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1.  Integrating phosphoproteomics in systems biology 
Phosphorylation of serine, threonine and tyrosine plays significant roles in cellular signal transduction and in modifying multiple protein functions. Phosphoproteins are coordinated and regulated by a network of kinases, phosphatases and phospho-binding proteins, which modify the phosphorylation states, recognize unique phosphopeptides, or target proteins for degradation. Detailed and complete information on the structure and dynamics of these networks is required to better understand fundamental mechanisms of cellular processes and diseases. High-throughput technologies have been developed to investigate phosphoproteomes in model organisms and human diseases. Among them, mass spectrometry (MS)-based technologies are the major platforms and have been widely applied, which has led to explosive growth of phosphoproteomic data in recent years. New bioinformatics tools are needed to analyze and make sense of these data. Moreover, most research has focused on individual phosphoproteins and kinases. To gain a more complete knowledge of cellular processes, systems biology approaches, including pathways and networks modeling, have to be applied to integrate all components of the phosphorylation machinery, including kinases, phosphatases, their substrates, and phospho-binding proteins. This review presents the latest developments of bioinformatics methods and attempts to apply systems biology to analyze phosphoproteomics data generated by MS-based technologies. Challenges and future directions in this field will be also discussed.
PMCID: PMC4204398  PMID: 25349677
Phosphoproteomics; Systems biology; Kinases; Phosphatases; Phospho-binding proteins; Phosphorylation network; Phospho-signaling networks; Mass spectrometry
2.  Kinase/phosphatase overexpression reveals pathways regulating hippocampal neuron morphology 
Kinases and phosphatases that regulate neurite number versus branching versus extension are weakly correlated.The kinase family that most strongly enhances neurite growth is a family of non-protein kinases; sugar kinases related to NADK.Pathway analysis revealed that genes in several cancer pathways were highly active in enhancing neurite growth.
In neural development, neuronal precursors differentiate, migrate, extend long axons and dendrites, and finally establish connections with their targets. Clinical conditions such as spinal cord injury, traumatic brain injury, stroke, multiple sclerosis, Parkinson's disease, Huntington's disease, and Alzheimer's disease are often associated with a loss of axon and/or dendrite connectivity and treatment strategies would be enhanced by new therapies targeting cell intrinsic mechanisms of axon elongation and regeneration.
Phosphorylation controls most cellular processes, including the cell cycle, proliferation, metabolism, and apoptosis. Neuronal differentiation, including axon formation and elongation, is also regulated by a wide range of kinases and phosphatases. For example, the non-receptor tyrosine kinase Src is required for cell adhesion molecule-dependent neurite outgrowth. In addition to individual kinases and phosphatases, signaling pathways like the MAPK, growth factor signaling, PIP3, cytoskeletal, and calcium-dependent pathways have been shown to impinge on or control neuronal process development. Recent results have implicated GSK3 and PTEN as therapeutically relevant targets in axonal regeneration after injury. However, these and other experiments have studied only a small fraction of the total kinases and phosphatases in the genome. Because of recent advances in genomic knowledge, large-scale cDNA production, and high-throughput phenotypic analysis, it is now possible to take a more comprehensive approach to understanding the functions of kinases and phosphatases in neurons.
We performed a large, unbiased set of experiments to answer the question ‘what effect does the overexpression of genes encoding kinases, phosphatases, and related proteins have on neuronal morphology?' We used ‘high-content analysis' to obtain detailed results about the specific phenotypes of neurons. We studied embryonic rat hippocampal neurons because of their stereotypical development in vitro (Dotti et al, 1988) and their widespread use in studies of neuronal differentiation and signaling. We transfected over 700 clones encoding kinases and phosphatases into hippocampal neurons and analyzed the resulting changes in neuronal morphology.
Many known genes, including PP1a, ERK1, ErbB2, atypical PKC, Calcineurin, CaMK2, IGF1R, FGFR, GSK3, and PIK3 were observed to have significant effects on neurite outgrowth in our system, consistent with earlier findings in the literature.
We obtained quantitative data for many cellular and neuronal morphological parameters from each neuron imaged. These included nuclear morphology (nuclear area and Hoechst dye intensity), soma morphology (tubulin intensity, area, and shape), and numerous parameters of neurite morphology (e.g. tubulin intensity along the neurites, number of primary neurites, neurite length, number of branches, distance from the cell body to the branches, number of crossing points, width and area of the neurites, and longest neurite; Supplementary Figure 1). Other parameters were reported on a ‘per well' basis, including the percentage of transfected neurons in a condition, as well as the percentage of neurons initiating neurite growth. Data for each treatment were normalized to a control (pSport CAT) within the same experiment, then aggregated across replicate experiments.
Correlations among the 19 normalized parameters were analyzed for neurons transfected with all kinase and phosphatase clones (Figure 2). On the basis of this analysis, the primary variables that define the neurite morphology are primary neurite count, neurite average length, and average branches. Interestingly, primary neurite count was not well correlated with neurite length or branching. The Pearson correlation coefficient (r2) between the number of primary neurites and the average length of the neurites was 0.3, and between the number of primary neurites and average branching was 0.2. In contrast, the correlation coefficient of average branching with neurite average length was 0.7. The most likely explanation is that signaling mechanisms underlying the neurite number determination are different than those controlling length/branching of the neurites.
Related proteins are often involved in similar neuronal functions. For example, families of receptor protein tyrosine phosphatases are involved in motor axon extension and guidance in both Drosophila and in vertebrates, and a large family of Eph receptor tyrosine kinases regulates guidance of retinotectal projections, motor axons, and axons in the corpus callosum. We therefore asked whether families of related genes produced similar phenotypes when overexpressed in hippocampal neurons. Our set of genes covered 40% of the known protein kinases, and many of the non-protein kinases and phosphatases.
Gene families commonly exhibit redundant function. Redundant gene function has often been identified when two or more knockouts are required to produce a phenotype. Our technique allowed us to measure whether different members of gene families had similar (potentially redundant) or distinct effects on neuronal phenotype.
To determine whether groups of related genes affect neuronal morphology in similar ways, we used sequence alignment information to construct gene clusters (Figure 6). Genes were clustered at nine different thresholds of similarity (called ‘tiers'). The functional effect for a particular parameter was then averaged within each cluster of a given tier, and statistics were performed to determine the significance of the effect. We analyzed the results for three key neurite parameters (average neurite length, primary neurite count, and average branching). Genes that perturbed each of these phenotypes are grouped in Figure 6. Eight families, most with only a few genes, produced significant changes for one or two parameters. A diverse family of non-protein kinases had a positive effect on neurite outgrowth in three of the four parameters analyzed. This family of kinases consisted of a variety of enzymes, mostly sugar and lipid kinases. A similar analysis was performed using pathway cluster analysis with pathways from the KEGG database, rather than sequence homology. Interestingly, pathways involved in cancer cell proliferation potentiated neurite extension and branching.
Our studies have identified a large number of kinases and phosphatases, as well as structurally and functionally defined families of these proteins, that affect neuronal process formation in specific ways. We have provided an analytical methodology and new tools to analyze functional data, and have implicated genes with novel functions in neuronal development. Our studies are an important step towards the goal of a molecular description of the intrinsic control of axodendritic growth.
Development and regeneration of the nervous system requires the precise formation of axons and dendrites. Kinases and phosphatases are pervasive regulators of cellular function and have been implicated in controlling axodendritic development and regeneration. We undertook a gain-of-function analysis to determine the functions of kinases and phosphatases in the regulation of neuron morphology. Over 300 kinases and 124 esterases and phosphatases were studied by high-content analysis of rat hippocampal neurons. Proteins previously implicated in neurite growth, such as ERK1, GSK3, EphA8, FGFR, PI3K, PKC, p38, and PP1a, were confirmed to have effects in our functional assays. We also identified novel positive and negative neurite growth regulators. These include neuronal-developmentally regulated kinases such as the activin receptor, interferon regulatory factor 6 (IRF6) and neural leucine-rich repeat 1 (LRRN1). The protein kinase N2 (PKN2) and choline kinase α (CHKA) kinases, and the phosphatases PPEF2 and SMPD1, have little or no established functions in neuronal function, but were sufficient to promote neurite growth. In addition, pathway analysis revealed that members of signaling pathways involved in cancer progression and axis formation enhanced neurite outgrowth, whereas cytokine-related pathways significantly inhibited neurite formation.
PMCID: PMC2925531  PMID: 20664637
bioinformatics; development; functional genomics; metabolic and regulatory networks; neuroscience
3.  The phosphoproteome of toll-like receptor-activated macrophages 
First global and quantitative analysis of phosphorylation cascades induced by toll-like receptor (TLR) stimulation in macrophages identifies nearly 7000 phosphorylation sites and shows extensive and dynamic up-regulation and down-regulation after lipopolysaccharide (LPS).In addition to the canonical TLR-associated pathways, mining of the phosphorylation data suggests an involvement of ATM/ATR kinases in signalling and shows that the cytoskeleton is a hotspot of TLR-induced phosphorylation.Intersecting transcription factor phosphorylation with bioinformatic promoter analysis of genes induced by LPS identified several candidate transcriptional regulators that were previously not implicated in TLR-induced transcriptional control.
Toll-like receptors (TLR) are a family of pattern recognition receptors that enable innate immune cells to sense infectious danger. Recognition of microbial structures, like lipopolysaccharide (LPS) of Gram-negative bacteria by TLR4, causes within hours substantial re-programming of macrophage gene expression, including up-regulation of chemokines driving inflammation, anti-microbial effector molecules and cytokines directing adaptive immune responses. TLR signalling is initiated by the adapter protein Myd88 and leads to the activation of kinase cascades that result in activation of the MAPK and NFkB pathways. Phosphorylation has an essential role in these early steps of TLR signalling, and in addition regulates critical transcription factors (TFs). Although TLR signalling has been extensively studied, a comprehensive analysis of phosphorylation events in TLR-activated macrophages is lacking. It is therefore unknown whether the canonical MAPK and NFkB pathways comprise the main phosphorylation events and which other molecular functions and processes are regulated by phosphorylation after stimulation with LPS.
Recent progress in mass spectrometry-based proteomics has opened the possibility to quantitatively investigate global changes in protein abundance and post-translational modifications. Stable isotope labelling with amino acids in cell culture (SILAC) allows highly accurate quantification, and has proved especially useful for direct comparison of phosphopeptide abundance in time-course or treatment analyses.
