Microbial Bioactives

1. Introduction

There is something quietly unsettling about the idea that a therapy meant to restore health could, under the wrong circumstances, become a delivery system for the very problem it was designed to fight. That, in essence, is the paradox now confronting probiotic medicine. Antimicrobial resistance (AMR) has become one of the defining public health emergencies of this century, and it is not receding — if anything, the trajectory looks worse than most clinicians would like to admit (Idakwoji et al., 2026). In 2019 alone, bacterial AMR was directly responsible for an estimated 1.27 million deaths and was associated with nearly 5 million more (Idakwoji et al., 2026; Khosrojerdi et al., 2026; Mayyas et al., 2026). One might have expected the COVID-19 pandemic, with its own catastrophic mortality, to have at least temporarily eclipsed this burden; it did not. Even in 2021, amid global disruption to health systems, AMR was still linked to 1.14 million direct deaths and 4.71 million associated deaths (Khosrojerdi et al., 2026). And the forward-looking numbers are, frankly, hard to sit with: left unaddressed, AMR-attributable mortality could climb toward 10 million deaths a year by 2050 (Idakwoji et al., 2026; Ataei-Alamdari et al., 2026; Hussain et al., 2026a).

The economic dimension of this crisis compounds the clinical one. By some projections, AMR could cost the global economy as much as US$100 trillion by 2030 (Ataei-Alamdari et al., 2026), and could shrink global gross domestic product by up to 3.8% by mid-century — a burden that, predictably, falls hardest on low- and middle-income countries (Mayyas et al., 2026). What makes this especially frustrating is that the pharmaceutical response has not kept pace, and arguably could not have been expected to. Antibiotic development performs poorly against the economic logic governing most drug pipelines; a short course of treatment for an acute infection generates far less return than a lifelong maintenance therapy for a chronic disease, and investment has drifted accordingly (Ataei-Alamdari et al., 2026). The result is a pipeline that has, for decades, mostly recycled existing chemical scaffolds rather than introducing genuinely novel mechanisms of action — a gap between resistance emergence and therapeutic innovation that keeps widening rather than closing (Khosrojerdi et al., 2026).

Against this backdrop, attention has turned toward the gut microbiota — the vast, metabolically active community of microorganisms inhabiting the human gastrointestinal tract (Abdul Manan, 2025; Niculescu et al., 2026). This ecosystem does considerably more than digest food; it matures the immune system, produces short-chain fatty acids, and provides a form of ecological “colonization resistance” against invading pathogens (Idakwoji et al., 2026; Niculescu et al., 2026). When that balance is disturbed — by antibiotics, by diet, by illness — the resulting dysbiosis leaves the host more vulnerable to infection and chronic inflammation (Idakwoji et al., 2026; Niculescu et al., 2026). Probiotics, defined jointly by the FAO and WHO as “live microorganisms which, when administered in adequate amounts, confer a health benefit on the host” (Abdul Manan, 2025; Saleh et al., 2025), have long been used to try to restore that balance, building on a tradition rooted in fermented foods (Abdul Manan, 2025). Commercial formulations have historically leaned on Gram-positive lactic acid bacteria — Lactobacillus, Bifidobacterium, Streptococcus, Pediococcus, Lactococcus, and Enterococcus — alongside select strains such as Escherichia coli Nissle 1917 and the yeast Saccharomyces boulardii (Saleh et al., 2025; Niculescu et al., 2026).

More recently, and rather rapidly, the field has moved beyond these familiar strains. Advances in metagenomic sequencing and synthetic biology have opened the door to next-generation probiotics (NGPs) and Live Biotherapeutic Products (LBPs) — organisms such as Akkermansia muciniphila, Faecalibacterium prausnitzii, Bacteroides fragilis, and Roseburia species, chosen not for tradition but for specific immunomodulatory and metabolic functions (Abdul Manan, 2025; Tyagi et al., 2026; Niculescu et al., 2026). Precision genome-editing tools, particularly CRISPR-Cas and CRISPR interference (CRISPRi), now allow researchers to fine-tune these organisms for stress tolerance, gut colonization, and targeted molecule delivery (Hussain et al., 2026b; Nogueira et al., 2026). It is an exciting moment for the field — but it is also one that demands a degree of caution that has not always accompanied the enthusiasm.

Here is the uncomfortable part. Probiotics are routinely given to patients specifically because they have just received, or are about to receive, antibiotics — which is to say, they are introduced into precisely the selective environment most conducive to horizontal gene transfer (HGT) (Saleh et al., 2025; Lertcanawanichakul et al., 2026). Reframed through this lens, the human gut microbiome is not simply a passive bystander in the AMR crisis; it is one of the largest reservoirs of antimicrobial resistance genes (ARGs) in the human body, sometimes termed the “resistome” (Idakwoji et al., 2026). Commensal organisms, and the probiotics introduced alongside them, can carry ARGs that sit clinically silent for long stretches, only to mobilize rapidly once antibiotic pressure arrives (Idakwoji et al., 2026).

HGT is the principal evolutionary engine behind this mobilization, and it proceeds through three broadly recognized routes: conjugation, the direct cell-to-cell transfer of plasmids or conjugative transposons; transformation, the uptake of free environmental DNA; and transduction, the bacteriophage-mediated delivery of foreign genetic material (Idakwoji et al., 2026; Niculescu et al., 2026). Of the three, conjugation is generally considered the most consequential in the densely populated environment of the human intestine, simply because of how much physical contact between cells that setting affords (Idakwoji et al., 2026; Niculescu et al., 2026). Mobile genetic elements — plasmids, transposons, integrons — are the physical vehicles carrying resistance traits across these routes (Idakwoji et al., 2026; Niculescu et al., 2026), and certain plasmid replicon families, including IncX4, IncI2, and IncHI2, have emerged as particularly efficient vectors for global ARG spread (Niculescu et al., 2026). The conjugative plasmid TP114, for instance, has been documented to achieve remarkably high transfer rates within gut microbial populations (Idakwoji et al., 2026).

