Gene Expression Profiling and the Use of Genome-Scale In Silico Models of Escherichia coli for Analysis: Providing Context for Content

Abstract

One of the most widely used high-throughput technologies is the oligonucleotide microarray. From the initial development of microarrays, high expectations were held for their use to aid in answering biological questions, due to their ability to measure mRNA abundances on a genome scale. However, accumulating experience is revealing that even when questions of sample preparation, data processing, and dealing with the inherently noisy data (81) are set aside, the large amount of data generated has proven difficult to analyze and interpret (12). It is also often challenging to narrow down specific novel findings based solely on expression profiling data. Here, we present a downloadable compendium of gene expression profiles for Escherichia coli and discuss the experience from one lab in which expression profiling data have been employed in a myriad of studies of E. coli. We will try to address two classes of expression profiling data usage: (i) how expression profiling can be analyzed using more traditional statistical methods to provide biological understanding and (ii) how genome-scale models form a context within which expression profiling data content increases in value.