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uncut gels shows figure 1, figure 2, figure 3 and figure 6 uncut gels

Supplementary Figure S1 shows Correlation of IL-8 expression with overall survival in multiple cancers.

Supplementary Figure S6 shows IL-8-CXCR1 does not affect the infiltration of macrophages and MDSCs in the orthotopic model

Supplementary Figure legends shows Figure S1-S6 legends

Legends for Supplementary Figures S1-S19.

Supplementary Figure S2 shows HBV induces IL-8 expression mainly through HBx

Supplementary Fig. S17. Representative immunohistochemistry showing intratumoral, peritumoral, and marginal tissue stained for IL-18 from patients.

Supplementary Figures S1-S16, S18, and S19 and Supplementary Tables S1-S4. Supplementary Fig. S1. Stratification of patients based on IL-18 staining density in intratumoral and peritumoral tissue. Supplementary Fig. S2. Efficient fibrosis induction by carbon tetrachloride and slightly modulated fibrosis burden between WT and IL18R1-/- mice. Supplementary Fig. S3. Multiple cell types produce IL-18 and IL18R1 in HCC. Supplementary Fig. S4. Enhanced neutrophil-to-lymphocyte ratios and decreased circulating lymphocytes in tumor-bearing IL18R1-/- mice. Supplementary Fig. S5. NK and NKT cells in liver and tumor are not significantly different between WT and IL18R1-/- mice. Supplementary Fig. S6. Myeloid cell accumulation in liver and tumor are not significantly different between WT and IL18R1-/- mice. Supplementary Fig. S7. Quantification of NK and T-cell populations in WT and IL18R1-/- mice. Supplementary Fig. S8. Representative flow cytometry of T-cell populations in non-tumor liver, tumor, and spleen in WT and IL18R1-/- mice. Supplementary Fig. S9. Alternative tumor models yield similar skewing of T-cell populations in the tumor by loss of IL18R1. Supplementary Fig. S10. Slightly increased proportions of CD44+ T-cells in IL18R1-/- mice compared to WT. Supplementary Fig. S11. No significant changes in CD4+ CD25+ cells, CD4+ FoxP3+ cells, or CD4+ CD25+ FoxP3+ cells. Supplementary Fig. S12. Modestly decreased PD-1 in CD8+ T cells in IL18R1-/- mice compared with WT mice. Supplementary Fig. S13. Slight differences in cytokine production, no differences in granzyme production in T-cells between WT and IL18R1-/- mice. Supplementary Fig. S14. Representative flow cytometry of differentiation and cytokine production of CD4+ T-cells from WT and IL18R1-/- mice. Supplementary Fig. S15. Representative flow cytometry of WT and IL18R1-/- CD8+ T-cell survival and proliferation upon reactivation and stimulation. Supplementary Fig. S16. Tumor-infiltrating NK cells have altered cytokine and transcription factor production between WT and IL18R1-/- mice. Supplementary Supplementary Fig. S18. Differences in IL-18 staining density between intratumoral and peritumoral tissue are more closely linked to peritumoral staining density. Supplementary Fig. S19. No difference in survival based on expression of IL18R1 in patient samples. Supplementary Table S1. Antibodies, Dyes, Stains, and Recombinant Proteins Used. Supplementary Table S2. qPCR Primers and shRNAs Used. Supplementary Table S3. Correlations between Patient Characteristics and Phenotypes and IL-18 Staining Density in Our 138 Patient Cohort. Supplementary Table S4. Average Density of Intratumoral and Peritumoral IL-18 Staining in Our 138 Patient Cohort.

Chronic inflammation in liver tissue is an underlying cause of hepatocellular carcinoma. High levels of inflammatory cytokine IL18 in the circulation of patients with hepatocellular carcinoma correlates with poor prognosis. However, conflicting results have been reported for IL18 in hepatocellular carcinoma development and progression. In this study, we used tissue specimens from hepatocellular carcinoma patients and clinically relevant mouse models of hepatocellular carcinoma to evaluate IL18 expression and function. In a mouse model of liver fibrosis that recapitulates a tumor-promoting microenvironment, global deletion of the IL18 receptor IL18R1 enhanced tumor growth and burden. Similarly, in a carcinogen-induced model of liver tumorigenesis, IL18R1 deletion increased tumor burden. Mechanistically, we found that IL18 exerted inflammation-dependent tumor-suppressive effects largely by promoting the differentiation, activity, and survival of tumor-infiltrating T cells. Finally, differences in the expression of IL18 in tumor tissue versus nontumor tissue were more predictive of patient outcome than overall tissue expression. Taken together, our findings resolve a long-standing contradiction regarding a tumor-suppressive role for IL18 in established hepatocellular carcinoma and provide a mechanistic explanation for the complex relationship between its expression pattern and hepatocellular carcinoma prognosis. Cancer Res; 76(8); 2394–405. ©2016 AACR.

