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Frontiers in Animal Science ·

Volume 7 - 2026 | https://doi.org/10.3389/fanim.2026.1920907

Effects of Aspergillus oryzae prebiotic on ruminal fermentation and prokaryotic and fungal microbiotas

  • Y. Wang1*corresponding author
  • F. Bargo2
  • I. Ipharraguerre3
  • T. W. Alexander1
  • M. Waldner1
  • T. A. McAllister1
  1. 1Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, Lethbridge, AB, Canada
  2. 2Biozyme Inc., St. Joseph, MO, United States
  3. 3Institute of Human Nutrition and Food Science, Division of Food Science, Faculty of Agricultural and Nutritional Sciences, University of Kiel, Kiel, Germany
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Abstract

Aspergillus oryzae prebiotics (AOP) have been shown to modulate rumen fermentation. However, their effect on the rumen microbiome has not been fully evaluated using up-to-date molecular techniques. An experiment using an artificial rumen system (Rusitec) was conducted to assess the effects of newly developed AOP on rumen fermentation and prokaryotic and fungal microbiotas. The experiment was conducted for 19 d with a completely randomized design of three treatments and four replications per treatment. Treatments were Control basal diet only, basal diet supplemented with AOP at 6 mg (low dose; AOPl) or 10 mg/fermenter (high dose; AOPh) per day. Total gas, methane, ammonia, volatile fatty acids and microbial protein production were measured. Specific rumen bacteria and methanogens were analyzed using real-time PCR. Prokaryotic and fungal microbiotas were determined by sequencing regions of the 16S rRNA and ITS genes, respectively. Supplementation of AOP at 6 and 10 mg/fermenter per day linearly increased total gas production (P < 0.01), dry matter disappearance (P < 0.05), neutral detergent fiber disappearance (P < 0.001), total volatile fatty acids (P < 0.01) and total microbial protein production (P < 0.05) with the most significant differences being observed between C and AOPh. However, starch disappearance, methane production and ratio of acetate: propionate were not affected by either AOPl or AOPh. PCR analysis revealed that AOP linearly increased (P < 0.05) the daily output of 16S rRNA gene copies of total cellulolytic bacteria (sum of Fibrobacter succinogenes, Ruminococcus albus and Ruminococcus flavefaciens), and especially for F. succinogenes associated with feed particles, when analyzed separately. Microbiota analysis revealed that AOP did not affect diversity and abundances of either prokaryotes or fungi at the phylum level. However, AOP increased (P < 0.05) the abundance of cellulolytic bacterial and fungal genera. The addition of AOP to the rumen improved fermentation efficiency via positively altering the bacterial and fungal microbiota associated with fiber digestion.

Keywords

Introduction

The rumen microbiota is a complex consortium of bacteria, protozoa, fungi, and archaea, that directly influence feed efficiency, methane emissions, and overall animal productivity. In-feed antibiotics and feed additives are widely used to modulate rumen microbial fermentation. However, global concerns over antimicrobial resistance has driven the search for natural and sustainable feed alternatives. Among these, direct-fed microbials and prebiotics have shown potential. Prebiotics are selectively fermented ingredients that promote specific changes in the composition and/or activity of gastrointestinal microbiota, conferring benefits to host health and performance (Gibson et al., 2017). However, inconsistent results of prebiotics in improving animal health and enhancing production efficiency have been reported, depending on their source and feed management (Cangiano et al., 2020; Ravanal et al., 2025).

Aspergillus oryzae fermentation products (AOP) are produced using a multi-step fermentation process of selected fungal strains that contains specific, indigestible carbohydrates (like complex fungal cell-wall polysaccharides) and enzymes that act as prebiotics when fed to animals (Uwineza et al., 2024). Feeding ruminants with AOP have been shown inconsistent results in improving rumen fermentation and animal performance (e.g. Caton et al., 1993; Nocek and Jensen, 2011; Sallam et al., 2020; Uwineza et al., 2024). Although some AOP have been shown to increase cellulolytic activities in the rumen and thereby enhance ruminal fiber digestion, their impacts on microbial ecology have not been fully evaluated. Anaerobic rumen fungi represent a minor microbial biomass niche but are disproportionately essential for plant cell wall degradation. They physically penetrate plant cuticles using rhizoids and secrete highly potent polysaccharidases, initiating the breakdown of recalcitrant lignocellulosic matrices (Gruninger et al., 2014). However, there is lack of information about the effects of AOP on rumen anaerobic funal microbiota. Zhang et al. (2022) showed that addition of Aspergillus oryzae fermentation extract to the diet of dairy cows (5 g/head/d) increased milk yield but did not affect rumen volatile fatty acids (VFA) and microbial protein production or the composition of rumen bacterial communities. In contrast, Wang et al. (2025) reported that a complex mixed prebiotic containing A. oryzae and Trichoderma longibrachiatum added to the diet of beef heifers 3.0 g/kg improved protein and fiber digestion through a positive impact on rumen bacterial microbiota. A comprehensive understanding of the dose-dependent effects of AOP on the rumen fermentation profiles and the concomitant shifts in the bacterial, archaeal and fungal communities remains incomplete.

The objective of this study was to determine the effects of a newly developed AOP feed additive on rumen fermentation and on bacterial and fungal microbiotas so as to provide insight into the microbial mechanisms by which AOP modulates rumen fermentation. It was hypothesized that supplementation of AOP would improve rumen fermentation in a dose-dependent manner via inducing a targeted enrichment of fibrolytic microbial taxa.

Materials and methods

Treatments and experimental design

A completely randomized experiment with three treatments; 1) Control (C) basal diet only, 2) basal diet supplemented with AOP at 6 mg (low dose; AOPl) or 3) 10 mg/fermenter (high dose; AOPh) per day was conducted in an artificial rumen (Rusitec) with four replicate vessels per treatment. The basal diet was a typical total mixed ration (TMR) containing (%; DM basis) 43 corn silage, 9 alfalfa hay, 27 corn grain, 16 canola meal, and 5 mineral-vitamin supplement. The diet was dried at 50°C for 48 h, ground to pass a 2-mm screen and then weighed (5 g/bag) into polyether bags (pore size = 50 μm; Ankom Technol. Corp., Macedon, NY). The AOP used in this study was a highly concentrated, commercially available product (AO-Biotics® AO-Ferm HC) that is a dried A. oryzae fermentation product obtained by submerged cultivation of a selected, non-GMO A. oryzae strain under controlled fermentation conditions. Following fermentation, the fungal biomass and associated fermentation-derived constituents are recovered as part of the fermentation matrix and dried onto silicon dioxide to produce a stable, free-flowing powder. The ingredient therefore consists of dried A. oryzae fermentation material, including fungal biomass-derived components and extracellular fermentation metabolites, with silicon dioxide used as a carrier/drying aid. On as fed basis, the product contained 28-38% of dried A. oryzae biomass (without viable fungal cells) and 56-66% of silicon dioxide. The approximate chemical composition of the product was crude protein 3.0% (minimum), crude fat 0.2% (minimum), acid detergent fiber 3.0% (maximum) and neutral detergent fiber 4.0% (maximum). The daily amount of feed additive was weighed onto a piece of Waterman filter paper of known weight and placed into the respective treatment feed bag prior to being placed into the Rusitec. A piece of the same size of filter paper without any feed additive was also placed into the Control feed bags.

