Recent advances in computational phylodynamics

Comparing Phylogeographies to Reveal Incompatible Geographical Histories within Genomes

Modern phylogeography aims at reconstructing the geographic movement of organisms based on their genomic sequences and spatial information. Phylogeographic approaches are often applied to pathogen sequences and therefore tend to neglect the possibility of recombination, which decouples the evolutionary and geographic histories of different parts of the genome. Genomic regions of recombining or reassorting pathogens often originate and evolve at different times and locations, which characterize their unique spatial histories. Measuring the extent of these differences requires new methods to compare geographic information on phylogenetic trees reconstructed from different parts of the genome. Here we develop for the first time a set of measures of phylogeographic incompatibility, aimed at detecting differences between geographical histories in terms of distances between phylogeographies. We study the effect of varying demography and recombination on phylogeographic incompatibilities using coalescent simulations. We further apply these measures to the evolutionary history of human and livestock pathogens, either reassorting or recombining, such as the Victoria and Yamagata lineages of influenza B and the O/Ind-2001 foot-and-mouth disease virus strain. Our results reveal diverse geographical paths of migration that characterize the origins and evolutionary histories of different viral genes and genomic segments. These incompatibility measures can be applied to any phylogeography, and more generally to any phylogeny where each tip has been assigned either a continuous or discrete "trait" independent of the sequence. We illustrate this flexibility with an analysis of the interplay between the phylogeography and phylolinguistics of Uralic-speaking human populations, hinting at patrilinear language transmission.

Building a pathway to One Health surveillance and response in Asian countries

To detect and respond to emerging diseases more effectively, an integrated surveillance strategy needs to be applied to both human and animal health. Current programs in Asian countries operate separately for the two sectors and are principally concerned with detection of events that represent a short-term disease threat. It is not realistic to either invest only in efforts to detect emerging diseases, or to rely solely on event-based surveillance. A comprehensive strategy is needed, concurrently investigating and managing endemic zoonoses, studying evolving diseases which change their character and importance due to influences such as demographic and climatic change, and enhancing understanding of factors which are likely to influence the emergence of new pathogens. This requires utilisation of additional investigation tools that have become available in recent years but are not yet being used to full effect. As yet there is no fully formed blueprint that can be applied in Asian countries. Hence a three-step pathway is proposed to move towards the goal of comprehensive One Health disease surveillance and response.

phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things)

Phylogenetic comparative methods comprise the general endeavor of using an estimated phylogenetic tree (or set of trees) to make secondary inferences: about trait evolution, diversification dynamics, biogeography, community ecology, and a wide range of other phenomena or processes. Over the past ten years or so, the phytools R package has grown to become an important research tool for phylogenetic comparative analysis. phytools is a diverse contributed R library now consisting of hundreds of different functions covering a variety of methods and purposes in phylogenetic biology. As of the time of writing, phytools included functionality for fitting models of trait evolution, for reconstructing ancestral states, for studying diversification on trees, and for visualizing phylogenies, comparative data, and fitted models, as well numerous other tasks related to phylogenetic biology. Here, I describe some significant features of and recent updates to phytools, while also illustrating several popular workflows of the phytools computational software.

Spatial and temporal dynamics of West Nile virus between Africa and Europe

It is unclear whether West Nile virus (WNV) circulates between Africa and Europe, despite numerous studies supporting an African origin and high transmission in Europe. We integrated genomic data with geographic observations and phylogenetic and phylogeographic inferences to uncover the spatial and temporal viral dynamics of WNV between these two continents. We focused our analysis towards WNV lineages 1 (L1) and 2 (L2), the most spatially widespread and pathogenic WNV lineages. Our study shows a Northern-Western African origin of L1, with back-and-forth exchanges between West Africa and Southern-Western Europe; and a Southern African origin of L2, with one main introduction from South Africa to Europe, and no back introductions observed. We also noticed a potential overlap between L1 and L2 Eastern and Western phylogeography and two Afro-Palearctic bird migratory flyways. Future studies linking avian and mosquito species susceptibility, migratory connectivity patterns, and phylogeographic inference are suggested to elucidate the dynamics of emerging viruses.

Phylodynamic approaches to studying avian influenza virus

Avian influenza viruses can cause severe disease in domestic and wild birds and are a pandemic threat. Phylodynamics is the study of how epidemiological, evolutionary, and immunological processes can interact to shape viral phylogenies. This review summarizes how phylodynamic methods have and could contribute to the study of avian influenza viruses. Specifically, we assess how phylodynamics can be used to examine viral spread within and between wild or domestic bird populations at various geographical scales, identify factors associated with virus dispersal, and determine the order and timing of virus lineage movement between geographic regions or poultry production systems. We discuss factors that can complicate the interpretation of phylodynamic results and identify how future methodological developments could contribute to improved control of the virus.

