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New Study Identifies Genetic Signature for Predicting Antibiotic Resistance
The escalating crisis of antibiotic resistance poses a serious threat to global public health, resulting in over a million fatalities each year. The World Health Organization predicts that by 2050, deaths resulting from antibiotic resistance may exceed those caused by cancer and heart disease, as more bacteria develop mechanisms to evade the effects of antibiotics.
An innovative study conducted by researchers at Tulane University has unveiled a distinctive genetic signature in certain bacteria, enabling predictions about their likelihood of developing antibiotic resistance. This research, published in Nature Communications, has the potential to accelerate the identification of targeted treatments that may be more effective against these challenging and often lethal pathogens.
Lead researcher Kalen Hall, PhD, noted the significance of this discovery, stating, “If we identify this genetic pattern during genome sequencing, we can anticipate the bacteria will become drug-resistant if treated.” Hall conducted this research as part of his studies at Tulane University School of Medicine, from which he graduated in 2024.
The focal point of this research is Pseudomonas aeruginosa, a notorious bacterium known for its multidrug-resistant capabilities and frequent infections in hospital settings. This bacterium is particularly vulnerable to issues in a specific DNA repair pathway, a defect that can lead to swift mutations contributing to the emergence of drug resistance.
Utilizing a method typically reserved for cancer research, the research team analyzed bacterial genomes for mutational signatures to map genetic alterations. They discovered a unique pattern tied to these DNA repair deficiencies, which accurately forecasts a bacterium’s potential to develop resistance to antibiotics.
“It’s essentially a fingerprint that’s able to predict the presence of potential multidrug-resistant bacteria,” remarked Zac Pursell, PhD, an associate professor of biochemistry and molecular biology at Tulane University School of Medicine.
A major factor in the acquisition of resistance is the treatment of bacteria with ineffective antibiotics, highlighting the critical need for appropriate treatment strategies. Alarmingly, findings indicate that bacteria can develop resistance even to antibiotics that were not part of the initial treatment.
Hall pointed out, “Over 50% of prescribed antibiotics are either not needed or are inappropriate treatments, and offering the wrong antibiotic only fosters further resistance.” This underlines the importance of selecting the correct antibiotic to mitigate resistance development.
The same DNA sequencing advancements that facilitate the identification of bacterial genetic “fingerprints” also assist clinicians in pinpointing effective treatment strategies. The researchers successfully identified different resistance pathways and tested combinations of antibiotics that specifically target these pathways, preventing the bacteria from gaining resistance to drugs.
Although the research is in preliminary stages, the potential development of a diagnostic tool could significantly limit antibiotic overuse and allow for more targeted treatments of bacterial infections. Hall has since taken on the role of CEO and cofounder of Informuta Inc., a startup based in San Diego focused on creating a machine learning model that analyzes bacterial samples to forecast antibiotic resistance trends.
“Nothing like this currently exists, and it could dramatically change outcomes for a wide range of patients. Each year, antibiotic resistance worsens,” Hall expressed. “I believe that effective antibiotic stewardship and precise diagnostics are vital components of addressing this critical issue.”
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