An Augmented Multiple-Protease-Based Human Phosphopeptide Atlas

Ultradeep O-GlcNAc proteomics reveals widespread O-GlcNAcylation on tyrosine residues of proteins

As a unique type of glycosylation, O-linked β-N-acetylglucosamine (O-GlcNAc) modification (O-GlcNAcylation) on Ser/Thr residues of proteins was discovered 40 y ago. O-GlcNAcylation is catalyzed by two enzymes: O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA), which add and remove O-GlcNAc, respectively. O-GlcNAcylation is an essential glycosylation that regulates the functions of many proteins in virtually all cellular processes. However, deep and site-specific characterization of O-GlcNAcylated proteins remains a challenge. We developed an ultradeep O-GlcNAc proteomics workflow by integrating digestion with multiple proteases, two mass spectrometric approaches (i.e., electron-transfer/higher-energy collision dissociation [EThcD] and HCD product-dependent electron-transfer/higher-energy collision dissociation [HCD-pd-EThcD]), and two data analysis tools (i.e., MaxQuant and Proteome Discoverer). The performance of this strategy was benchmarked by the analysis of whole lysates from PANC-1 (a pancreatic cancer cell line). In total, 2,831 O-GlcNAc sites were unambiguously identified, representing the largest O-GlcNAc dataset of an individual study reported so far. Unexpectedly, in addition to confirming known sites and identifying many other sites of Ser/Thr modification, O-GlcNAcylation was found on 121 tyrosine (Tyr) residues of 93 proteins. In vitro enzymatic assays showed that OGT catalyzes the transfer of O-GlcNAc onto Tyr residues of peptides and OGA catalyzes its removal. Taken together, our work reveals widespread O-GlcNAcylation on Tyr residues of proteins and that Tyr O-GlcNAcylation is mediated by OGT and OGA. As another form of glycosylation, Tyr O-GlcNAcylation is likely to have important regulatory roles.

Molecular Signatures of Neurodegenerative Diseases Identified by Proteomic and Phosphoproteomic Analyses in Aging Mouse Brain

A central hallmark of neurodegenerative diseases is the irreversible accumulation of misfolded proteins in the brain by aberrant phosphorylation. Understanding the mechanisms underlying protein phosphorylation and its role in pathological protein aggregation within the context of aging is crucial for developing therapeutic strategies aimed at preventing or reversing such diseases. Here, we applied multi-protease digestion and quantitative mass spectrometry to compare and characterize dysregulated proteins and phosphosites in the mouse brain proteome using three different age groups: young-adult (3-4 months), middle-age (10 months), and old mice (19-21 months). Proteins associated with senescence, neurodegeneration, inflammation, cell cycle regulation, the p53 hallmark pathway, and cytokine signaling showed significant age-dependent changes in abundances and level of phosphorylation. Several proteins implicated in Alzheimer's disease (AD) and Parkinson's disease (PD) including tau (Mapt), Nefh, and Dpysl2 (also known as Crmp2) were hyperphosphorylated in old mice brain suggesting their susceptibility to the diseases. Cdk5 and Gsk3b, which are known to phosphorylate Dpysl2 at multiple specific sites, had also increased phosphorylation levels in old mice suggesting a potential crosstalk between them to contribute to AD. Hapln2, which promotes α-synuclein aggregation in patients with PD, was one of the proteins with highest abundance in old mice. CD9, which regulates senescence through the PI3K-AKT-mTOR-p53 signaling was upregulated in old mice and its regulation was correlated with the activation of phosphorylated AKT1. Overall, the findings identify a significant association between aging and the dysregulation of proteins involved in various pathways linked to neurodegenerative diseases with potential therapeutic implications.

Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry

Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this Review will serve as a handbook for researchers who are new to the field of bottom-up proteomics.

An inert tracer: The binding site of a fluorescent dye on the antibody and its effects on Protein A chromatography

Fluorescently labeled antibodies are widely used to visualize the adsorption process in protein chromatography using confocal laser scanning microscopy (CLSM), but also as a tracer for determination of residence time distribution (RTD) in continuous chromatography. It is assumed that the labeled protein is inert and representative of the unlabeled antibody, ignoring the fact that labeling with a fluorescent dye can change the characteristics of the original molecule. It became evident that the fluorescently labeled antibody has a higher affinity toward protein A resins such as MabSelect Sure. This can be due to slight differences in hydrophobicity and net charge, which are caused by the addition of the fluorescent dye. However, this difference is eliminated when using high salt concentrations in the adsorption studies. In this work, the site occupancy of two labeled antibodies, MAb1 (IgG1 subclass) and MAb2 (IgG2 subclass) conjugated with the fluorescent dye Alexa Fluor™ 488 was elucidated by intact mass spectrometry (MS) and peptide mapping LC-MS/MS, employing a sequential cleavage with Endoproteinase Lys-C and trypsin and in parallel with chymotrypsin alone. It was shown that the main binding site for the dye was a specific lysine in the heavy chains of the MAb1 and MAb2 molecules, in positions 188 and 189 respectively. Other lysine residues distributed throughout the protein sequence were labeled to a lot lesser extent. The labeled antibody had a slightly different affinity to MabSelect Sure although its primary binding site (to Protein A) was not affected by labeling, despite the secondary region responsible for binding to the protein A was partly labeled. Overall, the fluorescent-labeled antibodies are a good compromise as an inert tracer in residence time distribution and chromatography studies because they are much cheaper than isotope-labeled antibodies; However, the differences between the labeled and unlabeled antibodies should be considered.

Global detection of human variants and isoforms by deep proteome sequencing

An average shotgun proteomics experiment detects approximately 10,000 human proteins from a single sample. However, individual proteins are typically identified by peptide sequences representing a small fraction of their total amino acids. Hence, an average shotgun experiment fails to distinguish different protein variants and isoforms. Deeper proteome sequencing is therefore required for the global discovery of protein isoforms. Using six different human cell lines, six proteases, deep fractionation and three tandem mass spectrometry fragmentation methods, we identify a million unique peptides from 17,717 protein groups, with a median sequence coverage of approximately 80%. Direct comparison with RNA expression data provides evidence for the translation of most nonsynonymous variants. We have also hypothesized that undetected variants likely arise from mutation-induced protein instability. We further observe comparable detection rates for exon-exon junction peptides representing constitutive and alternative splicing events. Our dataset represents a resource for proteoform discovery and provides direct evidence that most frame-preserving alternatively spliced isoforms are translated.

