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At least 19 recordsLinked to original sources

Proximity Labeling of Cell Surface Proteins via Cell Surface Remodeling.

Within the complex interplay of proteins, lipids and carbohydrates at the cell surface is the surfaceome, a dense layer of proteins and their posttranslationally modified counterparts that serves as a hub for cell signaling and signal transduction. The surfaceome plays crucial roles in mediating interactions between cells and the extracellular environment, which combined with their availability at the cell surface make it an attractive therapeutic target. Despite its importance, the development of technologies to selectively target cell surface proteins for empirical identification is challenged by their structural complexity. Here, we describe a proximity labeling-based technique to covalently label proteins at the cell surface with a biotin handle, enabling downstream streptavidin-based enrichment and manipulation in a variety of modalities, including fluorescence imaging, western blotting, and mass spectrometry-based proteomics.

Membrane Proteins

Comparison of Protein Coronas and Internalized Cell Surface Proteins of Positive and Negative Liposomes.

Positive nanoparticles have often a higher uptake than neutral and negative nanoparticles. This is usually attributed to electrostatic interactions with negatively charged proteoglycans on the cell membrane. However, upon contact with serum, nanoparticles adsorb a biomolecule corona and tend toward neutrality, suggesting that electrostatic interactions alone cannot explain the different uptake. Here, we used oppositely charged liposomes as an example to explore at a fundamental level why positive nanoparticles usually show a higher uptake than the negative ones. Two proteomic-based approaches were combined to compare their protein coronas and the cell surface proteins involved in their internalization. The results showed that the higher uptake of the positive liposomes used for this study could not be simply explained by the involvement of specific corona proteins and dominating cell surface proteins. Instead, small differences in the abundances of a large number of corona proteins and cell surface proteins were observed, including multiple low-abundance proteins. Importantly, the positive liposomes had higher uptake than the negative liposomes only when added to cells in the presence of serum, suggesting that the higher uptake likely resulted from the observed subtle differences in their corona and the collective contribution and interactions with multiple cell surface proteins.

Liposomes

Identification of Glioblastoma Cell Surface Proteins and Assessment of Their Expression Across Patient-Derived Stem-Like Cell Cultures.

Glioblastoma (GBM) is the most common primary brain cancer in adults and remains fatal, with a median survival of a few months. There is an urgent need to develop novel therapeutic strategies against this aggressive malignancy. Modern cancer research increasingly focuses on personalized therapies tailored toward unique molecular features of each tumor or patient. In this context, cell surface proteins (CSPs) represent an attractive class of therapeutic targets due to their accessibility and central roles in physiological and pathological processes, making them among the most targeted proteins in current drug development. In this study, promising CSPs were identified through an untargeted proteomics approach using high-resolution mass spectrometry on patient-derived GBM stem-like cell (GSC) cultures, complemented by RNA-seq data and computational database analyses. From this primary discovery, five CSPs, namely PTK7, PTPRZ1, OSMR, CSPG4, and IGDCC4, were selected for detailed investigation. A targeted UHPLC-multiple reaction monitoring (MRM) method was developed and optimized to assess their expression and evaluate their abundance variations across different GSC cultures and cell passage levels. Beyond confirming these CSPs as potential therapeutic targets in GBM, our study demonstrates the value of three-dimensional GSC cultures as robust models for biomarker research and target assessment.

Humans

Translational Gap in Biomarker Discovery: Tumor Surface Markers Rarely Mirror Circulating Levels.

BACKGROUND: Tumor-associated cell surface proteins are frequently proposed as circulating biomarkers for colorectal cancer (CRC) based on their high tumor expression. However, many candidates identified through tissue-based analyses fail to translate into clinically useful biomarkers. We investigated the translational gap between tissue-level expression and circulating detectability in CRC, focusing on molecular subtypes defined by caudal-type homeobox 2 (CDX2) expression. METHODS: Transcriptomic data from The Cancer Genome Atlas (TCGA) were analyzed to identify cell surface markers differentially expressed between CDX2-Low and CDX2-High CRCs. A clinical cohort of right-sided CRC patients was evaluated using paired tumor tissue and preoperative plasma samples. CDX2 expression was assessed by immunohistochemistry, and circulating concentrations of selected cell surface proteins were quantified using a multiplex ELISA platform. RESULTS: Several tumor-associated cell surface markers exhibited marked CDX2-dependent differences in tissue expression. However, for most markers, circulating plasma levels did not mirror tissue-level patterns. CEACAM1 was the sole marker demonstrating concordant CDX2-dependent differences in both tumor tissue and plasma, with significantly lower levels in CDX2-Low CRCs. In contrast, CEACAM5 showed a dissociation between tissue expression and circulating levels, despite analytical validation against serum carcinoembryonic antigen (CEA). CONCLUSIONS: Our findings demonstrate that tumor overexpression of cell surface markers does not necessarily translate into detectable circulating biomarkers. This translational disconnect underscores limitations of biomarker selection strategies based solely on tissue expression and highlights the importance of integrating systemic biology into biomarker development. While some tumor-associated proteins may lack utility as circulating biomarkers, they may still represent viable therapeutic targets in CRC.

CDX2

Identification of potential cell surface targets in patient-derived cultures toward photoimmunotherapy of high-grade serous ovarian cancer.

Tumor-targeted, activatable photoimmunotherapy (taPIT) has shown promise in preclinical models to selectively eliminate drug-resistant micrometastases that evade standard treatments. Moreover, taPIT has the potential to resensitize chemo-resistant tumor cells to chemotherapy, making it a complementary modality for treating recurrent high-grade serous ovarian cancer (HGSOC). However, the established implementation of taPIT relies on the overexpression of EGFR in tumor cells, which is not universally observed in HGSOCs. Motivated by the need to expand taPIT applications beyond EGFR, we conducted mRNA-sequencing and proteomics to identify alternative cell surface targets for taPIT in patient-derived HGSOC cell cultures with weak EGFR expression and lacking expression of other cell surface proteins commonly reported in the literature as overexpressed in ovarian cancers, such as FOLR1 and EpCAM. Our findings highlight TFRC and LRP1 as promising alternative targets. Notably, TFRC was overexpressed in 100% (N = 5) of the patient-derived HGSOC models tested, whereas only 60% of models had high EpCAM expression, suggesting that future larger cohort studies should include TFRC. While this study focuses on target identification, future work will expand the approaches developed here to larger HGSOC biopsy repositories and will also develop and evaluate antibody-photosensitizer conjugates targeting these proteins for taPIT applications.

Humans

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans

Allele Level Sequencing of Killer Cell Immunoglobulin-Like Receptor Genes Using Oxford Nanopore Long Read Sequencing.

The human Killer cell Immunoglobulin-like Receptor (KIR) genes, found on chromosome 19, encode for cell surface protein receptors that, through interaction with their ligand, modulate the action of Natural Killer (NK) cells and some subsets of T lymphocytes. KIR genes exhibit extensive variation through variable gene content, copy number, and allele polymorphism. The combination of KIR genes and their ligands is implicated in various clinical settings including haematopoietic stem cell and solid organ transplant, and infectious disease progression. KIR gene content has been used in the selection of optimal stem cell donors with haplotype variations in recipient and donor giving differential clinical outcomes. With the introduction of massively parallel clonal next generation sequencing and single molecule long read third generation sequencing, allele level determination of KIR genotypes has become feasible. We describe a method for amplicon-based long read sequencing on the Oxford Nanopore Technologies platform that provides largely unambiguous allele level typing of KIR genes. The method was validated using DNA extracted from 48 10th International Histocompatibility Workshop (IHWS) cell lines with previously published allele level KIR genotypes and 176 Western Australian samples previously tested for the presence or absence of KIR genes. Our long-read sequencing method was able to accurately determine KIR alleles with an overall concordance of 97%-99% with the published data. Importantly, phasing ambiguity caused by the inability to phase heterozygous base positions over long stretches of gene sequence was resolved in several samples. Thus, our long read PCR sequencing strategy can be used to determine KIR genotypes at allele resolution level.

Humans

A scalable, low-cost, sample hashing workflow for multiomic single-cell analysis using the Seq-Well S3 platform.

In-depth analyses of clinical samples have the potential to provide unparalleled insights into the cellular mechanisms that underlie both health and disease, as well as therapeutic and prophylactic responses. However, these specimens are often paucicellular, necessitating the use of workflows that maximize the amount of information that can be learned. Here we provide a detailed protocol for generating and analyzing single-cell multiomic data from low-input samples with the Seq-Well S3 platform. We further describe a matched pipeline for sample hashing that reduces costs and sources of technical variation in the resulting data while also enhancing throughput. In brief, our streamlined and efficient methodology involves: (1) optionally staining single-cell suspensions with antibody-oligonucleotide conjugates for cell surface protein quantification and/or sample multiplexing; (2) generating Seq-Well S3 sequencing libraries; (3) optionally producing bulk-RNA sequencing libraries via SMART-seq2 to support genetic demultiplexing; and (4) computationally analyzing the resulting data. Each step herein has been designed to leverage readily available reagents and standard laboratory equipment, substantially lowering barriers to entry for researchers. The overall Protocol can yield high-quality multiomic insights from samples in under a week.

Single-Cell Analysis

Interaction of Galpha 12 and Galpha 13 with the cytoplasmic domain of cadherin provides a mechanism for beta -catenin release.

The G12 subfamily of heterotrimeric G proteins, comprised of the alpha-subunits Galpha12 and Galpha13, has been implicated as a signaling component in cellular processes ranging from cytoskeletal changes to cell growth and oncogenesis. In an attempt to elucidate specific roles of this subfamily in cell regulation, we sought to identify molecular targets of Galpha12. Here we show a specific interaction between the G12 subfamily and the cytoplasmic tails of several members of the cadherin family of cell-surface adhesion proteins. Galpha12 or Galpha13 binding causes dissociation of the transcriptional activator beta-catenin from cadherins. Furthermore, in cells lacking the adenomatous polyposis coli protein required for beta-catenin degradation, expression of mutationally activated Galpha12 or Galpha13 causes an increase in beta-catenin-mediated transcriptional activation. These findings provide a potential molecular mechanism for the previously reported cellular transforming ability of the G12 subfamily and reveal a link between heterotrimeric G proteins and cellular processes controlling growth and differentiation.

Adenocarcinoma

Antibody-Mediated Targeting of Secretory Protein SCUBE3 Suppresses Cancer Progression by Inhibiting Oncogenic Signaling and Inducing Antitumor Immunity.

UNLABELLED: Approaches targeting factors that simultaneously promote tumor growth and progression, induce therapy resistance, and inhibit antitumor immunity offer clear benefits over therapies targeting only one of these tumor-promoting processes. Through comprehensive loss-of-function genomic screening, we identified SCUBE3 as a pivotal factor that supports survival and therapy resistance and also orchestrates an immunosuppressive tumor microenvironment. Secretory SCUBE3 supported oncogenic activity through interactions with key oncogenic cell surface receptor proteins, including EGFR, mutant CALR, and TGFβRI/II. These interactions activated the transcription factors FOXR2 and c-Myc, promoting cancer cell proliferation and therapy resistance by enhancing DNA damage repair. Additionally, the SCUBE3-FOXR2 axis created an immunosuppressive tumor microenvironment by facilitating recruitment of the DNMT1 epigenetic repressor complex to the transcription regulator IRF1, thereby inhibiting the expression of MHC-I and MHC-II genes. A first-in-class neutralizing antibody targeting SCUBE3, which was developed using a sophisticated antibody discovery platform and engineered with specific mutations in the heavy chain for enhanced specificity and efficacy, demonstrated profound therapeutic potential across various cancer types in preclinical models, including patient-derived breast and ovarian cancer xenografts. This discovery marks an advancement toward developing a targeted therapy for cancers characterized by hyperactive SCUBE3-associated signaling pathways. SIGNIFICANCE: Targeting SCUBE3 with a neutralizing antibody inhibits tumor growth and metastasis by blocking oncogenic signaling through FOXR2 and c-Myc and by circumventing immunosuppression, providing a promising pan-cancer treatment approach.

