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A functional siRNA screen identifies genes modulatingangiotensin II-mediated EGFR transactivation

Amee J. George1,2,3,4, Brooke W. Purdue1, Cathryn M. Gould3, Daniel W. Thomas3, Yanny Handoko3,

Hongwei Qian5, Gregory A. Quaife-Ryan1, Kylie A. Morgan2, Kaylene J. Simpson3,4,6, Walter G. Thomas1,*,` and

Ross D. Hannan1,2,3,6,7,8,*1School of Biomedical Sciences, The University of Queensland, St. Lucia, Queensland, 4072, Australia2Oncogenic Signalling and Growth Control Program, Peter MacCallum Cancer Centre, East Melbourne, Victoria, 3002, Australia3The Victorian Centre for Functional Genomics, Peter MacCallum Cancer, East Melbourne, Victoria, 3002, Australia4Department of Pathology, The University of Melbourne, Parkville, Victoria, 3010, Australia5Baker IDI Heart and Diabetes Institute, Melbourne, Victoria, 3004, Australia6Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, Victoria, 3010, Australia7Department of Biochemistry and Molecular Biology, The University of Melbourne, Parkville, Victoria, 3010, Australia8Department of Biochemistry and Molecular Biology, Monash University, Clayton, Victoria, 3800, Australia

*These authors contributed equally to this work`Author for correspondence (w.thomas@uq.edu.au)

Accepted 4 September 2013Journal of Cell Science 126, 5377–5390� 2013. Published by The Company of Biologists Ltddoi: 10.1242/jcs.128280

SummaryThe angiotensin type 1 receptor (AT1R) transactivates the epidermal growth factor receptor (EGFR) to mediate cellular growth,however, the molecular mechanisms involved have not yet been resolved. To address this, we performed a functional siRNA screen of

the human kinome in human mammary epithelial cells that demonstrate a robust AT1R–EGFR transactivation. We identified a suite ofgenes encoding proteins that both positively and negatively regulate AT1R–EGFR transactivation. Many candidates are componentsof EGFR signalling networks, whereas others, including TRIO, BMX and CHKA, have not been previously linked to EGFR

transactivation. Individual knockdown of TRIO, BMX or CHKA attenuated tyrosine phosphorylation of the EGFR by angiotensin IIstimulation, but this did not occur following direct stimulation of the EGFR with EGF, indicating that these proteins function betweenthe activated AT1R and the EGFR. Further investigation of TRIO and CHKA revealed that their activity is likely to be required for

AT1R–EGFR transactivation. CHKA also mediated EGFR transactivation in response to another G protein-coupled receptor (GPCR)ligand, thrombin, indicating a pervasive role for CHKA in GPCR–EGFR crosstalk. Our study reveals the power of unbiased, functionalgenomic screens to identify new signalling mediators important for tissue remodelling in cardiovascular disease and cancer.

Key words: Angiotensin, EGFR, G protein-coupled receptor, siRNA, Transactivation

IntroductionApart from its well-studied roles in vasoconstriction, aldosteronerelease, and fluid balance, angiotensin II (AngII), the principal

effector of the renin–angiotensin system (RAS), influences a

selection of homeostatic and modulatory processes that can also

serve as targets for dysregulation and subsequent development of

pathological states. These include cellular growth (hypertrophy)and remodelling (fibrosis); dyslipidaemia; endothelial dysfunction,

aneurysms and angiogenesis (Iwai and Horiuchi, 2009; Lu et al.,

2008; Mehta and Griendling, 2007; Weiss et al., 2001); pro-

inflammatory responses (Rompe et al., 2010; Schiffrin, 2010);stem cell programming and haematopoiesis (Heringer-Walther

et al., 2009; Park and Zambidis, 2009; Zambidis et al., 2008);

neuromodulation including cognition, memory and dementia (Li

et al., 2010; Miners et al., 2009); and cancer, as reviewed by us

(George et al., 2010).

AngII acts primarily on the angiotensin type 1 receptor

(AT1R), a G protein-coupled receptor (GPCR) encoded by a

single gene (AGTR1) in humans and two homologous isoforms inrodents (AT1A and AT1B) (de Gasparo et al., 2000; Hunyady and

Catt, 2006; Mehta and Griendling, 2007). Activated AT1Rs

couple to the heterotrimeric G proteins Gq/11 (to stimulate

phospholipase C b-mediated calcium mobilisation), Gi/o, G12/13

and Gs, as well as the monomeric G proteins (e.g. Rho, Ras and

Rac) (de Gasparo et al., 2000; Guilluy et al., 2010). The activated

AT1R also couples to soluble and receptor tyrosine kinases,

the mitogen-activated protein kinases (MAPK; extracellular

regulated kinases, ERK1/2, p38 MAPK and Jun N-terminal

kinase), the JAK–STAT pathway, the generation of reactive

oxygen species and various ion channels (de Gasparo et al., 2000;

Hunyady and Catt, 2006; Mehta and Griendling, 2007). Signal

termination is mediated by receptor phosphorylation and the

recruitment and binding of arrestins (Qian et al., 2001), which

terminate initial signalling, mediate receptor endocytosis and also

act as scaffolds to support secondary and tertiary signalling

complexes (Shenoy and Lefkowitz, 2011).

Daub and colleagues first reported that the epidermal growth

factor receptor (EGFR) and the neu oncoprotein (ErbB2/HER2)

are phosphorylated when stimulated with GPCR agonists

endothelin 1, lysophosphatidic acid (LPA) and thrombin, which

could be inhibited when cells were treated with EGFR antagonist

AG1478, suggestive of a role for GPCRs in receptor tyrosine

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kinase signalling cross-talk (Daub et al., 1996). Since then, we and

others have demonstrated that the AT1R can ‘hijack’ EGFR family

signalling machinery and this is crucial for the downstream AT1R-

mediated growth signalling and functional effects, such as cellular

hypertrophy and/or proliferation (Asakura et al., 2002; Eguchi

et al., 2001; Mifune et al., 2005; Thomas et al., 2002). Various

mechanisms have been described to explain AT1R–EGFR

transactivation, including metalloproteinase-mediated EGF

ligand shedding (Mifune et al., 2005; Ohtsu et al., 2006), Ca2+-

mediated Pyk2 activation (Eguchi et al., 1999), or direct

interaction of the EGFR with the activated AT1R, through its

tyrosine 319 residue (Seta and Sadoshima, 2003), although this

does not appear to be the mechanism in a rat cardiomyocyte model

(Smith et al., 2011).

To date, most studies have utilised a candidate approach to

identify the proteins that are involved in AT1R-mediated EGFR

transactivation in specific cell types. Although this has been

informative, more often than not, this approach has failed to give

the broader mechanistic picture of the underlying biology. Thus,

the exact molecular mechanism linking the AT1R to the EGFR

remains poorly defined and much detail is lacking. To address

this issue, we generated a robust and tractable human cellular

model of AT1R–EGFR transactivation, and used the model to

perform functional siRNA screening to unbiasedly identify novel

genes involved in the AT1R–EGFR transactivation process.

ResultsGeneration and characterisation of a stable cellular model

of AT1R–EGFR transactivation

In order to examine the molecular mechanisms underlying

AT1R–EGFR transactivation, a human cellular model was

generated by introducing the AT1R into HMEC-LST cells

(HMEC-LST-AT1R) using retroviral delivery of a vector that

co-expresses mCherry. The AT1R-expressing cell population was

enriched using fluorescence-activated cell sorting (FACS), and a

heterogeneous population of cells expressing mCherry (Fig. 1A)

was collected and expanded for further analysis. We confirmed

expression of the ectopically expressed AT1R protein bearing an

N-terminal HA epitope tag using western blot analysis (Fig. 1B).

Immunofluorescence detection of the AT1R revealed localisation

to the cell surface (Fig. 1C; supplementary material Fig. S1).

Competition [125I]AngII radioligand binding assays revealed a

Kd for AngII of 1.7 nM and a calculated receptor density of

1.87 pmol receptor/mg cellular protein (Fig. 1D). The AT1R-

expressing cells demonstrated a robust, dose-dependent Ca2+

transient upon AngII stimulation, with an EC50 value of 24.8 nM,

indicating appropriate coupling to Gq/11 (Fig. 1E).

Stimulation of the HMEC-LST-AT1R cells with 100 nM

AngII led to the robust and reproducible phosphorylation of

EGFR (pY1068) and ERK1/2 (p42/44; pERK1/2) (Fig. 2A).

