Variability of human Alpha-1-acid glycoprotein N-glycome in a Caucasian population.

AIM: Alpha-1-acid glycoprotein (AGP) is a highly glycosylated protein in human plasma and one of the most abundant acute phase proteins in humans. Glycosylation plays a crucial role in its biological functions, and alterations in AGP N-glycome have been associated with various diseases and inflammatory conditions. However, large-scale studies of AGP N-glycosylation in the general population are lacking. METHODS: Using recently developed high-throughput glycoproteomic workflow for site-specific AGP N-glycosylation analysis, 803 individuals from the Croatian island of Korcula were analyzed and their AGP N-glycome data associated with biochemical and physiological traits, as well as different environmental factors. RESULTS: After regression analysis, we found that AGP N-glycosylation is strongly associated with sex, somewhat less with age, along with multiple biochemical and physiological traits (e.g. BMI, triglycerides, uric acid, glucose, smoking status, fibrinogen). CONCLUSION: For the first time we have extensively explored the inter-individual variability of AGP N-glycome in a general human population, demonstrating its changes with sex, age, biochemical, and physiological status of individuals, providing the baseline for future population and clinical studies.

Influence of Desialylation on the Drug Binding Affinity of Human Alpha-1-Acid Glycoprotein Assessed by Microscale Thermophoresis.

Human serum alpha-1-acid glycoprotein (AAG) is an acute-phase plasma protein involved in the binding and transport of many drugs, especially basic and lipophilic substances. The sialic acid groups that terminate the N-glycan chains of AAG have been reported to change in response to numerous health conditions and may have an impact on the binding of drugs to AAG. In this study, we quantified the binding between native and desialylated AAG and seven drugs from different pharmacotherapeutic groups (carvedilol, diltiazem, dipyridamole, imipramine, lidocaine, propranolol, vinblastine) using microscale thermophoresis (MST). This method was chosen due to its robustness and high sensitivity, allowing precise quantification of molecular interactions based on the thermophoretic movement of fluorescent molecules. Detailed glycan analysis of native and desialylated AAG showed over 98% reduction in sialic acid content for the enzymatically desialylated AAG. The MST results indicate that desialylation generally alters the binding affinity between AAG and drugs, leading to either an increase or decrease in Kd values, probably due to conformational changes of AAG caused by the different sialic acid content. This effect is also reflected in an increased denaturation temperature of desialylated AAG. Our findings indicate that desialylation impacts free drug concentrations differently, depending on the binding affinity of the drug with AAG relative to human serum albumin (HSA). For drugs such as dipyridamole, lidocaine, and carvedilol, which have a higher affinity for AAG, desialylation significantly changes free drug concentrations. In contrast, drugs such as propranolol, imipramine, and vinblastine, which have a strong albumin binding, show only minimal changes. It is noteworthy that the free drug concentration of dipyridamole is particularly sensitive to changes in AAG concentration and glycosylation, with a decrease of up to 15% being observed, underscoring the need for dosage adjustments in personalized medicine.

Mapping of the gene network that regulates glycan clock of ageing.

Glycans are an essential structural component of immunoglobulin G (IgG) that modulate its structure and function. However, regulatory mechanisms behind this complex posttranslational modification are not well known. Previous genome-wide association studies (GWAS) identified 29 genomic regions involved in regulation of IgG glycosylation, but only a few were functionally validated. One of the key functional features of IgG glycosylation is the addition of galactose (galactosylation), a trait which was shown to be associated with ageing. We performed GWAS of IgG galactosylation (N=13,705) and identified 16 significantly associated loci, indicating that IgG galactosylation is regulated by a complex network of genes that extends beyond the galactosyltransferase enzyme that adds galactose to IgG glycans. Gene prioritization identified 37 candidate genes. Using a recently developed CRISPR/dCas9 system we manipulated gene expression of candidate genes in the in vitro IgG expression system. Upregulation of three genes, EEF1A1, MANBA and TNFRSF13B, changed the IgG glycome composition, which confirmed that these three genes are involved in IgG galactosylation in this in vitro expression system.

Human complement component C3 N-glycome changes in type 1 diabetes complications.

