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Details of Grant 

EPSRC Reference: EP/R019002/1
Title: SynBio3D: Establishing the engineering fundamentals of three-dimensional synthetic biology
Principal Investigator: Goni-Moreno, Dr A
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Sch of Computer Science
Organisation: Newcastle University
Scheme: First Grant - Revised 2009
Starts: 01 January 2018 Ends: 31 December 2019 Value (£): 101,057
EPSRC Research Topic Classifications:
Synthetic biology
EPSRC Industrial Sector Classifications:
Pharmaceuticals and Biotechnology
Related Grants:
Panel History:
Panel DatePanel NameOutcome
04 Oct 2017 Engineering Prioritisation Panel Meeting 4 October 2017 Announced
Summary on Grant Application Form
Synthetic biology applies rational engineering principles to the design and build of novel biomolecular devices. This allows us to use synthetic genetic 'circuits' to program microbes to behave as living processing units. A fundamental aim is to obtain useful (human-defined) behaviour in living systems. This approach builds on the predictive power of mathematical modelling and the current understanding of molecular biology to engineer organisms that will ultimately be of major value to society. Applications of these programmed microbes include biotechnological processes, from the production of biofuels to pharmaceuticals, bioremediation strategies, agriculture and bio-diagnostics.

However, there is currently one issue which threatens to undermine the success of synthetic biology going forwards: the complete disregard for spatial dimensions. This is in contrast to many other engineering disciplines, where the design of a complex system such an airplane must specify accurate physical locations for its circuit's components. To date, synthetic biology has no spatial resolution apart from the notions of inside and outside the cell. Novel biological genetic circuits are introduced inside cells with no notable attention to their whereabouts.

A major problem with this is that a cell is abstracted as a black box, thus viewed in terms of inputs/outputs alone without considering its internal workings. The exclusion of such information causes important problems when the organisms come to be used/tested. It is commonly required to re-engineer and retest the circuit with different genetic parts to fine-tune its function. That "refactoring" process is not only time consuming and costly but also unnecessary in many cases - if spatial dimensions were considered at the design stage. For example, our initial investigations have recently shown that the physical distance between the components of a given genetic circuit can change its functioning considerably. Therefore, the awareness of geometrical effects will assist the design of robust and predictable circuits. Each gene sequence and each protein may need a specific physical address in the spatial frame of a cell for optimal performance, a question that urgently needs further attention to enable synthetic biology to fulfil its potential. In this first grant, we will measure the impact of space in synthetic constructs and use it to establish the fundamentals of a new concept that we refer to as 'three-dimensional synthetic biology'.

SynBio3D will upgrade the synthetic biology lifecycle by adding spatial information, a goal unattained by any other research group to date. The project will address two major barriers to achieve success. Firstly, mathematical models, which are at the heart of genetic circuit development, are overwhelmingly based on time as the only reference. This restricts the way we represent biomolecular interactions to time-based kinetics, which assume an unrealistic zero-dimensional scenario. In response to this first problem we will develop novel computational methods to allow us to simulate genetic circuits using spatial constraints such as distances and molecular crowding. The second problem concerns the direct visualization in vivo of gene locations and single-molecule displacements. We will use super-resolution microscopy to obtain three-dimensional, real-time measurements of bespoke genetic circuits. Together, the resulting information will formally correlate, for the first time, a genetic circuit's dynamics in time with its geometrical features in space. This will allow to formalize spatial engineering fundamentals.

This three-dimensional approach to synthetic biology will lead the way in turning molecular networks into programmable systems; a goal revealed to be elusive with traditional time-based approaches. Furthermore, it will impact research lines in apparently distant fields ranging from biophysics to computer science.

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