ConBioChem: Continuous bio-production of commodity chemicals
Lead Research Organisation:
University of Cambridge
Department Name: Biochemistry
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Technical Summary
This ambitious, multidisciplinary project will establish generic design procedures to underpin the introduction of continuous bio-manufacturing processes for commodity/platform chemicals and added value intermediates. Crucial improvements in operational stability will be delivered through Synthetic Biology, to construct genetically stable chassis strains. Metabolic modelling will be used to design rational strain engineering and processing strategies, to divert cellular metabolism away from growth and towards product formation, to deliver critical improvements in product yields. The metabolic models will be integrated into multiscale models, involving reactor and process models and LCA, to enable seamless, integrated design of both the organisms and the processes, so that both will operate synergistically for maximal commercial benefit and sustainability. Success will be measured through technoeconomic analysis to deliver commercially relevant design approaches.
Planned Impact
As described in proposal submitted to IUK
Publications
Auffray C
(2019)
Ten years of Genome Medicine.
in Genome medicine
Julvez J
(2020)
Steady State Analysis of Flexible Nets
Julvez J
(2020)
Steady State Analysis of Flexible Nets
in IEEE Transactions on Automatic Control
Júlvez J
(2020)
A unifying modelling formalism for the integration of stoichiometric and kinetic models
in Journal of The Royal Society Interface
Júlvez J
(2019)
Flexible Nets: a modeling formalism for dynamic systems with uncertain parameters
in Discrete Event Dynamic Systems
Júlvez J
(2018)
Handling variability and incompleteness of biological data by flexible nets: a case study for Wilson disease.
in NPJ systems biology and applications
Júlvez J
(2019)
Modeling, analyzing and controlling hybrid systems by Guarded Flexible Nets
in Nonlinear Analysis: Hybrid Systems
Description | We have developed a computer modelling system (Flexible Nets) that allows us to represent both the metabolism of a microbe or mammalian cell together with relevant characteristics of the fermentation system in which the cells/microbes are grown. This allows us to determine the optimum conditions for the production of an industrial product by the microbe. Optimisation for different kinds of productivity may be carried out, e.g. amount of product produced by a given volume of fermenter per hour; amount of product produced per amount of biomass per hour; amount of product produced per mass of carbon source per hour. The optimised parameters can be exploited by genetic engineers in organism design or by chemical engineers in process design. |
Exploitation Route | The outcomes, in terms of both the tools and controllers developed, may be used by our industrial collaborators to design, optimise, and control biotechnological processes for chemicals production. They may also be exploited by producers ob biologics (e.g. antibodies) and we have been in close contact with such manufacturers to promote this. |
Sectors | Chemicals Healthcare Manufacturing including Industrial Biotechology Pharmaceuticals and Medical Biotechnology |
Description | In addition to the exploitation in the biotechological production of chemicals (see below). our Flexible Nets system may be used to control industrial biotechnological processes to achieve optimal production, indicating remedial action to be taken, in real time, when malfunctions occur. |
First Year Of Impact | 2019 |
Sector | Chemicals,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology |
Impact Types | Economic |
Description | Continous biprocesses for chemicals production |
Geographic Reach | National |
Policy Influence Type | Participation in a guidance/advisory committee |
Impact | Change in policy of chemicals manufacturers towards continuous bioprocesses and training in metabolic modelling, synthetic biology, and chemostat culture |
Description | IB Catalyst |
Amount | £525,090 (GBP) |
Funding ID | BB/N02348X/1 |
Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
Sector | Public |
Country | United Kingdom |
Start | 08/2016 |
End | 08/2021 |
Title | Flexible Nets |
Description | Mathematical models that combine predictive accuracy with explanatory power are central to the progress of systems and synthetic biology, but the heterogeneity and incompleteness of biological data impede our ability to construct such models. Furthermore, the robustness displayed by many biological systems means that they have the flexibility to operate under a range of physiological conditions and this is difficult for many modeling formalisms to handle. Flexible nets (FNs) address these challenges and represent a paradigm shift in model-based analysis of biological systems. FNs can: (i) handle uncertainties, ranges and missing information in concentrations, stoichiometry, network topology, and transition rates without having to resort to statistical approaches; (ii) accommodate different types of data in a unified model that integrates various cellular mechanisms; and (iii) be employed for system optimization and model predictive control. |
Type Of Material | Improvements to research infrastructure |
Year Produced | 2018 |
Provided To Others? | Yes |
Impact | Radical new method of modelling biological systems whcih also allows real-time control of bioprocesses. |
URL | https://bitbucket.org/Julvez/fnyzer.git |
Title | HeLanetss_results.xls from A unifying modelling formalism for the integration of stoichiometric and kinetic models |
Description | Current research on systems and synthetic biology relies heavily on mathematical models of the systems under study. The usefulness of such models depends on the quantity and quality of biological data, and on the availability of appropriate modelling formalisms that can gather and accommodate such data so that they can be exploited properly. Given our incomplete knowledge of biological systems and the fact that they consist of many subsystems, biological data are usually uncertain and heterogeneous. These facts hinder the use of mathematical models and computational methods. In the scope of dynamic biological systems, e.g. metabolic networks, this difficulty can be overcome by the novel modelling formalism of flexible nets (FNs). We show that an FN can combine, in a natural way, a stoichiometric model and a kinetic model. Moreover, the resulting net admits nonlinear dynamics and can be analysed in both transient and steady states. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/HeLanetss_results_xls_from_A_unifying_modelling_formalism_for_the_i... |
Title | HeLanetss_results.xls from A unifying modelling formalism for the integration of stoichiometric and kinetic models |
Description | Current research on systems and synthetic biology relies heavily on mathematical models of the systems under study. The usefulness of such models depends on the quantity and quality of biological data, and on the availability of appropriate modelling formalisms that can gather and accommodate such data so that they can be exploited properly. Given our incomplete knowledge of biological systems and the fact that they consist of many subsystems, biological data are usually uncertain and heterogeneous. These facts hinder the use of mathematical models and computational methods. In the scope of dynamic biological systems, e.g. metabolic networks, this difficulty can be overcome by the novel modelling formalism of flexible nets (FNs). We show that an FN can combine, in a natural way, a stoichiometric model and a kinetic model. Moreover, the resulting net admits nonlinear dynamics and can be analysed in both transient and steady states. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/HeLanetss_results_xls_from_A_unifying_modelling_formalism_for_the_i... |
Title | fnyzer |
Description | fnyzer, is a Python package for the analysis of Flexible Nets (FNs). FNs is a modelling formalism for dynamical systems that can handle a number of uncertain parameters, and that is particularly well suited to model the different types of networks arising in systems biology. fnyzer offers different types of analysis, can handle nonlinear dynamics, and can transform SBML models into FN format. |
Type Of Material | Computer model/algorithm |
Year Produced | 2019 |
Provided To Others? | Yes |
Impact | None yet |
URL | https://bitbucket.org/Julvez/fnyzer |
Description | Development of Flexible Net approaches for the modelling of biological systems |
Organisation | University of Zaragoza |
Country | Spain |
Sector | Academic/University |
PI Contribution | Provision of biological expertise and refined mathematical models of metabolic networks |
Collaborator Contribution | Computational expertise and extensions to the Flexible Net forlalism |
Impact | Multi-disciplinary: Systems Biology and Computer Science |
Start Year | 2016 |
Title | HeLanetss.py from A unifying modelling formalism for the integration of stoichiometric and kinetic models |
Description | Current research on systems and synthetic biology relies heavily on mathematical models of the systems under study. The usefulness of such models depends on the quantity and quality of biological data, and on the availability of appropriate modelling formalisms that can gather and accommodate such data so that they can be exploited properly. Given our incomplete knowledge of biological systems and the fact that they consist of many subsystems, biological data are usually uncertain and heterogeneous. These facts hinder the use of mathematical models and computational methods. In the scope of dynamic biological systems, e.g. metabolic networks, this difficulty can be overcome by the novel modelling formalism of flexible nets (FNs). We show that an FN can combine, in a natural way, a stoichiometric model and a kinetic model. Moreover, the resulting net admits nonlinear dynamics and can be analysed in both transient and steady states. |
Type Of Technology | Software |
Year Produced | 2020 |
Open Source License? | Yes |
URL | https://rs.figshare.com/articles/HeLanetss_py_from_A_unifying_modelling_formalism_for_the_integratio... |
Title | HeLanetss.py from A unifying modelling formalism for the integration of stoichiometric and kinetic models |
