Single-Nanometer Changes in Nanopore Geometry Influence

Jun 21, 2019 - Download MS PowerPoint Slide ... One of these design parameters describes pore taper (the .... it gets trapped at the free edges of the...
0 downloads 0 Views 3MB Size
Download PDF
Letter Cite This: Nano Lett. 2019, 19, 4770−4778

pubs.acs.org/NanoLett

Single-Nanometer Changes in Nanopore Geometry Influence Curvature, Local Properties, and Protein Localization in Membrane Simulations Alexis Belessiotis-Richards,†,‡,§ Stuart G. Higgins,†,‡,§ Ben Butterworth,† Molly M. Stevens,*,†,‡,§ and Alfredo Alexander-Katz*,∥ †

Department of Materials, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom Department of Bioengineering, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom § Institute of Biomedical Engineering, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom ∥ Department of Materials Science & Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States

Downloaded via KEAN UNIV on July 17, 2019 at 10:57:12 (UTC). See https://pubs.acs.org/sharingguidelines for options on how to legitimately share published articles.

‡

S Supporting Information *

ABSTRACT: Nanoporous surfaces are used in many applications in intracellular sensing and drug delivery. However, the effects of such nanostructures on cell membrane properties are still far from understood. Here, we use coarsegrained molecular dynamics simulations to show that nanoporous substrates can stimulate membrane-curvature effects and that this curvature-sensing effect is much more sensitive than previously thought. We define a series of design parameters for inducing a nanoscale membrane curvature and show that nanopore taper plays a key role in membrane deformation, elucidating a previously unexplored fabrication parameter applicable to many nanostructured biomaterials. We report significant changes in the membrane area per lipid and thickness at regions of curvature. Finally, we demonstrate that regions of the nanopore-induced membrane curvature act as local hotspots for an increased bioactivity. We show spontaneous binding and localization of the epsin N-terminal homology (ENTH) domain to the regions of curvature. Understanding this interplay between the membrane curvature and nanoporosity at the biointerface helps both explain recent biological results and suggests a pathway for developing the next generation of cell-active substrates. KEYWORDS: Molecular dynamics, bionanointerface, nanoporosity, membrane curvature, cell membrane, coarse-grained modeling

T

recently been shown to affect cell motility, gene expression, and focal adhesion organization.18 With the help of nano- and microfabrication techniques, we can now directly induce and study nanoscale curvature in the cell membrane. Nanoporosity has been studied in detail over the past few years in particular for promoting cell adhesion, proliferation, and differentiation on surfaces.19−27 We have shown experimentally that nanoporous nanoneedles facilitate intracellular sensing, drug delivery, and cell manipulation due in part to their highly porous surface and their significant deformation of cell membranes.28−31 Recently, we showed that porous nanoneedles directly stimulate endocytosis in cells to deliver cargo and observed accumulations of endocytic vesicles at the interface between the cell membrane and the nanoporous surface.32 These vesicles localized equally around the needle tips and sides, suggesting that the tight wrapping of the cell membrane around the nanoporous surface of the needles

he ability of a cell to deform its plasma membrane is an essential process for cellular life and function. Indeed, deformation of the cells protective membrane allows them to feel their surroundings, migrate via filopodia extension, and endocytose/exocytose nutrients by membrane budding. Such curvature of the cell membrane can be induced via many different mechanisms, notably by lipid composition mismatch,1−3 by protein crowding,4,5 and by direct deformation via actin polymerization.6,7 In addition to macroscale cellular functions, nanoscale membrane curvature plays a role in various other membrane-mediated processes such as viral entry into the cell,8−10 organizing local protein concentrations,11−14 and controlling protein activity.15 The interplay between local membrane curvature and the behavior of membrane-active proteins, and hence membrane-mediated cellular processes, is still far from being understood. Curvature-generating proteins may catalyze the localization of more membrane-active proteins, and conversely, local spontaneous membrane curvature may attract curvature-sensing proteins and initiate cellular processes such as endocytosis.12,16,17 Furthermore, curvature external to the cell, in the form of smooth topographical features, has © 2019 American Chemical Society

Received: May 15, 2019 Revised: June 19, 2019 Published: June 21, 2019 4770

DOI: 10.1021/acs.nanolett.9b01990 Nano Lett. 2019, 19, 4770−4778

Letter

Nano Letters

Figure 1. (a) Illustration of a cell in contact with a nanoporous substrate showing nanopore-induced membrane curvature and highlighting the approximate locations of curved membrane regions with modified membrane properties (pink lipid heads) exhibiting curvature, above average area per lipid, reduced thickness, as well as increased bioactivity. The membrane region not in contact with the wafer, as identified with the blue arrow, exhibits an increased lipid diffusion in both leaflets. (b) The wafer design parameters explored for influencing membrane deformation: pore radius (R, nm), pore taper (T, nm), and the surface attraction of the wafer surface (ε, kJ/mol). (c−e) Representative cross-sectional snapshots showing membranes after 300 ns of production molecular dynamics under different wafer construction conditions showing the effect of low (−) and high (+) values of each parameter from part b.

Employing coarse-grained molecular dynamics simulations, we studied membranes interacting with nanoporous wafers inspired by the surface topography of our previously reported porous silicon nanoneedles.28−30,32 Surprisingly, our simulations predict membrane deformation behavior on nanoscale features much smaller than previously reported. We show that pores as small as 8 nm in diameter can deform lipid bilayers. We can strongly control the extent to which the membrane is deformed by nanopores and hence define a series of design parameters for fabricating cell-active surfaces. One of these design parameters describes pore taper (the sharpness of the pore edge), a previously unexamined characteristic of nanostructures for cellular interfacing applications, applicable to the design of nanopores as well as high-aspect ratio nanostructures. These simulations show that, when curved, the properties of the membrane are modified, resulting in an increased area per lipid, decreased thickness, and increased lipid mobility in the inner or cytosolic leaflet of curved membrane regions. Experimental studies suggest that regions of membrane curvature have an increased bioactivity; thus, we hypothesized that regions with an increased lipid spacing would attract membrane-inserting proteins. This hypothesis was confirmed by simulating a nanopore-deformed membrane with a model membrane-inserting protein, the epsin N-terminal homology (ENTH) domain of epsin 1. These simulations show spontaneous localization and specificity of the protein domain to these regions suggesting a potential role of nanopore-induced curvature in localizing endocytic processes, confirming an increased bioactivity in the regions of membrane curvature.

plays a key role in facilitating endocytosis, potentially by introducing a nanoscale membrane curvature. Separate works by Galic et al. and Zhao et al. using nanostructured surfaces indicate that curvature-sensing proteins localize around regions of nanostructure-induced cell deformation, suggesting that membrane−protein interactions are influenced directly by the substrate.33,34 Experimentally, the benefits of nanostructured surfaces are clear; however, a better understanding of the cell− nanostructure interface is required to inform our understanding of intracellular access and mechanostransduction and to aid in the design of future biomaterials. Our aims are to elucidate the critical parameters needed to induce nanoscale membrane curvature for nano-bio interfacing applications and to characterize this interface by understanding the effects that nanostructures have on membrane properties and subsequent cellular function. Membrane deformation has been studied previously in silico using a mixture of coarse-grained and atomistic approaches.35,36 However, most models focus on protein-sensing or proteininduced deformation and neglect the influence of nanostructured surfaces. Of the few porosity-induced models, these have considered the impact of 10−100 nm structures, rather than sub-10 nm nanopores.37 The recent work by AgudoCanalejo et al. stands out; they show that complete adhesion of biomembranes to nanopitted surfaces is always (meta)stable.37 Here, we extend our understanding of this biointerface by showing how even below 10 nm nanoporous surfaces directly induce membrane curvature and subsequently influence protein localization. 4771

DOI: 10.1021/acs.nanolett.9b01990 Nano Lett. 2019, 19, 4770−4778

Letter

Nano Letters

Figure 2. (a) Curvature profile and (b) curvature values as a function of radial distance for representative membranes under different nanopore conditions. The effect of pore taper can be clearly seen in the middle column of part b showing a maximum curvature value at T = 2.5 nm. f(x) and K(x) refer to the functions in eqs 1 and 2, respectively.

More work needs to be done on examining different membraneactive proteins and their potential interactions with curvature, but our ENTH-domain simulations substantiate the bioactivity of such regions. In order to evaluate how membranes interact with nanoporous substrates, we relied on a highly controllable model containing a flat wafer with a single central pore, as shown schematically in Figure 1a. We then placed model bilayers above the wafer and allowed them to interact with the central nanopore, observing and evaluating membrane morphology on the nanopitted surface. Spontaneous curvature of the membrane was observed in almost all cases after interfacing with such structures. Three key nanopore construction parameters were defined to evaluate this effect: pore radius (R, nm), pore taper (T, nm), and surface attraction of the wafer surface (ε, kJ/mol) (shown schematically in Figure 1b). We modified each of these parameters and evaluated the subsequent effect on spontaneous membrane curvature. We designed nanopores with pore radii of 4, 6, 8, and 10 nm, pore tapers of 0.75, 1.25, 2.5, and 5 nm, and surface attraction of 0.5, 1.0, 1.5, and 2.0 kJ/mol, totaling 64 individual nanopore designs. Details of the wafer construction can be found in the Supporting Information, section S1. From the simulation snapshots in Figure 1b, we can clearly observe spontaneous curvature in the membranes. This figure shows cross sections of deformed membranes (after 300 ns of simulation) interacting with various wafer design conditions. These snapshots show the extent to which nanoporous surfaces curve membranes and the effect of each parameter on membrane curvature. Decreasing the surface attraction reduces the extent of membrane invagination into the pore (Figure 1c), while increasing the radius has no impact on the overall curvature of the membrane at pore edges (Figure 1e). However, minor increases in the pore taper have a strong influence, with the membrane changing from relatively flat to highly curved as seen in Figure 1d. In order to quantify the extent of curvature induction in our membranes, we extracted the positions of lipid heads in the membrane’s upper leaflet and averaged their positions radially from the central pore to create a “curvature profile” of the deformed membrane. This profile is then fitted to a sigmoid-like equation (shown schematically in Figure S1):

f (x ) =

a d+e

−c(x − x0)

