Phagemid-based capsid system for CRISPR-Cas13a antimicrobials targeting methicillin-resistant Staphylococcus aureus

In response to the escalating antibiotic resistance in multidrug-resistant pathogens, we propose an innovative phagemid-based capsid system to generate CRISPR-Cas13a-loaded antibacterial capsids (AB-capsids) for targeted therapy against multidrug-resistant Staphylococcus aureus. Our optimized phagemid system maximizes AB-capsid yield and purity, showing a positive correlation with phagemid copy number. Notably, an 8.65-fold increase in copy number results in a 2.54-fold rise in AB-capsid generation. Phagemids carrying terL-terS-rinA-rinB (prophage-encoded packaging site genes) consistently exhibit high packaging efficiency, and the generation of AB-capsids using lysogenized hosts with terL-terS deletion resulted in comparatively lower level of wild-type phage contamination, with minimal compromise on AB-capsid yield. These generated AB-capsids selectively eliminate S. aureus strains carrying the target gene while sparing non-target strains. In conclusion, our phagemid-based capsid system stands as a promising avenue for developing sequence-specific bactericidal agents, offering a streamlined approach to combat antibiotic-resistant pathogens within the constraints of efficient production and targeted efficacy.

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Publication Details

Journal
Communications Biology
Published
2024-09-13
DOI
https://doi.org/10.1038/s42003-024-06754-w
Citations
12
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
2.81

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article

Phagemid-based capsid system for CRISPR-Cas13a antimicrobials targeting methicillin-resistant Staphylococcus aureus

Priyanka Baranwal, Yusuke Sato’o, Kotaro Kiga, Adeline Yeo Syin Lian et al.
12 citations
Communications Biology
CRISPR and Genetic Engineering
2.81
article

Phagemid-based capsid system for CRISPR-Cas13a antimicrobials targeting methicillin-resistant Staphylococcus aureus

Priyanka Baranwal, Yusuke Sato’o, Kotaro Kiga, Adeline Yeo Syin Lian, Teppei Sasahara, Jastin Edrian Cocuangco Revilleza, Jayathilake Sarangi, Srivani Veeranarayanan, Mohammad Omar Faruk, Myat Myat Thu, Yuya Hidaka, Longzhu Cui, Yi Liu, Huong Minh Nguyen, Yuzuki Shimamori, Yoshifumi Aiba, Yutaro Nishikawa, Ola Alessa, Xin-Ee Tan, Kanate Thitiananpakorn, Geoffrey Peterkins Kumwenda, Kazuhiko Miyanaga, Anujin Batbold, Mahmoud Arbaah, Shinya Watanabe, Sharmin Sultana, Feng-Yu Li, Sarah Hossain, Ho Thi My Duyen, Takayuki Shimojyo, Maniruzzaman ‌‌, Nayanjin Tergel, Takashi Sugano, Tomofumi Kawaguchi
article en
12 citations

Abstract

In response to the escalating antibiotic resistance in multidrug-resistant pathogens, we propose an innovative phagemid-based capsid system to generate CRISPR-Cas13a-loaded antibacterial capsids (AB-capsids) for targeted therapy against multidrug-resistant Staphylococcus aureus. Our optimized phagemid system maximizes AB-capsid yield and purity, showing a positive correlation with phagemid copy number. Notably, an 8.65-fold increase in copy number results in a 2.54-fold rise in AB-capsid generation. Phagemids carrying terL-terS-rinA-rinB (prophage-encoded packaging site genes) consistently exhibit high packaging efficiency, and the generation of AB-capsids using lysogenized hosts with terL-terS deletion resulted in comparatively lower level of wild-type phage contamination, with minimal compromise on AB-capsid yield. These generated AB-capsids selectively eliminate S. aureus strains carrying the target gene while sparing non-target strains. In conclusion, our phagemid-based capsid system stands as a promising avenue for developing sequence-specific bactericidal agents, offering a streamlined approach to combat antibiotic-resistant pathogens within the constraints of efficient production and targeted efficacy.

Communications BiologyVol. 7(1)
Jichi Medical University (JP), National Institute of Infectious Diseases (JP), Eiken Chemical (Japan) (JP)
Jichi Medical University, Japan Society for the Promotion of Science, Moonshot Research and Development Program
Openalex Percentile: Top 9%
CRISPR and Genetic Engineering
2.81
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