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Chew YH, Marucci L. Mechanistic Model-Driven Biodesign in Mammalian Synthetic Biology. Methods Mol Biol 2024; 2774:71-84. [PMID: 38441759 DOI: 10.1007/978-1-0716-3718-0_6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2024]
Abstract
Mathematical modeling plays a vital role in mammalian synthetic biology by providing a framework to design and optimize design circuits and engineered bioprocesses, predict their behavior, and guide experimental design. Here, we review recent models used in the literature, considering mathematical frameworks at the molecular, cellular, and system levels. We report key challenges in the field and discuss opportunities for genome-scale models, machine learning, and cybergenetics to expand the capabilities of model-driven mammalian cell biodesign.
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Affiliation(s)
- Yin Hoon Chew
- School of Mathematics, University of Birmingham, Birmingham, UK
| | - Lucia Marucci
- Department of Engineering Mathematics, University of Bristol, Bristol, UK.
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK.
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de Cesare I, Salzano D, di Bernardo M, Renson L, Marucci L. Control-Based Continuation: A New Approach to Prototype Synthetic Gene Networks. ACS Synth Biol 2022; 11:2300-2313. [PMID: 35729740 PMCID: PMC9295158 DOI: 10.1021/acssynbio.1c00632] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
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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
modeling 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 the 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 an in
vivo experiment using an agent-based simulator describing
cell 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.
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Affiliation(s)
- Irene de Cesare
- Engineering Mathematics Department, University of Bristol, Bristol BS8 1TW, U.K.,Department of Electrical Engineering and Information Technologies, University of Naples Federico II, 80125 Naples, Italy
| | - Davide Salzano
- Engineering Mathematics Department, University of Bristol, Bristol BS8 1TW, U.K.,Department of Electrical Engineering and Information Technologies, University of Naples Federico II, 80125 Naples, Italy
| | - Mario di Bernardo
- Department of Electrical Engineering and Information Technologies, University of Naples Federico II, 80125 Naples, Italy
| | - Ludovic Renson
- Department of Mechanical Engineering, Imperial College London, London SW7 2BX, U.K
| | - Lucia Marucci
- Engineering Mathematics Department, University of Bristol, Bristol BS8 1TW, U.K.,BrisSynBio, University of Bristol, Bristol BS8 1TQ, U.K.,School of Cellular and Molecular Medicine, University of Bristol, Bristol BS8 1UB, U.K
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Pedone E, de Cesare I, Zamora-Chimal CG, Haener D, Postiglione L, La Regina A, Shannon B, Savery NJ, Grierson CS, di Bernardo M, Gorochowski TE, Marucci L. Cheetah: A Computational Toolkit for Cybergenetic Control. ACS Synth Biol 2021; 10:979-989. [PMID: 33904719 DOI: 10.1021/acssynbio.0c00463] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Advances in microscopy, microfluidics, and optogenetics enable single-cell monitoring and environmental regulation and offer the means to control cellular phenotypes. The development of such systems is challenging and often results in bespoke setups that hinder reproducibility. To address this, we introduce Cheetah, a flexible computational toolkit that simplifies the integration of real-time microscopy analysis with algorithms for cellular control. Central to the platform is an image segmentation system based on the versatile U-Net convolutional neural network. This is supplemented with functionality to robustly count, characterize, and control cells over time. We demonstrate Cheetah's core capabilities by analyzing long-term bacterial and mammalian cell growth and by dynamically controlling protein expression in mammalian cells. In all cases, Cheetah's segmentation accuracy exceeds that of a commonly used thresholding-based method, allowing for more accurate control signals to be generated. Availability of this easy-to-use platform will make control engineering techniques more accessible and offer new ways to probe and manipulate living cells.
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Affiliation(s)
- Elisa Pedone
- Department of Engineering Mathematics, University of Bristol, Ada Lovelace Building, University Walk, BS8 1TW Bristol, United Kingdom
- School of Cellular and Molecular Medicine, University of Bristol, Biomedical Sciences Building, University Walk, BS8 1TD Bristol, United Kingdom
| | - Irene de Cesare
- Department of Engineering Mathematics, University of Bristol, Ada Lovelace Building, University Walk, BS8 1TW Bristol, United Kingdom
| | - Criseida G. Zamora-Chimal
- Department of Engineering Mathematics, University of Bristol, Ada Lovelace Building, University Walk, BS8 1TW Bristol, United Kingdom
- BrisSynBio, Life Sciences Building, Tyndall Avenue, BS8 1TQ Bristol, United Kingdom
| | - David Haener
- Department of Engineering Mathematics, University of Bristol, Ada Lovelace Building, University Walk, BS8 1TW Bristol, United Kingdom
| | - Lorena Postiglione
- Department of Engineering Mathematics, University of Bristol, Ada Lovelace Building, University Walk, BS8 1TW Bristol, United Kingdom
| | - Antonella La Regina
- Department of Engineering Mathematics, University of Bristol, Ada Lovelace Building, University Walk, BS8 1TW Bristol, United Kingdom
- School of Cellular and Molecular Medicine, University of Bristol, Biomedical Sciences Building, University Walk, BS8 1TD Bristol, United Kingdom
| | - Barbara Shannon
- BrisSynBio, Life Sciences Building, Tyndall Avenue, BS8 1TQ Bristol, United Kingdom
- School of Biochemistry, University of Bristol, Biomedical Sciences Building, University Walk, BS8 1TD Bristol, United Kingdom
| | - Nigel J. Savery
- BrisSynBio, Life Sciences Building, Tyndall Avenue, BS8 1TQ Bristol, United Kingdom
- School of Biochemistry, University of Bristol, Biomedical Sciences Building, University Walk, BS8 1TD Bristol, United Kingdom
| | - Claire S. Grierson
- BrisSynBio, Life Sciences Building, Tyndall Avenue, BS8 1TQ Bristol, United Kingdom
- School of Biological Sciences, University of Bristol, Tyndall Avenue, BS8 1TQ Bristol, United Kingdom
| | - Mario di Bernardo
- Department of Engineering Mathematics, University of Bristol, Ada Lovelace Building, University Walk, BS8 1TW Bristol, United Kingdom
- BrisSynBio, Life Sciences Building, Tyndall Avenue, BS8 1TQ Bristol, United Kingdom
- Department of EE and ICT, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy
| | - Thomas E. Gorochowski
- BrisSynBio, Life Sciences Building, Tyndall Avenue, BS8 1TQ Bristol, United Kingdom
- School of Biological Sciences, University of Bristol, Tyndall Avenue, BS8 1TQ Bristol, United Kingdom
| | - Lucia Marucci
- Department of Engineering Mathematics, University of Bristol, Ada Lovelace Building, University Walk, BS8 1TW Bristol, United Kingdom
- School of Cellular and Molecular Medicine, University of Bristol, Biomedical Sciences Building, University Walk, BS8 1TD Bristol, United Kingdom
- BrisSynBio, Life Sciences Building, Tyndall Avenue, BS8 1TQ Bristol, United Kingdom
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