Identifying Microbial Biomarkers for Early Detection and Health Diagnosis of Harmful Algal Blooms in Freshwater Lakes
Start Date
23-5-2022 5:45 PM
End Date
23-5-2022 7:00 PM
Abstract
Harmful algal blooms (HABs) have been a very common phenomenon in the last few decades, intensified by global warming, eutrophication, and increased CO2 levels. We hypothesized that biological and chemical parameters will be available allowing early detection of HABs in coherence with microbial signatures, where the health status of the HABs could be indicated by lysis of cyanobacterial cells and release of intracellular materials. Using multi-omics and quantitative real-time PCR, we investigated applicability of microbial signatures as a prognostic tool towards determining bloom health in two Ohio lakes, Lake Erie (LE) and Grand Lake St. Marys (SM), by assessing with chemical data. Different cyanobacterial species dominated algal blooms at LE (Synechococcus and Microcystis) and SM (Dolichospermum and Planktothrix) in the year 2021. Unbound phycocyanin levels were positively correlated with the quantity of cyanobacterial 16S rRNA genes in both LE and SM, with varied strength of correlations, indicating unhealthy cyanobacterial cells being present during the bloom. Genera Pseudomonas and Sediminibacterium as well as the phylum Verrucomicrobia appeared as potential microbial signatures when investigated with relative abundance of cyanobacteria. These signatures are promising to be established and validated as biomarkers for early detection of HABs while integrated with functional gene quantification.
Identifying Microbial Biomarkers for Early Detection and Health Diagnosis of Harmful Algal Blooms in Freshwater Lakes
Harmful algal blooms (HABs) have been a very common phenomenon in the last few decades, intensified by global warming, eutrophication, and increased CO2 levels. We hypothesized that biological and chemical parameters will be available allowing early detection of HABs in coherence with microbial signatures, where the health status of the HABs could be indicated by lysis of cyanobacterial cells and release of intracellular materials. Using multi-omics and quantitative real-time PCR, we investigated applicability of microbial signatures as a prognostic tool towards determining bloom health in two Ohio lakes, Lake Erie (LE) and Grand Lake St. Marys (SM), by assessing with chemical data. Different cyanobacterial species dominated algal blooms at LE (Synechococcus and Microcystis) and SM (Dolichospermum and Planktothrix) in the year 2021. Unbound phycocyanin levels were positively correlated with the quantity of cyanobacterial 16S rRNA genes in both LE and SM, with varied strength of correlations, indicating unhealthy cyanobacterial cells being present during the bloom. Genera Pseudomonas and Sediminibacterium as well as the phylum Verrucomicrobia appeared as potential microbial signatures when investigated with relative abundance of cyanobacteria. These signatures are promising to be established and validated as biomarkers for early detection of HABs while integrated with functional gene quantification.