New Genome-Wide Algorithm Identifies Novel In-Vivo Expressed Mycobacterium Tuberculosis Antigens Inducing Human...

Area of Science:

• Immunology
• Microbiology
• Vaccinology

Background:

• Tuberculosis (TB) control requires novel vaccination strategies and tools.
• Identifying antigens expressed during Mycobacterium tuberculosis (Mtb) infection in the lung is crucial for vaccine development.
• Eliciting robust human immune responses against Mtb is a key challenge.

Purpose of the Study:

• To develop a novel approach for identifying in-vivo expressed TB (IVE-TB) antigens in the lung.
• To select promising IVE-TB candidate antigens based on expression, conservation, and epitope prediction.
• To validate the immunogenicity of selected antigens in human T-cell responses.

Main Methods:

• Genome-wide transcriptomics of Mtb-infected lungs to identify upregulated genes.
• Analysis of gene conservation across Mtb-complex strains.
• Prediction of HLA-class Ia and II presented epitopes using algorithms.
• In vitro T-cell proliferation and multi-cytokine production assays.
• Validation in independent cohorts of latently Mtb-infected individuals.

Main Results:

• Identified and prioritized novel IVE-TB antigens expressed in the lung during Mtb infection.
• Selected candidate antigens were recognized by T-cells from Mtb-exposed individuals.
• Demonstrated significant T-cell responses, including those independent of IFN-γ production.
• Validated the antigen discovery approach in independent cohorts.

Conclusions:

• The novel antigen discovery approach effectively identifies Mtb antigens, including those inducing unconventional T-cell responses.
• These findings provide potential new tools for TB vaccination and biomarker profiling.
• The generic approach is adaptable for discovering antigens for other infectious diseases.