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Related Experiment Video

Updated: May 28, 2026

Expression of Exogenous Antigens in the Mycobacterium bovis BCG Vaccine via Non-genetic Surface Decoration with the Avidin-biotin System

Expression of Exogenous Antigens in the Mycobacterium bovis BCG Vaccine via Non-genetic Surface Decoration with the Avidin-biotin System

Published on: January 31, 2018

Recombinant Immunogens Designed by AI Epitope Prioritization Confer Protection Against Mycobacterium tuberculosis.

Ning Fang¹, Anke Chen¹, Zhifei Zhang¹

¹Shanghai Pudong Hospital and School of Life Sciences, State Key Laboratory of Genetics and Development of Complex Phenotypes, Shanghai Engineering Research Center of Industrial Microorganisms, Fudan University, Shanghai 200438, China.

|May 26, 2026

Summary

Artificial intelligence identified novel tuberculosis vaccine candidates, RI-13, RI-20, and RI-31. RI-13 demonstrated strong immunogenicity and protective efficacy in preclinical models, offering a promising new vaccine strategy.

Keywords:

AI-guided RI-13 vaccine recombinant immunogens tuberculosis

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Last Updated: May 28, 2026

Expression of Exogenous Antigens in the Mycobacterium bovis BCG Vaccine via Non-genetic Surface Decoration with the Avidin-biotin System

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Adjuvant Activity of Mycobacterium paratuberculosis in Enhancing the Immunogenicity of Autoantigens During Experimental Autoimmune Encephalomyelitis

Adjuvant Activity of Mycobacterium paratuberculosis in Enhancing the Immunogenicity of Autoantigens During Experimental Autoimmune Encephalomyelitis

Published on: May 12, 2023

Area of Science:

Immunology
Vaccinology
Computational Biology

Background:

Tuberculosis (TB) presents a significant global health burden, necessitating the development of improved vaccines.
Current vaccine strategies require enhancement to effectively combat Mycobacterium tuberculosis (Mtb).

Purpose of the Study:

To employ an artificial intelligence (AI)-guided pipeline for predicting and prioritizing immunodominant Mtb epitopes.
To evaluate the immunogenicity and protective efficacy of novel vaccine candidates derived from AI-predicted epitopes.

Main Methods:

An AI framework predicted and prioritized Mtb epitopes, generating 72 recombinant immunogens.
Leading candidates RI-13, RI-20, and RI-31 were tested in zebrafish and mouse models (BALB/c, C57BL/6).
Protective efficacy was assessed via infection models, and immune responses (humoral and cellular) were analyzed.

Main Results:

RI-13, RI-20, and RI-31 significantly reduced pathology and bacterial load in zebrafish, outperforming existing antigen combinations.
DNA vaccination with these candidates in BALB/c mice decreased mycobacterial burden and lung damage.
All candidates induced robust immune responses; RI-13 showed superior immunogenicity with balanced Th1/Th2/Th17 profiles in C57BL/6 mice.

Conclusions:

RI-13, derived from Rv1174c, is identified as a potent next-generation TB vaccine candidate.
The study validates the effectiveness of AI-driven frameworks for designing and prioritizing novel TB immunogens.