R E S E A R C H A R T I C L E

C E L L M O T I L I T Y

ERK reinforces actin polymerization to powerpersistent edge protrusion during motilityMichelle C. Mendoza,1*†‡ Marco Vilela,1†§ Jesus E. Juarez,2 John Blenis,1¶ Gaudenz Danuser1*§

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Cells move through perpetual protrusion and retraction cycles at the leading edge. These cycles arecoordinated with substrate adhesion and retraction of the cell rear. We tracked spatial and temporalfluctuations in the molecular activities of individual moving cells to elucidate how extracellular signal–regulated kinase (ERK) signaling controlled the dynamics of protrusion and retraction cycles. ERK isactivated by many cell surface receptors, and we found that ERK signaling specifically reinforcedcellular protrusions so that they translated into rapid, sustained forward motion of the leading edge.Using quantitative fluorescent speckle microscopy and cross-correlation analysis, we showed thatERK controlled the rate and timing of actin polymerization by promoting the recruitment of the actinnucleator Arp2/3 to the leading edge. These findings support a model in which surges in ERK activityinduced by extracellular cues enhance Arp2/3-mediated actin polymerization to generate protrusionpower phases with enough force to counteract increasing membrane tension and to promote sus-tained motility.

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INTRODUCTION

Cell movement is essential to many biological phenomena, including em-bryogenesis, wound healing, and cancer metastasis. The motility processinvolves cycles of membrane protrusion and retraction at the leading edge,which are coordinated in space and time with adhesion dynamics and cellrear retraction (1).

In migrating epithelial sheets, the rate of edge protrusion is driven bythe rate of F-actin assembly (2). A dendritically branched polymernetwork grows against the leading-edge plasma membrane and turns overwithin 1 to 4 mm from the cell edge, which defines the lamellipodium(3, 4). The seven-subunit Arp2/3 protein complex mediates nucleation ofthis branched actin filament assembly. The WAVE regulatory complex ac-tivates Arp2/3 (5, 6) and is recruited along with Arp2/3 to the edge ofexpanding protrusions (7–9). Rac and phospholipid binding recruit theWAVE regulatory complex to the plasma membrane (10–13).

We have previously proposed a model in which protrusion initiation isfollowed by a power phase of increased actin filament assembly (wecalculated power output from the product of the cell boundary force andthe cell-edge motion) (14). We have proposed that as membrane tensionincreases during edge advancement, the power phase is terminated by amaximal tension level that exceeds the amount of propulsion and adhesionstress produced by the combined assembly of actin filaments and nascentadhesions. In this scenario, protrusion cycle duration is directly related tothe efficiency with which actin filament assembly is increased after pro-trusion initiation. Biochemical mechanisms involving signaling proteinslikely contribute to the force and tension-based control. For example,the Rac exchange factor b-PIX and the Rac-recruited Arp2/3 inhibitory

1Department of Cell Biology, Harvard Medical School, Boston, MA 02115,USA. 2Departments of Cell and Tissue Biology and Pathology, University of Cal-ifornia, San Francisco, 513 Parnassus Avenue, San Francisco, CA 94143, USA.*Corresponding author. E-mail: michelle.mendoza@ucsf.edu (M.C.M.); gaudenz.danuser@utsouthwestern.edu (G.D.)†These authors contributed equally to this work.‡Present address: Department of Cell and Tissue Biology, University of Cal-ifornia, San Francisco, San Francisco, CA 94143, USA.§Present address: Department of Cell Biology, University of Texas SouthwesternMedical School, 5323 Harry Hines Boulevard, Dallas, TX 75390–9039, USA.¶Present address: Meyer Cancer Center, Weill Cornell Medical College,1300 York Avenue, F-113, New York, NY 10065, USA.

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molecule Arpin create positive and negative feedback loops for lamellipodialactin polymerization that control protrusion and retraction cycles (15, 16).How extracellular signals feed into and perturb the force and control ofprotrusion cycle timing is largely unexplored.

Myriad signaling inputs from growth factors, hormones, neurotrans-mitters, and chemokines feed into the cell migration machinery. One ofthe chief transducers of signals is extracellular signal–regulated kinase(ERK), a mitogen-activated protein kinase (MAPK) (17, 18). ERK is ac-tivated by the small guanosine triphosphatase (GTPase) Ras, which recruitsthe Ser/Thr kinase Raf to the plasma membrane for activation. Raf phos-phorylates and activates the kinases MEK1/2 (MAPK kinase 1/2), whichactivate ERK1/2 (17, 18). Hereafter, we use MEK to refer to MEK1/2, andERK to refer to the ERK1/2 isoforms. ERK activity is necessary for epithe-lial sheet and tubule movement, forms of cell migration common duringembryogenesis, wound healing, and cancer metastasis (19–21). Reports onERK’s role in migration include transcription-dependent induction ofepithelial-to-mesenchymal transition (22, 23) to direct regulation of actinpolymerization and focal adhesions (24–26).

We have previously found that ERK phosphorylation of the WAVE reg-ulatory complex promotes the interaction of WAVE with Arp2/3 (25). ERKinhibition for several hours reduces spontaneous protrusion velocity in mod-el migrating epithelial sheets (25). Here, we asked whether the role of ERKin protrusion could be separated from its transcriptional activity by assayingthe immediate effects of acute ERK inhibition. We analyzed fluctuations inedge motion during steady-state motility and discovered that ERK promoteda gain in protrusion velocity and duration. We spatiotemporally resolvedERK’s point of action and found that after protrusion initiation, ERK pro-moted Arp2/3 accumulation at the cell edge, which drove the increase inactin polymerization for protrusion reinforcement. Thus, ERK signalingcreates the assembly power needed to overcome increasing membrane ten-sion as protrusions progress and cells move forward.

