In silico identification of NF-kappaB-regulated genes in pancreatic beta-cells

Background: Pancreatic beta-cells are the target of an autoimmune attack in type 1 diabetes mellitus (TIDM). This is mediated in part by cytokines, such as interleukin (IL)-1 beta and interferon (IFN)-gamma. These cytokines modify the expression of hundreds of genes, leading to beta-cell dysfunction and death by apoptosis. Several of these cytokine-induced genes are potentially regulated by the IL-1 beta-activated transcription factor (TF) nuclear factor (NF)-kappa, and previous studies by our group have shown that cytokine-induced NF-kappa B activation is pro-apoptotic in beta-cells. To identify NF-kappa B-regulated gene networks in beta-cells we presently used a discriminant analysis-based approach to predict NF-kappa B responding genes on the basis of putative regulatory elements. Results: The performance of linear and quadratic discriminant analysis (LDA, QDA) in identifying NF-kappa B-responding genes was examined on a dataset of 240 positive and negative examples of NF-kappa B regulation, using stratified cross-validation with an internal leave-one-out cross-validation (LOOCV) loop for automated feature selection and noise reduction. LDA performed slightly better than QDA, achieving 61% sensitivity, 91% specificity and 87% positive predictive value, and allowing the identification of 231, 251 and 580 NF-kappa B putative target genes in insulin- producing INS-IE cells, primary rat beta- cells and human pancreatic islets, respectively. Predicted NF-kappa B targets had a significant enrichment in genes regulated by cytokines (IL-1 beta or IL-1 beta + IFN-.) and double stranded RNA (dsRNA), as compared to genes not regulated by these NF-kappa B-dependent stimuli. We increased the confidence of the predictions by selecting only evolutionary stable genes, i.e. genes with homologs predicted as NF-kappa B targets in rat, mouse, human and chimpanzee. Conclusion: The present in silico analysis allowed us to identify novel regulatory targets of NF-kappa B using a supervised classification method based on putative binding motifs. This provides new insights into the gene networks regulating cytokine-induced beta-cell dysfunction and death.