Population genomics of diarrheagenic Escherichia coli uncovers high connectivity between urban and rural communities in Ecuador

Human movement may be an important driver of transmission dynamics for enteric pathogens but has largely been underappreciated except for international 'travelers' diarrhea or cholera. Phylodynamic methods, which combine genomic and epidemiological data, are used to examine rates and dynamics of disease matching underlying evolutionary history and biogeographic distributions, but these methods often are not applied to enteric bacterial pathogens. We used phylodynamics to explore the phylogeographic and evolutionary patterns of diarrheagenic E. coli in northern Ecuador to investigate the role of human travel in the geographic distribution of strains across the country. Using whole genome sequences of diarrheagenic E. coli isolates, we built a core genome phylogeny, reconstructed discrete ancestral states across urban and rural sites, and estimated migration rates between E. coli populations. We found minimal structuring based on site locations, urban vs. rural locality, pathotype, or clinical status. Ancestral states of phylogenomic nodes and tips were inferred to have 51% urban ancestry and 49% rural ancestry. Lack of structuring by location or pathotype E. coli isolates imply highly connected communities and extensive sharing of genomic characteristics across isolates. Using an approximate structured coalescent model, we estimated rates of migration among circulating isolates were 6.7 times larger for urban towards rural populations compared to rural towards urban populations. This suggests increased inferred migration rates of diarrheagenic E. coli from urban populations towards rural populations. Our results indicate that investments in water and sanitation prevention in urban areas could limit the spread of enteric bacterial pathogens among rural populations.

Genome-wide phylodynamic approach reveals the epidemic dynamics of the main Mycoplasma bovis subtype circulating in France

Mycoplasma bovis is a major aetiological agent of bovine respiratory disease worldwide. Genome-based analyses are increasingly being used to monitor the genetic diversity and global distribution of M. bovis, complementing existing subtyping schemes based on locus sequencing. However, these analyses have so far provided limited information on the spatiotemporal and population dynamics of circulating subtypes. Here we applied a genome-wide phylodynamic approach to explore the epidemic dynamics of 88 French M. bovis strains collected between 2000 and 2019 in France and belonging to the currently dominant polC subtype 2 (st2). A strong molecular clock signal detected in the genomic data enabled robust phylodynamic inferences, which estimated that the M. bovis st2 population in France is composed of two lineages that successively emerged from independent introductions of international strains. The first lineage appeared around 2000 and supplanted the previously established antimicrobial-susceptible polC subtype 1. The second lineage, which is likely more transmissible, progressively replaced the first M. bovis st2 lineage population from 2005 onward and became predominant after 2010. Analyses also showed a brief decline in this second M. bovis st2 lineage population in around 2011, possibly due to the challenge from the concurrent emergence of M. bovis polC subtype 3 in France. Finally, we identified non-synonymous mutations in genes associated with lineages, which raises prospects for identifying new surveillance molecular markers. A genome-wide phylodynamic approach provides valuable resources for monitoring the evolution and epidemic dynamics of circulating M. bovis subtypes, and may prove critical for developing more effective surveillance systems and disease control strategies.

Evolutionary Origin, Genetic Recombination, and Phylogeography of Porcine Kobuvirus

The newly identified porcine Kobuvirus (PKV) has raised concerns owing to its association with diarrheal symptom in pigs worldwide. The process involving the emergence and global spread of PKV remains largely unknown. Here, the origin, genetic diversity, and geographic distribution of PKV were determined based on the available PKV sequence information. PKV might be derived from the rabbit Kobuvirus and sheep were an important intermediate host. The most recent ancestor of PKV could be traced back to 1975. Two major clades are identified, PKVa and PKVb, and recombination events increase PKV genetic diversity. Cross-species transmission of PKV might be linked to interspecies conserved amino acids at 13-17 and 25-40 residue motifs of Kobuvirus VP1 proteins. Phylogeographic analysis showed that Spain was the most likely location of PKV origin, which then spread to pig-rearing countries in Asia, Africa, and Europe. Within China, the Hubei province was identified as a primary hub of PKV, transmitting to the east, southwest, and northeast regions of the country. Taken together, our findings have important implications for understanding the evolutionary origin, genetic recombination, and geographic distribution of PKV thereby facilitating the design of preventive and containment measures to combat PKV infection.

