Manual and robotic RNA extraction from human plasma with absolute quantification of miRNA through two-tailed RT-qPCR as part of research into early diagnosis of sepsis

Abstract: Each hour´s delay in administering antibiotics has been shown to result in a 9% increase in the odds of mortality in sepsis cases. It is thus evident that the development of a diagnostic method that ensures an early time to diagnosis of sepsis is essential. MiRNAs have shown promise with regards to diagnostic capabilities concerning sepsis, with differential expression of circulatory miRNAs seen during various diseased states. MiRNA can be quantified directly from a blood plasma sample, greatly decreasing the time to diagnosis, as the requirement for culturing is eliminated. Quantification of miRNA by means of qPCR has proven rather challenging, due to their short length. A solution might be two-tailed RT-qPCR, a method which utilizes a two-tailed RT primer. The aim of the project was to optimize the extraction and quantification of miRNAs from minimal amounts of human blood plasma samples, as to create a standardized and reproduceable method for measuring biomarker miRNAs within human blood plasma. In this study, a significant difference between manual and semi-automated extraction of miRNA from plasma with regards to A260/A280 ratios (p = 0.00) was observed. It was also found that a correlation exists between A260/A280 ratios and miR-seps6 quantified, using the two-tailed RT-qPCR method. This method has shown to be effective at amplifying circulating miR-seps6 arising from 100 µL of human blood plasma. A linear standard curve, constructed from synthetic miR-seps 6 produced optimal amplification efficiencies, and the melt curve indicated a single product, which correlates with good specificity. As successful detection and amplification of miR-seps 6 had been achieved during this study, the next phase of the project can be initiated, where it will be attempted to detect miR-seps 6 from plasma stored in a human biological material bank (biobank).