Genomic evolution of enteric pathogens: mechanisms of pathogenicity and diagnostic innovations

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 bla_NDM−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.

1 Introduction

The human intestine, as the largest immune and metabolic organ, harbors a complex and diverse microbial ecosystem essential for maintaining host health. According to the Global Burden of Disease Study, diarrheal diseases were responsible for an estimated 1.17 million deaths worldwide in 2021 [95% uncertainty interval (UI): 0.793–1.62 million] and accounted for 59 million disability-adjusted life years (DALYs), with viral pathogens such as rotavirus constituting major contributors. Although diarrheal diseases represent a global health threat, their epidemiological burden varies substantially across regions and age groups. Low- and middle-income countries (LMICs), particularly in sub-Saharan Africa, experience the highest burden, with diarrhea-related mortality reaching 151.9 per 100,000 population among children under 5 years of age. In contrast, high-income countries are primarily characterized by increased hospitalization rates and healthcare expenditures among elderly and immunocompromised populations, as exemplified by Clostridioides difficile infections (Collaborators, 2025).

The pathogen- and demographic-specific burden of diarrheal diseases further underscores their complexity. Among bacterial pathogens, Shigella is estimated to cause ~81,800 deaths annually in children under five, contributing to 7.34 million DALYs and ranking as the second leading cause of death in this age group. Clostridioides difficile predominantly affects individuals aged ≥70 years, resulting in ~15,600 deaths and 284,000 DALYs, often in the context of antimicrobial misuse. Enterotoxigenic Escherichia coli (ST-ETEC) and typical enteropathogenic Escherichia coli (tEPEC) exhibit high population attributable fractions (PAFs) of 13.4% and 13.6%, respectively, highlighting their relevance in pediatric populations. Among parasitic agents, Cryptosporidium is responsible for an estimated 118,000 deaths and 7.37 million DALYs globally, with a PAF of 20.1% among children under five. Entamoeba histolytica exceeds a 5% PAF in this age group, although its precise global burden remains uncertain. Viral pathogens remain predominant contributors to disease burden; rotavirus alone accounts for ~176,000 deaths annually—of which 120,000 occur in children under five—and 10.8 million DALYs. Additionally, adenovirus and norovirus are associated with ~81,100 and 124,000 deaths, respectively (Collaborators, 2025).

Fungal pathogens constitute a substantial burden on hospitalized and immunocompromised populations. As reported by The Lancet Infectious Diseases (2024), invasive fungal infections result in an estimated 6.5 million cases and 3.8 million deaths annually, with 68% of fatalities attributable to fungal etiologies. Candida species cause ~1.565 million invasive infections and 995,000 deaths per year. Cryptococcus meningitis accounts for ~194,000 cases and 147,000 deaths, primarily affecting HIV-infected individuals in sub-Saharan Africa. Infections caused by Aspergillus species are estimated to exceed 2 million cases and 1.8 million deaths annually. The burden of endemic fungi, such as Histoplasma, is thought to affect ~100,000 individuals globally, although data remain limited (Vallabhaneni et al., 2016).

Although prion diseases (e.g., Kuru, variant Creutzfeldt–Jakob disease) can be transmitted via the oral route, they are rare and are not generally categorized as enteric pathogens. Experimental models suggest that intestinal inflammation may enhance prion transmissibility; however, global burden estimates are currently lacking.

Sub-Saharan Africa continues to be the region most severely affected, with an estimated 14 million DALYs attributable to 85 pathogens, accounting for 61.5% of the total regional disease burden. This reflects the high prevalence of coinfections involving rotavirus, Plasmodium (malaria), and HIV. In South Asia, HIV and rotavirus are major contributors, jointly accounting for over 10 million DALYs among children under five. These data underscore the urgent need for expanded vaccination coverage and targeted public health interventions. Even in high socio-demographic index (SDI) settings, enteric pathogens remain a significant concern. For instance, surveillance in Zealand, Denmark has shown that rotavirus and enteropathogenic E. coli (EPEC) predominate in pediatric winter infections, whereas bacterial pathogens are more frequent in elderly patients during summer. These epidemiological trends highlight the necessity of implementing region- and age-specific precision public health strategies (Group, 2024; Johansen et al., 2023).

In addition to epidemiological determinants, genomic evolution plays a critical role in shaping virulence, antimicrobial resistance (AMR), and host adaptation in enteric pathogens. Mechanisms such as mutation, horizontal gene transfer (HGT), and chromosomal rearrangements collectively drive these processes. In bacterial pathogens, the diversification of virulence factors and resistance determinants underlies their pathogenic potential and informs biomarker discovery. Understanding these evolutionary mechanisms is essential for elucidating microbial biology, monitoring evolutionary trajectories, and guiding the development of next-generation diagnostic tools (Scott et al., 2025; Quan et al., 2023).

This review proposes a closed-loop conceptual framework, designated the Genomic Evolution–Biomarker Discovery–Diagnostic Development framework, which integrates microbial evolutionary dynamics with translational diagnostic strategies. It systematically connects pathogen genome evolution to the identification of robust molecular biomarkers and the advancement of rapid, accurate diagnostic platforms.

The manuscript is structured into three major sections:

(1) Evolutionary Mechanisms Across Enteric Pathogens: A comprehensive overview of key evolutionary processes—including HGT, chromosomal rearrangements, hypermutation, and epigenetic regulation—in bacteria, fungi, parasites, viruses, and prions, with emphasis on their roles in virulence, AMR, and host adaptation. Table 1 provides a systematic summary of the evolutionary mechanisms of the five enteric pathogen classes for clear and intuitive reference.

(2) Escherichia coli as a Model: Functional annotation and classification of 355 E. coli virulence genes to illustrate evolutionary patterns and demonstrate how genomic insights guide biomarker discovery and pathogen profiling.

(3) Molecular Diagnostics Guided by Evolutionary Biomarkers: Discussion of diagnostic platforms, including CRISPR-Cas and loop-mediated isothermal amplification with lateral flow assays (LAMP-LFA), emphasizing their application in detecting conserved virulence and resistance markers across diverse pathogens.

Table 1

Table 1. Hierarchical summary of genomic evolution mechanisms driving pathogenicity in intestinal microbes.

By bridging fundamental genomic research with clinical implementation, this review seeks to contribute to the advancement of precision diagnostics for enteric pathogens and enhance global public health preparedness.

2 Genomic evolutionary mechanisms of intestinal pathogens

2.1 Bacteria

Bacterial pathogens in the human gut play a critical role in gastrointestinal diseases by modulating host metabolism, immune responses, and digestive processes. Among these, Enterobacteriaceae—particularly Escherichia coli (E. coli) and Klebsiella spp.—are enriched in the gut microbiota of individuals with Crohn's disease and ulcerative colitis. Over the past decade, their genomes have demonstrated marked evolutionary plasticity, largely driven by virulence genes and mobile genetic elements (MGEs) that enhance pathogenicity across diverse host environments (Zhang J. et al., 2023). Key evolutionary mechanisms include horizontal gene transfer (HGT), recombination, regulatory network reprogramming, and antibiotic resistance development (Garud et al., 2019).

HGT facilitates rapid acquisition of virulence traits and reconfigures bacterial genomes by integrating genetic elements such as plasmids, bacteriophages, and transposons, thereby promoting adaptation to host-derived stresses. For example, E. coli O157:H7 acquired Shiga toxin genes (stx) via phage-mediated HGT, resulting in potent cytotoxicity and epithelial damage (Greig et al., 2020). Conjugative plasmids such as pVir mediate the transfer of master regulators like hilD, which activate type III secretion system 1 (TTSS-1), enhancing epithelial invasion and intracellular survival (Bakkeren et al., 2022). Bacteriophages, central to HGT, integrate into bacterial chromosomes as prophages and are induced by host stressors (e.g., oxidative bursts, antibiotics), entering lytic cycles that disseminate virulence factors between species (Frazao et al., 2019). Many prophage-encoded virulence genes exhibit phase variation, enabling dynamic expression in response to intestinal cues, thereby supporting immune evasion and persistent colonization.

Insertion sequence (IS) amplification—for example, IS1 and IS2 in Shigella spp.—drives genome reduction by disrupting or deleting functional genes, facilitating niche-specific adaptation and host specialization (Hawkey et al., 2020). These IS elements also cause chromosomal rearrangements affecting virulence gene expression. For instance, IS-mediated modifications in regulatory regions may upregulate or suppress invasion proteins, optimizing pathogenic potential. Such genome reduction enhances fitness in the intestinal niche by supporting immune evasion and colonization.

Beyond HGT, bacterial pathogens adapt by reprogramming metabolic and regulatory networks to resist environmental and host immune pressures. Adherent-invasive E. coli (AIEC), for example, acquires genomic islands encoding stress regulators such as yfcV, which confer oxidative stress resistance and promote survival within macrophage phagosomes. This tight linkage between virulence and persistence extends to regulation of biofilm formation and toxin production, reflecting multifactorial survival strategies in fluctuating gut environments.

Virulence evolution is also mediated by recombination and regulatory remodeling (Zhou et al., 2023). Unlike HGT, these processes modulate gene expression without sequence acquisition. Bacteria utilize promoter mutations, antisense RNAs, and epigenetic modifications to rapidly and reversibly regulate virulence genes. For instance, Klebsiella spp. control capsule polysaccharide synthesis via phase variation in rmpA, balancing immune evasion and genetic exchange to maintain adaptability (Wei et al., 2025). In Salmonella, the CRISPR-Cas system suppresses foreign DNA and concurrently represses hilD—a TTSS-1 regulator—linking immune defense to virulence attenuation (Sharma et al., 2024). Similarly, in Vibrio parahaemolyticus, the transcription factor QsvR synchronizes quorum sensing and virulence gene expression, coordinating responses to bile salts and mucus gradients to facilitate colonization (Zhang et al., 2021).

