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J. Biol. Chem., Vol. 278, Issue 30, 28109-28115, July 25, 2003
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From the
Experimental Biophysics Group, Max Planck
Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen,
Germany and the ¶Membrane Enzymology Group,
University of Groningen, Nijenborgh 4, 9747 AG Groningen, The
Netherlands
Received for publication, March 24, 2003 , and in revised form, April 28, 2003.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Commonly, lipid rafts are enriched in sphingolipids and cholesterol (1–4). The presence of long and saturated acyl chains in sphingolipids allows cholesterol to become tightly intercalated with such lipids, resulting in the organization of liquid-ordered (lo) phases. By contrast, unsaturated phospholipids are loosely packed and form a disordered state (usually indicated as liquid crystalline lc or liquid-disordered ld) (19, 20). The difference in packing ability leads to phase separation (21, 22). Model membrane studies carried out on ternary mixtures of cholesterol with phospholipids and sphingolipids show that lo phases, enriched in sphingolipids, separate from ld phases, enriched in phospholipids (19, 23). Several observations indicate that these "artificial rafts" are a reasonable, though crude, model of raft-containing cell membranes (24).
More recently, along with a number of techniques employed to address questions on rafts (11, 21, 25–27), important contributions have also come from optical microscopy (28, 29). Direct visualization of raft-like domains in model bilayer membranes has provided a tangible proof for the coexistence of liquid-ordered and liquid-disordered phases (30–33). However, rafts are by no means static structures. If it is true that their main function consists of forming platforms to concentrate certain proteins, then a detailed characterization of lipid and protein dynamics in the different phases is essential to understand mobility-dependent protein organization (34). Single particle tracking (SPT) has been applied to follow raft-associated proteins in vivo (29) and lipid mobility in cell membranes and in vitro (31, 35). Additional contributions have come from fluorescence recovery after photobleaching (FRAP) (32) and fluorescence resonance energy transfer (FRET) (28). However, a detailed characterization of cholesterol-containing membranes from a dynamic point of view is still lacking.
Fluorescence correlation spectroscopy (FCS)1 is based on the time-correlation of temporal fluorescence fluctuations detected in the focal volume, which are governed by dynamic parameters of the system at equilibrium (36, 37). The power of FCS relies on the single molecule sensitivity and the capability of exploring a wide range of dynamic events with high temporal resolution and good statistical accuracy (38). In the past, this technique has been proven to be a powerful tool to follow lipid dynamics in domain-forming giant unilamellar vesicles (GUVs) (39), which serve as excellent model membranes for single molecule optical microscopy (40).
In this study, we present a detailed characterization of lipid dynamics in raft-forming GUVs prepared from a ternary mixture of cholesterol, dioleoyl-phosphatidylcholine, and sphingomyelin. By combining confocal optical microscopy and FCS, insight is gained in the static and dynamic organization of lipids, partitioning in different phases. It is evident that cholesterol plays a key role in promoting raft formation and, most importantly, in tuning membrane lipid mobility. Finally, we show that FCS provides information on lipid raft composition, allowing for a mapping of the lipid phase diagram, entirely based on dynamic parameters.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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-cyclodextrin (MCD) was from
Sigma. All other chemicals were of reagent grade.
Preparation of GUVs—GUVs were prepared by electroformation
(40,
41). With this approach, truly
unilamellar vesicles are produced with sizes varying from 10 up to 100 µm
(42,
43). The flow chamber
(closed-bath perfusion chamber, RC-21, Warner Instruments Co.) used for
vesicle preparation was equipped with two microscope slides, each coated with
optically transparent and electrically conductive indium tin oxide (ITO).
