Biology subjects

Bates, D. G.

Publications and source records attributed to Bates, D. G..

7 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

gcFront: a tool for determining a Pareto front of growth-coupled cell factory designs

MotivationA widely applicable strategy to create cell factories is to knock out (KO) genes or reactions to redirect cell metabolism so that chemical synthesis is made obligatory when the cell grows at its maximum rate. Synthesis is thus growth-coupled, and the stronger the coupling the more deleterious any impediments in synthesis are to cell growth, making high producer phenotypes evolutionarily robust. Additionally, we desire that these strains grow and synthesise at high rates. Genome-scale metabolic models can be used to explore and identify KOs that growth-couple synthesis, but these are rare in an immense design space, making the search difficult and slow. ResultsTo address this multi-objective optimization problem, we developed a software tool named gcFront - using a genetic algorithm it explores KOs that maximise cell growth, product synthesis, and coupling strength. Moreover, our measure of coupling strength facilitates the search so that gcFront not only finds a growth coupled design in minutes but also outputs many alternative Pareto optimal designs from a single run - granting users flexibility in selecting designs to take to the lab. Availability and ImplementationgcFront, with documentation and a workable tutorial, is freely available at GitHub: https://github.com/lLegon/gcFront, the repository of which is archived at Zenodo, DOI: 10.5281/zenodo.6338595 (Legon et al., 2022). Supplementary InformationSupplementary notes and data files are available at Bioinformatics online.

bioinformatics↗

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

Designing an irreversible metabolic switch for scalable induction of microbial chemical production

Bacteria can be harnessed to synthesise high-value chemicals. A promising strategy for increasing productivity uses inducible control systems to switch metabolism from growth to chemical synthesis once a large population of cell factories are generated. However, use of expensive chemical inducers limits scalability of this approach for biotechnological applications. Switching using cheap nutrients is an appealing alternative, but their tightly regulated uptake and consumption again limits scalability. Here, using mathematical models of fatty acid uptake in E. coli as an exemplary case study, we unravel how the cells native regulation and program of induction can be engineered to minimise inducer usage. We show that integrating positive feedback loops into the circuitry creates an irreversible metabolic switch, which, requiring only temporary induction, drastically reduces inducer usage. Our proposed switch should be widely applicable, irrespective of the product of interest, and brings closer the realization of scalable and sustainable microbial chemical production.

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↗

bioRxiv2019

Minimally Complex Nucleic Acid Feedback Control Systems for First Experimental Implementations

Chemical reaction networks based on catalysis, degradation, and annihilation may be used as building blocks to construct a variety of dynamical and feedback control systems in Synthetic Biology. DNA strand-displacement, which is based on DNA hybridisation programmed using Watson-Crick base pairing, is an effective primitive to implement such reactions experimentally. However, experimental construction, validation and scale-up of nucleic acid control systems is still significantly lagging theoretical developments, due to several technical challenges, such as leakage, crosstalk, and toehold sequence design. To help the progress towards experimental implementation, we provide here designs representing two fundamental classes of reference tracking control circuits (integral and state-feedback control), for which the complexity of the chemical reactions required for implementation has been minimised. The supplied minimally complex control circuits should be ideal candidates for first experimental validations of nucleic acid controllers.

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↗