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Protein & Peptide Letters

Editor-in-Chief

ISSN (Print): 0929-8665
ISSN (Online): 1875-5305

Research Article

Flow Cytometric Analysis of Protein Aggregates

Author(s): Sushanta Debnath, Bikram Nath and Abhijit Chakrabarti*

Volume 24, Issue 10, 2017

Page: [969 - 973] Pages: 5

DOI: 10.2174/0929866524666170818155030

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Abstract

Background: Misfolding of proteins often leads to aggregation. Accumulation of diverse protein aggregates in various cells, tissue and organs is the hallmark of many diseases, such as Alzheimer's disease and Parkinson's disease.

Objectives: The main objective of this study was to present a novel method of characterization of protein aggregates, associated with differential toxicity with different size and composition in vitro using flow cytometry.

Methods: A Beckman Coulter Epics XL flow cytometer with argon ion laser operating at 488 nm was used for flow cytometry analysis. The voltage and the gain settings for individual channels were set at high voltage and gain for the detections of autofluorescence, fluorescence of adsorbed Congo red, forward scattering (FSC) and side scattering (SSC) intensities from the aggregates of proteins and nanoparticles. Each sample was analyzed to characterize and quantify the number of aggregates with a limit of maximum 20,000 events. The flow cytometry data were analyzed using Flowing software version 2.5.1 and Origin 8.0.

Results: Autofluorescence and scattering intensities could distinguish between amyloid and nonamyloid aggregates. Dot plots of both side scattering (SSC) and forward scattering (FSC) intensities also showed characteristic fingerprint of both the types of aggregates when compared with those of well known nanoparticles of oxides of Fe and Cu.

Conclusion: This work reports a novel, simple and robust flow cytometric method of characterization of protein aggregates of different size and composition which would find wider application in characterization of biomolecular aggregates, in general.

Keywords: Scattering intensity, autofluorescence, amyloid aggregates, nanoparticles, proteins, flow cytometer.

Graphical Abstract

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