+b

(1)

where a, b, c, d, and x0 are fitting parameters. Once fitted, we can calculate the curvature (K) of our membrane using the equation for the curvature of a function: K (x ) =

f ′′(x) 1 = R c(x) (1 + (f ′(x)2 )3/2

(2)

where K(x) is the absolute curvature of the function, Rc(x) is the radius of curvature, and f ′(x) and f ′′(x) are the first and second derivatives of the sigmoid-function fit of the membrane profile, respectively (see the Supporting Information, section S2, for full derivation and the explicit formula). Plots of the membrane profile, f(x), and curvature of the membrane, K(x), for membranes as a function of radial distance from the central pore are shown under various curvature conditions in Figure 2, respectively. This figure represents a summary of the fitted curves from different simulation snapshots, as per the example shown in Figure S1 and shows how nanoporous wafers can alter membrane curvature from zero curvature to radii of approximately 5 nm with ease. Each wafer construction parameter affects the final curvature of our membrane; for example, increasing the wafer pore size (R) from 4 to 10 nm reduces the final membrane curvature and shifts the maximum curvature position away from the central pore. Unsurprisingly, increasing the attraction between lipids and the surface improves the ability of the substrate to deform membranes. More interestingly, we see an optimal pore taper (T) value for inducing curvature. We see a maximum membrane curvature for a pore taper value of 2.5 nm. Below or above this value, curvature is less significant. Figures S2 and S3 show the curvature profiles and curvature values for all of the parameters investigated in this study. By solving the roots of the third derivative of the sigmoid fit f(x), we can evaluate the maximum curvature values of the membrane as a function of the wafer construction parameters described previously (see section S2 in the Supporting Information) and assign a final membrane curvature value for each of the 64 combinations of parameters evaluated in this study. We can then plot these values for each of our wafer 4772

DOI: 10.1021/acs.nanolett.9b01990 Nano Lett. 2019, 19, 4770−4778

Letter

Nano Letters

Figure 3. Parameter matrix showing the effects of pore size (R), pore taper (T), and surface attraction (ε) on final bilayer curvature, summarizing the results of all 64 combinations of the parameters simulated in this study. Each individual 4 × 4 square represents the varying pore taper and surface attraction values for a given pore size.

Figure 4. Heat maps of local membrane properties of the upper leaflet viewed from above showing (a) lipid orientation along the x−y plane, (b) membrane area per lipid, (c) membrane thickness, and (d) lipid movement for membranes under various conditions showing the effects of surface attraction, pore taper, and pore radius on final membrane properties.

construction parameters and determine wafer designs that maximize curvature generation, shown in Figure 3. We find that the maximum curvature for each pore radius is at a taper of 2.5 nm. This suggests that the sharpness of the pore edge plays a crucial role in determining the interaction between the substrate and the membrane. We see that membrane curvature decreases

with an increasing pore size, suggesting a diminishing effect of pore size on membrane curvature, which is also observed in Figure 2b. These parameters, in particular, surface attraction and pore taper, can be used to guide the design of nanostructures for biointerfacing applications. Increasing surface attraction via 4773

DOI: 10.1021/acs.nanolett.9b01990 Nano Lett. 2019, 19, 4770−4778

Letter

Nano Letters

Figure 5. (a) Crystal structure of the ENTH domain of epsin 1 (1H0A.pdb, PIP lipid not shown) and representation of its conformation when bound to the membrane (light blue) with hydrophobic and nonhydrophobic residues highlighted. (b) Histogram showing statistical frequency of contacts between lipid tails and the protein residues during simulation. (c) Histogram showing statistical frequency of the domain center of mass (CoM) for 4 μs of production MD and inner-leaflet lipid heads showing localization of the protein to membrane curvature at around 10 nm away from the central pore. Note that both plots in part c share the same x-axis.

lipid orientation, lipid movement, membrane area per lipid, and membrane thickness, respectively, for membranes in contact with wafers under various conditions. These maps show that not only do the nanopores induce curvature in the membranes but they also change key membrane properties at these regions. For a pore radius of 8 nm and a pore taper of 2.5 nm, the area per lipid in curved regions increases from 50−70 Å2 to almost 80 Å2 (Figure 4b).41,42 This observation is significant as an increased lipid spacing may result in increased binding of membraneembedding proteins, as well as influencing localization of large membrane components such as larger lipids or transmembrane proteins.1,13 This is not an artifact of periodic boundary conditions as the membranes we simulate are ribbons, periodic in only the y-direction, allowing them to widen and reshape with ease along the x-direction and hence avoiding undue tension within the membrane as they deform. This freedom is illustrated in Figure 4b−d, for a pore taper of 2.5 nm, where the unrestricted sides of the membrane have freely moved across their periodic boundaries. Curved regions have greater area per lipid and decreased membrane thickness. The tilted lipid angle across the pore edge is consistent with our analysis of the curved membranes. Figures S5−8 show the lipid orientation, movement, area per lipid, and membrane thickness maps for all of the parameters investigated in this study. During simulation, we see an increased lipid movement in the center of the membrane suspended across the pore opening. We attribute this to a lack of wafer−membrane interactions in this region, which otherwise dampen lipid diffusion in both leaflets, where the wafer and membrane are in contact. This is consistent with the observed increase in lipid velocity with a decreasing surface attraction (Figure 4d). We do not report the local diffusion parameter of lipids within our membranes, as reliable estimates cannot be obtained from this model. However, we confirmed the overall membrane diffusion parameters, calculated using the g_msd tool in GROMACS. Diffusion parameters were found to be between 4 and 5 × 10−7 cm2 s−1, consistent with prior reports.43 These changes in lipid dynamics could in