Hepatitis B–associated hepatocellular carcinoma (HCC) is often accompanied by severe vascular invasion and portal vein tumor thrombus, leading to a poor prognosis. However, the underlying mechanism of this disease remains obscure. In this study, we demonstrate that the hepatitis B virus (HBV)–encoded gene HBx induces high IL8 production through MEK–ERK signal activation, leading to enhanced endothelial permeability to facilitate tumor vascular invasion. In a vascular metastatic model using a tail vein injection in a transgenic mouse with selective expression of human CXCR1 in the endothelium, activation of the IL8–CXCR1 cascade by overexpression of IL8 in tumor cells dramatically enhanced liver metastasis. Mechanistically, IL8 selectively induced GARP-latent-TGFβ in liver sinusoidal endothelial cells and subsequently provoked preferential regulatory T-cell polarization to suppress antitumor immunity. Collectively, these findings reveal a hepatitis B–associated IL8–CXCR1 signaling axis that mediates vascular invasion and local microenvironmental immune escape of HCC to induce intrahepatic metastasis, which may serve as potential therapeutic targets for HBV-associated HCC.Significance:This study identifies a hepatitis B–induced IL8/CXCR1/TGFβ signaling cascade that suppresses antitumor immunity and enhances metastasis in hepatocellular carcinoma, providing new potential targets for therapeutic intervention.

Supplementary Figure S4 shows IL-8-CXCR1 axis has no effect on immune cell infiltration in lung and spleen

Supplementary Figure S5 shows IL-8-CXCR1 axis creates an immunosuppressive microenvironment in the liver

More detailed descriptions of patients and experimental protocols.

Mass spectrometry-based proteomics experiments can be subject to a large variability, which forms an obstacle to obtaining deep and accurate protein identification. Here, to obtain an optimal sample preparation workflow for in-depth proteome identification in human tissues, we systematically compared typical procedures in the four key steps during sample preparation, including two lysis buffers (5% SDS and 7M urea/2M thiourea), acetone precipitation, two proteolytic enzyme methods (in-solution digestion and FASP), and two pre-fractionation methods (SDS-PAGE and hi-pH RPLC). Compared with other methods, the procedure, including urea/thiourea as the lysis buffer, in-solution digestion, followed by hi-pH RPLC, yields an increase in proteome coverage (+15%), matched peptides (+42.4%), and significantly high protein concentrations. We also used combinations of these sample preparation methods to demonstrate a high identification rate in the range of low molecular weight (LMW), and the performance of sample preparation workflows varied between different groups of proteins. Importantly, 3 proteins defined as missing proteins (MPs) following the Human Proteome Project (HPP) guidelines were found in our data set. Overall, our findings provide an optimal sample preparation workflow for highly efficient and unbiased global proteomic analysis in human tissues.

Background & aims Regulatory T cell (Treg) depletion increases antitumor immunity. However, severe autoimmunity can occur following systemic loss of Tregs, which could be avoided by selectively depleting intratumoral Tregs. Herein, we aimed to investigate the role of tumor-infiltrating CCR4+ Tregs in hepatocellular carcinoma (HCC) and to provide a potential target strategy for immunotherapy. Methods CCR4+ Tregs were analyzed by flow cytometry in murine models and clinical samples. The function of tumor-infiltrating and induced CCR4+ Tregs was interrogated by genetic and epigenetic approaches. To block CCR4+ Treg chemotaxis, we developed an N-terminus recombinant protein of CCR4 (N-CCR4-Fc) as a neutralizing pseudo-receptor that effectively bound to its ligand CCL22. The efficacy of CCR4 antagonism as an immunotherapeutic agent was evaluated by tumor weights, growth kinetics and survival curves. Results CCR4+ Tregs were the predominant type of Tregs recruited to hepatitis B-associated HCC (HBV+ HCC), correlating with sorafenib resistance and HBV load titers. Compared with CCR4- Tregs, CCR4+ Tregs exhibited increased IL-10 and IL-35 expression, and enhanced functionality in suppressing CD8+ T cells. CCR4+ Tregs also displayed PD-1+TCF1+ stem-like properties. ATAC-seq data revealed substantial chromatin remodeling between tumor-infiltrating Tregs (TIL-Tregs) and induced Tregs, suggesting that long-term chromatin reprogramming accounted for the acquisition of enhanced immunosuppressive stem-like specificity by CCR4+ TIL-Tregs. Treatment with a CCR4 antagonist or N-CCR4-Fc blocked intratumoral Treg accumulation, overcame sorafenib resistance, and sensitized tumors to PD-1 checkpoint blockade. Conclusions Intratumoral stem-like CCR4+ Tregs orchestrated immunosuppressive resource cells in the tumor microenvironment. CCR4 could be targeted to enhance antitumor immunity by specifically blocking infiltration of Tregs into the tumor microenvironment and inhibiting maintenance of the TIL-Treg pool. Lay summary Targeting regulatory T cells is a promising approach in cancer immunotherapy; however, severe autoimmunity can occur following systemic regulatory T cell loss. This could be avoided by selectively depleting intratumoral regulatory T cells. Herein, targeting intratumoral stem-like CCR4+ regulatory T cells helped to overcome sorafenib resistance and sensitize tumors to immune checkpoint blockade in mouse models of liver cancer. This approach could have wide clinical applicability.

