A comparison of sequencing platforms and bioinformatics pipelines for compositional analysis of the gut microbiome
Open accessAbstract
BACKGROUND: Advancements in Next Generation Sequencing (NGS) technologies regarding throughput, read length and accuracy had a major impact on microbiome research by significantly improving 16S rRNA amplicon sequencing. As rapid improvements in sequencing platforms and new data analysis pipelines are introduced, it is essential to evaluate their capabilities in specific applications. The aim of this study was to assess whether the same project-specific biological conclusions regarding microbiome composition could be reached using different sequencing platforms and bioinformatics pipelines. RESULTS: Chicken cecum microbiome was analyzed by 16S rRNA amplicon sequencing using Illumina MiSeq, Ion Torrent PGM, and Roche 454 GS FLX Titanium platforms, with standard and modified protocols for library preparation. We labeled the bioinformatics pipelines included in our analysis QIIME1 and QIIME2 (de novo OTU picking [not to be confused with QIIME version 2 commonly referred to as QIIME2]), QIIME3 and QIIME4 (open reference OTU picking), UPARSE1 and UPARSE2 (each pair differs only in the use of chimera depletion methods), and DADA2 (for Illumina data only). GS FLX+ yielded the longest reads and highest quality scores, while MiSeq generated the largest number of reads after quality filtering. Declines in quality scores were observed starting at bases 150-199 for GS FLX+ and bases 90-99 for MiSeq. Scores were stable for PGM-generated data. Overall microbiome compositional profiles were comparable between platforms; however, average relative abundance of specific taxa varied depending on sequencing platform, library preparation method, and bioinformatics analysis. Specifically, QIIME with de novo OTU picking yielded the highest number of unique species and alpha diversity was reduced with UPARSE and DADA2 compared to QIIME. CONCLUSIONS: The three platforms compared in this study were capable of discriminating samples by treatment, despite differences in diversity and abundance, leading to similar biological conclusions. Our results demonstrate that while there were differences in depth of coverage and phylogenetic diversity, all workflows revealed comparable treatment effects on microbial diversity. To increase reproducibility and reliability and to retain consistency between similar studies, it is important to consider the impact on data quality and relative abundance of taxa when selecting NGS platforms and analysis tools for microbiome studies.
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Bias can be introduced throughout all stages of sample processing, including selection of sample collection protocol, preservative choice, storage temperature, DNA extraction protocol, library preparation, sequencing platform, and bioinformatics analysis pipeline.
“Bias can be introduced throughout all stages of sample processing, including the selection of sample collection protocol, preservative choice, storage temperature, DNA extraction protocol, library preparation, sequencing platform, and bioinformatics analysis pipeline.720–723”
From Microbiota–gut–brain axis and its therapeutic applications in neurodegenerative diseases (2024) · cites this paper as [720]
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Osteoarthritis induced by destabilization of the medial meniscus is reduced in germ-free mice
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Rabbit Microbiota Changes Throughout the Intestinal Tract
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Characterizing the Composition of the Pediatric Gut Microbiome: A Systematic Review
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Searching for a Consensus Among Inflammatory Bowel Disease Studies: A Systematic Meta-Analysis
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Microbiome Changes during Regenerative Endodontic Treatment Using Different Methods of Disinfection
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Differential Expression Analysis of RNA-seq Reads: Overview, Taxonomy, and Tools
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The promise and challenge of cancer microbiome research
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Unveiling the Human Gastrointestinal Tract Microbiome: The Past, Present, and Future of Metagenomics
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The Microbiome as a Maternal Effect: A Systematic Review on Vertical Transmission of Microbiota
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Exploring Cereal Metagenomics: Unravelling Microbial Communities for Improved Food Security
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Association of upper airway bacterial microbiota and asthma: systematic review
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Insufficient sampling constrains our characterization of plant microbiomes
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- Authors
- Allali, I., Arnold, J. W., Roach, J., Cadenas, M. B., Butz, N., Hassan, H. M., Koci, M., Ballou, A., Mendoza, M., Ali, R., & Azcarate-Peril, M. A.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- North Carolina State University (US)
- ORCID
- Venue
- BMC Microbiology
- Published
- 2017-09-13
- Volume
- 17
- Issue
- 1
- Pages
- 194-194
- ISSN
- 1471-2180 (ISSN-L)
- PMC
- PMC5598039
- OpenAlex
- W2754041971
- Cited by
- 298
- References
- 73
- Citations by year
- 2026: 32 · 2025: 22 · 2024: 40 · 2023: 27 · 2022: 35 · 2021: 48 · 2020: 40 · 2019: 30 · 2018: 21 · 2017: 3
- FWCI
- 10.49
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- BMC Microbiology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- U.S. Department of Agriculture (2012-68003-19621)
- National Institute of Diabetes and Digestive and Kidney Diseases (P30 DK34987)
- Fulbright Commission
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Keywords
- gut microbiota, 16S rRNA amplicon sequencing, sequencing platform comparison, bioinformatics pipeline comparison, QIIME, DADA2, library preparation, alpha diversity, reproducibility, Ion Torrent PGM, Illumina MiSeq
- MeSH terms
- Gastrointestinal Microbiome, Analysis of Variance, Animals, Bacteria, Base Sequence, Cecum, Chickens, DNA, Bacterial, Phylogeny, RNA, Ribosomal, 16S, Statistics as Topic, Reproducibility of Results, Gene Library, Multivariate Analysis, Computational Biology, Biodiversity, Microbial Consortia, High-Throughput Nucleotide Sequencing
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