Synthetic biology has always strived to prove that classical engineering principles are applicable in the field of science; however, several key challenges have yet to be overcome.
These include designing robust genetic circuits, predictive expression of proteins, and a standardization of how we, as synthetic biologists, characterize our parts to be continually utilized in ever changing systems. The Taguchi Method is a statistical way to analyze a set of parameters, for example which promoter to use with a gene of interest, and determines a set of experiments to determine which combination of the parameters gives the most robust system to outside noise such as E. coli strain. Optimization of protein expression is done by introducing multiple Shine-Dalgarno sequences into cistrons containing the gene of interest. Finally, collaboration among teams allowed for a new standardized form of submitting characterization of parts to the Parts Registry. These, when combined, help move the field of synthetic biology one step closer to being able to successfully prove that biology can, in fact, be engineered.
Synthetic biology is a rapidly growing field of science that promises to revolutionize almost every part of our technology. However, one of the biggest drawbacks of synthetic biology compared to other fields is the lack of standardization. Some of this can be attributed to the nature of the field itself; biological systems are much harder to control than electrical or mechanical ones.
A good portion of the problem though, comes from how the genetic parts are characterized and presented. The iGEM competition has sought for many years to create a “Registry of Standardized Parts” so that iGEM teams and other researchers can submit and use genetic parts that have been proven to work and function. While creating and characterizing new parts and devices to be added to the registry are important, if the information needed to use that part is not communicated efficiently, the parts themselves are useless. This year, the Purdue iGEM team set out to solve this problem by creating a definitive characterization standard for the registry. By talking and collaborating with over fifty other iGEM teams around the world, we have developed a way to standardize how characterization data is submitted and presented in the registry.
This system encompasses an easy, template-based system to enter data of a part into the iGEM Registry. Once implemented, our solution will revolutionize the Registry of Standardized Parts and add some much-needed standardization to the field of synthetic biology.
Robustness of Genetic Circuits
In nature, organisms’ genes are robust to the point that the organism persistently reproduces under different external and internal conditions. Synthetic robustness within the field of synthetic biology is a hurdle yet to be crossed. Taguchi Method is introduced to reduce variation in gene circuits through robust design of experiment. Three promoters combined with three ribosomal binding sites and three terminators are combined in a series of 27 different circuits each consisting of a promoter followed by an RBS followed by GFP and finished with a terminator.
Taguchi Method uses orthogonal arrays to organize the parameters and tests for pairs of combinations of factors to gather data with minimum experiments in order to reduce cost and time. The particular gene of interest is GFP, thus, expression level of fluorescence is used as criteria to predict the most robust combination with least variance.
Despite having progressed extensively in the field of synthetic biology in terms of DNA synthesis, analysis and transplanting, we still cannot reliably, quantitatively measure expression of new genetic constructs. We engineered an expression cassette to control transcription and translation initiation which can be reused in new genetic contexts. The Bicistronic design(BCD) consists of two Shine-Dalgarno sequences in its translation element which when combined with indiscriminate gene of interests are known to reliably express within twofold of the relative target expression window.