摘要
Objective： To re-analyze the data published in order to explore plausible biological pathways that can be used to explain the anti-aging effect of curcumin. Methods： Microarray data generated from other study aiming to investigate effect of curcumin on extending lifespan of Drosophila melanogaster were further used for pathway prediction analysis. The differentially expressed genes were identified by using GeneSpdng GX with a criterion of 3.0-fold change. Two Cytoscape plugins including BisoGenet and molecular complex detection （MCODE） were used to establish the protein-protein interaction （PPI） network based upon differential genes in order to detect highly connected regions. The function annotation clustering tool of Database for Annotation, Visualization and Integrated Discovery （DAVID） was used for pathway analysis. Results： A total of 87 genes expressed differentially in D. melanogaster treated with curcumin were identified, among which 50 were up-regulated significantly and 37 were remarkably down-regulated in D. melanogaster treated with curcumin. Based upon these differential genes, PPI network was constructed with 1,082 nodes and 2,412 edges. Five highly connected regions in PPI networks were detected by MCODE algorithm, suggesting anti-aging effect of curcumin may be underlined through five different pathways including Notch signaling pathway, basal transcription factors, cell cycle regulation, ribosome, Wnt signaling pathway, and p53 pathway. Conclusion： Genes and their associated pathways in D. rnelanogaster treated with anti-aging agent curcumin were identified using PPI network and MCODE algorithm, suggesting that curnumin may be developed as an alternative therapeutic medicine for treating aging-associated diseases.
Objective： To re-analyze the data published in order to explore plausible biological pathways that can be used to explain the anti-aging effect of curcumin. Methods： Microarray data generated from other study aiming to investigate effect of curcumin on extending lifespan of Drosophila melanogaster were further used for pathway prediction analysis. The differentially expressed genes were identified by using GeneSpdng GX with a criterion of 3.0-fold change. Two Cytoscape plugins including BisoGenet and molecular complex detection （MCODE） were used to establish the protein-protein interaction （PPI） network based upon differential genes in order to detect highly connected regions. The function annotation clustering tool of Database for Annotation, Visualization and Integrated Discovery （DAVID） was used for pathway analysis. Results： A total of 87 genes expressed differentially in D. melanogaster treated with curcumin were identified, among which 50 were up-regulated significantly and 37 were remarkably down-regulated in D. melanogaster treated with curcumin. Based upon these differential genes, PPI network was constructed with 1,082 nodes and 2,412 edges. Five highly connected regions in PPI networks were detected by MCODE algorithm, suggesting anti-aging effect of curcumin may be underlined through five different pathways including Notch signaling pathway, basal transcription factors, cell cycle regulation, ribosome, Wnt signaling pathway, and p53 pathway. Conclusion： Genes and their associated pathways in D. rnelanogaster treated with anti-aging agent curcumin were identified using PPI network and MCODE algorithm, suggesting that curnumin may be developed as an alternative therapeutic medicine for treating aging-associated diseases.
基金
Supported by the National Natural Science Foundation of China(No.81102680)
China Postdoctoral Science Foundation(No.20100470524)
