Controlling for Contaminants in Low-Biomass 16S rRNA Gene Sequencing Experiments.

ABSTRACT: Microbial communities are commonly studied using culture-independent methods, such as 16S rRNA gene sequencing. However, one challenge in accurately characterizing microbial communities is exogenous bacterial DNA contamination, particularly in low-microbial-biomass niches. Computational approaches to identify contaminant sequences have been proposed, but their performance has not been independently evaluated. To identify the impact of decreasing microbial biomass on polymicrobial 16S rRNA gene sequencing experiments, we created a mock microbial community dilution series. We evaluated four computational approaches to identify and remove contaminants, as follows: (i) filtering sequences present in a negative control, (ii) filtering sequences based on relative abundance, (iii) identifying seq

SUBMITTER: Karstens L 

PROVIDER: S-EPMC6550369 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature