The advent of targeted protein degradation technologies, particularly Proteolysis-Targeting Chimeras (PROTACs), enable the selective elimination of target proteins and open up new avenues for the treatment of various diseases. This review delves into the pivotal role of mass spectrometry (MS) in the advancement of PROTACs. MS-based methodologies serve as invaluable tools for identifying PROTAC targets, validating their efficacy, and elucidating ubiquitination sites and protein degradation dynamics. These insights profoundly enrich our comprehension of the mechanisms of action and facilitate the rational design of PROTACs. Furthermore, this review discusses the role of MS in the structural analysis of proteins and the formation of ternary complexes crucial for the activity of PROTACs. The synergy between MS and PROTAC technology holds the promise of groundbreaking advancements in drug discovery by deepening our understanding of the underlying mechanisms that govern PROTAC drug action, thereby promoting the development of innovative strategies for disease treatment.

The polarized and domain-specific distribution of membrane ion channels is essential for neuronal homeostasis, but delivery of these proteins to distal neuronal compartments (such as the axonal ends of peripheral sensory neurons) presents a logistical challenge. Recent developments have enabled the real-time imaging of single protein trafficking and the investigation of the life cycle of ion channels across neuronal compartments. These studies have revealed a highly regulated process involving post-translational modifications, vesicular sorting, motor protein-driven transport and targeted membrane insertion. Emerging evidence suggests that neuronal activity and disease states can dynamically modulate ion channel localization, directly influencing excitability. This Review synthesizes current knowledge on the spatiotemporal regulation of ion channel trafficking in both central and peripheral nervous system neurons. Understanding these processes not only advances our fundamental knowledge of neuronal excitability, but also reveals potential therapeutic targets for disorders involving aberrant ion channel distribution, such as chronic pain and neurodegenerative diseases.

Intermolecular interactions underlie all cellular functions, yet visualizing these interactions at the single-molecule level remains challenging. Single-molecule localization microscopy (SMLM) offers a potential solution. Given a nanoscale map of two putative interaction partners, it should be possible to assign molecules either to the class of coupled pairs or to the class of noncoupled bystanders. Here, we developed a probabilistic algorithm that allows accurate determination of both the absolute number and the proportion of molecules that form coupled pairs. The algorithm calculates interaction probabilities for all possible pairs of localized molecules, selects the most likely interaction set, and corrects for any spurious colocalizations. Benchmarking this approach across a set of simulated molecular localization maps with varying densities (up to ∼55 molecules μm-2) and localization precisions (1 to 50 nm) showed typical errors in the identification of correct pairs of only a few percent. At molecular densities of ∼5 to 10 molecules μm-2 and localization precisions of 20 to 30 nm, which are typical parameters for SMLM imaging, the recall was ∼90%. The algorithm was effective at differentiating between noninteracting and coupled molecules both in simulations and experiments. Finally, it correctly inferred the number of coupled pairs over time in a simulated reaction-diffusion system, enabling determination of the underlying rate constants. The proposed approach promises to enable direct visualization and quantification of intermolecular interactions using SMLM.

Traditional mass spectrometry (MS)-based proteomics aims to detect and measure protein expression on a global scale and elucidate the link between protein function and phenotypic characteristics. Although advances in MS technology have significantly broadened the scope of detectable proteomes, these methodologies primarily provide data on protein abundance and offer limited insights into their functional activities. Phenotypic traits emerge from the interplay between protein abundance and functional activity, making the accurate measurement of activity a critical but challenging task, owing to the complexity of biological systems. Furthermore, the biological function of a protein is strongly linked to its interaction with other molecules within the cellular environment. Chemical proteomics offers a complementary approach that uses a toolkit developed in chemical biology to map the molecular interactome and provide initial insights into the activities of specific target proteins. However, the value of these techniques lies not in isolation, but as part of a broader experimental workflow that includes follow-up biological investigations to validate the findings and elucidate their functional relevance. This tutorial review highlights the design principles of chemical tools and examines their applications in two key areas: (i) functional activity profiling of biomolecules and (ii) molecular proximity profiling for interactome characterization. We also discuss the importance of the experimental context in shaping data interpretation and ensuring the practical adoption of these methods by biologists. Although chemical proteomics is not a standalone solution, it represents a promising step toward next-generation omics technologies and advances our understanding of biological functions at the molecular level.

Rett syndrome (RTT) is a neurodevelopmental disorder that is mainly caused by mutations in the methyl-DNA-binding protein MECP2. MECP2 is an important epigenetic regulator that plays a pivotal role in neuronal gene regulation, where it has been reported to function as both a repressor and an activator. Despite extensive efforts in mechanistic studies over the past two decades, a clear consensus on how MECP2 dysfunction impacts molecular mechanisms and contributes to disease progression has not been reached. Here, we review recent insights from epigenomic, transcriptomic and proteomic studies that advance our understanding of MECP2 as an interacting hub for DNA, RNA and transcription factors, orchestrating diverse processes that are crucial for neuronal function. By discussing findings from different model systems, we identify crucial epigenetic details and cofactor interactions, enriching our understanding of the multifaceted roles of MECP2 in transcriptional regulation and chromatin structure. These mechanistic insights offer potential avenues for rational therapeutic design for RTT.

Cell-cell interactions are critical for the growth of organisms and maintaining homeostasis. In the tumor microenvironment, these interactions promote cancer progression. Given their importance in healthy and diseased conditions, we have developed a method to analyze the cell-to-cell interactome. Our approach uses enzyme-catalyzed proximity labeling and SILAC-based proteomics to identify the proteins involved in cancer cell interactions. By targeting HRP to the outer leaflet of the plasma membrane in bait cells, we were able to label the neighboring prey cells and distinguish between the proteomes of bait and prey cells using SILAC labeling in a co-culture system. We mapped both the homotypic and heterotypic interactomes of epithelial and mesenchymal breast cancer cells. The enrichment of cell surface and extracellular proteins confirms the specificity of our methodology. We further verified selected hits from different cell-cell interactomes in co-cultures using microscopy. This method revealed prominent signaling pathways orchestrating homotypic and heterotypic interactions of epithelial and mesenchymal cells. It also highlights the importance of exosomes in these interactions. Our methodology can be applied to any type of cell-cell interaction in 2D co-culture or 3D tumor models.

Proximity labeling (PL) proteomics has emerged as a powerful tool to capture both stable and transient protein interactions and subcellular networks. Despite the wide biological applications, PL still faces technical challenges in robustness, reproducibility, specificity, and sensitivity. Here, we discuss major analytical challenges in PL proteomics and highlight how the field is advancing to address these challenges by refining study design, tackling interferences, overcoming variation, developing novel tools, and establishing more robust platforms. We also provide our perspectives on best practices and the need for more robust, scalable, and quantitative PL technologies.

Cytoplasmic aggregation and nuclear depletion of TAR DNA-binding protein 43 (TDP-43) is a hallmark pathology of several neurodegenerative diseases including amyotrophic lateral sclerosis (ALS), frontotemporal lobar degeneration (FTLD) and limbic-predominant age-related TDP-43 encephalopathy (LATE). However, the protein interactome of TDP-43 remains incompletely defined. In this study, we aimed to identify putative TDP-43 protein partners within the nucleus and the cytoplasm and with different disease models of TDP-43 by comparing TDP-43 interaction partners in three different cell lines. We verified the levels of interaction of protein partners under stress conditions as well as after introducing TDP-43 variants containing ALS missense mutations (G294V and A315T). Overall, we identified 58 putative wild-type TDP-43 interactors, including novel binding partners responsible for RNA metabolism and splicing. Oxidative stress exposure broadly led to changes in TDP-43WT interactions with proteins involved in mRNA metabolism, suggesting a dysregulation of the transcriptional machinery early in disease. Conversely, although G294V and A315T mutations are both located in the C-terminal domain of TDP-43, both mutants presented different interactome profiles with most interaction partners involved in translational and transcriptional machinery. Overall, by correlating different cell lines and disease-simulating interventions, we provide a list of high-confidence TDP-43 interaction partners, including novel and previously reported proteins. Understanding pathological changes to TDP-43 and its specific interaction partners in different models of stress is critical to better understand TDP-43 proteinopathies and provide novel potential therapeutic targets and biomarkers.

Recent studies revealed that membrane-less subcellular organelles play important roles in cellular functions. Here, we present a protocol for identifying subcellular compartment components by antibody-based in situ biotinylation. We describe steps for in situ biotinylation labeling using a horseradish peroxidase (HRP)-conjugated antibody, purification of the biotinylated components, and sample preparation for high-throughput analysis. This protocol has potential for application in the comprehensive analysis of dynamic subcellular organelles. For complete details on the use and execution of this protocol, please refer to Noguchi et al.1.

The cell surface proteome, or surfaceome, is the hub for cells to interact and communicate with the outside world. Many disease-associated changes are hard-wired within the surfaceome, yet approved drugs target less than 50 cell surface proteins. In the past decade, the proteomics community has made significant strides in developing new technologies tailored for studying the surfaceome in all its complexity. In this review, we first dive into the unique characteristics and functions of the surfaceome, emphasizing the necessity for specialized labeling, enrichment, and proteomic approaches. An overview of surfaceomics methods is provided, detailing techniques to measure changes in protein expression and how this leads to novel target discovery. Next, we highlight advances in proximity labeling proteomics (PLP), showcasing how various enzymatic and photoaffinity proximity labeling techniques can map protein-protein interactions and membrane protein complexes on the cell surface. We then review the role of extracellular post-translational modifications, focusing on cell surface glycosylation, proteolytic remodeling, and the secretome. Finally, we discuss methods for identifying tumor-specific peptide MHC complexes and how they have shaped therapeutic development. This emerging field of neo-protein epitopes is constantly evolving, where targets are identified at the proteome level and encompass defined disease-associated PTMs, complexes, and dysregulated cellular and tissue locations. Given the functional importance of the surfaceome for biology and therapy, we view surfaceomics as a critical piece of this quest for neo-epitope target discovery.

Photocatalytic biomolecular labelling is gaining attention as a foundational technique for analyzing biological phenomena. However, photocatalytic reactions compatible with physiological conditions remain limited. Here, we present a photocatalytic reaction of diaryltetrazoles to generate nitrile imines, which readily couple with carboxylic acids in aqueous environments. This reaction is applied for photocatalyst-dependent labelling of proteins and cells.

Stress granules (SGs), transient nonmembranous cytoplasmic condensates that formed in response to cellular stresses, require precise characterization to unravel their cell-type and stress-specific protein compositions. This study introduced a G3BP1 antibody-guided proximity labeling (Ab-PL) method to explore the composition and diversity of SGs, overcoming the challenges of traditional enzyme-mediated proximity labeling techniques across various cell types, especially for the immune cells. Application of Ab-PL to HeLa and RAW264.7 cells under heat shock (HS), sodium arsenate (AS), and sodium chloride stress (SS) revealed two categories of SG proteins: "SG-core" and "SG-shell," characterized by their different abilities to undergo phase separation. The core proteins form the SG scaffold with strong self-segregation, while shell proteins are dynamically recruited based on the type of stress. Cell- and stress-specific SG proteins were also identified, highlighting compositional heterogeneity. Intriguingly, unique nuclear-cytoplasmic shuttling behaviors of SG components were observed under varying conditions, uncovering over 10 novel SG proteins, including REXO4, RBM28, and OGFR. This study provides a versatile tool for SG analysis across diverse cell types and offers insights into SG heterogeneity, which has potential implications for human diseases, paving the way for future studies on RNA metabolism, ribosome assembly, and immune regulation.

Most bioorthogonal photouncaging reactions preferentially occur in polar environments to accommodate biological applications in the aqueous cellular milieu. However, they are not precisely designed to chemically adapt to the diverse microenvironments of the cell. Herein, we report a hydrophobic photouncaging reaction with tailored photolytic kinetics toward solvent polarity. Structural modulations of the aminobenzoquinone-based photocage reveal the impact of cyclic ring size, steric substituent, and electronic substituent on the individual uncaging kinetics (kH2O and kdioxane) and polarity preference (kdioxane/kH2O). Rational incorporation of optimized moieties leads to up to 20.2-fold nonpolar kinetic selectivity (kdioxane/kH2O). Further photochemical spectroscopic characterizations and theoretical calculations together uncover the mechanism underlying the polarity-dependent uncaging kinetics. The uncaged ortho-quinone methide product bears covalent reactivity toward diverse nucleophiles of a protein revealed by tandem mass spectrometry. Finally, we demonstrate the application of such lipophilic photouncaging chemistry toward selective labeling and profiling of proteins in proximity to lipid droplets inside human fatty liver tissues. Together, this work studies the solvent polarity effects of a photouncaging reaction and chemically adapts it toward suborganelle-targeted protein proximity labeling and profiling.

RNA-protein interactions are fundamental to a wide range of biological processes, and understanding these interactions in their native cellular context is both vital and challenging. Traditional methods for studying RNA-protein interactions rely on crosslinking, which can introduce artifacts. Recently, proximity labeling-based techniques have emerged as powerful alternatives, offering a crosslinking-free approach to investigate these interactions. This review highlights recent advancements in the development and application of proximity labeling methods, focusing on both RNA-centric and protein-centric strategies for profiling cellular RNA-protein interactions. By examining these innovative approaches, we aim to provide insights into their potential for enhancing our understanding of RNA-protein dynamics in various biological settings.

