An attempt to simultaneously quantify the polysaccharide, total lipid, protein and pigment in single Cyclotella cryptica cell by Raman spectroscopy.

Abstract

Background: At present, the conventional methods for determining photosynthetic products of microalgae are usually based on a large number of cell mass to reach the measurement baseline, and the result can only reveal the average state at the population level, which is not feasible for large-scale and rapid screening of specific phenotypes from a large number of potential microalgae mutants. In recent years, single-cell Raman spectra (SCRS) has been proved to be able to rapidly and simultaneously quantify the biochemical components of microalgae. However, this method has not been reported to analyze the biochemical components of Cyclotella cryptica (C. cryptica). Thus, SCRS was first attempt to determine these four biochemical components in this diatom.

Results: The method based on SCRS was established to simultaneously quantify the contents of polysaccharide, total lipids, protein and Chl-a in C. cryptica, with thirteen Raman bands were found to be the main marker bands for the diatom components. Moreover, Partial Least Square Regression (PLSR) models based on full spectrum can reliably predict these four cellular components, with Pearson correlation coefficient for these components reached 0.949, 0.904, 0.801 and 0.917, respectively. Finally, based on SCRS data of one isogenic sample, the pairwise correlation and dynamic transformation process of these components can be analyzed by Intra-ramanome Correlation Analysis (IRCA), and the results showed silicon starvation could promote the carbon in C. cryptica cells to flow from protein and pigment metabolism to polysaccharide and lipid metabolism.

Conclusions: First, method for the simultaneous quantification of the polysaccharide, total lipid, protein and pigment in single C. cryptica cell are established. Second, the instant interconversion of intracellular components was constructed through IRCA, which is based on data set of one isogenic population and more precision and timeliness. Finally, total results indicated that silicon deficiency could promote the carbon in C. cryptica cells to flow from protein and pigment metabolism to polysaccharide and lipid metabolism.