bioRxivNeurosciencePreprint
Innate immunity pathways activate cell proliferation after penetrating traumatic brain injury in adult Drosophila
Khailee Marischuk, Kassi L. Crocker, Shawn M. Ahern-Djamali, Grace Boekhoff‐FalkiD
Abstract
We are utilizing an adult penetrating traumatic brain injury (PTBI) model in Drosophila to investigate regenerative mechanisms after damage to the central brain. We focused on cell proliferation as an early event in the regenerative process. To identify candidate pathways that may trigger cell proliferation following PTBI, we utilized RNA-Seq. We find that transcript levels for components of both Toll and Immune Deficiency (Imd) innate immunity pathways are rapidly and highly upregulated post-PTBI. We then tested mutants for the NF-{kappa}B transcription factors of the Toll and Imd pathways, Dorsal-related immunity factor (Dif) and Relish (Rel) respectively. We find that loss of either or both Dif and Rel results in loss of cell proliferation after injury. We then tested canonical downstream targets of Drosophila innate immune signaling, the antimicrobial peptides (AMPs), and find that they are not required for cell proliferation following PTBI. This suggests that there are alternative targets of Toll and Imd signaling that trigger cell division after injury. Furthermore, we find that while AMP levels are substantially elevated after PTBI, their levels revert to near baseline within 24 hours. Finally, we identify tissue-specific requirements for Dif and Rel. Taken together, these results indicate that the innate immunity pathways play an integral role in the regenerative response. Innate immunity previously has been implicated as both a potentiator and an inhibitor of regeneration. Our work suggests that modulation of innate immunity may be essential to prevent adverse outcomes. Thus, this work is likely to inform future experiments to dissect regenerative mechanisms in higher organisms.
- organism: Drosophila
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: experimental assay
- Citations
- 2
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