Magnetophoretic Particle & Cell Manipulation In Ferrofluid Flows Using Two Magnets

Micro-particle manipulation is often required for many chemical and biological applications. Many methods implementing force fields have been explored such as electric, optical, acoustic, and magnetic. Among these, magnetic forces stand out due to its low cost and versatility. A great advantage of using magnetic field is its absence of fluid heating as seen in optical and electric. In this presentation, I present a method of particle and cell manipulation in ferrofluid flows using a pair of magnets via negative magnetophoresis. By positioning each magnet in certain configurations, particular particle behaviors can be captured and studied that include focusing, trapping/concentration, and separation/sorting. In these projects, particle diameters of 3 to 10μm are considered and suspended in commercially available ferrofluid. Furthermore, once studies with polystyrene sphere particles are found practical, live yeast cells are employed and results for manipulation and bio-compatibility are verified

MAGNETIC MANIPULATION OF PARTICLES AND CELLS IN FERROFLUID FLOW THROUGH STRAIGHT MICROCHANNELS USING TWO MAGNETS

Microfluidic devices have been increasingly used in the past two decades for particle and cell manipulations in many chemical and biomedical applications. A variety of force fields have been demonstrated to control particle and cell transport in these devices including electric, magnetic, acoustic, and optical forces etc. Among these particle handling techniques, the magnetic approach provides clear advantages over others such as low cost, noninvasive, and free of fluid heating issues. However, the current knowledge of magnetic control of particle transport is still very limited, especially lacking is the handling of diamagnetic particle. This thesis is focused on the magnetic manipulation of diamagnetic particles and cells in ferrofluid flow through the use of a pair of permanent magnets. By varying the configuration of the two magnets, diverse operations of particles and cells is implemented in a straight microchannel that can potentially be integrated into lab-on-a-chip devices for various applications. First, an approach for embedding two, symmetrically positioned, repulsive permanent magnets about a straight rectangular microchannel in a PDMS-based microfluidic device is developed for particle focusing. Focusing particles and cells into a tight stream is often required in order for continuous detection, counting, and sorting. The closest distance between the magnets is limited only by the size of the magnets involved in the fabrication process. The device is used to implement and investigate the three-dimensional magnetic focusing of polystyrene particles in ferrofluid microflow with both top-view and side-view visualizations. The effects of flow speed and particle size on the particle focusing effectiveness are studied. This device is also applied to magnetically focus yeast cells in ferrofluid, which proves to be biocompatible as verified by cell viability test. In addition, an analytical model is developed and found to be able to predict the experimentally observed particle and cell focusing behaviors with reasonable agreement. Next, a simple magnetic technique to concentrate polystyrene particles and live yeast cells in ferrofluid flow through a straight rectangular microchannel is developed. Concentrating particles to a detectable level is often necessary in many applications. The magnetic field gradient is created by two attracting permanent magnets that are placed on the top and bottom of the planar microfluidic device and held in position by their natural attractive force. The effects of flow speed and magnet-magnet distance are studied and the device was applied for use for concentrating live yeast cells. The magnet-magnet distance is mainly controlled by the thickness of the device substrate and can be made small, providing a locally strengthened magnetic field as well as allowing for the use of dilute ferrofluid in the developed magnetic concentration technique. This advantage not only enables a magnetic/fluorescent label-free handling of diamagnetic particles but also renders such handling biocompatible. Lastly, a device is presented for a size-based continuous separation of particles through a straight rectangular microchannel. Particle separation is critical in many applications involving the sorting of cells. A first magnet is used for focusing the particle mixture into a single stream due to its relative close positioning with respect to the channel, thus creating a greater magnetic field magnitude. Then, a following magnet is used to displace the aligned particles to dissimilar flow paths by placing it farther away compared the first magnet, which provides a weaker magnetic field, therefore more sensitive towards the deflection of particles based on their size. The effects of both flow speed and separator magnet position are examined. The experimental data are found to fit well with analytical model predictions. This is followed by a study replacing the particles which are closely sized to that of live yeast cells and observe the separation of the cells from larger particles. Afterwards, a test for biocompatibility is confirmed

