Development of fully functional proteins with novel glycosylation via enzymatic glycan trimming

Recombinant glycoproteins present unique challenges to biopharmaceutical development, especially when efficacy is affected by glycosylation. In these cases, optimizing the protein's glycosylation is necessary, but difficult, since the glycan structures cannot be genetically encoded, and glycosylation in nonhuman cell lines can be very different from human glycosylation profiles. We are exploring a potential solution to this problem by designing enzymatic glycan optimization methods to produce proteins with useful glycan compositions. To demonstrate viability of this new approach to generating glycoprotein-based pharmaceuticals, the N-linked glycans of a model glycoprotein, ribonuclease B (RNase B), were modified using an α-mannosidase to produce a new glycoprotein with different glycan structures. The secondary structure of the native and modified glycoproteins was retained, as monitored using circular dichroism. An assay was also developed using an RNA substrate to verify that RNase B had indeed retained its function after being subjected to the necessary glycan modification conditions. This is the first study that verifies both activity and secondary structure of a glycoprotein after enzymatic glycan trimming for use in biopharmaceutical development methods. The evidence of preserved structure and function for a modified glycoprotein indicates that extracellular enzymatic modification methods could be implemented in producing designer glycoproteins. © 2008 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 98:2581–2591, 2009     

Oseltamivir-Resistant Influenza A Pandemic (H1N1) 2009 Virus, Hong Kong, China

Resistance to oseltamivir was observed in influenza A pandemic (H1N1) 2009 virus isolated from an untreated person in Hong Kong, China. Investigations showed a resistant virus with the neuraminidase (NA) 274Y genotype in quasi-species from a nasopharyngeal aspirate. Monitoring for the naturally occurring NA 274Y mutation in this virus is necessary.     

Risk Prediction for Peripartum Cardiomyopathy in Delivering Mothers: A Validated Risk Model: PPCM Risk Prediction Model

BackgroundPeripartum cardiomyopathy (PPCM) causes significant morbidity and mortality in childbearing women. Delays in diagnosis lead to worse outcomes; however, no validated risk prediction model exists. We sought to validate a previously described model and identify novel risk factors for PPCM presenting at the time of delivery.Methods and ResultsAdministrative hospital records from 5,277,932 patients from 8 states were screened for PPCM, identified by International Classification of Disease-9 Clinical Modification codes (674.5x) at the time of delivery. Demographics, comorbidities, procedures, and outcomes were quantified. Performance of a previously published regression model alone and with the addition of novel PPCM-associated characteristics was assessed using receiver operating characteristic area under the curve (AUC) analysis. Novel risk factors were identified using multivariate logistic regression and the likelihood ratio test. In total, 1186 women with PPCM were studied, including 535 of 4,003,912 delivering mothers (0.013%) in the derivation set compared with 651 of 5,277,932 (0.012%) in the validation set. The previously published risk prediction model performed well in both the derivation (area under the curve 0.822) and validation datasets (area under the curve 0.802). Novel PPCM-associated characteristics in the combined cohort included diabetes mellitus (odds ratio [OR] of PPCM 1.93, 95% confidence interval [CI] 1.23–3.02, P = .004), mood disorders (OR 1.74, 95% CI 1.22–2.47, P = .002), obesity (OR 1.92, 95% CI 1.45–2.55, P < .001), and Medicaid insurance (OR 1.54, 95% CI 1.22-1.96, P < .001).ConclusionsThis is the first validated risk prediction model to identify women at increased risk for PPCM at the time of delivery. Diabetes mellitus, obesity, mood disorders, and lower socioeconomic status are risk factors associated with PPCM. This model may be useful for identifying women at risk and preventing delays in diagnosis.     

Natural killer cell infiltration is discriminative for antibody-mediated rejection and predicts outcome after kidney transplantation

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