Dataset Information

Amelogenin Affects Brushite Crystal Morphology and Promotes Its Phase Transformation to Monetite.

ABSTRACT: Amelogenin protein is involved in organized apatite crystallization during enamel formation. Brushite (CaHPO4·2H2O), one of the precursors of hydroxyapatite mineralization in vitro, has been used for fabrication of biomaterials for hard tissue repair. In order to explore its potential application in biomimetic material synthesis, we studied the influence of the enamel protein amelogenin on brushite morphology and phase transformation to monetite. Our results show that amelogenin can adsorb onto the surface of brushite, leading to the formation of layered morphology on the (010) face. Amelogenin promoted the phase transformation of brushite into monetite (CaHPO4) in the dry state, presumably by interacting with crystalline water layers in brushite unit cells. Changes to the crystal morphology mediated by amelogenin continued even after the phase transformation from brushite to monetite, leading to the formation of organized platelets with an interlocked structure. This effect of amelogenin on brushite morphology and the phase transformation to monetite could provide a new approach to developing biomimetic materials.

SUBMITTER: Ren D

PROVIDER: S-EPMC5553050 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Amelogenin Affects Brushite Crystal Morphology and Promotes Its Phase Transformation to Monetite.

Ren Dongni D Ruan Qichao Q Tao Jinhui J Lo Jonathan J Nutt Steven S Moradian-Oldak Janet J

Crystal growth & design 20160805 9

Amelogenin protein is involved in organized apatite crystallization during enamel formation. Brushite (CaHPO4·2H2O), one of the precursors of hydroxyapatite mineralization in vitro, has been used for fabrication of biomaterials for hard tissue repair. In order to explore its potential application in biomimetic material synthesis, we studied the influence of the enamel protein amelogenin on brushite morphology and phase transformation to monetite. Our results show tha ...[more]

PMID: 28808430

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Project description:Total RNA was extracted from Lin-Sca-1+c-Kit+ (LSK) cells sorted from the BM of Spred1HSCΔ/ΔSCLtTA/BCR-ABL (HSC KO) and Spred1HSCwt/wtSCLtTA/BCR-ABL (HSC wt) (n=5 mice per group, both group given 7 doses of 250μg poly(I:C), ip, every two days, to activate Mx1-cre), Spred1ECΔ/ΔSCLtTA/BCR-ABL (EC KO) and Spred1ECwt/wtSCLtTA/BCR-ABL (EC wt) (n=5 mice per group) mice using the miRNeasy micro Kit (Qiagen, Valencia, CA). SMART-Seq® Ultra Low Input RNA Kit for Sequencing – v4 (TaKaRa, Cat 634888) was used for generating amplified double stranded (ds) cDNA from each sample with 2ng of input total RNA according to the manufacturer's protocol. The resulting ds cDNA was sheared with Covaris LE220 with the setting of DNA fragment size of 200bp peak. The sheared DNA was used for sequencing library preparation by using KAPA HyperPrep Kits (Roche, Cat KK8500). The final libraries were quantified with qubit and bioanalyzer. The sequencing was performed with the single read mode of 51 cycles of read1 and 7 cycles of index read with V4 reagents on Illumina Hiseq2500. Real-time analysis (RTA) 2.2.38 software was used to process the image analysis and base calling. The nf-core RNAseq pipeline v1.3 was used to process the raw sequencing reads (https://nf-co.re). RNA-Seq reads were trimmed to remove sequencing adapters using Trimmomatic3 and polyA tails using FASTP4. The processed reads were mapped back to the mouse genome (mm10) using STAR software (v. 020201)5. The HTSeq software (v.0.6.0)6 was applied to generate the count matrix, with default parameters. Differential expression analysis was conducted by adjusting read counts to normalized expression values using TMM normalization method in R7. Briefly, for each comparison between HSC KO LSKs and HSC wt LSKs and between EC KO LSKs and EC wt LSKs, general linear models were applied to identify DEGs using TMM normalization expression level as depending variable, and genotype as independent variable. Genes with a p-value less than 0.05 and with a fold change (FC) greater than 1.5 or less than 0.7 were considered as significant up- and down-regulated genes, respectively. Pathway analysis was conducted using GSEAPreranked algorithm using GSEA Desktop program in Java8, 9. The former requires a list of up- and down-regulated genes, while the latter a ranked list of whole genes according to their log2 fold change and p-values.

Dataset Information

Amelogenin Affects Brushite Crystal Morphology and Promotes Its Phase Transformation to Monetite.

Publications

Amelogenin Affects Brushite Crystal Morphology and Promotes Its Phase Transformation to Monetite.

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