Algorithm for cellular reprogramming

Ronquist, Scott; Patterson, Geoff; Muir, Lindsey A.; Lindsly, Stephen; Chen, Haiming; Brown, Markus A.; Wicha, Max S.; Bloch, Anthony M.; Brockett, Roger W.; Rajapakse, Indika

doi:10.1073/pnas.1712350114

Cited by 35 publications

(28 citation statements)

References 41 publications

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“…There is a growing interest to analyze Hi-C datasets and model chromosome interactions using network models [26][27][28], which has opened the door to study chromosomal datasets using network-based algorithms including community detection [29][30][31][32] and centrality [33,34]. These detection algorithms perform an unbiased search for robust structures (communities or clusters) at the scale they exist in an automated manner, quantifying how chromosome conformational changes can precede changes to transcription factors and gene expression [35,36] and leading to new approaches for cellular reprogramming [33,37].…”

Section: Introductionmentioning

confidence: 99%

Transient crosslinking kinetics optimize gene cluster interactions

Walker

Taylor

Lawrimore

et al. 2019

Preprint

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Our understanding of how chromosomes structurally organize and dynamically interact has been revolutionized through the lens of long-chain polymer physics. Major protein contributors to chromosome structure and dynamics are condensin and cohesin that stochastically generate loops within and between chains, and entrap proximal strands of sister chromatids. In this paper, we explore the ability of transient, protein-mediated, gene-gene crosslinks to induce clusters of genes, thereby dynamic architecture, within the highly repeated ribosomal DNA that comprises the nucleolus of budding yeast. We implement three approaches: live cell microscopy; computational modeling of the full genome during G1 in budding yeast, exploring four decades of timescales for transient crosslinks between 5kbp domains (genes) in the nucleolus on Chromosome XII; and, temporal network models with automated community (cluster) detection algorithms applied to the full range of 4D modeling datasets. The data analysis tools detect and track gene clusters, their size, number, persistence time, and their plasticity (deformation). Of biological significance, our analysis reveals an optimal mean crosslink lifetime that promotes pairwise and cluster gene interactions through "flexible" clustering. In this state, large gene clusters self-assemble yet frequently interact (merge and separate), marked by gene exchanges between clusters, which in turn maximizes global gene interactions in the nucleolus. This regime stands between two limiting cases each with far less global gene interactions: with shorter crosslink lifetimes, "rigid" clustering emerges with clusters that interact infrequently; with longer crosslink lifetimes, there is a dissolution of clusters. These observations are compared with imaging experiments on a normal yeast strain and two condensin-modified mutant cell strains. We apply the same image analysis pipeline to the experimental and simulated datasets, providing support for the modeling predictions. Author SummaryThe spatiotemporal organization of the genome plays an important role in cellular processes involving DNA, but remains poorly understood, especially in the nucleolus, May 21, 2019 1/25 which does not facilitate conventional techniques. Polymer chain models have shown ability in recent years to make accurate predictions of the dynamics of the genome. We consider a polymer bead-chain model of the full yeast genome during the interphase portion of the cell cycle, featuring special dynamic crosslinking to model the effects of structural maintenance proteins in the nucleolus, and investigate how the kinetic timescale on which the crosslinks bind and unbind affects the resulting dynamics inside the nucleolus. It was previously known that when this timescale is sufficiently short, large, stable clusters appear, but when it is long, there is no resulting structure. We find that there additionally exists a range of timescales for which flexible clusters appear, in which beads frequently enter and leave clusters. Furthermore, we demonst...

