Predicting protein post-translational modifications using meta-analysis of proteome scale data sets

Retinoic acid induced specific changes in the phosphoproteome of C17.2 neural stem cells

Retinoic acid (RA), a vitamin A derivative, is an effective cell differentiating factor which plays critical roles in neuronal differentiation induction and the production of neurotransmitters in neurons. However, the specific changes in phosphorylation levels and downstream signalling pathways associated with RA remain unclear. This study employed qualitative and quantitative phosphoproteomics approaches based on mass spectrometry to investigate the phosphorylation changes induced by RA in C17.2 neural stem cells (NSCs). Dimethyl labelling, in conjunction with TiO2 phosphopeptide enrichment, was utilized to profile the phosphoproteome of self-renewing and RA-induced differentiated cells in C17.2 NSCs. The results of our study revealed that, qualitatively, 230 and 14 phosphoproteins were exclusively identified in the self-renewal and RA-induced groups respectively. Quantitatively, we successfully identified and quantified 177 unique phosphoproteins, among which 70 exhibited differential phosphorylation levels. Analysis of conserved phosphorylation motifs demonstrated enrichment of motifs corresponding to cyclin-dependent kinase and MAPK in the RA-induced group. Additionally, through a comprehensive literature and database survey, we found that the differentially expressed proteins were associated with the Wnt/β-catenin and Hippo signalling pathways. This work sheds light on the changes in phosphorylation levels induced by RA in C17.2 NSCs, thereby expanding our understanding of the molecular mechanisms underlying RA-induced neuronal differentiation.

Rational design of supramolecular self-assembly sensor for living cell imaging of HDAC1 and its application in high-throughput screening

Supramolecular chemistry offers new insights in bioimaging, but specific tracking of enzyme in living cells via supramolecular host-guest reporter pair remains challenging, largely due to the interference caused by the complex cellular environment on the binding between analytes and hosts. Here, by exploiting the principle of supramolecular tandem assay (STA) and the classic host-guest reporter pair (p-sulfonatocalix[4]arene (SC4A) and lucigenin (LCG)) and rationally designing artificial peptide library to screen sequence with high affinity of the target enzyme, we developed a "turn-on" fluorescent sensing system for intracellular imaging of histone deacetylase 1 (HDAC1), which is a potential therapeutic target for various diseases, including cancer, neurological, and cardiovascular diseases. Based on computational simulations and experimental validations, we verified that the deacetylated peptide by HDAC1 competed LCG, freeing it from the SC4A causing fluorescence increase. Enzyme kinetics experiments were further conducted to prove that this assay could detect HDAC1 specifically with high sensitivity (the LOD value is 0.015 μg/mL, ten times lower than the published method). This system was further applied for high-throughput screening of HDAC1 inhibitors over a natural compound library containing 147 compounds, resulting in the identification of a novel HDAC1 down-regulator (Ginsenoside RK3). Our results demonstrated the sensitivity and robustness of the assay system towards HDAC1. It should serve as a valuable tool for biochemical studies and drug screening.

Prediction of Protein Function from Tertiary Structure of the Active Site in Heme Proteins by Convolutional Neural Network

Structure-function relationships in proteins have been one of the crucial scientific topics in recent research. Heme proteins have diverse and pivotal biological functions. Therefore, clarifying their structure-function correlation is significant to understand their functional mechanism and is informative for various fields of science. In this study, we constructed convolutional neural network models for predicting protein functions from the tertiary structures of heme-binding sites (active sites) of heme proteins to examine the structure-function correlation. As a result, we succeeded in the classification of oxygen-binding protein (OB), oxidoreductase (OR), proteins with both functions (OB-OR), and electron transport protein (ET) with high accuracy. Although the misclassification rate for OR and ET was high, the rates between OB and ET and between OB and OR were almost zero, indicating that the prediction model works well between protein groups with quite different functions. However, predicting the function of proteins modified with amino acid mutation(s) remains a challenge. Our findings indicate a structure-function correlation in the active site of heme proteins. This study is expected to be applied to the prediction of more detailed protein functions such as catalytic reactions.

The Okur-Chung Neurodevelopmental Syndrome Mutation CK2K198R Leads to a Rewiring of Kinase Specificity

Okur-Chung Neurodevelopmental Syndrome (OCNDS) is caused by heterozygous mutations to the CSNK2A1 gene, which encodes the alpha subunit of protein kinase CK2. The most frequently occurring mutation is lysine 198 to arginine (K198R). To investigate the impact of this mutation, we first generated a high-resolution phosphorylation motif of CK2^WT, including the first characterization of specificity for tyrosine phosphorylation activity. A second high resolution motif representing CK2^K198R substrate specificity was also generated. Here we report the impact of the OCNDS associated CK2^K198R mutation. Contrary to prior speculation, the mutation does not result in a complete loss of function, but rather shifts the substrate specificity of the kinase. Broadly speaking the mutation leads to 1) a decreased preference for acidic residues in the +1 position, 2) a decreased preference for threonine phosphorylation, 3) an increased preference for tyrosine phosphorylation, and 4) an alteration of the tyrosine phosphorylation specificity motif. To further investigate the result of this mutation we have developed a probability-based scoring method, allowing us to predict shifts in phosphorylation in the K198R mutant relative to the wild type kinase. As an initial step we have applied the methodology to the set of axonally localized ion channels in an effort to uncover potential alterations of the phosphoproteome associated with the OCNDS disease condition.

Soybean responds to phosphate starvation through reversible protein phosphorylation

Phosphorus (P) deficiency is considered as a major constraint on crop production. Although a set of adaptative strategies are extensively suggested in soybean (Glycine max) to phosphate (Pi) deprivation, molecular mechanisms underlying reversible protein phosphorylation in soybean responses to P deficiency remains largely unclear. In this study, isobaric tags for relative and absolute quantitation, combined with liquid chromatography and tandem mass spectrometry analysis was performed to identify differential phosphoproteins in soybean roots under Pi sufficient and deficient conditions. A total of 427 phosphoproteins were found to exhibit differential accumulations, with 213 up-regulated and 214 down-regulated. Among them, a nitrate reductase, GmNR4 exhibiting increased phosphorylation levels under low Pi conditions, was further selected to evaluate the effects of phosphorylation on its nitrate reductase activity and subcellular localization. Mutations of GmNR4 phosphorylation levels significantly influenced its activity in vitro, but not for its subcellular localization. Taken together, identification of differential phosphoproteins reveled the complex regulatory pathways for soybean adaptation to Pi starvation through reversible protein phosphorylation.

A phosphoproteomics study reveals a defined genetic program for neural lineage commitment of neural stem cells induced by olfactory ensheathing cell-conditioned medium

Since both Olfactory ensheathing cells (OECs) and neural stem cells (NSCs) have shown certain efficacy in the cellular therapy of nerve injury and disease, there have been a series of investigations in recent years looking at the co-culture of NSCs and OECs. Protein phosphorylation forms the basis for identifying a variety of cellular signaling pathways responsible for regulating the self-renewal and differentiation of NSCs induced by OECs. To better understand the signaling cascades in the early phases of OEC-induced NSC differentiation, changes in the NSC proteome and phosphoproteome during the first 24 h were determined using dimethyl labeling and TiO₂ phosphorylation enrichment coupled with Liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 565 proteins and 2511 phosphorylation sites were identified. According to quantitative phosphoproteomics analyses of NSC differentiation induced by OECs during the first 12 and 24 h, it was speculated that there were at least two different signal waves: one peaking within 12 h after stimulation and the second upsurge after 24 h. In addition to understanding the dynamics of the proteome and phosphoproteome in the early stages of NSC differentiation, our analyses identified a key role of the TGF-β3 protein secreted by OECs, which may be an initiating factor that promotes differentiation of NSCs into neurons induced by OECs. These findings not only redemonstrated a OECs-based therapeutic strategy in cell therapy, but also added a node to the regulatory network for the neural lineage commitment of NSCs induced by OECs.

