New research has uncovered a distinct genetic marker in bacteria that can forecast their chances of becoming resistant to antibiotics. This discovery can significantly assist in swiftly determining targeted treatments that are more effective against dangerous, treatment-resistant infections.
Antibiotic resistance poses a worldwide public health emergency, causing over a million fatalities each year. The World Health Organization projects that by 2050, it could eclipse cancer and heart disease as the primary cause of death, due to an increasing number of bacteria developing defenses against the medications aimed at eliminating them.
Researchers at Tulane University have pinpointed a unique genetic marker in bacteria that can indicate their likelihood of developing antibiotic resistance. This insight, detailed in a study published in Nature Communications, could enable researchers to more rapidly identify targeted treatments that effectively combat these lethal, resistant microbes.
“When we observe this genetic pattern in a genome sequence, we can anticipate that it will become resistant to the treatment,” explained Kalen Hall, PhD, the lead author who conducted this research before graduating from Tulane University School of Medicine in 2024.
The study primarily focuses on Pseudomonas aeruginosa, a bacterium known for its multidrug resistance and frequent role as an infection source in hospitals. This type of bacteria commonly exhibits shortcomings in a particular DNA repair mechanism, which is known to lead to rapid mutations, thereby heightening the risk of developing drug resistance.
By examining bacterial genomes for specific mutational markers—an approach often applied in cancer research to analyze genetic alterations in tumors—the research team identified a unique pattern linked to these DNA repair deficiencies, which could reliably forecast the bacteria’s potential to gain antibiotic resistance.
“It’s essentially a fingerprint that predicts the presence of potentially multidrug-resistant bacteria,” stated Zac Pursell, PhD, an associate professor of biochemistry and molecular biology at Tulane University School of Medicine.
Bacteria can only develop resistance after being treated with an antibiotic that is unable to eradicate them, emphasizing the necessity of selecting the right treatment method. Moreover, the results indicate that bacteria may develop resistance to medications that were not part of the initial treatment.
“More than 50% of antibiotics prescribed may be unnecessary or incorrectly chosen, and administering an inappropriate antibiotic fosters increasing resistance,” Hall remarked.
Crucially, the same DNA sequencing techniques used to identify these bacterial “fingerprints” can also highlight potential treatment targets for healthcare providers. The researchers successfully pinpointed distinct pathways of resistance and utilized specific combinations of antibiotics to combat these pathways, hindering the bacteria’s ability to become resistant.
While these findings are still preliminary, the successful development of a diagnostic tool could lead to a decrease in antibiotic overuse and facilitate more precise therapies for bacterial infections. Hall is currently the CEO and co-founder of Informuta Inc., a startup based in San Diego that plans to create a machine learning model to analyze bacterial samples and predict antibiotic resistance development.
“There’s nothing currently available like this, and it could revolutionize treatment for many patient groups. Year by year, antibiotic resistance continues to worsen,” Hall asserted. “I think effective antibiotic management and precise diagnostics are crucial components of a long-term solution.”
