A novel method for the manipulation of biological cells using fluid flow and realtime control

2017-02-27T02:04:35Z (GMT) by Curtis, Michael David
Cells are complex, with respect to both their biochemistry and mechanical properties. This complexity is multiplied further by the increasing body of evidence that the biochemical properties and mechanical properties may, in many cases, be intrinsically linked. Therefore, there is a clear unmet need for sophisticated and automated measurement tools that can produce quantitative measurements of cell deformation and cell responses to forces. In particular, the time-dependent response of cells to imposed force is of interest to the biological sciences, but there is a lack of tools that can measure this aspect of cell behaviour. Automation brings the capability to measure whole populations of cells and thereby provide both statistical relevance and repeatability. This is especially important in biological samples, which are known to vary widely in properties and behaviour on both an intra- and inter-sample basis. In this thesis, the technology and capabilities have been developed that allow, for the first time, the study of cell mechanics in a non-contact, purely fluidic environment, in a fully automated fashion. To achieve this, a number of innovative techniques have been postulated, developed, proven and demonstrated. These include a novel control system simulator for the control of coupled fluid-particle systems, innovative approaches for realtime flow feedback through realtime image analysis, tracking cells in noisy conditions, and an advanced flow controller designed specifically for high bandwidth manipulation of flow in microfluidic systems. The techniques developed and proven in this thesis allow the conception and construction of software-defined systems to manipulate not only cells, but also oil droplets, particles, and other suspended objects. These dynamic manipulation and measurement methods represent a significant advance over existing techniques for cell and droplet manipulation in diagnostics and research. In contrast to other methods, detailed multi-dimensional measurements (for example, both force-extension profiles and relaxation times) can be obtained using a single laboratory device, and on an individual cell basis, rather than through bulk measurement. The technology has been successfully applied to the measurement of key mechanical properties of live red blood cells. In particular, the ability to trap cells in an automated fashion at high extensional rates (corresponding to a physiologically-relevant net force), and measure the resultant dynamic behaviour of the cells, greatly expands upon the existing tools available for cell analysis. Cells were obtained, subjected to a minimum of processing, and the dynamic changes in cell shape tracked as a the cell was subjected to varying extensional forces. Unlike many of the preceding works, this was accomplished without the use of foreign manipulation devices — such as lasers or direct physical contact — and requires a minimum of operator intervention. By measuring both the steady-state and dynamic behaviours of cells, both the stiffness and time constant (viscosity) were obtained for individual cells. The work presented in this thesis enables researchers and clinicians to efficiently measure cell stiffness and viscosity simultaneously from single cells. This greatly improves the predictive and diagnostic power of cell mechanics measurements available to researchers and has the potential to revolutionise both our understanding of blood-related diseases (such as diabetes and malaria) and point-of-care diagnostics. This thesis documents a number of the scientific and technical advances over the existing body of knowledge (Part I), across a number of fields (including imaging, fluid dynamics and control systems), that have arisen from the development of this technology (Part II). In addition, extensive validation work (Part III) will demonstrate the application of the work in Part II to the analysis of the properties of biological cells.