Integrative Proteomic Characterization of Human Lung Adenocarcinoma.

Genomic studies of lung adenocarcinoma (LUAD) have advanced our understanding of the disease's biology and accelerated targeted therapy. However, the proteomic characteristics of LUAD remain poorly understood. We carried out a comprehensive proteomics analysis of 103 cases of LUAD in Chinese patients. Integrative analysis of proteome, phosphoproteome, transcriptome, and whole-exome sequencing data revealed cancer-associated characteristics, such as tumor-associated protein variants, distinct proteomics features, and clinical outcomes in patients at an early stage or with EGFR and TP53 mutations. Proteome-based stratification of LUAD revealed three subtypes (S-I, S-II, and S-III) related to different clinical and molecular features. Further, we nominated potential drug targets and validated the plasma protein level of HSP 90ß as a potential prognostic biomarker for LUAD in an independent cohort. Our integrative proteomics analysis enables a more comprehensive understanding of the molecular landscape of LUAD and offers an opportunity for more precise diagnosis and treatment.

Proteomics identifies new therapeutic targets of early-stage hepatocellular carcinoma.

Hepatocellular carcinoma is the third leading cause of deaths from cancer worldwide. Infection with the hepatitis B virus is one of the leading risk factors for developing hepatocellular carcinoma, particularly in East Asia1. Although surgical treatment may be effective in the early stages, the five-year overall rate of survival after developing this cancer is only 50-70%2. Here, using proteomic and phospho-proteomic profiling, we characterize 110 paired tumour and non-tumour tissues of clinical early-stage hepatocellular carcinoma related to hepatitis B virus infection. Our quantitative proteomic data highlight heterogeneity in early-stage hepatocellular carcinoma: we used this to stratify the cohort into the subtypes S-I, S-II and S-III, each of which has a different clinical outcome. S-III, which is characterized by disrupted cholesterol homeostasis, is associated with the lowest overall rate of survival and the greatest risk of a poor prognosis after first-line surgery. The knockdown of sterol O-acyltransferase 1 (SOAT1)-high expression of which is a signature specific to the S-III subtype-alters the distribution of cellular cholesterol, and effectively suppresses the proliferation and migration of hepatocellular carcinoma. Finally, on the basis of a patient-derived tumour xenograft mouse model of hepatocellular carcinoma, we found that treatment with avasimibe, an inhibitor of SOAT1, markedly reduced the size of tumours that had high levels of SOAT1 expression. The proteomic stratification of early-stage hepatocellular carcinoma presented in this study provides insight into the tumour biology of this cancer, and suggests opportunities for personalized therapies that target it.

Regulation of the Hippo-YAP Pathway by Glucose Sensor O-GlcNAcylation.

The Hippo pathway is crucial in organ size control and tissue homeostasis, with deregulation leading to cancer. An extracellular nutrition signal, such as glucose, regulates the Hippo pathway activation. However, the mechanisms are still not clear. Here, we found that the Hippo pathway is directly regulated by the hexosamine biosynthesis pathway (HBP) in response to metabolic nutrients. Mechanistically, the core component of Hippo pathway (YAP) is O-GlcNAcylated by O-GlcNAc transferase (OGT) at serine 109. YAP O-GlcNAcylation disrupts its interaction with upstream kinase LATS1, prevents its phosphorylation, and activates its transcriptional activity. And this activation is not dependent on AMPK. We also identified OGT as a YAP-regulated gene that forms a feedback loop. Finally, we confirmed that glucose-induced YAP O-GlcNAcylation and activation promoted tumorigenesis. Together, our data establish a molecular mechanism and functional significance of the HBP in directly linking extracellular glucose signal to the Hippo-YAP pathway and tumorigenesis.

Incidence and risk factors of stress urinary incontinence after laparoscopic hysterectomy.

