Alamethicin Disrupts the Cholesterol Distribution in Dimyristoyl

Sep 1, 2014 - Michael R. Sanders , Luke A. Clifton , Richard A. Frazier , and Rebecca J. Green. Langmuir 2017 33 (19), 4847-4853. Abstract | Full Text...
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Alamethicin Disrupts the Cholesterol Distribution in Dimyristoyl Phosphatidylcholine−Cholesterol Lipid Bilayers Shuo Qian,*,†,‡ Durgesh Rai,‡ and William T. Heller*,‡ †

Center for Structural Molecular Biology and ‡Biology and Soft Matter Division; Oak Ridge National Laboratory; P.O. Box 2008, MS-6473; Oak Ridge, Tennessee 37831, United States S Supporting Information *

ABSTRACT: Cell membranes are complex mixtures of lipids, proteins, and other molecules that serve as active, semipermeable barriers between cells, as well as between their internal organelles, and the surrounding medium. Their compositions and structures are tightly regulated to ensure proper function. Cholesterol is a key component in mammalian cellular membranes, where it serves to maintain membrane fluidity and permeability. Here, the interaction of alamethicin, a 20 amino acid residue peptide that creates transmembrane pores in lipid bilayer membranes in a concentration-dependent manner, with bilayer membranes composed of dimyristoyl phosphatidylcholine (DMPC) and cholesterol (Chol) was studied. Small-angle neutron scattering (SANS) data demonstrate that a low concentration of alamethicin (peptide-to-lipid ratio of 1/200) disrupts a lateral inhomogeneity seen in peptide-free DMPC:Chol vesicles, which analysis of the SANS data indicates are Chol-rich and Chol-poor phases having different thicknesses. Alamethicin disrupts this structure, producing laterally homogeneous bilayers that are thinner than either phase of the peptide-free bilayers, and possess a strong asymmetry in the Chol content of the inner and outer bilayer leaflets. The results suggest that a secondary membrane disruption mechanism exists in parallel with the well-understood cytotoxic membrane permeabilization that results when alamethcin forms transmembrane pores. Specifically, the peptide can disrupt laterally organized lipidic structures in cell membranes, as well as significantly perturb the compositions of the inner and outer leaflets of the membrane. The existence of a secondary mechanism of action against cellular membranes for alamethicin raises the possibility that other membrane-active peptides function similarly.

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INTRODUCTION The cellular membrane is composed of a mixture of lipids, proteins and other constituents that self-assemble into a heterogeneous structure that has been termed a “fluid mosaic”.1 The composition and structure of the membrane is actively maintained by the cell to ensure proper function. In mammalian cells, one key component is cholesterol, which serves to maintain membrane fluidity and permeability of the membrane. Cholesterol (Chol) also alters the mechanical properties of the bilayer, making it more rigid2−4 while reducing its permeability5,6 and increasing its fluidity.7 It interacts with the hydrophobic core of phospholipid membranes in a manner that depends on the lipid composition.8−10 Chol is a basic ingredient of lipid microdomains, or “lipid rafts”, that localize many membrane protein receptors. The total amount and distribution of Chol regulates many important processes, such as signaling cascades, and the activation of an immune response.11 Membrane-active peptides interact directly with the lipids of cell membranes, rather than possessing a specific membrane protein target. The physiological roles of membrane-active peptides vary widely. The honey bee venom component melittin is one familiar example, as are the antimicrobial peptides magainin, protegrin and the cecropins.12,13 Alamethicin from the fungus Trichoderma viriide is a well-studied © 2014 American Chemical Society

membrane-active peptide. It has 20 amino acids and carries a single negative charge at neutral pH. At low concentrations in the membrane, the helical peptide adsorbs into the polar region of the membrane with its helical axis lying parallel to the plane of the bilayer.14−16 At a sufficiently high, but bilayer composition-dependent, concentration, alamethicin transitions en masse to a membrane-spanning state that creates barrel-stave transmembrane pores.15−17 This transition is driven by the relative free energy cost of elastically deforming the bilayer structure when adsorbed into the polar region of the membrane15,16,18,19 versus the cost of forming transmembrane pores.16 This mechanism of action of alamethicin was first elucidated in single-component lipid bilayer membranes. The complexity of cell membranes necessitates that the interaction of alamethicin with more compositionally complex model membranes be studied to develop a more complete picture of how it functions. The peptide can modulate the structure of mixtures mixture of dioleyl phosphatidylcholine (DOPC) and dioleyl phosphatidylethanolamine (DOPE) between lamellar, hexagonal and cubic phases,20 pointing to a role in modifying the intrinsic curvature of the membrane. The Received: May 18, 2014 Revised: August 29, 2014 Published: September 1, 2014 11200

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studied, namely 6:4 and 8:2 in molar ratio. The peptide-to-lipid ratio studied was P/L = 1/200 and the molar ratio was with respect to the total lipid and cholesterol mixture employed, rather than being the ratio of alamethicin to d54-DMPC. The lipid and cholesterol mixture were codissolved in D2O at 2% w/ w concentration. To ensure that the mixture was uniform and the vesicles produced were unilamellar, the lipid suspension was subjected to at least three freeze−thaw cycles by alternately placing the suspension in a warm water bath (40 °C) and in a freezer (−20 °C). At this point, the appropriate quantity of peptide was titrated into the lipid suspension and vortexed immediately prior to vesicle extrusion. The vesicles were extruded by passing the suspension at least 10 times through a mini-extruder from Avanti Polar Lipids (Alabaster, AL) fit with a porous polycarbonate membrane having an average pore diameter of 100 nm. After extrusion, the vesicle sizes were uniformly distributed around 60 nm in radius, as determined by dynamic light scattering (Wyatt Technology Corp., Santa Barbara, CA). Throughout the whole extrusion process, the extruder was placed on a hot plate set at 40 °C, well above the DMPC gel−fluid phase transition temperature, which ensured that the lipids were in fluid phase. The unilamellar vesicle suspensions were stored at 4 °C if they were not used immediately. No obvious differences were observed between freshly prepared and stored samples. The samples were prepared for oriented circular dichroism (OCD) experiments by following well-established protocols.17 Briefly, about 1 mg of total mass of DMPC and Chol were codissolved in a 1:1 (v/v) mixture of chloroform and trifluoroethanol at molar ratios of 8:2 and 6:4. Alamethicin, also dissolved in the same solvent, was added into the lipid mixture to achieve the desired final peptide-to-lipid ratio (1/ 200 for all samples but one OCD measurement, which was performed at 1/20). The sample in the solvent mixture was deposited onto 19 mm by 19 mm by 0.5 mm thick quartz substrates. After the organic solvent evaporated, the samples were placed under vacuum for at least 1 h to remove any residual solvent prior to incubation with saturated water vapor at room temperature for a few hours to rehydrate before sealing them into the OCD sample chamber with saturated water vapor for the measurements. Circular Dichroism (CD) and Oriented Circular Dichroism (OCD). CD spectroscopy was performed to verify that alamethicin was associated with the vesicles studied is in a α-helical conformation. OCD spectroscopy26 was used to determine the orientation of alamethicin relative to the bilayer normal to determine if it was inserted across the membrane or if it was a surface adsorbed state oriented perpendicular to the bilayer normal. All CD and OCD data were measured at 37 °C with a Jasco J-810 CD spectropolarimeter (Tokyo, Japan). The solution samples used in SANS experiment were scanned from 190 to 260 nm using a 0.5 nm wavelength step with an accumulation of 5 scans. OCD spectra were collected from samples sealed into a sample cell having quartz windows. A relative humidity of ∼97% was maintained by a saturated potassium sulfate solution.27 To reduce the possible artifacts resulting from linear dichroism, the OCD samples were rotated by 90° around the sample normal direction and the measurements were repeated. The final OCD spectrum presented is the average of the spectra from the two sample orientations. The CD and OCD spectrum were corrected for the background signal produced by the DMPC:Chol mixture present in the solution or on the substrate, respectively.

addition of diphytanoyl phosphatidylethanolamine (DPhPE) to diphytanoyl phosphatidylcholine (DPhPC) membranes also increased the critical concentration for alamethicin pore formation,18 again showing alamethicin’s curvature-modifying behavior in these mixed zwitterionic membranes. A recent study demonstrated that alamethicin redistributes charged lipids in unilamellar vesicles composed of dimyristoyl phosphatidylcholine (DMPC) and dimyristoyl phosphatidylglycerol (DMPG), shifting the anionic DMPG to the outer leaflet of the bilayer.21 The effect takes place at concentrations well below those required to drive the transition from the surface-adsorbed state to the transmembrane, pore-forming state. The presence of cholesterol (Chol) in the membrane increases alamethicin’s critical concentration for pore formation and increases the threshold gating voltage of the resulting ion channels.22 The conductance of alamethicin channels also changes in response to asymmetric inclusion of Chol in membranes.23 Alamethicin-driven lipid reorganization in Cholcontaining bilayer membranes has not been previously investigated. Here, the impact of alamethicin on the structures of bilayers composed of DMPC and Chol was studied. Through the use of small-angle neutron scattering (SANS), chain-perdeuterated DMPC (d54-DMPC) and hydrogenated cholesterol (Chol) at DMPC:Chol molar ratios of 8:2 and 6:4, it was possible to highlight changes in the bilayer structure that result from incorporating alamethcin in vesicles at a peptide-to-lipid molar ratio (P/L) of 1/200. These DMPC:Chol mixtures were selected because they contain enough Chol when using deuterated lipid to make it possible to resolve peptide-driven changes in the system. Similarly, the P/L selected is anticipated to be below that required for alamethicin to form membranespanning pores.24 In the absence of alamethicin, the results indicate that the peptide-free 8:2 and 6:4 DMPC:Chol mixtures studied display a degree of lateral organization with regions of different thicknesses and compositions. Alamethicin both thins the DMPC:Chol membrane and disrupts the coexistence of the laterally segregated regions, resulting in a thinner, more laterally homogeneous bilayer. Interestingly, the peptide also creates a strong asymmetry in the Chol content between the inner and outer bilayer leaflets in a manner that depends on the cholesterol content of the vesicle. The results provide clear evidence that alamethicin’s interaction with Chol-containing lipid bilayer membranes has consequences beyond the formation of transmembrane pores. Instead, the results suggest that the impact of the peptide is more complex than the wellestablished two-state mechanism of cytotoxic action.24,25 The results may have far-reaching implications for the understanding of the mechanisms of action of membrane-active peptides.

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MATERIALS AND METHODS Materials. Chain-perdeuterated dimyristoyl phosphatidylcholine (d54-DMPC) was purchased from Avanti Polar Lipids, Inc. (Alabaster, AL). D2O (99.9% atomic D) was purchased from Cambridge Isotope Laboratories (Andover, MA). Alamethicin (product A4665; >98% purity) and cholesterol (product C8667; >99% purity) were purchased from SigmaAldrich (St. Louis, MO). All materials were used as provided. Sample Preparation. Preparation of small unilamellar vesicles followed previously described procedures.21 Modifications to incorporate cholesterol and alamethicin are briefly described here. Two different d54-DMPC:Chol ratios were 11201

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SANS Data Collection and Reduction. The samples were loaded into 1 mm path-length cylindrical quartz cells (Hellma, Germany). SANS data were collected using the Bio-SANS instrument of the High Flux Isotope Reactor28 and the EQSANS instrument of the Spallation Neutron Source,29 both at Oak Ridge National Laboratory. Data collected on Bio-SANS used sample-to-detector distances of 1.1 and 6.8 m. The neutron wavelength, λ, was set to 6 Å, and the wavelength spread, Δλ/λ, was set to 0.14. These configurations covered an effective q-range of ∼0.006 Å−1 to 0.70 Å−1, where q is the momentum transfer and has a magnitude q = (4π sin(θ))/λ, where 2θ is the scattering angle and λ is the wavelength. The measurements performed using the EQ-SANS instrument employed a sample-to-detector distance of 4m. The instrument was used in 30 Hz mode with a minimum wavelength setting of 2.5 Å, giving a second band starting at 9.4 Å, which provides an effective q-range of ∼0.005−0.45 Å−1. All measurements were performed at 37 °C. SANS data reduction followed standard procedures to correct for instrument dark current, being electronic noise and natural radiation, detector sensitivity, incident beam normalization, sample transmission, and solvent background. Reduced data were then azimuthally averaged to produce the 1D SANS intensity profile I(q) vs q. SANS Data Analysis and Modeling. SANS data analysis and modeling followed methods previously employed by this group in which data were fit using polydisperse multishell spherical models.21 Two different approaches were employed, as dictated by the data. In the first, a single scattering length density (SLD) profile comprising four shells, referred to hereafter as the 4-shell model (Figure 1A), of density was used to model the data. Radiating outward, the shells loosely correspond to the inner headgroup (HG) layer, the inner hydrocarbon core, the outer hydrocarbon core and the outer HG layer (Figure 1A). The bilayer was not constrained to have

