Diagnosing and staging epithelial ovarian cancer by serum glycoproteomic profiling.

BACKGROUND: There is a need for diagnostic tests for screening, triaging and staging of epithelial ovarian cancer (EOC). Glycoproteomics of blood samples has shown promise for biomarker discovery. METHODS: We applied glycoproteomics to serum of people with EOC or benign pelvic masses and healthy controls. A total of 653 analytes were quantified and assessed in multivariable models, which were tested in an independent cohort. Additionally, we analyzed glycosylation patterns in serum markers and in tissues. RESULTS: We identified a biomarker panel that distinguished benign lesions from EOC with sensitivity and specificity of 83.5% and 90.1% in the training set, and of 86.7 and 86.7% in the test set, respectively. ROC analysis demonstrated strong performance across a range of cutoffs. Fucosylated multi-antennary glycopeptide markers were higher in late-stage than in early-stage EOC. A comparable pattern was found in late-stage EOC tissues. CONCLUSIONS: Blood glycopeptide biomarkers have the potential to distinguish benign from malignant pelvic masses, and early- from late-stage EOC. Glycosylation of circulating and tumor tissue proteins may be related. This study supports the hypothesis that blood glycoproteomic profiling can be used for EOC diagnosis and staging and it warrants further clinical evaluation.

Mass Spectrometry Analysis of Glycopeptides Enriched by Anion Exchange-Mediated Methods Reveals PolyLacNAc-Extended N-Glycans in Integrins and Tetraspanins in Melanoma Cells.

Glycosylation is a key modulator of the functional state of proteins. Recent developments in large-scale analysis of intact glycopeptides have enabled the identification of numerous glycan structures that are relevant in pathophysiological processes. However, one motif found in N-glycans, poly-N-acetyllactosamine (polyLacNAc), still poses a substantial challenge to mass spectrometry-based glycoproteomic analysis due to its relatively low abundance and large size. In this work, we developed approaches for the systematic mapping of polyLacNAc-elongated N-glycans in melanoma cells. We first evaluated five anion exchange-based matrices for enriching intact glycopeptides and selected two materials that provided better overall enrichment efficiency. We then tested the robustness of the methodology by quantifying polyLacNAc-containing glycopeptides as well as changes in protein fucosylation and sialylation. Finally, we applied the optimal enrichment methods to discover glycopeptides containing polyLacNAc motifs in melanoma cells and found that integrins and tetraspanins are substantially modified with these structures. This study demonstrates the feasibility of glycoproteomic approaches for identification of glycoproteins with polyLacNAc motifs.

Decoding the glycoproteome: a new frontier for biomarker discovery in cancer.

Cancer early detection and treatment response prediction continue to pose significant challenges. Cancer liquid biopsies focusing on detecting circulating tumor cells (CTCs) and DNA (ctDNA) have shown enormous potential due to their non-invasive nature and the implications in precision cancer management. Recently, liquid biopsy has been further expanded to profile glycoproteins, which are the products of post-translational modifications of proteins and play key roles in both normal and pathological processes, including cancers. The advancements in chemical and mass spectrometry-based technologies and artificial intelligence-based platforms have enabled extensive studies of cancer and organ-specific changes in glycans and glycoproteins through glycomics and glycoproteomics. Glycoproteomic analysis has emerged as a promising tool for biomarker discovery and development in early detection of cancers and prediction of treatment efficacy including response to immunotherapies. These biomarkers could play a crucial role in aiding in early intervention and personalized therapy decisions. In this review, we summarize the significant advance in cancer glycoproteomic biomarker studies and the promise and challenges in integration into clinical practice to improve cancer patient care.

Combined analysis of secreted proteins and glycosylation identifies prognostic features in cholangiocarcinoma.

