Using Raman spectroscopy to characterize biological materials View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-03-10

AUTHORS

Holly J Butler, Lorna Ashton, Benjamin Bird, Gianfelice Cinque, Kelly Curtis, Jennifer Dorney, Karen Esmonde-White, Nigel J Fullwood, Benjamin Gardner, Pierre L Martin-Hirsch, Michael J Walsh, Martin R McAinsh, Nicholas Stone, Francis L Martin

ABSTRACT

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. More... »

PAGES

664-687

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/nprot.2016.036

    DOI

    http://dx.doi.org/10.1038/nprot.2016.036

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1037467384

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/26963630


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