Large-scale Identification and Time-course Quantification of Ubiquitylation Events During Maize Seedling De-etiolation

The ubiquitin system is crucial for the development and fitness of higher plants. De-etiolation, during which green plants initiate photomorphogenesis and establish autotrophy, is a dramatic and complicated process that is tightly regulated by a massive number of ubiquitylation/de-ubiquitylation events. Here we present site-specific quantitative proteomic data for the ubiquitylomes of de-etiolating seedling leaves of Zea mays L. (exposed to light for 1, 6, or 12 h) achieved through immunoprecipitation-based high-resolution mass spectrometry (MS). Through the integrated analysis of multiple ubiquitylomes, we identified and quantified 1926 unique ubiquitylation sites corresponding to 1053 proteins. We analyzed these sites and found five potential ubiquitylation motifs, KA, AXK, KXG, AK, and TK. Time-course studies revealed that the ubiquitylation levels of 214 sites corresponding to 173 proteins were highly correlated across two replicate MS experiments, and significant alterations in the ubiquitylation levels of 78 sites (fold change >1.5) were detected after de-etiolation for 12 h. The majority of the ubiquitylated sites we identified corresponded to substrates involved in protein and DNA metabolism, such as ribosomes and histones. Meanwhile, multiple ubiquitylation sites were detected in proteins whose functions reflect the major physiological changes that occur during plant de-etiolation, such as hormone synthesis/signaling proteins, key C4 photosynthetic enzymes, and light signaling proteins. This study on the ubiquitylome of the maize seedling leaf is the first attempt ever to study the ubiquitylome of a C4 plant and provides the proteomic basis for elucidating the role of ubiquitylation during plant de-etiolation.

Phosphoproteomic Profiling Reveals the Importance of CK2, MAPKs and CDPKs in Response to Phosphate Starvation in Rice

Phosphorus is one of the most important macronutrients required for plant growth and development. The importance of phosphorylation modification in regulating phosphate (Pi) homeostasis in plants is emerging. We performed phosphoproteomic profiling to characterize proteins whose degree of phosphorylation is altered in response to Pi starvation in rice root. A subset of 554 proteins, including 546 down-phosphorylated and eight up-phosphorylated proteins, exhibited differential phosphorylation in response to Pi starvation. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis with the differentially phosphorylated proteins indicated that RNA processing, transport, splicing and translation and carbon metabolism played critical roles in response to Pi starvation in rice. Levels of phosphorylation of four mitogen-activated protein kinases (MAPKs), including OsMAPK6, five calcium-dependent protein kinases (CDPKs) and OsCK2β3 decreased in response to Pi starvation. The decreased phosphorylation level of OsMAPK6 was confirmed by Western blotting. Mutation of OsMAPK6 led to Pi accumulation under Pi-sufficient conditions. Motif analysis indicated that the putative MAPK, casein kinase 2 (CK2) and CDPK substrates represented about 54.4%, 21.5% and 4.7%, respectively, of the proteins exhibiting differential phosphorylation. Based on the motif analysis, 191, 151 and 46 candidate substrates for MAPK, CK2 and CDPK were identified. These results indicate that modification of phosphorylation profiles provides complementary information on Pi-starvation-induced processes, with CK2, MAPK and CDPK protein kinase families playing key roles in these processes in rice.

Deep Protein Methylation Profiling by Combined Chemical and Immunoaffinity Approaches Reveals Novel PRMT1 Targets

Protein methylation has been implicated in many important biological contexts including signaling, metabolism, and transcriptional control. Despite the importance of this post-translational modification, the global analysis of protein methylation by mass spectrometry-based proteomics has not been extensively studied because of the lack of robust, well-characterized techniques for methyl peptide enrichment. Here, to better investigate protein methylation, we compared two methods for methyl peptide enrichment: immunoaffinity purification (IAP) and high pH strong cation exchange (SCX). Using both methods, we identified 1720 methylation sites on 778 proteins. Comparison of these methods revealed that they are largely orthogonal, suggesting that the usage of both techniques is required to provide a global view of protein methylation. Using both IAP and SCX, we then investigated changes in protein methylation downstream of protein arginine methyltransferase 1 (PRMT1). PRMT1 knockdown resulted in significant changes to 127 arginine methylation sites on 78 proteins. In contrast, only a single lysine methylation site was significantly changed upon PRMT1 knockdown. In PRMT1 knockdown cells, we found 114 MMA sites that were either significantly downregulated or upregulated on proteins enriched for mRNA metabolic processes. PRMT1 knockdown also induced significant changes in both asymmetric dimethyl arginine (ADMA) and symmetric dimethyl arginine (SDMA). Using characteristic neutral loss fragmentation ions, we annotated dimethylarginines as either ADMA or SDMA. Through integrative analysis of methyl forms, we identified 18 high confidence PRMT1 substrates and 12 methylation sites that are scavenged by other non-PRMT1 arginine methyltransferases in the absence of PRMT1 activity. We also identified one methylation site, HNRNPA1 R206, which switched from ADMA to SDMA upon PRMT1 knockdown. Taken together, our results suggest that deep protein methylation profiling by mass spectrometry requires orthogonal enrichment techniques to identify novel PRMT1 methylation targets and highlight the dynamic interplay between methyltransferases in mammalian cells.

ragp: Pipeline for mining of plant hydroxyproline-rich glycoproteins with implementation in R

Hydroxyproline-rich glycoproteins (HRGPs) are one of the most complex families of macromolecules found in plants, due to the diversity of glycans decorating the protein backbone, as well as the heterogeneity of the protein backbones. While this diversity is responsible for a wide array of physiological functions associated with HRGPs, it hinders attempts for homology based identification. Current approaches, based on identifying sequences with characteristic motifs and biased amino acid composition, are limited to prototypical sequences. Ragp is an R package for mining and analysis of HRGPs, with emphasis on arabinogalactan proteins. The ragp filtering pipeline exploits one of the HRGPs key features, the presence of hydroxyprolines which represent glycosylation sites. Main package features include prediction of proline hydroxylation sites, amino acid motif and bias analyses, efficient communication with web servers for prediction of N-terminal signal peptides, glycosylphosphatidylinositol modification sites and disordered regions and the ability to annotate sequences through hmmscan and subsequent GO enrichment, based on predicted Pfam domains. As such, ragp extends R's rich ecosystem for high-throughput sequence data analyses. The ragp R package is available under the MIT Open Source license and is freely available to download from GitHub at: https://github.com/missuse/ragp.

Lysine Acetylation is an Important Post-Translational Modification that Modulates Heat Shock Response in the Sea Cucumber Apostichopus japonicus

Heat stress (HS) is an important factor for the survival of the marine organism Apostichopus japonicus. Lysine acetylation is a pivotal post-translational modification that modulates diverse physiological processes including heat shock response (HSR). In this study, 4028 lysine acetylation sites in 1439 proteins were identified in A. japonicus by acetylproteome sequencing. A total of 13 motifs were characterized around the acetylated lysine sites. Gene Ontology analysis showed that major acetylated protein groups were involved in “oxidation–reduction process”, “ribosome”, and “protein binding” terms. Compared to the control group, the acetylation quantitation of 25 and 41 lysine sites changed after 6 and 48 h HS. Notably, lysine acetyltransferase CREB-binding protein (CBP) was identified to have differential acetylation quantitation at multiple lysine sites under HS. Various chaperones, such as caseinolytic peptidase B protein homolog (CLBP), T-complex protein 1 (TCP1), and cyclophilin A (CYP1), showed differential acetylation quantitation after 48 h HS. Additionally, many translation-associated proteins, such as ribosomal proteins, translation initiation factor (IF), and elongation factors (EFs), had differential acetylation quantitation under HS. These proteins represented specific interaction networks. Collectively, our results offer novel insight into the complex HSR in A. japonicus and provide a resource for further mechanistic studies examining the regulation of protein function by lysine acetylation.