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Section: Introductionmentioning

confidence: 99%

Transient crosslinking kinetics optimize gene cluster interactions

Walker

Taylor

Lawrimore

et al. 2019

Preprint

View full text Add to dashboard Cite

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“…One particular application we plan to investigate is that of cellular reprogramming which involves introducing transcription factors as a control mechanism to transform one cell type to another. These systems naturally have matrix or tensor state spaces describing their genome-wide structure and gene expression [25,26]. Such applications would also ideally be analyzed using nonlinearity and stochasticity in the multiway dynamical system representation and analysis framework.…”

Section: Resultsmentioning

confidence: 99%

Multilinear Time Invariant System Theory

Chen¹,

Surana²,

Bloch³

et al. 2019

2019 Proceedings of the Conference on Control and Its Applications

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In biological and engineering systems, structure, function and dynamics are highly coupled. Such interactions can be naturally and compactly captured via tensor based state space dynamic representations. However, such representations are not amenable to the standard system and controls framework which requires the state to be in the form of a vector. In order to address this limitation, recently a new class of multiway dynamical systems has been introduced in which the states, inputs and outputs are tensors. We propose a new form of multilinear time invariant (MLTI) systems based on the Einstein product and even-order paired tensors. We extend classical linear time invariant (LTI) system notions including stability, reachability and observability for the new MLTI system representation by leveraging recent advances in tensor algebra.

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“…Mechanobiology examines the role of physical and mechanical forces in the control of cell development and disease, in addition to chemicals and genes [13,14]. A major goal of the 4D nucleome project is to understand the subcellular details of this process compared to physical systems governed by Newton’s laws of motion [15]. The initial mathematical analysis of the multi-cell system using the digital computer based on Newton’s laws of motion proposed 4 types of changes involving the mechanical and the chemical parts: “The changes of position and velocity as given by Newton’s laws of motion. The stresses as given by the elasticities and motions, also taking into account the osmotic pressures as given from the chemical data. The chemical reactions. The diffusion of the chemical substances.…”

Section: Data Notesmentioning

confidence: 99%

“…Thus, cell shapes can affect the Notch signaling triggered events [52]. Key transcription factors/”master” regulators are considered important 4D nucelome modulators [5, 8, 15]. Glucocorticoid receptor (NR3C1) and transcription factor HES1 can bind their own promoters for dynamic autoregulation, they can also repress each other’s transcription via binding to the promoters [53, 54].…”

Section: Data Notesmentioning

confidence: 99%

Rotational 3D mechanogenomic Turing patterns of human colon Caco-2 cells during differentiation

Zheng

Kalinin

Dinov

et al. 2018

Preprint

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Recent reports suggest that actomyosin meshwork act in a mechanobiological manner alter cell/nucleus/tissue morphology, including human colon epithelial Caco-2 cancer cells that form polarized 2D epithelium or 3D sphere/tube when placed in different culture conditions. We observed the rotational motion of the nucleus in Caco-2 cells in vitro that appears to be driven by actomyosin network prior to the formation of a differentiated confluent epithelium. Caco-2 cell monolayer preparations demonstrated 2D patterns consistent with Allan Turing’s “gene morphogen” hypothesis based on live cell imaging analysis of apical tight junctions indicating the actomyosin meshwork. Caco-2 cells in 3D culture are frequently used as a model to study 3D epithelial morphogenesis involving symmetric and asymmetric cell divisions. Differentiation of Caco-2 cells in vitro demonstrated similarity to intestinal enterocyte differentiation along the human colon crypt axis. We observed rotational 3D patterns consistent with gene morphogens during Caco-2 cell differentiation. Single- to multi-cell ring/torus-shaped genomes were observed that were similar to complex fractal Turing patterns extending from a rotating torus centre in a spiral pattern consistent with gene morphogen motif. Rotational features of the epithelial cells may contribute to well-described differentiation from stem cells to the luminal colon epithelium along the crypt axis. This dataset may be useful to study the role of mechanobiological processes and the underlying molecular mechanisms as determinants of cellular and tissue architecture in space and time, which is the focal point of the 4D nucleome initiative.

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Algorithm for cellular reprogramming

Cited by 35 publications

References 41 publications

Transient crosslinking kinetics optimize gene cluster interactions

Transient crosslinking kinetics optimize gene cluster interactions

Multilinear Time Invariant System Theory

Rotational 3D mechanogenomic Turing patterns of human colon Caco-2 cells during differentiation

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