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


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Article Info

DATE

2007-02-15

AUTHORS

Najib Naamane, Jacques van Helden, Decio L Eizirik

ABSTRACT

BackgroundPancreatic beta-cells are the target of an autoimmune attack in type 1 diabetes mellitus (T1DM). This is mediated in part by cytokines, such as interleukin (IL)-1β and interferon (IFN)-γ. 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-1β-activated transcription factor (TF) nuclear factor (NF)-κB, and previous studies by our group have shown that cytokine-induced NF-κB activation is pro-apoptotic in beta-cells. To identify NF-κB-regulated gene networks in beta-cells we presently used a discriminant analysis-based approach to predict NF-κB responding genes on the basis of putative regulatory elements.ResultsThe performance of linear and quadratic discriminant analysis (LDA, QDA) in identifying NF-κB-responding genes was examined on a dataset of 240 positive and negative examples of NF-κB 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-κB putative target genes in insulin-producing INS-1E cells, primary rat beta-cells and human pancreatic islets, respectively. Predicted NF-κB targets had a significant enrichment in genes regulated by cytokines (IL-1β or IL-1β + IFN-γ) and double stranded RNA (dsRNA), as compared to genes not regulated by these NF-κB-dependent stimuli. We increased the confidence of the predictions by selecting only evolutionary stable genes, i.e. genes with homologs predicted as NF-κB targets in rat, mouse, human and chimpanzee.ConclusionThe present in silico analysis allowed us to identify novel regulatory targets of NF-κB 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. More... »

PAGES

55

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    http://scigraph.springernature.com/pub.10.1186/1471-2105-8-55

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    DIMENSIONS

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    PUBMED

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    37 schema:description BackgroundPancreatic beta-cells are the target of an autoimmune attack in type 1 diabetes mellitus (T1DM). This is mediated in part by cytokines, such as interleukin (IL)-1β and interferon (IFN)-γ. 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-1β-activated transcription factor (TF) nuclear factor (NF)-κB, and previous studies by our group have shown that cytokine-induced NF-κB activation is pro-apoptotic in beta-cells. To identify NF-κB-regulated gene networks in beta-cells we presently used a discriminant analysis-based approach to predict NF-κB responding genes on the basis of putative regulatory elements.ResultsThe performance of linear and quadratic discriminant analysis (LDA, QDA) in identifying NF-κB-responding genes was examined on a dataset of 240 positive and negative examples of NF-κB 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-κB putative target genes in insulin-producing INS-1E cells, primary rat beta-cells and human pancreatic islets, respectively. Predicted NF-κB targets had a significant enrichment in genes regulated by cytokines (IL-1β or IL-1β + IFN-γ) and double stranded RNA (dsRNA), as compared to genes not regulated by these NF-κB-dependent stimuli. We increased the confidence of the predictions by selecting only evolutionary stable genes, i.e. genes with homologs predicted as NF-κB targets in rat, mouse, human and chimpanzee.ConclusionThe present in silico analysis allowed us to identify novel regulatory targets of NF-κB 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.
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    46 LDA
    47 NF-kappaB
    48 NF-κB activation
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    52 RNA
    53 activation
    54 analysis
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    61 beta-cell dysfunction
    62 binding motif
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    64 chimpanzees
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    68 cytokine-induced NF-κB activation
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    70 cytokine-induced genes
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    84 gene networks
    85 genes
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    88 human pancreatic islets
    89 humans
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    91 identification
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    93 insulin-producing INS-1E cells
    94 interferon
    95 interleukin
    96 islets
    97 loop
    98 mellitus
    99 method
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    101 motif
    102 negative examples
    103 network
    104 new insights
    105 noise reduction
    106 novel regulatory target
    107 nuclear factor
    108 pancreatic islets
    109 part
    110 performance
    111 positive predictive value
    112 prediction
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    114 present
    115 previous studies
    116 primary rat
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    120 quadratic discriminant analysis
    121 rats
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