Quantification of the N-glycosylated secretome by super-SILAC during breast cancer progression and in human blood samples

4-plex quantitative glycoproteomics using glycan/protein-stable isotope labeling in cell culture

Alterations in glycoprotein abundance and glycan structures are closely linked to numerous diseases. The quantitative exploration of glycoproteomics is pivotal for biomarker discovery, but comprehensive analysis within biological samples remains challenging due to low abundance, complexity, and lack of universal technology. We developed a multiplex glycoproteomic approach using an LC-ESI-MS platform for direct comparison of glycoproteomic quantitation. Glycopeptides were isotopically labeled during cell culture, achieving high labeling efficiency (≥ 95 %) for both glycans and peptides. Quantitation was validated by mixing the same cell line in a 1:1:1:1 ratio, with mathematical correction applied to deconvolute the ratios. This method proved reliable and was applied to a comparative glycoproteomic study of three breast cancer cell lines (HTB22, MDA-MB-231, MDA-MB-231BR) and one brain cancer cell line (CRL-1620), quantifying glycopeptides from three replicates. The expression of glycopeptides was relatively quantified, and up/down-regulation between cell lines was investigated. This approach provided insights into glycosylation microheterogeneity, crucial for breast cancer brain metastasis research. Benefits include eliminating fluctuations from nano electrospray ionization and reducing analysis time, enabling up to 4-plex profiling in a single injection. Metabolic labeling introduced mass differences at the MS1 level, ensuring increased sensitivity and higher resolution for accurate quantitation. SIGNIFICANCE: Alternations in glycoprotein abundance, changes in glycosylation levels, and variations in glycan structures are closely linked to numerous diseases. The quantitative exploration of glycoproteomics has emerged as a popular area of research for biomarker discovery. However, conducting a comprehensive quantitative analysis of the glycoproteome within biological samples remains challenging due to low abundance, inherent complexities, and the absence of universal quantitative technology. Here, we developed a multiplex glycoproteomic approach using an LC-ESI-MS platform to facilitate direct comparison of glycoproteomic quantitation and enhance throughput. This approach offers benefits such as eliminating quantitative fluctuations arising from nano electrospray ionization (ESI) and reducing analysis time, enabling up to 4-plex glycoproteomic profiling in a single injection. Glycopeptides were stable isotopic labeled during cell culture procedure, attaching to monosaccharides, amino acids, or both. We achieved a high labeling efficiency (≥ 95 %) for both glycans and peptides. Quantitation validation was tested on glycopeptides by mixing the same cell line with 1:1:1:1 ratio. Due to the overlapped isotopes, a mathematical correction was applied to deconvolute the ratio of 4-plex glycopeptides. This method demonstrated quantitative reliability and was successfully applied to a comparative glycoproteomic study of three breast cancer cells (HTB22, MDA-MB-231, and MDA-MB-231BR) and one brain cancer cell (CRL-1620), identifying a total of 264 glycopeptides from three replicates. The expression of glycopeptides among these four cells was relatively quantified and up/down-regulation between two cell lines was investigated. The exploration of glycosylation microheterogeneity through glycopeptide quantification may offer valuable insights for further investigation into breast cancer brain metastasis. Conclusion: The primary advantage of our presented work lies in the multiplexing offered by combining two established labeling techniques, SILAC and IDAWG, both of which have been effectively used and widely cited in the scientific community. This combination enhances the applicability and accuracy of our method, as demonstrated by the extensive citations and successful use of these techniques independently. We believe that this multiplexing approach significantly advances the field, despite the method's current limitation to cell systems.

Combining Data Independent Acquisition With Spike-In SILAC (DIA-SiS) Improves Proteome Coverage and Quantification

Data-independent acquisition (DIA) is increasingly preferred over data-dependent acquisition due to its higher throughput and fewer missing values. Whereas data-dependent acquisition often uses stable isotope labeling to improve quantification, DIA mostly relies on label-free approaches. Efforts to integrate DIA with isotope labeling include chemical methods like mass differential tags for relative and absolute quantification and dimethyl labeling, which, while effective, complicate sample preparation. Stable isotope labeling by amino acids in cell culture (SILAC) achieves high labeling efficiency through the metabolic incorporation of heavy labels into proteins in vivo. However, the need for metabolic incorporation limits the direct use in clinical scenarios and certain high-throughput experiments. Spike-in SILAC (SiS) methods use an externally generated heavy sample as an internal reference, enabling SILAC-based quantification even for samples that cannot be directly labeled. Here, we combine DIA-SiS, leveraging the robust quantification of SILAC without the complexities associated with chemical labeling. We developed DIA-SiS and rigorously assessed its performance with mixed-species benchmark samples on bulk and single cell-like amount level. We demonstrate that DIA-SiS substantially improves proteome coverage and quantification compared to label-free approaches and reduces incorrectly quantified proteins. Additionally, DIA-SiS proves effective in analyzing proteins in low-input formalin-fixed paraffin-embedded tissue sections. DIA-SiS combines the precision of stable isotope-based quantification with the simplicity of label-free sample preparation, facilitating simple, accurate, and comprehensive proteome profiling.

Methods to Investigate the Secretome of Senescent Cells

The word "secretome" was first used to describe the proteins that cells secrete under different circumstances; however, recent studies have proven the existence of other molecules such as RNA and chemical compounds in the secretome. The study of secretome has significance for the diagnosis and treatment of disease as it provides insight into cellular functions, including immune responses, development, and homeostasis. By halting cell division, cellular senescence plays a role in both cancer defense and aging by secreting substances known as senescence-associated secretory phenotypes (SASP). A variety of techniques could be used to analyze the secretome: protein-based approaches like mass spectrometry and protein microarrays, nucleic acid-based methods like RNA sequencing, microarrays, and in silico prediction. Each method offers unique advantages and limitations in characterizing secreted molecules. Top-down and bottom-up strategies for thorough secretome analysis are became possible by mass spectrometry. Understanding cellular function, disease causes, and proper treatment targets is aided by these methodologies. Their approaches, benefits, and drawbacks will all be discussed in this review.

Mass spectrometry for the study of adipocyte cell secretome in cardiovascular diseases

Adipose tissue is classically considered the primary site of lipid storage, but in recent years has garnered appreciation for its broad role as an endocrine organ, capable of remotely signaling to other tissues to alter their metabolic program. The adipose tissue is now recognized as a crucial regulator of cardiovascular health, mediated by the secretion of several bioactive products, with a wide range of endocrine and paracrine effects on the cardiovascular system. Thanks to the development and improvement of high-throughput mass spectrometry, the size and components of the human secretome have been characterized. In this review, we summarized the recent advances in mass spectrometry-based studies of the cell and tissue secretome for the understanding of adipose tissue biology, which may help to decipher the complex molecular mechanisms controlling the crosstalk between the adipose tissue and the cardiovascular system, and their possible clinical translation.

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

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

Secretome Analysis: Reading Cellular Sign Language to Understand Intercellular Communication

A significant portion of mammalian proteomes is secreted to the extracellular space to fulfill crucial roles in cell-to-cell communication. To best recapitulate the intricate and multi-faceted crosstalk between cells in a live organism, there is an ever-increasing need for methods to study protein secretion in model systems that include multiple cell types. In addition, posttranslational modifications further expand the complexity and versatility of cellular communication. This review aims to summarize recent strategies and model systems that employ cellular coculture, chemical biology tools, protein enrichment, and proteomic methods to characterize the composition and function of cellular secretomes. This is all geared towards gaining better understanding of organismal biology in vivo mediated by secretory signaling.

Glycan/Protein-Stable Isotope Labeling in Cell Culture for Enabling Concurrent Quantitative Glycomics/Proteomics/Glycoproteomics

The complexity and heterogeneity of protein glycosylation present an analytical challenge to the studies of characterization and quantitation. Various LC-MS-based quantitation strategies have emerged in recent decades. Metabolic stable isotope labeling has been developed to enhance the accurate LC/MS-based quantitation between different cell lines. Stable isotope labeling by amino acids in a cell culture (SILAC) is the most widely used metabolic labeling method in proteomic analysis. However, it can only label the peptide backbone and is thus limited in glycomic studies. Here, we present a metabolic isotope labeling strategy, named GlyProSILC (Glycan Protein Stable Isotope Labeling in Cell Culture), that can label both the glycan motif and peptide backbone from the same batch of cells. It was performed by feeding cells with a heavy medium containing amide-15N-glutamine, 13C6-arginine (Arg6), and 13C6-15N2-lysine (Lys8). No significant change of cell line metabolism after GlyProSILC labeling was observed based on transcriptomic, glycomic, and proteomic data. The labeling conditions, labeling efficiency, and quantitation accuracy were investigated. After quantitation correction, we simultaneously quantified 62 N-glycans, 574 proteins, and 344 glycopeptides using the same batch of mixed 231BR/231 cell lines. So far, GlyProSILC provides an accurate and effective quantitation approach for glycomics, proteomics, and glycoproteomics in a cell culture system.

An Introduction to Analytical Challenges, Approaches, and Applications in Mass Spectrometry-Based Secretomics

The active release of proteins into the extracellular space and the proteolytic cleavage of cell surface proteins are key processes that coordinate and fine-tune a multitude of physiological functions. The entirety of proteins that fulfill these extracellular tasks are referred to as the secretome and are of special interest for the investigation of biomarkers of disease states and physiological processes related to cell-cell communication. LC-MS-based proteomics approaches are a valuable tool for the comprehensive and unbiased characterization of this important subproteome. This review discusses procedures, opportunities, and limitations of mass spectrometry-based secretomics to better understand and navigate the complex analytical landscape for studying protein secretion in biomedical science.

Proximity-inducing modalities: the past, present, and future

Living systems use proximity to regulate biochemical processes. Inspired by this phenomenon, bifunctional modalities that induce proximity have been developed to redirect cellular processes. An emerging example of this class is molecules that induce ubiquitin-dependent proteasomal degradation of a protein of interest, and their initial development sparked a flurry of discovery for other bifunctional modalities. Recent advances in this area include modalities that can change protein phosphorylation, glycosylation, and acetylation states, modulate gene expression, and recruit components of the immune system. In this review, we highlight bifunctional modalities that perform functions other than degradation and have great potential to revolutionize disease treatment, while also serving as important tools in basic research to explore new aspects of biology.

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.

Methods for quantification of glycopeptides by liquid separation and mass spectrometry

Recent advances in analytical techniques provide the opportunity to quantify even low-abundance glycopeptides derived from complex biological mixtures, allowing for the identification of glycosylation differences between healthy samples and those derived from disease states. Herein, we discuss the sample preparation procedures and the mass spectrometry (MS) strategies that have facilitated glycopeptide quantification, as well as the standards used for glycopeptide quantification. For sample preparation, various glycopeptide enrichment methods are summarized including the columns used for glycopeptide separation in liquid chromatography separation. For MS analysis strategies, MS1 level-based quantification and MS2 level-based quantification are described, either with or without labeling, where we have covered isotope labeling, TMT/iTRAQ labeling, data dependent acquisition, data independent acquisition, multiple reaction monitoring, and parallel reaction monitoring. The strengths and weaknesses of these methods are compared, particularly those associated with the figures of merit that are important for clinical biomarker studies and the pathological and functional studies of glycoproteins in various diseases. Possible future developments for glycopeptide quantification are discussed.

Applying multi-omics toward tumor microbiome research

Rather than a "short-term tenant," the tumor microbiome has been shown to play a vital role as a "permanent resident," affecting carcinogenesis, cancer development, metastasis, and cancer therapies. As the tumor microbiome has great potential to become a target for the early diagnosis and treatment of cancer, recent research on the relevance of the tumor microbiota has attracted a wide range of attention from various scientific fields, resulting in remarkable progress that benefits from the development of interdisciplinary technologies. However, there are still a great variety of challenges in this emerging area, such as the low biomass of intratumoral bacteria and unculturable character of some microbial species. Due to the complexity of tumor microbiome research (e.g., the heterogeneity of tumor microenvironment), new methods with high spatial and temporal resolution are urgently needed. Among these developing methods, multi-omics technologies (combinations of genomics, transcriptomics, proteomics, and metabolomics) are powerful approaches that can facilitate the understanding of the tumor microbiome on different levels of the central dogma. Therefore, multi-omics (especially single-cell omics) will make enormous impacts on the future studies of the interplay between microbes and tumor microenvironment. In this review, we have systematically summarized the advances in multi-omics and their existing and potential applications in tumor microbiome research, thus providing an omics toolbox for investigators to reference in the future.

Simultaneous enrichment and sequential separation of glycopeptides and phosphopeptides with poly-histidine functionalized microspheres

Protein phosphorylation and glycosylation coordinately regulate numerous complex biological processes. However, the main methods to simultaneously enrich them are based on the coordination interactions or Lewis acid-base interactions, which suffer from low coverage of target molecules due to strong intermolecular interactions. Here, we constructed a poly-histidine modified silica (SiO₂@Poly-His) microspheres-based method for the simultaneous enrichment, sequential elution and analysis of phosphopeptides and glycopeptides. The SiO₂@Poly-His microspheres driven by hydrophilic interactions and multiple hydrogen bonding interactions exhibited high selectivity and coverage for simultaneous enrichment of phosphopeptides and glycopeptides from 1,000 molar folds of bovine serum albumin interference. Furthermore, “on-line deglycosylation” strategy allows sequential elution of phosphopeptides and glycopeptides, protecting phosphopeptides from hydrolysis during deglycosylation and improving the coverage of phosphopeptides. The application of our established method to HT29 cell lysates resulted in a total of 1,601 identified glycopeptides and 694 identified phosphopeptides, which were 1.2-fold and 1.5-fold higher than those obtained from the co-elution strategy, respectively. The SiO₂@Poly-His based simultaneous enrichment and sequential separation strategy might have great potential in co-analysis of PTMs-proteomics of biological and clinic samples.

Circulating Biomarkers in the Management of Breast Cancer

Circulating biomarkers have become a promising modality in the management of many cancers. Similarly, in breast cancer, circulatory biomarkers are useful, non-invasive methods in the diagnosis, prognostication, and evaluation of response to treatment. Invasive surgical biopsies can be potentially replaced by “liquid biopsy,” which involves analysing circulatory biomarkers that may reveal features of primary and metastatic disease. Therefore, providing an insight into the cancer biology can be utilised to monitor treatment response, treatment-induced adaptation and tumour and disease progression through non-invasive means. The objective of this review is to provide an overview of the current status of the circulating biomarkers highlighting their promising impact on the management of patients with breast cancer.

Integrative, In Silico and Comparative Analysis of Breast Cancer Secretome Highlights Invasive-Ductal-Carcinoma-Grade Progression Biomarkers

Globally, BC is the most frequently diagnosed cancer in women. The aim of this study was to identify novel secreted biomarkers that may indicate progression to high-grade BC malignancies and therefore predict metastatic potential. A total of 33 studies of breast cancer and 78 of other malignancies were screened via a systematic review for eligibility, yielding 26 datasets, 8 breast cancer secretome datasets, and 18 of other cancers that were included in the comparative secretome analysis. Sequential bioinformatic analysis using online resources enabled the identification of enriched GO_terms, overlapping clusters, and pathway reconstruction. This study identified putative predictors of IDC grade progression and their association with breast cancer patient mortality outcomes, namely, HSPG2, ACTG1, and LAMA5 as biomarkers of in silico pathway prediction, offering a putative approach by which the abovementioned proteins may mediate their effects, enabling disease progression. This study also identified ITGB1, FBN1, and THBS1 as putative pan-cancer detection biomarkers. The present study highlights novel, putative secretome biomarkers that may provide insight into the tumor biology and could inform clinical decision making in the context of IDC management in a non-invasive manner.

