Transient cholesterol effects on nicotinic acetylcholine receptor cell-surface mobility.

To what extent do cholesterol-rich lipid platforms modulate the supramolecular organization of the nicotinic acetylcholine receptor (AChR)? To address this question, the dynamics of AChR particles at high density and its cholesterol dependence at the surface of mammalian cells were studied by combining total internal reflection fluorescence microscopy and single-particle tracking. AChR particles tagged with a monovalent ligand, fluorescent α-bungarotoxin (αBTX), exhibited two mobile pools: i) a highly mobile one undergoing simple Brownian motion (16%) and ii) one with restricted motion (∼50%), the rest being relatively immobile (∼44%). Depletion of membrane cholesterol by methyl-α-cyclodextrin increased the fraction of the first pool to 22% and 33% after 15 and 40 min, respectively; the pool undergoing restricted motion diminished from 50% to 44% and 37%, respectively. Monoclonal antibody binding results in AChR crosslinking-internalization after 2 h; here, antibody binding immobilized within minutes ∼20% of the totally mobile AChR. This proportion dramatically increased upon cholesterol depletion, especially during the initial 10 min (83.3%). Thus, antibody crosslinking and cholesterol depletion exhibited a mutually synergistic effect, increasing the average lifetime of cell-surface AChRs∼10 s to ∼20 s. The instantaneous (microscopic) diffusion coefficient D2-4 of the AChR obtained from the MSD analysis diminished from ∼0.001 µm2 s(-1) to ∼0.0001-0.00033 µm2 s(-1) upon cholesterol depletion, ∼30% of all particles falling into the stationary mode. Thus, muscle-type AChR exhibits heterogeneous motional regimes at the cell surface, modulated by the combination of intrinsic (its supramolecular organization) and extrinsic (membrane cholesterol content) factors

Investigating early formation of the cerebral cortex by in utero electroporation: Methods and protocols

Cortical development requires a strict balance between neuronal proliferation, differentiation, and cellular migration within restricted developmental stages. The precise spatiotemporal gene manipulation used in developmental studies can be achieved by in vitro or ex vivo experiments or by the generation of transgenic animals. However, these approaches have significant limitations when trying to investigate the origin and molecular regulation of early cortical neurons. In utero electroporation (IUE) is an informative cell labeling technique that provides the ability to label neural progenitor cells and their progeny in vivo with promoter-specific reporter constructs as well as to induce or repress gene expression in a spatially and temporally specific manner. Technical improvements of this method have allowed the targeting of multiple neural cell types, as well as the precise transfection of subpopulations of neurons at increasingly earlier embryonic stages. Furthermore, neuronal projection studies and the use of multiple electroporations in the same embryo have made it possible to examine processes occurring at different developmental stages and/or cortical areas and link their anatomy to their function. In this chapter, we present the latest advances of the in utero electroporation technique for the study of early formation of the cerebral cortex, together with a description of the necessary tools

Time-dependent evolution of the quantitative cluster maps.

<p>a) Alexa488-α-BTX labeled AChR particles imaged with TIRF microscopy in CHO-K1/A5 cells. The left column shows the interpolated cluster maps resulting from local-point pattern analysis of 4×4 µm regions in control and CDx-treated cells at the indicated intervals (10 min, 15 min). The maps, based on Ripley’s K-function <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100346#pone.0100346-Owen1" target="_blank">[39]</a> provide a graphical representation of the degree of aggregation of particles (black dots) per unit area in the entire series of frames. The threshold radius for assigning cluster status to a group of particles is set at 200 nm. The right column corresponds to the map of clustered BTX-stained particles, pseudocolored according to relative brightness of the detected particles. b) Time-dependent evolution of the cluster maps of mAb-crosslinked AChR particles. The left column corresponds to the interpolated cluster map based on Ripley’s K-function applied to CHO-K1/A5 cells labeled with primary anti-AChR monoclonal antibody (mAb210) followed by staining with Alexa⁴⁸⁸-labeled secondary antibody. The right column shows the map of clustered AChR particles pseudocolored according to brightness. Scale bar: 0.2 µm.</p

AChR particle mobility is drastically hindered by antibody crosslinking.

<p>a) Histogram depicting the distribution of diffusion coefficients for all trajectories for control fluorescent mAb-labeled samples (blue), and for samples treated with 10 mM CDx for 10 min (red), 20 min (green) and 40 min (purple), respectively. The shaded inset indicates the upper limit of the microscopic diffusion coefficient D_2–4. One can clearly observe that the amount of particles with D_2–4 below the critical value is higher than in the case of the BTX-labeled samples (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100346#pone-0100346-g005" target="_blank">Figure 5a</a>). b) Histogram showing the proportion of different types of motion undergone by all trajectories (S-simple; D-directed; R-restricted or confined; U-undetermined). The color scale codes for control fluorescent mAb-labeled samples (blue), and samples treated with 10 mM CDx for 10 min (red), 20 min (green) and for 40 min (purple), respectively. c) Representative percentages of types of motion corresponding to the histograms in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100346#pone-0100346-g007" target="_blank">Figure 7b</a>.</p

AChR particle and cluster statistics from the time-series experiments.