chemical functionalization of topographical substrates is commonly achieved by attaching peptide binding motifs or other components that mimic the naturally occurring extracellular matrix environment.38 However, modifying the taper of nanostructures is an interesting, underexplored characteristic that can be readily controlled using microfabrication procedures. The nanopore taper can be applied not only to the design of planar nanoporous substrates but also to high-aspect ratio structures such as porous nanoneedles.30 We suggest this approach could be used to enhance the net membrane curvature on substrates such as nanopillars or nanowires and could easily be implemented with microfabrication techniques such as metalassisted chemical etching,39 or reactive ion etching.40 Our model membranes are made purely of dipalmitoylphosphatidylcholine (DOPC) lipids and lack many of the structural components found in real cell membranes such as cholesterol, lipid moieties, membrane proteins, and receptors. The compositional differences between our model case and real membranes mean that exact curvature predictions should be avoided. However, the nature of our analysis suggests that the relative trends of surface attraction, pore radius, and pore taper on membrane curvature can inform the design of materials targeting cell membrane manipulation. Modifying the cholesterol content from 0 to 10% showed no difference in membrane curvature for similar cases (see Figure S4). The surface chemistry of our nanoporous substrate is controlled by modifying the depth of the Lennard−Jones potential well between surface beads and lipid headgroups. This method is analogous to modifying the surface charge to improve adhesion of cells and lipid membranes to surfaces, which can be achieved using techniques such as oxygen plasma treatments, polyelectrolyte layer coatings, or self-assembled monolayers.38 We modify the surface charge of our wafers to promote membrane adhesion in the solvent explicit simulations of the ENTH domain. Following the evaluation of general deformation in our membranes, we investigated the membrane properties around such regions of curvature. Figure 4a−d shows heat maps of the 4774

DOI: 10.1021/acs.nanolett.9b01990 Nano Lett. 2019, 19, 4770−4778

Letter

Nano Letters

lipids, that the ENTH domain spontaneously localizes to curved membrane regions. The domain remains bound for long simulation times (up to 4 μs modeled here), in both a biologically correct orientation and conformation mainly due to the action of its amphipathic H0 helix (Figure S10a).52 This suggests that other proteins or moieties within the cell containing amphipathic residues could preferentially localize at these regions. One could propose a mechanism by which nanotopographical tools could be used to artificially hijack and confine membrane-mediated intracellular processes through induction of nanoscale membrane curvature induction. In conclusion, we have shown how nanopores influence and deform cell membranes. We set out a series of design parameters, including pore radius, surface attraction, and pore taper, which can influence membrane curvature and can be used in the design of new nanostructured biomaterials. A new design parameter, pore taper, was shown to strongly influence membrane curvature, and we propose this parameter can be readily tailored using common microfabrication techniques. We observed a greater area per lipid and decreased thickness in curved membrane regions. The membrane-inserting ENTH domain was found to localize preferentially to these regions, suggesting consequences for biological signalingThese findings further our understanding of the changes occurring at the interface between biology and nanoporous surfaces and present a possible explanation for our recently reported observations of increased endocytosis localization around porous silicon nanoneedles.32 Further experimental work remains to quantify these effects on cellular membranes, as more complex membrane composition and size effects may play a role that our simulations cannot capture. This nanopore curvature model is highly controllable, facilitating further theoretical studies of the effects of membrane curvature on protein binding, protein function, and protein− lipid interactions. Finally, our results improve our understanding of the processes behind material-mediated drug delivery and could serve to inform the design of the next generation of nanomaterials for cytosolic delivery and cellular manipulation in nanomedicine. Materials and Methods. Simulations Details. All curvature simulations were performed at 310 K with Gromacs 4.6.753 using the Dry Martini implicit-solvent coarse-grained force field43 and visualized using VMD.54 The MDAnalysis package was used for all analysis in this work unless stated otherwise.55 Membranes were generated from dipalmitoylphosphatidylcholine (DOPC) lipids and contained 4056 molecules using the insane.py script.56 Porous wafers were built manually with beads arranged in a face centred cubic structure (FCC) using the atomic simulation environment (ASE) package.57 Full details of the methods used to construct the nanoporous wafers are presented in Supporting Information, section S1. Membranes were placed above the nanoporous wafers and were equilibrated for 20 ns using a 0.02 ps time step followed by two rounds of 300 ns of production MD using a 0.03 ps time step, the first round allowing for the membrane to come into contact with the wafer and the second for evaluating membrane properties. All implicit-solvent simulations were carried out without pressure coupling and using a velocity-rescaling thermostat with a 1 ps time constant. Protein simulations were performed at 323 K using the Martini force field with explicit water.58 Explicit and implicit water models showed a similar behavior as that shown in Figure S9. A case from the curvature-control simulations (R = 6 nm, T =

part explain the phase separation behavior observed in porespanning lipid bilayers.44 Our model indicates that unperturbed membranes have a nominal thickness of approximately 3.5 nm, consistent with physical measurements of DOPC bilayers.41,42 We observe a taper- and surface-attraction-dependent decrease in membrane thickness from 3.5 to 2.5 nm at regions of membrane curvature. Along with an increased lipid spacing, this membrane thinning may result in short transmembrane proteins preferentially localizing to such regions. The proteins typically disrupt the membrane to hide their hydrophobic residues.45,46 We suspect these structural defects, induced by cell−nanostructure interfacing, are present in many biointerfacing applications and that changes in membrane geometry may play a significant role in the measured cellular response. Full details of membrane analysis methods are presented in Supporting Informations, section S3 We posit that curved membrane regions could act as hotspots for certain membrane-mediated cellular processes and may modulate cellular function. We tested this hypothesis by combining a nanopore-deformed membrane (R = 6 nm, T = 5 nm, and ε = 2.0 kJ/mol) with a membrane-active epsin Nterminal homology (ENTH) protein domain. We selected this case in order to have a balanced area of curved and flat regions of the membrane so as not to bias the interaction between the domain and the deformed membrane. This domain binds charged phosphoinositide (PIP) lipids in the cell membrane and plays a crucial role in endocytosis as a structural component of epsin 1.47−49 The ENTH domain is the main membranebinding motif of epsin 1 and has been shown to recognize and localize to regions of membrane curvature.50 During simulations, we observed spontaneous localization of the domain to membrane curvature regions, as well as sustained localization of the protein domain for up to 4 μs of simulation time. Simulating with flat membranes showed no binding of the domain as it gets trapped at the free edges of the membrane or on the bottom side of the nanoporous wafer (data not shown). Implicit- and explicit-solvent models showed little difference between membrane properties (Figure S9). Figure 5a shows the crystal structure of the ENTH domain and its orientation when approximately 3.5 nm membrane (1H0A.pdb, PIP binding lipid not shown) with helix H0 inserted into the hydrophobic core of the membrane. Figure 5b shows the number of hydrophobic contacts between the protein residues and lipid tails evaluated throughout the MD simulation showing insertion of the domain’s H0 helix into the hydrophobic region of the membrane (residues 0−19) and domain compression upon insertion to allow for increased access by other hydrophobic residues (approximately residues 40−60). These residues are highlighted on the domain crystal structure shown in Figure S10a. The protein remains bound to the membrane throughout the simulation (Figure S10b), and its radius of gyration is stable throughout (Figure S10c). This finding is consistent with prior models of buckled membranes with preinserted transmembrane proteins and peptides, in which spontaneous localization was observed.51 Our model shows this behavior can occur, even if the protein is not preloaded into the membrane. Figure 5c plots the distribution of the radial location of the domain’s center of mass during the simulation, showing preferential localization to regions of membrane curvature at a radius of approximately 10 nm from the central pore. These simulations support our hypothesis of the bioactive nature of these regions of membrane curvature. Our simulations show, albeit without PIP membrane 4775

DOI: 10.1021/acs.nanolett.9b01990 Nano Lett. 2019, 19, 4770−4778

Letter

Nano Letters 5 nm, and ε = 2.0 kJ/mol) was taken and hydrated with coarsegrained water and 10% antifreeze particles. The ENTH domain was placed 3 nm above the center of the membrane. The system was equilibrated for 20 ns using a 0.02 ps time step and then simulated for 4 μs using a 0.03 ps time step. During equilibration and production MD, a semi-isotropic Berendsen and Parinello− Rahman barostat was used, using a time constant of 1 and 12 ps, respectively. The protein structure of the ENTH domain of epsin 1 was taken from the RCSB protein database from the structure resolved by Ford et al. (Protein Data Bank (PDB): 1H0A)59 and converted into a coarse-grained system using the martinize.py script provided by the Martini developers. The surface of the nanoporous substrate was negatively charged in order to promote adhesion of the membrane, better representing the strong attraction seen in reality,60,61 and overcoming the diminished adhesive effects in explicit water simulation. Counterions balancing the charges are also included. The protein minimum distance to the membrane and radius of gyration (shown in Figure S10b) were calculated using the g_mindist and g_gyrate tools, respectively, in Gromacs.53 The g_mindist tool was also used to compute the number of hydrophobic contacts between protein residues and lipid tails (Figure 5b). Curvature Evaluation. Following two rounds of production MD, the lipid heads in the membrane upper leaflet were averaged and fitted to the sigmoid function shown in eq 1 (Figure 2a and Figure S2) as represented schematically in Figure S1. The curvature of the membrane is then evaluated using eq 2 (Figure 2b and Figure S3). The maximum curvature values (Figure 3) of the membranes were then computed by solving the roots of the third derivative of eq 1 for each simulation case. Full derivations of eq 1 are presented in the Supporting Information, section S2. Membrane Analysis. All membrane property heat maps (Figure 4 and Figures S5−8) were evaluated over the last 90 ns of simulation time to avoid erroneous results as the membrane contacts the wafer, as well as incorrect property measurements due to the overall membrane motion. Each heat map was generated by segmenting membrane simulations into 30 by 30 equally spaced bins in the x−y plane. Full details of the analysis methods are presented in the Supporting Information, section S3.

■

ORCID

Alexis Belessiotis-Richards: 0000-0001-6838-5961 Molly M. Stevens: 0000-0002-7335-266X Author Contributions

M.M.S. and A.A.K. planned and supervised the research. A.B.R. designed and carried out the simulations. B.B. assisted with analysis. S.G.H. mentored A.B.R. and contributed to and edited the manuscript. All authors contributed to the discussion and prepared the manuscript. Notes

The authors declare no competing financial interest. Raw data is available upon reasonable request from aalexand@ mit.edu.

■

ACKNOWLEDGMENTS A.B.R. acknowledges a studentship from the Engineering and Physical Sciences Research Council (EPSRC) Centre for Doctoral Training in the Advanced Characterization of Materials (EP/L015277/1).

■ ■

ABBREVIATIONS PIP, phosphoinosotide; ENTH, epsin N-terminal homology; DOPC, dipalmitoylphosphatidylcholine (1) Koldso, H.; Shorthouse, D.; Helie, J.; Sansom, M. S. P. Lipid Clustering Correlates with Membrane Curvature as Revealed by Molecular Simulations of Complex Lipid Bilayers. PLoS Comput. Biol. 2014, 10, No. e1003911. (2) Vanni, S.; Hirose, H.; Barelli, H.; Antonny, B.; Gautier, R. A subnanometre view of how membrane curvature and composition modulate lipid packing and protein recruitment. Nat. Commun. 2014, 5, 4916. (3) Callan-Jones, A.; Sorre, B.; Bassereau, P. Curvature-driven lipid sorting in biomembranes. Cold Spring Harb. Perspect. Biol. 2011, 3, 1− 14. (4) Stachowiak, J. C.; et al. Membrane bending by protein − protein crowding. Nat. Cell Biol. 2012, 14, 944−949. (5) Simunovic, M.; Srivastava, A.; Voth, G. A. Linear aggregation of proteins on the membrane as a prelude to membrane remodeling. Proc. Natl. Acad. Sci. U. S. A. 2013, 110, 20396−20401. (6) Skruzny, M.; et al. Molecular basis for coupling the plasma membrane to the actin cytoskeleton during clathrin-mediated endocytosis. Proc. Natl. Acad. Sci. U. S. A. 2012, 109, E2533−E2542. (7) Kaksonen, M.; Toret, C. P.; Drubin, D. G. Harnessing actin dynamics for clathrin-mediated endocytosis. Nat. Rev. Mol. Cell Biol. 2006, 7, 404−414. (8) Hung, Y.-F.; et al. Dengue virus NS4A cytoplasmic domain binding to liposomes is sensitive to membrane curvature. Biochim. Biophys. Acta, Biomembr. 2015, 1848, 1119−1126. (9) Yao, H.; Lee, M. W.; Waring, A. J.; Wong, G. C. L.; Hong, M. Viral fusion protein transmembrane domain adopts β-strand structure to facilitate membrane topological changes for virus−cell fusion. Proc. Natl. Acad. Sci. U. S. A. 2015, 112, 10926−10931. (10) Schmidt, N. W.; Mishra, A.; Wang, J.; Degrado, W. F.; Wong, G. C. L. Influenza virus A M2 protein generates negative gaussian membrane curvature necessary for budding and scission. J. Am. Chem. Soc. 2013, 135, 13710−13719. (11) Weise, K.; et al. Membrane-mediated induction and sorting of KRas microdomain signaling platforms. J. Am. Chem. Soc. 2011, 133, 880−887. (12) Reynwar, B. J.; et al. Aggregation and vesiculation of membrane proteins by curvature-mediated interactions. Nature 2007, 447, 461− 464. (13) Strahl, H.; et al. Transmembrane protein sorting driven by membrane curvature. Nat. Commun. 2015, 6, 8728.

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.nanolett.9b01990.

■

REFERENCES

Nanoporous wafer construction, derivation of the curvature-fitting function, analysis methods for membrane properties, profiles and curvature values for all simulated cases, effect of cholesterol on membrane properties, lipid angle, area per lipid, membrane thickness, and lipid movement for all simulated cases, comparison between implicit- and explicit-solvent models, and additional details on protein interaction simulations (PDF)

AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected]. *E-mail: [email protected]. 4776

