Abstract

Modulators (Ms) are proteins that modify the activity of transcription factors (TFs) and influence expression of their target genes (TGs). To discover modulators of NF-κB/RelA, we first identified 365 NF-κB/RelA-binding proteins using liquid chromatography-tandem mass spectrometry (LC-MS/MS). We used a probabilistic model to infer 8349 (M, NF-κB/RelA, TG) triplets and their modes of modulatory action from our combined LC-MS/MS and ChIP-Seq (ChIP followed by next generation sequencing) data, published RelA modulators and TGs, and a compendium of gene expression profiles. Hierarchical clustering of the derived modulatory network revealed functional subnetworks and suggested new pathways modulating RelA transcriptional activity. The modulators with the highest number of TGs and most non-random distribution of action modes (measured by Shannon entropy) are consistent with published reports. Our results provide a repertoire of testable hypotheses for experimental validation. One of the NF-κB/RelA modulators we identified is STAT1. The inferred (STAT1, NF-κB/RelA, TG) triplets were validated by LC-selected reaction monitoring-MS and the results of STAT1 deletion in human fibrosarcoma cells. Overall, we have identified 562 NF-κB/RelA modulators, which are potential drug targets, and clarified mechanisms of achieving NF-κB/RelA multiple functions through modulators. Our approach can be readily applied to other TFs.

Highlights

  • Interacting proteins modulate the activity of NF-␬B/RelA transcription factor and expression of its targets

  • Implementation of the Probabilistic Model for (M, transcription factors (TFs), target genes (TGs)) Triplet Prediction—We implemented an algorithm for predicting (M, TF, TG) triplets based on a compendium of 2158 expression profiles

  • The underlying probabilistic model [19] of triplet action depends on four basic parameters, ␣c, ␣f, ␣m, and ␥, that correspond to the basal level of a TG, the dependence of TG expression on TF, the dependence on the M, and the interactive effect of the M and TF on the TG

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Summary

Introduction

Interacting proteins modulate the activity of NF-␬B/RelA transcription factor and expression of its targets. Results: By analyzing gene expression, protein binding, and DNA binding, we inferred and characterized 8349 such modulations. Modulators (Ms) are proteins that modify the activity of transcription factors (TFs) and influence expression of their target genes (TGs). We used a probabilistic model to infer 8349 (M, NF-␬B/RelA, TG) triplets and their modes of modulatory action from our combined LC-MS/MS and ChIP-Seq (ChIP followed by generation sequencing) data, published RelA modulators and TGs, and a compendium of gene expression profiles. Hierarchical clustering of the derived modulatory network revealed functional subnetworks and suggested new pathways modulating RelA transcriptional activity. The inferred (STAT1, NF-␬B/RelA, TG) triplets were validated by LC-selected reaction monitoring-MS and the results of STAT1 deletion in human fibrosarcoma cells.

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