ANALYSIS OF SINGLE CELL DYNAMICS AND THEIR RELATIONSHIP WITH THE CELL CYCLE AND CELL FATE IN MOUSE EMBRYONIC STEM CELLS

SEVLEVER F; ELIAS COSTA M; BRIVANLOU A; MIRIUKA S; GUBERMAN A; WAISMAN A; COSENTINO S; VENTURA A

Ciudad de Buenos

Congreso; Reunión Conjunta de Biociencias 2017; 2017

Mouse embryonic stem cells (mESCs) are pluripotent cells that resemble the preimplantation epiblast of the embryo. They can give rise to all the cells of the organism, which makes them an interesting cell type in the field of regenerative medicine. Recently, the cell cycle has gained attention as a key determinant of their properties, based on the observation that cells only respond to differentiation cues during the G1 phase. In addition, it has been reported that mESCs possess a cell cycle length (CC-L) significantly shorter than their differentiated counterparts. With the onset of differentiation, it has been reported that CC-L increases. However, most of the research came from experiments that address cell populations as a whole, without considering the underlying single-cell dynamics. In this work, we aimed to characterize the dynamics of proliferation in mESCs, both while maintaining the pluripotent state and during differentiation. With this objective, we performed 48 h time-lapse videos of mESCs expressing the FUCCI cell cycle reporters. We developed a bioinformatic pipeline to extract single-cell dynamics of thousands of cells, with information about their lineage relationships. Analysis of this database confirmed the short G1-L and CC-L of mESCs. It also showed that G1-L and CC-L are greatly correlated between sister cells, implying that these properties are partially inherited from the parental cell. We also show that during the first steps of differentiation, G1-L and CC-L decrease rather than increase, and that this is also accompanied by a decrease in S/G2/M-L. Along these lines, we applied Grassberger-Proccatia algorithm, that showed that the overall CC-L dynamics is a highly deterministic process where each CC-L can be well predicted from each cell´s lineage. By addressing the great complexity of single-cell dynamics of mESCs, we believe our work contributes to a greater understanding of the connection between the cell cycle and cell-fate decisions.