Multiple High-Throughput Analyses Monitor the Response of E. coli to Perturbations

Abstract

Analysis of cellular components at multiple levels of biological information can provide valuable functional insights. We performed multiple high-throughput measurements to study the response of Escherichia coli cells to genetic and environmental perturbations. Analysis of metabolic enzyme gene disruptants revealed unexpectedly small changes in messenger RNA and proteins for most disruptants. Overall, metabolite levels were also stable, reflecting the rerouting of fluxes in the metabolic network. In contrast, E. coli actively regulated enzyme levels to maintain a stable metabolic state in response to changes in growth rate. E. coli thus seems to use complementary strategies that result in a metabolic network robust against perturbations.

Regulatory crosstalk of the metabolic network

“…Experimentally, this idea is supported by large scale surveys of the Saccharomyces cerevisiae and Escherichia coli metabolomes [16,17]. In yeast, 75% of enzyme disruptions have no detectable effect on the overall metabolic flux [18].…”

“…Although this figure is biased, because of the large number of paralogous enzymes [18] and varied experimental conditions [19] it nonetheless indicates the remarkable robustness of the metabolic network. The deletion of most paralogue-free enzyme-encoding genes indeed causes changes in the metabolic flux [16,18], but at least in bacteria and yeast, most perturbations are only detected within a surprisingly narrow part of the network [17,18]. A low number of enzyme disruptions, however, cause a system-wide response.…”

“…Bacteria, for example, counteract perturbations via changes in their overall mRNA levels, protein content and growth rate; however, they maintain the concentration of central metabolites. Perturbations cause very specific and precise adaptations of the cellular enzyme content, indicating that monitoring of the network occurs at multiple nodes [17]. Balancing the perturbation is then manifold; consequences range from fine-tuning of a few enzymes up to adjusting the overall growth rate [17,[20][21][22][23].…”

“…Perturbations cause very specific and precise adaptations of the cellular enzyme content, indicating that monitoring of the network occurs at multiple nodes [17]. Balancing the perturbation is then manifold; consequences range from fine-tuning of a few enzymes up to adjusting the overall growth rate [17,[20][21][22][23]. The latter is energetically expensive; a change in the growth rate requires numerous metabolic transitions, and the entire transcriptome, proteome and metabolome must be adapted [23].…”

Quantitative microscopy and systems biology: seeing the whole picture

“…An important aspect of experimental systems biology is the use of diVerent experimental data sources that can be integrated by the methods of computational systems biology. For instance, Ishii et al used system wide data on transcriptional, protein and metabolite levels to study the central carbon metabolism of Escherichia coli (Ishii et al 2007). Such data sets provide the starting point for computational approaches that can be used to understand fundamental physiological processes.…”