Effects of growth phase, diel cycle and macronutrient stress on the quantification of Heterosigma akashiwo using qPCR and SHA

Abstract

The development of molecular probe technologies over the last several decades has enabled more rapid and specific identification and enumeration of phytoplankton species compared to traditional technologies, such as light microscopy. Direct comparisons of these methods with respect to physiological status, however, are sparse. Here we directly compare quantitative real-time PCR (qPCR) and sandwich hybridization assay (SHA) for enumerating the raphidophyte Heterosigma akashiwo at several points during its growth phase, over a diel cycle and with macronutrient stress in laboratory cultures. To ensure consistency between comparisons, a single cellular homogenate was generated from each culture and split for analysis by qPCR and SHA. Since the homogenate was generated from the same number of cells during each experiment, results reflect changes in nucleic acid content (rRNA and DNA) at each time point or in response to environmental conditions relative to a reference sample. Results show a greater level of precision in SHA results which contributed to significant (2–3 fold) differences in rRNA content per cell in several of these analyses. There was significantly greater rRNA content during lag and exponential phases compared to stationary phase cultures, and a significant decrease in rRNA content during the light cycle compared to cells harvested in the dark. In contrast, there were no significant differences in DNA content per cell as determined by qPCR over a diel cycle or during different growth phases. There was also no decrease in either rRNA or DNA content for cultures under low P conditions compared to nutrient replete conditions. However, both rRNA and DNA content were significantly lower under N stress when compared to nutrient replete conditions. Results of this study suggest that growth stage, nutrient stress and cell cycle may impact molecular analyses, and that physiological status should be taken into account when using these methods for HAB monitoring.