SPREAD 4: online visualisation of pathogen phylogeographic reconstructions

Phylogeographic analyses aim to extract information about pathogen spread from genomic data, and visualising spatio-temporal reconstructions is a key aspect of this process. Here we present SPREAD 4, a feature-rich web-based application that visualises estimates of pathogen dispersal resulting from Bayesian phylogeographic inference using BEAST on a geographic map, offering zoom-and-filter functionality and smooth animation over time. SPREAD 4 takes as input phylogenies with both discrete and continuous location annotation and offers customised visualisation as well as generation of publication-ready figures. SPREAD 4 now features account-based storage and easy sharing of visualisations by means of unique web addresses. SPREAD 4 is intuitive to use and is available online at https://spreadviz.org, with an accompanying web page containing answers to frequently asked questions at https://beast.community/spread4.

Accommodating sampling location uncertainty in continuous phylogeography

Phylogeographic inference of the dispersal history of viral lineages offers key opportunities to tackle epidemiological questions about the spread of fast-evolving pathogens across human, animal and plant populations. In continuous space, i.e. when locations are specified by longitude and latitude, these reconstructions are however often limited by the availability or accessibility of precise sampling locations required for such spatially explicit analyses. We here review the different approaches that can be considered when genomic sequences are associated with a geographic area of sampling instead of precise coordinates. In particular, we describe and compare the approaches to define homogeneous and heterogeneous prior ranges of sampling coordinates.

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.

SNPPar: identifying convergent evolution and other homoplasies from microbial whole-genome alignments

Homoplasic SNPs are considered important signatures of strong (positive) selective pressure, and hence of adaptive evolution for clinically relevant traits such as antibiotic resistance and virulence. Here we present a new tool, SNPPar, for efficient detection and analysis of homoplasic SNPs from large whole genome sequencing datasets (>1000 isolates and/or >100 000 SNPs). SNPPar takes as input an SNP alignment, tree and annotated reference genome, and uses a combination of simple monophyly tests and ancestral state reconstruction (ASR, via TreeTime) to assign mutation events to branches and identify homoplasies. Mutations are annotated at the level of codon and gene, to facilitate analysis of convergent evolution. Testing on simulated data (120 Mycobacterium tuberculosis alignments representing local and global samples) showed SNPPar can detect homoplasic SNPs with very high specificity (zero false-positives in all tests) and high sensitivity (zero false-negatives in 89 % of tests). SNPPar analysis of three empirically sampled datasets (Elizabethkingia anophelis, Burkholderia dolosa and M. tuberculosis) produced results that were in concordance with previous studies, in terms of both individual homoplasies and evidence of convergence at the codon and gene levels. SNPPar analysis of a simulated alignment of ~64 000 genome-wide SNPs from 2000 M. tuberculosis genomes took ~23 min and ~2.6 GB of RAM to generate complete annotated results on a laptop. This analysis required ASR be conducted for only 1.25 % of SNPs, and the ASR step took ~23 s and 0.4 GB of RAM. SNPPar automates the detection and annotation of homoplasic SNPs efficiently and accurately from large SNP alignments. As demonstrated by the examples included here, this information can be readily used to explore the role of homoplasy in parallel and/or convergent evolution at the level of nucleotide, codon and/or gene.

Evolutionary and Ecological Drivers Shape the Emergence and Extinction of Foot-and-Mouth Disease Virus Lineages

Livestock farming across the world is constantly threatened by the evolutionary turnover of foot-and-mouth disease virus (FMDV) strains in endemic systems, the underlying dynamics of which remain to be elucidated. Here, we map the eco-evolutionary landscape of cocirculating FMDV lineages within an important endemic virus pool encompassing Western, Central, and parts of Southern Asia, reconstructing the evolutionary history and spatial dynamics over the last 20 years that shape the current epidemiological situation. We demonstrate that new FMDV variants periodically emerge from Southern Asia, precipitating waves of virus incursions that systematically travel in a westerly direction. We evidence how metapopulation dynamics drive the emergence and extinction of spatially structured virus populations, and how transmission in different host species regulates the evolutionary space of virus serotypes. Our work provides the first integrative framework that defines coevolutionary signatures of FMDV in regional contexts to help understand the complex interplay between virus phenotypes, host characteristics, and key epidemiological determinants of transmission that drive FMDV evolution in endemic settings.