Quantification of western blot data revealed a 2-fold activation of

EGFR above the level in unstimulated cells (Fig. 2B) and a 2.5-

fold activation of ERK1/2 above the unstimulated cells upon

AngII treatment (Fig. 2C). Maximal activation of EGFR and

ERK1/2 occurred between 5 and 10 minutes (supplementary

material Fig. S2), whereas activation of AKT (Ser473), which

can also be activated downstream of EGFR and PI3K was not

observed, revealing the MAP kinase pathway is a prominent

pathway activated in response to AngII stimulation. As is well

described, other pathways do exist for ERK1/2 activation from

GPCRs (namely Ca2+, PKC and arrestins), therefore, to confirm

that activation of the EGFR and downstream ERK1/2 by AngII

Fig. 1. Generation and characterisation of

the AT1R–EGFR transactivation model.

(A) We stably introduced an N-terminally HA-

tagged angiotensin type I receptor (AT1R) into a

human mammary epithelial cell line (HMEC-

LST) (Elenbaas et al., 2001), and used mCherry

expression to FACS enrich a heterogeneous

population of cells expressing similar amounts

of AT1R. (B) HA-tagged AT1R expression in

HMEC-LST cells was determined by western

blot analysis of cell lysate. (C) The cells

transfected with the HA-tagged AT1R

ectopically expressed the protein on the cell

surface, but the control HMEC-LST-mCherry-

transfected (mCherry) cells showed no such

expression, as determined by

immunofluorescence when stained with an anti-

HA antibody (green) to detect the HA-tagged

AT1R and DAPI (blue) to detect nuclei. Scale

bars: 50 mm. (For individual confocal images

and merged images in supplementary material

Fig. S1.) (D) Cells expressing the AT1R readily

bound [125I]AngII (EC5051.7 nM) in a

radioligand-binding assay; [125I]AngII was not

observed to bind to the mCherry cells (n54

experiments). (E) When the HMEC-LST-AT1R

cells were stimulated with AngII, intracellular

Ca2+ was mobilised (EC50524.8 nM); this did

not occur in the mCherry cell line (n55

experiments).

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HMEC-LST-AT1R cells were pretreated for 30 minutes with

antagonists to EGFR (AG1478) or AT1R (candesartan cilexetil)

prior to stimulation with AngII (Fig. 2D). Phosphorylation of

EGFR and ERK1/2 was prevented when cells were pretreated

with either inhibitor, demonstrating that activation of EGFR and

ERK1/2 is due to the transactivation of the EGFR by ligand

(AngII) activation of the AT1R. These findings were also

confirmed when the AT1R was introduced into another human

mammary epithelial cell line, HMEC-HMLE-AT1R (supplementary

material Fig. S3).

AT1R–EGFR transactivation is inhibited by siRNAs

targeting known transactivation components

We performed proof-of-concept experiments to demonstrate that the

AT1R–EGFR transactivation response can be inhibited when cells

were transfected with siRNAs that target genes involved in the

process, specifically those of the AT1R, its cognate G protein (Gq/11)

and the EGFR. We used siGENOME SMARTpools targeting Agtr1a

to knock down expression of the rat AT1R by 80% (Fig. 3A) and this

prevented phosphorylation of both EGFR and ERK1/2 upon AngII

stimulation (Fig. 3B). Robust knockdown of Gq/11 (GNAQ), essential

for AT1R-mediated cardiomyocyte hypertrophy (Smith et al., 2011)

and the development of cardiac hypertrophy in mice (Wettschureck

et al., 2001), also abolished EGFR and ERK1/2 phosphorylation

following AngII stimulation (Fig. 3C,D). Similarly, knockdown of

EGFR using SMARTpool siRNAs prevented EGFR and ERK1/2

phosphorylation upon AngII stimulation (Fig. 3E,F) as well as

reducing the total EGFR protein, as expected. Together, these

experiments validated this system as suitable for detecting novel

genes involved AT1R–EGFR transactivation.

Functional siRNA screening of the human kinome reveals

candidates that modulate the AT1R–EGFR transactivation

response

We used functional genomic screening to identify genes that

modulate the AT1R–EGFR transactivation response. Using the

HMEC-LST-AT1R cells, we optimised an AT1R–EGFR

transactivation assay in microplate format for use in a siRNA

screen. We determined that stimulating the HMEC-LST-AT1R

cells for 10 minutes with 100 nM AngII in 96-well microplates

using the AlphaScreen SureFire phospho-ERK1/2 assay (as a

surrogate readout for AT1R–EGFR transactivation) gave a robust

1.5-fold activation of ERK1/2 above that of unstimulated cells

(supplementary material Fig. S4). Furthermore, stimulation of

cells with 100 ng/ml EGF for 10 minutes led to a 2.8-fold

increase in ERK1/2 activation above stimulated, while

pretreatment of cells with 5 mM AG1478 30 minutes prior to

stimulation blocked AngII and EGF mediated ERK1/2 activation.

This method was adapted to an siRNA screening format

(supplementary material Fig. S5; Tables S1, S2 and S3).

We performed a primary siRNA screen using the human

Dharmacon SMARTpool siRNA kinome library encompassing

720 kinase genes, outlined in Fig. 4A, because we hypothesised

that this gene set was likely to encode products that modulate the

signalling underlying AT1R–EGFR transactivation and were

potentially druggable. Robust Z-score analysis of the data and

ranking of each gene from the primary screen were performed

(supplementary material Table S2). As expected, and also to

validate our screening approach, EGFR present in the siRNA

library and independent of the siRNA plate controls, was

identified as being one of the top ‘hits’ in the screen.

We selected 50 highly ranking candidates from the primary

screen for further target validation, and performed a secondary

siRNA screen using the Dharmacon siGENOME deconvoluted

SMARTpool siRNA library (four siRNA duplexes per gene,

which comprised the original SMARTpool used in the primary

screen). We took an unbiased approach in our candidate gene

selection for secondary screening, selecting candidates with the

20 highest and 20 lowest robust Z-scores. In addition, we selected

a further 10 highly ranked candidates for analysis based on

literature that linked them with AT1R or EGFR signalling, or had

demonstrated some association with at least one of the other

highest ranked candidates identified by the primary screen.

Fig. 2. AT1R–EGFR transactivation occurs in HMEC-

LST-AT1R cells. (A) HMEC-LST cells (mCherry or AT1R

transduced) were serum starved then stimulated with 100 nM

AngII for 5-10 minutes. Robust activation of the EGFR

(pY1068) and ERK1/2 was observed in the AT1R-transduced

cells. (B,C) Quantification of western blot data using

densitometry analysis (ImageJ) illustrates increases in

phospho-EGFR (pY1068; B) and phospho-ERK1/2 (C) upon

stimulation with AngII (n54 experiments; *P50.0137,

**P50.0028, paired two-tailed Student’s t-test). (D) HMEC-

LST-AT1R cells were treated with 5 mM AG1478 (EGFR

inhibitor) or 1 mM candesartan cilexetil (AT1R antagonist)

for 30 minutes prior to stimulation with 100 nM AngII for 5-

10 minutes. Analysis revealed that inhibition of either EGFR

or AT1R activity blocks AngII-mediated AT1R–EGFR

transactivation (n53 experiments; a representative western

blot is shown).

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For our secondary screen analysis, we could not use robust Z-

scoring to rank hits. This is because the method relies on the

assumption that the majority of the siRNAs will not have a

biological effect (Birmingham et al., 2009), whereas in the

secondary screen, the expectation is that the majority of the

siRNAs identified (in the primary screen) are positive hits.

Hence, we calculated the average pERK1/2 value for the mock-

and siGFP-transfected cells and normalised the pERK1/2 reading

of each deconvoluted siRNA duplex to the average of the mock-

and siGFP-transfected cells (outlined in supplementary material

Table S1). We classified a duplex as being a ‘hit’ if the fold

change was greater than 1.5 or less than 21.5 (equating to a 50%

or more increase or decrease in AngII-mediated ERK1/2

activation compared to mock and siGFP-stimulated cells). The

hit score was identified as the maximum number of hits in one

particular direction (either positive or negative; the maximum hit

score was 4, the minimum was 0). The duplexes that did not score

within our cut-offs were deemed to be ‘unchanged’ and thus did

not contribute to the ‘hit’ score. From there, we used hit scoring

to identify high (4/4 and 3/4), medium (2/4) and low (1/4, 0/4)

confidence targets for their role in AT1R–EGFR transactivation

(Fig. 4A). The list of genes analysed in the secondary screen and

validation score is given in Table 1.

