Abstract
Stress response networks frequently have a single upstream regulator that controls many downstream genes. However, the downstream targets are often diverse, therefore it remains unclear how their expression is specialized when under the command of a common regulator. To address this, we focused on a stress response network where the multiple antibiotic resistance activator MarA from Escherichia coli regulates diverse targets ranging from small RNAs to efflux pumps. Using single-cell experiments and computational modeling, we showed that each downstream gene studied has distinct activation, noise, and information transmission properties. Critically, our results demonstrate that understanding biological context is essential; we found examples where strong activation only occurs outside physiologically relevant ranges of MarA and others where noise is high at wild type MarA levels and decreases as MarA reaches its physiological limit. These results demonstrate how a single regulatory protein can maintain specificity while orchestrating the response of many downstream genes.
Highlights
Genetic networks often feature master regulators that control suites of downstream genes
Bacteria can sense and respond to stress in their environment. This process is often coordinated by a master regulator that turns on or off many downstream genes, allowing the cell to survive the stress
We focus on how expression of diverse downstream genes is optimized by targets of the multiple antibiotic resistance activator MarA
Summary
Genetic networks often feature master regulators that control suites of downstream genes This type of architecture is common in stress response; examples include Msn and Crz in Saccharomyces cerevisiae, σB in Bacillus subtillis, and the multiple antibiotic resistance activator MarA in Escherichia coli [1,2,3,4]. Each of these regulators controls tens to hundreds of diverse downstream targets with widely varying functional roles. The properties are linked, they can be adjusted in a variety of ways to tailor the response of individual genes
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