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Evaluation of Oxford nanopore’s MinION: Use, functionality, and genome assembly
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]

The rapid and reliable detection of pathogens is of utmost importance in healthcare settings to ensure the appropriate treatment thereby reducing morbidity and mortality for the patient. Current culturing, PCR based and NGS species detection methods are time consuming (Opota et al., 2015), limited in their detection (Buckley et al., 2015), or require specialist skills and are expensive (Basho and Eterovic., 2015). Oxford Technologies Nanopore devices could provide detailed genomic sequencing at a fraction of the cost and without the need for technical bioinformatic skills. This study evaluates the MinION device and analysis tools to suggest best practice. Classification and genotyping of 12 Klebsiella isolates were performed using EPI2ME automated workflows and manual de novo assembly.  Automated workflows using raw MinION reads provided clinically relevant information identified in ~6hrs. Manual de novo assembly and analysis used hybrid, and single source data took >24hrs. The inclusion of MinION long reads overcome problems assembling short reads. Hybrid genomes provided the most contiguous and highly detailed contigs. MinION only read assemblies contained more errors but still identified similar genotypic findings. Automated workflows are rapid and require minimal bioinformatic know-how. There should be a dialogue between clinicians and bioinformaticians to develop bespoke analysis tools.  Although challenges remain around compatible kits and vulnerable flowcells long read sequencing can be an effective tool for species detection and pathogen typing. Furthermore, hybrid assemblies have the potential to advance our genome detailing and discovery.

Place, publisher, year, edition, pages
2019. , p. 57
Keywords [en]
MinION, Genome, Klebsiella, NGS
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:his:diva-17367OAI: oai:DiVA.org:his-17367DiVA, id: diva2:1334252
Subject / course
Systems Biology
Educational program
Molecular Biotechnology - Master's Programme, 120 ECTS
Presentation
2019-06-05, 13:00 (English)
Supervisors
Examiners
Available from: 2019-07-03 Created: 2019-07-02 Last updated: 2019-07-03Bibliographically approved

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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