Viral Sequences Recovered From Puma Tooth DNA Reconstruct Statewide Viral Phylogenies

Monitoring pathogens in wildlife populations is imperative for effective management, and for identifying locations for pathogen spillover among wildlife, domestic species and humans. Wildlife pathogen surveillance is challenging, however, as sampling often requires the capture of a significant proportion of the population to understand host pathogen dynamics. To address this challenge, we assessed the ability to use hunter-collected teeth from puma across Colorado to recover genetic data of two feline retroviruses, feline foamy virus (FFV) and feline immunodeficiency virus (FIVpco) and show they can be utilized for this purpose. Comparative phylogenetic analyses of FIVpco and FFV from tooth and blood samples to previous analyses conducted with blood samples collected over a nine-year period from two distinct areas was undertaken highlighting the value of tooth derived samples. We found less FIVpco phylogeographic structuring than observed from sampling only two regions and that FFV data confirmed previous findings of endemic infection, minimal geographic structuring, and supported frequent cross-species transmission from domestic cats to pumas. Viral analysis conducted using intentionally collected blood samples required extensive financial, capture and sampling efforts. This analysis illustrates that viral genomic data can be cost effectively obtained using tooth samples incidentally-collected from hunter harvested pumas, taking advantage of samples collected for morphological age identification. This technique should be considered as an opportunistic method to provide broad geographic sampling to define viral dynamics more accurately in wildlife.

On the Use of Phylogeographic Inference to Infer the Dispersal History of Rabies Virus: A Review Study

Rabies is a neglected zoonotic disease which is caused by negative strand RNA-viruses belonging to the genus Lyssavirus. Within this genus, rabies viruses circulate in a diverse set of mammalian reservoir hosts, is present worldwide, and is almost always fatal in non-vaccinated humans. Approximately 59,000 people are still estimated to die from rabies each year, leading to a global initiative to work towards the goal of zero human deaths from dog-mediated rabies by 2030, requiring scientific efforts from different research fields. The past decade has seen a much increased use of phylogeographic and phylodynamic analyses to study the evolution and spread of rabies virus. We here review published studies in these research areas, making a distinction between the geographic resolution associated with the available sequence data. We pay special attention to environmental factors that these studies found to be relevant to the spread of rabies virus. Importantly, we highlight a knowledge gap in terms of applying these methods when all required data were available but not fully exploited. We conclude with an overview of recent methodological developments that have yet to be applied in phylogeographic and phylodynamic analyses of rabies virus.

Dispersal dynamics of SARS-CoV-2 lineages during the first epidemic wave in New York City

During the first phase of the COVID-19 epidemic, New York City rapidly became the epicenter of the pandemic in the United States. While molecular phylogenetic analyses have previously highlighted multiple introductions and a period of cryptic community transmission within New York City, little is known about the circulation of SARS-CoV-2 within and among its boroughs. We here perform phylogeographic investigations to gain insights into the circulation of viral lineages during the first months of the New York City outbreak. Our analyses describe the dispersal dynamics of viral lineages at the state and city levels, illustrating that peripheral samples likely correspond to distinct dispersal events originating from the main metropolitan city areas. In line with the high prevalence recorded in this area, our results highlight the relatively important role of the borough of Queens as a transmission hub associated with higher local circulation and dispersal of viral lineages toward the surrounding boroughs.

A Phylodynamic Workflow to Rapidly Gain Insights into the Dispersal History and Dynamics of SARS-CoV-2 Lineages

Since the start of the COVID-19 pandemic, an unprecedented number of genomic sequences of SARS-CoV-2 have been generated and shared with the scientific community. The unparalleled volume of available genetic data presents a unique opportunity to gain real-time insights into the virus transmission during the pandemic, but also a daunting computational hurdle if analyzed with gold-standard phylogeographic approaches. To tackle this practical limitation, we here describe and apply a rapid analytical pipeline to analyze the spatiotemporal dispersal history and dynamics of SARS-CoV-2 lineages. As a proof of concept, we focus on the Belgian epidemic, which has had one of the highest spatial densities of available SARS-CoV-2 genomes. Our pipeline has the potential to be quickly applied to other countries or regions, with key benefits in complementing epidemiological analyses in assessing the impact of intervention measures or their progressive easement.

Testing methods of linguistic homeland detection using synthetic data

Two families of quantitative methods have been used to infer geographical homelands of language families: Bayesian phylogeography and the 'diversity method'. Bayesian methods model how populations may have moved using a phylogenetic tree as a backbone, while the diversity method assumes that the geographical area where linguistic diversity is highest likely corresponds to the homeland. No systematic tests of the performances of the different methods in a linguistic context have so far been published. Here, we carry out performance testing by simulating language families, including branching structures and word lists, along with speaker populations moving in space. We test six different methods: two versions of BayesTraits; the relaxed random walk model of BEAST 2; our own RevBayes implementations of a fixed rate and a variable rates random walk model; and the diversity method. As a result of the tests, we propose a hierarchy of performance of the different methods. Factors such as geographical idiosyncrasies, incomplete sampling, tree imbalance and small family sizes all have a negative impact on performance, but mostly across the board, the performance hierarchy generally being impervious to such factors. This article is part of the theme issue 'Reconstructing prehistoric languages'.