DOI: 10.1021/acs.nanolett.9b01990 Nano Lett. 2019, 19, 4770−4778

Letter

Nano Letters (14) Larsen, J. B.; et al. Membrane curvature enables N-Ras lipid anchor sorting to liquid-ordered membrane phases. Nat. Chem. Biol. 2015, 11, 192−194. (15) Hanna, M. G.; et al. Sar1 GTPase Activity Is Regulated by Membrane Curvature. J. Biol. Chem. 2016, 291, 1014−1027. (16) Š arić, A.; Cacciuto, A. Mechanism of membrane tube formation induced by adhesive nanocomponents. Phys. Rev. Lett. 2012, 109, 188101. (17) van der Wel, C.; Vahid, A.; Saric, A.đe.; Idema, T.; Heinrich, D.; Kraft, D. J.; et al. Lipid membrane-mediated attraction between curvature inducing objects. Sci. Rep. 2016, 6, 1−10. (18) Pieuchot, L.; Marteau, J.; Guignandon, A.; Dos Santos, T.; Brigaud, I.; Chauvy, P.-F.; Cloatre, T.; Ponche, A.; Petithory, T.; Rougerie, P.; Vassaux, M.; Milan, J.-L.; Tusamda Wakhloo, N.; Spangenberg, A.; Bigerelle, M.; Anselme, K.; et al. Curvotaxis directs cell migration through cell-scale curvature landscapes. Nat. Commun. 2018, 9, 3995. (19) Park, J.; Bauer, S.; Von Der Mark, K.; Schmuki, P. Nanosize and vitality: TiO2 nanotube diameter directs cell fate. Nano Lett. 2007, 7, 1686−1691. (20) Agrawal, A. A.; et al. Porous nanocrystalline silicon membranes as highly permeable and molecularly thin substrates for cell culture. Biomaterials 2010, 31, 5408−5417. (21) Vetrone, F.; et al. Nanoscale oxidative patterning of metallic surfaces to modulate cell activity and fate. Nano Lett. 2009, 9, 659−665. (22) Popat, K. C.; et al. Influence of nanoporous alumina membranes on long-term osteoblast response. Biomaterials 2005, 26, 4516−4522. (23) Park, J.; et al. TiO2 nanotube surfaces: 15 nm - an optimal length scale of surface topography for cell adhesion and differentiation. Small 2009, 5, 666−671. (24) Wang, S.; Kowal, T. J.; Marei, M. K.; Falk, M. M.; Jain, H. Nanoporosity significantly enhances the biological performance of engineered glass tissue scaffolds. Tissue Eng., Part A 2013, 19, 1632− 1640. (25) Guadarrama Bello, D.; Fouillen, A.; Badia, A.; Nanci, A. A nanoporous titanium surface promotes the maturation of focal adhesions and formation of filopodia with distinctive nanoscale protrusions by osteogenic cells. Acta Biomater. 2017, 60, 339−349. (26) Chen, Z.; et al. Nanoporous microstructures mediate osteogenesis by modulating the osteo-immune response of macrophages. Nanoscale 2017, 9, 706−718. (27) Chapman, C. A. R.; et al. Nanoporous gold as a neural interface coating: Effects of topography, surface chemistry, and feature size. ACS Appl. Mater. Interfaces 2015, 7, 7093−7100. (28) Chiappini, C.; et al. Biodegradable nanoneedles for localized delivery of nanoparticles in vivo: Exploring the biointerface. ACS Nano 2015, 9, 5500−5509. (29) Chiappini, C.; et al. Mapping Local Cytosolic Enzymatic Activity in Human Esophageal Mucosa with Porous Silicon Nanoneedles. Adv. Mater. 2015, 27, 5147−5152. (30) Chiappini, C.; et al. Biodegradable silicon nanoneedles delivering nucleic acids intracellularly induce localized in vivo neovascularization. Nat. Mater. 2015, 14, 532−539. (31) Hansel, C. S.; et al. Nanoneedle-Mediated Stimulation of Cell Mechanotransduction Machinery. ACS Nano 2019, 13, 2913−2926. (32) Gopal, S.; et al. Porous Silicon Nanoneedles Modulate Endocytosis to Deliver Biological Payloads. Adv. Mater. 2019, 31, 1806788. (33) Zhao, W.; et al. Nanoscale manipulation of membrane curvature for probing endocytosis in live cells. Nat. Nanotechnol. 2017, 12, 750− 756. (34) Galic, M.; et al. External push and internal pull forces recruit curvature-sensing N-BAR domain proteins to the plasma membrane. Nat. Cell Biol. 2012, 14, 874−881. (35) Ramakrishnan, N.; Bradley, R. P.; Tourdot, R. W.; Radhakrishnan, R. Biophysics of membrane curvature remodeling at molecular and mesoscopic lengthscales. J. Phys.: Condens. Matter 2018, 30, 273001.

