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Sphingolipids are an essential subset of bioactive lipids found in most eukaryotic cells that contribute to membrane biophysical properties and are involved in cellular differentiation, recognition, and mediating interactions. The described nanoHPLC-ESI-Q/ToF methodology utilizes known biosynthetic pathways, accurate mass detection, optimized collision-induced disassociation, and a robust nanoflow chromatographic separation for the analysis of intact sphingolipids found in human tissue, cells, and serum. The methodology was developed and validated with an emphasis on addressing the common issues experienced in profiling these amphipathic lipids, which are part of the glycocalyx and lipidome. The high sensitivity obtained using nanorange flow rates with robust chromatographic reproducibility over a wide range of concentrations and injection volumes results in confident identifications for profiling these low-abundant biomolecules.

Short-chain fatty acids (SCFAs) comprise the largest group of gut microbial fermentation products. While absorption of most nutrients occurs in the small intestine, indigestible dietary components, such as fiber, reach the colon and are processed by the gut microbiome to produce a wide array of metabolites that influence host physiology. Numerous studies have implicated SCFAs as key modulators of host health, such as in regulating irritable bowel syndrome (IBS). However, robust methods are still required for their detection and quantitation to meet the demands of biological studies probing the complex interplay of the gut-host-health paradigm. In this study, a sensitive, rapid-throughput, and readily expandible UHPLC-QqQ-MS platform using 2-PA derivatization was developed for the quantitation of gut-microbially derived SCFAs, related metabolites, and isotopically labeled homologues. The utility of this platform was then demonstrated by investigating the production of SCFAs in cecal contents from mice feeding studies, human fecal bioreactors, and fecal/bacterial fermentations of isotopically labeled dietary carbohydrates. Overall, the workflow proposed in this study serves as an invaluable tool for the rapidly expanding gut-microbiome and precision nutrition research field.

Glycogen is a highly branched biomacromolecule that functions as a glucose buffer. It is involved in multiple diseases such as glycogen storage disorders, diabetes, and even liver cancer, where the imbalance between biosynthetic and catabolic enzymes results in structural alterations and abnormal accumulation of glycogen that can be toxic to cells. Accurate and sensitive glycogen quantification and structural determination are prerequisites for understanding the phenotypes and biological functions of glycogen under these conditions. In this research, we furthered cell glycogen characterization by presenting a highly sensitive method to measure the glycogen content and degree of branching. The method employed a novel fructose density gradient as an alternative to the traditional sucrose gradient to fractionate glycogen from cell mixtures using ultracentrifugation. Fructose was used to avoid the large glucose background, allowing the method to be highly quantitative. The glycogen content was determined by quantifying 1-phenyl-3-methyl-5-pyrazolone (PMP)-derivatized glucose residues obtained from acid-hydrolyzed glycogen using ultra-high-performance liquid chromatography/triple quadrupole mass spectrometry (UHPLC/QqQ-MS). The degree of branching was determined through linkage analysis where the glycogen underwent permethylation, hydrolysis, PMP derivatization, and UHPLC/QqQ-MS analysis. The new approach was used to study the effect of insulin on the glycogen phenotypes of human hepatocellular carcinoma (Hep G2) cells. We observed that cells produced greater amounts of glycogen with less branching under increasing insulin levels before reaching the cell's insulin-resistant state, where the trend reversed and the cells produced less but higher-branched glycogen. The advantage of this method lies in its high sensitivity in characterizing both the glycogen level and the structure of biological samples.

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.

Glycoproteins are an underexploited drug target for cancer therapeutics. In this work, we integrated computational methods in network pharmacology and in silico docking approaches to identify phytochemical compounds that could potentially interact with several cancer-associated glycoproteins. We first created a database of phytochemicals from selected plant species, Manilkara zapota (sapodilla/chico), Mangifera indica (mango), Annona muricata (soursop/guyabano), Artocarpus heterophyllus (jackfruit/langka), Lansium domesticum (langsat/lanzones), and Antidesma bunius (bignay), and performed pharmacokinetic analysis to determine their drug-likeness properties. We then constructed a phytochemical-glycoprotein interaction network and characterized the degree of interactions between the phytochemical compounds and with cancer-associated glycoproteins and other glycosylation-related proteins. We found a high degree of interactions from α-pinene ( Mangifera indica ), cyanomaclurin ( Artocarpus heterophyllus ), genistein ( Annona muricata ), kaempferol ( Annona muricata and Antidesma bunius ), norartocarpetin ( Artocarpus heterophyllus ), quercetin ( Annona muricata , Antidesma bunius , Manilkara zapota , Mangifera indica ), rutin ( Annona muricata , Antidesma bunius , Lansium domesticum ), and ellagic acid ( Antidesma bunius and Mangifera indica ). Subsequent docking analysis confirmed that these compounds could potentially bind to EGFR, AKT1, KDR, MMP2, MMP9, ERBB2, IGF1R, MTOR, and HRAS proteins, which are known cancer biomarkers. In vitro cytotoxicity assays of the plant extracts showed that the n -hexane, ethyl acetate, and methanol leaf extracts from A. muricata , L. domesticum and M. indica gave the highest growth inhibitory activity against A549 lung cancer cells. These may help further explain the reported cytotoxic activities of select compounds from these plant species., Competing Interests: The authors declare no competing financial interest., (© 2023 The Authors. Published by American Chemical Society.)

Carbohydrates are the most abundant biomolecules in nature, and specifically, polysaccharides are present in almost all plants and fungi. Due to their compositional diversity, polysaccharide analysis remains challenging. Compared to other biomolecules, high-throughput analysis for carbohydrates has yet to be developed. To address this gap in analytical science, we have developed a multiplexed, high-throughput, and quantitative approach for polysaccharide analysis in foods. Specifically, polysaccharides were depolymerized using a nonenzymatic chemical digestion process followed by oligosaccharide fingerprinting using high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (HPLC-QTOF-MS). Both label-free relative quantitation and absolute quantitation were done based on the abundances of oligosaccharides produced. Method validation included evaluating recovery for a range of polysaccharide standards and a breakfast cereal standard reference material. Nine polysaccharides (starch, cellulose, β-glucan, mannan, galactan, arabinan, xylan, xyloglucan, chitin) were successfully quantitated with sufficient accuracy (5-25% bias) and high reproducibility (2-15% CV). Additionally, the method was used to identify and quantitate polysaccharides from a diverse sample set of food samples. Absolute concentrations of nine polysaccharides from apples and onions were obtained using an external calibration curve, where varietal differences were observed in some of the samples. The methodology developed in this study will provide complementary polysaccharide-level information to deepen our understanding of the interactions of dietary polysaccharides, gut microbial community, and human health.

