Extended section imaging property charts from layer and solution-based calibration samples.

<p>Comparable eSIP analysis using the same microscopic system with a homogenous fluorescent layer (<b>A</b>) and the solution-based calibration sample (<b>B</b>). Axial profiles (z profile) are shown in 5 different spatial positions (shown as a scheme within the plot). The 'Var over Mean' plot is scaled to maximum frequency in each Intensity bin to account for the different intensity distributions for layer and solution. The conversion factor (<i>CF</i>) is obtained by a linear fit (black line), which is 527.87±0.17 for the layer and 511.02±0.22 for the solution-based approach. The regression coefficient <i>R</i>² is given to describe the goodness of fit. All eSIP parameters are shown as 3 dimensional plots: Intensity (<i>A</i>) in percent of the maximal photon number (<i>p</i>_max), axial position (<i>z</i>₀) in μm, FWHM or steepness (<i>ω</i>_<i>FWHM</i>) in μm, offset (<i>I</i>₀) in digital levels (DL), skewness (<i>s</i>) or length constant (<i>LC</i>) in 1/μm and the Lorentz-Gauss fraction (<i>m</i>_<i>L</i>). Additional scanning parameters: excitation 440 nm with 2% laser power, emission Channel 529 nm centre wavelength, pinhole 0.5 AU, detector gain 700V, 354 x 354 μm field of view with 512 x 512 pixels, pixel dwell time 1.58 μs, and axial spacing is in (A) 0.2 μm and in (B) sequentially 0.1 μm (10 μm around the glass/solution border), 1 μm (for adjacent 45 μm) and 5 μm (for adjacent 200 μm).To give an impression on the computational load: The analysis of the data from (B) took about 3 minutes using a scripting language (MATLAB) on a good equipped office calculator (Intel Core i7 3.2GHz 64 bit system with 32 GB). An analysis of the data from (A) using the SIP approach published by Brakenhoff et al. can be found in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0134980#pone.0134980.s002" target="_blank">S2 Fig</a>.</p

Using section imaging property parameters to optimize microscope system settings.

<p>To estimate the correction collar setting at a Zeiss LSM 510 confocal microscope, a series of eSIP measurements can be used to define the influence on single eSIP parameters. (<b>A</b>) 2d plot of the intensity parameter for correction collar settings of a 40x/1.2 W C-Apochromat (Zeiss) ranging from 0.14 to 0.19 obtained at a wavelength range from 500 nm to 740 nm with pinhole setting 1.0 AU is shown. The data is derived from a 115 x 115 μm centre region of each plane. Although using an Apochromat the emission wavelength dependency is evident in this measurement. However the optimal settings can easily be found. In analogue fashion the influence of the correction collar was analysed based on the <i>ω</i>_<i>FWHM</i> parameter (<b>B</b>). Interestingly, there is no wavelength dependency for this parameter. Analysing the collimator setting in a lux-FRET paradigm with two different excitations at a Zeiss LSM 780 utilizing a 40x/1.2 W C-Apochromat objective revealed different optimal settings in respect to the observed parameter (<b>C and D</b>). In contrast to an optimization according to the maximal intensity (black), we found a different optimal setting, when the axial position difference between first (440 nm) and the second excitation (488 nm) is measured (red). For the collimator setting series we tested the solution-based approach (<b>C</b>) as well as the Argolight calibration slide (<b>D</b>).</p

Schematic representations of the two basic calibration concepts.

<p>The fit approach to measure eSIP parameters using a homogenous fluorescent layer (<b>A</b>) reveals the parameters amplitude (<i>A</i>), full width at half maximum (<i>ω</i>_<i>FWHM</i>), the axial position (<i>z</i>₀) and the offset (<i>I</i>₀). The skewness parameter and the Lorentz-Gauss fraction are not shown. If the solution-based sample is used (<b>B</b>) the steepness of the profile can also be expressed by <i>ω</i>_<i>FWHM</i> (compare Eqs <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0134980#pone.0134980.e005" target="_blank">5</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0134980#pone.0134980.e011" target="_blank">9</a>.), and instead of the skewness parameter we included the length constant (<i>LC</i>). Example data are shown in grey, and an appropriate fit is shown in black.</p

Moiré artefacts using structured calibration samples.

