The functional landscape of the human phosphoproteome

Post-translational regulation of the mTORC1 pathway: A switch that regulates metabolism-related gene expression

The mechanistic target of rapamycin complex 1 (mTORC1) is a kinase complex that plays a crucial role in coordinating cell growth in response to various signals, including amino acids, growth factors, oxygen, and ATP. Activation of mTORC1 promotes cell growth and anabolism, while its suppression leads to catabolism and inhibition of cell growth, enabling cells to withstand nutrient scarcity and stress. Dysregulation of mTORC1 activity is associated with numerous diseases, such as cancer, metabolic disorders, and neurodegenerative conditions. This review focuses on how post-translational modifications, particularly phosphorylation and ubiquitination, modulate mTORC1 signaling pathway and their consequential implications for pathogenesis. Understanding the impact of phosphorylation and ubiquitination on the mTORC1 signaling pathway provides valuable insights into the regulation of cellular growth and potential therapeutic targets for related diseases.

The logic of protein post-translational modifications (PTMs): Chemistry, mechanisms and evolution of protein regulation through covalent attachments

Protein post-translational modifications (PTMs) play a crucial role in all cellular functions by regulating protein activity, interactions and half-life. Despite the enormous diversity of modifications, various PTM systems show parallels in their chemical and catalytic underpinnings. Here, focussing on modifications that involve the addition of new elements to amino-acid sidechains, I describe historical milestones and fundamental concepts that support the current understanding of PTMs. The historical survey covers selected key research programmes, including the study of protein phosphorylation as a regulatory switch, protein ubiquitylation as a degradation signal and histone modifications as a functional code. The contribution of crucial techniques for studying PTMs is also discussed. The central part of the essay explores shared chemical principles and catalytic strategies observed across diverse PTM systems, together with mechanisms of substrate selection, the reversibility of PTMs by erasers and the recognition of PTMs by reader domains. Similarities in the basic chemical mechanism are highlighted and their implications are discussed. The final part is dedicated to the evolutionary trajectories of PTM systems, beginning with their possible emergence in the context of rivalry in the prokaryotic world. Together, the essay provides a unified perspective on the diverse world of major protein modifications.

Exploration of Nitrotyrosine-Containing Proteins and Peptides by Antibody-Based Enrichment Strategies

Nitrotyrosine, or 3-nitrotyrosine, is an oxidative post-translational modification induced by reactive nitrogen species. Although nitrotyrosine is considered a marker of oxidative stress and has been associated with inflammation, neurodegeneration, cardiovascular disease, and cancer, identification of nitrotyrosine-modified proteins remains challenging owing to its low stoichiometric levels in biological samples. To facilitate a comprehensive analysis of proteins and peptides containing nitrotyrosine, we optimized an immunoprecipitation-based enrichment workflow using a cell line model. The identification of proteins and peptides containing nitrotyrosine residues was carried out after peroxynitrite treatment of cell lysates, which generated modified nitrotyrosine residues on susceptible sites on proteins. We evaluated the efficacy of enriching nitrotyrosine-modified proteins and peptides by employing four different commercially available monoclonal antibodies directed against nitrotyrosine. LC-MS/MS analysis resulted in the identification of 1377 and 1624 nitrotyrosine-containing peptides from protein- and peptide-based enrichment experiments, respectively. Although the yield of nitrotyrosine-containing peptides was higher in experiments where peptides rather than proteins were enriched, we found a substantial proportion (37-65%) of identified nitrotyrosine-containing peptides contained nitrotyrosine at the N-terminus. However, in protein-based immunoprecipitation <9% of nitrotyrosine-containing peptides had nitrotyrosine modification at the N-terminus of the peptide. Overall, our study resulted in the identification of 2603 nitrotyrosine-containing peptides of which >2000 have not previously been reported. We synthesized 101 novel nitrotyrosine-containing peptides identified in our analysis and analyzed them by LC-MS/MS to validate our findings. We have confirmed the validity of 70% of these peptides, as they demonstrated a similarity score exceeding 0.7 when compared to peptides identified through experimental methods. Finally, we also validated the presence of nitrotyrosine modification on PKM and EF2 proteins in peroxynitrite-treated samples by immunoblot analysis. The large catalog presented in this study along with the workflow should facilitate the investigation of nitrotyrosine as an oxidative modification in a variety of settings in greater detail.

Taking Me away: the function of phosphorylation on histone lysine demethylases

Histone lysine demethylases (KDMs) regulate eukaryotic gene transcription by catalysing the removal of methyl groups from histone proteins. These enzymes are intricately regulated by the kinase signalling system in response to internal and external stimuli. Here, we review the mechanisms by which kinase-mediated phosphorylation influence human histone KDM function. These include the changing of histone KDM subcellular localisation or chromatin binding, the altering of protein half-life, changes to histone KDM complex formation that result in histone demethylation, non-histone demethylation or demethylase-independent effects, and effects on histone KDM complex dissociation. We also explore the structural context of phospho-sites on histone KDMs and evaluate how this relates to function.

Distinct functional constraints driving conservation of the cofilin N-terminal regulatory tail

Cofilin family proteins have essential roles in remodeling the cytoskeleton through filamentous actin depolymerization and severing. The short, unstructured N-terminal region of cofilin is critical for actin binding and harbors the major site of inhibitory phosphorylation. Atypically for a disordered sequence, the N-terminal region is highly conserved, but specific aspects driving this conservation are unclear. Here, we screen a library of 16,000 human cofilin N-terminal sequence variants for their capacity to support growth in S. cerevisiae in the presence or absence of the upstream regulator LIM kinase. Results from the screen and biochemical analysis of individual variants reveal distinct sequence requirements for actin binding and regulation by LIM kinase. LIM kinase recognition only partly explains sequence constraints on phosphoregulation, which are instead driven to a large extent by the capacity for phosphorylation to inactivate cofilin. We find loose sequence requirements for actin binding and phosphoinhibition, but collectively they restrict the N-terminus to sequences found in natural cofilins. Our results illustrate how a phosphorylation site can balance potentially competing sequence requirements for function and regulation.

The genetic and dietary landscape of the muscle insulin signalling network

Metabolic disease is caused by a combination of genetic and environmental factors, yet few studies have examined how these factors influence signal transduction, a key mediator of metabolism. Using mass spectrometry-based phosphoproteomics, we quantified 23,126 phosphosites in skeletal muscle of five genetically distinct mouse strains in two dietary environments, with and without acute in vivo insulin stimulation. Almost half of the insulin-regulated phosphoproteome was modified by genetic background on an ordinary diet, and high-fat high-sugar feeding affected insulin signalling in a strain-dependent manner. Our data revealed coregulated subnetworks within the insulin signalling pathway, expanding our understanding of the pathway's organisation. Furthermore, associating diverse signalling responses with insulin-stimulated glucose uptake uncovered regulators of muscle insulin responsiveness, including the regulatory phosphosite S469 on Pfkfb2, a key activator of glycolysis. Finally, we confirmed the role of glycolysis in modulating insulin action in insulin resistance. Our results underscore the significance of genetics in shaping global signalling responses and their adaptability to environmental changes, emphasising the utility of studying biological diversity with phosphoproteomics to discover key regulatory mechanisms of complex traits.

