The effects of sampling strategy on the quality of reconstruction of viral population dynamics using Bayesian skyline family coalescent methods: A simulation study

Cassava brown streak virus evolves with a nucleotide-substitution rate that is typical for the family Potyviridae

The ipomoviruses (family Potyviridae) that cause cassava brown streak disease (cassava brown streak virus [CBSV] and Uganda cassava brown streak virus [UCBSV]) are damaging plant pathogens that affect the sustainability of cassava production in East and Central Africa. However, little is known about the rate at which the viruses evolve and when they emerged in Africa - which inform how easily these viruses can host shift and resist RNAi approaches for control. We present here the rates of evolution determined from the coat protein gene (CP) of CBSV (Temporal signal in a UCBSV dataset was not sufficient for comparable analysis). Our BEAST analysis estimated the CBSV CP evolves at a mean rate of 1.43 × 10-3 nucleotide substitutions per site per year, with the most recent common ancestor of sampled CBSV isolates existing in 1944 (95% HPD, between years 1922 - 1963). We compared the published measured and estimated rates of evolution of CPs from ten families of plant viruses and showed that CBSV is an average-evolving potyvirid, but that members of Potyviridae evolve more quickly than members of Virgaviridae and the single representatives of Betaflexiviridae, Bunyaviridae, Caulimoviridae and Closteroviridae.

Reconstruction of Avian Reovirus History and Dispersal Patterns: A Phylodynamic Study

Avian reovirus (ARV) infection can cause significant losses to the poultry industry. Disease control has traditionally been attempted mainly through vaccination. However, the increase in clinical outbreaks in the last decades demonstrated the poor effectiveness of current vaccination approaches. The present study reconstructs the evolution and molecular epidemiology of different ARV genotypes using a phylodynamic approach, benefiting from a collection of more than one thousand sigma C (σC) sequences sampled over time at a worldwide level. ARVs' origin was estimated to occur several centuries ago, largely predating the first clinical reports. The origins of all genotypes were inferred at least one century ago, and their emergence and rise reflect the intensification of the poultry industry. The introduction of vaccinations had only limited and transitory effects on viral circulation and further expansion was observed, particularly after the 1990s, likely because of the limited immunity and the suboptimal and patchy vaccination application. In parallel, strong selective pressures acted with different strengths and directionalities among genotypes, leading to the emergence of new variants. While preventing the spread of new variants with different phenotypic features would be pivotal, a phylogeographic analysis revealed an intricate network of viral migrations occurring even over long distances and reflecting well-established socio-economic relationships.

No evidence that a transmissible cancer has shifted from emergence to endemism in Tasmanian devils

Tasmanian devils are endangered by a transmissible cancer known as Tasmanian devil facial tumour 1 (DFT1). A 2020 study by Patton et al. (Science 370, eabb9772 (doi:10.1126/science.abb9772)) used genome data from DFT1 tumours to produce a dated phylogenetic tree for this transmissible cancer lineage, and thence, using phylodynamics models, to estimate its epidemiological parameters and predict its future trajectory. It concluded that the effective reproduction number for DFT1 had declined to a value of one, and that the disease had shifted from emergence to endemism. We show that the study is based on erroneous mutation calls and flawed methodology, and that its conclusions cannot be substantiated.

The Effect of Global Spread, Epidemiology, and Control Strategies on the Evolution of the GI-19 Lineage of Infectious Bronchitis Virus

The GI-19 lineage of infectious bronchitis virus (IBV) has emerged as one of the most impactful, particularly in the "Old World". Originating in China several decades ago, it has consistently spread and evolved, often forming independent clades in various areas and countries, each with distinct production systems and control strategies. This study leverages this scenario to explore how different environments may influence virus evolution. Through the analysis of the complete S1 sequence, four datasets were identified, comprising strains of monophyletic clades circulating in different continents or countries (e.g., Asia vs. Europe and China vs. Thailand), indicative of single introduction events and independent evolution. The population dynamics and evolutionary rate variation over time, as well as the presence and intensity of selective pressures, were estimated and compared across these datasets. Since the lineage origin (approximately in the mid-20th century), a more persistent and stable viral population was estimated in Asia and China, while in Europe and Thailand, a sharp increase following the introduction (i.e., 2005 and 2007, respectively) of GI-19 was observed, succeeded by a rapid decline. Although a greater number of sites on the S1 subunit were under diversifying selection in the Asian and Chinese datasets, more focused and stronger pressures were evident in both the European (positions 2, 52, 54, 222, and 379 and Thai (i.e., positions 10, 12, 32, 56, 62, 64, 65, 78, 95, 96, 119, 128, 140, 182, 292, 304, 320, and 323) strains, likely reflecting a more intense and uniform application of vaccines in these regions. This evidence, along with the analysis of control strategies implemented in different areas, suggests a strong link between effective, systematic vaccine implementation and infection control. However, while the overall evolutionary rate was estimated at approximately 10-3 to 10-4, a significant inverse correlation was found between viral population size and the rate of viral evolution over time. Therefore, despite the stronger selective pressure imposed by vaccination, effectively constraining the former through adequate control strategies can efficiently prevent viral evolution and the emergence of vaccine-escaping variants.

Approaches and challenges to inferring the geographical source of infectious disease outbreaks using genomic data

Genomic data hold increasing potential in the elucidation of transmission dynamics and geographical sources of infectious disease outbreaks. Phylogeographic methods that use epidemiological and genomic data obtained from surveillance enable us to infer the history of spatial transmission that is naturally embedded in the topology of phylogenetic trees as a record of the dispersal of infectious agents between geographical locations. In this Review, we provide an overview of phylogeographic approaches widely used for reconstructing the geographical sources of outbreaks of interest. These approaches can be classified into ancestral trait or state reconstruction and structured population models, with structured population models including popular structured coalescent and birth-death models. We also describe the major challenges associated with sequencing technologies, surveillance strategies, data sharing, and analysis frameworks that became apparent during the generation of large-scale genomic data in recent years, extending beyond inference approaches. Finally, we highlight the role of genomic data in geographical source inference and clarify how this enhances understanding and molecular investigations of outbreak sources.

Reconstructing the phylodynamic history and geographic spread of the CRF01_AE-predominant HIV-1 epidemic in the Philippines from PR/RT sequences sampled from 2008 to 2018

The Philippines has had a rapidly growing human immunodeficiency virus (HIV) epidemic with a shift in the prevalent subtype from B to CRF01_AE. However, the phylodynamic history of CRF01_AE in the Philippines has yet to be reconstructed. We conducted a descriptive retrospective study reconstructing the history of HIV-1 CRF01_AE transmissions in the Philippines through molecular epidemiology. Partial polymerase sequences (n = 1144) collected between 2008 and 2018 from three island groups were collated from the Research Institute for Tropical Medicine drug resistance genotyping database. Estimation of the time to the most recent common ancestor (tMRCA), effective reproductive number (Re), effective viral population size (Ne), relative migration rates, and geographic spread of CRF01_AE was performed with BEAST. Re and Ne were compared between CRF01_AE and B. Most CRF01_AE sequences formed a single clade with a tMRCA of June 1996 [95 per cent highest posterior density (HPD): December 1991, October 1999]. An increasing CRF01_AE Ne was observed from the tMRCA to 2013. The CRF01_AE Re reached peaks of 2.46 [95 per cent HPD: 1.76, 3.27] in 2007 and 2.52 [95 per cent HPD: 1.83, 3.34] in 2015. A decrease of CRF01_AE Re occurred in the intervening years of 2007 to 2011, reaching as low as 1.43 [95 per cent HPD: 1.06, 1.90] in 2011, followed by a rebound. The CRF01_AE epidemic most likely started in Luzon and then spread to the other island groups of the country. Both CRF01_AE and Subtype B exhibited similar patterns of Re fluctuation over time. These results characterize the subtype-specific phylodynamic history of the largest CRF01_AE cluster in the Philippines, which contextualizes and may inform past, present, and future public health measures toward controlling the HIV epidemic in the Philippines.

