Ji Yuetong, He Yuehui, Cui Yanbin, Wang Tingting, Wang Yun, Li Yuanguang, Huang Wei E, Xu Jian
Single-Cell Center, CAS Key Laboratory of Biofuels and Shandong Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.
Biotechnol J. 2014 Dec;9(12):1512-8. doi: 10.1002/biot.201400165. Epub 2014 Jul 10.
Conventional methods for quantitation of starch content in cells generally involve starch extraction steps and are usually labor intensive, thus a rapid and non-invasive 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 (R(2) = 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 (ADP-glucose pyrophosphorylase) 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 in individual live cells. Compared to existing cellular starch quantitation methods, this single-cell Raman spectra-based approach is rapid, label-free, non-invasive, culture-independent, low-cost, and potentially able to simultaneously track multiple metabolites in individual live cells, therefore should enable many new applications.
细胞中淀粉含量的传统定量方法通常涉及淀粉提取步骤，且通常劳动强度大，因此一种快速且非侵入性的方法将很有价值。以产淀粉的单细胞微藻莱茵衣藻为模型，我们使用定制的拉曼光谱仪来捕捉在不同培养条件下及不同生长阶段单个细胞的拉曼光谱。结果显示，在478 cm(-1)处的信号强度与细胞的淀粉含量之间存在近乎线性的相关性（R(2) = 0.9893）。我们通过证明在AGPase（ADP-葡萄糖焦磷酸化酶）基因被破坏且淀粉生物合成因此受阻的突变菌株中，与淀粉相关的拉曼峰消失，验证了这种特定的相关性。此外，该方法在工业绿藻小球藻菌株中得到了验证。这是首次在单个活细胞中进行淀粉定量的证明。与现有的细胞淀粉定量方法相比，这种基于单细胞拉曼光谱的方法快速、无标记、非侵入性、不依赖培养、成本低，并且有可能同时追踪单个活细胞中的多种代谢物，因此应该能实现许多新的应用。
