Integrating CRISPR Technologies and Artificial Intelligence to Predict and Modulate Host-Microbe Interactions

Understanding the intricate dynamics between host immunity and gut microbiota is fundamental for developing precision immunotherapies. However, existing tools lack the capacity to manipulate microbial genomes in a targeted, adaptive, and interpretable way while capturing downstream systemic effects. This gap limits the clinical translation of host–microbiome research, particularly in inflammatory and autoimmune diseases. The study aims to design and validate a CRISPR–AI integrated framework for real-time modulation of host immune responses through microbial gene editing. By dynamically targeting microbial determinants of host cytokine networks, the study seeks to optimize immunomodulatory outcomes in a programmable and biologically coherent manner. A hybrid methodological pipeline was implemented, combining CRISPR-Cas-based genome editing across 87 microbial strains with AI-driven modeling of host immune responses in 240 gastrointestinal tissue samples. Techniques included PLS-DA classification, Bayesian DAG-based causal inference, multivariate ANOVA, and dynamic feedback from cytokine expression. Gene loci MCR-21 and GNT-4B were targeted for immune optimization. A novel metric, the Biological Signal Integrity Score (BSIS), was introduced to quantify post-editing immunological coherence. IL-6 concentrations decreased by 52.4%, TNF-αby 46.1%, and IL-1β by 41.3% (all p < 0.001) following CRISPR editing of key microbial genes. Beneficial taxa such as Faecalibacterium prausnitzii increased by 2.7-fold, while harmful species like Enterococcus faecalis declined 3.1-fold. The model achieved 94.3% classification accuracy (PLS-DA) and 0.962 ROC-AUC for phenotype prediction. Causal inference identified 11 high-confidence edges (score > 0.85) linking microbial edits to cytokine cascades. BSIS reached 0.783, indicating high signal integrity post-editing. The article establishes a powerful cyber-biological framework to engineer host immune modulation by editing microbial genomes in response to real-time physiological feedback. The integration of CRISPR targeting, immune profiling, and AI-based optimization paves the way for next-generation precision therapeutics that are both adaptive and biologically grounded. The system enables recursive refinement, making it applicable to complex inflammatory conditions and personalized microbiome-based interventions.