How can computer models help medical professionals combat antibiotic resistance? This is what a recent study published in PLOS Biology hopes to address as a team of researchers from the University of Virginia (UVA) developed computer models that can be used to target specific genes in bacteria to combat antimicrobial resistant (AMR) bacteria. This study has the potential to help scientists, medical professionals, and the public better understand innovative methods that can be used to combat AMR with bacterial diseases constantly posing a risk to global human health.
For the study, the researchers used computer models to produce an assemblage of genome-scale metabolic network reconstructions (GENREs) diseases to identify key genes in stomach diseases that can be targeted with antibiotics to circumvent AMR in these bacterial diseases. The researchers validated their findings with laboratory experiments involving microbial samples and found that a specific gene was responsible for producing stomach diseases, thus strengthening the argument for using targeted antibiotics to combat AMR.
“Using our computer models we found that the bacteria living in the stomach had unique properties,” said Emma Glass, who is a PhD Candidate in Biomedical Engineering at UVA and lead author of the study. “These properties can be used to guide design of targeted antibiotics, which could hopefully one day slow the emergence of resistant infections.”
This study comes as deaths due to AMR continue to pose global human health risks. For example, a 2024 study published in The Lancet estimated that AMR was responsible for one million deaths annually between 1990 and 2021, and the Institute for Health Metrics and Evaluation at the University of Washington estimates that AMR will be responsible for approximately 39 million deaths between 2025 and 2050. Finally, the World Health Organization estimates that AMR could result in approximately $3.4 trillion in gross domestic product losses by 2030.
How will computer models help combat AMR in the coming years and decades? Only time will tell, and this is why we science!
As always, keep doing science & keep looking up!
Sources: PLOS Biology, EurekAlert!, The Lancet, University of Washington, World Health Organization