Lipids in chloroform/methanol 9:1 (5 mM, prepared freshly and kept
under a nitrogen atmosphere) were deposited on preheated ITO coverslips and
the solvent was evaporated at 20 or 60 °C; both procedures yielded the
same results in terms of domain formation and lipid mobility. After adding
water into the chamber (
300 µl), a voltage of 1.1 V at 10 Hz was
applied for 1 h. After lipid swelling, the chamber was put either directly at
room temperature or cooled down slowly by using a heat block. Both cooling
procedures led to the same type of vesicles and domain pattern. Also the
presence of the reducing agent dithiothreitol (2 mM, final
concentration), to prevent possible lipid oxidation, did not affect domain
formation and lipid mobility under our conditions of GUV formation. Whatever
procedure was used, the GUVs were always prepared from fresh lipid mixtures
and kept under a nitrogen atmosphere as much as possible. Lipids were checked
for oxidation by UV/VIS spectroscopy and thin layer chromatography. Under the
conditions of GUV preparation, it was found that less than 0.1% of lipids were
oxidized.
DiI-C18 was added in the amount of 0.1 mol% for confocal imaging and 0.001 mol% for FCS. Since GM1 is known to change the lipid spatial distribution above 2 mol% (44, 45), the compound was used here in minimal amounts, for confocal imaging (0.1 mol%) and FCS (0.05 mol%).
Confocal Fluorescence Microscopy and FCS—Confocal
fluorescence microscopy and FCS were performed on a commercial ConfoCor2
(Zeiss, Jena, Germany). Confocal images were taken with the laser scanning
microscopy (LSM) module. The excitation light of an Ar ion laser at 488 nm and
of a HeNe laser at 543 nm was reflected by a dichroic mirror (HFT 488/543) and
focused through a Zeiss C-Apochromat 40x, NA = 1.2 water immersion
objective onto the sample. The fluorescence emission was recollected by the
same objective and split by another dichroic mirror (NFT 545) into two
channels. Detection of the fluorescence emission, after passing a
505–530-nm bandpass filter in the first channel and a 560-nm longpass
filter in the second channel, was obtained with two photomultipliers (PMTs).
The confocal geometry was ensured by pinholes (60 µm) in front of the PMTs.
FCS measurements were performed by epi-illuminating the sample with the 543 nm
HeNe laser (Iex 
1.2 kW/cm2). The
excitation light was reflected by a dichroic mirror (HTF 543) and focused onto
the sample by the same objective as for the LSM. The fluorescence emission was
recollected back and sent to an avalanche photodiode via a 560–615-nm
bandpass filter. Out-of-plane fluorescence was reduced by a pinhole (90 µm)
in front of the detector. The laser focus was positioned on the
topside/bottomside of GUVs, by performing an axial (z-) scan through the
membrane prior to the FCS recording. The fluorescence temporal signal was
recorded and the autocorrelation function G(
) was calculated,
according to Magde et al.
(44). The apparatus was
calibrated by measuring the known three-dimensional diffusion coefficient of
rhodamine in solution. The detection area on the focal plane was approximated
to a Gaussian profile and had a radius of 0.18 µm at 1/e2
relative intensity. Data fitting was performed with the Levenberg-Marquardt
nonlinear least-squares fit algorithm (ORIGIN, OriginLab, Northampton, MA).
The fitting equation made use of a two-dimensional Brownian diffusion model,
assuming a Gaussian beam profile as shown in
Equation 1,
 | (Eq. 1) |
Ci
is the two-dimensional time average
concentration of the species i in the detection area
Aeff and d,i is the average
residence time of the species i. The diffusion coefficient
Di for the species i is proportional to
d,i. For FCS measurements, three independent GUVs preparations
were analyzed and, for each of them, data from at least 20 different GUVs were
recorded with 100 s acquisition time per FCS measurement. When membrane phase
separation was visualized with the LSM, the laser focus was always positioned
onto one phase only for the FCS experiment. |
RESULTS |
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3
(45). We show here that
DiI-C18 is excluded from the sphingolipid-rich phase and rather
favors the DOPC-rich phase. The unambigous phase assignment was carried out by
determining the partitioning of GM1, a ganglioside frequently used to identify
sphingolipid-enriched rafts
(46). Upon incubation of GUVs
with the AlexaFluor conjugate of cholera toxin B subunit (AF-CTB), for which
GM1 is the natural receptor, the complex GM1-CTB was detected only in areas
from which DiI-C18 was strongly excluded (SM-enriched).
Fig. 1 shows a series of
confocal images of GUVs with different lipid compositions and well illustrates
the lipid organization and domain morphology when the fraction of cholesterol
is varied. GUVs made of pure DOPC exhibited uniform DiI-C18
fluorescence (Fig.
