Development of a novel automated analytical method for viability assessment of phytoplankton used for validation of ballast water treatment systems.
To limit the spreading of aquatic invasive species, regulations require ships' ballast water to be treated before discharge. To validate ballast water treatment system (BWTS) performance, treated water is analyzed for living organisms in different size classes. Quantitative assessment of the size class 10-50 μm (mainly phytoplankton) is carried out using the vital stain method, which requires labor-intensive manual microscope counts of fluorescent (i.e., living) cells. The method is slow, demands specialized personnel, and is challenged by subjectivity and mobile organisms. Using a high-content screening platform (HCS-Platform) and image analysis, we developed an automated, objective and faster quantification method. The automated method neutralized subjectivity by using fixed cell recognition parameters for image analysis. The implementation of membrane filters gently manipulated the organisms into a 2D plane that reduced mobility. Quantifications were performed at different concentrations using monocultures of slow-moving Rhodomonas salina, highly mobile Tetraselmis suecica and natural algae. Results were compared to the standard manual counting procedure. Automated counts of monocultures were comparable to manual counts at low and medium concentration levels. Manual counts of T. suecica at high concentration levels were significantly lower compared to automated counts stressing the challenge to count mobile cells in 3D. Natural algal counts were similar for both counting approaches, but accuracy was challenged by colony forming species and high number of algal species ~10 μm. Automated counts were significantly faster than manual counts. In conclusion, the HCS-Platform showed promising results as an alternative quantitative phytoplankton assessment method for BWTS validation.