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Department of Chemical & Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina
Correspondence: Address reprint requests to Jason M. Haugh, Box 7905, North Carolina State University, Raleigh, NC 27695. Tel.: 919-513-3851; Fax: 919-515-3465; E-mail: jason_haugh{at}ncsu.edu.
| ABSTRACT |
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| INTRODUCTION |
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Type I PI 3-kinases phosphorylate phosphatidylinositol (PtdIns) (4
,5
)-bisphosphate [PtdIns(4
,5
)P2], a lipid found in the inner leaflet of the plasma membrane, on the 3' position of the inositol ring (11
,12
). The product, PtdIns(3
,4
,5
)P3, and its derivative PtdIns(3
,4
)P2 (collectively referred to as 3' PIs), interact with specific signaling proteins and mediate pathways known to be responsible for modulation of the cytoskeleton, such as activation of the Rho family GTPases Rac and Cdc42 (13
,14
). Moreover, external chemoattractant gradients elicit polarized 3' PI patterns in numerous cell types, including fibroblasts (8
,15
,16
). Hence, a conceptual model has emerged in which gradient-sensing in eukaryotes is based on the spatially localized activation of cell surface receptors and PI 3-kinase and production of 3' PI lipid second messengers (17
19
). A prerequisite for spatial gradient sensing is that the range of the second messenger, defined by its relative diffusion and turnover rates, must be sufficiently small relative to cellular dimensions (8
,20
). To estimate these and other parameters quantitatively for many cells, we previously analyzed the kinetics and pattern of 3' PIs in mouse fibroblasts stimulated uniformly with PDGF (21
,22
). The restriction of PDGF-stimulated PI 3-kinase activity to the nonadherent portion of the plasma membrane in our cells produces a spatial 3' PI pattern, and the spatiotemporal response was characterized through direct comparison of results obtained from mathematical modeling and live-cell total internal reflection fluorescence (TIRF) microscopy experiments. The model equations were calculated on a hemispherical surface approximating the cell membrane.
Although this model gave good agreement with measured fluorescence profiles across the center of the contact area, it was anticipated that certain local regions of the membrane might exhibit 3' PI levels that deviate from the model (21
). This conjecture was based on our observation that certain localized regions of the contact area show significantly higher or lower fluorescence intensities relative to adjacent regions; such regions are referred to here as hot spots or cold spots, respectively. It was further recognized that a more realistic model of the cell geometry would be needed to account for the effect of cell shape on the 3' PI pattern in the contact area.
How might such hot and cold spots arise? It is clear that the cytoskeleton is not only a target for receptor-mediated signaling, but also a signaling mediator in its own right. Morphological polarization is a general characteristic of migrating cells and is seen dramatically at the free edges of "wounded" fibroblast monolayers. An actin-rich leading edge is formed, with one or more protruding lamellipodia and long, thin filopodia, accompanied by translocation of the microtubule organizing center and orientation of microtubules toward the leading edge (14
,23
,24
). Fibroblast polarization also enriches 3' PI lipids at the leading edge, in the absence of external stimuli (8
). In other cell systems, the cytoskeleton apparently amplifies 3' PI gradients in cells undergoing chemotaxis (25
27
). These observations indicate that there is an intrinsic spatial bias, at the level of 3' PI signaling, associated with cell morphological polarity and leading edge dynamics. Indeed, it has been suggested that positive feedback loops, involving PI 3-kinase, Rac/Cdc42, and/or the leading edge cytoskeleton, can give rise to spontaneous polarization (28
32
).
