Analysis of cell surface proteome changes via label-free, quantitative mass spectrometry

Tracking the effects of PLGA-based nanoparticles on protein expression in living cells through quantitative proteomics

Mass spectrometry (MS)-based proteomics can identify and quantify the differential abundance of expressed proteins in parallel, and bottom-up proteomic approaches are even approaching comprehensive coverage of the complex eukaryotic proteome. Protein-nanoparticle (NP) interactions have been extensively studied owing to their importance in biological applications and nanotoxicology. However, the proteome-level effects of NPs on cells have received little attention, although changes in protein abundance can reflect the direct effects of nanocarriers on protein expression. Herein, we investigated the effect of PLGA-based NPs on protein expression in HepG2 cells using a label-free quantitative proteomics approach with data independent acquisition (DIA). The percentage of two-fold change in the protein expression of cells treated with PLGA-based NPs was less than 10.15% during a 6 hour observation period. Among the changed proteins, we found that dynamic proteins involved in cell division, localization, and transport are more likely to be more susceptible to PLGA-based NPs.

Development and validation of machine learning models for diagnosis and prognosis of cancer by urinary proteomics, based on the FLEMENGHO cohort

The current study aims to develop and validate machine learning (ML) models for the prediction of cancer status by the non-invasive urinary proteomic in a population-based cohort. In this retrospective study, urinary proteome profiles in 804 cases from the FLEMENGHO cohort were measured by mass spectrometry. After feature selection by LASSO on both clinical variables and urinary proteome profile, benchmark models by clinical variables were built with six different ML algorithms. Proteome-based models and combined models were built and compared with the benchmark models. The models' performance, i.e. area under the curve (AUC) was compared by Delong method. The 95% confidence interval was estimated by the bootstrapping method. The best-performing model was explained by Shapley Additive Explanations (SHAP) method. The predictive role of proteome biomarkers in longitudinal cancer diagnosis was also explored. A clinical model, based on age, blood sugar and blood lipid profile, yielded the best AUC of 0.75 (0.68-0.82), with 0.80 (0.72-0.91) for the proteome model based on 13 selected biomarkers and 0.83 (0.77-0.90) for the combined model (P=0.01 for comparison with clinical model). SHAP on the support vector machine in the combined setting showed that except for age, proteome biomarkers contribute to the final prediction of the model. After adjusting with clinical factors, three proteome biomarkers are independent risk factors for longitudinal cancer development. Urinary proteome profiling, together with fine-tuned machine learning algorithms, demonstrates the predictive potential for cancer diagnosis transparently.

Defining the Cell Surface Cysteinome Using Two-Step Enrichment Proteomics

The plasma membrane proteome is a rich resource of functionally important and therapeutically relevant protein targets. Distinguished by high hydrophobicity, heavy glycosylation, disulfide-rich sequences, and low overall abundance, the cell surface proteome remains undersampled in established proteomic pipelines, including our own cysteine chemoproteomics platforms. Here, we paired cell surface glycoprotein capture with cysteine chemoproteomics to establish a two-stage enrichment method that enables chemoproteomic profiling of cell Surface Cysteinome. Our "Cys-Surf" platform captures >2,800 total membrane protein cysteines in 1,046 proteins, including 1,907 residues not previously captured by bulk proteomic analysis. By pairing Cys-Surf with an isotopic chemoproteomic readout, we uncovered 821 total ligandable cysteines, including known and novel sites. Cys-Surf also robustly delineates redox-sensitive cysteines, including cysteines prone to activation-dependent changes to cysteine oxidation state and residues sensitive to addition of exogenous reductants. Exemplifying the capacity of Cys-Surf to delineate functionally important cysteines, we identified a redox sensitive cysteine in the low-density lipoprotein receptor (LDLR) that impacts both the protein localization and uptake of low-density lipoprotein (LDL) particles. Taken together, the Cys-Surf platform, distinguished by its two-stage enrichment paradigm, represents a tailored approach to delineate the functional and therapeutic potential of the plasma membrane cysteinome.

Defining the Cell Surface Cysteinome using Two-step Enrichment Proteomics

The plasma membrane proteome is a rich resource of functional and therapeutically relevant protein targets. Distinguished by high hydrophobicity, heavy glycosylation, disulfide-rich sequences, and low overall abundance, the cell surface proteome remains undersampled in established proteomic pipelines, including our own cysteine chemoproteomics platforms. Here we paired cell surface glycoprotein capture with cysteine chemoproteomics to establish a two-stage enrichment method that enables chemoproteomic profiling of cell Surface Cysteinome. Our "Cys-Surf" platform captures >2,800 total membrane protein cysteines in 1,046 proteins, including 1,907 residues not previously captured by bulk proteomic analysis. By pairing Cys-Surf with an isotopic chemoproteomic readout, we uncovered 821 total ligandable cysteines, including known and novel sites. Cys-Surf also robustly delineates redox-sensitive cysteines, including cysteines prone to activation-dependent changes to cysteine oxidation state and residues sensitive to addition of exogenous reductants. Exemplifying the capacity of Cys-Surf to delineate functionally important cysteines, we identified a redox sensitive cysteine in the low-density lipoprotein receptor (LDLR) that impacts both the protein localization and uptake of LDL particles. Taken together, the Cys-Surf platform, distinguished by its two-stage enrichment paradigm, represents a tailored approach to delineate the functional and therapeutic potential of the plasma membrane cysteinome.

Systematic characterization of extracellular glycoproteins using mass spectrometry

Surface and secreted glycoproteins are essential to cells and regulate many extracellular events. Because of the diversity of glycans, the low abundance of many glycoproteins, and the complexity of biological samples, a system-wide investigation of extracellular glycoproteins is a daunting task. With the development of modern mass spectrometry (MS)-based proteomics, comprehensive analysis of different protein modifications including glycosylation has advanced dramatically. This review focuses on the investigation of extracellular glycoproteins using MS-based proteomics. We first discuss the methods for selectively enriching surface glycoproteins and investigating protein interactions on the cell surface, followed by the application of MS-based proteomics for surface glycoprotein dynamics analysis and biomarker discovery. We then summarize the methods to comprehensively study secreted glycoproteins by integrating various enrichment approaches with MS-based proteomics and their applications for global analysis of secreted glycoproteins in different biological samples. Collectively, MS significantly expands our knowledge of extracellular glycoproteins and enables us to identify extracellular glycoproteins as potential biomarkers for disease detection and drug targets for disease treatment.

