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MELiSSA Workshop, Date: 2016/06/08 - 2016/06/09, Location: Lausanne

Publication date: 2016-06-01

Author:

Nolla Ardevol, Vimac
Luther, Amanda ; Raffestin, Stephanie ; Lasseur, Christophe ; Bernaerts, Kristel ; Ryckeboer, Jaak ; Rabaey, Korneel ; Wattiez, Ruddy ; Gebri, Olivier ; Poughon, Laurent ; Wilmes, Paul ; Simonet, Pascal ; Bouchez, Theodore ; Faust, Karoline ; Smets, Ilse ; Springael, Dirk

Abstract:

As is the case for all of the MELiSSA compartments, the control of the C1 compartment relies on the design of a comprehensive mechanistic mathematical model. Such a model can only be developed on the basis of a thorough understanding of the C1 microbial community composition, the metabolic reactions involved and their kinetics, and the impact of operational and environmental conditions on them. Today, achieving such a deep understanding of the C1 compartment is still a daunting task and crucial questions remain such as which biological information is needed and at which resolution. Moreover, up to date technologies and approaches, mainly meta-omics combined with other culture independent techniques, are available to acquire an in depth knowledge on the composition of a microbial community and its functionality but still suffer from several issues such as (i) lack of standardization, both technical and experimental (ii) lack of knowledge about reproducibility and (iii) in some cases the techniques are not fully developed or have a low resolution. To bring light into this challenging task, ESA and KU Leuven organized a one day workshop in which renowned experts in the field of microbial systems biology, environmental meta-omics, microbial populations dynamics and process modeling discussed the challenges involved in the C1 microbial (community) characterization for modelling purposes and how to overcome them. In this presentation we will give an insight into the proposed short and long term roadmap and experimental design for the thorough characterization of the microbial community in the MELiSSA C1 reactor in view of mechanistic model development.