MMFPh: a maximal motif finder for phosphoproteomics datasets

DeepNphos: A deep-learning architecture for prediction of N-phosphorylation sites

MOTIVATION

Phosphorylation, a prevalent post-translational modification, plays a crucial role in regulating cellular activities. This process encompasses O-phosphorylation (e.g., phosphoserine) and N-phosphorylation (e.g., phospho-lysine (pK), phospho-arginine (pR), and phospho-histidine (pH)). While significant research has focused on O-phosphorylation, resulting in the development of various algorithms for predicting O-phosphorylation sites with commendable performance, there has been a notable absence of models designed to predict N-phosphorylation sites. This study introduces an integrated model named DeepNphos, designed to predict N-phosphorylation sites. This model is developed based on the analysis of thousands of experimentally identified pK, pR and pH sites.

RESULTS

Observing that the Convolutional Neural Network (CNN) model, incorporating the One-Hot encoding feature, demonstrates favorable performance in comparison to other models when predicting pK, pR, and pH sites. Additionally, pK exhibits similarities to other lysine modification types, and integrating the CNN model with a deep-transfer learning (DTL) strategy based on tens of thousands of known lysine modification sites could enhance pK prediction performance. In contrast, pR exhibits little similarity to other arginine modification types, and the integration of DTL has minimal impact on pR prediction performance. Furthermore, the decision was made to refrain from incorporating the DTL strategy in predicting pH sites, given the scarcity of histidine modification sites beyond those associated with pH. The final classifiers for predicting pK, pR, and pH sites achieve AUC values of 0.856, 0.805 and 0.802 for ten-fold cross-validation, respectively. Overall, DeepNphos is the first classifier for predicting N-phosphorylation sites, accessible at https://github.com/ChangXulinmessi/DeepNPhos.

Quantitative proteomics and phosphoproteomics of PP2A-PPP2R5D variants reveal deregulation of RPS6 phosphorylation via converging signaling cascades

Genetic germline variants of PPP2R5D (encoding: phosphoprotein phosphatase 2 regulatory protein 5D) result in PPP2R5D-related disorder (Jordan's Syndrome), which is characterized by intellectual disability, hypotonia, seizures, macrocephaly, autism spectrum disorder, and delayed motor skill development. The disorder originates from de novo single nucleotide mutations, generating missense variants that act in a dominant manner. Pathogenic mutations altering 13 different amino acids have been identified, with the E198K variant accounting for ∼40% of reported cases. However, the generation of a heterozygous E198K variant cell line to study the molecular effects of the pathogenic mutation has been challenging. Here, we use CRISPR-PRIME genomic editing to introduce a transition (c.592G>A) in a single PPP2R5D allele in HEK293 cells, generating E198K-heterozygous lines to complement existing E420K variant lines. We generate global protein and phosphorylation profiles of WT, E198K, and E420K cell lines and find unique and shared changes between variants and WT cells in kinase- and phosphatase-controlled signaling cascades. We observed ribosomal protein S6 (RPS6) hyperphosphorylation as a shared signaling alteration, indicative of increased ribosomal protein S6-kinase activity. Treatment with rapamycin or an RPS6-kinase inhibitor (LY2584702) suppressed RPS6 phosphorylation in both, suggesting upstream activation of mTORC1/p70S6K. Intriguingly, our data suggests ERK-dependent activation of mTORC1 in both E198K and E420K variant cells, with additional AKT-mediated mTORC1 activation in the E420K variant. Thus, although upstream activation of mTORC1 differs between PPP2R5D-related disorder genotypes, inhibition of mTORC1 or RPS6 kinases warrants further investigation as potential therapeutic strategies for patients.