Acquisition and Analysis of DIA-Based Proteomic Data: A Comprehensive Survey in 2023

Data-independent acquisition (DIA) mass spectrometry (MS) has emerged as a powerful technology for high-throughput, accurate, and reproducible quantitative proteomics. This review provides a comprehensive overview of recent advances in both the experimental and computational methods for DIA proteomics, from data acquisition schemes to analysis strategies and software tools. DIA acquisition schemes are categorized based on the design of precursor isolation windows, highlighting wide-window, overlapping-window, narrow-window, scanning quadrupole-based, and parallel accumulation-serial fragmentation-enhanced DIA methods. For DIA data analysis, major strategies are classified into spectrum reconstruction, sequence-based search, library-based search, de novo sequencing, and sequencing-independent approaches. A wide array of software tools implementing these strategies are reviewed, with details on their overall workflows and scoring approaches at different steps. The generation and optimization of spectral libraries, which are critical resources for DIA analysis, are also discussed. Publicly available benchmark datasets covering global proteomics and phosphoproteomics are summarized to facilitate performance evaluation of various software tools and analysis workflows. Continued advances and synergistic developments of versatile components in DIA workflows are expected to further enhance the power of DIA-based proteomics.

Requirement of Site-Specific Tyrosine Phosphorylation of Cortactin in Retinal Neovascularization and Vascular Leakage

BACKGROUND

Retinal neovascularization is a major cause of vision impairment. Therefore, the purpose of this study is to investigate the mechanisms by which hypoxia triggers the development of abnormal and leaky blood vessels.

METHODS

A variety of cellular and molecular approaches as well as tissue-specific knockout mice were used to investigate the role of Cttn (cortactin) in retinal neovascularization and vascular leakage.

RESULTS

We found that VEGFA (vascular endothelial growth factor A) stimulates Cttn phosphorylation at Y421, Y453, and Y470 residues in human retinal microvascular endothelial cells. In addition, we observed that while blockade of Cttn phosphorylation at Y470 inhibited VEGFA-induced human retinal microvascular endothelial cell angiogenic events, suppression of Y421 phosphorylation protected endothelial barrier integrity from disruption by VEGFA. In line with these observations, while blockade of Cttn phosphorylation at Y470 negated oxygen-induced retinopathy-induced retinal neovascularization, interference with Y421 phosphorylation prevented VEGFA/oxygen-induced retinopathy-induced vascular leakage. Mechanistically, while phosphorylation at Y470 was required for its interaction with Arp2/3 and CDC6 facilitating actin polymerization and DNA synthesis, respectively, Cttn phosphorylation at Y421 leads to its dissociation from VE-cadherin, resulting in adherens junction disruption. Furthermore, whereas Cttn phosphorylation at Y470 residue was dependent on Lyn, its phosphorylation at Y421 residue required Syk activation. Accordingly, lentivirus-mediated expression of shRNA targeting Lyn or Syk levels inhibited oxygen-induced retinopathy-induced retinal neovascularization and vascular leakage, respectively.

CONCLUSIONS

The above observations show for the first time that phosphorylation of Cttn is involved in a site-specific manner in the regulation of retinal neovascularization and vascular leakage. In view of these findings, Cttn could be a novel target for the development of therapeutics against vascular diseases such as retinal neovascularization and vascular leakage.

Engineered FHA domains can bind to a variety of Phosphothreonine-containing peptides

Antibodies play a crucial role in monitoring post-translational modifications, like phosphorylation, which regulates protein activity and location; however, commercial polyclonal and monoclonal antibodies have limitations in renewability and engineering compared to recombinant affinity reagents. A scaffold based on the Forkhead-associated domain (FHA) has potential as a selective affinity reagent for this post-translational modification. Engineered FHA domains, termed phosphothreonine-binding domains (pTBDs), with limited cross-reactivity were isolated from an M13 bacteriophage display library by affinity selection with phosphopeptides corresponding to human mTOR, Chk2, 53BP1, and Akt1 proteins. To determine the specificity of the representative pTBDs, we focused on binders to the pT543 phosphopeptide (536-IDEDGENpTQIEDTEP-551) of the DNA repair protein 53BP1. ELISA and western blot experiments have demonstrated the pTBDs are specific to phosphothreonine, demonstrating the potential utility of pTBDs for monitoring the phosphorylation of specific threonine residues in clinically relevant human proteins.

Designed Nanomaterials-Assisted Proteomics and Metabolomics Analysis for In Vitro Diagnosis

In vitro diagnosis (IVD) is pivotal in modern medicine, enabling early disease detection and treatment optimization. Omics technologies, particularly proteomics and metabolomics, offer profound insights into IVD. Despite its significance, omics analyses for IVD face challenges, including low analyte concentrations and the complexity of biological environments. In addition, the direct omics analysis by mass spectrometry (MS) is often hampered by issues like large sample volume requirements and poor ionization efficiency. Through manipulating their size, surface charge, and functionalization, as well as the nanoparticle-fluid incubation conditions, nanomaterials have emerged as a promising solution to extract biomolecules and enhance the desorption/ionization efficiency in MS detection. This review delves into the last five years of nanomaterial applications in omics, focusing on their role in the enrichment, separation, and ionization analysis of proteins and metabolites for IVD. It aims to provide a comprehensive update on nanomaterial design and application in omics, highlighting their potential to revolutionize IVD.

LAFEM: A Scoring Model to Evaluate Functional Landscape of Lysine Acetylome

Protein lysine acetylation is a critical post-translational modification involved in a wide range of biological processes. To date, about 20,000 acetylation sites of Homo sapiens were identified through mass spectrometry-based proteomic technology, but more than 95% of them have unclear functional annotations because of the lack of existing prioritization strategy to assess the functional importance of the acetylation sites on large scale. Hence, we established a lysine acetylation functional evaluating model (LAFEM) by considering eight critical features surrounding lysine acetylation site to high-throughput estimate the functional importance of given acetylation sites. This was achieved by selecting one of the random forest models with the best performance in 10-fold cross-validation on undersampled training dataset. The global analysis demonstrated that the molecular environment of acetylation sites with high acetylation functional scores (AFSs) mainly had the features of larger solvent-accessible surface area, stronger hydrogen bonding-donating abilities, near motif and domain, higher homology, and disordered degree. Importantly, LAFEM performed well in validation dataset and acetylome, showing good accuracy to screen out fitness directly relevant acetylation sites and assisting to explain the core reason for the difference between biological models from the perspective of acetylome. We further used cellular experiments to confirm that, in nuclear casein kinase and cyclin-dependent kinase substrate 1, acetyl-K35 with higher AFS was more important than acetyl-K9 with lower AFS in the proliferation of A549 cells. LAFEM provides a prioritization strategy to large scale discover the fitness directly relevant acetylation sites, which constitutes an unprecedented resource for better understanding of functional acetylome.

