High-fidelity CRISPR/Cas9- based gene-specific hydroxymethylation rescues gene expression and attenuates renal fibrosis
Xingbo Xu,
Xiaoying Tan,
Björn Tampe,
Tim Wilhelmi,
Melanie S. Hulshoff,
Shoji Saito,
Tobias Moser,
Raghu Kalluri,
Gerd Hasenfuss,
Elisabeth M. Zeisberg () and
Michael Zeisberg ()
Additional contact information
Xingbo Xu: University Medical Center Göttingen
Xiaoying Tan: German Center for Cardiovascular Research (DZHK) Partner Site
Björn Tampe: University Medical Center Göttingen
Tim Wilhelmi: University Medical Center Göttingen
Melanie S. Hulshoff: University Medical Center Göttingen
Shoji Saito: University Medical Center Göttingen
Tobias Moser: University Medical Center Göttingen
Raghu Kalluri: University of Texas, MD Anderson Cancer Center
Gerd Hasenfuss: University Medical Center Göttingen
Elisabeth M. Zeisberg: University Medical Center Göttingen
Michael Zeisberg: German Center for Cardiovascular Research (DZHK) Partner Site
Nature Communications, 2018, vol. 9, issue 1, 1-15
Abstract:
Abstract While suppression of specific genes through aberrant promoter methylation contributes to different diseases including organ fibrosis, gene-specific reactivation technology is not yet available for therapy. TET enzymes catalyze hydroxymethylation of methylated DNA, reactivating gene expression. We here report generation of a high-fidelity CRISPR/Cas9-based gene-specific dioxygenase by fusing an endonuclease deactivated high-fidelity Cas9 (dHFCas9) to TET3 catalytic domain (TET3CD), targeted to specific genes by guiding RNAs (sgRNA). We demonstrate use of this technology in four different anti-fibrotic genes in different cell types in vitro, among them RASAL1 and Klotho, both hypermethylated in kidney fibrosis. Furthermore, in vivo lentiviral delivery of the Rasal1-targeted fusion protein to interstitial cells and of the Klotho-targeted fusion protein to tubular epithelial cells each results in specific gene reactivation and attenuation of fibrosis, providing gene-specific demethylating technology in a disease model.
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-05766-5
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DOI: 10.1038/s41467-018-05766-5
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