Biology subjects

Dudas, G.

Publications and source records attributed to Dudas, 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

Phylodynamic analysis reveals asymmetric and accelerating global spread of dengue virus

Dengue virus (DENV) continues to expand globally, with increasing incidence in both endemic and non-endemic countries. Leveraging a large global dataset of DENV genomes starting from the 1940s, we reconstructed global and regional patterns of DENV spread using phylogeographic and phylodynamic methods. Our analyses reveal that the current global diversity of urban DENV originated in Asia in the first half of the 20th century. During the more than 100 years since, we find that the highest density of between-country spread occurs within Asia and the region continues to be a global source, seeding transmission in Africa and the Americas. Global spread is, however, not balanced. Even though there is more travel to South America, we show that DENV lineages primarily enter North America (mostly from South Asia) through a link defined by seasonal synchrony across the Northern Hemisphere. Along with a substantial increase in global travel starting ~2010, the rate of spread to the Americas is increasing, establishing new lineages associated with large recent outbreaks. DENV lineages do not frequently spread back to Asia from the Americas or Africa, and we posit this is due to higher genetic diversity in Asia, leading to stiffer competition for invading lineages. Within the Americas, the network of DENV dispersal initiates in North America, primarily the Caribbean, and then is maintained by major hubs in South America. Overall, we find that travel volume, rather than climate factors, is mostly responsible for long-term patterns of DENV spread globally and within the Americas. Our results highlight key nodes in the global dynamics of DENV lineages, and suggest spread will continue to accelerate in a more connected world.

genomics↗

bioRxiv2026

baltic: the Backronymed Adaptable Lightweight Tree vIsualisation Code

For ten years, baltic (Backronymed Adaptable Lightweight Tree vIsualization Code) has been used to make annotated phylogeny figures in molecular epidemiology, including during the West African Ebola epidemic, the Zika epidemic in the Americas, and the SARS-CoV-2 pandemic, as well as other fields. At its core, baltic is a Python library used for the efficient parsing, traversal, manipulation, and visualisation of phylogenetic trees. It is a small library with few dependencies that reads tree formats common in phylodynamic analyses and gives the user leverage to interact with a lightweight tree data structure to produce publication-ready figures with matplotlib. We present baltic v1.0, its first formally released and documented version. baltic reads and writes BEAST Nexus, Newick, and Nextstrain/Auspice JSON, and can process large BEAST posterior tree files in parallel to extract user-defined posterior statistics. The same objects are used for tree manipulation and for plotting in a single script. New to this release: a set of rooting methods (midpoint rooting, rerooting on any branch, and root-to-tip regression); support for reticulate evolution, with reassortment and recombination edges; and composite figures that combine a tree with other data, such as Muller plots, skygrid plots, tanglegrams, and plots connecting trees to maps. The release includes a documentation site with an API reference, tutorials, and a matplotlib-style gallery of worked examples.

bioinformatics↗

bioRxiv2026

Phylodynamic Analysis of the Global Dispersal and Spatiotemporal Dynamics of HIV-1 Subtype C

HIV-1 subtype C is the most prevalent HIV clade globally, yet its cross-continental transmission dynamics remain incompletely resolved due to sampling biases and unquantified analytical uncertainty. We performed a large-scale phylodynamic analysis of 1,221 near full-length genomic sequences from 32 countries (1986-2019). Employing a stratified subsampling strategy to mitigate bias, we systematically benchmarked 16 method combinations, pairing four maximum likelihood phylogenetic tools (FastTree, IQ-TREE, PhyML, RAxML-NG) with four temporal dating methods (TempEst, LSD, treedater, TreeTime). Topological analysis revealed significant discordance between rapid heuristics and higher-precision estimators. The estimated time to the most recent common ancestor (TMRCA) and the timing of individual introductions were highly sensitive to the temporal dating method, while evolutionary rates varied across both phylogenetic and temporal tools. Crucially, counts of viral introductions and the reconstruction of spatial transmission networks were statistically robust across all 16 combinations. Phylogeographic reconstruction confirmed a dominant, recurring dispersal corridor from Africa to Europe, with independent secondary reservoirs in South America and Asia. Ancestral trait reconstruction demonstrated transmission is primarily driven by heterosexual networks, within which "Not Recorded" risk groups were phylogenetically nested. This multi-method benchmarking reveals that while exact chronologies are sensitive to methodological choices, spatial network reconstructions and source-sink classifications remain remarkably consistent. These findings provide a robust map of subtype Cs global expansion and establish highly reliable, scalable workflows for resolving spatial dissemination routes for real-time genomic epidemiology.

