BEAGLE 3: Improved Performance, Scaling, and Usability for a High-Performance Computing Library for Statistical Phylogenetics

Accurate, scalable, and fully automated inference of species trees from raw genome assemblies using ROADIES

Inference of species trees plays a crucial role in advancing our understanding of evolutionary relationships and has immense significance for diverse biological and medical applications. Extensive genome sequencing efforts are currently in progress across a broad spectrum of life forms, holding the potential to unravel the intricate branching patterns within the tree of life. However, estimating species trees starting from raw genome sequences is quite challenging, and the current cutting-edge methodologies require a series of error-prone steps that are neither entirely automated nor standardized. In this paper, we present ROADIES, a novel pipeline for species tree inference from raw genome assemblies that is fully automated, easy to use, scalable, free from reference bias, and provides flexibility to adjust the tradeoff between accuracy and runtime. The ROADIES pipeline eliminates the need to align whole genomes, choose a single reference species, or pre-select loci such as functional genes found using cumbersome annotation steps. Moreover, it leverages recent advances in phylogenetic inference to allow multi-copy genes, eliminating the need to detect orthology. Using the genomic datasets released from large-scale sequencing consortia across three diverse life forms (placental mammals, pomace flies, and birds), we show that ROADIES infers species trees that are comparable in quality with the state-of-the-art approaches but in a fraction of the time. By incorporating optimal approaches and automating all steps from assembled genomes to species and gene trees, ROADIES is poised to improve the accuracy, scalability, and reproducibility of phylogenomic analyses.

New Vibrio cholerae sequences from Eastern and Southern Africa alter our understanding of regional cholera transmission

Despite ongoing containment and vaccination efforts, cholera remains prevalent in many countries in sub-Saharan Africa. Part of the difficulty in containing cholera comes from our lack of understanding of how it circulates throughout the region. To better characterize regional transmission, we generated and analyzed 118 Vibrio cholerae genomes collected between 2007-2019 from five different countries in Southern and Eastern Africa. We showed that V. cholerae sequencing can be successful from a variety of sample types and filled in spatial and temporal gaps in our understanding of circulating lineages, including providing some of the first sequences from the 2018-2019 outbreaks in Uganda, Kenya, Tanzania, Zambia, and Malawi. Our results present a complex picture of cholera transmission in the region, with multiple lineages found to be co-circulating within several countries. We also find evidence that previously identified sporadic cases may be from larger, undersampled outbreaks, highlighting the need for careful examination of sampling biases and underscoring the need for continued and expanded cholera surveillance across the African continent.

Spatiotemporal genotype replacement of H5N8 avian influenza viruses contributed to H5N1 emergence in 2021/2022 panzootic

Since 2020, clade 2.3.4.4b highly pathogenic avian influenza H5N8 and H5N1 viruses have swept through continents, posing serious threats to the world. Through comprehensive analyses of epidemiological, genetic, and bird migration data, we found that the dominant genotype replacement of the H5N8 viruses in 2020 contributed to the H5N1 outbreak in the 2021/2022 wave. The 2020 outbreak of the H5N8 G1 genotype instead of the G0 genotype produced reassortment opportunities and led to the emergence of a new H5N1 virus with G1's HA and MP genes. Despite extensive reassortments in the 2021/2022 wave, the H5N1 virus retained the HA and MP genes, causing a significant outbreak in Europe and North America. Furtherly, through the wild bird migration flyways investigation, we found that the temporal-spatial coincidence between the outbreak of the H5N8 G1 virus and the bird autumn migration may have expanded the H5 viral spread, which may be one of the main drivers of the emergence of the 2020-2022 H5 panzootic.IMPORTANCESince 2020, highly pathogenic avian influenza (HPAI) H5 subtype variants of clade 2.3.4.4b have spread across continents, posing unprecedented threats globally. However, the factors promoting the genesis and spread of H5 HPAI viruses remain unclear. Here, we found that the spatiotemporal genotype replacement of H5N8 HPAI viruses contributed to the emergence of the H5N1 variant that caused the 2021/2022 panzootic, and the viral evolution in poultry of Egypt and surrounding area and autumn bird migration from the Russia-Kazakhstan region to Europe are important drivers of the emergence of the 2020-2022 H5 panzootic. These findings provide important targets for early warning and could help control the current and future HPAI epidemics.

Spatio-temporal spread and evolution of Lassa virus in West Africa

BACKGROUND

Lassa fever is a hemorrhagic disease caused by Lassa virus (LASV), which has been classified by the World Health Organization as one of the top infectious diseases requiring prioritized research. Previous studies have provided insights into the classification and geographic characteristics of LASV lineages. However, the factor of the distribution and evolution characteristics and phylodynamics of the virus was still limited.

METHODS

To enhance comprehensive understanding of LASV, we employed phylogenetic analysis, reassortment and recombination detection, and variation evaluation utilizing publicly available viral genome sequences.

RESULTS

The results showed the estimated the root of time of the most recent common ancestor (TMRCA) for large (L) segment was approximately 634 (95% HPD: [385879]), whereas the TMRCA for small (S) segment was around 1224 (95% HPD: [10301401]). LASV primarily spread from east to west in West Africa through two routes, and in route 2, the virus independently spread to surrounding countries through Liberia, resulting in a wider spread of LASV. From 1969 to 2018, the effective population size experienced two significant increased, indicating the enhanced genetic diversity of LASV. We also found the evolution rate of L segment was faster than S segment, further results showed zinc-binding protein had the fastest evolution rate. Reassortment events were detected in multiple lineages including sub-lineage IIg, while recombination events were observed within lineage V. Significant amino acid changes in the glycoprotein precursor of LASV were identified, demonstrating sequence diversity among lineages in LASV.

CONCLUSION

This study comprehensively elucidated the transmission and evolution of LASV in West Africa, providing detailed insights into reassortment events, recombination events, and amino acid variations.

Scalable gradients enable Hamiltonian Monte Carlo sampling for phylodynamic inference under episodic birth-death-sampling models

Birth-death models play a key role in phylodynamic analysis for their interpretation in terms of key epidemiological parameters. In particular, models with piecewise-constant rates varying at different epochs in time, to which we refer as episodic birth-death-sampling (EBDS) models, are valuable for their reflection of changing transmission dynamics over time. A challenge, however, that persists with current time-varying model inference procedures is their lack of computational efficiency. This limitation hinders the full utilization of these models in large-scale phylodynamic analyses, especially when dealing with high-dimensional parameter vectors that exhibit strong correlations. We present here a linear-time algorithm to compute the gradient of the birth-death model sampling density with respect to all time-varying parameters, and we implement this algorithm within a gradient-based Hamiltonian Monte Carlo (HMC) sampler to alleviate the computational burden of conducting inference under a wide variety of structures of, as well as priors for, EBDS processes. We assess this approach using three different real world data examples, including the HIV epidemic in Odesa, Ukraine, seasonal influenza A/H3N2 virus dynamics in New York state, America, and Ebola outbreak in West Africa. HMC sampling exhibits a substantial efficiency boost, delivering a 10- to 200-fold increase in minimum effective sample size per unit-time, in comparison to a Metropolis-Hastings-based approach. Additionally, we show the robustness of our implementation in both allowing for flexible prior choices and in modeling the transmission dynamics of various pathogens by accurately capturing the changing trend of viral effective reproductive number.

Dispersion patterns of SARS-CoV-2 variants Gamma, Lambda and Mu in Latin America and the Caribbean

Latin America and Caribbean (LAC) regions were an important epicenter of the COVID-19 pandemic and SARS-CoV-2 evolution. Through the COVID-19 Genomic Surveillance Regional Network (COVIGEN), LAC countries produced an important number of genomic sequencing data that made possible an enhanced SARS-CoV-2 genomic surveillance capacity in the Americas, paving the way for characterization of emerging variants and helping to guide the public health response. In this study we analyzed approximately 300,000 SARS-CoV-2 sequences generated between February 2020 and March 2022 by multiple genomic surveillance efforts in LAC and reconstructed the diffusion patterns of the main variants of concern (VOCs) and of interest (VOIs) possibly originated in the Region. Our phylogenetic analysis revealed that the spread of variants Gamma, Lambda and Mu reflects human mobility patterns due to variations of international air passenger transportation and gradual lifting of social distance measures previously implemented in countries. Our results highlight the potential of genetic data to reconstruct viral spread and unveil preferential routes of viral migrations that are shaped by human mobility patterns.

Genetic insights of H9N2 avian influenza viruses circulating in Mali and phylogeographic patterns in Northern and Western Africa

Avian influenza viruses (AIVs) of the H9N2 subtype have become widespread in Western Africa since their first detection in 2017 in Burkina Faso. However, the genetic characteristics and diffusion patterns of the H9N2 virus remain poorly understood in Western Africa, mainly due to limited surveillance activities. In addition, Mali, a country considered to play an important role in the epidemiology of AIVs in the region, lacks more comprehensive data on the genetic characteristics of these viruses, especially the H9N2 subtype. To better understand the genetic characteristics and spatio-temporal dynamics of H9N2 virus within this region, we carried out a comprehensive genetic characterization of H9N2 viruses collected through active surveillance in live bird markets in Mali between 2021 and 2022. We also performed a continuous phylogeographic analysis to unravel the dispersal history of H9N2 lineages between Northern and Western Africa. The identified Malian H9N2 virus belonged to the G1 lineage, similar to viruses circulating in both Western and Northern Africa, and possessed multiple molecular markers associated with an increased potential for zoonotic transmission and virulence. Notably, some Malian strains carried the R-S-N-R motif at their cleavage site, mainly observed in H9N2 strains in Asia. Our continuous phylogeographic analysis revealed a single and significant long-distance lineage dispersal event of the H9N2 virus to Western Africa, likely to have originated from Morocco in 2015, shaping the westward diffusion of the H9N2 virus. Our study highlights the need for long-term surveillance of H9N2 viruses in poultry populations in Western Africa, which is crucial for a better understanding of virus evolution and effective management against potential zoonotic AIV strain emergence.

Many-core algorithms for high-dimensional gradients on phylogenetic trees

MOTIVATION

Advancements in high-throughput genomic sequencing are delivering genomic pathogen data at an unprecedented rate, positioning statistical phylogenetics as a critical tool to monitor infectious diseases globally. This rapid growth spurs the need for efficient inference techniques, such as Hamiltonian Monte Carlo (HMC) in a Bayesian framework, to estimate parameters of these phylogenetic models where the dimensions of the parameters increase with the number of sequences N. HMC requires repeated calculation of the gradient of the data log-likelihood with respect to (wrt) all branch-length-specific (BLS) parameters that traditionally takes O(N2) operations using the standard pruning algorithm. A recent study proposes an approach to calculate this gradient in O(N), enabling researchers to take advantage of gradient-based samplers such as HMC. The CPU implementation of this approach makes the calculation of the gradient computationally tractable for nucleotide-based models but falls short in performance for larger state-space size models, such as Markov-modulated and codon models. Here, we describe novel massively parallel algorithms to calculate the gradient of the log-likelihood wrt all BLS parameters that take advantage of graphics processing units (GPUs) and result in many fold higher speedups over previous CPU implementations.

RESULTS

We benchmark these GPU algorithms on three computing systems using three evolutionary inference examples exploring complete genomes from 997 dengue viruses, 62 carnivore mitochondria and 49 yeasts, and observe a >128-fold speedup over the CPU implementation for codon-based models and >8-fold speedup for nucleotide-based models. As a practical demonstration, we also estimate the timing of the first introduction of West Nile virus into the continental Unites States under a codon model with a relaxed molecular clock from 104 full viral genomes, an inference task previously intractable.

AVAILABILITY AND IMPLEMENTATION

We provide an implementation of our GPU algorithms in BEAGLE v4.0.0 (https://github.com/beagle-dev/beagle-lib), an open-source library for statistical phylogenetics that enables parallel calculations on multi-core CPUs and GPUs. We employ a BEAGLE-implementation using the Bayesian phylogenetics framework BEAST (https://github.com/beast-dev/beast-mcmc).

Comparative evolution of influenza A virus H1 and H3 head and stalk domains across host species

IMPORTANCE

For decades, researchers have studied the rapid evolution of influenza A viruses for vaccine design and as a useful model system for the study of host/parasite evolution. By performing an exhaustive analysis of hemagglutinin protein (HA) sequences from 49 lineages independently evolving in birds, swine, canines, equines, and humans over the last century, our work uncovers surprising features of HA evolution. In particular, the canine H3 stalk, unlike human H3 and H1 stalk domains, is not evolving slowly, suggesting that evolution in the stalk domain is not universally constrained across all host species. Therefore, a broader multi-host perspective on HA evolution may be useful during the evaluation and design of stalk-targeted vaccine candidates.

African bushpigs exhibit porous species boundaries and appeared in Madagascar concurrently with human arrival

Several African mammals exhibit a phylogeographic pattern where closely related taxa are split between West/Central and East/Southern Africa, but their evolutionary relationships and histories remain controversial. Bushpigs (Potamochoerus larvatus) and red river hogs (P. porcus) are recognised as separate species due to morphological distinctions, a perceived lack of interbreeding at contact, and putatively old divergence times, but historically, they were considered conspecific. Moreover, the presence of Malagasy bushpigs as the sole large terrestrial mammal shared with the African mainland raises intriguing questions about its origin and arrival in Madagascar. Analyses of 67 whole genomes revealed a genetic continuum between the two species, with putative signatures of historical gene flow, variable FST values, and a recent divergence time (<500,000 years). Thus, our study challenges key arguments for splitting Potamochoerus into two species and suggests their speciation might be incomplete. Our findings also indicate that Malagasy bushpigs diverged from southern African populations and underwent a limited bottleneck 1000-5000 years ago, concurrent with human arrival in Madagascar. These results shed light on the evolutionary history of an iconic and widespread African mammal and provide insight into the longstanding biogeographic puzzle surrounding the bushpig's presence in Madagascar.

Genomic surveillance reveals dynamic shifts in the connectivity of COVID-19 epidemics

The maturation of genomic surveillance in the past decade has enabled tracking of the emergence and spread of epidemics at an unprecedented level. During the COVID-19 pandemic, for example, genomic data revealed that local epidemics varied considerably in the frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage importation and persistence, likely due to a combination of COVID-19 restrictions and changing connectivity. Here, we show that local COVID-19 epidemics are driven by regional transmission, including across international boundaries, but can become increasingly connected to distant locations following the relaxation of public health interventions. By integrating genomic, mobility, and epidemiological data, we find abundant transmission occurring between both adjacent and distant locations, supported by dynamic mobility patterns. We find that changing connectivity significantly influences local COVID-19 incidence. Our findings demonstrate a complex meaning of "local" when investigating connected epidemics and emphasize the importance of collaborative interventions for pandemic prevention and mitigation.

Complete genome reconstruction of the global and European regional dispersal history of the lumpy skin disease virus

IMPORTANCE

Lumpy skin disease virus (LSDV) has a complex epidemiology involving multiple strains, recombination, and vaccination. Its DNA genome provides limited genetic variation to trace outbreaks in space and time. Sequencing of LSDV whole genomes has also been patchy at global and regional scales. Here, we provide the first fine-grained whole genome sequence sampling of a constrained LSDV outbreak (southeastern Europe, 2015-2017), which we analyze along with global publicly available genomes. We formally evaluate the past occurrence of recombination events as well as the temporal signal that is required for calibrating molecular clock models and subsequently conduct a time-calibrated spatially explicit phylogeographic reconstruction. Our study further illustrates the importance of accounting for recombination events before reconstructing global and regional dynamics of DNA viruses. More LSDV whole genomes from endemic areas are needed to obtain a comprehensive understanding of global LSDV dispersal dynamics.

