Benchmarking common quantification strategies for large-scale phosphoproteomics

Tandem mass tag-based proteomics analysis to reveal growth stage-dependent pathways in Dendrobium nobile Lindl

OBJECTIVE

This study aimed to analyze differentially proteins at various growth stages of Dendrobium nobile Lindl and attempt to find some possible functional proteins related to plant growth or pharmacological activity.

METHODS

The samples were grouped into two categories based on their growth periods as 2-3 years (S1) and 7-8 years (S2), respectively. Tandem Mass Tag(TMT) labeling-based quantitative proteomics combined LC-MS/MS was applied to identify differential protein expression at various growth stages of Dendrobium nobile Lindl. Those proteins were analyzed by various bioinformatics methods. The activities of several antioxidant enzymes including superoxide dismutase(SOD), peroxidase (POD) and catalase (CAT) in the plant were specifically examined using commercially available assay kits.

RESULTS

A total of 6032 proteins were identified with 283 differential proteins related to 168 up-regulated and 115 down-regulated. KEGG pathway enrichment analysis revealed that proteins involved in heat shock response, phenylpropanoid biosynthesis, and antioxidant activity showed significant changes across the growth stages. Specifically, a decrease in small heat shock proteins (sHSPs) was observed in older plants, potentially reducing their stress resilience, while proteins involved in lignin biosynthesis, such as SOD, CAT, and POD, were upregulated, suggesting improved stress response.

CONCLUSION

There are 283 differential proteins with diversiform function between different growth stages. Some upregulated antioxidant enzymes contribute to Dendrobium's ability to combat oxidative stress in older plants. These findings provide insights into how protein expression varies with growth stage, offering scientific support for determining optimal harvesting periods or pharmacological mechanism for Dendrobium nobile Lindl.

PCP-B peptides and CrRLK1L receptor kinases control pollination via pH gating of aquaporins in Arabidopsis

During pollen-stigma interaction, pollen coat protein B-class peptides (PCP-Bs) compete with stigmatic rapid alkalinization factor (RALF) for interaction with FERONIA/ANJEA receptor kinases (FER/ANJ), stimulating pollen hydration and germination. However, the molecular mechanism underlying PCP-Bs-induced, FER/ANJ-regulated compatible responses remains largely unknown. Through PCP-Bγ-induced phosphoproteomic analysis, we characterized a series of pollination-related signaling pathways regulated by FER/ANJ. Interestingly, on stigmatic papillary cells, pollen PCP-Bγ induced an elevation in cytosolic pH near the plasma membrane (PM), sustained by stigmatic RALF23/33 through regulation of the autoinhibited H+-ATPase 1/2 (AHA1/2) activity. We further found that RALFs/PCP-Bs and FER/ANJ regulated the pH alterations via phosphorylation of AHA1/2 C terminus. Furthermore, RALF23/33-FER/ANJ maintained the protonation of H197 in plasma membrane intrinsic proteins (PIPs), whereas PCP-B relieved the protonation through AHA activity. Altogether, this study reveals that pollen PCP-Bs trigger FER/ANJ-controlled compatible responses, particularly the opening of aquaporins via AHA-mediated pH changes, thereby facilitating pollen hydration in Arabidopsis.

Metal ion-enhanced ZIC-cHILIC StageTip for N-Glycoproteomic and Phosphoproteomic Profiling in EGFR-mutated Lung Cancer Cells

Surface glycosylation and intracellular phosphorylation regulates the cell-cell communication and signaling cascades. Due to complex glycosylation and dynamic phosphorylation, exploring their interplay remains technically challenging. In this study, we reported a tandem ZIC-cHILIC StageTip strategy for streamlined and simultaneous (sialo)glycoproteomic and phosphoproteomic profiling. We first demonstrated that Fe ions expand the utility of ZIC-cHILIC strategy to phosphoproteomic analysis with greatly enhanced >4-fold coverage and high specificity for mono-phosphopeptides (95%). The Fe-ZIC-cHILIC tandem tips, leveraging stepwise fractionation, enable large-scale coverage of 10,536 glycopeptides, including highly confident 4,285 sialoglycopeptpides, and 11,329 phosphopeptides in a single cell type. To study the mechanism underlying the tyrosine kinase inhibitor (TKI) resistance in non-small cell lung cancer (NSCLC), application of the strategy to 4 NSCLC cells harboring different EGFR mutations reveals significantly differential 1,559 glycopeptides and 1,949 phosphopeptides either in EGFR mutation or TKI resistant cells. Without protein immunoprecipitation, the approach identified FDA-approved drug targets, such as EGFR, ERBB2, MET, and integrin family members. Most prominent alterations were observed in EGFR (auto-phosphorylation Y1197 and 10 bi- and triantennary fucosyl-sialo glycans at N603), downstream PI3K-Akt pathway (ERBB2-T1240, MET-S990/T992, AKT-S124/S126) and integrin family (sialo-fucosyl glycans), suggesting site-specific alteration between N-glycosylation and phosphorylation interplay in the TKI resistant L858R-T790M mutant NSCLC cells. The glycoproteomic and phosphoproteomic landscape may help to unravel the complex modification alterations underlying the resistant mechanism, offering insights for improving therapeutic strategies and patient outcomes.

Mass-spectrometry-based proteomics: from single cells to clinical applications

Mass-spectrometry (MS)-based proteomics has evolved into a powerful tool for comprehensively analysing biological systems. Recent technological advances have markedly increased sensitivity, enabling single-cell proteomics and spatial profiling of tissues. Simultaneously, improvements in throughput and robustness are facilitating clinical applications. In this Review, we present the latest developments in proteomics technology, including novel sample-preparation methods, advanced instrumentation and innovative data-acquisition strategies. We explore how these advances drive progress in key areas such as protein-protein interactions, post-translational modifications and structural proteomics. Integrating artificial intelligence into the proteomics workflow accelerates data analysis and biological interpretation. We discuss the application of proteomics to single-cell analysis and spatial profiling, which can provide unprecedented insights into cellular heterogeneity and tissue architecture. Finally, we examine the transition of proteomics from basic research to clinical practice, including biomarker discovery in body fluids and the promise and challenges of implementing proteomics-based diagnostics. This Review provides a broad and high-level overview of the current state of proteomics and its potential to revolutionize our understanding of biology and transform medical practice.

Label-Free Quantitative Phosphoproteomics in the Fission Yeast Schizosaccharomyces pombe

Protein phosphorylation is a dynamic, reversible posttranslational modification that plays an important role in the regulation of cell signaling. Recently, label-free quantitative (LFQ) phosphoproteomics has become a powerful tool to analyze the phosphorylation of proteins within complex samples. In this chapter, we describe how to apply LFQ phosphoproteomics that is based on Fe-IMAC phosphopeptide enrichment followed by strong anion exchange (SAX) and porous graphitic carbon (PGC) fractionation strategies for identification and quantification of changes in the phosphoproteome in the fission yeast Schizosaccharomyces pombe.

Suppressed ORAI1-STIM1-dependent Ca2+ entry by protein kinase C isoforms regulating platelet procoagulant activity

Agonist-induced rises in cytosolic Ca2+ control most platelet responses in thrombosis and hemostasis. In human platelets, we earlier demonstrated that the ORAI1-STIM1 pathway is a major component of extracellular Ca2+ entry, in particular when induced via the ITAM-linked collagen receptor, glycoprotein VI (GPVI). In the present article, using functionally defective platelets from patients with a loss-of-function mutation in ORAI1 or STIM1, we show that Ca2+ entry induced by the endoplasmic reticulum ATPase inhibitor, thapsigargin, fully relies on this pathway. We demonstrate that both the GPVI-induced and thapsigargin-induced Ca2+ entry are strongly suppressed by protein kinase C (PKC) activation while leaving intracellular Ca2+ mobilization unchanged. Comparing the effects of a PKC inhibitory panel pointed to redundant roles of beta and theta PKC isoforms in Ca2+-entry suppression. In contrast, tyrosine kinases positively regulated GPVI-induced Ca2+ entry and mobilization. Label-free and stable isotope phosphoproteome analysis of GPVI-stimulated platelets suggested a regulatory role of bridging integrator-2 (BIN2), known as an important mediator of the ORAI1-STIM1 pathway in mouse platelets. Identified were 25 to 45 regulated phospho-sites in BIN2 and 16 to 18 in STIM1. Five of these were characterized as direct substrates of the expressed PKC isoforms alpha, beta delta, and theta. Functional platelet testing indicated that the downregulation of Ca2+ entry by PKC resulted in suppressed phosphatidylserine exposure and plasmatic thrombin generation. Conclusively, our results indicate that in platelets multiple PKC isoforms constrain the store-regulated Ca2+ entry via ORAI1-BIN2-STIM1, and hence downregulate platelet-dependent coagulation.

Identifying therapeutic strategies for triple-negative breast cancer via phosphoproteomics

INTRODUCTION

Given the poor prognosis of patients with TNBC, it is urgent to identify new biomarkers and therapeutic targets to enable personalized treatment strategies and improve patient survival. Comprehensive insights beyond genomic and transcriptomic analysis are crucial to improved outcomes for patients. As proteins are the workhorses of cellular function with their activity primarily regulated by phosphorylation, advanced phosphoproteomics techniques, such as mass spectrometry and antibody arrays, are essential for elucidating kinase signaling pathways that drive TNBC progression and contribute to therapy resistance.

AREA COVERED

This review discusses the critical need to integrate phosphoproteomics into TNBC research, evaluates commonly used technologies and their applications, and explores their advantages and limitations. We highlight significant findings from phosphoproteomic analyses in TNBC and address the challenges of implementing these technologies into clinical practice.

EXPERT OPINION

Rapid advances in phosphoproteomics analysis facilitate subtype stratification, adaptive response monitoring, and identification of biomarkers and therapeutic targets in TNBC. However, challenges in analyzing protein phosphorylation, especially in deep spatially resolved analysis of malignant cells and the tumor ecosystem, hinder the translation of phosphoproteomics to the CLIA setting. Nonetheless, phosphoproteomics offers a powerful tool that, when integrated into routine clinical practice, has the potential to revolutionize patient care.

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.

Proteome-Scale Tissue Mapping Using Mass Spectrometry Based on Label-Free and Multiplexed Workflows

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ∼3500 proteins at a spatial resolution of 50 μm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provides robust protein quantifications in identifying differentially abundant proteins and spatially covariable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial coexpression analysis.

Spatial proteomics: unveiling the multidimensional landscape of protein localization in human diseases

Spatial proteomics is a multidimensional technique that studies the spatial distribution and function of proteins within cells or tissues across both spatial and temporal dimensions. This field multidimensionally reveals the complex structure of the human proteome, including the characteristics of protein spatial distribution, dynamic protein translocation, and protein interaction networks. Recently, as a crucial method for studying protein spatial localization, spatial proteomics has been applied in the clinical investigation of various diseases. This review summarizes the fundamental concepts and characteristics of tissue-level spatial proteomics, its research progress in common human diseases such as cancer, neurological disorders, cardiovascular diseases, autoimmune diseases, and anticipates its future development trends. The aim is to highlight the significant impact of spatial proteomics on understanding disease pathogenesis, advancing diagnostic methods, and developing potential therapeutic targets in clinical research.

Proteomic approaches for protein kinase substrate identification in Apicomplexa

Apicomplexa is a phylum of protist parasites, notable for causing life-threatening diseases including malaria, toxoplasmosis, cryptosporidiosis, and babesiosis. Apicomplexan pathogenesis is generally a function of lytic replication, dissemination, persistence, host cell modification, and immune subversion. Decades of research have revealed essential roles for apicomplexan protein kinases in establishing infections and promoting pathogenesis. Protein kinases modify their substrates by phosphorylating serine, threonine, tyrosine, or other residues, resulting in rapid functional changes in the target protein. Post-translational modification by phosphorylation can activate or inhibit a substrate, alter its localization, or promote interactions with other proteins or ligands. Deciphering direct kinase substrates is crucial to understand mechanisms of kinase signaling, yet can be challenging due to the transient nature of kinase phosphorylation and potential for downstream indirect phosphorylation events. However, with recent advances in proteomic approaches, our understanding of kinase function in Apicomplexa has improved dramatically. Here, we discuss methods that have been used to identify kinase substrates in apicomplexan parasites, classifying them into three main categories: i) kinase interactome, ii) indirect phosphoproteomics and iii) direct labeling. We briefly discuss each approach, including their advantages and limitations, and highlight representative examples from the Apicomplexa literature. Finally, we conclude each main category by introducing prospective approaches from other fields that would benefit kinase substrate identification in Apicomplexa.

A Tutorial Review of Labeling Methods in Mass Spectrometry-Based Quantitative Proteomics

Recent advancements in mass spectrometry (MS) have revolutionized quantitative proteomics, with multiplex isotope labeling emerging as a key strategy for enhancing accuracy, precision, and throughput. This tutorial review offers a comprehensive overview of multiplex isotope labeling techniques, including precursor-based, mass defect-based, reporter ion-based, and hybrid labeling methods. It details their fundamental principles, advantages, and inherent limitations along with strategies to mitigate the limitation of ratio-distortion. This review will also cover the applications and latest progress in these labeling techniques across various domains, including cancer biomarker discovery, neuroproteomics, post-translational modification analysis, cross-linking MS, and single-cell proteomics. This Review aims to provide guidance for researchers on selecting appropriate methods for their specific goals while also highlighting the potential future directions in this rapidly evolving field.

Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry

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

Insights into the Complexity and Functionality of Plant Virus Protein Phosphorylation

Phosphorylation, the most extensive and pleiotropic form of protein posttranslation modification, is central to cellular signal transduction. Throughout the extensive co-evolution of plant hosts and viruses, modifications to phosphorylation have served multiple purposes. Such modifications highlight the evolutionary trajectories of viruses and their hosts, with pivotal roles in regulation and refinement of host-virus interactions. In plant hosts, protein phosphorylation orchestrates immune responses, enhancing the activities of defense-related proteins such as kinases and transcription factors, thereby strengthening pathogen resistance in plants. Moreover, phosphorylation influences the interactions between host and viral proteins, altering viral spread and replication within host plants. In the context of plant viruses, protein phosphorylation controls key aspects of the infection cycle, including viral protein functionality and the interplay between viruses and host plant cells, leading to effects on viral accumulation and dissemination within plant tissues. Explorations of the nuances of protein phosphorylation in plant hosts and their interactions with viruses are particularly important. This review provides a systematic summary of the biological roles of the proteins of plant viruses carrying diverse genomes in regulating infection and host responses through changes in the phosphorylation status. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Integrated Transcriptomics and Proteomics Identified CMPK1 as a Potential Biomarker for Type 2 Diabetes Mellitus

Aim/Introduction

Type 2 diabetes mellitus (T2DM) is one of the most frequent and widespread disease in the world.Obesity is the most significant predictor of T2DM, but the exact mechanism how obesity promotes T2DM remains unknown. Finding specific biomarkers to assist in diagnosing and treating patients with obese and T2DM is critical.

Materials and Methods

We collected liver tissues from obesity patients with and without T2DM for proteomic sequencing and immunohistochemistry assay. Analysis Gene Ontology(GO) enrichment, Kyoto Encyclopedia of Genes and Genomes(KEGG), and protein interaction network (PPI) were performed on the parameters and data derived from the Tandem Mass Tags(TMT)-based proteomics analysis of liver tissues. Transcriptome data were downloaded from the Gene Expression Omnibus(GEO)website and genes that are deferentially expressed in both transcriptome and proteome were selected.

Results

We identified 140 deferentially expressed proteins from proteomic sequencing. Six biomarkers were deferentially expressed in both proteome and transcriptome with consistent changes in direction. The protein-protein interaction (PPI) analysis suggested CMPK1, the expression with greatest difference, was the core protein among the six biomarkers. Immunohistochemistry validated CMPK1 was upregulated significantly in the liver tissues of T2DM patients. The correlation analysis revealed that the expression of CMPK1 was significantly associated with key molecules in T2DM-related pathways at both protein and transcriptome levels.

Conclusion and Novelty

Our study showed CMPK1 was upregulated in the liver of T2DM patients and provides a possible new target for screening and diagnosing T2DM in patients with obese and a novel theoretical basis for the pathophysiological mechanism of obesity-related metabolic diseases.

Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ~3500 proteins at a spatial resolution of 50 µm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.

Comparative transcriptomics reveal a novel tardigrade-specific DNA-binding protein induced in response to ionizing radiation

Tardigrades are microscopic animals renowned for their ability to withstand extreme conditions, including high doses of ionizing radiation (IR). To better understand their radio-resistance, we first characterized induction and repair of DNA double- and single-strand breaks after exposure to IR in the model species Hypsibius exemplaris. Importantly, we found that the rate of single-strand breaks induced was roughly equivalent to that in human cells, suggesting that DNA repair plays a predominant role in tardigrades' radio-resistance. To identify novel tardigrade-specific genes involved, we next conducted a comparative transcriptomics analysis across three different species. In all three species, many DNA repair genes were among the most strongly overexpressed genes alongside a novel tardigrade-specific gene, which we named Tardigrade DNA damage Response 1 (TDR1). We found that TDR1 protein interacts with DNA and forms aggregates at high concentration suggesting it may condensate DNA and preserve chromosome organization until DNA repair is accomplished. Remarkably, when expressed in human cells, TDR1 improved resistance to Bleomycin, a radiomimetic drug. Based on these findings, we propose that TDR1 is a novel tardigrade-specific gene conferring resistance to IR. Our study sheds light on mechanisms of DNA repair helping cope with high levels of DNA damage inflicted by IR.

FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Data Sets Built on FragPipe

Here, we present FLiPPR, or FragPipe LiP (limited proteolysis) Processor, a tool that facilitates the analysis of data from limited proteolysis mass spectrometry (LiP-MS) experiments following primary search and quantification in FragPipe. LiP-MS has emerged as a method that can provide proteome-wide information on protein structure and has been applied to a range of biological and biophysical questions. Although LiP-MS can be carried out with standard laboratory reagents and mass spectrometers, analyzing the data can be slow and poses unique challenges compared to typical quantitative proteomics workflows. To address this, we leverage FragPipe and then process its output in FLiPPR. FLiPPR formalizes a specific data imputation heuristic that carefully uses missing data in LiP-MS experiments to report on the most significant structural changes. Moreover, FLiPPR introduces a data merging scheme and a protein-centric multiple hypothesis correction scheme, enabling processed LiP-MS data sets to be more robust and less redundant. These improvements strengthen statistical trends when previously published data are reanalyzed with the FragPipe/FLiPPR workflow. We hope that FLiPPR will lower the barrier for more users to adopt LiP-MS, standardize statistical procedures for LiP-MS data analysis, and systematize output to facilitate eventual larger-scale integration of LiP-MS data.

Unravelling G protein-coupled receptor signalling networks using global phosphoproteomics

G protein-coupled receptor (GPCR) activation initiates signalling via a complex network of intracellular effectors that combine to produce diverse cellular and tissue responses. Although we have an advanced understanding of the proximal events following receptor stimulation, the molecular detail of GPCR signalling further downstream often remains obscure. Unravelling these GPCR-mediated signalling networks has important implications for receptor biology and drug discovery. In this context, phosphoproteomics has emerged as a powerful approach for investigating global GPCR signal transduction. Here, we provide a brief overview of the phosphoproteomic workflow and discuss current limitations and future directions for this technology. By highlighting some of the novel insights into GPCR signalling networks gained using phosphoproteomics, we demonstrate the utility of global phosphoproteomics to dissect GPCR signalling networks and to accelerate discovery of new targets for therapeutic development. LINKED ARTICLES: This article is part of a themed issue Therapeutic Targeting of G Protein-Coupled Receptors: hot topics from the Australasian Society of Clinical and Experimental Pharmacologists and Toxicologists 2021 Virtual Annual Scientific Meeting. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v181.14/issuetoc.