Precision Profiling of the Cardiovascular Post-Translationally Modified Proteome: Where There Is a Will, There Is a Way

There is an exponential increase in biological complexity as initial gene transcripts are spliced, translated into amino acid sequence, and post-translationally modified. Each protein can exist as multiple chemical or sequence-specific proteoforms, and each has the potential to be a critical mediator of a physiological or pathophysiological signaling cascade. Here, we provide an overview of how different proteoforms come about in biological systems and how they are most commonly measured using mass spectrometry-based proteomics and bioinformatics. Our goal is to present this information at a level accessible to every scientist interested in mass spectrometry and its application to proteome profiling. We will specifically discuss recent data linking various protein post-translational modifications to cardiovascular disease and conclude with a discussion for enablement and democratization of proteomics across the cardiovascular and scientific community. The aim is to inform and inspire the readership to explore a larger breadth of proteoform, particularity post-translational modifications, related to their particular areas of expertise in cardiovascular physiology.

Proteome-wide detection of S-nitrosylation targets and motifs using bioorthogonal cleavable-linker-based enrichment and switch technique

Cysteine modifications emerge as important players in cellular signaling and homeostasis. Here, we present a chemical proteomics strategy for quantitative analysis of reversibly modified Cysteines using bioorthogonal cleavable-linker and switch technique (Cys-BOOST). Compared to iodoTMT for total Cysteine analysis, Cys-BOOST shows a threefold higher sensitivity and considerably higher specificity and precision. Analyzing S-nitrosylation (SNO) in S-nitrosoglutathione (GSNO)-treated and non-treated HeLa extracts Cys-BOOST identifies 8,304 SNO sites on 3,632 proteins covering a wide dynamic range of the proteome. Consensus motifs of SNO sites with differential GSNO reactivity confirm the relevance of both acid-base catalysis and local hydrophobicity for NO targeting to particular Cysteines. Applying Cys-BOOST to SH-SY5Y cells, we identify 2,151 SNO sites under basal conditions and reveal significantly changed SNO levels as response to early nitrosative stress, involving neuro(axono)genesis, glutamatergic synaptic transmission, protein folding/translation, and DNA replication. Our work suggests SNO as a global regulator of protein function akin to phosphorylation and ubiquitination.

Reversible cysteine modifications play important roles in cellular redox signaling. Here, the authors develop a chemical proteomics strategy that enables the quantitative analysis of endogenous cysteine nitrosylation sites and their dynamic regulation under nitrosative stress conditions.

Comprehensive Analysis of Aspergillus nidulans PKA Phosphorylome Identifies a Novel Mode of CreA Regulation

The cyclic AMP (cAMP)-dependent protein kinase A (PKA) signaling pathway is well conserved across eukaryotes, and previous work has shown that it plays an important role in regulating development, growth, and virulence in a number of fungi. PKA is activated in response to extracellular nutrients and acts to regulate metabolism and growth. While a number of components in the PKA pathway have been defined in filamentous fungi, current understanding does not provide a global perspective on PKA function. Thus, this work is significant in that it comprehensively identifies proteins and functional pathways regulated by PKA in a model filamentous fungus. This information enhances our understanding of PKA action and may provide information on how to manipulate it for specific purposes.

In filamentous fungi, an important kinase responsible for adaptation to changes in available nutrients is cyclic AMP (cAMP)-dependent protein kinase (protein kinase A [PKA]). This kinase has been well characterized at a molecular level, but its systemic action and direct/indirect targets are generally not well understood in filamentous fungi. In this work, we used a pkaA deletion strain (ΔpkaA) to identify Aspergillus nidulans proteins for which phosphorylation is dependent (either directly or indirectly) on PKA. A combination of phosphoproteomic and transcriptomic analyses revealed both direct and indirect targets of PKA and provided a global perspective on its function. One of these targets was the transcription factor CreA, the main repressor responsible for carbon catabolite repression (CCR). In the ΔpkaA strain, we identified a previously unreported phosphosite in CreA, S319, which (based on motif analysis) appears to be a direct target of Stk22 kinase (AN5728). Upon replacement of CreA S319 with an alanine (i.e., phosphonull mutant), the dynamics of CreA import to the nucleus are affected. Collectively, this work provides a global overview of PKA function while also providing novel insight regarding significance of a specific PKA-mediated phosphorylation event.

Regulation of proline-directed kinases and the trans-histone code H3K9me3/H4K20me3 during human myogenesis

We present a system-level analysis of proteome, phosphoproteome, and chromatin state of precursors of muscle cells (myoblasts) differentiating into specialized myotubes. Using stable isotope labeling of amino acids in cell culture and nano-liqud chromatography-mass spectrometry/mass spectrometry, we found that phosphorylation motifs targeted by the kinases protein kinase C, cyclin-dependent kinase, and mitogen-activated protein kinase showed increased phosphorylation during myodifferentiation of LHCN-M2 human skeletal myoblast cell line. Drugs known to inhibit these kinases either promoted (PD0325901 and GW8510) or stalled (CHIR99021 and roscovitine) differentiation, resulting in myotube and myoblast phenotypes, respectively. The proteomes, especially the myogenic and chromatin-related proteins including histone methyltransferases, correlated with their phenotypes, leading us to quantify histone post-translational modifications and identify two gene-silencing marks, H3K9me3 and H4K20me3, with relative abundances changing in correlation with these phenotypes. ChIP-quantitative PCR demonstrated that H3K9me3 is erased from the gene loci of myogenic regulatory factors namely MYOD1, MYOG, and MYF5 in differentiating myotubes. Together, our work integrating histone post-translational modification, phosphoproteomics, and full proteome analysis gives a comprehensive understanding of the close connection between signaling pathways and epigenetics during myodifferentiation in vitro.

Quantitative Phosphoproteomic Analysis Reveals Shared and Specific Targets of Arabidopsis Mitogen-Activated Protein Kinases (MAPKs) MPK3, MPK4, and MPK6

In Arabidopsis, mitogen-activated protein kinases MPK3, MPK4, and MPK6 constitute essential relays for a variety of functions including cell division, development and innate immunity. Although some substrates of MPK3, MPK4 and MPK6 have been identified, the picture is still far from complete. To identify substrates of these MAPKs likely involved in cell division, growth and development we compared the phosphoproteomes of wild-type and mpk3, mpk4, and mpk6. To study the function of these MAPKs in innate immunity, we analyzed their phosphoproteomes following microbe-associated molecular pattern (MAMP) treatment. Partially overlapping substrates were retrieved for all three MAPKs, showing target specificity to one, two or all three MAPKs in different biological processes. More precisely, our results illustrate the fact that the entity to be defined as a specific or a shared substrate for MAPKs is not a phosphoprotein but a particular (S/T)P phosphorylation site in a given protein. One hundred fifty-two peptides were identified to be differentially phosphorylated in response to MAMP treatment and/or when compared between genotypes and 70 of them could be classified as putative MAPK targets. Biochemical analysis of a number of putative MAPK substrates by phosphorylation and interaction assays confirmed the global phosphoproteome approach. Our study also expands the set of MAPK substrates to involve other protein kinases, including calcium-dependent (CDPK) and sugar nonfermenting (SnRK) protein kinases.

Quantitative cardiac phosphoproteomics profiling during ischemia-reperfusion in an immature swine model

Ischemia-reperfusion (I/R) results in altered metabolic and molecular responses, and phosphorylation is one of the most noted regulatory mechanisms mediating signaling mechanisms during physiological stresses. To expand our knowledge of the potential phosphoproteomic changes in the myocardium during I/R, we used Isobaric Tags for Relative and Absolute Quantitation-based analyses in left ventricular samples obtained from porcine hearts under control or I/R conditions. The data are available via ProteomeXchange with identifier PXD006066. We identified 1,896 phosphopeptides within left ventricular control and I/R porcine samples. Significant differential phosphorylation between control and I/R groups was discovered in 111 phosphopeptides from 86 proteins. Analysis of the phosphopeptides using Motif-x identified five motifs: (..R..S..), (..SP..), (..S.S..), (..S…S..), and (..S.T..). Semiquantitative immunoblots confirmed site location and directional changes in phosphorylation for phospholamban and pyruvate dehydrogenase E1, two proteins known to be altered by I/R and identified by this study. Novel phosphorylation sites associated with I/R were also identified. Functional characterization of the phosphopeptides identified by our methodology could expand our understanding of the signaling mechanisms involved during I/R damage in the heart as well as identify new areas to target therapeutic strategies.NEW & NOTEWORTHY We used Isobaric Tags for Relative and Absolute Quantitation technology to investigate the phosphoproteomic changes that occur in cardiac tissue under ischemia-reperfusion conditions. The results of this study provide an extensive catalog of phosphoproteins, both predicted and novel, associated with ischemia-reperfusion, thereby identifying new pathways for investigation.

