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

Temporal variation in DNA methylation during gonadal development in a reptile with temperature-dependent sex determination

DNA methylation plays a significant role in transducing external environmental signals to a cellular response in reptiles; however, whether the methylation patterns are conserved across species remains unclear. Here, we examined the genome-wide DNA methylation differentiation between male and female hatchling gonads of the temperature-dependent sex determination (TSD) Mauremys mutica (M. mutica) using methylation-dependent restriction-site associated DNA sequencing (MethylRAD-seq) to test differentially methylated genes underlying sexual development. Several categories, including heat shock genes (HSP90A, HSP30C), histone- (KDM8) and ubiquitin-related genes (TRIM39), kinases (WNK3) and gonad differentiation or gonadal development related genes (HSD17B8, HSD17B12), were identified as candidates for future study. Additionally, we identified several regulatory pathways potentially mediating TSD thermosensitivity such as the GnRH signaling pathway and calcium signaling pathway. These findings provide evidence that sexually dimorphic DNA methylation may be associated with sex determination or sex differentiation in TSD M. mutica.

Mathematical models in GnRH research

Mathematical 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.

An information theoretic approach to insulin sensing by human kidney podocytes

Podocytes 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.