Microfluidic techniques for lysing, purification and bead-based detection of RNA from complex samples [electronic resource]

This dissertation describes three techniques aimed at automated, sensitive sample preparation and detection of RNA from complex samples. Microfluidic systems have advanced the state of the art for a wide number of chemical and biological assays, but robust and efficient sample preparation remains a major challenge. One of the most difficult processes is the lysing, purification, and detection of target RNA from whole blood samples. This dissertation addresses key challenges in each of these RNA workflow phases. In the first part of the dissertation, we demonstrate a novel assay for lysing followed by physicochemical extraction and isotachophoresis-based purification of 16S ribosomal RNA from whole human blood infected with Pseudomonas Putida. This assay is unique in that the extraction can be automated on-chip using isotachophoresis in a simple device with no moving parts, it protects RNA from degradation when isolating from ribonuclease-rich matrices (like blood), and produces a purified total nucleic acid (NA) sample which is compatible with enzymatic amplification assays. We show that the purified RNA are compatible with reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and demonstrate a clinically relevant sensitivity of 0.03 bacteria per nanoliter using RT-qPCR. In the second part of the dissertation, we present a model to aid in design and optimization of a wide range of electrophoresis (including isotachophoresis) assays. Our model captures the important contributors to the effects of temperature on the observable electrophoretic mobilities of small ions, and on solution ionic strength, conductivity and pH; the most relevant parameters in molecular reactions and separation assays. Our temperature model includes relations for temperature-dependent viscosity, ionic strength corrections, degree of ionization (pK), and ion solvation effects on mobility. We incorporate thermophysical data for water viscosity; temperature-dependence of the Onsager-Fuoss model for finite ionic strength effects on mobility; temperature-dependence of the extended Debye-Huckel theory for correction of ionic activity; the Clarke-Glew approach and tabulated thermodynamic quantities of ionization reaction for acid dissociation constants as a function of temperature; and species-specific, empirically evaluated correction terms for temperature-dependence of Stokes' radii. We incorporated our model into a MATLAB-based simulation tool we named Simulation of Temperature Effects on ElectroPhoresis (STEEP). We validated our model using conductance and pH measurements across a temperature variation of 25°C to 70°C for a set of electrolytes routinely used in electrophoresis. The model accurately captures electrolyte solution pH and conductivity, including important effects not captured by simple Walden type relations. In the third and final part of the dissertation, we introduce a cost-effective and simple-to-implement method for direct detection of RNA, by analyzing images of randomly distributed multicolor fluorescent beads bound by the target molecule. We term our method particle imaging, tracking and collocation (PITC). We use a fairly standard epifluorescence microscopy setup fitted with an off-the-shelf dual view color separator attachment which images fluorescence emission at two wavelengths onto two respective halves of a single CCD image array. We perform automated analysis of these two color channels to track thousands of particle images in either or both wavelengths, and we track particle image motion in time and space. We can quantify particle image wavelength (or wavelength ratio), absolute intensities, and particle image diameter. We also perform cross-correlation image analyses on this multi-wavelength data to track particle collocations and the degree of correlation of particle motion. Particles or cells can be suspended in solution and flowed through a wide variety of microchannels (with optical access for image collection). Particles can be transported through the detection region via electrophoresis and/or pressure driven flow, to increase throughput of analysis. We here introduce and evaluate the performance of our method. We use Monte Carlo simulations to demonstrate robustness of the algorithm and optimize algorithm parameters. We present an experimental demonstration of the method on challenging image data, including flow of randomly distributed Brownian particles and particle populations which undergo particle-to-particle binding. We show results of bead collocation measurements on bead-to-bead binding created by the E.coli 16S rRNA gene.

Keywords: Mechanical Engineering.
Advisor: Santiago Juan G. primary advisor. Thesis advisor
Goodson Kenneth E.
Kenny Thomas William advisor. Thesis advisor