Bilateral BBSRC NSF/BIO - Synthetic gene circuits to measure and mitigate translational stress during heterologous protein expression

Lead Research Organisation: University of Aberdeen
Department Name: Sch of Medicine, Medical Sci & Nutrition


Biotechnology uses recombinant gene expression to produce a range of medicines, including insulin, vaccines, and new anti-cancer therapeutic agents based upon antibodies. For instance, the human insulin gene has been introduced into the bacterium E. coli to drive the production of this valuable medicine in the new bacterial host, cheaply and safely. In this proposal, an interdisciplinary team of biologists and physicists will establish novel technologies to improve the ability of a cell to make recombinant proteins at higher efficiency, and with greater accuracy, improving the quality, yield, cost-effectiveness and safety of next-generation medicines.

Most products of biotechnology are proteins, long chains of units called amino acids, of which there are 20 different varieties. The structures of proteins, and the sequence of their amino acids, are determined by genes, DNA strands of nucleotides with a specific sequence. To make a protein, the coding information locked in the sequence of nucleotides within the gene is first copied into a messenger RNA (mRNA), also composed of nucleotides. Then a molecular machine in the cell called a ribosome reads the information within the mRNA to produce the correct chain of amino acids, forming the protein, in a process called translation. The sequence of amino acids in the protein defines its properties and function. When a cell is programmed to produce a recombinant protein, errors can occur during translation, when an amino acid is selected to add to the protein. These errors can change the nature of the manufactured protein, and can make it defective; in the case of a protein being used as a medicine, this can prevent effective treatment, and as a worst case scenario, represent a danger to the patient.

In this proposal, the research team will work with a biotechnology company to develop sensitive devices to detect this type of error, and use them to understand how and when the cellular protein manufacturing machinery makes mistakes, so they can be minimised in the future. The team will then use assemblies of genes in a synthetic biology approach to engineer new types of cells, designed to be used in industrial fermenters, that are capable of preventing these mistakes as the proteins are produced. We will use advanced mathematical models to guide the design and safety of these new synthetic biology gene circuits. Overall, the interdisciplinary approach described in this proposal will involve biologists and physicists working together to create systems that improve production of new generations of effective medicines. To allow these improvements, it will also provide insight into the fundamental mechanisms a cell uses to express its genes and make recombinant proteins accurately. More broadly, it will indicate clear routes to optimise production of a range of modified proteins important for biotechnology and medicine.

Technical Summary

Ribosomal decoding of the mRNA depends upon the accurate recognition of each of the 61 sense codons by its correct (cognate) tRNA. Each cognate tRNA differs by one nucleotide from up to fourteen near-cognate codons encoding different amino acids. The process is normally remarkably accurate with error frequencies between 10E-4 to 10E-6, depending upon the codon. These mistranslation error frequencies, including ribosome frameshift errors, increase sharply however during translation of rare codons served by low abundance tRNA, or during ribosomal pausing caused by depletion of charged tRNAs. The high-level expression of biotechnological proteins creates exactly these conditions-depleting normally abundant tRNAs, and thus increasing translational error frequencies. Indeed, many reports describe biotechnological protein expression generating a range of undesirable mistranslation events, compromising product yield and quality, and thus the safety and efficacy of biologics. In this project we will pursue a better understanding of the system-wide causes of translational error through the design and application of novel reporters of mistranslation, capable of producing either reporter enzyme activities, or regulatory transcription factors. We combine these experimental approaches with global mathematical modelling of translation and tRNA competition to predict when system stress will stimulate mistranslation. We then use synthetic biology gene circuits to transcriptionally couple the output from these new mistranslation sensors to rP expression, to autoregulate mistranslation and recombinant protein (rP) product quality. Our industrial partner will test these synthetic gene circuits to maximise the opportunities for realising the impact of this research on biotechnology. This research will reveal for the first time the role of rPs in triggering translation system stress, and identify novel ways in which stress can be ameliorated.

Planned Impact

The use of gene expression for high level expression of heterologous proteins in the biotechnology and pharmaceutical industries is key for the production of vaccines and other medicines, as well as novel chemical feedstocks. Thus research into how the cell regulates its translational accuracy, establishing when high-level recombinant protein (rP) expression induces translational stress will aid the optimisation of high-level protein production. Key beneficiaries of this research will therefore include biotechnology companies seeking to express proteins at high level, such as vaccine components, therapeutic proteins including anti-cancer therapeutics and antibodies, as well as other industrially-used proteins. Thus the pharmaceutical and biotechnology industries will particularly benefit from this research, which has the potential to enhance health, identify new treatments for disease, and strengthen industrial competitiveness. In the longer term, members of the public may benefit from this research, as developments of new pharmaceuticals, and the industrial production of heterologous proteins become available as products that improve health and the quality of life. Producing these products more accurately and predictably using the technology to be developed in this project would enhance their yield and efficacy, and improve product safety for the public.

The UK trained workforce will benefit from this proposal through the interdisciplinary training of the researchers employed on this project. As part of the outcomes of the interdisciplinary training delivered to them as part of this proposal, each PDRA, whether biologist or theoretician by primary training, will gain detailed insight into the research field and practices of the other, partly through structured and regular project interactions, and partly through a formal training element aided by the BBSRC SysMIC on-line systems biology training programme.

The general public will benefit from this research as part of the University of Aberdeen's vibrant outreach programme, involving Café Scientifique and TechFest programmes, the latter an annual science festival for the general public. The University's dedicated Public Engagement with Research Unit (PERU) is available to maximise public engagement impact on this project. IS regularly gives research talks aimed at a lay audience at these events, as well as visiting on average 2 schools per year to give science talks connected with his research. He has recently delivered a Café Scientifique talk on synthetic biology, and will seek opportunities to deliver further talks in future. Additionally, key research findings that may be of general interest to the public will be communicated to both local and national media outlets via press releases.


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Szavits-Nossan J (2018) Power series solution of the inhomogeneous exclusion process. in Physical review. E

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Szavits-Nossan J (2018) Deciphering mRNA Sequence Determinants of Protein Production Rate. in Physical review letters

Description Controlling cellular energy flux; tRNA biosynthesis as a key determinant of lipogenesis
Amount £54,277 (GBP)
Funding ID Internal funding; no grant number 
Organisation Wellcome Trust 
Sector Charity/Non Profit
Country United Kingdom
Start 10/2017 
End 01/2018
Title GLN4 shut-off RNA seq data 
Description High throughput RNAseq data deposited in NCBI's Gene Expression Omnibus and accessible through GEO Series accession number GSE126435 
Type Of Material Database/Collection of data 
Year Produced 2019 
Provided To Others? Yes  
Impact None currently