AggreCount: an unbiased image analysis tool for identifying and quantifying cellular aggregates in a spatially defined manner

Autor: Jacob Aaron Klickstein, Sirisha Mukkavalli, Malavika Raman
Rok vydání: 2020
Předmět:
0301 basic medicine
Huntingtin
p97/valosin-containing protein
Protein aggregation
Biochemistry
Inclusion bodies
polyubiquitin chain
Image Processing
Computer-Assisted
protein misfolding
Inclusion Bodies
polyQ inclusion body
Chemistry
aggregation
Huntington disease
image-based analysis
Sodium Compounds
ImageJ
aggregate
Aggresome
Proteome
Puromycin
misfolded protein
microscopic imaging
Arsenites
amyotrophic lateral sclerosis (ALS) (Lou Gehrig disease)
inclusion body
Cytoplasmic Granules
stress granule
protein aggregation
Protein Aggregates
03 medical and health sciences
Stress granule
aggresome
ubiquitin
Humans
protein quality control
Molecular Biology
Adaptor Proteins
Signal Transducing
Fluorescent Dyes
proteostasis
030102 biochemistry & molecular biology
Amyotrophic Lateral Sclerosis
Aggregate (data warehouse)
Proteins
Cell Biology
030104 developmental biology
Proteostasis
Microscopy
Fluorescence
Biophysics
HeLa Cells
Zdroj: The Journal of Biological Chemistry
ISSN: 0021-9258
DOI: 10.1074/jbc.ra120.015398
Popis: Protein quality control is maintained by a number of integrated cellular pathways that monitor the folding and functionality of the cellular proteome. Defects in these pathways lead to the accumulation of misfolded or faulty proteins that may become insoluble and aggregate over time. Protein aggregates significantly contribute to the development of a number of human diseases such as amyotrophic lateral sclerosis, Huntington's disease, and Alzheimer's disease. In vitro, imaging-based, cellular studies have defined key biomolecular components that recognize and clear aggregates; however, no unifying method is available to quantify cellular aggregates, limiting our ability to reproducibly and accurately quantify these structures. Here we describe an ImageJ macro called AggreCount to identify and measure protein aggregates in cells. AggreCount is designed to be intuitive, easy to use, and customizable for different types of aggregates observed in cells. Minimal experience in coding is required to utilize the script. Based on a user-defined image, AggreCount will report a number of metrics: (i) total number of cellular aggregates, (ii) percentage of cells with aggregates, (iii) aggregates per cell, (iv) area of aggregates, and (v) localization of aggregates (cytosol, perinuclear, or nuclear). A data table of aggregate information on a per cell basis, as well as a summary table, is provided for further data analysis. We demonstrate the versatility of AggreCount by analyzing a number of different cellular aggregates including aggresomes, stress granules, and inclusion bodies caused by huntingtin polyglutamine expansion.
Databáze: OpenAIRE
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