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Quantifying compartment-associated variations of protein abundance in proteomics data

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Item Type:Article
Title:Quantifying compartment-associated variations of protein abundance in proteomics data
Creators Name:Parca, L. and Beck, M. and Bork, P. and Ori, A.
Abstract:Quantitative mass spectrometry enables to monitor the abundance of thousands of proteins across biological conditions. Currently, most data analysis approaches rely on the assumption that the majority of the observed proteins remain unchanged across compared samples. Thus, gross morphological differences between cell states, deriving from, e.g., differences in size or number of organelles, are often not taken into account. Here, we analyzed multiple published datasets and frequently observed that proteins associated with a particular cellular compartment collectively increase or decrease in their abundance between conditions tested. We show that such effects, arising from underlying morphological differences, can skew the outcome of differential expression analysis. We propose a method to detect and normalize morphological effects underlying proteomics data. We demonstrate the applicability of our method to different datasets and biological questions including the analysis of sub-cellular proteomes in the context of Caenorhabditis elegans aging. Our method provides a complementary perspective to classical differential expression analysis and enables to uncouple overall abundance changes from stoichiometric variations within defined group of proteins.
Keywords:Cellular Compartment, Differential Expression, Linear Model, Organelle, Proteomics, Animals, Caenorhabditis elegans
Source:Molecular Systems Biology
ISSN:1744-4292
Publisher:EMBO Press
Volume:14
Number:7
Page Range:e8131
Date:2 July 2018
Official Publication:https://doi.org/10.15252/msb.20178131
PubMed:View item in PubMed

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