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An Improved Quantitative Real-Time PCR Assay for the Enumeration of Heterosigma akashiwo (Raphidophyceae) Cysts Using a DNA Debris Removal Method and a Cyst-Based Standard Curve.

Authors :
Kim JH
Kim JH
Wang P
Park BS
Han MS
Source :
PloS one [PLoS One] 2016 Jan 07; Vol. 11 (1), pp. e0145712. Date of Electronic Publication: 2016 Jan 07 (Print Publication: 2016).
Publication Year :
2016

Abstract

The identification and quantification of Heterosigma akashiwo cysts in sediments by light microscopy can be difficult due to the small size and morphology of the cysts, which are often indistinguishable from those of other types of algae. Quantitative real-time PCR (qPCR) based assays represent a potentially efficient method for quantifying the abundance of H. akashiwo cysts, although standard curves must be based on cyst DNA rather than on vegetative cell DNA due to differences in gene copy number and DNA extraction yield between these two cell types. Furthermore, qPCR on sediment samples can be complicated by the presence of extracellular DNA debris. To solve these problems, we constructed a cyst-based standard curve and developed a simple method for removing DNA debris from sediment samples. This cyst-based standard curve was compared with a standard curve based on vegetative cells, as vegetative cells may have twice the gene copy number of cysts. To remove DNA debris from the sediment, we developed a simple method involving dilution with distilled water and heating at 75°C. A total of 18 sediment samples were used to evaluate this method. Cyst abundance determined using the qPCR assay without DNA debris removal yielded results up to 51-fold greater than with direct counting. By contrast, a highly significant correlation was observed between cyst abundance determined by direct counting and the qPCR assay in conjunction with DNA debris removal (r2 = 0.72, slope = 1.07, p < 0.001). Therefore, this improved qPCR method should be a powerful tool for the accurate quantification of H. akashiwo cysts in sediment samples.

Details

Language :
English
ISSN :
1932-6203
Volume :
11
Issue :
1
Database :
MEDLINE
Journal :
PloS one
Publication Type :
Academic Journal
Accession number :
26741648
Full Text :
https://doi.org/10.1371/journal.pone.0145712