The 50-gene list was further analysed using STRING 9.0

(http://string-db.org), an online database of known and predicted

physical and functional protein interactions (Szklarczyk et al.,

2011) to generate an AT1R–EGFR transactivation ‘interactome’,

color-coded to represent the high, medium and low confidence

scores for each candidate in the secondary screen analysis

(Fig. 4B). Interestingly, we identified 36/50 candidates from the

secondary screen that were either functionally or physically

connected to at least one other candidate. Validated high and

medium confidence targets (30 in total) were implicated in

signalling pathways linked to EGFR–ERBB2, PI3K–AKT,

MAPK and PKC signalling, which was predicted, as analysis

of the literature revealed that these pathways have previously

been implicated in EGFR transactivation.

We subsequently performed validation on a selection of genes

from the high and medium hit list to determine (i) if the

SMARTpool siRNA was on target, and (ii) how knockdown of the

target gene affected transactivation of the EGFR (supplementary

material Fig. S6A,B). We focused primarily on three novel genes

encoding TRIO [triple functional domain (PTPRF interacting)], a

Rho/Rac GEF protein containing a kinase domain; CHKA (choline

kinase alpha) and BMX (BMX non-receptor tyrosine kinase), as

these have not been previously implicated in GPCR-mediated

EGFR transactivation.

TRIO, CHKA and BMX modulate AT1R–EGFRtransactivation

We used SMARTpool siRNAs to knock down the expression of

TRIO, CHKA and BMX (Fig. 5A,C,E, respectively) and to

confirm their contribution to AngII-stimulated activation of

EGFR and ERK1/2 (Fig. 5B,D,F). We observed a reduction in

AngII-mediated EGFR and ERK1/2 activation with knockdown

of TRIO, CHKA and BMX, and a modest reduction in basal

Fig. 3. AT1R–EGFR transactivation is reduced when cells are

transfected with siRNAs targeting AT1R, Gq/11 and EGFR

expression. Cells were transfected with Dharmacon siGENOME

SMARTpool siRNAs targeting the ectopically expressed AT1R

(siAgtr1a), Gq/11 (GNAQ, siGNAQ) or EGFR (siEGFR) mRNA

transcripts. (A,B) Cells transfected with siAgtr1a demonstrated mRNA

knockdown of ,80% at 24 hours (A), and the AT1R–EGFR

transactivation at 72 hour knockdown was abolished (B) (n53

experiments; ***P50.0009, paired two-tailed Student’s t-test).

(C,D) Transfection with siGNAQ resulted in over an 85% knockdown of

GNAQ mRNA at 24 hours (C), and a reduction in EGFR and ERK1/2

phosphorylation post-AngII stimulation (72 hour knockdown; D) (n53

experiments; ***P50.0002, paired two-tailed Student’s t-test).

(E,F) Similarly, when cells were transfected with siEGFR, ,75%

knockdown of EGFR mRNA was observed at 24 hours post-transfection

(E) and the AT1R–EGFR transactivation response was blunted at

72 hours (F) (n53 experiments; ***P50.0004, paired two-tailed

Student’s t-test). Western blot is representative of all of the experiments

carried out (n53).

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ERK1/2 activity with knockdown of all three candidates. We also

confirmed that individual siRNA duplexes knocked down the

target mRNA transcripts, and assessed their impact on AT1R–

EGFR transactivation by western blot analysis (supplementary

material Fig. S7A–F).

TRIO, CHKA and BMX function between the AT1R and

the EGFR

Our data are consistent with TRIO, CHKA and BMX acting

downstream of the AT1R, but upstream of the EGFR. To test this,

we reasoned that the phosphorylation of the EGFR and ERK1/2,

Fig. 4. Kinome siRNA screen to determine genes involved in

AT1R–EGFR transactivation. (A) Using the HMEC-LST-

AT1R cell line, we performed a primary siRNA screen using the

Dharmacon siGENOME SMARTpool siRNA library targeting

kinase genes (720 in total, 40 nM siRNA). (B) Phospho-ERK1/2

data (SureFire) was normalised to cellular confluency (IncuCyte)

for each well, and robust Z-score analysis carried out (for

individual gene data and descriptions, see supplementary

material Tables S1–S3). Secondary siRNA screening analysis

was performed on 50 high-ranking candidates identified from the

primary screen using the Dharmacon siGENOME SMARTpool

deconvoluted siRNA library (four individual duplexes

comprising the SMARTpool; 25 nM siRNA). High (4/4 and 3/

4), medium (2/4) and low (1/4, 0/4) confidence candidates were

then identified. (B) STRING analysis was performed on the

AT1R–EGFR transactivation secondary screen gene set to

identify physical and functional associations of the genes in the

list. Genes that remained as unconnected ‘nodes’ included

FN3KRP, ASK, BMX, CDC2L2, DGKH, FRK, PSKH2, SNRK,

STYK1 and TRIO.

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by direct stimulation with EGF ligands to bypass the AT1R (see

Fig. 6A), should not be affected by the knockdown of TRIO,

CHKA and BMX if they function downstream of the AT1R, but

upstream of the EGFR. We therefore knocked down TRIO,

CHKA and BMX using SMARTpool siRNAs in HMEC-LST-

AT1R cells and stimulated with either 100 nM AngII or 0.5 ng/ml

EGF for 10 minutes (Fig. 6B,C,D; supplementary material Fig.

S8A–C). Knockdown of TRIO, CHKA or BMX in HMEC-LST-

AT1R cells did not prevent activation of EGFR and ERK1/2 by

direct stimulation with EGF, indicating that they are likely to sit

mechanistically between the AT1R and EGFR in transactivation.

Furthermore, our analysis revealed that pre-treatment of cells with

5 mM AG1478 prevented AngII-mediated ERK1/2 activation

following TRIO, CHKA and BMX knockdown, implying thatthe activation of ERK1/2 is primarily EGFR dependent, and that

candidate knockdown combined with AG1478 treatment mayalso eliminate EGFR-independent and -dependent signalling,respectively (supplementary material Fig. S9A–C). Moreover,TRIO, CHKA and BMX knockdown did not have a dramatic

impact on Ca2+ mobilisation upon AngII stimulation(supplementary material Fig. S10A,B) suggesting that themechanism of action of these candidates is unlikely to be

through changes in AngII-mediated intracellular Ca2+ levels.

Mechanistic insights into the function of TRIO, CHKA andBMX in GPCR-mediated EGFR transactivation

We further investigated the mechanism(s) by which the three leadcandidates identified in our siRNA screen act to modulate AT1R–EGFR transactivation. TRIO contains two guanine nucleotide

exchange factor domains that can activate RhoA and Rac1.We took a genetic approach to determine whether RAC1 orRHOA, downstream of TRIO, modulated the AT1R–EGFR

transactivation response. We achieved .90% knockdown ofRAC1 and RHOA mRNA transcripts at 24 hours usingSMARTpool siRNAs (Fig. 7A). Furthermore, we observed a

reproducible, robust reduction in EGFR and ERK1/2 activationwith RAC1 knockdown (Fig. 7B), although RAC1 knockdownalso had a modest effect on total EGFR expression. RHOAknockdown lead to a reduction in EGFR activation, but only a

minimal reduction in AngII-mediated ERK1/2 activation(Fig. 7C). To further elucidate whether RAC1 is involved inAT1R–EGFR transactivation, we pre-treated the HMEC-LST-

AT1R cells for 30 minutes with 100 mM NSC-23766 (Fig. 7D),which lead to a reduction in AngII-mediated EGFR and ERK1/2activation. We also examined the requirement of CHKA activity

for AngII-mediated EGFR transactivation. Pretreatment of cellswith 10 mM CK37, an inhibitor of CHKA activity, for 30 minutesprior to AngII stimulation, also led to a reduction in EGFR and

ERK1/2 activation, with no observable effect on total CHKA(ChoK) protein expression (Fig. 7E).