Deep mining the proteome of trace biological samples is critical for biomedical applications. However, it remains a challenge due to the loss of analytes caused by current sample preparation procedures. To address this, we recently developed a single-pot and miniaturized in-solution digestion (SMID) method for minute sample handling with three streamlined steps and completed within 3 h. The SMID approach outperformed the traditional workflow in substantially saving time, reducing sample loss, and exhibiting extensive applicability for 10-100 000 cell analysis. This user-friendly and high-sensitivity strategy enables ∼5300 proteins and 53 000 peptides to be confidently identified within 1 h of mass spectrometry (MS) time from a small amount of 1000 HeLa cells. In addition, we accurately and robustly detected proteomes in 10 mouse oocytes with excellent reproducibility. We further adopted SMID for the proteome analysis in cell migration under confinement, which induced cells to undergo a mesenchymal-amoeboid transition (MAT). During the MAT, a systematic quantitative proteome map of 1000 HeLa cells was constructed with seven expression profile clusters, which illustrated the application of SMID and provided a fundamental resource to investigate the mechanism of MAT.

Great advances have been made in mass spectrometric data interpretation for intact glycopeptide analysis. However, accurate identification of intact glycopeptides and modified saccharide units at the site-specific level and with fast speed remains challenging. Here, we present a glycan-first glycopeptide search engine, pGlyco3, to comprehensively analyze intact N- and O-glycopeptides, including glycopeptides with modified saccharide units. A glycan ion-indexing algorithm developed for glycan-first search makes pGlyco3 5–40 times faster than other glycoproteomic search engines without decreasing accuracy or sensitivity. By combining electron-based dissociation spectra, pGlyco3 integrates a dynamic programming-based algorithm termed pGlycoSite for site-specific glycan localization. Our evaluation shows that the site-specific glycan localization probabilities estimated by pGlycoSite are suitable to localize site-specific glycans. With pGlyco3, we confidently identified N-glycopeptides and O-mannose glycopeptides that were extensively modified by ammonia adducts in yeast samples. The freely available pGlyco3 is an accurate and flexible tool that can be used to identify glycopeptides and modified saccharide units.

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N - and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved ‘high-coverage’ and ‘high-accuracy’ glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics., This analysis presents the results of a community-based evaluation of existing software for large-scale glycopeptide data analysis.

The wide dynamic range of serum proteome restrained discovery of clinically interested proteins in large cohort studies. Herein, we presented a high-sensitivity, high-throughput, and precise pan-targeted serum proteomic strategy for highly efficient cancer serum proteomic research and biomarker discovery. We constructed a resource of over 2000 cancer-secreted proteins, and the standard MS assays and spectra of at least one synthetic unique peptide per protein were acquired and documented (Cancer Serum Atlas, www.cancerserumatlas.com). Then, the standard peptide-anchored parallel reaction monitoring (SPA-PRM) method was developed with support of the Cancer Serum Atlas, achieving precise quantification of cancer-secreted proteins with high throughput and sensitivity. We directly quantified 325 cancer-related serum proteins in 288 serums of four cancer types (liver, stomach, lung, breast) and controls with the pan-targeted strategy and discovered considerable potential biomarker benefits for early detection of cancer. Finally, a proteomic-based multicancer detection model was built, demonstrating high sensitivity (87.2%) and specificity (100%), with 73.8% localization accuracy for an independent test set. In conclusion, the Cancer Serum Atlas provides a wide range of potential biomarkers that serve as targets and standard assays for systematic and highly efficient serological studies of cancer. The Cancer Serum Atlas-supported pan-targeted proteomic strategy enables highly efficient biomarker discovery and multicancer detection and thus can be a powerful tool for liquid biopsy.

Background: Alfalfa has small seeds and is intolerant to deep-sowing. We investigated seed emergence of alfalfa variety “Longmu 801” from deep-sowing and its quality improvement through different bio-fertilizer treatments. Methods: Seven fertilization treatments were tested: CK: no fertilization (control), A: amino acid fertilizer, B: amino acid fertilizer + selenium-rich yeast fertilizer diluent, C: amino acid fertilizer + selenium-rich yeast fertilizer dilution + microbial agent, D: amino acid fertilizer + algae extract, E: amino acid fertilizer + microbial agent and F: amino acid fertilizer + selenium-rich yeast fertilizer diluent + microbial agent + algae extract. Result: The bio-fertilizer treatments improved the alfalfa seedling emergence, growth and quality. Treatment E increased the emergence rate, plant height and yield by 10.6%, 41.0% and 68.9%, respectively; decreased the stem-leaf ratio, neutral detergent fiber and acid detergent fiber by 41.7%, 3.7% and 3.17%, respectively and increased crude protein, crude fat and relative feeding value by 2.5%, 0.5% and 8.6%, respectively; compared with that of the control. Soaking alfalfa seeds in 0.2% amino acid fertilizer and applying 13.5 g microbial agent was suggested as the most efficient fertilization technique to promote alfalfa emergence, growth and quality and provide profits to farmers due to its low cost.

