RESEARCH ARTICLE

Focus on composition and interaction potential of

single-pass transmembrane domains

Remigiusz Worch1, Christian Bokel2, Sigfried Hofinger3,4, Petra Schwille1,2

and Thomas Weidemann1

1 BIOTEC, Biophysics Research Group, Technical University Dresden, Dresden, Germany2 CRTD, Center for Regenerative Therapies, Technical University Dresden, Dresden, Germany3 Dipartimento di Chimica ‘‘G. Ciamician’’, Universita di Bologna, Bologna, Italy4 Department of Physics, Michigan Technological University, Houghton, MI, USA

Received: March 31, 2010

Revised: August 17, 2010

Accepted: August 22, 2010

Transmembrane domains (TMD) connect the inner with the outer world of a living cell. Single

TMD containing (bitopic) receptors are of particular interest, because their oligomerization

seems to be a common activation mechanism in cell signaling. We analyzed the composition of

TMDs in bitopic proteins within the proteomes of 12 model organisms. The average number of

strongly polar and charged residues decreases during evolution, while the occurrence of a

dimerization motif, GxxxG, remains unchanged. This may reflect the avoidance of unspecific

binding within a growing receptor interaction network. In addition, we propose a new

experimental approach for studying helix–helix interactions in giant plasma membrane vesicles

using scanning fluorescence cross-correlation spectroscopy. Measuring eGFP/mRFP tagged

versions of cytokine receptors confirms the homotypic interactions of the erythropoietin

receptor in contrast to the Interleukin-4 receptor chains. As a proof of principle, by swapping

the TMDs, the interaction potential of erythropoietin receptor was partially transferred to

Interleukin-4 receptor a and vice versa. Non-interacting receptors can therefore serve as host

molecules for TMDs whose oligomerization capability must be assessed. Computational

analysis of the free energy gain resulting from TMD dimer formation strongly corroborates the

experimental findings, potentially allowing in silico pre-screening of interacting pairs.

Keywords:

Giant plasma membrane vesicles / MM/PB11 free energy calculations / Protein

sequence analysis / Scanning fluorescence cross-correlation spectroscopy / Single-

pass transmembrane receptor interactions / Technology

1 Introduction

Most polypeptide chains passing the hydrophobic core of

the membrane adopt a secondary structure like a-helix or

b-strand. While b-barrels represent a more ancient fold for

membrane embedding, the expanding group of transmem-

brane (TM) proteins in eukaryotic cells is constructed from

a-helices [1]. In multi-pass (polytopic) TM proteins, as, for

example, in photosynthetic complexes, ion pumps, chan-

nels, or transporters, bundles of up to 12 a-helices form

stable clusters in the lipid bilayer, able to precisely position

small cofactors or confining the motion path of ions or

protons. In contrast, single-pass (bitopic) TM proteins, for

example, signaling complexes, exhibit increased structural

flexibility due to the required dynamic re-organization

during activation. It is not yet clear, however, in which way

the TM regions play a role for the context-dependent

assembly in the surface membrane [2].

From a physiological point of view, it is obvious that

the collective behavior of differentiated cells in large

multicellular organisms required the emergence of a highly

Abbreviations: CC, cross-/autocorrelation amplitude ratio; ECD,

extracellular domain; EpoR, erythropoietin receptor; FCS, fluor-

escence correlation spectroscopy; FCCS, fluorescence cross-

correlation spectroscopy; GPMV, giant plasma membrane

vesicle; IL-4R, Interleukin-4 receptor; MM, molecular mechanics;

PC, positive control; sFCCS, scanning FCCS; TM, transmem-

brane; TMD, transmembrane domain

Correspondence: Dr. Thomas Weidemann, BIOTEC, Biophysics

Research Group, Technical University Dresden, Tatzberg 47/51,

01307 Dresden, Germany

E-mail: thomas.weidemann@biotec.tu-dresden.de

Fax: 149-0351-463-40324

& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com

4196 Proteomics 2010, 10, 4196–4208DOI 10.1002/pmic.201000208

diversified set of membrane receptors for cellular commu-

nication (for reviews see [3–5]). Accordingly, several novel

signaling pathways successively appeared and expanded

during evolution. For instance, in the vertebrate lineage

single-pass TM proteins of the immune system, like T-cell

receptors or cytokine receptors, have become dramatically

expanded [3, 6]. Within one and the same bitopic receptor

family (e.g. class I cytokine receptors, transforming growth

factor-b receptors) the mechanisms of receptor activation

may actually be diverse: Some follow the classical ligand-

dependent dimerization and cross-activation scheme, other

receptors oligomerize prior to ligand binding at the plasma

membrane [7–9]. Owing to their pharmaceutical impor-

tance, the members of the class I cytokine receptors

(Interleukin-2, IL-3, IL-4, etc.) have been well studied in this

regard [10]. The erythropoietin receptor (EpoR) was among

the first examples shown to exist as pre-formed dimers and

mutational analysis pin-pointed this interaction to the TM

helix as well as a flanking hydrophobic motif [11–13].

Whether members of Interleukin-4 receptor (IL-4R) form

clusters in the membrane is still controversial [14, 15].

The underlying physico-chemical reasons for trans-

membrane domain (TMD) interactions are not yet comple-

tely understood. Nevertheless, recent experimental progress

has changed the status of single-pass TM helices dramati-

cally, from being viewed merely a passive membrane anchor

toward being domains controlling oligomerization [16, 17].

Interactions of TM helices were studied by various in vitrotechniques [18] as well as by a bacteria two-hybrid TOXCAT

assay [19]. Together with a statistical analysis, it was possible

to identify some common interaction motifs, like GxxxG

[20–23] and more complex patterns like Ser/Thr clusters [24]

or QxxS-motifs [25]. Recently, the GxxxG motif was refined

[26, 27]. Placing a single polar residue into the TMD can

stabilize dimers [28] and the presence of a hydrogen bond

was shown to drive helix oligomerization in lipid bilayers

[29, 30]. Some studies pointed out the role of Trp, Tyr, Phe

involved in aromatic stacking [31] or cation-p interactions

[32]. Recently, interactions between amino acid side chains

and helices inside the biomembrane were semi-quantita-

tively described by a simple membrane mimic based on a

continuum approximation [33].

