A predictive genome-scale Pseudomonas sp. LFM046 metabolic model

• Grant number: 18/05456-6
• Support type: Scholarships abroad - Research Internship - Doctorate (Direct)
• Effective date (Start): June 01, 2018
• Effective date (End): November 30, 2018
• Field of knowledge: Engineering - Chemical Engineering
• Principal Investigator: Marilda Keico Taciro
• Grantee: Rafael Augusto Theodoro Pereira de Souza Nahat
• Supervisor abroad: Marie-France Sagot
• Home Institution: Instituto de Ciências Biomédicas (ICB). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Local de pesquisa : Institut National de Recherche en Informatique et en Automatique (INRIA Antenne Lyon la Doua), France
• Associated to the scholarship: 16/01756-0 - Metabolic modelling of polihydroxyalkanoates production production with different monomeric compositions by Pseudomonas sp., BP.DD

Abstract

An essential part of the assessment and development of a bioprocess powered by a living organism is an accurate mathematical model of its metabolism. Building such model is to conciliate the enzyme activities inferred from the known gene sequences with the actual observed phenotypes. Currently, this is a complex non-automated task. Pseudomonas sp. LFM046 is an efficient wild-type producer of polyhydroxyalkanoates - a bioplastic of industrial interest - and also a promising multipurpose bioprocess platform with a large knowledge base already available: its full genome sequence, many bioreactor experiments in various conditions and a partial metabolic model. By combining the complementary expertises of two research groups (Brazil and France) which have been collaborating to this knowledge base, this project aims to: (i) consolidate a predictive genome-scale metabolic model for Pseudomonas sp. LFM046; and (ii) establish a method for building such models that is transferable to other organisms, simplifying the task which currently is a major bottleneck of systems biology R&D. (AU)