Background & Objectives
The overall objective of the proposed research was to design and validate an innovative biomarker for the rapid and sensitive prediction of toxic algal blooms in Lake Erie area. PCR-based molecular methods have recently raised high interest for the detection of toxic cyanobacteria. Current PCR and qPCR methods for the detection of bloom-forming cyanobacteria are based on the detection of genes – i.e., DNA –, which allows the detection of algal cells, but does not inform on the active expression of cyanotoxin synthase genes and/or the occurrence of associated toxic blooms. The innovative character of the proposed research relies on the design of molecular biomarkers based on the detection of cyanotoxin synthetase transcripts – i.e., messenger RNAs (mRNAs) – using reverse-transcription real-time PCR (RTqPCR). The proposed biomarkers will constitute a powerful measurement tool to predict harmful bloom development and toxin production. The proposed research involved three major technical objectives:
1. To design a molecular bioassay for the prediction of toxic algal blooms based on detection of cyanotoxin synthetase expression using reverse-transcription real-time PCR (RT-qPCR).
2. To validate the molecular bioassay by comparing the levels of cyanotoxin synthetase transcripts in algal cells with the cyanotoxin levels in water in the Lake Erie area.
3. To establish correlations between algal blooms – assessed by the abundance of cyanotoxin synthetase transcripts – and water quality parameters in impacted waters in Lake Erie area, including nutrient level, alkalinity, temperature, etc.
Over 70 water and algal samples were collected from different locations in the Erie Presque Isle area during the summer and fall 2015, 2016, and 2017. Because of concerns about the samples preservation, samples collected in 2015 and some samples collected in 2016 were not processed. A single sample collected in 2017 included significant and visible algal mat. Low algal biomass was collected from other samples using filtration. In many cases, analyses of samples could not be fully performed because of the absence or very low algal biomass collected during the sampling campaigns.
Design & Validation of the Molecular Bioassay
Selected algal samples collected in 2016 were used for the extracting DNA and RNA and validating the PCR-amplification of cyanotoxin synthetase genes and transcripts. Primer sequences were retrieved from the literature. Based on the qualitative (real-time PCR–qPCR amplification plots) and qualitative analysis (qPCR melting curves) of the results obtained with the different primer combinations tested, we selected the primer pairs, mcyE-F2a and MicmcyE-R8 (referred to as mcyE-MicmcyE thereafter) and mcyE-F and mcyE-R (referred to as mcyE thereafter) for the detection/quantification of the microcystin synthase signal. Universal 16S rDNA primers (referred to as 16S thereafter) were tested and chosen for the normalization the microcystin synthase signal.
Biochemical Analysis of Cyanotoxins
The biochemical detection of cyanotoxins in both water and algal samples was performed using the Microcystins-ADDA ELISA (Enzo Life Sciences) system, which has the advantage to be able to detect simultaneously microcystins and nodularins. The standard curves obtained were satisfactory with R2 ranging from 0.96 to 0.99. However, the measured concentrations of the controls were sometimes significantly different from the nominal values (by 5 to 12%) and/or associated with high standard deviations.
The concentration of cyanotoxin in algal biomass collected in August 19 and 29, 2016 at the Marina Gas Dock and Marina Piers ranged from 7.42 to 24.29 ppb (part per billion or μg/L). The concentration of cyanotoxin in September 19, 2016 samples from the Marina Gas Dock were much higher and ranged from 229 to 416 ppb.
No significant biomass could be collected during the summer 2017 for cyanotoxin analysis using ELISA. Cyanotoxin was then analyzed in the bulk water collected at the sites (Marina Gas Dock 1 & 2, Marina Pier 3 & 6, Ferry Landing, and Vista). Analyses revealed cyanotoxin concentrations ranging from 11.14 to 14.66 ppb in June 22, 2017 samples and from 19.26 to 27.43 ppb in October 5, 2017 samples.
