Abstract
Understanding how bacteria coordinate gene expression with biomass growth to adapt to various stress conditions remains a grand challenge in biology. Stress response is often associated with dramatic accumulation of cellular guanosine tetra- or penta-phosphate (p)ppGpp (also known as ‘magic spot’), which is a key second messenger participating in regulating various biochemical and physiological processes of bacteria. Despite of the extensive studies on the mechanism of gene regulation by (p)ppGpp during stringent response, the connection between (p)ppGpp and bacterial steady-state exponential growth remains elusive. Here, we establish a versatile genetic approach to systematically perturb the (p)ppGpp level of Escherichia coli through titrating either the single-function (p)ppGpp synthetase or the singe-function (p)ppGpp hydrolase and quantitatively characterize cell growth and gene expression. Strikingly, increased and decreased (p)ppGpp levels both cause remarkable growth suppression of E. coli. From a coarse-grained insight, we demonstrate that increased (p)ppGpp levels limit ribosome synthesis while decreased (p)ppGpp levels limit the expression of metabolic proteins, both resulting in non-optimal resource allocation. Our study reveals a profound role of (p)ppGpp in regulating bacterial growth through governing global resource allocation. Moreover, we highlight the Mesh1 (p)ppGpp hydrolase from Drosophila melanogaster as a powerful genetic tool for interrogating bacterial (p)ppGpp physiology.
Highlights
1.0 0.8 0.6 0.4 0.2 0.0 wt LB wt glucose relA LB relA glucose medium, glucose casamino acid medium, glucose minimal medium, glycerol minimal medium and acetate minimal medium. (B) SpoT E319Q overexpression (OE) based on the inducible lacIq-Ptac system. (C) Effect of SpoT E319Q over-expression on the growth rate of wild type cells or ΔrelA mutant cells growing in LB medium or glucose minimal medium. (D) The relative change of growth rate of E. coli upon
Data are average of triplicates with standard deviations being within 10%
The coding sequence has been optimized based on the E. coli codon bias
Summary
1.0 0.8 0.6 0.4 0.2 0.0 wt LB wt glucose relA LB relA glucose medium, glucose casamino acid medium, glucose minimal medium, glycerol minimal medium and acetate minimal medium. (B) SpoT E319Q overexpression (OE) based on the inducible lacIq-Ptac system. (C) Effect of SpoT E319Q over-expression on the growth rate of wild type cells or ΔrelA mutant cells growing in LB medium or glucose minimal medium. (D) The relative change of growth rate of E. coli upon. 0 μM IPTG 20 μM IPTG 25 μM IPTG 30 μM IPTG 35 μM IPTG 50 μM IPTG 0 μM IPTG 36 μM IPTG 40 μM IPTG 45 μM IPTG 50 μM IPTG
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