Secreted proteins are overexpressed in cholangiocarcinoma (CCA) and actively involved in promoting metastatic spread. Many of these proteins possess one or more sites of glycosylation and their various glycoforms have potential utility as prognostic or diagnostic biomarkers. To evaluate the effects of secretome glycosylation on patient outcome, we elucidated the glycosylation patterns of proteins secreted by parental and metastatic CCA cells using liquid chromatography-mass spectrometry. Our analysis showed that the secretome of CCA cells was dominated by fucosylated and fucosialylated glycoforms. Based on the glycan and protein profiles, we evaluated the combined prognostic significance of glycosyltransferases and secretory proteins. Significantly, genes encoding fucosyltransferases and sialyltransferases showed favorable prognostic effects when combined with secretory protein-coding gene expression, particularly thrombospondin-1. Combining these measures may provide improved risk assessment for CCA and be used to indicate stages of disease progression.

Plasma glycoproteomic biomarkers identify metastatic melanoma patients with reduced clinical benefit from immune checkpoint inhibitor therapy.

The clinical success of immune-checkpoint inhibitors (ICI) in both resected and metastatic melanoma has confirmed the validity of therapeutic strategies that boost the immune system to counteract cancer. However, half of patients with metastatic disease treated with even the most aggressive regimen do not derive durable clinical benefit. Thus, there is a critical need for predictive biomarkers that can identify individuals who are unlikely to benefit with high accuracy so that these patients may be spared the toxicity of treatment without the likely benefit of response. Ideally, such an assay would have a fast turnaround time and minimal invasiveness. Here, we utilize a novel platform that combines mass spectrometry with an artificial intelligence-based data processing engine to interrogate the blood glycoproteome in melanoma patients before receiving ICI therapy. We identify 143 biomarkers that demonstrate a difference in expression between the patients who died within six months of starting ICI treatment and those who remained progression-free for three years. We then develop a glycoproteomic classifier that predicts benefit of immunotherapy (HR=2.7; p=0.026) and achieves a significant separation of patients in an independent cohort (HR=5.6; p=0.027). To understand how circulating glycoproteins may affect efficacy of treatment, we analyze the differences in glycosylation structure and discover a fucosylation signature in patients with shorter overall survival (OS). We then develop a fucosylation-based model that effectively stratifies patients (HR=3.5; p=0.0066). Together, our data demonstrate the utility of plasma glycoproteomics for biomarker discovery and prediction of ICI benefit in patients with metastatic melanoma and suggest that protein fucosylation may be a determinant of anti-tumor immunity.

Serum Glycoprotein Markers in Nonalcoholic Steatohepatitis and Hepatocellular Carcinoma.

Fatty liver disease progresses through stages of fat accumulation and inflammation to nonalcoholic steatohepatitis (NASH), fibrosis and cirrhosis, and eventually hepatocellular carcinoma (HCC). Currently available diagnostic tools for HCC lack sensitivity and specificity. In this study, we investigated the use of circulating serum glycoproteins to identify a panel of potential prognostic markers that may be indicative of progression from the healthy state to NASH and further to HCC. Serum samples were processed and analyzed using a novel high-throughput glycoproteomics platform. Our initial dataset contained healthy, NASH, and HCC serum samples. We analyzed 413 glycopeptides, representing 57 abundant serum proteins, and compared among the three phenotypes. We studied the normalized abundance of common glycoforms and found 40 glycopeptides with statistically significant differences in abundances in NASH and HCC compared to controls. Summary level relative abundances of core-fucosylated, sialylated, and branched glycans containing glycopeptides were higher in NASH and HCC as compared to controls. We replicated some of our findings in an independent set of samples of individuals with benign liver conditions and HCC. Our results may be of value in the management of liver diseases. Data generated in this work can be downloaded from MassIVE (https://massive.ucsd.edu) with identifier MSV000088809.

Aldehyde dehydrogenase 1 (ALDH1) immunostaining in axillary lymph node metastases is an independent prognostic factor in ALDH1-positive breast cancer.

