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

PhosBERT: A self-supervised learning model for identifying phosphorylation sites in SARS-CoV-2-infected human cells

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a single-stranded RNA virus, which mainly causes respiratory and enteric diseases and is responsible for the outbreak of coronavirus disease 19 (COVID-19). Numerous studies have demonstrated that SARS-CoV-2 infection will lead to a significant dysregulation of protein post-translational modification profile in human cells. The accurate recognition of phosphorylation sites in host cells will contribute to a deep understanding of the pathogenic mechanisms of SARS-CoV-2 and also help to screen drugs and compounds with antiviral potential. Therefore, there is a need to develop cost-effective and high-precision computational strategies for specifically identifying SARS-CoV-2-infected phosphorylation sites. In this work, we first implemented a custom neural network model (named PhosBERT) on the basis of a pre-trained protein language model of ProtBert, which was a self-supervised learning approach developed on the Bidirectional Encoder Representation from Transformers (BERT) architecture. PhosBERT was then trained and validated on serine (S) and threonine (T) phosphorylation dataset and tyrosine (Y) phosphorylation dataset with 5-fold cross-validation, respectively. Independent validation results showed that PhosBERT could identify S/T phosphorylation sites with high accuracy and AUC (area under the receiver operating characteristic) value of 81.9% and 0.896. The prediction accuracy and AUC value of Y phosphorylation sites reached up to 87.1% and 0.902. It indicated that the proposed model was of good prediction ability and stability and would provide a new approach for studying SARS-CoV-2 phosphorylation sites.

PTMoreR-enabled cross-species PTM mapping and comparative phosphoproteomics across mammals

To support PTM proteomic analysis and annotation in different species, we developed PTMoreR, a user-friendly tool that considers the surrounding amino acid sequences of PTM sites during BLAST, enabling a motif-centric analysis across species. By controlling sequence window similarity, PTMoreR can map phosphoproteomic results between any two species, perform site-level functional enrichment analysis, and generate kinase-substrate networks. We demonstrate that the majority of real P-sites in mice can be inferred from experimentally derived human P-sites with PTMoreR mapping. Furthermore, the compositions of 129 mammalian phosphoproteomes can also be predicted using PTMoreR. The method also identifies cross-species phosphorylation events that occur on proteins with an increased tendency to respond to the environmental factors. Moreover, the classic kinase motifs can be extracted across mammalian species, offering an evolutionary angle for refining current motifs. PTMoreR supports PTM proteomics in non-human species and facilitates quantitative phosphoproteomic analysis.

The expanding landscape of canonical and non-canonical protein phosphorylation

Protein phosphorylation is a crucial regulatory mechanism in cell signaling, acting as a molecular switch that modulates protein function. Catalyzed by protein kinases and reversed by phosphoprotein phosphatases, it is essential in both normal physiological and pathological states. Recent advances have uncovered a vast and intricate landscape of protein phosphorylation that include histidine phosphorylation and more unconventional events, such as pyrophosphorylation and polyphosphorylation. Many questions remain about the true size of the phosphoproteome and, more importantly, its site-specific functional relevance. The involvement of unconventional actors such as pseudokinases and pseudophosphatases adds further complexity to be resolved. This review explores recent discoveries and ongoing challenges, highlighting the need for continued research to fully elucidate the roles and regulation of protein phosphorylation.

The fitness cost of spurious phosphorylation

The fidelity of signal transduction requires the binding of regulatory molecules to their cognate targets. However, the crowded cell interior risks off-target interactions between proteins that are functionally unrelated. How such off-target interactions impact fitness is not generally known. Here, we use Saccharomyces cerevisiae to inducibly express tyrosine kinases. Because yeast lacks bona fide tyrosine kinases, the resulting tyrosine phosphorylation is biologically spurious. We engineered 44 yeast strains each expressing a tyrosine kinase, and quantitatively analysed their phosphoproteomes. This analysis resulted in ~30,000 phosphosites mapping to ~3500 proteins. The number of spurious pY sites generated correlates strongly with decreased growth, and we predict over 1000 pY events to be deleterious. However, we also find that many of the spurious pY sites have a negligible effect on fitness, possibly because of their low stoichiometry. This result is consistent with our evolutionary analyses demonstrating a lack of phosphotyrosine counter-selection in species with tyrosine kinases. Our results suggest that, alongside the risk for toxicity, the cell can tolerate a large degree of non-functional crosstalk as interaction networks evolve.

