Strategy employed to quantify modulator-triggered changes in the leading edge area, or in key leading edge signaling reactions.

<p>Representative pair of RAW 264.7 cells treated with activator (ATP) in the top two rows and inhibitor (Go6976) in the bottom two rows, showing the masks used to quantify leading edge area and activity changes. <b>(A)</b> Leading edge <u><i>area</i></u> changes were determined by first outlining the leading edge region using the freehand selection tool in FIJI, while excluding the bulk of the cell body. The mask baseline (yellow line) was added at the base of the actively ruffling leading edge membrane prior to modulator addition. Changing leading edge area subsequent to addition of modulator, or modulator vehicle, was measured relative to that baseline at time = 0. <b>(B)</b> Leading edge <u><i>activity</i></u> changes were quantified by measuring sensor fluorescence (XFP sensor or CKAR or CellMask) within a defined boundary, depicted by the yellow outline enclosing a portion of leading edge membrane and adjacent cytoplasm. As the timecourse progressed, the mask was manually moved in order to remain proximal to the leading edge boundary. Additional details in Methods.</p

Steady-state changes in leading edge area following modulator addition.

<p>Polarized, actively ruffling RAW macrophages expressing the indicated activity sensor were imaged at specific times following addition of the indicated modulators (green = activator, red = inhibitor, black = carrier medium control). Open bars represent the initial leading edge area, normalized to 1.0, immediately after modulator addition. Filled bars represent the fold change as the leading edge area approaches a new steady state size approximately 5 min after modulator addition (t = 4.5 to 5.5 min (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0196678#sec012" target="_blank">Methods</a>)). As expected for functional leading edge signaling in all sensor backgrounds, activators trigger significant leading edge expansion, inhibitors trigger significant leading edge contraction, and controls have no significant effect. Error bars represent standard errors of the mean for 15–35 cells measured in at least 4 independent experiments. Asterisks indicate significance of each change from the initial area at t = 0 (one, two or three asterisks indicate p < 0.05, p < 0.01, or p < 0.001, respectively). Image analysis described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0196678#pone.0196678.g002" target="_blank">Fig 2A</a> and Methods.</p

A PKC-MARCKS-PI3K regulatory module links Ca²⁺ and PIP₃ signals at the leading edge of polarized macrophages

<div><p>The leukocyte chemosensory pathway detects attractant gradients and directs cell migration to sites of inflammation, infection, tissue damage, and carcinogenesis. Previous studies have revealed that local Ca²⁺ and PIP₃ signals at the leading edge of polarized leukocytes play central roles in positive feedback loop essential to cell polarization and chemotaxis. These prior studies showed that stimulation of the leading edge Ca²⁺ signal can strongly activate PI3K, thereby triggering a larger PIP₃ signal, but did not elucidate the mechanistic link between Ca²⁺ and PIP₃ signaling. A hypothesis explaining this link emerged, postulating that Ca²⁺-activated PKC displaces the MARCKS protein from plasma membrane PIP₂, thereby releasing sequestered PIP₂ to serve as the target and substrate lipid of PI3K in PIP₃ production. <i>In vitro</i> single molecule studies of the reconstituted pathway on lipid bilayers demonstrated the feasibility of this PKC-MARCKS-PI3K regulatory module linking Ca²⁺ and PIP₃ signals in the reconstituted system. The present study tests the model predictions in live macrophages by quantifying the effects of: (a) two pathway activators—PDGF and ATP that stimulate chemoreceptors and Ca²⁺ influx, respectively; and (b) three pathway inhibitors—wortmannin, EGTA, and Go6976 that inhibit PI3K, Ca²⁺ influx, and PKC, respectively; on (c) four leading edge activity sensors—AKT-PH-mRFP, CKAR, MARCKSp-mRFP, and leading edge area that report on PIP₃ density, PKC activity, MARCKS membrane binding, and leading edge expansion/contraction, respectively. The results provide additional evidence that PKC and PI3K are both essential elements of the leading edge positive feedback loop, and strongly support the existence of a PKC-MARCKS-PI3K regulatory module linking the leading edge Ca²⁺ and PIP₃ signals. As predicted, activators stimulate leading edge PKC activity, displacement of MARCKS from the leading edge membrane and increased leading edge PIP₃ levels, while inhibitors trigger the opposite effects. Comparison of the findings for the ameboid chemotaxis of leukocytes with recently published findings for the mesenchymal chemotaxis of fibroblasts suggests that some features of the emerging leukocyte leading edge core pathway (PLC-DAG-Ca²⁺-PKC-MARCKS-PIP₂-PI3K-PIP₃) may well be shared by all chemotaxing eukaryotic cells, while other elements of the leukocyte pathway may be specialized features of these highly optimized, professional gradient-seeking cells. More broadly, the findings suggest a molecular mechanism for the strong links between phospho-MARCKS and many human cancers.</p></div

