Deconvolution of gene expression noise into physical dynamics of cognate promoters

When facing recalcitrant pollutants, soil bacteria exploit noise of catabolic promoters for deploying environmentally beneficial phenotypes such as metabolic bet-hedging an/or division of biochemical labor. While the origin of such noise in terms of upstream promoter-regulator interplay is hardly understood, its dynamics has to be somehow encrypted in the patterns of flow-cytometry data delivered by transcriptional reporter fusions. On this background, we have examined the behaviour of the Pm promoter of the environmental bacterium Pseudomonas putida and its cognate 3-methylbenzoate-responsive regulator XylS under different conditions by following expression of Pm-GFP fusions in single cells. Using mathematical modeling and computational simulations we elucidated the kinetic properties of the system and use them as a baseline code to interpret the observed fluorescence output in terms of upstream regulator variability. Transcriptional noise was predicted to depend on the intracellular physical distance between the regulator source (where the e.g. XylS is being produced in the cells) and the target promoter. Experiments with engineered bacteria where this distance is either minimized or enlarged proved the effects of proximity on noise patterns as predicted by the model. This approach not only allowed deconvolution of cytometry data into mechanistic information on the gene expression flow. But it also provided a mechanistic basis for selecting a given level of noise in engineered regulatory nodes e.g. in Synthetic Biology constructs.