Modification site localization scoring integrated into a search engine

O-GlcNAc informatics: advances and trends

As a post-translational modification, protein glycosylation is critical in health and disease. O-Linked β-N-acetylglucosamine (O-GlcNAc) modification (O-GlcNAcylation), as an intracellular monosaccharide modification on proteins, was discovered 40 years ago. Thanks to technological advances, the physiological and pathological significance of O-GlcNAcylation has been gradually revealed and widely appreciated, especially in recent years. O-GlcNAc informatics has been quickly evolving. Clearly, O-GlcNAc informatics tools have not only facilitated O-GlcNAc functional studies, but also provided us a unique perspective on protein O-GlcNAcylation. In this article, we review O-GlcNAc-focused software tools and servers that have been developed for O-GlcNAc research over the past four decades. Specifically, we will (1) survey bioinformatics tools that have facilitated O-GlcNAc proteomics data analysis, (2) introduce databases/servers for O-GlcNAc proteins/sites that have been experimentally identified by individual research labs, (3) describe software tools that have been developed to predict O-GlcNAc sites, and (4) introduce platforms cataloging proteins that interact with the O-GlcNAc cycling enzymes (i.e., O-GlcNAc transferase and O-GlcNAcase). We hope these resources will provide useful information to both experienced researchers and new incomers to the O-GlcNAc field. We anticipate that this review provides a framework to stimulate the future development of more sophisticated informatic tools for O-GlcNAc research.

GRable Version 1.0: A Software Tool for Site-Specific Glycoform Analysis With Improved MS1-Based Glycopeptide Detection With Parallel Clustering and Confidence Evaluation With MS2 Information

High-throughput intact glycopeptide analysis is crucial for elucidating the physiological and pathological status of the glycans attached to each glycoprotein. Mass spectrometry-based glycoproteomic methods are challenging because of the diversity and heterogeneity of glycan structures. Therefore, we developed an MS1-based site-specific glycoform analysis method named "Glycan heterogeneity-based Relational IDentification of Glycopeptide signals on Elution profile (Glyco-RIDGE)" for a more comprehensive analysis. This method detects glycopeptide signals as a cluster based on the mass and chromatographic properties of glycopeptides and then searches for each combination of core peptides and glycan compositions by matching their mass and retention time differences. Here, we developed a novel browser-based software named GRable for semi-automated Glyco-RIDGE analysis with significant improvements in glycopeptide detection algorithms, including "parallel clustering." This unique function improved the comprehensiveness of glycopeptide detection and allowed the analysis to focus on specific glycan structures, such as pauci-mannose. The other notable improvement is evaluating the "confidence level" of the GRable results, especially using MS2 information. This function facilitated reduced misassignment of the core peptide and glycan composition and improved the interpretation of the results. Additional improved points of the algorithms are "correction function" for accurate monoisotopic peak picking; one-to-one correspondence of clusters and core peptides even for multiply sialylated glycopeptides; and "inter-cluster analysis" function for understanding the reason for detected but unmatched clusters. The significance of these improvements was demonstrated using purified and crude glycoprotein samples, showing that GRable allowed site-specific glycoform analysis of intact sialylated glycoproteins on a large-scale and in-depth. Therefore, this software will help us analyze the status and changes in glycans to obtain biological and clinical insights into protein glycosylation by complementing the comprehensiveness of MS2-based glycoproteomics. GRable can be freely run online using a web browser via the GlyCosmos Portal (https://glycosmos.org/grable).

Computational approaches to identify sites of phosphorylation

Due to their oftentimes ambiguous nature, phosphopeptide positional isomers can present challenges in bottom-up mass spectrometry-based workflows as search engine scores alone are often not enough to confidently distinguish them. Additional scoring algorithms can remedy this by providing confidence metrics in addition to these search results, reducing ambiguity. Here we describe challenges to interpreting phosphoproteomics data and review several different approaches to determine sites of phosphorylation for both data-dependent and data-independent acquisition-based workflows. Finally, we discuss open questions regarding neutral losses, gas-phase rearrangement, and false localization rate estimation experienced by both types of acquisition workflows and best practices for managing ambiguity in phosphosite determination.

Deep Learning Prediction Boosts Phosphoproteomics-Based Discoveries Through Improved Phosphopeptide Identification

Shotgun phosphoproteomics enables high-throughput analysis of phosphopeptides in biological samples. One of the primary challenges associated with this technology is the relatively low rate of phosphopeptide identification during data analysis. This limitation hampers the full realization of the potential offered by shotgun phosphoproteomics. Here we present DeepRescore2, a computational workflow that leverages deep learning-based retention time and fragment ion intensity predictions to improve phosphopeptide identification and phosphosite localization. Using a state-of-the-art computational workflow as a benchmark, DeepRescore2 increases the number of correctly identified peptide-spectrum matches by 17% in a synthetic dataset and identifies 19% to 46% more phosphopeptides in biological datasets. In a liver cancer dataset, 30% of the significantly altered phosphosites between tumor and normal tissues and 60% of the prognosis-associated phosphosites identified from DeepRescore2-processed data could not be identified based on the state-of-the-art workflow. Notably, DeepRescore2-processed data uniquely identifies EGFR hyperactivation as a new target in poor-prognosis liver cancer, which is validated experimentally. Integration of deep learning prediction in DeepRescore2 improves phosphopeptide identification and facilitates biological discoveries.

Efficient Analysis of Proteome-Wide FPOP Data by FragPipe

Monitoring protein structure before and after environmental alterations (e.g., different cell states) can give insights into the role and function of proteins. Fast photochemical oxidation of proteins (FPOP) coupled with mass spectrometry (MS) allows for monitoring of structural rearrangements by exposing proteins to OH radicals that oxidize solvent-accessible residues, indicating protein regions undergoing movement. Some of the benefits of FPOP include high throughput and a lack of scrambling due to label irreversibility. However, the challenges of processing FPOP data have thus far limited its proteome-scale uses. Here, we present a computational workflow for fast and sensitive analysis of FPOP data sets. Our workflow, implemented as part of the FragPipe computational platform, combines the speed of the MSFragger search with a unique hybrid search method to restrict the large search space of FPOP modifications. Together, these features enable more than 10-fold faster FPOP searches that identify 150% more modified peptide spectra than previous methods. We hope this new workflow will increase the accessibility of FPOP to enable more protein structure and function relationships to be explored.

Glycopeptide database search and de novo sequencing with PEAKS GlycanFinder enable highly sensitive glycoproteomics

Here we present GlycanFinder, a database search and de novo sequencing tool for the analysis of intact glycopeptides from mass spectrometry data. GlycanFinder integrates peptide-based and glycan-based search strategies to address the challenge of complex fragmentation of glycopeptides. A deep learning model is designed to capture glycan tree structures and their fragment ions for de novo sequencing of glycans that do not exist in the database. We performed extensive analyses to validate the false discovery rates (FDRs) at both peptide and glycan levels and to evaluate GlycanFinder based on comprehensive benchmarks from previous community-based studies. Our results show that GlycanFinder achieved comparable performance to other leading glycoproteomics softwares in terms of both FDR control and the number of identifications. Moreover, GlycanFinder was also able to identify glycopeptides not found in existing databases. Finally, we conducted a mass spectrometry experiment for antibody N-linked glycosylation profiling that could distinguish isomeric peptides and glycans in four immunoglobulin G subclasses, which had been a challenging problem to previous studies.

Efficient Analysis of Proteome-wide FPOP Data by FragPipe

Monitoring protein structure before and after perturbations can give insights into the role and function of proteins. Fast photochemical oxidation of proteins (FPOP) coupled with mass spectrometry (MS) allows monitoring of structural rearrangements by exposing proteins to OH radicals that oxidize solvent accessible residues, indicating protein regions undergoing movement. Some of the benefits of FPOP include high throughput and lack of scrambling due to label irreversibility. However, the challenges of processing FPOP data have thus far limited its proteome-scale uses. Here, we present a computational workflow for fast and sensitive analysis of FPOP datasets. Our workflow combines the speed of MSFragger search with a unique hybrid search method to restrict the large search space of FPOP modifications. Together, these features enable more than 10-fold faster FPOP searches that identify 50% more modified peptide spectra than previous methods. We hope this new workflow will increase the accessibility of FPOP to enable more protein structure and function relationships to be explored.

The Ribosomal S6 Kinase 2 (RSK2)-SPRED2 complex regulates phosphorylation of RSK substrates and MAPK signaling

Sprouty-related EVH-1 domain-containing (SPRED) proteins are a family of proteins that negatively regulate the RAS-MAPK pathway, which is involved in the regulation of the mitogenic response and cell proliferation. However, the mechanism by which these proteins affect RAS-MAPK signaling has not been fully elucidated. Patients with mutations in SPRED give rise to unique disease phenotypes, thus we hypothesized that distinct interactions across SPRED proteins may account for alternative nodes of regulation. To characterize the SPRED interactome and evaluate how members of the SPRED family function through unique binding partners, here we performed affinity purification mass spectrometry. We identified 90-kDa ribosomal S6 kinase 2 (RSK2) as a specific interactor of SPRED2, but not SPRED1 or SPRED3. We identified that the N-terminal kinase domain of RSK2 mediates interaction between amino acids 123-201 of SPRED2. Using X-ray crystallography, we determined the structure of the SPRED2-RSK2 complex and identified the SPRED2 motif, F145A, as critical for interaction. Additionally, we found that formation of this interaction is regulated by MAPK signaling events. We also find that that this interaction between SPRED2 and RSK2 has functional consequences, whereby knockdown of SPRED2 resulted in increased phosphorylation of RSK substrates, YB1 and CREB. Furthermore, SPRED2 knockdown hindered phospho-RSK membrane and nuclear subcellular localization. Lastly, we report that disruption of the SPRED2-RSK complex has effects on RAS-MAPK signaling dynamics. Overall, our analysis reveals that members of the SPRED family have unique protein binding partners and describes the molecular and functional determinants of SPRED2-RSK2 complex dynamics.

DeepFLR facilitates false localization rate control in phosphoproteomics

Protein phosphorylation is a post-translational modification crucial for many cellular processes and protein functions. Accurate identification and quantification of protein phosphosites at the proteome-wide level are challenging, not least because efficient tools for protein phosphosite false localization rate (FLR) control are lacking. Here, we propose DeepFLR, a deep learning-based framework for controlling the FLR in phosphoproteomics. DeepFLR includes a phosphopeptide tandem mass spectrum (MS/MS) prediction module based on deep learning and an FLR assessment module based on a target-decoy approach. DeepFLR improves the accuracy of phosphopeptide MS/MS prediction compared to existing tools. Furthermore, DeepFLR estimates FLR accurately for both synthetic and biological datasets, and localizes more phosphosites than probability-based methods. DeepFLR is compatible with data from different organisms, instruments types, and both data-dependent and data-independent acquisition approaches, thus enabling FLR estimation for a broad range of phosphoproteomics experiments.

Principles of phosphoproteomics and applications in cancer research

Phosphorylation constitutes the most common and best-studied regulatory post-translational modification in biological systems and archetypal signalling pathways driven by protein and lipid kinases are disrupted in essentially all cancer types. Thus, the study of the phosphoproteome stands to provide unique biological information on signalling pathway activity and on kinase network circuitry that is not captured by genetic or transcriptomic technologies. Here, we discuss the methods and tools used in phosphoproteomics and highlight how this technique has been used, and can be used in the future, for cancer research. Challenges still exist in mass spectrometry phosphoproteomics and in the software required to provide biological information from these datasets. Nevertheless, improvements in mass spectrometers with enhanced scan rates, separation capabilities and sensitivity, in biochemical methods for sample preparation and in computational pipelines are enabling an increasingly deep analysis of the phosphoproteome, where previous bottlenecks in data acquisition, processing and interpretation are being relieved. These powerful hardware and algorithmic innovations are not only providing exciting new mechanistic insights into tumour biology, from where new drug targets may be derived, but are also leading to the discovery of phosphoproteins as mediators of drug sensitivity and resistance and as classifiers of disease subtypes. These studies are, therefore, uncovering phosphoproteins as a new generation of disruptive biomarkers to improve personalised anti-cancer therapies.

MS-based glycomics and glycoproteomics methods enabling isomeric characterization

Glycosylation is one of the most significant and abundant posttranslational modifications in mammalian cells. It mediates a wide range of biofunctions, including cell adhesion, cell communication, immune cell trafficking, and protein stability. Also, aberrant glycosylation has been associated with various diseases such as diabetes, Alzheimer's disease, inflammation, immune deficiencies, congenital disorders, and cancers. The alterations in the distributions of glycan and glycopeptide isomers are involved in the development and progression of several human diseases. However, the microheterogeneity of glycosylation brings a great challenge to glycomic and glycoproteomic analysis, including the characterization of isomers. Over several decades, different methods and approaches have been developed to facilitate the characterization of glycan and glycopeptide isomers. Mass spectrometry (MS) has been a powerful tool utilized for glycomic and glycoproteomic isomeric analysis due to its high sensitivity and rich structural information using different fragmentation techniques. However, a comprehensive characterization of glycan and glycopeptide isomers remains a challenge when utilizing MS alone. Therefore, various separation methods, including liquid chromatography, capillary electrophoresis, and ion mobility, were developed to resolve glycan and glycopeptide isomers before MS. These separation techniques were coupled to MS for a better identification and quantitation of glycan and glycopeptide isomers. Additionally, bioinformatic tools are essential for the automated processing of glycan and glycopeptide isomeric data to facilitate isomeric studies in biological cohorts. Here in this review, we discuss commonly employed MS-based techniques, separation hyphenated MS methods, and software, facilitating the separation, identification, and quantitation of glycan and glycopeptide isomers.

Deep learning prediction boosts phosphoproteomics-based discoveries through improved phosphopeptide identification

Shotgun phosphoproteomics enables high-throughput analysis of phosphopeptides in biological samples, but low phosphopeptide identification rate in data analysis limits the potential of this technology. Here we present DeepRescore2, a computational workflow that leverages deep learning-based retention time and fragment ion intensity predictions to improve phosphopeptide identification and phosphosite localization. Using a state-of-the-art computational workflow as a benchmark, DeepRescore2 increases the number of correctly identified peptide-spectrum matches by 17% in a synthetic dataset and identifies 19%-46% more phosphopeptides in biological datasets. In a liver cancer dataset, 30% of the significantly altered phosphosites between tumor and normal tissues and 60% of the prognosis-associated phosphosites identified from DeepRescore2-processed data could not be identified based on the state-of-the-art workflow. Notably, DeepRescore2-processed data uniquely identifies EGFR hyperactivation as a new target in poor-prognosis liver cancer, which is validated experimentally. Integration of deep learning prediction in DeepRescore2 improves phosphopeptide identification and facilitates biological discoveries.

Multiple Layers of Complexity in O-Glycosylation Illustrated With the Urinary Glycoproteome

While N-glycopeptides are relatively easy to characterize, O-glycosylation analysis is more complex. In this article, we illustrate the multiple layers of O-glycopeptide characterization that make this task so challenging. We believe our carefully curated dataset represents perhaps the largest intact human glycopeptide mixture derived from individuals, not from cell lines. The samples were collected from healthy individuals, patients with superficial or advanced bladder cancer (three of each group), and a single bladder inflammation patient. The data were scrutinized manually and interpreted using three different search engines: Byonic, Protein Prospector, and O-Pair, and the tool MS-Filter. Despite all the recent advances, reliable automatic O-glycopeptide assignment has not been solved yet. Our data reveal such diversity of site-specific O-glycosylation that has not been presented before. In addition to the potential biological implications, this dataset should be a valuable resource for software developers in the same way as some of our previously released data has been used in the development of O-Pair and O-Glycoproteome Analyzer. Based on the manual evaluation of the performance of the existing tools with our data, we lined up a series of recommendations that if implemented could significantly improve the reliability of glycopeptide assignments.

A field guide to the proteomics of post-translational modifications in DNA repair

All cells incur DNA damage from exogenous and endogenous sources and possess pathways to detect and repair DNA damage. Post-translational modifications (PTMs), in the past 20 years, have risen to ineluctable importance in the study of the regulation of DNA repair mechanisms. For example, DNA damage response kinases are critical in both the initial sensing of DNA damage as well as in orchestrating downstream activities of DNA repair factors. Mass spectrometry-based proteomics revolutionized the study of the role of PTMs in the DNA damage response and has canonized PTMs as central modulators of nearly all aspects of DNA damage signaling and repair. This review provides a biologist-friendly guide for the mass spectrometry analysis of PTMs in the context of DNA repair and DNA damage responses. We reflect on the current state of proteomics for exploring new mechanisms of PTM-based regulation and outline a roadmap for designing PTM mapping experiments that focus on the DNA repair and DNA damage responses.

Transthyretin proteoforms of intraocular origin in human subretinal fluid

Understanding the molecular composition of ocular tissues and fluids could inform new approaches to prevalent causes of blindness. Subretinal fluid accumulating between the photoreceptor outer segments and retinal pigment epithelium (RPE) is potentially a rich source of proteins and lipids normally cycling among outer retinal cells and choroid. Herein, intact post-translationally modified proteins (proteoforms) were extracted from subretinal fluids of five patients with rhegmatogenous retinal detachment (RRD), analyzed by tandem mass spectrometry, and compared to published data on these same proteins as synthesized by other organs. Single-nuclei transcriptomic data from non-diseased human retina/RPE were used to identify whether proteins in subretinal fluid were of potential ocular origin. Two human donor eyes with normal maculas were immunoprobed for transthyretin (TTR) with appropriate controls. The three most abundant proteins detected in subretinal fluid were albumin, TTR, and apolipoprotein A-I. Remarkably, TTR relative to the other proteins was more abundant than its serum counterpart, suggestive of TTR being synthesized predominantly locally. Six post-translationally modified protein forms (proteoforms) of TTR were detected, with the relative amount of glutathionylated TTR being much higher in the subretinal fluid (12-43%) than values reported for serum (<5%) and cerebrospinal fluid (0.4-13%). Moreover, a putative glycosylated TTR dimer of 32,428 Da was detected as the fourth most abundant protein. The high abundance of TTR and putative TTR dimer in subretinal fluid was supported by analysis of available single-nuclei transcriptomic data, which showed strong and specific signal for TTR in RPE. Immunohistochemistry further showed strong diffuse TTR immunoreactivity in choroidal stroma that contrasted with vertically aligned signal in the outer segment zone of the subretinal space and negligible signal in RPE cell bodies. These results suggest that TTR in the retina is synthesized intraocularly, and glutathionylation is crucial for its normal function. Further studies on the composition, function, and quantities of TTR and other proteoforms in subretinal fluid could inform mechanisms, diagnostic methods, and treatment strategies for age-related macular degeneration, familial amyloidosis, and other retinal diseases involving dysregulation of physiologic lipid transfer and oxidative stress.

