Analysis of Components Difference of Yeast Strains Based on Laser Tweezers Raman Spectroscopy Combined with Multistatistical Analysis
LAI Jun-zhuo1, 2, LIU Bin3, WANG Gui-wen1, TAO Zhan-hua1, HUANG Shu-shi1*
1. Lab of Biophysics, Guangxi Academy of Sciences, Nanning 530003, China 2. College of Life Sciences and Technology, Guangxi University, Nanning 530005, China 3. Institute of Applied Microbiology, Agricultural College of Guangxi University, Nanning 530005, China
Abstract：The combination of laser tweezers and con-focusing Raman spectroscopy (LTRS) has made it possible to investigate single cells in aqueous media. In our experiments, a modified method of Percoll density gradient centrifugation was developed for isolating synchronous cells from six yeast strains and Raman spectra of single yeast cells were collected by LTRS as well, in which multiple statistical analysis, principal component analyses (PCA) and discriminant function analysis (DFA) were applied to distinguish synchronous cells between yeast strains statistically. The result showed that Raman spectra scattered from the trapping yeast cells could provide intrinsic molecular information, and there were remarkable difference among those of six yeast strains in Raman spectrogram which correspond to various biomacromolecule, the difference of protein as well as lipid were significantly higher than nucleinic acid between two of yeast strains randomly, and among the six strains, synchronized yeast cells can be discriminated using PCA and DFA based on 14 most contribution bands, 706, 862, 918, 997, 1 073, 1 127, 1 269, 1 291, 1 305, 1 429, 1 465, 1 591, 1 602 and 1 652 cm-1, 10 bands of which were from protein，3 bands were from lipoid, and 1 band was from nucleinic acid. To validate their significance, these variables were used to reperform DFA analysis and the re-plotted PC-DFA was the same as in the previous PC-DFA analysis, and the data would be considered validated. The authors show that the approach of laser tweezers Raman spectroscopy combined with multistatistical analysis has the potential to study difference among yeast strains.
赖钧灼1, 2，刘 斌3，王桂文1，陶站华1，黄庶识1* . 单细胞拉曼光谱结合多元统计方法分析不同酿酒酵母菌株的成分差异[J]. 光谱学与光谱分析, 2011, 31(02): 412-417.
LAI Jun-zhuo1, 2, LIU Bin3, WANG Gui-wen1, TAO Zhan-hua1, HUANG Shu-shi1* . Analysis of Components Difference of Yeast Strains Based on Laser Tweezers Raman Spectroscopy Combined with Multistatistical Analysis. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2011, 31(02): 412-417.
[1] SHEN Li-fei, YANG Zhen-quan, FANG Wei-ming, et al(沈力飞, 杨振泉, 方维明, 等). Food and Fermentation Industries(食品与发酵工业), 2005, 31(10): 1. [2] DAI Qun-wei, DONG Fa-qin(代群威, 董发勤). Journal of Southwest University of Science and Technology(西南科技大学学报), 2009, 24(1): 114. [3] Xie C A, Mace J, Dinno M A, et al. Anal. Chem., 2005, 77: 4390. [4] Huang W E, Ward A D, Whiteley A S. Environmental Microbiology Reports, 2009, 1(1): 44. [5] Grow A E. Principles of Bacteria Detection: Biosensors, Recognition Receptors and Microsystems. New York: Springer, 2008. 525. [6] Chen D, Huang S S, Li Y Q. Anal. Chem., 2006, 78(19): 6936. [7] WANG Gui-wen, YAO Hui-lu, PENG Li-xin, et al(王桂文, 姚辉璐, 彭立新, 等). Microbiology(微生物学通报), 2007, 34(6): 1109. [8] Mannie M D, McConnell T, Xie C A. Journal of Immunological Methods, 2005, 297: 53. [9] Allen C, Büttner S, Aragon A D, et al. The Journal of Cell Biology, 2006, 174(1): 89. [10] XU Yi-ming(许以明). Raman Spectroscopy and Its Application in Structural Biology (拉曼光谱及其在结构生物学中的应用). Beijing: Chemical Industry Press(北京: 化学工业出版社), 2005. [11] Notingher I. Sensors, 2007, 7: 1343. [12] Puppels G J, De Mul F F M, Otto C, et al. Nature, 1990, 347: 301. [13] Lord R C, Yu N T. J. Mol. Biol., 1970, 50: 509. [14] Huang W E, Hopper D, Goodacre R, et al. Journal of Microbiological Methods, 2006, 67: 275. [15] Ivleva N P, Wagner M, Horn H, et al. Anal. Bioanal. Chem., 2009, 393: 197. [16] Matthus C, Bird B, Miljkovic M, et al. Methods Cell Biol., 2008, 89: 275.
