Search

Research has been conducted on the molecular epidemiology of Mycobacterium tuberculosis complex. The use of the PCR-based M. tuberculosis-typing method targeting the variable-number tandem repeats (VNTR) of the minesatellite-like mycobacterial interspersed repetitive units and the identification of the VNTR loci in M. tuberculosis H37Rv are described.

Understanding how emergent pathogens successfully establish themselves and persist in previously unaffected populations is a crucial problem in disease ecology, with important implications for disease management. In multi‐host pathogen systems this problem is particularly difficult, as the importance of each host species to transmission is often poorly characterised, and the disease epidemiology is complex. Opportunities to observe and analyse such emergent scenarios are few.Here, we exploit a unique dataset combining densely collected data on the epidemiological and evolutionary characteristics of an outbreak of Mycobacterium bovis (the causative agent of bovine tuberculosis, bTB) in a population of cattle and badgers in an area considered low risk for bTB, with no previous record of either persistent infection in cattle, or of any infection in wildlife. We analyse the outbreak dynamics using a combination of mathematical modelling, Bayesian evolutionary analyses and machine learning.Comparison to M. bovis whole‐genome sequences from Northern Ireland confirmed this to be a pathogen single introduction from the latter region, with evolutionary analysis supporting an introduction directly into the local cattle population 6 years prior to its first discovery in badgers.Once introduced, the evidence supports M. bovis epidemiological dynamics passing through two phases, the first dominated by cattle‐to‐cattle transmission before becoming established in the local badger population.Synthesis and applications. The Mycobacterium bovis emergent outbreak that was the object of this study was of considerable concern because of the geographical distance from previously known high‐risk areas. Initial decisions about the outbreak control were supported by the whole‐genome sequencing data. The further analyses described here were used to estimate the time of introduction (and therefore the likely magnitude of any hidden outbreak) and the rates of cross‐species transmission, and provided valuable confirmation that the extent and focus of the imposed controls were appropriate. Not only do these findings strengthen the call for genomic surveillance, but they also pave the path for future outbreaks control, providing insights for more rapid and decisive evidence‐based decision‐making. As the methods we used and developed are agnostic to the disease itself, they are also valuable for other slowly transmitting pathogens. [ABSTRACT FROM AUTHOR]

Multi-host pathogens are particularly difficult to control, especially when at least one of the hosts acts as a hidden reservoir. Deep sequencing of densely sampled pathogens has the potential to transform this understanding, but requires analytical approaches that jointly consider epidemiological and genetic data to best address this problem. While there has been considerable success in analyses of single species systems, the hidden reservoir problem is relatively under-studied. A well-known exemplar of this problem is bovine Tuberculosis, a disease found in British and Irish cattle caused by Mycobacterium bovis, where the Eurasian badger has long been believed to act as a reservoir but remains of poorly quantified importance except in very specific locations. As a result, the effort that should be directed at controlling disease in badgers is unclear. Here, we analyse densely collected epidemiological and genetic data from a cattle population but do not explicitly consider any data from badgers. We use a simulation modelling approach to show that, in our system, a model that exploits available cattle demographic and herd-to-herd movement data, but only considers the ability of a hidden reservoir to generate pathogen diversity, can be used to choose between different epidemiological scenarios. In our analysis, a model where the reservoir does not generate any diversity but contributes to new infections at a local farm scale are significantly preferred over models which generate diversity and/or spread disease at broader spatial scales. While we cannot directly attribute the role of the reservoir to badgers based on this analysis alone, the result supports the hypothesis that under current cattle control regimes, infected cattle alone cannot sustain M. bovis circulation. Given the observed close phylogenetic relationship for the bacteria taken from cattle and badgers sampled near to each other, the most parsimonious hypothesis is that the reservoir is the infected badger population. More broadly, our approach demonstrates that carefully constructed bespoke models can exploit the combination of genetic and epidemiological data to overcome issues of extreme data bias, and uncover important general characteristics of transmission in multi-host pathogen systems. Author summary: For single host pathogens, pathogen genetic data have been transformative for understanding the transmission and control of many diseases, particuarly rapidly evolving RNA viruses. However garnering similar insights where pathogens are multi-host is more challenging, particularly when the evolution of the pathogen is slower and pathogen sampling often heavily biased. This is the case for Mycobacterium bovis, the causative agent of bovine Tuberculosis (bTB) and for which the Eurasian badger plays an as yet poorly understood role in transmission and spread. Here we have developed a computational model that incorporates M. bovis genetic data from cattle only with a highly abstracted model of an unobserved reservoir. Our research shows that a model in which the reservoir does not contribute to pathogen diversity, but is a source of infection in spatially localised areas around each farm, better describes the patterns of outbreaks observed in a population-level sample of a single M. bovis genotype in Northern Ireland over a period of 15 years, compared to models in which either the reservoir has no role, disease spread is spatially extensive, or where they generate considerable diversity on their own. While this reservoir model is not explicitly a model of badgers, its characteristics are consistent with other data that would suggest a reservoir consisting of infected badgers that contribute substantially to cattle infection, but could not maintain disease on their own. [ABSTRACT FROM AUTHOR]

