Imeglimin-mediated glycemic control in maternally inherited deafness and diabetes.

Mitochondrial dysfunction causes maternally inherited deafness and diabetes (MIDD). Herein, we report improved glycemic control in a 47-year-old Japanese woman with MIDD using imeglimin without major adverse effects. Biochemical tests and metabolome analysis were performed before and after imeglimin administration. Blood glucose level fluctuations were determined. Sulfonylureas, dipeptidyl peptidase-4 inhibitors (DPP4is), and sodium glucose transporter-2 inhibitors (SGLT2i) were administered to evaluate the efficacy of their combination with imeglimin. Imeglimin decreased the HbA1c and ammonia levels and increased the time-in-range, C-peptide reactivity, and glucagon level. Elevated citrulline and histamine levels were decreased by imeglimin. The hypoglycemic effect was not enhanced by imeglimin when combined with sulfonylurea or DPP4i, but the blood glucose level was improved when combined with SGLT2i. Imeglimin improved glucose concentration-dependent insulin secretion and maximized the insulin secretory capacity by improving mitochondrial function and glutamine metabolism and urea circuit abnormalities by promoting glucagon secretion. Imeglimin could improve glycemic control in MIDD.

Unveiling the affinity-stability relationship in anti-measles virus antibodies: a computational approach for hotspots prediction.

Recent years have seen an uptick in the use of computational applications in antibody engineering. These tools have enhanced our ability to predict interactions with antigens and immunogenicity, facilitate humanization, and serve other critical functions. However, several studies highlight the concern of potential trade-offs between antibody affinity and stability in antibody engineering. In this study, we analyzed anti-measles virus antibodies as a case study, to examine the relationship between binding affinity and stability, upon identifying the binding hotspots. We leverage in silico tools like Rosetta and FoldX, along with molecular dynamics (MD) simulations, offering a cost-effective alternative to traditional in vitro mutagenesis. We introduced a pattern in identifying key residues in pairs, shedding light on hotspots identification. Experimental physicochemical analysis validated the predicted key residues by confirming significant decrease in binding affinity for the high-affinity antibodies to measles virus hemagglutinin. Through the nature of the identified pairs, which represented the relative hydropathy of amino acid side chain, a connection was proposed between affinity and stability. The findings of the study enhance our understanding of the interactions between antibody and measles virus hemagglutinin. Moreover, the implications of the observed correlation between binding affinity and stability extend beyond the field of anti-measles virus antibodies, thereby opening doors for advancements in antibody research.

Electrostatic-triggered exothermic antibody adsorption to the cellulose nanoparticles.

Antibody-conjugated nanoparticles are used in a fields ranging from medicine to engineering. NanoAct® nanobeads are cellulose nanoparticles used in lateral flow assays that are highly water dispersible. In order to promote the adsorption of antibodies onto NanoAct® particles while maintaining their activity, we analyzed the adsorption onto NanoAct® particles thermodynamically and elucidated the adsorption mechanism. In an immunochromatographic assay, the amount of adsorbed antibody and the color intensity of the test line increased as the pH decreased. The zeta potential of the nanoparticles remained constant at around -30 mV over the pH range from 2 to 10. The model antibody had pI values between 6.2 and 6.8. Isothermal calorimetry analysis showed that adsorption of antibody to the NanoAct® particle is an endothermic reaction under low pH conditions, an exothermic reaction between pH 6 and pH 7, and a weakly exothermic reaction above pH 7. These data indicate that the changes in net charge of the antibody surface as a function of pH influence the pH dependence of antibody adsorption to the negatively charged NanoAct®. This suggests that increased positive charge on the antibody surface will result in a more sensitive NanoAct®-based immunoassay.

Anion solvation enhanced by positive supercharging mutations preserves thermal stability of an antibody in a wide pH range.

Proteins function through interactions with other molecules. In protein engineering, scientists often engineer proteins by mutating their amino acid sequences on the protein surface to improve various physicochemical properties. "Supercharging" is a method to design proteins by mutating surface residues with charged amino acids. Previous studies demonstrated that supercharging mutations conferred better thermal resistance, solubility, and cell penetration to proteins. Likewise, antibodies recognize antigens through the antigen-binding site on the surface. The genetic and structural diversity of antibodies leads to high specificity and affinity toward antigens, enabling antibodies to be versatile tools in various applications. When assessing therapeutic antibodies, surface charge is an important factor to consider because the isoelectric point plays a role in protein clearance inside the body. In this study, we explored how supercharging mutations affect physicochemical properties of antibodies. Starting from a crystal structure of an antibody with the net charge of -4, we computationally designed a supercharged variant possessing the net charge of +10. The positive-supercharged antibody exhibited marginal improvement in thermal stability, but the secondary structure and the binding affinity to the antigen (net charge of +8) were preserved. We also used physicochemical measurements and molecular dynamics simulations to analyze the effects of supercharging mutations in sodium phosphate buffer with different pH and ion concentrations, which revealed preferential solvation of phosphate ions to the supercharged surface relative to the wild-type surface. These results suggest that supercharging would be a useful approach to preserving thermal stability of antibodies in a wide range of pH, which may enable further diversification of antibody repertoires beyond natural evolution.

Characterization of novel SUMO family genes in the rice genome.

Small ubiquitin-related modifier (SUMO) is a post-translational modification factor composed of about 100 amino acid residues. Most plant species express a family of SUMO isoforms. We found three novel homologs of rice (Oryza sativa L.) SUMO genes, OsSUMO4, OsSUMO5 and OsSUMO6, in addition to the known SUMO genes OsSUMO1-OsSUMO3. Phylogenetic tree analysis revealed that rice SUMO genes have diverged considerably during their evolution. All six of these SUMO genes complemented the phenotype of the SUMO-deficient pmt3Δ mutant of fission yeast. Among the amino acid sequences of rice SUMO proteins, consensus motifs (ΨKXE/D) of the SUMO acceptor site were found in OsSUMO3, OsSUMO4, OsSUMO5 and OsSUMO6. The heat shock protein HSF7 is known to be SUMOylated in Arabidopsis thaliana. SUMOylation using a bacterial expression system revealed that the rice HSF7 homolog was modified by the six rice SUMOs, and further suggested that OsSUMO1, OsSUMO3, OsSUMO4 and OsSUMO6 are involved in its multiple SUMOylation.

Sudden cardiac arrest risk stratification based on 24-hour Holter ECG statistics.

This study examined the feasibility of using indices obtained from a long term Holter ECG record for sudden cardiac arrest (SCA) risk stratification. The ndices tested were the QT-RR interval co-variability and the alternans ratio percentile (ARP(θ)) which is defined as the θ(th) percentile of alternans ratios over a 24 hour period. The QT-RR interval co-variabilities are evaluated by the serial correlation coefficient between QT and RR trend sequences (QTRC). Previously reported Kalman filter technique and a simple smoothing spline method for the trend estimation are compared. Parameter θ in the alternans ratio percentile index was optimized to achieve the best classification accuracy. These indices were estimated from 26 cardiovascular outpatients for Holter ECG record. Patients were classified into high and low risk groups according to their clinical diagnosis, and the obtained indices were compared with those of 25 control subjects. A risk stratification using the two indices QTRC and ARP(θ) yielded an average sensitivity of 0.812 and a specificity of 0.925. The sensitivities and specificities of all three categories exceeded 0.8 except for the sensitivity to detect the high-risk patient group. Other short-term ECG parameters may need to be incorporated in order to improve the sensitivity.