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↗

bioRxiv2026

Thirty years of Achromobacter ruhlandii evolution reveal pathways to epidemic lineages

BackgroundAchromobacter spp. are emerging opportunistic pathogens, associated with chronic infections, antimicrobial resistance, and poor clinical outcomes. The Danish epidemic strain (DES) of A. ruhlandii is highly drug-resistant and adapted to the cystic fibrosis (CF) airway, yet its evolutionary history and defining genomic features remain poorly understood. MethodsWe analysed genome and antibiotic susceptibility testing data for 58 longitudinally collected DES isolates sampled over 21 years at Rigshospitalet, Denmark. We combined these with 79 publicly available A. ruhlandii genomes and applied phylogenomics to infer DES emergence and transmission, and genome-wide association studies (GWAS) to identify lineage-specific and adaptive genomic features. ResultsDES forms a distinct monophyletic clade within A. ruhlandii, estimated to have emerged around 1990, with no evidence of dissemination beyond Denmark. GWAS identified key lineage-defining traits, including acquisition of large mobile genetic elements, plasmid integration events, and enrichment of resistance and iron acquisition genes. In addition, we detected other epidemic A. ruhlandii lineages with evidence of long-term persistence and inter-country spread, sharing similar genetic signatures of adaptation. ConclusionsThis study elucidates the genomic features associated with chronic infection and epidemic potential in A. ruhlandii. The DES lineage illustrates how extensive horizontal gene transfer, high intrinsic resistance potential, and enhanced host-adaptation traits, such as increased iron acquisition, can facilitate the emergence and persistence of successful epidemic lineages. These findings highlight shared evolutionary signatures of epidemic A. ruhlandii and underscore the need for continued genomic surveillance to detect and monitor emerging high-risk lineages in chronic infections.

bioinformatics↗

bioRxiv2025

Evidence of latency reshapes our understanding of Ebola virus reservoir dynamics

The reservoir of Ebola virus (EBOV) has remained a mystery since the first recorded zoonotic epidemic in 1976. While recent outbreaks have revealed much about the epidemiological dynamics that sustain human-to-human transmission, the mechanisms by which the virus persists between epidemics are unknown. Observations of extreme EBOV evolutionary rate heterogeneity in humans suggest latency is an important, yet untested, factor in persistence between epidemics. We here explicitly model latency with a novel phylogenetic approach to characterise the natural history of EBOV and, by extension, its reservoir. We find evidence that EBOV undergoes extended periods (i.e., possibly decades) of quiescence in the reservoir. Accounting for these dynamics significantly changes our understanding of EBOVs evolutionary past and its geographic spread through Central Africa.

evolutionary biology↗

bioRxiv2025

Phylogeographic analysis of Influenza D virus evolution

Influenza D virus (IDV), first identified in 2011 and primarily affecting cattle, has since been detected in a wide range of mammalian hosts and geographic regions. Despite widespread circulation in domestic cattle, the viruss evolutionary history and global migration dynamics remain poorly understood. This study presents the first comprehensive phylogeographic analysis of IDV using segment 4 (HEF gene) sequences. A time-calibrated Bayesian phylogeographic reconstruction suggests a most recent common ancestor around 1998, with the root most likely in the USA or Japan, although data biases limit definitive conclusions. Generalized linear models (GLMs) were used to assess potential drivers of viral spread, revealing strong associations with cattle trade and shared land borders. However, sequencing efforts heavily influence inferred migration patterns, emphasizing the role of sampling bias in such reconstructions. These findings highlight the mobility of IDV and the critical need for expanded genomic surveillance in underrepresented regions to better detect similar pathogens and understand their transmission dynamics.