For this article we followed three lines of investigations:

(i) we asked, whether changes in physico-chemical proper-

ties of the TM helices are apparent on the primary sequence

level. To track evolutionary trends of amino acid composi-

tion, we statistically analyzed the sequences of TMDs found

in the proteomes of 12 model organisms. (ii) We propose an

experimental assay to measure TMD interactions in giant

plasma membrane vesicles (GPMVs), a close to native

membrane environment derived from transiently trans-

fected culture cells [34]. For detection we applied scanning

fluorescence cross-correlation spectroscopy (sFCCS) in its

dual color variant [35, 36]. Interactions were measured by

spectral cross-correlation of the signals arising from red and

green fluorescent protein tagged mutants of class I cytokine

receptors: IL-4Ra, IL-2Rg, and EpoR. In addition, we

performed a domain swap experiment between IL-4Ra and

EpoR in order to see whether the interaction potential could

be transferred with the TMD, thus, generating proof of

principle for a generic method of experimentally testing

TMD interactions. (iii) Finally we modeled the interaction

propensity of the TMD pairs, i.e. IL-4Ra, IL-2Rg, IL-13Ra1,

and EpoR by theoretical calculations (MM/PB11) based on

the combined effects of the force field and the solvation free

energy of the complex in a layered model biomembrane

mimic [33, 37].

Our bioinformatic results point towards the avoidance of

strongly polar and charged amino acids in the course of

evolution, and hence, the importance to restrict unspecific

binding potentials within a growing receptor interaction

network. Experimentally, we show for the first time that

neither IL-4Ra nor IL-2Rg by themselves oligomerize in the

membrane, while the interaction potential of EpoR was

found to be significant. TMD swap experiments verified

that the interaction potential of EpoR can be partially

transferred to the non-oligomerizing IL-4Ra chain, indicat-

ing that the EpoR core TMD indeed mediates receptor self-

association. These experimental results were in excellent

agreement with our model calculations in which EpoR

homodimers are found to be the only sample showing

significant free energy gain upon dimer formation inside

the biomembrane.

Our data suggest to potentially generalize this approach

by using short IL-4Ra receptors as host molecules to

experimentally assess larger collections of TMD interactions

in GPMVs. Since our modeling approach showed remark-

able consistence to our experimental results, we envisage a

broader application for in silico screening even on the

proteome level.

2 Materials and methods

2.1 Bioinformatic analysis

The databases of transmembrane (TM) regions were

created by downloading the sequences of proteins having

‘‘TRANSMEMBRANE’’ annotation in Uniprot service

(www.uniprot.org, UniProt Release 2010_05, April 20,

2010) or by using the prediction algorithm TMHMM2.0

(http://www.cbs.dtu.dk/services/TMHMM/) [38], taking the

complete proteome sequences as an input. Homology

cleanup was implemented by determining the redundancy

level (50 and 90%) directly in UNIPROT.

The bitopic TM proteins were extracted by using the

keyword (type:transmem count:1) in UniProt or by

TMHMM2.0 selecting the sequences having one TM helix

(PredHel 5 1). Signal peptides were excluded from the

analyzed data sets (default in Uniprot database) or by not taking

into consideration the TM regions predicted by TMHMM2.0

starting within the first 30 N-terminal amino acids.

Proteomics 2010, 10, 4196–4208 4197

& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com

The composition analysis was performed with sequences

of normalized length of 19 amino acids (90% homology),

which were selected by taking the region of maximal

hydrophobicity, using four different scales: Kyte and

Doolittle [39], GES scale [40], Wimley and White [41] toge-

ther with the experimental amino acid insertion efficiency

[42]. All four gave similar results thus the data set was finally

prepared following the GES scale. For this purpose, scripts

in Python (www.python.org) were developed. Functions of

single-pass TM proteins were obtained from Gene Ontology

assignment in UniProt. More general categories were

assigned using ‘‘Ancestor Charts’’ in Gene Ontology data-

base on the European Institute of Bioinformatics server

(www.ebi.ac.uk).

2.2 Genetic engineering of the constructs

The coding sequences for human IL-4Ra transcription

variant 1 (NCBI; GI: 56788409) and human IL-2Rg (NCBI;

GI:4557881) were amplified from cDNA derived from

human dendritic cells by PCR using the HindIII/BamHI

containing primer pairs (all oligos in 50430 direction) CCC

AAGCTT GCCACC ATG GGG TGG CTT TGC TCT G and

CG GGATCC CG AGA GAC CCT CAT GTA TGT GG for

IL-4Ra and CCC AAGCTT GCCACC ATG TTG AAG CCA

TCA TTA CCA T and CG GGATCC CG GGT TTC AGG

CTT TAG GGT GT for IL-2Rg. The coding sequences for

EpoR (NCBI; GI: 4557561) was purchased (pF1KB5941,

Kazusa DNA Res. Inst., Japan). A hexahistidine-tag was

introduced for IL-4Ra and IL-2Rg between the signal

peptide and the coding sequence after position 1 (initial

Met, mature numbering) by site-directed mutagenesis

(Gene Tailor, Invitrogen) as described [43]. We removed the

start codon and Kozak sequence of the EGFP in pEGFP-N1

coding sequence (NCBI; GI:1377911, Clontec) by amplifying

EGFP with the primer pair CGC ACC GGT CGT GAG CAA

GGG CGA GGA G and ATA AGA ATG CGG CCG CTT

TAC TTG TAC AG followed by AgeI/NotI directed reinser-

tion into the same vector, called pEGFP-N2. An expression

vector for the cytoplasmic deletion mutant pNHis-

IL4Ram266-EGFP-N2 coding for the amino acids M-His6-

IL4R(2-266)-ADPPV-EGFP(2-239) (mature numbering,

‘‘m266’’ indicating a truncation after amino acid 266) was

created using the BamHI containing reverse primer CG

GGATCC CG GGA CCG CTT CTC CC. From pNHis-

IL4Ram266-EGFP-N2, the open reading frame was excised

via HindIII/NotI and subcloned into pcDNA5/FRT (Invi-

trogen) to generate pcFRT-NHis-IL4Ram266-EGFP-N2. The

FRT landing site contained in this plasmid was not used for

this study. To lower the expression levels, we introduced the

early SV40 downstream of the CMV promoter by amplifying

the SV40 ‘‘HindIII-fragment’’ from pSV-mRFP1-EGFP [44]