Mapping protein states and interactions across the tree of life with co-fractionation mass spectrometry

We present CFdb, a harmonized resource of interaction proteomics data from 411 co-fractionation mass spectrometry (CF-MS) datasets spanning 21,703 fractions. Meta-analysis of this resource charts protein abundance, phosphorylation, and interactions throughout the tree of life, including a reference map of the human interactome. We show how large-scale CF-MS data can enhance analyses of individual CF-MS datasets, and exemplify this strategy by mapping the honey bee interactome.

Structure and function of SPP/SPPL proteases: insights from biochemical evidence and predictive modeling

More than 20 years ago, signal peptide peptidase (SPP) and its homologues, the signal peptide peptidase-like (SPPL) proteases have been identified based on their sequence similarity to presenilins, a related family of intramembrane aspartyl proteases. Other than those for the presenilins, no high-resolution structures for the SPP/SPPL proteases are available. Despite this limitation, over the years bioinformatical and biochemical data have accumulated, which altogether have provided a picture of the overall structure and topology of these proteases, their localization in the cell, the process of substrate recognition, their cleavage mechanism, and their function. Recently, the artificial intelligence-based structure prediction tool AlphaFold has added high-confidence models of the expected fold of SPP/SPPL proteases. In this review, we summarize known structural aspects of the SPP/SPPL family as well as their substrates. Of particular interest are the emerging substrate recognition and catalytic mechanisms that might lead to the prediction and identification of more potential substrates and deeper insight into physiological and pathophysiological roles of proteolysis.

VIPpred: a novel model for predicting variant impact on phosphorylation events driving carcinogenesis

Disrupted protein phosphorylation due to genetic variation is a widespread phenomenon that triggers oncogenic transformation of healthy cells. However, few relevant phosphorylation disruption events have been verified due to limited biological experimental methods. Because of the lack of reliable benchmark datasets, current bioinformatics methods primarily use sequence-based traits to study variant impact on phosphorylation (VIP). Here, we increased the number of experimentally supported VIP events from less than 30 to 740 by manually curating and reanalyzing multi-omics data from 916 patients provided by the Clinical Proteomic Tumor Analysis Consortium. To predict VIP events in cancer cells, we developed VIPpred, a machine learning method characterized by multidimensional features that exhibits robust performance across different cancer types. Our method provided a pan-cancer landscape of VIP events, which are enriched in cancer-related pathways and cancer driver genes. We found that variant-induced increases in phosphorylation events tend to inhibit the protein degradation of oncogenes and promote tumor suppressor protein degradation. Our work provides new insights into phosphorylation-related cancer biology as well as novel avenues for precision therapy.

Proteome-wide base editor screens to assess phosphorylation site functionality in high-throughput

Signaling pathways that drive gene expression are typically depicted as having a dozen or so landmark phosphorylation and transcriptional events. In reality, thousands of dynamic post-translational modifications (PTMs) orchestrate nearly every cellular function, and we lack technologies to find causal links between these vast biochemical pathways and genetic circuits at scale. Here, we describe "signaling-to-transcription network" mapping through the development of PTM-centric base editing coupled to phenotypic screens, directed by temporally-resolved phosphoproteomics. Using T cell activation as a model, we observe hundreds of unstudied phosphorylation sites that modulate NFAT transcriptional activity. We identify the phosphorylation-mediated nuclear localization of the phosphatase PHLPP1 which promotes NFAT but inhibits NFκB activity. We also find that specific phosphosite mutants can alter gene expression in subtle yet distinct patterns, demonstrating the potential for fine-tuning transcriptional responses. Overall, base editor screening of PTM sites provides a powerful platform to dissect PTM function within signaling pathways.

Engrailed 2 triggers the activation of multiple phosphorylation-induced signaling pathways in both transcription-dependent and -independent manners

Homeodomain (HD)-containing proteins are typically recognized as transcription factors. Engrailed 2 (EN2) is an HD-containing protein that is highly expressed in various types of cancers, however, the mechanism underlying the biological function of EN2 is not fully understood. Here, we report a transcription-independent function of EN2 in addition to its role as a transcription factor. EN2 expression leads to the activation of multiple signaling pathways mediated by phosphorylation cascades. A phosphoproteomic analysis revealed that the phosphorylation status of numerous protein sites was altered after EN2 is expressed. Notably, EN2 was shown to interact with a myriad of proteins implicated in phosphorylation signaling cascades, as determined by immunoprecipitation-mass spectrometry (IP-MS). We validated the interaction between EN2 and B55α, the regulatory subunit of the PP2A-B55α complex, and confirmed that the phosphatase activity of the complex was suppressed by EN2 binding. To target EN2-induced malignancy, two kinds of small molecules were utilized to inhibit the EN2-activated NF-κB and AKT signaling pathways. A clear synergistic effect was observed when the activation of the two pathways was simultaneously blocked. Collectively, the data show that EN2 functions in a transcription-independent manner in addition to its role as a transcription factor. This finding may have therapeutic implications in treating esophageal squamous cell carcinoma (ESCC).

Adaptive learning embedding features to improve the predictive performance of SARS-CoV-2 phosphorylation sites

MOTIVATION

The rapid and extensive transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to an unprecedented global health emergency, affecting millions of people and causing an immense socioeconomic impact. The identification of SARS-CoV-2 phosphorylation sites plays an important role in unraveling the complex molecular mechanisms behind infection and the resulting alterations in host cell pathways. However, currently available prediction tools for identifying these sites lack accuracy and efficiency.

RESULTS

In this study, we presented a comprehensive biological function analysis of SARS-CoV-2 infection in a clonal human lung epithelial A549 cell, revealing dramatic changes in protein phosphorylation pathways in host cells. Moreover, a novel deep learning predictor called PSPred-ALE is specifically designed to identify phosphorylation sites in human host cells that are infected with SARS-CoV-2. The key idea of PSPred-ALE lies in the use of a self-adaptive learning embedding algorithm, which enables the automatic extraction of context sequential features from protein sequences. In addition, the tool uses multihead attention module that enables the capturing of global information, further improving the accuracy of predictions. Comparative analysis of features demonstrated that the self-adaptive learning embedding features are superior to hand-crafted statistical features in capturing discriminative sequence information. Benchmarking comparison shows that PSPred-ALE outperforms the state-of-the-art prediction tools and achieves robust performance. Therefore, the proposed model can effectively identify phosphorylation sites assistant the biomedical scientists in understanding the mechanism of phosphorylation in SARS-CoV-2 infection.

AVAILABILITY AND IMPLEMENTATION

PSPred-ALE is available at https://github.com/jiaoshihu/PSPred-ALE and Zenodo (https://doi.org/10.5281/zenodo.8330277).

