Publication
Since stem cells have the unique ability to produce more of themselves (i.e. to "self-renew") and to generate specialized tissue cells, they are an ideal source of cells for regenerative medicine and in vitro tissue models. In order to fully exploit this potential, we have to better understand the mechanisms that regulate stem cell behavior at a single cell level. However, current in vitro methodologies to study single cells are limited by their throughput, do not afford to distinguish the fate of daughter cells or track the progeny of a single cell over long time periods. This thesis addresses these shortcomings by developing miniaturized devices to handle and analyze single live stem cells. To this end, a micro-structured platform was first established that consisted of miniaturized wells with diameters of 100 µm that were arranged in a regular grid. Single hematopoietic stem cells (HSCs) were then seeded into these "microwell arrays" and, since the HSCs could not leave the microwells, they could be tracked over many days, and their dynamics and proliferation rates could be studied. However, in order to analyze the daughter cells of these single HSCs individually, the daughter cells have to be physically separated by micromanipulation. For this purpose, a microdevice was developed to reliably manipulate single cells using hydrodynamic single cell trapping. This platform was thoroughly characterized using computational simulations combined with particle flow velocimetry and live-cell time-lapse microscopy. The optimization of design parameters towards increasing trapping efficiency ensured a nearly perfect efficiency of single cell trapping (97%) and a successful re-capture of daughter cells generated by dividing mother cells. Furthermore, it was demonstrated that cell trapping under very low flow is sufficiently gentle to enable long-term cell trapping in the microfluidic environment. To identify and track captured cells in these microfluidic single cell traps, automated image analysis tools were developed. A reliable and fast algorithm was generated to identify the borders of microchannels that were indicative for the position of single cell traps. These detected edges were used to individualize the single cell traps with a sub-pixel resolution such that it was possible to segment single HSCs on the chip by thresholding. Accordingly, single HSCs were discovered with efficiencies as high as >95%, allowing the automated tracking of microfluidic single cell trapping, as well as the detection of cell cycle phases of trapped single HSCs engineered with dual fluorescence reporter system marking G1 and S/G2-M. To actively micromanipulate single cells for downstream cell-fate analyses, on-chip valves were integrated on the microfluidic platform to precisely control the direction of medium flow in the microfluidic channels. This approach enabled a proof-of-concept study to demonstrate a more complex single cell manipulation: Cells were first captured i