Here, we adapted SILAC to primary mouse macrophages, and performed a global, quantitative and kinetic analysis of the macrophage phosphoproteome after LPS stimulation. Bioinformatic analyses were used to identify kinases, pathways and biological processes enriched in the LPS-regulated phosphoproteome. To connect TF phosphorylation with transcription, we generated a parallel dataset of nascent RNA and used in silico promoter analysis to identify transcriptional regulators with binding site enrichment among the LPS-regulated gene set.
After establishing SILAC conditions for efficient labelling of primary bone marrow-derived macrophages in two independent experiments 1850 phosphoproteins with a total of 6956 phosphorylation sites were reproducibly identified. Phosphoproteins were detected from all cellular compartments, with a clear enrichment for nuclear and cytoskeleton-associated proteins. LPS caused major regulation of a large fraction of phosphopeptides, with 24% of all sites up-regulated and 9% down-regulated after stimulation (Figure 3A and B). These changes were highly dynamic, as the majority of the regulated phosphopeptides were up-regulated or down-regulated transiently or in a delayed manner (Figure 3C). Overall, the extent of changes in the phosphoproteome was comparable to the transcriptional re-programming, underscoring the importance of phosphorylation cascades in TLR signalling. Our parallel transcriptome data also showed that widespread phosphorylation precedes massive transcriptional changes.
To obtain footprints of kinase activation in response to TLR ligation, we searched phosphopeptide sequences for known linear sequence motifs of 33 kinases and identified kinase motifs enriched among LPS-regulated phosphorylation sites (compared to non-regulated phosphorylation sites) (Table I). Motif ERK/MAPK was highly enriched, in accordance with the essential role of the MAPK module in TLR signalling. Other kinases with motif enrichment have also recently been linked to TLR signalling (e.g. PKD; AKT and its targets GSK3 and mTOR). However, the DNA damage-actviated kinases ATM/ATR and the cell cycle-associated kinases AURORA and CHK1/2 have not been associated with the macrophage response to TLR activation yet. These finding shed new light on older data on the effect of TLR on macrophage proliferation in response to macrophage colony stimulating factor. Of interest, in follow-up experiments using pharmacological inhibitors of the kinases with motif enrichment, we observed that inhibition of ATM kinase activity caused increased LPS-induced expression of several cytokines and chemokines, suggesting that this pathway regulates inflammatory responses.
In further bioinformatic analyses, the Gene Ontology and signalling pathway annotations of phosphoproteins were used to identify signalling pathways and cellular processes targeted by TLR4-controlled phosphorylation (Table II). Among the expected hits, based on the known TLR pathways, were TLR signalling, MAPK and AKT as well as mTOR signalling. Of interest, the annotation terms ‘Rho GTPase cycle' and ‘cytoskeleton' were significantly enriched among LPS-regulated phosphoproteins, indicating a more prominent role for cytoskeletal proteins in the transduction of TLR signals or in the biological response to it.
We were especially interested in the phosphorylation of TFs and its regulation by LPS (Figure 6A). We hypothesised that functionally important TFs should have an increased frequency of binding sites in the promoters of LPS-regulated genes (Figure 6B). To identify transcriptionally regulated genes with high sensitivity, we isolated nascent RNA after metabolic labelling (Figure 6C–E). In silico promoter scanning using Genomatix software for binding sites for all 50 TF families with phosphorylated members was used to test for enrichment in transciptionally induced genes (Figure 6F). At the early time point, binding site enrichment for the canonical TLR-associated TF NFkB was detected, and in addition we found that several other TF families with an established role in the transcription of individual LPS-target genes showed binding site enrichment (CEBP, MEF2, NFAT and HEAT). In addition, enrichment for OCT and HOXC binding sites at the early time point and SORY matrices later after stimulation indicated an involvement of the phosphorylated members of the respective TF families in the execution of TLR-induced transcriptional responses. An initial test of the function for a few of these candidate transcriptional regulators was performed using siRNA knockdown in primary macrophages. These experiments suggested that knock down of the SORY binding phosphoprotein Capicua homolog (Cic) and to a lesser extent of the CREB family member Atf7 selectively attenuates LPS-induced expression of Il1a and Il1b.
In summary, this study provides a novel and global perspective on innate immune activation by TLR signalling (Figure 5). We quantitatively detected a large number of previously unknown site-specific phosphorylation events, which are now publicly available through the Phosida database. By combining different data mining approaches, we consistently identified canonical and newly implicated TLR-activated signalling modules. In particular, the PI3K/AKT and the related mTOR pathway were highlighted; furthermore, DNA damage–response associated ATM/ATR kinases and the cytoskeleton emerged as unexpected hotspots for phosphorylation. Finally, weaving together corresponding phophoproteome and nascent transcriptome datasets through the loom of in silico promoter analysis we identified TFs with a likely role in mediating TLR-induced gene expression programmes.
Recognition of microbial danger signals by toll-like receptors (TLR) causes re-programming of macrophages. To investigate kinase cascades triggered by the TLR4 ligand lipopolysaccharide (LPS) on systems level, we performed a global, quantitative and kinetic analysis of the phosphoproteome of primary macrophages using stable isotope labelling with amino acids in cell culture, phosphopeptide enrichment and high-resolution mass spectrometry. In parallel, nascent RNA was profiled to link transcription factor (TF) phosphorylation to TLR4-induced transcriptional activation. We reproducibly identified 1850 phosphoproteins with 6956 phosphorylation sites, two thirds of which were not reported earlier. LPS caused major dynamic changes in the phosphoproteome (24% up-regulation and 9% down-regulation). Functional bioinformatic analyses confirmed canonical players of the TLR pathway and highlighted other signalling modules (e.g. mTOR, ATM/ATR kinases) and the cytoskeleton as hotspots of LPS-regulated phosphorylation. Finally, weaving together phosphoproteome and nascent transcriptome data by in silico promoter analysis, we implicated several phosphorylated TFs in primary LPS-controlled gene expression.
PMCID: PMC2913394  PMID: 20531401
macrophage; nascent RNA; phosphoproteome; SILAC; toll-like receptors
4.  Integrative Features of the Yeast Phosphoproteome and Protein–Protein Interaction Map 
PLoS Computational Biology  2011;7(1):e1001064.
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 ∼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.
Author Summary
To date, high-throughput proteome technologies have revealed that hundreds to thousands of proteins in each of many organisms are phosphorylated under the appropriate environmental conditions. A critical role of phosphorylation is control of protein signaling. However, only a fraction of the identified phosphoproteins participate in currently known protein signaling pathways, and the biological relevance of the remainder is unclear. This has raised the question of whether phosphorylation has other major roles. In this study, we identified new phosphoproteins in budding yeast by mass spectrometry and unified these new data with publicly available phosphoprotein data. We then performed an integrative data-mining of large-scale yeast phosphoproteins and protein–protein interactions (complex formation) by an exhaustive analysis that incorporated yeast protein information from several other sources. The phosphoproteome data integration surprisingly showed that nearly 60% of yeast genes encode phosphoproteins, and the subsequent data-mining analysis derived two models interpreting the mutual intracellular effects of large-scale protein phosphorylation and binding interaction. Biological interpretations of both large-scale intracellular phosphorylation and the topology of protein interaction networks are highly relevant to modern biology. This study sheds light on how in vivo protein pathways are supported by a combination of protein modification and molecular dynamics.
PMCID: PMC3029238  PMID: 21298081
5.  Proteomic snapshot of the EGF-induced ubiquitin network 
In this work, the authors report the first proteome-wide analysis of EGF-regulated ubiquitination, revealing surprisingly pervasive growth factor-induced ubiquitination across a broad range of cellular systems and signaling pathways.
Epidermal growth factor (EGF) triggers a novel ubiquitin (Ub)-based signaling cascade that appears to intersect both housekeeping and regulatory circuitries of cellular physiology.The EGF-regulated Ubiproteome includes scores ubiquitinating and deubiquitinating enzymes, suggesting that the Ub signal might be rapidly transmitted and amplified through the Ub machinery.The EGF-Ubiproteome overlaps significantly with the EGF-phosphotyrosine proteome, pointing to a possible crosstalk between these two signaling mechanisms.The significant number of biological insights uncovered in our study (among which EphA2 as a novel, downstream ubiquitinated target of EGF receptor) illustrates the general relevance of such proteomic screens and calls for further analysis of the dynamics of the Ubiproteome.
Ubiquitination is a process by which one or more ubiquitin (Ub) monomers or chains are covalently attached to target proteins by E3 ligases. Deubiquitinating enzymes (DUBs) revert Ub conjugation, thus ensuring a dynamic equilibrium between pools of ubiquitinated and deubiquitinated proteins (Amerik and Hochstrasser, 2004). Traditionally, ubiquitination has been associated with protein degradation; however, it is now becoming apparent that this post-translation modification is an important signaling mechanism that can modulate the function, localization and protein/protein interaction abilities of targets (Mukhopadhyay and Riezman, 2007; Ravid and Hochstrasser, 2008).
One of the best-characterized signaling pathways involving ubiquitination is the epidermal growth factor (EGF)-induced pathway. Upon EGF stimulation, a variety of proteins are subject to Ub modification. These include the EGF receptor (EGFR), which undergoes both multiple monoubiquitination (Haglund et al, 2003) and K63-linked polyubiquitination (Huang et al, 2006), as well as components of the downstream endocytic machinery, which are modified by monoubiquitination (Polo et al, 2002; Mukhopadhyay and Riezman, 2007). Ubiquitination of the EGFR has been shown to have an impact on receptor internalization, intracellular sorting and metabolic fate (Acconcia et al, 2009). However, little is known about the wider impact of EGF-induced ubiquitination on cellular homeostasis and on the pleiotropic biological functions of the EGFR. In this paper, we attempt to address this issue by characterizing the repertoire of proteins that are ubiquitinated upon EGF stimulation, i.e., the EGF-Ubiproteome.
