Three-Dimensional Heterogeneous Structure Formation on a

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Three-Dimensional Heterogeneous Structure Formation on Supported Lipid Bilayer Disclosed by Single Particle Tracking Yaning Zhong, and Gufeng Wang Langmuir, Just Accepted Manuscript • DOI: 10.1021/acs.langmuir.8b01690 • Publication Date (Web): 31 Aug 2018 Downloaded from http://pubs.acs.org on September 2, 2018

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Three-Dimensional Heterogeneous Structure Formation on Supported Lipid Bilayer Disclosed by Single Particle Tracking

Yaning Zhong and Gufeng Wang*

Department of Chemistry, North Carolina State University, Raleigh, NC 27695-8204

Address all correspondence to: Gufeng Wang, Department of Chemistry, North Carolina State University, Raleigh, NC 276958204. Tel: (919) 515-1819; E-mail: [email protected]

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Abstract Three-dimensional single particle tracking (3D SPT) was employed to study the lipid membrane morphology change at different pHs on glass supported lipid bilayers (DOPE : DOPS : DOPC = 5 : 3 : 2). 100-nm fluorescently tagged, carboxylated polystyrene nanoparticles were used as the probes. At neutral pHs, the particles’ diffusion was close to 2D Brownian motion, indicating a mainly planar structure of the supported lipid bilayers (SLB). When the environmental pH was tuned to be basic at 10.0, transiently confined diffusions within small areas were frequently observed. These confinements had a lateral dimension of 100~200 nm. Most interestingly, they showed 3D bulged structures protruding from the planar lipid bilayer. The particles were trapped by these 3D structures for a short period of time (~0.75 s), with an estimated escape activation energy of ~4.2 kBT. Non-uniform distribution of pH-sensitive lipids in the membrane was proposed to explain the formation of these 3D heterogeneous structures. This work suggests that the geometry of the 3D lipid structures can play a role in tuning the particle-lipid surface interactions. It sheds new light on the origin of lateral heterogeneity on lipid membrane.

Keywords: 3D single particle tracking; supported lipid bilayer; lipid domains; 2D diffusion


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Introduction Investigating the structure and functionality of cell membrane is critical to understanding many biological processes such as cell signaling and material exchange with the environment.1-6 Currently, it is generally accepted that cell membrane is not a uniform bilayer but rather there are many heterogeneous structures that can gather species with the similar affinity. The concept of lipid “domain” was proposed to account for the observation of lateral heterogeneity on supported lipid bilayers (SLBs) as well as on cell membranes.7-10 So far, it is believed that lipid domains form when lipids undergo lateral phase separations. Many studies are in agreements on general findings for compositional phase diagrams in SLBs, i.e., the coalescence of the liquid ordered (Lo) domains, which are rich in glycosphingolipids, cholesterols and/or anchor proteins.11, 12 Some of the studies show the coincidence of phase separation and locations with special membrane properties. The term lipid “domain” is specifically reserved for phase separated lipids. In practice, the use of this term is relaxed and lipid membrane lateral heterogeneous properties were frequently ascribed to the formation of lipid domains. Additional evidence of domains, or sometimes simply membrane heterogeneity, comes from the observation using a variety of different experimental techniques on model systems and on cell membranes, e.g., fluorescence photobleaching recovery (FRAP),13 single particle tracking (SPT),14-17 atomic force microscopy (AFM),18-20 stimulated emission depletion (STED) microscopy,21 and fluorescence resonance energy transfer (FRET)22, 23 methods, etc. The proposal of lipid “domains” provides a reasonable explanation that proteins and their specific interaction partners are observed to stay close to each other. Such a design would greatly increase the efficiency of organizing a large amount of proteins with various functions to achieve desired cell activities.


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The lateral membrane heterogeneity can be induced by many factors including changes in temperature, pressure, ionic strength, or by the addition of proteins and other chemicals. However, the structure and composition of the heterogeneous structures, as well as the mechanism to compartmentalize the membrane, are still not clear and under intensive investigation currently. The challenge comes from the difficulty in observing the highly fluidic but ordered lipid domains in the nano- to meso-scales. This has led to a gap between the concept of domains, which is frequently studied in theoretical models, and the observation of heterogeneous structures and their functions in biological cells. Thus, elucidating the origin, structure, composition, size, and lifetime of the domains in both synthetic and biological cell membranes is a key in understanding their roles in cell functions. Conventional 2D SPT has been applied to study lipid bilayers’ thermal fluctuation, fluidity of lipid domains, and protein-lipid interactions, etc.24, 25 In the presence of lipid domains, transiently confined areas for particle diffusion can be observed.16,

17, 26

As a result, the

diffusional motion of particle probes attached with molecular recognition units deviates from 2D Brownian motion. It should be noted that the confinements in 2D SPT are frequently ascribed to the presence of lipid domains without evidence of phase separation. The confinements are the results of the interactions between the particle probe and the cluster of membrane containing target molecules (e.g., anchor proteins, glycosphingolipid, etc.) that the particle probe recognizes.14 Domains with different sizes have been disclosed and reported using 2D SPT, which can be classified as nanodomains (10 ~ 100 nm)17 and microdomains (>100 nm).14, 27 The size difference of domains has been corroborated by using current super resolution optical microscopy, such as stochastic optical reconstruction microscopy (STORM) and STED microscopy.8 However, current SPT studies are mainly focused on the planar motion of the


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particle probes due to technical limitations. The information of the particles’ movement in the zdirection is lost. On the other hand, the surface morphology of lipid membranes has been studied with scanning probe microscopies because of their excellent capacity in imaging soft surface both in air and under liquid. Interestingly, 3D structures were observed on SLBs.28,

29

For example,

Goertz et al. found that even single-component lipid bilayers can form cap-like structures when being exposed to extreme basic pHs.30 Similar structures were reported by Hovis and coworkers for multicomponent lipid bilayers being exposed to asymmetric ionic strengths.31, 32 However, these measurements are under static conditions and it is unclear what is the relationship between these 3D structures with the lipid lateral heterogeneity observed in dynamic particle tracking experiments.8 The information of interactions between particles and such 3D structures is missing. In this study, we used three-dimensional single particle tracking (3D SPT) technique33-36 to study the lipid bilayer morphology and heterogeneous structure formation on SLBs upon the external stimulus of a pH change. We used 100 nm fluorescently tagged, carboxylated polystyrene nanoparticles as the probes. A model of mixed lipid bilayer (DOPE : DOPS : DOPC = 5 : 3 : 2) supported on glass surface was studied, which is frequently used in monitoring heparin therapy37 since it can synergistically improve heparin's anticoagulant effect.38 Two of the three components show pH-sensitive ionization states at basic pHs.39 We examined the 3D morphology of the heterogeneous structures, i.e., locations where entrapment of the particles occur, which were frequently interpreted as lipid domains in the literature using conventional 2D SPT techniques. We found that at neutral pHs, the mixed SLB forms a relatively uniform layer, on which the polystyrene particles diffuse randomly in the plane. As the pH is increased to 10.0,


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the membrane becomes more heterogeneous, with multiple transient confinements as disclosed by the particle’s 2D trajectories. More interestingly, the 3D trajectory discloses for the first time that these heterogeneous structures have a 3D bulged shape with a dimension on the ~100 nm length scale. The 3D structures indicate that lipids may self-organize beyond planar configurations, which could lead to a new means for tuning their functions through 3D geometric effect. This study sheds new light on our understanding of lipid membrane structure and functions.

Results and Discussion 3D particle trajectory discloses constraints on particle motion. The particle’s 3D moving trajectory should reflect the constraints on the particle. For example, a particle diffusing on lipid membrane surface should give a “flat” trajectory while a particle diffusing in a thin channel should give a 3D trajectory reflecting the thickness of the channel. Conventional 2D SPT does not have this z-resolution thus is insufficient to disclose the constraints applied on the particle in the z-direction. For example, Movie 1A shows the conventional 2D fluorescence images of a 100 nm polystyrene particle diffusing inside a thin channel filled with CHES buffer at pH 7.4. The channel was ~1 µm deep, formed between a glass slide and a coverslip using 1 µm polystyrene particles as spacers. The particle moved quickly laterally and stayed near the focal plane because of the boundaries at the z-direction set by the channel. It is challenging to tell the particle’s z-positions but most of the experienced microscopiests would agree that this particle is moving in a 3D space. As a comparison, we also imaged the conventional 2D movie of a 100 nm fluorescent polystyrene nanoparticle diffusing on supported lipid bilayer (DOPE : DOPS : DOPC = 5 : 3 : 2)


