Spatio-temporal Model of Endogenous ROS and Raft-Dependent WNT/Beta-Catenin Signaling Driving Cell Fate Commitment in Human Neural Progenitor Cells

<div><p>Canonical WNT/β-catenin signaling is a central pathway in embryonic development, but it is also connected to a number of cancers and developmental disorders. Here we apply a combined in-vitro and in-silico approach to investigate the spatio-temporal regulation of WNT/β-catenin signaling during the early neural differentiation process of human neural progenitors cells (hNPCs), which form a new prospect for replacement therapies in the context of neurodegenerative diseases. Experimental measurements indicate a second signal mechanism, in addition to canonical WNT signaling, being involved in the regulation of nuclear β-catenin levels during the cell fate commitment phase of neural differentiation. We find that the biphasic activation of β-catenin signaling observed experimentally can only be explained through a model that combines Reactive Oxygen Species (ROS) and raft dependent WNT/β-catenin signaling. Accordingly after initiation of differentiation endogenous ROS activates DVL in a redox-dependent manner leading to a transient activation of down-stream β-catenin signaling, followed by continuous auto/paracrine WNT signaling, which crucially depends on lipid rafts. Our simulation studies further illustrate the elaborate spatio-temporal regulation of DVL, which, depending on its concentration and localization, may either act as direct inducer of the transient ROS/β-catenin signal or as amplifier during continuous auto-/parcrine WNT/β-catenin signaling. In addition we provide the first stochastic computational model of WNT/β-catenin signaling that combines membrane-related and intracellular processes, including lipid rafts/receptor dynamics as well as WNT- and ROS-dependent β-catenin activation. The model’s predictive ability is demonstrated under a wide range of varying conditions for in-vitro and in-silico reference data sets. Our in-silico approach is realized in a multi-level rule-based language, that facilitates the extension and modification of the model. Thus, our results provide both new insights and means to further our understanding of canonical WNT/β-catenin signaling and the role of ROS as intracellular signaling mediator.</p></div

Experimental data vs. Simulation results.

<p>Nuclear <i>β</i>-catenin concentration fold changes in comparison between experimental data and the validated WNT/<i>β</i>-catenin model. The simulation result (red) of the WNT/<i>β</i>-catenin model (cf. <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004106#pcbi.1004106.g002" target="_blank">Fig. 2</a>, parametrized according to <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004106#pcbi.1004106.t001" target="_blank">Table 1</a>) matches all experimental values (blue) in untreated control cells (A). Though, in its current state it is not capable of reproducing the immediate early <i>β</i>-catenin activation in raft-deficient cells (B). Simulation results correspond to the mean simulation trajectory (red) with 95% confidence interval (gray error bars).</p

Parameter Table of the WNT/<i>β</i>-catenin model.

<p>Parameter and reference values of the WNT/<i>β</i>-catenin model as depicted in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004106#pcbi.1004106.g002" target="_blank">Fig. 2</a>. <b>Bold:</b> literature values, <i>Italics</i>: fitted values.</p><p>Parameter Table of the WNT/<i>β</i>-catenin model.</p

Table of varying WNT stimuli.

<p>Varying WNT stimuli applied in vitro by <i>Hannoush</i> and corresponding input parameter (k1/kWsyn) for model simulations. Concentration values have been recalculated to molecule numbers per available volume (membrane) (details see Text (Paragraph “Validation of the model”)).</p><p>Table of varying WNT stimuli.</p

Extended WNT/<i>β</i>-catenin model including ROS/<i>β</i>-catenin signaling.

<p>Schematic view of the extended WNT/<i>β</i>-catenin model illustrating the potential interplay between WNT/<i>β</i>-catenin- and DVL-mediated ROS/<i>β</i>-catenin signaling. In addition to the previous model (cf. <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004106#pcbi.1004106.g002" target="_blank">Fig. 2</a>), the newly introduced WNT-independent redox-signaling is depicted in the lower right. Two-sided arrows indicate reversible reactions. Dashed phosphorylation signs indicate that the depicted protein complex (i.e. AXIN/DVL and AXIN/DVL/LRP6) and the corresponding reactions occur independently of the phosphorylation state. The corresponding reaction rate constants are listed in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004106#pcbi.1004106.t001" target="_blank">Table 1</a> and <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004106#pcbi.1004106.t003" target="_blank">Table 3</a>. The entire model implementation in ML-Rules can be found in the Supporting Information (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004106#pcbi.1004106.s009" target="_blank">S4 Text</a>).</p

Impact of raft disruption on temporal regulation of nuclear <i>β</i>-catenin concentration after induction of differentiation in ReNCell VM197.