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.

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.

Bidirectional Movement of Emerging H5N8 Avian Influenza Viruses Between Europe and Asia via Migratory Birds Since Early 2020

Migratory birds play a critical role in the rapid spread of highly pathogenic avian influenza (HPAI) H5N8 virus clade 2.3.4.4 across Eurasia. Elucidating the timing and pattern of virus transmission is essential therefore for understanding the spatial dissemination of these viruses. In this study, we surveyed >27,000 wild birds in China, tracked the year-round migration patterns of 20 bird species across China since 2006, and generated new HPAI H5N8 virus genomic data. Using this new data set, we investigated the seasonal transmission dynamics of HPAI H5N8 viruses across Eurasia. We found that introductions of HPAI H5N8 viruses to different Eurasian regions were associated with the seasonal migration of wild birds. Moreover, we report a backflow of HPAI H5N8 virus lineages from Europe to Asia, suggesting that Europe acts as both a source and a sink in the global HPAI virus transmission network.

Emergence and Evolutionary Response of Vibrio cholerae to Novel Bacteriophage, Democratic Republic of the Congo1

Cholera causes substantial illness and death in Africa. We analyzed 24 toxigenic Vibrio cholerae O1 strains isolated in 2015-2017 from patients in the Great Lakes region of the Democratic Republic of the Congo. Strains originating in southern Asia appeared to be part of the T10 introduction event in eastern Africa. We identified 2 main strain lineages, most recently a lineage corresponding to sequence type 515, a V. cholerae cluster previously reported in the Lake Kivu region. In 41% of fecal samples from cholera patients, we also identified a novel ICP1 (Bangladesh cholera phage 1) bacteriophage, genetically distinct from ICP1 isolates previously detected in Asia. Bacteriophage resistance occurred in distinct clades along both internal and external branches of the cholera phylogeny. This bacteriophage appears to have served as a major driver for cholera evolution and spread, and its appearance highlights the complex evolutionary dynamic that occurs between predatory phage and bacterial host.

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.

Origins and Evolution of Seasonal Human Coronaviruses

Four seasonal human coronaviruses (sHCoVs) are endemic globally (229E, NL63, OC43, and HKU1), accounting for 5-30% of human respiratory infections. However, the epidemiology and evolution of these CoVs remain understudied due to their association with mild symptomatology. Using a multigene and complete genome analysis approach, we find the evolutionary histories of sHCoVs to be highly complex, owing to frequent recombination of CoVs including within and between sHCoVs, and uncertain, due to the under sampling of non-human viruses. The recombination rate was highest for 229E and OC43 whereas substitutions per recombination event were highest in NL63 and HKU1. Depending on the gene studied, OC43 may have ungulate, canine, or rabbit CoV ancestors. 229E may have origins in a bat, camel, or an unsampled intermediate host. HKU1 had the earliest common ancestor (1809-1899) but fell into two distinct clades (genotypes A and B), possibly representing two independent transmission events from murine-origin CoVs that appear to be a single introduction due to large gaps in the sampling of CoVs in animals. In fact, genotype B was genetically more diverse than all the other sHCoVs. Finally, we found shared amino acid substitutions in multiple proteins along the non-human to sHCoV host-jump branches. The complex evolution of CoVs and their frequent host switches could benefit from continued surveillance of CoVs across non-human hosts.

Quantifying rates of HIV-1 flow between risk groups and geographic locations in Kenya: A country-wide phylogenetic study

In Kenya, HIV-1 key populations including men having sex with men (MSM), people who inject drugs (PWID) and female sex workers (FSW) are thought to significantly contribute to HIV-1 transmission in the wider, mostly heterosexual (HET) HIV-1 transmission network. However, clear data on HIV-1 transmission dynamics within and between these groups are limited. We aimed to empirically quantify rates of HIV-1 flow between key populations and the HET population, as well as between different geographic regions to determine HIV-1 'hotspots' and their contribution to HIV-1 transmission in Kenya. We used maximum-likelihood phylogenetic and Bayesian inference to analyse 4058 HIV-1 pol sequences (representing 0.3 per cent of the epidemic in Kenya) sampled 1986-2019 from individuals of different risk groups and regions in Kenya. We found 89 per cent within-risk group transmission and 11 per cent mixing between risk groups, cyclic HIV-1 exchange between adjoining geographic provinces and strong evidence of HIV-1 dissemination from (i) West-to-East (i.e. higher-to-lower HIV-1 prevalence regions), and (ii) heterosexual-to-key populations. Low HIV-1 prevalence regions and key populations are sinks rather than major sources of HIV-1 transmission in Kenya. Targeting key populations in Kenya needs to occur concurrently with strengthening interventions in the general epidemic.

Accounting for spatial sampling patterns in Bayesian phylogeography

Statistical phylogeography has led to substantial progress in our understanding of the pace and means by which organisms colonize their habitats. Yet, inference from these models often relies on implicit assumptions pertaining to spatial sampling design, potentially leading to biased estimation of key biological parameters. While sampled locations sometimes convey signal about the processes that shape spatial biodiversity, they do not always do so. We present a statistical approach that permits accurate estimation of dispersal rates, even in cases where spatial sampling is driven by practical motivations unrelated to the outcome of the evolutionary process. The proposed framework paves the way to further developments in phylogeography with key applications, including the efficient monitoring of pandemics and invasive species during the course of their evolution.

Statistical phylogeography provides useful tools to characterize and quantify the spread of organisms during the course of evolution. Analyzing georeferenced genetic data often relies on the assumption that samples are preferentially collected in densely populated areas of the habitat. Deviation from this assumption negatively impacts the inference of the spatial and demographic dynamics. This issue is pervasive in phylogeography. It affects analyses that approximate the habitat as a set of discrete demes as well as those that treat it as a continuum. The present study introduces a Bayesian modeling approach that explicitly accommodates for spatial sampling strategies. An original inference technique, based on recent advances in statistical computing, is then described that is most suited to modeling data where sequences are preferentially collected at certain locations, independently of the outcome of the evolutionary process. The analysis of georeferenced genetic sequences from the West Nile virus in North America along with simulated data shows how assumptions about spatial sampling may impact our understanding of the forces shaping biodiversity across time and space.

H5Nx Viruses Emerged during the Suppression of H5N1 Virus Populations in Poultry

Highly pathogenic avian influenza (HPAI) H5 viruses have posed a substantial pandemic threat through repeated human infection since their emergence in China in 1996. Nationwide control measures, including vaccination of poultry, were implemented in 2005, leading to a sharp reduction in H5N1 virus outbreaks. In 2008, novel non-N1 subtype (H5Nx) viruses emerged, gradually replacing the dominant H5N1 subtype and causing global outbreaks. The cause of this major shift in the ecology of HPAI H5 viruses remains unknown. Here, we show that major H5N1 virus lineages underwent population bottlenecks in 2006, followed by a recovery in virus populations between 2007 and 2009. Our analyses indicate that control measures, not competition from H5Nx viruses, were responsible for the H5N1 decline, with an H5N1 lineage capable of infecting poultry and wild birds experiencing a less severe population bottleneck due to circulation in unaffected wild birds. We show that H5Nx viruses emerged during the successful suppression of H5N1 virus populations in poultry, providing an opportunity for antigenically distinct H5Nx viruses to propagate. Avian influenza vaccination programs would benefit from universal vaccines targeting a wider diversity of influenza viruses to prevent the emergence of novel subtypes.

