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Antimicrobial resistant infections kill millions of people every year. They have the potential to take us back to the dark ages, when common infections such as urinary tract infections (UTIs) or pneumonia were deadly and untreatable. Antimicrobial resistance (AMR) occurs when germs that cause infections – bacteria, viruses or fungi – develop ways to evade the drugs used to treat them. (Read this also | Superbugs pose a greater threat than COVID-19. Here’s everything you need to know about antimicrobial resistance,
Overuse of antibiotics in places such as poultry farms and health care clinics has become a major cause of AMR.
The good news is that major scientific efforts are making significant progress in the fight against AMR.
“The problem of antibiotic resistance is still not solved, but great progress has been made in better understanding and improved methods for discovering new antibiotics. [which overcome antimicrobial resistance]said Luis Pedro Coelho, a computational biologist at the Queensland University of Technology in Australia.
Coelho led a new study, published in the journal Cell, that presents a massive database of nearly one million potential antibiotic compounds.
Sebastian Hiller, a structural biologist at the University of Basel in Switzerland, who was not involved in the research, said the study is proof that we can be optimistic about AMR: “This is just one example of ongoing research that shows that our scientific capabilities to fight superbugs are enormous,” Hiller told DW.
Use of AI to discover new antibiotics
The study used machine learning to search for potential antibiotic agents in a vast database of microorganisms living in environments such as soil, sea, human and animal gut.
“In these environments, bacteria are constantly at war with each other, and to do this they use warfare tools called peptides, which they fire at other bacteria and kill them,” Hiller said. The researchers scoured this space for antibiotic peptides and found some hidden gems.
The algorithm sorted through billions of possible protein sequences and selected the top candidates with predicted antimicrobial activities.
In total, 863,498 new antimicrobial peptides were predicted, more than 90% of which had never been described before.
Coelho said all of the peptides have the same general mechanism for killing bacteria — by destroying the cell membranes that protect bacteria from the environment.
“We have also observed that some peptides are more effective against certain bacteria than others, but we cannot yet predict why this happens, or whether [say] “This is a study that shows which peptide will work against which bacteria,” Coelho told DW.
Peptide antibiotics are effective against bacterial infections
To find out which of these peptides might be useful as antibiotics, the researchers synthesized 100 peptides and tested them against 11 disease-causing bacteria in laboratory dishes.
They found that 79 peptides destroyed bacterial membranes and 63 peptides specifically targeted antibiotic-resistant bacteria, such as Escherichia coli (E. coli) and Staphylococcus aureus.
The researchers also tested these compounds on mice with infected skin abscesses, but only three peptides showed antimicrobial effects in the living organism.
“This suggests that their efficacy may be limited in the organism. Nevertheless, this is a remarkable result, and these compounds could reduce the severe toxicity side effects of last-resort antibiotics such as polymyxins,” said Saed Majed Modaressi of the University of Basel in Switzerland, who was not involved in the study.
Are these reasons to be optimistic about the fight against AMR?
The authors published their dataset with open access, giving other scientists the opportunity to review the 863,498 peptides and develop antibiotics with specific uses in mind.
For example, scientists could adapt antibiotic properties to minimize the impact on “friendly” bacteria in the human gut. Many antibiotics in use are known to destroy beneficial gut microbiota, leading to health problems and allowing the body to become dominated by potentially deadly microbes.
Scientists can also use this dataset to create antibiotics that bacteria do not develop resistance to, which would greatly help in the long-term fight against AMR.
Modaressi said the new study shows that artificial intelligence is playing an important role in the scientific fight against AMR and that “the application of machine learning has accelerated the process of discovering new antibiotics.”
He said the peptides discovered in this latest study were one type of antimicrobial agents, and the same techniques could be used to discover many other types of antibiotics, including bacteriophages.
Hiller said that although there are many reasons to be optimistic about the scientific fight against AMR, the next big challenge is to develop new antibiotic agents that are commercially viable.
“We only use new antibiotics when old antibiotics don’t work. This is good because it prevents bacteria from developing resistance to them, but it means they are not economically viable,” Hiller said.
Hiller said health organizations and governments are working on ways to make antibiotic commercialization more viable so they can tap the vast pool of potential antibiotics discovered by scientists.
Source:
Discovery of antimicrobial peptides in the global microbiome with machine learning, published in Cell (2024) by Santos-Junior et al.
Antimicrobial Resistance Collaborator. The global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Published in The Lancet (2022)
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