Evidence map›Paper›PMID 38366085›Full record

ArticleScientific reports2024

Choice of DNA extraction method affects stool microbiome recovery and subsequent phenotypic association analyses.

Asier Fernández-Pato, Trishla Sinha, Ranko Gacesa, Sergio Andreu-Sánchez, Milla F Brandao Gois, Jody Gelderloos-Arends, Dianne B H Jansen, Marloes Kruk, Martin Jaeger, Leo A B Joosten and 7 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 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

32 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  12. Nanopore sequencing of the Tunisian gut microbiome: effect of the DNA extraction methods.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2026
    Article
  13. Review
  14. Review
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  16. Defining reference values for the gut microbiota in a Southern European population.Frontiers in cellular and infection microbiology · 2026
    Article
  17. Article
  18. Review
  19. Unlocking the Metagenome: Pipeline for Microbiome Data Analysis.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  20. Article
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

17 authors.

Asier Fernández-PatoDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, 9713GZ, the Netherlands.
Trishla SinhaDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, 9713GZ, the Netherlands.
Ranko GacesaDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, 9713GZ, the Netherlands.
Sergio Andreu-SánchezDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, 9713GZ, the Netherlands.
Milla F Brandao GoisDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, 9713GZ, the Netherlands.
Jody Gelderloos-ArendsDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, 9713GZ, the Netherlands.
Dianne B H JansenDepartment of Gastroenterology and Hepatology, University Medical Center Groningen, Groningen, 9713GZ, the Netherlands.
Marloes KrukDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, 9713GZ, the Netherlands.
Martin JaegerDepartment of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.
Leo A B JoostenDepartment of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.
Mihai G NeteaDepartment of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.
Rinse K WeersmaDepartment of Gastroenterology and Hepatology, University Medical Center Groningen, Groningen, 9713GZ, the Netherlands.
Cisca WijmengaDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, 9713GZ, the Netherlands.
Hermie J M HarmsenMedical Microbiology and Infection Prevention, University of Groningen, University Medical Center Groningen, Groningen, 9713GZ, the Netherlands.
Jingyuan FuDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, 9713GZ, the Netherlands.
Alexandra ZhernakovaDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, 9713GZ, the Netherlands.
Alexander KurilshikovDepartment of Genetics, University of Groningen, University Medical Center Groningen, Groningen, 9713GZ, the Netherlands. alexa.kur@gmail.com.

Funding

ERC Consolidator grant 101001678EU Horizon Europe Program grant INITIALISE 101094099European Research Council (ERC) Starting Grant 715772Netherlands Heart Foundation CVON grant 2018-27Netherlands Organization for Scientific Research (NWO) VIDI grant 016.178.056NWO Gravitation grant ExposomeNL 024.004.017NWO Gravitation grant Netherlands Organ-on-Chip Initiative 024.003.001NWO Spinoza Prize SPI 92-266NWO VICI grant VI.C.202.022Seerave Foundation and the Dutch Digestive Foundation 16-14TIMID project LSHM18057-SGF
6 · The paper itself

Abstract

The lack of standardization in the methods of DNA extraction from fecal samples represents the major source of experimental variation in the microbiome research field. In this study, we aimed to compare the metagenomic profiles and microbiome-phenotype associations obtained by applying two commercially available DNA extraction kits: the AllPrep DNA/RNA Mini Kit (APK) and the QIAamp Fast DNA Stool Mini Kit (FSK). Using metagenomic sequencing data available from 745 paired fecal samples from two independent population cohorts, Lifelines-DEEP (LLD, n = 292) and the 500 Functional Genomics project (500FG, n = 453), we confirmed significant differences in DNA yield and the recovered microbial communities between protocols, with the APK method resulting in a higher DNA concentration and microbial diversity. Further, we observed a massive difference in bacterial relative abundances at species-level between the APK and the FSK protocols, with > 75% of species differentially abundant between protocols in both cohorts. Specifically, comparison with a standard mock community revealed that the APK method provided higher accuracy in the recovery of microbial relative abundances, with the absence of a bead-beating step in the FSK protocol causing an underrepresentation of gram-positive bacteria. This heterogeneity in the recovered microbial composition led to remarkable differences in the association with anthropometric and lifestyle phenotypes. The results of this study further reinforce that the choice of DNA extraction method impacts the metagenomic profile of human gut microbiota and highlight the importance of harmonizing protocols in microbiome studies.

Indexed as

Gastrointestinal MicrobiomeMicrobiotaDNADNA, BacterialFecesHumansMetagenomicsRNA, Ribosomal, 16SSequence Analysis, DNADNADNA, BacterialRNA, Ribosomal, 16SDNA extractionFecal sampleGut microbiomeShotgun metagenomics

Identifiers

PMID38366085
PMCPMC10873414

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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.