Aim: Changes in N-glycosylation have been described in numerous diseases and are being considered as biomarkers of ongoing pathological condition. Previous studies demonstrated the interrelation of N-glycosylation and type 1 diabetes (T1D), particularly linking serum N-glycan changes with complications accompanying the disease. Moreover, the role of complement component C3 in diabetic nephropathy and retinopathy has been implicated, and C3 N-glycome was found to be altered in young T1D patients. Therefore, we investigated associations between C3 N-glycan profiles and albuminuria and retinopathy accompanying T1D, as well as glycosylation connection with other known T1D complication risk factors. Research design and methods: Complement component C3 N-glycosylation profiles have been analyzed from 189 serum samples of T1D patients (median age 46) recruited at a Croatian hospital centre. Using our recently developed high-throughput method, relative abundances of all six of the C3 glycopeptides have been determined. Assessment of C3 N-glycome interconnection with T1D complications, hypertension, smoking status, estimated glomerular filtration rate (eGFR), glycaemic control and duration of the disease was done using linear modelling. Results: Significant changes of C3 N-glycome in severe albuminuria accompanying type 1 diabetes were observed, as well as in T1D subjects with hypertension. All except one of the C3 glycopeptides proved to be associated with measured HbA1c levels. One of the glycoforms was shown to be changed in non-proliferative T1D retinopathy. Smoking and eGFR showed no effect on C3 N-glycome. Furthermore, C3 N-glycosylation profile was shown to be independent of disease duration. Conclusion: This study empowered the role of C3 N-glycosylation in T1D, showing value in distinguishing subjects with different diabetic complications. Being independent of the disease duration, these changes may be associated with the disease onset, making C3 N-glycome a potential novel marker of the disease progression and severity.

Potential Clinically Relevant Effects of Sialylation on Human Serum AAG-Drug Interactions Assessed by Isothermal Titration Calorimetry: Insight into Pharmacoglycomics?

Human serum alpha-1 acid glycoprotein is an acute-phase plasma protein involved in the binding and transport of many drugs, especially basic and lipophilic substances. It has been reported that the sialic acid groups that terminate the N-glycan chains of alpha-1 acid glycoprotein change in response to certain health conditions and may have a major impact on drug binding to alpha-1 acid glycoprotein. The interaction between native or desialylated alpha-1 acid glycoprotein and four representative drugs-clindamycin, diltiazem, lidocaine, and warfarin-was quantitatively evaluated using isothermal titration calorimetry. The calorimetry assay used here is a convenient and widely used approach to directly measure the amount of heat released or absorbed during the association processes of biomolecules in solution and to quantitatively estimate the thermodynamics of the interaction. The results showed that the binding of drugs with alpha-1 acid glycoprotein were enthalpy-driven exothermic interactions, and the binding affinity was in the range of 10-5-10-6 M. Desialylated alpha-1 acid glycoprotein showed significantly different binding with diltiazem, lidocaine, and warfarin compared with native alpha-1 acid glycoprotein, whereas clindamycin showed no significant difference. Therefore, a different degree of sialylation may result in different binding affinities, and the clinical significance of changes in sialylation or glycosylation of alpha-1 acid glycoprotein in general should not be neglected.

Integrated glycomics and genetics analyses reveal a potential role for N-glycosylation of plasma proteins and IgGs, as well as the complement system, in the development of type 1 diabetes.

