Identification of differentially recognized T cell epitopes in the spectrum of Mtb infection

结核分枝杆菌感染谱中差异识别的 T 细胞表位的鉴定

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作者:Sudhasini Panda, Jeffrey Morgan, Catherine Cheng, Mayuko Saito, Robert H Gilman, Nelly Ciobanu, Valeriu Crudu, Donald G Catanzaro, Antonino Catanzaro, Timothy Rodwell, Judy S B Perera, Teshan Chathuranga, Bandu Gunasena, Aruna D DeSilva, Bjoern Peters, Alessandro Sette, Cecilia S Lindestam Arlehamn

Abstract

Tuberculosis caused by Mycobacterium tuberculosis is one of the leading causes of death from a single infectious agent. Identifying dominant epitopes and comparing their reactivity in different tuberculosis (TB) infection states can help design diagnostics and vaccines. We performed a proteome-wide screen of 20,610 Mtb derived peptides in 21 Active TB (ATB) patients 3-4 months post-diagnosis of pulmonary TB (mid-treatment) using an IFNγ and IL-17 Fluorospot assay. Responses were mediated exclusively by IFNγ and identified a total of 137 unique epitopes, with each patient recognizing, on average, 8 individual epitopes and 22 epitopes (16%) recognized by 2 or more participants. Responses were predominantly directed against antigens part of the cell wall and cell processes category. Testing 517 peptides spanning TB vaccine candidates and ESAT-6 and CFP10 antigens also revealed differential recognition between ATB participants mid-treatment and healthy IGRA+ participants of several vaccine antigens. An ATB-specific peptide pool consisting of epitopes exclusively recognized by participants mid-treatment, allowed distinguishing participants with active pulmonary TB from healthy interferon-gamma release assay (IGRA)+/- participants from diverse geographical locations. Analysis of longitudinal samples indicated decreased reactivity during treatment for pulmonary TB. Together, these results show that a proteome-wide screen of T cell reactivity identifies epitopes and antigens that are differentially recognized depending on the Mtb infection stage. These have potential use in developing diagnostics and vaccine candidates and measuring correlates of protection.

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