Spatial-proteomics reveals phospho-signaling dynamics at subcellular resolution

Dual SLIPT-A Lipid Mimic to Enable Spatiotemporally Defined, Sequential Protein Dimerization

Spatiotemporal control of proteins is crucial for cellular phenomena such as signal integration, propagation, as well as managing crosstalk. In membrane-associated signaling, this regulation is often enabled by lipids, wherein highly dynamic, sequential recruitment of interacting proteins is key to successful signaling. Here, we present dual SLIPT (self-localizing ligand-induced protein translocation), a lipid-analog tool, capable of emulating this lipid-mediated sequential recruitment of any two proteins of interest. Dual SLIPT self-localizes to the inner leaflet of the plasma membrane (PM). There, dual SLIPT presents trimethoprim (TMP) and HaloTag ligand (HTL) to cytosolic proteins of interest (POIs), whereupon POIs fused to the protein tags iK6eDHFR, or to HOB are recruited. A systematic extension of the linkers connecting the two mutually orthogonal headgroups was implemented to overcome the steric clash between the recruited POIs. Using Förster resonance energy transfer (FRET), we verify that the resulting probe is capable of simultaneous binding of both proteins of interest, as well as their dimerization. Dual SLIPT was found to be particularly suitable for use in physiologically relevant concentrations, such as recruitment via tightly regulated, transient lipid species. We further expanded dual SLIPT to the photocontrollable dual SLIPTNVOC, by introducing a photocaging group onto the TMP moiety. Dual SLIPTNVOC enables sequential and spatiotemporally defined dimerization upon blue light irradiation. Thus, dual SLIPTNVOC serves as a close mimic of physiology, enabling interrogation of dynamic cytosol-to-plasma membrane recruitment events and their impact on signaling.

Phosphorylation of SNX17 impedes activation of Retriever-mediated sorting

Sorting nexin 17 (SNX17) functions as cargo receptor on endosomal membranes that enables the recycling of numerous membrane cargo proteins by binding to the Retriever complex. Yet, little is known how SNX17 activity or its membrane recruitment is regulated. Here, we report that phosphorylation of SNX17 at serine 38 (Ser38) within the phox (PX) domain serves as a critical regulatory switch governing its endosomal localization and function. A mutant form mimicking the phosphorylated state disrupts SNX17's ability to bind phosphatidylinositol-3-phosphate (PI3P), which in turn impairs its association with early endosomal membranes and inactivates SNX17-dependent cargo-recycling in cells. Furthermore, our results demonstrate that Ser38 is part of an autoinhibitory mechanism to regulate SNX17 cargo binding. Collectively, these findings provide new insights into the dynamic regulation of SNX17 activity and Retriever-mediated sorting processes. It also highlights SNX17 Ser38 phosphorylation as a critical regulatory mechanism that controls SNX17's endosomal localization and cargo recycling function.

Multiplexed phosphoproteomics of low cell numbers using SPARCE

Understanding cellular diversity and disease mechanisms requires a global analysis of proteins and their modifications. While next-generation sequencing has advanced our understanding of cellular heterogeneity, it fails to capture downstream signalling networks. Ultrasensitive mass spectrometry-based proteomics enables unbiased protein-level analysis of low cell numbers, down to single cells. However, phosphoproteomics remains limited to high-input samples due to sample losses and poor reaction efficiencies associated with processing low cell numbers. Isobaric stable isotope labelling is a promising approach for reproducible and accurate quantification of low abundant phosphopeptides. Here, we introduce SPARCE (Streamlined Phosphoproteomic Analysis of Rare CElls) for multiplexed phosphoproteomic analysis of low cell numbers. SPARCE integrates cell isolation, water-based lysis, on-tip TMT labelling, and phosphopeptide enrichment. SPARCE outperforms traditional methods by enhancing labelling efficiency and phosphoproteome coverage. To demonstrate the utility of SPARCE, we analysed four patient-derived glioblastoma stem cell lines, reliably quantifying phosphosite changes from 1000 FACS-sorted cells. This workflow expands the possibilities for signalling analysis of rare cell populations.

The network response to Egf is tissue-specific

Epidermal growth factor receptor (Egfr)-driven signaling regulates fundamental homeostatic processes. Dysregulated signaling via Egfr is implicated in numerous disease pathologies and distinct Egfr-associated disease etiologies are known to be tissue-specific. The molecular basis of this tissue-specificity remains poorly understood. Most studies of Egfr signaling to date have been performed in vitro or in tissue-specific mouse models of disease, which has limited insight into Egfr signaling patterns in healthy tissues. Here, we carried out integrated phosphoproteomic, proteomic, and transcriptomic analyses of signaling changes across various mouse tissues in response to short-term stimulation with the Egfr ligand Egf. We show how both baseline and Egf-stimulated signaling dynamics differ between tissues. Moreover, we propose how baseline phosphorylation and total protein levels may be associated with clinically relevant tissue-specific Egfr-associated phenotypes. Altogether, our analyses illustrate tissue-specific effects of Egf stimulation and highlight potential links between underlying tissue biology and Egfr signaling output.

Mammalian TatD DNase domain containing 1 (TATDN1) is a proteostasis-responsive gene with roles in ventricular structure and neuromuscular function

The characterization of highly conserved but poorly understood genes often reveals unexpected biological roles, advancing our understanding of disease mechanisms. One such gene is Mammalian TatD DNase domain containing 1 (Tatdn1), the mammalian homolog of bacterial Twin-arginine translocation D (TatD), a protein proposed to have roles either in DNA degradation or protein quality control in unicellular organisms. Despite its association with different pathologies, including several cancer types and cardiovascular diseases, the role of TATDN1 in mammals remains unexplored. Here, we demonstrate that Tatdn1 encodes a cytoplasmic protein that does not participate in DNA degradation but is upregulated in cells under proteostasis stress. Tatdn1-deficient mice exhibit dysregulated expression of genes involved in membrane and extracellular protein biology, along with mild dilated cardiomyopathy and impaired motor coordination. These findings identify TATDN1 as a key player in cytosolic processes linked to protein homeostasis, with significant physiological implications for cardiac and neurological function.

Urinary extracellular vesicle N-glycomics identifies diagnostic glycosignatures for bladder cancer

Bladder cancer (BC) is the most common urologic malignancy, facing enormous diagnostic challenges. Urinary extracellular vesicles (EVs) are promising source for developing diagnostic markers for bladder cancer because of the direct contact between urine and bladder. This study pioneers urinary EV N-glycomics for bladder cancer diagnosis. We have generated a comprehensive N-glycome landscape of urinary EVs through high-throughput N-glycome analysis, identifying a total of 252 N-glycans from 333 individuals. In bladder cancer patients, urinary EVs exhibit decreased fucosylation and increased sialylation level. An Eight N-glycan diagnostic model demonstrates strong performance in both validation cohorts, achieving ROC AUC values of 0.88 and 0.86, respectively. Furthermore, this model successfully differentiates both non-muscle invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) from healthy individuals, underscoring the model's superiority. Moreover, urinary EVs N-glycoproteomic analysis reveals that the glycoproteins carrying cancer-associated N-glycan signatures are closely associated with immune activities. The N-glycome comparative analysis of EVs and their source cells indicate that the glycosylation profiles of EVs do not completely match the glycosylation backgrounds of their source cells. In summary, our study establishes urinary EV N-glycomics as a non-invasive BC screening tool and provide a framework for EV glycan biomarker discovery across cancers.

