MTB_LAM_MDR
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB25765 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Tuberculosis (TB) is one of the deadliest infectious disorders in the world. To effectively TB manage, an essential step is to gain insight into the lineage of Mycobacterium tuberculosis (MTB) strains and the distribution of drug resistance. Although the Campania region is declared a cluster area for the infection, to contribute to the effort to understand TB evolution and transmission, still poorly known, we have generated a dataset of 159 genomes of MTB strains, from Campania region collected during 2018-2021, obtained from the analysis of whole genome sequence data. The results show that the most frequent MTB lineage is the 4 according for 129 strains (81.11%). Regarding drug resistance, 139 strains (87.4%) were classified as multi susceptible, while the remaining 20 (12.58%) showed drug resistance. Among the drug-resistance strains, 8 were isoniazid-resistant MTB (HR-MTB), 7 were resistant only to one antibiotic (3 were resistant only to ethambutol and 3 isolate to streptomycin while one isolate showed resistance to fluoroquinolones), 4 multidrug-resistant MTB, while only one was classified as pre-extensively drug-resistant MTB (pre-XDR). This dataset expands the existing available knowledge on drug resistance and evolution of MTB, contributing to further TB-related genomics studies to improve the management of TB infection.
2023-11-17 | E-MTAB-13058 | biostudies-arrayexpress
Project description:The outcome of an infectious disease exposure is the result of interactions between host and pathogen and can depend on genetic variations in both. We explored this relationship in tuberculosis (TB) by conducting a genome-to-genome (g2g) study of paired human and Mycobacterium tuberculosis (Mtb) genomes from a cohort of 1556 TB patients in Lima, Peru. We identified an association between a human intronic variant (rs3130660, OR = 10.06, 95% CI: 4.87 - 20.77, P = 7.92 ⨉ 10-8 ) in the FLOT1 gene and a subclade of Mtb Lineage 2 (g2g-L2). We assessed this interaction in a Mtb-macrophage infection model between bacterial and host genetic backgrounds. We found that expression of FLOT1 and other genes in the MHC class-I region are differentially modulated by g2g-L2 compared to nearest neighbor strains. We also found distinct inflammatory responses with different host genetic backgrounds, with hosts carrying the A allele of rs3130660 inducing stronger type I and II interferon (IFN) gene signatures than hosts carrying only the T allele. TB infection with g2g-L2 strains shift macrophage responses away from this IFN signaling. In vitro analyses show that the g2g-L2 strains are distinguished by altered redox states and resistance to reductive stress and that these phenotypes result from a single mutation in thioredoxin reductase (trxB2, T2N). We also investigated this association in a 2020 cohort of 699 patients with TB recruited during the COVID-19 pandemic. Between 2010 and 2020, the prevalence of the g2g-L2 strain almost doubled, nearly fully replacing the other co-circulating L2 strains. However, g2g-L2 infection was not associated with rs3130660 in this cohort. These data raise the possibility of a more dynamic landscape of interacting host, pathogen and environmental risk factors than previously expected for TB.
2024-03-30 | GSE262379 | GEO
Project description:WGS of MTB (Astana 2014)
| PRJNA1013742 | ENA