Reverse-Transcription Real-Time PCR
RT-qPCR for detection of cyanotoxin synthetase mRNAs was performed for six samples from two sites (Marina Pier 2 & 3) collected in the summer 2016. (Not enough biomass and/or RNA could be obtained from other sites). RT-qPCR results showed clear amplification signals with the primer pairs, mcyE MicmcyE, mcyE, and 16S. No significant differences were observed between samples collected from the two sites. Examination of the melting curves revealed single narrow peaks with mcyE-MicmcyE, mcyE, and 16S primers, confirming the specificity of the amplification.
RT-qPCR results obtained with algal samples from June 22, 2017 (Marina Gas Dock 1 & 2, Marina Pier 3 & 6, and Vista) produced low intensity signals only when using the primers mcyE and 16S. Examination of the melting curves revealed multiple peaks indicating non-specific amplification. Low amplification plots associated with non-specific amplification indicates low quality and/or quantity of the nucleic acid material extracted from the collected biomass. This observation is consistent with the low cyanotoxin levels and absence of algal biomass observed in the water.
RT-qPCR results obtained with algal samples from October 5, 2017 (same sites as June 22) produced clear and strong signals using the primers mcyE, mcyE-MicmcyE, and 16S. Significantly higher signals were observed from Marina Gas Dock 1 & 2. Examination of the melting curves revealed single peaks with all primers, mcyE-MicmcyE, mcyE, and 16S, indicating specific amplification.
Water Quality Analysis
Water quality analysis of samples collected in 2016 showed generally low phosphorous and ammonia concentrations. High levels of total nitrogen, chemical oxygen demand (COD), and total solids were recorded. Suspended solids were low, as reflected by the low turbidity levels.
Water quality analysis of samples collected in June 22, 2017 showed generally low conductivity, turbidity, and dissolved solids. Nitrogen and phosphorous were also low, indicating low potential for eutrophication and algal blooms, which indeed were not observed at the time of sampling. Dissolved oxygen (DO) was low at Marina Gas Dock 1. We also noticed a low turbidity at Ferry, from which no significant biomass could be collected.
In October 5, 2017 samples, conductivity, dissolved solids, and salinity were generally low. pH was low at Gas Dock 1 site. Nitrogen was higher at the four Marina sites (confined area) than Ferry and Vista sites. Phosphorous was also higher at the Gas Dock sites. COD was much higher at Gas Dock 1 site. The higher nutrient and COD levels and low pH observed at Gas Dock 1 may be related to the high algal biomass detected at that site. Ferry and Vista sites, which are located outside the marina area, showed lower nutrient levels. Generally speaking, nutrient analyses performed in October 2017 showed higher numbers than in June 2017, which was especially true for samples collected at the Marina.
Correlation between Cyanotoxins Concentration, cyanotoxin synthase transcripts, and water quality parameters
All parameters measured during the 2017 sampling campaigns were analyzed for potential correlations by generating a correlation matrix (Pearson's correlation coefficients r and pvalues). No significant correlations were observed between cyanotoxin synthase transcripts (RT-qPCR) and cyanotoxin in water (ELISA) – or any other water quality parameters (r < 0.4, p > 0.05). On the other hand, significant correlations were observed between cyanotoxin in water (ELISA) and some water quality parameters, such as temperature (r = -0.84, p < 0.05) and nitrate (r = 0.82, p < 0.05). High temperatures may have resulted in faster degradation of cyanotoxins. The positive correlation between cyanotoxin and nitrate may indicate higher abundance of cyanobacteria when nutrients were higher. Other significant correlations were observed between several water quality parameters, such as pH and oxidation-reduction potential (r = -0.99, p < 0.05), total dissolved solid and conductivity (r = 0.99, p < 0.05), total nitrogen and nitrate (r = 0.89, p < 0.05), ammonia and nitrate (r = -0.76, p < 0.05), temperature and ammonia (r = 0.87, p < 0.05) and nitrate (r = -0.91, p < 0.05), and total phosphorous and chemical oxygen demand (r = 0.97, p < 0.05).