Serum IgE reactivity profiling in an asthma affected cohort.

BACKGROUND: Epidemiological evidence indicates that atopic asthma correlates with high serum IgE levels though the contribution of allergen specific IgE to the pathogenesis and the severity of the disease is still unclear. METHODS: We developed a microarray immunoassay containing 103 allergens to study the IgE reactivity profiles of 485 asthmatic and 342 non-asthmatic individuals belonging to families whose members have a documented history of asthma and atopy. We employed k-means clustering, to investigate whether a particular IgE reactivity profile correlated with asthma and other atopic conditions such as rhinitis, conjunctivitis and eczema. RESULTS: Both case-control and parent-to-siblings analyses demonstrated that while the presence of specific IgE against individual allergens correlated poorly with pathological conditions, particular reactivity profiles were significantly associated with asthma (p<10E-09). An artificial neural network (ANN)-based algorithm, calibrated with the profile reactivity data, correctly classified as asthmatic or non-asthmatic 78% of the individual examined. Multivariate statistical analysis demonstrated that the familiar relationships of the study population did not affect the observed correlations. CONCLUSIONS: These findings indicate that asthma is a higher-order phenomenon related to patterns of IgE reactivity rather than to single antibody reactions. This notion sheds new light on the pathogenesis of the disease and can be readily employed to distinguish asthmatic and non-asthmatic individuals on the basis of their serum reactivity profile.

Gepoclu: a software tool for identifying and analyzing gene positional clusters in large-scale gene expression analysis.

BACKGROUND: The notion that genes are non-randomly organized within the chromosomes of eukaryotic organisms has recently received strong experimental support. Clusters of co-expressed and co-localized genes have been recognized as playing key roles in a number of functional pathways and adaptive responses including organism development, differentiation, disease states and aging. The identification of genes arranged in close proximity with each other within a particular temporal and spatial transcriptional program is anticipated to unravel possible functional links and reciprocal interactions. RESULTS: We developed a novel software tool Gepoclu (Gene Positional Clustering) that automatically selects genes based on expression values from multiple sources, including microarray, EST and qRT-PCR, and performs positional clustering. Gepoclu provides expression-based gene selection from multiple experimental sources, position-based gene clustering and cluster visualization functionalities, all as parts of the same fully integrated, and interactive, package. This means rapid iterations while exploring for emergent behavior, and full programmability of the filtering and clustering steps. CONCLUSIONS: Gepoclu is a useful data-mining tool for exploring relationships among transcriptional data deriving form different sources. It provides an easy interactive environment for analyzing positional clustering behavior of co-expressed genes, and at the same time it is fully programmable, so that it can be customized and extended to support specific analysis needs.

An antigen microarray immunoassay for multiplex screening of mouse monoclonal antibodies.

The mouse monoclonal antibody (mAb) technology still represents a key source of reagents for research and clinical diagnosis, although it is relatively inefficient and expensive and therefore unsuitable for high-throughput production against a vast repertoire of antigens. In this article, we describe a protocol that combines the immunization of individual mice with complex mixtures of influenza virus strains and a microarray-based immunoassay procedure to perform a parallel screening against the viral antigens. The protocol involves testing the supernatants of somatic cell hybrids against a capture substratum containing an array of different antigens. For each fusion experiment, we carried out more than 25,000 antigen-antibody reactivity tests in less than a week, a throughput that is two orders of magnitude higher than that of traditional antibody detection assays such as enzyme-linked immunosorbent assays and immunofluorescence. Using a limited number of mice, we can develop a vast repertoire of mAbs directed against nuclear and surface proteins of several human and avian influenza virus strains.