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Record W4414830769 · doi:10.1093/jas/skaf300.695

PSXII-25 Effects of Aspergillus oryzae-derived prebiotics on ruminal fermentation and the microbiome in an artificial rumen system (Rusitec).

2025· article· en· W4414830769 on OpenAlexaff
Yuxi Wang, F. Bargo, Ignacio R. Ipharraguerre, Chunli Li, Trevor W. Alexander, Tim A. McAllister

Bibliographic record

VenueJournal of Animal Science · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsRumenFermentationAspergillus oryzaeMicrobiomeDry matterNeutral Detergent FiberBacteriaAnimal feed

Abstract

fetched live from OpenAlex

Abstract Prebiotics that stimulate beneficial microbes have had varying success in improving animal health and enhancing production efficiency. Aspergillus oryzae prebiotics (AOP) are produced from a multi-step fermentation process of a selected strain that have been shown to have beneficial effects on rumen fermentation. However, their effect on the rumen microbiome has not been fully evaluated using up-to-date molecular techniques. The objectives of this study were to assess the effects AOP on rumen fermentation and on bacterial and fungal communities in hope of generating insight into the mechanisms whereby AOP modulates rumen metabolism. The experiment was conducted using an artificial rumen (Rusitec) for 19 d in a completely randomized experiment. Three treatments consisting of the basal diet as Control (C), basal diet supplemented with AOP at 6 mg (AOPl) or 10 mg/fermenter (AOPh) per day were assessed with 4 replicate fermenters per treatment. Total gas production, methane, ammonia, volatile fatty acids (VFA) and microbial protein production were measured. Specific rumen bacteria and methanogens were analyzed using real-time PCR and bacterial (16SrRNA) and fungal (ITS) microbiomes were determined using Illumina MiSeq sequencing technology. Fermentation data were subjected to analysis of variance using the MIXED procedure of SAS with treatment as the main effect, and differences (P < 0.05) among treatments were tested using the LSMEANS procedure of SAS with the PDIFF option. Supplementation of AOP at 6 and 10 mg/fermenter per day linearly increased total gas production (P=0.005), dry matter disappearance (P=0.023), neutral detergent fiber disappearance (P< 0.001), total VFA (P=0.009) and total microbial protein production (P=0.044) with most differences being observed between C and AOPh. However, starch disappearance, methane production and ratio of acetate and propionate were not affected by either AOPl or AOPh. PCR analysis revealed that AOP linearly increased total daily output of 16S rRNA gene copies of total cellulolytic bacteria (sum of Fibrobacter succinogenes, Ruminococcus albus and Ruminococcus flavefaciens; P=0.049) associated with feed particles, with this response being greatest for F. succinogenes (P=0.027). However, treatment had no effect on daily total outputs of the mcrA gene associated with methanogens or on 16S rRNA gene copies of Ruminobacter amylophilus and Selenomonas ruminantium. Microbiome analysis revealed that AOP did not affect diversity and abundances of either bacterial or fungi at the phylum level. However, AOP altered the composition of bacterial and fungal community at the genera level, with and noteworthy increase (P< 0.05) in cellulolytic bacterial and fungal microbiota. These results demonstrated that addition of AOP to an artificial rumen improved fermentation efficiency via positively altering the bacterial and fungal microbiomes involved in fiber digestion.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.252
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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