We next tested the parental HMEC-LST cell line with aselection of GPCR ligands (endothelin-1, thrombin and 17-b-

oestradiol) to determine whether or not we could achieve GPCR-mediated EGFR transactivation with endogenous GPCRs, as aprelude to determining whether our identified screening

candidates generically modulate GPCR–EGFR transactivation(supplementary material Fig. S11A). Only thrombin was able toelicit a transactivation response. We next took advantage of our

observation that thrombin also promoted robust ERK1/2 signallingthrough EGFR transactivation in the parental HMEC-LST cell lineto determine whether TRIO, CHKA and BMX knockdownmodulates GPCR–EGFR transactivation (Fig. 7F). HMEC-LST

cells stimulated with 10 nM thrombin for 10 minutes robustlyactivated the EGFR and ERK1/2, which was blocked when thecells were pretreated for 30 minutes with 5 mM AG1478. We next

tested whether the knockdown of TRIO, CHKA or BMXaffected thrombin-mediated EGFR transactivation (Fig. 7G;supplementary material Fig. S11B). Thrombin-mediated EGFR

and ERK1/2 phosphorylation was reduced with CHKAknockdown, but remained unchanged when TRIO and BMXwere silenced, indicating that CHKA may be required for the

transactivation of EGFR by GPCR receptors other than AT1R,whereas TRIO and BMX are more selective and may be specific toAT1R-mediated EGFR transactivation. These data provide

Table 1. Genes assayed in the secondary siRNA screen and

duplex scores

Entrez ID Gene Duplex hits

High confidence 1119 CHKA 4/42064 ERBB2 4/4

79672 FN3KRP 4/4207 AKT1 3/4

10926 ASK 3/4660 BMX 3/4801 CALM1 3/4

728642 CDC2L2 3/41859 DYRK1A 3/41956 EGFR 3/42242 FES 3/42322 FLT3 3/45584 PRKCI 3/4

Medium confidence 10000 AKT3 2/464768 C9ORF12 2/41020 CDK5 2/41460 CSNK2B 2/4

160851 DGKH 2/42261 FGFR3 2/42444 FRK 2/45594 MAPK1 2/45290 PIK3CA 2/45297 PIK4CA 2/4

200576 PIP5K3 2/45562 PRKAA1 2/45580 PRKCD 2/4

85481 PSKH2 2/454861 SNRK 2/455359 STYK1 2/47204 TRIO 2/4

Low confidence 657 BMPR1A 1/48851 CDK5R1 1/4

80347 COASY 1/41399 CRKL 1/4

53944 CSNK1G1 1/41739 DLG1 1/42049 EPHB3 1/4

10114 HIPK3 1/451347 JIK 1/492335 LYK5 1/41326 MAP3K8 1/49833 MELK 1/4

55750 MULK 1/48395 PIP5K1B 1/41263 PLK3 1/45583 PRKCH 1/45592 PRKG1 1/48986 RPS6KA4 1/48576 STK16 1/46011 GRK1 0/4

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evidence that both common and distinct mechanisms control

GPCR–EGFR transactivation.

DiscussionThe development of siRNA platform technologies to permit

genome-wide, loss-of-function screening has provided an

unprecedented resource for delineating molecular and cellular

processes, including, for example, cell migration (Simpson et al.,

2008), necrotic cell death (Hitomi et al., 2008) and cell division

(Kittler et al., 2007). In the present study, we used RNAi-based

screening to unbiasedly identify kinase genes involved in AngII-

mediated activation of ERK1/2, specifically those related to

AT1R–EGFR transactivation. We developed and characterised a

human cellular model of AT1R–EGFR transactivation, then

performed a primary kinome screen, comprising SMARTpool

siRNAs targeting 720 kinase genes, and a subsequent secondary

validation screen of 50 of the highest-ranking candidates using

deconvoluted siRNAs. We identified many candidates that

modulate the AT1R–EGFR transactivation response; these

included molecules clearly related to the EGFR–PKC–PI3K–

MAPK signalling axis, as well as novel genes, such as those of

TRIO, BMX and CHKA, which appear to act mechanistically

between the AT1R and the EGFR. CHKA is likely to be a general

mediator of GPCR-induced EGFR transactivation, whereas TRIO

and BMX might act more specifically in this process.

The capacity of EGFRs (and other growth factor receptors) to

act as important conduits for multiple GPCR-related stimuli that

modulate cell growth and tissue remodelling is generally accepted.

Many studies, including our own, have linked the activation of the

AT1R to the phosphorylation and transactivation of the EGFR in

cardiac, renal and vascular tissues (Eguchi et al., 2001; Eguchi

et al., 1998; Thomas et al., 2002; Touyz et al., 2002; Uchiyama-

Tanaka et al., 2001). In support of the ‘‘triple membrane passing

signalling paradigm’’ proposed by Ullrich and colleagues (Daub

et al., 1996), some evidence exists for matrix metalloprotease

(MMP) and a disintegrin and metalloprotease (ADAM) shedding

of EGF ligands as a mechanism for AT1R-mediated EGFR

transactivation and tissue remodelling. In the kidney, ADAM17

shedding of TGFa has been associated with renal disease (Shah

and Catt, 2006); in heart, ADAM12 shedding of heparin-binding

EGF-like growth factor (HB-EGF) reportedly mediates cardiac

hypertrophy (Asakura et al., 2002); and ADAM17 inhibition

reduces AngII-mediated EGFR phosphorylation and the

proliferation of vascular smooth muscle cells (Ohtsu et al.,

2006). In contrast, others have suggested alternative mechanisms

for EGFR transactivation, such as through intracellular kinases,

including Pyk2 and Src, or subsequent to direct interaction

between the AT1R and the EGFR (Eguchi et al., 1999; Seta and

Sadoshima, 2003; Touyz et al., 2002). So, while many would

accept the authenticity and importance of EGFR transactivation by

GPCRs, such as the AT1R, the mechanisms remain poorly

understood. It was this lack of clarity that compelled us to

undertake and unbiased approach to identify novel components

involved in transactivation EGFR by AT1R.

Fig. 5. Further validation of TRIO, CHKA and BMX involvement in

AT1R–EGFR transactivation. (A,B) HMEC-LST-AT1R cells were

reverse transfected with 40 nM Dharmacon siGENOME SMARTpool

siRNAs targeting TRIO, CHKA or BMX expression. HMEC-LST-AT1R

cells transfected with TRIO siRNA (siTRIO) demonstrated an

approximate 45% knockdown of mRNA transcript at 24 hours, by qRT-

PCR (A) and at 72 hours post-transfection, knockdown of TRIO reduced

AT1R–EGFR transactivation upon stimulation with AngII (B).

(C,D) When cells were transfected with CHKA siRNA (siCHKA), an

approximate 90% knockdown of CHKA transcript was observed at

24 hours (C), coupled with a reduction in ChoK (CHKA) protein

expression and AT1R–EGFR transactivation at 72 hours (D).

(E,F) Similarly, cells transfected with BMX siRNA (siBMX)

demonstrated an approximate 90% knockdown of mRNA transcript at

24 hours (E), and a reduction in AT1R–EGFR transactivation (as

determined by phospho-EGFR and phospho-ERK1/2 abundance) was

observed after 72-hour siRNA knockdown (F). n53 or 4 experiments for

both mRNA and protein analysis; for mRNA analysis *P50.0144

(TRIO), ***P50.0002 (CHKA) and P50.0008 (BMX), paired two-

tailed Student’s t-test. Western blots are representative of all experiments.

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To permit a functional siRNA screen, we developed a cellularmodel of AT1R–EGFR transactivation that met our selection

criteria: (1) the cells were of human origin and readilyexpandable to generate large cell numbers required for

screening; (2) they could be efficiently transfected withsiRNAs; and (3) they robustly transactivated the EGFR upon

stimulation with AngII. Primary cell models of cardiomyocytes,vascular and renal cells used in previous studies to examine

AT1R–EGFR transactivation were not amenable to siRNAscreening. Therefore, we initially tested 14 human vascular,

endothelial and epithelial cell lines for their ability totransactivate the EGFR with either ectopically or endogenously

expressed AT1R, under the above criteria. Although several

of these cell lines demonstrated AT1R-mediated EGFRtransactivation, we ultimately selected an immortalised human

mammary epithelial cell line, stably expressing the AT1R(HMEC-LST-AT1R). This cell line displayed high affinity and

functional AT1R expression on the cell surface and exhibitedappropriate AT1R pharmacology and Gq/11-mediated signalling.

Importantly, these cells robustly activated the EGFR and ERK1/2in response to AngII stimulation and showed efficient siRNA

knockdown of known targets, making it suitable for our screen.Additionally, these cells were selected for their functional

relevance, where AT1R overexpression has been implicated inbreast cancer pathogenesis (De Paepe et al., 2001; Rhodes et al.,

2009; Tahmasebi et al., 2006). Furthermore, AT1R–EGFRtransactivation could be modulated by siRNA knockdown of

either the AT1R or EGFR as well as by targeting Gq/11, anabsolute requirement for AT1R–EGFR transactivation in other

cell types, including cultured cardiomyocytes (Smith et al., 2011)and vascular smooth muscle cells (VSMC) (Mifune et al., 2005;

Ohtsu et al., 2008).

