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Oscillatory Dynamics of Cdc42 GTPase in the Control of Polarized Growth

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Science  13 Jul 2012:
Vol. 337, Issue 6091, pp. 239-243
DOI: 10.1126/science.1218377

Pole to Pole

How do fission yeast cells decide when to grow at a single end (or pole) of the cell or whether to grow in a multipolar manner? Das et al. (p. 239, published online 17 May) found that accumulation of the active form of the small guanine nucleotide–binding protein Cdc42 at the growing tip of the cell oscillated with a period of a few minutes. In cells growing at one pole, the oscillations were primarily present at that pole and during bipolar growth symmetrical anticorrelated oscillations were observed. Dynamic competition for Cdc42 between multiple growth zones could represent a flexible mechanism to modulate cell growth asymmetry.

Abstract

Cells promote polarized growth by activation of Rho-family protein Cdc42 at the cell membrane. We combined experiments and modeling to study bipolar growth initiation in fission yeast. Concentrations of a fluorescent marker for active Cdc42, Cdc42 protein, Cdc42-activator Scd1, and scaffold protein Scd2 exhibited anticorrelated fluctuations and oscillations with a 5-minute average period at polarized cell tips. These dynamics indicate competition for active Cdc42 or its regulators and the presence of positive and delayed negative feedbacks. Cdc42 oscillations and spatial distribution were sensitive to the amounts of Cdc42-activator Gef1 and to the activity of Cdc42-dependent kinase Pak1, a negative regulator. Feedbacks regulating Cdc42 oscillations and spatial self-organization appear to provide a flexible mechanism for fission yeast cells to explore polarization states and to control their morphology.

The conserved guanosine triphosphatase (GTPase) Cdc42 establishes cell polarity by regulating the cytoskeletal asymmetry required for normal cell function, differentiation, and motility (1, 2). In budding yeast, Cdc42 breaks the symmetry of spherical cells by clustering in one area of the membrane, the site of bud growth, through a “winner-take-all” positive-feedback mechanism (36). However, such a mechanism cannot explain how multiple growing zones form simultaneously in other cells. Fission yeast cells initially grow in a monopolar fashion, from the tip that existed before division (the old end), and activate bipolar growth that includes the new end as well, once a minimal cell length has been achieved [“new end take off” (NETO)] (7). Fission yeast is thus an ideal system to study how Cdc42 is distributed at multiple sites.

To characterize Cdc42 during the transition to bipolar growth, we used a fluorescent fusion protein [Cdc42/Rac interactive binding peptide–green fluorescent protein (GFP), CRIB-GFP] that binds specifically to activated, guanosine triphosphate (GTP)–bound Cdc42 (8). In larger bipolar cells, CRIB-GFP intensities at cell ends showed out-of-phase oscillations with an average period of 5 min (Fig. 1, A and B; movies S1 and S2, and tables S2 and S3). Oscillations were detectable in more than 50% of cells (table S2), when imaging every 15 s instead of 1 min (Fig. 1C), and in three dimensions (Fig. 1D). The rest of the cells displayed anticorrelated fluctuations without obvious periodicity. For shorter cells, nongrowing ends still had detectable CRIB-GFP fluorescence, albeit at lower intensities than the older, growing ends (fig. S1). The tip intensities still underwent anticorrelated oscillations and fluctuations, but around asymmetric averages, unlike longer cells (table S2).