Method for Independent Estimation of the False Localization Rate for Phosphoproteomics

Phosphoproteomic methods are commonly employed to identify and quantify phosphorylation sites on proteins. In recent years, various tools have been developed, incorporating scores or statistics related to whether a given phosphosite has been correctly identified or to estimate the global false localization rate (FLR) within a given data set for all sites reported. These scores have generally been calibrated using synthetic datasets, and their statistical reliability on real datasets is largely unknown, potentially leading to studies reporting incorrectly localized phosphosites, due to inadequate statistical control. In this work, we develop the concept of scoring modifications on a decoy amino acid, that is, one that cannot be modified, to allow for independent estimation of global FLR. We test a variety of amino acids, on both synthetic and real data sets, demonstrating that the selection can make a substantial difference to the estimated global FLR. We conclude that while several different amino acids might be appropriate, the most reliable FLR results were achieved using alanine and leucine as decoys. We propose the use of a decoy amino acid to control false reporting in the literature and in public databases that re-distribute the data. Data are available via ProteomeXchange with identifier PXD028840.

Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.

Strategies for mass spectrometry-based phosphoproteomics using isobaric tagging

INTRODUCTION

Protein phosphorylation is a primary mechanism of signal transduction in cellular systems. Isobaric tagging can be used to investigate alterations in phosphorylation events in sample multiplexing experiments where quantification extends across all conditions. As such, innovations in tandem mass tag methods can facilitate the expansion of the depth and breadth of phosphoproteomic analyses.

AREAS COVERED

This review discusses the current state of tandem mass tag-centric phosphoproteomics and highlights advances in reagent chemistry, instrumentation, data acquisition, and data analysis. We stress that approaches for phosphoproteomic investigations require high-specificity enrichment, sensitive detection, and accurate phosphorylation site localization.

EXPERT OPINION

Tandem mass tag-centric phosphoproteomics will continue to be an important conduit for our understanding of signal transduction in living organisms. We anticipate that progress in phosphopeptide enrichment methodologies, enhancements in instrumentation and data acquisition technologies, and further refinements in analytical strategies will be key to the discovery of biologically relevant findings from phosphoproteomics studies.

The Hitchhiker's guide to glycoproteomics

Protein glycosylation is one of the most common post-translational modifications that are essential for cell function across all domains of life. Changes in glycosylation are considered a hallmark of many diseases, thus making glycoproteins important diagnostic and prognostic biomarker candidates and therapeutic targets. Glycoproteomics, the study of glycans and their carrier proteins in a system-wide context, is becoming a powerful tool in glycobiology that enables the functional analysis of protein glycosylation. This 'Hitchhiker's guide to glycoproteomics' is intended as a starting point for anyone who wants to explore the emerging world of glycoproteomics. The review moves from the techniques that have been developed for the characterisation of single glycoproteins to technologies that may be used for a successful complex glycoproteome characterisation. Examples of the variety of approaches, methodologies, and technologies currently used in the field are given. This review introduces the common strategies to capture glycoprotein-specific and system-wide glycoproteome data from tissues, body fluids, or cells, and a perspective on how integration into a multi-omics workflow enables a deep identification and characterisation of glycoproteins - a class of biomolecules essential in regulating cell function.

Characterization of an A3G-VifHIV-1-CRL5-CBFβ Structure Using a Cross-linking Mass Spectrometry Pipeline for Integrative Modeling of Host-Pathogen Complexes

Structural analysis of host-pathogen protein complexes remains challenging, largely due to their structural heterogeneity. Here, we describe a pipeline for the structural characterization of these complexes using integrative structure modeling based on chemical cross-links and residue-protein contacts inferred from mutagenesis studies. We used this approach on the HIV-1 Vif protein bound to restriction factor APOBEC3G (A3G), the Cullin-5 E3 ring ligase (CRL5), and the cellular transcription factor Core Binding Factor Beta (CBFβ) to determine the structure of the (A3G-Vif-CRL5-CBFβ) complex. Using the MS-cleavable DSSO cross-linker to obtain a set of 132 cross-links within this reconstituted complex along with the atomic structures of the subunits and mutagenesis data, we computed an integrative structure model of the heptameric A3G-Vif-CRL5-CBFβ complex. The structure, which was validated using a series of tests, reveals that A3G is bound to Vif mostly through its N-terminal domain. Moreover, the model ensemble quantifies the dynamic heterogeneity of the A3G C-terminal domain and Cul5 positions. Finally, the model was used to rationalize previous structural, mutagenesis and functional data not used for modeling, including information related to the A3G-bound and unbound structures as well as mapping functional mutations to the A3G-Vif interface. The experimental and computational approach described here is generally applicable to other challenging host-pathogen protein complexes.

The RAS GTPase RIT1 compromises mitotic fidelity through spindle assembly checkpoint suppression

The spindle assembly checkpoint (SAC) functions as a sensor of unattached kinetochores that delays mitotic progression into anaphase until proper chromosome segregation is guaranteed.^1,2 Disruptions to this safety mechanism lead to genomic instability and aneuploidy, which serve as the genetic cause of embryonic demise, congenital birth defects, intellectual disability, and cancer.^3,4 However, despite the understanding of the fundamental mechanisms that control the SAC, it remains unknown how signaling pathways directly interact with and regulate the mitotic checkpoint activity. In response to extracellular stimuli, a diverse network of signaling pathways involved in cell growth, survival, and differentiation are activated, and this process is prominently regulated by the Ras family of small guanosine triphosphatases (GTPases).⁵ Here we show that RIT1, a Ras-related GTPase that regulates cell survival and stress response,⁶ is essential for timely progression through mitosis and proper chromosome segregation. RIT1 dissociates from the plasma membrane (PM) during mitosis and interacts directly with SAC proteins MAD2 and p31^comet in a process that is regulated by cyclin-dependent kinase 1 (CDK1) activity. Furthermore, pathogenic levels of RIT1 silence the SAC and accelerate transit through mitosis by sequestering MAD2 from the mitotic checkpoint complex (MCC). Moreover, SAC suppression by pathogenic RIT1 promotes chromosome segregation errors and aneuploidy. Our results highlight a unique function of RIT1 compared to other Ras GTPases and elucidate a direct link between a signaling pathway and the SAC through a novel regulatory mechanism.

Advances in quantitative high-throughput phosphoproteomics with sample multiplexing

Eukaryotic protein phosphorylation modulates nearly every major biological process. Phosphorylation regulates protein activity, mediates cellular signal transduction, and manipulates cellular structure. Consequently, the dysregulation of kinase and phosphatase pathways has been linked to a multitude of diseases. Mass spectrometry-based proteomic techniques are increasingly used for the global interrogation of perturbations in phosphorylation-based cellular signaling. Strategies for studying phosphoproteomes require high-specificity enrichment, sensitive detection, and accurate localization of phosphorylation sites with advanced LC-MS/MS techniques and downstream informatics. Sample multiplexing with isobaric tags has also been integral to recent advancements in throughput and sensitivity for phosphoproteomic studies. Each of these facets of phosphoproteomics analysis present distinct challenges and thus opportunities for improvement and innovation. Here, we review current methodologies, explore persistent challenges, and discuss the outlook for isobaric tag-based quantitative phosphoproteomic analysis.

