Differential gene expression in normal and transformed human mammary epithelial cells in response to oxidative stress

Oxidative stress plays a key role in breast carcinogenesis. To investigate whether normal and malignant breast epithelial cells differ in their responses to oxidative stress, we examined the global gene expression profiles of three cell types, representing cancer progression from a normal to a malignant stage, under oxidative stress. Normal human mammary epithelial cells (HMECs), an immortalized cell line (HMLER-1), and a tumorigenic cell line (HMLER-5) were exposed to increased levels of reactive oxygen species (ROS) by treatment with glucose oxidase. Functional analysis of the metabolic pathways enriched with differentially expressed genes demonstrated that normal and malignant breast epithelial cells diverge substantially in their response to oxidative stress. Whereas normal cells exhibit the up-regulation of antioxidant mechanisms, cancer cells are unresponsive to the ROS insult. However, the gene expression response of normal HMECs under oxidative stress is comparable to that of the malignant cells under normal conditions, indicating that altered redox status is persistent in breast cancer cells, which makes them resistant to increased generation of ROS. We discuss some of the possible adaptation mechanisms of breast cancer cells under persistent oxidative stress that differentiate them from normal mammary epithelial cells as regards the response to acute oxidative stress.     

Co-expression analysis reveals a group of genes potentially involved in regulation of plant response to iron-deficiency

Iron (Fe) is an essential element for plant growth and development. Iron deficiency results in abnormal metabolisms from respiration to photosynthesis. Exploration of Fe-deficient responsive genes and their networks is critically important to understand molecular mechanisms leading to the plant adaptation to soil Fe-limitation. Co-expression genes are a cluster of genes that have a similar expression pattern to execute relatively biological functions at a stage of development or under a certain environmental condition. They may share a common regulatory mechanism. In this study, we investigated Fe-starved-related co-expression genes from Arabidopsis. From the biological process GO annotation of TAIR (The Arabidopsis Information Resource), 180 iron-deficient responsive genes were detected. Using ATTED-II database, we generated six gene co-expression networks. Among these, two modules of PYE and IRT1 were successfully constructed. There are 30 co-expression genes that are incorporated in the two modules (12 in PYE-module and 18 in IRT1-module). Sixteen of the co-expression genes were well characterized. The remaining genes (14) are poorly or not functionally identified with iron stress. Validation of the 14 genes using real-time PCR showed differential expression under iron-deficiency. Most of the co-expression genes (23/30) could be validated in pye and fit mutant plants with iron-deficiency. We further identified iron-responsive cis-elements upstream of the co-expression genes and found that 22 out of 30 genes contain the iron-responsive motif IDE1. Furthermore, some auxin and ethylene-responsive elements were detected in the promoters of the co-expression genes. These results suggest that some of the genes can be also involved in iron stress response through the phytohormone-responsive pathways.     

AtGGM2014, an Arabidopsis gene co-expression network for functional studies

Gene co-expression networks provide an important tool for systems biology studies. Using microarray data from the Array Express database, we constructed an Arabidopsis gene co-expression network, termed At GGM2014, based on the graphical Gaussian model, which contains 102,644 co-expression gene pairs among 18,068 genes. The network was grouped into 622 gene co-expression modules. These modules function in diverse house-keeping, cell cycle, development, hormone response, metabolism, and stress response pathways. We developed a tool to facilitate easy visualization of the expression patterns of these modules either in a tissue context or their regulation under different treatment conditions. The results indicate that at least six modules with tissue-specific expression pattern failed to record modular regulation under various stress conditions. This discrepancy could be best explained by the fact that experiments to study plant stress responses focused mainly on leaves and less on roots, and thus failed to recover specific regulation pattern in other tissues. Overall, the modular structures revealed by our network provide extensive information to generate testable hypotheses about diverse plant signaling pathways. At GGM2014 offers a constructive tool for plant systems biology studies.