Experiment procedure and measurements

The experiment was conducted using rumen simulation technique (Rusitec) units (Czerkawski and Breckenridge, 1977) for 19 d, with the first nine d as an adaptation period, followed by a 10-d sample collection period. Inoculum was prepared from rumen fluid and solid digesta collected from three cannulated beef heifers fed the same TMR as that fed to the Rusitec, 2-h after animal feeding. The cattle were fed for two weeks prior to collection of rumen contents. Cattle were fed twice daily, had free access to water and were cared for in accordance with the standards of the Canadian Council on Animal Care (Canadian Council on Animal Care, 2009). Rumen solid and liquid contents were collected via the rumen cannula from five locations within the rumen, strained through four layers of cheese cloth, combined in equal portions from the three cattle and transported to the lab in separate thermos containers. The animal care and rumen content collection protocol was approved by Lethbridge Research and Development Center animal care committee (ACC #2124, 2022). At the start of the experiment, 700 mL of rumen fluid, 200 mL of mineral buffer (McDougall, 1948), 10 g of solid digesta and 10 g of substrate in separate bags were placed in each fermenter under a stream of O2-free CO2. The fermenters were then immediately placed in the Rusitec and continuously infused with buffer (McDougall, 1948) at a dilution rate of 2.9%/h. After 24 h, the solid rumen digesta bag was replaced with a new feed bag. Thereafter, the 48-h feed bags were replaced daily, such that two feed bags were present at any time in each fermenter, with a total incubation time of 48 h for each bag. Mineral buffer was prepared daily during the experiment.

Volume of effluent and gas accumulation were determined daily during feed bag exchange throughout the entire experimental period. A wet-type gas flow meter (Alexander Wright, London, UK) was used to quantify total gas production in the collection bags. On d 10–15, subsamples of gas (20 mL) were taken from the bags and transferred to evacuated exetainers for CH4 analysis. On the same day, subsamples of fermentation liquid were taken, preserved with trichloroacetic acid (650 g/L) or ortho/metaphosphoric acid (250 g/L) and stored at −20 °C for ammonia N (NH3-N) or VFA analysis, respectively. Fermenter pH was also measured (Orion260A, Fisher Scientific, Toronto, ON, Canada) daily at the time of feed bag exchange. Feed bags removed from each fermenter after 48 h from d 10 to d 15 were washed under a stream of cold tap water until the water was clear. Bags was then dried at 55 °C for 48 h for analyses of DM, starch and neutral detergent fiber (NDF) and used to estimate the disappearance of each of these components.

The mineral buffer was modified on d 10 after effluent and solid sampling for determination of background 15N by replacing (NH4)2SO4 with 15N-enriched (15 NH4)2SO4 (Sigma Chemical Co., St Louis, MO, USA; minimum 15N enrichment 10.01atom %) for the remaining experiment. Effluent (150 mL) was collected from each vessel from d 16 to 19. The effluent sample was processed by differential centrifugation to obtain liquid associated (Li) microbial protein. Feed particle- associated (FPA) and feed particle-bound (FPB) microbial protein were isolated from feed particles incubated for 48 h in bags from d 16 to 19 and from bags incubated for 24 h on d 19 as described by Wang et al. (2001). The pooled samples of effluent, FPA and FPB were stored at -20 °C until analyzed. Subsamples of Li and FPA were also taken at the same time and processed as described below to quantify the bacterial species; Fibrobacter succinogenes, Prevotella bryantii, Ruminobacter amylophilus, Ruminococcus albus, Ruminococcus flavefaciens and Selenomonas ruminantium as well as total methanogens using real-time polymerase chain reaction (qPCR). Prokaryotic and fungal microbiotas were also characterized using sequencing and bioinformatics analysis as described below.

Sample processing and analysis

Chemical analyses

Substrate and fermentation residues were analyzed for DM (method 930.15; AOAC, 2005), starch (Herrera-Saldana et al., 1990) and NDF (Van Soest et al., 1991) with the addition of amylase and sodium sulfite. Ammonia-nitrogen was determined colorimetrically as described by Broderick and Kang (1980). Analyses of VFA and CH4 followed the procedure described by Nair et al. (2021).

Quantification of microbial protein synthesis

The Li, FPA and FPB fractions were freeze-dried, ball-ground and analyzed for total N and 15N using a mass spectrometer (NA 1500, Carlo Erba Instruments, Rodano, Italy) as described by Wang et al. (2001).

DNA extraction and real-time quantitative polymerase chain reaction

Microbial samples collected for Li and FPA fraction were extracted for DNA using the Qiagen QIAamp DNA stool mini kit, following the manufacturer’s protocols with minor modifications (Qiagen, Hilden, Germany). This included bead beating using a bead-beating homogenizer for 5 min at maximum amplitude to dissociate microbes. The DNA concentration was quantified using a spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and the quality of the DNA was assessed via electrophoresis on a 2% agarose gel (w/v). The DNA samples were stored at –40 °C until analyzed for qPCR targets and microbial characterization (see below).

The primers sequences used for qPCR quantification of the specific bacteria (16S rRNA) and methanogens (mcrA) are presented in Table 1. Real-time qPCR amplification was performed on a Bio-Rad CFX 96 Connect Real-Time PCR Detection System (Bio-Rad Laboratories Inc., Hercules, CA, USA), and data were analyzed using Bio-Rad CFX Manager software (version 3.0). Standard curves were generated using 10-fold serial dilutions of DNA plasmid standards containing the target gene sequences of the respective microbial groups. Negative controls (H2O) were included in the analyses. The PCR cycling conditions were an initial denaturation step at 95 °C for 3 min, followed by 40 cycles of denaturation at 95 °C for 25 s, annealing at 57 °C for 30 s, and extension at 72 °C for 45 s. The copy number of marker genes of the bacteria and methanogens were expressed as log10 copies.

