{"title":"带有自动回路的最小正反馈网络中出现的多稳定性、滞后和双相动态的逻辑依赖性","authors":"Akriti Srivastava, Mubasher Rashid","doi":"arxiv-2404.05379","DOIUrl":null,"url":null,"abstract":"Cellular decision-making (CDM) is a dynamic phenomenon often controlled by\nregulatory networks defining interactions between genes and transcription\nfactor proteins. Traditional studies have focussed on molecular switches such\nas positive feedback circuits that exhibit at most bistability. However,\nhigher-order dynamics such as tristability is also prominent in many biological\nprocesses. It is thus imperative to identify a minimal circuit that can alone\nexplain mono, bi, and tristable dynamics. In this work, we consider a\ntwo-component positive feedback network with an autoloop and explore these\nregimes of stability for different degrees of multimerization and the choice of\nBoolean logic functions. We report that this network can exhibit numerous\ndynamical scenarios such as bi-and tristability, hysteresis, and biphasic\nkinetics, explaining the possibilities of abrupt cell state transitions and the\nsmooth state swap without a step-like switch. Specifically, while with\nmonomeric regulation and competitive OR logic, the circuit exhibits mono-and\nbistability and biphasic dynamics, with non-competitive AND and OR logics only\nmonostability can be achieved. To obtain bistability in the latter cases, we\nshow that the autoloop must have (at least) dimeric regulation. In pursuit of\nhigher-order stability, we show that tristability occurs with higher degrees of\nmultimerization and with non-competitive OR logic only. Our results, backed by\nrigorous analytical calculations and numerical examples, thus explain the\nassociation between multistability, multimerization, and logic in this minimal\ncircuit. Since this circuit underlies various biological processes, including\nepithelial-mesenchymal transition which often drives carcinoma metastasis,\nthese results can thus offer crucial inputs to control cell state transition by\nmanipulating multimerization and the logic of regulation in cells.","PeriodicalId":501325,"journal":{"name":"arXiv - QuanBio - Molecular Networks","volume":"50 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Logic-dependent emergence of multistability, hysteresis, and biphasic dynamics in a minimal positive feedback network with an autoloop\",\"authors\":\"Akriti Srivastava, Mubasher Rashid\",\"doi\":\"arxiv-2404.05379\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cellular decision-making (CDM) is a dynamic phenomenon often controlled by\\nregulatory networks defining interactions between genes and transcription\\nfactor proteins. Traditional studies have focussed on molecular switches such\\nas positive feedback circuits that exhibit at most bistability. However,\\nhigher-order dynamics such as tristability is also prominent in many biological\\nprocesses. It is thus imperative to identify a minimal circuit that can alone\\nexplain mono, bi, and tristable dynamics. In this work, we consider a\\ntwo-component positive feedback network with an autoloop and explore these\\nregimes of stability for different degrees of multimerization and the choice of\\nBoolean logic functions. We report that this network can exhibit numerous\\ndynamical scenarios such as bi-and tristability, hysteresis, and biphasic\\nkinetics, explaining the possibilities of abrupt cell state transitions and the\\nsmooth state swap without a step-like switch. 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引用次数: 0
摘要
细胞决策(CDM)是一种动态现象,通常由定义基因和转录因子蛋白之间相互作用的调控网络控制。传统研究侧重于分子开关,如最多表现出双稳态的正反馈电路。然而,三稳态等高阶动力学在许多生物过程中也很突出。因此,当务之急是找出一种能单独解释单稳态、双稳态和三稳态动力学的最小电路。在这项研究中,我们考虑了具有自动环路的双分量正反馈网络,并探索了不同多聚化程度和布尔逻辑函数选择下的稳定状态。我们发现,这种网络可以表现出多种动力学情景,如双向和三向稳定性、滞后性和双镰刀动力学,从而解释了细胞状态突然转换和无阶跃开关的平滑状态交换的可能性。具体来说,在单调调节和竞争性 OR 逻辑下,电路表现出单双稳态和双相动力学,而在非竞争性 AND 和 OR 逻辑下,只能实现单稳态。要在后一种情况下获得双稳态性,我们需要证明自动环路必须(至少)具有二聚调节。为了追求更高阶的稳定性,我们证明了在更高的多聚化程度下以及仅在非竞争性 OR 逻辑下会出现三稳态。我们的研究结果得到了严密的分析计算和数字实例的支持,从而解释了这一最小电路中多态性、多聚化和逻辑之间的关联。由于这一电路是各种生物过程的基础,包括上皮-间质转化过程,而上皮-间质转化过程往往是癌细胞转移的驱动因素,因此这些结果可以为通过操纵细胞中的多聚化和调控逻辑来控制细胞状态转化提供重要的输入。
Logic-dependent emergence of multistability, hysteresis, and biphasic dynamics in a minimal positive feedback network with an autoloop
Cellular decision-making (CDM) is a dynamic phenomenon often controlled by
regulatory networks defining interactions between genes and transcription
factor proteins. Traditional studies have focussed on molecular switches such
as positive feedback circuits that exhibit at most bistability. However,
higher-order dynamics such as tristability is also prominent in many biological
processes. It is thus imperative to identify a minimal circuit that can alone
explain mono, bi, and tristable dynamics. In this work, we consider a
two-component positive feedback network with an autoloop and explore these
regimes of stability for different degrees of multimerization and the choice of
Boolean logic functions. We report that this network can exhibit numerous
dynamical scenarios such as bi-and tristability, hysteresis, and biphasic
kinetics, explaining the possibilities of abrupt cell state transitions and the
smooth state swap without a step-like switch. Specifically, while with
monomeric regulation and competitive OR logic, the circuit exhibits mono-and
bistability and biphasic dynamics, with non-competitive AND and OR logics only
monostability can be achieved. To obtain bistability in the latter cases, we
show that the autoloop must have (at least) dimeric regulation. In pursuit of
higher-order stability, we show that tristability occurs with higher degrees of
multimerization and with non-competitive OR logic only. Our results, backed by
rigorous analytical calculations and numerical examples, thus explain the
association between multistability, multimerization, and logic in this minimal
circuit. Since this circuit underlies various biological processes, including
epithelial-mesenchymal transition which often drives carcinoma metastasis,
these results can thus offer crucial inputs to control cell state transition by
manipulating multimerization and the logic of regulation in cells.