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.

Keywords: Voronoi treemap; cell resource allocation; cellular economy; functional classification; mass spectrometry.

Fig. 1.

Proteomap of the budding yeast S. cerevisiae based on data from ref. . Every tile (small polygon) represents one type of protein. Tiles are arranged and colored according to the hierarchical KEGG pathway maps such that larger regions correspond to functional categories. The diagrams show three hierarchy levels (top three panels) and the level of individual proteins (Bottom). Tile sizes represent the mass fractions of proteins (protein abundances obtained by mass spectrometry, multiplied by protein chain lengths). Color code: blue, genetic information processing; brown, metabolism; red, cellular processes; green, signaling. Proteins—mostly low-abundance ones—that do not map to any category are shown in a gray area. The light-gray hexagon illustrates the area that covers 1% of the proteome.

Fig. 2.

Proteomaps of the budding yeast S. cerevisiae, compared across nutrient conditions and measurement methods. Yeast cells were grown in a rich (Left) or minimal medium (Right). In a minimal medium, the proteome fraction of amino acid biosynthesis enzymes is higher. Protein abundances were measured by mass spectrometry (Upper) in rich (14) and in minimal (5) media, or by fluorescence of GFP-tagged proteins (Lower) in YEPD versus SD media (2).

Fig. 3.

Proteomaps of several model organisms. (Upper) Proteomaps labeled by functional categories. (Lower) The same diagrams, with gene names. Protein abundances shown are for the tiny human pathogen M. pneumoniae (7), E. coli growing at a rate of 0.48 1/h (13), S. cerevisiae (14), and an H. sapiens HeLa cell line (11).

Fig. 4.

Proteomes of primate cell lines. The Top row shows that lymphoblastoid cells from humans and chimpanzees display very similar proteomes (12). Proteomes of human HeLa cells are shown in the Middle row (10, 11), and human U2OS cells are compared at the Bottom (9, 11).