|M.Sc Student||Tom Ben-Arye|
|Subject||Single Cell Analysis in Nano-Liter Wells|
|Department||Department of Nanoscience and Nanotechnology||Supervisor||Full Professor Levenberg Shulamit|
Heterogeneity between individual cells exists even between genetically identical populations; however this information is generally lost in common bulk cell assays, which rely on ensemble averages to understand cellular phenomena. Kinetic data of cellular processes is also lost as different cells do not act simultaneously.
Microfluidics is a field used to design lab on a chip devices. Microfluidic devices have proven to be a leading tool for single cell analysis since device dimensions are on the same scale as those of cells, allowing for precise fluid and cell manipulation. In addition, microfluidic systems typically inexpensive and require minute amounts of reagent consumption, while providing high throughput data making them attractive for laboratories as well as industrial purposes. Since microfluidic devices are easily fabricated in custom made designs and since the flow inside the channels is well understood, these devices can be easily used for prototyping. This also eases integration of several microfluidic devices and the design of portable chips compatible with additional lab equipment. Moreover, if cells are chemically compartmentalized, cellular microenvironments can be controlled with high spatial and temporal resolution required for studying the single cell niche.
In this study we used the Stationary Nanoliter Droplet Array (SNDA) microfluidic device to investigate compartmentalized adherent and non-adherent single cells over prolonged time periods. The device performance was improved by fabricating higher resolution masters, thus increasing the possible number of wells and the types of substrates. In order to enable experiments which are longer than two days, a medium change method was developed as well as a method to prevent medium evaporation. AlamarBlue metabolic assay was performed with single cell resolution on a population of fibroblasts. As in bulk experiments, alamarBlue buildup had linear correlation with cell number. Using this assay, it was shown that the variation in single cell reduction potential is associated with the heterogeneity of the population morphology. In order to find and analyze cell cycle and G1 correlations of different cell relations, lineage tracking of lymphoma cells was performed inside the SNDA over days in high-throughput manner. Results showed a correlation in G1 phase and cell cycle duration between sister cells, while such correlation was not found between mother-daughter relations. In addition, the cell distribution inside the SNDA device was characterized and correlated with Poisson distribution. To allow analysis of single cell secretion content, single cell ELISA protocol was developed.