Cushing's syndrome mutant PKAL205R exhibits altered substrate specificity

The PKA^L205R hotspot mutation has been implicated in Cushing's syndrome through hyperactive gain-of-function PKA signaling; however, its influence on substrate specificity has not been investigated. Here, we employ the Proteomic Peptide Library (ProPeL) approach to create high-resolution models for PKA^WT and PKA^L205R substrate specificity. We reveal that the L205R mutation reduces canonical hydrophobic preference at the substrate P + 1 position, and increases acidic preference in downstream positions. Using these models, we designed peptide substrates that exhibit altered selectivity for specific PKA variants, and demonstrate the feasibility of selective PKA^L205R loss-of-function signaling. Through these results, we suggest that substrate rewiring may contribute to Cushing's syndrome disease etiology, and introduce a powerful new paradigm for investigating mutation-induced kinase substrate rewiring in human disease.

Homer1a drives homeostatic scaling-down of excitatory synapses during sleep

Sleep is an essential process that supports learning and memory by acting on synapses through poorly understood molecular mechanisms. Using biochemistry, proteomics, and imaging in mice, we find that during sleep, synapses undergo widespread alterations in composition and signaling, including weakening of synapses through removal and dephosphorylation of synaptic AMPA-type glutamate receptors. These changes are driven by the immediate early gene Homer1a and signaling from group I metabotropic glutamate receptors mGluR1/5. Homer1a serves as a molecular integrator of arousal and sleep need via the wake- and sleep-promoting neuromodulators, noradrenaline and adenosine, respectively. Our data suggest that homeostatic scaling-down, a global form of synaptic plasticity, is active during sleep to remodel synapses and participates in the consolidation of contextual memory.

Global phosphoproteomic profiling reveals perturbed signaling in a mouse model of dilated cardiomyopathy

Phospholamban (PLN) plays a central role in Ca²⁺ homeostasis in cardiac myocytes through regulation of the sarco(endo)plasmic reticulum Ca²⁺-ATPase 2A (SERCA2A) Ca²⁺ pump. An inherited mutation converting arginine residue 9 in PLN to cysteine (R9C) results in dilated cardiomyopathy (DCM) in humans and transgenic mice, but the downstream signaling defects leading to decompensation and heart failure are poorly understood. Here we used precision mass spectrometry to study the global phosphorylation dynamics of 1,887 cardiac phosphoproteins in early affected heart tissue in a transgenic R9C mouse model of DCM compared with wild-type littermates. Dysregulated phosphorylation sites were quantified after affinity capture and identification of 3,908 phosphopeptides from fractionated whole-heart homogenates. Global statistical enrichment analysis of the differential phosphoprotein patterns revealed selective perturbation of signaling pathways regulating cardiovascular activity in early stages of DCM. Strikingly, dysregulated signaling through the Notch-1 receptor, recently linked to cardiomyogenesis and embryonic cardiac stem cell development and differentiation but never directly implicated in DCM before, was a prominently perturbed pathway. We verified alterations in Notch-1 downstream components in early symptomatic R9C transgenic mouse cardiomyocytes compared with wild type by immunoblot analysis and confocal immunofluorescence microscopy. These data reveal unexpected connections between stress-regulated cell signaling networks, specific protein kinases, and downstream effectors essential for proper cardiac function.

N-linked glycosite profiling and use of Skyline as a platform for characterization and relative quantification of glycans in differentiating xylem of Populus trichocarpa

Our greater understanding of the importance of N-linked glycosylation in biological systems has spawned the field of glycomics and development of analytical tools to address the many challenges regarding our ability to characterize and quantify this complex and important modification as it relates to biological function. One of the unmet needs of the field remains a systematic method for characterization of glycans in new biological systems. This study presents a novel workflow for identification of glycans using Individuality Normalization when Labeling with Isotopic Glycan Hydrazide Tags (INLIGHT™) strategy developed in our lab. This consists of monoisotopic mass extraction followed by peak pair identification of tagged glycans from a theoretical library using an in-house program. Identification and relative quantification could then be performed using the freely available bioinformatics tool Skyline. These studies were performed in the biological context of studying the N-linked glycome of differentiating xylem of the poplar tree, a widely studied model woody plant, particularly with respect to understanding lignin biosynthesis during wood formation. Through our workflow, we were able to identify 502 glycosylated proteins including 12 monolignol enzymes and 1 peroxidase (PO) through deamidation glycosite analysis. Finally, our novel semi-automated workflow allowed for rapid identification of 27 glycans by intact mass and by NAT/SIL peak pairing from a library containing 1573 potential glycans, eliminating the need for extensive manual analysis. Implementing Skyline for relative glycan quantification allowed for improved accuracy and precision of quantitative measurements over current processing tools which we attribute to superior algorithms correction for baseline variation and MS1 peak filtering. Graphical abstract Workflow for FANGS-INLIGHT glycosite profiling of plant xylem and monolignol proteins followed by INLIGHT tagging with semi-automated identification of glycans by light-heavy peak pairs. Finally, manual validation and relative quantification was performed in Skyline.

A homology-based pipeline for global prediction of post-translational modification sites

The pathways of protein post-translational modifications (PTMs) have been shown to play particularly important roles for almost any biological process. Identification of PTM substrates along with information on the exact sites is fundamental for fully understanding or controlling biological processes. Alternative computational strategies would help to annotate PTMs in a high-throughput manner. Traditional algorithms are suited for identifying the common organisms and tissues that have a complete PTM atlas or extensive experimental data. While annotation of rare PTMs in most organisms is a clear challenge. In this work, to this end we have developed a novel homology-based pipeline named PTMProber that allows identification of potential modification sites for most of the proteomes lacking PTMs data. Cross-promotion E-value (CPE) as stringent benchmark has been used in our pipeline to evaluate homology to known modification sites. Independent-validation tests show that PTMProber achieves over 58.8% recall with high precision by CPE benchmark. Comparisons with other machine-learning tools show that PTMProber pipeline performs better on general predictions. In addition, we developed a web-based tool to integrate this pipeline at http://bioinfo.ncu.edu.cn/PTMProber/index.aspx. In addition to pre-constructed prediction models of PTM, the website provides an extensional functionality to allow users to customize models.

Proteomic and Phosphoproteomic Insights into a Signaling Hub Role for Cdc14 in Asexual Development and Multiple Stress Responses in Beauveria bassiana

Cdc14 is a dual-specificity phosphatase that regulates nuclear behavior by dephosphorylating phosphotyrosine and phosphoserine/phosphothreonine in fungi. Previously, Cdc14 was shown to act as a positive regulator of cytokinesis, asexual development and multiple stress responses in Beauveria bassiana, a fungal insect pathogen. This study seeks to gain deep insight into a pivotal role of Cdc14 in the signaling network of B. bassiana by analyzing the Cdc14-specific proteome and phosphoproteome generated by the 8-plex iTRAQ labeling and MS/MS analysis of peptides and phosphopeptides. Under normal conditions, 154 proteins and 86 phosphorylation sites in 67 phosphoproteins were upregulated in Δcdc14 versus wild-type, whereas 117 proteins and 85 phosphorylation sites in 58 phosphoproteins were significantly downregulated. Co-cultivation of Δcdc14 with NaCl (1 M), H₂O₂ (3 mM) and Congo red (0.15 mg/ml) resulted in the upregulation / downregulation of 23/63, 41/39 and 79/79 proteins and of 127/112, 52/47 and 105/226 phosphorylation sites in 85/92, 45/36 and 79/146 phosphoproteins, respectively. Bioinformatic analyses revealed that Cdc14 could participate in many biological and cellular processes, such as carbohydrate metabolism, glycerophospholipid metabolism, the MAP Kinase signaling pathway, and DNA conformation, by regulating protein expression and key kinase phosphorylation in response to different environmental cues. These indicate that in B. bassiana, Cdc14 is a vital regulator of not only protein expression but also many phosphorylation events involved in developmental and stress-responsive pathways. Fourteen conserved and novel motifs were identified in the fungal phosphorylation events.

