Proliferation history and transcription factor levels drive direct conversion

Abstract

The sparse and stochastic nature of reprogramming has obscured our understanding of how transcription factors drive cells to new identities. To overcome this limit, we developed a compact, portable reprogramming system that increases direct conversion of fibroblasts to motor neurons by two orders of magnitude. We show that subpopulations with different reprogramming potentials are distinguishable by proliferation history. By controlling for proliferation history and titrating each transcription factor, we find that conversion correlates with levels of the pioneer transcription factor Ngn2, whereas conversion shows a biphasic response to Lhx3. Increasing the proliferation rate of adult human fibroblasts generates morphologically mature, induced motor neurons at high rates. Using compact, optimized, polycistronic cassettes, we generate motor neurons that graft with the murine central nervous system, demonstrating the potential forin vivotherapies.One Sentence SummaryUsing a systems and synthetic biology approach to study the molecular determinants of reprogramming, we find that proliferation history and transcription factor levels drive cell fate in direct conversion to motor neurons.Highlightsminimal high-efficiency cocktail allows systematic interrogation of the reprogramming processhistory provides a principal axis to distinguish transcription factors’ influenceof the transcription factor cocktail impacts reprogramming efficiency and dynamicsof individual transcription factors differentially influence the rate of reprogrammingearly hyperproliferation increases direct conversion of adult human fibroblastsptimal cocktail allows neurotrophic factor-free reprogramming andin vivografting

Programmable promoter editing for precise control of transgene expression

“… 1 , 11 In particular, non-linear effects of gene expression can confound inference of positive and negative regulation of phenotypes. 1 , 2 , 12 , 13 Tools that support fine-scale titration of expression reveal non-monotonic relationships between expression of regulators and phenotypes. 1 , 2 , 12 While useful for identifying linear regulators, large-scale screening tools such as CRISPR-based knockout, knockdown, and activation often do not provide sufficient resolution to find regulators with non-linear relationships to phenotypes.…”

“… 1 , 2 , 12 , 13 Tools that support fine-scale titration of expression reveal non-monotonic relationships between expression of regulators and phenotypes. 1 , 2 , 12 While useful for identifying linear regulators, large-scale screening tools such as CRISPR-based knockout, knockdown, and activation often do not provide sufficient resolution to find regulators with non-linear relationships to phenotypes. Such CRISPR-based screening does not predict how overexpression of transgenes influences cellular behaviors.…”

“…Subtle changes in gene expression can generate diverging cell fates. [1][2][3][4][5][6] Overexpression of endogenous and synthetic genes drives and redirects native processes and can augment native cellular functions. [7][8][9][10] However, identifying which transgenes elicit these subtle effects requires fine-tuned control, and implementing control over dosage-sensitive regimes remains a challenge.…”