A new antibiotic kills dangerous and resistant bacteria

A new antibiotic kills dangerous and resistant bacteria

Research is an important step in the development of new effective drugs.

A new antibiotic that can fight against resistant bacteria.

Antibiotics have long been considered a miracle cure for bacterial infections. However, many pathogens have evolved to withstand antibiotics over time and therefore the search for new drugs is becoming increasingly urgent. Researchers from University of Basel were part of an international team that used computational analysis to identify a new antibiotic and decipher its mode of action. Their research is an important step in the creation of new, powerful drugs.

The WHO calls the growing number of bacteria that are resistant to antibiotics a “silent pandemic.” The situation is aggravated by the fact that there have not been many new drugs on the market in recent decades. Even now, not all infections can be properly treated, and patients still risk harm from routine interventions.

New active substances are urgently needed to stop the spread of antibiotic-resistant bacteria. A significant discovery was recently made by a team headed by researchers from Northeastern University in Boston and Professor Sebastian Hiller from the Biocentrum of the University of Basel. The results of this research, which was an integral part of the “AntiResist” project of the National Center of Competence in Research (NCCR), were recently published in Natural microbiology.

Tough opponents

Researchers have discovered a new antibiotic, Dynobactin, using a computational screening method. This compound kills gram-negative bacteria, which include many dangerous and resistant pathogens. “The search for antibiotics against this group of bacteria is far from trivial,” says Hiller. “They are well protected by their double membrane and therefore offer little opportunity for attack. And over millions of years of evolution, bacteria have found numerous ways to render antibiotics harmless.”

Just last year, Hiller’s team deciphered the mode of action of the recently discovered peptide antibiotic Darobactin. The acquired knowledge is integrated into the screening process for new compounds. The researchers took advantage of the fact that many bacteria produce antibiotic peptides to fight each other. And that these peptides, unlike natural substances, are coded in the bacterial genome.

Fatal effect

“The genes for such peptide antibiotics share a characteristic feature,” explains first author Dr. Seyed M. Modaresi. “According to this feature, the computer systematically examined the entire genome of those bacteria that produce such peptides. That’s how we identified Dynobactin.” In their study, the authors showed that this new compound is extremely effective. Mice with life-threatening sepsis caused by resistant bacteria survived severe infection with Dynobactin.

By combining different methods, the researchers were able to solve the structure as well as the mechanism of action of Dynobactin. This peptide blocks the bacterial membrane protein BamA, which plays an important role in the formation and maintenance of the outer protective coat of bacteria. “Dynobactin sticks into BamA from the outside like a plug and prevents it from doing its job. So the bacteria die,” says Modaresi. “Although Dynobactin has no chemical similarities with the already known Darobactin, it still has the same target on the surface of the bacteria. We didn’t expect this at the beginning.”

Incentive for antibiotic research

At the molecular level, however, the scientists discovered that Dynobactin interacts differently with BamA than Darobactin. By combining certain chemical characteristics of the two, potential drugs could be further improved and optimized. This is an important step on the way to an effective drug. “Computerized screening will give new impetus to the identification of urgently needed antibiotics,” says Hiller. “In the future, we want to expand our search and investigate more peptides in terms of their suitability as antimicrobial drugs.”

Reference: “Computational Identification of Systemic Antibiotics for Gram-Negative Bacteria” by Ryan D. Miller, Akira Iinishi, Seyed Majed Modaresi, Byung-Kuk Yoo, Thomas D. Curtis, Patrick J. Lariviere, Libang Liang, Sangkeun Son, Samantha Nicolau, Rachel Bargabos, Madeleine Morrissette, Michael F. Gates, Norman Pitt, Roman P. Jakob, Parthasarathi Rath, Timm Maier, Andrey G. Malyutin, Jens T. Kaiser, Samantha Niles, Blake Karavas, Meghan Ghiglieri, Sarah EJ Bowman, Douglas C .Rees, Sebastian Hiller and Kim Lewis Natural microbiology.
DOI: 10.1038/s41564-022-01227-4

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