Yuetong Ji, Yuehui He, Yanbin Cui, Tingting Wang, Yun Wang, Yuanguang Li, Wei E. Huang and Jian Xu
Conventional methods for quantitation of starch content in cells generally involve starch extraction steps and are usually labor intensive, thus a rapid and noninvasive method will be valuable. Using the starch-producing unicellular microalga Chlamydomonas reinhardtii as a model, we employed a customized Raman Spectrometer to capture the Raman spectra of individual single-cells under distinct culture conditions and along various growth stages. The results revealed a nearly linear correlation (R2=0.9893) between the signal intensity at 478 cm-1 and the starch content of the cells. We validated the specific correlation by showing that the starch-associated Raman peaks were eliminated in a mutant strain where the AGPase gene was disrupted and consequentially the biosynthesis of starch blocked. Furthermore, the method was validated in an industrial algal strain of Chlorella pyrenoidosa. This is the first demonstration of starch quantitation at individual live cells. Compared to existing cellular-starch quantitation methods, this single-cell Raman spectra based approach is rapid, label-free, noninvasive, culture-independent, low-cost and potentially able to simultaneously track multiple metabolites in individual live cells, therefore should enable many new applications.
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