alexa Immunogenicity of novel DosR regulon-encoded candidate antigens of Mycobacterium tuberculosis in three high-burden populations in Africa.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Computer Science & Systems Biology

Author(s): Black GF, Thiel BA, Ota MO, Parida SK, Adegbola R,

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Abstract Increasing knowledge about DosR regulon-encoded proteins has led us to produce novel Mycobacterium tuberculosis antigens for immunogenicity testing in human populations in three countries in Africa to which tuberculosis (TB) is endemic. A total of 131 tuberculin skin test-positive and/or ESAT-6/CFP10-positive, human immunodeficiency virus-negative adult household contacts of active pulmonary TB cases from South Africa (n = 56), The Gambia (n = 26), and Uganda (n = 49) were tested for gamma interferon responses to 7 classical and 51 DosR regulon-encoded M. tuberculosis recombinant protein antigens. ESAT-6/CFP10 fusion protein evoked responses in >75\% of study participants in all three countries. Of the DosR regulon-encoded antigens tested, Rv1733c was the most commonly recognized by participants from both South Africa and Uganda and the third most commonly recognized antigen in The Gambia. The four most frequently recognized DosR regulon-encoded antigens in Uganda (Rv1733c, Rv0081, Rv1735c, and Rv1737c) included the three most immunogenic antigens in South Africa. In contrast, Rv3131 induced the highest percentage of responders in Gambian contacts (38\%), compared to only 3.4\% of Ugandan contacts and no South African contacts. Appreciable percentages of TB contacts with a high likelihood of latent M. tuberculosis infection responded to several novel DosR regulon-encoded M. tuberculosis proteins. In addition to significant similarities in antigen recognition profiles between the three African population groups, there were also disparities, which may stem from genetic differences between both pathogen and host populations. Our findings have implications for the selection of potential TB vaccine candidates and for determining biosignatures of latent M. tuberculosis infection, active TB disease, and protective immunity.
This article was published in Clin Vaccine Immunol and referenced in Journal of Computer Science & Systems Biology

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