光谱学与光谱分析 |
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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 |
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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.
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Received: 2010-05-10
Accepted: 2010-08-20
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Corresponding Authors:
HUANG Shu-shi
E-mail: hshushi@gxas.cn;hshushi@yahoo.com.cn
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