a symmetric SLD profile. In the second modeling approach that was employed when the simpler 4-shell model did not provide acceptable fits to the data, models consisting of a superposition of two SLD profiles, hereafter referred to as the 2-profile model, were employed. Two 3-shell SLD profiles were generated and then provided a population averaging to represent regions of the vesicles having two different structures that were not constrained to have the same thickness (Figure 1B). The three shells roughly correspond to the inner HG layer, the hydrocarbon core and outer HG layer of the two profiles. In the 2-profile model, the inner and outer surface layers were constrained to have the same thickness, but not the same SLD. Both modeling approaches provided sufficient flexibility for fitting the data well without overfitting it. In the case of the 4-shell models, an initial search was performed to find the densities and radii that provided the best fits to the data. The radii of the shells were initially constrained to be between 4 and 15 Å. For the 2-profile models, the total bilayer thicknesses were allowed to range from 40 to 50 Å in one region and 50 to 65 Å in the other while the HG thicknesses were allowed to vary from 2 to 16 Å, with the remainder of each thickness being assigned to each hydrocarbon core. The starting ranges of the SLDs for each layer were based on the SLDs of the material that the samples were composed of. The search through the model parameter space was performed via Monte Carlo sampling and ∼107 models were tested in each of the initial searches and the subsequent refinement searches. The quality of fit was evaluated using the χ2 parameter employed previously.30,31 In all of the SANS data fitting performed, a list of the structural parameters for the bestfitting 100 models was maintained, as implemented previously.30 This list provided guidance for performing refinement searches using restricted ranges of model parameters. The final models presented here are the result of the refinement searches. The composition of the various regions obtained from the SANS data fitting were manually estimated from the SLD values found. At P/L = 1/200, the contribution of alamethicin to the SLD of any layer is on the order of a few percent, which is consistent with the uncertainties in the thicknesses and SLDs estimated from the fitting.30 As a result, the location of alamethicin was not considered when determining the composition of the various layers in the model.

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RESULTS The high concentration of cholesterol in the samples resulted in strong UV absorption at shorter wavelengths that produced significant noise in the CD and OCD data. This was particularly problematic for the 6:4 DMPC:Chol samples, and, as a result, the data are not presented. The CD spectrum collected from the 8:2 DMPC:Chol:Ala vesicle sample are presented in Figure 2A, while the OCD spectrum from the 8:2 DMPC:Chol:Ala sample is presented in Figure 2B. The data from the vesicle solution shows three broad peaks at wavelengths consistent with an α-helical conformation of alamethicin, indicating that it is associated with the membrane, although the relative intensities of the two shorter wavelength bands relative to negative longer wavelength band when compared to previously published results in cholesterol-free vesicles suggests that some wavelength-dependent absorption by the sample exists.32 OCD is a simple and effective technique for determining the orientation of membrane-active peptides, especially for α-helical peptides, in planar lipid bilayer membranes.14,18,33 When the peptides are lying parallel to the surface of the bilayer (viz., S-

Figure 1. Schematics of lipid bilayer showing 4-shell model (A) and 2profile model (B) used in SANS fitting. 11202

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Figure 2. (A) CD data collected for alamethicin in 8:2 DMPC:Chol vesicles at P/L = 1/200. (B) OCD data collected for alamethicin in 8:2 DMPC:Chol at P/L = 1/200 (solid line) and P/L = 1/20 (dashed line).

Figure 3. SANS data collected for the vesicle solutions of 8:2 d54DMPC:Chol (■), alamethicin in 8:2 d54-DMPC:Chol (○), 6:4 d54DMPC:Chol (▲), and alamethicin in 6:4 d54-DMPC:Chol (▽). The curves have been offset for clarity.

state) the resulting OCD spectrum is very distinct from the spectrum resulting from the state in which most of the peptides are inserted across the lipid bilayer (viz., I-state). Spectra collected at P/L = 1/200 and P/L = 1/20 are presented in Figure 2B. In the case of P/L = 1/20, the OCD data are clearly consistent with the I-state of alamethicin.14,18,33,34 The OCD data for the 8:2 DMPC:Chol:Ala sample at P/L = 1/200, which is the concentration used for the SANS measurements, displays broad negative peaks near 208 nm with a broad shoulder to higher wavelengths. The data become quite noisy below ∼200 nm, but have clearly positive values. Such a spectrum is most consistent with a primarily surface adsorbed S-state of alamethicin.14,18,33,34 The lipid composition of a Chol-free bilayer impacts the relative strength of the short wavelength features in the OCD spectra of alamethcin,34 and the muting of the band seen at ∼230 nm in Figure 2A may be the result of a similar effect produced by the cholesterol on the OCD data. The SANS data collected for the four samples studied are shown in Figure 3. The use of d54-DMPC, hydrogenated Chol and a solvent with a high D2O content minimized the amount of incoherent scattering from hydrogen, yielding high-quality data containing features needed for robust model fitting. The peptide-free 8:2 d54-DMPC:Chol and 6:4 d54-DMPC:Chol samples produced scattering profiles with a flattened oscillation centered near 0.14 Å−1 that spans from ∼0.07 Å−1 to ∼0.30 Å−1. This region of the SANS data results from the SLD profile of the lipid bilayer within the context of the vesicle.35 The addition of alamethicin to both lipid mixtures rounds out this feature and shifts the peak to near 0.175 Å−1, with the first minimum being around 0.09 Å−1, indicating significant alamethicin-driven changes in the lipid bilayer structure and thickness. It is interesting to note the presence of oscillations in the low-q SANS data (q < 0.02 Å−1) in the alamethicincontaining samples. This region of the data arises from the overall shape of the vesicle, rather than the bilayer structure,35 and the presence of oscillations may result from a lower vesicle size polydispersity in the samples containing alamethicin.

The model SANS profiles found by fitting the SANS data are presented in Figure 4, while the model parameters are provided in Table 1 for the 8:2 d54-DMPC:Chol samples and Table 2 for the 6:4 d54-DMPC:Chol samples. The alamethicin-free samples required the application of the 2-profile model (described above), and the resulting model SANS intensity profiles have χ2 values of 2.47 and 1.17 against the peptide-free 8:2 d54-DMPC:Chol and 6:4 d54-DMPC:Chol SANS data, respectively. For comparison, the best-fitting model SANS profiles found using the 4-shell model are presented in Figure S1 and have χ2 values of 3.73 and 2.14 against the peptide-free 8:2 d54-DMPC:Chol and 6:4 d54-DMPC:Chol SANS data, respectively. One potential cause for the quality of fit of the 2profile model, particularly in the case of the 8:2 d54DMPC:Chol data, is that the lateral inhomogeneities produced by the two regions may have length scales comparable to the bilayer thickness. Such features could contribute to the measured scattering intensity profile in the q-range modeled. The difference between the bilayer thicknesses of the two regions found is ∼15 Å for both DMPC:Chol mixtures and the thinner region has much less cholesterol than the thicker region. The area fractions occupied by the thinner of the two regions in the models are 69% and 75%, suggesting that the cholesterol content is not a strong determinant of the extent of lateral inhomogeneity found in the fitting. However, the simple model SLD profile employed may not fully capture the details present in the structure, particularly in the 8:2 d54DMPC:Chol sample. The simplicity was deemed a reasonable approach to avoid overfitting the data. The area fractions of the two domains were not the most important parameters for fitting the data well. The validity and robustness of the fitting of the data from the two different lipid compositions can be crosschecked through the simple relation Vtotal/A = Thickness1 × Fraction1 + Thickness2 × Fraction2, where Vtotal and A are the volume and area of the lipid bilayer, respectively and are determined solely from the radius of the vesicle. The 11203

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Figure 4. Fits of the model profiles to the SANS data for (A) 8:2 d54-DMPC:Chol (■), (B) 8:2 d54-DMPC:Chol:Ala (○), (C) 6:4 d54DMPC:Chol (▲), and (D) 6:4 d54-DMPC:Chol:Ala (▽). The model profiles are the red lines plotted with the data.

Table 1. Model Parametersa (A) Derived from Fitting 8:2 d54-DMPC:Chol SANS Data region 1 layer

thickness (Å)

inner HG 11.65 ± 0.28 core 22.94 ± 0.31 outer HG 11.65 ± 0.28 total thickness (Å) region 2 layer thickness (Å) inner HG 2.38 ± 0.25 core 57.14 ± 0.47 outer HG 2.38 ± 0.25 total thickness (Å) layer inner inner outer outer

a

HG core core HG

thickness (Å)

10

SLD (10 /cm2)

volume fraction chol.

4.52 ± 0.12 6.79 ± 0.03 4.89 ± 0.12

0.05* 0.01 0.05*

46.24 ± 0.78 SLD (1010/cm2) volume fraction chol. 3.87 ± 0.61 6.21 ± 0.03 3.25 ± 0.43

volume fraction HG

volume fraction chain

0.36 0.00* 0.28 fraction of region 1 volume fraction HG volume

0.56 0.00* 0.69 61.90 ± 0.97 fraction of region 2 (B) Derived from Fitting 8:2 d-54-DMPC:Chol:Ala SANS Data

SLD (1010/cm2)

7.10 ± 0.95 5.92 ± 0.05 12.22 ± 1.15 5.81 ± 0.08 14.22 ± 0.78 6.71 ± 0.04 7.98 ± 0.98 5.38 ± 0.14 total thickness (Å) core thickness (Å)

0.00* 0.12 0.00*

0.00* 0.99 0.00* fraction chain 0.00* 0.88 0.00*

volume fraction water 0.59 0.00* 0.67 0.69 ± 0.05 volume fraction water 0.44 0.00* 0.31 0.31 ± 0.05

volume fraction chol.

volume fraction HG

volume fraction chain

volume fraction water

0.00* 0.20 0.02 0.00*

0.10 0.00* 0.00* 0.22

0.00* 0.80 0.98 0.00* 41.52 ± 3.86 26.44 ± 1.93

0.90 0.00* 0.00* 0.78

Parameters that were kept fixed during the deconvolution are marked with an asterisk (∗).

compositions. Using the values from Table 1 for the 8:2 d54DMPC:Chol sample, Vtotal/A = 51.1 Å. Similarly, for the 6:4 d54-DMPC:Chol sample, Vtotal/A=49.8 Å, which is consistent with the 8:2 d54-DMPC:Chol result.

thicknesses and fractions are the values taken from the results of the SANS data modeling. Assuming that the vesicles made from two compositions have of the same size and size distribution, which is supported by the DLS measurements, the Vtotal/A should be the same for the different lipid 11204

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Table 2. Model Parametersa (A) Derived from Fitting 6:4 d54-DMPC:Chol SANS Data region 1 Layer

thickness (Å)

inner HG 10.89 ± 0.29 core 23.97 ± 0.32 outer HG 10.89 ± 0.29 total thickness (Å) region 2 layer Thickness (Å) inner HG 2.66 ± 0.34 core 56.63 ± 0.79 outer HG 2.66 ± 0.34 total thickness (Å) layer inner inner outer outer

a

HG core core HG

thickness (Å)

SLD (1010/cm2)

volume fraction chol.

4.69 ± 0.18 6.79 ± 0.04 4.86 ± 0.16

0.05* 0.01 0.05*

45.74 ± 0.90 SLD (1010/cm2) volume fraction chol. 3.25 ± 0.47 6.11 ± 0.03 4.35 ± 0.28

volume fraction HG

volume fraction chain

0.32 0.00* 0.29 fraction of region 1 volume fraction HG volume

0.67 0.00* 0.45 61.95 ± 1.47 fraction of region 2 (B) Derived from Fitting 6:4 d54-DMPC:Chol:Ala SANS Data

SLD (1010/cm2)

6.67 ± 1.00 4.87 ± 0.67 14.67 ± 1.32 6.74 ± 0.48 12.16 ± 0.98 5.85 ± 0.52 6.93 ± 0.96 5.92 ± 0.65 total thickness (Å) core thickness (Å)

0.00* 0.11 0.00*

0.00* 0.99 0.00* fraction chain 0.00* 0.89 0.00*

volume fraction water 0.63 0.00* 0.66 0.75 ± 0.06 volume fraction water 0.33 0.00* 0.55 0.25 ± 0.06

volume fraction chol.

volume fraction HG

volume fraction chain

volume fraction water

0.00* 0.02 0.19 0.00*

0.34 0.00* 0.00* 0.10

0.00* 0.98 0.81 0.00* 40.53 ± 4.26 Å 26.83 ± 2.30 Å

0.66 0.00* 0.00* 0.90

Parameters that were kept fixed during the deconvolution are marked with an asterisk (∗).

and maintaining such regions in vesicles with a saturated lipid, such as DMPC, and it should be noted that the high curvature present in the relatively small vesicles may also play a role in the structuring seen, but the effect would presumably have a larger impact on the relative Chol content of the inner and outer leaflets of the bilayer as opposed to the structuring in the plane of the bilayer. The data do not directly support the existence of well-defined, discrete domains, as was recently reported for lipid bilayer vesicles made of raft-forming lipid mixtures.39−41 The thickness difference between the two regions in the model is dramatic. While the thickness of the Chol-poor region in the present study is reasonably consistent with the bilayer thickness measured for fully hydrated, fluid Lα DMPC bilayers (43.4 Å),42 the thickness of the Chol-rich region found is considerably greater than the bilayer thickness determined for fully hydrated gel phase DMPC bilayers (48.2 Å),43 although the gel-phase chains are tilted at 32.3° from the bilayer normal in the crystal structure. Such a large tilt angle could be energetically unfavorable if it were to coexist with an interpenetrating region of lipids in the Lα phase. A simple geometric correction for chains of that length being aligned with the normal of the bilayer yields a thickness of 57.0 Å, which gives a mismatch of comparable size to what is observed in the present study. The temperature used in the present study (37 °C) is too high for the crystalline phase to exist, but the liquid ordered (Lo) phase known to form when Chol is present is thicker than the fluid Lα phase.44,45 Hung and co-workers studied DMPC:Chol mixtures at 98% relative humidity using lamellar X-ray diffraction.36 Their results obtained at 30 °C show a phosphate-to-phosphate (PtP) distance of ∼41 Å for 8:2 DMPC:Chol and ∼43 Å for 6:4 DMPC:Chol, both of which are thinner than the thickest region observed in the present study, but are considerably thicker than the cholesterol free PtP found (∼36 Å). While not directly comparable in light of the different measurements performed, the simple nature of the model used in the present study, the inherently lowerresolution of SANS data compared to diffraction data, as well as the possibility that lateral organization with length scales comparable to the bilayer thickness may be present that impact