evolutionary biology↗

bioRxiv2024

HIPSTR: highest independent posterior subtree reconstruction in TreeAnnotator X

In Bayesian phylogenetic and phylodynamic studies it is common to summarise the posterior distribution of trees with a time-calibrated consensus phylogeny. While the maximum clade credibility (MCC) tree is often used for this purpose, we here show that a novel consensus tree method - the highest independent posterior subtree reconstruction, or HIPSTR - contains consistently higher supported clades over MCC. We also provide faster computational routines for estimating both consensus trees in an updated version of TreeAnnotator X, an open-source software program that summarizes the information from a sample of trees and returns many helpful statistics such as individual clade credibilities contained in the consensus tree. HIPSTR and MCC reconstructions on two Ebola virus and two SARS-CoV-2 data sets show that HIPSTR yields consensus trees that consistently contain clades with higher support compared to MCC trees. The MCC trees regularly fail to include several clades with very high posterior probability ([≥] 0.95) as well as a large number of clades with moderate to high posterior probability ([≥] 0.50), whereas HIPSTR achieves near-perfect performance in this respect. HIPSTR also exhibits favorable computational performance over MCC in TreeAnnotator X. Comparison to the recently developed CCD0-MAP algorithm yielded mixed results, and requires more in-depth exploration in follow-up studies. TreeAnnotator X - which is part of the BEAST X (v10.5.0) software package - is available at https://github.com/beast-dev/beast-mcmc/releases.

bioinformatics↗

bioRxiv2024

Experimental comparison of mowing and mulching on snail communities in wet meadows

The condition of wet meadows nowadays depends mainly on human activities; the biodiversity and productivity of these habitats can only be maintained by appropriate management methods. Mowing and grazing are well-known traditional methods, but a new method, regular mulching - the fragmentation of plant material and its deposition in the area - is also increasingly used. The ecological impact of traditional management is still not fully known, and we know almost nothing about the effects of mulching. To better understand the impact of these methods we directly compared their effects on snails, an invertebrate taxon common in these habitats and known as good bioindicators. We experimentally manipulated management methods on two wet meadows in Northern Hungary, Europe, and surveyed their snail communities immediately before and one year after treatments. Our results showed that mowing had a detectable negative effect on the snail communities. On the other hand, mulching did not alter their characteristics. Therefore, mulching may be a more desirable method for short-term interventions on wet meadows, whilst at the same time also preserving their biodiversity.

ecology↗

bioRxiv2023

Evolutionary genomics identifies host-directed therapeutics to treat intracellular bacterial infections

Obligate intracellular bacteria shed essential biosynthetic pathways during their evolution towards host dependency, providing an opportunity for host-directed therapeutics. Using Rickettsiaceae as a model, we employed a novel computational pipeline called PoMeLo to systematically compare this cytosolic family of bacteria to the related Anaplasmataceae, which reside in a membrane-bound vacuole in the host cell. We identified 20 metabolic pathways that have been lost since the divergence of Anaplasmataceae and Rickettsiaceae, corresponding to the latters change to a cytosolic niche. We hypothesized that drug inhibition of these host metabolic pathways would reduce the levels of metabolites available to the bacteria, thereby inhibiting bacterial growth. We tested 22 commercially available inhibitors for 14 of the identified pathways and found that the majority (59%) reduced bacterial growth at concentrations that did not induce host cell cytotoxicity. Of these, 5 inhibitors with an IC50 under 5 M were tested to determine whether their mode of inhibition was bactericidal or bacteriostatic. Both mycophenolate mofetil, an inhibitor of inosine-5-monophosphate dehydrogenase in the purine biosynthesis pathway, and roseoflavin, an analog of riboflavin, displayed bactericidal activity. A complementary unbiased mass spectrometry-based metabolomics approach identified 14 pathways impacted by Rickettsia infection based on alterations in metabolite levels. Strikingly, 11 of these (79%) overlapped with those identified by our computational predictions. These in vitro validation studies support the feasibility of a novel evolutionary genomics-guided approach for host-directed antibiotic drug development against obligate pathogens. ImportanceMany pathogens have evolved to acquire essential metabolites from their host cell, while in turn shedding their own biosynthetic capacities. This leads to an interesting dilemma: on one hand, reduced genomes allow pathogens to save energy and replicate more quickly, while on the other hand, they become more dependent on the host cell for survival. This vulnerability can be exploited by identifying and therapeutically inhibiting the host pathways that are essential for pathogen survival. The significance of our research is in predicting the precise pathways lost during a pathogens evolutionary adaptation to parasitism and validating these predictions through targeted in vitro growth assays and an unbiased metabolomic survey of the host-pathogen interface.

genomics↗

bioRxiv2023

PoMeLo: a systematic computational approach to predicting metabolic loss in pathogen genomes

