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Identification of low abundance microbiome in clinical samples using whole genome sequencing

Identifying the microbiome composition from primary tissues directly affords an opportunity to study the causative relationships between the host microbiome and disease. However, this is challenging due the low abundance of microbial DNA relative to the host. We present a systematic evaluation of mi...

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Autores principales: Zhang, Chao, Cleveland, Kyle, Schnoll-Sussman, Felice, McClure, Bridget, Bigg, Michelle, Thakkar, Prashant, Schultz, Nikolaus, Shah, Manish A., Betel, Doron
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4661937/
https://www.ncbi.nlm.nih.gov/pubmed/26614063
http://dx.doi.org/10.1186/s13059-015-0821-z
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author Zhang, Chao
Cleveland, Kyle
Schnoll-Sussman, Felice
McClure, Bridget
Bigg, Michelle
Thakkar, Prashant
Schultz, Nikolaus
Shah, Manish A.
Betel, Doron
author_facet Zhang, Chao
Cleveland, Kyle
Schnoll-Sussman, Felice
McClure, Bridget
Bigg, Michelle
Thakkar, Prashant
Schultz, Nikolaus
Shah, Manish A.
Betel, Doron
author_sort Zhang, Chao
collection PubMed
description Identifying the microbiome composition from primary tissues directly affords an opportunity to study the causative relationships between the host microbiome and disease. However, this is challenging due the low abundance of microbial DNA relative to the host. We present a systematic evaluation of microbiome profiling directly from endoscopic biopsies by whole genome sequencing. We compared our methods with other approaches on datasets with previously identified microbial composition. We applied this approach to identify the microbiome from 27 stomach biopsies, and validated the presence of Helicobacter pylori by quantitative PCR. Finally, we profiled the microbial composition in The Cancer Genome Atlas gastric adenocarcinoma cohort. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-015-0821-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-46619372015-11-28 Identification of low abundance microbiome in clinical samples using whole genome sequencing Zhang, Chao Cleveland, Kyle Schnoll-Sussman, Felice McClure, Bridget Bigg, Michelle Thakkar, Prashant Schultz, Nikolaus Shah, Manish A. Betel, Doron Genome Biol Method Identifying the microbiome composition from primary tissues directly affords an opportunity to study the causative relationships between the host microbiome and disease. However, this is challenging due the low abundance of microbial DNA relative to the host. We present a systematic evaluation of microbiome profiling directly from endoscopic biopsies by whole genome sequencing. We compared our methods with other approaches on datasets with previously identified microbial composition. We applied this approach to identify the microbiome from 27 stomach biopsies, and validated the presence of Helicobacter pylori by quantitative PCR. Finally, we profiled the microbial composition in The Cancer Genome Atlas gastric adenocarcinoma cohort. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-015-0821-z) contains supplementary material, which is available to authorized users. BioMed Central 2015-11-27 2015 /pmc/articles/PMC4661937/ /pubmed/26614063 http://dx.doi.org/10.1186/s13059-015-0821-z Text en © Zhang et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Method
Zhang, Chao
Cleveland, Kyle
Schnoll-Sussman, Felice
McClure, Bridget
Bigg, Michelle
Thakkar, Prashant
Schultz, Nikolaus
Shah, Manish A.
Betel, Doron
Identification of low abundance microbiome in clinical samples using whole genome sequencing
title Identification of low abundance microbiome in clinical samples using whole genome sequencing
title_full Identification of low abundance microbiome in clinical samples using whole genome sequencing
title_fullStr Identification of low abundance microbiome in clinical samples using whole genome sequencing
title_full_unstemmed Identification of low abundance microbiome in clinical samples using whole genome sequencing
title_short Identification of low abundance microbiome in clinical samples using whole genome sequencing
title_sort identification of low abundance microbiome in clinical samples using whole genome sequencing
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4661937/
https://www.ncbi.nlm.nih.gov/pubmed/26614063
http://dx.doi.org/10.1186/s13059-015-0821-z
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