Using our cellular model, we adapted, optimised and

developed an AT1R–EGFR transactivation assay in microplateformat using the AlphaScreen SureFire phospho-ERK1/2 kit as

our readout. We screened using the Dharmacon SMARTpoolsiRNA kinome library, as we reasoned that kinases were likely to

be important for AT1R–EGFR transactivation and any hits wouldbe likely to be druggable in subsequent studies on function. We

ranked the candidates from the primary kinome screen on thebasis of robust Z-score, and pursued 50 highly ranked candidates

for a secondary screen, where we classified ‘hits’ as those withmore than a 1.5-fold change (in either direction) compared with

the mock- and siGFP-transfected cells. The result was a list ofhigh, medium and low confidence candidates, a number of which

we pursued using a candidate-type approach to further validatetheir role in AT1R–EGFR transactivation.

One of the major outcomes of our screen was the finding thatmany of the candidates related to the EFGR–ErbB2–PKC–PI3K–

MAPK signalling axis. Although in a way expected, thisobservation provided important confidence and validation that

the screen was sufficiently powerful to interrogate AT1R–EGFRtransactivation. The finding that ErbB2 (the common dimerising

partner for ErbB receptors) modulates the AT1R–EGFRtransactivation response in our mammary epithelial cell model

is consistent with previous studies suggesting that ErbB2 isrequired for AngII-mediated EGFR transactivation (Chan et al.,

2006; Negro et al., 2006). It also corroborates data from otherGPCRs, for example, the thrombin-dependent PAR1 activation in

MDA-MB-231 breast cancer cells that transactivates EGFR–

ErbB2 and increases cell invasiveness (Arora et al., 2008). Inaddition to ErbB2, we also identified and validated a number of

PKC isoforms (PKC-d and PKC-i) as modulators of AT1R–EGFR transactivation, consistent with previous reports of AT1R–

EGFR transactivation and PKC-d translocation in responseto AngII in primary breast cancer cells (Greco et al., 2003),

the PKC-d/Pyk2/Src-dependent AT1R–EGFR transactivationobserved in hepatic C9 cells (Shah and Catt, 2002) and

thromboxane A2 receptor-induced EGFR transactivation,involving Gq/11-mediated PKC-d and PKC-e activation

Fig. 6. The mechanism of action for TRIO, CHKA and

BMX lies between the AT1R and EGFR. (A) Our hypothesis

is that TRIO, CHKA and BMX lie between the activated AT1R

and EGFR and thus modulate the AT1R–EGFR transactivation

response. A proposed model for this theory is illustrated.

(B) HMEC-LST-AT1R cells were transfected with siGFP,

siTRIO, siCHKA or siBMX SMARTpool siRNAs for 72 hours

and stimulated with either AngII (100 nM) or EGF ligand

(0.5 ng/ml) for 10 minutes. Knockdown of TRIO (B), BMX

(C) or CHKA (D) did not alter the response of the cells to 0.5

ng/ml EGF ligand. Data are representative of three

independent experiments.

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(Uchiyama et al., 2009). Moreover, it has not escaped our

attention that a number of hits from our screen are proteins that

contain pleckstrin homology (PH) domains (including AKT1,AKT3, TRIO, BMX and DGKH), which, along with PI3K and

the PKC isoforms, suggests that phosphoinositide biosynthesis,

localisation, compartmentalisation and/or signalling are critical

factors for AT1R–EGFR transactivation. Interestingly, kinases

previously associated with both AT1R and GPCR-mediated

EGFR transactivation, including Pyk2 and Src (Andreev et al.,2001; Eguchi et al., 1999; Shah and Catt, 2002) were not strong

hits identified by our screen, which could suggest, at least in our

breast epithelial cell model, that other signalling candidates may

play a more prominent role in AT1R–EGFR transactivation.

When considering potential hits, our primary interest was in

candidates that had not been previously (or at least ostensibly)

associated with ErbB function. We were also seeking hits where a

demonstrable effect on EGFR–ERK activation was direct and not

secondary to global effects on cell viability or ‘non-specific’

alterations in total EGFR abundance, both of which might result

in apparent reduction in AngII-induced ERK1/2. With this in

mind, we assayed a number of the high/medium confidence

siRNA screening hits (14 in total) to quantify mRNA knockdown

by qRT-PCR and assess their performance in AT1R–EGFR

transactivation. For most of these candidates, we confirmed

siRNA-mediated knockdown and observed a reduced ERK1/2

activation following AngII stimulation. However, we noted for

some candidates, a large, presumably non-specific effect on total

EGFR expression (e.g. CDC2L2), or alternatively, little apparent

effect on the phosphorylation of the EGFR (e.g. DYRK1A,

STYK1), indicating the effect on ERK signalling was probably

Fig. 7. Elucidating the function of TRIO, CHKA and BMX in GPCR-mediated EGFR transactivation. RHOA and RAC1, downstream of TRIO, were

knocked down in HMEC-LST-AT1R cells to assess their role in AT1R–EGFR transactivation. (A) Greater than 90% knockdown of the RAC1 and RHOA

mRNA transcripts were observed at 24 hours. (B,C) At 72 hours post-transfection, knockdown of RAC1 reduced EGFR and ERK1/2 activity upon AngII

stimulation, and led to a small reduction in total EGFR protein expression (B), whereas RHOA knockdown affected EGFR but not ERK1/2 activity (C).

(D,E) Pre-treatment of cells with NSC-23766 (D) or CK37 (E) revealed a blunting in AT1R–EGFR transactivation upon AngII stimulation. (F) To identify whether

TRIO, CHKA and BMX were specific to AT1R–EGFR transactivation, we stimulated the parental HMEC-LST cell line (not containing the ectopically

expressed AT1R) with 10 nM thrombin for 10 minutes in the presence or absence of 5 mM AG1478 and evaluated EGFR and ERK1/2 phosphorylation.

(G) Knockdown of BMX and TRIO, but not CHKA in the HMEC-LST cells revealed little change in EGFR and ERK1/2 activation post thrombin stimulation

(ERK1/2 activation data for three independent experiments in which CHKA was knocked down is given in supplementary material Fig. S11C). n53 or 4

experiments for both mRNA and protein analysis; for mRNA analysis **P50.0014 (RHOA), ***P50.0009 (RAC1), paired two-tailed Student’s t-test. Western

blots are representative of all experiments performed.

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independent of EGFR transactivation. We dismissed suchcandidates in favour of others with clear and robust effects on

AngII-induced EGFR–ERK1/2 activation, without obviouschanges in total ERK–EGFR protein expression. We focusedon three leading, proof-of-principle candidates that have notpreviously been implicated in GPCR-EGFR transactivation,

TRIO, CHKA and BMX (a member of the Tec non-receptortyrosine kinase family). Knockdown of these candidatesselectively and strongly prevented AngII-mediated, but not

EGF-mediated activation of the EGFR, locating their site ofaction between the AT1R and the initiation of EGFR activation.

TRIO (also known as UNC-73) is a particularly interesting

target with respect to potential AT1R, Gq/11 or EGFR activity.The human full-length cDNA encodes a 2861 amino acid protein,containing a serine/threonine kinase domain and two functionalguanine nucleotide exchange factors (GEF) domains, one specific

for GDP–GTP exchange on RhoA and the other for Rac1 (Debantet al., 1996). Rho/Rac activity has not, to our knowledge, beendirectly related to activation of the EGFR, but their capacity to

engage downstream kinases (e.g. ROCK) and affect cell growthand function is well described. Although few publications linkTRIO activity to AngII stimulation, AngII does productively

engage other RhoA GEFs, such as Arhgef1, with important rolesin vascular tone and hypertension (Guilluy et al., 2010).Importantly, the TRIO homologue, UNC-73, was revealed in a

forward genetic screen in Caenorhabditis elegans as a majormediator of Gq signalling, growth, reproduction and locomotionin worms (Williams et al., 2007). Mechanistically, Gq/11 has beenidentified to activate the C-terminal Rho-specific DH-PH domain

of TRIO, and of the closely related protein, p63RhoGEF (Rojaset al., 2007). Moreover, the crystal structure of activated Gq/11

and p63RhoGEF has been solved, demonstrating that direct

binding of activated Gq/11 to p63RhoGEF could specificallyinduce Rho signalling independently of and in competition toPLCb activation (Lutz et al., 2005). Intriguingly, a recent study

that utilised a genome-wide RNAi screen in Drosophila cellsto identify regulators of AP-1 transcription factor complexactivation (downstream of Gq) found that TRIO activation is arequirement for mitogenic signalling mediated by Gq, and is part

of a ‘hard-wired’ protein–protein-interaction based signallingcircuitry that is required for sustained cellular growth signallingand a regulator of normal and aberrant cellular growth (Vaque

et al., 2013). Together with our data, these studies provide robustevidence that TRIO mediates GPCR activation of downstreamtranscriptional events, in part by EGFR transactivation.

