Engineering Probiotic Strains for Gut Health Enhancement Using CRISPR and Molecular Marker-assisted Technologies

Probiotics play a vital role in maintaining gut homeostasis, modulating immune responses, and promoting overall human health. Traditional approaches to probiotic strain development rely primarily on natural isolation and phenotypic screening, which are time-consuming and lack precision. The current study presents an in silico bioinformatics framework for the rational enhancement of probiotic strains through CRISPR-Cas9–guided design, integrated with structural bioinformatics and immunoinformatics analyses. Sequence homology and conservation were evaluated using BLAST and multiple sequence alignment to identify suitable genetic targets while minimizing off-target similarity. Structural insights were obtained from the PDB and MMDB, with PDB ID 2Z7X which was a representative immune-related protein model. Structural stability and conformational variation of hypothetical modifications were assessed using RMSD-based comparisons. Guide RNA candidates for genome editing were computationally nominated and ranked using E-CRISP and CHOPCHOP, emphasizing predicted efficiency and reduced off-target risk. To evaluate immunological safety, reverse vaccinology–based B-cell epitope prediction was performed using BepiPred, with epitope regions mapped onto three-dimensional protein structures. The integrated pipeline enables the identification of modification-tolerant regions while minimizing immunogenic potential. This purely computational strategy reduces experimental dependency, accelerates strain optimization, and provides a reproducible foundation for future probiotic engineering studies under appropriate biosafety and regulatory frameworks. This study provides a computational foundation for designing safer and more effective probiotic strains for gut health, immunomodulation, and disease prevention. The framework can support functional food development, precision microbiome therapies, vaccine-adjuvant research, and regulatory pre-screening of engineered probiotics while minimizing laboratory costs and biosafety risks.

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Publication Details

Journal
Computational Biology and Bioinformatics
Published
2026-01-19
DOI
https://doi.org/10.11648/j.cbb.20261401.11
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
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article

Engineering Probiotic Strains for Gut Health Enhancement Using CRISPR and Molecular Marker-assisted Technologies

Uma Kumari, Rechel Tirkey, Vipasha Rathi
Computational Biology and Bioinformatics
vaccines and immunoinformatics approaches
article

Engineering Probiotic Strains for Gut Health Enhancement Using CRISPR and Molecular Marker-assisted Technologies

Uma Kumari, Rechel Tirkey, Vipasha Rathi
article en

Abstract

Probiotics play a vital role in maintaining gut homeostasis, modulating immune responses, and promoting overall human health. Traditional approaches to probiotic strain development rely primarily on natural isolation and phenotypic screening, which are time-consuming and lack precision. The current study presents an in silico bioinformatics framework for the rational enhancement of probiotic strains through CRISPR-Cas9–guided design, integrated with structural bioinformatics and immunoinformatics analyses. Sequence homology and conservation were evaluated using BLAST and multiple sequence alignment to identify suitable genetic targets while minimizing off-target similarity. Structural insights were obtained from the PDB and MMDB, with PDB ID 2Z7X which was a representative immune-related protein model. Structural stability and conformational variation of hypothetical modifications were assessed using RMSD-based comparisons. Guide RNA candidates for genome editing were computationally nominated and ranked using E-CRISP and CHOPCHOP, emphasizing predicted efficiency and reduced off-target risk. To evaluate immunological safety, reverse vaccinology–based B-cell epitope prediction was performed using BepiPred, with epitope regions mapped onto three-dimensional protein structures. The integrated pipeline enables the identification of modification-tolerant regions while minimizing immunogenic potential. This purely computational strategy reduces experimental dependency, accelerates strain optimization, and provides a reproducible foundation for future probiotic engineering studies under appropriate biosafety and regulatory frameworks. This study provides a computational foundation for designing safer and more effective probiotic strains for gut health, immunomodulation, and disease prevention. The framework can support functional food development, precision microbiome therapies, vaccine-adjuvant research, and regulatory pre-screening of engineered probiotics while minimizing laboratory costs and biosafety risks.

Computational Biology and BioinformaticsVol. 14(1)
Institute of Bioinformatics (IN), Institute of Bioinformatics and Applied Biotechnology (IN)
Zero hunger
Openalex Percentile: Top 80%
vaccines and immunoinformatics approaches
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