AIMS/HYPOTHESIS: We previously demonstrated that N-glycosylation of plasma proteins and IgGs is different in children with recent-onset type 1 diabetes compared with their healthy siblings. To search for genetic variants contributing to these changes, we undertook a genetic association study of the plasma protein and IgG N-glycome in type 1 diabetes. METHODS: A total of 1105 recent-onset type 1 diabetes patients from the Danish Registry of Childhood and Adolescent Diabetes were genotyped at 183,546 genetic markers, testing these for genetic association with variable levels of 24 IgG and 39 plasma protein N-glycan traits. In the follow-up study, significant associations were validated in 455 samples. RESULTS: This study confirmed previously known plasma protein and/or IgG N-glycosylation loci (candidate genes MGAT3, MGAT5 and ST6GAL1, encoding beta-1,4-mannosyl-glycoprotein 4-beta-N-acetylglucosaminyltransferase, alpha-1,6-mannosylglycoprotein 6-beta-N-acetylglucosaminyltransferase and ST6 beta-galactoside alpha-2,6-sialyltransferase 1 gene, respectively) and identified novel associations that were not previously reported for the general European population. First, novel genetic associations of IgG-bound glycans were found with SNPs on chromosome 22 residing in two genomic intervals close to candidate gene MGAT3; these include core fucosylated digalactosylated disialylated IgG N-glycan with bisecting N-acetylglucosamine (GlcNAc) (pdiscovery=7.65 × 10-12, preplication=8.33 × 10-6 for the top associated SNP rs5757680) and core fucosylated digalactosylated glycan with bisecting GlcNAc (pdiscovery=2.88 × 10-10, preplication=3.03 × 10-3 for the top associated SNP rs137702). The most significant genetic associations of IgG-bound glycans were those with MGAT3. Second, two SNPs in high linkage disequilibrium (missense rs1047286 and synonymous rs2230203) located on chromosome 19 within the protein coding region of the complement C3 gene (C3) showed association with the oligomannose plasma protein N-glycan (pdiscovery=2.43 × 10-11, preplication=8.66 × 10-4 for the top associated SNP rs1047286). CONCLUSIONS/INTERPRETATION: This study identified novel genetic associations driving the distinct N-glycosylation of plasma proteins and IgGs identified previously at type 1 diabetes onset. Our results highlight the importance of further exploring the potential role of N-glycosylation and its influence on complement activation and type 1 diabetes susceptibility.

In a pursuit of optimal glycan fluorescent label for negative MS mode for high-throughput N-glycan analysis.

Over the past few decades, essential role of glycosylation in protein functioning has become widely recognized, rapidly advancing glycan analysis techniques. Because free glycan's lack chromophore or fluorophore properties, and do not ionize well, they are often derivatized to facilitate their separation or detection, and to enhance the sensitivity of the analysis. Released glycan's are usually derivatized using a fluorescent tag, which enables their optical detection in LC profiling. Some fluorescent labels can also promote ionization efficiency, thus facilitating MS detection. For this reason, there is a need to design fluorophores that will contribute more to the fluorescence and ionization of glycan's and the need to quantify these contributions to improve glycan analysis methods. In this paper we focused on negative MS mode as these methods are more informative than methods involving positive MS mode, allowing for a less ambiguous elucidation of detailed glycan structures. Additionally, traditional glycan labels in negative mode MS usually result with diminished sensitivity compared to positive mode, thus making selection of appropriate label even more important for successful high-throughput analysis. Therefore, eleven fluorescent labels of different chemo-physical properties were chosen to study the influence of label hydrophobicity and presence of a negative charge on glycan ionization in negative MS mode. N-glycans released from IgG sample were labeled with one of the eleven labels, purified with HILIC-SPE and analyzed with HILIC-UPLC-FLR-MS. To make evaluation of studied labels performance more objective, analysis was performed in two laboratories and at two mobile phase pH (4.4 and 7.4). Although there was a notable trend of more hydrophobic labels having bigger signal intensities in one laboratory, we observed no such trend in the other laboratory. The results show that MS parameters and intrinsic configuration of the spectrometer have even bigger effect on the final ESI response of the labeled-glycan ionization in negative MS mode that the labels themselves. With this in mind, further research and development of fluorophores that will be suitable for high-throughput glycan analysis in the negative MS mode are proposed.

High-Throughput Human Complement C3 N-Glycoprofiling Identifies Markers of Early Onset Type 1 Diabetes Mellitus in Children.

Recently, it was shown that children at the onset of type 1 diabetes (T1D) have a higher proportion of oligomannose glycans in their total plasma protein N-glycome compared to their healthy siblings. The most abundant complement component, glycoprotein C3, contains two N-glycosylation sites occupied exclusively by this type of glycans. Furthermore, complement system, as well as C3, was previously associated with T1D. It is also known that changes in glycosylation can modulate inflammatory responses, so our aim was to characterize the glycosylation profile of C3 in T1D. For this purpose, we developed a novel high-throughput workflow for human C3 concanavalin A lectin affinity enrichment and subsequent LC-MS glycopeptide analysis which enables protein-specific N-glycosylation profiling. From the Danish Childhood Diabetes Register, plasma samples of 61 children/adolescents newly diagnosed with T1D and 84 of their unaffected siblings were C3 N-glycoprofiled. Significant changes of C3 N-glycan profiles were found. T1D was associated with an increase in the proportion of unprocessed glycan structures with more mannose units. A regression model including C3 N-glycans showed notable discriminative power between children with early onset T1D and their healthy siblings with area under curve of 0.879. This study confirmed our previous findings of plasma high-mannose glycan changes in a cohort of recent onset T1D cases, suggesting the involvement of C3 N-glycome in T1D development. Our C3 glycan-based discriminative model could be valuable in assessment of T1D risk in children.

Fucosylated AGP glycopeptides as biomarkers of HNF1A-Maturity onset diabetes of the young.

AIMS: We previously demonstrated that antennary fucosylated N-glycans on plasma proteins are regulated by HNF1A and can identify cases of Maturity-Onset Diabetes of the Young caused by HNF1A variants (HNF1A-MODY). Based on literature data, we further postulated that N-glycans with best diagnostic value mostly originate from alpha-1-acid glycoprotein (AGP). In this study we analyzed fucosylation of AGP in subjects with HNF1A-MODY and other types of diabetes aiming to evaluate its diagnostic potential. METHODS: A recently developed LC-MS method for AGP N-glycopeptide analysis was utilized in two independent cohorts: a) 466 subjects with different diabetes subtypes to test the fucosylation differences, b) 98 selected individuals to test the discriminative potential for pathogenic HNF1A variants. RESULTS: Our results showed significant reduction in AGP fucosylation associated to HNF1A-MODY when compared to other diabetes subtypes. Additionally, ROC curve analysis confirmed significant discriminatory potential of individual fucosylated AGP glycopeptides, where the best performing glycopeptide had an AUC of 0.94 (95% CI 0.90-0.99). CONCLUSIONS: A glycopeptide based diagnostic tool would be beneficial for patient stratification by providing information about the functionality of HNF1A. It could assist the interpretation of DNA sequencing results and be a useful addition to the differential diagnostic process.

Mass Spectrometry-Based Methods for Immunoglobulin G N-Glycosylation Analysis.

Mass spectrometry and its hyphenated techniques enabled by the improvements in liquid chromatography, capillary electrophoresis, novel ionization, and fragmentation modes are truly a cornerstone of robust and reliable protein glycosylation analysis. Boost in immunoglobulin G (IgG) glycan and glycopeptide profiling demands for both applied biomedical and research applications has brought many new advances in the field in terms of technical innovations, sample preparation, improved throughput, and confidence in glycan structural characterization. This chapter summarizes mass spectrometry basics, focusing on IgG and monoclonal antibody N-glycosylation analysis on several complexity levels. Different approaches, including antibody enrichment, glycan release, labeling, and glycopeptide preparation and purification, are covered and illustrated with recent breakthroughs and examples from the literature omitting excessive theoretical frameworks. Finally, selected highly popular methodologies in IgG glycoanalytics such as liquid chromatography-mass spectrometry and matrix-assisted laser desorption ionization are discussed more thoroughly yet in simple terms making this text a practical starting point either for the beginner in the field or an experienced clinician trying to make sense out of the IgG glycomic or glycoproteomic dataset.

Plasma N-glycome shows continuous deterioration as the diagnosis of insulin resistance approaches.

INTRODUCTION: Prediction of type 2 diabetes mellitus (T2DM) and its preceding factors, such as insulin resistance (IR), is of great importance as it may allow delay or prevention of onset of the disease. Plasma protein N-glycome has emerged as a promising predictive biomarker. In a prospective longitudinal study, we included patients with a first diagnosis of impaired glucose metabolism (IR or T2DM) to investigate the N-glycosylation's predictive value years before diabetes development. RESEARCH DESIGN AND METHODS: Plasma protein N-glycome was profiled by hydrophilic interaction ultra-performance liquid chromatography in 534 TwinsUK participants free from disease at baseline. This included 89 participants with incident diagnosis of IR or T2DM during the follow-up period (7.14±3.04 years) whose last sample prior to diagnosis was compared using general linear regression with 445 age-matched unrelated controls. Findings were replicated in an independent cohort. Changes in N-glycome have also been presented in connection with time to diagnosis. RESULTS: Eight groups of plasma N-glycans were different between incident IR or T2DM cases and controls (p<0.05) after adjusting for multiple testing using Benjamini-Hochberg correction. These differences were noticeable up to 10 years prior to diagnosis and are changing continuously as becoming more expressed toward the diagnosis. The prediction model was built using significant glycan traits, displaying a discriminative performance with an area under the receiver operating characteristic curve of 0.77. CONCLUSIONS: In addition to previous studies, we showed the diagnostic potential of plasma N-glycome in the prediction of both IR and T2DM development years before the clinical manifestation and indicated the continuous deterioration of N-glycome toward the diagnosis.