Peripheral Nerve Single-Cell Analysis Identifies Mesenchymal Ligands that Promote Axonal Growth

Peripheral nerves provide a supportive growth environment for developing and regenerating axons and are essential for maintenance and repair of many non-neural tissues. This capacity has largely been ascribed to paracrine factors secreted by nerve-resident Schwann cells. Here, we used single-cell transcriptional profiling to identify ligands made by different injured rodent nerve cell types and have combined this with cell-surface mass spectrometry to computationally model potential paracrine interactions with peripheral neurons. These analyses show that peripheral nerves make many ligands predicted to act on peripheral and CNS neurons, including known and previously uncharacterized ligands. While Schwann cells are an important ligand source within injured nerves, more than half of the predicted ligands are made by nerve-resident mesenchymal cells, including the endoneurial cells most closely associated with peripheral axons. At least three of these mesenchymal ligands, ANGPT1, CCL11, and VEGFC, promote growth when locally applied on sympathetic axons. These data therefore identify an unexpected paracrine role for nerve mesenchymal cells and suggest that multiple cell types contribute to creating a highly pro-growth environment for peripheral axons.

An overview on enrichment methods for cell surface proteome profiling

Cell surface proteins are essential for many important biological processes, including cell-cell interactions, signal transduction, and molecular transportation. With the characteristics of low abundance, high hydrophobicity, and high heterogeneity, it is difficult to get a comprehensive view of cell surface proteome by direct analysis. Thus, it is important to selectively enrich the cell surface proteins before liquid chromatography with mass spectrometry analysis. In recent years, a variety of enrichment methods have been developed. Based on the separation mechanism, these methods could be mainly classified into three types. The first type is based on their difference in the physicochemical property, such as size, density, charge, and hydrophobicity. The second one is based on the bimolecular affinity interaction with lectin or antibody. And the third type is based on the chemical covalent coupling to free side groups of surface-exposed proteins or carbohydrate chains, such as primary amines, carboxyl groups, glycan side chains. In addition, metabolic labeling and enzymatic reaction-based methods have also been employed to selectively isolate cell surface proteins. In this review, we will provide a comprehensive overview of the enrichment methods for cell surface proteome profiling.

Profiling the Atlantic Salmon IgM+ B Cell Surface Proteome: Novel Information on Teleost Fish B Cell Protein Repertoire and Identification of Potential B Cell Markers

Fish immunology research is at a pivotal point with the increasing availability of functional immunoassays and major advances in omics approaches. However, studies on fish B cells and their distinct subsets remain a challenge due to the limited availability of differentially expressed surface markers. To address this constraint, cell surface proteome of Atlantic salmon IgM⁺ B cells were analyzed by mass spectrometry and compared to surface proteins detected from two adherent salmon head kidney cell lines, ASK and SSP-9. Out of 21 cluster of differentiation (CD) molecules identified on salmon IgM⁺ B cells, CD22 and CD79A were shortlisted as potential markers based on the reported B cell-specific surface expression of their mammalian homologs. Subsequent RT-qPCR analyses of flow cytometry-sorted subpopulations from head kidney leukocytes confirmed that both cd22 and cd79a genes were highly expressed in IgM⁺ lymphoid cells but were observed in barely detectable levels in IgM^- non-lymphoid suspension and adherent cells. Similarly, significantly high cd22 and cd79a mRNA levels were observed in IgM⁺ or IgT⁺ lymphoid cells from the spleen and peritoneal cavity, but not in their corresponding IgM^- IgT^- non-lymphoid fractions. This suggests that the B cell restrictive expression of CD22 and CD79A extend down to the transcription level, which was consistent across different lymphoid compartments and immunoglobulin isotypes, thus strongly supporting the potential of CD22 and CD79A as pan-B cell markers for salmon. In addition, this study provides novel information on the salmon B cell surface protein repertoire, as well as insights on B cell evolution. Further investigation of the identified salmon CD molecules, including development of immunological tools for detection, will help advance our understanding of the dynamics of salmon B cell responses such as during infection, vaccination, or immunostimulation.

Sensitive profiling of cell surface proteome by using an optimized biotinylation method

Cell surface proteins are responsible for many critical functions. Systematical profiling of these proteins would provide a unique molecular fingerprint to classify cells and provide important information to guide immunotherapy. Cell surface biotinylation method is one of the effective methods for cell surface proteome profiling. However, classical workflows suffer the disadvantage of poor sensitivity. In this work, we presented an optimized protocol which enabled identification of more cell surface proteins from a smaller number of cells. When this protocol was combined with a tip based fractionation scheme, 4510 proteins, including 2055 annotated cell surface-associated proteins, were identified with only 20 microgram protein digest, showing the superior sensitivity of the approach. To enable process 10 times fewer cells, a pipet tip based protocol was developed, which led to the identification of about 600 cell surface-associated proteins. Finally, the new protocol was applied to compare the cell surface proteomes of two breast cancer cell lines, BT474 and MCF7. It was found that many cell surface-associated proteins were differentially expressed. The new protocols were demonstrated to be easy to perform, time-saving, and yielding good selectivity and high sensitivity. We expect this protocol would have broad applications in the future. SIGNIFICANCE: Cell surface proteins confer specific cellular functions and are easily accessible. They are often used as drug targets and potential biomarkers for prognostic or diagnostic purposes. Thus, efficient methods for profiling cell surface proteins are highly demanded. Cell surface biotinylation method is one of the effective methods for cell surface proteome profiling. However, classical workflows suffer the disadvantage of poor sensitivity. In this work, we presented an optimized protocol which enabled identification of more cell surface proteins from a smaller number of starting cells. The new protocol is easier to perform, time-saving and has less protein loss. By using a special pipet tip, sensitive and in-depth cell surface proteome analysis could be achieved. In combination with label-free quantitative MS, the new protocol can be applied to the differential analysis of the cell surface proteomes between different cell lines to find genetically- or drug-induced changes. We expect this protocol would have broad application in cell surface protein studies, including the discovery of diagnostic marker proteins and potential therapeutic targets.

Mass Spectrometry-Based Identification of Extracellular Domains of Cell Surface N-Glycoproteins: Defining the Accessible Surfaceome for Immunophenotyping Stem Cells and Their Derivatives

Human stem cells and their progeny are valuable for a variety of research applications and have the potential to revolutionize approaches to regenerative medicine. However, we currently have limited tools to permit live isolation of homogeneous populations of cells apt for mechanistic studies or cellular therapies. While these challenges can be overcome through the use of immunophenotyping based on accessible cell surface markers, the success of this process depends on the availability of reliable antibodies and well-characterized markers, which are lacking for most stem cell lineages. This chapter outlines an iterative process for the development of new cell surface marker barcodes for identifying and selecting stem cell derived progeny of specific cell types, subtypes, and maturation stages, where antibody-independent identification of cell surface proteins is achieved using a modern chemoproteomic approach to specifically identify N-glycoproteins localized to the cell surface. By taking advantage of a large repository of available cell surfaceome data, proteins that are unlikely to confer cell type specificity can be rapidly eliminated from consideration. Subsequently, targeted quantitation by mass spectrometry can be used to refine candidates of interest, and a bioinformatic visualization tool is key to mapping experimental data to candidate protein sequences for the purpose of epitope selection during the antibody development phase. Overall, the process of developing cell surface barcodes for immunophenotyping is iterative and can include multiple rounds of discovery, refinement, and validation depending on the phenotypic resolution required.

