Time resolved response of E. coli to 5 different stress conditions

Environmental fluctuations lead to a rapid adjustment of the physiology of Escherichia coli, necessitating changes on every level of the underlying cellular and molecular network. Thus far, the vast majority of global analyses of E. coli stress responses have been limited to just one level, gene expression. Here we incorporate the metabolite composition together with gene expression data in order to provide a more comprehensive insight on system level stress adjustments by describing detailed time-resolved E. coli response to five different perturbations (cold, heat, oxidative stress, lactose diauxie, and stationary phase). The metabolite response is more specific as compared to the general response observed on the transcript level and is reflected by much higher specificity during the early stress adaptation phase and when comparing the stationary phase response to other perturbations. Despite these differences, the response on both levels still follows the same dynamics and general strategy of energy conservation as reflected by rapid decrease of central carbon metabolism intermediates coinciding with down regulation of genes related to cell growth. Application of co-clustering and canonical correlation analysis on combined metabolite and transcript data identified a number of significant condition dependent associations between metabolites and transcripts. The results confirm and extend existing models about co-regulation between gene expression and metabolites demonstrating the power of integrated systems oriented analysis. Four different environmental perturbations, comprising oxidative stress, glucose-lactose diauxic shift, heat, and cold treatments and using an unperturbed culture as a control have been used for transcript profiling. microarray-based transcript profiling was carried out for samples from time points 10-50 min post-perturbation plus two control time points prior to each perturbation for all conditions except the oxidative stress experiment in which all samples (12 time points) were used for transcript profiling covering the entire growth curve, including the stationary phase. Each experimental condition was independently repeated three times.