Hyperspectral imaging and adaptive thresholding to identify agonist-induced cAMP signals in pulmonary microvascular endothelial cells.

Cyclic AMP (cAMP) is a second messenger that regulates a wide variety of cellular functions. There is increasing evidence suggesting that signaling specificity is due in part to cAMP compartmentalization. In the last 15 years, development of cAMP-specific Förster resonance energy transfer (FRET) probes have allowed us to visualize spatial distributions of intracellular cAMP signals. The use of FRET-based sensors is not without its limitations, as FRET probes display low signal to noise ratio (SNR). Hyperspectral imaging and analysis approaches have, in part, allowed us to overcome these limitations by improving the SNR of FRET measurements. Here we demonstrate that the combination of hyperspectral imaging approaches, linear unmixing, and adaptive thresholding allow us to visualize regions of elevated cAMP (regions of interest - ROIs) in an unbiased manner. We transfected cDNA encoding the H188 FRET-based cAMP probe into pulmonary microvascular endothelial cells. Application of isoproterenol and prostaglandin E1 (PGE1) triggered complex cAMP responses. Spatial and temporal aspects of cAMP responses were quantified using an adaptive thresholding approach and compared between agonist treatment groups. Our data indicate that both the origination sites and spatial/temporal distributions of cAMP signals are agonist dependent in PMVECs. We are currently analyzing the data in order to better quantify the distribution of cAMP signals triggered by different agonists.

Measurement of agonist-induced Ca2+ signals in human airway smooth muscle cells using excitation scan-based hyperspectral imaging and image analysis approaches.

Ca2+ and cAMP are ubiquitous second messengers known to differentially regulate a variety of cellular functions over a wide range of timescales. Studies from a variety of groups support the hypothesis that these signals can be localized to discrete locations within cells, and that this subcellular localization is a critical component of signaling specificity. However, to date, it has been difficult to track second messenger signals at multiple locations. To overcome this limitation, we utilized excitation scan-based hyperspectral imaging approaches to track second messenger signals as well as labeled cellular structures and/or proteins in the same cell. We have previously reported that hyperspectral imaging techniques improve the signal-to-noise ratios of both fluorescence measurements, and are thus well suited for the measurement of localized Ca2+ signals. We investigated the spatial spread and intensities of agonist-induced Ca2+ signals in primary human airway smooth muscle cells (HASMCs) using the Ca2+ indicator Cal520. We measured responses triggered by three agonists, carbachol, histamine, and chloroquine. We utilized custom software coded in MATLAB and Python to assess agonist induced changes in Ca2+ levels. Software algorithms removed the background and applied correction coefficients to spectral data prior to linear unmixing, spatial and temporal filtering, adaptive thresholding, and automated region of interest (ROI) detection. All three agonists triggered transient Ca2+ responses that were spatially and temporally complex. We are currently analyzing differences in both ROI area and intensity distributions triggered by these agonists. This work was supported by NIH awards P01HL066299, K25HL136869, and R01HL137030 and NSF award MRI1725937.

Novel Hyperspectral imaging approaches allow 3D measurement of cAMP signals in localized subcellular domains of human airway smooth muscle cells.

Studies of the cAMP signaling pathway have led to the hypothesis that localized cAMP signals regulate distinct cellular responses. Much of this work focused on measurement of localized cAMP signals using cAMP sensors based upon FÓ§rster resonance energy transfer (FRET). FRET-based probes are comprised of a cAMP binding domain sandwiched between donor and acceptor fluorophores. Binding of cAMP triggers a conformational change which alters FRET efficiency. In order to study localized cAMP signals, investigators have targeted FRET probes to distinct subcellular domains. This approach allows detection of cAMP signals at distinct subcellular locations. However, these approaches do not measure localized cAMP signals per se, rather they measure cAMP signals at specific locations and typically averaged throughout the cell. To address these concerns, our group implemented hyperspectral imaging approaches for measuring highly multiplexed signals in cells and tissues. We have combined these approaches with custom analysis software implemented in MATLAB and Python. Images were filtered both spatially and temporally, prior to adaptive thresholding (OTSU) to detect cAMP signals. These approaches were used to interrogate the distributions of isoproterenol and prostaglandin-triggered cAMP signals in human airway smooth muscle cells (HASMCs). Results demonstrate that cAMP signals are spatially and temporally complex. We observed that isoproterenol- and prostaglandin-induced cAMP signals are triggered at the plasma membrane and in the cytosolic space. We are currently implementing analysis approaches to better quantify and visualize the complex distributions of cAMP signals. This work was supported by NIH P01HL066299, R01HL058506, and S10RR027535.

