Decoding gonadotropin-releasing hormone (GnRH) pulse frequency

解码促性腺激素释放激素 (GnRH) 脉冲频率

• 批准号: BB/J014699/1
• 负责人: Craig McArdle
• 金额: $ 76.79万
• 依托单位: University of Bristol
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2012
• 资助国家: 英国
• 起止时间: 2012 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FJ014699%2F1
• 关键词: Decoding; gonadotropin; releasing; hormone; GnRH

Within the body, cells communicate with one another using chemical signals such as hormones and neurotransmitters. These are often secreted in pulses and their effects are dependent upon pulse frequency so understanding how cells decode pulse frequency is fundamental to understanding how information is conveyed between (and within) cells. The brain's control of reproduction provides an excellent example and model for scientific exploration. Here, a neurohormone called GnRH (gonadotropin-releasing hormone) acts on cells in the pituitary gland to stimulate the synthesis and release of two other hormones (LH and FSH) that, in turn control the production of eggs and sex steroids in the gonads. A fundamental feature of this system is that GnRH secretion is pulsatile. Pulses of GnRH can be used to stimulate LH and FSH secretion and this is exploited in assisted reproduction. In contrast, sustained stimulation with GnRH ultimately reduces LH and FSH secretion. This, in turn reduces synthesis of sex steroids enabling treatment of hormone-dependent cancers (i.e. breast, ovary and prostate cancers). Thus, there is a "bell-shaped" frequency-response relationship (where sub-maximal GnRH pulse frequency elicits maximal responses) that underlies exploitation of the system, but remarkably little is known about the cellular, molecular or mathematical basis of this relationship. To explore this we have recently developed novel methods for monitoring effects of GnRH pulses on two intracellular biochemical pathways that mediate GnRH effects on gene expression (ERK and NFAT pathways). Using automated fluorescence microscopy to monitor these pathways in live cells we found that they are not GnRH frequency decoders (because they do not exhibit the negative feedback previously thought to underlie the bell-shaped frequency response relationship). However, we used this experimental data to develop and validate a sophisticated mathematical model for the mechanisms of GnRH action at the cellular level, and this model predicts that frequency decoding actually reflects the convergence of these pathways on the DNA elements that mediate GnRH effects on gene expression. Our unique wet-lab data and mathematical modelling has generated a novel theoretical frame-work that we believe represents a major breakthrough in understanding pulsatile GnRH signalling. In essence we are proposing that GnRH pulse frequency decoding is an emergent feature of the GnRH cell signalling network (rather than a characteristic of a single protein or pathway within the network) but we are still at a very early stage, as the mathematical model has not yet been tested experimentally. One of the most intriguing aspects of the modelling is the prediction that GnRH frequency-response relationships will be regulable rather than fixed (i.e. that the optimal pulse frequency for GnRH effects could differ before and after puberty, or could vary through the menstrual cycle) and this application aims to explore this possibility. Using the mathematical model for hypothesis generation, we now plan to define how some of the key model variables (such as GnRH receptor number and exposure to sex steroids) influence GnRH frequency-response relationships. We also plan to use the wet-lab data to refine the model, and to use a more formal mathematical approach for development and extension of the model. The direct importance of the planned work lies in the potential for greater understanding of GnRH signalling with physiologically relevant stimulation and for identifying novel targets for manipulation in the context in human and veterinary medicine as well as agriculture and aquaculture. The work is also likely to have widespread application because the structures and mechanisms considered are widespread in biological systems.