In enterohemorrhagic E. coli (EHEC) O157:H7, the two-component system UvrY functions as a central regulator, activating both the locus of enterocyte effacement (LEE) and non-LEE-encoded virulence genes, exemplifying a “master regulator–modular target” model (Wu et al., 2023). Under magnesium-limited conditions—commonly induced by host inflammation—sensor kinases phosphorylate UvrY, triggering LEE effector expression to promote epithelial adherence and secretion system activation. This signal-responsive network shifts resource allocation from growth to virulence, enhancing colonization under inflammatory stress.

Antimicrobial resistance (AMR) represents a critical global health threat extending beyond pediatric populations. The 2024 Global Burden of Disease study reported 1.26 million deaths directly attributable to AMR in 2021 and 4.95 million deaths associated overall (95% UI: 1.01–1.51 million and 3.95–5.70 million, respectively; Collaborators, 2024). Since 1990, AMR-related mortality has increased by over 100%, with disproportionate impacts in South Asia and Latin America. Projections estimate up to 1.91 million direct AMR deaths by 2050, particularly among the elderly, underscoring the urgency for preventive measures, vaccination, and novel antimicrobial development.

In gut pathogens, resistance typically follows a hierarchical trajectory: initial chromosomal mutations confer low-level resistance (e.g., gyrA mutations conferring fluoroquinolone resistance), followed by HGT-mediated acquisition of high-level resistance genes (e.g., qnr plasmids), and compensatory mutations that mitigate fitness costs. Although children in resource-limited regions are especially vulnerable, AMR constitutes a widespread and escalating global concern (Okumu et al., 2025).

Resistance emerges via intrinsic, acquired, and adaptive mechanisms (Elshobary et al., 2025). A notable example is the overexpression of resistance-nodulation-division (RND)-type efflux pumps, such as CmeABC in Campylobacter spp., which are upregulated by host-derived antimicrobial peptides and expel multiple antibiotics (Dai et al., 2024). While intrinsic resistance mechanisms represent baseline features, their amplification often results from regulatory mutations, contributing to multidrug resistance (MDR). Biofilm formation by E. coli also enhances resistance by limiting antibiotic penetration and reducing metabolic activity, yielding up to 1,000-fold increased tolerance, partly mediated by β-lactamase expression (Nasrollahian et al., 2024). Additional mechanisms include target site modification (e.g., rpoB mutations conferring rifampicin resistance), enzymatic degradation (e.g., extended-spectrum β-lactamases), and altered membrane permeability. HGT remains central to resistance dissemination, as exemplified by the co-localization of resistance genes on conjugative plasmids and integrons in Shigella spp. and non-typhoidal Salmonella (NTS) serovars (Wallace et al., 2020). These plasmids frequently co-transfer virulence and resistance genes—for example, bla_{CTX − M−15} alongside iroN—facilitating the emergence of hypervirulent, multidrug-resistant clones.

This co-evolution of resistance and virulence, driven by host and therapeutic pressures, enables pathogens to maintain colonization, invasion, and immune evasion despite antimicrobial exposure. Environmental stressors, such as climate change and pollution, further accelerate mutation rates and promote HGT via SOS response induction. Agricultural runoff containing heavy metals selects for metal resistance genes co-located with antibiotic resistance genes on MGEs, driving co-selection and sustaining resistance reservoirs even in the absence of antibiotic pressure.

In summary, gut bacterial pathogens evolve through HGT, regulatory remodeling, and resistance acquisition, resulting in extensive genomic plasticity that complicates clinical management. The convergence of virulence and resistance necessitates integrated surveillance systems monitoring both AMR determinants and virulence factors. A deeper understanding of these evolutionary mechanisms will facilitate the identification of genomic biomarkers (e.g., IS26 transposition sites) and inform the development of precision diagnostics. Novel therapeutic strategies—such as conjugation-blocking peptides, SOS response inhibitors, and CRISPR interference (CRISPRi) targeting key virulence regulators—represent promising approaches. Future research should prioritize longitudinal tracking of within-host pathogen evolution to inform personalized treatment regimens.

2.2 Fungi

Gut fungi predominantly adapt through genome remodeling and lineage-specific gene family diversification, in contrast to the horizontal gene transfer (HGT) mechanisms central to bacterial evolution. For instance, Candida adhesins evolve via recombination-driven diversification, demonstrating functional convergence across kingdoms under intense intestinal selective pressures. Elucidating these fungal adaptation strategies is essential for understanding infection dynamics and host–pathogen interactions.

Although less abundant than bacteria, gut fungi significantly influence host physiology and pathogenesis. Rather than relying on HGT, fungi adapt through structural genome variation, gene family expansion, and acquisition of antifungal resistance—mechanisms facilitating their transition from commensals to opportunistic pathogens within the complex intestinal ecosystem characterized by oxygen gradients, bile salts, and interkingdom competition (Huang et al., 2024).

Genomic structural variation constitutes a core mechanism underlying fungal adaptability and virulence regulation. Aneuploidy, chromosomal translocations, copy number variations (CNVs), and homologous recombination modulate both drug resistance and pathogenicity. These rearrangements are frequently induced by host-derived stressors; for example, bile acids induce DNA damage in Candida, while neutrophil-generated reactive oxygen species promote recombination in Candida glabrata.

In Candida albicans, chromosome 7 trisomy—commonly observed in the gut—elevates NRG1 dosage, a transcriptional repressor of hyphal formation. This promotes a yeast-phase-locked phenotype, facilitating mucosal colonization and immune evasion (Kakade et al., 2023). Under azole stress, C. albicans acquires aneuploidies involving chromosomes 3, 4, or 5, which harbor resistance genes such as ERG11, TAC1, and MRR1. The resulting gene dosage effects upregulate efflux pumps and drug targets, conferring rapid fluconazole tolerance (Wang et al., 2025).

In Cryptococcus species, recombination hotspots within transposon-dense centromeres drive interchromosomal translocations. Amplification of the transcription factor RYP2 enhances yeast morphology and elevates virulence through upregulation of adhesins and capsule biosynthesis (Voorhies et al., 2021). Environmental cues such as pH shifts and nutrient depletion further induce rearrangements in C. albicans, including tandem duplications of SAP protease genes and deletions of FCR family genes, thereby improving metabolic plasticity and adaptation to nutrient-limited niches (Todd et al., 2019).

Fungal virulence is further shaped by lineage-specific expansion and structural diversification of gene families, primarily mediated by endogenous mechanisms such as ectopic recombination, retrotransposition, and unequal crossing-over, particularly within subtelomeric regions characterized by elevated recombination activity.

In C. albicans, adhesin families such as ALS and HYR/IFF expand through recombination near chromosome ends, generating structural diversity within intrinsically disordered tandem repeats. This results in strain-specific adhesion profiles that optimize binding to mucins, epithelial surfaces, and abiotic substrates—enhancing biofilm formation, tissue tropism, and infection severity (Smoak et al., 2023). Similarly, Candida parapsilosis isolates from neonatal guts exhibit extensive CNV of RTA3, encoding a lipid translocase. Elevated RTA3 copy number alters membrane rigidity, increasing resistance to azoles and cationic peptides, linking membrane remodeling to immune evasion (West et al., 2021). In clinical C. albicans strains, elevated SAP gene copy numbers correlate with increased tissue invasiveness in murine models, while allelic diversity within SAP genes further modifies substrate specificity and proteolytic activity, contributing to niche adaptation (Zoppo et al., 2021).

Antifungal resistance in gut fungi emerges via a hierarchical, multi-step process: initial point mutations reduce drug binding affinity, followed by gene amplification enhancing efflux pump and target enzyme expression, culminating in biofilm-mediated drug tolerance. The gastrointestinal tract serves as a reservoir for resistant fungal populations.

In C. albicans, missense mutations in ERG11 (e.g., G464S) that reduce azole binding affinity often arise de novo during intestinal azole exposure. Biofilms further potentiate resistance through physical drug exclusion, overexpression of pumps such as CDR1 and MDR1, and formation of metabolically quiescent persister cells exhibiting 100–1,000-fold increased drug tolerance (Lee et al., 2023). Expression of CDR1 is regulated by the transcription factor TAC1, with both gain-of-function mutations and gene duplication at this locus contributing to high-level resistance (Kaur and Nobile, 2023; Ibe and Pohl, 2024).

Bacterial–fungal interactions also modulate antifungal resistance. For example, Enterococcus spp. secrete farnesol, which inhibits Candida biofilm dispersal, while Pseudomonas aeruginosa releases pyocyanin that induces CDR1, enhancing azole resistance. These interkingdom dynamics complicate therapeutic management in polymicrobial gut environments.

Additional resistance mechanisms include upregulation of alternative efflux pumps (MDR1, FLU1), alterations in membrane sterol synthesis via mutations in ERG3 and ERG6, and activation of stress response pathways that enhance fungal survival under oxidative and membrane stress. Collectively, these adaptations facilitate fungal persistence despite antifungal treatment.

