Sample Preservation, DNA or RNA Extraction and Data Analysis for High-Throughput Phytoplankton Community Sequencing

Area of Science:

• Aquatic Ecology
• Molecular Biology
• Environmental Science

Background:

• Phytoplankton are crucial primary producers and indicators of water quality.
• Traditional phytoplankton analysis via microscopy is time-consuming and subjective.
• Next-generation sequencing (NGS) presents an opportunity for automated and rapid phytoplankton assessment.

Purpose of the Study:

• To evaluate the impact of different preservation, nucleic acid extraction, and data analysis methods on NGS-based phytoplankton studies.
• To identify challenges and biases in DNA-based versus RNA-based phytoplankton analysis.
• To determine the most reliable method for quantitative phytoplankton assessment using NGS.

Main Methods:

• A mock community of phytoplankton species with varying cell wall hardness and nucleus size was used.
• Two phytoplankton preservation methods, three DNA extraction kits, three RNA extraction methods, and two data analysis procedures were tested.
• 18S rRNA gene sequencing was employed for both DNA and RNA analysis.

Main Results:

• DNA-based 18S rRNA gene sequencing was significantly affected by rRNA gene copy number variation, preservation, and extraction methods.
• Bioinformatic biases were observed with sliding-window quality trimming on Ion Torrent data.
• RNA-based analysis showed less variation across extraction methods and correlated better with biomass, dry weight, and carbon content.

Conclusions:

• DNA-based phytoplankton analysis using 18S rRNA gene sequencing faces critical challenges and biases.
• RNA-based analysis is more robust and recommended for quantitative phytoplankton studies due to better correlation with biomass.
• Optimized protocols for sample preservation and nucleic acid extraction are crucial for reliable NGS-based phytoplankton monitoring.