Roughness of Transmembrane Helices Reduces Lipid Membrane Dynamics.

The dynamics of cellular membranes is primarily determined by lipid species forming a bilayer. Proteins are considered mainly as effector molecules of diverse cellular processes. In addition to large assemblies of proteins, which were found to influence properties of fluid membranes, biological membranes are densely populated by small, highly mobile proteins. However, little is known about the effect of such proteins on the dynamics of membranes. Using synthetic peptides, we demonstrate that transmembrane helices interfere with the mobility of membrane components by trapping lipid acyl chains on their rough surfaces. The effect is more pronounced in the presence of cholesterol, which segregates from the rough surface of helical peptides. This may contribute to the formation or stabilization of membrane heterogeneities. Since roughness is a general property of helical transmembrane segments, our results suggest that, independent of their size or cytoskeleton linkage, integral membrane proteins affect local membrane dynamics and organization.

Introduction

Membranes support many vital functions of living cells. Diverse lipid species form the structural basis of cellular membranes. Lipids are also the main determinants of a membrane's physical properties (e.g., fluidity and continuity), which, in turn, influence the probability of the intermolecular interactions of its constituents (Bernardino de la Serna et al., 2016). On the other hand, proteins are key effectors involved in membrane-associated processes such as cell adhesion, signaling, and metabolism. Proteins constitute up to 50% of the total membrane mass (Dupuy and Engelman, 2008). A large part of these proteins is fully integrated into the hydrophobic core of membranes via one or more transmembrane domains (TMDs), which are in direct contact with lipids. This presents an important question: “How do integral proteins influence membrane properties”?

Detailed data are available on how the lipid composition, temperature, and surrounding environment (e.g., ions) influence membrane properties and organization in the absence of proteins (for review, see Heberle and Feigenson, 2011). However, little is known about these parameters when integrated peptides or proteins are present in lipid membranes. Structural studies of membrane proteins have suggested extensive trapping of lipid acyl chains at the surface of the transmembrane (TM) segments (Hite et al., 2010), but do not provide any insight into the more general consequences of this phenomenon. Early spectroscopy measurements (electron paramagnetic resonance or electron spin resonance spectroscopy [EPR/ESR] and nuclear magnetic resonance [NMR]) uncovered the existence of annular (or boundary) lipids forming the first shell surrounding the TM segments of membrane proteins (Brotherus et al., 1981, Jost et al., 1973, Jost et al., 1977, Bienvenue et al., 1982). Annular lipids exhibit restricted rotational mobility, slower exchange rates, and altered conformational order of acyl chains compared with the lipids in protein-free membranes (Marsh, 2008). Such altered lipid properties were observed for the first shell, but did not extend to the lipids of the bulk membrane (for the review, see Marsh, 2008). Moreover, in these experiments, the lipid annulus was easily detected when large, multispanning proteins (e.g., rhodopsin or cytochrome c oxidase) were tested. On the contrary, only small changes in the physical properties of annular lipids were detected in membranes containing simple TM peptides, and these were largely attributed to hydrophobic mismatch (Marsh, 2008, de Planque et al., 1998, de Planque et al., 1999). This phenomenon is caused by the mismatch between the length of a hydrophobic peptide and the thickness of the membrane's hydrophobic core. The mismatch leads to the deformation of lipid acyl chains and, possibly, the formation of lipid domains (de Planque and Killian, 2003, Anderson and Jacobson, 2002, Mouritsen and Bloom, 1984). These spectroscopic data, supported by fluorescence quenching experiments (London and Feigenson, 1981), led to the conclusion that large integral proteins, with their hard surface and low mobility, affect lipid dynamics in membranes, including those in cells (Marsh, 2008, Nyholm, 2015). It is important to note that protein aggregation, formation of domains, and membrane multilamellarity, which may contribute to the measured changes in spectra, could not be controlled in these pilot works on proteo-membranes. The abovementioned spectroscopic techniques are also limited by narrow observation space and low hydration of tested samples.

Recent developments in fluorescence microscopic and spectroscopic techniques enabled more detailed physical characterization of fully hydrated, free-standing, and unilamellar membranes. Using fluorescence correlation spectroscopy (FCS), Ramadurai et al. measured the lateral diffusion of a set of purified proteins reconstituted in free-standing giant unilamellar vesicles (GUVs) and found that protein and lipid diffusion decreased linearly with increasing content of large, multispanning membrane proteins (Ramadurai et al., 2009). The results were interpreted as an impact of protein crowding, in agreement with existing theoretical predictions (Saxton, 1987). These conclusions were supported by calculated anomality parameters (α), but remain controversial owing to the low protein surface density of tested samples (<3,000 proteins/μm2). The effect of obstacles is limited to large or immobile objects at high concentrations (Oppenheimer and Diamant, 2011). Low concentrations of proteins were used probably due to inefficient reconstitution of such large purified proteins in tested membranes. In addition, the proteins were mobile (Ramadurai et al., 2009). Furthermore, most proteins in cellular membranes are rather small (single spanners; Pieper et al., 2013). In their other two works, Ramadurai et al. again used FCS and well-defined membranes to demonstrate the altered diffusion of proteins in membranes with extensive hydrophobic mismatch (Ramadurai et al., 2010a, Ramadurai et al., 2010b). The lateral mobility of both large membrane proteins and TM peptides of varying length was measured in membranes of different thickness. However, the effect of increased protein or peptide content in membranes was not tested in these studies. It is most likely that, in cellular membranes composed of a broad spectrum of lipid species, any temporary hydrophobic mismatch will be rapidly compensated by the lipids that match the TM segment of a protein. We were therefore interested in whether small, highly mobile proteins at near-physiological concentrations can influence membrane dynamics in the absence of previously described mechanisms such as protein crowding and aggregation or hydrophobic mismatch.

Cholesterol is an essential component of selected cellular membranes (van Meer et al., 2008). Its impact on protein-free membranes is well described (Mouritsen and Zuckermann, 2004). Cholesterol increases the rigidity of highly fluid, disordered membranes but has a disordering (fluidifying) effect on membranes composed of highly rigid lipids with low melting temperatures (Tm). The presence of cholesterol increases the membrane thickness (Gallova et al., 2004) and reduces the probability of membrane penetration by hydrophilic molecules (Raffy and Teissie, 1999). Very few studies have investigated protein- or peptide-containing membranes in the presence of cholesterol (Nystrom et al., 2010, Kaiser et al., 2011). It was shown there that increasing presence of TM peptides affects cholesterol partitioning into membranes (Nystrom et al., 2010) and, in a reverse setup, that increasing the concentration of cholesterol leads to the aggregation of TM peptides (Kaiser et al., 2011). These data indicate that TMDs of proteins can influence the properties of cholesterol-containing membranes, but they do not provide more detailed insight into the interrelation between TM segments of proteins and cholesterol. In this work, we tested the impact of a simple TM peptide on membrane dynamics in the absence and presence of physiological levels of cholesterol (25 mol %).

Results

Reduced Lateral Diffusion and Increased Local Viscosity in Membranes with Helical Transmembrane Peptides

To investigate the direct impact of small and mobile TM proteins on membrane dynamics, we first adjusted our experimental model to minimize the impact of hydrophobic mismatch, molecular clusters, and crowding or membrane lipid domains on measured parameters. To comply with all these conditions, we focused on model membranes with only two components: α-helical TM peptides and phospholipids (Figure S1). The synthetic, highly purified TM peptide (LW21: GLLDSKKWWLLLLLLLLALLLLLLLLWWKKFSRS) and DOPC (dioleoyl phosphatidylcholine) were selected based on a number of prerequisites: (1) the peptide is monomeric and does not aggregate in DOPC membranes (Figure S2, Sparr et al., 2005), (2) there is no hydrophobic mismatch between the TM segment of the LW21 peptide and the thickness of DOPC membranes (Kaiser et al., 2011), (3) the LW21 peptide adopts a transbilayer orientation and α-helical structure in DOPC membranes (Kaiser et al., 2011, Machan et al., 2014), and (4) DOPC, with its low melting point of −18.3°C, provides a highly fluid lipid environment with no detectable nanodomains in all tested vesicles in the absence and presence of 25 mol % cholesterol (Stefl et al., 2012). Importantly, LW21 and similar TM peptides have comparable size with lipids and are highly mobile in DOPC vesicles (Figure 1A; Ramadurai et al., 2009). Therefore, no crowding is expected in membranes composed of LW21 peptides and DOPC. Finally, we have selected these components to comply with the prevalent α-helical structure of TMDs and dominance of glycerophospholipids in mammalian cell membranes.

Figure 1

Impeded Local Viscosity and Lateral Diffusion in Membranes with Peptides

(A) Lateral diffusion coefficients of the lipid tracer (DiD; full lines) and fluorescently labeled LW21 peptide (dashed lines) were measured in GUVs composed of DOPC (black and red lines) and DOPC:cholesterol (75:25; blue and yellow lines) in the presence of increasing concentrations of unlabeled peptides. Each presented diffusion coefficient (D) was measured for at least 10 vesicles in three independent experiments using the calibration-free z-scan FCS technique. Error bars indicate standard deviations (SD).

(B) Local lipid mobility (viscosity) as a function of increasing peptide concentration was determined in the absence (black squares) or presence (blue circles) of 25 mol % cholesterol using a Laurdan fluorescent probe by TRES. The relaxation time τR reports on the local lipid mobility. Error bars represent intrinsic uncertainty of the method.

(C) Lateral diffusion coefficients of the lipid tracer (DiD; gray and blue bars) and fluorescently labeled LW21 peptide (red and yellow bars) were measured in GUVs composed of DOPC:PAPC (90:10; black and red bars) and DOPC:PAPC:cholesterol (65:10:25; blue and yellow bars), in the absence and presence (3 mol %) of the unlabeled peptide. Each presented diffusion coefficient (D) was measured for at least 8 vesicles in two independent experiments using calibration-free z-scan FCS technique. Error bars indicate SD.

To our knowledge, no molar concentrations were experimentally determined for lipids and proteins in cell membranes to date. However, proteins were found to form around one-half of total mass in cellular membranes (Dupuy and Engelman, 2008). By considering a small size of lipids (∼1 kDa) and an average size of proteins (∼40 kDa; Brocchieri and Karlin, 2005), we estimate the molar concentration of proteins in cell membranes to be approximately 2.5 mol %. Therefore, we have examined free-standing model membranes (GUVs) containing 0–3 mol % of the LW21 peptide. The calibration-free z-scan FCS technique (Benda et al., 2003) was used to measure lateral diffusion of the fluorescent lipid tracer, DiD, and fluorescently labeled LW21 embedded in membranes. In Figure 1A, we demonstrate that increasing the concentration of the monomeric α-helical peptide reduced lateral diffusion of both the lipid tracer and labeled peptide (gray and red lines, respectively). At the highest tested peptide concentration, 3 mol %, the diffusivity of both molecules was reduced by approximately 35% in DOPC membranes. In agreement with the literature (Weiss et al., 2013), lipid molecules diffused somewhat faster than peptides at all tested peptide concentrations. The observed effect was comparable to the reduction of lateral mobility in membranes with the highest tested concentration of large, multispanning proteins (0.02–0.2 mol %; Ramadurai et al., 2009). However, no anomalous diffusion was observed for all tested compositions (Table S1). Next, the experiments were performed in the presence of 25 mol % cholesterol to better mimic cell membranes (van Meer et al., 2008). The peptide incorporates into membranes with and without cholesterol with comparable efficiency (Figures S3 and S4). The impact of the peptide on the lateral diffusion of membrane components was more pronounced in the presence of cholesterol than in its absence. At the highest peptide concentration, 3 mol %, we observed a 2- to 3-fold decrease in the diffusion coefficients for both tested molecules (Figure 1A). Quantitative analysis supports the enhanced effect of the peptide on the mobility of membrane components in the presence of cholesterol compared with its absence (D25/D0 values; Table S2). Importantly, lateral diffusion of lipids and peptides was indistinguishable in membranes with cholesterol (Figure 1A; blue and yellow lines). Again, no anomalous diffusion was observed in the presence of cholesterol (Table S1).

To characterize the physical properties of membranes containing peptides, we evaluated the dynamics of the peptide-containing membranes at the nanoscale using environment-sensitive fluorescent probes. First, the time-resolved emission spectra (TRES) of a Laurdan probe located at the interface of the hydrophobic and hydrophilic parts of the lipid bilayer at the level of lipid carbonyls were measured (Figure S5). The speed of Laurdan TRES red shift, represented by the relaxation time τR, reports on the local mobility of lipids. The total emission shift Δν reflects hydration of tested membranes. Significant increase of τR as a function of the peptide content in DOPC membranes demonstrates that LW21 hinders lipid mobility (Figure 1B). The hindrance was slightly stronger in the presence of cholesterol compared with its absence (Figure 1B; linear regression slope of 0.05 versus 0.03, respectively), supporting a stronger effect of peptides on lateral diffusion in membranes with the sterol. Interestingly, Δν values remained unchanged under all tested conditions (Table S3), indicating that the presence of the LW21 peptide does not disturb the structural integrity of lipid bilayer. Second, the time-resolved anisotropy of a diphenylhexatriene (DPH) probe was measured to characterize the order and mobility of lipid tails forming the hydrophobic interior of the membrane. The results show the restriction in DPH rotation manifested in the elevated DPH order parameter S in the presence of peptide (Table 1). This effect was preserved in cholesterol-containing membranes, which agrees with the previously published data (Nystrom et al., 2010).

Table 1

Order Parameter S of DPH in Membranes with the LW21 Peptide and the Standard Deviation

Membrane (Large Unilamellar Vesicles)	S (DOPC)	S (DOPC/Cholesterol)
DOPC	0.19 ± 0.06	0.43 ± 0.01
DOPC +3% LW21	0.28 ± 0.04	0.51 ± 0.05
DOPC +10% LW21	0.39 ± 0.02	0.55 ± 0.08

Phospholipids in cellular membranes commonly contain two different fatty acids attached to their head groups, one of which is often polyunsaturated (Harayama and Riezman, 2018). Moreover, polyunsaturated acyl chains tend to preferentially associate with membrane proteins, especially in the presence of cholesterol (Polozova and Litman, 2000, Pitman et al., 2005). To evaluate whether TM peptides modulate the dynamics of membranes with polyunsaturated acyl chains, we measured the mobility of DiD and labeled the LW21 peptide in DOPC membranes containing 10 mol % of palmitoyl-arachidonoylphosphatidylcholine (PAPC). The results shown in Figure 1C demonstrate that the presence of the peptide (3 mol %) reduces the mobility of membrane components by approximately 35%, which is the level comparable to the membranes composed of only DOPC. Again, a greater effect was observed in the presence of 25 mol % cholesterol. The addition of 3 mol % of the LW21 peptide to the cholesterol- and PAPC-containing membranes caused a 2- to 4-fold reduction in the lateral mobility of lipid and peptide probes (Figure 1C). These data demonstrate that small, highly mobile proteins affect the dynamics of membranes containing hybrid lipids with one polyunsaturated acyl chain.

Trapping of Acyl Chains on the Rough Surfaces of Helical Transmembrane Peptides

To better understand the mechanism responsible for the reduced membrane dynamics observed in our experiments, we performed fully atomistic molecular dynamics (MD) simulations of the LW21 peptide in the lipid bilayers composed of DOPC (Video S1). The simulations were performed over 500 ns, including the first 200 ns used for the equilibration of the system. The data confirmed that the mobility of the lipids close to the peptide is severely impeded (Figure S6). Interestingly, we observed that this is caused by the rough surface of the peptide and the trapping of acyl chains of annular lipids in the grooves therein (Figures 2A and 2B). Such lipid-peptide contacts are nonspecific (Figure S7) and exhibit substantial stability (Figure 2C). Combined with our experimental data, these findings demonstrate that the mobility of lipids is affected not only by large, multispanning proteins, as reported in recent computational studies (Camley et al., 2010, Niemela et al., 2010), but also by much smaller objects such as a single TMD, owing to its rough surface. In the literature, TMDs are often represented by smooth cylinders (Figure 3A). However, stable helical peptides formed by native amino acids are intrinsically rough (Figure 3B). The rough surface is formed by amino acid side chains of helical peptides and is not limited to poly-leucine segments. Indeed, a rough surface has been observed in all TMDs of proteins characterized so far by X-ray crystallography or NMR at sufficient resolution (<4.5 Å; PDBTM database, http://pdbtm.enzim.hu/; Kozma et al., 2013).

Figure 2

Lipid Acyl Chain Trapping on the Rough Surface of the LW21 Peptide

(A and B) A typical snapshot from MD simulation of the peptide in the DOPC bilayer, indicating trapping of lipid acyl chains in the grooves formed by peptide side chains. Peptide surface (A) is shown in red. Interacting lipids are shown in different shades of gray using licorice representation (B). Non-interacting lipids and water were removed for clarity. The molecular composition of the system characterized by the MD simulation is in Table S5.

(C) Autocorrelation functions of peptide backbone contact with individual acyl chains, cholesterol, and water in the membranes without and with 25 mol % of cholesterol. A cutoff of 0.75 nm was employed for the definition of contacts.

Figure 3

Rough Surface of Transmembrane Helices

(A) Common illustration styles representing TMDs as smooth cylinders.

(B) On the contrary, helical peptides have inherently rough surfaces formed by amino acid side chains. Poly-glycine, poly-alanine, and poly-isoleucine artificial helical peptides represent diverse sequences composed of single amino acid species. Excepting poly-glycine, all helices exhibit rough surfaces. Oligo-glycine alone does not support helical structure. The combination of amino acids AILS (blue-gray) indicates that the non-homogenous amino acid sequence forms even more extensive roughness. Surface representations for LW21 peptide and 2 TM domains (EpoR— PDB: 2MV6; and nicastrin— PDB: 2N7R) are shown for comparison. The structure of helical peptides (monogenic, AILS, and LW21) was modeled using surface visualization in PyMOL software. These structures do not represent calculated surfaces and are shown solely to indicate roughness of the surface for any combination of amino acids.

Video S1. The Last 100 ns of the 500 ns-Long MD Simulation of the DOPC/LW21 System, Related to Figure 2

Side view (parallel to the bilayer midplane) of the simulation box is shown. The video was created based on the trajectory sampled each 100 ps with the smoothing employed for each three frames. The trajectory was centered with respect to the peptide center of geometry. Rotations with respect to the helix were removed. Phosphorous atoms of DOPC are shown as white balls, and DOPC chains are presented as gray lines. The peptide is depicted using NewCartoon representation with coloring based on the secondary structure (purple, helical; white, non-helical). The remaining atoms and molecules, including water, are not shown for clarity. The video was prepared employing MovieMaker plugin of VMD. H264-MPEG-4 encoding was used.

The data acquired using the LW21 peptide could not be compared with a smooth variant because all α-helix-forming amino acids intrinsically form structures with a rough surface (Figure 3B). Therefore, we have generated coarse-grain toy models of cylinder-like objects with varying surface roughness (M1-M3; Figure 4A) that were embedded in DOPC membranes. The autocorrelation data acquired from MD simulations indicate longer lipid contacts with the rougher models (M3 > M2 > M1; Figure 4B). The acyl chains are entrapped in the grooves of rougher models (M2 and M3), which hinders their mobility (Figure S8). Virtually no trapping was observed on the smooth surface of model M1 (Figure 4B). These results are in agreement with previously published findings regarding the interference of nanoscopically rough surfaces composed of diverse synthetic materials on the mobility of polymers (Wang et al., 2015) and peptides (Shezad et al., 2016). This suggests that cylinder-like objects with rough surfaces embedded in membranes impede lipids similarly to the LW21 peptide.

Figure 4

Rough Surface Interferes with Membrane Dynamics

(A) Toy models (M1–M3) of cylinder-like structures generated using a coarse-grain force field.

(B) The autocorrelation curves for contacts between lipid tails and the surface of model structures M1–M3 with increasing roughness embedded in DOPC membrane, indicating the trapping of acyl chains at the rough surface of M2 and M3. Similar effect was observed in the presence of 25 mol % cholesterol (Figure S9).

Segregation of Cholesterol from the Rough Surface of Helical Transmembrane Peptides

We also performed MD simulations of the LW21 peptide in lipid bilayers composed of DOPC and 25 mol % cholesterol (Videos S2 and S3). We found cholesterol to be excluded from the peptide annulus for the full period of the simulations (500 ns), enabling phospholipid acyl chains to interact preferentially with the rough surface of the peptide (Figure 5). Only very rare and highly transient contacts of cholesterol with the peptide were detected (Figures 2C and 5B). This is probably caused by the incompatibility between the planar shape of cholesterol molecule and the roughness of helical TM peptides, which prefer the flexibility of phospholipid acyl chains (Figure 5F, compare to Figure 2B; Rog et al., 2007).

Figure 5

Cholesterol Segregation from the Rough Surface of the LW21 Peptide

(A) Pair correlation function [g(r)] of phospholipids and cholesterol from the center of mass of the peptide calculated in MD simulations of the LW21 peptide in a DOPC/cholesterol membrane (Video S2). The function quantifies the probability of intermolecular distances between the peptide and lipids with respect to those in an ideally mixed system. The molecular composition of the system characterized by the MD simulation is in Table S5.

(B) Quantification of phospholipid and cholesterol contacts with the peptide in a simulated membrane as in (A). Error bars represent error of the mean estimated by the block averaging method.

(C–E) Distribution maps of phospholipids (C) and cholesterol (D) in membrane containing the peptide. (E) The merged distribution map showing phospholipids in gray, cholesterol in blue and the peptide in red. The peptide was centered, and rotations were removed by data postprocessing.

(F) Cholesterol structure (blue) forms a planar interface that cannot fill the grooves on the surface of the LW21 peptide (red). Structures of both molecules are shown as van der Waals (ball) representations using VMD software. A typical snapshot from the MD trajectory is presented with one representative cholesterol molecule residing in the vicinity of the peptide. Remaining cholesterol molecules, phospholipids (DOPC), and water were removed for clarity.

Video S2. The Last 100 ns of the 500 ns-Long MD Simulation of the DOPC/CHOL/LW21 System, Related to Figure 5

Side view (parallel to the bilayer midplane) of the simulation box is shown. The video was created based on the trajectory sampled each 100 ps with the smoothing employed for each three frames. The trajectory was centered with respect to the peptide center of geometry. Rotations with respect to the helix were removed. Phosphorous atoms of DOPC are shown as white balls, and DOPC chains are presented as gray lines. Cholesterol is shown in red employing the licorice representation. The peptide is depicted using NewCartoon representation with coloring based on the secondary structure (purple, helical; white, non-helical). The remaining atoms and molecules, including water, are not shown for clarity. The video was prepared employing MovieMaker plugin of VMD. H264-MPEG-4 encoding was used.

Video S3. The Last 100 ns of the 500 ns-Long MD Simulation of the DOPC/CHOL/LW21 System as in Video S2 but Highlighting the Annular Lipids, Related to Figure 5

Only the acyl chains of DOPC molecules with at least one of its atoms at distance <0.21 nm from any peptide atom are depicted using a ball-and-stick representation. Smoothing every three frames was not used for lipid and peptide CPK representation to better visualize the dynamics of annular lipids and peptide side chains. Phosphorous atoms of DOPC are shown as white balls. The peptide is depicted using both NewCartoon representation with coloring based on the secondary structure (purple, helical; white, non-helical) and CPK representation (green). The remaining atoms and molecules, including water and cholesterol, are not shown for clarity. The video was prepared employing MovieMaker plugin of VMD. H264-MPEG-4 encoding was used.

Interestingly, organization of phospholipids in the vicinity of the peptide and the trapping of their acyl chains on its rough surface remain unaffected in the absence and presence of cholesterol. This observation is supported by the detailed analysis of acyl chain order calculated from MD simulations wherein the lipids from the peptide annulus and those in the bulk (non-annular) can be analyzed separately (Figure 6 and Table S4). These data suggest that the overall mobility-reducing effect of peptides in the presence of cholesterol is probably caused by complex events: (1) the rough surface of the peptide causes lipid acyl chain trapping and the locally reduced lateral mobility of phospholipids (Figures 1A, 2B, and S6) and (2) cholesterol presence is strongly reduced in the peptide annulus (Figure 5; see also Rog et al., 2008, Pitman et al., 2005), which leads to (3) the increased concentration of cholesterol in the bulk of the lipid membrane and reduced lateral mobility (increased acyl chain order) therein (Figure 6). The last of these three is probably caused by the rigidifying effect of cholesterol itself as observed in peptide-free membranes (Mouritsen and Zuckermann, 2004). Therefore, the lipid acyl chain trapping at the rough surface of the peptide applies for both membranes with and without cholesterol. However, owing to the segregation of cholesterol, MD simulations indicate a different impact of the peptide on membranes with and without cholesterol. The peptide decelerates the dynamics of cholesterol-containing membranes due to a combined effect of its rough surface on phospholipids and cholesterol.

