cross-talk and decision making in map kinase pathways

Cross-talk and decision making in MAP kinase pathwaysMegan N McClean1,2, Areez Mody1, James R Broach3 & Sharad Ramanathan1,4

Cells must respond specifically to different environmentalstimuli in order to survive. The signal transduction pathwaysinvolved in sensing these stimuli often share the same orhomologous proteins. Despite potential cross-wiring, cellsshow specificity of response. We show, through modeling,that the physiological response of such pathways exposed tosimultaneous and temporally ordered inputs can demonstratesystem-level mechanisms by which pathways achievespecificity. We apply these results to the hyperosmolar andpheromone mitogen-activated protein (MAP) kinase pathwaysin the yeast Saccharomyces cerevisiae. These two pathwaysspecifically sense osmolar and pheromone signals1–3, despitesharing a MAPKKK, Ste11, and having homologous MAPKs(Fus3 and Hog1). We show that in a single cell, the pathwaysare bistable over a range of inputs, and the cell responds toonly one stimulus even when exposed to both. Our resultsimply that these pathways achieve specificity by filteringout spurious cross-talk through mutual inhibition. The variabilitybetween cells allows for heterogeneity of the decisions.

Although components shared between pathways provide the signalingnetwork with a capacity for signal integration, they pose a problem:signals transmitted through one pathway could cross-activate theother through these shared components, leading to a loss of specificity.The signaling network must be able to overcome this problem in orderfor the cell to respond faithfully to external stimuli.

Two fundamentally different mechanisms allow signaling pathwaysthat share components to respond specifically to any one stimulus.The first mechanism is insulation4. This can be achieved by incorpor-ating the shared component into distinct macromolecular com-plexes—one for each signal to be processed (Fig. 1a). The secondmechanism is mutual inhibition, which is used to eliminate unwantedinteractions between the pathways (Fig. 1b). Through mathematicalmodeling, we show that we can use physiological measurements todistinguish between these two mechanisms of achieving specificity. Wethen apply our analysis to the specific example of MAPK pathways inthe yeast S. cerevisiae.

We studied two models (Fig. 1a,b), which achieve specificity ofresponse to any one signal by insulation and mutual inhibition,respectively (Box 1). In order for insulation to be effective, compo-

nents of each pathway must be in distinct complexes that must bestable enough to prevent cross-activation. For mutual inhibition to bea viable mechanism for specificity, our calculations indicate thatinhibition should act downstream of the common components andthat its strength should be greater than a critical value (Fig. 1c). Thereshould be a bias in the activation of the right pathway by its signal.Scaffolding proteins can provide such a bias and are known to beimportant for the specificity of MAPK pathways5–11. Our calculationsshow that both reduced levels of inhibiting proteins (SupplementaryFigs. 1–3 online) and, in the absence of feedback and saturation, veryhigh levels of both inputs can destroy the switch. Our analysis allowsus to distinguish between the two models. If two pathways respond toboth signals when exposed to them simultaneously over all of inputspace, specificity must be achieved by insulation. If the pathwaysrespond to only one of the two signals when exposed to both in anyregion of the input space, and if the activated forms of sharedcomponents are not in limiting concentrations, then specificity mustbe achieved by mutual inhibition. Our calculations show that, formutual inhibition, the pathways should be bistable: that is, the outputof the pathways should be bimodal and history dependent. Therefore,this output depends on the order in which the signals are added(Fig. 1d). Furthermore, this bistable, switch-like behavior is elimi-nated if the inhibition of one pathway by the other is lifted. Hence,experimental measurements of the input-output characteristics of twopathways exposed simultaneously to both signals allow us to distin-guish between the two means of achieving specificity. To detectbistability, measurements must be done at the single-cell level, asmeasurements in lysates average the responses over many cells5. Ourstudy of physiological responses complements work on detailedmolecular interactions underlying specificity6–12 by providing amechanism at a system level.

The two MAPK pathways in the yeast S. cerevisiae that sensepheromone and hyperosmolar pressure (Fig. 2) share identical,homologous proteins, yet they respond to their inputs specifically6,7.Components of both these pathways are organized on distinctscaffolding proteins8–11, and in addition, the hyperosmolar pathwayinhibits the pheromone pathway12. These pathways could achievespecificity by either insulation or mutual inhibition, making them agood experimental system on which to apply our analysis. Whereas thepheromone pathway is linear3, the hyperosmolar pathway consists of

Received 14 August 2006; accepted 6 December 2006; published online 28 January; corrected after print 14 March 2007; doi:10.1038/ng1957

1FAS Center for Systems Biology and 2Division of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, USA. 3Department ofMolecular Biology, Princeton University, Princeton, New Jersey 08544, USA. 4Bell Laboratories, Lucent Technologies, Murray Hill, New Jersey 07974, USA.Correspondence should be addressed to S.R. ([email protected]).

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two branches from Sho1 (ref. 7) and Sln1 (refs. 13,14), both of whichconverge on the MAPKK Pbs2. The Sln1 branch is active at modestand high osmolar pressures, whereas the Sho1 branch is active at highosmolar pressures15. One of the component proteins of these twopathways (the MAPKKK Ste11) is identical; the MAPKs in the twopathways, Fus3 and Hog1, are homologous to each other10,12,16.

To measure the input-output characteristics of these two pathways,we used fluorescent proteins as transcriptional reporters. We placedthe green fluorophore gene GFP17 under the control of the nativeFUS1 promoter, which responds strongly and specifically to phero-mone activation18 (Supplementary Fig. 4 online). In the same strain,we inserted the monomeric red fluorescent protein gene mRFP1(ref. 19) under the control of the native STL1 promoter, whichresponds strongly and specifically to exposure of cells to high osmolarpressure20 (Supplementary Fig. 4). GFP expression on pheromoneexposure is abolished when the genes FUS3 and KSS1 are deleted16.The expression of mRFP1 protein on exposure to osmolar pressure is

abolished when HOG1 is deleted (Supplementary Fig. 4). Thus,these reporters specifically monitor the activation states of theirrespective MAPKs.

After our theoretical analysis, we studied the response of cellsstimulated by both signals. We grew cultures of cells to an earlyexponential phase (optical density at 600 nm (OD600) ¼ 0.05) in SCgrowth medium and placed the cells in a perfusion chamber. Wetitrated levels of pheromone and sorbitol to explore if there wereregions of input space where cells showed a switch-like behavior. Weperfused solutions of sorbitol (0.25 M to 1.5 M) and pheromone(10 to 50 ng/ml; that is, 5.9 nM to 29.7 nM) over cells in a perfusionchamber and monitored the GFP and mRFP1 intensities of single cellsunder an epifluorescence microscope for 1 h (see Methods). Underthese conditions, we found that all responding cells expressed eitheronly GFP or only RFP. By titrating the levels of pheromone andsorbitol, we were able to continuously change the proportion of cellsresponding to one signal versus the other (Figs. 3 and 4a,b). Thus, theresponse of the cells was bimodal: cells responded to one stimulus orthe other but not to both at the same time.

To determine if the response was history dependent and hencebistable, we performed the experiment suggested in Figure 1d (andSupplementary Fig. 2), in which the pathways are exposed to the

p2

p1

Signal 1 Signal 2 Signal 1 Signal 2

Sig

nal 2

Signal 10 1 kd

~

ka

~

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ka

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X1 Y1

X2

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Y2

Y3

X1 Y1

X2

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Y2

Y3

a b

c d1

Figure 1 Different mechanisms for achieving specificity of two parallel

signaling pathways yield different responses after exposure to both signals.

(a) Scaffolding proteins insulate two pathways from each other. For perfect

insulation, the rate of cross-activation ka equals 0. When exposed to both

signals simultaneously, both pathways are active. (b) Two pathways show

cross-activation but maintain specificity by cross-inhibition of X3 and Y3.

(c) The behavior of the pathways in b is diagrammed as a function of ~ka(dimensionless strength of cross-activation) and ~kd (dimensionless strength

of mutual inhibition). Yellow region: both pathways respond even when

excited by a single signal owing to bleed-through. In the orange region,

they are bistable and respond to only one of the two signals presented

simultaneously. The two regions are separated by a curve that intersects the~ka axis at ~kd ¼ 1. The strength of the mutual inhibition (~kd ) must be greater

than a critical value for it to be effective. (d) Orange region of c: the

pathways show a bistable switch-like behavior and a memory of past history.The response of the pathways to different levels of costimulation is shown.

In the green and red regions, respectively, they respond to signal 1 or to

signal 2. In the white region, the response depends on prior history. Pathway

1 is predominantly active if a point in this region was reached along path p1

(that is, cells were first stimulated by signal 1 and then by signal 2), but

pathway 2 is predominantly active if it was reached via path p2.

BOX 1 DYNAMICS OF INTERACTING PATHWAYS

To understand how pathway architecture affects the input-output characteristics of two pathways, we created mathematical models (Fig. 1a,b). The model cascades

consist of two three-layer cascades, each consisting of three proteins (X1, X2, X3 and Y1, Y2, Y3). Each protein activates the one immediately downstream of it. The

inputs ‘signal 1’ and ‘signal 2’ activate proteins X1 and Y1, respectively. The cross-activation of X2 by Y1 and of Y2 by X1 occurs with a rate constant ka. Cross-

inhibition between X3 and Y3 occurs with strength kd. The dynamics of the lowest level of these pathways is given by

dX �3

dt¼ X �

2 ðS1; kaS2Þ½XT3 � X �

3 � �kdY

�3X

�3

1+X �3=KM

ð1Þ

and

dY �3

dt¼ Y �

2 ðkaS1;S2Þ½Y T3 � Y �

3 � �kdY

�3X

�3

1+Y �3=KM

ð2Þ

where XT3 and Y T

3 are the total concentrations of X3 and Y3, and X �3 and Y �

3 are the concentrations of their activated form. The activated level of X2, X �2 , is a function of

the strength of signal 1 (S1) and ka S2, the strength of signal 2 (S2) multiplied by the strength of the spurious cross-activation of X2 by Y1 (ka). Similarly, Y �2 is a

function of S2 and ka S1. When ka ¼ 0 and kd ¼ 0, we obtain the model in Figure 1a, with perfect insulation. For the model of mutual inhibition in Figure 1b, we

studied the input-output characteristics as a function of these two parameters (see results in Fig. 1c,d).

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same input conditions achieved through two different paths. Specifi-cally, we exposed cells at OD600 ¼ 0.05 to sorbitol for about 5 minfollowed by simultaneous exposure to both pheromone and sorbitol.We exposed different cells from the same culture to pheromone for5 min followed by simultaneous exposure to both pheromone andsorbitol. We compared the pheromone response of both cultures andfound that fewer cells in the culture with prior exposure to sorbitolresponded to pheromone than did cells in the culture with priorexposure to pheromone, as reflected in their GFP intensities 40 minafter treatment with sorbitol and pheromone (Fig. 4a,b). The orderof addition of stimuli affected the final response; therefore, thepathways show bistable behavior. The pathways behave like a switchthat remembers its state and, once flipped in one direction, needsa higher threshold to be turned to the other. These results areconsistent with mutual inhibition between the pheromone andhyperosmolar pathways.

One caveat to the above conclusion is the possibility that specificityto one signal could be achieved by one pathway titrating outlimiting concentrations of activated forms of shared proteins. If thiswere so, addition of small amounts of the second signal should haveno effect on, or should reduce, the response of the pathways to thefirst signal.

To determine if one of the activated proteins of either pathway wasin limiting concentrations under our experimental conditions, we splita culture of cells in early exponential growth phase (OD600 ¼ 0.05)

into two samples. We exposed one of these to 50 ng/ml (29.7 nM)pheromone alone and the other to 50 ng/ml pheromone plus 0.125 M,0.25 M or 0.5 M sorbitol. Under both these conditions, allcells responded to pheromone, but those exposed to both pheromoneand sorbitol showed higher pheromone response (Fig. 4c). As theaddition of sorbitol increased rather than decreased the response ofcells to pheromone, we conclude that shared components are notrate limiting.

Our models show that if mutual inhibition were responsible for theswitch, lifting of the inhibition of one pathway by the other shouldabolish bistable behavior21 (Supplementary Fig. 2). Activation of thehyperosmolar pathway has previously been shown to inhibit signalingthrough the pheromone pathway, and a mutant form of the MAPKprotein Fus3 has been described, D317G, which resists inhibition by

Pheromone Osmolar shock

Ste2

Ste4/Ste18

Ste20

Ste50

Ste11

Ste7

Fus3

Ste

5

Sho1

Ste20

Ste50

Ste11

Pbs2

Hog1

Sln1

Ypd1

Ssk1

Ssk2/Ssk22

Figure 2 Pheromone and high-osmolarity pathways. Pheromone binding to

a G protein–coupled receptor initiates signaling. Consequent release of

the subunits of the associated G protein (Ste4 and Ste18) stimulates

recruitment of the Ste5 protein to the plasma membrane. Ste5, a scaffold,

binds Ste11 (MAPKKK), Ste7 (MAPKK) and Fus3 (MAPK), whose

sequential activation is initiated by kinase Ste20. Ste5 regulates the activity

of the pheromone pathway27. Activated Fus3 phosphorylates Ste12, leading

to the transcription of genes containing a pheromone responsive element

(PRE) in their promoter. fus1::GFP is a reporter for this pathway’s activity.

The hyperosmolar pathway has two sensors, Sln1 and Sho1. Sln1 activates

the MAPKKKs Ssk2 and Ssk22, eventually exciting MAPKK Pbs2. Sho1

activates Pbs2 through Ste11. Pbs2 functions as a scaffold binding Ste11

and Hog1 (MAPK). Activation of Hog1 leads to a transcriptional response.

stl1::mRFP1 is a transcriptional reporter for pathway activity.

6

4

2

0

0 2 4 6 8 10 12GFP intensity

(relative to unstimulated cells)

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GFP intensity(relative to unstimulated cells)

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)

0 2 4 6 8 10 12

0 2 4 6 8

6

4

2

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8

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2

0

a d

b e

c f

Figure 3 Cells costimulated with sorbitol and pheromone show mutually

exclusive activation of the pheromone and the high-osmolarity response

pathways. (a–f) Exponentially growing cells with reporter constructs as

diagrammed in Figure 2 were exposed simultaneously to 0.25 M sorbitol

and 50 ng/ml (29.7 nM) pheromone (a,d), 0.5 M sorbitol and 50 ng/ml

(29.7 nM) pheromone (b,e) or 1 M sorbitol and 12.5 ng/ml (7.4 nM)

pheromone (c,f) and were examined by fluorescence microscopy 1 h after

exposure. At right are scatter plots of the increase in GFP intensity versusthe increase in mRFP1 fluorescence intensity of B150 cells (relative to

untreated cells), as well as typical images of cells obtained in both the GFP

(green) and mRFP (red) channels. Cells responding to pheromone turn

green; those responding to sorbitol turn red. Increase in fluorescence

intensity at a given emission frequency was computed relative to the mean

autofluorescence of unstimulated cells at that frequency.


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the hyperosmolar pathway22. We exposed cells carrying thisFUS3D317G mutant to sorbitol and pheromone simultaneously. Wefound that these cells did not demonstrate switch-like behavior butthat they showed dual expression of PFUS1-GFP and PSTL1-mRFP1 onexposure to both stimuli (Fig. 5). These findings support the require-ment for mutual inhibition between the pathways for their switch-likebehavior23. We therefore deduce that mutual inhibition between theseMAPK pathways is important for their specific responses.

Our analysis can be applied to complex signaling networks, where acareful measurement of its input-output characteristics after excitationby multiple temporally ordered stimuli allows dissection of its signalprocessing properties and hence the underlying architecture. Ourwork also suggests interesting directions for further research on

these MAPK pathways, emphasizing their mutual inhibition. Previouswork has indeed shown that inactivating mutations of the geneencoding HOG1 result in significant pheromone response on exposureto 1 M sorbitol12, an observation we confirmed in our strain (Fig. 5a).These results suggest that Hog1 or a component downstream of itinhibits the pheromone pathway. Our experiments predict that thepheromone pathway also inhibits the hyperosmolar pathway, asmutual inhibition is required for switch-like behavior. Consistentwith that prediction, we found that fus3Dkss1D cells showed anosmolar response on exposure to high pheromone levels (Fig. 5b).Consistent with previous high-throughput analyses24, we found thatFus3 phosphorylated Hog1 in vitro and that the activation of thepheromone pathway altered the specific pattern of unstimulated Hog1phosphorylation in vivo (data not shown). We also found thatpretreatment of cells with pheromone reduced the level of Hog1phosphorylation induced by subsequent stimulation with sorbitol(Supplementary Fig. 5 online). These results are consistent with theinhibition of Hog1 through direct or indirect interactions with Fus3.

Our work raises the question of why cells stimulated by pheromoneand sorbitol elect to respond to one but not to both. Previous workhas shown that increased internal glycerol blocks zygote formation,suggesting that the mating process is very sensitive to increasedinternal osmotic pressure25. As yeast cells respond to activation ofthe high-osmolarity pathway by increasing internal glycerol concen-trations, yeast cells responding to high osmolarity would not becapable of mating. This observation suggests that a cell presented

1.0

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Pheromone + 1.5 M sorbitol1.5 M sorbitol + Pheromone

Pheromone + 1 M sorbitol1 M sorbitol + Pheromone

50 ng/ml pheromone50 ng/ml pheromone 0.125 M sorbitol50 ng/ml pheromone 0.25 M sorbitol50 ng/ml pheromone 0.5 M sorbitol

80

60

40

20

00 2 4 6

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ls

GFP intensity (relative to unstimulated cells)

a b c

Figure 4 Cells show history dependence in their response to pheromone. (a) Cells from one culture (sampled at OD600 ¼ 0.05) were placed in two channels

of the flow cell. The fluorescent intensities of B100 cells were measured at time zero. Cells in one channel were first exposed to sorbitol for 5 min, followed

by simultaneous exposure to sorbitol and the indicated concentration of pheromone. Cells in the second channel were first exposed to the indicated

concentration of pheromone for 5 min, followed by simultaneous exposure to sorbitol and the indicated concentration of pheromone. Error bars were

obtained from the distribution of the means of half the data set. The fraction of cells that responded to pheromone is shown as a function of pheromone

concentration. At these pheromone levels, cells exposed to pheromone alone showed 100% response. (b) Experiment as in a, repeated with 1 M sorbitol.

(c) Cells attached to a flow cell were treated with 50 ng/ml (29.7 nM) pheromone and sorbitol simultaneously. After 1 h, we measured the increase in each

cell’s fluorescence intensity over that determined before treatment. A histogram of this increase is shown (bin width of 25 fluorescent units).


mR

FP

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f

0 5 10 0 5 10

4

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00 5 10 14

Figure 5 Switch-like signaling behavior depends on pathway cross-

inhibition. (a) YSR20 cells (hog1D PFUS1-GFP PSTL1-mRFP) cells exposed

for 1 h to 1 M sorbitol activate a pheromone response. (b) YSR44 cells

(fus3D kss1D PFUS1–GFP PSTL1-mRFP) exposed to 1 mg/ml (593.8 nM)

pheromone activates an osmolar response. mRFP is localized in the vacuole

in these cells. (c) YSR122 cells (PFUS1-GFP PSTL1-mRFP [FUS3D317G])

exposed simultaneously to both sorbitol and pheromone are shown to

activate both pheromone and osmolar responses. (d–f) Scatter plots of theincrease in GFP fluorescence intensity versus mRFP1 fluorescence intensity

relative to the mean initial intensities of unstimulated cells for YSR122 cells

(PFUS1-GFP PSTL1-mRFP [FUS3D317G]) 1 h after exposure to 0.25 M sorbitol

and 50 ng/ml (29.7 nM) pheromone (d), 0.5 M sorbitol and 50 ng/ml

(29.7 nM) pheromone (e) and 1 M sorbitol and 12.5 ng/ml (7.4 nM)

pheromone (f). These cells show both pheromone and osmolar response,

in contrast to the wild-type cells under the same conditions (Fig. 3a–c).


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with both pheromone and high osmolarity has to choose whether toinitiate a mating response or to increase internal osmolarity. Althoughcells confronted with both stimuli could be hard-wired so that allresponded by mating or all responded by increasing internal osmo-larity, our results suggest that the response is significantly moresophisticated. The signaling pathways are wired so that some cells inthe population initiate the mating response, whereas others initiate theosmotic response. Thus, the population can achieve what individualcells cannot: an osmolarity response on one hand and a matingresponse on the other. We also find computationally that the fila-mentous and pheromone pathways could be bistable (SupplementaryFigs. 6 and 7), suggesting that mutual inhibition might be a generalmechanism of achieving specificity in MAPK pathways.

This conclusion highlights the question of cell-to-cell variability inresponses. Cells with identical genetic endowment show distinctbehaviors in response to a given stimulus, as seen in images wheresome cells respond to pheromone whereas others respond to sorbitol(Fig. 3). The setting of this switch depends on the history of the cell,on its local conditions and on variable protein levels owing tostochastic gene expression (Supplementary Fig. 3), resulting indistinct decisions by each cell. The mechanism that allows for thisvariability may facilitate enhanced survival by allowing identical cellsto pursue different courses in response to a changing environment,exploring a wider behavioral space. Thus, genetically identical yeastcells presented with MAPK stimuli may comprise a collection ofdistinct subpopulations, each with a different expression pattern,behavioral competency and developmental potential.

METHODSModel. The details of the model are described in the Supplementary Methods.

The differential equations were solved analytically as well through simulations

using Mathematica and Matlab.

Yeast strains and plasmids. Yeast strains and plasmids were constructed using

standard molecular biology techniques. We used sigma strains26 that are

commonly used to study MAPK pathways (see Supplementary Methods

for the list of strains used in this study and the details of the strain and

plasmid construction).

Yeast growth conditions. Cells were grown overnight at 30 1C in SC medium,

reinoculated into fresh SC medium and grown at 30 1C for 4–5 h to an OD600

of 0.05 before microscopy. Cells from a 1-ml sample of this culture were

harvested by centrifugation, resuspended in 100 ml SC and sonicated for about

10 s to separate cells. At higher OD, fewer cells responded to pheromone. This

is consistent with our other finding that even short periods of glucose

starvation cause a smaller fraction of cells to respond to pheromones (data

not shown). As much of the variability of the pheromone response depended

on growth conditions, the data points for Figure 4a–c, which show that the

same final conditions were reached through different paths, were gathered on

the same day, with the same culture and with two or more channels in the same

flow chamber. The same frozen stock solution of pheromone was used to the

extent possible (in particular, for Figs. 3 and 5) to avoid variability in the

pheromone quality between lots.

Perfusion chamber and attachment of yeast cells. Cells were deposited on a

wide coverslip coated with polylysine. The coverslip was washed with SC

medium to remove the unattached cells. The coverslip was attached to a

slide using double-sided Scotch tape along the long side of the coverslip,

and the appropriate medium was perfused through the gap between the

coverslip and slide through capillary action, using a pipette and a filter paper

as a wick. The approximate volume of the gap was 350 ml. CoverWell gaskets

(Molecular Probes) were also used for analyzing multiple conditions at the

same time.

To expose the cells to pheromone or sorbitol, appropriate amounts of these

were dissolved in SC and perfused through the flow-cell. During a change in

medium, three chamber volumes of new medium passed through the chamber

in o45 s. There was batch-to-batch variability in pheromones we purchased,

and we calibrated the concentration by determining the concentration at which

50% of the cells responded to pheromones on exposure to 1 M sorbitol.

Microscopy and image processing. The cells were observed using a Delta-

Vision deconvolution fluorescence microscope (Applied Precision), based on a

Nikon TE2000 fluorescence microscope. Images were acquired with a CoolSnap

HQ CCD camera with 1,024 � 1,024 pixel resolution through a 100�Apochromat objective lens with 1.4 NA. For images for the time-course

experiments, 45 0.3-mm z sections were acquired. The cells were also observed

using a Zeiss 200M fluorescence microscope with an Orca-II-ER camera and

a 100�/1.45 NA plan a fluar objective. Emission from GFP was visualized at

528 nm (38-nm bandwidth) upon excitation at 490 nm (20-nm bandwidth),

and emission of RFP was visualized at 617 nm (73-nm bandwidth) upon

excitation at 555 nm (28-nm bandwidth). The noise characteristics of the CCD

camera were determined by measuring both the closed shutter noise and the

noise from a region of the slide with no cells for the same exposure periods. The

noise characteristics were used to calibrate the images by normalizing both the

mean and the s.d. of the image in blank areas.

For the time course experiments, cells were initially photographed to

measure their autofluorescence levels. Subsequently, cells were photographed

in 10-min intervals throughout the course of the experiment. At each time

point, five to ten images were acquired with the same fixed exposure time to

calibrate photobleaching.

The first image was subtracted from subsequent images to correct for the

autofluorescence of each cell. In each of the experiments, between 300–1,200

cells were monitored. The cells were assumed to respond to the appropriate

changes in the environment, if the change in their intensity through the course

of the hour-long experiment was greater than 3 s.d. above the mean of the

calibrated CCD camera noise. For the scatter plots and images in Figure 3, data

were gathered 1 h after the change in medium from SC to SC plus pheromones

and/or sorbitol.

Protein blots. The details of the protocol for protein blots are provided in the

Supplementary Methods.

Note: Supplementary information is available on the Nature Genetics website.

ACKNOWLEDGMENTSWe thank J. Weiner, P. Houston, K. Thorn, K. Duevel, L. Schneper, E. Xuand P. Hersen for help with experiments, R. Tsien and E. Winters for reagents,A. Sengupta, A. Murray and M. Tyers for helpful discussions and A. Regev,L. Garwin, K. Vestrepen, P. Swain, E. O’Shea, I. Nachman, N. Barkai andA. Amon for comments on the manuscript. This work was supported by grantsfrom the NIH (J.R.B.), GRPW fellowship, Lucent Technologies (M.N.M.),Keck Futures Initiative (S.R.) and the FAS Center for Systems Biology(S.R. and M.N.M.). Requests for materials should be addressed to S.R.([email protected]).

AUTHOR CONTRIBUTIONSS.R., J.R.B. and M.M. designed the experiments; M.M. and A.M. did themodeling and J.R.B., M.M., A.M. and S.R. wrote the paper.

COMPETING INTERESTS STATEMENTThe authors declare that they have no competing financial interests.

Published online at http://www.nature.com/naturegenetics

Reprints and permissions information is available online at http://npg.nature.com/

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CORR IGENDUM

Corrigendum: Cross-talk and decision making in MAP kinase pathwaysMegan N McClean, Areez Mody, James R Broach & Sharad RamanathanNat. Genet. 39, 409–414 (2007); published online 28 January; corrected after print 14 March 2007

In the version of this article initially published, the strain referred to as FUS3D63S on pp. 411-412 of the main text and in the figure legend for Figure 5c-f should instead read 5c-f should instead read 5c-f FUS3D317G. The error has been corrected in the PDF version of the article.

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