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      Distinct signaling mechanisms regulate migration in unconfined versus confined spaces

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          Abstract

          α4β1 integrin promotes migration of fibroblast-like cells in confined environment by enhancing myosin IIA via Rac1 inhibition, whereas unconfined migration requires Rac1 and myosin IIB.

          Abstract

          Using a microchannel assay, we demonstrate that cells adopt distinct signaling strategies to modulate cell migration in different physical microenvironments. We studied α4β1 integrin–mediated signaling, which regulates cell migration pertinent to embryonic development, leukocyte trafficking, and melanoma invasion. We show that α4β1 integrin promotes cell migration through both unconfined and confined spaces. However, unlike unconfined (2D) migration, which depends on enhanced Rac1 activity achieved by preventing α4/paxillin binding, confined migration requires myosin II–driven contractility, which is increased when Rac1 is inhibited by α4/paxillin binding. This Rac1–myosin II cross talk mechanism also controls migration of fibroblast-like cells lacking α4β1 integrin, in which Rac1 and myosin II modulate unconfined and confined migration, respectively. We further demonstrate the distinct roles of myosin II isoforms, MIIA and MIIB, which are primarily required for confined and unconfined migration, respectively. This work provides a paradigm for the plasticity of cells migrating through different physical microenvironments.

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          Myosin IIA regulates cell motility and actomyosin-microtubule crosstalk.

          Non-muscle myosin II has diverse functions in cell contractility, cytokinesis and locomotion, but the specific contributions of its different isoforms have yet to be clarified. Here, we report that ablation of the myosin IIA isoform results in pronounced defects in cellular contractility, focal adhesions, actin stress fibre organization and tail retraction. Nevertheless, myosin IIA-deficient cells display substantially increased cell migration and exaggerated membrane ruffling, which was dependent on the small G-protein Rac1, its activator Tiam1 and the microtubule moter kinesin Eg5. Myosin IIA deficiency stabilized microtubules, shifting the balance between actomyosin and microtubules with increased microtubules in active membrane ruffles. When microtubule polymerization was suppressed, myosin IIB could partially compensate for the absence of the IIA isoform in cellular contractility, but not in cell migration. We conclude that myosin IIA negatively regulates cell migration and suggest that it maintains a balance between the actomyosin and microtubule systems by regulating microtubule dynamics.
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            Rho protein crosstalk: another social network?

            Many fundamental processes in cell biology are regulated by Rho GTPases, including cell adhesion, migration and differentiation. While regulating cellular functions, members of the Rho protein family cooperate or antagonize each other. The resulting molecular network exhibits many levels of interaction dynamically regulated in time and space. In the first part of this review we describe the main mechanisms of this crosstalk, which can occur at three different levels of the pathway: (i) through regulation of activity, (ii) through regulation of protein expression and stability, and (iii) through regulation of downstream signaling pathways. In the second part we illustrate the importance of Rho protein crosstalk with two examples: integrin-based adhesion and cell migration. Copyright © 2011 Elsevier Ltd. All rights reserved.
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              Nonpolarized signaling reveals two distinct modes of 3D cell migration

