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

BACKGROUND: Pancreatic 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)-1beta 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-1beta-activated transcription factor (TF) nuclear factor (NF)-kappaB, and previous studies by our group have shown that cytokine-induced NF-kappaB activation is pro-apoptotic in beta-cells. To identify NF-kappaB-regulated gene networks in beta-cells we presently used a discriminant analysis-based approach to predict NF-kappaB responding genes on the basis of putative regulatory elements. RESULTS: The performance of linear and quadratic discriminant analysis (LDA, QDA) in identifying NF-kappaB-responding genes was examined on a dataset of 240 positive and negative examples of NF-kappaB 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-kappaB putative target genes in insulin-producing INS-1E cells, primary rat beta-cells and human pancreatic islets, respectively. Predicted NF-kappaB targets had a significant enrichment in genes regulated by cytokines (IL-1beta or IL-1beta + IFN-gamma) and double stranded RNA (dsRNA), as compared to genes not regulated by these NF-kappaB-dependent stimuli. We increased the confidence of the predictions by selecting only evolutionary stable genes, i.e. genes with homologs predicted as NF-kappaB targets in rat, mouse, human and chimpanzee. CONCLUSION: The present in silico analysis allowed us to identify novel regulatory targets of NF-kappaB 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

55-55

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

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    38 schema:description BACKGROUND: Pancreatic 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)-1beta 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-1beta-activated transcription factor (TF) nuclear factor (NF)-kappaB, and previous studies by our group have shown that cytokine-induced NF-kappaB activation is pro-apoptotic in beta-cells. To identify NF-kappaB-regulated gene networks in beta-cells we presently used a discriminant analysis-based approach to predict NF-kappaB responding genes on the basis of putative regulatory elements. RESULTS: The performance of linear and quadratic discriminant analysis (LDA, QDA) in identifying NF-kappaB-responding genes was examined on a dataset of 240 positive and negative examples of NF-kappaB 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-kappaB putative target genes in insulin-producing INS-1E cells, primary rat beta-cells and human pancreatic islets, respectively. Predicted NF-kappaB targets had a significant enrichment in genes regulated by cytokines (IL-1beta or IL-1beta + IFN-gamma) and double stranded RNA (dsRNA), as compared to genes not regulated by these NF-kappaB-dependent stimuli. We increased the confidence of the predictions by selecting only evolutionary stable genes, i.e. genes with homologs predicted as NF-kappaB targets in rat, mouse, human and chimpanzee. CONCLUSION: The present in silico analysis allowed us to identify novel regulatory targets of NF-kappaB 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 INS-1E cells
    47 LDA
    48 NF-kappaB
    49 NF-kappaB activation
    50 NF-kappaB putative target genes
    51 NF-kappaB regulation
    52 NF-kappaB targets
    53 QDA
    54 RNA
    55 activation
    56 analysis
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    58 apoptosis
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    60 attacks
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    63 beta-cell dysfunction
    64 binding motif
    65 cells
    66 chimpanzees
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    70 cytokine-induced NF-kappaB activation
    71 cytokine-induced beta-cell dysfunction
    72 cytokine-induced genes
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    74 datasets
    75 death
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    77 diabetes mellitus
    78 discriminant analysis
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    80 dysfunction
    81 elements
    82 enrichment
    83 evolutionary stable genes
    84 example
    85 expression
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    87 factor (TF) nuclear factor
    88 factors
    89 feature selection
    90 gene networks
    91 genes
    92 group
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    94 human pancreatic islets
    95 humans
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    97 identification
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    99 insulin-producing INS-1E cells
    100 interferon
    101 interleukin
    102 internal leave
    103 islets
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    107 method
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    109 motif
    110 negative examples
    111 network
    112 new insights
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    114 novel regulatory targets
    115 nuclear factor
    116 one-out cross-validation (LOOCV) loop
    117 pancreatic islets
    118 part
    119 performance
    120 positive predictive value
    121 prediction
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    123 present
    124 previous studies
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    126 putative binding motifs
    127 putative regulatory elements
    128 putative target genes
    129 quadratic discriminant analysis
    130 rats
    131 reduction
    132 regulation
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