The SANS data from the d54-DMPC:Chol:Ala samples were well-fit by the 4-shell model, as can be seen in Figure 4. The best-fitting model parameters found are presented in Table 1 (8:2 d54-DMPC:Chol:Ala) and Table 2 (6:4 d54-DMPC:Chol:Ala). The model SANS profiles have χ2 values of 0.722 for 8:2 d54-DMPC:Chol:Ala and 0.714 for 6:4 d54-DMPC:Chol:Ala. The experimental uncertainties are derived using assumptions about the neutron counting statistics, so values less than 1.0 are not unreasonable and the χ2 parameter remains an effective least-squares minimization target. In both cases, the bilayer with alamethicin is thinner than either of the two bilayer structures present in the alamethicin-free vesicles. The outer leaflet’s core region of the 8:2 d54-DMPC:Chol:Ala structure is composed almost entirely of the deuterated lipid chains and very little Chol. Similarly, while there is a strong asymmetric Chol distribution in the 6:4 d54-DMPC:Chol:Ala sample, it is the inner leaflet’s core region that lacks Chol. It should be noted that the material volume fractions determined the fitting results are very nearly identical. The approach to the SLD profile deconvolution was kept simple, and it is certainly possible that there is Chol in the inner or outer HG region of the bilayer in the 6:4 d54-DMPC:Chol:Ala vesicles, particularly in the case of the inner HG region. The higher concentration of Chol is near the DMPC:Chol miscibility limit.36

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DISCUSSION The use of neutron scattering and selective deuteration has provided new insight into alamethicin’s interaction with Cholcontaining lipid bilayer membranes. The results have shown that two compositionally segregated regions, one Chol-rich and the other Chol-poor, coexist within the peptide-free vesicles. The flattening of the bilayer structural features in the SANS data could not be fit with a single SLD profile model or two SLD profiles having the same thickness, suggesting that the vesicles are not laterally uniform, but instead have regions with different thicknesses and compositions. The flattening features have not been observed in small-angle scattering data from vesicles made of other 2-component phospholipid mixtures.21,37,38 Thus, Chol seems to be essential for creating 11205

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the SANS data in the specific q-range modeled, the results and interpretation presented here are consistent with cholesterol increasing the average thickness of the bilayer. Hung and co-workers concluded from their X-ray diffraction study that DMPC and Chol mixed uniformly and homogeneously at up to 40% (molar) Chol content.36 While this may seem to contradict the result of the current study, the electron density profiles presented in Figure 5 of ref 36 clearly show that the electron density profile of the bilayer changes a great deal as the Chol content increases. A laterally inhomogeneous bilayer structure in a well-ordered multilamellar stack having a single repeat spacing could produce a very different electron density profile than a truly uniform bilayer, but structuring in the plane of the bilayer would not be directly observable using the θ−2θ diffraction measurements employed.36 SANS data from a vesicle provides information on both the lateral and normal structure of the bilayer, albeit mapped onto the vesicles freely diffusing in solution. The presence of regions of a bilayer with different thicknesses was observed in simulations of DMPC:Chol mixtures performed by de Meyer and coworkers.46,47 Variations in thickness across the area of membrane simulated were up to 10 Å and involved variations in local Chol content. Interestingly, the lateral variations in composition and thickness in both the 8:2 DMPC:Chol and 6:4 DMPC:Chol simulations were on the order of tens of angstroms. The lateral structuring seen was best described as random interpenetrating phases with loosely defined boundaries giving rise to smooth variations in thickness. In another words, the Chol-rich phases do not form a small number of large domains having well-defined boundaries that are dispersed in the Chol-poor phase. This sort of diminishing lateral organization of Chol has been observed as a function of increasing Chol concentration.48,49 If the length scales of the thickness and SLD fluctuations are comparable to the bilayer thickness, a SANS profile reflecting this additional structuring in the material could result that gives the appearance of a greater thickness difference between the Chol-rich and Cholpoor regions than actually exists. At present, simulating an entire vesicle, along the lines of the work of de Meyer and coworkers,47 to model the present SANS data are not feasible. The work presented here demonstrates that a low concentration of alamethicin dramatically remodels both the normal and lateral structure of DMPC:Chol bilayers. The observed thinning of the peptide-containing bilayer relative to the thickness of either region from the peptide-free bilayer is consistent with the peptide being adsorbed into the HG region of the bilayer in the S-state, which does not create transmembrane pores. In such a state, geometric packing effects could drive the different Chol content between the inner and outer leaflets of the bilayer, much like the presence of alamethicin or melittin caused a charged lipid to move from the inner to outer bilayer leaflet.21 The more surprising result is the observation of the lateral structure in the DMPC:Chol system revealed by SANS and deuterium labeling and its disruption by alamethcin. Much of the work related to raft formation and other forms of membrane sortingbe it of lipids or proteinsis from the perspective of formation and maintenance of functional domains within the cell membrane, rather than the disruption or elimination of such domains. The present study suggests that the harmful effects of membrane-active peptides are not strictly limited to the cytotoxic transitions, such as the formation of transmembrane pores or the carpet-model permeation of the