The clinical stakes are not abstract. Genes conferring extended-spectrum β-lactamase (ESBL) activity — bla_CTX-M, bla_TEM, bla_SHV — compromise third-generation cephalosporins, while the plasmid-borne mobilized colistin resistance gene mcr-1 threatens polymyxins, arguably the last meaningful line of defense against multidrug-resistant Gram-negative infections (Mayyas et al., 2026; Idakwoji et al., 2026; Saleh et al., 2025; Niculescu et al., 2026). Enterococci and E. coli residing quietly in the gut have been shown to act as silent incubators for vancomycin resistance (vanA, vanB) and carbapenemases (bla_KPC, bla_NDM) well before these determinants reach a pathogen of clinical concern (Idakwoji et al., 2026). Gut biofilms only make matters worse: their physical architecture impedes antibiotic penetration and allows dormant persister cells to linger, communicate, and exchange conjugative plasmids at elevated rates under localized selective pressure (Idakwoji et al., 2026; Hussain et al., 2026a). Nor is this confined to human medicine — subtherapeutic antibiotic use in animal agriculture has effectively turned livestock and poultry guts into an active crucible for HGT, with resistance genes circulating continuously between animals, the environment, and, eventually, the human resistome (Mayyas et al., 2026; Idakwoji et al., 2026).

Regulatory bodies have not been oblivious to this risk. The European Food Safety Authority, the U.S. Food and Drug Administration, and the joint FAO/WHO framework all mandate screening protocols intended to keep probiotic products from becoming vectors of resistance amplification (Hussain et al., 2026a; Saleh et al., 2025). One practical tool is the Multiple Antibiotic Resistance (MAR) index, a phenotypic measure in which a value above 0.2 is taken to suggest that a strain originated from a heavily antibiotic-exposed environment (Hussain et al., 2026a). Yet phenotype alone is not enough — it cannot reliably distinguish a strain’s transmissible resistance genes from stable, chromosomally fixed ones (Hussain et al., 2026a). This is why whole-genome sequencing (WGS) has, in a relatively short span of time, gone from optional to essentially non-negotiable as a screening requirement, particularly when paired with curated databases such as the Comprehensive Antibiotic Resistance Database (CARD) and the Virulence Factor Database (VFDB) (Hussain et al., 2026a; Saleh et al., 2025).

It is with this landscape in view that the present review is organized. We aim, first, to examine the molecular and biological mechanisms of horizontal gene transfer within the human gastrointestinal microbiome; second, to evaluate the role of mobile genetic elements as vectors of resistance dissemination between probiotic strains and host pathogens; third, to critically assess the safety and resistome profiles of both commercial and next-generation engineered probiotic strains, with particular attention to transferable ESBL, carbapenemase, and colistin resistance determinants; and fourth, to analyze current regulatory frameworks, genomic screening methodologies, and synthetic biocontainment strategies designed to mitigate these risks. Taken together, these objectives are meant not to condemn probiotic therapeutics — they remain, on balance, valuable tools — but to insist that their promise be pursued with the genomic rigor the resistome problem actually demands.

2. Gut Dysbiosis, Inter-Organ Communication, and the Resistome: Mechanisms and Precision Therapeutics

2.1 Eubiosis, Dysbiosis, and the Dynamics of Intestinal Permeability

It helps, before going further, to be precise about what a “healthy” gut microbiome actually looks like — not as a static inventory of species, but as a functioning ecology. The human gastrointestinal tract houses an estimated 3.8 × 10^13 microbial cells, and under ordinary physiological conditions this community exists in a state researchers call eubiosis: high taxonomic diversity, a resilient interaction network, and, crucially, substantial functional redundancy (Abeltino et al., 2024). That last property is easy to overlook but matters enormously — it refers to the capacity of taxonomically distinct organisms to perform overlapping metabolic jobs, so that the loss of any single species does not necessarily collapse the system's overall function (Abeltino et al., 2024). It is, in a sense, a built-in redundancy that buys the ecosystem some tolerance for minor perturbation.

Mechanistically, this stability rests on a fairly delicate physical arrangement: a single layer of intestinal epithelial cells, tight-junction proteins — zonula occludens-1 and -2, occludins, claudins — and a thick mucus layer secreted by goblet cells (Salem et al., 2018; Munteanu et al., 2025). Together these form a mucosal barrier that keeps luminal microbes physically and immunologically separated from the gut-associated lymphoid tissue (GALT), which happens to be the body's largest reservoir of immune cells (Salem et al., 2018). When environmental, pharmacological, or lifestyle stressors disturb this balance — and antibiotics are a particularly blunt disturbance — the system tips into dysbiosis (Socałą et al., 2021). What follows is fairly characteristic: a marked drop in microbial diversity, depletion of protective keystone taxa such as Faecalibacterium prausnitzii and Akkermansia muciniphila, and an overgrowth of opportunistic pathobionts, often within the Enterobacteriaceae family (Rampanelli & Nieuwdorp, 2023; Tan et al., 2026).

At the barrier level, dysbiosis compromises tight-junction assembly, increasing paracellular permeability in what is colloquially, if a bit imprecisely, called “leaky gut” (Salem et al., 2018). This breach permits translocation of viable bacteria, pathobionts, and pro-inflammatory microbial fragments — lipopolysaccharide (LPS) chief among them — across the epithelial monolayer into portal and systemic circulation, where they can trigger both local and systemic inflammatory cascades (Salem et al., 2018; Munteanu et al., 2025) (Figure 2).

This ecological breakdown is inseparable from shifts in microbial metabolism. Beneficial commensals ferment dietary fiber into short-chain fatty acids (SCFAs) — acetate, propionate, and butyrate being the dominant three — which function as critical regulatory signals rather than mere metabolic byproducts (Salem et al., 2018). Butyrate, in particular, serves as the primary energy substrate for colonic epithelial cells and reinforces tight-junction integrity by modulating occludin, claudin, and zonulin expression (Tan et al., 2026). SCFAs additionally act through G-protein-coupled receptors — GPR41, GPR43, GPR109a — to favor differentiation of anti-inflammatory regulatory T cells while suppressing pro-inflammatory Th1 and Th17 populations (Salem et al., 2018). In parallel, a healthy microbiota converts primary bile acids into secondary bile acids, such as deoxycholic and lithocholic acid, via specialized gene clusters like the bile acid-inducible (bai) operon found in certain Clostridiales (Suresh Kumar et al., 2026). When dysbiosis depletes the commensals responsible for these conversions, primary bile acids accumulate, SCFA output collapses, and the host's broader immunological competence takes a hit that extends well beyond the gut itself (Tan et al., 2026; Rampanelli & Nieuwdorp, 2023).

