An improved method for the molecular identification of single dinoflagellate cysts.

BACKGROUND

Dinoflagellate cysts (i.e., dinocysts) are biologically and ecologically important as they can help dinoflagellate species survive harsh environments, facilitate their dispersal and serve as seeds for harmful algal blooms. In addition, dinocysts derived from some species can produce more toxins than vegetative forms, largely affecting species through their food webs and even human health. Consequently, accurate identification of dinocysts represents the first crucial step in many ecological studies. As dinocysts have limited or even no available taxonomic keys, molecular methods have become the first priority for dinocyst identification. However, molecular identification of dinocysts, particularly when using single cells, poses technical challenges. The most serious is the low success rate of PCR, especially for heterotrophic species.

METHODS

In this study, we aim to improve the success rate of single dinocyst identification for the chosen dinocyst species (, , , and ) distributed in the South China Sea. We worked on two major technical issues: cleaning possible PCR inhibitors attached on the cyst surface and designing new dinoflagellate-specific PCR primers to improve the success of PCR amplification.

RESULTS

For the cleaning of single dinocysts separated from marine sediments, we used ultrasonic wave-based cleaning and optimized cleaning parameters. Our results showed that the optimized ultrasonic wave-based cleaning method largely improved the identification success rate and accuracy of both molecular and morphological identifications. For the molecular identification with the newly designed dinoflagellate-specific primers (18S634F-18S634R), the success ratio was as high as 86.7% for single dinocysts across multiple taxa when using the optimized ultrasonic wave-based cleaning method, and much higher than that (16.7%) based on traditional micropipette-based cleaning.

DISCUSSION

The technically simple but robust method improved on in this study is expected to serve as a powerful tool in deep understanding of population dynamics of dinocysts and the causes and consequences of potential negative effects caused by dinocysts.