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bioRxiv2016

Genomic epidemiology and global diversity of the emerging bacterial pathogen Elizabethkingia anophelis

Elizabethkingia anophelis is an emerging pathogen. Genomic analysis of strains from clinical, environmental or mosquito sources is needed to understand the epidemiological emergence of E. anophelis and to uncover genetic elements implicated in antimicrobial resistance, pathogenesis, or niche adaptation. Here, the genomic sequences of two nosocomial isolates that caused neonatal meningitis in Bangui, Central African Republic, were determined and compared with Elizabethkingia isolates from other world regions and sources. Average nucleotide identity firmly confirmed that E. anophelis, E. meningoseptica and E. miricola represent distinct genomic species and led to re-identification of several strains. Phylogenetic analysis of E. anophelis strains revealed several sublineages and demonstrated a single evolutionary origin of African clinical isolates, which carry unique antimicrobial resistance genes acquired by horizontal transfer. The Elizabethkingia genus and the species E. anophelis had pan-genomes comprising respectively 7,801 and 6,880 gene families, underlining their genomic heterogeneity. African isolates were capsulated and carried a distinctive capsular polysaccharide synthesis cluster. A core-genome multilocus sequence typing scheme applicable to all Elizabethkingia isolates was developed, made publicly available (http://bigsdb.web.pasteur.fr/elizabethkingia), and shown to provide useful insights into E. anophelis epidemiology. Furthermore, a clustered regularly interspaced short palindromic repeats (CRISPR) locus was uncovered in E. meningoseptica, E. miricola and in a few E. anophelis strains. CRISPR spacer variation was observed between the African isolates, illustrating the value of CRISPR for strain subtyping. This work demonstrates the dynamic evolution of E. anophelis genomes and provides innovative tools for Elizabethkingia identification, population biology and epidemiology.\n\nIMPORTANCEElizabethkingia anophelis is a recently recognized bacterial species involved in human infections and outbreaks in distinct world regions. Using whole-genome sequencing, we showed that the species comprises several sublineages, which differ markedly in their genomic features associated with antibiotic resistance and host-pathogen interactions. Further, we have devised high-resolution strain subtyping strategies and provide an open genomic sequence analysis tool, facilitating the investigation of outbreaks and tracking of strains across time and space. We illustrate the power of these tools by showing that two African healthcare-associated meningitis cases observed 5 years apart were caused by the same strain, providing evidence that E. anophelis can persist in the hospital environment.

Microbiology↗

bioRxiv2016

Microevolution of Bank Voles (Myodes glareolus) at Neutral and Immune Related Genes During Multiannual Dynamic Cycles: Consequences for Puumala hantavirus Epidemiology

Understanding how host dynamics, including variations of population size and dispersal, may affect the epidemiology of infectious diseases through ecological and evolutionary processes is an active research area. Here we focus on a bank vole (Myodes glareolus) metapopulation surveyed in Finland between 2005 and 2009. Bank vole is the reservoir of Puumala hantavirus (PUUV), the agent of nephropathia epidemica (NE, a mild form of hemorrhagic fever with renal symptom) in humans. M glareolus populations experience multiannual density fluctuations that may influence the level of genetic diversity maintained in bank voles, PUUV prevalence and NE occurrence. We examine bank vole metapopulation genetics at presumably neutral markers and immune-related genes involved in susceptibility to PUUV (Tnf-promoter, Mhc-Drb, Tlr4, Tlr7 and Mx2 gene) to investigate the links between population dynamics, microevolutionary processes and PUUV epidemiology. We show that genetic drift slightly and transiently affects neutral and adaptive genetic variability within the metapopulation. Gene flow seems to counterbalance its effects during the multiannual density fluctuations. The low abundance phase may therefore be too short to impact genetic variation in the host, and consequently viral genetic diversity. Environmental heterogeneity does not seem to affect vole gene flow, which might explain the absence of spatial structure previously detected in PUUV in this area. Besides, our results suggest the role of vole dispersal on PUUV circulation through sex-specific and density-dependent movements. We find little evidence of selection acting on immune-related genes within this metapopulation. Footprint of positive selection is detected at Tlr-4 gene in 2008 only. We observe marginally significant associations between Mhc-Drb haplotypes and PUUV serology, and between Mx2 genotype and PUUV genogroups. These results show that microevolutionary changes and PUUV epidemiology in this metapopulation are mainly driven by neutral processes, although the relative effects of neutral and adaptive forces could vary temporally with density fluctuations.

