Biology subjects

Darlington, A. P. S.

Publications and source records attributed to Darlington, A. P. S..

5 recordsLinked to original sources

bioRxiv2024

Design principles for engineering bacteria to maximise chemical production from batch cultures

Bacteria can be engineered to manufacture chemicals, but it is unclear how to optimally engineer a single cell to maximise production performance from batch cultures. Moreover, the performance of engineered production pathways is affected by competition for the hosts native resources. Here, using a "host-aware" computational framework which captures competition for both metabolic and gene expression resources, we uncover design principles for engineering the expression of host and production enzymes in a cell to maximise volumetric productivity and yield from batch cultures. Our results suggest that selecting strains in the lab for maximum growth and product synthesis can achieve close to maximum culture productivity and yield, but the growth-synthesis trade-off fundamentally limits production performance. We show that engineering genetic circuits to switch cells to a high synthesis-low growth state after first growing to a large population can further improve performance. By analysing different circuit topologies, we show that optimal performance is achieved by circuits that inhibit host metabolism to redirect it to product synthesis. Our results should facilitate construction of microbial cell factories with high and efficient production capabilities.

synthetic biology↗

bioRxiv2021

The interplay between growth rate and nutrient quality defines gene expression capacity

The gene expression capacity of bacterial cells depends on the interplay between growth and the availability of the transcriptional and translational machinery. Growth rate is widely accepted as the global physiological parameter controlling the allocation of cell resources. This allocation has an impact on the ability of the cell to produce both host and heterologous proteins required for synthetic circuits and pathways. Understanding the relationship between growth and resources is key for the efficient design of artificial genetic constructs, however, it is obscured by the mutual dependence of growth and gene expression on each other. In this work, we investigate the individual contributions of molecular factors, growth rate and metabolism to gene expression by investigating the behaviour of bacterial cells growing in chemostats in growth-limited conditions. We develop a model of the whole cell that captures trade-offs in gene expression arising from the individual contributions of different factors, and validate it by analysing gene couplings which emerge from competition for the gene expression machinery. Our results show that while growth rate and molecular factors, such as the number of rRNA operons, set the abundance of transcriptional and translational machinery available, it is metabolism that governs the usage of those resources by tuning elongation rates. We show that synthetic gene expression capacity can be maximised by using low growth in a high-quality medium. These findings provide valuable insights into fundamental trade-offs in microbial physiology that will inform future strain and bioprocesses optimisation.

synthetic biology↗

bioRxiv2020

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

Recent work on engineering synthetic cellular circuitry has shown that non-regulatory interactions brought about through competition for shared gene expression resources, such as RNA polymerase and ribosomes, can result in degraded performance or even circuit failure. Transcriptional and translational resource allocation controllers based on orthogonal circuit-specific gene expression machineries have previously been separately designed to enforce modularity and improve circuit performance. Here we investigate the potential advantages, challenges, and design trade-offs involved in combining transcriptional and translational resource allocation into one overarching centralised control system. We design a number of biologically feasible controllers that reduce coupling at both the transcriptional and translational levels simultaneously, and identify some key performance tradeoffs. We apply tools from robust control theory to rigorously quantify the impact of uncertainty/variability arising due to experimental implementations on the operation of such controllers. Based on these results, we identify promising architectures for the construction of robust dual transcriptional-translational resource allocation controllers.

synthetic biology↗

bioRxiv2018

Engineering Translational Resource Allocation Controllers: Mechanistic Models, Design Guidelines, and Potential Biological Implementations

The use of orthogonal ribosomes in combination with dynamic resource allocation controllers is a promising approach for relieving the negative effects of cellular resource limitations on the modularity of synthetic gene circuits. Here, we develop a detailed mechanistic model of gene expression and resource allocation, which when simplified to a tractable level of complexity, allows the rational design of translational resource allocation controllers. Analysis of this model reveals a fundamental design trade-off; that reducing coupling acts to decrease gene expression. Through a sensitivity analysis of the experimentally tuneable controller parameters, we identify how each controller design parameter affects the overall closed-loop behaviour of the system, leading to a detailed set of design guidelines for optimally managing this trade-off. Based on our designs, we evaluated a number of alternative potential experimental implementations of the proposed system using commonly available biological components. Finally, we show that the controller is capable of dynamically allocating ribosomes as needed to restore modularity in a number of more complex synthetic circuits, such as the repressilator, and activation cascades composed of multiple interacting modules.

synthetic biology↗

bioRxiv2017

Dynamic Allocation Of Orthogonal Ribosomes Facilitates Uncoupling Of Co-Expressed Genes

Introduction of synthetic circuits into host microbes creates competition between circuit and host genes for shared cellular resources, such as RNA polymerases and ribosomes. This can lead to the emergence of unwanted coupling between the expression of different genes, complicating circuit design and potentially leading to circuit failure. Here we demonstrate the ability of orthogonal ribosomes to alleviate the effects of this resource competition. We partition the ribosome pool by expressing an engineered 16S RNA with altered specificity, and use this division of specificity to build simple resource allocators which reduce the level of ribosome-mediated gene coupling. We then design and implement a dynamic resource allocation controller, which acts to increase orthogonal ribosome production as the demand for translational resources by a synthetic circuit increases. Our results highlight the potential of dynamic translational resource allocation as a means of minimising the impact of cellular limitations on the function of synthetic circuitry.

synthetic biology↗