OBJECTIVE: To determine whether aldehyde dehydrogenase 1 (ALDH1) immunostaining in axillary lymph node metastases in patients with breast cancer is associated with poor clinical prognosis. METHODS: This retrospective study reviewed data from the medical records of patients with immunohistochemistry-confirmed invasive ductal carcinoma (IDC) and 1-3 metastatic lymph nodes in the ipsilateral axilla between December 2012 and July 2015. The association between ALDH1 immunostaining in axillary lymph node metastases and clinical parameters and prognosis was analysed using χ2-test, Kaplan-Meier survival analysis, univariate and multivariate Cox regression analyses. RESULTS: A total of 229 patients with IDC were enrolled in the study. The median follow-up was 61 months (range, 20-89 months). Patients with ALDH1-positive axillary lymph node metastases had significantly shorter relapse-free survival and overall survival compared with those with ALDH1-negative axillary lymph node metastases. ALDH1 immunostaining in axillary lymph node metastases was a significant predictor of poor prognosis in univariate and multivariate analyses. CONCLUSION: This large study with long-term follow-up suggests that ALDH1 immunostaining in axillary lymph node metastases is an independent predictor of poor prognosis in patients with breast cancer. The clinical relevance of this finding should be confirmed in further well-designed prospective studies.

Glycan-protein cross-linking mass spectrometry reveals sialic acid-mediated protein networks on cell surfaces.

A cross-linking method is developed to elucidate glycan-mediated interactions between membrane proteins through sialic acids. The method provides information on previously unknown extensive glycomic interactions on cell membranes. The vast majority of membrane proteins are glycosylated with complicated glycan structures attached to the polypeptide backbone. Glycan-protein interactions are fundamental elements in many cellular events. Although significant advances have been made to identify protein-protein interactions in living cells, only modest advances have been made on glycan-protein interactions. Mechanistic elucidation of glycan-protein interactions has thus far remained elusive. Therefore, we developed a cross-linking mass spectrometry (XL-MS) workflow to directly identify glycan-protein interactions on the cell membrane using liquid chromatography-mass spectrometry (LC-MS). This method involved incorporating azido groups on cell surface glycans through biosynthetic pathways, followed by treatment of cell cultures with a synthesized reagent, N-hydroxysuccinimide (NHS)-cyclooctyne, which allowed the cross-linking of the sialic acid azides on glycans with primary amines on polypeptide backbones. The coupled peptide-glycan-peptide pairs after cross-linking were identified using the latest techniques in glycoproteomic and glycomic analyses and bioinformatics software. With this approach, information on the site of glycosylation, the glycoform, the source protein, and the target protein of the cross-linked pair were obtained. Glycoprotein-protein interactions involving unique glycoforms on the PNT2 cell surface were identified using the optimized and validated method. We built the GPX network of the PNT2 cell line and further investigated the biological roles of different glycan structures within protein complexes. Furthermore, we were able to build glycoprotein-protein complex models for previously unexplored interactions. The method will advance our future understanding of the roles of glycans in protein complexes on the cell surface.

Hard antler extract inhibits invasion and epithelial-mesenchymal transition of triple-negative and Her-2+ breast cancer cells by attenuating nuclear factor-κB signaling.

