title: Visual account of protein investment in cellular functions.
abstract: Proteomics techniques generate an avalanche of data and promise to satisfy biologists' long-held desire to measure absolute protein abundances on a genome-wide scale. However, can this knowledge be translated into a clearer picture of how cells invest their protein resources? This article aims to give a broad perspective on the composition of proteomes as gleaned from recent quantitative proteomics studies. We describe proteomaps, an approach for visualizing the composition of proteomes with a focus on protein abundances and functions. In proteomaps, each protein is shown as a polygon-shaped tile, with an area representing protein abundance. Functionally related proteins appear in adjacent regions. General trends in proteomes, such as the dominance of metabolism and protein production, become easily visible. We make interactive visualizations of published proteome datasets accessible at www.proteomaps.net. We suggest that evaluating the way protein resources are allocated by various organisms and cell types in different conditions will sharpen our understanding of how and why cells regulate the composition of their proteomes.
authors.affiliation: Institut für Biochemie, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany;Department of Plant Sciences, Weizmann Institute of Science, Rehovot 76100, Israel;
authors.forename: Wolfram
authors.initials: W
authors.lastname: Liebermeister
authors.affiliation: Department of Plant Sciences, Weizmann Institute of Science, Rehovot 76100, Israel;
authors.forename: Elad
authors.initials: E
authors.lastname: Noor
authors.affiliation: Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720; and.
authors.forename: Avi
authors.initials: A
authors.lastname: Flamholz
authors.affiliation: Department of Plant Sciences, Weizmann Institute of Science, Rehovot 76100, Israel;
authors.forename: Dan
authors.initials: D
authors.lastname: Davidi
authors.affiliation: Institute for Microbiology, Greifswald University, 17487 Greifswald, Germany ron.milo@weizmann.ac.il Joerg.Bernhardt@uni-greifswald.de.
authors.forename: Jörg
authors.initials: J
authors.lastname: Bernhardt
authors.affiliation: Department of Plant Sciences, Weizmann Institute of Science, Rehovot 76100, Israel; ron.milo@weizmann.ac.il Joerg.Bernhardt@uni-greifswald.de.
authors.forename: Ron
authors.initials: R
authors.lastname: Milo
mesh_terms: D030562:Databases, Protein; D004926:Escherichia coli / Q000166:cytology / Q000378:metabolism; D006801:Humans; D020407:Internet; D008954:Models, Biological; D009177:Mycoplasma pneumoniae / Q000166:cytology / Q000378:metabolism; D011506:Proteins / Q000032:analysis* / Q000145:classification / Q000378:metabolism; D020543:Proteome / Q000032:analysis* / Q000145:classification / Q000378:metabolism; D040901:Proteomics / Q000379:methods*; D012441:Saccharomyces cerevisiae / Q000166:cytology / Q000378:metabolism; D015398:Signal Transduction; D013045:Species Specificity
chemical_list: D011506:Proteins; D020543:Proteome
keywords: Voronoi treemap; cell resource allocation; cellular economy; functional classification; mass spectrometry