Quantitative 3D imaging of the cranial microvascular environment at single-cell resolution.
Alexandra N RindoneXiaonan LiuStephanie FarhatAlexander Perdomo-PantojaTimothy F WithamDaniel L CoutuMei WanWarren L GraysonPublished in: Nature communications (2021)
Vascularization is critical for skull development, maintenance, and healing. Yet, there remains a significant knowledge gap in the relationship of blood vessels to cranial skeletal progenitors during these processes. Here, we introduce a quantitative 3D imaging platform to enable the visualization and analysis of high-resolution data sets (>100 GB) throughout the entire murine calvarium. Using this technique, we provide single-cell resolution 3D maps of vessel phenotypes and skeletal progenitors in the frontoparietal cranial bones. Through these high-resolution data sets, we demonstrate that CD31hiEmcnhi vessels are spatially correlated with both Osterix+ and Gli1+ skeletal progenitors during postnatal growth, healing, and stimulated remodeling, and are concentrated at transcortical canals and osteogenic fronts. Interestingly, we find that this relationship is weakened in mice with a conditional knockout of PDGF-BB in TRAP+ osteoclasts, suggesting a potential role for osteoclasts in maintaining the native cranial microvascular environment. Our findings provide a foundational framework for understanding how blood vessels and skeletal progenitors spatially interact in cranial bone, and will enable more targeted studies into the mechanisms of skull disease pathologies and treatments. Additionally, our technique can be readily adapted to study numerous cell types and investigate other elusive phenomena in cranial bone biology.
Keyphrases
- high resolution
- single cell
- rna seq
- high throughput
- bone loss
- mass spectrometry
- healthcare
- bone mineral density
- mesenchymal stem cells
- preterm infants
- machine learning
- drug delivery
- cell therapy
- metabolic syndrome
- high speed
- growth factor
- skeletal muscle
- insulin resistance
- wild type
- smooth muscle
- deep learning
- artificial intelligence
- recombinant human