Salmonella Gene Expression in Complex Environments

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DESCRIPTION (provided by applicant): Salmonella causes tens of millions of infections in humans each year and it has been used as a bioterror weapon. This organism must contend with a highly complex gut microbiota in order to infect the host and the characteristics of the microbiota are known to affect the success of this infection process. Indeed, infectivity by Salmonella is reduced by 100,000-fold in the presence of normal gut flora. What are the genetic processes that underlie the interaction of a pathogen with commensal or symbiotic microbiota? These are difficult environments to investigate without reporter methods. Two methods, which could be used for studying pathogens in a population of other organisms, will be compared and contrasted using Salmonella as a model. In each of these methods, all the genes or promoters in a Salmonella genome will be tagged, en mass, with reporter systems. The mixture of bacteria, each individual carrying a single tag, will then be introduced into three groups of mice: abiotic, gnotobiotic, and normal. After growth in these environments, changes in the distribution of all the tags in Salmonella genes or promoters will be monitored on a Salmonella-specific microarray that we have built. The methods to be tested involve (i), selection for genes that are required in an environment by transposon tagging of the genome, and (ii), identification of genes that are induced, but not necessarily required, in an environment by screening for expression of a promoterless fluorescent marker in a promoter plasmid library. Tagging of genes and subsequent analysis by microarrays should allow monitoring of gene expression in complex environments that would be difficult or impossible to monitor by other methods. The methods may reveal new pathways that will lead to a better understanding of interactions with the microbiota, as well as revealing potential new vulnerabilities that can be exploited to fight these pathogens. As a class, these methods should be applicable to studying gene expression in any bacterial or eukaryotic microbial community.