Arbitrary-Region Raster Image Correlation Spectroscopy

• Published in: Biophysical journal 2016-10, Vol.111 (8), p.1785-1796
• Main Authors: Hendrix, Jelle, Dekens, Tomas, Schrimpf, Waldemar, Lamb, Don C.
• Format: Article
• Language: English
• Subjects: Algorithms; Biophysics; Cell Biophysics; Cell Membrane - metabolism; Cells; Diffusion; Fluorescence; HeLa Cells; Humans; Image Processing, Computer-Assisted; Membranes; Microscopy; Microscopy, Confocal; Spectrum Analysis
• ISSN: 0006-3495; 1542-0086
• DOI: 10.1016/j.bpj.2016.09.012

Combining imaging with correlation spectroscopy, as in raster image correlation spectroscopy (RICS), makes it possible to extract molecular translational diffusion constants and absolute concentrations, and determine intermolecular interactions from single-channel or multicolor confocal laser-scanning microscopy (CLSM) images. Region-specific RICS analysis remains very challenging because correlations are always calculated in a square region-of-interest (ROI). In this study, we describe a generalized image correlation spectroscopy algorithm that accepts arbitrarily shaped ROIs. We show that an image series can be cleaned up before arbitrary-region RICS (ARICS) analysis. We demonstrate the power of ARICS by simultaneously measuring molecular mobility in the cell membrane and the cytosol. Mobility near dynamic subcellular structures can be investigated with ARICS by generating a dynamic ROI. Finally, we derive diffusion and concentration pseudo-maps using the ARICS method. ARICS is a powerful expansion of image correlation spectroscopy with the potential of becoming the new standard for extracting biophysical parameters from confocal fluorescence images.