Through the overexpression of key transcription factors – Oct4, Klf4, c-Myc, and Sox2 (OKMS) – mouse somatic cells can be reprogrammed to an induced pluripotent stem cell (iPSC) state, enabling them to give rise to all cell types of the body. However, the process of reprogramming has remained elusive and it is unclear whether all somatic cells traverse the same trajectory following OKMS transgene overexpression. The reprogramming process has been mapped by conducting ‘omics analyses of bulk reprogramming culture over time. These population-averaged datasets describe reprogramming as a stepwise process where somatic cells transition through a (transgene-dependent) pre-iPSC state to finally stabilise in a (transgene-independent) iPSCs state. On the other hand, single mouse somatic cells reprogrammed in isolation exhibit stochastic reprogramming latencies. As a result, cells experiencing asynchronous reprogramming dynamics are expected to give rise to heterogeneity in bulk reprogramming culture. Here, we aim to consolidate the apparent dichotomy between stepwise cell state changes observed in population reprogramming with the stochasticity of isolated clonal reprogramming by investigating heterogeneity in mouse reprogramming culture.
We first develop a surface marker strategy to track transgene-dependent and -independent iPSCs, enabling us to assess heterogeneity with ease. This marker strategy also shows utility in separating naïve and primed pluripotent states in mouse and human culture. We next combine this surface marker-based approach with clonal tracking and mathematical modeling to investigate the reprogramming trajectory of individual reprogramming clones in bulk culture. In doing so, we uncover clonal competition as a novel driver of population reprogramming dynamics. In fact, we show that a subset of poised somatic cells gives rise to clones that have an elite propensity to dominate bulk reprogramming culture and contribute to the iPSC fraction. We also show, for the first time, that a few clones overtake population reprogramming culture, thus making population-averaged data clonally biased. This work provides novel insights into the role of cell competition in driving heterogeneity in reprogramming culture, providing a new lens with which to interpret population-averaged ‘omics datasets. Taken together, we show that not all reprogramming clones exhibit equivalent behaviour in multicellular contexts, underscoring the need to consider the competition potential of iPSCs.Ph.D.2018-12-19 00:00:0
