AI can help to identify potential ingredients for a gonorrhoea vaccine, new research findings suggest.
In a study published in the journal mBio, researchers identified two promising antigens as candidates for such a vaccine.
The scientists used an AI model called Efficacy Discriminative Educated Network, or EDEN, to identify the protective proteins.
The researchers also used EDEN to predict how well antigen combinations would reduce pathogenic bacterial populations of Neisseria gonorrhoeae, the microbe that causes gonorrhoea.
Researcher Sanjay Ram, M.D., at the University of Massachusetts Chan Medical School, said: “To the best of our knowledge, this correlation has not been shown before.”
The scientists tested the antigens identified by EDEN in lab and animal models.
In 2008, Andreas Holm Mattsson, in Denmark, mined published literature to assemble a large dataset of protective surface proteins from a variety of pathogenic bacteria.
The same year, Mattsson founded Evaxion, an AI immunology startup, and wanted to design an AI-based system that could identify vaccine targets in infectious microbes.
In the new study, Mattsson and his colleagues applied this new 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.
Mattsson said: “EDEN uses a feature like face recognition to understand the difference among proteins.”
Once the researchers had compiled the list, they sent it to Ram and Gulati in Massachusetts.
The group first tested combinations of two or three antigens in mice.
The 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.
In further experiments, immunised mice were infected with N. gonorrhoeae, and the vaccine decreased the bacterial burden.
Ram said: “That really was a surprise.
“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.”
Given the efficacy of the individual tests, the Evaxion researchers then combined the proteins into a single chimeric protein, which induced an immune response that similarly showed efficacy in lab and animal models.
The investigation also revealed a mechanism critical to clearance of N. gonorrhoeae infection by this vaccine candidate.
Whether such mechanisms of bacterial clearance occur in humans will have to be revealed in further studies.
The researchers are now using EDEN to look for vaccine candidate proteins in other pathogenic microbes, including several bacteria for which EDEN has predicted high efficacy in rodent models.
The scientists are also thinking about how to move beyond the promise of preclinical work and see if the same proteins are protective in the human body.
The team recently partnered with a South African biotechnology company to develop an experimental mRNA vaccine based on the antigens.