Mechanistic Understanding of the Interactions between Nano-Objects

Mechanistic Understanding of the Interactions between Nano-Objects with Different Surface Properties and α‑Synuclein Downloaded via MACQUARIE UNIV on February 27, 2019 at 14:39:16 (UTC). See https://pubs.acs.org/sharingguidelines for options on how to legitimately share published articles.

Hossein Mohammad-Beigi,† Atiyeh Hosseini,‡,§ Mohsen Adeli,⊥,¶ Mohammad Reza Ejtehadi,*,∥,# Gunna Christiansen,∇ Cagla Sahin,†,○ Zhaoxu Tu,¶ Mahdi Tavakol,◆ Arezou Dilmaghani-Marand,● Iraj Nabipour,◇ Farshad Farzadfar,● Daniel Erik Otzen,*,†,△ Morteza Mahmoudi,*,▲ and Mohammad Javad Hajipour*,●,◇ †

Interdisciplinary Nanoscience Centre (iNANO), Aarhus University, Gustav Wieds Vej 14, DK−8000 Aarhus C, Denmark

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Institute for Nanoscience and Nanotechnology (INST), Sharif University of Technology, Tehran 1458889694, Iran

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Center of Excellence in Complex Systems and Condensed Matter (CSCM), Sharif University of Technology, Tehran 1458889694, Iran

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Faculty of Science, Lorestan University, Khorramabad, Iran

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Department of Biology, Chemistry, Pharmacy, Institute of Chemistry and Biochemistry, Freie University Berlin, 14195 Berlin, Germany

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School of Nano Science, Institute for Research in Fundamental Sciences (IPM), P.O. Box 19395-5531, Tehran, Iran

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Department of Physics, Sharif University of Technology, P.O. Box 11155-9161, Tehran 1245, Iran

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Department of Biomedicine-Medical Microbiology and Immunology, Aarhus University, 8000 Aarhus C, Denmark

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Science for Life Laboratory, Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Solnavägen 9, 171 65 Stockholm, Sweden

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Department of Mechanical Engineering, Sharif University of Technology, Tehran 1245, Iran

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Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran 1411713137, Iran

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Persian Gulf Marine Biotechnology Research Center, The Persian Gulf Biomedical Sciences Research Institute, Bushehr University of Medical Sciences, Bushehr 75147, Iran

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Department of Molecular Biology and Genetics, Aarhus University, Gustav Wieds Vej 14, DK−8000 Aarhus C, Denmark

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Department of Anesthesiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115, United States S Supporting Information *

ABSTRACT: Aggregation of the natively unfolded protein α-synuclein (α-syn) is key to the development of Parkinson’s disease (PD). Some nanoparticles (NPs) can inhibit this process and in turn be used for treatment of PD. Using simulation strategies, we show here that α-syn self-assembly is electrostatically driven. Dimerization by head-tohead monomer contact is triggered by dipole−dipole interactions and subsequently stabilized by van der Waals interactions and hydrogen bonds. Therefore, we hypothesized that charged nano-objects could interfere with this process and thus prevent α-syn fibrillation. In our simulations, positively and negatively charged graphene sheets or superparamagnetic iron oxide NPs first interacted with α-syn’s N/ C terminally charged residues and then with hydrophobic residues in the non-amyloidβ component (61−95) region. In the experimental setup, we demonstrated that the charged nano-objects have the capacity not only to strongly inhibit α-syn fibrillation (both nucleation and elongation) but also to disaggregate the mature fibrils. Through the α-syn fibrillation process, the charged nano-objects induced the formation of offpathway oligomers.

KEYWORDS: α-synuclein, Parkinson’s disease, fibrillation, graphene, superparamagnetic iron oxide nanoparticles, electrostatic interaction elf-assembly of α-synuclein (α-syn) into oligomers and fibrils is believed to be the main cause of Parkinson’s disease (PD).1−5 α-Syn fibrillation is a nucleationdependent growth process that follows sigmoidal kinetics

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© XXXX American Chemical Society

Received: November 26, 2018 Accepted: February 19, 2019

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DOI: 10.1021/acsnano.8b08983 ACS Nano XXXX, XXX, XXX−XXX

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Figure 1. (a) Interaction energies and (b) correlation for head-to-head interaction of three α-syn monomers. (c) Number of hydrogen bonds formed through self-assembly of α-syn monomers. (d) The successive but opposite charged residues induce high local dipole moments and electrostatic interactions in initial time of α-syn fibrillation process. (e) Distribution of negatively charged Asp and Glu and positively charged Lys in α-syn protein.

or destabilize the pre-exist fibrils could be as promising as a drug candidate against PD. As α-syn fibrillation is a complicated process depending on multibiological events/molecules and conditions and leads to formation of structurally different selfassembly states, the current strategies to reduce cytotoxicity associated with α-syn are challenging.12−16 The complex nature of α-syn species limits the application of therapeutics to destabilize the pre-exist α-syn oligomer/fibril.17−19 The

which leads to conversion of monomeric α-syn to toxic oligomeric and fibrillar species. These oligomers and fibrils have a capacity to trigger neuronal impairment via disrupting function of mitochondria, degradation machinery, and membrane.6−9 Therapeutic approaches currently used for prevention and treatment of amyloid-related diseases are focused on clearance and/or prevention of amyloid oligomers/fibrils.10,11 Therefore, the therapeutics that delay/prevent α-syn fibrillation B


