Live single-cell imaging has emerged as an advanced single-cell study tool for approaching a quantitative understanding of many biological questions in recent years. In previous cell studies using bulk cell measurements, the population averages can miss the information from cell to cell variability and mask the underlying signaling networks and mechanisms. Currently, some single cell analysis methods, including but not limited to, live single-cell imaging experiments that built around a fluorescent imaging setup and microfluidic devices enable the measurement and analysis of cell dynamics and responses of single cells across a population and across time. Furthermore, by changing the cells’ environmental conditions in well controlled ways, e.g. balanced steady growth, or temporal pulses, live single-cell imaging can record the cellular behaviors corresponding to these changes in exquisite details.

An important question of current interest in both developmental, stem cell and cancer biology is the question of epigenetic differentiation. Continuous long-term live single-cell observations offer insights into the molecular control of cell fate. However, maintaining the imaged cells in a healthy state remains a major challenge. One of our aims in this work was to develop a semi-automated single-cell live imaging and analysis platform to obtain dynamic information of the cellular processes. An imaging incubator that controls and regulates the environmental conditions of the imaged cells also had to be designed and tested.

In this thesis, I address the key design considerations of developing a single-cell live imaging platform and demonstrate the capability of this technology through three case studies.

To test the design and fabrication of microfluidic devices and micro-valves in imaging malaria infected red blood cells (iRBCs), I recorded the flow of iRBCs through microfluidic channels and constrictions in Chapter 3. Our results illustrate the behaviors of iRBCs with different flow rates and the potential to offer dynamic control in studying the infection probability of iRBCs by implementing the micro-valve system.

In order to develop a more adaptable live cell imaging platform, we further developed our semi-automated imaging software and in house built imaging incubator to explore the link between proliferation and differentiation of CD4+ T cells in Chapter 4. By using cells expressing an IL-13-GFP reporter, we distinguished between differentiating and non-differentiating CD4+ T cell population and demonstrated a positive association between cycling differentiation of CD4+ T cells.

In Chapter 5, we incorporated the FUCCI cell reporter system in our single cell live imaging system to reveal the effect of different media conditions on the cell cycle progression and cell fate choices of mouse embryonic stem (mES) cells. By improving different factors such as longer pre-incubation time before imaging and exchanging media during the experiments, we maintained a healthy state of mES cells during live cell imaging for extended periods. We observed significant differences in time between divisions of mES cells cultured in 2i +LIF and serum + LIF media, and also small but significant differences in durations of sub-cell cycle phases (G1,G1/S,S/G2/M) between the two media conditions. We further applied this imaging setup to study the behaviors of differentiating mES cells in vitro, and observed lengthening of the G1 phase for both 2i-LIF and serum-LIF cells in agreement with literature.

Overall, our semi-automated single cell imaging platform not only offers adjustable intervals between fluorescent imaging, but also provides a constant temperature and gas feeding devices that allows the cells to proliferate for extended microscope imaging. Commercially produced incubators that fit onto the microscope stage and satisfied all requirements in restriction of the cell movement, gas feeding, temperature regulation and optical accessibility are not easily available. Thus, there exists a significant potential for our imaging setup to provide a versatile and adaptable live cell imaging platform for both academia and industrial researchers.