Contamination in Low Microbial Biomass Microbiome Studies: Issues and Recommendations

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. 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. 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. DNA from sources other than the sample(s) under study (e.g., DNA from reagents or researchers performing laboratory work). an umbrella term encompassing both contaminant DNA and cross-contamination (see below). DNA exchange between samples within a study (e.g., accidental movement of DNA between different sample tubes during DNA extraction). a negative control consisting of an empty tube/well that is processed alongside biological samples during DNA extraction and allows for the detection of contaminant DNA introduced during DNA extraction. a positive control consisting of serially diluted cells of known type(s) that is processed alongside biological samples during DNA extraction and allows for determination of the limit of detection, monitoring of extraction efficiency, and quantification of cross-contamination during DNA extraction. a biological sample that contains similar quantities of target microbial DNA in the sample compared to negative controls (e.g., ≤10 000 microbial cells [19Salter S.J. et al.Reagent and laboratory contamination can critically impact sequence-based microbiome analyses.BMC Biol. 2014; 12: 87Crossref PubMed Scopus (1797) Google Scholar]). the microorganisms of a specific habitat, their genomes, and the surrounding environmental conditions [84Marchesi J.R. Ravel J. The vocabulary of microbiome research: a proposal.Microbiome. 2015; 3: 31Crossref PubMed Google Scholar]. the assemblage of microorganisms present in a defined environment [84Marchesi J.R. Ravel J. The vocabulary of microbiome research: a proposal.Microbiome. 2015; 3: 31Crossref PubMed Google Scholar]. a negative control made by preparing an amplification or library preparation reaction without input template (i.e., sample DNA) that is processed alongside biological samples and allows for the detection contaminant DNA during library preparation/PCR amplification. a positive control consisting of serially diluted DNA from known organism type(s) that are processed alongside biological samples during amplification or library preparation and allows for determination of the limit of detection, monitoring of library preparation efficiency, and quantification of cross-contamination during library preparation. report methodology, include controls, determine the level of contamination, and explore the impacts of contamination in downstream analysis; a minimum standards checklist for low microbial biomass microbiome studies. a negative control consisting of an empty tube that is processed alongside the collection of biological samples. Allows the detection of contaminant DNA introduced during the sampling procedure (e.g., airborne, swabs, preservatives).