation to date. We distribute Delphy as a client-side web application, enabling users worldwide to turn raw data into interactive results within minutes, without the data ever leaving the users machine. Delphy automatically identifies key viral lineages and mutations, as well as their emergence and prevalence through time, all with quantified uncertainties derived from a solid theoretical foundation. Delphy shows the power of Bayesian phylogenetics as a fast, accessible frontline tool for tackling future outbreaks.

genomics↗

bioRxiv2025

Dynamics of natural selection preceding human viral epidemics and pandemics.

Using a phylogenetic framework to characterize natural selection, we investigate the hypothesis that zoonotic viruses require adaptation prior to zoonosis to sustain human-to-human transmission. Examining the zoonotic emergence of Ebola virus, Marburg virus, influenza A virus, SARS-CoV, and SARS-CoV-2, we find no evidence of a change in the intensity of natural selection immediately prior to a host switch, compared with typical selection within reservoir hosts. We conclude that extensive pre-zoonotic adaptation is not necessary for human-to-human transmission of zoonotic viruses. In contrast, the reemergence of H1N1 influenza A virus in 1977 showed a change in selection, consistent with the hypothesis of passage in a laboratory setting prior to its reintroduction into the human population, purportedly during a vaccine trial. Holistic phylogenetic analysis of selection regimes can be used to detect evolutionary signals of host switching or laboratory passage, providing insight into the circumstances of past and future viral emergence.

evolutionary biology↗

bioRxiv2024

Deep mutational scanning reveals functional constraints and antigenic variability of Lassa virus glycoprotein complex

Lassa virus is estimated to cause thousands of human deaths per year, primarily due to spillovers from its natural host, Mastomys rodents. Efforts to create vaccines and antibody therapeutics must account for the evolutionary variability of Lassa viruss glycoprotein complex (GPC), which mediates viral entry into cells and is the target of neutralizing antibodies. To map the evolutionary space accessible to GPC, we use pseudovirus deep mutational scanning to measure how nearly all GPC amino-acid mutations affect cell entry and antibody neutralization. Our experiments define functional constraints throughout GPC. We quantify how GPC mutations affect neutralization by a panel of monoclonal antibodies and show that all antibodies are escaped by mutations that exist among natural Lassa virus lineages. Overall, our work describes a biosafety-level-2 method to elucidate the mutational space accessible to GPC and shows how prospective characterization of antigenic variation could aid design of therapeutics and vaccines.

microbiology↗

bioRxiv2023

Genetic tracing of market wildlife and viruses at the epicenter of the COVID-19 pandemic

Zoonotic spillovers of viruses have occurred through the animal trade worldwide. The start of the COVID-19 pandemic was traced epidemiologically to the Huanan Wholesale Seafood Market, the site with the most reported wildlife vendors in the city of Wuhan, China. Here, we analyze publicly available qPCR and sequencing data from environmental samples collected in the Huanan market in early 2020. We demonstrate that the SARS-CoV-2 genetic diversity linked to this market is consistent with market emergence, and find increased SARS-CoV-2 positivity near and within a particular wildlife stall. We identify wildlife DNA in all SARS-CoV-2 positive samples from this stall. This includes species such as civets, bamboo rats, porcupines, hedgehogs, and one species, raccoon dogs, known to be capable of SARS-CoV-2 transmission. We also detect other animal viruses that infect raccoon dogs, civets, and bamboo rats. Combining metagenomic and phylogenetic approaches, we recover genotypes of market animals and compare them to those from other markets. This analysis provides the genetic basis for a short list of potential intermediate hosts of SARS-CoV-2 to prioritize for retrospective serological testing and viral sampling.

genomics↗

bioRxiv2022

Genomic and phenotypic analyses suggest moderate fitness differences among Zika virus lineages

RNA viruses have short generation times and high mutation rates, allowing them to undergo rapid molecular evolution during epidemics. However, the extent of RNA virus phenotypic evolution within epidemics and the resulting effects on fitness and virulence remain mostly unknown. Here, we screened the 2015-2016 Zika epidemic in the Americas for lineage-specific fitness differences. We engineered a library of recombinant viruses representing twelve major Zika virus lineages and used them to measure replicative fitness within disease-relevant human primary cells and live mosquitoes. We found that two of these lineages conferred significant in vitro replicative fitness changes among human primary cells, but we did not find fitness changes in Aedes aegypti mosquitoes. Additionally, we found evidence for elevated levels of positive selection among five amino acid sites that define major Zika virus lineages. While our work suggests that Zika virus may have acquired several phenotypic changes during a short time scale, these changes were relatively moderate and do not appear to have enhanced virulence or transmission during the epidemic.