Labeling Carboxyl Groups of Surface-Exposed Proteins Provides an Orthogonal Approach for Cell Surface Isolation

Quantitative profiling of cell surface proteins is critically important for the understanding of cell-cell communication, signaling, tissue development, and homeostasis. Traditional proteomics methods are challenging for cell surface proteins due to their hydrophobic nature and low abundance, necessitating alternative methods to efficiently identify and quantify this protein group. Here we established carboxyl-reactive biotinylation for selective and efficient biotinylation and isolation of surface-exposed proteins of living cells. We assessed the efficiency of carboxyl-reactive biotinylation for plasma membrane proteins by comparing it with a well-established protocol, amine-reactive biotinylation, using SILAC (stable isotope labeling in cell culture). Our results show that carboxyl-reactive biotinylation of cell surface proteins is both more selective and more efficient than amine-reactive biotinylation. We conclude that it is a useful approach, which is partially orthogonal to amine-reactive biotinylation, allowing us to cast a wider net for a comprehensive profiling of cell surface proteins.

Targeting RAS-driven human cancer cells with antibodies to upregulated and essential cell-surface proteins

While there have been tremendous efforts to target oncogenic RAS signaling from inside the cell, little effort has focused on the cell-surface. Here, we used quantitative surface proteomics to reveal a signature of proteins that are upregulated on cells transformed with KRAS^G12V, and driven by MAPK pathway signaling. We next generated a toolkit of recombinant antibodies to seven of these RAS-induced proteins. We found that five of these proteins are broadly distributed on cancer cell lines harboring RAS mutations. In parallel, a cell-surface CRISPRi screen identified integrin and Wnt signaling proteins as critical to RAS-transformed cells. We show that antibodies targeting CDCP1, a protein common to our proteomics and CRISPRi datasets, can be leveraged to deliver cytotoxic and immunotherapeutic payloads to RAS-transformed cancer cells and report for RAS signaling status in vivo. Taken together, this work presents a technological platform for attacking RAS from outside the cell.

Dissociative role for dorsal hippocampus in mediating heroin self-administration and relapse through CDK5 and RhoB signaling revealed by proteomic analysis

Addiction is characterized by drug craving, compulsive drug taking and relapse, which is attributed to aberrant neuroadaptation in brain regions implicated in drug addiction, induced by changes in gene and protein expression in these regions after chronic drug exposure. Accumulating evidence suggests that the dorsal hippocampus (DH) plays an important role in mediating drug-seeking and drug-taking behavior and relapse. However, the molecular mechanisms underlying these effects of the DH are unclear. In the present study, we employed a label-free quantitative proteomic approach to analyze the proteins altered in the DH of heroin self-administering rats. A total of 4015 proteins were quantified with high confidence, and 361 proteins showed significant differences compared with the saline control group. Among them, cyclin-dependent kinase 5 (CDK5) and ras homolog family member B (RhoB) were up-regulated in rats with a history of extended access to heroin. Functionally, inhibition of CDK5 in the DH enhanced heroin self-administration, indicating that CDK5 signaling in the DH acts as a homeostatic compensatory mechanism to limit heroin-taking behavior, whereas blockade of the Rho-Rho kinase (ROCK) pathway attenuated context-induced heroin relapse, indicating that RhoB signaling in the DH is required for the retrieval (recall) of addiction memory. Our findings suggest that manipulation of CDK5 signaling in the DH may be essential in determining vulnerability to opiate taking, whereas manipulation of RhoB signaling in the DH may be essential in determining vulnerability to relapse. Overall, the present study suggests that the DH can exert dissociative effects on heroin addiction through CDK5 and RhoB signaling.

Paired Expression Analysis of Tumor Cell Surface Antigens

Adoptive immunotherapy with antibody-based therapy or with T cells transduced to express chimeric antigen receptors (CARs) is useful to the extent that the cell surface membrane protein being targeted is not expressed on normal tissues. The most successful CAR-based (anti-CD19) or antibody-based therapy (anti-CD20) in hematologic malignancies has the side effect of eliminating the normal B cell compartment. Targeting solid tumors may not provide a similar expendable marker. Beyond antibody to Her2/NEU and EGFR, very few antibody-based and no CAR-based therapies have seen broad clinical application for solid tumors. To expand the way in which the surfaceome of solid tumors can be analyzed, we created an algorithm that defines the pairwise relative overexpression of surface antigens. This enables the development of specific immunotherapies that require the expression of two discrete antigens on the surface of the tumor target. This dyad analysis was facilitated by employing the Hotelling’s T-squared test (Hotelling–Lawley multivariate analysis of variance) for two independent variables in comparison to a third constant entity (i.e., gene expression levels in normal tissues). We also present a unique consensus scoring mechanism for identifying transcripts that encode cell surface proteins. The unique application of our bioinformatics processing pipeline and statistical tools allowed us to compare the expression of two membrane protein targets as a pair, and to propose a new strategy based on implementing immunotherapies that require both antigens to be expressed on the tumor cell surface to trigger therapeutic effector mechanisms. Specifically, we found that, for MYCN amplified neuroblastoma, pairwise expression of ACVR2B or anaplastic lymphoma kinase (ALK) with GFRA3, GFRA2, Cadherin 24, or with one another provided the strongest hits. For MYCN, non-amplified stage 4 neuroblastoma, neurotrophic tyrosine kinase 1, or ALK paired with GFRA2, GFRA3, SSK1, GPR173, or with one another provided the most promising paired-hits. We propose that targeting these markers together would increase the specificity and thereby the safety of CAR-based therapy for neuroblastoma.

Chemical Glycoproteomics

Chemical tools have accelerated progress in glycoscience, reducing experimental barriers to studying protein glycosylation, the most widespread and complex form of posttranslational modification. For example, chemical glycoproteomics technologies have enabled the identification of specific glycosylation sites and glycan structures that modulate protein function in a number of biological processes. This field is now entering a stage of logarithmic growth, during which chemical innovations combined with mass spectrometry advances could make it possible to fully characterize the human glycoproteome. In this review, we describe the important role that chemical glycoproteomics methods are playing in such efforts. We summarize developments in four key areas: enrichment of glycoproteins and glycopeptides from complex mixtures, emphasizing methods that exploit unique chemical properties of glycans or introduce unnatural functional groups through metabolic labeling and chemoenzymatic tagging; identification of sites of protein glycosylation; targeted glycoproteomics; and functional glycoproteomics, with a focus on probing interactions between glycoproteins and glycan-binding proteins. Our goal with this survey is to provide a foundation on which continued technological advancements can be made to promote further explorations of protein glycosylation.

