A bottom-up approach to gene regulation

Abstract

The ability to construct synthetic gene networks enables experimental investigations of deliberately simplified systems that can be compared to qualitative and quantitative models. If simple, well-characterized modules can be coupled together into more complex networks with behaviour that can be predicted from that of the individual components, we may begin to build an understanding of cellular regulatory processes from the 'bottom up'. Here we have engineered a promoter to allow simultaneous repression and activation of gene expression in Escherichia coli. We studied its behaviour in synthetic gene networks under increasingly complex conditions: unregulated, repressed, activated, and simultaneously repressed and activated. We develop a stochastic model that quantitatively captures the means and distributions of the expression from the engineered promoter of this modular system, and show that the model can be extended and used to accurately predict the in vivo behaviour of the network when it is expanded to include positive feedback. The model also reveals the counterintuitive prediction that noise in protein expression levels can increase upon arrest of cell growth and division, which we confirm experimentally. This work shows that the properties of regulatory subsystems can be used to predict the behaviour of larger, more complex regulatory networks, and that this bottom-up approach can provide insights into gene regulation.

Deviant effects in molecular reaction pathways

“…Importantly, as local dynamics can then propagate through biomolecular networks-for example, via signal transduction pathways [26][27][28][29][30][31] , potentially expressing themselves in species that are otherwise directly involved only in strictly classical kinetics-the presence of just one such mechanism within a larger biological process may lead to a variety of system-wide nonclassical behavior modes 22,[32][33][34][35][36][37][38][39][40] . Given such potentially global implications of locally deviant pathway dynamics, we hope that this work may offer biologists involved with kinetic analysis or molecular modeling additional tools and intuition to help decide whether their work requires the use of discrete and stochastic chemical master equation-based methods or whether the simpler classical chemical kinetics framework is sufficient.…”

Metabolic engineering of microorganisms for biofuels production: from bugs to synthetic biology to fuels

“…For example, Ro et al [ 60] were able to take the already optimized mevalonate pathway [ 61] and extend it to produce artemisinic acid. As the number of biologically produced molecules increases, the need to reuse and mix enzymatic pathways or subpathways will increase as well [ 62]. Creation of modular subpathways that can be easily interconnected is an area of active research with much potential.…”

Self-regulation in a minimal model of chemical self-replication

“…Like others, i.e., [12,19] and [38,39], we consider a simple functional form to model either repression or activation of gene transcription characterized by the values (m,n). Since genetic repression is more often observed in biochemical systems, the repression case (0,2) has been widely studied in the literature [40][41][42][43][44][45], while the activation case has been seldom used [9][10][11][12][13]. Although repression tends to stabilize a dynamical system, activation coupled with degradation can show oscillatory behavior or even complex oscillations.…”

“…In general, repression, characterized by a negative feedback, is more common in biological systems because of its tendency to stabilize the concentration of relevant metabolites [7,8]. Nevertheless, activation characterized by a positive feedback is also observed in biological systems [9][10][11][12][13], and it is considered necessary for multistability [8][9][10][11][12][13][14].…”