Table 1. Primer used to quantify specific bacteria and total methanogens.

Target sequenceSequence (5’ to 3’)References
Total methanogensF-CCGGAGATGGAACCTGAGACZhou et al., 2009
R-CGGTCTTGCCCAGCTCTTATTC
Ruminococcus flavefaciensF-TCTGGAAACGGATGGTAKoike and Kobayashi, 2001
R-CCTTTAAGACAGGAGTTTACAA
Ruminococcus albusF-CCCTAAAAAGCAGTCTTAGTTCGKoike and Kobayashi, 2001
R-CCTCCTTGCGGTTAGAACA
Prevotella bryantiiF-ACTGCAGCGCGAACTGTCAGATajima et al., 2001
R-ACCTTACGGTGGCAGTGTCTC
Fibrobacter succinogenesF-GGTATGGGATGAGCTTGCTajima et al., 2001
R-GCCTGCCCCTGAACTATC
Selenomonas ruminantiumF-TGCTAATACCGAATGTTGTajima et al., 2001
R-TCCTGCACTCAAGAAAGA
Ruminobacter amylophilusF-CAACCAGTCGCATTCAGATajima et al., 2001
R-CACTACTCATGGCAACAT

Microbiota characterization

Purified DNA samples were analyzed by Molecular Research (MRDNA) (Shallowater, TX, US) using Illumina MiSeq (San Francisco, CA, USA) sequencing technology. Libraries of 16S rRNA gene sequences were generated using a two-step PCR protocol. The V4 region of the 16S rRNA gene was amplified using the universal bacterial and archaeal primers 515-F (GTGYCAGCMGCCGCGGTAA) and 806-R (GGACTACNVGGGTWTCTAAT) in the first step of PCR (Walters et al., 2016). A unique 10-bp barcode and Illumina (Illumina, San Diego, CA, USA) adapter sequences were added at the 5’ end of each amplicon in the second PCR step. The 515-F and 806-R primers amplify prokaryotic DNA, including both bacterial and archaeal sequences. Primers for amplification of fungal rRNA genes were ITS1 (TCCGTAGGTGAACCTGCGG) and ITS2 (GCTGCGTTCTTCATCGATGC) (White et al., 1990).

The quality of the raw reads was initially validated with FastQC 0.11.9 and MultiQC 1.12 (Ewels et al., 2016). Subsequent sequence trimming was performed with Trimmomatic 0.39 (Bolger et al., 2014) to remove low quality regions and reads with settings HEADCROP:10, SLIDINGWINDOW:5:20, LEADING:20, and TRAILING:20. Subsequent statistical analysis was performed in R 4.1.0 (R Core Team, 2018). Trimmed paired reads were filtered with DADA2 1.22.0 (Callahan et al., 2016) with default settings and merged. Bimeric sequences were removed from merged sequences with DADA2 removeBimeraDenovo. Taxonomic classification of the 16S and ITS sequences were performed with DADA2 IdTaxa using the SILVA 138 database (Quast et al., 2012), or UNITE 9.0 database (Nilsson et al., 2019) respectively, to construct an amplicon sequence variant (ASV) table. Phyloseq 1.38.0 (McMurdie and Holmes, 2013), vegan 2.5-7 (Oksanen et al., 2019), and DESeq2 1.34.0 (Love et al., 2014) were used for further statistical analysis and plots were visualized with ggplot2 3.3.5 (Wickham, 2011). Alpha diversity of the dataset was assessed via the Shannon diversity index and richness index (observed ASV) using vegan. The ASV table was filtered for ASV present (count ≥ 2) in at least 1% of the samples to reduce noise in downstream analysis. A one-way ANOVA was used to evaluate alpha diversity with respect to treatment. Microbial community structure was analyzed with vegan 2.6-4 (Oksanen et al., 2019) using β-dispersion and permutational multivariate analysis of variance (PERMANOVA) with 9999 permutations to determine the effect of each treatment. Beta diversities were calculated by normalizing the filtered ASV counts with size factors calculated with GMPR in DESeq2. Sample-sample distances were determined with the Bray-Curtis metric using phyloseq ordinate and visualized with detrended correspondence analysis (DCA). The phyla and genus with the highest abundance in each treatment were identified with phyloseq. Significant (P < 0.05) differentially abundant genera were identified with DESeq2 by fitting a negative binomial model to each treatment against the Control treatment with Benjamini-Hochberg adjustment. Sequences have been submitted to NCBI under PRJNA1482215.

Calculations and data analysis

Disappearance of DM (DMD), starch and NDF (NDFD) from feed bags were determined gravimetrically. Daily microbial N (MN) output was calculated by summarizing those in the effluent (Li), FPA and FPB fractions, which were estimated using 15N enrichment with the procedure described by Wang et al. (2001).

Digestion, fermentation products and microbial protein production data were subjected to analysis of variance using the MIXED procedure of SAS (SAS Institute Inc, 2012) with treatment as the main effect. The same fermentation parameter obtained at different dates were averaged as a single value for each fermenter and therefore individual fermenter was considered as random factor. Orthogonal polynomial contrasts were used to determine linear and quadratic responses to the levels of AOP supplementation. Differences among treatments were tested using the LSMEANS procedure of SAS with the PDIFF option. Significant differences and trends were declared at P < 0.05 and 0.10 > P > 0.05, respectively.

Results

Ruminal fermentation characteristics

Overall, increasing dosages of AOP from to 0 to 10 mg/d linearly increased GP (P < 0.01), DMD (P < 0.05), NDFD (P < 0.001) and concentrations of total VFA (P < 0.01), acetate (P < 0.01), butyrate (P < 0.01), iso-butyrate (P < 0.01) and iso-valerate (P < 0.01) (Table 2). However, significant increases (P < 0.05) of these parameters were mainly observed between C and AOPh, with the exception of NDFD and iso-valerate concentration which also increased (P < 0.05) with AOPl. Furthermore, fermenters supplemented with AOPh had a higher DMD (P < 0.05), NDFD (P < 0.001), iso-butyrate concentration (P < 0.05) and ammonia-N concentration (P < 0.01), and tended to have higher gas production (P = 0.09) than AOPl. No difference was observed among treatments with regard to starch digestion, methane production, propionate concentration or the acetate:propionate ratio.

