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Dryad

Data from: HIF prolyl hydroxylase 2/3 deletion disrupts astrocytic integrity and exacerbates neuroinflammation

Cite this dataset

Rosiewicz, Kamil et al. (2023). Data from: HIF prolyl hydroxylase 2/3 deletion disrupts astrocytic integrity and exacerbates neuroinflammation [Dataset]. Dryad. https://doi.org/10.5061/dryad.jwstqjqdb

Abstract

Astrocytes constitute the parenchymal border of the blood-brain barrier (BBB), modulate the exchange of soluble and cellular elements, and are essential for neuronal metabolic support. Thus, astrocytes critically influence neuronal network integrity. In hypoxia, astrocytes upregulate a transcriptional program that has been shown to boost neuroprotection in several models of neurological diseases. We investigated transgenic mice with astrocyte-specific activation of the hypoxia-response program by deleting the oxygen sensors, HIF prolyl-hydroxylase domains 2 and 3 (Phd2/3). We induced Phd2/3 deletion in experimental autoimmune encephalomyelitis (EAE) in a therapeutic approach that led to an exacerbation of the disease mediated by massive immune cell infiltration. We found that Phd2/3-ko astrocytes, though expressing a neuroprotective signature, exhibited a gradual loss of gap-junctional Connexin-43 (Cx43), which was induced by vascular endothelial growth factor-alpha (Vegf-a) expression. These results provide mechanistic insights into astrocyte biology, their critical role in hypoxic states, and in chronic inflammatory CNS diseases.

Methods

By using TRAP (translating ribosome affinity purification) just actively translating mRNA from astrocytes of mice Aldh1l1-creERT2; Phd2fl/fl or wt/wt; Phd3fl/fl or wt/wt; L10a-eGFP was collected (spinal cord and brain stem), purified and sequenced at the HiSeq4000 system. For detailed protocol information please refer to Heiman et al., 2014 and Rosiewicz et al., 2020. Then raw fastq files were quality checked by FastQC, then rRNA content was filtered-out with SortMeRNA and finally aligned to mouse genome by Salmon.

Usage notes

Salmon output data can be further analyzed by R based package DESeq2.

Funding

Deutsche Forschungsgemeinschaft