SParQ

SParQ automates identification and quantification of punctate fluorescent vesicular structures in Fiji/ImageJ to support quantitative analysis of the endolysosomal system and protein homeostasis, including autophagy.


Key Features:

  • Automation: Automates quantification of punctate fluorescent structures within images.
  • Fiji/ImageJ integration: Operates as a plug-in within Fiji/ImageJ to perform analyses inside that image analysis environment.
  • User control and evaluation: Provides user oversight at critical stages of the quantification process to support accuracy and evaluation.
  • Large-dataset processing: Enables efficient processing of large imaging datasets.
  • Targeted vesicle quantification: Identifies and quantifies endosomes, autophagosomes, lysosomes, and model substrates labeled with fluorescent markers or fluorescent antibodies.

Scientific Applications:

  • Endolysosomal system analysis: Quantitative analysis of endosomes, autophagosomes, lysosomes, and model substrates in fluorescence microscopy images.
  • Protein homeostasis and transport: Studies of protein homeostasis and intracellular transport mechanisms relevant to cellular physiology.
  • Autophagy research: Comparative quantification in chaperone-mediated autophagy (CMA), macroautophagy (MA), and endosomal microautophagy (eMI).
  • Condition-based imaging studies: Quantification of vesicular structures across different experimental conditions using fluorescent markers or antibodies.

Methodology:

Identifies and quantifies punctate fluorescent structures within images via an automated Fiji/ImageJ plug-in workflow with user oversight at critical stages.

Topics

Details

Added:
1/14/2020
Last Updated:
11/24/2024

Operations

Publications

Mesquita A, Pereira J, Jenny A. Streamlined particle quantification (SParQ) plug-in is an automated fluorescent vesicle quantification plug-in for particle quantification in Fiji/ImageJ. Autophagy. 2019;16(9):1711-1717. doi:10.1080/15548627.2019.1695400. PMID:31752589. PMCID:PMC8386606.

PMID: 31752589
PMCID: PMC8386606
Funding: - American Heart Association: 18POST34030231 - NIH: GM119160