Evolutionary Biology↗

bioRxiv2016

Beta regression improves the detection of differential DNA methylation for epigenetic epidemiology

BackgroundDNA methylation is the most readily assayed epigenetic mark, possessing confirmed relationships with gene expression, imprinting, and chromatin accessibility.Given the increasingly widespread use of DNA methylation microarrays in population-scale epidemiological applications, we sought to determine which methods provided the greatest statistical power to reproducibly detect differences in DNA methylation across various conditions,using publicly available data sets on tissue type and aging.\n\nResultsBeta regression, as proposed originally by Ferrari and Cribari-Neto, yielded more validated hits in each of our comparisons than any other method under consideration, both in a regression setting and in comparisons to two-group tests such as the Wilcoxon-Mann-Whitney, Student t, and Welch t tests.In large cohorts of whole blood samples, we corrected for compositional differences and batch effects, and found that marginal likelihood ratio tests from beta regression models uniformly dominate popular alternatives based on linear models.The superior sensitivity and specificity exhibited by beta regression in epidemiologically relevant cohort sizes corresponded to approximately a 2% increase in sensitivity at the same specificity when compared to linear models fitted on raw beta values (proportion of signal intensity due to the methylated allele), M-values, or rankquantile normalized values.\n\nConclusionsInvestigators should consider beta regression to maximize statistical power in studies of DNA methylation using microarrays.At epidemiologically relevant sample sizes, with typical quality control procedures (compositional and batch effect correction), cross-cohort agreement uniformly favors beta regression over popular alternatives.

Bioinformatics↗

bioRxiv2017

Integrating Patient And Whole Genome Sequencing Data To Provide Insights Into The Epidemiology Of Seasonal Influenza A(H3N2) Viruses

Genetic surveillance of seasonal influenza is largely focused upon sequencing of the haemagglutinin gene. Consequently, our understanding of the contribution of the remaining seven gene segments to the evolution and epidemiological dynamics of seasonal influenza is relatively limited. The increased availability of next generation sequencing technologies allows rapid and economic whole genome sequencing (WGS). Here, 150 influenza A(H3N2) positive clinical specimens with linked epidemiological data, from the 2014/15 season in Scotland, were sequenced directly using both Sanger sequencing of the HA1 region and WGS using the Illumina MiSeq platform. Sequences generated by both methods were highly consistent and WGS provided on average >90% whole genome coverage. As reported in other European countries during 2014/15, all strains belonged to genetic group 3C, with subgroup 3C.2a predominating. Inter-subgroup reassortants were identified (9%), including three 3C.3 viruses descended from a single reassortment event, which had persisted in the population. Significant phylogenetic associations with cases of severe acute respiratory illness observed herein warrant further investigation. Severe cases were also more likely to be associated with reassortant viruses (odds ratio: 4.4 (1.3-15.5)) and occur later in the season. These results suggest that increased levels of WGS, linked to clinical and epidemiological data, could improve influenza surveillance.

microbiology↗

bioRxiv2020

Genomic Epidemiology with Mixed Samples

Genomic epidemiology is a tool for tracing transmission of pathogens based on whole-genome sequencing. We introduce the mGEMS pipeline for genomic epidemiology with plate sweeps representing mixed samples of a target pathogen, skipping the colony pick step. The pipeline includes the novel mGEMS read binner for probabilistic assignments of sequencing reads, and the scalable pseudoaligner Themisto. We demonstrate the effectiveness of our approach using closely related samples in a nosocomial setting, obtaining results that are comparable to those based on colony picks. Our results lend firm support to more widespread consideration of genomic epidemiology with mixed infection samples.