Scalable gradients enable Hamiltonian Monte Carlo sampling for phylodynamic inference under episodic birth-death-sampling models

Birth-death models play a key role in phylodynamic analysis for their interpretation in terms of key epidemiological parameters. In particular, models with piecewise-constant rates varying at different epochs in time, to which we refer as episodic birth-death-sampling (EBDS) models, are valuable for their reflection of changing transmission dynamics over time. A challenge, however, that persists with current time-varying model inference procedures is their lack of computational efficiency. This limitation hinders the full utilization of these models in large-scale phylodynamic analyses, especially when dealing with high-dimensional parameter vectors that exhibit strong correlations. We present here a linear-time algorithm to compute the gradient of the birth-death model sampling density with respect to all time-varying parameters, and we implement this algorithm within a gradient-based Hamiltonian Monte Carlo (HMC) sampler to alleviate the computational burden of conducting inference under a wide variety of structures of, as well as priors for, EBDS processes. We assess this approach using three different real world data examples, including the HIV epidemic in Odesa, Ukraine, seasonal influenza A/H3N2 virus dynamics in New York state, America, and Ebola outbreak in West Africa. HMC sampling exhibits a substantial efficiency boost, delivering a 10- to 200-fold increase in minimum effective sample size per unit-time, in comparison to a Metropolis-Hastings-based approach. Additionally, we show the robustness of our implementation in both allowing for flexible prior choices and in modeling the transmission dynamics of various pathogens by accurately capturing the changing trend of viral effective reproductive number.

Online tree expansion could help solve the problem of scalability in Bayesian phylogenetics

Bayesian phylogenetics is now facing a critical point. Over the last 20 years, Bayesian methods have reshaped phylogenetic inference and gained widespread popularity due to their high accuracy, the ability to quantify the uncertainty of inferences and the possibility of accommodating multiple aspects of evolutionary processes in the models that are used. Unfortunately, Bayesian methods are computationally expensive, and typical applications involve at most a few hundred sequences. This is problematic in the age of rapidly expanding genomic data and increasing scope of evolutionary analyses, forcing researchers to resort to less accurate but faster methods, such as maximum parsimony and maximum likelihood. Does this spell doom for Bayesian methods? Not necessarily. Here, we discuss some recently proposed approaches that could help scale up Bayesian analyses of evolutionary problems considerably. We focus on two particular aspects: online phylogenetics, where new data sequences are added to existing analyses, and alternatives to Markov chain Monte Carlo (MCMC) for scalable Bayesian inference. We identify 5 specific challenges and discuss how they might be overcome. We believe that online phylogenetic approaches and Sequential Monte Carlo hold great promise and could potentially speed up tree inference by orders of magnitude. We call for collaborative efforts to speed up the development of methods for real-time tree expansion through online phylogenetics.

Scalable Bayesian Divergence Time Estimation With Ratio Transformations

Divergence time estimation is crucial to provide temporal signals for dating biologically important events from species divergence to viral transmissions in space and time. With the advent of high-throughput sequencing, recent Bayesian phylogenetic studies have analyzed hundreds to thousands of sequences. Such large-scale analyses challenge divergence time reconstruction by requiring inference on highly correlated internal node heights that often become computationally infeasible. To overcome this limitation, we explore a ratio transformation that maps the original $N-1$ internal node heights into a space of one height parameter and $N-2$ ratio parameters. To make the analyses scalable, we develop a collection of linear-time algorithms to compute the gradient and Jacobian-associated terms of the log-likelihood with respect to these ratios. We then apply Hamiltonian Monte Carlo sampling with the ratio transform in a Bayesian framework to learn the divergence times in 4 pathogenic viruses (West Nile virus, rabies virus, Lassa virus, and Ebola virus) and the coralline red algae. Our method both resolves a mixing issue in the West Nile virus example and improves inference efficiency by at least 5-fold for the Lassa and rabies virus examples as well as for the algae example. Our method now also makes it computationally feasible to incorporate mixed-effects molecular clock models for the Ebola virus example, confirms the findings from the original study, and reveals clearer multimodal distributions of the divergence times of some clades of interest.

Epidemiology, genetic diversity, and evolutionary dynamics of Tembusu virus

Tembusu virus (TMUV) is an emerging pathogenic flavivirus associated with acute egg-drop and fatal encephalitis in domestic waterfowl. Since its initial identification in mosquitoes in 1955, TMUV has been confirmed to infect ducks, pigeons, sparrows, geese, and chickens, posing a significant threat to the poultry industry. Here, we sequenced two DTMUV strains isolated in 2019 and systematically investigated the possible origin, genetic relationships, evolutionary dynamics, and transmission patterns of TMUV based on complete virus genome sequences in the public database. We found that TMUV can be divided into four major clusters: TMUV, cluster 1, cluster 2, and cluster 3. Interestingly, we found that cluster 2.2 (within cluster 2) is the most commonly involved in interspecies transmission events, and subcluster 2.1.2 (within cluster 2.1) is currently the most prevalent cluster circulating in Asia. Notably, we also identified three positively selected sites in the E and NS1 proteins, which may be involved in virus replication, immune evasion, and host adaptation. Finally, phylogeographic analysis revealed that cluster dispersal originated in Southeast Asia and that short-distance transmission events have occurred frequently. Altogether, these data provide novel insights into the evolution and dispersal of TMUV, facilitating the development of rapid diagnostics, vaccines, and therapeutics against TMUV infection.

Highly pathogenic avian influenza A (H5N1) in marine mammals and seabirds in Peru

Highly pathogenic avian influenza (HPAI) A/H5N1 viruses (lineage 2.3.4.4b) are rapidly invading the Americas, threatening wildlife, poultry, and potentially evolving into the next global pandemic. In November 2022 HPAI arrived in Peru, triggering massive pelican and sea lion die-offs. We report genomic characterization of HPAI/H5N1 in five species of marine mammals and seabirds (dolphins, sea lions, sanderlings, pelicans and cormorants). Peruvian viruses belong to lineage 2.3.4.4b, but they are 4:4 reassortants where 4 genomic segments (PA, HA, NA and MP) position within the Eurasian lineage that initially entered North America from Eurasia, while the other 4 genomic segments (PB2, PB1, NP and NS) position within the American lineage (clade C) that circulated in North America. These viruses are rapidly accruing mutations, including mutations of concern, that warrant further examination and highlight an urgent need for active local surveillance to manage outbreaks and limit spillover into other species, including humans.

Uncovering the endemic circulation of rabies in Cambodia

In epidemiology, endemicity characterizes sustained pathogen circulation in a geographical area, which involves a circulation that is not being maintained by external introductions. Because it could potentially shape the design of public health interventions, there is an interest in fully uncovering the endemic pattern of a disease. Here, we use a phylogeographic approach to investigate the endemic signature of rabies virus (RABV) circulation in Cambodia. Cambodia is located in one of the most affected regions by rabies in the world, but RABV circulation between and within Southeast Asian countries remains understudied. Our analyses are based on a new comprehensive data set of 199 RABV genomes collected between 2014 and 2017 as well as previously published Southeast Asian RABV sequences. We show that most Cambodian sequences belong to a distinct clade that has been circulating almost exclusively in Cambodia. Our results thus point towards rabies circulation in Cambodia that does not rely on external introductions. We further characterize within-Cambodia RABV circulation by estimating lineage dispersal metrics that appear to be similar to other settings, and by performing landscape phylogeographic analyses to investigate environmental factors impacting the dispersal dynamic of viral lineages. The latter analyses do not lead to the identification of environmental variables that would be associated with the heterogeneity of viral lineage dispersal velocities, which calls for a better understanding of local dog ecology and further investigations of the potential drivers of RABV spread in the region. Overall, our study illustrates how phylogeographic investigations can be performed to assess and characterize viral endemicity in a context of relatively limited data.