Figure 6

Acyl Chain Ordering in Membranes Containing the LW21 Peptide Was Calculated from MD Simulation Data

The graph represents the average deuterium order parameter SCD of sn-2 acyl chains of DOPC in the absence (left) or presence (right) of 25 mol % cholesterol. Peptide-free membranes (gray bars) are compared with annular (red bars) and non-annular lipids (brown bars) of the LW21 peptide. Error bars represent error of the mean calculated based on the block averaging method. The ordering of acyl chains increases with SCD. The acyl chain order parameter calculated from the angles between C-C bonds in the lipid acyl chain and the membrane normal (MD simulations) directly reflects the geometry of the acyl chain rather than its freedom to move. See also Table S4.

Discussion

In this study, we have investigated how small, highly mobile TM proteins can influence membrane dynamics and organization under well-controlled conditions in synthetic model membranes. Our model system was selected to avoid the impact of factors that were previously shown to influence membrane properties, e.g., hydrophobic mismatch, protein crowding and clustering (aggregation), or formation of domains. This could not be achieved in cells or other complex model systems (e.g., cell-derived vesicles). The presence of a variety of chemical species together with active membrane processes provides cells with enormous adaptability, and the experimental conditions cannot be properly controlled externally. In addition to these previously described phenomena, which depend on specific membrane environment, we were interested in whether integral proteins, independent of their size and higher organization, possess some universal property that can directly modulate membrane dynamics. Our results demonstrate that the rough surface of TM protein segments decelerates membrane dynamics, especially in the presence of cholesterol. This effect has not been previously shown experimentally in a well-controlled, fully hydrated system, and the available fragmented data did not provide good basis for a universal model explaining how proteins can affect membranes.

The mobility of membrane molecules is described in the Saffman-Delbrück (S-D) hydrodynamic model (Saffman and Delbruck, 1975), which highlights the impact of viscosity and, partially, the size of molecules. The variants of the S-D model for large immobile objects (Oppenheimer and Diamant, 2011) or multispanners in heterogeneous lipid membranes (Camley et al., 2010) considered proteins (or their TMDs) to be smooth cylinders with an effective radius of >4 nm. The calculated effect of such objects on lateral diffusion was negligible at low concentrations (<5 mol %). In nature, a majority of proteins possess a single or very few TMDs (Pieper et al., 2013). Their effective intramembranous radius is thus more comparable to the size of lipids (∼1 nm) than to large, multispanning proteins. Moreover, most of the tested proteins were highly mobile in cellular membranes with diffusivities of 0.001–0.1 μm2/s (Bernardino de la Sern et al., 2016, Jacobson et al., 1987). It is therefore important to verify whether small, highly mobile TM peptides (a model of a single TMD) at low, physiologically relevant concentrations (<5 mol %) modulate membrane dynamics. We demonstrate that such peptides reduce the diffusivity of membrane components by exposing their rough surface to the surrounding phospholipids. The effect is more pronounced in membranes containing physiological levels of cholesterol (25 mol %), which better mimic properties of the selected membranes of eukaryotic cells (e.g., plasma membrane, Golgi apparatus, and endosomes). This observation agrees with our toy model (Figure 4), showing that objects with rough surfaces have a stronger effect on membranes compared with smooth ones. The rough surface causes lipid acyl chain trapping, increased local viscosity, and, consequently, a reduction in lateral diffusion of membrane molecules.