Dietary fiber has long been known to be an essential component of a healthy diet, and recent investigations into the gut microbiome-health paradigm have identified fiber as a prime determinant in this interaction. Further, fiber is now known to impact the gut microbiome in a structure-specific manner, conferring differential bioactivities to these specific structures. However, current analytical methods for food carbohydrate analysis do not capture this important structural information. To address this need, we utilized rapid-throughput LC-MS methods to develop a novel analytical pipeline to determine the structural composition of soluble and insoluble fiber fractions from two AOAC methods (991.43 and 2017.16) at the total monosaccharide, glycosidic linkage, and free saccharide level. Two foods were chosen for this proof-of-concept study: oats and potato starch. For oats, both AOAC methods gave similar results. Insoluble fiber was found to be comprised of linkages corresponding to β-glucan, arabinoxylan, xyloglucan, and mannan, while soluble fiber was found to be mostly β-glucan, with small amounts of arabinogalactan. For raw potato starch, each AOAC method gave markedly different results in the soluble fiber fractions. These observed differences are attributable to the resistant starch content of potato starch and the different starch digestion conditions used in each method. Together, these tools are a means to obtain the complex structures present within dietary fiber while retaining "classical" determinations such as soluble and insoluble fiber. These efforts will provide an analytical framework to connect gravimetric fiber determinations with their constituent structures to better inform gut microbiome and clinical nutrition studies.

Aberrant glycosylation has been extensively reported in cancer, with fundamental changes in the glycosylation patterns of cell-surface and secreted proteins largely occurring during cancer progression. As such, serum glycan and glycopeptide biomarkers have been discovered using mass spectrometry and proposed for cancer detection. Here, we report for the first time potential serum N -glycan and glycopeptide biomarkers for Philippine lung cancer patients. The N -glycan and glycoprotein profiles of a cohort ( n = 26 patients, n = 22 age- and gender-matched) of lung cancer patients were analyzed and compared to identify potential N -glycan and glycopeptide serum biomarkers using nano-QToF-MS/MS and ultra-high-performance liquid chromatography coupled with triple quadrupole mass spectrometry dynamic multiple monitoring methods, respectively. Statistical analyses identified differential N -glycan and glycopeptide abundances. The N -glycans were mostly sialylated and sialofucosylated branched structures. The glycopeptides involved proteins in complement and coagulation cascades ( p adj = 6.418 × 10 -4 ), innate immunity ( p adj = 6.094 × 10 -3 ), acute inflammatory response ( p adj = 6.404 × 10 -5 ), defense response ( p adj = 2.082 × 10 -4 ), complement activation pathways ( p adj = 1.895 × 10 -2 ), and immunoglobulin-mediated immune response pathways ( p adj = 4.818 × 10 -2 ). Biomarker models were constructed using serum N -glycans [area under the curve (AUC) = 0.775; 95% CI: 0.617-0.931] and glycopeptides (AUC = 0.959; 95% CI: 0.85-1.0), with glycopeptides having higher accuracies than N -glycans. The results suggest that in the Philippine lung cancer patient sera, specific N -glycans and site-specific glycans are differentially expressed between cases and controls. This report represents the first serum glycan and glycopeptide biomarkers of Philippine lung cancer patients, further demonstrating the utility of mass spectrometry-based glycomic and glycoproteomic methods., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)

Prenatal plus postnatal small-quantity lipid-based nutrient supplements (SQ-LNS) improved child growth at 18 months in the International Lipid-Based Nutrient Supplements DYAD trial in Ghana. In this secondary outcome analysis, we determined whether SQ-LNS versus prenatal iron and folic acid (IFA) supplementation improves the cholesterol efflux capacity (CEC) of high-density lipoprotein (HDL) particles and alters their lipidomic, proteomic, or glycoproteomic composition in a subset of 80 children at 18 months of age. HDL CEC was higher among children in the SQ-LNS versus IFA group (20.9 ± 4.1 vs 19.4 ± 3.3%; one-tailed p = 0.038). There were no differences in HDL lipidomic or proteomic composition between groups. Twelve glycopeptides out of the 163 analyzed were significantly altered by SQ-LNS, but none of the group differences remained significant after correction for multiple testing. Exploratory analysis showed that 6 out of the 33 HDL-associated proteins monitored differed in glycopeptide enrichment between intervention groups, and 6 out of the 163 glycopeptides were correlated with CEC. We conclude that prenatal plus postnatal SQ-LNS may modify HDL protein glycoprofiles and improve the CEC of HDL particles in children, which may have implications for subsequent child health outcomes. This trial was registered at clinicaltrials.gov as NCT00970866., Competing Interests: The authors declare no competing financial interest., (© 2021 The Authors. Published by American Chemical Society.)

Proteins on cell membrane are modified by N- and O-glycans. N-Glycans have been extensively characterized using advanced separation and mass spectrometry techniques. However, O-glycans remain a challenge, because of the lack of universal enzymes to release them and the large background abundances of N-glycans. Here, we report a method for in-depth structural analysis and quantitation of O-glycans derived from human cell membrane. O-Glycans were chemically released from isolated cell membrane glycoproteins following N-glycan and lipid/glycolipid removal by PNGase F digestion and Folch extraction, respectively. Released O-glycans were purified by an optimized protocol to eliminate interference from small molecules and degraded proteins. Cell surface O-glycans were then analyzed using a nanoLC-chip-QTOF mass spectrometer with a porous graphitized carbon (PGC) column, while the N-glycans and glycolipids isolated from the same cell membrane fractions were analyzed in parallel using previously reported methods. The monosaccharide compositions and linkages of the detected O-glycans were identified by exoglycosidase digestion facilitated with tandem mass spectrometry (MS/MS). Using this method, we identified 44 cell membrane O-glycan isomers with MS/MS, and, among them, we unambiguously characterized 25 O-glycan structures with exoglycosidase digestion to create a library with their complete structures, accurate masses, and retention times. In this process, we identified and characterized unexpected mannose oligomers that are α(1-2/3) linked. This library enabled the identification and quantification of unique cell surface O-glycans from different cell lines and the study of specific O-glycan changes during cell differentiation.

Since high-density lipoprotein (HDL) glycoprofiles are associated with HDL functional capacity, we set out to determine whether diet can alter the glycoprofiles of key HDL-associated proteins, including ApoE, a potent driver of chronic disease risk. Ten healthy subjects consumed a fast food (FF) and a Mediterranean (Med) diet for 4 days in randomized order, with a 4-day wash-out between treatments. A multiple reaction monitoring method was used to characterize the site-specific glycoprofiles of HDL proteins, and HDL functional capacity was analyzed. We describe for the first time that ApoE has 7 mucin-type O-glycosylation sites, which were not affected by short-term diet. The glycoprofiles of other HDL-associated proteins were also unaffected, except that a disialylated ApoC-III glycan was enriched after Med diet, and a nonsialylated ApoC-III glycan was enriched after FF diet. Twenty-five individual glycopeptides were significantly correlated with cholesterol efflux capacity and 21 glycopeptides were correlated with immunomodulatory capacity. Results from this study indicate that the glycoprofiles of HDL-associated proteins including ApoE are correlated with HDL functional capacity but generally unaffected by diet in the short term, except ApoC-III sialylation. These results suggest that HDL protein glycoprofiles are affected by both acute and long-term factors and may be useful for biomarker discovery.