Lysosomal proteomics reveals mechanisms of neuronal apoE4-associated lysosomal dysfunction

ApoE4 is the primary risk factor for Alzheimer Disease (AD). Early AD pathological events first affect the neuronal endolysosomal system, which in turn causes neuronal protein aggregation and cell death. Despite the crucial influence of lysosomes upon AD pathophysiology, and that apoE4 localizes to lysosomes, the influence of apoE4 on lysosomal function remains unexplored. We find that expression of apoE4 in neuronal cell lines results in lysosomal alkalinization and impaired lysosomal function. To identify driving factors for these defects, we performed quantitative lysosomal proteome profiling. This revealed that apoE4 expression results in differential regulation of numerous lysosomal proteins, correlating with apoE allele status and disease severity in AD brains. In particular, apoE4 expression results in the depletion of lysosomal Lgals3bp and the accumulation of lysosomal Tmed5. We additionally validated that these lysosomal protein changes can be targeted to modulate lysosomal function. Taken together, this work thereby reveals that apoE4 causes widespread lysosomal defects through remodeling the lysosomal proteome, with the lysosomal Tmed5 accumulation and Lgals3bp depletion manifesting as lysosomal alkalinization in apoE4 neurons.

Global organelle profiling reveals subcellular localization and remodeling at proteome scale

Defining the subcellular distribution of all human proteins and their remodeling across cellular states remains a central goal in cell biology. Here, we present a high-resolution strategy to map subcellular organization using organelle immunocapture coupled to mass spectrometry. We apply this workflow to a cell-wide collection of membranous and membraneless compartments. A graph-based analysis assigns the subcellular localization of over 7,600 proteins, defines spatial networks, and uncovers interconnections between cellular compartments. Our approach can be deployed to comprehensively profile proteome remodeling during cellular perturbation. By characterizing the cellular landscape following HCoV-OC43 viral infection, we discover that many proteins are regulated by changes in their spatial distribution rather than by changes in abundance. Our results establish that proteome-wide analysis of subcellular remodeling provides key insights for elucidating cellular responses, uncovering an essential role for ferroptosis in OC43 infection. Our dataset can be explored at organelles.czbiohub.org.

A multi-tissue longitudinal proteomics study to evaluate the suitability of post-mortem samples for pathophysiological research

Recent developments in mass spectrometry-based proteomics have established it as a robust tool for system-wide analyses essential for pathophysiological research. While post-mortem samples are a critical source for these studies, our understanding of how body decomposition influences the proteome remains limited. Here, we have revisited published data and conducted a clinically relevant time-course experiment in mice, revealing organ-specific proteome regulation after death, with only a fraction of these changes linked to protein autolysis. The liver and spleen exhibit significant proteomic alterations within hours post-mortem, whereas the heart displays only modest changes. Additionally, subcellular compartmentalization leads to an unexpected surge in proteome alterations at the earliest post-mortem interval (PMI). Additionally, we have conducted a comprehensive analysis of semi-tryptic peptides, revealing distinct consensus motifs for different organs, indicating organ-specific post-mortem protease activity. In conclusion, our findings emphasize the critical importance of considering PMI effects when designing proteomics studies, as these effects may significantly overshadow the impacts of diseases. Preferably, the samples should be taken in the operation room, especially for studies including subcellular compartmentalization or trans-organ comparison. In single-organ studies, the planning should involve careful control of PMI.

Functional Analysis of MS-Based Proteomics Data: From Protein Groups to Networks

Mass spectrometry-based proteomics allows the quantification of thousands of proteins, protein variants, and their modifications, in many biological samples. These are derived from the measurement of peptide relative quantities, and it is not always possible to distinguish proteins with similar sequences due to the absence of protein-specific peptides. In such cases, peptide signals are reported in protein groups that can correspond to several genes. Here, we show that multi-gene protein groups have a limited impact on GO-term enrichment, but selecting only one gene per group affects network analysis. We thus present the Cytoscape app Proteo Visualizer (https://apps.cytoscape.org/apps/ProteoVisualizer) that is designed for retrieving protein interaction networks from STRING using protein groups as input and thus allows visualization and network analysis of bottom-up MS-based proteomics data sets.

Ultra-fast label-free quantification and comprehensive proteome coverage with narrow-window data-independent acquisition

Mass spectrometry (MS)-based proteomics aims to characterize comprehensive proteomes in a fast and reproducible manner. Here we present the narrow-window data-independent acquisition (nDIA) strategy consisting of high-resolution MS1 scans with parallel tandem MS (MS/MS) scans of ~200 Hz using 2-Th isolation windows, dissolving the differences between data-dependent and -independent methods. This is achieved by pairing a quadrupole Orbitrap mass spectrometer with the asymmetric track lossless (Astral) analyzer which provides >200-Hz MS/MS scanning speed, high resolving power and sensitivity, and low-ppm mass accuracy. The nDIA strategy enables profiling of >100 full yeast proteomes per day, or 48 human proteomes per day at the depth of ~10,000 human protein groups in half-an-hour or ~7,000 proteins in 5 min, representing 3× higher coverage compared with current state-of-the-art MS. Multi-shot acquisition of offline fractionated samples provides comprehensive coverage of human proteomes in ~3 h. High quantitative precision and accuracy are demonstrated in a three-species proteome mixture, quantifying 14,000+ protein groups in a single half-an-hour run.

Subcellular Proteomic Mapping of Lysine Lactylation

Protein lactylation is a novel post-translational modification (PTM) involved in many important physiological processes such as macrophage polarization, immune regulation, and tumor cell growth. However, traditional methodologies for studying lactylation have predominantly relied on peptide enrichment from whole-cell lysates, which tend to favor the detection of high-abundance peptides, thus limiting the identification of low-abundance lactylated peptides. To address this limitation, here, we employed subcellular fractionation to separate proteins and map lactylated peptides from each isolated subcellular fraction using a model cell line. In brief, we identified 1,217 lysine lactylation (Kla) sites on 553 proteins across four subcellular fractions. Subsequent pathway enrichment analysis revealed that Kla proteins participate in distinct pathways depending on the subcellular contexts. In addition, this subcellular fractionation method enabled the discovery of 36 previously unreported Kla proteins and 223 novel Kla sites, many of which are present in low abundance. Notably, several proteins contain multiple newly identified Kla sites, exemplified by the transcriptional regulator ATRX. Furthermore, our results indicate the possibility of PTM crosstalk between Kla and other PTMs such as ubiquitination and sumoylation. In conclusion, subcellular fractionation facilitates the identification of Kla proteins that have been previously uncovered and could be overlooked by affinity enrichment of whole-cell lysates.