Addressing the Protease Bias in Quantitative Proteomics

Protein quantification strategies using multiple proteases have been shown to deliver poor interprotease accuracy in label-free mass spectrometry experiments. By utilizing six different proteases with different cleavage sites, this study explores the protease bias and its effect on accuracy and precision by using recombinant protein standards. We established 557 SRM assays, using a recombinant protein standard resource, toward 10 proteins in human plasma and determined their concentration with multiple proteases. The quantified peptides of these plasma proteins spanned 3 orders of magnitude (0.02–70 μM). In total, 60 peptides were used for absolute quantification and the majority of the peptides showed high robustness. The retained reproducibility was achieved by quantifying plasma proteins using spiked stable isotope standard recombinant proteins in a targeted proteomics workflow.

Profiling the Human Phosphoproteome to Estimate the True Extent of Protein Phosphorylation

Public phosphorylation databases such as PhosphoSitePlus (PSP) and PeptideAtlas (PA) compile results from published papers or openly available mass spectrometry (MS) data. However, there is no database-level control for false discovery of sites, likely leading to the overestimation of true phosphosites. By profiling the human phosphoproteome, we estimate the false discovery rate (FDR) of phosphosites and predict a more realistic count of true identifications. We rank sites into phosphorylation likelihood sets and analyze them in terms of conservation across 100 species, sequence properties, and functional annotations. We demonstrate significant differences between the sets and develop a method for independent phosphosite FDR estimation. Remarkably, we report estimated FDRs of 84, 98, and 82% within sets of phosphoserine (pSer), phosphothreonine (pThr), and phosphotyrosine (pTyr) sites, respectively, that are supported by only a single piece of identification evidence─the majority of sites in PSP. We estimate that around 62 000 Ser, 8000 Thr, and 12 000 Tyr phosphosites in the human proteome are likely to be true, which is lower than most published estimates. Furthermore, our analysis estimates that 86 000 Ser, 50 000 Thr, and 26 000 Tyr phosphosites are likely false-positive identifications, highlighting the significant potential of false-positive data to be present in phosphorylation databases.

Data-Independent Acquisition Protease-Multiplexing Enables Increased Proteome Sequence Coverage Across Multiple Fragmentation Modes

The use of multiple proteases has been shown to increase protein sequence coverage in proteomics experiments; however, due to the additional analysis time required, it has not been widely adopted in routine data-dependent acquisition (DDA) proteomic workflows. Alternatively, data-independent acquisition (DIA) has the potential to analyze multiplexed samples from different protease digests, but has been primarily optimized for fragmenting tryptic peptides. Here we evaluate a DIA multiplexing approach that combines three proteolytic digests (Trypsin, AspN, and GluC) into a single sample. We first optimize data acquisition conditions for each protease individually with both the canonical DIA fragmentation mode (beam type CID), as well as resonance excitation CID, to determine optimal consensus conditions across proteases. Next, we demonstrate that application of these conditions to a protease-multiplexed sample of human peptides results in similar protein identifications and quantitative performance as compared to trypsin alone, but enables up to a 63% increase in peptide detections, and a 45% increase in nonredundant amino acid detections. Nontryptic peptides enabled noncanonical protein isoform determination and resulted in 100% sequence coverage for numerous proteins, suggesting the utility of this approach in applications where sequence coverage is critical, such as protein isoform analysis.

ProteomicsDB: toward a FAIR open-source resource for life-science research

ProteomicsDB (https://www.ProteomicsDB.org) is a multi-omics and multi-organism resource for life science research. In this update, we present our efforts to continuously develop and expand ProteomicsDB. The major focus over the last two years was improving the findability, accessibility, interoperability and reusability (FAIR) of the data as well as its implementation. For this purpose, we release a new application programming interface (API) that provides systematic access to essentially all data in ProteomicsDB. Second, we release a new open-source user interface (UI) and show the advantages the scientific community gains from such software. With the new interface, two new visualizations of protein primary, secondary and tertiary structure as well an updated spectrum viewer were added. Furthermore, we integrated ProteomicsDB with our deep-neural-network Prosit that can predict the fragmentation characteristics and retention time of peptides. The result is an automatic processing pipeline that can be used to reevaluate database search engine results stored in ProteomicsDB. In addition, we extended the data content with experiments investigating different human biology as well as a newly supported organism.

Phosphoproteomics Sample Preparation Impacts Biological Interpretation of Phosphorylation Signaling Outcomes

The influence of phosphoproteomics sample preparation methods on the biological interpretation of signaling outcome is unclear. Here, we demonstrate a strong bias in phosphorylation signaling targets uncovered by comparing the phosphoproteomes generated by two commonly used methods-strong cation exchange chromatography-based phosphoproteomics (SCXPhos) and single-run high-throughput phosphoproteomics (HighPhos). Phosphoproteomes of embryonic stem cells exposed to ionizing radiation (IR) profiled by both methods achieved equivalent coverage (around 20,000 phosphosites), whereas a combined dataset significantly increased the depth (>30,000 phosphosites). While both methods reproducibly quantified a subset of shared IR-responsive phosphosites that represent DNA damage and cell-cycle-related signaling events, most IR-responsive phosphoproteins (>82%) and phosphosites (>96%) were method-specific. Both methods uncovered unique insights into phospho-signaling mediated by single (SCXPhos) versus double/multi-site (HighPhos) phosphorylation events; particularly, each method identified a distinct set of previously unreported IR-responsive kinome/phosphatome (95% disparate) directly impacting the uncovered biology.

Toward Comprehensive Plasma Proteomics by Orthogonal Protease Digestion

Rapid and consistent protein identification across large clinical cohorts is an important goal for clinical proteomics. With the development of data-independent technologies (DIA/SWATH-MS), it is now possible to analyze hundreds of samples with great reproducibility and quantitative accuracy. However, this technology benefits from empirically derived spectral libraries that define the detectable set of peptides and proteins. Here, we apply a simple and accessible tip-based workflow for the generation of spectral libraries to provide a comprehensive overview on the plasma proteome in individuals with and without active tuberculosis (TB). To boost protein coverage, we utilized nonconventional proteases such as GluC and AspN together with the gold standard trypsin, identifying more than 30,000 peptides mapping to 3309 proteins. Application of this library to quantify plasma proteome differences in TB infection recovered more than 400 proteins in 50 min of MS acquisition, including diagnostic Mycobacterium tuberculosis (Mtb) proteins that have previously been detectable primarily by antibody-based assays and intracellular proteins not previously described to be in plasma.

