Discovery of Antimicrobial Lysins from the “Dark Matter” of Uncharacterized Phages Using Artificial Intelligence

The rapid rise of antibiotic resistance and slow discovery of new antibiotics have threatened global health. While novel phage lysins have emerged as potential antibacterial agents, experimental screening methods for novel lysins pose significant challenges due to the enormous workload. Here, the fi...

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Bibliographic Details
Published in:Advanced science 2024-08, Vol.11 (32), p.e2404049-n/a
Main Authors: Zhang, Yue, Li, Runze, Zou, Geng, Guo, Yating, Wu, Renwei, Zhou, Yang, Chen, Huanchun, Zhou, Rui, Lavigne, Rob, Bergen, Phillip J., Li, Jian, Li, Jinquan
Format: Article
Language:English
Subjects:
antibacterial protein
antibiotic resistance
Antibiotics
Artificial intelligence
Bacteria
Bacterial infections
Dark matter
Drug resistance
Genomes
high‐throughput screening
infectious diseases
Kinases
Machine learning
Mining
Pathogens
phage lysin
prophage
Proteins
Software
stacking model
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Summary:The rapid rise of antibiotic resistance and slow discovery of new antibiotics have threatened global health. While novel phage lysins have emerged as potential antibacterial agents, experimental screening methods for novel lysins pose significant challenges due to the enormous workload. Here, the first unified software package, namely DeepLysin, is developed to employ artificial intelligence for mining the vast genome reservoirs (“dark matter”) for novel antibacterial phage lysins. Putative lysins are computationally screened from uncharacterized Staphylococcus aureus phages and 17 novel lysins are randomly selected for experimental validation. Seven candidates exhibit excellent in vitro antibacterial activity, with LLysSA9 exceeding that of the best‐in‐class alternative. The efficacy of LLysSA9 is further demonstrated in mouse bloodstream and wound infection models. Therefore, this study demonstrates the potential of integrating computational and experimental approaches to expedite the discovery of new antibacterial proteins for combating increasing antimicrobial resistance. DeepLysin is the first unified software that employs artificial intelligence to mine novel antibacterial proteins from the “dark matter.” The best‐in‐class antibacterial protein LLysSA9 is identified, which can effectively kill drug‐resistant bacteria in vitro and in vivo, being a potent candidate with clinical application prospects. This software expedites the discovery of new antibacterial proteins for combating increasing antimicrobial resistance.
ISSN:2198-3844
2198-3844
DOI:10.1002/advs.202404049