To investigate why responses of mast cells to antigen-induced IgE receptor (Fc?RI) aggregation depend nonlinearly on antigen dose, we characterized a new artificial ligand, DF3, through complementary modeling and experimentation. This ligand is a stable trimer of peptides derived from bacteriophage T4 fibritin, each conjugated to a hapten (DNP). We found low and high doses of DF3 at which degranulation of mast cells sensitized with DNP-specific IgE is minimal, but ligand-induced receptor aggregation is comparable to aggregation at an intermediate dose, optimal for degranulation. This finding makes DF3 an ideal reagent for studying the balance of negative and positive signaling in the Fc?RI pathway. We find that the lipid phosphatase SHIP and the protein tyrosine phosphatase SHP-1 negatively regulate mast cell degranulation over all doses considered. In contrast, SHP-2 promotes degranulation. With high DF3 doses, relatively rapid recruitment of SHIP to the plasma membrane may explain the reduced degranulation response. Our results demonstrate that optimal secretory responses of mast cells depend on the formation of receptor aggregates that promote sufficient positive signaling by Syk to override phosphatase-mediated negative regulatory signals.
Many cellular signaling processes are initiated by dimerization or oligomerization of membrane proteins. However, since the spatial scale of these interactions is below the diffraction limit of the light microscope, the dynamics of these interactions have been difficult to study on living cells. We have developed a novel high-speed hyperspectral microscope (HSM) to perform single particle tracking of up to 8 spectrally distinct species of quantum dots (QDs) at 27 frames per second. The distinct emission spectra of the QDs allows localization with ?10 nm precision even when the probes are clustered at spatial scales below the diffraction limit. The capabilities of the HSM are demonstrated here by application of multi-color single particle tracking to observe membrane protein behavior, including: 1) dynamic formation and dissociation of Epidermal Growth Factor Receptor dimers; 2) resolving antigen induced aggregation of the high affinity IgE receptor, Fc?R1; 3) four color QD tracking while simultaneously visualizing GFP-actin; and 4) high-density tracking for fast diffusion mapping.
Single-particle tracking (SPT) using fluorescent quantum dots (QDs) provides high-resolution spatial-temporal information on receptor dynamics that cannot be obtained through traditional biochemical techniques. In particular, the high brightness and photostability of QDs make them ideal probes for SPT on living cells. We have shown that QD-labeled IgE can be used to characterize the dynamics of the high-affinity IgE Receptor. Here, we describe protocols for (1) coupling QDs to IgE, (2) tracking individual QD-bound receptors, and (3) analyzing one- and two-color tracking data.
The extent to which ligand occupancy and dimerization contribute to erbB1 signaling is controversial. To examine this, we used two-color quantum-dot tracking for visualization of the homodimerization of human erbB1 and quantification of the dimer off-rate (k(off)) on living cells. Kinetic parameters were extracted using a three-state hidden Markov model to identify transition rates between free, co-confined and dimerized states. We report that dimers composed of two ligand-bound receptors are long-lived and their k(off) is independent of kinase activity. By comparison, unliganded dimers have a more than four times faster k(off). Transient co-confinement of receptors promotes repeated encounters and enhances dimer formation. Mobility decreases more than six times when ligand-bound receptors dimerize. Blockade of erbB1 kinase activity or disruption of actin networks results in faster diffusion of receptor dimers. These results implicate both signal propagation and the cortical cytoskeleton in reduced mobility of signaling-competent erbB1 dimers.
We report a method for tracking individual quantum dot (QD) labeled proteins inside of live cells that uses four overlapping confocal volume elements and active feedback once every 5 ms to follow three-dimensional molecular motion. This method has substantial advantages over three-dimensional molecular tracking methods based upon charge-coupled device cameras, including increased Z-tracking range (10 ?m demonstrated here), substantially lower excitation powers (15 ?W used here), and the ability to perform time-resolved spectroscopy (such as fluorescence lifetime measurements or fluorescence correlation spectroscopy) on the molecules being tracked. In particular, we show for the first time fluorescence photon antibunching of individual QD labeled proteins in live cells and demonstrate the ability to track individual dye-labeled nucleotides (Cy5-dUTP) at biologically relevant transport rates. To demonstrate the power of these methods for exploring the spatiotemporal dynamics of live cells, we follow individual QD-labeled IgE-Fc?RI receptors both on and inside rat mast cells. Trajectories of receptors on the plasma membrane reveal three-dimensional, nanoscale features of the cell surface topology. During later stages of the signal transduction cascade, clusters of QD labeled IgE-Fc?RI were captured in the act of ligand-mediated endocytosis and tracked during rapid (~950 nm/s) vesicular transit through the cell.
