Year: 2018
Type: article
Abstract: Microglia function is orchestrated through highly-coupled signaling pathways that depend on calcium (Ca 2+ ). In response to extracellular adenosine triphosphate (ATP), transient increases in intracellular Ca 2+ driven through the activation of purinergic receptors, P 2 X and P 2 Y, are sufficient to promote cytokine synthesis and potentially their release. While steps comprising the pathways bridging purinergic receptor activation with transcriptional responses have been probed in great detail, a quantitative model for how these steps collectively control cytokine production has not been established. Here we developed a minimal computational model that quantitatively links extracellular stimulation of two prominent ionotropic puriner-gic receptors, P 2 X 4 and P 2 X 7 , with the graded production of a gene product, namely the tumor necrosis factor α (TNF α ) cytokine. In addition to Ca 2+ handling mechanisms common to eukaryotic cells, our model includes microglia-specific processes including ATP-dependent P 2 X 4 and P 2 X 7 activation, activation of NFAT transcription factors, and TNF α production. Parameters for this model were optimized to reproduce published data for these processes, where available. With this model, we determined the propensity for TNF α production in microglia, subject to a wide range of ATP exposure amplitudes, frequencies and durations that the cells could encounter in vivo. Furthermore, we have investigated the extent to which modulation of the signal transduction pathways influence TNF α production. Our key findings are that TNF α production via P 2 X 4 is maximized at low ATP when subject to high frequency ATP stimulation, whereas P 2 X 7 contributes most significantly at millimolar ATPranges. Given that Ca 2+ homeostasis in microglia is profoundly important to its function, this computational model provides a quantitative framework to explore hypotheses pertaining to microglial physiology.
Source: The Journal of Physiology
DOI: 10.1113/jp277377
Institution: University of Kentucky
Language: English
Subfield: Physiology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2950319918