OBJECTIVE: To observe the long-term effects of total hysterectomy on urinary function, evaluate the effects of preoperative nutritional status, urinary occult infection, and surgical factors on the induction of postoperative stress urinary incontinence (SUI), and explore the incidence and risk factors of SUI. STUDY DESIGN: From January 2017 to December 2017, 164 patients with benign non-prolapsing diseases who underwent a laparoscopic total hysterectomy in the First People's Hospital of Taicang were selected as the analysis objects. The International Incontinence Standard Questionnaire for Female Lower Urinary Tract Symptoms (ICIQ-FLUTS) and Pelvic Floor Impact Questionnaire-short version 20 (PFDI-20) were used for telephone follow-up to subjectively assess the urinary function of patients, collect their medical records, and statistically analyze the number of postoperative SUI cases. Logistic multivariate analysis was used to analyze the influencing factors of postoperative female SUI, presented as adjusted odds ratios with 95% confidence intervals. RESULTS: Only 97 out of 164 patients completed the ICIQ-FLUTS and PFDI-20 questionnaires. Among these participants, 28 patients (28.86%) were diagnosed with SUI (study group), while 69 patients (71.13%) were classified as women without SUI (control group). The age, menopause, parity ≥ 2 times, Body mass index (BMI) ≥ 28 kg/m2, neonatal weight ≥ 4000 g, history of chronic cough, preoperative hemoglobin ≤ 100 g/L, preoperative urine bacteria ≥ 100u/L, preoperative uterine volume ≥ 90 cm3, intraoperative blood loss, and operation time of the study group were compared with those of the control group. The differences were statistically significant (P < 0.05). Further Logistic multivariate analysis showed that menopause, preoperative hemoglobin ≤ 100 g/L, preoperative urine bacteria ≥ 100u/L, uterine volume ≥ 90 cm3, history of chronic cough, BMI ≥ 28 kg/m2 were risk factors for postoperative SUI in patients undergoing hysterectomy (P < 0.05). CONCLUSIONS: Hysterectomy for benign non-prolapse diseases has a long-term potential impact on the urinary system of patients, and the risk of postoperative SUI increases. The main risk factors of SUI are parity, menopausal status, obesity, preoperative nutritional status, and occult infection of the urinary system.

The CDK4/6 Inhibitor Palbociclib Induces Cell Senescence of High-grade Serous Ovarian Cancer Through Acetylation of p53.

Cell senescence is an anti-cancer strategy following DNA repair and apoptosis, which is associated with the initiation, progression, and treatment of ovarian cancer. The CDK4/6 inhibitor alters cell cycle and induces cell senescence dependent on retinoblastoma (RB) family proteins. Objective Herein, we aimed to explore the effects of Palbociclib (a CDK4/6 inhibitor) on cellular senescence of high-grade serous ovarian cancer (HGSOC). Cell viability and cell cycle were evaluated by cell counting kit-8 and flow cytometry. Cell senescence was analyzed using the SA-ß-gal staining assay. The senescence-associated secretory phenotype was assessed using quantitative PCR (qPCR). Senescence-related markers were tested using western blot. The role of Palbociclib in vivo was clarified using xenograft tumor. Acetylation of p53 was evaluated by qPCR and western blot. The results showed that Palbociclib inhibited cell viability, blocked cell cycle at G0/G1 phase, and induced cell senescence. A rescue study indicated that knockdown of p53 reversed the effects on cell cycle and senescence induced by Palbociclib. Moreover, we found that Palbociclib promotes P300-mediated p53 acetylation, thus increasing p53 stability and transcription activity. Moreover, Palbociclib suppressed tumor growth in vivo with increased p53 and acetylated p53 levels. In conclusion, Palbociclib induced cell senescence of HGSOC through P300-mediated p53 acetylation, suggesting that Palbociclib may have the effect of treating HGSOC.

Absolute Quantification of Dynamic Cellular Uptake of Small Extracellular Vesicles via Lanthanide Element Labeling and ICP-MS.

