https://doi.org/10.17113/ftb.56.02.18.5393 

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

Ranko Gacesa^1,2,3#, Damir Baranasic^1,4#, Antonio Starcevic^1,5, Janko Diminic^1,5, Marino Korlević⁶, Mirjana Najdek⁶, Maria Blažina⁶, Davor Oršolić¹, Domagoj Kolesarić¹, Paul F. Long^2,3, John Cullum⁴, Daslav Hranueli^1,5, Sandi Orlic^7,8 and Jurica Zucko^1,5*

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

Summary:
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.

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^#These authors contributed equally to this work