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.

Biological drugs (e.g. monoclonal antibodies, MAbs) based on recombinant DNA technology have transformed the treatment of life-limiting diseases including cancer, haemophilia and rheumatoid arthritis. The recent explosive growth in the biologics sector looks set to continue, with growing applications in precision medicine and personalised healthcare, and there are many new complex biologics in the drug discovery pipeline (e.g. bispecific, trispecific, and conjugated MAbs). The intrinsic complexity of these life-saving drugs is too challenging for synthesis by simple chemistry and requires the utilisation of living cells. Forcing cells to produce proteins that they do not naturally express is complex, and often requires a long period of trial and error cell manipulation, making the bio-manufacturing process time-consuming and very expensive and directly impacting on the delivery of transformative medicines to patients. With the recent remarkable development of powerful tools for editing mammalian genomes, new methods and automation for the synthesis of large numbers of DNA constructs, and the context provided by systems biology, the time is now right for using Synthetic Biology to establish a new paradigm for cost-effective manufacture of biologic drugs. In turn this will have a major impact on medicine and the health related industries, and make the biopharmaceutical value chain more cost-efficient. The scale of the economic opportunity associated with this project is enormous. The UK has one of the most dynamic and innovative healthcare industries in the world and has developed over 20% of the world's top 100 selling drugs. The medical technology sector in the UK consists of around 2,800 companies, employing 52,000 people and generating around £10.6bn of turnover annually. An increasing portion of all medicines, currently estimated at 20%, are biopharmaceuticals. The global biologics market was valued at an estimated $251.5 billion in 2018 and is predicted to reach $319 billion by 2021. The CHO cell is the most widely used industrial expression system, which generates ~70% of approved and marketed therapeutic recombinant proteins, including multiple monoclonal antibodies (mAbs), so any enhancement of production efficiency and quality has a huge economic impact. The vision of this prosperity partnership is to utilise state of the art investigational tools and synthetic biology approaches to both elucidate the intricacies of the CHO cell manufacturing platform and engineer it to be more predictive, effective, cost-efficient, and competitive for the production of biotherapeutics in the UK.

Cells use small membrane bound envelopes, called vesicles, to store and export molecules out of the cell. The ability to reprogram a cell to control this process has huge potential for synthetic biology as it would allow us to harness the cell's machinery for the controlled packaging and release of commercially-valuable molecules neatly packaged into vesicles. This project is based on our discovery of a way to hijack the cell to control this process. This simple and cost-effective invention works by adding a small tag onto the protein. This tag results in bacteria producing huge numbers of these membrane packages filled with the tagged molecules of interest. These packages are exported from the cell into the growth broth, and result in more than a 100-fold increase in protein yield. Protein function is preserved within these packages for months in the fridge. This novel technology represents a major breakthrough in recombinant protein production as it facilitates simple, efficient and rapid purification of diverse proteins for use in biotechnology and medical applications. In this project we will develop this technology and apply it to enhance production and purification of a wide range of biotechnologically and medically important proteins. Working with industry (Fujifilm-Diosynth Biotechnologies) we will optimise the system to large scale fermentation cultures, and develop methods to allow simple and cost-effective purification of the vesicle packaged proteins. Finally, we will extend this recombinant vesicle packaging system to more complex types of cell to further extend the range of therapeutic proteins and downstream applications. Development of this technology will benefit both discovery science and commercial applications, as it will allow scientists to produce biomolecules such as diagnostic and therapeutic antibodies, exported by the cells in a stable environment for easier isolation and storage of proteins.

