Bayesian Evaluation of Temporal Signal in Measurably Evolving Populations

Rivers and landscape ecology of a plant virus, Rice yellow mottle virus along the Niger Valley

To investigate the spread of Rice yellow mottle virus (RYMV) along the Niger River, regular sampling of virus isolates was conducted along 500 km of the Niger Valley in the Republic of Niger and was complemented by additional sampling in neighbouring countries in West Africa and Central Africa. The spread of RYMV into and within the Republic of Niger was inferred as a continuous process using a Bayesian statistical framework applied previously to reconstruct its dispersal history in West Africa, East Africa, and Madagascar. The spatial resolution along this section of the Niger River was the highest implemented for RYMV and possibly for any plant virus. We benefited from the results of early field surveys of the disease for the validation of the phylogeographic reconstruction and from the well-documented history of rice cultivation changes along the Niger River for their interpretation. As a prerequisite, the temporal signal of the RYMV data sets was revisited in the light of recent methodological advances. The role of the hydrographic network of the Niger Basin in RYMV spread was examined, and the link between virus population dynamics and the extent of irrigated rice was assessed. RYMV was introduced along the Niger River in the Republic of Niger in the early 1980s from areas to the southwest of the country where rice was increasingly grown. Viral spread was triggered by a major irrigation scheme made of a set of rice perimeters along the river valley. The subsequent spatial and temporal host continuity and the inoculum build-up allowed for a rapid spread of RYMV along the Niger River, upstream and downstream, over hundreds of kilometres, and led to the development of severe epidemics. There was no evidence of long-distance dissemination of the virus through natural water. Floating rice in the main meanders of the Middle Niger did not contribute to virus dispersal from West Africa to Central Africa. RYMV along the Niger River is an insightful example of how agricultural intensification favours pathogen emergence and spread.

The Recovery, Interpretation and Use of Ancient Pathogen Genomes

The ability to sequence genomes from ancient biological material has provided a rich source of information for evolutionary biology and engaged considerable public interest. Although most studies of ancient genomes have focused on vertebrates, particularly archaic humans, newer technologies allow the capture of microbial pathogens and microbiomes from ancient and historical human and non-human remains. This coming of age has been made possible by techniques that allow the preferential capture and amplification of discrete genomes from a background of predominantly host and environmental DNA. There are now near-complete ancient genome sequences for three pathogens of considerable historical interest — pre-modern bubonic plague (Yersinia pestis), smallpox (Variola virus) and cholera (Vibrio cholerae) — and for three equally important endemic human disease agents — Mycobacterium tuberculosis (tuberculosis), Mycobacterium leprae (leprosy) and Treponema pallidum pallidum (syphilis). Genomic data from these pathogens have extended earlier work by paleopathologists. There have been efforts to sequence the genomes of additional ancient pathogens, with the potential to broaden our understanding of the infectious disease burden common to past populations from the Bronze Age to the early 20^th century. In this review we describe the state-of-the-art of this rapidly developing field, highlight the contributions of ancient pathogen genomics to multidisciplinary endeavors and describe some of the limitations in resolving questions about the emergence and long-term evolution of pathogens.

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:-.

Using host genetics to infer the global spread and evolutionary history of HCV subtype 3a

Studies have shown that hepatitis C virus subtype 3a (HCV-3a) is likely to have been circulating in South Asia before its global spread. However, the time and route of this dissemination remain unclear. For the first time, we generated host and virus genome-wide data for more than 500 patients infected with HCV-3a from the UK, North America, Australia, and New Zealand. We used the host genomic data to infer the ancestry of the patients and used this information to investigate the epidemic history of HCV-3a. We observed that viruses from hosts of South Asian ancestry clustered together near the root of the tree, irrespective of the sampling country, and that they were more diverse than viruses from other host ancestries. We hypothesized that South Asian hosts are more likely to have been infected in South Asia and used the inferred host ancestries to distinguish between the location where the infection was acquired and where the sample was taken. Next, we inferred that three independent transmission events resulted in the spread of the virus from South Asia to the UK, North America, and Oceania. This initial spread happened during or soon after the end of World War II. This was subsequently followed by many independent transmissions between the UK, North America, and Oceania. Using both host and virus genomic information can be highly informative in studying the virus epidemic history, especially in the context of chronic infections where migration histories need to be accounted for.

Assessing the extent of community spread caused by mink-derived SARS-CoV-2 variants

SARS-CoV-2 has recently been found to have spread from humans to minks and then to have transmitted back to humans. However, it is unknown to what extent the human-to-human transmission caused by the variant has reached. Here, we used publicly available SARS-CoV-2 genomic sequences from both humans and minks collected in Denmark and the Netherlands, and combined phylogenetic analysis with Bayesian inference under an epidemiological model, to trace the possibility of person-to-person transmission. The results showed that at least 12.5% of all people being infected with dominated mink-derived SARS-CoV-2 variants in Denmark and the Netherlands were caused by human-to-human transmission, indicating that this “back-to-human” SARS-CoV-2 variant has already caused human-to-human transmission. Our study also indicated the need for monitoring this mink-derived and other animal source “back-to-human” SARS-CoV-2 in future and that prevention and control measures should be tailored to avoid large-scale community transmission caused by the virus jumping between animals and humans.