Evolutionary dynamics and adaptive analysis of Seneca Valley virus

Over the past 20 years, the Seneca Valley virus (SVV) has emerged in various countries and regions around the world. Infected pigs display symptoms similar to foot-and-mouth disease and other vesicular diseases, causing severe economic losses to affected countries. In recent years, the number of SVV infections has been increasing in Brazil, China, and the United States. In this study, we comprehensively analyzed SVV genomic sequence data from the perspectives of evolutionary dynamics, phylogeography, and codon usage bias. We aimed to gain further insights into SVV's genetic diversity, spatiotemporal distribution patterns, and evolutionary adaptations. Phylogenetic analysis revealed that SVV has evolved into eight distinct lineages. Based on the results of phylogeographic analysis, it is speculated that the United States might have been the source of SVV, from where it subsequently spread to different countries and regions. Moreover, our analysis of positive selection sites in SVV capsid proteins suggests their potential importance in the process of receptor recognition. Finally, codon preference analysis indicates that natural selection has been a primary evolutionary driver influencing SVV codon usage bias. In conclusion, our in-depth investigation into SVV's origin, dissemination, evolution, and adaptation emphasizes the significance of SVV surveillance and control measures.

Accelerated evolution of SARS-CoV-2 in free-ranging white-tailed deer

The zoonotic origin of the COVID-19 pandemic virus highlights the need to fill the vast gaps in our knowledge of SARS-CoV-2 ecology and evolution in non-human hosts. Here, we detected that SARS-CoV-2 was introduced from humans into white-tailed deer more than 30 times in Ohio, USA during November 2021-March 2022. Subsequently, deer-to-deer transmission persisted for 2-8 months, disseminating across hundreds of kilometers. Newly developed Bayesian phylogenetic methods quantified how SARS-CoV-2 evolution is not only three-times faster in white-tailed deer compared to the rate observed in humans but also driven by different mutational biases and selection pressures. The long-term effect of this accelerated evolutionary rate remains to be seen as no critical phenotypic changes were observed in our animal models using white-tailed deer origin viruses. Still, SARS-CoV-2 has transmitted in white-tailed deer populations for a relatively short duration, and the risk of future changes may have serious consequences for humans and livestock.

Newly identified lineages of porcine hemagglutinating encephalomyelitis virus exhibit respiratory phenotype

Swine pathogens have a long history of zoonotic transmission to humans, occasionally leading to sustained outbreaks or pandemics. Through a retrospective epidemiological study of swine populations in China, we describe novel lineages of porcine hemagglutinating encephalomyelitis virus (PHEV) complex coronaviruses (CoVs) that cause exclusively respiratory symptoms with no signs of the neurological symptoms typically associated with classical PHEV infection. Through large-scale epidemiological surveillance, we show that these novel lineages have circulated in at least eight provinces in southeastern China. Phylogenetic and recombination analyses of twenty-four genomes identified two major viral lineages causing respiratory symptoms with extensive recombination within them, between them, and between classical PHEV and the novel respiratory variant PHEV (rvPHEV) lineages. Divergence times among the sampled lineages in the PHEV virus complex date back to 1886-1958 (mean estimate 1928), with the two major rvPHEV lineages separating approximately 20 years later. Many rvPHEV viruses show amino acid substitutions at the carbohydrate-binding site of hemagglutinin esterase (HE) and/or have lost the cysteine required for HE dimerization. This resembles the early adaptation of human CoVs, where HE lost its hemagglutination ability to adapt to growth in the human respiratory tract. Our study represents the first report of the evolutionary history of rvPHEV circulating in swine and highlights the importance of characterizing CoV diversity and recombination in swine to identify pathogens with outbreak potential that could threaten swine farming.

A topology-marginal composite likelihood via a generalized phylogenetic pruning algorithm

Bayesian phylogenetics is a computationally challenging inferential problem. Classical methods are based on random-walk Markov chain Monte Carlo (MCMC), where random proposals are made on the tree parameter and the continuous parameters simultaneously. Variational phylogenetics is a promising alternative to MCMC, in which one fits an approximating distribution to the unnormalized phylogenetic posterior. Previous work fit this variational approximation using stochastic gradient descent, which is the canonical way of fitting general variational approximations. However, phylogenetic trees are special structures, giving opportunities for efficient computation. In this paper we describe a new algorithm that directly generalizes the Felsenstein pruning algorithm (a.k.a. sum-product algorithm) to compute a composite-like likelihood by marginalizing out ancestral states and subtrees simultaneously. We show the utility of this algorithm by rapidly making point estimates for branch lengths of a multi-tree phylogenetic model. These estimates accord with a long MCMC run and with estimates obtained using a variational method, but are much faster to obtain. Thus, although generalized pruning does not lead to a variational algorithm as such, we believe that it will form a useful starting point for variational inference.

Genomic Detection of the Emerging, Highly Pathogenic HIV-1 Subtype D in Bahia, Northeast Brazil

(1) Background: The HIV subtype D is generally associated with a faster decline in CD4+ T cell counts, a higher viral load, and a faster progression to AIDS. However, it is still poorly characterized in Brazil. In this study, we used genomics and epidemiological data to investigate the transmission dynamics of HIV subtype D in the state of Bahia, Northeast Brazil. (2) Methods: To achieve this goal, we obtained four novel HIV-1 subtype D partial pol genome sequences using the Sanger method. To understand the emergence of this novel subtype in the state of Bahia, we used phylodynamic analysis on a dataset comprising 3704 pol genome sequences downloaded from the Los Alamos database. (3) Results: Our analysis revealed three branching patterns, indicating multiple introductions of the HIV-1 subtype D in Brazil from the late 1980s to the late 2000s and a single introduction event in the state of Bahia. Our data further suggest that these introductions most likely originated from European, Eastern African, Western African, and Southern African countries. (4) Conclusion: Understanding the distribution of HIV-1 viral strains and their temporal dynamics is crucial for monitoring the real-time evolution of circulating subtypes and recombinant forms, as well as for designing novel diagnostic and vaccination strategies. We advocate for a shift to active surveillance, to ensure adequate preparedness for future epidemics mediated by emerging viral strains.

The recency and geographical origins of the bat viruses ancestral to SARS-CoV and SARS-CoV-2

The emergence of SARS-CoV in 2002 and SARS-CoV-2 in 2019 has led to increased sampling of related sarbecoviruses circulating primarily in horseshoe bats. These viruses undergo frequent recombination and exhibit spatial structuring across Asia. Employing recombination-aware phylogenetic inference on bat sarbecoviruses, we find that the closest-inferred bat virus ancestors of SARS-CoV and SARS-CoV-2 existed just ~1-3 years prior to their emergence in humans. Phylogeographic analyses examining the movement of related sarbecoviruses demonstrate that they traveled at similar rates to their horseshoe bat hosts and have been circulating for thousands of years in Asia. The closest-inferred bat virus ancestor of SARS-CoV likely circulated in western China, and that of SARS-CoV-2 likely circulated in a region comprising southwest China and northern Laos, both a substantial distance from where they emerged. This distance and recency indicate that the direct ancestors of SARS-CoV and SARS-CoV-2 could not have reached their respective sites of emergence via the bat reservoir alone. Our recombination-aware dating and phylogeographic analyses reveal a more accurate inference of evolutionary history than performing only whole-genome or single gene analyses. These results can guide future sampling efforts and demonstrate that viral genomic fragments extremely closely related to SARS-CoV and SARS-CoV-2 were circulating in horseshoe bats, confirming their importance as the reservoir species for SARS viruses.

