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Comparison of Fecal Collection Methods for Microbiome and Metabolomics Studies

Background: Integrated microbiome and metabolomics analyses hold the potential to reveal interactions between host and microbiota in relation to disease risks. However, there are few studies evaluating how field methods influence fecal microbiome characterization and metabolomics profiling. Methods:...

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Autores principales: Wang, Zheng, Zolnik, Christine P., Qiu, Yunping, Usyk, Mykhaylo, Wang, Tao, Strickler, Howard D., Isasi, Carmen R., Kaplan, Robert C., Kurland, Irwin J., Qi, Qibin, Burk, Robert D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6127643/
https://www.ncbi.nlm.nih.gov/pubmed/30234027
http://dx.doi.org/10.3389/fcimb.2018.00301
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author Wang, Zheng
Zolnik, Christine P.
Qiu, Yunping
Usyk, Mykhaylo
Wang, Tao
Strickler, Howard D.
Isasi, Carmen R.
Kaplan, Robert C.
Kurland, Irwin J.
Qi, Qibin
Burk, Robert D.
author_facet Wang, Zheng
Zolnik, Christine P.
Qiu, Yunping
Usyk, Mykhaylo
Wang, Tao
Strickler, Howard D.
Isasi, Carmen R.
Kaplan, Robert C.
Kurland, Irwin J.
Qi, Qibin
Burk, Robert D.
author_sort Wang, Zheng
collection PubMed
description Background: Integrated microbiome and metabolomics analyses hold the potential to reveal interactions between host and microbiota in relation to disease risks. However, there are few studies evaluating how field methods influence fecal microbiome characterization and metabolomics profiling. Methods: Five fecal collection methods [immediate freezing at −20°C without preservative, OMNIgene GUT, 95% ethanol, RNAlater, and Flinders Technology Associates (FTA) cards] were used to collect 40 fecal samples from eight healthy volunteers. We performed gut microbiota 16S rRNA sequencing, untargeted metabolomics profiling, and targeted metabolomics focusing on short chained fatty acids (SCFAs). Metrics included α-diversity and β-diversity as well as distributions of predominant phyla. To evaluate the concordance with the “gold standard” immediate freezing, the intraclass correlation coefficients (ICCs) for alternate fecal collection systems were calculated. Correlations between SCFAs and gut microbiota were also examined. Results: The FTA cards had the highest ICCs compared to the immediate freezing method for α-diversity indices (ICCs = 0.96, 0.96, 0.76 for Shannon index, Simpson's Index, Chao-1 Index, respectively), followed by OMNIgene GUT, RNAlater, and 95% ethanol. High ICCs (all >0.88) were observed for all methods for the β-diversity metric. For untargeted metabolomics, in comparison to immediate freezing which detected 621 metabolites at ≥75% detectability level, 95% ethanol showed the largest overlapping set of metabolites (n = 430; 69.2%), followed by FTA cards (n = 330; 53.1%) and OMNIgene GUT (n = 213; 34.3%). Both OMNIgene GUT (ICCs = 0.82, 0.93, 0.64) and FTA cards (ICCs = 0.87, 0.85, 0.54) had acceptable ICCs for the top three predominant SCFAs (butyric acid, propionic acid and acetic acid). Nominally significant correlations between bacterial genera and SCFAs (P < 0.05) were observed in fecal samples collected by different methods. Of note, a high correlation between the genus Blautia (known butyrate producer) and butyric acid was observed for both immediate freezing (r = 0.83) and FTA cards (r = 0.74). Conclusions: Four alternative fecal collection methods are generally comparable with immediate freezing, but there are differences in certain measures of the gut microbiome and fecal metabolome across methods. Choice of method depends on the research interests, simplicity of fecal collection procedures and ease of transportation to the lab, especially for large epidemiological studies.
