Optimization for the design of biological circuits

In this module, we will introduce optimization-based algorithms for the automated design of biological circuits. First, we will illustrate the capacities of optimization based tools for the design of de novo circuits with predefined performance, as part of the forward design cycle in Synthetic Biology. This section will cover:

• Formulation and efficient solution of the biocircuit design problem, taking into account plug-and-play modularity and biological diversity (one functional behavior can be carried out by many different biological processes).
• Multi-criteria design, introducing adapted multi-objective optimization techniques to find the Pareto sets of bio-circuits with best tradeoffs between a number of conflicting goals.

In a second part we will use optimization based frameworks for reverse design, identifying motifs performing a specific biological task, and helping to infer design principles of biological circuits. We will combine theory with practical examples, including the design of genetic switches and oscillators from a library of standard parts. 

Workshop 2

Kinetic and optimization­-based models for understanding the regulation of cellular metabolism

Organizers:
The ROBUSTYEAST consortium
Steffen Waldherr (OvGU Magdeburg / KU Leuven), Alexander Bockmayr (FU Berlin), Frank Bruggeman (VU Amsterdam), Vassily Hatzimanikatis (EPF Lausanne)

Constraint­-based models formulated as an optimization problem are an established framework to describe the metabolic behaviour of living cells. In such models, the biochemical reaction fluxes are modelled as optimization variables subject to biophysical constraints, and an optimization problem with a biologically reasonable objective is solved to obtain model predictions for the values of the fluxes. As an alternative model class, kinetic models explicitly include the regulation of reactions in the model description. Classically, this requires that all regulations, e.g., allosteric, are known for the model construction. However, new modeling approaches soften this requirement, enabling the construction of genome-scale kinetic models similar in scope to established constraint-based models. The proposed workshop focusses specifically on the interface between kinetic and optimization-based models to understand the regulation of cellular metabolism in a dynamic context.

The workshop is being organized by the ROBUSTYEAST consortium. ROBUSTYEAST is an European research consortium funded under the ERA­Net for Applied Systems Biology (ERASysAPP) program with the goal of revealing the engineering principles for robustness of metabolism to nutrient dynamics with yeast as a model organism. The connection between optimization­-based and kinetic models plays a crucial role in this, and the purpose of the workshop is to act as a platform for scientific exchange about the state of the art in this area between researchers within and outside the ROBUSTYEAST consortium.

There is also an invited session in the main conference program by the same organizers which builds upon this workshop. Details will be provided when the conference program has been finalized.

Workshop contributions

• Henning Lindhorst, Otto-von-Guericke-University Magdeburg, DE: 
  “Optimization methods for metabolic networks – Cellular decision making by robust optimization”

• Ronan Fleming, University of Luxembourg, LU:
  “Variational kinetics: kinetic modelling based on variational analysis"

• Ljubisa Miskovic, Georgios Fengos, Meric Ataman, Tuure Hameri, Vassily Hatzimanikatis, EPF Lausanne, CH:
  “Kinetic modeling of genome­scale metabolic networks of E. coli and yeast without sacrificing stoichiometric, thermodynamic and physiological constraints”

• Panel discussion with the workshop contributors and the ROBUSTYEAST consortium about the connection between kinetic and optimization-based models.