Bioprospecting for Genes Encoding Hydrocarbon-Degrading Enzymes from Metagenomic Samples Isolated from Northern Adriatic Sea Sediments
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...
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Published in | Food technology and biotechnology Vol. 56; no. 2; pp. 270 - 277 |
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Main Authors | , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Croatia
Sveuciliste U Zagrebu
01.06.2018
Sveuciliste u Zagrebu, Prehramheno-Biotehnoloski Fakultet University of Zagreb Faculty of Food Technology and Biotechnology |
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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
-alkane degradation. The use of this system for bioprospecting was exemplified using potential
and
genes from this library. |
---|---|
AbstractList | 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. 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.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. 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. 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 -alkane degradation. The use of this system for bioprospecting was exemplified using potential and genes from this library. 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 ( Key words: oil pollution, n-alkane degradation, database |
Audience | Academic |
Author | Kolesarić, Domagoj Cullum, John Starcevic, Antonio Korlević, Marino Oršolić, Davor Long, Paul F. Orlić, Sandi Blažina, Marijana Baranasic, Damir Hranueli, Daslav Zucko, Jurica Gacesa, Ranko Diminic, Janko Najdek, Mirjana |
AuthorAffiliation | These authors contributed equally to this work |
AuthorAffiliation_xml | – name: These authors contributed equally to this work |
Author_xml | – sequence: 1 givenname: Ranko orcidid: 0000-0003-2119-0539 surname: Gacesa fullname: Gacesa, Ranko – sequence: 2 givenname: Damir orcidid: 0000-0001-5948-0932 surname: Baranasic fullname: Baranasic, Damir – sequence: 3 givenname: Antonio orcidid: 0000-0003-2386-2124 surname: Starcevic fullname: Starcevic, Antonio – sequence: 4 givenname: Janko orcidid: 0000-0001-5104-5813 surname: Diminic fullname: Diminic, Janko – sequence: 5 givenname: Marino surname: Korlević fullname: Korlević, Marino – sequence: 6 givenname: Mirjana orcidid: 0000-0002-3915-0765 surname: Najdek fullname: Najdek, Mirjana – sequence: 7 givenname: Marijana orcidid: 0000-0002-6990-7597 surname: Blažina fullname: Blažina, Marijana – sequence: 8 givenname: Davor orcidid: 0000-0002-5385-1031 surname: Oršolić fullname: Oršolić, Davor – sequence: 9 givenname: Domagoj orcidid: 0000-0003-0831-2685 surname: Kolesarić fullname: Kolesarić, Domagoj – sequence: 10 givenname: Paul F. orcidid: 0000-0001-6410-5803 surname: Long fullname: Long, Paul F. – sequence: 11 givenname: John orcidid: 0000-0002-3850-8526 surname: Cullum fullname: Cullum, John – sequence: 12 givenname: Daslav orcidid: 0000-0001-8336-4384 surname: Hranueli fullname: Hranueli, Daslav – sequence: 13 givenname: Sandi orcidid: 0000-0002-6339-4145 surname: Orlić fullname: Orlić, Sandi – sequence: 14 givenname: Jurica orcidid: 0000-0001-7782-6503 surname: Zucko fullname: Zucko, Jurica |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30228802$$D View this record in MEDLINE/PubMed |
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CitedBy_id | crossref_primary_10_1007_s00438_023_01995_6 crossref_primary_10_1007_s11356_022_18492_9 crossref_primary_10_3389_fmicb_2021_667944 crossref_primary_10_3389_fenvs_2021_624070 crossref_primary_10_3389_fbioe_2021_804234 crossref_primary_10_1007_s00203_022_02806_z crossref_primary_10_1016_j_jece_2022_107219 crossref_primary_10_1038_s41522_022_00299_8 |
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Copyright | COPYRIGHT 2018 Sveuciliste U Zagrebu 2018. This work is published under https://creativecommons.org/licenses/by-nc/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2018 University of Zagreb Faculty of Food Technology and Biotechnology |
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CorporateAuthor | Department of Chemistry, King’s College London, Franklin-Wilkins Building, Stamford Street, London SE1 9NH, UK Faculty of Food Technology and Biotechnology, University of Zagreb, Pierottijeva 6, 10000 Zagreb, Croatia Centre for Marine Research, Ruđer Bošković Institute, G. Paliaga 5, 52210 Rovinj, Croatia Institute of Pharmaceutical Science King’s College London, Franklin-Wilkins Building, Stamford Street, London SE1 9NH, UK Department of Genetics, University of Kaiserslautern, Postfach 3049, 67653 Kaiserslautern, Germany Centre of Research Excellence for Marine Bioprospecting - BioProCro, Ruđer Bošković Institute, Bijenička cesta 54, 10000 Zagreb, Croatia Ruđer Bošković Institute, Bijenička cesta 54, 10000 Zagreb, Croatia Center of Excellence for Science and Technology Integrating Mediterranean Region, Microbial Ecology, 10000 Zagreb, Croatia |
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SubjectTerms | Alkanes Biodegradation Biodiversity Bioinformatics Bioprospecting Bioremediation Crude oil Degradation Deoxyribonucleic acid DNA Enzymes Functional analysis Genes Genetic code Genomes Genomics Hydrocarbon-degrading enzymes Hydrocarbons Markov chains Markov processes n-alkane degradation oil pollution Oil spills Petroleum Proteins Relational data bases Scientific Notes Sediment samplers Sediments Taxonomy |
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Title | Bioprospecting for Genes Encoding Hydrocarbon-Degrading Enzymes from Metagenomic Samples Isolated from Northern Adriatic Sea Sediments |
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