Small extracellular vesicles (sEVs) are increasingly reported to play important roles in numerous physiological and pathological processes. Cellular uptake of sEVs is of great significance for functional regulation in recipient cells. Although various sEV quantification, labeling, and tracking methods have been reported, it is still highly challenging to quantify the absolute amount of cellular uptake of sEVs and correlate this information with phenotypic variations in the recipient cell. Therefore, we developed a novel strategy using lanthanide element labeling and inductively coupled plasma-mass spectrometry (ICP-MS) for the absolute and sensitive quantification of sEVs. This strategy utilizes the chelation interaction between Eu3+ and the phosphate groups on the sEV membrane for specific labeling. sEVs internalized by cells can then be quantified by ICP-MS using a previously established linear relationship between the europium content and the particle numbers. High Eu labeling efficiency and stability were demonstrated by various evaluations, and no structural or functional alterations in the sEVs were discovered after Eu labeling. Application of this method revealed that 4020 ± 171 sEV particles/cell were internalized by HeLa cells at 37 °C and 61% uptake inhibition at 4 °C. Further investigation led to the quantitative differential analysis of sEV cellular uptake under the treatment of several chemical endocytosis inhibitors. A 23% strong inhibition indicated that HeLa cells uptake sEVs mainly through the macropinocytosis pathway. This facile labeling and absolute quantification strategy of sEVs with ppb-level high sensitivity is expected to become a potential tool for studying the functions of sEVs in intracellular communication and cargo transportation.

Noninvasive urinary protein signatures combined clinical information associated with microvascular invasion risk in HCC patients.

BACKGROUND: Microvascular invasion (MVI) is the main factor affecting the prognosis of patients with hepatocellular carcinoma (HCC). The aim of this study was to identify accurate diagnostic biomarkers from urinary protein signatures for preoperative prediction. METHODS: We conducted label-free quantitative proteomic studies on urine samples of 91 HCC patients and 22 healthy controls. We identified candidate biomarkers capable of predicting MVI status and combined them with patient clinical information to perform a preoperative nomogram for predicting MVI status in the training cohort. Then, the nomogram was validated in the testing cohort (n = 23). Expression levels of biomarkers were further confirmed by enzyme-linked immunosorbent assay (ELISA) in an independent validation HCC cohort (n = 57). RESULTS: Urinary proteomic features of healthy controls are mainly characterized by active metabolic processes. Cell adhesion and cell proliferation-related pathways were highly defined in the HCC group, such as extracellular matrix organization, cell-cell adhesion, and cell-cell junction organization, which confirms the malignant phenotype of HCC patients. Based on the expression levels of four proteins: CETP, HGFL, L1CAM, and LAIR2, combined with tumor diameter, serum AFP, and GGT concentrations to establish a preoperative MVI status prediction model for HCC patients. The nomogram achieved good concordance indexes of 0.809 and 0.783 in predicting MVI in the training and testing cohorts. CONCLUSIONS: The four-protein-related nomogram in urine samples is a promising preoperative prediction model for the MVI status of HCC patients. Using the model, the risk for an individual patient to harbor MVI can be determined.

FASFLNet: feature adaptive selection and fusion lightweight network for RGB-D indoor scene parsing.

RGB-D indoor scene parsing is a challenging task in computer vision. Conventional scene-parsing approaches based on manual feature extraction have proved inadequate in this area because indoor scenes are both unordered and complex. This study proposes a feature adaptive selection, and fusion lightweight network (FASFLNet) for RGB-D indoor scene parsing that is both efficient and accurate. The proposed FASFLNet utilizes a lightweight classification network (MobileNetV2), constituting the backbone of the feature extraction. This lightweight backbone model guarantees that FASFLNet is not only highly efficient but also provides good performance in terms of feature extraction. The additional information provided by depth images (specifically, spatial information such as the shape and scale of objects) is used in FASFLNet as supplemental information for feature-level adaptive fusion between the RGB and depth streams. Furthermore, during decoding, the features of different layers are fused from top-bottom and integrated at different layers for final pixel-level classification, resulting in an effect similar to that of pyramid supervision. Experimental results obtained on the NYU V2 and SUN RGB-D datasets indicate that the proposed FASFLNet outperforms existing state-of-the-art models and is both highly efficient and accurate.

Differential analysis of core-fucosylated glycoproteomics enabled by single-step truncation of N-glycans.

Alpha-1,6 fucosylation of N-glycans (core fucosylation, CF) represents a unique form of N-glycans and is widely involved in disease progression. In order to accurately identify CF glycoproteins, several approaches have been developed based on sequential cleavage with different glycosidases to truncate the N-glycans. Since multi-step sample treatments may introduce quantitation bias and affect the practicality of these approaches in large-scale applications. Here, we systematically evaluated the performance of the single-step treatment of intact glycopeptides by endoglycosidase F3 for CF glycoproteome. The single-step truncation (SST) strategy demonstrated higher quantitative stability and higher efficiency compared with previous approaches. The strategy was further practiced on both cell lines and serum samples. The dysregulation of CF glycopeptides between preoperative and postoperative serum from patients with pancreatic ductal adenocarcinoma was revealed, and the CF modifications of BCHE_N369, CDH5_N112 and SERPIND1_N49 were found to be potential prognostic markers. This study thus provides an efficient solution for large-scale quantitative analysis of the CF glycoproteome.

