Watson, S. B. | bioRxiv Science

bioRxiv2019

Rapid assessment of phytoplankton assemblages using Next Generation Sequencing - Barcode of Life database: a widely applicable toolkit to monitor biodiversity and harmful algal blooms (HABs)

Harmful algal blooms have important implications for the health, functioning and services of aquatic ecosystems. Our ability to detect and monitor these events is often challenged by the lack of rapid and cost-effective methods to identify bloom-forming organisms and their potential for toxin production, Here, we developed and applied a combination of DNA barcoding and Next Generation Sequencing (NGS) for the rapid assessment of phytoplankton community composition with focus on two important indicators of ecosystem health: toxigenic bloom-forming cyanobacteria and impaired planktonic biodiversity. To develop this molecular toolset for identification of cyanobacterial and algal species present in HABs (Harmful Algal Blooms), hereafter called HAB-ID, we optimized NGS protocols, applied a newly developed bioinformatics pipeline and constructed a BOLD (Barcode of Life Data System) 16S reference database from cultures of 203 cyanobacterial and algal strains representing 101 species with particular focus on bloom and toxin producing taxa. Using the new reference database of 16S rDNA sequences and constructed mock communities of mixed strains for protocol validation we developed new NGS primer set which can recover 16S from both cyanobacteria and eukaryotic algal chloroplasts. We also developed DNA extraction protocols for cultured algal strains and environmental samples, which match commercial kit performance and offer a cost-efficient solution for large scale ecological assessments of harmful blooms while giving benefits of reproducibility and increased accessibility. Our bioinformatics pipeline was designed to handle low taxonomic resolution for problematic genera of cyanobacteria such as the Anabaena-Aphanizomenon-Dolichospermum species complex, two clusters of Anabaena (I and II), Planktothrix and Microcystis. This newly developed HAB-ID toolset was further validated by applying it to assess cyanobacterial and algal composition in field samples from waterbodies with recurrent HABs events.

molecular biology↗

bioRxiv2019

Large increases in emissions of methane and nitrous oxide from eutrophication in Lake Erie

Eutrophication is linked to greenhouse gas emissions from inland waters. Phytoplankton blooms in Lake Erie, one of Earths largest lakes, have increased with nutrient runoff linked to climate warming, although greenhouse gas emissions from this or other large eutrophic lakes are not well characterized. We measured greenhouse gases around Lake Erie in all four seasons and found that CH4 and N2O emissions have increased 10 times or more with re-eutrophication, especially during and after phytoplankton blooms. Lake Erie is a positive source of CH4 throughout the entire year and around the entire lake, with the highest emissions in spring and summer near the mouth of the Maumee River. While Lake Erie is an overall N2O source, it is an N2O sink in winter throughout the lake and in some locations during large phytoplankton blooms. We estimate that Lake Erie emits ~6300 metric tons of CH4-C yr-1 ({+/-} 19%) and ~600 metric tons N2O-N yr-1 ({+/-} 37%): almost 500,000 metric tons CO2-eq yr-1 total. These results highlight the gravity of eutrophication-related increases in large lake GHG emissions: an overlooked, but potentially major feedback to global climate change.

ecology↗