New Computer Models Open Door to Far More Targeted Antibiotics

With antibiotic resistance a growing problem, University of Virginia School of Medicine researchers have developed cutting-edge computer models that could give the disease-fighting drugs a laser-like precision to target only specific bacteria in specific parts of the body.

As it stands, antibiotics kill bacteria indiscriminately. Because the drugs are used so widely, increasing numbers of dangerous bugs are growing resistant, threatening one of modern medicine’s most important weapons against disease.

UVA's new approach, on the other hand, would dramatically limit how often bacteria are exposed to antibiotics, reducing the chance they could become resistant to antibiotics. Further, the approach would represent a significant step forward for precision medicine, allowing doctors to better tailor treatments to individual patients’ needs. Instead of taking an antibiotic that kills bacteria regardless of whether helpful or harmful, patients could be given antibiotics that target specific bacteria causing a specific problem in a specific area of the body.

"Many biomedical challenges are incredibly complex, and computer models are emerging as a powerful tool for tackling such problems," said researcher Jason Papin, PhD, of UVA's Department of Biomedical Engineering. "We're hopeful that these computer models of the molecular networks in bacteria will help us develop new strategies to treat infections."

UVA's new approach was made possible by a herculean effort by Papin, PhD student Emma Glass and their collaborators. Working with Andrew Warren, PhD, of UVA's Biocomplexity Institute, the researchers in Papin’s lab developed sophisticated computer models of every human bacterial pathogen with sufficient genetic information available.

Glass then analyzed all those models and identified shared traits among the bacteria. This analysis yielded the discovery that bacteria in certain parts of the body, such as the stomach, tended to share metabolic properties. Basically, where they live shapes how they function.

"Using our computer models we found that the bacteria living in the stomach had unique properties," Glass said. "These properties can be used to guide design of targeted antibiotics, which could hopefully one day slow the emergence of resistant infections."

The shared similarities among the microbes in different locales could be the Achilles' heel for harmful bacteria in our bodies. With further research, doctors may be able to target specific types of bacteria in specific areas, reducing the need for broad-spectrum antibiotics.

Putting their computer-modeling approach to the test, Papin and his team have already found that they could inhibit the growth of harmful stomach bugs in lab experiments. That’s a promising sign for the future potential of their computer-modeling approach.

"We still have much to do to test these ideas for other bacteria and types of infections," Papin said. "but this work shows the incredible promise of data science and computer modeling for tackling some of the most important problems in biomedical research."

Glass EM, Dillard LR, Kolling GL, Warren AS, Papin JA.
Niche-specific metabolic phenotypes can be used to identify antimicrobial targets in pathogens.
PLoS Biol. 2024 Nov 18;22(11):e3002907. doi: 10.1371/journal.pbio.3002907

Most Popular Now

Unlocking the 10 Year Health Plan

The government's plan for the NHS is a huge document. Jane Stephenson, chief executive of SPARK TSL, argues the key to unlocking its digital ambitions is to consider what it...

Alcidion Grows Top Talent in the UK, wit…

Alcidion has today announced the addition of three new appointments to their UK-based team, with one internal promotion and two external recruits. Dr Paul Deffley has been announced as the...

AI can Find Cancer Pathologists Miss

Men assessed as healthy after a pathologist analyses their tissue sample may still have an early form of prostate cancer. Using AI, researchers at Uppsala University have been able to...

AI, Full Automation could Expand Artific…

Automated insulin delivery (AID) systems such as the UVA Health-developed artificial pancreas could help more type 1 diabetes patients if the devices become fully automated, according to a new review...

How AI could Speed the Development of RN…

Using artificial intelligence (AI), MIT researchers have come up with a new way to design nanoparticles that can more efficiently deliver RNA vaccines and other types of RNA therapies. After training...

MIT Researchers Use Generative AI to Des…

With help from artificial intelligence, MIT researchers have designed novel antibiotics that can combat two hard-to-treat infections: drug-resistant Neisseria gonorrhoeae and multi-drug-resistant Staphylococcus aureus (MRSA). Using generative AI algorithms, the research...

AI Hybrid Strategy Improves Mammogram In…

A hybrid reading strategy for screening mammography, developed by Dutch researchers and deployed retrospectively to more than 40,000 exams, reduced radiologist workload by 38% without changing recall or cancer detection...

Penn Developed AI Tools and Datasets Hel…

Doctors treating kidney disease have long depended on trial-and-error to find the best therapies for individual patients. Now, new artificial intelligence (AI) tools developed by researchers in the Perelman School...

New Training Year Starts at Siemens Heal…

In September, 197 school graduates will start their vocational training or dual studies in Germany at Siemens Healthineers. 117 apprentices and 80 dual students will begin their careers at Siemens...

Are You Eligible for a Clinical Trial? C…

A new study in the academic journal Machine Learning: Health discovers that ChatGPT can accelerate patient screening for clinical trials, showing promise in reducing delays and improving trial success rates. Researchers...

New AI Tool Addresses Accuracy and Fairn…

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms...

Global Study Reveals How Patients View M…

How physicians feel about artificial intelligence (AI) in medicine has been studied many times. But what do patients think? A team led by researchers at the Technical University of Munich...