Fluorescence correlation spectroscopy (FCS) is a powerful technique to investigate molecular dynamics with single molecule sensitivity. In particular, in the life sciences it has found widespread application using fluorescent proteins as molecularly specific labels. However, FCS data analysis and interpretation using fluorescent proteins remains challenging due to typically low signal-to-noise ratio of FCS data and correlated noise in autocorrelated data sets. As a result, naive fitting procedures that ignore these important issues typically provide similarly good fits for multiple competing models without clear distinction of which model is preferred given the signal-to-noise ratio present in the data. Recently, we introduced a Bayesian model selection procedure to overcome this issue with FCS data analysis. The method accounts for the highly correlated noise that is present in FCS data sets and additionally penalizes model complexity to prevent over interpretation of FCS data. Here, we apply this procedure to evaluate FCS data from fluorescent proteins assayed in vitro and in vivo. Consistent with previous work, we demonstrate that model selection is strongly dependent on the signal-to-noise ratio of the measurement, namely, excitation intensity and measurement time, and is sensitive to saturation artifacts. Under fixed, low intensity excitation conditions, physical transport models can unambiguously be identified. However, at excitation intensities that are considered moderate in many studies, unwanted artifacts are introduced that result in nonphysical models to be preferred. We also determined the appropriate fitting models of a GFP tagged secreted signaling protein, Wnt3, in live zebrafish embryos, which is necessary for the investigation of Wnt3 expression and secretion in development. Bayes model selection therefore provides a robust procedure to determine appropriate transport and photophysical models for fluorescent proteins when appropriate models are provided, to help detect and eliminate experimental artifacts in solution, cells, and in living organisms.

Monomeric hIAPP significantly destabilizes both model and live cell membranes by increasing membrane fluidity. This interaction with membranes happens via carpet formation followed by lipid extraction in a concentration dependent manner and thus we propose that hIAPP aggregation prior to membrane interaction may not be necessary for its cytotoxicity.

Amyloid fibril deposition of human islet amyloid polypeptide (hIAPP) in pancreatic islet cells is implicated in the pathogenesis of type II diabetes. A growing number of studies suggest that small peptide aggregates are cytotoxic via their interaction with the plasma membrane, which leads to membrane permeabilization or disruption. A recent study using imaging total internal reflection-fluorescence correlation spectroscopy (ITIR-FCS) showed that monomeric hIAPP induced the formation of cellular plasma membrane microdomains containing dense lipids, in addition to the modulation of membrane fluidity. However, the spatial organization of microdomains and their temporal evolution were only partially characterized due to limitations in the conventional analysis and interpretation of imaging FCS datasets. Here, we apply a previously developed Bayesian analysis procedure to ITIR-FCS data to resolve hIAPP-induced microdomain spatial organization and temporal dynamics. Our analysis enables the visualization of the temporal evolution of multiple diffusing species in the spatially heterogeneous cell membrane, lending support to the carpet model for the association mode of hIAPP aggregates with the plasma membrane. The presented Bayesian analysis procedure provides an automated and general approach to unbiased model-based interpretation of imaging FCS data, with broad applicability to resolving the heterogeneous spatial-temporal organization of biological membrane systems.

Wnt3 is a morphogen that activates the Wnt signaling pathway and regulates a multitude of biological processes ranging from cell proliferation and cell fate specification to differentiation over embryonic induction to neural patterning. Recent studies have shown that the palmitoylation of Wnt3 by Porcupine, a membrane-bound O-acyltransferase, plays a significant role in the intracellular membrane trafficking of Wnt3 and subsequently, its secretion in live zebrafish embryos, where chemical inhibition of Porcupine reduced the membrane-bound and secreted fractions of Wnt3 and eventually led to defective brain development. However, the membrane distribution of Wnt3 in cells remains not fully understood. Here, we determine the membrane organization of functionally active Wnt3-EGFP in cerebellar cells of live transgenic zebrafish embryos and the role of palmitoylation in its organization using single plane illumination microscopy-fluorescence correlation spectroscopy (SPIM-FCS), a multiplexed modality of FCS, which generates maps of molecular dynamics, concentration, and interaction of biomolecules. The FCS diffusion law was applied to SPIM-FCS data to study the subresolution membrane organization of Wnt3. We find that at the plasma membrane in vivo, Wnt3 is associated with cholesterol-dependent domains. This association reduces with increasing concentrations of Porcupine inhibitor (C59), confirming the importance of palmitoylation of Wnt3 for its association with cholesterol-dependent domains. Reduction of membrane cholesterol also results in a decrease of Wnt3 association with cholesterol-dependent domains in live zebrafish. This demonstrates for the first time, to our knowledge, in live vertebrate embryos that Wnt3 is associated with cholesterol-dependent domains.

Fluorescence correlation spectroscopy (FCS) and fluorescence recovery after photobleaching (FRAP) are widely used methods to determine diffusion coefficients. However, they often do not yield the same results. With the advent of camera-based imaging FCS, which measures the diffusion coefficient in each pixel of an image, and proper bleaching corrections, it is now possible to measure the diffusion coefficient by FRAP and FCS in the exact same images. We thus performed simultaneous FCS and FRAP measurements on supported lipid bilayers and live cell membranes to test how far the two methods differ in their results and whether the methodological differences, in particular the high bleach intensity in FRAP, the bleach corrections, and the fitting procedures in the two methods explain observed differences. Overall, we find that the FRAP bleach intensity does not measurably influence the diffusion in the samples, but that bleach correction and fitting introduce large uncertainties in FRAP. We confirm our results by simulations.

Fluorescence correlation spectroscopy (FCS) is a widely used technique in biophysics and has helped address many questions in the life sciences. It provides important advantages compared to other fluorescence and biophysical methods. Its single molecule sensitivity allows measuring proteins within biological samples at physiological concentrations without the need of overexpression. It provides quantitative data on concentrations, diffusion coefficients, molecular transport and interactions even in live organisms. And its reliance on simple fluorescence intensity and its fluctuations makes it widely applicable. In this review we focus on applications of FCS in live samples, with an emphasis on work in the last 5 years, in the hope to provide an overview of the present capabilities of FCS to address biologically relevant questions.

Monomeric hIAPP significantly destabilizes both model and live cell membranes by increasing membrane fluidity. This interaction with membranes happens via carpet formation followed by lipid extraction in a concentration dependent manner and thus we propose that hIAPP aggregation prior to membrane interaction may not be necessary for its cytotoxicity.