Genealogical Working Distributions for Bayesian Model Testing with Phylogenetic Uncertainty

Current Evolutionary Dynamics of Porcine Epidemic Diarrhea Virus (PEDV) in the U.S. a Decade After Introduction

Porcine Epidemic Diarrhea Virus (PEDV) was introduced in the United States (U.S.) in 2013, spreading rapidly and leading to economic losses. Two strains, S-INDEL and non-S-INDEL, are present in the U.S. We analyzed 313 genomes and 556 Spike protein sequences generated since its introduction. PEDV case numbers were highest during the first two years after its introduction (epidemic phase), then declined and stabilized in the following years (endemic phase). Sequence surveillance was higher during the initial epidemic phase. Our results suggest the non-S-INDEL strain is the predominant strain in U.S. The non-S-INDEL sequences exhibit pairwise nucleotide identity percentages above 97.6%. Most non-S-INDEL sequences sampled after 2017 clustered into two sub-clades. No descendants derived from other clades present in the epidemic period were detected in the contemporary data, suggesting that these clades are no longer circulating in the U.S. The two clades currently circulating are restricted to two respective geographic regions and our results suggest limited inter-regional spread. This insight helps determine the risk of re-introduction of PEDV if it were regionally eliminated. Ongoing molecular surveillance is essential to confirming that some older clades no longer circulate anymore in the U.S., mapping the distribution and spread of recent clades, and understanding PEDV's evolutionary diversification.

Molecular epidemiology, evolution, and transmission dynamics of raccoon rabies virus in Connecticut

In North America, raccoon rabies virus (RRV) is a public health concern due to its potential for rapid spread, maintenance in wildlife, and impact on human and domesticated animal health. RRV is an endemic zoonotic pathogen throughout the eastern USA. In 1991, an outbreak of RRV in Fairfield County, Connecticut, spread through the state and eventually throughout the Northeast and into Canada. Factors that contribute to, or curb, RRV transmission should be explored and quantified to guide targeted rabies control efforts, including the size and location of buffer zones of vaccinated animals. However, population dynamics and potential underlying determinants of rabies virus diversity and circulation in Connecticut have not been fully studied. In this study, we aim to (i) investigate RRV source-sink dynamics between Connecticut and surrounding states and provinces, (ii) explore the impact of the Connecticut River as a natural barrier to transmission, and (iii) characterize the genomic diversity and transmission dynamics in Connecticut. Using RRV whole-genome sequences collected from various host species between 1990 and 2020, we performed comparative genetic and Bayesian phylodynamic analyses at multiple spatial scales. We analyzed 71 whole-genome sequences from Connecticut, including 21 recent RRV specimens collected at the Connecticut Veterinary Medical Diagnostic Laboratory that we sequenced for this study. Our analyses revealed evidence of RRV incursions over the US-Canada border, including bidirectional spread between Quebec and Vermont. Additionally, we highlighted the importance of Connecticut and New York in seeding RRV transmission in eastern North America, including two introduction events from New York to Connecticut that resulted in sustained local transmission. While RRV transmission does occur across the Housatonic and Connecticut Rivers, we demonstrated the distinct presence of spatial structuring in the phylogenetic trees and characterized the directionality of RRV migration. The significantly higher mean transition rates from locations east to west of the Connecticut River, compared to west to east, may be leveraged in directing interventions to fortify these natural barriers. Ultimately, the findings of these international, regional, and state analyses can inform targeted control programs, vaccination efforts, and enhanced surveillance at borders of key viral sources and sinks.

Bayesian phylogeographic inference of wheat yellow mosaic virus in China and Japan suggests that the virus migration history coincided with historical events

Wheat yellow mosaic virus (WYMV) is one of the most serious viral pathogens causing reductions in wheat yield in East Asia. We investigated the phylodynamics of WYMV by analysing the CP, VPg and P1 genes to understand the origin and dispersal of the virus. A Bayesian phylogenetic analysis revealed that the most recent common WYMV ancestor occurred in approximately 1742 (95% credibility interval, 1439-1916) CE (Common Era), and the evolutionary rates of the VPg, CP and P1 genes were 6.669 × 10-4 (95% credibility interval: 4.575 × 10-4-8.927 × 10-4), 2.468 × 10-4 (95% credibility interval: 1.667 × 10-4-3.338 × 10-4) and 5.765 × 10-5 (95% credibility interval: 3.285 × 10-6-1.252 × 10-4), respectively. Our phylogeographic analysis indicated that the WYMV population may have originated in Henan Province, China, first spreading to Japan in the mid-19th century and stopping after the Japanese surrender in World War II. The second wave spread to Japan from Shandong Province, China, in approximately 1977, a few years after the establishment of diplomatic relations between China and Japan. Before the founding of the People's Republic of China, Henan Province was the emigration centre of WYMV in East Asia, and after the late 20th century, Jiangsu and Shandong Provinces were also the virus emigration centres in East Asia. In addition, there were two migration pathways from Japan to Jiangsu and Shandong Provinces, China, in approximately 1918 and approximately 1999 respectively. Our results suggest that the wide spread of WYMV in East Asia is strongly related to human factors.

Phylogeography and Evolutionary Dynamics of Tobacco Curly Shoot Virus

Tobacco curly shoot virus (TbCSV), a begomovirus, causes significant economic losses in tobacco and tomato crops across East, Southeast, and South Asia. Despite its agricultural importance, the evolutionary dynamics and emergence process of TbCSV remain poorly understood. This study analyzed the phylodynamics of TbCSV by examining its nucleotide sequences of the coat protein (CP) gene collected between 2000 and 2022. Using various combinations of priors, Bayes factor comparisons identified heterochronous datasets (3 × 100 million chains) generated from a strict molecular clock and Bayesian skyline tree priors as the most robust. The mean substitution rate of the CP gene was estimated at 6.50 × 10-4 substitutions/site/year (95% credibility interval: 4.74 × 10-4-8.50 × 10-4). TbCSV was inferred to have diverged around 1920 CE (95% credibility interval: 1887-1952), with its most probable origin in South Asia. These findings provide valuable insights for the phylogeography and evolutionary dynamics of TbCSV, and contribute to a broader understanding of begomovirus epidemiology.

Assessing the effect of model specification and prior sensitivity on Bayesian tests of temporal signal

Our understanding of the evolution of many microbes has been revolutionised by the molecular clock, a statistical tool to infer evolutionary rates and timescales from analyses of biomolecular sequences. In all molecular clock models, evolutionary rates and times are jointly unidentifiable and 'calibration' information must therefore be used. For many organisms, sequences sampled at different time points can be employed for such calibration. Before attempting to do so, it is recommended to verify that the data carry sufficient information for molecular dating, a practice referred to as evaluation of temporal signal. Recently, a fully Bayesian approach, BETS (Bayesian Evaluation of Temporal Signal), was proposed to overcome known limitations of other commonly used techniques such as root-to-tip regression or date randomisation tests. BETS requires the specification of a full Bayesian phylogenetic model, posing several considerations for untangling the impact of model choice on the detection of temporal signal. Here, we aimed to (i) explore the effect of molecular clock model and tree prior specification on the results of BETS and (ii) provide guidelines for improving our confidence in molecular clock estimates. Using microbial molecular sequence data sets and simulation experiments, we assess the impact of the tree prior and its hyperparameters on the accuracy of temporal signal detection. In particular, highly informative priors that are inconsistent with the data can result in the incorrect detection of temporal signal. In consequence, we recommend: (i) using prior predictive simulations to determine whether the prior generates a reasonable expectation of parameters of interest, such as the evolutionary rate and age of the root node, (ii) conducting prior sensitivity analyses to assess the robustness of the posterior to the choice of prior, and (iii) selecting a molecular clock model that reasonably describes the evolutionary process.