[Affinity chromatography based phosphoproteome research on lung cancer cells and its application]

磷酸化是蛋白质翻译后修饰的重要形式之一,其异常往往会导致细胞内信号通路的紊乱和疾病的发生。固定化金属离子亲和色谱(IMAC)是磷酸化肽段的高效富集技术,在磷酸化蛋白质组研究方面应用广泛。该研究以金属钛离子(Ti⁴⁺)螯合IMAC材料(Ti⁴⁺-IMAC)为载体,进行磷酸化肽段富集。比较了10 μm Ti⁴⁺-IMAC通过振荡法和固相萃取法(SPE)富集磷酸肽的效果,发现振荡法可以富集到更多的磷酸肽;对比了两种尺寸(10 μm和30 μm)Ti⁴⁺-IMAC在磷酸化肽段富集中的差异,发现小尺寸材料富集效果更佳。进一步采用优化的策略比较了不同转移能力肺癌细胞的磷酸化蛋白质组,免标记定量蛋白质组学结果表明,优化的Ti⁴⁺-IMAC方法可以从正常的肺成纤维细胞MRC5、低转移肺癌细胞95C和高转移肺癌细胞95D中分别鉴定到510、863和1108种磷酸化蛋白质,其中317种为3组所共有。该研究共鉴定到1268种磷酸化蛋白质上的7560个磷酸化位点,其中1130个为差异磷酸化位点,文献报道显示部分异常表达的激酶与癌症转移密切相关。通过生信对比分析发现,异常表达的磷酸化蛋白质主要与细胞侵袭、迁移和死亡等细胞迁移方面的功能有关。通过优化磷酸化肽富集策略,初步阐明了磷酸化蛋白质网络的异常与肺癌转移之间的相关性,该方法有望用于肺癌进展相关的磷酸化位点、磷酸化蛋白质及其信号通路研究。

WIDENING THE BOTTLENECK OF PHOSPHOPROTEOMICS: EVOLVING STRATEGIES FOR PHOSPHOPEPTIDE ENRICHMENT

Phosphorylation is a form of protein posttranslational modification (PTM) that regulates many biological processes. Whereas phosphoproteomics is a scientific discipline that identifies and quantifies the phosphorylated proteome using mass spectrometry (MS). This task is extremely challenging as ~30% of the human proteome is phosphorylated; and each phosphoprotein may exist as multiple phospho-isoforms that are present in low abundance and stoichiometry. Hence, phosphopeptide enrichment techniques are indispensable to (phospho)proteomics laboratories. These enrichment methods encompass widely-adopted techniques such as (i) affinity-based chromatography; (ii) ion exchange and mixed-mode chromatography (iii) enrichment with phospho-specific antibodies and protein domains, and (iv) functionalized polymers and other less common but emerging technologies such as hydroxyapatite chromatography and precipitation with inorganic ions. Here, we review these techniques, their history, continuous development and evaluation. Besides, we outline associating challenges of phosphoproteomics that are linked to experimental design, sample preparation, and proteolytic digestion. In addition, we also discuss about the future outlooks in phosphoproteomics, focusing on elucidating the noncanonical phosphoproteome and deciphering the "dark phosphoproteome". © 2020 John Wiley & Sons Ltd.

ARS2/SRRT: at the nexus of RNA polymerase II transcription, transcript maturation and quality control

ARS2/SRRT is an essential eukaryotic protein that has emerged as a critical factor in the sorting of functional from non-functional RNA polymerase II (Pol II) transcripts. Through its interaction with the Cap Binding Complex (CBC), it associates with the cap of newly made RNAs and acts as a hub for competitive exchanges of protein factors that ultimately determine the fate of the associated RNA. The central position of the protein within the nuclear gene expression machinery likely explains why its depletion causes a broad range of phenotypes, yet an exact function of the protein remains elusive. Here, we consider the literature on ARS2/SRRT with the attempt to garner the threads into a unifying working model for ARS2/SRRT function at the nexus of Pol II transcription, transcript maturation and quality control.

Regulation of the Phosphoinositide Code by Phosphorylation of Membrane Readers

The genetic code that dictates how nucleic acids are translated into proteins is well known, however, the code through which proteins recognize membranes remains mysterious. In eukaryotes, this code is mediated by hundreds of membrane readers that recognize unique phosphatidylinositol phosphates (PIPs), which demark organelles to initiate localized trafficking and signaling events. The only superfamily which specifically detects all seven PIPs are the Phox homology (PX) domains. Here, we reveal that throughout evolution, these readers are universally regulated by the phosphorylation of their PIP binding surfaces based on our analysis of existing and modelled protein structures and phosphoproteomic databases. These PIP-stops control the selective targeting of proteins to organelles and are shown to be key determinants of high-fidelity PIP recognition. The protein kinases responsible include prominent cancer targets, underscoring the critical role of regulated membrane readership.

Global Phosphoproteome Analysis Using High-Field Asymmetric Waveform Ion Mobility Spectrometry on a Hybrid Orbitrap Mass Spectrometer

Mass spectrometry is the premier tool for identifying and quantifying protein phosphorylation on a global scale. Analysis of phosphopeptides requires enrichment, and even after the samples remain highly complex and exhibit broad dynamic range of abundance. Achieving maximal depth of coverage for phosphoproteomics therefore typically necessitates offline liquid chromatography prefractionation, a time-consuming and laborious approach. Here, we incorporate a recently commercialized aerodynamic high-field asymmetric waveform ion mobility spectrometry (FAIMS) device into the phosphoproteomic workflow. We characterize the effects of phosphorylation on the FAIMS separation, describe optimized compensation voltage settings for unlabeled phosphopeptides, and demonstrate the advantages of FAIMS-enabled gas-phase fractionation. Standard FAIMS single-shot analyses identified around 15-20% additional phosphorylation sites than control experiments without FAIMS. In comparison to liquid chromatography prefractionation, FAIMS experiments yielded similar or superior results when analyzing up to four discrete gas-phase fractions. Although using FAIMS led to a modest reduction in the precision of quantitative measurements when using label-free approaches, the data collected with FAIMS yielded a 26% increase in total reproducible measurements. Overall, we conclude that the new FAIMS technology is a valuable addition to any phosphoproteomic workflow, with greater benefits emerging from longer analyses and higher amounts of material.

PhosphoShield: Improving Trypsin Digestion of Phosphoproteins by Shielding the Negatively Charged Phosphate Moiety

Protein phosphorylation is a post-translational modification that is essential to cellular signaling, cellular function, and associated disease progression. Bottom-up proteomics based on enzymatic digestion is the most widely used approach for identifying and quantifying phosphoproteins in complex biological samples. Researchers have largely optimized the experimental conditions for trypsin digestion, and it is now a routine procedure. However, trypsin digestion is impaired by the presence of phosphorylated residues in the protein sequence. This impairment arises from the fact that there are commonly salt bridges between a negatively charged phosphate group and the side chain of protonated arginine or lysine. On average, 55% of all phosphopeptides have their phosphosites located less than three amino acid residues from a cleavage site. Salt bridges reduce the cleavage accessibility for trypsin by masking the basic site chain groups of arginine and lysine. Thus, there are frequent missed cleavages in the vicinity of phosphorylation sites, thereby lessening both the depth of proteome coverage and the quantification accuracy of phosphoproteomics. In this work, we propose a method termed PhosphoShield to mitigate salt bridge formation by adding a digallium complex that exhibits a high binding affinity to the phosphate group. We tested our method using quantitative mass spectrometry analysis of the phosphoproteome of human liver cancer cells (HepG2). PhosphoShield enhances the cleavage frequency of at least 17% of tryptic phosphopeptides having cleavage sites close to the phosphate group.

Analyzing Ribosome Remodeling in Health and Disease

Increasing evidence suggests that ribosomes actively regulate protein synthesis. However, much of this evidence is indirect, leaving this layer of gene regulation largely unexplored, in part due to methodological limitations. Indeed, evidence is reviewed demonstrating that commonly used methods, such as transcriptomics, are inadequate because the variability in mRNAs coding for ribosomal proteins (RP) does not necessarily correspond to RP variability. Thus protein remodeling of ribosomes should be investigated by methods that allow direct quantification of RPs, ideally of isolated ribosomes. Such methods are reviewed, focusing on mass spectrometry and emphasizing method-specific biases and approaches to control these biases. It is argued that using multiple complementary methods can help reduce the danger of interpreting reproducible systematic biases as evidence for ribosome remodeling.

Proteomics Using Protease Alternatives to Trypsin Benefits from Sequential Digestion with Trypsin

Trypsin is the most used enzyme in proteomics. Nevertheless, proteases with complementary cleavage specificity have been applied in special circumstances. In this work, we analyzed the characteristics of five protease alternatives to trypsin for protein identification and sequence coverage when applied to S. pombe whole cell lysates. The specificity of the protease heavily impacted the number of proteins identified. Proteases with higher specificity led to the identification of more proteins than proteases with lower specificity. However, AspN, GluC, chymotrypsin, and proteinase K largely benefited from being paired with trypsin in sequential digestion, as had been shown by us for elastase before. In the most extreme case, predigesting with trypsin improves the number of identified proteins for proteinase K by 731%. Trypsin predigestion also improved the protein identifications of other proteases, AspN (+62%), GluC (+80%), and chymotrypsin (+21%). Interestingly, the sequential digest with trypsin and AspN yielded even a higher number of protein identifications than digesting with trypsin alone.

Using phosphoproteomics data to understand cellular signaling: a comprehensive guide to bioinformatics resources

Mass spectrometry-based phosphoproteomics is becoming an essential methodology for the study of global cellular signaling. Numerous bioinformatics resources are available to facilitate the translation of phosphopeptide identification and quantification results into novel biological and clinical insights, a critical step in phosphoproteomics data analysis. These resources include knowledge bases of kinases and phosphatases, phosphorylation sites, kinase inhibitors, and sequence variants affecting kinase function, and bioinformatics tools that can predict phosphorylation sites in addition to the kinase that phosphorylates them, infer kinase activity, and predict the effect of mutations on kinase signaling. However, these resources exist in silos and it is challenging to select among multiple resources with similar functions. Therefore, we put together a comprehensive collection of resources related to phosphoproteomics data interpretation, compared the use of tools with similar functions, and assessed the usability from the standpoint of typical biologists or clinicians. Overall, tools could be improved by standardization of enzyme names, flexibility of data input and output format, consistent maintenance, and detailed manuals.

Targeting proline in (phospho)proteomics

Mass spectrometry-based proteomics experiments typically start with the digestion of proteins using trypsin, chosen because of its high specificity, availability, and ease of use. It has become apparent that the sole use of trypsin may impose certain limits on our ability to grasp the full proteome, missing out particular sites of post-translational modifications, protein segments, or even subsets of proteins. To tackle this problem, alternative proteases have been introduced and shown to lead to an increase in the detectable (phospho)proteome. Here, we argue that there may be further room for improvement and explore the protease EndoPro. For optimal peptide identification rates, we explored multiple peptide fragmentation techniques (HCD, ETD, and EThcD) and employed Byonic as search algorithm. We obtain peptide IDs for about 40% of the MS2 spectra (66% for trypsin). EndoPro cleaves with high specificity at the C-terminal site of Pro and Ala residues and displays activity in a broad pH range, where we focused on its performance at pH = 2 and 5.5. The proteome coverage of EndoPro at these two pH values is rather distinct, and also complementary to the coverage obtained with trypsin. As about 40% of mammalian protein phosphorylations are proline-directed, we also explored the performance of EndoPro in phosphoproteomics. EndoPro extends the coverable phosphoproteome substantially, whereby both the, at pH = 2 and 5.5, acquired phosphoproteomes are complementary to each other and to the phosphoproteome obtained using trypsin. Hence, EndoPro is a powerful tool to exploit in (phospho)proteomics applications.