Methods for Enrichment and Assignment of N-Acetylglucosamine Modification Sites

O-GlcNAcylation, the addition of a single N-acetylglucosamine residue to serine and threonine residues of cytoplasmic, nuclear, or mitochondrial proteins, is a widespread regulatory posttranslational modification. It is involved in the response to nutritional status and stress, and its dysregulation is associated with diseases ranging from Alzheimer's to diabetes. Although the modification was first detected over 35 years ago, research into the function of O-GlcNAcylation has accelerated dramatically in the last 10 years owing to the development of new enrichment and mass spectrometry techniques that facilitate its analysis. This article summarizes methods for O-GlcNAc enrichment, key mass spectrometry instrumentation advancements, particularly those that allow modification site localization, and software tools that allow analysis of data from O-GlcNAc-modified peptides.

Recent Advances in Software Tools for More Generic and Precise Intact Glycopeptide Analysis

Intact glycopeptide identification has long been known as a key and challenging barrier to the comprehensive and accurate understanding the role of glycosylation in an organism. Intact glycopeptide analysis is a blossoming field that has received increasing attention in recent years. MS-based strategies and relative software tools are major drivers that have greatly facilitated the analysis of intact glycopeptides, particularly intact N-glycopeptides. This article provides a systematic review of the intact glycopeptide-identification process using MS data generated in shotgun proteomic experiments, which typically focus on N-glycopeptide analysis. Particular attention is paid to the software tools that have been recently developed in the last decade for the interpretation and quality control of glycopeptide spectra acquired using different MS strategies. The review also provides information about the characteristics and applications of these software tools, discusses their advantages and disadvantages, and concludes with a discussion of outstanding tools.

Precise, fast and comprehensive analysis of intact glycopeptides and modified glycans with pGlyco3

Great advances have been made in mass spectrometric data interpretation for intact glycopeptide analysis. However, accurate identification of intact glycopeptides and modified saccharide units at the site-specific level and with fast speed remains challenging. Here, we present a glycan-first glycopeptide search engine, pGlyco3, to comprehensively analyze intact N- and O-glycopeptides, including glycopeptides with modified saccharide units. A glycan ion-indexing algorithm developed for glycan-first search makes pGlyco3 5-40 times faster than other glycoproteomic search engines without decreasing accuracy or sensitivity. By combining electron-based dissociation spectra, pGlyco3 integrates a dynamic programming-based algorithm termed pGlycoSite for site-specific glycan localization. Our evaluation shows that the site-specific glycan localization probabilities estimated by pGlycoSite are suitable to localize site-specific glycans. With pGlyco3, we confidently identified N-glycopeptides and O-mannose glycopeptides that were extensively modified by ammonia adducts in yeast samples. The freely available pGlyco3 is an accurate and flexible tool that can be used to identify glycopeptides and modified saccharide units.

Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.

O-Pair Search with MetaMorpheus for O-glycopeptide characterization

We report O-Pair Search, an approach to identify O-glycopeptides and localize O-glycosites. Using paired collision- and electron-based dissociation spectra, O-Pair Search identifies O-glycopeptides via an ion-indexed open modification search and localizes O-glycosites using graph theory and probability-based localization. O-Pair Search reduces search times more than 2,000-fold compared to current O-glycopeptide processing software, while defining O-glycosite localization confidence levels and generating more O-glycopeptide identifications. Beyond the mucin-type O-glycopeptides discussed here, O-Pair Search also accepts user-defined glycan databases, making it compatible with many types of O-glycosylation. O-Pair Search is freely available within the open-source MetaMorpheus platform at https://github.com/smith-chem-wisc/MetaMorpheus .

O-Pair Search with MetaMorpheus for O-glycopeptide characterization

We report O-Pair Search, a new approach to identify O-glycopeptides and localize O-glycosites. Using paired collision- and electron-based dissociation spectra, O-Pair Search identifies O-glycopeptides using an ion-indexed open modification search and localizes O-glycosites using graph theory and probability-based localization. O-Pair Search reduces search times more than 2,000-fold compared to current O-glycopeptide processing software, while defining O-glycosite localization confidence levels and generating more O-glycopeptide identifications. Beyond the mucin-type O-glycopeptides discussed here, O-Pair Search also accepts user-defined glycan databases, making it compatible with many types of O-glycosylation. O-Pair Search is freely available within the open-source MetaMorpheus platform at https://github.com/smith-chem-wisc/MetaMorpheus.

The influence of proline isomerization on potency and stability of anti-HIV antibody 10E8

Monoclonal antibody (mAb) 10E8 recognizes a highly conserved epitope on HIV and is capable of neutralizing > 95% of circulating viral isolates making it one of the most promising Abs against HIV. Solution instability and biochemical heterogeneity of 10E8 has hampered its development for clinical use. We identify the source of 10E8 heterogeneity being linked to cis/trans isomerization at two prolines within the YPP motif in the CRD3 loop that exists as two predominant conformers that interconvert on a slow timescale. The Y_transP conformation conformer can bind the HIV gp41 epitope, while the Y_cisP is not binding competent and shows a higher aggregation propensity. The high barrier of isomerization and propensity to adopt non-binding competent proline conformers provides novel insight into the slow binding kinetics, low potency, and poor solubility of 10E8. This study highlights how proline isomerization should be considered a critical quality attribute for biotherapeutics with paratopes containing potential cis proline amide bonds.

Novel O-linked sialoglycan structures in human urinary glycoproteins

Glycopeptides represent cross-linked structures between chemically and physically different biomolecules. Mass spectrometric analysis of O-glycopeptides may reveal the identity of the peptide, the composition of the glycan and even the connection between certain sugar units, but usually only the combination of different MS/MS techniques provides sufficient information for reliable assignment. Currently, HCD analysis followed by diagnostic sugar fragment-triggered ETD or EThcD experiments is the most promising data acquisition protocol. However, the information content of the different MS/MS data is handled separately by search engines. We are convinced that these data should be used in concert, as we demonstrate in the present study. First, glycopeptides bearing the most common glycans can be identified from EThcD and/or HCD data. Then, searching for Y₀ (the gas-phase deglycosylated peptide) in HCD spectra, the potential glycoforms of these glycopeptides could be lined up. Finally, these spectra and the corresponding EThcD data can be used to verify or discard the tentative assignments and to obtain further structural information about the glycans. We present 18 novel human urinary sialoglycan structures deciphered using this approach. To accomplish this in an automated fashion further software development is necessary.

