bioRxivMicrobiology
Efficacy of fecal sampling as a gut proxy in the study of chicken gut microbiota
W. Yan, J. Zheng, C. WEN, C. Ji, D. Zhang, Y. Chen, C. Sun, N. Yang
Abstract
BackgroundDespite the convenience and noninvasiveness of fecal sampling, the fecal microbiota does not fully represent that of the gastrointestinal (GI) tract, and the efficacy of fecal sampling to accurately represent the gut microbiota in birds is poorly understood. In this study, we aim to identify the efficacy of feces as a gut proxy in birds using chickens as a model. We collected 1,026 samples from 206 chickens, including duodenum, jejunum, ileum, cecum and feces samples, for 16S rRNA amplicon sequencing analyses.\n\nResultsIn this study, the efficacy of feces as a gut proxy was partitioned to microbial community membership and community structure. Most taxa in the small intestine (84.11 - 87.28%) and ceca (99.39%) could be identified in feces. Microbial community membership was reflected with a gut anatomic feature, but community structure was not. Excluding shared microbes, the small intestine and ceca contributed 34.12 and 5.83% of the total fecal members, respectively. The composition of Firmicutes members in the small intestine and that of Actinobacteria, Bacteroidetes, Firmicutes and Proteobacteria members in the ceca could be well mirrored by the observations in fecal samples ({rho} = 0.54 - 0.71 and 0.71 - 0.78, respectively, P < 0.001). However, there were few significant correlations for each genus between feces and each of the 4 gut segments, and these correlations were not high ({rho} = -0.2 - 0.4, P < 0.05) for most genera.\n\nConclusionsOur results provide evidence that the good potential of feces to identify most taxa in chicken guts, but it should be interpreted with caution by using feces as a proxy for gut in microbial structure analyses. This work provides insights and future directions regarding the usage of fecal samples in studies of the gut microbiome.
- organism: chicken / avian
- assay: metagenomics
- research focus: cell type annotation
- approach: statistical model
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