Hyperspectral imaging (HSI) technologies have enabled a range of experimental techniques and studies in the fluorescence microscopy field. Unfortunately, a drawback of many HSI microscope platforms is increased acquisition time required to collect images across many spectral bands, as well as signal loss due to the need to filter or disperse emitted fluorescence into many discrete bands. We have previously demonstrated that an alternative approach of scanning the fluorescence excitation spectrum can greatly improve system efficiency by decreasing light losses associated with emission filtering. Our initial system was configured using an array of thin-film tunable filters (TFTFs, VersaChrome, Semrock) mounted in a tiltable filter wheel (VF-5, Sutter) that required ~150-200 ms to switch between wavelengths. Here, we present a new configuration for high-speed switching of TFTFs to allow rapid time-lapse HSI microscopy. A TFTF array was mounted in a custom holder that was attached to a piezoelectric rotation mount (ThorLabs), allowing high-speed rotation. Switching between adjacent filters was achieved using the internal optics of a DG-4 lightsource (Sutter Instrument), including a pair of off-axis parabolic mirrors and galvanometers. Output light was coupled to a liquid lightguide and into an inverted widefield fluorescence microscope (TI-2, Nikon Instruments). Initial tests indicate that the HSI system provides a 15-20 nm bandwidth tunable excitation band and ~10-20 ms wavelength switch time, allowing for high-speed HSI imaging of dynamic cellular events. This work was supported by NIH P01HL066299, R01HL169522, NIH TL1TR003106, and NSF MRI1725937.
SignificanceHyperspectral imaging (HSI) technologies offer great potential in fluorescence microscopy for multiplexed imaging, autofluorescence removal, and analysis of autofluorescent molecules. However, there are also associated trade-offs when implementing HSI in fluorescence microscopy systems, such as decreased acquisition speed, resolution, or field-of-view due to the need to acquire spectral information in addition to spatial information. The vast majority of HSI fluorescence microscopy systems provide spectral discrimination by filtering or dispersing the fluorescence emission, which may result in loss of emitted fluorescence signal due to optical filters, dispersive optics, or supporting optics, such as slits and collimators. Technologies that scan the fluorescence excitation spectrum may offer an approach to mitigate some of these trade-offs by decreasing the complexity of the emission light path.AimWe describe the development of an optical technique for hyperspectral imaging fluorescence excitation-scanning (HIFEX) on a microscope system.ApproachThe approach is based on the design of an array of wavelength-dependent light emitting diodes (LEDs) and a unique beam combining system that uses a multifurcated mirror. The system was modeled and optimized using optical ray trace simulations, and a prototype was built and coupled to an inverted microscope platform. The prototype system was calibrated, and initial feasibility testing was performed by imaging multilabel slide preparations.ResultsWe present results from optical ray trace simulations, prototyping, calibration, and feasibility testing of the system. Results indicate that the system can discriminate between at least six fluorescent labels and autofluorescence and that the approach can provide decreased wavelength switching times, in comparison with mechanically tuned filters.ConclusionsWe anticipate that LED-based HIFEX microscopy may provide improved performance for time-dependent and photosensitive assays.
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.
KEYWORDS: Fluorescence resonance energy transfer, Data modeling, Visualization, Interference (communication), Finite element methods, Signal to noise ratio, Hyperspectral imaging, Lung, Signal detection, Sensors
A ubiquitous second messenger molecule, cAMP is responsible for orchestrating many different cellular functions through a variety of pathways. Fӧrster 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.
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 Fӧrster
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.
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.
F¨orster resonance energy transfer (FRET) is a tool used for studying various biological process as well as for measuring molecular distances. This process can occur when the emission spectrum of the donor fluorophore overlaps with the excitation spectrum of the acceptor, and the fluorophores are in close enough distance for the energy to pass from donor to acceptor non-radiatively. The efficiency of this energy transfer is dependent on the distance and orientation of the fluorophores, in addition to their overlapping spectra. Here we present a study to assess the impact of tissue autofluorescence on estimates of FRET efficiency and fluorophore abundance within experimental cellular images in tissue. To accomplish this we performed a theoretical sensitivity analysis on FRET rat kidney control images with varying ranges of donor and acceptor fluorophores to observe their pixel by pixel responses. In the experimental data, the donor was the Turquoise fluorescent protein and the acceptor fluorophore was the Venus fluorescent protein. Detection of the acceptor was more difficult due to its excitation spectrum closely resembling the autofluorescence spectrum from the base image while the emission spectrum of the Turquoise donor was more unique and easier to detect. In addition, variable FRET efficiencies were added to data at different fluorophore levels to compare the visible abundance of FRET to the autofluorescence in the resultant images. This analysis can benefit future work by furthering the understanding of the donor and acceptor concentrations needed for strong FRET measurements.