Table 2. Effects of Aspergillus oryzae prebiotic (AOP) on nutrient digestion, volatile fatty acids VFA), ammonia, total gas and methane production.

ItemCAOPlAOPhSEMC vs. AOPAOP(L)AOP(Q)
pH6.776.766.750.0120.2350.1720.866
GP; mL/d1581b1732ab1985a132.80.0220.0050.480
DMD; %79.5b79.5b80.8a0.320.1150.0230.083
NDFD; %56.8c58.1b59.9a0.34<0.001<0.0010.227
Starch; %98.698.498.50.100.1580.4200.090
CH4; mL/d13013915617.80.4270.3260.746
CH4; %7.787.848.090.2850.6110.4850.731
Concentrations of VFA (mmol)
Total VFA76.8b79.7ab81.9a1.390.0200.0090.900
Acetate (A)42.1b44.3ab45.6a0.870.0100.0060.896
Propionate (P)20.720.921.50.510.4210.2730.613
Butyrate8.7b9.2ab9.6a0.270.0210.0080.765
Iso-butyrate0.61b0.63b0.68a0.0170.0210.0030.246
Valerate2.432.532.610.2300.4770.4090.922
Iso-valerate1.42b1.60a1.56a0.039<0.0010.0030.026
Caproic0.530.510.570.0340.8420.4010.141
A/P2.052.122.130.0390.0930.1150.492
NH3 (mmol)9.28b9.22b9.84a0.2400.2380.0370.059

C, Control (no additive); AOPl, Aspergillus oryzae prebiotic added at 6 mg/fermenter; AOPh, Aspergillus oryzae prebiotic added at 10 mg/fermenter; DMD, dry matter disappearance; NDFD, neutral detergent fibre disappearance; GP, gas production; SEM, standard error of mean; L, linear; Q, quadratic.

Values with different letter within a row differed significantly (P < 0.05).

Microbial N production and microbial populations

Supplementation of AOP up to 10 mg/d linearly increased (P < 0.05) daily MN production (Li+FPA+FPB) through a tendency to increase FPA (L, P = 0.061) and FPB (Q, P = 0.084) bacterial fractions, although it did not affect the Li fraction (Table 3).

Table 3. Effects of Aspergillus oryzae prebiotic (AOP) on microbial N production (mg/day) and microbial 15N enrichment in the residual feed particles.

ItemCAOPlAOPhSEMC vs. AOPAOP(L)AOP(Q)
Liquid (Li)52.051.657.21.910.3320.1120.169
FPA (A)10.912.512.70.620.0530.0610.514
FPB (B)16.519.316.51.160.3530.8280.084
Li+A+B79.4b82.6ab86.4a2.090.0750.0440.728
15N µg/g feed particle
(A+B)_24 h87.0145.5147.525.500.0890.1100.498
(A+B)_48 h172.5b182.5b200.3a6.550.0430.0170.432

C, Control (no additive); AOPl, Aspergillus oryzae prebiotic added at 6 mg/fermenter; AOPh, Aspergillus oryzae prebiotic added at 10 mg/fermenter; SEM, standard error of mean; L, linear; Q, quadratic; FPA, feed particle associated fraction; FPB, feed particle bound fraction; (A+B)_24 h, feed particle related microbial 15N with 24 h-incubated feed particles; (A+B)_48 h: feed particle related microbial 15N with 48 h-incubated feed particles.

Values with different letter within a row differed significantly (P < 0.05).

Compared with C, AOPh tended to have higher daily MN yield for FPA (P = 0.082) and Li fractions (P = 0.076) and increased total MN daily yield (P < 0.05). Similarly, AOPl tended (P = 0.060) to have a higher daily MN yield than C in the FPB fraction. Microbial 15N enrichment was linearly increased (P < 0.05) in 48-h, but not 24-h incubated feed particle related fractions (FPA+FPB), with it being higher for AOPh than for C (P < 0.01) and AOPl (P < 0.05).

In general, treatment did not affect daily outputs of 16S rRNA gene copies of the six bacterial species measured in this experiment (Table 4). Exceptions were that AOP linearly increased 16S rRNA copies of F. succinogenes in the FPA fraction but decreased it for P. bryantii in Li (P < 0.05) and FPA (P < 0.05) fractions. Treatment had no effect on daily liquid or particle associated fractions of the mcrA gene associated with methanogens.

Table 4. Effects of Aspergillus oryzae prebiotic (AOP) on daily output of 16S rRNA gene copies (log 10 transformed) of cellulolytic bacteria (Fibrobacter succinogenes, Ruminococcus flavefaciens and Ruminococcus albus), non-cellulolytic bacteria (Prevotella bryantii, Ruminobacter amylophilus and Selenomonas ruminantium) and mcrA gene copies of methanogen in fermentation liquid (Li) and feed particle associated (FPA) fractions.

BacteriaFractionsCAOPlAOPhSEMC vs. AOPAOP(L)AOP(Q)
F. succinogenesLi7.387.427.640.1350.3930.2280.482
FPA5.33b5.64ab5.83a0.1380.0390.0270.977
Li+FPA7.397.427.650.1340.3810.2190.482
R. flavefaciensLi5.905.976.010.1300.5950.5690.982
FPA5.045.225.060.0820.3460.7120.139
Li+FPA5.966.076.060.1040.4130.4730.676
R. albusLi6.837.007.030.1650.3770.3880.811
FPA5.225.335.140.0920.9070.6340.184
Li+FPA6.847.017.040.1620.3720.3870.796
Sum of cellulolytic bacteriaLi7.507.577.760.1330.3450.2160.595
FPA5.695.955.990.0960.1160.0490.539
Li+FPA7.517.587.770.1300.3250.2060.608
P. bryantiiLi8.87a7.81b8.63a0.1050.0010.0390.001
FPA5.63ab5.99a5.55b0.1330.3890.9270.034
Li+FPA8.87a7.82b8.64a0.1030.0010.0360.001
S. ruminantiumLi7.107.287.050.2850.8650.9470.566
FPA5.725.895.180.2450.5590.2030.134
Li+FPA7.147.317.060.2760.9020.8870.529
R. amylophilusLi5.385.495.400.1040.6270.8350.461
FPA5.355.265.270.1980.7250.7480.885
Li+FPA5.685.725.710.1160.8100.8320.908
MethanogensLi6.636.466.700.1210.7390.8130.187
FPA6.646.476.710.1200.7490.8060.191
Li+FPA6.946.777.010.1210.7430.8120.189

C, Control (no additive); AOPl, Aspergillus oryzae prebiotic added at 6 mg/fermenter; AOPh, Aspergillus oryzae prebiotic added at 10 mg/fermenter; SEM, standard error of mean; L, linear; Q, quadratic.

