Genomic evolution of enteric pathogens: mechanisms of pathogenicity and diagnostic innovations - Li, Tao; Li, Jin; Tang, Zhiping; Liu, Xing; Yao, Shiwen; Zhu, Jiabao; Wang, Wei; Huo, Linju; Chen, Song; Zhang, Gaihua; Liu, Zhonghua (Frontiers in Microbiology, 2025)
Genomic evolution serves as a pivotal driver of pathogenicity and host adaptation in intestinal pathogens. This review systematically dissects, from a phylogenetic perspective, the key genomic evolutionary mechanisms underpinning pathogenesis across five major classes of intestinal pathogens and their significance. Bacteria (e.g., Escherichia coli) acquire virulence- and antibiotic resistance-enhancing genes via horizontal gene transfer and genomic recombination, equipping them to disrupt the intestinal mucosal barrier and evade host immune defenses. Fungi (e.g., Candida albicans and Cryptococcus spp.) significantly augment their pathogenic potential through chromosomal rearrangements and dynamic expansions or losses within gene families. Parasites (e.g., Giardia lamblia) successfully evade host immune recognition and clearance through complex life cycles and stage-specific gene expression regulation. Viruses (e.g., rotaviruses and noroviruses) rapidly adapt to host cellular environments via genomic mutation and recombination, triggering acute gastroenteritis. Although prions primarily propagate via the nervous system, the pronounced cellular stress response they elicit in intestinal tissues suggests the gut may serve as a potential secondary transmission or amplification site. Collectively, these diverse evolutionary mechanisms confer unique colonization, survival, and competitive advantages upon distinct pathogen classes within the complex gut microenvironment. Employing Escherichia coli as a paradigm, systematic bioinformatic analysis of 335 key virulence factors revealed evolutionarily stable functional clusters (e.g., effector/toxin systems, 21.0%) with core contributions to pathogenicity. These conserved genomic signatures provide a robust foundation for developing novel high-precision diagnostics. For instance, CRISPR-based platforms achieve 100% clinical concordance in detecting the Shiga toxin gene (stx2), while loop-mediated isothermal amplification coupled with lateral flow assay (LAMP-LFA) enables rapid (< 40 min) and accurate detection of blaNDM − 1-mediated carbapenem resistance. The deep integration of multi-omics data (genomics, transcriptomics, proteomics, etc.) with artificial intelligence (AI) is substantially accelerating the discovery of novel biomarkers. Looking forward, innovative technologies such as real-time nanopore sequencing and nanomaterial-enhanced high-sensitivity biosensors hold promise for achieving rapid, broad-spectrum pathogen detection, thereby robustly supporting the World Health Organization (WHO)'s “One Health” strategic goals. In conclusion, the “Genomic Evolution–Biomarker Discovery–Diagnostic Development” integrated triad framework presented herein offers crucial insights and actionable pathways for advancing next-generation precision diagnostics and formulating effective global infection control strategies.