Abstract
Bovine tuberculosis (bTB) has yet to be eradicated in Brazil. Herds of cattle and buffalo are important sources of revenue to people living in the banks of the Amazon River basin. A better understanding of Mycobacterium bovis (M. bovis) populational structure and transmission dynamics affecting these animals can significantly contribute in efforts to improve their sanitary status. Herein, we sequenced the whole genome of 22 M. bovis isolates (15 from buffalo and 7 from cattle) from 10 municipalities in the region of the Lower Amazon River Basin in Brazil and performed phylogenomic analysis and Single Nucleotide Polymorphism (SNP)-based transmission inference to evaluate population structure and transmission networks. Additionally, we compared these genomes to others obtained in unrelated studies in the Marajó Island (n = 15) and worldwide (n = 128) to understand strain diversity in the Amazon and to infer M. bovis lineages. Our results show a higher genomic diversity of M. bovis genomes obtained in the Lower Amazon River region when compared to the Marajó Island, while no significant difference was observed between M. bovis genomes obtained from cattle and buffalo (p ≥ 0.05). This high genetic diversity is reflected by the weak phylogenetic clustering of M. bovis from the Lower Amazon River region based on geographic proximity and in the detection of only two putative transmission clusters in the region. One of these clusters is the first description of inter-species transmission between cattle and buffalo in the Amazon, bringing implications to the bTB control program. Surprisingly, two M. bovis lineages were detected in our dataset, namely Lb1 and Lb3, constituting the first description of Lb1 in South America. Most of the strains of this study (13/22) and all 15 strains of the Marajó Island carried no clonal complex marker, suggesting that the recent lineage classification better describe the diversity of M. bovis in the Amazon.
Highlights
Mycobacterium bovis (M. bovis) is a member of the Mycobacterium tuberculosis complex (MTBC) and is the leading causative agent of bovine tuberculosis, an OIE (World Organization for Animal Health) notifiable disease that affects mainly cattle, buffalo, and other domesticated and wild animals, but can be transmitted to humans [1, 2]. bTB is distributed worldwide but has very low prevalence in most industrialized countries and has even been eradicated in few nations
M. bovis has been historically classified by Clonal Complexes (CCs), which are identified by genomic deletions, few Single Nucleotide Polymorphism’s (SNPs), and/or spoligotypes patterns [10]
The spoligotype SB0822 in Brazil was first described in our previous study [20] and we agree with the recent study in Marajó Island in Pará state [24] which seems to demonstrate that SB0822 is the predominant spoligotype in the Amazon region, opposite to a national study with 143 samples from 10 states that found only one occurrence of SB0822 [21]
Summary
Mycobacterium bovis (M. bovis) is a member of the Mycobacterium tuberculosis complex (MTBC) and is the leading causative agent of bovine tuberculosis (bTB), an OIE (World Organization for Animal Health) notifiable disease that affects mainly cattle, buffalo, and other domesticated and wild animals, but can be transmitted to humans (zoonotic TB) [1, 2]. bTB is distributed worldwide but has very low prevalence in most industrialized countries and has even been eradicated in few nations. With the advent of WGS, recent studies at a global scale provided insights into the population structure and evolution of M. bovis lineages [9], showing that CCs do not represent the whole genomic diversity of the isolates [9, 15, 16] and suggesting the existence of at least four M. bovis lineages, named Lb1 through Lb4, and three “unknown groups” [9]. With the populational structure of M. bovis based on WGS starting to be unveiled, additional studies covering different geographic locations are needed to better comprehend worldwide disease spread and to provide new insights regarding the use of genomes to understand disease transmission at the herd and farm levels
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