Improvement of the metabolic network reconstruction of Kalmanozyma brasiliensis and associated metabolic simulations

• Grant number: 16/13968-1
• Support Opportunities: Scholarships abroad - Research Internship - Master's degree
• Start date: December 01, 2016
• End date: March 31, 2017
• Field of knowledge: Biological Sciences - Biochemistry - Metabolism and Bioenergetics
• Principal Investigator: Gustavo Henrique Goldman
• Grantee: Renato Augusto Corrêa dos Santos
• Supervisor: Jason Papin
• Host Institution: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM). Ministério da Ciência, Tecnologia e Inovação (Brasil). Campinas , SP, Brazil
• Institution abroad: University of Virginia (UVa), United States
• Associated to the scholarship: 14/15799-7 - Genomic analysis of the xylanolytic yeast Pseudozyma brasiliensis, BP.MS

Abstract

Genome-scale metabolic network reconstructions have been used for many applications, such as guidance of metabolic engineering of industrially and biotechnologically important microorganisms. In the main master proposal, the reconstruction of a draft of metabolic networks of a basidiomycetous yeast Kalmanozyma brasiliensis GHG001 was proposed, for further simulations aiming improvements in pathways involved in second generation bioethanol production. The current proposal of Research Internship Abroad - Master (BEPE-MS) at the Computational Systems Biology Laboratory, University of Virginia, supervised by Dr. Jason Papin aims (i) to improve the metabolic reconstruction of K. brasiliensis, (ii) to start constraint-based simulations such as Flux Balance Analysis (FBA), (iii) to learn good practices in model reconstruction and simulation. Improvement of the metabolic model of K. brasiliensis will be carried out by interaction with the research group and application of comparative computational methods, independent of experimental data. In addition, networking with students in the research group will allow use of well-established metabolic models of Saccharomyces cerevisiae (http://systemsbiology.ucsd.edu/InSilicoOrganisms/Yeast) for starting in silico simulations, further applied to research in which the student is involved. (AU)