Sepsis is an often fatal, critical health condition that arises when the body’s reaction to an infection systemically damages its own tissues and organs. The reality of sepsis is that it can kill within four to twelve hours from the incidence of symptoms. As of 2017, sepsis accounts for one in five deaths worldwide. The current golden standard for diagnosis is blood culturing, which requires 72 hours to cultivate and identify the pathogen and may yield no results due to low microbial concentration in the blood stream. The future diagnostics of sepsis project aimed to reduce the time from admission to sepsis diagnosis by investigating new methods of microbial DNA extraction from spiked whole human blood. The extracted DNA was sequenced through the MinION device, a new technology developed by Oxford Nanopore Technologies. A metataxonomic analysis of the results was then conducted to identify microbes to a species accurate level. The newly investigated methods were successful in isolating microbial DNA from spiked whole human blood. The metataxonomic identification analysis was conducted through the EPI2ME platform using the Fastq What’s In My Pot directory. Although the barcoding system did not work as intended, the analysis resulted in two fully developed taxonomic trees in which the most identified taxa belonged to the Staphylococcus family. This study is a first that moves forward, towards a new day. A day in which hopefully we are able to provide early and precise care, and see more and more patients fully recover. / <p>Det finns övrigt digitalt material (t.ex. film-, bild- eller ljudfiler) eller modeller/artefakter tillhörande examensarbetet som ska skickas till arkivet.</p><p>There are other digital material (eg film, image or audio files) or models/artifacts that belongs to the thesis and need to be archived.</p>
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:his-21699 |
| Date | January 2022 |
| Creators | Savaia, Adriana |
| Publisher | Högskolan i Skövde, Institutionen för biovetenskap |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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