Fӧrster resonance energy transfer (FRET) based cAMP sensors have become a standard approach to visualize cAMP signals in cells. However, FRET sensors inherently offer low signal-to-noise ratios, making cAMP measurements challenging, especially in 3 spatial dimensions. In previous studies, we used 4-dimensional (x, y, z, and λ) hyperspectral imaging and analysis approaches to measure agonist – induced distribution of cAMP signals in cultured pulmonary microvascular endothelial cells. In many cell types including PMVECs, transient transfection of FRET sensors results in a low transfection efficiency (1-5%), which limits the possibilities of studying spatial distribution of FRET signals in many cells simultaneously. We developed a transgenic rat model that expresses the H187 FRET sensor. In current studies, we utilize hyperspectral imaging and analysis approaches to characterize the distribution of FRET signals in different tissues and vessels harvested from transgenic rats. Hyperspectral z-stacks of tissues and vessels were acquired using a Nikon A1R confocal microscope equipped with 20X multi-immersion objective and a 32 channel PMT detector. Samples were excited using 405 nm and 561 nm lasers and emission was collected from 424 nm -724 nm at 10 nm intervals. Tissues including lungs, heart, mesentery, kidney, expressed the H187 FRET sensor. In conclusion, transgenic rats provide a platform to visualize cAMP signals in-vitro and in-situ.
Structural complexity and heterogeneity may play critical roles in pathophysiology and therapeutic effect, at length scales ranging from subcellular (nm) to whole organ (cm). Here, we report on efforts to utilize a multidimensional spectral FRET imaging approach for visualization of the effects of pharmacologic treatments on tissues. We have developed a transgenic rat line expressing a cAMP FRET reporter for visualization of second messenger signaling in tissues in response to treatment and pathological conditions. When utilized with vascular and lung preparations, transgenic FRET tissues displayed the ability to elicit agonist-induced cAMP responses in single cells.
Förster resonance energy transfer (FRET) is a valuable tool for measuring molecular distances and the effects of biological processes such as cyclic nucleotide messenger signaling and protein localization. Most FRET techniques require two fluorescent proteins with overlapping excitation/emission spectral pairing to maximize detection sensitivity and FRET efficiency. FRET microscopy often utilizes differing peak intensities of the selected fluorophores measured through different optical filter sets to estimate the FRET index or efficiency. Microscopy platforms used to make these measurements include wide-field, laser scanning confocal, and fluorescence lifetime imaging. Each platform has associated advantages and disadvantages, such as speed, sensitivity, specificity, out-of-focus fluorescence, and Zresolution. In this study, we report comparisons among multiple microscopy and spectral filtering platforms such as standard 2-filter FRET, emission-scanning hyperspectral imaging, and excitation-scanning hyperspectral imaging. Samples of human embryonic kidney (HEK293) cells were grown on laminin-coated 28 mm round gridded glass coverslips (10816, Ibidi, Fitchburg, Wisconsin) and transfected with adenovirus encoding a cAMP-sensing FRET probe composed of a FRET donor (Turquoise) and acceptor (Venus). Additionally, 3 FRET “controls” with fixed linker lengths between Turquoise and Venus proteins were used for inter-platform validation. Grid locations were logged, recorded with light micrographs, and used to ensure that whole-cell FRET was compared on a cell-by-cell basis among the different microscopy platforms. FRET efficiencies were also calculated and compared for each method. Preliminary results indicate that hyperspectral methods increase the signal-to-noise ratio compared to a standard 2-filter approach.
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 within a single cell. This difficulty is largely due to the inability to measure multiplexed florescence signals in real time. To overcome this limitation, we have utilized both emission scan- and 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 and FRET measurements, and are thus well suited for the measurement of localized second messenger signals. Using these approaches, we have measured near plasma membrane and near nuclear membrane cAMP signals, as well as distributed signals within the cytosol, in several cell types including airway smooth muscle, pulmonary endothelial, and HEK-293 cells. We have also measured cAMP and Ca2+ signals near autofluorescent structures that appear to be golgi. Our data demonstrate that hyperspectral imaging approaches provide unique insight into the spatial and kinetic distributions of cAMP and Ca2+ signals in single cells.