<p>Example images of maximum projections, taken from a structured non-homogenous layer (Argolight calibration sample). The depicted images show the same field of view of a vertical grid structure (the “homogenous pattern” of the Argolight slide), which were either scanned perpendicular to the grid (<b>A-D</b>) or in a parallel fashion (<b>E-H</b>) with a decreasing pixel size (increasing number of pixels). A Fourier analysis in x direction of the images (<b>I and J</b>) reveals several instances of moiré artefacts (arrow) in addition to the frequency of the grid itself (arrow head). At low resolution (<b>A and E</b>), these artefacts are dominating the images; the grid structure itself becomes invisible.</p

Gaining information on X and Y from a commercially available calibration sample.

<p>Neither the layer- nor the solution-based eSIP approach provide information about the lateral imaging properties. Utilizing defined fluorescent structures makes it possible to describe aberrations in these dimensions, too. The grid structure on the commercially available Argolight slide was imaged using two excitation wavelength (440 nm and 488 nm) and maximized field of view (<b>A</b>). The analysis of this grid structure revealed strong distortions which can be quantified using second order polynomial fits. To depict this aberration, the second order term (multiplied with 10⁵) is shown next to the corresponding fit (white lines) for the first excitation (<b>B)</b>. The difference in the two excitations is depicted in <b>C</b> as vectors at the position of grid crossings reflecting the direction and the size of the shift (the size of the arrows are multiplied by 100 for visibility).</p

Cleavage of Hyaluronan and CD44 Adhesion Molecule Regulate Astrocyte Morphology via Rac1 Signalling

<div><p>Communication of cells with their extracellular environment is crucial to fulfill their function in physiological and pathophysiological conditions. The literature data provide evidence that such a communication is also important in case of astrocytes. Mechanisms that contribute to the interaction between astrocytes and extracellular matrix (ECM) proteins are still poorly understood. Hyaluronan is the main component of ECM in the brain, where its major receptor protein CD44 is expressed by a subset of astrocytes. Considering the fact that functions of astrocytes are tightly coupled with changes in their morphology (e.g.: glutamate clearance in the synaptic cleft, migration, astrogliosis), we investigated the influence of hyaluronan cleavage by hyaluronidase, knockdown of CD44 by specific shRNA and CD44 overexpression on astrocyte morphology. Our results show that hyaluronidase treatment, as well as knockdown of CD44, in astrocytes result in a “stellate”-like morphology, whereas overexpression of CD44 causes an increase in cell body size and changes the shape of astrocytes into flattened cells. Moreover, as a dynamic reorganization of the actin cytoskeleton is supposed to be responsible for morphological changes of cells, and this reorganization is controlled by small GTPases of the Rho family, we hypothesized that GTPase Rac1 acts as a downstream effector for hyaluronan and CD44 in astrocytes. We used FRET-based biosensor and a dominant negative mutant of Rac1 to investigate the involvement of Rac1 activity in hyaluronidase- and CD44-dependent morphological changes of astrocytes. Both, hyaluronidase treatment and knockdown of CD44, enhances Rac1 activity while overexpression of CD44 reduces the activity state in astrocytes. Furthermore, morphological changes were blocked by specific inhibition of Rac1 activity. These findings indicate for the first time that regulation of Rac1 activity is responsible for hyaluronidase and CD44-driven morphological changes of astrocytes.</p></div

Deactivation of Rac1 activity rescues CD44 knockdown and hyaluronidase-induced morphological changes of astrocytes.

