Future trends and challenges in pathogenomics. A Foresight study

A chemical ecogenomics approach to understand the roles of secondary metabolites in fungal cereal pathogens

Secondary metabolites (SMs) are known to play important roles in the virulence and lifestyle of fungal plant pathogens. The increasing availability of fungal pathogen genome sequences and next-generation genomic tools have allowed us to survey the SM gene cluster inventory in individual fungi. Thus, there is immense opportunity for SM discovery in these plant pathogens. Comparative genomics and transcriptomics have been employed to obtain insights on the genetic features that enable fungal pathogens to adapt in individual ecological niches and to adopt the different pathogenic lifestyles. Here, we will discuss how we can use these tools to search for ecologically important SM gene clusters in fungi, using cereal pathogens as models. This ecological genomics approach, combined with genome mining and chemical ecology tools, is likely to advance our understanding of the natural functions of SMs and accelerate bioactive molecule discovery.

Molecular analysis as an aid to assess the public health risk of non-O157 Shiga toxin-producing Escherichia coli strains

Shiga toxin-producing Escherichia coli (STEC) strains are commensal bacteria in cattle with high potential for environmental and zoonotic transmission to humans. Although O157:H7 is the most common STEC serotype, there is growing concern over the emergence of more than 200 highly virulent non-O157 STEC serotypes that are globally distributed, several of which are associated with outbreaks and/or severe human illness such as hemolytic-uremic syndrome (HUS) and hemorrhagic colitis. At present, the underlying genetic basis of virulence potential in non-O157 STEC is unknown, although horizontal gene transfer and the acquisition of new pathogenicity islands are an expected origin. We used seropathotype classification as a framework to identify genetic elements that distinguish non-O157 STEC strains posing a serious risk to humans from STEC strains that are not associated with severe and epidemic disease. We report the identification of three genomic islands encoding non-LEE effector (nle) genes and 14 individual nle genes in non-O157 STEC strains that correlate independently with outbreak and HUS potential in humans. The implications for transmissible zoonotic spread and public health are discussed. These results and methods offer a molecular risk assessment strategy to rapidly recognize and respond to non-O157 STEC strains from environmental and animal sources that might pose serious public health risks to humans.

Proteomic analysis of hepatitis B surface antigen positive transgenic mouse liver and decrease of cyclophilin A

The small, 22-nm spherical particles associated with hepatitis B infection are composed of hepatitis B surface antigen (HBsAg) and usually outnumber the virions by a ratio of 10(2) or 10(3). To study the interactions and pathogenesis between liver cells and the expression of HBsAg, global protein profiles were compared by two dimensional gel-based differential proteomics between the livers of a lineage of HBsAg positive transgenic mice and their HBsAg negative control siblings. A total of 93 proteins were identified in the HBV transgenic mice. Around 45% of these differentially expressed proteins were enzymes associated with metabolism, suggesting that the processing of lipids, carbohydrates and certain amino acids were up- or down-regulated. Among these proteins, cyclophilin A (CypA), the major target for the potent immunosuppressive drug cyclosporin A, was found decreased in HBsAg positive transgenic mouse liver and in a stable cell line expressing HBsAg when compared to their controls. The decrease of intracellular CypA was accompanied by an increased secretion of this protein into the supernatant of HBsAg positive cells. Possible implications of HBsAg expression and the intracellular decrease of CypA are discussed.

Towards pathogenomics: a web-based resource for pathogenicity islands

Pathogenicity islands (PAIs) are genetic elements whose products are essential to the process of disease development. They have been horizontally (laterally) transferred from other microbes and are important in evolution of pathogenesis. In this study, a comprehensive database and search engines specialized for PAIs were established. The pathogenicity island database (PAIDB) is a comprehensive relational database of all the reported PAIs and potential PAI regions which were predicted by a method that combines feature-based analysis and similarity-based analysis. Also, using the PAI Finder search application, a multi-sequence query can be analyzed onsite for the presence of potential PAIs. As of April 2006, PAIDB contains 112 types of PAIs and 889 GenBank accessions containing either partial or all PAI loci previously reported in the literature, which are present in 497 strains of pathogenic bacteria. The database also offers 310 candidate PAIs predicted from 118 sequenced prokaryotic genomes. With the increasing number of prokaryotic genomes without functional inference and sequenced genetic regions of suspected involvement in diseases, this web-based, user-friendly resource has the potential to be of significant use in pathogenomics. PAIDB is freely accessible at .