Multi-omics & pathway analysis identify potential roles for tumor N-acetyl aspartate accumulation in murine models of castration-resistant prostate cancer

Castration-resistant prostate cancer (CRPC) is incurable and remains a significant worldwide challenge (Oakes and Papa, 2015). Matched untargeted multi-level omic datasets may reveal biological changes driving CRPC, identifying novel biomarkers and/or therapeutic targets. Untargeted RNA sequencing, proteomics, and metabolomics were performed on xenografts derived from three independent sets of hormone naive and matched CRPC human cell line models of local, lymph node, and bone metastasis grown as murine orthografts. Collectively, we tested the feasibility of muti-omics analysis on models of CRPC in revealing pathways of interest for future validation investigation. Untargeted metabolomics revealed NAA and NAAG commonly accumulating in CRPC across three independent models and proteomics showed upregulation of related enzymes, namely N-acetylated alpha-linked acidic dipeptidases (FOLH1/NAALADL2). Based on pathway analysis integrating multiple omic levels, we hypothesize that increased NAA in CRPC may be due to upregulation of NAAG hydrolysis via NAALADLases providing a pool of acetyl Co-A for upregulated sphingolipid metabolism and a pool of glutamate and aspartate for nucleotide synthesis during tumor growth.

Identification of diverse lipid-binding modes in the groove of zinc α2 glycoprotein reveals its functional versatility

ZAG is a multifunctional glycoprotein with a class I MHC-like protein fold and an α1-α2 lipid-binding groove. The intrinsic ZAG ligand is unknown. Our previous studies showed that ZAG binds the dansylated C₁₁ fatty acid, DAUDA, differently to the boron dipyrromethane C₁₆ fatty acid, C₁₆ -BODIPY. Here, the molecular basis for this difference was elucidated. Multi-wavelength analytical ultracentrifugation confirmed that DAUDA and C₁₆ -BODIPY individually bind to ZAG and compete for the same binding site. Molecular docking of lipid-binding in the structurally related Cluster of differentiation 1 proteins predicted nine conserved ligand contact residues in ZAG. Twelve mutants were accordingly created by alanine scanning site directed mutagenesis for characterisation. Mutation of Y12 caused ZAG to misfold. Mutation of K147, R157 and A158 abrogated C₁₆ -BODIPY but not DAUDA binding. L69 and T169 increased the fluorescence emission intensity of C₁₆ -BODIPY but not of DAUDA compared to wild-type ZAG and showed that C₁₆ -BODIPY binds close to T169 and L69. Distance measurements of the crystal structure revealed K147 forms a salt bridge with D83. A range of bioactive bulky lipids including phospholipids and sphingolipids displaced DAUDA from the ZAG binding site but unexpectedly did not displace C₁₆ -BODIPY. We conclude that the ZAG α1-α2 groove contains separate but overlapping sites for DAUDA and C₁₆ -BODIPY and is involved in binding to a bulkier and wider repertoire of lipids than previously reported. This work suggested that the in vivo activity of ZAG may be dictated by its lipid ligand.

Proteomic Interrogation in Cancer Biomarker

Biomarkers factor into the diagnosis and treatment of almost every patient with cancer. The innovation in proteomics follows improvement of mass spectrometry techniques and data processing strategy. Recently, proteomics and typical biological studies have been the answer for clinical applications. The clinical proteomics techniques are now actively adapted to protein identification in large patient cohort, biomarker development for more sensitive and specific screening based on quantitative data. And, it is important for clinical, translational researchers to be acutely aware of the issues surrounding appropriate biomarker development, in order to facilitate entry of clinically useful biomarkers into the clinic. Here, we discuss in detail include the case research for clinical proteomics. Furthermore, we give an overview on the current developments and novel findings in proteomics-based cancer biomarker research.

Quantitative capillary zone electrophoresis-mass spectrometry reveals the N-glycome developmental plan during vertebrate embryogenesis

Glycans are known to be involved in many biological processes, while little is known about the expression of N-glycans during vertebrate development. We now report the first quantitative studies of both the expression of N-linked glycans at six early development stages and the expression of N-glycosylated peptides at two early development stages in Xenopus laevis, the African clawed frog. N-Glycans were labeled with isobaric tandem mass tags, pooled, separated by capillary electrophoresis, and characterized using tandem mass spectrometry. We quantified 110 N-glycan compositions that spanned four orders of magnitude in abundance. Capillary electrophoresis was particularly useful in identifying charged glycans; over 40% of the observed glycan compositions were sialylated. The glycan expression was relatively constant until the gastrula-neurula transition (developmental stage 13), followed by massive reprogramming. An increase in oligomannosidic and a decrease in the paucimannosidic and phosphorylated oligomannosidic glycans were observed at the late tailbud stage (developmental stage 41). Two notable and opposing regulation events were detected for sialylated glycans. LacdiNAc and Lewis antigen features distinguished down-regulated sialylation from up-regulated species. The level of Lewis antigen decreased at later stages, which was validated by Aleuria aurantia lectin (AAL) and Ulex europaeus lectin (UEA-I) blots. We also used HPLC coupled with tandem mass spectrometry to identify 611 N-glycosylation sites on 350 N-glycoproteins at the early stage developmental stage 1 (fertilized egg), and 1682 N-glycosylation sites on 1023 N-glycoproteins at stage 41 (late tailbud stage). Over two thirds of the N-glycoproteins identified in the late tailbud stage are associated with neuron projection morphogenesis, suggesting a vital role of the N-glycome in neuronal development.

Enhancing Comprehensive Analysis of Secreted Glycoproteins from Cultured Cells without Serum Starvation

Glycoproteins secreted by cells play essential roles in the regulation of extracellular activities. Secreted glycoproteins are often reflective of cellular status, and thus glycoproteins from easily accessible bodily fluids can serve as excellent biomarkers for disease detection. Cultured cells have been extensively employed as models in the research fields of biology and biomedicine, and global analysis of glycoproteins secreted from these cells provides insights into cellular activities and glycoprotein functions. However, comprehensive identification and quantification of secreted glycoproteins is a daunting task because of their low abundances compared with the high-abundance serum proteins required for cell growth and proliferation. Several studies employed serum-free media to analyze secreted proteins, but it has been shown that serum starvation, even for a short period of time, can alter protein secretion. To overcome these issues, we developed a method to globally characterize secreted glycoproteins and their N-glycosylation sites from cultured cells by combining selective enrichment of secreted glycoproteins with a boosting approach. The results demonstrated the importance of the boosting sample selection and the boosting-to-sample ratio for improving the coverage of secreted glycoproteins. The method was applied to globally quantify secreted glycoproteins from THP-1 monocytes and macrophages in response to lipopolysaccharides (LPS) and from Hep G2 cells treated with TGF-β without serum starvation. We found differentially secreted glycoproteins in these model systems that showed the cellular response to the immune activation or the epithelial-to-mesenchymal transition. Benefiting from the selective enrichment and the signal enhancement of low-abundance secreted glycoproteins, this method can be extensively applied to study secreted glycoproteins without serum starvation, which will provide a better understanding of protein secretion and cellular activity.

