Glycomic Profiling Research Articles

Daily glycome and transcriptome profiling reveals polysaccharide structures and correlated glycosyltransferases critical for cotton fiber growth.

Cotton fiber is the most valuable naturally available material for the textile industry and the fiber length and strength are key determinants of its quality. Dynamic changes in the pectin, xyloglucan, xylan, and cellulose polysaccharide epitope content during fiber growth contribute to complex remodeling of fiber cell wall (CW) and quality. Detailed knowledge about polysaccharide compositional and structural alteration in the fiber during fiber elongation and strengthening is important to understand the molecular dynamics of fiber development and improve its quality. Here, large-scale glycome profiling coupled with fiber phenotype and transcriptome profiling was conducted on fiber collected daily covering the most critical window of fiber development. The profiling studies with high temporal resolution allowed us to identify specific polysaccharide epitopes associated with distinct fiber phenotypes that might contribute to fiber quality. This study revealed the critical role of highly branched RG-I pectin epitopes such as β-1,4-linked-galactans, β-1,6-linked-galactans, and arabinogalactans, in addition to earlier reported homogalacturonans and xyloglucans in the formation of cotton fiber middle lamella and contributing to fiber plasticity and elongation. We also propose the essential role of heteroxylans (Xyl-MeGlcA and Xyl-3Ar), as a guiding factor for secondary CW cellulose microfibril arrangement, thus contributing to fiber strength. Correlation analysis of profiles of polysaccharide epitopes from glycome data and expression profiles of glycosyltransferase-encoding genes from transcriptome data identified several key putative glycosyltransferases that are potentially involved in synthesizing the critical polysaccharide epitopes. The findings of this study provide a foundation to identify molecular factors that dictate important fiber traits.

The restricted N-glycome of neurons is programmed during differentiation.

The protein glycome of individual cell types in the brain is unexplored, despite the critical function of these modifications in development and disease. In aggregate, the most abundant asparagine (N-) linked glycans in the adult brain are high mannose structures, and specifically Man 5 GlcNAc 2 (Man-5), which normally exits the ER for further processing in the Golgi. Mannose structures are uncommon in other organs and often overlooked or excluded in most studies. To understand cell-specific contributions to the unique brain N-glycome and its abundance of Man-5, we performed RNAseq and MALDI-MS TOF protein N-glycomics at several timepoints during differentiation of multiple cell types. To this end, homogeneous cultures of glutamatergic neurons, GABAergic neurons, and brain-specific endothelial cells were generated from monoclonal human inducible pluripotent stem cells (hiPSCs) through cellular reprogramming. Small molecule induction of stably integrated synthetic transcription units driving morphogen expression generated differentiated cells with distinct patterns mirroring intact tissue. Comparing uninduced hiPSCs for each cell type revealed identical transcriptomic and glycomic profiles before differentiation, with low quantities of Man-5. In differentiated glutamatergic and GABAergic neurons, the most abundant N-glycans became Man-5 and its immediate precursor Man-6, despite the presence of transcripts encoding enzymes for their subsequent modification. Differentiation to brain-specific endothelial cells showed an opposite effect, with the N-glycome displaying an abundance of complex N-glycans and terminal modifications of the late secretory pathway. These results confirm that the restricted N-glycome profile of brain is programmed into neuronal differentiation, with regulation independent of the transcriptome and under tight evolutionary constraint.

Rapid and large-scale glycopeptide enrichment strategy based on chemical ligation.

Protein glycosylation, the most universal post-translational modification, is thought to play a crucial role in regulating multiple essential cellular processes. However, the low abundance of glycoproteins and the heterogeneity of glycans complicate their comprehensive analysis. Here, we develop a rapid and large-scale glycopeptide enrichment strategy via bioorthogonal ligation and trypsin cleavage. The enrichment process is performed in one tube to minimize sample loss and time costs. This method combines convenience and practicality, identifying over 900 O-GlcNAc sites from a 500μg sample. Surprisingly, it allows simultaneous identification of N-glycosites, O-GlcNAc sites, O-GalNAc sites and N-glycans via a two-step enzymatic release strategy. Combined with quantitative analysis, it reveals the distinct O-GlcNAcylation patterns in different compartments during oxidative stress. In summary, our study offers a convenient and robust tool for glycoproteome and glycome profiling, facilitating in-depth analysis to elucidate the biological functions of glycosylation.