In this article, we address the effects of cell morphology and morphological polarity on the 3' PI pattern observed in PDGF-stimulated fibroblasts and shed light on the mechanisms that give rise to hot and cold spots. First, we describe improvements to our previous analytical approach that allow the numerical solution of model equations in cell contact area morphologies imported from image analysis software. This led to refined estimates of the model parameters, in particular the relative rates of 3' PI turnover and diffusion. Second, in characterizing the hot and cold spots observed in TIRF experiments, we report that our cells typically exhibit multiple hot spots, associated with leading edge structures, whereas cold spots are less prevalent and found at the rear of the contact area. Although morphological polarity thus influences the 3' PI pattern, we found that the local morphology of the contact area alone does not explain the presence of hot or cold spots, suggesting that these regions reflect local differences in 3' PI production and/or turnover kinetics. Finally, we present an analysis of the 3' PI accumulation and decay kinetics in hot spots. We find that their apparent kinetics are consistent with a combination of enhanced PI 3-kinase activation, regulation of 3' PI turnover, and/or slow or constrained 3' PI diffusion, suggesting mechanisms by which local 3' PI levels are governed in leading edge structures.
| MATERIALS AND METHODS |
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Total internal reflection fluorescence microscopy
Total internal reflection fluorescence (TIRF) microscopy is a mode of live-cell imaging whereby fluorophores in close proximity to the cell-substratum contact area are selectively excited by an evanescent wave, which penetrates a characteristic distance of
100 nm into the cell (34
36
). Our prism-based TIRF microscope was described in detail previously (22
). Briefly, two laser heads from Melles-Griot (Irvine, CA) were used: a tunable wavelength Ar ion laser head, emitting lines of 488 nm (EGFP, 60 mW) or 514 nm (EYFP, 60 mW), and a HeCd laser head, emitting a 442-nm line (ECFP, 120 mW). All lines were used at maximum power, and the measured incidence angle of the reflected beam ranged from 68 to 69° across experiments. Band-pass emission filters (Chroma, Rockingham, VT) were 480/30 nm for ECFP, 515/30 nm for EGFP, and 535/30 nm for EYFP. Digital images were acquired using an ORCA ER-cooled CCD (Hamamatsu, Bridgewater, NJ) and Metamorph software (Universal Imaging, West Chester, PA). The imaging buffer was composed of 20 mM HEPES pH 7.4, 125 mM NaCl, 5 mM KCl, 1.5 mM MgCl2, 1.5 mM CaCl2, 10 mM glucose, and 2 mg/ml fatty acid-free bovine serum albumin. Fields of cells were visualized at a combined magnification of 25x or 12.5x, and TIRF images were acquired with 2 x 2 binning every 1020 s over a 2030-min time course. The exposure time x gain setting was fixed at
400 ms for EGFP and EYFP constructs and
2400 ms for ECFP constructs.
Association-dissociation experiments and analysis of fluorescence profiles in cell contact area geometries
In association-dissociation experiments, cells transfected with GFP-AktPH or its spectral variants are stimulated with a maximal dose of PDGF-BB (Peprotech, Rocky Hill, NJ) for
10 min, during which an increase in TIRF fluorescence is observed (association). Thereafter, a high concentration of wortmannin (Sigma) or LY294002 (Calbiochem, San Diego, CA) is added to rapidly block the PI 3-kinase activity, isolating the degradation of 3' PI lipids (dissociation). Experiments and image processing were performed as described previously (22
).
The normalized fluorescence data from such experiments can be directly compared with a mathematical model that accounts for 3' PI insertion, diffusion, and turnover in the adherent (i.e., bottom) and nonadherent (i.e., top) portions of the plasma membrane, as well as the binding of the GFP-AktPH probe (see the Appendix). In our previous analytical approach (21
), the dimensionless model parameters Da,
, pss, and x0 were estimated directly from four fluorescence metrics: the initial fluorescence (f0), the extent of the dip in fluorescence in the center of the contact area (fmin), the steady-state fluorescence value at the center (fss(0)), and the average fluorescence value at steady state (
). This procedure was previously carried out for six limiting cases of the model that considered the extremes of lipid-probe interaction parameters and top-bottom polarity of 3' PI insertion; the model calculations, assuming a hemispherical cell, were finally fit to the real-time data using two additional parameters: a lag time, tlag, and the degradation rate constant, k (21
).