Proneurogenic Ligands Defined by Modeling Developing Cortex Growth Factor Communication Networks

The neural stem cell decision to self-renew or differentiate is tightly regulated by its microenvironment. Here, we have asked about this microenvironment, focusing on growth factors in the embryonic cortex at a time when it is largely comprised of neural precursor cells (NPCs) and newborn neurons. We show that cortical NPCs secrete factors that promote their maintenance, while cortical neurons secrete factors that promote differentiation. To define factors important for these activities, we used transcriptome profiling to identify ligands produced by NPCs and neurons, cell-surface mass spectrometry to identify receptors on these cells, and computational modeling to integrate these data. The resultant model predicts a complex growth factor environment with multiple autocrine and paracrine interactions. We tested this communication model, focusing on neurogenesis, and identified IFNγ, Neurturin (Nrtn), and glial-derived neurotrophic factor (GDNF) as ligands with unexpected roles in promoting neurogenic differentiation of NPCs in vivo.

Integral membrane proteins in proteomics. How to break open the black box?

Integral membrane proteins (IMPs) are coded by 20-30% of human genes and execute important functions - transmembrane transport, signal transduction, cell-cell communication, cell adhesion to the extracellular matrix, and many other processes. Due to their hydrophobicity, low expression and lack of trypsin cleavage sites in their transmembrane segments, IMPs have been generally under-represented in routine proteomic analyses. However, the field of membrane proteomics has changed markedly in the past decade, namely due to the introduction of filter assisted sample preparation (FASP), the establishment of cell surface capture (CSC) protocols, and the development of methods that enable analysis of the hydrophobic transmembrane segments. This review will summarize the recent developments in the field and outline the most successful strategies for the analysis of integral membrane proteins.

SIGNIFICANCE

Integral membrane proteins (IMPs) are attractive therapeutic targets mostly due to their many important functions. However, our knowledge of the membrane proteome is severely limited to effectively exploit their potential. This is mostly due to the lack of appropriate techniques or methods compatible with the typical features of IMPs, namely hydrophobicity, low expression and lack of trypsin cleavage sites. This review summarizes the most recent development in membrane proteomics and outlines the most successful strategies for their large-scale analysis.

Slx5/Slx8 Promotes Replication Stress Tolerance by Facilitating Mitotic Progression

Loss of minichromosome maintenance protein 10 (Mcm10) causes replication stress. We uncovered that S. cerevisiae mcm10-1 mutants rely on the E3 SUMO ligase Mms21 and the SUMO-targeted ubiquitin ligase complex Slx5/8 for survival. Using quantitative mass spectrometry, we identified changes in the SUMO proteome of mcm10-1 mutants and revealed candidates regulated by Slx5/8. Such candidates included subunits of the chromosome passenger complex (CPC), Bir1 and Sli15, known to facilitate spindle assembly checkpoint (SAC) activation. We show here that Slx5 counteracts SAC activation in mcm10-1 mutants under conditions of moderate replication stress. This coincides with the proteasomal degradation of sumoylated Bir1. Importantly, Slx5-dependent mitotic relief was triggered not only by Mcm10 deficiency but also by treatment with low doses of the alkylating drug methyl methanesulfonate. Based on these findings, we propose a model in which Slx5/8 allows for passage through mitosis when replication stress is tolerable.

Surface proteome analysis identifies platelet derived growth factor receptor-alpha as a critical mediator of transforming growth factor-beta-induced collagen secretion

Fibroblasts are extracellular matrix-producing cells in the lung. Fibroblast activation by transforming growth factor-beta leads to myofibroblast-differentiation and increased extracellular matrix deposition, a hallmark of pulmonary fibrosis. While fibroblast function with respect to migration, invasion, and extracellular matrix deposition has been well-explored, little is known about the surface proteome of lung fibroblasts in general and its specific response to fibrogenic growth factors, in particular transforming growth factor-beta. We thus performed a cell-surface proteome analysis of primary human lung fibroblasts in presence/absence of transforming growth factor-beta, followed by characterization of our findings using FACS analysis, Western blot, and siRNA-mediated knockdown experiments. We identified 213 surface proteins significantly regulated by transforming growth factor-beta, platelet derived growth factor receptor-alpha being one of the top down-regulated proteins. Transforming growth factor beta-induced downregulation of platelet derived growth factor receptor-alpha induced upregulation of platelet derived growth factor receptor-beta expression and phosphorylation of Akt, a downstream target of platelet derived growth factor signaling. Importantly, collagen type V expression and secretion was strongly increased after forced knockdown of platelet derived growth factor receptor-alpha, an effect that was potentiated by transforming growth factor-beta. We therefore show previously underappreciated cross-talk of transforming growth factor-beta and platelet derived growth factor signaling in human lung fibroblasts, resulting in increased extracellular matrix deposition in a platelet derived growth factor receptor-alpha dependent manner. These findings are of particular importance for the treatment of lung fibrosis patients with high pulmonary transforming growth factor-beta activity.

Identification of a Novel Function of Adipocyte Plasma Membrane-Associated Protein (APMAP) in Gestational Diabetes Mellitus by Proteomic Analysis of Omental Adipose Tissue

Gestational diabetes mellitus (GDM) is considered as an early stage of type 2 diabetes mellitus. In this study, we compared demographic and clinical data between six GDM subjects and six normal glucose tolerance (NGT; healthy controls) subjects and found that homeostasis model of assessment for insulin resistance index (HOMA-IR) increased in GDM. Many previous studies demonstrated that omental adipose tissue dysfunction could induce insulin resistance. Thus, to investigate the cause of insulin resistance in GDM, we used label-free proteomics to identify differentially expressed proteins in omental adipose tissues from GDM and NGT subjects (data are available via ProteomeXchange with identifier PXD003095). A total of 3528 proteins were identified, including 66 significantly changed proteins. Adipocyte plasma membrane-associated protein (APMAP, a.k.a. C20orf3), one of the differentially expressed proteins, was down-regulated in GDM omental adipose tissues. Furthermore, mature 3T3-L1 adipocytes were used to simulate omental adipocytes. The inhibition of APMAP expression by RNAi impaired insulin signaling and activated NFκB signaling in these adipocytes. Our study revealed that the down-regulation of APMAP in omental adipose tissue may play an important role in insulin resistance in the pathophysiology of GDM.