and subcloning into pcDNA5/FRT using the NheI/HindIII

containing primers CTA GCTAGC TGT ACG ACGCGT

AGC TTG AGA AAT GGC ATT and CCC AAGCTT AGC

TTT TTG CAA AAG CCT AG. The vector system containing

both, CMV and a downstream SV40 promoter was called

pc2. In pc2-NHis-IL4Ram266-EGFP-N2, the EGFP was

replaced by mRFP1 (NCBI; GI:21464837) using the AgeI/

NotI containing primer AT ACCGGT CGG TGC TGG AGC

CTC CTC CGA G and GCGGCCGC TTA GGC GCC GGT

GGA GTG GCG GCC. The short versions NHis-IL-

4Ram241 and NHis-IL-2Rgm291 were created by subclon-

ing into pc2 via HindIII/BamHI using the gene-specific

forward primer mentioned above together with the reverse

primers CG GGATCC GC TCC AGC TCC AAT CTG ATC

CCA CCA TTC TTT C and CGC GGATCC GC TCC AGC

TCC CAC ACC ACT CCA GGC CGA AA, respectively. The

short version of EpoRm259 in pc2 was cloned accordingly

using CCC AAGCTT GCC ACC ATG GAC CAC CTC GGG

GCG and CGC GGATCC GC TCC AGC TCC CCA GAT

CTT CTG CTT CAG AG.

For the swap of the TMDs, the extracellular domains

(ECDs) of the EpoR and IL4Ra were amplified with the

gene-specific forward primers and the reverse primers GGG

GTC CAG GTC GCT AGG CGT CAG and GAG CGT CAG

GAT GAG GTG CTG CTC GAA GGG, respectively. Sepa-

rately, the TMD of the EpoR was amplified using the

primers CCC TTC GAG CAG CAC CTC ATC CTG ACG

CTC and TTC TTT CTT AAT CTT GGT GAG CAG CGC

GAG, and the TMD of the the IL4Ra chain using the

primers CCTA GCG ACC TGG ACC CCC TCC TGC TG

and AGC CCG GCG GTG GGA GAT GCT GAC ATA GCA.

The resulting PCR products contain the TMD and

several bases from flanking intra- and ECDs of the respec-

tive other receptor chain. Separately, the short intracellular

domains of the EpoRm259 and IL-4Ram241 were

amplified using the gene-specific reverse primers listed

above and the forward primers AGC CCG GCG GTG

GGA GAT GCT GAC ATA GCA and GCG CTG CTC

ACC AAG ATT AAG AAA GAA TGG, respectively. The

intra- and ECDs of each receptor were then fused to the

TMD of the respective other receptor by two rounds of

fusion PCR. The resulting PCR products were then inserted

into pc2 vectors upstream of EGFP or mRFP using the

BamHI and HindIII sites, thus generating pc2-NHis-IL4R-

EpoRTMD-EGFP-N2, pc2-NHis-IL4R-EpoRTMD-mRFP

as well as pc2-EpoR-IL4RaTMD-EGFP-N2 and pc2-EpoR-

IL4RaTMD-mRFP.

The membrane-associated GFP-mRFP positive control

(PC) was generated by excising EGFP fused to tandem

N-terminal Lyn myristoylation–palmitoylation sites from

pCS2-2xmemGFP (plasmid gift of M. Nowak, Dresden) and

cloning the fragment into pc2SV using HindIII/NotIrestriction sites, the pc2SV-versions comprising the pc2

vector backbone from which the CMV promoter was excised

via MluI. The mRFP1 ORF including a GAGA amino acid

linker was then amplified using the BsrGI and NotIrestriction site containing primers CTG TAC AAG GGA

GCT GGA GCA GCC TCC TC GAG and GCG GCC GCT

TAG GCG CCG GTG GAG TGG CGG CC and c-terminally

4198 R. Worch et al. Proteomics 2010, 10, 4196–4208

& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com

fused to GFP using BsrGI/NotI, thus generating pc2SV-

2xmemGFP-mRFP.

2.3 GPMV formation

GPMVs were formed using the method described by Scott

et al. [45, 46], modified by Baugmart [34]. 16� 103 HEK293T

cells/well were seeded in a chambered 8-well cover glass

] 1.5 (Lab Tek, Nunc) and transfected on the following day.

Transfection was done with Lipofectamine 2000 (Invitrogen)

and OptiMEM-I (Gibco) according to the manufacturers

protocol using 100–120 ng DNA for the GFP construct and

100–150 ng DNA for the mRFP construct to compensate

asymmetric expression. Twenty-four hours later, the cells

were washed once with HEPES pH 7.4 containing 150 mM

NaCl and 2 mM CaCl2 and GPMVs were induced by adding

the same buffer containing 2 mM DTT, 25 mM formalde-

hyde supplemented with EDTA free protease inhibitor mix

Complete (tablets, Roche). Cells were incubated overnight at

371C and measurements were carried out the following day

in the same buffer.

2.4 Antibody staining

Purified anti-IL4Ra monoclonal antibodies (clone M10.1,

Beckton Dickinson, ] 552472) were randomly labeled with

Cy5.5 Mono NHS Ester (Amersham, ]PA15101). 800mL

containing 0.4 mg of Ab were dialyzed against 2� 500 ml

100 mM NaHCO3, pH 8.4 in D-tubes (Novagen, MWCO

3.5 kDa, ] 71506-3). The lyophilized dye was dissolved in

DMSO to 9 mM from which 0.73mL was added under stirring

to a 400mL aliquot of dialyzed M10.1 (five-fold molar excess).

After gel filtration using Nap5 (GE Healthcare) the fractions

were diluted 1:50 and measured by fluorescence correlation

spectroscopy (FCS). Fractions containing 480% of a slow

diffusing species (360ms versus 50ms for Cy5) were pooled.

Comparing protein absorption at 280 nm (IgG 1 mg/mL

�1.35 Abs) with 650 nm for Cy5 (e5 250 000 M�1 cm�1)

returned a labeling stoichiometry of 1.1. SDS-PAGE analysis

under non-reducing conditions showed that 90% of the anti-

bodies occur as dimers [47]. For experiments with blebs, Anti-

IL4Ra-Cy5 was administered in a final concentration of 28mg/

mL. Cross-linking of hexahisidine-containing receptors in

blebs was done applying 6.6mg/mL mouse anti-pentahistidine

antibody (] 34660, QIAgen, Germany). Blebs were incubated

with antibodies 30 min before the FCS measurements.

2.5 Confocal imaging and scanning FCS

measurements

Imaging and scanning FCS measurements were performed

using the Zeiss ConfoCor3 system with a C-Apochromat

� 40, numerical aperture (NA) 1.2 water immersion objective

at room temperature. A dichroic mirror (NTF 545) and filters

(BP 505–530 for green, BP560–610 for red) were used to split

the eGFP/mRFP emission into two detection channels. For

sFCCS measurements, the fluorescent blebs were first

imaged and a scanning path was positioned perpendicular to

the equatorial membrane with a pixel time of 1.536 ms (zoom

12, maximum scan rate, sequential scanning for each color).