Humans

The modern expansion of Dscam1 isoform diversity in Drosophila is linked to fitness and immunity.

Drosophila melanogaster Down Syndrome cell adhesion molecule 1 (Dscam1) gene encodes 38,016 diverse cell surface receptor proteins via alternative splicing, which have both nervous and immune functions. However, it remains elusive why organisms have evolved such an astonishing diversity of isoforms. Here, we show that fitness and immunity properties have driven the modern evolution of Dscam1 isoform diversity. We assess multiple aspects of fly fitness in deletion mutants harboring exon 4, 6, or 9 clusters, respectively, reducing ectodomain isoform diversity stepwise from 18,612 to 396. All fitness-related traits generally improved as the potential number of isoforms increased; however, the magnitude of the changes varied remarkably in a variable cluster-specific manner. Correlation analysis revealed that fitness-related traits were much more sensitive to reductions in Dscam1 diversity compared to canonical neuronal self/non-self discrimination. We conclude that the role of Dscam1 isoforms in canonical neuronal self-avoidance and self/non-self discrimination is mediated by a small fraction of all isoforms (<1/10), whereas a separate role essential for other developmental contexts and resistances, likely in fitness and immunity, requires almost full isoform diversity. Thus, fitness and immunity properties, rather than canonical neuronal functions, are the dominant drivers during the modern diversification of the Dscam1 isoform. Our findings suggest that Dscam1 diversity is closely linked to adaptation and species diversification in arthropods.

Animals

Functional screening of ZIP8 naturally occurring variants identifies pathogenic mutations and trafficking defects.

The rapid expansion of human genomic data has revealed a large number of naturally occurring variants, creating a major challenge for functional annotation. The human metal transporter SLC39A8 (ZIP8) is a clinically important divalent metal transporter, yet most of its documented variants remain uncharacterized. Here, we developed a workflow to functionally evaluate ZIP8 variants by integrating laser ablation inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-TOF-MS) with scaled-up cell-based transport assays. Using this method, we systematically analyzed 33 naturally occurring missense variants located in the extracellular domain (ECD) of ZIP8. The assay enables direct quantification of intracellular metal accumulation with substantially improved throughput (&#x223c;150 samples per hour). Functional screening identified 14 potential pathogenic variants with significantly reduced transport activity. Comparison with computational predictions revealed a moderate correlation between activity and AlphaMissense pathogenicity scores (R2 = 0.423), while an error rate of &#x223c;20% for AlphaMissense underscores the need for experimental validation. Flow cytometry analysis showed that most loss-of-function variants exhibit impaired trafficking of the protein to the cell surface possibly due to mutation-caused protein misfolding or instability. Structural mapping of activity-compromised variants, together with functional assessment of the ZIP8-ECD, highlights the importance of this domain in ZIP8 expression and intracellular protein trafficking. Together, this work establishes a scalable approach for functional screening of metal transporter variants and provides new insights into the structure-function relationships of ZIP8.

Journal Article

Functional screening of ZIP8 naturally occurring variants identifies pathogenic mutations and trafficking defects.

