C3N Nanodots Impede Aβ Peptides Aggregation Pathogenic Path in Alzheimer's Disease

doi:10.21203/rs.3.rs-2253428/v1

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C3N Nanodots Impede Aβ Peptides Aggregation Pathogenic Path in Alzheimer's Disease

https://doi.org/10.21203/rs.3.rs-2253428/v1

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published 15 Sep, 2023

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Despite accumulating evidence that the development of Alzheimer's disease (AD) is highly associated with the aggregation of Aβ peptides. Still, FDA has approved only one anti-aggregation-based therapy over the past several decades. Here, we report the discovery of an Aβ peptide aggregation inhibitor: an ultra-small nanodot called C₃N. C₃N nanodots alleviate aggregation-induced neuron cytotoxicity, rescue neuronal death, and prevent neurite damage in vitro. Importantly, they reduce the global cerebral Aβ peptides levels, particularly in fibrillar amyloid plaques, and restore synaptic loss in AD mice. Consequently, these C₃N nanodots significantly ameliorate behavioral deficits of APP/PS1 double transgenic AD mice. Moreover, analysis of critical tissues (e.g., heart, liver, spleen, lung, and kidney) display no obvious pathological damage, suggesting C₃N nanodots are biologically safe. Finally, molecular dynamics simulations also reveal the inhibitory mechanisms of C₃N nanodots in Aβ peptides aggregation and its potential application against AD.

Biological sciences/Biophysics

Physical sciences/Nanoscience and technology

Alzheimer's Disease

C3N Nanodots

Aβ Peptides Aggregation

Restore Synaptic Loss

Ameliorate Behavioral Deficits

Alois Alzheimer reported the first case of Alzheimer's disease (AD) in 1906^{1, 2}. Now, more than one century later, AD remains an unresolved public health problem worldwide³. AD is a progressive neurodegenerative disease associated with insidious onset and slow progression of behavioral and cognitive dysfunction. The severity of the AD from early stage ⁴ advances to obvious symptoms which further aggravates the need to utilize immediate remedies against the progression of the disease. Moreover, the incidence of AD also increases with the increasing age reflected by the increasing rate of ~ 27.6% in 65–74 year-old people to ~ 36.4% in people over 80 years old⁵. This significant increase with age also poses a worldwide threat of acquiring AD among elderly population. This also urges the need of developing novel and effective AD management therapies for clinical purposes.

Growing evidence suggests the aggregation of Aβ peptides is highly related with synaptic dysfunction, neuroinflammation, oxidative stress damage, neurotoxicity mediated by the triggered hyperphosphorylation of downstream Tau protein, as well as the ultimate cell death^{6, 7}. In contrast, suppression of the Aβ peptides aggregation process also offers a suitable therapeutic strategy against AD. However, the successful implementation of this concept remains a huge challenge despite decades of effort along this direction. On the other hand, the lack of effective drugs against AD, with the only available FDA approved drug aducanumab⁸, raises high demand for alternate therapeutic options. Besides, other anti-AD agents (including peptides^{9, 10}, polymers^{11, 12}, small drug molecules^{13, 14, 15, 16}, and metal oxides¹⁷) show only a very mild inhibition effect on Aβ peptides aggregation. Recently, nanomaterials (e.g., graphene oxide¹⁸, fullerenes^{19, 20}, quantum dots²¹, carbon nanotube²², and g-C₃N₄^{23, 24}) have been reported to inhibit, directly or indirectly, the aggregation of Aβ peptides, including both the inhibition of oligomer fibrillization and disaggregation of mature fiber in vitro, but very few of them can still work in vivo. Interestingly, graphene quantum dots were also found to inhibit α-synuclein aggregation, disassociate mature fibrils, and penetrate the blood-brain barrier (BBB) leading to ultimate protection of dopamine neurons²⁵. Therefore, the use of nanomaterials may offer valuable alternate source as therapeutic agents for protein conformational diseases (e.g., AD, Parkinson's disease, Huntington's disease, Type 2 diabetes).

In this study, we demonstrate that C₃N nanodots can significantly inhibit Aβ peptides aggregation, relieve aggregation-induced neuron cytotoxicity, rescue neuronal death, protect neurites from damage, and exhibit only mild cytotoxicity both in vitro and in vivo. Moreover, the intraperitoneal administration of C₃N nanodots for 6 months significantly improves the learning and spatial memory abilities of APP/PS1 in double transgenic AD mice. Additionally, the underlying molecular mechanism of Aβ peptide aggregation inhibition by C₃N nanodots has also been explored using all-atom molecular dynamics (MD) simulations. Thus, we believe our current study provides novel insights into the anti-Aβ peptides aggregation capability of C₃N nanodots and its potential application against AD.

C₃N nanodots inhibit Aβ₄₂ peptides fibrillization in vitro

C₃N nanodots were synthesized by polymerization of 2,3-diaminophenazine using hydrothermal synthesis following a previous report²⁶. The synthesized nanodots had an average lateral size of 4.5 ± 0.4 nm (Fig. 1a) with a lattice spacing of 0.21 nm, which corresponds to the (100) plane of graphite. Initially, the identification and characterization of C₃N nanodots were performed using several spectroscopic techniques including UV–visible (UV–vis) absorption spectroscopy, Fourier transform infrared (FTIR) spectroscopy and X-ray photoelectron spectroscopy (XPS). (Figure S1).

We first studied the role of C₃N nanodots towards the aggregation behavior of Aβ₄₂ peptides, which were shown to have more implications than Aβ₄₀ in forming neurotoxic assemblies and causing AD pathogenesis^{27, 28}. In the absence of C₃N nanodots, Aβ₄₂ peptides aggregated into mature amyloid fibers, as demonstrated by various experimental procedures. This included the utility of ThT fluorescence, dot blot assay, atomic force microscope (AFM), transmission electron microscope (TEM), and CD spectroscopy. During these investigations, C₃N nanodots effectively inhibited the aggregation of Aβ₄₂ peptides (Fig. 1). It was evident from delayed aggregation kinetics and reduced ThT fluorescence intensity (after convergence of aggregation process) following C₃N nanodots treatment. The inhibition strength was found positively correlated with C₃N nanodots treatment concentration (Fig. 1b). The final peptide self-assembly samples were also examined through dot blotting using an amyloid fiber conformation-specific antibody (mOC87)²⁹. Notably, amyloid fiber content decreased with the increasing concentration of C₃N nanodots during treatment (Fig. 1c). This confirmed the inhibition function of C₃N nanodots against peptides aggregation. Morphologically, Aβ₄₂ peptides aggregated to long and well-defined mature fibers after 24 hours in PBS without C₃N nanodots, as demonstrated through AFM and TEM imaging (Fig. 1d and S2). In contrast, incubation with C₃N nanodots for 24 hours resulted in a gradual morphologic change of Aβ₄₂ peptides self-assembly samples from long mature fibers to diffused punctiform structures. Overall, these results suggested that C₃N nanodots effectively inhibit the aggregation of Aβ₄₂ peptides.

To further unveil the regulating process and underlying molecular mechanisms of C₃N nanodots towards inhibiting aggregation of these peptides, we then performed all-atom molecular dynamics (MD) simulations. In the absence of C₃N, two Aβ₄₂ peptides self-assembled into a partially ordered structure (containing β-sheets). However, C₃N nanodot application significantly inhibited the formation of any β-sheets. For instance, in two out of three trajectories (run 1 and run 3), very rare β-sheet contents were formed (i.e. in run 2, β-sheet appeared at t = 80 ns, then disappeared at t = 340 ns) (Fig. 1e and S3). Convergence of the simulations (> 900 ns) demonstrated an overall decrease in the β-sheet content of 10.6 ± 1.5% without C₃N to 0.2 ± 0.6% with C₃N. Simultaneously, the random-coiled and bend components increased from 37.0 ± 2.4% to 40.6 ± 1.7%, and 13.5–20.3% (Fig. 1f), respectively. These findings suggested that C₃N nanodot effectively redirects Aβ₄₂ peptides self-assembly to disordered structures. Moreover, CD spectroscopy confirmed that C₃N nanodots redirected the secondary structure of Aβ₄₂ peptides (at t = 24 hours) from the β-sheet-rich to disordered random-coiled conformations (Fig. 1g). These results sufficiently demonstrate the structural modulating role of C₃N nanodot in impeding the aggregation of Aβ₄₂ peptides.

The detailed interaction energies including both van der Waals (vdW) and electrostatic (elec) interactions between C₃N and peptides were also explored (Fig. 1h). This was performed by analyzing the key binding configurations in a typical trajectory to better illustrate the binding mechanisms. Driven by vdW and hydrophobic interactions, one peptide was adsorbed onto the surface of C₃N (t = 1 ns) and strengthened by π‒π stacking interactions (F4 and F20) (t = 10 ns). At t = 13 ns, another peptide was adsorbed onto the edge of C₃N by electrostatic attractions between E17, D7, and E3 residues with ‒NH₃⁺ groups at the edge of C₃N nanodot. At t = 33 ns, this peptide was fully adsorbed onto the other side of C₃N nanodot via vdW and π‒π stacking interactions. After 96 ns, the adsorption process converged. At this state, most hydrophobic and aromatic residues were adsorbed onto the C₃N nanodot surface. Meanwhile, some charged or polar residues formed salt-bridge or hydrogen bonds with edge groups (e.g., ‒COO^‒ and ‒NH₃⁺) of C₃N nanodot while suppressing subsequent aggregation of peptides. Hence, the strong adsorption between peptides and C₃N nanodot was collectively driven by a combination of vdW and electrostatic, hydrophobic, hydrogen bonding, and π‒π stacking interactions, with the vdW interaction dominating (Fig. 1h), to induce disruption in peptides self-assembly and form disordered structures.

C₃N-nanodots alleviate neuron cytotoxicity induced by Aβ₄₂ peptides and demonstrate superior cytocompatibility

As shown above, C₃N nanodots exhibited an effective inhibiting function against Aβ₄₂ peptides aggregation at molecular level. At this stage, it was logical to examine whether C₃N nanodots alleviate aggregation-induced neuron cytotoxicity (Fig. 2). Herein, we analyzed primary neuron cells viability and toxicity under different conditions using cell counting kit 8 (CCK-8), Lactate Dehydrogenase (LDH), and Live/Dead assays. The CCK-8 assay results demonstrated that Aβ₄₂ peptides aggregation causes severe toxicity in neurons. This was found after neuronal cells incubation with 50 µM Aβ₄₂ peptides for 24 hours which resulted in a survival rate of only 29.89 ± 3.98%. However, increased treatment concentration with C₃N nanodots resulted in improved cell survival rate: ~44.83 ± 6.90% (100 µg/ml) to 65.52 ± 9.12% (500 µg/ml) (Fig. 2a). Hence, C₃N nanodots dose-dependently relieved Aβ₄₂ peptides aggregation-induced neuron cytotoxicity, which was further confirmed by LDH (Fig. 2b) and Live/Dead experimental (Fig. 2c & d) results. In addition, the cytotoxicity of C₃N nanodots was found very mild with C₃N nanodots administered at 500 µg/mL resulting a neuronal survival rate of ~ 88.51 ± 2.0%. We further investigated the morphologies of neurons under different conditions using scanning electron microscope (SEM) technology (Fig. 2e). Normal neurons presented in a plump-pear shape with many dendrites. However, Aβ₄₂ aggregation-induced significant deformations of neurons, e.g., the cellular body shrunk notably and was accompanied by severe dendrites loss. In contrast, the treatment with C₃N nanodots resulted in well maintained dense dendrites suggesting inverse effect against the toxicity caused by Aβ₄₂ peptides aggregation in neurons. It also distinguished the mild influence of C₃N nanodots on the shape of neurons.

In addition, the cytotoxicity of C₃N nanodots in several cell lines was also examined, including red blood cells (RBC), rat adrenal chromaffin cell tumor cells (PC12), primary neuron (Neuron), primary astrocytes (Astrocyte), human umbilical vein endothelial cells (HUVCE), and human neuroblastoma cells (SH-SY5Y). The results showed that C₃N nanodots possess decent cytocompatibility among all tested cell lines (Figure S4 and S5). This revealed that C₃N nanodots alleviate neuron cytotoxicity, reduce cell death, protect Aβ₄₂ aggregation-induced axonal and dendritic damages and demonstrate remarkable cytocompatibility.

C₃N-nanodots improve the learning and spatial memory capabilities of APP/PS1 mice with limited biotoxicity

Following the encouraging in vitro findings, we sought to determine whether C₃N nanodots have neuroprotective functions towards AD mice via inhibition of Aβ peptides aggregation. For this purpose, we used APP/PS1 double transgenic mice as the model AD organism. This in-vivo model overexpresses Aβ peptides in the brain by inducing amyloid plaque formation which eventually leads to the occurrence of AD symptoms^{31, 32}. The expression of Aβ peptides in APP/PS1 mice begins at 3‒4 months of age. Thus, we treated the APP/PS1 mice with C₃N nanodots-saline solution per day from 3 to 9 months via intraperitoneal injection. APP/PS1 mice received saline only were set as the positive control group, and wildtype mice with non-intervention were set as the negative control. After six months of C₃N nanodots injection vs. no injection, the cognitive function of APP/PS1 mice were examined using the Morris water maze and novel object recognition tests (Fig. 3).

We first refined the optimal C₃N nanodots administration dose from the assessment of the escape latency. In the Morris water maze test during the 5-day learning phase, the latency time for APP/PS1 mice to find the survival platform (initially placed in the third quadrant) in the saline group underwent a very mild decrease as shown previously³³. Treatment with C₃N nanodots significantly shortened the latency time, indicating a remarkably improved learning capacity of AD mice (Fig. 3a). We also noted that treatment with 1 mg/kg/d dose obtained better therapeutic effect than that treated with 5 mg/kg/d dose (Fig. 3a), suggesting that 1 mg/kg/d may be the optimal dose. The potential contribution of the swimming capability (swimming speed) to the learning effects was excluded because there was no distinct difference in the average swimming speed between two C₃N nanodots treated groups and the wildtype mice (Fig. 3b). Overall, these results demonstrated the efficacy of C₃N nanodots in the treatment and improving the learning capacity of AD mice, with an optimal dose of ~ 1 mg/kg/d. Hence, 1 mg/kg/d was used in the following in vivo experiments.

To further measure the spatial memory capability, the third quadrant residence time of mice was accumulated during 60s swimming after retrieval of the survival platform on day 6. C₃N nanodots-treated AD mice spent significantly more time in the third quadrant and crossed this target quandrant more often compared to control APP/PS1 mice (Fig. 3c, d & f). In addition, the time to explore the new object among APP/PS1 mice was significantly reduced as compared to that of the wild-type. However, treatment with C₃N nanodots can remarkably prolong the time of APP/PS1 mice to explore the new object, which resulted in the recognition index (RI) of APP/PS1 mice (treated with C₃N nanodots) was remarkably improved to level comparable with wild-type mice (Fig. 3e & g). These results were indicative that C₃N nanodots treatment could partially rescue these defects in APP/PS1 mice and may offer utility against AD.

Furthermore, the body weights among both C₃N nanodots treated and untreated AD mice increased steadily during the entire administration period (Figure S6) suggesting the higher biocompatibility of C₃N nanodots in animals. Moreover, the H&E staining in heart, liver, spleen, lung, and kidney tissue showed no distinct lesions indicating C₃N nanodots related limited biotoxicity in vivo (Figure S7).

In vivo efficacy of C₃N nanodots against amyloid pathology

Next, we detected the level of cerebral fibrillar amyloid plaques as hallmark of AD³⁴ in wild-type and APP/PS1 mice untreated/treated with C₃N nanodots. The 6E10 anti-Aβ antibody was used because of its specific binding capability with residues 1 to 16 of the Aβ peptide. Notably, massive amyloid plaques accumulated in both the cerebral cortex and hippocampus of APP/PS1 mice treated with saline (1.22 ± 0.29%) (Fig. 4a). However, the amyloid plaques deposition levels remarkably decreased after treatment with 1 mg/kg/d (0.33 ± 0.18%; a 74.4% decrease) C₃N nanodots treatment (Fig. 4b). These results were also confirmed by counting the number of amyloid plaques (Fig. 4c).

Considering that Aβ₄₀ and Aβ₄₂ peptides are the dominant component of the plaques in the brains of AD patients²⁷. We then used enzyme-linked immunosorbent assay (ELISA) to quantify the level of intra-cephalic Aβ₄₂/Aβ₄₀ peptides. This involved using Tris-buffered saline (TBS) ‒, sodium dodecyl sulfate (SDS)‒, and formic acid (FA)‒soluble Aβ forms corresponding to the soluble, partially soluble (non-dense plaque), and completely insoluble (dense plaque) Aβ forms, respectively. These analyses showed that treatment with C₃N nanodots decreased the level of Aβ₄₂ / Aβ₄₀ peptides by 37% / 33%, respectively. The relative FA‒soluble Aβ₄₂ / Aβ₄₀ species levels was reduced most significantly by 84% / 81% (Fig. 4d & e), which suggested that C₃N nanodots effectively inhibit Aβ peptides aggregating into completely insoluble dense plaques. Overall, C₃N nanodots possessed the strong ability to delay or obstruct Aβ peptide aggregation pathogenesis in vivo.

C₃N nanodots improve the level of synaptic function-related proteins in vivo

Synaptic dysfunction is another important pathological feature of AD^{35, 36} having a strong impact in nerves development and neurotransmitters release (including dopamine and glutamate). The SNAP25 and VAMP2 proteins are the two main synaptic proteins which protects synaptic integrality^{37, 38}. Therefore, we assessed the changes in expression levels of these two proteins using western blot and immunohistochemistry fluorescence assays. Western blot results demonstrated that the content of two proteins was up-regulated (Fig. 5a) after treatment with C₃N nanodots. The quantification of the SNAP25 and VAMP2 protein levels was performed using grey density analyses by utilizing Image J software. The results showed that expression levels of the two proteins were increased by 43% & 22% respectively, after treatment with C₃N nanodots (Fig. 5b).

In addition, we also examined the synaptic damage by double-staining brain tissue with an antibody against microtubule-associated protein 2 (MAP2; a neuronal marker) and SNAP25 (a synaptic marker) (n = 3/group). The co-localization of SNAP25 and MAP2 signals reflected the expression level of synaptic proteins in neurons. In APP/PS1 mice treated with saline only, SNAP25/MAP2 co-localization yellow pixel intensity decreased remarkably, which indicated serious dysfunction of the neural network as compared to wild-type mice. In contrast, treatment with C₃N nanodots for six months resulted in significantly elevated SNAP25/MAP2 expression levels (Fig. 5c). These results demonstrated that C₃N nanodots maintains an effective protective function in the synapse.

In this study, an effective Aβ peptides aggregation nano-inhibitor called C₃N nanodots has been explored against AD. This novel inhibitor redirects peptide self-assembly to disordered off-pathway species and reduces aggregation-induced neuron cytotoxicity in vitro and in vivo. Several experimental analyses including ThT fluorescence, dot blot assays and CD spectra collectively demonstrate that C₃N nanodots guide Aβ peptides self-assembly to disordered structures rather than β-sheet-rich structures. Similarly, morphological observations using AFM and TEM imaging showed that after treatment with C₃N nanodots these Aβ peptides form small diffused oligomeric structures, in contrast to the long and well-defined mature amyloid fibers formed in the absence of C₃N nanodots. The results from CCK-8, LDH, and Live/Dead assay revealed that C₃N nanodots relieve neuron toxicity induced by Aβ aggregation and rescue neuronal death. SEM images further helped to depict that C₃N nanodots protect normal neuronal morphology from Aβ aggregation-induced destruction. Furthermore, MD simulations demonstrated that both the non-specific hydrophobic and electrostatic interactions, and the specific π‒π stacking and hydrogen bonding interactions between C₃N nanodots and Aβ peptides synergistically obstruct the aggregation process of Aβ peptides.

The cognitive abilities among the studied mice were also restored following C₃N nanodots treatment. After C₃N nanodots treatment, the cognitive ability of APP/PS1 mice significantly improved to levels comparable with wild-type mice. Several immunological experiments including immunohistochemistry fluorescence, western blot, and ELISA assays demonstrated that APP/PS1 mice experience a decrease in cerebral fibrillar amyloid plaque levels and an increase in SNAP25 and VAMP2 with C₃N nanodots treatments. Conclusively, this study not only provides useful experimental and theoretical basis for the application of C₃N nanodots in neuronal protection, but also offers the groundwork for subsequent optimal designs of nanomaterials targeting Aβ peptides aggregation in AD.

Preparation of C₃N nanodots and characterizations

The synthesis of C₃N nanodots was based on the method reported by our group²⁶. Briefly, the aqueous solution of 2,3-Diaminophenazine (80 mL, 1.4mM) was heated and kept at320°C for 36 hours in a 100 mLpoly (p-phenylene)-lined stainless-steel autoclave. The products were filtered by 0.02 µm alumina microporous membrane to obtain the raw C₃N nanodots. Then, the raw C₃N nanodots were treated with H₂O₂ (5 M, 80°C for 6 h) for further oxidization. Finally, the sample was purified via membrane dialysis with the molecular weight cutoff of 500–1000 Da for 5 days, and the oxygen-modified C₃N nanodots were obtained.

The transmission electron microscopy (TEM) and high-resolution TEM (HRTEM) images were obtained using transmission electron microscope with the accelerating voltage of 200 kV (Tecnai G2 F20, FEI Corporation, American). The Fourier transform infrared (FT-IR) spectra of C₃N nanodots were characterized using fourier transform infrared spectrometer (Hyperion, Bruker Corporation, Germany). The UV-vis spectra analysis utilized a UV-vis spectrophotometer (Lambda 750, PerkinElmer, American), and the X-ray photoelectron spectra (XPS) were obtained using a X-ray photoelectron spectrometer (Axis ultra DLD, Kratos, Britain).

Preparation of Aβ₄₂ peptides

Aβ₄₂ (NH2-DAEFRHDSGYEVHHQKLVFFAEDVGSNKGAIIGLMVGGVVIV-COOH, purity ≥ 98%) peptides were purchased from APeptide Co., Ltd (Shanghai, China) and prepared according to protocols previous described^{39, 40}. Briefly, Aβ₄₂ peptides were first dissolved in hexafluoroisopropanol (HFIP, 10522, Sigma Aldrich) and sonicated for 10 minutes. The Aβ₄₂‒HFIP solution was then incubated at room temperature for 1 hour to ensure the monomerization and structural randomization of peptides, and placed into a fume hood to completely evaporate HFIP. The obtained peptide film was stored at ‒80°C. Immediately before use, the peptide film was resuspended to 5 mM in dimethyl sulfoxide (DMSO, D2650, Sigma Aldrich) and diluted to a final concentration of 100 µM in phosphate-buffered solution (PBS, 0.1 M). The solution was then centrifuged at 16000 g for 10 min at 4°C to remove the pre-formed fibers. In the aggregation experiment, Aβ₄₂ (100 µM) was mixed with C₃N nanodots at various concentrations or PBS solution to a final concentration of 50 µM and then incubated at 37°C with constant agitation at 300 rpm for 24 h.

Thioflavin-T (ThT) Assay

Fluorescence with Thioflavin T (ThT) was used to detect aggregated Aβ containing β-sheets, as previously described⁴¹. A 50 µL sample was mixed with 150 µL ThT (20 µM, T3516, Sigma Aldrich) in a 96-well plate. The resulting fluorescence intensity was detected immediately after mixing with a fluorescence plate reader (BioTek, USA) at excitation and emission wavelengths of 450 nm and 485 nm, respectively. Fluorescence values of C₃N nanodots and ThT were subtracted from that of the mixed solution. Error bars (± s.d.) of triplicate samples are shown for selected data points.

Dot blot assay

Dot blot assays were carried out as described previously⁴² to probe the formation level of Aβ₄₂ amyloid mature fibers under different conditions. Briefly, 5 µL aliquots of the sample were dropped onto nitrocellulose membranes (1060002, GE Healthcare). Once the membranes dried, they were blocked for 1 hour with 3% nonfat milk in tris-buffered saline (TBS) solution and then incubated with Anti-Amyloid Fibril antibody (mOC87) (1:8000, ab201062, Abcam) overnight at 4°C. The membranes were washed 3 times in TBST for 5 minutes and then incubated with the horseradish peroxidase (HRP)-conjugated donkey anti-rabbit secondary antibody (1:5000, 711-035-152, Jackson ImunoResearch) for 2 hours at room temperature. Finally, the membranes were developed by chemiluminescence using ECL Plus (P0018S, Beyotime).

Atomic Force Microscope (AFM)

Here, 10 µL of each sample was dispersed on freshly cleaved mica sheets. After air-drying, samples were scanned and analyzed using the tapping mode of AFM (Bruker, Germany), and the height of the sample was recorded.

Transmission Electron Microscopy (TEM)

Ten microliters of each sample were dispersed on a copper grid (carbon and formvar coated 300 mesh, Zhongjing Technology Co., Ltd., China) for 2 min at room temperature. Then, they were washed twice with ultrapure water and negatively stained with 1% uranyl acetate for 2 min. After air-drying, images of peptides were observed using a Tecnai G2 spirit BioTwin TEM at 120 kV.

Circular Dichroism (CD) Spectroscopy

All samples were diluted six times under PBS conditions. Spectra were detected using a Jasco J-815 circular dichroism spectropolarimeter (1 mm path length cuvette) at 25°C. The spectrum of PBS was set as the baseline. Each sample was scanned three times and the average value was adopted. Raw data, after subtracting the buffer spectra, were smoothed according to the manufacturer’s instructions.

Primary neuron culture

Mouse primary cortical neurons were obtained from embryonic day 18 C57BL/6 mice as reported previously²⁵ with minor changes. All animal procedures followed the policies of the Soochow University Animal Care and Use Committee (SUACUC). In brief, dissociated neurons were plated onto dishes coated with poly-D-lysine (P6407, Sigma Aldrich) then suspended in culture medium (Neurobasal Media (21103-049, Invitrogen) containing 2% B-27 (17504-044, Invitrogen), 1% penicillin/streptomycin (15140122, P/S, Gibco), 1% L-glutamine and 0.25% GlutaMax™ (35050, Invitrogen)). Next, the plating medium was substituted with feeding medium (Neurobasal medium supplemented with 2% B27, 1% P/S, and 1% L-glutamine) on the second day after cell plating. The medium was replaced twice a week and the cultures were incubated in a 5% CO₂ incubator at 37°C. Cells were used for experimentation 8 days after seeding.

Primary astrocyte cultures

Primary astrocyte cultures were extracted from the cerebral cortex of 1-3-d-old rats (Sprague-Dawley) following prior methods⁴³. In brief, dissociated cortical cells were suspended in DMEM media (sh30022.01b, Hyclone) containing 1% P/S (Gibco) and 10% Fetal bovine serum (10099141, Gibco) and plated on PDL-coated 75 cm² flasks at a density of 6 × 10⁵ cells/cm². Monolayers of type 1 astrocytes were harvested 12–14 days after plating. Non-astrocytic cells were separated and removed from the flasks by shaking and changing the medium. Astrocytes were dissociated through trypsinization and reseeded on uncoated 96-well plates. The cells grew to 80–90% confluence before exposure to C₃N nanodots.

Cell viability assay and morphology observation

Cell viability was evaluated using CCK-8 kit (ck04, Dojindo), LDH cytotoxicity assay kit (K311-400, Biovision), and Live/Dead kit (l3224, Invitrogen). Before experimentation, the neuron culture medium was used to dilute 5 mM Aβ₄₂ peptide stock solution and C₃N nanodots solution to achieve a mixture of 50 µM Aβ₄₂ and C₃N nanodots at various concentrations (e.g., 100, 200, 300, 400, and 500 µg/mL). A control group with medium solution and experimental groups with 50 µM Aβ₄₂ peptide solution and 500 µg/mL C₃N nanodots solution were analyzed. The culture solutions were incubated at 4°C for 24 hours and then added to cells for another 24 hours at 5% CO₂ humidified environment 37°C.

For the CCK-8 assay, the diluted CCK-8 solution was added to the cells and incubated in 5% CO₂ at 37°C for 30 minutes. The optical density was measured at 450 nm on a microplate reader (BioTek, USA). Cell viability of the control group was set to 100%, and cell viability of other groups was calculated by comparison to the control group.

The LDH assay was performed according to LDH cytotoxicity assay kit instructions. A group of cells treated with 1% Triton X-100 was added as a positive control; the cell-free group was the negative control. Optical density at 490 nm was measured on a microplate reader and the cytotoxicity of each group was calculated according to:

Cytotoxicity (%) = (Test Sample - Negative Control) / (Positive Control - Negative Control) × 100% (1)

For the Live/Dead assay, the prepared dye was incubated with cells for 15 minutes according to the Live/Dead kit instructions. Cells were then photographed under a fluorescence microscope (Leica, Germany), and live vs. dead cells were counted using Image J software.

Cells were planted on cell culture slides, washed twice with PBS, and fixed overnight with 2.5% glutaraldehyde at 4°C for morphological observation. Twenty-four hours later, they were washed 3x with ultrapure water for 5 minutes each. Then, 30%, 50%, 70%, 80%, 90%, 95%, and 100% ethanol dehydration occurred in sequence for 10 minutes. Gold was then sprayed on the surface of the sample, and cell morphology was observed using a scanning electron microscope (SEM, Zeiss, Germany).

Animals and drug treatment

APP/PS1 [B6C3-Tg (APPswePSEN1dE9)/Nju] double transgenic AD mice and C57BL/6 mice were used in this study (Nanjing Model Animal Research Center, Nanjing, China). All experiments were reviewed and approved by the Animal Ethics Committee of Soochow University. APP/PS1 mice were produced and maintained on a C57BL/6 hybrid background with free access to chow and drinking water under a 12 hour light/dark cycle under constant temperature (22 ± 1°C) and humidity (40‒70%).

APP/PS1 mice were randomly divided into three groups. The positive control group was intraperitoneally injected with vehicle (saline; APP/PS1 group). The other two groups were injected intraperitoneally with either 1 mg/kg or 5 mg/kg C₃N nanodots solution. Littermate wild-type mice treated with saline solution were used as negative controls (WT group). Drugs were given once per day from 3 months of age for six months.

Tissue preparations

After behavioral tests, each group of mice was subdivided into two additional groups. In the first group, mice were subjected to cardiac perfusion under deep anesthesia and perfused with PBS and 4% paraformaldehyde (PFA, 158127, Sigma Aldrich) dehydrated with sucrose. In the second group, mouse brains were harvested by decapitation, then quickly placed in ‒80°C for the extraction of brain proteins.

Western blotting analysis

Tissues at ‒80°C were homogenized in cold lysis buffer (P0013C, Beyotime) containing protease inhibitor cocktail (4693116001, Roche). The supernatants were incubated at 100°C for 10 min. Each protein (15 µg) was separated by electrophoresis using a 12% SDS-PAGE gel (P0692, Beyotime) and transferred onto a PVDF membrane (ipvh00010, Millipore). The membranes were blocked by incubation with 5% non-fat milk (wt/vol) in Tris-buffered saline containing 0.1% Tween-20 (vol/vol) (TBST) for 60 minutes at 25°C. The membranes were then incubated with primary antibody to synaptosomal-associated 25 KD protein (SNAP25, 1:2000, 111-002, Synaptic Systems), antibody to vesicle-associated membrane protein 2 (VAMP2, 1:1000, ab3347, Abcam), and antibody to β-actin (1:5 000, bs1002, Bioworld technology) overnight at 4°C. The membranes were washed thrice in TBST for 5 minutes and incubated with HRP–conjugated IgG secondary antibody (1:5,000, Jackson ImunoResearch) for 2 hours at room temperature. The membranes were washed in TBST (3 × 5 minutes) before a 2-hour incubation with HRP-linked secondary antibodies to rabbit or mouse accordingly at room temperature. The membranes were then visualized using chemiluminescence on ECL Plus, and the densitometric quantifications were analyzed by Image J software.