              Introduction How normal cells move efficiently through chemically and structurally diverse 3D environments in vivo is not well understood. In contrast, findings of metazoan cells migrating on uniform 2D surfaces in vitro have led to a comprehensive model of cell motility wherein polarized signaling orchestrates cell movement by directing lamellipodial protrusion at the leading edge, adhesion to the underlying substrate, and retraction at the trailing edge (Lauffenburger and Horwitz, 1996; Ridley et al., 2003). The second messenger phosphatidylinositol (3,4,5)-trisphosphate (PIP3) is enriched at the leading edge (Haugh et al., 2000), where it can recruit downstream effectors, such as guanine exchange factors (Côté et al., 2005) that activate the Rho family of GTPases. Rho family members Rac1, Cdc42, and RhoA are active at the leading edge and coordinate protrusion and adhesion (Kraynov et al., 2000; Nalbant et al., 2004; Pertz et al., 2006; Machacek et al., 2009). Disrupting the subcellular localization of Rac1, Cdc42, or RhoA can lead to defects in adhesion and motility (van Hennik et al., 2003; ten Klooster et al., 2006; Bass et al., 2007), whereas the light-mediated activation of photosensitive guanine exchange factor, Rac1, or Cdc42 constructs at discrete regions of the plasma membrane triggers protrusion and directional cell migration (Levskaya et al., 2009; Wu et al., 2009). Discrepancies in the localization of Rho family GTPase activities during cell migration in vivo versus on 2D surfaces might reveal differences in the mechanisms that drive cell motility. Studies of cancer cell migration in 3D environments show that metastatic cells can switch between adhesion-dependent mesenchymal (elongated) and adhesion-independent amoeboid (rounded) cell motility (Table S1), driven by actin polymerization and actomyosin contraction, respectively (Wolf et al., 2003; Lämmermann and Sixt, 2009). Although these two different modes of cancer cell migration have specific requirements for Rho family GTPase signaling, how that signaling is organized is not known. Furthermore, it is unclear how the mesenchymal–amoeboid transition relates to normal 3D cell migration (Sanz-Moreno and Marshall, 2010). Some aspects of intracellular signaling organization during cell migration in vivo can differ from the organization seen on 2D surfaces. Chemotaxing primordial germ cells display randomly distributed regions of RhoA activity and a uniform distribution of PIP3 in the plasma membrane (Dumstrei et al., 2004; Kardash et al., 2010). However, Rac1 activity is enriched at the leading edge of migrating border cells and primordial germ cells during development, and PIP3 is abundant at the leading edge of neutrophils during interstitial migration toward wounded tissue (Kardash et al., 2010; Wang et al., 2010; Yoo et al., 2010). The reason for these differences is not clear, but they may result from structural differences in the surrounding ECM (Friedl and Wolf, 2010). Two structural parameters that characterize the ECM are stiffness, defined by the elastic or Young’s modulus (E; Engler et al., 2006), and strain stiffening, a measurement of how the stiffness of a material depends on the magnitude of force applied to it (here measured as Ehigh/Emed; Storm et al., 2005; Winer et al., 2009). Strain stiffening (Ehigh/Emed > 1) is a form of nonlinear elasticity; thus, materials that do not undergo strain stiffening (Ehigh/Emed = 1) are considered linearly elastic. Tissue explants and in vitro models of the 3D ECM, such as the cell-derived matrix (CDM) and type I collagen, can closely mimic different complex tissue environments (Elsdale and Bard, 1972; Cukierman et al., 2001; Even-Ram and Yamada, 2005; Ahlfors and Billiar, 2007; Wolf et al., 2009) and permit high-resolution live-cell imaging to visualize intracellular signaling. We used primary human fibroblasts in these models to test the hypothesis that structurally distinct 3D ECM environments support different modes of normal cell migration. We find that the degree of polarization of PIP3 and Rho family GTPase signaling at the leading edge identifies two distinct modes of normal cell motility governed intrinsically by RhoA, Rho-associated protein kinase (ROCK), and myosin II and extrinsically by the elastic behavior of the ECM. Results Lamellipodia-independent 3D migration in dermal explants Dermal tissue explants derived from mouse ears contain many of the structural features found in the human dermis (Fig. 1 A; Montagna et al., 1992; Lämmermann et al., 2008). Thick bundles of collagen fibers are proximal to the basal explant surface, whereas adipocytes and hair follicles embedded within reticular collagen and elastic fibers tend to be more distal (Fig. 1 B). Human fibroblasts migrating in both proximal and distal regions of the explant were predominantly uniaxial, consistent with cells migrating inside 3D in vitro models of the ECM (Fig. 1 C; Bard and Hay, 1975; Cukierman et al., 2001). The prominent lamellipodia and flat lamellae of cells migrating in 2D were not apparent, and many cells instead featured large blunt, cylindrical protrusions characteristic of lobopodia (Kudo, 1977), an intracellular pressure-driven protrusion (Fig. 1 C and Video 1; Yanai et al., 1996). This morphology of human foreskin fibroblasts (HFFs) in dermal explants was similar to that of cells in wounded tissue (Singer et al., 1984). In addition, cells often displayed small blebs along their sides that we termed lateral blebs (Fig. 1 C, arrowheads). Imaging a dual-chain Rac1 biosensor based on intermolecular fluorescence resonance energy transfer (FRET) revealed that, contrary to findings using 2D surfaces (Kraynov et al., 2000), active Rac1 was not targeted to the leading edge during HFF migration in both proximal or distal regions of the explant (85%, n = 26; Rac1 polarization index [PI] = −0.04 ± 0.09, in which 1 = forward polarization, 0 = nonpolarization, and −1 = rear polarization; Figs. 1 D, S1, and S2). Thus, Rac1 activity was not polarized in elongated HFFs migrating within the structurally heterogeneous, physiological 3D environment of dermal explants. To study the mechanistic basis of this apparently novel mode of lamellipodia-independent 3D cell motility (hereafter referred to as lobopodia-based migration), we recapitulated it using 3D in vitro models of the ECM. Figure 1. Lobopodia-based 3D migration occurs in the mammalian dermis. (A) A 3D reconstruction of a mouse ear dermal explant labeled with Alexa Fluor 633 (grayscale). Stratum corneum (SC), basal keratinocytes (BK), papillary dermis (PD), and reticular dermis (RD) are indicated. Sebaceous gland (SG) and hair follicle (HF) are outlined in gray. (B) Examples of ECM structures proximal (left) and distal (right) to the basal surface of a dermal explant labeled with Alexa Fluor 633. Images are from the same confocal stack, 9 µm (left) and 30 µm (right) from the basal surface. AC, adipocyte. (C) 3D reconstructions of lobopodia-bearing HFFs migrating in proximal and distal collagen; GFP-actin is shown in green, and second harmonic imaging of collagen appears in grayscale. Arrowheads indicate lateral blebs. (D) Active Rac1 is not targeted to the leading edge of HFFs migrating in the mammalian dermis. Rac1 activity was imaged in HFFs migrating in proximal or distal ECMs; active Rac1, representing the Fc image, was pseudocolored according to the 16-color scale shown to the right of the figure, and the explant was labeled with Alexa Fluor 633 (grayscale). All cells are oriented with the leading edge toward the right of the figure. Bars, 5 µm. Lobopodia and lamellipodia in 3D in vitro models of the ECM The CDM contains fibronectin, collagen I and III, hyaluronic acid, heparan sulfate proteoglycan, and thrombospondin in parallel fibers 50–500 nm thick (Fig. 2 A; Hedman et al., 1979; Allio and McKeown-Longo, 1988). Polymerized collagen I forms a nonaligned 3D meshwork (Fig. 2 A) of single or bundled collagen fibers 2–500 nm in diameter (Elsdale and Bard, 1972; Gelman et al., 1979). We compared the mechanical properties of dermal explants, the CDM, and collagen by characterizing their stiffness and elastic behavior. Dermal explants (6,427 Pa, range of 277–19,400 Pa) and CDMs (627 Pa, range of 224–2,454 Pa) were stiffer than 1.7 mg/ml collagen (15 Pa, range of 11–21 Pa), did not undergo strain stiffening (Ehigh/Emed = 1.01), and were thus linearly elastic (Fig. 2, B and C). In contrast, 1.7 mg/ml collagen displayed the strain-stiffening behavior (Ehigh/Emed = 1.12) characteristic of nonlinear elastic materials as previously established (Storm et al., 2005). Cells migrating in the soft 1.7 mg/ml of 3D collagen deformed the collagen fibers as described in a previous study of collagen remodeling by motile cells (Grinnell and Lamke, 1984), whereas the arrangement of fibers within the stiffer CDM was largely unaffected by migrating HFFs (Fig. 2 A). Figure 2. CDM and type I collagen support lobopodia- and lamellipodia-based 3D migration, respectively. (A) HFF-generated CDM has an aligned, fibrillar structure (top left), whereas polymerized 1.7 mg/ml type I collagen forms a random meshwork (bottom left). Both images are maximum projections of 30-µm confocal stacks. Collagen is remodeled by migrating HFFs (GFP, green) along the axis of migration (bottom right), whereas the organization of the CDM is unaffected by migrating HFFs (top right). The CDM was labeled with Alexa Fluor 633, and collagen was visualized by reflection microscopy. (B) Matrix stiffness (Young’s modulus [E]) of the indicated 3D matrices. (C) Strain-stiffening (Ehigh/Emed) behavior of the indicated 3D matrices. Ehigh/Emed > 1 indicates nonlinear elasticity, whereas Ehigh/Emed = 1 indicates linear elasticity (dashed red line). (D) Collagen and 2D CDM support lamellipodia-based migration, whereas 3D CDM triggers lobopodia-based motility. (top) Maximum projections of HFFs expressing GFP migrating inside the 3D CDM, on top of the 2D CDM, or inside type I collagen. LM, lamellipodium; LB, lobopodium. (bottom) The orthogonal views of the corresponding panel above, with the CDM (Alexa Fluor 633) and type I collagen (reflection microscopy) in red. Arrowheads indicate lateral blebs. (E) Cortactin is not enriched at the leading edge during lobopodia-based migration. HFFs migrating in the indicated ECM were fixed and immunostained for cortactin. Arrows indicate the local accumulation of cortactin at the leading edge. Bottom graphs correspond with their respective top images and represent the mean cortactin intensity measured from the leading edge (0 µm) toward the cell center. Each cortactin intensity profile was averaged from 13 cells, with three measurements per cell. Bars: (A and E) 5 µm; (D, top left and middle) 10 µm; (D, top right) 20 µm. All cells are oriented with the leading edge toward the right of the figure. Error bars show means ± SEM. *, P 500 arbitrary units (Fig. S1, C and F). We confirmed that their expression did not significantly affect