A team of researchers, led by one of Indian-origin, used artificial intelligence (AI) to identify key ingredients of a vaccine for antibiotic-resistant gonorrhoea — a sexually transmitted bacterial infection that affects more than 80 million people worldwide every year.

Gonorrhoea has become resistant to almost all known antibiotics. That makes it notoriously difficult to treat, but if left untreated, the infection could lead to serious or even fatal complications. It also increases a person’s risk of contracting HIV.

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In the study published in mBio journal, researchers reported the identification of two promising antigens as candidates for a gonorrhoea vaccine.

The researchers used an AI model called Efficacy Discriminative Educated Network, or EDEN, to identify the protective proteins.

They also used EDEN to generate scores that accurately predicted how well antigen combinations would reduce pathogenic bacterial populations of Neisseria gonorrhoeae, the microbe that causes gonorrhoea.

“To the best of our knowledge, this correlation has not been shown before,” said infectious disease researcher Sanjay Ram, at the University of Massachusetts Chan Medical School.

For the study, the team applied the AI model to the proteomes of 10 clinically-relevant strains of Neisseria gonorrhoeae to predict a set of bacterial proteins that, in a vaccine, could help teach the body’s immune system to recognise and fend off the bacteria.

The team tested and validated the vaccine candidates in mouse models. The group first tested combinations of two or three antigens in mice.

That analysis identified two proteins involved in cell division as promising candidates, neither of which were previously known to be exposed on the surface of the cell.

In lab experiments, blood samples taken from mice immunised with these two proteins killed bacteria from multiple strains of gonorrhoea in vitro. Those findings lined up with EDEN’s predictions.

In additional experiments, immunised mice were infected with N. gonorrhoeae, and the vaccine decreased the bacterial burden.

“That really was a surprise,” Ram said.

“Nobody would have predicted that these two proteins that were believed not to be surface exposed would work in vaccines, and other researchers reacted with scepticism.”

The team is now thinking about how to move beyond the promise of preclinical work and see if the same proteins are protective in the human body. They recently partnered with a South African biotechnology company to develop an experimental mRNA vaccine based on the antigens.