The extensive characterization of glycosidic linkages in carbohydrates remains a challenge because of the lack of known standards and limitations in current analytical techniques. This study encompasses the construction of an extensive glycosidic linkage library built from synthesized standards. It includes an improved liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the quantitation of glycosidic linkages derived from disaccharides, oligosaccharides, and polysaccharides present in complicated matrices. We present a method capable of the simultaneous identification of over 90 unique glycosidic linkages using ultrahigh-performance liquid chromatography coupled with triple quadrupole mass spectrometry (UHPLC/QqQ MS) operated in dynamic multiple reaction monitoring (dMRM) mode. To build the library, known monosaccharides commonly found in plants were subjected to partial methylation to yield partially derivatized species representing trisecting, bisecting, linear, and terminal structures. The library includes glycosidic linkage information for three hexoses (glucose, galactose, and mannose), three pentoses (xylose, arabinose, and ribose), two deoxyhexoses (fucose and rhamnose), and two hexuronic acids (glucuronic acid and galacturonic acid). The resulting partially methylated monosaccharides were then labeled with 1-phenyl-3-methyl-5-pyrazolone (PMP) followed by separation and analysis by UHPLC/dMRM MS. Validation of the synthesized standards was performed using disaccharide, oligosaccharide, and polysaccharide standards. Accuracy, reproducibility, and robustness of the method was demonstrated by analysis of xyloglucan (tamarind) and whole carrot root. The synthesized standards represent the most comprehensive group of carbohydrate linkages to date.

The recruitment of a bacterial consortium by the host is a strategy not limited to animals but is also used in plants. A maize aerial root mucilage has been found that harbors nitrogen fixing bacteria that are attracted to the carbohydrate rich environment. This synbiotic relationship is facilitated by a polysaccharide, whose complicated structure has been previously unknown. In this report, we present the characterization of the maize polysaccharide by employing new analytical strategies combining chemical depolymerization, oligosaccharide sequencing, and monosaccharide and glycosidic linkage quantitation. The mucilage contains a single heterogeneous polysaccharide composed of a highly fucosylated and xylosylated galactose backbone with arabinan and mannoglucuronan branches. This unique polysaccharide structure may select for the diazotrophic community by containing monosaccharides and linkages that correspond to the glycosyl hydrolases associated with the microbial community. The elucidation of this complicated structure illustrates the power of the analytical methods, which may serve as a general platform for polysaccharide analysis in the future.

Carbohydrates make up the largest component of plant-based foods and have long been known to provide fuel. However, many carbohydrates possess intrinsic biological activities that are dictated by their structures. Carbohydrates are the most abundant biopolymers in nature and are also the most structurally complicated and diverse. Consequently, the structural analysis of carbohydrates remains severely limited. To further understand their biological activities, we need new analytical tools to analyze the different classes of carbohydrates that range in size from monosaccharides to polysaccharides. These tools must be capable of rapid throughput with highly sensitive quantitation for use in clinical studies that probe their fate in human and animal fluids and tissues.

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.

The structural analysis of carbohydrates remains challenging mainly due to the lack of rapid analytical methods able to determine and quantitate glycosidic linkages between the diverse monosaccharides found in natural oligosaccharides and polysaccharides. In this research, we present the first liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based method for the rapid and simultaneous relative quantitation of glycosidic linkages for oligosaccharide and polysaccharide characterization. The method developed employs ultrahigh-performance liquid chromatography coupled with triple quadrupole mass spectrometry (UHPLC/QqQ-MS) analysis performed in multiple reaction monitoring (MRM) mode. A library of 22 glycosidic linkages was built using commercial oligosaccharide standards. Permethylation and hydrolysis conditions along with LC-MS/MS parameters were optimized resulting in a workflow requiring only 50 μg of substrate for the analysis. Samples were homogenized, permethylated, hydrolyzed, and then derivatized with 1-phenyl-3-methyl-5-pyrazolone (PMP) prior to analysis by UHPLC/MRM-MS. Separation by C18 reversed-phase UHPLC along with the simultaneous monitoring of derivatized terminal, linear, bisecting, and trisecting monosaccharide linkages by mass spectrometry is achieved within a 15 min run time. Reproducibility, efficacy, and robustness of the method was demonstrated with galactan ( Lupin) and polysaccharides within food such as whole carrots. The speed and specificity of the method enables its application toward the rapid glycosidic linkage analysis of oligosaccharides and polysaccharides.

Glycomic and glycoproteomic analyses involve the characterization of oligosaccharides (glycans) conjugated to proteins. Glycans are produced through a complicated nontemplate driven process involving the competition of enzymes that extend the nascent chain. The large diversity of structures, the variations in polarity of the individual saccharide residues, and the poor ionization efficiencies of glycans all conspire to make the analysis arguably much more difficult than any other biopolymer. Furthermore, the large number of glycoforms associated with a specific protein site makes it more difficult to characterize than any post-translational modification. Nonetheless, there have been significant progress, and advanced separation and mass spectrometry methods have been at its center and the main reason for the progress. While glycomic and glycoproteomic analyses are still typically available only through highly specialized laboratories, new software and workflow is making it more accessible. This review focuses on the role of mass spectrometry and separation methods in advancing glycomic and glycoproteomic analyses. It describes the current state of the field and progress toward making it more available to the larger scientific community.

High density lipoprotein (HDL) particles are believed to be protective due to their inverse correlation with the prevalence of cardiovascular diseases. However, recent studies show that in some conditions such as heart disease and diabetes, HDL particles can become dysfunctional. Great attention has been directed toward HDL particle composition because the relative abundances of HDL constituents determine HDL's functional properties. A key factor to consider when studying the structure and composition of plasma particles is the protein glycosylation. Here, we profile the O- and N-linked glycosylation of HDL associated-proteins including the truncated form of Apo CIII and their glycan heterogeneity in a site-specific manner. Apolipoprotein CIII, fetuin A, and alpha 1 antitrypsin are glycoproteins associated with lipoproteins and are implicated in many cardiovascular and other disease conditions. A targeted method (UHPLC-QQQ) was used to measure the glycoprotein concentrations and site-specific glycovariations of the proteins in human plasma and compared with HDL particles isolated from the same plasma samples. The proteins found in the plasma are differentially glycosylated compared to those isolated in HDL. The results of this study suggest that glycosylation may play a role in protein partitioning in the blood, with possible functional implications.

