Literature DB >> 24034606

Automated quantification of the subcellular localization of multicompartment proteins via Q-SCAn.

Nicholas C Bauer1, Anita H Corbett, Paul W Doetsch.   

Abstract

In eukaryotic cells, proteins can occupy multiple intracellular compartments and even move between compartments to fulfill critical biological functions or respond to cellular signals. Examples include transcription factors that reside in the cytoplasm but are mobilized to the nucleus as well as dual-purpose DNA repair proteins that are charged with simultaneously maintaining the integrity of both the nuclear and mitochondrial genomes. While numerous methods exist to study protein localization and dynamics, automated methods to quantify the relative amounts of proteins that occupy multiple subcellular compartments have not been extensively developed. To address this need, we present a rapid, automated method termed quantitative subcellular compartmentalization analysis (Q-SCAn). To develop this method, we exploited the facile molecular biology of the budding yeast, Saccharomyces cerevisiae. Individual subcellular compartments are defined by a fluorescent marker protein and the intensity of a target GFP-tagged protein is then quantified within each compartment. To validate Q-SCAn, we analyzed relocalization of the transcription factor Yap1 following oxidative stress and then extended the approach to multicompartment localization by examining two DNA repair proteins critical for the base excision repair pathway, Ntg1 and Ung1. Our findings demonstrate the utility of Q-SCAn for quantitative analysis of the subcellular distribution of multicompartment proteins.
© 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  Saccharomyces cerevisiae; automated; compartmentalization; fluorescence; image analysis; localization; mitochondria; nuclei; quantification

Mesh:

Substances:

Year:  2013        PMID: 24034606      PMCID: PMC3836439          DOI: 10.1111/tra.12118

Source DB:  PubMed          Journal:  Traffic        ISSN: 1398-9219            Impact factor:   6.215


  43 in total

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  2 in total

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  2 in total

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