Sirt3-Mediated Opa1 Deacetylation Protects Against Sepsis-Induced Acute Lung Injury by Inhibiting Alveolar Macrophage Pro-Inflammatory Polarization.

Aims: Mitochondrial dynamics in alveolar macrophages (AMs) are associated with sepsis-induced acute lung injury (ALI). In this study, we aimed to investigate whether changes in mitochondrial dynamics could alter the polarization of AMs in sepsis-induced ALI and to explore the regulatory mechanism of mitochondrial dynamics by focusing on sirtuin (SIRT)3-induced optic atrophy protein 1 (OPA1) deacetylation. Results: The AMs of sepsis-induced ALI showed imbalanced mitochondrial dynamics and polarization to the M1 macrophage phenotype. In sepsis, SIRT3 overexpression promotes mitochondrial dynamic equilibrium in AMs. However, 3-(1H-1, 2, 3-triazol-4-yl) pyridine (3TYP)-specific inhibition of SIRT3 increased the mitochondrial dynamic imbalance and pro-inflammatory polarization of AMs and further aggravated sepsis-induced ALI. OPA1 is directly bound to and deacetylated by SIRT3 in AMs. In AMs of sepsis-induced ALI, SIRT3 protein expression was decreased and OPA1 acetylation was increased. OPA1 acetylation at the lysine 792 amino acid residue (OPA1-K792) promotes self-cleavage and is associated with an imbalance in mitochondrial dynamics. However, decreased acetylation of OPA1-K792 reversed the pro-inflammatory polarization of AMs and protected the barrier function of alveolar epithelial cells in sepsis-induced ALI. Innovation: Our study revealed, for the first time, the regulation of mitochondrial dynamics and AM polarization by SIRT3-mediated deacetylation of OPA1 in sepsis-induced ALI, which may serve as an intervention target for precision therapy of the disease. Conclusions: Our data suggest that imbalanced mitochondrial dynamics promote pro-inflammatory polarization of AMs in sepsis-induced ALI and that deacetylation of OPA1 mediated by SIRT3 improves mitochondrial dynamic equilibrium, thereby ameliorating lung injury.

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.

PROMOTING MITOCHONDRIAL DYNAMIC EQUILIBRIUM ATTENUATES SEPSIS-INDUCED ACUTE LUNG INJURY BY INHIBITING PROINFLAMMATORY POLARIZATION OF ALVEOLAR MACROPHAGES.

ABSTRACT: Sepsis-induced acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) is characterized by widespread pulmonary inflammation and immune response, in which proinflammatory polarization of alveolar macrophages (AMs) plays an important role. Mitochondria are the key intracellular signaling platforms regulating immune cell responses. Moreover, accumulating evidence suggests that the mitochondrial dynamics of macrophages are imbalanced in sepsis and severe ALI/ARDS. However, the functional significance of mitochondrial dynamics of AMs in septic ALI/ARDS remains largely unknown, and whether it regulates the polarized phenotype of AMs is also unclear. Here, we demonstrated that the mitochondrial dynamics of AMs are imbalanced, manifested by impaired mitochondrial fusion, increased fission and mitochondrial cristae remodeling, both in septic models and ARDS patients. However, suppressing excessive mitochondrial fission with Mdivi-1 or promoting mitochondrial fusion with PM1 to maintain mitochondrial dynamic equilibrium in AMs could inhibit the polarization of AMs into proinflammatory phenotype and attenuate sepsis-induced ALI. These data suggest that mitochondrial dynamic imbalance mediates altered polarization of AMs and exacerbates sepsis-induced ALI. This study provides new insights into the underlying mechanisms of sepsis-induced ALI, suggesting the possibility of identifying future drug targets from the perspective of mitochondrial dynamics in AMs.

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.

GlycoNote with Iterative Decoy Searching and Open-Search Component Analysis for High-Throughput and Reliable Glycan Spectral Interpretation.

Mass spectrometry-based glycome analysis is a viable strategy for the compositional and functional exploration of glycosylation. However, the lack of generic tools for high-throughput and reliable glycan spectral interpretation largely hampers the broad usability of glycomic research. Here, we developed a generic and reliable glycomic tool, GlycoNote, for comprehensive and precise glycome analysis. GlycoNote supports interpretation of tandem-mass spectrometry glycomic data from any sample source, uses a novel target-decoy method with iterative decoy searching for highly reliable result output, and embeds an open-search component analysis mode for heterogeneity analysis of monosaccharides and modifications. We tested GlycoNote on several different large-scale glycomic datasets, including human milk oligosaccharides, N- and O-glycome from human cell lines, plant polysaccharides, and atypical glycans from Caenorhabditis elegans, demonstrating its high capacity for glycome analysis. An application of GlycoNote to the analysis of labeled and derived glycans further demonstrates its broad usability in glycomic studies. By enabling generic characterization of various glycan types and elucidation of component heterogeneity in glycomic samples, the freely available GlycoNote is a promising tool for facilitating glycomics in glycobiology research.

Study of Anticorrosion and Antifouling Properties of a Cu-Doped TiO2 Coating Fabricated via Micro-Arc Oxidation.

