Structure and Dynamics of Immunoglobulin G Glycoproteins

Predicting Biochemical and Physiological Parameters: Deep Learning from IgG Glycome Composition

In immunoglobulin G (IgG), N-glycosylation plays a pivotal role in structure and function. It is often altered in different diseases, suggesting that it could be a promising health biomarker. Studies indicate that IgG glycosylation not only associates with various diseases but also has predictive capabilities. Additionally, changes in IgG glycosylation correlate with physiological and biochemical traits known to reflect overall health state. This study aimed to investigate the power of IgG glycans to predict physiological and biochemical parameters. We developed two models using IgG N-glycan data as an input: a regression model using elastic net and a machine learning model using deep learning. Data were obtained from the Korčula and Vis cohorts. The Korčula cohort data were used to train both models, while the Vis cohort was used exclusively for validation. Our results demonstrated that IgG glycome composition effectively predicts several biochemical and physiological parameters, especially those related to lipid and glucose metabolism and cardiovascular events. Both models performed similarly on the Korčula cohort; however, the deep learning model showed a higher potential for generalization when validated on the Vis cohort. This study reinforces the idea that IgG glycosylation reflects individuals' health state and brings us one step closer to implementing glycan-based diagnostics in personalized medicine. Additionally, it shows that the predictive power of IgG glycans can be used for imputing missing covariate data in deep learning frameworks.

Immunoglobulin G glycosylation and its alterations in aging-related diseases

Immunoglobulin G (IgG) is an important serum glycoprotein and a major component of antibodies. Glycans on IgG affect the binding of IgG to the Fc receptor or complement C1q, which in turn affects the biological activity and biological function of IgG. Altered glycosylation patterns on IgG emerge as important biomarkers in the aging process and age-related diseases. Key aging-related alterations observed in IgG glycosylation include reductions in galactosylation and sialylation, alongside increases in agalactosylation, and bisecting GlcNAc. Understanding the role of IgG glycosylation in aging-related diseases offers insights into disease mechanisms and provides opportunities for the development of diagnostic and therapeutic strategies. This review summarizes five aspects of IgG: an overview of IgG, IgG glycosylation, IgG glycosylation with inflammation mediation, IgG glycan changes with normal aging, as well as the relevance of IgG glycan changes to aging-related diseases. This review provides a reference for further investigation of the regulatory mechanisms of IgG glycosylation in aging-related diseases, as well as for evaluating the potential of IgG glycosylation changes as markers of aging and aging-related diseases.

IgG glycans in health and disease: Prediction, intervention, prognosis, and therapy

Immunoglobulin (IgG) glycosylation is a complex enzymatically controlled process, essential for the structure and function of IgG. IgG glycome is relatively stable in the state of homeostasis, yet its alterations have been associated with aging, pollution and toxic exposure, as well as various diseases, including autoimmune and inflammatory diseases, cardiometabolic diseases, infectious diseases and cancer. IgG is also an effector molecule directly involved in the inflammation processes included in the pathogenesis of many diseases. Numerous recently published studies support the idea that IgG N-glycosylation fine-tunes the immune response and plays a significant role in chronic inflammation. This makes it a promising novel biomarker of biological age, and a prognostic, diagnostic and treatment evaluation tool. Here we provide an overview of the current state of knowledge regarding the IgG glycosylation in health and disease, and its potential applications in pro-active prevention and monitoring of various health interventions.

Probiotic Effects of Bacillus licheniformis DSM5749 on Growth Performance and Intestinal Microecological Balance of Laying Hens

This study was conducted to investigate the effects of Bacillus licheniformis DSM5749 on the production performance and intestinal health in laying hens. A total of 32-week-old laying hens (Hyline Brown) were randomly assigned to two dietary groups (10 replicates of 27 laying hens), namely, basal diet and basal diet complemented with 200 g/t B. licheniformis (3.2 × 10⁹ CFU/kg). The trial lasted for 8 weeks, and samples were collected at the last week. Results revealed that B. licheniformis DSM5749 significantly improved laying performance, including an increase in egg production rate and average daily egg yield, and a decrease in the feed-to-egg ratio during the entire 8-week experimental period (P < 0.05). B. licheniformis DSM5749 increased the levels of superoxide dismutase and glutathione peroxidase in the liver and decreased the IL-1 level in the serum (P < 0.05). In addition, the integrity of intestinal morphology (villus height, crypt depth, and villus height/crypt depth), tight junctions (ZO-1, Claudin-1, and Occludin), and lipase vitality in the intestine were potentiated by B. licheniformis DSM5749 in laying hens (P < 0.05). B. licheniformis DSM5749 decreased the Firmicutes/Bacteroidetes ratio (P < 0.05) in the cecum. Furthermore, B. licheniformis DSM5749 modulated the microbiota in the cecum of the laying hens, increased the relative abundance of beneficial bacteria (e.g., Prevotella) at the genus level and decreased the relative abundance of potential pathogens (e.g., Desulfovibrio). In conclusion, B. licheniformis DSM5749 can improve laying performance, promote intestinal health, affect the composition of cecal microorganisms, and regulate the intestinal micro-ecological balance, making B. licheniformis a good probiotic candidate for application in the laying hens industry.

Glutamine-free mammalian expression of recombinant glycoproteins with uniform isotope labeling: an application for NMR analysis of pharmaceutically relevant Fc glycoforms of human immunoglobulin G1

Mammalian cells are widely used for producing recombinant glycoproteins of pharmaceutical interest. However, a major drawback of using mammalian cells is the high production costs associated with uniformly isotope-labeled glycoproteins due to the large quantity of labeled L-glutamine required for their growth. To address this problem, we developed a cost-saving method for uniform isotope labeling by cultivating the mammalian cells under glutamine-free conditions, which was achieved by co-expression of glutamine synthase. We demonstrate the utility of this approach using fucosylated and non-fucosylated Fc glycoforms of human immunoglobulin G1.

