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|Title:||Concentration gradient generation for microfluidic applications||Authors:||Toh, Alicia Guek Geok||Keywords:||DRNTU::Engineering::Mechanical engineering||Issue Date:||2016||Source:||Toh, A. G. G. (2016). Concentration gradient generation for microfluidic applications. Doctoral thesis, Nanyang Technological University, Singapore.||Abstract:||Microfluidic concentration gradient generators (µCGG) are a unique class of fluidic devices that can be used to produce rapidly programmable, repeatable and precise concentration landscapes for biological applications. The miniaturization of length and time scales in µCGGs has greatly improved the accuracy and control of concentration gradients, as compared to traditional techniques that utilize static diffusion chambers. However, the spatio-temporal control of chemical gradients with insignificant flow induced shear effects has proved difficult due to two conflicting mass transport mechanisms. The high temporal resolution for concentration gradient control is achieved at the expense of increasing flow rates which thereupon, results in strong flow induced shear effects. Due to this limitation, fast microfluidic gradient generation exposes cells to flow shear levels that may not be present in their native microenvironments. The presence of shear may elicit cell responses which differ greatly from that exhibited in-vivo. This dissertation presents a systematic and in-depth investigation of using stagnation flows to control binary and combinational concentration gradients in low flow shear environments. Stagnation flows, characterized by their diminishing velocity fields that surround a stagnation point, are used to precisely confine concentration gradients under low flow shear conditions. Analogous to the confinement effects in potential wells, it is hypothesized that the diminishing flow fields around the stagnation point could function as fluid velocity wells. These velocity wells could be used to hydrodynamically confine and control concentration gradients that are formed between concentration sources and sinks. A stagnation flow gradient generator is designed by making modifications to the conventional cross-slot design. Concentration generation of binary and combinational chemical species within the modified cross-slot (MCS) device is tested and evaluated. The concentration gradients formed across the stagnation velocity well is studied with respect to velocity well steepness. The effect of flow rate on velocity well steepness, flow shear stress, concentration gradient length and time to gradient stability is studied and characterized by introducing the dimensionless Péclet number. The Péclet number characterizes the balance between convection and diffusion. Experimental and numerical results show that the Péclet number is inversely scaled to gradient length but has a direct correlation to velocity well steepness, flow shear stress and time to gradient stability. This trend confirms the hypothesis that the stagnation flow can be used to control both temporal and physical parameters related to concentration gradient generation in velocity wells. In this thesis, Chapter 1 introduces the background and motivation of this work, followed by a review of the state-of-the-art in microfluidic gradient generation, its role in biological applications and a summary of current gradient generation technologies. Chapter 2 delves into the design of the stagnation flow gradient generator, the analytical and numerical models used to understand the physical parameters governing concentration gradient generation across stagnation flows. Chapter 3 covers the device fabrication, experimental setup and protocols used in gradient generation studies. Chapter 4 presents the experimental and analytical results pertaining to steady-state and transient concentration gradient confinement across stagnation flows. Chapter 5 describes experiments and numerical results regarding the use of stagnation flows to hydrodynamically confine and control both binary and combinational concentration gradient landscapes. Chapter 6 discusses the results obtained from biological experiments in which the individual cell sensing characteristics of Pseudomonas Aeruginosa (P. Aeruginosa) cells were studied in response to rapid temporal stimuli from a chemoattractant. Chapter 7 summarizes the findings of this thesis research and also provides recommendations for future areas of research. Experiment results revealed that binary and combinational concentration gradients can be confined and stretched across velocity wells that are produced in stagnation flows. During concentration gradient generation, the convection- diffusion processes across the stagnation flow were found to have a direct correlation to the flow strain rate. Based on linear flow analysis, the flow strain rate is a key parameter in determining the characteristic flow velocities and Pé number of flows within the MCS device. Proper length and time scaling through the introduction of this Pé number results in a simplified analytical model that was used to describe the spatiotemporal characteristics of concentration gradient formation across stagnation flows. Experiments revealed that near the stagnation point, concentration gradient lengths of 85 µm to 350 µm are directly controllable while maintaining low flow-induced shear stresses. In line with the hypothesis, it was found that the stabilization and spatial movement of concentration gradients can be achieved rapidly, at temporal resolutions of 3s or less. The results highlight the efficacy of stagnation flows, and its velocity wells to produce low flow shear concentration gradients within short characteristic times. Finally, this gradient generation approach was used to study freely rotating, tethered Pseudomonas Aeruginosa cells, in the presence of a fast changing chemoattractant microenvironment. As stagnation flow within the MCS device can be controlled dynamically, this allows us to test both the chemotactic response and adaptation of individual P. Aeruginosa cells. Stagnation flow within the MCS device was leveraged to study these cells since shear stresses as low as 2.4 mPa were found to adversely influence cell sensing and flagellum rotation during chemotaxis. Cell responses were studied in two scenarios- an abrupt enrichment and depletion of a chemoattractant (L-Serine) within the cells’ microenvironment. Enrichment of the cells’ microenvironment was achieved by flowing L-Serine into the stagnation chamber, thereby producing a ramp-up chemoattractant signal. On the other hand, stagnation flow introducing M9 medium (the control buffer) into the stagnation chamber produced a ramp-down in the chemoattractant signal. In both scenarios, chemoattractant signaling was achieved within 3s or less, thereby minimizing any data convolution resulting from signaling kinetics. In their pre-stimulus state, cells were found to spend equivalent durations in either clockwise or counter-clockwise rotational phases. This behavior was similar to control experiments performed in the petri dish. Upon exposure to ramp-up signals, cells experienced a bias in flagella rotation, allowing the cell to continue moving towards the favorable environment. However, when cells experienced the ramp-down signal, cells performed a reversal in their rotational phase, followed by a bias in the reversed rotational phase. In both cases, the rotational bias persisted for ~22s and subsequently returned to its pre-stimulus state, having little rotational bias. Calculation of the adaptation kinetics of P. Aeruginosa revealed that cells responded to ramp-up and ramp-down chemoattractant signals similarly, with an adaptation time of 88.9s and 86.8s, respectively. The work presented here revealed that P. Aeruginosa exhibits an entirely different biophysical chemotactic adaptation as compared to that reported for the model E.coli cell. The findings here suggest that differences in the flagellar apparatus and chemosensory network of cells result in a variety of chemotactic and adaptation responses. Understanding these differences can lead to the development of relevant biophysical models and bring us closer to developing and controlling artificial molecular machines. Further to the work in this thesis, it is envisioned that the spatio-temporal resolutions achieved by this novel gradient generation approach would be useful for biological studies involving shear- sensitive cells.||URI:||https://hdl.handle.net/10356/69096||DOI:||10.32657/10356/69096||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||MAE Theses|
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