Literature DB >> 30228802

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

Ranko Gacesa1,2,3, Damir Baranasic1,4, Antonio Starcevic1,5, Janko Diminic1,5, Marino Korlević6, Mirjana Najdek6, Maria Blažina6, Davor Oršolić1, Domagoj Kolesarić1, Paul F Long2,3, John Cullum4, Daslav Hranueli1,5, Sandi Orlic7,8, Jurica Zucko1,5.   

Abstract

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.

Entities:  

Keywords:  database; n-alkane degradation; oil pollution

Year:  2018        PMID: 30228802      PMCID: PMC6117985          DOI: 10.17113/ftb.56.02.18.5393

Source DB:  PubMed          Journal:  Food Technol Biotechnol        ISSN: 1330-9862            Impact factor:   3.918


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