Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pcbi.1003504
Title: Quantitative Protein Localization Signatures Reveal an Association between Spatial and Functional Divergences of Proteins
Authors: Loo L.-H. 
Laksameethanasan D.
Tung Y.-L.
Keywords: article
budding
cell compartmentalization
cell organelle
cellular distribution
comparative study
computer analysis
evolution
image analysis
intracellular space
microscopy
nonhuman
protein analysis
protein function
protein localization
Protein Localization Analysis and Search Tool
protein structure
qualitative analysis
quantitative analysis
Saccharomyces cerevisiae
Algorithms
Automation
Computational Biology
Databases, Protein
Green Fluorescent Proteins
Image Processing, Computer-Assisted
Internet
Microscopy, Fluorescence
Models, Statistical
Open Reading Frames
Proteins
Saccharomyces cerevisiae
Software
Issue Date: 2014
Citation: Loo L.-H., Laksameethanasan D., Tung Y.-L. (2014). Quantitative Protein Localization Signatures Reveal an Association between Spatial and Functional Divergences of Proteins. PLoS Computational Biology 10 (3) : e1003504. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pcbi.1003504
Rights: Attribution 4.0 International
Abstract: Protein subcellular localization is a major determinant of protein function. However, this important protein feature is often described in terms of discrete and qualitative categories of subcellular compartments, and therefore it has limited applications in quantitative protein function analyses. Here, we present Protein Localization Analysis and Search Tools (PLAST), an automated analysis framework for constructing and comparing quantitative signatures of protein subcellular localization patterns based on microscopy images. PLAST produces human-interpretable protein localization maps that quantitatively describe the similarities in the localization patterns of proteins and major subcellular compartments, without requiring manual assignment or supervised learning of these compartments. Using the budding yeast Saccharomyces cerevisiae as a model system, we show that PLAST is more accurate than existing, qualitative protein localization annotations in identifying known co-localized proteins. Furthermore, we demonstrate that PLAST can reveal protein localization-function relationships that are not obvious from these annotations. First, we identified proteins that have similar localization patterns and participate in closely-related biological processes, but do not necessarily form stable complexes with each other or localize at the same organelles. Second, we found an association between spatial and functional divergences of proteins during evolution. Surprisingly, as proteins with common ancestors evolve, they tend to develop more diverged subcellular localization patterns, but still occupy similar numbers of compartments. This suggests that divergence of protein localization might be more frequently due to the development of more specific localization patterns over ancestral compartments than the occupation of new compartments. PLAST enables systematic and quantitative analyses of protein localization-function relationships, and will be useful to elucidate protein functions and how these functions were acquired in cells from different organisms or species. A public web interface of PLAST is available at http://plast.bii.a-star.edu.sg. © 2014 Loo et al.
Source Title: PLoS Computational Biology
URI: https://scholarbank.nus.edu.sg/handle/10635/161612
ISSN: 1553734X
DOI: 10.1371/journal.pcbi.1003504
Rights: Attribution 4.0 International
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