Literature DB >> 32098801

Integrative analysis suggests cell type-specific decoding of NF-κB dynamics.

Erik W Martin1, Alicja Pacholewska1, Heta Patel1, Himanshu Dashora1, Myong-Hee Sung2.   

Abstract

The complex signaling dynamics of transcription factors can encode both qualitative and quantitative information about the extracellular environment, which increases the information transfer capacity and potentially supports accurate cellular decision-making. An important question is how these signaling dynamics patterns are translated into functionally appropriate gene regulation programs. To address this question for transcription factors of the nuclear factor κB (NF-κB) family, we profiled the single-cell dynamics of two major NF-κB subunits, RelA and c-Rel, induced by a panel of pathogen-derived stimuli in immune and nonimmune cellular contexts. Diverse NF-κB-activating ligands produced different patterns of RelA and c-Rel signaling dynamic features, such as variations in duration or time-integrated activity. Analysis of nascent transcripts delineated putative direct targets of NF-κB as compared to genes controlled by other transcriptional and posttranscriptional mechanisms and showed that the transcription of more than half of the induced genes was tightly linked to specific dynamic features of NF-κB signaling. Fibroblast and macrophage cell lines shared a cluster of such "NF-κB dynamics-decoding" genes, as well as cell type-specific decoding genes. Dissecting the subunit specificity of dynamics-decoding genes suggested that target genes were most often linked to both RelA and c-Rel or to RelA alone. Thus, our analysis reveals the cell type-specific interpretation of pathogenic information through the signaling dynamics of NF-κB.
Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Entities:  

Year:  2020        PMID: 32098801      PMCID: PMC7294995          DOI: 10.1126/scisignal.aax7195

Source DB:  PubMed          Journal:  Sci Signal        ISSN: 1945-0877            Impact factor:   8.192


  57 in total

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