{"title":"Theory of epigenetic switching due to stochastic histone mark loss during DNA replication.","authors":"Ander Movilla Miangolarra, Martin Howard","doi":"10.1088/1478-3975/ad942c","DOIUrl":null,"url":null,"abstract":"<p><p>How much information does a cell inherit from its ancestors beyond its genetic sequence? What are the epigenetic mechanisms that allow this? Despite the rise in available epigenetic data, how such information is inherited through the cell cycle is still not fully understood. Often, epigenetic marks can display bistable behaviour and their bistable state is transmitted to daughter cells through the cell cycle, providing the cell with a form of memory. However, loss-of-memory events also take place, where a daughter cell switches epigenetic state (with respect to the mother cell). Here, we develop a framework to compute these epigenetic switching rates, for the case when they are driven by DNA replication, i.e. the frequency of loss-of-memory events due to replication. We consider the dynamics of histone modifications during the cell cycle deterministically, except at DNA replication, where nucleosomes are randomly distributed between the two daughter DNA strands, which is therefore implemented stochastically. This hybrid stochastic-deterministic approach enables an analytic derivation of the replication-driven switching rate. While retaining great simplicity, this framework can explain experimental switching rate data, establishing its biological importance as a framework to quantitatively study epigenetic inheritance.</p>","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":" ","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11605279/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physical biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1088/1478-3975/ad942c","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
How much information does a cell inherit from its ancestors beyond its genetic sequence? What are the epigenetic mechanisms that allow this? Despite the rise in available epigenetic data, how such information is inherited through the cell cycle is still not fully understood. Often, epigenetic marks can display bistable behaviour and their bistable state is transmitted to daughter cells through the cell cycle, providing the cell with a form of memory. However, loss-of-memory events also take place, where a daughter cell switches epigenetic state (with respect to the mother cell). Here, we develop a framework to compute these epigenetic switching rates, for the case when they are driven by DNA replication, i.e. the frequency of loss-of-memory events due to replication. We consider the dynamics of histone modifications during the cell cycle deterministically, except at DNA replication, where nucleosomes are randomly distributed between the two daughter DNA strands, which is therefore implemented stochastically. This hybrid stochastic-deterministic approach enables an analytic derivation of the replication-driven switching rate. While retaining great simplicity, this framework can explain experimental switching rate data, establishing its biological importance as a framework to quantitatively study epigenetic inheritance.
除了基因序列,细胞还能从祖先那里继承多少信息?有哪些表观遗传机制可以做到这一点?尽管现有的表观遗传学数据不断增加,但人们对这些信息如何在细胞周期中遗传仍不完全清楚。通常情况下,表观遗传标记会表现出双稳态行为,其双稳态状态会通过细胞周期传递给子细胞,为细胞提供一种记忆形式。然而,也会发生失忆事件,即子细胞(相对于母细胞)改变表观遗传状态。在此,我们开发了一个框架,用于计算这些表观遗传学切换率,即由 DNA 复制驱动的表观遗传学切换率,也就是由复制导致的失忆事件的频率。我们以确定的方式考虑组蛋白修饰在细胞周期中的动态变化,但 DNA 复制时除外,此时核小体在两条子 DNA 链之间随机分布,因此我们以随机的方式实现组蛋白修饰的动态变化。这种随机-确定混合方法可以分析推导出复制驱动的转换率。这个框架非常简单,却能解释实验中的切换率数据,从而确立了它作为定量研究表观遗传框架的生物学重要性。
期刊介绍:
Physical Biology publishes articles in the broad interdisciplinary field bridging biology with the physical sciences and engineering. This journal focuses on research in which quantitative approaches – experimental, theoretical and modeling – lead to new insights into biological systems at all scales of space and time, and all levels of organizational complexity.
Physical Biology accepts contributions from a wide range of biological sub-fields, including topics such as:
molecular biophysics, including single molecule studies, protein-protein and protein-DNA interactions
subcellular structures, organelle dynamics, membranes, protein assemblies, chromosome structure
intracellular processes, e.g. cytoskeleton dynamics, cellular transport, cell division
systems biology, e.g. signaling, gene regulation and metabolic networks
cells and their microenvironment, e.g. cell mechanics and motility, chemotaxis, extracellular matrix, biofilms
cell-material interactions, e.g. biointerfaces, electrical stimulation and sensing, endocytosis
cell-cell interactions, cell aggregates, organoids, tissues and organs
developmental dynamics, including pattern formation and morphogenesis
physical and evolutionary aspects of disease, e.g. cancer progression, amyloid formation
neuronal systems, including information processing by networks, memory and learning
population dynamics, ecology, and evolution
collective action and emergence of collective phenomena.