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Current IssueSpecial IssueEditorial BoardOnline First ArticlesArchive

Review Article

Dietary Modulation of the Gut Mycobiome in Poultry and Monogastric Animals: A Systematic Review of Composition, Measurement, Trans-kingdom Interactions and the Absence of Fungal-targeted Nutrition Trials

K
Karl Louisse D. Obispo1,*
1Department of Animal Science, College of Agriculture, Food, Environment and Natural Resources, Cavite State University, Indang, Cavite, 4122 Philippines.

ABSTRACT

Fungi form a minor but functionally disproportionate fraction of the monogastric gut microbiota. Bacterial communities in poultry and pigs are well characterized, but the mycobiome remains poorly defined and its dietary responsiveness is largely assumed. This review establishes mycobiome composition and measurement in healthy poultry and pigs, synthesizes dietary and feed-processing drivers of fungal load and diversity, evaluates trans-kingdom interactions linked to performance, Candida overgrowth and mycotoxin dynamics and quantifies the gap in fungal-targeted dietary-intervention trials. A systematic search of Semantic Scholar, PubMed and Scopus used twenty structured queries across five sub-areas derived from a hybrid PICO-decomposition framework. Records were screened against a priori eligibility criteria centered on poultry and porcine hosts; methodological literature from other hosts was retained where it informed measurement validity. Of 387 records retrieved, 231 were unique and 80 met eligibility. The porcine mycobiome converges on Kazachstania slooffiae as a dominant post-weaning resident, whereas the chicken mycobiome is transient, diet-derived and lacks succession, an asymmetry with direct implications for intervention design. No marker-database combination performed universally and common ITS primers failed to amplify piglet-native fungi. Feed processing reduced viable mold counts by 27-65%, yet aflatoxin was higher in pelleted than mash feed. Critically, live-yeast and mycotoxin-mitigation trials, where the agent or hazard is itself fungal, almost universally reported bacterial endpoints alone; fewer than five controlled dietary trials in either species reported fungal community outcomes.

INTRODUCTION

The gastrointestinal microbiota of poultry and pigs has been intensively studied for two decades, reshaping applied monogastric nutrition, yet that literature is overwhelmingly bacterial. Fungi, collectively the mycobiome, represent only 0.01-2% of intestinal microbial cells, though an average fungal cell occupies roughly one hundred times the volume of a bacterial cell, so read-proportion abundance understates fungal biomass (Deng et al., 2025). Fungal cell-wall polysaccharides, β-glucans and mannans, are potent pattern-recognition ligands for the vertebrate innate immune system (Saijo and Iwakura, 2011) and fungi secrete hydrolytic enzymes and metabolites acting on bacterial neighbors and host epithelium alike (Hu et al., 2023; McCrory et al., 2024).
       
For the animal nutritionist, three developments make this omission increasingly untenable. First, withdrawal of antibiotic growth promoters has driven commercial-scale adoption of yeast-based feed additives, live Saccharomyces cerevisiae, yeast cell wall preparations, yeast culture and postbiotics (Kim et al., 2022; Saleem et al., 2018): fungi administered to modulate a gut ecosystem whose fungal component goes unmeasured. Second, mycotoxin contamination of cereal-based diets is a persistent, climate-sensitive hazard (Guerre, 2016; Jubair et al., 2026); mycotoxins are fungal secondary metabolites, yet the producing fungi and their fate in the gut are rarely quantified alongside toxin concentrations. Third, routine feed-processing operations measurably affect the viable fungal load entering the animal and diet is the principal source of the chicken intestinal mycobiome (Robinson et al., 2022). Each is a fungal intervention already embedded in commercial practice and evaluated almost exclusively through bacterial endpoints.
       
Poultry and pigs also should not be treated as a single case biologically. The porcine gut supports a genuine fungal resident, K. slooffiae, which colonizes after weaning and persists into adulthood (Summers et al., 2019; Urubschurov et al., 2011), whereas the chicken mycobiome appears largely transient, replenished continuously from feed and environment without stable succession (Robinson et al., 2022). This distinction determines whether dietary modulation means shaping a resident community or controlling a continuous environmental influx, objectives requiring different interventions and measurements.
       
Several recent narrative reviews have surveyed intestinal fungi in monogastric animals (Deng et al., 2025; Liu et al., 2025), but none has applied systematic search and reporting methodology to dietary modulation specifically, or quantified rather than merely asserted the intervention-trial gap. Given documented reporting deficiencies in the animal health and veterinary systematic review literature (Sargeant et al., 2021; Toews, 2017), a transparent, reproducible approach is warranted.
       
This review therefore addresses four objectives: characterize the composition of the healthy poultry and porcine gut mycobiome and how it is measured, including ITS amplicon versus shotgun metagenomic approaches and reference-database limitations; synthesize dietary and feed-processing determinants of fungal load and diversity; examine trans-kingdom fungal-bacterial interactions linked to performance, Candida overgrowth and mycotoxin dynamics; and quantify the absence of controlled dietary-intervention trials with fungal endpoints and derive a prioritized research agenda.
 
Protocol and reporting
 
This review was conducted at the Department of Animal Science, Cavite State University, Indang, Cavite, Philippines and is reported per the PRISMA 2020 statement and its explanation and elaboration document (Page et al., 2021a; Page et al., 2021b). Because the evidence base was anticipated to be heterogeneous in design, host species, sampling site and analytical platform, narrative synthesis with structured tabulation was specified a priori rather than quantitative meta-analysis.
 
Search framework and question formulation
 
The review question combined PICO with topic decomposition, since the scope spans both a population-intervention question (dietary modulation) and a methodological question (measurement validity). Population: broilers, laying hens and pigs, emphasizing peri-weaning and early post-hatch periods. Intervention: diet composition, feed additives, processing method and mycotoxin exposure. Outcomes: fungal community composition, diversity and load, performance, gut health and mycotoxin dynamics. This mapped to five search sub-areas: mycobiome composition; methodological comparison and database limitations; dietary and feed-processing drivers; trans-kingdom interactions; and intervention trials and the endpoint gap.
 
Information sources and search strategy
 
Searches were executed in Semantic Scholar, PubMed and Scopus. Twenty structured queries, each combining a biological target, host species, methodological term and outcome term as natural-language strings (semantic rather than Boolean retrieval), were run between May and July 2026. Grey literature and non-English sources were not systematically sought, so coverage of the applied feed-technology literature is likely incomplete.
 
Eligibility criteria
 
Records were eligible if they reported original data or synthesis on intestinal, fecal or excreta fungal communities in poultry or pigs; on dietary, additive or feed-processing effects on fungal load or diversity; or on fungal-bacterial interactions with host outcomes. Methodological studies on fungal marker genes, primers, reference databases or quantification approaches were eligible regardless of host or matrix. Mechanistic studies in humans, mice or in vitro systems were eligible only where they addressed a mechanism directly invoked in interpreting livestock data and are identified as such throughout. Records addressing ruminant hosts exclusively, feed contamination without a gut- or animal-related outcome, or fungal disease pathology unrelated to the commensal community were excluded.
       
A record was classified as a fungal-endpoint dietary trial only if it met all four criteria: A controlled dietary or feed-processing intervention with a concurrent comparison group; live target-species animals; A fungal community or load measurement as an outcome and that measurement made in GI, fecal or excreta material rather than feed alone. This definition underlies the gap quantification reported in Results.
 
Selection process, data extraction and synthesis
 
Records returned by each query were screened at title and abstract level against the eligibility criteria, with full text examined where necessary; duplicates were identified by title matching and removed. Extracted variables comprised host species and production stage, sample matrix and GI site, fungal marker gene and reference database, endpoint type, intervention type and principal findings. Findings were synthesized narratively within the five sub-areas, with discordant results tabulated explicitly and adjudicated on methodological grounds rather than reconciled by omission. Formal risk-of-bias assessment was not applied, given the predominant designs (see Limitations).
 
Search yield and characteristics of the evidence base
 
The twenty queries returned 387 records, of which 231 were unique and 80 met the eligibility criteria; the most relevant are cited herein. Every query returned results, so yield was constrained by relevance, not retrieval; several returned predominantly bacterial-endpoint literature despite fungal search terms.
       
That pattern is a principal finding: the query on dietary fiber and prebiotic effects on the broiler gut returned twenty records, eighteen reporting 16S rRNA bacterial endpoints exclusively; the live-yeast-in-pigs query returned twenty records, none reporting gut fungal outcomes and only one enumerating yeast numbers at all (Li et al., 2006). This matches evidence that livestock microbiome research overwhelmingly targets bacteria, fungi being markedly under-studied (Forcina et al., 2022).
 
Composition of the healthy gut mycobiome: A fundamental species asymmetry
 
At phylum level the two species converge: Ascomycota and Basidiomycota dominate the intestinal mycobiome of both broilers and pigs, jointly accounting for 90-99% of fungal sequences regardless of gut segment, age or production system (Robinson et al., 2022; Arfken et al., 2020; Scott et al., 2025). Below phylum level the similarity ends and the divergence is ecological rather than merely taxonomic.
       
In pigs, the defining feature is the emergence of a genuine resident. K. slooffiae is essentially absent before weaning, rises sharply after the transition to solid feed and persists into adulthood, culture-based work confirming a post-weaning increase in fungal burden that does not differ from adult levels (Summers et al., 2019; Urubschurov et al., 2011). In a cohort of 514 Duroc pigs, the mycobiota was dominated by yeasts, with Kazachstania spp. abundance positively associated with piglet body weight, while low heritability of fungal α-diversity (0.15-0.28) indicated a community shaped predominantly by environment and diet rather than host genotype (Ramayo-Caldas et al., 2020) and therefore tractable by nutritional means.
       
In broilers, no equivalent resident has been identified. Comprehensive ITS2 characterization found significant spatial and temporal variation but no successional trend to 42 days of age, with the community more diverse in the upper than lower tract, the inverse of the bacterial pattern; total fungal populations ranged from 1.0 × 104 to 1.1 × 106 per gram of digesta, under 0.06% of bacterial counts by day 42 and hatchery-derived mycobiota in newly hatched chicks were replaced by diet-derived fungi within three days (Robinson et al., 2022). Earlier work found the day-28 mycobiome dominated by just three species, Scopulariopsis brevicaulis, Trichosporon asahii and Aspergillus spp., over 80% of fungal reads, against hundreds of bacterial taxa (Robinson et al., 2020). In pigs, dietary modulation thus means shaping a resident yeast population; in poultry, it means managing a continuous dietary influx in which feed fungal composition is the proximate determinant of gut fungal composition, different problems that have permitted unwarranted extrapolation between species.
       
Both communities are strongly structured by non-dietary factors that any trial must control for. Production system exerts a large effect, with pasture-raised pigs hosting significantly greater fungal richness than conventionally raised animals (Scott et al., 2025) and in eleven pigs of matched genetics, housing and diet sampled in two batches ten months apart, batch and sampling time influenced fungal composition more than GI location (Li et al., 2022): a trial that does not block on batch and season risks attributing to treatment what belongs to time.
 
Measurement: no marker-database combination performs universally
 
The methodological literature describes a measurement system whose principal failure modes remain unresolved, conditioning the interpretation of every compositional finding above.
       
The most direct evidence comes from mock-community analysis in pigs. Comparing 18S, ITS1 and ITS2 markers against UNITE and SILVA databases using defined communities from five fungal isolates recovered from weanling piglet feces, no marker–database combination consistently outperformed the others; ITS markers were marginally superior for species identification, but Lichtheimia corymbifera, a common piglet-gut community member, was not amplified by either ITS1 or ITS2 primer, skewing ITS-based estimates while 18S profiles remained accurate. Gene copy number also varied by taxon (83-85 for K. slooffiae, 90-144 for L. corymbifera), confounding conversion of read counts into abundance (Arfken et al., 2023).
       
These findings are corroborated across matrices: amplicon length heterogeneity in the ITS1-ITS2 region overestimates species with shorter amplicons, whereas 18S and 26S amplicons quantify more reliably (De Filippis et al., 2017) and across 37 mock communities, classification accuracy (56-100%) varied with marker, database, software, taxonomic level and extraction protocol alike, abundance estimation from read counts performing poorly regardless (Bakker, 2018).
       
Shotgun metagenomics is no straightforward remedy: in 1,772 participants with paired ITS1 and shotgun data, no meaningful agreement was observed between platforms for fungal taxa, unlike close agreement for bacteria, since fungi occur at low relative abundance against sparse reference genomes (Usyk et al., 2023). Enrichment with in-house fungal databases can render shotgun profiling viable, as now demonstrated across 750 pig gut metagenomes (Xie et al., 2023; Wei et al., 2026), but only with substantial bespoke effort. ITS remains the best general fungal barcode despite inherent limitations unresolvable by bioinformatics alone (Kauserud, 2023).
       
Two practical remedies remain under-used. First, relative abundance should be supplemented by absolute quantification: spike-in constructs and a validated qPCR assay for K. slooffiae and total yeasts have existed for a decade (Tkacz et al., 2018; Urubschurov et al., 2015), since relative abundance can fall while absolute abundance rises (Tkacz et al., 2018). Second, host-specific mock communities should be sequenced alongside experimental samples (Arfken et al., 2023). This review therefore reports findings with the marker used and examines discrepancies methodologically before biological interpretation; high inter-study variation in intestinal mycobiota (Robinson et al., 2022) is at least partly a measurement artefact.
 
Dietary and feed-processing drivers of fungal load and diversity
 
Diet is the primary source of the chicken intestinal mycobiome (Robinson et al., 2022) and dietary carbohydrate composition restructures the colonic fungal community in pigs (Luo et al., 2021). These findings should have generated a substantial applied literature; they have not.
       
The carbohydrate evidence in pigs is strongest. In an orthogonal design varying amylose:amylopectin ratio, non-starch polysaccharide level and mannan-oligosaccharide (MOS) inclusion, colonic fungal communities responded in the order MOS>amylose:amylopectin>non-starch polysaccharide, with genera including Saccharomycopsis and Wallemia correlating with colonic glucose, fructose and β-D-glucosidase activity (Luo et al., 2021). A controlled trial comparing inulin and cellulose (5%) in growing pigs restructured rectal fungal communities with distinct temporal dynamics correlated with SCFA profiles (Qin et al., 2026), one of the very few studies meeting this review’s fungal-endpoint dietary-trial definition.
       
Dietary fiber level interacts with host genotype: high- versus low-fiber diets in three pig breeds reduced the pathogenic fungus Mucor and increased fiber-degrading Neocallimastix, with breed determining fungal pathogenicity-gene abundance (Wang et al., 2023). Protein and starch source studies in pigs are numerous but almost uniformly bacterial in endpoints.
       
In 1962, culture-based enumeration in 57 pigs found  Candida slooffii (now K. slooffiae) at up to 9 × 106 viable organisms per gram, starch-rich feed apparently raising and cellulose- or protein-rich feed lowering yeast counts (van Uden and do Carmo-Sousa, 1962): A dietary effect documented over sixty years ago and never re-examined with modern sequencing, though yeasts are known to establish only after grain-based feed consumption (Urubschurov et al., 2011).
       
Feed processing is a second, unexploited lever. Total mold counts were significantly higher in mashed than pelleted poultry feed (15 × 103 versus 11 × 102 CFU/g), heat processing reducing but not eliminating contamination, as some species survived and continued to sporulate (Ghaemmaghami et al., 2018). Extrusion before pelleting reduced fungal CFU by 27-65% depending on cereal (Cwalina et al., 2025) and processing shifted community composition from Fusarium-dominant mash to Aspergillus-dominant pellets (Ghaemmaghami et al., 2023).
       
Combining these two literatures yields the single highest-value testable hypothesis identified here: if the chicken gut mycobiome derives principally from diet (Robinson et al., 2022) and pelleting/extrusion reduce viable dietary fungal load an order of magnitude while altering its composition (Ghaemmaghami et al., 2018; Cwalina et al., 2025; Ghaemmaghami et al., 2023), then birds fed mash versus pellets of identical formulation should differ systematically in gut fungal load and structure (Table 1). This requires no novel technology, only that a standard mash-versus-pellet comparison already routine in poultry nutrition add ITS sequencing and fungal qPCR of digesta; to our knowledge this has not been done. An analogous opportunity exists in pigs, where production system exerts a large effect (Scott et al., 2025) but diet, environment and management remain confounded, so a trial isolating diet form or fiber source while holding housing constant would resolve which component is operative.

Table 1: Prioritized research agenda for the gut mycobiome in poultry and pigs, ranked by evidentiary yield relative to cost.


 
Trans-kingdom interactions, performance, Candida overgrowth and mycotoxin dynamics
 
Fungal-bacterial interactions in the monogastric gut are documented consistently enough to be regarded as established and are mechanistically plausible in both directions.
       
In pigs, positive correlations link Kazachstania to several bacterial genera including Lactobacillus, while Aspergillus correlates negatively with SCFA producers (Arfken et al., 2019). Metagenomic analysis of 750 pig gut metagenomes quantified this, with K. slooffiae correlating strongly with Lactobacillus johnsonii (r= 0.75) and negatively with Lachancea kluyveri versus Lactobacillus amylovorus (r= -0.48) and cross-kingdom network connectivity increasing across weaning (Wei et al., 2026; Arfken et al., 2020).
       
Mechanisms are being resolved. Bacterially derived SCFA inhibit fungal growth and modulate fungal cell-surface antigens recognized by immune cells (McCrory et al., 2024): dietary fiber that raises butyrate is thereby an antifungal intervention, unmeasured as such. Direct nutrient competition between intestinal bacteria and fungi has also been demonstrated by shotgun metagenomics (Xie et al., 2023).
       
Links to host performance are documented but not established as causal. Kazachstania abundance was positively associated with piglet BW (Ramayo-Caldas et al., 2020) and K. slooffiae promotes intestinal epithelial glycolysis by decreasing lysine succinylation via sirtuin-5 activation, a defined mechanism linking a resident gut fungus to host energy metabolism (Hu et al., 2023). The yeast also has higher nitrogen and lysine content than nutritional S. cerevisiae, suggesting a nutritional contribution independent of signaling (Urubschurov et al., 2018).
       
These positive findings must be set against directly contradictory evidence (Table 2). K. slooffiae metabolites reduce transepithelial electrical resistance and increase permeability in piglet epithelial cells without affecting viability (Harlow et al., 2024b) and Kazachstania is enriched in diarrheic relative to healthy piglets (Ren et al., 2025; Wei et al., 2026), though it also correlates negatively with the pathogen Mucor circinelloides, suggesting a protective role during dysbiosis (Wei et al., 2026). The most parsimonious reconciliation is that K. slooffiae is a context-dependent commensal whose absolute abundance and surrounding bacteria, resolvable only by dose-response trials.

Table 2: Discordant findings in the poultry and porcine gut mycobiome literature.


       
In broilers, the trans-kingdom picture is dominated by Candida. Shotgun profiling of broiler excreta across 21 days found early C. albicans dominance shifting later toward Fusarium and Malassezia, correlating positively with Streptococcus and Escherichia/Shigella and negatively with Bifidobacterium and Faecalibacterium (Fonseca et al., 2025), positioning Candida abundance as acand idate dysbiosis index rather than a pathogen per se. In mammals, C. albicans is commensal in most healthy individuals, its transition to pathogenicity requiring microbiome imbalance, immune suppression or barrier impairment, with carriage density associated with diet (Jawhara, 2022; Delavy et al., 2023). Candida overgrowth is thus best interpreted as a downstream signal of bacterial and barrier disruption, not an independent target.
       
The immunological basis for fungal effects is well characterized, explaining why yeast-derived additives function even without colonizing. β-glucan is recognized by Dectin-1 and α-mannan by Dectin-2, C-type lectin receptors signaling through Syk and CARD9 to drive pro-inflammatory and Th17 responses (Saijo and Iwakura, 2011); intestinal epithelial cells express Dectin-1 and secrete chemokines in response to β-glucans (Cohen-Kedar et al., 2014) and fluctuating β-glucan and mannan presentation during commensal colonization is required to prime protective Th17 immunity (Shao et al., 2022). A YCW product is thus a defined immunomodulatory ligand rather than a microbial colonizer.
       
Mycotoxin dynamics expose the field’s principal blind spot. Deoxynivalenol and fumonisins impair intestinal barrier function, immunity and performance in both species and mycotoxins alter bacterial composition while the microbiota contributes to detoxification (Jia et al., 2023; Liew and Mohd-Redzwan, 2018). Deoxynivalenol promoted Campylobacter jejuni multiplication in broilers, with aggravated permeability and translocation to liver and spleen (Ruhnau et al., 2020); conversely, YCW extract mitigated mycotoxin effects on gut health in young pigs (Kim et al., 2019) and a multi-component deactivator counteracted fumonisin- and DON-induced changes in broilers (Dasireddy et al., 2026). In each, the hazard and in two, the mitigant, is fungal, yet none measured the gut fungal community.
 
The intervention-trial gap: quantification and characterization
 
Applying the Methods’ operational definition, this review identified fewer than five controlled dietary or feed-processing interventions in poultry or pigs reporting fungal outcomes in gut, fecal or excreta material: The porcine carbohydrate-composition experiment (Luo et al., 2021) the inulin-versus-cellulose fiber trial (Qin et al., 2026), the fiber-by-genotype study (Wang et al., 2023), the broiler feed-additive comparison (Fonseca et al., 2025), the bacitracin methylene disalicylate mycobiome study (Robinson et al., 2020) and the direct K. slooffiae supplementation trial (Harlow et al., 2024a). Against a livestock literature of thousands of controlled feeding trials, this is a vanishingly small evidence base.
       
The gap is sharpest where the intervention is itself fungal. Live yeast supplementation improves average daily gain and alters bacterial composition in piglets (Kiros et al., 2019; Puspani et al., 2023; Floc’h et al., 2022) and broiler gut health (Kyoung et al., 2023; Somkuna et al., 2025), yet across twenty live-yeast records, none reported gut fungal outcomes; only one, from 2006, even enumerated yeast numbers, finding no treatment differences (Li et al., 2006). The one trial that did measure it found K. slooffiae administration produced regional mycobiome shifts but no improvement in weight gain, gut health or immunity, the weaning transition influencing community development far more than supplementation (Harlow et al., 2024a), a negative result found precisely because the fungal endpoint was measured.
       