Abstract Background Animal identification is pivotal in governmental agricultural policy, enabling the management of subsidy payments, movement of livestock, test scheduling and control of disease. Advances in bovine genomics have made it possible to utilise inherent genetic variability to uniquely identify individual animals by DNA profiling, much as has been achieved with humans over the past 20 years. A DNA profiling test based on bi-allelic single nucleotide polymorphism (SNP) markers would offer considerable advantages over current short tandem repeat (STR) based industry standard tests, in that it would be easier to analyse and interpret. In this study, a panel of 51 genome-wide SNPs were genotyped across panels of semen DNA from 6 common breeds for the purposes of ascertaining allelic frequency. For SNPs on the same chromosome, the extent of linkage disequilbrium was determined from genotype data by Expectation Maximization (EM) algorithm. Minimum probabilities of unique identification were determined for each breed panel. The usefulness of this SNP panel was ascertained by comparison to the current bovine STR Stockmarks II assay. A statistically representative random sampling of bovine animals from across Northern Ireland was assembled for the purposes of determining the population allele frequency for these STR loci and subsequently, the minimal probability of unique identification they conferred in sampled bovine animals from Northern Ireland. Results 6 SNPs exhibiting a minor allele frequency of less than 0.2 in more than 3 of the breed panels were excluded. 2 Further SNPs were found to reside in coding areas of the cattle genome and were excluded from the final panel. The remaining 43 SNPs exhibited genotype frequencies which were in Hardy Weinberg Equilibrium. SNPs on the same chromosome were observed to have no significant linkage disequilibrium/allelic association. Minimal probabilities of uniquely identifying individual animals from each of the breeds were obtained and were observed to be superior to those conferred by the industry standard STR assay. Conclusions The 43 SNPs characterised herein may constitute a starting point for the development of a SNP based DNA identification test for European cattle.

Abstract Background The Direct Repeat locus of the Mycobacterium tuberculosis complex (MTC) is a member of the CRISPR (Clustered regularly interspaced short palindromic repeats) sequences family. Spoligotyping is the widely used PCR-based reverse-hybridization blotting technique that assays the genetic diversity of this locus and is useful both for clinical laboratory, molecular epidemiology, evolutionary and population genetics. It is easy, robust, cheap, and produces highly diverse portable numerical results, as the result of the combination of (1) Unique Events Polymorphism (UEP) (2) Insertion-Sequence-mediated genetic recombination. Genetic convergence, although rare, was also previously demonstrated. Three previous international spoligotype databases had partly revealed the global and local geographical structures of MTC bacilli populations, however, there was a need for the release of a new, more representative and extended, international spoligotyping database. Results The fourth international spoligotyping database, SpolDB4, describes 1939 shared-types (STs) representative of a total of 39,295 strains from 122 countries, which are tentatively classified into 62 clades/lineages using a mixed expert-based and bioinformatical approach. The SpolDB4 update adds 26 new potentially phylogeographically-specific MTC genotype families. It provides a clearer picture of the current MTC genomes diversity as well as on the relationships between the genetic attributes investigated (spoligotypes) and the infra-species classification and evolutionary history of the species. Indeed, an independent Naïve-Bayes mixture-model analysis has validated main of the previous supervised SpolDB3 classification results, confirming the usefulness of both supervised and unsupervised models as an approach to understand MTC population structure. Updated results on the epidemiological status of spoligotypes, as well as genetic prevalence maps on six main lineages are also shown. Our results suggests the existence of fine geographical genetic clines within MTC populations, that could mirror the passed and present Homo sapiens sapiens demographical and mycobacterial co-evolutionary history whose structure could be further reconstructed and modelled, thereby providing a large-scale conceptual framework of the global TB Epidemiologic Network. Conclusion Our results broaden the knowledge of the global phylogeography of the MTC complex. SpolDB4 should be a very useful tool to better define the identity of a given MTC clinical isolate, and to better analyze the links between its current spreading and previous evolutionary history. The building and mining of extended MTC polymorphic genetic databases is in progress.

Bovine tuberculosis (bTB), caused by Mycobacterium bovis, remains a persistent problem for cattle industries in endemic countries. The frequency, quality, and performance of tests, and the presence of wildlife reservoirs, have been identified as impediments to eradication. Recently, exposure to helminth infection (Fasciola hepatica) has been associated negatively with the disclosure of bTB. Here, for the first time, we assess impact of concurrent infections of Fasciola hepatica and the disclosure of bTB at the animal‐level using large surveillance datasets. We utilized a dataset of 138,566 animal records from an abattoir from Northern Ireland (2011–2013). The presence of F. hepatica infection was assessed from macroscopic tissue inspection at abattoir. Multivariable models were developed to assess co‐infection associations with bTB status based on: Single Intradermal Comparative Tuberculin Test (SICTT), lesion, bacteriological confirmation, including either all animals, or only skin‐test negative animals (lesions at routine slaughter; LRS; confirmed nonreactors at routine slaughter; cNRs) or positive (reactors) animals alone, respectively. The relationship between skin tuberculin reaction sizes and fluke status was also explored for a subset of animals with field recordings (n = 24,680). Controlling for known risk factors (e.g., climatic, herd, and individual level characteristics), we did not find significant associations between the SICTT (standard or severe interpretation), lesion, nor confirmation status of animals and their liver fluke status. The only exception was a negative association between liver fluke positivity, and LRS or cNRs, respectively; though effect‐sizes were small (e.g., LRS Odds‐Ratio: 0.87; 95% CI: 0.76–1.00). There was limited evidence of a relationship between tuberculin reaction sizes during SICTT testing and liver fluke infection status. These data do not support the contention that the detection of bTB using skin‐tests or reactor postmortem follow‐up may be compromised by co‐infection at a population level, but the relationship with lesion formation (pathogenesis) may indicate an impact for postmortem surveillance. [ABSTRACT FROM AUTHOR]