DNA methylation is a significant component in proximal chromatin regulation and plays crucial roles in regulating gene expression and maintaining the repressive state of retrotransposon elements. However, accurate profiling of the proteomics which simultaneously identifies specific DNA sequences and their associated epigenetic modifications remains a challenge. Here, we report a strategy termed SelectID (selective profiling of epigenetic control at genome targets identified by dCas9), which introduces methylated DNA binding domain into dCas9-mediated proximity labeling system to enable in situ protein capture at repetitive elements with 5-methylcytosine (5mC) modifications. SelectID is demonstrated as feasible as dCas9-TurboID system at specific DNA methylation regions, such as the chromosome 9 satellite. Using SelectID, we successfully identify CHD4 as potential repressors of methylated long interspersed nuclear element-1 (LINE-1) retrotransposon through direct binding at the 5' untranslated region (5'UTR) of young LINE-1 elements. Overall, our SelectID approach has opened up avenues for uncovering potential regulators of specific DNA regions with DNA methylation, which will greatly facilitate future studies on epigenetic regulation.

Bacterial pathogens have evolved diverse strategies to manipulate host cells to establish infection. At a molecular level, this is often mediated by virulence factors that are secreted into host cells (herein referred to as effectors), which target host cellular pathways by initiating host-pathogen protein-protein interactions that alter cellular function in the host. By establishing this network of host-pathogen protein-protein interactions, pathogenic bacteria modulate and hijack host cell processes for the benefit of the pathogen, ultimately promoting survival, replication, and cell-to-cell spread within the host. Effector proteins also mediate diverse host-microbe interactions in nature, contributing to symbiotic relationships spanning from mutualism to commensalism to parasitism. While effector proteins play crucial roles in nature, molecular properties such as the transient nature of the underlying protein-protein interactions and their affinity for targeting host biological membranes often presents challenges to elucidating host targets and mechanism of action. Proximity-dependent biotin identification (termed BioID) has proven to be a valuable tool in the field of cell biology to identify candidate protein-protein interactions in eukaryotic cells, yet has remained relatively underexploited by bacterial pathogenesis researchers. Here, we discuss bacterial effector function at a molecular level, and challenges presented by traditional approaches to host target identification. We highlight the BioID approach and its potential strengths in the context of identifying host-pathogen protein-protein interactions, and explore BioID's implementation to study host-microbe interactions mediated by bacteria. Collectively, BioID represents a powerful tool for the study of bacterial effector proteins, providing new insight into our understanding of pathogenesis and other symbiotic relationships, and opportunities to identify new factors that contribute to host response to infection.

TDP-43 mislocalization, aggregation, and loss of splicing function are neuropathological hallmarks in over 97% of Amyotrophic Lateral Sclerosis (ALS), 45% of Frontotemporal Lobar Degeneration (FTLD), and 60% of Alzheimer's Disease, which has been reclassified as LATE-NC. However, the mechanisms underlying TDP-43 dysfunction remain elusive. Here, we utilize APEX2-driven proximity labeling and mass spectrometry to characterize the context-dependent TDP-43 interactome in conditions of cytoplasmic mislocalization, impaired RNA-binding contributing to aggregation, and oxidative stress. We describe context-dependent interactors, including disrupted interactions with splicing-related proteins and altered biomolecular condensate (BMC) associations. By integrating ALS and FTLD snRNA-seq data, we uncover disease-relevant molecular alterations and validate our dataset through a functional screen that identifies key TDP- 43 regulators. We demonstrate that disrupting nuclear speckle integrity, particularly through the downregulation of the splicing factor SRRM2, promotes TDP-43 mislocalization and loss of function. Additionally, we identify NUFIP2 as an interactor associated with mislocalization that sequesters TDP-43 into cytoplasmic aggregates and co-localizes with TDP-43 pathology in patient tissue. We also highlight HNRNPC as a potent TDP-43 splicing regulator, where precise modulation of TDP-43 or HNRNPC can rescue cryptic exon splicing. These findings provide mechanistic insights and potential therapeutic targets for TDP-43 dysfunction.

During infection and granuloma formation, pathogenic mycobacteria store triacylglycerol as intrabacterial lipid inclusions (ILIs). This accumulation of nutrients provides a carbon source for bacterial persistence and slows down intracellular metabolism. Mycobacterium abscessus (Mab), a rapidly growing non-tuberculous actinobacterium, produces ILI throughout its infection cycle. Here, Mab was used as a model organism to identify proteins associated with ILI accumulation on a global scale. By using the APEX2 proximity labeling method in an in vitro model for ILI accumulation, we identified 228 proteins possibly implicated in ILI biosynthesis. Fluorescence microscopy of strains overexpressing eight ILI-associated proteins (IAP) candidates fused to superfolder green fluorescent protein showed co-localization with ILI. Genetic inactivation of these potential IAP-encoding genes and subsequent lipid analysis emphasized the importance of MAB_3486 and MAB_4532c as key enzymes influencing triacylglycerol storage. This study underscores the dynamic process of ILI biogenesis and advances our understanding of lipid metabolism in pathogenic mycobacteria. Identifying major IAP in lipid accumulation offers new therapeutic perspectives to control the growth and persistence of pathogenic mycobacteria.