ETHNOPHARMACOLOGICAL RELEVANCE: Hard antler extract (HAE) is a traditional Chinese medicine and has potent antitumor, antioxidative, anti-inflammatory, and immunomodulatory activities. Previous studies have demonstrated that HAE can inhibit human prostate cancer metastasis and murine breast cancer proliferation. However, the effect of HAE on human breast cancer cells has not been clarified. AIM OF THE STUDY: To investigate the effects and underlying mechanism of HAE on self-renewal of stem-like cells and spontaneous and transforming growth factor (TGF)-ß1-enhanced wound healing, invasion and epithelial-mesenchymal transition (EMT) in breast cancer cells. METHODS: HAE was prepared from sika deer by sequential enzymatic digestions and the active compounds were determined by HPLC. The effects of HAE on the viability, mammosphere formation, wound healing and invasion of MDA-MB-231 and SK-BR3 cells were determined. The impact of HAE treatment on spontaneous and TGF-ß1-promoted EMT and the nuclear factor (NF)-κB signaling in breast cancer cells was examined by quantitative RT-PCR and western blotting. RESULTS: Treatment with HAE at varying concentrations did not change the viability of breast cancer cells. However, HAE at 0.25 or 0.5 mg/mL significantly reduced the number and size of formed mammospheres, and inhibited spontaneous and TGF-ß1-enhanced wound healing, invasion and EMT in MDA-MB-231 and SK-BR3 cells in a dose-dependent manner. TGF-ß1 treatment significantly decreased IκBα expression and increased NF-kBp65 phosphorylation in breast cancer cells, indicating that TGF-ß1 enhanced NF-κB signaling. In contrast, HAE treatment attenuated the spontaneous and TGF-ß1-enhanced NF-κB signaling in breast cancer cells. CONCLUSION: Our data indicated that HAE inhibited the self-renewal of stem-like cells and spontaneous and TGF-ß1-enhanced wound healing, invasion and EMT in breast cancer cells by attenuating the NF-κB signaling in vitro.

Indole-3-lactic acid associated with Bifidobacterium-dominated microbiota significantly decreases inflammation in intestinal epithelial cells.

BACKGROUND: Bifidobacterium longum subsp. infantis (B. infantis) is a commensal bacterium that colonizes the gastrointestinal tract of breast-fed infants. B. infantis can efficiently utilize the abundant supply of oligosaccharides found in human milk (HMO) to help establish residence. We hypothesized that metabolites from B. infantis grown on HMO produce a beneficial effect on the host. RESULTS: In a previous study, we demonstrated that B. infantis routinely dominated the fecal microbiota of a breast fed Bangladeshi infant cohort (1). Characterization of the fecal metabolome of binned samples representing high and low B. infantis populations from this cohort revealed higher amounts of the tryptophan metabolite indole-3-lactic acid (ILA) in feces with high levels of B. infantis. Further in vitro analysis confirmed that B. infantis produced significantly greater quantities of the ILA when grown on HMO versus lactose, suggesting a growth substrate relationship to ILA production. The direct effects of ILA were assessed in a macrophage cell line and intestinal epithelial cell lines. ILA (1-10 mM) significantly attenuated lipopolysaccharide (LPS)-induced activation of NF-kB in macrophages. ILA significantly attenuated TNF-α- and LPS-induced increase in the pro-inflammatory cytokine IL-8 in intestinal epithelial cells. ILA increased mRNA expression of the aryl hydrogen receptor (AhR)-target gene CYP1A1 and nuclear factor erythroid 2-related factor 2 (Nrf2)-targeted genes glutathione reductase 2 (GPX2), superoxide dismutase 2 (SOD2), and NAD(P) H dehydrogenase (NQO1). Pretreatment with either the AhR antagonist or Nrf-2 antagonist inhibited the response of ILA on downstream effectors. CONCLUSIONS: These findings suggest that ILA, a predominant metabolite from B. infantis grown on HMO and elevated in infant stool high in B. infantis, and protects gut epithelial cells in culture via activation of the AhR and Nrf2 pathway.

A site-specific map of the human plasma glycome and its age and gender-associated alterations.