In this work, a two-step approach was adopted. We first assumed a flat, two-sided disk (pancake) morphology for the model cell, for which a closed-form analytical solution was derived (see the Appendix). The dimensionless parameters (Da,
, pss, x0) determined for the disk model served as initial guesses for the second step, in which model calculations were performed using the actual contact area geometry of each cell. To achieve this, the outline of each cell was imported from a thresholded image into the finite-element modeling package, FEMLAB (Comsol, Burlington, MA). As in the disk model, the nonadherent plasma membrane was assumed to be flat, with the same shape as the contact area, and the 3' PI concentrations and fluxes were matched at all corresponding points along the peripheries of the two domains in FEMLAB. The two-sided disk model was used to confirm the accuracy of the finite-element calculations. It was also confirmed that the mesh, automatically generated by FEMLAB, was sufficiently refined. Model calculations were used to generate stacks of simulated images for sequential association and dissociation kinetics. Identical line scans were taken from both the model and experimental stacks and directly compared; an interpolation macro was written in MATLAB (MathWorks, Natick, MA) to estimate the normalized fluorescence values at the same pixel locations as in the experimental line scan. Finally, the values of Da,
, and x0 were adjusted in an iterative fashion to match the initial and steady-state fluorescence profiles observed in the association phase of the experiment.
Modeling of hot and cold spot regions
Hot and cold spots were modeled in FEMLAB as small regions at the periphery of the cell (mirrored in both the top and bottom domains) with different properties from the rest of the membrane. The governing equations were solved in dimensionless form, and so the parameter values in these regions are defined relative to their corresponding values in the bulk membrane. To be consistent with experimental observations, only the bottom domain of the cell contributes to the average fluorescence value reported for the hot/cold spot.
| RESULTS |
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Of particular interest is the value of the Damköhler number,
![]() | (1) |
![]() | (2) |
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= (Vp/Ap)(k/D)1/2, where Vp and Ap are the volume and surface area of the particle, respectively (37
Hot and cold spots of 3' PI signaling
From the association-dissociation experiments it was apparent that certain contact area regions are significantly more or less fluorescent (by approximately a factor of 2) than neighboring regions. These localized regions of high and low fluorescence, identified by inspection of TIRF images, are termed hot and cold spots, respectively. In all cases, these differences in fluorescence disappeared by the end of the dissociation phase (after PI 3-kinase inhibition). In control experiments with cells expressing soluble ECFP/EYFP or membrane-targeted lyn-CFP, regions with higher or lower fluorescence were seen much less frequently and differed in intensity by
25% or less; the same trends were observed in cells co-transfected with YFP-AktPH/lyn-CFP, YFP-AktPH/ECFP, or CFP-AktPH/EYFP, in which there were no correlations between the two fluorescence channels (data not shown). We conclude that regions of significantly higher or lower GFP-AktPH fluorescence report local differences in the density of 3' PI lipids.
A total of 49 cells transfected with GFP-AktPH were analyzed and found to contain a total of 129 hot spots and 39 cold spots. Fig. 3 a, a histogram of the number of hot and cold spots per cell, illustrates that hot spots were much more abundant than cold spots. The vast majority of the cells exhibited at least two hot spots and either zero or one cold spot.
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Given the effect of contact area morphology on the calculated 3' PI pattern (Fig. 1) and the prevalence of hot and cold spots in membrane extensions, we asked whether or not cell shape could explain the presence of apparent hot or cold spots. This possibility was ruled out through a simple analysis. As proven in the Appendix, the uniform stimulation model predicts the same 3' PI level at all points along the cell periphery, regardless of contact area shape. Consequently, higher fluorescence in a thin extension cannot be attributed to geometric effects. Curvature of the nonadherent membrane also cannot explain significant differences in 3' PI level; at steady state, the maximum difference between periphery 3' PI levels in the disk and hemisphere models is
30% (one-half versus two-thirds); if anything, this would yield slightly lower fluorescence intensities in flat extensions compared to the periphery of the cell body. To illustrate this conclusion, TIRF images and finite-element calculations were compared after maximal PDGF stimulation (Fig. 3 b). Subtracting the steady-state model prediction from the TIRF image or vice versa, it is clear that hot and cold spots identified from TIRF images have significantly higher or lower fluorescence intensities, respectively, than those predicted by the uniform stimulation model. We conclude that hot and cold spots arise from local differences in 3' PI production, turnover, and/or diffusion.
Hot and cold spots exhibit distinct kinetics in association-dissociation experiments
The kinetics of the hot and cold spot responses to the association-dissociation protocol were also characterized (Fig. 4). A predominant characteristic of hot spots in this regard was a sluggish response compared with the rest of the cell (Fig. 4, a and c, and Movie S2 in the Supplementary Material). Specifically, in the association phase of the experiment, such a hot spot exhibits a slower approach to the steady state; its fluorescence intensity continues to increase after the fluorescence profile in the cell body has apparently settled upon a pseudo-steady state. Further, during the dissociation phase, whereas the fluorescence profile in the cell body rapidly becomes homogeneous as it decays (22
), the fluorescence intensity of the hot spot fails to converge with that of the cell body until all of the 3' PI is consumed (Fig. 4, a and c).
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Motivated by the prevalence of hot spots in our cells and their unique kinetic features in both phases of the experiment, hot spot responses were further characterized through the following quantitative analysis (Fig. 5). For each cell, a region at the periphery of the cell body was chosen as a reference. Its decay in normalized fluorescence during the dissociation phase was fit to an appropriate function (which assumes exponential decay of 3' PI concentration and pseudo-equilibrium with the GFP-AktPH probe),
![]() | (3) |
1, together with a value ratio >1, indicates that the hot spot and reference fluorescence intensities have neither converged nor are in the process of doing so. Based on these criteria, with a reasonable value ratio cutoff of 1.2, 61% of the hot spots failed to converge with the reference region (Fig. 5). Further, 48% of these hot spots (or 29% total) decayed at a significantly slower relative rate (decay ratio <0.8) than the reference region; this observation will be significant in our subsequent modeling analysis.
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Hot spot responses are consistent with a combination of mechanisms: enhanced PI 3-kinase activation, reduced 3' PI turnover, and/or slow or constrained 3' PI diffusion
Given that hot spots arise from local differences in 3' PI production, turnover, and/or diffusion, we sought to elucidate which of these mechanisms are at play. Hot spots consistently showed distinct kinetics in both phases of the experiment, which is significant because differences found during the dissociation phase can only be attributed to differing rates of 3' PI turnover and/or diffusion. When the turnover rate constant k and diffusion coefficient D are the same throughout the plasma membrane, the 3' PI density at all points along the contact area periphery decays according to a single exponential (see the Appendix):
![]() | (4) |
We proceeded to model hot spots simply as defined subcompartments of the membrane with their own values of the model parameters, and analysis of the model led to a number of conclusions (Fig. 6). First, in hot spots with enhanced PI 3-kinase activity alone (Fig. 6, a and d), we expect that the fluorescence intensity would rapidly merge with that of the cell body during the dissociation phase; this is illustrated in Fig. 6 d. Second, if enhanced PI 3-kinase activity is coupled with very slow or constrained diffusion in the hot spot, (Fig. 6, b and e), its 3' PI density is effectively isolated from the rest of the membrane and thus decays according to Eq. 4 during the dissociation phase, at the same relative rate as the rest of the periphery. Thus, in this case the hot spot 3' PI density does not converge with that of the cell body (Fig. 6 e). Finally, the 3' PI density also fails to converge in hot spots with normal PI 3-kinase activation and 3' PI diffusion but reduced 3' PI turnover (Fig. 6, c and f, and Movie S4 in the Supplementary Material). Such hot spots would also tend to exhibit a higher local 3' PI density before stimulation and a slower approach to the steady state during the association phase, consistent with the characteristics of a significant fraction of hot spots (Fig. 6 f). Of course, these effects would also arise if one assumes local differences in basal PI 3-kinase activity and the kinetics of receptor-stimulated PI 3-kinase activation.