Interestingly, in our HMEC-LST-AT1R cell line, RAC1knockdown and the NSC-23766 compound (downstream ofTRIO) were both able to blunt the AT1R–EGFR transactivation

response. An inhibitor of Rac1 binding and activation by theRac1-specific GEF domain of TRIO (and Tiam1), NSC-23766 issuggested to have no demonstrable effect on RhoA or Cdc42(Gao et al., 2004). This data suggest that AngII, through AT1R/

Gq/11, can enhance TRIO Rac-GEF activity that contributes toactivation of signalling pathways and/or cytoskeletal remodellingthat is permissive for AT1R–EGFR transactivation.

BMX is a member of the Tec family of non-receptor tyrosinekinases (Tamagnone et al., 1994) and contains Tec homology(TH), PH, SH2, SH3 and kinase domains. BMX is expressed

in a variety of human cell types, including bone marrow,haematopoietic and endothelial cells (Tamagnone et al., 1994),and in the endocardium and large arteries of the mouse (Ekman

et al., 1997). BMX expression is altered in a number of differentcancers, including those of the bladder and prostate (Dai et al.,

2006; Guo et al., 2011; Jiang et al., 2007). Tec family kinaseshave been directly implicated in GPCR signalling, where Gq and/or bc subunits of the heterotrimeric G protein complex can bindto and activate the kinase (Bence et al., 1997; Langhans-

Rajasekaran et al., 1995; Tsukada et al., 1994). BMX, through itsPH domain, binds to the thrombin-activated GPCR, PAR1, andthis is a requirement for association with Shc and oncogenic

activity (Cohen et al., 2010). Together, this evidence suggeststhat Tec family kinases can modulate GPCR function by acting assignalling scaffolds that allow recruitment of other binding

partners and effector proteins, or as second messengers thatmodulate downstream signalling activities. Indeed, with respectto our observation that AT1R–EGFR transactivation leads tohypertrophic growth in rat cardiomyocytes (Thomas et al., 2002),

it is interesting that Bmx knockout mice display reduced cardiachypertrophy in a model of transverse aortic constriction,suggesting that Bmx is required for the morphological

responses to pressure overload in the heart (Mitchell-Jordanet al., 2008). Combined with our finding that BMX knockdownprevents AT1R–EGFR transactivation, this evidence suggests a

novel and plausible signalling mechanism underpinning AT1R–EGFR cardiomyocyte hypertrophy, which warrants furtherinvestigation.

Choline kinase alpha (CHKA, ChoK) phosphorylates choline to

produce phosphocholine (PCho), an important intermediate in thegeneration of the key membrane phospholipid, phosphatidylcholine(Aoyama et al., 2004). Homozygous knockout of CHKA in mice

results in embryonic lethality at the blastocyst stage (Wu et al.,2008), whereas upregulation of CHKA activity, or increasedabundance of choline/PCho is commonly observed in cancer

(Glunde et al., 2008; Hernando et al., 2009; Miyake and Parsons,2012). CHKA is required for growth-factor-induced cellularproliferation in primary human mammary epithelial cells

(Ramırez de Molina et al., 2004). Inhibition of CHKA in HeLacells reduces the steady-state levels of phosphatidylcholine andphosphatidic acid, affecting both PI3K and MAPK signalling(Yalcin et al., 2010). Recent evidence suggests that in breast cancer

and immortalised mammary epithelial cells, EGFR and c-Srccan synergise to regulate CHKA protein expression and activity(Miyake and Parsons, 2012). Furthermore, the same study

demonstrated that EGFR and CHKA form a complex in thepresence of c-Src, which is required for maximal EGF-dependentcellular growth. Attempts to determine whether CHKA binds to

either the HA-tagged AT1R or the EGFR upon AngII stimulationusing co-immunoprecipitation were inconclusive (data not shown).

We demonstrate that inhibition of CHKA with CK37, acompetitive inhibitor of CHKA activity also blunts the AT1R–

EGFR transactivation response. This is particularly interestingbecause CK37 has been shown to inhibit MAPK and PI3K–AKTsignalling, disrupt actin cytoskeleton organisation and reduce

membrane ruffling in transformed cells (Clem et al., 2011).Although no published reports link AngII and/or AT1R to CHKA,its role in lipid biosynthesis and its binding to the EGFR and

regulation of Src-mediated growth signalling are provocative,especially considering that its knockdown also impededthrombin-mediated EGFR transactivation, indicating that it

affects GPCR–EGFR transactivation more generally than justthe AT1R. Furthermore, it may suggest that spatiotemporalchanges within a cell upon stimulation with GPCR ligands play

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an essential role in GPCR-mediated EGFR transactivation,

though this will require further investigation.

In conclusion, the present study screened 720 kinase genes toidentify critical signalling molecules controlling AT1R–EGFRtransactivation that were potentially druggable, which would

facilitate subsequent studies to test their importance inpathophysiological states associated with dysregulated AT1Rsignalling. Using this approach, we have uncovered a suite of

new signalling targets involved in AT1R–EGFR transactivationand have also confirmed that the EFGR–ErbB2–PKC–PI3K–MAPK signalling axis is important in AT1R–EGFR

transactivation. In particular, this work provides the platformfor investigating the molecular basis for TRIO, BMX and CHKAaction in AT1R–EGFR transactivation and provides proof thatgenome-wide approaches can offer powerful new insights into

this process and permit the assembly of the AT1R–EGFRtransactivation ‘interactome’, which is increasingly appreciatedas an important mediator of cell and tissue function.

Materials and MethodsCell lines and culturing

Human mammary epithelial cells immortalised with human telomerase (hTERT)and transformed with SV40 Large T and small t antigens (HMEC-LST, HMEC-HMLE) were a gift from Professor Robert Weinberg (Whitehead Institute forBiomedical Research, Massachusetts Institute of Technology). HEK293T cellswere obtained from Open Biosystems (Thermo Fisher Scientific, Scoresby,Australia). Unless otherwise specified, media and tissue culture consumables wereobtained from Gibco BRL (Life Technologies, Mulgrave, Australia). HMEC-LSTand HMEC-HMLE cells were maintained in HuMEC ready medium containingHuMEC growth supplements and bovine pituitary extract (no. 12752-010). Forserum starvation experiments, cells were washed with Dulbecco’s phosphate-buffered saline (PBS, pH 7.4) and serum starved with HuMEC basal medium (no.12753-018). Unless otherwise indicated, HuMEC media (ready or basal) weresupplemented with 50 mg/ml gentamicin. HEK293T cells were grown in DMEMwith 20 mM HEPES, 10% FBS and antibiotic-antimycotic solution. HMEC-LST,HMEC-HMLE and HEK293T cell lines were maintained in vented flasks (BectonDickinson, North Ryde, Australia) in a humidified incubator at 37 C with 5% CO2.Unless otherwise stated, incubation steps for cell culture assays were performed at37 C with 5% CO2. Cell number was determined using a Z2 Cell and ParticleCounter (Beckman Coulter, Lane Cove, Australia). Specific details for passagingthe HMEC cell lines are given in supplementary material Table S1.

Retroviral construct generation

The cloning of pRc/CMV/NHA-AT1A, a vector encoding the N-terminally HA-epitope-tagged rat angiotensin type Ia receptor cDNA has been describedpreviously (Thomas et al., 1998). The pRc/CMV/NHA-AT1A plasmid wasdigested with HindIII and the NHA-AT1A cDNA was subcloned into the HindIIIsite of the pBluescript KS2 plasmid (Stratagene, Agilent Technologies, Mulgrave,Australia). The pBluescript KS-NHA-AT1A plasmid was digested with BamHI andXhoI to liberate the HindIII-flanked NHA-AT1A cDNA, which was inserted intothe MSCV-IRES-mCherry vector (a gift from Dr Sarah Russell, Peter MacCallumCancer Centre, Melbourne, Australia) to generate the MSCV-IRES-NHA-AT1A

(AT1R) plasmid.