Protein glycosylation fingerprints are widely recognized as potential markers for disease states, and indeed differential glycosylation has been identified in multiple types of autoimmune diseases and several types of cancer. However, releasing the glycans leave the glycoproteins unknown; therefore, there exists a need for high-throughput methods that allow quantification of site- and protein-specific glycosylation patterns from complex biological mixtures. In this study, a targeted multiple reaction monitoring (MRM)-based method for the protein- and site-specific quantitation involving serum proteins immunoglobulins A, G and M, alpha-1-antitrypsin, transferrin, alpha-2-macroglobulin, haptoglobin, alpha-1-acid glycoprotein and complement C3 was developed. The method is based on tryptic digestion of serum glycoproteins, followed by immediate reverse phase UPLC-QQQ-MS analysis of glycopeptides. To quantitate protein glycosylation independent of the protein serum concentration, a nonglycosylated peptide was also monitored. Using this strategy, 178 glycopeptides and 18 peptides from serum glycoproteins are analyzed with good repeatability (interday CVs of 3.65-21-92%) in a single 17 min run. To assess the potential of the method, protein glycosylation was analyzed in serum samples from ovarian cancer patients and controls. A training set consisting of 40 cases and 40 controls was analyzed, and differential analyses were performed to identify aberrant glycopeptide levels. All findings were validated in an independent test set (n = 44 cases and n = 44 controls). In addition to the differential glycosylation on the immunoglobulins, which was reported previously, aberrant glycosylation was also observed on each of the glycoproteins, which could be corroborated in the test set. This report shows the development of a method for targeted protein- and site-specific glycosylation analysis and the potential of such methods in biomarker development.

Ovarian cancer is a major cause of cancer mortality among women, largely due to late diagnosis of advanced metastatic disease. More extensive molecular analysis of metastatic ovarian cancer is needed to identify post-translational modifications of proteins, especially glycosylation that is particularly associated with metastatic disease to better understand the metastatic process and identify potential therapeutic targets. Glycoproteins in ascites fluid were enriched by affinity binding to lectins (ConA or WGA) and other affinity matrices. Separate glycomic, proteomic, and glycopeptide analyses were performed. Relative abundances of different N-glycan groups and proteins were identified from ascites fluids and a serum control. Levels of biomarkers CA125, MUC1, and fibronectin were also monitored in OC ascites samples by Western blot analysis. N-Glycan analysis of ascites fluids showed the presence of large, highly fucosylated and sialylated complex and hybrid glycans, some of which were not observed in normal serum. OC ascites glycoproteins, haptoglobin, fibronectin, lumican, fibulin, hemopexin, ceruloplasmin, alpha-1-antitrypsin, and alpha-1-antichymotrypsin were more abundant in OC ascites or not present in serum control samples. Further glycopeptide analysis of OC ascites identified N- and O-glycans in clusterin, hemopexin, and fibulin glycopeptides, some of which are unusual and may be important in OC metastasis.

During the development of recombinant monoclonal antibody (rMAb) drugs, glycosylation receives particular focus because changes in the attached glycans can have a significant impact on the antibody effector functions. The vast heterogeneity of structures that exist across glycosylation sites hinders the in-depth analysis of glycan changes specific to an individual protein within a complex mixture. In this study, we established a sensitive and specific method for monitoring site-specific glycosylation in rMAbs using multiple reaction monitoring (MRM) on an ultrahigh-performance liquid chromatography-triple quadrupole MS (UHPLC-QqQ-MS). Our results showed that irrespective of the IgG subclass expressed in the drugs, the N-glycopeptide profiles are nearly the same but differ in abundances. In all rMAb drugs, a single subclass of IgG comprised over 97% of the total IgG content and showed over 97% N-glycan site occupancy. This study demonstrates the utility of an MRM-based method to rapidly characterize over 130 distinct glycopeptides and determine the extent of site occupancy within minutes. Such multilevel structural characterization is important for the successful development of therapeutic antibodies.

Previous studies indicated that glycans in serum may serve as biomarkers for diagnosis of ovarian cancer; however, it was unclear to which proteins these glycans belong. We hypothesize that protein-specific glycosylation profiles of the glycans may be more informative of ovarian cancer and can provide insight into biological mechanisms underlying glycan aberration in serum of diseased individuals. Serum samples from women diagnosed with epithelial ovarian cancer (EOC, n = 84) and matched healthy controls (n = 84) were obtained from the Gynecologic Oncology Group. Immunoglobulin (IgG, IgA, and IgM) concentrations and glycosylation profiles were quantified using multiple reaction monitoring mass spectrometry. Differential and classification analyses were performed to identify aberrant protein-specific glycopeptides using a training set. All findings were validated in an independent test set. Multiple glycopeptides from immunoglubins IgA, IgG, and IgM were found to be differentially expressed in serum of EOC patients compared with controls. The protein-specific glycosylation profiles showed their potential in the diagnosis of EOC. In particular, IgG-specific glycosylation profiles are the most powerful in discriminating between EOC case and controls. Additional studies of protein- and site-specific glycosylation profiles of immunoglobulins and other proteins will allow further elaboration on the characteristics of biological functionality and causality of the differential glycosylation in ovarian cancer and thus ultimately lead to increased sensitivity and specificity of diagnosis.

Objectives: To test whether recently developed methods for comprehensive profiling of the high-density lipoprotein (HDL) glycome combined with the HDL proteome can distinguish individuals with coronary artery disease (CAD) from those without., Methods: Twenty subjects at risk for CAD, who underwent diagnostic coronary arteriography, were analyzed. Ten subjects had CAD, and ten did not. HDL was extracted from fasting plasma samples by ultracentrifugation, followed by shotgun proteomic, glycomic, and ganglioside analyses using LC-MS. CAD vs non-CAD subjects' data were compared using univariate and multivariate statistics., Results: Principal components analysis showed a clear separation of CAD and non-CAD subjects, confirming that combined HDL proteomic and glycomic profiles distinguished at-risk subjects with atherosclerosis from those without. CAD patients had lower HDL apolipoprotein content (specifically ApoA-I, A-II, and E, p < 0.05), and lower serum amyloid A2 (SAA2, p = 0.020) and SAA4 (p = 0.007) but higher sialylated glycans (p < 0.05)., Conclusion: Combined proteomic and glycomic profiling of isolated HDL was tested as a novel analytical approach for developing biomarkers of disease. In this pilot study we found that HDL proteome and glycome distinguished between individuals who had CAD from those who did not within a group of individuals equally at risk for heart disease.

A comprehensive glycan map was constructed for the top eight abundant glycoproteins in plasma using both specific and nonspecific enzyme digestions followed by nano liquid chromatography (LC)-chip/quadrupole time-of-flight mass spectrometry (MS) analysis. Glycopeptides were identified using an in-house software tool, GPFinder. A sensitive and reproducible multiple reaction monitoring (MRM) technique on a triple quadrupole MS was developed and applied to quantify immunoglobulins G, A, M, and their site-specific glycans simultaneously and directly from human serum/plasma without protein enrichments. A total of 64 glycopeptides and 15 peptides were monitored for IgG, IgA, and IgM in a 20 min ultra high performance (UP)LC gradient. The absolute protein contents were quantified using peptide calibration curves. The glycopeptide ion abundances were normalized to the respective protein abundances to separate protein glycosylation from protein expression. This technique yields higher method reproducibility and less sample loss when compared with the quantitation method that involves protein enrichments. The absolute protein quantitation has a wide linear range (3-4 orders of magnitude) and low limit of quantitation (femtomole level). This rapid and robust quantitation technique, which provides quantitative information for both proteins and glycosylation, will further facilitate disease biomarker discoveries.

