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

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

Isolated Bacterial Chemosensory Array Possesses Quasi- and Ultrastable Components: Functional Links between Array Stability, Cooperativity, and Order

Bacteria utilize a large multiprotein chemosensory array to sense attractants and repellents in their environment. The array is a hexagonal lattice formed from three core proteins: a transmembrane receptor, the His kinase CheA, and the adaptor protein CheW. The resulting, highly networked array architecture yields several advantages including strong positive cooperativity in the attractant response and rapid signal transduction through the preformed, integrated signaling circuit. Moreover, when isolated from cells or reconstituted in isolated bacterial membranes, the array possesses extreme kinetic stability termed ultrastability (Erbse and Falke (2009) <i>Biochemistry 48:</i>6975–87) and is the most long-lived multiprotein enzyme complex described to date. The isolated array retains kinase activity, attractant regulation, and its bound core proteins for days or more at 22 °C. The present work quantitates this ultrastability and investigates its origin. The results demonstrate that arrays consist of two major components: (i) a quasi-stable component with a lifetime of 1–2 days that decays due to slow proteolysis of CheA kinase in the lattice and (ii) a truly ultrastable component with a lifetime of ∼20 days that is substantially more protected from proteolysis. Following proteolysis of the quasi-stable component the apparent positive cooperativity of the array increases, arguing the quasi-stable component is not as cooperative as the ultrastable component. Introduction of structural defects into the array by coupling a bulky probe to a subset of receptors reveals that modification of only 2% of the receptor population is sufficient to abolish ultrastability, supporting the hypothesis that the ultrastable component requires a high level of array spatial order. Overall, the findings are consistent with a model in which the quasi- and ultrastable components arise from distinct regions of the array, such that the ultrastable regions possess more extensive, better-ordered, multivalent interconnectivities between core components, thereby yielding extraordinary stability and cooperativity. Furthermore, the findings indicate that the chemosensory array is a promising platform for the development of ultrastable biosensors

Hydrophobic Contributions to the Membrane Docking of Synaptotagmin 7 C2A Domain: Mechanistic Contrast between Isoforms 1 and 7

Synaptotagmin (Syt) triggers Ca²⁺-dependent membrane fusion via its tandem C2 domains, C2A and C2B. The 17 known human isoforms are active in different secretory cell types, including neurons (Syt1 and others) and pancreatic β cells (Syt7 and others). Here, quantitative fluorescence measurements reveal notable differences in the membrane docking mechanisms of Syt1 C2A and Syt7 C2A to vesicles comprised of physiological lipid mixtures. In agreement with previous studies, the Ca²⁺ sensitivity of membrane binding is much higher for Syt7 C2A. We report here for the first time that this increased sensitivity is due to the slower target membrane dissociation of Syt7 C2A. Association and dissociation rate constants for Syt7 C2A are found to be ∼2-fold and ∼60-fold slower than Syt1 C2A, respectively. Furthermore, the membrane dissociation of Syt7 C2A but not Syt1 C2A is slowed by Na₂SO₄ and trehalose, solutes that enhance the hydrophobic effect. Overall, the simplest model consistent with these findings proposes that Syt7 C2A first docks electrostatically to the target membrane surface and then inserts into the bilayer via a slow hydrophobic mechanism. In contrast, the membrane docking of Syt1 C2A is known to be predominantly electrostatic. Thus, these two highly homologous domains exhibit distinct mechanisms of membrane binding correlated with their known differences in function

Hydrophobic Contributions to the Membrane Docking of Synaptotagmin 7 C2A Domain: Mechanistic Contrast between Isoforms 1 and 7

Synaptotagmin (Syt) triggers Ca²⁺-dependent membrane fusion via its tandem C2 domains, C2A and C2B. The 17 known human isoforms are active in different secretory cell types, including neurons (Syt1 and others) and pancreatic β cells (Syt7 and others). Here, quantitative fluorescence measurements reveal notable differences in the membrane docking mechanisms of Syt1 C2A and Syt7 C2A to vesicles comprised of physiological lipid mixtures. In agreement with previous studies, the Ca²⁺ sensitivity of membrane binding is much higher for Syt7 C2A. We report here for the first time that this increased sensitivity is due to the slower target membrane dissociation of Syt7 C2A. Association and dissociation rate constants for Syt7 C2A are found to be ∼2-fold and ∼60-fold slower than Syt1 C2A, respectively. Furthermore, the membrane dissociation of Syt7 C2A but not Syt1 C2A is slowed by Na₂SO₄ and trehalose, solutes that enhance the hydrophobic effect. Overall, the simplest model consistent with these findings proposes that Syt7 C2A first docks electrostatically to the target membrane surface and then inserts into the bilayer via a slow hydrophobic mechanism. In contrast, the membrane docking of Syt1 C2A is known to be predominantly electrostatic. Thus, these two highly homologous domains exhibit distinct mechanisms of membrane binding correlated with their known differences in function