cell velocity or downstream signaling (Fig. S2, A and B). Additionally, the subcellular localization of the CFP-tagged Rac1 and Cdc42 was predominantly cytosolic and consistent with the corresponding endogenous protein (Fig. S2 C); excessive GTPase expression would have resulted in inappropriate membrane targeting (Michaelson et al., 2001). Active Rac1 and Cdc42 were both polarized near the leading edge of cells on the 2D CDM (Rac1: PI = 0.73, n = 27; Cdc42: PI = 0.49, n = 14; Fig. 3, C–F) and in 3D collagen (Rac1: PI = 0.49, n = 34; Cdc42: PI = 0.38, n = 21; Fig. 3, C–F), as previously reported for lamellipodia-based migration on 2D surfaces (Kraynov et al., 2000; Nalbant et al., 2004). However, during lobopodia-based migration in the 3D CDM, active Rac1 and Cdc42 were no longer restricted to the leading edge; instead, they were localized to patches of unknown function around the perimeter of the cell (Rac1: PI = 0.22, n = 44; Cdc42: PI = 0, n = 21; Fig. 3, C–F), consistent with the nonpolarized distribution of active Rac1 in HFFs in dermal explants (Fig. 1 D). The distribution of Rac1 and Cdc42 activity in lobopodia could not be attributed to failure of the biosensors because nonfunctional versions reported uniform Fc patterns in HFFs on 2D and in 3D CDMs (100%; Fig. S2 D). Together, these data show that the canonical polarizations of PIP3, Rac1, and Cdc42 signaling during 2D migration are not necessary for lobopodia-based 3D migration in dermal explants and the CDM but are observed during lamellipodia-based migration in 3D collagen. RhoA, ROCK, and myosin II are required for lobopodia-based 3D migration To define further the mechanistic basis of lobopodia-based 3D migration, the roles of Rac1, Cdc42, and RhoA in motility in the 3D CDM were tested by specific siRNA-mediated knockdown (Figs. 4, A and B; and S4). Reducing Rac1 or Cdc42 protein levels moderately increased or decreased the velocity of HFFs migrating in and on the CDM, respectively, without affecting the mode of 3D cell motility (Fig. 4, C and D). Cells that were inside the 3D CDM continued to migrate without lamellipodia (94% for Rac1 siRNA and 92% for Cdc42 siRNA), and many of the cells retained lateral blebs. In contrast to Rac1 and Cdc42 siRNA, knockdown of RhoA protein and activity dramatically switched the mode of migration in the 3D CDM from lobopodia to lamellipodia based. RhoA-depleted cells migrated in the 3D CDM with distinct lamellipodia at the leading edge (100%; Figs. 4 C and S4 A and Video 4) and without any lateral blebs. The role of RhoA in regulating the mode of migration was confirmed with independent single siRNAs (Fig. S4, B–D) and a single siRNA from the original RhoA siRNA pool (Fig. S4, E–G). Additionally, treating cells migrating in the 3D CDM with a RhoA inhibitor switched the cells to lamellipodia-based motility (Fig. S4, H and I). Despite switching the mode of 3D cell migration in the CDM, knocking down RhoA did not affect the velocity of HFF migration in or on the CDM (Fig. 4 D). Figure 4. RhoA, ROCK, and myosin II are required for lobopodia-based 3D migration inside CDM. (A) A representative Western blot demonstrating the specificity of siRNA-mediated knockdown of Rac1, Cdc42, or RhoA. HFFs were transfected with the indicated siRNAs and lysed 72 h after transfection, and the lysates were blotted with the indicated antibodies. (B) Quantification of Western blots represented in A. (C) RhoA siRNA treatment switches HFFs to lamellipodia-based 3D migration in the CDM. The percentage of lobopodia-bearing HFFs migrating inside the CDM after the indicated treatments. (A and B) *, P 500 but typically between 700 and 1,300) or GFP-AktPH intensity (considered positive when 1.5× greater than the cytoplasmic background fluorescence) were plotted relative to the cell’s center of mass. The PI for each cell was calculated using PI = ∑ i n ( x i S L D i ) n , in which x is the distance of the region from the origin along the x axis, SLD is the straight line distance of the region from the origin, and n is the number of regions per cell. In this scheme, a PI of 1 = forward polarization (all regions lie on the positive x axis), 0 = nonpolarization (regions are uniformly distributed), and −1 = rearward polarization (all regions lie on the negative x axis). siRNA treatment, Western blotting, and motility assays 2 × 105 HFFs were plated in each of three 60-mm dishes and transfected the next day with a 20-nM solution of the indicated siRNA preparation. 48 h later, 105 siRNA-treated cells from the first 60-mm dish were transfected with pGFP-actin, plated on the CDM labeled with Alexa Fluor 633, and imaged the next day using a spinning-disc confocal microscope. 104 HFFs from the second 60-mm dish were plated in 10% FBS in DME on the CDM. The next day, time-lapse sequences were captured at 37°C and 10% CO2 using a 5×, 0.12 NA A-Plan objective on a microscope (Axiovert 40C; Carl Zeiss) with a charge-coupled device camera (INFINITY2; Lumenera). Cells were tracked every 26 min for 12 h using the Manual Tracking plugin (F. Cordelieres, Institut Curie, Paris, France) with ImageJ 1.40g. Velocity and directionality (the ratio of Euclidean to accumulated distance traveled, in which 1 = a straight line) were calculated from the tracking data using the Chemotaxis and Migration Tool plugin (ibidi) with ImageJ. For the integrin, ROCK, or myosin II inhibition experiments or PDGF ± glucose motility assays, 104 HFFs were plated on glass, the CDM, or in 1.7 mg/ml collagen in 35-mm MatTek dishes and treated the following day. Imaging, cell tracking (every 26 min for 12 h), and analysis were performed as described for the siRNA-treated cells. 