Generation of stable cell lines

HEK293T cells were co-transfected with MSCV-IRES-mCherry (mCherry, vectorcontrol) or receptor-containing MSCV-IRES-NHA-AT1A (AT1R) plasmids in thepresence of an amphotrophic packaging vector (Dr Phillip Darcy, PeterMacCallum Cancer Centre, Melbourne, Australia) at a 2:1 ratio. Viralsupernatant was filtered through a 0.45 mm Minisart filter (Sartorius Stedim,Dandenong South, Australia) and Sequabrene (Sigma-Aldrich, Castle Hill,Australia) was added at a final concentration of 4 mg/ml before addition totarget cells. Cells were exposed to fresh viral supernatant three times over24 hours, grown to ,80% confluency and passaged twice prior to fluorescence-activated cell sorting (FACS) using the FACS Vantage SE Diva (BD Biosciences).

Antibodies, ligands and inhibitors

Angiotensin II (human; no. 2078) and endothelin-1 (no. 2110) was purchased fromAuspep (Tullamarine, Australia), and human EGF (no. 100-15) was purchasedfrom Peprotech (Rocky Hill, NJ, USA). Thrombin (human plasma, high activity,no. 605195), CK37 (no. 229103) and AG1478 (no. 658552) were obtained fromCalbiochem (Merck Millipore, Kilsyth, Australia). NSC-23766 (no. 2161) was

obtained from Tocris Bioscience (Abacus ALS, East Brisbane, Australia). TotalEGFR (sc-03), total ERK 1 (sc-93), ChoK (sc-376489) and RhoA (sc-418)antibodies were obtained from Santa Cruz Biotechnology (Dallas, TX, USA). Rac1antibody (05-389) was purchased from Merck Millipore. Phospho-p44/42 MAPK(ERK1/2; no. 9106), total EGFR (no. 4267), phospho-AKT (Ser473) (no. 4058)and total AKT (no. 9272) antibodies were purchased from Cell SignallingTechnologies (Danvers, MA, USA). Phospho-EGFR (pY1068; no. 44-788G) andanti-HA (high affinity, no. 1867423001) were purchased from Life Technologiesand Roche (Castle Hill, Australia) respectively. 17-b-oestradiol (no. E8875) andanti-a-tubulin (no. T5168) were obtained from Sigma Aldrich. Goat anti-rabbitIgG (H+L) HRP conjugate (no. 170-6515) and anti-mouse IgG (no. 170-6516) werepurchased from Bio-Rad (Gladesville, Australia), and polyclonal rabbit anti-ratimmunoglobulin/HRP (P0450) was purchased from DAKO (Campbellfield,Australia). Alexa Fluor 488 goat anti-rat antibody (no. A-11006) was obtainedfrom Molecular Probes (Life Technologies). Candesartan cilexetil was a gift fromAstra Zeneca (North Ryde, Australia).

GPCR–EGFR transactivation assays

HMEC-LST cells were seeded into cell culture or microplates and incubated for24 hours at 37 C with 5% CO2, then serum starved in HuMEC basal medium for24–48 hours prior to stimulation. For experiments involving inhibitors, cells werepre-treated for 30 minutes at 37 C with either AG1478 (5 mM), candesartancilexetil (1 mM), CK37 (10 mM) or NSC-23766 (100 mM). Cells were stimulatedwith 100 nM AngII (or 10 nM thrombin) for specified times at 37 C prior toharvesting. The AlphaScreen SureFire phospho-ERK 1/2 assay (TGR Biosciencesno. TGRES10K, Thebarton, Australia; Perkin Elmer no. 658552, Glen Waverley,Australia), a high-throughput microplate-based ERK1/2 activation assay describedin the literature (Osmond et al., 2005) was performed as per the standard protocol,details of which can be found in the MIARE (minimum information about anRNAi experiment) in supplementary material Table S1.

siRNA screening and siRNA transfections

A detailed methodology for siRNA screening is outlined in supplementary materialTable S1, and primary and secondary siRNA screen data in supplementary materialTables S2 and S3. Data is also publically available in the PubChem BioAssaydatabase (http://pubchem.ncbi.nlm.nih.gov) (Wang et al., 2012). siGENOMESMARTpool siRNAs to rat Agtr1a (M-093349-00), human GNAQ (M-008562-00), EGFR (M-003114-03), BMX (M-003106-04), CHKA, (M-006704-01), TRIO(M-005047-00), RAC1 (M-003560-06), RHOA (M-003860-03) and the GFPduplex (D-001300-01) were obtained from Dharmacon RNAi Technologies(ThermoFisher Scientific) and resuspended in 16Dharmacon siRNA buffer priorto use. For siRNA validation (quantifying mRNA knockdown and determining theeffect of knockdown on transactivation), conditions outlined from the siRNAscreen were scaled up to a 12-well plate format to harvest protein and/or RNA.Briefly, 40 nM Dharmacon SMARTpool siRNA or 25 nM DharmaconSMARTpool deconvoluted siRNA (individual duplex) were complexed for20 minutes at ambient temperature in a 200 ml volume of HuMEC basal mediumwith a final concentration of 1 ml per well of DharmaFECT 1 transfection lipid(ThermoFisher Scientific). HMEC-LST-AT1R cells (,100,000) in antibiotic-freeHuMEC complete medium (800 ml volume) were seeded into each well along withthe complexed siRNA and incubated for 24 hours. For RNA experiments, RNAwas extracted from cells at a 24-hour knockdown (see RNA extraction and cDNAsynthesis section for details). For protein analysis, after a 24-hour knockdown,wells were washed once with Dulbecco’s PBS (pH 7.4), cells were serum starvedfor 48 hours in HuMEC basal medium (total 72 hour knockdown) prior tostimulation with AngII for 10 minutes at 37 C, and protein was harvested.

Protein extraction, SDS-PAGE and western blot analysis

Cells were washed twice with ice-cold PBS and harvested in ice-cold RIPA buffer[50 mM Tris-HCl pH 7.5, 100 mM NaCl, 2 mM EDTA, 50 mM sodium fluoride,0.1% (w/v) SDS, 0.5% (w/v) sodium deoxycholate, 1% (v/v) Triton X-100, 10 mMsodium pyrophosphate, 10 mM sodium orthovanadate] containing CompleteEDTA-free protease inhibitor cocktail (Roche). Cells were gently lysed for1 hour at 4 C and centrifuged at 15,000 g for 15 minutes at 4 C. Proteinconcentration was determined using the DC protein assay kit (Bio-Rad) inmicroplates as per the manufacturer’s instructions. For the resolution of all proteins(apart from the AT1R), protein samples were mixed with Laemmli sample buffer(Laemmli, 1970) containing 8% b-mercaptoethanol and heated at 95 C for5 minutes. To resolve the AT1R, freshly prepared lysate was mixed at a 1:1 ratiowith 62.5 mM Tris-HCl (pH 6.8), 2% (w/v) SDS, 6 M urea, 10% b-mercaptoethanol and 20% glycerol and heated to 60 C for 15 minutes. Sampleswere electrophoresed on Tris-glycine SDS-PAGE gels, and protein transferred toPVDF membrane (Immobilon-P, Merck Millipore). Membranes were blocked with5% low-fat milk (Diploma, Fonterra Foodservices, Mount Waverley, Australia) or1% BSA (Sigma-Aldrich) in Tris-buffered saline (TBS) pH 7.6 containing 0.05%(v/v) Tween 20 (TBST). Antibodies were prepared in either 5% low-fat milk or 1%BSA in TBST. Membranes were washed with TBST and treated with the relevantsecondary antibody in 5% low-fat milk or TBST. Membranes were developed

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using Western Lightning ECL Plus (Perkin Elmer) to Hyperfilm (GE Healthcare,

Rydalmere, Australia).

Immunofluorescence to detect AT1R expression

HMEC-LST cells (150,000) in HuMEC complete medium were seeded into

chamber slides (Nunc Lab-Tek II, 4 chamber, BD Biosciences) and incubated for

24 hours. Chambers were washed with PBS, fixed with 4% PFA, blocked in 1%

BSA and treated with 40 ng/ml of anti-HA high-affinity antibody in 1% BSA.

Chambers were washed with PBS containing 0.05% Tween 20 (PBST). AlexaFluor 488 goat anti-rat antibody (Molecular Probes) in 1% BSA was added to each

well (protected from light). Nuclei and cell membranes were counterstained with

DAPI (Sigma-Aldrich) and Cell Mask-Alexa Fluor 647 (Life Technologies),

respectively. Slides were mounted in Vectashield (Vector Labs, Burlingame, CA,

USA) with a coverslip, and sealed prior to use. Confocal images (Z-stacks at 2 mm

intervals) were obtained with the Nikon C2 confocal microscope using the NIS

elements AR.3.2 program (Nikon Instruments, Melville, NY, USA) with a 406objective. Z-stack images were imported into NIH ImageJ (version 1.44o,available online at http://imagej.nih.gov/ij) (Abramoff et al., 2004). The maximum

intensity of each stack for each channel (3 channels in total) was obtained, images

were smoothed and despeckled and a scale bar added. ‘‘RGB channel merge’’ was

used to merge the respective channels. Individual images and a three channel

merged image are shown in supplementary material Fig. S1.