High-Throughput and Site-Specific N-Glycosylation Analysis of Human Alpha-1-Acid Glycoprotein Offers a Great Potential for New Biomarker Discovery.

Alpha-1-acid glycoprotein (AGP) is an acute phase glycoprotein in blood, which is primarily synthetized in the liver and whose biological role is not completely understood. It consists of 45% carbohydrates that are present in the form of five N-linked complex glycans. AGP N-glycosylation was shown to be changed in many different diseases, and some changes appear to be disease-specific; thus, it has a great diagnostic and prognostic potential. However, AGP glycosylation was mainly analyzed in small cohorts and without detailed site-specific glycan information. Here, we developed a cost-effective method for a high-throughput and site-specific N-glycosylation LC-MS analysis of AGP which can be applied on large cohorts, aid in search for novel disease biomarkers, and enable better understanding of AGP's role and function in health and disease. The method does not require isolation of AGP with antibodies and affinity chromatography, but AGP is enriched by acid precipitation from 5 µl of bloodplasma in a 96-well format. After trypsinization, AGP glycopeptides are purified using a hydrophilic interaction chromatography-based solid-phase extraction and analyzed by reversed-phase-liquid chromatography-electrospray ionization-MS. We used our method to show for the first time that AGP N-glycan profile is stable in healthy individuals (14 individuals in three time points), which is a requirement for evaluation of its diagnostic potential. Furthermore, we tested our method on a population including individuals with registered hyperglycemia in critical illness (59 cases and 49 controls), which represents a significantly increased risk of developing type 2 diabetes. Individuals at higher risk of diabetes presented increased N-glycan branching on AGP's second glycosylation site and lower sialylation of N-glycans on AGP's third and AGP1's fourth glycosylation site. Although this should be confirmed on a larger prospective cohort, it indicates that site-specific AGP N-glycan profile could help distinguish individuals who are at risk of type 2 diabetes.

A strategy to incorporate prior knowledge into correlation network cutoff selection.

Correlation networks are frequently used to statistically extract biological interactions between omics markers. Network edge selection is typically based on the statistical significance of the correlation coefficients. This procedure, however, is not guaranteed to capture biological mechanisms. We here propose an alternative approach for network reconstruction: a cutoff selection algorithm that maximizes the overlap of the inferred network with available prior knowledge. We first evaluate the approach on IgG glycomics data, for which the biochemical pathway is known and well-characterized. Importantly, even in the case of incomplete or incorrect prior knowledge, the optimal network is close to the true optimum. We then demonstrate the generalizability of the approach with applications to untargeted metabolomics and transcriptomics data. For the transcriptomics case, we demonstrate that the optimized network is superior to statistical networks in systematically retrieving interactions that were not included in the biological reference used for optimization.

Global variability of the human IgG glycome.

Immunoglobulin G (IgG) is the most abundant serum antibody which structural characteristics and effector functions are modulated through the attachment of various sugar moieties called glycans. Composition of the IgG N-glycome changes with age of an individual and in different diseases. Variability of IgG glycosylation within a population is well studied and is known to be affected by both genetic and environmental factors. However, global inter-population differences in IgG glycosylation have never been properly addressed. Here we present population-specific N-glycosylation patterns of IgG, analyzed in 5 different populations totaling 10,482 IgG glycomes, and of IgG's fragment crystallizable region (Fc), analyzed in 2,579 samples from 27 populations sampled across the world. Country of residence associated with many N-glycan features and the strongest association was with monogalactosylation where it explained 38% of variability. IgG monogalactosylation strongly correlated with the development level of a country, defined by United Nations health and socioeconomic development indicators, and with the expected lifespan. Subjects from developing countries had low levels of IgG galactosylation, characteristic for inflammation and ageing. Our results suggest that citizens of developing countries may be exposed to environmental factors that can cause low-grade chronic inflammation and the apparent increase in biological age.