Streamlined analysis of drug targets by proteome integral solubility alteration indicates organ-specific engagement

Proteins are the primary targets of almost all small molecule drugs. However, even the most selectively designed drugs can potentially target several unknown proteins. Identification of potential drug targets can facilitate design of new drugs and repurposing of existing ones. Current state-of-the-art proteomics methodologies enable screening of thousands of proteins against a limited number of drug molecules. Here we report the development of a label-free quantitative proteomics approach that enables proteome-wide screening of small organic molecules in a scalable, reproducible, and rapid manner by streamlining the proteome integral solubility alteration (PISA) assay. We used rat organs ex-vivo to determine organ specific targets of medical drugs and enzyme inhibitors to identify drug targets for common drugs such as Ibuprofen. Finally, global drug profiling revealed overarching trends of how small molecules affect the proteome through either direct or indirect protein interactions.

Advances in spatial proteomics: Mapping proteome architecture from protein complexes to subcellular localizations

Proteins are responsible for most intracellular functions, which they perform as part of higher-order molecular complexes, located within defined subcellular niches. Localization is both dynamic and context specific and mislocalization underlies a multitude of diseases. It is thus vital to be able to measure the components of higher-order protein complexes and their subcellular location dynamically in order to fully understand cell biological processes. Here, we review the current range of highly complementary approaches that determine the subcellular organization of the proteome. We discuss the scale and resolution at which these approaches are best employed and the caveats that should be taken into consideration when applying them. We also look to the future and emerging technologies that are paving the way for a more comprehensive understanding of the functional roles of protein isoforms, which is essential for unraveling the complexities of cell biology and the development of disease treatments.

Ultrafast and Chemoselective Biotinylation of Living Cell Surfaces for Time-Resolved Surfaceome Analysis

Cell surface proteins participate in many important biological processes, such as cell-to-cell interaction, signal transduction, cell adhesion, and protein transportation. In-depth study of the cell surface protein group is of great significance. Nevertheless, detection and analysis of the surfaceome remain a significant challenge due to their low abundance and hydrophobicity. Herein, we reported an ultrafast and chemoselective labeling method using our newly developed trifunctional probe, the OPA-S-S-alkyne, which labeled cell surface lysine residues, and then established a novel cell surfaceome profiling approach. According to our experimental results, the OPA-S-S-alkyne probe can react extremely fast with living cells, labeling cells in only 1 min, while traditional NHS (labeling cell surface lysine with N-hydroxysuccinimide ester probe) and CSC (labeling cell surface glycan with hydrazide biotin probe) methods normally take longer time of more than 30 min and 1 h, respectively. Taking advantage of this ultrafast property of the method, we highlight the utility of this method by exploring the temporal dynamic changes of surfaceome upon EGF stimulation in living Hela cells and reported "early" and "late" EGF-regulated cell surface proteins, which are difficult to be distinguished by the current cell surface profiling approaches.

Recent Advancements in Subcellular Proteomics: Growing Impact of Organellar Protein Niches on the Understanding of Cell Biology

The mammalian cell is a complex entity, with membrane-bound and membrane-less organelles playing vital roles in regulating cellular homeostasis. Organellar protein niches drive discrete biological processes and cell functions, thus maintaining cell equilibrium. Cellular processes such as signaling, growth, proliferation, motility, and programmed cell death require dynamic protein movements between cell compartments. Aberrant protein localization is associated with a wide range of diseases. Therefore, analyzing the subcellular proteome of the cell can provide a comprehensive overview of cellular biology. With recent advancements in mass spectrometry, imaging technology, computational tools, and deep machine learning algorithms, studies pertaining to subcellular protein localization and their dynamic distributions are gaining momentum. These studies reveal changing interaction networks because of "moonlighting proteins" and serve as a discovery tool for disease network mechanisms. Consequently, this review aims to provide a comprehensive repository for recent advancements in subcellular proteomics subcontexting methods, challenges, and future perspectives for method developers. In summary, subcellular proteomics is crucial to the understanding of the fundamental cellular mechanisms and the associated diseases.

µPhos: a scalable and sensitive platform for high-dimensional phosphoproteomics

Mass spectrometry has revolutionized cell signaling research by vastly simplifying the analysis of many thousands of phosphorylation sites in the human proteome. Defining the cellular response to perturbations is crucial for further illuminating the functionality of the phosphoproteome. Here we describe µPhos ('microPhos'), an accessible phosphoproteomics platform that permits phosphopeptide enrichment from 96-well cell culture and small tissue amounts in <8 h total processing time. By greatly minimizing transfer steps and liquid volumes, we demonstrate increased sensitivity, >90% selectivity, and excellent quantitative reproducibility. Employing highly sensitive trapped ion mobility mass spectrometry, we quantify ~17,000 Class I phosphosites in a human cancer cell line using 20 µg starting material, and confidently localize ~6200 phosphosites from 1 µg. This depth covers key signaling pathways, rendering sample-limited applications and perturbation experiments with hundreds of samples viable. We employ µPhos to study drug- and time-dependent response signatures in a leukemia cell line, and by quantifying 30,000 Class I phosphosites in the mouse brain we reveal distinct spatial kinase activities in subregions of the hippocampal formation.

6-Plex Tandem Phosphorus Tags (TPT) for Accurate Quantitative Proteomics

Isobaric chemical labeling is a widely used strategy for high-throughput quantitative proteomics based on mass spectrometry. However, commercially available reagents have high costs in applications as well as the sensitivity limitations for detection of the trace protein samples. Previously, we developed a 2-plex isobaric labeling strategy based on phosphorus chemistry for ultrasensitive proteome quantification with high accuracy. In this work, 6-plex tandem phosphorus tags (TPT) were developed with 3-fold increase in the multiplexing quantitative capacity compared to the 2-plex isobaric phosphorus reagents introduced previously. High isotope enrichment of 18O labeling was incorporated into the phosphoryl group with three exchangeable oxygen atoms by using commercially available H218O. The combinational incorporations of 18O atom in reporter ions and balance group set up the low-cost foundation for development of multiplex TPT reagents. The novel 6-plex TPT reagents could produce phosphoramidate as unique reporter ions with approximately 1 Da mass difference and thus enable 6-plex quantitative analysis in high-resolution ESI-MS/MS analysis. Using HeLa cell tryptic peptides, we concluded that 6-plex TPT reagents could facilitate large-scale accurate quantitative proteomics with very high labeling efficiency.

