Principal Investigator: 
Benoit VanAken (bvanaken@temple.edu)
Institution: 
Temple University
Bloom-forming cyanobacteria release powerful toxins in recreation waters and power supplies, potentially imposing serious hazard to human health and the environment. Conventional diagnostic methods for toxic cyanobacteria, including morphological cell identification (microscopy), analytical detection of cyanotoxins (LC/MALDI-TOF/MS), and biochemical assays (ELISA) are not fully satisfactory, as they are either inaccurate or expensive and time-consuming. Following the recent identification of cyanotoxin synthetase gene clusters, e.g., microcystin (mcy) and nodularin (nda), molecular methods based on PCR and quantitative PCR (qPCR) have been developed, which are extremely sensitive, specific, rapid, and relatively inexpensive. However, these PCR methods are based on the detection of genes – i.e., DNA –, which does not allow detecting active cyanotoxin gene expression and associated toxic blooms.  The synthesis of toxins during cyanobacterium blooms is initiated by the transcription of cyanotoxin synthetase genes, which is induced by environmental and/or cellular conditions. In this application, we propose to develop molecular biomarkers based on the detection of cyanotoxin synthetase transcripts – i.e., messenger RNAs (mRNAs) – using reverse-transcription real-time PCR (RT-qPCR). This approach will target gene expression and active cyanotoxin production, which will then allow predicting the onset of toxic algal blooms.  The objectives of this project are to 1) design a bioassay for the reverse-transcription (RT) of selected cyanotoxins synthetase mRNAs and the detection/quantification of corresponding complementary DNAs (cDNAs) using qPCR; 2) validate the molecular bioassay by comparison with existing cyanotoxin biochemical assays (e.g., ELISA) using algal and water samples collected during toxic bloom events in Lake Erie area; and establish correlations between cyanotoxin synthetase gene activity and water quality parameters in impacted watersheds, including nutrient level, alkalinity, temperature, etc.

 

Research Year: 
2016
Funding Amount: 
$45,424
Current or Past research?: 
Current Research

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