getpdf  NLM-PubMed-Logo 

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

Ranko Gacesa1,2,3#orcid tiny, Damir Baranasic1,4#orcid tiny, Antonio Starcevic1,5orcid tiny, Janko Diminic1,5orcid tiny, Marino Korlević6orcid tiny, Mirjana Najdek6orcid tiny, Maria Blažina6orcid tiny, Davor Oršolić1orcid tiny, Domagoj Kolesarić1orcid tiny, Paul F. Long2,3orcid tiny, John Cullum4orcid tiny, Daslav Hranueli1,5orcid tiny, Sandi Orlic7,8orcid tiny and Jurica Zucko1,5*orcid tiny

1Faculty of Food Technology and Biotechnology, University of Zagreb, Pierottijeva 6, HR-10000 Zagreb, Croatia
2Institute of Pharmaceutical Science King’s College London, Franklin-Wilkins Building, Stamford Street, London SE1 9NH, UK
3Department of Chemistry, King’s College London, Franklin-Wilkins Building, Stamford Street, London SE1 9NH, UK
4Department of Genetics, University of Kaiserslautern, Postfach 3049, DE-67653 Kaiserslautern, Germany
5Centre of Research Excellence for Marine Bioprospecting - BioProCro, Ruđer Bošković Institute, Bijenička cesta 54, HR-10000 Zagreb, Croatia
6Centre for Marine Research, Ruđer Bošković Institute, G. Paliaga 5, HR-52210 Rovinj, Croatia
7Ruđer Bošković Institute, Bijenička cesta 54, HR-10000 Zagreb, Croatia
8Center of Excellence for Science and Technology Integrating Mediterranean Region, Microbial Ecology, HR-10000 Zagreb, Croatia

Article history:
Received: 16 June 2017
Accepted: 12 February 2018

Key words:
oil pollution, n-alkane degradation, database

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 (, 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.

*Corresponding author:  tel3  +38514605151
                                           fax2  +38514836083
                                            email3  This email address is being protected from spambots. You need JavaScript enabled to view it.

#These authors contributed equally to this work