<p>A: Representative images of astrocytes transfected with CD44shRNA/pSuper or co-transfected with pcDNA3-EGFP-Rac1-T17N (Rac1-DN) constructs. The β-actin-RFP construct was used for cell visualization. Scale: 20 μm. B: Morphometric analysis of shape-describing parameters of cells treated as in A. One way ANOVA, area: F(3.112) = 2.456, p>0,05, solidity: F(3.114) = 30.173, p<0.001 Sidak post hoc test, circularity: F(3.114) = 13.834, p<0.001, branching: F(3.114) = 51, 825, p<0,001. Dunnett’s C post hoc test. C: Representative images of astrocytes transfected with pcDNA3-EGFP-Rac1-T17N (Rac1-DN) and β-actin-RFP constructs and treated with hyaluronidase. Scale: 20 μm. D: Morphometric analysis of shape-describing parameters of cells treated as in C. One way ANOVA, area: F(2.147) = 1.520, p>0.05, solidity: F(2.147) = 106.292, p<0.001, circularity: F(2.147) = 96.843, p<0.001, branching: F(2.147) = 135.932; p<0,001, Dunnett’s C post hoc tests.</p

Hyaluronidase treatment and CD44-knockdown leads to enhanced Rac1 activity.

<p>A: Cells were transfected with FRET based biosensor pRaichu-Rac1/1011X and then treated or not with hyaluronidase for 24h. YFP-CFP ratio was calculated as a readout of Rac1 activity. T-Student test, t(589) = 3.212; p<0,001. B: Cells were co-transfected with pRaichu-Rac1/1011X and pSuper/CD44shRNA/CD44-RFP constructs. YFP-CFP ratio was calculated as a readout of Rac1 activity. One way ANOVA, F(2.527) = 39.998; p<0.001, Sidak post hoc test.</p

Astrocytes treated with hyaluronidase acquire the stellate-like morphology.

<p>A. Hyaluronan digestion by hyaluronidase was evaluated by staining with hyaluronan binding protein (HABP) (red). Scale: 30 μm. B. Measurement of fluorescence intensity. One way ANOVA test was performed, F(2.57) = 53.169; p<0.001, Dunnett’s C post hoc. C. Representative images of astrocytes transfected with β-actin GFP and either untreated (control) or treated with hyaluronidase or heat inactivated hyaluronidase for 48h. Cell nuclei were visualized with DAPI staining. Scale: 30 μm.D. Morphometric analysis of shape-describing parameters of cells treated as described in C. One way ANOVA test was performed, area: F(2.57) = 2.658; p>0.05, solidity: F(2.57) = 16.814; p<0.001, circularity: F(2.57) = 13.799; p<0.001, branching: F(2.57) = 16.774; p<0,001 Dunnett’s C post hoc test.</p

CD44 regulates astrocyte morphology.

<p>A: Validation of CD44shRNA and CD44-GFP constructs. Astrocytes were transfected with pSuper, CD44shRNA or CD44-GFP constructs (together with β-actin-GFP plasmid) and then immunostained with anti-CD44 antibody (red). The level of CD44 expression was evaluated by measuring CD44 immunofluorescence (IF) signal intensity with the use of ImageJ program. One way ANOVA, F(2.71) = 71.187, p<0.001, Dunnett C post hoc tests. Scale: 30 μm. B: Morphological analysis of shape-describing parameters of astrocytes in 2D cultures co-transfected with pSuper, CD44shRNA or CD44shRNA/CD44Rescue constructs together with β-actin-GFP plasmid. One way ANOVA test was performed, area: F(3.150) = 8.169; p<0.001, solidity: F(3.153) = 21.454; p<0.001, circularity: F(3.153) = 18.873; p<0.001, Dunnett’s C post hoc tests, branching: F(3.151) = 33,478; p<0.001, Sidak post hoc test. Scale: 30 μm. C: The morphological analysis of shape-describing parameters of astrocytes in 3D cultures transfected with pSuper or CD44shRNA constructs (together with β-actin-GFP plasmid) or CD44-GFP. One way ANOVA test was performed, area: F(2.92) = 12.311; p<0.001, Sidak post hoc test; solidity: F(2.95) = 42.208; p<0.001, Dunnett’s C post hoc test, circularity: F(2.94) = 20.609; p<0.001, Dunnett’s C post hoc test, branching: F(2.95) = 17.703; p<0.001, Sidak post hoc test. Scale: 30 μm.</p