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In-silico gene mining, characterisation and the phylogenetic relationships of bacteriocins from selected phyla
Dissertation (MSc)--University of Pretoria, 2018.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2019
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| _version_ | 1867613499440496640 |
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| access_status_str | Open Access |
| author2 | Beukes, Mervyn |
| author_browse | Beukes, Mervyn |
| author_facet | Beukes, Mervyn |
| collection | Thesis |
| dc_rights_str_mv | © 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Dissertation (MSc)--University of Pretoria, 2018. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/70703 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:37:07.296Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/70703 In-silico gene mining, characterisation and the phylogenetic relationships of bacteriocins from selected phyla Beukes, Mervyn ilana.krieg@gmail.com Krieg, Ilana Lucille UCTD Phylogeny Protein In-silico study Gene mining Physiochemical classification Dissertation (MSc)--University of Pretoria, 2018. Bacteriocins are post-translationally modified antimicrobial peptides of bacterial origin. Bacteriocins have been suggested for various applications including food preservation and alternates to antibiotic treatments. Over the last 2 decades discovery of these peptides evolved from expensive, time-consuming lab based screening methods to reasonably high throughput computer-based alternatives via in silico gene mining such as BAGEL. In this project 932 genomes were mined for the presence of bacteriocin gene clusters. Of the 932, a total of 11 Eukaryotic genomes were used as a negative control. Analysis was performed to identify the type of bacteriocins and distribution amongst following phyla: Actinobacteria, BV4, Firmicutes, Glidobacteria and Proteobacteria. Novel bacteriocins identified were characterised in silico with respect to their physiochemical properties, including molecular weight, pI, extinction coefficient, aliphatic index, hydropathy index and estimated half-life in mammalian cells, yeast and bacteria. Characterisation of the 3D structures was done by homology modelling. All bacteriocins of the Actinobacteria, Firmicutes and Proteobacteria were then subjected to phylogenetic analysis. In this study the in silico mining of 932 genomes identified 407 novel bacteriocins. The physiochemical characterisation and homology models provide predicted chemical and structural characteristics of the identified bacteriocins. Sequence alignments indicate conservation of genetic clusters within the phyla. Phylogenetic trees were inferred from these alignments to study evolutionary relationships between bacteriocins and between producer species. The phylogeny of these species interestingly supports horizontal as well as lateral gene transfer patterns. The findings from this project will assist in laboratory investigations to further explore the growing field of bacteriocins and their possible application. Biochemistry MSc unrestricted 2019-07-12T13:22:37Z 2019-07-12T13:22:37Z 2019-07-01 2018 Dissertation Krieg, IL 2018, In-silico gene mining, characterisation and the phylogenetic relationships of bacteriocins from selected phyla, MSc Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/70703> S2019 http://hdl.handle.net/2263/70703 en © 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | UCTD Phylogeny Protein In-silico study Gene mining Physiochemical classification In-silico gene mining, characterisation and the phylogenetic relationships of bacteriocins from selected phyla |
| title | In-silico gene mining, characterisation and the phylogenetic relationships of bacteriocins from selected phyla |
| title_full | In-silico gene mining, characterisation and the phylogenetic relationships of bacteriocins from selected phyla |
| title_fullStr | In-silico gene mining, characterisation and the phylogenetic relationships of bacteriocins from selected phyla |
| title_full_unstemmed | In-silico gene mining, characterisation and the phylogenetic relationships of bacteriocins from selected phyla |
| title_short | In-silico gene mining, characterisation and the phylogenetic relationships of bacteriocins from selected phyla |
| title_sort | in silico gene mining characterisation and the phylogenetic relationships of bacteriocins from selected phyla |
| topic | UCTD Phylogeny Protein In-silico study Gene mining Physiochemical classification |
| url | http://hdl.handle.net/2263/70703 |