Glycomics of cervicovaginal fluid from women at risk of preterm birth reveals immuno-regulatory epitopes that are hallmarks of cancer and viral glycosylation

During pregnancy the immune system needs to maintain immune tolerance of the foetus while also responding to infection, which can cause premature activation of the inflammatory pathways leading to the onset of labour and preterm birth. The vaginal microbiome is an important modifier of preterm birth risk, with Lactobacillus dominance during pregnancy associated with term delivery while high microbial diversity is associated with an increased risk of preterm birth. Glycans on glycoproteins along the lower female reproductive tract are fundamental to microbiota-host interactions and the mediation of inflammatory responses. However, the specific glycan epitopes involved in these processes are not well understood. To address this, we conducted glycomic analyses of cervicovaginal fluid (CVF) from 36 pregnant women at high risk of preterm birth and 4 non-pregnant women. Our analysis of N- and O-glycans revealed a rich CVF glycome. While O-glycans were shown to be the main carriers of ABO blood group epitopes, the main features of N-glycans were the presence of abundant paucimannose and high mannose glycans, and a remarkable diversity of complex bi-, tri-, and tetra-antennary glycans decorated with fucose and sialic acid. We identified immuno-regulatory epitopes, such as Lewis antigens, and found that fucosylation was negatively correlated to pro-inflammatory factors, such as IL-1β, MMP-8, C3a and C5a, while glycans with only sialylated antennae were mainly positively correlated to those. Similarly, paucimannose glycans showed a positive correlation to pro-inflammatory factors. We revealed a high abundance of glycans which have previously been identified as hallmarks of cancer and viral glycosylation, such as Man8 and Man9 high mannose glycans. Although each pregnant woman had a unique glycomic profile, longitudinal studies showed that the main glycosylation features were consistent throughout pregnancy in women who delivered at term, whereas women who experienced extreme preterm birth exhibited sharp changes in the CVF glycome shortly before delivery. These findings shed light on the processes underlying the role of glycosylation in maintaining a healthy vaginal microbiome and associated host immune responses. In addition, these discoveries facilitate our understanding of the lower female reproductive tract which has broad implications for women’s health.

"Comparative Analysis of Glycoproteomic Software Using a Tailored Glycan Database".

Glycoproteomics is a rapidly developing field, and data analysis has been stimulated by several technological innovations. As a result, there are many software tools from which to choose; and each comes with unique features that can be difficult to compare. This work presents a head-to-head comparison of five modern analytical software: Byonic, Protein Prospector, MSFraggerGlyco, pGlyco3, and GlycoDecipher. To enable a meaningful comparison, parameter variables were minimized. One potential confounding variable is the glycan database that informs glycoproteomic searches. We performed glycomic profiling of the samples and used the output to construct matched glycan databases for each software. Up to 19,000 glycopeptide spectra were identified across three replicates of wild-type SH-SY5Y cells. There was substantial overlap among most software for glycoproteins identified, locations of glycosites, and glycans, although Byonic reported a suspiciously large number of glycoproteins and glycosites of questionable reliability. We show that Protein Prospector identified the most glycopeptide spectrum matches with high agreement to known glycosites in UniProt. Overall, our results indicate that glycoproteomic searches should involve more than one software to generate confidence. It may be useful to consider software with peptide-first approaches and with glycan-first approaches.

Deciphering disease through glycan codes: leveraging lectin microarrays for clinical insights.

Glycosylation, a crucial posttranslational modification, plays a significant role in numerous physiological and pathological processes. Lectin microarrays, which leverage the high specificity of lectins for sugar binding, are ideally suited for profiling the glycan spectra of diverse and complex biological samples. In this review, we explore the evolution of lectin detection technologies, as well as the applications and challenges of lectin microarrays in analyzing the glycome profiles of various clinical samples, including serum, saliva, tissues, sperm, and urine. This review not only emphasizes significant advancements in the high-throughput analysis of polysaccharides but also provides insight into the potential of lectin microarrays for diagnosing and managing diseases such as tumors, autoimmune diseases, and chronic inflammation. We aim to provide a clear, concise, and comprehensive overview of the use of lectin microarrays in clinical settings, thereby assisting researchers in conducting clinical studies in glycobiology.