Cross-species transmission and PB2 mammalian adaptations of highly pathogenic avian influenza A/H5N1 viruses in Chile

H5N1 highly pathogenic avian influenza viruses (HPAIV) emerged in wild birds in Chile in December 2022 and spilled over into poultry, marine mammals, and one human. Between December 9, 2022 - March 14, 2023, a coordinated government/academic response detected HPAIV by real-time RT-PCR in 8.5% (412/4735) of samples from 23 avian and 3 mammal orders. Whole-genome sequences obtained from 77 birds and 8 marine mammals revealed that all Chilean H5N1 viruses belong to lineage 2.3.4.4b and cluster monophyletically with viruses from Peru, indicating a single introduction from North America into Peru/Chile. Mammalian adaptations were identified in the PB2 segment: D701N in two sea lions, one human, and one shorebird, and Q591K in the human and one sea lion. Minor variant analysis revealed that D701N was present in 52.9 - 70.9% of sequence reads, indicating the presence of both genotypes within hosts. Further surveillance of spillover events is warranted to assess the emergence and potential onward transmission of mammalian adapted H5N1 HPAIV in South America.

Automatic Differentiation is no Panacea for Phylogenetic Gradient Computation

Gradients of probabilistic model likelihoods with respect to their parameters are essential for modern computational statistics and machine learning. These calculations are readily available for arbitrary models via "automatic differentiation" implemented in general-purpose machine-learning libraries such as TensorFlow and PyTorch. Although these libraries are highly optimized, it is not clear if their general-purpose nature will limit their algorithmic complexity or implementation speed for the phylogenetic case compared to phylogenetics-specific code. In this paper, we compare six gradient implementations of the phylogenetic likelihood functions, in isolation and also as part of a variational inference procedure. We find that although automatic differentiation can scale approximately linearly in tree size, it is much slower than the carefully implemented gradient calculation for tree likelihood and ratio transformation operations. We conclude that a mixed approach combining phylogenetic libraries with machine learning libraries will provide the optimal combination of speed and model flexibility moving forward.

Analyses of Early ZIKV Genomes Are Consistent with Viral Spread from Northeast Brazil to the Americas

The Americas, particularly Brazil, were greatly impacted by the widespread Zika virus (ZIKV) outbreak in 2015 and 2016. Efforts were made to implement genomic surveillance of ZIKV as part of the public health responses. The accuracy of spatiotemporal reconstructions of the epidemic spread relies on the unbiased sampling of the transmission process. In the early stages of the outbreak, we recruited patients exhibiting clinical symptoms of arbovirus-like infection from Salvador and Campo Formoso, Bahia, in Northeast Brazil. Between May 2015 and June 2016, we identified 21 cases of acute ZIKV infection and subsequently recovered 14 near full-length sequences using the amplicon tiling multiplex approach with nanopore sequencing. We performed a time-calibrated discrete phylogeographic analysis to trace the spread and migration history of the ZIKV. Our phylogenetic analysis supports a consistent relationship between ZIKV migration from Northeast to Southeast Brazil and its subsequent dissemination beyond Brazil. Additionally, our analysis provides insights into the migration of ZIKV from Brazil to Haiti and the role Brazil played in the spread of ZIKV to other countries, such as Singapore, the USA, and the Dominican Republic. The data generated by this study enhances our understanding of ZIKV dynamics and supports the existing knowledge, which can aid in future surveillance efforts against the virus.

Influenza A viruses in gulls in landfills and freshwater habitats in Minnesota, United States

Introduction: The unpredictable evolution of avian influenza viruses (AIVs) presents an ongoing threat to agricultural production and public and wildlife health. Severe outbreaks of highly pathogenic H5N1 viruses in US poultry and wild birds since 2022 highlight the urgent need to understand the changing ecology of AIV. Surveillance of gulls in marine coastal environments has intensified in recent years to learn how their long-range pelagic movements potentially facilitate inter-hemispheric AIV movements. In contrast, little is known about inland gulls and their role in AIV spillover, maintenance, and long-range dissemination. Methods: To address this gap, we conducted active AIV surveillance in ring-billed gulls (Larus delawarensis) and Franklin's gulls (Leucophaeus pipixcan) in Minnesota's natural freshwater lakes during the summer breeding season and in landfills during fall migration (1,686 samples). Results: Whole-genome AIV sequences obtained from 40 individuals revealed three-lineage reassortants with a mix of genome segments from the avian Americas lineage, avian Eurasian lineage, and a global "Gull" lineage that diverged more than 50 years ago from the rest of the AIV global gene pool. No poultry viruses contained gull-adapted H13, NP, or NS genes, pointing to limited spillover. Geolocators traced gull migration routes across multiple North American flyways, explaining how inland gulls imported diverse AIV lineages from distant locations. Migration patterns were highly varied and deviated far from assumed "textbook" routes. Discussion: Viruses circulating in Minnesota gulls during the summer breeding season in freshwater environments reappeared in autumn landfills, evidence of AIV persistence in gulls between seasons and transmission between habitats. Going forward, wider adoption of technological advances in animal tracking devices and genetic sequencing is needed to expand AIV surveillance in understudied hosts and habitats.

Genome-Scale Analysis Reveals Extensive Diversification of Voltage-Gated K+ Channels in Stem Cnidarians

Ion channels are highly diverse in the cnidarian model organism Nematostella vectensis (Anthozoa), but little is known about the evolutionary origins of this channel diversity and its conservation across Cnidaria. Here, we examined the evolution of voltage-gated K+ channels in Cnidaria by comparing genomes and transcriptomes of diverse cnidarian species from Anthozoa and Medusozoa. We found an average of over 40 voltage-gated K+ channel genes per species, and a phylogenetic reconstruction of the Kv, KCNQ, and Ether-a-go-go (EAG) gene families identified 28 voltage-gated K+ channels present in the last common ancestor of Anthozoa and Medusozoa (23 Kv, 1 KCNQ, and 4 EAG). Thus, much of the diversification of these channels took place in the stem cnidarian lineage prior to the emergence of modern cnidarian classes. In contrast, the stem bilaterian lineage, from which humans evolved, contained no more than nine voltage-gated K+ channels. These results hint at a complexity to electrical signaling in all cnidarians that contrasts with the perceived anatomical simplicity of their neuromuscular systems. These data provide a foundation from which the function of these cnidarian channels can be investigated, which will undoubtedly provide important insights into cnidarian physiology.

Delta-Omicron recombinant escapes therapeutic antibody neutralization

The emergence of recombinant viruses is a threat to public health, as recombination may integrate variant-specific features that together result in escape from treatment or immunity. The selective advantages of recombinant SARS-CoV-2 isolates over their parental lineages remain unknown. We identified a Delta-Omicron (AY.45-BA.1) recombinant in an immunosuppressed transplant recipient treated with monoclonal antibody Sotrovimab. The single recombination breakpoint is located in the spike N-terminal domain adjacent to the Sotrovimab binding site. While Delta and BA.1 are sensitive to Sotrovimab neutralization, the Delta-Omicron recombinant is highly resistant. To our knowledge, this is the first described instance of recombination between circulating SARS-CoV-2 variants as a functional mechanism of resistance to treatment and immune escape.

Accelerated evolution of SARS-CoV-2 in free-ranging white-tailed deer

While SARS-CoV-2 has sporadically infected a wide range of animal species worldwide1, the virus has been repeatedly and frequently detected in white-tailed deer in North America2â€"7. The zoonotic origins of this pandemic virus highlight the need to fill the vast gaps in our knowledge of SARS-CoV-2 ecology and evolution in non-human hosts. Here, we detected SARS-CoV-2 was introduced from humans into white-tailed deer more than 30 times in Ohio, USA during November 2021-March 2022. Subsequently, deer-to-deer transmission persisted for 2-8 months, which disseminated across hundreds of kilometers. We discovered that alpha and delta variants evolved in white-tailed deer at three-times the rate observed in humans. Newly developed Bayesian phylogenetic methods quantified how SARS-CoV-2 evolution is not only faster in white-tailed deer but driven by different mutational biases and selection pressures. White-tailed deer are not just short-term recipients of human viral diversity but serve as reservoirs for alpha and other variants to evolve in new directions after going extinct in humans. The long-term effect of this accelerated evolutionary rate remains to be seen as no critical phenotypic changes were observed in our animal model experiments using viruses isolated from white-tailed deer. Still, SARS-CoV-2 viruses have transmitted in white-tailed deer populations for a relatively short duration, and the risk of future changes may have serious consequences for humans and livestock.