RESULTS

ERK promotes cell motilityWe assessed the effects of MEK1/2 inhibition on cell movements usingAZD6244, a noncompetitive MEK1/2 inhibitor with improved potency

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and specificity over U0126, an older inhibitor that also inhibits MEK5signaling to ERK5 (27–29). Phosphatases constantly remove MEK’s ac-tivating phosphorylations on ERK (30) so that treatment of PtK1 epithelialcells with the MEK inhibitor AZD6244 reduced ERK activation within1 min (fig. S1A). Phosphorylation of the ERK substrates p90 ribosomalS6 kinase (31) and WAVE2 (32) was lost in 2 to 3 min (fig. S1, A and B).Inhibiting MEK with the compound AZD6244 reduced single-cell migra-tion distance in many cell types, including Panc1 pancreatic cancer cellsharboring an activating Kras mutation, MDA-MB-468 breast cancer cellsharboring amplification of the EGFR gene (which encodes the epidermalgrowth factor receptor), and Sk-Mel-28 and A375 melanoma lines har-boring the activating BrafV600E mutation (Fig. 1A). MEK inhibition alsoreduced the epithelial sheet migration of untransformed PtK1 cells closinga wound (Fig. 1B), a process driven by edge protrusion and adhesion rath-er than actomyosin contraction (2). Dimethyl sulfoxide (DMSO)–treatedsheets moved at a median velocity of 0.328 mm/min, whereas AZD6244-treated sheets moved at 0.198 mm/min (P = 0.0081).

ERK signaling increases membrane protrusion velocityand persistence timeWe imaged the spontaneous edge protrusion and retraction cycles ofsteady-state (log-phase) PtK1 epithelial cells expressing Emerald-LifeActas a generic actin cytoskeleton marker (movies S1 and S2). We identifiedthe cell edge and tracked it over time (Fig. 1C), and from these traces, wecalculated the velocity along the entire cell edge (movies S3 and S4) (33).We developed a signal detection algorithm to extract the significant pro-trusion and retraction events from the noisy velocity profile of each edgesegment (Materials and Methods). From each detected event, we extractedthe event duration and calculated the mean and maximum velocities of thatduration. Quantification of the percentage of cell-edge segments in statesof protrusion, retraction, and quiescence (when velocity was at 0) revealeda retraction response induced by the physical perturbation of adding re-agent to both control and treated cells. DMSO-treated cells recovered theirnative motion state within 5 to 10 min after treatment, whereas AZD6244-treated cells did not (Fig. 1D). We removed the retraction artifact from theedge velocity analysis by dividing the data into three time intervals: steadystate, 1 to 10 min after treatment, and 10 to 20 min after treatment. Wefound that short-term MEK inhibition reduced the mean protrusion veloc-ity 10 to 20 min after treatment (Fig. 1E, All, and table S1). Although theprotrusion velocity of the control cells was statistically different betweensteady state and 10 to 20 min after treatment, the distributions overlappedby 70%. In contrast, the distribution overlap between steady-state andMEK inhibitor–treated cells after 10 to 20 min was only 20%. The reduc-tion in protrusion velocity after DMSO treatment was likely a residual ef-fect of the retraction artifact induced by physically perturbing the cells.When compared to the protrusion dynamics of control cells treated withDMSO for 10 to 20 min (median of the mean velocities: 12.4 nm/s), MEKinhibition significantly reduced protrusion velocity (median of the meanvelocities: 8.1 nm/s; fig. S1C and table S1). MEK inhibition also reducedprotrusion persistence time (Fig. 1F, All, and table S1). Thus, MEK inhi-bition shifted the distribution of edge protrusions to events with slowervelocities and shorter durations.

We hypothesized that ERK activity was particularly necessary for theproduction of faster, more persistent protrusions that have entered thepower phase. Indeed, the reduction in both protrusion velocity and persist-ence upon MEK inhibition became more evident when only the 25% fastestand longest protrusion events were analyzed (Fig. 1, E and F, fig. S1C, 75thPercentile, and table S1). Cells treated for 10 to 20 min with DMSO exhib-ited a 75th percentile mean protrusion velocity of 25.6 nm/s, whereas cellstreated with the MEK inhibitor exhibited protrusions with a 75th percentile

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mean velocity of 18.9 nm/s. Similar results were found when the data wereanalyzed using the maximum protrusion velocity reached per protrusioncycle (table S1) and when cells were treated with the structurally distinctMEK inhibitor U0126 and imaged on an independent microscopeconfiguration (fig. S1, E to G). In the latter case, the overall protrusion velocitywas slower, which we attributed to lot-specific variability in the imagingmedium and changes in the microscope configuration. Nonetheless, U0126significantly reduced protrusion velocity and persistence. To test whetherERK was necessary for the maximum range of protrusion velocity andpersistence, we plotted the maximum velocity against the duration of eachprotrusion event in steady-state cells and 10 to 20 min after treatment (Fig.1G). In control cells, 25% of protrusion events reached velocities greaterthan 50 nm/s and lasted for more than 90 s. Treatment with the vehicleDMSO did not change this distribution, whereas MEK inhibition caused ashift to slower, shorter protrusions, such that only 1% of the treated eventsreached peak velocities greater than 50 nm/s. These findings were furtherconfirmed in PtK1 cells stably expressing hyperactive BrafV600E, whichcauses a moderate increase in ERK activity (fig. S2A). The BrafV600E cellsexhibited more frequent protrusion events that reached greater mean andmaximum velocities than did cells expressing empty vector (fig. S2, B andC). The persistence time was reduced in the 75th percentile BrafV600E

events (fig. S2D), suggesting that the more frequent and faster protrusionsmight be running out of other necessary actin assembly factors to maintaintheir persistence.