Quantitative proteomics and phosphoproteomics of PPP2R5D variants reveal deregulation of RPS6 phosphorylation through converging signaling cascades

Variants in the phosphoprotein phosphatase-2 regulatory protein-5D gene ( PPP2R5D ) cause the clinical phenotype of Jordan's Syndrome (PPP2R5D-related disorder), which includes intellectual disability, hypotonia, seizures, macrocephaly, autism spectrum disorder and delayed motor skill development. The disorder originates from de novo single nucleotide mutations, generating missense variants that act in a dominant manner. Pathogenic mutations altering 13 different amino acids have been identified, with the E198K variant accounting for ∼40% of reported cases. Here, we use CRISPR-PRIME genomic editing to introduce a transition (c.592G>A) in the PPP2R5D allele in a heterozygous manner in HEK293 cells, generating E198K-heterozygous lines to complement existing E420K variant lines. We generate global protein and phosphorylation profiles of wild-type, E198K, and E420K cell lines and find unique and shared changes between variants and wild-type cells in kinase- and phosphatase-controlled signaling cascades. As shared signaling alterations, we observed ribosomal protein S6 (RPS6) hyperphosphorylation, indicative of increased ribosomal protein S6-kinase activity. Rapamycin treatment suppressed RPS6 phosphorylation in both, suggesting activation of mTORC1. Intriguingly, our data suggest AKT-dependent (E420K) and -independent (E198K) activation of mTORC1. Thus, although upstream activation of mTORC1 differs between PPP2R5D-related disorder genotypes, treatment with rapamycin or a p70S6K inhibitor warrants further investigation as potential therapeutic strategies for patients.

Identifying Cyclin A/Cdk1 Substrates in Mitosis in Human Cells

Cyclin A promotes Cdk activity in a cell cycle-dependent manner to facilitate specific cell cycle events and transitions with an established role for DNA replication in S phase. Recent evidence demonstrates that cyclin A also activates Cdk during early mitosis to promote faithful chromosome segregation by regulating the stability of kinetochore-microtubule (k-MT) attachments. Here we describe a methodology to identify protein substrates of cyclin A/Cdk during mitosis in human cells. The method combines selective cell cycle synchrony in mitosis with stable isotope labeling of amino acids in cell culture (SILAC) coupled to mass spectrometry. This strategy identified a catalogue of potential cyclin A/Cdk substrates in mitosis, as well as unveiled potential intersections between signaling regulated by Aurora, Polo-like, and Cdk mitotic kinases.

Robust unsupervised deconvolution of linear motifs characterizes 68 protein modifications at proteome scale

The local sequence context is the most fundamental feature determining the post-translational modification (PTM) of proteins. Recent technological improvements allow for the detection of new and less prevalent modifications. We found that established state-of-the-art algorithms for the detection of PTM motifs in complex datasets failed to keep up with this technological development and are no longer robust. To overcome this limitation, we developed RoLiM, a new linear motif deconvolution algorithm and webserver, that enables robust and unbiased identification of local amino acid sequence determinants in complex biological systems demonstrated here by the analysis of 68 modifications found across 30 tissues in the human draft proteome map. Furthermore, RoLiM analysis of a large-scale phosphorylation dataset comprising 30 kinase inhibitors of 10 protein kinases in the EGF signalling pathway identified prospective substrate motifs for PI3K and EGFR.

Phosphorylation Site Motifs in Plant Protein Kinases and Their Substrates

Protein phosphorylation is an important cellular regulatory mechanism affecting the activity, localization, conformation, and interaction of proteins. Protein phosphorylation is catalyzed by kinases, and thus kinases are the enzymes regulating cellular signaling cascades. In the model plant Arabidopsis, 940 genes encode for kinases. The substrate proteins of kinases are phosphorylated at defined sites, which consist of common patterns around the phosphorylation site, known as phosphorylation motifs. The discovery of kinase specificity with a preference of phosphorylation of certain motifs and application of such motifs in deducing signaling cascades helped to reveal underlying regulation mechanisms, and facilitated the prediction of kinase-target pairs. In this mini-review, we took advantage of retrieved data as examples to present the functions of kinase families along with their commonly found phosphorylation motifs from their substrates.