Three further gaps follow. Causal inference is largely absent, the livestock literature being almost entirely cross-sectional, whereas rodent work has reached causal demonstration, e.g. Schizosaccharomyces pombe supplementation improved lipid and glucose metabolism in obese mice (Zhan et al., 2024). Absolute quantification is almost never reported alongside composition despite validated tools existing (Tkacz et al., 2018; Urubschurov et al., 2015), so whether treatments alter fungal load, community structure, or both remains unknown and dose-response relationships are entirely uncharacterized for fungal outcomes, an obstacle to rational formulation given that immune effects operate through threshold-dependent receptor recognition (Saijo and Iwakura, 2011).
       
Finally, on the AGP transition motivating much of this interest: the assumption that antibiotic withdrawal releases fungi from bacterial suppression is not well founded. In mice, a four-antibiotic cocktail increased fungal abundance roughly 40-fold (Dollive et al., 2013), but amoxicillin-clavulanic acid decreased total fungal load while remodeling the population via expansion of fungus-suppressing Enterobacteriaceae (Spatz et al., 2023); the effect is antibiotic-class specific and bacterially mediated. Whether AGP removal from pig and poultry diets has increased, decreased or restructured the gut mycobiome remains unknown, despite being a global, decade-long, uncontrolled natural experiment.
 
Limitations of this review
 
Four limitations bear on interpretation. First, grey literature and non-English publications were not systematically sought, so the applied feed-technology literature is likely under-represented and the count of qualifying intervention trials should be read as an upper bound on absence, not a definitive census. Second, the review was not prospectively registered. Third, screening and extraction were not duplicated by independent reviewers, introducing possible selection error. Fourth, formal risk-of-bias assessment was not applied, since the dominant designs are poorly served by intervention-oriented instruments; methodological limitations are instead discussed narratively per evidence cluster, following PRISMA 2020 item 27 (Page et al., 2021a) and documented reporting deficiencies in the animal health literature (Sargeant et al., 2021; Toews, 2017). None of this affects the central finding, which concerns the near-total absence of a study category rather than an effect-size estimate.

CONCLUSION

The gut mycobiome of poultry and pigs is a small, measurable, dietarily responsive community whose neglect in monogastric nutrition is no longer defensible; three conclusions follow.
       
First, poultry and pigs require separate treatment. The porcine gut supports K. slooffiae as a genuine post-weaning resident with documented trans-kingdom associations and a defined mechanism of action on host epithelial metabolism, whereas the chicken mycobiome is a transient, diet-derived assemblage without stable succession; interventions and endpoints appropriate to one species do not transfer to the other. Second, measurement remains a constraint: No marker-database combination performs universally, common ITS primers fail to amplify fungi native to the piglet gut and relative abundance cannot distinguish community-structure change from load change; until host-specific mock communities and absolute quantification become routine, disagreements between studies cannot be adjudicated biologically. Third and most consequentially, the field’s defining feature is not a contested finding but an absent category of evidence: Fewer than five controlled dietary interventions in poultry or pigs have reported gut fungal outcomes, despite live yeast being fed to millions of animals and mycotoxin binders addressing a fungal hazard, both evaluated bacterially. The remedy is neither expensive nor technically demanding: The highest-value experiment identified here, a mash-versus-pellet comparison in broilers with ITS sequencing and fungal qPCR of digesta, requires only adding two assays to a trial design already standard in poultry nutrition. Until such measurements are made, dietary modulation of the gut mycobiome will remain a plausible hypothesis, not an established practice.

ACKNOWLEDGEMENT

This review received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
 
Disclaimers
 
The views and conclusions expressed are solely those of the author and do not necessarily represent those of the affiliated institution, which accepts no liability for losses resulting from use of this content.
 
Informed consent
 
This is a systematic review of published literature and did not involve live animals or human participants; ethical approval was therefore not required. Primary studies cited are assumed to have obtained appropriate institutional animal ethics approval as reported by their authors.

CONFLICT OF INTEREST

The author declares no conflicts of interest. No funding or sponsorship influenced the study design, data collection, analysis, publication decision, or manuscript preparation.

REFERENCES


  1. Al-Nijir, M., Chuck, C.J., Bedford, M.R and Henk, D.A. (2024). Metabolic modelling uncovers the complex interplay between fungal probiotics, poultry microbiomes and diet. Microbiome. 12(1): 267.

  2. Arfken, A., Frey, J. and Summers, K. (2020). Temporal dynamics of the gut bacteriome and mycobiome in the weanling pig. Microorganisms. 8(6): 868. 

  3. Arfken, A., Frey, J., Carrillo, N., Dike, N.I., Onyeachonamm, O., Rivera, D., Davies, C. and Summers, K. (2023). Porcine fungal mock community analyses: implications for mycobiome investigations. Frontiers in Cellular and Infection Microbiology. 13: 928353. 

  4. Arfken, A., Frey, J., Ramsay, T. and Summers, K. (2019). Yeasts of burden: exploring the mycobiome-bacteriome of the piglet GI tract. Frontiers in Microbiology. 10: 2286. 

  5. Bakker, M.G. (2018). A fungal mock community control for amplicon sequencing experiments. Molecular Ecology Resources. 18(3): 541-556. 

  6. Cohen-Kedar, S., Baram, L., Elad, H., Brazowski, E., Guzner Gur, H. and Dotan, I. (2014). Human intestinal epithelial cells respond to β glucans via Dectin 1 and Syk. European Journal of Immunology. 44(12): 3729-3740. 

  7. Cwalina, P., Obidziñski, S., Kowczyk-Sadowy, M., Sienkiewicz, A. and Mazur, J. (2025). Extrusion processing of fungal- contaminated cereals as a method for spore reduction and binder development in feed materials. Materials. 18(22): 5117. 

  8. Dasireddy, J.R., Kappari, L., Pender, C., Doupovec, B., Selvaraj, R.K., Applegate, T.J. and Shanmugasundaram, R. (2026). Effects of a mycotoxin deactivator in broilers exposed to subclinical doses of fumonisins and deoxynivalenol. Poultry Science. 105(6): 106843. 

  9. De Filippis, F., Laiola, M., Blaiotta, G. and Ercolini, D. (2017). Different amplicon targets for sequencing-based studies of fungal diversity. Applied and Environmental Microbiology. 83: e00905-e00917. 

  10. Delavy, M., Sertour, N., Patin, E., Chatelier, L.E., Cole, N., Dubois, F., Xie, Z., Saint- André, V., Manichanh, C., Walker, A.W., Quintana-Murci, L., Duffy, D., d’Enfert, C., Bougnoux, M. and Consortium, M.I. (2023). Unveiling Candida albicans intestinal carriage in healthy volunteers: the role of micro- and mycobiota, diet, host genetics and immune response. Gut Microbes. 15(2): 2287618. 

  11. Deng, X., Li, H., Wu, A., He, J., Mao, X., Dai, Z., Tian, G., Cai, J., Tang, J. and Luo, Y. (2025). Composition, influencing factors and effects on host nutrient metabolism of fungi in gastrointestinal tract of monogastric animals. Animals. 15(4): 512. 

  12. Dollive, S., Chen, Y.Y., Grunberg, S., Bittinger, K., Hoffmann, C.V., Vandivier, L.E., Cuff, C.C., Lewis, J.D., Wu, G.D. and Bushman, F. (2013). Fungi of the murine gut: Episodic variation and proliferation during antibiotic treatment. Plos One. 8(8): e71806. 

  13. Floc’h, L.N., Achard, C., Eugenio, F.A., Apper, E., Combes, S. and Quesnel, H. (2022). Effect of live yeast supplementation in sow diet during gestation and lactation on sow and piglet fecal microbiota, health and performance. Journal of Animal Science. 100(8): skac209. 

  14. Fonseca, A., Kenney, S.M., Boney, J. and Ganda, E. (2025). Mycobiome temporal and functional dynamics in broilers: Ecological perspective on bacterial-fungal correlations and the effect of feed additives. Poultry Science. 104(12): 106092. 

  15. Forcina, G., Pérez-Pardal, L., Carvalheira, J. and Beja-Pereira, A. (2022). Gut microbiome studies in livestock: achievements, challenges and perspectives. Animals. 12(23): 3375. 

  16. Ghaemmaghami, S., Nowroozi, H. and Moghadam, M.T. (2018). Toxigenic fungal contamination for assessment of poultry feeds: Mashed vs. pellet. Iranian Journal of Toxicology. 12(5): 5-10. 

  17. Ghaemmaghami, S., Rouhanipour, H. and Sharifi, S.D. (2023). Aflatoxin levels in poultry feed: A comparison of mash and pellet forms. Poultry Science. 103(1): 103254. 

  18. Guerre, P. (2016). Worldwide mycotoxins exposure in pig and poultry feed formulations. Toxins. 8(12): 350. 

  19. Harlow, K., Summers, K., Oliver, W., Wells, J.E., Crouse, M., Neville, B., Rempel, L.A., Rivera, I., Ramsay, T.G. and Davies, C.P. (2024a). Weaning transition, but not the administration of probiotic candidate Kazachstania slooffiae, shaped the gastrointestinal bacterial and fungal communities in nursery piglets. Frontiers in Veterinary Science. 10: 1303984. 

  20. Harlow, K., Summers, K., Rivera, I., Postnikova, O., Ramsay, T.G. and Davies, C.P. (2024b). PSII-21 Metabolites of Kazachstania slooffiae reduce tight junction integrity in piglet intestinal epithelial cells. Journal of Animal Science. 102(3): 698. 

  21. Hu, J., Chen, J., Hou, Q., Xu, X., Ren, J.L. and Yan, X. (2023). Core-predominant gut fungus Kazachstania slooffiae promotes intestinal epithelial glycolysis via lysine desuccinylation in pigs. Microbiome. 11(3): 31.

  22. Jawhara, S. (2022). How Gut Bacterial Dysbiosis Can Promote  Candida albicans Overgrowth during Colonic Inflammation. Microorganisms. 10(5): 1014. 

  23. Jia, B., Lin, H., Yu, S., Liu, N., Yu, D. and Wu, A. (2023). Mycotoxin deoxynivalenol-induced intestinal flora disorders, dysfunction and organ damage in broilers and pigs. Journal of Hazardous Materials. 451: 131172. 

  24. Jubair, A.F., Al-Nuaimy, A.A., Obaid, N.H. and Al-Jabry, S.M.E. (2026). Effect of mycotoxins produced by Fusarium moniliforme and Aspergillus flavus associated with wheat grains cultivated in the Al-Muthanna Desert and used as poultry feed. Agricultural Science Digest. 45(6): 1082- 1086. doi: 10.18805/ag.DF-741.

  25. Kauserud, H. (2023). ITS alchemy: on the use of ITS as a DNA marker in fungal ecology. Fungal Ecology. 65: 101274. 

  26. Kim, E.J., Kyoung, H., Koh, N.H., Lee, H., Lee, S., Kim, Y., Park, K.I., Heo, J. and Song, M. (2022). Supplementation of live yeast culture modulates intestinal health, immune responses and microbiota diversity in broiler chickens. Journal of Animal Science. 100(5): skac122. 

  27. Kim, S., Holanda, D., Gao, X., Park, I. and Yiannikouris, A. (2019). Efficacy of a yeast cell wall extract to mitigate the effect of naturally co-occurring mycotoxins contaminating feed ingredients fed to young pigs: Impact on gut health, microbiome and growth. Toxins. 11(11): 633. 

