Prospecção de genes na microbiota do rúmen bovino com propriedades degradadoras da biomassa vegetal - Ribeiro, Lucas Daniel [UNESP] (2015)
Since the expansion of industry through the Industrial Revolution, the world population has increased unprecedented. This rise together the constant technological advances leveraged the world's energy consumption. This scenario has encouraged countries around the world to seek alternatives to higher energy production, being the biofuels one of the adopted alternatives, which ethanol has excelled. Therefore, the plant biomass degradation for the release of structural sugars from plant fiber fermentation has intensified. Ethanol is the main Brazilian biofuel and the use of plant biomass is an alternative for increasing its production. However, inefficient enzymatic action in the degradation of structural polysaccharides prevents industrial production. One solution is the prospect of biomass degrading enzymes and an environment for this search may be the rumen, which is an environment rich in microorganisms that degrade lignocellulose. Whereas about 99% of the microorganisms are not amenable to traditional growth, in order to break these limitations was used a metagenomics approach in this study to characterize genes with potential to degrade biomass and to evaluate the taxonomic diversity of bovine rumen environment. Rumen samples were collected from Nelore cattle for obtaining total DNA, which was subsequently sequenced by SQ HiScan (Illumina) sequencer. Sixtyfive million sequences were obtained, each with a 100 bp, which were analyzed by MG-RAST server. In order to mount the taxonomic profile of this metagenomic we used three databases on the analysis of sequences: Ribosomal Database Project (RDP), which found 18 phyla in the sample; GreenGenes, which found 16 phyla; and SILVA Small subunit (SSU) which found 22 phyla. Among all the phyla, Firmicutes was the most abundant, followed by Bacteroidetes and Proteobacteria by the three databases. For the functional analysis were used five databases for prospecting glycoside Hydrolases ...