Porphyria is a group of genetic photodermatoses that cause too much porphyrin to accumulate in the blood, skin, and liver, resulting in skin photosensitivity and damage, liver disease, or potential liver failure. Conventional detection methods include high-performance liquid chromatography and fluorescence spectrometry. However, these methods usually require complicated pretreatment and time-consuming processes. Therefore, efficient and fast detection of porphyria is urgently needed. Herein, we develop a molecular afterglow reporter-based sensing scheme for the detection of porphyrins in whole blood. The afterglow reporter can respond to the production of singlet oxygen (1O2) of porphyrins after light excitation, and the detection signals can be amplified through adjusting the amount of singlet oxygen and afterglow reporter molecules. Moreover, without the use of a real-time excitation source, afterglow signals can avoid the scattering and autofluorescence interference in biological samples, thereby reducing background noise. More importantly, we prove the applicability of the afterglow reporter in the quantitative detection of porphyrins in whole blood and demonstrate its great clinical potential.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection often causes severe complications and even death. However, asymptomatic infection has also been reported, highlighting the difference in immune responses among individuals. Here we performed single-cell chromatin accessibility and T cell-receptor analyses of peripheral blood mononuclear cells collected from individuals convalescing from COVID-19 and healthy donors. Chromatin remodelling was observed in both innate and adaptive immune cells in the individuals convalescing from COVID-19. Compared with healthy donors, recovered individuals contained abundant TBET-enriched CD16+ and IRF1-enriched CD14+ monocytes with sequential trained and activated epigenomic states. The B-cell lineage in recovered individuals exhibited an accelerated developmental programme from immature B cells to antibody-producing plasma cells. Finally, an integrated analysis of single-cell T cell-receptor clonality with the chromatin accessibility landscape revealed the expansion of putative SARS-CoV-2-specific CD8+ T cells with epigenomic profiles that promote the differentiation of effector or memory cells. Overall, our data suggest that immune cells of individuals convalescing from COVID-19 exhibit global remodelling of the chromatin accessibility landscape, indicative of the establishment of immunological memory.

Large-scale intact glycopeptide identification has been advanced by software tools. However, tools for quantitative analysis remain lagging behind, which hinders exploring the differential site-specific glycosylation. Here, we report pGlycoQuant, a generic tool for both primary and tandem mass spectrometry-based intact glycopeptide quantitation. pGlycoQuant advances in glycopeptide matching through applying a deep learning model that reduces missing values by 19–89% compared with Byologic, MSFragger-Glyco, Skyline, and Proteome Discoverer, as well as a Match In Run algorithm for more glycopeptide coverage, greatly expanding the quantitative function of several widely used search engines, including pGlyco 2.0, pGlyco3, Byonic and MSFragger-Glyco. Further application of pGlycoQuant to the N-glycoproteomic study in three different metastatic HCC cell lines quantifies 6435 intact N-glycopeptides and, together with in vitro molecular biology experiments, illustrates site 979-core fucosylation of L1CAM as a potential regulator of HCC metastasis. We expected further applications of the freely available pGlycoQuant in glycoproteomic studies.

Background In diabetes, delayed wound healing was considered as the result of excessive recruitment and retention of pro-inflammatory cells and factors. Hematopoietic prostaglandin D synthase (HPGDS) was identified from differently expressed genes of diabetic human foot skin. HPGDS is responsible for the production of prostaglandin D2 (PGD2), an inflammatory mediator. Therefore, we aim to explore whether HPGDS could be a therapeutic target in the diabetic wound (DW). Method In this study, we compared gene expression profilings of diabetic human foot skin and non-diabetic human foot skin from the Gene Expression Omnibus database. We detected the characteristics of immune components in diabetic mice wound and investigated the role and underlying mechanism of the differently expressed Hpgds for the diabetic wound healing. For in vivo studies, we engineered ADSC to overexpress Hpgds (ADSCHpgds) and evaluated its effects on diabetic wound healing using a full-thickness skin wound model. For in vitro studies, we evaluated the role of ADSCHpgds conditioned medium and PGD2 on Lipopolysaccharide (LPS) induced macrophage. Results Hpgds was significantly down-regulated in type 2 diabetic mice wound and its deficiency delayed normal wound healing. ADSCHpgds accelerated DW healing by reducing neutrophil and CD8T cell recruitment, promoting M2 macrophage polarization and increasing the production of growth factors. ADSCHpgds conditioned medium showed superior capability in promoting M2 macrophage transition than conditioned medium derived from ADSC alone. Conclusion Our results demonstrated that Hpgds is required for wound healing, and ADSCHpgds could accelerate DW healing by improving anti-inflammatory state and normalizing the proliferation phase of wound healing in mice. These findings provide a new insight in the therapeutic strategy of diabetic wound.

Hepatitis B–associated hepatocellular carcinoma (HCC) is often accompanied by severe vascular invasion and portal vein tumor thrombus, leading to a poor prognosis. However, the underlying mechanism of this disease remains obscure. In this study, we demonstrate that the hepatitis B virus (HBV)–encoded gene HBx induces high IL8 production through MEK–ERK signal activation, leading to enhanced endothelial permeability to facilitate tumor vascular invasion. In a vascular metastatic model using a tail vein injection in a transgenic mouse with selective expression of human CXCR1 in the endothelium, activation of the IL8–CXCR1 cascade by overexpression of IL8 in tumor cells dramatically enhanced liver metastasis. Mechanistically, IL8 selectively induced GARP-latent-TGFβ in liver sinusoidal endothelial cells and subsequently provoked preferential regulatory T-cell polarization to suppress antitumor immunity. Collectively, these findings reveal a hepatitis B–associated IL8–CXCR1 signaling axis that mediates vascular invasion and local microenvironmental immune escape of HCC to induce intrahepatic metastasis, which may serve as potential therapeutic targets for HBV-associated HCC. Significance: This study identifies a hepatitis B–induced IL8/CXCR1/TGFβ signaling cascade that suppresses antitumor immunity and enhances metastasis in hepatocellular carcinoma, providing new potential targets for therapeutic intervention.

Tobacco is a traditional Chinese medicine containing a variety of biologically active substances. In addition to being used to make cigarettes, tobacco is also a vastly underdeveloped medicinal resource. In order to identify and clarify the biological activities and medicinal value of tobacco leaves, the metabolomes of tobacco leaves were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) based on multiple reaction monitoring (MRM). In total, 1169 metabolites were identified and quantified. The results showed that the metabolic profiles of the tobacco cultivars K326 and Yun87 are similar to each other but different from that of Hongda. Moreover, the curing process affects the metabolic profiles of tobacco leaves. Flavonoids are the largest class of metabolites in tobacco leaves. Flavonoids have multiple biological functions; for example, they can promote or inhibit inflammation. We found that quercetin provides anti-inflammatory activity by inhibiting the il-1β mRNA expression, while glycitin and neohesperidin can promote il-1β and il-6 production. Our results provide in-depth insights into the medical uses and biological mechanisms of tobacco leaves.

To solve the problem that finite element analysis and calculation need to be repeated during model updates, which leads to tedious and inefficient correction work, ABAQUS (a powerful finite element software for engineering simulation) is used to develop a user-friendly graphical user interface platform for automatic completion of this update for cable-stayed bridges. In this paper, a method for establishing the benchmark finite element model of cable-stayed bridges based on ABAQUS and influence matrix (IM)-hunter prey optimization (HPO) is proposed. The method is based on the secondary development of ABAQUS to realize the modules of sensitivity analysis, influence matrix, and optimization. According to the sensitivity analysis module, the influence of the change in the finite element model parameters on the static response of a cable-stayed bridge is studied, and the cable area is used as the parameter to be corrected. The influence matrix module is used to obtain the IM of the cable area to girder displacement and cable force under a static load. The objective function is constructed by combining the measured displacement and cable force data using the optimization module, and the global optimal solution of the parameters to be corrected in the objective function is found by HPO. Finally, the solution is sent to the finite element model for correction, and the corrected displacement and cable force data are compared with the measured data. The results show that the modified calculation results obtained by this method are in good agreement with the measured results. The modified finite element model can be used as presented.

Imaging mass spectrometry is a rapidly developing research field, especially in the fields of life sciences and medicine. Various types of small and macromolecules in biological tissues can be scanned by imaging mass spectrometry technology. These biomolecules are closely related to the physiological and pathological states of organisms. Therefore, imaging mass spectrometry is a vital supplement to the method of optical morphological imaging. There are three techniques of imaging mass spectrometry: matrix assisted laser desorption ionization (MALDI) mass spectrometry imaging, secondary ion mass spectrometry (SIMS) imaging, and desorption electrospray ionization (DESI) mass spectrometry imaging. This review illustrated the principles and techniques of these three techniques and their applications in scientific and clinical research. The characteristics of these three types of mass spectrometry imaging can be summarized as follows: the spatial resolutions are separately 100, 10, and 0.1–1 μm; the working environments are atmospheric pressure, vacuum or low pressure, and vacuum; the analytes are small molecules, peptides or proteins or nucleic acid, small molecule or inorganic element; the application fields are environment, biomedicine, and material science.

Sphingolipids (SPLs) are bioactive lipids that manifest structural diversity and complexity in eukaryotes. However, the distributions and functions of these molecules in mammalian tissues/cells have not been systematically investigated. Herein, we integrated shotgun lipidomics with targeted LC-MRM/MS approach to comprehensively analyze SPL species in various biological samples with high accuracy. Preliminarily, 1311 SPL molecules were identified in 18 kinds of mammalian samples, including 3 groups of human sera, 10 mouse tissues and 5 cell lines via 26 sphingoid long-chain bases scanning. The sphingolipidome compositions and distributions were systematically characterized and distinct qualitative and quantitative profiles were clearly exhibited in various samples, indicating unique biological functions of the sphingolipidomes. Next, targeted SPLs analysis by LC-MRM/MS with critical criteria monitoring two characteristic fragments of one precursor was applied to human serum samples from 24 coronary artery disease (CAD) patients and 12 healthy controls, which successfully quantified 170 SPL molecules. Ten novel SPL molecules were discovered as a potential diagnostic panel for CAD patients via multivariate exploratory receiver operating characteristic curve-based biomarker analysis. The diagnostic panel with the 10 SPL molecules achieved 97.2% accuracy, with a favorable auxiliary diagnostic value (AUC = 1.000), for the detection of CAD. These results clearly support the sphingolipidomic approach in application to discovering disease biomarker panel as well as deep investigation of biological functions of complex SPLs in mammalian samples.

The prevalence of intracranial aneurysm (IA) is increasing, and the consequences of its rupture are severe. This study aimed to reveal specific, sensitive, and non‐invasive biomarkers for diagnosis and classification of ruptured and unruptured IA, to benefit the development of novel treatment strategies and therapeutics altering the course of the disease. We first assembled an extensive candidate biomarker bank of IA, comprising up to 717 proteins, based on altered proteins discovered in the current tissue and serum proteomic analysis, as well as from previous studies. Mass spectrometry assays for hundreds of biomarkers were efficiently designed using our proposed deep learning‐based method, termed DeepPRM. A total of 113 potential markers were further quantitated in serum cohort I (n = 212) & II (n = 32). Combined with a machine‐learning‐based pipeline, we built two sets of biomarker combinations (P6 & P8) to accurately distinguish IA from healthy controls (accuracy: 87.50%) or classify IA rupture patients (accuracy: 91.67%) upon evaluation in the external validation set (n = 32). This extensive circulating biomarker development study provides valuable knowledge about IA biomarkers.