Alterations in the human glycome have been associated with cancer and autoimmunity. Thus, constructing a site-specific map of the human glycome for biomarker research and discovery has been a highly sought-after objective. However, due to analytical barriers, comprehensive site-specific glycoprofiling is difficult to perform. To develop a platform to detect easily quantifiable, site-specific, disease-associated glycan alterations for clinical applications, we have adapted the multiple reaction monitoring mass spectrometry method for use in glycan biomarker research. The adaptations allow for highly precise site-specific glycan monitoring with minimum sample prep. Using this technique, we successfully mapped out the relative abundances of the most common 159 glycopeptides in the plasma of 97 healthy volunteers. This plasma glycome map revealed 796 significant (FDR < 0.05) site-specific inter-protein and intra-protein glycan associations, of which the vast majority were previously unknown. Since age and gender are relevant covariants in biomarker research, these variables were also characterized. 13 glycopeptides were found to be associated with gender and 41 to be associated with age. Using just five age-associated glycopeptides, a highly accurate age prediction model was constructed and validated (r2 = 0.62 ± 0.12). The human plasma site-specific glycan map described herein has utility in applications ranging from glycan biomarker research and discovery to the development of novel glycan-altering interventions.

Preparation of ROS-responsive core crosslinked polycarbonate micelles with thioketal linkage.

Herein, we prepared novel reactive oxygen species (ROS) responsive core crosslinked (CCL/TK) polycarbonate micelles conveniently by click reaction between amphiphilic diblock copolymer poly(ethylene glycol)-poly(5-methyl-5-propargylxycar-bonyl-1,3-dioxane-2-one) (PEG-PMPC) with pendant alkynyl group and thioketal containing azide derivative bis (2-azidoethyl) 3, 3'- (propane-2, 2-diylbis (sulfanediyl)) dipropanoate (TK-N3). The CCL/TK micelles were obtained with small size of 146.4 nm, showing excellent stability against dilution and high doxorubicin (DOX) loading. In vitro toxicity tests demonstrated that the obtained CCL/TK micelles have good biocompatibility and low toxicity with cell viability above 95 %. Furthermore, DOX-loaded CCL/TK micelles showed significantly superior toxicity with IC50 values for HeLa and MCF-7 cells about 3.74 µg/mL and 3.91 µg/mL, respectively. Confocal laser scanning microscope (CLSM) and flow cytometry showed excellent internalization efficiency and intracellular drug release of DOX-loaded CCL/TK micelles. The obtained ROS-responsive CCL/TK micelles showed great potential for anticancer drug delivery.

PB-Net: Automatic peak integration by sequential deep learning for multiple reaction monitoring.

Mass spectrometry (MS) based proteomics has become an indispensable component of modern molecular and cellular biochemistry analysis. Multiple reaction monitoring (MRM) is one of the most well-established MS techniques for molecule detection and quantification. Despite its wide usage, there lacks an accurate computational framework to analyze MRM data, and expert annotation is often required, especially to perform peak integration. Here we propose a deep learning method PB-Net (Peak Boundary Neural Network), built upon recent advances in sequential neural networks, for fully automatic chromatographic peak integration. To train PB-Net, we generated a large dataset of over 170,000 expert annotated peaks from MS transitions spanning a wide dynamic range, including both peptides and intact glycopeptides. Our model demonstrated outstanding performances on unseen test samples, reaching near-perfect agreement (Pearson's r 0.997) with human annotated ground truth. Systematic evaluations also show that PB-Net is substantially more robust and accurate compared to previous state-of-the-art peak integration software. PB-Net can benefit the wide community of mass spectrometry data analysis, especially in applications involving high-throughput MS experiments. Codes and test data used in this work are available at https://github.com/miaecle/PB-net. SIGNIFICANCE: Human annotations serve an important role in accurate quantification of multiple reaction monitoring (MRM) experiments, though they are costly to collect and limit analysis throughput. In this work we proposed and developed a novel technique for the peak-integration step in MRM, based on recent innovations in sequential deep learning models. We collected in total 170,000 expert-annotated MRM peaks and trained a set of accurate and robust neural networks for the task. Results demonstrated a substantial improvement over the current state-of-the-art software for mass spectrometry analysis and comparable level of accuracy and precision as human annotators.