MoMo: discovery of statistically significant post-translational modification motifs

MOTIVATION

Post-translational modifications (PTMs) of proteins are associated with many significant biological functions and can be identified in high throughput using tandem mass spectrometry. Many PTMs are associated with short sequence patterns called 'motifs' that help localize the modifying enzyme. Accordingly, many algorithms have been designed to identify these motifs from mass spectrometry data. Accurate statistical confidence estimates for discovered motifs are critically important for proper interpretation and in the design of downstream experimental validation.

RESULTS

We describe a method for assigning statistical confidence estimates to PTM motifs, and we demonstrate that this method provides accurate P-values on both simulated and real data. Our methods are implemented in MoMo, a software tool for discovering motifs among sets of PTMs that we make available as a web server and as downloadable source code. MoMo re-implements the two most widely used PTM motif discovery algorithms-motif-x and MoDL-while offering many enhancements. Relative to motif-x, MoMo offers improved statistical confidence estimates and more accurate calculation of motif scores. The MoMo web server offers more proteome databases, more input formats, larger inputs and longer running times than the motif-x web server. Finally, our study demonstrates that the confidence estimates produced by motif-x are inaccurate. This inaccuracy stems in part from the common practice of drawing 'background' peptides from an unshuffled proteome database. Our results thus suggest that many of the papers that use motif-x to find motifs may be reporting results that lack statistical support.

AVAILABILITY AND IMPLEMENTATION

The MoMo web server and source code are provided at http://meme-suite.org.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Phosphoproteomics Analysis Identifies Novel Candidate Substrates of the Nonreceptor Tyrosine Kinase, Src-related Kinase Lacking C-terminal Regulatory Tyrosine and N-terminal Myristoylation Sites (SRMS)

SRMS (Src-related kinase lacking C-terminal regulatory tyrosine and N-terminal myristoylation sites), also known as PTK 70 (Protein tyrosine kinase 70), is a non-receptor tyrosine kinase that belongs to the BRK family of kinases (BFKs). To date less is known about the cellular role of SRMS primarily because of the unidentified substrates or signaling intermediates regulated by the kinase. In this study, we used phosphotyrosine antibody-based immunoaffinity purification in large-scale label-free quantitative phosphoproteomics to identify novel candidate substrates of SRMS. Our analyses led to the identification of 1258 tyrosine-phosphorylated peptides which mapped to 663 phosphoproteins, exclusively from SRMS-expressing cells. DOK1, a previously characterized SRMS substrate, was also identified in our analyses. Functional enrichment analyses revealed that the candidate SRMS substrates were enriched in various biological processes including protein ubiquitination, mitotic cell cycle, energy metabolism and RNA processing, as well as Wnt and TNF signaling. Analyses of the sequence surrounding the phospho-sites in these proteins revealed novel candidate SRMS consensus substrate motifs. We utilized customized high-throughput peptide arrays to validate a subset of the candidate SRMS substrates identified in our MS-based analyses. Finally, we independently validated Vimentin and Sam68, as bona fide SRMS substrates through in vitro and in vivo assays. Overall, our study identified a number of novel and biologically relevant SRMS candidate substrates, which suggests the involvement of the kinase in a vast array of unexplored cellular functions.

Therapeutically targeting tumor microenvironment-mediated drug resistance in estrogen receptor-positive breast cancer

Tumor microenvironment (TME) cytokine screening revealed FGF2 as a clinically relevant mechanism of resistance to anti-estrogens, mTORC1 inhibition, and PI3K inhibition in ER+ breast cancer. Shee et al. highlight an underdeveloped aspect of precision oncology: treating patients according to their TME constitution.