Quantitative Profiling of the Activity of Protein Lysine Methyltransferase SMYD2 Using SILAC-Based Proteomics

The significance of non-histone lysine methylation in cell biology and human disease is an emerging area of research exploration. The development of small molecule inhibitors that selectively and potently target enzymes that catalyze the addition of methyl-groups to lysine residues, such as the protein lysine mono-methyltransferase SMYD2, is an active area of drug discovery. Critical to the accurate assessment of biological function is the ability to identify target enzyme substrates and to define enzyme substrate specificity within the context of the cell. Here, using stable isotopic labeling with amino acids in cell culture (SILAC) coupled with immunoaffinity enrichment of mono-methyl-lysine (Kme1) peptides and mass spectrometry, we report a comprehensive, large-scale proteomic study of lysine mono-methylation, comprising a total of 1032 Kme1 sites in esophageal squamous cell carcinoma (ESCC) cells and 1861 Kme1 sites in ESCC cells overexpressing SMYD2. Among these Kme1 sites is a subset of 35 found to be potently down-regulated by both shRNA-mediated knockdown of SMYD2 and LLY-507, a selective small molecule inhibitor of SMYD2. In addition, we report specific protein sequence motifs enriched in Kme1 sites that are directly regulated by endogenous SMYD2 activity, revealing that SMYD2 substrate specificity is more diverse than expected. We further show direct activity of SMYD2 toward BTF3-K2, PDAP1-K126 as well as numerous sites within the repetitive units of two unique and exceptionally large proteins, AHNAK and AHNAK2. Collectively, our findings provide quantitative insights into the cellular activity and substrate recognition of SMYD2 as well as the global landscape and regulation of protein mono-methylation.

Uncovering Phosphorylation-Based Specificities through Functional Interaction Networks

Protein kinases are an important class of enzymes involved in the phosphorylation of their targets, which regulate key cellular processes and are typically mediated by a specificity for certain residues around the target phospho-acceptor residue. While efforts have been made to identify such specificities, only ∼30% of human kinases have a significant number of known binding sites. We describe a computational method that utilizes functional interaction data and phosphorylation data to predict specificities of kinases. We applied this method to human kinases to predict substrate preferences for 57% of all known kinases and show that we are able to reconstruct well-known specificities. We used an in vitro mass spectrometry approach to validate four understudied kinases and show that predicted models closely resemble true specificities. We show that this method can be applied to different organisms and can be extended to other phospho-recognition domains. Applying this approach to different types of posttranslational modifications (PTMs) and binding domains could uncover specificities of understudied PTM recognition domains and provide significant insight into the mechanisms of signaling networks.

Correct machine learning on protein sequences: a peer-reviewing perspective

Machine learning methods are becoming increasingly popular to predict protein features from sequences. Machine learning in bioinformatics can be powerful but carries also the risk of introducing unexpected biases, which may lead to an overestimation of the performance. This article espouses a set of guidelines to allow both peer reviewers and authors to avoid common machine learning pitfalls. Understanding biology is necessary to produce useful data sets, which have to be large and diverse. Separating the training and test process is imperative to avoid over-selling method performance, which is also dependent on several hidden parameters. A novel predictor has always to be compared with several existing methods, including simple baseline strategies. Using the presented guidelines will help nonspecialists to appreciate the critical issues in machine learning.

Systematic Analysis of the Genetic Variability That Impacts SUMO Conjugation and Their Involvement in Human Diseases

Protein function has been observed to rely on select essential sites instead of requiring all sites to be indispensable. Small ubiquitin-related modifier (SUMO) conjugation or sumoylation, which is a highly dynamic reversible process and its outcomes are extremely diverse, ranging from changes in localization to altered activity and, in some cases, stability of the modified, has shown to be especially valuable in cellular biology. Motivated by the significance of SUMO conjugation in biological processes, we report here on the first exploratory assessment whether sumoylation related genetic variability impacts protein functions as well as the occurrence of diseases related to SUMO. Here, we defined the SUMOAMVR as sumoylation related amino acid variations that affect sumoylation sites or enzymes involved in the process of connectivity, and categorized four types of potential SUMOAMVRs. We detected that 17.13% of amino acid variations are potential SUMOAMVRs and 4.83% of disease mutations could lead to SUMOAMVR with our system. More interestingly, the statistical analysis demonstrates that the amino acid variations that directly create new potential lysine sumoylation sites are more likely to cause diseases. It can be anticipated that our method can provide more instructive guidance to identify the mechanisms of genetic diseases.

Phosphoproteome Analysis Links Protein Phosphorylation to Cellular Remodeling and Metabolic Adaptation during Magnaporthe oryzae Appressorium Development

The rice pathogen, Magnaporthe oryzae, undergoes a complex developmental process leading to formation of an appressorium prior to plant infection. In an effort to better understand phosphoregulation during appressorium development, a mass spectrometry based phosphoproteomics study was undertaken. A total of 2924 class I phosphosites were identified from 1514 phosphoproteins from mycelia, conidia, germlings, and appressoria of the wild type and a protein kinase A (PKA) mutant. Phosphoregulation during appressorium development was observed for 448 phosphosites on 320 phosphoproteins. In addition, a set of candidate PKA targets was identified encompassing 253 phosphosites on 227 phosphoproteins. Network analysis incorporating regulation from transcriptomic, proteomic, and phosphoproteomic data revealed new insights into the regulation of the metabolism of conidial storage reserves and phospholipids, autophagy, actin dynamics, and cell wall metabolism during appressorium formation. In particular, protein phosphorylation appears to play a central role in the regulation of autophagic recycling and actin dynamics during appressorium formation. Changes in phosphorylation were observed in multiple components of the cell wall integrity pathway providing evidence that this pathway is highly active during appressorium development. Several transcription factors were phosphoregulated during appressorium formation including the bHLH domain transcription factor MGG_05709. Functional analysis of MGG_05709 provided further evidence for the role of protein phosphorylation in regulation of glycerol metabolism and the metabolic reprogramming characteristic of appressorium formation. The data presented here represent a comprehensive investigation of the M. oryzae phosphoproteome and provide key insights on the role of protein phosphorylation during infection-related development.

Lysine acetylproteome analysis suggests its roles in primary and secondary metabolism in Saccharopolyspora erythraea

Lysine acetylation is a dynamic, reversible posttranslational modification that is known to play an important role in regulating the activity of many key enzymes in bacteria. Acetylproteome studies have been performed on some bacteria. However, until now, there have been no data on Actinomycetes, which are the major producers of therapeutic antibiotics. In this study, we investigated the first acetylproteome of the erythromycin-producing actinomycete Saccharopolyspora erythraea using a high-resolution mass spectrometry-based proteomics approach. Using immune-affinity isolation of acetyl-peptides with an anti-acetyllysine antibody followed by nano ultra performance liquid chromatography tandem mass spectroscopy (nanoUPLC-MS/MS) analysis, we identified 664 unique lysine-acetylated sites on 363 proteins. Acetylated proteins are involved in many biological processes such as protein synthesis, glycolysis/gluconeogenesis, citric acid (TCA) cycle, fatty acid metabolism, secondary metabolism, and the feeder metabolic pathways of erythromycin synthesis. We characterized the acetylproteome and analyzed in detail the impact of acetylation on diverse cellular functions according to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Four motif sequences surrounding the acetylation sites (K(AC)H, K(AC)Y, K(AC)XXXXR, and K(AC)XXXXK) were found in the S. erythraea acetylproteome. These findings suggest that abundant lysine acetylation occurs in Actinomycetes, expand our current knowledge of the bacterial acetylproteome, and provide insight into the regulatory function of acetylation in primary and secondary metabolism.