bioinformatics↗

bioRxiv2020

Epidemiology of Dengue viral infection in Nepal: 2006-2019

BackgroundDengue is one of the newest emerging diseases in Nepal with increasing burden and geographic spread over the last 14 years. The main objective of this study was to explore the spatio-temporal epidemiological patterns of Dengue since its first report (2006) till 2019 in Nepal. MethodsThis study is a retrospective analysis of dengue data available from the Epidemiological Disease Control Division (EDCD) of Government of Nepal. The data in this study cover the last 14 years (2006-2019) of reported dengue cases in Nepal. Epidemiological trend and spatio-temporal analyses were performed. Maps of reported case incidence were created using QGIS version 3.4. ResultsSince the first report of dengue in a foreigner in 2004, Nepal reported a total of 17,992 dengue cases in 68 districts of Nepal in 2019. The incidence was approximately five times higher in 2018 (Incidence Rate Ratio (IRR): 4.8; 95% CI: 1.5 - 15.3) and over 140 times higher in 2019 (IRR: 141.6; CI: 45.8 - 438.4). Population density was not a statistically significant predictor of case incidence. Mean elevation had a negative association with case incidence. A one standard deviation increase in elevation was associated with a 90% decrease in reported case incidence (IRR: 0.10; CI: 0.01 - 0.20). However, the association with mean elevation varied across the years. In comparison to 2016, incidence was greater at higher elevations in 2018 (IRR: 22.7; CI: 6.0 - 86.1) and 2019 (IRR: 9.6; CI: 2.6 - 36.1). ConclusionThere is a high risk of dengue outbreak in the Terai region with increasing spread towards the mid-mountains and beyond as seen over the last 14 years. Urgent measures are required to increase the availability of diagnostics and resources to mitigate future dengue epidemics. Findings from this study can inform the spatio-temporal distribution of dengue and can help in resource allocation and priority setting for future epidemic. Author summaryDengue in humans is caused by four different serotypes (DENV-1, DENV-2, DENV-3 & DENV-4). Globally it is the most pervasive vector borne diseases with increasing number of cases in recent years. Dengue is one of the youngest emerging diseases in Nepal with increasing cases and spread from the tropical lowland to the highland (hilly) regions. We conducted a spatio-temporal analysis of national data to consolidate the information using QGIS to measure the dengue incidence at district levels of Nepal. Spatio-temporal analysis exploring the incidence and distribution of dengue cases aids in identification of high-risk areas which can ultimately enable national dengue programme to mobilize and allocate resources for the control and treatment. This study shows, the persistent high risk of dengue outbreak in lowland Terai region with annual rise in the risk of spread towards the mid-mountains and beyond. Urgent measures are required to increase the diagnostics and resources to mitigate the epidemic burden of dengue in Terai and peripheral regions.

microbiology↗

bioRxiv2020

Initial insights into the genetic epidemiology of SARS-CoV-2 isolates from Kerala suggest local spread from limited introductions

Coronavirus disease 2019 (COVID-19) rapidly spread from a city in China to almost every country in the world, affecting millions of individuals. Genomic approaches have been extensively used to understand the evolution and epidemiology of SARS-CoV-2 across the world. Kerala is a unique state in India well connected with the rest of the world through a large number of expatriates, trade, and tourism. The first case of COVID-19 in India was reported in Kerala in January 2020, during the initial days of the pandemic. The rapid increase in the COVID-19 cases in the state of Kerala has necessitated the understanding of the genetic epidemiology of circulating virus, evolution, and mutations in SARS-CoV-2. We sequenced a total of 200 samples from patients at a tertiary hospital in Kerala using COVIDSeq protocol at a mean coverage of 7,755X. The analysis identified 166 unique high-quality variants encompassing 4 novel variants and 89 new variants identified for the first time in SARS-CoV-2 samples isolated from India. Phylogenetic and haplotype analysis revealed that the circulating population of the virus was dominated (94.6% of genomes) by three distinct introductions followed by local spread, apart from identifying polytomies suggesting recent outbreaks. The genomes formed a monophyletic distribution exclusively mapping to the A2a clade. Further analysis of the functional variants revealed two variants in the S gene of the virus reportedly associated with increased infectivity and 5 variants that mapped to five primer/probe binding sites that could potentially compromise the efficacy of RT-PCR detection. To the best of our knowledge, this is the first and most comprehensive report of genetic epidemiology and evolution of SARS-CoV-2 isolates from Kerala.