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spelling pubmed-61276432018-09-19 Comparison of Fecal Collection Methods for Microbiome and Metabolomics Studies Wang, Zheng Zolnik, Christine P. Qiu, Yunping Usyk, Mykhaylo Wang, Tao Strickler, Howard D. Isasi, Carmen R. Kaplan, Robert C. Kurland, Irwin J. Qi, Qibin Burk, Robert D. Front Cell Infect Microbiol Cellular and Infection Microbiology Background: Integrated microbiome and metabolomics analyses hold the potential to reveal interactions between host and microbiota in relation to disease risks. However, there are few studies evaluating how field methods influence fecal microbiome characterization and metabolomics profiling. Methods: Five fecal collection methods [immediate freezing at −20°C without preservative, OMNIgene GUT, 95% ethanol, RNAlater, and Flinders Technology Associates (FTA) cards] were used to collect 40 fecal samples from eight healthy volunteers. We performed gut microbiota 16S rRNA sequencing, untargeted metabolomics profiling, and targeted metabolomics focusing on short chained fatty acids (SCFAs). Metrics included α-diversity and β-diversity as well as distributions of predominant phyla. To evaluate the concordance with the “gold standard” immediate freezing, the intraclass correlation coefficients (ICCs) for alternate fecal collection systems were calculated. Correlations between SCFAs and gut microbiota were also examined. Results: The FTA cards had the highest ICCs compared to the immediate freezing method for α-diversity indices (ICCs = 0.96, 0.96, 0.76 for Shannon index, Simpson's Index, Chao-1 Index, respectively), followed by OMNIgene GUT, RNAlater, and 95% ethanol. High ICCs (all >0.88) were observed for all methods for the β-diversity metric. For untargeted metabolomics, in comparison to immediate freezing which detected 621 metabolites at ≥75% detectability level, 95% ethanol showed the largest overlapping set of metabolites (n = 430; 69.2%), followed by FTA cards (n = 330; 53.1%) and OMNIgene GUT (n = 213; 34.3%). Both OMNIgene GUT (ICCs = 0.82, 0.93, 0.64) and FTA cards (ICCs = 0.87, 0.85, 0.54) had acceptable ICCs for the top three predominant SCFAs (butyric acid, propionic acid and acetic acid). Nominally significant correlations between bacterial genera and SCFAs (P < 0.05) were observed in fecal samples collected by different methods. Of note, a high correlation between the genus Blautia (known butyrate producer) and butyric acid was observed for both immediate freezing (r = 0.83) and FTA cards (r = 0.74). Conclusions: Four alternative fecal collection methods are generally comparable with immediate freezing, but there are differences in certain measures of the gut microbiome and fecal metabolome across methods. Choice of method depends on the research interests, simplicity of fecal collection procedures and ease of transportation to the lab, especially for large epidemiological studies. Frontiers Media S.A. 2018-08-28 /pmc/articles/PMC6127643/ /pubmed/30234027 http://dx.doi.org/10.3389/fcimb.2018.00301 Text en Copyright © 2018 Wang, Zolnik, Qiu, Usyk, Wang, Strickler, Isasi, Kaplan, Kurland, Qi and Burk. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cellular and Infection Microbiology
Wang, Zheng
Zolnik, Christine P.
Qiu, Yunping
Usyk, Mykhaylo
Wang, Tao
Strickler, Howard D.
Isasi, Carmen R.
Kaplan, Robert C.
Kurland, Irwin J.
Qi, Qibin
Burk, Robert D.
Comparison of Fecal Collection Methods for Microbiome and Metabolomics Studies
title Comparison of Fecal Collection Methods for Microbiome and Metabolomics Studies
title_full Comparison of Fecal Collection Methods for Microbiome and Metabolomics Studies
title_fullStr Comparison of Fecal Collection Methods for Microbiome and Metabolomics Studies
title_full_unstemmed Comparison of Fecal Collection Methods for Microbiome and Metabolomics Studies
title_short Comparison of Fecal Collection Methods for Microbiome and Metabolomics Studies
title_sort comparison of fecal collection methods for microbiome and metabolomics studies
topic Cellular and Infection Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6127643/
https://www.ncbi.nlm.nih.gov/pubmed/30234027
http://dx.doi.org/10.3389/fcimb.2018.00301
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