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

Abstract

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 ≥10cysts/cc sediment.For method 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 1cm contains more recent cysts while those in the next 1-3cm 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.

Fig. 1

Comparison of different methods for cyst DNA extraction. Replicate samples of approximately 800 cysts were extracted using the DNEasy Tissue Kit or QIAmp Stool DNA kit, with or without mechanical breakage (bead-beating). Extraction efficiency was assessed based on (A) the total amount of DNA recovered and (B) the extent of amplification by real-time PCR (as a proxy for the number of ribosomal RNA gene copies recovered).

Fig. 2

Inhibition of PCR by sediment DNA extracts. DNA was extracted from field-collected sediment samples, and added to a qPCR reaction containing pUC plasmid DNA as a target. Sample DNA was added at (A) full strength, 2-fold, 5-fold, or 10-fold dilution and (B) 20-fold, 50-fold or 100-fold dilution. In (B), “mb” indicates that the extract was cleaned using the MoBio cleanup kit, and “etoh” indicates that the extract was ethanol precipitated before the assay. PCR inhibition was indicated by an increase in reaction C_t relative to the pUC only control, which had no added sample DNA.

Fig. 3

Representative qPCR standard curve. Standard curves were constructed from serial dilutions of a plasmid containing a cloned fragment of the large subunit ribosomal RNA gene of A. tamarense. Reaction efficiencies ranged from 86–100% over all runs. The lowest target copy number tested was 520 copies per reaction, which corresponds to a detection limit of 10 cysts/cc in a standard sample volume of 4cc.

Fig. 4

Comparison of PCR and microscope methods for cyst enumeration. A total of 129 field-collected sediment samples were processed, split, and analyzed in parallel using both the qPCR and primulin staining/microscopy methods. The solid line and equation are the best linear curve fit to the data. The cyst values calculated from the two methods are significantly correlated (p<0.001).

Fig. 5

Comparison of PCR and microscope methods for samples collected at different sediment depths. The samples shown in Figure 4 are compared separately based upon the sediment depth at which the sample was collected. (A) 70 samples were analyzed from the top 1cm of sediment and (B) 59 samples were derived from the 1–3cm depth. The solid lines and equations are the best linear curve fit to the data. The cyst values calculated from the two methods are significantly correlated (p<0.005).

Fig. 6

Comparison of the cyst counts obtained by the qPCR and primulin-staining/microscopy methods. The extent of variation between the methods was assessed by calculating the ratio of cysts/cc determined by primulin-staining to the cysts/cc calculated by the qPCR method. For example, a ratio of 0.5–2.0 corresponds to ≤ 2-fold difference in values between the two methods. The data are shown as the percent of total samples within the given ratio range.