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Strengths and Limitations of 16S rRNA Gene Amplicon Sequencing in Revealing Temporal Microbial Community Dynamics
Open accessAbstract
This study explored the short-term planktonic microbial community structure and resilience in Lake Lanier (GA, USA) while simultaneously evaluating the technical aspects of identifying taxa via 16S rRNA gene amplicon and metagenomic sequence data. 16S rRNA gene amplicons generated from four temporally discrete samples were sequenced with 454 GS-FLX-Ti yielding ∼40,000 rRNA gene sequences from each sample and representing ∼300 observed OTUs. Replicates obtained from the same biological sample clustered together but several biases were observed, linked to either the PCR or sequencing-preparation steps. In comparisons with companion whole-community shotgun metagenome datasets, the estimated number of OTUs at each timepoint was concordant, but 1.5 times and ∼10 times as many phyla and genera, respectively, were identified in the metagenomes. Our analyses showed that the 16S rRNA gene captures broad shifts in community diversity over time, but with limited resolution and lower sensitivity compared to metagenomic data. We also identified OTUs that showed marked shifts in abundance over four close timepoints separated by perturbations and tracked these taxa in the metagenome vs. 16S rRNA amplicon data. A strong summer storm had less of an effect on community composition than did seasonal mixing, which revealed a distinct succession of organisms. This study provides insights into freshwater microbial communities and advances the approaches for assessing community diversity and dynamics in situ.
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“Such hypervariable genes or regions permit identification of microbial community members but can be limited in their capacity to resolve phylogenetically related species or strains and do not provide information on functional gene content of the microbial members present.72”
From The oral microbiome: Role of key organisms and complex networks in oral health and disease (2021) · cites this paper as [72]
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Additional file 1 of Differential richness inference for 16S rRNA marker gene surveys
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Additional file 5 of Differential richness inference for 16S rRNA marker gene surveys
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Additional file 4 of Differential richness inference for 16S rRNA marker gene surveys
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Additional file 3 of Differential richness inference for 16S rRNA marker gene surveys
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Additional file 7 of Differential richness inference for 16S rRNA marker gene surveys
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Additional file 6 of Differential richness inference for 16S rRNA marker gene surveys
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Metadata
- Authors
- Poretsky, R., Rodriguez-R, L. M., Luo, C., Tsementzi, D., & Konstantinidis, K. T.
- Affiliations
- Georgia Institute of Technology (US)
- Corresponding author
- Poretsky, Rachel
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2014-04-08
- Volume
- 9
- Issue
- 4
- Pages
- e93827
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3979728
- OpenAlex
- W2019163239
- Cited by
- 684
- References
- 63
- Citations by year
- 2026: 50 · 2025: 70 · 2024: 45 · 2023: 78 · 2022: 71 · 2021: 83 · 2020: 69 · 2019: 67 · 2018: 62 · 2017: 37 · 2016: 29 · 2015: 20 · 2014: 2
- FWCI
- 25.43
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Science Foundation (1241046)
- U.S. Department of Energy (DESC0006662)
- Emory University
- Topics
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Physical Sciences › Environmental Science › Ecology › Environmental DNA in Biodiversity Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- 16S rRNA gene amplicon sequencing, metagenomics, planktonic microbial communities, freshwater microbial communities, Lake Lanier, community resilience, sequencing bias, PCR bias, seasonal mixing, storm disturbance, microbial succession, community diversity
- MeSH terms
- Bacteria, Fresh Water, Plankton, RNA, Ribosomal, 16S, Metagenome, Metagenomics
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