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，细胞利用激素和神经递质等化学信号相互沟通。这些通常以脉冲形式分泌，其影响取决于脉冲频率，因此了解细胞如何解码脉冲频率对于理解信息如何在细胞之间（和细胞内）传递至关重要。大脑对生殖的控制为科学探索提供了极好的范例和模型。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细胞，刺激其他两种激素（LH 和 FSH）的合成和释放，进而控制性腺中卵子和性类固醇的产生。该系统的一个基本特征是 GnRH 分泌是脉动的。 GnRH 脉冲可用于刺激 LH 和 FSH 分泌，这可用于辅助生殖。相反，GnRH 的持续刺激最终会减少 LH 和 FSH 的分泌。这反过来又减少了性类固醇的合成，从而能够治疗激素依赖性癌症（即乳腺癌、卵巢癌和前列腺癌）。因此，存在一种“钟形”频率响应关系（其中次最大 GnRH 脉冲频率引发最大响应），这是该系统利用的基础，但人们对这种关系的细胞、分子或数学基础知之甚少。为了探索这一点，我们最近开发了新方法来监测 GnRH 脉冲对介导 GnRH 对基因表达影响的两条细胞内生化途径（ERK 和 NFAT 途径）的影响。使用自动荧光显微镜监测活细胞中的这些通路，我们发现它们不是 GnRH 频率解码器（因为它们不表现出先前认为是钟形频率响应关系基础的负反馈）。然而，我们使用这些实验数据开发并验证了细胞水平上 GnRH 作用机制的复杂数学模型，该模型预测频率解码实际上反映了这些途径在介导 GnRH 对基因的影响的 DNA 元件上的收敛。表达。我们独特的湿实验室数据和数学模型产生了一个新颖的理论框架，我们相信它代表了理解脉动 GnRH 信号传导的重大突破。本质上，我们提出 GnRH 脉冲频率解码是 GnRH 细胞信号网络的一个新兴特征（而不是网络内单个蛋白质或通路的特征），但我们仍处于非常早期的阶段，因为数学模型已经尚未经过实验测试。该模型最有趣的方面之一是预测 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可能在青春期前后不同，或者可能在整个月经周期中变化）和该应用程序旨在探索这种可能性。使用用于假设生成的数学模型，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。我们还计划使用湿实验室数据来完善模型，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更好地理解具有生理相关刺激的 GnRH 信号传导，并确定在人类和兽医以及农业和水产养殖领域中进行操作的新目标。这项工作也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