*: sum of three cellulolytic bacteria.

Values with different letter within a row differed significantly (P < 0.05).

Prokaryotic microbiota

The observed ASV or Shannon Index (SI) for both Li (Figure 1A) and FPA (Figure 1B) samples were not affected (P > 0.05) by treatment. Similarly, PERMANOVA indicated that treatment did not affect prokaryotic structure (P > 0.05), and this was supported by DCA plots showing a lack of clustering according to treatment for both Li (Figure 2A) and FPA (Figure 2B) microbiotas.

Box plots of the observed amplicon sequence variant (ASV) and Shannon diversity for liquid-associated **(A)** and feed particle-associated **(B)** prokaryotes by treatment. Treatments were: C, Control diet, AOPl, *Aspergillus oryzae* prebiotic added at 6 mg/fermenter, AOPh, *Aspergillus oryzae* prebiotic added at 10 mg/fermenter. Error bars indicate ± standard error of the mean. The box in the plots indicates the interquartile range (IQR) (middle 50% of the data), the middle line represents the median value, and the whiskers represents 1.5 times the IQR.
Figure 1. Box plots of the observed amplicon sequence variant (ASV) and Shannon diversity for liquid-associated (A) and feed particle-associated (B) prokaryotes by treatment. Treatments were: C, Control diet, AOPl, Aspergillus oryzae prebiotic added at 6 mg/fermenter, AOPh, Aspergillus oryzae prebiotic added at 10 mg/fermenter. Error bars indicate ± standard error of the mean. The box in the plots indicates the interquartile range (IQR) (middle 50% of the data), the middle line represents the median value, and the whiskers represents 1.5 times the IQR.
Detrended correspondence analysis (DCA) plots of the Bray-Curtis dissimilarities for liquid-associated **(A)** and feed particle-associated **(B)** bacteria samples by treatment. Treatments were: C, Control diet, AOPl, *Aspergillus oryzae* prebiotic added at 6 mg/fermenter, AOPh, *Aspergillus oryzae* prebiotic added at 10 mg/fermenter.
Figure 2. Detrended correspondence analysis (DCA) plots of the Bray-Curtis dissimilarities for liquid-associated (A) and feed particle-associated (B) bacteria samples by treatment. Treatments were: C, Control diet, AOPl, Aspergillus oryzae prebiotic added at 6 mg/fermenter, AOPh, Aspergillus oryzae prebiotic added at 10 mg/fermenter.

A total of 21 and 20 phyla were identified from Li and FPA samples respectively. Both sample types contained 17 bacterial phyla, and one eukaryotic phyla, but differed in the number of archaeal phyla detected. Liquid fraction samples contained three archaeal phyla, and two archaeal phyla were present in FPA samples. There were distinct differences between Li and FPA samples in abundances of the top phyla that made up more than 1% of the total dataset (Figure 3). For Li fraction samples (Figure 3A), the most abundant phyla included Proteobacteria (46.4%), Bacteroidota (23.8%), Firmicutes (18.7%), Verrucomicrobiota (2.5%), Actinobacteriota (2.0%), and Spirochaetota (2.0%), which accounted for 95% of the total sequence reads. In contrast, the top phyla in FPA samples (Figure 3B) were Bacteroidota (40.1%), Proteobacteria (26.3%), Firmicutes (25.6%), and Verrucomicrobiota (1.0%), which accounted for 93% of the sequences. In both fractions for each treatment, phyla within archaea and eukaryota represented less than 1% of reads. Liquid fraction samples contained archaeal phyla Euryarchaeota (0.37%), Halobacteria (0.05%), and Thermoplasmatota (0.06%), and eukaryotic Parabasalia (0.02%). FPA fraction samples only contained archaeal genera Euryarchaeota (0.39%), and Thermoplasmatota (0.003%), and the eukaryotic genera Parabasalia (0.02%). Nevertheless, no difference was observed between phyla abundances of the C and AOPl or AOPh, for both Li and FPA samples.

Effects of treatments on the relative abundance of ruminal prokaryotic phyla for liquid-associated **(A)** and feed particle-associated **(B)** samples. Treatments were: Control diet, AOPl, *Aspergillus oryzae* prebiotic added at 6 mg/fermenter, AOPh, *Aspergillus oryzae* prebiotic added at 10 mg/fermenter.
Figure 3. Effects of treatments on the relative abundance of ruminal prokaryotic phyla for liquid-associated (A) and feed particle-associated (B) samples. Treatments were: Control diet, AOPl, Aspergillus oryzae prebiotic added at 6 mg/fermenter, AOPh, Aspergillus oryzae prebiotic added at 10 mg/fermenter.

A total of 127 genera (121 bacterial, four archaeal, and two eukaryotic) and 118 genera (115 bacterial, two archaeal, and one eukaryotic) were detected in Li and FPA fraction samples, respectively. The top nine genera were all within the domain bacteria (Figure 4). Their relative abundances in Li samples (Figure 4A) were Succinivibrio (42.7%), Rikenellaceae RC9 gut group (9.4%), Prevotella (5.3%), Megasphaera (3.4%), Lactobacillus (2.8%), Ruminobacter (2.1%), Treponema (2.0%), Bifidobacterium (1.5% and Succinivibrionaceae UCG-002 (1.4%). In contrast, the top 9 genera and their relative abundances in FPA samples (Figure 4B) were Succinivibrio (25.2%), Rikenellaceae RC9 gut group (21.5%), Prevotella (5.4%), Succiniclasticum (3.3%), Saccharofermentans (2.5%), Butyrivibrio (2.0%), Veillonellaceae UCG-001 (1.5%), Papillibacter (1.5%) and Christensenellaceae R-7 group (1.3%). While present in low abundance, Li fraction samples contained four archaeal genera: Methobrevibacter (0.4%), Candidatus Methanomethylophilus (0.07%), Methanomicrobium (0.05%), and Methanosphaera (0.0008%); and two eukaryotic genera: Trichomitius (0.009%) and Tetratrichomonas (0.009%). Similarly, FPA fraction samples contained two archaeal genera: Methobrevibacter (0.4%), and Candidatus Methanomethylophilus (0.003%) and a single eukaryotic genus: Tetratrichomonas (0.002%).