Systematic Evaluation of Normalization Methods for Glycomics Data Based on Performance of Network Inference.

Glycomics measurements, like all other high-throughput technologies, are subject to technical variation due to fluctuations in the experimental conditions. The removal of this non-biological signal from the data is referred to as normalization. Contrary to other omics data types, a systematic evaluation of normalization options for glycomics data has not been published so far. In this paper, we assess the quality of different normalization strategies for glycomics data with an innovative approach. It has been shown previously that Gaussian Graphical Models (GGMs) inferred from glycomics data are able to identify enzymatic steps in the glycan synthesis pathways in a data-driven fashion. Based on this finding, here, we quantify the quality of a given normalization method according to how well a GGM inferred from the respective normalized data reconstructs known synthesis reactions in the glycosylation pathway. The method therefore exploits a biological measure of goodness. We analyzed 23 different normalization combinations applied to six large-scale glycomics cohorts across three experimental platforms: Liquid Chromatography - ElectroSpray Ionization - Mass Spectrometry (LC-ESI-MS), Ultra High Performance Liquid Chromatography with Fluorescence Detection (UHPLC-FLD), and Matrix Assisted Laser Desorption Ionization - Furier Transform Ion Cyclotron Resonance - Mass Spectrometry (MALDI-FTICR-MS). Based on our results, we recommend normalizing glycan data using the 'Probabilistic Quotient' method followed by log-transformation, irrespective of the measurement platform. This recommendation is further supported by an additional analysis, where we ranked normalization methods based on their statistical associations with age, a factor known to associate with glycomics measurements.

Glycosylation of immunoglobulin G is regulated by a large network of genes pleiotropic with inflammatory diseases.

Effector functions of immunoglobulin G (IgG) are regulated by the composition of a glycan moiety, thus affecting activity of the immune system. Aberrant glycosylation of IgG has been observed in many diseases, but little is understood about the underlying mechanisms. We performed a genome-wide association study of IgG N-glycosylation (N = 8090) and, using a data-driven network approach, suggested how associated loci form a functional network. We confirmed in vitro that knockdown of IKZF1 decreases the expression of fucosyltransferase FUT8, resulting in increased levels of fucosylated glycans, and suggest that RUNX1 and RUNX3, together with SMARCB1, regulate expression of glycosyltransferase MGAT3. We also show that variants affecting the expression of genes involved in the regulation of glycoenzymes colocalize with variants affecting risk for inflammatory diseases. This study provides new evidence that variation in key transcription factors coupled with regulatory variation in glycogenes modifies IgG glycosylation and has influence on inflammatory diseases.

Heritability of Human Plasma N-Glycome.

The N-glycosylation profile of total human plasma proteins could be a useful biomarker for various pathological states. Reliable high-throughput methods for such profiling have been developed. However, studies of relative importance of genetic and environmental factors in regulating plasma N-glycome are scarce. The aim of our study was to determine the role of genetic factors in phenotypic variation of plasma N-glycan profile through the estimates of its heritability. Thirty-nine total plasma N-glycome traits were analyzed in 2816 individuals from the TwinsUK data set. For the majority of the traits, high heritability estimates (>50%) were obtained pointing at a significant contribution of genetic factors in plasma N-glycome variation, especially for glycans mostly attached to immunoglobulins. We have also found several structures with higher environmental contribution to their variation.

Antagonistic and synergistic epigenetic modulation using orthologous CRISPR/dCas9-based modular system.

