Hyperspectral Measurements Allow Separation Of Fret Signals From Non-Uniform Background Fluorescence

In recent years Forster resonance energy transfer (FRET) has become a standard imaging approach to gain insight into localized biochemical processes within cells. These processes include changes in protein colocalization, second messenger concentration, and activation of effector proteins such as protein kinase A (PKA). However, there are several limitations in FRET measurements that are not often considered. In recent years our group has used hyperspectral imaging approaches to address a subset of these limitations, including the inherently low signal-to-noise ratio of standard two and three filter set FRET measurements. Here we present data demonstrating that hyperspectral imaging approaches can be used to correct for non-uniform background fluorescence in low intensity FRET measurements. We utilized the FRET-based cAMP probe H188. The H188 probe contains a cAMP binding domain between donor (Turquoise) and acceptor (Venus) fluorescent proteins. The probe was transfected into pulmonary microvascular endothelial cells plated on glass coverslips. Hyperspectral image stacks were acquired using a Nikon A1R inverted confocal microscope. Changes in cAMP were triggered by addition of 0.1 µM isoproterenol (a beta adrenergic receptor agonist) 0.1 µM PGE1 (a prostanoid receptor agonist) or 50 µM forskolin (an adenylyl cyclase activator). Data were analyzed using Nikon Elements software and custom MATLAB scripts. Results demonstrate that non-uniform background fluorescence associated with glass coverslips can contaminate FRET measurements from weak fluorescence signals. Linear unmixing approaches were able to separate the abundances of background, donor and acceptor fluorescence signals. Thus, results from this study demonstrate that hyperspectral unmixing approaches can readily separate non-uniform background fluorescence from other fluorescence signatures, allowing for more accurate quantification of FRET efficiency. This work was supported by NIH P01HL066299, NIH S10RR027535, NIH T32HL076125, AHA 16PRE27130004, USA SURF Program, and the Abraham Mitchell Cancer Research Fund.