IMPORTANCE A major shift in the ecology of highly pathogenic avian influenza (HPAI) H5 viruses occurred from 2008 to 2014, when viruses with non-N1 neuraminidase genes (termed H5Nx viruses) emerged and caused global H5 virus outbreaks. Here, we demonstrate that nationwide control measures, including vaccination in China, successfully suppressed H5N1 populations in poultry, providing an opportunity for antigenically distinct H5Nx viruses to emerge. In particular, we show that the widespread use of H5N1 vaccines likely conferred a fitness advantage to H5Nx viruses due to the antigenic mismatch of the neuraminidase genes. These results indicate that avian influenza vaccination programs would benefit from universal vaccines that target a wider diversity of influenza viruses to prevent potential emergence of novel subtypes.

Optimizing viral genome subsampling by genetic diversity and temporal distribution (TARDiS) for phylogenetics

SUMMARY

TARDiS is a novel phylogenetic tool for optimal genetic subsampling. It optimizes both genetic diversity and temporal distribution through a genetic algorithm.

AVAILABILITY AND IMPLEMENTATION

TARDiS, along with example datasets and a user manual, is available at https://github.com/smarini/tardis-phylogenetics.

Fundamental Identifiability Limits in Molecular Epidemiology

Viral phylogenies provide crucial information on the spread of infectious diseases, and many studies fit mathematical models to phylogenetic data to estimate epidemiological parameters such as the effective reproduction ratio (Re) over time. Such phylodynamic inferences often complement or even substitute for conventional surveillance data, particularly when sampling is poor or delayed. It remains generally unknown, however, how robust phylodynamic epidemiological inferences are, especially when there is uncertainty regarding pathogen prevalence and sampling intensity. Here, we use recently developed mathematical techniques to fully characterize the information that can possibly be extracted from serially collected viral phylogenetic data, in the context of the commonly used birth-death-sampling model. We show that for any candidate epidemiological scenario, there exists a myriad of alternative, markedly different, and yet plausible "congruent" scenarios that cannot be distinguished using phylogenetic data alone, no matter how large the data set. In the absence of strong constraints or rate priors across the entire study period, neither maximum-likelihood fitting nor Bayesian inference can reliably reconstruct the true epidemiological dynamics from phylogenetic data alone; rather, estimators can only converge to the "congruence class" of the true dynamics. We propose concrete and feasible strategies for making more robust epidemiological inferences from viral phylogenetic data.

Sample size calculation for phylogenetic case linkage

Sample size calculations are an essential component of the design and evaluation of scientific studies. However, there is a lack of clear guidance for determining the sample size needed for phylogenetic studies, which are becoming an essential part of studying pathogen transmission. We introduce a statistical framework for determining the number of true infector-infectee transmission pairs identified by a phylogenetic study, given the size and population coverage of that study. We then show how characteristics of the criteria used to determine linkage and aspects of the study design can influence our ability to correctly identify transmission links, in sometimes counterintuitive ways. We test the overall approach using outbreak simulations and provide guidance for calculating the sensitivity and specificity of the linkage criteria, the key inputs to our approach. The framework is freely available as the R package phylosamp, and is broadly applicable to designing and evaluating a wide array of pathogen phylogenetic studies.

Sequencing the genetic material of viral and bacterial pathogens has become an important part of tracking and combating human infectious diseases. Specifically, comparing the pathogen DNA or RNA sequences collected from infected individuals can allow researchers and public health experts to determine who infected whom, or detect when a pathogen entered a specific country or geographic area. However, it is often impossible to collect samples from every single infected person, and these missing sequences can pose problems for this type of analysis, especially if there is some bias behind which samples were selected for sequencing. We have developed a mathematical framework that allows users to determine the probability their conclusions about pathogen transmission are correct given the number and proportion of samples from a pathogen outbreak they have sequenced. This framework is freely available, easy to use, and broadly generalizable to any pathogen, and we hope that it can be used to inform the design and sampling strategies behind future sequencing-based studies.

Repeated introductions and intensive community transmission fueled a mumps virus outbreak in Washington State

In 2016/2017, Washington State experienced a mumps outbreak despite high childhood vaccination rates, with cases more frequently detected among school-aged children and members of the Marshallese community. We sequenced 166 mumps virus genomes collected in Washington and other US states, and traced mumps introductions and transmission within Washington. We uncover that mumps was introduced into Washington approximately 13 times, primarily from Arkansas, sparking multiple co-circulating transmission chains. Although age and vaccination status may have impacted transmission, our data set could not quantify their precise effects. Instead, the outbreak in Washington was overwhelmingly sustained by transmission within the Marshallese community. Our findings underscore the utility of genomic data to clarify epidemiologic factors driving transmission and pinpoint contact networks as critical for mumps transmission. These results imply that contact structures and historic disparities may leave populations at increased risk for respiratory virus disease even when a vaccine is effective and widely used.

Integration of genomic sequencing into the response to the Ebola virus outbreak in Nord Kivu, Democratic Republic of the Congo

On 1 August 2018, the Democratic Republic of the Congo (DRC) declared its tenth Ebola virus disease (EVD) outbreak. To aid the epidemiologic response, the Institut National de Recherche Biomédicale (INRB) implemented an end-to-end genomic surveillance system, including sequencing, bioinformatic analysis and dissemination of genomic epidemiologic results to frontline public health workers. We report 744 new genomes sampled between 27 July 2018 and 27 April 2020 generated by this surveillance effort. Together with previously available sequence data (n = 48 genomes), these data represent almost 24% of all laboratory-confirmed Ebola virus (EBOV) infections in DRC in the period analyzed. We inferred spatiotemporal transmission dynamics from the genomic data as new sequences were generated, and disseminated the results to support epidemiologic response efforts. Here we provide an overview of how this genomic surveillance system functioned, present a full phylodynamic analysis of 792 Ebola genomes from the Nord Kivu outbreak and discuss how the genomic surveillance data informed response efforts and public health decision making.

Emergence of porcine delta-coronavirus pathogenic infections among children in Haiti through independent zoonoses and convergent evolution

Coronaviruses have caused three major epidemics since 2003, including the ongoing SARS-CoV-2 pandemic. In each case, coronavirus emergence in our species has been associated with zoonotic transmissions from animal reservoirs^1,2, underscoring how prone such pathogens are to spill over and adapt to new species. Among the four recognized genera of the family Coronaviridae – Alphacoronavirus, Betacoronavirus, Deltacoronavirus, Gammacoronavirus, – human infections reported to date have been limited to alpha- and betacoronaviruses³. We identify, for the first time, porcine deltacoronavirus (PDCoV) strains in plasma samples of three Haitian children with acute undifferentiated febrile illness. Genomic and evolutionary analyses reveal that human infections were the result of at least two independent zoonoses of distinct viral lineages that acquired the same mutational signature in the nsp15 and the spike glycoprotein genes by convergent evolution. In particular, structural analysis predicts that one of the changes in the Spike S1 subunit, which contains the receptor-binding domain, may affect protein’s flexibility and binding to the host cell receptor. Our findings not only underscore the ability of deltacoronaviruses to adapt and potentially lead to human-to-human transmission, but also raise questions about the role of such transmissions in development of pre-existing immunity to other coronaviruses, such as SARS-CoV-2.

