Evaluating N-Glycosylation of a Therapeutic Monoclonal Antibody Using UHPLC-FLR-MS with RapiFluor-MS Labeling.

Released N-glycan analysis using the fluorescent label 2-AB (2-aminobenzamide) has been the "gold standard" method for released glycan analysis for several years. The more recent RapiFluor-MS™ labeling technique, however, offers enhanced mass spectrometric detection of released N-glycans, improving the sensitivity and detection limits of the method. The optimized multidimensional detection offers increased confidence in glycan identification which can be further supported by an exoglycosidase digestion array (optional). Here we describe the PNGase F release of N-glycans from a typical IgG1 monoclonal antibody (mAb) with subsequent labeling with RapiFluor-MS™ for detection by HILIC-FLR-MS. The method output quantifies the relative proportion of each glycan species including core afucosylation, sialylation, and high-mannose content, and has a limit of detection (LOD) of 0.01% relative abundance.

Hybrid mass spectrometry methods reveal lot-to-lot differences and delineate the effects of glycosylation on the tertiary structure of Herceptin®.

To quantify the measurable variations in the structure of a biopharmaceutical product we systematically evaluate three lots of Herceptin®, two mAb standards and an intact Fc-hinge fragment. Each mAb is examined in three states; glycan intact, truncated (following endoS2 treatment) and fully deglycosylated. Despite equivalence at the intact protein level, each lot of Herceptin® gives a distinctive signature in three different mass spectrometry approaches. Ion mobility mass spectrometry (IM-MS) shows that in the API, the attached N-glycans reduce the conformational spread of each mAb by 10.5-25%. Hydrogen/deuterium exchange mass spectrometry (HDX-MS) data support this, with lower global deuterium uptake in solution when comparing intact to the fully deglycosylated protein. HDX-MS and activated IM-MS map the influence of glycans on the mAb and reveal allosteric effects which extend far beyond the Fc domains into the Fab region. Taken together, these findings and the supplied interactive data sets establish acceptance criteria with application for MS based characterisation of biosimilars and novel therapeutic mAbs.

LC-MS/MS strategies for therapeutic antibodies and investigation into the quantitative impact of antidrug-antibodies.

AIM: We aimed to establish novel, high-throughput LC-MS/MS strategies for quantification of monoclonal antibodies in human serum and examine the potential impact of antidrug antibodies. METHODOLOGY: We present two strategies using a thermally stable immobilized trypsin. The first strategy uses whole serum digestion and the second introduces Protein G enrichment to improve the selectivity. The impact of anti-trastuzumab antibodies on the methods was tested. CONCLUSION: Whole serum digestion has been validated for trastuzumab (LLOQ 0.25 µg/ml). Protein G enrichment has been validated for trastuzumab (LLOQ 0.1 µg/ml), bevacizumab (LLOQ 0.1 µg/ml) and adalimumab (LLOQ 0.25 µg/ml). We have shown the potential for anti-drug antibodies to impact on the quantification and we have subsequently established a strategy to overcome this impact where total quantification is desired.

Orthogonal Assessment of Biotherapeutic Glycosylation: A Case Study Correlating N-Glycan Core Afucosylation of Herceptin with Mechanism of Action.

In the development of therapeutic antibodies and biosimilars, an appropriate biopharmaceutical CMC control strategy that connects critical quality attributes with mechanism of action should enable product assessment at an early stage of development in order to mitigate risk. Here we demonstrate a new analytical workflow using trastuzumab which comprises "middle-up" analysis using a combination of IdeS and the endoglycosidases EndoS and EndoS2 to comprehensively map the glycan content. Enzymatic cleavage between the two N-acetyl glucosamine residues of the chitobiose core of N-glycans significantly simplifies the oligosaccharide component enabling facile distinction of GlcNAc from GlcNAc with core fucose. This approach facilitates quantitative determination of total Fc-glycan core-afucosylation, which was in turn correlated with receptor binding affinity by surface plasmon resonance and in vitro ADCC potency with a cell based bioassay. The strategy also quantifies Fc-glycan occupancy and the relative contribution from high mannose glycans.