Phosphopeptide enrichment for phosphoproteomic analysis - A tutorial and review of novel materials

Significant technical advancements in phosphopeptide enrichment have enabled the identification of thousands of p-peptides (mono and multiply phosphorylated) in a single experiment. However, it is still not possible to enrich all p-peptide species in a single step. A range of new techniques and materials has been developed, with the potential to provide a step-change in phosphopeptide enrichment. The first half of this review contains a tutorial for new potential phosphoproteomic researchers; discussing the key steps of a typical phosphoproteomic experiment used to investigate canonical phosphorylation sites (serine, threonine and tyrosine). The latter half then show-cases the latest developments in p-peptide enrichment including: i) Strategies to mitigate non-specific binding in immobilized metal ion affinity chromatography and metal oxide affinity chromatography protocols; ii) Techniques to separate multiply phosphorylated peptides from monophosphorylated peptides (including canonical from non-canonical phosphorylated peptides), or to simultaneously co-enrich other post-translational modifications; iii) New hybrid materials and methods directed towards enhanced selectivity and efficiency of metal-based enrichment; iv) Novel materials that hold promise for enhanced phosphotyrosine enrichment. A combination of well-understood techniques and materials is much more effective than any technique in isolation; but the field of phosphoproteomics currently requires benchmarking of novel materials against current methodologies to fully evaluate their utility in peptide based proteoform analysis.

Affinity chromatography assisted comprehensive phosphoproteomics analysis of human saliva for lung cancer

Affinity chromatography is a powerful technology for phosphopeptide enrichment from body fluids. Saliva is a non-invasive body fluid for disease diagnosis, while few studies applied affinity enrichment for saliva phosphoproteome. In this study, we tested two kinds of affinity chromatography materials, Ti⁴⁺-IMAC (immobilized metal affinity chromatography) and CaTiO₃, for the enrichment of phosphopeptides. Through comparison, Ti⁴⁺-IMAC method was demonstrated as the superior one, which was utilized for the comprehensive analysis of salivary phosphoproteome. More than 360 phosphoproteins were specifically extracted and identified from human saliva. Ti⁴⁺-IMAC method was further applied to compare the phosphoprotein profiling in the saliva of lung cancer group and normal control group through label-free quantification. Accordingly, 477 and 699 phosphopeptides were enriched, respectively, which corresponded to 339 and 466 proteins. In total, 796 unique phosphopeptides were revealed for 517 saliva phosphoproteins. In particular, 709 phosphorylation sites were identified, among which 26 were up-regulated (>1.5) and 149 were down-regulated (<0.66) in lung cancer. Their corresponding proteins were mainly associated with cancer promotion, system disorder, and organismal injury. Our data collectively demonstrated that salivary phosphopeptides can be comprehensively characterized through Ti⁴⁺-IMAC method. These discovered phosphoprotein candidates might be used for lung cancer detection through salivary diagnostics.

Quantitative phosphoproteomic analysis identifies the potential therapeutic target EphA2 for overcoming sorafenib resistance in hepatocellular carcinoma cells

Limited therapeutic options are available for advanced-stage hepatocellular carcinoma owing to its poor diagnosis. Drug resistance to sorafenib, the only available targeted agent, is commonly reported. The comprehensive elucidation of the mechanisms underlying sorafenib resistance may thus aid in the development of more efficacious therapeutic agents. To clarify the signaling changes contributing to resistance, we applied quantitative phosphoproteomics to analyze the differential phosphorylation changes between parental and sorafenib-resistant HuH-7 cells. Consequently, an average of ~1500 differential phosphoproteins were identified and quantified, among which 533 were significantly upregulated in resistant cells. Further bioinformatic integration via functional categorization annotation, pathway enrichment and interaction linkage analysis led to the discovery of alterations in pathways associated with cell adhesion and motility, cell survival and cell growth and the identification of a novel target, EphA2, in resistant HuH-7^R cells. In vitro functional analysis indicated that the suppression of EphA2 function impairs cell proliferation and motility and, most importantly, overcomes sorafenib resistance. The attenuation of sorafenib resistance may be achieved prior to its development through the modulation of EphA2 and the subsequent inhibition of Akt activity. Binding analyses and in silico modeling revealed a ligand mimic lead compound, prazosin, that could abate the ligand-independent oncogenic activity of EphA2. Finally, data obtained from in vivo animal models verified that the simultaneous inhibition of EphA2 with sorafenib treatment can effectively overcome sorafenib resistance and extend the projected survival of resistant tumor-bearing mice. Thus our findings regarding the targeting of EphA2 may provide an effective approach for overcoming sorafenib resistance and may contribute to the management of advanced hepatocellular carcinoma.

ExteNDing Proteome Coverage with Legumain as a Highly Specific Digestion Protease

Bottom-up mass spectrometry-based proteomics utilizes proteolytic enzymes with well characterized specificities to generate peptides amenable for identification by high-throughput tandem mass spectrometry. Trypsin, which cuts specifically after the basic residues lysine and arginine, is the predominant enzyme used for proteome digestion, although proteases with alternative specificities are required to detect sequences that are not accessible after tryptic digest. Here, we show that the human cysteine protease legumain exhibits a strict substrate specificity for cleavage after asparagine and aspartic acid residues during in-solution digestions of proteomes extracted from Escherichia coli, mouse embryonic fibroblast cell cultures, and Arabidopsis thaliana leaves. Generating peptides highly complementary in sequence, yet similar in their biophysical properties, legumain (as compared to trypsin or GluC) enabled complementary proteome and protein sequence coverage. Importantly, legumain further enabled the identification and enrichment of protein N-termini not accessible in GluC- or trypsin-digested samples. Legumain cannot cleave after glycosylated Asn residues, which enabled the robust identification and orthogonal validation of N-glycosylation sites based on alternating sequential sample treatments with legumain and PNGaseF and vice versa. Taken together, we demonstrate that legumain is a practical, efficient protease for extending the proteome and sequence coverage achieved with trypsin, with unique possibilities for the characterization of post-translational modification sites.

Tandem Mass Tag Labeling Facilitates Reversed-Phase Liquid Chromatography-Mass Spectrometry Analysis of Hydrophilic Phosphopeptides

Protein phosphorylation is a critical post-translational modification (PTM). Despite recent technological advances in reversed-phase liquid chromatography (RPLC)-mass spectrometry (MS)-based proteomics, comprehensive phosphoproteomic coverage in complex biological systems remains challenging, especially for hydrophilic phosphopeptides with enriched regions of serines, threonines, and tyrosines that often orchestrate critical biological functions. To address this issue, we developed a simple, easily implemented method to introduce a commonly used tandem mass tag (TMT) to increase peptide hydrophobicity, effectively enhancing RPLC-MS analysis of hydrophilic peptides. Different from conventional TMT labeling, this method capitalizes on using a nonprimary amine buffer and TMT labeling occurring before C18-based solid phase extraction. Through phosphoproteomic analyses of MCF7 cells, we have demonstrated that this method can greatly increase the number of identified hydrophilic phosphopeptides and improve MS detection signals. We applied this method to study the peptide QPSSSR, a very hydrophilic tryptic peptide located on the C-terminus of the G protein-coupled receptor (GPCR) CXCR3. Identification of QPSSSR has never been reported, and we were unable to detect it by traditional methods. We validated our TMT labeling strategy by comparative RPLC-MS analyses of both a hydrophilic QPSSSR peptide library as well as common phosphopeptides. We further confirmed the utility of this method by quantifying QPSSSR phosphorylation abundances in HEK 293 cells under different treatment conditions predicted to alter QPSSSR phosphorylation. We anticipate that this simple TMT labeling method can be broadly used not only for decoding GPCR phosphoproteome but also for effective RPLC-MS analysis of other highly hydrophilic analytes.

