Dataset Information

Predicting blooms of toxic cyanobacteria in eutrophic lakes with diverse cyanobacterial communities.

ABSTRACT: We investigated possibility of predicting whether blooms, if they occur, would be formed of microcystin-producing cyanobacteria. DGGE analysis of 16S-ITS and mcyA genes revealed that only Planktothrix and Microcystis possessed mcy-genes and Planktothrix was the main microcystin producer. qPCR analysis revealed that the proportion of cells with mcy-genes in Planktothrix populations was almost 100%. Microcystin concentration correlated with the number of potentially toxic and total Planktothrix cells and the proportion of Planktothrix within all cyanobacteria, but not with the proportion of cells with mcy-genes in total Planktothrix. The share of Microcystis cells with mcy-genes was low and variable in time. Neither the number of mcy-possessing cells, nor the proportion of these cells in total Microcystis, correlated with the concentration of microcystins. This suggests that it is possible to predict whether the bloom in the Masurian Lakes will be toxic based on Planktothrix occurrence. Two species of toxin producing Planktothrix, P. agardhii and P. rubescens, were identified by phylogenetic analysis of 16S-ITS. Based on morphological and ecological features, the toxic Planktothrix was identified as P. agardhii. However, the very high proportion of cells with mcy-genes suggests P. rubescens. Our study reveals the need of universal primers for mcyA genes from environment.

SUBMITTER: Bukowska A

PROVIDER: S-EPMC5566422 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Predicting blooms of toxic cyanobacteria in eutrophic lakes with diverse cyanobacterial communities.

Bukowska Aleksandra A Kaliński Tomasz T Koper Michał M Kostrzewska-Szlakowska Iwona I Kwiatowski Jan J Mazur-Marzec Hanna H Jasser Iwona I

Scientific reports 20170821 1

We investigated possibility of predicting whether blooms, if they occur, would be formed of microcystin-producing cyanobacteria. DGGE analysis of 16S-ITS and mcyA genes revealed that only Planktothrix and Microcystis possessed mcy-genes and Planktothrix was the main microcystin producer. qPCR analysis revealed that the proportion of cells with mcy-genes in Planktothrix populations was almost 100%. Microcystin concentration correlated with the number of potentially toxic and total Planktothrix ce ...[more]

PMID: 28827675

Similar Datasets

Project description:Fresh-water sources of drinking water are experiencing toxic cyanobacterial blooms more frequently. Chemical oxidation is a common approach to treat cyanobacteria and their toxins. This study systematically investigates the bacterial/cyanobacterial community following chemical oxidation (Cl2, KMnO4, O3, H2O2) using high throughput sequencing. Raw water results from high throughput sequencing show that Proteobacteria, Actinobacteria, Cyanobacteria and Bacteroidetes were the most abundant phyla. Dolichospermum, Synechococcus, Microcystis and Nostoc were the most dominant genera. In terms of species, Dolichospermum sp.90 and Microcystis aeruginosa were the most abundant species at the beginning and end of the sampling, respectively. A comparison between the results of high throughput sequencing and taxonomic cell counts highlighted the robustness of high throughput sequencing to thoroughly reveal a wide diversity of bacterial and cyanobacterial communities. Principal component analysis of the oxidation samples results showed a progressive shift in the composition of bacterial/cyanobacterial communities following soft-chlorination with increasing common exposure units (CTs) (0-3.8 mg·min/L). Close cyanobacterial community composition (Dolichospermum dominant genus) was observed following low chlorine and mid-KMnO4 (287.7 mg·min/L) exposure. Our results showed that some toxin producing species may persist after oxidation whether they were dominant species or not. Relative persistence of Dolichospermum sp.90 was observed following soft-chlorination (0.2-0.6 mg/L) and permanganate (5 mg/L) oxidation with increasing oxidant exposure. Pre-oxidation using H2O2 (10 mg/L and one day contact time) caused a clear decrease in the relative abundance of all the taxa and some species including the toxin producing taxa. These observations suggest selectivity of H2O2 to provide an efficient barrier against toxin producing cyanobacteria entering a water treatment plant.

Project description:Harmful algal blooms threaten the water quality of many eutrophic and hypertrophic lakes and cause severe ecological and economic damage worldwide. Dense blooms often deplete the dissolved CO2 concentration and raise pH. Yet, quantitative prediction of the feedbacks between phytoplankton growth, CO2 drawdown and the inorganic carbon chemistry of aquatic ecosystems has received surprisingly little attention. Here, we develop a mathematical model to predict dynamic changes in dissolved inorganic carbon (DIC), pH and alkalinity during phytoplankton bloom development. We tested the model in chemostat experiments with the freshwater cyanobacterium Microcystis aeruginosa at different CO2 levels. The experiments showed that dense blooms sequestered large amounts of atmospheric CO2, not only by their own biomass production but also by inducing a high pH and alkalinity that enhanced the capacity for DIC storage in the system. We used the model to explore how phytoplankton blooms of eutrophic waters will respond to rising CO2 levels. The model predicts that (1) dense phytoplankton blooms in low- and moderately alkaline waters can deplete the dissolved CO2 concentration to limiting levels and raise the pH over a relatively wide range of atmospheric CO2 conditions, (2) rising atmospheric CO2 levels will enhance phytoplankton blooms in low- and moderately alkaline waters with high nutrient loads, and (3) above some threshold, rising atmospheric CO2 will alleviate phytoplankton blooms from carbon limitation, resulting in less intense CO2 depletion and a lesser increase in pH. Sensitivity analysis indicated that the model predictions were qualitatively robust. Quantitatively, the predictions were sensitive to variation in lake depth, DIC input and CO2 gas transfer across the air-water interface, but relatively robust to variation in the carbon uptake mechanisms of phytoplankton. In total, these findings warn that rising CO2 levels may result in a marked intensification of phytoplankton blooms in eutrophic and hypertrophic waters.

Dataset Information

Predicting blooms of toxic cyanobacteria in eutrophic lakes with diverse cyanobacterial communities.

Publications

Predicting blooms of toxic cyanobacteria in eutrophic lakes with diverse cyanobacterial communities.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure