Sebastian Thallmair1, Helgi I Ingólfsson1,2, Siewert J Marrink1. 1. Groningen Biomolecular Sciences and Biotechnology Institute and The Zernike Institute for Advanced Material , University of Groningen , Nijenborgh 7 , 9747 AG Groningen , Netherlands. 2. Biosciences and Biotechnology Division, Physical and Life Sciences Directorate , Lawrence Livermore National Laboratory , 7000 East Avenue , Livermore , 94550 California , United States.
Abstract
The plasma membrane is a highly complex multicomponent system that is central to the functioning of cells. Cholesterol, a key lipid component of the plasma membrane, promotes the formation of nanodomains. These nanodomains are often correlated across the two membrane leaflets, but the underlying physical mechanism remains unclear. Using coarse-grained molecular dynamics simulations, we investigate the influence of cholesterol flip-flop on membrane properties, in particular, the interleaflet coupling of cholesterol-enriched domains. We show that the cholesterol density correlation between the leaflets of an average mammalian plasma membrane is significantly reduced by suppressing interleaflet cholesterol population. Our results suggest an amplifying role of cholesterol in signal transduction across the leaflets.
The plasma membrane is a highly complex multicomponent system that is central to the functioning of cells. Cholesterol, a key lipid component of the plasma membrane, promotes the formation of nanodomains. These nanodomains are often correlated across the two membrane leaflets, but the underlying physical mechanism remains unclear. Using coarse-grained molecular dynamics simulations, we investigate the influence of cholesterol flip-flop on membrane properties, in particular, the interleaflet coupling of cholesterol-enriched domains. We show that the cholesterol density correlation between the leaflets of an average mammalian plasma membrane is significantly reduced by suppressing interleaflet cholesterol population. Our results suggest an amplifying role of cholesterol in signal transduction across the leaflets.
The plasma
membrane (PM) plays
a central role in biology by serving as the border of living cells,
separating the cell interior from its environment. Typically, hundreds
of different lipid types are present in the PM.[1,2] The
complexity of the PM gives rise to structural and compositional heterogeneity,
as expressed by the raft concept.[3,4]A major
component of cellular membranes is cholesterol (CHOL).
In various model membranes and over a substantial range of compositions,
cholesterol induces phase separation into cholesterol-enriched liquid
ordered (Lo) and cholesterol-depleted liquid disordered
(Ld) domains.[5,6] Such domains are also
observed in membranes extracted from real cells, pointing to their
potential biological relevance as a membrane organizing principle.[7,8]Interestingly, in many cases, the domains in both leaflets
appear
to be correlated.[9−11] Currently, multiple theories exist about the major
driving force for this domain registration, including curvature coupling,
interleaflet midplane tension, line tension of the domain boundary,
chain interdigitation, electrostatic coupling, and cholesterol flip-flop.[12−14] Molecular dynamics (MD) simulations are, in principle, suited to
unravel these driving forces. In fact, a number of recent simulation
studies address the issue of domain registration and point to a variety
of factors that contribute to alignment or even anti-alignment of
the domains.[15−21] The extent of domain registration therefore involves multiple factors
and appears highly system-dependent.Whereas the molecular mechanism
of CHOL flip-flop has been investigated
in detail by means of MD simulations,[22−24] a few studies have started
to look at the CHOL influence on domain registration exploiting net
CHOL translocation between the leaflets,[25] the aliphatic chain length of CHOL,[16] or increasing CHOL concentration.[26] Chloroform,
which, like CHOL, rapidly flip-flops between the leaflets, has been
shown to drive phase registration in ternary model membranes.[19] Here, using coarse-grain (CG) MD simulations,
we investigate the contribution of cholesterol flip-flop to the domain
registration without changing the chemical nature of CHOL or the bilayer
composition. We use simple model systems consisting of three to four
lipid types[27] and our recently developed
realistic mammalian PM model[28,29] and compare simulations
where the CHOL flip-flop was suppressed with ones allowing CHOL flip-flop.
We applied two different flat-bottomed potentials to suppress CHOL
flip-flopping (Figure S1): “wider”
potentials (denoted fb3.5), allowing CHOL to populate the region between
both leaflets,[22] and “thinner”
potentials (fb1.6), restricting CHOL to the individual leaflets. Besides
the influence on domain registration, we analyze global membrane properties
like area per lipid (APL), lipid tail order, and bilayer thickness.First, we will discuss the behavior of the ternary mixtures, followed
by the quaternary mixture and the mammalian PM model. The ternary
mixture consists of either dipalmitoylphosphatidylcholine (DPPC)/dilinoleoylphosphatidylcholine
(DLiPC)/CHOL at a molar ratio of 0.42/0.28/0.30 or DPPC/dioleoylphosphatidylcholine
(DOPC)/CHOL at a molar ratio of 0.64/0.16/0.20. The first mixture
is strongly phase-separating due to the presence of the polyunsaturatedDLiPClipid, whereas the second mixture forms only small transient
domains at the CG resolution of the employed Martini force field. Figure a shows the final
snapshot of the DPPC/DLiPC/CHOL bilayer after 30 μs. The phase
separation of DPPC (saturated tails) and DLiPC (double unsaturated
tails) is clearly visible; CHOL preferentially resides in the DPPC-enriched
Lo domains. The two domains are registered across the leaflets.
Figure 1
Lipid
mixtures of DPPC/DLiPC/CHOL (a,d), DPPC/DOPC/CHOL (b,e),
and DPPC/DOPC/DLiPC/CHOL (c,f). (a–c) Top and side views of
the membrane organization after 30 μs of simulation without
any restrictions on CHOL. DPPC, blue; DOPC, purple; DLiPC, red; CHOL,
yellow. The phospholipid headgroups are omitted for clarity. (d–f)
Distributions of the Pearson correlation of the CHOL densities of
the two leaflets evaluated for the last 20 μs of the simulations.
Snapshots were taken every 500 ps without averaging.
Lipid
mixtures of DPPC/DLiPC/CHOL (a,d), DPPC/DOPC/CHOL (b,e),
and DPPC/DOPC/DLiPC/CHOL (c,f). (a–c) Top and side views of
the membrane organization after 30 μs of simulation without
any restrictions on CHOL. DPPC, blue; DOPC, purple; DLiPC, red; CHOL,
yellow. The phospholipid headgroups are omitted for clarity. (d–f)
Distributions of the Pearson correlation of the CHOL densities of
the two leaflets evaluated for the last 20 μs of the simulations.
Snapshots were taken every 500 ps without averaging.Table lists the
global membrane properties of the DPPC/DLiPC/CHOL bilayer. The average
APL remains almost unchanged upon restricting CHOL flip-flop. A similar
behavior is observed for the area compressibility, the tail order,
as well as the bilayer thickness. Overall, the global membrane properties
are virtually unaffected by the restriction of the CHOL flip-flop.
Table 1
Membrane Properties of the Ternary
Mixtures DPPC/DLiPC/CHOL and DPPC/DOPC/CHOLa
DPPC/DLiPC/CHOL
DPPC/DOPC/CHOL
w/o flip-flop
w/o flip-flop
w/flip-flop
fb3.5
fb1.6
w/flip-flop
fb3.5
fb1.6
average APL (nm2)b
0.736
0.737
0.738
0.659
0.660
0.659
average area compressibility (mN/m)b
399 ± 5
407 ± 5
411 ± 7
389 ± 4
392 ± 6
391 ± 7
average tail order DPPCc
0.634
0.626
0.639
0.533
0.534
0.535
average tail order DLiPC/DOPCc
0.244
0.245
0.241
0.380
0.382
0.382
average bilayer
thickness (nm)c
4.071
4.075
4.061
4.191
4.190
4.190
CHOL flip-flop rate (106 s–1)b
5.45 ± 0.08
0.0
0.0
1.77 ± 0.05
0.0
0.0
All errors are standard errors
and were omitted if ≤0.002.
Averaged over the last 10 μs.
Averaged over the last 2 μs.
All errors are standard errors
and were omitted if ≤0.002.Averaged over the last 10 μs.Averaged over the last 2 μs.To analyze the extent by which cholesterol
flip-flop affects the
composition of the Lo and Ld domains, we evaluated
the relative number of neighboring lipids for each lipid type (listed
in Table S2). DPPC and CHOL prefer to be
surrounded by each other or themselves, whereas they try to avoid
DLiPC. On the contrary, DLiPC prefers itself in its surrounding, in
line with the strong phase separation apparent from the snapshots
(Figure a). This trend
is unaffected by the CHOL flip-flop.Finally, we analyzed the
spatial correlation of the CHOL densities
of the upper and lower leaflet, which provides a measure for the registration
of the CHOL domains. In doing so, we extract the positions of the
polar CHOL headgroups in each leaflet, convert it to a continuous
density using a Gaussian kernel of σ = 15
Å, and calculate the Pearson correlation between the CHOL densities
of the lower and upper leaflet (for details, see the SI). Figure d illustrates the distribution of the Pearson correlation for the
DPPC/DLiPC/CHOL system in the last 20 μs of the simulations.
The distributions exhibit a Gaussian shape and show no changes if
CHOL flip-flop is restricted (maximum at 0.866 ± 0.001 with flip-flop,
0.863 ± 0.001 with fb3.5, 0.866 ± 0.001 with fb1.6). The
maxima were determined by fitting a Gaussian function. The temporal
evolution of the correlation of all three systems is depicted in Figure S6, showing a convergence of these data
on a time scale of ∼4 μs. Apparently, restricting the
CHOL flip-flop has virtually no effect on the interleaflet registration.
To verify the CHOL density as a suitable measure of the domain registration,
we also calculated the interleaflet correlation of the saturated (DPPC)
and unsaturated (DLiPC) lipid densities, which are depicted in Figure S8.An overall similar picture arises
for the second ternary mixture
investigated (DPPC/DOPC/CHOL). The final snapshot of the bilayer after
30 μs is depicted in Figure b. A non-ideal mixing of DPPC and DOPC is visible,
but there is no clear domain formation. Because of the higher DPPC
content, the CHOL flip-flop rate is smaller by a factor of ∼3.
The average APL, area compressibility, tail order, and bilayer thickness
are listed in Table . As in the previous example, these global membrane properties are
unaffected by restricting the CHOL flip-flop.The lower tendency
of the DPPC/DOPC/CHOL bilayer to form defined
lateral domains is also reflected in the relative number of neighboring
lipids (Table S3). The unsaturatedlipidDOPC still prefers itself over DPPC or CHOL as a neighbor, but the
relative preference is reduced to 1.38 compared to 2.18 for DLiPC.
Again, CHOL flip-flop has no significant effect on the relative numbers
of neighboring lipids.Because the bilayer does not show a clear
tendency to phase-separate
in our simulations, the Pearson correlation of the CHOL densities
is slightly negative (−0.011 ± 0.001 for the simulations
with flip-flop; Figure e). It has a broader distribution compared to the DPPC/DLiPC/CHOL
system and does not change upon CHOL restriction (fb3.5: −0.020
± 0.001, fb1.6: −0.025 ± 0.001). Together, our data
on ternary mixtures show that the degree of domain registration is
sensitive to system composition, in line with previous results,[17] but that cholesterol flip-flop has no significant
contribution.To approach the complexity of the PM, we investigate
the quaternary
lipid mixture DPPC/DOPC/DLiPC/CHOL 0.37/0.14/0.19/0.30. The number
of unsaturated, singly unsaturated, and double unsaturated tails mimics
their fraction in our idealized mammalian PM mixture. The final snapshot
of the bilayer after 30 μs is depicted in Figure c. Here the formation of nanodomains
is visible. In contrast to DPPC/DLiPC/CHOL (see Figure a), where full macroscopic
phase separation occurs, the lipid domains of the DPPC/DOPC/DLiPC/CHOL
mixture are smaller and more dynamic (Figure S7 and Table S1).The average APL,
area compressibility, tail order, and bilayer
thickness are listed in Table S6. These
global membrane properties show an overall similar picture compared
to the ternary mixtures and are unaffected by restricting the CHOL
flip-flop. In the unrestraint simulation, the CHOL flip-flop rate
is 4.82 × 106 s–1, which is slightly
reduced compared to DPPC/DLiPC/CHOL (5.48 × 106 s–1).The tendency to form lateral domains
is also reflected in the relative
number of neighboring lipids (Table S4).