Early Genomic Surveillance and Phylogeographic Analysis of Getah Virus, a Reemerging Arbovirus, in Livestock in China

Getah virus (GETV) mainly causes disease in livestock and may pose an epidemic risk due to its expanding host range and the potential of long-distance dispersal through animal trade. Here, we used metagenomic next-generation sequencing (mNGS) to identify GETV as the pathogen responsible for reemerging swine disease in China and subsequently estimated key epidemiological parameters using phylodynamic and spatially-explicit phylogeographic approaches. The GETV isolates were able to replicate in a variety of cell lines, including human cells, and showed high pathogenicity in a mouse model, suggesting the potential for more mammal hosts. We obtained 16 complete genomes and 79 E2 gene sequences from viral strains collected in China from 2016 to 2021 through large-scale surveillance among livestock, pets, and mosquitoes. Our phylogenetic analysis revealed that three major GETV lineages are responsible for the current epidemic in livestock in China. We identified three potential positively selected sites and mutations of interest in E2, which may impact the transmissibility and pathogenicity of the virus. Phylodynamic inference of the GETV demographic dynamics identified an association between livestock meat consumption and the evolution of viral genetic diversity. Finally, phylogeographic reconstruction of GETV dispersal indicated that the sampled lineages have preferentially circulated within areas associated with relatively higher mean annual temperature and pig population density. Our results highlight the importance of continuous surveillance of GETV among livestock in southern Chinese regions associated with relatively high temperatures. IMPORTANCE Although livestock is known to be the primary reservoir of Getah virus (GETV) in Asian countries, where identification is largely based on serology, the evolutionary history and spatial epidemiology of GETV in these regions remain largely unknown. Through our sequencing efforts, we provided robust support for lineage delineation of GETV and identified three major lineages that are responsible for the current epidemic in livestock in China. We further analyzed genomic and epidemiological data to reconstruct the recent demographic and dispersal history of GETV in domestic animals in China and to explore the impact of environmental factors on its genetic diversity and its diffusion. Notably, except for livestock meat consumption, other pig-related factors such as the evolution of live pig transport and pork production do not show a significant association with the evolution of viral genetic diversity, pointing out that further studies should investigate the potential contribution of other host species to the GETV outbreak. Our analysis of GETV demonstrates the need for wider animal species surveillance and provides a baseline for future studies of the molecular epidemiology and early warning of emerging arboviruses in China.

Multiple Introductions of SARS-CoV-2 Alpha and Delta Variants into White-Tailed Deer in Pennsylvania

The SARS-CoV-2 pandemic began by viral spillover from animals to humans; today multiple animal species are known to be susceptible to infection. White-tailed deer, Odocoileus virginianus, are infected in North America at substantial levels, and genomic data suggests that a variant in deer may have spilled back to humans. Here, we characterize SARS-CoV-2 in deer from Pennsylvania (PA) sampled during fall and winter 2021. Of 123 nasal swab samples analyzed by RT-qPCR, 20 (16.3%) were positive for SARS-CoV-2. Seven whole genome sequences were obtained, together with six more partial spike gene sequences. These annotated as alpha and delta variants, the first reported observations of these lineages in deer, documenting multiple new jumps from humans to deer. The alpha lineage persisted in deer after its displacement by delta in humans, and deer-derived alpha variants diverged significantly from those in humans, consistent with a distinctive evolutionary trajectory in deer. IMPORTANCE Coronaviruses have been documented to replicate in numerous species of vertebrates, and multiple spillovers of coronaviruses from animals into humans have founded human epidemics. The COVID-19 epidemic likely derived from a spillover of SARS-CoV-2 from bats into humans, possibly via an intermediate host. There are now several examples of SARS-CoV-2 jumping from humans into other mammals, including mink and deer, creating the potential for new animal reservoirs from which spillback into humans could occur. For this reason, data on formation of new animal reservoirs is of great importance for understanding possible sources of future infection. Here, we identify extensive infection in white-tailed deer in Pennsylvania, including what appear to be multiple independent transmissions. Data further suggests possible transmission among deer. These data thus help identify a potential new animal reservoir and provide background information relevant to its management.

Scalable Bayesian phylogenetics

Recent advances in Bayesian phylogenetics offer substantial computational savings to accommodate increased genomic sampling that challenges traditional inference methods. In this review, we begin with a brief summary of the Bayesian phylogenetic framework, and then conceptualize a variety of methods to improve posterior approximations via Markov chain Monte Carlo (MCMC) sampling. Specifically, we discuss methods to improve the speed of likelihood calculations, reduce MCMC burn-in, and generate better MCMC proposals. We apply several of these techniques to study the evolution of HIV virulence along a 1536-tip phylogeny and estimate the internal node heights of a 1000-tip SARS-CoV-2 phylogenetic tree in order to illustrate the speed-up of such analyses using current state-of-the-art approaches. We conclude our review with a discussion of promising alternatives to MCMC that approximate the phylogenetic posterior. This article is part of a discussion meeting issue 'Genomic population structures of microbial pathogens'.

Data integration in Bayesian phylogenetics

Researchers studying the evolution of viral pathogens and other organisms increasingly encounter and use large and complex data sets from multiple different sources. Statistical research in Bayesian phylogenetics has risen to this challenge. Researchers use phylogenetics not only to reconstruct the evolutionary history of a group of organisms, but also to understand the processes that guide its evolution and spread through space and time. To this end, it is now the norm to integrate numerous sources of data. For example, epidemiologists studying the spread of a virus through a region incorporate data including genetic sequences (e.g. DNA), time, location (both continuous and discrete) and environmental covariates (e.g. social connectivity between regions) into a coherent statistical model. Evolutionary biologists routinely do the same with genetic sequences, location, time, fossil and modern phenotypes, and ecological covariates. These complex, hierarchical models readily accommodate both discrete and continuous data and have enormous combined discrete/continuous parameter spaces including, at a minimum, phylogenetic tree topologies and branch lengths. The increased size and complexity of these statistical models have spurred advances in computational methods to make them tractable. We discuss both the modeling and computational advances below, as well as unsolved problems and areas of active research.

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

Lassa fever is a severe viral hemorrhagic fever caused by a zoonotic virus that repeatedly spills over to humans from its rodent reservoirs. It is currently not known how climate and land use changes could affect the endemic area of this virus, currently limited to parts of West Africa. By exploring the environmental data associated with virus occurrence using ecological niche modelling, we show how temperature, precipitation and the presence of pastures determine ecological suitability for virus circulation. Based on projections of climate, land use, and population changes, we find 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 ecological conditions that are suitable for Lassa virus circulation may drastically increase by 2070. By analysing geotagged viral genomes using spatially-explicit phylogeography and simulating virus dispersal, 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.

Using multiple sampling strategies to estimate SARS-CoV-2 epidemiological parameters from genomic sequencing data

The choice of viral sequences used in genetic and epidemiological analysis is important as it can induce biases that detract from the value of these rich datasets. This raises questions about how a set of sequences should be chosen for analysis. We provide insights on these largely understudied problems using SARS-CoV-2 genomic sequences from Hong Kong, China, and the Amazonas State, Brazil. We consider multiple sampling schemes which were used to estimate Rt and rt as well as related R0 and date of origin parameters. We find that both Rt and rt are sensitive to changes in sampling whilst R0 and the date of origin are relatively robust. Moreover, we find that analysis using unsampled datasets result in the most biased Rt and rt estimates for both our Hong Kong and Amazonas case studies. We highlight that sampling strategy choices may be an influential yet neglected component of sequencing analysis pipelines.