(36) Bradley, R.; Radhakrishnan, R. Coarse-grained models for protein-cell membrane interactions. Polymers 2013, 5, 890−936. (37) Agudo-Canalejo, J.; Discher, D. E. Biomembrane Adhesion to Substrates Topographically Patterned with Nanopits. Biophys. J. 2018, 115, 1292−1306. (38) Rizwan, M.; Tse, J. W.; Nori, A.; Leong, K. W.; Yim, E. K.F. Cell− Substrate Interactions. Principles of Regenerative Medicine 2019, 437− 468. (39) Huang, Z.; Geyer, N.; Werner, P.; de Boor, J.; Gösele, U. MetalAssisted Chemical Etching of Silicon: A Review. Adv. Mater. 2011, 23, 285−308. (40) Whitney, A. V.; Myers, B. D.; Van Duyne, R. P. Sub-100 nm triangular nanopores fabricated with the reactive ion etching variant of nanosphere lithography and angle-resolved nanosphere lithography. Nano Lett. 2004, 4, 1507. (41) Kucerka, N.; Nieh, M.-P.; Katsaras, J. Fluid phase lipid areas and bilayer thicknesses of commonly used phosphatidylcholines as a function of temperature. Biochim. Biophys. Acta, Biomembr. 2011, 1808, 2761−2771. (42) Reddy, A. S.; Warshaviak, D. T.; Chachisvilis, M. Effect of membrane tension on the physical properties of DOPC lipid bilayer membrane. Biochim. Biophys. Acta, Biomembr. 2012, 1818, 2271−2281. (43) Arnarez, C.; et al. Dry Martini, a Coarse-Grained Force Field for Lipid Membrane Simulations with Implicit Solvent. J. Chem. Theory Comput. 2015, 11, 260−275. (44) Schuette, O. M.; et al. Size and mobility of lipid domains tuned by geometrical constraints. Proc. Natl. Acad. Sci. U. S. A. 2017, 114, E6064−E6071. (45) Mitra, K.; Ubarretxena-Belandia, I.; Taguchi, T.; Warren, G.; Engelman, D. M. Modulation of the bilayer thickness of exocytic pathway membranes by membrane proteins rather than cholesterol. Proc. Natl. Acad. Sci. U. S. A. 2004, 101, 4083−4088. (46) Andersen, O. S.; Koeppe, R. E. Bilayer Thickness and Membrane Protein Function: An Energetic Perspective. Annu. Rev. Biophys. Biomol. Struct. 2007, 36, 107−130. (47) Jakobsson, J.; et al. Role of epsin 1 in synaptic vesicle endocytosis. Proc. Natl. Acad. Sci. U. S. A. 2008, 105, 6445−6450. (48) Messa, M.; Fernandez-Busnadiego, R.; Sun, E. W.; Chen, H.; Czapla, H.; Wrasman, K.; Wu, Y.; Ko, G.; Ross, T.; Wendland, B.; De Camilli, P.; et al. Epsin deficiency impairs endocytosis by stalling the actin-dependent invagination of endocytic clathrin-coated pits. Elife 2014, 3, No. e03311. (49) Chen, H.; et al. Epsin is an EH-domain-binding protein implicated in clathrin-mediated endocytosis. Nature 1998, 394, 793− 797. (50) Capraro, B. R.; Yoon, Y.; Cho, W.; Baumgart, T. Curvature sensing by the epsin N-terminal homology domain measured on cylindrical lipid membrane tethers. J. Am. Chem. Soc. 2010, 132, 1200− 1201. (51) Wu, Q. Y.; Liang, Q. Interplay between curvature and lateral organization of lipids and peptides/proteins in model membranes. Langmuir 2014, 30, 1116−1122. (52) Lai, C. L.; et al. Membrane Binding and Self-Association of the Epsin N-Terminal Homology Domain. J. Mol. Biol. 2012, 423, 800− 817. (53) Hess, B.; Kutzner, C.; Van Der Spoel, D.; Lindahl, E. GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation. J. Chem. Theory Comput. 2008, 4, 435−447. (54) Humphrey, W.; Dalke, A.; Schulten, K. VMD: Visual molecular dynamics. J. Mol. Graphics 1996, 14, 33−38. (55) Michaud-Agrawal, N.; Denning, E. J.; Woolf, T. B.; Beckstein, O. MDAnalysis: A toolkit for the analysis of molecular dynamics simulations. J. Comput. Chem. 2011, 32, 2319−2327. (56) Wassenaar, T. A.; Ingólfsson, H. I.; Böckmann, R. A.; Tieleman, D. P.; Marrink, S. J. Computational Lipidomics with insane : A Versatile Tool for Generating Custom Membranes for Molecular Simulations. J. Chem. Theory Comput. 2015, 11, 2144−2155. 4777

DOI: 10.1021/acs.nanolett.9b01990 Nano Lett. 2019, 19, 4770−4778

Letter

Nano Letters (57) Hjorth Larsen, A.; et al. The atomic simulation environment - A Python library for working with atoms. J. Phys.: Condens. Matter 2017, 29, 273002. (58) Marrink, S. J.; Risselada, H. J.; Yefimov, S.; Tieleman, D. P.; de Vries, A. H. The MARTINI force field: Coarse grained model for biomolecular simulations. J. Phys. Chem. B 2007, 111, 7812−7824. (59) Ford, M. G. J.; et al. Curvature of clathrin-coated pits driven by epsin. Nature 2002, 419, 361−366. (60) Cremer, P. S.; Boxer, S. G. Formation and Spreading of Lipid Bilayers on Planar Glass Supports. J. Phys. Chem. B 1999, 103, 2554− 2559. (61) Nollert, P.; Kiefer, H.; Jähnig, F. Lipid vesicle adsorption versus formation of planar bilayers on solid surfaces. Biophys. J. 1995, 69, 1447−1455.

4778

DOI: 10.1021/acs.nanolett.9b01990 Nano Lett. 2019, 19, 4770−4778