2.2 Systemic Inter-Organ Communication: Decoding the Physiological Axes

Bidirectional communication between the intestinal tract and the skin runs largely through the systemic circulation of immune and metabolic signals (Salem et al., 2018; Munteanu et al., 2025). Gut dysbiosis raises mucosal permeability, letting translocated bacterial DNA, LPS, and active metabolites reach the blood and lymphatic circulation (Munteanu et al., 2025). Once in cutaneous tissue, these mediators activate keratinocytes and recruit pro-inflammatory T cells, reducing synthesis of cutaneous antimicrobial peptides and precipitating inflammatory skin disorders such as atopic dermatitis (Munteanu et al., 2025; Lagoa et al., 2025). The relationship runs both ways, too: skin exposures — UV-stimulated vitamin D synthesis, topical treatments — can shift the composition of the intestinal microbiome in turn (Lagoa et al., 2025).

The gut-brain axis links the central nervous system to enteric metabolic outputs in a similarly bidirectional fashion (Socałą et al., 2021). Commensal gut bacteria synthesize a surprisingly diverse set of neuroactive molecules; Lactobacillus and Bifidobacterium produce acetylcholine and GABA, while Streptococcus, Enterococcus, and Escherichia contribute serotonin, dopamine, and norepinephrine (Socałą et al., 2021). Gut microbes also regulate tryptophan metabolism, controlling systemic availability of serotonin, melatonin, and indoles, while microbiota-derived SCFAs support neural plasticity, help maintain blood-brain barrier integrity, and modulate neuroinflammation (Socałą et al., 2021).

In veterinary medicine, the enteromammary pathway offers a particularly direct illustration of gut-distant organ trafficking (Li et al., 2025). Dendritic cells in the gut lamina propria sample luminal microorganisms, ferry them through the lymphatic system to mesenteric lymph nodes, and ultimately traffic them to mammary-associated lymph nodes, where they help shape the milk microbiota (Li et al., 2025). Intestinal dysbiosis — frequently driven by subacute ruminal acidosis in dairy cattle — compromises gut barriers, allowing gut-derived LPS and pathobionts such as Stenotrophomonas to enter the bloodstream, localize in the mammary gland, and trigger mastitis (Zhao et al., 2022a; Li et al., 2025). Neural-microbial interactions compound this further: vagotomy alters gut microbial structure, reduces anti-inflammatory tryptophan metabolites such as 5-hydroxyindole acetic acid, disrupts the blood-milk barrier, and worsens mammary inflammation (Zhao et al., 2022b; Zhao et al., 2023).

In the pathogenesis of Type 1 Diabetes Mellitus, gut dysbiosis and mucosal barrier failure appear to consistently precede clinical pancreatic autoimmunity (Tan et al., 2026; Rampanelli & Nieuwdorp, 2023). Depletion of butyrate-producing commensals impairs tight junctions and disrupts GPCR-mediated signaling in GALT, which in turn impairs regulatory T-cell differentiation — normally promoted by taxa like Prevotella histicola — while accelerating differentiation of pro-inflammatory Th1 and Th17 subsets, a shift associated with Akkermansia muciniphila overrepresentation in this particular context (Tan et al., 2026). The resulting translocation of trans-epithelial endotoxins activates toll-like receptor 4 pathways, escalating systemic inflammation and accelerating autoimmune destruction of insulin-producing pancreatic β-cells (Tan et al., 2026; Rampanelli & Nieuwdorp, 2023).

2.3 The Intestinal Resistome: Molecular Mechanisms of Horizontal Gene Transfer

The human gastrointestinal tract, then, is best understood not merely as a digestive organ but as an active ecological crucible for the selection and dissemination of antimicrobial resistance genes — a collective genetic repository often termed the gut resistome (Idakwoji et al., 2026; Michaelis & Grohmann, 2023). This resistome contains both intrinsic resistance factors, such as cell-wall impermeability or efflux pumps in dominant Gram-negative anaerobes like Bacteroides, and acquired resistance determinants sitting on mobilizable genetic elements (Michaelis & Grohmann, 2023). Under selective antibiotic pressure, resident microbes effectively behave as silent incubators, accumulating and mobilizing resistance genes well before transferring them to clinically significant pathobionts (Idakwoji et al., 2026).

Horizontal gene transfer remains the principal mechanism behind resistome expansion, moving resistance traits rapidly across phylogenetically distant taxa (Idakwoji et al., 2026; Niculescu et al., 2026). Of its three canonical routes — conjugation, transformation, and transduction — plasmid-mediated conjugation is consistently identified as the dominant pathway in vivo, largely a function of the sheer cellular density and physical contact within the intestinal lumen (Idakwoji et al., 2026; Neil et al., 2020). Genomic surveys point to specific conjugative plasmid families — IncX4, IncI2, and IncHI2 — as unusually efficient vectors for global ARG dissemination (Niculescu et al., 2026; Zeb et al., 2026) (Figure 1).

The physical architecture of biofilms only intensifies this process (Costea et al., 2026). Their extracellular polymeric substance (EPS) matrix acts as a diffusion barrier that limits antibiotic penetration, allowing persister cells to remain in close proximity and exchange conjugative plasmids — the highly transferrable IncI2 plasmid TP114 being a well-documented example — at rates substantially higher than those observed in free-living, planktonic populations (Neil et al., 2020; Costea et al., 2026). In agricultural settings, subtherapeutic antibiotic administration in poultry and livestock has, in effect, converted the avian and mammalian gut into an active evolutionary crucible for resistome expansion, with zoonotic transmission pathways subsequently carrying resistant pathobionts to humans via contaminated food chains (Mayyas et al., 2026; Chen et al., 2025).

