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532 results on '"Mario di Bernardo"'

236. Tunable genetic devices through simultaneous control of transcription and translation

Author

Grace A. Meaker, Thomas E. Gorochowski, Vittorio Bartoli, Mario di Bernardo, Bartoli, Vittorio, Meaker, Grace A., DI BERNARDO, Mario, and Gorochowski, Thomas E.

Subjects
0301 basic medicine, Transcription, Genetic, Computer science, Science, Distributed computing, 0206 medical engineering, General Physics and Astronomy, BrisSynBio, 02 engineering and technology, General Biochemistry, Genetics and Molecular Biology, Article, Synthetic biology, 03 medical and health sciences, 0302 clinical medicine, Transcription (biology), Gene Regulatory Networks, RNA, Catalytic, lcsh:Science, 030304 developmental biology, Electronic circuit, 0303 health sciences, Multidisciplinary, Bristol BioDesign Institute, NOR logic, General Chemistry, Gene regulation, 030104 developmental biology, Genetic circuit engineering, Gene Expression Regulation, Protein Biosynthesis, Inverter, RNA, lcsh:Q, Gene expression, 030217 neurology & neurosurgery, 020602 bioinformatics
Abstract

Synthetic genetic circuits allow us to modify the behavior of living cells. However, changes in environmental conditions and unforeseen interactions with the host cell can cause deviations from a desired function, resulting in the need for time-consuming reassembly to fix these issues. Here, we use a regulatory motif that controls transcription and translation to create genetic devices whose response functions can be dynamically tuned. This allows us, after construction, to shift the on and off states of a sensor by 4.5- and 28-fold, respectively, and modify genetic NOT and NOR logic gates to allow their transitions between states to be varied over a >6-fold range. In all cases, tuning leads to trade-offs in the fold-change and the ability to distinguish cellular states. This work lays the foundation for adaptive genetic circuits that can be tuned after their physical assembly to maintain functionality across diverse environments and design contexts., Synthetic genetic circuits are sensitive to their environment and host cell, requiring many rounds of physical reassembly to achieve a desired function. Here the authors use a multi-level regulatory motif to dynamically tune the function of genetic parts as a step towards robust adaptive circuits.

Published
2020
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237. Control-Based Continuation: A New Approach to Prototype Synthetic Gene Networks

Author

Irene De Cesare, Davide Salzano, Mario Di Bernardo, Ludovic Renson, Lucia Marucci, de Cesare, Irene, Salzano, Davide, di Bernardo, Mario, Renson, Ludovic, Marucci, Lucia, Royal Academy of Engineering, and Royal Academy Of Engineering

Subjects
EXPRESSION, Biochemistry & Molecular Biology, BACTERIAL, Biochemical Phenomena, control-based continuation, Biomedical Engineering, 0601 Biochemistry and Cell Biology, Biochemistry, Genetics and Molecular Biology (miscellaneous), Biochemical Research Methods, Quantitative Biology::Cell Behavior, 0903 Biomedical Engineering, parasitic diseases, Genes, Synthetic, SWITCH, Gene Regulatory Networks, Computer Science::Cryptography and Security, Science & Technology, 0304 Medicinal and Biomolecular Chemistry, Cell Cycle, General Medicine, Models, Theoretical, bifurcation, synthetic biology, toggle switch, Life Sciences & Biomedicine, bifurcations
Abstract

Control-Based Continuation (CBC) is a general and systematic method to carry out the bifurcation analysis of physical experiments. CBC does not rely on a mathematical model and thus overcomes the uncertainty introduced when identifying bifurcation curves indirectly through modelling and parameter estimation. We demonstrate, in silico, CBC applicability to biochemical processes by tracking the equilibrium curve of a toggle switch which includes additive process noise and exhibits bistability. We compare results obtained when CBC uses a model-free and model-based control strategy and show that both can track stable and unstable solutions, revealing bistability. We then demonstrate CBC in conditions more representative of a real experiment using an agent-based simulator describing cells growth and division, cell-to-cell variability, spatial distribution, and diffusion of chemicals. We further show how the identified curves can be used for parameter estimation and discuss how CBC can significantly accelerate the prototyping of synthetic gene regulatory networks.

Published
2022

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