genomics↗

bioRxiv2020

MGDrivE 2: A simulation framework for gene drive systems incorporating seasonality and epidemiological dynamics

O_LIInterest in gene drive technology has continued to grow as promising new drive systems have been developed in the lab and discussions are moving towards implementing field trials. The prospect of field trials requires models that incorporate a significant degree of ecological detail, including parameters that change over time in response to environmental data such as temperature and rainfall, leading to seasonal patterns in mosquito population density. Epidemiological outcomes are also of growing importance, as: i) the suitability of a gene drive construct for release will depend on its expected impact on disease transmission, and ii) initial field trials are expected to have a measured entomological outcome and a modeled epidemiological outcome. C_LIO_LIWe present MGDrivE 2 (Mosquito Gene Drive Explorer 2): an extension of and development from the MGDrivE 1 simulation framework that investigates the population dynamics of a variety of gene drive architectures and their spread through spatially-explicit mosquito populations. Key strengths and improvements of the MGDrivE 2 framework are: i) the ability of parameters to vary with time and induce seasonal population dynamics, ii) an epidemiological module accommodating reciprocal pathogen transmission between humans and mosquitoes, and iii) an implementation framework based on stochastic Petri nets that enables efficient model formulation and flexible implementation. C_LIO_LIExample MGDrivE 2 simulations are presented to demonstrate the application of the framework to a CRISPR-based homing gene drive system intended to drive a disease-refractory gene into a population, incorporating time-varying temperature and rainfall data, and predict impact on human disease incidence and prevalence. Further documentation and use examples are provided in vignettes at the projects CRAN repository. C_LIO_LIMGDrivE 2 is an open-source R package freely available on CRAN. We intend the package to provide a flexible tool capable of modeling gene drive constructs as they move closer to field application and to infer their expected impact on disease transmission. C_LI

bioinformatics↗

bioRxiv2020

An Evaluation of Phylogenetic Workflows in Viral Molecular Epidemiology

The use of computational techniques to analyze viral sequence data and ultimately inform public health intervention has become increasingly common in the realm of epidemiology. These methods typically attempt to make epidemiological inferences based on multiple sequence alignments and phylogenies estimated from the raw sequence data. Like all estimation techniques, multiple sequence alignment and phylogenetic inference tools are error-prone, and the impacts of such imperfections on downstream epidemiological inferences are poorly understood. To address this, we executed multiple commonly-used workflows for conducting viral phylogenetic analyses on simulated viral sequence data modeling HIV, HCV, and Ebola, and we computed multiple methods of accuracy motivated by transmission clustering techniques. For multiple sequence alignment, MAFFT consistently outperformed MUSCLE and Clustal Omega in both accuracy and runtime. For phylogenetic inference, FastTree 2, IQ-TREE, RAxML-NG, and PhyML had similar topological accuracies, but branch lengths and pairwise distances were consistently most accurate in phylogenies inferred by RAxML-NG. However, FastTree 2 was orders of magnitude faster than the other tools, and when the other tools were used to optimize branch lengths along a fixed topology provided by FastTree 2 (i.e., no tree search), the resulting phylogenies had accuracies that were indistinguishable from their original counterparts, but with a fraction of the runtime. Our results indicate that an ideal workflow for viral phylogenetic inference is to (1) use MAFFT to perform MSA, (2) use FastTree 2 under the GTR model with discrete gamma-distributed site-rate heterogeneity to quickly obtain a reasonable tree topology, and (3) use RAxML-NG to optimize branch lengths along the fixed FastTree 2 topology.

bioinformatics↗

bioRxiv2021

Insights from Genomes and Genetic Epidemiology of SARS-CoV-2 isolates from the state of Andhra Pradesh

