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Method development for sepsis biomarkers : Detection and quantification of extracted microRNA using the novel two-tailed RT-qPCR method

Sepsis is a condition of the host’s extreme response to an infection affecting multiple physical functions which can lead to septic shock and death. Currently, the method for diagnosing sepsis is time-consuming and relies on multiple non-specific biomarkers such as Procalcitonin, lactate and C-reactive protein, with blood culturing being the golden standard. Recently proposed and possible sepsis-specific biomarkers are the microRNAs, which are short, ~22 nucleotide long non-coding RNAs that regulate gene expression post transcriptionally. MicroRNA expression levels have the advantage of being more specific to certain disease types, making them promising biomarkers for sepsis diagnostics. The aim of this study was to evaluate the method and performance of microRNA extraction, using microRNA spike-ins to increase concentration of said extractions, and microRNA amplification by using the novel two-tailed RT-qPCR method developed by TATAA Biocenter. Blood gathered from self-assessed healthy donors wascentrifuged to collect plasma, from which microRNA extraction was performed using the miRNeasy Serum/Plasma Advanced kit (Qiagen). Each sample was spiked with the synthetic microRNAs miR-223 or miR-let7b either before or after RNA extraction. The two-tailed RT-qPCR method was used to amplify the spiked-in microRNAs miR-223 and miR-let7b present in the extractions, and absolute quantification was used to determine the amount of those microRNA. The results conclude that spiked-in microRNA from plasma could be amplified using the twotailed RT-qPCR, and the results depended on which synthetic microRNA had been added, at what concentration and at what stage of the extraction process.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:his-20376
Date January 2020
CreatorsReihell, Isabelle
PublisherHögskolan i Skövde, Institutionen för biovetenskap
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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