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.

Time-resolved fluorescence spectroscopy is a spectroscopist's most valuable tool for the investigation of excited state dynamics in molecules, complexes, or semiconductors. In recent years, the study of luminescence properties has gained in popularity in many scientific fields, including Chemistry, Biology, Physics, as well as in Life, Material or Environmental Sciences. The investigations to be carried out in each of these fields impose different requirements. On one side, monitoring dynamic processes in the excited state necessitates high time resolution that can be achieved by fast pulsed lasers and detectors along with appropriate time-correlated single photon counting (TCSPC) units and small monochromators. On the other hand, high spectral resolution is desirable for fluorophore characterization, requiring detectors with high quantum efficiencies, flash lamps for phosphorescence measurements and large monochromators. Up to now, spectrometers have been usually targeted towards either one of these two specifications. Spectrometers equipped with hybrid detectors, versatile TCSPC cards with optional longer time ranges, and pulsed lasers capable of working in a burst mode can offer an combined solution, covering most of the demands of either high time or spectral resolution. We will demonstrate the performance of such a spectrometer in terms of its time resolution, the ability to measure long decays and record time-gated spectra using laser drivers with burst capabilities. This type of instrument is of great value for analytical facilities in research centers, as it offers a wide range of possible spectroscopic applications in a single, easy to use instrument.

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trafficking, which can be explored by manifold fluorescence spectroscopy techniques. However, none of these experimental tools has been specifically developed to take into account a spatial distribution of directed motions, commonly arising from the active transport of nanoparticles along cytoskeletal networks. To fulfill this gap, we show how a two-dimensional motion driven by Brownian diffusion and flow terms that are uniformly distributed in an angular range can be fully characterized by exploiting general concepts of the spatiotemporal image correlation analysis. The proposed approach can be regarded as an extension of the image-derived mean square displacement method and recovers dynamic and geometric features, which are commonly achieved through single particle analyses. Starting from a time series of the collected images, a spatiotemporal correlation function is computed and studied over the entire domain of the lag-variables. Then, overall information about the investigated dynamics is obtained by decoupling the flow terms, to quantify both the net displacement of the ensemble and the strength of the driving speed. These interdependent contributions are related to the intrinsic anisotropy of the particle flow and the symmetry arising when an angular dispersion affects the directionality of motion. The method has been validated by numeric simulations and in vitro experiments, which demonstrate high stability in the measurement procedure, accurate description of the particle dynamics and low sensitivity to background. Therefore, we argue that it will contribute to advance our understanding about the movement of nanoparticles in cells, their interactions with the biological environment and the subsequent effects on their therapeutic efficiency. The curvature of cellular membranes varies a lot from organelle to organelle and within small subsections of the plasma membrane. A growing amount of evidence suggests that membrane curvature serves a purpose of regulating oligomerization, activity, membrane protein conformation, and recruitment of proteins. We have developed a novel live cell strategy for quantification of protein densities with regard to membrane curvature. This fluorescence-based technique takes advantage of a neuronal-derived cell line forming a high amount of filopodia of various diameters (and therefore various membrane curvatures) serving as a model for highly curved membranes in the cell. Relating the protein density to membrane curvature in the filopodia allows us to asses protein sorting as a function of membrane curvature in living cells. The assay was validated by comparing the membrane localization of the non-curvature sensing, transmembrane protein Aquaporin0, and two I-BAR containing proteins, IRSp53 and MIM, which interact with negatively curved membranes. Quantitative analysis revealed significantly different negative curvature sensing behavior by the Aquaporin0, IRSp53, and MIM. Furthermore, probing three isoforms of Ras GTPases (H-Ras, N-Ras and K-Ras) with this new technique reveal...

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