An integrated workflow for crosslinking mass spectrometry

We present a concise workflow to enhance the mass spectrometric detection of crosslinked peptides by introducing sequential digestion and the crosslink identification software xiSEARCH. Sequential digestion enhances peptide detection by selective shortening of long tryptic peptides. We demonstrate our simple 12-fraction protocol for crosslinked multi-protein complexes and cell lysates, quantitative analysis, and high-density crosslinking, without requiring specific crosslinker features. This overall approach reveals dynamic protein-protein interaction sites, which are accessible, have fundamental functional relevance and are therefore ideally suited for the development of small molecule inhibitors.

iHPDM: In Silico Human Proteome Digestion Map with Proteolytic Peptide Analysis and Graphical Visualizations

When conducting proteomics experiments to detect missing proteins and protein isoforms in the human proteome, it is desirable to use a protease that can yield more unique peptides with properties amenable for mass spectrometry analysis. Though trypsin is currently the most widely used protease, some proteins can yield only a limited number of unique peptides by trypsin digestion. Other proteases and multiple proteases have been applied in reported studies to increase the number of identified proteins and protein sequence coverage. To facilitate the selection of proteases, we developed a web-based resource, called in silico Human Proteome Digestion Map (iHPDM), which contains a comprehensive proteolytic peptide database constructed from human proteins, including isoforms, in neXtProt digested by 15 protease combinations of one or two proteases. iHPDM provides convenient functions and graphical visualizations for users to examine and compare the digestion results of different proteases. Notably, it also supports users to input filtering criteria on digested peptides, e.g., peptide length and uniqueness, to select suitable proteases. iHPDM can facilitate protease selection for shotgun proteomics experiments to identify missing proteins, protein isoforms, and single amino acid variant peptides.

Strong anion exchange-mediated phosphoproteomics reveals extensive human non-canonical phosphorylation

Phosphorylation is a key regulator of protein function under (patho)physiological conditions, and defining site-specific phosphorylation is essential to understand basic and disease biology. In vertebrates, the investigative focus has primarily been on serine, threonine and tyrosine phosphorylation, but mounting evidence suggests that phosphorylation of other "non-canonical" amino acids also regulates critical aspects of cell biology. However, standard methods of phosphoprotein characterisation are largely unsuitable for the analysis of non-canonical phosphorylation due to their relative instability under acidic conditions and/or elevated temperature. Consequently, the complete landscape of phosphorylation remains unexplored. Here, we report an unbiased phosphopeptide enrichment strategy based on strong anion exchange (SAX) chromatography (UPAX), which permits identification of histidine (His), arginine (Arg), lysine (Lys), aspartate (Asp), glutamate (Glu) and cysteine (Cys) phosphorylation sites on human proteins by mass spectrometry-based phosphoproteomics. Remarkably, under basal conditions, and having accounted for false site localisation probabilities, the number of unique non-canonical phosphosites is approximately one-third of the number of observed canonical phosphosites. Our resource reveals the previously unappreciated diversity of protein phosphorylation in human cells, and opens up avenues for high-throughput exploration of non-canonical phosphorylation in all organisms.

An Advanced Strategy for Comprehensive Profiling of ADP-ribosylation Sites Using Mass Spectrometry-based Proteomics

ADP-ribosylation is a widespread post-translational modification (PTM) with crucial functions in many cellular processes. Here, we describe an in-depth ADP-ribosylome using our Af1521-based proteomics methodology for comprehensive profiling of ADP-ribosylation sites, by systematically assessing complementary proteolytic digestions and precursor fragmentation through application of electron-transfer higher-energy collisional dissociation (EThcD) and electron transfer dissociation (ETD), respectively. Although ETD spectra yielded higher identification scores, EThcD generally proved superior to ETD in identification and localization of ADP-ribosylation sites regardless of protease employed. Notwithstanding, the propensities of complementary proteases and fragmentation methods expanded the detectable repertoire of ADP-ribosylation to an unprecedented depth. This system-wide profiling of the ADP-ribosylome in HeLa cells subjected to DNA damage uncovered >11,000 unique ADP-ribosylated peptides mapping to >7,000 ADP-ribosylation sites, in total modifying over one-third of the human nuclear proteome and highlighting the vast scope of this PTM. High-resolution MS/MS spectra enabled identification of dozens of proteins concomitantly modified by ADP-ribosylation and phosphorylation, revealing a considerable degree of crosstalk on histones. ADP-ribosylation was confidently localized to various amino acid residue types, including less abundantly modified residues, with hundreds of ADP-ribosylation sites pinpointed on histidine, arginine, and tyrosine residues. Functional enrichment analysis suggested modification of these specific residue types is directed in a spatial manner, with tyrosine ADP-ribosylation linked to the ribosome, arginine ADP-ribosylation linked to the endoplasmic reticulum, and histidine ADP-ribosylation linked to the mitochondrion.

Elucidating synergistic dependencies in lung adenocarcinoma by proteome-wide signaling-network analysis

To understand drug combination effect, it is necessary to decipher the interactions between drug targets-many of which are signaling molecules. Previously, such signaling pathway models are largely based on the compilation of literature data from heterogeneous cellular contexts. Indeed, de novo reconstruction of signaling interactions from large-scale molecular profiling is still lagging, compared to similar efforts in transcriptional and protein-protein interaction networks. To address this challenge, we introduce a novel algorithm for the systematic inference of protein kinase pathways, and applied it to published mass spectrometry-based phosphotyrosine profile data from 250 lung adenocarcinoma (LUAD) samples. The resulting network includes 43 TKs and 415 inferred, LUAD-specific substrates, which were validated at >60% accuracy by SILAC assays, including "novel' substrates of the EGFR and c-MET TKs, which play a critical oncogenic role in lung cancer. This systematic, data-driven model supported drug response prediction on an individual sample basis, including accurate prediction and validation of synergistic EGFR and c-MET inhibitor activity in cells lacking mutations in either gene, thus contributing to current precision oncology efforts.

