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Seasonal variation in gut microbiota composition: cross-sectional evidence from Ukrainian population

BACKGROUND: Gut microbiota composition is known to depend on environmental (diet, day length, infections, xenobiotic exposure) and lifestyle (alcohol/drug intake, physical activity) factors. All these factors fluctuate seasonally, especially in areas with highly variable climatic conditions between...

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Detalles Bibliográficos
Autores principales: Koliada, Alexander, Moseiko, Vladyslav, Romanenko, Mariana, Piven, Liubov, Lushchak, Oleh, Kryzhanovska, Nadiia, Guryanov, Vitaly, Vaiserman, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7175530/
https://www.ncbi.nlm.nih.gov/pubmed/32316935
http://dx.doi.org/10.1186/s12866-020-01786-8
Descripción
Sumario:BACKGROUND: Gut microbiota composition is known to depend on environmental (diet, day length, infections, xenobiotic exposure) and lifestyle (alcohol/drug intake, physical activity) factors. All these factors fluctuate seasonally, especially in areas with highly variable climatic conditions between seasons. Seasonal microbiota changes were reported in several previous studies. The purpose of our study was to investigate whether there is a seasonal variability in the gut microbiota composition in Ukrainian population. In contrast to previous studies performed on small-size samples using a longitudinal design, we used cross-sectional design with a large sample size (n = 769). Determination of microbial composition at the level of major microbial phyla was performed by qRT-PCR. RESULTS: The relative abundance of major taxonomic groups of gut microbiota was found to be affected by month of sampling. Actinobacteria were more abundant and Bacteroidetes were less abundant in summer-derived samples compared to those obtained during other seasons, whereas Firmicutes content was seasonally independent. The Firmicutes to Bacteroidetes (F/B) ratio was significantly higher in summer-derived samples than in winter-derived ones. Odds to have F/B > 1 were 3.3 times higher in summer samples and 1.9 times higher in autumn samples than in winter ones; neither age, nor sex were significant confounding factors. CONCLUSIONS: Seasonality of sampling could influence results of human microbiome research, thereby potentially biasing estimates. This factor must be taken into consideration in further microbiome research.