1A). Here, the lipids were in the fluid phase at room
temperature, as following photobleaching of a spot, a quick recovery of
fluorescence was observed. GUVs prepared from pure SM were, within the optical
resolution, also uniformly fluorescent, but in this case the membrane was in
the solid state, at room temperature. Consistently, following photobleaching,
no significant recovery of fluorescence was observed within hours (see
Fig. 1B). Uniform
fluorescence was also observed in bilayers formed from DOPC/SM (0.5/0.5 molar
ratio) (not shown). However, inclusion of as little as 10 mol% of cholesterol
in the SM/DOPC (0.5/0.5) bilayer, sufficed to induce lipid segregation, as
evidenced by the preferential partitioning of DiI-C18 in one phase
(red areas in Fig.
1C). Strikingly, the marker partitioned in the
fluid-disordered phase by a factor of 50, assuming the quantum efficiency
of DiI-C18 was the same in both lipid phases. Alexa-Fluor-labeled
cholera toxin AF-CTB bound to areas in the GUVs, from which DiI-C18
was excluded and formed fluorescent regions exactly complementary to the ones
covered by DiI-C18 (green areas in
Fig. 1C). The size of
SM-enriched domains could vary from a few microns up to a size covering almost
half of a 20 µm-sized GUV. Unilamellarity of the vesicles allowed us to
look for phase interlayer coupling and it was found that, in all of the GUVs,
the phase domains comprised both apposing membrane leaflets. Phase separation
was also visualized at higher amounts of cholesterol (SM/DOPC = 0.5/0.5), as
shown in Fig. 1D for
20 mol% and in Fig. 1E
for 33 mol% of cholesterol. The domain morphology was the same as described
for 10 mol% cholesterol, except that the total surface area of the SM-enriched
phase increased with the amount of cholesterol. At 50 mol% cholesterol, rafts
were no longer observed within the optical resolution
(Fig. 1F). Similarly,
uniform fluorescence from DiI-C18 and GM1-bound AF-CTB was detected
in GUVs with 65 mol% cholesterol (not shown).
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Membrane Lipid Mobility Is Controlled by Cholesterol—We
assessed the membrane lipid mobility of GUVs made from ternary mixtures of
DOPC/SM/cholesterol by measuring the diffusion coefficient of
DiI-C18 by FCS. In Fig.
2A, correlation curves are shown for the
liquid-disordered, DOPC-enriched domain, where DiI-C18
preferentially partitioned, and in Fig.
2B those for the liquid-ordered, SM-enriched domain, from
which DiI-C18 was largely excluded. Note that the sensitivity of
FCS allows one to measure lipid diffusion with the fluorescent marker at very
low concentrations in both phases. As soon as phase separation occurred, in
the presence of 10 mol% of cholesterol
(Fig. 2A,
dash (d)), the lipid mobility in liquid-disordered domains
(D = 4.9 ± 0.3 x 10–8
cm2/s) almost matched the one of pure DOPC membranes (D =
6.3 ± 0.2 x 10–8 cm2/s,
Fig. 2A, dot
(a)). This mobility was significantly higher than that measured in
DOPC/SM (0.5/0.5) GUVs in the absence of cholesterol (D = 2.6
± 0.2 x 10–8 cm2/s,
Fig. 2A,
solid (e)). An increase in the cholesterol concentration
hardly affected the mobility value of DiI-C18 relative to values
measured for pure DOPC. On the other hand, cholesterol greatly varied the
lipid mobility in the SM-enriched phase
(Fig. 2B), where lipid
diffusion was significantly slower than in the fluid-disordered phase and in
the SM/DOPC (0.5/0.5) mixture without cholesterol
(Fig. 2B,
solid (a)). However, by increasing the amount of
cholesterol, the membrane lipid mobility in SM-enriched domains greatly
increased, from D = 0.105 ± 0.031 x
10–8 cm2/s (10 mol% cholesterol,
Fig. 2B, dash
(f)) up to D = 0.795 ± 0.108 x
10–8 cm2/s (33 mol% cholesterol,
Fig. 2B, dash dot
dot (d)) approaching that of SM/DOPC (0.5/0.5) mixtures. By
further increasing the amount of cholesterol, the domains disappeared but the
lipid mobility remained higher than that of the SM-rich domains (50 mol%
cholesterol, Fig. 2B,
short dash (b)), though lower than in SM/DOPC = 0.5/0.5
GUVs. Any further increase in cholesterol concentration made the whole
membrane stiffer (e.g. 65 mol% cholesterol in
Fig. 2B, short
dash dot (c)). Taking different SM/PC molar ratios 
1
(e.g. 0.53/0.13), the domain morphology and the lipid diffusion were
unchanged (see Table I). On the
other hand, in the case of SM/PC molar ratios < 1, no domains were
visualized by confocal microscopy and the lipid dynamics measured was rather
high and very close to that in pure DOPC (e.g. SM/DOPC 0.13/0.53, see
Table I). For all of the FCS
curves, excellent fits were produced with a one-component normal Brownian
diffusion model (37). The
diffusion coefficients, calculated from the fitting of FCS curves shown in
Fig. 2, are reported as a
function of mol% of cholesterol in Fig.
