A common molecular logic determines embryonic stem cell self‐renewal and reprogramming

Abstract

During differentiation and reprogramming, new cell identities are generated by reconfiguration of gene regulatory networks. Here, we combined automated formal reasoning with experimentation to expose the logic of network activation during induction of naïve pluripotency. We find that a Boolean network architecture defined for maintenance of naïve state embryonic stem cells (ESC) also explains transcription factor behaviour and potency during resetting from primed pluripotency. Computationally identified gene activation trajectories were experimentally substantiated at single‐cell resolution by RT–qPCR. Contingency of factor availability explains the counterintuitive observation that Klf2, which is dispensable for ESC maintenance, is required during resetting. We tested 124 predictions formulated by the dynamic network, finding a predictive accuracy of 77.4%. Finally, we show that this network explains and predicts experimental observations of somatic cell reprogramming. We conclude that a common deterministic program of gene regulation is sufficient to govern maintenance and induction of naïve pluripotency. The tools exemplified here could be broadly applied to delineate dynamic networks underlying cell fate transitions.

Zfp281 orchestrates interconversion of pluripotent states by engaging Ehmt1 and Zic2

“…The former is consistent with perturbed epiblast maturation in Zfp281 mutant embryos (Huang et al, 2017), but whether Zfp281 protects cellular identities against de-differentiation in vivo remains to be determined. We, however, note that Zfp281 restrains iPSC formation from fibroblasts at a late pre-iPSC stage (Fidalgo et al, 2012), supporting the notion that resetting of EpiSCs into naïve pluripotency recapitulates a late phase of somatic cell reprogramming (Dunn et al, 2019). Other factors that, similar to Zfp281, drive differentiation and inhibit de-differentiation of cell states not represented in our ESC-EpiSC conversion system are likely to exist.…”

USP9X deubiquitinase couples the pluripotency network and cell metabolism to regulate ESC differentiation potential

“…Pluripotency is defined by the ability to self-renew and, under appropriate conditions, differentiate into all somatic cell lineages [1]. Embryonic stem cells (ESC) transition to different states of pluripotency, that can be recapitulated in vitro by culture conditions, and that correlates with different behaviours and abilities to contribute to blastocyst chimeras [1][2][3]. The dynamic nature of ESC relies on discrete changes in signalling pathways, gene expression and epigenetic regulations.…”

Let it RE : IN : integrating experimental observations to predict pluripotency network behaviour

“…Our ability to reprogram cells and induce transitions between states has fast become a commonplace tool, but our understanding of the underlying processes and capacity to predict these is still relatively rudimentary. A new article by Dunn et al (2019) combines a computational reasoning approach with experimental observation to construct a network-level understanding of the transcription factors instructing acquisition of naïve pluripotency during reprogramming. The EMBO Journal (2019) 38: e101133 See also: SJ Dunn et al (January 2019) I t is not unusual for biologists to sketch the interactions of genes or proteins in their system of interest in order to construct networks that describe the phenomenon that they study.…”

“…In this issue, Dunn et al (2019) tackle this problem in an unconventional way by applying their Reasoning Engine for Interaction Networks (RE:IN) approach, introduced earlier to establish a minimal regulatory network architecture required for ESCs selfrenewal (Dunn et al, 2014;Yordanov et al, 2016) to paradigms of pluripotency induction. Rather than generating or drawing a single network that describes the system of interest, they constructed a constrained abstract Boolean network (or cABN) which reduces the set of all possible networks to those that reliably reconstitute constraints from experimental observations.…”

“…In each of these networks, nodes are allowed to be in a high/low state and the dynamics of the networks defined by a universal set of update rules. These rules allowed Dunn et al (2019) to initialise a network in one state and then, by applying the update rules, evolve into different states. To further use this method to predict the effects of perturbations on the networks (i.e.…”