BackgroundGenome streamlining, the process by which genomes become smaller and encode fewer genes over time, is a common phenomenon among pathogenic bacteria. This reduction is driven by selection for faster replication and minimized energy expenditure in a nutrientrich environment. As pathogens evolve to become more reliant on the host, metabolic genes and resulting capabilities are lost in favor of siphoning metabolites from the host. Characterizing genome streamlining, gene loss, and pathway degradation can be useful in assessing pathogen metabolic dependency on host metabolism and identifying potential targets for host-directed therapeutics. ResultsPoMeLo (Predictor of Metabolic Loss) is a novel evolutionary genomics-guided computational approach for identifying metabolic gaps in the genomes of pathogenic bacteria. PoMeLo leverages a centralized public database of high-quality genomes and annotations and allows the user to compare an unlimited number of genomes across individual genes and pathways. PoMeLo runs locally using user-friendly prompts in a matter of minutes and generates tabular and visual outputs for users to compare predicted metabolic capacity between groups of bacteria and individual species. Each pathway is assigned a Predicted Metabolic Loss (PML) score to assess the magnitude of genome streamlining. Optionally, PoMeLo places results in an evolutionary context by including phylogenetic relationships in visual outputs. It can also initially compute phylogenetically-weighted mean genome sizes to identify genome streamlining events. Here we describe PoMeLo and demonstrate its use in identifying metabolic gaps in genomes of pathogenic Treponema species. ConclusionsPoMeLo represents an advance over existing methods for identifying metabolic gaps in genomic data, allowing comparison across large numbers of genomes and placing the resulting data in a phylogenetic context. PoMeLo is freely available for academic and nonacademic use at https://github.com/czbiohub-sf/pomelo.

bioinformatics↗

bioRxiv2022

Accumulated metagenomic studies reveal recent migration, whole genome evolution, and taxonomic incompleteness of orthomyxoviruses

Metagenomic studies have uncovered many novel viruses by looking beyond hosts of public health or economic interest. However, the resulting viral genomes are often incomplete, and analyses largely characterize the distribution of viruses over their dynamics. Here, we integrate accumulated data from metagenomic studies to reveal geographic and evolutionary dynamics in a case study of Orthomyxoviridae, the RNA virus family that includes influenza virus. First, we use sequences of the orthomyxovirid W[u]han mosquito virus 6 to track the migrations of its host. We then look at orthomyxovirus genome evolution, finding gene gain and loss across members of the family, especially in the surface proteins responsible for cell and host tropism. We find that the surface protein of W[u]han mosquito virus 6 exhibits accelerated non-synonymous evolution suggestive of antigenic evolution i.e. vertebrate infection, and belongs to a wider quaranjavirid group bearing highly diverged surface proteins. Finally we quantify the progress of orthomyxovirus discovery and forecast that many diverged Orthomyxoviridae members remain to be found. We argue that continued metagenomic studies will be fruitful for understanding the dynamics, evolution, ecology of viruses and their hosts, regardless of whether novel viruses are identified or not, as long as study designs allowing for the resolution of complete viral genomes are employed. 0.1 ImportanceThe number of known virus species has increased dramatically through metagenomic studies, which search genetic material sampled from a host for non-host genes. Here, we focus on an important viral family that includes influenza viruses, the Orthomyxoviridae, with over a hundred recently discovered viruses infecting hosts from humans to fish. We find one virus called W[u]han mosquito virus 6, discovered in mosquitoes in China, has spread across the globe very recently. Surface proteins used to enter cells show signs of rapid evolution in W[u]han mosquito virus 6 and its relatives which suggests an ability to infect vertebrate animals. We compute the rate at which new orthomyxovirus species discovered add evolutionary history to the tree of life, predict that many viruses remain to be discovered, and discuss what appropriately designed future studies can teach us about how diseases cross between continents and species.

evolutionary biology↗

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↗

bioRxiv2021

Reservoir host studies of Lloviu virus: first isolation, sequencing and serology in Schreiber's bats in Europe

