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Analysis of Interactions between Endobiotics and Human Gut Microbiota Using In Vitro Bath Fermentation Systems

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An Ecological Framework for Interpreting the Canine Gut Microbiome.

Bernard Walther¹, Fabrice Bouilloux², Philippe Vayer¹

¹AREGTeC, 12 Rue des Ormeaux, 45150 Darvoy, France.

Animals : an Open Access Journal From MDPI

|June 26, 2026

Summary

This study introduces a new framework for analyzing dog gut health using fecal calprotectin and 16S rRNA gene sequencing. The approach integrates inflammation, dysbiosis, and resilience for better canine microbiome interpretation.

Keywords:

16S rRNA canine microbiome dysbiosis fecal calprotectin gut ecology microbiological inflammatory score microbiome resilience

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Compost Microcosms as Microbially Diverse, Natural-like Environments for Microbiome Research in Caenorhabditis elegans

Compost Microcosms as Microbially Diverse, Natural-like Environments for Microbiome Research in Caenorhabditis elegans

Published on: September 13, 2022

Area of Science:

Veterinary Medicine
Microbiome Research
Canine Health

Background:

The canine intestinal microbiome is crucial for gastrointestinal health, but its interpretation is challenging.
Current methods often rely on limited ecological targets or costly shotgun metagenomics.
A need exists for accessible, integrative approaches to analyze canine microbiome data.

Purpose of the Study:

To develop an integrative interpretation framework for canine gut microbiome analysis.
To combine fecal calprotectin and 16S rRNA gene sequencing for a multidimensional assessment.
To evaluate biological inflammation, microbiological inflammatory pressure (MIS), and microbiome resilience (MRS) in dogs.

Main Methods:

Integrated fecal calprotectin and 16S rRNA gene sequencing data from privately owned dogs.
Calculated Microbiological Inflammatory Score (MIS) and Microbiome Resilience Score (MRS).
Employed alpha diversity, beta diversity, taxonomic weighting, and distance to a reference microbiome core.

Main Results:

Strong correlations were found between microbiome resilience, microbial diversity, and dysbiosis metrics.
Microbiome resilience correlated highly with Shannon diversity (ρ = 0.98, p < 0.001).
A continuum from stable to inflammatory dysbiosis was observed, with distinct clusters of canine microbiomes.

Conclusions:

A multidimensional framework integrating inflammation, dysbiosis, and resilience improves canine microbiome interpretation.
The framework provides complementary ecological dimensions for a comprehensive understanding of gut health.
This approach offers valuable insights for routine veterinary diagnostics and research.