Richard Hammond Head of Synthetic Biology Cambridge Consultants
SCREAM if You Want to Go Faster
Just before his death in 1988, Richard Feynman wrote on his blackboard in his Caltech office, “What I cannot create, I do not understand.” This statement has lived on in a way that perhaps not even professor Feynman could have predicted: as a founding tenet of the field of synthetic biology.
Synthetic biology is defined as, “the design and engineering of biologically based parts, novel devices and systems as well as the redesign of existing, natural biological systems”1, and this emerging technology is rapidly changing the way industry and academia are approaching problems within a wide range of applications—particularly medicine and drug development.
Bioengineers now have a number of tools available to “create” biological systems from the bottom-up, which the experimenters, to some degree, are able to predict and control. To some extent, but not sufficiently; the complexities of seemingly simple systems can be daunting and challenging to overcome, with negative implications for synthetic biology technologies and products actually reaching the market.
The main issues are related to the vastness and complexity of biological systems. In order to develop biologically based circuits analogous to classical electronic circuits, the bioengineer is dependent on reliable parts with defined functions that can be connected to form higher-order, predictable networks. However, biomolecular components are often incompatible and only work within a certain pathway or network, and the system may be so overwhelmingly complex that the interactions between the parts cannot be entirely understood.
The bioengineer may start at an ostensibly simple component level, but as new pathways and interactions are constructed, he or she will need tools for rapid and comprehensive characterization of the system as a whole. Much work has been done to develop individual biomolecular components; however it is clear that there is a keenly felt need in the field of synthetic biology to be able to create designable and fully predictable interaction networks2,3.
In much the same way as is done for electronic systems and subsystems, each biobased pathway must be suitable for prototyping, individual optimization and rigorous testing. The design-build-test cycle for synthetic biology is therefore contingent upon the development of accurate models and robust algorithms for the components, subsystems and the whole system. Such models embody the “understanding” leading to the “creating”, according to the Feynman principle, and will be the key to integration of biological circuitry. Intrinsic to those models will be large amounts of experimental data, and here is where a major pinch point appears: the need for SCREAM technologies: small, cheap, rapid, extensible, automated, multiplexed technologies to enable detailed specification and characterization of the biological system at any point during development.
An illustration of this challenge is the development of aptamers using synthetic biology approaches. Aptamers are typically oligonucleotide molecules generated via systematic evolution by exponential enrichment (SELEX) and selected for high binding specificity to a certain target. Their unique stability and toxicity profiles, along with superior ligand-binding modifiability, have suggested they have great potential for use in diagnostics and therapeutics, especially as novel drug delivery platforms or drugs against previously intractable targets4-6. Aptamers also lend themselves very well as tools and components in drug development and synthetic biology networks.
For example, a bioengineer may make use of so-called riboswitches; RNA aptamers that are engineered to couple binding to a certain ligand with a conformation change that determines the output—such as expression of a gene or activation of a pathway— of a designed system. However, the SELEX method for screening a large (1014-1015) oligonucleotide library can be very laborious and fail to select an appropriate aptamer7. Therefore, technologies to extend the search space and making the process SCREAM, are in great demand in synthetic biology and drug development.
An example of a large-scale high-throughput experimental platform that will allow highly multiplexed screening of aptamer binding parameters (“binding screening”) is the use of high-resolution interferometry. Such platforms are designed to study, rapidly and cheaply, surface-based interactions between biological molecules without the need to use elaborate labelling approaches. An interferometric, label-free approach allows a large number of binding experiments to be arranged in arrays and interrogated simultaneously; this provides deep multiplexing and highly-parallel operation to allow for large amounts of data to be collected in short time-frames.
The incorporation of microfluidics to control the introduction of exogenous biochemical signals onto the arrays lends an additional dimension, allowing the combination of parts into small functional units, then into subsystems, interconnecting pathways and systems of increasing complexity. Platforms such as this, with appropriate sensitivity, flexibility and ease-of-use, open up opportunities for large coverage of interaction space in order to select the best aptamer.
The impact on aptamer development, and more generally synthetic biology, by the use of highly multiplex platforms may be significant, particularly in addressing problems regarding variable components, condition control and incompatibility. Multiplexed experimentation has the potential to open the door to massively parallel testing of biomolecular components for a multitude of parameters including binding kinetics and input/output robustness, allowing selection of appropriate parts for integrating into a designed system.
To return to the example of riboswitch aptamers, massive parallelization of interaction studies has the potential to generate detailed data on environmental parameters allowing precise sensing/response control; in addition, the array configuration of parts coupled with microfluidics may enable higher order network design by sequestering parts while providing absolute signal control.
Another considerable impact of the above technology on synthetic biology is that the high-fidelity, data-rich experiments will facilitate the construction of adaptive and predictive in silico network models.The use of large amounts of reproducible and experimental data will be crucial to quicken the pace of development of synthetic biology as a true engineering discipline.
The use of synthetic biology technologies in industrial applications is currently largely focused on innovation in medical devices (diagnostics and therapeutics) and energy production and storage (biofuels), but the potential to expand bioengineering across a wider range of scientific disciplines, such as computing, smart materials and sensors, is under intense research.
The availability of suitable SCREAM technologies will be central for making synthetic biology real and for bringing synthetic biology products, such as novel drugs, to the market. Undoubtedly, as massively multiplex experimentation and development of predictive models continue to inform and shape our understanding of synthetic biological systems, the creating will ultimately be limited only by the bioengineer’s creativity. Indeed, to paraphrase Professor Feynman: “the more we understand, the more we will be able to create.”
Richard Hammond (Richard.firstname.lastname@example.org) is the head of synthetic biology at Cambridge Consultants.
1 Technology Strategy Board (2012), A Synthetic Biology Roadmap for the UK
2 Bölker, M. (2014), Complexity in Synthetic Biology: Unnecessary or Essential? Synthetic Biology (Springer International Publishing) 59-69 (doi: 10.1007/978-3-319-02783-8_3)
3 Kwok, R. (2010) Five hard truths for synthetic biology Nature 463 288-290 (doi:10.1038/463288a)
4 Wu, X. et al (2015) Aptamers: active targeting ligands for cancer diagnosis and therapy. Theranostics 5(4): 322-344 (doi: 10.7150/thno.10257)
5 Ashrafuzzaman, M. (2014) Aptamers as both drugs and drug-carriers Biomed Res Int 2014:697923 (doi: 10.1155/2014/697923)
6 Kanwar, J.R. (2015) Nucleic-based aptamers: applications, development and clinical trials Curr Med Chem 22(21):2539-57 (doi: 10.2174/0929867322666150227144909#sthash.baWQFk1g.dpuf)
7 Jiang, F. (2015) Progress and Challenges in Developing Aptamer-Functionalized Targeted Drug Delivery Systems Int J Mol Sci 16(10) 23784-23822 (doi:10.3390/ijms161023784)