Of particular clinical concern is the zoonotic transmission of extended-spectrum β-lactamase genes — bla_CTX-M, bla_TEM, bla_SHV — which compromise third-generation cephalosporins, and mobilized colistin resistance genes, mcr-1 through mcr-10, which compromise polymyxins, the last-resort antibiotic class for treating multidrug-resistant Gram-negative infections (Mayyas et al., 2026; Zeb et al., 2026).

Figure 1. Mechanistic pathway from antibiotic selective pressure to multidrug-resistant infection via horizontal gene transfer (HGT). Antibiotic exposure selects for probiotic and commensal strains harboring mobile antimicrobial resistance genes (ARGs); these genes are transferred to resident pathobionts through conjugation, transformation, or transduction, a process markedly accelerated within biofilm microenvironments, ultimately disseminating clinically critical resistance determinants such as ESBLs, mcr genes, vanA/vanB, and carbapenemases (Idakwoji et al., 2026; Niculescu et al., 2026).

Figure 2. Structural and functional transition from eubiosis to dysbiosis. Under stable conditions (top), high microbial diversity, an intact epithelial barrier, and balanced short-chain fatty acid and bile-acid metabolism maintain host-microbiome homeostasis; antibiotic or environmental stress collapses this balance (bottom), depleting keystone taxa, compromising tight junctions, and permitting lipopolysaccharide translocation, which expands the gut resistome and disrupts downstream inter-organ signaling axes (Salem et al., 2018; Tan et al., 2026).

2.4 Therapeutic Revolutions: Next-Generation Probiotics, CRISPR Engineering, and Tri-Modal Integration

Faced with these risks, microbial therapeutics research has been shifting — not without some growing pains — from empirical, broad-spectrum pathogen eradication toward target-specific, mechanism-driven precision medicine (Jadhav et al., 2026; Hussain et al., 2026b).

Rather than relying on empirical donor fecal microbiota transplantation (FMT), which carries its own risks of pathogen transmission and considerable batch-to-batch variability, research has been moving toward standardized, multi-strain bacterial consortia manufactured from clonal cell banks (Suresh Kumar et al., 2026). Formulations such as SER-109 (Vowst) and VE303, developed under Good Manufacturing Practice conditions, contain purified Bacillota (Firmicutes) spores designed to restore specific metabolic fluxes (Suresh Kumar et al., 2026). These defined consortia re-establish primary-to-secondary bile acid conversion via the bai operon and stimulate SCFA production, which appears sufficient to suppress germination and colonization of Clostridioides difficile in several reported settings (Nogueira et al., 2026; Suresh Kumar et al., 2026).

Bacteriocins offer a conceptually different strategy: sequence-specific, ribosome-synthesized peptides with a narrow spectrum of activity, in contrast to the indiscriminate commensal die-off caused by conventional antibiotics (Tyagi et al., 2026). They recognize target receptors on specific pathogens and execute rapid bactericidal activity through membrane depolarization and pore formation, largely sparing bystander commensals (Tyagi et al., 2026). Synthetic biology is now leveraging these traits directly — a TAD1-deficient knockout mutant of Saccharomyces cerevisiae, for instance, has been shown to secrete cell-free supernatants capable of disrupting pathogenic biofilms and eradicating multidrug-resistant E. coli, S. aureus, and K. pneumoniae in vivo by triggering intracellular reactive oxygen species accumulation and compromising envelope integrity (Tyagi et al., 2026).

CRISPR-Cas genome editing and CRISPR interference have, meanwhile, enabled site-specific modification of probiotic chassis organisms such as Lactobacillus, Bifidobacterium, and Enterococcus (Hussain et al., 2026a; Meng et al., 2025). This programmable technology works through two broadly complementary routes. Subtractive editing, or pathogenicity curing, programs CRISPR systems to selectively target and cleave plasmids or chromosomal regions harboring specific ARGs — bla_NDM-1, bla_KPC, mcr-1 — within pathobionts, clearing resistance traits and resensitizing bacteria to conventional antibiotics without necessarily lysing the cell (Kuo et al., 2026; Allemailem, 2024). Additive engineering, by contrast, equips probiotics with defined expression cassettes that respond to local biochemical cues, allowing them to overexpress tight-junction proteins, synthesize immunomodulatory cytokines, or secrete quorum-quenching enzymes — lactonases and acylases — that degrade interspecies signaling autoinducers such as AI-2 and AHL, silencing pathobiont virulence networks without applying direct selective killing pressure (Hussain et al., 2026a; Gholizadeh et al., 2020). To keep these engineered strains from persisting or spreading unintentionally in the environment, robust biocontainment safeguards — synthetic auxotrophy, context-dependent genetic kill switches — are generally built in alongside the therapeutic payload (Hussain et al., 2026a; Wan et al., 2021).

To address the persistent challenge of probiotic gastric viability and delivery precision, a tripartite therapeutic framework has emerged, weaving together three previously separate disciplines (Hussain et al., 2026b) (Figure 4). Artificial intelligence and machine learning platforms — iProbiotics and ProbML among them — use Support Vector Machines, Random Forest classifiers, and deep learning to mine clinical, genomic, and metagenomic datasets, predicting probiotic-pathogen interactions and optimizing multi-strain consortium design (Jeyavelkumaran et al., 2026). Systems-biology approaches, including joint flux balance analysis and generalized Lotka-Volterra models, simulate metabolic cross-feeding and competition to forecast probiotic engraftment (Jeyavelkumaran et al., 2026). In parallel, nanotechnology-based delivery addresses the very real problem of probiotic viability loss under gastric acidity and bile-salt exposure; encapsulating cells or their postbiotics within pH-responsive nanocarriers — alginate-chitosan nanoparticles, liposomes, hydrogels — protects them during gastric transit and enables controlled, targeted release at intestinal, urogenital, or wound-associated sites (Hussain et al., 2026b; Gholamian et al., 2025). Once delivered, the selected or bioengineered probiotics restore the mucosal barrier, downregulate inflammatory markers, and deploy localized metabolites and bacteriocins, establishing conditions that

Figure 3. Inter-organ communication axes originating from the gut microbiome. Translocated microbial metabolites and immune mediators connect gut dysbiosis to cutaneous inflammation (gut-skin axis), neuroinflammatory changes (gut-brain axis), mastitis risk (gut-mammary axis), and pancreatic β-cell autoimmunity (gut-islet axis), illustrating how a single ecological disturbance can propagate into multiple, clinically distinct disease phenotypes (Munteanu et al., 2025; Socałą et al., 2021; Li et al., 2025; Tan et al., 2026).