High-throughput proteomics of breast cancer interstitial fluid: identification of tumor subtype-specific serologically relevant biomarkers

Despite significant advancements in breast cancer (BC) research, clinicians lack robust serological protein markers for accurate diagnostics and tumor stratification. Tumor interstitial fluid (TIF) accumulates aberrantly externalized proteins within the local tumor space, which can potentially gain access to the circulatory system. As such, TIF may represent a valuable starting point for identifying relevant tumor-specific serological biomarkers. The aim of the study was to perform comprehensive proteomic profiling of TIF to identify proteins associated with BC tumor status and subtype. A liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of 35 TIFs of three main subtypes: luminal (19), Her2 (4), and triple-negative (TNBC) (12) resulted in the identification of > 8800 proteins. Unsupervised hierarchical clustering segregated the TIF proteome into two major clusters, luminal and TNBC/Her2 subgroups. High-grade tumors enriched with tumor infiltrating lymphocytes (TILs) were also stratified from low-grade tumors. A consensus analysis approach, including differential abundance analysis, selection operator regression, and random forest returned a minimal set of 24 proteins associated with BC subtypes, receptor status, and TIL scoring. Among them, a panel of 10 proteins, AGR3, BCAM, CELSR1, MIEN1, NAT1, PIP4K2B, SEC23B, THTPA, TMEM51, and ULBP2, was found to stratify the tumor subtype-specific TIFs. In particular, upregulation of BCAM and CELSR1 differentiates luminal subtypes, while upregulation of MIEN1 differentiates Her2 subtypes. Immunohistochemistry analysis showed a direct correlation between protein abundance in TIFs and intratumor expression levels for all 10 proteins. Sensitivity and specificity were estimated for this protein panel by using an independent, comprehensive breast tumor proteome dataset. The results of this analysis strongly support our data, with eight of the proteins potentially representing biomarkers for stratification of BC subtypes. Five of the most representative proteomics databases currently available were also used to estimate the potential for these selected proteins to serve as putative serological markers.

A Pragmatic Guide to Enrichment Strategies for Mass Spectrometry-Based Glycoproteomics

Glycosylation is a prevalent, yet heterogeneous modification with a broad range of implications in molecular biology. This heterogeneity precludes enrichment strategies that can be universally beneficial for all glycan classes. Thus, choice of enrichment strategy has profound implications on experimental outcomes. Here we review common enrichment strategies used in modern mass spectrometry-based glycoproteomic experiments, including lectins and other affinity chromatographies, hydrophilic interaction chromatography and its derivatives, porous graphitic carbon, reversible and irreversible chemical coupling strategies, and chemical biology tools that often leverage bioorthogonal handles. Interest in glycoproteomics continues to surge as mass spectrometry instrumentation and software improve, so this review aims to help equip researchers with the necessary information to choose appropriate enrichment strategies that best complement these efforts.

Significant reductions in apoptosis-related proteins (HSPA6, HSPA8, ITGB3, YWHAH, and PRDX6) are involved in immune thrombocytopenia

To investigate differences in the expression of plasma proteins in immune thrombocytopenia (ITP) and normal control groups, bone marrow samples were collected from 20 active ITP patients and 20 healthy controls. Quantitative proteomics analysis based on mass spectrometry was used to measure the protein levels and understand the protein networks. We found differentially expressed proteins in ITP patients and healthy controls. Parallel reaction monitoring (PRM), a targeted proteome quantification technique, was used to quantitatively confirm the identified target proteins and verify the proteomics data. In this study, a total of 829 proteins were identified, and the fold-change cut-off was set at 1.5 (patients vs controls); a total of 26 proteins were upregulated, and 69 proteins were downregulated. The bioinformatics analysis indicated that some differentially expressed proteins were associated with apoptosis. KEGG enrichment analysis showed that the apoptosis-related proteins were closely related to the PI3K-Akt signalling pathway. PRM demonstrated that apoptosis-related proteins were significantly decreased in ITP patients, which further confirmed the important effect of apoptosis on ITP pathogenesis. We hypothesised that apoptosis may be closely related to ITP pathogenesis through the PI3K-Akt signalling pathway.

Shedding of cancer susceptibility candidate 4 by the convertases PC7/furin unravels a novel secretory protein implicated in cancer progression

The proprotein convertases (PCs) are responsible for the maturation of precursor proteins, and are involved in multiple and critical biological processes. Over the past 30 years, the PCs have had great translational applications, but the physiological roles of PC7, the seventh member of the family, are still obscure. Searching for new substrates of PC7, a quantitative proteomics screen for selective enrichment of N-glycosylated polypeptides secreted from hepatic HuH7 cells identified two human type-II transmembrane proteins of unknown function(s): Cancer Susceptibility Candidate 4 (CASC4) and Golgi Phosphoprotein of 130 kDa (GPP130/GOLIM4). Concentrating on CASC4, its mutagenesis characterized the PC7/Furin-shedding site to occur at KR₆₆↓NS, in HEK293 cells. We defined PC7 and Furin trafficking and activity, and demonstrated that CASC4 shedding occurs in acidic endosomes and/or in the trans-Golgi Network. Our data unraveled a cancer-protective role for CASC4, because siRNA silencing of endogenous CASC4 expression in the invasive triple-negative breast cancer human cell line MDA-MB-231 resulted in a significantly increased cellular migration and invasion. Conversely, MDA-MB-231 cells stably expressing CASC4 exhibited reduced migration and invasion, which can be explained by an increased number of paxillin-positive focal adhesions. This phenotypic cancer-protective role of CASC4 is reversed in cells overexpressing an optimally PC7/Furin-cleaved CASC4 mutant, or upon overexpression of the N-terminally convertase-generated membrane-bound segment. This phenotype was associated with increased formation of podosome-like structures, especially evident in cells overexpressing the N-terminal fragment. In accord, breast cancer patients’ data sets show that high CASC4 and PCSK7 expression levels predict a significantly worse prognosis compared to high CASC4 but low PCSK7 levels. In conclusion, CASC4 shedding not only disrupts its anti-migratory/invasive role, but also generates a membrane-bound fragment that drastically modifies the actin cytoskeleton, resulting in an enhanced cellular migration and invasion. This phenotype might be clinically relevant in the prognosis of breast cancer patients.

The ER-associated protease Ste24 prevents N-terminal signal peptide-independent translocation into the endoplasmic reticulum in Saccharomyces cerevisiae

Soluble proteins destined for the secretory pathway contain an N-terminal signal peptide that induces their translocation into the endoplasmic reticulum (ER). The importance of N-terminal signal peptides for ER translocation has been extensively examined over the past few decades. However, in the budding yeast Saccharomyces cerevisiae, a few proteins devoid of a signal peptide are still translocated into the ER and then N-glycosyl-ated. Using signal peptide-truncated reporter proteins, here we report the detection of significant translocation of N-terminal signal peptide-truncated proteins in a yeast mutant strain (ste24Δ) that lacks the endopeptidase Ste24 at the ER membrane. Furthermore, several ER/cytosolic proteins, including Sec61, Sec66, and Sec72, were identified as being involved in the translocation process. On the basis of screening for 20 soluble proteins that may be N-glycosylated in the ER in the ste24Δ strain, we identified the transcription factor Rme1 as a protein that is partially N-glycosylated despite the lack of a signal peptide. These results clearly indicate that some proteins lacking a signal peptide can be translocated into the ER and that Ste24 typically suppresses this process.

