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bioRxiv2022

Growth rate controls the sensitivity of gene regulatory circuits

Unicellular organisms adapt to their changing environments by gene regulatory switches that sense chemical cues and induce specific target genes when the inducing signal is over a critical threshold. Using mathematical modeling we here show that, because growth rate sets the dilution rate of intracellular molecules, the sensitivity of gene regulatory switches automatically couples to growth rate, in a way that can be exploited by natural selection. We confirm the modeling predictions by experimentally demonstrating that, as nutrient quality is varied, the concentration of inducer required for activating the lac operon in E. coli increases quadratically with the populations growth rate. Our theory further predicts that, when growth rate is instead modulated by translation inhibition, critical inducer levels are invariant, and we experimentally validate this prediction as well. Moreover, we establish that this growth-coupled sensitivity allows bacteria to implement concentration-dependent sugar preferences, in which a new carbon source is used only if its concentration is high enough to improve upon the current growth rate of the cells. Using microfluidics in combination with time-lapse microscopy, we validate experimentally that this strategy governs how mixtures of glucose and lactose are used in E. coli at single-cell level. Overall, growth-coupled sensitivity provides a general mechanism through which cells can mute external signals in beneficial conditions when growth is fast, and become highly sensitive to alternative nutrients or stresses when growth is slow or arrested.

systems biology↗

bioRxiv2020

Subpopulations of sensorless bacteria drive fitness in fluctuating environments

Populations of bacteria often undergo a lag in growth when switching conditions. Because growth lags can be large compared to typical doubling times, variations in growth lag are an important but often overlooked component of bacterial fitness in fluctuating environments. We here explore how growth lag variation is determined for the archetypical switch from glucose to lactose as a carbon source in E. coli. First, we show that single-cell lags are bimodally distributed and controlled by a single-molecule trigger. That is, gene expression noise causes the population before the switch to divide cells with zero pre-existing into subpopulations with zero and nonzero lac operon expression. While ’sensorless’ lac expression at the switch have long lags because they are unable to sense the lactose signal, any nonzero lac operon expression suffices to ensure a short lag. Second, we show that the growth lag at the population level depends crucially on the fraction of sensorless cells, and that this fraction in turn depends sensitively on the growth condition before the switch. Consequently, even small changes in basal expression affecting the fraction of sensorless cells can significantly affect population lags and fitness under switching conditions, and may thus be subject to significant natural selection. Indeed, we show that condition-dependent population lags vary across wild E. coli isolates. Since many sensory genes are naturally low expressed in conditions where their inducer is not present, bimodal responses due to subpopulations of sensorless cells may be a general mechanism inducing phenotypic heterogeneity and controlling population lags in switching environments. This mechanism also illustrates how gene expression noise can turn even simple sensory gene circuits into a bet-hedging module, and underlines the profound role of gene expression noise in regulatory responses.Competing Interest StatementThe authors have declared no competing interest.View Full Text

systems biology↗