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Marucci, L.

Publications and source records attributed to Marucci, L..

2 recordsLinked to original sources

A tunable dual-input system for on-demand dynamic geneexpression regulation.

Cellular systems have evolved numerous mechanisms to finely control signalling pathway activation and properly respond to changing environmental stimuli. This is underpinned by dynamic spatiotemporal patterns of gene expression. Indeed, in addition to gene transcription and translation regulation, modulation of protein levels, dynamics and localization are also essential checkpoints that govern cell functions. The introduction of tetracycline-inducible promoters has allowed gene expression control using orthogonal small molecules, facilitating rapid and reversible manipulation to study gene function in biological systems. However, differing protein stabilities means this solely transcriptional regulation is insufficient to allow precise ON-OFF dynamics, thus hindering generation of temporal profiles of protein levels seen in vivo. We developed an improved Tet-On based system augmented with conditional destabilising elements at the post-translational level that permits simultaneous control of gene expression and protein stability. Integrating these properties to control expression of a fluorescent protein in mouse Embryonic Stem Cells (mESCs), we found that adding protein stability control allows faster response times to changes in small molecules, fully tunable and enhanced dynamic range, and vastly improved microfluidic-based in-silico feedback control of gene expression. Finally, we highlight the effectiveness of our dual-input system to finely modulate levels of signalling pathway components in stem cells.

synthetic biology

Designing Genomes using Design-Simulate-Test Cycles

In the future, entire genomes tailored to specific functions and environments could be designed using computational tools. However, computational tools for genome design are currently scarce. Here we present algorithms that enable the use of design-simulate-test cycles for genome design, using genome minimisation as a proof-of-concept. Minimal genomes are ideal for this purpose as they have a very simple functional assay, the cell can either replicate or not. We used the first (and currently only published) whole-cell model, for the bacterium Mycoplasma genitalium 1. Our computational design-simulate-test cycles discovered novel in-silico minimal genomes smaller than JCVI-Syn3.0 2, a bacterial cell with the currently known smallest genome that can be grown in pure culture. In the process, we identified 10 low essentiality genes, 18 high essentiality genes 3, and produced evidence for at least two minimal genomes for Mycoplasma genitalium in-silico. This work brings combined computational and laboratory genome design and construction a step closer.

synthetic biology