Department of Plant Physiology, Leipzig University, Institute of Biology, Johannisallee 21-23, 04103, Leipzig, Germany.
Elettra - Sincrotrone Trieste, Synchrotron Infrared Source for Spectroscopy and Imaging - SISSI, 34149, Trieste, Basovizza, Italy.
BMC Plant Biol. 2019 Apr 15;19(1):142. doi: 10.1186/s12870-019-1736-8.
Technical 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).
The PLSr models generated to quantify cell macromolecules presented high quality fit (R ≥ 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.
The 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.
在分析浮游植物生物量时，由于受到技术限制，我们对自然种群中的碳通量的认识有限，因此对水生生态系统中的碳、营养物质和能量循环的认识也有限。在本研究中，我们利用同步辐射傅里叶变换红外微光谱和偏最小二乘回归（PLSr）算法，同时在两个温度（15°C 和 25°C）下，对由蓝藻、绿藻和硅藻组成的模拟浮游植物群落中的单个细胞水平的蛋白质、脂类和碳水化合物含量进行定量。
为定量细胞大分子而生成的 PLSr 模型具有较高的拟合质量（R≥0.90）和较低的预测误差（RMSEP 为干重的 2-6%）。回归系数表明，对每种大分子的预测并不完全依赖于对应化合物的光谱特征，而是依赖于所有主要的大分子库，反映了整个细胞碳平衡的调整。通过核密度估计器对单细胞分析表明，在 15°C 和 25°C 时，大分子的密度分布模式不同。然而，由于种群异质性，相当一部分细胞在两种温度下具有相同的生物化学性质。
本研究中提出的光谱方法允许对单个浮游植物细胞中的大分子进行定量。该方法表明，种群异质性很可能确保了未适应细胞的备份，这些细胞可以迅速利用新的有利小生境。这一发现可能对浮游植物种群的生态学产生重要影响，并表明“平均细胞”概念可能极大地限制了我们对水生生态系统中种群动态和生物地球化学循环的理解。