Description | Current research on systems and synthetic biology relies heavily on mathematical models of the systems under study. The usefulness of such models depends on the quantity and quality of biological data, and on the availability of appropriate modelling formalisms that can gather and accommodate such data so that they can be exploited properly. Given our incomplete knowledge of biological systems and the fact that they consist of many subsystems, biological data are usually uncertain and heterogeneous. These facts hinder the use of mathematical models and computational methods. In the scope of dynamic biological systems, e.g. metabolic networks, this difficulty can be overcome by the novel modelling formalism of flexible nets (FNs). We show that an FN can combine, in a natural way, a stoichiometric model and a kinetic model. Moreover, the resulting net admits nonlinear dynamics and can be analysed in both transient and steady states. |
Type Of Technology | Software |
Year Produced | 2020 |
Open Source License? | Yes |
URL | https://rs.figshare.com/articles/HeLanetss_py_from_A_unifying_modelling_formalism_for_the_integratio... |
Title | hillpwlnet.py from A unifying modelling formalism for the integration of stoichiometric and kinetic models |
Description | Current research on systems and synthetic biology relies heavily on mathematical models of the systems under study. The usefulness of such models depends on the quantity and quality of biological data, and on the availability of appropriate modelling formalisms that can gather and accommodate such data so that they can be exploited properly. Given our incomplete knowledge of biological systems and the fact that they consist of many subsystems, biological data are usually uncertain and heterogeneous. These facts hinder the use of mathematical models and computational methods. In the scope of dynamic biological systems, e.g. metabolic networks, this difficulty can be overcome by the novel modelling formalism of flexible nets (FNs). We show that an FN can combine, in a natural way, a stoichiometric model and a kinetic model. Moreover, the resulting net admits nonlinear dynamics and can be analysed in both transient and steady states. |
Type Of Technology | Software |
Year Produced | 2020 |
Open Source License? | Yes |
URL | https://rs.figshare.com/articles/hillpwlnet_py_from_A_unifying_modelling_formalism_for_the_integrati... |
Title | hillpwlnet.py from A unifying modelling formalism for the integration of stoichiometric and kinetic models |
Description | Current research on systems and synthetic biology relies heavily on mathematical models of the systems under study. The usefulness of such models depends on the quantity and quality of biological data, and on the availability of appropriate modelling formalisms that can gather and accommodate such data so that they can be exploited properly. Given our incomplete knowledge of biological systems and the fact that they consist of many subsystems, biological data are usually uncertain and heterogeneous. These facts hinder the use of mathematical models and computational methods. In the scope of dynamic biological systems, e.g. metabolic networks, this difficulty can be overcome by the novel modelling formalism of flexible nets (FNs). We show that an FN can combine, in a natural way, a stoichiometric model and a kinetic model. Moreover, the resulting net admits nonlinear dynamics and can be analysed in both transient and steady states. |
Type Of Technology | Software |
Year Produced | 2020 |
Open Source License? | Yes |
URL | https://rs.figshare.com/articles/hillpwlnet_py_from_A_unifying_modelling_formalism_for_the_integrati... |
Title | inprod.py from A unifying modelling formalism for the integration of stoichiometric and kinetic models |
Description | Current research on systems and synthetic biology relies heavily on mathematical models of the systems under study. The usefulness of such models depends on the quantity and quality of biological data, and on the availability of appropriate modelling formalisms that can gather and accommodate such data so that they can be exploited properly. Given our incomplete knowledge of biological systems and the fact that they consist of many subsystems, biological data are usually uncertain and heterogeneous. These facts hinder the use of mathematical models and computational methods. In the scope of dynamic biological systems, e.g. metabolic networks, this difficulty can be overcome by the novel modelling formalism of flexible nets (FNs). We show that an FN can combine, in a natural way, a stoichiometric model and a kinetic model. Moreover, the resulting net admits nonlinear dynamics and can be analysed in both transient and steady states. |
Type Of Technology | Software |
Year Produced | 2020 |
Open Source License? | Yes |
URL | https://rs.figshare.com/articles/inprod_py_from_A_unifying_modelling_formalism_for_the_integration_o... |
Title | inprod.py from A unifying modelling formalism for the integration of stoichiometric and kinetic models |
Description | Current research on systems and synthetic biology relies heavily on mathematical models of the systems under study. The usefulness of such models depends on the quantity and quality of biological data, and on the availability of appropriate modelling formalisms that can gather and accommodate such data so that they can be exploited properly. Given our incomplete knowledge of biological systems and the fact that they consist of many subsystems, biological data are usually uncertain and heterogeneous. These facts hinder the use of mathematical models and computational methods. In the scope of dynamic biological systems, e.g. metabolic networks, this difficulty can be overcome by the novel modelling formalism of flexible nets (FNs). We show that an FN can combine, in a natural way, a stoichiometric model and a kinetic model. Moreover, the resulting net admits nonlinear dynamics and can be analysed in both transient and steady states. |
