Mathematical modeling of gonadotropin-releasing hormone signaling.

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Gonadotropin-releasing hormone (GnRH) acts via G-protein coupled receptors on pituitary gonadotropes to control of reproduction. These are Gq-coupled receptors that mediate acute effects of GnRH on the exocytotic secretion of luteinizing hormone (LH) and follicle-stimulating hormone (FSH), as well as the chronic regulation of their synthesis. GnRH is secreted in short pulses and GnRH effects on its target cells are dependent upon the dynamics of these pulses. Here we overview GnRH receptors and their signaling network, placing emphasis on pulsatile signaling, and how mechanistic mathematical models and an information theoretic approach have helped further this field.This work was funded Project Grants from MRC (93447) and the BBSRC (J014699). KTA and MV gratefully acknowledge the financial support of the EPSRC via grant EP/N014391/1 and an MRC Biomedical Informatics Fellowship (MR/K021826/1), respectively

Gonadotropin-releasing hormone signaling: An information theoretic approach

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Gonadotropin-releasing hormone (GnRH) is a peptide hormone that mediates central control of reproduction, acting via G-protein coupled receptors that are primarily Gq coupled and mediate GnRH effects on the synthesis and secretion of luteinizing hormone and follicle-stimulating hormone. A great deal is known about the GnRH receptor signaling network but GnRH is secreted in short pulses and much less is known about how gonadotropes decode this pulsatile signal. Similarly, single cell measures reveal considerable cell-cell heterogeneity in responses to GnRH but the impact of this variability on signaling is largely unknown. Ordinary differential equation-based mathematical models have been used to explore the decoding of pulse dynamics and information theory-derived statistical measures are increasingly used to address the influence of cell-cell variability on the amount of information transferred by signaling pathways. Here, we describe both approaches for GnRH signaling, with emphasis on novel insights gained from the information theoretic approach and on the fundamental question of why GnRH is secreted in pulses.This work was funded Project Grants from MRC (93447) and the BBSRC (J014699). KTA and MV gratefully acknowledge the financial support of the EPSRC via grant EP/N014391/1 and an MRC Biomedical Informatics Fellowship (MR/K021826/1), respectively

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

This is the final version of the article. Available from Oxford University Press via the DOI in this record.Information theoretic approaches can be used to quantify information transfer via cell signaling networks. In this study, we do so for gonadotropin-releasing hormone (GnRH) activation of extracellular signal-regulated kinase (ERK) and nuclear factor of activated T cells (NFAT) in large numbers of individual fixed LβT2 and HeLa cells. Information transfer, measured by mutual information between GnRH and ERK or NFAT, was <1 bit (despite 3-bit system inputs). It was increased by sensing both ERK and NFAT, but the increase was <50%. In live cells, information transfer via GnRH receptors to NFAT was also <1 bit and was increased by consideration of response trajectory, but the increase was <10%. GnRH secretion is pulsatile, so we explored information gained by sensing a second pulse, developing a model of GnRH signaling to NFAT with variability introduced by allowing effectors to fluctuate. Simulations revealed that when cell–cell variability reflects rapidly fluctuating effector levels, additional information is gained by sensing two GnRH pulses, but where it is due to slowly fluctuating effectors, responses in one pulse are predictive of those in another, so little information is gained from sensing both. Wet laboratory experiments revealed that the latter scenario holds true for GnRH signaling; within the timescale of our experiments (1 to 2 hours), cell–cell variability in the NFAT pathway remains relatively constant, so trajectories are reproducible from pulse to pulse. Accordingly, joint sensing, sensing of response trajectories, and sensing of repeated pulses can all increase information transfer via GnRH receptors, but in each case the increase is small.This work was supported by Biochemical and Biophysical Science Research Council Grant BBSRC BB/J014699/1 (to C.A.M. and K.T.-A.). M.V. acknowledges the support of the Medical Research Council (a strategic skills development fellowship in biomedical informatics) and the Engineering and Physical Sciences Research Council via Grant EP/N014391/1

