R-spondin 3 deletion induces Erk phosphorylation to enhance Wnt signaling and promote bone formation in the appendicular skeleton
Abstract
Activation of Wnt signaling leads to high bone density. The R-spondin family of four secreted glycoproteins (Rspo1-4) amplifies Wnt signaling. In humans, RSPO3 variants are strongly associated with bone density. Here we investigated the role of Rspo3 in skeletal homeostasis in mice. Using a comprehensive set of mouse genetic and mechanistic studies, we show that in the appendicular skeleton, Rspo3 haplo-insufficiency and Rspo3 targeted deletion in Runx2+ osteoprogenitors lead to an increase in trabecular bone mass, with increased number of osteoblasts and bone formation. In contrast and highlighting the complexity of Wnt signaling in the regulation of skeletal homeostasis, we show that Rspo3 deletion in osteoprogenitors results in the opposite phenotype in the axial skeleton, i.e., low vertebral trabecular bone mass. Mechanistically, Rspo3 deficiency impairs the inhibitory effect of Dkk1 on Wnt signaling activation and bone mass. We demonstrate that Rspo3 deficiency leads to activation of Erk signaling which in turn, stabilizes b-catenin and Wnt signaling activation. Our data demonstrate that Rspo3 haplo-insufficiency/deficiency boosts canonical Wnt signaling by activating Erk signaling, to favor osteoblastogenesis, bone formation and bone mass.
Data availability
All data generated or analysed during this study are included in the manuscript and supporting file.
Article and author information
Author details
Funding
Nih-NIAMS (R01AR064724)
- Roland Baron
NIH-NIDCR (R01DE029615)
- Francesca Gori
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Mone Zaidi, Icahn School of Medicine at Mount Sinai, United States
Ethics
Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All experiments were performed with age- and sex-matched littermates. All animals are in the C57BL/6 background and were housed in the Harvard Center for Comparative Medicine and all experimental procedures were approved by the Harvard University Institutional Animal Care and Use Committee. The protocol number associated with the ethical approval of the animal work is IS1045.
Version history
- Preprint posted: September 3, 2021 (view preprint)
- Received: October 12, 2022
- Accepted: October 18, 2022
- Accepted Manuscript published: November 2, 2022 (version 1)
- Version of Record published: November 22, 2022 (version 2)
Copyright
© 2022, Nagano et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 851
- views
-
- 181
- downloads
-
- 5
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Medicine
Caesarean section scar diverticulum (CSD) is a significant cause of infertility among women who have previously had a Caesarean section, primarily due to persistent inflammatory exudation associated with this condition. Even though abnormal bacterial composition is identified as a critical factor leading to this chronic inflammation, clinical data suggest that a long-term cure is often unattainable with antibiotic treatment alone. In our study, we employed metagenomic analysis and mass spectrometry techniques to investigate the fungal composition in CSD and its interaction with bacteria. We discovered that local fungal abnormalities in CSD can disrupt the stability of the bacterial population and the entire microbial community by altering bacterial abundance via specific metabolites. For instance, Lachnellula suecica reduces the abundance of several Lactobacillus spp., such as Lactobacillus jensenii, by diminishing the production of metabolites like Goyaglycoside A and Janthitrem E. Concurrently, Clavispora lusitaniae and Ophiocordyceps australis can synergistically impact the abundance of Lactobacillus spp. by modulating metabolite abundance. Our findings underscore that abnormal fungal composition and activity are key drivers of local bacterial dysbiosis in CSD.
-
- Medicine
- Neuroscience
Gait is impaired in musculoskeletal conditions, such as knee arthropathy. Gait analysis is used in clinical practice to inform diagnosis and to monitor disease progression or intervention response. However, clinical gait analysis relies on subjective visual observation of walking, as objective gait analysis has not been possible within clinical settings due to the expensive equipment, large-scale facilities, and highly trained staff required. Relatively low-cost wearable digital insoles may offer a solution to these challenges. In this work, we demonstrate how a digital insole measuring osteoarthritis-specific gait signatures yields similar results to the clinical gait-lab standard. To achieve this, we constructed a machine learning model, trained on force plate data collected in participants with knee arthropathy and controls. This model was highly predictive of force plate data from a validation set (area under the receiver operating characteristics curve [auROC] = 0.86; area under the precision-recall curve [auPR] = 0.90) and of a separate, independent digital insole dataset containing control and knee osteoarthritis subjects (auROC = 0.83; auPR = 0.86). After showing that digital insole derived gait characteristics are comparable to traditional gait measurements, we next showed that a single stride of raw sensor time series data could be accurately assigned to each subject, highlighting that individuals using digital insoles can be identified by their gait characteristics. This work provides a framework for a promising alternative to traditional clinical gait analysis methods, adds to the growing body of knowledge regarding wearable technology analytical pipelines, and supports clinical development of at-home gait assessments, with the potential to improve the ease, frequency, and depth of patient monitoring.