2016 – TRANSCRIPTIONAL DYNAMICS OF THE PU.1-GATA NETWORK AT SINGLE MOLECULE RESOLUTION IN HEMATOPOIETIC STEM CELLS

Molecular noise is a natural and inescapable physical phenomenon inherent to all biological systems. How robust tissue homeostasis can arise despite these stochastic processes is a conundrum. Here, to quantitatively investigate this issue, we use single-molecule mRNA FISH (smFISH) in HSPC to measure the transcription dynamics of three key transcription factor (TF) genes: PU.1, Gata1 and Gata2. Our results indicate that infrequent, stochastic bursts of transcription result in the co-expression of these antagonistic TF in the majority of hematopoietic stem and progenitor cells. Moreover, by pairing smFISH with time-lapse microscopy and the analysis of pedigrees, we find that while individual stem cell clones produce offspring that are in transcriptionally related states, akin to a transcriptional priming phenomenon, the underlying transition dynamics between different transcriptional states are nevertheless best captured by stochastic and reversible models. As such, the outcome of a stochastic process can produce cellular behaviors that may be incorrectly inferred to have arisen from deterministic dynamics. Considering our findings, we propose a model of HSC transcriptional network sampling whereby the intrinsic stochasticity of gene expression facilitates, rather than impedes, concomitant maintenance of transcriptional plasticity and stem cell robustness. Using these tools, the quantitative predictions from our studies, and live cell imaging at single protein resolution, we are now determining how extrinsic factors integrate into these dynamics, both at the level of expression of these TF and at the level of their respective gene regulatory functions.