This study sheds light into the complex process of intracellular lipid accumulation and storage in the survival and persistence of pathogenic mycobacteria, which is of clinical relevance. By identifying the proteins involved in the formation of intrabacterial lipid inclusions and revealing their impact on lipid metabolism, our data may lead to the development of new therapeutic strategies to target and control pathogenic mycobacteria, potentially improving outcomes for patients with mycobacterial infections.

Ovarian cancer (OC) is diagnosed at advanced stages, resulting in limited treatment options for patients. While early detection of OC has been investigated, the invasiveness of approaches, high sample requirements, or false-positive rates undermined its benefits. Here, we present a "one-step" high-throughput microfluidic platform for epithelial ovarian cancer (EOC) detection that integrates small extracellular vesicle (sEV) capture, in situ lysis, and protein biomarker detection.

We identified 1,818 differentially expressed proteins (DEPs) through proteomic analysis of sEVs from patients' serum, combined with cell lines. Through multi-step screening of DEPs, we identified EOC biomarkers to customize the microfluidic platform. We used the microfluidic platform to test the expression of EOC biomarkers with 2 µL of serum from 209 participants in a prospective cohort. Based on the test results, an EOC detection model (P9) was constructed, which achieved a sensitivity of 92.3% (95% CI, 75.9-97.9%) for stage I, 90.0% (95% CI, 69.9-97.2%) for stage II at a specificity of 98.8% (95% CI, 93.6-99.8%) in the training set. The specificities reached 98.8% (95% CI, 93.6-99.8%) in the training set and 100.0% (95% CI, 91.6-100.0%) in the validation set of a held-out group of 105 participants. A model combining the P9 and patient's CA125 value exhibited 100.0% (95% CI, 95.6-100%) specificity in both training and validation, without compromising sensitivity.

We developed a non-invasive high-throughput microfluidic platform for EOC sEV-derived biomarker detection. It significantly reduced false positives and sample volume. Given its convenience and low cost, this platform could advance OC early detection to benefit of women.

The composition and organization of the cell surface determine how cells interact with their environment. Traditionally, glycosylated transmembrane proteins were thought to be the major constituents of the external surface of the plasma membrane. Here, we provide evidence that a group of RNA-binding proteins (RBPs) is present on the surface of living cells. These cell-surface RBPs (csRBPs) precisely organize into well-defined nanoclusters enriched for multiple RBPs and glycoRNAs, and their clustering can be disrupted by extracellular RNase addition. These glycoRNA-csRBP clusters further serve as sites of cell-surface interaction for the cell-penetrating peptide trans-activator of transcription (TAT). Removal of RNA from the cell surface, or loss of RNA-binding activity by TAT, causes defects in TAT cell internalization. Together, we provide evidence of an expanded view of the cell surface by positioning glycoRNA-csRBP clusters as a regulator of communication between cells and the extracellular environment.

Horseradish peroxidase (HRP), isolated from horseradish roots, is heavily glycosylated, making it difficult to crystallize. In this work, we produced recombinant HRP in E. coli and obtained an X-ray structure of the ferric enzyme at 1.63 Å resolution. The structure shows that the recombinant HRP contains four disulphide bonds and two calcium ions, which are highly conserved in class III peroxidase enzymes. The heme active site contains histidine residues at the proximal (His 170) and distal (His 42) positions, and an active site arginine (Arg 38). Surprisingly, an ethylene glycol molecule was identified in the active site, forming hydrogen bonds with His 42 and Arg 38 at the δ-heme edge. The high yields obtained from the recombinant expression system, and the successful crystallization of the enzyme pave the way for new structural studies in the future.

Biased signaling has transformed pharmacology by revealing that receptors, particularly G protein-coupled receptors (GPCRs), can activate specific intracellular pathways selectively rather than uniformly. This discovery enables the development of targeted therapeutics that minimize side effects by precisely modulating receptor activity. Functionally selective ligands, which preferentially activate distinct signaling branches, have become essential tools for exploring receptor mechanisms and uncovering the complexities of GPCR signaling. These ligands help clarify receptor function in various physiological and pathological contexts, offering profound implications for therapeutic innovation. GPCRs, which mediate a wide range of cellular responses through coupling to G proteins and arrestins, are key pharmacological targets, with nearly a third of FDA-approved drugs acting on them. Recent advancements in biosensor development, multiplex assay platforms, and deep mutational scanning methods are improving our ability to define GPCR signaling, allowing for a better understanding of biased signaling pathways.

