Comparative genomics of Listeria species isolated from the meat processing chain in South Africa

dc.contributor.advisorReva, Oleg N.
dc.contributor.coadvisorPierneef, Rian Ewald
dc.contributor.emailmafunathendo@gmail.comen_US
dc.contributor.postgraduateMafuna, Thendo
dc.date.accessioned2022-12-07T10:31:46Z
dc.date.available2022-12-07T10:31:46Z
dc.date.created2023-04-23
dc.date.issued2022
dc.descriptionThesis (PhD (Bioinformatics))--University of Pretoria, 2022.en_US
dc.description.abstractThis thesis, Comparative genomics of Listeria species isolated from the meat processing chain in South Africa, explores the applications of Whole Genome Sequencing (WGS) of meat products isolated from food and food processing facilities to enhance understanding of the overall distribution of genomic elements that contribute toward the pathogenicity and survival of Listeria spp. including L. monocytogenes, L. innocua, and L. welshimeri in food and food processing environments. The work in this thesis adds to the exponentially increasing body of evidence on the pathogen surveillance application of WGS in food industries. This study is to date the largest to report baseline data on the presence of Listeria spp. including L. monocytogenes, L. innocua, and L. welshimeri’s serogroups, lineages, Sequence Types, and Clonal Complexes across the meat value chain in SA. This study further highlights the association of multiple STs of Listeria spp. to different meat products in SA and their resistance and virulence traits as well as genetic mutations of certain subgroups found in food products. This study also showed how these pathogens thrive in different environments and conditions by developing tolerance and resistance against such factors. This thesis further explores the development of a rapid online tool for sequence typing of Listeria spp. from Next Generation Sequencing raw data The insights from this work directly informed the incorporation of WGS into the national surveillance of Listeria spp. and the information generated here can be used in food safety risk assessment, management, and protection public health.en_US
dc.description.availabilityUnrestricteden_US
dc.description.degreePhD (Bioinformatics)en_US
dc.description.departmentBiochemistry, Genetics and Microbiology (BGM)en_US
dc.description.sponsorshipDepartment of Agriculture, Forestry and Fisheries (DAFF)en_US
dc.description.sponsorshipAgricultural Research Council (ARC)en_US
dc.description.sponsorshipNational Research Foundation (NRF)en_US
dc.identifier.citation*en_US
dc.identifier.doihttps://doi.org/10.25403/UPresearchdata.21682877en_US
dc.identifier.otherA2023
dc.identifier.urihttps://repository.up.ac.za/handle/2263/88689
dc.identifier.uriDOI: https://doi.org/10.25403/UPresearchdata.21682877
dc.language.isoenen_US
dc.publisherUniversity of Pretoria
dc.rights© 2022 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.
dc.subjectUCTDen_US
dc.subjectComparative genomicsen_US
dc.subjectListeriaen_US
dc.subjectMeat processing chainen_US
dc.subjectFood industryen_US
dc.subjectWhole genome sequencing (WGS)en_US
dc.subjectFood industryen_US
dc.titleComparative genomics of Listeria species isolated from the meat processing chain in South Africaen_US
dc.typeThesisen_US

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