Single Particle Tracking of Peptides-Modified Nanocargo on Lipid

Nov 25, 2016 - Understanding the detailed diffusion behavior of the nanocargo on lipid membrane can afford deep insight into the surface chemistry con...
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Single Particle Tracking of Peptides-Modified Nanocargo on Lipid Membrane Reveals Bulk-Mediated Diffusion Lin Wei, Zhongju Ye, Yueling Xu, Bo Chen, Edward S. Yeung, and Lehui Xiao Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.6b03420 • Publication Date (Web): 25 Nov 2016 Downloaded from http://pubs.acs.org on November 29, 2016

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Analytical Chemistry

Single Particle Tracking of Peptides-Modified Nanocargo on Lipid Membrane Reveals Bulk-Mediated Diffusion Lin Wei,† Zhongju Ye,† Yueling Xu,‡ Bo Chen,† Edward S Yeung§ and Lehui Xiao*,†,‡ †

Key Laboratory of Chemical Biology & Traditional Chinese Medicine Research, Ministry of Education, Key Laboratory of Phytochemical R&D of Hunan Province, College of Chemistry and Chemical Engineering, Hunan Normal University, Changsha, Hunan, 410081, China. ‡ College of Chemistry, Nankai University, Tianjin, 300071, China. § Department of Chemistry, Iowa State University, Iowa, 50011, USA. *Corresponding author. Email: [email protected], Fax: +86-022-23500201. observations, the knowledge of the diffusion mechanism for drug delivery nanocargo on lipid membrane is still limited because earlier studies were primarily designed to explore the receptormediated interaction by using plasmonic nanoparticles as the probe. However, in the context of drug and gene delivery system, numerous studies have reported that non-viral nanocargos usually suffer from relatively low levels of translocation efficiency because of the obstacles formed by the cell or nuclear membrane.14,15 Comprehensive surface chemistry was then explored for the improvement of translocation efficiency.1-3,19 A convenient yet robust example is cell-penetrating peptide (CPP), which significantly improves the membrane translocation efficiency not only for drug delivery but also for gene transfection.20 On this account, elucidation of the diffusion behavior of CPPfunctionalized nanocargo on lipid membranes is fundamentally important for the understanding of the translocation mechanism and subsequently would afford new insight into the development of novel drug delivery nanocargo. In this work, we explored the diffusion behavior of TAT peptide (a well-known CPP derived from human immunodeficiency virus with excellent cellular translocation efficiency which could deliver diverse types of nanocargos into the living cell) functionalized 60 nm GNPs on an artificial lipid membrane.7,20 According to the single particle tracking results, when the surface of GNPs was modified with TAT peptides and PEG molecules, the nanoparticles could be temporarily confined for random waiting times between surface displacements produced by excursions through the bulk fluid, Figure 1a, which was not reported before under similar system and was noticeably distinct from the confined twodimensional random walk and Gaussian statistics that are commonly assumed for individual small molecule (i.e. organic dyes) surface diffusion.21,22 The single particle tracking experiments were performed on an upright dark-field microscope.7 The exposure time was set to 10 ms. The imaging area is 100 x100 µm2. The lipid bilayer was formed by self-assembling of 100 nm (in diameter) POPC SUV lipid vesicles in PBS buffer inside a home-built micro-channel with a width around 0.5 mm.23 The integrity of the membrane was characterized by labeling the membrane with 0.001% of TexasRed-labeled DHPE lipids. Under fluorescent mode, an even fluorescence lipid layer was observed within the channel after incubation of 3-4 h, indicative of a uniform two-dimensional lipid layer.

ABSTRACT: Understanding the detailed diffusion behavior of the nanocargo on lipid membrane can afford deep insight into the surface chemistry controlled translocation mechanism for the rational design of efficient delivery system. By tracking the diffusion trajectory of transacting activator of transcription (TAT, a cell penetrating peptide) peptides-modified nanocargo on lipid membrane, bulk-mediated (intermittent hopping) diffusion was observed for the first time after a blended modification of TAT peptides and PEG molecules onto the nanoparticle surface. In contrast to random walk or confined diffusion, the nanoparticles could be temporarily confined for random waiting times between surface displacements produced by excursions through the bulk fluid, which was not noted before. Non-Gaussian distributed step length (with a stretched power law like tail) was observed, making large displacements much more probable than one would predict for regular Gaussian decay. This kind of larger displacements would therefore significantly facilitate kinetically controlled surface searching process like heterogeneous penetration site recognition on fluidic membrane with suitable spatial orientation.

Recently, great efforts have been paid to design novel nanocargos for drug and gene delivery in living cells owing to the low toxicity and immunogenicity, lack of pathogenicity, and ease of pharmacologic production.1,2 Knowledge of the cellular uptake process of these newly designed nanocargos is essentially built according to the ensemble spectroscopic measurements (e.g. flow cytometry) or static cell imaging results (e.g. transmission electronic microscopy).3-6 Less is known about the detailed mechanism of the intermediate step (i.e. the diffusion dynamics of nanocargo on lipid membrane before the endocytosis process) because, until recently, there are lacking of efficient experimental methods and nanoprobes for tempo-spatially resolved single particle imaging and tracking.7-12 The rapid progress on the fabrication of nanometer-sized materials, particularly noble metal nanoparticles (e.g. gold nanoparticles, GNPs), has produced a new class of probes for biological imaging as well as drug and gene delivery.13-16 Previous studies have successfully adopted GNPs as the probe to explore the diffusion behavior inside the cell with either interference detection or direct scattering observation.8,12,17,18 Despite those interesting

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White light (halogen lamp) was adopted to illuminate the plasmonic nanoparticles on the lipid membrane under dark-field mode. Bright green scattering light was readily observed from individual GNPs, agreeing well with the localized plasmon resonance wavelength of individual probes, Figure S1, which is also corroborated with the single particle spectroscopic measurement. In order to further ascertain the observed nanoparticles are monomers rather than aggregated clusters, we randomly captured dark-field images and statistically analyzed the scattering intensity of these particles at single particle level. As shown in Figure S1, the single particle intensity distribution from PEG and PEG/TAT-functionalized GNPs exhibited a typical normal distribution with peak intensity comparable to that of freshly prepared GNPs without modification, confirming the mono-dispersiveness of the sample.

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mixed modified GNPs along the x direction as a function of time were shown in Figure S2. For the first type of motion, the surface of the particles was basically modified with PEG molecules (noted as PEG-GNPs), which is commonly applied to shield the nonspecific interaction with biomolecules for biological orientated applications. The good mobility as well as short residence time on the lipid membrane confirms weak association force with the lipid membrane, consistent with the observation reported before.23 In addition, according to their diffusion trajectories, the type of motion is qualitatively consistent with the behavior expected for normal Brownian motion in two dimensions. Once the surface was conjugated with TAT peptides, the mobility of the particles changed notably. The mobility varied when the density of the TAT peptide on the nanoparticle surface was changed gradually, i.e, 0.01±0.01, 0.1±0.03, and 0.17±0.02 per nm2. In the following discussions, these samples were noted as TAT-GNPs-1, -2 and -3 respectively. In order to give a quantitative description of the motion of peptide-modified nanocargo on the lipid membrane, we statistically calculated the mean squared displacement based on the function of  ∆   |   | , where  is the coordinate position of the nanoparticle on the membrane,  is the lag time, and the brackets indicate an ensemble average over all trajectories.10 For PEG-modified particles, the MSD increases linearly with lag time  as expected for Fickian diffusion despite the reduced diffusion coefficient in contrast to that in bulk solution, Figure 2a.23 When TAT was introduced to the surface of GNPs, the movability decreased gradually as revealed in the slope of the curve. Distinct from the case of PEG-modified GNPs, the slope of the curve slightly declined as the lag time increased, reminiscent of a power law relation  Δ  4  (with α=1.1, o.73, o.64 and 0.48 for PEG-GNPs, TAT-GNPs-1, -2 and -3 respectively).10 This kind of relationship is typically noted in the case of subdiffusion on two-dimensional membrane, where obstacles or strong association exists.

Figure 1. a) Schematic diagram of TAT-modified GNPs diffusion on lipid membrane. Periods of slowed diffusion on the membrane associated with occasional jumps from the interface were noted when the surface of GNPs was modified with TAT peptides and PEG molecules. b) Distinctive surface chemistry dependent inter-face diffusions were noted from the two dimensional single particle trajectories, i.e. slowed random diffusion, intermittent hopping diffusion and confined diffusion, as shown in the low-right panel.

Exploring the diffusion dynamics of nanoparticles on twodimensional fluidic surface has broad implications in diverse chemical and biological processes, such as the rational design of nanovectors for highly efficient drug delivery, surface-based biosensing on solid substrate, the ligand recognition mechanism for the corresponding receptors and so on.10,11,17,24,25 The movability as well as interactions of the nanoparticle with the surface have strong impact on the reaction mechanism in nanoscale systems. For example, during the cellular uptake process, the diffusion kinetics of the nanocargo on cell membrane controls the location where to go and therefore regulates the uptake efficiency as well as the transmembrane mechanism.7,12,26-29 Figure 1b shows representative trajectories of functionalized GNPs on the lipid membrane under a phosphate buffer solution with pH of 8.2. Surface chemistry dependent heterogeneity was observed among the particles with different modifications. Generally, for PEG-modified GNPs, they typically displayed high mobility and were associated with short residence time (with apparent sticking time but generally less than 0.5 s) on the lipid membrane. If a blended modification (TAT peptide and PEG together) was adopted, reduced diffusion with evident intermittent residence time during the diffusion process was readily observed. Even effective confinement event (with an area of moving approximately less than 0.3 µm2 within the time scale of 5 s) could be noted once the density of peptide reached 0.17±0.02 per nm2. For a more direct expression, representative trajectories from the

Figure 2. a) Double-logarithmic plots of MSD versus lag time from individual PEG- and TAT-GNPs. From b) to e) are 2D diffusion coefficient distributions of GNPs with different modifications with mean value of 3.7±2.38, 0.15±0.04, 0.08±0.02 and 0.04±0.02µm2/s for PEG-GNPs, TAT-GNPs-1, -2 and -3 respectively.

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To give a more detailed picture on the surface chemistrydependent movability, we statistically compared the diffusion coefficient of particles with different modifications. For the simplicity of calculation, we fitted the MSD curve of the first five points (with a maximum lag time of 0.05 s) in a linear trend and then determined the diffusion coefficient by   Δ  /4. The diffusion coefficient determined in this way reflects the motion of the particle at the most of the time and weighted out the occasional transitions (large jumps) during the whole track. It could also reflect the movability of the particles even under confined areas. As shown in Figure 2b-2e, when the density of the peptide increased, the diffusion coefficient of the nanoparticle on the lipid membrane decreased accordingly and followed with narrower distribution in the diffusion coefficient. In contrast to the PEG-modified nanoparticles, around two orders of magnitude decrease was noted for TAT-GNPs-3. The significantly reduced diffusion coefficient could be largely ascribed to the enhanced association force (e.g. hydrogen bond) because more peptides are available at the contact point. These observations are in good agreement with our previous observations where frozen translation diffusion of TAT peptides-modified nanocargo on the lipid surface could be achieved when the peptide density reached to 0.35±0.06 per nm2. Multi-association forces at the contact point account for the significantly reduced translational diffusion as revealed according to the binding energy estimation.23 To gain deep insight into the details of the diffusion process after the mixed modification, we further explored the ensemble-averaged step-size distribution which is quantified in terms of the self-part  of the van Hove correlation function,  ∆, ∆    30-33 ∑ This function represents        ∆   . the probability that a molecule has moved a distance ∆ along the x or y coordinate during time ∆ . For a simple Fickian diffusion, the distribution typically follows Gaussian decay.30-33

When the density of the peptide increased, narrower step size was noted, consistent with expectations where stronger association would take place when more peptides are available on the nanoparticle surface. Furthermore, all of these particles showed a similar kind of non-Gaussian distribution. This kind of nonGaussian distribution was previously observed in the case of interfacial diffusion (e.g. solid/liquid and air/liquid interface), when displacements occur via desorption, bulk diffusion, and subsequent re-adsorption at the interface. For example, pioneer works have demonstrated that small molecules (e.g., organic molecules, polymers, proteins) on a glass slide surface also exhibited similar kind of motion.31,34-37 However, this kind of motion was not revealed before for biomolecules-functionalized nanocargo on twodimensional fluidic membrane. Generally, there are two types of models have been proposed to describe the intermittent hopping diffusions at the interface, i.e. desorption mediated diffusion as described by the O’Shaughnessy model and the so-called continuous time random walk (CTRW) model.38,39 The first model gives certain assumptions, including an exponential distribution of desorption time t, which is typically shorter than the time over which diffusion is observed. Clearly, this picture is not satisfactory to depict the dynamics in this case from the consideration of the following two points. First, the duration of the jump is not fixed as indicated in the diffusion track, which is broadly distributed. Second, a fixed characteristic desorption time also reflects a stable desorption energy barrier which is hard to achieve for a tempo-spatially dependent heterogeneous nanoparticle surface due to the uneven peptide distribution at nanometer scale as well as the flexibility of the peptide. For the second model, which is applied to describe diffusion that switches between immobilization and mobility. Distinct from the discrete random walk, in the CTRW model, the walker spends random waiting time t immobilized between each instantaneous displacement. As a consequence, the intermittency of the trajectories can be characterized statistically by the distribution of waiting time, t, between surface displacements. Given the adsorption is due to trapping with a single binding energy  , the distribution of waiting time follows an exponential distribution,   ∼ exp /$, where, $ ∝ exp   /'(. On this basis, the distributions of dwelling time for these nanoparticles were determined.