15N metabolic labeling-TMT multiplexing approach to facilitate the quantitation of glycopeptides derived from cell lines

The study of glycoproteomics presents a set of unique challenges, primarily due to the low abundance of glycopeptides and their intricate heterogeneity, which is specific to each site. Glycoproteins play a crucial role in numerous biological functions, including cell signaling, adhesion, and intercellular communication, and are increasingly recognized as vital markers in the diagnosis and study of various diseases. Consequently, a quantitative approach to glycopeptide research is essential. One effective strategy to address this need is the use of multiplex glycopeptide labeling. By harnessing the synergies of 15N metabolic labeling via the isotopic detection of amino sugars with glutamine (IDAWG) technique for glycan parts and tandem mass tag (TMT)pro labeling for peptide backbones, we have developed a method that allows for the accurate quantification and comparison of multiple samples simultaneously. The adoption of the liquid chromatography-synchronous precursor selection (LC-SPS-MS3) technique minimizes fragmentation interference, enhancing data reliability, as shown by a 97% TMT labeling efficiency. This method allows for detailed, high-throughput analysis of 32 diverse samples from 231BR cell lines, using both 14N and 15N glycopeptides at a 1:1 ratio. A key component of our methodology was the precise correction for isotope and TMTpro distortions, significantly improving quantification accuracy to less than 5% distortion. This breakthrough enhances the efficiency and accuracy of glycoproteomic studies, increasing our understanding of glycoproteins in health and disease. Its applicability to various cancer cell types sets a new standard in quantitative glycoproteomics, enabling deeper investigation into glycopeptide profiles.

Determining the ERK-regulated phosphoproteome driving KRAS-mutant cancer

To delineate the mechanisms by which the ERK1 and ERK2 mitogen-activated protein kinases support mutant KRAS-driven cancer growth, we determined the ERK-dependent phosphoproteome in KRAS-mutant pancreatic cancer. We determined that ERK1 and ERK2 share near-identical signaling and transforming outputs and that the KRAS-regulated phosphoproteome is driven nearly completely by ERK. We identified 4666 ERK-dependent phosphosites on 2123 proteins, of which 79 and 66%, respectively, were not previously associated with ERK, substantially expanding the depth and breadth of ERK-dependent phosphorylation events and revealing a considerably more complex function for ERK in cancer. We established that ERK controls a highly dynamic and complex phosphoproteome that converges on cyclin-dependent kinase regulation and RAS homolog guanosine triphosphatase function (RHO GTPase). Our findings establish the most comprehensive molecular portrait and mechanisms by which ERK drives KRAS-dependent pancreatic cancer growth.

Developing forebrain synapses are uniquely vulnerable to sleep loss

Sleep is an essential behavior that supports lifelong brain health and cognition. Neuronal synapses are a major target for restorative sleep function and a locus of dysfunction in response to sleep deprivation (SD). Synapse density is highly dynamic during development, becoming stabilized with maturation to adulthood, suggesting sleep exerts distinct synaptic functions between development and adulthood. Importantly, problems with sleep are common in neurodevelopmental disorders including autism spectrum disorder (ASD). Moreover, early life sleep disruption in animal models causes long lasting changes in adult behavior. Different plasticity engaged during sleep necessarily implies that developing and adult synapses will show differential vulnerability to SD. To investigate distinct sleep functions and mechanisms of vulnerability to SD across development, we systematically examined the behavioral and molecular responses to acute SD between juvenile (P21-28), adolescent (P42-49) and adult (P70-100) mice of both sexes. Compared to adults, juveniles lack robust adaptations to SD, precipitating cognitive deficits in the novel object recognition test. Subcellular fractionation, combined with proteome and phosphoproteome analysis revealed the developing synapse is profoundly vulnerable to SD, whereas adults exhibit comparative resilience. SD in juveniles, and not older mice, aberrantly drives induction of synapse potentiation, synaptogenesis, and expression of peri-neuronal nets. Our analysis further reveals the developing synapse as a convergent node between vulnerability to SD and ASD genetic risk. Together, our systematic analysis supports a distinct developmental function of sleep and reveals how sleep disruption impacts key aspects of brain development, providing mechanistic insights for ASD susceptibility.

Cerebrospinal fluid proteomic signatures are associated with symptom severity of first-episode psychosis

Apart from their diagnostic, monitoring, or prognostic utility in clinical settings, molecular biomarkers may be instrumental in understanding the pathophysiology of psychiatric disorders, including schizophrenia. Using untargeted metabolomics, we recently identified eight cerebrospinal fluid (CSF) metabolites unique to first-episode psychosis (FEP) subjects compared to healthy controls (HC). In this study, we sought to investigate the CSF proteomic signatures associated with FEP. We employed 16-plex tandem mass tag (TMT) mass spectrometry (MS) to examine the relative protein abundance in CSF samples of 15 individuals diagnosed with FEP and 15 age-and-sex-matched healthy controls (HC). Multiple linear regression model (MLRM) identified 16 differentially abundant CSF proteins between FEP and HC at p < 0.01. Among them, the two most significant CSF proteins were collagen alpha-2 (IV) chain (COL4A2: standard mean difference [SMD] = -1.12, p = 1.64 × 10-4) and neuron-derived neurotrophic factor (NDNF: SMD = -1.03, p = 4.52 × 10-4) both of which were down-regulated in FEP subjects compared to HC. We also identified several potential CSF proteins associated with the pathophysiology and the symptom profile and severity in FEP subjects, including COL4A2, NDNF, hornerin (HRNR), contactin-6 (CNTN6), voltage-dependent calcium channel subunit alpha-2/delta-3 (CACNA2D3), tropomyosin alpha-3 chain (TPM3 and TPM4). Moreover, several protein signatures were associated with cognitive performance. Although the results need replication, our exploratory study suggests that CSF protein signatures can be used to increase the understanding of the pathophysiology of psychosis.

Endothelium-mediated regulation of platelet activation: Involvement of multiple protein kinases

The endothelial regulation of platelet activity is incompletely understood. Here we describe novel approaches to find molecular pathways implicated on the platelet-endothelium interaction. Using high-shear whole-blood microfluidics, employing coagulant or non-coagulant conditions at physiological temperature, we observed that the presence of human umbilical vein endothelial cells (HUVEC) strongly suppressed platelet adhesion and activation, via the collagen receptor glycoprotein VI (GPVI) and the PAR receptors for thrombin. Real-time monitoring of the cytosolic Ca2+ rises in the platelets indicated no major improvement of inhibition by prostacyclin or nitric oxide. Similarly under stasis, exposure of isolated platelets to HUVEC reduced the Ca2+ responses by collagen-related peptide (CRP-XL, GPVI agonist) and thrombin (PAR agonist). We then analyzed the label-free phosphoproteome of platelets (three donors), exposed to HUVEC, CRP-XL, and/or thrombin. High-resolution mass spectrometry gave 5463 phosphopeptides, corresponding to 1472 proteins, with good correlation between biological and technical replicates (R > .86). Stringent filtering steps revealed 26 regulatory pathways (Reactome) and 143 regulated kinase substrates (PhosphoSitePlus), giving a set of protein phosphorylation sites that was differentially (44) or similarly (110) regulated by HUVEC or agonist exposure. The differential regulation was confirmed by stable-isotope analysis of platelets from two additional donors. Substrate analysis indicated major roles of poorly studied protein kinase classes (MAPK, CDK, DYRK, STK, PKC members). Collectively, these results reveal a resetting of the protein phosphorylation profile in platelets exposed to endothelium or to conventional agonists and to endothelium-promoted activity of a multi-kinase network, beyond classical prostacyclin and nitric oxide actors, that may contribute to platelet inhibition.