In summary, gut fungi exhibit remarkable adaptive potential through chromosomal remodeling, gene family diversification, and antifungal resistance evolution. These mechanisms fundamentally differ from bacterial strategies based on horizontal gene acquisition. Fungal aneuploidy involves metabolic trade-offs balancing growth and virulence, while adhesin variation enables niche-specific colonization. Together, these strategies shape the evolutionary trajectory of fungal pathogens within the gut. Targeting fungal genome instability—such as suppressing aneuploidy or recombination hotspots—represents a promising therapeutic approach. Future research integrating multi-omics and in vivo models is essential for elucidating convergent evolutionary mechanisms shaped by host–microbe interactions.

2.3 Parasites

Intestinal parasites, particularly protozoans, have evolved distinct adaptive trajectories under the selective pressure of obligate parasitism. Their pathogenicity is primarily driven by three core evolutionary strategies: extreme genome reduction, antigenic variation, and modulation of host regulatory networks. These mechanisms, arising from prolonged host–parasite coevolution, collectively underpin persistent colonization and immune evasion.

Genome compaction represents a hallmark of parasitic adaptation, characterized by the elimination of redundant metabolic pathways and the conservation or amplification of genes essential for virulence. Encephalitozoon cuniculi, an obligate intracellular microsporidian, harbors a highly reduced genome (< 3 Mbp)—substantially smaller than those of many prokaryotes—with extensive loss of central metabolic processes, including the tricarboxylic acid (TCA) cycle and mitochondrial respiration (Zarsky et al., 2023). Devoid of autonomous ATP synthesis, this parasite relies entirely on host-derived energy, facilitated by conserved invasion machinery such as polar tube proteins (PTP1–5) and hexokinases. This metabolic parasitism enhances replication efficiency and exacerbates virulence, particularly in immunocompromised hosts.

Giardia lamblia exhibits analogous genomic streamlining. Its nucleolar proteome contains only ~147 proteins, predominantly dedicated to ribosome biogenesis (e.g., fibrillarin, nucleolin), thereby supporting efficient protein translation while eliminating non-essential nuclear functions (Feng et al., 2020). This compact proteomic organization enables rapid trophozoite proliferation during intestinal colonization.

Cryptosporidium spp. have undergone further extensive genome reduction, completely abolishing mitochondrial oxidative phosphorylation. Their mitosomes retain only iron–sulfur (Fe–S) cluster assembly functions, enforcing strict reliance on host-derived ATP (Arias-Agudelo et al., 2020). Their streamlined genomes prioritize the expression of effector molecules critical for invasion and survival, including mucin-like GP900 for epithelial adhesion, thrombospondin-related adhesive protein TRAP-C1 for gliding motility, and dense granule proteins (GRAs) that restructure host epithelial cells to form parasitophorous vacuoles, thereby facilitating intracellular persistence and immune evasion.

To evade host adaptive immunity, protozoan parasites employ antigenic variation systems that dynamically modulate their surface antigen profiles. Entamoeba histolytica expresses multiple isoforms of Gal/GalNAc lectins—surface adhesins mediating mucin binding, epithelial cell attachment, and cytotoxicity. Isoform switching alters antigenic presentation, directly facilitating immune evasion. Additionally, E. histolytica secretes cysteine proteases that degrade secretory immunoglobulin A (IgA) and extracellular matrix components, impairing mucosal defense mechanisms and promoting tissue invasion (Marie and Petri, 2014).

Blastocystis spp., particularly subtype ST6, also secrete cysteine proteases that degrade IgA and modulate host immune signaling. These enzymes induce interleukin-8 (IL-8) expression, recruiting polymorphonuclear leukocytes (PMNs) and initiating localized inflammation. Concurrently, elevated levels of T helper 1 (Th1) cytokines—including interleukin-12 (IL-12) and interferon-gamma (IFN-γ)—reflect a cell-mediated immune response that facilitates chronic colonization. Subtypes ST2 and ST6 are notably correlated with increased proteolytic activity, upregulated interleukin-6 (IL-6) secretion, and symptomatic infection. Such inflammatory responses may predispose hosts to irritable bowel syndrome (IBS), linking Blastocystis-induced immune modulation to chronic gastrointestinal pathology (Karamati et al., 2021).

Beyond immune evasion, intestinal parasites manipulate host immune function through the secretion of immunomodulatory molecules. Trichuris trichiura (whipworm) releases excretory–secretory (ES) products—including the p43 protein, short-chain fatty acids (e.g., acetate, butyrate), and complex glycans—that interact with Toll-like receptor (TLR)-expressing dendritic cells. These signals suppress tumor necrosis factor-alpha (TNF-α) production, inhibit dendritic cell maturation, and attenuate Th1/Th17 responses, while promoting interleukin-10 (IL-10) secretion and mucosal tolerance. Although regulatory T cell (Treg) expansion is modest compared to other helminths, the induced anti-inflammatory milieu supports sustained colonization. Notably, the immunomodulatory activity of short-chain fatty acids may be enhanced by the parasite-associated microbiota (Shears and Grencis, 2022).

Structural adaptations further enhance persistence. Giardia lamblia utilizes a ventral adhesive disc composed of microtubule–actin complexes to maintain tight adhesion to intestinal epithelium and resist peristaltic clearance. The actin-like protein GlActin is essential for disc structural integrity and function; its depletion disrupts attachment. Disc and actin-associated protein 1 (DAAP1), localized to the ventral groove, regulates fluid dynamics to stabilize adhesion under shear stress. While DAAP1 is not required for disc morphogenesis, its absence significantly impairs attachment strength and colonization efficiency in murine models (Steele-Ogus et al., 2022).

In summary, parasitic protozoa rely on genomic minimality, antigenic plasticity, and modulation of host regulatory networks to establish chronic infections within the gastrointestinal tract. Unlike bacteria, which frequently acquire virulence traits via horizontal gene transfer, or fungi, which depend on chromosomal rearrangements, parasites exemplify an alternative evolutionary strategy—achieving functional complexity through reductive genomic evolution. From energy harvesting in Cryptosporidium to proteomic efficiency in Giardia lamblia, these adaptations illustrate how parasitic lifestyles are optimized via streamlined genetic architectures. Elucidation of these mechanisms provides critical insights into conserved evolutionary strategies across biological kingdoms and identifies promising targets for therapeutic intervention.

2.4 Viruses

Within the intestinal ecosystem, viruses constitute highly adaptable pathogenic agents, with their pathogenicity primarily governed by three core genomic strategies: hypermutation, genetic recombination, and structural optimization for immune evasion. Collectively, these evolutionary mechanisms mediate immune escape, expand tissue tropism and host range, and augment viral persistence and transmissibility across diverse host environments.

RNA viruses such as norovirus GII.4 exemplify mutation-driven adaptation. Owing to the absence of proofreading activity in RNA-dependent RNA polymerases (RdRps), noroviruses exhibit mutation rates ranging from 10⁻³ to 10⁻⁵ substitutions per nucleotide per replication cycle, generating extensive quasispecies swarms that enable rapid phenotypic adaptation. In norovirus GII.4, mutations predominantly accumulate in the VP1 major capsid protein, particularly within antigenic epitopes (Sites A–G), inducing subtle structural alterations that evade neutralizing antibodies while preserving affinity for histo-blood group antigens (HBGAs) expressed on intestinal epithelial cells. Concurrent mutations in the VP2 (p22) minor capsid protein enhance virion stability and replication fidelity, conferring additional fitness advantages under immune pressure (Kistler and Bedford, 2023).

Similarly, rotavirus A (e.g., strain G9P[8]) undergoes immune-driven antigenic evolution via amino acid substitutions in the VP7 glycoprotein, specifically within antigenic regions (Sites 7–8), which reduce antibody-mediated neutralization. Segmental reassortment between VP4 and VP7 genes further diversifies antigenic profiles, generating variants capable of reinfecting previously vaccinated individuals. Astrovirus MLB2 adapts through remodeling of the capsid P2 domain, which enhances HBGA binding affinity and alters viral uncoating kinetics, thereby increasing intestinal tropism and fecal shedding. These capsid adaptations balance immune evasion with infectivity, supporting persistence in hosts with pre-existing immunity (Liu X. et al., 2022).

Zoonotic enteric viruses exhibit heightened mutational plasticity. For instance, rodent-borne rosavirus demonstrates a VP1 mutation rate of 2.12 × 10⁻³ substitutions per site per year, with mutations concentrated in hydrophobic receptor-binding regions. Deep sequencing analyses reveal variant-rich quasispecies swarms with expanded receptor usage, indicating an augmented potential for cross-species transmission (Zhang et al., 2024).

Beyond point mutations, genetic recombination drives abrupt evolutionary shifts. Rotavirus A frequently undergoes segmental reassortment and homologous recombination, particularly within the VP1 polymerase gene, where recombination breakpoints cluster in conserved RNA stem-loop regions (nucleotides 800–850), facilitating template switching. Recombinant G9P[8]-DS-1-like strains exhibit enhanced capsid stability (ΔG = −3.2 kcal/mol) and escape from dominant neutralizing epitopes, promoting persistence despite widespread population immunity (Hoxie and Dennehy, 2020).

In noroviruses, recombination events near the ORF1/ORF2 junction generate hybrid capsids that integrate non-structural and structural proteins. These chimeric P2 domains expand HBGA-binding capabilities and enhance mucosal adherence, increasing fecal shedding and transmission efficiency—particularly in pediatric populations and high-density settings (Ludwig-Begall et al., 2021; Cannon et al., 2021).

Cross-species recombination events pose significant zoonotic risks. The human–porcine reassortant rotavirus strain HB05 (G9P[23]) incorporates a human-derived VP7 segment with a porcine-origin VP4, conferring dual-species receptor tropism. This strain replicates 3.5-fold more efficiently in human intestinal organoids and induces 89% mortality in neonatal piglets, underscoring its heightened virulence potential (Li et al., 2025). Similarly, neurotropic astrovirus recombinants (e.g., MLB1–VA1) harbor capsid modifications that enhance sialic acid binding affinity and facilitate neuronal cell entry, contributing to encephalitis in immunocompromised hosts (Roach and Langlois, 2021).

