Contamination in Low Microbial Biomass Microbiome Studies: Issues and Recommendations
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Next-generation sequencing approaches in microbiome research have allowed surveys of microbial communities, their genomes, and their functions with higher sensitivity than ever before. However, this sensitivity is a double-edged sword because these tools also efficiently detect contaminant DNA and cross-contamination, which can confound the interpretation of microbiome data. Therefore, there is an urgent need to integrate key controls into microbiome research to improve the integrity of microbiome studies. Here, we review how contaminant DNA and cross-contamination arise within microbiome studies and discuss their negative impacts, especially during the analysis of low microbial biomass samples. We then identify several key measures that researchers can implement to reduce the impact of contaminant DNA and cross-contamination during microbiome research. We put forward a set of minimal experimental criteria, the 'RIDE' checklist, to improve the validity of future low microbial biomass research.
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The tumor microbiome has relatively low biomass, making contamination problematic.
“Because the tumor microbiome has a relatively low biomass, contamination of the tumor samples with bacteria or bacterial DNA can be problematic (30, 31).”
From The human tumor microbiome is composed of tumor type–specific intracellular bacteria (2020) · cites this paper as [31]
Validation plasma samples were processed with extensive controls, a single library preparation method, in a single batch, in one deep-sequencing run.
“Cell-free DNA was extracted from these plasma samples with extensive controls18,22 (Extended Data Figs. 9b–c), and processed for whole metagenomic sequencing by a limited set of users, using a single library preparation method47, in a single batch, in one deep-sequencing run.”
From RETRACTED ARTICLE: Microbiome analyses of blood and tissues suggest cancer diagnostic approach (2020) · cites this paper as [18]
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Husso, A., Jalanka, J., Alipour, M. J., Huhti, P., Kareskoski, M., Pessa‐Morikawa, T., Iivanainen, A., & Niku, M. (2020) · Scientific Reports · doi:10.1038/s41598-019-57003-8 · Cited by 63 · see citing works
Then, C. K., Paillas, S., Wang, X., Hampson, A., & Kiltie, A. E. (2020) · BMC Biology · doi:10.1186/s12915-020-00836-x · Cited by 61 · see citing works
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- Authors
- Eisenhofer, R., Minich, J. J., Marotz, C., Cooper, A., Knight, R., & Weyrich, L. S.
- Affiliations
- Australian Research Council (AU)
- Scripps Institution of Oceanography (US)
- University of California San Diego (US)
- Corresponding author
- Eisenhofer, Raphael
- Venue
- Trends in Microbiology
- Publisher
- Elsevier BV
- Published
- 2019-02
- Volume
- 27
- Issue
- 2
- Pages
- 105-117
- ISSN
- 0966-842X (ISSN-L)
- OpenAlex
- W2903174799
- Cited by
- 1,146
- References
- 86
- Citations by year
- 2026: 234 · 2025: 149 · 2024: 112 · 2023: 150 · 2022: 153 · 2021: 163 · 2020: 120 · 2019: 62 · 2018: 1
- FWCI
- 8.61
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Trends in Microbiology (publishedVersion)
- PubMed (publishedVersion)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- Funders
- Discovery Early Career Researcher Award (DE150101574)
- ARC (CE170100015)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Keywords
- cross-contamination, experimental control
- MeSH terms
- DNA, Bacterial, Humans, Microbiological Techniques, Specimen Handling, Reproducibility of Results, Biomass, Metagenomics, High-Throughput Nucleotide Sequencing, DNA Contamination, Microbiota
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