Document Type

Article

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Disciplines

Biochemistry, Biophysics, and Structural Biology | Bioinformatics | Biology | Biotechnology | Genetics and Genomics | Genomics | Immunology and Infectious Disease | Medicine and Health Sciences | Microbiology

CIT Disciplines

Biochemistry and molecular biology; Microbiology; Biochemical research methods; Genetics and heredity; 3. MEDICAL AND HEALTH SCIENCES; 3.1 BASIC MEDICINE; 3.4 HEALTH BIOTECHNOLOGY; Technologies involving identifying the functioning of DNA,; 3.5 OTHER MEDICAL SCIENCES; 4. AGRICULTURAL SCIENCES; 4.4 AGRICULTURAL BIOTECHNOLOGY

Publication Details

PLoS One

Editor: Bryan A White, University of Illinois, UNITED STATES Received: September 8, 2015 Accepted: January 12, 2016 Published: February 5, 2016 Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Data Availability Statement: Sequence data are available from the NCBI Short Read Archive. The accession number is SRP068612. Funding: This publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2273 and 11/PI/1137 and by FP7 funded CFMATTERS (Cystic Fibrosis Microbiomedetermined Antibiotic Therapy Trial in Exacerbations: Results Stratified, Grant Agreement no. 603038). The funders had no role in study design, data collection

Abstract

Rapid advancements in sequencing technologies along with falling costs present widespread opportunities for microbiome studies across a vast and diverse array of environments. These impressive technological developments have been accompanied by a considerable growth in the number of methodological variables, including sampling, storage, DNA extraction, primer pairs, sequencing technology, chemistry version, read length, insert size, and analysis pipelines, amongst others. This increase in variability threatens to compromise both the reproducibility and the comparability of studies conducted. Here we perform the first reported study comparing both amplicon and shotgun sequencing for the three leading next-generation sequencing technologies. These were applied to six human stool samples using Illumina HiSeq, MiSeq and Ion PGM shotgun sequencing, as well as amplicon sequencing across two variable 16S rRNA gene regions. Notably, we found that the factor responsible for the greatest variance in microbiota composition was the chosen methodology rather than the natural inter-individual variance, which is commonly one of the most significant drivers in microbiome studies. Amplicon sequencing suffered from this to a large extent, and this issue was particularly apparent when the 16S rRNA V1-V2 region amplicons were sequenced with MiSeq. Somewhat surprisingly, the choice of taxonomic binning software for shotgun sequences proved to be of crucial importance with even greater discriminatory power than sequencing technology and choice of amplicon. Optimal N50 assembly values for the HiSeq was obtained for 10 million reads per sample, whereas the applied MiSeq and PGM sequencing depths proved less sufficient for shotgun sequencing of stool samples. The latter technologies, on the other hand, provide a better basis for functional gene categorisation, possibly due to their longer read lengths. Hence, in addition to highlighting methodological biases, this study demonstrates the risks associated with comparing data generated using different strategies. We also recommend that laboratories with particular interests in certain microbes s

Share

COinS