top of page

What are possible functions of dynamic gene regulation?

We have a number of projects investigating the roles of dynamic gene regulation, including investigating the roles of stochasticity in creating phenotypic diversity and in patterning.

Projects include:

Stochastic pulsing of gene expression enables the generation of spatial patterns in Bacillus subtilis biofilms. Using bacterial biofilms as a model system, we investigated the role of  stochastic pulsing of gene expression in the formation of spatial patterns. We used quantitative microscopy and time-lapse imaging to observe pulses in the activity of the general stress response sigma factor, σB, in individual cells during biofilm development. We found that both σB and sporulation activity increase in a gradient, peaking at the top of the biofilm, even though σB represses sporulation. Through modelling and experiment, we propose that stochastic pulsing of σB allows cells to activate either σB or sporulation, allowing mutually exclusive cell states to co-exist in the same regions of the biofilm. Thus, stochastic pulses of gene expression can enable the formation of simple spatial patterns in biofilms.

SigB gradient biofilm.jpg

Escherichia coli can survive stress by noisy growth modulation

We have shown how noisy expression of a key stress-response regulator, RpoS, allows E. coli to modulate its growth dynamics to survive future adverse environments. Using single-cell, time-lapse microscopy and microfluidics along with a stochastic model, we found that a dynamic positive feedback loop between RpoS and growth rate produces multi-generation RpoS pulses. We demonstrated that E. coli prepares for sudden stress by entering prolonged periods of slow growth mediated by RpoS. This dynamic phenotype is captured by an RpoS-growth feedback model. This work on the relationship between noisy gene expression, growth and survival paves the way for further exploration of functional phenotypic variability. See Patange et al., 2018.

Fluctuations of the transcription factor ATML1 can pattern giant cells in the Arabidopsis sepal. In collaboration with Dr. Adrienne Roeder and Professor Henrik Jonsson we have examined the role of stochasticity in the expression of the transcription factor ATML1 in giant cell formation in Arabidopsis sepals. Although ATML1 is expressed in all epidermal cells, we find that ATML1 functions in a sensitive dosage dependent manner, in which high levels specify giant cells. Using modelling, live imaging, and computational image analyses we found that ATML1 fluctuates in all epidermal cells. If ATML1 levels surpass a soft threshold during the G2 phase of the cell cycle, the cell has a high probability of entering endoreduplication and becoming giant. Otherwise, the cell divides. Our results suggest a fluctuation patterning mechanism for how cellular decisions can be initiated through random processes.

See Meyer et al. 2018

ATML1 Ploidy figure.jpg

An ABA-GA bistable switch can account for variability of Arabidopsis seed germination time

Variability in seed germination time amongst genetically identical seeds is thought to function as a bet-hedging strategy. In collaboration with Professor Dame Ottoline Leyser we studied the mechanisms underlying variability in seed germination time in Arabidopsis. We identified two QTL underlying variability, showing that both may modulate sensitivity of of seeds to the hormone abscisic acid (ABA). ABA interacts with another hormone, GA, in a mutually antagonistic manner, forming a bistable switch. We developed a stochastic model of this bistable switch and showed that it can account for variability in seed germination times and explain the effect of ABA sensitivity on the level of variability. Our work provides a foundation for understanding the mechanism and functional role of phenotypic variability in germination time. 

ABA GA germination figure.jpg
bottom of page