Emergence of the B.1.214.2 SARS-CoV-2 lineage with an Omicron-like spike insertion and a unique upper airway immune signature

We investigate the emergence, mutation profile, and dissemination of SARS-CoV-2 lineage B.1.214.2, first identified in Belgium in January 2021. This variant, featuring a 3-amino acid insertion in the spike protein similar to the Omicron variant, was speculated to enhance transmissibility or immune evasion. Initially detected in international travelers, it substantially transmitted in Central Africa, Belgium, Switzerland, and France, peaking in April 2021. Our travel-aware phylogeographic analysis, incorporating travel history, estimated the origin to the Republic of the Congo, with primary European entry through France and Belgium, and multiple smaller introductions during the epidemic. We correlate its spread with human travel patterns and air passenger data. Further, upon reviewing national reports of SARS-CoV-2 outbreaks in Belgian nursing homes, we found this strain caused moderately severe outcomes (8.7% case fatality ratio). A distinct nasopharyngeal immune response was observed in elderly patients, characterized by 80% unique signatures, higher B- and T-cell activation, increased type I IFN signaling, and reduced NK, Th17, and complement system activation, compared to similar outbreaks. This unique immune response may explain the variant's epidemiological behavior and underscores the need for nasal vaccine strategies against emerging variants.

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.

Molecular epidemiology of recurrent zoonotic transmission of mpox virus in West Africa

Nigeria and Cameroon reported their first mpox cases in over three decades in 2017 and 2018 respectively. The outbreak in Nigeria is recognised as an ongoing human epidemic. However, owing to sparse surveillance and genomic data, it is not known whether the increase in cases in Cameroon is driven by zoonotic or sustained human transmission. Notably, the frequency of zoonotic transmission remains unknown in both Cameroon and Nigeria. To address these uncertainties, we investigated the zoonotic transmission dynamics of the mpox virus (MPXV) in Cameroon and Nigeria, with a particular focus on the border regions. We show that in these regions mpox cases are still driven by zoonotic transmission of a newly identified Clade IIb.1. We identify two distinct zoonotic lineages that circulate across the Nigeria-Cameroon border, with evidence of recent and historic cross border dissemination. Our findings support that the complex cross-border forest ecosystems likely hosts shared animal populations that drive cross-border viral spread, which is likely where extant Clade IIb originated. We identify that the closest zoonotic outgroup to the human epidemic circulated in southern Nigeria in October 2013. We also show that the zoonotic precursor lineage circulated in an animal population in southern Nigeria for more than 45 years. This supports findings that southern Nigeria was the origin of the human epidemic. Our study highlights the ongoing MPXV zoonotic transmission in Cameroon and Nigeria, underscoring the continuous risk of MPXV (re)emergence.

Assessing the emergence time of SARS-CoV-2 zoonotic spillover

Understanding the evolution of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) and its relationship to other coronaviruses in the wild is crucial for preventing future virus outbreaks. While the origin of the SARS-CoV-2 pandemic remains uncertain, mounting evidence suggests the direct involvement of the bat and pangolin coronaviruses in the evolution of the SARS-CoV-2 genome. To unravel the early days of a probable zoonotic spillover event, we analyzed genomic data from various coronavirus strains from both human and wild hosts. Bayesian phylogenetic analysis was performed using multiple datasets, using strict and relaxed clock evolutionary models to estimate the occurrence times of key speciation, gene transfer, and recombination events affecting the evolution of SARS-CoV-2 and its closest relatives. We found strong evidence supporting the presence of temporal structure in datasets containing SARS-CoV-2 variants, enabling us to estimate the time of SARS-CoV-2 zoonotic spillover between August and early October 2019. In contrast, datasets without SARS-CoV-2 variants provided mixed results in terms of temporal structure. However, they allowed us to establish that the presence of a statistically robust clade in the phylogenies of gene S and its receptor-binding (RBD) domain, including two bat (BANAL) and two Guangdong pangolin coronaviruses (CoVs), is due to the horizontal gene transfer of this gene from the bat CoV to the pangolin CoV that occurred in the middle of 2018. Importantly, this clade is closely located to SARS-CoV-2 in both phylogenies. This phylogenetic proximity had been explained by an RBD gene transfer from the Guangdong pangolin CoV to a very recent ancestor of SARS-CoV-2 in some earlier works in the field before the BANAL coronaviruses were discovered. Overall, our study provides valuable insights into the timeline and evolutionary dynamics of the SARS-CoV-2 pandemic.

Molecular evolution and phylogeographic analysis of wheat dwarf virus

Wheat dwarf virus (WDV) has caused considerable economic loss in the global production of grain crops. Knowledge of the evolutionary biology and population history of the pathogen remain poorly understood. We performed molecular evolution and worldwide phylodynamic analyses of the virus based on the genes in the protein-coding region of the entire viral genome. Our results showed that host-driven and geography-driven adaptation are major factors that affects the evolution of WDV. Bayesian phylogenetic analysis estimates that the average WDV substitution rate was 4.240 × 10-4 substitutions/site/year (95% credibility interval, 2.828 × 10-4-5.723 × 10-4), and the evolutionary rates of genes encoding proteins with virion-sense transcripts and genes encoding proteins with complementary-sense transcripts were different. The positively selected sites were detected in only two genes encoding proteins with complementary-sense, and WDV-barley are subject to stronger purifying selection than WDV-wheat. The time since the most recent common WDV ancestor was 1746 (95% credibility interval, 1517-1893) CE. Further analyses identified that the WDV-barley population and WDV-wheat population experienced dramatic expansion-decline episodes, and the expansion time of the WDV-barley population was earlier than that of the WDV-wheat population. Our phylogeographic analysis showed that the WDV population originating in Iran was subsequently introduced to Europe, and then spread from Eastern Europe to China.

Evaluating the Accuracy of Methods for Detecting Correlated Rates of Molecular and Morphological Evolution

Determining the link between genomic and phenotypic change is a fundamental goal in evolutionary biology. Insights into this link can be gained by using a phylogenetic approach to test for correlations between rates of molecular and morphological evolution. However, there has been persistent uncertainty about the relationship between these rates, partly because conflicting results have been obtained using various methods that have not been examined in detail. We carried out a simulation study to evaluate the performance of 5 statistical methods for detecting correlated rates of evolution. Our simulations explored the evolution of molecular sequences and morphological characters under a range of conditions. Of the methods tested, Bayesian relaxed-clock estimation of branch rates was able to detect correlated rates of evolution correctly in the largest number of cases. This was followed by correlations of root-to-tip distances, Bayesian model selection, independent sister-pairs contrasts, and likelihood-based model selection. As expected, the power to detect correlated rates increased with the amount of data, both in terms of tree size and number of morphological characters. Likewise, greater among-lineage rate variation in the data led to improved performance of all 5 methods, particularly for Bayesian relaxed-clock analysis when the rate model was mismatched. We then applied these methods to a data set from flowering plants and did not find evidence of a correlation in evolutionary rates between genomic data and morphological characters. The results of our study have practical implications for phylogenetic analyses of combined molecular and morphological data sets, and highlight the conditions under which the links between genomic and phenotypic rates of evolution can be evaluated quantitatively.

Ancient chicken remains reveal the origins of virulence in Marek's disease virus

The pronounced growth in livestock populations since the 1950s has altered the epidemiological and evolutionary trajectory of their associated pathogens. For example, Marek's disease virus (MDV), which causes lymphoid tumors in chickens, has experienced a marked increase in virulence over the past century. Today, MDV infections kill >90% of unvaccinated birds, and controlling it costs more than US$1 billion annually. By sequencing MDV genomes derived from archeological chickens, we demonstrate that it has been circulating for at least 1000 years. We functionally tested the Meq oncogene, one of 49 viral genes positively selected in modern strains, demonstrating that ancient MDV was likely incapable of driving tumor formation. Our results demonstrate the power of ancient DNA approaches to trace the molecular basis of virulence in economically relevant pathogens.