Coronavirus disease (COVID-19) emerged from a city in China and has now spread as a global pandemic affecting millions of individuals. The causative agent, SARS-CoV-2 is being extensively studied in terms of its genetic epidemiology using genomic approaches. Andhra Pradesh is one of the major states of India with the third-largest number of COVID-19 cases with limited understanding of its genetic epidemiology. In this study, we have sequenced 293 SARS-CoV-2 genome isolates from Andhra Pradesh with a mean coverage of 13,324X. We identified 564 high-quality SARS-CoV-2 variants, out of which 15 are novel. A total of 18 variants mapped to RT-PCR primer/probe sites, and 4 variants are known to be associated with an increase in infectivity. Phylogenetic analysis of the genomes revealed the circulating SARS-CoV-2 in Andhra Pradesh majorly clustered under the clade A2a (94%), while 6% fall under the I/A3i clade, a clade previously defined to be present in large numbers in India. To the best of our knowledge, this is the most comprehensive genetic epidemiological analysis performed for the state of Andhra Pradesh.

genomics↗

bioRxiv2021

Agri-environment nectar chemistry suppresses parasite social epidemiology in an important pollinator

Emergent infectious diseases are a principal driver of biodiversity loss globally. The population and range declines of a suite of North American bumblebees, a group of important pollinators, have been linked to emergent infection with the microsporidian Nosema bombi. Previous work has shown that phytochemicals in pollen and nectar can negatively impact parasites in individual bumblebees, but how this relates to social epidemiology and by extension whether plants can be effectively used as disease management strategies remains unexplored. Here we show that caffeine, identified in the nectar of Sainfoin, a constituent of agri-environment schemes, significantly reduced N. bombi infection intensity in individual bumblebees and, for the first time, that such effects impact social epidemiology, with colonies reared from wild caught queens having lower prevalence and intensity of infection. Furthermore, infection prevalence was lower in foraging bumblebees from these colonies, suggesting a likely reduction in population-level transmission. Our results demonstrate that phytochemicals can impact pollinator disease epidemiology and that planting strategies, which increase floral abundance to support biodiversity could be co-opted as disease management strategies.

ecology↗

bioRxiv2021

Frequent intergenotypic recombination between the non-structural and structural genes is a major driver of epidemiological fitness in caliciviruses

The diversity of lagoviruses (Caliciviridae) in Australia has increased considerably. By the end of 2017, five variants from three viral genotypes were present in populations of Australian rabbits, while prior to 2014 only two variants were known. To understand the interactions between these lagovirus variants we monitored their geographical distribution and relative incidence over time through a landscape-scale competition study, and from this, revealed potential drivers of epidemiological fitness. Within three years of the arrival of GI.1bP-GI.2 (RHDV2) into Australia, we observed the emergence of two novel recombinant lagovirus variants, GI.4eP-GI.2 (4e-recombinant) in New South Wales and GI.4cP-GI.2 (4c-recombinant) in Victoria. Although both novel recombinants contain the non-structural genes from benign, rabbit-specific, enterotropic viruses, these variants were recovered from the livers of both rabbits and hares that had died acutely. This suggests that determinants of host and tissue tropism for lagoviruses are associated with the structural genes, and that tropism is intricately connected with pathogenicity. Phylogenetic analyses demonstrated that the 4c-recombinant emerged independently on multiple occasions, with five distinct lineages observed. Both new recombinant variants replaced the previous dominant parental RHDV2 in their respective geographical areas, despite sharing an identical or near-identical (i.e., single amino acid change) major capsid protein with the parental virus. This suggests that epidemiological fitness of these recombinants was not driven by antigenic variation in the capsid, implicating the non-structural genes as key drivers of epidemiological fitness. Molecular clock estimates place the GI4.e recombination event in early to mid-2015, while the five GI.4c recombination events occurred from late 2015 through to early 2017. The emergence of at least six viable recombinant variants within a two-year period highlights an unprecedented frequency of these events, detectable only due to intensive surveillance, and demonstrates the importance of recombination in lagovirus evolution.

microbiology↗

bioRxiv2021

Optimal immune specificity at the intersection of host life history and parasite epidemiology

