Integrated Phosphoproteomics Analysis of a Signaling Network Governing Nutrient Response and Peroxisome Induction

In the face of dynamic cellular environments, cells must detect and compute signals they receive and execute an integrated and coordinated response involving multiple transcriptional and morphological programs. The rapid transduction of signals to the nucleus is accomplished in large part by altering the posttranslational states and thus activities of proteins that form relay networks for signal transmission. Phosphorylation is a ubiquitous posttranslational modification occurring on serine, threonine, and tyrosine aminoacyl residues that provides a common mechanism through which protein activity states are altered. Reversible phosphorylation is involved in virtually all cellular processes in eukaryotes, modulating enzymatic activities, protein subcellular distributions, protein half-lives, and protein-protein interactions (1, 2). The study of the phosphorylome is, therefore, a central component of systems approaches to understanding cellular processes. We are interested in cellular responses to nutrient changes that induce peroxisomes. Peroxisomes are ubiquitous intracellular organelles responsible for many metabolic activities, most notably fatty acid (FA)1 β-oxidation. In yeast, genes encoding abundant peroxisomal proteins are repressed in cells grown in glucose and highly induced in response to FA. The induction process involves global reorganization of transcriptional networks and activities (3, 4), peroxisome proliferation (5) (a process that highlights the dynamic nature of the peroxisomal proteome (6, 7)), and a host of additional coordinated cellular responses such as alterations to the cell cycle, cytoskeleton, membrane dynamics, and chromatin. Signaling molecules are key regulators of these complex and coordinate responses. We previously used cell-based reporter studies of gene deletions to delineate a core FA response signaling network governing the induction of peroxisomes in yeast (8). In an effort to both expand the network beyond the focus on peroxisomes and to understand information flow within the FA response network, we took a quantitative phosphoproteomics approach to characterize the differences between the phosphorylated portions of the proteomes of glucose-grown (peroxisome-repressed) and oleic acid-treated (peroxisome-induced) cells. Phosphoproteomes are a subset of proteomes with given phosphorylation events occurring at low stoichiometry (9). Mass spectrometry-based approaches to comprehensively identify phosphoproteomes have generally relied upon the reduction of sample complexity through fractionation, either gel-based (9, 10) or chromatographic (11–13), and enrichment strategies, generally through the use of immobilized metal affinity chromatography (IMAC) (14), titanium dioxide (TiO2) (15, 16), or phosphoramidate chemistry (17, 18). Although analysis of the phosphorylome remains a significant challenge, these approaches and improvements to mass spectrometers have significantly increased the number of identifications of phosphorylated peptides and their respective proteins. Known phosphorylation events are now on the order of several thousand (19). Phosphorylation is a dynamic process with phosphorylation states changing rapidly on the order of minutes or even seconds (20–22). As mass spectrometry-based experiments rely on ex vivo approaches, careful consideration must be given to the cellular environment during the cell disruption procedures. Ideally, the presence of a stimulus should be maintained until the cells are processed to a point at which reorientation of the phosphoproteome is unable to occur. Given the rapidity with which phosphorylation states can reorient, we developed a cryolysis-based disruption, urea solubilization methodology to minimize the opportunity for kinase or phosphatase activity and maintain the condition-specific phosphorylation status of the proteome. We also combined stable isotope labeling with amino acids in cell culture with orthogonal peptide fractionation procedures to identify proteins that are significantly responsive to cell exposure to FAs. Using cryolysis, hydrophilic interaction-based chromatography, and a combination of LC-MS2 and multistage activation (MSA) approaches, we identified a global data set of proteins that are differentially phosphorylated upon transition from a glucose- to a FA-stimulated state. Integration of this phosphoproteomics data set with data from an analysis of signaling molecules regulating peroxisome induction during the FA response (8) and known interactions from the literature allowed for the identification of numerous novel phosphorylated forms of signaling and transcription factors and the derivation of an expanded FA-responsive signaling network with properties indicative of scale-free topology. Interestingly, the most highly connected nodes influence the response to FAs to the greatest extent. Taken together, these analyses provide a comprehensive view of the network specifically responsive to the exposure of cells to FAs and further demonstrate the conservation of common network architecture within signaling networks with the feature of a few hubs exerting the largest effects persisting at condition- or phenotype-specific levels.