Proteomics Analysis of the Protective Effect of Polydeoxyribonucleotide Extracted from Sea Cucumber (Apostichopus japonicus) Sperm in a Hydrogen Peroxide-Induced RAW264.7 Cell Injury Model

Sea cucumber viscera contain various naturally occurring active substances, but they are often underutilized during sea cucumber processing. Polydeoxyribonucleotide (PDRN) is an adenosine A2A receptor agonist that activates the A2A receptor to produce various biological effects. Currently, most studies on the activity of PDRN have focused on its anti-inflammatory, anti-apoptotic, and tissue repair properties, yet relatively few studies have investigated its antioxidant activity. In this study, we reported for the first time that PDRN was extracted from the sperm of Apostichopus japonicus (AJS-PDRN), and we evaluated its antioxidant activity using 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2'-azino-bis-3-ethylbenzothiazoline-6-sulphonic acid (ABTS), and hydroxyl radical scavenging assays. An in vitro injury model was established using H2O2-induced oxidative damage in RAW264.7 cells, and we investigated the protective effect of AJS-PDRN on these cells. Additionally, we explored the potential mechanism by which AJS-PDRN protects RAW264.7 cells from damage using iTRAQ proteomics analysis. The results showed that AJS-PDRN possessed excellent antioxidant activity and could significantly scavenge DPPH, ABTS, and hydroxyl radicals. In vitro antioxidant assays demonstrated that AJS-PDRN was cytoprotective and significantly enhanced the antioxidant capacity of RAW264.7 cells. The results of GO enrichment and KEGG pathway analysis indicate that the protective effects of AJS-PDRN pretreatment on RAW264.7 cells are primarily achieved through the regulation of immune and inflammatory responses, modulation of the extracellular matrix and signal transduction pathways, promotion of membrane repair, and enhancement of cellular antioxidant capacity. The results of a protein-protein interaction (PPI) network analysis indicate that AJS-PDRN reduces cellular oxidative damage by upregulating the expression of intracellular selenoprotein family members. In summary, our findings reveal that AJS-PDRN mitigates H2O2-induced oxidative damage through multiple pathways, underscoring its significant potential in the prevention and treatment of diseases caused by oxidative stress.

Refinement of paramagnetic bead-based digestion protocol for automatic sample preparation using an artificial neural network

Despite technological advances in the proteomics field, sample preparation still represents the main bottleneck in mass spectrometry (MS) analysis. Bead-based protein aggregation techniques have recently emerged as an efficient, reproducible, and high-throughput alternative for protein extraction and digestion. Here, a refined paramagnetic bead-based digestion protocol is described for Opentrons® OT-2 platform (OT-2) as a versatile, reproducible, and affordable alternative for the automatic sample preparation for MS analysis. For this purpose, an artificial neural network (ANN) was applied to maximize the number of peptides without missed cleavages identified in HeLa extract by combining factors such as the quantity (μg) of trypsin/Lys-C and beads (MagReSyn® Amine), % (w/v) SDS, % (v/v) acetonitrile, and time of digestion (h). ANN model predicted the optimal conditions for the digestion of 50 μg of HeLa extract, pointing to the use of 2.5% (w/v) SDS and 300 μg of beads for sample preparation and long-term digestion (16h) with 0.15 μg Lys-C and 2.5 μg trypsin (≈1:17 ratio). Based on the results of the ANN model, the manual protocol was automated in OT-2. The performance of the automatic protocol was evaluated with different sample types, including human plasma, Arabidopsis thaliana leaves, Escherichia coli cells, and mouse tissue cortex, showing great reproducibility and low sample-to-sample variability in all cases. In addition, we tested the performance of this method in the preparation of a challenging biological fluid such as rat bile, a proximal fluid that is rich in bile salts, bilirubin, cholesterol, and fatty acids, among other MS interferents. Compared to other protocols described in the literature for the extraction and digestion of bile proteins, the method described here allowed identify 385 unique proteins, thus contributing to improving the coverage of the bile proteome.

Post-translational modification-centric 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 the high-throughput, functional assessment of phosphorylation sites 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 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.

Post-natal muscle growth and protein turnover: a narrative review of current understanding

A model explaining the dietary-protein-driven post-natal skeletal muscle growth and protein turnover in the rat is updated, and the mechanisms involved are described, in this narrative review. Dietary protein controls both bone length and muscle growth, which are interrelated through mechanotransduction mechanisms with muscle growth induced both from stretching subsequent to bone length growth and from internal work against gravity. This induces satellite cell activation, myogenesis and remodelling of the extracellular matrix, establishing a growth capacity for myofibre length and cross-sectional area. Protein deposition within this capacity is enabled by adequate dietary protein and other key nutrients. After briefly reviewing the experimental animal origins of the growth model, key concepts and processes important for growth are reviewed. These include the growth in number and size of the myonuclear domain, satellite cell activity during post-natal development and the autocrine/paracrine action of IGF-1. Regulatory and signalling pathways reviewed include developmental mechanotransduction, signalling through the insulin/IGF-1-PI3K-Akt and the Ras-MAPK pathways in the myofibre and during mechanotransduction of satellite cells. Likely pathways activated by maximal-intensity muscle contractions are highlighted and the regulation of the capacity for protein synthesis in terms of ribosome assembly and the translational regulation of 5-TOPmRNA classes by mTORC1 and LARP1 are discussed. Evidence for and potential mechanisms by which volume limitation of muscle growth can occur which would limit protein deposition within the myofibre are reviewed. An understanding of how muscle growth is achieved allows better nutritional management of its growth in health and disease.

Mapping protein-protein interactions by mass spectrometry

Protein-protein interactions (PPIs) are essential for numerous biological activities, including signal transduction, transcription control, and metabolism. They play a pivotal role in the organization and function of the proteome, and their perturbation is associated with various diseases, such as cancer, neurodegeneration, and infectious diseases. Recent advances in mass spectrometry (MS)-based protein interactomics have significantly expanded our understanding of the PPIs in cells, with techniques that continue to improve in terms of sensitivity, and specificity providing new opportunities for the study of PPIs in diverse biological systems. These techniques differ depending on the type of interaction being studied, with each approach having its set of advantages, disadvantages, and applicability. This review highlights recent advances in enrichment methodologies for interactomes before MS analysis and compares their unique features and specifications. It emphasizes prospects for further improvement and their potential applications in advancing our knowledge of PPIs in various biological contexts.

Exercise-Regulated Mitochondrial and Nuclear Signalling Networks in Skeletal Muscle

Exercise perturbs energy homeostasis in skeletal muscle and engages integrated cellular signalling networks to help meet the contraction-induced increases in skeletal muscle energy and oxygen demand. Investigating exercise-associated perturbations in skeletal muscle signalling networks has uncovered novel mechanisms by which exercise stimulates skeletal muscle mitochondrial biogenesis and promotes whole-body health and fitness. While acute exercise regulates a complex network of protein post-translational modifications (e.g. phosphorylation) in skeletal muscle, previous investigations of exercise signalling in human and rodent skeletal muscle have primarily focused on a select group of exercise-regulated protein kinases [i.e. 5' adenosine monophosphate-activated protein kinase (AMPK), protein kinase A (PKA), Ca2+/calmodulin-dependent protein kinase (CaMK) and mitogen-activated protein kinase (MAPK)] and only a small subset of their respective protein substrates. Recently, global mass spectrometry-based phosphoproteomic approaches have helped unravel the extensive complexity and interconnection of exercise signalling pathways and kinases beyond this select group and phosphorylation and/or translocation of exercise-regulated mitochondrial and nuclear protein substrates. This review provides an overview of recent advances in our understanding of the molecular events associated with acute endurance exercise-regulated signalling pathways and kinases in skeletal muscle with a focus on phosphorylation. We critically appraise recent evidence highlighting the involvement of mitochondrial and nuclear protein phosphorylation and/or translocation in skeletal muscle adaptive responses to an acute bout of endurance exercise that ultimately stimulate mitochondrial biogenesis and contribute to exercise's wider health and fitness benefits.