To decrease the mortality of lung cancer, better screening and diagnostic tools as well as treatment options are needed. Protein glycosylation is one of the major post-translational modifications that is altered in cancer, but it is not exactly clear which glycan structures are affected. A better understanding of the glycan structures that are differentially regulated in lung tumor tissue is highly desirable and will allow us to gain greater insight into the underlying biological mechanisms of aberrant glycosylation in lung cancer. Here, we assess differential glycosylation patterns of lung tumor tissue and nonmalignant tissue at the level of individual glycan structures using nLC-chip-TOF-MS. Using tissue samples from 42 lung adenocarcinoma patients, 29 differentially expressed (FDR < 0.05) glycan structures were identified. The levels of several oligomannose type glycans were upregulated in tumor tissue. Furthermore, levels of fully galactosylated glycans, some of which were of the hybrid type and mostly without fucose, were decreased in cancerous tissue, whereas levels of non- or low-galactosylated glycans mostly with fucose were increased. To further assess the regulation of the altered glycosylation, the glycomics data was compared to publicly available gene expression data from lung adenocarcinoma tissue compared to nonmalignant lung tissue. The results are consistent with the possibility that the observed N-glycan changes have their origin in differentially expressed glycosyltransferases. These results will be used as a starting point for the further development of clinical glycan applications in the fields of imaging, drug targeting, and biomarkers for lung cancer.

Glycosylation is an important post-translational modification of proteins present in the vast majority of human proteins. For this reason, they are potentially new sources of biomarkers and active targets of therapeutics and vaccines. However, the absence of a biosynthetic template as in the genome and the general complexity of the structures have limited the development of methods for comprehensive structural analysis. Even now, the exact structures of many abundant N-glycans in serum are not known. Structural elucidation of oligosaccharides remains difficult and time-consuming. Here, we introduce a means of rapidly identifying released N-glycan structures using their accurate masses and retention times based on a glycan library. This serum glycan library, significantly expanded from a previous one covering glycans released from a handful of serum glycoproteins, has more than 170 complete and partial structures and constructed instead from whole serum. The method employs primarily nanoflow liquid chromatography and accurate mass spectrometry. The method allows us to readily profile N-glycans in biological fluids with deep structural analysis. This approach is used to determine the relative abundances and variations in the N-glycans from several individuals providing detailed variations in the abundances of the important N-glycans in blood.

Secretory immunoglobulin A (sIgA) is a major glycoprotein in milk and plays a key role in mediating immune protection of the gut mucosa. Although it is a highly glycosylated protein, its site-specific glycosylation and associated glycan micro-heterogeneity have still not been fully elucidated. In this study, the site-specific glycosylation of sIgA isolated from human colostrum (n = 3) was analyzed using a combination of LC-MS and LC-MS/MS and in-house software (Glycopeptide Finder). The majority of the glycans found are biantennary structures with one or more acidic Neu5Ac residues; however, a large fraction belonged to truncated complex structures with terminal GlcNAc. Multiple glycosites were identified with nearly 30 glycan compositions located at seven sites on the secretory component, six compositions at a single site on the J chain, and 16 compositions at five sites on the IgA heavy (H) chain. Site-specific heterogeneity and relative quantitation of each composition and the extent of occupation at each site were determined using nonspecific proteases. Additionally, 54 O-linked glycan compositions located at the IgA1 hinge region (HR) were identified by comparison against a theoretical O-glycopeptide library. This represents the most comprehensive report to date detailing the complexity of glycan micro-heterogeneity with relative quantitation of glycoforms for each glycosylation site on milk sIgA. This strategy further provides a general method for determining site-specific glycosylation in large protein complexes.

Human milk oligosaccharides (HMOs) play a key role in shaping and maintaining a healthy infant gut microbiota. This article demonstrates the potential of combining recent advances in glycomics and genomics to correlate abundances of fecal microbes and fecal HMOs. Serial fecal specimens from two healthy breast-fed infants were analyzed by bacterial DNA sequencing to characterize the microbiota and by mass spectrometry to determine abundances of specific HMOs that passed through the intestinal tract without being consumed by the luminal bacteria. In both infants, the fecal bacterial population shifted from non-HMO-consuming microbes to HMO-consuming bacteria during the first few weeks of life. An initial rise in fecal HMOs corresponded with bacterial populations composed primarily of non-HMO-consuming Enterobacteriaceae and Staphylococcaeae. This was followed by decreases in fecal HMOs as the proportion of HMO-consuming Bacteroidaceae and Bifidobacteriaceae increased. Analysis of HMO structures with isomer differentiation revealed that HMO consumption is highly structure-specific, with unique isomers being consumed and others passing through the gut unaltered. These results represent a proof-of-concept and are consistent with the highly selective, prebiotic effect of HMOs in shaping the gut microbiota in the first weeks of life. The analysis of selective fecal bacterial substrates as a measure of alterations in the gut microbiota may be a potential marker of dysbiosis.

Little is known about the digestive process in infants. In particular, the chronological activity of enzymes across the course of digestion in the infant remains largely unknown. To create a temporal picture of how milk proteins are digested, enzyme activity was compared between intact human milk samples from three mothers and the gastric samples from each of their 4-12 day postpartum infants, 2 h after breast milk ingestion. The activities of 7 distinct enzymes are predicted in the infant stomach based on their observed cleavage pattern in peptidomics data. We found that the same patterns of cleavage were evident in both intact human milk and gastric milk samples, demonstrating that the enzyme activities that begin in milk persist in the infant stomach. However, the extent of enzyme activity is found to vary greatly between the intact milk and gastric samples. Overall, we observe that milk-specific proteins are cleaved at higher levels in the stomach compared to human milk. Notably, the enzymes we predict here only explain 78% of the cleavages uniquely observed in the gastric samples, highlighting that further investigation of the specific enzyme activities associated with digestion in infants is warranted.

Human milk is known to contain several proteases, but little is known about whether these enzymes are active, which proteins they cleave, and their relative contribution to milk protein digestion in vivo. This study analyzed the mass spectrometry-identified protein fragments found in pooled human milk by comparing their cleavage sites with the enzyme specificity patterns of an array of enzymes. The results indicate that several enzymes are actively taking part in the digestion of human milk proteins within the mammary gland, including plasmin and/or trypsin, elastase, cathepsin D, pepsin, chymotrypsin, a glutamyl endopeptidase-like enzyme, and proline endopeptidase. Two proteins were most affected by enzyme hydrolysis: β-casein and polymeric immunoglobulin receptor. In contrast, other highly abundant milk proteins such as α-lactalbumin and lactoferrin appear to have undergone no proteolytic cleavage. A peptide sequence containing a known antimicrobial peptide is released in breast milk by elastase and cathepsin D.