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at pH 7.4 (Movie 1D). The movie is very similar to Movie 1A except that the particle on lipid membrane surface diffused slower. The particle showed smeared images from time to time, making it to look like diffusing in the 3D space. Practically, the two cases (diffusion on a flat surface or a thin channel) are indistinguishable using conventional 2D imaging. Note that these fluorescent particles were carboxylated and negatively charged (zeta potential ~ -50 mV).33 Though, they can attach to the bilipid membrane and diffuse on the surface, possibly by inserting dangling chain ends into the interior of membrane through van der Waals interaction despite of the repulsion from the samely charged lipid membrane surface.40 The interaction can be very strong between the nanoparticles and lipid membrane. For examples, it can be as large as ~500 kJ/mol for a 2-nm polystyrene nanoparticle with SLB.40 Or, it needs ~1 nN force (order of magnitude) to detach polymer-protected silica nanoparticles from cell surface.41 All these are consistent with our observations that polystyrene nanoparticles can firmly bind to SLB and desorption is rarely observed in the experiments. To investigate their 3D trajectories, a highly precise 3D single particle tracking technique is needed. Currently, there are significant efforts made toward tracking particles or molecules in the full 3D space and promising progress has been achieved. These methods include intensitybased z-tracking,42-44 imaging using z-sensitive point spread functions (PSF),33, 45-51 and confocal microscopy-based 3D tracking,52-55 etc. Here, we used our astigmatism-based image method, which allows the tracking of 85 nm fluorescently labeled nanoparticles in aqueous solution with a precision of 10~20 nm in all 3 axes at ~30 frames per second (fps).33, 34 We show that using this method, the two cases can be clearly distinguished. Movies 1B and 1E show the images collected using this astigmatic imaging method for the same particles as in Movies 1A and 1D, respectively. In Movie 1B, the particle image pattern changed when it was diffusing in the


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channel, indicating its z-position changed over time. For the particle diffusing on the lipid membrane surface (Movie 1E), the particles stayed in the same z-plane throughout, giving a nearly constant image pattern.

Figure 1. 100 nm polystyrene particle diffusing in a channel and on SLB membrane surface. (A,B,C) Diffusing in a 1 µm-thick microchannel filled with CHES buffer. (D,E,F) On SLB membrane surface. (A,D) Top views of the 3D trajectories. (B,E) Side views. The redlines define the boundaries of the microchannel. For all experiments, the glass substrate was on the top side (+ z-values) and the solution is on the bottom side (- z-values). (C,F) Mean squared 8 ACS Paragon Plus Environment

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displacements of the two particles, respectively. The red lines show the linear fitting of the MSDs, from which the diffusion coefficient of the particle can be calculated. From the movies, we can recover both particles’ 3D trajectories. Figures 1AB show the top view and the side view, respectively, of the particle diffusing in the 1 µm channel (the 3D trajectory can be viewed in Movie 1C). The top view of the trajectory reflects that this particle was diffusing randomly. The side view shows that the particle was also moving in the z-direction, but only in a range of ~1.2 µm confined by the channel. The particle’s diffusion coefficient was estimated using its 3D trajectory with the Einstein equation (Figure 1C): (1)

< L2 >= 2 nD t

where < L2 > is the mean squared displacement (MSD); n is the number of dimension (n = 3 for 3D diffusion and n = 2 for 2D diffusion); D is the diffusion coefficient; t is time interval. The MSD-t plot is linear within a time of 0.6 s, indicating a Brownian diffusion of the particle. The recovered diffusion coefficient for this particle is 2.7 µm2/s, which is consistent with our past studies.33 Figures 1DE show the top view and the side view, respectively, of the particle’s 3D trajectory when it diffused on SLB surface at pH 7.4. This particle also showed typical Brownian motion on the 2D plane as the MSD-t plot is linear with a time scale of 0.6 s (Figure 1F). The diffusion coefficient for this particle is 0.40 µm2/s. Compared to lipid molecules diffusing in SLBs or cell membrane (D ~3~4 µm2/s),56 this value is ~10 times smaller. This value is also ~10 times smaller than that the particle diffusing in free solution. These reflect the viscosity inside the membrane, and possibly suggest that the particle was diffusing with a cluster of lipid molecules in the lipid membrane.16, 17 Most interestingly, Figure 1E shows that this particle was on the SLB surface throughout the observation time (30 s). The standard deviation of all zpositions of this trajectory was 22 nm, which is slightly larger than the observation error 9 ACS Paragon Plus Environment

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(typically ~15 nm from repeated measurements of an immobilized particle on glass surface). This small difference could come from: (1) a fast moving particle in the xy-plane may give low quality images thus a larger error; (2) the particle may have a larger variation in its z-position due to the self-fluctuation of the SLBs.

Heterogeneity of lipid bilayer and complicated behavior of particles. With the highresolution 3D single particle tracking technique, we studied single particle diffusion trajectories on SLBs (DOPE : DOPS : DOPC = 5 : 3 : 2) supported by glass surface at pH 7.4. It turns out that the generally assumed 2D diffusion of particles on a flat model SLB surface can be complicated. Many features that were missed in 2D SPT were disclosed using the 3D SPT. Two main missed features are: (1) the morphology of the SLB surface could be more heterogeneous than one would expect for a model system; (2) the particle could have complicated behavior other than simple 2D diffusion on the surface, e.g., desorption and re-adsorption can be involved. (1) Heterogeneous SLB surface morphology. The 3D tracking technique shows that the SLB membrane may contain 3D structures, which are hemispherical bulges protruding from the flat surface. Figure 2 shows a selected trajectory of a 100 nm nanoparticle diffusing on SLB surface at pH 7.4. The particle diffused on lipid surface in the first ~25 seconds and eventually desorbed and diffused away in the solution. Figure 2A shows the particle’s x, y and z positions as a function of time for 30 s. The z trajectory shows that the particle permanently desorbed from the surface and diffused away at 25.4 s. More interestingly, during 8.6 ~ 11.2 s, the particle moved away from the surface plane by ~600 nm but did not leave the surface completely (square framed in Figure 2A). At the meantime, the particle’s xy-movement were also limited within a range of ~1 µm. The particle’s 2D trajectory (which is the top view of the 3D trajectory, Figure


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2B) shows a typical confined diffusion of the particle in an area of ~1 × 1 µm2 (circled in Figure 2B).

Figure 2. 100 nm particle diffusing on solid supported lipid bilayer at pH 7.4. (A) The x, y and z positions of the particle over time. The curves are shifted to have a clear view. (B) Top view of the 3D trajectory. (C) Side view. The negative direction in z trajectory indicates that the particle is moving away from the surface. (D) MSD curve from the first 25 s of the trajectory and the fitting. (E) Expanded view of the 3D trajectory between 8.6 s to 11.2 s. However, the 3D trajectory shows that this confined diffusion was not on a flat surface but on a hemi-spherical lipid structure protruding from the lipid bilayer surface. This can be seen from the side view (Figure 2C) and the expanded 3D view (Figure 2E) of the 3D trajectory.


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Apparently, the particle dwelled on the bulge for a period of time, leaving a domain-like footprint in the conventional 2D trajectory. However, the 3D SPT clearly discloses that the confinement is 3D in nature and the particle is simply diffusing on a hemi-spherical lipid structure. The MSD of the particle from the first 25 s shows a straight line, indicating that the rare confined diffusion had little effect on the 2D Brownian diffusion. The D for this specific particle is also 0.40 µm2/s.

Figure 3. Two representative examples of particle adsorption/desorption on lipid bilayer surface. (A-C) One example. (D-F) Another example. (A) and (D) x, y, and z positions as a function of


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time. Curves are shifted for viewing. (B) and (E) Top views of the trajectory. (C) and (F) Side views of the trajectory. (2) Transient desorption may happen but is not a dominant factor for particle diffusion. How particles diffuse on lipid surface, e.g., whether desorption is involved and helps the lateral movement, is currently unclear and under investigation.57 The 3D tracking technique shows that the particle may show complicated behavior such as transient desorption and re-adsorption during the surface diffusion. For examples, Figure 3 shows two typical trajectories that involve both adsorption and desorption processes. In the first example (Movies 3AB and Figures 3A-3C), the particle attached onto the SLB surface at 2.2 s. It diffused for 6.8 s on the surface and then desorbed and diffused away at 9.0 s. The z-profile (Figure 3A) shows the desorption event and the exact time point of the adsorption, which are usually challenging to identify in conventional 2D imaging. During the surface diffusion period, there were two occasions that the particle had active z-movements: one at 2.2-2.7 s (labeled in red circle) and the other at 3.3-3.7 s (labeled in green circle). The particle left the plane for ~ 600 nm; meanwhile they also show limited movement in the xy-plane. These two occasions are similarly assigned as bulge-like structures on lipid surface. Figures 3D-3F show another example of particle desorption/adsorption events on the membrane surface (Movies 3CD). From the z profile in Figure 3D, we can observe that the particle was diffusing on the lipid membrane surface until at 14.6 s it permanently desorbed from the surface. During the surface diffusion, the particle had two events in which its z-position varied significantly: one at 8.6-8.9 s (labeled in green square), and the other at 12.4-13.0 s (labeled in red square). The interesting case was at 8.6 s when the particle left the surface for 9 frames (~0.27 s) with a z-displacement of ~1.8 µm. The largest step had a z-displacement of 1.0 µm, > 6 times of the mean step size of the particle diffusing on lipid membrane surface for the 13 ACS Paragon Plus Environment

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same period of time. Thus, this event is very likely a desorption event. This example shows that particles may desorb temporarily from the lipid membrane, which were again challenging to capture using conventional 2D imaging. However, we noticed that the transient desorption events were very rare (i.e., 3 cases in a total of 20 trajectories). Hence, it is very unlikely that desorption-mediated diffusion plays a significant role in particle diffusion on SLBs at a time scale > 30 ms. We do realize that whether particles desorb frequently or not strongly depends on particle-surface interaction as well as the observation time scale. It should be discussed in a caseby-case base. Nonetheless, the 3D tracking method will provide a clearer view whether desorption is important in these studies. These examples demonstrate that the 3D tracking technique provides great opportunities to observe the 3D structures of the inhomogeneities on the lipid membrane surface, and abnormal behaviors of particle diffusing on lipid membrane surface.

pH-induced lipid heterogeneous structures on SLB surface and their 3D shapes. Above examples were selected to demonstrate that 3D SPT can identify abnormities of particle diffusion and surface morphology on SLB surface that is hypothetically flat. But generally, at neutral pHs, these events were relatively rare and the particle diffusion can be viewed as 2D Brownian motion. When the pH was tuned to 10.0, completely different particle diffusion behaviors and surface morphology on the SLB membrane were disclosed by the 3D SPT. By introducing CHES buffer (pH 10.0) to the channel containing SLB formed at pH 7.4, uneven environments were created on either side of the lipid membrane.30 After introducing particles to the solution, many transiently confined diffusions can be spotted visually from the conventional 2D imaging. Figure 4 shows a representative example in which several confined diffusion events were identified


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(Movies 4AB). In Figure 4B, the 2D trajectory, which is the top view of the 3D trajectory, shows that the particle was confined multiple times in small areas. The confinements have a typical size of ~100-200 nm. Four significant confined diffusion events were labeled (circled in red). Because of these confinements, its MSD curve deviates from a straightly line quickly from ~0.2 s (Figure 4C).

Figure 4. A representative trajectory of particle diffusion on lipid bilayer surface at pH 10.0. Four occasions of confined diffusion can be identified (labeled with arrows). (A) x, y, and z positions as a function of time. (B) Top view of the 3D trajectory. (C) MSD ~ t. (D) Expanded 3D view of the trajectory for the confined diffusion labeled 1 in (A) and (B). To have a better look of these confined diffusions, their x, y, z-profiles as a function of t were plotted in Figure 4A. During the confined diffusion periods, the particle’s x and y positions 15 ACS Paragon Plus Environment

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varied little: ~100-200 nm. The most interesting feature is the z-profile: whenever the particle was in the confinement, the particle will have a larger variation in the z-position. Most of the times, the particle can move ~150 nm away from the surface, which indicates that these lipid structures are three-dimensional in shape. Figure 4D shows the expanded 3D view of the trajectory for one of the confinements labeled as 1 in Figures 4A and 4B. The 3D trajectory shows a hemispherical shape, suggesting that these heterogeneous structures are bulges protruding from the planar lipid layer. When the particle diffused on to these bulges, it was trapped there for a short period of time, leaving a trace of confined diffusion in the area. The particle diffused on the top portion of the bulge, showing a different z-position than on the planar region. The overly extended period of time for the entrapment possibly suggests that the diffusion from the curved lipid surface to the flat region needs to overcome an activation energy barrier.


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Figure 5. Another representative trajectory showing the 3D lipid structures at pH 10.0. The particle visited the same lipid structure for 3 times in this trajectory. (A) x, y, and z positions as a function of time. (B) Top view of the 3D trajectory. (C) MSD ~ t. Figure 5 displays another representative trajectory (Movies 5AB), which shows the existence of multiple trapping events on SLB surface. Again, the 3D trajectory discloses that these lipid structures providing the entrapments were 3D in nature (Figure 5A). The most interesting feature of this trajectory is that the particle revisited the same lipid structure 3 times after diffusing away from it. In Figure 5A, 3 trapped diffusion events are labeled with arrows. Their x and y positions show that this is the same lipid structure on the surface (Figure 5B, circled in green). This example discloses that these lipid structures we observed were immobilized, stable and may exist for long time (minutes to hours).

