Bioprospecting for Genes Encoding Hydrocarbon-Degrading Enzymes from Metagenomic Samples Isolated from Northern Adriatic Sea Sediments

• Main Authors: Ranko Gacesa, Damir Baranasic, Antonio Starcevic, Janko Diminic, Marino Korlević, Mirjana Najdek, Maria Blažina, Davor Oršolić, Domagoj Kolesarić, Paul F. Long, John Cullum, Daslav Hranueli, Sandi Orlic, Jurica Zucko
• Format: Article
• Language: English
• Published: University of Zagreb 2018-01-01
• Series: Food Technology and Biotechnology
• Subjects: oil pollution; n-alkane degradation; database
• Online Access: http://hrcak.srce.hr/file/299544

Three metagenomic libraries were constructed using surface sediment samples from the northern Adriatic Sea. Two of the samples were taken from a highly polluted and an unpolluted site respectively. The third sample from a polluted site had been enriched using crude oil. The results of the metagenome analyses were incorporated in the REDPET relational database (http://redpet.bioinfo.pbf.hr/REDPET), which was generated using the previously developed MEGGASENSE platform. The database includes taxonomic data to allow the assessment of the biodiversity of metagenomic libraries and a general functional analysis of genes using hidden Markov model (HMM) profiles based on the KEGG database. A set of 22 specialised HMM profiles was developed to detect putative genes for hydrocarbon-degrading enzymes. Use of these profiles showed that the metagenomic library generated after selection on crude oil had enriched genes for aerobic n-alkane degradation. The use of this system for bioprospecting was exemplified using potential alkB and almA genes from this library.