KEYWORDS: Fluorescence resonance energy transfer, Hyperspectral imaging, Microscopy, Signal to noise ratio, 3D metrology, Visualization, Sensors, Venus, Fluorescent proteins, Imaging technologies, 3D image processing, Luminescence
Cyclic AMP (cAMP) is a ubiquitous second messenger known to differentially regulate many cellular functions. Several lines of evidence suggest that the distribution of cAMP within cells is not uniform. However, to date, no studies have measured the kinetics of 3D cAMP distributions within cells. This is largely due to the low signal-tonoise ratio of FRET-based probes. We previously reported that hyperspectral imaging improves the signal-to-noise ratio of FRET measurements. Here we utilized hyperspectral imaging approaches to measure FRET signals in five dimensions (5D) – three spatial (x, y, z), wavelength (λ), and time (t) – allowing us to visualize cAMP gradients in pulmonary endothelial cells. cAMP levels were measured using a FRET-based sensor (H188) comprised of a cAMP binding domain sandwiched between FRET donor and acceptor - Turquoise and Venus fluorescent proteins. We observed cAMP gradients in response to 0.1 or 1 μM isoproterenol, 0.1 or 1 μM PGE1, or 50 μM forskolin. Forskolin- and isoproterenol-induced cAMP gradients formed from the apical (high cAMP) to basolateral (low cAMP) face of cells. In contrast, PGE1-induced cAMP gradients originated from both the basolateral and apical faces of cells. Data suggest that 2D (x,y) studies of cAMP compartmentalization may lead to erroneous conclusions about the existence of cAMP gradients, and that 3D (x,y,z) studies are required to assess mechanisms of signaling specificity. Results demonstrate that 5D imaging technologies are powerful tools for measuring biochemical processes in discrete subcellular domains.
Over the past 2 decades, hyperspectral imaging technologies have been adapted to address the need for molecule-specific identification in the biomedical imaging field. Applications have ranged from single-cell microscopy to whole-animal in vivo imaging and from basic research to clinical systems. Enabling this growth has been the availability of faster, more effective hyperspectral filtering technologies and more sensitive detectors. Hence, the potential for growth of biomedical hyperspectral imaging is high, and many hyperspectral imaging options are already commercially available. However, despite the growth in hyperspectral technologies for biomedical imaging, little work has been done to aid users of hyperspectral imaging instruments in selecting appropriate analysis algorithms. Here, we present an approach for comparing the effectiveness of spectral analysis algorithms by combining experimental image data with a theoretical “what if” scenario. This approach allows us to quantify several key outcomes that characterize a hyperspectral imaging study: linearity of sensitivity, positive detection cut-off slope, dynamic range, and false positive events. We present results of using this approach for comparing the effectiveness of several common spectral analysis algorithms for detecting weak fluorescent protein emission in the midst of strong tissue autofluorescence. Results indicate that this approach should be applicable to a very wide range of applications, allowing a quantitative assessment of the effectiveness of the combined biology, hardware, and computational analysis for detecting a specific molecular signature.
Cyclic AMP (cAMP) is a ubiquitous second messenger known to differentially regulate many cellular functions over a wide range of timescales. Several lines of evidence have suggested that the distribution of cAMP within cells is not uniform, and that cAMP compartmentalization is largely responsible for signaling specificity within the cAMP signaling pathway. However, to date, no studies have experimentally measured three dimensional (3D) cAMP distributions within cells. Here we use both 2D and 3D hyperspectral microscopy to visualize cAMP gradients in endothelial cells from the pulmonary microvasculature (PMVECs). cAMP levels were measured using a FRETbased cAMP sensor comprised of a cAMP binding domain from EPAC sandwiched between FRET donors and acceptors — Turquoise and Venus fluorescent proteins. Data were acquired using either a Nikon A1R spectral confocal microscope or custom spectral microscopy system. Analysis of hyperspectral image stacks from a single confocal slice or from summed images of all slices (2D analysis) indicated little or no cAMP gradients were formed within PMVECs under basal conditions or following agonist treatment. However, analysis of hyperspectral image stacks from 3D cellular geometries (z stacks) demonstrate marked cAMP gradients from the apical to basolateral membrane of PMVECs. These results strongly suggest that 2D imaging studies of cAMP compartmentalization — whether epifluorescence or confocal microscopy — may lead to erroneous conclusions about the existence of cAMP gradients, and that 3D studies are required to assess mechanisms of signaling specificity.
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