Effects of treatments on relative abundance of the nine most abundant genera in liquid-associated **(A)** and feed particle-associated **(B)** samples. Treatments were: Control diet, AOPl, *Aspergillus oryzae* prebiotic added at 6 mg/fermenter, or AOPh, at 10 mg/fermenter.
Figure 4. Effects of treatments on relative abundance of the nine most abundant genera in liquid-associated (A) and feed particle-associated (B) samples. Treatments were: Control diet, AOPl, Aspergillus oryzae prebiotic added at 6 mg/fermenter, or AOPh, at 10 mg/fermenter.

Differences in genera between prebiotic treatments and the Control for both Li and FPA samples are shown in Figure 5. For Li samples (Figure 5A), the relative abundances of total 71 genera differed (P < 0.05) between C and AOP treatments. Specifically, the relative abundances of 62 and 55 genera in AOPl and AOPh either increased or decreased (P < 0.05) compared to C. For FPA samples (Figure 5B), there were 72 genera that differed (increased or decreased; P < 0.05) between Control and AOP treatment, which included 60 and 58 genera in AOPl and AOPh respectively. Methanobrevibacter was the only genus with archaea that showed a treatment effect, and it was increased in AOPl compared to control FPA samples.

Relative changes (log2 fold change; P < 0.05) of ruminal prokaryotes by treatment *vs*. Control at the genus level for liquid-associated **(A)** and feed particle-associated **(B)** samples. Treatments were: Control diet, AOPl, *Aspergillus oryzae* added at 6 mg/fermenter, AOPh, *Aspergillus oryzae* added at 10 mg/fermenter.
Figure 5. Relative changes (log2 fold change; P < 0.05) of ruminal prokaryotes by treatment vs. Control at the genus level for liquid-associated (A) and feed particle-associated (B) samples. Treatments were: Control diet, AOPl, Aspergillus oryzae added at 6 mg/fermenter, AOPh, Aspergillus oryzae added at 10 mg/fermenter.

Fungal microbiota

Within Li (Figure 6A) or FPA (Figure 6B) fractions, diversity metrics (Richness, SI) were not affected by treatment for fungi. PERMANOVA indicated that fungal populations were not affected (P > 0.05) by treatment (compared to C), for both Li (Figure 7A) and FPA (Figure 7B) samples. This was supported by a lack of clustering in the DCA plots.

Box plots of the amplicon sequence variant (ASV) and Shannon diversity for liquid-associated **(A)** and feed particle-associated **(B)** fungal in samples by treatment. Treatments were: C, Control diet, AOPl, *Aspergillus oryzae* added at 6 mg/fermenter, or AOPh, at 10 mg/fermenter. Error bars indicate ± standard error of the mean. The box in the plots indicates the interquartile range (IQR) (middle 50% of the data), the middle line represents the median value, and the whiskers represents 1.5 times the IQR.
Figure 6. Box plots of the amplicon sequence variant (ASV) and Shannon diversity for liquid-associated (A) and feed particle-associated (B) fungal in samples by treatment. Treatments were: C, Control diet, AOPl, Aspergillus oryzae added at 6 mg/fermenter, or AOPh, at 10 mg/fermenter. Error bars indicate ± standard error of the mean. The box in the plots indicates the interquartile range (IQR) (middle 50% of the data), the middle line represents the median value, and the whiskers represents 1.5 times the IQR.
Detrended correspondence analysis (DCA) plots of the Bray-Curtis dissimilarities for liquid-associated **(A)** and feed particle-associated **(B)** fungus samples by treatment. Treatments were: C, Control diet, AOPl, *Aspergillus oryzae* added at 6 mg/fermenter, or AOPh, at 10 mg/fermenter.
Figure 7. Detrended correspondence analysis (DCA) plots of the Bray-Curtis dissimilarities for liquid-associated (A) and feed particle-associated (B) fungus samples by treatment. Treatments were: C, Control diet, AOPl, Aspergillus oryzae added at 6 mg/fermenter, or AOPh, at 10 mg/fermenter.

A total of six phyla were observed in Li fraction samples, with Neocallimastigomycota (99.4%) predominating. Other phyla included Basidiomycota (0.3%), Fungi_phy_Incertae_sedis (0.1%), Ascomycota (0.1%), Chytridiomycota (0.04%), Mortierellomycota (0.01%) and the remaining were unclassified < 0.01%. Similarly a total of five phyla were identified in FPA samples, which included Neocallimastigomycota (99.4%), Basidiomycota (0.3%), Fungi_phy_Incertae_sedis (0.2%), Ascomycota (0.04%), and Chytridiomycota (0.01%). Treatment had no effect on the relative abundances of fungal phyla in either Li or FPA samples.

There were 36 and 18 fungal genera observed in Li and FPA samples, respectively. The nine most abundant genera in liquid (Figure 8A) samples were Caecomyces (77.2%), Neocallimastix (15.2%), Pecoramyces (5.7%), Piromyces (1.4%), Wallemia (0.2%), Fungi_gen_Incertae_sedis (0.1%), Filobasidium (0.1%), Aspergillus 0.04%), and Hymenochaetales_gen_Incertae_sedis (0.01%), whilst that in FPA samples (Figure 8B) were Caecomyces (74.6%), Neocallimastix (19.6%), Piromyces (3.2%), Pecoramyces (2.0%), Filobasidium (0.3%), Fungi_gen_Incertae_sedis (0.2%), Wallemia (0.03%), Penicillium (0.02%) and Cladosporium (0.01%).

Relative abundance of the nine most abundant fungal genera in the liquid-associated **(A)** and feed particle-associated **(B)** samples. Treatments were: C, Control diet, AOPl, *Aspergillus oryzae* added at 6 mg/fermenter, or AOPh, at 10 mg/fermenter.
Figure 8. Relative abundance of the nine most abundant fungal genera in the liquid-associated (A) and feed particle-associated (B) samples. Treatments were: C, Control diet, AOPl, Aspergillus oryzae added at 6 mg/fermenter, or AOPh, at 10 mg/fermenter.

