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Synthetic spike-in standards for high-throughput 16S rRNA gene amplicon sequencing.

ABSTRACT: High-throughput sequencing of 16S rRNA gene amplicons (16S-seq) has become a widely deployed method for profiling complex microbial communities but technical pitfalls related to data reliability and quantification remain to be fully addressed. In this work, we have developed and implemented a set of synthetic 16S rRNA genes to serve as universal spike-in standards for 16S-seq experiments. The spike-ins represent full-length 16S rRNA genes containing artificial variable regions with negligible identity to known nucleotide sequences, permitting unambiguous identification of spike-in sequences in 16S-seq read data from any microbiome sample. Using defined mock communities and environmental microbiota, we characterized the performance of the spike-in standards and demonstrated their utility for evaluating data quality on a per-sample basis. Further, we showed that staggered spike-in mixtures added at the point of DNA extraction enable concurrent estimation of absolute microbial abundances suitable for comparative analysis. Results also underscored that template-specific Illumina sequencing artifacts may lead to biases in the perceived abundance of certain taxa. Taken together, the spike-in standards represent a novel bioanalytical tool that can substantially improve 16S-seq-based microbiome studies by enabling comprehensive quality control along with absolute quantification.

SUBMITTER: Tourlousse DM

PROVIDER: S-EPMC5389483 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Synthetic spike-in standards for high-throughput 16S rRNA gene amplicon sequencing.

Tourlousse Dieter M DM Yoshiike Satowa S Ohashi Akiko A Matsukura Satoko S Noda Naohiro N Sekiguchi Yuji Y

Nucleic acids research 20170201 4

High-throughput sequencing of 16S rRNA gene amplicons (16S-seq) has become a widely deployed method for profiling complex microbial communities but technical pitfalls related to data reliability and quantification remain to be fully addressed. In this work, we have developed and implemented a set of synthetic 16S rRNA genes to serve as universal spike-in standards for 16S-seq experiments. The spike-ins represent full-length 16S rRNA genes containing artificial variable regions with negligible id ...[more]

PMID: 27980100

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Project description:BackgroundAdvances in sequencing technologies and bioinformatics have made the analysis of microbial communities almost routine. Nonetheless, the need remains to improve on the techniques used for gathering such data, including increasing throughput while lowering cost and benchmarking the techniques so that potential sources of bias can be better characterized.MethodsWe present a triple-index amplicon sequencing strategy to sequence large numbers of samples at significantly lower c ost and in a shorter timeframe compared to existing methods. The design employs a two-stage PCR protocol, incorpo rating three barcodes to each sample, with the possibility to add a fourth-index. It also includes heterogeneity spacers to overcome low complexity issues faced when sequencing amplicons on Illumina platforms.ResultsThe library preparation method was extensively benchmarked through analysis of a mock community in order to assess biases introduced by sample indexing, number of PCR cycles, and template concentration. We further evaluated the method through re-sequencing of a standardized environmental sample. Finally, we evaluated our protocol on a set of fecal samples from a small cohort of healthy adults, demonstrating good performance in a realistic experimental setting. Between-sample variation was mainly related to batch effects, such as DNA extraction, while sample indexing was also a significant source of bias. PCR cycle number strongly influenced chimera formation and affected relative abundance estimates of species with high GC content. Libraries were sequenced using the Illumina HiSeq and MiSeq platforms to demonstrate that this protocol is highly scalable to sequence thousands of samples at a very low cost.ConclusionsHere, we provide the most comprehensive study of performance and bias inherent to a 16S rRNA gene amplicon sequencing method to date. Triple-indexing greatly reduces the number of long custom DNA oligos required for library preparation, while the inclusion of variable length heterogeneity spacers minimizes the need for PhiX spike-in. This design results in a significant cost reduction of highly multiplexed amplicon sequencing. The biases we characterize highlight the need for highly standardized protocols. Reassuringly, we find that the biological signal is a far stronger structuring factor than the various sources of bias.

Project description:BackgroundNext-generation sequencing (NGS) methods and especially 16S rRNA gene amplicon sequencing have become indispensable tools in microbial ecology. While they have opened up new possibilities for studying microbial communities, they also have one drawback, namely providing only relative abundances and thus compositional data. Quantitative PCR (qPCR) has been used for years for the quantification of bacteria. However, this method requires the development of specific primers and has a low throughput. The constraint of low throughput has recently been overcome by the development of high-throughput qPCR (HT-qPCR), which allows for the simultaneous detection of the most prevalent bacteria in moderately complex systems, such as cheese and other fermented dairy foods. In the present study, the performance of the two approaches, NGS and HT-qPCR, was compared by analyzing the same DNA samples from 21 Raclette du Valais protected designation of origin (PDO) cheeses. Based on the results obtained, the differences, accuracy, and usefulness of the two approaches were studied in detail.ResultsThe results obtained using NGS (non-targeted) and HT-qPCR (targeted) show considerable agreement in determining the microbial composition of the cheese DNA samples studied, albeit the fundamentally different nature of these two approaches. A few inconsistencies in species detection were observed, particularly for less abundant ones. The detailed comparison of the results for 15 bacterial species/groups measured by both methods revealed a considerable bias for certain bacterial species in the measurements of the amplicon sequencing approach. We identified as probable origin to this PCR bias due to primer mismatches, variations in the number of copies for the 16S rRNA gene, and bias introduced in the bioinformatics analysis.ConclusionAs the normalized microbial composition results of NGS and HT-qPCR agreed for most of the 21 cheese samples analyzed, both methods can be considered as complementary and reliable for studying the microbial composition of cheese. Their combined application proved to be very helpful in identifying potential biases and overcoming methodological limitations in the quantitative analysis of the cheese microbiota.

Dataset Information

Synthetic spike-in standards for high-throughput 16S rRNA gene amplicon sequencing.

Publications

Synthetic spike-in standards for high-throughput 16S rRNA gene amplicon sequencing.

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