Deep sequencing reveals novel Set7 networks

BACKGROUND

Methyl-dependent regulation of transcription has expanded from a traditional focus on histones to encompass transcription factor modulation. While the Set7 lysine methyltransferase is associated with pro-inflammatory gene expression in vascular endothelial cells, genome-wide regulatory roles remain to be investigated. From initial characterization of Set7 as specific for methyl-lysine 4 of H3 histones (H3K4m1), biochemical activity toward non-histone substrates has revealed additional mechanisms of gene regulation.

RESULTS

mRNA-Seq revealed transcriptional deregulation of over 8,000 genes in an endothelial model of Set7 knockdown. Gene ontology identified up-regulated pathways involved in developmental processes and extracellular matrix remodeling, whereas pathways regulating the inflammatory response as well as nitric oxide signaling were down-regulated. Chromatin maps derived from ChIP-Seq profiling of H3K4m1 identified several hundred loci with loss of H3K4m1 at gene regulatory elements associated with an unexpectedly subtle effect on gene expression. Transcription factor network analysis implicated six previously described Set7 substrates in mRNA-Seq changes, and we predict that Set7 post-translationally regulates other transcription factors associated with vascular endothelial gene expression through the presence of Set7 amino acid methylation motifs.

CONCLUSION

We describe a role for Set7 in regulating developmental pathways and response to stimuli (inflammation/immune response) in human endothelial cells of vascular origin. Set7-dependent gene expression changes that occurred independent of H3K4m1 may involve transcription factor lysine methylation events. The method of mapping measured transcriptional changes to transcription factors to identify putative substrates with strong associations to functional changes is applicable to substrate prediction for other broad-substrate histone modifiers.

Large-scale phosphoproteome analysis in seedling leaves of Brachypodium distachyon L

Background

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.

Results

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.

Conclusions

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.

Motifs tree: a new method for predicting post-translational modifications

MOTIVATION

Post-translational modifications (PTMs) are important steps in the maturation of proteins. Several models exist to predict specific PTMs, from manually detected patterns to machine learning methods. On one hand, the manual detection of patterns does not provide the most efficient classifiers and requires an important workload, and on the other hand, models built by machine learning methods are hard to interpret and do not increase biological knowledge. Therefore, we developed a novel method based on patterns discovery and decision trees to predict PTMs. The proposed algorithm builds a decision tree, by coupling the C4.5 algorithm with genetic algorithms, producing high-performance white box classifiers. Our method was tested on the initiator methionine cleavage (IMC) and N(α)-terminal acetylation (N-Ac), two of the most common PTMs.

RESULTS

The resulting classifiers perform well when compared with existing models. On a set of eukaryotic proteins, they display a cross-validated Matthews correlation coefficient of 0.83 (IMC) and 0.65 (N-Ac). When used to predict potential substrates of N-terminal acetyltransferaseB and N-terminal acetyltransferaseC, our classifiers display better performance than the state of the art. Moreover, we present an analysis of the model predicting IMC for Homo sapiens proteins and demonstrate that we are able to extract experimentally known facts without prior knowledge. Those results validate the fact that our method produces white box models.

AVAILABILITY AND IMPLEMENTATION

Predictors for IMC and N-Ac and all datasets are freely available at http://terminus.unige.ch/.

Integrative network analysis of the signaling cascades in seedling leaves of bread wheat by large-scale phosphoproteomic profiling

Here, we conducted the first large-scale leaf phosphoproteome analysis of two bread wheat cultivars by liquid chromatography-tandem mass spectrometry. Altogether, 1802 unambiguous phosphorylation sites representing 1175 phosphoproteins implicated in various molecular functions and cellular processes were identified by gene ontology enrichment analysis. Among the 1175 phosphoproteins, 141 contained 3-10 phosphorylation sites. The phosphorylation sites were located more frequently in the N- and C-terminal regions than in internal regions, and ∼70% were located outside the conserved regions. Conservation analysis showed that 90.5% of the phosphoproteins had phosphorylated orthologs in other plant species. Eighteen significantly enriched phosphorylation motifs, of which six were new wheat phosphorylation motifs, were identified. In particular, 52 phosphorylated transcription factors (TFs), 85 protein kinases (PKs), and 16 protein phosphatases (PPs) were classified and analyzed in depth. All the Tyr phosphorylation sites were in PKs such as mitogen-activated PKs (MAPKs) and SHAGGY-like kinases. A complicated cross-talk phosphorylation regulatory network based on PKs such as Snf1-related kinases (SnRKs), calcium-dependent PKs (CDPKs), and glycogen synthase kinase 3 (GSK3) and PPs including PP2C, PP2A, and BRI1 suppressor 1 (BSU1)-like protein (BSL) was constructed and was found to be potentially involved in rapid leaf growth. Our results provide a series of phosphoproteins and phosphorylation sites in addition to a potential network of phosphorylation signaling cascades in wheat seedling leaves.

Global phosphoproteomic profiling reveals distinct signatures in B-cell non-Hodgkin lymphomas

Deregulation of signaling pathways controlled by protein phosphorylation underlies the pathogenesis of hematological malignancies; however, the extent to which deregulated phosphorylation may be involved in B-cell non-Hodgkin lymphoma (B-NHL) pathogenesis is largely unknown. To identify phosphorylation events important in B-NHLs, we performed mass spectrometry-based, label-free, semiquantitative phosphoproteomic profiling of 11 cell lines derived from three B-NHL categories: Burkitt lymphoma, follicular lymphoma, and mantle-cell lymphoma. In all, 6579 unique phosphopeptides, corresponding to 1701 unique phosphorylated proteins, were identified and quantified. The data are available via ProteomeXchange with identifier PXD000658. Hierarchical clustering highlighted distinct phosphoproteomic signatures associated with each lymphoma subtype. Interestingly, germinal center-derived B-NHL cell lines were characterized by phosphorylation of proteins involved in the B-cell receptor signaling. Of these proteins, phosphoprotein associated with glycosphingolipid-enriched microdomains 1 (PAG1) was identified with the most phosphorylated tyrosine peptides in Burkitt lymphoma and follicular lymphoma. PAG1 knockdown resulted in perturbation of the tyrosine phosphosignature of B-cell receptor signaling components. Significantly, PAG1 knockdown increased cell proliferation and response to antigen stimulation of these germinal center-derived B-NHLs. These data provide a detailed annotation of phosphorylated proteins in human lymphoid cancer. Overall, our study revealed the utility of unbiased phosphoproteome interrogation in characterizing signaling networks that may provide insights into pathogenesis mechanisms in B-cell lymphomas.

RUBI: rapid proteomic-scale prediction of lysine ubiquitination and factors influencing predictor performance

Post-translational modification of protein lysines was recently shown to be a common feature of eukaryotic organisms. The ubiquitin modification is regarded as a versatile regulatory mechanism with many important cellular roles. Large-scale datasets are becoming available for H. sapiens ubiquitination. However, using current experimental techniques the vast majority of their sites remain unidentified and in silico tools may offer an alternative. Here, we introduce Rapid UBIquitination (RUBI) a sequence-based ubiquitination predictor designed for rapid application on a genome scale. RUBI was constructed using an iterative approach. At each iteration, important factors which influenced performance and its usability were investigated. The final RUBI model has an AUC of 0.868 on a large cross-validation set and is shown to outperform other available methods on independent sets. Predicted intrinsic disorder is shown to be weakly anti-correlated to ubiquitination for the H. sapiens dataset and improves performance slightly. RUBI predicts the number of ubiquitination sites correctly within three sites for ca. 80% of the tested proteins. The average potentially ubiquitinated proteome fraction is predicted to be at least 25% across a variety of model organisms, including several thousand possible H. sapiens proteins awaiting experimental characterization. RUBI can accurately predict ubiquitination on unseen examples and has a signal across different eukaryotic organisms. The factors which influenced the construction of RUBI could also be tested in other post-translational modification predictors. One of the more interesting factors is the influence of intrinsic protein disorder on ubiquitinated lysines where residues with low disorder probability are preferred.

Mass spectrometry-driven phosphoproteomics: patterning the systems biology mosaic

Protein phosphorylation is the best-studied posttranslational modification and plays a role in virtually every biological process. Phosphoproteomics is the analysis of protein phosphorylation on a proteome-wide scale, and mainly uses the same instrumentation and analogous strategies as conventional mass spectrometry (MS)-based proteomics. Measurements can be performed either in a discovery-type, also known as shotgun mode, or in a targeted manner which monitors a set of a priori known phosphopeptides, such as members of a signal transduction pathway, across biological samples. Here, we delineate the different experimental levels at which measures can be taken to optimize the scope, reliability, and information content of phosphoproteomic analyses. Various chromatographic and chemical protocols exist to physically enrich phosphopeptides from proteolytic digests of biological samples. Subsequent mass spectrometric analysis revolves around peptide ion fragmentation to generate sequence information and identify the backbone sequence of phosphopeptides as well as the phosphate group attachment site(s), and different modes of fragmentation like collision-induced dissociation (CID), electron transfer dissociation (ETD), and higher energy collisional dissociation (HCD) have been established for phosphopeptide analysis. Computational tools are important for the identification and quantification of phosphopeptides and mapping of phosphorylation sites, the deposition of large-scale phosphoproteome datasets in public databases, and the extraction of biologically meaningful information by data mining, integration with other data types, and descriptive or predictive modeling. Finally, we discuss how orthogonal experimental approaches can be employed to validate newly identified phosphorylation sites on a biochemical, mechanistic, and physiological level.

In silico platform for prediction of N-, O- and C-glycosites in eukaryotic protein sequences

Glycosylation is one of the most abundant and an important post-translational modification of proteins. Glycosylated proteins (glycoproteins) are involved in various cellular biological functions like protein folding, cell-cell interactions, cell recognition and host-pathogen interactions. A large number of eukaryotic glycoproteins also have therapeutic and potential technology applications. Therefore, characterization and analysis of glycosites (glycosylated residues) in these proteins is of great interest to biologists. In order to cater these needs a number of in silico tools have been developed over the years, however, a need to get even better prediction tools remains. Therefore, in this study we have developed a new webserver GlycoEP for more accurate prediction of N-linked, O-linked and C-linked glycosites in eukaryotic glycoproteins using two larger datasets, namely, standard and advanced datasets. In case of standard datasets no two glycosylated proteins are more similar than 40%; advanced datasets are highly non-redundant where no two glycosites’ patterns (as defined in methods) have more than 60% similarity. Further, based on our results with several algorihtms developed using different machine-learning techniques, we found Support Vector Machine (SVM) as optimum tool to develop glycosite prediction models. Accordingly, using our more stringent and non-redundant advanced datasets, the SVM based models developed in this study achieved a prediction accuracy of 84.26%, 86.87% and 91.43% with corresponding MCC of 0.54, 0.20 and 0.78, for N-, O- and C-linked glycosites, respectively. The best performing models trained on advanced datasets were then implemented as a user-friendly web server GlycoEP (http://www.imtech.res.in/raghava/glycoep/). Additionally, this server provides prediction models developed on standard datasets and allows users to scan sequons in input protein sequences.

Phosphorylation of serine palmitoyltransferase long chain-1 (SPTLC1) on tyrosine 164 inhibits its activity and promotes cell survival

In BCR-ABL-expressing cells, sphingolipid metabolism is altered. Because the first step of sphingolipid biosynthesis occurs in the endoplasmic reticulum (ER), our objective was to identify ABL targets in the ER. A phosphoproteomic analysis of canine pancreatic ER microsomes identified 49 high scoring phosphotyrosine-containing peptides. These were then categorized in silico and validated in vitro. We demonstrated that the ER-resident human protein serine palmitoyltransferase long chain-1 (SPTLC1), which is the first enzyme of sphingolipid biosynthesis, is phosphorylated at Tyr(164) by the tyrosine kinase ABL. Inhibition of BCR-ABL using either imatinib or shRNA-mediated silencing led to the activation of SPTLC1 and to increased apoptosis in both K562 and LAMA-84 cells. Finally, we demonstrated that mutation of Tyr(164) to Phe in SPTLC1 increased serine palmitoyltransferase activity. The Y164F mutation also promoted the remodeling of cellular sphingolipid content, thereby sensitizing K562 cells to apoptosis. Our observations provide a mechanistic explanation for imatinib-mediated cell death and a novel avenue for therapeutic strategies.

Global remodelling of cellular microenvironment due to loss of collagen VII

Loss of collagen VII causes recessive dystrophic epidermolysis bullosa. Quantitative proteomics analysis of the extracellular matrix and secretome of human fibroblasts derived from pathologically altered skin reveals a global remodelling of the cellular microenvironment.

A global analysis of the microenvironment of human skin fibroblasts was carried out to reveal disease-related alterations in the extracellular proteome.

The loss of collagen VII causes a deregulation of the basement membrane and dermal matrix proteome.

Post-translational modifications of secreted proteins were altered in fibroblasts from recessive dystrophic epidermolysis bullosa samples.

Metalloproteases displayed reduced activity and turnover in collagen VII-deficient cells.

The mammalian cellular microenvironment is shaped by soluble factors and structural components, the extracellular matrix, providing physical support, regulating adhesion and signalling. A global, quantitative mass spectrometry strategy, combined with bioinformatics data processing, was developed to assess proteome differences in the microenvironment of primary human fibroblasts. We studied secreted proteins of fibroblasts from normal and pathologically altered skin and their post-translational modifications. The influence of collagen VII, an important structural component, which is lost in genetic skin fragility, was used as model. Loss of collagen VII had a global impact on the cellular microenvironment and was associated with proteome alterations highly relevant for disease pathogenesis including decrease in basement membrane components, increase in dermal matrix proteins, TGF-β and metalloproteases, but not higher protease activity. The definition of the proteome of fibroblast microenvironment and its plasticity in health and disease identified novel disease mechanisms and potential targets of intervention.

Systematic analysis of human lysine acetylation proteins and accurate prediction of human lysine acetylation through bi-relative adapted binomial score Bayes feature representation

Lysine acetylation is a reversible post-translational modification (PTM) which has been linked to many biological and pathological implications. Hence, localization of lysine acetylation is essential for deciphering the mechanism of such implications. Whereas many acetylated lysines in human proteins have been localized through experimental approaches in wet lab, it still fails to reach completion. In the present study, we proposed a novel feature extraction approach, bi-relative adapted binomial score Bayes (BRABSB), combined with support vector machines (SVMs) to construct a human-specific lysine acetylation predictor, which yields, on average, a sensitivity of 83.91%, a specificity of 87.25% and an accuracy of 85.58%, in the case of 5-fold cross validation experiments. Results obtained through the validation on independent data sets show that the proposed approach here outperforms other existing lysine acetylation predictors. Furthermore, due to the fact that global analysis of human lysine acetylproteins, which would ultimately facilitate the systematic investigation of the biological and pathological consequences associated with lysine acetylation events, remains to be resolved, we made an attempt to systematically analyze human lysine acetylproteins, demonstrating their diversity with respect to subcellular localization as well as biological process and predominance by "binding" in terms of molecular function. Our analysis also revealed that human lysine acetylproteins are significantly enriched in neurodegenerative disorders and cancer pathways. Remarkably, lysine acetylproteins in mitochondria are significantly related to neurodegenerative disorders and those in the nucleus are instead significantly involved in pathways in cancers, all of which might ultimately provide novel global insights into such pathological processes for the therapeutic purpose. The web server is deployed at http://www.bioinfo.bio.cuhk.edu.hk/bpbphka.