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1), but a key difference is that these two mechanisms tend to give different relative rates of decay. Slow or constrained diffusion keeps the value ratio high and brings the decay ratio very close to one; as outlined above, the 3' PI level in a hot spot with slow/constrained diffusion and normal turnover decays at the same relative rate (% decrease per unit time) as regions at the periphery of the cell body. Reduced turnover produces a decay ratio <1 and is unique in this respect (Fig. 6 g). In Fig. 5, we noted that a significant fraction of hot spots exhibited value ratios >1.2 and decay ratios <0.8, an indication of significant reduction in turnover. The fact that these hot spots also showed sluggish association kinetics is consistent with this view. From the spectrum of decay ratios observed, we conclude that hot spots arise from enhanced PI 3-kinase activation as well as reduced 3' PI turnover, perhaps influenced by slow or constrained 3' PI diffusion, although individual hot spots likely differ with respect to the dominant mechanism(s).
| DISCUSSION |
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We first employed this framework to more accurately estimate model parameters. Use of idealized, circular contact area geometry is adequate for estimating the spatial range of 3' PIs (Eq. 2) within a factor of 2 or so, but it consistently underestimates this quantity. A good compromise for parameter estimation was found in the application of the Thiele modulus, commonly used to analyze diffusion-reaction coupling in heterogeneous catalysis. Although lateral 3' PI diffusion is important for interactions between 3' PI-bound proteins and other membrane-associated components, not to mention its potential role in smoothing out stochastic fluctuations, in this context it is detrimental to the maintenance of long-range 3' PI gradients. As we now apply the finite-element modeling approach to characterize cells responding to PDGF gradients, in which cells vary with respect to their morphology and orientation relative to the PDGF source (I.C. Schneider and J.M. Haugh, unpublished), use of the true cell geometry and accurate parameter estimates are vital.
The second motivation for more realistic modeling of contact area geometry was to shed light on the mechanisms that give rise to localized regions with significantly higher or lower fluorescence intensity (hot and cold spots, respectively), observed in peripheral membrane structures that correlated strongly with the cell's morphological polarity. With geometric effects accounted for, we analyzed the hypothetical influences of local differences in PI 3-kinase activation and 3' PI turnover and compared these effects with the kinetics typically observed in response to PDGF. Hot spots, typically found in numerous regions coinciding with (possibly competing) leading edge structures, were characterized by slower kinetics, exemplified by a dramatic time shift in the fluorescence decay kinetics after PI 3-kinase inhibition. From a quantitative analysis of these kinetics together with model calculations, we concluded that one of the mechanisms contributing to the higher 3' PI densities in hot spots is a local reduction in the rate of 3' PI turnover. Therefore, although pathways and feedback loops affecting PI 3-kinase activity at the leading edge have received considerable attention, we must also consider the local regulation of PI 3-phosphatases or other 3' PI consumption pathways.
A PI 3-phosphatase studied actively in recent years is phosphatase and tensin homolog deleted on chromosome 10 (PTEN). In Dictyostelium discoideum, PTEN is localized at the plasma membrane in a reciprocal fashion with respect to PI 3-kinase; i.e., it is membrane-associated before stimulation, dissociates transiently in response to uniform chemoattractant stimulation, and is persistently membrane-localized at the rear and sides during chemotaxis (27
,41
,42
). The localization and activity of mammalian PTEN, however, are subject to additional regulatory mechanisms, as implicated by its different domain structure (43
). It remains possible, then, that the membrane binding and/or activity of mammalian PTEN or other 3' PI phosphatases may be altered in a highly localized fashion, although the signaling determinants involved are presently uncertain. In our cells, we established previously that 3' PI turnover is not globally regulated in response to PDGF (22
), yet such enzymes do appear to be less active in or excluded from certain leading edge locations.
Although hot spots are apparently affected by regulation of 3' PI turnover, we found that enhanced PI 3-kinase activation was also required to explain the degree of 3' PI enrichment in many hot spots. Locally restricted 3' PI diffusion may also be important, as has been implicated in PI 3-kinase-dependent signaling processes driving phagocytosis (44
). Incidentally, the less abundant cold spots apparently arise from a lack of PDGF-stimulated PI 3-kinase activation in these regions, or in the case of transient cold spots, a delay in the PI 3-kinase activation kinetics (analysis not shown). Together, these effects are consistent with the notion that leading and trailing edges of the membrane exhibit unique signaling activities and/or present different environments for signaling to take place there.
