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Infectious Disorders - Drug Targets

Editor-in-Chief

ISSN (Print): 1871-5265
ISSN (Online): 2212-3989

Microarray Analysis of Human Epithelial Cell Responses to Bacterial Interaction

Author(s): Jeffrey J. Mans, Richard J. Lamont and Martin Handfield

Volume 6, Issue 3, 2006

Page: [299 - 309] Pages: 11

DOI: 10.2174/187152606778249926

Price: $65

Abstract

Host-pathogen interactions are inherently complex and dynamic. The recent use of human microarrays has been invaluable to monitor the effects of various bacterial and viral pathogens upon host cell gene expression programs. This methodology has allowed the host response transcriptome of several cell lines to be studied on a global scale. To this point, the great majority of reports have focused on the response of immune cells, including macrophages and dendritic cells. These studies revealed that the immune response to microbial pathogens is tailored to different microbial challenges. Conversely, the paradigm for epithelial cells has-until recently-held that the epithelium mostly served as a relatively passive physical barrier to infection. It is now generally accepted that the epithelial barrier contributes more actively to signaling events in the immune response. In light of this shift, this review will compare transcriptional profiling data from studies that involved host-pathogen interactions occurring with epithelial cells. Experiments that defined both a common core response, as well as pathogen-specific host responses will be discussed. This review will also summarize the contributions that transcriptional profiling analysis has made to our understanding of bacterial physio-pathogensis of infection. This will include a discussion of how host transcriptional responses can be used to infer the function of virulence determinants from bacterial pathogens interacting with epithelial mucosa. In particular, we will expand upon the lessons that have been learned from gastro-intestinal and oral pathogens, as well as from members of the commensal flora.

Keywords: Transcriptome, infectome, host-pathogen interactions, differential gene expression


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