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Comparing Circadian Rhythmicity in the Human Gut Microbiome

Targeted sequencing of 16S rRNA genes enables the analysis of microbiomes. Here, we describe a protocol for the collection, storage, and preparation of fecal samples. We describe how we cluster similar sequences and assign bacterial taxonomies. Using diversity analysis and machine learning, we can e...

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Detalles Bibliográficos
Autores principales: Reitmeier, Sandra, Kiessling, Silke, Neuhaus, Klaus, Haller, Dirk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7757335/
https://www.ncbi.nlm.nih.gov/pubmed/33377042
http://dx.doi.org/10.1016/j.xpro.2020.100148
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author Reitmeier, Sandra
Kiessling, Silke
Neuhaus, Klaus
Haller, Dirk
author_facet Reitmeier, Sandra
Kiessling, Silke
Neuhaus, Klaus
Haller, Dirk
author_sort Reitmeier, Sandra
collection PubMed
description Targeted sequencing of 16S rRNA genes enables the analysis of microbiomes. Here, we describe a protocol for the collection, storage, and preparation of fecal samples. We describe how we cluster similar sequences and assign bacterial taxonomies. Using diversity analysis and machine learning, we can extract disease-associated features. We also describe a circadian analysis to identify the presence or absence of rhythms in taxonomies. Differences in rhythmicity between cohorts can contribute to determining disease-associated bacterial signatures. For complete details on the use and execution of this protocol, please refer to Reitmeier et al. (2020).
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spelling pubmed-77573352020-12-28 Comparing Circadian Rhythmicity in the Human Gut Microbiome Reitmeier, Sandra Kiessling, Silke Neuhaus, Klaus Haller, Dirk STAR Protoc Protocol Targeted sequencing of 16S rRNA genes enables the analysis of microbiomes. Here, we describe a protocol for the collection, storage, and preparation of fecal samples. We describe how we cluster similar sequences and assign bacterial taxonomies. Using diversity analysis and machine learning, we can extract disease-associated features. We also describe a circadian analysis to identify the presence or absence of rhythms in taxonomies. Differences in rhythmicity between cohorts can contribute to determining disease-associated bacterial signatures. For complete details on the use and execution of this protocol, please refer to Reitmeier et al. (2020). Elsevier 2020-10-26 /pmc/articles/PMC7757335/ /pubmed/33377042 http://dx.doi.org/10.1016/j.xpro.2020.100148 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Protocol
Reitmeier, Sandra
Kiessling, Silke
Neuhaus, Klaus
Haller, Dirk
Comparing Circadian Rhythmicity in the Human Gut Microbiome
title Comparing Circadian Rhythmicity in the Human Gut Microbiome
title_full Comparing Circadian Rhythmicity in the Human Gut Microbiome
title_fullStr Comparing Circadian Rhythmicity in the Human Gut Microbiome
title_full_unstemmed Comparing Circadian Rhythmicity in the Human Gut Microbiome
title_short Comparing Circadian Rhythmicity in the Human Gut Microbiome
title_sort comparing circadian rhythmicity in the human gut microbiome
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7757335/
https://www.ncbi.nlm.nih.gov/pubmed/33377042
http://dx.doi.org/10.1016/j.xpro.2020.100148
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