Whole genome analyses accounting for structures in genotype data

Whole genome analysis is a powerful tool for accurately predicting the genetic merit of selection candidates and for mapping quantitative trait loci (QTL) with high resolution. Single-nucleotide polymorphism (SNP) markers that cover the entire genome unveil the information about QTL through either linkage disequilibrium (LD) with the QTL in founders or cosegregation (CS) with the QTL in nonfounders given a pedigree. Due to the advances in molecular biology and the associated drop in the cost of genotyping, the density of SNPs and the number of individuals that have phenotypes and genotypes are both increasing dramatically for whole genome analyses. Consider a matrix of genotypes collected for analysis, where rows are the genotypes of individuals across SNPs and columns are the genotypes of SNPs across individuals. As explained below, structures exist in such a genotype matrix and will become more evident and important as the SNP density and the training population size increase. Horizontally, haplotype block structures are observed across SNP loci in the genome due to the historical cosegregation, which creates LD, or recent cosegregation. These structures exist even in the gametes of a single individual. The statistical dependence of the SNP effects is therefore expected in small chromosomal segments given the presence of QTL. However, most of the methods for whole genome analyses do not account for this dependence of the SNP effects. Vertically, individuals in the pedigree will share a large proportion of alleles that are identical-by-descent (IBD) if they have a common recent ancestor, or vice versa. The genomic (IBD) relationship structure therefore manifests at each locus across individuals in the pedigree, and for closely linked loci, these structures will be very similar due to CS. Alleles that are identical-by-descent are also identical-by-state (IBS) but the inverse is not true. Thus, the genomic relationship structures may not be properly accounted for by the methods that use IBS relationships computed from SNP genotypes. Two methods, BayesN and the QTL model, have been developed in this thesis to account for the structure in the genotypes that are used for whole genome analyses. BayesN is a nested marker effects model, where SNP effects in each small genomic window are a priori considered dependent. Compared with BayesB, where the structure in the genome is ignored and SNP effects are assumed to be independently and identically distributed, BayesN gave a higher accuracy of genomic prediction for breeding values, especially when high-density SNP panels were used and the QTL had rare alleles. When BayesN was used for QTL discovery, the proportion of false positives (PFP) for finding QTL was perfectly controlled in the case of common QTL alleles and was controlled better than BayesB in the case of rare QTL alleles. At the same level of PFP, BayesN had a higher power than BayesB for detecting QTL that had rare alleles and at least 1% of the total genetic variance. The advantage of BayesN is attributed to the modeling of dependence between SNP effects such that they jointly explained more genetic variance at the QTL and shrunk the effects of SNPs not associated with QTL more toward zero. Moreover, BayesN has a benefit in computing time, which is only one-fourth of that for BayesB in the case of high-density SNP panels. The QTL model includes the effects of the unobserved QTL genotypes, and the phenotype therefore has a mixture distribution. The mixture model exploits information from the pedigree, LD and CS optimally to model the QTL allele states in founders and allele inheritance in nonfounders. Thus, the QTL model accounts for horizontal structure across loci and vertical structure across individuals because only information from the SNPs that are within a small chromosomal segment contribute to the modeling of QTL alleles in that segment. In a range of pedigree structures, the QTL model had a substantially higher accuracy than BayesC for genomic prediction when training population consisted of multiple families, generations, or breeds. The advantages of the QTL model increased with the complexity of the pedigree structure and the contribution of CS information. Furthermore, use of the QTL model permits direct inferences on the unobserved QTL. As expected, the QTL model had a better control of PFP than BayesC and a higher power for detecting any size of QTL when PFP was limited to be a small value. In this thesis, a method to calculate the credible intervals for multiple QTL locations is developed. The method presented here is straightforward and can easily be applied to other models that fit QTL effects for the unobserved genotypes. The credible intervals for the QTL locations provide important information to guide future fine-mapping studies. In QTL discovery, signal from the QTL may bleed to neighboring genomic windows depending on the structures of the genome. It is therefore suggested to search QTL in the window that has a positive test result as well as its flanking windows, or to use hypotheses that only test for large genetic variance (at least 1% of the total genetic variance for example). In conclusion, parsimonious and sophisticated methods that account for the horizontal and vertical structures in genotypes were developed for whole genome analyses. Both methods gave higher accuracy of genomic prediction and trait loci discovery than the widely used methods that ignore these structures. Both methods are expected to be more efficient with respect to computing time and performance as higher SNP densities or sequence data are used in whole genome analyses