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Figure 2. Interaction energies for binding of α-syn to (a) graphene(+), (b) SPION(+), (c) graphene(0), (d) graphene(−), (e) SPION(−), and (f) SPION(0). Initial and final interactions of α-syn with (g) graphene(+), (h) SPION(+), (i) graphene(−), (j) SPION(−), (k) graphene(0), and (l) SPION(0).

amyloidogenic proteins.33−39 Although there are a few reports on the NPs effects on α-syn fibrillation kinetics, the majority of previous studies, to the best of our knowledge, have shown that NPs (i.e., gold and surface modified albumin NPs) accelerate αsyn fibrillation.33,34 In contrast, a few others (e.g., graphene quantum dots) can inhibit α-syn fibrillation, disaggregate existing fibrils, and protect neurons from neuropathological αsyn aggregates.40 The mechanistic understanding of the effects of physicochemical properties of NPs on the fibrillation kinetics is required not only to target the desired state of α-syn (e.g., monomer,

therapeutic approaches such as stabilizing protein folding, immunotherapy to clear α-syn, and blocking α-syn binding to neuron membrane have not showed clinical success.20−22 Moreover, many available compounds/materials that demonstrated meaningful interactions with α-syn23−31 failed clinically, and the treatment of PD remained elusive.32 A promising investigational approach involves the use of nanoparticles (NPs) to prevent unwanted fibrillation.33,34 Depending on their physicochemical properties (e.g., size, charge, surface chemistry) and concentration, NPs show different inhibitory or acceleratory effects on fibrillation of C


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Figure 3. Correlation between electrostatic and vdW forces for interaction of α-syn with (a) graphene(+), (b) graphene(−), (c) SPION(+), and (d) SPION(−). Number of formed hydrogen bonds through interaction of α-syn monomers with (e) graphene(+), (f) graphene(−), (g) SPION(+), and (h) SPION(−).

oligomer and fibril) but also to perturb precise microscopic events (e.g., primary nucleation, elongation and secondary nucleation) involved in the fibrillation process. Here, we combined both simulation and experimental approaches to understand how graphene sheets and superparamagnetic iron oxide nanoparticles (SPIONs) with different properties (e.g., size, charge, functional group and coating) affect α-syn fibrillation.

oligomers/fibrils initially starts as a result of electrostatic interactions (the electrostatic energy at beginning is about −17 kBT, while van der Waals (vdW) is about −1 kBT) (Figure 1a, b). Moreover, intra/inter hydrogen bonds between residues keep α-syn monomers in contact with each other (Figure 1c). Most visibly, electrostatic contacts between oppositely charged residues such as Lys12(+)Glu13(−)/ Glu20(−)Lys21(+)/ Lys34(+)Glu35(−)/ Lys45(+)Glu46(−)/ Glu57(−)Lys58(+)/ Lys60(+)Glu61(−)/ Lys96(+)Lys97(+)Asp98(−) induce initial interaction and subsequent fibrillation of α-syn monomers (Figure 1d). Indeed, these successive but oppositely charged residues induce high local dipole moments along the chains, which have a major role in long-range electrostatic interactions. Through interaction of three α-syn monomers, first, the Nterminal residues mediate the head-to-head electrostatic interaction, and then the hydrophobic residues located in the

RESULTS AND DISCUSSION Molecular Dynamic Simulation. The highly hydrophobic non-amyloid-β component (NAC) region (residues 61−95) drives α-syn fibrillation and is integrated into the fibril structure.41 However, our simulation results revealed that the primary force in trimmer self-assembly of α-syn for formation of D


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Thanks to their higher number, the negatively charged residues have the higher capacity to interact with the positively charged nano-objects via electrostatic interaction, compared to the positive residues. In other words, the positively charged nanoobjects are expected to adsorb/capture a large number of α-syn monomers, making them promising candidates to prevent or delay the fibrillation process. The discrepancy between the shape of the SPIONs and graphene (sphere vs sheet) is another important factor affecting their interactions with α-syn. In this case, the planar graphene structure provides more surface to the α-syn monomers compared to the SPIONs, which facilitates hydrophobic interactions of the monomers with graphene surface over time. However, the highly curved surface of the SPIONs enables α-syn to be attached to the surface through the preferred charged residues (e.g., negatively charged residues for attachment to the positively charged site of the SPIONs). This phenomena is more visible in the Figure 2h, where the SPION(+) makes strong electrostatic interactions with negatively charged residues of α-syn such as Glu and Asp over time. For graphene(+), initial electrostatic interactions have a capacity to reduce the distance between α-syn and the graphene(+) surface which in turn empower the hydrophobic forces. Unlike the charged nano-objects, the neutral-charged ones (graphene(0) and SPION(0)), did not directly interact with the charged amino acids located at the C- and N-termini of α-syn. The neutral NPs demonstrated the lowest affinity, compared to the charged nano-objects, to α-syn and mainly attached to the central region of α-syn through vdW interactions (Figure 2c, f, k, l and Figures S5 and S8). As hydrogen bonding holds α-syn monomers together in the initial stages of association (Figure 1c), the hydrogen bonds formed through interaction of α-syn with SPION/graphene were also calculated. A large number of hydrogen bonds formed through interaction of charged nano-objects with α-syn. As shown in Figure 3a−h, the same trend was observed regarding the role of vdW interactions and the number of hydrogen bonds. Graphene provides more surface to α-syn, compared to the SPIONs, which in turn leads to existence of higher hydrogen bonds (Figure 3e−h). In particular, due to their functional group (NH2), the positively charged nano-objects had a larger number of hydrogen bonds with α-syn compared to negative ones. The greatest number of hydrogen bonds were formed through α-syngraphene(+) interaction having the advantages of both flat surface and the amine functional groups. In contrast, SPION(−) had the less tendency to make hydrogen bonds (Figure 3e−h). It is noteworthy that the figures represent the initial states of docking by considering the functional groups. Due to the orientation of side chain of the residues interacting with the functional groups, even after relaxation steps, no hydrogen bonds were formed on SPION(−) in the initial stages. Mechanistic Understanding the Interactions between Nano-Objects with Different Surface Properties and αSyn. To validate our simulation results, we measured in vitro how these NPs affect α-syn fibrillation. In the absence of nanoobjects, there are three stages of protein fibrillation: a lag phase of several hours, followed by a steep elongation phase until a plateau is reached (Figure 4a). Accordingly, the fibrillation kinetics of the control case (α-syn in the absence of nanoobjects) was fit by a sigmoidal curve characteristic for typical amyloidogenic proteins. Transmission electron microscopy (TEM) images of control samples also confirmed the formation of long and mature fibrils (Figure 4a). α-Syn fibrillation kinetics

NAC region stabilize this interaction (Figure 1a, b, d). The electrostatic forces also support vdW interactions between hydrophobic residues. According to the Debye−Hü ckel approximation to Poisson−Boltzmann equation (PBE), the screening effect in electrostatic interactions for dipoles is weaker compared to monopoles.42 Our finding robustly confirms the crucial role of charged residues in triggering α-syn trimmer selfassembly. Thus, we hypothesized that the charged nano-objects, regardless of their composition, have the capacity to bind to and block α-syn charged residues and therefore prevent the fibrillation process. In this context, we note that α-syn has a highly acidic C-terminal tail as well as a highly charged Nterminal region (Figure 1e). To test this hypothesis, the interaction of α-syn with graphene polyglycerol (graphene(0)), graphene polyglycerol sulfate (graphene(−)), graphene polyglycerol amine (graphene(+)), SPIONs (SPION (0)), SPIONs-COOH (SPION(−)), and SPIONs-NH2 (SPION(+)) were simulated with OPLS-AA force field, as well as a particle-mesh Ewald (PME) summation with a 1.4 nm cutoff, and 0.12 nm fast-Fourier grid spacing (Figures S1 and S3−S8). To improve the accuracy and reproducibility of our gathered statistics, each system with the same initial conditions was replicated five times (35 runs with 40 ns production run). Most contributing residues in the interaction of α-syn and graphene/SPIONs were identified based on calculating the root-mean-square fluctuations (RMSF) (Figure S2, further information is provided in the Supporting Information). The most striking observation is that different types of amino acids are involved through interaction of α-syn with any of the charged nano-object (Figure 2a-l and Figures S3−S8). RMSF calculation showed that NAC, N- and C-terminal regions of αsyn interacted with nano-objects have minimum flexibility over the course of time. In addition, Cα RMSFs decreased through this interaction. Initially, the charged and then hydrophobic residues dominate in binding α-syn to the charged nano-objects (Figure 2g-l). For instance, graphene(+) initially binds α-syn monomers through electrostatic forces between their amine functional groups and negatively charged amino acids of α-syn and then interact with hydrophobic residues (0−10 ns, the difference between electrostatic and vdW energies is about −1.5 kBT) (Figure 2a, g). In the case of graphene(+), it is noteworthy that the correlation chart of electrostatic vs vdW strongly confirms the critical role of electrostatic forces in interactions between α-syn and NPs (Figure 3a). Glu and Asp residues located at the N- and C-termini trigger the binding of α-syn to graphene(+) and/or SPION(+). Hydrophobic residues (e.g., Val and Ala) support these interactions (Figure 2a, b, g, h and Figures S3 and S6). The correlation between vdW-electrostatic energy shows that, after 20 ns, the vdW is the driving force for graphene(+)-α-syn binding (Figures 2a and 3a and Figure S3), while for SPION(+)-α-syn interaction, the role of electrostatic force is dominant (Figures 2b and 3c and Figure S6). In the case of graphene(−) and/or SPION(−), the positively charged Lys mainly positioned at the N-terminus of α-syn starts the initial attachment to these nano-objects, followed by binding of hydrophobic residues (e.g., Val, Tyr, and Ala) (Figures 2d, e, i, j and 3b, d and Figures S4 and S7). Our simulation results demonstrated that both positive and negative nano-objects have binding preference for the highly charged N and C-termini (whose total charges are +5 and −13e, respectively). The α-syn protein is rich in charged amino acids (40 charged residues) and has 24 and 16 negative and positive residues, respectively. E