Radioligand competition binding assay

For competition radioligand binding assays, 500,000 HMEC-LST-AT1R or control

mCherry-expressing cells were seeded into 24-well plates, and allowed to adhere

for 24 hours. Culture medium was replaced with unlabelled AngII and

330,000 cpm of [125I]AngII (Prosearch International, Malvern, Australia),

diluted in OptiMEM (Life Technologies) supplemented with 1% BSA, wasadded and incubated at ambient temperature for 1 hour. Wells were washed with

PBS and cells solubilised with 500 ml 0.1 M NaOH. Radioactivity was counted

using a 2470 Wizard 2 Automatic Gamma Counter (Perkin Elmer). Data for the

displacement of bound radiolabelled [125I]AngII by unlabelled AngII was

collected. Concentrations of unlabelled AngII were assayed in triplicate wells

and averaged for four independent experiments. Relative protein concentration in

each well was determined using the DC protein assay kit (Bio-Rad) as per the

manufacturer’s instructions, and the relative number of binding sites per amount ofprotein (pmol receptor/mg cellular protein) calculated.

Calcium mobilisation assay

Cells were seeded at a density of 100,000 cells/well into 96-well plates pre-coated with poly-L-lysine, and incubated for ,5 hours. Cells were washed with

PBS and serum starved overnight. The following day, cells were loaded with

2.9 mg/ml of Fluo-4AM (0.3 mg/well) in assay buffer (HBSS, 20 mM HEPES,

2.5 mM probenecid, pH 7.4) for 45 minutes at 37 C, protected from light. Wells

were washed once with assay buffer and de-esterified for 30 minutes at ambient

temperature, protected from light. Prior to stimulation with AngII, background

fluorescence of cells was imaged for 10 seconds on the FLIPR Tetra (Molecular

Devices, Sunnyvale, CA, USA). AngII (diluted in the assay buffer at various

concentrations) was added using the FLIPR Tetra and fluorescence was measuredfor a total of 250 seconds/well. Data was analysed using the FLIPR Tetra

Software (Screenworks 3.1.0.3, Molecular Devices) to calculate Max-Min (10–

250 seconds) values, then data plotted into GraphPad Prism 5.0d (Graphpad

Software, La Jolla, CA, USA) to fit curves using non-linear regression.

Concentrations of AngII were assayed in triplicate wells in each independent

experiment. To perform calcium mobilisation with siRNA knockdown, the

protocol was performed as described above with the following modifications:

HMEC-LST-AT1R cells (50,000 cells/well) were reverse transfected with 40 nMDharmacon SMARTpool siRNA and 0.1 ml DharmaFECT 1 (per well; duplicate

plates for each condition) and incubated for 24 hours. At 24 hours, RNA was

extracted from eight wells of one plate and pooled to assess target knockdown

(described below). The second plate was serum starved for 48 hours (72 hour

knockdown) prior to Fluo-4AM loading and proceeding with the assay as

described. Data are displayed as the percentage change in fluorescence (DF) over

baseline fluorescence (F0).

RNA extraction and cDNA synthesis

Cell monolayers were washed with ice-cold PBS, and RNA extracted using the

Bioline Isolate RNA mini kit (Bioline, Alexandria, Australia) as per manufacturer’s

instructions. RNA was eluted from columns with 40 ml of RNase-free H2O and theconcentration determined using the Nanodrop ND-1000 spectrophotometer (Thermo

Scientific). RNA was stored at 280 C until use. For cDNA synthesis, up to 400 ng

RNA was treated with 1 Unit of RQ1 RNase-free DNase (Promega, Alexandria,

Australia) for 30 minutes at 37 C, then reverse transcribed for 1 hour at 50 C using

the Superscript III kit (Invitrogen, Life Technologies) with random primers

(Promega). cDNA was stored at 220 C prior to use.

Primers and real-time quantitative PCR

Primers for real-time quantitative PCR were designed over exon–exon junctions(where possible) using NCBI Primer Blast (Primer3) (http://www.ncbi.nlm.nih.gov/tools/primer-blast) (Rozen and Skaletsky, 2000) with predicted amplicon sizesranging from 110–160 bp. Sequences are listed in supplementary material TableS4. Primers were obtained from Geneworks (Hindmarsh, Australia), resuspendedin sterile H2O and stored at 220 C prior to use. For real-time PCR analysis, FastSYBR Green Master Mix (Applied Biosystems, Life Technologies), cDNAtemplate and 300 nM of forward and reverse primers in a final reaction volume of20 ml was assayed. Samples were run on the Applied Biosystems StepOne Real-Time PCR System for 40 cycles using the default machine settings with a meltcurve ramp of 0.7 C. Data was analysed using the 7000 SDS 1.1 RQ Software(Applied Biosystems) where relative quantification of gene expression wasperformed and gene expression was normalised to GAPD expression.

STRING analysis

STRING 9.0 (http://string-db.org), a publically available online database of functionalprotein interactions (Szklarczyk et al., 2011) was used to generate an AT1R–EGFRtransactivation ‘interactome’. The secondary siRNA screen gene list was submitted tothe database using the ‘high confidence interactions’ option. Data were redrawn inAdobe Illustrator CS5 (Adobe Systems, San Jose, CA, USA) to incorporate theconfidence level of each target identified from the siRNA screen. Thicker connectinglines (linking the nodes) represent increasing confidence of interactions.

Densitometry analysis

Densitometry analysis of western blot data (scanned to TIFF format) wasperformed using NIH ImageJ 1.44o software (Abramoff et al., 2004). The densityof phospho-EGFR (pY1068) or phospho-ERK1/2 bands were normalised to tubulinband density for each sample. Data was imported into Microsoft Excel (Microsoft,Redmond, WA, USA), and graphs drawn in GraphPad Prism 5.0d.

Statistical analyses

The statistical analyses performed for the siRNA screen are outlined insupplementary material Table S1. Data was analysed using paired two-tailedStudent’s t-tests within the GraphPad Prism 5.0d program. Unless otherwisedescribed, data presented graphically are the means 6 standard error of the mean(s.e.m.), with statistical significance set at P,0.05.

AcknowledgementsOur thanks to Mr Ralph Rossi and Ms Viki Milovak (FACS), Dr JillianDanne (confocal microscopy), Ms Alison Boast, Ms Analia Lesmanaand Ms Anna-Kristen Szubert (technical assistance), Associate ProfessorPhillip Darcy and Dr Sarah Russell (plasmid constructs) and DrKatherine Hannan (proofreading manuscript) (all at Peter MacCallumCancer Centre, Melbourne, Australia). Thanks to Professor RobertWeinberg (Whitehead Institute for Biomedical Research, MassachusettsInstitute of Technology, USA) for providing HMEC cell lines.

The Victorian Centre for Functional Genomics is funded by theAustralian Cancer Research Foundation (ACRF), the VictorianDepartment of Industry, Innovation and Regional Development(DIIRD), the Australian Phenomics Network supported by fundingfrom the Australian Government’s Education Investment Fundthrough the Super Science Initiative, the Australasian GenomicsTechnologies Association (AMATA) and the Brockoff Foundation.

Author contributionsA.J.G designed, performed and analysed the siRNA screening andvalidation experiments and wrote the manuscript; B.W.P performed theradioligand binding and intracellular calcium mobilisation assays andreviewed the manuscript; C.M.G performed the informatics analyses;D.W.T and Y.H assisted with assay design and siRNA screening;G.A.Q-R assisted with siRNA knockdown and calcium mobilisationassays; K.A.M and H.Q assisted with the generation and testing of celllines; K.J.S assisted with the design and execution of the siRNA screen,discussed data and reviewed the manuscript; W.G.T and R.D.H designedthe conceptual framework of the study and experiments, analysed anddiscussed data, obtained funding for this study and wrote the manuscript.

FundingThis work was supported by the Australian National Health andMedical Research Council project grants [grant numbers 472640,

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1024726 to W.G.T. and R.D.H]; and a project grant awarded toR.D.H, funded in Australia by the Captain Courageous Foundation(http://www.captaincourageousfoundation.com). R.D.H also holdsan NHMRC senior research fellowship [grant number 1022402].

Supplementary material available online at

http://jcs.biologists.org/lookup/suppl/doi:10.1242/jcs.128280/-/DC1

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