Strain-dependent variation in the early transcriptional response to CNS injury using a cortical explant system - Harris Brent T; Graber David J; Hickey William F (Journal of Neuroinflammation, 2011)
Abstract Background While it is clear that inbred strains of mice have variations in immunological responsiveness, the influence of genetic background following tissue damage in the central nervous system is not fully understood. A cortical explant system was employed as a model for injury to determine whether the immediate transcriptional response to tissue resection revealed differences among three mouse strains. Methods Immunological mRNAs were measured in cerebral cortex from SJL/J, C57BL/6J, and BALB/cJ mice using real time RT-PCR. Freshly isolated cortical tissue and cortical sections incubated in explant medium were examined. Levels of mRNA, normalized to β-actin, were compared using one way analysis of variance with pooled samples from each mouse strain. Results In freshly isolated cerebral cortex, transcript levels of many pro-inflammatory mediators were not significantly different among the strains or too low for comparison. Constitutive, baseline amounts of CD74 and antisecretory factor (ASF) mRNAs, however, were higher in SJL/J and C57BL/6J, respectively. When sections of cortical tissue were incubated in explant medium, increased message for a number of pro-inflammatory cytokines and chemokines occurred within five hours. Message for chemokines, IL-1α, and COX-2 transcripts were higher in C57BL/6J cortical explants relative to SJL/J and BALB/cJ. IL-1β, IL-12/23 p40, and TNF-α were lower in BALB/cJ explants relative to SJL/J and C57BL/6J. Similar to observations in freshly isolated cortex, CD74 mRNA remained higher in SJL/J explants. The ASF mRNA in SJL/J explants, however, was now lower than levels in both C57BL/6J and BALB/cJ explants. Conclusions The short-term cortical explant model employed in this study provides a basic approach to evaluate an early transcriptional response to neurological damage, and can identify expression differences in genes that are influenced by genetic background.