Proteomic strategies to characterize signaling pathways

Cells respond to external stimuli by transducing signals through a series of intracellular molecules and eliciting an appropriate response. The cascade of events through which the signals are transduced include post-translational modifications such as phosphorylation and ubiquitylation in addition to formation of multi-protein complexes. Improvements in biological mass spectrometry and protein/peptide microarray technology have tremendously improved our ability to probe proteins, protein complexes, and signaling pathways in a high-throughput fashion. Today, a single mass spectrometry-based investigation of a signaling pathway has the potential to uncover the large majority of known signaling intermediates painstakingly characterized over decades in addition to discovering a number of novel ones. Here, we discuss various proteomic strategies to characterize signaling pathways and provide protocols for phosphoproteomic analysis.

Computational prediction of lysine acetylation proteome-wide

Several studies have contributed to our knowledge of the enzymology underlying acetylation, including focused efforts to understand the molecular mechanism of substrate recognition by several acetyltransferases; however, conventional experiments to determine intrinsic features of substrate site specificity have proven challenging. In this chapter, I describe in detail a computational method that involves clustering analysis of protein sequences to predict protein acetylation based on the sequence characteristics of acetylated lysines within histones. This method illustrates that sequence composition has predictive power on datasets of acetylation marks, and can be used to predict other posttranslational modifications such as methylation and phosphorylation. Later in this chapter, other recent methods to predict lysine acetylation are described and together, these approaches combined with more traditional experimental methods, can be useful for identifying acetylated substrates proteome-wide.

Using bacteria to determine protein kinase specificity and predict target substrates

The identification of protein kinase targets remains a significant bottleneck for our understanding of signal transduction in normal and diseased cellular states. Kinases recognize their substrates in part through sequence motifs on substrate proteins, which, to date, have most effectively been elucidated using combinatorial peptide library approaches. Here, we present and demonstrate the ProPeL method for easy and accurate discovery of kinase specificity motifs through the use of native bacterial proteomes that serve as in vivo libraries for thousands of simultaneous phosphorylation reactions. Using recombinant kinases expressed in E. coli followed by mass spectrometry, the approach accurately recapitulated the well-established motif preferences of human basophilic (Protein Kinase A) and acidophilic (Casein Kinase II) kinases. These motifs, derived for PKA and CK II using only bacterial sequence data, were then further validated by utilizing them in conjunction with the scan-x software program to computationally predict known human phosphorylation sites with high confidence.

CPhos: a program to calculate and visualize evolutionarily conserved functional phosphorylation sites

Profiling using high-throughput MS has discovered an overwhelming number of novel protein phosphorylation sites ("phosphosites"). However, the functional relevance of these sites is not always clear. In light of recent studies on the evolutionary mechanism of phosphorylation, we have developed CPhos, a Java program that can assess the conservation of phosphosites among species using an information theory-based approach. The degree of conservation established using CPhos can be used to assess the functional significance of phosphosites. CPhos has a user friendly graphical user interface and is available both as a web service and as a standalone Java application to assist phosphoproteomic researchers in analyzing and prioritizing lists of phosphosites for further experimental validation. CPhos can be accessed or downloaded at http://helixweb.nih.gov/CPhos/.

Prediction of lysine post-translational modifications using bioinformatic tools

Our understanding of the importance of lysine post-translational modifications in mediating protein function has led to a significant improvement in the experimental tools aimed at characterizing their existence. Nevertheless, it remains likely that at present we have only experimentally detected a small fraction of all lysine modification sites across the commonly studied proteomes. As a result, online computational tools aimed at predicting lysine modification sites have the potential to provide valuable insight to researchers developing hypotheses regarding these modifications. This chapter discusses the metrics and procedures used to assess predictive tools and surveys 11 online computational tools aimed at the prediction of the four most widely studied lysine post-translational modifications (acetylation, methylation, SUMOylation and ubiquitination). Analyses using unbiased testing data sets suggest that nine of the 11 lysine post-translational modification tools perform no better than random, or have false-positive rates which make them unusable by the experimental biologist, despite self-reported sensitivity and specificity values to the contrary. The implications of these findings for those using and creating lysine post-translational modification software are discussed.

S-nitrosylation inhibits pannexin 1 channel function

S-nitrosylation is a post-translational modification on cysteine(s) that can regulate protein function, and pannexin 1 (Panx1) channels are present in the vasculature, a tissue rich in nitric oxide (NO) species. Therefore, we investigated whether Panx1 can be S-nitrosylated and whether this modification can affect channel activity. Using the biotin switch assay, we found that application of the NO donor S-nitrosoglutathione (GSNO) or diethylammonium (Z)-1-1(N,N-diethylamino)diazen-1-ium-1,2-diolate (DEA NONOate) to human embryonic kidney (HEK) 293T cells expressing wild type (WT) Panx1 and mouse aortic endothelial cells induced Panx1 S-nitrosylation. Functionally, GSNO and DEA NONOate attenuated Panx1 currents; consistent with a role for S-nitrosylation, current inhibition was reversed by the reducing agent dithiothreitol and unaffected by 1H-[1,2,4]oxadiazolo[4,3-a]quinoxalin-1-one, a blocker of guanylate cyclase activity. In addition, ATP release was significantly inhibited by treatment with both NO donors. To identify which cysteine residue(s) was S-nitrosylated, we made single cysteine-to-alanine substitutions in Panx1 (Panx1(C40A), Panx1(C346A), and Panx1(C426A)). Mutation of these single cysteines did not prevent Panx1 S-nitrosylation; however, mutation of either Cys-40 or Cys-346 prevented Panx1 current inhibition and ATP release by GSNO. This observation suggested that multiple cysteines may be S-nitrosylated to regulate Panx1 channel function. Indeed, we found that mutation of both Cys-40 and Cys-346 (Panx1(C40A/C346A)) prevented Panx1 S-nitrosylation by GSNO as well as the GSNO-mediated inhibition of Panx1 current and ATP release. Taken together, these results indicate that S-nitrosylation of Panx1 at Cys-40 and Cys-346 inhibits Panx1 channel currents and ATP release.

Predicting and analyzing protein phosphorylation sites in plants using musite

Although protein phosphorylation sites can be reliably identified with high-resolution mass spectrometry, the experimental approach is time-consuming and resource-dependent. Furthermore, it is unlikely that an experimental approach could catalog an entire phosphoproteome. Computational prediction of phosphorylation sites provides an efficient and flexible way to reveal potential phosphorylation sites and provide hypotheses in experimental design. Musite is a tool that we previously developed to predict phosphorylation sites based solely on protein sequence. However, it was not comprehensively applied to plants. In this study, the phosphorylation data from Arabidopsis thaliana, B. napus, G. max, M. truncatula, O. sativa, and Z. mays were collected for cross-species testing and the overall plant-specific prediction as well. The results show that the model for A. thaliana can be extended to other organisms, and the overall plant model from Musite outperforms the current plant-specific prediction tools, Plantphos, and PhosphAt, in prediction accuracy. Furthermore, a comparative study of predicted phosphorylation sites across orthologs among different plants was conducted to reveal potential evolutionary features. A bipolar distribution of isolated, non-conserved phosphorylation sites, and highly conserved ones in terms of the amino acid type was observed. It also shows that predicted phosphorylation sites conserved within orthologs do not necessarily share more sequence similarity in the flanking regions than the background, but they often inherit protein disorder, a property that does not necessitate high sequence conservation. Our analysis also suggests that the phosphorylation frequencies among serine, threonine, and tyrosine correlate with their relative proportion in disordered regions. Musite can be used as a web server (http://musite.net) or downloaded as an open-source standalone tool (http://musite.sourceforge.net/).