Diffusion in the presence of multiple heterogeneous structures on lipid surface. Above examples show that at pH 10.0, the lipid membrane becomes more heterogeneous as disclosed by 3D SPT: there are multiple 3D structures that confine the diffusion of the polystyrene particles. The more heterogeneous particle diffusion trajectories could reflect that (1) the lipid surface becomes more rugged as compared to that at pH 7.4, or (2) the lipid surface is the same but the sampling of the lipid surface is biased by the change of particle charges at different pHs. To exclude the second possibility, we measured the zeta potentials of the particles at both pHs. The reported values (6 measurements) are 48.9 ± 3.4 mV for pH 7.4, 48.8 ± 1.9 mV for pH 10.0, respectively. The zeta potentials are practically identical at these two pHs because the charged groups on the particles are carboxylic acids, which have a pKa in the range of 4~5, well below pH 7.4 or pH 10.0. This result shows that there is significant difference between the lipid surface


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morphology at pH 7.4 and 10.0, and the lipid surface is indeed more rugged at pH 10.0. This conclusion is also consistent with earlier literature reports where AFM was used.30 These 3D heterogeneous structures may be identified as lipid “domains” using conventional 2D single particle tracking. However, there is no clear evidence from this study to support phase separation in these lipid structures although they look like lipid “domains” in many aspects. To follow the conventional definition of lipid domains, we name these special areas as “lipid heterogenous structures” or simply “lipid structures”. Whether these 3D lipid structures are lipid domains is currently being studied. To investigate these 3D lipid structures and their effect on the particle diffusion, we collected the trajectories from 25 particles at pH 10.0. One hundred events of confined diffusion were studied, with some of them on the same heterogenous structures multiple times. For all of the collected trajectories, the particles spent 41% of the total time in these lipid structures. Figure 6A shows the histogram of the particles’ dwelling times in these heterogeneous structures. Most of the particles stayed within the structures below 1 s, with a median dwelling time of 0.75 s. Figure 6B shows the size of the heterogeneous structures, which is defined as the distance between the planar lipids to the top of the bulge, judging from the 3D trajectory. This distance is generally consistent with the lateral size of these lipid heterogeneous structures. The median size of these structures was 140 nm.


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Figure 6. Lipid heterogeneous structures and their effects on particle diffusion. (A) Dwelling times of particles diffusing inside lipid structures at pH 10.0. A total 100 confined diffusion events were analyzed. (B) Size distribution of the lipid heterogeneous structures. (C) Apparent diffusion coefficient of particles on lipid bilayer at pH 7.4. (D) At pH 10.0. (E) Schematic of the potential energy surface for the particle to diffuse between the 3D lipid heterogeneous structures and planar SLBs. Because of the multiple trapping events in these heterogeneous structures, the apparent surface diffusion coefficient for the particles slowed down significantly. At pH 7.4, the apparent diffusion coefficient was 0.38 ± 0.05 µm2/s from ~20 particles (Figure 6C). The diffusion


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coefficient D was calculated from the beginning linear portion (0.6 s) of the MSD curve. As a comparison, the MSD curve usually deviates from a straight line for particles on SLB surface at pH 10.0. Nevertheless, the apparent D can be obtained from the forced fitting of the beginning region of the MSD curve (~ 0.2 s). The analysis of ~25 particles gave a D of 0.23 ± 0.13 µm2/s (Figure 6D), significantly smaller than that on SLB surface at pH 7.4. However, if we only consider the particle trajectories outside the lipid 3D structures for the same particles, the D was estimated to be 0.44 ± 0.14 µm2/s, similar to that at pH 7.4. This indicates that the slowing down of the particle diffusion at pH 10.0 is mainly caused by the entrapment of these heterogeneous structures. The mobility of the particles inside the heterogeneous structures, however, was not ready to be disclosed due to the limited time resolution. The linear diffusion distance within the frame time (31 ms) was ~160 nm assuming the diffusion coefficient is 0.44 µm2/s, larger than the average dimension of lipid heterogeneous structures in this study. However, the entrapment of the particle within the structures indicates that there is an energy barrier for the particle to move out of these heterogeneous structures. It is conjectured that these heterogeneous structures have a bulge-like shape, which will show a concave curvature at the neck between the bulge portion and the planar portion of the lipid membrane. Due to the large size of the particle, the attached nanoparticle cannot move freely from the bulge region to the flat region due to steric hindrance. In order for the particle to cross the boundary, the bulge must deform so that the particle can move over. Thus, there is an energy barrier associated with this movement. The activation energy for the particle moving out of these lipid heterogeneous structures can be estimated from the dwelling time of the particle in the lipid structures. The de-retention rate constant k is the inverse of the dwelling time (a median of 0.75 s for 100 events). The rate


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constant k for the particle moving out of the confinement can also be formulated accordingly to the simple collision theory:

k = ν e − Ea / kBT

(2)

where v is the frequency that the particle encounters the boundary of the confinement; Ea is activation energy for the particle to go over the barrier; kB is the Boltzmann constant; T is the temperature. The collision frequency v is the inverse of the average time between two encounters of the particle with the boundary of the lipid structure. It can be estimated from the average linear distance between two collisions and the diffusion coefficient of the particle. Taking the lipid structure dimension of 140 nm, and the diffusion coefficient 0.44 µm2/s, the average collision time between the particle and the confinement boundary is estimated to be 11 ms, or a frequency of 90 s-1. Putting these number into Equation 2, we obtain Ea to be 4.2 kBT. This value is slightly larger but on the same order of magnitude of the thermal activity of the particle. It explains why the particles tend to be trapped in the lipid heterogeneous structures with a short period of time.

The origin of the 3D lipid heterogeneous structures. We have shown that at neutral pHs, the lipid surface is much smoother, with occasional large bulges (500 nm ~1 µm), possibly because of the defective structures when the lipid vesicles collapse and form the continuous planar bilipid membrane. The occurrence of these large confinements was rare, with a total time fraction < 1% for ~20 trajectories. However, when the pH of the solution on the top side of the lipid membrane was changed to basic condition at pH 10.0, many small 3D lipid structures were observed, with a size of ~100-200 nm. The total time fraction for the particles diffusing on these 3D heterogeneous structures was 41% for ~25 trajectories.


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Why these 3D structures form at basic conditions while not at neutral pHs? A possible reason is the non-uniform distribution of different lipid components when they form the bilipid membrane.58 The lipids we used in this experiment is a mixture of DOPE : DOPS : DOPC = 5 : 3 : 2, which has been widely used to mimic platelet membranes for coagulation studies. DOPC has a choline group in the head region, which is a quaternary ammonium cation. The protonated phosphate group in DOPC has a pKa of ~1.0.39 The molecule is neutral in a broad pH range from 2~12. DOPE (containing an ethanolamine group) has two ionizable groups: pKa 1.7 for the protonated phosphate group and pKa for the ammonium ion varied from 9.8 to 11.25.39 The pKa’s for DOPS (containing a serine group) are reported to be 2.6, 5.5, and 11.55 for the protonated phosphate, carboxylate, and amine groups, respectively.39 At neutral pHs, DOPC and DOPE are zwitterions while DOPS is negatively charged. When they were mixed to form the lipid bilayer at pH 7.4, the negatively charged lipids were uniformly distributed to minimize the repulsion due to high fluidity of the lipid molecules in the membrane. However, when the pH was tuned to 10.0, a part of DOPE became negatively charged. Due to the reduced fluidity of SLB on glass surface, areas having more DOPE will be crowded with negative charges, leading to the deformation of the lipid membrane and the creation of a bulge-likes structure due to increased repulsion. There are two reasons for the formation of bulge-like structures protruding toward the solution side:30 (1). The charges were uneven on outer and inner leaflets due to different pH values. (2) Lipid molecules change shape from a cylinder to a truncated cone when it becomes charged from 7.4 to 10.0. The packing of lipid molecules with asymmetric shapes will lead to the formation of curved, bulge-like structures. Such special structures may be further stabilized by the interaction between the lipids


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and the glass surface, leading to long lived, immobilized lipid heterogeneous structures as observed in this study.

Conclusion This study shows that the 3D SPT can disclose many details about SLB surface morphology and particle surface diffusion, which were not disclosed by conventional 2D SPT in the past. At neutral pHs, the lipid membrane has a uniform planar structure. However, when the pH was adjusted to be basic, many of the particles attached on lipid membrane showed transiently confined diffusions with in an area ~100-200 nm. The particles are trapped for short periods of times (~0.75 s), with an escape activation energy of ~4.2 kBT. 3D SPT discloses that these confinements are from 3D bulge-like lipid structures, which contribute to the lateral heterogeneity on lipid membrane. Non-uniform distribution of pH-sensitive lipids in the membrane was proposed to explain the formation of these 3D heterogeneous structures. This 3D shape of these special lipid heterogeneous structures may suggest that not only hydrophobicity of phase-separated lipids, but also the geometry can play an important role in retaining certain species in special locations. This work sheds new light on understanding lipid membrane lateral heterogeneity and particle-lipid surface interactions.

Experiments Chemicals and sample preparation. 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE), 1,2-dioleoyl-sn-glycero-3-phospho-L-serine (sodium salt) (DOPS), 1,2-dioleoyl-sn-glycero-3phosphocholine (DOPC) with a pre-mixed ratio of 5:3:2 (Coag. Reagent I, 790304) were purchased directly from Avanti Polar Lipids (Alabaster, AL). The supported lipid bilayers were


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prepared by self-assembly of small unilamellar vesicles (SUVs), which were obtained by vesicle extrusion.59, 60 In brief, the pre-mixed lipid blends were swelled in PBS buffer for 30 min and suspended by vortex. Then, the lipid solution was diluted to a final concentration of 1.0 mg/mL. The PBS buffer contains 137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4 and 1.8 mM KH2PO4 and was tuned to pH 7.4 by adding small amount of 1.0 M HCl. The lipid solution was extruded 15 times through a polycarbonate membrane (220 nm pore size) using a syringe. The SUVs solution was stored at 4 oC and used in one week. The supported lipid bilayers were prepared inside a 3 mm wide, 100 µm thick flow channel made of a glass slide, a coverglass and Scotch tape (~ 100 µm thickness) as spacers. The coverglass was soaked in 10.0 M NaOH solution for 20 min and then in ethanol/water mixture (50%/50%) for 20 min. The coverglass was then cleaned twice by ethanol and 3 times by DI water and dried with N2 gas flow. The flow channel was washed using PBS buffer twice and then injected with 30 µL SUVs solution and incubated for 30 min at 40 oC. The extra SUVs in the flow channel was washed away by PBS buffer for 3 times. The 100 nm diameter nanoparticles were carboxylated polystyrene nanoparticles doped with fluorescent dyes from Thermo Scientific (R100TS). The zeta potential of the particles was measured (Zetasizer, Malvern Pananalytical) in 25 mM phosphate buffer adjusted to pH 7.4 and 10.0, respectively. The reported values (from 6 measurements) were 48.9 ± 3.4 mV for pH 7.4, 48.8 ± 1.9 mV for pH 10.0, respectively. The 100 nm particles in aqueous suspensions were packaged as 1% solids and diluted 100,000-fold in PBS buffer. The single particle tracking experiment was performed by injecting 10 µL nanoparticle solution into the prepared flow channel containing SLBs to incubate for


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another 10 min at room temperature. The observation started after particles attach onto the surface and started surface diffusion. For observation of SLB exposed to basic environment at pH 10.0, we first prepared the lipid bilayer at pH 7.4 with the same method mentioned above. The channel was then washed 3 times with PBS buffer and 4 times with 25 mM pH 10.0 CHES buffer. The 25 mM CHES buffer was added with 120 mM NaCl and 1.0 mM KCl (final concentration) to generate a similar ionic strength as that of the PBS buffer. The particles diluted in the buffer was then introduced to the channel for observation.

Epi-fluorescence microscopy and CCD camera. An upright Nikon Eclipse 80i microscope was applied to complete the 3D single particle tracking experiments. To produce astigmatism and observe different image patterns at different z-positions, we inserted a weak cylindrical lens (f = 1.0 m) between the microscope objective and the tube lens (~7.5 cm from the tube lens). The signal was collected by a 100× Apo TIRF/1.49 oil immersion objective. A P-725 PIFOC longtravel objective scanner from Physik Instrument (model no. P725.2CD) was used to control the axial distance from the sample to the objective. An Andor iXon 897 camera (512 × 512 imaging arrays, 160 µm pixel size) was used to collect the images and videos. All the videos were collected with 30 ms integration time (frame time ~31 ms). MATLAB and NIH ImageJ were used to analyze and process the collected images and videos. In the observation, the microscope objective was on the glass substrate (coverglass) side. Since this was an upright microscope, the lipids and the solution were beneath the glass substrate. All the figures were prepared with the same configuration: the glass substrate is on the top side


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(+ z-values) and the solution is on the bottom side (- z-values). The x, y, and z values were shifted or centered for clearer presentations.

ACKNOWLEDGMENTS This work was supported by the Chemistry Department, North Carolina State University.

Supporting Information Available: 16 movies.


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TOC Graphic


Three-Dimensional Heterogeneous Structure Formation on a

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