The innovative models being developed may enable antibiotics to accurately target specific bacteria in particular areas of the body. This advancement could significantly improve our fight against the increasingly serious issue of antibiotic resistance.
Recognizing the escalating concern of antibiotic resistance, researchers at the University of Virginia School of Medicine have created advanced computer models that could allow these vital medications to precisely target only certain bacteria in designated regions of the body.
Currently, antibiotics act indiscriminately, killing all bacteria they encounter. Their widespread usage has led to a rising number of resistant bacteria, jeopardizing one of medical science’s key defenses against illness.
Conversely, UVA’s new strategy aims to minimize bacterial exposure to antibiotics, thereby lowering the risk of developing resistance. This method also marks a significant advancement in precision medicine, which enables healthcare providers to customize treatments according to individual patient needs. Instead of prescribing broad-spectrum antibiotics that eliminate both harmful and beneficial bacteria, patients could receive targeted antibiotics that focus solely on the bacteria responsible for specific issues in targeted areas of the body.
“Many biomedical problems are incredibly intricate, and computer models are proving to be a powerful resource for addressing these challenges,” noted researcher Jason Papin, PhD, from UVA’s Department of Biomedical Engineering. “We are optimistic that our molecular network computer models of bacteria will aid in creating new infection treatment strategies.”
More Targeted Antibiotics
UVA’s novel method resulted from an extraordinary effort led by Papin, PhD student Emma Glass, and their team, in collaboration with Andrew Warren, PhD, from UVA’s Biocomplexity Institute. Together, they developed intricate computer models of every known human bacterial pathogen with enough genetic information accessible.
Glass then assessed all the models and pinpointed shared characteristics among the bacteria. This investigation revealed that bacteria residing in certain body regions, like the stomach, typically exhibited similar metabolic traits. Essentially, their environment significantly influences their behavior.
“Our computer models showed that stomach-dwelling bacteria exhibit distinct properties,” stated Glass. “These characteristics can guide the development of targeted antibiotics, which we hope will one day mitigate the emergence of resistant infections.”
The commonalities found among microbes in various locations could present vulnerabilities for harmful bacteria within our bodies. Continued research may enable healthcare providers to target specific bacterial types in designated areas, minimizing reliance on broad-spectrum antibiotics.
By applying their computer-modeling techniques, Papin and his team have successfully inhibited the growth of harmful stomach bacteria in laboratory tests. This outcome bodes well for the future applications of their modeling strategy.
“We still have a lot to explore to validate these concepts for different bacteria and infection types,” Papin indicated. “Nonetheless, this work highlights the tremendous potential of data science and computer modeling to address significant challenges in biomedical research.”