In this paper we report the application of a novel method for fitting kinetic models to temporally resolved hyperspectral images of fluorescently labeled cells to mathematically resolve pure-component spatial images, pure-component spectra, and pure-component reaction profiles. The method is demonstrated on one simulated image and two experimental cell images, including human embryonic kidney cells (HEK 293) and human A549 pulmonary type II epithelial cells. In both cell images, inhibitor kappa B kinase alpha (IKK(alpha)) and mitochondrial antiviral signaling protein (MAVS) were labeled with green and yellow fluorescent protein, respectively. Kinetic modeling was performed on the compressed images by using a separable least squares method. A combination of several first-order decays were needed to adequately model the photobleaching processes for each fluorophore observed in these images, consistent with the hypothesis that each fluorophore was found in several different environments within the cells. Numerous plausible mechanisms for kinetic modeling of the photobleaching processes in these images were tested and a method for selecting the most parsimonious and statistically sufficient model was used to prepare spatial maps of each fluorophore.
Elucidating kinetic information (rate constants) from temporally resolved hyperspectral confocal fluorescence images offers some very important opportunities for the interpretation of spatially resolved hyperspectral confocal fluorescence images but also presents significant challenges, these being (1) the massive amount of data contained in a series of time-resolved spectral images (one time course of spectral data for each pixel) and (2) unknown concentrations of the reactants and products at time = 0, a necessary precondition normally required by traditional kinetic fitting approaches. This paper describes two methods for solving these problems: direct nonlinear (DNL) estimation of all parameters and separable least squares (SLS). The DNL method can be applied to reactions of any rate law, while the SLS method is restricted to first-order reactions. In SLS, the inherently linear and nonlinear parameters of first-order reactions are solved in separate linear and nonlinear steps, respectively. The new methods are demonstrated using simulated data sets and an experimental data set involving photobleaching of several fluorophores. This work demonstrates that both DNL and SLS hard-modeling methods applied to the kinetic modeling of temporally resolved hyperspectral images can outperform traditional soft-modeling and hard/soft-modeling methods which use multivariate curve resolution-alternating least squares (MCRALS) methods. In addition, the SLS method is much faster and is able to analyze much larger data sets than the DNL method.
Protein folding is a complex process that can take place through different pathways depending on the inducing agent and on the monitored time scale. This diversity of possibilities requires a good design of experiments and powerful data analysis tools that allow operating with multitechnique measurements and/or with diverse experiments related to different aspects of the process of interest. Multivariate curve resolution-alternating least squares (MCR-ALS) has been the core methodology used to perform multitechnique and/or multiexperiment data analysis. This algorithm allows for obtaining the process concentration profiles and pure spectra of all species involved in the protein folding from the sole raw spectroscopic measurements obtained during the experimental monitoring. The process profiles provide insight on the mechanism of the process studied whereas the shapes of the recovered pure spectra help in the characterization of the protein conformations involved. Relevant features of the MCR-ALS algorithm are the possibility to handle fused data, i.e., series of experiments monitored with different techniques and/or performed under different experimental conditions, and the flexibility to include a priori information linked to general properties of concentration profiles and spectra and to the kinetic model governing the folding process. All these characteristics help to obtain a comprehensive description of the protein folding mechanism. To our knowledge, this work includes for the first time the simultaneous analysis of steady-state and short-time scale kinetic experiments linked to a protein folding process. The potential of this methodology is shown taking myoglobin as a model system for protein folding or, in general, for the study of any complex biological process that needs multitechnique and multiexperiment monitoring and analysis. Transformations in myoglobin due to changes in pH have been monitored by ultraviolet/visible (UV-vis) absorption and circular dichroism (CD) spectroscopy. Steady-state and stopped-flow experiments were carried out to account for the evolution of the process at different time scales. In this example, the multiexperiment analysis has allowed for the reliable detection and modeling of a kinetic transient species in the myoglobin folding process, absent in the steady-state working conditions.
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