cell membrane, that take place at high peptide-to-lipid ratios.13,24,25 As shown in the present study and previously,21 even small amounts of a membrane-active peptide can disrupt the distribution of the components of the membrane, which would force a target cell to respond to return its membrane to its natural state. It is known that Chol level and distribution in the cellular membrane is tightly regulated,50 and tipping the balance by even a small amount by a membrane-active peptide, as these results demonstrate, could have a significant impact on the health of a cell. For example, the removal or redistribution of Chol could lead to dissociation of proteins preferably associated with Chol-rich membrane.11 When disrupting a cell membrane in this manner, the peptide can be argued to be a metabolic inhibitor.51 While not immediately lethal, the disruption of the membrane structure by low concentrations of an antimicrobial peptide could slow the progress of an infection such that other elements of the immune system would have more time to eliminate the invading cell. In the case of the lytic alamethicin’s interaction with Chol, which is more prevalent in mammalian cells than bacterial cells, disruption of the functional, laterally organized cell membrane structures would be a stressor that contributes to the harmful physiological effects produced by the peptide, even if it were not the ultimate source of the peptide’s toxicity. Further, this kind of membrane disruption could trigger a cascade of effects that have implications beyond toxicity. As a matter of fact, many membrane-active peptides, including some antimicrobial peptides, have been found to influence a varieties of cellular processes, such as chemotactic activity, antigen presentation, angiogenesis, and even wound healing.52 The results presented here suggest a physical mechanism behind the nonlytic response of cells to membrane-active peptides.

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CONCLUSIONS The remodeling of the DMPC:Chol mixtures by alamethcin is dramatic and supports the notion of an alternative, secondary mechanism of action for it that may also exist for other membrane-active peptides. The present study, as well as others employing increasingly realistic model lipid mixtures, provides new insight into the action of membrane-active peptides. Teasing out the specific molecular interactions and changes that take place in these more complicated systems requires the use of appropriate experimental techniques and new approaches to modeling the data. Neutron scattering, particularly when leveraging the power of selective deuterium labeling and contrast variation methods, is extremely well-suited for such studies and provides unique information that can lead to a deeper understanding of the interactions between membranes and proteins.

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ASSOCIATED CONTENT

S Supporting Information *

Fit of the 4-shell model to SANS data from peptide-free vesicles. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Authors

*(S.Q.) Telephone: 865-241-1934. E-mail: [email protected]. *(W.T.H.) Telephone: 865-241-0093. E-mail: hellerwt@ornl. gov. 11206

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Notes

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The authors declare no competing financial interests.

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ACKNOWLEDGMENTS This work was supported by the Laboratory Directed Research and Development program of Oak Ridge National Laboratory. The Oak Ridge National Laboratory Center for Structural Molecular Biology (F.W.P. ERKP291) is supported by the Office of Biological and Environmental Research of the US Department of Energy. Research at the High Flux Isotope Reactor and at the Spallation Neutron Source of Oak Ridge National Laboratory was sponsored by the Scientific User Facilities Division, Office of Basic Energy Sciences, US Department of Energy.

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