We have analyzed the apparent relationship between morphological polarity and 3' PI signaling, in the context of both unstimulated and PDGF-stimulated fibroblasts. This relationship leads us to speculate that cell polarity yields an intrinsic bias for directed migration, at the level of the 3' PI pattern, which would either reinforce or antagonize the external bias of a PDGF gradient oriented in a certain direction. This concept is consistent with a model put forward recently, which is based on the correlation of spontaneous 3' PI pulses at the leading edge with cell turning behavior during random and directed cell migration (45
). Obviously, we present here only a snapshot of signaling that occurs during cell movement, which must be integrated with the control of cell polarity, membrane protrusion, and cell adhesiveness.
| APPENDIX |
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t and
b, respectively); here we explicitly assume that the 3' PI diffusion coefficient and turnover rate constant (D and k, respectively) are the same in both domains. In mathematical terms, the conservation equations to be solved are
![]() | (5) |
![]() | (6) |
![]() | (7) |
![]() | (8) |
![]() | (9) |
![]() | (10) |
Solution for a two-sided disk
We turn now to a circular bottom domain of radius R (L = R), with a specified concentration at the periphery. The general solution is given in terms of z = xb x|S, as a function of radial position
= r/R and dimensionless time:
![]() | (11) |
t = 1;
b =
) and the 3' PI profile is assumed to be flat initially (xb(
,0) = x0, z(
,0) = 0),
![]() | (12) |
![]() | (13) |
t =
b = 0), it is noted that Eq. 13 serves as the initial condition, with xb,ss(
) + xt,ss(
) = 1 +
at all
. Hence,
![]() | (14) |
![]() | (15) |
Fluorescence profile
Given a 3' PI profile xb, the normalized fluorescence profile, f, was determined as derived previously (21
); assuming pseudo-equilibrium for GFP-AktPH/3' PI binding,
![]() | (16) |
| SUPPLEMENTARY MATERIAL |
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| ACKNOWLEDGEMENTS |
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Submitted on February 15, 2005; accepted for publication May 23, 2005.
| REFERENCES |
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2. Pierce, G. F., T. A. Mustoe, B. W. Altrock, T. F. Deuel, and A. Thomason. 1991. Role of platelet-derived growth factor in wound healing. J. Cell. Biochem. 45:319326.[CrossRef][Medline]
3. Claesson-Welsh, L. 1994. Platelet-derived growth factor receptor signals. J. Biol. Chem. 269:3202332026.
4. Heldin, C.-H., and B. Westermark. 1999. Mechanism of action and in vivo role of platelet-derived growth factor. Physiol. Rev. 79:12831316.
5. Wennström, S., P. Hawkins, F. Cooke, K. Hara, K. Yonezawa, M. Kasuga, T. Jackson, L. Claesson-Welsh, and L. Stephens. 1994. Activation of phosphoinositide 3-kinase is required for PDGF-stimulated membrane ruffling. Curr. Biol. 4:385393.[CrossRef][Medline]
6. Wennström, S., A. Siegbahn, K. Yokote, A. Arvidsson, C.-H. Heldin, S. Mori, and L. Claesson-Welsh. 1994. Membrane ruffling and chemotaxis transduced by the PDGF ß-receptor require the binding site for phosphatidylinositol 3' kinase. Oncogene. 9:651660.[Medline]
7. Kundra, V., J. A. Escobedo, A. Kazlauskas, H. K. Kim, S. G. Rhee, L. T. Williams, and B. R. Zetter. 1994. Regulation of chemotaxis by the platelet-derived growth factor receptor-ß. Nature. 367:474476.[CrossRef][Medline]
8. Haugh, J. M., F. Codazzi, M. Teruel, and T. Meyer. 2000. Spatial sensing in fibroblasts mediated by 3' phosphoinositides. J. Cell Biol. 151:12691279.
9. Ridley, A. J. 2001. Rho proteins, PI 3-kinases, and monocyte/macrophage motility. FEBS Lett. 498:168171.[CrossRef][Medline]
10. Rameh, L. E., and L. C. Cantley. 1999. The role of phosphoinositide 3-kinase lipid products in cell function. J. Biol. Chem. 274:83478350.
