Title
Integrative Features Of The Yeast Phosphoproteome And Protein-Protein Interaction Map
Abstract
Following recent advances in high-throughput mass spectrometry (MS)-based proteomics, the numbers of identified phosphoproteins and their phosphosites have greatly increased in a wide variety of organisms. Although a critical role of phosphorylation is control of protein signaling, our understanding of the phosphoproteome remains limited. Here, we report unexpected, large-scale connections revealed between the phosphoproteome and protein interactome by integrative data-mining of yeast multi-omics data. First, new phosphoproteome data on yeast cells were obtained by MS-based proteomics and unified with publicly available yeast phosphoproteome data. This revealed that nearly 60% of similar to 6,000 yeast genes encode phosphoproteins. We mapped these unified phosphoproteome data on a yeast protein-protein interaction (PPI) network with other yeast multi-omics datasets containing information about proteome abundance, proteome disorders, literature-derived signaling reactomes, and in vitro substratomes of kinases. In the phospho-PPI, phosphoproteins had more interacting partners than nonphosphoproteins, implying that a large fraction of intracellular protein interaction patterns (including those of protein complex formation) is affected by reversible and alternative phosphorylation reactions. Although highly abundant or unstructured proteins have a high chance of both interacting with other proteins and being phosphorylated within cells, the difference between the number counts of interacting partners of phosphoproteins and nonphosphoproteins was significant independently of protein abundance and disorder level. Moreover, analysis of the phospho-PPI and yeast signaling reactome data suggested that co-phosphorylation of interacting proteins by single kinases is common within cells. These multi-omics analyses illuminate how wide-ranging intracellular phosphorylation events and the diversity of physical protein interactions are largely affected by each other.
Year
DOI
Venue
2011
10.1371/journal.pcbi.1001064
PLOS COMPUTATIONAL BIOLOGY
Keywords
Field
DocType
protein protein interaction,phosphorylation,proteome,mass spectrometry,protein binding,protein complex,data mining,high throughput
Phosphorylation,Plasma protein binding,Interactome,Protein–protein interaction,Biology,Proteomics,Cell biology,Fungal protein,Proteome,Yeast,Bioinformatics
Journal
Volume
Issue
ISSN
7
1
1553-7358
Citations 
PageRank 
References 
7
0.65
9
Authors
5
Name
Order
Citations
PageRank
Nozomu Yachie1252.50
R Saito29814.12
Naoyuki Sugiyama3131.81
Masaru Tomita41009180.20
Yasushi Ishihama5374.71