The regulatory landscape of the yeast phosphoproteome

The cellular ability to react to environmental fluctuations depends on signaling networks that are controlled by the dynamic activities of kinases and phosphatases. Here, to gain insight into these stress-responsive phosphorylation networks, we generated a quantitative mass spectrometry-based atlas of early phosphoproteomic responses in Saccharomyces cerevisiae exposed to 101 environmental and chemical perturbations. We report phosphosites on 59% of the yeast proteome, with 18% of the proteome harboring a phosphosite that is regulated within 5 min of stress exposure. We identify shared and perturbation-specific stress response programs, uncover loss of phosphorylation as an integral early event, and dissect the interconnected regulatory landscape of kinase-substrate networks, as we exemplify with target of rapamycin signaling. We further reveal functional organization principles of the stress-responsive phosphoproteome based on phosphorylation site motifs, kinase activities, subcellular localizations, shared functions and pathway intersections. This information-rich map of 25,000 regulated phosphosites advances our understanding of signaling networks.

Gene editing of SAMHD1 in macrophage-like cells reveals complex relationships between SAMHD1 phospho-regulation, HIV-1 restriction, and cellular dNTP levels

IMPORTANCE

We introduce BLaER1 cells as an alternative myeloid cell model in combination with CRISPR/Cas9-mediated gene editing to study the influence of sterile α motif and HD domain-containing protein 1 (SAMHD1) T592 phosphorylation on anti-viral restriction and the control of cellular dNTP levels in an endogenous, physiologically relevant context. A proper understanding of the mechanism of the anti-viral function of SAMHD1 will provide attractive strategies aiming at selectively manipulating SAMHD1 without affecting other cellular functions. Even more, our toolkit may inspire further genetic analysis and investigation of restriction factors inhibiting retroviruses and their cellular function and regulation, leading to a deeper understanding of intrinsic anti-viral immunity.

Predicting protein and pathway associations for understudied dark kinases using pattern-constrained knowledge graph embedding

The 534 protein kinases encoded in the human genome constitute a large druggable class of proteins that include both well-studied and understudied "dark" members. Accurate prediction of dark kinase functions is a major bioinformatics challenge. Here, we employ a graph mining approach that uses the evolutionary and functional context encoded in knowledge graphs (KGs) to predict protein and pathway associations for understudied kinases. We propose a new scalable graph embedding approach, RegPattern2Vec, which employs regular pattern constrained random walks to sample diverse aspects of node context within a KG flexibly. RegPattern2Vec learns functional representations of kinases, interacting partners, post-translational modifications, pathways, cellular localization, and chemical interactions from a kinase-centric KG that integrates and conceptualizes data from curated heterogeneous data resources. By contextualizing information relevant to prediction, RegPattern2Vec improves accuracy and efficiency in comparison to other random walk-based graph embedding approaches. We show that the predictions produced by our model overlap with pathway enrichment data produced using experimentally validated Protein-Protein Interaction (PPI) data from both publicly available databases and experimental datasets not used in training. Our model also has the advantage of using the collected random walks as biological context to interpret the predicted protein-pathway associations. We provide high-confidence pathway predictions for 34 dark kinases and present three case studies in which analysis of meta-paths associated with the prediction enables biological interpretation. Overall, RegPattern2Vec efficiently samples multiple node types for link prediction on biological knowledge graphs and the predicted associations between understudied kinases, pseudokinases, and known pathways serve as a conceptual starting point for hypothesis generation and testing.

Synaptic Activity Causes Minute-scale Changes in BAF Complex Composition and Function

Genes encoding subunits of the SWI/SNF or BAF ATP-dependent chromatin remodeling complex are among the most enriched for deleterious de novo mutations in intellectual disabilities and autism spectrum disorder, but the causative molecular pathways are not fully known 1,2 . Synaptic activity in neurons is critical for learning and memory and proper neural development 3 . Neural activity prompts calcium influx and transcription within minutes, facilitated in the nucleus by various transcription factors (TFs) and chromatin modifiers 4 . While BAF is required for activity-dependent developmental processes such as dendritic outgrowth 5-7 , the immediate molecular consequences of neural activity on BAF complexes and their functions are unknown. Here we mapped minute-scale biochemical consequences of neural activity, modeled by membrane depolarization of embryonic mouse primary cortical neurons, on BAF complexes. We used acute chemical perturbations of BAF ATPase activity and kinase signaling to define the activity-dependent effects on BAF complexes and activity-dependent BAF functions. Our studies found that BAF complexes change in subunit composition and are selectively phosphorylated within 10 minutes of depolarization. Increased levels of the core PBAF subunit Baf200/ Arid2 , uniquely containing an RFX-like DNA-binding domain, are concurrent with ATPase-dependent opening of chromatin at RFX/X-box motifs. Changes in BAF composition and phosphorylation lead to the regulation of chromatin accessibility for critical neurogenesis TFs. These biochemical effects are a convergent phenomenon downstream of multiple growth factor signaling pathways in mouse neurons and fibroblasts suggesting that BAF integrates signaling information from the membrane. In support of such a membrane-to-nucleus signaling cascade, we also identified a BAF-interacting kinase, Dclk2, whose inhibition attenuates BAF phosphorylation selectively. Our findings support a direct role of BAF complexes in responding to synaptic activity to regulate TF binding and transcription.

SARS-CoV-2 variants evolve convergent strategies to remodel the host response

SARS-CoV-2 variants of concern (VOCs) emerged during the COVID-19 pandemic. Here, we used unbiased systems approaches to study the host-selective forces driving VOC evolution. We discovered that VOCs evolved convergent strategies to remodel the host by modulating viral RNA and protein levels, altering viral and host protein phosphorylation, and rewiring virus-host protein-protein interactions. Integrative computational analyses revealed that although Alpha, Beta, Gamma, and Delta ultimately converged to suppress interferon-stimulated genes (ISGs), Omicron BA.1 did not. ISG suppression correlated with the expression of viral innate immune antagonist proteins, including Orf6, N, and Orf9b, which we mapped to specific mutations. Later Omicron subvariants BA.4 and BA.5 more potently suppressed innate immunity than early subvariant BA.1, which correlated with Orf6 levels, although muted in BA.4 by a mutation that disrupts the Orf6-nuclear pore interaction. Our findings suggest that SARS-CoV-2 convergent evolution overcame human adaptive and innate immune barriers, laying the groundwork to tackle future pandemics.

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.

