New test shows which antibiotics actually work
Drugs that act against bacteria are mainly assessed based on how well they inhibit bacterial growth under laboratory conditions. A critical factor, however, is whether the active substances actually kill the pathogens in the body. Researchers at the University of Basel have presented a new method for measuring how effectively antibiotics kill bacteria.
09 January 2026 | Angelika Jacobs
Antibiotic-resistant bacteria are one of the biggest health problems of our time. Due to mutations, bacteria are increasingly resisting the effects of common drugs, making these infections increasingly difficult to treat.
But even without resistance, bacteria are sometimes able to withstand antibiotics, especially if the bacteria are in a dormant state. Although they do not reproduce when in this state, they are not killed by the antibiotics either. This allows the bacteria to wake up and start growing again at a later time, for example after antibiotic therapy has been stopped. Particularly in the case of tuberculosis and other complex infections, which take many months to treat, selecting drugs that kill the bacteria and completely sterilize the infection is crucial.
Previous laboratory tests mainly reported whether a drug stopped bacteria from growing – not whether the bacteria actually died. Researchers led by Dr. Lucas Boeck from the Department of Biomedicine at the University of Basel and University Hospital Basel have developed a new method to better predict treatment success. They have described this new method in the scientific journal Nature Microbiology.
Filming the fate of individual bacteria
The method, which the researchers call “antimicrobial single-cell testing,” is based on microscopic imaging of millions of individual bacteria under thousands of different conditions. “We use it to film each individual bacterium over several days and observe whether and how quickly a drug actually kills it,” explains Lucas Boeck. This makes it possible to measure precisely what proportion of the bacterial population is eliminated by the treatment and how efficiently.
To demonstrate their method, the research team tested 65 combination therapies on the tuberculosis pathogen Mycobacterium tuberculosis. The researchers also tested the method on bacterial samples from 400 patients with a different complex lung infection triggered by Mycobacterium abscessus, which is related to the tuberculosis pathogen.
Differences were observed firstly between different therapies and secondly between different bacterial strains in different patients. Experts call the latter antibiotic tolerance. Subsequent analyses revealed that certain genetic characteristics are responsible for how well the bacteria can “sit out” the antibiotic treatment.
“The better bacteria tolerate an antibiotic, the lower the chances of therapeutic success are for the patients,” says Lucas Boeck, summarizing the results. Compared with data from clinical studies and animal models, the results of antimicrobial single-cell testing provided a very good reflection of how well the different therapeutic agents eradicate infections.
Benefits for patients and drug development
The new method has so far been used as a research tool, but it could also be used in clinics and industry in the future. It could one day be beneficial both for patients and for drug development in a number of ways, explains Lucas Boeck. “Our test method allows us to tailor antibiotic therapies specifically to the bacterial strains in individual patients.” He adds that a better understanding of the underlying genetics could one day enable even simpler and quicker antibiotic tolerance tests to be performed and could also help improve estimates of the efficacy of new drugs during their development.
"Last but not least, the data can help researchers to better understand the survival strategies of pathogens and thus lay the foundation for new, more effective therapeutic approaches,” says Boeck.
Original publication
Alexander Jovanovic, Frederick K. Bright, Ahmad Sadeghi et al.
Large-scale testing of antimicrobial lethality at single-cell resolution predicts mycobacterial infection outcomes
Nature Microbiology (2026), doi: 10.1038/s41564-025-02217-y