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Enregistrement W6958497358 · doi:10.6084/m9.figshare.28518590

Additional file 1 of Ruminal-buccal microbiota transmission and their diagnostic roles in subacute rumen acidosis in dairy goats

2025· article· en· W6958497358 sur OpenAlexaff

Notice bibliographique

RevueFigshare · 2025
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueRuminant Nutrition and Digestive Physiology
Établissements canadiensUniversity of AlbertaUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésRumenSignificant differenceGeneDairy cattleTransmission (telecommunications)Buccal administration

Résumé

récupéré en direct d'OpenAlex

Additional file 1: Fig. S1 Analysis of gene expression in the rumen epithelium. (A) Venn diagram of the identified genes in the CON, LRDSS and HRDSS groups. (B) The numbers of differentially expressed genes (DEGs) in CON vs. LRDSS and LRDST vs. LRDSS. Red and blue indicate upregulated and downregulated genes, respectively. Fig. S2 Ruminal differential genera identified in the comparison among groups of dairy goats varying between SARA susceptibility. (A) The number of ASVs in each rumen samples. (B) The number of filtered sequences in each rumen samples. (C and D) Comparison of ruminal microbial alpha diversity with the Chao1 index (C) and PD index (D) among the CON, LRDSS, LRDST, HRDSS, and HRDST groups. (E) Differential genera selected from the comparison between the LRDST group and the LRDSS group. (F) Differential genera selected from the comparison between the HRDST group and the HRDSS group. * indicates that the difference is significant at P < 0.05, ** indicates that the difference is significant at P < 0.01, *** indicates that the difference is significant at P < 0.001. Fig. S3 The numbers of ASVs and sequences in buccal cavity and tooth. (A-B) The number of ASVs (A) and filtered sequences (B) in each buccal sample. (C and D) The number of ASVs (C) and filtered sequences (D) in each tooth sample. Fig. S4 Buccal differential genera identified in the comparison among groups of dairy goats varying in SARA susceptibility. (A) Differential genera selected from the comparison between the LRDST group and the LRDSS group. (B) Differential genera selected from the comparison between the HRDST group and the HRDSS group. * indicates that the difference is significant at P < 0.05, ** indicates that the difference is significant at P < 0.01, *** indicates that the difference is significant at P< 0.001. (C) The 15 most predictive buccal genera to classify samples of the S group versus the H group were selected by random forest classification analysis. (D) The accuracy of distinguishing the S group from the H group based on buccal Prevotellaceae_UCG-003. Fig. S5 Comparison of tooth microbiota of dairy goats exhibiting SARA occurrence (SARA susceptible) or healthy (control and SARA tolerance) status. (A) The differential genera identified when the comparison between the CON group and SARA (LRDSS and HRDSS) groups was performed. (The genera that gradually increased along the CON, LRDSS and HRDSS groups are highlighted in brown, and the genera that gradually decreased along the CON group, LRDSS group and HRDSS group are highlighted in purple). (B) Differential genera selected from the comparison between the LRDST group and the LRDSS group. (C) Differential genera selected from the comparison between the HRDST group and the HRDSS group. * indicates that the difference is significant with FDR < 0.05, ** indicates that the difference is significant with FDR < 0.01, *** indicates that the difference is significant with FDR < 0.001. (D) Spearman correlation between the common genus-level differences in the bacteria in dairy goats from the CON group and SARA (LRDSS and HRDSS) groups and their rumen fermentation parameters. (E) The accuracy of distinguishing SARA dairy goats from healthy dairy goats based on tooth Bacteroides and Romboutsia. The figures presented from left to right were based on the comparison groups of the CON vs. LRDSS, CON vs. HRDSS, and health vs. SARA. Fig. S6 The identification of the association between oral microbiota and rumen microbiota and the connection between rumen microbiota and genes that affected the occurrence of epithelial inflammation. (A) The correlation among buccal Prevotellaceae_UCG-003, ruminal differential genera and the genes that were differentially expressed in ruminal epithelium based on Spearman's rank correlation coefficient analysis (correlation coefficient > 0.6 and P < 0.05). (B) The affiliation relationship between identified rumen epithelial immune-related differentially expressed genes and their involved GO enrichment terms, the genes showed in this graph were all significantly associated with the identified differential ruminal bacteria. Fig. S7 Comparison of ruminal and oral microbiota. (A) Chao1 index of ruminal and oral (buccal mucosa and tooth) microbiota. * indicates that the difference is significant at P < 0.05, ** indicates that the difference is significant at P < 0.01, *** indicates that the difference is significant at P < 0.001. (B) Principal coordinate analysis (PCoA) of ruminal and oral (buccal mucosa and tooth) microbiota. (C) Average relative abundance of microbiota at the genus level of ruminal and oral (buccal mucosa and tooth) microbiota; those bacteria whose relative abundance was less than 1% were classified as others. (D) Two different microbial types were identified based on the genera of ruminal and oral (buccal mucosa and tooth) sample types. (E) The microbial type distribution was compared between ruminal, buccal and tooth sample types. (F) Average relative abundance of microbiota at the genus level of the two different microbial types; those bacteria whose relative abundance was less than 1% were classified as others. Fig. S8 The oral and ruminal microbiota diversity comparison between the Healthy-R and SARA-R groups. (A-B) The oral Chao1 index (A) and beta diversity (B) were compared between goats from the Healthy-R and SARA-R groups. (C-D) The ruminal Chao1 index (C) and beta diversity (D) were compared between goats from the Healthy-R and SARA-R groups. The Mann-Whitney U test was employed to test microbial alpha diversity differences between the two groups. ANOSIM analysis based on Bray-Curtis distance matrices was used to identify beta diversity differences. Table S1. The ingredients and nutrient composition of the three diets on a dry matter (DM) basis. Table S2. Comparison of rumen LPS and lactate concentrations among the CON, LRDST, LRDSS, HRDST and HRDSS groups. Table S3. Identification of key genera based on calculated degree centrality, closeness centrality, and betweenness centrality.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,019
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,847
Score d'incertitude au seuil0,219

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,019
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0020,003
Études des sciences et des technologies0,0010,000
Communication savante0,0020,002
Science ouverte0,0020,001
Intégrité de la recherche0,0020,001
Charge utile insuffisante (le modèle a refusé de juger)0,8470,109

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,012
Tête enseignante GPT0,206
Écart entre enseignants0,194 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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