Evidence map›Paper›PMID 31915218›Full record

ArticlemSphere2020

Systematic Analysis of Impact of Sampling Regions and Storage Methods on Fecal Gut Microbiome and Metabolome Profiles.

Yali Liang, Tianyu Dong, Minjian Chen, Lianping He, Tingzhang Wang, Xingyin Liu, Hang Chang, Jian-Hua Mao, Bo Hang, Antoine M Snijders and 1 more

Open access · goldAbstract read
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 48 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 2 pooled it
3.2field-weighted citation impact, top 7% of its field
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

48 citing papers in PubMed, 2 syntheses or guidelines pooled it, 64 citations in OpenAlex.

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  16. A novel method for precise endoscopic sampling of duodenal microbiota.Frontiers in cellular and infection microbiology · 2025
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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

11 authors at 4 institutions in 2 countries.

Yali LiangSchool of Public Health, Wannan Medical College, Wuhu, China.
Tianyu DongState Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
Minjian ChenState Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
Lianping HeDepartment of Immunology, Nanjing Medical University, Nanjing, China.
Tingzhang WangZhejiang Institute of Microbiology, Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, China.
Xingyin LiuDepartment of Pathogen Biology-Microbiology Division, Nanjing Medical University, Nanjing, China.ORCID 0000-0001-8770-3494
Hang ChangBiological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA.
Jian-Hua MaoBiological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA.ORCID 0000-0001-9320-6021
Bo HangBiological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA.
Antoine M SnijdersBiological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA amsnijders@lbl.gov yankaixia@njmu.edu.cn.
Yankai XiaState Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China amsnijders@lbl.gov yankaixia@njmu.edu.cn.
Nanjing Medical University · CNLawrence Berkeley National Laboratory · USInstitute of Microbiology · CNWannan Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The contribution of human gastrointestinal (GI) microbiota and metabolites to host health has recently become much clearer. However, many confounding factors can influence the accuracy of gut microbiome and metabolome studies, resulting in inconsistencies in published results. In this study, we systematically investigated the effects of fecal sampling regions and storage and retrieval conditions on gut microbiome and metabolite profiles from three healthy children. Our analysis indicated that compared to homogenized and snap-frozen samples (standard control [SC]), different sampling regions did not affect microbial community alpha diversity, while a total of 22 of 176 identified metabolites varied significantly across different sampling regions. In contrast, storage conditions significantly influenced the microbiome and metabolome. Short-term room temperature storage had a minimal effect on the microbiome and metabolome profiles. Sample storage in RNALater showed a significant level of variation in both microbiome and metabolome profiles, independent of the storage or retrieval conditions. The effect of RNALater on the metabolome was stronger than the effect on the microbiome, and individual variability between study participants outweighed the effect of RNALater on the microbiome. We conclude that homogenizing stool samples was critical for metabolomic analysis but not necessary for microbiome analysis. Short-term room temperature storage had a minimal effect on the microbiome and metabolome profiles and is recommended for short-term fecal sample storage. In addition, our study indicates that the use of RNALater as a storage medium of stool samples for microbial and metabolomic analyses is not recommended.

Indexed as

MetabolomeTemperatureChild, PreschoolDNA, BacterialFecesFemaleGastrointestinal MicrobiomeHumansMaleMetabolomicsRNA, Ribosomal, 16SSequence Analysis, DNASpecimen HandlingDNA, BacterialRNA, Ribosomal, 16Sfecesmetabolomemicrobiomesampling regionsstorage methods

Identifiers

PMID31915218
PMCPMC6952195
OpenAlexW2999239475

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.