Synthetic Biology aims at re-engineering cells with DNA circuits that carry out specific functions. Circuits are made of Parts, i.e. DNA segments that have a well-defined function either in transcription or translations. Examples of Parts are promoters, bacterial RBSs (Ribosome Binding Site), coding regions for proteins or small RNAs, and terminators. Synthetic gene circuits are designed on the computer. As in electronics, one chooses, first, all the necessary components, then display them on the computer screen and, finally, wire them together. Biological wires are supposed to host fluxes of moleculessuch as RNA polymerases, ribosomes, and transcription factors that establish communication among circuit components.
Once designed, synthetic gene circuits are associated with mathematical models. They permit circuit analysis and simulations. Computational results drive the wet-lab implementation of circuits into living cells or in vitro.
The first synthetic gene circuits were implemented in E. coli. They consisted of very few genes and behaved like oscillators, pulse generators, and toggle switches. Later on, yeast and mammalian cells became popular chassis too and circuit complexity increased moving from the initial gene networks to signaling pathwayre-engineering and cell consortia.
Research in Synthetic Biology facesseveral challenges: Parts’ standardization, construction of predictive mathematical models, development of user-friendly software for circuit design, and automation of DNA assembly in wet-lab experiments. Solutions to these issues will lead in the future to build, in a systematic way,synthetic gene circuits that will find applications in many, different, important fieldssuch as environmental care (detection and degradation of pollutants), medical diagnostics, cure of diseases, and biofuel production.
Lab description
Our research proceeds on two main parallel tracks:
In particular, we are interested in the automatic in silico design and in vivo construction of biosensors. This kind of circuits produces an output (e.g., fluorescence) in response to the presence of chemicals in the environment. A simple biosensor is a cell that contains a synthetic AND gate. It accepts two inputs and returns a fluorescent signal only when both inputs are present (in high quantity) in the cellular environment.
On the computational side, we are developing a piece of software called “Parts & Pool” [1-2] for the modular design of both prokaryotic and eukaryotic circuits. Modules are Standard Biological Parts (DNA sequences such as promoters, coding regions, and terminators) and Pools of signal carrier molecules (RNA polymerases, ribosomes, transcription factors, small RNAs, and chemicals). “Parts & Pools” is, at present, a collection of scripts written in Perl and Python. Each script generates a biochemical model for a different Part or Pool. Scripts for complex Parts, which contain a high number of species and interactions, call an external piece of software, BioNetGen [3], that carries out species and reaction calculation via a rule-based modeling technique. Once generated by our scripts, files for Parts/Pools are loaded into another external piece of software, ProMoT [4], whose graphical user interface is a canvas for the visual, “drag & drop” design of synthetic gene circuits.“Parts & Pools” has been adapted to the automatic design of digital gene circuits [5]. They represent the biosensors we want to build in our wet lab.
In the wet lab, we are working on a library of regulated promoters and mRNAs. They mimic basic logic functions such as AND, NOT, N-IMPLY and are the basic components for the biosensors generated by our software. DNA transcription units are assembled into pRS shuttle vectors [6] via the Gibson method [7]. Plasmids are stored into E coli cells and transformed into yeast cells (simple transformation or genomic integration). Circuit read-out is fluorescence that is quantified via FACS experiments.
References
[1] Marchisio, M. A. and Stelling, J., Bioinformatics, 2008, 24, 1903-1910
[2] Marchisio, M. A. et al., BMC systems biology, 2013, 7, 42
[3] Blinov, M. L. et al.,Bioinformatics, 2004, 20, 3289-3291
[4] Mirschel, S. et al., Bioinformatics, 2009, 25, 687-689
[5] Marchisio, M. A. &Stelling, J., PLoS computational biology, 2011, 7, e1001083
[6] Sikorski, R. S. &Hieter, P., Genetics, 1989, 122, 19-27
[7] Gibson, D. G. et al., Nature Methods, 2009, 6, 343-345
Recent publications
1.Marchisio M.A., Parts & Pools: a framework for modular design of synthetic gene circuits, Frontiers Bioeng Biotech, 2014, 42, doi: 10.3389/fbioe.2014.00042
2.Marchisio, M. A., Insilico design and in vivo implementation of yeast gene Boolean gates. J BiolEng, 2014, 8, 6