Quantitative proteomics analysis reveals important roles of N-glycosylation on ER quality control system for development and pathogenesis in Magnaporthe oryzae

Genetic studies have shown essential functions of N-glycosylation during infection of the plant pathogenic fungi, however, systematic roles of N-glycosylation in fungi is still largely unknown. Biological analysis demonstrated N-glycosylated proteins were widely present at different development stages of Magnaporthe oryzae and especially increased in the appressorium and invasive hyphae. A large-scale quantitative proteomics analysis was then performed to explore the roles of N-glycosylation in M. oryzae. A total of 559 N-glycosites from 355 proteins were identified and quantified at different developmental stages. Functional classification to the N-glycosylated proteins revealed N-glycosylation can coordinate different cellular processes for mycelial growth, conidium formation, and appressorium formation. N-glycosylation can also modify key components in N-glycosylation, O-glycosylation and GPI anchor pathways, indicating intimate crosstalk between these pathways. Interestingly, we found nearly all key components of the endoplasmic reticulum quality control (ERQC) system were highly N-glycosylated in conidium and appressorium. Phenotypic analyses to the gene deletion mutants revealed four ERQC components, Gls1, Gls2, GTB1 and Cnx1, are important for mycelial growth, conidiation, and invasive hyphal growth in host cells. Subsequently, we identified the Gls1 N-glycosite N497 was important for invasive hyphal growth and partially required for conidiation, but didn’t affect colony growth. Mutation of N497 resulted in reduction of Gls1 in protein level, and localization from ER into the vacuole, suggesting N497 is important for protein stability of Gls1. Our study showed a snapshot of the N-glycosylation landscape in plant pathogenic fungi, indicating functions of this modification in cellular processes, developments and pathogenesis.

The fungal pathogen Magnaporthe oryzae can cause rice blast and wheat blast diseases, which threatens worldwide food production. During infection, M. oryzae follows a sequence of distinct developmental stages adapted to survival and invasion of the host environment. M. oryzae attaches onto the host by the conidium, and then develops an appressorium to breach the host cuticle. After penetrating, it forms invasive hyphae to quickly spread in the host cells. Numerous genetic studies have focused on the mechanisms underlying each step in the infection process, but systemic approaches are needed for a broader, integrated understanding of regulatory events during M. oryzae pathogenesis. Many infection-related signaling events are regulated through post-translational protein modifications within the pathogen. N-linked glycosylation, in which a glycan moiety is added to the amide group of an asparagine residue, is an abundant modification known to be essential for M. oryzae infection. In this study, we employed a quantitative proteomics analysis to unravel the overall regulatory mechanisms of N-glycosylation at different developmental stages of M. oryzae. We detected changes in N-glycosylation levels at 559 glycosylated residues (N-glycosites) in 355 proteins during different stages, and determined that the ER quality control system is elaborately regulated by N-glycosylation. The insights gained will help us to better understand the regulatory mechanisms of infection in pathogenic fungi. These findings may be also important for developing novel strategies for fungal disease control.

Multiple protein and mRNA expression correlations in the rat cerebral cortex after ischemic injury and repair due to buchang naoxintong jiaonang (BNJ) intervention

Stroke is the one of the most common causes of death worldwide. Systematic description and characterization of the types of stroke and the effects induced in the cerebral cortex have not been performed so far. Here, we analyzed the protein and mRNA expression in the cerebral cortex12 h after ischemic injury and repair. Drug intervention using Buchang Naoxintong Jiaonang (BNJ), which has been reported to have good clinical therapeutic effects, was selected for our study of cerebral ischemic repair in rat models. Two powerful techniques can be merged in a single study to examine and yield new perspectives in physiology and pathophysiology. Combining LC-MS/MS and DNA microarray analyses of the rat cerebral cortex confidently identified two large datasets in more than three biological replicates. Quantitative approaches were then used to quantify the differences among the four experimental groups the naive, sham, middle cerebral artery occlusion MCAO and MCAO + BNJ groups by a label-free proteomics approach and a Cy5-labeled microarray approach. In brief, 3217 unique proteins and 24,300 unique gene symbols were confidently identified. Bioinformatics analysis revealed that of these unique proteins and gene symbols, 269 proteins and 632 gene symbols were identified to be differentially expressed. The results of subcellular localization, hierarchical clustering, and pathway enrichment analyses were combined with the results of the injury and repair phase analyses, and twelve proteins and twenty-seven gene symbols were significantly differentially expressed and were identified as potential candidates for cerebral ischemic injury involvement; all the candidates were verified by western blot and quantitative real-time PCR analysis. The primary enriched MAPK signaling pathway may play a key role in the molecular mechanisms related to cerebral ischemic injury. The observations of the present study help to illuminate the regulatory mechanism of cerebral ischemic injury and repair due to BNJ intervention.

Crystal structure of zinc-α2-glycoprotein in complex with a fatty acid reveals multiple different modes of protein-lipid binding

Human zinc-α2-glycoprotein (ZAG) is a 42 kDa adipokine which regulates body fat mass and is associated with cachexia and obesity. ZAG belongs to the major histocompatibility complex class I protein family and binds long-chain polyunsaturated fatty acids in its groove formed from the α1 and α2 domains. To identify the molecular basis of its lipid-binding function, we determined the first crystal structure at 2.49 Å resolution for fatty acid-bound ZAG, where the ligand was the fluorescent 11-(dansylamino)undecanoic acid (DAUDA). The 192 kDa crystallographic asymmetric unit contained six ZAG and eight fatty acid molecules in unique conformations. Six fatty acid molecules were localised to the ZAG grooves, where their tails were bound in two distinct conformations. The carboxylate groups of three fatty acids projected out of the groove, while the fourth was hydrogen bonded with R73 inside the groove. Other ligand-residue contacts were primarily hydrophobic. A new fatty acid site was revealed for two further DAUDA molecules at the ZAG α3 domains. Following conformational changes from unbound ZAG, the α3 domains formed tetrameric β-barrel structures lined by fatty acid molecules that doubled the binding capacity of ZAG. Analytical ultracentrifugation revealed that ZAG in solution was a monomer in the absence of DAUDA, but formed small amounts of tetramers with DAUDA. By showing that ZAG binds fatty acids in different locations, we demonstrate an augmented mechanism for fatty acid binding in ZAG that is distinct from other known fatty acid binding proteins, and may be relevant to cachexia.

N-GlycositeAtlas: a database resource for mass spectrometry-based human N-linked glycoprotein and glycosylation site mapping

BACKGROUND

N-linked glycoprotein is a highly interesting class of proteins for clinical and biological research. The large-scale characterization of N-linked glycoproteins accomplished by mass spectrometry-based glycoproteomics has provided valuable insights into the interdependence of glycoprotein structure and protein function. However, these studies focused mainly on the analysis of specific sample type, and lack the integration of glycoproteomic data from different tissues, body fluids or cell types.

METHODS

In this study, we collected the human glycosite-containing peptides identified through their de-glycosylated forms by mass spectrometry from over 100 publications and unpublished datasets generated from our laboratory. A database resource termed N-GlycositeAtlas was created and further used for the distribution analyses of glycoproteins among different human cells, tissues and body fluids. Finally, a web interface of N-GlycositeAtlas was created to maximize the utility and value of the database.

RESULTS

The N-GlycositeAtlas database contains more than 30,000 glycosite-containing peptides (representing > 14,000 N-glycosylation sites) from more than 7200 N-glycoproteins from different biological sources including human-derived tissues, body fluids and cell lines from over 100 studies.

CONCLUSIONS

The entire human N-glycoproteome database as well as 22 sub-databases associated with individual tissues or body fluids can be downloaded from the N-GlycositeAtlas website at http://nglycositeatlas.biomarkercenter.org.

Novel secretome-to-transcriptome integrated or secreto-transcriptomic approach to reveal liquid biopsy biomarkers for predicting individualized prognosis of breast cancer patients

Background

Presently, a 50-gene expression model (PAM50) serves as a breast cancer (BC) subtype classifier that is insufficient to distinguish, within each single PAM50-classified subtype, patient subpopulations having different prognosis. There is a pressing need for inexpensive and minimally invasive biomarker tests to easily and accurately predict individuals’ clinical outcomes and response to treatments. Although quantitative proteomic approaches have been developed to identify/profile proteins secreted (secretome) from various cancer cell lines in vitro, missing are the clinicopathological relevance and the associated prognostic value of these secretomic identifications.