Vaccination imposes strong selective pressure that can inadvertently accelerate viral evolution. In norovirus GII.4, mutations within the VP1 P2 domain (e.g., A358N, D9YIN, S59MD, T97A) alter epitope conformation, surface hydrophobicity, and electrostatic charge, preserving HBGA-binding affinity while reducing antibody recognition. Notably, Site A (residues 294–298) is critical for immune evasion and vaccine escape, contributing to breakthrough infections even in vaccinated cohorts (Carlson et al., 2024).

Live-attenuated rotavirus vaccines (RVVs) impose additional evolutionary constraints. Post-vaccination viral shedding facilitates reassortment between vaccine-derived and wild-type strains, while immune pressure selects for emerging genotypes. Novel variants such as G12P[6] exhibit modified VP4/VP7 antigens and enhanced immune evasion properties, contributing to increased breakthrough infection rates (Mhango et al., 2023).

Recombinant astrovirus strains carrying mink-derived capsid segments demonstrate expanded organotropism, leveraging upregulated platelet-derived growth factor receptor alpha (PDGFRα) to infect human neural progenitor cells, resulting in extra-intestinal manifestations such as encephalitis (El-Heneidy et al., 2023).

Porcine epidemic diarrhea virus (PEDV) illustrates vaccine-induced lineage replacement. G2 strains have supplanted G1 variants via mutations in the S1 domain that increase sialic acid affinity and alter COE neutralizing epitopes, thereby evading G1-derived maternal antibodies and causing >95% mortality in piglets—highlighting how vaccine-driven immune selection can enhance viral pathogenicity (Zhang H. et al., 2023).

Collectively, immune pressure channels viral evolution along adaptive landscapes, where antigenic changes may outpace host immunological memory. The emergence of novel norovirus GII.4 variants is frequently marked by amino acid insertions and shifts in charge/hydrophobicity within the VP1 P2 domain, preserving HBGA binding while reducing susceptibility to neutralization. Although quantitative estimates of >40% vaccine efficacy loss remain limited, these antigenic dynamics present substantial challenges for effective vaccine design (Chhabra et al., 2024).

In summary, the genomic evolution of enteric viruses—driven by mutation, recombination, and immune selection—enhances their virulence, transmissibility, and zoonotic potential. Addressing these challenges requires a multifaceted strategy encompassing: (1) global genomic surveillance of emerging variants; (2) rational vaccine design targeting conserved, functionally constrained epitopes (e.g., norovirus HBGA-binding sites, rotavirus VP6); (3) antiviral strategies exploiting error-prone replication (e.g., lethal mutagenesis); and (4) ecological interventions to reduce animal–human transmission interfaces. Recognizing enteric viruses as dynamic quasispecies is critical for guiding public health policy and strengthening pandemic preparedness.

2.5 Prions

Prions are unique infectious agents comprising solely misfolded proteins, devoid of nucleic acid components. Their pathogenicity originates from the conformational conversion of host-encoded cellular prion protein (PrP^∧C) into a pathogenic, self-propagating isoform (PrP^∧Sc), which assembles into highly stable, transmissible fibrils. Although prion diseases—such as bovine spongiform encephalopathy (BSE) and Creutzfeldt–Jakob disease (CJD)—are classically defined by fatal central nervous system (CNS) neurodegeneration, the gastrointestinal (GI) tract serves as a critical reservoir for prion entry, persistence, and neuroinvasion. Following oral exposure, prions establish long-term persistence within gut-associated lymphoid tissues (GALT), most notably in Peyer's patches, where they leverage mucosal immune tolerance mechanisms to evade clearance. Subsequent retrograde transport via the enteric nervous system (ENS) facilitates neuroinvasion, underscoring the GI tract as a pivotal determinant of prion pathogenesis. The evolutionary trajectory of prion pathogenicity is governed by three interrelated processes: (i) microenvironmental modulation of misfolding kinetics, (ii) host genetic determinants of susceptibility and phenotypic expression, and (iii) polymorphic constraints on cross-species transmissibility.

The intestinal lumen represents a complex, dynamic microenvironment in which the gut microbiota and their metabolites profoundly modulate prion misfolding dynamics and disease progression. Microbial dysbiosis has been identified as a critical modulator of prion pathogenesis through multiple convergent pathways: disruption of epithelial barrier integrity, reduction of protective short-chain fatty acids (SCFAs; e.g., butyrate), elevation of pro-inflammatory molecules such as lipopolysaccharide (LPS), and cross-seeding of prion aggregation by bacterial amyloid proteins (e.g., Curli; Mahbub et al., 2024). These alterations promote PrP^∧Sc formation and stabilization within the intestinal milieu. Notably, while certain SCFA-producing bacteria (e.g., Lachnospiraceae, Ruminococcaceae) are typically regarded as beneficial, their expansion may paradoxically exacerbate neuroinflammation via microglial activation, indirectly supporting PrP^∧Sc persistence. Conversely, increased abundance of SCFA-suppressing genera such as Bilophila has been associated with impaired hippocampal synaptic plasticity, potentially accelerating prion dissemination (Losa et al., 2024). Additionally, accumulation of neurotoxic microbial metabolites—including D-lactate and ammonia—further disrupts the gut–brain barrier and promotes CNS inflammation, thereby facilitating PrP^∧Sc propagation along the gut–brain axis (Islam et al., 2024). Collectively, these findings highlight the central role of the intestinal microbiota in regulating prion conformational transitions and neuropathological outcomes.

At the host genomic level, polymorphisms in the PRNP gene constitute primary determinants of prion disease susceptibility, incubation period, and clinicopathological manifestations. Over 50 pathogenic PRNP mutations have been reported worldwide, underlying familial prion disease variants. For example, the E200K mutation is frequently associated with familial CJD in European populations; the D178N mutation, in conjunction with codon 129 polymorphism, dictates phenotypic divergence between genetic CJD and fatal familial insomnia; the P102L mutation is linked to Gerstmann–Sträussler–Scheinker syndrome with variable expressivity; and the rare R208H mutation has been described in cases resembling progressive supranuclear palsy. Octapeptide repeat insertions (OPRIs) exhibit variable phenotypic outcomes contingent upon both repeat number and codon 129 status. Homozygosity at codon 129 (MM or VV) significantly increases susceptibility to both acquired and inherited prion diseases, with nearly complete penetrance observed in many familial cases (Jankovska et al., 2021). In sporadic CJD (sCJD), codon 129 genotype acts as a key modifier: MM homozygosity predominates among patients (~60% in Barcelona, ~71% in Bologna), whereas heterozygosity (MV) confers significant protective effects, presumably by reducing the efficiency of PrP^∧C-to-PrP^∧Sc conformational conversion (Gelpi et al., 2022). In cervids with chronic wasting disease (CWD), PRNP polymorphisms (e.g., S96, H95) modulate susceptibility, incubation period, prion burden, and strain properties. CWD strains further demonstrate adaptive evolution in novel hosts (e.g., the H95′ strain in tg60 transgenic mice), emphasizing the critical role of PRNP diversity in intra- and interspecies prion adaptation (Duque Velasquez et al., 2020).

Cross-species transmission represents a major evolutionary mechanism in prion biology, primarily governed by structural compatibility between exogenous PrP^∧Sc and host PrP^∧C. This compatibility is determined by sequence homology and conformational dynamics influenced by host PRNP polymorphisms. Protein misfolding cyclic amplification (PMCA) assays evaluating the zoonotic potential of CWD prions reveal strict host-specific barriers. For instance, CWD prions from elk with 132MM or 132ML genotypes efficiently convert human 129VV PrP^∧C but display minimal conversion of 129MM PrP^∧C; elk 132LL prions demonstrate negligible conversion across genotypes. White-tailed deer (WTD)–derived prions exhibit even lower conversion efficiency for human 129VV PrP^∧C substrates (Wang et al., 2021). Specific PRNP alleles modulate transmission potential: WTD genotypes 96SS and 95HH confer reduced susceptibility; the 225F allele in mule deer prolongs the incubation period; sheep haplotype VRQ facilitates scrapie transmission, while ARR confers protection. In humans, homozygosity for methionine at codon 129 markedly increases susceptibility to variant CJD. These polymorphisms reconfigure the conformational landscape of PrP^∧C, influencing templating efficiency and conversion kinetics. Alleles such as 96S in WTD and 225F in mule deer function as molecular bottlenecks, emulating interspecies transmission barriers. Such polymorphic dynamics underpin the reported ability of CWD to infect diverse species—including Sus scrofa (swine), Ovis aries (sheep), and Bos taurus (cattle)—highlighting the pressing need for comprehensive risk assessment of its zoonotic potential (Moazami-Goudarzi et al., 2021).

In summary, prion evolution fundamentally differs from that of nucleic acid-based pathogens, being mediated solely through protein conformational transitions. This process is elaborately regulated by host genetic factors (notably PRNP polymorphisms) and the intestinal microenvironment. The GI tract not only acts as a critical site for prion uptake and initial propagation but also functions as a dynamic junction where microbial ecology and host genetics converge to determine misfolding efficiency, neuroinvasion capacity, and disease progression. Furthermore, polymorphic variations in host PrP^∧C impose substantial—albeit frequently surmountable—barriers to cross-species transmission, enabling the adaptive evolution of novel prion strains with expanded host ranges and altered pathogenic properties. Elucidating the interactions between protein misfolding dynamics, host genetic predisposition, and interspecies transmission potential is critical for forecasting outbreak risks, identifying therapeutic targets (e.g., interventions against gut-phase amplification or PrP^∧Sc formation), and reducing zoonotic risks posed by animal prion diseases such as CWD.