The intensity was measured by continuously scanning the

bleb for 300–500 s while the photon arrival times were

recorded in photon mode with an external USB hardware

correlator Flex 02-01D (http://correlator.com). Data analysis

was performed as described previously [35, 36] using a home-

developed software in Matlab (MathWorks). In brief, the

continuous signal was aligned according to the maximum

intensity, reflecting the membrane position on the scan path.

The maximum and adjacent pixels of each scan were aver-

aged and the resulting intensity trace correlated over time.

The correlation curves were fitted with a 1-component,

2-dimensional diffusion model:

GðtÞ ¼1

N11

ttd

� ��1

ð1Þ

where N 5 G�1(0) denotes the average number of observed

particles in the detection volume. We normalized the cross-

correlation by the simultaneously measured autocorrelation

amplitude of the more abundant color CC ¼ Gccð0Þ=Ga;tð0Þ;

t indexing the color channel (t 5 green or t 5 red). The

meaning of CC for different binding models was discussed

[48, 49]. To calibrate for instrumental limitations, we

rescaled the CC values with respect to a PC, a tandem eGFP-

mRFP polypeptide, for which the maximum CC in each

experimental session was taken as 100% (‘‘normalized

CC’’). This procedure assumes the absence of any spectral

cross-talk as it is given for alternating excitation schemes.

The diffusion times derived from Eq. (1) were calibrated by

measuring a standard solution of free AlexaFluor488 and

using the diffusion coefficient Dt;A488 ¼ 414 mm2=s accord-

ing to Dt ¼ Dt;A488tdiff=tdiff;A488 [50]. Measuring eGFP/

mRFP-tagged interacting single-pass TM receptors

produced CC values scattering between 0 and a saturating

maximum. In order to compare different constructs we

quantified the magnitude of CC by averaging the upper

third of measured values, rescaled with respect to CC

obtained for the eGFP-mRFP tandem, and displayed their

average with standard deviations (n46; Fig. 4D).

2.6 Theoretical calculations

Models for a-helical TMDs were set up for IL4Ra (P24394:

233-256), IL2Rg (P31785: 263-283), IL13Ra1 (P78552:

344–367), and EpoR (P19235: 251–273). N/C terminal resi-

dues were masked with standard protection groups

ACE/NME. The TMDs were placed in the membrane

so that the N-terminal residue points along the x-axis (in

the membrane plane) and the helical axis is oriented in

Proteomics 2010, 10, 4196–4208 4199

& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com

direction of the membrane normal z. The TMD was dupli-

cated (homo-dimers) or combined with a second TMD

(hetero-dimers) and both monomers were positioned side-

by-side such that N-terminal residues face each other. The

‘‘quasi-cylindrical’’ extension of TMDs is assumed to have a

diameter of 11 A and about half of the radial extension

becomes penetrated by neighboring residues. TMD mono-

mers were rotated individually in a-helical-characteristic

increments of 1051. Emerging TMD-TMD geometries were

minimized (2000 steps of steepest descent using AMBER

parameters [51] and all relaxed structures became subject to

the molecular mechanics (MM)-Poisson–Boltzmann surface

area (PBSA) approach for estimation of interaction energies

neglecting entropic contributions [37]. In contrast to

previously published approaches [37], the PBSA term was

replaced with the multiple continua approach established to

mimic biomembrane environments: aqueous domain

modeled by water, polar head group domain modeled by

ethanol, hydrophobic core domain modeled by cyclohexane

(MM/PB11) [33]. Any partial term of the analysis describes

the consequences of forming a TMD-dimer minus having

two separated TMDs in isolated configuration.

3 Results

3.1 Abundance and function of single-pass TM

proteins

We assembled a comprehensive set of TMDs in UniProt and

found that the proteomes of different model organisms

contain varying numbers of single-pass TM proteins. The

percentages, calculated as the ratio of single-pass to the total

number of TM proteins, were �15% for bacteria, 30–40%

for lower eukaryotes, and increased to over 40% in the case

of mammals (Fig. 1A). Applying a homology filter (50 and

90%) had only a minor effect and did not change the overall

increasing trend. The obtained ratios correspond well with

reported percentages, 12–22% for bacteria and 30–40% for

eukaryota, averaged over many species [23].

Based on gene ontology, single-pass TM proteins show a

clearly distinguished pattern of functional categories asso-

ciated with unicellular and multicellular organisms, even

across the border separating pro- from eukaryotic kingdoms

(Fig. 1B). For unicellular organisms (E. coli and S. cerevisiae)

around 20% of the single-pass TM proteins are involved in

transport, �10% associate with external responses, and the

remaining annotated functions belong to a class termed

other metabolic processes. At the coarse level of gene

ontology, the difference between pro- and eukaryotic orga-

nization is almost invisible; reflected by 2% belonging to

regulation and development in yeast. In contrast, the

evolutionary step towards multicellular organization clearly

required a variety of novel functions related to intercellular

communication, such as: cell adhesion, signal transduction

and other multicellular organismal processes. While cate-

gories covering cell adhesion, multicellular processes, and

regulation and development deal with body architecture and

formation, immune responses, the distinction of self and

non-self, emerges as a new requirement for multicellular

organisms.

3.2 Composition of single-pass TM helices

To see whether the dramatic functional broadening is

reflected on the sequence level, we performed statistical

composition analysis of singe-pass TM regions. We eval-

uated the frequency of TM-contained amino acids belonging

to one of three classes: polar (Ser, Thr, Tyr, Asn, Gln, His,

Arg, Lys, Asp, Glu), ‘‘strongly polar’’, for which Ser, Thr,

and Tyr were excluded, and charged (Arg, Lys, Asp, Glu; His

was treated as neutral). Throughout the taxa, most TMDs

(ca. 90%) contain at least one polar residue (Fig. 2A). When

only strongly polar residues are considered the overall

frequency drops to about 40%. However, these values varied

markedly between the studied proteomes: TMDs containing

strongly polar side chains were most common in yeast,

while the lowest values were found for mammals (Fig. 2B).