The glycosylation in recombinant monoclonal antibody (rMab) drugs is a major concern in the biopharmaceutical industry as it impacts the drugs' many attributes. Characterization is important but complicated by the intricate structures, microheterogeneity, and the limitations of current tools for structural analysis. In this study, we developed a liquid chromatography-mass spectrometry (LC-MS) N-glycan library based on eight commercial rMab drugs. A library of over 70 structures was developed for the rapid characterization of rMab. N-Glycans were separated on a porous graphitized carbon (PGC) column incorporated on a chip and then analyzed by an electrospray ionization hybrid quadrupole time-of-flight (ESI-Q-TOF) MS. The retention time and accurate mass for each N-glycan were recorded in the library. The complete structures were obtained through exoglycosidase sequencing. The results showed that most of the N-glycans between different antibodies are nearly the same with different abundances. The utility of this library enables one to identify structures in a rapid manner by matching LC retention times and accurate masses.

An absolute quantitation method for measuring free human milk oligosaccharides (HMOs) in milk samples was developed using multiple reaction monitoring (MRM). To obtain the best sensitivity, the instrument conditions were optimized to reduce the source and postsource fragmentation prior to the quadrupole transmission. Fragmentation spectra of HMOs using collision-induced dissociation were studied to obtain the best characteristic fragments. At least two MRM transitions were used to quantify and identify each structure in the same run. The fragment ions corresponded to the production of singly charged mono-, di-, and trisaccharide fragments. The sensitivity and accuracy of the quantitation using MRM were determined, with the detection limit in the femtomole level and the calibration range spanning over 5 orders of magnitude. Seven commercial HMO standards were used to create calibration curves and were used to determine a universal response for all HMOs. The universal response factor was used to estimate absolute amounts of other structures and the total oligosaccharide content in milk. The quantitation method was applied to 20 human milk samples to determine the variations in HMO concentrations from women classified as secretors and nonsecretors, a phenotype that can be identified by the concentration of 2'-fucosylation in their milk.

In clinical settings, biopsies are routinely used to determine cancer type and grade based on tumor cell morphology, as determined via histochemical or immunohistochemical staining. Unfortunately, in a significant number of cases, traditional biopsy results are either inconclusive or do not provide full subtype differentiation, possibly leading to inefficient or ineffective treatment. Glycomic profiling of the cell membrane offers an alternate route toward cancer diagnosis. In this study, isomer-sensitive nano-LC/MS was used to directly obtain detailed profiles of the different N-glycan structures present on cancer cell membranes. Membrane N-glycans were extracted from cells representing various subtypes of breast, lung, cervical, ovarian, and lymphatic cancer. Chip-based porous graphitized carbon nano-LC/MS was used to separate, identify, and quantify the native N-glycans. Structure-sensitive N-glycan profiling identified hundreds of glycan peaks per cell line, including multiple isomers for most compositions. Hierarchical clusterings based on Pearson correlation coefficients were used to quickly compare and separate each cell line according to originating organ and disease subtype. Based simply on the relative abundances of broad glycan classes (e.g., high mannose, complex/hybrid fucosylated, complex/hybrid sialylated, etc.), most cell lines were readily differentiated. More closely related cell lines were differentiated based on several-fold differences in the abundances of individual glycans. Based on characteristic N-glycan profiles, primary cancer origins and molecular subtypes could be distinguished. These results demonstrate that stark differences in cancer cell membrane glycosylation can be exploited to create an MS-based biopsy, with potential applications toward cancer diagnosis and direction of treatment.

Many of the functional proteins and lipids in high density lipoprotein (HDL) particles are potentially glycosylated, yet very little is known about the glycoconjugates of HDL. In this study, HDL was isolated from plasma by sequential micro-ultracentrifugation, followed by glycoprotein and glycolipid analysis. N-Glycans, glycopeptides, and gangliosides were extracted and purified followed by analysis with nano-HPLC Chip quadrupole time of flight mass spectrometry and MS/MS. HDL particles were found to be highly sialylated. Most of the N-glycans (∼90%) from HDL glycoproteins were sialylated with one or two neuraminic acids (Neu5Ac). The most abundant N-glycan was a biantennary complex type glycan with two sialic acids (Hexose5HexNAc4Neu5Ac2) and was found in multiple glycoproteins using site-specific glycosylation analysis. The observed O-glycans were all sialylated, and most contained a core 1 structure with two Neu5Acs, including those that were associated with apolipoprotein CIII (ApoC-III) and fetuin A. GM3 (monosialoganglioside, NeuAc2-3Gal1-4Glc-Cer) and GD3 (disialoganglioside, NeuAc2-8NeuAc2-3Gal1-4Glc-Cer) were the major gangliosides in HDL. A 60% GM3 and 40% GD3 distribution was observed. Both GM3 and GD3 were composed of heterogeneous ceramide lipid tails, including d18:1/16:0 and d18:1/23:0. This report describes for the first time a glycomic approach for analyzing HDL, highlighting that HDL are highly sialylated particles.

Bovine milk is known to contain naturally occurring peptides, but relatively few of their sequences have been determined. Human milk contains hundreds of endogenous peptides, and the ensemble has been documented for antimicrobial actions. Naturally occurring peptides from bovine milk were sequenced and compared with human milk peptides. Bovine milk samples from six cows in second-stage peak lactation at 78-121 days postpartum revealed 159 peptides. Most peptides (73%) were found in all six cows sampled, demonstrating the similarity of the intramammary peptide degradation across these cows. One peptide sequence, ALPIIQKLEPQIA from bovine perilipin 2, was identical to another found in human milk. Most peptides derived from β-casein, αs1-casein, and αs2-casein. No peptides derived from abundant bovine milk proteins such as lactoferrin, β-lactoglobulin, and secretory immunoglobulin A. The enzymatic cleavage analysis revealed that milk proteins were degraded by plasmin, cathepsins B and D, and elastase in all samples.

Prebiotics are nondigestible substrates that stimulate the growth of beneficial microbes in the human intestine. Galactooligosaccharides (GOS) are food ingredients that possess prebiotic properties, in particular, promoting the growth of bifidobacteria in situ. However, precise mechanistic details of GOS consumption by bifidobacteria remain poorly understood. Because GOS are mixtures of polymers of different lengths and linkages, there is interest in determining which specific structures provide prebiotic effects to potentially create better supplements. This paper presents a method comprising porous graphitic carbon separation, isotopic labeling, and mass spectrometry analysis for the structure-specific analysis of GOS isomers and their bacterial consumption rate. Using this strategy, the differential bacterial consumption of GOS by the bifidobacteria species Bifidobacterium longum subsp. infantis, Bifidobacterium animalis subsp. lactis, and Bifidobacterium adolescentis was determined, indicating that the use of specific GOS isomers in infant formula may provide enrichment of distinct species.

