The Truth About Metagenomics: Quantifying and Counteracting Bias in 16S RRNA Studies

• Activity Number: 140
• Type: Contributed
• Date/Time: Monday, August 10, 2015 : 8:30 AM to 10:20 AM
• Sponsor: Quality and Productivity Section
• Author(s): David Edwards* and Vaginal Microbiome Consortium
• Companies: Virginia Commonwealth University and Virginia Commonwealth University
• Keywords: bias ; microbiome ; mixture experiments ; next-generation sequencing ; quality control

Abstract

Characterizing microbial communities via next-generation sequencing is subject to a number of pitfalls involving sample processing. The observed community composition can be a severe distortion of the quantities of bacteria actually present in the microbiome, hampering analysis and threatening the validity of conclusions from metagenomic studies. We introduce an experimental protocol using mixture experiments and mock communities for quantifying and characterizing bias introduced in the sample processing pipeline. The processing steps affected different bacteria in different ways, resulting in amplified and suppressed observed proportions of a community. When predictive models were applied to clinical samples from a subject, the predicted microbiome profiles were better reflections of the physiology and diagnosis of the subject at the visits than the observed community compositions.