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Figure 4. (a) Sigmoidal kinetic profile (ThT) of α-syn fibrillation and TEM image of mature fibril formed in the absence of NPs (control case). The effects of different concentrations of (b) SPION(0), (c) SPION(+), (d) SPION-CH, (e) SPION-PEG, and (f) SPION(−) on α-syn fibrillation monitored by ThT fluorescence. Kinetic parameters ((g) relative half time (t1/2/t1/2, control), (h) relative ThT end level, (i) relative lag time (tN/ tN, control), and (j) relative growth rate (ν/νcontrol)) for α-syn fibrillation as a function of various concentration of SPIONs relative to the values in the absence of the SPIONs. The effects of different concentrations of (k) graphene(+), (l) graphene(0), and (m) graphene(−) on α-syn fibrillation monitored by ThT fluorescence. Kinetic parameters ((n) relative half time (t1/2/t1/2, control), (o) relative ThT end level, (p) relative lag time (tN/ tN, control), and (q) relative growth rate (ν/νcontrol)) for α-syn fibrillation as a function of different concentrations of graphene relative to the values in the absence of the graphene.

characteristic of synthesized and commercial nano-objects are provided in Supporting Information Figure S9a−d and Tables S1−S3, respectively). Irrespective of size or concentration, the uncharged SPION(0) (20−100 nm) had negligible effects on α-

was assessed in the presence of commercial SPIONs and synthesized graphene sheets with different physicochemical properties and at various concentrations (10−1000 μg mL−1) using Thioflavin T (ThT) and TEM analyses (details on F


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Figure 5. (a) TEM images of α-syn after 24 h incubation in the absence (control) and presence of SPION(0), SPION(−), SPION(+), SPION-CH, SPION-PEG, graphene(0), graphene(−), and graphene(+) (500 μg mL−1, scale bar, 200 nm). Far-UV CD spectra of α-syn fibrils formed in the absence (control) and presence of (b) SPIONs and (c) graphenes (500 μg mL−1). Fluorescence anisotropy values of α-syn alone and incubated with (d) SPION and (e) graphenes (mean ± SD, n = 3, **p < 0.01 significant compared with α-syn). Effects of (f) SPIONs and (g) graphenes on the elongation step monitored by ThT fluorescence. (h) Schematic representation of potential inhibitory effects of SPIONs/graphene on different steps (primary nucleation, elongation and secondary nucleation) of the α-syn fibrillation process.

syn fibrillation (Figure S10a−f). Similar effects were observed for graphene sheets, where an increase in the lateral size from 200 to 1000 nm did not affect their inhibitory impact on the

overall fibrillation process (Figure S10g−x). Clearly, the changes in the size of nano-objects had no effect on α-syn fibrillation. G


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ThT fluorescence changes are not always reliable quantitative measures of the extent of fibrillation; binding of ThT to nonfibrillar assemblies may lead to artifacts.45 To address this issue, ThT kinetics data were confirmed by TEM and far-UV circular dichroism (CD) analyses, which provide valuable information on the morphology and extent of α-syn fibrils. As shown in Figure 5a, long and thick fibrils formed in the presence of graphene(0), SPION(0), and SPION-CH. Indeed, similar fibrils formed in the presence and absence of these nano-objects. In contrast, a few short fibrils were formed in the presence of positively and negatively charged SPIONs/graphene (Figure 5a). Fibril reduction can be explained by the inhibitory effect of charged nano-objects. Far-UV CD analysis was used to determine the secondary structural changes that occurred after α-syn fibrillation. CD spectra of fibrils formed in the absence of nano-objects with a negative band at 218 nm and a positive band at 196 nm are consistent with a β-sheet secondary structure (Figure 5b, c). Similar CD spectra were obtained for fibrils formed in the presence of graphene(0) and SPION(0), confirming the lack of effect of these NPs on α-syn aggregation. In contrast, the CD spectra of the formed fibrils in the presence of surface modified SPIONs and graphene sheets revealed considerable changes in the intensities of positive and negative bands, which are due to the reduction in the β-sheet/fibril contents. In the case of fibril formation in the presence of SPION(+), SPION(−), SPION-PEG and graphene(+), both negative and positive bands disappeared. Fluorescence anisotropy assay was used to measure variations of the rotational Brownian motion of α-syn_Cy5 caused by protein interactions with the nano-objects.46 If the rotation is slowed down by binding to surfaces or self-association, the fluorescence anisotropy increases. We observed a significant enhancement in the fluorescence anisotropy of α-syn_Cy5 during its interactions with SPION(−) and SPION(+) but not to SPION(0) (Figure 5d). Similar results were also observed for graphene(+), graphene(−), and graphene(0) incubated with αsyn_Cy5 (Figure 5e). These results indicate that positively and negatively charged nano-objects have a higher binding affinity to α-syn_Cy5 compared to neutral ones, consistent with their role in reducing α-syn fibrillation The obtained data from these analyses raise the question of why the charged nano-objects can effectively prevent α-syn fibrillation. A possible mechanism for this therapeutic efficacy is likely related to their surface charge/functional group and high affinity to α-syn, which is rich in charged residues. Examples of Specific Inhibition of Elongation Steps. To study the effects of nano-objects on the secondary nucleation and elongation phases, short fibrillar seeds (5%), resulted after sonication of mature fibrils, were incubated with the monomeric α-syn (1 mg mL−1). This strategy bypasses the primary nucleation and immediately starts fibril growth. Short fibrillar seeds may provide active ends and surface area required to trigger the elongation and secondary nucleation, respectively. As seen in Figure 5f, while all types of SPIONs inhibited the fibrillation process, SPION(+) and SPION(−) showed the strongest inhibitory effects. Similarly, in the case of graphene sheets, the graphene(+) showed the highest inhibitory effects when compared to others (Figure 5g). Clearly the charged SPIONs and graphene sheets have a great capacity to prevent the α-syn fibrillation by inhibiting elongation phases. Short fibrils formed in the primary stages can also catalyze the surface-mediated formation of additional oligomers/nuclei, which trigger fibrillation, through secondary nucleation.47

As seen in Figure 4b−f, SPIONs-Polyethylene glycol 3000 (SPION-PEG), SPION(−), and SPION(+) inhibited the α-syn fibrillation in a concentration−dependent manner, clearly evidenced by the shift of sigmoidal curve toward longer lag times and less steep elongation phases. To quantify the inhibitory effects of the nano-objects on different steps of the fibrillation process, the ThT kinetic curve was analyzed using Finke−Watzky (F−W) model (Seq 1 and Seq 2).43,44 Fitting this model to ThT kinetic data provides valuable quantitative information on the required time to form half of the total products (t1/2) and fibril growth rate (ν), from which the nucleation time, called lag phase (tN), can be calculated. As shown in Figure 4g, for the SPION(−), SPION(+), and SPIONPEG, t1/2 increased with increasing the NP concentration. The maximum t1/2 was achieved at 250 μg mL−1 for SPION(+) and at 1000 μg mL−1 for SPION(−) and SPION-PEG. We also quantified the amount of the formed fibril at the end of fibrillation based on the ThT level. The lowest number of fibrils were formed in the presence of SPION(+), but SPION(−) also inhibited fibrillation significantly (Figure 4h). To interpret the effects of these inhibitors on individual steps of the reaction kinetics, both fibril growth rate (v) and primary nucleation time were calculated. The overall inhibition caused by these nano-objects can be attributed to their effects on the lag and elongation phases. As shown in Figure 4i, increasing the concentration of SPION(+), SPION(−), and SPION-PEG increases the lag time. Both SPION(−) and SPION-PEG increase the lag time at high concentration, while much greater extension in the lag time achieved in the presence of low SPION(+) concentration. SPIONs also influenced the α-syn fibrillation kinetics by affecting the elongation phase. SPION(+), SPION(−), and SPION-PEG reduced fibril growth rate in a concentration-dependent manner (Figure 4j), while SPION(0) and SPIONs-chitosan (SPION-CH) had no significant effects on the lag and elongation phases (Figure 4i, j). We also evaluated the effects of graphene(0), graphene(−), and graphene(+) on α-syn fibrillation kinetics under the same conditions. These sheets inhibited the α-syn fibrillation in a concentration-dependent manner and showed the same trends as SPIONs. Positively and negatively charged graphene sheets showed greater inhibitory effects than neutral sheets. Low concentrations of graphene(+) and graphene(−) (i.e., 50 and 100 μg mL−1) strongly reduced production of α-syn fibrils (Figure 4k−m). In comparison to graphene(0) and graphene(−), the lower concentration (100 μg mL−1) of graphene(+) is required to significantly reduce the number of the end level fibrils (Figure 4o). Similar to SPIONs, the graphene sheets interfered with αsyn fibrillation by increasing the lag phase and/or altering the elongation phase (Figure 4n−q). Low and high concentrations of graphene(−) and graphene(+), respectively, considerably prolonged the lag time, while graphene(0) showed no significant effect on this step even at high concentrations (Figure 4p). Graphene(0), graphene(+), and graphene(−) all affected elongation phases, but in different manners (Figure 4q). The rate of fibrillar growth was considerably reduced by increasing the graphene concentration (Figures 4q and Figure S10t). The most striking observation was the dual effect of graphene(−) on the fibril growth rate; low concentrations enhanced the growth rate, while high concentrations inhibited it (Figure 4q and Figure S10x). We conclude that the inhibitory or acceleratory effect of graphene(−) on growth rate depends on the ratio of graphene(−) surface area to α-syn concentration. H


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Figure 6. SEC profile of small oligomers produced after 1 h incubation of α-syn with and without SPIONs. (a) Zoom in of the volumes where oligomers come out of the SEC column for RI detection and (b) UV absorbance. Effects of oligomers formed in the presence of (c) SPIONs and (d) graphene on the α-syn fibrillation monitored by ThT fluorescence. Kinetic profile of α-syn fibril disaggregation in the presence of (e) SPIONs and (f) graphene monitored by ThT fluorescence. (g) TEM images of α-syn fibrils disaggregated in the presence of SPIONs and graphene. (h) The SEC profile of small oligomers produced after fibril breakage. I


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broken down into short fibrils in the presence of SPIONs or graphene (Figure 6g). Paradoxically, fibril fragmentation may be undesirable, since it will increase the total surface area and the concentration of fibril active ends as well as possible production of cytotoxic oligomers.59 Therefore, we measured the amount of oligomers produced after fibril disaggregation. After incubation of SPIONs with mature fibrils overnight, NPs and insoluble fragmented fibrils were removed via centrifugation, and the soluble oligomers remaining in the supernatant were run on SECMALS system. The data obtained from this analysis showed that the amount of oligomeric α-syn species was constant before and after fibril breakage (Figure 6h). Therefore, these NPs are able to dissociate the preformed α-syn fibrils in a safe manner.

Therefore, the lag time extension induced by the charged nanoobjects cannot be attributed simply to the prevention of the primary nucleation. Inhibitory effects of nano-objects may result from their binding to primary or secondary nuclei or surfaces of existing short fibrils. Capturing monomers can delay or prevent both primary and secondary nucleation and elongation phases. Blocking the fibril surface and active ends inhibits the secondary nucleation and elongation respectively (Figure 5h). Additional fibril active ends generated after seed formation or fibril fragmentation may exponentially accelerate the fibrillation process.48 Effective inhibitors that delay or prevent α-syn fibrillation typically block targets that exist at low levels, for example, fibrillation nuclei or the growing ends of fibrils.49 As fibril constructed of multitude monomers, the number of fibril active ends is much lower than monomer quantity. Therefore, the inhibitors blocking fibril active ends are able to effectively prevent fibrillation at the lowest concentration. Consistent with this hypothesis, the positive nano-objects, which showed the strongest inhibitory effects on elongation phase (fibril active ends), worked at the lowest concentration. NPs Induced Formation of Off-Pathway Oligomers. A growing body of evidence supports the critical role of oligomeric species of α-syn in the pathogenesis and progress of PD.50−53 αSyn forms heterogeneous populations of small (e.g., annular, spherical and pore-like oligomers) and elongated large oligomers.54−56 Therefore, we measured the amount of soluble oligomers formed in both presence and absence of SPIONs by SEC-MALS. This analysis provided robust population estimates based on refractory index and absorbance at 280 nm. The SECMALS analysis showed that all SPIONs, except SPION-CH, increase the formation of small oligomers. According to SECMALS, we rank the SPIONs ability to produce small oligomers in the following order: SPION-PEG > SPION(+) > SPION(0) > SPION(−) (Figure 6a, b). In all cases, the concentration of monomers was kept constant. Heterogeneous oligomers with different sizes, β-sheet content, and structure differently induce the fibrillation process and cytotoxicity.57 To determine whether the oligomers produced in the presence of SPIONs/graphene trigger fibrillation, we incubated SPIONs or graphene with α-syn monomers for 30h, after which we removed SPIONs/graphene and insoluble fibrils through centrifugation. The remaining soluble oligomers were added to α-syn monomers. As seen in Figure 6c, d, oligomers produced by SPION(+), graphene(0), and graphene(+) led to the lowest amount of fibrils, consistent with the formation of off-pathway oligomers. SPIONs and Graphene Disaggregate Preformed Fibrils. Disaggregation of preformed mature fibrils is the most commonly used strategy for treating PD. Several strategies have been developed to improve the disaggregation ability of NPs.58 However, the majority of fibril destructive NPs showed weak destruction power. The fibril disaggregation ability of SPIONs and graphene was studied using ThT and TEM analyses. As seen in Figure 6e, SPION(+), SPION(−), SPION-CH, and SPIONPEG strongly disaggregated the preformed fibrils, while SPION(0) showed no significant impact. The disaggregation ability of graphene could be ranked as graphene(+) > graphene(0) > graphene(−) (Figure 6f). The higher fibril disaggregation efficacy of positive nano-objects is possibly related to their higher affinity to charged α-syn residues. The ThT results were also verified by TEM images. The elongated large fibrils were

CONCLUSIONS In summary, we revealed that the electrostatic forces have a dominant role in α-synuclein fibrillation process and the use of charges nano-objects can slow-down or prevent the fibrillation process. Using both simulation and experimental evaluations, we earned mechanistic understanding of the nature of interactions between α-synuclein and different types of NPs (i.e., SPIONs and graphene sheets with different physicochemical properties). According to our outcomes, the physicochemical properties of nano-objects have a crucial role in dictating their interactions with α-synuclein; therefore, these important characteristics should be considered in the development of nanotechnologybased therapeutic approaches. For in vivo therapeutic purposes, further studies should be performed to probe how the physicochemical properties of these nano-objects direct their biological fates and may dictate their interactions with αsynuclein. In addition, strategies that enable nano-objects to pass the blood−brain barrier should be also considered.60 METHODS Molecular Dynamic Simulation. We performed atomistic molecular dynamic simulations to investigate the mechanism of SPION/graphene-α-syn interactions and identify key residues involved in these interactions. In this regard, the GROMACS (Groningen machine for chemical simulations) software and OPLS-AA force field were used for doing all simulations, and rendering was performed by using the VMD 1.9.3.61,62 The structure of α-syn (polypeptide with 140 residues) was obtained from the Protein Data Bank (http://www.rcsb. org) (1XQ8). The amino acid sequence of α-syn can be divided into three regions: N-terminus contains residues 1−60 (total charge: +5 e), central region contains residues 61−95 (total charge: −1 e), and Cterminus contains residues 96−140 (total charge: −13 e). Graphene (170.0 Å × 70.0 Å, along X−Y Cartesian coordinates) and SPIONs were modeled using VMD 1.9.3.62 The functionalized graphenes/ SPIONs, in accordance with experiments, were modeled with positive or negative charges (Figure S1). In order to simulate the biological conditions, modeled α-syn and graphenes/SPIONs (graphene polyglycerol (graphene (0) ), graphene polyglycerolsulfate (graphene(−)), graphene polyglycerolamine (graphene(+)), SPIONs (SPION (0) ), SPIONs-COOH (SPION (−) ), and SPIONs-NH 2 (SPION(+))) were solvated in TIP3P (transferable intermolecular potential with 3 points) water molecules with 150 mM NaCl.63 In addition, extra ions (Na+ and Cl−) were also introduced to ensure the systems neutrality, and along the Cartesian coordinates the periodic boundary conditions were exploited. We focused on the residues having crucial roles in the interactions between α-syn and graphene(+)/ graphene(−)/graphene(0)/SPION(+)/SPION(−)/SPION(0). To find the good initial conditions, we used AutoDock Vina followed with minimization by steepest descent algorithm.64 The linear constraint solver (LINCS) algorithm was applied to constraint bonds with a Lennard-Jones cutoff radius of 1.4 nm.65 The particle-mesh Ewald J


