Review
Functional and comparative genomics of pathogenic bacteria

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Abstract

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.

Introduction

A microarray is a device that provides a surface containing representations of all (or most) of the identified open reading frames (ORFs) of a sequenced and annotated genome. Whether fabricated as a glass-spotted microarray 1., 2., 3., high-density oligonucleotide array 4., 5. or nylon membrane macroarrray, this simple experimental system provides the basis for two quite distinctive experimental paradigms. Functional genomics uses expression profiling of mRNA to provide a condition-specific and time-specific genome-scale snapshot of the transcriptome 6., 7.. Comparative genomics contrasts two or more genomes at the ORF-content level of resolution 8., 9.. Both applications entail the use of clustering algorithms 10., 11. and pathway databases 12., 13. to identify co-regulated genes that perform common metabolic and biosynthetic functions. However, microarray expression profiling data poses special analytical challenges that have required the development of new statistical instruments and the recognition that multiple biological replicates of the same experiment are needed to identify significantly regulated genes 14••., 15•., 16•.. Although not the topic of this review, some of the most comprehensive microarray studies to date concern the non-pathogenic model systems Escherichia coli K-12 17., 18., 19., 20., 21., 22., 23., Bacillus subtilis [24] and Caulobacter crescentus [25].

This review focuses on two aspects of bacterial pathogenicity, gleaned from an emerging literature that describes the use of genome microarrays to study the biology of infectious agents. Included here are expression profiling studies of bacteria cultured in vitro under conditions intended to induce in vivo transcriptional programs, to define regulon membership, and to illuminate crucial biosynthetic pathways. Also discussed are the capacity of comparative genomic studies by microarray methods to characterize the genetic variability of natural populations, and to identify differences between pathogen and commensal, and between related pathogens that occupy different host niches or vary in some other subtle manner. The review concludes with a brief summary of expression studies of infected host cells and the promise that this holds for capturing the dialogue between host and pathogen.

Section snippets

Microarray expression profiling of pathogenic bacteria

The ultimate goal of whole genome expression studies of pathogenic bacteria is the identification of bacterial genes that are differentially regulated in the host. Within this class of genes are those that adapt the microbe to host-specific microenvironments or encode virulence determinants. Ideally, studies of this kind would compare expression profiles of bacteria within infected tissues with profiles from bacteria cultured under standardized in vitro conditions of growth. Unfortunately, this

Microarray-based comparative genomics

Genetic variability and natural selection yield strains and species adapted to particular microenvironments of the host and result in phenotypic differences between non-pathogenic commensals and virulent biotypes. Accordingly, genomic comparisons between pathogenic and non-pathogenic strains of the same species can be particularly informative because genes exclusively present in the former may be required for infectivity, virulence or adaptation to a particular host niche. Microarray-based

Profiling the dialogue between pathogen and host

Pathogenesis entails not only the differential expression of bacterial genes, but also responses by the host. In principle, then, microarray expression analysis of bacterially infected cells and tissues can identify, simultaneously and in the same sample, host and pathogen genes that are regulated during the infectious process. Although not within the scope of this review, the host contribution to this process has been the focus of five published microarray studies 49•., 50••., 51•., 52•., 53••.

Conclusions

The studies reviewed here show that microarray expression profiling is a powerful method to identify genes differentially regulated by biochemical signatures of host microenvironments, genes that are controlled, directly or indirectly, by transcription factors and genes that code for components of multistep metabolic and biosynthetic pathways. Equally illuminating are microarray-based comparative studies to assess the extent and nature of genetic variability within natural populations of

Acknowledgements

I thank past and current members of my laboratory for their contributions to the art and science of microarray expression work in my laboratory, which was supported by grants from the National Institutes of Health (AI 39521, AI 43422 and AI44826) and the Glaxo Group Research Action TB Program.

References and recommended reading

Papers of particular interest, published within the annual period of review, have been highlighted as:

  • • of special interest

  • •• of outstanding interest

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