Methods

To discover biomarkers to predict individualized prognosis we introduce a new multi-omics (secreto-transcriptomics) method that identifies, in their oncogenically secreted states, candidate markers of BC subtypes whose genes bear patient-specific mRNA expression alterations of prognostic significance. First, we used label-free quantitative (LFQ) proteomics to identify the proteins showing BC-subtypic secretion from a series of BC cell lines representing major BC-subtypes. To determine and externally validate the prognostic value of these secreted proteins, we developed a secreto-transcriptomic approach that discovered a PAM50-subtypic Secretion-Correlated mRNA Expression Pattern (SeCEP) wherein the PAM50-subtypic secretion of select proteins statistically correlated with cis-mRNA expression of their encoding genes in patients of the corresponding PAM50-subtypes. Kaplan-Meier analysis of SeCEP genes was used to identify new liquid biopsy biomarkers for predicting individualized prognosis.

Results

The mRNA expression-to-secretion correlation (SeCEP) pinpointed multiple genes that are fully translated into the oncogenically active secretome in a PAM50-subtypic manner. Further, multiple SeCEP genes in distinct combinations or panels of multiple SeCEP genes were identified as ‘systems prognostic markers’ that showed mRNA co-overexpression patterns in the distinct subpopulations of PAM50-subtypic patients with poor prognosis or high-risk of relapse. Thus, our secreto-transcriptomic approach statistically linked BC subtypic secretome genes with patient-specific information about their mRNA expression alterations and significantly improved the sensitivity and specificity in patient stratification in the context of clinical outcomes or prognosis.

Conclusions

By combining LFQ secretome screening with proteo-transcriptomic retrospective analysis of patient data our integrated multi-omics approach bypasses costly, tedious, genome-wide fishing and predictive modeling that are commonly required to distinguish a few prognostically altered genes from thousands of other non-BC related genes in a genome.

Electronic supplementary material

The online version of this article (10.1186/s12920-019-0530-7) contains supplementary material, which is available to authorized users.

Mapping human N-linked glycoproteins and glycosylation sites using mass spectrometry

N-linked glycoprotein is a highly interesting class of proteins for clinical and biological research. Over the last decade, large-scale profiling of N-linked glycoproteins and glycosylation sites from biological and clinical samples has been achieved through mass spectrometry-based glycoproteomic approaches. In this paper, we reviewed the human glycoproteomic profiles that have been reported in more than 80 individual studies, and mainly focused on the N-glycoproteins and glycosylation sites identified through their deglycosylated forms of glycosite-containing peptides. According to our analyses, more than 30,000 glycosite-containing peptides and 7,000 human glycoproteins have been identified from five different body fluids, twelve human tissues (or related cell lines), and four special cell types. As the glycoproteomic data is still missing for many organs and tissues, a systematical glycoproteomic analysis of various human tissues and body fluids using a uniform platform is still needed for an integrated map of human N-glycoproteomes.

An integrated strategy for high-sensitive and multi-level glycoproteome analysis from low micrograms of protein samples

Glycosylation, as a biologically important protein post-translational modification, often alters on both glycosites and glycans, simultaneously. However, most of current approaches focused on biased profiling of either glycosites or glycans, and limited by time-consuming process and milligrams of starting protein material. We describe here a simple and integrated spintip-based glycoproteomics technology (termed Glyco-SISPROT) for achieving a comprehensive view of glycoproteome with shorter sample processing time and low microgram starting material. By carefully integrating and optimizing SCX, C18 and Concanavalin A (Con A) packing material and their combination in spintip format, both predigested peptides and protein lysates could be processed by Glyco-SISPROT with high efficiency. More importantly, deglycopeptide, intact glycopeptide and glycans released by multiple glycosidases could be readily collected from the same Glyco-SISPROT workflow for LC-MS analysis. In total, above 1850 glycosites in ˜1770 unique deglycopeptides were characterized from mouse liver by using either 100 μg of predigested peptides or directly using 100 μg of protein lysates, in which about 30% of glycosites were released by both PNGase F and Endos. To the best of our knowledge, this approach should be one of the most comprehensive glycoproteomic approaches by using limited protein starting material. One significant benefit of Glyco-SISPROT is that whole processing time is dramatically reduced from a few days to less than 6 h with good reproducibility when protein lysates were directly processed by Glyco-SISPROT. We expect that this method will be suitable for multi-level glycoproteome analysis of rare biological samples with high sensitivity.

Identification of Rabbit Oviductal Fluid Proteins Involved in Pre-Fertilization Processes by Quantitative Proteomics

Oviductal fluid (ODF) proteins modulate and support reproductive processes in the oviduct. In the present study, proteins involved in the biological events that precede fertilization have been identified in the rabbit ODF proteome, isolated from the ampulla and isthmus of the oviduct at different time points within 8 h after intrauterine insemination. A workflow is used that integrates lectin affinity capture with stable-isotope dimethyl labeling prior to nanoLC-MS/MS analysis. In total, over 400 ODF proteins, including 214 lectin enriched glycoproteins, are identified and quantified. Selected data are validated by Western blot analysis. Spatiotemporal alterations in the abundance of ODF proteins in response to insemination are detected by global analysis. A subset of 63 potentially biologically relevant ODF proteins is identified, including extracellular matrix components, chaperones, oxidoreductases, and immunity proteins. Functional enrichment analysis reveals an altered peptidase regulator activity upon insemination. In addition to protein identification and abundance changes, N-glycopeptide analysis further identifies 281 glycosites on 199 proteins. Taken together, these results show, for the first time, the evolving oviductal milieu early upon insemination. The identified proteins are likely those that modulate in vitro processes, including spermatozoa function.

Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) for Quantitative Proteomics

Stable isotope labeling by amino acids in cell culture (SILAC) is a powerful approach for high-throughput quantitative proteomics. SILAC allows highly accurate protein quantitation through metabolic encoding of whole cell proteomes using stable isotope labeled amino acids. Since its introduction in 2002, SILAC has become increasingly popular. In this chapter we review the methodology and application of SILAC, with an emphasis on three research areas: dynamics of posttranslational modifications, protein-protein interactions, and protein turnover.

Analytical techniques for characterization of biological molecules - proteins and aptamers/oligonucleotides

With the advent of the high-throughput technologies and exciting times for biology, the discipline of analytical methodology is experiencing a surge in the growth and the scope. Over the years, multitude of analytical techniques have evolved from a work-intensive, low sensitivity and high volume of reagent and sample consumption endeavor to automated, better selectivity, lower limit of quantification and cost-effective techniques for biological research. In this review, we give an overview of the currently available wide range of cell-based and noncell based and structural based analytical techniques, their principle and biological applications. The analytical techniques discussed in this paper includes surface plasmon resonance, electrophoresis, enzyme linked immunosorbent assay, Western blotting, flow cytometry, fluorescence activated cell sorting, mass spectrometry, nuclear magnetic resonance and x-ray crystallography.

