Evidence map›Paper›PMID 32250964›Full record

ArticlemSphere2020

Comparison of Methods To Collect Fecal Samples for Microbiome Studies Using Whole-Genome Shotgun Metagenomic Sequencing.

Doratha A Byrd, Rashmi Sinha, Kristi L Hoffman, Jun Chen, Xing Hua, Jianxin Shi, Nicholas Chia, Joseph Petrosino, Emily Vogtmann

Abstract readComparative Study
In one paragraph

Article in mSphere, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Comparing the Metagenomic Performance of Stools Collected from Custom Cards and 95% Ethanol in Epidemiologic Studies.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
    Article
  10. Article
  11. Article
  12. Analysis of metagenomic data.Nature reviews. Methods primers · 2025
    Article
  13. Review
  14. Nanopore R10.4 metagenomic detection of blaNature communications · 2024
    Article
  15. Article
  16. Article
  17. Article
  18. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Doratha A ByrdMetabolic Epidemiology Branch, Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA byrdda@nih.gov.
Rashmi SinhaMetabolic Epidemiology Branch, Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Kristi L HoffmanAlkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas, USA.
Jun ChenMicrobiome Program, Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota, USA.
Xing HuaBiostatistics Branch, Division of Cancer Epidemiology & Genetics, National Cancer Institute, Bethesda, Maryland, USA.
Jianxin ShiBiostatistics Branch, Division of Cancer Epidemiology & Genetics, National Cancer Institute, Bethesda, Maryland, USA.
Nicholas ChiaMicrobiome Program, Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota, USA.
Joseph PetrosinoAlkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas, USA.
Emily VogtmannMetabolic Epidemiology Branch, Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.ORCID 0000-0003-1355-5593

Funding

Training CoreP42ES010349 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI NAVAS-ACIEN, ANA · 2000 to 2020
$53.6M
Lower Gastrointestinal Cancer StudiesZIACP010198 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI SINHA, RASHMI · 2009 to 2025
$6.6M
Microbial Metabolic Toxicity Drives Colon CancerR01CA179243 · NCI · MAYO CLINIC ROCHESTER · PI CHIA, NICHOLAS · 2014 to 2018
$2.0M
NCI NIH HHS R01 CA179243NIEHS NIH HHS P42 ES010349
6 · The paper itself

Abstract

Few previous studies have assessed stability and "gold-standard" concordance of fecal sample collection methods for whole-genome shotgun metagenomic sequencing (WGSS), an increasingly popular method for studying the gut microbiome. We used WGSS data to investigate ambient temperature stability and putative gold-standard concordance of microbial profiles in fecal samples collected and stored using fecal occult blood test (FOBT) cards, fecal immunochemical test (FIT) tubes, 95% ethanol, or RNAlater. Among 15 Mayo Clinic employees, for each collection method, we calculated intraclass correlation coefficients (ICCs) to estimate stability of fecal microbial profiles after storage for 4 days at ambient temperature and concordance with immediately frozen, no-solution samples (i.e., the putative gold standard). ICCs were estimated for multiple metrics, including relative abundances of select phyla, species, KEGG k-genes (representing any coding sequence that had >70% identity and >70% query coverage with respect to a known KEGG ortholog), KEGG modules, and KEGG pathways; species and k-gene alpha diversity; and Bray-Curtis and Jaccard species beta diversity. ICCs for microbial profile stability were excellent (≥90%) for fecal samples collected via most of the collection methods, except those preserved in 95% ethanol. Concordance with the immediately frozen, no-solution samples varied for all collection methods, but the number of observed species and the beta diversity metrics tended to have higher concordance than other metrics. Our findings, taken together with previous studies and feasibility considerations, indicated that FOBT cards, FIT tubes, and RNAlater are acceptable choices for fecal sample collection methods in future WGSS studies.

Indexed as

MetagenomeWhole Genome SequencingAdultDNA, BacterialEthanolFecesFemaleFreezingGastrointestinal MicrobiomeHealthy VolunteersHumansMaleMetagenomicsMiddle AgedPreservation, BiologicalRNA, Ribosomal, 16SDNA, BacterialEthanolRNA, Ribosomal, 16Sfecal sample collection methodFIT tubesFOBT cardsmicrobiomewhole-genome shotgun sequencing

Identifiers

PMID32250964
PMCPMC7045388

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.