Long-term molecular surveillance provides clues on a cattle origin for Mycobacterium bovis in Portugal

Abstract

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.

Association of bacterial vaginosis with periodontitis in a cross-sectional American nationwide survey

“…Due to its novelty, we are not able to compare our results. Also, NHANES waves stated in this paper used a partial index to assess periodontal status which diminishes the sensitivity and specificity 77 , 78 , and this may limit the validity of the established association duo to a possible underestimation of PD. Hence future studies shall implement full-mouth periodontal charts to contribute to more consistent results.…”

Phylogenomics Sheds Light on the population structure ofMycobacterium bovisfrom a Multi-Host Tuberculosis System

“…This dataset was selected for WGS from a wider M. bovis dataset recovered in Portugal ( n =487) that was previously submitted to molecular characterization by classical genotyping techniques, namely spoligotyping and 8 loci MIRU-VNTR (Supplementary Fig. 1) (Reis et al, 2020). To represent the population genetic diversity, two selection criteria were applied: first, isolates should represent major spoligotyping-MIRU type groups and adjacent variants; and second, they should cover different host species, geographic regions and temporal/epidemiological contexts (using year of M. bovis isolation as proxy) (Supplementary Fig.…”

“…To date, works with reference to M. bovis molecular characterization in Portugal have been based on the analysis of repetitive genomic regions, namely spoligotyping (spacer oligonucleotide typing) and MIRU-VNTR ( Mycobacterial Interspersed Repetitive Units-Variable Number Tandem Repeats ). The focus has been placed over isolates from cattle, red deer and wild boar from TB hotspot areas located in the central and south regions of the country (Cunha et al, 2012; Duarte, Domingos, Amado, Cunha, & Botelho, 2010; Reis, Tenreiro, Albuquerque, Botelho, & Cunha, 2020). These works provided evidences for M. bovis population diversity and structure, highlighting the main genotypes across host species and regions, as well as intra- and inter-specific transmission (Cunha et al, 2012; Duarte et al, 2010; Reis et al, 2020).…”

“…The focus has been placed over isolates from cattle, red deer and wild boar from TB hotspot areas located in the central and south regions of the country (Cunha et al, 2012; Duarte, Domingos, Amado, Cunha, & Botelho, 2010; Reis, Tenreiro, Albuquerque, Botelho, & Cunha, 2020). These works provided evidences for M. bovis population diversity and structure, highlighting the main genotypes across host species and regions, as well as intra- and inter-specific transmission (Cunha et al, 2012; Duarte et al, 2010; Reis et al, 2020). However, these molecular typing approaches have explored epidemiological links via genotype associations, which are not sufficiently discriminatory to accurately assess transmission at a fine-scale, nor to gain insights on the roles exerted by different species in a multi-host system.…”

“…With the aim to improve knowledge on M. bovis population structure and transmission within and across TB hotspots in Portugal, WGS of 44 M. bovis obtained between 2003 and 2015 from cattle, red deer and wild boar was completed. These isolates were selected as being representative of the M. bovis population diversity in those areas, which was previously assessed by a large-scale genotyping study that combined standard genotyping techniques (spoligotyping and MIRU-VNTR) with Bayesian clustering (Reis et al, 2020). The methodological framework aimed to: (1) identify phylogenetic clades and build a catalogue of SNPs that may be used as specific molecular markers of each clade; (2) explore how specific nucleotide differences are associated with distinct host and/or geographic regions; (3) disclose transmission networks for global and local datasets from Portugal; and (4) infer infectivity in distinct host species and geographic locations.…”