Detecting Episodic Evolution through Bayesian Inference of Molecular Clock Models

Molecular evolutionary rate variation is a key aspect of the evolution of many organisms that can be modeled using molecular clock models. For example, fixed local clocks revealed the role of episodic evolution in the emergence of SARS-CoV-2 variants of concern. Like all statistical models, however, the reliability of such inferences is contingent on an assessment of statistical evidence. We present a novel Bayesian phylogenetic approach for detecting episodic evolution. It consists of computing Bayes factors, as the ratio of posterior and prior odds of evolutionary rate increases, effectively quantifying support for the effect size. We conducted an extensive simulation study to illustrate the power of this method and benchmarked it to formal model comparison of a range of molecular clock models using (log) marginal likelihood estimation, and to inference under a random local clock model. Quantifying support for the effect size has higher sensitivity than formal model testing and is straight-forward to compute, because it only needs samples from the posterior and prior distribution. However, formal model testing has the advantage of accommodating a wide range molecular clock models. We also assessed the ability of an automated approach, known as the random local clock, where branches under episodic evolution may be detected without their a priori definition. In an empirical analysis of a data set of SARS-CoV-2 genomes, we find "very strong" evidence for episodic evolution. Our results provide guidelines and practical methods for Bayesian detection of episodic evolution, as well as avenues for further research into this phenomenon.

Bayesian phylodynamic analysis reveals the evolutionary history and the dispersal patterns of citrus tristeza virus in China based on the p25 gene

BACKGROUND

Citrus tristeza virus (CTV) is one of the most serious threats to the citrus industry, and is present in both wild and cultivated citrus. The origin and dispersal patterns of CTV is still poorly understood in China.

METHODS

In this study, 524 CTV suspected citrus samples from China were collected, including 354 cultivated citrus samples and 174 wild citrus samples. Finally, 126 CTV coat protein sequences were obtained with time-stamped from 10 citrus origins in China. Bayesian phylodynamic inference were performed for CTV origin and dispersal patterns study in China.

RESULT

We found that CTV was mainly distributed in southern and coastal areas of China. The substitution rate of CTV was 4.70 × 10- 4 subs/site/year (95% credibility interval: 1.10 × 10- 4 subs/site/year ~ 9.10 × 10- 4 subs/site/year), with a slight increasing trend in CTV populations between 1990 and 2006. The CTV isolates in China shared a most common recent ancestor around 1875 (95% credibility interval: 1676.57 ~ 1961.02). The CTV in China was originated from wild citrus in Hunan and Jiangxi, and then spread from the wild citrus to cultivated citrus in the growing regions of Sichuan, Chongqing, Hubei, Fujian, Zhejiang, Guangxi and Guangdong provinces.

CONCLUSIONS

This study has proved that CTV in China was originated from wild citrus in Hunan and Jiangxi. The spatial-temporal distribution and dispersal patterns has uncovered the population and pandemic history of CTV, providing hints toward a better understanding of the spread and origin of CTV in China.

Application of referenced thermodynamic integration to Bayesian model selection

Evaluating normalising constants is important across a range of topics in statistical learning, notably Bayesian model selection. However, in many realistic problems this involves the integration of analytically intractable, high-dimensional distributions, and therefore requires the use of stochastic methods such as thermodynamic integration (TI). In this paper we apply a simple but under-appreciated variation of the TI method, here referred to as referenced TI, which computes a single model's normalising constant in an efficient way by using a judiciously chosen reference density. The advantages of the approach and theoretical considerations are set out, along with pedagogical 1 and 2D examples. The approach is shown to be useful in practice when applied to a real problem -to perform model selection for a semi-mechanistic hierarchical Bayesian model of COVID-19 transmission in South Korea involving the integration of a 200D density.

The tumour is in the detail: Local phylogenetic, population and epidemiological dynamics of a transmissible cancer in Tasmanian devils

Infectious diseases are a major threat for biodiversity conservation and can exert strong influence on wildlife population dynamics. Understanding the mechanisms driving infection rates and epidemic outcomes requires empirical data on the evolutionary trajectory of pathogens and host selective processes. Phylodynamics is a robust framework to understand the interaction of pathogen evolutionary processes with epidemiological dynamics, providing a powerful tool to evaluate disease control strategies. Tasmanian devils have been threatened by a fatal transmissible cancer, devil facial tumour disease (DFTD), for more than two decades. Here we employ a phylodynamic approach using tumour mitochondrial genomes to assess the role of tumour genetic diversity in epidemiological and population dynamics in a devil population subject to 12 years of intensive monitoring, since the beginning of the epidemic outbreak. DFTD molecular clock estimates of disease introduction mirrored observed estimates in the field, and DFTD genetic diversity was positively correlated with estimates of devil population size. However, prevalence and force of infection were the lowest when devil population size and tumour genetic diversity was the highest. This could be due to either differential virulence or transmissibility in tumour lineages or the development of host defence strategies against infection. Our results support the view that evolutionary processes and epidemiological trade-offs can drive host-pathogen coexistence, even when disease-induced mortality is extremely high. We highlight the importance of integrating pathogen and population evolutionary interactions to better understand long-term epidemic dynamics and evaluating disease control strategies.

The evolutionary history of hepaciviruses

In the search for natural reservoirs of hepatitis C virus (HCV), a broad diversity of non-human viruses within the Hepacivirus genus has been uncovered. However, the evolutionary dynamics that shaped the diversity and timescale of hepaciviruses evolution remain elusive. To gain further insights into the origins and evolution of this genus, we screened a large dataset of wild mammal samples (n = 1,672) from Africa and Asia, and generated 34 full-length hepacivirus genomes. Phylogenetic analysis of these data together with publicly available genomes emphasizes the importance of rodents as hepacivirus hosts and we identify 13 rodent species and 3 rodent genera (in Cricetidae and Muridae families) as novel hosts of hepaciviruses. Through co-phylogenetic analyses, we demonstrate that hepacivirus diversity has been affected by cross-species transmission events against the backdrop of detectable signal of virus-host co-divergence in the deep evolutionary history. Using a Bayesian phylogenetic multidimensional scaling approach, we explore the extent to which host relatedness and geographic distances have structured present-day hepacivirus diversity. Our results provide evidence for a substantial structuring of mammalian hepacivirus diversity by host as well as geography, with a somewhat more irregular diffusion process in geographic space. Finally, using a mechanistic model that accounts for substitution saturation, we provide the first formal estimates of the timescale of hepacivirus evolution and estimate the origin of the genus to be about 22 million years ago. Our results offer a comprehensive overview of the micro- and macroevolutionary processes that have shaped hepacivirus diversity and enhance our understanding of the long-term evolution of the Hepacivirus genus.

LoRaD: Marginal likelihood estimation with haste (but no waste)

The Lowest Radial Distance (LoRaD) method is a modification of the recently introduced Partition-Weighted Kernel method for estimating the marginal likelihood of a model, a quantity important for Bayesian model selection. For analyses involving a fixed tree topology, LoRaD improves upon the Steppingstone or Thermodynamic Integration (Path Sampling) approaches now in common use in phylogenetics because it requires sampling only from the posterior distribution, avoiding the need to sample from a series of ad hoc power posterior distributions, and yet is more accurate than other fast methods such as the Generalized Harmonic Mean (GHM) method. We show that the method performs well in comparison to the Generalized Steppingstone method on an empirical fixed-topology example from molecular phylogenetics involving 180 parameters. The LoRaD method can also be used to obtain the marginal likelihood in the variable-topology case if at least one tree topology occurs with sufficient frequency in the posterior sample to allow accurate estimation of the marginal likelihood conditional on that topology. [Bayesian; marginal likelihood; phylogenetics.].

Diversification Models Conflate Likelihood and Prior, and Cannot be Compared Using Conventional Model-Comparison Tools

Time-calibrated phylogenetic trees are a tremendously powerful tool for studying evolutionary, ecological, and epidemiological phenomena. Such trees are predominantly inferred in a Bayesian framework, with the phylogeny itself treated as a parameter with a prior distribution (a "tree prior"). However, we show that the tree "parameter" consists, in part, of data, in the form of taxon samples. Treating the tree as a parameter fails to account for these data and compromises our ability to compare among models using standard techniques (e.g., marginal likelihoods estimated using path-sampling and stepping-stone sampling algorithms). Since accuracy of the inferred phylogeny strongly depends on how well the tree prior approximates the true diversification process that gave rise to the tree, the inability to accurately compare competing tree priors has broad implications for applications based on time-calibrated trees. We outline potential remedies to this problem, and provide guidance for researchers interested in assessing the fit of tree models. [Bayes factors; Bayesian model comparison; birth-death models; divergence-time estimation; lineage diversification].

Molecular Characterization of Dengue Virus Strains from the 2019-2020 Epidemic in Hanoi, Vietnam

Dengue virus (DENV), which has circulated in Vietnam for several decades, has multiple serotypes and genotypes. A 2019 dengue outbreak resulted in a larger number of cases than any other outbreak. We conducted a molecular characterization using samples collected in 2019-2020 from dengue patients in Hanoi and nearby cities located in northern Vietnam. The circulating serotypes were DENV-1 (25%, n = 22) and DENV-2 (73%, n = 64). Phylogenetic analyses revealed that all DENV-1 (n = 13) were genotype I and clustered to local strains circulating during the previous outbreak in the 2017, whereas DENV-2 consisted of two genotypes: Asian-I (n = 5), related to local strains from 2006-2022, and cosmopolitan (n = 18), the predominant genotype in this epidemic. The current cosmopolitan virus was identified as having an Asian-Pacific lineage. The virus was closely related to strains in other recent outbreaks in Southeast Asian countries and China. Multiple introductions occurred in 2016-2017, which were possibly from maritime Southeast Asia (Indonesia, Singapore, and Malaysia), mainland Southeast Asia (Cambodia and Thailand), or China, rather than from an expansion of localized Vietnamese cosmopolitan strains that were previously detected in the 2000s. We also analyzed the genetic relationship between Vietnam's cosmopolitan strain and recent global strains reported from Asia, Oceania, Africa, and South America. This analysis revealed that viruses of Asian-Pacific lineage are not restricted to Asia but have spread to Peru and Brazil in South America.

Phylogeographic reconstruction of the emergence and spread of Powassan virus in the northeastern United States

Powassan virus is an emerging tick-borne virus of concern for public health, but very little is known about its transmission patterns and ecology. Here, we expanded the genomic dataset by sequencing 279 Powassan viruses isolated from Ixodes scapularis ticks from the northeastern United States. Our phylogeographic reconstructions revealed that Powassan virus lineage II was likely introduced or emerged from a relict population in the Northeast between 1940 and 1975. Sequences strongly clustered by sampling location, suggesting a highly focal geographical distribution. Our analyses further indicated that Powassan virus lineage II emerged in the northeastern United States mostly following a south-to-north pattern, with a weighted lineage dispersal velocity of ~3 km/y. Since the emergence in the Northeast, we found an overall increase in the effective population size of Powassan virus lineage II, but with growth stagnating during recent years. The cascading effect of population expansion of white-tailed deer and I. scapularis populations likely facilitated the emergence of Powassan virus in the northeastern United States.

Evolutionary history and global spatiotemporal pattern of alfalfa mosaic virus

Alfalfa mosaic virus (AMV) is an important plant virus causing considerable economic loss to alfalfa production. Knowledge of the evolutionary and demographic history of the pathogen is limited but essential to the development of effective and sustainable pathogen management schemes. In this study, we performed worldwide phylodynamic analyses of AMV based on 154 nucleotide sequences of the coat protein gene, sampled from 1985 to 2020, to understand the epidemiology of this pathogen. Bayesian phylogenetic reconstruction estimates that the crown group of AMV dates back to 1840 (95% credibility interval, 1687-1955). We revealed that AMV continuously evolves at a rate of 4.14 × 10^-4 substitutions/site/year (95% credibility interval, 1.04 × 10^-4 - 6.68 × 10^-4). Our phylogeographic analyses identified multiple migration links between Europe and other regions, implying that Europe played a key role in spreading the virus worldwide. Further analyses showed that the clustering pattern of AMV isolates is significantly correlated to geographic regions, indicating that geography-driven adaptation may be a factor that affects the evolution of AMV. Our findings may be potentially used in the development of effective control strategies for AMV.

The Evolution and Global Spatiotemporal Dynamics of Senecavirus A

Recurrent outbreaks of senecavirus A (SVA)-associated vesicular disease have led to a large number of infected pigs being culled and has caused considerable economic losses to the swine industry. Although SVA was discovered 2 decades ago, knowledge about the evolutionary and transmission histories of SVA remains unclear. Herein, we performed an integrated analysis of the recombination, phylogeny, selection, and spatiotemporal dynamics of SVA. Phylogenetic analysis demonstrated that SVA diverged into two main branches, clade I (pre-2007 strains) and clade II (post-2007 strains). Importantly, analysis of selective strength showed that clade II was evolving under relaxed selection compared with clade I. Positive selection analysis identified 27 positive selective sites, most of which are located on the outer surface of capsid protomer or on the important functional domains of nonstructure proteins. Bayesian phylodynamics suggested that the estimated time to the most recent common ancestor of SVA was around 1986, and the estimated substitution rate of SVA was 3.3522 × 10-3 nucleotide substitutions/site/year. Demographic history analysis revealed that the effective population size of SVA has experienced a gradually increasing trend with slight fluctuation until 2017 followed by a sharp decline. Notably, Bayesian phylogeographic analysis inferred that Brazil might be the source of SVA's global transmission since 2015. In summary, these data illustrated that the ongoing evolution of SVA drove the lineage-specific innovation and potentially phenotypically important variation. Our study sheds new light on the fundamental understanding of SVA evolution and spread history. IMPORTANCE Recurrent outbreaks and global epidemics of senecavirus A-associated vesicular disease have caused heavy economic losses and have threatened the development of the pig industry. However, the question of where the virus comes from has been one of the biggest puzzles due to the stealthy nature of the virus. Consequently, tracing the source, evolution, and transmission pattern of SVA is a very challenging task. Based on the most comprehensive analysis, we revealed the origin time, rapid evolution, epidemic dynamics, and selection of SVA. We observed two main genetic branches, clade I (pre-2007 strains) and clade II (post-2007 strains), and described the epidemiological patterns of SVA in different countries. We also first identified Brazil as the source of SVA's global transmission since 2015. Findings in this study provide important implications for the control and prevention of the virus.

Phylogeographic patterns of the yellow fever virus around the metropolitan region of São Paulo, Brazil, 2016-2019

From 2016 to 2019, the largest outbreak caused by the Yellow Fever virus (YFV) in the 21st century in the Americas occurred in southeastern Brazil. A sylvatic cycle of transmission was reported near densely populated areas, such as the large metropolitan area of the city of São Paulo. Here, we describe the origin, spread, and movement of the YFV throughout the state of São Paulo. Whole-genome sequences were obtained from tissues of two patients who died due to severe yellow fever, during 2018-2019. Molecular analysis indicated that all analyzed tissues were positive for YFV RNA, with the liver being the organ with the highest amount of viral RNA. Sequence analysis indicates that genomes belonged to the South American genotype I and were grouped in the epidemic clade II, which includes sequences from the states of Goiás, Minas Gerais, and São Paulo of previous years. The analysis of viral dispersion indicates that the outbreak originated in Goiás at the end of 2014 and reached the state of São Paulo through the state of Minas Gerais after 2016. When the virus reached near the urban area, it spread towards both the east and south regions of the state, not establishing an urban transmission cycle in the metropolitan region of São Paulo. The virus that moved towards the east met with YFV coming from the south of the state of Rio de Janeiro, and the YFV that was carried to the south reached the Brazilian states located in the south region of the country.