在体内，细胞使用激素和神经递质等化学信号相互通信。这些通常是在脉冲中分泌的，它们的效果取决于脉冲频率，因此了解细胞如何解码脉冲频率是理解细胞之间（和内部）如何传达信息的基础。大脑对繁殖的控制为科学探索提供了一个很好的例子和模型。在这里，一种称为GNRH（促性腺激素释放激素）的神经激素作用于垂体中的细胞，以刺激另外两种激素（LH和FSH）的合成和释放，进而控制了贡纳德蛋白中卵和性类固醇的产生。该系统的一个基本特征是GNRH分泌是脉动的。 GnRH的脉冲可用于刺激LH和FSH分泌，这在辅助繁殖中被利用。相比之下，GNRH持续刺激最终减少了LH和FSH分泌。这反过来降低了性类固醇的合成，从而可以治疗激素依赖性癌症（即乳腺癌，卵巢和前列腺癌）。因此，存在一个“钟形”的频率响应关系（其中亚最大GNRH脉冲频率引起最大响应），这是对系统的开发的基础，但是对这种关系的细胞，分子或数学基础知之甚少。为了探讨这一点，我们最近开发了新的方法来监测GnRH脉冲对两个细胞内生化途径的影响，这些途径介导GnRH对基因表达的影响（ERK和NFAT途径）。使用自动荧光显微镜来监测活细胞中的这些途径，我们发现它们不是GnRH频率解码器（因为它们没有表现出以前认为是贝尔形频率响应关系的负反馈）。但是，我们使用此实验数据来开发和验证一个复杂的数学模型，以用于在细胞水平上GNRH作用的机理，并且该模型预测频率解码实际上反映了这些途径在介导GnRH对基因表达影响的DNA元件上的收敛性。我们独特的湿地数据和数学建模产生了一种新颖的理论框架 - 我们认为这代表了理解脉动GNRH信号传导的重大突破。从本质上讲，我们提出的是GnRH脉冲频率解码是GnRH细胞信号网络的新兴特征（而不是网络中单个蛋白质或途径的特征），但是我们仍处于很早的阶段，因为数学模型尚未经过实验测试。建模最吸引人的方面之一是预测，GNRH频率响应关系将是可调节的，而不是固定的（即，GNRH效应的最佳脉冲频率在青春期之前和之后可能会有所不同，或者在月经周期可能会有所不同），并且该应用程序旨在探索这种可能性。使用数学模型进行假设产生，我们现在计划定义一些关键模型变量（例如GNRH受体数量和性类固醇暴露）如何影响GnRH频率响应关系。我们还计划使用湿的数据来完善模型，并使用更正式的数学方法来开发和扩展模型。计划工作的直接重要性在于有可能通过生理相关的刺激对GNRH信号进行更多了解，并在人类和兽医医学以及农业和水产养殖中确定对操纵的新目标。这项工作也很可能具有广泛的应用，因为所考虑的结构和机制在生物系统中广泛存在。

项目成果

Mathematical modeling of gonadotropin-releasing hormone signaling.

• DOI: 10.1016/j.mce.2016.08.022
• 发表时间: 2017-07-05
• 期刊: Molecular and cellular endocrinology
• 影响因子: 4.1
• 作者: Pratap A;Garner KL;Voliotis M;Tsaneva-Atanasova K;McArdle CA
• 通讯作者: McArdle CA

Gonadotropin-releasing hormone signaling: An information theoretic approach.

促性腺激素释放激素信号传导：一种信息论方法。

• DOI: 10.1016/j.mce.2017.07.028
• 发表时间: 2018
• 期刊: Molecular and cellular endocrinology
• 影响因子: 4.1
• 作者: Voliotis M

Exploring Dynamics and Noise in Gonadotropin-Releasing Hormone (GnRH) Signaling.

探索促性腺激素释放激素 (GnRH) 信号传导的动态和噪声。

• DOI: 10.1007/978-1-4939-8618-7_19
• 发表时间: 2018
• 期刊: Methods in molecular biology (Clifton, N.J.)
• 作者: Voliotis M

Information Transfer in Gonadotropin-releasing Hormone (GnRH) Signaling: EXTRACELLULAR SIGNAL-REGULATED KINASE (ERK)-MEDIATED FEEDBACK LOOPS CONTROL HORMONE SENSING.

• DOI: 10.1074/jbc.m115.686964
• 发表时间: 2016-01-29
• 期刊: The Journal of biological chemistry
• 作者: Garner KL;Perrett RM;Voliotis M;Bowsher C;Pope GR;Pham T;Caunt CJ;Tsaneva-Atanasova K;McArdle CA
• 通讯作者: McArdle CA

Information Transfer via Gonadotropin-Releasing Hormone Receptors to ERK and NFAT: Sensing GnRH and Sensing Dynamics.

• DOI: 10.1210/js.2016-1096
• 发表时间: 2017-04-01
• 期刊: Journal of the Endocrine Society
• 影响因子: 4.1
• 作者: Garner KL;Voliotis M;Alobaid H;Perrett RM;Pham T;Tsaneva-Atanasova K;McArdle CA
• 通讯作者: McArdle CA