PTMProphet: Fast and Accurate Mass Modification Localization for the Trans-Proteomic Pipeline

Spectral matching sequence database search engines commonly used on mass spectrometry-based proteomics experiments excel at identifying peptide sequence ions, and in addition, possible sequence ions carrying post-translational modifications (PTMs), but most do not provide confidence metrics for the exact localization of those PTMs when several possible sites are available. Localization is absolutely required for downstream molecular cell biology analysis of PTM function in vitro and in vivo. Therefore, we developed PTMProphet, a free and open-source software tool integrated into the Trans-Proteomic Pipeline, which reanalyzes identified spectra from any search engine for which pepXML output is available to provide localization confidence to enable appropriate further characterization of biologic events. Localization of any type of mass modification (e.g., phosphorylation) is supported. PTMProphet applies Bayesian mixture models to compute probabilities for each site/peptide spectrum match where a PTM has been identified. These probabilities can be combined to compute a global false localization rate at any threshold to guide downstream analysis. We describe the PTMProphet tool, its underlying algorithms, and demonstrate its performance on ground-truth synthetic peptide reference data sets, one previously published small data set, one new larger data set, and also on a previously published phosphoenriched data set where the correct sites of modification are unknown. Data have been deposited to ProteomeXchange with identifier PXD013210.

The mitogen-activated protein kinase 4-phosphorylated heat shock factor A4A regulates responses to combined salt and heat stresses

Heat shock factors regulate responses to high temperature, salinity, water deprivation, or heavy metals. Their function in combinations of stresses is, however, not known. Arabidopsis HEAT SHOCK FACTOR A4A (HSFA4A) was previously reported to regulate responses to salt and oxidative stresses. Here we show, that the HSFA4A gene is induced by salt, elevated temperature, and a combination of these conditions. Fast translocation of HSFA4A tagged with yellow fluorescent protein from cytosol to nuclei takes place in salt-treated cells. HSFA4A can be phosphorylated not only by mitogen-activated protein (MAP) kinases MPK3 and MPK6 but also by MPK4, and Ser309 is the dominant MAP kinase phosphorylation site. In vivo data suggest that HSFA4A can be the substrate of other kinases as well. Changing Ser309 to Asp or Ala alters intramolecular multimerization. Chromatin immunoprecipitation assays confirmed binding of HSFA4A to promoters of target genes encoding the small heat shock protein HSP17.6A and transcription factors WRKY30 and ZAT12. HSFA4A overexpression enhanced tolerance to individually and simultaneously applied heat and salt stresses through reduction of oxidative damage. Our results suggest that this heat shock factor is a component of a complex stress regulatory pathway, connecting upstream signals mediated by MAP kinases MPK3/6 and MPK4 with transcription regulation of a set of stress-induced target genes.

Mapping Post-Translational Modifications of de Novo Purine Biosynthetic Enzymes: Implications for Pathway Regulation

Purines represent a class of essential metabolites produced by the cell to maintain cellular homeostasis and facilitate cell proliferation. In times of high purine demand, the de novo purine biosynthetic pathway is activated; however, the mechanisms that facilitate this process are largely unknown. One plausible mechanism is through intracellular signaling, which results in enzymes within the pathway becoming post-translationally modified to enhance their individual enzyme activities and the overall pathway metabolic flux. Here, we employ a proteomic strategy to investigate the extent to which de novo purine biosynthetic pathway enzymes are post-translationally modified in 293T cells. We identified 7 post-translational modifications on 135 residues across the 6 human pathway enzymes. We further asked whether there were differences in the post-translational modification state of each pathway enzyme isolated from cells cultured in the presence or absence of purines. Of the 174 assigned modifications, 67% of them were only detected in one experimental growth condition in which a significant number of serine and threonine phosphorylations were noted. A survey of the most-probable kinases responsible for these phosphorylation events uncovered a likely AKT phosphorylation site at residue Thr397 of PPAT, which was only detected in cells under purine-supplemented growth conditions. These data suggest that this modification might alter enzyme activity or modulate its interaction(s) with downstream pathway enzymes. Together, these findings propose a role for post-translational modifications in pathway regulation and activation to meet intracellular purine demand.

PTMiner: Localization and Quality Control of Protein Modifications Detected in an Open Search and Its Application to Comprehensive Post-translational Modification Characterization in Human Proteome

The open (mass tolerant) search of tandem mass spectra of peptides shows great potential in the comprehensive detection of post-translational modifications (PTMs) in shotgun proteomics. However, this search strategy has not been widely used by the community, and one bottleneck of it is the lack of appropriate algorithms for automated and reliable post-processing of the coarse and error-prone search results. Here we present PTMiner, a software tool for confident filtering and localization of modifications (mass shifts) detected in an open search. After mass-shift-grouped false discovery rate (FDR) control of peptide-spectrum matches (PSMs), PTMiner uses an empirical Bayesian method to localize modifications through iterative learning of the prior probabilities of each type of modification occurring on different amino acids. The performance of PTMiner was evaluated on three data sets, including simulated data, chemically synthesized peptide library data and modified-peptide spiked-in proteome data. The results showed that PTMiner can effectively control the PSM FDR and accurately localize the modification sites. At 1% real false localization rate (FLR), PTMiner localized 93%, 84 and 83% of the modification sites in the three data sets, respectively, far higher than two open search engines we used and an extended version of the Ascore localization algorithm. We then used PTMiner to analyze a draft map of human proteome containing 25 million spectra from 30 tissues, and confidently identified over 1.7 million modified PSMs at 1% FDR and 1% FLR, which provided a system-wide view of both known and unknown PTMs in the human proteome.

Detection of Phytochrome Phosphorylation in Plants

Posttranslational modification (PTM) of proteins occurs during or after translation and in most cases means covalent binding of a functional group to certain amino acid side chains. Among PTMs, phosphorylation is extensively studied for decades. During phosphorylation, a phosphate group is added to the target residue that is dominantly serine, threonine, and tyrosine in eukaryotes. The phosphate group attachment is catalyzed by kinases, whereas the removal of phosphate (dephosphorylation) is performed by phosphatases. Phosphorylation of phytochrome photoreceptors alters light signaling in multiple ways, thus the examination of this PTM is an expanding aspect of light signaling research. Although this chapter presents methods for detecting phosphorylated phytochrome B molecules, it can be applied on other phytochrome species. The first presented protocol of this chapter shows how the phosphorylation state of phytochrome photoreceptors can be monitored in a modified polyacrylamide gel electrophoresis system. The second protocol describes in detail how phosphorylated amino acids of a target molecule can be identified using mass spectrometry analysis.

