Differentiating α-synuclein aggregates using charge-sensitive gold nanoclusters

The accumulation of α-synuclein (α-syn) aggregates in the brain is associated with Parkinson's disease, making it a promising biomarker for understanding the disease's pathogenesis. Distinguishing between oligomeric forms of amyloidogenic proteins is crucial, as their toxicity depends on conformation. This study leverages surface charge differences to distinguish α-syn monomers from amyloids. We employed label-free gold nanoclusters (AuNCs) with distinct surface charges to differentiate between wild-type and mutant [A30P]-α-Syn based on their charge characteristics. Fluorescence spectroscopy and electrochemical measurements were performed to evaluate the sensitivity and interaction mechanisms. Our results show that Pro-AuNCs exhibit greater sensitivity towards monomeric forms of both wild-type and mutant α-Syn, while His-AuNCs are more sensitive to amyloid forms. Impedance spectroscopy shows a detection limit in the picomolar range (pM), which is twice as sensitive as fluorescence measurements. Cell culture studies further validate our <i>in vitro</i> findings, demonstrating the effective specificity of AuNCs for detecting different conformations of α-syn. Overall, our results indicate that this probe can successfully identify aggregated and monomeric forms of α-syn, suggesting its potential for developing sensors aimed at understanding the etiology of Parkinson's disease.

Authors

Institutions

Publication Details

Journal
Nanoscale
Published
2025-01-01
DOI
https://doi.org/10.1039/d5nr00887e
Citations
1
Primary Topic
Nanocluster Synthesis and Applications
Type
article
Field-Weighted Citation Impact
0.52

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Differentiating α-synuclein aggregates using charge-sensitive gold nanoclusters

Sharmistha Sinha, Arpit Tyagi, Indu Sharma, Harpreet Kaur et al.
1 citations
Nanoscale
Nanocluster Synthesis and Applications
0.52
article

Differentiating α-synuclein aggregates using charge-sensitive gold nanoclusters

Sharmistha Sinha, Arpit Tyagi, Indu Sharma, Harpreet Kaur, Deepak Sharma
article en
1 citations

Abstract

The accumulation of α-synuclein (α-syn) aggregates in the brain is associated with Parkinson's disease, making it a promising biomarker for understanding the disease's pathogenesis. Distinguishing between oligomeric forms of amyloidogenic proteins is crucial, as their toxicity depends on conformation. This study leverages surface charge differences to distinguish α-syn monomers from amyloids. We employed label-free gold nanoclusters (AuNCs) with distinct surface charges to differentiate between wild-type and mutant [A30P]-α-Syn based on their charge characteristics. Fluorescence spectroscopy and electrochemical measurements were performed to evaluate the sensitivity and interaction mechanisms. Our results show that Pro-AuNCs exhibit greater sensitivity towards monomeric forms of both wild-type and mutant α-Syn, while His-AuNCs are more sensitive to amyloid forms. Impedance spectroscopy shows a detection limit in the picomolar range (pM), which is twice as sensitive as fluorescence measurements. Cell culture studies further validate our <i>in vitro</i> findings, demonstrating the effective specificity of AuNCs for detecting different conformations of α-syn. Overall, our results indicate that this probe can successfully identify aggregated and monomeric forms of α-syn, suggesting its potential for developing sensors aimed at understanding the etiology of Parkinson's disease.

NanoscaleVol. 17(32)
Institute of Microbial Technology (IN), Institute of Nano Science and Technology, Academy of Scientific and Innovative Research (IN)
Indian Council of Medical Research, Council of Scientific and Industrial Research, India
Openalex Percentile: Top 36%
Nanocluster Synthesis and Applications
0.52
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.