Fig. 1

Oscillations and fluctuations of CRIB-GFP fluorescence at fission yeast cell tips. (A) CRIB-GFP fluorescence at cell tips in a bipolar cell (2-min intervals). (B) Old (red) and new end (blue) CRIB-GFP intensity in a bipolar cell (1-min intervals). A.U., arbitrary units. (C) As in (B), for 15-s intervals. (D) Three-dimensional reconstruction of confocal Z-stack images of a bipolar cell showing CRIB-GFP at the old and new end (20-s intervals). (E) Old (red) and new end (blue) CRIB-GFP intensity and cell growth at the old (green) and new (purple) ends in a cell undergoing NETO. The cell was 8.3 μm long at time 0. Bar, bottom right: 1 pixel = 0.1 μm. (F) Instantaneous growth rate, binned by CRIB-GFP tip fraction (ratio of intensity at one tip over sum of tip intensities) and tip type (old or new). Error bars indicate SEM. (G) Heat-map of CRIB-GFP tip fraction versus cell length in wild-type cells (smoothed data, n = 653). Note three regions: asymmetric, short cells (I); intermediate-length region with large intensity variations (II); symmetric, longer cells (III).

We visualized fluorescently labeled scaffold protein Scd2, which is proposed to mediate Cdc42 activation by binding to the Cdc42 GEF (guanine nucleotide exchange factor) Scd1 and to Cdc42 (9, 10). Scd2-GFP intensity at the cell tips oscillated and fluctuated much like CRIB-GFP intensity (fig. S2 and table S2), as did Scd1-3xGFP and Cdc42-GFP (fig. S3). Thus, CRIB-GFP oscillations and fluctuations appear to reflect the activated Cdc42 protein complex.

To understand how GTP-Cdc42 levels might influence the NETO transition, we measured instantaneous cell growth rates along with CRIB-GFP intensity in cells undergoing NETO, which occurs in cells longer than 9 μm (7). Intensities at both new and old ends fluctuated strongly over time (Fig. 1E). The instantaneous growth rate was correlated with abundance of CRIB-GFP at both old and new ends; cell tips with a CRIB-GFP tip fraction below 0.2 grew slower than tips with the fraction above 0.2 (Fig. 1F). Varied degrees of asymmetry were also observed at intermediate lengths in a population of asynchronous cells (Fig. 1G, region II). These findings indicate that NETO is a noisy transition driven by GTP-Cdc42 redistribution.

To determine the essential requirements for the transition from oscillating monopolar (asymmetric) to oscillating bipolar (symmetric) states during cell elongation, we developed a coarse-grained mathematical model (Fig. 2A) (1114). Instead of describing specific molecular interactions, we took into consideration several experimental observations to predict system behavior. We assumed that tips compete for Cdc42 or its effectors and regulators, on the basis of observed GTP-Cdc42 anticorrelations. We also assumed that positive and delayed negative feedbacks combine to generate oscillations, as they do in the bacterial Min system (15). We added noise to represent random concentration fluctuations and to capture the observed variability (fig. S4A). The model reproduced the observed time courses: dominant-tip oscillations in short cells (with anticorrelated lagging tip) and out-of-phase oscillations at both tips in long cells (Fig. 2B). Allowing different rate constants at the two tips caused them to oscillate around slightly different averages, as observed in many cells (fig. S4B). The model also predicted varied Cdc42 asymmetry in cells with similar length (Fig. 2C, “coexistence region”; and fig. S5), as in Fig. 1G.

Fig. 2

Test of mathematical model describing Cdc42 oscillations. (A) Model schematic showing GTP-Cdc42 distribution between tips and the cytoplasm, autocatalytic amplification (green), and delayed dissociation (red). (B) Simulation showing GTP-Cdc42 fraction at each tip as cell progresses from monopolar to bipolar growth. (C) Model predicts three regions similar to Fig. 1G. Asymmetric states (I); “coexistence” of symmetric and asymmetric states (II); symmetric states (III). (D) CRIB-GFP in wild-type, gef1∆, cdc25-22 at the permissive temperature (25°C), and Gef1-overexpressing nmt1-gef1 [+thiamine, in YE medium, which contains dextrose (30 mg/ml) and yeast extract (5 mg/ml)] cells. Scale bar, 5 μm. (E) CRIB-GFP tip intensities, in a gef1∆ cell (1-min intervals). (F) CRIB-GFP tip fractions versus cell length, in gef1Δ cells (as in Fig. 1G, n = 381). (G) CRIB-GFP tip intensities, in a cdc25-22 cell at 25°C. (H) Anticorrelation of CRIB-GFP tip intensities decreases with respect to wild-type cells and with increasing cell length in cdc25-22 mutants (*P = 0.03, ***P = 0.00039, Student’s t test). (I) CRIB-GFP tip intensities of cell moderately overexpressing Gef1 (+thiamine, in YE medium). (J) CRIB-GFP tip anticorrelation decreases in cells moderately overexpressing Gef1 (***P = 5.7 × 10−6, Student’s t test). Whiskers in (H) and (J) indicate the full range of data.

According to the mathematical model, changes in abundance or activity of Cdc42, or of its regulators, can shift the system to more asymmetric or symmetric states. It indicated that cells with a lower rate of Cdc42 activation (or decreased total amounts of GTP-Cdc42 or Cdc42 GEFs), favor asymmetric states, because the lagging tip is influenced more severely by the accumulation of GTP-Cdc42 at the dominant tip and by the resulting depletion of the cytoplasmic pool (figs. S5A and S6A). To test this, we analyzed CRIB-GFP in gef1∆ cells, which lack one of the two Cdc42 GEFs and thus exhibit decreased amounts of global active GTP-Cdc42 (16) but otherwise grow at a normal rate (table S5). Most (75%; n = 12) gef1∆ cells had lower amounts of CRIB-GFP at the new tips in time-lapse recordings (Fig. 2, D and E; and movie S3). CRIB-GFP tip fractions in gef1∆ cells (n = 381) were asymmetric (Fig. 2F), consistent with the model.

In our model, increasing cell size increases the total amount of active Cdc42 or of Cdc42 GEFs. In the presence of noise, this is predicted to decouple oscillations, because one tip can no longer deplete the pool available to the other. Thus, we studied cdc25-22 cells that delay entry into mitosis, owing to a mutation in a cell-cycle control gene, and become longer than wild-type cells at permissive temperatures (17). Consistent with this prediction, we found less anticorrelation between CRIB-GFP tip signals in longer cdc25-22 cells (Fig. 2, D, G, and H; and table S3).

To test if Cdc42 GEF availability influences the anticorrelation of Cdc42 oscillations, we overexpressed Gef1. This eliminated the anticorrelation of CRIB-GFP signal at the cell tips (Fig. 2, I and J; and movie S4). Increased amounts of Gef1 also led to increased symmetry of CRIB-GFP and Cdc42-target formin For3 (18) (Fig. 2, D and I; and fig. S6, B, C, and D). This agrees with the model, which predicts that increasing Cdc42 activation rate (or total amounts of active Cdc42 or Cdc42 GEFs) (fig. S6A) leads to more symmetrical GTP-Cdc42 distribution.

Autocatalytic activation within the Cdc42 complex (9, 10, 19, 20) and actin-mediated transport (21) are likely contributors to positive feedback, as in budding yeast (36). Much less is known about negative feedback (22), a required mechanism for oscillations. To identify possible mechanisms, we analyzed CRIB-GFP in morphological mutants (fig. S7, A and B), including orb2-34 and tea1∆, which are monopolar (23, 24); rdi1∆ (encoding the Rho guanine nucleotide dissociation inhibitor); and rga4∆ (encoding the only known Cdc42 GTPase-activating protein) (8, 25). orb2-34 mutants oscillated asymmetrically, but with a longer period and a decreased amplitude of CRIB-GFP oscillations (table S2 and Fig. 3, A and B). Conversely, rdi1∆ and rga4∆ mutants displayed normal, mostly symmetrical oscillations; tea1∆ mutants fluctuated asymmetrically (fig. S7C).

Fig. 3

Negative regulation of Cdc42 by the kinase Pak1. (A) Fluorescence of CRIB-GFP in orb2-34 (pak1/shk1 mutant allele) cells (25°C) at growing cell tip (2-min intervals). (B) CRIB-GFP fluorescence at growing (red) and nongrowing (blue) tips in an orb2-34 cell (1-min intervals). (C) Scd1-GFP, in wild-type and orb2-34 cells visualized in the same field. (D) Scd2-GFP, in wild-type and orb2-34 cells visualized in the same field. (E) Scd2-GFP tip intensity in wild-type (old end, total) and orb2-34 mutant cells (growing end, total) visualized in the same field (***P < 0.0001, Student’s t test). Error bars indicate SD. (F) Recovery following mild LatA treatment (10 μM, 10 min) in wild-type and orb2-34 cells. Both show symmetric (thin arrows) and transiently ectopic (wide arrows) CRIB-GFP after treatment. orb2-34 mutants progressively revert to monopolar distribution (arrow heads). Scale bar, 5 μm.

Amounts of CRIB-GFP, Cdc42 GEF Scd1-GFP, and scaffold Scd2-GFP at the one growing tip of orb2-34 cells were increased compared with the same complexes in control cells (Fig. 3, C, D, and E; and fig. S8, A and B). No localization change was seen for Gef1-3xYFP (yellow fluorescent protein) or Rga4-GFP (fig. S8C) (8). The intensity of Scd2-GFP signal (Fig. 3E) or Scd1-GFP at the growing tip in orb2-34 cells roughly equaled the total fluorescence at both tips (new end plus old end) in control cells (Fig. 3E). Amounts of total protein were not changed (fig. S7D). Thus, orb2 regulates intracellular distribution of Scd1 and Scd2. In the model, this behavior is expected when the maximal active Cdc42 allowable at each tip increases (fig. S8E). In mutant cells unable to suppress maximal tip accumulation, the growing tip could function as a “sink,” entrapping Scd1 and Scd2.

To confirm that orb2-34 mutants remain monopolar because of their inability to redistribute Scd1, Scd2, or other regulators, we destabilized the actin-dependent (21) localization of Scd1 by exposing cells for 10 min to latrunculin A (LatA). In orb2-34 and wild-type cells, CRIB-GFP, Scd1-GFP, and Scd2-GFP became symmetric in the first hour after LatA removal (Fig. 3F and fig. S9), consistent with reports of brief actin depolymerization promoting bipolar growth in monopolar cells cdc10ts and ssp1∆ (13, 26). However, 90 min after LatA removal, orb2-34 cells reaccumulated these markers at one tip, which could be different than the tip originally growing, whereas wild-type cells remained largely symmetric (Fig. 3F and fig. S9). This agrees with the model’s prediction of lack of a symmetric attractor for cells with reduced negative feedback and convergence to a symmetric attractor for wild-type cells after a perturbation (fig. S4A).

orb2-34, a mutant allele of pak1 (also known as shk1) (23) contains a point mutation [Glu replaces Gly517 (G517E); see (12)] in the Pak1 kinase domain that decreases its activity (fig. S7, E and F). Pak1, a Cdc42-dependent kinase (27, 28), localizes to tips in an Scd1 and Scd2-dependent manner (21). Negative regulation of Cdc42 could thus be linked to its own activation, as expected from a negative-feedback loop. It might occur through Scd2, a substrate of Pak1 (20), consistent with findings in Saccharomyces cerevisiae, where the Pak1 homolog Cla4 negatively regulates the interaction of the scaffold protein Bem1, an Scd2 homolog with Cdc42 GEF Cdc24 (29).

Increased accumulation of Cdc42 GEFs at the membrane, by Gef1 overexpression or loss of negative inhibition (orb2-34 mutants), dampens Cdc42 fluctuations (fig. S10A). These mutants are wider, possibly because increasing tip-bound Cdc42 results in growth over a wider area (16) (fig. S10, B and C). We suggest that wild-type cells regulate diameter by maintaining Cdc42 activity at the tips within a normal range and activate bipolar growth by Cdc42 redistribution (Fig. 4A). Oscillations and fluctuations may regulate cell morphology and help the switch to bipolar growth. Before NETO, accumulation of Cdc42 at the old end provides a kinetic barrier to bipolar symmetry by depleting the resources available to the new end. Oscillations and fluctuations may relieve this depletion, giving the new end a chance to take off by allowing the system to reach an otherwise inaccessible state of bipolarity (figs. S11 and S12). Mutations affecting Cdc42 regulation may alter the system’s dynamics, by promoting a different pattern of Cdc42 distribution and changing cell diameter and symmetry (Fig. 4B).

Fig. 4

Model of self-organization of Cdc42 at the cell tips and control of cell morphogenesis. (A) In wild-type cells, Cdc42 recruitment or activation balances Cdc42 removal or deactivation, limiting GTP-Cdc42 tip level and thus setting cell diameter at a normal range. Increased GEF availability promotes bipolar Cdc42 activation at the new cell tip as cell size increases. (B) Changes in the system’s dynamics alter Cdc42 distribution. Decreased Cdc42 activation (gef1∆ mutants) increases Cdc42 asymmetry and decreased cell diameter. GEF overexpression increases Cdc42 activation at both tips, which leads to increased diameter. Decreased negative feedback (orb2-34 mutants) leads to the accumulation of most Cdc42 activity at one single tip and results in monopolar growth. Increased active Cdc42 levels at the growing end results in increased cell diameter.

Fission yeast Cdc42 oscillations and fluctuations might represent exploratory behavior, a general strategy among self-organizing biological systems (30). Despite the associated energy cost, biological systems may benefit because they acquire the ability to quickly reach states that would otherwise be difficult to access. Fluctuations of Cdc42 activity allows fission yeast to rapidly respond to changing intracellular conditions, such as cell volume and length. In an environment with changing external cues, such as nutrient or pheromone gradients, Rho GTPase fluctuations may allow eukaryotic cells to adapt and redirect the direction of growth.

Supplementary Materials

www.sciencemag.org/cgi/content/full/science.1218377/DC1

Materials and Methods

Supplementary Text

Figs. S1 to S12

Tables S1 to S4

References (31–51)

Movies S1 to S4

References and Notes

  1. The model [see (12)] has two populations of Cdc42 associated with each tip, Ctip1 and Ctip2, and one in the cytoplasm, Ccyto. We assumed competition for Cdc42 but similar results are obtained for Cdc42 GEFs or GTP-Cdc42. The total amount, CtotCtip1 + Ctip2 + Ccyto, increases in proportion to cell volume V. Association to the tips obeys Embedded Image, j = 1, 2. Here, λ+ and k represent rate constants; V is the cell volume. Autocatalytic activation, Embedded Image, with n ≥ 2, generates asymmetry by allowing one tip to deplete the cytoplasmic pool and preventing the other tip from gathering Cdc42. Saturation at level Csat recovers bipolarity for long cells. Oscillations result by assuming Cdc42 triggers its own removal (delayed negative feedback): Embedded Image. Here, Embedded Image determines the delayed dissociation strength, Embedded Image is delay time, and h gives the nonlinearity of the effect.
  2. Materials and methods are available as supplementary materials on Science Online.
  3. Acknowledgments: We thank E. Karsenti, C. Luetje, S. Lemmon, G. D’Urso, and T. K. Harris for critically reading the manuscript; M. Ioannidou and K. Zhang for help with data analysis; B. Skibbens and Yi Hu for facilitating experiments; and K. Shiozaki, P. Perez, and S. Martin for various strains. This work was supported by NSF grant 0745129, NIH grant 1R01GM095867, and a University of Miami NSF ADVANCE award 0820128 to F.V., and by NIH grant R21GM083928 and a Lehigh University Class of 68 Faculty Fellowship to D.V. T.D. was supported by a Sigma Xi grant-in-aid and as a Graduate Assistance in Areas of National Need Fellow through the U.S. Department of Education.
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