3 Virulence factor-based analysis Paradigm: Escherichia coli and beyond

3.1 E. coli as a model for virulence factor evolution and detection strategy

Escherichia coli stands as the preeminent Gram-negative model for virulence evolution research, leveraging its comprehensively annotated genome, unparalleled genetic tractability, and robust experimental versatility. Systematic dissection of its nine intestinal pathotypes—enteropathogenic E. coli (EPEC), enterohemorrhagic E. coli (EHEC), enterotoxigenic E. coli (ETEC), enteroinvasive E. coli (EIEC), enteroaggregative E. coli (EAEC), diffusely adherent E. coli (DAEC), adherent-invasive E. coli (AIEC), alongside emerging hybrid pathovars—reveals how horizontally transmitted mobile genetic elements orchestrate virulence arsenals. Plasmids, bacteriophages, and composite transposons encode EHEC's Shiga toxins (stx1/stx2), EPEC's type III secretion system effectors (EspA/B/D), and ETEC's colonizing factors (CFA/I/II/IV) coupled with heat-labile and heat-stable enterotoxins. These molecular adaptations exemplify real-time pathoadaptation driven by genomic plasticity, providing an evolutionary roadmap for enteropathogens (Pakbin et al., 2021).

Critically, E. coli exhibits bimodal genomic architecture characterized by ~1,000–3,000 essential core genes vs. dynamic accessory genomes enabling ecological diversification. Its eight phylogenomic groups (A, B1, B2, C, D, E, F, cryptic clade I) harbor hybrid pathogens that maintain equilibrium between virulence and commensalism. When integrated with single-cell omics and CRISPR-interference (CRISPRi) technologies, this model illuminates landscape-scale gene flux across microbial guilds, spatiotemporal dynamics of host-pathogen dialogues, and rational design of next-generation vaccines exemplified by MecVax against ETEC (Geurtsen et al., 2022). This cross-kingdom relevance extends to viral, prion, and bacterial pathogenesis studies, directly catalyzing diagnostic innovation through comparative pathoadaptation mechanisms.

3.2 Overview of VFDB and virulence factor selection

The Virulence Factor Database (VFDB) represents the definitive resource for virulence annotation (Liu B. et al., 2022). The 2022 release introduces transformative features including ontological restructuring into 14 universal categories such as adhesion, invasion, and toxin production, with over 100 subcategories resolving longstanding taxonomic biases. Expanded curation encompasses 1,885 adhesins, 391 invasins, and a novel immunoevasion class addressing functional redundancy. Computational optimization via a JavaScript-free interface accelerates large-scale queries, while standardized datasets enable machine learning-driven virulence prediction through homology searches and functional forecasting.

Our analysis leveraged 335 curated Escherichia coli virulence factors from VFDB spanning enteropathogenic E. coli (EPEC), Shiga toxin-producing E. coli (STEC), and emerging pathotypes. These molecular determinants encapsulate mobile genetic element-mediated evolutionary mechanisms detailed in Section 3.1, with phylogenomic interrogation revealing tempo-spatial patterns of virulence module dissemination across ecological gradients through recombination hotspots and selection signatures.

3.3 Functional annotation and molecular mechanism inference of E. coli virulence factors

To systematically characterize the functional modules and pathogenic mechanisms of Escherichia coli (E. coli) virulence factors, this study conducted high-throughput annotation and mechanistic inference of 335 representative virulence genes curated from the Virulence Factor Database (VFDB). We integrated three widely utilized bioinformatics platforms—COG (Clusters of Orthologous Groups), GO (Gene Ontology), and InterProScan—to link large-scale data mining with detailed molecular interpretation.

Initial annotation via the COG database was performed for 301 virulence factors, with GO functional terms assigned to 67 genes (Figure 1A); collectively, these platforms annotated 225 genes. An additional 110 genes were annotated by only one system, while 135 remained unannotated, highlighting significant functional ambiguity. The updated COG platform enhances annotation accuracy and cross-species consistency through RefSeq identifier stabilization, incorporation of over 200 new protein families, and reintroduction of detailed metabolic pathway classifications—particularly improving annotation of key virulence genes such as Shiga toxins (Figure 1B) (Galperin et al., 2021). Integration with InterProScan domain analysis assigned clear functional roles to 125 of the previously unannotated 135 factors, underscoring the utility of domain-based strategies in completing annotations. By integrating multiple signature databases and AlphaFold-predicted structures, InterProScan provides multilayered annotations (Figure 1C)—including GO terms for molecular function, biological process, and cellular component—thereby supporting robust virulence genomics and anti-infective discovery (Blum et al., 2025). In total, InterProScan successfully annotated 327 of the 335 virulence factors, significantly improving annotation coverage and reliability (Figure 1D).

Figure 1

Figure 1. Functional annotation analysis of high-quality Escherichia coli virulence factors (n = 335). Integrative multi-dimensional functional annotation of 335 rigorously curated Escherichia coli virulence factors from the Virulence Factor Database (VFDB), presented in four panels (A–D): (A) Differential functional enrichment analysis. (A1) Gene Ontology (GO) enrichment comparing high-confidence virulence factors to the full VFDB dataset, identifying 43 significantly upregulated genes (P < 0.01; detailed statistical methods in Methods). (A2) Functional categorization of these 43 genes shown as a bar chart, with colors corresponding to Clusters of Orthologous Groups (COG) categories in panel (B) to facilitate integrative cross-platform comparison. (B) COG-based functional annotation of all 335 virulence factors depicted as a pie chart showing proportional distribution across categories; color scheme matches panel (A2) for consistency. (C) InterProScan domain-based annotation of 135 virulence factors initially classified as “function unknown” by COG, with 125 successfully annotated. The 30 most frequent functional categories, ranked by occurrence, are visualized in a donut chart, highlighting core functional modules derived from protein domain analysis. (D) Comparative annotation coverage across COG, GO, and InterProScan platforms shown as a stacked bar chart, quantifying relative completeness and illustrating the complementary strengths of the combined approaches, emphasizing enhanced functional resolution via integration.

3.3.1 Effector and toxin-associated mechanisms

Approximately 21% of annotated factors are linked to classical effector or toxin functions, including families such as NleG, Shiga toxins, and cytolethal distending toxins (CDT). These factors disrupt host metabolism, cell cycle regulation, or immune responses. GO enrichment for “toxin metabolic process” and classification within COG category Q (secondary metabolite biosynthesis) further support their central role in virulence mechanisms (Marcos-Vilchis et al., 2025).

3.3.2 Repeat domains and regulatory mechanisms

Roughly 18.1% of factors contain repeat motifs (e.g., ankyrin repeats, leucine-rich repeats), suggesting involvement in protein–protein interactions and DNA-binding activities related to virulence regulation. InterProScan identified H-NS-like DNA-binding regulators within this group, while COG category U classification implicates these proteins in intracellular transport and signal transduction.

3.3.3 Adhesion and structural components

Approximately 9.4% of factors, including fimbrial adhesins (e.g., PapE), are implicated in bacterial adherence and structural assembly—processes essential for host colonization. GO enrichment analysis confirmed significant involvement of adhesion-related pathways.

3.3.4 Secretory and nutrient acquisition systems

Around 10.1% of genes contribute to secretion systems (e.g., type III secretion system [T3SS]) and siderophore-mediated iron uptake (e.g., enterobactin receptors), with enrichment in COG categories P (secretion systems) and U. T3SS components (e.g., SsaH, SctQ) facilitate direct effector translocation into host cells to modulate immune responses, while siderophore systems confer nutritional advantages within host environments, positioning them as attractive anti-infective targets (Cavas and Kirkiz, 2022).

Additionally, 7.2% of genes were grouped into fragmented or poorly defined functional categories, including those encoding ribosome-inactivating domains, suggesting uncharacterized virulence mechanisms. Approximately 10 virulence factors remained unannotated by all methods, warranting further investigation via structural modeling and multi-omics approaches.

The integrated use of COG, GO, and InterProScan has substantially enhanced both the depth and resolution of E. coli virulence gene annotation. This comprehensive framework clarifies principal functional classes of virulence factors and establishes a scalable methodological basis for functional inference across diverse pathogenic taxa.

3.4 Extension to other intestinal Pathogens: resources and limitations

Following the multi-dimensional functional annotation and mechanistic classification of Escherichia coli (E. coli) virulence factors, this study evaluates the feasibility of extending this analytical paradigm to other major intestinal pathogens, including viruses, fungi, parasites, and prions. Despite divergent evolutionary trajectories and infection mechanisms, these pathogens universally rely on functionally defined virulence factors and pathogenic strategies for critical processes such as host invasion, immune evasion, and infection establishment. Cross-species conservation assessments of bacterial virulence factors—such as quorum-sensing systems (QSSs)—may yield critical insights for anti-virulence strategies targeting viruses or parasites, enabling the identification of shared mechanisms and facilitating the development of broad-spectrum anti-virulence agents. Additionally, methodologies including genome island detection, pathogen genome-wide association studies (GWAS), and associated functional validation pipelines may be adapted for non-bacterial pathogen research (Lau et al., 2023).

