In the fight against antibiotics, bacteria are gaining the upper hand and are becoming more and more resistant to antibiotic attack. but new Paper published in plos biology It suggests that computer models could contribute to creating more targeted antibiotics while reducing the risk of increasing antibiotic resistance in bacteria.
According to the paper’s authors, once produced, these laser-like antibiotics can attack specific bacteria in specific areas of our bodies, reducing overall contact with antibiotic drugs and reducing the likelihood that bacteria throughout our bodies will become resistant to them. Reduce it. .
“Many biomedical problems are incredibly complex, and computer models are emerging as powerful tools for solving those problems,” said study author Jason Papin, professor of biomedical engineering at the University of Virginia. press release. “We expect that these computer models of the molecular networks of bacteria will help develop new strategies for treating infections.”
antibiotic adaptation
When we take antibiotics, the bacteria in our bodies have the opportunity to: adaptAntibiotic resistance develops. Today, with the widespread use of antibiotics in modern medicine, dangerous bacteria are increasingly developing antibiotic resistance, weakening the ability of these drugs to prevent disease.
To solve this problem, the research team created a series of computer models of dangerous bacteria and then analyzed the models to identify shared metabolic properties. Their analysis revealed a set of metabolic properties that could be used to create custom antibiotics, targeting specific bacteria in specific body parts rather than targeting bacteria throughout the body.
By inhibiting contact with antibiotics, these targeted treatments can replace non-targeted treatments that attack a broad range of bacteria.
Read more: Antibiotic-resistant bacteria: What they are and how scientists fight them
Alternative to broad-spectrum bacterial treatment
Using a type of computer model called GENRE (genome-scale metabolic network reconstruction), the researchers discovered that certain metabolic traits are common to certain bacteria, such as stomach bacteria.
“Using computer models, we discovered that the bacteria living in the stomach have unique properties,” study author Emma Glass, a biomedical engineering student at the University of Virginia, said in a press release. “These properties could one day be used to guide the design of targeted antibiotics that could slow the emergence of resistant infections.”
Testing this approach in the laboratory, the study authors showed that targeted antibiotics can inhibit the survival and spread of stomach bacteria, indicating its potential as a precision medicine treatment.
“There is still a lot of work to be done to test these ideas on other bacteria and types of infections,” Papin said in a press release. “But this study demonstrates the incredible potential of data science and computer modeling to solve the most important problems in biomedical research.”
Read more: COVID-19 and drug-resistant superbugs are a scary combination
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Sam Walters is a journalist for Discover who covers a variety of topics, including archeology, paleontology, ecology, and evolution. Before joining the Discover team as an assistant editor in 2022, Sam studied journalism at Northwestern University in Evanston, Illinois.