Figure 4. Tri-modal convergence framework for next-generation probiotic therapeutics. Computational modeling (AI/ML strain selection and metabolic simulation), nanoencapsulation-based delivery (pH-responsive gastric protection), and CRISPR-engineered biological chassis (next-generation probiotics with biocontainment safeguards) act in concert to restore mucosal homeostasis while constraining the horizontal-gene-transfer risk associated with conventional probiotic strains (Hussain et al., 2026b; Jeyavelkumaran et al., 2026).

are, at least in principle, resistant to reinfection (Hussain et al., 2026b; Jeyavelkumaran et al., 2026).

3. Methodology

3.1 Review Design and Reporting Standard

This review was conducted as a structured narrative synthesis, organized in a manner broadly consistent with the reporting logic of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, adapted here for a narrative rather than a quantitative meta-analytic synthesis (Idakwoji et al., 2026; Hussain et al., 2026a). We did not attempt a formal meta-analysis — the underlying literature is too heterogeneous in design, organism, and outcome measure for that to be meaningful — but we did apply an explicit, documented, and in principle reproducible search-and-screening protocol, in keeping with the transparency expectations increasingly applied to biomedical narrative reviews indexed in PubMed.

3.2 Information Sources and Search Strategy

We searched PubMed/MEDLINE, Scopus, Web of Science, and ScienceDirect for peer-reviewed articles published between January 2019 and 2026, this window chosen to capture both the foundational mechanistic literature on horizontal gene transfer and the more recent (2025-2026) surge of publications on next-generation probiotics, CRISPR-based antimicrobial engineering, and AI-guided strain design. Search terms were combined using Boolean operators in the general form: (“probiotic*” OR “next-generation probiotic*” OR “live biotherapeutic product*”) AND (“horizontal gene transfer” OR “conjugation” OR “transduction” OR “transformation” OR “mobile genetic element*” OR “plasmid”) AND (“antimicrobial resistance” OR “antibiotic resistance” OR “resistome”). Supplementary searches added terms specific to each thematic subsection — “CRISPR-Cas”, “whole-genome sequencing”, “Multiple Antibiotic Resistance index”, “gut-brain axis”, “gut-skin axis”, “mcr-1”, “ESBL”, and “biocontainment” — to ensure adequate coverage of each mechanistic and translational domain addressed in this review. Reference lists of retrieved articles were hand-searched for additional relevant sources, a step that, admittedly, introduces some snowball-sampling bias but was judged necessary given how fragmented this literature still is across microbiology, pharmacology, veterinary science, and bioengineering journals.

3.3 Eligibility Criteria

Articles were included if they (a) were published in peer-reviewed journals in English; (b) addressed at least one of the four core review objectives — HGT mechanisms in the gastrointestinal microbiome, mobile genetic elements as resistance vectors, genomic/phenotypic safety profiling of probiotic strains, or genomic screening and biocontainment strategies; and (c) reported original data, a systematic or narrative synthesis, or a mechanistic model with clear methodological description. We excluded conference abstracts without full-text availability, non-peer-reviewed preprints (unless subsequently published and cross-checked against the published version), and articles focused exclusively on plant or environmental microbiomes with no connection to human or animal gastrointestinal health.

3.4 Study Selection and Data Extraction

Titles and abstracts identified through the search strategy were screened independently against the eligibility criteria above, with full-text review conducted for any record where relevance could not be confidently determined from the abstract alone. For each included article, we extracted, where reported: study or review type; organism(s) and mobile genetic element(s) studied; the HGT mechanism(s) addressed; resistance gene(s) or antibiotic class(es) discussed; any quantitative safety metric reported, such as MAR index values or transfer-frequency estimates; and the genomic, phenotypic, or in silico methodology underpinning the reported findings. This extraction schema was designed so that, in principle, another reviewer applying the same search strategy and eligibility criteria to the same databases and date range should retrieve a substantially overlapping evidence base — the reproducibility standard we understand PubMed-indexed reviews to be increasingly held to.

3.5 Synthesis Approach

Findings were synthesized thematically rather than study-by-study, organized around the four review objectives stated in the Introduction. Where multiple sources reported convergent findings — for instance, the identification of IncX4, IncI2, and IncHI2 plasmids as dominant ARG vectors, corroborated across Niculescu et al. (2026) and Zeb et al. (2026) — we treated this convergence as strengthening confidence in the underlying claim. Where sources offered complementary rather than overlapping evidence, such as the mechanistic CRISPR-Cas effector data in Khosrojerdi et al. (2026) alongside the applied probiotic-engineering evidence in Hussain et al. (2026a, 2026b), we integrated these into a single narrative arc rather than treating them as independent silos. This synthesis strategy is, admittedly, more interpretive than a formal quantitative pooling would be; we consider that an acceptable, even necessary, trade-off given the mechanistic and cross-disciplinary nature of the underlying evidence base.

4. Gut Resistome Dynamics and CRISPR-Based Strategies for Combating Antimicrobial Resistance

4.1 Resistome Expansion and the Dynamics of Horizontal Gene Transfer

Taken together, the reviewed literature makes a fairly compelling case that the human and animal gastrointestinal tracts function not merely as digestive organs but as highly active ecological crucibles for the selection and dissemination of antimicrobial resistance genes (Idakwoji et al., 2026; Mayyas et al., 2026). This collective genetic repository, the gut resistome, remains dynamically responsive to pharmacological and environmental selective pressures (Idakwoji et al., 2026; Niculescu et al., 2026). Longitudinal metagenomic analyses indicate that broad-spectrum antibiotic therapies exert a largely non-selective, decimating pressure on commensal obligate anaerobes — Bacteroides and Faecalibacterium among them — collapsing the ecological barrier of colonization resistance and opening space for opportunistic pathobionts to expand (Niculescu et al., 2026; Idakwoji et al., 2026) (Figure 1).

