Biomedical subjects

David L Kolin

Publications and source records attributed to David L Kolin.

5 recordsLinked to original sources

PubMed2006

Probing the integrin-actin linkage using high-resolution protein velocity mapping.

Cell migration is regulated in part by the connection between the substratum and the actin cytoskeleton. However, the very large number of proteins involved in this linkage and their complex network of interactions make it difficult to assess their role in cell migration. We apply a novel image analysis tool, spatio-temporal image correlation spectroscopy (STICS), to quantify the directed movements of adhesion-related proteins and actin in protrusions of migrating cells. The STICS technique reveals protein dynamics even when protein densities are very low or very high, and works in the presence of large, static molecular complexes. Detailed protein velocity maps for actin and the adhesion-related proteins alpha-actinin, alpha5-integrin, talin, paxillin, vinculin and focal adhesion kinase are presented. The data show that there are differences in the efficiency of the linkage between integrin and actin among different cell types and on the same cell type grown on different substrate densities. We identify potential mechanisms that regulate efficiency of the linkage, or clutch, and identify two likely points of disconnect, one at the integrin and the other at alpha-actinin or actin. The data suggests that the efficiency of the linkage increases as actin and adhesions become more organized showing the importance of factors that regulate the efficiency in adhesion signaling and dynamics.

3T3 Cells↗

PubMed2006

k-Space image correlation spectroscopy: a method for accurate transport measurements independent of fluorophore photophysics.

We present the theory and application of reciprocal space image correlation spectroscopy (kICS). This technique measures the number density, diffusion coefficient, and velocity of fluorescently labeled macromolecules in a cell membrane imaged on a confocal, two-photon, or total internal reflection fluorescence microscope. In contrast to r-space correlation techniques, we show kICS can recover accurate dynamics even in the presence of complex fluorophore photobleaching and/or "blinking". Furthermore, these quantities can be calculated without nonlinear curve fitting, or any knowledge of the beam radius of the exciting laser. The number densities calculated by kICS are less sensitive to spatial inhomogeneity of the fluorophore distribution than densities measured using image correlation spectroscopy. We use simulations as a proof-of-principle to show that number densities and transport coefficients can be extracted using this technique. We present calibration measurements with fluorescent microspheres imaged on a confocal microscope, which recover Stokes-Einstein diffusion coefficients, and flow velocities that agree with single particle tracking measurements. We also show the application of kICS to measurements of the transport dynamics of alpha5-integrin/enhanced green fluorescent protein constructs in a transfected CHO cell imaged on a total internal reflection fluorescence microscope using charge-coupled device area detection.

Animals↗

PubMed2006

Membrane lateral diffusion and capture of CFTR within transient confinement zones.

The cystic fibrosis transmembrane conductance regulator (CFTR) channel interacts with scaffolding and other proteins that are expected to restrict its lateral movement, yet previous studies have reported predominantly free diffusion. We examined the lateral mobility of CFTR channels on live baby hamster kidney cells using three complementary methods. Channels bearing an extracellular biotinylation target sequence were labeled with streptavidin conjugated with fluorescent dyes (Alexa Fluor 488 or 568) or quantum dots (qDot605). Fluorescence recovery after photobleaching and image correlation spectroscopy of the dye-labeled channels revealed a significant immobile population ( approximately 50%), which was confirmed by direct single particle tracking (SPT) of qDot605-labeled CFTR. Adding 10 histidine residues at the C-terminus of CFTR to mask the postsynaptic density 95, Discs large, ZO-1 (PDZ) binding motif abolished its association with EBP50/NHERF1, reduced the immobile fraction, and increased mobility. Other interactions that are not normally detected on this timescale became apparent when binding of PDZ domain proteins was disrupted. SPT revealed that CFTR(His-10) channels diffuse randomly, become immobilized for periods lasting up to 1 min, and in some instances are recaptured at the same location. The impact of transient confinement on the measured diffusion using the three fluorescence techniques were assessed using computer simulations of the biological experiments. Finally, the impact of endosomal CFTR on mobility measurements was assessed by fluorescence correlation spectroscopy. These results reveal unexpected features of CFTR dynamics which may influence its ion channel activity.

Animals↗

PubMed2005

Sampling effects, noise, and photobleaching in temporal image correlation spectroscopy.

We present an extensive investigation of the accuracy and precision of temporal image correlation spectroscopy (TICS). Using simulations of laser scanning microscopy image time series, we investigate the effect of spatiotemporal sampling, particle density, noise, sampling frequency, and photobleaching of fluorophores on the recovery of transport coefficients and number densities by TICS. We show that the recovery of transport coefficients is usually limited by spatial sampling, while the measurement of accurate number densities is restricted by background noise in an image series. We also demonstrate that photobleaching of the fluorophore causes a consistent overestimation of diffusion coefficients and flow rates, and a severe underestimation of number densities. We derive a bleaching correction equation that removes both of these biases when used to fit temporal autocorrelation functions, without increasing the number of fit parameters. Finally, we image the basal membrane of a CHO cell with EGFP/alpha-actinin, using two-photon microscopy, and analyze a subregion of this series using TICS and apply the bleaching correction. We show that the photobleaching correction can be determined simply by using the average image intensities from the time series, and we use the simulations to provide good estimates of the accuracy and precision of the number density and transport coefficients measured with TICS.

Algorithms↗

PubMed2005

Accuracy and dynamic range of spatial image correlation and cross-correlation spectroscopy.

We present a comprehensive study of the accuracy and dynamic range of spatial image correlation spectroscopy (ICS) and image cross-correlation spectroscopy (ICCS). We use simulations to model laser scanning microscopy imaging of static subdiffraction limit fluorescent proteins or protein clusters in a cell membrane. The simulation programs allow us to control the spatial imaging sampling variables and the particle population densities and interactions and introduce and vary background and counting noise typical of what is encountered in digital optical microscopy. We systematically calculate how the accuracy of both image correlation methods depends on practical experimental collection parameters and characteristics of the sample. The results of this study provide a guide to appropriately plan spatial image correlation measurements on proteins in biological membranes in real cells. The data presented map regimes where the spatial ICS and ICCS provide accurate results as well as clearly showing the conditions where they systematically deviate from acceptable accuracy. Finally, we compare the simulated data with standard confocal microscopy using live CHO cells expressing the epidermal growth factor receptor fused with green fluorescent protein (GFP/EGFR) to obtain typical values for the experimental variables that were investigated in our study. We used our simulation results to estimate a relative precision of 20% for the ICS measured receptor density of 64 microm(-2) within a 121 x 98 pixel subregion of a single cell.

Algorithms↗