To achieve this, we employed two different purification procedures (endogenous—based on the purification of proteins modified by endogenous Ub from human cells; tandem affinity purification (TAP)—based on the purification of proteins modified by an ectopically expressed tagged-Ub from mouse cells) with stable isotope labeling with amino acids in cell culture-based MS to obtain both steady-state Ubiproteomes and EGF-induced Ubiproteomes. The steady-state Ubiproteomes consist of 1175 and 582 unambiguously identified proteins for the endogenous and TAP approaches, respectively, which we largely validated. Approximately 15% of the steady-state Ubiproteome was EGF-regulated at 10 min after stimulation; 176 of 1175 in the endogenous approach and 105 of 582 in the TAP approach. Both hyper- and hypoubiquitinated proteins were detected, indicating that EGFR-mediated signaling can modulate the ubiquitin network in both directions. Interestingly, many E2, E3 and DUBs were present in the EGF-Ubiproteome, suggesting that the Ub signal might be rapidly transmitted and amplified through the Ub machinery. Moreover, analysis of Ub-chain topology, performed using mass spectrometry and specific abs, suggested that the K63-linkage was the major Ub-based signal in the EGF-induced pathway.
To obtain a higher-resolution molecular picture of the EGF-regulated Ub network, we performed a network analysis on the non-redundant EGF-Ubiproteome (265 proteins). This analysis revealed that in addition to well-established liaisons with endocytosis-related pathways, the EGF-Ubiproteome intersects many circuitries of intracellular signaling involved in, e.g., DNA damage checkpoint regulation, cell-to-cell adhesion mechanisms and actin remodeling (Figure 5A).
Moreover, the EGF-Ubiproteome was enriched in hubs, proteins that can establish multiple protein/protein interaction and thereby regulate the organization of networks. These results are indicative of a crosstalk between EGFR-activated pathways and other signaling pathways through the Ub-network.
As EGF binding to its receptor also triggers a series of phosphorylation events, we examined whether there was any overlap between our EGF-Ubiproteome and published EGF-induced phosphotyrosine (pY) proteomes (Blagoev et al, 2004; Oyama et al, 2009; Hammond et al, 2010). We observed a significant overlap between ubiquitinated and pY proteins: 23% (61 of 265) of the EGF-Ubiproteome proteins were also tyrosine phosphorylated. Pathway analysis of these 61 Ub/pY-containing proteins revealed a significant enrichment in endocytic and signal-transduction pathways, while ‘hub analysis' revealed that Ub/pY-containing proteins are enriched in highly connected proteins to an even greater extent than Ub-containing proteins alone. These data point to a complex interplay between the Ub and pY networks and suggest that the flow of information from the receptor to downstream signaling molecules is driven by two complementary and interlinked enzymatic cascades: kinases/phosphatases and E3 ligases/DUBs.
Finally, we provided a proof of principle of the biological relevance of our EGF-Ubiproteome. We focused on EphA2, a receptor tyrosine kinase, which is involved in development and is often overexpressed in cancer (Pasquale, 2008). We started from the observation that EphA2 is present in the EGF-Ubiproteome and that proteins of the EGF-Ubiproteome are enriched in the Ephrin receptor signaling pathway(s). We confirmed the MS data by demonstrating that the EphA2 is ubiquitinated upon EGF stimulation. Moreover, EphA2 also undergoes tyrosine phosphorylation, indicating crosstalk between the two receptors. The EGFR kinase domain was essential for these modifications of EphA2, and a partial co-internalization with EGFR upon EGF activation was clearly detectable. Finally, we demonstrated by knockdown of EphA2 in MCF10A cells that this receptor is critically involved in EGFR biological outcomes, such as proliferation and migration (Figure 7).
Overall, our results unveil the complex impact of growth factor signaling on Ub-based intracellular networks to levels that extend well beyond what might have been expected and highlight the ‘resource' feature of our EGF-Ubiproteome.
The activity, localization and fate of many cellular proteins are regulated through ubiquitination, a process whereby one or more ubiquitin (Ub) monomers or chains are covalently attached to target proteins. While Ub-conjugated and Ub-associated proteomes have been described, we lack a high-resolution picture of the dynamics of ubiquitination in response to signaling. In this study, we describe the epidermal growth factor (EGF)-regulated Ubiproteome, as obtained by two complementary purification strategies coupled to quantitative proteomics. Our results unveil the complex impact of growth factor signaling on Ub-based intracellular networks to levels that extend well beyond what might have been expected. In addition to endocytic proteins, the EGF-regulated Ubiproteome includes a large number of signaling proteins, ubiquitinating and deubiquitinating enzymes, transporters and proteins involved in translation and transcription. The Ub-based signaling network appears to intersect both housekeeping and regulatory circuitries of cellular physiology. Finally, as proof of principle of the biological relevance of the EGF-Ubiproteome, we demonstrated that EphA2 is a novel, downstream ubiquitinated target of epidermal growth factor receptor (EGFR), critically involved in EGFR biological responses.
PMCID: PMC3049407  PMID: 21245847
EGF; network; proteomics; signaling; ubiquitin
6.  Phosphoproteomic Analyses Reveal Signaling Pathways That Facilitate Lytic Gammaherpesvirus Replication 
PLoS Pathogens  2013;9(9):e1003583.
Lytic gammaherpesvirus (GHV) replication facilitates the establishment of lifelong latent infection, which places the infected host at risk for numerous cancers. As obligate intracellular parasites, GHVs must control and usurp cellular signaling pathways in order to successfully replicate, disseminate to stable latency reservoirs in the host, and prevent immune-mediated clearance. To facilitate a systems-level understanding of phosphorylation-dependent signaling events directed by GHVs during lytic replication, we utilized label-free quantitative mass spectrometry to interrogate the lytic replication cycle of murine gammaherpesvirus-68 (MHV68). Compared to controls, MHV68 infection regulated by 2-fold or greater ca. 86% of identified phosphopeptides – a regulatory scale not previously observed in phosphoproteomic evaluations of discrete signal-inducing stimuli. Network analyses demonstrated that the infection-associated induction or repression of specific cellular proteins globally altered the flow of information through the host phosphoprotein network, yielding major changes to functional protein clusters and ontologically associated proteins. A series of orthogonal bioinformatics analyses revealed that MAPK and CDK-related signaling events were overrepresented in the infection-associated phosphoproteome and identified 155 host proteins, such as the transcription factor c-Jun, as putative downstream targets. Importantly, functional tests of bioinformatics-based predictions confirmed ERK1/2 and CDK1/2 as kinases that facilitate MHV68 replication and also demonstrated the importance of c-Jun. Finally, a transposon-mutant virus screen identified the MHV68 cyclin D ortholog as a viral protein that contributes to the prominent MAPK/CDK signature of the infection-associated phosphoproteome. Together, these analyses enhance an understanding of how GHVs reorganize and usurp intracellular signaling networks to facilitate infection and replication.
Author Summary
Systems-level evaluations of infection-related changes to host phosphoprotein networks are not currently available for any gammaherpesvirus (GHV). Here we describe a quantitative phosphoproteomic analysis of productive GHV replication that demonstrates alterations in the phosphorylation status of more than 80% of host phosphoproteins and identifies 18 viral phosphoproteins. Systematic bioinformatics analyses reveal a predominance of MAPK and CDK signaling events within infected cells and suggest a virus-induced reorganization of signal-transduction pathways within the host phosphoprotein network. Functional experiments confirmed that CDKs and ERK MAPKs facilitate efficient viral replication and identify transcription factor c-Jun as a potential downstream target contributing to MHV68 replication. Finally, we identify the viral cyclin D ortholog as a major pathogen-encoded factor contributing to the MAPK/CDK signature of the infected cell phosphoproteome. These data provide new insight into both viral and host factors that regulate phosphorylation-dependent signaling during lytic GHV replication and offer a new resource for better defining host-pathogen interactions in general.
PMCID: PMC3777873  PMID: 24068923
7.  Characterization of the Phosphoproteome in SLE Patients 
PLoS ONE  2012;7(12):e53129.
Protein phosphorylation is a complex regulatory event that is involved in the signaling networks that affect virtually every cellular process. The protein phosphorylation may be a novel source for discovering biomarkers and drug targets. However, a systematic analysis of the phosphoproteome in patients with SLE has not been performed. To clarify the pathogenesis of systemic lupus erythematosus (SLE), we compared phosphoprotein expression in PBMCs from SLE patients and normal subjects using proteomics analyses. Phosphopeptides were enriched using TiO2 from PBMCs isolated from 15 SLE patients and 15 healthy subjects and then analyzed by automated LC-MS/MS analysis. Phosphorylation sites were identified and quantitated by MASCOT and MaxQuant. A total of 1035 phosphorylation sites corresponding to 618 NCBI-annotated genes were identified in SLE patients compared with normal subjects. Differentially expressed proteins, peptides and phosphorylation sites were then subjected to bioinformatics analyses. Gene ontology(GO) and pathway analyses showed that nucleic acid metabolism, cellular component organization, transport and multicellular organismal development pathways made up the largest proportions of the differentially expressed genes. Pathway analyses showed that the mitogen-activated protein kinase (MAPK) signaling pathway and actin cytoskeleton regulators made up the largest proportions of the metabolic pathways. Network analysis showed that rous sarcoma oncogene (SRC), v-rel reticuloendotheliosis viral oncogene homolog A (RELA), histone deacetylase (HDA1C) and protein kinase C, delta (PRKCD) play important roles in the stability of the network. These data suggest that aberrant protein phosphorylation may contribute to SLE pathogenesis.
PMCID: PMC3532163  PMID: 23285258
8.  Ser/Thr/Tyr Protein Phosphorylation in the Archaeon Halobacterium salinarum—A Representative of the Third Domain of Life 
PLoS ONE  2009;4(3):e4777.
In the quest for the origin and evolution of protein phosphorylation, the major regulatory post-translational modification in eukaryotes, the members of archaea, the “third domain of life”, play a protagonistic role. A plethora of studies have demonstrated that archaeal proteins are subject to post-translational modification by covalent phosphorylation, but little is known concerning the identities of the proteins affected, the impact on their functionality, the physiological roles of archaeal protein phosphorylation/dephosphorylation, and the protein kinases/phosphatases involved. These limited studies led to the initial hypothesis that archaea, similarly to other prokaryotes, use mainly histidine/aspartate phosphorylation, in their two-component systems representing a paradigm of prokaryotic signal transduction, while eukaryotes mostly use Ser/Thr/Tyr phosphorylation for creating highly sophisticated regulatory networks. In antithesis to the above hypothesis, several studies showed that Ser/Thr/Tyr phosphorylation is also common in the bacterial cell, and here we present the first genome-wide phosphoproteomic analysis of the model organism of archaea, Halobacterium salinarum, proving the existence/conservation of Ser/Thr/Tyr phosphorylation in the “third domain” of life, allowing a better understanding of the origin and evolution of the so-called “Nature's premier” mechanism for regulating the functional properties of proteins.
