Engineered burden-based feedback for robust and optimised synthetic biology

Lead Research Organisation: Imperial College London
Department Name: Bioengineering


Synthetic biology is an exciting new subject that is accelerating the research and development of new biotechnologies by rigorously applying engineering design principles to the way we work with biological systems. The most prominent application of synthetic biology is the rational modification and redesign of living organisms like microbes for new efficient use in sectors such as energy production, biomedicine, drug production and food technology. Crucial to developing and applying synthetic biology is the rigorous quantification, modelling, analysis and control of the synthetic biology designs. By using this engineering framework we aim to be able to reliably predict and robustly control how engineered biological systems will operate.

Although synthetic biology has had numerous successes in research, it is still difficult to predict how engineered cells behave when new synthetic genetic information is added to these host cells. One of the major reasons for this is that new synthetic genes add an as-yet unquantified burden to cells, particularly to commonly used microbes like E. coli. This burden effect is due to the new genes requiring resources to be maintained and function. This means that the introduced genes take resources away from those needed by their host cell in order to grow and survive. Usually the result of this is the unpredictable failure of the synthetic biology design to behave as expected or the creation of designs that only function in a narrow set of ideal conditions.

The work proposed in this project seeks to address and make use of the understudied effect of synthetic biology we know as burden. To achieve this goal, we will use novel genetic tools to quantify the effect of burden for several typical synthetic biology devices and do this work in the well-characterised microbe E. coli so that our results are useful to the many researchers who work with this model organism. To see how the cell naturally reacts to burden we will use the high-resolution tool of RNA sequencing to quantify the gene expression changes that a cell triggers when it is burdened. Quantified burden combined with the quantified gene expression changes in response to burden will together give us crucial data that can be used to build a mathematical model of how a cell reacts to new synthetic genes being added and used. This model will allow future applications of synthetic biology to predict how synthetic systems will interact with their host cells and therefore open the door for rigorous optimisation of the robustness/performance compromise inherent to any control engineering design. It will also allow for a new generation of synthetic biology devices that automatically account for the burden effect. To demonstrate this final point, this project will use our quantified understanding of burden to engineer novel synthetic plasmid vectors that are designed to auto-regulate their copy number via feedback mechanisms that take into account burden, thereby serving as general purpose burden-based controllers. We will show how these plasmid systems work by building and testing a self-regulating biological nightlight that emits bioluminescence in the dark without any significant loss in growth. The new plasmid systems we generate will be extremely valuable for synthetic biology as they will allow synthetic devices and systems to respond directly to cell health thereby endowing them with the robust and predictable behaviours needed for future applications in health, energy and biosensing.

Planned Impact

Synthetic biology is an EPSRC priority research area where scientists apply engineering principles to modify and reconstruct biology, in order to make biological engineering a scalable, predictable and economically successful industry for the 21st century. The USA has so far led the way in synthetic biology, but the UK's strong record in fundamental science puts us in an enviable position to deliver the foundational tools needed to move synthetic biology from ad-hoc custom designs to an advanced engineering discipline. The key to delivering this lucrative future is the predictable and repeatable engineering of biology from parts, using a rational approach incorporating modelling, design, analysis, control and simulation. This method is still non-trivial, partly due to a lack of well-characterised parts and predictive models, but also due to a major gap in our understanding of how engineered biology interacts with the natural cellular systems in which it is hosted. The burden synthetic biology imparts on its host cell is a crucial part of this understudied gap. Without sufficient understanding and control over burden, many designs in synthetic biology fail unexpectedly. Clearly, to accelerate the realisation and predictability of synthetic biology designs for research and industry, we need to bridge this gap. This project is a rational plan to address this, by understanding, quantifying, modelling and controlling the burden of synthetic biology and so advance our ability to engineer biology for human needs.

