Expression of CGRP, vasculogenesis and osteogenesis associated mRNAs in the developing mouse mandible and tibia
The neuropeptide Calcitonin Gene-Related Peptide (CGRP) is a well-characterized neurotransmitter. However, little is known about the role of CGRP in osteogenesis and vascular genesis during the developmental formation of bone. In the present study, we assessed the abundance of CGRP mRNA and the mRNA of osteogenesis and vascular genesis markers in the foetal mouse mandible and leg bone (tibia). We also analysed the expression and localization of CGRP, osteopontin (OPN) and vascular endothelial growth factor (VEGF-A) using in situ hybridization and immunohistochemical localization in the mouse mandible and tibia at embryonic days 12.5 (E12.5), E14.5, E17.5, and postnatal day 1 (P1). CGRP was clearly detected in the mandible relative to the tibia at E14.5. Hybridization using an anti-sense probe for CGRP was not detected in the mandible at P1. Hybridization with an anti-sense probe for OPN was detected at E14.5, later in the mandible and at P1 in Meckelâ€™s cartilage. However, OPN was only detected in the tibia at E17.5 and later. The abundance of CGRP mRNA differed between the mandible and tibia. The level of vasculogenesis markers, such as VEGF-A, was similar to that of CGRP in the mandible. The levels of VEGF-A, cluster of differentiation 31 (CD31) and lymphatic vessel endothelial hyaluronan receptor 1 (LIVE-1) differed from that of OPN in the mandible. In contrast, the levels of VEGF-A, CD31, matrix metalloproteinase-2 (MMP-2), collagen I (Col I), collagen II (Col II) and OPN mRNA differed from E12.5 to P1 (P<0.001) in the tibia. The abundance of mRNA of CGRP and bone matrix markers (Col I, Col II, and OPN) was low at P5 in the tibia. These differences in CGRP and other mRNAs may induce a different manner of ossification between the mandible and tibia. Therefore, a time lag of ossification occurs between the mandible and tibia during foetal development.
PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.
Copyright (c) 2017 Yuuki Maeda, Yoko Miwa, Iwao Sato
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.