The Population Genomics of Increased Virulence and Antibiotic Resistance in Human Commensal Escherichia coli over 30 Years in France

Escherichia coli is a commensal species of the lower intestine but is also a major pathogen causing intestinal and extraintestinal infections that is increasingly prevalent and resistant to antibiotics. Most studies on genomic evolution of E. coli used isolates from infections. Here, instead, we whole-genome sequenced a collection of 403 commensal E. coli isolates from fecal samples of healthy adult volunteers in France (1980 to 2010). These isolates were distributed mainly in phylogroups A and B2 (30% each) and belonged to 152 sequence types (STs), the five most frequent being ST10 (phylogroup A; 16.3%), ST73 and ST95 (phylogroup B2; 6.3 and 5.0%, respectively), ST69 (phylogroup D; 4.2%), and ST59 (phylogroup F; 3.9%), and 224 O:H serotypes. ST and serotype diversity increased over time. The O1, O2, O6, and O25 groups used in bioconjugate O-antigen vaccine against extraintestinal infections were found in 23% of the strains of our collection. The increase in frequency of virulence-associated genes and antibiotic resistance was driven by two evolutionary mechanisms. Evolution of virulence gene frequency was driven by both clonal expansion of STs with more virulence genes ("ST-driven") and increases in gene frequency within STs independent of changes in ST frequencies ("gene-driven"). In contrast, the evolution of resistance was dominated by increases in frequency within STs ("gene-driven"). This study provides a unique picture of the phylogenomic evolution of E. coli in its human commensal habitat over 30 years and will have implications for the development of preventive strategies. IMPORTANCE Escherichia coli is an opportunistic pathogen with the greatest burden of antibiotic resistance, one of the main causes of bacterial infections and an increasing concern in an aging population. Deciphering the evolutionary dynamics of virulence and antibiotic resistance in commensal E. coli is important to understand adaptation and anticipate future changes. The gut of vertebrates is the primary habitat of E. coli and probably where selection for virulence and resistance takes place. Unfortunately, most whole-genome-sequenced strains are isolated from pathogenic conditions. Here, we whole-genome sequenced 403 E. coli commensals isolated from healthy French subjects over a 30-year period. Virulence genes increased in frequency by both clonal expansion of clones carrying them and increases in frequency within clones, whereas resistance genes increased by within-clone increased frequency. Prospective studies of E. coli commensals should be performed worldwide to have a broader picture of evolution and adaptation of this species.

Genetic characterization and evolution of H6N6 subtype avian influenza viruses

H6-subtype avian influenza virus (AIV) was prevalent in the world and could sporadically infect humans. Here, a new chicken-derived H6N6-subtype AIV strain A/chicken/Zhejiang/49/2021 (ZJ49) was isolated in Zhejiang Province, China in 2021. Phylogenetic analysis by Maximum likelihood methods showed that H6-subtype AIVs were classed into 13 groups according to HA gene. The ZJ49 strain belonged to the G12 group, which mainly consisted of strains from Asian and dominated in recent years. Based on NA gene, H6-subtype AIVs were divided into N6.1 and N6.2 clades according to the NA gene. The ZJ49 isolate was located in the N6.2e clade, which mainly consisted of the H5N6-subtype AIVs. Phylogenetic analysis by Bayesian methods showed that the effective quantity size of H6-subtype AIVs increased around 1990, reached a peak around 2015, declined after 2015, then kept in a stable level after 2018. The reassortment analysis predicted that the PB2, PA, and NA genes of ZJ49 may recombine with H5-subtype AIVs. The amino acid at 222 position of HA gene of ZJ49 strain mutated from A to V, suggesting that ZJ49 has a potential ability to cross species barriers. The four glycosylation sites were highly conserved, implying less impact on the fold and conception of HA stem structure. Our results revealed the complicated evolution, reassortment, and mutations of receptor binding sites of H6-subtype AIVs, which emphasize the importance to continuously monitor the epidemiology and evolution of H6-subtype AIVs.

Molecular Epidemiology of Porcine Parvovirus Type 1 (PPV1) and the Reactivity of Vaccine-Induced Antisera Against Historical and Current PPV1 Strains

Porcine Parvovirus Type 1 (PPV1) contributes to important losses in the swine industry worldwide. During a PPV1 infection, embryos and fetuses are targeted, resulting in stillbirth, mummification, embryonic death, and infertility (SMEDI syndrome). Even though vaccination is common in gilts and sows, strains mainly belonging to the 27a-like group have been spreading in Europe since early 2000s, resulting in SMEDI problems and requiring in-depth studies into the molecular epidemiology and vaccination efficacy of commercial vaccines. Here, we show that PPV1 has evolved since 1855 [1737, 1933] at a rate of 4.71 × 10⁻⁵ nucleotide substitutions per site per year. Extensive sequencing allowed evaluating and reassessing the current PPV1 VP1-based classifications, providing evidence for the existence of four relevant phylogenetic groups. While most European strains belong to the PPV1a (G1) or PPV1b (G2 or 27a-like) group, most Asian and American G2 strains and some European strains were divided into virulent PPV1c (e.g. NADL-8) and attenuated PPV1d (e.g. NADL-2) groups. The increase in the swine population, vaccination degree, and health management (vaccination and biosafety) influenced the spread of PPV1. The reactivity of anti-PPV1 antibodies from sows vaccinated with Porcilis^© Parvo, Eryseng^© Parvo, or ReproCyc^© ParvoFLEX against different PPV1 field strains was the highest upon vaccination with ReproCyc^© ParvoFLEX, followed by Eryseng^© Parvo, and Porcilis^© Parvo. Our findings contribute to the evaluation of the immunogenicity of existing vaccines and support the development of new vaccine candidates. Finally, the potential roles of cluster-specific hallmark amino acids in elevated pathogenicity and viral entry are discussed.

Purifying Selection Determines the Short-Term Time Dependency of Evolutionary Rates in SARS-CoV-2 and pH1N1 Influenza

High-throughput sequencing enables rapid genome sequencing during infectious disease outbreaks and provides an opportunity to quantify the evolutionary dynamics of pathogens in near real-time. One difficulty of undertaking evolutionary analyses over short timescales is the dependency of the inferred evolutionary parameters on the timespan of observation. Crucially, there are an increasing number of molecular clock analyses using external evolutionary rate priors to infer evolutionary parameters. However, it is not clear which rate prior is appropriate for a given time window of observation due to the time-dependent nature of evolutionary rate estimates. Here, we characterize the molecular evolutionary dynamics of SARS-CoV-2 and 2009 pandemic H1N1 (pH1N1) influenza during the first 12 months of their respective pandemics. We use Bayesian phylogenetic methods to estimate the dates of emergence, evolutionary rates, and growth rates of SARS-CoV-2 and pH1N1 over time and investigate how varying sampling window and data set sizes affect the accuracy of parameter estimation. We further use a generalized McDonald-Kreitman test to estimate the number of segregating nonneutral sites over time. We find that the inferred evolutionary parameters for both pandemics are time dependent, and that the inferred rates of SARS-CoV-2 and pH1N1 decline by ∼50% and ∼100%, respectively, over the course of 1 year. After at least 4 months since the start of sequence sampling, inferred growth rates and emergence dates remain relatively stable and can be inferred reliably using a logistic growth coalescent model. We show that the time dependency of the mean substitution rate is due to elevated substitution rates at terminal branches which are 2-4 times higher than those of internal branches for both viruses. The elevated rate at terminal branches is strongly correlated with an increasing number of segregating nonneutral sites, demonstrating the role of purifying selection in generating the time dependency of evolutionary parameters during pandemics.