PaxDb 5.0: Curated Protein Quantification Data Suggests Adaptive Proteome Changes in Yeasts

The "Protein Abundances Across Organisms" database (PaxDb) is an integrative metaresource dedicated to protein abundance levels, in tissue-specific or whole-organism proteomes. PaxDb focuses on computing best-estimate abundances for proteins in normal/healthy contexts and expresses abundance values for each protein in "parts per million" in relation to all other protein molecules in the cell. The uniform data reprocessing, quality scoring, and integrated orthology relations have made PaxDb one of the preferred tools for comparisons between individual datasets, tissues, or organisms. In describing the latest version 5.0 of PaxDb, we particularly emphasize the data integration from various types of raw data and how we expanded the number of organisms and tissue groups as well as the proteome coverage. The current collection of PaxDb includes 831 original datasets from 170 species, including 22 Archaea, 81 Bacteria, and 67 Eukaryota. Apart from detailing the data update, we also present a comparative analysis of the human proteome subset of PaxDb against the two most widely used human proteome data resources: Human Protein Atlas and Genotype-Tissue Expression. Lastly, through our protein abundance data, we reveal an evolutionary trend in the usage of sulfur-containing amino acids in the proteomes of Fungi.

A Multipathway Phosphopeptide Standard for Rapid Phosphoproteomics Assay Development

Recent advances in methodology have made phosphopeptide analysis a tractable problem for many proteomics researchers. There are now a wide variety of robust and accessible enrichment strategies to generate phosphoproteomes while free or inexpensive software tools for quantitation and site localization have simplified phosphoproteome analysis workflow tremendously. As a research group under the Association for Biomolecular Resource Facilities umbrella, the Proteomics Standards Research Group has worked to develop a multipathway phosphopeptide standard based on a mixture of heavy-labeled phosphopeptides designed to enable researchers to rapidly develop assays. This mixture contains 131 mass spectrometry vetted phosphopeptides specifically chosen to cover as many known biologically interesting phosphosites as possible from seven different signaling networks: AMPK signaling, death and apoptosis signaling, ErbB signaling, insulin/insulin-like growth factor-1 signaling, mTOR signaling, PI3K/AKT signaling, and stress (p38/SAPK/JNK) signaling. Here, we describe a characterization of this mixture spiked into a HeLa tryptic digest stimulated with both epidermal growth factor and insulin-like growth factor-1 to activate the MAPK and PI3K/AKT/mTOR pathways. We further demonstrate a comparison of phosphoproteomic profiling of HeLa performed independently in five labs using this phosphopeptide mixture with data-independent acquisition. Despite different experimental and instrumentation processes, we found that labs could produce reproducible, harmonized datasets by reporting measurements as ratios to the standard, while intensity measurements showed lower consistency between labs even after normalization. Our results suggest that widely available, biologically relevant phosphopeptide standards can act as a quantitative "yardstick" across laboratories and sample preparations enabling experimental designs larger than a single laboratory can perform. Raw data files are publicly available in the MassIVE dataset MSV000090564.

Deciphering the functional landscape of phosphosites with deep neural network

Current biochemical approaches have only identified the most well-characterized kinases for a tiny fraction of the phosphoproteome, and the functional assignments of phosphosites are almost negligible. Herein, we analyze the substrate preference catalyzed by a specific kinase and present a novel integrated deep neural network model named FuncPhos-SEQ for functional assignment of human proteome-level phosphosites. FuncPhos-SEQ incorporates phosphosite motif information from a protein sequence using multiple convolutional neural network (CNN) channels and network features from protein-protein interactions (PPIs) using network embedding and deep neural network (DNN) channels. These concatenated features are jointly fed into a heterogeneous feature network to prioritize functional phosphosites. Combined with a series of in vitro and cellular biochemical assays, we confirm that NADK-S48/50 phosphorylation could activate its enzymatic activity. In addition, ERK1/2 are discovered as the primary kinases responsible for NADK-S48/50 phosphorylation. Moreover, FuncPhos-SEQ is developed as an online server.

Integrative analysis of cancer dependency data and comprehensive phosphoproteomics data revealed the EPHA2-PARD3 axis as a cancer vulnerability in KRAS-mutant colorectal cancer

Colorectal cancer (CRC), a common malignant tumour of the gastrointestinal tract, is a life-threatening cancer worldwide. Mutations in KRAS and BRAF, the major driver mutation subtypes in CRC, activate the RAS pathway, contribute to tumorigenesis in CRC and are being investigated as potential therapeutic targets. Despite recent advances in clinical trials targeting KRASG12C or RAS downstream signalling molecules for KRAS-mutant CRC, there is a lack of effective therapeutic interventions. Therefore, understanding the unique molecular characteristics of KRAS-mutant CRC is essential for identifying molecular targets and developing novel therapeutic interventions. We obtained in-depth proteomics and phosphoproteomics quantitative data for over 7900 proteins and 38 700 phosphorylation sites in cells from 35 CRC cell lines and performed informatic analyses, including proteomics-based coexpression analysis and correlation analysis between phosphoproteomics data and cancer dependency scores of the corresponding phosphoproteins. Our results revealed novel dysregulated protein-protein associations enriched specifically in KRAS-mutant cells. Our phosphoproteomics analysis revealed activation of EPHA2 kinase and downstream tight junction signalling in KRAS-mutant cells. Furthermore, the results implicate the phosphorylation site Y378 in the tight junction protein PARD3 as a cancer vulnerability in KRAS-mutant cells. Together, our large-scale phosphoproteomics and proteomics data across 35 steady-state CRC cell lines represent a valuable resource for understanding the molecular characteristics of oncogenic mutations. Our approach to predicting cancer dependency from phosphoproteomics data identified the EPHA2-PARD3 axis as a cancer vulnerability in KRAS-mutant CRC.

PerTurboID, a targeted in situ method reveals the impact of kinase deletion on its local protein environment in the cytoadhesion complex of malaria-causing parasites

Reverse genetics is key to understanding protein function, but the mechanistic connection between a gene of interest and the observed phenotype is not always clear. Here we describe the use of proximity labeling using TurboID and site-specific quantification of biotinylated peptides to measure changes to the local protein environment of selected targets upon perturbation. We apply this technique, which we call PerTurboID, to understand how the Plasmodium falciparum-exported kinase, FIKK4.1, regulates the function of the major virulence factor of the malaria-causing parasite, PfEMP1. We generated independent TurboID fusions of two proteins that are predicted substrates of FIKK4.1 in a FIKK4.1 conditional KO parasite line. Comparing the abundance of site-specific biotinylated peptides between wildtype and kinase deletion lines reveals the differential accessibility of proteins to biotinylation, indicating changes to localization, protein-protein interactions, or protein structure which are mediated by FIKK4.1 activity. We further show that FIKK4.1 is likely the only FIKK kinase that controls surface levels of PfEMP1, but not other surface antigens, on the infected red blood cell under standard culture conditions. We believe PerTurboID is broadly applicable to study the impact of genetic or environmental perturbation on a selected cellular niche.

