Miniaturization of biological analysis is a trend in the field of biotechnology aiming to increase resolution and sensitivity in biological assays. Decreasing the reaction volumes to analyze fewer analytes in each reaction vessel enables the detection of rare analytes in a vast background of more common variants. Droplet microfluidics is a high throughput technology for the generation, manipulation and analysis of picoliter scale water droplets an in immiscible oil. The capacity for high throughput processing of discrete reaction vessels makes droplet microfluidics a valuable tool for miniaturization of biological analysis. In the first paper, detection methods compatible with droplet microfluidics was expanded to include SiNR FET sensors. An integrated droplet microfluidics SiNR FET sensor device capable of extracting droplet contents, transferring a train of droplets to the SiNR to measure pH was implemented and tested. In paper II, a workflow was developed for scalable and target flexible multiplex droplet PCR using fluorescently color-coded beads for target detection. The workflow was verified for concurrent detection of two microorganisms infecting poultry. The detection panel was increased to multiple targets in one assay by the use of target specific capture probes on color-coded detection beads. In paper III, droplet microfluidics has been successfully applied to single cell processing, demonstrated in paper III, where reverse transcription was performed on 65000 individually encapsulated mammalian cells. cDNA yield was approximately equivalent for reactions performed in droplets and in microliter scale. This workflow was further developed in paper IV to perform reverse transcription PCR in microfluidic droplets for detection of exosomes based on 18S RNA content. The identification of single exosomes based on RNA content can be further developed to detect specific RNA biomarkers for disease diagnostics. Droplet microfluidics has great potential for increasing resolution in biological analysis and to become a standard tool in disease diagnostics and clinical research. / <p>QC 20171024</p>
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-216669 |
| Date | January 2017 |
| Creators | Söderberg, Lovisa |
| Publisher | KTH, Skolan för bioteknologi (BIO), Science for Life Laboratory, SciLifeLab, Stockholm |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Doctoral thesis, comprehensive summary, info:eu-repo/semantics/doctoralThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | TRITA-BIO-Report, 1654-2312 ; 2017:15 |
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