Modelling KNDy neurons and gonadotropin-releasing hormone pulse generation

This is the final version. Available on open access from Elsevier via the DOI in this record The pulsatile release of gonadotropin-releasing hormone (GnRH) and its frequency are crucial for healthy reproductive function. To understand what drives GnRH pulses a combination of experimental and mathematical modelling approaches have been used. Early work focussed on the possibility that GnRH pulse generation is an intrinsic feature of GnRH neurons, with autocrine feedback generating pulsatility. However, there is now ample evidence suggesting that a network of upstream KNDy (kisspeptin, neurokinin-B and dynorphin) neurons are the source of this GnRH pulse generator. The interplay of slow positive and negative feedback via neurokinin-B and dynorphin respectively allow the network to act as a relaxation oscillator, driving pulsatile secretion of kisspeptin, and consequently, of GnRH and LH. Here we review the mathematical modelling approaches exploring both scenarios and suggest that with pulsatile GnRH secretion driven by the KNDy pulse generator, autocrine feedback still has the potential to modulate GnRH output.Engineering and Physical Sciences Research Council (EPSRC)Biotechnology & Biological Sciences Research Council (BBSRC

Information Transfer in Gonadotropin-releasing Hormone (GnRH) Signaling: extracellular signal-regulated kinase (ERK)-mediated feedback loops control hormone sensing

The computation model used in the study of GnRH signalling which was used to generate the data appearing in this paper is in ORE at http://hdl.handle.net/10871/27844Cell signaling pathways are noisy communication channels, and statistical measures derived from information theory can be used to quantify the information they transfer. Here we use single cell signaling measures to calculate mutual information as a measure of information transfer via gonadotropin-releasing hormone (GnRH) receptors (GnRHR) to extracellular signal-regulated kinase (ERK) or nuclear factor of activated T-cells (NFAT). This revealed mutual information values <1 bit, implying that individual GnRH-responsive cells cannot unambiguously differentiate even two equally probable input concentrations. Addressing possible mechanisms for mitigation of information loss, we focused on the ERK pathway and developed a stochastic activation model incorporating negative feedback and constitutive activity. Model simulations revealed interplay between fast (min) and slow (min-h) negative feedback loops with maximal information transfer at intermediate feedback levels. Consistent with this, experiments revealed that reducing negative feedback (by expressing catalytically inactive ERK2) and increasing negative feedback (by Egr1-driven expression of dual-specificity phosphatase 5 (DUSP5)) both reduced information transfer from GnRHR to ERK. It was also reduced by blocking protein synthesis (to prevent GnRH from increasing DUSP expression) but did not differ for different GnRHRs that do or do not undergo rapid homologous desensitization. Thus, the first statistical measures of information transfer via these receptors reveals that individual cells are unreliable sensors of GnRH concentration and that this reliability is maximal at intermediate levels of ERK-mediated negative feedback but is not influenced by receptor desensitization.This work was supported by a Biochemical and Biophysical Science Research Council award (BBSRC BB/J014699/1; to C. A. M. and K. T.-A.)

Homologous and heterologous desensitization of guanylyl cyclase-B signaling in GH3 somatolactotropes

The guanylyl cyclases, GC-A and GC-B, are selective receptors for atrial and C-type natriuretic peptides (ANP and CNP, respectively). In the anterior pituitary, CNP and GC-B are major regulators of cGMP production in gonadotropes and yet mouse models of disrupted CNP and GC-B indicate a potential role in growth hormone secretion. In the current study, we investigate the molecular and pharmacological properties of the CNP/GC-B system in somatotrope lineage cells. Primary rat pituitary and GH3 somatolactotropes expressed functional GC-A and GC-B receptors that had similar EC50 properties in terms of cGMP production. Interestingly, GC-B signaling underwent rapid homologous desensitization in a protein phosphatase 2A (PP2A)-dependent manner. Chronic exposure to either CNP or ANP caused a significant down-regulation of both GC-A- and GC-B-dependent cGMP accumulation in a ligand-specific manner. However, this down-regulation was not accompanied by alterations in the sub-cellular localization of these receptors. Heterologous desensitization of GC-B signaling occurred in GH3 cells following exposure to either sphingosine-1-phosphate or thyrotrophin-releasing hormone (TRH). This heterologous desensitization was protein kinase C (PKC)-dependent, as pre-treatment with GF109203X prevented the effect of TRH on CNP/GC-B signaling. Collectively, these data indicate common and distinct properties of particulate guanylyl cyclase receptors in somatotropes and reveal that independent mechanisms of homologous and heterologous desensitization occur involving either PP2A or PKC. Guanylyl cyclase receptors thus represent potential novel therapeutic targets for treating growth-hormone-associated disorders

Measuring luteinising hormone pulsatility with a robotic aptamer-enabled electrochemical reader