evolutionary biology↗

bioRxiv2022

Outbreak.info: A standardized, searchable platform to discover and explore COVID-19 resources and data

To combat the ongoing COVID-19 pandemic, scientists have been conducting research at breakneck speeds, producing over 52,000 peer-reviewed articles within the first year. To address the challenge in tracking the vast amount of new research located in separate repositories, we developed outbreak.info Research Library, a standardized, searchable interface of COVID-19 and SARS-CoV-2 resources. Unifying metadata from sixteen repositories, we assembled a collection of over 350,000 publications, clinical trials, datasets, protocols, and other resources as of October 2022. We used a rigorous schema to enforce consistency across different sources and resource types and linked related resources. Researchers can quickly search the latest research across data repositories, regardless of resource type or repository location, via a search interface, public API, and R package. Finally, we discuss the challenges inherent in combining metadata from scattered and heterogeneous resources and provide recommendations to streamline this process to aid scientific research.

bioinformatics↗

bioRxiv2021

Predicting the evolution of Lassa Virus endemic area and population at risk over the next decades

Lassa fever is listed among the diseases that pose the greatest risks to public health by the World Health Organization. This severe viral hemorrhagic fever is caused by Lassa virus, a zoonotic pathogen that repeatedly spills over to humans from its rodent reservoirs. It is currently not known how climate change, transformations in land use, and human population growth could affect the endemic area of this virus, currently limited to parts of West Africa. By exploring the environmental data associated with virus occurrence, we show how temperature, precipitation and the presence of pastures determine ecological suitability for virus circulation. We project that regions in Central and East Africa will likely become suitable for Lassa virus over the next decades and estimate that the total population living in areas suitable for Lassa virus may grow from about 100 million to 700 million by 2070. By analysing geotagged viral genomes, we find that in the event of Lassa virus being introduced into a new suitable region, its spread might remain spatially limited over the first decades. Our results highlight how the endemic area of Lassa virus may expand well beyond West Africa in the next decades due to human impact on the environment, putting hundreds of million more people at risk of infection.

microbiology↗

bioRxiv2020

EMPress enables tree-guided, interactive, and exploratory analyses of multi-omic datasets

Standard workflows for analyzing microbiomes often include the creation and curation of phylogenetic trees. Here we present EMPress, an interactive tool for visualizing trees in the context of microbiome, metabolome, etc. community data scalable beyond modern large datasets like the Earth Microbiome Project. EMPress provides novel functionality--including ordination integration and animations--alongside many standard tree visualization features, and thus simplifies exploratory analyses of many forms of omic data.

bioinformatics↗

bioRxiv2020

Accommodating individual travel history, global mobility, and unsampled diversity in phylogeography: a SARS-CoV-2 case study.

Spatiotemporal bias in genome sequence sampling can severely confound phylogeographic inference based on discrete trait ancestral reconstruction. This has impeded our ability to accurately track the emergence and spread of SARS-CoV-2, the virus responsible for the COVID-19 pandemic. Despite the availability of unprecedented numbers of SARS-CoV-2 genomes on a global scale, evolutionary reconstructions are hindered by the slow accumulation of sequence divergence over its relatively short transmission history. When confronted with these issues, incorporating additional contextual data may critically inform phylodynamic reconstructions. Here, we present a new approach to integrate individual travel history data in Bayesian phylogeographic inference and apply it to the early spread of SARS-CoV-2, while also including global air transportation data. We demonstrate that including travel history data for each SARS-CoV-2 genome yields more realistic reconstructions of virus spread, particularly when travelers from undersampled locations are included to mitigate sampling bias. We further explore methods to ameliorate the impact of sampling bias by augmenting the phylogeographic analysis with lineages from undersampled locations in the analyses. Our reconstructions reinforce specific transmission hypotheses suggested by the inclusion of travel history data, but also suggest alternative routes of virus migration that are plausible within the epidemiological context but are not apparent with current sampling efforts. Although further research is needed to fully examine the performance of our travel-aware phylogeographic analyses with unsampled diversity and to further improve them, they represent multiple new avenues for directly addressing the colossal issue of sample bias in phylogeographic inference.