Meta-Analysis of Rice Phosphoproteomics Data to Understand Variation in Cell Signaling Across the Rice Pan-Genome

Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have reanalyzed publicly available mass spectrometry proteomics data sets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we identified 15,565 phosphosites on serine, threonine, and tyrosine residues on rice proteins. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation likely caused by different kinase groups. We cross-referenced phosphosites against the rice 3,000 genomes, to identify single amino acid variations (SAAVs) within or proximal to phosphosites that could cause loss of a site in a given rice variety and clustered the data to identify groups of sites with similar patterns across rice family groups. The data has been loaded into UniProt Knowledge-Base─enabling researchers to visualize sites alongside other data on rice proteins, e.g., structural models from AlphaFold2, PeptideAtlas, and the PRIDE database─enabling visualization of source evidence, including scores and supporting mass spectra.

Oxygen-regulated post-translation modifications as master signalling pathway in cells

Oxygen is essential for viability in mammalian organisms. However, cells are often exposed to changes in oxygen availability, due to either increased demand or reduced oxygen supply, herein called hypoxia. To be able to survive and/or adapt to hypoxia, cells activate a variety of signalling cascades resulting in changes to chromatin, gene expression, metabolism and viability. Cellular signalling is often mediated via post-translational modifications (PTMs), and this is no different in response to hypoxia. Many enzymes require oxygen for their activity and oxygen can directly influence several PTMS. Here, we review the direct impact of changes in oxygen availability on PTMs such as proline, asparagine, histidine and lysine hydroxylation, lysine and arginine methylation and cysteine dioxygenation, with a focus on mammalian systems. In addition, indirect hypoxia-dependent effects on phosphorylation, ubiquitination and sumoylation will also be discussed. Direct and indirect oxygen-regulated changes to PTMs are coordinated to achieve the cell's ultimate response to hypoxia. However, specific oxygen sensitivity and the functional relevance of some of the identified PTMs still require significant research.

A meta-analysis of rice phosphoproteomics data to understand variation in cell signalling across the rice pan-genome

Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have re-analysed publicly available mass spectrometry proteomics datasets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we identified 15,522 phosphosites on serine, threonine and tyrosine residues on rice proteins. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation likely caused by different kinase groups. We cross-referenced phosphosites against the rice 3,000 genomes, to identify single amino acid variations (SAAVs) within or proximal to phosphosites that could cause loss of a site in a given rice variety. The data was clustered to identify groups of sites with similar patterns across rice family groups, for example those highly conserved in Japonica, but mostly absent in Aus type rice varieties - known to have different responses to drought. These resources can assist rice researchers to discover alleles with significantly different functional effects across rice varieties. The data has been loaded into UniProt Knowledge-Base - enabling researchers to visualise sites alongside other data on rice proteins e.g. structural models from AlphaFold2, PeptideAtlas and the PRIDE database - enabling visualisation of source evidence, including scores and supporting mass spectra.

