ArticleApplied microbiology and biotechnology2024
Quantifying variation across 16S rRNA gene sequencing runs in human microbiome studies.
Article in Applied microbiology and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Comparison of the effects of four commercially available prescription diet regimens on the fecal microbiome in healthy cats.The Journal of veterinary medical science · 2026Article
- Interpreting oral microbiome research in clinical dentistry: terminology, limitations and clinical implications.British dental journal · 2026Review
- Canine Idiopathic Epilepsy as a Natural Animal Model for Human Epilepsy: A Scoping Review Highlighting Metabolic Perspectives Beyond the Brain.Nutrients · 2026Article
- The fecal metabolome and microbiome are altered in dogs with idiopathic epilepsy compared to healthy dogs.Scientific reports · 2025Article
- Effects of diet type on the core fecal bacterial taxa and the dysbiosis index of healthy adult dogs.Frontiers in veterinary science · 2025Article
- Stabilized and unstabilized sampling methods result in differential fecal 16S rRNA microbial sequencing results.PloS one · 2025Article
- An insight into the gut microbiota of healthy and allergic West Highland Whiter Terrier dogs.PloS one · 2025Article
- Effect of Omeprazole on Esophageal Microbiota in Dogs Detected Using a Minimally Invasive Sampling Method.Journal of veterinary internal medicineArticle
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Authors and funding
5 authors.
Funding
Abstract
Recent microbiome research has incorporated a higher number of samples through more participants in a study, longitudinal studies, and metanalysis between studies. Physical limitations in a sequencing machine can result in samples spread across sequencing runs. Here we present the results of sequencing nearly 1000 16S rRNA gene sequences in fecal (stabilized and swab) and oral (swab) samples from multiple human microbiome studies and positive controls that were conducted with identical standard operating procedures. Sequencing was performed in the same center across 18 different runs. The simplified mock community showed limitations in accuracy, while precision (e.g., technical variation) was robust for the mock community and actual human positive control samples. Technical variation was the lowest for stabilized fecal samples, followed by fecal swab samples, and then oral swab samples. The order of technical variation stability was inverse of DNA concentrations (e.g., highest in stabilized fecal samples), highlighting the importance of DNA concentration in reproducibility and urging caution when analyzing low biomass samples. Coefficients of variation at the genus level also followed the same trend for lower variation with higher DNA concentrations. Technical variation across both sample types and the two human sampling locations was significantly less than the observed biological variation. Overall, this research providing comparisons between technical and biological variation, highlights the importance of using positive controls, and provides semi-quantified data to better understand variation introduced by sequencing runs. KEY POINTS: • Mock community and positive control accuracy were lower than precision. • Samples with lower DNA concentration had increased technical variation across sequencing runs. • Biological variation was significantly higher than technical variation due to sequencing runs.
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