IMPRINTS.CETSA and IMPRINTS.CETSA.app: an R package and a Shiny application for the analysis and interpretation of IMPRINTS-CETSA data

IMPRINTS-CETSA (Integrated Modulation of Protein Interaction States-Cellular Thermal Shift Assay) provides a highly resolved means to systematically study the interactions of proteins with other cellular components, including metabolites, nucleic acids and other proteins, at the proteome level, but no freely available and user-friendly data analysis software has been reported. Here, we report IMPRINTS.CETSA, an R package that provides the basic data processing framework for robust analysis of the IMPRINTS-CETSA data format, from preprocessing and normalization to visualization. We also report an accompanying R package, IMPRINTS.CETSA.app, which offers a user-friendly Shiny interface for analysis and interpretation of IMPRINTS-CETSA results, with seamless features such as functional enrichment and mapping to other databases at a single site. For the hit generation part, the diverse behaviors of protein modulations have been typically segregated with a two-measure scoring method, i.e. the abundance and thermal stability changes. We present a new algorithm to classify modulated proteins in IMPRINTS-CETSA experiments by a robust single-measure scoring. In this way, both the numerical changes and the statistical significances of the IMPRINTS information can be visualized on a single plot. The IMPRINTS.CETSA and IMPRINTS.CETSA.app R packages are freely available on GitHub at https://github.com/nkdailingyun/IMPRINTS.CETSA and https://github.com/mgerault/IMPRINTS.CETSA.app, respectively. IMPRINTS.CETSA.app is also available as an executable program at https://zenodo.org/records/10636134.

Innovative strategies for measuring kinase activity to accelerate the next wave of novel kinase inhibitors

The development of protein kinase inhibitors (PKIs) has gained significance owing to their therapeutic potential for diseases like cancer. In addition, there has been a rise in refining kinase activity assays, each possessing unique biological and analytical characteristics crucial for PKI development. However, the PKI development pipeline experiences high attrition rates and approved PKIs exhibit unexploited potential because of variable patient responses. Enhancing PKI development efficiency involves addressing challenges related to understanding the PKI mechanism of action and employing biomarkers for precision medicine. Selecting appropriate kinase activity assays for these challenges can overcome these attrition rate issues. This review delves into the current obstacles in kinase inhibitor development and elucidates kinase activity assays that can provide solutions.

Deciphering Drug Targets and Actions with Single-Cell and Spatial Resolution

Recent advances in chemical, molecular, and genetic approaches have provided us with an unprecedented capacity to identify drug-target interactions across the whole proteome and genome. Meanwhile, rapid developments of single-cell and spatial omics technologies are revolutionizing our understanding of the molecular architecture of biological systems. However, a significant gap remains in how we align our understanding of drug actions, traditionally based on molecular affinities, with the in vivo cellular and spatial tissue heterogeneity revealed by these newer techniques. Here, we review state-of-the-art methods for profiling drug-target interactions and emerging multiomics tools to delineate the tissue heterogeneity at single-cell resolution. Highlighting the recent technical advances enabling high-resolution, multiplexable in situ small-molecule drug imaging (clearing-assisted tissue click chemistry, or CATCH), we foresee the integration of single-cell and spatial omics platforms, data, and concepts into the future framework of defining and understanding in vivo drug-target interactions and mechanisms of actions.

TransGCN: a semi-supervised graph convolution network-based framework to infer protein translocations in spatio-temporal proteomics

Protein subcellular localization (PSL) is very important in order to understand its functions, and its movement between subcellular niches within cells plays fundamental roles in biological process regulation. Mass spectrometry-based spatio-temporal proteomics technologies can help provide new insights of protein translocation, but bring the challenge in identifying reliable protein translocation events due to the noise interference and insufficient data mining. We propose a semi-supervised graph convolution network (GCN)-based framework termed TransGCN that infers protein translocation events from spatio-temporal proteomics. Based on expanded multiple distance features and joint graph representations of proteins, TransGCN utilizes the semi-supervised GCN to enable effective knowledge transfer from proteins with known PSLs for predicting protein localization and translocation. Our results demonstrate that TransGCN outperforms current state-of-the-art methods in identifying protein translocations, especially in coping with batch effects. It also exhibited excellent predictive accuracy in PSL prediction. TransGCN is freely available on GitHub at https://github.com/XuejiangGuo/TransGCN.

Development of a sample preparation method for micro-proteomics analysis of the formaldehyde-fixed paraffin-embedded liver tissue samples

Liver micro-proteomics based on the routinely used formaldehyde-fixed paraffin-embedded (FFPE) samples is valuable for innovative research, but the technical approach for sample preparation is often challenging. In this study, we aimed to develop a method for sample preparation for micro-proteomics on using the FFPE liver samples. We collected 2000 individual cells per batch from FFPE liver slices with laser capture microdissection and used them as test samples. We used the microscale fresh-frozen liver samples or HepG2 cells as control samples. For the FFPE samples, we first established a procedure for protein extraction. 2 h incubation at 95 °C in alkaline amine buffer supplemented with 4% sodium dodecyl sulfate allows improved production, efficiency, and quality of protein extraction. Then, we developed a dedicated protocol HDMSP for the micro-concentrated (<0.05 μg/μL) protein preparation for mass spectrometry (MS) based analysis, in which 2 μg/μL carboxyl magnetic beads and 70% acetonitrile are used to induce protein precipitation. For the 0.01 μg/μL protein control samples, protein recovery rate (PRR) by HDMSP is 72.1%, while the PRR is 5.9% if using a standard method solid phase-enhanced sample preparation. For the FFPE samples, the HDMSP PRR is 88.8%, and the subsequent MS analysis demonstrates increased depth, robustness, and quantitation accuracy for HDMSP relative to the control of in-gel digestion. Moreover, the physicochemical properties and subcellular location of the FFPE liver micro-proteome are comparable to those of the fresh-frozen control samples processed with filter-aided sample preparation (FASP). HDMSP is also comparable to FASP in terms of reproducibility and physicochemical properties in liver subcellular proteomes, and meanwhile reduces the sample preparation time by 15.9% and the experimental cost by 30.8%. Overall, the new method is simple and highly effective for preparing the microscale FFPE liver protein samples for MS analysis. This study provides a useful solution for FFPE liver micro-proteomics.