Hydrophobic Contributions to the Membrane Docking of Synaptotagmin 7 C2A Domain: Mechanistic Contrast between Isoforms 1 and 7

Synaptotagmin (Syt) triggers Ca²⁺-dependent membrane fusion via its tandem C2 domains, C2A and C2B. The 17 known human isoforms are active in different secretory cell types, including neurons (Syt1 and others) and pancreatic β cells (Syt7 and others). Here, quantitative fluorescence measurements reveal notable differences in the membrane docking mechanisms of Syt1 C2A and Syt7 C2A to vesicles comprised of physiological lipid mixtures. In agreement with previous studies, the Ca²⁺ sensitivity of membrane binding is much higher for Syt7 C2A. We report here for the first time that this increased sensitivity is due to the slower target membrane dissociation of Syt7 C2A. Association and dissociation rate constants for Syt7 C2A are found to be ∼2-fold and ∼60-fold slower than Syt1 C2A, respectively. Furthermore, the membrane dissociation of Syt7 C2A but not Syt1 C2A is slowed by Na₂SO₄ and trehalose, solutes that enhance the hydrophobic effect. Overall, the simplest model consistent with these findings proposes that Syt7 C2A first docks electrostatically to the target membrane surface and then inserts into the bilayer via a slow hydrophobic mechanism. In contrast, the membrane docking of Syt1 C2A is known to be predominantly electrostatic. Thus, these two highly homologous domains exhibit distinct mechanisms of membrane binding correlated with their known differences in function

Defining a Key Receptor–CheA Kinase Contact and Elucidating Its Function in the Membrane-Bound Bacterial Chemosensory Array: A Disulfide Mapping and TAM-IDS Study

The three core components of the ubiquitous bacterial chemosensory array  the transmembrane chemoreceptor, the histidine kinase CheA, and the adaptor protein CheW  assemble to form a membrane-bound, hexagonal lattice in which receptor transmembrane signals regulate kinase activity. Both the regulatory domain of the kinase and the adaptor protein bind to overlapping sites on the cytoplasmic tip of the receptor (termed the protein interaction region). Notably, the kinase regulatory domain and the adaptor protein share the same fold constructed of two SH3-like domains. The present study focuses on the structural interface between the receptor and the kinase regulatory domain. Two models have been proposed for this interface: Model 1 is based on the crystal structure of a homologous Thermotoga complex between a receptor fragment and the CheW adaptor protein. This model has been used in current models of chemosensory array architecture to build the receptor–CheA kinase interface. Model 2 is based on a newly determined crystal structure of a homologous Thermotoga complex between a receptor fragment and the CheA kinase regulatory domain. Both models present unique strengths and weaknesses, and current evidence is unable to resolve which model best describes contacts in the native chemosensory arrays of <i>Escherichia coli</i>, <i>Salmonella typhimurium</i>, and other bacteria. Here we employ disulfide mapping and tryptophan and alanine mutation to identify docking sites (TAM-IDS) to test Models 1 and 2 in well-characterized membrane-bound arrays formed from <i>E. coli</i> and <i>S. typhimurium</i> components. The results reveal that the native array interface between the receptor protein interaction region and the kinase regulatory domain is accurately described by Model 2, but not by Model 1. In addition, the results show that the interface possesses both a structural function that contributes to stable CheA kinase binding in the array and a regulatory function central to transmission of the activation signal from receptor to CheA kinase. On–off switching alters the disulfide formation rates of specific Cys pairs at the interface, but not most Cys pairs, indicating that signaling perturbs localized regions of the interface. The findings suggest a simple model for the rearrangement of the interface triggered by the attractant signal and for longer range transmission of the signal in the chemosensory array