An RNA tagging approach for system-wide RNA-binding proteome profiling and dynamics investigation upon transcription inhibition.

RNA-protein interactions play key roles in epigenetic, transcriptional and posttranscriptional regulation. To reveal the regulatory mechanisms of these interactions, global investigation of RNA-binding proteins (RBPs) and monitor their changes under various physiological conditions are needed. Herein, we developed a psoralen probe (PP)-based method for RNA tagging and ribonucleic-protein complex (RNP) enrichment. Isolation of both coding and noncoding RNAs and mapping of 2986 RBPs including 782 unknown candidate RBPs from HeLa cells was achieved by PP enrichment, RNA-sequencing and mass spectrometry analysis. The dynamics study of RNPs by PP enrichment after the inhibition of RNA synthesis provides the first large-scale distribution profile of RBPs bound to RNAs with different decay rates. Furthermore, the remarkably greater decreases in the abundance of the RBPs obtained by PP-enrichment than by global proteome profiling suggest that PP enrichment after transcription inhibition offers a valuable way for large-scale evaluation of the candidate RBPs.

A Cytological Atlas of the Human Liver Proteome from PROTEOMESKY-LIVERHu 2.0, a Publicly Available Database.

The liver plays a unique role as a metabolic center of the body, and also performs other important functions such as detoxification and immune response. Here, we establish a cell type-resolved healthy human liver proteome including hepatocytes (HCs), hepatic stellate cells (HSCs), Kupffer cells (KCs), and liver sinusoidal endothelial cells (LSECs) by high-resolution mass spectrometry. Overall, we quantify total 8354 proteins for four cell types and over 6000 proteins for each cell type. Analysis of this data set and regulatory pathway reveals the cellular labor division in the human liver follows the pattern that parenchymal cells make the main components of pathways, but nonparenchymal cells trigger these pathways. Human liver cells show some novel molecular features: HCs maintain KCs and LSECs homeostasis by producing cholesterol and ketone bodies; HSCs participate in xenobiotics metabolism as an agent deliverer; KCs and LSECs mediate immune response through MHC class II-TLRs and MHC class I-TGFß cascade, respectively; and KCs play a central role in diurnal rhythms regulation through sensing diurnal IGF and temperature flux. Together, this work expands our understandings of liver physiology and provides a useful resource for future analyses of normal and diseased livers.

Strategy for Microscale Extraction and Proteome Profiling of Peripheral Blood Mononuclear Cells.

Peripheral blood mononuclear cells (PBMCs) play vital roles in physiological and pathological processes and represent a rich source for disease monitoring. Typical molecular profiling on PBMCs involves the sorting of cell subsets and thus requires a large volume of peripheral blood (PB), which impedes the clinical practicability of omics tools in PBMC measurements. It would be clinically invaluable to develop a convenient approach for preparing PBMCs from small volumes of PB and for deep proteome profiling of PBMCs. To this end, here, we designed an apparatus (PBMC-mCap) for microscale enrichment and proteome analysis of PBMCs, which pushed the needed PB volume from the normal 2 mL or higher to 100 µL or lower, comparable to the volume of a drop of finger blood. A PBMC-specific mass spectra library containing 8869 proteins and 121,956 peptides was further built, which, in combination with the optimized data-independent acquisition strategy, helped to identify 6000 and 6500 proteins from PBMCs with 100 µL and 1 mL of PB as initial materials, respectively. Further application of the strategy for PBMC proteomes revealed a steady difference between gender (male vs female) and upon stimulus (COVID-19 vaccination). For the latter, we observed differentially expressed genes and pathways involving the activation of immune cells, including the NF-κB pathway, inflammation response, and antiviral response. Our strategy for the proteome analysis of microscale PBMCs may provide a convenient clinical toolkit for disease diagnosis and healthy state monitoring.