We argue that this effect is not restricted to the peptide tested in this work because all amino acids, apart from glycine, form a rough surface when assembled in a helix (Figure 3B). Non-specific trapping of lipid acyl chains in the grooves on the surface of membrane proteins is a common finding in those crystallized in lipid membranes, for example, aquaporin-0 (Hite et al., 2010) and Na+K+ pump (Kanai et al., 2013). A rough surface of TM segments with a potential for acyl chain trapping can be found in virtually all available structures of membrane proteins (PDBTM database; Kozma et al., 2013). Whether there is any selectivity for particular lipids or fatty acids by the rough surface of helical TMDs remains to be evaluated. Experimental and in silico data (Pitman et al., 2005, Polozova and Litman, 2000) suggest the preference of polyunsaturated fatty acids for the annulus, a finding that is in agreement with a tendency of cells to keep membrane fluid even in the presence of rigidifying effects. Our results from the system containing PAPC, glycerophospholipid containing one saturated (palmitoyl; C16:0) and one polyunsaturated acyl chain (arachidonoyl; C20:4), indicate that the rough surface of proteins has a rigidifying effect even in membranes with unsaturated fatty acids and hybrid lipids. The inverse correlation between protein density and lateral diffusion previously observed in model and cell membranes, therefore, might not be exclusively explained by the impact of crowding (Ramadurai et al., 2009, Peters and Cherry, 1982, Frick et al., 2007). A majority of proteins in membranes are mobile and contain only a few TMDs that cannot be considered obstacles for small membrane components such as lipids. In this work, we show that integral proteins reduce the mobility of membrane lipids and proteins independent of their size or higher-order organization.

Our data also provide a likely explanation for the earlier findings that integral proteins and peptides prefer more fluid areas in phase-separated membranes (Schafer et al., 2011, Fastenberg et al., 2003). First, the rough surface of TM segments causes increased local viscosity. In more rigid membranes, this could cause significant reduction in the mobility of membrane molecules and, potentially, their immobilization. Moreover, highly unsaturated acyl chains of lipids were shown to preferentially associate with TMDs (Pitman et al., 2005, Polozova and Litman, 2000). Such lipids have a local disordering effect, thus preventing the immobilization of membrane molecules. In cells, immobilization of the components of signaling or metabolic pathways would be in conflict with the fact that these processes are largely driven by the diffusion of highly mobile molecules (e.g., in membranes; Cebecauer et al., 2010). Indeed, it seems that membrane proteins are sorted to more fluid parts of the membranes, thus avoiding their uncontrolled immobilization. Transiently immobilized surface receptors were shown to be rapidly eliminated from the plasma membrane by endocytosis (Andrews et al., 2008).

In ternary membranes, we demonstrate that the impact of the TM helical peptide on membrane dynamics is further escalated by the segregation of planar molecules like cholesterol from its rough surface (Figure 5). This, in principle, could lead to a segregation of the two molecules into different membrane domains. Indeed, reported electron microscopic images of plasma membrane sheets reproducibly indicate the coexistence of protein-rich and protein-low regions (Wilson et al., 2000). It remains to be determined whether cholesterol is predominantly found in one of those two regions of the plasma membrane. A tendency of cholesterol to segregate from TMDs might help the formation and/or stabilization of cholesterol-enriched, protein-low domains, a principle that was previously suggested in the literature (Nyholm, 2015).

The physical impact of the TMD roughness on membrane dynamics and organization demonstrated in this work may have other, previously unexpected consequences for membrane-associated processes in cells. Reduced lateral diffusion was observed in areas of the plasma membrane with higher protein density in living cells (Frick et al., 2007). This implies that reorganization of proteins, e.g., through interaction of ligands and cytoskeleton with receptors, might cause transient local reduction in the mobility of membrane molecules. Consequently, the slowdown of intermolecular interactions may positively or negatively affect the reaction kinetics of membrane-associated processes and thus affect the vital functions of living cells.

Limitations of Study

Some combinations of amino acids can form “less rough” surface of TM helices, and it would be interesting to know how peptides with different surface roughness influence membranes. However, the differences will be always minute (e.g., for a peptide with alternating leucines and alanines), and we are confident that the available methods do not have sensitivity to distinguish between the changes caused by such peptides. Moreover, a poly-alanine peptide, which would represent probably the smoothest model helical peptide, does not stably incorporate into membranes in transbilayer orientation.

Methods

All methods can be found in the accompanying Transparent Methods supplemental file.