Statistical modelling of citation exchange between statistics journals.

Rankings of scholarly journals based on citation data are often met with scepticism by the scientific community. Part of the scepticism is due to disparity between the common perception of journals' prestige and their ranking based on citation counts. A more serious concern is the inappropriate use of journal rankings to evaluate the scientific influence of researchers. The paper focuses on analysis of the table of cross-citations among a selection of statistics journals. Data are collected from the Web of Science database published by Thomson Reuters. Our results suggest that modelling the exchange of citations between journals is useful to highlight the most prestigious journals, but also that journal citation data are characterized by considerable heterogeneity, which needs to be properly summarized. Inferential conclusions require care to avoid potential overinterpretation of insignificant differences between journal ratings. Comparison with published ratings of institutions from the UK's research assessment exercise shows strong correlation at aggregate level between assessed research quality and journal citation 'export scores' within the discipline of statistics.

Bees as Biosensors: Chemosensory Ability, Honey Bee Monitoring Systems, and Emergent Sensor Technologies Derived from the Pollinator Syndrome.

This review focuses on critical milestones in the development path for the use of bees, mainly honey bees and bumble bees, as sentinels and biosensors. These keystone species comprise the most abundant pollinators of agro-ecosystems. Pollinating 70%-80% of flowering terrestrial plants, bees and other insects propel the reproduction and survival of plants and themselves, as well as improve the quantity and quality of seeds, nuts, and fruits that feed birds, wildlife, and us. Flowers provide insects with energy, nutrients, and shelter, while pollinators are essential to global ecosystem productivity and stability. A rich and diverse milieu of chemical signals establishes and maintains this intimate partnership. Observations of bee odor search behavior extend back to Aristotle. In the past two decades great strides have been made in methods and instrumentation for the study and exploitation of bee search behavior and for examining intra-organismal chemical communication signals. In particular, bees can be trained to search for and localize sources for a variety of chemicals, which when coupled with emerging tracking and mapping technologies create novel potential for research, as well as bee and crop management.

A rapid approach for characterization of thiol-conjugated antibody-drug conjugates and calculation of drug-antibody ratio by liquid chromatography mass spectrometry.

We present the demonstration of a rapid "middle-up" liquid chromatography mass spectrometry (LC-MS)-based workflow for use in the characterization of thiol-conjugated maleimidocaproyl-monomethyl auristatin F (mcMMAF) and valine-citrulline-monomethyl auristatin E (vcMMAE) antibody-drug conjugates. Deconvoluted spectra were generated following a combination of deglycosylation, IdeS (immunoglobulin-degrading enzyme from Streptococcus pyogenes) digestion, and reduction steps that provide a visual representation of the product for rapid lot-to-lot comparison-a means to quickly assess the integrity of the antibody structure and the applied conjugation chemistry by mass. The relative abundance of the detected ions also offer information regarding differences in drug conjugation levels between samples, and the average drug-antibody ratio can be calculated. The approach requires little material (<100 µg) and, thus, is amenable to small-scale process development testing or as an early component of a complete characterization project facilitating informed decision making regarding which aspects of a molecule might need to be examined in more detail by orthogonal methodologies.

Iridovirus and microsporidian linked to honey bee colony decline.

