Matthew Page

A Mixture of Functionally Oligoclonal Humanized Monoclonal Antibodies That Neutralize Clostridium difficile TcdA and TcdB with High Levels of In Vitro Potency Shows In Vivo Protection in a Hamster Infection Model

ABSTRACT Clostridium difficile infections are a major cause of antibiotic-associated diarrhea in hospital and care facility patients. In spite of the availability of effective antibiotic treatments, C. difficile infection (CDI) is still a major cause of patient suffering, death, and substantial health care costs. Clostridium difficile exerts its major pathological effects through the actions of two protein exotoxins, TcdA and TcdB, which bind to and disrupt gut tissue. Antibiotics target the infecting bacteria but not the exotoxins. Administering neutralizing antibodies against TcdA and TcdB to patients receiving antibiotic treatment might modulate the effects of the exotoxins directly. We have developed a mixture of three humanized IgG1 monoclonal antibodies (MAbs) which neutralize TcdA and TcdB to address three clinical needs: reduction of the severity and duration of diarrhea, reduction of death rates, and reduction of the rate of recurrence. The UCB MAb mixture showed higher potency in a variety of in vitro binding and neutralization assays (∼10-fold improvements), higher levels of protection in a hamster model of CDI (82% versus 18% at 28 days), and higher valencies of toxin binding (12 versus 2 for TcdA and 3 versus 2 for TcdB) than other agents in clinical development. Comparisons of the MAb properties also offered some insight into the potential relative importance of TcdA and TcdB in the disease process.

Human biallelic MFN2 mutations induce mitochondrial dysfunction, upper body adipose hyperplasia, and suppression of leptin expression

MFN2 encodes mitofusin 2, a membrane-bound mediator of mitochondrial membrane fusion and inter-organelle communication. MFN2 mutations cause axonal neuropathy, with associated lipodystrophy only occasionally noted, however homozygosity for the p.Arg707Trp mutation was recently associated with upper body adipose overgrowth. We describe similar massive adipose overgrowth with suppressed leptin expression in four further patients with biallelic MFN2 mutations and at least one p.Arg707Trp allele. Overgrown tissue was composed of normal-sized, UCP1-negative unilocular adipocytes, with mitochondrial network fragmentation, disorganised cristae, and increased autophagosomes. There was strong transcriptional evidence of mitochondrial stress signalling, increased protein synthesis, and suppression of signatures of cell death in affected tissue, whereas mitochondrial morphology and gene expression were normal in skin fibroblasts. These findings suggest that specific MFN2 mutations cause tissue-selective mitochondrial dysfunction with increased adipocyte proliferation and survival, confirm a novel form of excess adiposity with paradoxical suppression of leptin expression, and suggest potential targeted therapies. DOI: http://dx.doi.org/10.7554/eLife.23813.001

NeuroTransDB : highly curated and structured transcriptomic metadata for neurodegenerative diseases

Neurodegenerative diseases are chronic debilitating conditions, characterized by progressive loss of neurons that represent a significant health care burden as the global elderly population continues to grow. Over the past decade, high-throughput technologies such as the Affymetrix GeneChip microarrays have provided new perspectives into the pathomechanisms underlying neurodegeneration. Public transcriptomic data repositories, namely Gene Expression Omnibus and curated ArrayExpress, enable researchers to conduct integrative meta-analysis; increasing the power to detect differentially regulated genes in disease and explore patterns of gene dysregulation across biologically related studies. The reliability of retrospective, large-scale integrative analyses depends on an appropriate combination of related datasets, in turn requiring detailed meta-annotations capturing the experimental setup. In most cases, we observe huge variation in compliance to defined standards for submitted metadata in public databases. Much of the information to complete, or refine meta-annotations are distributed in the associated publications. For example, tissue preparation or comorbidity information is frequently described in an article’s supplementary tables. Several value-added databases have employed additional manual efforts to overcome this limitation. However, none of these databases explicate annotations that distinguish human and animal models in neurodegeneration context. Therefore, adopting a more specific disease focus, in combination with dedicated disease ontologies, will better empower the selection of comparable studies with refined annotations to address the research question at hand. In this article, we describe the detailed development of NeuroTransDB, a manually curated database containing metadata annotations for neurodegenerative studies. The database contains more than 20 dimensions of metadata annotations within 31 mouse, 5 rat and 45 human studies, defined in collaboration with domain disease experts. We elucidate the step-by-step guidelines used to critically prioritize studies from public archives and their metadata curation and discuss the key challenges encountered. Curated metadata for Alzheimer’s disease gene expression studies are available for download. Database URL: www.scai.fraunhofer.de/NeuroTransDB.html

PCAN: phenotype consensus analysis to support disease-gene association

BackgroundBridging genotype and phenotype is a fundamental biomedical challenge that underlies more effective target discovery and patient-tailored therapy. Approaches that can flexibly and intuitively, integrate known gene-phenotype associations in the context of molecular signaling networks are vital to effectively prioritize and biologically interpret genes underlying disease traits of interest.ResultsWe describe Phenotype Consensus Analysis (PCAN); a method to assess the consensus semantic similarity of phenotypes in a candidate gene’s signaling neighborhood. We demonstrate that significant phenotype consensus (p < 0.05) is observable for ~67% of 4,549 OMIM disease-gene associations, using a combination of high quality String interactions + Metabase pathways and use Joubert Syndrome to demonstrate the ease with which a significant result can be interrogated to highlight discriminatory traits linked to mechanistically related genes.ConclusionsWe advocate phenotype consensus as an intuitive and versatile method to aid disease-gene association, which naturally lends itself to the mechanistic deconvolution of diverse phenotypes. We provide PCAN to the community as an R package (http://bioconductor.org/packages/PCAN/) to allow flexible configuration, extension and standalone use or integration to supplement existing gene prioritization workflows.