Addressing biological uncertainties in engineering gene circuits

Abstract

Synthetic biology has grown tremendously over the past fifteen years. It represents a new strategy to develop biological understanding and holds great promise for diverse practical applications. Engineering of a gene circuit typically involves computational design of the circuit, selection of circuit components, and test and optimization of circuit functions. A fundamental challenge in this process is the predictable control of circuit function due to multiple layers of biological uncertainties. These uncertainties can arise from different sources. We categorize these uncertainties into incomplete quantification of parts, interactions between heterologous components and the host, or stochastic dynamics of chemical reactions and outline potential design strategies to minimize or exploit them.

Design trade-offs and robust architectures for combined transcriptional and translational resource allocation controllers

“…Analysing the best decoupling (i.e. lowest 2D score) designs for UBER-OR shows that these controllers can be implemented on various combinations of single and medium (20) multicopy plasmids, with the orthogonal RNA polymerase, o-rRNA and translational controller protein (p f ) being carried on the multicopy plasmid and the transcriptional regulator (p q ) being carried on the lower copy counterpart ( Figure S4A). The translational controller protein requires a strong RBS (low β f,f ).…”

“…Even when a part with a desired set of kinetics exists with small uncertainty, it is not clear how circuit context effects may impact this level of uncertainty; for example the surrounding DNA sequence may cause subtle changes in binding rates. The causes of uncertainty in biological circuit design have been reviewed extensively in [2] and [20]. To take account of these biological realities, here we assess the robustness of both dual controllers to parametric uncertainty; focusing on the 'designable' parameters governing the production rates of the orthogonal RNA polymerase and rRNA and the production rates and action of the other controller proteins (Table 1).…”

Quantitative and synthetic biology approaches to combat bacterial pathogens

“…A major challenge in predictable engineering of genetic circuits in living cells is the complex interactions between cellular physiology and the designed circuits [38-40]. To address this challenge, cell-free systems provide a simplified platform for gene circuits whose functions primarily depend on gene expression or simple gene regulation [41].…”

A Computational Design of a Programmable Biological Processor

“…One of the main differences between the digital electronic systems and biological systems is in the free diffusion of signals carrying the information in the latter. It is thus vital to ensure orthogonality between the synthetic parts as well as orthogonality between the synthetic parts and the cellular metabolism of the host, which is extremely hard when the number of synthetic parts is increased [19,20]. Several approaches, such as the use of synthetically designed transcription or translation regulators (see e.g.…”