A Bayesian inference framework to reconstruct transmission trees using epidemiological and genetic data

The accurate identification of the route of transmission taken by an infectious agent through a host population is critical to understanding its epidemiology and informing measures for its control. However, reconstruction of transmission routes during an epidemic is often an underdetermined problem: data about the location and timings of infections can be incomplete, inaccurate, and compatible with a large number of different transmission scenarios. For fast-evolving pathogens like RNA viruses, inference can be strengthened by using genetic data, nowadays easily and affordably generated. However, significant statistical challenges remain to be overcome in the full integration of these different data types if transmission trees are to be reliably estimated. We present here a framework leading to a bayesian inference scheme that combines genetic and epidemiological data, able to reconstruct most likely transmission patterns and infection dates. After testing our approach with simulated data, we apply the method to two UK epidemics of Foot-and-Mouth Disease Virus (FMDV): the 2007 outbreak, and a subset of the large 2001 epidemic. In the first case, we are able to confirm the role of a specific premise as the link between the two phases of the epidemics, while transmissions more densely clustered in space and time remain harder to resolve. When we consider data collected from the 2001 epidemic during a time of national emergency, our inference scheme robustly infers transmission chains, and uncovers the presence of undetected premises, thus providing a useful tool for epidemiological studies in real time. The generation of genetic data is becoming routine in epidemiological investigations, but the development of analytical tools maximizing the value of these data remains a priority. Our method, while applied here in the context of FMDV, is general and with slight modification can be used in any situation where both spatiotemporal and genetic data are available

Host-pathogen evolutionary signatures reveal dynamics and future invasions of vampire bat rabies

Anticipating how epidemics will spread across landscapes requires understanding host dispersal events that are notoriously difficult to measure. Here, we contrast host and virus genetic signatures to resolve the spatiotemporal dynamics underlying geographic expansions of vampire bat rabies virus (VBRV) in Peru. Phylogenetic analysis revealed recent viral spread between populations that, according to extreme geographic structure in maternally inherited host mitochondrial DNA, appeared completely isolated. In contrast, greater population connectivity in biparentally inherited nuclear microsatellites explained the historical limits of invasions, suggesting that dispersing male bats spread VBRV between genetically isolated female populations. Host nuclear DNA further indicated unanticipated gene flow through the Andes mountains connecting the VBRV-free Pacific coast to the VBRV-endemic Amazon rainforest. By combining Bayesian phylogeography with landscape resistance models, we projected invasion routes through northern Peru that were validated by real-time livestock rabies mortality data. The first outbreaks of VBRV on the Pacific coast of South America could occur by June 2020, which would have serious implications for agriculture, wildlife conservation, and human health. Our results show that combining host and pathogen genetic data can identify sex biases in pathogen spatial spread, which may be a widespread but underappreciated phenomenon, and demonstrate that genetic forecasting can aid preparedness for impending viral invasions

Joint genomic and proteomic analysis identifies meta-trait characteristics of virulent and non-virulent Staphylococcus aureus strains

Staphylococcus aureus is an opportunistic pathogen of humans and warm-blooded animals and presents a growing threat in terms of multi-drug resistance. Despite numerous studies, the basis of staphylococcal virulence and switching between commensal and pathogenic phenotypes is not fully understood. Using genomics, we show here that S. aureus strains exhibiting virulent (VIR) and non-virulent (NVIR) phenotypes in a chicken embryo infection model genetically fall into two separate groups, with the VIR group being much more cohesive than the NVIR group. Significantly, the genes encoding known staphylococcal virulence factors, such as clumping factors, are either found in different allelic variants in the genomes of NVIR strains (compared to VIR strains) or are inactive pseudogenes. Moreover, the pyruvate carboxylase and gamma-aminobutyrate permease genes, which were previously linked with virulence, are pseudogenized in NVIR strain ch22. Further, we use comprehensive proteomics tools to characterize strains that show opposing phenotypes in a chicken embryo virulence model. VIR strain CH21 had an elevated level of diapolycopene oxygenase involved in staphyloxanthin production (protection against free radicals) and expressed a higher level of immunoglobulin-binding protein Sbi on its surface compared to NVIR strain ch22. Furthermore, joint genomic and proteomic approaches linked the elevated production of superoxide dismutase and DNA-binding protein by NVIR strain ch22 with gene duplications

Poxviruses in bats … so what?

Poxviruses are important pathogens of man and numerous domestic and wild animal species. Cross species (including zoonotic) poxvirus infections can have drastic consequences for the recipient host. Bats are a diverse order of mammals known to carry lethal viral zoonoses such as Rabies, Hendra, Nipah, and SARS. Consequent targeted research is revealing bats to be infected with a rich diversity of novel viruses. Poxviruses were recently identified in bats and the settings in which they were found were dramatically different. Here, we review the natural history of poxviruses in bats and highlight the relationship of the viruses to each other and their context in the Poxviridae family. In addition to considering the zoonotic potential of these viruses, we reflect on the broader implications of these findings. Specifically, the potential to explore and exploit this newfound relationship to study coevolution and cross species transmission together with fundamental aspects of poxvirus host tropism as well as bat virology and immunology

Genome Sequence of the Chestnut Blight Fungus Cryphonectria parasitica EP155: A Fundamental Resource for an Archetypical Invasive Plant Pathogen.

Cryphonectria parasitica is the causal agent of chestnut blight, a fungal disease that almost entirely eliminated mature American chestnut from North America over a 50-year period. Here, we formally report the genome of C. parasitica EP155 using a Sanger shotgun sequencing approach. After finishing and integration with simple-sequence repeat markers, the assembly was 43.8 Mb in 26 scaffolds (L50 = 5; N50 = 4.0Mb). Eight chromosomes are predicted: five scaffolds have two telomeres and six scaffolds have one telomere sequence. In total, 11,609 gene models were predicted, of which 85% show similarities to other proteins. This genome resource has already increased the utility of a fundamental plant pathogen experimental system through new understanding of the fungal vegetative incompatibility system, with significant implications for enhancing mycovirus-based biological control