Precise and automated analysis of site-specific O-glycosylation on single proteins is crucial for comprehensive characterization of some important glycoproteins, such as tumor biomarkers and recombinant drug proteins. Mass spectrometry has been proven to be a powerful technique for protein sequencing and N-glycosylation analysis. However, challenges remain in developing computational tools for intact O-glycopeptide analysis, which has greatly hindered the development of mass-spectrometry-based O-glycosylation analysis. Herein, an integrated strategy together with a dedicated automated computational tool termed AOGP was developed for intact O-glycopeptide analysis on single proteins. AOGP utilized de novo sequencing for O-glycans and a database search strategy for peptide backbones. The false discovery rate (FDR) of the identification results was controlled and validated by a mixed Gaussian distribution estimation method. AOGP exhibited superior performance in identifying intact O-glycopeptides of the human erythropoietin with a total of 188 O-glycopeptide spectra reported under 1% FDR. AOGP is developed in Python, is fully open-sourced, and is equipped with a user-friendly interface. Such an easy-operating and robust tool would greatly facilitate O-glycosylation analysis on single proteins in tumor biomarker and recombinant drug protein development.

Introduction: Glycomics, which aims to define the glycome of a biological system to better assess the biological attributes of the glycans, has attracted increasing interest. However, the complexity and diversity of glycans present challenging barriers to glycome definition. Technological advances are major drivers in glycomics.Areas covered: This review summarizes the main methods and emphasizes the most recent advances in mass spectrometry-based methods regarding glycomics following the general workflow in glycomic analysis.Expert opinion: Recent mass spectrometry-based technological advances have significantly lowered the barriers in glycomics. The field of glycomics is moving toward both generic and precise analysis.

Serum/plasma holds promise as an important source of disease-related proteins and even biomarkers in clinical practice. However, the discovery of biomarker candidates in serum/plasma remains challenging. In this study, we constructed an MS strategy that enables the fast and precise quantification of serum biomarkers through coupling a high-throughput scheduled MRM strategy with a stable isotope-labelled (SIL) peptide panel from more than 500 plasma proteins as internal standards. With this strategy, we discovered relevant serum proteins of atherosclerosis (AS), lung cancer (LC) and breast cancer (BC), which can simultaneously recognize these diseases. The results indicate that the powerful strategy we constructed has the potential for serum biomarker screening and disease detection.

Histone modifications play an important role in regulating transcriptional gene expression and chromatin processes in eukaryotes. Increasing researches proved that aberrant post-translational modifications (PTMs) of histones is associated with many diseases. However, MS-based identification and quantification of histone PTMs are still challenging. Although classic chemical derivatization in conjunction with trypsin digestion is widely used for histone PTMs analysis in a bottom-up strategy, several side reactions have been observed in practice. In this work, outer membrane protease T (OmpT) was utilized as a protease for direct histone proteolysis and generated appropriate lengths of histone peptides for retention on reversed-phase chromatography. The powerful and unique tolerance of OmpT for modified lysines and arginines was demonstrated and can be quantitatively described for the first time, making it useful for detecting natural modifications. Using the optimized digestion conditions, we succeeded in identifying 121 histone marks from HEK293T cells, 42 of which were previously unreported. Additionally, histone H3 PTMs were quantitatively profiled in the KMS11 multiple myeloma cells and NSD2 selective knockout KMS11cells, revealing that NSD2 was of high specificity on H3K36 dimethylation. Histone chemical derivatizations are not required in our strategy, showing a remarkable strength over the conventional trypsin-based workflow.

Protein phosphorylation is a reversible and important post-translational modification. Identification of phosphopeptides without enrichment is difficult for the low-abundance of phosphopeptides in real complex biological samples. Therefore, the effective and selective concentration of phosphopeptides prior to proteomic identification by mass spectrometer is necessary. In this study, we synthesized a novel titanium-based immobilized metal ion affinity chromatography material for highly selective enrichment of phosphopeptides. To improve material hydrophilia to the maximum extent, titanium ions were immobilized on the 4-armed Poly(ethylene oxide)(4μ-PEO-Ti4+), a totally soluble polymer with large molecular weight (20000 g/mol). The 4μ-PEO-Ti4+ was used to enrich phosphopeptides from tryptic digests of standard proteins and real complex biological samples, followed by MALDI-TOF MS analysis. In enrichment of phosphopeptides from 4 pmol β-casein, the 4μ-PEO-Ti4+ performed the best property with starting material of 99–132 μg, loading buffer of 50% ACN/5% TFA (v/v), elution buffer of 10% NH3·H2O (v/v) and elution time of 30 min. The 4μ-PEO-Ti4+ has a superior detection sensitivity as low as 2 fmol for phosphopeptides. The high selectivity of 4μ-PEO-Ti4+ allows a deep enrichment of phosphopeptides of β-casein from a mixture with BSA of 1000-fold abundant. The 4μ-PEO-Ti4+ shows great stability and endurability and can be recycled up to at least 5 times. In addition, 4μ-PEO-Ti4+ could detect 10 and 15 phosphopeptides from non-fat milk and nonenzymatic human saliva, respectively. In total, 4μ-PEO-Ti4+ is a novel excellent material which shows great sensitive and selective enrichment of low-abundance phosphopeptides in real complex biological samples.