72 h after transfection with siRNA, HFFs from the third 60-mm dish were lysed in lysis buffer (2% IGEPAL, 40 mM NaCl, 10 mM MgCl2, and 50 mM Tris, pH 7.5) plus protease inhibitors (Cytoskeleton). Cleared lysates were combined with an equal volume of 2× sample buffer (Invitrogen), heated to 95°C for 5 min, resolved by SDS-PAGE on a 4–12% Tris-glycine polyacrylamide gel (Invitrogen), and transferred to nitrocellulose (0.2-µm pores; Invitrogen). Antibodies used for Western blotting were mouse anti-Rac1 (Millipore), mouse anti-Cdc42 (BD), mouse anti-RhoA (Abcam), mouse antiactin (Sigma-Aldrich), and mouse anti–glyceraldehyde 3-phosphate dehydrogenase (Fitzgerald Industries). Blots were developed using ECL reagents (GE Healthcare) and visualized on a luminescent image analyzer (LAS-4000; Fujifilm). Western blots were quantified by normalizing the GTPase intensity to the corresponding glyceraldehyde 3-phosphate dehydrogenase signal and determining the change in expression relative to the siGLO-treated control. Measurement of Young’s modulus by atomic force microscopy Experiments were performed using an atomic force microscope (Catalyst; Bruker AXS) mounted on the stage of an inverted microscope (Axiovert 200) placed on a vibration isolation table (IsoStation). Matrices were kept at 37°C and buffered with PBS throughout the experiments. Force displacement curves were obtained in contact mode using pyramidal tip cantilevers of nominal stiffness, k = 0.03 N/m. For each cantilever used, stiffness was obtained by the thermal fluctuations method (Butt and Jaschke, 1995). Force displacement curves were acquired by ramping the cantilever 12 µm at 1 Hz. To prevent damage to the samples, the maximum force applied was ∼0.5 nN for soft matrices and ∼3 nN for stiff matrices. Young’s modulus (E) was computed by fitting force displacement curves with Sneddon’s formula for an indenting cone using F = 2 E tan α π ( 1 − v 2 ) δ 2 , in which F is the applied force, ν is Poisson’s ratio and was assumed to be 0.5, δ is the indentation, and α is the half-opening angle of the pyramidal tip (Sneddon, 1965). To measure strain stiffening, E was computed fitting only regions of the force displacement curves corresponding to large indentations or medium indentations. The ratio of Ehigh/Emed was reported as a measure of the matrix’s strain-hardening behavior. All computations were performed using custom-built code written in Matlab (MathWorks). Modification of the 3D in vitro models Alexa Fluor 633–labeled CDM was treated with 0.05% trypsin + 0.5 mM EDTA (Invitrogen) for 10 min at 37°C and then washed extensively with DME with 10% FBS. 1.7 mg/ml collagen and trypsinized CDM were cross-linked with 25 mM BS(PEG)9 (bis-N-succinimidyl-(nonaethylene glycol) ester) and BS(PEG)5 (Thermo Fisher Scientific), respectively, in PBS for 30 min at RT followed by extensive washing with DME with 10% FBS. 105 HFFs transfected with pCFP-Rac1 and pYPet-PBD or pGFP-actin were plated on the trypsinized and/or cross-linked matrix and imaged the next day. GFP-actin dynamics were analyzed by spinning-disc confocal microscopy, and Rac1 activity was visualized using the confocal microscope (LSM 710 Axio Examiner.Z1) as described in Live-cell imaging in dermal explants. Statistical analysis Results are reported as the mean ± SEM. One-way analysis of variance with Tukey posttests was used to compare three or more variables; otherwise, unpaired, two-tailed Student’s t tests were performed. Nonparametric Kruskal–Wallis tests were used with a Dunn’s multiple comparisons posttest when comparing more than two groups of measurements with bounded values when analyzing the PI. All comparisons were performed using Prism5 (GraphPad Software). Differences were considered statistically significant at P < 0.05. Online supplemental material Fig. S1 and S2 detail the validation of the Rac1 and Cdc42 FRET-based biosensors. Fig. S3 shows the relative distribution of GFP-PLC-δPH in HFFs in different environments, along with endogenous PIP2 and PIP3. Fig. S4 provides additional evidence that RhoA activity is required for lobopodia formation in the 3D CDM. Table S1 compares the lobopodia- and lamellipodia-based 3D migration of normal cells with previously published work examining cancer cell motility. Video 1 shows lobopodia-based 3D migration in the mammalian dermis. Video 2 shows lobopodia-based 3D migration in the CDM and lamellipodia-based 2D migration on top of the CDM. Video 3 that shows HFFs use lamellipodia-based 3D migration in type I collagen. Video 4 shows that reduction of RhoA protein switches the mode to lamellipodia-based 3D migration in the CDM. Video 5 shows that ROCK activity is required for lobopodia-based migration. Video 6 is a phase-contrast video of HFFs migrating in and on the CDM during blebbistatin treatment. Video 7 shows that HFFs use lamellipodia-based 3D migration in a pliable CDM. Video 8 shows that cross-linking the trypsinized CDM restores lobopodia-based 3D migration. Video 9 shows that HFFs use lobopodia-based 3D migration in cross-linked collagen. Video 10 shows lamellipodia-based 3D HFF migration in 8.6 mg/ml collagen. Online supplemental material is available at http://www.jcb.org/cgi/content/full/jcb.201201124/DC1.
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                Author and article information

