Balancing dynamic tradeoffs drives cellular reprogramming

Kn, Babos; Galloway, Kate E.; Kisler, Kassandra; Zitting, Madison; Y, Li; Quintino, Brooke; Rh, Chow; Bv, Zlokovic; Jk, Ichida

doi:10.1101/393934

Cited by 2 publications

(3 citation statements)

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“…Beyond primary tumors, dynamic epigenetic state switching enables persistence of drug-tolerant subpopulations and metastases (Denny et al, 2016;Sharma et al, 2010). Within populations of cells, unique processes mark privileged populations capable of mediating the massive epigenetic transition to reprogram (Babos et al, 2019;Guo et al, 2014). The subpopulation of fast-cycling cells reprogram to highly proliferative iPSCs and post-mitotic neurons at much higher rates (5-100-fold) than slower cycling cells (Babos et al, 2019;Guo et al, 2014).…”

Section: Ll Open Accessmentioning

confidence: 99%

“…Within populations of cells, unique processes mark privileged populations capable of mediating the massive epigenetic transition to reprogram (Babos et al, 2019;Guo et al, 2014). The subpopulation of fast-cycling cells reprogram to highly proliferative iPSCs and post-mitotic neurons at much higher rates (5-100-fold) than slower cycling cells (Babos et al, 2019;Guo et al, 2014). Reprogramming of somatic nuclei via fusion with ESCs requires DNA synthesis, suggesting that S phase may provide a unique environment for reprogramming (Tsubouchi et al, 2013).…”

Section: Ll Open Accessmentioning

confidence: 99%

“…Together these observations suggest that proliferation may promote reprogramming via cell-cycle-induced resetting and restructuring of chromatin. Additionally, high transcription rates in hyperproliferative cells result in near-deterministic reprogramming (Babos et al, 2019). Hypertranscription may facilitate rapid, extensive chromatin remodeling to drive cellular reprogramming.…”

Section: Ll Open Accessmentioning

confidence: 99%

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Understanding and Engineering Chromatin as a Dynamical System across Length and Timescales

Johnstone¹,

Wang²,

Sevier

et al. 2020

Cell Systems

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Connecting the molecular structure and function of chromatin across length and timescales remains a grand challenge to understanding and engineering cellular behaviors. Across five orders of magnitude, dynamic processes constantly reshape chromatin structures, driving spaciotemporal patterns of gene expression and cell fate. Through the interplay of structure and function, the genome operates as a highly dynamic feedback control system. Recent experimental techniques have provided increasingly detailed data that revise and augment the relatively static, hierarchical view of genomic architecture with an understanding of how dynamic processes drive organization. Here, we review how novel technologies from sequencing, imaging, and synthetic biology refine our understanding of chromatin structure and function and enable chromatin engineering. Finally, we discuss opportunities to use these tools to enhance understanding of the dynamic interrelationship of chromatin structure and function. INTRODUCTION TO CHROMATIN AND DYNAMIC MODES OF GENE REGULATION Chromatin can facilitate pattern formation and information transfer across multiple time and length scales (Figure 1A). Nanometer-scale interactions such as transcription factor binding occur on the order of milliseconds (Fierz and Poirier, 2019), while chromosome territories, the largest subnuclear structures, persist over many cell divisions (Dekker and Mirny, 2016). Because of the short-ranged stochastic nature of DNA-protein ll

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Section: Ll Open Accessmentioning

confidence: 99%

Section: Ll Open Accessmentioning

confidence: 99%

Section: Ll Open Accessmentioning

confidence: 99%

See 1 more Smart Citation

Understanding and Engineering Chromatin as a Dynamical System across Length and Timescales

Johnstone¹,

Wang²,

Sevier

et al. 2020

Cell Systems

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Single-cell mapping of lineage and identity in direct reprogramming

Biddy

Kong

Kamimoto

et al. 2018

Nature

292

372

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Direct lineage reprogramming involves the remarkable conversion of cellular identity. Single-cell technologies aid in deconstructing the considerable heterogeneity that emerges during lineage conversion. However, lineage relationships are typically lost during cell processing, complicating trajectory reconstruction. Here, we present ‘CellTagging’, a combinatorial cell indexing methodology, permitting the parallel capture of clonal history and cell identity, where sequential rounds of cell labelling enable the construction of multi-level lineage trees. CellTagging and longitudinal tracking of fibroblast to induced endoderm progenitor (iEP) reprogramming reveals two distinct trajectories: one leading to successfully reprogrammed cells, and one leading to a ‘dead-end’ state, paths determined in the earliest reprogramming stages. We find that expression of a putative methyltransferase, Mettl7a1, is associated with the successful reprogramming trajectory, where its addition to the reprogramming cocktail increases the yield of iEPs. Together, these results demonstrate the utility of our lineage tracing method to reveal dynamics of direct reprogramming.

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Balancing dynamic tradeoffs drives cellular reprogramming

Cited by 2 publications

References 46 publications

Understanding and Engineering Chromatin as a Dynamical System across Length and Timescales

Understanding and Engineering Chromatin as a Dynamical System across Length and Timescales

Single-cell mapping of lineage and identity in direct reprogramming

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