PMCID: PMC2652253  PMID: 19274099
9.  An Acetone-based Peptide Labeling and Mass Spectrometry Phosphoproteomics Workflow Enables Identification of Biomolecular Targets Relevant to a Fibroblast Growth Factor Induced Post-ischemic Cardiac Recovery 
Protein phosphorylation modulates normal cellular functions, and disease initiations/progressions, thus understanding phosphoproteomic changes of biological systems in response to external stimuli is essential for therapeutic interventions. Mass spectrometry (MS) methods are currently popular to study such changes, but have yet to become common in solving biological problems; partly due to expensive differential peptide tagging chemistries like iTRAQ (Isobaric Tags for Relative/Absolute Quantification) that are pivotal in comparing phosphoproteomes. A cost-effective MS-workflow that relies on acetone (d0 and d6) for peptide labeling which is amenable to phosphopeptide enrichment by TiO2-chromatography has been developed. This was achieved by applying the workflow to standard phosphoprotein alpha-casein and monitoring its predetermined quantitative ratios using mass spectrometry. Here, we apply the workflow to evaluate its robustness in delivering biologically relevant phosphoproteomic targets or elucidating signaling networks related to a cardiac injury model for subsequent therapeutic interventions.
/9LMW FGF2 (low-molecular weight fibroblast growth factor 2), improves post-ischemic recovery of cardiac function, which is mediated by various protein kinase signaling cascades. However, much is unknown about downstream targets and their phosphorylation changes induced by LMW FGF2 for improved cardiac function. Thus, using the developed workflow, five biologically distinct pair wise phosphoproteomic comparisons of cardiac tissue extracts obtained from “LMW FGF2-expressed” and “not-expressed” mouse hearts subjected to 60 minutes of ischemia and 5 minutes of reperfusion were performed. Alpha-casein was also “spiked-in” into the cardiac tissue extracts as an external standard to monitor procedural errors associated with the workflow. Phosphoproteomic differences in potential targets were revealed that are previously recognized and biologically relatable to cardioprotection signaling by LMW FGF2—e.g. cardiac myosin binding protein C (cMyBP-C) phosphorylations at Ser273, Ser282 and Ser-284, and connexin-43 (Cx43) phosphorylation, respectively. Also, identified phosphoproteins were several new LMW FGF2 targets that are being further evaluated in our labs for their significance.
PMCID: PMC3635419
10.  Division of labor by dual feedback regulators controls JAK2/STAT5 signaling over broad ligand range 
Quantitative analysis of time-resolved data in primary erythroid progenitor cells reveals that a dual negative transcriptional feedback mechanism underlies the ability of STAT5 to respond to the broad spectrum of physiologically relevant Epo concentrations.
A mathematical dual feedback model of the Epo-induced JAK2/STAT5 signaling pathway was calibrated with extensive time-resolved quantitative data sets from immunoblotting, mass spectrometry and qRT–PCR experiments in primary erythroid progenitor cells.We show that the amount of nuclear phosphorylated STAT5 integrated for 60 min post Epo stimulation directly correlates with the fraction of surviving cells 24 h later.CIS and SOCS3 were identified as the most relevant transcriptional feedback regulators of JAK2/STAT5 signaling in primary erythroid progenitor cells. Applying the model, we revealed that CIS-mediated inhibitory effects are most important at low ligand concentrations, whereas SOCS3 inhibition is more effective at high ligand doses.The distinct modes of inhibition of CIS and SOCS3 at various Epo concentrations provide a strategy for achieving control of JAK2/STAT5 signaling over the entire range of physiological Epo concentrations.
Cells interpret information encoded by extracellular stimuli through the activation of intracellular signaling networks and translate this information into cellular decisions. A prime example for a system that is exposed to extremely variable ligand concentrations is the erythroid lineage. The key regulator Erythropoietin (Epo) facilitates continuous renewal of erythrocytes at low basal levels but also secures compensation in case of, e.g., blood loss through an up to 1000-fold increase in hormone concentration. The Epo receptor (EpoR) is expressed on erythroid progenitor cells at the colony forming unit erythroid (CFU-E) stage. Stimulation of these cells with Epo leads to rapid but transient activation of receptor and JAK2 phosphorylation followed by phosphorylation of the latent transcription factor STAT5. Although STAT5 is known to be an essential regulator of survival and differentiation of erythroid progenitor cells, a quantitative link between the dynamic properties of STAT5 signaling and survival decisions remained unknown. STAT5-mediated responses in CFU-E cells are modulated by multiple attenuation mechanisms that operate on different time scales. Fast-acting mechanisms such as depletion of Epo by rapid receptor turnover and recruitment of the phosphatase SHP-1 control the initial signal amplitude at the receptor level. Transcriptional feedback regulators such as suppressor of cytokine signaling (SOCS) family members CIS and SOCS3 operate at a slower time scale. Despite the ample knowledge of the individual components involved, only little is known about the specific contributions of these regulators in controlling dynamic properties of STAT5 in response to a broad range of input signals. Therefore, dynamic pathway modeling is required to understand the complex regulatory network of feedback regulators.
To address these questions, we established a dual negative feedback model of JAK2/STAT5 signaling in primary erythroid progenitor cells isolated from mouse fetal livers. We provide a large data set of JAK2/STAT5 signaling dynamics employing quantitative immunoblotting, mass spectrometry and quantitative RT–PCR measured under different perturbation conditions to calibrate our model (Figure 3). The structure of our model was constructed to comprise the minimal number of parameters necessary to explain the data. Thereby, we aimed at a model with fully identifiable parameters that are essential to obtain high predictive power. Parameter identifiability was analyzed by the profile likelihood approach. Applying this method, we could establish a dual negative feedback model of JAK2-STAT5 signaling with structurally and in most cases practically identifiable parameters.
A major bottle-neck in combining signal transduction events with cellular phenotypes is the discrepancy in the time scale and stimuli concentrations that are applied in the different experiments. The sensitivity of biochemical assays to determine phosphorylation events within minutes or hours after stimulation is usually lower than the threshold of sensitivity in assays to determine the physiological response after one or more days. Facilitated by the model, we were able to compute the integrated response of JAK2/STAT5 signaling components for experimentally unaddressable Epo concentrations. Our results demonstrate that the integrated response of pSTAT5 in the nucleus accurately correlates with the experimentally determined survival of CFU-E cells. This provides a quantitative link of the dependency of primary CFU-E cells on pSTAT5 activation dynamics. By correlation analysis, we could identify the early signaling phase (⩽1 h) of STAT5 to be the most predictive for the fraction of surviving cells, which was determined ∼24 h later. Thus, we hypothesize that as a general principle in apoptotic decisions, ligand concentrations translated into kinetic-encoded information of early signaling events downstream of receptors can be predictive for survival decisions 24 h later.
After the first hour of stimulation, it is important to constrain signaling to a residual steady-state level. Constitutive phosphorylation of the JAK2/STAT5 pathway has a crucial role in the onset of polycythemia vera (PV), a disease associated with Epo-independent erythroid differentiation. The two identified transcriptional feedback proteins, CIS and SOCS3, are responsible for adjusting the phosphorylation level of STAT5 after 1 h of stimulation. Since the Epo input signal can vary over a broad range of ligand concentrations, we asked how CIS and SOCS3 can facilitate control of STAT5 long-term phosphorylation levels over the entire physiological relevant hormone concentrations. By using model simulations, we revealed that the two feedbacks are most effective at different Epo concentration ranges. Predicted by our mathematical model, the major role of CIS in modulating STAT5 phosphorylation levels is at low, basal Epo concentrations, whereas SOCS3 is essential to control the STAT5 phosphorylation levels at high Epo doses (Figure 6). As a potential molecular mechanism of this dose-dependent inhibitory effect, we could identify the quantity of pJAK2 relative to pEpoR that increases with higher Epo concentrations. Since SOCS3 can inhibit JAK2 directly via its KIR domain to attenuate downstream STAT5 activation, SOCS3 becomes more effective with the relative increase of JAK2 activation. Hence, CIS and SOCS3 act in a concerted manner to ensure tight regulation of STAT5 responses over the broad physiological range of Epo concentrations.
In summary, our mathematical approach provided new insights into the specific function of feedback regulation in STAT5-mediated life or death decisions of primary erythroid cells. We dissected the roles of the transcriptionally induced proteins CIS and SOCS3 that operate as dual feedback with divided function thereby facilitating the control of STAT5 activation levels over the entire range of physiological Epo concentrations. The detailed understanding of the molecular processes and control distribution of Epo-induced JAK/STAT signaling can be further applied to gain insights into alterations promoting malignant hematopoietic diseases.
Cellular signal transduction is governed by multiple feedback mechanisms to elicit robust cellular decisions. The specific contributions of individual feedback regulators, however, remain unclear. Based on extensive time-resolved data sets in primary erythroid progenitor cells, we established a dynamic pathway model to dissect the roles of the two transcriptional negative feedback regulators of the suppressor of cytokine signaling (SOCS) family, CIS and SOCS3, in JAK2/STAT5 signaling. Facilitated by the model, we calculated the STAT5 response for experimentally unobservable Epo concentrations and provide a quantitative link between cell survival and the integrated response of STAT5 in the nucleus. Model predictions show that the two feedbacks CIS and SOCS3 are most effective at different ligand concentration ranges due to their distinct inhibitory mechanisms. This divided function of dual feedback regulation enables control of STAT5 responses for Epo concentrations that can vary 1000-fold in vivo. Our modeling approach reveals dose-dependent feedback control as key property to regulate STAT5-mediated survival decisions over a broad range of ligand concentrations.
PMCID: PMC3159971  PMID: 21772264
apoptosis; erythropoietin; mathematical modeling; negative feedback; SOCS
11.  Integrating Phosphoproteomics and Bioinformatics to Study Brassinosteroid-Regulated Phosphorylation Dynamics in Arabidopsis 
BMC Genomics  2015;16(1):533.