The fitness cost of spurious phosphorylation

The fidelity of signal transduction requires the binding of regulatory molecules to their cognate targets. However, the crowded cell interior risks off-target interactions between proteins that are functionally unrelated. How such off-target interactions impact fitness is not generally known, but quantifying this is required to understand the constraints faced by cell systems as they evolve. Here, we use the model organism S. cerevisiae to inducibly express tyrosine kinases. Because yeast lacks bona fide tyrosine kinases, most of the resulting tyrosine phosphorylation is spurious. This provides a suitable system to measure the impact of artificial protein interactions on fitness. We engineered 44 yeast strains each expressing a tyrosine kinase, and quantitatively analysed their phosphoproteomes. This analysis resulted in ~30,000 phosphosites mapping to ~3,500 proteins. Examination of the fitness costs in each strain revealed a strong correlation between the number of spurious pY sites and decreased growth. Moreover, the analysis of pY effects on protein structure and on protein function revealed over 1000 pY events that we predict to be deleterious. However, we also find that a large number of the spurious pY sites have a negligible effect on fitness, possibly because of their low stoichiometry. This result is consistent with our evolutionary analyses demonstrating a lack of phosphotyrosine counter-selection in species with bona fide tyrosine kinases. Taken together, our results suggest that, alongside the risk for toxicity, the cell can tolerate a large degree of non-functional crosstalk as interaction networks evolve.

Considerations for defining +80 Da mass shifts in mass spectrometry-based proteomics: phosphorylation and beyond

Post-translational modifications (PTMs) are ubiquitous and key to regulating protein function. Understanding the dynamics of individual PTMs and their biological roles requires robust characterisation. Mass spectrometry (MS) is the method of choice for the identification and quantification of protein modifications. This article focusses on the MS-based analysis of those covalent modifications that induce a mass shift of +80 Da, notably phosphorylation and sulfation, given the challenges associated with their discrimination and pinpointing the sites of modification on a polypeptide chain. Phosphorylation in particular is highly abundant, dynamic and can occur on numerous residues to invoke specific functions, hence robust characterisation is crucial to understanding biological relevance. Showcasing our work in the context of other developments in the field, we highlight approaches for enrichment and site localisation of phosphorylated (canonical and non-canonical) and sulfated peptides, as well as modification analysis in the context of intact proteins (top down proteomics) to explore combinatorial roles. Finally, we discuss the application of native ion-mobility MS to explore the effect of these PTMs on protein structure and ligand binding.

A global view of the human post-translational modification landscape

Post-translational modifications (PTMs) provide a rapid response to stimuli, finely tuning metabolism and gene expression and maintain homeostasis. Advances in mass spectrometry over the past two decades have significantly expanded the list of known PTMs in biology and as instrumentation continues to improve, this list will surely grow. While many PTMs have been studied in detail (e.g. phosphorylation, acetylation), the vast majority lack defined mechanisms for their regulation and impact on cell fate. In this review, we will highlight the field of PTM research as it currently stands, discussing the mechanisms that dictate site specificity, analytical methods for their detection and study, and the chemical tools that can be leveraged to define PTM regulation. In addition, we will highlight the approaches needed to discover and validate novel PTMs. Lastly, this review will provide a starting point for those interested in PTM biology, providing a comprehensive list of PTMs and what is known regarding their regulation and metabolic origins.

A Phosphoproteomics Data Resource for Systems-level Modeling of Kinase Signaling Networks

Building mechanistic models of kinase-driven signaling pathways requires quantitative measurements of protein phosphorylation across physiologically relevant conditions, but this is rarely done because of the insensitivity of traditional technologies. By using a multiplexed deep phosphoproteome profiling workflow, we were able to generate a deep phosphoproteomics dataset of the EGFR-MAPK pathway in non-transformed MCF10A cells across physiological ligand concentrations with a time resolution of <12 min and in the presence and absence of multiple kinase inhibitors. An improved phosphosite mapping technique allowed us to reliably identify >46,000 phosphorylation sites on >6600 proteins, of which >4500 sites from 2110 proteins displayed a >2-fold increase in phosphorylation in response to EGF. This data was then placed into a cellular context by linking it to 15 previously published protein databases. We found that our results were consistent with much, but not all previously reported data regarding the activation and negative feedback phosphorylation of core EGFR-ERK pathway proteins. We also found that EGFR signaling is biphasic with substrates downstream of RAS/MAPK activation showing a maximum response at <3ng/ml EGF while direct substrates, such as HGS and STAT5B, showing no saturation. We found that RAS activation is mediated by at least 3 parallel pathways, two of which depend on PTPN11. There appears to be an approximately 4-minute delay in pathway activation at the step between RAS and RAF, but subsequent pathway phosphorylation was extremely rapid. Approximately 80 proteins showed a >2-fold increase in phosphorylation across all experiments and these proteins had a significantly higher median number of phosphorylation sites (~18) relative to total cellular phosphoproteins (~4). Over 60% of EGF-stimulated phosphoproteins were downstream of MAPK and included mediators of cellular processes such as gene transcription, transport, signal transduction and cytoskeletal arrangement. Their phosphorylation was either linear with respect to MAPK activation or biphasic, corresponding to the biphasic signaling seen at the level of the EGFR. This deep, integrated phosphoproteomics data resource should be useful in building mechanistic models of EGFR and MAPK signaling and for understanding how downstream responses are regulated.

