Spatial modelling of transcription dynamics in bacterial gene regulatory networks

Abstract

In Synthetic biology, researchers can alter the DNA sequence of organisms such that the behaviour to specific inputs is predictable. Regulatory systems have been ‘hacked’ into doing computation, help with bio-production, aid in personalised medicine and providing highly specific sensors. A major bottleneck in current synthetic biology is that models fail to predict system behaviour reliably, causing recent progress to be reliant on the trial and error of model-assisted system designs. One of the reasons for the models to fail is the neglect of Spatial effects. While this neglect simplifies models, recent experimental data shows localised effects. This work shows that only the combination of 3D cytosol diffusion and the 1D sliding along the chromosome of transcription factors can explain localised effects; the modelling transcription factors initial sliding route after formation reproduces experimental results. However, one essential assumption for the model described above is the initial location of a functional transcription factor at the encoding gene. While the coupled transcription and translation in prokaryotes are experimentally verified and can lead to the localisation of Transcription Factor proteins, this localisation must be assumed to be transferred to the active dimer form to reproduce the experiment. To substantiate this assumption, this work expands the limited field of protein dimerisation. A new model is introduced to explain the localisation effect with an extra pathway we call Translation Mediated Dimerisation. Here, the partially formed transcription factors still undergoing translation are thought to meet and form a dimer while still constrained to the mRNA on the other end. Even if this occurs in a minority of events, this can drastically affect non-linear behaviour. This model allows utilisation of localised effects for the rational design of system dynamics otherwise unavailable, expanding the possibilities and increasing the efficiency of synthetic biology