Milk gangliosides have gained considerable attention because they participate in diverse biological processes, including neural development, pathogen binding, and activation of the immune system. Herein, we present a quantitative measurement of the gangliosides present in bovine milk and other dairy products and byproducts. Ultrahigh performance liquid chromatography separation was used for high-throughput analysis and achieved a short running time without sacrificing chromatographic resolution. Dynamic multiple reaction monitoring was conducted for 12 transitions for GM3 and 12 transitions for GD3. Transitions to sialic acid fragments (m/z 290.1) were chosen for the quantitation. There was a considerable amount of gangliosides in day 2 milk (GM3, 0.98 mg/L; GD3, 15.2 mg/L) which dramatically decreased at day 15 and day 90. GM3 and GD3 were also analyzed in pooled colostrum, colostrum cream, colostrum butter, and colostrum buttermilk. The separation and analytical approaches here proposed could be integrated into the dairy industry processing adding value to side-streams.

Despite recent advances, site-specific profiling of protein glycosylation remains a significant analytical challenge for conventional proteomic methodology. To alleviate the issue, we propose glyco-analytical multispecific proteolysis (Glyco-AMP) as a strategy for glycoproteomic characterization. Glyco-AMP consists of rapid, in-solution digestion of an analyte glycoprotein (or glycoprotein mixture) by a multispecific protease (or protease cocktail). Resulting glycopeptides are chromatographically separated by isomer-specific porous graphitized carbon nano-LC, quantified by high-resolution MS, and structurally elucidated by MS/MS. To demonstrate the consistency and customizability of Glyco-AMP methodology, the glyco-analytical performances of multispecific proteases subtilisin, pronase, and proteinase K were characterized in terms of quantitative accuracy, sensitivity, and digestion kinetics. Glyco-AMP was shown be effective on glycoprotein mixtures as well as glycoproteins with multiple glycosylation sites, providing detailed, quantitative, site- and structure-specific information about protein glycosylation.

Studies aimed toward glycan biomarker discovery have focused on glycan characterization by the global profiling of released glycans. Site-specific glycosylation analysis is less developed but may provide new types of biomarkers with higher sensitivity and specificity. Quantitation of peptide-conjugated glycans directly facilitates the differential analysis of distinct glycoforms associated with specific proteins at distinct sites. We have developed a method using MRM to monitor protein glycosylation normalized to absolute protein concentrations to examine quantitative changes in glycosylation at a site-specific level. This new approach provides information regarding both the absolute amount of protein and the site-specific glycosylation profile and will thus be useful to determine if altered glycosylation profiles in serum/plasma are due to a change in protein glycosylation or a change in protein concentration. The remarkable sensitivity and selectivity of MRM enable the detection of low abundance IgG glycopeptides, even when IgG was digested directly in serum with no cleanup prior to the liquid chromatography. Our results show a low limit of detection of 60 amol and a wide dynamic range of 3 orders magnitude for IgG protein quantitation. The results show that IgG glycopeptides can be analyzed directly from serum (without enrichment) and yield more accurate abundances when normalized to the protein content. This report represents the most comprehensive study so far of the use of multiple reaction monitoring for the quantitation of glycoproteins and their glycosylation patterns in biofluids.

Site-specific glycosylation (SSG) of glycoproteins remains a considerable challenge and limits further progress in the areas of proteomics and glycomics. Effective methods require new approaches in sample preparation, detection, and data analysis. While the field has advanced in sample preparation and detection, automated data analysis remains an important goal. A new bioinformatics approach implemented in software called GP Finder automatically distinguishes correct assignments from random matches and complements experimental techniques that are optimal for glycopeptides, including nonspecific proteolysis and high mass resolution liquid chromatography/tandem mass spectrometry (LC/MS/MS). SSG for multiple N- and O-glycosylation sites, including extensive glycan heterogeneity, was annotated for single proteins and protein mixtures with a 5% false-discovery rate, generating hundreds of nonrandom glycopeptide matches and demonstrating the proof-of-concept for a self-consistency scoring algorithm shown to be compliant with the target-decoy approach (TDA). The approach was further applied to a mixture of N-glycoproteins from unprocessed human milk and O-glycoproteins from very-low-density-lipoprotein (vLDL) particles.

Mice are the premier mammalian models for studies of human physiology and disease, bearing extensive biological similarity to humans with far fewer ethical, economic, or logistic complications. To facilitate glycomic studies based on the mouse model, we comprehensively profiled the mouse serum N-glycome using isomer-specific nano-LC/MS and -LC/MS/MS. N-Glycans were identified by accurate mass MS and structurally elucidated by MS/MS. Porous graphitized carbon nano-LC was able to separate out nearly 300 N-linked glycan compounds (including isomers) from just over 100 distinct N-linked glycan compositions. Additional MS/MS structural analysis was performed on a number of novel N-glycans, revealing the structural characteristics of modifications such as dehydration, O-acetylation, and lactylation. Experimental findings were combined with known glycobiology to generate a theoretical library of all biologically possible mouse serum N-glycan compositions. The library may be used for automated identification of complex mixtures of mouse N-glycans, with possible applications to a wide range of mouse-related research endeavors, including pharmaceutical drug development and biomarker discovery.

Milk is traditionally considered an ideal source of the basic elemental nutrients required by infants. More detailed examination is revealing that milk represents a more functional ensemble of components with benefits to both infants and mothers. A comprehensive peptidomics method was developed and used to analyze human milk yielding an extensive array of protein products present in the fluid. Over 300 milk peptides were identified originating from major and many minor protein components of milk. As expected, the majority of peptides derived from β-casein, however no peptide fragments from the major milk proteins lactoferrin, α-lactalbumin, and secretory immunoglobulin A were identified. Proteolysis in the mammary gland is selective-released peptides were drawn only from specific proteins and typically from only select parts of the parent sequence. A large number of the peptides showed significant sequence overlap with peptides with known antimicrobial or immunomodulatory functions. Antibacterial assays showed the milk peptide mixtures inhibited the growth of Escherichia coli and Staphylococcus aureus . The predigestion of milk proteins and the consequent release of antibacterial peptides may provide a selective advantage through evolution by protecting both the mother's mammary gland and her nursing offspring from infection.

O-Glycans in saliva and tear isolated from patients suffering from ocular rosacea, a form of inflammatory ocular surface disease, were profiled, and their structures were elucidated using high resolution mass spectrometry. We have previously shown that certain structures, particularly sulfated oligosaccharides, increased in the tear and saliva of rosacea patients. In this study, the structures of these glycans were elucidated using primarily tandem mass spectrometry. There were important similarities in the glycan profiles of tears and saliva with the majority of the structures in common. The structures of the most abundant species common to both tear and saliva, which were also the most abundant species in both, were elucidated. For sulfated species, the positions of the sulfate groups were localized. The majority of the structures were new, with the sulfated glycans comprising mucin core 1- and core 2-type structures. As both saliva and tear are rich in mucins, it is suggested that the O-glycans are mainly components of mucins. The study further illustrates the strong correspondence between the glycans in the tear and saliva of ocular rosacea patients.