Metastasis of cholangiocarcinoma is promoted by extended high-mannose glycans.

Membrane-bound oligosaccharides form the interfacial boundary between the cell and its environment, mediating processes such as adhesion and signaling. These structures can undergo dynamic changes in composition and expression based on cell type, external stimuli, and genetic factors. Glycosylation, therefore, is a promising target of therapeutic interventions for presently incurable forms of advanced cancer. Here, we show that cholangiocarcinoma metastasis is characterized by down-regulation of the Golgi α-mannosidase I coding gene MAN1A1, leading to elevation of extended high-mannose glycans with terminating α-1,2-mannose residues. Subsequent reshaping of the glycome by inhibiting α-mannosidase I resulted in significantly higher migratory and invasive capabilities while masking cell surface mannosylation suppressed metastasis-related phenotypes. Exclusive elucidation of differentially expressed membrane glycoproteins and molecular modeling suggested that extended high-mannose glycosylation at the helical domain of transferrin receptor protein 1 promotes conformational changes that improve noncovalent interaction energies and lead to enhancement of cell migration in metastatic cholangiocarcinoma. The results provide support that α-1,2-mannosylated N-glycans present on cancer cell membrane proteins may serve as therapeutic targets for preventing metastasis.

The DNA repair enzyme MUTYH potentiates cytotoxicity of the alkylating agent MNNG by interacting with abasic sites.

Higher expression of the human DNA repair enzyme MUTYH has previously been shown to be strongly associated with reduced survival in a panel of 24 human lymphoblastoid cell lines exposed to the alkylating agent N-methyl-N'-nitro-N-nitrosoguanidine (MNNG). The molecular mechanism of MUTYH-enhanced MNNG cytotoxicity is unclear, because MUTYH has a well-established role in the repair of oxidative DNA lesions. Here, we show in mouse embryonic fibroblasts (MEFs) that this MNNG-dependent phenotype does not involve oxidative DNA damage and occurs independently of both O6-methyl guanine adduct cytotoxicity and MUTYH-dependent glycosylase activity. We found that blocking of abasic (AP) sites abolishes higher survival of Mutyh-deficient (Mutyh-/-) MEFs, but this blockade had no additive cytotoxicity in WT MEFs, suggesting the cytotoxicity is due to MUTYH interactions with MNNG-induced AP sites. We found that recombinant mouse MUTYH tightly binds AP sites opposite all four canonical undamaged bases and stimulated apurinic/apyrimidinic endonuclease 1 (APE1)-mediated DNA incision. Consistent with these observations, we found that stable expression of WT, but not catalytically-inactive MUTYH, enhances MNNG cytotoxicity in Mutyh-/- MEFs and that MUTYH expression enhances MNNG-induced genomic strand breaks. Taken together, these results suggest that MUTYH enhances the rapid accumulation of AP-site intermediates by interacting with APE1, implicating MUTYH as a factor that modulates the delicate process of base-excision repair independently of its glycosylase activity.

Infection-generated electric field in gut epithelium drives bidirectional migration of macrophages.

Many bacterial pathogens hijack macrophages to egress from the port of entry to the lymphatic drainage and/or bloodstream, causing dissemination of life-threatening infections. However, the underlying mechanisms are not well understood. Here, we report that Salmonella infection generates directional electric fields (EFs) in the follicle-associated epithelium of mouse cecum. In vitro application of an EF, mimicking the infection-generated electric field (IGEF), induces directional migration of primary mouse macrophages to the anode, which is reversed to the cathode upon Salmonella infection. This infection-dependent directional switch is independent of the Salmonella pathogenicity island 1 (SPI-1) type III secretion system. The switch is accompanied by a reduction of sialic acids on glycosylated surface components during phagocytosis of bacteria, which is absent in macrophages challenged by microspheres. Moreover, enzymatic cleavage of terminally exposed sialic acids reduces macrophage surface negativity and severely impairs directional migration of macrophages in response to an EF. Based on these findings, we propose that macrophages are attracted to the site of infection by a combination of chemotaxis and galvanotaxis; after phagocytosis of bacteria, surface electrical properties of the macrophage change, and galvanotaxis directs the cells away from the site of infection.

