ArticlemSystems2025
Response of the gut microbiome and metabolome to dietary fiber in healthy dogs.
Article in mSystems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Fecal Microbiota Transplantation in Dogs and Cats: Evidence for Gastrointestinal and Emerging Extra-Intestinal Applications.Animals : an open access journal from MDPI · 2026Review
- Effects of a single-cell protein source fromFrontiers in veterinary science · 2026Article
- Linking shelter conditions to health: A multisystem analysis of stress, metabolism, and fecal microbiota in dogs.PloS one · 2026Article
- Diet-induced metabolic and faecal microbiome responses in pet dogs fed a minimally processed versus extruded kibble diet.Frontiers in veterinary science · 2026Article
- Dietary Modulation of the Gut Microbiota in Dogs and Cats and Its Role in Disease Management.Microorganisms · 2025Review
- Fiber, microbiomes, and SCFAs: insights from companion animal models to inform personalized nutrition.mSystems · 2025Article
- Impact of an abrupt change from dry to canned diet on digestive function and gut microbiota in dogs.Journal of animal science · 2025Article
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6 authors.
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Abstract
Dietary fiber confers multiple health benefits originating from the expansion of beneficial gut microbial activity. However, very few studies have established the metabolic consequences of interactions among specific fibers, microbiome composition, and function in either human or representative animal models. In a study design reflective of realistic population dietary variation, fecal metagenomic and metabolomic profiles were analyzed from healthy dogs fed 12 test foods containing different fiber sources and quantities (5-13% as-fed basis). Taxa and functions were identified whose abundances were associated either with overall fiber intake or with specific fiber compositions. Fourteen microbial species were significantly enriched in response to ≥1 specific fiber source; enrichment of fiber-derived metabolites was more pronounced in response to these fiber sources. Positively associated fecal metabolites, including short-chain fatty acids, acylglycerols, fiber bound sugars, and polyphenols, co-occurred with microbes enriched in specific food groups. Critically, the specific metabolite pools responsive to differential fiber intake were dependent on differences both in individual microbial community membership and in overall ecological configuration. This helps to explain, for the first time, differences in microbiome-diet associations observed in companion animal epidemiology. Thus, our study corroborates findings in human cohorts and reinforces the role of personalized microbiomes even in seemingly phenotypically homogeneous subjects. IMPORTANCE: Consumption of dietary fiber changes the composition of the gut microbiome and, to a larger extent, the associated metabolites. Production of health-relevant metabolites such as short-chain fatty acids from fiber depends both on the consumption of a specific fiber and on the enrichment of beneficial metabolite-producing species in response to it. Even in a seemingly homogeneous population, the benefit received from fiber consumption is personalized and emphasizes specific fiber-microbe-host interactions. These observations are relevant for both population-wide and personalized nutrition applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.