The Emergence of SARS-CoV-2 Variants of Concern Is Driven by Acceleration of the Substitution Rate

The ongoing SARS-CoV-2 pandemic has seen an unprecedented amount of rapidly generated genome data. These data have revealed the emergence of lineages with mutations associated to transmissibility and antigenicity, known as variants of concern (VOCs). A striking aspect of VOCs is that many of them involve an unusually large number of defining mutations. Current phylogenetic estimates of the substitution rate of SARS-CoV-2 suggest that its genome accrues around two mutations per month. However, VOCs can have 15 or more defining mutations and it is hypothesized that they emerged over the course of a few months, implying that they must have evolved faster for a period of time. We analyzed genome sequence data from the GISAID database to assess whether the emergence of VOCs can be attributed to changes in the substitution rate of the virus and whether this pattern can be detected at a phylogenetic level using genome data. We fit a range of molecular clock models and assessed their statistical performance. Our analyses indicate that the emergence of VOCs is driven by an episodic increase in the substitution rate of around 4-fold the background phylogenetic rate estimate that may have lasted several weeks or months. These results underscore the importance of monitoring the molecular evolution of the virus as a means of understanding the circumstances under which VOCs may emerge.

Identification of a novel SARS-CoV-2 P.1 sub-lineage in Brazil provides new insights about the mechanisms of emergence of variants of concern

One of the most remarkable severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOC) features is the significant number of mutations they acquired. However, the specific factors that drove the emergence of such variants since the second half of 2020 are not fully resolved. In this study, we describe a new SARS-CoV-2 P.1 sub-lineage circulating in Brazil, denoted here as Gamma-like-II, that as well as the previously described lineage Gamma-like-I shares several lineage-defining mutations with the VOC Gamma. Reconstructions of ancestor sequences support that most lineage-defining mutations of the Spike (S) protein, including those at the receptor-binding domain (RBD), accumulated at the first P.1 ancestor. In contrast, mutations outside the S protein were mostly fixed at subsequent steps. Our evolutionary analyses estimate that P.1-ancestral strains carrying RBD mutations of concern probably circulated cryptically in the Amazonas for several months before the emergence of the VOC Gamma. Unlike the VOC Gamma, the other P.1 sub-lineages displayed a much more restricted dissemination and accounted for a low fraction (<2 per cent) of SARS-CoV-2 infections in Brazil in 2021. The stepwise diversification of lineage P.1 through multiple inter-host transmissions is consistent with the hypothesis that partial immunity acquired from natural SARS-CoV-2 infections in heavily affected regions might have been a major driving force behind the natural selection of some VOCs. The lag time between the emergence of the P.1 ancestor and the expansion of the VOC Gamma and the divergent epidemic trajectories of P.1 sub-lineages support a complex interplay between the emergence of mutations of concern and viral spread in Brazil.

Genomic Evaluation of the Genus Coltivirus Indicates Genetic Diversity among Colorado Tick Fever Virus Strains and Demarcation of a New Species

The type species of the genus Coltivirus, Colorado tick fever virus (CTFV), was discovered in 1943 and is the most common tick-borne viral infection in the Western US. Despite its long history, very little is known about the molecular diversity of viruses classified within the species Colorado tick fever coltivirus. Previous studies have suggested genetic variants and potential serotypes of CTFV, but limited genetic sequence information is available for CTFV strains. To address this knowledge gap, we report herein the full-length genomes of five strains of CTFV, including Salmon River virus and California hare coltivirus (CTFV-Ca). The sequence from the full-length genome of Salmon River virus identified a high genetic identity to the CTFV prototype strain with >90% amino acid identity in all the segments except segment four, suggesting Salmon River virus is a strain of the species Colorado tick fever coltivirus. Additionally, analysis suggests that segment four has been associated with reassortment in at least one strain. The CTFV-Ca full-length genomic sequence was highly variable from the prototype CTFV in all the segments. The genome of CTFV-Ca was most similar to the Eyach virus, including similar segments six and seven. These data suggest that CTFV-Ca is not a strain of CTFV but a unique species. Additional sequence information of CTFV strains will improve the molecular surveillance tools and provide additional taxonomic resolution to this understudied virus.

Parallel power posterior analyses for fast computation of marginal likelihoods in phylogenetics

In Bayesian phylogenetic inference, marginal likelihoods can be estimated using several different methods, including the path-sampling or stepping-stone-sampling algorithms. Both algorithms are computationally demanding because they require a series of power posterior Markov chain Monte Carlo (MCMC) simulations. Here we introduce a general parallelization strategy that distributes the power posterior MCMC simulations and the likelihood computations over available CPUs. Our parallelization strategy can easily be applied to any statistical model despite our primary focus on molecular substitution models in this study. Using two phylogenetic example datasets, we demonstrate that the runtime of the marginal likelihood estimation can be reduced significantly even if only two CPUs are available (an average performance increase of 1.96x). The performance increase is nearly linear with the number of available CPUs. We record a performance increase of 13.3x for cluster nodes with 16 CPUs, representing a substantial reduction to the runtime of marginal likelihood estimations. Hence, our parallelization strategy enables the estimation of marginal likelihoods to complete in a feasible amount of time which previously needed days, weeks or even months. The methods described here are implemented in our open-source software RevBayes which is available from http://www.RevBayes.com.

Use of Slaughterhouses as Sentinel Points for Genomic Surveillance of Foot-and-Mouth Disease Virus in Southern Vietnam

The genetic diversity of foot-and-mouth disease virus (FMDV) poses a challenge to the successful control of the disease, and it is important to identify the emergence of different strains in endemic settings. The objective of this study was to evaluate the sampling of clinically healthy livestock at slaughterhouses as a strategy for genomic FMDV surveillance. Serum samples (n = 11,875) and oropharyngeal fluid (OPF) samples (n = 5045) were collected from clinically healthy cattle and buffalo on farms in eight provinces in southern and northern Vietnam (2015-2019) to characterize viral diversity. Outbreak sequences were collected between 2009 and 2019. In two slaughterhouses in southern Vietnam, 1200 serum and OPF samples were collected from clinically healthy cattle and buffalo (2017 to 2019) as a pilot study on the use of slaughterhouses as sentinel points in surveillance. FMDV VP1 sequences were analyzed using discriminant principal component analysis and time-scaled phylodynamic trees. Six of seven serotype-O and -A clusters circulating in southern Vietnam between 2017-2019 were detected at least once in slaughterhouses, sometimes pre-dating outbreak sequences associated with the same cluster by 4-6 months. Routine sampling at slaughterhouses may provide a timely and efficient strategy for genomic surveillance to identify circulating and emerging FMDV strains.

The Tien Shan vole (Microtus ilaeus; Rodentia: Cricetidae) as a new species in the Late Pleistocene of Europe

Grey voles (subgenus Microtus) represent a complex of at least seven closely related and partly cryptic species. The range of these species extends from the Atlantic to the Altai Mountains, but most of them occur east of the Black Sea. Using ancient DNA analyses of the Late Pleistocene specimens, we identified a new mtDNA lineage of grey voles in Europe. Phylogenetic analysis of mitochondrial DNA cytochrome b sequences from 23 voles from three caves, namely, Emine-Bair-Khosar (Crimea, Ukraine), Cave 16 (Bulgaria), and Bacho Kiro (Bulgaria), showed that 14 specimens form a previously unrecognized lineage, sister to the Tien Shan vole. The average sequence divergence of this lineage and the extant Tien Shan vole was 4.8%, which is similar to the divergence of grey vole forms, which are considered distinct species or being on the verge of speciation; M. arvalis and M. obscurus or M. mystacinus and M. rossiaemeridionalis. We estimated the time to the most recent common ancestor of the grey voles to be 0.66 Ma, which is over twice the recent estimates, while the divergence of the extant Tien Shan vole and the new lineage to be 0.29 Ma. Our discovery suggests that grey voles may have been more diversified in the past and that their ranges may have differed substantially from current ones. It also underlines the utility of ancient DNA to decipher the evolutionary history of voles.