The rapid expansion of human genomic data has revealed a large number of naturally occurring variants, creating a major challenge for functional annotation. The human metal transporter SLC39A8 (ZIP8) is a clinically important, promiscuous divalent metal transporter, yet most of its documented variants remain uncharacterized. Here, we developed a workflow to functionally evaluate ZIP8 variants by integrating laser ablation inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-TOF-MS) with scaled-up cell-based transport assays. Using this method, we systematically analyzed 33 naturally occurring missense variants located in the extracellular domain (ECD) of ZIP8. The assay enables direct quantification of intracellular metal accumulation with substantially improved throughput (~150 samples per hour). Functional screening identified 14 potential pathogenic variants with significantly reduced transport activity. Comparison with computational predictions revealed a moderate correlation between activity and AlphaMissense pathogenicity scores (R2 = 0.423), while an error rate of ~20% underscores the need for experimental validation. Flow cytometry analysis showed that most loss-of-function variants exhibit impaired trafficking of the protein to the cell surface possibly due to mutation-caused protein misfolding or instability. Structural mapping of activity-compromised variants, together with functional assessment of the ZIP8-ECD, highlights the importance of this domain in ZIP8 expression and intracellular trafficking. Together, this work establishes a scalable approach for functional screening of metal transporter variants and provides new insights into the structure-function relationships of ZIP8.

Journal Article

Establishment of a multi-targeted magnetic combined enrichment system for circulating tumor cells in gastric cancer and analysis of their genomic profiles.

Background: This study aims to establish an efficient Circulating tumor cells (CTCs) multi-targeted magnetic combined sorting system for Gastric cancer (GC), while comparing it with tissue and circulating tumor DNA (ctDNA) samples to evaluate its feasibility and consistency for genomic profiling analysis. Method: Establish an efficient CTCs sorting system for GC targeting epithelial cell adhesion molecule, cell surface vimentin, and protein tyrosine kinase 7, and evaluate its physicochemical properties and cell capture efficiency. Assess the feasibility of tumor cell detection through animal experiments. Sixty-eight GC patients underwent CTCs detection. Clinical information was analyzed to evaluate the clinical utility of CTCs in the auxiliary diagnosis of GC. Next-generation sequencing was performed on GC tissue, CTCs, and ctDNA samples to assess the consistency of genetic mutations across different sample types. Results: The constructed CTCs sorting system exhibits excellent physicochemical properties, achieving a capture rate of 94.68%. Animal studies confirm a positive correlation between tumor cells count and tumor volume. The number of CTCs in the blood of GC patients is significantly correlated with tumor size, stage, and metastasis. The CTCs count in GC patients is significantly higher than in healthy individuals and high-risk groups for cancer, with diagnostic sensitivity and specificity of 97.29% and 97.73%, respectively. The mutation detection rate in CTCs samples was significantly higher than that in tissue and ctDNA samples. The concordance rate between CTCs and tissue mutations was 24.32%, while the concordance rate between CTCs and ctDNA mutations was 19.05%. Conclusion: This study successfully established a multi-target combined CTCs multi-targeted magnetic combined sorting system for GC. CTCs detection based on this system can be used for the auxiliary diagnosis of GC patients. Furthermore, compared to GC tissue and ctDNA samples, CTCs detection enables more comprehensive genomic profiling analysis and serves as an important supplement to GC genomic analysis.

Humans

Single-cell RNA sequencing of peripheral blood defines two immunological subtypes of Sj&#xf6;gren's disease distinguished by anti-SSA antibodies and aberrant B cell populations.

OBJECTIVES: Sj&#xf6;gren's disease (SjD) is a heterogeneous autoimmune disorder characterized by substantial clinical and molecular diversity. This heterogeneity raises key questions regarding the existence of distinct pathogenic mechanisms underlying disease subtypes. The objective of this study was to comprehensively characterize peripheral immune cell states associated with SjD and to identify features that could enable better patient stratification for targeted treatments. METHODS: We performed single-cell RNA sequencing with surface protein profiling on 1.5 million peripheral blood mononuclear cells (PBMCs) from 333 participants. Individuals were stratified by SjD diagnosis and anti-SSA status to enable comparative analyses between disease subgroups and controls. RESULTS: Our analysis identified two immunological endotypes of SjD, with SSA-positive participants exhibiting a dominant and persistent IFN-I signature that was also associated with altered immune cell composition. Transitional B cells were particularly affected, displaying altered developmental states, reduced BCR diversity, shorter CDR3 regions, and increased predicted interactions with activated immune cell populations, findings consistent with perturbations of early B-cell selection processes. By contrast, SSA-negative SjD participants exhibited limited transcriptional differences compared with symptomatic non-SjD controls, highlighting substantial biological heterogeneity within SjD. CONCLUSIONS: These findings support a two-disease model of SjD and highlight transitional B cells as both a key biomarker and a therapeutic target.