Quantifying Homologous Proteins and Proteoforms

Many proteoforms-arising from alternative splicing, post-translational modifications (PTM), or paralogous genes-have distinct biological functions, such as histone PTM proteoforms. However, their quantification by existing bottom-up mass-spectrometry (MS) methods is undermined by peptide-specific biases. To avoid these biases, we developed and implemented a first-principles model (HIquant) for quantifying proteoform stoichiometries. We characterized when MS data allow inferring proteoform stoichiometries by HIquant and derived an algorithm for optimal inference. We applied this algorithm to infer proteoform stoichiometries in two experimental systems that supported rigorous bench-marking: alkylated proteoforms spiked-in at known ratios and endogenous histone 3 PTM proteoforms quantified relative to internal heavy standards. When compared with the benchmarks, the proteoform stoichiometries interfered by HIquant without using external standards had relative error of 5-15% for simple proteoforms and 20-30% for complex proteoforms. A HIquant server is implemented at: https://web.northeastern.edu/slavov/2014HIquant/.

Recent advances in phosphoproteomics and application to neurological diseases

Phosphorylation has an incredible impact on the biological behavior of proteins, altering everything from intrinsic activity to cellular localization and complex formation. It is no surprise then that this post-translational modification has been the subject of intense study and that, with the advent of faster, more accurate instrumentation, the number of large-scale mass spectrometry-based phosphoproteomic studies has swelled over the past decade. Recent developments in sample preparation, phosphorylation enrichment, quantification, and data analysis strategies permit both targeted and ultra-deep phosphoproteome profiling, but challenges remain in pinpointing biologically relevant phosphorylation events. We describe here technological advances that have facilitated phosphoproteomic analysis of cells, tissues, and biofluids and note applications to neuropathologies in which the phosphorylation machinery may be dysregulated, much as it is in cancer.

Reconstruction of global regulatory network from signaling to cellular functions using phosphoproteomic data

Cellular signaling regulates various cellular functions via protein phosphorylation. Phosphoproteomic data potentially include information for a global regulatory network from signaling to cellular functions, but a procedure to reconstruct this network using such data has yet to be established. In this paper, we provide a procedure to reconstruct a global regulatory network from signaling to cellular functions from phosphoproteomic data by integrating prior knowledge of cellular functions and inference of the kinase-substrate relationships (KSRs). We used phosphoproteomic data from insulin-stimulated Fao hepatoma cells and identified protein phosphorylation regulated by insulin specifically over-represented in cellular functions in the KEGG database. We inferred kinases for protein phosphorylation by KSRs, and connected the kinases in the insulin signaling layer to the phosphorylated proteins in the cellular functions, revealing that the insulin signal is selectively transmitted via the Pi3k-Akt and Erk signaling pathways to cellular adhesions and RNA maturation, respectively. Thus, we provide a method to reconstruct global regulatory network from signaling to cellular functions based on phosphoproteomic data.

A comprehensive analysis of Candida albicans phosphoproteome reveals dynamic changes in phosphoprotein abundance during hyphal morphogenesis

The morphological plasticity of Candida albicans is a virulence determinant as the hyphal form has significant roles in the infection process. Recently, phosphoregulation of proteins through phosphorylation and dephosphorylation events has gained importance in studying the regulation of pathogenicity at the molecular level. To understand the importance of phosphorylation in hyphal morphogenesis, global analysis of the phosphoproteome was performed after hyphal induction with elevated temperature, serum, and N-acetyl-glucosamine (GlcNAc) treatments. The study identified 60, 20, and 53 phosphoproteins unique to elevated temperature-, serum-, and GlcNAc-treated conditions, respectively. Distribution of unique phosphorylation sites sorted by the modified amino acids revealed that predominant phosphorylation occurs in serine, followed by threonine and tyrosine residues in all the datasets. However, the frequency distribution of phosphorylation sites in the proteins varied with treatment conditions. Further, interaction network-based functional annotation of protein kinases of C. albicans as well as identified phosphoproteins was performed, which demonstrated the interaction of kinases with phosphoproteins during filamentous growth. Altogether, the present findings will serve as a base for further functional studies in the aspects of protein kinase-target protein interaction in effectuating phosphorylation of target proteins, and delineating the downstream signaling networks linked to virulence characteristics of C. albicans.

Targeted Quantification of Phosphorylation Dynamics in the Context of EGFR-MAPK Pathway

Large-scale phosphoproteomics with coverage of over 10,000 sites of phosphorylation have now been routinely achieved with advanced mass spectrometry (MS)-based workflows. However, accurate targeted MS-based quantification of phosphorylation dynamics, an important direction for gaining quantitative understanding of signaling pathways or networks, has been much less investigated. Herein, we report an assessment of the targeted workflow in the context of signal transduction pathways, using the epidermal growth factor receptor (EGFR)-mitogen-activated protein kinase (MAPK) pathway as our model. A total of 43 phosphopeptides from the EGFR-MAPK pathway were selected for the study. The recovery and sensitivity of two commonly used enrichment methods, immobilized metal affinity chromatography (IMAC) and titanium oxide (TiO₂), combined with selected reaction monitoring (SRM)-MS were evaluated. The recovery of phosphopeptides by IMAC and TiO₂ enrichment was quantified to be 38 ± 5% and 58 ± 20%, respectively, based on internal standards. Moreover, both enrichment methods provided comparable sensitivity from 1 to 100 μg starting peptides. Robust quantification was consistently achieved for most targeted phosphopeptides when starting with 25-100 μg peptides. However, the numbers of quantified targets significantly dropped when peptide samples were in the 1-25 μg range. Finally, IMAC-SRM was applied to quantify signaling dynamics of EGFR-MAPK pathway in Hs578T cells following 10 ng/mL EGF treatment. The kinetics of phosphorylation clearly revealed early and late phases of phosphorylation, even for very low abundance proteins. These results demonstrate the feasibility of robust targeted quantification of phosphorylation dynamics for specific pathways, even starting with relatively small amounts of protein.

