Abnormalities in A-to-I RNA editing patterns in CNS injuries correlate with dynamic changes in cell type composition

Abstract

Adenosine to Inosine (A-to-I) RNA editing is a co- or post-transcriptional mechanism that modifies genomically encoded nucleotides at the RNA level. A-to-I RNA editing is abundant in the brain, and altered editing levels have been reported in various neurological pathologies and following spinal cord injury (SCI). The prevailing concept is that the RNA editing process itself is dysregulated by brain pathologies. Here we analyzed recent RNA-seq data, and found that, except for few mammalian conserved editing sites, editing is significantly higher in neurons than in other cell populations of the brain. We studied A-to-I RNA editing in stab wound injury (SWI) and SCI models and showed that the apparent under-editing observed after injury correlates with an approximately 20% reduction in the relative density of neurons, due to cell death and immune cell infiltration that may account for the observed under-editing. Studies of neuronal and astrocyte cultures and a computational analysis of SCI RNA-seq data further supported the possibility that a reduction in neuronal density is responsible for alterations in the tissue-wide editing patterns upon injury. Thus, our data suggest that the case for a mechanistic linkage between A-to-I RNA editing and brain pathologies should be revisited.

Figure 1. Neurons exhibit elevated editing relative to other brain cell types.

Comparison of global editing measures across cell types isolated from cerebral cortex samples (two replicates for each cell type, one microglia excluded) and three whole cerebral cortex samples (where the editing level is the weighted average over all cell types). (a) SINE editing index, the weighted editing level over all adenosines in SINEs (b) CEI, the weighted editing level over all mammalian conserved sites.

Figure 2. Distinct patterns of RNA editing in mammalian conserved editing sites across brain cells subpopulations.

(a) The editing profile across the conserved sites, presented for each of the samples analyzed in Fig. 1. If coverage did not exceed 15 reads, editing levels was not calculated (black). Editing sites where this cutoff was not achieved in at least two kinds of cell types were discarded. Note that endothelial and microglia samples are lowly expressed in many of the conserved sites. (b) Sanger sequencing validation of differential editing in selected targets using isolated neurons and astrocytes cultures.

Figure 3. ADAR transcripts are over-expressed in neurons.

FPKM values for each cerebral cortex cell-type and whole cerebral cortex samples are presented. Neurons over-express (a) ADAR, (b) ADARB1, and (c) ADARB2 in comparison to other cell types.

Figure 4. Decrease in A-to-I global RNA editing measures following CNS injuries (SWI and SCI).

(a) Schematic illustration of study workflow using microfluidics-based multiplex PCR (mm-PCR) coupled with next generation sequencing. TS: target-specific sequence; CS: custom sequence; BC: barcode sequence; Ad: Illumina adaptor sequence; Seq primer: Illumina sequencing primer; In Seq primer: Index sequencing primer. (b) Reduction in CEI induced by CNS injuries. A similar reduction in global editing levels at conserved sites was observed for the SWI (triangles) and SCI (dots) models. Each of the SCI data points represents a pool of three mice. (c) SINE editing index in control (blue), acute SCI (2d; bright green) and subacute SCI (7d; dark green) samples reveals a decrease in global editing levels following injury.

Figure 5. Changes in ADAR expression levels following CNS injuries.

(a) Relative levels of ADAR isoforms (ADARp110 and ADARp150), ADARB1, and ADARB2 in control and SWI samples (cortex and hippocampus) were quantified by real-time PCR analysis. The y-axis represents the relative expression compared to the CHMP2A reference gene (ΔΔCt method). (b) ADARs expression levels in acute SCI samples (2d) based on FPKM values as reported by Chen et al. (no statistical analysis, due to the small sample size). Error bars represent one standard error of mean.

Figure 6. Reduced A-to-I RNA editing in CNS injuries is explained by a dynamic change in cell type composition.

(a) Representative example of a coronal section of cortex and hippocampus after injury in low magnification, stained with DAPI. Box 1: injured cortex; box 2: cortex on contralateral non-injured side; box 3: injured hippocampus; box 4: hippocampus on contralateral non-injured side. (b) The boxed regions shown in panel A stained with anti-NeuN. Stars in boxes 1 and 3 mark sites of neuron loss as a result of the injury. Scale bar, 79 μm. Note that while neurons are lost at the injury site, the total density of cells (based on the DAPI staining) is higher on the injured side as compared to the contralateral side. (c) Relative mRNA levels of NeuN, a neural marker, measured by real-time PCR analysis (means ± SEM) for cortical and hippocampal tissues 3 days post-injury. (d) Relative mRNA levels of CD45, an immune cell marker (means ± SEM). (e) Brain cells cluster into two distinct groups based on their editome profile: neuronal vs. non-neuronal. Clustering was done based on pairwise Pearson correlation of the editing levels at conserved sites. (f) Differential editing upon injury (SCI, 2d vs. control) correlates with the differences in editing between neurons and astrocytes. We included conserved editing sites (red) and the SINE editing indices (blue). (g) No change in CEI was observed in cultured neurons and astrocytes following injury in an in vitro model.