Downregulation of the CD151 protects the cardiac function by the crosstalk between the endothelial cells and cardiomyocytes via exosomes

BACKGROUND

Heart failure (HF) is the last stage in the progression of various cardiovascular diseases. Although it is documented that CD151 contributes to regulate the myocardial infarction, the function of CD151 on HF and involved mechanisms are still unclear.

METHOD AND RESULTS

In the present study, we found that the recombinant adeno-associated virus (rAAV)-mediated endothelial cell-specific knockdown of CD151-transfected mice improved transverse aortic constriction (TAC)-induced cardiac function, attenuated myocardial hypertrophy and fibrosis, and increased coronary perfusion, whereas overexpression of the CD151 protein aggravated cardiac dysfunction and showed the opposite effects. In vitro, the cardiomyocytes hypertrophy induced by PE were significantly improved, while the proliferation and migration of cardiac fibroblasts (CFs) were significantly reduced, when co-cultured with the CD151-silenced endothelial cells (ECs). To further explore the mechanisms, the exosomes from the CD151-silenced ECs were taken by cardiomyocyte (CMs) and CFs, verified the intercellular communication. And the protective effects of CD151-silenced ECs were inhibited when exosome inhibitor (GW4869) was added. Additionally, a quantitative proteomics method was used to identify potential proteins in CD151-silenced EC exosomes. We found that the suppression of CD151 could regulate the PPAR signaling pathway via exosomes.

CONCLUSION

Our observations suggest that the downregulation of CD151 is an important positive regulator of cardiac function of heart failure, which can regulate exosome-stored proteins to play a role in the cellular interaction on the CMs and CFs. Modulating the exosome levels of ECs by reducing CD151 expression may offer novel therapeutic strategies and targets for HF treatment.

Phosphorylation Dynamics in a flg22-Induced, G Protein-Dependent Network Reveals the AtRGS1 Phosphatase

The microbe-associated molecular pattern flg22 is recognized in a flagellin-sensitive 2-dependent manner in root tip cells. Here, we show a rapid and massive change in protein abundance and phosphorylation state of the Arabidopsis root cell proteome in WT and a mutant deficient in heterotrimeric G-protein-coupled signaling. flg22-induced changes fall on proteins comprising a subset of this proteome, the heterotrimeric G protein interactome, and on highly-populated hubs of the immunity network. Approximately 95% of the phosphorylation changes in the heterotrimeric G-protein interactome depend, at least partially, on a functional G protein complex. One member of this interactome is ATBα, a substrate-recognition subunit of a protein phosphatase 2A complex and an interactor to Arabidopsis thaliana Regulator of G Signaling 1 protein (AtRGS1), a flg22-phosphorylated, 7-transmembrane spanning modulator of the nucleotide-binding state of the core G-protein complex. A null mutation of ATBα strongly increases basal endocytosis of AtRGS1. AtRGS1 steady-state protein level is lower in the atbα mutant in a proteasome-dependent manner. We propose that phosphorylation-dependent endocytosis of AtRGS1 is part of the mechanism to degrade AtRGS1, thus sustaining activation of the heterotrimeric G protein complex required for the regulation of system dynamics in innate immunity. The PP2A(ATBα) complex is a critical regulator of this signaling pathway.

A Causal Model of Ion Interference Enables Assessment and Correction of Ratio Compression in Multiplex Proteomics

Multiplex proteomics using isobaric labeling tags has emerged as a powerful tool for the simultaneous relative quantification of peptides and proteins across multiple experimental conditions. However, the quantitative accuracy of the approach is largely compromised by ion interference, a phenomenon that causes fold changes to appear compressed. The degree of compression is generally unknown, and the contributing factors are poorly understood. In this study, we thoroughly characterized ion interference at the MS2 level using a defined two-proteome experimental system with known ground-truth. We discovered remarkably poor agreement between the apparent precursor purity in the isolation window and the actual level of observed reporter ion interference in MS2 scans-a discrepancy that we found resolved by considering cofragmentation of peptide ions hidden within the spectral "noise" of the MS1 isolation window. To address this issue, we developed a regression modeling strategy to accurately predict reporter ion interference in any dataset. Finally, we demonstrate the utility of our procedure for improved fold change estimation and unbiased PTM site-to-protein normalization. All computational tools and code required to apply this method to any MS2 TMT dataset are documented and freely available.

Differences of protein expression in enterococcus faecalis biofilm during resistance to environmental pressures

BACKGROUND

Enterococcus faecalis biofilm was frequently found on the failed treated root canal wall, which survived by resisting disinfectant during endodontic treatment.Many researches have been conducted to explore the mechanisms of persistence of this pathogen in unfavorable conditions. However, no comprehensive proteomics studies have been conducted to investigate stress response in Enterococcus faecalis caused by alkali and NaOCl.

OBJECTIVE

Enterococcus faecalis (E.f) has been recognized as a main pathogen of refractory apical periodontitis, its ability to withstand environmental pressure is the key to grow in the environment of high alkaline and anti-bacterial drug that causes chronic infection in the root canal. This study aims to focus on the protein expression patterns of E.f biofilm under extreme pressure environment".

METHODS

Enterococcus faecalis biofilm model was established in vitro. Liquid Chromatograph-Mass Spectrometer (LC-MS/MS)-based label free quantitative proteomics approach was applied to compare differential protein expression under different environmental pressures (pH 10 and 5% sodium hypochlorite (NaOCl)). And then qPCR and Parallel Reaction Monitoring Verification (PRM) were utilized to verify the consequence of proteomics.

RESULTS

The number of taxa in this study was higher than those in previous studies, demonstrating the presence of a remarkable number of proteins in the groups of high alkaline and NaOCl. Proteins involved in ATP-binding cassette (ABC) transporter were significantly enriched in experimental samples. We identified a total of 15 highly expressed ABC transporters in the high alkaline environment pressure group, with 7 proteins greater than 1.5 times.

CONCLUSIONS

This study revealed considerable changes in expression of proteins in E.f biofilm during resistance to environmental pressures. The findings enriched our understanding of association between the differential expression proteins and environmental pressures.

Comprehensive Overview of Bottom-Up Proteomics using Mass Spectrometry

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

An economic and robust TMT labeling approach for high throughput proteomic and metaproteomic analysis

Multiplexed quantitative proteomics using tandem mass tag (TMT) is increasingly used in -omic study of complex samples. While TMT-based proteomics has the advantages of the higher quantitative accuracy, fewer missing values, and reduced instrument analysis time, it is limited by the additional reagent cost. In addition, current TMT labeling workflows involve repeated small volume pipetting of reagents in volatile solvents, which may increase the sample-to-sample variations and is not readily suitable for high throughput applications. In this study, we demonstrated that the TMT labeling procedures could be streamlined by using pre-aliquoted dry TMT reagents in a 96 well plate or 12-tube strip. As little as 50 μg dry TMT per channel was used to label 6-12 μg peptides, yielding high TMT labeling efficiency (∼99%) in both microbiome and mammalian cell line samples. We applied this workflow to analyze 97 samples in a study to evaluate whether ice recrystallization inhibitors improve the cultivability and activity of frozen microbiota. The results demonstrated tight sample clustering corresponding to groups and consistent microbiome responses to prebiotic treatments. This study supports the use of TMT reagents that are pre-aliquoted, dried, and stored for robust quantitative proteomics and metaproteomics in high throughput applications.

