Identification of Optimal Decalcification Method and Tissue Preparation Protocol for RNAscope In Situ Hybridization in Rodent Incisor Tooth
Year: 2025
Type: article
Abstract: Background: RT-qPCR is the gold standard for quantitative gene expression analysis, but it requires homogenized tissue and thus loses spatial information. RNA in situ hybridization (ISH) preserves tissue localization but is technically challenging, especially in calcified tissues such as bone and teeth, where decalcification can damage RNA. RNAscope, an advanced ISH method with high sensitivity and specificity, has been applied successfully to bone, but its use in dental pulp remains largely unexplored despite the pulp’s crucial role in tooth function and health. Our goal was to identify the optimal decalcification process of mouse tooth samples for RNAscope ISH, which preserves RNA integrity in mouse tooth pulp. Methods: We tested five different decalcification procedures (EDTA, Plank-Rychlo solution, 5% formic acid, ACD decalcification buffer and Morse solution) on tooth samples from 3-month-old male C57BL/6J mice. Micro-CT and hematoxylin-eosin (HE) staining was performed to evaluate the decalcification, the quality and the microstructure of the sections. RNAscope ISH was used to examine mRNA integrity by analyzing the expression patterns of three housekeeping genes with different expression levels (low, medium and high). Results: All five decalcification methods demonstrated well-preserved tissue structure based on HE staining, but RNA integrity was only preserved in the case of mouse dental pulp using the ACD decalcification buffer and Morse’s solution. Conclusions: We successfully identified the optimal decalcification procedures preserving RNA integrity in mouse tooth samples, which may be useful for any target RNA examinations by RNAscope ISH in the future.
Source: Dentistry Journal
DOI: 10.3390/dj13110538
Institutions: University of Pecs, University of Debrecen
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,413
Funder: Pécsi Tudományegyetem
Awards: G1603026476, G6581228878
OpenAlex ID: W4416229786