3 (see also Table
I).
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Lipid Mobility in Binary Mixtures—In order to investigate in
more detail the lipid spatial organization in raft-exhibiting membranes, lipid
mobility in GUVs prepared from ternary mixtures of SM/DOPC/cholesterol was
compared with that in GUVs from binary mixtures of DOPC/cholesterol,
SM/cholesterol and DOPC/SM. For all of these binary compositions, GUVs showed
no phase separation by confocal microscopy. The FCS measurements of
DiI-C18 mobility could be well fitted with a one
diffusion-component. In Fig.
4A, FCS curves recorded for DOPC/cholesterol membranes
are shown. The diffusion coefficients obtained from the fitting are plotted as
a function of cholesterol concentration in
Fig. 4B: a gradual
shift of lipid mobility toward lower values is observed upon increase of the
amount of cholesterol. Compared with DOPC/cholesterol mixtures, the opposite
effect of the cholesterol was observed in SM/cholesterol mixtures, where the
lipid mobility increased upon increase of mol% of cholesterol (see FCS curves
in Fig. 4C and the
corresponding diffusion coefficients reported as a function of mol% of
cholesterol in Fig.
4D). For binary mixtures of SM/DOPC, phase separation was
observed by confocal microscopy for mol% of SM 80%. DiI-C18
favored the SM/DOPC gel-phase, with a partition coefficient of 3. In
Fig. 4E the FCS curves
and in Fig. 4F the
corresponding diffusion coefficients of DiI-C18 are reported for
GUVs composed of SM/DOPC at different ratios. For the data at 80 mol% SM, only
FCS curves in the less bright fluid-disordered regions could be recorded, as
the FCS measurements in the SM gel-phase were strongly affected by
photobleaching. These latter results confirm that, in SM/DOPC membranes with
80 mol% of SM, an equilibrium is established at room temperature between
a SM-enriched gel-phase and a SM/DOPC-containing, liquid-disordered phase
characterized by high lipid mobility.
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Phase Diagram—The FCS measurements were used to build the
phase diagram shown in Fig. 5.
