Competition for FcRn-mediated transport gives rise to short half-life of human IgG3 and offers therapeutic potential

Human IgG3 displays the strongest effector functions of all IgG subclasses but has a short half-life for unresolved reasons. Here we show that IgG3 binds to IgG-salvage receptor (FcRn), but that FcRn-mediated transport and rescue of IgG3 is inhibited in the presence of IgG1 due to intracellular competition between IgG1 and IgG3. We reveal that this occurs because of a single amino acid difference at position 435, where IgG3 has an arginine instead of the histidine found in all other IgG subclasses. While the presence of R435 in IgG increases binding to FcRn at neutral pH, it decreases binding at acidic pH, affecting the rescue efficiency—but only in the presence of H435–IgG. Importantly, we show that in humans the half-life of the H435-containing IgG3 allotype is comparable to IgG1. H435–IgG3 also gave enhanced protection against a pneumococcal challenge in mice, demonstrating H435–IgG3 to be a candidate for monoclonal antibody therapies

nEASE: a method for gene ontology subclassification of high-throughput gene expression data.

UNLABELLED: High-throughput technologies can identify genes whose expression profiles correlate with specific phenotypes; however, placing these genes into a biological context remains challenging. To help address this issue, we developed nested Expression Analysis Systematic Explorer (nEASE). nEASE complements traditional gene ontology enrichment approaches by determining statistically enriched gene ontology subterms within a list of genes based on co-annotation. Here, we overview an open-source software version of the nEASE algorithm. nEASE can be used either stand-alone or as part of a pathway discovery pipeline. AVAILABILITY: nEASE is implemented within the Multiple Experiment Viewer software package available at http://www.tm4.org/mev. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online