Browsing by Author "Li, Yanda"
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Item Integrated Omics Study Delineates the Dynamics of Lipid Droplets in Rhodococcus Opacus PD630(Oxford University Press, 2013-10-22) Chen, Yong; Ding, Yunfeng; Yang, Li; Yu, Jinhai; Liu, Guiming; Wang, Xumin; Zhang, Shuyan; Zhang, Michael Q.; Li, Yanda; 0000 0001 1707 1372 (Zhang, MQ); 99086074 (Zhang, MQ); Zhang, Michael Q.Rhodococcus opacus strain PD630 (R. opacus PD630), is an oleaginous bacterium, and also is one of few prokaryotic organisms that contain lipid droplets (LDs). LD is an important organelle for lipid storage but also intercellular communication regarding energy metabolism, and yet is a poorly understood cellular organelle. To understand the dynamics of LD using a simple model organism, we conducted a series of comprehensive omics studies of R. opacus PD630 including complete genome, transcriptome and proteome analysis. The genome of R. opacus PD630 encodes 8947 genes that are significantly enriched in the lipid transport, synthesis and metabolic, indicating a super ability of carbon source biosynthesis and catabolism. The comparative transcriptome analysis from three culture conditions revealed the landscape of gene-altered expressions responsible for lipid accumulation. The LD proteomes further identified the proteins that mediate lipid synthesis, storage and other biological functions. Integrating these three omics uncovered 177 proteins that may be involved in lipid metabolism and LD dynamics. A LD structure-like protein LPD06283 was further verified to affect the LD morphology. Our omics studies provide not only a first integrated omics study of prokaryotic LD organelle, but also a systematic platform for facilitating further prokaryotic LD research and biofuel development.Item Miror: A Method for Cell-Type Specific MicroRNA Occupancy Rate Prediction(Royal Soc Chemistry, 2014-03-13) Xie, Peng; Liu, Yu; Li, Yanda; Zhang, Michael Q.; Wang, Xiaowo; 0000 0001 1707 1372 (Zhang, MQ); 99086074 (Zhang, MQ); Zhang, Michael Q.MicroRNA (miRNA) regulation is highly cell-type specific. It is sensitive to both the miRNA-mRNA relative abundance and the competitive endogenous RNA (ceRNA) effect. However, almost all existing miRNA target prediction methods neglected the influence of the cellular environment when analyzing miRNA regulation effects. In this study, we proposed a method, MIROR (miRNA Occupancy Rate predictor), to predict miRNA regulation intensity in a given cell type. The major considerations were the miRNA-mRNA relative abundance and the endogenous competition between different mRNA species. The output of MIROR is the predicted miRNA occupancy rates of each target site. The predicted results significantly correlated with Ago HITS-CLIP experiment that indicated miRNA binding intensities. When applied to the analysis of the breast invasive carcinoma dataset, MIROR identified a number of differentially regulated miRNA-mRNA pairs with significant miRNA occupancy rate changes between tumor and normal tissues. Many of the predictions were supported by previous research studies, including the ones without a significant change in the mRNA expression level. These results indicate that MIROR provides a novel strategy to study the miRNA differential regulation in different cell types.