Changes in the bacterial community and overall metabolic profile in a first-generation ethanol distillery under distinct fermentative yield

• Ano de defesa: 2020
• Autor(a) principal: Iurif, Vanessa Costa
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Contaminantes; Contaminants; Fermentação; Fermentation; Metabarcoding; Metabolômica; Metabolomics
• Link de acesso: https://www.teses.usp.br/teses/disponiveis/105/105131/tde-07012021-162305/

Growing concerns about the greenhouse gases emmisions, produced by the fossil fuel combustion, on climate change have intensified the search for alternative sources of energy. In this scenario, bioethanol was recognized as a viable alternative for the replacement of certain fossil fuels. The main route for ethanol production is the ethanolic fermentation of sugary feedstocks. Through the fermentation of sugarcane derivatives, Brazil is the second-largest ethanol producer in the world. The presence of bacterial contaminants is common in all stages of Brazilian ethanol production. It is well known that the presence of contaminants can lead to a decrease in ethanol productivity and cause financial losses for the ethanol industry. In order to evaluate if there are differences in the bacterial community of distinct ethanol productivity yield, samples from must and fermentation tanks were collected from an industrial ethanol production distillery in the Piracicaba region (SP-Brazil) running in a continues system of fermentation. Bacterial communities were identified through metabarcoding sequencing of regions of the 16S rDNA gene. We were able to observe differences in the microbiota from samples representing low and normal ethanol productivity. In the must samples we observed different proportions of bacterial genera. In the fermentation tanks, as expected, we observed a predominance of Lactobacillus. However, despite microbes being from this genus, we observe some differences in OTU patterns in samples from Low and Normal productivity. Since our data showed that there are differences in the distillery community on different productivity conditions, our second goal was to examine the metabolic profile aiming to find potential key metabolites for process monitoring. Using untargeted GC-MS the extracellular and intracellular metabolic profile of the same distillery were explored in low and normal productivity conditions. This approach proved to be effective to select metabolites from the extracellular medium to be further explored for the distillery as potential monitoring markers of productivity, such as the metabolites Oleic acid, Tagatose, 3-O-methyl-Glucose, 5 beta- Dihydrotestosterone, NA 1045 and NA901. Through intracellular analysis it was possible to identify metabolites related to changes in metabolic pathways. We noticed a greater abundance of energy-related metabolism pathways in Normal productivity, such as: Glucose, Glucose-6- phosphate, Lactulose, Maltotriose and Sorbose. It was also possible to detect metabolites related to changes in the microbiological community under different conditions of productivity, such as the metabolite mannitol, for example to select metabolites to be further explored for the distillery as potential monitoring markers of productivity. It was also possible to identify, through GC-MS approaches, some metabolites probably related to changes of the microbial community under distinct fermentative yield situations.