Protein phosphorylation regulated by plant hormone is involved in the coordination of fundamental plant development. Brassinosteroids (BRs), a group of phytohormones, regulated phosphorylation dynamics remains to be delineated in plants. In this study, we performed a mass spectrometry (MS)-based phosphoproteomics to conduct a global and dynamic phosphoproteome profiling across five time points of BR treatment in the period between 5 min and 12 h. MS coupling with phosphopeptide enrichment techniques has become the powerful tool for profiling protein phosphorylation. However, MS-based methods tend to have data consistency and coverage issues. To address these issues, bioinformatics approaches were used to complement the non-detected proteins and recover the dynamics of phosphorylation events.
A total of 1104 unique phosphorylated peptides from 739 unique phosphoproteins were identified. The time-dependent gene ontology (GO) analysis shows the transition of biological processes from signaling transduction to morphogenesis and stress response. The protein-protein interaction analysis found that most of identified phosphoproteins have strongly connections with known BR signaling components. The analysis by using Motif-X was performed to identify 15 enriched motifs, 11 of which correspond to 6 known kinase families. To uncover the dynamic activities of kinases, the enriched motifs were combined with phosphorylation profiles and revealed that the substrates of casein kinase 2 and mitogen-activated protein kinase were significantly phosphorylated and dephosphorylated at initial time of BR treatment, respectively. The time-dependent kinase-substrate interaction networks were constructed and showed many substrates are the downstream of other signals, such as auxin and ABA signaling. While comparing BR responsive phosphoproteome and gene expression data, we found most of phosphorylation changes were not led by gene expression changes. Our results suggested many downstream proteins of BR signaling are induced by phosphorylation via various kinases, not through transcriptional regulation.
Through a large-scale dynamic profile of phosphoproteome coupled with bioinformatics, a complicated kinase-centered network related to BR-regulated growth was deciphered. The phosphoproteins and phosphosites identified in our study provide a useful dataset for revealing signaling networks of BR regulation, and also expanded our knowledge of protein phosphorylation modification in plants as well as further deal to solve the plant growth problems.
Electronic supplementary material
The online version of this article (doi:10.1186/s12864-015-1753-4) contains supplementary material, which is available to authorized users.
PMCID: PMC4506601  PMID: 26187819
Phosphoproteomics; Bioinformatics; Brassinosteroids; Phosphorylation dynamics; Kinase-centered network
12.  Analysis of the Phosphoproteome of Chlamydomonas reinhardtii Provides New Insights into Various Cellular Pathways†  
Eukaryotic Cell  2006;5(3):457-468.
The unicellular flagellated green alga Chlamydomonas reinhardtii has emerged as a model organism for the study of a variety of cellular processes. Posttranslational control via protein phosphorylation plays a key role in signal transduction, regulation of gene expression, and control of metabolism. Thus, analysis of the phosphoproteome of C. reinhardtii can significantly enhance our understanding of various regulatory pathways. In this study, we have grown C. reinhardtii cultures in the presence of an inhibitor of Ser/Thr phosphatases to increase the phosphoprotein pool. Phosphopeptides from these cells were enriched by immobilized metal-ion affinity chromatography and analyzed by nano-liquid chromatography-electrospray ionization-mass spectrometry (MS) with MS-MS as well as neutral-loss-triggered MS-MS-MS spectra. In this way, we were able to identify 360 phosphopeptides from 328 different phosphoproteins of C. reinhardtii, thus providing new insights into a variety of cellular processes, including metabolic and signaling pathways. Comparative analysis of the phosphoproteome also yielded new functional information on proteins controlled by redox regulation (thioredoxin target proteins) and proteins of the chloroplast 70S ribosome, the centriole, and especially the flagella, for which 32 phosphoproteins were identified. The high yield of phosphoproteins of the latter correlates well with the presence of several flagellar kinases and indicates that phosphorylation/dephosphorylation represents one of the key regulatory mechanisms of eukaryotic cilia. Our data also provide new insights into certain cilium-related mammalian diseases.
PMCID: PMC1398068  PMID: 16524901
13.  Cross-talk between phosphorylation and lysine acetylation in a genome-reduced bacterium 
The effect of kinase, phosphatase and N-acetyltransferase deletions on proteome phosphorylation and acetylation was investigated in Mycoplasma pneumoniae. Bi-directional cross-talk between post-transcriptional modifications suggests an underlying regulatory molecular code in prokaryotes.
Post-translational modifications (PTMs) change the chemical properties of proteins, conferring diversity beyond the amino-acid sequence. Proteins are often modified on multiple sites. A PTM code has been proposed, whereby modifications at specific positions influence further modifications. These regulatory circuits though have rarely been studied on a large-scale; conservation in prokaryotes remains elusive.Here, we studied two important PTMs– phosphorylation and lysine acetylation in the small bacterium Mycoplasma pneumoniae. We combined genetics and quantitative mass spectrometry to measure the effect of systematic kinase, phosphatase and N-acetyltransferase deletions on proteome abundance, phosphorylation and lysine acetylation.The data set represents a comprehensive analysis of both phosphorylation and lysine acetylation in a single prokaryote. It reveals (1) proteins often carry multiple modifications and multiple types of PTMs, reminiscent of the PTM code proposed in eukaryotes, (2) phosphorylation exerts pleiotropic effect on proteins abundances, phosphorylation, but also lysine acetylation, (3) the cross-talk between the two PTMs is bi-directional and (4) PTMs are frequently located at interaction interfaces and in multifunctional proteins, illustrating how PTMs could modulate protein functions affecting the way they interact.The study provides an unbiased and quantitative view on cross-talk between phosphorylation and lysine acetylation. It suggests that these regulatory circuits are a fundamental principle of regulation that might have evolved before the divergence of prokaryotes and eukaryotes.
Protein post-translational modifications (PTMs) represent important regulatory states that when combined have been hypothesized to act as molecular codes and to generate a functional diversity beyond genome and transcriptome. We systematically investigate the interplay of protein phosphorylation with other post-transcriptional regulatory mechanisms in the genome-reduced bacterium Mycoplasma pneumoniae. Systematic perturbations by deletion of its only two protein kinases and its unique protein phosphatase identified not only the protein-specific effect on the phosphorylation network, but also a modulation of proteome abundance and lysine acetylation patterns, mostly in the absence of transcriptional changes. Reciprocally, deletion of the two putative N-acetyltransferases affects protein phosphorylation, confirming cross-talk between the two PTMs. The measured M. pneumoniae phosphoproteome and lysine acetylome revealed that both PTMs are very common, that (as in Eukaryotes) they often co-occur within the same protein and that they are frequently observed at interaction interfaces and in multifunctional proteins. The results imply previously unreported hidden layers of post-transcriptional regulation intertwining phosphorylation with lysine acetylation and other mechanisms that define the functional state of a cell.
PMCID: PMC3293634  PMID: 22373819
kinase; N-acetyltransferase; network; phosphatase; post-translational modification
14.  A modular gradient-sensing network for chemotaxis in Escherichia coli revealed by responses to time-varying stimuli 
Combining in vivo FRET with time-varying stimuli, such as steps, ramps, and sinusoids allowed deduction of the molecular mechanisms underlying cellular signal processing.The bacterial chemotaxis pathway can be described as a two-module feedback circuit, the transfer functions of which we have characterized quantitatively by experiment. Model-driven experimental design allowed the use of a single FRET pair for measurements of both transfer functions of the pathway.The adaptation module's transfer function revealed that feedback near steady state is weak, consistent with high sensitivity to shallow gradients, but also strong steady-state fluctuations in pathway output.The measured response to oscillatory stimuli defines the frequency band over which the chemotaxis system can compute time derivatives.
In searching for better environments, bacteria sample their surroundings by random motility, and make temporal comparisons of experienced sensory cues to bias their movement toward favorable directions (Berg and Brown, 1972). Thus, the problem of sensing spatial gradients is reduced to time-derivative computations, carried out by a signaling pathway that is well characterized at the molecular level in Escherichia coli. Here, we study the physiology of this signal processing system in vivo by fluorescence resonance energy transfer (FRET) experiments in which live cells are stimulated by time-varying chemoeffector signals. By measuring FRET between the active response regulator of the pathway CheY-P and its phosphatase CheZ, each labeled with GFP variants, we obtain a readout that is directly proportional to pathway activity (Sourjik et al, 2007). We analyze the measured response functions in terms of mechanistic models of signaling, and discuss functional consequences of the observed quantitative characteristics.
Experiments are guided by a coarse-grained modular model (Tu et al, 2008) of the sensory network (Figure 1), in which we identify two important ‘transfer functions': one corresponding to the receptor–kinase complex, which responds to changes in input ligand concentration on a fast time scale, and another corresponding to the adaptation system, which provides negative feedback, opposing the effect of ligand on a slower time scale. For the receptor module, we calibrate an allosteric MWC-type model of the receptor–kinase complex by FRET measurements of the ‘open-loop' transfer function G([L],m) using step stimuli. This calibration provides a basis for using the same FRET readout (between CheY-P and CheZ) to further study properties of the adaptation module.
It is well known that adaptation in E. coli's chemotaxis system uses integral feedback, which guarantees exact restoration of the baseline activity after transient responses to step stimuli (Barkai and Leibler, 1997; Yi et al, 2000). However, the output of time-derivative computations during smoothly varying stimuli depends not only on the presence of integral feedback, but also on what is being integrated. As this integrand can in general be any function of the output, we represent it by a black-box function F(a) in our model, and set out to determine its shape by experiments with time-varying stimuli.
We first apply exponential ramp stimuli—waveforms in which the logarithm of the stimulus level varies linearly with time, at a fixed rate r. It was shown many years ago that during such a stimulus, the kinase output of the pathway changes to a new constant value, ac that is dependent on the applied ramp rate, r (Block et al, 1983). A plot of ac versus r (Figure 5A) can thus be considered as an output of time-derivative computations by the network, and could also be used to study the ‘gradient sensitivity' of bacteria traveling at constant speeds.
To obtain the feedback transfer function, F(a), we apply a simple coordinate transformation, identified using our model, to the same ramp-response data (Figure 5B). This function reveals how the temporal rate of change of the feedback signal m depends on the current output signal a. The shape of this function is analyzed using a biochemical reaction scheme, from which in vivo kinetic parameters of the feedback enzymes, CheR and CheB, are extracted. The fitted Michaelis constants for these enzymatic reactions are small compared with the steady-state abundance of their substrates, thus indicating that these enzymes operate close to saturation in vivo. The slope of the function near steady state can be used to assess the strength of feedback, and to compute the relaxation time of the system, τm. Relaxation is found to be slow (i.e. large τm), consistent with large fluctuations about the steady-state activity caused by the near-saturation kinetics of the feedback enzymes (Emonet and Cluzel, 2008).