Drug resistance to approved systemic therapies in estrogen receptor–positive (ER+) breast cancer remains common. We hypothesized that factors present in the human tumor microenvironment (TME) drive drug resistance. Screening of a library of recombinant secreted microenvironmental proteins revealed fibroblast growth factor 2 (FGF2) as a potent mediator of resistance to anti-estrogens, mTORC1 inhibition, and phosphatidylinositol 3-kinase inhibition in ER+ breast cancer. Phosphoproteomic analyses identified ERK1/2 as a major output of FGF2 signaling via FGF receptors (FGFRs), with consequent up-regulation of Cyclin D1 and down-regulation of Bim as mediators of drug resistance. FGF2-driven drug resistance in anti-estrogen–sensitive and –resistant models, including patient-derived xenografts, was reverted by neutralizing FGF2 or FGFRs. A transcriptomic signature of FGF2 signaling in primary tumors predicted shorter recurrence-free survival independently of age, grade, stage, and FGFR amplification status. These findings delineate FGF2 signaling as a ligand-based drug resistance mechanism and highlights an underdeveloped aspect of precision oncology: characterizing and treating patients according to their TME constitution.

Cyclin A/Cdk1 modulates Plk1 activity in prometaphase to regulate kinetochore-microtubule attachment stability

The fidelity of chromosome segregation in mitosis is safeguarded by the precise regulation of kinetochore microtubule (k-MT) attachment stability. Previously, we demonstrated that Cyclin A/Cdk1 destabilizes k-MT attachments to promote faithful chromosome segregation. Here, we use quantitative phosphoproteomics to identify 156 Cyclin A/Cdk1 substrates in prometaphase. One Cyclin A/Cdk1 substrate is myosin phosphatase targeting subunit 1 (MYPT1), and we show that MYPT1 localization to kinetochores depends on Cyclin A/Cdk1 activity and that MYPT1 destabilizes k-MT attachments by negatively regulating Plk1 at kinetochores. Thus, Cyclin A/Cdk1 phosphorylation primes MYPT1 for Plk1 binding. Interestingly, priming of PBIP1 by Plk1 itself (self-priming) increased in MYPT1-depleted cells showing that MYPT1 provides a molecular link between the processes of Cdk1-dependent priming and self-priming of Plk1 substrates. These data demonstrate cross-regulation between Cyclin A/Cdk1-dependent and Plk1-dependent phosphorylation of substrates during mitosis to ensure efficient correction of k-MT attachment errors necessary for high mitotic fidelity.

Recent findings and technological advances in phosphoproteomics for cells and tissues

Site-specific phosphorylation is a fast and reversible covalent post-translational modification that is tightly regulated in cells. The cellular machinery of enzymes that write, erase and read these modifications (kinases, phosphatases and phospho-binding proteins) is frequently deregulated in different diseases, including cancer. Large-scale studies of phosphoproteins – termed phosphoproteomics – strongly rely on the use of high-performance mass spectrometric instrumentation. This powerful technology has been applied to study a great number of phosphorylation-based phenotypes. Nevertheless, many technical and biological challenges have to be overcome to identify biologically relevant phosphorylation sites in cells and tissues. This review describes different technological strategies to identify and quantify phosphorylation sites with high accuracy, without significant loss of analysis speed and reproducibility in tissues and cells. Moreover, computational tools for analysis, integration and biological interpretation of phosphorylation events are discussed.

Phosphoproteomic Analyses of NRAS(G12) and NRAS(Q61) Mutant Melanocytes Reveal Increased CK2α Kinase Levels in NRAS(Q61) Mutant Cells