SILAC-based quantitative proteomic analysis of the livers of spontaneous obese and diabetic rhesus monkeys

Type 2 diabetes mellitus (T2DM) is a severe metabolic disorder that affects more than 10% of the population worldwide. Obesity is a major cause of insulin resistance and contributes to the development of T2DM. Liver is an essential metabolic organ that plays crucial roles in the pathogenesis of obesity and diabetes. However, the underlying mechanisms of liver in the transition of obesity to diabetes are not fully understood. The nonhuman primate rhesus monkey is an appropriate animal for research of human diseases. Here, we first screened and selected three individuals of spontaneously diabetic rhesus monkeys. Interestingly, the diabetic monkeys were obese with a high body mass index at the beginning, but gradually lost their body weight during one year of observation. Furthermore, we performed stable isotope labeling with amino acids in cell culture-based quantitative proteomics to identify proteins and signaling pathways with altered expression in the liver of obese and diabetic monkeys. In total, 3,509 proteins were identified and quantified, of which 185 proteins displayed an altered expression level. Gene ontology analysis revealed that the expression of proteins involved in fatty acids β-oxidation and galactose metabolism was increased in obese monkeys; while proteins involved in oxidative phosphorylation and branched chain amino acid (BCAA) degradation were upregulated in diabetic monkeys. In addition, we observed mild apoptosis in the liver of diabetic monkeys, suggesting liver injury at the late onset of diabetes. Taken together, our liver proteomics may reveal a distinct metabolic transition from fatty acids β-oxidation in obese monkey to BCAA degradation in diabetic monkeys.

Defining tissue proteomes by systematic literature review

Defining protein composition is a key step in understanding the function of both healthy and diseased biological systems. There is currently little consensus between existing published proteomes in tissues such as the aorta, cartilage and organs such as skin. Lack of agreement as to both the number and identity of proteins may be due to issues in protein extraction, sensitivity/specificity of detection and the use of disparate tissue/cell sources. Here, we developed a method combining bioinformatics and systematic review to screen >32M articles from the Web of Science for evidence of proteins in healthy human skin. The resulting Manchester Proteome (www.manchesterproteome.manchester.ac.uk) collates existing evidence which characterises 2,948 skin proteins, 437 unique to our database and 2011 evidenced by both mass spectrometry and immune-based techniques. This approach circumvents the limitations of individual proteomics studies and can be applied to other species, organs, cells or disease-states. Accurate tissue proteomes will aid development of engineered constructs and offer insight into disease treatments by highlighting differences in proteomic composition.

In-depth analysis of secretome and N-glycosecretome of human hepatocellular carcinoma metastatic cell lines shed light on metastasis correlated proteins

Cancer cell metastasis is a major cause of cancer fatality. But the underlying molecular mechanisms remain incompletely understood, which results in the lack of efficient diagnosis, therapy and prevention approaches. Here, we report a systematic study on the secretory proteins (secretome) and secretory N-glycoproteins (N-glycosecretome) of four human hepatocellular carcinoma (HCC) cell lines with different metastatic potential, to explore the molecular mechanism of metastasis and supply the clues for effective measurement of diagnosis and therapy. Totally, 6242 unique gene products (GPs) and 1637 unique N-glycosites from 635 GPs were confidently identified. About 4000 GPs on average were quantified in each of the cell lines, 1156 of which show differential expression (p<0.05). Ninety-nine percentage of the significantly altered proteins were secretory proteins and proteins correlated to cell movement were significantly activated with the increasing of metastatic potential of the cell lines. Twenty-three GPs increased both in the secretome and the N-glycosecretome were chosen as candidates and verified by western blot analysis, and 10 of them were chosen for immunohistochemistry (IHC) analysis. The cumulative survival rates of the patients with candidate (FAT1, DKK3) suggested that these proteins might be used as biomarkers for HCC diagnosis. In addition, a comparative analysis with the published core human plasma database (1754 GPs) revealed that there were 182 proteins not presented in the human plasma database but identified by our studies, some of which were selected and verified successfully by western blotting in human plasma.

In-Depth Proteomic Analysis of the Hippocampus in a Rat Model after Cerebral Ischaemic Injury and Repair by Danhong Injection (DHI)

Stroke is the second most common cause of death worldwide. A systematic description and characterization of the strokes and the effects induced in the hippocampus have not been performed so far. Here, we analysed the protein expression in the hippocampus 24 h after cerebral ischaemic injury and repair. Drug intervention using Danhong injection (DHI), which has been reported to have good therapeutic effects in a clinical setting, was selected for our study of cerebral ischaemia repair in rat models. A larger proteome dataset and total 4091 unique proteins were confidently identified in three biological replicates by combining tissue extraction for rat hippocampus and LC-MS/MS analysis. A label-free approach was then used to quantify the differences among the four experimental groups (Naive, Sham, middle cerebral artery occlusion (MCAO) and MCAO + DHI groups) and showed that about 2500 proteins on average were quantified in each of the experiment group. Bioinformatics analysis revealed that in total 280 unique proteins identified above were differentially expressed (P < 0.05). By combining the subcellular localization, hierarchical clustering and pathway information with the results from injury and repair phase, 12 significant expressed proteins were chosen and verified with respect to their potential as candidates for cerebral ischaemic injury by Western blot. The primary three signalling pathways of the candidates related may be involved in molecular mechanisms related to cerebral ischaemic injury. In addition, a glycogen synthase kinase-3β (Gsk-3β) inhibitor of the candidates with the best corresponding expression trends between western blotting (WB) and label-free quantitative results were chosen for further validation. The results of Western blot analysis of protein expression and 2,3,5- chloride three phenyl tetrazole (TTC) staining of rat brains showed that DHI treatment and Gsk-3β inhibitor are both able to confer protection against ischaemic injury in rat MCAO model. The observations of the present study provide a novel understanding regarding the regulatory mechanism of cerebral ischaemic injury.

Mass spectrometry as a tool for biomarkers searching in gynecological oncology

Tumors of the female reproductive tract are an important target for the development of diagnostic, prognostic and therapeutic strategies. Recent research has turned to proteomics based on mass spectrometry techniques, to achieve more effective diagnostic results. Mass spectrometry (MS) enables identification and quantification of multiple molecules simultaneously in a single experiment according to mass to charge ratio (m/z). Several proteomic strategies may be applied to establish the function of a particular protein/peptide or to identify a novel disease and specific biomarkers related to it. Therefore, MS could facilitate treatment in patients with tumors by helping researchers discover new biomarkers and narrowly targeted drugs. This review presents a comprehensive discussion of mass spectrometry as a tool for biomarkers searching that may lead to the discovery of easily available diagnostic tests in gynecological oncology with emphasis on clinical proteomics over the past decade. The article provides an insight into different MS based proteomic approaches.

An engineered high affinity Fbs1 carbohydrate binding protein for selective capture of N-glycans and N-glycopeptides

A method for selective and comprehensive enrichment of N-linked glycopeptides was developed to facilitate detection of micro-heterogeneity of N-glycosylation. The method takes advantage of the inherent properties of Fbs1, which functions within the ubiquitin-mediated degradation system to recognize the common core pentasaccharide motif (Man3GlcNAc2) of N-linked glycoproteins. We show that Fbs1 is able to bind diverse types of N-linked glycomolecules; however, wild-type Fbs1 preferentially binds high-mannose-containing glycans. We identified Fbs1 variants through mutagenesis and plasmid display selection, which possess higher affinity and improved recovery of complex N-glycomolecules. In particular, we demonstrate that the Fbs1 GYR variant may be employed for substantially unbiased enrichment of N-linked glycopeptides from human serum. Most importantly, this highly efficient N-glycopeptide enrichment method enables the simultaneous determination of N-glycan composition and N-glycosites with a deeper coverage (compared to lectin enrichment) and improves large-scale N-glycoproteomics studies due to greatly reduced sample complexity.

Protein glycosylation is an essential post-translational modification which analysis is complicated by the diversity of glycan composition and heterogeneity at individual attachment sites. Here the authors describe a method to selectively enrich N-linked glycopeptides to facilitate the detection of micro-heterogeneity in N-glycosylation.

