Contamination in low microbial biomass microbiome studies: issues and recommendations

Abstract

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.