In melanoma, mutant and thereby constantly active neuroblastoma rat sarcoma (NRAS) affects 15-20% of tumors, contributing to tumor initiation, growth, invasion, and metastasis. Recent therapeutic approaches aim to mimic RAS extinction by interfering with critical signaling pathways downstream of the mutant protein. This study investigates the phosphoproteome of primary human melanocytes bearing mutations in the two hot spots of NRAS, NRAS(G12) and NRAS(Q61). Stable isotope labeling by amino acids in cell culture followed by mass spectrometry identified 14,155 spectra of 3,371 unique phosphopeptides mapping to 1,159 proteins (false discovery rate < 2%). Data revealed pronounced PI3K/AKT signaling in NRAS(G12V) mutant cells and pronounced mitogen-activated protein kinase (MAPK) signaling in NRAS(Q61L) variants. Computer-based prediction models for kinases involved, revealed that CK2α is significantly overrepresented in primary human melanocytes bearing NRAS(Q61L) mutations. Similar differences were found in human NRAS(Q61) mutant melanoma cell lines that were also more sensitive to pharmacologic CK2α inhibition compared with NRAS(G12) mutant cells. Furthermore, CK2α levels were pronounced in patient samples of NRAS(Q61) mutant melanoma at the mRNA and protein level. The preclinical findings of this study reveal that codon 12 and 61 mutant NRAS cells have distinct signaling characteristics that could allow for the development of more effective, mutation-specific treatment modalities.

Identification of Candidate Cyclin-dependent kinase 1 (Cdk1) Substrates in Mitosis by Quantitative Phosphoproteomics

Cyclin-dependent kinase 1 (Cdk1) is an essential regulator of many mitotic processes including the reorganization of the cytoskeleton, chromosome segregation, and formation and separation of daughter cells. Deregulation of Cdk1 activity results in severe defects in these processes. Although the role of Cdk1 in mitosis is well established, only a limited number of Cdk1 substrates have been identified in mammalian cells. To increase our understanding of Cdk1-dependent phosphorylation pathways in mitosis, we conducted a quantitative phosphoproteomics analysis in mitotic HeLa cells using two small molecule inhibitors of Cdk1, Flavopiridol and RO-3306. In these analyses, we identified a total of 24,840 phosphopeptides on 4,273 proteins, of which 1,215 phosphopeptides on 551 proteins were significantly reduced by 2.5-fold or more upon Cdk1 inhibitor addition. Comparison of phosphopeptide quantification upon either inhibitor treatment revealed a high degree of correlation (R(2) value of 0.87) between the different datasets. Motif enrichment analysis of significantly regulated phosphopeptides revealed enrichment of canonical Cdk1 kinase motifs. Interestingly, the majority of proteins identified in this analysis contained two or more Cdk1 inhibitor-sensitive phosphorylation sites, were highly connected with other candidate Cdk1 substrates, were enriched at specific subcellular structures, or were part of protein complexes as identified by the CORUM database. Furthermore, candidate Cdk1 substrates were enriched in G2 and M phase-specific genes. Finally, we validated a subset of candidate Cdk1 substrates by in vitro kinase assays. Our findings provide a valuable resource for the cell signaling and mitosis research communities and greatly increase our knowledge of Cdk1 substrates and Cdk1-dependent signaling pathways.

MAP4K4 Is a Threonine Kinase That Phosphorylates FARP1

Mitogen-activated protein kinase 4 (MAP4K4) regulates the MEK kinase cascade and is implicated in cytoskeletal rearrangement and migration; however, identifying MAP4K4 substrates has remained a challenge. To ascertain MAP4K4-dependent phosphorylation events, we combined phosphoproteomic studies of MAP4K4 inhibition with in vitro assessment of its kinase specificity. We identified 235 phosphosites affected by MAP4K4 inhibition in cells and found that pTP and pSP motifs were predominant among them. In contrast, in vitro assessment of kinase specificity showed that MAP4K4 favors a pTL motif. We showed that MAP4K4 directly phosphorylates and coimmunoprecipitates with FERM, RhoGEF, and pleckstrin domain-containing protein 1 (FARP1). MAP4K4 inhibition in SH-SY5Y cells increases neurite outgrowth, a process known to involve FARP1. As FARP1 and MAP4K4 both contribute to cytoskeletal rearrangement, the results suggest that MAP4K4 exerts some of its effects on the cytoskeleton via phosphorylation of FARP1.

