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      Combining genomics and epidemiology to analyse bi-directional transmission of Mycobacterium bovis in a multi-host system

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          Abstract

          Quantifying pathogen transmission in multi-host systems is difficult, as exemplified in bovine tuberculosis (bTB) systems, but is crucial for control. The agent of bTB, Mycobacterium bovis, persists in cattle populations worldwide, often where potential wildlife reservoirs exist. However, the relative contribution of different host species to bTB persistence is generally unknown. In Britain, the role of badgers in infection persistence in cattle is highly contentious, despite decades of research and control efforts. We applied Bayesian phylogenetic and machine-learning approaches to bacterial genome data to quantify the roles of badgers and cattle in M. bovis infection dynamics in the presence of data biases. Our results suggest that transmission occurs more frequently from badgers to cattle than vice versa (10.4x in the most likely model) and that within-species transmission occurs at higher rates than between-species transmission for both. If representative, our results suggest that control operations should target both cattle and badgers.

          eLife digest

          Disease-causing microbes that infect more than one type of animal can be difficult to control. This is especially true when they infect wildlife. For example, Mycobacterium bovis is a bacterium that causes tuberculosis in tens of thousands of cattle in Britain every year and also infects badgers and other wildlife. Controlling the infections in cattle is essential, as it helps prevent the bacteria from infecting humans, improves cattle welfare and reduces the substantial costs to the livestock industry.

          Analysing the relatedness of M. bovis genomes from infected cattle and badgers may help scientists work out how often badgers infect cattle and vice versa. Scientists have collected data and M. bovis samples from infected badgers in Woodchester Park, in England, for over three decades. Using these data and additional information about M. bovis infecting nearby cattle may help scientists learn how the bacteria spreads and how to stop it.

          Now, Crispell et al. show that complex patterns of contact between cattle and badgers likely drive the persistence of tuberculosis in cattle, also known as bovine tuberculosis. In three separate analyses, Crispell et al. compared the genomes of M. bovis found in cattle and badgers, the animals' locations, when they were infected, and whether they could have been in contact. The analyses found that M. bovis was likely to have been transmitted more frequently from badgers to cattle rather than from cattle to badgers. They also showed that transmission within each species happened more often than transmission between species.

          If these results are confirmed by other studies, they may help scientists develop better strategies for controlling tuberculosis in British cattle. In particular, controversial control strategies – such as badger culls – could be more targeted to better combat tuberculosis in cattle but have less of an impact on badgers. These insights might also aid control efforts in other countries where bovine tuberculosis is a problem and an important source of human tuberculosis.

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          Most cited references62

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          Identifying Reservoirs of Infection: A Conceptual and Practical Challenge

          (2002)
          Many infectious agents, especially those that cause emerging diseases, infect more than one host species. Managing reservoirs of multihost pathogens often plays a crucial role in effective disease control. However, reservoirs remain variously and loosely defined. We propose that reservoirs can only be understood with reference to defined target populations. Therefore, we define a reservoir as one or more epidemiologically connected populations or environments in which the pathogen can be permanently maintained and from which infection is transmitted to the defined target population. Existence of a reservoir is confirmed when infection within the target population cannot be sustained after all transmission between target and nontarget populations has been eliminated. When disease can be controlled solely by interventions within target populations, little knowledge of potentially complex reservoir infection dynamics is necessary for effective control. We discuss the practical value of different approaches that may be used to identify reservoirs in the field.
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            Using Time-Structured Data to Estimate Evolutionary Rates of Double-Stranded DNA Viruses

