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在整体水平上的单一酶级联中的操作状态。

Operating regimes in a single enzymatic cascade at ensemble-level.

机构信息

Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, India.

出版信息

PLoS One. 2019 Aug 1;14(8):e0220243. doi: 10.1371/journal.pone.0220243. eCollection 2019.

Abstract

Single enzymatic cascade, ubiquitously found in cellular signaling networks, is a phosphorylation-dephosphorylation reaction cycle causing a transition between inactive and active states of a protein catalysed by kinase and phosphatase, respectively. Steady-state information processing ability of such a cycle (e.g., MAPK cascade) has been classified into four qualitatively different operating regimes, viz., hyperbolic (H), signal-transducing (ST), threshold-hyperbolic (TH) and ultrasensitive (U). These four regimes represent qualitatively different dose-response curves, that is, relationship between concentrations of input kinase (e.g., pMEK) and response activated protein (e.g., pERK). Regimes were identified using a deterministic model accounting for population-averaged behavior only. Operating regimes can be strongly influenced by the inherently present cell-to-cell variability in an ensemble of cells which is captured in the form of pMEK and pERK distributions using reporter-based single-cell experimentation. In this study, we show that such experimentally acquired snapshot pMEK and pERK distribution data of a single MAPK cascade can be directly used to infer the underlying operating regime even in the absence of a dose-response curve. This deduction is possible primarily due to the presence of a monotonic relationship between experimental observables RIQR, ratio of the inter-quartile range of the pERK and pMEK distribution pairs and RM, ratio of the medians of the distribution pair. We demonstrate this relationship by systematic analysis of a quasi-steady state approximated model superimposed with an input gamma distribution constrained by the stimulus strength specific pMEK distribution measured on Jurkat-T cells stimulated with PMA. As a first, we show that introduction of cell-to-cell variability only in the upstream kinase achieved by superimposition of an appropriate input pMEK distribution on the dose-response curve can predict bimodal response pERK distribution in ST regime. Implementation of the proposed method on the input-response distribution pair obtained in stimulated Jurkat-T cells revealed that while low-dosage PMA stimulation preserves the H regime observed in resting cells, high-dosage causes H to ST regime transition.

摘要

细胞信号转导网络中广泛存在的单一酶级联反应是一种磷酸化-去磷酸化反应循环,分别由激酶和磷酸酶催化蛋白质从非活性状态向活性状态转变。这种循环的稳态信息处理能力(例如 MAPK 级联)已被分类为四种不同的操作模式,即双曲线(H)、信号转导(ST)、阈值双曲线(TH)和超敏(U)。这四种模式代表了不同的剂量-反应曲线,即输入激酶(例如 pMEK)和激活蛋白(例如 pERK)浓度之间的关系。这些模式是使用仅考虑群体平均行为的确定性模型确定的。操作模式会受到细胞间固有变异性的强烈影响,这种变异性以基于报告器的单细胞实验中 pMEK 和 pERK 分布的形式表现出来。在这项研究中,我们表明,即使没有剂量-反应曲线,也可以直接使用单个 MAPK 级联的这种实验获得的 snapshot pMEK 和 pERK 分布数据来推断潜在的操作模式。这种推断主要是由于实验可观察量 RIQR(pERK 和 pMEK 分布对的四分位距比)和 RM(分布对中位数比)之间存在单调关系。我们通过对受刺激的 Jurkat-T 细胞中 PMA 刺激下测量的特定于刺激强度的 pMEK 分布约束的输入伽马分布进行准稳态近似模型的系统分析,证明了这种关系。首先,我们表明,仅通过在剂量-反应曲线上叠加适当的输入 pMEK 分布来引入上游激酶的细胞间变异性,可以预测 ST 模式下的双模态响应 pERK 分布。在受刺激的 Jurkat-T 细胞的输入-响应分布对上实施该方法表明,低剂量 PMA 刺激保留了静止细胞中观察到的 H 模式,而高剂量则导致 H 向 ST 模式转变。

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