COMBO: CONTROL-BASED BIODESIGN OF MAMMALIAN CELL DYNAMICS

Systems Biologists, by combining cell biology with mathematical approaches, have shown that feedback loops in molecular regulatory networks tightly control cellular homeostasis and responses. The interplay between endogenous feedbacks and the extracellular environment results in complex and non-linear cellular dynamics.
Mathematical models can help in tackling this complexity, aiding in characterising the links between cellular dynamics and cell-decision making. However, the validity of models relies on modelling assumptions and the quality of data used for parameter fitting: stochasticity and noise limit the power of model predictions across Systems Biology and Systems Pharmacology applications.

Conversely, the forward engineering of exogenous gene expression dynamics that recapitulate native cellular behaviours, often used by Synthetic Biologists, is limited by poor robustness to physical parameter variations, diverse modular parts and choice of chassis.

To tackle these challenges, this Fellowship proposes to directly and automatically program complex dynamics in mammalian cells, by combining external feedback control to ensure robustness and a microfluidics/microscopy platform to observe and perturb cells in real-time.
Exploitation of this technology will allow to:
i) Unravel causation in coupled processes and dissect the role that temporal patterns across scales (i.e. gene expression dynamics and cell-cycle) play in stem cell fate, ultimately exploiting such dynamics for the design of superior stem cell culture protocols.
ii) Directly track from experiments non-linear biochemical dynamics, without the need of mathematical models, to quantitatively determine causes/robustness of complex native/engineered behaviours, respectively, using experimental and Control-Based Continuation.

Direct industrial applications will be explored, including the characterisation of stem cell culture protocols across culture scales, and the use of feedback control to design optimal drug dosing schedules for target cancer cell responses.

Our aims are underpinned by two highly synergetic research tracks at the interface of interdisciplinary disciplines. The combination of methodologies from control theory, Synthetic, Systems and Stem cell biology will provide a quantitative framework and highly novel tools to understand, steer and design mammalian cell dynamic phenotypes, with great potential for future therapeutic purposes.

This Fellowship takes a multidisciplinary approach to apply Synthetic Biology and Control Engineering methodologies to steer mammalian cell phenotypes across applications, and has a potential impact on the:

1) Academic community
Outcomes of the proposed research will have important implications for the Synthetic Biology, Systems Biology and Pharmacology, Control Engineering and Stem Cell Biology communities (see "Academic beneficiaries" section). The immediate term impact will be promoted via scientific dissemination and discussion of findings within my network of interdisciplinary collaborators; immediate and long-term impact will be pursued by scientific publications in peer-reviewed journals and participation to international conferences. My involvement in the Bristol Institute for BioDesign, the Bristol Centre for Synthetic Biology and the Synthetic Biology CDT (Bristol, Oxford and Warwick Universities) will facilitate dissemination of project findings and foster novel collaborations.

2) Academic community/Bioindustry
A strong interaction between the academic community and industrial stakeholders is needed to realise the ambition of mammalian cell Synthetic Biology to transform common methodologies used in the Bioindustry. To disseminate results to a wider community, host presentations by leading groups and interact with industrial stakeholders, we will organise two workshops focused on exploring Synthetic Biology applications in Stem Cell Biology, and evaluating advances, opportunities and challenges in microfluidics-based Synthetic Biology approaches.

3) Bioindustry
Benefits of this Fellowship span a range of emerging markets: Synthetic Biology, Stem Cell Biology, Quantitative Systems Pharmacology. Indeed, the proposed research will lay the foundations for introducing automation and improving robustness in: i) mammalian stem cell cultures across scales; ii) optimisation of drug combination treatments in cancer; iii) design and prototyping synthetic gene circuits. The industrial support for the project from two partners (AstraZeneca, Cellesce) makes both the immediate and the long-term impact of the work clear. My further links to the bioindustry (through the Synthetic Biology CDT, SynbiCITE, and the UK Quantitative Systems Pharmacology network) will enable discussion about additional translation of research outcomes.

4) Research personnel involved in this project
The appointed PDRAs and PhD student will gain a number of cutting edge skills that will help them in their future academic or industrial career; this will result in long-term impact for the UK economy. I will provide continuous mentoring; I am experienced in working in both the experimental and the computational communities, and in leading interdisciplinary research teams. I will facilitate required training of the research personnel, their participation to conferences and seminars, and their direct interaction with the academic and industrial partners. If funded, this Fellowship will permit establishing myself as an international leader in mammalian cell Synthetic Biology, and developing new links with leading research institutes and biomedical industries.

5) General public
Synthetic Biology and Stem Cell Biology are topics of great interest and debate for general public. Sharing research hypothesis and results in a clear way is a fundamental part of my work. For immediate and long-term public engagement, I will disseminate project findings by taking part to public engagement activities organised by the University of Bristol and the Institutes of the project partners, and setting-up a project website.