3.4.1 Cross-species applicability of mainstream analytic platforms

Many mainstream analytic platforms are inherently designed for cross-species utility. For example, InterProScan performs protein function annotation based on structural domains and supports bacterial, eukaryotic, and viral proteins, making it suitable for identifying fungal virulence factors, viral structural proteins, and protozoan effectors. The Gene Ontology (GO) system, a taxonomically neutral functional classification standard, is widely used for annotating viral envelope proteins, fungal adhesins, and parasitic secretory factors. Metabolic pathway databases such as KEGG and Reactome further aid in identifying shared biological processes associated with virulence expression across pathogen types. KEGG, for instance, provides a genome browser integrating viral ortholog clusters (VOCs) and KEGG Orthology (KO) entries to support conserved order analysis and functional prediction of viral genes; recent “provisional KO” definitions extend its coverage in viral annotation (Homma et al., 2023).

With the increasing availability of high-precision protein structure prediction tools like AlphaFold, domain-based modeling has emerged as a powerful approach to compensate for genome annotation gaps. AlphaFold-Multimer (AFM) enables complex structure prediction, offering a framework to dissect cross-species interactions among virulence factors—a critical advantage where conventional homology-based methods fail. These structural insights provide a molecular basis for understanding host–pathogen interactions and disease resistance mechanisms in both humans and crops. Integrating structural genomics with evolutionary algorithms may further accelerate the co-development of interactomics and function prediction pipelines (Jin et al., 2023).

3.4.2 Pathogen-specific barriers to implementation

Despite the potential for cross-application, pathogen-specific biological differences impose practical challenges. Viral genomes are typically short with frequent overlapping genes, complicating open reading frame (ORF) detection and function prediction. Viral proteins often lack homologous sequences, rendering traditional annotation tools ineffective. Fungi exhibit complex genome architectures, alternative splicing, and epigenetic regulation, demanding higher annotation accuracy. Protozoan parasites (e.g., Cryptosporidium, Plasmodium) display pronounced stage-specific gene expression, with many virulence factors restricted to specific life stages, challenging static annotation methods. Prions, as non-nucleic acid infectious agents, lie entirely outside sequence-based analysis, requiring structure modeling and biophysical experiments. While platforms like Companion address issues such as inaccurate gene models, limited RNA sequencing (RNA-Seq) support, or poor-quality reference genomes through genome alignment and visualization tools, challenges persist due to the lack of standardized evaluation criteria, high interspecies sequence variability, and strict International Nucleotide Sequence Database Collaboration (INSDC) submission requirements (Haese-Hill et al., 2024).

Several pathogen-specific databases support functional annotation across diverse pathogen types:

(1) PHI-base (Pathogen–Host Interactions Database): Launched in 2005, PHI-base is an open-access database cataloging experimentally verified pathogen–host interaction phenotypes, including virulence genes and effector proteins in fungal, bacterial, and protozoan pathogens. Adhering to FAIR principles (Findable, Accessible, Interoperable, Reusable), it supports cross-species comparative analysis and facilitates target discovery in medicine, agriculture, and ecology (Urban et al., 2022).

(2) EuPathDB: Integrating genomic, transcriptomic, and phenotypic data for 22 eukaryotic parasites (e.g., Leishmania, Toxoplasma, Trypanosoma), EuPathDB enables virulence factor screening via multi-step ortholog-based search strategies. For example, Plasmodium-derived genes can guide the identification of apicoplast-targeting genes in Toxoplasma. The platform offers over 80 search functionalities and user annotation tools, supporting biosecurity and global health initiatives. Future updates will incorporate phenotype and metabolome datasets to enhance discovery capabilities (Aurrecoechea et al., 2010).

(3) ViPR (Virus Pathogen Database and Analysis Resource): Supported by the U.S. National Institute of Allergy and Infectious Diseases (NIAID) Bioinformatics Resource Center (BRC), ViPR integrates multi-viral family data, including sequence records, gene/protein annotations, 3D structures, immune epitopes, clinical metadata, and comparative genomics results. It serves as a comprehensive resource for virology research, supporting diagnostics, therapeutics, and preventive strategies for high-priority and emerging viral pathogens.

(4) PrionHome: Compiling ~2,000 sequences, PrionHome uses N/Q-bias analysis and hidden Markov model (HMM) algorithms to identify prion-related proteins, including known prionogenic sequences (PrP, Sup35p, Ure2p), candidate prion sequences, and their homologs. It analyzes key features (N/Q-rich domains, YYR motifs, intrinsically disordered regions, structural elements) to aid prion candidate screening. Case studies demonstrate that yeast prion sequences exhibit strong N/Q enrichment and retain characteristic motifs (e.g., YYR in PrP), while interaction partners (e.g., GPR1) can induce prion formation via cross-seeding. Users can efficiently search via BLAST or SQL queries; future updates plan to incorporate polymorphism data for enhanced functionality (Harbi et al., 2012).

Despite inherent biological differences among pathogen classes, the annotation and mechanistic classification framework developed for E. coli virulence factors offers significant translational value, reflected in three key aspects:

(1) Broad Applicability of Domain-Based and Phylogenetic Tools: Platforms like InterProScan, GO, and COG leverage structural domains and evolutionary conservation, ensuring robust performance across bacteria, fungi, viruses, and protozoa—providing a common basis for virulence gene identification.

(2) Cross-Pathogen Adaptability of Functional Module Mapping: Virulence modules defined in E. coli (effectors, adhesion, secretion, metabolic pathways) can be analogously mapped to other pathogen types. For example, fungal membrane proteins, viral capsid proteins, and protozoan secretory factors may correspond to similar functional categories.

(3) Enhanced Predictive Power via High-Dimensional Tools: Techniques such as AlphaFold-Multimer (AFM), protein language models (e.g., ESM), and GWAS enable structural inference and semantic embedding for candidate identification, even in contexts lacking homologs, exhibiting lifecycle divergence, or complex genome structures—thus improving generalization capacity.

The virulence factor mining and annotation strategy established for E. coli represents a scalable methodological paradigm extendable to diverse intestinal pathogens (fungi, parasites, viruses, prions). This framework provides critical support for broad-spectrum pathogen detection and control, advancing both basic research and translational applications in infectious disease management.

4 Molecular diagnostics informed by evolutionary Signatures: integrative strategies and practical challenges

Genomic variants accumulated during the long-term evolution of enteric pathogens reflect adaptive mechanisms underlying host colonization, virulence enhancement, and immune evasion. Concurrently, these variants provide critical molecular targets for precise diagnostics. Virulence genes, resistance determinants, and insertion sequences—characterized by lineage-specific stability and functional specificity—have emerged as core biomarkers for pathogen detection. Advances in large-scale genome sequencing have enabled the identification of evolutionarily representative genomic regions, facilitating their translation into rapid clinical diagnostic assays. Building on the comprehensive annotation of 355 Escherichia coli (E. coli) virulence factors, this section extends the “evolution-driven marker emergence” paradigm to fungal, parasitic, viral, and prion pathogens, emphasizing their diagnostic relevance across nucleic acid detection, protein conformational analysis, and related molecular modalities.

4.1 Diagnostic targets derived from pathogen genome Evolution: types and representative examples

Pathogen genomes acquire virulence determinants, resistance traits, and environmental adaptation features via horizontal gene transfer (HGT), recombination, point mutations, and chromosomal rearrangements, enhancing ecological fitness and pathogenicity (Good et al., 2025). These evolution-driven genetic variations facilitate niche expansion and virulence enhancement while serving as stable, functionally explicit biomarkers for molecular diagnostics. Key targets include virulence genes, resistance loci, pathogenicity islands, antigenic variation-related regions, and regulatory domains—all exhibiting high evolutionary conservation and functional specificity.

E. coli exemplifies these evolutionary dynamics. The O104:H4 strain, which acquired virulence elements from both uropathogenic (UPEC) and enterohemorrhagic (EHEC) lineages via HGT, harbors the stx2-encoding prophage and locus of enterocyte effacement (LEE) pathogenicity island—both characterized by high structural conservation and stable maintenance. These features render them critical targets for CRISPR-based diagnostics targeting persistent public health threats (Kimata et al., 2020). The high-risk sequence type 131 (ST131) clone, which coharbors β-lactamase genes (e.g., bla_{CTX − M−15}) and virulence factors (e.g., aec, bap), facilitates global dissemination and multidrug resistance. Its genetic stability supports application in rapid field detection platforms such as loop-mediated isothermal amplification–lateral flow assay (LAMP-LFA; Mills et al., 2022). Furthermore, the highly conserved eae and tir genes within the LEE island, whose subtype distributions correlate tightly with serotypes, with structural variations localized to intergenic and terminal regions, serve as essential markers for multi-omics and machine learning (ML)–based strain typing and pathogenicity prediction (Sváb et al., 2022).

Pathogenicity in fungi primarily arises from chromosomal rearrangements and expansions of surface protein families. For example, Candida auris harbors 30 tandem repeats of the ALS4 gene (encoding 1844 amino acids) in the subtelomeric region of chromosome 5, augmenting adhesion and biofilm formation. The pronounced expression (~400-fold) and copy number variation (CNV) at this locus represent key targets for protein microarrays and ML approaches, enabling strain tracking and outbreak risk assessment in clinical settings (Bing et al., 2023).

Antigenic variation mediated by Variant Surface Protein (VSP) families is a hallmark of parasitic adaptation. In Giardia lamblia, hundreds of VSP genes undergo tightly regulated epigenetic switching to ensure monoallelic expression, facilitating immune evasion. This mechanism underpins pathogenic evolution and offers novel targets for structural bioinformatics and CRISPR-based interventions (Rodriguez-Walker et al., 2022).

RNA viruses exhibit rapid antigenic evolution driven by high mutation and recombination rates. In Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), mutations in the Spike protein's receptor-binding domain (RBD) and N-terminal domain (NTD)—notably N501Y and N439R—significantly enhance transmissibility and immune escape. Similarly, norovirus GII.4's major capsid protein VP1 contains hypervariable antigenic sites that facilitate immune evasion and epidemic spread. With over one million SARS-CoV-2 genomes sequenced, deep sequencing enables real-time variant monitoring and supports extensive ML modeling efforts (Harvey et al., 2021).

Prions, lacking nucleic acids, depend on conformational alterations of the prion protein (PrP) for pathogenicity. Polymorphisms in the PRNP gene modulate the stability of the β2-α2 loop and α3 helix in cellular PrP (PrP^∧C), influencing susceptibility, transmission, and progression of chronic wasting disease (CWD). In vitro studies using protein misfolding cyclic amplification (PMCA) and nuclear magnetic resonance (NMR) have elucidated these polymorphisms' mechanistic roles in conversion to the scrapie isoform (PrP^∧Sc), providing a basis for proteomic interventions and early diagnostic markers (Moazami-Goudarzi et al., 2021).

Diagnostic targets derived from pathogen evolutionary signatures encapsulate fundamental mechanisms of host adaptation and serve as a foundation for developing highly specific and stable molecular assays. Integration with multi-omics data and machine intelligence enhances detection efficiency of pathogen evolutionary dynamics, advancing precision medicine and public health surveillance.

4.2 Adaptation mechanisms between technological platforms and Biomarkers: from detection to imaging

Pathogen genome evolution not only drives the emergence of novel virulence and resistance mechanisms but also shapes recognizable molecular diagnostic targets. Diverse evolutionary products—including point mutations, genomic island insertions, and structural rearrangements—align with optimal detection technologies. This section categorizes major diagnostic platforms by biomarker type and systematically reviews their target adaptation mechanisms, with practical value illustrated through representative pathogens.

4.2.1 Point mutations and minor variants: CRISPR-Cas and digital PCR systems

Point mutations represent pivotal adaptive mechanisms in pathogens, frequently linked to enhanced resistance or immune evasion. For example, non-synonymous mutations in the mgrB gene of Klebsiella pneumoniae (K. pneumoniae) inactivate the PhoP/PhoQ two-component regulatory system, upregulating lipid A modification genes that increase L-Ara4N or P-EtN modifications. These changes reduce colistin affinity, inducing resistance. Atomic force microscopy (AFM) and transmission electron microscopy (TEM) confirm that mutant strains exhibit thickened capsules and enhanced cell wall rigidity, which hinder antibiotic penetration. Increased capsular polysaccharide (CPS) synthesis and ion transport particle accumulation further amplify resistance and transmission potential, necessitating targeted detection and combination therapies (Yap et al., 2022).

CRISPR-Cas12a/Cas13a systems, with base-level recognition capability, enable precise CRISPR RNA (crRNA)-guided targeting of mutation sites (e.g., stx2a, bla_{NDM − 1}) when combined with polymerase chain reaction (PCR) or recombinase polymerase amplification (RPA). This achieves visual detection of virulence and resistance mutations within 60 min. Optimized reverse transcription recombinase-aided amplification (RT-RAA)-Cas12a assays detect norovirus genotypes GII.4 and GII.17 at ultra-low viral loads (~0.1 copies/μL) within 30–40 min, offering rapid, portable field diagnostics (Qian et al., 2022).

Digital PCR (dPCR), with its absolute quantification capacity, sensitively detects resistance-related single nucleotide polymorphisms (SNPs; e.g., rlmL, mltB) in bloodstream infections. It facilitates low-frequency mutation screening and dynamic modeling, demonstrating superior sensitivity and specificity in diagnosing Escherichia coli (E. coli) bacteremia compared to conventional molecular methods. This positions dPCR as a promising novel rapid resistance biomarker (Kitagawa et al., 2025).

4.2.2 Genomic islands and integrated elements: LAMP, RPA, and lateral flow assays

Pathogenicity islands or resistance plasmids acquired via horizontal transfer are key drivers of bacterial genome evolution. For instance, structural variations in the 3′ untranslated region (3′UTR) of aggR in enteroaggregative E. coli (EAEC) enhance transcript stability, upregulating AggR expression. This promotes motility, pAA plasmid conjugation, and adhesion-related metabolic pathways, significantly boosting pathogenicity. The locus of enterocyte effacement (LEE) island in enterohemorrhagic E. coli (EHEC) integrates at specific loci to encode virulence factors (e.g., eae), facilitating effector secretion and host attachment. EAEC's pAA plasmid coordinates adhesion and metabolism through aggR and aafA, intensifying virulence and plasmid dissemination (Prieto et al., 2021).

Due to their distinct structural specificity, these elements are well-suited for target recognition via loop-mediated isothermal amplification (LAMP) and RPA, combined with lateral flow assays (LFA) for equipment-free rapid onsite detection. LAMP-LFA systems demonstrate high sensitivity and adaptability in rapidly screening novel virulent strains (e.g., E. coli O104:H4, Clostridioides difficile ribotype 027 [RT027]) in complex samples, providing reliable technical support for food safety and public health surveillance (Nuchchanart et al., 2023).

4.2.3 Structural rearrangements and repeat Expansions: nanopore sequencing and protein microarrays

Certain fungi and parasites exhibit structural rearrangements and copy number amplifications during evolution, necessitating high-throughput sequencing or structural probe techniques for detection. For example, multiple clinical strains of Candida auris acquire fluconazole resistance through duplication of ERG11 and TAC1B genes, while Giardia lamblia achieves antigenic variation via tandem repeats and expression switching of Variant Surface Proteins (VSPs), underpinning chronic infection (Rodriguez-Walker et al., 2022). Such structural variants challenge conventional PCR and require long-read platforms like nanopore sequencing to resolve large rearrangements.

Structural prediction tools (e.g., AlphaFold) accurately model protein 3D conformations, aiding identification of domain expansions and diagnostic epitope variations, thereby enhancing conformational epitope recognition efficiency. Protein microarrays enable high-throughput screening of linear epitopes; when integrated with AlphaFold-mapped binding sites, they facilitate discovery of potential conformational epitopes, improving the specificity and accuracy of diagnostic targets (Grewal et al., 2024).

4.2.4 Conformational changes and epigenetic modifications: aggregation detection and high-throughput mass spectrometry

Certain pathogen evolutionary variations manifest not at the sequence level but as protein conformational changes or post-translational modifications. For instance, in variant Creutzfeldt-Jakob Disease (vCJD), PrP^∧Sc exhibits unique glycosylation patterns and amyloid aggregate conformations, leading to enhanced amplification efficiency and sensitivity in real-time quaking-induced conversion (RT-QuIC) and protein misfolding cyclic amplification (PMCA) assays. RT-QuIC monitors PrP^∧Sc-induced fibril formation in real time, while PMCA amplifies PrP^∧Sc via autocatalytic conversion, jointly supporting early non-invasive vCJD diagnosis (Camacho et al., 2019).

Fungi also commonly display species-specific glycosylation modifications with diagnostic potential. Clinical Candida isolates frequently present O-linked β-N-acetylglucosamine (O-GlcNAc) glycosylation on adhesion proteins, serving as candidate diagnostic antigens. Surface-enhanced Raman spectroscopy (SERS), combined with Fe₃O₄@polyethyleneimine (PEI) magnetic nanoparticle capture and silver nanoparticle (AgNP) signal enhancement, directly detects O-GlcNAc spectral features. Coupled with orthogonal partial least squares discriminant analysis (OPLS-DA) modeling, classification accuracy reaches up to 99.8%, outperforming culture-dependent matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). This non-destructive SERS strategy reduces detection time to 1 h, demonstrating significant advantages for early diagnosis of candidemia (Hu et al., 2021).

4.3 Trends in pan-pathogen diagnostics driven by multi-omics and intelligent computing

As gut pathogens evolve at the population level, traditional diagnostic methods reliant on single virulence or resistance factors have increasingly exposed their limitations, particularly in contexts of co-infection, frequent mutation, and enhanced environmental adaptation. Multi-omics strategies integrated with intelligent tools such as machine learning (ML) are driving the development of “cross-pathogen” diagnostic platforms, providing a systematic framework to unravel complex infectious etiologies.

Recent metagenomic sequencing combined with variant analysis has been widely used to monitor horizontal transfer of resistance islands and virulence factors within gut microbiomes. For example, metagenomic studies identified plasmid-mediated horizontal gene transfer (HGT) of CTX-M-type β-lactamase genes (bla_{CTX − M}) from Escherichia coli (E. coli) to Klebsiella pneumoniae (K. pneumoniae) in hospital wastewater in northern India, with high abundance in urban hospital samples. The gene cassette structure of class 1 integrons (including intI1 and sul1) co-occurs tightly with bla_{CTX − M}, and specific domains such as the attC site are recognized as evolutionary targets in the HGT process. These findings underscore hospital wastewater as a critical reservoir for antibiotic resistance gene (ARG) dissemination and emphasize the need for intervention strategies targeting integron structures to curb antimicrobial resistance (AMR) spread (Talat et al., 2023).

