Phosphatases are predicted to govern prolactin-mediated JAK–STAT signaling in pancreatic beta cells

Abstract

Patients with diabetes are unable to produce a sufficient amount of insulin to properly regulate their blood glucose levels. One potential method of treating diabetes is to increase the number of insulin-secreting beta cells in the pancreas to enhance insulin secretion. It is known that during pregnancy, pancreatic beta cells proliferate in response to the pregnancy hormone, prolactin (PRL). Leveraging this proliferative response to PRL may be a strategy to restore endogenous insulin production for patients with diabetes. To investigate this potential treatment, we previously developed a computational model to represent the PRL-mediated JAK–STAT signaling pathway in pancreatic beta cells. Here, we applied the model to identify the importance of particular signaling proteins in shaping the response of a population of beta cells. We simulated a population of 10 000 heterogeneous cells with varying initial protein concentrations responding to PRL stimulation. We used partial least squares regression to analyze the significance and role of each of the varied protein concentrations in producing the response of the cell. Our regression models predict that the concentrations of the cytosolic and nuclear phosphatases strongly influence the response of the cell. The model also predicts that increasing PRL receptor strengthens negative feedback mediated by the inhibitor suppressor of cytokine signaling. These findings reveal biological targets that can potentially be used to modulate the proliferation of pancreatic beta cells to enhance insulin secretion and beta cell regeneration in the context of diabetes.

Systematic Bayesian Posterior Analysis Guided by Kullback-Leibler Divergence Facilitates Hypothesis Formation

“…We tested our approach on a biologically-relevant mathematical model of pancreatic beta signaling and demonstrate that it can be used to generate alternative hypotheses. This model was previously established in Mortlock et al (Mortlock et al, 2021) and most recently used to investigate cell heterogeneity (Simoni et al, 2022). Before applying our approach, we improved upon the original Bayesian inference procedure presented in Mortlock et al After verifying convergence of the posterior and verifying that our model adequately explained the available experimental data, we used our KL divergence-based approach to determine if there are multiple biological mechanisms that explain the observed protein dynamics.…”

“…First, we apply our KL divergence ranking to an established example of Bayesian hypothesis formation previously presented in the literature (Tötsch and Hoffmann, 2020). Then, we apply our ranking in a novel study of a computational model of prolactin-induced JAK2-STAT5 signaling, which was previously established in in Mortlock et al (Mortlock et al, 2021) and most recently used to investigate cell heterogeneity (Simoni et al, 2022). In both examples, we used KL divergence to rank parameters by how much information they gain from experimental data.…”

“…The rate equations are governed by mass action kinetics or Michaelis-Menten kinetics. This model was most recently used to study the effect of heterogeneity in the intracellular protein concentrations (Simoni et al, 2022). Now, we use it as the basis for this work.…”

An update on pancreatic regeneration mechanisms: Searching for paths to a cure for type 2 diabetes

“…The PRL receptor (PRLR) is a cytokine class-1 receptor and activates the JAK2-STAT intracellular pathway, as well as Ras/Rap/MAPK and PI3K/AKT/mTOR signaling cascades, which strongly influence cellular response by modulating concentrations of cytosolic and nuclear phosphatases [ 49 ]. Among the various effects, the activation of JAK2-STAT5 signaling induces the transcription of the gene coding for Pbk kinase which has a crucial role in the β-cell proliferation [ 50 ].…”

“…Serotonin acts in a paracrine fashion contributing to β-cell expansion. Animal studies Human studies Effect Hormones Prolactin and placental lactogen ↑ β-cell serotonin secretion [ 48 ] ↑JAK2/STAT5 and PI3K-AKT-mTOR signaling pathway [ 49 ] ↓ Menin1 expression [ 42 ] β-cell proliferation Serotonin Co-secreted with insulin by β-cells ↑β-cell expansion (paracrine action) [ 48 ] Β-cell expansion Intracellular factors JAK2/STAT5 signalling ↑Pbk kinase [ 50 ] β-cell proliferation PI3K/AKT/mTOR signalling ↑β-cell growth and differentiation [ 66 ] β-cell growth and differentiation Foxd3 Maintain glucose homeostasis. ↑ β cell expansion [ 51 ] Expressed in human islets [ 51 ] β-cell expansion FoxM1 cell-cycle transcription factor [ 52 , 53 ] β-cell proliferation Menin1 maintain cell cycle inhibitors p27 and p18 active [ 42 ] β-cell proliferation (due to downregulation) Others Hepatocyte growth factor (HGF) decreased β-cell regeneration and increased β-cell apoptosis in c-Met KO mice [ 56 ] Circulating HGF markedly increased during pregnancy [ 67 ] mitogenic, antiapoptotic and insulinotropic agent for the β-cell Micro-RNA modulate β-cell gene expression [ 57 , 59 ] β-cell differentiation, proliferation, survival Macrophages Pancreatic macrophages depletion compromises β-cell proliferation and leads to glucose intolerance [ 63 ] …”