A New Way to Track Evolving Superbugs in Real Time

Superbugs are almost like shapeshifters that can live inside your body. As medicines and the immune system try to destroy them, superbugs fight back. They change form, gaining resistance to drugs and defenses.

A new study in Nature Communications shows superbugs evolve during infection. Real-time tracking may help doctors choose more targeted treatments. Researchers focused on Staphylococcus aureus, a common bacterium carried by 30% of people.

S. aureus is usually harmless, but it turns dangerous when it spreads. Once it infects the bloodstream, it can resist several antibiotics. This study shows how tracking its evolution during care may improve treatment.

How Did Researchers Track Superbug Mutations in Real Time?

The study’s researchers analyzed 60 bacterial strains from 11 patients. All patients had severe S. aureus infections that resisted treatment. The team collected samples at the start and during treatment failure.

They looked for signs of adaptive evolution in each strain. These are mutations that help bacteria survive antibiotic pressure. One-third of strains showed new mutations in known resistance genes.

The team identified changes that let bacteria survive drugs during infection. This approach mirrors cancer genomics, where doctors track mutations in tumors. Now, bacterial genomics could be used in real-time clinical care.

How Might Bacterial Genomics Help Explain Antibiotic Treatment Failures?

Bacterial genomics is rarely used in real-time clinical settings. Unlike cancer or human genomics, turnaround times are slower. There is also limited data on its value during active treatment.

Still, whole-genome sequencing (WGS) can reveal each patient’s bacterial strain. This becomes especially helpful when superbug treatments fail. Persistent and recurrent infections often involve bacteria that have mutated during treatment.

By tracking adaptive evolution, scientists can spot these genetic changes. Doctors already use this approach in cancer to adjust treatments as tumors evolve. A similar model could improve care for stubborn bacterial infections.

Studies have shown these mutations in S. aureus and other bacteria. These include Mycobacterium tuberculosis, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Acinetobacter baumannii. Mutations in these strains drive resistance and help bacteria evade the immune system.

How Does Real-Time Genomic Tracking Reveal Bacterial Evolution in Failed Treatments?

The research team proposed a four-step method to study treatment failure. First, they checked if infections came from the same or new strains. New strains meant reinfection or superinfection needing different treatment plans.

Second, they used genome data and lab tests to find hidden resistance. Third, they analyzed if bacteria had mutated inside the patient. Adaptive mutations help bacteria survive despite antibiotic use.

Finally, if no mutations were found, doctors focused elsewhere. They considered increasing antibiotic doses or removing infection sources.

Doctors were also asked to predict if adaptive mutations had occurred. They were correct in only two of four cases. This shows clinical data alone can’t reliably detect bacterial evolution.

Conclusion

Superbugs can evolve inside the body during treatment. Real-time genomic tracking can help doctors respond to these changes faster. With more research, this method could improve care for antibiotic-resistant infections.

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Logan Hamilton is a health and wellness freelance writer for hire. He’s passionate about crafting crystal-clear, captivating, and credible content that elevates brands and establishes trust. When not writing, Logan can be found hiking, sticking his nose in bizarre books, or playing drums in a local rock band. Find him at loganjameshamilton.com.