White (industrial), green (agriculture) and red (health) biotechnology use enhanced and/or engineered microorganisms as cell factories to produce high-added values specialty metabolites (e.g. amino acids, vitamins, and food additives, biofuels, biofilms and tissues). Biotechnological engineering is of paramount importance for the future of health, chemical, food and other process industries. Yet, the current state-of-the-art, characterized by uncertainty and lack of in-depth real-time knowledge about the process state, forces industry to operate their bioprocesses at too conservative, suboptimal and not intensified regimes, so as to avoid undesirable microorganism physiological states. Such practices cause problems such as poor efficiency, lack of process stability and increased waste of product.

In order to surmount these difficulties, there is a need of identifying desirable metabolic (physiological) states (such as ones of high productivity) and of developing bioreactor optimization, monitoring and control methods so as to lead the system to the desired state in the course of a process, while considering the metabolic state and constraints. This implies considering processes in a wide range of temporal scales (from seconds for metabolic

fluxes, minutes for the aggregated population and extracellular metabolites dynamics, to hours for genetic regulation) and spatial ones (from the intracellular dynamics to the microorganisms population inside the bioreactor).

Within the systems and synthetic bioprocesses context, MultiScaleS will provide systematic methods, tools and protocols for inference, real-time monitoring, optimization and feedback control of bio-systems by means of multiscale strategies, spanning from micro (e.g. metabolic and genetic networks) to macro scales (e.g. population macroscopic dynamics as used in the context of bioreactors monitoring and control). MultiScaleS expected results will be instrumental to achieve end products inside specifications and optimal productivity while operating at intensified regimes. It is expected these results can also be applied within other industrial contexts characterized by muti-scale dynamics and coordination of dynamical agents.

The project partly relies on previous results obtained within the framework of MultiSysBio ("Multi-scale modelling approach to systems biology", DPI2008-06880-C03, http://www.multisysbio.org), pushes them further, and explores new related topics, focussing on:

1. Further investigating, improving and exploiting topics concerning multi-scale model building and analysis methods and tools, including systematic model building and experimental design, grey modelling, scaling-up, inference in biological systems, and multicellular coordinated dynamics analysis.
2. Novel multi-scale optimization and control methods, including new metaheuristics for optimization and optimal control in metabolic engineering, optimal integrated design and control (steps towards synthetic biology), model-based software sensors (observers) accounting for multiple scales, bioreactor control considering the metabolic state and constraints, and control of cell interactions.
3. Application to biotechnological industrial production, with special emphasis on how low level biological metabolic states can be controlled at the bioreactor level. Proof –of-concept on real industrial cases.

The companies BIOPOLIS S.L. and inBIOnova Biotech S.L. will be acting as actively participating promoting entities (EPO) in this project, BIOPOLIS S.L. will provide access and commit resources drawn from its state-of the-art bioprocessing and fermentation facilities, analytical equipment and bioproduction know-how; Inbionova will provide its resources with several severs and access to the cluster Ben Arabí (4th in Spain), as well as its analytical facilities for Metabolomics (HPLC-MS) and Transcriptomics (Affymetrix) and the know-how related.