ArticleFrontiers in microbiology2017
Sample Preservation, DNA or RNA Extraction and Data Analysis for High-Throughput Phytoplankton Community Sequencing.
Article in Frontiers in microbiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Comparing DNA metabarcoding with light microscopy to identify eukaryotic phytoplankton in the Baltic Sea, Kattegat and Skagerrak.Scientific reports · 2026Article
- From nets to networks: tools for deciphering phytoplankton metabolic interactions within communities and their global significance.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Review
- The eukaryome of modern microbialites reveals distinct colonization across aquatic ecosystems.NPJ biofilms and microbiomes · 2024Article
- Article
- Diversity, community structure, and quantity of eukaryotic phytoplankton revealed using 18S rRNA and plastid 16S rRNA genes and pigment markers: a case study of the Pearl River Estuary.Marine life science & technology · 2023Article
- Evaluating the Reproducibility of Amplicon Sequencing Data Derived from Deep-Sea Cold Seep Sediment-Associated Microbiota.Microbiology spectrum · 2023Article
- A robust approach to estimate relative phytoplankton cell abundances from metagenomes.Molecular ecology resources · 2023Article
- A metabarcode based (species) inventory of the northern Adriatic phytoplankton.Biodiversity data journal · 2023Article
- Trophic State Drives the Diversity of Protists in a Tropical River (New River, Belize).Microorganisms · 2022Article
- DNA extraction bias is more pronounced for microbial eukaryotes than for prokaryotes.MicrobiologyOpen · 2022Article
- Seasonal phytoplankton and geochemical shifts in the subsurface chlorophyll maximum layer of a dimictic ferruginous lake.MicrobiologyOpen · 2022Article
- Capturing marine microbiomes and environmental DNA: A field sampling guide.Frontiers in microbiology · 2022Review
- Preserving plant samples from remote locations for detection of RNA and DNA viruses.Frontiers in microbiology · 2022Article
- Size-Fractionated Filtration Combined with Molecular Methods Reveals the Size and Diversity of Picophytoplankton.Biology · 2021Article
- Assessing the Use of Molecular Barcoding and qPCR for Investigating the Ecology ofMicroorganisms · 2021Article
- Freshwater phytoplankton diversity: models, drivers and implications for ecosystem properties.Hydrobiologia · 2021Review
- Article
- Preserving Microbial Community Integrity in Oilfield Produced Water.Frontiers in microbiology · 2020Article
- Consistency of Targeted Metatranscriptomics and Morphological Characterization of Phytoplankton Communities.Frontiers in microbiology · 2020Article
- Everything is not everywhere: can marine compartments shape phytoplankton assemblages?Proceedings. Biological sciences · 2019Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Phytoplankton is the basis for aquatic food webs and mirrors the water quality. Conventionally, phytoplankton analysis has been done using time consuming and partly subjective microscopic observations, but next generation sequencing (NGS) technologies provide promising potential for rapid automated examination of environmental samples. Because many phytoplankton species have tough cell walls, methods for cell lysis and DNA or RNA isolation need to be efficient to allow unbiased nucleic acid retrieval. Here, we analyzed how two phytoplankton preservation methods, three commercial DNA extraction kits and their improvements, three RNA extraction methods, and two data analysis procedures affected the results of the NGS analysis. A mock community was pooled from phytoplankton species with variation in nucleus size and cell wall hardness. Although the study showed potential for studying Lugol-preserved sample collections, it demonstrated critical challenges in the DNA-based phytoplankton analysis in overall. The 18S rRNA gene sequencing output was highly affected by the variation in the rRNA gene copy numbers per cell, while sample preservation and nucleic acid extraction methods formed another source of variation. At the top, sequence-specific variation in the data quality introduced unexpected bioinformatics bias when the sliding-window method was used for the quality trimming of the Ion Torrent data. While DNA-based analyses did not correlate with biomasses or cell numbers of the mock community, rRNA-based analyses were less affected by different RNA extraction procedures and had better match with the biomasses, dry weight and carbon contents, and are therefore recommended for quantitative phytoplankton analyses.
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