Role of Glycolytic and Glutamine Metabolism Reprogramming on the Proliferation, Invasion, and Apoptosis Resistance through Modulation of Signaling Pathways in Glioblastoma

Glioma cells exhibit genetic and metabolic alterations that affect the deregulation of several cellular signal transduction pathways, including those related to glucose metabolism. Moreover, oncogenic signaling pathways induce the expression of metabolic genes, increasing the metabolic enzyme activities and thus the critical biosynthetic pathways to generate nucleotides, amino acids, and fatty acids, which provide energy and metabolic intermediates that are essential to accomplish the biosynthetic needs of glioma cells. In this review, we aim to explore how dysregulated metabolic enzymes and their metabolites from primary metabolism pathways in glioblastoma (GBM) such as glycolysis and glutaminolysis modulate anabolic and catabolic metabolic pathways as well as pro-oncogenic signaling and contribute to the formation, survival, growth, and malignancy of glioma cells. Also, we discuss promising therapeutic strategies by targeting the key players in metabolic regulation. Therefore, the knowledge of metabolic reprogramming is necessary to fully understand the biology of malignant gliomas to improve patient survival significantly.

Investigating the cell membrane localization of PADI4 in breast cancer cells and inhibition of anti-PADI4 monoclonal antibody

BACKGROUND

Peptidyl arginine deiminase 4 (PADI4) is a post-translational modification enzymecan that converts arginine in protein into citrulline in the presence of calcium ions, which is called citrullination. PADI4 has been reported to be expressed in the cytoplasm and nucleus in a variety of malignant tumors. Based on the GeneCards database and our previous research, it is speculated that PADI4 may also be expressed on the cell membrane. This study aimed to confirm the membrane expression of PADI4 and the effect of anti-PADI4 antibodies on cell membrane PADI4. This may be another mechanism of action of anti-PADI4 monoclonal antibodies in the treatment of breast cancer.

METHODS

The subcellular localizations of PADI4 in MDA-MB-231 and MCF-7 breast cancer cells were determined by immunofluorescence, immunoelectron microscopy, and Western blot analysis. The tumor cells were treated with PADI4 antibody, and cell proliferation, migration, colony formation, apoptosis, glycolysis, and epithelial-mesenchymal transition (EMT) were measured as well as the expression of some essential tumor genes.

RESULTS

PADI4 was not only localized in the nucleus and cytoplasm of breast cancer cells but was also detected on the cell membrane. Following PADI4 antibody treatment, cell proliferation, migration, colony formation, EMT, and ATP production through glycolysis were decreased, and the mRNA expression of MYC proto-oncogene (MYC), FAT atypical cadherin 1 (FAT1), nuclear factor kappa B subunit 1 (NFκB), and tumor necrosis factor (TNF-α) in breast cancer cells was downregulated, while the mRNA expression of tumor protein p63 (TP63) was upregulated.

CONCLUSIONS

PADI4 is expressed on the cell membrane in breast cancer cells. Anti-PADI4 antibodies can affect the biological functions of cell membrane PADI4, including proliferation, migration, apoptosis, and glycolysis, thereby inhibiting tumor progression.

Keep in touch: a perspective on the mitochondrial social network and its implication in health and disease

Mitochondria have been the focus of extensive research for decades since their dysfunction is linked to more than 150 distinct human disorders. Despite considerable efforts, researchers have only been able to skim the surface of the mitochondrial social complexity and the impact of inter-organelle and inter-organ communication alterations on human health. While some progress has been made in deciphering connections among mitochondria and other cytoplasmic organelles through direct (i.e., contact sites) or indirect (i.e., inter-organelle trafficking) crosstalk, most of these efforts have been restricted to a limited number of proteins involved in specific physiological pathways or disease states. This research bottleneck is further narrowed by our incomplete understanding of the cellular alteration timeline in a specific pathology, which prevents the distinction between a primary organelle dysfunction and the defects occurring due to the disruption of the organelle's interconnectivity. In this perspective, we will (i) summarize the current knowledge on the mitochondrial crosstalk within cell(s) or tissue(s) in health and disease, with a particular focus on neurodegenerative disorders, (ii) discuss how different large-scale and targeted approaches could be used to characterize the different levels of mitochondrial social complexity, and (iii) consider how investigating the different expression patterns of mitochondrial proteins in different cell types/tissues could represent an important step forward in depicting the distinctive architecture of inter-organelle communication.

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.

Conditional fluorescent mouse translocation reporters for ERK1/2 and AKT signaling

Understanding how cells activate intracellular signaling pathways in response to external signals, such as growth factors, is a longstanding goal of cell and developmental biology. Recently, live-cell signaling reporters have greatly expanded our understanding of signaling dynamics in response to wide-ranging stimuli and chemical or genetic perturbation, both ex vivo (cell lines) and in vivo (whole embryos or animals). Among the many varieties of reporter systems, translocation reporters that change sub-cellular localization in response to pathway activation have received considerable attention for their ease of use compared to FRET systems and favorable response times compared to transcriptional reporters. We reasoned that mouse reporter lines expressed in a conditional fashion would be a useful addition to the arsenal of mouse genetic tools, as such lines remain undeveloped despite widespread use of these sensors. We therefore created and validated two novel mouse reporter lines at the ROSA26 locus. One expresses an ERK1/2 pathway reporter and a nuclear marker from a single transcript, while the second additionally expresses an AKT reporter in order to simultaneously interrogate both pathways.

Intracellular spatiotemporal metabolism in connection to target engagement

The metabolism in eukaryotic cells is a highly ordered system involving various cellular compartments, which fluctuates based on physiological rhythms. Organelles, as the smallest independent sub-cell unit, are important contributors to cell metabolism and drug metabolism, collectively designated intracellular metabolism. However, disruption of intracellular spatiotemporal metabolism can lead to disease development and progression, as well as drug treatment interference. In this review, we systematically discuss spatiotemporal metabolism in cells and cell subpopulations. In particular, we focused on metabolism compartmentalization and physiological rhythms, including the variation and regulation of metabolic enzymes, metabolic pathways, and metabolites. Additionally, the intricate relationship among intracellular spatiotemporal metabolism, metabolism-related diseases, and drug therapy/toxicity has been discussed. Finally, approaches and strategies for intracellular spatiotemporal metabolism analysis and potential target identification are introduced, along with examples of potential new drug design based on this.

Deep and fast label-free Dynamic Organellar Mapping

The Dynamic Organellar Maps (DOMs) approach combines cell fractionation and shotgun-proteomics for global profiling analysis of protein subcellular localization. Here, we enhance the performance of DOMs through data-independent acquisition (DIA) mass spectrometry. DIA-DOMs achieve twice the depth of our previous workflow in the same mass spectrometry runtime, and substantially improve profiling precision and reproducibility. We leverage this gain to establish flexible map formats scaling from high-throughput analyses to extra-deep coverage. Furthermore, we introduce DOM-ABC, a powerful and user-friendly open-source software tool for analyzing profiling data. We apply DIA-DOMs to capture subcellular localization changes in response to starvation and disruption of lysosomal pH in HeLa cells, which identifies a subset of Golgi proteins that cycle through endosomes. An imaging time-course reveals different cycling patterns and confirms the quantitative predictive power of our translocation analysis. DIA-DOMs offer a superior workflow for label-free spatial proteomics as a systematic phenotype discovery tool.

