Data Sheet 1_A comparative transcriptomics analysis of mammalian and non-mammalian acute kidney injury (AKI) models.csv

IntroductionAcute kidney injury (AKI) is a complex clinical condition characterized by decline in renal function and widespread transcriptional dysregulation. While transcriptomic studies that compare human and other mammalian models of AKI have provided insight, much less is known about commonalities and contrasts between mammalian models and nontraditional and regenerative laboratory models. Understanding these molecular level responses to injury in both regenerative and non-regenerative models may reveal conserved and unique pathways in renal repair.
MethodsTo investigate transcriptional responses to AKI across species, we incorporated newly available RNA-seq data from zebrafish, axolotl, and spiny mouse models into an expanded cross-species comparative analysis. These were analyzed alongside existing and previously analyzed data from both human and mouse (Mus) models. Differential gene expression and gene-ontology (GO) enrichment analyses we utilized to identify conserved and regeneration-specific during injury and recovery phases.
ResultsComparative transcriptomic analysis revealed distinct transcriptional programs in each species during AKI, including both shared and species-specific responses. Of note, zebrafish show differential expression of apolipoproteins, molecules of increasing interest to the greater field of nephrology. In the recovery setting, we show that animals with regenerative capacity have conserved and divergent transcriptional programs.
DiscussionOur findings demonstrate that non-traditional animal models of AKI, such as zebrafish, axolotls, and spiny mice, provide valuable insights into the molecular basis of kidney regeneration. The identification of conserved and divergent injury responses suggests evolutionary conservation in core AKI mechanisms, while also pointing to regeneration-associated transcriptional programs that could inform future therapeutic strategies. This work underscores the importance of using non-traditional models as well as the value in comparative analysis with traditional models and clinical data.