The unsaturatedlipidsDLiPC and DOPC prefer themselves as neighbors
over DPPC and CHOL. In addition, they prefer the same unsaturatedlipid more than the other type. DPPC prefers itself and CHOL as neighbors;
CHOL prefers DPPC and clearly disfavors DLiPC. Again, CHOL flip-flop
has no significant effect on the relative numbers of neighboring lipids.Because the bilayer does not show full macroscopic phase separation,
the Pearson correlation of the CHOL densities ρCHOL is smaller than that in the DPPC/DLiPC/CHOL system. However, the
tendency to form small lateral domains can be clearly recognized in
the distributions of the Pearson correlation of the CHOL densities
in Figure f. The simulations
with flip-flop show a mean value of 0.208 ± 0.002 (fb3.5: 0.246
± 0.003, fb1.6: 0.030 ± 0.001). Whereas by restricting CHOL
with the wider flat-bottomed potential, the interleaflet correlation
slightly increases, the narrower one results in a drastic decrease.
A control simulation using the final snapshot of the unrestrained
simulation as the starting configuration shows that after 2 μs
the correlation decreases to −0.013 ± 0.005 (Figure S9). This assigns a key role to the CHOL
interleaflet population in driving domain registration.Let
us now take a look at the impact of CHOL flip-flop on an idealized
average PM mixture, consisting of >60 different lipid types asymmetrically
distributed between the two leaflets.[28] The final snapshot of the simulated PM patch after 100 μs
with CHOL flip-flop is depicted in Figure a. The asymmetric composition can be easily
recognized. Despite this, the clustering of the glycolipids (red)
is clearly noticeable.[28]
Figure 2
Final snapshot of the
average PM simulated with CHOL flip-flop
at 100 μs. (a) Top and side views of the membrane organization.
The lipids are colored according to their headgroups: PC, blue; PE,
cyan; SM, gray; PS, green; glycolipids, red; PI, pink; PA, white;
PIPs, magenta; CER, ice blue; DAG, brown; CHOL, yellow. (b) Snapshot
of the final CHOL density calculated with a Gaussian kernel of σ = 15 Å. (c) Distributions of the Pearson correlation
of the CHOL densities of the two leaflets evaluated for the last 80
μs of the simulations. Snapshots of the CHOL densities were
taken every 500 ps without averaging. (d) Mean Pearson correlation
depending on the Gaussian kernel size σ used to calculate the
CHOL density.
Final snapshot of the
average PM simulated with CHOL flip-flop
at 100 μs. (a) Top and side views of the membrane organization.
The lipids are colored according to their headgroups: PC, blue; PE,
cyan; SM, gray; PS, green; glycolipids, red; PI, pink; PA, white;
PIPs, magenta; CER, ice blue; DAG, brown; CHOL, yellow. (b) Snapshot
of the final CHOL density calculated with a Gaussian kernel of σ = 15 Å. (c) Distributions of the Pearson correlation
of the CHOL densities of the two leaflets evaluated for the last 80
μs of the simulations. Snapshots of the CHOL densities were
taken every 500 ps without averaging. (d) Mean Pearson correlation
depending on the Gaussian kernel size σ used to calculate the
CHOL density.Table summarizes
the global membrane properties of the PM with and without CHOL flip-flop.
Similar to the simpler mixtures, they are mostly unchanged. The APL
is almost unaffected by suppressing CHOL flip-flop, with a maximum
difference of 0.004 nm2 lower in the case of the wide flat-bottomed
potential (fb3.5). Without CHOL flip-flop, the average tail order
parameter in the outer leaflet slightly increases, while the trend
in the inner leaflet is not so clear. The reason might be that the
overall level of saturation is higher for the outer leaflet (Table S7). The average bilayer thickness measured
at the phosphate groups decreases as well, especially for fb1.6. The
area compressibility increases slightly when applying fb1.6. These
observations could be traced back to the missing CHOL population in
the bilayer middle, as fb1.6 does not allow the space between the
leaflets to be populated. The resulting slightly higher CHOL concentration
in the leaflets increases the lipid packing and thus the order parameter
and the area compressibility. The CHOL flip-flop rate in the reference
simulation is comparable to the one of the DPPC/DLiPC/CHOL mixture
(Table ).
