The fecal microbiota of lactating Holstein dairy cows: a meta-analysis highlighting key microbial profiles and methodological challenges
Arnalot, L.; Pascal, G.; DEJEAN, S.; Foucras, G.; Zened, A.
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In cattle, the digestive microbiota has been poorly studied outside the rumen, despite its recognized role in animal physiology, health, and production. This study aimed to provide a comprehensive meta-analysis of the fecal microbiota of lactating Holstein dairy cows. A systematic online search of PubMed was performed in June 2023 to identify studies on the fecal microbiota of lactating Holstein dairy cows. Of the 526 articles retrieved from the systematic online search, only 28 met our required inclusion criteria. Raw sequencing data targeting the 16S rRNA gene (V3-V4 region) were obtained either from public repositories or directly from the authors. Two recently published articles were included as they met the inclusion criteria. A total of 2,136 samples were included in the analysis. The number of sequences per sample varied considerably between studies, and the metadata were sparse. The core microbiota was identified as the most prevalent and shared taxa, comprising 21 microbiota families that accounted for 82% of the relative abundance. The observed clustering, which depended on study, highlighted the significant impact of environmental factors and experimental conditions on the microbial communities of cattle. A multi-group analysis was performed to correct for the study effect and successfully identified three microbiota profiles. The meta-analysis approach is a rigorous and systematic method of analyzing research findings that allows for the generation of reliable and reproducible results. This approach ensures the independence of results from a single experimental facility or condition, thereby enhancing the reliability and generalizability of the findings. ImportanceThis meta-analysis provides the most comprehensive and up-to-date overview of the fecal microbiota of lactating Holstein dairy cows, based on a rigorous selection of over 2,000 samples. By controlling for inter-study variation, it successfully identified consistent microbial patterns and establishes a robust core microbiota. This work not only highlighted the microbial taxa most likely essential to bovine physiology and health, but also emphasized the need for standardized methodologies and improved data-sharing practices across studies. Ultimately, the findings pave the way for strategies that target the modulation of microbiota with potential benefits for animal health and environmental impacts.
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