Compared to the C group, relative abundances of 24 fungal genera were significantly affected (P < 0.05) by treatment (increased or decreased) for Li samples, with 13 and 20 genera being altered for AOPl and AOPh, respectively (Figure 9A). In most cases, these genera were increased for prebiotic treatments, compared to the C. In contrast, relative abundances of only 12 fungal genera were altered (P < 0.05) by treatment (increased or decreased) for FPA samples, with 10 and 11 genera being different for AOPl and AOPh, respectively (Figure 9B).

Relative changes (log2 fold change; P < 0.05) of ruminal fungus genera by treatment *vs*. Control in liquid-associated **(A)** and feed particle-associated **(B)** samples. Treatments were: Control diet, AOPl, *Aspergillus oryzae* added at 6 mg/fermenter, or AOPh, at 10 mg/fermenter.
Figure 9. Relative changes (log2 fold change; P < 0.05) of ruminal fungus genera by treatment vs. Control in liquid-associated (A) and feed particle-associated (B) samples. Treatments were: Control diet, AOPl, Aspergillus oryzae added at 6 mg/fermenter, or AOPh, at 10 mg/fermenter.

Discussions

Effects of AOP on rumen fermentation

The prebiotic evaluated in this study was produced from a select A. oryzae strain that has been shown to enhance nutrient digestion through increasing rumen microbial activity, especially cellulolytic activity (Wiedmeier et al., 1987; Frumholtz et al., 1989; Caton et al., 1993; Varel et al., 1993; Chang et al., 1999; Nocek, 2011). The greater DMD, NDFD, gas production, total VFA production and MN yield observed for AOP than for C indicated that the prebiotic improved DM and fiber digestion and increased energy and microbial protein production under the present Rusitec conditions. The linear increase in these fermentation parameters as the AOP dosage increased to 10 mg/fermenter demonstrated that positive responses were dose-dependent.

The greater VFA production for AOPh was associated with the production of more acetate and butyrate than the Control. This is consistent with the enhanced NDF digestion as rumen microbial digestion of fiber mainly produces acetic and butyric acids (Church, 1993). The increased NDF digestion and subsequent acetate and butyrate production were likely due to AOP favorably altering the rumen microbiota, as discussed below. It needs to be noted that methane production from ruminal fermentation usually increases with increasing fiber digestion, owning to increased cellulolytic activity (Tapio et al., 2017). However, in this study methane production was not affected even though NDF digestion was increased. This suggests that AOP may have promoted the digestion of plant cell walls without leading to a corresponding increase in methane emissions, a response that requires further investigation. Terranova et al. (2024) has shown that more efficient digestion of fiber can lead to proportionately lower methane production under certain conditions. Methane formation is governed by ruminal hydrogen partitioning. Enhanced fermentation may increase hydrogen production, but a greater proportion of reducing equivalents can be redirected toward alternative sinks such as propionate production, microbial biomass synthesis, and other reductive pathways rather than methanogenesis (Greening et al., 2019). Therefore, improvements in fiber digestion do not necessarily translate into increased methane output. Hence, the absence of a methane response despite enhanced fiber digestion observed in this study may reflect improved fermentation efficiency and altered microbial hydrogen utilization with increased microbial production rather than increased methanogenic activity.

The greater ammonia-N concentration in the fermentation fluid for AOPh than for Control may indicate increased ruminal protein degradation as others have also found that AOP increased protein digestion (Gomez-Alarcon et al., 1991). Compared to the Control, the greater concentrations of iso-butyrate and iso-valerate with AOPh, which are derived from deamination of amino acids, is consistent with the increased ammonia-N concentration.

The higher microbial 15N concentration in feed particles for AOPh suggests that it promoted microbial attachment to feed particles. Enhanced microbial attachment to feed particles can result in more efficient fiber digestion (Wang and McAllister, 2002). It is well known that ruminal fiber digestion is more related to feed particle associated/attached microbes as compared to those that are in the liquid fraction. This is also consistent with the qPCR results that showed supplementation of AOP increased feed particle associated 16S rRNA gene copies of F. succinogenes, which is a major ruminal cellulolytic bacterium. These results were consistent with the observation that AOP increased NDFD in this study.

Effects of AOP on ruminal prokaryotic microbiota

It is commonly acknowledged that rumen fermentation depends on ruminal microbial diversity and community composition. Rumen microbiota include bacteria, archaea, fungi and protozoa (Silva et al., 2024). The 16S rRNA primers used for sequencing amplified regions of both bacteria and archaea, so both domains were analyzed. Effects of AOP on prokaryotic and fungal communities were assessed for both Li and FPA samples. In all samples, phyla within archaea represented only a small fraction of total 16S rRNA reads, and bacterial sequences were dominant. In contrast, although a similar number of bacterial phyla were detected for Li and FPA samples, the relative abundances of these phyla differed. For example, relative abundances of Firmicutes, Bacteroidota and Proteobacteria were 18.7, 23.8 and 46.4% in Li samples whilst these were 26.3, 41.5 and 23.6% in FPA samples. This indicated that prokaryotic activity in Li and FPA differ in their digestive functions.

The results showed that AOP did not affect either prokaryotic diversity or composition in Li and FPA samples. However, the prebiotic indeed altered the compositions of some prokaryotic genera, especially bacteria relating to fiber digestion. Thus, the prebiotic did not impact the general microbial community, but rather induced changes of specific taxa. Similar findings have been reported when the effect of animal sex (Lu et al., 2025) or forage (Dwan et al., 2026) on rumen microbiota were compared. In our study, the relative abundance of Fibrobacter in FPA samples was significantly increased by AOP. Fibrobacter contains cellulolytic bacteria that play an important role in plant cell wall digestion. This was consistent with the qPCR results which found that 16S rRNA copies of F. succinogenes were selectively increased by AOP. Increased growth rates of fibrolytic bacteria with AOP has been reported by other researchers (Frumholtz et al., 1989; Varel et al., 1993; Beharka and Nagaraja, 1993; 1998). In FPA samples, the relative abundances of other bacterial genera associated with carbohydrate digestion including Ruminococcus, Monoglobus, Eubacterium hallii group, Eubacterium hallii, Prevotellaceae UCG-003, were also increased by AOP. Most of these genera are members of Firmicutes and are recognized for their role in energy metabolism. Increased relative abundances of these bacteria by AOP likely in part accounted for the enhanced fiber digestion observed in the current study. Interestingly, Methanobrevibacter was the only archeal genus shown to be affected, and was increased in FPA samples of the AOPl treatment. While difficult to explain, no increases in total methanogens by qPCR or methane from fermentation indicated that the change in Methanobrevibacter was not enough to alter methanogenesis parameters.