Development of Phylodynamic Methods for Bacterial Pathogens

Phylodynamic methods have been essential to understand the interplay between the evolution and epidemiology of infectious diseases. To date, the field has centered on viruses. Bacterial pathogens are seldom analyzed under such phylodynamic frameworks, due to their complex genome evolution and, until recently, a paucity of whole-genome sequence data sets with rich associated metadata. We posit that the increasing availability of bacterial genomes and epidemiological data means that the field is now ripe to lay the foundations for applying phylodynamics to bacterial pathogens. The development of new methods that integrate more complex genomic and ecological data will help to inform public heath surveillance and control strategies for bacterial pathogens that represent serious threats to human health.

Universal probabilistic programming offers a powerful approach to statistical phylogenetics

Statistical phylogenetic analysis currently relies on complex, dedicated software packages, making it difficult for evolutionary biologists to explore new models and inference strategies. Recent years have seen more generic solutions based on probabilistic graphical models, but this formalism can only partly express phylogenetic problems. Here, we show that universal probabilistic programming languages (PPLs) solve the expressivity problem, while still supporting automated generation of efficient inference algorithms. To prove the latter point, we develop automated generation of sequential Monte Carlo (SMC) algorithms for PPL descriptions of arbitrary biological diversification (birth-death) models. SMC is a new inference strategy for these problems, supporting both parameter inference and efficient estimation of Bayes factors that are used in model testing. We take advantage of this in automatically generating SMC algorithms for several recent diversification models that have been difficult or impossible to tackle previously. Finally, applying these algorithms to 40 bird phylogenies, we show that models with slowing diversification, constant turnover and many small shifts generally explain the data best. Our work opens up several related problem domains to PPL approaches, and shows that few hurdles remain before these techniques can be effectively applied to the full range of phylogenetic models.

Global emergence and evolutionary dynamics of bluetongue virus

Bluetongue virus (BTV) epidemics are responsible for worldwide economic losses of up to US$ 3 billion. Understanding the global evolutionary epidemiology of BTV is critical in designing intervention programs. Here we employed phylodynamic models to quantify the evolutionary characteristics, spatiotemporal origins, and multi-host transmission dynamics of BTV across the globe. We inferred that goats are the ancestral hosts for BTV but are less likely to be important for cross-species transmission, sheep and cattle continue to be important for the transmission and maintenance of infection between other species. Our models pointed to China and India, countries with the highest population of goats, as the likely ancestral country for BTV emergence and dispersal worldwide over 1000 years ago. However, the increased diversification and dispersal of BTV coincided with the initiation of transcontinental livestock trade after the 1850s. Our analysis uncovered important epidemiological aspects of BTV that may guide future molecular surveillance of BTV.

Comparative Circulation Dynamics of the Five Main HIV Types in China

The HIV epidemic in China accounts for 3% of the global HIV incidence. We compared the patterns and determinants of interprovincial spread of the five most prevalent circulating types. HIV pol sequences sampled across China were used to identify relevant transmission networks of the five most relevant HIV-1 types (B and circulating recombinant forms [CRFs] CRF01_AE, CRF07_BC, CRF08_BC, and CRF55_01B) in China. From these, the dispersal history across provinces was inferred. A generalized linear model (GLM) was used to test the association between migration rates among provinces and several measures of human mobility. A total of 10,707 sequences were collected between 2004 and 2017 across 26 provinces, among which 1,962 are newly reported here. A mean of 18 (minimum and maximum, 1 and 54) independent transmission networks involving up to 17 provinces were identified. Discrete phylogeographic analysis largely recapitulates the documented spread of the HIV types, which in turn, mirrors within-China population migration flows to a large extent. In line with the different spatiotemporal spread dynamics, the identified drivers thereof were also heterogeneous but are consistent with a central role of human mobility. The comparative analysis of the dispersal dynamics of the five main HIV types circulating in China suggests a key role of large population centers and developed transportation infrastructures as hubs of HIV dispersal. This advocates for coordinated public health efforts in addition to local targeted interventions.IMPORTANCE While traditional epidemiological studies are of great interest in describing the dynamics of epidemics, they struggle to fully capture the geospatial dynamics and factors driving the dispersal of pathogens like HIV as they have difficulties capturing linkages between infections. To overcome this, we used a discrete phylogeographic approach coupled to a generalized linear model extension to characterize the dynamics and drivers of the across-province spread of the five main HIV types circulating in China. Our results indicate that large urbanized areas with dense populations and developed transportation infrastructures are facilitators of HIV dispersal throughout China and highlight the need to consider harmonized country-wide public policies to control local HIV epidemics.