Unveiling the human nitroproteome: Protein tyrosine nitration in cell signaling and cancer

Covalent amino acid modification significantly expands protein functional capability in regulating biological processes. Tyrosine residues can undergo phosphorylation, sulfation, adenylation, halogenation, and nitration. These posttranslational modifications (PTMs) result from the actions of specific enzymes: tyrosine kinases, tyrosyl-protein sulfotransferase(s), adenylate transferase(s), oxidoreductases, peroxidases, and metal-heme containing proteins. Whereas phosphorylation, sulfation, and adenylation modify the hydroxyl group of tyrosine, tyrosine halogenation and nitration target the adjacent carbon residues. Because aberrant tyrosine nitration has been associated with human disorders and with animal models of disease, we have created an updated and curated database of 908 human nitrated proteins. We have also analyzed this new resource to provide insight into the role of tyrosine nitration in cancer biology, an area that has not previously been considered in detail. Unexpectedly, we have found that 879 of the 1971 known sites of tyrosine nitration are also sites of phosphorylation suggesting an extensive role for nitration in cell signaling. Overall, the review offers several forward-looking opportunities for future research and new perspectives for understanding the role of tyrosine nitration in cancer biology.

Recent advances in kinase signaling network profiling by mass spectrometry

Mass spectrometry-based phosphoproteomics is currently the leading methodology for the study of global kinase signaling. The scientific community is continuously releasing technological improvements for sensitive and fast identification of phosphopeptides, and their accurate quantification. To interpret large-scale phosphoproteomics data, numerous bioinformatic resources are available that help understanding kinase network functional role in biological systems upon perturbation. Some of these resources are databases of phosphorylation sites, protein kinases and phosphatases; others are bioinformatic algorithms to infer kinase activity, predict phosphosite functional relevance and visualize kinase signaling networks. In this review, we present the latest experimental and bioinformatic tools to profile protein kinase signaling networks and provide examples of their application in biomedicine.

Combining a hybrid chip and tube microfluidic system with fluorescent molecularly imprinted polymer (MIP) core-shell particles for the derivatisation, extraction, and detection of peptides with N-terminating phosphorylated tyrosine

The reliable identification and quantitation of phosphorylated amino acids, peptides and proteins is one of the key challenges in contemporary bioanalytical research, an area of particular interest when attempting to diagnose and treat diseases at an early stage. We have developed a synthetic probe for targeting phosphorylated amino acids, based on core-shell submicron-sized particles consisting of a silica core, coated with a molecularly imprinted polymer (MIP) shell. The MIP layer contains a fluorescent probe crosslinker which binds selectively to phosphorylated tyrosine (pY) moieties with a significant imprinting factor (IF) and responds with a "light-up" fluorescence signal. The bead-based ratiometric detection scheme has been successfully transferred to a microfluidic chip format and its applicability to rapid assays has been exemplarily shown by discriminating a pY-terminating oligopeptide against its non-phosphorylated counterpart. Such miniaturised devices could lead to an automated pY or pY N-terminated peptide measurement system in the future. The setup combines a modular microfluidic system for amino acid derivatisation, extraction (by micropillar co-flow) and selective adsorption and detection with the fluorescent MIP core-shell particle probes. A miniaturised optical assembly for low-light fluorescence measurements was also developed, based on miniaturised opto-electronic parts and optical fibres. The emission from the MIP particles upon binding of pY or pY N-terminated peptides could be monitored in real-time.

