Western diet-based NutriCol medium: A high-pectin, low-inulin culture medium promoted gut microbiota stability and diversity in PolyFermS and M-ARCOL continuous in vitro models
Notice bibliographique
Résumé
Optimizing fermentation media to accurately reflect the colonic environment remains a challenge in developing in vitro models that simulate the human colon. This study aimed to develop a fermentation medium, Nutritive Colonic (NutriCol), which mimics colonic chyme with fiber content reflective of a typical Western diet and compared to the widely used MacFarlane medium. MacFarlane/NutriCol media contained the following fiber (g/L): potato starch (5/0.1), pectin (2/5.6), xylan (2/4.4), arabinogalactan (2/1.8), guar gum (1/0.4), glucomannan (0/0.8), and inulin (1/0.2). The performance of NutriCol was evaluated using two in vitro models: PolyFermS, which simulates the human proximal colon, and M-ARCOL, which mimics both the lumen and mucosa of the human colon. In the PolyFermS model, findings revealed that NutriCol maintained microbiota α-diversity closer to the donor fecal samples and significantly higher than MacFarlane (Shannon's p ≤ 0.01; Simpson's p ≤ 0.001). In contrast, no significant differences in α-diversity were observed between NutriCol and MacFarlane in the M-ARCOL model, likely due to differences in model design and donor microbiome composition. Microbial community structure, assessed by Bray-Curtis distance and A Permutational multivariate analysis of variance (PERMANOVA), revealed significant variations between the two media in both models (PolyFermS: p = 0.02; M-ARCOL: p = 0.01). Additionally, NutriCol demonstrated a higher capacity to cultivate gut microbes, with increased ASV numbers compared to MacFarlane across PolyFermS and M-ARCOL. SCFAs production was influenced by media composition, individual microbiome structure, and the colonic model used. In the M-ARCOL, NutriCol significantly increased acetate ( p = 0.0006) and butyrate ( p = 0.02) levels compared to MacFarlane. While a similar trend was observed with the PolyFermS, the differences were not statistically significant ( p > 0.05). This increase is attributed to the enrichment of SCFA-producing bacteria, such as Butyricicoccus , Lachnospira , Oscillospiraceae UCG-003, Clostridium butyricum , and Lachnospiraceae NK4A136-group. Additionally, NutriCol generated lower levels of intestinal gases (H 2 , O 2 , CO 2 , and CH 4 ) than MacFarlane in the M-ARCOL model. In conclusion, our study demonstrates that NutriCol, a growth medium specifically designed to replicate the typical fiber content of a Western diet, supports gut microbiota diversity and structure better than the established MacFarlane medium. NutriCol's impact was model- and donor-dependent, enhancing microbiota diversity in PolyFermS, while promoting SCFA production and reducing gas levels in M-ARCOL. • The nutritive medium is a key parameter of in vitro gut models. • Nutritive Colonic (NutriCol) medium aims to better mimic fiber content of a Western diet. • NutriCol efficiency was evaluated in two colonic models compared to MacFarlane. • A higher bacterial diversity was retained with NutriCol compared to MacFarlane. • Short-chain fatty acids levels increased with NutriCol due to enrichment in producing bacteria.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».