Integrated Strategy for Unbiased Profiling of the Histidine Phosphoproteome.

Histidine phosphorylation (pHis), which plays a key role in signal transduction in bacteria and lower eukaryotes, has been shown to be involved in tumorigenesis. Due to its chemical instability, substoichiometric properties, and lack of specific enrichment reagents, there is a lack of approaches for specific and unbiased enrichment of pHis-proteins/peptides. In this study, an integrated strategy was established and evaluated as an unbiased tool for exploring the histidine phosphoproteome. First, taking advantage of the lower charge states of pHis-peptides versus the non-modified naked peptides at weak acid solution (∼pH 2.7), strong cation exchange (SCX) chromatography was used to differentiate modified and non-modified naked peptides. Furthermore, selective enrichment of the pHis-peptide was performed by applying Cu-IDA beads enrichment. Finally, stable isotope dimethyl labeling was introduced to guarantee high-confidence assignment of pHis-peptides. Using this integrated strategy, 563 different pHis-peptides (H = 1) in 385 proteins were identified from HeLa lysates. Motif analysis revealed that pHis prefers hydrophobic amino acids and has the consensus motif-HxxK, which covered the reports from different approaches. Thus, our method may provide an unbiased and effective tool to reveal histidine phosphoproteome and to study the biological process and function of histidine phosphorylation.

An Integrated Strategy for Mass Spectrometry-Based Multiomics Analysis of Single Cells.

Single-cell-based genomics and transcriptomics analysis have revealed substantial cellular heterogeneity among seemingly identical cells. Knowledge of the cellular heterogeneity at multiomics levels is vital for a better understanding of tumor metastasis and drug resistance, stem cell differentiation, and embryonic development. However, unlike genomics and transcriptomics studies, single-cell characterization of metabolites, proteins, and post-translational modifications at the omics level remains challenging due to the lack of amplification methods and the wide diversity of these biomolecules. Therefore, new tools that are capable of investigating these unamplifiable "omes" from the same single cells are in high demand. In this work, a microwell chip was prepared and the internal surface was modified for hydrophilic interaction liquid chromatography-based tandem extraction of metabolites and proteins and subsequent protein digestion. Next, direct electrospray ionization mass spectrometry was adopted for single-cell metabolome identification, and a data-independent acquisition-mass spectrometry approach was established for simultaneous proteome profiling and phosphoproteome analysis without phosphopeptide enrichment. This integrated strategy resulted in 132 putatively annotated compounds, more than 1200 proteins, and the first large-scale phosphorylation data set from single-cell analysis. Application of this strategy in chemical perturbation studies provides a multiomics view of cellular changes, demonstrating its capability for more comprehensive investigation of cellular heterogeneity.

A new tandem enrichment strategy for the simultaneous profiling of O-GlcNAcylation and phosphorylation in RNA-binding proteome.

RNA-protein interactions play important roles in almost every step of the lifetime of RNAs, such as RNA splicing, transporting, localization, translation and degradation. Post-translational modifications, such as O-GlcNAcylation and phosphorylation, and their "cross-talk" (OPCT) are essential to the activity and function regulation of RNA-binding proteins (RBPs). However, due to the extremely low abundance of O-GlcNAcylation and the lack of RBP-targeted enrichment strategies, large-scale simultaneous profiling of O-GlcNAcylation and phosphorylation on RBPs is still a challenging task. In the present study, we developed a tandem enrichment strategy combining metabolic labeling-based RNA tagging for selective purification of RBPs and HILIC-based enrichment for simultaneous O-GlcNAcylation and phosphorylation profiling. Benefiting from the sequence-independent RNA tagging by ethynyluridine (EU) labeling, 1115 RBPs binding to different types of RNAs were successfully enriched and identified by quantitative mass spectrometry (MS) analysis. Further HILIC enrichment on the tryptic-digested RBPs and MS analysis led to the first large-scale identification of O-GlcNAcylation and phosphorylation in the RNA-binding proteome, with 461 O-GlcNAc peptides corresponding to 300 RBPs and 671 phosphopeptides corresponding to 389 RBPs. Interestingly, ∼25% RBPs modified by two PTMs were found to be related to multiple metabolism pathways. This strategy has the advantage of high compatibility with MS and provides peptide-level evidence for the identification of O-GlcNAcylated RBPs. We expect it will support simultaneous mapping of O-GlcNAcylation and phosphorylation on RBPs and facilitate further elucidation of the crucial roles of OPCT in the function regulation of RBPs.