evolutionary biology↗

bioRxiv2019

Phylogeographic and phylodynamic approaches to epidemiological hypothesis testing

Computational analyses of pathogen genomes are increasingly used to unravel the dispersal history and transmission dynamics of epidemics. Here, we show how to go beyond historical reconstructions and use spatially-explicit phylogeographic and phylodynamic approaches to formally test epidemiological hypotheses. We illustrate our approach by focusing on the West Nile virus (WNV) spread in North America that has been responsible for substantial impacts on public, veterinary, and wildlife health. WNV isolates have been sampled at various times and locations across North America since its introduction to New York twenty years ago. We exploit this genetic data repository to demonstrate that factors hypothesised to affect viral dispersal and demography can be formally tested. Specifically, we detail and apply an analytical workflow consisting of state-of-the art methods that we further improve to test the impact of environmental factors on the dispersal locations, velocity, and frequency of viral lineages, as well as on the genetic diversity of the viral population through time. We find that WNV lineages tend to disperse faster in areas with higher temperatures and we identify temporal variation in temperature as a main predictor of viral genetic diversity through time. Using a simulation procedure, we find no evidence that viral lineages preferentially circulate within the same migratory bird flyway, suggesting a substantial role for non-migratory birds or mosquito dispersal along the longitudinal gradient. Finally, we also separately apply our testing approaches on the three WNV genotypes that circulated in North America in order to understand and compare their dispersal ability. Our study demonstrates that the development and application of statistical approaches, coupled with comprehensive pathogen genomic data, can address epidemiological questions that might otherwise be difficult or impractically expensive to answer.

evolutionary biology↗

bioRxiv2018

International travelers and genomics uncover a ‘hidden’ Zika outbreak

The ongoing Zika epidemic in the Americas has challenged public health surveillance, response, and control systems. Even as the epidemic appears to be near its end in the Americas, it is unclear whether substantial Zika virus transmission may still be ongoing. This issue is exacerbated by large discrepancies in local case reporting and significant delays in detecting outbreaks due to surveillance gaps. To uncover locations with lingering outbreaks in the Americas, we investigated travel-associated Zika cases diagnosed in the United States and Europe to identify signatures of transmission dynamics that were not captured by local reporting. We found that a large and unreported Zika outbreak occurred in Cuba during 2017, a year after peak transmission in neighboring countries, with cases still appearing in 2018. By sequencing Zika virus from infected travelers, we show that the 2017 outbreak in Cuba was sparked by long-lived lineages of Zika virus introduced from multiple places in the Americas a year prior. Our data suggest that while aggressive mosquito control in Cuba may initially have been effective at mitigating Zika virus transmission, in the absence of vaccines, herd immunity, or strong international coordination, such control measures may need to be maintained to be effective. Our study highlights how Zika virus may still be silently spreading in the Americas and provides a framework for more accurately understanding outbreak dynamics.

epidemiology↗

bioRxiv2018

An emergent Ebola virus nucleoprotein variant influences virion budding, oligomerization, transcription and replication

For highly pathogenic viruses, reporter assays that can be rapidly performed are critically needed to identify potentially functional mutations for further study under maximal containment (e.g., biosafety level 4 [BSL-4]). The Ebola virus nucleoprotein (NP) plays multiple essential roles during the viral life cycle, yet few tools exist to study the protein under BSL-2 or equivalent containment. Therefore, we adapted reporter assays to measure NP oligomerization and virion-like particle (VLP) production in live cells and further measure transcription and replication using established minigenome assays. As a proof-of-concept, we examined the NP-R111C substitution, which emerged during the 2013-2016 Western African Ebola virus disease epidemic and rose to high frequency. NP-R111C slightly increased NP oligomerization and VLP budding but slightly decreased transcription and replication. By contrast, a synthetic charge-reversal mutant, NP-R111E, greatly increased oligomerization but abrogated transcription and replication. These results are intriguing in light of recent structures of NP oligomers, which reveal that the neighboring residue, K110, forms a salt bridge with E349 on adjacent NP molecules. By developing and utilizing multiple reporter assays, we find that the NP-111 position mediates a complex interplay between NPs roles in protein structure, virion budding, and transcription and replication.

