From Sample to Multi-Omics Conclusions in under 48 Hours

ABSTRACT Multi-omics methods have greatly advanced our understanding of the biological organism and its microbial associates. However, they are not routinely used in clinical or industrial applications, due to the length of time required to generate and analyze omics data. Here, we applied a novel i...

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Autores principales:	Robert A. Quinn, Jose A. Navas-Molina, Embriette R. Hyde, Se Jin Song, Yoshiki Vázquez-Baeza, Greg Humphrey, James Gaffney, Jeremiah J. Minich, Alexey V. Melnik, Jakob Herschend, Jeff DeReus, Austin Durant, Rachel J. Dutton, Mahdieh Khosroheidari, Clifford Green, Ricardo da Silva, Pieter C. Dorrestein, Rob Knight
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2016
Materias:	16S rRNA microbiome fermented food metabolome molecular networking rapid response Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/0f17874a07d14105893c61eda2b008cf
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spelling	oai:doaj.org-article:0f17874a07d14105893c61eda2b008cf2021-12-02T18:15:43ZFrom Sample to Multi-Omics Conclusions in under 48 Hours10.1128/mSystems.00038-162379-5077https://doaj.org/article/0f17874a07d14105893c61eda2b008cf2016-04-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00038-16https://doaj.org/toc/2379-5077ABSTRACT Multi-omics methods have greatly advanced our understanding of the biological organism and its microbial associates. However, they are not routinely used in clinical or industrial applications, due to the length of time required to generate and analyze omics data. Here, we applied a novel integrated omics pipeline for the analysis of human and environmental samples in under 48 h. Human subjects that ferment their own foods provided swab samples from skin, feces, oral cavity, fermented foods, and household surfaces to assess the impact of home food fermentation on their microbial and chemical ecology. These samples were analyzed with 16S rRNA gene sequencing, inferred gene function profiles, and liquid chromatography-tandem mass spectrometry (LC-MS/MS) metabolomics through the Qiita, PICRUSt, and GNPS pipelines, respectively. The human sample microbiomes clustered with the corresponding sample types in the American Gut Project (http://www.americangut.org ), and the fermented food samples produced a separate cluster. The microbial communities of the household surfaces were primarily sourced from the fermented foods, and their consumption was associated with increased gut microbial diversity. Untargeted metabolomics revealed that human skin and fermented food samples had separate chemical ecologies and that stool was more similar to fermented foods than to other sample types. Metabolites from the fermented foods, including plant products such as procyanidin and pheophytin, were present in the skin and stool samples of the individuals consuming the foods. Some food metabolites were modified during digestion, and others were detected in stool intact. This study represents a first-of-its-kind analysis of multi-omics data that achieved time intervals matching those of classic microbiological culturing. IMPORTANCE Polymicrobial infections are difficult to diagnose due to the challenge in comprehensively cultivating the microbes present. Omics methods, such as 16S rRNA sequencing, metagenomics, and metabolomics, can provide a more complete picture of a microbial community and its metabolite production, without the biases and selectivity of microbial culture. However, these advanced methods have not been applied to clinical or industrial microbiology or other areas where complex microbial dysbioses require immediate intervention. The reason for this is the length of time required to generate and analyze omics data. Here, we describe the development and application of a pipeline for multi-omics data analysis in time frames matching those of the culture-based approaches often used for these applications. This study applied multi-omics methods effectively in clinically relevant time frames and sets a precedent toward their implementation in clinical medicine and industrial microbiology.Robert A. QuinnJose A. Navas-MolinaEmbriette R. HydeSe Jin SongYoshiki Vázquez-BaezaGreg HumphreyJames GaffneyJeremiah J. MinichAlexey V. MelnikJakob HerschendJeff DeReusAustin DurantRachel J. DuttonMahdieh KhosroheidariClifford GreenRicardo da SilvaPieter C. DorresteinRob KnightAmerican Society for Microbiologyarticle16S rRNAmicrobiomefermented foodmetabolomemolecular networkingrapid responseMicrobiologyQR1-502ENmSystems, Vol 1, Iss 2 (2016)
institution	DOAJ
collection	DOAJ
language	EN