Subcellular RNA localization is a conserved mechanism in eukaryotic cells and plays critical roles in diverse physiological processes including cell proliferation, differentiation, and embryo development. Nevertheless, the characterization of centrosome-localized mRNAs remains underexplored due to technical difficulties. In this study, we utilize APEX2-mediated proximity labeling to map the centrosome-proximal transcriptome, identifying DLGAP5 mRNA as a novel centrosome-localized transcript during mitosis. Using a combination of drug perturbation, truncation, deletion, and mutagenesis, we demonstrate that microtubule binding of nascent MBD1 polypeptides is required for centrosomal transport of DLGAP5 mRNA. Our data also reveal that mRNA targeting efficiency is tightly linked to the coding sequence (CDS) length. Thus, our study provides a transcriptomic resource for future investigation of centrosome-localized RNAs and sheds light on mechanisms underlying mRNA centrosomal localization.

Emerging evidence indicates that lipid droplets (LDs) play important roles in lipid metabolism, energy homeostasis, and cell stress management. Notably, dysregulation of LDs is tightly linked to numerous diseases, including lipodystrophies, cancer, obesity, atherosclerosis, and others. The pivotal physiological roles of LDs have led to an exploration of research in recent years. The functions of LDs are inherently connected to the composition of their proteome. Current methods for profiling LD proteins mostly utilize LD fractionation, including those based on proximity-based labeling techniques. Global profiling of the LD proteome in live cells without the isolation of LDs is still challenging. Herein, we disclose two small-molecule chemical probes, termed LDF and LDPL. Both LDF/LDPL are small in size and could freely and specifically migrate within the lipid context of LDs. Consequently, they were successfully used for live-cell fluorescence imaging of LDs and from animal tissues. We further showed that LDPL was capable of large-scale profiling of the LD proteome without the need of LD isolation. By using LDPL, 1584 high-confidence proteins, most of which could be annotated to prominent LD functions, were next identified. Importantly, further validation studies by using representative "hit" proteins revealed that CHMP6 and PRDX4 could act as the lipophagy receptor and lipolysis suppressor, respectively. Our results thus confirmed for the first time that LDPL is a powerful chemical tool for in situ profiling of LD proteomes. With the ability to provide a deeper understanding of LD proteomics from the native cellular environments, our newly developed strategy may be used in future to decipher the dynamics and molecular mechanism of LDs in various diseases.

The Legionella SidE effectors ubiquitinate host proteins independently of the canonical E1-E2 cascade. Here we engineer the SidE ligases to develop a modular proximity ligation approach for the identification of targets of small molecules and proteins, which we call SidBait. We validate the method with known small molecule-protein interactions and use it to identify CaMKII as an off-target interactor of the breast cancer drug ribociclib. Structural analysis and activity assays confirm that ribociclib binds the CaMKII active site and inhibits its activity. We further customize SidBait to identify protein-protein interactions, including substrates for enzymes, and discover the F-actin capping protein (CapZ) as a target of the Legionella effector RavB during infection. Structural and biochemical studies indicate that RavB allosterically binds CapZ and decaps actin, thus functionally mimicking eukaryotic CapZ interacting proteins. Collectively, our results establish SidBait as a reliable tool for identifying targets of small molecules and proteins.

Exosomes are multivesicular body-derived extracellular vesicles that are secreted by metazoan cells. Exosomes have utility as disease biomarkers, and exosome-mediated miRNA secretion has been proposed to facilitate tumor growth and metastasis. Previously, we demonstrated that the Lupus La protein (La) mediates the selective incorporation of miR-122 into metastatic breast cancer-derived exosomes; however, the mechanism by which La itself is sorted into exosomes remains unknown. Using unbiased proximity labeling proteomics, biochemical fractionation, superresolution microscopy and genetic tools, we establish that the selective autophagy receptor p62 sorts La and miR-122 into exosomes. We then performed small RNA sequencing and found that p62 depletion reduces the exosomal secretion of tumor suppressor miRNAs and results in their accumulation within cells. Our data indicate that p62 is a quality control factor that modulates the miRNA composition of exosomes. Cancer cells may exploit p62-dependent exosome cargo sorting to eliminate tumor suppressor miRNAs and thus to promote cell proliferation.

Immunotherapy efficacy in solid tumors varies greatly, influenced by the tumor microenvironment (TME) and the dynamic tumor-immune interactions within it. Decoding these interactions in situ with minimal interference with native tissue architecture and delicate immune responses is critical for understanding tumor progression and optimizing therapeutic strategies. Here, we introduce CAT-Tissue, a novel deep-red photocatalytic proximity labeling method that enables ultrafast, high-resolution profiling of tumor-immune interactions in primary tissues. By leveraging nanobody-Chlorin e6 as the photocatalyst and biotin-aniline as the probe, CAT-Tissue enabled the rapid and comprehensive detection of various tumor-immune interactions in both coculture systems and primary tumor sections. Coupled with bulk RNA-sequencing, CAT-Tissue revealed distinct gene expression patterns between tumor-neighboring and tumor-distal lymphocytes, highlighting the recognition and immune responses of tumor-neighboring CD8+ T cells, which exhibited activated, effector, and exhausted phenotypes. By leveraging a deep-red photocatalytic proximity cell labeling strategy with excellent tissue penetration and biocompatibility, CAT-Tissue offers a nongenetically encoded platform with high sensitivity and spatiotemporal controllability for rapid profiling tumor-immune interactions within complex tissue environments in situ, which may advance our understanding of tumor immunology and guide the development of more effective immunotherapies.