Table 2
Membrane Properties of the Average
PMa
w/o flip-flop
w/flip-flop
fb3.5
fb1.6
outer average APL (nm2)b
0.503
0.499
0.502
inner average APL (nm2)b
0.542
0.538
0.541
average area compressibility (mN/m)b
367 ± 12
378 ± 12
396 ± 5
outer average tail orderc
0.429
0.430
0.436
inner average
tail orderc
0.379
0.376
0.382
average bilayer thickness (nm)c
4.166
4.162
4.138
CHOL flip-flop rate (106 s–1)b
5.48 ± 0.02
0.0
0.0
All errors are standard errors
and were omitted if ≤0.002.
Averaged over the last 10 μs.
Averaged over the last 40 μs.
All errors are standard errors
and were omitted if ≤0.002.Averaged over the last 10 μs.Averaged over the last 40 μs.To characterize the degree of lateral
inhomogeneity in the PM patch, Table S5 lists the relative number of neighboring
lipids in the average PM. The majority of the lipid neighbors do not
change when the CHOL flip-flop is restricted. The most striking effect
appears for the lipids with two unsaturated tails in the outer leaflet;
they have a larger tendency to be surrounded by themselves, whereas
lipids with one or two saturated tails are slightly more depleted
in their environment. Surprisingly, the amount of CHOL in their surroundings
is not influenced. For the inner leaflet, this effect is of only minor
importance.Finally, we take a look at the Pearson correlation
of the CHOL
densities in the outer and inner leaflet of the PM evaluated for the
last 80 μs of the simulations. The CHOL densities were calculated
using a Gaussian kernel of σ = 15 Å (cf. SI). Figure c shows their distributions evaluated for single snapshots.
Their width is somewhat smaller than the ones of the DPPC/DOPC/CHOL
bilayer. In the simulated patch with CHOL flip-flop, a correlation
of 0.034 is observed. By applying the wider flat-bottomed potential
the correlation remains almost unchanged (0.039), but it is reduced
to −0.012 in the case of fb1.6 (all errors ≤0.0003).
Corresponding to the quaternary mixture, the narrower flat-bottomed
potential leads to a significant decrease in the CHOL density correlation. Figure d depicts the influence
of the Gaussian kernel size σ on the interleaflet CHOL correlation.
For σ < 30 Å, fb1.6 shows a reduced CHOL correlation.
For larger σ, the difference becomes blurred.We performed
additional control simulations for the PM mixture
where we suppressed CHOL flip-flop starting from the final snapshot
after 100 μs of the PM patch simulated with flip-flop. These
simulations were performed for 20 μs. Figure S10 depicts the distributions of the Pearson correlation of
the CHOL densities of the two leaflets evaluated for the last 15 μs
of these control simulations. The maximum of the distributions is
at 0.015 ± 0.001 using fb3.5 and at −0.003 ± 0.001
using fb1.6, respectively, showing that suppressing the interleaflet
CHOL population leads to a deregistration of the CHOL densities in
both leaflets.In summary, we investigated the effect of CHOL
flip-flop by means
of CG MD simulations of four different lipid bilayers: the ternary
mixtures DPPC/DLiPC/CHOL and DPPC/DOPC/CHOL, the quaternary mixture
DPPC/DOPC/DLiPC/CHOL, as well as a more complex idealized mammalian
PM model. In all four cases, no striking changes of the global membrane
properties or in terms of the lipid mixing were observed. For the
ternary mixtures, the correlation of the CHOL densities in the upper
and lower leaflet was also unaffected by CHOL flip-flop, but distinct
changes were observed for the quaternary mixture and the PM model.