PTMiner: Localization and Quality Control of Protein Modifications Detected in an Open Search and Its Application to Comprehensive Post-translational Modification Characterization in Human Proteome.

The open (mass tolerant) search of tandem mass spectra of peptides shows great potential in the comprehensive detection of post-translational modifications (PTMs) in shotgun proteomics. However, this search strategy has not been widely used by the community, and one bottleneck of it is the lack of appropriate algorithms for automated and reliable post-processing of the coarse and error-prone search results. Here we present PTMiner, a software tool for confident filtering and localization of modifications (mass shifts) detected in an open search. After mass-shift-grouped false discovery rate (FDR) control of peptide-spectrum matches (PSMs), PTMiner uses an empirical Bayesian method to localize modifications through iterative learning of the prior probabilities of each type of modification occurring on different amino acids. The performance of PTMiner was evaluated on three data sets, including simulated data, chemically synthesized peptide library data and modified-peptide spiked-in proteome data. The results showed that PTMiner can effectively control the PSM FDR and accurately localize the modification sites. At 1% real false localization rate (FLR), PTMiner localized 93%, 84 and 83% of the modification sites in the three data sets, respectively, far higher than two open search engines we used and an extended version of the Ascore localization algorithm. We then used PTMiner to analyze a draft map of human proteome containing 25 million spectra from 30 tissues, and confidently identified over 1.7 million modified PSMs at 1% FDR and 1% FLR, which provided a system-wide view of both known and unknown PTMs in the human proteome.

Integrated Strategy for Large-Scale Investigation on Protein Core Fucosylation Stoichiometry Based on Glycan-Simplification and Paired-Peaks-Extraction.

Core fucosylation (CF) is a special form of N-glycosylation and plays an important role in pathological and biological processes. Increasing efforts in this area are focused on the identification of CF glycosites, whereas evidence showed that the stoichiometry of CF occupancy is functionally important. Here, an integrated strategy based on "Glycan-Simplification and Paired-Peaks-extraction" (GSPPE) for detecting large-scale stoichiometries of CF was developed. After HILIC enrichment of intact glycopeptides, sequential cleavages by endoglycosidases H and endoglycosidases F3 were performed to generate simplified glycopeptide forms (SGFs), i.e., peptide-GlcNAc (pep-HN) and peptide-GlcNAc-Fucose (pep-CF). These paired SGFs were found to be eluted consecutively on a reversed-phase chromatography column, which allowed us to obtain peak areas of SGF pairs, even if only one of the peaks was captured by the mass spectrometer (MS), by introducing the Paired-Peaks-Extraction algorithm. Thus, the missing value dilemma of random data-dependent MS/MS acquisition was reduced and the stoichiometry of site-specific CF could be calculated. We systematically evaluated the feasibility of this strategy using standard glycoproteins and then explored urinary samples from healthy individuals and hepatocellular carcinoma (HCC) patients. In total, 1449 highly reliable core fucose glycosites and their corresponding CF stoichiometries were obtained. Dozens of glycosites that differed significantly in the urine of healthy individuals and HCC patients were disclosed. The developed approach and program presented here may promote studies on core fucosylation and lead to a deeper understanding of their dysregulation in physiological- or pathological processes.

An Integrated Mass Spectroscopy Data Processing Strategy for Fast Identification, In-Depth, and Reproducible Quantification of Protein O-Glycosylation in a Large Cohort of Human Urine Samples.