Eubacterium hallii is a major butyrate producer that has the ability to utilize glucose and the fermentation intermediates, acetate and lactate (Duncan et al., 2004; Louis et al., 2014). Eubacterium ventriosum can also produce short-chain fatty acids (Zhao et al., 2023). It has previously been observed that the abundances of Ruminococcus, Pseudoramibacter, Prevotella, Selenomonas and Syntrophococcus were positively correlated with acetate, propionate, butyrate, valerate, and total VFA production (Zhao et al., 2023). All these bacteria were up-regulated by AOP in either Li, FPA or both fractions, which would partially explain the increased total acetate, butyrate or total VFA productions observed with the prebiotic additive. In addition Prevotella plays a key role in the metabolism of carbohydrates and proteins (Deusch et al., 2017; Kim et al., 2017). Thus, the increased relative abundance of Prevotellaceae UCG-003 in FPA samples likely contributed to the increased ammonia concentration associated with AOP. Overall, the observed changes in bacterial taxa generally supported the differences in digestion and fermentation resulting from AOP supplementation in this study.

Effective compounds in A. oryzae fermentation products have been identified as fungal cell-wall polysaccharides (e.g. β-glucans, mannans and mannan-oligosaccharides, galactomannans, mannoproteins, etc), fermentation metabolites (e.g. organic acids, amino acids, peptides, vitamins, antioxidant metabolites, etc) and extracellular enzymes (e.g. cellulases, xlanases, amylases, proteases, β-mannanases, etc) and they have been shown to act as microbiota-modulating compounds that selectively stimulate beneficial rumen microorganisms and improve rumen fermentation (Jana et al., 2022; Kadooka et al., 2023; Uwineza et al., 2024; Xie et al., 2025). The findings of this study were consistent with results.

Effects of AOP on ruminal fungal microbiota

Rumen anaerobic fungi account for about 8%–10% of the rumen microbial biomass, readily attach to fiber, and play a pivotal role in the degradation of plant cell walls (Dagar et al., 2015). This study showed that regardless of treatment, Neocallimastigomycota was the dominant phylum, accounting for 99% of the relative abundance in both Li and FPA samples. This result is consistent with observations that Neocallimastigomycota is the most abundant fungi in rumen samples (Gruninger et al., 2014; Langda et al., 2020).

Neocallimastix, Caecomyces, Pecoramyces and Piromyces were the most abundant fungal genera in all samples, with Caecomyces being predominant. The significant increase of Caecomyces abundance in AOP relative to C for both Li and FPA suggests that this additive stimulated the growth of this genera. Caecomyces readily colonizes plant cell walls and initiates feed degradation through the production of an array of carbohydrate active enzymes (Gerbi et al., 1996; Brown et al., 2021). The increase in this genera as a result of the addition of AOP likely contributed to the enhanced fiber digestion observed in this study.

Piromyces is also a member of the Neocallimastigomycota, and plays a key role in the herbivore digestive tract with its capacity to digest plant cell walls and convert cellulose to glucose and other simple sugars (Dijkerman et al., 1996). Wang et al. (2019) inoculated corn silage with Piromyces sp. CN6 CGMCC 14449 and observed improved silage quality and nutrient composition and increased fiber digestibility. The increased abundance of Piromyces by AOP in FPA samples was noticeable although its abundance was reduced in Li samples. The discrepancy of the effects of AOP between Li and FPA samples with regard to Piromyces might be due to AOP promoting attachment of Piromyces onto feed particles, which partially contributed to the increased NDFD by AOP observed in this study.

Conclusion

A. oryzae prebiotic had positive effects on rumen fermentation in terms of enhancing DM and NDF digestion, while increasing VFA and microbial protein production. The effects of AOP on ruminal fermentation were dose-dependent, with the most obvious results observed when AOP was added at 10 mg/fermenter. The positive effects of AOP on rumen fermentation was due to alteration of the composition of ruminal microbiotas, including selectively increased cellulolytic bacteria taxa and fungi, especially feed particle associated populations. Further research is needed to evaluate the efficacy of this feed additive on animal performance.

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Correction note

A correction has been made to this article. Details can be found at: 10.3389/fanim.2026.2003293.

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Footnotes

Edited by: Etna Aida Peña-Ramos, Centro de Investigacion en Alimentacion y Desarrollo AC, Mexico

Reviewed by: Zhiqiang Cheng, Yangzhou University, China

Randi Mulianda, Universitas Tjut Nyak Dhien, Indonesia

Statements

Conflict of interest

Author FB was employed by the company BioZyme Inc., and author II received consulting fee from the company BioZyme Inc.

The remaining author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The authors YW and II declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This research was funded by BioZyme Inc. grant numbers J-002850 and Agriculture and Agri-Food Canada, Lethbridge Research and Development Center. The funder, BioZyme Inc., had no involvement in the the study design, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.

Data availability

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/supplementary material.

Ethics approval

The animal study was approved by Lethbridge Research and Development Centre Animal Care Committee. The study was conducted in accordance with the local legislation and institutional requirements.

Author contributions

YW: Writing – original draft, Funding acquisition, Project administration, Validation, Methodology, Conceptualization, Supervision, Writing – review & editing, Investigation. FB: Methodology, Validation, Conceptualization, Funding acquisition, Writing – review & editing. II: Methodology, Conceptualization, Writing – review & editing. TA: Methodology, Data curation, Writing – review & editing, Formal Analysis. MW: Writing – review & editing, Methodology, Formal Analysis, Data curation, Visualization. TM: Methodology, Validation, Conceptualization, Resources, Writing – review & editing.

Acknowledgements

The authors thank Z. Xu, W. Smart, and H-E. Yang for their technical support on this project.

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Citation

Wang, Y., et al. (2026). Effects of Aspergillus oryzae prebiotic on ruminal fermentation and prokaryotic and fungal microbiotas. Frontiers in Animal Science, Volume 7. https://doi.org/
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7 - 2026

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Copyright © 2026 Fernando Bargo, Ignacio Ipharragurre and His Majesty the King in Right of Canada, as represented by the Minister of Agriculture and Agri-Food for the contribution of Yuxi Wang, Trevor Alexander, Matthew Waldner, and Tim A. McAllister.

License: https://creativecommons.org/licenses/by/4.0/

*Correspondence: Y. Wang

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