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Article . 2014
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Automated Quantification of the Subcellular Localization of Multicompartment Proteins via Q‐SCAn

Authors: Nicholas C, Bauer; Anita H, Corbett; Paul W, Doetsch;

Automated Quantification of the Subcellular Localization of Multicompartment Proteins via Q‐SCAn

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.

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Keywords

Cell Nucleus, Cytoplasm, Saccharomyces cerevisiae Proteins, Green Fluorescent Proteins, Active Transport, Cell Nucleus, Saccharomyces cerevisiae, Recombinant Proteins, Automation, Microscopy, Fluorescence, DNA-(Apurinic or Apyrimidinic Site) Lyase, Uracil-DNA Glycosidase, Transcription Factors

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
bronze