Journal Article

Bordetella pertussis risA, but not risS, is required for maximal expression of Bvg-repressed genes.

Expression of virulence determinants by Bordetella pertussis, the primary etiological agent of whooping cough, is regulated by the BvgAS two-component regulatory system. The role of a second two-component regulatory system, encoded by risAS, in this process is not defined. Here, we show that mutation of B. pertussis risA does not affect Bvg-activated genes or proteins. However, mutation of risA resulted in greatly diminished expression of Bvg-repressed antigens and decreased transcription of Bvg-repressed genes. In contrast, mutation of risS had no effect on the expression of Bvg-regulated molecules. Mutation of risA also resulted in decreased bacterial invasion in a HeLa cell model. However, decreased invasion could not be attributed to the decreased expression of Bvg-repressed products, suggesting that mutation of risA may affect the expression of a variety of genes. Unlike the risAS operons in B. parapertussis and B. bronchiseptica, B. pertussis risS is a pseudogene that encodes a truncated RisS sensor. Deletion of the intact part of the B. pertussis risS gene does not affect the expression of risA-dependent, Bvg-repressed genes. These observations suggest that RisA activation occurs through cross-regulation by a heterologous system.

Bacterial Adhesion

Immunopeptidomics Mapping of Listeria monocytogenes T Cell Epitopes in Mice.

Listeria monocytogenes is a foodborne intracellular bacterial model pathogen. Protective immunity against Listeria depends on an effective CD8+ T cell response, but very few T cell epitopes are known in mice as a common animal infection model for listeriosis. To identify epitopes, we screened for Listeria immunopeptides presented in the spleen of infected mice by mass spectrometry-based immunopeptidomics. We mapped more than 6000&#xa0;mouse self-peptides presented on MHC class I molecules, including 12 high confident Listeria peptides from 12 different bacterial proteins. Bacterial immunopeptides with confirmed fragmentation spectra were further tested for their potential to activate CD8+ T cells, revealing VTYNYINI from the putative cell wall surface anchor family protein LMON_0576 as a novel bona fide peptide epitope. The epitope showed high biological potency in a prime boost model and can be used as a research tool to probe CD8+ T cell responses in the mouse models of Listeria infection. Together, our results demonstrate the power of immunopeptidomics for bacterial antigen identification.

Animals

shinyDeepGxP: a user-friendly R shiny app for predicting surface protein abundance from scRNA-seq expression using deep learning in blood cells.

MOTIVATION: Understanding accurate immune cell heterogeneity and function in single-cell datasets requires access to protein-level information, which is often unavailable due to experimental limitations. RESULTS: We present shinyDeepGxP, an interactive web application featuring our deep learning model, DeepGxP, for predicting surface protein abundance from single-cell RNA-sequencing (scRNA-seq) data. This platform makes DeepGxP accessible to researchers without programming skills. Users can upload scRNA-seq count matrices and use "Predict Protein" to predict the abundance of 224 biologically relevant surface proteins. shinyDeepGxP provides visualizations to help identify distinct cell populations based on predicted protein profiles. Moreover, users can choose "Explore Model" to reveal key RNA predictors and their associated biological pathways for each protein. Overall, shinyDeepGxP is a user-friendly, freely available web tool that provides protein-level detail for RNA-only single-cell datasets, enabling multimodal discovery without additional experiments. AVAILABILITY AND IMPLEMENTATION: shinyDeepGxP can be launched on https://shiny.crc.pitt.edu/deepgxp/.

Journal Article