Spatiotemporal monitoring of hard tissue development reveals unknown features of tooth and bone development

0575031 - ÚŽFG 2024 RIV US eng J - Journal Article
Gonzales Lopez, M. - Hutečková, Barbora - Lavický, J. - Zezula, N. - Rakultsev, V. - Fridrichová, V. - Tuaima, H. - Nottmeier, C. - Petersen, J. - Kavková, M. - Zikmund, T. - Kaiser, J. - Lav, R. - Star, H. - Bryja, V. - Henys, P. - Vořechovský, M. - Tucker, A. S. - Harnoš, J. - Buchtová, Marcela - Křivánek, J.
Spatiotemporal monitoring of hard tissue development reveals unknown features of tooth and bone development.
Science Advances. Roč. 9, č. 31 (2023), č. článku eadi0482. ISSN 2375-2548. E-ISSN 2375-2548
R&D Projects: GA ČR GA22-02794S
Institutional support: RVO:67985904
Keywords : bones * teeth * hard tissue development
OECD category: Cell biology
Impact factor: 13.6, year: 2022
Method of publishing: Open access
https://www.science.org/doi/10.1126/sciadv.adi0482

Mineralized tissues, such as bones or teeth, are essential structures of all vertebrates. They enable rapid movement, protection, and food processing, in addition to providing physiological functions. Although the development, regeneration, and pathogenesis of teeth and bones have been intensely studied, there is currently no tool to accurately follow the dynamics of growth and healing of these vital tissues in space and time. Here, we present the BEE-ST (Bones and tEEth Spatio-Temporal growth monitoring) approach, which allows precise quantification of development, regeneration, remodeling, and healing in any type of calcified tissue across different species. Using mouse teeth as model the turnover rate of continuously growing incisors was quantified, and role of hard/soft diet on molar root growth was shown. Furthermore, the dynamics of bones and teeth growth in lizards, frogs, birds, and zebrafish was uncovered. This approach represents an effective, highly reproducible, and versatile tool that opens up diverse possibilities in developmental biology, bone and tooth healing, tissue engineering, and disease modeling.
Permanent Link: https://hdl.handle.net/11104/0345018