  28. Kiros, T., Luise, D., Derakhshani, H., Petri, R., Trevisi, P., D’inca, R., Auclair, E. and Van Kessel, A.V. (2019). Effect of live yeast Saccharomyces cerevisiae supplementation on the performance and cecum microbial profile of suckling piglets. Plos One. 14(7): e0219557. 

  29. Kyoung, H., Kim, E.J., Cho, J., Lee, H., Kim, Y., Park, K. I., Kim, H. and Song, M. (2023). Dietary yeast cell wall enhanced intestinal health of broiler chickens by modulating intestinal integrity, immune responses and microbiota. Poultry Science. 102(6): 102660. 

  30. Li, J., Chen, D., Yu, B., He, J., Huang, Z., Zheng, P., Mao, X., Li, H., Yu, J., Luo, J., Yan, H. and Luo, Y. (2022). Batch and sampling time exert a larger influence on the fungal community than gastrointestinal location in model animals: A meaningful case study. Frontiers in Nutrition. 9: 1021215. 

  31. Li, J., Li, D., Gong, L., Y., He, Y. and Zhai, H. (2006). Effects of live yeast on the performance, nutrient digestibility, gastrointestinal microbiota and concentration of volatile fatty acids in weanling pigs. Archives of Animal Nutrition. 60(4): 277-288. 

  32. Liew, W.P.P. and Mohd-Redzwan, S. (2018). Mycotoxin: its impact on gut health and microbiota. Frontiers in Cellular and Infection Microbiology. 8: 60.

  33. Liu, H.Y., Li, S., Ogamune, K.J., Ahmed, A.A., Kim, I., Zhang, Y. and Cai, D. (2025). Fungi in the gut microbiota: Interactions, homeostasis and host physiology. Microorganisms. 13(1): 70. https://doi.org/10.3390/microorganisms13010070.

  34. Luo, Y., Li, J., Zhou, H., Yu, B., He, J., Wu, A., Huang, Z., Zheng, P., Mao, X., Yu, J., Li, H., Wang, H., Wang, Q., Yan, H. and Chen, D. (2021). The nutritional significance of intestinal fungi: Alteration of dietary carbohydrate composition triggers colonic fungal community shifts in a pig model. Applied and Environmental Microbiology. 87: e00038- e00021. 

  35. McCrory, C., Lenardon, M. and Traven, A. (2024). Bacteria-derived short-chain fatty acids as potential regulators of fungal commensalism and pathogenesis. Trends in Microbiology. 32(11): P1106-1118. 

  36. Page, M., McKenzie, J., Bossuyt, P., Boutron, I., Hoffmann, T., Mulrow, C., Shamseer, L., Tetzlaff, J., Akl, E., Brennan, S., Chou, R., Glanville, J.M., Grimshaw, J., Hrõbjartsson, A., Lalu, M., Li, T., Loder, E., Mayo-Wilson, E., McDonald, S. and Moher, D. (2021a). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Systematic Reviews. 10. 

  37. Page, M., Moher, D., Bossuyt, P., Boutron, I., Hoffmann, T., Mulrow, C., Shamseer, L., Tetzlaff, J. et al. (2021b). PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. The BMJ. 372. 

  38. Puspani, E.C., Rawati, D.P.M.A. and Bidura, I.G.N.G. (2023). Effects of dietary yeast culture on growth performance, feed digestibility and faecal microbiota in weaned piglets. Asian Journal of Dairy and Food Research. 42(4): 490-494. doi: 10.18805/ajdfr.DRF-290.

  39. Qin, J., Li, H., Deng, X., Huang, S., He, J., Wu, A., Dai, Z., Cai, J., Tian, G., Mao, X., Yu, B., Zheng, P., Luo, J., Yan, H., Tang, J. and Luo, Y. (2026). Dietary fiber-driven shifts in mycobiota and short-chain fatty acid landscape in porcine hindgut. Animal Microbiome. 8(1): 68. doi: 10.1186/s425 23-026-00563-8.

  40. Ramayo-Caldas, Y., Prenafeta, F., Zingaretti, L., Gonzales, O., Dalmau, A., Quintanilla, R. and Ballester, M. (2020). Gut eukaryotic communities in pigs: diversity, composition and host genetics contribution. Animal Microbiome. 2(1): 18. 

  41. Ren, R., Zhang, X., Lou, F., Li, Y., L., Xiao, Y., Chen, Q., Wen, Y. and Lyu, W. (2025). Intestinal fungi biogeography, succession and its association with diarrhea in pigs. Journal of Animal Science and Biotechnology. 16: 80. 

  42. Robinson, K., Xiao, Y., Johnson, T., Chen, B., Yang, Q., Lyu, W., Wang, J., Fansler, N., Becker, S., Liu, J., Yang, H. and Zhang, G. (2020). Chicken intestinal mycobiome: Initial characterization and its response to bacitracin methylene disalicylate. Applied and Environmental Microbiology. 86: e00304-e00321.

  43. Robinson, K., Yang, Q., Stewart, S.N., Whitmore, M.A. and Zhang, G. (2022). Biogeography, succession and origin of the chicken intestinal mycobiome. Microbiome. 10(1): 55. doi: 10.1186/s40168-022-01252-9. 

  44. Ruhnau, D., Hess, C., Grenier, B., Doupovec, B., Schatzmayr, D., Hess, M. and Awad, W. (2020). The Mycotoxin Deoxynivalenol (DON) Promotes Campylobacter jejuni multiplication in the intestine of broiler chickens with consequences on bacterial translocation and gut integrity. Frontiers in Veterinary Science. 7. 

  45. Saijo, S. and Iwakura, Y. (2011). Dectin-1 and Dectin-2 in innate immunity against fungi. International Immunology. 23(8): 467-472. 

  46. Saleem, M.U., Masood, S., Zaneb, H., Durrani, A.Z., Aslam, A., Ashraf, K., Rashid, M.I., Habib-ur-Rehman, Muti-ur- Rehman, Ashraf, S., Usman, M.M. and Shaheen, M.S. (2018). Combined supplementation of organic acid blend and hydrolyzed yeast mixture increases growth performance and tibia bone strength in broilers. Indian Journal of Animal Research. 52(11): 1613-1617. doi: 10.18805/ijar.B-858.

  47. Sargeant, J., Reynolds, K., Winder, C. and O’Connor, A. (2021). Completeness of reporting of systematic reviews in the animal health literature: A meta-research study. Preventive Veterinary Medicine. 195: 105472. 

  48. Scott, C., Holman, D., Gzyl, K.E., Ibe, A. and Taheri, A. (2025). Production Systems and Age Influence Fecal Mycobiota Diversity and Composition in Swine. Microbial Ecology. 88: 104. 

  49. Shao, T.Y., Kakade, P., Witchley, J., Frazer, C., Murray, K., Ene, I.V., Haslam, D., Hagan, T., Noble, S., Bennett, R. and Way, S. (2022). Candida albicans oscillating UME6 expression during intestinal colonization primes systemic Th17 protective immunity. Cell Reports. 39(7): 110837. 

  50. Somkuna, N., Somkuna, E., Rattanasintupong, K., Triwiset, C. and Wongsuwan, N. (2025). Dietary utilization of yeast- fermented coconut milk residue on productive performance and carcass traits of broilers. Asian Journal of Dairy and Food Research. 44(5): 838-843. doi: 10.18805/ajdfr.DRF-481.

  51. Spatz, M., Da Costa, G., Ventin-Holmberg, R., Planchais, J., Michaudel, C., Wang, Y., Danne, C., Lapière, A., Michel, M., Kolho, K., Langella, P., Sokol, H. and Richard, M.L. (2023). Antibiotic treatment using amoxicillin-clavulanic acid impairs gut mycobiota development through modification of the bacterial ecosystem. Microbiome 11(1): 73. doi: 10.1186/s40168-023-01516-y.  

  52. Summers, K., Frey, J., Ramsay, T. and Arfken, A. (2019). The piglet mycobiome during the weaning transition: A pilot study. Journal of Animal Science. 97(7): 2889-2900. 

  53. Tkacz, A., Hortala, M. and Poole, P. (2018). Absolute quantitation of microbiota abundance in environmental samples. Microbiome. 6(1): 110. 

  54. Toews, L. (2017). Compliance of systematic reviews in veterinary journals with preferred reporting items for systematic reviews and meta-analysis (PRISMA) literature search reporting guidelines. Journal of the Medical Library Association. 105: 233-239. 

  55. Urubschurov, V., Büsing, K., Janczyk, P., Souffrant, W. and Zeyner, A. (2015). Development and evaluation of qPCR assay for quantitation of Kazachstania slooffiae and total yeasts occurring in the porcine gut. Current Microbiology. 71(3): 373-381. 

  56. Urubschurov, V., Büsing, K., Souffrant, W., Schauer, N. and Zeyner, A. (2018). Porcine intestinal yeast species, Kazachstania slooffiae, a new potential protein source with favourable amino acid composition for animals. Journal of Animal Physiology and Animal Nutrition. 102(2): e892-e901. 

  57. Urubschurov, V., Janczyk, P., Souffrant, W., Freyer, G. and Zeyner, A. (2011). Establishment of intestinal microbiota with focus on yeasts of unweaned and weaned piglets kept under different farm conditions. FEMS Microbiology Ecology. 77(3): 493-502. 

  58. Usyk, M., Peters, B., Karthikeyan, S., McDonald, D., Sollecito, C., Vázquez-Baeza, Y., Shaffer, J.P., Gellman, M., Talavera, G., Daviglus, M., Thyagarajan, B., Knight, R., Qi, Q., Kaplan, R. and Burk, R. (2023). Comprehensive evaluation of shotgun metagenomics, amplicon sequencing and harmonization of these platforms for epidemiological studies. Cell Reports Methods. 3(1): 100391. 

  59. van Uden, N. and do Carmo-Sousa, L. (1962). Quantitative aspects of the intestinal yeast flora of swine. Microbiology. 27(1): 35-40. 

  60. Wang, T., Liu, J., Luo, Y., Yu, B., Kong, X., Zheng, P., Huang, Z., Mao, X., Yu, J., Luo, J., Yan, H. and He, J. (2023). Combined effects of host genetics and diet on porcine intestinal fungi and their pathogenic genes. Frontiers in Microbiology. 14: 1192288. 

  61. Wei, G.C., Liu, M., Huang, L. and Chen, C. (2026). Metagenomic sequencing reveals the dynamic changes of pig gut fungal composition following the ages and identifies fungal species associated with diarrhea in piglets. Animal Microbiome 8(1): 60. 

  62. Xie, Z., Canalda-Baltrons, A., d’Enfert, C. and Manichanh, C. (2023). Shotgun metagenomics reveals interkingdom association between intestinal bacteria and fungi involving competition for nutrients. Microbiome. 11(1): 275. doi: 10.1186/s40 168-023-01693-w. 

