ArticleFrontiers in microbiology2025
Comparison of metagenomic analysis of fecal and gastrointestinal tract samples for identifying beneficial gut microorganisms.
Article in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Characterization of dysbiosis patterns in gut microbiota of digestive system cancers: an umbrella review.Frontiers in microbiology · 2026Pooled it
- Operationalising Genomic Surveillance for Antimicrobial Resistance in Low- and Middle-Income Countries: A One Health Perspective from Bangladesh.Microorganisms · 2026Review
- The gut microbiome as a major source of drug-resistant infections: emerging strategies to decolonize and target the gut reservoir.Frontiers in cellular and infection microbiology · 2025Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Previous research on the gut microbiome has primarily focused on fecal microbiota, raising concerns about whether fecal samples accurately represent the entire intestinal microbiota. Studies have shown that microbial communities across the gastrointestinal (GI) tract are more diverse than those in feces, suggesting that microbial composition may vary depending on the sampling method. Additionally, analyzing the broader diversity of microbial communities in the GI tract may enhance the identification of potentially beneficial microbiota. Methods: In this study, we compare gut microbiome datasets obtained from fecal samples and GI samples (collected by pooling luminal contents and mucosal scrapings from the stomach to the end of the colon) of 6-month-old mice using 16S rRNA sequencing. We further investigate the associations between gut microbiota and motor, cognitive, and emotional functions in mice, examining differences between the two sample types. To assess these variations, we apply DESeq2 analysis to identify microbial species enriched in high-functioning groups and evaluate how their selection may differ depending on the sampling approach. Results: Our findings reveal notable differences in microbial composition between fecal and GI samples, suggesting that sampling methods may influence the identification of beneficial bacteria. Discussion: These results highlight the importance of selecting an appropriate sampling approach in microbiome research to ensure a comprehensive understanding of gut microbiota-host interactions.
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Registered trials
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