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ACS Nano (PME) summation with a 1.4 nm cutoff, fourth PME order, and 0.12 nm fast-Fourier grid spacing for molecular dynamic runs were applied.66 The systems were equilibrated in canonical ensemble and also NPT ensemble, which systems are coupled to a Berendsen thermostat at 310 K (Maxwellian distribution of velocities) with a coupling time constant of 0.5 ps for 10 ns.67 The 40 ns production runs were carried out using a leapfrog algorithm with a time step of 1 fs (Δt = 0.001 ps). For calculating electrostatic and vdW energies, we have postprocessing simple MATLAB code to calculate the Lennard-Jones (6− 12) potential: ÅÄÅ ÑÉ Åi σ y12 i σ y6ÑÑ Φ(r ) = 4ϵÅÅÅÅjjj zzz − jjj zzz ÑÑÑÑ ÅÅk r { k r { ÑÑÑÖ ÅÇ

7.2), followed by incubation for 10 min. The cells were then pelleted (by centrifugation at 9000 g, 20 °C, 30 min), resuspended in ice-cold deionized water, and incubated on ice for 3 min after addition of saturated MgCl2 (40 μL). The supernatant was precipitated by titration with 1 M HCl to pH 3.5, collected by centrifugation and titrated to pH 7.5 with 1 M NaOH, and loaded on a Q-Sepharose column (HiTrap Q H P) which was pre-equilibrated with 20 mM Tris-HCl pH 7.5. Finally, the α-syn was eluted with a NaCl gradient from 0.1 to 0.5 M. SDSPAGE technique was then used to analyze and purify the eluted fractions of the α-syn. The extracted lyophilized α-syn states were then stored at −20 °C. Plate Reader Fibril Formation Assays. A Genios Pro fluorescence plate reader (Tecan, Mänerdorf, Switzerland) was employed to analyze α-syn fibril formation.76 Briefly, PBS solution (150 μL) containing freshly dissolved and filtered 0.2 μm α-syn (70 μM), 40 μM ThT, and varying concentrations of nano-objects, with different physicochemical properties, was added to each well of a 96well-plate (Nunc, Thermo Fischer Scientific, Roskilde, Denmark) with a 3 mm diameter glass bead and sealed with Crystal clear sealing tape (Hampton Research, Aliso Viejo, CA). The fibrillation process was performed at 37 °C with 300 rpm orbital shaking. The fibril formation was monitored through excitation and emission at 448 and 485 nm, respectively. The achieved ThT fibrillation data was fitted by using the Finke− Watzky (F−W)43 equations:

and the modified coulomb potential for calculating electrostatic interactions:68 Φ(r ) =

1 5 5r 3 r4 − + 4 − 5 r 3rc 3rc rc

We have also verified the outcomes with available post-processing GROMACS extensions for calculating these energies (e.g., gmx_energy). To determine if a hydrogen bond exists, a geometrical criterion is used: r < rHB = 0.35nm,

F(t ) =

α < αHB = 30°

The lifetime of the hydrogen bonds is calculated from the relaxation time averaged over all autocorrelation functions. This method was fully explained by Spoel group.69 Synthesis of Graphene with Different Sizes and Surface Chemistry. A series of graphene derivatives with different functionalities, charges and sizes, but the same polymer contents, was synthesized to study the effect of surface charge and lateral size of graphene sheets on the α-syn fibrillation. Triazine-functionalized graphene sheets were synthesized by nitrene [2 + 1] cycloaddition reaction at ambient conditions by our recently published procedure.70−74 Then, they were modified with polyglycerol to obtain large neutral graphene sheets with hydroxyl functionality. Conversion of the hydroxyl functional groups of the large polyglycerol-functionalized graphene sheets to sulfate and amine groups resulted in negatively and positively charged analogs with polyglycerolsulfate and polyglycerolamine coatings, respectively. Large graphene derivatives were then broken down to medium and small sizes by tip sonication to obtain nine compounds with different sizes and surface charges but equal polymer contents and density of functional groups (Figure S9a). Graphene derivatives with polyglycerol, polyglycerolamine, and polyglycerolsulfate coverage were called graphene(0)-X, graphene(+)-X, and graphene(−)-X, where X is L, M, and S for large, medium, and small analogs, respectively. In addition to graphene, we also evaluated the effects of commercial SPIONs with different size (e.g., 20, 50, and 100 nm), functional group (e.g., COOH and NH2), and coverage (e.g., PEG-300 and chitosan) on the α-syn fibrillation (Table S3). Nuclear Magnetic Resonance Spectroscopy, Transmission Electron Microscopy, and Thermal Gravimetric Analyses. Nuclear magnetic resonance spectroscopy (NMR) data were obtained on a Jeol Eclipse 500 MHz. Thermal gravimetric analysis (TGA) was performed on Linseis STA PT 1600 with temperature from 100 to 800 °C and heating rate at 10 °C/min with argon atmosphere. Tip sonication was conducted by a sonicator from BANDELIN SONOPULS. Transmission electron microscopy (TEM) was measured with Philips CM12 microscope. The ζ potential was measured by NANO ZSPO (Malvern) in PBS solution (pH = 7.4). Protein Production and Purification. Escherichia coli BL21(DE3) strain with a plasmid vector pET11-D was employed to express the recombinant human α-synuclein (α-syn); more details can be found in ref 75. Briefly, the cells were pelleted and consequently suspended in osmotic shock buffer (30 mM Tris-HCl, 40% sucrose, 2 mM EDTA, pH

ThTend level 1 + e−4v(t − t1/2)

tN = t1/2 −

1 2v

(1) (2)

where t1/2 is the required time for production of 50% ThT end level, ν is the rate of growth at t1/2, and tN is the duration of the nucleation (lag) phase. Transmission Electron Microscopy (TEM). The JEM-1010 TEM (JEOL, Tokyo, Japan) operating at 60 kV was used to analyze the interactions between fibrils and nano-objects. Images were obtained using an Olympus KeenView G2 camera. The samples were prepared on a carbon-coated, glow-discharged 400 mesh grid for 30 s. The grids were washed using 2 drops of double distilled water, stained with 1% phosphotungstic acid (pH 6.8), and blotted dry. Circular Dichroism (CD) Spectroscopy. Far-UV CD of sonicated fibril solutions with protein concentration of 14 μM were measured from 250 to 195 nm at 25 °C with a Jasco J-810 spectrophotometer (Jasco Spectroscopic Co. Ltd., Japan). CD spectra of PBS buffer and the nano-objects were recorded and subtracted from the protein spectra, and the CD signal given as mean residue ellipticity (degrees cm2 dmol−1). Fluorescence Labeling of α-Syn Monomers and Fluorescence Anisotropy. Cyanine5 NHS ester was used to label the α-syn monomers. One mL PBS buffer containing 1 mg mL−1 α-syn and 10 μL stock solution of the dye (2 mg mL−1) were shaked for 2 h at room temperature. Then, the protein solution was run on a PD-10 desalting column (GE Healthcare) to separate the free dye from the labeled α-syn monomers. As the fluorescence anisotropy has a capacity to measure changes in rotational correlation time of the molecule, we hypothesized that this approach can monitor the binding of α-syn to nano-objects. The LS 55 luminescence spectrometer (PerkinElmer) was used to monitor the interactions of the α-syn and nano-objects through excitation and emission at 646 and 662 nm (respectively) using both parallel and perpendicular polarizers. The anisotropies were obtained at a protein concentration of 2 μM and nano-objects concentration of 500 μg mL−1. Seeding Experiments. The seeding experiment assays were performed using the same setting as for the fibrillation assay in the presence of 50 μg mL−1 seeds and either 500 μg mL−1 SPIONs or graphene in a solution of 70 μM monomeric α-syn in 96-well plates. The fibrils were sonicated for 2 min on ice (pulse 5 s on and 5 s off) with an amplitude of 20% on a QSonica Sonicators (Q500, Newtown, CT, USA) to obtain short fibrils as seeds. K


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ACS Nano Fibril Disaggregation and Oligomerization Assays. For fibril disaggregation assay, 35 μM aggregated α-syn (monomer equivalents), which was prepared using the same setting as for the fibrillation assay, was incubated overnight either alone or with SPION or graphene (500 μg mL−1) at 37 °C. Then, the solutions were imaged using TEM. In the oligomerization assays, 1 mg mL−1 of α-syn monomer was incubated on an Eppendorf TS-100 thermoshaker (BioSan, Latvia) either alone or with 500 μg mL−1 SPION for 1 h at 37 °C and 900 rpm. The solutions of both disaggregation and oligomerization assays were then centrifuged (14500 rpm, 20 min), and the supernatants were analyzed by SEC-MALS system (Wyatt Technology Europe) using separation on a Superose 6_10/300 gel filtration column and analyzed using refractive index (Optilab T-rEX differential refractometer) and absorbance at 280 nm (Agilent 1260 Analytical UV cell). The achieved data were then analyzed by ASTRA 6.1.7.17 (Wyatt Technology Europe) software. In this study, all in vitro work has been repeated at least three times by independent experiments.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsnano.8b08983. Full details of characterization of nanoparticles and fibrillation processes (PDF)

AUTHOR INFORMATION Corresponding Authors

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

Daniel Erik Otzen: 0000-0002-2918-8989 Morteza Mahmoudi: 0000-0002-2575-9684 Mohammad Javad Hajipour: 0000-0002-2876-5473 Notes

The authors declare no competing financial interest.

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