Abstract
The increasing demand for energy use and the growing consensus on the need to significantly reduce greenhouse gas emissions and dependence on fossil fuels are boosting the development and improvement of biofuels production. Ethanol is the most widely used biofuel, obtained from the fermentation of sugars extracted mainly from sugarcane (Brazil) and corn (USA). Despite the large production, great efforts are being made to increase these numbers, and one of the options would be the production of second generation (2G) ethanol. The 2G ethanol is produced by the fermentation of sugars (hexoses and pentoses) released from complex polysaccharides found in plant biomass. However, for the use of lignocellulosic materials and the 2G ethanol production, it is necessary that a number of biotechnology challenges be overcome. Several technological difficulties need to be solved, such as disrupt the recalcitrant cell wall structure from bagasse to increase the depolymerization and release of sugars for fermentation. During this process, some toxic compound are released, such as weak acids, furan aldehydes and phenolics, threaten the yeast surviving and performance. For example, these inhibitors can provoke an excessive waste of ATP, oxidative stress, DNA damage, membranes loss of integrity, and others. Our group previously developed an engineered strain of the yeast Saccharomyces cerevisiae with an efficient ability to ferment xylose and produce ethanol with yields above 92% of the maximum theoretical. The next step is to increase the yeast tolerance and survival to these toxic compounds. To develop a more robust and efficient strains for 2G technologies, it's necessary a deep knowledge of the yeast behavior exposed to different types of stresses, to understand the molecular basis of the physiological stress responses and understand how they are integrated. In order to accomplish this objective, we will perform analysis on population dynamics before and after a large scale adaptive evolution process to stress exposure, to understand how alleles are been fixed under selective pressures. To validate the genomic variation results, we will perform a comparative transcriptomic analysis during the fermentation, under different stresses. Hence, our proposal is to carry out a deep learning on the physiology of yeasts through a large-scale multi-omic approach, aiming to integrate data from evolved and tolerant populations. Despite the volume of information about yeast stress, there are no previous works with an integrative approach that allows discriminate the single effects of each stress and unravel the central regulator for them. Ours preliminary results showed the combined stresses increases the sugar uptake and tolerance. This work will explore this phenomena, discerning between the effects of each stresses isolated, reveling a gene regulation network responsible for each system activation. In this way, our work will drives a major contribution of the development of an inhibitor-resistant strain, which have a key role to become the ethanol 2G a viable alternative in Brazil. (AU)
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