The deliverables leading to major impact on knowledge are four-fold: (i) a major advance in our understanding of the burden interactions between synthetic biology systems and their host cell, (ii) a new set of well-characterised biological parts regulated by burden effects and useful for future designs, (iii) a mathematical model of the cellular response to burden that will inform and predict future constructs, and (iv) a set of new burden-regulated plasmids capable of feedback-regulated self-optimisation. Each of these deliverables will immediately have economic and societal impact on current and future synthetic biology research projects, improving predictability of designs and therefore accelerating turn-over times from ideas to realisation. The fundamental research that we will perform will also provide new insights for microbiology and have useful synergy to systems biology research aiming at a greater understanding of the processes underlying natural cell behaviour.

The private sector is actively involved in synthetic biology and its presence in industry is growing at a rate where it is not unreasonable to believe that it will eventually replace large parts of the petrochemical industry. This project will impact here by enabling more complex yet robust designs using our proposed self-optimising plasmids and burden-responsive parts. We especially expect to make an impact on the next challenge in biosynthesis of fuels and high-value compounds by incorporating regulation to optimise production in a range of conditions.

This project will also impact on educational training. Synthetic biology is an increasingly popular subject with students, specifically because of its increasing repeatability, ease-of-use and due to its anticipated impact on the future. The members of this project play an active role in the training and education of the next generation through synthetic biology teaching at Imperial and intend to incorporate the findings, models and parts from this project into courses and suitable research competitions such as iGEM ( or CAGEN ( The UK has had remarkable success in teaching parts-based synthetic biology, producing many world-class undergraduate projects, so investment in further research here in the UK is critical to retaining the best students in the country and building a successful UK-based biotechnology industry.
Description This research aims at engineering a burden-based feedback for robust and optimised Synthetic Biology. The project progressed well: cellular burden caused by a collection of synthetic devices was assessed using two burden-monitor strains developed in the lab. A sub-set of devices was then chosen to perform RNAseq analysis to investigate the transcriptional changes occurring in the cells due to burden. Samples were submitted and analysed and led to the identification of burden responsive promoters. With this information we were able to build a burden - responsive feedback system. A mathematical model was also developed to aid experimental design.

The project managed to meet all of the stated aims of the project by its conclusion and has led to a major 2018 research paper in Nature Methods. The burden-responsive feedback controller represents a useful tool for the whole synthetic biology community with potential applications in industry for more robust and optimised production of useful proteins by cells. Also, this project provides significant new foundational information on the molecular mechanisms of burden in E. coli that are now proving useful for the understanding of the interaction between bacterial cells and synthetic constructs, and devising new ways to design experiments.
Exploitation Route Our capacity measurement assay - published in Nature Methods in 2015 (Ceroni et al) can be used by anyone who wants to measure the gene expression capacity costs of their parts and designs. It has already been implemented at a US cloud lab company (Transcriptic). Our RNAseq data - published in Nature Methods in 2018 (Ceroni et al) is an open-access resource for those researching in systems and synthetic biology of E. coli. Our burden-based feedback system has been intentionally designed as a modular add-on that others can use in their research. Indeed, the DNA encoding this module is available for sharing via and has been shared with nearly a dozen groups as of late 2019.
Sectors Manufacturing

including Industrial Biotechology

Pharmaceuticals and Medical Biotechnology

Description The development of a burden-based feedback platform for the control of gene expression represents an important tool for the field of Synthetic Biology in industry. The novel capacity measurement platform we have produced and published allows researchers in industrial biotechnology to design more efficient gene expression and to achieve more robust and optimised expression of molecules of interest. The capacity measurement platform has been used extensively by the synthetic biology field and following our invention of this in 2014, other groups have now reported versions made for measuring capacity in human cells, yeast cells and other organisms following the principles of our original design. Several companies in the biotechnology sector have also contacted us to get recommendations on how to use this in their own industrial processes. The DNA encoding our feedback-based control system has been requested by many other scientists via and discussions have been ongoing with UK and US biotechnology and synthetic biology companies on licensing this technology for their protein-production workflows.
First Year Of Impact 2014
Sector Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology
Impact Types Economic