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Multidomain analyses of a longitudinal human microbiome intestinal cleanout perturbation experiment.
Fukuyama, Julia; Rumker, Laurie; Sankaran, Kris; Jeganathan, Pratheepa; Dethlefsen, Les; Relman, David A; Holmes, Susan P.
Afiliación
  • Fukuyama J; Statistics Department, Stanford University, Stanford, California, USA.
  • Rumker L; Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, California, USA.
  • Sankaran K; Harvard Medical School, Boston, Massachusetts, USA.
  • Jeganathan P; Statistics Department, Stanford University, Stanford, California, USA.
  • Dethlefsen L; Statistics Department, Stanford University, Stanford, California, USA.
  • Relman DA; Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, California, USA.
  • Holmes SP; Department of Medicine, Stanford University School of Medicine, Stanford, California, USA.
PLoS Comput Biol ; 13(8): e1005706, 2017 Aug.
Article en En | MEDLINE | ID: mdl-28821012
ABSTRACT
Our work focuses on the stability, resilience, and response to perturbation of the bacterial communities in the human gut. Informative flash flood-like disturbances that eliminate most gastrointestinal biomass can be induced using a clinically-relevant iso-osmotic agent. We designed and executed such a disturbance in human volunteers using a dense longitudinal sampling scheme extending before and after induced diarrhea. This experiment has enabled a careful multidomain analysis of a controlled perturbation of the human gut microbiota with a new level of resolution. These new longitudinal multidomain data were analyzed using recently developed statistical methods that demonstrate improvements over current practices. By imposing sparsity constraints we have enhanced the interpretability of the analyses and by employing a new adaptive generalized principal components analysis, incorporated modulated phylogenetic information and enhanced interpretation through scoring of the portions of the tree most influenced by the perturbation. Our analyses leverage the taxa-sample duality in the data to show how the gut microbiota recovers following this perturbation. Through a holistic approach that integrates phylogenetic, metagenomic and abundance information, we elucidate patterns of taxonomic and functional change that characterize the community recovery process across individuals. We provide complete code and illustrations of new sparse statistical methods for high-dimensional, longitudinal multidomain data that provide greater interpretability than existing methods.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Metagenoma / Metagenómica / Microbioma Gastrointestinal / Modelos Biológicos Tipo de estudio: Observational_studies / Prognostic_studies Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Metagenoma / Metagenómica / Microbioma Gastrointestinal / Modelos Biológicos Tipo de estudio: Observational_studies / Prognostic_studies Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos