CoChat
Sign Up
Cited by 135Alzheimer's disease research and treatmentsExtracellular vesicles in diseaseNanoparticle-Based Drug Delivery

The DOI matches its Crossref record; 50 of the 50 references it cites were found in a registry or an index.

Fe65-engineered neuronal exosomes encapsulating corynoxine-B ameliorate cognition and pathology of Alzheimer’s disease

Open access
Iyaswamy, Ashok, Thakur, Abhimanyu, Guan, Xin-Jie, Krishnamoorthi, Senthilkumar, Fung, Tsz Yan, Lu, Kejia, Gaurav, Isha, Yang, Zhijun, Su, Cheng-Fu, Lau, Kwok-Fai, Zhang, Kui, Ng, Roy Chun-Laam, Lian, Qizhou, Cheung, King-Ho, Ye, Keqiang, Chen, Huanhuan Joyce, Li, Min·2023·Signal Transduction and Targeted Therapy
DOI 10.1038/s41392-023-01657-4PMC PMC10590775
Open this paper in CoChat — free accountOpen PDF

Abstract

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by the predominant impairment of neurons in the hippocampus and the formation of amyloid plaques, hyperphosphorylated tau protein, and neurofibrillary tangles in the brain. The overexpression of amyloid-β precursor protein (APP) in an AD brain results in the binding of APP intracellular domain (AICD) to Fe65 protein via the C-terminal Fe65-PTB2 interaction, which then triggers the secretion of amyloid-β and the consequent pathogenesis of AD. Apparently, targeting the interaction between APP and Fe65 can offer a promising therapeutic approach for AD. Recently, exosome, a type of extracellular vesicle with diameter around 30–200 nm, has gained much attention as a potential delivery tool for brain diseases, including AD, due to their ability to cross the blood–brain barrier, their efficient uptake by autologous cells, and their ability to be surface-modified with target-specific receptor ligands. Here, the engineering of hippocampus neuron cell-derived exosomes to overexpress Fe65, enabled the development of a novel exosome-based targeted drug delivery system, which carried Corynoxine-B (Cory-B, an autophagy inducer) to the APP overexpressed-neuron cells in the brain of AD mice. The Fe65-engineered HT22 hippocampus neuron cell-derived exosomes (Fe65-EXO) loaded with Cory-B (Fe65-EXO-Cory-B) hijacked the signaling and blocked the natural interaction between Fe65 and APP, enabling APP-targeted delivery of Cory-B. Notably, Fe65-EXO-Cory-B induced autophagy in APP-expressing neuronal cells, leading to amelioration of the cognitive decline and pathogenesis in AD mice, demonstrating the potential of Fe65-EXO-Cory-B as an effective therapeutic intervention for AD.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41392-023-01657-4

Cites

50 of 50 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig. 1 Development and characterization of Fe65-engineered exosomes. a Schematic diagram showing the steps involved in the production of engineered Fe65-EXO. Representative b, c immunofluorescence images showing expression of Fe65, d protein level of Fe65 in control- and Fe65 OE- HT22 hippocampus neuron cells. Representative e–g size distribution, h–j, k–m CD63-, and Fe65-positive immunogold dots, and their relative quantification, n, o protein level of Fe65 by n WB, and o dot-blot, and p zeta potential of exosomes isolated from control- and Fe65 OE- HT22 hippocampus neuron cells. In g, j, m, and p data are shown as mean ± standard error mean (SEM). Statistical analysis was performed by Student’s t-test to compare Control-EXO vs. Fe65-EXO. Significance level: **P < 0.01, NS not significant
Fig. 1 Development and characterization of Fe65-engineered exosomes. a Schematic diagram showing the steps involved in the production of engineered Fe65-EXO. Representative b, c immunofluorescence images showing expression of Fe65, d protein level of Fe65 in control- and Fe65 OE- HT22 hippocampus neuron cells. Representative e–g size distribution, h–j, k–m CD63-, and Fe65-positive immunogold dots, and their relative quantification, n, o protein level of Fe65 by n WB, and o dot-blot, and p zeta potential of exosomes isolated from control- and Fe65 OE- HT22 hippocampus neuron cells. In g, j, m, and p data are shown as mean ± standard error mean (SEM). Statistical analysis was performed by Student’s t-test to compare Control-EXO vs. Fe65-EXO. Significance level: **P < 0.01, NS not significantCC BY · PubMed Central
Fig. 2 Higher autologous uptake of Fe65-engineered exosomes by APP overexpressed hippocampus neuron cells. a–h Enhanced autologous uptake of Fe65-EXO by APP OE-HT22 cells compared with HT22 cells, and i–p enhanced heterologous uptake of Fe65-EXO by APP OE-N2a cells compared with N2a cells after 24 h. Nuclei: DAPI (blue), cell membrane: APP (red), Fe65-EXO: Green (green). EXO-APP (yellow). In a–p; scale bar = 10 µm. q, r Effect of Fe65-EXO on the viability of HT22- and N2a- neuron cells, respectively. HT22- and N2a- neuron cells were treated with cell culture medium (control), control EXO, or Fe65-EXO for 24 h, followed by the measurement of viability using MTT assay protocol. In q and r, data are shown as mean ± S.E.M (N = 6). Statistical analysis was performed by one-way ANOVA for multiple comparison of Vehicle Control vs. Control EXO or Fe65-EXO, Significance level: **P < 0.01, NS not significant
Fig. 2 Higher autologous uptake of Fe65-engineered exosomes by APP overexpressed hippocampus neuron cells. a–h Enhanced autologous uptake of Fe65-EXO by APP OE-HT22 cells compared with HT22 cells, and i–p enhanced heterologous uptake of Fe65-EXO by APP OE-N2a cells compared with N2a cells after 24 h. Nuclei: DAPI (blue), cell membrane: APP (red), Fe65-EXO: Green (green). EXO-APP (yellow). In a–p; scale bar = 10 µm. q, r Effect of Fe65-EXO on the viability of HT22- and N2a- neuron cells, respectively. HT22- and N2a- neuron cells were treated with cell culture medium (control), control EXO, or Fe65-EXO for 24 h, followed by the measurement of viability using MTT assay protocol. In q and r, data are shown as mean ± S.E.M (N = 6). Statistical analysis was performed by one-way ANOVA for multiple comparison of Vehicle Control vs. Control EXO or Fe65-EXO, Significance level: **P < 0.01, NS not significantCC BY · PubMed Central
Fig. 3 Delivery of Cory-B by Fe65-EXO caused BECN1-dependent augmented autophagy in neuronal cells. a, b Representative immunoblots depicting the protein level of autophagy markers (SQSTM1 and LC3B-II) in N2a cells, without and with pre-treatment of chloroquine (CQ, 100 μM), and the corresponding bar graphs. c, d Representative electron micrograph of N2a cells showing the formation of autolysosome and the corresponding bar graphs, respectively. Scale bar: 200 nm. In b and d, data are presented as mean ± SEM (N = 3). Statistical analysis was performed by one-way ANOVA with Dunnett’s multiple comparison test to compare Control vs. treatment groups. Significance level at *P < 0.05, **P < 0.01, and ***P < 0.001
Fig. 3 Delivery of Cory-B by Fe65-EXO caused BECN1-dependent augmented autophagy in neuronal cells. a, b Representative immunoblots depicting the protein level of autophagy markers (SQSTM1 and LC3B-II) in N2a cells, without and with pre-treatment of chloroquine (CQ, 100 μM), and the corresponding bar graphs. c, d Representative electron micrograph of N2a cells showing the formation of autolysosome and the corresponding bar graphs, respectively. Scale bar: 200 nm. In b and d, data are presented as mean ± SEM (N = 3). Statistical analysis was performed by one-way ANOVA with Dunnett’s multiple comparison test to compare Control vs. treatment groups. Significance level at *P < 0.05, **P < 0.01, and ***P < 0.001CC BY · PubMed Central
Fig. 4 Biodistribution of Fe65-EXO-Cory-B in the brain of AD mouse. Intravenously injected a control exosomes, b Fe65-EXO, c Cory-B, and d Fe65-EXO-Cory-B in 5xFAD mouse model. e Intraperitoneally injected Fe65-EXO-Cory-B in 5xFAD mouse model. The exosomes are labeled with Exo-Glow dye, and after its administration, AD mice were imaged at various times using the IVIS In Vivo Imaging System. f–j The quantitative time course bar graphs show the biodistribution of control-EXO, Fe65-EXO, Cory-B, and Fe65-EXO-Cory-B (i.v. or i.p.) in the brain of a 5xFAD mouse model. k–o Immunofluorescence staining showing colocalization of APP (shown in red) and exosomes (labeled with Exo-Green; shown in green) in the hippocampus region of brain of 5xFAD mouse model treated with control-EXO, Fe65-EXO, Cory-B, and Fe65-EXO-Cory-B (i.v. or i.p.), and p–t the corresponding fluorescence intensity of APP and Exo-Green, depicting the strength of their colocalization. In k–o, scale bar = 25 µm
Fig. 4 Biodistribution of Fe65-EXO-Cory-B in the brain of AD mouse. Intravenously injected a control exosomes, b Fe65-EXO, c Cory-B, and d Fe65-EXO-Cory-B in 5xFAD mouse model. e Intraperitoneally injected Fe65-EXO-Cory-B in 5xFAD mouse model. The exosomes are labeled with Exo-Glow dye, and after its administration, AD mice were imaged at various times using the IVIS In Vivo Imaging System. f–j The quantitative time course bar graphs show the biodistribution of control-EXO, Fe65-EXO, Cory-B, and Fe65-EXO-Cory-B (i.v. or i.p.) in the brain of a 5xFAD mouse model. k–o Immunofluorescence staining showing colocalization of APP (shown in red) and exosomes (labeled with Exo-Green; shown in green) in the hippocampus region of brain of 5xFAD mouse model treated with control-EXO, Fe65-EXO, Cory-B, and Fe65-EXO-Cory-B (i.v. or i.p.), and p–t the corresponding fluorescence intensity of APP and Exo-Green, depicting the strength of their colocalization. In k–o, scale bar = 25 µmCC BY · PubMed Central
Fig. 5 Fe65-EXO-Cory-B improves cognitive behavior in AD mice. a A schematic plan of the experiment showing the treatment schedule, followed by behavior experiments in 5xFAD mice. b Representative bar graph shows the time spent by the AD mice on the accelerating rotarod platform under various treatment conditions, as analyzed by rotarod test. c–e Analysis of general activity level, gross locomotor activity, and exploration habits of AD mice by open field test in a white Plexiglas box under various treatment conditions. Bar graphs d and e show the time spent by the AD mice in the margin and center of the Plexiglas box, based on the recorded tracks of the mice as shown in c. f Diagrammatic illustration of cued and contextual fear conditioning. g Representative graph showing freezing time of AD mice under various treatment conditions after the cue tone, as analyzed from the contextual fear conditioning. h Representative graph showing the escape latency of AD mice. i, j Analysis of spatial learning and memory in AD mice by Morris’s water maize (MWM) test under various treatment conditions. Representative i graph showing time spent by AD mice in target quadrant based on their swim paths or mouse trajectory j recorded in MWM. k, l Representative k electron microscopy images showing the formation of synapses (scale bar: 200 nm), and l the corresponding bar graph depicting the number of synapses formed in the hippocampus region of AD mouse brain under various treatment conditions. Data are presented as mean ± SEM (N = 6 mice/group). Statistical analysis was performed by one-way ANOVA with Dunnett’s multiple comparison test to compare Tg-Vehicle vs. treatment groups. Significance level at *P < 0.05, **P < 0.01, ***P < 0.001. Comparison of Tg-Vehicle vs. WT-Vehicle group. Significance level at #P < 0.05, ##P < 0.01, ###P < 0.001
Fig. 5 Fe65-EXO-Cory-B improves cognitive behavior in AD mice. a A schematic plan of the experiment showing the treatment schedule, followed by behavior experiments in 5xFAD mice. b Representative bar graph shows the time spent by the AD mice on the accelerating rotarod platform under various treatment conditions, as analyzed by rotarod test. c–e Analysis of general activity level, gross locomotor activity, and exploration habits of AD mice by open field test in a white Plexiglas box under various treatment conditions. Bar graphs d and e show the time spent by the AD mice in the margin and center of the Plexiglas box, based on the recorded tracks of the mice as shown in c. f Diagrammatic illustration of cued and contextual fear conditioning. g Representative graph showing freezing time of AD mice under various treatment conditions after the cue tone, as analyzed from the contextual fear conditioning. h Representative graph showing the escape latency of AD mice. i, j Analysis of spatial learning and memory in AD mice by Morris’s water maize (MWM) test under various treatment conditions. Representative i graph showing time spent by AD mice in target quadrant based on their swim paths or mouse trajectory j recorded in MWM. k, l Representative k electron microscopy images showing the formation of synapses (scale bar: 200 nm), and l the corresponding bar graph depicting the number of synapses formed in the hippocampus region of AD mouse brain under various treatment conditions. Data are presented as mean ± SEM (N = 6 mice/group). Statistical analysis was performed by one-way ANOVA with Dunnett’s multiple comparison test to compare Tg-Vehicle vs. treatment groups. Significance level at *P < 0.05, **P < 0.01, ***P < 0.001. Comparison of Tg-Vehicle vs. WT-Vehicle group. Significance level at #P < 0.05, ##P < 0.01, ###P < 0.001CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

Sorted by citations

See all 135

Related

See all

Metadata

Authors
Iyaswamy, A., Thakur, A., Guan, X.-J., Krishnamoorthi, S., Fung, T. Y., Lu, K., Gaurav, I., Yang, Z., Su, C.-F., Lau, K.-F., Zhang, K., Ng, R. C.-L., Lian, Q., Cheung, K.-H., Ye, K., Chen, H. J., & Li, M.
Affiliations
  • Hong Kong Baptist University (HK)
  • University of Chicago (US)
  • Chinese University of Hong Kong (HK)
  • Manchester Academic Health Science Centre (GB)
  • Guangzhou Women and Children Medical Center (CN)
  • Chinese Academy of Sciences (CN)
Corresponding author
  • Iyaswamy, Ashok
  • Thakur, Abhimanyu
  • Chen, Huanhuan Joyce
  • Li, Min
ORCID
Venue
Signal Transduction and Targeted Therapy
Publisher
Springer Science and Business Media LLC
Published
2023-10-23
Volume
8
Issue
1
Pages
404-404
ISSN
2059-3635 (ISSN-L)
DOI
10.1038/s41392-023-01657-4
PMC
PMC10590775
OpenAlex
W4387857159
Cited by
134
References
50
Citations by year
2026: 41 · 2025: 61 · 2024: 32
FWCI
23.80
Type
journal article
Language
en
Open access
Licence
Locations
  • Signal Transduction and Targeted Therapy (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Knowledge@UChicago (University of Chicago) (submittedVersion, cc-by-nc-nd)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Research Explorer (The University of Manchester) (submittedVersion, cc-by)
  • University of Chicago (cc-by)
Funders
  • Cancer Research Foundation
  • Lung Cancer Research Foundation
  • University of Chicago
  • Hong Kong Baptist University (IRCMS/19–20/H02, RC-IRCS-17-18/03, HKBU/RC-IRCs/17-18/03, HKBU-MPCF-003-2022-23)
  • Health and Medical Research Fund (HMRF/17182551, 17182541, HMRF17182541, 17182551, 09203776)
  • National Cancer Institute (R00CA226353, K99CA226353)
Topics
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Extracellular vesicles in disease
  • Physical Sciences › Materials Science › Biomaterials › Nanoparticle-Based Drug Delivery
Keywords
Alzheimer's disease, Fe65, amyloid precursor protein, exosome-based drug delivery, autophagy, hippocampal neurons, cognitive decline, amyloid plaques, tau hyperphosphorylation, extracellular vesicles
MeSH terms
Alzheimer Disease, Animals, Cognition, Indoles, Nerve Tissue Proteins, Neurons, Spiro Compounds, Amyloid beta-Protein Precursor, Mice, Exosomes

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review