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Record W3193622874 · doi:10.3389/fmicb.2021.718884

Mucosal Microbiota and Metabolome in the Ileum of Hu Sheep Offered a Low-Grain, Pelleted or Non-pelleted High-Grain Diet

2021· article· en· W3193622874 on OpenAlexaff
Ruiyang Zhang, Zhiqiang Zhong, Huiting Ma, Limei Lin, Fei Xie, Shengyong Mao, David M. Irwin, Zhe Wang, Shuyi Zhang

Bibliographic record

VenueFrontiers in Microbiology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsUniversity of Toronto
FundersShenyang Agricultural UniversityChina Postdoctoral Science FoundationDepartment of Education of Liaoning ProvinceNational Natural Science Foundation of China
KeywordsBiologyIleumMetabolomeAkkermansiaFecesEubacteriumMicrobiomeGut floraAnimal scienceIntestinal mucosaMetabolomicsFood scienceInternal medicineMicrobiologyLactobacillusFermentationBacteriaEndocrinologyBiochemistryMedicine

Abstract

fetched live from OpenAlex

Alterations in mucosal microbiota and metabolites are critical to intestinal homeostasis and host health. This study used a combination of 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC/MS) to investigate mucosal microbiota and their metabolic profiles in the ileum of Hu sheep fed different diets. Here, we randomly allocated 15 Hu sheep to three diets, a non-pelleted low-grain diet (control diet; CON), a non-pelleted high-grain diet (HG), and a pelleted high-grain diet (HP). After 60 days of treatment, ileal mucosal samples were collected for microbiome and metabolome analysis. The results of principal coordinate analysis and permutation multivariate analysis showed that there was a tendency for microbial differentiation between the CON and HG groups (P < 0.1), although no significant difference between the HG and HP groups was observed (P > 0.05). Compared with the CON diet, the HG diet decreased (P < 0.05) the abundance of some probiotic species (e.g., Sphingomonas and Candidatus Arthromitus) and increased (P < 0.05) the abundance of acid-producing microbiota (e.g., Succiniclasticum, Nesterenkonia, and Alloprevotella) in the ileal mucosa. Compared with the HG diet, the HP diet decreased (P < 0.05) the abundance of Alloprevotella and increased (P < 0.05) the abundance of Mycoplasma in the ileal mucosa. Furthermore, partial least squares discriminant analysis and orthogonal partial least-squared discriminant analysis indicated that different dietary treatments resulted in different metabolic patterns in the ileal mucosa of the CON, HG, and HP groups. The HG diet altered (VIP > 1 and P < 0.05) the metabolic patterns of amino acids, fatty acids, and nucleotides/nucleosides (such as increased amounts of ornithine, tyrosine, cis-9-palmitoleic acid, and adenosine) compared with the CON diet. However, 10 differential metabolites (VIP > 1 and P < 0.05; including tyrosine, ornithine, and cis-9-palmitoleic acid) identified in the HG group exhibited a diametrically opposite trend in the HP group, suggesting that the HP diet could partially eliminate the changes brought upon by the HG diet. Collectively, our findings demonstrate that different diets altered the ileal mucosal microbiota and metabolites and provide new insight into the effects of high-grain diets on the intestinal health of ruminant animals.

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)0.0000.000

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 head0.005
GPT teacher head0.224
Teacher spread0.218 · 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

Citations13
Published2021
Admission routes1
Has abstractyes

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