BACKGROUND: In 2010 Colony Collapse Disorder (CCD), again devastated honey bee colonies in the USA, indicating that the problem is neither diminishing nor has it been resolved. Many CCD investigations, using sensitive genome-based methods, have found small RNA bee viruses and the microsporidia, Nosema apis and N. ceranae in healthy and collapsing colonies alike with no single pathogen firmly linked to honey bee losses. METHODOLOGY/PRINCIPAL FINDINGS: We used Mass spectrometry-based proteomics (MSP) to identify and quantify thousands of proteins from healthy and collapsing bee colonies. MSP revealed two unreported RNA viruses in North American honey bees, Varroa destructor-1 virus and Kakugo virus, and identified an invertebrate iridescent virus (IIV) (Iridoviridae) associated with CCD colonies. Prevalence of IIV significantly discriminated among strong, failing, and collapsed colonies. In addition, bees in failing colonies contained not only IIV, but also Nosema. Co-occurrence of these microbes consistently marked CCD in (1) bees from commercial apiaries sampled across the U.S. in 2006-2007, (2) bees sequentially sampled as the disorder progressed in an observation hive colony in 2008, and (3) bees from a recurrence of CCD in Florida in 2009. The pathogen pairing was not observed in samples from colonies with no history of CCD, namely bees from Australia and a large, non-migratory beekeeping business in Montana. Laboratory cage trials with a strain of IIV type 6 and Nosema ceranae confirmed that co-infection with these two pathogens was more lethal to bees than either pathogen alone. CONCLUSIONS/SIGNIFICANCE: These findings implicate co-infection by IIV and Nosema with honey bee colony decline, giving credence to older research pointing to IIV, interacting with Nosema and mites, as probable cause of bee losses in the USA, Europe, and Asia. We next need to characterize the IIV and Nosema that we detected and develop management practices to reduce honey bee losses.

Neuregulin1 (NRG1) signaling through Fyn modulates NMDA receptor phosphorylation: differential synaptic function in NRG1+/- knock-outs compared with wild-type mice.

We previously identified Neuregulin1 (NRG1) as a gene contributing to the risk of developing schizophrenia. Furthermore, we showed that NRG1+/- mutant mice display behavioral abnormalities that are reversed by clozapine, an atypical antipsychotic drug used for the treatment of schizophrenia. We now present evidence that ErbB4 (v-erb-a erythroblastic leukemia viral oncogene homolog 4), the tyrosine kinase receptor for NRG1 in hippocampal neurons, interacts with two nonreceptor tyrosine kinases, Fyn and Pyk2 (proline-rich tyrosine kinase 2). NRG1 stimulation of cells expressing ErbB4 and Fyn leads to the association of Fyn with ErbB4 and consequent activation. Furthermore, we show that NRG1 signaling, through activation of Fyn and Pyk2 kinases, stimulates phosphorylation of Y1472 on the NR2B subunit of the NMDA receptor (NMDAR), a key regulatory site that modulates channel properties. NR2B Y1472 is hypophosphorylated in NRG1+/- mutant mice, and this defect can be reversed by clozapine at a dose that reverses their behavioral abnormalities. We also demonstrate that short-term synaptic plasticity is altered and theta-burst long-term potentiation is impaired in NRG1+/- mutant mice, and incubation of hippocampal slices from these mice with NRG1 reversed those effects. Attenuated NRG1 signaling through ErbB4 may contribute to the pathophysiology of schizophrenia through dysfunction of NMDAR modulation. Thus, our data support the glutamate hypothesis of schizophrenia.

Relative index of inequality: definition, estimation, and inference.

The relative index of inequality (RII) is a commonly used measure of the extent to which the occurrence of an outcome such as chronic illness or early death varies with socioeconomic status or some other background variable. The standard RII estimator applies only to linear variation in incidence rates. In this paper a general definition of the RII is introduced, alternative approaches to point estimation are considered, and a parametric bootstrap method is suggested for the construction of approximate confidence intervals. Estimation based on cubic splines fitted by maximum penalized likelihood is developed in some detail, and the proposed approach handles naturally the commonly needed adjustment for a 'standardizing' covariate such as age. Death rates in a large longitudinal study in England and Wales from 1996-2000 are analyzed in order to illustrate the various methods. A small simulation study explores the relative merits of different estimators. The approach based on cubic splines is found to reduce bias substantially, at the expense of some increase in variance, when variation in incidence rates is nonlinear.