Molecular PsychiatryNeurosciencePeer-reviewed journal article
Forebrain-specific loss of erythropoietin provokes compensatory upregulation of different EPO receptors
Umer Javed ButtiD, Umut ÇakıriD, Anne-Fleur WildenburgiD, Yasmina CurtoiD, Liu YeiD, Vikas BansaliD, Susann BoretiusiD, Klaus‐Armin NaveiD, Manvendra SinghiD, Hannelore EhrenreichiD
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Abstract
The procognitive growth factor erythropoietin (EPO) and its canonical receptor, EPOR, have long been recognized to be expressed by most cell types in the brain. Cognitive domains, improved by injections of exogenous EPO or by endogenous, hypoxia-stimulated EPO, include important forebrain functions, namely attention, working memory, drive, and executive performance. To gain mechanistic insight into the involvement of forebrain-expressed EPO, we deleted EPO in mice using as specific cre-driver Emx1. Here, we report that these mutant mice act comparably to their wildtype littermates in a comprehensive behavioral test battery. Importantly, we find that the transcripts of both EPOR and a novel, brain-expressed EPO receptor, EphB4, respond to EPO deletion with compensatory upregulation. EphB4 expression in brain and its increase upon forebrain erasure of EPOR are confirmed by in situ hybridization and immunohistochemistry. The augmented expression of both EPOR and EphB4 and their regulatory intercorrelation may explain why EmxEPO mutants show an even superior performance in the most challenging working memory task. Using the previously published single-nuclei-RNA-seq dataset, we further confirm the suggested compensatory mechanism, wherein EPO loss or reduction drives elevated EPOR expression, adding another layer to the intricate regulation of EPO signaling in hippocampal pyramidal neurons. Collectively, these data may explain the lack of behavioral and negative cognitive consequences upon forebrain-wide EPO elimination.
- organism: mouse
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: database / resource
- approach: statistical model
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