Determining protein-specific glycosylation in protein mixtures remains a difficult task. A common approach is to use gel electrophoresis to isolate the protein followed by glycan release from the identified band. However, gel bands are often composed of several proteins. Hence, release of glycans from specific bands often yields products not from a single protein but a composite. As an alternative, we present an approach whereby glycans are released with peptide tags allowing verification of glycans bound to specific proteins. We term the process in-gel nonspecific proteolysis for elucidating glycoproteins (INPEG). INPEG combines rapid gel separation of a protein mixture with in-gel nonspecific proteolysis of protein bands followed by tandem mass spectrometry (MS) analysis of the resulting N- and O-glycopeptides. Here, in-gel digestion is shown for the first time with nonspecific and broad specific proteases such as Pronase, proteinase K, pepsin, papain, and subtilisin. Tandem MS analysis of the resulting glycopeptides separated on a porous graphitized carbon (PGC) chip was achieved via nanoflow liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (nano-LC/Q-TOF MS). In this study, rapid and automated glycopeptide assignment was achieved via an in-house software (Glycopeptide Finder) based on a combination of accurate mass measurement, tandem MS data, and predetermined protein identification (obtained via routine shotgun analysis). INPEG is here initially validated for O-glycosylation (κ casein) and N-glycosylation (ribonuclease B). Applications of INPEG were further demonstrated for the rapid determination of detailed site-specific glycosylation of lactoferrin and transferrin following gel separation and INPEG analysis on crude bovine milk and human serum, respectively.

Mass spectrometric analysis of peptides contained in enzymatically digested hydrolysates of proteins is increasingly being used to characterize potentially bioactive or otherwise interesting hydrolysates. However, when preparations containing mixtures of enzymes are used, from either biological or experimental sources, it is unclear which of these enzymes have been most important in hydrolyzing the sample. We have developed a tool to rapidly evaluate the evidence for which enzymes are most likely to have cleaved the sample. EnzymePredictor, a web-based software, has been developed to (i) identify the protein sources of fragments found in the hydrolysates and map them back on it, (ii) identify enzymes that could yield such cleavages, and (iii) generate a colored visualization of the hydrolysate, the source proteins, the fragments, and the predicted enzymes. It tabulates the enzymes ranked according to their cleavage counts. The provision of odds ratio and standard error in the table permits users to evaluate how distinctively particular enzymes may be favored over other enzymes as the most likely cleavers of the samples. Finally, the method displays the cleavage not only according to peptides, but also according to proteins, permitting evaluation of whether the cleavage pattern is general across all proteins, or specific to a subset. We illustrate the application of this method using milk hydrolysates, and show how it can rapidly identify the enzymes or enzyme combinations used in generating the peptides. The approach developed here will accelerate the identification of enzymes most likely to have been used in hydrolyzing a set of mass spectrometrically identified peptides derived from proteins. This has utility not only in understanding the results of mass spectrometry experiments, but also in choosing enzymes likely to yield similar cleavage patterns. EnzymePredictor can be found at http://bioware.ucd.ie/∼enzpred/Enzpred.php.

Human milk oligosaccharides (HMOs), as an abundant and bioactive component of breast milk, work in many ways to promote the health of breast fed infants. The expression of HMOs has been shown to vary in accordance with Lewis blood type and secretor status, as women of different blood types differ in the expression of α1,2 fucosyltransferase (FUT2) and α1,3/4 fucosyltransferase (FUT3). In this study, HMOs were extracted from the milk of 60 women from The Gambia, Africa with various Lewis and secretor blood types. The HMOs were profiled using high resolution HPLC-Chip/TOF mass spectrometry. Notably, the amounts of fucosylation varied significantly between Le(a+b-) nonsecretors, Le(a-b+) and Le(a-b-) secretors, and Le(a-b-) nonsecretors. With higher frequency of expression of the recessive Lewis negative and nonsecretor phenotypes in West African populations, the HMO profiles of several milks from women of these phenotypes were examined, demonstrating decreased amounts of total oligosaccharide abundance and lower relative amounts of fucosylation. Also in this study, four specific fucosylated structures (2'FL, LNFP I, LDFT, and LNDFH I) were determined to be specific and sensitive glycan markers for rapidly determining secretor status without the need for serological testing.

Structure-specific characterization and quantitation is often required for effective functional studies of oligosaccharides. Inside the gut, HMOs are preferentially bound and catabolized by the beneficial bacteria. HMO utility by these bacteria employs structure-specific catabolism based on a number of glycosidases. Determining the activity of these enzymes requires accurate quantitation of a large number of structures. In this study, we describe a method for the quantitation of human milk oligosaccharide (HMO) structures employing LC/MS and isotopically labeled internal standards. Data analysis was accomplished with a newly developed software tool, LC/MS Searcher, that employs a reference structure library to process LC/MS data yielding structural identification with accurate quantitation. The method was used to obtain a meta-enzyme analysis of bacteria, the simultaneous characterization of all glycosidases employed by bacteria for the catabolism of milk oligosaccharides. Analysis of consumed HMO structures confirmed the utility of a β-1,3-galactosidase in Bifidobacterium longum subsp. infantis ATCC 15697 (B. infantis). In comparison, Bifidobacterium breve ATCC 15700 showed significantly less HMO catabolic activity compared to B. infantis.

Breast milk is the ideal nutrition for term infants but must be supplemented to provide adequate growth for most premature infants. Human milk oligosaccharides (HMOs) are remarkably abundant and diverse in breast milk and yet provide no nutritive value to the infant. HMOs appear to have at least two major functions: prebiotic activity (stimulation of the growth of commensal bacteria in the gut) and protection against pathogens. Investigations of HMOs in milk from women delivering preterm have been limited. We present the first detailed mass spectrometric analysis of the fucosylation and sialylation in HMOs in serial specimens of milk from 15 women delivering preterm and 7 women delivering at term using nanohigh performance liquid chromatography chip/time-of-flight mass spectrometry. A mixed-effects model with Levene's test was used for the statistical analyses. We find that lacto-N-tetraose, a core HMO, is both more abundant and more highly variable in the milk of women delivering preterm. Furthermore, fucosylation in preterm milk is not as well regulated as in term milk, resulting in higher within and between mother variation in women delivering preterm vs term. Of particular clinical interest, the α1,2-linked fucosylated oligosaccharide 2'-fucosyllactose, an indicator of secretor status, is not consistently present across lactation of several mothers that delivered preterm. The immaturity of HMO production does not appear to resolve over the time of lactation and may have relevance to the susceptibility of premature infants to necrotizing enterocolitis, late onset sepsis, and related neurodevelopmental impairments.