Establishing causal relationship between epigenetic marks and gene transcription requires molecular tools, which can precisely modify specific genomic regions. Here, we present a modular and extensible CRISPR/dCas9-based toolbox for epigenetic editing and direct gene regulation. It features a system for expression of orthogonal dCas9 proteins fused to various effector domains and includes a multi-gRNA system for simultaneous targeting dCas9 orthologs to up to six loci. The C- and N-terminal dCas9 fusions with DNMT3A and TET1 catalytic domains were thoroughly characterized. We demonstrated simultaneous use of the DNMT3A-dSpCas9 and TET1-dSaCas9 fusions within the same cells and showed that imposed cytosine hyper- and hypo-methylation altered level of gene transcription if targeted CpG sites were functionally relevant. Dual epigenetic manipulation of the HNF1A and MGAT3 genes, involved in protein N-glycosylation, resulted in change of the glycan phenotype in BG1 cells. Furthermore, simultaneous targeting of the TET1-dSaCas9 and VPR-dSpCas9 fusions to the HNF1A regulatory region revealed strong and persistent synergistic effect on gene transcription, up to 30 days following cell transfection, suggesting involvement of epigenetic mechanisms in maintenance of the reactivated state. Also, modulation of dCas9 expression effectively reduced off-target effects while maintaining the desired effects on target regions.

Intense Physical Exercise Induces an Anti-inflammatory Change in IgG N-Glycosylation Profile.

Exercise is known to improve many aspects of human health, including modulation of the immune system and inflammatory status. It is generally understood that exercise reduces inflammation, but there are missing links in terms of understanding the mechanisms as well as the differences between exercise modalities. N-glycosylation of immunoglobulin G (IgG) and total plasma proteins was previously shown to reflect changes in inflammatory pathways, which could provide valuable information to further clarify exercise effects. In order to further expand the understanding of the relationship between physical activity and inflammation, we examined the effect of intense exercise, in the form of repeated sprint training (RST), on IgG and total plasma proteins N-glycosylation in combination with traditionally used inflammation markers: C-reactive protein (CRP), interleukin 6 (IL-6), and leukocyte count. Twenty-nine male physical education students were separated into treatment (RST, N = 15) and control (N = 14) groups. The RST group completed a 6-week exercise protocol while the control group was instructed to refrain from organized physical activity for the duration of the study. Three blood samples were taken at different time points: prior to start of the training program, the final week of the exercise intervention (EXC), and at the end of the 4-week recovery period (REC). Following the end of the recovery period IgG N-glycosylation profiles showed anti-inflammatory changes in RST group compared to the control group, which manifested as a decrease in agalactosylated (p = 0.0473) and an increase in digalactosylated (p = 0.0473), and monosialylated (p = 0.0339) N-glycans. Plasma protein N-glycans didn't change significantly, while traditional inflammatory markers also didn't show significant change in inflammatory status. Observed results demonstrate the potential of intense physical exercise to reduce levels of systemic basal inflammation as well as the potential for IgG N-glycosylation to serve as a sensitive longitudinal systemic inflammation marker.

N-glycosylation patterns of plasma proteins and immunoglobulin G in chronic obstructive pulmonary disease.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a complex condition, whose diagnosis requires spirometric assessment. However, considering its heterogeneity, subjects with similar spirometric parameters do not necessarily have the same functional status. To overcome this limitation novel biomarkers for COPD have been investigated. Therefore, we aimed to explore the potential value of N-glycans as COPD biomarkers and to examine the individual variation of plasma protein and immunoglobulin G (IgG) glycosylation profiles in subjects with COPD and healthy controls. METHODS: Both the total plasma protein and IgG N-glycome have been profiled in the total of 137 patients with COPD and 95 matching controls from Croatia. Replication cohort consisted of 61 subjects with COPD and 148 controls recruited at another Croatian medical centre. RESULTS: Plasma protein N-glycome in COPD subjects exhibited significant decrease in low branched and conversely, an increase in more complex glycan structures (tetragalactosylated, trisialylated, tetrasialylated and antennary fucosylated glycoforms). We also observed a significant decline in plasma monogalactosylated species, and the same change replicated in IgG glycome. N-glycans also showed value in distinguishing subjects in different COPD GOLD stages, where the relative abundance of more complex glycan structures increased as the disease progressed. Glycans also showed statistically significant associations with the frequency of exacerbations and demonstrated to be affected by smoking, which is the major risk factor for COPD development. CONCLUSIONS: This study showed that complexity of glycans associates with COPD, mirroring also the disease severity. Moreover, changes in N-glycome associate with exacerbation frequency and are affected by smoking. In general, this study provided new insights into plasma protein and IgG N-glycome changes occurring in COPD and pointed out potential novel markers of the disease progression and severity.