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

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Abstract

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.

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Insight into biases and sequencing errors for amplicon sequencing with the Illumina MiSeq platform

Melanie Schirmer, Umer Z. Ijaz, Rosalinda D'Amore … (2015)

With read lengths of currently up to 2 × 300 bp, high throughput and low sequencing costs Illumina's MiSeq is becoming one of the most utilized sequencing platforms worldwide. The platform is manageable and affordable even for smaller labs. This enables quick turnaround on a broad range of applications such as targeted gene sequencing, metagenomics, small genome sequencing and clinical molecular diagnostics. However, Illumina error profiles are still poorly understood and programs are therefore not designed for the idiosyncrasies of Illumina data. A better knowledge of the error patterns is essential for sequence analysis and vital if we are to draw valid conclusions. Studying true genetic variation in a population sample is fundamental for understanding diseases, evolution and origin. We conducted a large study on the error patterns for the MiSeq based on 16S rRNA amplicon sequencing data. We tested state-of-the-art library preparation methods for amplicon sequencing and showed that the library preparation method and the choice of primers are the most significant sources of bias and cause distinct error patterns. Furthermore we tested the efficiency of various error correction strategies and identified quality trimming (Sickle) combined with error correction (BayesHammer) followed by read overlapping (PANDAseq) as the most successful approach, reducing substitution error rates on average by 93%.

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Experimental and analytical tools for studying the human microbiome.

Justin Kuczynski, Christian L Lauber, William Walters … (2011)

The human microbiome substantially affects many aspects of human physiology, including metabolism, drug interactions and numerous diseases. This realization, coupled with ever-improving nucleotide sequencing technology, has precipitated the collection of diverse data sets that profile the microbiome. In the past 2 years, studies have begun to include sufficient numbers of subjects to provide the power to associate these microbiome features with clinical states using advanced algorithms, increasing the use of microbiome studies both individually and collectively. Here we discuss tools and strategies for microbiome studies, from primer selection to bioinformatics analysis.

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Evaluation of Methods for the Extraction and Purification of DNA from the Human Microbiome

Sanqing Yuan, Dora Cohen, Jacques Ravel … (2012)

Background DNA extraction is an essential step in all cultivation-independent approaches to characterize microbial diversity, including that associated with the human body. A fundamental challenge in using these approaches has been to isolate DNA that is representative of the microbial community sampled. Methodology/Principal Findings In this study, we statistically evaluated six commonly used DNA extraction procedures using eleven human-associated bacterial species and a mock community that contained equal numbers of those eleven species. These methods were compared on the basis of DNA yield, DNA shearing, reproducibility, and most importantly representation of microbial diversity. The analysis of 16S rRNA gene sequences from a mock community showed that the observed species abundances were significantly different from the expected species abundances for all six DNA extraction methods used. Conclusions/Significance Protocols that included bead beating and/or mutanolysin produced significantly better bacterial community structure representation than methods without both of them. The reproducibility of all six methods was similar, and results from different experimenters and different times were in good agreement. Based on the evaluations done it appears that DNA extraction procedures for bacterial community analysis of human associated samples should include bead beating and/or mutanolysin to effectively lyse cells.