Multi-omics approaches also demonstrate significant diagnostic value for viral and protozoan pathogens. Norovirus genotype GII.4 (NoV GII.4) enhances replication and antigenic variation through ORF1/2 recombination and mutations in the RNA-dependent RNA polymerase (RdRp) region, with key antigenic mutations in sites A and D of the P2 domain driving immune evasion. Omics analyses reveal these mutations cluster in the P2 domain, where machine learning models predict immune escape potential based on sequence and structural features. Consequently, strategies targeting conserved regions of the P2 domain for broad-spectrum antibodies and multivalent virus-like particle (VLP) vaccines have been proposed to address challenges posed by ongoing GII.4 evolution (Tohma et al., 2022).

In Giardia lamblia (G. lamblia), the Variant Surface Protein (VSP) family exhibits pronounced sequence polymorphism and splicing isoform diversity during host adaptation, resulting in highly heterogeneous expression profiles. Single-cell transcriptomics reveal dynamic VSP expression patterns underlying antigenic variation, and deep learning models trained on these data can automatically classify virulence subtypes and identify key features linked to immune escape and host specificity. This approach offers a powerful tool for rapid prediction of Giardia virulence evolution and individual adaptability, informing precise intervention strategies (Rodriguez-Walker et al., 2022).

Structural omics coupled with artificial intelligence (AI)-assisted prediction is emerging as a powerful tool to discover cross-species virulence domains. AlphaFold2 combined with sequence alignments has uncovered highly conserved β-helical core domains in the ALS family adhesins of Candida albicans (C. albicans) and Candida tropicalis (C. tropicalis), providing a common structural basis for cross-species adhesion functionality. This conserved domain serves as an ideal target for protein microarray typing, supporting lineage tracing and pathogenicity studies, and aiding the development of intervention strategies (Oh et al., 2021). Similar approaches have been employed to explore previously unannotated virulence factors in enterohemorrhagic E. coli (EHEC) strains. Studies use AlphaFold2 to predict their 3D structures and apply random forest algorithms to identify discriminative functional epitopes, enabling the design of novel multiplex diagnostic platforms that bridge “gene sequence annotation” and “structural-functional localization.”

With increasing complexity of evolutionary mutations and expansion of pathogen spectra, integration of multi-omics data with AI algorithms is driving diagnostics from “specific site recognition” toward “generalized evolutionary prediction.” By categorizing, aggregating, and mapping mutation features onto structure-function relationships, diagnostic systems are increasingly capable of identifying novel variants, predicting transmission potential, and forecasting resistance trends. This paradigm shift not only enhances diagnostic accuracy for complex infections but also provides critical technological support for rapid responses to emerging pathogens.

4.4 Technology integration and real-world challenges: from laboratory to clinic and field

Despite rapid advancements in molecular diagnostics due to their high sensitivity and specificity for infectious disease detection, translating these technologies from laboratory research to real-world field applications presents persistent practical constraints. Particularly given the rapid evolution and transmission diversity of gut pathogens, single detection techniques often fail to balance broad-spectrum capability, cost-effectiveness, and field adaptability. Consequently, integrated technological approaches have become essential for overcoming these barriers.

4.4.1 Multi-technology integration: enhancing field adaptability

CRISPR-Cas systems, loop-mediated isothermal amplification (LAMP), and protein structural recognition technologies are increasingly integrated for synergistic application. For example, portable diagnostic platforms combining CRISPR/Cas12a with LAMP enable multiplex detection of Escherichia coli (E. coli) virulence factors within 40 min, providing instrument-free visual interpretation via lateral flow strips or LED blue light. This approach achieves high sensitivity and specificity suitable for field applications in resource-limited regions (Shi et al., 2022). Field validation across rural clinical settings demonstrated 96.4% detection sensitivity, confirming the utility of integrated platforms for pathogen screening in low-resource environments.

4.4.2 Sample compatibility optimization: mitigating inhibitor interference

Complex matrices such as feces and wastewater contain inhibitors that compromise diagnostic accuracy through false-negative results. Incorporating reduced graphene oxide (rGO) into lateral flow assay (LFA) electrodes enhances electrochemical signal stability by over three-fold, leveraging rGO's electron transfer efficiency, gold nanoparticle immobilization capacity, and enzyme stabilization properties. This platform successfully identified Shiga toxin-positive samples in simulated diarrheal stool, demonstrating robust potential for field diagnostics under challenging sample conditions (Calucho et al., 2024).

4.4.3 Addressing expression heterogeneity: from structural to functional monitoring

Virulence gene expression heterogeneity represents a critical gap in current surveillance. Hybridization chain reaction (HCR) RNA-fluorescence in situ hybridization (RNA-FISH) revealed spatiotemporal variation in Candida albicans (C. albicans) HWP1 expression during murine tongue mucosa infection, illustrating dynamic virulence regulation under host immune pressure. This phenomenon may explain asymptomatic carriers or atypical presentations, indicating that future field diagnostics should incorporate expression-sensitive biomarkers (Lindemann-Perez et al., 2024).

4.4.4 Translational framework: bidirectional adaptation

Effective translation from laboratory validation to field deployment requires aligning diagnostic design with pathogen evolutionary mechanisms. Prioritizing stress-resistant conserved domains avoids overreliance on variable promoter targets. Concurrently, integrating virulence expression prediction into diagnostic models enhances interpretability for heterogeneous samples and complex infections.

This bidirectional integration model—synthesizing evolutionary insights with technological innovation—provides a critical pathway toward precise, efficient, and equitable infectious disease management.

5 Conclusions and future perspectives

The genomic evolution of enteric pathogens continually poses global public health challenges by driving enhanced virulence, dissemination of antimicrobial resistance (AMR), and host adaptation. Dynamic mechanisms—including horizontal gene transfer (HGT), chromosomal rearrangements, hypermutation, and epigenetic regulation—critically modulate pathogenic potential and epidemiology, thereby influencing the global burden of infectious diseases and intervention strategies. This review systematically examines the evolutionary trajectories of five major enteric pathogen classes (bacteria, fungi, parasites, viruses, and prions), emphasizing the central roles of virulence gene clusters, resistance elements, and mobile genetic elements (MGEs) in microbial pathogenicity. Using Escherichia coli (E. coli) as a paradigmatic model, we performed a comprehensive multidimensional annotation of 335 virulence factors (Figure 1), validating the feasibility of a closed-loop framework integrating genomic evolution, biomarker identification, and diagnostic assay development. This framework elucidates key molecular principles underlying pathogen-host interactions and provides methodological support for advancing precision diagnostics.

Recent advances highlight the translational potential of evolutionarily conserved diagnostic targets: CRISPR-Cas systems targeting the stx2 gene achieved complete concordance with clinical outcomes; loop-mediated isothermal amplification combined with lateral flow assay (LAMP-LFA) demonstrated 98.7% sensitivity for detecting bla_{NDM − 1} resistance mutations in fecal specimens; and AlphaFold-based structural domain prediction successfully identified immunogenic regions of the Cryptococcus HWP1 protein. These findings validate the robustness of evolutionarily stable biomarkers and provide a data-driven foundation for iterative technological refinement.

Nonetheless, the inherent complexity of enteric pathogen evolution poses significant challenges for diagnostic development:

(1) Phenotypic plasticity arising from host microenvironmental dynamics—including low-abundance co-infections and stress-induced gene expression reprogramming—limits the reliability of single-target assays;

(2) Rapid HGT of resistance elements outpaces diagnostic update cycles, necessitating dynamic surveillance frameworks; and

(3) Resource constraints in low-income regions restrict deployment of advanced technologies.

Future research directions to address these challenges include:

(1) Integration of multi-omics and real-time monitoring approaches: Leveraging single-cell spatial transcriptomics, deep mutational scanning, and nanopore sequencing to construct “digital twin” models that capture pathogen virulence heterogeneity and resistance mutation trajectories.

(2) Development of cost-effective, high-sensitivity diagnostics: Utilizing biomimetic magnetic bead capture, reduced graphene oxide (rGO)-quantum dot composite probes, and smartphone-based imaging to realize paper-based microfluidic platforms for point-of-care testing with per-assay costs under $5.

(3) Establishment of “One Health” surveillance networks: Integrating cloud-based artificial intelligence (AI) and real-time sequencing data across human, animal, and environmental reservoirs to enable early warning of emerging cross-species pathogens such as chronic wasting disease (CWD) prions.

In conclusion, elucidating genomic evolution in enteric pathogens not only advances fundamental understanding of disease mechanisms but also drives innovation in diagnostic development and public health strategies. The closed-loop paradigm of evolution-driven biomarker discovery and diagnostic translation holds promise for shifting infectious disease control from reactive responses toward proactive surveillance and precision intervention on a global scale.

Author contributions

TL: Writing – original draft, Conceptualization, Formal analysis, Methodology, Visualization, Writing – review & editing, Data curation, Investigation, Project administration. JL: Writing – original draft, Conceptualization, Formal analysis, Methodology, Visualization. ZT: Writing – original draft, Conceptualization, Methodology, Writing – review & editing, Investigation. XL: Writing – original draft, Conceptualization, Investigation. SY: Writing – original draft, Conceptualization, Data curation, Methodology. JZ: Writing – original draft, Conceptualization, Investigation, Methodology. WW: Writing – original draft, Data curation, Investigation. LH: Writing – review & editing, Methodology, Resources, Project administration. SC: Writing – review & editing, Methodology, Resources, Project administration. GZ: Writing – review & editing, Funding acquisition, Methodology, Resources, Data curation. ZL: Funding acquisition, Methodology, Project administration, Resources, Writing – review & editing.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. This work was supported by the Hunan Provincial Postgraduate Research and Innovation Project (Grant No. CX20240544 to TL) and the Large-scale Instrument Testing Open Fund of Hunan Normal University (Grant No. 24CSY224 to TL).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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