Finally, exponential sine-wave stimuli are used to map out the system's frequency response (Figure 5C). The measured data points for both the amplitude and phase of the response are found to be in excellent agreement with model predictions based on parameters from the independently measured step and ramp responses. No curve fitting was required to obtain this agreement. Although the amplitude response as a function of frequency resembles a first-order high-pass filter with a well-defined cutoff frequency, νm, we point out that the chemotaxis pathway is actually a low-pass filter if the time derivative of the input is viewed as the input signal. In this latter perspective, νm defines an upper bound for the frequency band over which time-derivative computations can be carried out.
The two types of measurements yield complementary information regarding time-derivative computations by E. coli. The ramp-responses characterize the asymptotically constant output when a temporal gradient is held fixed over extended periods. Interestingly, the ramp responses do not depend on receptor cooperativity, but only on properties of the adaptation system, and thus can be used to reveal the in vivo adaptation kinetics, even outside the linear regime of the kinase response. The frequency response is highly relevant in considering spatial searches in the real world, in which experienced gradients are not held fixed in time. The characteristic cutoff frequency νm is found by working within the linear regime of the kinase response, and depends on parameters from both modules (it increases with both cooperativity in the receptor module, and the strength of feedback in the adaptation module).
Both ramp responses and sine-wave responses were measured at two different temperatures (22 and 32°C), and found to differ significantly. Both the slope of F(a) near steady state, from ramp experiments, and the characteristic cutoff frequency, from sine-wave experiments, were higher by a factor of ∼3 at 32°C. Fits of the enzymatic model to F(a) suggest that temperature affects the maximal velocity (Vmax) more strongly than the Michaelis constants (Km) for CheR and CheB.
Successful application of inter-molecular FRET in live cells using GFP variants always requires some degree of serendipity. Genetic fusions to these bulky fluorophores can impair the function of the original proteins, and even when fusions are functional, efficient FRET still requires the fused fluorophores to come within the small (<10 nm) Förster radius on interactions between the labeled proteins. Thus, when a successful FRET pair is identified, it is desirable to make the most of it. We have shown here that combined with careful temporal control of input stimuli, and appropriately calibrated models, a single FRET pair can be used to study the structure of multiple transfer functions within a signaling network.
The Escherichia coli chemotaxis-signaling pathway computes time derivatives of chemoeffector concentrations. This network features modules for signal reception/amplification and robust adaptation, with sensing of chemoeffector gradients determined by the way in which these modules are coupled in vivo. We characterized these modules and their coupling by using fluorescence resonance energy transfer to measure intracellular responses to time-varying stimuli. Receptor sensitivity was characterized by step stimuli, the gradient sensitivity by exponential ramp stimuli, and the frequency response by exponential sine-wave stimuli. Analysis of these data revealed the structure of the feedback transfer function linking the amplification and adaptation modules. Feedback near steady state was found to be weak, consistent with strong fluctuations and slow recovery from small perturbations. Gradient sensitivity and frequency response both depended strongly on temperature. We found that time derivatives can be computed by the chemotaxis system for input frequencies below 0.006 Hz at 22°C and below 0.018 Hz at 32°C. Our results show how dynamic input–output measurements, time honored in physiology, can serve as powerful tools in deciphering cell-signaling mechanisms.
PMCID: PMC2913400  PMID: 20571531
adaptation; feedback; fluorescence resonance energy transfer (FRET); frequency response; Monod–Wyman–Changeux (MWC) model
15.  P3DB 3.0: From plant phosphorylation sites to protein networks 
Nucleic Acids Research  2013;42(Database issue):D1206-D1213.
In the past few years, the Plant Protein Phosphorylation Database (P3DB, has become one of the most significant in vivo data resources for studying plant phosphoproteomics. We have substantially updated P3DB with respect to format, new datasets and analytic tools. In the P3DB 3.0, there are altogether 47 923 phosphosites in 16 477 phosphoproteins curated across nine plant organisms from 32 studies, which have met our multiple quality standards for acquisition of in vivo phosphorylation site data. Centralized by these phosphorylation data, multiple related data and annotations are provided, including protein–protein interaction (PPI), gene ontology, protein tertiary structures, orthologous sequences, kinase/phosphatase classification and Kinase Client Assay (KiC Assay) data—all of which provides context for the phosphorylation event. In addition, P3DB 3.0 incorporates multiple network viewers for the above features, such as PPI network, kinase-substrate network, phosphatase-substrate network, and domain co-occurrence network to help study phosphorylation from a systems point of view. Furthermore, the new P3DB reflects a community-based design through which users can share datasets and automate data depository processes for publication purposes. Each of these new features supports the goal of making P3DB a comprehensive, systematic and interactive platform for phosphoproteomics research.
PMCID: PMC3965113  PMID: 24243849
16.  Large-scale phosphoproteome analysis in seedling leaves of Brachypodium distachyon L. 
BMC Genomics  2014;15(1):375.
Protein phosphorylation is one of the most important post-translational modifications involved in the regulation of plant growth and development as well as diverse stress response. As a member of the Poaceae, Brachypodium distachyon L. is a new model plant for wheat and barley as well as several potential biofuel grasses such as switchgrass. Vegetative growth is vital for biomass accumulation of plants, but knowledge regarding the role of protein phosphorylation modification during vegetative growth, especially in biofuel plants, is far from comprehensive.
In this study, we carried out the first large-scale phosphoproteome analysis of seedling leaves in Brachypodium accession Bd21 using TiO2 microcolumns combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) and MaxQuant software. A total of 1470 phosphorylation sites in 950 phosphoproteins were identified, and these phosphoproteins were implicated in various molecular functions and basic cellular processes by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Among the 950 phosphoproteins identified, 127 contained 3 to 8 phosphorylation sites. Conservation analysis showed that 93.4% of the 950 phosphoproteins had phosphorylation orthologs in other plant species. Motif-X analysis of the phosphorylation sites identified 13 significantly enriched phosphorylation motifs, of which 3 were novel phosphorylation motifs. Meanwhile, there were 91 phosphoproteins with both multiple phosphorylation sites and multiple phosphorylation motifs. In addition, we identified 58 phosphorylated transcription factors across 21 families and found out 6 significantly over-represented transcription factor families (C3H, Trihelix, CAMTA, TALE, MYB_related and CPP). Eighty-four protein kinases (PKs), 8 protein phosphatases (PPs) and 6 CESAs were recognized as phosphoproteins.
Through a large-scale bioinformatics analysis of the phosphorylation data in seedling leaves, a complicated PKs- and PPs- centered network related to rapid vegetative growth was deciphered in B. distachyon. We revealed a MAPK cascade network that might play the crucial roles during the phosphorylation signal transduction in leaf growth and development. The phosphoproteins and phosphosites identified from our study expanded our knowledge of protein phosphorylation modification in plants, especially in monocots.
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-375) contains supplementary material, which is available to authorized users.
PMCID: PMC4079959  PMID: 24885693
Bd21; Leaf; Phosphoproteome; Transcription factors; Phosphorylation motif; Protein kinases
17.  Towards Systematic Discovery of Signaling Networks in Budding Yeast Filamentous Growth Stress Response Using Interventional Phosphorylation Data 
PLoS Computational Biology  2013;9(6):e1003077.
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.
Author Summary
Signal transduction is a ubiquitous and essential mechanism regulating cellular functions, including responses to environmental stress. Dysfunction of signaling pathways results in a variety of diseases, including cancer, diabetes, and cardiovascular disease. Phosphorylation regulates the activity of signaling and target proteins at different cellular locations and controls activation and inactivation of signal pathways. Here, we provide an analysis of phosphoproteome datasets from yeast, utilizing kinase mutants versus wild type strains. In order to provide an objective approach to identify candidate proteins involved in the transition to a filamentous growth form, we proposed and applied a comprehensive pipeline incorporating statistical and mathematical methods to investigate the phosphoproteome data from multiple perspectives. This included phosphorylation variation in response to a single mutant, phosphorylation variation patterns over multiple mutants, and the relationships represented by these patterns. We make an effort to discover the components and targets of the signaling network, infer the network structure, and to find the relationships of changes of protein phosphorylation to cellular functions, specifically in response to stress in the context of filamentous growth.
PMCID: PMC3694812  PMID: 23825934
18.  A systems toxicology approach identifies Lyn as a key signaling phosphoprotein modulated by mercury in a B lymphocyte cell model 
Network and protein-protein interaction analyses of proteins undergoing Hg2+-induced phosphorylation and dephosphorylation in Hg2+-intoxicated mouse WEHI-231 B cells identified Lyn as the most interconnected node. Lyn is a Src family protein tyrosine kinase known to be intimately involved in the B Cell Receptor (BCR) signaling pathway. Under normal signaling conditions the tyrosine kinase activity of Lyn is controlled by phosphorylation, primarily of two well known canonical regulatory tyrosine sites, Y-397 and Y-508. However, Lyn has several tyrosine residues that have not yet been determined to play a major role under normal signaling conditions, but are potentially important sites for phosphorylation following mercury exposure. In order to determine how Hg2+ exposure modulates the phosphorylation of additional residues in Lyn, a targeted MS assay was developed. Initial mass spectrometric surveys of purified Lyn identified 7 phosphorylated tyrosine residues. A quantitative assay was developed from these results using the multiple reaction monitoring (MRM) strategy. WEHI-231 cells were treated with Hg2+, pervanadate (a phosphatase inhibitor), or anti-Ig antibody (to stimulate the BCR). Results from these studies showed that the phosphoproteomic profile of Lyn after exposure of the WEHI-231 cells to low a low concentration of Hg2+ closely resembled that of anti-Ig antibody stimulation, whereas exposure to higher concentrations of Hg2+ led to increases in the phosphorylation of Y-193/Y-194, Y-501 and Y-508 residues. These data indicate that mercury can disrupt a key regulatory signal transduction pathway in B cells and point to phospho-Lyn as a potential biomarker for mercury exposure.