The ability to reprogram a cell to direct the packaging of specific molecules into discrete membrane envelopes is a major objective for synthetic biology. This controlled packaging into membrane vesicles will allow biologists to create a plethora of new technologies, which could be applied in both biotechnology and medical industries. These include the generation of novel metabolic factories within a cell for energy production; for rapidly packaging toxic proteins into contained environments before they have a chance to harm any normal metabolic activities, so they can be purified for use in subsequent pharmaceutical applications; the creation of protective packages filled with difficult to isolate biomolecules, which can be kept in stable environment to allow their storage and purification; and also generate simple vehicles for delivery of drugs and vaccines to the patient. Here, we provide a simple and cost effective solution to the problem. We have discovered a method to program a simple cell to create membrane packages which can be filled with different molecules of interest. We have not only discovered a way to fine-tune the shape of the membrane package (e.g. into long tubular matrices or spherical vesicles), but we have also devised controllable mechanisms that either keep the package within, or secrete the package out of the cell. Thus we have therefore made a landmark breakthrough in synthetic biology research. A major aim of this BBSRC key strategic area is to design from new and improve on natural systems and exploit these for the production of commercially important chemicals and biotherapeutics, which is what we have achieved here. Our overall aim in this project is to make use of these exciting discoveries to modify cells, making them capable of creating membrane bound packages filled with any protein of interest, which can then either be secreted from the cell and isolated from the culture media using a simple one step filtration technique, or stored within the cell where it can be made to act as a metabolic micro-factories, producing useful and/or valuable molecules without intoxicating the cells. In this way we hope to develop new ways to produce fine and platform chemicals as well as biotherapeutics. Through the research described in this application we are certain that we will be able to contribute to the development of new sustainable approaches for generating biotherapeutics, which will be assimilated into production techniques by diverse bio-industries.

Enzymes are proteins catalysing almost all reactions required for cellular life and, when defective, they can cause severe pathologies. For example, in humans, alpha-galactosidase (a-GAL) deficiency, a condition affecting up to 1 in 3000 newborn known as Fabry's disease (FD), causes life threatening damage to heart and kidneys. Since these diseases are usually caused by inherited genomic mutations, they cannot be cured, but they can be treated using Enzyme Replacement Therapies (ERTs), which consist of the injection of a recombinant version of the affected enzymes into patients. Unfortunately, ERTs have limitations; recombinant enzymes have lower enzymatic activity compared to the human wild-type versions, are unstable in blood, are poorly absorbed by human cells, and often trigger an immune response. Moreover, manufacturing therapeutic enzymes is extremely expensive because standard mammalian cell-based expression systems have low yield. Developing effective therapeutic enzymes requires design methods able to discover new amino acid sequences that can encode the same catalytic function, while optimising the therapeutic properties of the molecule. Then, these enzymes must be converted into highly optimised DNA triplets, called codons, to maximise expression and yield in host organisms that can grow in inexpensive media. With the increasing incidence of enzymatic deficiencies and current treatments costing up to £400K per year per patient, it is crucial to establish effective methods to perform these tasks and implement a platform for effective and sustainable production of therapeutic enzymes. Through the EPSRC fellowship, I will develop the computational and experimental methods required for engineering and manufacturing designer enzymes. I will use deep generative machine learning (ML) to design and codon optimise new enzymes, which will then be rapidly built and tested at scale using the lab automation platform available at the University of Edinburgh (UoE). As a proof of concept, I will build a library of designer human a-GAL enzymes using P. pastoris, a high-yield expression system used in the pharmaceutical industry. To deliver this ambitious project, I have set four objectives over the 4 years of my fellowship : 1. Developing deep generative learning models for enzyme design. 2. Developing deep generative learning models for codon optimisation. 3. Building a library of designer human a-GAL enzymes in P. pastoris. 4. Developing a computer aided design (CAD) software for enzyme engineering. Each objective addresses current limitations in enzyme engineering and manufacturing. ML avoids the need for accurate biophysical models by learning design rules directly from existing enzymes. Thus, by reverse engineering Nature's design principles, it will be possible to engineer functional designer enzymes at unprecedented scale. Coupling in-silico design with a robotic platform will allow building and testing thousands of different variants, thus minimising the time required for identifying a functional enzyme. Here I will test this new approach by engineering the human a-GAL enzyme, which is currently difficult to manufacture and optimise for therapeutic treatment; this effort will not only provide experimental evidence for the effectiveness of my platform but could also identify new potential treatments for FD. The project is supported by a strong network of experts in synthetic biology and machine learning, in the UK and the US, industrial biopharmaceutical and biotechnology partners, such as Fujifilm Diosynth Biotechnologies UK (FDBK) and the Industrial Biotechnology Innovation Centre (IBioIC), and unique research facilities available at UoE, such as the Edinburgh Genome Foundry. With this fellowship, I will lay the foundation for data-driven biological engineering and deliver enabling computational and experimental technologies to rapidly design, build and test new therapeutic molecules.