Independent infections of porcine deltacoronavirus among Haitian children

Coronaviruses have caused three major epidemics since 2003, including the ongoing SARS-CoV-2 pandemic. In each case, the emergence of coronavirus in our species has been associated with zoonotic transmissions from animal reservoirs^1,2, underscoring how prone such pathogens are to spill over and adapt to new species. Among the four recognized genera of the family Coronaviridae, human infections reported so far have been limited to alphacoronaviruses and betacoronaviruses^3-5. Here we identify porcine deltacoronavirus strains in plasma samples of three Haitian children with acute undifferentiated febrile illness. Genomic and evolutionary analyses reveal that human infections were the result of at least two independent zoonoses of distinct viral lineages that acquired the same mutational signature in the genes encoding Nsp15 and the spike glycoprotein. In particular, structural analysis predicts that one of the changes in the spike S1 subunit, which contains the receptor-binding domain, may affect the flexibility of the protein and its binding to the host cell receptor. Our findings highlight the potential for evolutionary change and adaptation leading to human infections by coronaviruses outside of the previously recognized human-associated coronavirus groups, particularly in settings where there may be close human-animal contact.

The Molecular Epidemiology and Transmission Dynamics of HIV Type 1 in a General Population Cohort in Uganda

The General Population Cohort (GPC) in south-western Uganda has a low HIV-1 incidence rate (<1%). However, new infections continue to emerge. In this research, 3796 HIV-1 pol sequences (GPC: n = 1418, non-GPC sites: n = 1223, Central Uganda: n = 1010 and Eastern Uganda: n = 145) generated between 2003–2015 were analysed using phylogenetic methods with demographic data to understand HIV-1 transmission in this cohort and inform the epidemic response. HIV-1 subtype A1 was the most prevalent strain in the GPC area (GPC and non-GPC sites) (39.8%), central (45.9%) and eastern (52.4%) Uganda. However, in the GPC alone, subtype D was the predominant subtype (39.1%). Of the 524 transmission clusters identified by Cluster Picker, all large clusters (≥5 individuals, n = 8) involved individuals from the GPC. In a multivariate analysis, clustering was strongly associated with being female (adjusted Odds Ratio, aOR = 1.28; 95% CI, 1.06–1.54), being >25 years (aOR = 1.52; 95% CI, 1.16–2.0) and being a resident in the GPC (aOR = 6.90; 95% CI, 5.22–9.21). Phylogeographic analysis showed significant viral dissemination (Bayes Factor test, BF > 3) from the GPC without significant viral introductions (BF < 3) into the GPC. The findings suggest localized HIV-1 transmission in the GPC. Intensifying geographically focused combination interventions in the GPC would contribute towards controlling HIV-1 infections.

Bovine Coronavirus: Variability, Evolution, and Dispersal Patterns of a No Longer Neglected Betacoronavirus

Bovine coronavirus (BoCV) is an important pathogen of cattle, causing severe enteric disease and playing a role in the bovine respiratory disease complex. Similar to other coronaviruses, a remarkable variability characterizes both its genome and biology. Despite their potential relevance, different aspects of the evolution of BoCV remain elusive. The present study reconstructs the history and evolution of BoCV using a phylodynamic approach based on complete genome and spike protein sequences. The results demonstrate high mutation and recombination rates affecting different parts of the viral genome. In the spike gene, this variability undergoes significant selective pressures—particularly episodic pressure—located mainly on the protein surface, suggesting an immune-induced selective pressure. The occurrence of compensatory mutations was also identified. On the contrary, no strong evidence in favor of host and/or tissue tropism affecting viral evolution has been proven. The well-known plasticity is thus ascribable to the innate broad viral tropism rather than mid- or long-term adaptation. The evaluation of the geographic spreading pattern clearly evidenced two clusters: a European cluster and an American–Asian cluster. While a relatively dense and quick migration network was identified in the former, the latter was dominated by the primary role of the United States (US) as a viral exportation source. Since the viral spreading pattern strongly mirrored the cattle trade, the need for more intense monitoring and preventive measures cannot be underestimated as well as the need to enforce the vaccination of young animals before international trade, to reduce not only the clinical impact but also the transferal and mixing of BoCV strains.

Estimating effective population size changes from preferentially sampled genetic sequences

Coalescent theory combined with statistical modeling allows us to estimate effective population size fluctuations from molecular sequences of individuals sampled from a population of interest. When sequences are sampled serially through time and the distribution of the sampling times depends on the effective population size, explicit statistical modeling of sampling times improves population size estimation. Previous work assumed that the genealogy relating sampled sequences is known and modeled sampling times as an inhomogeneous Poisson process with log-intensity equal to a linear function of the log-transformed effective population size. We improve this approach in two ways. First, we extend the method to allow for joint Bayesian estimation of the genealogy, effective population size trajectory, and other model parameters. Next, we improve the sampling time model by incorporating additional sources of information in the form of time-varying covariates. We validate our new modeling framework using a simulation study and apply our new methodology to analyses of population dynamics of seasonal influenza and to the recent Ebola virus outbreak in West Africa.

Estimating changes in the number of individuals in a given population is a challenging problem in some settings. For example, estimating population size trajectories of the number of people infected by a pathogen (e.g., Influenza virus) is a difficult problem, because many infections in a large population remain unobserved/hidden. One indirect way of assessing population size changes is to take a sample of individuals from the population of interest and analyze genetic sequences from these individuals (e.g., Influenza virus genomes). Intuitively, genetic data is informative about population size changes, because genetic diversity increases/decreases together with the population size. However, if we sample more individuals when the population size increases and less when it decreases, this strategy produces biased results. To avoid this bias, we propose a method that explicitly and flexibly models potential dependency of genetic sequence sampling on the population size. An added bonus of this new modeling framework is more precise estimation of population size changes. We demonstrate strengths of our new methodology on simulated data and on genetic sequences of Influenza and Ebola viruses.

Quantifying the transmission of antimicrobial resistance at the human and livestock interface with genomics

BACKGROUND

Livestock have been implicated as a reservoir for antimicrobial resistance (AMR) that can spread to humans. Close proximity and ecological interfaces involving livestock have been posited as risk factors for the transmission of AMR. In spite of this, there are sparse data and limited agreement on the transmission dynamics that occur.

OBJECTIVES

To identify how genome sequencing approaches can be used to quantify the dynamics of AMR transmission at the human-livestock interface, and where current knowledge can be improved to better understand the impact of transmission on the spread of AMR.

SOURCES

Key articles investigating various aspects of AMR transmission at the human-livestock interface are discussed, with a focus on Escherichia coli.

CONTENT

We recapitulate the current understanding of the transmission of AMR between humans and livestock based on current genomic and epidemiological approaches. We discuss how the use of well-designed, high-resolution genome sequencing studies can improve our understanding of the human-livestock interface.

IMPLICATIONS

A better understanding of the human-livestock interface will aid in the development of evidence-based and effective One Health interventions that can ultimately reduce the burden of AMR in humans.

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.

Jointly Inferring the Dynamics of Population Size and Sampling Intensity from Molecular Sequences

Estimating past population dynamics from molecular sequences that have been sampled longitudinally through time is an important problem in infectious disease epidemiology, molecular ecology, and macroevolution. Popular solutions, such as the skyline and skygrid methods, infer past effective population sizes from the coalescent event times of phylogenies reconstructed from sampled sequences but assume that sequence sampling times are uninformative about population size changes. Recent work has started to question this assumption by exploring how sampling time information can aid coalescent inference. Here, we develop, investigate, and implement a new skyline method, termed the epoch sampling skyline plot (ESP), to jointly estimate the dynamics of population size and sampling rate through time. The ESP is inspired by real-world data collection practices and comprises a flexible model in which the sequence sampling rate is proportional to the population size within an epoch but can change discontinuously between epochs. We show that the ESP is accurate under several realistic sampling protocols and we prove analytically that it can at least double the best precision achievable by standard approaches. We generalize the ESP to incorporate phylogenetic uncertainty in a new Bayesian package (BESP) in BEAST2. We re-examine two well-studied empirical data sets from virus epidemiology and molecular evolution and find that the BESP improves upon previous coalescent estimators and generates new, biologically useful insights into the sampling protocols underpinning these data sets. Sequence sampling times provide a rich source of information for coalescent inference that will become increasingly important as sequence collection intensifies and becomes more formalized.

