SSBD:database

Detail of Fig1A_Tcell_BrightField

Taro Ichimura, Liang-da Chiu, Katsumasa Fujita, Hiroaki Machiyama, Tomoyuki Yamaguchi, Tomonobu M Watanabe, Hideaki Fujita (2016) Non-label immune cell state prediction using Raman spectroscopy., Scientific reports, Volume 6, pp. 37562

Published in 2016 Nov 23 (Electronic publication in Nov. 23, 2016, midnight )

• doi: 10.1038/srep37562
• pmid: 27876845
  

(Abstract) The acquired immune system, mainly composed of T and B lymphocytes, plays a key role in protecting the host from infection. It is important and technically challenging to identify cell types and their activation status in living and intact immune cells, without staining or killing the cells. Using Raman spectroscopy, we succeeded in discriminating between living T cells and B cells, and visualized the activation status of living T cells without labeling. Although the Raman spectra of T cells and B cells were similar, they could be distinguished by discriminant analysis of the principal components. Raman spectra of activated T cells with anti-CD3 and anti-CD28 antibodies largely differed compared to that of naive T cells, enabling the prediction of T cell activation status at a single cell level. Our analysis revealed that the spectra of individual T cells gradually change from the pattern of naive T cells to that of activated T cells during the first 24 h of activation, indicating that changes in Raman spectra reflect slow changes rather than rapid changes in cell state during activation. Our results indicate that the Raman spectrum enables the detection of dynamic changes in individual cell state scattered in a heterogeneous population.

• Animals
• B-Lymphocytes/immunology[major]
• Lymphocyte Activation/immunology
• Mice, Inbred BALB C
• Mice, Transgenic
• Spectrum Analysis, Raman/methods[major]
• T-Lymphocytes/immunology[major]
• Time Factors