A similar trend was observed for the class of charged

residues (Fig. 2C).

immunologymulti-organismalresponse to stimulicell adhesionregulation and development

other metabolic processestransportnot characterized

E. coli S. cerevisiae D. melanogaster H. sapiens

A

B

50

40

30

20

10

0

Abu

ndan

ce [%

]

S. c

erev

isia

e

E. c

oli

B. s

ubtil

lis

S. p

ombe

A. t

halia

na

C. e

lega

ns

D. m

elan

ogas

ter

D. r

erio

X. l

aevi

s

M. m

uscu

lus

R. n

orve

gicu

s

H. s

apie

ns

50 %90 %

Figure 1. (A) Abundance of single-pass TM proteins in the

analyzed proteomes of 12 different organisms calculated for two

levels of sequence redundancy (50 and 90%). (B) Relative

distribution of the assigned functional categories within the

single-pass TM proteins of selected organisms.

4200 R. Worch et al. Proteomics 2010, 10, 4196–4208

& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com

In addition to single amino acids we also analyzed the

abundance of the GxxxG motif, one of the best characterized

examples for a TM binding motif. In our data set, this motif

was found with an average frequency of 10.6% (11.2%, when

using TMHMM2.0, see Supporting Information Fig. 2D),

which agrees well with reported values from Senes et al.(12.1%) [23] and Unterreitmeier et al. (12.4%) [27]. In

comparison with the strong variations seen for the single

residue frequencies, it seems that the prevalence of GxxxG is

almost unchanged among the different organisms (Fig. 2D).

Interestingly, there is a significant drop in the frequency

of strongly polar and charged residues when comparing

uni- and multicellular organisms within the eukaryotic

kingdom. This led us to focus on S. cerevisiae and H. sapiensin more detail for which we analyzed the frequency

distribution of TMDs containing multiple polar or

charged amino acids (Fig. 3). Reflecting the overall

average, the most likely number of polar residues shifts

from 4 in the case of S. cerevisiae to 2 in the case of H. sapiens(Fig. 3A). Narrowing the class down to ‘‘strongly polar’’,

changed the histogram shape, since it was most likely not to

find a single strongly polar residue (�75% in human and

�50% in yeast, Fig. 3B). A similar distribution was found

for the charged residues (Fig. 3C). For all of the subsets of

amino acids, the differences between the two organisms

were maintained.

TMD annotations in UniProt rely on three different

sources: experimental evidence, protein family classifica-

tion, or prediction algorithms (TMHMM, Memstat,

Phobius). Up to now around 20 different prediction

algorithms were developed and novel methods are still

invented [52, 53]. In order to cross-check whether a de novoprediction of TMDs preserve the described trends, we

generated Figs. 1–3 with a data set using TMHMM2.0 as

benchmark without observing major differences (Support-

ing Information Figs. 1–3).

3.3 Experimental assay for measuring TMD

interactions

Understanding how TM helices contribute to thermo-

dynamic properties of the receptor interaction network is

hampered by two major caveats: structural information of

single-pass TM proteins is almost non-existing, and direct

observation of oligomerization states in a highly dynamic

plasma membrane in living cells is difficult. GPMVs are

10–20 mm spherical blebs that develop when cells are treated

8090

100A [%] of TMD with at least 1:

102030

4050

6070

strongly polarB [%]

1020304050

chargedC [%]

E. c

oli

B. s

ubtil

lis

S. c

erev

isia

e

S. p

ombe

A. t

halia

na

C. e

lega

ns

D. m

elan

ogas

ter

D. r

erio

X. l

aevi

s

M. m

uscu

lus

R. n

orve

gicu

s

H. s

apie

ns

010

20GxxxG motifD [%]

polar

Figure 2. Frequency of occurrence of at least one (A) polar, (B)

strongly polar, (C) charged amino acid, and (D) GxxxG motif

contained in the TMD regions within the 12 analyzed proteomes.

Freq

uenc

y [%

]

30

20

10

00 1 2 3 4 6 7 8 9 105

polar

charged

75

50

25

0

Freq

uenc

y [%

]

strongly polar

0 1 2 3 4

Number of amino acids

Number of amino acids

0 1 2 3 4

A

B C

Figure 3. Histograms of a given number of (A) polar, (B) strongly

polar or (C) charged amino acids in TMDs present in the

proteomes of H. sapiens (dark gray) and S. cerevisiae (light

gray).

Proteomics 2010, 10, 4196–4208 4201

& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com

with a low concentration of formaldehyde under reducing

conditions. Their proteome mainly represents the content of

the surface plasma membrane, while for the lipid compo-

sition some differences were recently described [54, 55].

Since they are detached from the cytoskeleton, GPMVs

show no vesicular traffic and movements, and thus provide a

platform to study diffusion-driven protein oligomerization

events in isolation. Prior to blebbing, we transfected cells

with constructs encoding cytoplasmic truncated and fluor-

escent protein-tagged class I cytokine receptors (Fig. 4A).

The spherical geometry of these vesicles facilitates

performing scanning FCS, a recently introduced method for

measuring diffusion in membranes [35]. In brief, the laser

focus was moved perpendicularly through the membrane at

the equatorial plane of the vesicle, and the recorded

membrane fluorescence was correlated post-measurement

eliminating effects of membrane drift. Autocorrelation

analysis provides the diffusion coefficient and concentration

of fluorescently tagged receptors in the membrane. For our

GFP-tagged short IL-4Ra construct, the diffusion coefficient

in blebs was Dt 5 1.870.4 mm2/s (n 5 19) and thus 5–7-fold

increased as compared with native plasma membranes of

living cells (not shown). The faster mobility of single pass

TM proteins in blebs was mainly attributed to the cytoske-

leton detachment [56]. Because the non-interacting, eGFP-

tagged receptors can be assumed to be equally bright, the

inverse autocorrelation amplitude G�1(0) directly reflects

their concentration. Within this data set, we obtained

surface densities between 40 and 1100 receptors per mm2.