Type Of Technology | Software |
Year Produced | 2020 |
Open Source License? | Yes |
URL | https://rs.figshare.com/articles/inprod_py_from_A_unifying_modelling_formalism_for_the_integration_o... |
Title | modint.py from A unifying modelling formalism for the integration of stoichiometric and kinetic models |
Description | Current research on systems and synthetic biology relies heavily on mathematical models of the systems under study. The usefulness of such models depends on the quantity and quality of biological data, and on the availability of appropriate modelling formalisms that can gather and accommodate such data so that they can be exploited properly. Given our incomplete knowledge of biological systems and the fact that they consist of many subsystems, biological data are usually uncertain and heterogeneous. These facts hinder the use of mathematical models and computational methods. In the scope of dynamic biological systems, e.g. metabolic networks, this difficulty can be overcome by the novel modelling formalism of flexible nets (FNs). We show that an FN can combine, in a natural way, a stoichiometric model and a kinetic model. Moreover, the resulting net admits nonlinear dynamics and can be analysed in both transient and steady states. |
Type Of Technology | Software |
Year Produced | 2020 |
Open Source License? | Yes |
URL | https://rs.figshare.com/articles/modint_py_from_A_unifying_modelling_formalism_for_the_integration_o... |
Title | modint.py from A unifying modelling formalism for the integration of stoichiometric and kinetic models |
Description | Current research on systems and synthetic biology relies heavily on mathematical models of the systems under study. The usefulness of such models depends on the quantity and quality of biological data, and on the availability of appropriate modelling formalisms that can gather and accommodate such data so that they can be exploited properly. Given our incomplete knowledge of biological systems and the fact that they consist of many subsystems, biological data are usually uncertain and heterogeneous. These facts hinder the use of mathematical models and computational methods. In the scope of dynamic biological systems, e.g. metabolic networks, this difficulty can be overcome by the novel modelling formalism of flexible nets (FNs). We show that an FN can combine, in a natural way, a stoichiometric model and a kinetic model. Moreover, the resulting net admits nonlinear dynamics and can be analysed in both transient and steady states. |
Type Of Technology | Software |
Year Produced | 2020 |
Open Source License? | Yes |
URL | https://rs.figshare.com/articles/modint_py_from_A_unifying_modelling_formalism_for_the_integration_o... |
Title | ratecon.py from A unifying modelling formalism for the integration of stoichiometric and kinetic models |
Description | Current research on systems and synthetic biology relies heavily on mathematical models of the systems under study. The usefulness of such models depends on the quantity and quality of biological data, and on the availability of appropriate modelling formalisms that can gather and accommodate such data so that they can be exploited properly. Given our incomplete knowledge of biological systems and the fact that they consist of many subsystems, biological data are usually uncertain and heterogeneous. These facts hinder the use of mathematical models and computational methods. In the scope of dynamic biological systems, e.g. metabolic networks, this difficulty can be overcome by the novel modelling formalism of flexible nets (FNs). We show that an FN can combine, in a natural way, a stoichiometric model and a kinetic model. Moreover, the resulting net admits nonlinear dynamics and can be analysed in both transient and steady states. |
Type Of Technology | Software |
Year Produced | 2020 |
Open Source License? | Yes |
URL | https://rs.figshare.com/articles/ratecon_py_from_A_unifying_modelling_formalism_for_the_integration_... |
Title | ratecon.py from A unifying modelling formalism for the integration of stoichiometric and kinetic models |
Description | Current research on systems and synthetic biology relies heavily on mathematical models of the systems under study. The usefulness of such models depends on the quantity and quality of biological data, and on the availability of appropriate modelling formalisms that can gather and accommodate such data so that they can be exploited properly. Given our incomplete knowledge of biological systems and the fact that they consist of many subsystems, biological data are usually uncertain and heterogeneous. These facts hinder the use of mathematical models and computational methods. In the scope of dynamic biological systems, e.g. metabolic networks, this difficulty can be overcome by the novel modelling formalism of flexible nets (FNs). We show that an FN can combine, in a natural way, a stoichiometric model and a kinetic model. Moreover, the resulting net admits nonlinear dynamics and can be analysed in both transient and steady states. |
Type Of Technology | Software |
Year Produced | 2020 |
Open Source License? | Yes |
URL | https://rs.figshare.com/articles/ratecon_py_from_A_unifying_modelling_formalism_for_the_integration_... |