Behavioral analysis

Spatial learning and memory performance were tested using the MWM task and the novel object recognition test. The Morris water maze was conducted with minor adjustments as previously described⁴⁴, which was conducted in a circular pool (120 cm diameter) divided into four quadrants. In the center of the third quadrant (i.e., the target quadrant), a circular platform (i.e., survival platform) with a diameter of 10 cm was placed just below the water surface (1 centimeter). Mice were trained four times a day for the first five days, with quadrant one as the water entry point. The time for mice to find the survival platform within 60 seconds was recorded. On the sixth day, the survival platform was removed, and the time spent in each quadrant and locomotion of the mice were recorded.

For the novel object recognition test⁴⁵, a cube (side length of 50 cm) was used, and two identical objects (i.e., old objects) were placed symmetrically at a position 10 cm from the sidewall. Mice were placed with their backs to the objects from the perpendicular bisector of the two objects, and the exploration time of the mice was recorded for 7 minutes. Before placing the next mice, the chamber was cleaned with 75% ethanol. The mice were trained for three days. On the fourth day, one of the old objects was replaced with a novel object and the exploration time and path were recorded. The results are represented by the novel object recognition index (RI), which was calculated as follows:

RI = (time to explore the new object)/ (time to explore the new object + time to explore the old object) × 100% (2)

Data acquisition utilized detection and analysis software of Shanghai Xinsoft Information Technology Co., Ltd.

Immunohistochemistry

Immunohistochemistry was performed as previously described^{46, 47}. After sucrose dehydration, brain tissue was embedded with optimal cutting temperature compound (OTC, 4583, SAKURA) and sliced into 15 µm sections (CM1950, Leica, Germany). Anti-6E10 (1:500, Covance) was used to examine the extracellular Aβ deposits, anti-MAP2 (1:1000, Millipore) and anti-SNAP25 (1:500, Synaptic Systems) were used to detect dysfunction in neuronal networks. Brian sections were stained with primary antibodies overnight at 4°C in a humid chamber, after being washed in PBS, followed by 2 hours of incubation of Cy3-conjugated (Jackson ImmunoResearch) or/and 488-conjugated (Jackson ImmunoResearch) secondary antibodies in the dark at room temperature. Fluorescent images were acquired using a fluorescence microscope (Leica, Germany) or a confocal microscope (FV1200, Olympus, Japan) following coverslipping. The number and the area of senile plaques were quantitatively analyzed by Image J software. For histopathology of major organs, the heart, liver, kidney, spleen, lung, and kidney were isolated and stained with an H&E staining kit (ab245880, Abcam).

Aβ₄₀/Aβ₄₂ Quantification

Aβ₄₀/Aβ₄₂ content was measured using enzyme-linked immunosorbent assay (ELISA) according to the previous reports¹¹. The right hemisphere was weighed and homogenized in TBS (pH 7.4, 1:12, w/v) containing a complete protease inhibitor cocktail and centrifuged. Afterward, the precipitation was centrifuged in 2% SDS and 70% formic acid. The FA-soluble fraction was neutralized with 1 M Tris (pH 11.0) and then diluted with PBS. TBS-soluble and SDS-soluble fractions were directly diluted with PBS. Quantitation was performed according to the instructions using a Human Aβ₄₀/Aβ₄₂ Elisa Kit (E-EL-H0542/ E-EL-M0068km, Elabscience Biotechnology). The optical density of the samples was measured with a microplate reader (BioTek, USA) at 450 nm wavelength, and the content of Aβ₄₀/Aβ₄₂ in the brain was calculated as moles per gram of wet tissue.

Statistical analysis

All results are expressed as mean ± standard deviation (SD) from at least three independent experiments. Statistical analyses conducted using GraphPad PRISM (version 9.0). Datasets with only two independent groups were analyzed for statistical significance using unpaired, two-tailed Student’s t test or Mann-Whitney test. Datasets with more than two groups were analyzed using one-way ANOVA, followed by Bonferroni or Tukey post hoc test. Datasets with two independent factors were analyzed using two-way ANOVA, followed by Bonferroni post hoc test. All p values below or equal to 0.05 were considered significant. * p＜0.05, ** p＜0.01, and *** p＜0.001.

Simulation model system setup

The C₃N used in the simulations had a diameter of ~ 4.5 nm corresponding to the average diameter of C₃N measured in the experiments (Figure S8). The initial Aβ₄₂ peptide crystal structure was taken from RCSB Protein Data Bank (PDB ID: 1Z0Q)⁴⁸ (Figure S8). To investigate the effect of C₃N on Aβ₄₂ aggregation, two Aβ₄₂ peptides were simulated in the absence or presence of C₃N. In the system without C₃N (control system), two peptides were solvated into a 9.6 nm × 9.1 nm × 6.5 nm water box containing 17,911 water molecules. The “peptides + C₃N” system was derived from its counterpart, by randomly adding a C₃N with a minimum distance of 1.5 nm to any heavy atom of the peptide. Then, two Aβ₄₂ peptides + C₃N were solvated into a water box (9.6 nm × 9.1 nm × 8.2 nm) containing 22,604 water molecules. Na⁺ and Cl^‒ ions were added to the solvent to neutralize systems and mimic the physiological conditions of 0.15 mol/L NaCl. The detailed illustration of the initial system is shown in Figure S7.

MD Simulations

The MD simulations were carried out using the GROMACS-4.6.6⁴⁹ software package with AMBER99SB-ILDN force field⁵⁰. The VMD software was adopted to visualize the trajectories and configurations of the MD simulations⁵¹. The TIP3P water model was adopted for solvent molecules⁵². Long-range electrostatic interactions were conducted with the particle mesh Ewald method⁵³. The van der Waals (vdW) interactions were calculated with a smooth cutoff distance of 1.2 nm. Each solvated system was first minimized using the conjugate gradient method and succeeded by a 10 ns NPT relaxation at 300 K and 1 bar. During production runs, the simulation temperature and pressure were fixed at 300 K and 1 bar with the v-rescale thermostat and Parrinello − Rahman coupling scheme^{54, 55}, respectively. A time step of 2.0 fs was used, and coordinates were collected every 20 ps. For each system, three independent 1000 ns trajectories were collected for the analysis. Periodic boundary conditions were introduced in all directions. All solute bonds were constrained at their equilibrium values by employing the LINCS algorithm⁵⁶, and water geometry was constrained with the SETTLE algorithm⁵⁷.

Acknowledgments

We would like to thank Taimoor Khan for critical reading of the manuscript. The authors also acknowledge support from the National Key Research and Development Program of China (2021YFA1201201 and 2021YFF1200404), the National MCF Energy R&D Program of China (2018YFE0306105), the National Key R&D Program of China (2020YFA0406104, 2020YFA0406101), the Innovative Research Group Project of the National Natural Science Foundation of China (51821002), the National Natural Science Foundation of China (U1967217, 22176137, 51725204, 21771132, 51972216, and 52041202), the National Independent Innovation Demonstration Zone Shanghai Zhangjiang Major Projects (ZJZX2020014), the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (20KJA150010), the Starry Night Science Fund at Shanghai Institute for Advanced Study of Zhejiang University (SN-ZJU-SIAS-003), and BirenTech Research (BR-ZJU-SIAS-001). The authors are also grateful for Carbon-based Functional Materials and Devices, Institute of Functional Nano and Soft Materials Natural Science Foundation of Jiangsu Province (BK20190041), Key−Area Research and Development Program of GuangDong Province (2019B010933001), and the Collaborative Innovation Center of Suzhou Nano Science & Technology, the 111 Project, and Suzhou Key Laboratory of Functional Nano & Soft Materials.

Author contributions

R.Z. Z.Y. and Z.K. conceived and designed the research. X.W., M.Z. and Z.K. synthesized the title material and characterization. X.Y., J.S., and S.L. carried out the molecular, cellular, and animal experiments and analyzed data. H.Z., and Z.Y. performed MD simulations and data analysis. Z.Y., X.Y., Z.K., and R.Z. co-wrote the paper. All authors discussed and commented on the manuscript.

Competing interests

The authors declare no competing interests.

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C3N Nanodots Impede Aβ Peptides Aggregation Pathogenic Path in Alzheimer's Disease

Status:

Journal Publication

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Abstract

Figures

Introduction

Results And Discussion

C3N nanodots inhibit Aβ42 peptides fibrillization in vitro

C3N-nanodots alleviate neuron cytotoxicity induced by Aβ42 peptides and demonstrate superior cytocompatibility

C3N-nanodots improve the learning and spatial memory capabilities of APP/PS1 mice with limited biotoxicity

In vivo efficacy of C3N nanodots against amyloid pathology

C3N nanodots improve the level of synaptic function-related proteins in vivo

Conclusion

Methods And Materials

Preparation of C3N nanodots and characterizations

Preparation of Aβ42 peptides

Thioflavin-T (ThT) Assay

Dot blot assay

Atomic Force Microscope (AFM)

Transmission Electron Microscopy (TEM)

Circular Dichroism (CD) Spectroscopy

Primary neuron culture

Primary astrocyte cultures

Cell viability assay and morphology observation

Animals and drug treatment

Tissue preparations

Western blotting analysis

Behavioral analysis

Immunohistochemistry

Aβ40/Aβ42 Quantification

Statistical analysis

Simulation model system setup

MD Simulations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1

C₃N nanodots inhibit Aβ₄₂ peptides fibrillization in vitro

C₃N-nanodots alleviate neuron cytotoxicity induced by Aβ₄₂ peptides and demonstrate superior cytocompatibility

C₃N-nanodots improve the learning and spatial memory capabilities of APP/PS1 mice with limited biotoxicity

In vivo efficacy of C₃N nanodots against amyloid pathology

C₃N nanodots improve the level of synaptic function-related proteins in vivo

Preparation of C₃N nanodots and characterizations

Preparation of Aβ₄₂ peptides

Aβ₄₀/Aβ₄₂ Quantification