PMCID: PMC4005802  PMID: 24440445
autoimmune disease; B cell; Lyn; mass spectrometry; mercury; multiple reaction monitoring; phosphoproteomics; systems biology; toxicology; WEHI-231
19.  Modularity and hormone sensitivity of the Drosophila melanogaster insulin receptor/target of rapamycin interaction proteome 
First systematic analysis of the evolutionary conserved InR/TOR pathway interaction proteome in Drosophila.Quantitative mass spectrometry revealed that 22% of identified protein interactions are regulated by the growth hormone insulin affecting membrane proximal as well as intracellular signaling complexes.Systematic RNA interference linked a significant fraction of network components to the control of dTOR kinase activity.Combined biochemical and genetic data suggest dTTT, a dTOR-containing complex required for cell growth control by dTORC1 and dTORC2 in vivo.
Cellular growth is a fundamental process that requires constant adaptations to changing environmental conditions, like growth factor and nutrient availability, energy levels and more. Over the years, the insulin receptor/target of rapamycin pathway (InR/TOR) emerged as a key signaling system for the control of metazoan cell growth. Genetic screens carried out in the fruit fly Drosophila melanogaster identified key InR/TOR pathway components and their relationships. Phenotypes such as altered cell growth are likely to emerge from perturbed dynamic networks containing InR/TOR pathway components, which stably or transiently interact with other cellular proteins to form complexes and networks thereof. Systematic studies on the topology and dynamics of protein interaction networks become therefore highly relevant to gain systems level understanding of deregulated cell growth. Despite much progress in genetic analysis only few systematic protein interaction studies have been reported for Drosophila, which in most cases lack quantitative information representing the dynamic nature of such networks. Here, we present the first quantitative affinity purification mass spectrometry (AP–MS/MS) analysis on the evolutionary conserved InR/TOR signaling network in Drosophila. Systematic RNAi-based functional analysis of identified network components revealed key components linked to the regulation of the central effector kinase dTOR. This includes also dTTT, a novel dTOR-containing complex required for the control of dTORC1 and dTORC2 in vivo.
For systematic AP–MS analysis, we generated Drosophila Kc167 cell lines inducibly expressing affinity-tagged bait proteins previously linked to InR/TOR signaling. Bait expressing Kc167 cell lines were harvested before and after insulin stimulation for subsequent affinity purification. Following LC–MS/MS analysis and probabilistic data filtering using SAINT (Choi et al, 2010), we generated a quantitative network model from 97 high confidence protein–protein interactions and 58 network components (Figure 2). The presented network displayed a high degree of orthologous interactions conserved also in human cells and identified a number of novel molecular interactions with InR/TOR signaling components for future hypothesis driven analysis.
To measure insulin-induced changes within the InR/TOR interaction proteome, we applied a recently introduced label-free quantitative MS approach (Rinner et al, 2007). The obtained quantitative data suggest that 22% of all interactions in the network are regulated by insulin. Major changes could be observed within the membrane proximal InR/chico/PI3K signaling complexes, and also in 14-3-3 protein containing signaling complexes and dTORC1, a complex that contains besides dTOR all major orthologous proteins found also in human mTORC1 including the two dTORC1 substrates d4E-BP (Thor) and S6 Kinase (S6K). Insulin triggered both, dissociation and association of dTORC1 proteins. Among the proteins that showed enhanced binding to dTORC1 upon insulin stimulation we found Unkempt, a RING-finger protein with a proposed role in ubiquitin-mediated protein degradation (Lores et al, 2010). Besides dTORC1 our systematic AP–MS analysis also revealed the presence of dTORC2, the second major TOR complex in Drosophila. dTORC2 contains the Drosophila orthologous of human mTORC2 proteins, but in contrast to dTORC1 was not affected upon insulin stimulation. Interestingly, we also found a specific set of proteins that were not linked to the canonical TOR complexes TORC1 and TORC2 in dTOR purifications. These include LqfR (liquid facets related), Pontin, Reptin, Spaghetti and the gene product of CG16908. We found the same set of proteins when we used CG16908 as a bait, suggesting complex formation among the identified proteins. None of the dTORC1/2 components besides dTOR was identified in CG16908 purifications, indicating that these proteins form dTOR complexes distinct from dTORC1 and dTORC2. Based on known interaction information from other species and data obtained from this study we refer to this complex as dTTT (Drosophila TOR, TELO2, TTI1) (Horejsi et al, 2010; [18]Hurov et al, 2010; [20]Kaizuka et al, 2010). A directed quantitative MS analysis of dTOR complex components suggests that dTORC1 is the most abundant dTOR complex we identified in Kc167 cells.
We next studied the potential roles of the identified network components for controlling the activity of the dInR/TOR pathway using systematic RNAi depletion and quantitative western blotting to measure the changes in abundance of phosphorylated substrates of dTORC1 (Thor/d4E-BP, dS6K) and dTORC2 (dPKB) in RNAi-treated cells (Figure 5). Overall, we could identify 16 proteins (out of 58) whose depletion caused an at least 50% increase or decrease in the levels of phosphorylated d4E-BP, S6K and/or PKB compared with control GFP RNAi. Besides established pathway components, we found several novel regulators within the dInR/TOR interaction network. For example, RNAi against the novel insulin-regulated dTORC1 component Unkempt resulted in enhanced phosphorylation of the dTORC1 substrate d4E-BP, which suggests a negative role for Unkempt on dTORC1 activity. In contrast, depletion of CG16908 and LqfR caused hypo-phosphorylation of all dTOR substrates similar to dTOR itself, suggesting a positive role for the dTTT complex on dTOR activity. Subsequently, we tested whether dTTT components also plays a role in dTOR-mediated cell growth in vivo. Depletion of both dTTT components, CG16908 and LqfR, in the Drosophila eye resulted in a substantial decrease in eye size. Likewise, FLP-FRT-mediated mitotic recombination resulted in CG16908 and LqfR mutant clones with a similar reduced growth phenotype as observed in dTOR mutant clones. Hence, the combined biochemical and genetic analysis revealed dTTT as a dTOR-containing complex required for the activity of both dTORC1 and dTORC2 and thus plays a critical role in controlling cell growth.
Taken together, these results illustrate how a systematic quantitative AP–MS approach when combined with systematic functional analysis in Drosophila can reveal novel insights into the dynamic organization of regulatory networks for cell growth control in metazoans.
Using quantitative mass spectrometry, this study reports how insulin affects the modularity of the interaction proteome of the Drosophila InR/TOR pathway, an evolutionary conserved signaling system for the control of metazoan cell growth. Systematic functional analysis linked a significant number of identified network components to the control of dTOR activity and revealed dTTT, a dTOR complex required for in vivo cell growth control by dTORC1 and dTORC2.
Genetic analysis in Drosophila melanogaster has been widely used to identify a system of genes that control cell growth in response to insulin and nutrients. Many of these genes encode components of the insulin receptor/target of rapamycin (InR/TOR) pathway. However, the biochemical context of this regulatory system is still poorly characterized in Drosophila. Here, we present the first quantitative study that systematically characterizes the modularity and hormone sensitivity of the interaction proteome underlying growth control by the dInR/TOR pathway. Applying quantitative affinity purification and mass spectrometry, we identified 97 high confidence protein interactions among 58 network components. In all, 22% of the detected interactions were regulated by insulin affecting membrane proximal as well as intracellular signaling complexes. Systematic functional analysis linked a subset of network components to the control of dTORC1 and dTORC2 activity. Furthermore, our data suggest the presence of three distinct dTOR kinase complexes, including the evolutionary conserved dTTT complex (Drosophila TOR, TELO2, TTI1). Subsequent genetic studies in flies suggest a role for dTTT in controlling cell growth via a dTORC1- and dTORC2-dependent mechanism.
PMCID: PMC3261712  PMID: 22068330
cell growth; InR/TOR pathway; interaction proteome; quantitative mass spectrometry; signaling
20.  Phosphoproteomic Analysis of KSHV-Infected Cells Reveals Roles of ORF45-Activated RSK during Lytic Replication 
PLoS Pathogens  2015;11(7):e1004993.
Kaposi’s Sarcoma-Associated Herpesvirus (KSHV) is an oncogenic virus which has adapted unique mechanisms to modulate the cellular microenvironment of its human host. The pathogenesis of KSHV is intimately linked to its manipulation of cellular signaling pathways, including the extracellular signal-regulated kinase (ERK) mitogen-activated protein kinase (MAPK) pathway. We have previously shown that KSHV ORF45 contributes to the sustained activation of both ERK and p90 ribosomal S6 kinase (RSK, a major functional mediator of ERK/MAPK signaling) during KSHV lytic replication. ORF45-activated RSK is required for optimal KSHV lytic gene expression and progeny virion production, though the underlying mechanisms downstream of this activation are still unclear. We hypothesized that the activation of RSK by ORF45 causes differential phosphorylation of cellular and viral substrates, affecting biological processes essential for efficient KSHV lytic replication. Accordingly, we observed widespread and significant differences in protein phosphorylation upon induction of lytic replication. Mass-spectrometry-based phosphoproteomic screening identified putative substrates of ORF45-activated RSK in KSHV-infected cells. Bioinformatic analyses revealed that nuclear proteins, including several transcriptional regulators, were overrepresented among these candidates. We validated the ORF45/RSK-dependent phosphorylation of several putative substrates by employing KSHV BAC mutagenesis, kinase inhibitor treatments, and/or CRISPR-mediated knockout of RSK in KSHV-infected cells. Furthermore, we assessed the consequences of knocking out these substrates on ORF45/RSK-dependent regulation of gene expression and KSHV progeny virion production. Finally, we show data to support that ORF45 regulates the translational efficiency of a subset of viral/cellular genes with complex secondary structure in their 5’ UTR. Altogether, these data shed light on the mechanisms by which KSHV ORF45 manipulates components of the host cell machinery via modulation of RSK activity. Thus, this study has important implications for the pathobiology of KSHV and other diseases in which RSK activity is dysregulated.
Author Summary
Kaposi’s sarcoma-associated herpesvirus (KSHV) is a human tumor virus which hijacks the host signaling pathways in order to maintain persistent infection. We previously discovered that the KSHV protein ORF45 binds to and activates the cellular kinase RSK (p90 ribosomal S6 kinase), and that this activation is vital for optimal KSHV gene expression and virion production. Here, we performed a phosphoproteomic analysis of KSHV-infected cells to further characterize the specific substrates of ORF45-activated RSK. Bioinformatic analyses provided insights into the functional roles of these substrates. We verified the ORF45/RSK-dependent phosphorylation of a subset of these substrates by various means. Finally, we used genome editing to knock out RSK, as well as several cellular substrates identified by our screening, and characterized the consequent effect(s) on regulation of gene expression and virion production. Thus, this work further elucidates one of the key signaling nodes modulated by KSHV, and implicates ORF45-mediated activation of RSK in the regulation of viral and host gene expression during KSHV lytic replication.
