4.7 Article

Using Raman spectroscopy to characterize biological materials

期刊

NATURE PROTOCOLS
卷 11, 期 4, 页码 664-687

出版社

NATURE PUBLISHING GROUP
DOI: 10.1038/nprot.2016.036

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资金

  1. European Regional Development Fund (ERDF)
  2. UK Engineering and Physical Sciences Research Council (EPSRC)
  3. Rosemere Cancer Foundation
  4. UK Biotechnology and Biological Sciences Research Council (BBSRC)
  5. Michigan Diabetes Research and Training (National Institutes of Health (NIH)/National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)) [2P30 DK020572]
  6. EPSRC [EP/K020374/1] Funding Source: UKRI
  7. Natural Environment Research Council [ceh010010] Funding Source: researchfish

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Raman spectroscopy can be used to measure the chemical composition of a sample, which can in turn be used to extract biological information. Many materials have characteristic Raman spectra, which means that Raman spectroscopy has proven to be an effective analytical approach in geology, semiconductor, materials and polymer science fields. The application of Raman spectroscopy and microscopy within biology is rapidly increasing because it can provide chemical and compositional information, but it does not typically suffer from interference from water molecules. Analysis does not conventionally require extensive sample preparation; biochemical and structural information can usually be obtained without labeling. In this protocol, we aim to standardize and bring together multiple experimental approaches from key leaders in the field for obtaining Raman spectra using a microspectrometer. As examples of the range of biological samples that can be analyzed, we provide instructions for acquiring Raman spectra, maps and images for fresh plant tissue, formalin-fixed and fresh frozen mammalian tissue, fixed cells and biofluids. We explore a robust approach for sample preparation, instrumentation, acquisition parameters and data processing. By using this approach, we expect that a typical Raman experiment can be performed by a nonspecialist user to generate high-quality data for biological materials analysis.

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