4.7 Article

Label-free Raman imaging of live osteosarcoma cells with multivariate analysis

Journal

APPLIED MICROBIOLOGY AND BIOTECHNOLOGY
Volume 103, Issue 16, Pages 6759-6769

Publisher

SPRINGER
DOI: 10.1007/s00253-019-09952-3

Keywords

Confocal Raman microspectral imaging; Live osteosarcoma cells; Multi-variate analysis; K-means cluster analysis; Principal component analysis

Funding

  1. Natural Science Research Foundation of Shaanxi Province, China [2018JM6033]
  2. Major Fundamental Research Program of Shaanxi Province, China [2016ZDJC-15]
  3. Innovative Team Foundation of Shaanxi Province, China [S2018-ZC-TD-0061]
  4. Medical research program in Science and Technology + projects of Xi'an city, Shaanxi, China [201805096YX4SF30(2)]

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Confocal Raman microspectral imaging (CRMI) is an advanced cell-imaging method that maps endogenous molecular compositions with their unique spectral fingerprint indicators. The aim of this work was to provide a visualized understanding of subcellular features of live osteosarcoma cells using a 532-nm laser excitation without the use of dyes or molecular probes. Both malignant osteoblast and spindle osteosarcoma cells derived from the BALB/c mouse osteosarcoma cell line K7M2 were investigated in this work. After preprocessing the obtained spectral dataset, K-means cluster analysis (KCA) is employed to reconstruct Raman spectroscopic maps of single biological cells by identifying regions of the cellular membrane, cytoplasm, organelles, and nucleus with their corresponding mean spectra. Principal component analysis (PCA) was further employed to indicate variables of significant influence on the separation of the spectra of each cellular component. The biochemical components of the two cell types were then extracted by showing the spectral and distribution features attributed to proteins, lipids, and DNA. Using this standardized CRMI technique and multivariate analysis approaches, the results obtained could be a sound foundation for a typical Raman imaging protocol of live cellular biomedical analysis.

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