UVM Theses and Dissertations
Format:
Print
Author:
Schuster, Lesley E.
Dept./Program:
Natural Resources
Year:
2011
Degree:
MS
Abstract:
For the last decade, Lake Champlain has experienced summer blooms of harmful cyanobacteria. Accumulations have been most dense in Missisquoi Bay, where blooms have occurred 9 of the last 10 years. The genus Microcystis is of particular concern because it produces a hepatotoxin (microcystin) that poses a threat to public health. Our data set shows that higher cell densities are not always associated with higher toxin levels. Not all cells will contain the genes necessary to produce microcystin, so as the first step to determining why some blooms are toxic and some are not, we adapted a quantitative polymerase chain reaction (qPCR) assay for Microcystis, assaying for both the MICR and mcyD genes.
Samples were collected in association with a water quality monitoring program that also analyzed microcystin and nutrient concentrations as well as other environmental characteristics. We explored both multiplex and singleplex methods of qPCR and found the singleplex method was most reliable for capturing the presence of the toxin gene in Lake Champlain. Environmental data and qPCR results were used in principal component analysis and stepwise multiple regression to explore which variables most influenced total Microcystis cell densities and toxin concentrations. Models based primarily on nutrients explained 72% of the variation in Microcystis cell density and 49% of the variation in toxin concentration. QPCR can provide a practical approach to exploring Microcystis bloom dynamics on a molecular level.
Samples were collected in association with a water quality monitoring program that also analyzed microcystin and nutrient concentrations as well as other environmental characteristics. We explored both multiplex and singleplex methods of qPCR and found the singleplex method was most reliable for capturing the presence of the toxin gene in Lake Champlain. Environmental data and qPCR results were used in principal component analysis and stepwise multiple regression to explore which variables most influenced total Microcystis cell densities and toxin concentrations. Models based primarily on nutrients explained 72% of the variation in Microcystis cell density and 49% of the variation in toxin concentration. QPCR can provide a practical approach to exploring Microcystis bloom dynamics on a molecular level.