The human health significance of bacterial phenotypic diversity is evident in the emergence of new pathogens, the clinical severity of different isolates, and the development of antibiotic resistance. Despite the availability of hundreds of microbial genome sequences, however, we are largely ignorant of the genetic basis of bacterial phenotypic diversity. To directly address this issue, we propose a general, systems-level strategy to identify the DNA differences that underlie the phenotypic diversity between species of the genus Shewanella. Specifically, we will assess the contribution of shared versus unique genes in the origin of bacterial phenotypic diversity. Phenotype profiling will be used to identify qualitative differences in metabolism and quantitative differences in stress tolerance among four Shewanella species isolated from distinct environments. We will perform two functional assays on each species: whole-genome mRNA expression profiling to identify all transcriptionally regulated genes and a novel, transposon mutagenesis screen to identify all nonessential genes that contribute to the phenotypes under investigation. We will use computational tools to integrate the phenotype, mutagenesis, mRNA expression, and genome sequence data to generate specific, testable hypotheses regarding which genetic differences contribute to the observed phenotypic diversity. A handful of these hypotheses will be tested through genetic assays at the single-gene level. Importantly, the techniques we propose, the data we generate, and our insights into bacterial diversity and evolution are applicable to all microorganisms, including those with a significant impact on human health. ? ? The diverse physiological capabilities of human bacterial pathogens impact disease emergence, prevalence, and severity. Unfortunately, the inability to relate these diverse physiological capabilities to genetic variation hinders the prevention and treatment of these infections. We propose a general approach to correlate physiological diversity to DNA variation in bacteria and apply this strategy to a genetically amenable system. ? ? ?
| Oh, Julia; Fung, Eula; Price, Morgan N et al. (2010) A universal TagModule collection for parallel genetic analysis of microorganisms. Nucleic Acids Res 38:e146 |
