Dataset Information

An African origin for Mycobacterium bovis.

ABSTRACT: Background and objectives:Mycobacterium bovis and Mycobacterium caprae are two of the most important agents of tuberculosis in livestock and the most important causes of zoonotic tuberculosis in humans. However, little is known about the global population structure, phylogeography and evolutionary history of these pathogens. Methodology:We compiled a global collection of 3364 whole-genome sequences from M.bovis and M.caprae originating from 35 countries and inferred their phylogenetic relationships, geographic origins and age. Results:Our results resolved the phylogenetic relationship among the four previously defined clonal complexes of M.bovis, and another eight newly described here. Our phylogeographic analysis showed that M.bovis likely originated in East Africa. While some groups remained restricted to East and West Africa, others have subsequently dispersed to different parts of the world. Conclusions and implications:Our results allow a better understanding of the global population structure of M.bovis and its evolutionary history. This knowledge can be used to define better molecular markers for epidemiological investigations of M.bovis in settings where whole-genome sequencing cannot easily be implemented. Lay summary:During the last few years, analyses of large globally representative collections of whole-genome sequences (WGS) from the human-adapted Mycobacterium tuberculosis complex (MTBC) lineages have enhanced our understanding of the global population structure, phylogeography and evolutionary history of these pathogens. In contrast, little corresponding data exists for M. bovis, the most important agent of tuberculosis in livestock. Using whole-genome sequences of globally distributed M. bovis isolates, we inferred the genetic relationships among different M. bovis genotypes distributed around the world. The most likely origin of M. bovis is East Africa according to our inferences. While some M. bovis groups remained restricted to East and West Africa, others have subsequently dispersed to different parts of the world driven by cattle movements.

SUBMITTER: Loiseau C

PROVIDER: S-EPMC7081938 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

An African origin for <i>Mycobacterium bovis</i>.

Loiseau Chloé C Menardo Fabrizio F Aseffa Abraham A Hailu Elena E Gumi Balako B Ameni Gobena G Berg Stefan S Rigouts Leen L Robbe-Austerman Suelee S Zinsstag Jakob J Gagneux Sebastien S Brites Daniela D

Evolution, medicine, and public health 20200131 1

<h4>Background and objectives</h4><i>Mycobacterium bovis</i> and <i>Mycobacterium caprae</i> are two of the most important agents of tuberculosis in livestock and the most important causes of zoonotic tuberculosis in humans. However, little is known about the global population structure, phylogeography and evolutionary history of these pathogens.<h4>Methodology</h4>We compiled a global collection of 3364 whole-genome sequences from <i>M.bovis</i> and <i>M.caprae</i> originating from 35 countries ...[more]

PMID: 32211193

Similar Datasets

Project description:Animal tuberculosis (TB), caused by Mycobacterium bovis, is maintained in Portugal in a multi-host system, with cattle, red deer and wild boar, playing a central role. However, the ecological processes driving transmission are not understood. The main aim of this study was thus to contribute to the reconstruction of the spatiotemporal history of animal TB and to refine knowledge on M. bovis population structure in order to inform novel intervention strategies. A collection of 948 M. bovis isolates obtained during long-term surveillance (2002-2016, 15 years) of cattle (n = 384), red deer (n = 303) and wild boar (n = 261), from the main TB hotspot areas, was characterized by spoligotyping and 8 to 12-loci MIRU-VNTR. Spoligotyping identified 64 profiles and MIRU-VNTR distinguished 2 to 36 subtypes within each spoligotype, enabling differentiation of mixed or clonal populations. Common genotypic profiles within and among livestock and wildlife in the same spatiotemporal context highlighted epidemiological links across hosts and regions, as for example the SB0119-M205 genotype shared by cattle in Beja district or SB0121-M34 shared by the three hosts in Castelo Branco and Beja districts. These genomic data, together with metadata, were integrated in a Bayesian inference framework, identifying five ancestral M. bovis populations. The phylogeographic segregation of M. bovis in specific areas of Portugal where the disease persists locally is postulated. Concurrently, robust statistics indicates an association of the most probable ancient population with cattle and Beja, providing a clue on the origin of animal TB epidemics. This relationship was further confirmed through a multinomial probability model that assessed the influence of host species on spatiotemporal clustering. Two significant clusters were identified, one that persisted between 2004 and 2010, in Beja district, with Barrancos county at the centre, overlapping the central TB core area of the Iberian Peninsula, and highlighting a significant higher risk associated to cattle. The second cluster was predominant in the 2012-2016 period, holding the county Rosmaninhal at the centre, in Castelo Branco district, for which wild boar contributed the most in relative risk. These results provide novel quantitative insights beyond empirical perceptions, that may inform adaptive TB control choices in different regions.

Project description:Mycobacterium bovis causes bovine tuberculosis and is the main organism responsible for zoonotic tuberculosis in humans. We performed the sequencing, assembly and annotation of a Brazilian strain of M. bovis named SP38, and performed comparative genomics of M. bovis genomes deposited in GenBank. M. bovis SP38 has a traditional tuberculous mycobacterium genome of 4,347,648 bp, with 65.5% GC, and 4,216 genes. The majority of CDSs (2,805, 69.3%) have predictive function, while 1,206 (30.07%) are hypothetical. For comparative analysis, 31 M. bovis, 32 M. bovis BCG, and 23 Mycobacterium tuberculosis genomes available in GenBank were selected. M. bovis RDs (regions of difference) and Clonal Complexes (CC) were identified in silico. Genome dynamics of bacterial groups were analyzed by gene orthology and polymorphic sites identification. M. bovis polymorphic sites were used to construct a phylogenetic tree. Our RD analyses resulted in the exclusion of three genomes, mistakenly annotated as virulent M. bovis. M. bovis SP38 along with strain 35 represent the first report of CC European 2 in Brazil, whereas two other M. bovis strains failed to be classified within current CC. Results of M. bovis orthologous genes analysis suggest a process of genome remodeling through genomic decay and gene duplication. Quantification, pairwise comparisons and distribution analyses of polymorphic sites demonstrate greater genetic variability of M. tuberculosis when compared to M. bovis and M. bovis BCG (p ≤ 0.05), indicating that currently defined M. tuberculosis lineages are more genetically diverse than M. bovis CC and animal-adapted MTC (M. tuberculosis Complex) species. As expected, polymorphic sites annotation shows that M. bovis BCG are subjected to different evolutionary pressures when compared to virulent mycobacteria. Lastly, M. bovis phylogeny indicates that polymorphic sites may be used as markers of M. bovis lineages in association with CC. Our findings highlight the need to better understand host-pathogen co-evolution in genetically homogeneous and/or diverse host populations, considering the fact that M. bovis has a broader host range when compared to M. tuberculosis. Also, the identification of M. bovis genomes not classified within CC indicates that the diversity of M. bovis lineages may be larger than previously thought or that current classification should be reviewed.

Dataset Information

An African origin for Mycobacterium bovis.

Publications

An African origin for <i>Mycobacterium bovis</i>.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets