Finding Antimicrobial peptides in the global microbiome using machine learning

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Speaker: 

Luis Pedro Coelho is a group leader at the Centre for Microbiome Research at the Queensland University of Technology. His research focuses on using very large scale datasets of the global microbiome to understand microbial ecology. His group is also known for developing high-quality tools, most notably SemiBin for metagenomics binning. Before moving to Australia, Luis got a PhD from Carnegie Mellon University in the (US), worked at the EMBL in Germany, and at Fudan University in China.

Abstract:

Antimicrobial peptides (AMPs) are small peptides (operationally defined as those up to 100 amino acids) which kill or inhibit microbes. AMPs are produced by organisms from all domains of life, including by bacteria (which use it to compete with each other). They are of interest for drug development as they are less likely to lead to resistance than traditional antibiotics. However, the vast majority of AMPs are unknown. We have developed a machine learning approach to predict AMPs from metagenomic data. We have applied this approach to the global microbiome and found nearly one million novel AMPs. We tested 100 in vitro and found that 79 had antimicrobial activity. Subsequently, we tested the top candidates in vivo in a mouse model of infection and found that they were effective in reducing bacterial load at a level comparable to polymyxin B a clinically used antibiotic. This work demonstrates the power of machine learning to discover novel bioactive molecules from the global microbiome.

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Date And Time

2024-09-24 @ 05:00 AM (GMT)
 

Location

Online Event
 

Event Types

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