Protein O-glycosylation has long been recognized to be closely associated with many diseases, particularly with tumor proliferation, invasion, and metastasis. The ability to efficiently profile the variation of O-glycosylation in large-scale clinical samples provides an important approach for the development of biomarkers for cancer diagnosis and for therapeutic response evaluation. Therefore, mass spectrometry (MS)-based techniques for high throughput, in-depth and reliable elucidation of protein O-glycosylation in large clinical cohorts are in high demand. However, the wide existence of serine and threonine residues in the proteome and the tens of mammalian O-glycan types lead to extremely large searching space composed of millions of theoretical combinations of peptides and O-glycans for intact O-glycopeptide database searching. As a result, an exceptionally long time is required for database searching, which is a major obstacle in O-glycoproteome studies of large clinical cohorts. More importantly, because of the low abundance and poor ionization of intact O-glycopeptides and the stochastic nature of data-dependent MS2 acquisition, substantially elevated missing data levels are inevitable as the sample number increases, which undermines the quantitative comparison across samples. Therefore, we report a new MS data processing strategy that integrates glycoform-specific database searching, reference library-based MS1 feature matching and MS2 identification propagation for fast identification, in-depth, and reproducible label-free quantification of O-glycosylation of human urinary proteins. This strategy increases the database searching speeds by up to 20-fold and leads to a 30%-40% enhanced intact O-glycopeptide quantification in individual samples with an obviously improved reproducibility. In total, we identified 1300 intact O-glycopeptides in 36 healthy human urine samples with a 30%-40% reduction in the amount of missing data. This is currently the largest dataset of urinary O-glycoproteome and demonstrates the application potential of this new strategy in large-scale clinical investigations.

Site-Specific and Quantitative N-Glycan Heterogeneity Analysis of the Charge Isomers of an Anti-VEGF Recombinant Fusion Protein by High-Resolution Two-Dimensional Gel Electrophoresis and Mass Spectrometry.

Glycan modification prompts important concerns about the quality control of biopharmaceutical production. Conbercept is a multiglycosylated recombinant fusion protein drug approved for the treatment of age-related macular degeneration (AMD). With 14 N-glycosites in the molecule and 7 N-glycosites in the monomer, the charge isomer separation and characterization of conbercept pose great challenges due to its enormous heterogeneities. The batch-to-batch stability on the charge isomer distribution and the possible causation of the pattern necessitate the development of effective analytical approaches. Here, the immobilized pH gradient (IPG)-based two-dimensional gel electrophoresis (2-DE) approach was first optimized to achieve high-resolution, high-reproducible separation and preparation of charge isomers. Then, combined with the quantitative analysis strategy of site-specific N-glycan heterogeneity based on the diagnostic MS2 ion (peptides+GlcNAc, Y1 ions) of glycopeptides, an integrated approach for the quantitation of site-specific N-glycan heterogeneities among charge isomers was established. Finally, the quantitation of site-specific N-glycoforms in each of the 2-DE resolved spots were performed, and the results showed that the sialylation tends to increase for gel spots located in the acidic regions. This study provides an effective approach to separate the charge isomers of the heavily glycosylated protein drugs, and to quantitatively explore the site-specific N-glycans dynamics along with the different charge isomers.

Novel Two-Dimensional MoS2-Ti4+ Nanomaterial for Efficient Enrichment of Phosphopeptides and Large-Scale Identification of Histidine Phosphorylation by Mass Spectrometry.

Due to its key roles in regulating the occurrence and development of cancer, protein histidine phosphorylation has been increasingly recognized as an important form of post-translational modification in recent years. However, large-scale analysis of histidine phosphorylation is much more challenging than that of serine/threonine or tyrosine phosphorylation, mainly because of its acid lability. In this study, MoS2-Ti4+ nanomaterials were synthesized using a solvothermal method and taking advantage of the electrostatic adsorption between MoS2 nanosheets and Ti4+. The MoS2-Ti4+ nanomaterials have the advantage of the combined affinity of Ti4+ and Mo toward phosphorylation under medium acidic conditions (pH = 3), which is crucial for preventing hydrolysis and loss of histidine phosphorylation during enrichment. The feasibility of using the MoS2-Ti4+ nanomaterial for phosphopeptide enrichment was demonstrated using mixtures of ß-casein and bovine serum albumin (BSA). Further evaluation revealed that the MoS2-Ti4+ nanomaterial is capable of enriching synthetic histidine phosphopeptides from 1000 times excess tryptic-digested HeLa cell lysate. Application of the MoS2-Ti4+ nanomaterials for large-scale phosphopeptide enrichment results in the identification of 10 345 serine, threonine, and tyrosine phosphosites and the successful mapping of 159 histidine phosphosites in HeLa cell lysates, therefore indicating great potential for deciphering the vital biological roles of protein (histidine) phosphorylation.