Towards in vivo estimation of reaction kinetics using high-throughput metabolomics data: a maximum likelihood approach

Background

High-throughput assays such as mass spectrometry have opened up the possibility for large-scale in vivo measurements of the metabolome. This data could potentially be used to estimate kinetic parameters for many metabolic reactions. However, high-throughput in vivo measurements have special properties that are not taken into account in existing methods for estimating kinetic parameters, including significant relative errors in measurements of metabolite concentrations and reaction rates, and reactions with multiple substrates and products, which are sometimes reversible. A new method is needed to estimate kinetic parameters taking into account these factors.

Results

A new method, InVEst (In Vivo Estimation), is described for estimating reaction kinetic parameters, which addresses the specific challenges of in vivo data. InVEst uses maximum likelihood estimation based on a model where all measurements have relative errors. Simulations show that InVEst produces accurate estimates for a reversible enzymatic reaction with multiple reactants and products, that estimated parameters can be used to predict the effects of genetic variants, and that InVEst is more accurate than general least squares and graphic methods on data with relative errors. InVEst uses the bootstrap method to evaluate the accuracy of its estimates.

Conclusions

InVEst addresses several challenges of in vivo data, which are not taken into account by existing methods. When data have relative errors, InVEst produces more accurate and robust estimates. InVEst also provides useful information about estimation accuracy using bootstrapping. It has potential applications of quantifying the effects of genetic variants, inference of the target of a mutation or drug treatment and improving flux estimation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0214-7) contains supplementary material, which is available to authorized users.

Bioorthogonal labeling cell-surface proteins expressed in pancreatic cancer cells to identify potential diagnostic/therapeutic biomarkers

To develop new diagnostic and therapeutic tools to specifically target pancreatic tumors, it is necessary to identify cell-surface proteins that may serve as potential tumor-specific targets. In this study we used an azido-labeled bioorthogonal chemical reporter to metabolically label N-linked glycoproteins on the surface of pancreatic cancer cell lines to identify potential targets that may be exploited for detection and/or treatment of pancreatic cancer. Labeled glycoproteins were tagged with biotin using click chemistry, purified by streptavidin-coupled magnetic beads, separated by gel electrophoresis, and identified by liquid chromatography-tandem mass spectrometry (MS). MS/MS analysis of peptides from 3 cell lines revealed 954 unique proteins enriched in the azido sugar samples relative to control sugar samples. A comparison of the proteins identified in each sample indicated 20% of these proteins were present in 2 cell lines (193 of 954) and 17 of the proteins were found in all 3 cell lines. Five of the 17 proteins identified in all 3 cell lines have not been previously reported to be expressed in pancreatic cancer; thus indicating that novel cell-surface proteins can be revealed through glycoprotein profiling. Western analysis of one of these glycoproteins, ecto-5'-nucleotidase (NT5E), revealed it is expressed in 8 out of 8 pancreatic cancer cell lines examined. Further, immunohistochemical analysis of human pancreatic tissues indicates NT5E is significantly overexpressed in pancreatic tumors compared to normal pancreas. Thus, we have demonstrated that metabolic labeling with bioorthogonal chemical reporters can be used to selectively enrich and identify novel cell-surface glycoproteins expressed in pancreatic ductal adenocarcinomas.

Preparation of hydrazine functionalized polymer brushes hybrid magnetic nanoparticles for highly specific enrichment of glycopeptides

Hydrazide chemistry is a powerful technique in glycopeptides enrichment. However, the low density of the monolayer hydrazine groups on the conventional hydrazine-functionalized magnetic nanoparticles limits the efficiency of glycopeptides enrichment. Herein, a novel magnetic nanoparticle grafted with poly(glycidyl methacrylate) (GMA) brushes was fabricated via reversible addition-fragmentation chain transfer (RAFT) polymerization, and a large amount of hydrazine groups were further introduced to the GMA brushes by ring-opening the epoxy groups with hydrazine hydrate. The resulting magnetic nanoparticles (denoted as Fe3O4@SiO2@GMA-NHNH2) demonstrated the high specificity of capturing glycopeptides from a tryptic digest of the sample comprising a standard non-glycosylated protein bovine serum albumin (BSA) and four standard glycoproteins with a weight ratio of 50 : 1, and the detection limit was as low as 130 fmol. In the analysis of a real complex biological sample, the tryptic digest of hepatocellular carcinoma, 179 glycosites were identified by the Fe3O4@SiO2@GMA-NHNH2 nanoparticles, surpassing that of 68 glycosites by Fe3O4@SiO2-single-NHNH2 (with monolayer hydrazine groups on the surface). It can be expected that the magnetic nanoparticles modified with hydrazine functionalized polymer brushes via RAFT technique will improve the specificity and the binding capacity of glycopeptides from complex samples, and show great potential in the analysis of protein glycosylation in biological samples.

AMP-Activated Protein Kinase Regulates the Cell Surface Proteome and Integrin Membrane Traffic

The cell surface proteome controls numerous cellular functions including cell migration and adhesion, intercellular communication and nutrient uptake. Cell surface proteins are controlled by acute changes in protein abundance at the plasma membrane through regulation of endocytosis and recycling (endomembrane traffic). Many cellular signals regulate endomembrane traffic, including metabolic signaling; however, the extent to which the cell surface proteome is controlled by acute regulation of endomembrane traffic under various conditions remains incompletely understood. AMP-activated protein kinase (AMPK) is a key metabolic sensor that is activated upon reduced cellular energy availability. AMPK activation alters the endomembrane traffic of a few specific proteins, as part of an adaptive response to increase energy intake and reduce energy expenditure. How increased AMPK activity during energy stress may globally regulate the cell surface proteome is not well understood. To study how AMPK may regulate the cell surface proteome, we used cell-impermeable biotinylation to selectively purify cell surface proteins under various conditions. Using ESI-MS/MS, we found that acute (90 min) treatment with the AMPK activator A-769662 elicits broad control of the cell surface abundance of diverse proteins. In particular, A-769662 treatment depleted from the cell surface proteins with functions in cell migration and adhesion. To complement our mass spectrometry results, we used other methods to show that A-769662 treatment results in impaired cell migration. Further, A-769662 treatment reduced the cell surface abundance of β1-integrin, a key cell migration protein, and AMPK gene silencing prevented this effect. While the control of the cell surface abundance of various proteins by A-769662 treatment was broad, it was also selective, as this treatment did not change the cell surface abundance of the transferrin receptor. Hence, the cell surface proteome is subject to acute regulation by treatment with A-769662, at least some of which is mediated by the metabolic sensor AMPK.