Clinically Relevant Post-Translational Modification Analyses-Maturing Workflows and Bioinformatics Tools

Post-translational modifications (PTMs) can occur soon after translation or at any stage in the lifecycle of a given protein, and they may help regulate protein folding, stability, cellular localisation, activity, or the interactions proteins have with other proteins or biomolecular species. PTMs are crucial to our functional understanding of biology, and new quantitative mass spectrometry (MS) and bioinformatics workflows are maturing both in labelled multiplexed and label-free techniques, offering increasing coverage and new opportunities to study human health and disease. Techniques such as Data Independent Acquisition (DIA) are emerging as promising approaches due to their re-mining capability. Many bioinformatics tools have been developed to support the analysis of PTMs by mass spectrometry, from prediction and identifying PTM site assignment, open searches enabling better mining of unassigned mass spectra-many of which likely harbour PTMs-through to understanding PTM associations and interactions. The remaining challenge lies in extracting functional information from clinically relevant PTM studies. This review focuses on canvassing the options and progress of PTM analysis for large quantitative studies, from choosing the platform, through to data analysis, with an emphasis on clinically relevant samples such as plasma and other body fluids, and well-established tools and options for data interpretation.

Extended Sialylated O-Glycan Repertoire of Human Urinary Glycoproteins Discovered and Characterized Using Electron-Transfer/Higher-Energy Collision Dissociation

A relatively novel activation technique, electron-transfer/higher-energy collision dissociation (EThcD) was used in the LC-MS/MS analysis of tryptic glycopeptides enriched with wheat germ agglutinin from human urine samples. We focused on the characterization of mucin-type O-glycopeptides. EThcD in a single spectrum provided information on both the peptide modified and the glycan carried. Unexpectedly, glycan oxonium ions indicated the presence of O-acetyl, and even O-diacetyl-sialic acids. B and Y fragment ions revealed that (i) in core 1 structures the Gal residue featured the O-acetyl-sialic acid, when there was only one in the glycan; (ii) several glycopeptides featured core 1 glycans with disialic acids, in certain instances O-acetylated; (iii) the disialic acid was linked to the GalNAc residue whatever the degree of O-acetylation; (iv) core 2 isomers with a single O-acetyl-sialic acid were chromatographically resolved. Glycan fragmentation also helped to decipher additional core 2 oligosaccharides: a LacdiNAc-like structure, glycans carrying sialyl Lewis^X/A at different stages of O-acetylation, and blood antigens. A sialo core 3 structure was also identified. We believe this is the first study when such structures were characterized from a very complex mixture and were linked not only to a specific protein, but also the sites of modifications have been determined.

Status Report on the High-Throughput Characterization of Complex Intact O-Glycopeptide Mixtures

A very complex mixture of intact, human N- and O-glycopeptides, enriched from the tryptic digest of urinary proteins of three healthy donors using a two-step lectin affinity enrichment, was analyzed by LC-MS/MS, leading to approximately 45,000 glycopeptide EThcD spectra. Two search engines, Byonic and Protein Prospector, were used for the interpretation of the data, and N- and O-linked glycopeptides were assigned from separate searches. The identification rate was very low in all searches, even when results were combined. Thus, we investigated the reasons why was it so, to help to improve the identification success rate. Focusing on O-linked glycopeptides, we noticed that in EThcD, larger glycan oxonium ions better survive the activation than those in HCD. These fragments, combined with reducing terminal Y ions, provide important information about the glycan(s) present, so we investigated whether filtering the peaklists for glycan oxonium ions indicating the presence of a tetra- or hexasaccharide structure would help to reveal all molecules containing such glycans. Our study showed that intact glycans frequently do not survive even mild supplemental activation, meaning one cannot rely on these oxonium ions exclusively. We found that ETD efficiency is still a limiting factor, and for highly glycosylated peptides, the only information revealed in EThcD was related to the glycan structures. The limited overlap of results delivered by the two search engines draws attention to the fact that automated data interpretation of O-linked glycopeptides is not even close to being solved. Graphical abstract ᅟ.

Large-scale intact glycopeptide identification by Mascot database search

Workflows capable of determining glycopeptides in large-scale are missing in the field of glycoproteomics. We present an approach for automated annotation of intact glycopeptide mass spectra. The steps in adopting the Mascot search engine for intact glycopeptide analysis included: (i) assigning one letter codes for monosaccharides, (ii) linearizing glycan sequences and (iii) preparing custom glycoprotein databases. Automated annotation of both N- and O-linked glycopeptides was proven using standard glycoproteins. In a large-scale study, a total of 257 glycoproteins containing 970 unique glycosylation sites and 3447 non-redundant N-linked glycopeptide variants were identified in 24 serum samples. Thus, a single tool was developed that collectively allows the (i) elucidation of N- and O-linked glycopeptide spectra, (ii) matching glycopeptides to known protein sequences, and (iii) high-throughput, batch-wise analysis of large-scale glycoproteomics data sets.

Coevolving MAPK and PID phosphosites indicate an ancient environmental control of PIN auxin transporters in land plants

Plant growth flexibly adapts to environmental conditions, implying cross-talk between environmental signalling and developmental regulation. Here, we show that the PIN auxin efflux carrier family possesses three highly conserved putative mitogen-activated protein kinase (MAPK) sites adjacent to the phosphorylation sites of the well-characterised AGC kinase PINOID, which regulates the polar localisation of PINs and directional auxin transport, thereby underpinning organ growth. The conserved sites of PIN1 are phosphorylated in vitro by two environmentally activated MAPKs, MPK4 and MPK6. In contrast to AGC kinases, MAPK-mediated phosphorylation of PIN1 at adjacent sites leads to a partial loss of the plasma membrane localisation of PIN1. MAPK-mediated modulation of PIN trafficking may participate in environmental adjustment of plant growth.

Analysis of Mammalian O-Glycopeptides-We Have Made a Good Start, but There is a Long Way to Go

Glycosylation is perhaps the most common post-translational modification. Recently there has been growing interest in cataloging the glycan structures, glycoproteins, and specific sites modified and deciphering the biological functions of glycosylation. Although the results are piling up for N-glycosylation, O-glycosylation is seriously trailing behind. In our review we reiterate the difficulties researchers have to overcome in order to characterize O-glycosylation. We describe how an ingenious cell engineering method delivered exciting results, and what could we gain from "wild-type" samples. Although we refer to the biological role(s) of O-glycosylation, we do not provide a complete inventory on this topic.