Under-the-Radar Dengue Virus Infections in Natural Populations of Aedes aegypti Mosquitoes

The incidence of locally acquired dengue infections increased during the last decade in the United States, compelling a sustained research effort concerning the dengue mosquito vector, Aedes aegypti, and its microbiome, which has been shown to influence virus transmission success. We examined the "metavirome" of four populations of Aedes aegypti mosquitoes collected in 2016 to 2017 in Manatee County, FL. Unexpectedly, we discovered that dengue virus serotype 4 (DENV4) was circulating in these mosquito populations, representing the first documented case of such a phenomenon in the absence of a local DENV4 human case in this county over a 2-year period. We confirmed that all of the mosquito populations carried the same DENV4 strain, assembled its full genome, validated infection orthogonally by reverse transcriptase PCR, traced the virus origin, estimated the time period of its introduction to the Caribbean region, and explored the viral genetic signatures and mosquito-specific virome associations that potentially mediated DENV4 persistence in mosquitoes. We discuss the significance of prolonged maintenance of the DENV4 infections in A. aegypti that occurred in the absence of a DENV4 human index case in Manatee County with respect to the inability of current surveillance paradigms to detect mosquito vector infections prior to a potential local outbreak.IMPORTANCE Since 1999, dengue outbreaks in the continental United States involving local transmission have occurred only episodically and only in Florida and Texas. In Florida, these episodes appear to be coincident with increased introductions of dengue virus into the region through human travel and migration from countries where the disease is endemic. To date, the U.S. public health response to dengue outbreaks has been largely reactive, and implementation of comprehensive arbovirus surveillance in advance of predictable transmission seasons, which would enable proactive preventative efforts, remains unsupported. The significance of our finding is that it is the first documented report of DENV4 transmission to and maintenance within a local mosquito vector population in the continental United States in the absence of a human case during two consecutive years. Our data suggest that molecular surveillance of mosquito populations in high-risk, high-tourism areas of the United States may enable proactive, targeted vector control before potential arbovirus outbreaks.

Animal Disease Surveillance in the 21st Century: Applications and Robustness of Phylodynamic Methods in Recent U.S. Human-Like H3 Swine Influenza Outbreaks

Emerging and endemic animal viral diseases continue to impose substantial impacts on animal and human health. Most current and past molecular surveillance studies of animal diseases investigated spatio-temporal and evolutionary dynamics of the viruses in a disjointed analytical framework, ignoring many uncertainties and made joint conclusions from both analytical approaches. Phylodynamic methods offer a uniquely integrated platform capable of inferring complex epidemiological and evolutionary processes from the phylogeny of viruses in populations using a single Bayesian statistical framework. In this study, we reviewed and outlined basic concepts and aspects of phylodynamic methods and attempted to summarize essential components of the methodology in one analytical pipeline to facilitate the proper use of the methods by animal health researchers. Also, we challenged the robustness of the posterior evolutionary parameters, inferred by the commonly used phylodynamic models, using hemagglutinin (HA) and polymerase basic 2 (PB2) segments of the currently circulating human-like H3 swine influenza (SI) viruses isolated in the United States and multiple priors. Subsequently, we compared similarities and differences between the posterior parameters inferred from sequence data using multiple phylodynamic models. Our suggested phylodynamic approach attempts to reduce the impact of its inherent limitations to offer less biased and biologically plausible inferences about the pathogen evolutionary characteristics to properly guide intervention activities. We also pinpointed requirements and challenges for integrating phylodynamic methods in routine animal disease surveillance activities.

Toxigenic Vibrio cholerae evolution and establishment of reservoirs in aquatic ecosystems

The spread of cholera in the midst of an epidemic is largely driven by direct transmission from person to person, although it is well-recognized that Vibrio cholerae is also capable of growth and long-term survival in aquatic ecosystems. While prior studies have shown that aquatic reservoirs are important in the persistence of the disease on the Indian subcontinent, an epidemiological view postulating that locally evolving environmental V. cholerae contributes to outbreaks outside Asia remains debated. The single-source introduction of toxigenic V. cholerae O1 in Haiti, one of the largest outbreaks occurring this century, with 812,586 suspected cases and 9,606 deaths reported through July 2018, provided a unique opportunity to evaluate the role of aquatic reservoirs and assess bacterial transmission dynamics across environmental boundaries. To this end, we investigated the phylogeography of both clinical and aquatic toxigenic V. cholerae O1 isolates and show robust evidence of the establishment of aquatic reservoirs as well as ongoing evolution of V. cholerae isolates from aquatic sites. Novel environmental lineages emerged from sequential population bottlenecks, carrying mutations potentially involved in adaptation to the aquatic ecosystem. Based on such empirical data, we developed a mixed-transmission dynamic model of V. cholerae, where aquatic reservoirs actively contribute to genetic diversification and epidemic emergence, which underscores the complexity of transmission pathways in epidemics and endemic settings and the need for long-term investments in cholera control at both human and environmental levels.

Isolation of Mayaro Virus from a Venezuelan Patient with Febrile Illness, Arthralgias, and Rash: Further Evidence of Regional Strain Circulation and Possible Long-Term Endemicity

Fifty-two febrile patients living in Barquisimeto, Venezuela, were screened for arbovirus infection by virus culture during an outbreak of what was thought to be Zika virus infection. We report identification of Mayaro virus (MAYV) on culture of plasma from one patient, an 18-year-old woman with acute febrile illness, arthralgias, and psoriasiform rash. The strain was sequenced and was found to be most closely related to a 1999 strain from French Guiana, which, in turn, was related to two 2014 strains from Haiti. By contrast, previously reported outbreak-related MAYV strains from a sylvatic area approximately 80 miles from where the case patient lived were most closely related to Peruvian isolates. The two strain groups show evidence of having diverged genetically approximately 100 years ago.

High-Resolution Evolutionary Analysis of Within-Host Hepatitis C Virus Infection

BACKGROUND

Despite recent breakthroughs in treatment of hepatitis C virus (HCV) infection, we have limited understanding of how virus diversity generated within individuals impacts the evolution and spread of HCV variants at the population scale. Addressing this gap is important for identifying the main sources of disease transmission and evaluating the risk of drug-resistance mutations emerging and disseminating in a population.

METHODS

We have undertaken a high-resolution analysis of HCV within-host evolution from 4 individuals coinfected with human immunodeficiency virus 1 (HIV-1). We used long-read, deep-sequenced data of full-length HCV envelope glycoprotein, longitudinally sampled from acute to chronic HCV infection to investigate the underlying viral population and evolutionary dynamics.

RESULTS

We found statistical support for population structure maintaining the within-host HCV genetic diversity in 3 out of 4 individuals. We also report the first population genetic estimate of the within-host recombination rate for HCV (0.28 × 10-7 recombination/site/year), which is considerably lower than that estimated for HIV-1 and the overall nucleotide substitution rate estimated during HCV infection.

CONCLUSIONS

Our findings indicate that population structure and strong genetic linkage shapes within-host HCV evolutionary dynamics. These results will guide the future investigation of potential HCV drug resistance adaptation during infection, and at the population scale.