11. Fruman, D. A., R. E. Meyers, and L. C. Cantley. 1998. Phosphoinositide kinases. Annu. Rev. Biochem. 67:481507.[CrossRef][Medline]
12. Vanhaesebroeck, B., S. J. Leevers, K. Ahmadi, J. Timms, R. Katso, P. C. Driscoll, R. Woscholski, P. J. Parker, and M. D. Waterfield. 2001. Synthesis and function of 3-phosphorylated inositol lipids. Annu. Rev. Biochem. 70:535602.[CrossRef][Medline]
13. Nobes, C. D., and A. Hall. 1999. Rho GTPases control polarity, protrusion, and adhesion during cell movement. J. Cell Biol. 144:12351244.
14. Ridley, A. J., M. A. Schwartz, K. Burridge, R. A. Firtel, M. H. Ginsberg, G. Borisy, T. J. Parsons, and A. R. Horwitz. 2003. Cell migration: integrating signals from front to back. Science. 302:17041709.
15. Servant, G., O. D. Weiner, P. Herzmark, T. Balla, J. W. Sedat, and H. R. Bourne. 2000. Polarization of chemoattractant receptor signaling during neutrophil chemotaxis. Science. 287:10371040.
16. Parent, C. A., B. J. Blacklock, W. M. Froehlich, D. B. Murphy, and P. N. Devreotes. 1998. G-protein signaling events are activated at the leading edge of chemotactic cells. Cell. 95:8191.[CrossRef][Medline]
17. Parent, C. A., and P. N. Devreotes. 1999. A cell's sense of direction. Science. 284:765770.
18. Weiner, O. D. 2002. Regulation of cell polarity during eukaryotic chemotaxis: the chemotactic compass. Curr. Opin. Cell Biol. 14:196202.[CrossRef][Medline]
19. Merlot, S., and R. A. Firtel. 2003. Leading the way: directional sensing through phosphatidylinositol 3-kinase and other signaling pathways. J. Cell Sci. 116:34713478.
20. Postma, M., and P. J. M. Van Haastert. 2001. A diffusion-translocation model for gradient sensing by chemotactic cells. Biophys. J. 81:13141323.
21. Haugh, J. M., and I. C. Schneider. 2004. Spatial analysis of 3' phosphoinositide signaling in living fibroblasts. I. Uniform stimulation model and bounds on dimensionless groups. Biophys. J. 86:589598.
22. Schneider, I. C., and J. M. Haugh. 2004. Spatial analysis of 3' phosphoinositide signaling in living fibroblasts. II. Parameter estimates for individual cells from experiments. Biophys. J. 86:599608.
23. Pollard, T. D., and G. G. Borisy. 2003. Cellular motility driven by assembly and disassembly of actin filaments. Cell. 112:453465.[CrossRef][Medline]
24. Etienne-Manneville, S. 2004. Cdc42the centre of polarity. J. Cell Sci. 117:12911300.
25. Wang, F., P. Herzmark, O. D. Weiner, S. Srinivasan, G. Servant, and H. R. Bourne. 2002. Lipid products of PI3Ks maintain persistent cell polarity and directed motility in neutrophils. Nat. Cell Biol. 4:513518.[CrossRef][Medline]
26. Weiner, O. D., G. Servant, M. D. Welch, T. J. Mitchison, J. W. Sedat, and H. R. Bourne. 1999. Spatial control of actin polymerization during neutrophil chemotaxis. Nat. Cell Biol. 1:7581.[CrossRef][Medline]
27. Janetopoulos, C., L. Ma, P. N. Devreotes, and P. A. Iglesias. 2004. Chemoattractant-induced phosphatidylinositol 3,4,5-trisphosphate accumulation is spatially amplified and adapts, independent of the actin cytoskeleton. Proc. Natl. Acad. Sci. USA. 101:89518956.