Quantitative phosphoproteomics reveals new roles for the protein phosphatase PP6 in mitotic cells

Protein phosphorylation is an important regulatory mechanism controlling mitotic progression. Protein phosphatase 6 (PP6) is an essential enzyme with conserved roles in chromosome segregation and spindle assembly from yeast to humans. We applied a baculovirus-mediated gene silencing approach to deplete HeLa cells of the catalytic subunit of PP6 (PP6c) and analyzed changes in the phosphoproteome and proteome in mitotic cells by quantitative mass spectrometry-based proteomics. We identified 408 phosphopeptides on 272 proteins that increased and 298 phosphopeptides on 220 proteins that decreased in phosphorylation upon PP6c depletion in mitotic cells. Motif analysis of the phosphorylated sites combined with bioinformatics pathway analysis revealed previously unknown PP6c-dependent regulatory pathways. Biochemical assays demonstrated that PP6c opposed casein kinase 2-dependent phosphorylation of the condensin I subunit NCAP-G, and cellular analysis showed that depletion of PP6c resulted in defects in chromosome condensation and segregation in anaphase, consistent with dysregulation of condensin I function in the absence of PP6 activity.

Comparison of phosphorylation patterns across eukaryotes by discriminative N-gram analysis

Background

How protein phosphorylation relates to kingdom/phylum divergence is largely unknown and the amino acid residues surrounding the phosphorylation site have profound importance on protein kinase–substrate interactions. Standard motif analysis is not adequate for large scale comparative analysis because each phophopeptide is assigned to a unique motif and perform poorly with the unbalanced nature of the input datasets.

Results

First the discriminative n-grams of five species from five different kingdom/phyla were identified. A signature with 5540 discriminative n-grams that could be found in other species from the same kingdoms/phyla was created. Using a test data set, the ability of the signature to classify species in their corresponding kingdom/phylum was confirmed using classification methods. Lastly, ortholog proteins among proteins with n-grams were identified in order to determine to what degree was the identity of the detected n-grams a property of phosphosites rather than a consequence of species-specific or kingdom/phylum-specific protein inventory. The motifs were grouped in clusters of equal physico-chemical nature and their distribution was similar between species in the same kingdom/phylum while clear differences were found among species of different kingdom/phylum. For example, the animal-specific top discriminative n-grams contained many basic amino acids and the plant-specific motifs were mainly acidic. Secondary structure prediction methods show that the discriminative n-grams in the majority of the cases lack from a regular secondary structure as on average they had 88 % of random coil compared to 66 % found in the phosphoproteins they were derived from.

Conclusions

The discriminative n-grams were able to classify organisms in their corresponding kingdom/phylum, they show different patterns among species of different kingdom/phylum and these regions can contribute to evolutionary divergence as they are in disordered regions that can evolve rapidly. The differences found possibly reflect group-specific differences in the kinomes of the different groups of species.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0657-2) contains supplementary material, which is available to authorized users.

Global Phosphoproteomic Mapping of Early Mitotic Exit in Human Cells Identifies Novel Substrate Dephosphorylation Motifs