Improving Visualization of cAMP Gradients Using Algorithmic Modelling.

A ubiquitous second messenger molecule, cAMP is responsible for orchestrating many different cellular functions through a variety of pathways. FÓ§rster resonance energy transfer (FRET) probes have been used to visualize cAMP spatial gradients in pulmonary microvascular endothelial cells (PMVECs). However, FRET probes have inherently low signal-to-noise ratios; multiple sources of noise can obscure accurate visualization of cAMP gradients using a hyperspectral imaging system. FRET probes have also been used to measure cAMP gradients in 3D; however, it can be difficult to differentiate between true FRET signals and noise. To further understand the effects of noise on experimental data, a model was developed to simulate cAMP gradients under experimental conditions. The model uses a theoretical cAMP heatmap generated using finite element analysis. This heatmap was converted to simulate the FRET probe signal that would be detected experimentally with a hyperspectral imaging system. The signal was mapped onto an image of unlabeled PMVECs. The result was a time lapse model of cAMP gradients obscured by autofluorescence, as visualized with FRET probes. Additionally, the model allowed the simulated expression level of FRET signal to be varied. This allowed accurate attribution of signal to FRET and autofluorescence. Comparing experimental data to the model results at different levels of FRET efficiency has allowed improved understanding of FRET signal specificity and how autofluorescence interferes with FRET signal detection. In conclusion, this model can more accurately determine cAMP gradients in PMVECs. This work was supported by NIH award P01HL066299, R01HL58506 and NSF award 1725937.

Automated Image Analysis of FRET Signals for Subcellular cAMP Quantification.

A variety of FRET probes have been developed to examine cAMP localization and dynamics in single cells. These probes offer a readily accessible approach to measure localized cAMP signals. However, given the low signal-to-noise ratio of most FRET probes and the dynamic nature of the intracellular environment, there have been marked limitations in the ability to use FRET probes to study localized signaling events within the same cell. Here, we outline a methodology to dissect kinetics of cAMP-mediated FRET signals in single cells using automated image analysis approaches. We additionally extend these approaches to the analysis of subcellular regions. These approaches offer a unique opportunity to assess localized cAMP kinetics in an unbiased, quantitative fashion.

Milestones in the development and implementation of FRET-based sensors of intracellular signals: A biological perspective of the history of FRET.

FÓ§rster resonance energy transfer (FRET) has been described for more than a century. FRET has become a mainstay for the study of protein localization in living cells and tissues. It has also become widely used in the fields that comprise cellular signaling. FRET-based probes have been developed to monitor second messenger signals, the phosphorylation state of peptides and proteins, and subsequent cellular responses. Here, we discuss the milestones that led to FRET becoming a widely used tool for the study of biological systems: the theoretical description of FRET, the insight to use FRET as a molecular ruler, and the isolation and genetic modification of green fluorescent protein (GFP). Each of these milestones were critical to the development of a myriad of FRET-based probes and reporters in common use today. FRET-probes offer a unique opportunity to interrogate second messenger signals and subsequent protein phosphorylation - and perhaps the most effective approach for study of cAMP/PKA pathways. As such, FRET probes are widely used in the study of intracellular signaling pathways. Yet, somehow, the potential of FRET-based probes to provide windows through which we can visualize complex cellular signaling systems has not been fully reached. Hence we conclude by discussing the technical challenges to be overcome if FRET-based probes are to live up to their potential for the study of complex signaling networks.