Normal reproductive functioning is critically dependent on pulsatile secretion of luteinising hormone (LH). Assessment of LH pulsatility is important for the clinical diagnosis of reproductive disorders, but current methods are hampered by frequent blood sampling coupled to expensive serial immunochemical analysis. Here, we report the development and application of a Robotic APTamer-enabled Electrochemical Reader (RAPTER) electrochemical analysis system to determine LH pulsatility. Through selective evolution of ligands by exponential enrichment (SELEX), we identify DNA aptamers that bind specifically to LH and not to related hormones. The aptamers are integrated into electrochemical aptamer-based (E-AB) sensors on a robotic platform. E-AB enables rapid, sensitive and repeatable determination of LH concentration profiles. Bayesian Spectrum Analysis is applied to determine LH pulsatility in three distinct patient cohorts. This technology has the potential to transform the clinical care of patients with reproductive disorders and could be developed to allow real-time in vivo hormone monitoring

Mathematical models in GnRH research

This is the final version. Available on open access from Wiley via the DOI in this recordMathematical modelling is an indispensable tool in modern biosciences, enabling quantitative analysis and integration of biological data, transparent formulation of our understanding of complex biological systems, and efficient experimental design based on model predictions. This review article provides an overview of the impact that mathematical models had on GnRH research. Indeed, over the last 20 years mathematical modelling has been used to describe and explore the physiology of the GnRH neuron, the mechanisms underlying GnRH pulsatile secretion, and GnRH signalling to the pituitary. Importantly, these models have contributed to GnRH research via novel hypotheses and predictions regarding the bursting behaviour of the GnRH neuron, the role of kisspeptin neurons in the emergence of pulsatile GnRH dynamics, and the decoding of GnRH signals by biochemical signalling networks. We envisage that with the advent of novel experimental technologies, mathematical modelling will have an even greater role to play in our endeavour to understand the complex spatiotemporal dynamics underlying the reproductive neuroendocrine system.Biotechnology & Biological Sciences Research Council (BBSRC)Kings College Londo

Skeletal muscle transcriptomics identifies common pathways in nerve crush injury and ageing

Motor unit remodelling involving repeated denervation and re-innervation occurs throughout life. The efficiency of this process declines with age contributing to neuromuscular deficits. This study investigated differentially expressed genes (DEG) in muscle following peroneal nerve crush to model motor unit remodelling in C57BL/6 J mice. Muscle RNA was isolated at 3 days post-crush, RNA libraries were generated using poly-A selection, sequenced and analysed using gene ontology and pathway tools. Three hundred thirty-four DEG were found in quiescent muscle from (26mnth) old compared with (4-6mnth) adult mice and these same DEG were present in muscle from adult mice following nerve crush. Peroneal crush induced 7133 DEG in muscles of adult and 699 DEG in muscles from old mice, although only one DEG (ZCCHC17) was found when directly comparing nerve-crushed muscles from old and adult mice. This analysis revealed key differences in muscle responses which may underlie the diminished ability of old mice to repair following nerve injury. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13395-021-00283-4

An information theoretic approach to insulin sensing by human kidney podocytes

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordPodocytes are key components of the glomerular filtration barrier (GFB). They are insulin-responsive but can become insulin-resistant, causing features of the leading global cause of kidney failure, diabetic nephropathy. Insulin acts via insulin receptors to control activities fundamental to GFB integrity, but the amount of information transferred is unknown. Here we measure this in human podocytes, using information theory-derived statistics that take into account cell-cell variability. High content imaging was used to measure insulin effects on Akt, FOXO and ERK. Mutual Information (MI) and Channel Capacity (CC) were calculated as measures of information transfer. We find that insulin acts via noisy communication channels with more information flow to Akt than to ERK. Information flow estimates were increased by consideration of joint sensing (ERK and Akt) and response trajectory (live cell imaging of FOXO1-clover translocation). Nevertheless, MI values were always <1Bit as most information was lost through signaling. Constitutive PI3K activity is a predominant feature of the system that restricts the proportion of CC engaged by insulin. Negative feedback from Akt supressed this activity and thereby improved insulin sensing, whereas sensing was robust to manipulation of feedforward signaling by inhibiting PI3K, PTEN or PTP1B. The decisions made by individual podocytes dictate GFB integrity, so we suggest that understanding the information on which the decisions are based will improve understanding of diabetic kidney disease and its treatment.Kidney Research UK Gran