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A gene expression-based comparison of cell adhesion to extracellular matrix and RGD-terminated monolayers.

ABSTRACT: This work uses global gene expression analysis to compare the extent to which model substrates presenting peptide adhesion motifs mimic the use of conventional extracellular matrix protein coated substrates for cell culture. We compared the transcriptional activities of genes in cells that were cultured on matrix-coated substrates with those cultured on self-assembled monolayers presenting either a linear or cyclic RGD peptide. Cells adherent to cyclic RGD were most similar to those cultured on native ECM, while cells cultured on monolayers presenting the linear RGD peptide had transcriptional activities that were more similar to cells cultured on the uncoated substrates. This study suggests that biomaterials presenting the cyclic RGD peptide are substantially better mimics of extracellular matrix than are uncoated materials or materials presenting the common linear RGD peptide.

SUBMITTER: Sobers CJ

PROVIDER: S-EPMC4379455 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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A gene expression-based comparison of cell adhesion to extracellular matrix and RGD-terminated monolayers.

Sobers Courtney J CJ Wood Sarah E SE Mrksich Milan M

Biomaterials 20150303

This work uses global gene expression analysis to compare the extent to which model substrates presenting peptide adhesion motifs mimic the use of conventional extracellular matrix protein coated substrates for cell culture. We compared the transcriptional activities of genes in cells that were cultured on matrix-coated substrates with those cultured on self-assembled monolayers presenting either a linear or cyclic RGD peptide. Cells adherent to cyclic RGD were most similar to those cultured on ...[more]

PMID: 25818445

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Project description:There is limited information on region-specific gene expression in the human corneal stroma. In this study, we aimed to investigate the expression profile of the extracellular matrix and adhesion molecules in the normal corneal stroma using laser capture microdissection (LCM) and molecular techniques.Frozen sections of human cornea without ocular disease were used to isolate the central and peripheral corneal stromal keratocytes by LCM. RNA was extracted from LCM-captured tissues and the RT2 Profiler PCR Arrays were used to examine the expression profile of extracellular matrix and adhesion molecules in the central and peripheral stroma. Real-time quantitative PCR was used to quantify gene expression. Proteomic and western blotting (WB) analyses were performed to confirm gene expression at protein level. Function association network was generated via the web tools String and Cytoscape.The gene expression profiling demonstrated that 35 out of the 84 extracellular matrix and adhesion molecules represented in the array were expressed in stromal keratocytes. Among them, 24 genes were not previously described in the corneal stroma. Two genes were found more abundantly expressed in the central stroma than in the periphery: TGFBI, COL6A2 (p < 0.05). ADAMTS13 was detected only in the central stroma. Proteomics and WB analysis confirmed the expression of 10 genes. Functional analysis revealed that most identified genes were presented in a core cluster that had multiple and strong associations with other genes.This study identified genes not previously described in the corneal stroma, revealed regional differences in gene expression between central and peripheral stroma, and also detected some interesting candidate genes that may play important roles in corneal function. These observations serve as the foundation to further investigate the molecular and cellular mechanisms regulating the pathogenesis of regional corneal stromal disorders such as keratoconus.

Dataset Information

A gene expression-based comparison of cell adhesion to extracellular matrix and RGD-terminated monolayers.

Publications

A gene expression-based comparison of cell adhesion to extracellular matrix and RGD-terminated monolayers.

Similar Datasets

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