Extracellular proteins play pivotal roles in both intracellular signaling and intercellular communications in health and disease. While recent advancements in proximity labeling (PL) methods, such as peroxidase- and photocatalyst-based approaches, have facilitated the resolution of extracellular proteomes, their in vivo compatibility remains limited. Here, we report TyroID, an in vivo-compatible PL method for the unbiased mapping of extracellular proteins with high spatiotemporal resolution. TyroID employs plant- and bacteria-derived tyrosinases to produce reactive o-quinone intermediates, enabling the labeling of multiple residues on endogenous proteins with bioorthogonal handles, thereby allowing for their identification via chemical proteomics. We validate TyroID's specificity by mapping extracellular proteomes and HER2-neighboring proteins using affibody-directed recombinant tyrosinases. Demonstrating its superiority over other PL methods, TyroID enables in vivo mapping of extracellular proteomes, including mapping HER2-proximal proteins in tumor xenografts, quantifying the turnover of plasma proteins and labeling hippocampal-specific proteomes in live mouse brains. TyroID emerges as a potent tool for investigating protein localization and molecular interactions within living organisms.

Proximity labeling (PL) has emerged as a powerful technique for the in situ elucidation of biomolecular interaction networks. However, PL methods generally rely on single-biological-hierarchy control of spatial localization at the labeling site, which limits their application in multi-tiered biological systems. Here, we introduced another enzymatic reaction upstream of an enzyme-based PL reaction and targeted the two enzymes to markers indicating different biological hierarchies, establishing a two-level spatially localized proximity labeling (P2L) platform for in situ molecular measurement and manipulation. Using the cellular- and glycan-level as the hierarchical models, we demonstrated the ability of P2L to efficiently execute a two-step logic operation and to discriminate target cells with different levels of glycosylation within mixed cell populations. By mounting clickable handles via P2L, we reprogrammed the robust covalent assembly of cells at designated sites. The combination of P2L with proteomics led to the profiling of the protein microenvironment of specific glycans on target cells, revealing changes in tumor-cell-surface interactions under immune pressure from a glycan perspective. P2L provides not only a solution for revealing the heterogeneity of biological systems, but also new insights in the fields of intelligent logic computation, enzyme engineering, tissue engineering, etc.

Peroxynitrite (ONOO-), the product of the diffusion-controlled reaction of superoxide (O2•-) with nitric oxide (NO•), plays a crucial role in oxidative and nitrative stress and modulates key physiological processes such as redox signaling. While biological ONOO- is conventionally analyzed using 3-nitrotyrosine antibodies and fluorescent sensors, such probes lack specificity and sensitivity, making high-throughput and comprehensive profiling of ONOO--associated proteins challenging. In this study, we used a conditional proteomics approach to investigate ONOO- homeostasis by identifying its protein neighbors in cells. We developed Peroxynitrite-responsive protein Labeling reagents (Porp-L) and, for the first time, discovered 2,6-dichlorophenol as an ideal moiety that can be selectively and rapidly activated by ONOO- for labeling of proximal proteins. The reaction of Porp-L with ONOO- generated several short-lived reactive intermediates that can modify Tyr, His, and Lys residues on the protein surface. We have demonstrated the Porp-L-based conditional proteomics in immune-stimulated macrophages, which indeed identified proteins known to be involved in the generation and modification of ONOO- and revealed the endoplasmic reticulum (ER) as a ONOO- hot spot. Moreover, we discovered a previously unknown role for Ero1a, an ER-resident protein, in the formation of ONOO-. Overall, Porp-L represent a promising research tool for advancing our understanding of the biological roles of ONOO-.

Promyelocytic leukemia (PML) protein forms the scaffold for PML nuclear bodies (PML NB) that reorganize into Lipid-Associated PML Structures (LAPS) under fatty acid stress. We determined how the fatty acid oleate alters the interactome of PMLI or PMLII by expressing fusions with the ascorbate peroxidase APEX2 in U2OS cells. The resultant interactome included ESCRT and COPII transport protein nodes. Proximity ligation assay (PLA) revealed that COPII proteins SEC23B, SEC24A and USO1 preferentially associated with PML NBs. Nuclear localization of USO1, but not SEC23B and SEC24A, was reduced in PML knockout cells and restored by PMLII expression. Thus, proximity-labelling methods identified COPII transport protein interactions with PML NBs that are disrupted by fatty acid stress.

