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Updated: Jan 2, 2026

Modeling Tuberculosis in Mycobacterium marinum Infected Adult Zebrafish
Published on: October 8, 2018
Reverse zoonotic tuberculosis transmission from an emerging Uganda I strain between pastoralists and cattle in
Hezekiah Kehinde Adesokan1, Victor Oluwatoyin Akinseye2, Elizabeth Maria Streicher3
1Department of Veterinary Public Health and Preventive Medicine, University of Ibadan, Ibadan, Nigeria. latterglory70@yahoo.co.in.
Background:
Tuberculosis remains a major public health challenge globally with increasing risks for inter-transmission between pastoralists and cattle in Nigeria. This study was aimed at using molecular tools to establish zoonotic transmission of tuberculosis between pastoralists and their cattle in Ebonyi State, Nigeria. Sputum (n = 149) and milk (n = 144) samples from pastoralists and cattle, respectively were screened on the assumption of subclinical infections considering unguarded human-livestock interactions. Isolates obtained were analysed using deletion typing, spoligotyping and 24-Mycobacterial Interspersed Repetitive Unit-Variable Number Tandem Repeats (MIRU-VNTR).
Results:
Fifty-four MTC were confirmed by deletion typing and were differentiated accordingly (M. tuberculosis: pastoralists =42, cattle = 2; M. bovis: pastoralists =1; M. africanum: pastoralists =9). Spoligotyping indicated 59.2% Uganda I/SIT46 (pastoralists =28; cattle = 1), 16.3% Latin American Mediterranean/SIT61 (pastoralists =8), 2.0% T/SIT53 (pastoralists =1) strains of M. tuberculosis and new strains of M. bovis and M. africanum. The 24-MIRU-VNTR of selected predominant cluster isolates shared by cattle and pastoralists (Uganda I/SIT46: pastoralists =9; cattle = 1) showed the same number of copies at each of the repetitive loci.
Conclusions:
Mycobacterium bovis was confirmed in humans and a reverse zoonotic tuberculosis transmission from an emerging Uganda I M. tuberculosis strain between pastoralists and cattle in Nigeria evidenced by MIRU-VNTR. Using molecular tools will help mitigate disease burden through informed epidemiological insights.
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