Hyperspectral Superresolution Imaging

Hyperspectral superresolution imaging is a new area of research within superresolution microscopy that combines spectroscopy and localization microscopy. We believe this will one day allow biologists and biophysicists to measure changes in pH or temperature within a cell by using the small variations in spectral content associated with thermo-chemical state variables. Combining nanometer resolution images, with the spectroscopic information contained from shifting fluorescent dyes will give researchers a deeper understanding of the nanoscale complexity that underlies living systems. 

Our approach integrates a special phase element installed in the Fourier plane of a super-resolution fluorescence microscope. This phase element alters the phase of the collected fluorescence, making the point-spread function (PSF) of the microscope strongly dependent on wavelength (Fig. 1).  As a first step, we performed multi-color imaging of fluorescent beads and used only the shape of the modified PSF to separate the wavelength channels (Fig. 2).  We have also imaged stained and fixed biological cells and identified labeled cellular components using the modified PSF to determine the emission wavelength point by point in the image (Fig. 3).  Concurrently, we’re installing a deformable mirror into the light collection pathway to give our microscope more dynamic control (Fig. 4).  It will also allow us to optimize the modified point-spread function for several fluorescent dyes that are useful in bioimaging applications.  We’ve developed a statistical figure of merit that will allow us to find the shape of our mirror that optimizes the point-spread function for wavelength sensitivity.

Students and Postdocs Involved:
Jason Martineau, PhD, Postdoctoral Scholar, Former Physics PhD student (defended 2019)
Sanduni Fernando, Physics PhD student
Carl Ebeling, PhD, Former Physics PhD student (defended 2014)

Erik Jorgensen, School of Biological Sciences, University of Utah
Rajesh Menon, Department of Electrical and Computer Engineering, University of Utah

© Jordan Gerton 2019