Signaling pathways often convergence on transcription factors and other DNA-binding proteins that regulate chromatin structure and gene expression, thereby governing a broad range of essential cellular functions. However, the repertoire of DNA-binding proteins is incompletely understood even for the best-characterized pathways. Here, we optimized a strategy for the isolation of Proteins on Chromatin (iPOC) exploiting tagged nucleoside analogs to label the DNA and capture associated proteins, thus enabling the comprehensive, sensitive, and unbiased characterization of the DNA-bound proteome. We then applied iPOC to investigate chromatome changes upon perturbation of the cancer-relevant PI3K-AKT-mTOR pathway. Our results show distinct dynamics of the DNA-bound proteome upon selective inhibition of PI3K, AKT, or mTOR, and we provide evidence how this signaling cascade regulates the DNA-bound status of SUZ12, thereby modulating H3K27me3 levels. Collectively, iPOC is a powerful approach to study the composition of the DNA-bound proteome operating downstream of signaling cascades, thereby both expanding our knowledge of the mechanism of action of the pathway and unveiling novel chromatin modulators that can potentially be targeted pharmacologically.

Dystrophic neurites (also termed axonal spheroids) are found around amyloid deposits in Alzheimer's disease (AD), where they impair axonal electrical conduction, disrupt neural circuits and correlate with AD severity. Despite their importance, the mechanisms underlying spheroid formation remain incompletely understood. To address this, we developed a proximity labeling approach to uncover the proteome of spheroids in human postmortem and mouse brains. Additionally, we established a human induced pluripotent stem cell (iPSC)-derived AD model enabling mechanistic investigation and optical electrophysiology. These complementary approaches revealed the subcellular molecular architecture of spheroids and identified abnormalities in key biological processes, including protein turnover, cytoskeleton dynamics and lipid transport. Notably, the PI3K/AKT/mTOR pathway, which regulates these processes, was activated in spheroids. Furthermore, phosphorylated mTOR levels in spheroids correlated with AD severity in humans. Notably, mTOR inhibition in iPSC-derived neurons and mice ameliorated spheroid pathology. Altogether, our study provides a multidisciplinary toolkit for investigating mechanisms and therapeutic targets for axonal pathology in neurodegeneration.

Loss of the tubulin-binding protein STMN2 is implicated in amyotrophic lateral sclerosis (ALS) but how it protects neurons is not known. STMN2 is known to turn over rapidly and accumulate at axotomy sites. We confirmed fast turnover of STMN2 in U2OS cells and iPSC-derived neurons and showed that degradation occurs mainly by the ubiquitin-proteasome system. The membrane targeting N-terminal domain of STMN2 promoted fast turnover, whereas its tubulin binding stathmin-like domain (SLD) promoted stabilization. Proximity labeling and imaging showed that STMN2 localizes to trans-Golgi network membranes and that tubulin binding reduces this localization. Pull-down assays showed that tubulin prefers to bind to soluble over membrane-bound STMN2. Our data suggest that STMN2 interconverts between a soluble form that is rapidly degraded unless bound to tubulin and a membrane-bound form that does not bind tubulin. We propose that STMN2 is sequestered and stabilized by tubulin binding, while its neuroprotective function depends on an unknown molecular activity of its membrane-bound form.

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.

Elucidating the subcellular localization of RNAs and proteins is fundamental to understanding their biological functions. Genetically encoded proteins/enzymes provide an attractive approach to target many proteins of interest, but are limited to specific cell lines. Although small-molecule-based methods have been explored, a comprehensive system for profiling multiple locations in living cells, comparable to fusion-protein techniques, is yet to be established. In this study, we introduce a novel proximity labeling strategy employing a suite of small molecules derived from benzo-phenoselenazine (e.g., selenium-containing Nile Blue [SeNB]), which achieves proximity labeling through singlet oxygen generation upon near-infrared light activation in the presence of propargylamine. These SeNB compounds allow for selective labeling of RNAs and proteins within living cells, exhibiting a distinct preference for organelle membranes, which are systematically investigated via in vitro, computational, and in cellulo examinations. Our findings highlight the capabilities of SeNB derivatives as wash-free and genetics-free approaches to illuminate the subcellular localization of biological molecules with deep penetration and high spatial resolution. Moreover, SeNB derivatives are capable of elucidating inter-organelle interactions at the molecular level, as evidenced by proteomic and transcriptomic analyses, thus holding significant potential for advancing our understanding of cellular processes related to disease progression and therapeutic development.