Considering a typical diameter of the blebs (20 mm), this

Figure 4. (A) GPMVs containing IL2Rgm291-eGFP (green) and IL4Ram241-mRFP (red) stained by anti-IL4Ra-Cy5 antibody (blue). (B) Auto-

(green and red) and cross-correlation (blue) curves measured for eGFP/mRFP tagged pairs of NHis-IL4Ram241 (left panel) and NHis-

IL2Rgm291 coupled by anti-His-tag antibodies (right panel). (C) Domain swap experiment: ratio of cross- and autocorrelation amplitudes

(CC) as a function of the inverse amplitudes in the eGFP channel for individual blebs containing eGFP/mRFP tagged constructs

(EpoRm259, IL4Ram241, and both with swapped TMDs). The data points saturate toward higher concentrations. For comparison in (D),

the upper third of obtained values was averaged (color shaded area). (D) Normalized cross-correlation ratios (norm. CC) for homotypic

receptor pairs with respect to our tandem mRFP-eGFP positive control (PC, black). The negligible norm. CC for IL-4Ra and IL-2Rgconstructs (wt, white) was increased in the presence of cross-linking antibodies (1Ab, gray; anti-IL4Ra-ECD-Cy5 for IL-4Ra and anti-

hexahistidine for IL-2Rg, all values averaged). Saturation values of norm. CC for EpoRm259 homodimers (wt, blue) was reduced for the TM

domain swapped construct (IL4Ra-TMD, turqoise), whereas for IL-4Ram241 it was induced (TMD-EpoR, turqoise).

4202 R. Worch et al. Proteomics 2010, 10, 4196–4208

& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com

translates into a (50–1300)� 103 receptor molecules perGPMV. In contrast, endogenous cytokine receptors are

present in 100–5000 proteins per cell [57]. We are therefore

performing our measurements at more than a 500-fold

overexpression level. Assuming that the surface membrane

area of cells and GMPVs are roughly of the same order of

magnitude, endogenous expression levels would correspond

to 0.1–5 receptors per mm2 and thus are much below of what

can be detected by FCS.

In its dual-color version, sFCCS provides a cross-correlation

signal which is sensitive to co-diffusion of differently labeled

proteins detected in the respective spectral channels [36, 58].

Binding can be quantitatively monitored by observing CC, the

mean ratio of cross- and autocorrelation amplitude [48, 49]. In

order to assess instrumental limitations, we first measured a

PC designed by a tandem eGFP-mRFP fusion protein that was

recruited to the plasma membrane by a dimeric palmitoyl-

myristoyl anchoring domain derived from Lyn kinase. The

reduced average ratio of CC 5 3578% merely reflects the

optical properties of the setup. The reduction is mainly due to

chromatic aberrations; the imperfect overlap of the differently

sized detection areas for green and red, scaling with l2, as well

as additional imperfections of the optical performance along

the scan path, different cuvettes and positions within the

sample. Despite all these factors the cross-correlation for this

construct was always significant and reproducible and allowed

to interpret binding-related CC-changes within a defined range.

3.4 TMD interactions of class I cytokine receptors

Measuring wild type IL-4R chains, NHis-IL-4Ram241 and

NHis-IL-2Rgm291, with sFCCS showed no detectable inter-

actions. We observed a close to zero cross-correlation ampli-

tude (Fig. 4B, left panel) regardless of the varying surface

densities of the independently expressed eGFP/mRFP tagged

constructs (Fig. 4C, lower left panel). To exclude that uneven

expression levels or other unknown experimental pitfalls cover

a potential interaction of the IL-4R chains, we enforced

receptor cross-linking within the same sample. Vesicles

containing red- and green-tagged NHis-IL-4Ram241 were

measured in the presence of a Cy5 labeled antibody directed

against its ECD. The binding of Anti-IL-4Ra-Cy5 was specific,

as visualized by the perfect correlation with receptor expression

levels in the blebs (Fig. 4A). Antibody treatment increased the

normalized CC to 35%; 55% were reached with an antibody

directed against a hexahistidine stretch genetically incorpo-

rated at the extracellular N-terminus of Nhis-IL-2Rgm291

(Fig. 4B, right panel; Fig. 4C). Both control experiments

suggested that IL-4R chains indeed bear no detectable

propensity to self-interact in the membrane.

In contrast to the IL-4R chains, the EpoR constructs showed

evidence for complex formation (Fig. 4C, upper left panel).

Independent of the overall expression level, the obtained CC-

values scatter between 0 and a maximum of 12%. Significant

CC was still observed in comparably dim blebs, close to the

detection limit of sFCCS, suggesting a sub-micromolar affinity

constant. In order to further dissect this interaction, we

performed a domain swapping experiment for which the

hydrophobic portion of the TM helices have been exchanged

between EpoR and IL-4Ra (Table 1). The result of a typical data

set is shown in Fig. 4C: Exchanging the TMD of EpoR by that

of IL-4Ra shows a systematic dependence on the overall

receptor density similar to a hyperbolic binding curve (Fig. 4C,

upper right panel). A similar progression was observed for IL-

4Ra containing the hydrophobic core of the EpoR-TMD (Fig.

4C, lower right panel). Comparison of the abscissa for all three

cases of binding shows that significant CC, and hence binding,

was reached at different surface densities. Such a comparison

is still valid because the inverse amplitudes composed of

contributions of interacting particles, although non-linear, still

scales monotonically with the true total concentration of

tagged receptors. Therefore, the affinities for self-interaction

can be ranked in the order EpoR4EpoR-TMD-IL4Ra4IL4Ra-

TMD-EpoR. Consistent with current knowledge in Epo

signaling, the interaction potential of EpoR was not completely

abolished, because juxtamembrane sequences were supposed

to retain some of the interaction potential [11, 12, 59]. Here it is

especially noteworthy that SER 273 at the C-terminal end of

the EpoR TMD was not included in the domain swap which

appeared to play an important role for binding as revealed by

our computational analysis (Fig. 5B).

Normalizing the CC values by a suitable red–green-labeled

PC allows to draw further conclusions about stoichiometry of

the formed complexes. Because of the variation in the data,

we approximated a saturating maximum of CC by simply

averaging the upper third of measured values (shaded regions

in Fig. 4C) followed by rescaling (colored bars in Fig. 4D).

The normalized CC of 30% for wild type EpoR was reduced to

22% when containing the TMD of IL-4Ra. In the opposite

case, IL-4Ra chains containing the EpoR-TMD, did not fully

restore the level of EpoR, as it increased from 0% only to

about 19%. Owing to the concentration dependence discus-

sed above, the slightly diminished maximum values of the

domain swapped constructs most likely reflect incomplete

dimerization in a dynamic equilibrium.

Binding studies deal with dynamically interacting parti-

cles; thus, the formed complexes carry different numbers of

tags and therefore exhibit varying molecular brightness.

This renders the concentration dependence non-linear

Table 1. TM regions of studied cytokine receptors according toUniProt and as used for the model calculations

Receptor TM region

IL4Ra LLLGVSVSCIVILAVCLLCYVSITIL2Rg VVISVGSMGLIISLLCVYFWLIL13Ra1 LYITMLLIVPVIVAGAIIVLLLYLEpoR LILTLSLILVVILVLLTVLALLS

Polar amino acids are underlined. For the domain swapexperiment between EpoR and IL-4Ra the bold amino acidswere not included.