Histones participate in epigenetic regulation via dynamic post-translational modifications (PTMs) of histone variants. Comprehensive characterization of histone markers, especially those for the histone variants, could help to decipher the mechanism of epigenetic regulation. However, correctly profiling histone PTMs and its variants using mass spectrometry remains a challenge. Here, we developed an improved, specific and sensitive LC separation in conjunction with a high throughput multiple reaction monitoring combined with stable isotope-labeled internal standards (MRM-SIS) based quantitative method for histone H3 variants in the study of epigenetic regulation in the cell cycle. PTM patterns and the overall abundance of the three main histone H3 variants from Karpas 422 cells were analyzed and quantified simultaneously during different cell stages. The methylation pattern varied between different sites and modification states during the cell cycle. The canonical H3.1 presented regular patterns on K27 and K36, similar to H3.2, albeit differing from variant H3.3. H3.3 K36me2 increased from G1, S to G2 phase, whereas the same marker decreased in both H3.1 and H3.2. This novel discovery inspires more focus and research on the histone variants behavior and function during cell cycle. Moreover, this improved method could be applied to unveil PTMs dynamics of histone variants in several biological processes.

Interpreting large-scale glycoproteomic data for intact glycopeptide identification has been tremendously advanced by software tools. However, software tools for quantitative analysis of intact glycopeptides remain lagging behind, which greatly hinders exploring the differential expression and functions of site-specific glycosylation in organisms. Here, we report pGlycoQuant, a generic software tool for accurate and convenient quantitative intact glycopeptide analysis, supporting both primary and tandem mass spectrometry quantitation for multiple quantitative strategies. pGlycoQuant enables intact glycopeptide quantitation with very low missing values via a deep residual network, thus greatly expanding the quantitative function of several powerful search engines, currently including pGlyco 2.0, pGlyco3, Byonic and MSFragger-Glyco. The pGlycoQuant-based site-specific N-glycoproteomic study conducted here quantifies 6435 intact N-glycopeptides in three hepatocellular carcinoma cell lines with different metastatic potentials and, together with in vitro molecular biology experiments, illustrates core fucosylation at site 979 of the L1 cell adhesion molecule (L1CAM) as a potential regulator of HCC metastasis. pGlycoQuant is freely available at https://github.com/expellir-arma/pGlycoQuant/releases/. We have demonstrated pGlycoQuant to be a powerful tool for the quantitative analysis of site-specific glycosylation and the exploration of potential glycosylation-related biomarker candidates, and we expect further applications in glycoproteomic studies.

Zebrafish (Danio rerio) embryos are widely used in toxicity tests, especially in investigations on chlorinated or brominated flame retardants (BFRs) and metals. A key challenge in environmental risk assessment (ERA) is how to clarify the same or different sites of toxic action in a species after exposure to the individual chemicals or chemical mixtures and further provide the common toxic sites or organs for risk assessment of chemical mixtures. In this study, zebrafish embryo was used to evaluate the sublethal toxicity (gas bladder damage) of tris(2,3-dibromopropyl) isocyanurate (TBC), Chlorinated paraffins (CPs), hexabromocyclododecane (HBCD), and Cu, Cd, Pb, Ag, Zn, and corresponding sublethal molecular levels (and inflammation-related enzymes [deiodinase (DIO) enzymes]) in fish through optical microscopy methods. The tested chemicals all caused failed inflation of the gas bladder, as indicated by activity inhibition of type 2 iodothyroxine deiodinase enzyme. We put up with the common targeted sites or organs for further studying the toxic mechanisms underlying the chemical mixtures.

Large-scale profiling of intact glycopeptides is critical but challenging in glycoproteomics. Data independent acquisition (DIA) is an emerging technology with deep proteome coverage and accurate quantitative capability in proteomics studies, but is still in the early stage of development in the field of glycoproteomics. We propose GproDIA, a framework for the proteome-wide characterization of intact glycopeptides from DIA data with comprehensive statistical control by a 2-dimentional false discovery rate approach and a glycoform inference algorithm, enabling accurate identification of intact glycopeptides using wide isolation windows. We further utilize a semi-empirical spectrum prediction strategy to expand the coverage of spectral libraries of glycopeptides. We benchmark our method for N-glycopeptide profiling on DIA data of yeast and human serum samples, demonstrating that DIA with GproDIA outperforms the data-dependent acquisition-based methods for glycoproteomics in terms of capacity and data completeness of identification, as well as accuracy and precision of quantification. We expect that this work can provide a powerful tool for glycoproteomic studies., Data independent acquisition (DIA) proteomics provides deep coverage and high quantitative accuracy, but is not yet well established in glycoproteomics. Here, the authors develop a DIA-based glycoproteomics workflow with stringent statistical controls to enable accurate glycopeptide identification.