<div><p>(A) Confocal microscopy images of Lipid Rafts staining (red) in control (upper row) and raft-deficient, MbCD treated cells (lower row). Cell surface was stained with Vybrant Lipid Raft Labelling kit and nuclei were stained with Hoechst staining. Scale bar 10<i>μ</i>m.</p> <p>(B-C) Time-dependent relative concentration levels of nuclear <i>β</i>-catenin during differentiation with (C) and without (B) MbCD treatment. Graphs show data of four and three independent experiments for control and MbCD-treated cells, respectively, as mean ± SEM, Student’s t-test (*p < 0.05; **p < 0.01; significant difference from 0h (proliferation); ^‡p < 0.05; significant difference between control and MbCD treated cells at specific time point), <i>β</i>-Actin was used a loading control.</p> <p>(D) Confocal microscopy images of nuclear <i>β</i>-catenin signal intensity in control and MbCD treated cells during differentiation confirm western blot data. Cells were labeled with anti-<i>β</i>-catenin antibody (red) and Hoechst Nuclei staining. Scale bar = 10<i>μ</i>m. For illustration purpose, only the <i>β</i>-catenin concentration within the nuclei are shown and other cell compartments, like cytoplasm and membrane are excluded from the view. Please see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004106#pcbi.1004106.s002" target="_blank">S2 Fig</a> and <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004106#pcbi.1004106.s003" target="_blank">S3 Fig</a> for the entire microscopy images from which nuclei sections were extracted.</p></div

Confocal Microscopy of mitochondrial ROS level.

<p>Confocal microscopy of mito-ROS levels for untreated (control) cells and MbCD-treated cells. Proliferating cells have been treated with H₂O₂ as positive control and MbCD for 1 hour (first column). 1 hour after induction of differentiation cells show a marked increase of mito-ROS levels, and subsequent decrease after 3 hours. Images further confirm that neither proliferating nor differentiating cells are subject to crucial changes in mitochondrial ROS level due to raft disruption through MbCD treatment. Scale bar 20 <i>μ</i>m.</p

<i>β</i>-catenin activation in response to transient and continuous WNT stimuli.

<div><p>(A-B) Comparison of simulation results (<i>β</i>-catenin concentration fold change) between the newly derived WNT/<i>β</i>-catenin signaling model (red line) and the Lee model (blue, dashed line) [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004106#pcbi.1004106.ref027" target="_blank">27</a>] in response to a transient WNT stimulus. Without adaptation both models expose a similar excitation level, but the temporal scale differs significantly (A). Adopting the temporal scale of our WNT/<i>β</i>-catenin signaling model yields similar simulation results for both models (B).</p> <p>(C) <i>β</i>-catenin accumulation after 2 hours of WNT stimulation with varying concentrations, compared between our simulation results (red line) and experimental in-vitro measurements by <i>Hannoush</i> (blue line) [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004106#pcbi.1004106.ref049" target="_blank">49</a>]. Parametrization of the <i>β</i>-catenin model is exactly the same as listed in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004106#pcbi.1004106.t001" target="_blank">Table 1</a>, despite the WNT production rate (<i>k</i>1), which has been parameterized in accordance to the varying WNT stimuli applied by <i>Hannoush</i>, cf. <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004106#pcbi.1004106.t002" target="_blank">Table 2</a>. The simulation results match almost perfectly with the experimental data for all WNT concentrations applied. Note that the in-silico <i>β</i>-catenin concentration values are scaled by a linear scaling factor to allow a comparison with the experimentally derived values, that measure the <i>β</i>-catenin accumulation based on fluorescence intensities, instead of concentration or fold changes. Simulation results for our model corresponds to mean simulation trajectory (red) with 95% confidence interval (gray error bars).</p></div

WNT/<i>β</i>-catenin model combining membrane and intracellular kinetics.

<p>Schematic view of the implemented model combining membrane and intracellular kinetics of WNT/<i>β</i>-catenin signaling. In the upper half all membrane-related dynamics included in the model are illustrated. The lower half shows the intracellular processes incorporated in the model, i.e. cytosolic and nuclear dynamics as modeled in [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004106#pcbi.1004106.ref044" target="_blank">44</a>]. Two-sided arrows indicate reversible reactions. Dashed phosphorylation signs indicate that the depicted protein complex (i.e. AXIN/LRP6) and the corresponding reactions occur independently of the phosphorylation state. The corresponding reaction rate constants are listed in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004106#pcbi.1004106.t001" target="_blank">Table 1</a>. For the formal model implementation in ML-Rules see Supporting Information (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004106#pcbi.1004106.s008" target="_blank">S3 Text</a>).</p

Additional file 6: Figure S5. of GMP-conformant on-site manufacturing of a CD133+ stem cell product for cardiovascular regeneration

Representative ISHAGE-based gating strategy used for the quality control of the automatically generated cell product (CP). Debris was excluded from CD45+ cells (a). CD34+ cells were selected from viable CD45+ cells (b). Events with high expression of the CD45 marker were excluded from viable CD45+/CD34+cells (c). FSC/SSC backgate was employed to select viable CD45+/CD34+ hematopoietic progenitor cells (HPCs) with blast morphology (d). Viable CD45+/CD34+/CD133+ cells were selected (e). Events with high expression of the CD45 marker were excluded from viable CD45+/CD34+/CD133+ cells (f). FSC/SSC backgate was employed to select viable CD45+/CD34+/CD133+ HPCs with blast morphology (g). A control gate (‘Ly’, lymphocytes) was used during exclusion of mature CD45+ HSCs. Red: target cell population. Gray: dead cells. (PDF 374 kb