Naga S. Annamdevula

Hyperspectral imaging microscopy for identification and quantitative analysis of fluorescently-labeled cells in highly autofluorescent tissue

Standard fluorescence microscopy approaches rely on measurements at single excitation and emission bands to identify specific fluorophores and the setting of thresholds to quantify fluorophore intensity. This is often insufficient to reliably resolve and quantify fluorescent labels in tissues due to high autofluorescence. Here we describe the use of hyperspectral analysis techniques to resolve and quantify fluorescently labeled cells in highly autofluorescent lung tissue. This approach allowed accurate detection of green fluorescent protein (GFP) emission spectra, even when GFP intensity was as little as 15% of the autofluorescence intensity. GFP-expressing cells were readily quantified with zero false positives detected. In contrast, when the same images were analyzed using standard (single-band) thresholding approaches, either few GFP cells (high thresholds) or substantial false positives (intermediate and low thresholds) were detected. These results demonstrate that hyperspectral analysis approaches uniquely offer accurate and precise detection and quantification of fluorescence signals in highly autofluorescent tissues.

An approach for characterizing and comparing hyperspectral microscopy systems.

Hyperspectral imaging and analysis approaches offer accurate detection and quantification of fluorescently-labeled proteins and cells in highly autofluorescent tissues. However, selecting optimum acquisition settings for hyperspectral imaging is often a daunting task. In this study, we compared two hyperspectral systems—a widefield system with acoustic optical tunable filter (AOTF) and charge coupled device (CCD) camera, and a confocal system with diffraction gratings and photomultiplier tube (PMT) array. We measured the effects of system parameters on hyperspectral image quality and linear unmixing results. Parameters that were assessed for the confocal system included pinhole diameter, laser power, PMT gain and for the widefield system included arc lamp intensity, and camera gain. The signal-to-noise ratio (SNR) and the root-mean-square error (RMS error) were measured to assess system performance. Photobleaching dynamics were studied. Finally, theoretical sensitivity studies were performed to estimate the incremental response (sensitivity) and false-positive detection rates (specificity). Results indicate that hyperspectral imaging assays are highly dependent on system parameters and experimental conditions. For detection of green fluorescent protein (GFP)-expressing cells in fixed lung tissues, a confocal pinhole of five airy disk units, high excitation intensity and low detector gain were optimal. The theoretical sensitivity studies revealed that widefield hyperspectral microscopy was able to detect GFP with fewer false positive occurrences than confocal microscopy, even though confocal microscopy offered improved signal and noise characteristics. These studies provide a framework for optimization that can be applied to a variety of hyperspectral imaging systems.

In the absence of effector proteins, the Pseudomonas aeruginosa type three secretion system needle tip complex contributes to lung injury and systemic inflammatory responses.

Herein we describe a pathogenic role for the Pseudomonas aeruginosa type three secretion system (T3SS) needle tip complex protein, PcrV, in causing lung endothelial injury. We first established a model in which P. aeruginosa wild type strain PA103 caused pneumonia-induced sepsis and distal organ dysfunction. Interestingly, a PA103 derivative strain lacking its two known secreted effectors, ExoU and ExoT [denoted PA103 (ΔU/ΔT)], also caused sepsis and modest distal organ injury whereas an isogenic PA103 strain lacking the T3SS needle tip complex assembly protein [denoted PA103 (ΔPcrV)] did not. PA103 (ΔU/ΔT) infection caused neutrophil influx into the lung parenchyma, lung endothelial injury, and distal organ injury (reminiscent of sepsis). In contrast, PA103 (ΔPcrV) infection caused nominal neutrophil infiltration and lung endothelial injury, but no distal organ injury. We further examined pathogenic mechanisms of the T3SS needle tip complex using cultured rat pulmonary microvascular endothelial cells (PMVECs) and revealed a two-phase, temporal nature of infection. At 5-hours post-inoculation (early phase infection), PA103 (ΔU/ΔT) elicited PMVEC barrier disruption via perturbation of the actin cytoskeleton and did so in a cell death-independent manner. Conversely, PA103 (ΔPcrV) infection did not elicit early phase PMVEC barrier disruption. At 24-hours post-inoculation (late phase infection), PA103 (ΔU/ΔT) induced PMVEC damage and death that displayed an apoptotic component. Although PA103 (ΔPcrV) infection induced late phase PMVEC damage and death, it did so to an attenuated extent. The PA103 (ΔU/ΔT) and PA103 (ΔPcrV) mutants grew at similar rates and were able to adhere equally to PMVECs post-inoculation indicating that the observed differences in damage and barrier disruption are likely attributable to T3SS needle tip complex-mediated pathogenic differences post host cell attachment. Together, these infection data suggest that the T3SS needle tip complex and/or another undefined secreted effector(s) are important determinants of P. aeruginosa pneumonia-induced lung endothelial barrier disruption.

Spectral imaging of FRET-based sensors reveals sustained cAMP gradients in three spatial dimensions: 4D spectral imaging of FRET-based sensors

Cyclic AMP is a ubiquitous second messenger that orchestrates a variety of cellular functions over different timescales. The mechanisms underlying specificity within this signaling pathway are still not well understood. Several lines of evidence suggest the existence of spatial cAMP gradients within cells, and that compartmentalization underlies specificity within the cAMP signaling pathway. However, to date, no studies have visualized cAMP gradients in three spatial dimensions (3D: x, y, z).This is in part due to the limitations of FRET‐based cAMP sensors, specifically the low signal‐to‐noise ratio intrinsic to all intracellular FRET probes. Here, we overcome this limitation, at least in part, by implementing spectral imaging approaches to estimate FRET efficiency when multiple fluorescent labels are used and when signals are measured from weakly expressed fluorescent proteins in the presence of background autofluorescence and stray light. Analysis of spectral image stacks in two spatial dimensions (2D) from single confocal slices indicates little or no cAMP gradients formed within pulmonary microvascular endothelial cells (PMVECs) under baseline conditions or following 10 min treatment with the adenylyl cyclase activator forskolin. However, analysis of spectral image stacks in 3D demonstrates marked cAMP gradients from the apical to basolateral face of PMVECs. Results demonstrate that spectral imaging approaches can be used to assess cAMP gradients—and in general gradients in fluorescence and FRET—within intact cells. Results also demonstrate that 2D imaging studies of localized fluorescence signals and, in particular, cAMP signals, whether using epifluorescence or confocal microscopy, may lead to erroneous conclusions about the existence and/or magnitude of gradients in either FRET or the underlying cAMP signals. Thus, with the exception of cellular structures that can be considered in one spatial dimension, such as neuronal processes, 3D measurements are required to assess mechanisms underlying compartmentalization and specificity within intracellular signaling pathways.

Comparing methods for analysis of biomedical hyperspectral image data

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.

5D imaging approaches reveal the formation of distinct intracellular cAMP spatial gradients

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.

Three-dimensional measurement of cAMP gradients using hyperspectral confocal microscopy

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.