In vitro treatment with liposome-encapsulated Mannose-1-phosphate restores N-glycosylation in PMM2-CDG patient-derived fibroblasts

SummaryPMM2-CDG is the most common congenital disorder of glycosylation (CDG). Patients with this disease often carry compound heterozygous mutations of the gene encoding the phosphomannomutase 2 (PMM2) enzyme. PMM2 converts mannose-6-phosphate (M6P) to mannose-1-phosphate (M1P), which is a critical upstream metabolite for proper protein N-glycosylation. Therapeutic options for PMM2-CDG patients are limited to management of the disease symptoms, as no drug is currently approved to treat this disease. GLM101 is a M1P-loaded liposomal formulation being developed as a candidate drug to treat PMM2-CDG. This report describes the effect of GLM101 treatment on protein N-glycosylation of PMM2-CDG patient-derived fibroblasts. This treatment normalized intracellular GDP-mannose, increased the relative glycoprotein mannosylation content and TNFα-induced ICAM-1 expression. Moreover, glycomics profiling revealed that GLM101 treatment of PMM2-CDG fibroblasts resulted in normalization of most high mannose glycans and partial correction of multiple complex and hybrid glycans. In vivo characterization of GLM101 revealed its favorable pharmacokinetics, liver-targeted biodistribution, and tolerability profile with achieved systemic concentrations significantly greater than its effective in vitro potency. Taken as a whole, the results described in this report support further exploration of GLM101's safety, tolerability, and efficacy in PMM2-CDG patients.

Assessing marine ecosystem health using multi-omic analysis of blue mussel liquid biopsies: A case study within a national marine park

Marine ecosystems are under escalating threats from myriad environmental stressors, necessitating a deeper understanding of their impact on biodiversity and the health of sentinel organisms. In this study, we carried out a spatiotemporal multi-omic analysis of liquid biopsies collected from mussels (Mytilus spp.) in marine ecosystems of a national park. We delved into the epigenomic, transcriptomic, glycomic, proteomic, and microbiomic profiles to unravel the intricate interplay between ecosystem biodiversity and mussels' biological response to their environments. Our analysis revealed temporal fluctuations in the alpha diversity of the circulating microbiome associated with human activities. Analysis of the hemolymphatic circulating cell-free DNA (ccfDNA) provided information on the biodiversity and the presence of potential pathogens. Epigenomic analysis revealed widespread hypomethylation sites within the mitochondrial (mtDNA). Comparative transcriptomic and glycomic analyses highlighted differences in metabolic pathways and genes associated with immune and wound healing functions. This study demonstrates the potential of multi-omic analysis of liquid biopsy in sentinel to provide a holistic view of human activities' environmental impacts on marine coastal ecosystems. Overall, this approach has the potential to enhance the effectiveness and efficiency of various conservation efforts, leading to more informed decision-making and better outcomes for biodiversity and ecosystem conservation.

Distinguishing Turkish pine honey from multi-floral honey through MALDI-MS-based N-glycomics and machine learning

Honey, a multifaceted blend of sugars, amino acids, vitamins, proteins, and minerals, exhibits compositional variability dependent upon the floral source. While previous studies have attempted to categorize honey, the use of glycomic profiles for honey classification remains an unexplored avenue. This investigation seeks to establish a methodology for distinguishing honey types, specifically multi-floral and pine honey, employing mass spectrometry-based glycomic analysis in tandem with machine learning. In this search, seven samples of pine honey and eight samples of multi-floral honey were obtained from diverse regions of Turkey. Subsequently, the proteins within these honey samples were extracted, and glycans were enzymatically released. The released glycans were labeled with 2-aminobenzoic acid (2-AA) and subjected to analysis via matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). The glycan profiles of pine and multi-floral honey were determined through these analytical procedures, revealing a total of 76 distinct N-glycan structures. Among these, 13 N-glycan profiles consistently established at high levels across experimental replicates and were incorporated in subsequent analyses. Following the quantification of individual glycan abundances, statistically significant differences in glycan profiles were determined. Notably, N-glycans Hex5HexNAc2, Hex4HexNAc3, and Hex5HexNAc3 displayed considerable differences. Using the 13 N-glycan profiles, an accuracy rate of 93.5% was obtained from machine learning analysis, which increased to 100% when incorporating the identified significantly changed glycans. The most productive models were identified as “subspace and fine k-nearest neighbors (KNN).” The findings underscore the potential of mass spectrometry-based glycomics in conjunction with machine learning as a robust tool for precise honey type classification and its prospective utility in quality control and honey product authentication.

