Theory of cell fate

被引:26
作者
Casey, Michael J. [1 ,2 ]
Stumpf, Patrick S. [2 ,3 ]
MacArthur, Ben D. [1 ,2 ,3 ]
机构
[1] Univ Southampton, Math Sci, Southampton, Hants, England
[2] Univ Southampton, Inst Life Sci, Southampton, Hants, England
[3] Univ Southampton, Ctr Human Dev Stem Cells & Regenerat, Southampton, Hants, England
基金
英国医学研究理事会;
关键词
cell fate; mathematical model; systems biology; GENOME-WIDE EXPRESSION; STEM; HETEROGENEITY; INFERENCE; DYNAMICS; PROGENITOR; LINEAGE; SEQ;
D O I
10.1002/wsbm.1471
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
Cell fate decisions are controlled by complex intracellular molecular regulatory networks. Studies increasingly reveal the scale of this complexity: not only do cell fate regulatory networks contain numerous positive and negative feedback loops, they also involve a range of different kinds of nonlinear protein-protein and protein-DNA interactions. This inherent complexity and nonlinearity makes cell fate decisions hard to understand using experiment and intuition alone. In this primer, we will outline how tools from mathematics can be used to understand cell fate dynamics. We will briefly introduce some notions from dynamical systems theory, and discuss how they offer a framework within which to build a rigorous understanding of what we mean by a cell "fate", and how cells change fate. We will also outline how modern experiments, particularly high-throughput single-cell experiments, are enabling us to test and explore the limits of these ideas, and build a better understanding of cellular identities. This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Biological Mechanisms > Cell Fates Models of Systems Properties and Processes > Cellular Models
引用
收藏
页数:11
相关论文
共 62 条
[1]   Stochastic NANOG fluctuations allow mouse embryonic stem cells to explore pluripotency [J].
Abranches, Elsa ;
Guedes, Ana M. V. ;
Moravec, Martin ;
Maamar, Hedia ;
Svoboda, Petr ;
Raj, Arjun ;
Henrique, Domingos .
DEVELOPMENT, 2014, 141 (14) :2770-2779
[2]  
Aibar S, 2017, NAT METHODS, V14, P1083, DOI [10.1038/NMETH.4463, 10.1038/nmeth.4463]
[3]   A clonogenic common myeloid progenitor that gives rise to all myeloid lineages [J].
Akashi, K ;
Traver, D ;
Miyamoto, T ;
Weissman, IL .
NATURE, 2000, 404 (6774) :193-197
[4]   Gene Regulatory Logic for Reading the Sonic Hedgehog Signaling Gradient in the Vertebrate Neural Tube [J].
Balaskas, Nikolaos ;
Ribeiro, Ana ;
Panovska, Jasmina ;
Dessaud, Eric ;
Sasai, Noriaki ;
Page, Karen M. ;
Briscoe, James ;
Ribes, Vanessa .
CELL, 2012, 148 (1-2) :273-284
[5]   Dimensionality reduction for visualizing single-cell data using UMAP [J].
Becht, Etienne ;
McInnes, Leland ;
Healy, John ;
Dutertre, Charles-Antoine ;
Kwok, Immanuel W. H. ;
Ng, Lai Guan ;
Ginhoux, Florent ;
Newell, Evan W. .
NATURE BIOTECHNOLOGY, 2019, 37 (01) :38-+
[6]   The heterogeneity of human CD127+ innate lymphoid cells revealed by single-cell RNA sequencing [J].
Bjorklund, Asa K. ;
Forkel, Marianne ;
Picelli, Simone ;
Konya, Viktoria ;
Theorell, Jakob ;
Friberg, Danielle ;
Sandberg, Rickard ;
Mjosberg, Jenny .
NATURE IMMUNOLOGY, 2016, 17 (04) :451-+
[7]   Fast unfolding of communities in large networks [J].
Blondel, Vincent D. ;
Guillaume, Jean-Loup ;
Lambiotte, Renaud ;
Lefebvre, Etienne .
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT, 2008,
[8]   Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells [J].
Buettner, Florian ;
Natarajan, Kedar N. ;
Casale, F. Paolo ;
Proserpio, Valentina ;
Scialdone, Antonio ;
Theis, Fabian J. ;
Teichmann, Sarah A. ;
Marioni, John C. ;
Stegie, Oliver .
NATURE BIOTECHNOLOGY, 2015, 33 (02) :155-160
[9]   Integrating single-cell transcriptomic data across different conditions, technologies, and species [J].
Butler, Andrew ;
Hoffman, Paul ;
Smibert, Peter ;
Papalexi, Efthymia ;
Satija, Rahul .
NATURE BIOTECHNOLOGY, 2018, 36 (05) :411-+
[10]   The single-cell transcriptional landscape of mammalian organogenesis [J].
Cao, Junyue ;
Spielmann, Malte ;
Qiu, Xiaojie ;
Huang, Xingfan ;
Ibrahim, Daniel M. ;
Hill, Andrew J. ;
Zhang, Fan ;
Mundlos, Stefan ;
Christiansen, Lena ;
Steemers, Frank J. ;
Trapnell, Cole ;
Shendure, Jay .
NATURE, 2019, 566 (7745) :496-+