酵母极性电路双稳态多尺度建模

IF 5.1 2区 生物学 Q2 CELL BIOLOGY Cells Pub Date : 2024-08-15 DOI:10.3390/cells13161358
Siarhei Hladyshau, Kaiyun Guan, Nivedita Nivedita, Beverly Errede, Denis Tsygankov, Timothy C Elston
{"title":"酵母极性电路双稳态多尺度建模","authors":"Siarhei Hladyshau, Kaiyun Guan, Nivedita Nivedita, Beverly Errede, Denis Tsygankov, Timothy C Elston","doi":"10.3390/cells13161358","DOIUrl":null,"url":null,"abstract":"<p><p>Cell polarity refers to the asymmetric distribution of proteins and other molecules along a specified axis within a cell. Polarity establishment is the first step in many cellular processes. For example, directed growth or migration requires the formation of a cell front and back. In many cases, polarity occurs in the absence of spatial cues. That is, the cell undergoes symmetry breaking. Understanding the molecular mechanisms that allow cells to break symmetry and polarize requires computational models that span multiple spatial and temporal scales. Here, we apply a multiscale modeling approach to examine the polarity circuit of yeast. In addition to symmetry breaking, experiments revealed two key features of the yeast polarity circuit: bistability and rapid dismantling of the polarity site following a loss of signal. We used modeling based on ordinary differential equations (ODEs) to investigate mechanisms that generate these behaviors. Our analysis revealed that a model involving positive and negative feedback acting on different time scales captured both features. We then extend our ODE model into a coarse-grained reaction-diffusion equation (RDE) model to capture the spatial profiles of polarity factors. After establishing that the coarse-grained RDE model qualitatively captures key features of the polarity circuit, we expand it to more accurately capture the biochemical reactions involved in the system. We convert the expanded model to a particle-based model that resolves individual molecules and captures fluctuations that arise from the stochastic nature of biochemical reactions. Our models assume that negative regulation results from negative feedback. However, experimental observations do not rule out the possibility that negative regulation occurs through an incoherent feedforward loop. Therefore, we conclude by using our RDE model to suggest how negative feedback might be distinguished from incoherent feedforward regulation.</p>","PeriodicalId":9743,"journal":{"name":"Cells","volume":null,"pages":null},"PeriodicalIF":5.1000,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11352540/pdf/","citationCount":"0","resultStr":"{\"title\":\"Multiscale Modeling of Bistability in the Yeast Polarity Circuit.\",\"authors\":\"Siarhei Hladyshau, Kaiyun Guan, Nivedita Nivedita, Beverly Errede, Denis Tsygankov, Timothy C Elston\",\"doi\":\"10.3390/cells13161358\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Cell polarity refers to the asymmetric distribution of proteins and other molecules along a specified axis within a cell. Polarity establishment is the first step in many cellular processes. For example, directed growth or migration requires the formation of a cell front and back. In many cases, polarity occurs in the absence of spatial cues. That is, the cell undergoes symmetry breaking. Understanding the molecular mechanisms that allow cells to break symmetry and polarize requires computational models that span multiple spatial and temporal scales. Here, we apply a multiscale modeling approach to examine the polarity circuit of yeast. In addition to symmetry breaking, experiments revealed two key features of the yeast polarity circuit: bistability and rapid dismantling of the polarity site following a loss of signal. We used modeling based on ordinary differential equations (ODEs) to investigate mechanisms that generate these behaviors. Our analysis revealed that a model involving positive and negative feedback acting on different time scales captured both features. We then extend our ODE model into a coarse-grained reaction-diffusion equation (RDE) model to capture the spatial profiles of polarity factors. After establishing that the coarse-grained RDE model qualitatively captures key features of the polarity circuit, we expand it to more accurately capture the biochemical reactions involved in the system. We convert the expanded model to a particle-based model that resolves individual molecules and captures fluctuations that arise from the stochastic nature of biochemical reactions. Our models assume that negative regulation results from negative feedback. However, experimental observations do not rule out the possibility that negative regulation occurs through an incoherent feedforward loop. Therefore, we conclude by using our RDE model to suggest how negative feedback might be distinguished from incoherent feedforward regulation.</p>\",\"PeriodicalId\":9743,\"journal\":{\"name\":\"Cells\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.1000,\"publicationDate\":\"2024-08-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11352540/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cells\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.3390/cells13161358\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cells","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.3390/cells13161358","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