  63. Zhan, H., Wan, Y., Sun, Y., Xu, Z., Zhang, F., Yang, K., Zhu, W., Cheung, C., Tang, W., Ng, E.K. et al. (2024). Gut mycobiome alterations in obesity in geographically different regions. Gut Microbes. 16(1): 2367297.
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    Review Article

    Dietary Modulation of the Gut Mycobiome in Poultry and Monogastric Animals: A Systematic Review of Composition, Measurement, Trans-kingdom Interactions and the Absence of Fungal-targeted Nutrition Trials

    K
    Karl Louisse D. Obispo1,*
    1Department of Animal Science, College of Agriculture, Food, Environment and Natural Resources, Cavite State University, Indang, Cavite, 4122 Philippines.

    ABSTRACT

    Fungi form a minor but functionally disproportionate fraction of the monogastric gut microbiota. Bacterial communities in poultry and pigs are well characterized, but the mycobiome remains poorly defined and its dietary responsiveness is largely assumed. This review establishes mycobiome composition and measurement in healthy poultry and pigs, synthesizes dietary and feed-processing drivers of fungal load and diversity, evaluates trans-kingdom interactions linked to performance, Candida overgrowth and mycotoxin dynamics and quantifies the gap in fungal-targeted dietary-intervention trials. A systematic search of Semantic Scholar, PubMed and Scopus used twenty structured queries across five sub-areas derived from a hybrid PICO-decomposition framework. Records were screened against a priori eligibility criteria centered on poultry and porcine hosts; methodological literature from other hosts was retained where it informed measurement validity. Of 387 records retrieved, 231 were unique and 80 met eligibility. The porcine mycobiome converges on Kazachstania slooffiae as a dominant post-weaning resident, whereas the chicken mycobiome is transient, diet-derived and lacks succession, an asymmetry with direct implications for intervention design. No marker-database combination performed universally and common ITS primers failed to amplify piglet-native fungi. Feed processing reduced viable mold counts by 27-65%, yet aflatoxin was higher in pelleted than mash feed. Critically, live-yeast and mycotoxin-mitigation trials, where the agent or hazard is itself fungal, almost universally reported bacterial endpoints alone; fewer than five controlled dietary trials in either species reported fungal community outcomes.

    INTRODUCTION

    The gastrointestinal microbiota of poultry and pigs has been intensively studied for two decades, reshaping applied monogastric nutrition, yet that literature is overwhelmingly bacterial. Fungi, collectively the mycobiome, represent only 0.01-2% of intestinal microbial cells, though an average fungal cell occupies roughly one hundred times the volume of a bacterial cell, so read-proportion abundance understates fungal biomass (Deng et al., 2025). Fungal cell-wall polysaccharides, β-glucans and mannans, are potent pattern-recognition ligands for the vertebrate innate immune system (Saijo and Iwakura, 2011) and fungi secrete hydrolytic enzymes and metabolites acting on bacterial neighbors and host epithelium alike (Hu et al., 2023; McCrory et al., 2024).
           
    For the animal nutritionist, three developments make this omission increasingly untenable. First, withdrawal of antibiotic growth promoters has driven commercial-scale adoption of yeast-based feed additives, live Saccharomyces cerevisiae, yeast cell wall preparations, yeast culture and postbiotics (Kim et al., 2022; Saleem et al., 2018): fungi administered to modulate a gut ecosystem whose fungal component goes unmeasured. Second, mycotoxin contamination of cereal-based diets is a persistent, climate-sensitive hazard (Guerre, 2016; Jubair et al., 2026); mycotoxins are fungal secondary metabolites, yet the producing fungi and their fate in the gut are rarely quantified alongside toxin concentrations. Third, routine feed-processing operations measurably affect the viable fungal load entering the animal and diet is the principal source of the chicken intestinal mycobiome (Robinson et al., 2022). Each is a fungal intervention already embedded in commercial practice and evaluated almost exclusively through bacterial endpoints.
           
    Poultry and pigs also should not be treated as a single case biologically. The porcine gut supports a genuine fungal resident, K. slooffiae, which colonizes after weaning and persists into adulthood (Summers et al., 2019; Urubschurov et al., 2011), whereas the chicken mycobiome appears largely transient, replenished continuously from feed and environment without stable succession (Robinson et al., 2022). This distinction determines whether dietary modulation means shaping a resident community or controlling a continuous environmental influx, objectives requiring different interventions and measurements.
           
    Several recent narrative reviews have surveyed intestinal fungi in monogastric animals (Deng et al., 2025; Liu et al., 2025), but none has applied systematic search and reporting methodology to dietary modulation specifically, or quantified rather than merely asserted the intervention-trial gap. Given documented reporting deficiencies in the animal health and veterinary systematic review literature (Sargeant et al., 2021; Toews, 2017), a transparent, reproducible approach is warranted.
           
    This review therefore addresses four objectives: characterize the composition of the healthy poultry and porcine gut mycobiome and how it is measured, including ITS amplicon versus shotgun metagenomic approaches and reference-database limitations; synthesize dietary and feed-processing determinants of fungal load and diversity; examine trans-kingdom fungal-bacterial interactions linked to performance, Candida overgrowth and mycotoxin dynamics; and quantify the absence of controlled dietary-intervention trials with fungal endpoints and derive a prioritized research agenda.
     
    Protocol and reporting
     
    This review was conducted at the Department of Animal Science, Cavite State University, Indang, Cavite, Philippines and is reported per the PRISMA 2020 statement and its explanation and elaboration document (Page et al., 2021a; Page et al., 2021b). Because the evidence base was anticipated to be heterogeneous in design, host species, sampling site and analytical platform, narrative synthesis with structured tabulation was specified a priori rather than quantitative meta-analysis.
     
    Search framework and question formulation
     
    The review question combined PICO with topic decomposition, since the scope spans both a population-intervention question (dietary modulation) and a methodological question (measurement validity). Population: broilers, laying hens and pigs, emphasizing peri-weaning and early post-hatch periods. Intervention: diet composition, feed additives, processing method and mycotoxin exposure. Outcomes: fungal community composition, diversity and load, performance, gut health and mycotoxin dynamics. This mapped to five search sub-areas: mycobiome composition; methodological comparison and database limitations; dietary and feed-processing drivers; trans-kingdom interactions; and intervention trials and the endpoint gap.
     
    Information sources and search strategy
     
    Searches were executed in Semantic Scholar, PubMed and Scopus. Twenty structured queries, each combining a biological target, host species, methodological term and outcome term as natural-language strings (semantic rather than Boolean retrieval), were run between May and July 2026. Grey literature and non-English sources were not systematically sought, so coverage of the applied feed-technology literature is likely incomplete.
     
    Eligibility criteria
     
    Records were eligible if they reported original data or synthesis on intestinal, fecal or excreta fungal communities in poultry or pigs; on dietary, additive or feed-processing effects on fungal load or diversity; or on fungal-bacterial interactions with host outcomes. Methodological studies on fungal marker genes, primers, reference databases or quantification approaches were eligible regardless of host or matrix. Mechanistic studies in humans, mice or in vitro systems were eligible only where they addressed a mechanism directly invoked in interpreting livestock data and are identified as such throughout. Records addressing ruminant hosts exclusively, feed contamination without a gut- or animal-related outcome, or fungal disease pathology unrelated to the commensal community were excluded.
           
    A record was classified as a fungal-endpoint dietary trial only if it met all four criteria: A controlled dietary or feed-processing intervention with a concurrent comparison group; live target-species animals; A fungal community or load measurement as an outcome and that measurement made in GI, fecal or excreta material rather than feed alone. This definition underlies the gap quantification reported in Results.
     
    Selection process, data extraction and synthesis
     
    Records returned by each query were screened at title and abstract level against the eligibility criteria, with full text examined where necessary; duplicates were identified by title matching and removed. Extracted variables comprised host species and production stage, sample matrix and GI site, fungal marker gene and reference database, endpoint type, intervention type and principal findings. Findings were synthesized narratively within the five sub-areas, with discordant results tabulated explicitly and adjudicated on methodological grounds rather than reconciled by omission. Formal risk-of-bias assessment was not applied, given the predominant designs (see Limitations).
     
    Search yield and characteristics of the evidence base
     
    The twenty queries returned 387 records, of which 231 were unique and 80 met the eligibility criteria; the most relevant are cited herein. Every query returned results, so yield was constrained by relevance, not retrieval; several returned predominantly bacterial-endpoint literature despite fungal search terms.
           
    That pattern is a principal finding: the query on dietary fiber and prebiotic effects on the broiler gut returned twenty records, eighteen reporting 16S rRNA bacterial endpoints exclusively; the live-yeast-in-pigs query returned twenty records, none reporting gut fungal outcomes and only one enumerating yeast numbers at all (Li et al., 2006). This matches evidence that livestock microbiome research overwhelmingly targets bacteria, fungi being markedly under-studied (Forcina et al., 2022).
     
    Composition of the healthy gut mycobiome: A fundamental species asymmetry
     
    At phylum level the two species converge: Ascomycota and Basidiomycota dominate the intestinal mycobiome of both broilers and pigs, jointly accounting for 90-99% of fungal sequences regardless of gut segment, age or production system (Robinson et al., 2022; Arfken et al., 2020; Scott et al., 2025). Below phylum level the similarity ends and the divergence is ecological rather than merely taxonomic.
           
    In pigs, the defining feature is the emergence of a genuine resident. K. slooffiae is essentially absent before weaning, rises sharply after the transition to solid feed and persists into adulthood, culture-based work confirming a post-weaning increase in fungal burden that does not differ from adult levels (Summers et al., 2019; Urubschurov et al., 2011). In a cohort of 514 Duroc pigs, the mycobiota was dominated by yeasts, with Kazachstania spp. abundance positively associated with piglet body weight, while low heritability of fungal α-diversity (0.15-0.28) indicated a community shaped predominantly by environment and diet rather than host genotype (Ramayo-Caldas et al., 2020) and therefore tractable by nutritional means.
           
    In broilers, no equivalent resident has been identified. Comprehensive ITS2 characterization found significant spatial and temporal variation but no successional trend to 42 days of age, with the community more diverse in the upper than lower tract, the inverse of the bacterial pattern; total fungal populations ranged from 1.0 × 104 to 1.1 × 106 per gram of digesta, under 0.06% of bacterial counts by day 42 and hatchery-derived mycobiota in newly hatched chicks were replaced by diet-derived fungi within three days (Robinson et al., 2022). Earlier work found the day-28 mycobiome dominated by just three species, Scopulariopsis brevicaulis, Trichosporon asahii and Aspergillus spp., over 80% of fungal reads, against hundreds of bacterial taxa (Robinson et al., 2020). In pigs, dietary modulation thus means shaping a resident yeast population; in poultry, it means managing a continuous dietary influx in which feed fungal composition is the proximate determinant of gut fungal composition, different problems that have permitted unwarranted extrapolation between species.
           
    Both communities are strongly structured by non-dietary factors that any trial must control for. Production system exerts a large effect, with pasture-raised pigs hosting significantly greater fungal richness than conventionally raised animals (Scott et al., 2025) and in eleven pigs of matched genetics, housing and diet sampled in two batches ten months apart, batch and sampling time influenced fungal composition more than GI location (Li et al., 2022): a trial that does not block on batch and season risks attributing to treatment what belongs to time.
     
    Measurement: no marker-database combination performs universally
     
    The methodological literature describes a measurement system whose principal failure modes remain unresolved, conditioning the interpretation of every compositional finding above.
           