Glycoproteins in Claudin-Low Breast Cancer Cell Lines Have a Unique Expression Profile

Claudin proteins are components of epithelial tight junctions; a subtype of breast cancer has been defined by the reduced expression of mRNA for claudins and other genes. Here, we characterize the expression of glycoproteins in breast cell lines for the claudin-low subtype using liquid chromatography/tandem mass spectrometry. Unsupervised clustering techniques reveal a group of claudin-low cell lines that is distinct from nonmalignant, basal, and luminal lines. The claudin-low cell lines express F11R, EPCAM, and other proteins at very low levels, whereas CD44 is expressed at a high level. Comparison of mRNA expression to glycoprotein expression shows modest correlation; the best agreement occurs when the mRNA expression level is lowest and little or no protein is detected. These findings from cell lines are compared to those for tumor samples by the Clinical Proteomic Tumor Analysis Consortium (CPTAC). The CPTAC samples contain a group low in CLDN3. The samples low in CLDN3 proteins share many differentially expressed glycoproteins with the claudin-low cell lines. In contrast to the situation for cell lines or patient samples classified as claudin-low by RNA expression, however, most of the tumor samples low in CLDN3 protein express the estrogen receptor or HER2. These tumor samples express CD44 protein at low rather than high levels. There is no correlation between CLDN3 gene expression and protein expression in these CPTAC samples; hence, the claudin-low subtype defined by gene expression is not the same group of tumors as that defined by low expression of CLDN3 protein.

Quantitative Proteomics Using SILAC

The ability to enumerate all of the proteins in a cell is quickly becoming a reality. Quantitative proteomics adds an extra dimension to proteome-wide discovery experiments by enabling differential measurements of protein concentrations, characterization of protein turnover, increased stringency of co-immunoprecipitation reactions, as well as many other intriguing applications. One of the most widely used techniques that enable relative protein quantitation is stable isotope labeling by amino acids in cell culture (SILAC) (Ong et al., Mol Cell Proteomics 1(5):376-386, 2002). Over the past decade, SILAC has become the preferred approach for proteome-wide quantitation by mass spectrometry. This approach relies on the metabolic incorporation of isotopically enriched amino acids into the proteome of cells-the proteome of "light" (¹H, ¹²C, ¹⁴N) cells can then be compared to "heavy" (²H, ¹³C, ¹⁵N) cells as the isotopically labeled proteins and peptides are easily distinguished in a mass spectrometer. Since cellular uptake and response to isotopically different amino acid(s) is naïve, it is without impact on cell physiology. We provide a detailed step-by-step procedure for performing SILAC-based experiment for proteome-wide quantitation in this chapter.

Global Analysis of Secreted Proteins and Glycoproteins in Saccharomyces cerevisiae

Protein secretion is essential for numerous cellular activities, and secreted proteins in bodily fluids are a promising and noninvasive source of biomarkers for disease detection. Systematic analysis of secreted proteins and glycoproteins will provide insight into protein function and cellular activities. Yeast (Saccharomyces cerevisiae) is an excellent model system for eukaryotic cells, but global analysis of secreted proteins and glycoproteins in yeast is challenging due to the low abundances of secreted proteins and contamination from high-abundance intracellular proteins. Here, by using mild separation of secreted proteins from cells, we comprehensively identified and quantified secreted proteins and glycoproteins through inhibition of glycosylation and mass spectrometry-based proteomics. In biological triplicate experiments, 245 secreted proteins were identified, and comparison with previous experimental and computational results demonstrated that many identified proteins were located in the extracellular space. Most quantified secreted proteins were down-regulated from cells treated with an N-glycosylation inhibitor (tunicamycin). The quantitative results strongly suggest that the secretion of these down-regulated proteins was regulated by glycosylation, while the secretion of proteins with minimal abundance changes was contrarily irrelevant to protein glycosylation, likely being secreted through nonclassical pathways. Glycoproteins in the yeast secretome were globally analyzed for the first time. A total of 27 proteins were quantified in at least two protein and glycosylation triplicate experiments, and all except one were down-regulated under N-glycosylation inhibition, which is solid experimental evidence to further demonstrate that the secretion of these proteins is regulated by their glycosylation. These results provide valuable insight into protein secretion, which will further advance protein secretion and disease studies.

Combining Click Chemistry-Based Proteomics With Dox-Inducible Gene Expression

Inactivating mutations in single genes can trigger, prevent, promote, or alleviate diseases. Identifying such disease-related genes is a main pillar of medical research. Since proteins play a crucial role in mediating these effects, their impact on the diseased cells' proteome including posttranslational modifications has to be elucidated for a detailed understanding of the role of these genes in the disease process. In complex disorders, like cancer, several genes contribute to the disease process, thereby hampering the assignment of a proteomic change to the corresponding causative gene. To enable comprehensive screening for the impact of inactivation of a gene, e.g., loss of a tumor suppressor in cancer, on the cellular proteome, we present a strategy based on combination of three technologies that is recombinase-mediated cassette exchange, click chemistry, and mass spectrometry. The methodology is exemplified by the analysis of the proteomic changes induced by the loss of a tumor suppressor gene in colorectal cancer cells. To demonstrate the applicability to screen for posttranslational modification changes, we also describe the analysis of protein glycosylation changes caused by the tumor suppressor inactivation. In principle, this strategy can be applied to analyze the effects of any gene of interest on protein expression as well as posttranslational modification by glycosylation. Moreover adaptation of the strategy to an appropriate cell culture model has the potential for application on a broad range of diseases where the disease-promoting mutations have been identified.

Integrated and Quantitative Proteomics of Human Tumors

Quantitative proteomics represents a powerful approach for the comprehensive analysis of proteins expressed under defined conditions. These properties have been used to investigate the proteome of disease states, including cancer. It has become a major subject of studies to apply proteomics for biomarker and therapeutic target identification. In the last decades, technical advances in mass spectrometry have increased the capacity of protein identification and quantification. Moreover, the analysis of posttranslational modification (PTM), especially phosphorylation, has allowed large-scale identification of biological mechanisms. Even so, increasing evidence indicates that global protein quantification is often insufficient for the explanation of biology and has shown to pose challenges in identifying new and robust biomarkers. As a consequence, to improve the accuracy of the discoveries made using proteomics in human tumors, it is necessary to combine (i) robust and reproducible methods for sample preparation allowing statistical comparison, (ii) PTM analyses in addition to global proteomics for additional levels of knowledge, and (iii) use of bioinformatics for decrypting protein list. Herein, we present technical specificities for samples preparation involving isobaric tag labeling, TiO₂-based phosphopeptides enrichment and hydrazyde-based glycopeptides purification as well as the key points for the quantitative analysis and interpretation of the protein lists. The method is based on our experience with tumors analysis derived from hepatocellular carcinoma, chondrosarcoma, human embryonic intervertebral disk, and chordoma experiments.

Mass Spectrometry-Based Approaches to Understand the Molecular Basis of Memory

The central nervous system is responsible for an array of cognitive functions such as memory, learning, language, and attention. These processes tend to take place in distinct brain regions; yet, they need to be integrated to give rise to adaptive or meaningful behavior. Since cognitive processes result from underlying cellular and molecular changes, genomics and transcriptomics assays have been applied to human and animal models to understand such events. Nevertheless, genes and RNAs are not the end products of most biological functions. In order to gain further insights toward the understanding of brain processes, the field of proteomics has been of increasing importance in the past years. Advancements in liquid chromatography-tandem mass spectrometry (LC-MS/MS) have enabled the identification and quantification of thousands of proteins with high accuracy and sensitivity, fostering a revolution in the neurosciences. Herein, we review the molecular bases of explicit memory in the hippocampus. We outline the principles of mass spectrometry (MS)-based proteomics, highlighting the use of this analytical tool to study memory formation. In addition, we discuss MS-based targeted approaches as the future of protein analysis.