Variation of IgG N-linked glycosylation profile in diabetic retinopathy

BACKGROUND

The relationship of immunoglobulin G (IgG) glycosylation with diabetes and diabetic nephropathy has been reported, but its role in diabetic retinopathy (DR) remains unclear. We aimed to investigate and validate the association of IgG glycosylation with DR.

METHODS

We analyzed the IgG N-linked glycosylation profile and primarily selected candidate glycans by lasso (least absolute shrinkage and selection operator) regression analysis in the discovery population. The findings were validated in the replication population using a binary logistics model. The association between the significant glycosylation panel and clinical features was illustrated with Spearman's coefficient. The results were confirmed by sensitivity analyses.

RESULTS

Among 16 selected glycan candidates using lasso, two IgG glycans (GP15, GP20) and two derived traits (IGP32, IGP54) were identified and validated to be significantly associated with DR (P < .05), and the combined adjusted odds ratios (ORs) were 0.587, 0.613, 1.970, and 0.593, respectively. The glycosylation panel showed a weak correlation with clinical features, except for age. In addition, the results remained consistent when the subjects with prediabetes were excluded from the controls, and the adjusted ORs were 0.677, 0.738, 1.597, and 0.678 in the whole population. Furthermore, in the 1:3 rematched population, a significant association was observed, apart from GP20.

CONCLUSIONS

The IgG glycosylation profile, reflecting an aging and pro-inflammatory status, was significantly associated with DR. The variation in the IgG glycome deserves more attention in diabetic complications.

Rigid monoclonal antibodies improve detection of SARS-CoV-2 nucleocapsid protein

Monoclonal antibodies (mAbs) are the basis of treatments and diagnostics for pathogens and other biological phenomena. We conducted a structural characterization of mAbs against the N-terminal domain of nucleocapsid protein (NP NTD ) from SARS-CoV-2 using small angle X-ray scattering (SAXS). Our solution-based results distinguished the mAbs' flexibility and how this flexibility impacts the assembly of multiple mAbs on an antigen. By pairing two mAbs that bind different epitopes on the NP NTD , we show that flexible mAbs form a closed sandwich-like complex. With rigid mAbs, a juxtaposition of the Fabs is prevented, enforcing a linear arrangement of the mAb pair, which facilitates further mAb polymerization. In a modified sandwich ELISA, we show the rigid mAb-pairings with linear polymerization led to increased NP NTD detection sensitivity. These enhancements can expedite the development of more sensitive and selective antigen-detecting point-of-care lateral flow devices (LFA), key for early diagnosis and epidemiological studies of SARS-CoV-2 and other pathogens.

Rigid monoclonal antibodies improve detection of SARS-CoV-2 nucleocapsid protein

Monoclonal antibodies (mAbs) are the basis of treatments and diagnostics for pathogens and other biological phenomena. We conducted a structural characterization of mAbs against the N-terminal domain of nucleocapsid protein (NPNTD) from SARS-CoV-2 using small-angle X-ray scattering and transmission electron microscopy. Our solution-based results distinguished the mAbs' flexibility and how this flexibility affects the assembly of multiple mAbs on an antigen. By pairing two mAbs that bind different epitopes on the NPNTD, we show that flexible mAbs form a closed sandwich-like complex. With rigid mAbs, a juxtaposition of the antigen-binding fragments is prevented, enforcing a linear arrangement of the mAb pair, which facilitates further mAb polymerization. In a modified sandwich enzyme-linked immunosorbent assay, we show that rigid mAb-pairings with linear polymerization led to increased NPNTD detection sensitivity. These enhancements can expedite the development of more sensitive and selective antigen-detecting point-of-care lateral flow devices, which are critical for early diagnosis and epidemiological studies of SARS-CoV-2 and other pathogens.

NMR of glycoproteins: profiling, structure, conformation and interactions

In glycoproteins, carbohydrates are responsible for the selective interaction and tight regulation of cellular processes, constituting the main information transducer interface in protein-glycoprotein interactions. Increasing experimental and computational evidence suggest that such interactions often induce allosteric changes in the host protein, underlining the importance of studying intact glycoproteins. Technical issues have precluded such studies for years but, nowadays, a promising era is emerging where NMR spectroscopy, among other techniques, allows the characterization of the composition, structure and segmental dynamics of glycoproteins. In this review, we discuss such advances and highlight some selected examples. This novel technology unravels multiple new functional mechanisms, subtly hidden within the sugar code.

Biophysical characterization of dynamic structures of immunoglobulin G

Immunoglobulin G (IgG) is a major antibody and functions as a hub linking specific antigen binding and recruitment of effector molecules typified by Fcγ receptors (FcγRs). These activities are associated primarily with interactions involving its Fab and Fc sites, respectively. An IgG molecule is characterized by a multiple domain modular structure with conserved N-glycosylation in Fc. The molecule displays significant freedom in internal motion on various spatiotemporal scales. The consequent conformational flexibility and plasticity of IgG glycoproteins are functionally significant and potentially important factors for design and engineering of antibodies with enhanced functionality. In this article, experimental and computational approaches are outlined for characterizing the conformational dynamics of IgG molecules in solution. In particular, the importance of integration of these approaches is highlighted, as illustrated by dynamic intramolecular interactions between the pair of N-glycans and their proximal amino acid residues in Fc. These interactions can critically affect effector functions mediated by human IgG1 and FcγRIII. Further improvements in individual biophysical techniques and their integration will advance understanding of dynamic behaviors of antibodies in physiological and pathological conditions. Such understanding will provide opportunities for engineering antibodies through controlling allosteric networks in IgG molecules.