Pai VP et al. (2016), Genome-wide analysis reveals conserved transcri...

XB-ART-52496

Regeneration (Oxf) 2016 Feb 01;31:3-25. doi: 10.1002/reg2.48.

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Genome-wide analysis reveals conserved transcriptional responses downstream of resting potential change in Xenopus embryos, axolotl regeneration, and human mesenchymal cell differentiation.

Pai VP , Martyniuk CJ , Echeverri K , Sundelacruz S , Kaplan DL , Levin M .

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Endogenous bioelectric signaling via changes in cellular resting potential (V mem) is a key regulator of patterning during regeneration and embryogenesis in numerous model systems. Depolarization of V mem has been functionally implicated in dedifferentiation, tumorigenesis, anatomical re-specification, and appendage regeneration. However, no unbiased analyses have been performed to understand genome-wide transcriptional responses to V mem change in vivo. Moreover, it is unknown which genes or gene networks represent conserved targets of bioelectrical signaling across different patterning contexts and species. Here, we use microarray analysis to comparatively analyze transcriptional responses to V mem depolarization. We compare the response of the transcriptome during embryogenesis (Xenopus development), regeneration (axolotl regeneration), and stem cell differentiation (human mesenchymal stem cells in culture) to identify common networks across model species that are associated with depolarization. Both subnetwork enrichment and PANTHER analyses identified a number of key genetic modules as targets of V mem change, and also revealed important (well-conserved) commonalities in bioelectric signal transduction, despite highly diverse experimental contexts and species. Depolarization regulates specific transcriptional networks across all three germ layers (ectoderm, mesoderm, and endoderm) such as cell differentiation and apoptosis, and this information will be used for developing mechanistic models of bioelectric regulation of patterning. Moreover, our analysis reveals that V mem change regulates transcripts related to important disease pathways such as cancer and neurodegeneration, which may represent novel targets for emerging electroceutical therapies.

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Species referenced: Xenopus
Genes referenced: bmp2

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	Figure 1. (A) Experimental design for the Xenopus microarray experiment. Xenopus embryos were microinjected at the one‐cell stage with water (control) or mRNA for dominant‐negative KATP (DN KATP, 666 construct) or GlyR channel mRNA. GlyR‐injected embryos were incubated in channel opener drug ivermectin (IVM). The transcriptional response begins in the Xenopus embryos at stage 8. The embryos were flash‐frozen at stage 11, mRNA was extracted, and transcripts were compared between the experimental and control samples. Extracts from 50 embryos was pooled for each experimental group. Only those transcripts that were similarly modified in both the GlyR+IVM and DN KATP groups were used as depolarization‐specific modified transcripts. (B) Experimental design for the axolotl microarray experiment; 2−3 cm axolotl were used. The central canal of the spinal cord was pressure injected with vehicle (water, controls) or injected with IVM (depolarization). Immediately after injection spinal cord injury was performed by removing a small portion of the cord. One day post‐injury the area of injury was removed after anesthetizing the animals. Tissues from 10 animals were pooled for each experiment. Extracted RNA was used to detect changed transcripts in IVM‐injected animals in comparison to control (water injected). (C) Experimental design for the primary human mesenchymal stem cells (hMSCs) microarray experiment. hMSCs were induced to differentiate into osteoblasts. These osteoblasts were then treated with ouabain (Na+/K+ ATPase inhibitor) or incubated in medium with high potassium (both depolarizing conditions). The mRNA extracted from the treated cells was compared with that of untreated osteoblasts (controls). Among the modified transcripts only those that were similarly modified in both the treatments were used as depolarization‐specific modified transcripts.
	Figure 2. (A) Cell processes affected in each dataset. List 4 is the total list of all cell processes in the program. There were 2990 cell processes that were not affected in any of the three datasets. (B) Diseases affected in each dataset. List 4 is the total list of all diseases in the program. There were 4065 diseases that were not affected in any of the three datasets.
	Figure 3. Subnetwork enrichment analysis of the Xenopus dataset identified (A) organogenesis as a process significantly enriched with a list of key genes that are involved in organogenesis indicated in red, (B) regulated genes that are involved in brain/neural development, (C) regulated genes that are involved in bone morphogenesis. Acronyms can be found in Appendix S5. Gene functions can be found in Table S1.
	Figure 4. (A) Pie chart of the functional classification of the Xenopus dataset using the PANTHER database showing enrichment of embryonic developmental processes particularly organ development. (B) Subnetwork enrichment analysis of the Xenopus dataset identified regulated genes involved in “large‐scale functions” (those seen across germ layers and various tissues during development) like cell cycle, differentiation, dedifferentiation, proliferation, etc. Acronyms can be found in Appendix S4. The gene list and their fold change can be found in Appendix S1.
	Figure 5. Subnetwork enrichment analysis of the Xenopus dataset identifies regulated genes that are involved in (A) BMP2 signaling, (B) calcium signaling, and (C) histone deacetylase (HDAC) signaling. Acronyms can be found in Appendix S5.
	Figure 6. Subnetwork enrichment analysis (SNEA) of all three (frog, axolotl, and human) datasets identifies regulated cell processes and diseases common in all three datasets that are involved in metabolic disease pathways. The pathways depicted are the ones mapped with axolotl genes, but these same processes and diseases were affected in both frog and human (i.e., the processes were common in all three). The specific genes from the frog and human datasets may be different but they affect the same cell processes and diseases. (A) metabolic disease pathways, and (B) brain‐related pathways within the “disease” database. Acronyms can be found in Appendix.
	Figure 7. Summary of comparative genomic analysis, showing common themes of differentially expressed genes in response to depolarization.

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