microbiology↗

bioRxiv2018

An amplicon-based sequencing framework for accurately measuring intrahost virus diversity using PrimalSeq and iVar

How viruses evolve within hosts can dictate infection outcomes; however, reconstructing this process is challenging. We evaluated our multiplexed amplicon approach - PrimalSeq - to demonstrate how virus concentration, sequencing coverage, primer mismatches, and replicates influence the accuracy of measuring intrahost virus diversity. We developed an experimental protocol and computational tool (iVar) for using PrimalSeq to measure virus diversity using Illumina and compared the results to Oxford Nanopore sequencing. We demonstrate the utility of PrimalSeq by measuring Zika and West Nile virus diversity from varied sample types and show that the accumulation of genetic diversity is influenced by experimental and biological systems.

evolutionary biology↗

bioRxiv2017

Common Piezo1 allele in African populations causes xerocytosis and attenuates Plasmodium infection

Hereditary xerocytosis (HX) is thought to be a rare genetic condition characterized by red blood cell (RBC) dehydration with mild hemolysis. Gain-of-function (GOF) mutations in mechanosensitive Piezo1 ion channels are identified in HX patients. RBC dehydration is linked to reduced Plasmodium infection rates in vitro. We engineered a Piezo1 mouse model of HX and show that Plasmodium infection fails to cause experimental cerebral malaria in these mice. Furthermore, we identified a novel GOF human Piezo1 variant, E756del, present in a third of African population. Remarkably, RBCs from individuals carrying this allele are dehydrated and protected against Plasmodium infection in vitro. The presence of an HX-causing Piezo1 mutation at such high frequencies in African population is surprising, and suggests an association with malaria resistance.

physiology↗

bioRxiv2017

Genetic characterization of the Zika virus epidemic in the US Virgin Islands

Here we release draft genome sequences of Zika virus (ZIKV) that were sequenced from PCR-positive diagnostic specimens collected by the United States Virgin Islands Department of Health (USVI DoH) as part of their ongoing response to the ZIKV outbreak. We will use these sequences to conduct a genomic epidemiological study of ZIKV transmission in the USVI. We are releasing these genomes in the hope that they are useful for those individuals involved in the public health response to ZIKV and to other groups working to understand Zika virus transmission and evolution.

epidemiology↗

bioRxiv2017

Epidemic establishment and cryptic transmission of Zika virus in Brazil and the Americas

Zika virus (ZIKV) transmission in the Americas was first confirmed in May 2015 in Northeast Brazil1. Brazil has the highest number of reported ZIKV cases worldwide (>200,000 by 24 Dec 20162) as well as the greatest number of cases associated with microcephaly and other birth defects (2,366 confirmed cases by 31 Dec 20162). Following the initial detection of ZIKV in Brazil, 47 countries and territories in the Americas have reported local ZIKV transmission, with 22 of these reporting ZIKV-associated severe disease3. Yet the origin and epidemic history of ZIKV in Brazil and the Americas remain poorly understood, despite the value of such information for interpreting past trends in reported microcephaly. To address this we generated 53 complete or partial ZIKV genomes, mostly from Brazil, including data generated by the ZiBRA project - a mobile genomics lab that travelled across Northeast Brazil in 2016. One sequence represents the earliest confirmed ZIKV infection in Brazil. Joint analyses of viral genomes with ecological and epidemiological data estimate that the ZIKV epidemic first became established in NE Brazil by March 2014 and likely disseminated from there, both nationally and internationally, before the first detection of ZIKV in the Americas. Estimated dates of the international spread of ZIKV from Brazil coincide with periods of high vector suitability in recipient regions and indicate the duration of pre-detection cryptic transmission in those regions. NE Brazils role in the establishment of ZIKV in the Americas is further supported by geographic analysis of ZIKV transmission potential and by estimates of the virus basic reproduction number.\n\nOne Sentence SummaryVirus genomes reveal the establishment of Zika virus in Northeast Brazil and the Americas, and provide an appropriate timeframe for baseline (pre-Zika) microcephaly in different regions.

genomics↗