Abstract
BackgroundTechnical limitations regarding bulk analysis of phytoplankton biomass limit our comprehension of carbon fluxes in natural populations and, therefore, of carbon, nutrients and energy cycling in aquatic ecosystems. In this study, we took advantage of Synchrotron FTIR micro-spectroscopy and the partial least square regression (PLSr) algorithm to simultaneously quantify the protein, lipid and carbohydrate content at the single-cell level in a mock phytoplankton community (composed by a cyanobacterium, a green-alga and a diatom) grown at two temperatures (15 °C and 25 °C).ResultsThe PLSr models generated to quantify cell macromolecules presented high quality fit (R2 ≥ 0.90) and low error of prediction (RMSEP 2–6% of dry weight). The regression coefficients revealed that the prediction of each macromolecule was not exclusively dependent on spectral features corresponding to that compound, but rather on all major macromolecular pools, reflecting adjustments in the overall cell carbon balance.The single-cell analysis, studied by means of Kernel density estimators, showed that the modes of density distribution of macromolecules were different at 15 °C and 25 °C. However, a substantial proportion of cells was biochemically identical at the two temperatures because of population heterogeneity.ConclusionsThe spectroscopic approach presented in this study allows the quantification of macromolecules in single phytoplankton cells. This method showed that population heterogeneity most likely ensures a backup of non-acclimated cells that may rapidly exploit new favourable niches. This finding may have important consequences for the ecology of phytoplankton populations and shows that the “average cell” concept might substantially limit our comprehension of population dynamics and biogeochemical cycles in aquatic ecosystems.
Highlights
Technical limitations regarding bulk analysis of phytoplankton biomass limit our comprehension of carbon fluxes in natural populations and, of carbon, nutrients and energy cycling in aquatic ecosystems
We developed an approach that combines both Synchrotron Fourier Transform Infrared (FTIR) micro-spectroscopy and chemometric predictive models based on the partial least square regression algorithm (PLSr) [30, 31], to quantify the whole macromolecular composition of single phytoplankton cells
Macromolecule quantification by reference biochemical methods The dry weight (DW) of A. obliquus and M. aeruginosa was not influenced by temperature
Summary
Technical limitations regarding bulk analysis of phytoplankton biomass limit our comprehension of carbon fluxes in natural populations and, of carbon, nutrients and energy cycling in aquatic ecosystems. It is interesting to notice that within a clonal phytoplankton population relative macromolecular differences among cells have been observed [9, 10], due to a drastic population heterogeneity in gene expression [11] This in turn limits our comprehension of phytoplankton dynamics in nature, as well as our ability to model primary production. Recent ecological theories have been scaled down at the single-cell level (virus-phytoplankton, bacteria-phytoplankton, phytoplankton-phytoplankton interactions etc.), information about the single biological units of a population may be of great help to better understand community dynamics [12] This high resolution is especially required when considering the great diversity of C-allocation strategies adopted by different taxa (and even species) in response to environmental changes [4, 7, 13, 14]
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