Development of methods of analysis and data integration applied to the construction of industrial yeasts for the production of second generation bioethanol

Author(s)

Lucas Miguel de Carvalho

• Document type: Doctoral Thesis
• Press: Campinas, SP.
• Institution: Universidade Estadual de Campinas (UNICAMP). Instituto de Biologia
• Defense date: 2019-04-12

Examining board members

Gonçalo Amarante Guimarães Pereira; Renato Vicentini; Marcelo Mendes Brandão; Helder Takashi Imoto Nakaya

• Advisor: Gonçalo Amarante Guimarães Pereira; Marcelo Falsarella Carazzolle

Abstract

Brazil is one of the world leaders in the production of ethanol, being a pioneer in the field of alcohol fuel. However, the country already faces a major constraint imposed by first-generation ethanol technology. Thus, new alternatives have been proposed, with emphasis on second-generation technology, which consists of using lignocellulosic residues from sugarcane to produce ethanol. One of the major challenges of this new technology is the development of an industrial yeast capable of producing ethanol not only from hexose (glucose) but also from pentoses, which represent between 15% and 45% of the lignocellulosic material. The objective of this work is to use and develop tools and methodologies of bioinformatics and systemic biology to study in silico the inclusion of reductive / oxidative and xylose isomerization in Pedra II (PE-II), an industrial strain of yeast Saccharomyces cerevisiae which had its genome sequenced by Unicamp's Laboratory of Genomics and Expression. The xylose consumption pathways were included in the metabolic model of S. cerevisiae and, through analyzes of optimization of metabolic flow and development of models using stochastic Petri Net, we carried out the study of possible genetic alterations that contribute to an increase in ethanol production from xylose. In addition, an integrative pipeline, called Network Integrated Module (NIM), was developed from a protein-protein networks that allows new insights into the regulatory mechanism by inferring direction at the edges of the network (AU)

• FAPESP's process: 15/06263-9 - Development of methods of analysis and data integration of omics applied to the construction of industrial yeasts for second generation bioethanol production
• Grantee: Lucas Miguel de Carvalho
• Support Opportunities: Scholarships in Brazil - Doctorate