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Evaluation of next-generation sequencing as a tool for determining the presence of pathogens in clinical samples
University of Skövde, School of Bioscience.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 30 credits / 45 HE creditsStudent thesis
Abstract [en]

Metagenomic sequencing is an increasingly popular way of determining microbial diversity from environmental and clinical samples. By specifically targeting the 16S rRNA gene found in all bacteria, classifications of pathogens can be determined based on the variable and conserved regions found in the gene. Metagenomic sequencing can therefore highlight the vast difference in microbiological diversity between culture-dependent and culture-independent methods. Today, this has expanded into various next-generation sequencing platforms which can provide massively parallel sequencing of the target fragment. One of these platforms is Ion-torrent, which can be utilized for targeting the 16S rRNA gene and with the help of bioinformatics pipelines be able to classify pathogens using the bacteria’s own variable and conserved regions. The overall aim of the present work is to evaluate the clinical use of Ion-torrent 16S ribosomal RNA sequencing for determining pathogenic species from clinical samples, but also to set up a pipeline for clinical practice. Optimal DNA-extraction and quantification methods were determined towards each evaluated sample-type and DNA-eluates were sent for 16S rRNA Sanger and Next-generation sequencing. The result indicated that the next-generation sequencing shows a concordance in results towards the culturing-based method, but also the importance of experimental design and effective quality trimming of the NGS data. The conclusion of the project is that the Ion-torrent pipeline provided by the Public Health Agency of Sweden shows great promise in determining pathogens from clinical samples. However, there is still a lot of validation and standardisations needed for the successful implementation into a clinical setting.

Place, publisher, year, edition, pages
2019. , p. 44
Keywords [en]
NGS, next generation sequencing, clinical microbiology, systems biology
National Category
Bioinformatics and Systems Biology Microbiology
Identifiers
URN: urn:nbn:se:his:diva-17374OAI: oai:DiVA.org:his-17374DiVA, id: diva2:1334559
External cooperation
Unilabs Skövde
Subject / course
Systems Biology
Educational program
Biomarkers in Molecular Medicine - Master's Programme 120 ECTS
Supervisors
Examiners
Available from: 2019-07-03 Created: 2019-07-03 Last updated: 2019-07-03Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Language
  • de-DE
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  • Other locale
More languages
Output format
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