UC San Diego Researchers Develop Novel Detection Method for Antibiotics Resistance

UC San Diego Researchers Develop Novel Detection Method for Antibiotics Resistance

A recent article by UC San Diego researchers, published in the journal EBioMedicine, reported the development of a novel, rapid and efficient technique able to determine whether bacteria are resistant to antibiotics in only a few hours.

Pathogenic bacteria are a potential cause of human infections or aggravation of diseases including a variety of lung illnesses such as chronic obstructive pulmonary disease (COPD), pneumoconiosis, bronchiectasis, tuberculosis, and cystic fibrosis. Most of these infections are treated through the use of antibiotics, but bacteria are developing resistance to antibiotics much faster than the development of new anti-resistance therapies.

This results in a substantial number of infections, estimated to cause 2 million illnesses annually, according to the Centers for Disease Control and Prevention (CDC).

From a diagnostic viewpoint, because these infections could progress quickly, it is always critical for physicians to rapidly differentiate between drug resistant and drug sensitive strains, in order to prescribe the appropriate therapy. Furthermore, with the current methods, it often takes days for a physician to receive results related to bacterial resistance. This requires doctors to treat patients based on the assumptions that the infection is drug-resistant.

The new method developed at UC San Diego has two key advantages: It is fast, taking only a few hours for typical culture-based assays, and it does not require any detailed understanding of the bacterium that causes the infection or the genes responsible for the resistance.

The method is based on a previously developed technique in the lab of Kit Pogliano, Ph.D. a biology professor at UC San Diego who headed the research team. “Previously we developed a microscopy-based method that performs an autopsy on bacterial cells that allows us to determine how each cell died, and we have shown that this method can identify new antibiotics and help understand how these antibiotics work,” Pogliano said in a UC San Diego news release.

Researchers tested whether the method could be used to determine antibiotic susceptibility in Staphylococcus aureus strains, bacteria responsible for roughly 60 percent of the hospital-acquired infections, which can cause pneumonia.

“We tested to see if this method could be applied to antibiotic susceptibility testing,” Pogliano said. “Surprisingly, we not only found that our method was able to accurately differentiate sensitive S. aureus strains from resistant MRSA [methicillin-resistant S. aureus] strains, but that we were able to identify two subgroups of MRSA strains, one of which is susceptible to combinations of antibiotics that could be used in the hospital.

“We are excited by the accuracy and speed of this test, as well as by its unanticipated ability to identify these two types of MRSA infections, which would have been missed by other tests,” she said.

Joe Pogliano, Ph.D., also a professor of biology at UC San Diego, said, “Regardless of the type of bacterium, a healthy and growing bacterium looks different from a dead bacterium, so whenever we detect a difference in how the cells look, we know that the bacterium is sensitive to the antibiotic we have applied. When we combine careful culture conditions, cutting edge imaging methods and a detailed quantitative analysis, we can turn this simple approach into a reliable test.”

“Rapid and precise identification of antibiotic sensitivity patterns allows the most potent and effective drug to be administered,” said Victor Nizet, M.D., a professor of pediatrics and pharmacy. “Equally important, more specific antibiotic therapy can help preserve the normal bacteria living in our gut microbiome that play an important role in our health and immune system function.”

The researchers believe the novel method could be applied to various types of bacteria.

“Our new method worked surprising well at rapidly detecting antibiotic resistant strains of S. aureus,” said Diana Quach, a graduate student and lead author of the study. “We are now optimizing it to provide a more accurate test for other types of antibiotic resistant bacteria, such as Pseudomonas aeruginosa.”

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