4.6 Article

Label-Free Raman Hyperspectral Imaging of Single Cells Cultured on Polymer Substrates

Journal

APPLIED SPECTROSCOPY
Volume 71, Issue 12, Pages 2595-2607

Publisher

SAGE PUBLICATIONS INC
DOI: 10.1177/0003702817715042

Keywords

Raman spectroscopy; hyperspectral imaging; cells; polymer substrates; background correction

Funding

  1. Engineering and Physical Sciences Research Council [EP/M506588/1, EP/L025620/1]
  2. BBSRC [BB/G010285/1] Funding Source: UKRI
  3. EPSRC [EP/L025620/1] Funding Source: UKRI
  4. MRC [MC_PC_13072] Funding Source: UKRI
  5. Biotechnology and Biological Sciences Research Council [BB/G010285/1] Funding Source: researchfish
  6. Engineering and Physical Sciences Research Council [EP/L025620/1] Funding Source: researchfish
  7. Medical Research Council [MC_PC_13072] Funding Source: researchfish

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While Raman hyperspectral imaging has been widely used for label-free mapping of biomolecules in cells, these measurements require the cells to be cultured on weakly Raman scattering substrates. However, many applications in biological sciences and engineering require the cells to be cultured on polymer substrates that often generate large Raman scattering signals. Here, we discuss the theoretical limits of the signal-to-noise ratio in the Raman spectra of cells in the presence of polymer signals and how optical aberrations may affect these measurements. We show that Raman spectra of cells cultured on polymer substrates can be obtained using automatic subtraction of the polymer signals and demonstrate the capabilities of these methods in two important applications: tissue engineering and invitro toxicology screening of drugs. Apart from their scientific and technological importance, these applications are examples of the two most common measurement configurations: (1) cells cultured on an optically thick polymer substrate measured using an immersion/dipping objective; and (2) cells cultured on a transparent polymer substrate and measured using an inverted optical microscope. In these examples, we show that Raman hyperspectral data sets with sufficient quality can be successfully acquired to map the distribution of common biomolecules in cells, such as nucleic acids, proteins, and lipids, as well as detecting the early stages of apoptosis. We also discuss strategies for further improvements that could expand the application of Raman hyperspectral imaging on polymer substrates even further in biomedical sciences and engineering.

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