Synthetic Biology: A Primer by Baldwin Geoff & Kitney Richard I & Travis Bayer & Freemont Paul S & Tom Ellis & Karen Polizzi & Guy-Bary Stan

Author:Baldwin, Geoff & Kitney Richard I & Travis Bayer & Freemont Paul S & Tom Ellis & Karen Polizzi & Guy-Bary Stan [Baldwin, Geoff]
Language: eng
Format: epub
Publisher: World Scientific Publishing
Published: 2012-06-08T00:00:00+00:00

Fig. 6.1 The engineering design cycle — design starts in silico and proceeds iteratively along the cycle. The use of Computer Aided Design tools can allow for the in silico modelling, analysis and optimisation of the design prior to the actual wet laboratory implementation of the system. (Inspired by Chandran et al., 2008.)

The in silico candidate designs are then ‘translated/compiled’ into DNA sequences which are then implemented in vitro or in vivo. The implementation is tested and characterised to yield biological data that are then compared with the initial design objectives, thereby allowing assessment of the quality of the design and, if necessary, improvements by iterating once or several times around the design cycle. The use of Computer-Aided Design (CAD) tools can make iterations between these different steps easier and more efficient. Furthermore, CAD tools can be supplemented by Graphical User Interfaces (GUIs), which enable the construction of devices and systems by graphically interconnecting components on a canvas and automatically building the corresponding models in the background. Ultimately, computational tools could also be used to predict the DNA sequence that is required for the in vivo or in vitro implementation of the designed model into a particular host cell or even to control and automate the DNA assembly or de novo synthesis process using liquid-handling robots.

The engineering design cycle shown in Fig. 6.1 enables the efficient design of synthetic biology systems of increasing complexity using a forward-engineering approach very similar to the one successfully used in many other engineering disciplines. In particular, this approach enables the adoption of another important engineering principle: abstraction (see Chapter 3). Abstraction allows the construction of complex systems without the need for a detailed understanding of the processes involved at each stage along the design cycle. In other words, using abstraction each step along the cycle can be realised by different experts who do not need to know the details of the implementation of the other steps. The only knowledge required is that of the interface between the steps, what each step receives from the others and what it provides to the others. In particular, using abstraction system design and system fabrication can be separated (Fig. 6.2).

The advantage of such a separation is that it saves time, money and effort since the main burden of the design is realised more efficiently in silico than in vivo or in vitro.

6.4 Types of Mathematical Models and their Role

In the following sections we briefly introduce various types of mathematical models that are typically used in synthetic and systems biology to capture the essential dynamics of biochemical processes.

6.4.1 Choosing the level of mathematical abstraction/resolution of the model

As in other disciplines, synthetic biology systems can be modelled in a variety of ways and at many different levels of resolution and time scales (Fig. 6.3).

Download

Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.