Accounting for population structure reveals ambiguity in the Zaire Ebolavirus reservoir dynamics

Ebolaviruses pose a substantial threat to wildlife populations and to public health in Africa. Evolutionary analyses of virus genome sequences can contribute significantly to elucidate the origin of new outbreaks, which can help guide surveillance efforts. The reconstructed between-outbreak evolutionary history of Zaire ebolavirus so far has been highly consistent. By removing the confounding impact of population growth bursts during local outbreaks on the free mixing assumption that underlies coalescent-based demographic reconstructions, we find-contrary to what previous results indicated-that the circulation dynamics of Ebola virus in its animal reservoir are highly uncertain. Our findings also accentuate the need for a more fine-grained picture of the Ebola virus diversity in its reservoir to reliably infer the reservoir origin of outbreak lineages. In addition, the recent appearance of slower-evolving variants is in line with latency as a survival mechanism and with bats as the natural reservoir host.

Ecophylogeography of the disjunct South American xerophytic tree species Prosopis chilensis (Fabaceae)

The intraspecific evolutionary history of South American xerophytic plant species has been poorly explored. The tree species Prosopis chilensis has a disjunct distribution in four South American regions: southern Peru, southern Bolivia, central–western Argentina and central Chile. Here, we combined phylogeographical (based on chloroplast and nuclear markers), morphological and climatic data to evaluate the relative contribution of historical demo-stochastic and adaptive processes in differentiating the disjunct areas of distribution. The results obtained with the two molecular markers revealed two closely related phylogroups (Northern and Southern, predominating in Bolivian Chaco and in Argentine Chaco/Monte, respectively), which would have diverged at ~5 Mya, probably associated with transgression of the Paranaense Sea. Bolivia and Argentina have a larger number of exclusive haplotypes/alleles and higher molecular diversity than Chile, suggesting a long-lasting in situ persistence in the former and a relatively recent colonization in the latter, from the Bolivian and Argentinian lineages. The two main lineages differ in morphology and climatic niche, revealing two significant, independent evolutionary units within P. chilensis promoted by local adaptation and geographical isolation.

Agricultural and geographic factors shaped the North American 2015 highly pathogenic avian influenza H5N2 outbreak

The 2014-2015 highly pathogenic avian influenza (HPAI) H5NX outbreak represents the largest and most expensive HPAI outbreak in the United States to date. Despite extensive traditional and molecular epidemiological studies, factors associated with the spread of HPAI among midwestern poultry premises remain unclear. To better understand the dynamics of this outbreak, 182 full genome HPAI H5N2 sequences isolated from commercial layer chicken and turkey production premises were analyzed using evolutionary models able to accommodate epidemiological and geographic information. Epidemiological compartmental models embedded in a phylogenetic framework provided evidence that poultry type acted as a barrier to the transmission of virus among midwestern poultry farms. Furthermore, after initial introduction, the propagation of HPAI cases was self-sustainable within the commercial poultry industries. Discrete trait diffusion models indicated that within state viral transitions occurred more frequently than inter-state transitions. Distance and sample size were very strongly supported as associated with viral transition between county groups (Bayes Factor > 30.0). Together these findings indicate that the different types of midwestern poultry industries were not a single homogenous population, but rather, the outbreak was shaped by poultry industries and geographic factors.

Phyloanatomic characterization of the distinct T cell and monocyte contributions to the peripheral blood HIV population within the host

Human immunodeficiency virus (HIV) is a rapidly evolving virus, allowing its genetic sequence to act as a fingerprint for epidemiological processes among, as well as within, individual infected hosts. Though primarily infecting the CD4+ T-cell population, HIV can also be found in monocytes, an immune cell population that differs in several aspects from the canonical T-cell viral target. Using single genome viral sequencing and statistical phylogenetic inference, we investigated the viral RNA diversity and relative contribution of each of these immune cell types to the viral population within the peripheral blood. Results provide evidence of an increased prevalence of circulating monocytes harboring virus in individuals with high viral load in the absence of suppressive antiretroviral therapy. Bayesian phyloanatomic analysis of three of these individuals demonstrated a measurable role for these cells, but not the circulating T-cell population, as a source of cell-free virus in the plasma, supporting the hypothesis that these cells can act as an additional conduit of virus spread.

A Shift in Porcine Circovirus 3 (PCV-3) History Paradigm: Phylodynamic Analyses Reveal an Ancient Origin and Prolonged Undetected Circulation in the Worldwide Swine Population

The identification of a new circovirus (Porcine circovirus 3, PCV-3) has raised a remarkable concern because of some analogies with Porcine circovirus 2 (PCV-2). Preliminary results suggest an extremely recent PCV-3 emergence and high mutation rate. Retrospective studies prove its circulation at least since the early 1990s, revealing that PCV-3 could have been infecting pigs for an even longer period. Therefore, a new evaluation, based on an updated collection of PCV-3 sequences spanning more than 20 years, is performed using a phylodynamic approach. The obtained results overrule the previous PCV-3 history concept, indicating an ancient origin. These evidences are associated with an evolutionary rate far lower (10-5-10-6 substitution/site/year) than the PCV-2 one. Accordingly, the action of selective pressures on PCV-3 open reading frames (ORFs) seems to be remarkably lower compared to those acting on PCV-2, suggesting either a reduced PCV-3 plasticity or a less efficient host-induced natural selection. A complex and not-directional viral flow network is evidenced through phylogeographic analysis, indicating a long lasting circulation rather than a recent emergence followed by spreading. Being recent emergence has been ruled out, efforts should be devoted to understand whether its recent discovery is simply due to improved detection capabilities or to the breaking of a previous equilibrium.

Assessing biases in phylodynamic inferences in the presence of super-spreaders

Phylodynamic analyses using pathogen genetic data have become popular for making epidemiological inferences. However, many methods assume that the underlying host population follows homogenous mixing patterns. Nevertheless, in real disease outbreaks, a small number of individuals infect a disproportionately large number of others (super-spreaders). Our objective was to quantify the degree of bias in estimating the epidemic starting date in the presence of super-spreaders using different sample selection strategies. We simulated 100 epidemics of a hypothetical pathogen (fast evolving foot and mouth disease virus-like) over a real livestock movement network allowing the genetic mutations in pathogen sequence. Genetic sequences were sampled serially over the epidemic, which were then used to estimate the epidemic starting date using Extended Bayesian Coalescent Skyline plot (EBSP) and Birth–death skyline plot (BDSKY) models. Our results showed that the degree of bias varies over different epidemic situations, with substantial overestimations on the epidemic duration occurring in some occasions. While the accuracy and precision of BDSKY were deteriorated when a super-spreader generated a larger proportion of secondary cases, those of EBSP were deteriorated when epidemics were shorter. The accuracies of the inference were similar irrespective of whether the analysis used all sampled sequences or only a subset of them, although the former required substantially longer computational times. When phylodynamic analyses need to be performed under a time constraint to inform policy makers, we suggest multiple phylodynamics models to be used simultaneously for a subset of data to ascertain the robustness of inferences.

Robust Design for Coalescent Model Inference

The coalescent process describes how changes in the size or structure of a population influence the genealogical patterns of sequences sampled from that population. The estimation of (effective) population size changes from genealogies that are reconstructed from these sampled sequences is an important problem in many biological fields. Often, population size is characterized by a piecewise-constant function, with each piece serving as a population size parameter to be estimated. Estimation quality depends on both the statistical coalescent inference method employed, and on the experimental protocol, which controls variables such as the sampling of sequences through time and space, or the transformation of model parameters. While there is an extensive literature on coalescent inference methodology, there is comparatively little work on experimental design. The research that does exist is largely simulation-based, precluding the development of provable or general design theorems. We examine three key design problems: temporal sampling of sequences under the skyline demographic coalescent model, spatio-temporal sampling under the structured coalescent model, and time discretization for sequentially Markovian coalescent models. In all cases, we prove that 1) working in the logarithm of the parameters to be inferred (e.g., population size) and 2) distributing informative coalescent events uniformly among these log-parameters, is uniquely robust. "Robust" means that the total and maximum uncertainty of our parameter estimates are minimized, and made insensitive to their unknown (true) values. This robust design theorem provides rigorous justification for several existing coalescent experimental design decisions and leads to usable guidelines for future empirical or simulation-based investigations. Given its persistence among models, this theorem may form the basis of an experimental design paradigm for coalescent inference.

