Usage Information

Transcription factor EGR1 directs tendon differentiation and promotes tendon repair
Marie-Justine Guerquin, … , Francis Berenbaum, Delphine Duprez
Marie-Justine Guerquin, … , Francis Berenbaum, Delphine Duprez
Published August 1, 2013; First published July 25, 2013
Citation Information: J Clin Invest. 2013;123(8):3564-3576. https://doi.org/10.1172/JCI67521.
View: Text | PDF
Categories: Research Article Muscle biology

Transcription factor EGR1 directs tendon differentiation and promotes tendon repair

Abstract

Tendon formation and repair rely on specific combinations of transcription factors, growth factors, and mechanical parameters that regulate the production and spatial organization of type I collagen. Here, we investigated the function of the zinc finger transcription factor EGR1 in tendon formation, healing, and repair using rodent animal models and mesenchymal stem cells (MSCs). Adult tendons of Egr1–/– mice displayed a deficiency in the expression of tendon genes, including Scx, Col1a1, and Col1a2, and were mechanically weaker compared with their WT littermates. EGR1 was recruited to the Col1a1 and Col2a1 promoters in postnatal mouse tendons in vivo. Egr1 was required for the normal gene response following tendon injury in a mouse model of Achilles tendon healing. Forced Egr1 expression programmed MSCs toward the tendon lineage and promoted the formation of in vitro–engineered tendons from MSCs. The application of EGR1-producing MSCs increased the formation of tendon-like tissues in a rat model of Achilles tendon injury. We provide evidence that the ability of EGR1 to promote tendon differentiation is partially mediated by TGF-β2. This study demonstrates EGR1 involvement in adult tendon formation, healing, and repair and identifies Egr1 as a putative target in tendon repair strategies.

Authors

Marie-Justine Guerquin, Benjamin Charvet, Geoffroy Nourissat, Emmanuelle Havis, Olivier Ronsin, Marie-Ange Bonnin, Mathilde Ruggiu, Isabel Olivera-Martinez, Nicolas Robert, Yinhui Lu, Karl E. Kadler, Tristan Baumberger, Levon Doursounian, Francis Berenbaum, Delphine Duprez

×

Usage data is cumulative from October 2018 through October 2019.

Usage JCI PMC
Text version 520 175
PDF 144 202
Figure 228 0
Table 18 0
Supplemental data 54 35
Citation downloads 28 0
Totals 992 412
Total Views 1,404
(Click and drag on plot area to zoom in. Click legend items above to toggle)

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

Advertisement