Starting from the left axis (DOPC/cholesterol), the membrane lipid mobility
continuously decreases upon increase of cholesterol concentration. Consistent
with previous findings for phospholipid/cholesterol mixtures
(23,
47), a transition from
liquid-disordered to liquid-ordered phase can be identified around 40
mol% of cholesterol. As the lipid diffusion coefficients in DOPC-enriched
domains of DOPC/SM/cholesterol GUVs almost match that of pure DOPC, we can
conclude that the DOPC-enriched phase is largely devoid of cholesterol and
that the SM-enriched phase takes up most, if not all, of the cholesterol
present in the membrane. The slight mismatch could be simply due to the
presence of small amounts (5–10%) of SM/cholesterol clusters in the
DOPC-rich phase. In contrast to DOPC membranes, lipid dynamics in SM membranes
(right axis in Fig. 5)
increases upon addition of cholesterol and undergoes a transition from
gel-phase to a liquid-ordered phase around 40 mol% of cholesterol. The trend
of diffusion coefficients is comparable to that of the SM-rich phase in
DOPC/SM/cholesterol GUVs and, remarkably, much steeper than what estimated in
previous reports (31,
32). However, the values of
diffusion coefficient are larger in the SM-rich areas of ternary mixtures than
in the binary SM/cholesterol. Therefore, we can conclude that the
liquid-ordered phase in SM/DOPC/cholesterol membranes is mainly composed of
SM/cholesterol but, most likely, also contains some DOPC, which further
increases the lipid mobility. Finally, the lipid dynamics in DOPC/SM GUVs is
regulated by the amount of SM soluble in the fluid DOPC membrane. The trend of
lipid diffusion coefficients as a function of mol% of SM suggests the presence
of two transition points, the first being around 10 mol% SM and the second
around 45 mol%. The difference in lipid mobility between these ranges may be
due to different molecular packing and spatial distributions of gel-phase and
liquid-disordered lipid clusters.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Previously, domains with raft-like properties were visualized by one- and two-photon fluorescence microscopy in model membranes (31, 32). Depletion and repletion of cholesterol in membranes composed of SM/DOPC/cholesterol (1/1/1) resulted in disappearance and reappearance of lipid rafts in supported monolayers (32). However, a systematic investigation of the morphology of raft-like domains as a function of cholesterol concentration has never been attempted. From the confocal images shown here, it is evident that cholesterol is the determining factor in causing phase separation of sphingolipids and unsaturated phospholipids. Confocal images of GUVs made of SM/DOPC (0.5/0.5) and different amounts of cholesterol show that, at room temperature, extended phase separation starts to occur at 10 mol% cholesterol. Consistent with previous studies reporting phase separation in model membranes with similar lipid mixtures (31, 32), the round shape of the domains suggests the coexistence of a liquid-ordered and a liquid-disordered phase, as the circular borders of the domains minimize the line energy. GUVs with less than 10% or more than 50% cholesterol did not exhibit phase separation, at least within the optical resolution. As previously observed in artificial membranes (31, 38), ordered phase domains in apposing leaflets were always perfectly coincident. Therefore, at least in the case of SM/DOPC/cholesterol mixtures, where the long fatty acid chains of SM in opposite leaflets can superimpose by interdigitation, the lipid component alone is able to create strong coupling between inner and outer leaflet.
It has been proposed that cholesterol-rich membranes exhibit formation of a
sphingolipid-rich, liquid-ordered phase, which separates from a
phospholipid-rich, liquid-disordered phase
(1–4).
Lipid segregation is driven by the tendency of sphingolipids to engage special
molecular interactions with cholesterol and to organize in a more ordered
manner than unsaturated phospholipids. By adding a certain amount of
cholesterol to the SM/DOPC mixture, the lipophilic probe DiI-C18 is
squeezed out of the SM-enriched regions and greatly favors the unsaturated
phospholipid-enriched domain. In contrast, in GUVs prepared from SM/DOPC
mixtures, with 80 mol% of SM, DiI-C18 presents a slight
preference for the SM-rich gel-phase.
We have used FCS to systematically analyze lipid mobility and identify the
effect of cholesterol in rafts. FCS has been successfully applied to study
diffusion of lipids and proteins in membranes
(39,
48). Quantitative information
on the average number of the particles in focus and their dynamic properties,
e.g. diffusion coefficients, can be obtained with excellent
statistical accuracy (38). FCS
has been shown to be sensitive to deviations from single-phase behavior,
e.g. caused by heterogeneities in the sample
(39). As lipid rafts are
thought to be dynamic assemblies in membranes, the assessment of lipid dynamic
properties is an important step toward the understanding of how lipids
modulate membrane lipid mobility and, thereby, possibly control the timing of
cellular events, such as sorting or signaling. This technique is less
time-consuming than SPT and, in contrast to FRAP, FCS works at single molecule
regimes. This is a great advantage in experiments on domain formation in
membranes, because of the following. (i) Lipid analogs do not need to be
introduced at high amounts, which have been shown to affect, in some cases,
the lipid organization (48,
49), and (ii) at a single
molecule level, clustering of the dye may be readily spotted. FCS illustrates,
here, the important role of cholesterol in tuning the membrane lipid mobility
in raft-containing membranes. Consistent with previous studies
(32), lipid diffusion in
liquid-disordered phase is 2 times faster than in cholesterol devoid GUVs
(SM/DOPC 0.5/0.5). However, the most remarkable effect is found for the lipid
diffusion in SM-enriched phases, where the mobility increases by a factor of
8 as the cholesterol concentration is increased from 10% up to 33%. This
implies that cholesterol acts as raft-promoting component and, most
importantly, is able to control the lipid dynamics in domains. On the other
hand, the SM level (for SM/DOPC molar ratios 1) does not affect very much
the lipid dynamics in domains. This result might have some physiological
implications, as it implies that cells can alter the SM levels without
altering the dynamic properties of the domains.
