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Cited by 373Alzheimer's disease research and treatmentsNanoparticle-Based Drug DeliveryGold and Silver Nanoparticles Synthesis and Applications

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Chiral gold nanoparticles enantioselectively rescue memory deficits in a mouse model of Alzheimer’s disease

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Hou, Ke, Zhao, Jing, Wang, Hui, Li, Bin, Li, Kexin, Shi, Xinghua, Wan, Kaiwei, Ai, Jing, Lv, Jiawei, Wang, Dawei, Huang, Qunxing, Wang, Huayi, Cao, Qin, Liu, Shaoqin, Tang, Zhiyong·2020·Nature Communications
DOI 10.1038/s41467-020-18525-2PMC PMC7509831
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Abstract

Preventing aggregation of amyloid beta (Aβ) peptides is a promising strategy for the treatment of Alzheimer's disease (AD), and gold nanoparticles have previously been explored as a potential anti-Aβ therapeutics. Here we design and prepare 3.3 nm L- and D-glutathione stabilized gold nanoparticles (denoted as L3.3 and D3.3, respectively). Both chiral nanoparticles are able to inhibit aggregation of Aβ42 and cross the blood-brain barrier (BBB) following intravenous administration without noticeable toxicity. D3.3 possesses a larger binding affinity to Aβ42 and higher brain biodistribution compared with its enantiomer L3.3, giving rise to stronger inhibition of Aβ42 fibrillation and better rescue of behavioral impairments in AD model mice. This conjugation of a small nanoparticle with chiral recognition moiety provides a potential therapeutic approach for AD.

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Fig. 1 Effect of L3.3, D3.3, and C3.5 on Aβ42 fibrillization in vitro. a ThT fluorescence assay of Aβ42 in the absence and presence of 3.3-nm L-GSH capped Au nanoparticles (denoted as Aβ42 + L3.3), 3.3 nm D-GSH capped Au nanoparticles (abbreviated as Aβ42 + D3.3), or 3.5 nm citrate-capped Au nanoparticles (denoted as Aβ42 + C3.5). The fibrillation kinetics is fitted with a sigmoidal function. b CD spectra of Aβ42 (40 μM) in the absence and presence of L3.3, D3.3, or C3.5 (110 nM) after co-incubation for 48 h. c Analysis of protein secondary structure. d AFM images of Aβ42 (40 μM) in the absence and presence of L3.3, D3.3, or C3.5 (110 nM) after co-incubation for 48 h. Scale bars, 1 μm. e TEM images of Aβ42 (40 μM) in the absence and presence of L3.3, D3.3, or C3.5 (110 nM) after co-incubation for 48 h. Scale bars, 200 nm. Error bars indicate the s.d. (n = 3 independent samples). *P < 0.05, **P < 0.01, ***P < 0.001, two-sided Student’s t test. For detailed statistical analysis see Supplementary Tables 6 and 7. Source data are provided as a Source Data file.
Fig. 1 Effect of L3.3, D3.3, and C3.5 on Aβ42 fibrillization in vitro. a ThT fluorescence assay of Aβ42 in the absence and presence of 3.3-nm L-GSH capped Au nanoparticles (denoted as Aβ42 + L3.3), 3.3 nm D-GSH capped Au nanoparticles (abbreviated as Aβ42 + D3.3), or 3.5 nm citrate-capped Au nanoparticles (denoted as Aβ42 + C3.5). The fibrillation kinetics is fitted with a sigmoidal function. b CD spectra of Aβ42 (40 μM) in the absence and presence of L3.3, D3.3, or C3.5 (110 nM) after co-incubation for 48 h. c Analysis of protein secondary structure. d AFM images of Aβ42 (40 μM) in the absence and presence of L3.3, D3.3, or C3.5 (110 nM) after co-incubation for 48 h. Scale bars, 1 μm. e TEM images of Aβ42 (40 μM) in the absence and presence of L3.3, D3.3, or C3.5 (110 nM) after co-incubation for 48 h. Scale bars, 200 nm. Error bars indicate the s.d. (n = 3 independent samples). *P < 0.05, **P < 0.01, ***P < 0.001, two-sided Student’s t test. For detailed statistical analysis see Supplementary Tables 6 and 7. Source data are provided as a Source Data file.CC BY · PubMed Central
Fig. 2 Analysis of interaction between L3.3/D3.3 and Aβ42 monomer. a, b Typical ITC data for titration of Aβ42 (0.138 mM) into solution of L3.3 (1.5 μM) (a) and D3.3 (1.5 μM) (b) at 25 °C. (Upper) raw data and (lower) integrated data. The solid curves represent the best-fit results using a one-site binding model. The experiment was repeated for three times. c Summary of binding stoichiometry n0, binding constant K, enthalpy changes ΔH, entropy changes ΔS, and Gibbs free energy changes ΔG of binding process of Aβ42 monomer on L3.3 (a) and D3.3 (b). Error bars indicate mean ± s.d. *P < 0.05, two-sided Student’s t test. For detailed statistical analysis see Supplementary Table 7. d, e The most stable structures of Aβ17-36 with l- (d) and d-GSH-coated Au (111) surface (e) obtained from molecular docking simulation (atom color: C, gray; H, white; N, blue; O, red; S, green; Au, yellow). Green dotted lines represent hydrogen bonding. Source data are provided as a Source Data file.
Fig. 2 Analysis of interaction between L3.3/D3.3 and Aβ42 monomer. a, b Typical ITC data for titration of Aβ42 (0.138 mM) into solution of L3.3 (1.5 μM) (a) and D3.3 (1.5 μM) (b) at 25 °C. (Upper) raw data and (lower) integrated data. The solid curves represent the best-fit results using a one-site binding model. The experiment was repeated for three times. c Summary of binding stoichiometry n0, binding constant K, enthalpy changes ΔH, entropy changes ΔS, and Gibbs free energy changes ΔG of binding process of Aβ42 monomer on L3.3 (a) and D3.3 (b). Error bars indicate mean ± s.d. *P < 0.05, two-sided Student’s t test. For detailed statistical analysis see Supplementary Table 7. d, e The most stable structures of Aβ17-36 with l- (d) and d-GSH-coated Au (111) surface (e) obtained from molecular docking simulation (atom color: C, gray; H, white; N, blue; O, red; S, green; Au, yellow). Green dotted lines represent hydrogen bonding. Source data are provided as a Source Data file.CC BY · PubMed Central
Fig. 3 Inhibition effect of L3.3 and D3.3 on Aβ42-induced neuronal death. a Cell toxicity of Aβ42 (40 μM) in the absence and presence of L3.3 and D3.3 (110 nM). b Bright-field and confocal fluorescence images of SH-SY5Y cells treated with Aβ42 (40 μM) in the absence and presence of L3.3 and D3.3 (110 nM) for 48 h. Scale bars, 50 μm. c Population of apoptosis cells summarized from flow cytometry analysis. d Flow cytogram representing apoptosis assay based on annexin V-fluorescein isothiocyanate (Annexin V-FITC)/propidium iodide (PI) staining of SH-SY5Y cells after treatment with different therapeutic groups for 48 h. Error bars indicate the s.d. (n = 3 independent samples). **P < 0.01; ***P < 0.001; NS not significant; one-way ANOVA, followed by Holm-Sidak post hoc test. For detailed statistical analysis see Supplementary Tables 6 and 7. Source data are provided as a Source Data file.
Fig. 3 Inhibition effect of L3.3 and D3.3 on Aβ42-induced neuronal death. a Cell toxicity of Aβ42 (40 μM) in the absence and presence of L3.3 and D3.3 (110 nM). b Bright-field and confocal fluorescence images of SH-SY5Y cells treated with Aβ42 (40 μM) in the absence and presence of L3.3 and D3.3 (110 nM) for 48 h. Scale bars, 50 μm. c Population of apoptosis cells summarized from flow cytometry analysis. d Flow cytogram representing apoptosis assay based on annexin V-fluorescein isothiocyanate (Annexin V-FITC)/propidium iodide (PI) staining of SH-SY5Y cells after treatment with different therapeutic groups for 48 h. Error bars indicate the s.d. (n = 3 independent samples). **P < 0.01; ***P < 0.001; NS not significant; one-way ANOVA, followed by Holm-Sidak post hoc test. For detailed statistical analysis see Supplementary Tables 6 and 7. Source data are provided as a Source Data file.CC BY · PubMed Central
Fig. 4 Biodistribution and toxicity evaluation of L3.3 and D3.3 in vivo. a, b Biodistribution of L3.3 and D3.3 in the brain (a) and blood (b) at 6 h, 12 h, 24 h, and 48 h post-injection. Error bars indicate the s.d. (n = 4 mice per group). *P < 0.05; NS not significant; two-sided Student’s t test. For detailed statistical analysis see Supplementary Tables 6 and 7. c Elimination kinetics of L3.3 and D3.3 in plasma. The concentration-time profiles of L3.3 and D3.3 in plasma (b) fit the first-order elimination. The fitting equation for L3.3 and D3.3 groups is y = 1.396 − 0.0211x (r2 = 0.992) and y = 1.43758 − 0.0203x (r2 = 0.989), respectively. d Hematological parameters, including red blood cells (RBC), hemoglobin (HGB), platelets (PLT), and white blood cells (WBC) of the KM mice after treatment with L3.3 or D3.3 for 6 h, 12 h, 24 h, and 48 h. The shadow regions represent the normal range of control groups. Error bars indicate the s.d. (n = 3 mice per group). For detailed statistical analysis see Supplementary Table 6. e H&E staining assays of the heart, liver, spleen, lung, and kidney from all experimental groups (n = 2 mice per group). Scale bars, 100 μm. Source data are provided as a Source Data file.
Fig. 4 Biodistribution and toxicity evaluation of L3.3 and D3.3 in vivo. a, b Biodistribution of L3.3 and D3.3 in the brain (a) and blood (b) at 6 h, 12 h, 24 h, and 48 h post-injection. Error bars indicate the s.d. (n = 4 mice per group). *P < 0.05; NS not significant; two-sided Student’s t test. For detailed statistical analysis see Supplementary Tables 6 and 7. c Elimination kinetics of L3.3 and D3.3 in plasma. The concentration-time profiles of L3.3 and D3.3 in plasma (b) fit the first-order elimination. The fitting equation for L3.3 and D3.3 groups is y = 1.396 − 0.0211x (r2 = 0.992) and y = 1.43758 − 0.0203x (r2 = 0.989), respectively. d Hematological parameters, including red blood cells (RBC), hemoglobin (HGB), platelets (PLT), and white blood cells (WBC) of the KM mice after treatment with L3.3 or D3.3 for 6 h, 12 h, 24 h, and 48 h. The shadow regions represent the normal range of control groups. Error bars indicate the s.d. (n = 3 mice per group). For detailed statistical analysis see Supplementary Table 6. e H&E staining assays of the heart, liver, spleen, lung, and kidney from all experimental groups (n = 2 mice per group). Scale bars, 100 μm. Source data are provided as a Source Data file.CC BY · PubMed Central
Fig. 5 Effect of L3.3 and D3.3 on rescuing memory impairments in AD model mice. a Latency for escape to platform in the training phase. b Percentage (%) of time spent in the target quadrant in probe test. c Number of crossing platform time in probe test. Error bars indicate the s.d. (n = 6 mice per group). *P < 0.05; **P < 0.01; ***P < 0.001; NS not significant; one-way ANOVA, followed by Holm-Sidak post hoc test. For detailed statistical analysis see Supplementary Tables 6 and 7. d Track of probe test. e Immunofluorescence for Aβ in the hippocampus of WT control mice, AD control mice, AD mice with L3.3 or D3.3 treatment. Scale bars, 200 μm. f–i Soluble Aβ42 (f), insoluble Aβ42 (g), soluble Aβ40 (h), and insoluble Aβ40 (i) in the brains measured by ELISA. Error bars indicate the s.d. (n = 3 mice per group). *P < 0.05; **P < 0.01; ***P < 0.001; NS not significant; one-way ANOVA, followed by Holm-Sidak post hoc test. For detailed statistical analysis see Supplementary Tables 6 and 7. Source data are provided as a Source Data file.
Fig. 5 Effect of L3.3 and D3.3 on rescuing memory impairments in AD model mice. a Latency for escape to platform in the training phase. b Percentage (%) of time spent in the target quadrant in probe test. c Number of crossing platform time in probe test. Error bars indicate the s.d. (n = 6 mice per group). *P < 0.05; **P < 0.01; ***P < 0.001; NS not significant; one-way ANOVA, followed by Holm-Sidak post hoc test. For detailed statistical analysis see Supplementary Tables 6 and 7. d Track of probe test. e Immunofluorescence for Aβ in the hippocampus of WT control mice, AD control mice, AD mice with L3.3 or D3.3 treatment. Scale bars, 200 μm. f–i Soluble Aβ42 (f), insoluble Aβ42 (g), soluble Aβ40 (h), and insoluble Aβ40 (i) in the brains measured by ELISA. Error bars indicate the s.d. (n = 3 mice per group). *P < 0.05; **P < 0.01; ***P < 0.001; NS not significant; one-way ANOVA, followed by Holm-Sidak post hoc test. For detailed statistical analysis see Supplementary Tables 6 and 7. Source data are provided as a Source Data file.CC BY · PubMed Central

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Metadata

Authors
Hou, K., Zhao, J., Wang, H., Li, B., Li, K., Shi, X., Wan, K., Ai, J., Lv, J., Wang, D., Huang, Q., Wang, H., Cao, Q., Liu, S., & Tang, Z.
Affiliations
  • Peking University (CN)
  • Harbin Institute of Technology (CN)
  • National Center for Nanoscience and Technology (CN)
  • Sun Yat-sen University (CN)
  • Harbin Medical University (CN)
  • Howard Hughes Medical Institute (US)
Corresponding author
  • Liu, Shaoqin
  • Tang, Zhiyong
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2020-09-22
Volume
11
Issue
1
Pages
4790-4790
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-020-18525-2
PMC
PMC7509831
OpenAlex
W3088242221
Cited by
373
References
51
Citations by year
2026: 41 · 2025: 79 · 2024: 76 · 2023: 68 · 2022: 68 · 2021: 40 · 2020: 1
FWCI
26.62
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Griffith Research Online (submittedVersion, cc-by)
Funders
  • Howard Hughes Medical Institute
  • National Natural Science Foundation of China (2014CB931801, 21890381, 21721002, 21721002 and 21475029, 21890381, QYZDJ-SSW-SLH038, 21721002, 21475029, 2016YFA0200700, 51825202)
  • Chinese Academy of Sciences (2016YFA0200700, QYZDJ‐SSW‐SLH038, 21721002)
  • Peking University
  • K. C. Wong Education Foundation
  • National Science Fund for Distinguished Young Scholars (51825202)
Topics
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
  • Physical Sciences › Materials Science › Biomaterials › Nanoparticle-Based Drug Delivery
  • Physical Sciences › Materials Science › Electronic, Optical and Magnetic Materials › Gold and Silver Nanoparticles Synthesis and Applications
Keywords
gold nanoparticles, chiral nanoparticles, Alzheimer's disease, amyloid-beta 42, amyloid aggregation inhibition, enantiomers, blood-brain barrier penetration, brain biodistribution, memory impairment, anti-amyloid therapy, nanoparticle drug delivery
MeSH terms
Alzheimer Disease, Animals, Blood-Brain Barrier, Brain, Cell Survival, Disease Models, Animal, Gold, Male, Memory Disorders, Mice, Inbred C57BL, Peptide Fragments, Stereoisomerism, Amyloid beta-Peptides, Mice, Metal Nanoparticles, Molecular Docking Simulation

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