Background: Previous studies examining post-feeding organ regeneration in the Burmese python (Python molurus bivittatus) have identified thousands of genes that are significantly differentially regulated during this process. However, substantial gaps remain in our understanding of coherent mechanisms and specific growth pathways that underlie these rapid and extensive shifts in organ form and function. Here we addressed these gaps by comparing gene expression in the Burmese python heart, liver, kidney, and small intestine across pre- and post-feeding time points (fasted, one day post-feeding, and four days post-feeding), and by conducting detailed analyses of molecular pathways and predictions of upstream regulatory molecules across these organ systems. Results: Identified enriched canonical pathways and upstream regulators indicate that while downstream transcriptional responses are fairly tissue specific, a suite of core pathways and upstream regulator molecules are shared among responsive tissues. Pathways such as mTOR signaling, PPAR/LXR/RXR signaling, and NRF2-mediated oxidative stress response are significantly differentially regulated in multiple tissues, indicative of cell growth and proliferation along with coordinated cell-protective stress responses. Upstream regulatory molecule analyses identify multiple growth factors, kinase receptors, and transmembrane receptors, both within individual organs and across separate tissues. Downstream transcription factors MYC and SREBF are induced in all tissues. Conclusions: These results suggest that largely divergent patterns of post-feeding gene regulation across tissues are mediated by a core set of higher-level signaling molecules. Consistent enrichment of the NRF2-mediated oxidative stress response indicates this pathway may be particularly important in mediating cellular stress during such extreme regenerative growth.
Bibliographical noteFunding Information:
We thank J. Castoe, R. Wostl, and D. Polanco for assistance with laboratory aspects of this work and the Minnesota Supercomputing Institute and the Texas Advanced Computing Center for access to computational resources. Funding Support was provided from startup funds from the University of Texas at Arlington to TAC, and grants from the University of Texas at Arlington Phi Sigma Society to ALA. Additional support was provided by the National Science Foundation (IOB-0466139) to SMS and an NIH Director's Transformative Research Award (1R01DK113597-01) to AC.