MS1-based label-free proteomics using a quadrupole orbitrap mass spectrometer

Presented is a data set for benchmarking MS1-based label-free quantitative proteomics using a quadrupole orbitrap mass spectrometer. Escherichia coli digest was spiked into a HeLa digest in four different concentrations, simulating protein expression differences in a background of an unchanged complex proteome. The data set provides a unique opportunity to evaluate the proteomic platform (instrumentation and software) in its ability to perform MS1-intensity-based label-free quantification. We show that the presented combination of informatics and instrumentation produces high precision and quantification accuracy. The data were also used to compare different quantitative protein inference methods such as iBAQ and Hi-N. The data can also be used as a resource for development and optimization of proteomics informatics tools, thus the raw data have been deposited to ProteomeXchange with identifier PXD001385.

Quantitative mass spectrometric analysis of glycoproteins combined with enrichment methods

Mass spectrometry (MS) has been a core technology for high sensitive and high-throughput analysis of the enriched glycoproteome in aspects of quantitative assays as well as qualitative profiling of glycoproteins. Because it has been widely recognized that aberrant glycosylation in a glycoprotein may involve in progression of a certain disease, the development of efficient analysis tool for the aberrant glycoproteins is very important for deep understanding about pathological function of the glycoprotein and new biomarker development. This review first describes the protein glycosylation-targeting enrichment technologies mainly employing solid-phase extraction methods such as hydrizide-capturing, lectin-specific capturing, and affinity separation techniques based on porous graphitized carbon, hydrophilic interaction chromatography, or immobilized boronic acid. Second, MS-based quantitative analysis strategies coupled with the protein glycosylation-targeting enrichment technologies, by using a label-free MS, stable isotope-labeling, or targeted multiple reaction monitoring (MRM) MS, are summarized with recent published studies.

Coupling enrichment methods with proteomics for understanding and treating disease

Owing to recent advances in proteomics analytical methods and bioinformatics capabilities there is a growing trend toward using these capabilities for the development of drugs to treat human disease, including target and drug evaluation, understanding mechanisms of drug action, and biomarker discovery. Currently, the genetic sequences of many major organisms are available, which have helped greatly in characterizing proteomes in model animal systems and humans. Through proteomics, global profiles of different disease states can be characterized (e.g. changes in types and relative levels as well as changes in PTMs such as glycosylation or phosphorylation). Although intracellular proteomics can provide a broad overview of physiology of cells and tissues, it has been difficult to quantify the low abundance proteins which can be important for understanding the diseased states and treatment progression. For this reason, there is increasing interest in coupling comparative proteomics methods with subcellular fractionation and enrichment techniques for membranes, nucleus, phosphoproteome, glycoproteome as well as low abundance serum proteins. In this review, we will provide examples of where the utilization of different proteomics-coupled enrichment techniques has aided target and biomarker discovery, understanding the drug targeting mechanism, and mAb discovery. Taken together, these improvements will help to provide a better understanding of the pathophysiology of various diseases including cancer, autoimmunity, inflammation, cardiovascular disease, and neurological conditions, and in the design and development of better medicines for treating these afflictions.

Quantitative comparison of a human cancer cell surface proteome between interphase and mitosis

The cell surface is the cellular compartment responsible for communication with the environment. The interior of mammalian cells undergoes dramatic reorganization when cells enter mitosis. These changes are triggered by activation of the CDK1 kinase and have been studied extensively. In contrast, very little is known of the cell surface changes during cell division. We undertook a quantitative proteomic comparison of cell surface-exposed proteins in human cancer cells that were tightly synchronized in mitosis or interphase. Six hundred and twenty-eight surface and surface-associated proteins in HeLa cells were identified; of these, 27 were significantly enriched at the cell surface in mitosis and 37 in interphase. Using imaging techniques, we confirmed the mitosis-selective cell surface localization of protocadherin PCDH7, a member of a family with anti-adhesive roles in embryos. We show that PCDH7 is required for development of full mitotic rounding pressure at the onset of mitosis. Our analysis provided basic information on how cell cycle progression affects the cell surface. It also provides potential pharmacodynamic biomarkers for anti-mitotic cancer chemotherapy.

Surfaceome profiling reveals regulators of neural stem cell function

The composition of cell-surface proteins changes during lineage specification, altering cellular responses to their milieu. The changes that characterize maturation of early neural stem cells (NSCs) remain poorly understood. Here we use mass spectrometry-based cell surface capture technology to profile the cell surface of early NSCs and demonstrate functional requirements for several enriched molecules. Primitive NSCs arise from embryonic stem cells upon removal of Transforming growth factor-β signaling, while definitive NSCs arise from primitive NSCs upon Lif removal and FGF addition. In vivo aggregation assays revealed that N-cadherin upregulation is sufficient for the initial exclusion of definitive NSCs from pluripotent ectoderm, while c-kit signaling limits progeny of primitive NSCs. Furthermore, we implicate EphA4 in primitive NSC survival signaling and Erbb2 as being required for NSC proliferation. This work elucidates several key mediators of NSC function whose relevance is confirmed on forebrain-derived populations and identifies a host of other candidates that may regulate NSCs.

The life cycle and pathogenesis of human cytomegalovirus infection: lessons from proteomics

Viruses have coevolved with their hosts, acquiring strategies to subvert host cellular pathways for effective viral replication and spread. Human cytomegalovirus (HCMV), a widely-spread β-herpesvirus, is a major cause of birth defects and opportunistic infections in HIV-1/AIDS patients. HCMV displays an intricate system-wide modulation of the human cell proteome. An impressive array of virus-host protein interactions occurs throughout the infection. To investigate the virus life cycle, proteomics has recently become a significant component of virology studies. Here, we review the mass spectrometry-based proteomics approaches used in HCMV studies, as well as their contribution to understanding the HCMV life cycle and the virus-induced changes to host cells. The importance of the biological insights gained from these studies clearly demonstrate the impact that proteomics has had and can continue to have on understanding HCMV biology and identifying new therapeutic targets.

Ribonomic approaches to study the RNA-binding proteome

Gene expression is controlled through a complex interplay among mRNAs, non-coding RNAs and RNA-binding proteins (RBPs), which all assemble along with other RNA-associated factors in dynamic and functional ribonucleoprotein complexes (RNPs). To date, our understanding of RBPs is largely limited to proteins with known or predicted RNA-binding domains. However, various methods have been recently developed to capture an RNA of interest and comprehensively identify its associated RBPs. In this review, we discuss the RNA-affinity purification methods followed by mass spectrometry analysis (AP-MS); RBP screening within protein libraries and computational methods that can be used to study the RNA-binding proteome (RBPome).