The multifurcating skyline plot

A variety of methods based on coalescent theory have been developed to infer demographic history from gene sequences sampled from natural populations. The 'skyline plot' and related approaches are commonly employed as flexible prior distributions for phylogenetic trees in the Bayesian analysis of pathogen gene sequences. In this work we extend the classic and generalized skyline plot methods to phylogenies that contain one or more multifurcations (i.e. hard polytomies). We use the theory of Λ-coalescents (specifically, Beta ( 2 - α , α ) -coalescents) to develop the 'multifurcating skyline plot', which estimates a piecewise constant function of effective population size through time, conditional on a time-scaled multifurcating phylogeny. We implement a smoothing procedure and extend the method to serially sampled (heterochronous) data, but we do not address here the problem of estimating trees with multifurcations from gene sequence alignments. We validate our estimator on simulated data using maximum likelihood and find that parameters of the Beta ( 2 - α , α ) -coalescent process can be estimated accurately. Furthermore, we apply the multifurcating skyline plot to simulated trees generated by tracking transmissions in an individual-based model of epidemic superspreading. We find that high levels of superspreading are consistent with the high-variance assumptions underlying Λ-coalescents and that the estimated parameters of the Λ-coalescent model contain information about the degree of superspreading.

Phylogeography of HIV-1 suggests that Ugandan fishing communities are a sink for, not a source of, virus from general populations

Although fishing communities (FCs) in Uganda are disproportionately affected by HIV-1 relative to the general population (GP), the transmission dynamics are not completely understood. We earlier found most HIV-1 transmissions to occur within FCs of Lake Victoria. Here, we test the hypothesis that HIV-1 transmission in FCs is isolated from networks in the GP. We used phylogeography to reconstruct the geospatial viral migration patterns in 8 FCs and 2 GP cohorts and a Bayesian phylogenetic inference in BEAST v1.8.4 to analyse the temporal dynamics of HIV-1 transmission. Subtype A1 (pol region) was most prevalent in the FCs (115, 45.1%) and GP (177, 50.4%). More recent HIV transmission pairs from FCs were found at a genetic distance (GD) <1.5% than in the GP (Fisher’s exact test, p = 0.001). The mean time depth for pairs was shorter in FCs (5 months) than in the GP (4 years). Phylogeographic analysis showed strong support for viral migration from the GP to FCs without evidence of substantial viral dissemination to the GP. This suggests that FCs are a sink for, not a source of, virus strains from the GP. Targeted interventions in FCs should be extended to include the neighbouring GP for effective epidemic control.

Evidence for a recombinant origin of HIV-1 Group M from genomic variation

Reconstructing the early dynamics of the HIV-1 pandemic can provide crucial insights into the socioeconomic drivers of emerging infectious diseases in human populations, including the roles of urbanization and transportation networks. Current evidence indicates that the global pandemic comprising almost entirely of HIV-1/M originated around the 1920s in central Africa. However, these estimates are based on molecular clock estimates that are assumed to apply uniformly across the virus genome. There is growing evidence that recombination has played a significant role in the early history of the HIV-1 pandemic, such that different regions of the HIV-1 genome have different evolutionary histories. In this study, we have conducted a dated-tip analysis of all near full-length HIV-1/M genome sequences that were published in the GenBank database. We used a sliding window approach similar to the 'bootscanning' method for detecting breakpoints in inter-subtype recombinant sequences. We found evidence of substantial variation in estimated root dates among windows, with an estimated mean time to the most recent common ancestor of 1922. Estimates were significantly autocorrelated, which was more consistent with an early recombination event than with stochastic error variation in phylogenetic reconstruction and dating analyses. A piecewise regression analysis supported the existence of at least one recombination breakpoint in the HIV-1/M genome with interval-specific means around 1929 and 1913, respectively. This analysis demonstrates that a sliding window approach can accommodate early recombination events outside the established nomenclature of HIV-1/M subtypes, although it is difficult to incorporate the earliest available samples due to their limited genome coverage.

GI-16 lineage (624/I or Q1), there and back again: The history of one of the major threats for poultry farming of our era

The genetic variability of Infectious bronchitis virus (IBV) is one of the main challenges for its control, hindering not only the development of effective vaccination strategies but also its classification and, consequently, epidemiology understanding. The 624/I and Q1 genotypes, now recognized to be part of the GI-16 lineage, represent an excellent example of the practical consequences of IBV molecular epidemiology limited knowledge. In fact, being their common origin unrecognized for a long time, independent epidemiological pictures were drawn for the two genotypes. To fix this misinterpretation, the present study reconstructs the history, population dynamics and spreading patterns of GI-16 lineage as a whole using a phylodynamic approach. A collection of worldwide available hypervariable region 1 and 2 (HVR12) and 3 (HVR3) sequences of the S1 protein was analysed together with 258 HVR3 sequences obtained from samples collected in Italy (the country where this genotype was initially identified) since 1963. The results demonstrate that after its emergence at the beginning of the XX century, GI-16 was able to persist until present days in Italy. Approximately in the late 1980s, it migrated to Asia, which became the main nucleus for further spreading to Middle East, Europe and especially South America, likely through multiple introduction events. A remarkable among-country diffusion was also demonstrated in Asia and South America. Interestingly, although most of the recent Italian GI-16 strains originated from ancestral viruses detected in the same country, a couple were closely related to Chinese ones, supporting a backward viral flow from China to Italy. Besides to the specific case-study results, this work highlights the misconceptions that originate from the lack of a unified nomenclature and poor molecular epidemiology data generation and sharing. This shortcoming appears particularly relevant since the described scenario could likely be shared by many other IBV genotypes and pathogens in general.

Global emergence and population dynamics of divergent serotype 3 CC180 pneumococci

Streptococcus pneumoniae serotype 3 remains a significant cause of morbidity and mortality worldwide, despite inclusion in the 13-valent pneumococcal conjugate vaccine (PCV13). Serotype 3 increased in carriage since the implementation of PCV13 in the USA, while invasive disease rates remain unchanged. We investigated the persistence of serotype 3 in carriage and disease, through genomic analyses of a global sample of 301 serotype 3 isolates of the Netherlands3-31 (PMEN31) clone CC180, combined with associated patient data and PCV utilization among countries of isolate collection. We assessed phenotypic variation between dominant clades in capsule charge (zeta potential), capsular polysaccharide shedding, and susceptibility to opsonophagocytic killing, which have previously been associated with carriage duration, invasiveness, and vaccine escape. We identified a recent shift in the CC180 population attributed to a lineage termed Clade II, which was estimated by Bayesian coalescent analysis to have first appeared in 1968 [95% HPD: 1939-1989] and increased in prevalence and effective population size thereafter. Clade II isolates are divergent from the pre-PCV13 serotype 3 population in non-capsular antigenic composition, competence, and antibiotic susceptibility, the last of which resulting from the acquisition of a Tn916-like conjugative transposon. Differences in recombination rates among clades correlated with variations in the ATP-binding subunit of Clp protease, as well as amino acid substitutions in the comCDE operon. Opsonophagocytic killing assays elucidated the low observed efficacy of PCV13 against serotype 3. Variation in PCV13 use among sampled countries was not independently correlated with the CC180 population shift; therefore, genotypic and phenotypic differences in protein antigens and, in particular, antibiotic resistance may have contributed to the increase of Clade II. Our analysis emphasizes the need for routine, representative sampling of isolates from disperse geographic regions, including historically under-sampled areas. We also highlight the value of genomics in resolving antigenic and epidemiological variations within a serotype, which may have implications for future vaccine development.

