P2X 7 receptor activity regulation: the role of CD44 proteoglycan GAG chains

P2X7 receptors have received special attention in the literature for their involvement in several diseases characterized by inflammatory processes such as cancer, arthritis, neurodegenerative pathologies and chronic pains

Post-translational allosteric activation of the P2X 7 receptor through glycosaminoglycan chains of CD44 proteoglycans

Here, we present evidence for the positive allosteric modulation of the P2X7 receptor through glycosaminoglycans (GAGs) in CHO (cell line derived from the ovary of the Chinese hamster) cells. The marked potentiation of P2X7 activity through GAGs in the presence of non-saturating agonists concentrations was evident with the endogenous expression of the receptor in CHO cells. The presence of GAGs on the surface of CHO cells greatly increased the sensitivity to adenosine 5′-triphosphate and changed the main P2X7 receptor kinetic parameters EC50, Hill coefficient and Emax. GAGs decreased the allosteric inhibition of P2X7 receptor through Mg2+. GAGs activated P2X7 receptor-mediated cytoplasmic Ca2+ influx and pore formation. Consequently, wild-type CHO-K1 cells were 2.5-fold more sensitive to cell death induced through P2X7 agonists than mutant CHO-745 cells defective in GAGs biosynthesis. In the present study, we provide the first evidence that the P2X7 receptor interacts with CD44 on the CHO-K1 cell surface. Thus, these data demonstrated that GAGs positively modulate the P2X7 receptor, and sCD44 is a part of a regulatory positive feedback loop linking P2X7 receptor activation for the intracellular response mediated through P2X7 receptor stimulation

Statistical Coding and Decoding of Heartbeat Intervals

The heart integrates neuroregulatory messages into specific bands of frequency, such that the overall amplitude spectrum of the cardiac output reflects the variations of the autonomic nervous system. This modulatory mechanism seems to be well adjusted to the unpredictability of the cardiac demand, maintaining a proper cardiac regulation. A longstanding theory holds that biological organisms facing an ever-changing environment are likely to evolve adaptive mechanisms to extract essential features in order to adjust their behavior. The key question, however, has been to understand how the neural circuitry self-organizes these feature detectors to select behaviorally relevant information. Previous studies in computational perception suggest that a neural population enhances information that is important for survival by minimizing the statistical redundancy of the stimuli. Herein we investigate whether the cardiac system makes use of a redundancy reduction strategy to regulate the cardiac rhythm. Based on a network of neural filters optimized to code heartbeat intervals, we learn a population code that maximizes the information across the neural ensemble. The emerging population code displays filter tuning proprieties whose characteristics explain diverse aspects of the autonomic cardiac regulation, such as the compromise between fast and slow cardiac responses. We show that the filters yield responses that are quantitatively similar to observed heart rate responses during direct sympathetic or parasympathetic nerve stimulation. Our findings suggest that the heart decodes autonomic stimuli according to information theory principles analogous to how perceptual cues are encoded by sensory systems