Epidemiology and life history are commonly hypothesized to influence host immune strategy, and the pairwise relationships between immune strategy and each factor have been extensively investigated. But the interaction of these two is rarely considered, despite evidence that this interaction might produce emergent effects on optimal immune strategy. Here we investigate the confluence of epidemiology and life history as it affects immune strategy through a demographically-framed model of sensitivity and specificity in parasite recognition and response. We find that variation in several different life history traits associated with both reproduction and longevity alters optimal immune strategies - but the direction and magnitude of these effects depends on how epidemiological risks vary across life. Drawing on published life history data, we also find that our predictions apply across chordate taxa. Our results shed light on the complex interactions shaping immune strategy and may prove valuable in interpreting empirical results in ecoimmunology.

ecology↗

bioRxiv2021

Genomic epidemiology of Mycobacterium bovis infection in sympatric badger and cattle populations in Northern Ireland.

BackgroundBovine tuberculosis (bTB) is a costly, epidemiologically complex, multi-host, endemic disease. Pathogen whole genome sequencing can improve the resolution of epidemiological tracing. We genome sequenced an exceptional data set of 619 Mycobacterium bovis isolates from badgers and cattle in a 100km2 bTB hotspot. Historical molecular subtyping data permitted the targeting of an endemic pathogen lineage, whose long-term persistence provided an opportunity to study genome epidemiology in detail. To assess whether badger population genetic structure was associated with the spatial distribution of pathogen genetic diversity, we microsatellite genotyped hair samples from 769 badgers trapped in this area. ResultsEight lineages of M. bovis were circulating in the study area, seven of which were likely non-endemic, and imported by animal movement. The endemic lineage exhibited low genetic diversity with an average inter-isolate genetic distance of 7.6 SNPs (s.d. {+/-} 4.0), consistent with contemporary transmission. Bayesian phylogenetic methods determined an evolutionary rate of 0.30 substitutions per genome per year for this lineage, estimating its emergence 40-50 years before present, while Bayesian Skyline analysis identified significant population expansion of the endemic lineage in the 1990s and again in 2011-2012. The phylogeny revealed distinct sub-lineages, all of which contained isolates from both cattle and badger hosts, indicative of the sharing of closely related strains and inter-species transmission. However, the presence of significant badger population genetic structure was not associated with the spatial distribution of M. bovis genetic diversity. ConclusionsOur data provided unparalleled detail on the evolutionary history of an endemic M. bovis lineage. Findings are consistent with ongoing interspecies transmission in the study area but suggest that badger intra-species transmission may not be a major driver of persistence in this area. In addition, the data collected permitted the tracking of incursions of novel pathogen lineages into the study area and means to determine if they were involved in disease transmission.

evolutionary biology↗

bioRxiv2021

Epidemiological dynamics of viral infection in a marine pico-eukaryote

Ostreococcus tauri is a ubiquitous marine pico-eukaryote that is susceptible to lysis upon infection by its species specific Ostreococcus tauri viruses (OtVs). In natural populations of O. tauri, costs of resistance are usually invoked to explain the persistence or reappearance of susceptible individuals in resistant populations. Given the low costs of resistance measured in laboratory experiments with the O. tauri/OtV system to date, the question remains of why susceptible individuals persist in the wild at all. Epidemiological models of host and pathogen population dynamics are one useful approach to understand the conditions that can allow the coexistence of susceptible and resistant hosts. We used a SIR (Susceptible-Infected-Resistant) model to investigate epidemiological dynamics under different laboratory culturing regimes that are commonly used in the O.tauri/OtV system. When taking into account serial transfer (i.e. batchcycle lengths) and dilution rates as well as different resistance costs, our model predicts that no susceptible cells should be detected under any of the simulated conditions - this is consistent with laboratory findings. We thus considered an alternative model that is not used in laboratory experiments, but which incorporates one key process in natural populations: host populations are periodically re-seeded with new infective viruses. In this model, susceptible individuals re-occurred in the population, despite low costs of resistance. This suggests that periodic attack by new viruses, rather than (or in addition to) costs of resistance, may explain the high proportion of susceptible hosts in natural populations, and underlie the discrepancy between laboratory studies and observations of fresh isolates. ImportanceIn natural samples of Ostreococcus sp. and its associated viruses, susceptible hosts are common. However, in laboratory experiments, fully resistant host populations readily and irreversibly evolve. Laboratory experiments are powerful methods for studying process because they offer a stripped-down simplification of a complex system, but this simplification may be an oversimplification for some questions. For example, laboratory and field systems of marine microbes and their viruses differ in population sizes and dynamics, mixing or migration rates, and species diversity, all of which can dramatically alter process outcomes. We demonstrate the utility of using epidemiological models to explore experimental design and to understand mechanisms underlying host-virus population dynamics. We highlight that such models can be used to form strong, testable hypotheses about which key elements of natural systems need to be included in laboratory systems to make them simplified, rather than oversimplified, versions of the processes we use them to study.

