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Profiling antibody responses to M. tuberculosis proteins in TB suspects’ sera using full-proteome microarrays.

ABSTRACT: Understanding the immune response to tuberculosis requires greater knowledge of humoral responses. To characterize antibody targets and the effect of disease parameters on target recognition, we developed a systems immunology approach that integrated detection of antibodies against the entire Mycobacterium tuberculosis proteome, bacterial metabolic and regulatory pathway information, and patient data. Probing ~4,000 M. tuberculosis proteins with sera from >500 suspected tuberculosis patients worldwide revealed that antibody responses recognized ~10% of the bacterial proteome. This result defines the immunoproteome of M. tuberculosis, which is rich in membrane-associated and extracellular proteins. Most serum reactivity during active tuberculosis focused onto ~0.5% of the proteome. Within this pool, which is selectively enriched for extracellular proteins (but not for membrane-associated proteins), relative target preference varied among patients. The shift in relative M. tuberculosis protein reactivity observed with active tuberculosis defines the evolution of the humoral immune response during M. tuberculosis infection and disease.

ORGANISM(S): Homo sapiens Mycobacterium tuberculosis H37Rv

PROVIDER: GSE19433 | GEO | 2010/07/14

SECONDARY ACCESSION(S): PRJNA122303

REPOSITORIES: GEO

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Project description:Understanding the immune response to tuberculosis requires greater knowledge of humoral responses. To characterize antibody targets and the effect of disease parameters on target recognition, we developed a systems immunology approach that integrated detection of antibodies against the entire Mycobacterium tuberculosis proteome, bacterial metabolic and regulatory pathway information, and patient data. Probing ~4,000 M. tuberculosis proteins with sera from >500 suspected tuberculosis patients worldwide revealed that antibody responses recognized ~10% of the bacterial proteome. This result defines the immunoproteome of M. tuberculosis, which is rich in membrane-associated and extracellular proteins. Most serum reactivity during active tuberculosis focused onto ~0.5% of the proteome. Within this pool, which is selectively enriched for extracellular proteins (but not for membrane-associated proteins), relative target preference varied among patients. The shift in relative M. tuberculosis protein reactivity observed with active tuberculosis defines the evolution of the humoral immune response during M. tuberculosis infection and disease. Peripheral blood was collected from prospectively enrolled TB suspects among subjects seeking care for pulmonary symptoms at clinics associated with national TB control programs in 11 countries. M. tuberculosis proteome microarrays representing 4099 bacterial protein spots were probed with sera from 561 TB suspects. Based on the final diagnosis, they belonged to two classes: TB (n=254) and Non-TB Disease (n=307). In addition, healthy individuals negative to Latent TB Infection (LTBI neg, n=64) were also tested (negative control sera). Each serum was tested with a single array and no replicate experiments were performed. The reactivity of a serum to an M. tuberculosis protein (reactivity call) was defined based on the distribution of negative control sera intensity for that protein using Z-statistics. Based on the distribution of reactivity calls, 27 outlier samples reacting with more than 20 proteins were excluded from further analysis. The association of reactivity calls of each protein with TB/NTBD status of TB suspects was determined by estimating odds ratio and 95% confidence interval.

Project description:Human infection with Mycobacterium tuberculosis results in a continuum of ill-defined, clinical manifestations with stable latent M. tuberculosis infection (LTBI) and severe active disease at the ends. Identifying different states of infection is of importance to tuberculosis (TB) control since risk of developing active disease varies among different asymptomatic states while infectiousness varies among patients with different bacterial burden. We investigated changes in proteome-scale antibody responses during disease progression in a non-human primate model of tuberculosis. We probed M. tuberculosis proteome microarrays with serial sera collected from three infection-outcome groups (active, reactivation, and latent). We found that each infection outcome is associated with characteristic changes in the antibody levels and number of antigenic targets, which suggested an association between antibody responses and bacillary burden. Additional proteome-scale serological profiling of > 400 human TB suspects established that antibody responses are positively associated with bacterial load. Thus tuberculosis-specific antibody levels and number of antigenic targets increases with disease progression. Serum samples collected from adult patients with suspected tuberculosis during a multi-site study was used to probe whole proteome microarrays. Subject recruitment was conducted under uniform protocols approved by the institutional ethics committee at each site. Final diagnosis of active TB was based on positive M. tuberculosis culture results. The active TB patients were further subdivided into smear-positive and negative disease based on results of Ziehl-Neelsen staining of sputum smears for acid fast bacilli. Active TB was excluded as a diagnosis (Non-TB Disease [NTBD] patients) based on having negative M. tuberculosis culture and smear results and on having an alternate diagnosis. All subjects were presumably negative for HIV infection given the very low incidence of HIV infection in the study sites. Sera from 169 TB and 242 NTBD patients were selected for microarray probing. The control sera (n = 14) which was used to generate negative control distribution for each protein were negative to latent M. tuberculosis infection, as indicated by negative results to tuberculin skin test.

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Profiling antibody responses to M. tuberculosis proteins in TB suspects’ sera using full-proteome microarrays.

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