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Published on: December 14, 2015
Stromal Cell-Derived Factor-1a Autocrine/Paracrine Signaling Contributes to Spatiotemporal Gradients in the Brain
Kassondra N Hickey1, Shannon M Grassi1, Michael R Caplan2
1School of Biological and Health Systems Engineering, Arizona State University, PO Box 879709, Tempe, AZ 85287-9709 USA.
Introduction:
Stromal cell derived factor-1a (SDF-1a) and its receptor CXCR4 modulate stem cell recruitment to neural injury sites. SDF-1a gradients originating from injury sites contribute to chemotactic cellular recruitment. To capitalize on this injury-induced cell recruitment, further investigation of SDF-1a/CXCR4 signaling dynamics are warranted. Here, we studied how exogenous SDF-1a delivery strategies impact spatiotemporal SDF-1a levels and the role autocrine/paracrine signaling plays.
Methods:
We first assessed total SDF-1a and CXCR4 levels over the course of 7 days following intracortical injection of either bolus SDF-1a or SDF-1a loaded nanoparticles in CXCR4-EGFP mice. We then investigated cellular contributors to SDF-1a autocrine/paracrine signaling via time course in vitro measurements of SDF-1a and CXCR4 gene expression following exogenous SDF-1a application. Lastly, we created mathematical models that could recapitulate our in vivo observations.
Results:
In vivo, we found sustained total SDF-1a levels beyond 3 days post injection, indicating endogenous SDF-1a production. We confirmed in vitro that microglia, astrocytes, and brain endothelial cells significantly change SDF-1a and CXCR4 expression after exposure. We found that diffusion-only based mathematical models were unable to capture in vivo SDF-1a spatial distribution. Adding autocrine/paracrine mechanisms to the model allowed for SDF-1a temporal trends to be modeled accurately, indicating it plays an essential role in SDF-1a sustainment.
Conclusions:
We conclude that autocrine/paracrine dynamics play a role in endogenous SDF-1a levels in the brain following exogenous delivery. Implementation of these dynamics are necessary to improving SDF-1a delivery strategies. Further, mathematical models introduced here may be utilized in predicting future outcomes based upon new biomaterial designs.
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