A novel fluoro-electrochemical technique for classifying diverse marine nanophytoplankton

TitleA novel fluoro-electrochemical technique for classifying diverse marine nanophytoplankton
Publication TypeMiscellaneous
Year of Publication2023
AuthorsBarton S, Yang M, Chen H, Batchelor-McAuley C, Compton R, Bouman H, Rickaby R
KeywordsRCC1, rcc1084, RCC1130, RCC1150, RCC1178, RCC1185, RCC1198, RCC1216, rcc1217, RCC1242, RCC1314, RCC1346, RCC1489, RCC1511, RCC1546, RCC1557, RCC1614, rcc1731, RCC191, RCC2570, RCC3598, RCC3696, RCC3776, RCC3780, RCC4207, RCC4221, RCC4273, RCC4657, RCC4660, RCC6, RCC623, RCC6516, RCC656, RCC678, RCC69, RCC74, RCC76, RCC8, RCC80, RCC81, RCC88, RCC911, RCC950

To broaden our understanding of pelagic ecosystem responses to environmental change, it is essential that we improve the spatio-temporal resolution of in situ monitoring of phytoplankton communities. A key challenge for existing methods is in classifying and quantifying cells within the nanophytoplankton size range (2-20µm). This is particularly difficult when there are similarities in morphology, making visual differentiation difficult for both trained taxonomists and machine learning based approaches. Here we present a rapid fluoro-electrochemical technique for classifying nanophytoplankton, and using a library of 52 diverse strains of nanophytoplankton we assess the accuracy of this technique based on two measurements at the individual level: charge required to reduce per cell chlorophyll a fluorescence by 50%, and cell radius. We demonstrate a high degree of accuracy overall (>90%) in categorising cells belonging to widely recognised key functional groups, however this is reduced when we consider the broader diversity of “nano-phytoflagellates”. Notably, we observe that some groups, for example calcifying Isochrysidales, have much greater resilience to electrochemically driven oxidative conditions relative to others of a similar size, making them more easily categorised by the technique. The findings of this study present a promising step forward in advancing our toolkit for monitoring phytoplankton communities. We highlight that, for improved categorisation accuracy, future iterations of the method can be enhanced by measuring additional predictor variables with minimal adjustments to the set-up. In doing so, we foresee this technique being highly applicable, and potentially invaluable, for in situ classification and enumeration of the nanophytoplankton size fraction.