PMCID: PMC4489790  PMID: 26133373
21.  Cellular phosphatases facilitate combinatorial processing of receptor-activated signals 
BMC Research Notes  2008;1:81.
Although reciprocal regulation of protein phosphorylation represents a key aspect of signal transduction, a larger perspective on how these various interactions integrate to contribute towards signal processing is presently unclear. For example, a key unanswered question is that of how phosphatase-mediated regulation of phosphorylation at the individual nodes of the signaling network translates into modulation of the net signal output and, thereby, the cellular phenotypic response.
To address the above question we, in the present study, examined the dynamics of signaling from the B cell antigen receptor (BCR) under conditions where individual cellular phosphatases were selectively depleted by siRNA. Results from such experiments revealed a highly enmeshed structure for the signaling network where each signaling node was linked to multiple phosphatases on the one hand, and each phosphatase to several nodes on the other. This resulted in a configuration where individual signaling intermediates could be influenced by a spectrum of regulatory phosphatases, but with the composition of the spectrum differing from one intermediate to another. Consequently, each node differentially experienced perturbations in phosphatase activity, yielding a unique fingerprint of nodal signals characteristic to that perturbation. This heterogeneity in nodal experiences, to a given perturbation, led to combinatorial manipulation of the corresponding signaling axes for the downstream transcription factors.
Our cumulative results reveal that it is the tight integration of phosphatases into the signaling network that provides the plasticity by which perturbation-specific information can be transmitted in the form of a multivariate output to the downstream transcription factor network. This output in turn specifies a context-defined response, when translated into the resulting gene expression profile.
PMCID: PMC2573882  PMID: 18798986
22.  Systems-wide Analysis of a Phosphatase Knock-down by Quantitative Proteomics and Phosphoproteomics 
Signal transduction in metazoans regulates almost all aspects of biological function, and aberrant signaling is involved in many diseases. Perturbations in phosphorylation-based signaling networks are typically studied in a hypothesis-driven approach, using phospho-specific antibodies. Here we apply quantitative, high-resolution mass spectrometry to determine the systems response to the depletion of one signaling component. Drosophila cells were metabolically labeled using stable isotope labeling by amino acids in cell culture (SILAC) and the phosphatase Ptp61F, the ortholog of mammalian PTB1B, a drug target for diabetes, was knocked down by RNAi. In total we detected more than 10,000 phosphorylation sites in the phosphoproteome of Drosophila Schneider cells and trained a phosphorylation site predictor with this data. SILAC-based quantitation after phosphatase knock-down showed that apart from the phosphatase, the proteome was minimally affected whereas 288 of 6,478 high-confidence phosphorylation sites changed significantly. Responses at the phosphotyrosine level included the already described Ptp61F substrates Stat92E and Abi. Our analysis highlights a connection of Ptp61F to cytoskeletal regulation through GTPase regulating proteins and focal adhesion components.
PMCID: PMC2722773  PMID: 19429919
23.  Phosphoproteomics of collagen receptor networks reveals SHP-2 phosphorylation downstream of wild-type DDR2 and its lung cancer mutants 
Biochemical Journal  2013;454(Pt 3):501-513.
Collagen is an important extracellular matrix component that directs many fundamental cellular processes including differentiation, proliferation and motility. The signalling networks driving these processes are propagated by collagen receptors such as the β1 integrins and the DDRs (discoidin domain receptors). To gain an insight into the molecular mechanisms of collagen receptor signalling, we have performed a quantitative analysis of the phosphorylation networks downstream of collagen activation of integrins and DDR2. Temporal analysis over seven time points identified 424 phosphorylated proteins. Distinct DDR2 tyrosine phosphorylation sites displayed unique temporal activation profiles in agreement with in vitro kinase data. Multiple clustering analysis of the phosphoproteomic data revealed several DDR2 candidate downstream signalling nodes, including SHP-2 (Src homology 2 domain-containing protein tyrosine phosphatase 2), NCK1 (non-catalytic region of tyrosine kinase adaptor protein 1), LYN, SHIP-2 [SH2 (Src homology 2)-domain-containing inositol phosphatase 2], PIK3C2A (phosphatidylinositol-4-phosphate 3-kinase, catalytic subunit type 2α) and PLCL2 (phospholipase C-like 2). Biochemical validation showed that SHP-2 tyrosine phosphorylation is dependent on DDR2 kinase activity. Targeted proteomic profiling of a panel of lung SCC (squamous cell carcinoma) DDR2 mutants demonstrated that SHP-2 is tyrosine-phosphorylated by the L63V and G505S mutants. In contrast, the I638F kinase domain mutant exhibited diminished DDR2 and SHP-2 tyrosine phosphorylation levels which have an inverse relationship with clonogenic potential. Taken together, the results of the present study indicate that SHP-2 is a key signalling node downstream of the DDR2 receptor which may have therapeutic implications in a subset of DDR2 mutations recently uncovered in genome-wide lung SCC sequencing screens.
The present study characterizes integrin and DDR2 signalling networks activated by collagen. Using clustering approaches, DDR2-specific signalling components such as SHP-2 were identified. We further demonstrate that SHP-2 is phosphorylated by a subset of DDR2 lung cancer mutants.
PMCID: PMC3893797  PMID: 23822953
cell signalling; collagen; discoidin domain receptor; lung cancer; mass spectrometry; phosphoproteomics; CDK1, cyclin-dependent kinase 1; DDR, discoidin domain receptor; DMEM, Dulbecco’s modified Eagle’s medium; DYRK1A, dual-specificity tyrosine-phosphorylation-regulated kinase 1A; EGFR, epidermal growth factor receptor; ERK, extracellular-signal-regulated kinase; EV, empty vector; GO, Gene Ontology; HEK, human embryonic kidney; HRP, horseradish peroxidase; IL, interleukin; IMAC, immobilized metal-ion-affinity chromatography; KD, kinase domain; mAb, monoclonal antibody; MCAM, multiple clustering analysis methodology; NCK1, non-catalytic region of tyrosine kinase adaptor protein 1; PIK3C2A, phosphatidylinositol-4-phosphate 3-kinase, catalytic subunit type 2α; PLCL2, phospholipase C-like 2; RFB, radiometric filter binding; RTK, receptor tyrosine kinase; SCC, squamous cell carcinoma; SHIP-2, SH2 (Src homology 2)-domain-containing inositol phosphatase 2; SHP-2, Src homology 2 domain-containing protein tyrosine phosphatase 2; SRM, selective reaction monitoring; TDA, template-directed assembly; TEAB, triethylammonium bicarbonate; TFA, trifluoroacetic acid
24.  Identification of New Substrates of the Protein-tyrosine Phosphatase PTP1B by Bayesian Integration of Proteome Evidence* 
The Journal of Biological Chemistry  2010;286(6):4173-4185.
There is growing evidence that tyrosine phosphatases display an intrinsic enzymatic preference for the sequence context flanking the target phosphotyrosines. On the other hand, substrate selection in vivo is decisively guided by the enzyme-substrate connectivity in the protein interaction network. We describe here a system wide strategy to infer physiological substrates of protein-tyrosine phosphatases. Here we integrate, by a Bayesian model, proteome wide evidence about in vitro substrate preference, as determined by a novel high-density peptide chip technology, and “closeness” in the protein interaction network. This allows to rank candidate substrates of the human PTP1B phosphatase. Ultimately a variety of in vitro and in vivo approaches were used to verify the prediction that the tyrosine phosphorylation levels of five high-ranking substrates, PLC-γ1, Gab1, SHP2, EGFR, and SHP1, are indeed specifically modulated by PTP1B. In addition, we demonstrate that the PTP1B-mediated dephosphorylation of Gab1 negatively affects its EGF-induced association with the phosphatase SHP2. The dissociation of this signaling complex is accompanied by a decrease of ERK MAP kinase phosphorylation and activation.
PMCID: PMC3039405  PMID: 21123182
ERK; Phospholipase C; Ras; Receptor-tyrosine Kinase; Tyrosine-protein Phosphatase (Tyrosine Phosphatase); Gab1; PTP1B; SHP2
25.  Early Phosphoproteomic Changes in the Mouse Spleen During Deoxynivalenol-Induced Ribotoxic Stress 
Toxicological Sciences  2013;135(1):129-143.
The trichothecene mycotoxin deoxynivalenol (DON) targets the innate immune system and is of public health significance because of its frequent presence in human and animal food. DON-induced proinflammatory gene expression and apoptosis in the lymphoid tissue have been associated with a ribotoxic stress response (RSR) that involves rapid phosphorylation of mitogen-activated protein kinases (MAPKs). To better understand the relationship between protein phosphorylation and DON’s immunotoxic effects, stable isotope dimethyl labeling–based proteomics in conjunction with titanium dioxide chromatography was employed to quantitatively profile the immediate (≤ 30min) phosphoproteome changes in the spleens of mice orally exposed to 5mg/kg body weight DON. A total of 90 phosphoproteins indicative of novel phosphorylation events were significantly modulated by DON. In addition to critical branches and scaffolds of MAPK signaling being affected, DON exposure also altered phosphorylation of proteins that mediate phosphatidylinositol 3-kinase/AKT pathways. Gene ontology analysis revealed that DON exposure affected biological processes such as cytoskeleton organization, regulation of apoptosis, and lymphocyte activation and development, which likely contribute to immune dysregulation associated with DON-induced RSR. Consistent with these findings, DON impacted phosphorylation of proteins within diverse immune cell populations, including monocytes, macrophages, T cells, B cells, dendritic cells, and mast cells. Fuzzy c-means clustering analysis further indicated that DON evoked several distinctive temporal profiles of regulated phosphopeptides. Overall, the findings from this investigation can serve as a template for future focused exploration and modeling of cellular responses associated with the immunotoxicity evoked by DON and other ribotoxins.
PMCID: PMC3748769  PMID: 23811945
ribotoxic stress response; phosphorylation; quantitative proteomics; trichothecene mycotoxin; deoxynivalenol.

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