Microarray expression profiling and the development of data-mining tools and new statistical instruments affords an unprecedented opportunity for the genome-scale study of bacterial pathogenicity. Expression profiles obtained from bacteria grown in media simulating host microenvironments yield a portrait of interacting metabolic pathways and multistage developmental programs and disclose regulatory networks. The analysis of closely related strains and species by microarray-based comparative genomics provides a measure of genetic variability within natural populations and identifies crucial differences between pathogen and commensal. In the near future, the combined use of bacterial and host microarrays to study the same infected tissue will reveal the host–pathogen dialogue in a gene-by-gene and site- and time-specific manner. This review discusses the use of microarray-based expression profiling to identify genes of pathogenic bacteria that are differentially regulated in response to host-specific signals. Additionally, the review describes the application of microarray methods to disclose differences in gene content between taxonomically related strains that vary with respect to pathogenic phenotype.