Epidemiological hypothesis testing using a phylogeographic and phylodynamic framework

Computational analyses of pathogen genomes are increasingly used to unravel the dispersal history and transmission dynamics of epidemics. Here, we show how to go beyond historical reconstructions and use spatially-explicit phylogeographic and phylodynamic approaches to formally test epidemiological hypotheses. We illustrate our approach by focusing on the West Nile virus (WNV) spread in North America that has substantially impacted public, veterinary, and wildlife health. We apply an analytical workflow to a comprehensive WNV genome collection to test the impact of environmental factors on the dispersal of viral lineages and on viral population genetic diversity through time. We find that WNV lineages tend to disperse faster in areas with higher temperatures and we identify temporal variation in temperature as a main predictor of viral genetic diversity through time. By contrasting inference with simulation, we find no evidence for viral lineages to preferentially circulate within the same migratory bird flyway, suggesting a substantial role for non-migratory birds or mosquito dispersal along the longitudinal gradient.

Evolutionary dynamics and transmission patterns of Newcastle disease virus in China through Bayesian phylogeographical analysis

The Chinese poultry industry has experienced outbreaks of Newcastle disease (ND) dating back to the 1920s. However, the epidemic has exhibited a downtrend in recent years. In this study, both observational and genetic data [fusion (F) and haemagglutinin-neuraminidase genes (HN)] were analyzed, and phylogeographic analysis based on prevalent genotypes of Newcastle disease virus (NDV) was conducted for better understanding of the evolution and spatiotemporal dynamics of ND in China. In line with the observed trend of epidemic outbreaks, the effective population size of F and HN genes of circulating NDV is no longer growing since 2000, which is supported by 95% highest posterior diversity (HPD) intervals. Phylogeographic analysis indicated that the two eastern coastal provinces, Shandong and Jiangsu were the most relevant hubs for NDV migration, and the geographical regions with active NDV diffusion seemed to be constrained to southern and eastern China. The live poultry trade may play an important role in viral spread. Interestingly, no migration links from wild birds to poultry received Bayes factor support (BF > 3), while the migration links from poultry to wild birds accounted for 64% in all effective migrations. This may indicate that the sporadic cases of ND in wild bird likely spillover events from poultry. These findings contribute to predictive models of NDV transmission, and potentially help in the prevention of future outbreaks.

Porcine reproductive and respiratory syndrome virus dissemination across pig production systems in the United States

Porcine reproductive and respiratory syndrome virus (PRRSV) remains widespread in the North American pig population. Despite improvements in virus characterization, it is unclear whether PRRSV infections are a product of viral circulation within production systems (local) or across production systems (external). Here, we examined the local and external dissemination dynamics of PRRSV and the processes facilitating its spread in three production systems. Overall, PRRSV genetic diversity has declined since 2018, while phylodynamic results support frequent external transmission. We found that PRRSV dissemination predominantly occurred mostly through transmission between farms of different production companies for several months, especially from November until May, a timeframe already established as PRRSV season. Although local PRRSV dissemination occurred mainly through regular pig flow (from sow to nursery and then to finisher farms), an important flux of PRRSV dissemination also occurred in the opposite direction, from finisher to sow and nursery farms, highlighting the importance of downstream farms as sources of the virus. Our results also showed that farms with pig densities of 500 to 1,000 pig/km² and farms located at a range within 0.5 km and 0.7 km from major roads were more likely to be infected by PRRSV, whereas farms at an elevation of 41 to 61 meters and surrounded by denser vegetation were less likely to be infected, indicating their role as dissemination barriers. In conclusion, our results demonstrate that external dissemination was intense, and reinforce the importance of farm proximity on PRRSV spread. Thus, consideration of farm location, geographic characteristics and animal densities across production systems may help to forecast PRRSV collateral dissemination.

