Rutgers Health research has discovered why a relatively new tuberculosis (TB) antibiotic works against multidrug-resistant strains, potentially inspiring better treatments and drug development strategies.

THE study scientists from Rutgers Medical School of New Jersey and other institutions have found that deficiencies in a key enzyme make tuberculosis bacteria that are resistant to older antibiotics more vulnerable to the new antibiotic bedaquiline.

“Understanding how a drug works could help us design new, more effective molecules and prevent bacteria from becoming resistant,” said Jason Yangassistant professor in the School of Medicine and lead author of the study.

Tuberculosis continues to be among the deadliest infectious diseases in the world, killing more than 1.5 million people each year. Multidrug-resistant TB, defined as disease resistant to at least two first-line drugs, poses a growing threat to global TB control efforts.

Approved in 2012 by the U.S. Food and Drug Administration (FDA), bedaquiline was the first new anti-tuberculosis drug in more than 40 years. It works well against multidrug-resistant strains of tuberculosis, but the mechanisms behind its effectiveness were not fully understood.

The findings could help boost tuberculosis treatment and drug development. Understanding these vulnerabilities could inspire strategies to make bedaquiline more effective, potentially allowing lower doses or shorter treatment durations. It could also guide the development of new drugs or drug combinations.

“We can prevent resistance by developing other drugs that improve the effectiveness of bedaquiline,” Yang said. For example, combining bedaquiline with another antibiotic called isoniazid appears to prevent the development of resistance to either drug, he said.

Although tuberculosis is primarily a problem in developing countries, it remains a global concern. However, outbreaks still occur in the United States. For example, there was around 500 cases in New York last year.

“TB itself is a ridiculously big problem right now, as is antibiotic resistance,” Yang said. report in the Lancet projecting that if antibiotic resistance gets worse, then we won’t be able to treat infections, and if we can’t treat infections, much of modern medicine will die. We couldn’t even do surgery because surgical infections would kill the patients.

The researchers of the study, published in Natural communications, examined both clinical isolates and laboratory strains of Mycobacterium tuberculosis, the bacteria that causes tuberculosis. The researchers used a systems biology approach, combining genetic studies, RNA sequencing and metabolic modeling.

They found that deficiencies in an enzyme called catalase peroxidase, encoded by a gene called katG, make drug-resistant tuberculosis more sensitive to bedaquiline. Mutations in katG are the most common cause of resistance to the first-line anti-tuberculosis drug isoniazid.

This catalase deficiency causes several changes that make the bacteria more vulnerable to the new drug. It increases the accumulation of reactive oxygen species and susceptibility to DNA damage while altering transcriptional programs that regulate bacterial biology and repressing multiple biosynthetic pathways.

“We discovered previously unreported mechanisms,” Yang said. “We show that these are the different types of vulnerabilities in the biology or physiology of TB that occur specifically in drug-resistant TB. »

The research also highlights potential avenues for repurposing existing drugs. Researchers found that trimethoprim and sulfamethoxazole, antibiotics used to treat other diseases, were also effective against drug-resistant strains of tuberculosis with catalase deficiency.

The new paper was part of a related duo that appeared in Natural communications from the same team. THE second article used whole-genome CRISPRi screening to identify drug vulnerabilities in a treatment-resistant disease strain.

Looking ahead, Yang and his colleagues are pursuing several lines of research building on these findings.

“We are developing machine learning tools to understand other changes that occur in the biology or physiology of TB that are caused by other types of drug resistance,” Yang said. “We are extending these machine learning models to see if we can extrapolate results from a laboratory directly to patients and clinical strains.”

This could potentially lead to personalized medical approaches for tuberculosis, tailoring treatments based on the specific characteristics of the infecting strain.

The team is also developing synthetic biology tools to study how TB evolves drug resistance and how this process could be targeted to prevent resistance to bedaquiline and any new drugs developed.