Return to search

Sepsis and circulating miRNA : The road towards absolute quantification of unknown miRNA levels in plasma utilizing two-tailed RT-qPCR, while testing two extraction methods, striving to create multi-marker panel for sepsis diagnosis

Sepsis is a preventable yet life threatening condition, resulting from body response to infection. Time is crucial in sepsis diagnosis since deterioration in patients’ health can occur rapidly. Blood culturing is the gold standard for diagnosis, along with clinical assessment. The discovery of miRNA in biofluids as a biomarker, founded the way for extensive research on its capabilities. MiRNA showed promises in diagnosing, assessing outcome and reporting sepsis progression. Since being delicate to handle while present in biofluid, the need was uttermost to find an effective way for miRNA isolation and detection, to facilitate developing multi-marker panel that help diagnosing sepsis, more efficiently than blood culturing. The current study aimed at using manual and robotic (QIAcube) methods, with MiRNeasy Serum/Plasma Advanced (Qiagen) as kit and protocol, to extract miRNA from human plasma samples. Plasma was either spiked with synthetic miR-223 to act as a positive control, or non-spiked. Once extraction was done, quality-quantity assessment was conducted using Qubit and Nanodrop. Two-tailed RT-qPCR (TATAA Biocenter) was used for miRNA quantification. QIAcube showed better results in quantity, hands-on and turn-around time compared to manual extraction, while better purity was scored for the manual method. While amplification appeared in all spiked samples, absolute quantification detected miRNA in some of the non-spiked samples. The study verified using the extraction kit with 100 μl of plasma is effective for miRNA extraction. Although faced with difficulties, absolute quantification using two-tailed RT-qPCR demonstrates its success in detecting lowly expressed miRNA. Future studies are needed for more optimized verification.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:his-20235
Date January 2021
CreatorsElawad, Hazzim
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

Page generated in 0.0019 seconds