细胞极性是指蛋白质和其他分子在细胞内沿特定轴线的不对称分布。极性的建立是许多细胞过程的第一步。例如,定向生长或迁移需要形成细胞的正面和背面。在许多情况下,极性是在没有空间线索的情况下发生的。也就是说,细胞发生了对称性破坏。要了解细胞打破对称性和极化的分子机制,需要跨越多个空间和时间尺度的计算模型。在这里,我们采用多尺度建模方法来研究酵母的极性回路。除了对称性破坏,实验还揭示了酵母极性回路的两个关键特征:双稳态性和极性位点在信号丢失后的快速解体。我们利用基于常微分方程(ODE)的建模来研究产生这些行为的机制。我们的分析表明,一个涉及在不同时间尺度上起作用的正反馈和负反馈的模型可以捕捉到这两个特征。然后,我们将 ODE 模型扩展为粗粒度反应扩散方程(RDE)模型,以捕捉极性因子的空间分布。在确定粗粒度 RDE 模型定性地捕捉了极性回路的关键特征之后,我们对其进行了扩展,以更准确地捕捉系统中涉及的生化反应。我们将扩展后的模型转换为基于粒子的模型,该模型可解析单个分子并捕捉生化反应的随机性所产生的波动。我们的模型假定负调控来自负反馈。然而,实验观察并不排除负调控通过不连贯的前馈环路发生的可能性。因此,我们最后利用我们的 RDE 模型提出了如何将负反馈与不连贯前馈调节区分开来的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Multiscale Modeling of Bistability in the Yeast Polarity Circuit.

Cell polarity refers to the asymmetric distribution of proteins and other molecules along a specified axis within a cell. Polarity establishment is the first step in many cellular processes. For example, directed growth or migration requires the formation of a cell front and back. In many cases, polarity occurs in the absence of spatial cues. That is, the cell undergoes symmetry breaking. Understanding the molecular mechanisms that allow cells to break symmetry and polarize requires computational models that span multiple spatial and temporal scales. Here, we apply a multiscale modeling approach to examine the polarity circuit of yeast. In addition to symmetry breaking, experiments revealed two key features of the yeast polarity circuit: bistability and rapid dismantling of the polarity site following a loss of signal. We used modeling based on ordinary differential equations (ODEs) to investigate mechanisms that generate these behaviors. Our analysis revealed that a model involving positive and negative feedback acting on different time scales captured both features. We then extend our ODE model into a coarse-grained reaction-diffusion equation (RDE) model to capture the spatial profiles of polarity factors. After establishing that the coarse-grained RDE model qualitatively captures key features of the polarity circuit, we expand it to more accurately capture the biochemical reactions involved in the system. We convert the expanded model to a particle-based model that resolves individual molecules and captures fluctuations that arise from the stochastic nature of biochemical reactions. Our models assume that negative regulation results from negative feedback. However, experimental observations do not rule out the possibility that negative regulation occurs through an incoherent feedforward loop. Therefore, we conclude by using our RDE model to suggest how negative feedback might be distinguished from incoherent feedforward regulation.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Cells
Cells Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (all)
CiteScore
9.90
自引率
5.00%
发文量
3472
审稿时长
16 days
期刊介绍: Cells (ISSN 2073-4409) is an international, peer-reviewed open access journal which provides an advanced forum for studies related to cell biology, molecular biology and biophysics. It publishes reviews, research articles, communications and technical notes. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. Full experimental and/or methodical details must be provided.
期刊最新文献
Asparagine614 Determines the Transport and Function of the Murine Anti-Aging Protein Klotho. N6-Methyladenosine RNA Modification Regulates the Differential Muscle Development in Large White and Ningxiang Pigs. Comparative Analysis of Extracellular Vesicles from Cytotoxic CD8+ αβ T Cells and γδ T Cells. Correction: Szymanska et al. The Effect of Visfatin on the Functioning of the Porcine Pituitary Gland: An In Vitro Study. Cells 2023, 12, 2835. DNA-Binding Protein A Is Actively Secreted in a Calcium-and Inflammasome-Dependent Manner and Negatively Influences Tubular Cell Survival.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1