(566b) Exploiting Transcriptional Patterns of Antibiotic Activity for Treatment Optimization and Development

Genome-wide analysis of gene expression has been successfully used to study the nature and consequences of environmental, metabolic and genetic changes. We used this methodology to elucidate and classify molecular mechanisms, phenotypic states, and cellular outcomes of action of antibiotics. The introduction of antibiotics is one of the most important achievements over the past 50 years, and they are expected to remain the most effective tool in fighting infectious diseases in the foreseeable future. Many antibiotic treatments of bacterial cells result in complex transcriptional responses, presumably resulting from the multiplicity of primary and secondary effects. Understanding the molecular consequences of antibiotic action and correlating them with macroscopic outcomes may reveal important information that can be used for sensitizing microbes to currently used drugs, identification of new targets, development of combinational treatments, and optimization of drug activity by chemically modifying available antibacterials and/or the treatment regimes. In this study, a compendium of transcriptional responses to various antibiotics has been assembled and analyzed. The data contain transcriptional patterns of activity of antibacterials targeting basic cellular processes in Escherichia coli bacterium, including (1) cell wall synthesis; (2) protein synthesis; (3) nucleic acid synthesis; (4) metabolic function. We addressed the following questions. (1) What are the common and specific transcriptional responses to the drug treatments? (2) How variable are gene expression patterns elicited by the drugs with only slightly different target specificities? (3) Can transcriptional profiles be used to predict a drug's mechanism of action and cellular outcome? (4) Given the classification of drug responses and effects on cell growth and viability in susceptible and resistant strains, targeting of which cellular processes and reactions, alone or in combination, is likely to be most effective against bacteria with specific metabolic and physiological constraints? So far, this work has provided interesting insights into molecular mechanisms of drug action and into the relationship between the target processes, cellular states and drug efficiency.