Exploring next-gen antibiotics in our environment

An international research team has identified nearly a million potential antibiotic sources in nature, marking a significant advancement in the fight against antimicrobial resistance (AMR). The study, published in the journal Cell, was led by computational biologist Associate Professor Luis Pedro Coelho from Queensland University of Technology (QUT). Utilizing machine learning, the team pinpointed 863,498 antimicrobial peptides—small molecules capable of killing or inhibiting infectious microbes.

The discovery comes at a crucial moment as the world grapples with the rising threat of superbugs that are resistant to existing antibiotics. According to Professor Coelho, who conducts research at the QUT Centre for Microbiome Research, the need for new antibiotic discovery methods is urgent. AMR is recognized as a major public health threat, responsible for 1.27 million deaths annually. Projections indicate that without effective intervention, AMR could result in up to 10 million deaths per year by 2050.

The innovative use of artificial intelligence aims to harness the global microbiome’s potential to drive research toward better public health outcomes. The team validated their machine learning predictions by synthesizing 100 laboratory-made peptides and testing them against clinically important pathogens. The results were promising: 79 of these peptides disrupted bacterial membranes, while 63 specifically targeted antibiotic-resistant bacteria such as Staphylococcus aureus and Escherichia coli.

In preclinical trials involving mice, some of the peptides demonstrated remarkable efficacy. Notably, two peptides reduced bacterial counts by up to four orders of magnitude. The peptide treatment outcomes were comparable to those achieved with polymyxin B, a commercially available antibiotic used to treat severe infections like meningitis, pneumonia, sepsis, and urinary tract infections.

To achieve these findings, the researchers analyzed over 60,000 metagenomes. These metagenomes, representing the genetic material of over one million organisms, were sourced from diverse environments worldwide, including marine and soil habitats, as well as the guts of humans and animals. This extensive genetic analysis culminated in the creation of AMPSphere—a comprehensive, publicly accessible database of novel peptides available for new antibiotic discovery.

Professor Coelho’s research falls under his ARC Future Fellowship and involved collaboration with several prestigious institutions, including the Cesar de la Fuente laboratory at the University of Pennsylvania, Fudan University, the European Molecular Biology Laboratory, and APC Microbiome Ireland.

This groundbreaking research not only opens new avenues for antibiotic discovery but also emphasizes the potential of integrating artificial intelligence with microbiome research to address one of the most pressing health challenges of our time. By turning to nature and leveraging advanced technologies, the scientific community hopes to develop innovative solutions that can mitigate the growing threat of antimicrobial resistance and improve global health outcomes.