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MICROARRAY EXPRESSION STUDIES ON AN IN VITRO MODEL OF HUMAN AIRWAY EPITHELIUM (EPIAIRWAY).

Moffatt1, M.F., Hill1, A.L., Hao1, L., Taylor2, J., Hayden3, P.J., Cookson1, W.O.C.M. 1Wellcome Trust Centre for Human Genetics, University of Oxford, U.K; 2Department of Statistics, Oxford Centre for Gene Function, University of Oxford, U.K; 3MatTek Corporation, Ashland, MA, U.S.A.
Abstract

This study by researchers at the Wellcome Trust Centre for Human Genetics, Oxford University’s Centre for Gene Function and MatTek Corp. demonstrated how MatTek’s EpiAirway in vitro human tracheal/bronchial tissue equivalent can be used to identify genes and processes involved in the development of human respiratory epithelium and its defenses. Microarray technology now permits analysis of the expression of the whole human genome in a single chip. Using Affymetrix U133 Plus 2.0 arrays, we have analyzed the expression of 47,000 transcripts including 21,000 well-characterized human genes in an in vitro model of human airway epithelium – EpiAirway™ (MatTek Corp.). Normal human-derived tracheal/bronchial epithelial cells are cultured using air-liquid interface (ALI) techniques resulting in a highly differentiated layer of cells that resembles the epithelial layer of the respiratory tract. This (EpiAirway) organotypic model makes it possible to carry out a range of studies into airway diseases including asthma. In order to increase our understanding of the differentiation and development processes involved in the EpiAirway™ model, we studied six time points ranging from basal cells to 13 days ALI culture. High quality RNA was extracted for each time point in triplicate and hybridizations to U133 Plus 2.0 chips performed following standard Affymetrix protocols. Normalization and filtering of raw expression data was carried out ensuring only genes present in all replicates at each time point were considered in downstream analyses. 1,647 genes were shown to have a significant variation (=2 SD) across the samples. Hierarchical clustering of these genes recognised 16 clusters which showed differential expression of their genes during airway development. This data has identified genes and processes involved in the development of the respiratory epithelium and its defences. This will be a key tool in understanding the aetiology of airway disease.

Keywords

Air liquid interface (ALI), Airway epithelium, Asthma, Chronic obstructive pulmonary disease (COPD), EpiAirway, Gene Ontology (GO), Human airway epithelium, Inflammation, Inflammatory, Inflammatory response, Microarray, Normal respiratory epithelia, RNA, Statistical analysis of means (SAM)

Materials Tested

EpiAirway tissue

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