Gonorrhea, a pervasive sexually transmitted bacterial infection, has been a medical challenge for decades, with antibiotic resistance complicating treatment. Left untreated, gonorrhea can lead to severe health consequences and increase the risk of contracting other diseases, including HIV. However, recent research has shown a promising path forward in the form of artificial intelligence (AI). In this study, AI helped identify key vaccine components, paving the way for a potential gonorrhea vaccine (Figure1 ).
This research harnessed an AI model named Efficacy Discriminative Educated Network (EDEN) to pinpoint potential antigens for a gonorrhea vaccine. These antigens play a vital role in teaching the immune system to recognize and combat the bacteria causing gonorrhea. EDEN not only identified these antigens but also generated scores that accurately predicted the antigens’ effectiveness in reducing bacterial populations of Neisseria gonorrhoeae, the culprit behind the infection.
To validate their findings, researchers applied EDEN to the proteomes of ten clinically relevant Neisseria gonorrhoeae strains. This predictive approach yielded a list of bacterial proteins with the potential to be included in a vaccine. The research team then put these candidates to the test in mouse models.
The study first explored combinations of two or three antigens in mice, and the results were intriguing. It unveiled two proteins associated with cell division that had not previously been known to be exposed on the bacterial cell surface. Blood samples from mice immunized with these proteins could kill bacteria from multiple gonorrhea strains, aligning with EDEN’s predictions.
The research team’s success extended beyond individual tests. By merging the two proteins into a single chimeric protein, they induced an immune response that demonstrated efficacy in both laboratory and animal models. Furthermore, the study uncovered a pivotal mechanism in the clearance of Neisseria gonorrhoeae infection by this vaccine candidate.
While the results are promising, further studies are necessary to determine whether these mechanisms hold in human subjects. The discovery stands as a beacon of hope in the battle against gonorrhea, highlighting the potential of AI-driven research in the pursuit of novel vaccines.
Journal article: Gulati, S., et al., 2023. Preclinical efficacy of a cell division protein candidate gonococcal vaccine identified by artificial intelligence. mBio.
Summary by Stefan Botha