As a promising material for petroleum industrial applications, titanium (Ti) and its alloys receive wide attention due to their outstanding physicochemical properties. However, the harsh industrial environment requires an antifouling surface with a desired corrosion resistance for Ti and its alloys. In order to achieve the desired antifouling properties, micro-arc oxidation (MAO) was used to prepare a Cu-doped TiO2 coating. The microstructure of the Cu-doped TiO2 coating was investigated by TF-XRD, SEM, and other characterization techniques, and its antifouling and anticorrosion properties were also tested. The results show the effects of the incorporation of Cu (~1.73 wt.%) into TiO2 to form a Cu-doped TiO2, namely, a Ti-Cu coating. The porosity (~4.8%) and average pore size (~0.42 µm) of the Ti-Cu coating are smaller than the porosity (~5.6%) and average pore size (~0.66 µm) of Ti-blank coating. In addition, there is a significant reduction in the amount of SRB adhesion on the Ti-Cu coating compared to the Ti-blank coating under the same conditions, while there is little difference in corrosion resistance between the two coatings. There, the addition of copper helps to improve the fouling resistance of TiO2 coatings without compromising their corrosion resistance. Our work provides a practical method to improve the antifouling function of metallic Ti substrates, which could promote the application of Ti in the petroleum industry.

Differential Peripheral Blood Glycoprotein Profiles in Symptomatic and Asymptomatic COVID-19.

Glycosylation is the most common form of post-translational modification of proteins, critically affecting their structure and function. Using liquid chromatography and mass spectrometry for high-resolution site-specific quantification of glycopeptides coupled with high-throughput artificial intelligence-powered data processing, we analyzed differential protein glycoisoform distributions of 597 abundant serum glycopeptides and nonglycosylated peptides in 50 individuals who had been seriously ill with COVID-19 and in 22 individuals who had recovered after an asymptomatic course of COVID-19. As additional comparison reference phenotypes, we included 12 individuals with a history of infection with a common cold coronavirus, 16 patients with bacterial sepsis, and 15 healthy subjects without history of coronavirus exposure. We found statistically significant differences, at FDR < 0.05, for normalized abundances of 374 of the 597 peptides and glycopeptides interrogated between symptomatic and asymptomatic COVID-19 patients. Similar statistically significant differences were seen when comparing symptomatic COVID-19 patients to healthy controls (350 differentially abundant peptides and glycopeptides) and common cold coronavirus seropositive subjects (353 differentially abundant peptides and glycopeptides). Among healthy controls and sepsis patients, 326 peptides and glycopeptides were found to be differentially abundant, of which 277 overlapped with biomarkers that showed differential expression between symptomatic COVID-19 cases and healthy controls. Among symptomatic COVID-19 cases and sepsis patients, 101 glycopeptide and peptide biomarkers were found to be statistically significantly abundant. Using both supervised and unsupervised machine learning techniques, we found specific glycoprotein profiles to be strongly predictive of symptomatic COVID-19 infection. LASSO-regularized multivariable logistic regression and K-means clustering yielded accuracies of 100% in an independent test set and of 96% overall, respectively. Our findings are consistent with the interpretation that a majority of glycoprotein modifications observed which are shared among symptomatic COVID-19 and sepsis patients likely represent a generic consequence of a severe systemic immune and inflammatory state. However, there are glycoisoform changes that are specific and particular to severe COVID-19 infection. These may be representative of either COVID-19-specific consequences or susceptibility to or predisposition for a severe course of the disease. Our findings support the potential value of glycoproteomic biomarkers in the biomedical understanding and, potentially, the clinical management of serious acute infectious conditions.

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.

The glycoproteomics of hawk and caiman tears.

BACKGROUND: Glycoproteins are important tear components that participate in the stability of the ocular surface. However, the glycopeptides that are present in the tears of wild animals have not yet been described. This work aimed to describe the glycoproteomic profile of roadside hawk (Rupornis magnirostris) and caiman (Caiman latirostris) tears. METHODS: Tears collected from 10 hawks and 70 caimans using Schirmer tear test strips were used in this study. The samples were submitted to trypsin digestion and separated using a reverse-phase column coupled to a mass spectrometer associated to a nanospray ionization source. The glycoproteins were categorized as: cellular components, biological processes and molecular function, according to the UniProt Knowledgebase. RESULTS: As shown by the liquid chromatography-mass spectrometry, all glycopeptides found were classified as N-type. Of the 51 glycoproteins that were identified in the hawk tear film, the most abundant were ovotransferrin, globulins and complement system proteins. In the caiman tear film, 29 glycoproteins were identified. The most abundant caiman glycoproteins were uncharacterized proteins, ATPases, globulins and proteasome components. Ontological characterization revealed that the glycoproteins were extracellular, and the most identified molecular function was endopeptidase activity for both species. CONCLUSION: Glycoproteins are abundant in the tear film of the bird and reptile species studied herein, and all these molecules were shown to have N-type modifications. Location at the extracellular space and an endopeptidase inhibitor activity were the main cell component and molecular function for both species, respectively. These profiles showed differences when compared to human tears, are possibly linked to adaptive processes and can be the basis for further studies on the search of disease biomarkers.

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 biomarkers of autoimmunity and bile acid-associated alterations of the human glycome: Primary biliary cirrhosis and primary sclerosing cholangitis-specific glycans.

We have recently introduced multiple reaction monitoring (MRM) mass spectrometry as a novel tool for glycan biomarker research and discovery. Herein, we employ this technique to characterize the site-specific glycan alterations associated with primary biliary cirrhosis (PBC) and primary sclerosing cholangitis (PSC). Glycopeptides associated with disease severity were also identified. Multinomial regression modelling was employed to construct and validate multi-analyte diagnostic models capable of accurately distinguishing PBC, PSC, and healthy controls from one another (AUC = 0.93 ± 0.03). Finally, to investigate how disease-relevant environmental factors can influence glycosylation, we characterized the ability of bile acids known to be differentially expressed in PBC to alter glycosylation. We hypothesize that this could be a mechanism by which altered self-antigens are generated and become targets for immune attack. This work demonstrates the utility of the MRM method to identify diagnostic site-specific glycan classifiers capable of distinguishing even related autoimmune diseases from one another.

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.

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

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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.