<p>The threshold radius for assigning cluster status to a group of particles was set at 200 nm.</p><p>Symbols denote statistically significant differences (Kruskal Wallis test, P<0.05).</p><p>Total number of particles:</p>b<p>exhibited statistically significant difference with a and c.</p>d<p>exhibited statistically significant difference with e, f and g.</p><p>Particles in clusters:</p>b<p>exhibited statistically significant difference with a and c.</p>d<p>exhibited statistically significant difference with e, f and g.</p><p>Brightness:</p>a<p>exhibited statistically significant difference with b and c.</p>e<p>exhibited statistically significant difference with d, f and g.</p

Multiple trajectories of AChR particles labeled with BTX and mAb210, respectively.

<p>Sequence of 15 successive frames (out of a total of 1024) corresponding to control BTX- (left column) and mAb (right column)-labeled samples superimposed on the raw TIRF initial frames. Particles were initially localized using a fixed-width Gaussian fitting. Detected particles were subsequently analyzed for their trajectories with the software Localizer <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100346#pone.0100346-Dedecker1" target="_blank">[34]</a> ran in an Igor-Pro environment. Typical total number of trajectories was in the order of 800 (4%) and 700 (ca. 10%) out of a total of 15,000 and 8,000 for BTX and mAb-labeled samples, respectively. Scale bar = 3 µm.</p

Mobility parameters of AChR particles in samples labeled with Alexa⁴⁸⁸α-BTX or with a primary anti-AChR monoclonal antibody (mAb210) followed by staining with Alexa⁴⁸⁸-labeled secondary antibody, with or without treatment with 15 mM methyl-β-cyclodextrin (CDx).

<p>Mobility parameters of AChR particles in samples labeled with Alexa⁴⁸⁸α-BTX or with a primary anti-AChR monoclonal antibody (mAb210) followed by staining with Alexa⁴⁸⁸-labeled secondary antibody, with or without treatment with 15 mM methyl-β-cyclodextrin (CDx).</p

Detection and visualization of individual particles in a fluorescence TIRF time-series.

<p>A) The three images correspond to the initial frames (1, 5 and 10, respectively) of a time-series obtained from a 7.2×7.2 µm region of a CHO-K1/A5 cell treated with 10 mM CDx for 20 min and labeled with Alexa⁴⁸⁸-αBTX. AChR particles labeled in blue correspond to those detected in the initial phase using the U-track method of Jaqaman et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100346#pone.0100346-Jaqaman1" target="_blank">[26]</a>. Pink-labeled pixels correspond to coincidences between initial estimation of a detected particle and the same, when validated upon optimization by application of the algorithms of Jaqaman et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100346#pone.0100346-Jaqaman1" target="_blank">[26]</a>. B) Visualization of the trajectories followed by several cell-surface AChR particles. The two upper figures correspond to CHO-K1/A5 cells labeled with a monovalent ligand (AlexaFluor⁴⁸⁸α-BTX, left) or BTX followed by CDx treatment. The two lower figures correspond to cells labeled with a multivalent ligand (monoclonal anti-AChR mAb210 antibody followed by AlexaFluor⁴⁸⁸-conjugated IgG secondary antibody) at 4°C and recorded as in Fig. 1. The different trajectories are color-coded to facilitate their identification and their temporal scale: initial (green), middle (blue) and final (red) portions of the trajectory are shown in each case. As a rule, particles were followed for periods of ∼25–40 s (300 initial steps at 12.4–7.5 Hz, 80–130 ms/frame). Notice the relative immobility of the mAb210 antibody-labeled samples in comparison to the α-BTX-labeled samples. Analyzed using the U-track method of Jaqaman et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100346#pone.0100346-Jaqaman1" target="_blank">[26]</a>.</p

Mean square displacement (MSD) of AChR particles in samples labeled with Alexa⁴⁸⁸α-BTX or with anti-AChR monoclonal antibody (mAb210) followed by staining with Alexa⁴⁸⁸-labeled secondary antibody, with or without treatment with 15 mM methyl-β-cyclodextrin (CDx).

<p>Analyzed with the software Localizer <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100346#pone.0100346-Dedecker1" target="_blank">[34]</a>.</p

Individual trajectory and mean-squared displacement (MSD) of an AChR particle.

<p>The upper row shows the displacement of the same particle at the different time points indicated in the graph. The MSD (<i>t</i>) of the fluorescent-labeled particle was calculated for the initial 15 time lag intervals, Δ<i>t</i>, for trajectories longer than a critical number (15) of frames. In the example shown, the time-series was acquired at 20°C in a control CHO-K1/A5 cell labeled with Alexa⁴⁸⁸-α-BTX for 1 h at 4°C. The 2-dimensional MSD (<i>t</i>) for each particlés trajectory (Δ<i>r</i>(Δ<i>t</i>))², was calculated for every time interval <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100346#pone.0100346-Kusumi1" target="_blank">[28]</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100346#pone.0100346-Qian1" target="_blank">[30]</a>.</p