A PKC-MARCKS-PI3K regulatory module links Ca²⁺ and PIP₃ signals at the leading edge of polarized macrophages - Fig 5

<p><b>Timecourses of leading edge area changes (A) and leading edge activity changes (B-E) following modulator addition.</b> Timecourses were measured for same polarized, actively ruffling RAW macrophages imaged in Figs <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0196678#pone.0196678.g002" target="_blank">2</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0196678#pone.0196678.g003" target="_blank">3</a> (see those figure legends for additional details) following addition of the indicated modulators (green = activator, red = inhibitor, open = carrier medium control). (A) The area change data indicate that the leading edge area expansion triggered by activators is slower, and appears to exhibit biphasic kinetics with a lag phase, compared to the more monophasic contraction triggered by inhibitors. (B-D) The most rapid leading edge activity changes are observed for the inhibitor-triggered decreased in PIP₃ density sensed by AKTPH-mRFP, while the slowest change is observed for the attractant PDGF-triggered dissociation of MARCKSp-mRFP from the leading edge membrane. Error bars represent standard errors of the mean for 15–35 cells measured in at least 4 independent experiments.</p

Steady state changes in leading edge activity sensors following modulator addition.

<p>The same polarized, actively ruffling RAW macrophages imaged in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0196678#pone.0196678.g003" target="_blank">Fig 3</a> were also monitored for leading edge signaling activities as detected by the indicated activity sensor at specific times following addition of the indicated modulators (green = activator, red = inhibitor, black = carrier medium control). At each timepoint, the fluorescence signal of the sensor was measured to quantify the leading edge activity it monitors. Open bars represent the initial leading edge activity, normalized to 1.0, immediately after modulator addition. Filled bars represent the fold change as the activity approaches a new steady state level approximately 5 min after modulator addition (t = 4.5 to 5.5 min (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0196678#sec012" target="_blank">Methods</a>)). The findings indicate that activators significantly increase (and inhibitors significantly decrease) the leading edge PIP₃ density sensed by AKTPH-mRFP, and the leading edge PKC activity sensed by CKAR. In contrast, the opposite significant changes are observed for MARCKS binding to the leading edge membrane sensed by MARCKSp-mRFP. No significant changes in leading edge membrane binding were observed for the MARCKSp-SA4-mRFP sensor that lacks the Ser residues required for phosphoregulation by PKC. Error bars represent standard errors of the mean for 15–35 cells measured in at least 4 independent experiments. Asterisks indicate significance of each change from t = 0 (one, two or three asterisks indicate p < 0.05, p < 0.01, or p < 0.001, respectively). Image analysis described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0196678#pone.0196678.g002" target="_blank">Fig 2B</a> and Methods.</p

Interactions of Protein Kinase C‑α C1A and C1B Domains with Membranes: A Combined Computational and Experimental Study

Protein kinase C-α (PKCα) has been studied widely as a paradigm for conventional PKCs, with two C1 domains (C1A and C1B) being important for the regulation and function of the kinase. However, it is challenging to explore these domains in membrane-bound environments with either simulations or experiments alone. In this work, we have combined modeling, simulations, and experiments to understand the molecular basis of the PKCα C1A and C1B domain interactions with membranes. Our atomistic simulations of the PKCα C1 domains reveal the dynamic interactions of the proteins with anionic lipids, as well as the conserved hydrogen bonds and the distinct nonpolar contacts formed with lipid activators. Corroborating evidence is obtained from additional simulations and experiments in terms of lipid binding and protein diffusion. Overall, our study, for the first time, explains with atomistic detail how the PKCα C1A and C1B domains interact differently with various lipids. On the molecular level, the information provided by our study helps to shed light on PKCα regulation and activation mechanism. The combined computational/experimental approach demonstrated in this work is anticipated to enable further studies to explore the roles of C1 domains in many signaling proteins and to better understand their molecular mechanisms in normal cellular function and disease development

Site-directed spin label mutants of GRP1 PH domain and their measured parameters.

1<p>For spin-labeled mutants (R1), the indicated residue in the Cysless PH domain is changed to Cys and labeled with MTSSL. Also indicated is the secondary structure element in which each spin label is located.</p>2<p>The qualitative ranking of spectral changes in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033640#pone-0033640-g004" target="_blank">Figure 4</a> utilizes three categories: large change (++), detectable change (+) and no detectable change (−).</p

Hyperbolic relationship between spin label depth parameters and membrane penetration depths in the optimized, self-consistent EPR docking model.