The dominant driver of resistome expansion, consistent across the reviewed sources, is horizontal gene transfer, which moves resistance traits rapidly across phylogenetically distant taxa (Idakwoji et al., 2026; Niculescu et al., 2026). Among the three canonical HGT routes, plasmid-mediated conjugation is repeatedly identified as the most dominant pathway in vivo, a consequence of the high cellular density and physical proximity characteristic of the intestinal lumen (Idakwoji et al., 2026; Niculescu et al., 2026). Synthesized genomic data point specifically to the IncX4, IncI2, and IncHI2 replicon families as unusually efficient vectors facilitating global ARG spread (Niculescu et al., 2026; Zeb et al., 2026).

Of particular clinical concern is the rapid mobilization of extended-spectrum β-lactamase genes — bla_CTX-M, bla_TEM, bla_SHV — and mobilized colistin resistance genes, mcr-1 through mcr-10 (Mayyas et al., 2026; Zeb et al., 2026). Commensal Escherichia coli and Enterococcus species act as silent, persistent incubators for these genes within the gut (Idakwoji et al., 2026; Mayyas et al., 2026), and under concurrent antibiotic therapy, these reservoirs horizontally transfer the relevant mobile genetic elements to highly virulent pathogens, rendering last-resort antibiotics — third-generation cephalosporins, polymyxins — clinically ineffective (Idakwoji et al., 2026; Zeb et al., 2026; Mayyas et al., 2026). Biofilm microenvironments compound this risk further: the extracellular polymeric substance matrix limits antibiotic penetration and keeps bacterial cells in close spatial proximity, allowing exchange of conjugative plasmids such as TP114 at transfer rates markedly higher than those observed in planktonic states (Idakwoji et al., 2026; Niculescu et al., 2026).

4.2 Phenotypic versus Genotypic AMR Profiles in Probiotic Candidates

To keep probiotic biotherapeutics from serving, unintentionally, as vectors for resistance-gene dissemination, stringent safety screening is required at the strain level (Saleh et al., 2025; Lertcanawanichakul et al., 2026). Systematic evaluations of commercial and farmhouse probiotic isolates reveal a genuinely concerning mismatch between phenotypic antibiotic-susceptibility profiles and the underlying genotype — a discrepancy that puts real strain on the assumption behind “Generally Recognized As Safe” classifications, particularly within Enterococcus and lactic acid bacteria genera (Gardoul et al., 2025) (Table 4).

The Multiple Antibiotic Resistance (MAR) index functions as a useful, if imperfect, first-line phenotypic screening tool, indicating prior antibiotic exposure and environmental selective pressure (Gardoul et al., 2025). A MAR value above the established 0.2 threshold suggests an isolate likely originated from an environment carrying heavy antibiotic contamination, such as intensive livestock farming or a clinical setting (Gardoul et al., 2025). Reported phenotypic screening data show elevated, high-risk MAR index values in farmhouse strains of Enterococcus durans (MAR = 0.41) and Lactococcus lactis (MAR = 0.35), both displaying multidrug-resistant phenotypes spanning tetracycline, gentamicin, kanamycin, and streptomycin (Gardoul et al., 2025). By contrast, Lactiplantibacillus plantarum strains show favorably low MAR indices (0.11), consistent with minimal prior selective exposure (Gardoul et al., 2025) (Table 4).

Phenotypic assays alone, however, cannot confirm safety — transmissible resistance determinants can remain transcriptionally silent under standard laboratory testing conditions (Gardoul et al., 2025). Whole-genome sequencing has, accordingly, become close to a non-negotiable regulatory standard for distinguishing intrinsic from acquired resistance mechanisms (Gardoul et al., 2025; Saleh et al., 2025). Intrinsic resistance — chromosomal mutations, cell-wall-mediated drug impermeability — is stable, non-transmissible, and generally considered clinically acceptable; it can even provide added therapeutic value by letting the probiotic survive and support the gut barrier during concurrent antibiotic treatment (Idakwoji et al., 2026; Gardoul et al., 2025). Commercial Bacillus clausii strains illustrate this well, harboring stable, chromosomally integrated resistance determinants — aadD2, cat(Bcl), blaBCL-1 — that do not transfer horizontally (Niculescu et al., 2026). By contrast, whole-genome sequencing disqualifies candidates carrying acquired resistance genes such as tet(M) or erm(B) when these are flanked by transposable insertion sequences or located on mobile plasmids, given the high risk of horizontal transmission to gut-resident pathobionts that this genomic architecture implies (Gardoul et al., 2025; Saleh et al., 2025) (Table 4). While Table 3 presents the Inter-organ communication axes linking gut dysbiosis to microbiota-driven disease pathogenesis.

4.3 Comparative Effector and Delivery Performance of CRISPR-Cas Systems

Repurposing prokaryotic CRISPR-Cas adaptive immune systems into programmable, sequence-specific antimicrobials represents one of the more significant technological developments now bearing on the AMR problem (Khosrojerdi et al., 2026). Synthesized mechanistic data point to a fairly clear division of labor among the major Cas effectors (Table 1). Cas9 (Type II) and Cas12 (Type V) are robust double-stranded DNA endonucleases that generate double-strand breaks within target plasmid-borne or chromosomal resistance genes, such as bla_NDM-1 or mecA (Khosrojerdi et al., 2026). Because most bacteria lack efficient non-homologous end-joining repair pathways, these Cas9-induced breaks tend to result in cell death or permanent plasmid curing, effectively eliminating the resistant population (Khosrojerdi et al., 2026; Agha et al., 2025). Cas12 additionally allows multiplexed guide processing, enabling simultaneous silencing of up to six distinct resistance loci, while Cas13 (Type VI) targets single-stranded RNA rather than DNA, allowing tunable, reversible transcript knockdown without permanent genomic damage or the selective pressure that tends to favor escape mutants (Khosrojerdi et al., 2026; Kiga et al., 2020).

