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Data Sheet 1_Population structure and antibiotic resistance profiles of Mycobacterium tuberculosis isolates from Ibadan, Nigeria (2019–2020): a pilot study to improve affordable molecular diagnostic tools.pdf

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NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/Data_Sheet_1_Population_structure_and_antibiotic_resistance_profiles_of_Mycobacterium_tuberculosis_isolates_from_Ibadan_Nigeria_2019_2020_a_pilot_study_to_improve_affordable_molecular_diagnostic_tools_pdf/30230281
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Nigeria ranks as the sixth country globally and the first in Africa with the highest burden of tuberculosis (TB) infection. The emergence and spread of multidrug-resistant TB (MDR-TB) strains have posed significant challenges to effective disease management in the country. In this study, 55 Mycobacterium tuberculosis (MTB) isolates from patients attending a hospital in Ibadan city (Nigeria) were selected. MTB isolates were analyzed using PCR amplification of gene fragments associated with antibiotic resistance, followed by Sanger sequencing and bioinformatics analysis. Additionally, MIRU-VNTR genotyping was performed to address population structure and transmission dynamics. Results show an association between mutations in the rpoB, inhA and gyrA genes and phenotypic resistance to rifampicin, isoniazide and fluoroquinolones in a significant percentage of the MTB isolates. However, an extended panel of genes would enable a better characterization of antibiotic resistance. The population structure of MTB in Ibadan, as determined by using MIRU-VNTR, revealed that 96.1% of the strains belong to lineage 4, distributed in the following sublineages: Uganda I (47.1%), LAM (21.6%), Cameroon (17.6%), and Ghana (9.8%). Meanwhile, 3.9% of the strains correspond to lineage 5 (L5), West African-1 sub-lineage. The population structure was very heterogeneous and no active transmission clusters were detected. Overall, this pilot study demonstrated the utility of cost-effective molecular tools in enhancing TB surveillance and control programs in settings where whole-genome sequencing (WGS) is still an economical challenge.
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2025-09-29
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