Lineage BA.2 dominated the Omicron SARS-CoV-2 epidemic wave in the Philippines

The Omicron severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant led to a dramatic global epidemic wave following detection in South Africa in November 2021. The BA.1 Omicron lineage was dominant and responsible for most SARS-CoV-2 outbreaks in countries around the world during December 2021-January 2022, while other Omicron lineages, including BA.2, accounted for the minority of global isolates. Here, we describe the Omicron wave in the Philippines by analysing genomic data. Our results identify the presence of both BA.1 and BA.2 lineages in the Philippines in December 2021, before cases surged in January 2022. We infer that only the BA.2 lineage underwent sustained transmission in the country, with an estimated emergence around 18 November 2021 (95 per cent highest posterior density: 6-28 November), while despite multiple introductions, BA.1 transmission remained limited. These results suggest that the Philippines was one of the earliest areas affected by BA.2 and reiterate the importance of whole genome sequencing for monitoring outbreaks.

Evolutionary and genomic insights into the long-term colonization of in animals

The enteroinvasive bacterium Shigella flexneri is known as a highly host-adapted human pathogen. There had been no known other reservoirs reported until recently. Here 34 isolates obtained from animals (yaks, dairy cows and beef cattle) from 2016-2017 and 268 human S. flexneri isolates from China were sequenced to determine the relationships between animal and human isolates and infer the evolutionary history of animal-associated S. flexneri. The 18 animal isolates (15 yak and 3 beef cattle isolates) in PG1 were separated into 4 lineages, and the 16 animal isolates (1 yak, 5 beef cattle and 10 dairy cow isolates) in PG3 were clustered in 8 lineages. The most recent human isolates from China belonged to PG3 whereas Chinese isolates from the 1950s-1960s belonged to PG1. PG1 S. flexneri may has been transmitted to the yaks during PG1 circulation in the human population in China and has remained in the yak population since, while PG3 S. flexneri in animals were likely recent transmissions from the human population. Increased stability of the large virulence plasmid and acquisition of abundant antimicrobial resistance determinants may have enabled PG3 to expand globally and replaced PG1 in China. Our study confirms that animals may act as a reservoir for S. flexneri. Genomic analysis revealed the evolutionary history of multiple S. flexneri lineages in animals and humans in China. However, further studies are required to determine the public health threat of S. flexneri from animals.

Two Separate Clusters of SARS-CoV-2 Delta Variant Infections in A Group of 41 Students Travelling from India: An Illustration of the Need for Rigorous Testing and Quarantine

We report two clusters of SARS-CoV-2 B.1.617.2 (Delta variant) infections in a group of 41 Indian nursing students who travelled from New Delhi, India, to Belgium via Paris, France. All students tested negative before departure and had a second negative antigen test upon arrival in Paris. Upon arrival in Belgium, the students were quarantined in eight different houses. Four houses remained COVID-free during the 24 days of follow-up, while all 27 residents of the other four houses developed an infection during quarantine, including the four residents who were fully vaccinated and the two residents who were partially vaccinated. Genome sequencing revealed two distinct clusters affecting one and three houses, respectively. In this group of students, vaccination status did not seem to prevent infection nor decrease the viral load. No severe symptoms were reported. Extensive contact tracing and 3 months of nationwide genomic surveillance confirmed that these outbreaks were successfully contained and did not contribute to secondary community transmission in Belgium. These clusters highlight the importance of repeated testing and quarantine measures among travelers coming from countries experiencing a surge of infections, as all infections were detected 6 days or more after arrival.

Comparative Phylodynamics Reveals the Evolutionary History of SARS-CoV-2 Emerging Variants in the Arabian Peninsula

Emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to be responsible for an unprecedented worldwide public health and economic catastrophe. Accurate understanding and comparison of global and regional evolutionary epidemiology of novel SARS-CoV-2 variants are critical to guide current and future interventions. Here, we utilized a Bayesian phylodynamic pipeline to trace and compare the evolutionary dynamics, spatiotemporal origins, and spread of five variants (Alpha, Beta, Delta, Kappa, and Eta) across the Arabian Peninsula. We found variant-specific signatures of evolution and spread that are likely linked to air travel and disease control interventions in the region. Alpha, Beta, and Delta variants went through sequential periods of growth and decline, whereas we inferred inconclusive population growth patterns for the Kappa and Eta variants due to their sporadic introductions in the region. Non-pharmaceutical interventions imposed between mid-2020 and early 2021 likely played a role in reducing the epidemic progression of the Beta and the Alpha variants. In comparison, the combination of the non-pharmaceutical interventions and the rapid rollout of vaccination might have shaped Delta variant dynamics. We found that the Alpha and Beta variants were frequently introduced into the Arab peninsula between mid-2020 and early 2021 from Europe and Africa, respectively, whereas the Delta variant was frequently introduced between early 2021 and mid-2021 from East Asia. For these three variants, we also revealed significant and intense dispersal routes between the Arab region and Africa, Europe, Asia, and Oceania. In contrast, the restricted spread and stable effective population size of the Kappa and the Eta variants suggest that they no longer need to be targeted in genomic surveillance activities in the region. In contrast, the evolutionary characteristics of the Alpha, Beta, and Delta variants confirm the dominance of these variants in the recent outbreaks. Our study highlights the urgent need to establish regional molecular surveillance programs to ensure effective decision making related to the allocation of intervention activities targeted toward the most relevant variants.

Archival influenza virus genomes from Europe reveal genomic variability during the 1918 pandemic

The 1918 influenza pandemic was the deadliest respiratory pandemic of the 20th century and determined the genomic make-up of subsequent human influenza A viruses (IAV). Here, we analyze both the first 1918 IAV genomes from Europe and the first from samples prior to the autumn peak. 1918 IAV genomic diversity is consistent with a combination of local transmission and long-distance dispersal events. Comparison of genomes before and during the pandemic peak shows variation at two sites in the nucleoprotein gene associated with resistance to host antiviral response, pointing at a possible adaptation of 1918 IAV to humans. Finally, local molecular clock modeling suggests a pure pandemic descent of seasonal H1N1 IAV as an alternative to the hypothesis of origination through an intrasubtype reassortment.

For archival pathogens, like pH1N1 Influenza A virus the causative agent of 1918/19 pandemic, only few whole genome sequences exist. Here, Patrono et al. provide one complete and two partial genomes from Germany and find variation in two sites in the nucleoprotein gene in pandemic samples compared to pre-pandemic samples, that are associated with resistance to host antiviral response, pointing at a possible viral adaptation to humans.

Global spatial dynamics and vaccine-induced fitness changes of Bordetella pertussis

As with other pathogens, competitive interactions between Bordetella pertussis strains drive infection risk. Vaccines are thought to perturb strain diversity through shifts in immune pressures; however, this has rarely been measured because of inadequate data and analytical tools. We used 3344 sequences from 23 countries to show that, on average, there are 28.1 transmission chains circulating within a subnational region, with the number of chains strongly associated with host population size. It took 5 to 10 years for B. pertussis to be homogeneously distributed throughout Europe, with the same time frame required for the United States. Increased fitness of pertactin-deficient strains after implementation of acellular vaccines, but reduced fitness otherwise, can explain long-term genotype dynamics. These findings highlight the role of vaccine policy in shifting local diversity of a pathogen that is responsible for 160,000 deaths annually.

