A quantitative real-time PCR assay for the identification and enumeration of Alexandrium cysts in marine sediments

Harmful algal blooms (HABs) are a global problem that affects both human and ecosystem health. One of the most serious and widespread HAB poisoning syndromes is paralytic shellfish poisoning, commonly caused by Alexandrium spp. dinoflagellates. Like many toxic dinoflagellates, Alexandrium produces resistant resting cysts as part of its life cycle. These cysts play a key role in bloom initiation and decline, as well as dispersal and colonization of new areas. Information on cyst numbers and identity is essential for understanding and predicting blooms, yet comprehensive cyst surveys are extremely time- and labor-intensive. Here we describe the development and validation of a quantitative real-time PCR (qPCR) technique for the enumeration of cysts of A. tamarense of the toxic North American/Group I ribotype. The method uses a cloned fragment of the large subunit ribosomal RNA gene as a standard for cyst quantification, with an experimentally determined conversion factor of 28,402±6152 LSU ribosomal gene copies per cyst. Tests of DNA extraction and PCR efficiency show that mechanical breakage is required for adequate cyst lysis, and that it was necessary to dilute our DNA extracts 50-fold in order to abolish PCR inhibition from compounds co-extracted from the sediment. The resulting assay shows a linear response over 6 orders of magnitude and can reliably quantify ≥10 cysts/cm3 sediment. thod validation, 129 natural sediment samples were split and analyzed in parallel, using both the qPCR and primulin-staining techniques. Overall, there is a significant correlation (p<0.001) between the cyst abundances determined by the two methods, although the qPCR counts tend to be lower than the primulin values. This underestimation is less pronounced in those samples collected from the top 1 cm of sediment, and more pronounced in those derived from the next 1–3 cm of the core. These differences may be due to the condition of the cysts in the different layers, as the top 1 cm contains more recent cysts while those in the next 1–3 cm may have been in the sediments for many years. Comparison of the cyst densities obtained by both methods shows that a majority (56.6%) of the values are within a two-fold range of each other and almost all of the samples (96.9%) are within an order of magnitude. Thus, the qPCR method described here represents a promising alternative to primulin-staining for the identification and enumeration of cysts. The qPCR method has a higher throughput, enabling the extraction and assay of 24 samples in the time required to process and count 8–10 samples by primulin-staining. Both methods require prior expertise, either in taxonomy or molecular biology. Fewer person-hours per sample are required for qPCR, but primulin-staining has lower reagent costs. The qPCR method might be more desirable for large-scale cyst mapping, where large numbers of samples are generated and a higher sample analysis rate is necessary. While the qPCR and primulin-staining methods generate similar data, the choice of counting method may be most influenced by the practical issue of the different relative costs of labor and materials between the two methods.