While a restriction with the wider flat-bottomed potential fb3.5 inflicted
no changes (or even an increase for the quaternary mixture), suppressing
the interleaflet CHOL population (fb1.6) resulted in a significant
decrease in the CHOL density correlation. This is remarkable because
it shows that it is not the flip-flop process itself that increases
correlation between the leaflets but that it results from the intermediate
state where CHOL is sandwiched between the leaflets. This state is
significantly populated, in particular, in the presence of (poly)unsaturatedlipids in line with neutron scattering data.[22]Taken together, our results demonstrate a remarkable impact
of
CHOL flip-flop on the domain registration, most pronounced in complex
lipid bilayers. A possible explanation for the dependency of this
effect on the system composition is obtained by considering the different
nature of the domains in the four studied systems. The DPPC/DLiPC/CHOL
mixture is strongly phase-separating and the interleaflet surface
tension is likely the major driving force for the strong domain coupling.[27] In the case of the DPPC/DOPC/CHOL mixture, only
small transient DOPC clusters are formed, which might have a too small
spatial extent and a too short lifetime (Figure S7 and Table S1) to be influenced
by the CHOL flip-flop. Although the domains in the quaternary mixture
and the PM are also transient, their larger extent together with their
dynamic flexibility allows them to react to the presence of an
interleaflet CHOL population (see Figure ). This interleaflet CHOL prefers Ld domains in its surrounding because they offer more space and enable
a better embedding of the CHOL molecules. Thus interleaflet CHOL leads
to a weak repulsion of Lo domains, resulting in an increased
interleaflet correlation (Figure , bottom). A recent simulation study showing that interleaflet
CHOL prefers registered Ld domains over registered Lo domains and anti-registered domains in DPPC/DLiPC/CHOL mixtures[26] supports this idea.
Figure 3
Changes of the interleaflet
correlation of the CHOL densities by
restricting CHOL flip-flop relative to the unrestricted bilayer (top).
Schematic presentation of the effect of the interleaflet CHOL population
to promote phase registration (bottom; CHOL, yellow): The interleaflet
CHOL prefers to stay between registered Ld phases (red).
It repels the lipids in the gray shaded part of the Lo phase
(blue) and thus enhances registration.
Changes of the interleaflet
correlation of the CHOL densities by
restricting CHOL flip-flop relative to the unrestricted bilayer (top).
Schematic presentation of the effect of the interleaflet CHOL population
to promote phase registration (bottom; CHOL, yellow): The interleaflet
CHOL prefers to stay between registered Ld phases (red).
It repels the lipids in the gray shaded part of the Lo phase
(blue) and thus enhances registration.On a more general note, our study shows that CHOL serves
as an
efficient signaling molecule transferring information between the
leaflets by populating the interleaflet space. Through the alignment
of (transient) domains, CHOL can quickly transfer local density gradients
across the leaflets. Proteins being omnipresent in biological membranes
might trigger such small local density gradients, for example, by
their individual lipid fingerprint.[33] Together
with the help of CHOL, this could potentially steer a variety of cellular
processes that depend on lateral membrane organization.
Computational
Methods
All MD simulations were performed with the CG force
field Martini
(version 2.2)[30,31] using the MD package GROMACS
(versions 4.6.7 and 2016.1).[32] We applied
flat-bottomed potentials in the direction of the membrane normal to
the CHOL molecules to suppress their flip-flopping between the leaflets
(Figure S1). Two different widths were
used: “wider” potentials with a flat region of 3.5 nm
(denoted fb3.5), allowing CHOL to populate the region between both
leaflets, and “thinner” potentials with a flat region
of 1.6 nm (fb1.6), restricting the polar CHOL heads to the lipid linker
region. As a reference, additional simulations without any restrictions
to CHOL were performed for each bilayer. For further details of the
bilayer compositions and the simulation setup, see the SI.
Authors: Siewert J Marrink; H Jelger Risselada; Serge Yefimov; D Peter Tieleman; Alex H de Vries Journal: J Phys Chem B Date: 2007-06-15 Impact factor: 2.991
Authors: Sarah L Veatch; Pietro Cicuta; Prabuddha Sengupta; Aurelia Honerkamp-Smith; David Holowka; Barbara Baird Journal: ACS Chem Biol Date: 2008-05-16 Impact factor: 5.100
Authors: W F Drew Bennett; Justin L MacCallum; Marlon J Hinner; Siewert J Marrink; D Peter Tieleman Journal: J Am Chem Soc Date: 2009-09-09 Impact factor: 15.419
Authors: Siewert J Marrink; Valentina Corradi; Paulo C T Souza; Helgi I Ingólfsson; D Peter Tieleman; Mark S P Sansom Journal: Chem Rev Date: 2019-01-09 Impact factor: 72.087
Authors: Yang Liu; Alex H De Vries; Jonathan Barnoud; Weria Pezeshkian; Josef Melcr; Siewert J Marrink Journal: J Phys Chem B Date: 2020-05-01 Impact factor: 2.991