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Microarray expression profiling: capturing a genome‐wide portrait of the transcriptome
Author(s) -
Conway Tyrrell,
K. Gary
Publication year - 2003
Publication title -
molecular microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.857
H-Index - 247
eISSN - 1365-2958
pISSN - 0950-382X
DOI - 10.1046/j.1365-2958.2003.03338.x
Subject(s) - biology , transcriptome , gene expression profiling , organism , dna microarray , computational biology , microarray , microarray analysis techniques , model organism , genome , genetics , phenotype , gene expression , gene
Summary The bacterial transcriptome is a dynamic entity that reflects the organism's immediate, ongoing and genome‐wide response to its environment. Microarray expression profiling provides a comprehensive portrait of the transcriptional world enabling us to view the organism as a ‘system’ that is more than the sum of its parts. The vigilance of microorganisms to environmental change, the alacrity of the transcriptional response, the short half‐life of bacterial mRNA and the genome‐scale nature of the investigation collectively explain the power of this method. These same features pose the most significant experimental design and execution issues which, unless surmounted, predictably generate a distorted image of the transcriptome. Conversely, the expression profile of a properly conceived and conducted microarray experiment can be used for hypothesis testing: disclosure of the metabolic and biosynthetic pathways that underlie adaptation of the organism to chang‐ing conditions of growth; the identification of co‐ordinately regulated genes; the regulatory circuits and signal transduction systems that mediate the adaptive response; and temporal features of developmental programmes. The study of bacterial pathogenesis by microarray expression profiling poses special challenges and opportunities. Although the technical hurdles are many, obtaining expression profiles of an organism growing in tissue will probably reveal strategies for growth and survival in the host's microenvironment. Identifying these colonization strategies and their cognate expression patterns involves a ‘deconstruction’ process that combines bioinformatics analysis and in vitro DNA array experimentation.
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