28. Weiner, O. D., P. O. Neilsen, G. D. Prestwich, M. W. Kirschner, L. C. Cantley, and H. R. Bourne. 2002. A PtdInsP3- and Rho GTPase-mediated positive feedback loop regulates neutrophil polarity. Nat. Cell Biol. 4:509512.[CrossRef][Medline]
29. Srinivasan, S., F. Wang, S. Glavas, A. Ott, F. Hofmann, K. Aktories, D. Kalman, and H. R. Bourne. 2003. Rac and Cdc42 play distinct roles in regulating PI(3,4,5)P3 and polarity during neutrophil chemotaxis. J. Cell Biol. 160:375385.
30. Wedlich-Soldner, R., S. Altschuler, L. Wu, and R. Li. 2003. Spontaneous cell polarization through actomyosin-based delivery of the Cdc42 GTPase. Science. 299:12311235.
31. Nalbant, P., L. Hodgson, V. Kraynov, A. Toutchkine, and K. M. Hahn. 2004. Activation of endogenous Cdc42 visualized in living cells. Science. 305:16151619.
32. Postma, M., J. Roelofs, J. Goedhart, H. M. Loovers, A. J. Visser, and P. J. M. Van Haastert. 2004. Sensitization of Dictyostelium chemotaxis by phosphoinositide-3-kinase-mediated self-organizing signalling patches. J. Cell Sci. 117:29252935.
33. Teruel, M. N., T. A. Blanpied, K. Shen, G. J. Augustine, and T. Meyer. 1999. A versatile microporation technique for the transfection of cultured CNS neurons. J. Neurosci. Methods. 93:3748.[CrossRef][Medline]
34. Axelrod, D. 2001. Total internal reflection fluorescence microscopy in cell biology. Traffic. 2:764774.[CrossRef][Medline]
35. Steyer, J. A., and W. Almers. 2001. A real-time view of life within 100 nm of the plasma membrane. Nat. Rev. Mol. Cell Biol. 2:268275.[CrossRef][Medline]
36. Toomre, D., and D. J. Manstein. 2001. Lighting up the cell surface with evanescent wave microscopy. Trends Cell Biol. 11:298303.[CrossRef][Medline]
37. Aris, R. 1957. On shape factors for irregular particles. I. The steady-state problem. Diffusion and reaction. Chem. Eng. Sci. 6:262268.[CrossRef]
38. Subramanian, K. K., and A. Narang. 2004. A mechanistic model for eukaryotic gradient sensing: spontaneous and induced phosphoinositide polarization. J. Theor. Biol. 231:4967.[CrossRef][Medline]
39. Ma, L., C. Janetopoulos, L. Yang, P. N. Devreotes, and P. A. Iglesias. 2004. Two complementary, local excitation, global inhibition mechanisms acting in parallel can explain the chemoattractant-induced regulation of PI(3,4,5)P3 response in Dictyostelium cells. Biophys. J. 87:37643774.
40. Slepchenko, B. M., J. C. Schaff, J. H. Carson, and L. M. Loew. 2002. Computational cell biology: spatiotemporal simulation of cellular events. Annu. Rev. Biophys. Biomol. Struct. 31:423441.[CrossRef][Medline]
41. Iijima, M., and P. Devreotes. 2002. Tumor suppressor PTEN mediates sensing of chemoattractant gradients. Cell. 109:599610.[CrossRef][Medline]
42. Funamoto, S., R. Meili, S. Lee, L. Parry, and R. A. Firtel. 2002. Spatial and temporal regulation of 3-phosphoinositides by PI 3-kinase and PTEN mediates chemotaxis. Cell. 109:611623.[CrossRef][Medline]
43. Leslie, N. R., and C. P. Downes. 2004. PTEN function: how normal cells control it and tumour cells lose it. Biochem. J. 382:111.[CrossRef][Medline]
44. Marshall, J. G., J. W. Booth, V. Stambolic, T. Mak, T. Balla, A. D. Schreiber, T. Meyer, and S. Grinstein. 2001. Restricted accumulation of phosphatidylinositol 3-kinase products in a plasmalemmal subdomain during Fc gamma receptor-mediated phagocytosis. J. Cell Biol. 153:13691380.
45. Arrieumerlou, C., and M. Meyer. 2005. A local coupling model and compass parameter for eukaryotic chemotaxis. Dev. Cell. 8:215227.[CrossRef][Medline]
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