Protein-centric N-glycoproteomics analysis of membrane and plasma membrane proteins

The advent of proteomics technology has transformed our understanding of biological membranes. The challenges for studying membrane proteins have inspired the development of many analytical and bioanalytical tools, and the techniques of glycoproteomics have emerged as an effective means to enrich and characterize membrane and plasma-membrane proteomes. This Review summarizes the development of various glycoproteomics techniques to overcome the hurdles formed by the unique structures and behaviors of membrane proteins with a focus on N-glycoproteomics. Example contributions of N-glycoproteomics to the understanding of membrane biology are provided, and the areas that require future technical breakthroughs are discussed.

Identification of chemoresistance-related cell-surface glycoproteins in leukemia cells and functional validation of candidate glycoproteins

Chemoresistance remains the most significant obstacle to successful chemotherapy for leukemia, and its exact mechanism is still unknown. In this work, we used the cell-surface capturing method together with quantitative proteomics to investigate differences in the glycoproteomes of adriamycin-sensitive and adriamycin-resistant leukemia cells. Two quantitative methods, isotopic dimethyl labeling and SWATH, were used to quantify glycoproteins, and 35 glycoproteins were quantified by both methods. High correlation was observed between the glycoproteins quantified by the above two methods, and 15 glycoproteins displayed a consistent significant change trend in both sets of quantitative results. These 15 proteins included classical multidrug resistance-related glycoproteins such as ABCB1 as well as a set of novel glycoproteins that have not previously been reported to be associated with chemoresistance in leukemia cells. Further validation with quantitative real-time PCR and Western blotting confirmed the proteomic screening results. Subsequent functional experiments based on RNA interference technology showed that CTSD, FKBP10, and SLC2A1 are novel genes that participate in the acquisition and maintenance of the adriamycin-resistant phenotype in leukemia cells.

CD109 Overexpression in Pancreatic Cancer Identified by Cell-Surface Glycoprotein Capture

BACKGROUND

The development of novel targeted cancer therapies and/or diagnostic tools is dependent upon an understanding of the differential expression of molecular targets between normal tissues and tumors. Many of these potential targets are cell-surface receptors; however, our knowledge of the cell-surface proteins upregulated in pancreatic tumors is limited, thus impeding the development of targeted therapies for pancreatic cancer. To develop new diagnostic and therapeutic tools to specifically target pancreatic tumors, we sought to identify cell-surface proteins that may serve as potential tumor-specfic targets.

METHODS

Membrane glycoproteins on the pancreatic cancer cell lines BxPC-3 were labeled with the bifunctional linker biocytin hydrazide. Following proteolytic digestion, biotinylated glycopeptides were captured with streptavidin-coupled beads then released by PNGaseF-mediated endoglycosidase cleavage and identified by liquid chromatography-tandem mass spectrometry (MS). A protein identified by the cell-surface glycoprotein capture procedure, CD109, was evaluated by western analysis of lysates of pancreatic cancer cell lines and by immunohistochemistry in sections of pancreatic ductal adenocarcinoma and non- neoplastic pancreatic tissues.

RESULTS

MS/MS analysis of glycopeptides captured from BxPC-3 cells revealed 18 proteins predicted or known to be associated with the plasma membrane, including CD109, which has not been reported in pancreatic cancer. Western analysis of CD109 in lysates prepared from pancreatic cancer cell lines revealed it was expressed in 6 of 8 cell lines, with a high level of expression in BxPC-3, MIAPaCa-2, and Panc-1 cells. Immunohistochemical analyses of human pancreatic tissues indicate CD109 is significantly overexpressed in pancreatic tumors compared to normal pancreas.

CONCLUSIONS

The selective capture of glycopeptides from the surface of pancreatic cancer cell lines can reveal novel cell-surface glycoproteins expressed in pancreatic ductal adenocarcinomas.

Targeting the endothelial progenitor cell surface proteome to identify novel mechanisms that mediate angiogenic efficacy in a rodent model of vascular disease

Endothelial progenitor cells (EPCs) promote angiogenesis, and clinical trials suggest autologous EPC-based therapy may be effective in treatment of vascular diseases. Albeit promising, variability in the efficacy of EPCs associated with underlying disease states has hindered the realization of EPC-based therapy. Here we first identify and characterize EPC dysfunction in a rodent model of vascular disease (SS/Mcwi rat) that exhibits impaired angiogenesis. To identify molecular candidates that mediate the angiogenic potential of these cells, we performed a broad analysis of cell surface protein expression using chemical labeling combined with mass spectrometry. Analysis revealed EPCs derived from SS/Mcwi rats express significantly more type 2 low-affinity immunoglobulin Fc-gamma (FCGR2) and natural killer 2B4 (CD244) receptors compared with controls. Genome-wide sequencing (RNA-seq) and qt-PCR confirmed isoforms of CD244 and FCGR2a transcripts were increased in SS/Mcwi EPCs. EPCs with elevated expression of FCGR2a and CD244 receptors are predicted to increase the probability of SS/Mcwi EPCs being targeted for death, providing a mechanistic explanation for their reduced angiogenic efficacy in vivo. Pathway analysis supported this contention, as "key" molecules annotated to cell death paths were differentially expressed in the SS/Mcwi EPCs. We speculate that screening and neutralization of cell surface proteins that "tag" and impair EPC function may provide an alternative approach to utilizing incompetent EPCs in greater numbers, as circulating EPCs are depleted in patients with vascular disease. Overall, novel methods to identify putative targets for repair of EPCs using discovery-based technologies will likely provide a major advance in the field of regenerative medicine.

Proteomic techniques for characterisation of mesenchymal stem cell secretome

Mesenchymal stem cells (MSCs) are multipotent cells with a substantial potential in human regenerative medicine due to their ability to migrate to sites of injury, capability to suppress immune response and accessibility in large amount from patient's own bone marrow or fat tissue. It has been increasingly observed that the transplanted MSCs did not necessarily engraft and differentiate at the site of injury but might exert their therapeutic effects through secreted trophic signals. The MSCs secrete a variety of autocrine/paracrine factors, called secretome, that support regenerative processes in the damaged tissue, induce angiogenesis, protect cells from apoptotic cell death and modulate immune system. The cell culture medium conditioned by MSCs or osteogenic, chondrogenic as well as adipogenic precursors derived from MSCs has become a subject of intensive proteomic profiling in the search for and identification of released factors and microvesicles that might be applicable in regenerative medicine. Jointly with the methods for MSC isolation, expansion and differentiation, proteomic analysis of MSC secretome was enabled recently mainly due to the extensive development in protein separation techniques, mass spectrometry, immunological methods and bioinformatics. This review describes proteomic techniques currently applied or prospectively applicable in MSC secretomics, with a particular focus on preparation of the secretome sample, protein/peptide separation, mass spectrometry and protein quantification techniques, analysis of posttranslational modifications, immunological techniques, isolation and characterisation of secreted vesicles and exosomes, analysis of cytokine-encoding mRNAs and bioinformatics.