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.

Investigation of the Host Kinome Response to Coronavirus Infection Reveals PI3K/mTOR Inhibitors as Betacoronavirus Antivirals

Host kinases play essential roles in the host cell cycle, innate immune signaling, the stress response to viral infection, and inflammation. Previous work has demonstrated that coronaviruses specifically target kinase cascades to subvert host cell responses to infection and rely upon host kinase activity to phosphorylate viral proteins to enhance replication. Given the number of kinase inhibitors that are already FDA approved to treat cancers, fibrosis, and other human disease, they represent an attractive class of compounds to repurpose for host-targeted therapies against emerging coronavirus infections. To further understand the host kinome response to betacoronavirus infection, we employed multiplex inhibitory bead mass spectrometry (MIB-MS) following MERS-CoV and SARS-CoV-2 infection of human lung epithelial cell lines. Our MIB-MS analyses revealed activation of mTOR and MAPK signaling following MERS-CoV and SARS-CoV-2 infection, respectively. SARS-CoV-2 host kinome responses were further characterized using paired phosphoproteomics, which identified activation of MAPK, PI3K, and mTOR signaling. Through chemogenomic screening, we found that clinically relevant PI3K/mTOR inhibitors were able to inhibit coronavirus replication at nanomolar concentrations similar to direct-acting antivirals. This study lays the groundwork for identifying broad-acting, host-targeted therapies to reduce betacoronavirus replication that can be rapidly repurposed during future outbreaks and epidemics. The proteomics, phosphoproteomics, and MIB-MS datasets generated in this study are available in the Proteomics Identification Database (PRIDE) repository under project identifiers PXD040897 and PXD040901.

Solid-Phase Compatible Silane-Based Cleavable Linker Enables Custom Isobaric Quantitative Chemoproteomics

Mass spectrometry-based chemoproteomics has emerged as an enabling technology for functional biology and drug discovery. To address limitations of established chemoproteomics workflows, including cumbersome reagent synthesis and low throughput sample preparation, here, we established the silane-based cleavable isotopically labeled proteomics (sCIP) method. The sCIP method is enabled by a high yielding and scalable route to dialkoxydiphenylsilane fluorenylmethyloxycarbonyl (DADPS-Fmoc)-protected amino acid building blocks, which enable the facile synthesis of customizable, isotopically labeled, and chemically cleavable biotin capture reagents. sCIP is compatible with both MS1- and MS2-based quantitation, and the sCIP-MS2 method is distinguished by its click-assembled isobaric tags in which the reporter group is encoded in the sCIP capture reagent and balancer in the pan cysteine-reactive probe. The sCIP-MS2 workflow streamlines sample preparation with early stage isobaric labeling and sample pooling, allowing for high coverage and increased sample throughput via customized low cost six-plex sample multiplexing. When paired with a custom FragPipe data analysis workflow and applied to cysteine-reactive fragment screens, sCIP proteomics revealed established and unprecedented cysteine-ligand pairs, including the discovery that mitochondrial uncoupling agent FCCP acts as a covalent-reversible cysteine-reactive electrophile.

Determining DNA-Protein Binding Affinities and Specificities from Crude Lysates Using a Combined SILAC/TMT Labeling Strategy

In recent years, quantitative mass spectrometry-based interaction proteomics technology has proven very useful in identifying specific DNA-protein interactions using single pull-downs from crude lysates. Here, we applied a SILAC/TMT-based higher-order multiplexing approach to develop an interaction proteomics workflow called Protein-nucleic acid Affinity and Specificity quantification by MAss spectrometry in Nuclear extracts or PASMAN. In PASMAN, DNA pull-downs using a concentration range of specific and control DNA baits are performed in SILAC-labeled nuclear extracts. MS1-based quantification to determine specific DNA-protein interactions is then combined with sequential TMT-based quantification of fragmented SILAC peptides, allowing the generation of Hill-like curves and determination of apparent binding affinities. We benchmarked PASMAN using the SP/KLF motif and further applied it to gain insights into two CGCG-containing consensus DNA motifs. These motifs are recognized by two BEN domain-containing proteins, BANP and BEND3, which we find to interact with these motifs with distinct affinities. Finally, we profiled the BEND3 proximal proteome, revealing the NuRD complex as the major BEND3 proximal protein complex in vivo. In summary, PASMAN represents, to our knowledge, the first higher-order multiplexing-based interaction proteomics method that can be used to decipher specific DNA-protein interactions and their apparent affinities in various biological and pathological contexts.

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.

Enhanced Multiplexing Technology for Proteomics

The identification of thousands of proteins and their relative levels of expression has furthered understanding of biological processes and disease and stimulated new systems biology hypotheses. Quantitative proteomics workflows that rely on analytical assays such as mass spectrometry have facilitated high-throughput measurements of proteins partially due to multiplexing. Multiplexing allows proteome differences across multiple samples to be measured simultaneously, resulting in more accurate quantitation, increased statistical robustness, reduced analysis times, and lower experimental costs. The number of samples that can be multiplexed has evolved from as few as two to more than 50, with studies involving more than 10 samples being denoted as enhanced multiplexing or hyperplexing. In this review, we give an update on emerging multiplexing proteomics techniques and highlight advantages and limitations for enhanced multiplexing strategies.

Evaluation in a porcine wound model and long-term clinical assessment of an autologous heterogeneous skin construct used to close full-thickness wounds

Acute and chronic wounds involving deeper layers of the skin are often not adequately healed by dressings alone and require therapies such as skin grafting, skin substitutes, or growth factors. Here we report the development of an autologous heterogeneous skin construct (AHSC) that aids wound closure. AHSC is manufactured from a piece of healthy full-thickness skin. The manufacturing process creates multicellular segments, which contain endogenous skin cell populations present within hair follicles. These segments are physically optimized for engraftment within the wound bed. The ability of AHSC to facilitate closure of full thickness wounds of the skin was evaluated in a swine model and clinically in 4 patients with wounds of different etiologies. Transcriptional analysis demonstrated high concordance of gene expression between AHSC and native tissues for extracellular matrix and stem cell gene expression panels. Swine wounds demonstrated complete wound epithelialization and mature stable skin by 4 months, with hair follicle development in AHSC-treated wounds evident by 15 weeks. Biomechanical, histomorphological, and compositional analysis of the resultant swine and human skin wound biopsies demonstrated the presence of epidermal and dermal architecture with follicular and glandular structures that are similar to native skin. These data suggest that treatment with AHSC can facilitate wound closure.

LFQ-Based Peptide and Protein Intensity Differential Expression Analysis

Testing for significant differences in quantities at the protein level is a common goal of many LFQ-based mass spectrometry proteomics experiments. Starting from a table of protein and/or peptide quantities from a given proteomics quantification software, many tools and R packages exist to perform the final tasks of imputation, summarization, normalization, and statistical testing. To evaluate the effects of packages and settings in their substeps on the final list of significant proteins, we studied several packages on three public data sets with known expected protein fold changes. We found that the results between packages and even across different parameters of the same package can vary significantly. In addition to usability aspects and feature/compatibility lists of different packages, this paper highlights sensitivity and specificity trade-offs that come with specific packages and settings.

A Phytophthora infestans RXLR effector targets a potato ubiquitin-like domain-containing protein to inhibit the proteasome activity and hamper plant immunity

Ubiquitin-like domain-containing proteins (UDPs) are involved in the ubiquitin-proteasome system because of their ability to interact with the 26S proteasome. Here, we identified potato StUDP as a target of the Phytophthora infestans RXLR effector Pi06432 (PITG_06432), which supresses the salicylic acid (SA)-related immune pathway. By overexpressing and silencing of StUDP in potato, we show that StUDP negatively regulates plant immunity against P. infestans. StUDP interacts with, and destabilizes, the 26S proteasome subunit that is referred to as REGULATORY PARTICLE TRIPLE-A ATP-ASE (RPT) subunit StRPT3b. This destabilization represses the proteasome activity. Proteomic analysis and Western blotting show that StUDP decreases the stability of the master transcription factor SYSTEMIC ACQUIRED RESISTANCE DEFICIENT 1 (SARD1) in SA biosynthesis. StUDP negatively regulates the SA signalling pathway by repressing the proteasome activity and destabilizing StSARD1, leading to a decreased expression of the SARD1-targeted gene ISOCHORISMATE SYNTHASE 1 and thereby a decrease in SA content. Pi06432 stabilizes StUDP, and it depends on StUDP to destabilize StRPT3b and thereby supress the proteasome activity. Our study reveals that the P. infestans effector Pi06432 targets StUDP to hamper the homeostasis of the proteasome by the degradation of the proteasome subunit StRPT3b and thereby suppresses SA-related immunity.

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.

Multi-omics analyses reveal ClpP activators disrupt essential mitochondrial pathways in triple-negative breast cancer

ClpP activators ONC201 and related small molecules (TR compounds, Madera Therapeutics), have demonstrated significant anti-cancer potential in vitro and in vivo studies, including clinical trials for refractory solid tumors. Though progress has been made in identifying specific phenotypic outcomes following ClpP activation, the exact mechanism by which ClpP activation leads to broad anti-cancer activity has yet to be fully elucidated. In this study, we utilized a multi-omics approach to identify the ClpP-dependent proteomic, transcriptomic, and metabolomic changes resulting from ONC201 or the TR compound TR-57 in triple-negative breast cancer cells. Applying mass spectrometry-based methods of proteomics and metabolomics, we identified ∼8,000 proteins and 588 metabolites, respectively. From proteomics data, 113 (ONC201) and 191 (TR-57) proteins significantly increased and 572 (ONC201) and 686 (TR-57) proteins significantly decreased in this study. Gene ontological (GO) analysis revealed strong similarities between proteins up- or downregulated by ONC201 or TR-57 treatment. Notably, this included the downregulation of many mitochondrial processes and proteins, including mitochondrial translation and mitochondrial matrix proteins. We performed a large-scale transcriptomic analysis of WT SUM159 cells, identifying ∼7,700 transcripts (746 and 1,100 significantly increasing, 795 and 1,013 significantly decreasing in ONC201 and TR-57 treated cells, respectively). Less than 21% of these genes were affected by these compounds in ClpP null cells. GO analysis of these data demonstrated additional similarity of response to ONC201 and TR-57, including a decrease in transcripts related to the mitochondrial inner membrane and matrix, cell cycle, and nucleus, and increases in other nuclear transcripts and transcripts related to metal-ion binding. Comparison of response between both compounds demonstrated a highly similar response in all -omics datasets. Analysis of metabolites also revealed significant similarities between ONC201 and TR-57 with increases in α-ketoglutarate and 2-hydroxyglutaric acid and decreased ureidosuccinic acid, L-ascorbic acid, L-serine, and cytidine observed following ClpP activation in TNBC cells. Further analysis identified multiple pathways that were specifically impacted by ClpP activation, including ATF4 activation, heme biosynthesis, and the citrulline/urea cycle. In summary the results of our studies demonstrate that ONC201 and TR-57 induce highly similar and broad effects against multiple mitochondrial processes required for cell proliferation.

Ion Mobility Mass Spectrometry (IM-MS) for Structural Biology: Insights Gained by Measuring Mass, Charge, and Collision Cross Section

The investigation of macromolecular biomolecules with ion mobility mass spectrometry (IM-MS) techniques has provided substantial insights into the field of structural biology over the past two decades. An IM-MS workflow applied to a given target analyte provides mass, charge, and conformation, and all three of these can be used to discern structural information. While mass and charge are determined in mass spectrometry (MS), it is the addition of ion mobility that enables the separation of isomeric and isobaric ions and the direct elucidation of conformation, which has reaped huge benefits for structural biology. In this review, where we focus on the analysis of proteins and their complexes, we outline the typical features of an IM-MS experiment from the preparation of samples, the creation of ions, and their separation in different mobility and mass spectrometers. We describe the interpretation of ion mobility data in terms of protein conformation and how the data can be compared with data from other sources with the use of computational tools. The benefit of coupling mobility analysis to activation via collisions with gas or surfaces or photons photoactivation is detailed with reference to recent examples. And finally, we focus on insights afforded by IM-MS experiments when applied to the study of conformationally dynamic and intrinsically disordered proteins.

