Raman spectroscopy in cell biology and microbiology

被引:134
作者
Pezzotti, Giuseppe [1 ,2 ,3 ,4 ,5 ,6 ]
机构
[1] Kyoto Inst Technol, Ceram Phys Lab, Kyoto, Japan
[2] Tokyo Med Univ, Dept Orthoped Surg, Tokyo, Japan
[3] Osaka Univ, Ctr Adv Med Engn & Informat, Osaka, Japan
[4] Kyoto Prefectural Univ Med, Grad Sch Med Sci, Dept Immunol, Kyoto, Japan
[5] Tokyo Med & Dent Univ, Inst Biomat & Bioengn, Tokyo, Japan
[6] Kyoto Prefectural Univ Med, Grad Sch Med Sci, Dept Dent Med, Kyoto, Japan
关键词
INFLUENZA-A VIRUS; QUANTITATIVE CRYSTALLOGRAPHIC ANALYSES; PORPHYROMONAS-GINGIVALIS GINGIPAINS; ENRICHED MEMBRANE DOMAINS; SINGLE LIVING CELLS; X-RAY-DIFFRACTION; CALF-THYMUS DNA; STREPTOCOCCUS-MUTANS; NUCLEIC-ACIDS; AMINO-ACIDS;
D O I
10.1002/jrs.6204
中图分类号
O433 [光谱学];
学科分类号
0703 ; 070302 ;
摘要
The Raman spectrum of living cells and microorganisms contains highly specific fingerprint-like signatures, useful in unequivocally identifying different species and interpreting physiological and metabolic responses to environmental stressors. In situ Raman imaging with dedicated highly sensitive instruments can translate selected spectroscopic fingerprints into vivid snapshots of molecular species or specific physiological reactions. Time-lapse experiments, crucial in characterizing growth-dependent phenomena and metabolic response to drugs or substrates, are possible because Raman imaging is life compatible. This review covers miscellaneous examples of Raman analyses and imaging of eukaryotic cells, bacteria, and viruses. Fundamental microbiological analyses covered here include (i) identification of different species of cells, bacteria, and viruses; (ii) characterization of the metabolic responses of cells and bacteria to different substrates; (iii) time-lapse analyses of cell metabolic reactions upon viral inoculation; (iv) chemical imaging of axon sprouting in neuronal cells; and (v) visualization of the myelinating activity of living Schwann cells in coculture with neuronal cells. The spectroscopic findings displayed here, which are based on a machine learning approach applied to Raman analysis and imaging, demonstrate the invaluable potential for Raman spectroscopy in biophysics research.
引用
收藏
页码:2348 / 2443
页数:96
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