TY - JOUR

T1 - Unraveling the epidemiology of Mycobacterium bovis using whole-genome sequencing combined with environmental and demographic data

AU - Rossi, Gianluigi

AU - Shih, Barbara Bo Ju

AU - Egbe, Nkongho Franklyn

AU - Motta, Paolo

AU - Duchatel, Florian

AU - Kelly, Robert Francis

AU - Ndip, Lucy

AU - Sander, Melissa

AU - Tanya, Vincent Ngwang

AU - Lycett, Samantha J.

AU - Bronsvoort, Barend Mark

AU - Muwonge, Adrian

N1 - Funding Information: The primary data used in this study were generated with funding from Wellcome Trust (WT094945), with BCMB as the principal investigator. BS, SL, MB, BB, and AM are supported by the Biotechnology and Biological Sciences Research Council (BBSRC) program grant to Roslin Institute (Award numbers BBS/E/D/20002172 and BBS/E/D/200021723), and AM later by his BBSRC Future leader Fellowship and current Chancellor's fellowship. GR, SL, and BB additionally received support from the Scottish Government Rural and Environment Science and Analytical Services Division as part of the Center of Expertise on Animal Disease Outbreaks (EPIC). We are also grateful to the staff of MENIPIA, especially the veterinarians and delegates who diligently supported the primary fieldwork that generated this data. BS was partially funded by a BBSRC Core Capability Grant BB/CCG1780/1 awarded to The Roslin Institute. M. bovis sequencing was carried out by Edinburgh Genomics, The University of Edinburgh, which is partly supported through core grants from NERC (R8/H10/56), MRC (MR/K001744/1), and BBSRC (BB/J004243/1). Funding Information: The primary data used in this study were generated with funding from Wellcome Trust (WT094945), with BCMB as the principal investigator. BS, SL, MB, BB, and AM are supported by the Biotechnology and Biological Sciences Research Council (BBSRC) program grant to Roslin Institute (Award numbers BBS/E/D/20002172 and BBS/E/D/200021723), and AM later by his BBSRC Future leader Fellowship and current Chancellor's fellowship. GR, SL, and BB additionally received support from the Scottish Government Rural and Environment Science and Analytical Services Division as part of the Center of Expertise on Animal Disease Outbreaks (EPIC). We are also grateful to the staff of MENIPIA, especially the veterinarians and delegates who diligently supported the primary fieldwork that generated this data. BS was partially funded by a BBSRC Core Capability Grant BB/CCG1780/1 awarded to The Roslin Institute. M. bovis sequencing was carried out by Edinburgh Genomics, The University of Edinburgh, which is partly supported through core grants from NERC (R8/H10/56), MRC (MR/K001744/1), and BBSRC (BB/J004243/1). Publisher Copyright: Copyright © 2023 Rossi, Shih, Egbe, Motta, Duchatel, Kelly, Ndip, Sander, Tanya, Lycett, Bronsvoort and Muwonge.

PY - 2023/5/17

Y1 - 2023/5/17

N2 - When studying the dynamics of a pathogen in a host population, one crucial question is whether it transitioned from an epidemic (i.e., the pathogen population and the number of infected hosts are increasing) to an endemic stable state (i.e., the pathogen population reached an equilibrium). For slow-growing and slow-evolving clonal pathogens such as Mycobacterium bovis, the causative agent of bovine (or animal) and zoonotic tuberculosis, it can be challenging to discriminate between these two states. This is a result of the combination of suboptimal detection tests so that the actual extent of the pathogen prevalence is often unknown, as well as of the low genetic diversity, which can hide the temporal signal provided by the accumulation of mutations in the bacterial DNA. In recent years, the increased availability, efficiency, and reliability of genomic reading techniques, such as whole-genome sequencing (WGS), have significantly increased the amount of information we can use to study infectious diseases, and therefore, it has improved the precision of epidemiological inferences for pathogens such as M. bovis. In this study, we use WGS to gain insights into the epidemiology of M. bovis in Cameroon, a developing country where the pathogen has been reported for decades. A total of 91 high-quality sequences were obtained from tissue samples collected in four abattoirs, 64 of which were with complete metadata. We combined these with environmental, demographic, ecological, and cattle movement data to generate inferences using phylodynamic models. Our findings suggest M. bovis in Cameroon is slowly expanding its epidemiological range over time; therefore, endemic stability is unlikely. This suggests that animal movement plays an important role in transmission. The simultaneous prevalence of M. bovis in co-located cattle and humans highlights the risk of such transmission being zoonotic. Therefore, using genomic tools as part of surveillance would vastly improve our understanding of disease ecology and control strategies.

AB - When studying the dynamics of a pathogen in a host population, one crucial question is whether it transitioned from an epidemic (i.e., the pathogen population and the number of infected hosts are increasing) to an endemic stable state (i.e., the pathogen population reached an equilibrium). For slow-growing and slow-evolving clonal pathogens such as Mycobacterium bovis, the causative agent of bovine (or animal) and zoonotic tuberculosis, it can be challenging to discriminate between these two states. This is a result of the combination of suboptimal detection tests so that the actual extent of the pathogen prevalence is often unknown, as well as of the low genetic diversity, which can hide the temporal signal provided by the accumulation of mutations in the bacterial DNA. In recent years, the increased availability, efficiency, and reliability of genomic reading techniques, such as whole-genome sequencing (WGS), have significantly increased the amount of information we can use to study infectious diseases, and therefore, it has improved the precision of epidemiological inferences for pathogens such as M. bovis. In this study, we use WGS to gain insights into the epidemiology of M. bovis in Cameroon, a developing country where the pathogen has been reported for decades. A total of 91 high-quality sequences were obtained from tissue samples collected in four abattoirs, 64 of which were with complete metadata. We combined these with environmental, demographic, ecological, and cattle movement data to generate inferences using phylodynamic models. Our findings suggest M. bovis in Cameroon is slowly expanding its epidemiological range over time; therefore, endemic stability is unlikely. This suggests that animal movement plays an important role in transmission. The simultaneous prevalence of M. bovis in co-located cattle and humans highlights the risk of such transmission being zoonotic. Therefore, using genomic tools as part of surveillance would vastly improve our understanding of disease ecology and control strategies.

KW - genomic surveillance

KW - multi-host system

KW - Mycobacterium bovis

KW - one health

KW - phylodynamics

KW - phylogeography

KW - whole genome sequencing (WGS)

KW - zoonotic tuberculosis

U2 - 10.3389/fvets.2023.1086001

DO - 10.3389/fvets.2023.1086001

M3 - Journal article

AN - SCOPUS:85161014356

VL - 10

JO - Frontiers in Veterinary Science

JF - Frontiers in Veterinary Science

SN - 2297-1769

M1 - 1086001

ER -