Gene editing of SAMHD1 in macrophage-like cells reveals complex relationships between SAMHD1 phospho-regulation, HIV-1 restriction and cellular dNTP levels

Sterile α motif (SAM) and HD domain-containing protein 1 (SAMHD1) is a dNTP triphosphate triphosphohydrolase (dNTPase) and a potent restriction factor for immunodeficiency virus 1 (HIV-1), active in myeloid and resting CD4+ T cells. The anti-viral activity of SAMHD1 is regulated by dephosphorylation of the residue T592. However, the impact of T592 phosphorylation on dNTPase activity is still under debate. Whether additional cellular functions of SAMHD1 impact anti-viral restriction is not completely understood. We report BLaER1 cells as a novel human macrophage HIV-1 infection model combined with CRISPR/Cas9 knock-in (KI) introducing specific mutations into the SAMHD1 locus to study mutations in a physiological context. Transdifferentiated BLaER1 cells harbor active dephosphorylated SAMHD1 that blocks HIV-1 reporter virus infection. As expected, homozygous T592E mutation, but not T592A, relieved a block to HIV-1 reverse transcription. Co-delivery of VLP-Vpx to SAMHD1 T592E KI mutant cells did not further enhance HIV-1 infection indicating the absence of an additional SAMHD1-mediated antiviral activity independent of T592 de-phosphorylation. T592E KI cells retained dNTP levels similar to WT cells indicating uncoupling of anti-viral and dNTPase activity of SAMHD1. The integrity of the catalytic site in SAMHD1 was critical for anti-viral activity, yet poor correlation of HIV-1 restriction and global cellular dNTP levels was observed in cells harboring catalytic core mutations. Together, we emphasize the complexity of the relationship between HIV-1 restriction, SAMHD1 enzymatic function and T592 phospho-regulation and provide novel tools for investigation in an endogenous and physiological context.

Human Triosephosphate Isomerase Is a Potential Target in Cancer Due to Commonly Occurring Post-Translational Modifications

Cancer involves a series of diseases where cellular growth is not controlled. Cancer is a leading cause of death worldwide, and the burden of cancer incidence and mortality is rapidly growing, mainly in developing countries. Many drugs are currently used, from chemotherapeutic agents to immunotherapy, among others, along with organ transplantation. Treatments can cause severe side effects, including remission and progression of the disease with serious consequences. Increased glycolytic activity is characteristic of cancer cells. Triosephosphate isomerase is essential for net ATP production in the glycolytic pathway. Notably, some post-translational events have been described that occur in human triosephosphate isomerase in which functional and structural alterations are provoked. This is considered a window of opportunity, given the differences that may exist between cancer cells and their counterpart in normal cells concerning the glycolytic enzymes. Here, we provide elements that bring out the potential of triosephosphate isomerase, under post-translational modifications, to be considered an efficacious target for treating cancer.

Understanding the Human RECQ5 Helicase-Connecting the Dots from DNA to Clinics

RECQ5, a member of the conserved RECQ helicase family, is the sole human RECQ homolog that has not been linked to a hereditary developmental syndrome. Nonetheless, dysregulation of RECQ5 has emerged as a significant clinical concern, being linked to cancer predisposition, cardiovascular disease, and inflammation. In cells, RECQ5 assumes a crucial role in the regulation of DNA repair pathways, particularly in the repair of DNA double-strand breaks and inter-strand DNA crosslinks. Moreover, RECQ5 exhibits a capacity to modulate gene expression by interacting with transcription machineries and their co-regulatory proteins, thus safeguarding against transcription-induced DNA damage. This review aims to provide an overview of the multifaceted functions of RECQ5 and its implications in maintaining genomic stability. We will discuss the potential effects of clinical variants of RECQ5 on its cellular functions and their underlying mechanisms in the pathogenesis of cancer and cardiovascular disease. We will review the impact of RECQ5 variants in the field of pharmacogenomics, specifically their influence on drug responses, which may pave the way for novel therapeutic interventions targeting RECQ5 in human diseases.

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.

Substrate and phosphorylation site selection by phosphoprotein phosphatases

Dynamic protein phosphorylation and dephosphorylation are essential regulatory mechanisms that ensure proper cellular signaling and biological functions. Deregulation of either reaction has been implicated in several human diseases. Here, we focus on the mechanisms that govern the specificity of the dephosphorylation reaction. Most cellular serine/threonine dephosphorylation is catalyzed by 13 highly conserved phosphoprotein phosphatase (PPP) catalytic subunits, which form hundreds of holoenzymes by binding to regulatory and scaffolding subunits. PPP holoenzymes recognize phosphorylation site consensus motifs and interact with short linear motifs (SLiMs) or structural elements distal to the phosphorylation site. We review recent advances in understanding the mechanisms of PPP site-specific dephosphorylation preference and substrate recruitment and highlight examples of their interplay in the regulation of cell division.

Systematic analysis of the impact of phosphorylation and O-GlcNAcylation on protein subcellular localization

The subcellular localization of proteins is critical for their functions in eukaryotic cells and is tightly correlated with protein modifications. Here, we comprehensively investigate the nuclear-cytoplasmic distributions of the phosphorylated, O-GlcNAcylated, and non-modified forms of proteins to dissect the correlation between protein distribution and modifications. Phosphorylated and O-GlcNAcylated proteins have overall higher nuclear distributions than non-modified ones. Different distributions among the phosphorylated, O-GlcNAcylated, and non-modified forms of proteins are associated with protein size, structure, and function, as well as local environment and adjacent residues around modification sites. Moreover, we perform site-mutagenesis experiments using phosphomimetic and phospho-null mutants of two proteins to validate the proteomic results. Additionally, the effects of the OGT/OGA inhibition on glycoprotein distribution are systematically investigated, and the distribution changes of glycoproteins are related to their abundance changes under the inhibitions. Systematic investigation of the relationship between protein modification and localization advances our understanding of protein functions.

Large-scale phosphomimetic screening identifies phospho-modulated motif-based protein interactions

Phosphorylation is a ubiquitous post-translation modification that regulates protein function by promoting, inhibiting or modulating protein-protein interactions. Hundreds of thousands of phosphosites have been identified but the vast majority have not been functionally characterised and it remains a challenge to decipher phosphorylation events modulating interactions. We generated a phosphomimetic proteomic peptide-phage display library to screen for phosphosites that modulate short linear motif-based interactions. The peptidome covers ~13,500 phospho-serine/threonine sites found in the intrinsically disordered regions of the human proteome. Each phosphosite is represented as wild-type and phosphomimetic variant. We screened 71 protein domains to identify 248 phosphosites that modulate motif-mediated interactions. Affinity measurements confirmed the phospho-modulation of 14 out of 18 tested interactions. We performed a detailed follow-up on a phospho-dependent interaction between clathrin and the mitotic spindle protein hepatoma-upregulated protein (HURP), demonstrating the essentiality of the phospho-dependency to the mitotic function of HURP. Structural characterisation of the clathrin-HURP complex elucidated the molecular basis for the phospho-dependency. Our work showcases the power of phosphomimetic ProP-PD to discover novel phospho-modulated interactions required for cellular function.

