From single cells to microbial consortia: bridging the gaps between synthetic circuit design and emerging dynamics of heterogeneous populations
The project aims to develop mathematical methods to control synthetic gene circuits in microbial populations, enhancing functionality and bioproduction of challenging proteins through population dynamics.
Projectdetails
Introduction
A key turning point in the evolution of life was the transition from single-cell to multicellular organisms and the optimization of fitness via division of labour and specialization. Similarly, microorganisms have evolved equivalent strategies by forming communities or consortia.
Division of Labour in Microbial Populations
Division of labour in isogenic microbial populations is often implemented by mechanisms that create or act upon population heterogeneity to diversify functionality. Rational design in synthetic biology, on the other hand, is focused on the engineering of gene circuits with deterministically predictable functionality within single cells.
Challenges in Synthetic Biology
While synthetic biology has certainly come a long way, predictable functionality of circuits in growing microbial populations still remains elusive or limited to tightly constrained operating conditions.
Development of Novel Mathematical Methods
We will develop novel mathematical methods to characterize and control the dynamics of synthetic gene circuits within growing microbial populations.
Modelling Framework
We will develop a modelling framework and novel computational methods that take both stochasticity of single-cell processes and consequences of heterogeneity for population dynamics into account.
Mathematical Coupling
On the mathematical side, this necessitates coupling single-cell stochastic processes to state-dependent population processes such as growth or selection.
Methods for Parameter Inference and Control
We will develop methods for parameter inference, experimental design, and control for such models. This will enable the construction of models that can be used to design synthetic circuits that function as specified within growing populations and that can be deployed to regulate single-cell processes such that desirable dynamics emerge at the scale of populations and consortia.
Application in Bioproduction
We will apply the methodology for bioproduction problems in which proteins that are hard to fold need to be produced. Overproducing such proteins impairs cellular growth, which creates couplings between single-cell and population processes and raises the need to feedback control production.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 1.497.790 |
Totale projectbegroting | € 1.497.790 |
Tijdlijn
Startdatum | 1-5-2023 |
Einddatum | 30-4-2028 |
Subsidiejaar | 2023 |
Partners & Locaties
Projectpartners
- INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET AUTOMATIQUEpenvoerder
Land(en)
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Engineering, Analysis and Control of Biomolecular Circuits Under Uncertainty
CellWise aims to enhance predictability in Synthetic Biology by developing mathematical tools for engineering complex biomolecular circuits, focusing on cell cognition and decision-making under uncertainty.
Mapping vast functional landscapes with single-species resolution: a new approach for precision engineering of microbial consortia
ECOPROSPECTOR aims to optimize microbial community composition for enhanced starch hydrolysis using machine learning and evolutionary theories, bridging ecology and biotechnology.
Unravelling the chemical-physical principles of life through minimal synthetic cellularity
The project aims to construct synthetic cells with life-like properties by exploring compartmentalization and communication in molecular reaction networks to understand life's fundamental principles.
Biophysical Models of Bacterial Growth
The project aims to develop integrated biophysical models to understand and predict how microorganisms regulate self-replication and respond to environmental fluctuations.
Metabolism-driven division of minimal cell-like systems
MetaDivide aims to synthesize minimal cells by integrating metabolic networks and division mechanisms, enhancing understanding of cellular life and informing antibacterial strategies.