Prophage Activation: An In Silico Platform for Identifying Prophage Regulatory Elements to Inform Phage Engineering Against Drug-Resistant Bacteria

Multidrug-resistant bacterial infections pose a severe global health threat, highlighting the urgent need for innovative therapeutic options beyond traditional antibiotics. Phage therapy, which employs bacteriophages to infect and eradicate pathogenic bacteria, specifically offers a promising solution. However, the lack of well-characterized therapeutic phages has limited their broader clinical use. A critical aspect of activating the lytic potential of dormant prophages involves the strategic manipulation of transcription factor binding sites (TFBS), which function as pivotal regulatory nodes governing the transition between lysogenic dormancy and lytic activation. Our platform utilizes advanced bioinformatics tools to accurately identify and analyze TFBS, facilitating the targeted redesign or replacement of these sites to disrupt host-mediated repression. By systematically simulating modifications of these regulatory 'switches,' our platform computationally predicts reduced repressor activity, suggesting the potential for prophage activation and bacterial cell lysis. This novel methodology not only broadens the spectrum of therapeutic bacteriophages but also establishes a basis for individualized phage-based therapies, presenting a robust strategy to address the escalating challenge of antibiotic-resistant infections. By enabling the precise identification and engineering of TFBS, our platform signifies a transformative advancement in phage biology, effectively bridging the divide between computational analysis and therapeutic application.

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Publication Details

Journal
Life
Published
2025-09-09
DOI
https://doi.org/10.3390/life15091417
Citations
1
Primary Topic
Bacteriophages and microbial interactions
Type
article
Field-Weighted Citation Impact
1.72
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article

Prophage Activation: An In Silico Platform for Identifying Prophage Regulatory Elements to Inform Phage Engineering Against Drug-Resistant Bacteria

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1 citations
Life
Bacteriophages and microbial interactions
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article

Prophage Activation: An In Silico Platform for Identifying Prophage Regulatory Elements to Inform Phage Engineering Against Drug-Resistant Bacteria

Yanhui Xiang, Yufei Huang, Sen Liu, Wei Wang, Ze‐Guang Han, Wen Yin, Saher Musrrat
article en
1 citations

Abstract

Multidrug-resistant bacterial infections pose a severe global health threat, highlighting the urgent need for innovative therapeutic options beyond traditional antibiotics. Phage therapy, which employs bacteriophages to infect and eradicate pathogenic bacteria, specifically offers a promising solution. However, the lack of well-characterized therapeutic phages has limited their broader clinical use. A critical aspect of activating the lytic potential of dormant prophages involves the strategic manipulation of transcription factor binding sites (TFBS), which function as pivotal regulatory nodes governing the transition between lysogenic dormancy and lytic activation. Our platform utilizes advanced bioinformatics tools to accurately identify and analyze TFBS, facilitating the targeted redesign or replacement of these sites to disrupt host-mediated repression. By systematically simulating modifications of these regulatory 'switches,' our platform computationally predicts reduced repressor activity, suggesting the potential for prophage activation and bacterial cell lysis. This novel methodology not only broadens the spectrum of therapeutic bacteriophages but also establishes a basis for individualized phage-based therapies, presenting a robust strategy to address the escalating challenge of antibiotic-resistant infections. By enabling the precise identification and engineering of TFBS, our platform signifies a transformative advancement in phage biology, effectively bridging the divide between computational analysis and therapeutic application.

LifeVol. 15(9)
East China University of Science and Technology (CN), Shenzhen Institutes of Advanced Technology (CN), University of Chinese Academy of Sciences (CN), Hubei University of Technology (CN)
Openalex Percentile: Top 14%
Bacteriophages and microbial interactions
1.72
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