Reconstructing the evolutionary history of pandemic foot-and-mouth disease viruses: the impact of recombination within the emerging O/ME-SA/Ind-2001 lineage

Foot-and-mouth disease (FMD) is a highly contagious disease of livestock affecting animal production and trade throughout Asia and Africa. Understanding FMD virus (FMDV) global movements and evolution can help to reconstruct the disease spread between endemic regions and predict the risks of incursion into FMD-free countries. Global expansion of a single FMDV lineage is rare but can result in severe economic consequences. Using extensive sequence data we have reconstructed the global space-time transmission history of the O/ME-SA/Ind-2001 lineage (which normally circulates in the Indian sub-continent) providing evidence of at least 15 independent escapes during 2013–2017 that have led to outbreaks in North Africa, the Middle East, Southeast Asia, the Far East and the FMD-free islands of Mauritius. We demonstrated that sequence heterogeneity of this emerging FMDV lineage is accommodated within two co-evolving divergent sublineages and that recombination by exchange of capsid-coding sequences can impact upon the reconstructed evolutionary histories. Thus, we recommend that only sequences encoding the outer capsid proteins should be used for broad-scale phylogeographical reconstruction. These data emphasise the importance of the Indian subcontinent as a source of FMDV that can spread across large distances and illustrates the impact of FMDV genome recombination on FMDV molecular epidemiology.

Molecular Evolution of the VP1 Gene in Human Norovirus GII.4 Variants in 1974-2015

Human norovirus (HuNoV) is a leading cause of viral gastroenteritis worldwide, of which GII.4 is the most predominant genotype. Unlike other genotypes, GII.4 has created various variants that escaped from previously acquired immunity of the host and caused repeated epidemics. However, the molecular evolutionary differences among all GII.4 variants, including recently discovered strains, have not been elucidated. Thus, we conducted a series of bioinformatic analyses using numerous, globally collected, full-length GII.4 major capsid (VP1) gene sequences (466 strains) to compare the evolutionary patterns among GII.4 variants. The time-scaled phylogenetic tree constructed using the Bayesian Markov chain Monte Carlo (MCMC) method showed that the common ancestor of the GII.4 VP1 gene diverged from GII.20 in 1840. The GII.4 genotype emerged in 1932, and then formed seven clusters including 14 known variants after 1980. The evolutionary rate of GII.4 strains was estimated to be 7.68 × 10⁻³ substitutions/site/year. The evolutionary rates probably differed among variants as well as domains [protruding 1 (P1), shell, and P2 domains]. The Osaka 2007 variant strains probably contained more nucleotide substitutions than any other variant. Few conformational epitopes were located in the shell and P1 domains, although most were contained in the P2 domain, which, as previously established, is associated with attachment to host factors and antigenicity. We found that positive selection sites for the whole GII.4 genotype existed in the shell and P1 domains, while Den Haag 2006b, New Orleans 2009, and Sydney 2012 variants were under positive selection in the P2 domain. Amino acid substitutions overlapped with putative epitopes or were located around the epitopes in the P2 domain. The effective population sizes of the present strains increased stepwise for Den Haag 2006b, New Orleans 2009, and Sydney 2012 variants. These results suggest that HuNoV GII.4 rapidly evolved in a few decades, created various variants, and altered its evolutionary rate and antigenicity.

Divergent HIV-1 strains (CRF92_C2U and CRF93_cpx) co-circulating in the Democratic Republic of the Congo: Phylogenetic insights on the early evolutionary history of subtype C

Molecular epidemiological studies revealed that the epicenter of the HIV pandemic was Kinshasa, the capital city of the Democratic Republic of the Congo (DRC) in Central Africa. All known subtypes and numerous complex recombinant strains co-circulate in the DRC. Moreover, high intra-subtype diversity has been also documented. During two previous surveys on HIV-1 antiretroviral drug resistance in the DRC, we identified two divergent subtype C lineages in the protease and partial reverse transcriptase gene regions. We sequenced eight near full-length genomes and classified them using bootscanning and likelihood-based phylogenetic analyses. Four strains are more closely related to subtype C although within the range of inter sub-subtype distances. However, these strains also have small unclassified fragments and thus were named CRF92_C2U. Another strain is a unique recombinant of CRF92_C2U with an additional small unclassified fragment and a small divergent subtype A fragment. The three remaining strains represent a complex mosaic named CRF93_cpx. CRF93_cpx have two fragments of divergent subtype C sequences, which are not conventional subtype C nor the above described C2, and multiple divergent subtype A-like fragments. We then inferred the time-scaled evolutionary history of subtype C following a Bayesian approach and a partitioned analysis using major genomic regions. CRF92_C2U and CRF93_cpx had the most recent common ancestor with conventional subtype C around 1932 and 1928, respectively. A Bayesian demographic reconstruction corroborated that the subtype C transition to a faster phase of exponential growth occurred during the 1950s. Our analysis showed considerable differences between the newly discovered early-divergent strains and the conventional subtype C and therefore suggested that this virus has been diverging in humans for several decades before the HIV/M diversity boom in the 1950s.

Think globally, act locally: Phylodynamic reconstruction of infectious bronchitis virus (IBV) QX genotype (GI-19 lineage) reveals different population dynamics and spreading patterns when evaluated on different epidemiological scales

Infectious bronchitis virus (IBV) represents one of the poultry industry major threats, particularly in high density producing countries. The emergence and spread of new IBV genotypes have frustrated the various disease control efforts implemented over time. Despite that, few comprehensive and large scale studies have been performed to understand the international and local spreading dynamics of this virus. In the present work, these phenomena were evaluated by implementing a Bayesian phylodynamic approach to reconstruct the epidemiological patterns and population history of the QX genotype (currently renamed GI-19 lineage), the most relevant IBV lineage of the Old-World. Our analysis, based on 807 partial S1 sequences of strains collected from 18 countries between 1993 and 2015, demonstrates that this genotype originated in China well before its first identification. After a prolonged local circulation, it started spreading to other European, Asian and Middle East countries in successive waves, which were mirrored by concomitant fluctuations in viral population size. Interestingly, the within-Europe spread was characterized by a higher estimated migration rate compared with the inter-continental one, potentially reflecting the closer geographic and economic relationships among these countries. Nevertheless, the colonization of new states by the GI-19 lineage appeared to occur mostly by single introduction events in both intra and inter-continental spread, likely because of epidemiological factor and health policy combination which seems to prevent the frequent introduction and mixing of different strains. On the other hand, the within Italy QX circulation reconstruction showed a much more intricate connection network among different locations, evidencing the difficulty in controlling IBV spread especially in highly densely poultry populated areas. The presence of several well supported epidemiological links among distantly related Italian regions testifies that animal transportation and indirect transmission routes rather than local airborne diffusion contribute to the QX success and persistence at local scale. Globally, the spreading dynamics and evolution of the QX genotype were reconstructed from its very origin to nowadays, demonstrating the need of more effective direct control measures, particularly within each country. Unfortunately, the incompleteness of available molecular epidemiology data represents an insurmountable limit which leaves many questions currently unsolved, thus highlighting the compulsoriness of a structured monitoring and data sharing system implementation.