IntroductoryFiloviruses are prime examples of emerging human pathogens that are transmitted to humans by zoonotic spillover events. Since their initial discovery, filovirus outbreaks have occured with increasing frequency and intensity. There is an urgent need to better understand their enzootic ecology and pathogenic potential, given recent zoonotic virus spillover events including the 2013-2016 West African Ebola virus (EBOV) epidemic. Several novel filoviruses have been discovered with a markedly wider geographic distribution than previously described. One of these novel filoviruses, Lloviu virus (LLOV), was first identified in 2002 in Schreibers bats (Miniopterus schreibersii) in Spain, Portugal, and southern France. Subsequently, in 2016, LLOV was detected during the passive monitoring of bats in Hungary. Here we report the first isolation of infectious Lloviu virus; from the blood of an asymptomatic Schreibers bat, subsequently cultivated in the Miniopterus sp. kidney cell line SuBK12-08. We also show that LLOV is able to infect monkey and human cells, suggesting that LLOV might have spillover potential. We performed a multi-year surveillance of LLOV and detected LLOV RNA in both deceased and asymptomatic live animals as well as in coupled ectoparasites from the families Nycteribiidae and Ixodidae. We present data on the natural infection and seropositivity of Schreibers bats and provide novel LLOV genomic sequence information from a bat host and an arthropod parasite. Our data support the role of bats, specifically Miniopterus schreibersii as natural reservoirs for the LLOV filovirus in Europe. We also suggest that bat-associated parasites might play a role in the natural ecology of filoviruses in temperate climate regions compared to filoviruses in the tropics. These results raise the possibility of cross-species transmission events via bat-human interactions.

microbiology↗

bioRxiv2021

Polymorphism of Genetic Ambigrams

Double synonyms in the genetic code can be used as a tool to test competing hypotheses regarding ambigrammatic narnavirus genomes. Applying the analysis to recent observations of Culex narnavirus 1 and Zhejiang mosquito virus 3 ambigrammatic viruses indicates that the open reading frame on the complementary strand of the segment coding for RNA-dependent RNA polymerase does not code for a functional protein. Culex narnavirus 1 has been shown to possess a second segment, also ambigrammatic, termed Robin. We find a comparable segment for Zhejiang mosquito virus 3, a moderately diverged relative of Culex narnavirus 1. Our analysis of Robin polymorphisms suggests that its reverse open reading frame also does not code for a functional protein. We make a hypothesis about its role.

genomics↗

bioRxiv2020

Multiple SARS-CoV-2 introductions shaped the early outbreak in Central Eastern Europe: comparing Hungarian data to a worldwide sequence data-matrix

Severe Acute Respiratory Syndrome Coronavirus 2 is the third highly pathogenic human coronavirus in history. Since the emergence in Hubei province, China, during late 2019 the situation evolved to pandemic level. Following China, Europe was the second epicenter of the pandemic. To better comprehend the detailed founder mechanisms of the epidemic evolution in Central-Eastern Europe, particularly in Hungary, we determined the full-length SARS-CoV-2 genomes from 32 clinical samples collected from laboratory confirmed COVID-19 patients over the first month of disease in Hungary. We applied a haplotype network analysis on all available complete genomic sequences of SARS-CoV-2 from GISAID database as of the 21th of April, 2020. We performed additional phylogenetic and phylogeographic analyses to achieve the recognition of multiple and parallel introductory events into our region. Here we present a publicly available network imaging of the worldwide haplotype relations of SARS-CoV-2 sequences and conclude the founder mechanisms of the outbreak in Central-Eastern Europe.

microbiology↗

bioRxiv2020

The latitudinal diversity gradient in brush-footed butterflies (Nymphalidae): conserved ancestral tropical niche but different continental histories.

The latitudinal diversity gradient (LDG) is arguably one of the most striking patterns in nature. The global increase in species richness toward the tropics across continents and taxonomic groups stimulated the formulation of many hypotheses to explain the underlying mechanisms of this pattern. We evaluated several of these hypotheses to explain spatial diversity patterns in the butterfly family, Nymphalidae, by assessing the contributions of speciation, extinction, and dispersal to the LDG, and also the extent to which these processes differ among regions at the same latitude. We generated a new, time-calibrated phylogeny of Nymphalidae based on 10 gene fragments and containing ca. 2,800 species ([~]45% of extant diversity). Neither speciation nor extinction rate variations consistently explain the LDG among regions because temporal diversification dynamics differ greatly across longitude. For example, we found that Neotropical nymphalid diversity results from low extinction rates, not high speciation rates, and that biotic interchanges with other regions were rare. Southeast Asia was also characterized by a low speciation rate but, unlike the Neotropics, was the main source of dispersal events through time. Our results suggest that global climate change throughout the Cenozoic, particularly during the Eocene-Oligocene transition, combined with the conserved ancestral tropical niches, played a major role in generating the modern LDG of butterflies.

ecology↗