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SARS-CoV-2 transmission from human to mink is not lineage specific

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Mink-derived SARS-CoV-2 variants keep human-to-human transmission

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At least 12.5% of patients with mink-derived SARS-CoV-2 were caused by human-to-human transmission

Genomic epidemiology of tuberculosis in eastern Malaysia: insights for strengthening public health responses

Tuberculosis is a leading public health priority in eastern Malaysia. Knowledge of the genomic epidemiology of tuberculosis can help tailor public health interventions. Our aims were to determine tuberculosis genomic epidemiology and characterize resistance mutations in the ethnically diverse city of Kota Kinabalu, Sabah, located at the nexus of Malaysia, Indonesia, Philippines and Brunei. We used an archive of prospectively collected Mycobacterium tuberculosis samples paired with epidemiological data. We collected sputum and demographic data from consecutive consenting outpatients with pulmonary tuberculosis at the largest tuberculosis clinic from 2012 to 2014, and selected samples from tuberculosis inpatients from the tertiary referral centre during 2012-2014 and 2016-2017. Two hundred and eight M. tuberculosis sequences were available for analysis, representing 8 % of cases notified during the study periods. Whole-genome phylogenetic analysis demonstrated that most strains were lineage 1 (195/208, 93.8 %), with the remainder being lineages 2 (8/208, 3.8 %) or 4 (5/208, 2.4 %). Lineages or sub-lineages were not associated with patient ethnicity. The lineage 1 strains were diverse, with sub-lineage 1.2.1 being dominant (192, 98 %). Lineage 1.2.1.3 isolates were geographically most widely distributed. The greatest diversity occurred in a border town sub-district. The time to the most recent common ancestor for the three major lineage 1.2.1 clades was estimated to be the year 1966 (95 % HPD 1948-1976). An association was found between failure of culture conversion by week 8 of treatment and infection with lineage 2 (4/6, 67 %) compared with lineage 1 strains (4/83, 5 %) (P<0.001), supporting evidence of greater virulence of lineage 2 strains. Eleven potential transmission clusters (SNP difference ≤12) were identified; at least five included people living in different sub-districts. Some linked cases spanned the whole 4-year study period. One cluster involved a multidrug-resistant tuberculosis strain matching a drug-susceptible strain from 3 years earlier. Drug resistance mutations were uncommon, but revealed one phenotype-genotype mismatch in a genotypically multidrug-resistant isolate, and rare nonsense mutations within the katG gene in two isolates. Consistent with the regionally mobile population, M. tuberculosis strains in Kota Kinabalu were diverse, although several lineage 1 strains dominated and were locally well established. Transmission clusters - uncommonly identified, likely attributable to incomplete sampling - showed clustering occurring across the community, not confined to households or sub-districts. The findings indicate that public health priorities should include active case finding and early institution of tuberculosis management in mobile populations, while there is a need to upscale effective contact investigation beyond households to include other contacts within social networks.

Bayesian Phylogeographic Analysis Incorporating Predictors and Individual Travel Histories in BEAST

Advances in sequencing technologies have tremendously reduced the time and costs associated with sequence generation, making genomic data an important asset for routine public health practices. Within this context, phylogenetic and phylogeographic inference has become a popular method to study disease transmission. In a Bayesian context, these approaches have the benefit of accommodating phylogenetic uncertainty, and popular implementations provide the possibility to parameterize the transition rates between locations as a function of epidemiological and ecological data to reconstruct spatial spread while simultaneously identifying the main factors impacting the spatial spread dynamics. Recent developments enable researchers to make use of travel history data of infected individuals in the reconstruction of pathogen spread, offering increased inference accuracy and mitigating sampling bias. Here, we describe a detailed workflow to reconstruct the spatial spread of a pathogen through Bayesian phylogeographic analysis in discrete space using these novel approaches, implemented in BEAST. The individual protocols focus on how to incorporate molecular data, covariates of spread, and individual travel history data into the analysis. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Creating a SARS-CoV-2 MSA using sequences from GISAID Basic Protocol 2: Setting up a discrete trait phylogeographic reconstruction in BEAUti Basic Protocol 3: Phylogeographic reconstruction incorporating travel history information Basic Protocol 4: Visualizing ancestral spatial trajectories for specific taxa.