microbiology↗

bioRxiv2021

Molecular epidemiology of peste des petits ruminants virus emergence in critically endangered Mongolian saiga antelope and other wild ungulates

Peste des petits ruminants virus (PPRV) causes disease in domestic and wild ungulates, is the target of a global eradication programme and threatens biodiversity. Understanding the epidemiology and evolution of PPRV in wildlife is important, but hampered by the paucity of wildlife-origin PPRV genomes. In this study, full PPRV genomes were generated from three Mongolian saiga antelope, one Siberian ibex and one goitered gazelle from the 2016-2017 PPRV outbreak. Phylogenetic analysis showed that for Mongolian and Chinese PPRV since 2013, the wildlife and livestock-origin genomes were closely related and interspersed. There was strong phylogenetic support for a monophyletic group of PPRV from Mongolian wildlife and livestock, belonging to clade of lineage IV PPRV from livestock and wildlife from China since 2013. Discrete diffusion analysis found strong support for PPRV spread into Mongolia from China and phylogeographic analysis indicated Xinjiang Province as the most likely origin, although genomic surveillance for PPRV is poor and lack of sampling from other regions could bias this result. Times of most recent common ancestor (TMRCA) were June 2015 (95% HPD: August 2014 - March 2016) for all Mongolian PPRV genomes and May 2016 (95% HPD: October 2015 - October 2016) for Mongolian wildlife-origin PPRV. This suggests that PPRV was circulating undetected in Mongolia for at least six months before the first reported outbreak in August 2016, and that wildlife were likely infected before livestock vaccination began in October 2016. Finally, genetic variation and positively-selected sites were identified that might be related to PPRV emergence in Mongolian wildlife. This study is the first to sequence multiple PPRV genomes from a wildlife outbreak, across several host species. Additional full PPRV genomes and associated metadata from the livestock-wildlife interface are needed to enhance the power of molecular epidemiology, support PPRV eradication and safeguard the health of the whole ungulate community. Author SummaryRecent mass mortality of critically endangered Mongolian saiga antelope due to peste des petits ruminants virus (PPRV) has dramatically highlighted the threat this viral disease represents for biodiversity. The genome of viruses such as PPRV evolve fast, so virus genetic data gathered from infected animals can be used to trace disease spread between livestock and wildlife, and to determine if the virus is adapting to infect wildlife more efficiently. Here we obtained PPRV virus genomes from Mongolian wildlife and compared them with other published PPRV genomes. Using a molecular clock, we estimated that the disease was circulating in Mongolia well before it was first reported. Genetic analyses support the hypothesis of virus spread from livestock to wildlife, with genetic changes potentially helping infection in Asian wild ungulates. However, more PPR virus genomes and epidemiology data are needed from disease outbreaks in areas shared between livestock and wildlife to confirm these results and take efficient actions to safeguard the health of the whole ungulate community.