Clinical translation of these tools depends heavily on delivery-vehicle efficiency and safety, and here the reviewed literature reveals meaningfully different performance profiles across platforms (Table 2). Engineered phagemids represent the most potent biological vectors reported, demonstrating up to a 4-log reduction of MRSA in vivo and highly target-specific delivery, although their host range remains constrained by phage receptor specificity (Khosrojerdi et al., 2026; Selle et al., 2020). Conjugative plasmids offer a broader target range by exploiting natural bacterial conjugation pathways to spread the CRISPR cassette through dense bacterial populations, achieving up to 99.99% plasmid clearance in mixed biofilm communities in some reported settings (Khosrojerdi et al., 2026; Sheng et al., 2023). Non-viral alternatives — lipid nanoparticles, outer membrane vesicles — offer superior manufacturing scalability and lower host immunogenicity but are constrained by lower loading capacities and variable transfection efficiency in Gram-positive species (Khosrojerdi et al., 2026; Gholamian et al., 2025). In mature biofilm environments specifically, outer membrane vesicles and engineered phages expressing matrix-degrading enzymes — depolymerases, endolysins — show superior therapeutic performance, penetrating dense EPS matrices and clearing embedded resistant persister cells (Khosrojerdi et al., 2026; Ataei-Alamdari et al., 2026).

4.4 Tri-Modal Integration and Next-Generation Living Therapeutics

The evident limitations of traditional, empirical single-strain probiotics have catalyzed a transition toward rationally designed next-generation probiotics and Live Biotherapeutic Products (Abdul Manan, 2025; Hussain et al., 2026b). Rather than relying on non-specific gut colonization, contemporary therapeutic strategies increasingly integrate artificial intelligence, materials science, and biological engineering into a coordinated tri-modal framework (Hussain et al., 2026b; Jeyavelkumaran et al., 2026). Specialized computational pipelines, such as iProbiotics and ProbML, apply Support Vector Machines

Table 1. Comparison of core CRISPR-Cas effectors used in antimicrobial resistance (AMR) applications. The table summarizes the molecular target, mechanism of action, and reported therapeutic efficacy of the three principal Cas effector classes discussed in this review, illustrating why Cas9/Cas12 are favored for permanent resistance-gene clearance while Cas13 supports tunable, reversible transcript silencing (Khosrojerdi et al., 2026).

Table 2. Quantitative and qualitative comparison of CRISPR-Cas delivery platforms for in vivo antimicrobial applications. The table contrasts host-range, manufacturing scalability, and reported clearance efficiency across biological (phagemid, conjugative plasmid) and non-viral (lipid nanoparticle, outer membrane vesicle) delivery vehicles, highlighting the trade-off between delivery potency and host-range breadth (Khosrojerdi et al., 2026; Selle et al., 2020; Sheng et al., 2023).

Table 3. Inter-organ communication axes linking gut dysbiosis to microbiota-driven disease pathogenesis. Each axis is summarized by its principal signaling route, the systemic mediator involved, and its associated clinical or subclinical outcome, synthesizing evidence from human and veterinary sources discussed in Section 2.2 of this review (Salem et al., 2018; Socałą et al., 2021; Li et al., 2025; Tan et al., 2026).

Table 4. Genomic and phenotypic characterization of antimicrobial resistance risk in representative probiotic strains. The table contrasts Multiple Antibiotic Resistance (MAR) index values with the underlying genomic basis of resistance (intrinsic/chromosomal versus acquired/mobilizable), showing why phenotype alone is an unreliable proxy for transmissibility risk and why whole-genome sequencing is required for definitive strain classification (Gardoul et al., 2025; Niculescu et al., 2026).

and Random Forest classifiers to mine global gut metagenomic datasets, predicting optimal probiotic strains and modeling host-probiotic-pathogen metabolic networks (Jeyavelkumaran et al., 2026; Hussain et al., 2026b). Advanced systems-biology modeling — joint flux balance analysis, generalized Lotka-Volterra models — simulates interspecies cross-feeding and metabolic competition, allowing researchers to predict probiotic engraftment and design multi-strain consortia with synergistic anti-pathogen activity (Jeyavelkumaran et al., 2026).

On the delivery side, sensitive therapeutic strains are increasingly encapsulated within stimuli-responsive, biodegradable nanocarriers to shield them from gastric acidity and bile salts (Hussain et al., 2026b). pH-responsive biopolymer matrices — alginate-chitosan nanoparticles, nanostructured cellulose-starch coatings — protect viable cells during gastric transit at pH below 3.0 and enable targeted, controlled release directly at intestinal or wound-associated disease sites (Hussain et al., 2026b; Ataei-Alamdari et al., 2026). Once delivered to the targeted mucosal niche, next-generation probiotics such as Akkermansia muciniphila or Faecalibacterium prausnitzii, and CRISPR-engineered probiotic chassis more broadly, actively restore the mucosal barrier and outcompete pathogens (Hussain et al., 2026b; Jeyavelkumaran et al., 2026). These engineered strains are programmed to secrete sequence-specific bacteriocins or quorum-quenching enzymes, such as lactonases, that degrade bacterial communication signals — silencing pathogen virulence and disrupting biofilms without generating the strong evolutionary selective pressure that tends to drive antimicrobial resistance in the first place (Tyagi et al., 2026; Hussain et al., 2026a).

5. Discussion: Reconciling Microbiome Restoration with Resistome Containment

5.1 The Central Tension: Restorative Intent versus Resistance Risk

Pulling these threads together, the picture that emerges is not one of probiotics being inherently dangerous — that would be an overstatement, and not one this literature actually supports — but of a therapeutic category whose safety cannot be assumed by category alone. The same organisms prized for restoring colonization resistance and metabolic function after antibiotic disruption are, by virtue of being administered into precisely that disrupted, antibiotic-pressured environment, positioned as ideal participants in horizontal gene transfer (Saleh et al., 2025; Lertcanawanichakul et al., 2026). It is worth sitting with that irony for a moment: the clinical logic for giving a probiotic (recent or concurrent antibiotic exposure) is the same condition that maximizes the selective pressure favoring HGT (Idakwoji et al., 2026). This is not a reason to abandon probiotic therapeutics, but it is a reason to stop treating strain safety as something settled once and for all at the genus level.

