title: PaxDb, a database of protein abundance averages across all three domains of life.
abstract: Although protein expression is regulated both temporally and spatially, most proteins have an intrinsic, "typical" range of functionally effective abundance levels. These extend from a few molecules per cell for signaling proteins, to millions of molecules for structural proteins. When addressing fundamental questions related to protein evolution, translation and folding, but also in routine laboratory work, a simple rough estimate of the average wild type abundance of each detectable protein in an organism is often desirable. Here, we introduce a meta-resource dedicated to integrating information on absolute protein abundance levels; we place particular emphasis on deep coverage, consistent post-processing and comparability across different organisms. Publicly available experimental data are mapped onto a common namespace and, in the case of tandem mass spectrometry data, re-processed using a standardized spectral counting pipeline. By aggregating and averaging over the various samples, conditions and cell-types, the resulting integrated data set achieves increased coverage and a high dynamic range. We score and rank each contributing, individual data set by assessing its consistency against externally provided protein-network information, and demonstrate that our weighted integration exhibits more consistency than the data sets individually. The current PaxDb-release 2.1 (at http://pax-db.org/) presents whole-organism data as well as tissue-resolved data, and covers 85,000 proteins in 12 model organisms. All values can be seamlessly compared across organisms via pre-computed orthology relationships.
authors.affiliation: Institute of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland.
authors.forename: M
authors.initials: M
authors.lastname: Wang
authors.forename: M
authors.initials: M
authors.lastname: Weiss
authors.forename: M
authors.initials: M
authors.lastname: Simonovic
authors.forename: G
authors.initials: G
authors.lastname: Haertinger
authors.forename: S P
authors.initials: SP
authors.lastname: Schrimpf
authors.forename: M O
authors.initials: MO
authors.lastname: Hengartner
authors.forename: C
authors.initials: C
authors.lastname: von Mering
mesh_terms: D000818:Animals; D017360:Arabidopsis / Q000235:genetics / Q000378:metabolism; D001419:Bacteria / Q000235:genetics / Q000378:metabolism; D001426:Bacterial Proteins / Q000235:genetics / Q000378:metabolism; D030562:Databases, Protein; D006801:Humans; D020407:Internet; D010940:Plant Proteins / Q000235:genetics / Q000378:metabolism; D020543:Proteome / Q000235:genetics / Q000378:metabolism*; D040901:Proteomics / Q000706:statistics & numerical data*; D012441:Saccharomyces cerevisiae / Q000235:genetics / Q000378:metabolism; D029701:Saccharomyces cerevisiae Proteins / Q000235:genetics / Q000378:metabolism; D013045:Species Specificity; D053719:Tandem Mass Spectrometry; D059467:Transcriptome / Q000235:genetics
chemical_list: D001426:Bacterial Proteins; D010940:Plant Proteins; D020543:Proteome; D029701:Saccharomyces cerevisiae Proteins