Accurate phosphorylation site localization using phospho-brackets

Phosphorylation is one of the most important and widely studied protein post-translational modifications. Tandem mass spectrometry using higher-energy collisional dissociation has evolved into a state-of-the-art analytical platform for both phosphorylation identification and site localization. Tens of thousands of phosphopeptides can now be routinely identified from a single shotgun proteomics study; site localization, however, is much more complicated and many challenges still exist. Here, we report our development of P-bracket using direct experimental evidence of phospho-containing site-determining product ions for accurate site localization without the need for additional FLR control. A P-bracket is defined as a complementary product ion pair that forms a bracket to confine a phosphorylation event to a unique site. P-bracket has been successfully benchmarked with a set of six synthetic phosphopeptides with a single phosphorylation event, a set of 96 synthetic peptides and phosphopeptide reference libraries, and two HeLa phosphopeptide LC-MS/MS (HCD) datasets; Accurate phosphosite localization by P-bracket will greatly enhance identification confidence of phosphopeptides and contribute to structural and functional studies of phosphoproteins.

Phosphoproteomics-Based Profiling of Kinase Activities in Cancer Cells

Cellular signaling, predominantly mediated by phosphorylation through protein kinases, is found to be deregulated in most cancers. Accordingly, protein kinases have been subject to intense investigations in cancer research, to understand their role in oncogenesis and to discover new therapeutic targets. Despite great advances, an understanding of kinase dysfunction in cancer is far from complete.A powerful tool to investigate phosphorylation is mass-spectrometry (MS)-based phosphoproteomics, which enables the identification of thousands of phosphorylated peptides in a single experiment. Since every phosphorylation event results from the activity of a protein kinase, high-coverage phosphoproteomics data should indirectly contain comprehensive information about the activity of protein kinases.In this chapter, we discuss the use of computational methods to predict kinase activity scores from MS-based phosphoproteomics data. We start with a short explanation of the fundamental features of the phosphoproteomics data acquisition process from the perspective of the computational analysis. Next, we briefly review the existing databases with experimentally verified kinase-substrate relationships and present a set of bioinformatic tools to discover novel kinase targets. We then introduce different methods to infer kinase activities from phosphoproteomics data and these kinase-substrate relationships. We illustrate their application with a detailed protocol of one of the methods, KSEA (Kinase Substrate Enrichment Analysis). This method is implemented in Python within the framework of the open-source Kinase Activity Toolbox (kinact), which is freely available at http://github.com/saezlab/kinact/ .

Myosin phosphatase and RhoA-activated kinase modulate neurotransmitter release by regulating SNAP-25 of SNARE complex

Reversible phosphorylation of neuronal proteins plays an important role in the regulation of neurotransmitter release. Myosin phosphatase holoenzyme (MP) consists of a protein phosphatase-1 (PP1) catalytic subunit (PP1c) and a regulatory subunit, termed myosin phosphatase targeting subunit (MYPT1). The primary function of MP is to regulate the phosphorylation level of contractile proteins; however, recent studies have shown that MP is localized to neurons, and is also involved in the mediation of neuronal processes. Our goal was to investigate the effect of RhoA-activated kinase (ROK) and MP on the phosphorylation of one potential neuronal substrate, the synaptosomal-associated protein of 25 kDa (SNAP-25). SNAP-25 is a member of the SNARE (soluble N-ethylmaleimide sensitive factor attachment protein receptor) complex, along with synaptobrevin and syntaxin, and the primary role of SNAP25 is to mediate vesicle fusion. We showed that MYPT1 interacts with SNAP-25, as revealed by immunoprecipitation and surface plasmon resonance based binding studies. Mass spectrometry analysis and in vitro phosphorylation/dephosphorylation assays demonstrated that ROK phosphorylates, while MP dephosphorylates, SNAP-25 at Thr138. Silencing MYPT1 in B50 neuroblastoma cells increased phosphorylation of SNAP-25 at Thr138. Inhibition of PP1 with tautomycetin increased, whereas inhibition of ROK by H1152, decreased the phosphorylation of SNAP-25 at Thr138 in B50 cells, in cortical synaptosomes, and in brain slices. In response to the transduction of the MP inhibitor, kinase-enhanced PP1 inhibitor (KEPI), into synaptosomes, an increase in phosphorylation of SNAP-25 and a decrease in the extent of neurotransmitter release were detected. The interaction between SNAP-25 and syntaxin increased with decreasing phosphorylation of SNAP-25 at Thr138, upon inhibition of ROK. Our data suggest that ROK/MP play a crucial role in vesicle trafficking, fusion, and neurotransmitter release by oppositely regulating the phosphorylation of SNAP-25 at Thr138.

Proteomic analysis reveals O-GlcNAc modification on proteins with key regulatory functions in Arabidopsis

Genetic studies have shown essential functions of O-linked N-acetylglucosamine (O-GlcNAc) modification in plants. However, the proteins and sites subject to this posttranslational modification are largely unknown. Here, we report a large-scale proteomic identification of O-GlcNAc-modified proteins and sites in the model plant Arabidopsis thaliana Using lectin weak affinity chromatography to enrich modified peptides, followed by mass spectrometry, we identified 971 O-GlcNAc-modified peptides belonging to 262 proteins. The modified proteins are involved in cellular regulatory processes, including transcription, translation, epigenetic gene regulation, and signal transduction. Many proteins have functions in developmental and physiological processes specific to plants, such as hormone responses and flower development. Mass spectrometric analysis of phosphopeptides from the same samples showed that a large number of peptides could be modified by either O-GlcNAcylation or phosphorylation, but cooccurrence of the two modifications in the same peptide molecule was rare. Our study generates a snapshot of the O-GlcNAc modification landscape in plants, indicating functions in many cellular regulation pathways and providing a powerful resource for further dissecting these functions at the molecular level.

Modification Site Localization in Peptides

There are a large number of search engines designed to take mass spectrometry fragmentation spectra and match them to peptides from proteins in a database. These peptides could be unmodified, but they could also bear modifications that were added biologically or during sample preparation. As a measure of reliability for the peptide identification, software normally calculates how likely a given quality of match could have been achieved at random, most commonly through the use of target-decoy database searching (Elias and Gygi, Nat Methods 4(3): 207-214, 2007). Matching the correct peptide but with the wrong modification localization is not a random match, so results with this error will normally still be assessed as reliable identifications by the search engine. Hence, an extra step is required to determine site localization reliability, and the software approaches to measure this are the subject of this part of the chapter.