Prospecção de genes de interesse biotecnológico : uma abordagem metagenômica

• Autor(a) principal: Silva, Rita de Cássia Barreto da
• Data de Publicação: 2009
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFRN
• Texto Completo: https://repositorio.ufrn.br/jspui/handle/123456789/16763
• topic: Metagenoma; Biotecnologia; Hidrolases; Reparo de DNA; Biossurfactantes; Metagenome; Biotechnology; Hydrolases; DNA repair; Biosurfactants; CNPQ::CIENCIAS BIOLOGICAS::BIOQUIMICA::BIOLOGIA MOLECULAR

The total number of prokaryotic cells on Earth has been estimated at 4 to 6x1030 and only about 1% of microorganisms present in the environment can be cultivated by standard techniques of cultivation and plating. Therefore, it is a huge biological and genetic pool that can be exploited, for the identification and characterization of genes with biotechnological potential. Within this perspective, the metagenomics approach was applied in this work. Functional screening methods were performed aiming to identify new genes related to DNA repair and / or oxidative stress resistance, hydrocarbon degradation and hydrolytic activities (lipase, amylase and protease). Metagenomic libraries were built utilizing DNA extracted from soil samples collected in João Câmara RN. The libraries were analyzed functionally using specific substrate containing solid medium (hydrolytic activity), supplemented with H2O2 (DNA repair and / or resistance to oxidative stress) and liquid medium supplemented with light Arabian oil (activity, degradation of hydrocarbons). After confirmation of activity and exclusion of false-positive results, 49 clones were obtained, being 2 positive for amylase activity, 22 resistant to oxidative stress generated by H2O2 and 25 clones active for hydrocarbons degradation. Analysis of the sequences showed hypothetical proteins, dienelactona hydrolase, DNA polymerase, acetyltransferase, phosphotransferase, methyltransferase, endonucleases, among other proteins. The sequence data obtained matched with the functions tested, highlighting the success of metagenomics approaches combined with functional screening methods, leading to very promising results