topic	16S rRNA microbiome fermented food metabolome molecular networking rapid response Microbiology QR1-502
spellingShingle	16S rRNA microbiome fermented food metabolome molecular networking rapid response Microbiology QR1-502 Robert A. Quinn Jose A. Navas-Molina Embriette R. Hyde Se Jin Song Yoshiki Vázquez-Baeza Greg Humphrey James Gaffney Jeremiah J. Minich Alexey V. Melnik Jakob Herschend Jeff DeReus Austin Durant Rachel J. Dutton Mahdieh Khosroheidari Clifford Green Ricardo da Silva Pieter C. Dorrestein Rob Knight From Sample to Multi-Omics Conclusions in under 48 Hours
description	ABSTRACT Multi-omics methods have greatly advanced our understanding of the biological organism and its microbial associates. However, they are not routinely used in clinical or industrial applications, due to the length of time required to generate and analyze omics data. Here, we applied a novel integrated omics pipeline for the analysis of human and environmental samples in under 48 h. Human subjects that ferment their own foods provided swab samples from skin, feces, oral cavity, fermented foods, and household surfaces to assess the impact of home food fermentation on their microbial and chemical ecology. These samples were analyzed with 16S rRNA gene sequencing, inferred gene function profiles, and liquid chromatography-tandem mass spectrometry (LC-MS/MS) metabolomics through the Qiita, PICRUSt, and GNPS pipelines, respectively. The human sample microbiomes clustered with the corresponding sample types in the American Gut Project (http://www.americangut.org ), and the fermented food samples produced a separate cluster. The microbial communities of the household surfaces were primarily sourced from the fermented foods, and their consumption was associated with increased gut microbial diversity. Untargeted metabolomics revealed that human skin and fermented food samples had separate chemical ecologies and that stool was more similar to fermented foods than to other sample types. Metabolites from the fermented foods, including plant products such as procyanidin and pheophytin, were present in the skin and stool samples of the individuals consuming the foods. Some food metabolites were modified during digestion, and others were detected in stool intact. This study represents a first-of-its-kind analysis of multi-omics data that achieved time intervals matching those of classic microbiological culturing. IMPORTANCE Polymicrobial infections are difficult to diagnose due to the challenge in comprehensively cultivating the microbes present. Omics methods, such as 16S rRNA sequencing, metagenomics, and metabolomics, can provide a more complete picture of a microbial community and its metabolite production, without the biases and selectivity of microbial culture. However, these advanced methods have not been applied to clinical or industrial microbiology or other areas where complex microbial dysbioses require immediate intervention. The reason for this is the length of time required to generate and analyze omics data. Here, we describe the development and application of a pipeline for multi-omics data analysis in time frames matching those of the culture-based approaches often used for these applications. This study applied multi-omics methods effectively in clinically relevant time frames and sets a precedent toward their implementation in clinical medicine and industrial microbiology.
format	article
author	Robert A. Quinn Jose A. Navas-Molina Embriette R. Hyde Se Jin Song Yoshiki Vázquez-Baeza Greg Humphrey James Gaffney Jeremiah J. Minich Alexey V. Melnik Jakob Herschend Jeff DeReus Austin Durant Rachel J. Dutton Mahdieh Khosroheidari Clifford Green Ricardo da Silva Pieter C. Dorrestein Rob Knight
author_facet	Robert A. Quinn Jose A. Navas-Molina Embriette R. Hyde Se Jin Song Yoshiki Vázquez-Baeza Greg Humphrey James Gaffney Jeremiah J. Minich Alexey V. Melnik Jakob Herschend Jeff DeReus Austin Durant Rachel J. Dutton Mahdieh Khosroheidari Clifford Green Ricardo da Silva Pieter C. Dorrestein Rob Knight
author_sort	Robert A. Quinn
title	From Sample to Multi-Omics Conclusions in under 48 Hours
title_short	From Sample to Multi-Omics Conclusions in under 48 Hours
title_full	From Sample to Multi-Omics Conclusions in under 48 Hours
title_fullStr	From Sample to Multi-Omics Conclusions in under 48 Hours
title_full_unstemmed	From Sample to Multi-Omics Conclusions in under 48 Hours
title_sort	from sample to multi-omics conclusions in under 48 hours
publisher	American Society for Microbiology
publishDate	2016
url	https://doaj.org/article/0f17874a07d14105893c61eda2b008cf
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From Sample to Multi-Omics Conclusions in under 48 Hours

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