Proteomics 2010, 10, 4196–4208 4203

& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com

because brighter particles are over-represented in correlation

curves. Nevertheless, for a heterotypic dimerization reaction,

the normalized CC directly reflects the fraction of formed

dimers with respect to the orthogonal color channel. More

explicitly, dividing the cross-correlation by the autocorrela-

tion amplitude of the green channel returns the fraction of

dimers with respect to the total number of red-labeled

receptors in the membrane. For the homotypic interactions

studied here, the situation is complicated by the fact that

also double-red or double-green dimers can form, which

influence both the cross- as well as the autocorrelation

amplitudes. Denoting b as the degree of oligomerization

(2 for dimers, 3 for trimers, etc.) and pt the molar fraction of

receptors tagged by the particular color type t used for the

division, the maximum normalized CC for a reaction at the

side of fully formed complexes was explicitly derived [49]:

normalized CC ¼Gccð0Þ

Ga;tð0Þ

� �GPC

a;t ð0Þ

GPCcc ð0Þ

!¼

b� 1

b� 111=ptð2Þ

We always chose the lower autocorrelation amplitude for

normalization leading to normalized CC values between 1/3

(pt 5 0.5) and 1/2 (pt 5 1). Of course, the upper limit of 1/2 is

never reached since the correlation curve of the less abundant

color breaks down due to insufficient signal above noise. For

realistic ratios obtained by co-expression and careful selection

of the blebs (up to 1:3), a pure dimerization will produce a

normalized CC of 33 to 44%. Since all our interacting

constructs seem to saturate in this range we conclude that the

EpoR-mediated interaction, be it mediated by the juxtamem-

brane portions or the hydrophobic core, indeed leads to a

dimerization and not to higher order aggregates.

3.5 Computing interaction potentials for helix

dimers in a model membrane

The compositional complexity of cellular membranes poses

great challenges to the prediction of interaction free ener-

gies by theoretical means. Larger biomolecules, like for

example a-helical TMDs, seek to accommodate themselves

in optimal orientation in such a complicated environment

where physical properties change on very small length

scales: for example, the dielectric constant e5 2 for the

hydrophobic core, e5 25 for the interface domain rich in

phospholipids and acetyl groups and e5 80 for the

surrounding water [60]. Our MM/PB11 approach aims at

reproducing this complex setup by assigning three char-

acteristic mimicry solvents that form individual continuum

layers of approximately the aforementioned dielectric

constants [33]. Dimerization free energies were computed

like DG(TMD1:TMD2)�DG(TMD1)�DG(TMD2); hence, a

systematic screen of different TMD combinations can be

carried out. However, the strength of interaction will depend

on the relative orientation of the two TMD domains towards

each other. Consequently, we rotate both individual TMDs

in a-helix-specific increments of 1051 and set up a series of

sample conformations to be probed for free energies of

dimer formation.

Placing rotational conformers of TMD pairs into the

membrane, the multiple continua approach did not reveal

any conformation with significant DDGenv of negative sign,

indicating that the membranous environment alone would

not favor dimer formation for all TMDs tested. In contrast,

several samples involving EpoR, IL2R, IL4R and IL13R

would be prone to dimer formation when regarding solely

direct TMD-TMD interaction energies in vacuum (i.e. the

MM term). Dimer formation free energies of the most

favorable conformation of all calculated class I cytokine

TMDs are summarized in Supporting Information. Table 1.

However, combining both – which is the essence of the

MM/PB11 approach – yields two EpoR-conformations that

show clear preference for dimer formation beyond the

confidence interval (see position of arrows in Fig. 5, items 0,

180 and 315, 495). The two conformations identified may

actually be reduced to one single geometry because either

combination of rotation angles describes an almost identical

A TMD interactions B

−20−10

0 10 20 30 40 50 60 70 80 90

315/180315/285315/390315/495210/75210/180210/285210/390105/−

30105/75105/180105/2850/−

1350/−

300/750/180

ΔΔ

G [k

cal/m

ol]

Rotation Angles [°/°]

EpoR TMD 0°/180°

SER273

Figure 5. In silico prediction of TMD interac-

tions. (A) Combined environmental and MM-

derived relative Gibbs-free energies for the

homotypic TMD dimers IL4Ra (red), IL2Rg(blue), IL13Ra1 (turquoise) and EpoR (green)

and the heterotypic interactions for IL4Ra/

IL2Rg (black) and IL4Ra/IL13Ra1 (gray). Two

EpoR-TMD orientations (arrows) were

detected beyond an estimated confidence

interval (gray shading) below zero (dashed

line). (B) TMD-TMD conformer (01/1801) of

EpoR showing the highest interaction

energy. Leu is shown in pink, Ile in green, Val

in brown, Ala in blue, Thr in purple and Ser in

yellow. The N-terminal TMD-ends are located

at the top while the C-terminal TMD end (Ser

273) positioned at the bottom.

4204 R. Worch et al. Proteomics 2010, 10, 4196–4208

& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com

relative orientation of the two TMDs. A detailed structural

representation of the two identified EpoR homo dimers with

favorable dimerization free energy is shown in Fig. 5B. The

alcohol group of SER273 forms a hydrogen bond to the

backbone carbonyl-oxygen of the neighboring-helix of

ALA270; thus, destabilizing the regular a-helical motif of

the i–i14 backbone interaction. Polar residues in the

hydrophobic core do not interact; rather appear to be

excluded from the interface between the two helices.

4 Discussion

From a physicochemical point of view, limiting the number

of TM segments in a protein leads to an increased popula-

tion of low-energy conformations, which might favor

putative interactions [1]. It was also proposed that strongly

polar residues have more potential to drive TM helix inter-

actions, as compared with hydroxy or thiol group-containing

side chains [29, 30, 61]. In a number of disease-related gain-

of-function mutations, polar residues in the TM region were

shown to constitutively activate a signaling pathway. This

was described in particular for receptor tyrosine kinases [62]

and other receptor families [17]. The observed trends of a

decreasing abundance of both strongly polar and charged

amino acids during eukaryotic evolution suggest that there

might be a negative selection pressure on their existence in

the TM region, due to their propensity to promote unspe-

cific helix–helix interactions. Lowering the propensity for

interactions in the membrane for the bulk of TMDs in

single-pass TM proteins in turn provides a contrasting

background for the emergence of selective physiologically

relevant interactions.

