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Quantifying spatiotemporal variability and noise in absolute microbiota abundances using replicate sampling.
Ji, Brian W; Sheth, Ravi U; Dixit, Purushottam D; Huang, Yiming; Kaufman, Andrew; Wang, Harris H; Vitkup, Dennis.
Afiliação
  • Ji BW; Department of Systems Biology, Columbia University, New York, NY, USA.
  • Sheth RU; Integrated Program in Cellular, Molecular, and Biomedical Studies, Columbia University, New York, NY, USA.
  • Dixit PD; Department of Systems Biology, Columbia University, New York, NY, USA.
  • Huang Y; Integrated Program in Cellular, Molecular, and Biomedical Studies, Columbia University, New York, NY, USA.
  • Kaufman A; Department of Systems Biology, Columbia University, New York, NY, USA.
  • Wang HH; Department of Systems Biology, Columbia University, New York, NY, USA.
  • Vitkup D; Integrated Program in Cellular, Molecular, and Biomedical Studies, Columbia University, New York, NY, USA.
Nat Methods ; 16(8): 731-736, 2019 08.
Article em En | MEDLINE | ID: mdl-31308552
Metagenomic sequencing has enabled detailed investigation of diverse microbial communities, but understanding their spatiotemporal variability remains an important challenge. Here, we present decomposition of variance using replicate sampling (DIVERS), a method based on replicate sampling and spike-in sequencing. The method quantifies the contributions of temporal dynamics, spatial sampling variability, and technical noise to the variances and covariances of absolute bacterial abundances. We applied DIVERS to investigate a high-resolution time series of the human gut microbiome and a spatial survey of a soil bacterial community in Manhattan's Central Park. Our analysis showed that in the gut, technical noise dominated the abundance variability for nearly half of the detected taxa. DIVERS also revealed substantial spatial heterogeneity of gut microbiota, and high temporal covariances of taxa within the Bacteroidetes phylum. In the soil community, spatial variability primarily contributed to abundance fluctuations at short time scales (weeks), while temporal variability dominated at longer time scales (several months).
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Microbiologia do Solo / Bactérias / Algoritmos / Fezes / Metagenômica / Análise Espaço-Temporal / Microbioma Gastrointestinal Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Microbiologia do Solo / Bactérias / Algoritmos / Fezes / Metagenômica / Análise Espaço-Temporal / Microbioma Gastrointestinal Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article