Contamination in Low Microbial Biomass Microbiome Studies: Issues and Recommendations

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 c...

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Bibliographic Details
Published in:Trends in microbiology (Regular ed.) Vol. 27; no. 2; pp. 105 - 117
Main Authors: Eisenhofer, Raphael, Minich, Jeremiah J., Marotz, Clarisse, Cooper, Alan, Knight, Rob, Weyrich, Laura S.
Format: Journal Article
Language:English
Published: England Elsevier Ltd 01.02.2019
Elsevier Science Ltd
Subjects:
Biomass
Contaminants
Contamination
cross contamination
Deoxyribonucleic acid
DNA
DNA Contamination
DNA, Bacterial - analysis
DNA, Bacterial - genetics
genome
Genomes
High-Throughput Nucleotide Sequencing
Humans
laboratory contamination
low biomass
Metagenomics
methodology
Microbial activity
microbial biomass
microbial communities
Microbial contamination
Microbiological Techniques - methods
Microbiological Techniques - standards
microbiome
Microbiomes
microbiota
Microbiota - genetics
Microorganisms
Next-generation sequencing
Reproducibility of Results
Sensitivity
Specimen Handling
surveys
microbiota
laboratory contamination
DNA contamination
microbiome
methodology
low biomass
ISSN:0966-842X, 1878-4380, 1878-4380
Online Access:Get full text
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Summary: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. There is increasing interest in applying metagenomic techniques to find correlations between microorganisms and disease. Metagenomic techniques are highly sensitive and can detect contaminant DNA (DNA from sources other than the samples under study) and cross-contamination (DNA exchange between samples). Recent studies have shown that contaminant DNA and cross-contamination can confound metagenomic studies, especially for sample types that have low microbial biomass. There is an urgent need for the field to adopt authentication criteria to prevent future metagenomic studies from falling prey to the pitfalls of contaminant DNA and cross-contamination.
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ISSN:0966-842X
1878-4380
1878-4380
DOI:10.1016/j.tim.2018.11.003