These particular examples show indeed that TMD inter-

actions play an important mechanistic role in the quaternary

structures of single-pass TM receptors. The TM regions of

IL-4R and EpoR contain several polar amino acids (Table 1),

but they are not organized in any known motif; therefore,

predicting their dimerizing properties is not straightfor-

ward. We show here for the first time that the receptor

chains, IL-4Ra and IL-2Rg, do not homotypically interact in

the membrane of GPMVs, even at surface densities far

above physiological levels. Such a behavior contrasts with

the self-assembly of EpoR chains, as detected by our sFCCS

assay. This result was fully reproduced by our computational

analysis, identifying two EpoR dimer orientations as the

only examples with significant interaction energy. The

conformation of interacting EpoR helices (Fig. 5B) reveal a

distinctive role of a flanking serine forming a hydrogen

bond to the peptide backbone of the adjacent chain in the

phospho-head group containing transition zone of the

membrane. The fact that such hydrogen bonds can actually

form within the membrane was recently documented for the

z-z T-cell receptor dimer, where it persists in the middle of

the HC core [63]. Notably, the conformation the z-z T-cell

receptor dimer could also be reproduced by the continuum

approach [33]. In contrast, the interface between the two

EpoR helices is not populated by polar residues indicating a

pure van der Waals interactions for this region. The physical

relevance of van der Waals energy contributions was

demonstrated further by the TMD swap experiment,

because this interaction was clearly detected in otherwise

non-interacting IL-4Ra chains. For the future it may be

interesting to address how functional relevant polar and

charged residues distribute within the TMD, whether non-

covalent bonds dominate in the phospho-head group layer

or the hydrophobic core.

Different oligomerization states of single-pass receptors

at the plasma membrane reflect a difference in the activa-

tion mechanisms. What is that difference about? The fact

that these mechanisms differ within the same receptor

families, in which, for example, structural features relevant

for ligand binding and specificity are well conserved, may

hint to differential fine-tuning in regulation. Our data show

that the degree of TMD-mediated interaction, as in the case

of EpoR, strongly depend on surface densities. Thus, the

affinity between individual receptor chains is tuned such

that variations in local concentrations may determine the

oligomerization state of the signaling complex. We believe

that variations of TMD interaction potential serve as an

underlying architecture for a kinetic control of the signaling

pathway rather than a static structural feature for ligand

recognition.

For cytokine receptors, a surprisingly broad variety of

activation mechanisms were described [10, 14]. While pre-

formed dimers in the absence of ligand appear as a common

theme for the subgroup of homo-interacting receptors like

EpoR, it is conceivable that sub-families grouped around

shared receptor subunits, like the common g chain, preserve

a state in which receptor chains can dynamically exchange

in the plasma membrane. Full-length cytokine receptors

were shown to be tightly, though non-covalently, bound by

their cognate Janus kinases (JAKs) [64]. Because in our

receptor constructs, the tail was truncated 5–10 amino acids

downstream of the TM helix within the box-1 motif, binding

of JAKs or any other cytoplasmic factor was abolished. Since

the JAKs are an integral part of the receptor architecture,

their influence on the oligomerization state of the receptor

must be assessed in future experiments. Here the sFCCS

assay may provide an excellent platform since the respective

co-factors can be simply co-transfected.

GPMVs represent an intermediate membrane model

between fully defined reconstituted artificial membrane

systems and the complex plasma membrane of living

cells. Although the vesicle formation is induced by a low

amount of formaldehyde, the data for non-interacting

IL-4Ra chains show clearly that the amount of accidentally

cross-linked protein is negligible. Thus, we suggest GPMVs

as a platform to study lateral TM protein interactions.

Compared with protein purification, genetic engineering

and expression of constructs are straightforward and less

laborious. Therefore, a much larger number of combina-

Proteomics 2010, 10, 4196–4208 4205

& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com

tions of receptors and co-factors can be measured, a feature

which may be crucial to fully cope with the rich composition

of signaling complexes. As an additional advantage, corre-

sponding ligands, TMD targeting drugs or other extra-

cellular factors can simply be added to the buffer. The non-

interacting short IL4Ram241 chain may be used as a host

system to address TMD–TMD interactions in more detail.

This may include site-directed mutagenesis of the TMDs.

Investigating small libraries of TMDs, combined with

theoretical models, may expand our understanding of the

underlying physical forces. In this context our MM/PB11

approach is of particular interest, since it combines a

remarkable success rate for predicting TMD interactions in

a complicated membrane environment with a minimal cost

of computation time.

For our experiments we expressed the eGFP and mRFP-

tagged constructs with two individual vector systems, which is

not optimal for even expression of both colors. This may easily

be improved by standard molecular biology methods, e.g.combining both colored constructs on a single vector system

or the use of inducible promoters. sFCCS was used to detect

the interacting complexes on a background of single colored

complexes or single proteins. sFCCS is an elegant method to

deal with slow membrane fluctuations and to avoid spectral

cross-talk contributions. However, it suffers from long

measurement times. Pulsed interleaved excitation combined

with top positioning on the GPMVs may provide an alter-

native approach [65]. Improving the statistical accuracy of the

measurements through this technique may even allow to

determine the surface Kd. Notably, Eq. (2) links the saturation

value of the normalized CC to different receptor stoichiometry

of the formed complexes and may therefore be used to

discriminate different binding models.

GPMVs have recently been introduced as a system to

study lipid bilayer thermodynamics, like Lo/Ld phase

separation, partitioning between different phases and criti-

cal fluctuations, and thus providing clues about the lateral

membrane organization in the context of the concept of

lipid rafts [34]. Here we see an additional avenue for inter-

esting experiments, for example, the oligomerization state

and partitioning could be measured in different phases.

Thus, this approach significantly extends the repertoire of

quite rare techniques in the field and may have strong

impact to elucidate mechanistic aspects in receptor biology.

We thank Heiko Keller for introducing us into bleb formingtechniques and Jonas Ries for support with sFCCS. R. W. isgrateful for receiving a postdoctoral fellowship from the Alex-ander von Humboldt Foundation (Germany). The use of aConfocor3 was amply supported by Carl Zeiss AG (Germany).We thank Karin Crell, Ellen Sieber, and Stephanie von Kannenfor their excellent technical assistance. This work was in partsupported by a CRTD seed grant to C. B., T. W., and P. S. and aDFG/ESF grant to P. S.

The authors have declared no conflict of interest.

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