We also found that MEK inhibition reduced and MEK activation pro-moted retraction velocity (fig. S3, A, B, and E). This is in contrast to ourprevious data (25), in which we treated cells with the MEK inhibitor for4 hours and did not remove noise in the velocity analysis. ERK may alsopromote retraction persistence. Retractions in control cells exhibited aninsignificant reduction in persistence time from 32.5 to 30.9 s upon treat-ment with DMSO for 10 to 20 min, whereas retractions in MEK inhibitor–treated cells exhibited a significant reduction in persistence from 34.6 to27.4 s (fig. S3C and table S1). However, because of cell-to-cell heteroge-neity, the steady states in control and treated groups were not equivalentand the retraction persistence after DMSO and AZD6244 treatments wasnot significantly different (fig. S3D). Increased ERK activation by BrafV600E

expression reduced retraction persistence (fig. S3F), similar to the BrafV600E-induced reduction in protrusion persistence. The regulation of retraction byERK could be secondary to reduced protrusion, because protrusion andretraction forces are in equilibrium during motility (2) or through directmodulation of the retraction machinery, such as myosin light chain kinaseor the adhesion component paxillin (34–37).

ERK promotes actin assembly dynamics in protrusionsWe hypothesized that ERK regulates protrusion by directly regulating ac-tin assembly in the power phase. Because ERK activation at adhesionscontributes to cell migration velocity (34), we aimed to directly assess actindynamics in situ. We microinjected fluorescent actin and used quantitativefluorescent speckle microscopy (qFSM) to identify speckles of assembledactin monomers and track their motion (38). We imaged cells for 9 min toobtain a measure of steady-state dynamics, added the MEK inhibitor, andimaged the cells again after a 10-min recovery period (movies S5 and S6).We confirmed that these cells had reduced protrusion velocity and persist-ence time upon MEK inhibition, similar to the cells labeled with LifeAct(39) (fig. S4, A to C).

Using actin qFSM software, we identified speckles in the raw images(Fig. 2A), and we tracked their displacements (Fig. 2B and movies S7 andS8) and used them to identify local events of actin filament polymerizationand depolymerization (40). In this method, speckles are assigned assemblyand disassembly scores, which are a function of the rate of change in

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Fig. 1. ERK signaling extends membrane protrusion velocity and persistence time. (A)Displacement distributions of cancer cells migrating after treatment with DMSO orAZD6244 (MEK inhibitor). n = number of cells tracked in three independent experiments.

(B) Representative images of the migration of a DMSO- or AZD6244-treated PtK1 monolayer after scratch wounding. (C) Representative overlay of single cell-edge dynamics tracked for 10 to 20min after treatment. Blue, early time points; red, late time points. (D) Representative profile (one of five cells in each treatmentgroup) of the fraction of the cell edge in protrusion, retraction, and quiescent states. (E and F) Velocity (E) and persistence time distributions (F) ofm significantprotrusion events inn=5DMSO-andAZD6244-treatedcells tracked in three to four independent experiments. The “>75thPercentile”graphsplot thedistributionof the top 25% of events in the corresponding “All” graphs. For (A), (E), and (F), gray area indicates total smoothed distribution, and the boxes’ upper and loweredges represent the 75th and 25th distribution percentiles, respectively. Central horizontal line indicates the median. Error bars about the median indicate 95%confidence interval. (G)Maximumvelocity compared topersistence timeof all protrusionevents tracked in three to four independent experiments. Encircledareasindicate eventswithin the 1st to 75th percentile of the joint velocity andpersistencedistribution. Shadedareas indicate protrusionswithin the 1st to 99th percentile.

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speckle intensity (net number of fluorescent actin monomers that areincorporated or unincorporated into the actin filament) and backgroundfluorescence. In our PtK1 cells, heterogeneous and rapidly changing cellprotrusion and retraction states along the cell edge meant that actin as-sembly and assembly-driven actin retrograde flows were spatially segre-gated and transient. As previously reported, averaging the actin dynamicsover time concealed spatiotemporal definition (41) but revealed typicallamellipodial actin characteristics: rapid retrograde flow (600 to 800 nm/min)toward the cell center and a 1- to 2-mm band of assembly followed by a 1-to 2-mm band of disassembly (4, 42, 43) (fig. S4, D and E). Fluorescence

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recovery after photobleaching (FRAP) of enhanced green fluorescent pro-tein (EGFP)–actin in B16-F1 melanoma cells has also shown that actinturnover is restricted to within ~2 mm of the cell edge (7). We then removedthe nonspecific spatial and temporal averaging and averaged the actinassembly and disassembly scores as a function of distance from the celledge. We found that during protrusion events, flow rates peaked at the celledge and continuously decreased over the 2- to 3-mm width of the lamel-lipodium (Fig. 2C). Actin polymerization peaked at, but was not restrictedto, the cell edge, and depolymerization peaked 0.5 mm inside the edge.Treatment with the MEK inhibitor reduced actin retrograde flow and actin

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assembly and disassembly rates at the celledge in protruding edges (Fig. 2, C to F).The effect of MEK inhibition on actin flowwas likely secondary to its effect on actinpolymerization, because less polymeriza-tion against the plasma membrane wouldgenerate less force converted into retrogradeflow (14). The MEK inhibitor–induced re-duction in actin disassembly is likely a com-bination of a shift in the steady-state balanceof lamellipodial actin assembly and dis-assembly and reduced incorporation ofArp2/3, because adenosine triphosphate hy-drolysis of incorporated Arp2 and Arp3contributes to actin network disassembly (44).

ERK regulates actin dynamicsduring the protrusion power phaseBecause cells treated with ERK inhibitorexhibit reduced protrusion velocity and per-sistence and reduced actin filament assem-bly rates, we postulated that these cellsgenerated a weaker actin assembly–driven“power phase” and their filament propulsionwas outcompeted by plasma membranetension earlier in the protrusion cycle thanin cells with normal ERK signaling. To testwhether ERK controlled the timing of actindynamics with respect to edge motion, wecomputed the cross-correlation of thesetwo waveforms. Cross-correlation scoresindicated the strength of coupling betweentwo waveforms, and the lag of the peak inthe score indicated the timing of the strongestcorrelation. Consistent with our previousresults (14), we found that in DMSO-treatedcells, actin flow negatively correlated withedge dynamics at time lag = 0 (Fig. 3A, mark1). Furthermore, actin flow positively corre-lated with edge motion in a MEK inhibitor–sensitive manner when flow was shifted 50to 60 s forward in time (Fig. 3A, mark 2 inleft panel; this correlation disappears in theright panel).

We then deconvolved the correlationplots by calculating the correlation scoresin retraction against protrusion events sep-arately. We found that the negative correla-tion between edge motion and flow waspresent in retractions, but not in protrusions

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Fig. 2. ERK promotes actin flow and assembly in protrusions. (A) Raw image of fluorescent actin speckles.The red outline defines the computationally segmented cell mask. (B) Instantaneous flow vectors ofspeckles identified in (A), calculated with qFSM software (38). Longer and red vectors indicate faster flowrate. Scale bar, 5 mm. (C to F) Normalized instantaneous rates of actin retrograde flow (C), polymerization(D and E), and depolymerization (F) calculated as average rate over all identified speckles as a function ofdistance from the cell edge. Data from a single representative control cell and a MEK inhibitor–treated cellbefore and after treatment. Shaded areas are 95% confidence interval. On average, within a micrometerfrom the cell edge, DMSO treatment reduced flow by 18 ± 1.1%, actin assembly by 2 ± 3.3%, and actindisassembly by 9 ± 7.3% (n = 6 cells tracked in four independent experiments). AZD6244 treatment re-duced flow rates by 28 ± 0.8%, actin assembly by 31 ± 5.7%, and actin disassembly by 38 ± 3.1% (n = 4cells tracked in four independent experiments).

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(Fig. 3, B and C), indicating that retrograde flow was fastest when retrac-tion velocity was peaking (Fig. 3B, mark 1′). In contrast, edge motion andflow positively correlated in the protrusions of DMSO-treated cells, butwith a shorter time delay (time lag = 20 s) than when total edge motionwas analyzed (Fig. 3C, mark 2′, compared to Fig. 3A, mark 2). We ana-lyzed a synthetic data set (fig. S5A) to test whether edge motion in retrac-tions artificially delayed the positive correlation between actin flow andedge motion in protrusions when both forms of edge motion were includedin the analysis. The synthetic total edge motion and flow and retractionmotion and flow were negatively correlated at lag = 0 (fig. S5, B andC). However, the positive correlation between edge motion and flow wasshifted toward longer time lags when total edge motion was correlated withprotrusion motion (fig. S5, B and D). Thus, because the negative correlation

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was stronger than the positive correlation, its inclusion in the analysis ar-tificially delayed the positive correlation between protrusion motion andactin retrograde flow. We concluded that the rate of retrograde flow peaked20 s after the maximal protrusion velocity, at the end of the power phase(Fig. 3C).

Because our previous model of the protrusion and retraction cycle wasbased on correlations with total edge motion (14), we computed the cross-correlation between edge motion and actin assembly rates separately duringprotrusion and retraction events. No correlation was found during retractionevents (Fig. 3D). In protrusion events, the correlation maximum occurredat lag = 20 s (Fig. 3E, left panel), indicating that the highest rate of actinassembly occurred 20 s after maximal protrusion velocity is reached, con-sistent with our previous report (14). Our new analysis indicated that

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Fig. 3. ERK regulates actin dynamics during protrusion power phase. (A)Temporal cross-correlation of actin flow with edge velocity along entireedge, including retractions and protrusions. Marks 1 and 2 indicate negativeand positive extrema, respectively. (B and C) Temporal cross-correlation ofactin flow specifically in retractions (B) and protrusions (C). Marks 1′ and 2′indicate that the negative and positive extrema of the combined cross-correlation in (A) are associated with retraction and protrusion events, re-spectively. (D and E) Temporal cross-correlation of actin assembly withedge velocity in retractions (D) and protrusions (E). Retraction velocitywas computed with negative values. Positive time lags in the x axis indi-cate that actin dynamics were delayed relative to edge motion. Thecorresponding model diagrams interpret the cross-correlation scores asreadouts of temporal coordination between actin dynamics and edge ve-

locity. E.V., edge velocity; R.F., retrograde flow; A.A., actin assembly. Or-ange arrows indicate how the indicated parameter of actin dynamics isaltered relative to the edge velocity upon MEK inhibition. In controlDMSO-treated cells, actin assembly correlated with protrusive edge mo-tion with a cross-correlation score of 0.4 and a delay of 20 s. In cells treatedwith AZD6244 and lacking ERK activity, actin assembly dynamics wereless correlated with edge motion (cross-correlation score of 0.2), and thiscorrelation occurred with a delay of only 10 s. (F) Revised model of thesequence of mechanical processes during protrusion and retractionevents. Actin retrograde flow correlates with the cell edge twice during aprotrusion-retraction cycle: once when peak retraction velocities are at-tained and once 20 s after protrusion initiation, which coincides with peakactin assembly.

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maximum retrograde flow occurred at the same time as the peak actinassembly during protrusion events. Both were delayed relative to the peakprotrusion velocity. Retrograde flow then peaked again when retractionvelocity was maximal, likely as a result of a release of adhesions andan increase in actomyosin contraction (14, 45) (Fig. 3F).

We next tested whether ERK activity controls the timing of actin dy-namics in the protrusion cycle. MEK inhibition had no effect on the neg-ative correlation between edge motion and actin flow during retraction(Fig. 3B, right panel). In contrast, MEK inhibition abrogated the correla-tion between edge dynamics and actin retrograde flow during protrusions(Fig. 3C). AZD6244 treatment also reduced the correlation score andshortened the time delay between edge dynamics and actin assembly dur-ing protrusion (Fig. 3E). Thus, ERK specifically coordinated the timing ofactin polymerization and retrograde flow during edge protrusion, but notretraction. Actin assembly and retrograde flow were reduced in cells withERK inhibition (Fig. 2), and actin assembly peaked sooner in the protru-sion cycle and was less correlated with edge motion than in cells withintact ERK signaling (Fig. 3). We conclude that ERK was necessary forreinforcing actin assembly against increasing membrane tension duringthe protrusion power phase.

ERK controls the protrusion power phase by modulatingArp2/3 recruitmentWe wanted to determine whether the effect of ERK on protrusion speedand persistence was through regulation of Arp2/3-mediated actin polym-erization. We hypothesized that ERK controls the intensity of activation ofprelocalized WAVE regulatory complex to increase the recruitment andactivation of Arp2/3. This is because ERK does not regulate WAVE re-cruitment to the membrane (25), and although ERK is sequestered in dif-ferent subcellular locales through scaffolding proteins, passive diffusion

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allows activated Ras to rapidly spread over 10 mm within seconds (18, 46).Thus, ERK is unlikely to be a localization signal for Arp2/3 recruitment orprotrusion initiation. In our previous experiments in which serum-starvedcells had been stimulated with EGF, we observed localization of phos-phorylated ERK with WAVE2 along the cell edge (25). Here, we exam-ined log-phase migrating cells harboring a low ratio of phosphorylated/unphosphorylated ERK. At any given time, these steady-state cells haveedges in states of protrusion, retraction, and quiescence, but immuno-fluorescence did not show a strong cell-edge localization of active ERK.Rather, phosphorylated ERK was found at the edge and throughout thelamella and cell body (fig. S6A). Phosphorylated ERK was not spatiallyrestricted to areas of active protrusion or retraction, as gauged by edgemorphology and Arp2/3 levels (fig. S6A). The specificity of the phospho-ERK–488 signal was demonstrated by the lack of staining in cells treatedwith the MEK inhibitor (fig. S6, B and D) or in cells that were not incu-bated with the anti–phospho-ERK antibody (fig. S6C).

We used GFP-tagged Arp3 to determine the effects of ERK inhibitionon Arp2/3 localization to the cell edge during steady-state motility (Fig. 4A).We quantified the GFP intensity in temporally aligned profiles (Fig. 4, Bto E). MEK inhibition reduced the amount of Arp3 recruited along theprofiles, but the reduction was only significant in the profile temporallyaligned 20 s after maximum protrusion, during the power phase (Fig. 4D).Thus, the presence of active ERK in initiated protrusions increased Arp2/3recruitment during the remainder of the protrusion cycle. We used immu-nofluorescence of ARPC2, a distinct Arp2/3 subunit, as an independentmethod of validating that ERK regulates Arp2/3 recruitment. We did notexpect to find a complete abrogation of Arp2/3 localization to the celledge upon ERK inhibition because the edges of fixed cells are in variousstates of protrusion initiation, power phase, retraction, and quiescence.However, we did find a trend in which MEK inhibition reduced overall

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Fig. 4. ERK controls actin assemblyand protrusion power phase by en-hancing Arp2/3 recruitment. (A to E)GFP-Arp3 localization at cell edge.

Green arrows indicate protrusion events(A). Normalized mean Arp3 intensity (m =2779 protrusion events from n = 5 cellstracked in three independent experiments)in cells treated with DMSO (blue) or MEKinhibitor (red) at protrusion initiation (B),point of maximum velocity (C), power phase(~20 s after maximal protrusion velocity)(D), and protrusion end (E). GFP intensity

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at the cell edge (within 0 to 0.5 mm) was normalized to intensity in the lamella (3 to 3.5 mm). Shaded areas indicate 95% confidence intervals. (F)Cross-correlation of Arp2/3 intensity and cell-edge velocity shows reduced correlation and delayed recruitment with MEK inhibitor. (G) Model of the roleof ERK in controlling edge protrusion. After protrusion initiation, ERK controls an intensity rheostat of WAVE regulatory complex (WRC) activation andArp2/3 recruitment to induce actin polymerization power for sustained events.

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ARPC2 localization to the cell edge (fig. S6, A, B, and E). We proposethat in cells with ERK inhibition, reduced Arp2/3 recruitment led to a lossof correlation between actin and edge dynamics during protrusion.

Cross-correlation of GFP-Arp3 intensity with edge velocity duringprotrusion events showed two peaks in Arp2/3 recruitment (Fig. 4F). Thefirst peak indicated that a pool of Arp2/3 was recruited to the cell edge atthe same time as the peak in edge protrusion velocity. The second peakindicated that a second, weakly correlated pool of Arp2/3 was recruited 20 slater, which coincided with the peak in actin polymerization rates. Thetiming of the second Arp2/3 peak might depend upon the first. In addi-tion, we expect that both of these pools of Arp2/3 contribute to the peak inactin assembly in the power phase.

In cells treated with the MEK inhibitor, the peak in Arp2/3 correlationwas delayed by 20 s (Fig. 4F). A smaller peak coincided with the peak inedge protrusion, a finding that indicated that recruitment of Arp2/3 to thecell edge took longer when ERK was inhibited. Furthermore, the first poolof Arp2/3 that was recruited at the same time as the increase in protrusionvelocity was less correlated with edge motion than in uninhibited cells(cross-correlation score was 0.2 in control cells and 0.1 with AZD6244treatment). The residual Arp2/3 that was recruited during the shortened,weakened power phase was slightly more correlated with edge motionthan the power phase peak in uninhibited cells. This could be explainedby the homogenization of protrusion behavior under MEK inhibition. Un-inhibited cells had a wide range of protrusion behavior, ranging fromslower protrusions that lack a “power” phase to faster, longer protrusionswith substantial power phases. In cells treated with the MEK inhibitor, thedistribution collapsed to a uniform protrusion cycle of weakened, shortprotrusions. In conclusion, ERK regulated both the extent and the corre-lation of Arp2/3 recruitment to edge motion.

DISCUSSION

Here, we have deduced the mechanisms by which the ERK signalingpathway altered the protrusion and retraction cycles to promote productivemigration. We found that the ERK pathway was not essential for protru-sion initiation but rather promoted protrusion reinforcement by Arp2/3-mediated actin polymerization. We uncovered this mechanistic insightby cross-correlating signaling readouts with the mechanical processes ofsteady-state cell migration in defined protrusion and retraction events.

Phospholipids and locally activated Rac recruit and basally activate theWAVE regulatory complex, which activates Arp2/3 (10–12). Arp2/3 nu-cleates actin dendritic branches to accelerate membrane protrusion. Mean-while, a positive feedback loop between Rac and the actin cytoskeletonrecruits more Rac, WAVE regulatory complex, and basally active Arp2/3(15, 47). We have previously found that peak Rac recruitment occurs20 s after protrusion initiation (48), which corresponds to our finding herethat actin polymerization peaked 20 s after protrusion initiation. Yet, wealso found here that a relatively small percentage of protrusion events were“stabilized” with increased protrusion velocity and duration to compel celldisplacement. We propose that in these events, ERK localized to the celledge phosphorylates and activates the WAVE regulatory complex for fur-ther Arp2/3 recruitment and activation (Fig. 4G) (25). This effect generatesthe actin polymerization power needed to overcome increasing membranetension and to augment protrusion velocity and persistence (Fig. 3F) (14).We speculate that the role of ERK-mediated enhancement of actin polym-erization may be more important in three-dimensional migration, a processin which protrusion events tend to experience resistance from the sur-rounding matrix in addition to membrane tension.

We have previously found that upon growth factor stimulation, activeERK colocalizes with WAVE2 at the cell edge at the time of active pro-

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trusion but does not control WAVE2 localization (25). Here, we found thatin steady-state migrating cells, active ERK was distributed throughout thecell edge and cytoplasm. These results are consistent with the diffuse cy-toplasmic localization of active ERK in migrating epithelial sheets (20).Thus, growth factor stimulation induces active ERK to transiently accu-mulate at the cell edge before moving to the nucleus, whereas steady-stateconditions maintain low levels of active ERK localized at the cell edge andthroughout the cell (18, 25, 49–51). Our finding that ERK regulated Arp2/3recruitment is consistent with our previous study showing that ERK-mediated phosphorylation of WAVE2 and of Abi1 controls the ability ofArp2/3 to interact with the WAVE regulatory complex (25). We proposethat ERK signaling to the WAVE regulatory complex and Arp2/3 modulatesan intensity rheostat of actin polymerization to increase the volume of tread-milling branched actin at the cell edge. In the setting of oncogenic BrafV600E

or an influx of growth factor signals, a global increase in ERK activity willlead to an increase in cell edge–localized active ERK. In this model, thepresence of active ERK at the cell edge when Rac and theWAVE regulatorycomplex are recruited would increase the WAVE-mediated recruitment ofArp2/3 and the likelihood that protrusions are stabilized into productive,persistent events that generate motility. In this manner, the WAVE regulatorycomplex functions as a coincidence detector for ERK and Rac signals torecruit sufficient Arp2/3 for protrusion power.

Our finding that inhibition of a central signaling pathway duringsteady-state motility causes specific effects on protrusion mechanics suggeststhat protrusion is controlled by multiple, overlapping points of regulationby additional pathways. Indeed, when these other regulatory pathways aresuppressed by starvation, ERK inhibition completely blocks EGF-inducedprotrusion, including protrusion initiation (25). In the human mammaryepithelial cells used in those experiments, EGF is not expected to activatephosphatidylinositol 3-kinase (PI3K)/Akt, Abl, or Src signaling (32),which also participate in WAVE activation, or Rho GTPases, which acti-vate the formin family of actin nucleators and elongators (52). In that lessphysiological situation involving serum starvation and EGF stimulation,ERK signaling drives protrusion. We found here that in log-phase migrat-ing cells, steady-state ERK signaling specifically regulated protrusion re-inforcement. We observed migration defects upon MEK inhibition invarious cancer cell lines, and embryonic ERK inhibition causes neural crestcell migration defects that result in craniofacial and heart abnormalities(53, 54). However, the weak, short protrusions that remain after ERK in-hibition may be sufficient for motility in some cell types and environ-ments. For example, Arp2/3-deficient fibroblasts lack lamellipodia andundergo filopodia-based protrusion with reduced migration speed (55).

In conclusion, this work elucidates the role of ERK’s direct activity onthe actin polymerization machinery: to reinforce the progression of ini-tiated protrusions into rapid, sustained forward motion of the leading edge.ERK-mediated control occurs specifically in protrusion events, not retractions,and involves the recruitment of Arp2/3 for actin polymerization and treadmill-ing at the cell edge. This point of regulation explains the previously predictedand observed timing sequence in which actin assembly peaks after protru-sion onset and after maximal protrusion velocity is reached (14).

MATERIALS AND METHODS

Cell culture, imaging medium, and inhibitor treatmentPanc1, MDA-MB-468, Sk-Mel-28, and A375 cells were cultured and im-aged in Dulbecco’s modified Eagle’s medium with 10% fetal bovine ser-um (FBS), 20 mM Hepes. PtK1 cells were cultured in F-12 with 10% FBSand imaged in L-15 with 10% FBS, 20 mM Hepes. AZD6244 (5 mM) wasused for all treatments.

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Migration and wound-healing assayCells were plated in their normal growth medium on glass-bottomeddishes 2 days before assay. Cells were treated with DMSO or AZD6244and then immediately imaged with phase contrast at 37°C, 5% CO2 usinga Nikon Ti inverted microscope with perfect focus, Prior ProScan motor-ized stage, and incubation chamber. Images were collected every 10 minwith MetaMorph software for 12 hours. For migration assay, displacementor the distance migrated over a 6-hour period was calculated using theTrack Points function in MetaMorph. To ensure that bias was not intro-duced into the analysis, every cell that did not divide or move out of thefield of view over the 6-hour period was tracked. The results were ob-tained from three independent experiments. Normality was assessed usingthe Anderson-Darling test in Matlab. The data were not normally distrib-uted. Therefore, the permutation test was used to calculate statistical sig-nificance of changes in the distributions. Error bars about the median wereestimated from the 95% confidence interval of the bootstrapped mediandistribution.

For wound healing, cells were treated with DMSO or AZD6244 im-mediately after wound scratching. Start and end points of assay were 0 and11 hours after scratching, respectively. Results were obtained from twoindependent experiments. Wounds in which the edge did not uniformlymigrate were excluded (for example, when only part of the edge migratedor the wound closed from opposite or different part of edge). To avoidissues with the unequal sample size causing type I error inflation (56),we used the Wilcoxon rank sum test to assess the significance of thedifference between the control and treated sample medians.

LifeAct imaging and image processingPtK1 cells were electroporated with Emerald GFP–tagged LifeAct usingthe Neon transfection system and plated on acid-treated glass coverslips.Cells were cultured for 48 hours at 37°C, 5% CO2 and imaged using aNikon Ti motorized inverted microscope with Perfect Focus System,Yokogawa CSU-X1 spinning disc confocal and Spectral Applied ResearchBorealis modification, 491 solid-state laser, 100x 1.45 numerical aperture(NA) objective, Hamamatsu ORCA-AG cooled charge-coupled device(CCD) camera, and MetaMorph software. Cells were in L-15 mediumcontaining 10% FBS, 20 mM Hepes, and Oxyrase (0.03 U/ml). Experi-ments using U0126 were carried out using a Nikon TE2000 inverted mi-croscope with Perfect Focus System, Yokogawa CSU-10 spinning discconfocal, 488 solid-state laser, 60x 1.4 NA objective, Andor Clara cooledCCD camera, and NIS Elements software.

Cells were imaged for 10 min before perturbation and 20 min afterperturbation (30 min total). PtK1 cell boundaries were detected fromthe fluorescence microscopy data using a threshold method. Once identi-fied, the edge was then subdivided into 1-mm-long segments, and theirrespective velocities were calculated as described previously (25). Forinhibitor-treated experiments, results were obtained from three to fourindependent experiments. For BrafV600E overexpression experiments,results were obtained from two independent experiments.

Edge velocity analysisThe velocity traces for each segment were processed using a signal detec-tion algorithm on the basis of empirical mode decomposition (57). Veloc-ities within the noise level were classified as insignificant and the respectiveedge segment as inactive. Once a significant event was detected, it wasclassified as either protrusion or retraction, and the mean and maximumvalues were extracted. The event duration was also measured. The Anderson-Darling test indicated that the distributions were not Gaussian. Rather, pro-trusion and retraction velocities followed a log-normal distribution, whichsuggested the use of the median value instead of mean for comparisons

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among different experimental conditions. The median error bars were es-timated from the 95% confidence interval of the bootstrapped mediandistribution.

Protrusion and retraction velocity data exhibited log-normal distribu-tions. We applied the Anderson-Darling test to confirm that the velocityand persistence time for all cells in each protrusion and retraction treat-ment group came from the same distribution, indicating that they wererepresentative for the same general cell population. The fast and slow,long, and short events were confirmed to be equally distributed amongthe different cells in all conditions. The permutation test was used to cal-culate statistical significance of changes in the distributions of the meanvelocity and persistence time for the different conditions.

Actin qFSMActin microinjection, imaging, and qFSM analysis were carried out as de-scribed previously (38). Cells were microinjected with Alexa-568 actinmonomers (Molecular Probes) using a Sutter microinjection system. Briefly,cells were allowed to recover for 30 min and were then imaged in L-15medium with 10% FBS in a 37°C, 5% CO2 incubation chamber on aNikon Ti motorized inverted microscope with Perfect Focus and YokogawaCSU-X1 spinning disc confocal with a Spectral Applied Research Borealismodification. Images were acquired every 10 s using a 561-nm (200-mW)solid-state laser excitation and a Hamamatsu ORCA-AG cooled CCDcamera controlled by MetaMorph image acquisition software. The actinspeckles provided enough out-of-focus light for computational detectionof the cell edge and the partitioning of cell-edge segments and associatedprobing windows. Steady-state actin flow maps depict the raw speckle dis-placements spatially averaged in 0.7-mm regions and temporally averagedover 4 min.

We identified and tracked >103 speckles per FSM movie. The auto-correlation function of the PtK1 cell-edge dynamics was six frames (60 s).Correlation-based flow tracking revealed the raw speckle displacementsspatially averaged in 0.7-mm regions and temporally integrated over 40 s.We then used these flow templates to track the individual speckles andperformed statistical processing of the speckle intensity fluctuations tomap F-actin flow and assembly and disassembly (kinetics). We averaged9 frames for steady-state flow analysis and 55 frames for kinetic maps.Average flow at the cell edge varied between 400 and 1000 nm/min be-tween cells, likely because of variability in the fraction of protruding andretracting cell edge and in the protrusion velocity during the captured timeseries. Reduced flow upon MEK inhibition was reproduced in n = 5 cells,obtained from four independent experiments.

GFP-Arp3 analysisPtK1 cells were infected with retrovirus carrying pBabeNeo-GFP-Arp3and selected with G418. Cells were imaged by Yokogawa CSU-X1spinning disc confocal with Spectral Applied Research Borealis modifica-tion, in L-15 medium containing 20 mM Hepes and Oxyrase (0.03 U/ml),with a 100× 1.45 NA objective and a Hamamatsu R2 camera with 2 x 2binning.

Cells were segmented using a thresholding method, and the Arp2/3fluorescence intensity was then averaged in 0.5-mm-thick bands parallelto the cell edge at increasing distances from the cell edge. To handle thevariability of fluorescence intensity among cells, we normalized the averageof each band by the average of the band 3 mm away from the cell edge. Thisnormalization allowed us to average the signal from multiple cells withoutintroducing artifacts from cells with too high or too low intensities. The finalconfidence interval was calculated by propagating the error from the nor-malized mean calculated for each cell. Images were obtained from threeindependent experiments.