T-antigen as a biomarker of progression-free survival in patients with glioblastoma.

Glioblastoma (GBM) is one of the most aggressive brain tumors and often leads to poor outcomes. Studies have indicated that glycan levels are significantly correlated with the pathogenesis and development of cancers. However, whether glycan levels can serve as diagnostic or prognostic biomarkers in GBM remains unclear. We obtained glycomic profiles in tissue and serum samples from 55 individuals with GBM using a well-established lectin biochip platform probing with 11 specific lectins. Our univariate analysis showed that 5 out of the 11 lectin-probed glycans (LPGs) were significantly higher in GBM tissues than in peri-tumoral tissues. After logistic regression analyses, only the Jacalin-probed T-antigen difference between the two groups remained significant (p = 0.037). Moreover, survival-related analyses showed that the level of Jacalin-probed T-antigen was significantly associated with the progression-free survival (p = 0.038) of patients. However, none of the LPG levels were correlated with the overall survival or the chemosensitivity to temozolomide therapy. The correlation coefficient analysis showed a moderate-to-strong correlation in the Jacalin-probed T-antigen levels between GBM tissues and serum samples, indicating its potential usefulness as a non-invasive GBM progression biomarker. Glycomics analyses can be helpful in the prediction of GBM recurrences and may provide information useful for GBM glycan-based target therapies or vaccine development.

(Sialyl)Lewis Antigen Expression on Glycosphingolipids, N-, and O-Glycans in Colorectal Cancer Cell Lines is Linked to a Colon-Like Differentiation Program

Alterations in the glycomic profile are a hallmark of cancer, including colorectal cancer (CRC). While, the glycosylation of glycoproteins and glycolipids has been widely studied for CRC cell lines and tissues, a comprehensive overview of CRC glycomics is still lacking due to the usage of different samples and analytical methods. In this study, we compared glycosylation features of N-, O-glycans, and glycosphingolipid glycans for a set of 22 CRC cell lines, all measured by porous graphitized carbon nano-liquid chromatography-tandem mass spectrometry. An overall, high abundance of (sialyl)Lewis antigens for colon-like cell lines was found, while undifferentiated cell lines showed high expression of H blood group antigens and α2-3/6 sialylation. Moreover, significant associations of glycosylation features were found between the three classes of glycans, such as (sialyl)Lewis and H blood group antigens. Integration of the datasets with transcriptomics data revealed positive correlations between (sialyl)Lewis antigens, the corresponding glycosyltransferase FUT3 and transcription factors CDX1, ETS, HNF1/4A, MECOM, and MYB. This indicates a possible role of these transcription factors in the upregulation of (sialyl)Lewis antigens, particularly on glycosphingolipid glycans, via FUT3/4 expression in colon-like cell lines. In conclusion, our study provides insights into the possible regulation of glycans in CRC and can serve as a guide for the development of diagnostic and therapeutic biomarkers.

Impaired Glycosylation of Gastric Mucins Drives Gastric Tumorigenesis and Serves as a Novel Therapeutic Target

BackgroundGastric cancer is often accompanied by a loss of MUC6, but its pathogenic role in gastric carcinogenesis remains unclear. MethodMuc6 knockout (Muc6-/-) mice and Muc6-dsRED mice were newly generated. Tff1Cre, Golph3-/-, R26-Golgi-mCherry, Hes1flox/flox, Cosmcflox/flox, A4gnt-/- mice were also used. Histology, DNAs and RNAs, proteins, and sugar chains were analyzed by whole exon DNA sequence, RNA sequence, immunohistochemistry, lectin-binding assays, and LC-MS analysis. Gastric organoids and cell lines were used for in vitro assays and xenograft experiments. ResultDeletion of Muc6 in mice spontaneously causes pan-gastritis and invasive gastric cancers. Muc6-deficient tumor growth was dependent on MAPK activation, mediated by Golgi stress-induced upregulation of GOLPH3. Glycomic profiling revealed aberrant expression of mannose-rich N-linked glycans in gastric tumors, detected with Banana lectin in association with lack of MUC6 expression. We identified a precursor of clusterin as a binding partner of mannose glycans. MAPK activation, Golgi stress responses, aberrant mannose expression are found in a separate Cosmc- and A4gnt-deficient mouse models which lack normal O-glycosylation. Banana lectin-drug conjugates proved an effective treatment for mannose-rich murine and human gastric cancer. ConclusionWe propose that Golgi stress responses and aberrant glycans are important drivers of, and promising new therapeutic targets for gastric cancer.

