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Assessment of manual and robotic miRNAs extraction methods with optimization of the two-tailed RT-qPCR technology for miRNAs detection as biomarkers from human plasma for early sepsis diagnosis : Future diagnostics of sepsis

Sepsis is a life-threatening syndrome that occurs due to dysregulated body response to pathogenic infections. More than 30 million cases are recorded annually worldwide, with a high mortality rate of up to 40% of the recorded cases. Early diagnosis of sepsis will help clinicians to start proper therapy as early as possible and save lives. Circulating miRNAs in biofluids were found previously as potential biomarkers that can be used in a multi-marker panel to develop a rapid, friendly user diagnostic kit for the early sepsis diagnosis. This study assessed miRNAs from healthy donors’ human plasma by two extraction methods, manually and robotically via QIAcube. In addition to optimizing two-tailed RT-qPCR (TATAA Biocenter) technology for miRNAs detection and quantification. The extraction of miRNAs was using miRNeasy® Serum/Plasma Advanced kit (Qiagen) for the two methods. Plasma was spiked in with synthetic miRNA-210 to ensure miRNA detection and was used as a positive control for the study. The concentration and the purity of the RNA eluates were measured and statistically analyzed to identify which method could be better in conventional laboratory practice. QIAcube results showed its ability to compete with manual RNA extraction protocols. However, more studies are required for RNA extractions with different kits using QIAcube. The two-tailed RT-qPCR technology successfully detected many miRNAs, but more samples are required to be tested for accurate conclusions. The results emphasize the ability of two-tailed RT-qPCR to detect and quantify miRNAs from human plasma as potential biomarkers in a multi-marker panel for early sepsis diagnosis.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:his-20233
Date January 2021
CreatorsYoussef, Nermeen
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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