    The most direct evidence comes from mock-community analysis in pigs. Comparing 18S, ITS1 and ITS2 markers against UNITE and SILVA databases using defined communities from five fungal isolates recovered from weanling piglet feces, no marker–database combination consistently outperformed the others; ITS markers were marginally superior for species identification, but Lichtheimia corymbifera, a common piglet-gut community member, was not amplified by either ITS1 or ITS2 primer, skewing ITS-based estimates while 18S profiles remained accurate. Gene copy number also varied by taxon (83-85 for K. slooffiae, 90-144 for L. corymbifera), confounding conversion of read counts into abundance (Arfken et al., 2023).
           
    These findings are corroborated across matrices: amplicon length heterogeneity in the ITS1-ITS2 region overestimates species with shorter amplicons, whereas 18S and 26S amplicons quantify more reliably (De Filippis et al., 2017) and across 37 mock communities, classification accuracy (56-100%) varied with marker, database, software, taxonomic level and extraction protocol alike, abundance estimation from read counts performing poorly regardless (Bakker, 2018).
           
    Shotgun metagenomics is no straightforward remedy: in 1,772 participants with paired ITS1 and shotgun data, no meaningful agreement was observed between platforms for fungal taxa, unlike close agreement for bacteria, since fungi occur at low relative abundance against sparse reference genomes (Usyk et al., 2023). Enrichment with in-house fungal databases can render shotgun profiling viable, as now demonstrated across 750 pig gut metagenomes (Xie et al., 2023; Wei et al., 2026), but only with substantial bespoke effort. ITS remains the best general fungal barcode despite inherent limitations unresolvable by bioinformatics alone (Kauserud, 2023).
           
    Two practical remedies remain under-used. First, relative abundance should be supplemented by absolute quantification: spike-in constructs and a validated qPCR assay for K. slooffiae and total yeasts have existed for a decade (Tkacz et al., 2018; Urubschurov et al., 2015), since relative abundance can fall while absolute abundance rises (Tkacz et al., 2018). Second, host-specific mock communities should be sequenced alongside experimental samples (Arfken et al., 2023). This review therefore reports findings with the marker used and examines discrepancies methodologically before biological interpretation; high inter-study variation in intestinal mycobiota (Robinson et al., 2022) is at least partly a measurement artefact.
     
    Dietary and feed-processing drivers of fungal load and diversity
     
    Diet is the primary source of the chicken intestinal mycobiome (Robinson et al., 2022) and dietary carbohydrate composition restructures the colonic fungal community in pigs (Luo et al., 2021). These findings should have generated a substantial applied literature; they have not.
           
    The carbohydrate evidence in pigs is strongest. In an orthogonal design varying amylose:amylopectin ratio, non-starch polysaccharide level and mannan-oligosaccharide (MOS) inclusion, colonic fungal communities responded in the order MOS>amylose:amylopectin>non-starch polysaccharide, with genera including Saccharomycopsis and Wallemia correlating with colonic glucose, fructose and β-D-glucosidase activity (Luo et al., 2021). A controlled trial comparing inulin and cellulose (5%) in growing pigs restructured rectal fungal communities with distinct temporal dynamics correlated with SCFA profiles (Qin et al., 2026), one of the very few studies meeting this review’s fungal-endpoint dietary-trial definition.
           
    Dietary fiber level interacts with host genotype: high- versus low-fiber diets in three pig breeds reduced the pathogenic fungus Mucor and increased fiber-degrading Neocallimastix, with breed determining fungal pathogenicity-gene abundance (Wang et al., 2023). Protein and starch source studies in pigs are numerous but almost uniformly bacterial in endpoints.
           
    In 1962, culture-based enumeration in 57 pigs found  Candida slooffii (now K. slooffiae) at up to 9 × 106 viable organisms per gram, starch-rich feed apparently raising and cellulose- or protein-rich feed lowering yeast counts (van Uden and do Carmo-Sousa, 1962): A dietary effect documented over sixty years ago and never re-examined with modern sequencing, though yeasts are known to establish only after grain-based feed consumption (Urubschurov et al., 2011).
           
    Feed processing is a second, unexploited lever. Total mold counts were significantly higher in mashed than pelleted poultry feed (15 × 103 versus 11 × 102 CFU/g), heat processing reducing but not eliminating contamination, as some species survived and continued to sporulate (Ghaemmaghami et al., 2018). Extrusion before pelleting reduced fungal CFU by 27-65% depending on cereal (Cwalina et al., 2025) and processing shifted community composition from Fusarium-dominant mash to Aspergillus-dominant pellets (Ghaemmaghami et al., 2023).
           
    Combining these two literatures yields the single highest-value testable hypothesis identified here: if the chicken gut mycobiome derives principally from diet (Robinson et al., 2022) and pelleting/extrusion reduce viable dietary fungal load an order of magnitude while altering its composition (Ghaemmaghami et al., 2018; Cwalina et al., 2025; Ghaemmaghami et al., 2023), then birds fed mash versus pellets of identical formulation should differ systematically in gut fungal load and structure (Table 1). This requires no novel technology, only that a standard mash-versus-pellet comparison already routine in poultry nutrition add ITS sequencing and fungal qPCR of digesta; to our knowledge this has not been done. An analogous opportunity exists in pigs, where production system exerts a large effect (Scott et al., 2025) but diet, environment and management remain confounded, so a trial isolating diet form or fiber source while holding housing constant would resolve which component is operative.

    Table 1: Prioritized research agenda for the gut mycobiome in poultry and pigs, ranked by evidentiary yield relative to cost.


     
    Trans-kingdom interactions, performance, Candida overgrowth and mycotoxin dynamics
     
    Fungal-bacterial interactions in the monogastric gut are documented consistently enough to be regarded as established and are mechanistically plausible in both directions.
           
    In pigs, positive correlations link Kazachstania to several bacterial genera including Lactobacillus, while Aspergillus correlates negatively with SCFA producers (Arfken et al., 2019). Metagenomic analysis of 750 pig gut metagenomes quantified this, with K. slooffiae correlating strongly with Lactobacillus johnsonii (r= 0.75) and negatively with Lachancea kluyveri versus Lactobacillus amylovorus (r= -0.48) and cross-kingdom network connectivity increasing across weaning (Wei et al., 2026; Arfken et al., 2020).
           
    Mechanisms are being resolved. Bacterially derived SCFA inhibit fungal growth and modulate fungal cell-surface antigens recognized by immune cells (McCrory et al., 2024): dietary fiber that raises butyrate is thereby an antifungal intervention, unmeasured as such. Direct nutrient competition between intestinal bacteria and fungi has also been demonstrated by shotgun metagenomics (Xie et al., 2023).
           
    Links to host performance are documented but not established as causal. Kazachstania abundance was positively associated with piglet BW (Ramayo-Caldas et al., 2020) and K. slooffiae promotes intestinal epithelial glycolysis by decreasing lysine succinylation via sirtuin-5 activation, a defined mechanism linking a resident gut fungus to host energy metabolism (Hu et al., 2023). The yeast also has higher nitrogen and lysine content than nutritional S. cerevisiae, suggesting a nutritional contribution independent of signaling (Urubschurov et al., 2018).
           
    These positive findings must be set against directly contradictory evidence (Table 2). K. slooffiae metabolites reduce transepithelial electrical resistance and increase permeability in piglet epithelial cells without affecting viability (Harlow et al., 2024b) and Kazachstania is enriched in diarrheic relative to healthy piglets (Ren et al., 2025; Wei et al., 2026), though it also correlates negatively with the pathogen Mucor circinelloides, suggesting a protective role during dysbiosis (Wei et al., 2026). The most parsimonious reconciliation is that K. slooffiae is a context-dependent commensal whose absolute abundance and surrounding bacteria, resolvable only by dose-response trials.

    Table 2: Discordant findings in the poultry and porcine gut mycobiome literature.


           
    In broilers, the trans-kingdom picture is dominated by Candida. Shotgun profiling of broiler excreta across 21 days found early C. albicans dominance shifting later toward Fusarium and Malassezia, correlating positively with Streptococcus and Escherichia/Shigella and negatively with Bifidobacterium and Faecalibacterium (Fonseca et al., 2025), positioning Candida abundance as acand idate dysbiosis index rather than a pathogen per se. In mammals, C. albicans is commensal in most healthy individuals, its transition to pathogenicity requiring microbiome imbalance, immune suppression or barrier impairment, with carriage density associated with diet (Jawhara, 2022; Delavy et al., 2023). Candida overgrowth is thus best interpreted as a downstream signal of bacterial and barrier disruption, not an independent target.
           
    The immunological basis for fungal effects is well characterized, explaining why yeast-derived additives function even without colonizing. β-glucan is recognized by Dectin-1 and α-mannan by Dectin-2, C-type lectin receptors signaling through Syk and CARD9 to drive pro-inflammatory and Th17 responses (Saijo and Iwakura, 2011); intestinal epithelial cells express Dectin-1 and secrete chemokines in response to β-glucans (Cohen-Kedar et al., 2014) and fluctuating β-glucan and mannan presentation during commensal colonization is required to prime protective Th17 immunity (Shao et al., 2022). A YCW product is thus a defined immunomodulatory ligand rather than a microbial colonizer.
           
    Mycotoxin dynamics expose the field’s principal blind spot. Deoxynivalenol and fumonisins impair intestinal barrier function, immunity and performance in both species and mycotoxins alter bacterial composition while the microbiota contributes to detoxification (Jia et al., 2023; Liew and Mohd-Redzwan, 2018). Deoxynivalenol promoted Campylobacter jejuni multiplication in broilers, with aggravated permeability and translocation to liver and spleen (Ruhnau et al., 2020); conversely, YCW extract mitigated mycotoxin effects on gut health in young pigs (Kim et al., 2019) and a multi-component deactivator counteracted fumonisin- and DON-induced changes in broilers (Dasireddy et al., 2026). In each, the hazard and in two, the mitigant, is fungal, yet none measured the gut fungal community.
     
    The intervention-trial gap: quantification and characterization
     
    Applying the Methods’ operational definition, this review identified fewer than five controlled dietary or feed-processing interventions in poultry or pigs reporting fungal outcomes in gut, fecal or excreta material: The porcine carbohydrate-composition experiment (Luo et al., 2021) the inulin-versus-cellulose fiber trial (Qin et al., 2026), the fiber-by-genotype study (Wang et al., 2023), the broiler feed-additive comparison (Fonseca et al., 2025), the bacitracin methylene disalicylate mycobiome study (Robinson et al., 2020) and the direct K. slooffiae supplementation trial (Harlow et al., 2024a). Against a livestock literature of thousands of controlled feeding trials, this is a vanishingly small evidence base.
           
    The gap is sharpest where the intervention is itself fungal. Live yeast supplementation improves average daily gain and alters bacterial composition in piglets (Kiros et al., 2019; Puspani et al., 2023; Floc’h et al., 2022) and broiler gut health (Kyoung et al., 2023; Somkuna et al., 2025), yet across twenty live-yeast records, none reported gut fungal outcomes; only one, from 2006, even enumerated yeast numbers, finding no treatment differences (Li et al., 2006). The one trial that did measure it found K. slooffiae administration produced regional mycobiome shifts but no improvement in weight gain, gut health or immunity, the weaning transition influencing community development far more than supplementation (Harlow et al., 2024a), a negative result found precisely because the fungal endpoint was measured.
           
