P0112
Metabolic Fingerprinting of Microorganisms Presenting in Fermentative Process of Ethanol

Date: Monday, January 12, 2015
Room:
Mariana Souza Silva , ESALQ/USP, Piracicaba, Brazil
Ilara G. Bundzinsk , ESALQ/USP, Piracicaba, Brazil
Thais Regiani , ESALQ/USP, Piracicaba, Brazil
Fabrício E. Moraes , ESALQ/USP, Piracicaba, Brazil
Carlos A. Labate , ESALQ/USP, Piracicaba, Brazil
The yeast population used in fermentative process of ethanol may vary according to the environmental stress imposed to yeast cells during the process and the contamination caused by others microorganisms (e.g. fungi and bacteria), that influences in high alcohol productivity. The yeast Saccharomyces cerevisiae has traditionally been used and remains the organism of choice for large-scale industrial ethanol production from starch- and sugar-based feedstocks. Some wild S. cerevisiae strains and others microorganims, isolated from the ethanol industry in Brazil, persist and prevail in the harsh industrial environment. Based on this, the metabolome analysis can contribute to the separation of all different microorganisms. Here we present a first evaluation of the intra-cellular metabolites of some widely used industrial yeast strain: PE-1, PE-2, SaccharomycesSA, baker’s yeast and others 23 microorganisms contaminants in the fermentative process. Metabolites were extracted from microorganisms cells similar to the method described in Fairchild et al. (2010). Samples were analyzed by UPLC-Q-TOF-MS, using the analytical column Acquity C18 Waters (100mm, 1,7 µm) at a flow rate of 0,5mL/min. Data processing and multivariate analysis were performed in MarkerLynx and MetaboAnalyst softwares. Principal component analysis (PCA) was conducted by the metabolome data. By the score plot analysis, we observed that the Principal component 1 and 2 clearly separate the different microorganisms samples. PLS-DA analysis resulted in the separation of microorganisms into different groups and by the variable importance in the projection (VIP) many differentially abundant metabolites were identified using the YMDB database (http://www.ymdb.ca). Financial support: FAPESP (2011/23816-0).