Reconciling molecular regulatory mechanisms with noise patterns of bacterial metabolic promoters in induced and repressed states

Abstract

Assessing gene expression noise in order to obtain mechanistic insights requires accurate quantification of gene expression on many individual cells over a large dynamic range. We used a unique method based on 2-photon fluorescence fluctuation microscopy to measure directly, at the single cell level and with single-molecule sensitivity, the absolute concentration of fluorescent proteins produced from the two Bacillus subtilis promoters that control the switch between glycolysis and gluconeogenesis. We quantified cellto-cell variations in GFP concentrations in reporter strains grown on glucose or malate, including very weakly transcribed genes under strong catabolite repression. Results revealed strong transcriptional bursting, particularly for the glycolytic promoter. Noise pattern parameters of the two antagonistic promoters controlling the nutrient switch were differentially affected on glycolytic and gluconeogenic carbon sources, discriminating between the different mechanisms that control their activity. Our stochastic model for the transcription events reproduced the observed noise patterns and identified the critical parameters responsible for the differences in expression profiles of the promoters. The model also resolved apparent contradictions between in vitro operator affinity and in vivo repressor activity at these promoters. Finally, our results demonstrate that negative feedback is not noise-reducing in the case of strong transcriptional bursting.B. subtilis | central carbon metabolism | promoter activity | stochastic gene expression | gene expression control

Geometric structure and information change in phase transitions

“…[18][19][20][21][22][23]. One of the most striking attributes of some bistable systems is continuous switching between ordered and disordered states, the transition occurring in bursts interspersed by a quiescent period (e.g., see [18]).…”

Relating network rigidity, time scale hierarchies, and expression noise in gene networks

“…Our findings offer mathematical substance to the counterintuitive result [6][7][8] that self-repression can be a noise maintaining mechanism, possibly important in bet-hedging adaptation strategies [16]. We estimate that switching times of ten seconds or larger should lead to mRNA and protein expression noise that is not buffered by negative feedback.…”

“…Because these time scales are not rare in repressed bacterial or eukaryotic promoters, our results should be testable by accurate expression quantification experiments on large collections of promoters with different characteristics. A recent experimental study of a few carbon catabolic operons in Bacillus subtilis [8] showed that the noisiest repressed promoter is self-repressed. This result can be explained by the inverse proportionality of the switching time and of the transcriptional bursting amplitude with the concentration of active repressor, which, for self-repressed promoters, is low in the repressed state.…”

“…This parametrization allows one, for the same promoter, to study the effect of changes of the affinity of the repressor. In bacteria, such an adaptation process could result from stress or metabolic changes such as a switch in carbon source [8]. From (12) and (13), we get…”

“…Several studies [2,3] suggest by extrapolation that noise generated by gene networks is buffered by negative feedback. However, this idea is challenged by recent theoretical [6,7] and experimental [8] work showing that negative feedback is not always noise reducing. In this paper, we relate fluctuations to time scales of the gene expression mechanisms and show that the independence of expression noise on network rigidity follows from an inversion between two such time scales.…”