The mismatch between phenotypic MAR-index screening and whole-genome sequencing results, reported here for Enterococcus durans and Lactococcus lactis farmhouse isolates (MAR = 0.41 and 0.35, respectively) against the comparatively reassuring Lactiplantibacillus plantarum profile (MAR = 0.11), makes this concretely visible (Gardoul et al., 2025) (Table 4). A regulatory framework that stopped at phenotype would, in effect, be blind to exactly the genomic architecture — acquired resistance genes flanked by mobile insertion sequences — that matters most clinically. We think this is the single most actionable finding to emerge from the reviewed literature: genomic screening is not an optional add-on to phenotypic testing, it is the test that actually answers the safety question regulators are asking.

5.2 Mobile Genetic Elements and Biofilms as Amplifiers of Risk

A second theme worth dwelling on is how much the physical microenvironment shapes transfer risk, independent of which organism is involved. The recurring identification of IncX4, IncI2, and IncHI2 plasmid families across multiple independent sources (Niculescu et al., 2026; Zeb et al., 2026) suggests these are not incidental findings but genuinely privileged vehicles for ARG dissemination — plausibly because their conjugative machinery is unusually well adapted to gut conditions. Layered onto this, biofilm architecture appears to function almost as a force multiplier: by limiting antibiotic penetration and keeping cells packed closely together, biofilms create exactly the physical conditions conjugation needs (Idakwoji et al., 2026; Niculescu et al., 2026; Costea et al., 2026). One practical implication, not always made explicit in the source literature but reasonably inferred from it, is that probiotic safety assessment probably should not stop at planktonic-culture testing; transfer rates measured in dispersed culture may meaningfully understate what happens once a strain colonizes a biofilm niche in vivo.

5.3 CRISPR-Cas Engineering: Promise, and Where It Still Falls Short

The CRISPR-Cas literature synthesized here (Table 1, Table 2) is genuinely encouraging, and we do not want to undersell it — subtractive editing that cures resistance plasmids without lysing the cell, and additive engineering that adds therapeutic payloads under tight biocontainment, together represent a real technical advance over blunt antibiotic-based approaches (Khosrojerdi et al., 2026; Hussain et al., 2026a). That said, delivery remains the practical bottleneck, and the reviewed evidence is fairly explicit about the trade-offs involved: phagemids are potent but host-range-limited (Selle et al., 2020); conjugative plasmid delivery spreads broadly but relies on the same conjugative machinery this review flags as a resistance-dissemination risk in the first place, which is a slightly uncomfortable dependency (Sheng et al., 2023); and non-viral carriers are safer to manufacture but underperform in Gram-positive species specifically (Khosrojerdi et al., 2026). None of this is disqualifying, but it does suggest that CRISPR-based antimicrobials are, at present, better understood as a complement to genomic screening than as a wholesale replacement for it.

5.4 The Tri-Modal Framework: A Plausible but Still-Maturing Path Forward

The convergence of AI-guided strain selection, nanoencapsulated delivery, and engineered biological antagonism (Figure 4) represents, in our reading, the most coherent proposed solution to the tension outlined above — not because any single component is decisive, but because the framework as a whole addresses viability, precision, and safety simultaneously rather than sequentially (Hussain et al., 2026b; Jeyavelkumaran et al., 2026). We would nonetheless flag that most of the supporting evidence remains preclinical or early translational; validated head-to-head clinical comparisons against conventional probiotic formulations are, as far as this review's search could determine, still largely absent from the literature. This is less a criticism of the framework than an honest acknowledgment of where the field currently stands.

5.5 Regulatory and Practical Implications

Taken as a whole, this synthesis supports a fairly direct policy recommendation: regulatory frameworks from EFSA, the FDA, and FAO/WHO should formally require whole-genome sequencing — ideally cross-referenced against CARD and VFDB — as a baseline biosafety standard for any probiotic strain intended for clinical or agricultural deployment, with MAR-index phenotyping retained as a useful, low-cost preliminary flag rather than a standalone safety determination (Hussain et al., 2026a; Saleh et al., 2025; Gardoul et al., 2025). Given the agricultural contribution to resistome expansion documented here (Mayyas et al., 2026), we would also argue that One Health surveillance — tracking ARG-carrying mobile genetic elements across human, animal, and environmental reservoirs jointly — deserves more prominence in probiotic biosafety policy than it currently receives.

5.6 Limitations

This review has the limitations inherent to any narrative synthesis: it is not a formal meta-analysis, quantitative pooling of transfer-frequency or MAR-index data across studies was not attempted, and the underlying primary literature spans considerable heterogeneity in organism, methodology, and reporting standard. Much of the evidence base also draws on a relatively recent (2025-2026) publication window, meaning long-term clinical outcome data for several of the discussed interventions — CRISPR-engineered probiotics, tri-modal nanotherapeutics — are not yet available. We have tried to flag these gaps honestly throughout rather than paper over them.

6. Conclusion

The evidence reviewed here converges on a fairly clear, if sobering, conclusion: probiotics are not a neutral intervention with respect to antimicrobial resistance, and treating them as one carries real clinical risk. The human gut functions as an active resistome in which conjugative plasmids — particularly the IncX4, IncI2, and IncHI2 families — move clinically critical resistance genes, including ESBLs, mcr-1 through mcr-10, and carbapenemases, between commensals, probiotic strains, and opportunistic pathogens, a process substantially accelerated within gut biofilms. Phenotypic screening tools such as the Multiple Antibiotic Resistance index remain useful as a first-pass flag, but the demonstrated mismatch between phenotype and genotype means they cannot, on their own, certify a strain as safe; whole-genome sequencing against curated resistance and virulence databases should be considered the non-negotiable standard going forward. At the same time, the emerging toolkit — CRISPR-Cas subtractive and additive engineering, synthetic biocontainment, and a tri-modal integration of artificial intelligence, nanoencapsulated delivery, and precision biological antagonism — offers a genuinely plausible route toward probiotics that restore the microbiome without expanding its resistome. Realizing that potential will require regulatory frameworks that formally mandate genomic screening, sustained One Health surveillance linking human, animal, and environmental resistance reservoirs, and continued translational research to move CRISPR-engineered and nanoencapsulated probiotics from preclinical promise toward validated clinical use. In short, the future of probiotic therapeutics looks less like uncritical enthusiasm and more like careful, genomically informed stewardship — which is, on balance, exactly what a therapy this widely used should have had from the start.

References