            Abstract Double-stranded (ds) DNA viruses are often described as evolving through long-term codivergent associations with their hosts, a pattern that is expected to be associated with low rates of nucleotide substitution. However, the hypothesis of codivergence between dsDNA viruses and their hosts has rarely been rigorously tested, even though the vast majority of nucleotide substitution rate estimates for dsDNA viruses are based upon this assumption. It is therefore important to estimate the evolutionary rates of dsDNA viruses independent of the assumption of host-virus codivergence. Here, we explore the use of temporally structured sequence data within a Bayesian framework to estimate the evolutionary rates for seven human dsDNA viruses, including variola virus (VARV) (the causative agent of smallpox) and herpes simplex virus-1. Our analyses reveal that although the VARV genome is likely to evolve at a rate of approximately 1 × 10−5 substitutions/site/year and hence approaching that of many RNA viruses, the evolutionary rates of many other dsDNA viruses remain problematic to estimate. Synthetic data sets were constructed to inform our interpretation of the substitution rates estimated for these dsDNA viruses and the analysis of these demonstrated that given a sequence data set of appropriate length and sampling depth, it is possible to use time-structured analyses to estimate the substitution rates of many dsDNA viruses independently from the assumption of host-virus codivergence. Finally, the discovery that some dsDNA viruses may evolve at rates approaching those of RNA viruses has important implications for our understanding of the long-term evolutionary history and emergence potential of this major group of viruses.
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              Transmission of multidrug-resistant Mycobacterium tuberculosis in Shanghai, China: a retrospective observational study using whole-genome sequencing and epidemiological investigation.

              Multidrug-resistance is a substantial threat to global elimination of tuberculosis. Understanding transmission patterns is crucial for control of the disease. We used a genomic and epidemiological approach to assess recent transmission of multidrug-resistant (MDR) tuberculosis and identify potential risk factors for transmission.
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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                17 December 2019
                2019
                : 8
                : e45833
                Affiliations
                [1 ]deptSchool of Veterinary Medicine, Veterinary Sciences Centre University College Dublin DublinIreland
                [2 ]deptNational Wildlife Management Centre Animal & Plant Health Agency (APHA) LondonUnited Kingdom
                [3 ]deptRoslin Institute University of Edinburgh EdinburghUnited Kingdom
                [4 ]European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI) CambridgeUnited Kingdom
                [5 ]deptInstitute of Biodiversity, Animal Health & Comparative Medicine, College of Medical, Veterinary & Life Sciences University of Glasgow GlasgowUnited Kingdom
                [6 ]Agri-Food & Biosciences Institute Northern Ireland (AFBNI) BelfastUnited Kingdom
                [7 ]Animal & Plant Health Agency (APHA) LondonUnited Kingdom
                [8 ]deptCentre for Bovine Tuberculosis, Institute of Biological, Environmental and Rural Sciences University of Aberystwyth AberystwythUnited Kingdom
                [9 ]Genomics Medicine Ireland DublinIreland
                [10 ]Quadram Institute Bioscience NorwichUnited Kingdom
                [11 ]deptBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health University of Oxford OxfordUnited Kingdom
                [12 ]deptRoyal (Dick) School of Veterinary Studies University of Edinburgh EdinburghUnited Kingdom
                Harvard TH Chan School of Public Health United States
                Imperial College London United Kingdom
                Harvard TH Chan School of Public Health United States
                Instituto de Investigación en Recursos Cinegéticos IREC Spain
                Author information
                https://orcid.org/0000-0002-0364-7112
                https://orcid.org/0000-0003-3958-8748
                http://orcid.org/0000-0003-3159-596X
                http://orcid.org/0000-0002-0940-3311
                http://orcid.org/0000-0002-1164-8000
                https://orcid.org/0000-0003-0919-6401
                Article
                45833
                10.7554/eLife.45833
                6917503
                31843054
                a9cb885e-0194-4bda-99e4-f50e4285bc1e
                © 2019, Crispell et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 06 February 2019
                : 15 October 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001602, Science Foundation Ireland;
                Award ID: 16/BBSRC/3390
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100004440, Wellcome Trust;
                Award ID: 714 101237/Z/13/Z
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BBS/E/D/20002173
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/L010569/1
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/L010569/2
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100004440, Wellcome Trust;
                Award ID: 081696/Z/06/Z
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/P010598/1
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Epidemiology and Global Health
                Microbiology and Infectious Disease
                Custom metadata
                Analyses combining genomic and epidemiological data of Mycobacterium bovis, which causes bovine tuberculosis, revealed evidence of transmission within and between cattle and badger populations.

                Life sciences
                mycobacterium bovis,whole genome sequencing,bovine tuberculosis,cattle,badger,other
                Life sciences
                mycobacterium bovis, whole genome sequencing, bovine tuberculosis, cattle, badger, other

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