Molecular and Cellular NeuroscienceNeurosciencePeer-reviewed journal article
Protein phosphatases regulate the formation of Müller glia-derived progenitor cells in the chick retina
Lisa E. Kelly, Heithem M. El‐HodiriiD, Andrew Crider, Andy J. FischeriD
Abstract
Different kinase-dependent cell signaling pathways are known to play important roles in glia-mediated neuroprotection and reprogramming of Muller glia (MG) into Muller glia-derived progenitor cells (MGPCs) in the retina. However, very little is known about the phosphatases that regulate kinase-dependent signaling in MG. Using single-cell RNA-sequencing (scRNA-seq) databases, we investigated patterns of expression of Dual Specificity Phosphatases (DUSP1/6) and other protein phosphatases in normal and damaged chick retinas. We found that DUSP1, DUSP6, PPP3CB, PPP3R1 and PPPM1A/B/D/E/G are dynamically expressed by MG and MGPCs in retinas during the process of reprogramming. We find that inhibition of DUSP1/6 and PP2C phosphatases enhances the formation of proliferating MGPCs in damaged retinas and in retinas treated with insulin in FGF2 in the absence of damage. By contrast, inhibition of PP2B phosphatases suppressed the formation of proliferating MGPCs, but increased numbers of proliferating MGPCs in undamaged retinas treated with insulin and FGF2. In damaged retinas, inhibition of DUSP1/6 increased levels of pERK1/2 and cFos in MG whereas inhibition of PP2Bs decreased levels of pStat3 and pS6 in MG. Analyses of scRNA-seq libraries identified numerous differentially activated gene modules in MG in damaged retinas versus MG in retinas treated with insulin+FGF2 suggesting significant differences in kinase-dependent signaling pathways that converge on the formation of MGPCs. Inhibition of phosphatases had no significant effects upon numbers of dying cells in damaged retinas. We conclude that the activity of different protein phosphatases "fine-tune" the cell signaling responses of MG in damaged retinas and during the reprogramming of MG into MGPCs.
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: benchmarking
- approach: statistical model
- Citations
- 4
- FWCI
- 0.55
- Field percentile
- top 43%
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