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.

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.

Prospects of Using Protein Engineering for Selective Drug Delivery into a Specific Compartment of Target Cells

A large number of proteins are successfully used to treat various diseases. These include natural polypeptide hormones, their synthetic analogues, antibodies, antibody mimetics, enzymes, and other drugs based on them. Many of them are demanded in clinical settings and commercially successful, mainly for cancer treatment. The targets for most of the aforementioned drugs are located at the cell surface. Meanwhile, the vast majority of therapeutic targets, which are usually regulatory macromolecules, are located inside the cell. Traditional low molecular weight drugs freely penetrate all cells, causing side effects in non-target cells. In addition, it is often difficult to elaborate a small molecule that can specifically affect protein interactions. Modern technologies make it possible to obtain proteins capable of interacting with almost any target. However, proteins, like other macromolecules, cannot, as a rule, freely penetrate into the desired cellular compartment. Recent studies allow us to design multifunctional proteins that solve these problems. This review considers the scope of application of such artificial constructs for the targeted delivery of both protein-based and traditional low molecular weight drugs, the obstacles met on the way of their transport to the specified intracellular compartment of the target cells after their systemic bloodstream administration, and the means to overcome those difficulties.

Spatially Resolved Top-Down Proteomics of Tissue Sections Based on a Microfluidic Nanodroplet Sample Preparation Platform

Conventional proteomic approaches measure the averaged signal from mixed cell populations or bulk tissues, leading to the dilution of signals arising from subpopulations of cells that might serve as important biomarkers. Recent developments in bottom-up proteomics have enabled spatial mapping of cellular heterogeneity in tissue microenvironments. However, bottom-up proteomics cannot unambiguously define and quantify proteoforms, which are intact (i.e., functional) forms of proteins capturing genetic variations, alternatively spliced transcripts and posttranslational modifications. Herein, we described a spatially resolved top-down proteomics (TDP) platform for proteoform identification and quantitation directly from tissue sections. The spatial TDP platform consisted of a nanodroplet processing in one pot for trace samples-based sample preparation system and an laser capture microdissection-based cell isolation system. We improved the nanodroplet processing in one pot for trace samples sample preparation by adding benzonase in the extraction buffer to enhance the coverage of nucleus proteins. Using ∼200 cultured cells as test samples, this approach increased total proteoform identifications from 493 to 700; with newly identified proteoforms primarily corresponding to nuclear proteins. To demonstrate the spatial TDP platform in tissue samples, we analyzed laser capture microdissection-isolated tissue voxels from rat brain cortex and hypothalamus regions. We quantified 509 proteoforms within the union of top-down mass spectrometry-based proteoform identification and characterization and TDPortal identifications to match with features from protein mass extractor. Several proteoforms corresponding to the same gene exhibited mixed abundance profiles between two tissue regions, suggesting potential posttranslational modification-specific spatial distributions. The spatial TDP workflow has prospects for biomarker discovery at proteoform level from small tissue sections.

Protein-Peptide Turnover Profiling reveals the order of PTM addition and removal during protein maturation

Post-translational modifications (PTMs) regulate various aspects of protein function, including degradation. Mass spectrometric methods relying on pulsed metabolic labeling are popular to quantify turnover rates on a proteome-wide scale. Such data have traditionally been interpreted in the context of protein proteolytic stability. Here, we combine theoretical kinetic modeling with experimental pulsed stable isotope labeling of amino acids in cell culture (pSILAC) for the study of protein phosphorylation. We demonstrate that metabolic labeling combined with PTM-specific enrichment does not measure effects of PTMs on protein stability. Rather, it reveals the relative order of PTM addition and removal along a protein's lifetime-a fundamentally different metric. This is due to interconversion of the measured proteoform species. Using this framework, we identify temporal phosphorylation sites on cell cycle-specific factors and protein complex assembly intermediates. Our results thus allow tying PTMs to the age of the modified proteins.

Spatially resolved phosphoproteomics reveals fibroblast growth factor receptor recycling-driven regulation of autophagy and survival

Receptor Tyrosine Kinase (RTK) endocytosis-dependent signalling drives cell proliferation and motility during development and adult homeostasis, but is dysregulated in diseases, including cancer. The recruitment of RTK signalling partners during endocytosis, specifically during recycling to the plasma membrane, is still unknown. Focusing on Fibroblast Growth Factor Receptor 2b (FGFR2b) recycling, we reveal FGFR signalling partners proximal to recycling endosomes by developing a Spatially Resolved Phosphoproteomics (SRP) approach based on APEX2-driven biotinylation followed by phosphorylated peptides enrichment. Combining this with traditional phosphoproteomics, bioinformatics, and targeted assays, we uncover that FGFR2b stimulated by its recycling ligand FGF10 activates mTOR-dependent signalling and ULK1 at the recycling endosomes, leading to autophagy suppression and cell survival. This adds to the growing importance of RTK recycling in orchestrating cell fate and suggests a therapeutically targetable vulnerability in ligand-responsive cancer cells. Integrating SRP with other systems biology approaches provides a powerful tool to spatially resolve cellular signalling.

Spatially resolved phosphoproteomics reveals fibroblast growth factor receptor recycling-driven regulation of autophagy and survival

Receptor Tyrosine Kinase (RTK) endocytosis-dependent signalling drives cell proliferation and motility during development and adult homeostasis, but is dysregulated in diseases, including cancer. The recruitment of RTK signalling partners during endocytosis, specifically during recycling to the plasma membrane, is still unknown. Focusing on Fibroblast Growth Factor Receptor 2b (FGFR2b) recycling, we reveal FGFR signalling partners proximal to recycling endosomes by developing a Spatially Resolved Phosphoproteomics (SRP) approach based on APEX2-driven biotinylation followed by phosphorylated peptides enrichment. Combining this with traditional phosphoproteomics, bioinformatics, and targeted assays, we uncover that FGFR2b stimulated by its recycling ligand FGF10 activates mTOR-dependent signalling and ULK1 at the recycling endosomes, leading to autophagy suppression and cell survival. This adds to the growing importance of RTK recycling in orchestrating cell fate and suggests a therapeutically targetable vulnerability in ligand-responsive cancer cells. Integrating SRP with other systems biology approaches provides a powerful tool to spatially resolve cellular signalling.

Phosphoproteomics of primary AML patient samples reveals rationale for AKT combination therapy and p53 context to overcome selinexor resistance

Acute myeloid leukemia (AML) is a heterogeneous disease with variable patient responses to therapy. Selinexor, an inhibitor of nuclear export, has shown promising clinical activity for AML. To identify the molecular context for monotherapy sensitivity as well as rational drug combinations, we profile selinexor signaling responses using phosphoproteomics in primary AML patient samples and cell lines. Functional phosphosite scoring reveals that p53 function is required for selinexor sensitivity consistent with enhanced efficacy of selinexor in combination with the MDM2 inhibitor nutlin-3a. Moreover, combining selinexor with the AKT inhibitor MK-2206 overcomes dysregulated AKT-FOXO3 signaling in resistant cells, resulting in synergistic anti-proliferative effects. Using high-throughput spatial proteomics to profile subcellular compartments, we measure global proteome and phospho-proteome dynamics, providing direct evidence of nuclear translocation of FOXO3 upon combination treatment. Our data demonstrate the potential of phosphoproteomics and functional phosphorylation site scoring to successfully pinpoint key targetable signaling hubs for rational drug combinations.

