Abstract

The PPE (proline-proline-glutamic acid) proteins of Mycobacterium tuberculosis are characterized by a conserved N-terminal domain of approximately 180 amino acids and variable C-terminal domain. Since last decade, these proteins have gained much importance in the serodiagnosis of tuberculosis (TB) as they act as a source of antigenic variation. We have demonstrated earlier that one of the PPE proteins PPE17 (Rv1168c) induces strong B-cell and T-cell responses in active TB disease and also displays a higher antibody titer compared to immunodominant antigens such as ESAT-6, Hsp60 and PPD. However, the immunodominant domain of PPE17 (N-terminal or C-terminal) was not examined in detail. In the present study, we observed that antibody responses elicited in TB patients were directed mostly towards the N-terminal domain of PPE17 (N-PPE17). The antibody generated against N-PPE17 in TB patients did not significantly cross-react with N-terminal domains of other PPE proteins used in this study. Our data suggest that the N-terminal domain of PPE17 protein is immunodominant and could be used as a better serodiagnostic marker than the full-length PPE17 protein.

Highlights

  • Despite the fact that the disease tuberculosis (TB) can be cured, it remains one of the world’s biggest threats accounting for millions of deaths every year

  • When sera obtained from TB patients were incubated with either PPE17 or N-terminal domain of PPE17 (N-PPE17) protein and compared with that of BCG-vaccinated healthy controls, significantly higher antibody titers were observed in TB patients as compared to healthy controls (P < 0.001; Fig 1A)

  • In continuation of our efforts towards serological characterization of PPE17 in detail, we studied the specific domain(s) of PPE17 that were responsible for induction of higher antibody responses in active TB patients

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Summary

Introduction

Despite the fact that the disease tuberculosis (TB) can be cured, it remains one of the world’s biggest threats accounting for millions of deaths every year. The World Health Organization (WHO) has estimated 10.4 million new cases of active TB and 1.8 million deaths due to TB in 2015 [1]. The current situation has become more complicated due to emergence of multi and extensively drug resistant strains of M. tuberculosis and appearance of co-infection of human immunodeficiency virus (HIV) with TB. TB together with HIV infection ranks as a leading cause of death worldwide. Available methods for diagnosis of active TB have several limitations.

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