Diagnostic Challenges of Ocular Rosacea.

This study aims to address the issues surrounding the diagnosis of ocular rosacea and to evaluate the development of the patients’ condition after treatment, as well as to distinguish between healthy and diseased patients using a glycomic analysis of tears. A prospective study was conducted to assess a total of 68 eyes in 34 patients over a six-week period. These patients were diagnosed with ocular rosacea based on subjective symptoms and clinical examination. The study monitored the development of objective and subjective values. The difference between patients with the pathology and healthy controls was established by means of analysis of glycans in tears. Skin lesions were diagnosed in 94% of patients with ocular rosacea, with the most commonly observed phenotype being erythematotelangiectatic (68.8%). The mean duration of symptoms was 29.3 months (range 0.5–126 months) with a median of 12 months. Throughout the study, an improvement in all monitored parameters was observed, including Meibomian gland dysfunction, bulbar conjunctival hyperemia, telangiectasia of the eyelid margin, anterior blepharitis, uneven and reddened eyelid margins, and corneal neovascularization. The study also observed improvements in subjective manifestations of the disease, such as foreign body sensation, burning, dryness, lachrymation, itching eyes, photophobia, and morning discomfort. The analysis of glycans in tears partially separated tear samples based on their origin, which allowed for the differentiation of patients with rosacea from healthy controls. In the first sample, the pathology was determined in a total of 63 eyes (98.4%) of 32 patients, with further samples showing a change in the glycomic profile of patients’ tears during treatment. The study demonstrated objective and subjective improvements in all the patients. Tear sampling and analysis could provide a means of timely diagnosis of ocular rosacea.

P1042 Serum N-glycan Biomarkers Predict Patient Response to Biologics for Crohn’s Disease

Abstract Background Several therapeutic antibodies are approved to treat Crohn’s Disease (CD), for example, Vedolizumab (anti-α4β7), Ustekinumab (targets IL-12 and IL-23), Adalimumab and Infliximab (anti-TNF). Glycosylation alterations have been associated with CD, but have not been thoroughly investigated as potential predictors of disease remission¹. A comparison of serum N-glycan profiles between responders and non-responders prior to each therapy was used to detect potential biomarkers to response. The N-glycan composition after treatment was used to distinguish the different mechanisms of the biologics. In addition, a comparison of glycomic profiles across the different therapies could highlight the distinct biological pathways involved in response. Methods Serum samples, before (t1) and after (t2) treatment, were taken from 166 patients, containing the four sub-cohorts of patients under different biologics with CD. Treatment response, observed in 100 patients, was assessed by a combination of clinical and endoscopic outcomes. Firstly, the Serum N-glycans were detected by hydrophilic interaction liquid chromatography to produce a 62-peak chromatogram. Followed by quantifying the relative area of 62 glycan peaks via HappyTools². Logistic regression was used to determine which glycan peaks at t1 are predictive of response (p-value <0.05) and which are markers of response (p-value<0.05). 5 fold cross-validation tested on a variety of classifiers was used to derive the optimal predictor of response. The glycomic profiles across the four biologics, at both t1 and t2, were compared through the Kruskal test. The significant peaks (p-value < 0.05) were then combined to generate a multiclass model to predict response in each therapeutic. Results The N-glycan classification models for all four sub-cohorts under different biologics, Ustekinumab (0.78 AUC), Adalimumab (0.82 AUC), Infliximab (0.75 AUC), Vedolizumab (0.75 AUC), performed moderately well at predicting therapy response prior to treatment(figure 1A). In turn, patients could be identified as responders after treatment by N-glycan based classification models, Ustekinumab (0.70 AUC), Adalimumab (0.86 AUC), Infliximab (0.85 AUC), Vedolizumab (0.84 AUC). Prior to treatment, patients who responded were strongly distinguished by the therapy type (0.96 AUC) through a combination of 13 significant glycan peaks (figure 1B). Conclusion This study has demonstrated multiple N-glycans are potential predictors of biological response, with the possibility to guide clinicians in the most appropriate form of treatment. These results require the integration of mass spectrometry and validation by larger cohorts.

