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Related Concept Videos

The Antiviral System of Bacteria and Archaea: CRISPR01:23

The Antiviral System of Bacteria and Archaea: CRISPR

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CRISPR stands for Clustered Regularly Interspaced Short Palindromic Repeats is a adaptive immune system found in bacteria and archaea that protects against viral infections. This system enables prokaryotic cells to identify, remember, and neutralize foreign genetic elements, primarily bacteriophages, by storing fragments of the invader’s DNA as a genetic memory.The CRISPR immune response begins during an initial infection. Cas (CRISPR-associated) proteins play a central role in this...
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Bacteria and archaea are susceptible to viral infections just like eukaryotes; therefore, they have developed a unique adaptive immune system to protect themselves. Clustered regularly interspaced short palindromic repeats and CRISPR-associated proteins (CRISPR-Cas) are present in more than 45% of known bacteria and 90% of known archaea.
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In silico approaches for discovering microbial antiviral defense systems.

Lixu Jiang1, Yansheng Li2, Baocai Xie2

  • 1Department of Critical Care Medicine, Intensive Care Unit, Shenzhen Key Laboratory of Microbiology in Genomic Modification & Editing and Application, Shenzhen Institute of Translational Medicine, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, 3002 Sungang West Road, Futian District, Shenzhen 518060, China.

Briefings in Bioinformatics
|December 5, 2025
PubMed
Summary

Computational methods are crucial for discovering diverse prokaryotic antiviral defense systems. This review categorizes four strategies to enhance the identification of novel microbial immune systems for applications like phage therapy.

Keywords:
in silico discoveryantiviral defense systemsartificial intelligencebacterial immunitydefense islands

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Immunology

Background:

  • Prokaryotes utilize a wide array of antiviral defense systems against phage predation.
  • Challenges in discovering these systems include horizontal gene transfer, sequence diversity, and rapid evolution.
  • High-throughput sequencing generates vast genomic data, necessitating computational discovery tools.

Purpose of the Study:

  • To review and categorize computational strategies for discovering prokaryotic antiviral defense systems.
  • To provide a framework for systematically exploring microbial immune systems.
  • To guide applications in phage therapy, microbiome engineering, and synthetic biology.

Main Methods:

  • Categorization of computational approaches into four strategies: sequence homology, structure-guided, genomic context, and artificial intelligence.
  • Discussion of emerging tools like conserved gene cluster discovery and genomic foundation models.
  • Comparison of methodological principles, strengths, and limitations.

Main Results:

  • Sequence homology methods reliably identify known systems but miss divergent ones.
  • Structure-guided approaches detect remote homologs but are computationally expensive.
  • Genomic context strategies uncover multi-gene clusters and novel modules.
  • AI-powered methods integrate sequence and context for large-scale discovery of novel systems.

Conclusions:

  • Computational strategies are indispensable for efficient and comprehensive discovery of microbial defense systems.
  • Emerging tools and AI offer powerful capabilities for identifying novel systems and designing synthetic modules.
  • This review provides a practical framework for advancing the study of prokaryotic immunity and its applications.