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Towards systematic discovery of signaling networks in budding yeast filamentous growth stress response using interventional phosphorylation data.

ABSTRACT: Reversible phosphorylation is one of the major mechanisms of signal transduction, and signaling networks are critical regulators of cell growth and development. However, few of these networks have been delineated completely. Towards this end, quantitative phosphoproteomics is emerging as a useful tool enabling large-scale determination of relative phosphorylation levels. However, phosphoproteomics differs from classical proteomics by a more extensive sampling limitation due to the limited number of detectable sites per protein. Here, we propose a comprehensive quantitative analysis pipeline customized for phosphoproteome data from interventional experiments for identifying key proteins in specific pathways, discovering the protein-protein interactions and inferring the signaling network. We also made an effort to partially compensate for the missing value problem, a chronic issue for proteomics studies. The dataset used for this study was generated using SILAC (Stable Isotope Labeling with Amino acids in Cell culture) technique with interventional experiments (kinase-dead mutations). The major components of the pipeline include phosphopeptide meta-analysis, correlation network analysis and causal relationship discovery. We have successfully applied our pipeline to interventional experiments identifying phosphorylation events underlying the transition to a filamentous growth form in Saccharomyces cerevisiae. We identified 5 high-confidence proteins from meta-analysis, and 19 hub proteins from correlation analysis (Pbi2p and Hsp42p were identified by both analyses). All these proteins are involved in stress responses. Nine of them have direct or indirect evidence of involvement in filamentous growth. In addition, we tested four of our predicted proteins, Nth1p, Pbi2p, Pdr12p and Rcn2p, by interventional phenotypic experiments and all of them present differential invasive growth, providing prospective validation of our approach. This comprehensive pipeline presents a systematic way for discovering signaling networks using interventional phosphoproteome data and can suggest candidate proteins for further investigation. We anticipate the methodology to be applicable as well to other interventional studies via different experimental platforms.

SUBMITTER: Zhang Y

PROVIDER: S-EPMC3694812 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Towards systematic discovery of signaling networks in budding yeast filamentous growth stress response using interventional phosphorylation data.

Zhang Yan Y Kweon Hye Kyong HK Shively Christian C Kumar Anuj A Andrews Philip C PC

PLoS computational biology 20130627 6

Reversible phosphorylation is one of the major mechanisms of signal transduction, and signaling networks are critical regulators of cell growth and development. However, few of these networks have been delineated completely. Towards this end, quantitative phosphoproteomics is emerging as a useful tool enabling large-scale determination of relative phosphorylation levels. However, phosphoproteomics differs from classical proteomics by a more extensive sampling limitation due to the limited number ...[more]

PMID: 23825934

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Project description:BackgroundPhosphorylation is a ubiquitous and fundamental regulatory mechanism that controls signal transduction in living cells. The number of identified phosphoproteins and their phosphosites is rapidly increasing as a result of recent mass spectrometry-based approaches.ResultsWe analyzed time-course phosphoproteome data obtained previously by liquid chromatography mass spectrometry with the stable isotope labeling using amino acids in cell culture (SILAC) method. This provides the relative phosphorylation activities of digested peptides at each of five time points after stimulating HeLa cells with epidermal growth factor (EGF). We initially calculated the correlations between the phosphorylation dynamics patterns of every pair of peptides and connected the strongly correlated pairs to construct a network. We found that peptides extracted from the same intracellular fraction (nucleus vs. cytoplasm) tended to be close together within this phosphorylation dynamics-based network. The network was then analyzed using graph theory and compared with five known signal-transduction pathways. The dynamics-based network was correlated with known signaling pathways in the NetPath and Phospho.ELM databases, and especially with the EGF receptor (EGFR) signaling pathway. Although the phosphorylation patterns of many proteins were drastically changed by the EGF stimulation, our results suggest that only EGFR signaling transduction was both strongly activated and precisely controlled.ConclusionsThe construction of a phosphorylation dynamics-based network provides a useful overview of condition-specific intracellular signal transduction using quantitative time-course phosphoproteome data under specific experimental conditions. Detailed prediction of signal transduction based on phosphoproteome dynamics remains challenging. However, since the phosphorylation profiles of kinase-substrate pairs on the specific pathway were localized in the dynamics-based network, our method will be a complementary strategy to explore new components of protein signaling pathways in combination with previous methods (including software) of predicting direct kinase-substrate relationships.

Project description:Many fungal species, including pathogens, undergo a morphogenetic response called filamentous growth, where cells differentiate into a specialized cell type to promote nutrient foraging and surface colonization. Despite the fact that filamentous growth is required for virulence in some plant and animal pathogens, certain aspects of this behavior remain poorly understood. By examining filamentous growth in the budding yeast Saccharomyces cerevisiae and the opportunistic pathogen Candida albicans, we identify responses where cells undergo filamentous growth in groups of cells or aggregates. In S. cerevisiae, aggregate invasive growth was regulated by signaling pathways that control normal filamentous growth. These pathways promoted aggregation in part by fostering aspects of microbial cooperation. For example, aggregate invasive growth required cellular contacts mediated by the flocculin Flo11p, which was produced at higher levels in aggregates than cells undergoing regular invasive growth. Aggregate invasive growth was also stimulated by secreted enzymes, like invertase, which produce metabolites that are shared among cells. Aggregate invasive growth was also induced by alcohols that promote density-dependent filamentous growth in yeast. Aggregate invasive growth also required highly polarized cell morphologies, which may affect the packing or organization of cells. A directed selection experiment for aggregating phenotypes uncovered roles for the fMAPK and RAS pathways, which indicates that these pathways play a general role in regulating aggregate-based responses in yeast. Our study extends the range of responses controlled by filamentation regulatory pathways and has implications in understanding aspects of fungal biology that may be relevant to fungal pathogenesis.IMPORTANCE Filamentous growth is a fungal morphogenetic response that is critical for virulence in some fungal species. Many aspects of filamentous growth remain poorly understood. We have identified an aspect of filamentous growth in the budding yeast Saccharomyces cerevisiae and the human pathogen Candida albicans where cells behave collectively to invade surfaces in aggregates. These responses may reflect an extension of normal filamentous growth, as they share the same signaling pathways and effector processes. Aggregate responses may involve cooperation among individual cells, because aggregation was stimulated by cell adhesion molecules, secreted enzymes, and diffusible molecules that promote quorum sensing. Our study may provide insights into the genetic basis of collective cellular responses in fungi. The study may have ramifications in fungal pathogenesis, in situations where collective responses occur to promote virulence.

Dataset Information

Towards systematic discovery of signaling networks in budding yeast filamentous growth stress response using interventional phosphorylation data.

Publications

Towards systematic discovery of signaling networks in budding yeast filamentous growth stress response using interventional phosphorylation data.

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