共 4 条
Closed-form stochastic solutions for non-equilibrium dynamics and inheritance of cellular components over many cell divisions
被引:27
|作者:
Johnston, Iain G.
[1
]
Jones, Nick S.
[1
]
机构:
[1] Univ London Imperial Coll Sci Technol & Med, Dept Math, London SW7 2AZ, England
来源:
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
|
2015年
/
471卷
/
2180期
关键词:
stochastic processes;
stochastic biology;
cellular populations;
MITOCHONDRIAL-DNA MUTATIONS;
GENE-EXPRESSION;
CLONAL EXPANSION;
MODEL;
MTDNA;
SIZE;
DIVERSIFICATION;
HETEROGENEITY;
REPLICATION;
VARIABILITY;
D O I:
10.1098/rspa.2015.0050
中图分类号:
O [数理科学和化学];
P [天文学、地球科学];
Q [生物科学];
N [自然科学总论];
学科分类号:
07 ;
0710 ;
09 ;
摘要:
Stochastic dynamics govern many important processes in cellular biology, and an underlying theoretical approach describing these dynamics is desirable to address a wealth of questions in biology and medicine. Mathematical tools exist for treating several important examples of these stochastic processes, most notably gene expression and random partitioning at single-cell divisions or after a steady state has been reached. Comparatively little work exists exploring different and specific ways that repeated cell divisions can lead to stochastic inheritance of unequilibrated cellular populations. Here we introduce a mathematical formalism to describe cellular agents that are subject to random creation, replication and/or degradation, and are inherited according to a range of random dynamics at cell divisions. We obtain closed-form generating functions describing systems at any time after any number of cell divisions for binomial partitioning and divisions provoking a deterministic or random, subtractive or additive change in copy number, and show that these solutions agree exactly with stochastic simulation. We apply this general formalism to several example problems involving the dynamics of mitochondrial DNA during development and organismal lifetimes.
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