Fecal-adherent mucus is a non-invasive source of primary human MUC2 for structural and functional characterization in health and disease

The O-glycoprotein Mucin-2 (MUC2) forms the protective colon mucus layer. While animal models have demonstrated the importance of Muc2, few studies have explored human MUC2 in similar depth. Recent studies have revealed that secreted MUC2 is bound to human feces. We hypothesized human fecal MUC2 (HF-MUC2) was accessible for purification and downstream structural and functional characterization. We tested this via histologic and quantitative imaging on human fecal sections; extraction from feces for proteomic and O-glycomic characterization; and functional studies via growth and metabolic assays in vitro. Quantitative imaging of solid fecal sections showed a continuous mucus layer of varying thickness along human fecal sections with barrier functions intact. Lectin profiling showed HF-MUC2 bound several lectins but was weak to absent for Ulex europaeus 1 (α1,2 fucose-binding) and Sambucus nigra agglutinin (α2,6 sialic acid-binding), and did not have obvious b1/b2 barrier layers. HF-MUC2 separated by electrophoresis showed high molecular weight glycoprotein bands (∼1-2 MDa). Proteomics and Western analysis confirmed the enrichment of MUC2 and potential MUC2-associated proteins in HF-MUC2 extracts. MUC2 O-glycomics revealed diverse fucosylation, moderate sialylation, and little sulfation vs. porcine colonic MUC2 and murine fecal Muc2. O-glycans were functional and supported the growth of Bacteroides thetaiotaomicron (B. theta) and short-chain fatty acid (SCFA) production in vitro. MUC2 could be similarly analyzed from inflammatory bowel disease stools, which displayed an altered glycomic profile and differential growth and SCFA production by B. theta vs. healthy samples. These studies describe a new non-invasive platform for human MUC2 characterization in health and disease.

The glycosylation landscape of prostate cancer tissues and biofluids.

An overview of the role of glycosylation in prostate cancer (PCa) development and progression is presented, focusing on recent advancements in defining the N-glycome through glycomic profiling and glycoproteomic methodologies. Glycosylation is a common post-translational modification typified by oligosaccharides attached N-linked to asparagine or O-linked to serine or threonine on carrier proteins. These attached sugars have crucial roles in protein folding and cellular recognition processes, such that altered glycosylation is a hallmark of cancer pathogenesis and progression. In the past decade, advancements in N-glycan profiling workflows using Matrix Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) technology have been applied to define the spatial distribution of glycans in PCa tissues. Multiple studies applying N-glycan MALDI-MSI to pathology-defined PCa tissues have identified significant alterations in N-glycan profiles associated with PCa progression. N-glycan compositions progressively increase in number, and structural complexity due to increased fucosylation and sialylation. Additionally, significant progress has been made in defining the glycan and glycopeptide compositions of prostatic-derived glycoproteins like prostate-specific antigen in tissues and biofluids. The glycosyltransferases involved in these changes are potential drug targets for PCa, and new approaches in this area are summarized. These advancements will be discussed in the context of the further development of clinical diagnostics and therapeutics targeting glycans and glycoproteins associated with PCa progression. Integration of large scale spatial glycomic data for PCa with other spatial-omic methodologies is now feasible at the tissue and single-cell levels.

Changes in tissue protein N-glycosylation and associated molecular signature occur in the human Parkinsonian brain in a region-specific manner.

Parkinson's disease (PD) associated state of neuroinflammation due to the aggregation of aberrant proteins is widely reported. One type of post-translational modification involved in protein stability is glycosylation. Here, we aimed to characterize the human Parkinsonian nigro-striatal N-glycome, and related transcriptome/proteome, and its correlation with endoplasmic reticulum (ER) stress and unfolded protein response (UPR), providing a comprehensive characterization of the PD molecular signature. Significant changes were seen upon a PD: a 3% increase in sialylation and 5% increase in fucosylation in both regions, and a 2% increase in oligomannosylated N-glycans in the substantia nigra. In the latter, a decrease in the mRNA expression of sialidases and an upregulation in the UPR pathway were also seen. To show the correlation between these, we also describe a small in vitro study where changes in specific glycosylation trait enzymes (inhibition of sialyltransferases) led to impairments in cell mitochondrial activity, changes in glyco-profile, and upregulation in UPR pathways. This complete characterization of the human nigro-striatal N-glycome provides an insight into the glycomic profile of PD through a transversal approach while combining the other PD "omics" pieces, which can potentially assist in the development of glyco-focused therapeutics.