Online Bayesian Phylodynamic Inference in BEAST with Application to Epidemic Reconstruction

Reconstructing pathogen dynamics from genetic data as they become available during an outbreak or epidemic represents an important statistical scenario in which observations arrive sequentially in time and one is interested in performing inference in an "online" fashion. Widely used Bayesian phylogenetic inference packages are not set up for this purpose, generally requiring one to recompute trees and evolutionary model parameters de novo when new data arrive. To accommodate increasing data flow in a Bayesian phylogenetic framework, we introduce a methodology to efficiently update the posterior distribution with newly available genetic data. Our procedure is implemented in the BEAST 1.10 software package, and relies on a distance-based measure to insert new taxa into the current estimate of the phylogeny and imputes plausible values for new model parameters to accommodate growing dimensionality. This augmentation creates informed starting values and re-uses optimally tuned transition kernels for posterior exploration of growing data sets, reducing the time necessary to converge to target posterior distributions. We apply our framework to data from the recent West African Ebola virus epidemic and demonstrate a considerable reduction in time required to obtain posterior estimates at different time points of the outbreak. Beyond epidemic monitoring, this framework easily finds other applications within the phylogenetics community, where changes in the data-in terms of alignment changes, sequence addition or removal-present common scenarios that can benefit from online inference.

Long-term virus evolution in nature

Viruses spread to give rise to epidemics and pandemics, and some key parameters that include virus and host population numbers determine virus persistence or extinction in nature. Viruses evolve at different rates depending on the polymerase copying fidelity during genome replication and a number of environmental influences. Calculated rates of evolution in nature vary depending on the time interval between virus isolations. In particular, intrahost evolution is generally more rapid that interhost evolution, and several possible mechanisms for this difference are considered. The mechanisms by which the error-prone viruses evolve are very unlikely to render the operation of a molecular clock (constant rate of incorporation of mutations in the evolving genomes), although a clock is assumed in many calculations. Several computational tools permit the alignment of viral sequences and the establishment of phylogenetic relationships among viruses. The evolution of the virus in the form of dynamic mutant clouds in each infected individual, together with multiple environmental parameters renders the emergence and reemergence of viral pathogens an unpredictable event, another facet of biological complexity.

Using phylogeographic approaches to analyse the dispersal history, velocity and direction of viral lineages - Application to rabies virus spread in Iran

Recent years have seen the extensive use of phylogeographic approaches to unveil the dispersal history of virus epidemics. Spatially explicit reconstructions of viral spread represent valuable sources of lineage movement data that can be exploited to investigate the impact of underlying environmental layers on the dispersal of pathogens. Here, we performed phylogeographic inference and applied different post hoc approaches to analyse a new and comprehensive data set of viral genomes to elucidate the dispersal history and dynamics of rabies virus (RABV) in Iran, which have remained largely unknown. We first analysed the association between environmental factors and variations in dispersal velocity among lineages. Second, we present, test and apply a new approach to study the link between environmental conditions and the dispersal direction of lineages. The statistical performance (power of detection, false-positive rate) of this new method was assessed using simulations. We performed phylogeographic analyses of RABV genomes, allowing us to describe the large diversity of RABV in Iran and to confirm the cocirculation of several clades in the country. Overall, we estimate a relatively high lineage dispersal velocity, similar to previous estimates for dog rabies virus spread in northern Africa. Finally, we highlight a tendency for RABV lineages to spread in accessible areas associated with high human population density. Our analytical workflow illustrates how phylogeographic approaches can be used to investigate the impact of environmental factors on several aspects of viral dispersal dynamics.

Advances in Visualization Tools for Phylogenomic and Phylodynamic Studies of Viral Diseases

Genomic and epidemiological monitoring have become an integral part of our response to emerging and ongoing epidemics of viral infectious diseases. Advances in high-throughput sequencing, including portable genomic sequencing at reduced costs and turnaround time, are paralleled by continuing developments in methodology to infer evolutionary histories (dynamics/patterns) and to identify factors driving viral spread in space and time. The traditionally static nature of visualizing phylogenetic trees that represent these evolutionary relationships/processes has also evolved, albeit perhaps at a slower rate. Advanced visualization tools with increased resolution assist in drawing conclusions from phylogenetic estimates and may even have potential to better inform public health and treatment decisions, but the design (and choice of what analyses are shown) is hindered by the complexity of information embedded within current phylogenetic models and the integration of available meta-data. In this review, we discuss visualization challenges for the interpretation and exploration of reconstructed histories of viral epidemics that arose from increasing volumes of sequence data and the wealth of additional data layers that can be integrated. We focus on solutions that address joint temporal and spatial visualization but also consider what the future may bring in terms of visualization and how this may become of value for the coming era of real-time digital pathogen surveillance, where actionable results and adequate intervention strategies need to be obtained within days.