Assessing Uncertainty in the Rooting of the SARS-CoV-2 Phylogeny

The rooting of the SARS-CoV-2 phylogeny is important for understanding the origin and early spread of the virus. Previously published phylogenies have used different rootings that do not always provide consistent results. We investigate several different strategies for rooting the SARS-CoV-2 tree and provide measures of statistical uncertainty for all methods. We show that methods based on the molecular clock tend to place the root in the B clade, whereas methods based on outgroup rooting tend to place the root in the A clade. The results from the two approaches are statistically incompatible, possibly as a consequence of deviations from a molecular clock or excess back-mutations. We also show that none of the methods provide strong statistical support for the placement of the root in any particular edge of the tree. These results suggest that phylogenetic evidence alone is unlikely to identify the origin of the SARS-CoV-2 virus and we caution against strong inferences regarding the early spread of the virus based solely on such evidence.

Development of Phylodynamic Methods for Bacterial Pathogens

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

Molecular detection and genomic characterization of diverse hepaciviruses in African rodents

Hepatitis C virus (HCV; genus Hepacivirus) represents a major public health problem, infecting about three per cent of the human population. Because no animal reservoir carrying closely related hepaciviruses has been identified, the zoonotic origins of HCV still remain unresolved. Motivated by recent findings of divergent hepaciviruses in rodents and a plausible African origin of HCV genotypes, we have screened a large collection of small mammals samples from seven sub-Saharan African countries. Out of 4,303 samples screened, eighty were found positive for the presence of hepaciviruses in twenty-nine different host species. We, here, report fifty-six novel genomes that considerably increase the diversity of three divergent rodent hepacivirus lineages. Furthermore, we provide strong evidence for hepacivirus co-infections in rodents, which were exclusively found in four sampled species of brush-furred mice. We also detect evidence of recombination within specific host lineages. Our study expands the available hepacivirus genomic data and contributes insights into the relatively deep evolutionary history of these pathogens in rodents. Overall, our results emphasize the importance of rodents as a potential hepacivirus reservoir and as models for investigating HCV infection dynamics.

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.

Accommodating individual travel history and unsampled diversity in Bayesian phylogeographic inference of SARS-CoV-2

Spatiotemporal bias in genome sampling can severely confound discrete trait phylogeographic inference. This has impeded our ability to accurately track the spread of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, despite the availability of unprecedented numbers of SARS-CoV-2 genomes. Here, we present an approach to integrate individual travel history data in Bayesian phylogeographic inference and apply it to the early spread of SARS-CoV-2. We demonstrate that including travel history data yields i) more realistic hypotheses of virus spread and ii) higher posterior predictive accuracy compared to including only sampling location. We further explore methods to ameliorate the impact of sampling bias by augmenting the phylogeographic analysis with lineages from undersampled locations. Our reconstructions reinforce specific transmission hypotheses suggested by the inclusion of travel history data, but also suggest alternative routes of virus migration that are plausible within the epidemiological context but are not apparent with current sampling efforts.

Temporal signal and the phylodynamic threshold of SARS-CoV-2

The ongoing SARS-CoV-2 outbreak marks the first time that large amounts of genome sequence data have been generated and made publicly available in near real time. Early analyses of these data revealed low sequence variation, a finding that is consistent with a recently emerging outbreak, but which raises the question of whether such data are sufficiently informative for phylogenetic inferences of evolutionary rates and time scales. The phylodynamic threshold is a key concept that refers to the point in time at which sufficient molecular evolutionary change has accumulated in available genome samples to obtain robust phylodynamic estimates. For example, before the phylodynamic threshold is reached, genomic variation is so low that even large amounts of genome sequences may be insufficient to estimate the virus’s evolutionary rate and the time scale of an outbreak. We collected genome sequences of SARS-CoV-2 from public databases at eight different points in time and conducted a range of tests of temporal signal to determine if and when the phylodynamic threshold was reached, and the range of inferences that could be reliably drawn from these data. Our results indicate that by 2 February 2020, estimates of evolutionary rates and time scales had become possible. Analyses of subsequent data sets, that included between 47 and 122 genomes, converged at an evolutionary rate of about 1.1 × 10⁻³ subs/site/year and a time of origin of around late November 2019. Our study provides guidelines to assess the phylodynamic threshold and demonstrates that establishing this threshold constitutes a fundamental step for understanding the power and limitations of early data in outbreak genome surveillance.

Measles virus and rinderpest virus divergence dated to the sixth century BCE

Many infectious diseases are thought to have emerged in humans after the Neolithic revolution. Although it is broadly accepted that this also applies to measles, the exact date of emergence for this disease is controversial. We sequenced the genome of a 1912 measles virus and used selection-aware molecular clock modeling to determine the divergence date of measles virus and rinderpest virus. This divergence date represents the earliest possible date for the establishment of measles in human populations. Our analyses show that the measles virus potentially arose as early as the sixth century BCE, possibly coinciding with the rise of large cities.