Site-Specific Glycosylation Quantitation of 50 Serum Glycoproteins Enhanced by Predictive Glycopeptidomics for Improved Disease Biomarker Discovery.

Analysis of serum protein glycovariants has the potential to identify new biomarkers of human disease. However, the inability to rapidly quantify glycans in a site-specific fashion remains the major barrier to applying such biomarkers clinically. Advancements in sample preparation and glycopeptide quantification are thus needed to better bridge glycoscience with biomarker discovery research. We present here the successful utilization of several sample preparation techniques, including multienzyme digestion and glycopeptide enrichment, to increase the repertoire of glycopeptides that can be generated from serum glycoproteins. These techniques combined with glycopeptide retention time prediction and UHPLC-QqQ conditions optimization were then used to develop a dynamic multiple-reaction monitoring (dMRM)-based strategy to simultaneously monitor over 100 glycosylation sites across 50 serum glycoproteins. In total, the abundances of over 600 glycopeptides were simultaneously monitored, some of which were identified by utilizing theoretically predicted ion products and presumed m/ z values. The dMRM method was found to have good sensitivity. In the targeted dMRM mode, the limit of quantitation (LOQ) of nine standard glycoproteins reached femtomole levels with dynamic ranges spanning 3-4 orders of magnitude. The dMRM-based strategy also showed high reproducibility with regards to both instrument and sample preparation performance. The high coverage of the serum glycoproteins that can be quantitated to the glycopeptide level makes this method especially suitable for the biomarker discovery from large sample sets. We predict that, in the near future, biomarkers, such as these, will be deployed clinically, especially in the fields of cancer and autoimmunity.

FGF2 Induces Migration of Human Bone Marrow Stromal Cells by Increasing Core Fucosylations on N-Glycans of Integrins.

Since hundreds of clinical trials are investigating the use of multipotent stromal cells (MSCs) for therapeutic purposes, effective delivery of the cells to target tissues is critical. We have found an unexplored mechanism, by which basic fibroblast growth factor (FGF2) induces expression of fucosyltransferase 8 (FUT8) to increase core fucosylations of N-linked glycans of membrane-associated proteins, including several integrin subunits. Gain- and loss-of-function experiments show that FUT8 is both necessary and sufficient to induce migration of MSCs. Silencing FUT8 also affects migration of MSCs in zebrafish embryos and a murine bone fracture model. Finally, we use in silico modeling to show that core fucosylations restrict the degrees of freedom of glycans on the integrin's surface, hence stabilizing glycans on a specific position. Altogether, we show a mechanism whereby FGF2 promotes migration of MSCs by modifying N-glycans. This work may help improve delivery of MSCs in therapeutic settings.

Intact glycosphingolipidomic analysis of the cell membrane during differentiation yields extensive glycan and lipid changes.

Glycosphingolipids (GSLs) are found in cellular membranes of most organisms and play important roles in cell-cell recognition, signaling, growth, and adhesion, among others. A method based on nanoflow high performance liquid chromatography-chip-quadrupole-time-of-flight mass spectrometry (nanoHPLC Chip-Q-TOF MS) was applied towards identifying and quantifying intact GSLs from a variety of samples, including cultured cell lines and animal tissue. The method provides the composition and sequence of the glycan, as well as variations in the ceramide portion of the GSL. It was used to profile the changes in the glycolipidome of Caco-2 cells as they undergo differentiation. A total of 226 unique GSLs were found among Caco-2 samples from five differentiation time-points. The method provided a comprehensive glycolipidomic profile of a cell during differentiation to yield the dynamic variation of intact GSL structures.