microbiology↗

bioRxiv2022

Genomics epidemiology analysis reveals hidden signatures of drug resistance in Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) causes the majority of reported cases of human tuberculosis (TB), one of the deadliest infectious diseases worldwide. New diagnostic tools and approaches to detect drug-resistance must be introduced by 2025 to achieve the End-TB Strategy goals set for 2030 by the WHO. Genomic epidemiology of TB has allowed the expansion of catalogs listing genetic signatures of Mtb drug-resistance. However, very few Mtb strains from Latin America have participate in previous genomic epidemiologic efforts. Here we present the first functional genomic epidemiology study of drug-resistant Mtb strains in Mexico, incorporating the genomic characterization of 133 genomes, including 53 newly sequenced isolates, to provide a comprehensive phylogeographic analysis of drug resistant Mtb in Mexico. The study evidences the prevalence of Euro-American Lineage L4 (96.2%), featuring a uniform distribution of the sublineages X-type (33.08%), LAM (22.56%), and Haarlem (21.05%). Our results demonstrate low levels of agreement with traditional drug sensitivity tests (DST), raising concerns for drug-resistant isolates lacking any previously reported genetic signatures of resistance. Finally, we propose a novel functional networking tool (FuN-TB) to explore metabolic and cellular signatures of drug resistance. Applying functional genomics approaches to Latin American Mtb genomes will provide new drug-resistance screening targets that can contribute to bed side decision-making and advise local public policy. Abstract importanceWe presented the first phylogeographic analysis of Mycobacterium tuberculosis (Mtb) of Mexico. Our analysis integrates 133 genome sequences and is focused on the identification of genetic signatures associated to drug-resistance. The results show the geographic distribution of sublineages and drug-resistance phenotypic classes. Additionally, we propose a novel functional networking tool (FuN-TB) to explore metabolic and cellular signatures of drug resistance associated. We show for the first time that Mtb isolates from Mexico encode for region-specific genetic signarures of antimicrobial resistance. Applying functional genomics approaches to Latin American Mtb genomes will provide new drug-resistance screening targets that can contribute to bed side decision-making and advise local public policy.

genomics↗

bioRxiv2022

Genomic epidemiology and multilevel genome typing of Australian Salmonella enterica serovar Enteritidis

Salmonella enterica serovar Enteritidis is one of the leading causes of salmonellosis in Australia. However, the majority of S. Enteritidis cases in Australia are travel-related with a small proportion being locally acquired. This study aimed to characterise the genomic features of Australian S. Enteritidis and compare them with international strains using multilevel genome typing (MGT). A total of 568 S. Enteritidis isolates from two Australian states across two consecutive years were analysed using the S. Enteritidis MGT scheme and database (MGTdb) - which contained 40,390 publicly available genomes from 99 countries. The Australian S. Enteritidis strains were divided into three phylogenetic clades (A, B and C). Clades A and C represented 16.4% and 3.5% of the total isolates, respectively, and were of local origin. Clade B accounted for 80.1% of the isolates which belonged to seven previously defined lineages but was dominated by the global epidemic lineage (MGT4-CC1). At MGT5 level, three out of five top sequence types (STs) in Australia were also top STs in Asia, suggesting that a fair proportion of Australian S. Enteritidis cases may be epidemiologically linked with Asian strains. In 2018, a large egg-associated local outbreak was caused by a recently defined clade B lineage prevalent in Europe and was closely related, but not directly linked, to three isolates from Europe. Additionally, antimicrobial-resistance genes were only found in Australian clade B isolates, with a predicted multidrug resistance (MDR) rate of 11.7%. Over half (54.8%) of the MDR isolates belonged to 10 MDR-associated MGT-STs, which were also frequent in Asian S. Enteritidis. IncX1 plasmids were frequently present in the Australian MDR isolates. Overall, this study investigated the genomic epidemiology of S. Enteritidis in Australia, including the first large local outbreak, using MGT. The open MGT platform enables a standardised and sharable nomenclature that can be effectively applied to public health for unified surveillance of S. Enteritidis nationally and globally. ImportanceSalmonella enterica serovar Enteritidis is a leading cause of foodborne infections. We previously developed a genomic typing database - MGTdb for S. Enteritidis to facilitate global surveillance of this pathogen. In this study we examined the genomic features of Australian S. Enteritidis using the MGTdb and found that Australian S. Enteritidis is mainly epidemiologically linked with Asian strains (especially strains carrying antimicrobial resistance genes) followed by European strains. The first large-scale egg-associated local outbreak in Australia was caused by a recently defined lineage prevalent in Europe, and three European isolates in the MGTdb were closely related but not directly linked to this outbreak. In summary, the S. Enteritidis MGTdb open platform is shown to be a potential powerful tool for national and global public health surveillance of this pathogen.

genomics↗