The lipid diffusion coefficient characterizes a certain lipid phase composition, given the data reproducibility, the good statistical accuracy of the results and the excellent properties of GUVs as model membranes. Vesicle unilamellarity ensures that the diffusion components in the autocorrelation curve belong only to molecules diffusing within a single bilayer. On the basis of our data, we constructed a phase diagram for the DOPC/SM/cholesterol mixture. The classic method for studying equilibrium between phases in membranes is Differential Scanning Calorimetry (DSC), often combined with infrared and fluorescence spectroscopy (47). Additional information can be extracted by Atomic Force Microscopy (in the sub-micrometer scale) (46), or one- and two-photon fluorescence microscopy (in the µm scale) (30–32). These techniques describe the static lipid organization, whereas, here, we exploit the time dimension and use the dynamic parameters obtained by FCS as a fingerprint for membrane phases. We have identified regions of lipid compositions that give rise to phase separation and obtained information on the phase transition points. A large amount of literature has been previously reported on phase diagrams of similar ternary systems (Refs. 47 and 51, see Ref. 52 for an excellent review). Our data on lipid dynamics add new information as we show how membrane lipid mobility changes, not only between different phase regions but also within a particular region.
In conclusion, FCS has been proven to be a valuable tool to assess the molecular basis of lipid mobility in raft-like domains, which is crucial for our understanding of the dynamics of many biological processes. Here, we focused on the role of cholesterol in promoting phase separation and increasing the lipid mobility in SM-enriched phases. In addition, by using the dynamic parameters obtained by FCS, we built a phase diagram, which reports on the lipid dynamic properties within different lipid phases.
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FOOTNOTES |
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Recipient of Short Term EMBO Fellowship ASTF66-2002.
|| To whom correspondence should be addressed. Tel.: 31-50-3634190; Fax: 31-50-3634165; E-mail: b.poolman{at}chem.rug.nl.
1 The abbreviations used are: FCS, fluorescence correlation spectroscopy;
GUVs, giant unilamellar vesicles; LUVs, large unilamellar vesicles; DOPC,
L-
-dioleoyl-phosphatidylcholine; SM,
N-stearoyl-D-erythrosphingosylphosphorylcholine;
DiI-C18,
1,1'-dioctadecyl-3,3,3',3'-tetramethylindocarbocyanine
perchlorate; MCD, methyl--cyclodextrin; ITO, indium tin oxide.
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ACKNOWLEDGMENTS |
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REFERENCES |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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20 mol% cholesterol was
too low to be measured by FCS. D, average diffusion coefficients, as
determined from the fitting of the autocorrelation curves in C, are
reported as a function of cholesterol concentration. Bars represent
the S.D. from the average values (see ``Materials and Methods'' for details).
E, FCS autocorrelation curves are shown for DiI-C18
mobility in DOPC/SM GUVs, short dash dot (a) for 0 mol%,
short dot (b) for 20 mol%, short dash (c)
for 33 mol%, dash dot dot (d) for 42 mol%, dash dot
(f) for 50 mol%, dot (e) for 67 mol%, dash
(g) for 74 mol%, and solid (h) for 80 mol% SM.
F, average diffusion coefficients, as determined from fitting of the
autocorrelation curves in E, are reported as a function of SM
concentration. Bars represent the S.D. from the average values (see
``Materials and Methods'' for details).