Entry into mitosis is driven by the coordinated phosphorylation of thousands of proteins. For the cell to complete mitosis and divide into two identical daughter cells it must regulate dephosphorylation of these proteins in a highly ordered, temporal manner. There is currently a lack of a complete understanding of the phosphorylation changes that occur during the initial stages of mitotic exit in human cells. Therefore, we performed a large unbiased, global analysis to map the very first dephosphorylation events that occur as cells exit mitosis. We identified and quantified the modification of >16,000 phosphosites on >3300 unique proteins during early mitotic exit, providing up to eightfold greater resolution than previous studies. The data have been deposited to the ProteomeXchange with identifier PXD001559. Only a small fraction (∼ 10%) of phosphorylation sites were dephosphorylated during early mitotic exit and these occurred on proteins involved in critical early exit events, including organization of the mitotic spindle, the spindle assembly checkpoint, and reformation of the nuclear envelope. Surprisingly this enrichment was observed across all kinase consensus motifs, indicating that it is independent of the upstream phosphorylating kinase. Therefore, dephosphorylation of these sites is likely determined by the specificity of phosphatase/s rather than the activity of kinase/s. Dephosphorylation was significantly affected by the amino acids at and surrounding the phosphorylation site, with several unique evolutionarily conserved amino acids correlating strongly with phosphorylation status. These data provide a potential mechanism for the specificity of phosphatases, and how they co-ordinate the ordered events of mitotic exit. In summary, our results provide a global overview of the phosphorylation changes that occur during the very first stages of mitotic exit, providing novel mechanistic insight into how phosphatase/s specifically regulate this critical transition.

Human cytomegalovirus pUL97 kinase induces global changes in the infected cell phosphoproteome

Replication of human cytomegalovirus (HCMV) is regulated in part by cellular kinases and the single viral Ser/Thr kinase, pUL97. The virus-coded kinase augments the replication of HCMV by enabling nuclear egress and altering cell cycle progression. These roles are accomplished through direct phosphorylation of nuclear lamins and the retinoblastoma protein, respectively. In an effort to identify additional pUL97 substrates, we analyzed the phosphoproteome of SILAC-labeled human fibroblasts during infection with either wild-type HCMV or a pUL97 kinase-dead mutant virus. Phosphopeptides were enriched over a titanium dioxide matrix and analyzed by high-resolution MS. We identified 157 unambiguous phosphosites from 106 cellular and 17 viral proteins whose phosphorylation required UL97. Analysis of peptides containing these sites allowed the identification of several candidate pUL97 phosphorylation motifs, including a completely novel phosphorylation motif, LxSP. Substrates harboring the LxSP motif were enriched in nucleocytoplasmic transport functions, including a number of components of the nuclear pore complex. These results extend the known functions of pUL97 and suggest that modulation of nuclear pore function may be important during HCMV replication.

Analysis of the Candida albicans Phosphoproteome

Candida albicans is an important human fungal pathogen in both immunocompetent and immunocompromised individuals. C. albicans regulation has been studied in many contexts, including morphological transitions, mating competence, biofilm formation, stress resistance, and cell wall synthesis. Analysis of kinase- and phosphatase-deficient mutants has made it clear that protein phosphorylation plays an important role in the regulation of these pathways. In this study, to further our understanding of phosphorylation in C. albicans regulation, we performed a deep analysis of the phosphoproteome in C. albicans. We identified 19,590 unique peptides that corresponded to 15,906 unique phosphosites on 2,896 proteins. The ratios of serine, threonine, and tyrosine phosphosites were 80.01%, 18.11%, and 1.81%, respectively. The majority of proteins (2,111) contained at least two detected phosphorylation sites. Consistent with findings in other fungi, cytoskeletal proteins were among the most highly phosphorylated proteins, and there were differences in Gene Ontology (GO) terms for proteins with serine and threonine versus tyrosine phosphorylation sites. This large-scale analysis identified phosphosites in protein components of Mediator, an important transcriptional coregulatory protein complex. A targeted analysis of the phosphosites in Mediator complex proteins confirmed the large-scale studies, and further in vitro assays identified a subset of these phosphorylations that were catalyzed by Cdk8 (Ssn3), a kinase within the Mediator complex. These data represent the deepest single analysis of a fungal phosphoproteome and lay the groundwork for future analyses of the C. albicans phosphoproteome and specific phosphoproteins.

