ArticleScientific reports2024
Variability and bias in microbiome metagenomic sequencing: an interlaboratory study comparing experimental protocols.
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 46 papers.
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Who cites it
46 citing papers in PubMed, 40 citations in OpenAlex.
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- Integrating multi-omics technologies to decipher microbiome functions.Nature communications · 2026Review
- Effect of low dose azithromycin on the fecal microbiome and fecal bile acids in healthy dogs.Journal of veterinary internal medicine · 2026Article
- Diet, the Gut Microbiome, and Mental Health: Mechanistic Perspectives.Molecular nutrition & food research · 2026Review
- Integrative multicohort analysis reveals consistent sex differences in gut microbiota of multiple sclerosis patients.mSystems · 2026Article
- The role of the microbiota in hematological malignancies: A narrative review of mechanisms and therapeutic potential.New microbes and new infections · 2026Review
- Can the leafhopper microbiome unlock new strategies for its control?Journal of economic entomology · 2026Review
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- Targeting the Microbiota-Gut-Brain Axis: Emerging Nanomedicine Approaches for Neurodegenerative Diseases.The European journal of neuroscience · 2026Review
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- Quantitative evaluation of microbiome sequencing resolution under varying experimental conditions using defined mock communities.Scientific reports · 2026Article
- The gut-joint axis in osteoarthritis.Nature reviews. Rheumatology · 2026Review
- Canine Idiopathic Epilepsy as a Natural Animal Model for Human Epilepsy: A Scoping Review Highlighting Metabolic Perspectives Beyond the Brain.Nutrients · 2026Article
- LLM-Assessed Relatedness of Microbiome Study Descriptions Aligns more Strongly with Functional than with Taxonomic Profile Similarity.Microbial ecology · 2026Article
- Evaluating the analytical performance of direct-to-consumer gut microbiome testing services.Communications biology · 2026Article
- Review
- A mathematical framework to correct for compositionality in microbiome data sets.Applied and environmental microbiology · 2026Article
- Gut Microbiota in the Hepato-Cardiorenal Axis: Microbial Metabolites, Inflammation, and Emerging Therapeutic Targets.Current pharmaceutical design · 2026Review
- Methodological bias shapes the interpretation of the urinary microbiome in low-biomass systems.Frontiers in microbiology · 2026Review
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Authors and funding
33 authors at 20 institutions in 10 countries.
Funding
Abstract
Several studies have documented the significant impact of methodological choices in microbiome analyses. The myriad of methodological options available complicate the replication of results and generally limit the comparability of findings between independent studies that use differing techniques and measurement pipelines. Here we describe the Mosaic Standards Challenge (MSC), an international interlaboratory study designed to assess the impact of methodological variables on the results. The MSC did not prescribe methods but rather asked participating labs to analyze 7 shared reference samples (5 × human stool samples and 2 × mock communities) using their standard laboratory methods. To capture the array of methodological variables, each participating lab completed a metadata reporting sheet that included 100 different questions regarding the details of their protocol. The goal of this study was to survey the methodological landscape for microbiome metagenomic sequencing (MGS) analyses and the impact of methodological decisions on metagenomic sequencing results. A total of 44 labs participated in the MSC by submitting results (16S or WGS) along with accompanying metadata; thirty 16S rRNA gene amplicon datasets and 14 WGS datasets were collected. The inclusion of two types of reference materials (human stool and mock communities) enabled analysis of both MGS measurement variability between different protocols using the biologically-relevant stool samples, and MGS bias with respect to ground truth values using the DNA mixtures. Owing to the compositional nature of MGS measurements, analyses were conducted on the ratio of Firmicutes: Bacteroidetes allowing us to directly apply common statistical methods. The resulting analysis demonstrated that protocol choices have significant effects, including both bias of the MGS measurement associated with a particular methodological choices, as well as effects on measurement robustness as observed through the spread of results between labs making similar methodological choices. In the analysis of the DNA mock communities, MGS measurement bias was observed even when there was general consensus among the participating laboratories. This study was the result of a collaborative effort that included academic, commercial, and government labs. In addition to highlighting the impact of different methodological decisions on MGS result comparability, this work also provides insights for consideration in future microbiome measurement study design.
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Registered trials
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.