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Comparison of Fecal Collection Methods for Microbiome and Metabolomics Studies

Overview of attention for article published in Frontiers in Cellular and Infection Microbiology, August 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

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1 news outlet
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1 blog
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8 X users

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311 Mendeley
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Title
Comparison of Fecal Collection Methods for Microbiome and Metabolomics Studies
Published in
Frontiers in Cellular and Infection Microbiology, August 2018
DOI 10.3389/fcimb.2018.00301
Pubmed ID
Authors

Zheng Wang, Christine P. Zolnik, Yunping Qiu, Mykhaylo Usyk, Tao Wang, Howard D. Strickler, Carmen R. Isasi, Robert C. Kaplan, Irwin J. Kurland, Qibin Qi, Robert D. Burk

Abstract

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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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 311 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 311 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 53 17%
Researcher 45 14%
Student > Master 32 10%
Student > Bachelor 27 9%
Student > Doctoral Student 21 7%
Other 42 14%
Unknown 91 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 57 18%
Agricultural and Biological Sciences 38 12%
Medicine and Dentistry 34 11%
Immunology and Microbiology 25 8%
Chemistry 10 3%
Other 48 15%
Unknown 99 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 August 2020.
All research outputs
#1,717,574
of 23,577,654 outputs
Outputs from Frontiers in Cellular and Infection Microbiology
#260
of 6,873 outputs
Outputs of similar age
#37,408
of 335,942 outputs
Outputs of similar age from Frontiers in Cellular and Infection Microbiology
#5
of 95 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,873 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 335,942 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 95 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.