Emergence and spread of SARS-CoV-2 lineage B.1.620 with variant of concern-like mutations and deletions

Distinct SARS-CoV-2 lineages, discovered through various genomic surveillance initiatives, have emerged during the pandemic following unprecedented reductions in worldwide human mobility. We here describe a SARS-CoV-2 lineage - designated B.1.620 - discovered in Lithuania and carrying many mutations and deletions in the spike protein shared with widespread variants of concern (VOCs), including E484K, S477N and deletions HV69Δ, Y144Δ, and LLA241/243Δ. As well as documenting the suite of mutations this lineage carries, we also describe its potential to be resistant to neutralising antibodies, accompanying travel histories for a subset of European cases, evidence of local B.1.620 transmission in Europe with a focus on Lithuania, and significance of its prevalence in Central Africa owing to recent genome sequencing efforts there. We make a case for its likely Central African origin using advanced phylogeographic inference methodologies incorporating recorded travel histories of infected travellers.

Genomic population structure associated with repeated escape of Salmonella enterica ATCC14028s from the laboratory into nature

Salmonella enterica serovar Typhimurium strain ATCC14028s is commercially available from multiple national type culture collections, and has been widely used since 1960 for quality control of growth media and experiments on fitness (“laboratory evolution”). ATCC14028s has been implicated in multiple cross-contaminations in the laboratory, and has also caused multiple laboratory infections and one known attempt at bioterrorism. According to hierarchical clustering of 3002 core gene sequences, ATCC14028s belongs to HierCC cluster HC20_373 in which most internal branch lengths are only one to three SNPs long. Many natural Typhimurium isolates from humans, domesticated animals and the environment also belong to HC20_373, and their core genomes are almost indistinguishable from those of laboratory strains. These natural isolates have infected humans in Ireland and Taiwan for decades, and are common in the British Isles as well as the Americas. The isolation history of some of the natural isolates confirms the conclusion that they do not represent recent contamination by the laboratory strain, and 10% carry plasmids or bacteriophages which have been acquired in nature by HGT from unrelated bacteria. We propose that ATCC14028s has repeatedly escaped from the laboratory environment into nature via laboratory accidents or infections, but the escaped micro-lineages have only a limited life span. As a result, there is a genetic gap separating HC20_373 from its closest natural relatives due to a divergence between them in the late 19^th century followed by repeated extinction events of escaped HC20_373.

Clades of closely related bacteria exist in nature. Individual isolates from such clades are often distinguishable by genomic sequencing because genomic sequence differences can be acquired over a few years due to neutral drift and natural selection. The evolution of laboratory strains is often largely frozen, physically due to storage conditions and genetically due to long periods of storage. Thus, laboratory strains can normally be readily distinguished from natural isolates because they show much less diversity. However, laboratory strain ATCC14028s shows modest levels of sequence diversity because it has been shipped around the world to multiple laboratories and is routinely used for analyses of laboratory evolution. Closely related natural isolates also exist, but their genetic diversity is not dramatically greater at the core genome level. Indeed, many scientists doubt that such isolates are natural, and interpret them as undetected contamination by the laboratory strain. We present data indicating that ATCC14028s has repeatedly escaped from the laboratory through inadvertent contamination of the environment, infection of technical staff and deliberate bioterrorism. The escapees survive in nature long enough that some acquire mobile genomic elements by horizontal gene transfer, but eventually they go extinct. As a result, even extensive global databases of natural isolates lack closely related isolates whose ancestors diverged from ATCC14028s within the last 100 years.

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.

Evolutionary dynamics of multidrug resistant Salmonella enterica serovar 4,[5],12:i:- in Australia

Salmonella enterica serovar 4,[5],12:i:- (Salmonella 4,[5],12:i:-) is a monophasic variant of Salmonella Typhimurium that has emerged as a global cause of multidrug resistant salmonellosis. We used Bayesian phylodynamics, genomic epidemiology, and phenotypic characterization to describe the emergence and evolution of Salmonella 4,[5],12:i:- in Australia. We show that the interruption of the genetic region surrounding the phase II flagellin, FljB, causing a monophasic phenotype, represents a stepwise evolutionary event through the accumulation of mobile resistance elements with minimal impairment to bacterial fitness. We identify three lineages with different population dynamics and discrete antimicrobial resistance profiles emerged, likely reflecting differential antimicrobial selection pressures. Two lineages are associated with travel to South-East Asia and the third lineage is endemic to Australia. Moreover antimicrobial-resistant Salmonella 4,[5],12:i- lineages efficiently infected and survived in host phagocytes and epithelial cells without eliciting significant cellular cytotoxicity, suggesting a suppression of host immune response that may facilitate the persistence of Salmonella 4,[5],12:i:-.

Regional effect on the molecular clock rate of protein evolution in Eutherian and Metatherian genomes

BACKGROUND

Different types of proteins diverge at vastly different rates. Moreover, the same type of protein has been observed to evolve with different rates in different phylogenetic lineages. In the present study we measured the rates of protein evolution in Eutheria (placental mammals) and Metatheria (marsupials) on a genome-wide basis and we propose that the gene position in the genome landscape has an important influence on the rate of protein divergence.

RESULTS

We analyzed a protein-encoding gene set (n = 15,727) common to 16 mammals (12 Eutheria and 4 Metatheria). Using sliding windows that averaged regional effects of protein divergence we constructed landscapes in which strong and lineage-specific regional effects were seen on the molecular clock rate of protein divergence. Within each lineage, the relatively high rates were preferentially found in subtelomeric chromosomal regions. Such regions were observed to contain important and well-studied loci for fetal growth, uterine function and the generation of diversity in the adaptive repertoire of immunoglobulins.

CONCLUSIONS

A genome landscape approach visualizes lineage-specific regional differences between Eutherian and Metatherian rates of protein evolution. This phenomenon of chromosomal position is a new element that explains at least part of the lineage-specific effects and differences between proteins on the molecular clock rates.

Untangling introductions and persistence in COVID-19 resurgence in Europe

After the first wave of SARS-CoV-2 infections in spring 2020, Europe experienced a resurgence of the virus starting in late summer 2020 that was deadlier and more difficult to contain1. Relaxed intervention measures and summer travel have been implicated as drivers of the second wave2. Here we build a phylogeographical model to evaluate how newly introduced lineages, as opposed to the rekindling of persistent lineages, contributed to the resurgence of COVID-19 in Europe. We inform this model using genomic, mobility and epidemiological data from 10 European countries and estimate that in many countries more than half of the lineages circulating in late summer resulted from new introductions since 15 June 2020. The success in onward transmission of newly introduced lineages was negatively associated with the local incidence of COVID-19 during this period. The pervasive spread of variants in summer 2020 highlights the threat of viral dissemination when restrictions are lifted, and this needs to be carefully considered in strategies to control the current spread of variants that are more transmissible and/or evade immunity. Our findings indicate that more effective and coordinated measures are required to contain the spread through cross-border travel even as vaccination is reducing disease burden.

Temporal phylogeny and molecular characterization of echovirus 30 associated with aseptic meningitis outbreaks in China

BACKGROUND

An outbreak of aseptic meningitis occurred from June to August 2016, in Inner Mongolia Autonomous Region, China.

METHODS

To determine its epidemiological characteristics, etiologic agent, and possible origin, specimens were collected for virus isolation and identification, followed by molecular epidemiological analysis.

