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BackgroundMycobacterium tuberculosis var. bovis is one of the causative agents of Tuberculosis primarily known to infect cattle and is a member of the Mycobacterium Tuberculosis Complex. M.bovis is zoonotic and infects human and other animals resulting in immense economic losses globally. M.bovis is often misdiagnosed and becomes a challenge for treatment and recovery, as M.bovis is intrinsically resistant to certain antibiotics. Hence, the need for accurate diagnostics for zoonotic tuberculosis. ResultsIn order to discern the differences which lie between M.tuberculosis and M.bovis isolates we collected a global collection of M.bovis isolates from NCBI and carried out variant identification studies keeping M.tuberculosis as the reference. Clustering approaches like Principal component analysis and distance-based UPGMA methods helped to segregate isolates into different clusters of homogeneous and heterogeneous populations, which were further analyzed for variant identification. Methods like Joint Variant Calling using population-based studies was adopted for the M.bovis strains, which helped to discern high confidence polymorphisms for each set of populations. Four different variant callers were used to predict SNPs present in their genomic regions. Based on the predicted SNPs, M.bovis samples isolated from New-Zealand were identified as a heterogeneous fast evolving population, whereas the UK samples were identified as a slow evolving homogeneous population. The core-SNP identified for each population revealed the “fixed” mutations present within the populations, whereas, the total-SNP for heterogeneous population indicated presence of clonal subpopulations. A methodology for assignment of genomic coordinates to the reference SNP cluster id of M.tuberculosis entries in dbSNP was also developed and implemented, which helped to identify the percentage of known variants in a population. ConclusionsPopulation-specific studies for global collection of M.bovis samples aided in identification of SNPs responsible for zoonosis. The core-SNP set identified across global M.bovis isolates provide a rationale for further studies to the underlying host-tropism along with aiding in as a robust genetic biomarker for distinguishing M.bovis form M.tuberculosis in addition to the already known RDs. The variation profile reported in this study can serve as potential biomarkers for identification of M.bovis isolates and provide a rationale for further studies to the underlying host-tropism.

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A total of two lineages of Mycobacterium tuberculosis var. africanum (Maf), L5 and L6, which are members of the Mycobacterium tuberculosis complex (MTBC), are responsible for causing tuberculosis in West Africa. Regions of difference (RDs) are usually used for delineation of MTBC. With increased data availability, single nucleotide polymorphisms (SNPs) promise to provide better resolution. Publicly available 380 Maf samples were analyzed for identification of “core-cluster-specific-SNPs,” while additional 270 samples were used for validation. RD-based methods were used for lineage-assignment, wherein 31 samples remained unidentified. The genetic diversity of Maf was estimated based on genome-wide SNPs using phylogeny and population genomics approaches. Lineage-based clustering (L5 and L6) was observed in the whole genome phylogeny with distinct sub-clusters. Population stratification using both model-based and de novo approaches supported the same observations. L6 was further delineated into three sub-lineages (L6.1–L6.3), whereas L5 was grouped as L5.1 and L5.2 based on the occurrence of RD711. L5.1 and L5.2 were further divided into two (L5.1.1 and L5.1.2) and four (L5.2.1–L5.2.4) sub-clusters, respectively. Unassigned samples could be assigned to definite lineages/sub-lineages based on clustering observed in phylogeny along with high-confidence posterior membership scores obtained during population stratification. Based on the (sub)-clusters delineated, “core-cluster-specific-SNPs” were derived. Synonymous SNPs (137 in L5 and 128 in L6) were identified as biomarkers and used for validation. Few of the cluster-specific missense variants in L5 and L6 belong to the central carbohydrate metabolism pathway which include His6Tyr (Rv0946c), Glu255Ala (Rv1131), Ala309Gly (Rv2454c), Val425Ala and Ser112Ala (Rv1127c), Gly198Ala (Rv3293) and Ile137Val (Rv0363c), Thr421Ala (Rv0896), Arg442His (Rv1248c), Thr218Ile (Rv1122), and Ser381Leu (Rv1449c), hinting at the differential growth attenuation. Genes harboring multiple (sub)-lineage-specific “core-cluster” SNPs such as Lys117Asn, Val447Met, and Ala455Val (Rv0066c; icd2) present across L6, L6.1, and L5, respectively, hinting at the association of these SNPs with selective advantage or host-adaptation. Cluster-specific SNPs serve as additional markers along with RD-regions for Maf delineation. The identified SNPs have the potential to provide insights into the genotype–phenotype correlation and clues for endemicity of Maf in the African population.