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Phosphoproteomics with functional scoring uncovers context for selinexor sensitivity

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Functional p53 correlates with selinexor sensitivity, which is enhanced by nutlin-3a

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Dysregulated AKT-FOXO3 drives selinexor resistance, which is overcome with MK-2206

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Spatial proteomics reveals selinexor-induced nucleocytoplasmic protein shuttling

Rapid and in-depth coverage of the (phospho-)proteome with deep libraries and optimal window design for dia-PASEF

Data-independent acquisition (DIA) methods have become increasingly attractive in mass spectrometry–based proteomics because they enable high data completeness and a wide dynamic range. Recently, we combined DIA with parallel accumulation–serial fragmentation (dia-PASEF) on a Bruker trapped ion mobility (IM) separated quadrupole time-of-flight mass spectrometer. This requires alignment of the IM separation with the downstream mass selective quadrupole, leading to a more complex scheme for dia-PASEF window placement compared with DIA. To achieve high data completeness and deep proteome coverage, here we employ variable isolation windows that are placed optimally depending on precursor density in the m/z and IM plane. This is implemented in the freely available py_diAID (Python package for DIA with an automated isolation design) package. In combination with in-depth project-specific proteomics libraries and the Evosep liquid chromatography system, we reproducibly identified over 7700 proteins in a human cancer cell line in 44 min with quadruplicate single-shot injections at high sensitivity. Even at a throughput of 100 samples per day (11 min liquid chromatography gradients), we consistently quantified more than 6000 proteins in mammalian cell lysates by injecting four replicates. We found that optimal dia-PASEF window placement facilitates in-depth phosphoproteomics with very high sensitivity, quantifying more than 35,000 phosphosites in a human cancer cell line stimulated with an epidermal growth factor in triplicate 21 min runs. This covers a substantial part of the regulated phosphoproteome with high sensitivity, opening up for extensive systems-biological studies.

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Optimal dia-PASEF window design with py_diAID combined with deep libraries.

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Quantification of the HeLa cell proteome to a depth of >7700 in only 44 min.

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Ion mobility–resolved phosphoproteomics determines >35,000 class I phosphosites.

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py_diAID is freely available as GUI, CLI, and Python modules.

Advances in enrichment methods for mass spectrometry-based proteomics analysis of post-translational modifications

Post-translational modifications (PTMs) occur during or after protein biosynthesis and increase the functional diversity of proteome. They comprise phosphorylation, acetylation, methylation, glycosylation, ubiquitination, sumoylation (among many other modifications), and influence all aspects of cell biology. Mass-spectrometry (MS)-based proteomics is the most powerful approach for PTM analysis. Despite this, it is challenging due to low abundance and labile nature of many PTMs. Hence, enrichment of modified peptides is required for MS analysis. This review provides an overview of most common PTMs and a discussion of current enrichment methods for MS-based proteomics analysis. The traditional affinity strategies, including immunoenrichment, chromatography and protein pull-down, are outlined together with their strengths and shortcomings. Moreover, a special attention is paid to chemical enrichment strategies, such as capture by chemoselective probes, metabolic and chemoenzymatic labelling, which are discussed with an emphasis on their recent progress. Finally, the challenges and future trends in the field are discussed.

Intein-Mediated Protein Engineering for Cell-Based Biosensors

Cell-based sensors provide a flexible platform for screening biologically active targets and for monitoring their interactions in live cells. Their applicability extends across a vast array of biological research and clinical applications. Particularly, cell-based sensors are becoming a potent tool in drug discovery and cell-signaling studies by allowing function-based screening of targets in biologically relevant environments and enabling the in vivo visualization of cellular signals in real-time with an outstanding spatiotemporal resolution. In this review, we aim to provide a clear view of current cell-based sensor technologies, their limitations, and how the recent improvements were using intein-mediated protein engineering. We first discuss the characteristics of cell-based sensors and present several representative examples with a focus on their design strategies, which differentiate cell-based sensors from in vitro analytical biosensors. We then describe the application of intein-mediated protein engineering technology for cell-based sensor fabrication. Finally, we explain the characteristics of intein-mediated reactions and present examples of how the intein-mediated reactions are used to improve existing methods and develop new approaches in sensor cell fabrication to address the limitations of current technologies.

Obtaining Complete Human Proteomes

Proteins are the molecular effectors of the information encoded in the genome. Proteomics aims at understanding the molecular functions of proteins in their biological context. In contrast to transcriptomics and genomics, the study of proteomes provides deeper insight into the dynamic regulatory layers encoded at the protein level, such as posttranslational modifications, subcellular localization, cell signaling, and protein-protein interactions. Currently, mass spectrometry (MS)-based proteomics is the technology of choice for studying proteomes at a system-wide scale, contributing to clinical biomarker discovery and fundamental molecular biology. MS technologies are continuously being developed to fulfill the requirements of speed, resolution, and quantitative accuracy, enabling the acquisition of comprehensive proteomes. In this review, we present how MS technology and acquisition methods have evolved to meet the requirements of cutting-edge proteomics research, which is describing the human proteome and its dynamic posttranslational modifications with unprecedented depth. Finally, we provide a perspective on studying proteomes at single-cell resolution. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 23 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Proximity-Dependent Biotinylation Approaches to Explore the Dynamic Compartmentalized Proteome

In recent years, proximity-dependent biotinylation approaches, including BioID, APEX, and their derivatives, have been widely used to define the compositions of organelles and other structures in cultured cells and model organisms. The associations between specific proteins and given compartments are regulated by several post-translational modifications (PTMs); however, these effects have not been systematically investigated using proximity proteomics. Here, we discuss the progress made in this field and how proximity-dependent biotinylation strategies could elucidate the contributions of PTMs, such as phosphorylation, to the compartmentalization of proteins.

A peptidoform based proteomic strategy for studying functions of post-translational modifications

Protein post-translational modifications (PTMs) generate an enormous, but as yet undetermined, expansion of the produced proteoforms. In this Viewpoint, we firstly reviewed the concepts of proteoform and peptidoform. We show that many of the current PTM biological investigation and annotation studies largely follow a PTM site-specific rather than proteoform-specific approach. We further illustrate a potentially useful matching strategy in which a particular "modified peptidoform" is matched to the corresponding "unmodified peptidoform" as a reference for the quantitative analysis between samples and conditions. We suggest this strategy has the potential to provide more directly relevant information to learn the PTM site-specific biological functions. Accordingly, we advocate for the wider use of the nomenclature "peptidoform" in future bottom-up proteomic studies.