Figure 3. Double-logarithmic plots of step size distribution of GNPs (normalized by the initial point) with different modifications, a) PEGGNPs, b) TAT-GNPs-1, c) TAT-GNPs-2, and d) TAT-GNPs-3. The red squares show the hypothetical Gaussian decay that would lead to the diffusion coefficients implied by the raw data in Figure 2a.

Figure 3 shows the double-logarithmic plots of correlation function of TAT-GNPs-1 with time duration of 0.1s (green circles). Interestingly, the curve decays more slowly than a Gaussian distribution. This is contrary to the case of PEG-GNPs, where the step size is much broader and exhibits a characteristic Gaussian shape, indicative of Fickian diffusion. It is worth noting that further increasing the time duration of each step, the distribution of the step still deviates from a Gaussian curve, Figure S3.

Figure 4. a) Double-logarithmic plots of dwelling time distribution of GNPs with different modifications, a) TAT-GNPs-1, b) TAT-GNPs2, and c) TAT-GNPs-3.

Figure 4 shows the double-logarithmic plot of the distributions of the dwelling time for TAT-GNPs-1, -2 and -3. Interestingly, all of these samples display a linear trend in the logarithmic plot,

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indicating a non-exponential distribution. In other words, a spectrum of binding energies accompanies with the continuous desorption-adsorption process, confirming a tempo-spatially dependent association process. This complex binding energy distribution along the diffusion trajectory therefore reflects a power law distribution for the dwelling time. The phenomenological power law follows the relation of )~  . It is worth noting that, increasing the peptide density, the exponent gradually increased from -3.1 to -1.8, demonstrating progressively increased association force. Similar intermittent hopping diffusion and searching strategies are also widely observed at various scales (i.e. macroand micro-scale).38 In the context of micro-scale, many interesting reaction kinetics are involved in this searching mechanism, for example the localization of a protein to a specific DNA sequence, active transport of vesicles inside the cell. However, the previous studies on this facilitated diffusion are basically based on ensemble measurements. The single particle (or molecule) tracking strategy noted above could therefore afford deep insight into the reaction mechanism based on the tempo-spatially resolved diffusion trajectories. In summary, with dark-field microscopy, the tempo-spatially dependent diffusion dynamics of TAT peptides-functionalized nanoparticles on lipid membrane were explored. Upon a close inspection of the diffusion trajectories, intermittent hopping diffusion was observed on the fluidic lipid membrane, which is primarily controlled by the peptide density on the nanoparticle surface. Distinct from the random walk or confined diffusion mode, the nanoparticles could be temporarily confined for random waiting time between surface displacements produced by excursions through the bulk fluid. Power-law dependent displacement was also observed from these particles, making large displacements much more probable than Gaussian decay. This kind of larger displacements could therefore significantly influence kinetically controlled surface process like heterogeneous penetration site recognition, which might finally regulate the corresponding cellular uptake efficiency.

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ASSOCIATED CONTENT AUTHOR INFORMATION Corresponding Author *E-mail: [email protected], Fax: +86-022-23500201

Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. L. W. and Z. Y. contributed equally to this work.

Notes The authors declare no competing financial interests.

ACKNOWLEDGMENT This work was supported by NSFC (21405045, 21522502), Program for New Century Excellent Talents in University (China, NCET-13-0789), and Hunan Natural Science Funds for Distinguished Young Scholar (14JJ1017).

Supporting Information The Supporting Information is available free of charge on the website. The chemicals and materials, experimental details of gold nanoparticles fabrication, modification and characterizations, methods for single particle tracking and data analysis, and supporting figures.

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