Recent advances and challenges in plant phosphoproteomics

Plants are sessile organisms that need to respond to environmental changes quickly and efficiently. They can accomplish this by triggering specialized signaling pathways often mediated by protein phosphorylation and dephosphorylation. Phosphorylation is a fast response that can switch on or off a myriad of biological pathways and processes. Proteomics and MS are the main tools employed in the study of protein phosphorylation. Advances in the technologies allow simultaneous identification and quantification of thousands of phosphopeptides and proteins that are essential to understanding the sophisticated biological systems and regulations. In this review, we summarize the advances in phosphopeptide enrichment and quantitation, MS for phosphorylation site mapping and new data acquisition methods, databases and informatics, interpretation of biological insights and crosstalk with other PTMs, as well as future directions and challenges in the field of phosphoproteomics.

Discriminative pattern mining and its applications in bioinformatics

Discriminative pattern mining is one of the most important techniques in data mining. This challenging task is concerned with finding a set of patterns that occur with disproportionate frequency in data sets with various class labels. Such patterns are of great value for group difference detection and classifier construction. Research on finding interesting discriminative patterns in class-labeled data evolves rapidly and lots of algorithms have been proposed to specifically address this problem. Discriminative pattern mining techniques have proven their considerable value in biological data analysis. The archetypical applications in bioinformatics include phosphorylation motif discovery, differentially expressed gene identification, discriminative genotype pattern detection, etc. In this article, we present an overview of discriminative pattern mining and the corresponding effective methods, and subsequently we illustrate their applications to tackling the bioinformatics problems. In the end, we give a general discussion of potential challenges and future work for this task.

Mining Conditional Phosphorylation Motifs

Phosphorylation motifs represent position-specific amino acid patterns around the phosphorylation sites in the set of phosphopeptides. Several algorithms have been proposed to uncover phosphorylation motifs, whereas the problem of efficiently discovering a set of significant motifs with sufficiently high coverage and non-redundancy still remains unsolved. Here we present a novel notion called conditional phosphorylation motifs. Through this new concept, the motifs whose over-expressiveness mainly benefits from its constituting parts can be filtered out effectively. To discover conditional phosphorylation motifs, we propose an algorithm called C-Motif for a non-redundant identification of significant phosphorylation motifs. C-Motif is implemented under the Apriori framework, and it tests the statistical significance together with the frequency of candidate motifs in a single stage. Experiments demonstrate that C-Motif outperforms some current algorithms such as MMFPh and Motif-All in terms of coverage and non-redundancy of the results and efficiency of the execution. The source code of C-Motif is available at: https://sourceforge. net/projects/cmotif/.

Meta-Analysis of Arabidopsis thaliana Phospho-Proteomics Data Reveals Compartmentalization of Phosphorylation Motifs

Protein (de)phosphorylation plays an important role in plants. To provide a robust foundation for subcellular phosphorylation signaling network analysis and kinase-substrate relationships, we performed a meta-analysis of 27 published and unpublished in-house mass spectrometry-based phospho-proteome data sets for Arabidopsis thaliana covering a range of processes, (non)photosynthetic tissue types, and cell cultures. This resulted in an assembly of 60,366 phospho-peptides matching to 8141 nonredundant proteins. Filtering the data for quality and consistency generated a set of medium and a set of high confidence phospho-proteins and their assigned phospho-sites. The relation between single and multiphosphorylated peptides is discussed. The distribution of p-proteins across cellular functions and subcellular compartments was determined and showed overrepresentation of protein kinases. Extensive differences in frequency of pY were found between individual studies due to proteomics and mass spectrometry workflows. Interestingly, pY was underrepresented in peroxisomes but overrepresented in mitochondria. Using motif-finding algorithms motif-x and MMFPh at high stringency, we identified compartmentalization of phosphorylation motifs likely reflecting localized kinase activity. The filtering of the data assembly improved signal/noise ratio for such motifs. Identified motifs were linked to kinases through (bioinformatic) enrichment analysis. This study also provides insight into the challenges/pitfalls of using large-scale phospho-proteomic data sets to nonexperts.