<p>As described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033640#s4" target="_blank">Methods</a>, the crystal structure of the GRP1 PH domain co-complex with IP₄ (1FGY <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033640#pone.0033640-Lietzke1" target="_blank">[22]</a>) was modeled with MTSSL spin labels at the 18 chosen positions, then docked to the target bilayer using an interactive procedure that optimizes the known hyperbolic relationship between the measured spin label EPR depth parameters and the calculated spin label membrane penetration depths. Shown are the measured depth parameters for the protein spin labels (filled symbols) and the calibration lipid spin labels (open symbols), as well as the calculated membrane depth for each spin label in the final optimized, self-consistent EPR membrane docking model (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033640#pone-0033640-g006" target="_blank">Figure 6</a>). The excellent agreement with the best-fit hyperbola (solid curve) emphasizes the high quality of the docking model. Depth parameters were measured by EPR power saturation (Methods) at 23°C and samples contained 10–200 µM protein, 40 mM total lipid as SUVs, 25 mM HEPES, 140 mM KCl, 15 mM NaCl, 0.5 mM MgCl₂, pH 7.4. Except where otherwise indicated, errors are propagated from the errors of the accessibility parameters (Π(NiEDDA) and Π(O₂)) used to calculate the depth parameter (Eq. 1), n≥15 power settings were used for each accessibility parameter measurement.</p

Protein-membrane interactions in the optimized, self-consistent EPR docking model.

<p>Shown is the optimized, self-consistent EPR docking model for GRP1 PH domain co-complexed with IP₄ (1FGY <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033640#pone.0033640-Lietzke1" target="_blank">[22]</a>) and docked to a target bilayer. The schematic target bilayer highlights transient positions of backbone phosphates (red-brown spheres) and headgroups (PC or PS, black spheres) from a snapshot of a simulated bilayer <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033640#pone.0033640-Hoff1" target="_blank">[50]</a>. (A) Views of the PIP₃ headgroup relative to the mean backbone phosphate plane in both its lowest energy conformation (left) and its PH domain-bound conformation (right), illustrating the effect of PH domain binding on the target headgroup depth and orientation. (B) The PH domain docked to the schematic target bilayer in the optimized geometry. (C) Basic residues of the PH domain (dark blue spheres for R277, K279, K282, R283, R322, K323, R349) that can contact the negatively charged target bilayer in the optimized docking geometry. In some cases, the indicated side chain rotomer was adjusted to enhance membrane contact. (D) Hydrophobic and polar residues (light blue spheres for V278, T280, W281, P321, A346) that can contact the bilayer. Y298 obstructs the view and is not shown; it also contacts the bilayer and, perhaps more importantly, contacts multiple side chains responsible for specific PIP₃ binding. (E) Acidic residues (red spheres for D320, E345, D347) that contact the anionic bilayer surface and are thus proposed to limit protein penetration into the target bilayer.</p

Control EPR spectra for a representative mutant.

<p>Shown are reproducible EPR spectral overlays for the MTSSL spin-labeled GRP1 PH domain V278R1, illustrating the strategy employed to analyze the spectral effects of membrane docking. (A) V278R1 PH domain in the absence and presence of control PC∶ PS (3∶1) membranes lacking PIP₃, illustrating spectral broadening due to nonspecific membrane association. (B) V278R1 PH domain saturated with 200 µM IP₆, both in the absence and presence of control PC∶ PS (3∶1) membranes, showing that unlike the apo PH domain the IP₆-PH domain complex does not bind nonspecifically to membranes when PIP₃ is absent. (C) V278R1 PH domain saturated with 200 µM IP₆, both in the absence and presence of target PC∶ PS∶ PIP₃ (74∶ 24∶ 2) membranes, showing the spectral change upon docking of the IP₆-PH domain complex to membrane-bound PIP₃ (with release of IP₆). This is the standard comparison carried out for all spin-labeled PH domains (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033640#pone-0033640-g004" target="_blank">Fig. 4</a>), since the free IP₆-PH domain complex does not dock to background lipids and use of this complex as a reference point ensures that spectral changes are due to the environmental effects of membrane docking, rather than to the conformational effects of ligand binding cleft occupancy. (D) V278R1 PH domain binding to target PC∶ PS∶ PIP₃ (74∶ 24∶ 2) membranes in the absence and presence of saturating 200 µM IP₆, showing that the competitive inhibitor IP₆ does not perturb PH domain binding to target membrane PIP₃ under these conditions. Each pair of overlayed spectra were obtained for two samples made from the same protein stock to ensure nearly identical spin concentrations, for which the same number of scans were collected and plotted in absolute intensity mode. Double integrations confirmed that each pair of spectra represented virtually identical numbers of spins. Thus, the relative intensities of each spectral pair can be directly compared. Spectra were acquired at 23°C and samples contained 10–200 µM protein, 0 or 40 mM total lipid as SUVs, and 0 or 200 µM IP₆, in 25 mM HEPES, 140 mM KCl, 15 mM NaCl, 0.5 mM MgCl₂, pH 7.4.</p