Journal Article

Systematic improvement of amplicon marker gene methods for increased accuracy in microbiome studies

Hunter, Ryan, Gohl, Daryl M, Becker, Aaron, Clayton, Jonathan B, Garbe, John, Gould, Trevor J, MacLean, Allison, Johnson, Timothy J, Knights, Dan, Vangay, Pajau, Beckman, Kenneth B, Hauge, Adam

2016

Overview

Sources of error and bias in PCR amplification of microbial samples for 16S rRNA gene sequencing are systematically evaluated, and best-practice recommendations for reliable amplification are made. Amplicon-based marker gene surveys form the basis of most microbiome and other microbial community studies. Such PCR-based methods have multiple steps, each of which is susceptible to error and bias. Variance in results has also arisen through the use of multiple methods of next-generation sequencing (NGS) amplicon library preparation. Here we formally characterized errors and biases by comparing different methods of amplicon-based NGS library preparation. Using mock community standards, we analyzed the amplification process to reveal insights into sources of experimental error and bias in amplicon-based microbial community and microbiome experiments. We present a method that improves on the current best practices and enables the detection of taxonomic groups that often go undetected with existing methods.

• Publisher: Nature Publishing Group US,Nature Publishing Group
• Subject: 45/77 / 631/1647/2234 / 631/208/514/2254 / 631/326/2565/2134 / 631/61/212 / Agriculture / analysis / Bioinformatics / Biomarkers / Biomedical Engineering/Biotechnology / Biomedicine / Biotechnology / DNA Replication - genetics / Gene expression / Gene Library / Genes / Genetic aspects / Genetic Markers - genetics / High-Throughput Nucleotide Sequencing - methods / High-Throughput Nucleotide Sequencing - standards / Life Sciences / Microbial colonies / Microbiota - genetics / Observations / Polymerase chain reaction / Polymerase Chain Reaction - methods / Polymerase Chain Reaction - standards / Practice Guidelines as Topic / Reproducibility of Results / Sensitivity and Specificity