Dataset Information

Fine tuning of Rac1 and RhoA alters cuspal shapes by remolding the cellular geometry.

ABSTRACT: The anatomic and functional combinations of cusps and lophs (ridges) define the tooth shape of rodent molars, which distinguishes species. The species-specific cusp patterns result from the spatiotemporal induction of enamel knots (EKs), which require precisely controlled cellular behavior to control the epithelial invagination. Despite the well-defined roles of EK in cusp patterning, the determinants of the ultimate cuspal shapes and involvement of epithelial cellular geometry are unknown. Using two typical tooth patterns, the lophodont in gerbils and the bunodont in mice, we showed that the cuspal shape is determined by the dental epithelium at the cap stage, whereas the cellular geometry in the inner dental epithelium (IDE) is correlated with the cuspal shape. Intriguingly, fine tuning Rac1 and RhoA interconvert cuspal shapes between two species by remolding the cellular geometry. Either inhibition of Rac1 or ectopic expression of RhoA could region-distinctively change the columnar shape of IDE cells in gerbils to drive invagination to produce cusps. Conversely, RhoA reduction in mice inhibited invagination and developed lophs. Furthermore, we found that Rac1 and RhoA modulate the choices of cuspal shape by coordinating adhesion junctions, actin distribution, and fibronectin localization to drive IDE invagination.

SUBMITTER: Li L

PROVIDER: S-EPMC5124948 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Fine tuning of Rac1 and RhoA alters cuspal shapes by remolding the cellular geometry.

Li Liwen L Tang Qinghuang Q Nakamura Takashi T Suh Jun-Gyo JG Ohshima Hayato H Jung Han-Sung HS

Scientific reports 20161128

The anatomic and functional combinations of cusps and lophs (ridges) define the tooth shape of rodent molars, which distinguishes species. The species-specific cusp patterns result from the spatiotemporal induction of enamel knots (EKs), which require precisely controlled cellular behavior to control the epithelial invagination. Despite the well-defined roles of EK in cusp patterning, the determinants of the ultimate cuspal shapes and involvement of epithelial cellular geometry are unknown. Usin ...[more]

PMID: 27892530

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Project description:To create a dataset of PSMs that does not exhibit tryptic bias, we selected PSMs with a uniform distribution of amino acids at the C-terminal peptide positions from two datasets: MassIVE-KB [Wang2018] and PROSPECT [Shouman2022]. The MassIVE-KB dataset contains 30 million PSMs and consists entirely of data generated using trypsin; hence, only a small proportion of the MassIVE-KB peptides do not end in K or R, corresponding to those that appear at the C-terminus of the corresponding protein. The PROSPECT dataset is a collection of 61 million PSMs generated from synthetic peptides. To avoid overrepresentation of some peptides in this dataset, we randomly selected at most 100 PSMs per unique peptide, similar to the processing that was done during the creation of the MassIVE-KB dataset. This pre-selection step reduced the size of the PROSPECT dataset to 12.6 million PSMs. Finally, to create a non-enzymatic dataset containing 1 million peptides, we selected 50,000 PSMs for each canonical amino acid. These PSMs were selected at random from MassIVE-KB, then supplemented as necessary from PROSPECT to obtain the desired count (see Yilmaz et al. [Yilmaz2023] Supplementary Table S1). This dataset contained PSMs from 247,859 unique peptides, which were randomly split into training, validation and test sets in the ratio 80/10/10. FTP directory contains the mgf files corresponding to train, validation and test splits. [Wang2018] M. Wang, J. Wang, J. Carver, B. Pullman, S. Won Cha, N. Bandeira, "Assembling the Community-Scale Discoverable Human Proteome", Cell Systems, Volume 7, Issue 4, 2018. [Shouman2022] O. Shouman, W. Gabriel, V. Giurcoiu, V. Sternlicht, M. Wilhelm, "PROSPECT: Labeled Tandem Mass Spectrometry Dataset for Machine Learning in Proteomics", NeurIPS Datasets and Benchmarks, 2022 [Yilmaz2023] M. Yilmaz*, W. Fondrie*, W. Bittremieux, R. Nelson, V. Ananth, S. Oh, and W. Noble,"Sequence-to-sequence translation from mass spectra to peptides with a transformer model", bioRxiv, 2023

Dataset Information

Fine tuning of Rac1 and RhoA alters cuspal shapes by remolding the cellular geometry.

Publications

Fine tuning of Rac1 and RhoA alters cuspal shapes by remolding the cellular geometry.

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