Antibody escape and global spread of SARS-CoV-2 lineage A.27

In spring 2021, an increasing number of infections was observed caused by the hitherto rarely described SARS-CoV-2 variant A.27 in south-west Germany. From December 2020 to June 2021 this lineage has been detected in 31 countries. Phylogeographic analyses of A.27 sequences obtained from national and international databases reveal a global spread of this lineage through multiple introductions from its inferred origin in Western Africa. Variant A.27 is characterized by a mutational pattern in the spike gene that includes the L18F, L452R and N501Y spike amino acid substitutions found in various variants of concern but lacks the globally dominant D614G. Neutralization assays demonstrate an escape of A.27 from convalescent and vaccine-elicited antibody-mediated immunity. Moreover, the therapeutic monoclonal antibody Bamlanivimab and partially the REGN-COV2 cocktail fail to block infection by A.27. Our data emphasize the need for continued global monitoring of novel lineages because of the independent evolution of new escape mutations.

Phylodynamic inference of bacterial outbreak parameters using nanopore sequencing

Nanopore sequencing and phylodynamic modeling have been used to reconstruct the transmission dynamics of viral epidemics, but their application to bacterial pathogens has remained challenging. Cost-effective bacterial genome sequencing and variant calling on nanopore platforms would greatly enhance surveillance and outbreak response in communities without access to sequencing infrastructure. Here, we adapt random forest models for single nucleotide polymorphism (SNP) polishing developed by Sanderson and colleagues (2020. High precision Neisseria gonorrhoeae variant and antimicrobial resistance calling from metagenomic nanopore sequencing. Genome Res. 30(9):1354–1363) to estimate divergence and effective reproduction numbers (R_e) of two methicillin-resistant Staphylococcus aureus (MRSA) outbreaks from remote communities in Far North Queensland and Papua New Guinea (PNG; n = 159). Successive barcoded panels of S. aureus isolates (2 × 12 per MinION) sequenced at low coverage (>5× to 10×) provided sufficient data to accurately infer genotypes with high recall when compared with Illumina references. Random forest models achieved high resolution on ST93 outbreak sequence types (>90% accuracy and precision) and enabled phylodynamic inference of epidemiological parameters using birth–death skyline models. Our method reproduced phylogenetic topology, origin of the outbreaks, and indications of epidemic growth (R_e > 1). Nextflow pipelines implement SNP polisher training, evaluation, and outbreak alignments, enabling reconstruction of within-lineage transmission dynamics for infection control of bacterial disease outbreaks on portable nanopore platforms. Our study shows that nanopore technology can be used for bacterial outbreak reconstruction at competitive costs, providing opportunities for infection control in hospitals and communities without access to sequencing infrastructure, such as in remote northern Australia and PNG.

Positive Selection Drives the Adaptive Evolution of Mitochondrial Antiviral Signaling (MAVS) Proteins-Mediating Innate Immunity in Mammals

The regulated production of filamentous protein complexes is essential in many biological processes and provides a new paradigm in signal transmission. The mitochondrial antiviral signaling protein (MAVS) is a critical signaling hub in innate immunity that is activated when a receptor induces a shift in the globular caspase activation and recruitment domain of MAVS into helical superstructures (filaments). It is of interest whether adaptive evolution affects the proteins involved in innate immunity. Here, we explore and confer the role of selection and diversification on mitochondrial antiviral signaling protein in mammalian species. We obtined the MAVS proteins of mammalian species and examined their differences in evolutionary patterns. We discovered evidence for these proteins being subjected to substantial positive selection. We demonstrate that immune system proteins, particularly those encoding recognition proteins, develop under positive selection using codon-based probability methods. Positively chosen regions within recognition proteins cluster in domains involved in microorganism recognition, implying that molecular interactions between hosts and pathogens may promote adaptive evolution in the mammalian immune systems. These significant variations in MAVS development in mammalian species highlights the involvement of MAVS in innate immunity. Our findings highlight the significance of accounting for how non-synonymous alterations affect structure and function when employing sequence-level studies to determine and quantify positive selection.

Evolution of influenza A virus in intensive and free-range swine farms in Spain

Swine harbor genetically diverse influenza A viruses (IAVs) with the capacity to host-switch to humans, causing global pandemics. Spain is the largest swine producer in Europe and has a mixed production system that includes 'white coat' pigs raised intensively in modern buildings and free-range Iberian pigs that interface differently with humans, wildlife, and other swine. Through active longitudinal IAV surveillance in nine Spanish provinces during 2015-9, we generated forty-seven complete or near-complete genome sequences from IAVs collected from swine in both systems. Genetically diverse IAVs were identified in intensively raised white pigs and free-range Iberian pigs, including new H3N1 reassortants. Both systems are dynamic environments for IAV evolution, but driven by different processes. IAVs in white pigs were genetically related to viruses found in swine raised intensively in other European countries, reflecting high rates of viral introduction following European trade routes. In contrast, IAVs in Iberian pigs have a genetic makeup shaped by frequent introductions of human IAVs, reflecting rearing practices with high rates of human contact. Transmission between white and Iberian pigs also occurred. In conclusion, Iberian swine with high rates of human contact harbor genetically diverse IAVs and potentially serve as intermediary hosts between white pigs and humans, presenting an understudied zoonotic risk that requires further investigation.

Phylogeography reveals association between swine trade and the spread of porcine epidemic diarrhea virus in China and across the world

The ongoing SARS (severe acute respiratory syndrome)-CoV (coronavirus)-2 pandemic has exposed major gaps in our knowledge on the origin, ecology, evolution, and spread of animal coronaviruses. Porcine epidemic diarrhea virus (PEDV) is a member of the genus Alphacoronavirus in the family Coronaviridae that may have originated from bats and leads to significant hazards and widespread epidemics in the swine population. The role of local and global trade of live swine and swine-related products in disseminating PEDV remains unclear, especially in developing countries with complex swine production systems. Here, we undertake an in-depth phylogeographic analysis of PEDV sequence data (including 247 newly sequenced samples) and employ an extension of this inference framework that enables formally testing the contribution of a range of predictor variables to the geographic spread of PEDV. Within China, the provinces of Guangdong and Henan were identified as primary hubs for the spread of PEDV, for which we estimate live swine trade to play a very important role. On a global scale, the United States and China maintain the highest number of PEDV lineages. We estimate that, after an initial introduction out of China, the United States acted as an important source of PEDV introductions into Japan, Korea, China, and Mexico. Live swine trade also explains the dispersal of PEDV on a global scale. Given the increasingly global trade of live swine, our findings have important implications for designing prevention and containment measures to combat a wide range of livestock coronaviruses.

SARS-CoV-2 infection in free-ranging white-tailed deer

Humans have infected a wide range of animals with SARS-CoV-2 viruses^1-5, but the establishment of a new natural animal reservoir has not been observed. Here, we document that free-ranging white-tailed deer (Odocoileus virginianus) are highly susceptible to infection with SARS-CoV-2 virus, are exposed to a range of viral diversity from humans, and are capable of sustaining transmission in nature. SARS-CoV-2 virus was detected by rRT-PCR in more than one-third (129/360, 35.8%) of nasal swabs obtained from Odocoileus virginianus in northeast Ohio (USA) during January-March 2021. Deer in 6 locations were infected with 3 SARS-CoV-2 lineages (B.1.2, B.1.582, B.1.596). The B.1.2 viruses, dominant in humans in Ohio at the time, infected deer in four locations. Probable deer-to-deer transmission of B.1.2, B.1.582, and B.1.596 viruses was observed, allowing the virus to acquire amino acid substitutions in the spike protein (including the receptor-binding domain) and ORF1 that are infrequently seen in humans. No spillback to humans was observed, but these findings demonstrate that SARS-CoV-2 viruses have the capacity to transmit in US wildlife, potentially opening new pathways for evolution. There is an urgent need to establish comprehensive "One Health" programs to monitor deer, the environment, and other wildlife hosts globally.