Computational Systems Biology

Synthetic Biology

Genetic Oscillators

Fig. 1: Periods of stochastic simulations according to parameter variation

One of the central topics in molecular biology consists of understanding the mechanisms involved in biological rhythms and whether it is possible to influence the underlying genetic clockwork to tune the expression of key genes. Answering this question may prove to be central in the design of future gene therapies, particularly those requiring a periodic input.

For such purpose, we have investigated design principles for synthetic regulatory networks that provide tunable oscillating gene expression. Similar to natural circadian oscillators, the basic design contains positive and negative feedback loops.

Fig. 2: Amplitudes of stochastic simulations according to parameter variation

Genetic oscillators, albeit robust, generally portray notoriously high noise and take place in lengthy time spans, the reason why we have opted for a coarse-grained stochastic framework for the in silico analysis of our proposed systems. Our stochastic simulations are in agreement with experimental data in the literature and show that variability in oscillator behavior is largely caused by stochastic fluctuations, despite high numbers of the molecules involved. They also provide us with sufficient conditions for tuning targeted gene expression.

Computational Design of Synthetic Circuits

Genetic circuits can be engineered by means of Standard Biological Parts. They represent either simple pieces of DNA with a well-defined function (basic parts like promoters and terminators) or complex devices perfoming particular tasks (e. g. reporter generators and inverters).

Taking inspiration from electrical engineering, where circuits are realized by connecting simple components (e. g. resistors, solenoids and batteries) by means of wires through which electrons flow, we realized a "drag and drop" tool to design biological circuits by means of composable parts i. e. parts which exchange common signal carriers.

Fig. 3: The Repressilator (Elowitz and Leibler, Nature 403, 335-338; 2000) implemented with ProMoT

As in electronics electrons mediate the exchange of information among circuit components, molecules like RNA polymerases, ribosomes, transcription factors, for instance, can be supposed to play the same role in biology.

Genetic circuits can then be designed by placing biological parts on a canvas and by making them communicate through wires where different molecules flow carring the necessary information to regulate transcriptional and translational mechanisms.

We developed a mathematical model (based on ordinary differential equations) for each of the Basic Parts depicted in the MIT Registry of Standard Biological Parts. Details can be found into "A guide to composable parts and pools".

The canvas for biological circuit design has been provided by ProMoT. Instructions for circuit design are contained into "How to design synthetic gene circuits with composable parts and pools in the ProMoT framework".

The final code associated with a circuit can be exported into Matlab or SBML format (Level-1 and Level-2) allowing to run both deterministic and stochastic simulations.

Results on largely-studied circuits fairly agree both with computational and experimental data in literature.

Fig. 4: Stochastic simulation results for the Repressilator


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