Using Linear Motif Database Resources to Identify SH2 Domain Binders

The SH2-binding phosphotyrosine class of short linear motifs (SLiMs) are key conditional regulatory elements, particularly in signaling protein complexes beneath the cell's plasma membrane. In addition to transmitting cellular signaling information, they can also play roles in cellular hijack by invasive pathogens. Researchers can take advantage of bioinformatics tools and resources to predict the motifs at conserved phosphotyrosine residues in regions of intrinsically disordered protein. A candidate SH2-binding motif can be established and assigned to one or more of the SH2 domain subgroups. It is, however, not so straightforward to predict which SH2 domains are capable of binding the given candidate. This is largely due to the cooperative nature of the binding amino acids which enables poorer binding residues to be tolerated when the other residues are optimal. High-throughput peptide arrays are powerful tools used to derive SH2 domain-binding specificity, but they are unable to capture these cooperative effects and also suffer from other shortcomings. Tissue and cell type expression can help to restrict the list of available interactors: for example, some well-studied SH2 domain proteins are only present in the immune cell lineages. In this article, we provide a table of motif patterns and four bioinformatics strategies that introduce a range of tools that can be used in motif hunting in cellular and pathogen proteins. Experimental followup is essential to determine which SH2 domain/motif-containing proteins are the actual functional partners.

A multi-purpose, regenerable, proteome-scale, human phosphoserine resource for phosphoproteomics

Mass-spectrometry-based phosphoproteomics has become indispensable for understanding cellular signaling in complex biological systems. Despite the central role of protein phosphorylation, the field still lacks inexpensive, regenerable, and diverse phosphopeptides with ground-truth phosphorylation positions. Here, we present Iterative Synthetically Phosphorylated Isomers (iSPI), a proteome-scale library of human-derived phosphoserine-containing phosphopeptides that is inexpensive, regenerable, and diverse, with precisely known positions of phosphorylation. We demonstrate possible uses of iSPI, including use as a phosphopeptide standard, a tool to evaluate and optimize phosphorylation-site localization algorithms, and a benchmark to compare performance across data analysis pipelines. We also present AScorePro, an updated version of the AScore algorithm specifically optimized for phosphorylation-site localization in higher energy fragmentation spectra, and the FLR viewer, a web tool for phosphorylation-site localization, to enable community use of the iSPI resource. iSPI and its associated data constitute a useful, multi-purpose resource for the phosphoproteomics community.

Proteomic repository data submission, dissemination, and reuse: key messages

INTRODUCTION

The creation of ProteomeXchange data workflows in 2012 transformed the field of proteomics, consisting of the standardization of data submission and dissemination and enabling the widespread reanalysis of public MS proteomics data worldwide. ProteomeXchange has triggered a growing trend toward public dissemination of proteomics data, facilitating the assessment, reuse, comparative analyses, and extraction of new findings from public datasets. By 2022, the consortium is integrated by PRIDE, PeptideAtlas, MassIVE, jPOST, iProX, and Panorama Public.

AREAS COVERED

Here, we review and discuss the current ecosystem of resources, guidelines, and file formats for proteomics data dissemination and reanalysis. Special attention is drawn to new exciting quantitative and post-translational modification-oriented resources. The challenges and future directions on data depositions including the lack of metadata and cloud-based and high-performance software solutions for fast and reproducible reanalysis of the available data are discussed.

EXPERT OPINION

The success of ProteomeXchange and the amount of proteomics data available in the public domain have triggered the creation and/or growth of other protein knowledgebase resources. Data reuse is a leading, active, and evolving field; supporting the creation of new formats, tools, and workflows to rediscover and reshape the public proteomics data.

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.