Protein biomarkers of intracranial aneurysm (IA) are essential for early detection and prediction of its rupture to facilitate the diagnosis and clinical management of the disease, monitor treatment response and detect recurrence. Here, we developed a comprehensive strategy for IA biomarker discovery by analyzing tissues from an animal model (n = 4) and serum from human patients (n = 60) using isobaric tandem mass tags-based quantitative proteomics. A total of 4811 and 562 proteins were identified from aneurysm tissue and serum samples, respectively. The 223 candidate protein biomarkers were further validated in an independent serum cohort (n = 30) by multiple reaction monitoring analysis. Combined with a logistic regression model, we built a diagnostic classifier P2 (FCN2RARRES2) to differentiate IA from healthy controls with accuracy of 93.3%, as well as a diagnostic classifier P7 (ADAM12, APOL3, F9, C3, CEACAM1, ICAM3, KLHDC7A) to classify ruptured IA from unruptured IA with accuracy of 95.0%. Taken together, our results suggest a valuable strategy for biomarker discovery and patient stratification in IA.

Mass spectrometry (MS)-based proteomics have been extensively applied in clinical practice to discover potential protein and peptide biomarkers. However, the traditional sample pretreatment workflow remains labor-intensive and time-consuming, which limits the application of MS-based proteomic biomarker discovery studies in a high throughput manner. In the current work, we improved the previously reported procedure of the simple and rapid sample preparation methods (RSP) by introducing macroporous ordered siliceous foams (MOSF), namely RSP-MOSF. With the aid of MOSF, we further reduced the digestion time to 10 min, facilitating the whole sample handling process within 30 min. Combining with 30 min direct data independent acquisition (DIA) of LC-MS/MS, we accomplished a serum sample analysis in 1 h. Comparing with the RSP method, the performance of protein and peptide identification, quantitation, as well as the reproducibility of RSP-MOSF is comparable or even outperformed the RSP method. We further applied this workflow to analyze serum samples for potential candidate biomarker discovery of pancreatic cancer. Overall, 576 serum proteins were detected with 41 proteins significantly changed, which could serve as potential biomarkers for pancreatic cancer. Additionally, we evaluated the performance of RSP-MOSF method in a 96-well plate format which demonstrated an excellent reproducibility of the analysis. These results indicated that RSP-MOSF method had the potential to be applied on an automatic platform for further scaled analysis.

Glycosylation is a widely occurring posttranslational modification. Here, we applied a quick, convenient and high-throughput strategy (lectin array) to investigate the variation in glycans on different macrophage subtypes derived from THP-1 and RAW264.7 cells. For THP-1 cells, there were more significant differences in the glycan on M2 macrophages compared to the other two subtypes. In contrast, M1 macrophages exhibited more significant glycan remodeling than the other subtypes for the RAW264.7 cell line. The response of the lectins which recogonize the N-glycan and α2,6 sialic acid was higher during polarization into anti-inflammatory phase (THP-1 derived M2 subtypes), and lower in pro-inflammatory phase (RAW264.7 M1 subtypes). The regulation of several α2,6 sialyltransferase genes was coincident with the regulation of the α2,6 sialic acid on the two cell lines. The lectin response and glycosyltranferase gene expression confirmed that α2,6 sialic acid showed higher expression in the anti-inflammatory phase. This indicated that α2,6 sialic acid was a potential indicator for the anti-inflammatory response.

The heterogeneity and low abundance of protein glycosylation present challenging barriers to the analysis of intact glycopeptides, which is key to comprehensively understanding the role of glycosylation in an organism. Efficient and specific enrichment of intact glycopeptides could help greatly with this problem. Here, we propose a new enrichment strategy using a boronic acid (BA)-functionalized mesoporous graphene-silica composite (denoted as GO@mSiO2-GLYMO-APB) for isolating intact glycopeptides from complex biological samples. The merits of this composite, including high surface area and synergistic effect from size exclusion functionality of mesoporous material, hydrophilic interaction of silica, and the reversible covalent binding with BA, enable the effective and specific enrichment of both intact N- and O-glycopeptides. The results from the enrichment performance of the strategy evaluated by standard glycoproteins and the application to global N- and O-glycosylation analyses in human serum indicate the robustness and potential of the strategy for intact glycopeptide analysis.

Nascent proteome is crucial in directly revealing how the expression of a gene is regulated on a translation level. In the nascent protein identification, puromycin capture is one of the pivotal methods, but it is still facing the challenge in the deep profiling of nascent proteomes due to the low abundance of most nascent proteins. Here, we describe the synthesis of puromycin-modified silica microspheres (PMSs) as the sorbent of dispersive solid-phase microextraction and the establishment of the PMS-based nascent proteomics (PMSNP) method for efficient capture and analysis of nascent proteins. The modification efficiency of puromycin groups on silica microspheres reached 91.8% through the click reaction. After the optimization and simplification of PMSNP, more than 3500 and 3900 nascent proteins were rapidly identified in HeLa cells and mouse brains within 13.5 h, respectively. The PMSNP method was successfully applied to explore changes in the translation process in a biological stress model, namely, the lipopolysaccharide-stimulated HeLa cells. Biological functional analyses revealed the unique characters of the nascent proteomes and exhibited the superiority of the PMSNP in the identification of low abundance and secreted nascent proteins, thus demonstrating the sensitivity and immediacy of the PMSNP method.