Neuron enriched nuclear proteome isolated from human brain

The brain consists of diverse cell types including neurons, astrocytes, oligodendrocytes, and microglia. The isolation of nuclei from these distinct cell populations provides an opportunity to identify cell-type-specific nuclear proteins, histone modifications, and regulation networks that are altered with normal brain aging or neurodegenerative disease. In this study, we used a method by which intact neuronal and non-neuronal nuclei were purified from human post-mortem brain employing a modification of fluorescence activated cell sorting (FACS) termed fluorescence activated nuclei sorting (FANS). An antibody against NeuN, a neuron specific splicing factor, was used to isolate neuronal nuclei. Utilizing mass spectrometry (MS) based label-free quantitative proteomics, we identified 1755 proteins from sorted NeuN-positive and negative nuclear extracts. Approximately 20% of these proteins were significantly enriched or depleted in neuronal versus non-neuronal populations. Immunoblots of primary cultured rat neuron, astrocyte, and oligodendrocyte extracts confirmed that distinct members of the major nucleocytoplasmic structural linkage complex (LINC), nesprin-1 and nesprin-3, were differentially enriched in neurons and astrocytes, respectively. These comparative proteomic data sets also reveal a number of transcription and splicing factors that are selectively enriched in a cell-type-specific manner in human brain.

Effect of posttranslational modifications on enzyme function and assembly

The detailed examination of enzyme molecules by mass spectrometry and other techniques continues to identify hundreds of distinct PTMs. Recently, global analyses of enzymes using methods of contemporary proteomics revealed widespread distribution of PTMs on many key enzymes distributed in all cellular compartments. Critically, patterns of multiple enzymatic and nonenzymatic PTMs within a single enzyme are now functionally evaluated providing a holistic picture of a macromolecule interacting with low molecular mass compounds, some of them being substrates, enzyme regulators, or activated precursors for enzymatic and nonenzymatic PTMs. Multiple PTMs within a single enzyme molecule and their mutual interplays are critical for the regulation of catalytic activity. Full understanding of this regulation will require detailed structural investigation of enzymes, their structural analogs, and their complexes. Further, proteomics is now integrated with molecular genetics, transcriptomics, and other areas leading to systems biology strategies. These allow the functional interrogation of complex enzymatic networks in their natural environment. In the future, one might envisage the use of robust high throughput analytical techniques that will be able to detect multiple PTMs on a global scale of individual proteomes from a number of carefully selected cells and cellular compartments. This article is part of a Special Issue entitled: Posttranslational Protein modifications in biology and Medicine.

Systematic proteomic analysis identifies β-site amyloid precursor protein cleaving enzyme 2 and 1 (BACE2 and BACE1) substrates in pancreatic β-cells

Expansion of functional islet β-cell mass is a physiological process to compensate for increased insulin demand. Deficiency or pharmacological inhibition of the plasma membrane protease BACE2 enhances pancreatic β-cell function and proliferation, and therefore BACE2 is a putative target for the therapeutic intervention under conditions of β-cell loss and dysfunction. To gain a molecular understanding of BACE2 function, we performed a systematic and quantitative proteomic analysis to map the natural substrate repertoire of BACE2 and its homologue BACE1 in β-cells. Loss- and gain-of-function studies of in vitro and in vivo models identified specific and functionally heterogeneous targets. Our analysis revealed non-redundant roles of BACE1/2 in ectodomain shedding with BACE1 regulating a broader and BACE2 a more distinct set of β-cell-enriched substrates including two proteins of the seizure 6 protein family (SEZ6L and SEZ6L2). Lastly, our study provides insights into the global β-cell sheddome and secretome, an important prerequisite to uncover novel mechanisms contributing to β-cell homeostasis and a resource for therapeutic target and biomarker discoveries.

Characterization of membrane-associated glycoproteins using lectin affinity chromatography and mass spectrometry

Membrane-associated glycoproteins play critical roles in many biological processes and are often the therapeutic targets for drug discovery. Lectin affinity chromatography is one of the most widely used approaches for enrichment of glycoproteins at the protein level. Here, we describe a strategy for the characterization of membrane glycoproteins including membrane protein extraction, lectin affinity chromatography, protein digestion, and analysis by LC-MS/MS.

CSC technology: selective labeling of glycoproteins by mild oxidation to phenotype cells

Cell surface glycoproteins represent important markers for the phenotyping of healthy and malignantly transformed cells. The mass spectrometry-based cell surface capturing (CSC) technology allows for extensive multiplexed identification and relative quantification of glycoproteins expressed on the cell surface at a given point in time. CSC technology is based on the mild oxidation of glycans from cell surface proteins on living cells. Oxidized glycans are tagged with a bifunctional linker molecule and glycopeptides are subsequently enriched by affinity chromatography. Here, we describe a step-by-step protocol of the CSC technology, which not only enables the identification of cell surface glycoproteins, but also the concurrent determination of protein N-glycosylation sites.

The promiscuous binding of pharmaceutical drugs and their transporter-mediated uptake into cells: what we (need to) know and how we can do so

A recent paper in this journal sought to counter evidence for the role of transport proteins in effecting drug uptake into cells, and questions that transporters can recognize drug molecules in addition to their endogenous substrates. However, there is abundant evidence that both drugs and proteins are highly promiscuous. Most proteins bind to many drugs and most drugs bind to multiple proteins (on average more than six), including transporters (mutations in these can determine resistance); most drugs are known to recognise at least one transporter. In this response, we alert readers to the relevant evidence that exists or is required. This needs to be acquired in cells that contain the relevant proteins, and we highlight an experimental system for simultaneous genome-wide assessment of carrier-mediated uptake in a eukaryotic cell (yeast).

The pancreatic beta cell surface proteome

The pancreatic beta cell is responsible for maintaining normoglycaemia by secreting an appropriate amount of insulin according to blood glucose levels. The accurate sensing of the beta cell extracellular environment is therefore crucial to this endocrine function and is transmitted via its cell surface proteome. Various surface proteins that mediate or affect beta cell endocrine function have been identified, including growth factor and cytokine receptors, transporters, ion channels and proteases, attributing important roles to surface proteins in the adaptive behaviour of beta cells in response to acute and chronic environmental changes. However, the largely unknown composition of the beta cell surface proteome is likely to harbour yet more information about these mechanisms and provide novel points of therapeutic intervention and diagnostic tools. This article will provide an overview of the functional complexity of the beta cell surface proteome and selected surface proteins, outline the mechanisms by which their activity may be modulated, discuss the methods and challenges of comprehensively mapping and studying the beta cell surface proteome, and address the potential of this interesting subproteome for diagnostic and therapeutic applications in human disease.