Geographic dispersal and genetic diversity of tick-borne phleboviruses (Phenuiviridae, Phlebovirus) as revealed by the analysis of L segment sequences

The large diversity of new tick-borne phleboviruses, and the negative impacts of the virulent viruses on human/animal health have led to a growing interest in their analysis. In this report, new insights are brought out into the diversity of putative phleboviruses circulating in Portugal (both the continental territory and the islands of São Miguel, in the Azores, and Madeira), as well as in the Spanish western regions of Extremadura and Castilla and León. Phlebovirus sequences were frequently detected (L-segment) from both questing and feeding ticks, but especially in Rhipicephalus sanguineus sensu lato (s.l.) specimens. These sequences were detected in adult ticks, as well as nymphs and eggs, supporting the hypothesis of viral maintenance by vertical transmission. Though multiple genetic groups could be identified in phylogenetic trees (AnLuc, KarMa, RiPar virus 1, and Spanish group 1 and 2), all the sequences from Portugal and Spain shared common ancestry with other viral sequence obtained from samples collected over a large geographic coverage. Spatiotemporal analysis placed Middle-East as the geographic origin of the most recent common ancestor (MRCA) of all phleboviruses analysed in the present study. More recent viral transitions might include migrations from Spain to continental Portugal, and from there to the Portuguese Islands. Our findings suggest that the time of the MRCA of phleboviruses was dated around 225 years ago [95% HPD: 124-387 year before the last sampling date].

Evaluating an automated clustering approach in a perspective of ongoing surveillance of porcine reproductive and respiratory syndrome virus (PRRSV) field strains

Porcine reproductive and respiratory syndrome virus (PRRSV) has a major economic impact on the swine industry. The important genetic diversity needs to be considered for disease management. In this regard, information on the circulating endemic strains and their dispersal patterns through ongoing surveillance is beneficial. The objective of this project was to classify Quebec PRRSV ORF5 sequences in genetic clusters and evaluate stability of clustering results over a three-year period using an in-house automated clustering system. Phylogeny based on maximum likelihood (ML) was first inferred on 3661 sequences collected in 1998-2013 (Run 1). Then, sequences collected between January 2014 and September 2016 were sequentially added into 11 consecutive runs, each one covering a three-month period. For each run, detection of clusters, which were defined as groups of ≥15 sequences having a≥70% rapid bootstrap support (RBS) value, was automated in Python. Cluster stability was described for each cluster and run based on the number of sequences, RBS value, maximum pairwise distance and agreement in sequence assignment to a specific cluster. First and last run identified 29 and 33 clusters, respectively. In the last run, about 77% of the sequences were classified by the system. Most clusters were stable through time, with sequences attributed to one cluster in Run 1 staying in the same cluster for the 11 remaining runs. However, some initial groups were further subdivided into subgroups with time, which is important for monitoring since one specific wild-type cluster increased from 0% in 2007 to 45% of all sequences in 2016. This automated classification system will be integrated into ongoing surveillance activities, to facilitate communication and decision-making for stakeholders of the swine industry.

Increasing importance of European lineages in seeding the hepatitis C virus subtype 1a epidemic in Spain

BackgroundReducing the burden of the hepatitis C virus (HCV) requires large-scale deployment of intervention programmes, which can be informed by the dynamic pattern of HCV spread. In Spain, ongoing transmission of HCV is mostly fuelled by people who inject drugs (PWID) infected with subtype 1a (HCV1a).AimOur aim was to map how infections spread within and between populations, which could help formulate more effective intervention programmes to halt the HCV1a epidemic in Spain.MethodsEpidemiological links between HCV1a viruses from a convenience sample of 283 patients in Spain, mostly PWID, collected between 2014 and 2016, and 1,317, 1,291 and 1,009 samples collected abroad between 1989 and 2016 were reconstructed using sequences covering the NS3, NS5A and NS5B genes. To efficiently do so, fast maximum likelihood-based tree estimation was coupled to a flexible Bayesian discrete phylogeographic inference method.ResultsThe transmission network structure of the Spanish HCV1a epidemic was shaped by continuous seeding of HCV1a into Spain, almost exclusively from North America and European countries. The latter became increasingly relevant and have dominated in recent times. Export from Spain to other countries in Europe was also strongly supported, although Spain was a net sink for European HCV1a lineages. Spatial reconstructions showed that the epidemic in Spain is diffuse, without large, dominant within-country networks.ConclusionTo boost the effectiveness of local intervention efforts, concerted supra-national strategies to control HCV1a transmission are needed, with a strong focus on the most important drivers of ongoing transmission, i.e. PWID and other high-risk populations.