    Three further gaps follow. Causal inference is largely absent, the livestock literature being almost entirely cross-sectional, whereas rodent work has reached causal demonstration, e.g. Schizosaccharomyces pombe supplementation improved lipid and glucose metabolism in obese mice (Zhan et al., 2024). Absolute quantification is almost never reported alongside composition despite validated tools existing (Tkacz et al., 2018; Urubschurov et al., 2015), so whether treatments alter fungal load, community structure, or both remains unknown and dose-response relationships are entirely uncharacterized for fungal outcomes, an obstacle to rational formulation given that immune effects operate through threshold-dependent receptor recognition (Saijo and Iwakura, 2011).
           
    Finally, on the AGP transition motivating much of this interest: the assumption that antibiotic withdrawal releases fungi from bacterial suppression is not well founded. In mice, a four-antibiotic cocktail increased fungal abundance roughly 40-fold (Dollive et al., 2013), but amoxicillin-clavulanic acid decreased total fungal load while remodeling the population via expansion of fungus-suppressing Enterobacteriaceae (Spatz et al., 2023); the effect is antibiotic-class specific and bacterially mediated. Whether AGP removal from pig and poultry diets has increased, decreased or restructured the gut mycobiome remains unknown, despite being a global, decade-long, uncontrolled natural experiment.
     
    Limitations of this review
     
    Four limitations bear on interpretation. First, grey literature and non-English publications were not systematically sought, so the applied feed-technology literature is likely under-represented and the count of qualifying intervention trials should be read as an upper bound on absence, not a definitive census. Second, the review was not prospectively registered. Third, screening and extraction were not duplicated by independent reviewers, introducing possible selection error. Fourth, formal risk-of-bias assessment was not applied, since the dominant designs are poorly served by intervention-oriented instruments; methodological limitations are instead discussed narratively per evidence cluster, following PRISMA 2020 item 27 (Page et al., 2021a) and documented reporting deficiencies in the animal health literature (Sargeant et al., 2021; Toews, 2017). None of this affects the central finding, which concerns the near-total absence of a study category rather than an effect-size estimate.

    CONCLUSION

    The gut mycobiome of poultry and pigs is a small, measurable, dietarily responsive community whose neglect in monogastric nutrition is no longer defensible; three conclusions follow.
           
    First, poultry and pigs require separate treatment. The porcine gut supports K. slooffiae as a genuine post-weaning resident with documented trans-kingdom associations and a defined mechanism of action on host epithelial metabolism, whereas the chicken mycobiome is a transient, diet-derived assemblage without stable succession; interventions and endpoints appropriate to one species do not transfer to the other. Second, measurement remains a constraint: No marker-database combination performs universally, common ITS primers fail to amplify fungi native to the piglet gut and relative abundance cannot distinguish community-structure change from load change; until host-specific mock communities and absolute quantification become routine, disagreements between studies cannot be adjudicated biologically. Third and most consequentially, the field’s defining feature is not a contested finding but an absent category of evidence: Fewer than five controlled dietary interventions in poultry or pigs have reported gut fungal outcomes, despite live yeast being fed to millions of animals and mycotoxin binders addressing a fungal hazard, both evaluated bacterially. The remedy is neither expensive nor technically demanding: The highest-value experiment identified here, a mash-versus-pellet comparison in broilers with ITS sequencing and fungal qPCR of digesta, requires only adding two assays to a trial design already standard in poultry nutrition. Until such measurements are made, dietary modulation of the gut mycobiome will remain a plausible hypothesis, not an established practice.

    ACKNOWLEDGEMENT

    This review received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
     
    Disclaimers
     
    The views and conclusions expressed are solely those of the author and do not necessarily represent those of the affiliated institution, which accepts no liability for losses resulting from use of this content.
     
    Informed consent
     
    This is a systematic review of published literature and did not involve live animals or human participants; ethical approval was therefore not required. Primary studies cited are assumed to have obtained appropriate institutional animal ethics approval as reported by their authors.

    CONFLICT OF INTEREST

    The author declares no conflicts of interest. No funding or sponsorship influenced the study design, data collection, analysis, publication decision, or manuscript preparation.

    REFERENCES


    1. Al-Nijir, M., Chuck, C.J., Bedford, M.R and Henk, D.A. (2024). Metabolic modelling uncovers the complex interplay between fungal probiotics, poultry microbiomes and diet. Microbiome. 12(1): 267.

    2. Arfken, A., Frey, J. and Summers, K. (2020). Temporal dynamics of the gut bacteriome and mycobiome in the weanling pig. Microorganisms. 8(6): 868. 

    3. Arfken, A., Frey, J., Carrillo, N., Dike, N.I., Onyeachonamm, O., Rivera, D., Davies, C. and Summers, K. (2023). Porcine fungal mock community analyses: implications for mycobiome investigations. Frontiers in Cellular and Infection Microbiology. 13: 928353. 

    4. Arfken, A., Frey, J., Ramsay, T. and Summers, K. (2019). Yeasts of burden: exploring the mycobiome-bacteriome of the piglet GI tract. Frontiers in Microbiology. 10: 2286. 

    5. Bakker, M.G. (2018). A fungal mock community control for amplicon sequencing experiments. Molecular Ecology Resources. 18(3): 541-556. 

    6. Cohen-Kedar, S., Baram, L., Elad, H., Brazowski, E., Guzner Gur, H. and Dotan, I. (2014). Human intestinal epithelial cells respond to β glucans via Dectin 1 and Syk. European Journal of Immunology. 44(12): 3729-3740. 

    7. Cwalina, P., Obidziñski, S., Kowczyk-Sadowy, M., Sienkiewicz, A. and Mazur, J. (2025). Extrusion processing of fungal- contaminated cereals as a method for spore reduction and binder development in feed materials. Materials. 18(22): 5117. 

    8. Dasireddy, J.R., Kappari, L., Pender, C., Doupovec, B., Selvaraj, R.K., Applegate, T.J. and Shanmugasundaram, R. (2026). Effects of a mycotoxin deactivator in broilers exposed to subclinical doses of fumonisins and deoxynivalenol. Poultry Science. 105(6): 106843. 

    9. De Filippis, F., Laiola, M., Blaiotta, G. and Ercolini, D. (2017). Different amplicon targets for sequencing-based studies of fungal diversity. Applied and Environmental Microbiology. 83: e00905-e00917. 

    10. Delavy, M., Sertour, N., Patin, E., Chatelier, L.E., Cole, N., Dubois, F., Xie, Z., Saint- André, V., Manichanh, C., Walker, A.W., Quintana-Murci, L., Duffy, D., d’Enfert, C., Bougnoux, M. and Consortium, M.I. (2023). Unveiling Candida albicans intestinal carriage in healthy volunteers: the role of micro- and mycobiota, diet, host genetics and immune response. Gut Microbes. 15(2): 2287618. 

    11. Deng, X., Li, H., Wu, A., He, J., Mao, X., Dai, Z., Tian, G., Cai, J., Tang, J. and Luo, Y. (2025). Composition, influencing factors and effects on host nutrient metabolism of fungi in gastrointestinal tract of monogastric animals. Animals. 15(4): 512. 

    12. Dollive, S., Chen, Y.Y., Grunberg, S., Bittinger, K., Hoffmann, C.V., Vandivier, L.E., Cuff, C.C., Lewis, J.D., Wu, G.D. and Bushman, F. (2013). Fungi of the murine gut: Episodic variation and proliferation during antibiotic treatment. Plos One. 8(8): e71806. 

    13. Floc’h, L.N., Achard, C., Eugenio, F.A., Apper, E., Combes, S. and Quesnel, H. (2022). Effect of live yeast supplementation in sow diet during gestation and lactation on sow and piglet fecal microbiota, health and performance. Journal of Animal Science. 100(8): skac209. 

    14. Fonseca, A., Kenney, S.M., Boney, J. and Ganda, E. (2025). Mycobiome temporal and functional dynamics in broilers: Ecological perspective on bacterial-fungal correlations and the effect of feed additives. Poultry Science. 104(12): 106092. 

    15. Forcina, G., Pérez-Pardal, L., Carvalheira, J. and Beja-Pereira, A. (2022). Gut microbiome studies in livestock: achievements, challenges and perspectives. Animals. 12(23): 3375. 

    16. Ghaemmaghami, S., Nowroozi, H. and Moghadam, M.T. (2018). Toxigenic fungal contamination for assessment of poultry feeds: Mashed vs. pellet. Iranian Journal of Toxicology. 12(5): 5-10. 

    17. Ghaemmaghami, S., Rouhanipour, H. and Sharifi, S.D. (2023). Aflatoxin levels in poultry feed: A comparison of mash and pellet forms. Poultry Science. 103(1): 103254. 

    18. Guerre, P. (2016). Worldwide mycotoxins exposure in pig and poultry feed formulations. Toxins. 8(12): 350. 

    19. Harlow, K., Summers, K., Oliver, W., Wells, J.E., Crouse, M., Neville, B., Rempel, L.A., Rivera, I., Ramsay, T.G. and Davies, C.P. (2024a). Weaning transition, but not the administration of probiotic candidate Kazachstania slooffiae, shaped the gastrointestinal bacterial and fungal communities in nursery piglets. Frontiers in Veterinary Science. 10: 1303984. 

    20. Harlow, K., Summers, K., Rivera, I., Postnikova, O., Ramsay, T.G. and Davies, C.P. (2024b). PSII-21 Metabolites of Kazachstania slooffiae reduce tight junction integrity in piglet intestinal epithelial cells. Journal of Animal Science. 102(3): 698. 

    21. Hu, J., Chen, J., Hou, Q., Xu, X., Ren, J.L. and Yan, X. (2023). Core-predominant gut fungus Kazachstania slooffiae promotes intestinal epithelial glycolysis via lysine desuccinylation in pigs. Microbiome. 11(3): 31.

    22. Jawhara, S. (2022). How Gut Bacterial Dysbiosis Can Promote  Candida albicans Overgrowth during Colonic Inflammation. Microorganisms. 10(5): 1014. 

    23. Jia, B., Lin, H., Yu, S., Liu, N., Yu, D. and Wu, A. (2023). Mycotoxin deoxynivalenol-induced intestinal flora disorders, dysfunction and organ damage in broilers and pigs. Journal of Hazardous Materials. 451: 131172. 

    24. Jubair, A.F., Al-Nuaimy, A.A., Obaid, N.H. and Al-Jabry, S.M.E. (2026). Effect of mycotoxins produced by Fusarium moniliforme and Aspergillus flavus associated with wheat grains cultivated in the Al-Muthanna Desert and used as poultry feed. Agricultural Science Digest. 45(6): 1082- 1086. doi: 10.18805/ag.DF-741.

    25. Kauserud, H. (2023). ITS alchemy: on the use of ITS as a DNA marker in fungal ecology. Fungal Ecology. 65: 101274. 

    26. Kim, E.J., Kyoung, H., Koh, N.H., Lee, H., Lee, S., Kim, Y., Park, K.I., Heo, J. and Song, M. (2022). Supplementation of live yeast culture modulates intestinal health, immune responses and microbiota diversity in broiler chickens. Journal of Animal Science. 100(5): skac122. 

    27. Kim, S., Holanda, D., Gao, X., Park, I. and Yiannikouris, A. (2019). Efficacy of a yeast cell wall extract to mitigate the effect of naturally co-occurring mycotoxins contaminating feed ingredients fed to young pigs: Impact on gut health, microbiome and growth. Toxins. 11(11): 633. 

