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. 

TITLE=Comparison of Fecal Collection Methods for Microbiome and Metabolomics Studies

JOURNAL=Frontiers in Cellular and Infection Microbiology

VOLUME=8

YEAR=2018

URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2018.00301

DOI=10.3389/fcimb.2018.00301

ISSN=2235-2988

ABSTRACT=<p><bold>Background:</bold> 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.</p><p><bold>Methods:</bold> Five fecal collection methods [immediate freezing at −20°C without preservative, OMNIgene GUT, 95% ethanol, RNA<italic>later</italic>, 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.</p><p><bold>Results:</bold> 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, RNA<italic>later</italic>, and 95% ethanol. High ICCs (all &gt;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 (<italic>n</italic> = 430; 69.2%), followed by FTA cards (<italic>n</italic> = 330; 53.1%) and OMNIgene GUT (<italic>n</italic> = 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 (<italic>P</italic> &lt; 0.05) were observed in fecal samples collected by different methods. Of note, a high correlation between the genus <italic>Blautia</italic> (known butyrate producer) and butyric acid was observed for both immediate freezing (<italic>r</italic> = 0.83) and FTA cards (<italic>r</italic> = 0.74).</p><p><bold>Conclusions:</bold> 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.</p>