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ImmunofluorescencePtK1 cells were grown on glass coverslips for 48 hours and fixed with3.7% formaldehyde with 10 nM calyculin A in phosphate-buffered saline(137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, 1 mM KH2PO4, pH 7).Cells were permeabilized and blocked with 0.2% Triton and 3% bovineserum albumin (BSA). Cells were stained with purified mouse monoclonalanti–phospho-ERK (Sigma), rabbit anti-ARPC2 (Millipore), and phalloidin-647 (Molecular Probes) in 1% BSA, 0.2% Tween 20 in tris-buffered saline.Images were acquired on a Nikon Ti motorized inverted microscope withYokogawa CSU-X1 spinning disc confocal, using 405-, 488-, 561-, and647-nm solid-state laser excitation and an Andor Clara cooled CCD cameracontrolled by Nikon Elements image acquisition software.

Cells were segmented by thresholding in the phalloidin-647 channel.Because the peak Arp2/3 fluorescence was in front of the phalloidin signal,the segmented masks were then dilated out 0.5 mm from the edge. Thesedilated masks were then applied to the 488 and 568 channels, and the sig-nal intensities were integrated over the cell area (mask). The ARP2C-568fluorescence intensity was further averaged in a 1-mm-thick band parallelto the cell edge (0.5 to 0.5 mm), and the percentage of total signal presentin this band was averaged for each group. The SEM and 95% confidenceinterval were graphed.

Cross-correlationCross-correlation analysis can indicate relationships and timing betweentwo events (58). As previously described, correlation scores between theedge motion and sampled signals (for example, Arp3 intensity) werecalculated for each window of the cell edge for all cells and then averagedusing bootstrap and a variance stabilization method (58). Cross-correlationscores were graphed in the y axis, with the score value indicating how wellthe two activities were correlated with a specific time lag (x axis) betweenthem. The uncertainty on each correlation value was defined as the 95%confidence interval of the bootstrapped distribution at each time lag.

In silico experimentsWe performed in silico experiments to confirm the artificial shift on thepositive correlation peak between edge motion and retrograde flow. Timeseries for both variables were generated using a periodic sawtooth wave-form with added Gaussian noise (signal to noise = 2). These waves had180° phase difference, and a Gaussian random sequence of one quarter ofthe period was introduced between the peaks for the synthetic retrogradeflow. A thousand replicas of both time series were generated, and the cor-relation scores were calculated as described above. Then, the correlationscores were separately recalculated for the negative and positive compo-nent of the edge motion.

SUPPLEMENTARY MATERIALSwww.sciencesignaling.org/cgi/content/full/8/377/ra47/DC1Fig. S1. ERK inhibition in PtK1 cells.Fig. S2. ERK hyperactivation increases protrusion velocity.Fig. S3. ERK increases retraction velocity.Fig. S4. ERK promotes peak membrane protrusion velocity and persistence time in PtK1cells microinjected with Alexa-568 actin monomers.Fig. S5. Simulation of cross-correlation of actin retrograde flow with cell-edge velocity.Fig. S6. ERK regulates Arp2/3 localization to the cell edge.Table S1. Event velocity averages.Movie S1. Spontaneous protrusion and retraction cycles.Movie S2. MEK inhibition dampens spontaneous edge motion.Movie S3. Edge motion analysis.Movie S4. Analysis of spontaneous edge motion upon MEK inhibition.Movie S5. Actin speckles.Movie S6. Actin speckles with MEK inhibition.Movie S7. Flow tracking of actin qFSM.Movie S8. Actin flow under MEK inhibition.

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Acknowledgments: We thank the Nikon Imaging Center at Harvard Medical School andT. Wittman and A. Sil at the University of California, San Francisco, for help with lightmicroscopy. Funding: This work was funded by NIH grants K01 CA168850 to M.C.M.,F32 GM103278 to M.V., R01 GM071868 and U01 GM068230 to G.D., and R01CA046595 to J.B. Author contributions: The project was conceived by M.C.M. and J.B.The research design was regularly adjusted in discussions between M.C.M., M.V., and G.D.M.C.M. performed all live-cell imaging experiments, Western blotting for the AZD6244 treat-ments, and routine data analysis using speckle analysis software. J.E.J. performed theWesternblotting for the U0126 treatments and the ARPC2 immunofluorescence. M.V. extended thespeckle analysis software, wrote new programs for correlation analysis, and, together withM.C.M., interpreted the results in the context of the proposed model. M.C.M. and M.V. jointlyprepared the figures. M.C.M. drafted the manuscript. All authors contributed to the final edit-ing. Competing interests: The authors declare that they have no competing interests.

Submitted 9 February 2015Accepted 30 April 2015Final Publication 19 May 201510.1126/scisignal.aaa8859Citation: M. C. Mendoza, M. Vilela, J. E. Juarez, J. Blenis, G. Danuser, ERK reinforcesactin polymerization to power persistent edge protrusion during motility. Sci. Signal. 8,ra47 (2015).

ww.SCIENCESIGNALING.org 19 May 2015 Vol 8 Issue 377 ra47 10

ERK reinforces actin polymerization to power persistent edge protrusion during motilityMichelle C. Mendoza, Marco Vilela, Jesus E. Juarez, John Blenis and Gaudenz Danuser

DOI: 10.1126/scisignal.aaa8859 (377), ra47.8Sci. Signal. 

activated by many cell surface receptors, can link extracellular signals to changes in cellular motility.polymerization that reinforced the leading edge to enable moving cells to sustain forward movement. Thus, ERK, which isleading edge in cells treated with an inhibitor of the kinase ERK. They found that ERK signaling enhanced the actin

tracked and temporally correlated actin polymerization with subcellular movements of theet al.cells forward. Mendoza during cancer metastasis. Motile cells become polarized, and the front or leading edge provides propulsion to move the

Cells move to the correct locations during development, to sites of infection or damage, and to form new tumorsPower to the front

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