Synthetic Biology in Mammals
Synthetic biology aims at building novel biological ‘circuits’ (synthetic network) in the cell able to perform specific tasks, or to control the behaviour of the biological process in a desired way. It can also be used to build simplified models of complex biological pathways in order to better understand the way they work.
We have currently two ongoing projects: (1) Automatic control of gene expression in a cell population; (2) Entrainment and Synchronisation of biological clocks in signaling.
- (1) In this project, we are using computer-controlled microfluidics devices to achieve an automatic control strategy to regulate the dynamics of gene expression across a population of yeast cells in real-time. We implemented a control strategy by making use of a microfluidics device for cell growth and for delivery of galactose/glucose with desired dynamics though computer- controlled syringes. The closed-loop control is achieved via time-lapse fluorescence microscopy, which is used to monitor reporter gene expression and feed it to the control algorithm, which in turn moves the syringes to control the amount of inducer molecule delivered to the cells.
- (2) In this project we are investigating biological clocks via Systems and Synthetic Biology approaches. Cyclic expression of genes (i.e. oscillation) is essential for multicellular life and it is involved in basic processes such as the cell-cycle and the circadian clock. Ultradian oscillations, i.e. with periods much shorter than 24 hours, have been observed also in the major signalling pathways, but their relevance is still unclear. Emphasis on the molecular biology of these "clock" mechanisms in individual cells has detracted the attention from the "biological synchronisation" among individual clocks across the cell population and its physiological significance. In this project we will investigate the collective behaviour of both synthetic and natural biological clocks, in terms of rhythmic, periodic gene expression via an integrated experimental and computational approach.