Glycome profiling and immunohistochemistry uncover changes in cell walls of Arabidopsis thaliana roots during spaceflight

A large and diverse library of glycan-directed monoclonal antibodies (mAbs) was used to determine if plant cell walls are modified by low-gravity conditions encountered during spaceflight. This method called glycome profiling (glycomics) revealed global differences in non-cellulosic cell wall epitopes in Arabidopsis thaliana root extracts recovered from RNA purification columns between seedlings grown on the International Space Station-based Vegetable Production System and paired ground (1-g) controls. Immunohistochemistry on 11-day-old seedling primary root sections showed that ten of twenty-two mAbs that exhibited spaceflight-induced increases in binding through glycomics, labeled space-grown roots more intensely than those from the ground. The ten mAbs recognized xyloglucan, xylan, and arabinogalactan epitopes. Notably, three xylem-enriched unsubstituted xylan backbone epitopes were more intensely labeled in space-grown roots than in ground-grown roots, suggesting that the spaceflight environment accelerated root secondary cell wall formation. This study highlights the feasibility of glycomics for high-throughput evaluation of cell wall glycans using only root high alkaline extracts from RNA purification columns, and subsequent validation of these results by immunohistochemistry. This approach will benefit plant space biological studies because it extends the analyses possible from the limited amounts of samples returned from spaceflight and help uncover microgravity-induced tissue-specific changes in plant cell walls.

An improved evanescent fluorescence scanner suitable for high-resolution glycome mapping of formalin-fixed paraffin-embedded tissue sections.

Lectin microarray (LMA) is a high-throughput platform that enables the rapid and sensitive analysis of N- and O-glycans attached to glycoproteins in biological samples, including formalin-fixed paraffin-embedded (FFPE) tissue sections. Here, we evaluated the sensitivity of the advanced scanner based on the evanescent-field fluorescence principle, which is equipped with a 1× infinity correction optical system and a high-end complementary metal-oxide semiconductor (CMOS) image sensor in digital binning mode. Using various glycoprotein samples, we estimated that the mGSR1200-CMOS scanner has at least fourfold higher sensitivity for the lower limit of linearity range than that of a previous charge-coupled device scanner (mGSR1200). A subsequent sensitivity test using HEK293T cell lysates demonstrated that cell glycomic profiling could be performed with only three cells, which has the potential for the glycomic profiling of cell subpopulations. Thus, we examined its application in tissue glycome mapping, as indicated in the online LM-GlycomeAtlas database. To achieve fine glycome mapping, we refined the laser microdissection-assisted LMA procedure to analyze FFPE tissue sections. In this protocol, it was sufficient to collect 0.1 mm2 of each of the tissue fragments from 5-μm-thick sections, which differentiated the glycomic profile between the glomerulus and renal tubules of a normal mouse kidney. In conclusion, the improved LMA enables high-resolution spatial analysis, which expands the possibilities of its application classifying cell subpopulations in clinical FFPE tissue specimens. This will be used in the discovery phase for the development of novel glyco-biomarkers and therapeutic targets, and to expand the range of target diseases.

IgG glycomic profiling identifies potential biomarkers for diagnosis of echinococcosis

Echinococcosis caused by larval stage of the genus Echinococcus, is a serious and potentially fatal parasitic zoonosis distributed globally. The two types of the disease in human are cystic echinococcosis (CE) and alveolar echinococcosis (AE). As the biological and encysting characteristics of the parasite, early diagnosis remains to address. In the present study, we demonstrate the value of Immunoglobulin G (IgG) glycome as a potential diagnostic biomarker for echinococcosis. Serum IgG glycome profiles were analyzed by ultra-performance liquid chromatography in a cohort comprised of 127 echinococcosis patients, of them 98 were diagnosed as CE and 29 as AE. IgG N-glycome analysis in pretreatment serum of echinococcosis patients presents 25 glycans and 64 derived traits. Compared with IgG glycans of healthy control group, neutral glycans, fucosylation and agalactosylated N-glycans increased while sialylation and galactosylation decreased in echinococcosis patients. Combined with a machine-learning-based approach, we built three biomarker combinations to distinguish CE, AE and healthy controls. Meanwhile, galactosylation, sialylation and A2BG2S1 in IgG glycan profiles were evidently associated with different types of CE (from CE1 to CE5). Our findings suggest that the alterations in IgG N-glycome may be of value in CE and AE diagnosis and follow-up CE disease progress. The role of IgG N-glycans as diagnostic biomarker remains to be verified in future study.