Combined excitation scan-based hyperspectral imaging and digital deconvolution for the assessment of the kinetic and spatial distributions of cAMP signals

handling. However, the mechanisms by which cAMP signals differentially regulate specific physiological responses remain elusive. Recent studies from a variety of groups provide compelling evidence that the subcellular location of cAMP signals contributes to signal specificity. Our previous work using a spectral Nikon A1R confocal microscope system highlights the need to consider cAMP signals in three spatial distributions (x,y,z). However, this and other commercially available microscope systems lack sufficient sensitivity and speed to track the kinetics of cAMP signals in four dimensions (4D: x,y,z,t). Here, we propose a combination of excitation scan-based hyperspectral imaging and digital deconvolution approaches to overcome this limitation. Imaging was performed using a custom excitation-scanning hyperspectral microscope based upon an Eclipse Ti2 microscope platform (Nikon Instruments), Titan 300 Xenon arc lamp (Sunoptics), VersaChrome thin-film tunable filters (Semrock Inc.) in a VF-5 tiltable filter wheel (Sutter Instruments), and a Prime 95B sCMOS camera (Photometrics). HEK293 and LNCaP cells were transfected with caDDis cAMP probes (Montana Molecular), and subsequently labeled with MitoTracker and/or NucBlue. Cells were imaged at excitation wavelengths ranging from 360 to 525 nm in 5 nm increments and emission was detected using a 532 nm long pass dichroic filter (Semrock Inc.). Hyperspectral image stacks were acquired at 250-500 nm axial increments (z-stacks). NIS Elements analysis software was used to deconvolve image data at each acquisition wavelength. The contributions from each fluorophore were then assessed using nonnegative linear unmixing. Preliminary results indicate that digital deconvolution of hyperspectral image stacks offers an effective approach to assess the spatial distributions of multiple fluorophores including cAMP probes in 5D (x, y, z, λ, and t). This work was supported by the University of South Alabama Center for Lung Biology, NIH R01HL169522 and S10OD028606, and NSF DBI-2408000.