Recent progress in quantitative phosphoproteomics

INTRODUCTION

Protein phosphorylation is a critical post-translational modification involved in the regulation of numerous cellular processes from signal transduction to modulation of enzyme activities. Knowledge of dynamic changes of phosphorylation levels during biological processes, under various treatments or between healthy and disease models is fundamental for understanding the role of each phosphorylation event. Thereby, LC-MS/MS based technologies in combination with quantitative proteomics strategies evolved as a powerful strategy to investigate the function of individual protein phosphorylation events.

AREAS COVERED

State-of-the-art labeling techniques including stable isotope and isobaric labeling provide precise and accurate quantification of phosphorylation events. Here, we review the strengths and limitations of recent quantification methods and provide examples based on current studies, how quantitative phosphoproteomics can be further optimized for enhanced analytic depth, dynamic range, site localization, and data integrity. Specifically, reducing the input material demands is key to a broader implementation of quantitative phosphoproteomics, not least for clinical samples.

EXPERT OPINION

Despite quantitative phosphoproteomics is one of the most thriving fields in the proteomics world, many challenges still have to be overcome to facilitate even deeper and more comprehensive analyses as required in the current research, especially at single cell levels and in clinical diagnostics.

An optogenetic-phosphoproteomic study reveals dynamic Akt1 signaling profiles in endothelial cells

The serine/threonine kinase AKT is a central node in cell signaling. While aberrant AKT activation underlies the development of a variety of human diseases, how different patterns of AKT-dependent phosphorylation dictate downstream signaling and phenotypic outcomes remains largely enigmatic. Herein, we perform a systems-level analysis that integrates methodological advances in optogenetics, mass spectrometry-based phosphoproteomics, and bioinformatics to elucidate how different intensity, duration, and pattern of Akt1 stimulation lead to distinct temporal phosphorylation profiles in vascular endothelial cells. Through the analysis of ~35,000 phosphorylation sites across multiple conditions precisely controlled by light stimulation, we identify a series of signaling circuits activated downstream of Akt1 and interrogate how Akt1 signaling integrates with growth factor signaling in endothelial cells. Furthermore, our results categorize kinase substrates that are preferably activated by oscillating, transient, and sustained Akt1 signals. We validate a list of phosphorylation sites that covaried with Akt1 phosphorylation across experimental conditions as potential Akt1 substrates. Our resulting dataset provides a rich resource for future studies on AKT signaling and dynamics.

Hybrid-DIA: intelligent data acquisition integrates targeted and discovery proteomics to analyze phospho-signaling in single spheroids

Achieving sufficient coverage of regulatory phosphorylation sites by mass spectrometry (MS)-based phosphoproteomics for signaling pathway reconstitution is challenging, especially when analyzing tiny sample amounts. To address this, we present a hybrid data-independent acquisition (DIA) strategy (hybrid-DIA) that combines targeted and discovery proteomics through an Application Programming Interface (API) to dynamically intercalate DIA scans with accurate triggering of multiplexed tandem mass spectrometry (MSx) scans of predefined (phospho)peptide targets. By spiking-in heavy stable isotope labeled phosphopeptide standards covering seven major signaling pathways, we benchmark hybrid-DIA against state-of-the-art targeted MS methods (i.e., SureQuant) using EGF-stimulated HeLa cells and find the quantitative accuracy and sensitivity to be comparable while hybrid-DIA also profiles the global phosphoproteome. To demonstrate the robustness, sensitivity, and biomedical potential of hybrid-DIA, we profile chemotherapeutic agents in single colon carcinoma multicellular spheroids and evaluate the phospho-signaling difference of cancer cells in 2D vs 3D culture.

xProtCAS: A Toolkit for Extracting Conserved Accessible Surfaces from Protein Structures

The identification of protein surfaces required for interaction with other biomolecules broadens our understanding of protein function, their regulation by post-translational modification, and the deleterious effect of disease mutations. Protein interaction interfaces are often identifiable as patches of conserved residues on a protein's surface. However, finding conserved accessible surfaces on folded regions requires an understanding of the protein structure to discriminate between functional and structural constraints on residue conservation. With the emergence of deep learning methods for protein structure prediction, high-quality structural models are now available for any protein. In this study, we introduce tools to identify conserved surfaces on AlphaFold2 structural models. We define autonomous structural modules from the structural models and convert these modules to a graph encoding residue topology, accessibility, and conservation. Conserved surfaces are then extracted using a novel eigenvector centrality-based approach. We apply the tool to the human proteome identifying hundreds of uncharacterised yet highly conserved surfaces, many of which contain clinically significant mutations. The xProtCAS tool is available as open-source Python software and an interactive web server.

Orchestration of Mitochondrial Function and Remodeling by Post-Translational Modifications Provide Insight into Mechanisms of Viral Infection

The regulation of mitochondria structure and function is at the core of numerous viral infections. Acting in support of the host or of virus replication, mitochondria regulation facilitates control of energy metabolism, apoptosis, and immune signaling. Accumulating studies have pointed to post-translational modification (PTM) of mitochondrial proteins as a critical component of such regulatory mechanisms. Mitochondrial PTMs have been implicated in the pathology of several diseases and emerging evidence is starting to highlight essential roles in the context of viral infections. Here, we provide an overview of the growing arsenal of PTMs decorating mitochondrial proteins and their possible contribution to the infection-induced modulation of bioenergetics, apoptosis, and immune responses. We further consider links between PTM changes and mitochondrial structure remodeling, as well as the enzymatic and non-enzymatic mechanisms underlying mitochondrial PTM regulation. Finally, we highlight some of the methods, including mass spectrometry-based analyses, available for the identification, prioritization, and mechanistic interrogation of PTMs.

PARPs and ADP-ribosylation: Deciphering the complexity with molecular tools

PARPs catalyze ADP-ribosylation-a post-translational modification that plays crucial roles in biological processes, including DNA repair, transcription, immune regulation, and condensate formation. ADP-ribosylation can be added to a wide range of amino acids with varying lengths and chemical structures, making it a complex and diverse modification. Despite this complexity, significant progress has been made in developing chemical biology methods to analyze ADP-ribosylated molecules and their binding proteins on a proteome-wide scale. Additionally, high-throughput assays have been developed to measure the activity of enzymes that add or remove ADP-ribosylation, leading to the development of inhibitors and new avenues for therapy. Real-time monitoring of ADP-ribosylation dynamics can be achieved using genetically encoded reporters, and next-generation detection reagents have improved the precision of immunoassays for specific forms of ADP-ribosylation. Further development and refinement of these tools will continue to advance our understanding of the functions and mechanisms of ADP-ribosylation in health and disease.