                Journal
                J Cell Biol
                J. Cell Biol
                jcb
                The Journal of Cell Biology
                The Rockefeller University Press
                0021-9525
                1540-8140
                2 September 2013
                : 202
                : 5
                : 807-824
                Affiliations
                [1 ]Department of Chemical and Biomolecular Engineering ; [2 ]Physical Sciences-Oncology Center ; [3 ]Center for Cancer Nanotechnology Excellence ; [4 ]Institute for NanoBioTechnology ; and [5 ]Department of Oncology and [6 ]Department of Cell Biology, School of Medicine; Johns Hopkins University, Baltimore, MD 21218
                Author notes
                Correspondence to Konstantinos Konstantopoulos: konstant@ 123456jhu.edu ; or Joy T. Yang: jyang@ 123456jhmi.edu
                Article
                201302132
                10.1083/jcb.201302132
                3760608
                23979717
                0bbdc53f-0114-4f94-a3f2-123360518e86
                © 2013 Hung et al.

                This article is distributed under the terms of an Attribution–Noncommercial–Share Alike–No Mirror Sites license for the first six months after the publication date (see http://www.rupress.org/terms). After six months it is available under a Creative Commons License (Attribution–Noncommercial–Share Alike 3.0 Unported license, as described at http://creativecommons.org/licenses/by-nc-sa/3.0/).

                History
                : 25 February 2013
                : 26 July 2013
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                Cell biology
                Cell biology

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