    28. Kiros, T., Luise, D., Derakhshani, H., Petri, R., Trevisi, P., D’inca, R., Auclair, E. and Van Kessel, A.V. (2019). Effect of live yeast Saccharomyces cerevisiae supplementation on the performance and cecum microbial profile of suckling piglets. Plos One. 14(7): e0219557. 

    29. Kyoung, H., Kim, E.J., Cho, J., Lee, H., Kim, Y., Park, K. I., Kim, H. and Song, M. (2023). Dietary yeast cell wall enhanced intestinal health of broiler chickens by modulating intestinal integrity, immune responses and microbiota. Poultry Science. 102(6): 102660. 

    30. Li, J., Chen, D., Yu, B., He, J., Huang, Z., Zheng, P., Mao, X., Li, H., Yu, J., Luo, J., Yan, H. and Luo, Y. (2022). Batch and sampling time exert a larger influence on the fungal community than gastrointestinal location in model animals: A meaningful case study. Frontiers in Nutrition. 9: 1021215. 

    31. Li, J., Li, D., Gong, L., Y., He, Y. and Zhai, H. (2006). Effects of live yeast on the performance, nutrient digestibility, gastrointestinal microbiota and concentration of volatile fatty acids in weanling pigs. Archives of Animal Nutrition. 60(4): 277-288. 

    32. Liew, W.P.P. and Mohd-Redzwan, S. (2018). Mycotoxin: its impact on gut health and microbiota. Frontiers in Cellular and Infection Microbiology. 8: 60.

    33. Liu, H.Y., Li, S., Ogamune, K.J., Ahmed, A.A., Kim, I., Zhang, Y. and Cai, D. (2025). Fungi in the gut microbiota: Interactions, homeostasis and host physiology. Microorganisms. 13(1): 70. https://doi.org/10.3390/microorganisms13010070.

    34. Luo, Y., Li, J., Zhou, H., Yu, B., He, J., Wu, A., Huang, Z., Zheng, P., Mao, X., Yu, J., Li, H., Wang, H., Wang, Q., Yan, H. and Chen, D. (2021). The nutritional significance of intestinal fungi: Alteration of dietary carbohydrate composition triggers colonic fungal community shifts in a pig model. Applied and Environmental Microbiology. 87: e00038- e00021. 

    35. McCrory, C., Lenardon, M. and Traven, A. (2024). Bacteria-derived short-chain fatty acids as potential regulators of fungal commensalism and pathogenesis. Trends in Microbiology. 32(11): P1106-1118. 

    36. Page, M., McKenzie, J., Bossuyt, P., Boutron, I., Hoffmann, T., Mulrow, C., Shamseer, L., Tetzlaff, J., Akl, E., Brennan, S., Chou, R., Glanville, J.M., Grimshaw, J., Hrõbjartsson, A., Lalu, M., Li, T., Loder, E., Mayo-Wilson, E., McDonald, S. and Moher, D. (2021a). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Systematic Reviews. 10. 

    37. Page, M., Moher, D., Bossuyt, P., Boutron, I., Hoffmann, T., Mulrow, C., Shamseer, L., Tetzlaff, J. et al. (2021b). PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. The BMJ. 372. 

    38. Puspani, E.C., Rawati, D.P.M.A. and Bidura, I.G.N.G. (2023). Effects of dietary yeast culture on growth performance, feed digestibility and faecal microbiota in weaned piglets. Asian Journal of Dairy and Food Research. 42(4): 490-494. doi: 10.18805/ajdfr.DRF-290.

    39. Qin, J., Li, H., Deng, X., Huang, S., He, J., Wu, A., Dai, Z., Cai, J., Tian, G., Mao, X., Yu, B., Zheng, P., Luo, J., Yan, H., Tang, J. and Luo, Y. (2026). Dietary fiber-driven shifts in mycobiota and short-chain fatty acid landscape in porcine hindgut. Animal Microbiome. 8(1): 68. doi: 10.1186/s425 23-026-00563-8.

    40. Ramayo-Caldas, Y., Prenafeta, F., Zingaretti, L., Gonzales, O., Dalmau, A., Quintanilla, R. and Ballester, M. (2020). Gut eukaryotic communities in pigs: diversity, composition and host genetics contribution. Animal Microbiome. 2(1): 18. 

    41. Ren, R., Zhang, X., Lou, F., Li, Y., L., Xiao, Y., Chen, Q., Wen, Y. and Lyu, W. (2025). Intestinal fungi biogeography, succession and its association with diarrhea in pigs. Journal of Animal Science and Biotechnology. 16: 80. 

    42. Robinson, K., Xiao, Y., Johnson, T., Chen, B., Yang, Q., Lyu, W., Wang, J., Fansler, N., Becker, S., Liu, J., Yang, H. and Zhang, G. (2020). Chicken intestinal mycobiome: Initial characterization and its response to bacitracin methylene disalicylate. Applied and Environmental Microbiology. 86: e00304-e00321.

    43. Robinson, K., Yang, Q., Stewart, S.N., Whitmore, M.A. and Zhang, G. (2022). Biogeography, succession and origin of the chicken intestinal mycobiome. Microbiome. 10(1): 55. doi: 10.1186/s40168-022-01252-9. 

    44. Ruhnau, D., Hess, C., Grenier, B., Doupovec, B., Schatzmayr, D., Hess, M. and Awad, W. (2020). The Mycotoxin Deoxynivalenol (DON) Promotes Campylobacter jejuni multiplication in the intestine of broiler chickens with consequences on bacterial translocation and gut integrity. Frontiers in Veterinary Science. 7. 

    45. Saijo, S. and Iwakura, Y. (2011). Dectin-1 and Dectin-2 in innate immunity against fungi. International Immunology. 23(8): 467-472. 

    46. Saleem, M.U., Masood, S., Zaneb, H., Durrani, A.Z., Aslam, A., Ashraf, K., Rashid, M.I., Habib-ur-Rehman, Muti-ur- Rehman, Ashraf, S., Usman, M.M. and Shaheen, M.S. (2018). Combined supplementation of organic acid blend and hydrolyzed yeast mixture increases growth performance and tibia bone strength in broilers. Indian Journal of Animal Research. 52(11): 1613-1617. doi: 10.18805/ijar.B-858.

    47. Sargeant, J., Reynolds, K., Winder, C. and O’Connor, A. (2021). Completeness of reporting of systematic reviews in the animal health literature: A meta-research study. Preventive Veterinary Medicine. 195: 105472. 

    48. Scott, C., Holman, D., Gzyl, K.E., Ibe, A. and Taheri, A. (2025). Production Systems and Age Influence Fecal Mycobiota Diversity and Composition in Swine. Microbial Ecology. 88: 104. 

    49. Shao, T.Y., Kakade, P., Witchley, J., Frazer, C., Murray, K., Ene, I.V., Haslam, D., Hagan, T., Noble, S., Bennett, R. and Way, S. (2022). Candida albicans oscillating UME6 expression during intestinal colonization primes systemic Th17 protective immunity. Cell Reports. 39(7): 110837. 

    50. Somkuna, N., Somkuna, E., Rattanasintupong, K., Triwiset, C. and Wongsuwan, N. (2025). Dietary utilization of yeast- fermented coconut milk residue on productive performance and carcass traits of broilers. Asian Journal of Dairy and Food Research. 44(5): 838-843. doi: 10.18805/ajdfr.DRF-481.

    51. Spatz, M., Da Costa, G., Ventin-Holmberg, R., Planchais, J., Michaudel, C., Wang, Y., Danne, C., Lapière, A., Michel, M., Kolho, K., Langella, P., Sokol, H. and Richard, M.L. (2023). Antibiotic treatment using amoxicillin-clavulanic acid impairs gut mycobiota development through modification of the bacterial ecosystem. Microbiome 11(1): 73. doi: 10.1186/s40168-023-01516-y.  

    52. Summers, K., Frey, J., Ramsay, T. and Arfken, A. (2019). The piglet mycobiome during the weaning transition: A pilot study. Journal of Animal Science. 97(7): 2889-2900. 

    53. Tkacz, A., Hortala, M. and Poole, P. (2018). Absolute quantitation of microbiota abundance in environmental samples. Microbiome. 6(1): 110. 

    54. Toews, L. (2017). Compliance of systematic reviews in veterinary journals with preferred reporting items for systematic reviews and meta-analysis (PRISMA) literature search reporting guidelines. Journal of the Medical Library Association. 105: 233-239. 

    55. Urubschurov, V., Büsing, K., Janczyk, P., Souffrant, W. and Zeyner, A. (2015). Development and evaluation of qPCR assay for quantitation of Kazachstania slooffiae and total yeasts occurring in the porcine gut. Current Microbiology. 71(3): 373-381. 

    56. Urubschurov, V., Büsing, K., Souffrant, W., Schauer, N. and Zeyner, A. (2018). Porcine intestinal yeast species, Kazachstania slooffiae, a new potential protein source with favourable amino acid composition for animals. Journal of Animal Physiology and Animal Nutrition. 102(2): e892-e901. 

    57. Urubschurov, V., Janczyk, P., Souffrant, W., Freyer, G. and Zeyner, A. (2011). Establishment of intestinal microbiota with focus on yeasts of unweaned and weaned piglets kept under different farm conditions. FEMS Microbiology Ecology. 77(3): 493-502. 

    58. Usyk, M., Peters, B., Karthikeyan, S., McDonald, D., Sollecito, C., Vázquez-Baeza, Y., Shaffer, J.P., Gellman, M., Talavera, G., Daviglus, M., Thyagarajan, B., Knight, R., Qi, Q., Kaplan, R. and Burk, R. (2023). Comprehensive evaluation of shotgun metagenomics, amplicon sequencing and harmonization of these platforms for epidemiological studies. Cell Reports Methods. 3(1): 100391. 

    59. van Uden, N. and do Carmo-Sousa, L. (1962). Quantitative aspects of the intestinal yeast flora of swine. Microbiology. 27(1): 35-40. 

    60. Wang, T., Liu, J., Luo, Y., Yu, B., Kong, X., Zheng, P., Huang, Z., Mao, X., Yu, J., Luo, J., Yan, H. and He, J. (2023). Combined effects of host genetics and diet on porcine intestinal fungi and their pathogenic genes. Frontiers in Microbiology. 14: 1192288. 

    61. Wei, G.C., Liu, M., Huang, L. and Chen, C. (2026). Metagenomic sequencing reveals the dynamic changes of pig gut fungal composition following the ages and identifies fungal species associated with diarrhea in piglets. Animal Microbiome 8(1): 60. 

    62. Xie, Z., Canalda-Baltrons, A., d’Enfert, C. and Manichanh, C. (2023). Shotgun metagenomics reveals interkingdom association between intestinal bacteria and fungi involving competition for nutrients. Microbiome. 11(1): 275. doi: 10.1186/s40 168-023-01693-w. 

    63. Zhan, H., Wan, Y., Sun, Y., Xu, Z., Zhang, F., Yang, K., Zhu, W., Cheung, C., Tang, W., Ng, E.K. et al. (2024). Gut mycobiome alterations in obesity in geographically different regions. Gut Microbes. 16(1): 2367297.
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