Small-sample learning reveals propionylation in determining global protein homeostasis

Proteostasis is fundamental for maintaining organismal health. However, the mechanisms underlying its dynamic regulation and how its disruptions lead to diseases are largely unclear. Here, we conduct in-depth propionylomic profiling in Drosophila, and develop a small-sample learning framework to prioritize the propionylation at lysine 17 of H2B (H2BK17pr) to be functionally important. Mutating H2BK17 which eliminates propionylation leads to elevated total protein level in vivo. Further analyses reveal that H2BK17pr modulates the expression of 14.7-16.3% of genes in the proteostasis network, and determines global protein level by regulating the expression of genes involved in the ubiquitin-proteasome system. In addition, H2BK17pr exhibits daily oscillation, mediating the influences of feeding/fasting cycles to drive rhythmic expression of proteasomal genes. Our study not only reveals a role of lysine propionylation in regulating proteostasis, but also implements a generally applicable method which can be extended to other issues with little prior knowledge.

A basic phosphoproteomic-DIA workflow integrating precise quantification of phosphosites in systems biology

Phosphorylation is one of the most important post-translational modifications (PTMs) of proteins, governing critical protein functions. Most human proteins have been shown to undergo phosphorylation, and phosphoproteomic studies have been widely applied due to recent advancements in high-resolution mass spectrometry technology. Although the experimental workflow for phosphoproteomics has been well-established, it would be useful to optimize and summarize a detailed, feasible protocol that combines phosphoproteomics and data-independent acquisition (DIA), along with follow-up data analysis procedures due to the recent instrumental and bioinformatic advances in measuring and understanding tens of thousands of site-specific phosphorylation events in a single experiment. Here, we describe an optimized Phos-DIA protocol, from sample preparation to bioinformatic analysis, along with practical considerations and experimental configurations for each step. The protocol is designed to be robust and applicable for both small-scale phosphoproteomic analysis and large-scale quantification of hundreds of samples for studies in systems biology and systems medicine.

Decrypting drug actions and protein modifications by dose- and time-resolved proteomics

Although most cancer drugs modulate the activities of cellular pathways by changing posttranslational modifications (PTMs), little is known regarding the extent and the time- and dose-response characteristics of drug-regulated PTMs. In this work, we introduce a proteomic assay called decryptM that quantifies drug-PTM modulation for thousands of PTMs in cells to shed light on target engagement and drug mechanism of action. Examples range from detecting DNA damage by chemotherapeutics, to identifying drug-specific PTM signatures of kinase inhibitors, to demonstrating that rituximab kills CD20-positive B cells by overactivating B cell receptor signaling. DecryptM profiling of 31 cancer drugs in 13 cell lines demonstrates the broad applicability of the approach. The resulting 1.8 million dose-response curves are provided as an interactive molecular resource in ProteomicsDB.

Integrated analysis of SR-like protein kinases Sky1 and Sky2 links signaling networks with transcriptional regulation in Candida albicans

Fungal infections are a major global health burden where Candida albicans is among the most common fungal pathogen in humans and is a common cause of invasive candidiasis. Fungal phenotypes, such as those related to morphology, proliferation and virulence are mainly driven by gene expression, which is primarily regulated by kinase signaling cascades. Serine-arginine (SR) protein kinases are highly conserved among eukaryotes and are involved in major transcriptional processes in human and S. cerevisiae. Candida albicans harbors two SR protein kinases, while Sky2 is important for metabolic adaptation, Sky1 has similar functions as in S. cerevisiae. To investigate the role of these SR kinases for the regulation of transcriptional responses in C. albicans, we performed RNA sequencing of sky1Δ and sky2Δ and integrated a comprehensive phosphoproteome dataset of these mutants. Using a Systems Biology approach, we study transcriptional regulation in the context of kinase signaling networks. Transcriptomic enrichment analysis indicates that pathways involved in the regulation of gene expression are downregulated and mitochondrial processes are upregulated in sky1Δ. In sky2Δ, primarily metabolic processes are affected, especially for arginine, and we observed that arginine-induced hyphae formation is impaired in sky2Δ. In addition, our analysis identifies several transcription factors as potential drivers of the transcriptional response. Among these, a core set is shared between both kinase knockouts, but it appears to regulate different subsets of target genes. To elucidate these diverse regulatory patterns, we created network modules by integrating the data of site-specific protein phosphorylation and gene expression with kinase-substrate predictions and protein-protein interactions. These integrated signaling modules reveal shared parts but also highlight specific patterns characteristic for each kinase. Interestingly, the modules contain many proteins involved in fungal morphogenesis and stress response. Accordingly, experimental phenotyping shows a higher resistance to Hygromycin B for sky1Δ. Thus, our study demonstrates that a combination of computational approaches with integration of experimental data can offer a new systems biological perspective on the complex network of signaling and transcription. With that, the investigation of the interface between signaling and transcriptional regulation in C. albicans provides a deeper insight into how cellular mechanisms can shape the phenotype.

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.

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.

FCGR2A as one novel potential target for poor survival prognosis of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cell carcinoma. Immunoglobulin FcγRIIa receptor (FCGR2A) has been implicated in various cancers, however, its role on ccRCC is not well studied. A total of 151 patients with ccRCC were recruited for the study. Cox proportional hazards regression analysis was performed to calculate the hazard radios of FCGR2A expression and tumor characteristics. Pathological changes associated with ccRCC in tumor tissue sections were analyzed by hematoxylin-eosin staining. Immunohistochemical and immunofluorescence staining were used to detect the protein expression of FCGR2A in the tissue sections. Correlation between the expression of FCGR2A and the overall survival (OS) of ccRCC patients was analyzed by biological process neural network and support vector machine. The expression of FCGR2A was significantly correlated with the TNM of tumor, family history of ccRCC and Fuhrman stage of ccRCC. Patients with high FCGR2A expression in the tumor tissue, had poorer OS than the patients with low and moderate FCGR2A expression. The Receiver operating characteristic curve showed that FCGR2A can be used as a sensitive and specific biomarker for the diagnosis of ccRCC. Western blotting revealed that the FCGR2A was expressed at higher levels in the ccRCC tissues. Biological process neural network and support vector machine fitting showed that the R2 between FCGR2A and survival time of ccRCC patients was 0.8429 and 0.7669, respectively. FCGR2A is highly expressed in ccRCC, higher expression of FCGR2A is associated with poorer OS of ccRCC.

Pan-Cancer landscape of protein activities identifies drivers of signalling dysregulation and patient survival

Genetic alterations in cancer cells trigger oncogenic transformation, a process largely mediated by the dysregulation of kinase and transcription factor (TF) activities. While the mutational profiles of thousands of tumours have been extensively characterised, the measurements of protein activities have been technically limited until recently. We compiled public data of matched genomics and (phospho)proteomics measurements for 1,110 tumours and 77 cell lines that we used to estimate activity changes in 218 kinases and 292 TFs. Co-regulation of kinase and TF activities reflects previously known regulatory relationships and allows us to dissect genetic drivers of signalling changes in cancer. We find that loss-of-function mutations are not often associated with the dysregulation of downstream targets, suggesting frequent compensatory mechanisms. Finally, we identified the activities most differentially regulated in cancer subtypes and showed how these can be linked to differences in patient survival. Our results provide broad insights into the dysregulation of protein activities in cancer and their contribution to disease severity.