Bioinertization of nanoLC/MS/MS systems by depleting metal ions from the mobile phases for phosphoproteomics

We have successfully developed a bioinertized nanoflow liquid chromatography/tandem mass spectrometry (nanoLC/MS/MS) system for the highly sensitive analysis of phosphopeptides by depleting metal ions from the mobile phase. We found that not only direct contact of phosphopeptides with metal components, but also indirect contact with nanoLC pumps through the mobile phase causes significant losses during the recovery of phosphopeptides. Moreover, electrospray ionization was adversely affected by the mobile phase containing multiple metal ions as well as by the sample solvents contaminated with metal ions used in immobilized metal ion affinity chromatography for phosphopeptide enrichment. To solve these problems, metal ions were depleted by inserting an on-line metal ion removal device containing metal-chelating membranes between the gradient mixer and the autosampler. As a result, the peak areas of the identified phosphopeptides increased an average of 9.9-fold overall and 77-fold for multiply phosphorylated peptides with the insertion of the on-line metal ion removal system. This strategy would be applicable to highly sensitive analysis of other phosphorylated biomolecules by microscale-LC/MS/MS.

cKMT1 is a new lysine methyltransferase that methylates the ferredoxin-NADP(+) oxidoreductase (FNR) and regulates energy transfer in cyanobacteria

Lysine methylation is a conserved and dynamic regulatory post-translational modification performed by lysine methyltransferases (KMTs). KMTs catalyze the transfer of mono-, di-, or tri-methyl groups to substrate proteins and play a critical regulatory role in all domains of life. To date, only one KMT has been identified in cyanobacteria. Here, we tested all of the predicted KMTs in the cyanobacterium Synechocystis sp. PCC 6803 (Synechocystis), and we biochemically characterized sll1526 that we termed cKMT1 (cyanobacterial lysine methyltransferase 1), and determined that it can catalyze lysine methylation both in vivo and in vitro. Loss of cKMT1 alters photosynthetic electron transfer in Synechocystis. We analyzed cKMT1-regulated methylation sites in Synechocystis using a timsTOF Pro instrument. We identified 305 class I lysine methylation sites within 232 proteins, and of these, 80 methylation sites in 58 proteins were hypomethylated in ΔcKMT1 cells. We further demonstrated that cKMT1 could methylate ferredoxin-NADP(+) oxidoreductase (FNR) and its potential sites of action on FNR were identified. Amino acid residues H118 and Y219 were identified as key residues in the putative active site of cKMT1 as indicated by structure simulation, site-directed mutagenesis, and KMT activity measurement. Using mutations that mimic the unmethylated forms of FNR, we demonstrated that the inability to methylate K139 residues results in a decrease in the redox activity of FNR and affects energy transfer in Synechocystis. Together, our study identified a new KMT in Synechocystis and elucidated a methylation-mediated molecular mechanism catalyzed by cKMT1 for the regulation of energy transfer in cyanobacteria.

A Python Package for the Localization of Protein Modifications in Mass Spectrometry Data

Determining the correct localization of post-translational modifications (PTMs) on peptides aids in interpreting their effect on protein function. While most algorithms for this task are available as standalone applications or incorporated into software suites, improving their versatility through access from popular scripting languages facilitates experimentation and incorporation into novel workflows. Here we describe pyAscore, an efficient and versatile implementation of the Ascore algorithm in Python for scoring the localization of user defined PTMs in data dependent mass spectrometry. pyAscore can be used from the command line or imported into Python scripts and accepts standard file formats from popular software tools used in bottom-up proteomics. Access to internal objects for scoring and working with modified peptides adds to the toolbox for working with PTMs in Python. pyAscore is available as an open source package for Python 3.6+ on all major operating systems and can be found at pyascore.readthedocs.io.

Computational systems approach towards phosphoproteomics and their downstream regulation

Protein phosphorylation plays an essential role in modulating cell signalling and its downstream transcriptional and translational regulations. Until recently, protein phosphorylation has been studied mostly using low-throughput biochemical assays. The advancement of mass spectrometry (MS)-based phosphoproteomics transformed the field by enabling measurement of proteome-wide phosphorylation events, where tens of thousands of phosphosites are routinely identified and quantified in an experiment. This has brought a significant challenge in analysing large-scale phosphoproteomic data, making computational methods and systems approaches integral parts of phosphoproteomics. Previous works have primarily focused on reviewing the experimental techniques in MS-based phosphoproteomics, yet a systematic survey of the computational landscape in this field is still missing. Here, we review computational methods and tools, and systems approaches that have been developed for phosphoproteomics data analysis. We categorise them into four aspects including data processing, functional analysis, phosphoproteome annotation and their integration with other omics, and in each aspect, we discuss the key methods and example studies. Lastly, we highlight some of the potential research directions on which future work would make a significant contribution to this fast-growing field. We hope this review provides a useful snapshot of the field of computational systems phosphoproteomics and stimulates new research that drives future development.

The 2022 Nobel Prize in Chemistry for the development of click chemistry and bioorthogonal chemistry

The 2022 Nobel Prize in Chemistry recognized the development of biorthogonal chemical ligation reactions known as click chemistry in biomedicine. This concept has catalyzed significant progress in sensing and diagnosis, chemical biology, materials chemistry, and drug discovery and delivery. In proteomics, the ability to incorporate a click tag into proteins has propelled development of powerful new methods for selective enrichment of protein complexes that inform understanding of protein networks. It also has had a strong influence on the ability to enrich for protein post-translational modifications. This feature article summarizes the impacts of biorthogonal click chemistry on proteomics.

Data-independent acquisition boosts quantitative metaproteomics for deep characterization of gut microbiota

Metaproteomics can provide valuable insights into the functions of human gut microbiota (GM), but is challenging due to the extreme complexity and heterogeneity of GM. Data-independent acquisition (DIA) mass spectrometry (MS) has been an emerging quantitative technique in conventional proteomics, but is still at the early stage of development in the field of metaproteomics. Herein, we applied library-free DIA (directDIA)-based metaproteomics and compared the directDIA with other MS-based quantification techniques for metaproteomics on simulated microbial communities and feces samples spiked with bacteria with known ratios, demonstrating the superior performance of directDIA by a comprehensive consideration of proteome coverage in identification as well as accuracy and precision in quantification. We characterized human GM in two cohorts of clinical fecal samples of pancreatic cancer (PC) and mild cognitive impairment (MCI). About 70,000 microbial proteins were quantified in each cohort and annotated to profile the taxonomic and functional characteristics of GM in different diseases. Our work demonstrated the utility of directDIA in quantitative metaproteomics for investigating intestinal microbiota and its related disease pathogenesis.

A streamlined tandem tip-based workflow for sensitive nanoscale phosphoproteomics

Effective phosphoproteome of nanoscale sample analysis remains a daunting task, primarily due to significant sample loss associated with non-specific surface adsorption during enrichment of low stoichiometric phosphopeptide. We develop a tandem tip phosphoproteomics sample preparation method that is capable of sample cleanup and enrichment without additional sample transfer, and its integration with our recently developed SOP (Surfactant-assisted One-Pot sample preparation) and iBASIL (improved Boosting to Amplify Signal with Isobaric Labeling) approaches provides a streamlined workflow enabling sensitive, high-throughput nanoscale phosphoproteome measurements. This approach significantly reduces both sample loss and processing time, allowing the identification of >3000 (>9500) phosphopeptides from 1 (10) µg of cell lysate using the label-free method without a spectral library. It also enables precise quantification of ~600 phosphopeptides from 100 sorted cells (single-cell level input for the enriched phosphopeptides) and ~700 phosphopeptides from human spleen tissue voxels with a spatial resolution of 200 µm (equivalent to ~100 cells) in a high-throughput manner. The new workflow opens avenues for phosphoproteome profiling of mass-limited samples at the low nanogram level.