Evidence map›Paper›PMID 28683838›Full record

ArticleMicrobiome2017

A novel ultra high-throughput 16S rRNA gene amplicon sequencing library preparation method for the Illumina HiSeq platform.

Eric J de Muinck, Pål Trosvik, Gregor D Gilfillan, Johannes R Hov, Arvind Y M Sundaram

Abstract read
In one paragraph

Article in Microbiome, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

66 citing papers in PubMed.

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  14. The Dynamic Changes ofPlants (Basel, Switzerland) · 2024
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6 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Eric J de MuinckCentre for Ecological and Evolutionary Synthesis, Department of Biosciences, University of Oslo, Oslo, Norway.
Pål TrosvikCentre for Ecological and Evolutionary Synthesis, Department of Biosciences, University of Oslo, Oslo, Norway.
Gregor D GilfillanDepartment of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway.
Johannes R HovNorwegian PSC Research Center and Research Institute of Internal Medicine, Oslo University Hospital Rikshospitalet and University of Oslo, Oslo, Norway.
Arvind Y M SundaramDepartment of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway. arvind.sundaram@medisin.uio.no.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Gene LibraryBacteriaComputational BiologyDNA Barcoding, TaxonomicHigh-Throughput Nucleotide SequencingMetagenomicsPolymerase Chain ReactionRNA, Ribosomal, 16SSequence Analysis, DNARNA, Ribosomal, 16S16S rRNA gene amplicon sequencingBenchmarkingChimera formationEnvironmental sequencingIllumina library preparationIndexed PCRMock communityPCR bias

Identifiers

PMID28683838
PMCPMC5501495

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.