RESULTS

A total of 363 patients were clinically diagnosed from June 1st to August 31st 2016, and most cases (63.1%, n = 229) were identified between June 22nd and July 17th, with children aged 6 to 12 years constituting the highest percentage (68.9%, n = 250). All viral isolates from this study belonged to genotype C of echovirus 30 (E30), which dominated transmission in China. To date, two E30 transmission lineages have been identified in China, of which Lineage 2 was predominant. We observed fluctuant progress of E30 genetic diversity, with Lineage 2 contributing to increased genetic diversity after 2002, whereas Lineage 1 was significant for the genetic diversity of E30 before 2002.

CONCLUSIONS

We identified the epidemiological and etiological causes of an aseptic meningitis outbreak in Inner Mongolia in 2016, and found that Lineage 2 played an important role in recent outbreaks. Moreover, we found that Gansu province could play an important role in E30 spread and might be a possible origin site. Furthermore, Fujian, Shandong, Taiwan, and Zhejiang provinces also demonstrated significant involvement in E30 evolution and persistence over time in China.

Bayesian Evaluation of Temporal Signal in Measurably Evolving Populations

Phylogenetic methods can use the sampling times of molecular sequence data to calibrate the molecular clock, enabling the estimation of evolutionary rates and timescales for rapidly evolving pathogens and data sets containing ancient DNA samples. A key aspect of such calibrations is whether a sufficient amount of molecular evolution has occurred over the sampling time window, that is, whether the data can be treated as having come from a measurably evolving population. Here, we investigate the performance of a fully Bayesian evaluation of temporal signal (BETS) in sequence data. The method involves comparing the fit to the data of two models: a model in which the data are accompanied by the actual (heterochronous) sampling times, and a model in which the samples are constrained to be contemporaneous (isochronous). We conducted simulations under a wide range of conditions to demonstrate that BETS accurately classifies data sets according to whether they contain temporal signal or not, even when there is substantial among-lineage rate variation. We explore the behavior of this classification in analyses of five empirical data sets: modern samples of A/H1N1 influenza virus, the bacterium Bordetella pertussis, coronaviruses from mammalian hosts, ancient DNA from Hepatitis B virus, and mitochondrial genomes of dog species. Our results indicate that BETS is an effective alternative to other tests of temporal signal. In particular, this method has the key advantage of allowing a coherent assessment of the entire model, including the molecular clock and tree prior which are essential aspects of Bayesian phylodynamic analyses.

Discovery of Novel Herpes Simplexviruses in Wild Gorillas, Bonobos, and Chimpanzees Supports Zoonotic Origin of HSV-2

Viruses closely related to human pathogens can reveal the origins of human infectious diseases. Human herpes simplexvirus type 1 (HSV-1) and type 2 (HSV-2) are hypothesized to have arisen via host-virus codivergence and cross-species transmission. We report the discovery of novel herpes simplexviruses during a large-scale screening of fecal samples from wild gorillas, bonobos, and chimpanzees. Phylogenetic analysis indicates that, contrary to expectation, simplexviruses from these African apes are all more closely related to HSV-2 than to HSV-1. Molecular clock-based hypothesis testing suggests the divergence between HSV-1 and the African great ape simplexviruses likely represents a codivergence event between humans and gorillas. The simplexviruses infecting African great apes subsequently experienced multiple cross-species transmission events over the past 3 My, the most recent of which occurred between humans and bonobos around 1 Ma. These findings revise our understanding of the origins of human herpes simplexviruses and suggest that HSV-2 is one of the earliest zoonotic pathogens.

Intrahost speciations and host switches played an important role in the evolution of herpesviruses

In times when herpesvirus genomic data were scarce, the cospeciation between these viruses and their hosts was considered to be common knowledge. However, as more herpesviral sequences were made available, tree reconciliation analyses started to reveal topological incongruences between host and viral phylogenies, indicating that other cophylogenetic events, such as intrahost speciation and host switching, likely played important roles along more than 200 million years of evolutionary history of these viruses. Tree reconciliations performed with undated phylogenies can identify topological differences, but offer insufficient information to reveal temporal incongruences between the divergence timing of host and viral species. In this study, we performed cophylogenetic analyses using time-resolved trees of herpesviruses and their hosts, based on careful molecular clock modelling. This approach enabled us to infer cophylogenetic events over time and also integrate information on host biogeography to better understand host-virus evolutionary history. Given the increasing amount of sequence data now available, mismatches between host and viral phylogenies have become more evident, and to account for such phylogenetic differences, host switches, intrahost speciations and losses were frequently found in all tree reconciliations. For all subfamilies in Herpesviridae, under all scenarios we explored, intrahost speciation and host switching were more frequent than cospeciation, which was shown to be a rare event, restricted to contexts where topological and temporal patterns of viral and host evolution were in strict agreement.

The phylogeographic history of tomato mosaic virus in Eurasia

Tomato mosaic virus (ToMV) is a tobamovirus affecting solanaceous crops worldwide. The process of its emergence, however, is poorly understood. Here, Bayesian phylogenetic framework was employed to reconstruct the phylogeography of ToMV in Eurasia. The results showed that the ToMV in Europe, Middle East and East Asia has been evolving at a rate of 4.05 × 10^-4 substitutions/site/year (95% credibility interval 2.43 × 10^-4 - 5.62 × 10^-4). Their most recent common ancestor (MRCA), most probably first appeared in Europe, was dated to around 1757 Common Era. The first introduction of ToMV into Middle East occurred in 1920s, with Europe as the source, while the first introduction of ToMV into East Asia occurred shortly afterwards, with Middle East as the source. From about 1950 onwards, inter-regional migrations of ToMV between Europe, Middle East and East Asia have been common. Overall, these data provide a glimpse into the phylogeographic history of ToMV in Eurasia.

A Novel Sub-Lineage of Chikungunya Virus East/Central/South African Genotype Indian Ocean Lineage Caused Sequential Outbreaks in Bangladesh and Thailand

In recent decades, chikungunya virus (CHIKV) has become geographically widespread. In 2004, the CHIKV East/Central/South African (ECSA) genotype moved from Africa to Indian ocean islands and India followed by a large epidemic in Southeast Asia. In 2013, the CHIKV Asian genotype drove an outbreak in the Americas. Since 2016, CHIKV has re-emerged in the Indian subcontinent and Southeast Asia. In the present study, CHIKVs were obtained from Bangladesh in 2017 and Thailand in 2019, and their nearly full genomes were sequenced. Phylogenetic analysis revealed that the recent CHIKVs were of Indian Ocean Lineage (IOL) of genotype ECSA, similar to the previous outbreak. However, these CHIKVs were all clustered into a new distinct sub-lineage apart from the past IOL CHIKVs, and they lacked an alanine-to-valine substitution at position 226 of the E1 envelope glycoprotein, which enhances CHIKV replication in Aedes albopictus. Instead, all the re-emerged CHIKVs possessed mutations of lysine-to-glutamic acid at position 211 of E1 and valine-to-alanine at position 264 of E2. Molecular clock analysis suggested that the new sub-lineage CHIKV was introduced to Bangladesh around late 2015 and Thailand in early 2017. These results suggest that re-emerged CHIKVs have acquired different adaptations than the previous CHIKVs.

Genomic and phylodynamic analysis of sapoviruses isolated in Henan Province, China

In this study, we determined the near-complete and partial genome sequences of ten SaV isolates. Phylogenetic analysis based on full-length VP1 and RdRp nucleotide sequences indicated that nine isolates were of GI.1 and one was GII.3. Evolutionary dynamics analysis indicated that GI.1 and GII.3 SaVs evolved at different rates, the latter evolving more rapidly. Cluster analysis indicated that distantly related GI.1 SaVs were more similar in their amino acid compositions than were GII.3 SaVs. The data provided in this study may facilitate studies on SaV genomic diversity and epidemiological patterns in China and worldwide.

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.