Matching an immersion medium's refractive index to a cell's cytosol isolates organelle scattering.
Kaitlin J DunnTresa M EliasEdward B BrownAndrew J BergerPublished in: Biomedical optics express (2022)
Angularly-resolved light scattering has been proven to be an early detector of subtle changes in organelle size due to its sensitivity to scatterer size and refractive index contrast. However, for cells immersed in media with a refractive index close to 1.33, the cell itself acts as a larger scatterer and contributes its own angular signature. This whole-cell scattering, highly dependent on the cell's shape and size, is challenging to distinguish from the desired organelle scattering signal. This degrades the accuracy with which organelle size information can be extracted from the angular scattering. To mitigate this effect, we manipulate the refractive index of the immersion medium by mixing it with a water-soluble, biocompatible, high-refractive-index liquid. This approach physically reduces the amount of whole-cell scattering by minimizing the refractive index contrast between the cytosol and the modified medium. We demonstrate this technique on live cells adherent on a coverslip, using Fourier transform light scattering to compute the angular scattering from complex field images. We show that scattering from the cell: media refractive index contrast contributes significant scattering at angles up to twenty degrees and that refractive index-matching reduces such low-angle scatter by factors of up to 4.5. This result indicates the potential of refractive index-matching for improving the estimates of organelle size distributions in single cells.
Keyphrases
- single cell
- cell therapy
- induced apoptosis
- magnetic resonance
- monte carlo
- cataract surgery
- magnetic resonance imaging
- healthcare
- cell cycle arrest
- oxidative stress
- stem cells
- mesenchymal stem cells
- machine learning
- social media
- computed tomography
- bone marrow
- climate change
- endoplasmic reticulum stress
- cell proliferation
- drug release
- convolutional neural network