Application of the broadband collision-induced dissociation (bbCID) mass spectrometry approach for protein glycosylation and phosphorylation analysis

RATIONALE

Analysis of post-translationally modified peptides by mass spectrometry (MS) remains incomplete, in part due to incomplete sampling of all peptides which is inherent to traditional data-dependent acquisition (DDA). An alternative MS approach, data-independent acquisition (DIA), enables comprehensive recording of all detectable precursor and product ions, independent of precursor intensity. The use of broadband collision-induced dissociation (bbCID), a DIA method, was evaluated for the identification of protein glycosylation and phosphorylation.

METHODS

bbCID was applied to identify glycopeptides and phosphopeptides generated from standard proteins using a high-resolution Bruker maXis 3G mass spectrometer. In bbCID, precursor and product ion spectra were obtained by alternating low and high collision energy. Precursor ions were assigned manually based on the detection of diagnostic ions specific to either glycosylation or phosphorylation. The composition of the glycan modification was resolved in the positive ion mode, while the level of phosphorylation was investigated in the negative ion mode.

RESULTS

The results demonstrate for the first time that the use of a bbCID approach is suitable for the identification of glycopeptides and phosphopeptides based on the detection of specific diagnostic and associated precursor ions. The novel use of bbCID in negative ion mode allowed the discrimination of singly and multiply phosphorylated peptides based on the detection of phosphate diagnostic ions. The results also demonstrate the ability of this approach to allow the identification of glycan composition in N- and O-linked glycopeptides, in positive ion mode.

CONCLUSIONS

We contend that bbCID is a valuable addition to the existing toolkit for PTM discovery. Moreover, this technique could be employed to direct targeted proteomics methods, particularly where there is no a priori information on glycosylation or phosphorylation status. This technique is immediately relevant to the characterisation of individual proteins or biological samples of low complexity, as demonstrated for the analysis of the glycosylation status of a therapeutic protein.

Altering the Peptide Binding Selectivity of Polymeric Reverse Micelle Assemblies via Metal Ion Loading

Supramolecular reverse micelle assemblies, formed by amphiphilic copolymers, can selectively encapsulate molecules in their interiors depending on the functional groups present in the polymers. Altering the binding selectivity of these materials typically requires the synthesis of alternate functional groups. Here, we demonstrate that the addition of Zr(IV) ions to the interiors of reverse micelles having phosphonate functional groups transforms the supramolecular materials from ones that selectively bind positively charged peptides into materials that selectively bind phosphorylated peptides. We also show that the binding selectivity of these reverse micelle assemblies can be further tuned by varying the fractions of phosphonate groups in the copolymer structure. The optimized reverse micelle materials can selectively transfer and bind phosphorylated peptides from aqueous solutions over a wide range of pH conditions and can selectively enrich phosphorylated peptides even in complicated mixtures.

Quantifying Missing (Phospho)Proteome Regions with the Broad-Specificity Protease Subtilisin

Despite huge efforts to map the human proteome using mass spectrometry the overall sequence coverage achieved to date is still below 50%. Reasons for missing areas of the proteome comprise protease-resistant domains including the lack/excess of enzymatic cleavage sites, nonunique peptide sequences, impaired peptide ionization/separation and low expression levels. To access novel areas of the proteome the beneficial use of enzymes complementary to trypsin, such as Glu-C, Asp-N, Lys-N, Arg-C, LysargiNase has been reported. Here, we present how the broad-specificity protease subtilisin enables mapping of previously hidden areas of the proteome. We systematically evaluated its digestion efficiency and reproducibility and compared it to the gold standard in the field, trypsin. Notably, subtilisin allows reproducible near-complete digestion of cells lysates in 1-5 min. As expected from its broad specificity the generation of overlapping peptide sequences reduces the number of identified proteins compared to trypsin (8363 vs 6807; 1% protein FDR). However, subtilisin considerably improved the coverage of missing and particularly proline-rich areas of the proteome. Along 14 628 high confidence phosphorylation sites identified in total, only 33% were shared between both enzymes, while 37% were exclusive to subtilisin. Notably, 926 of these were not even accessible by additional in silico digestion with either Asp-N, Arg-C, Glu-C, Lys-C, or Lys-N. Thus, subtilisin might be particularly beneficial for system-wide profiling of post-translational modification sites. Finally, we demonstrate that subtilisin can be used for reporter-ion based in-depth quantification, providing a precision comparable to trypsin-despite broad specificity and fast digestion that may increase technical variance.

Intersectin associates with synapsin and regulates its nanoscale localization and function

Mutations in genes regulating neurotransmission in the brain are implicated in neurological disorders and neurodegeneration. Synapsin is a crucial regulator of neurotransmission and allows synapses to maintain a large reserve pool of synaptic vesicles. Human mutations in synapsin genes are linked to epilepsy and autism. How synapsin function is regulated to allow replenishment of synaptic vesicles and sustain neurotransmission is largely unknown. Here we identify a function for the endocytic scaffold protein intersectin, a protein overexpressed in patients with Down syndrome, as a regulator of synapsin nanoscale distribution and function that is controlled by a phosphorylation-dependent autoinhibitory switch. Our results unravel a hitherto unknown molecular connection between the machineries for synaptic vesicle reserve pool organization and endocytosis.

Neurotransmission is mediated by the exocytic release of neurotransmitters from readily releasable synaptic vesicles (SVs) at the active zone. To sustain neurotransmission during periods of elevated activity, release-ready vesicles need to be replenished from the reserve pool of SVs. The SV-associated synapsins are crucial for maintaining this reserve pool and regulate the mobilization of reserve pool SVs. How replenishment of release-ready SVs from the reserve pool is regulated and which other factors cooperate with synapsins in this process is unknown. Here we identify the endocytic multidomain scaffold protein intersectin as an important regulator of SV replenishment at hippocampal synapses. We found that intersectin directly associates with synapsin I through its Src-homology 3 A domain, and this association is regulated by an intramolecular switch within intersectin 1. Deletion of intersectin 1/2 in mice alters the presynaptic nanoscale distribution of synapsin I and causes defects in sustained neurotransmission due to defective SV replenishment. These phenotypes were rescued by wild-type intersectin 1 but not by a locked mutant of intersectin 1. Our data reveal intersectin as an autoinhibited scaffold that serves as a molecular linker between the synapsin-dependent reserve pool and the presynaptic endocytosis machinery.

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/ .