Back

Tumor suppressor NME1/NM23-H1 modulates DNA binding of NF-κB RelA

Shahabi, S.; Maurya, M.; Subramaniam, S.; Ghosh, G.

2024-10-06 biochemistry
10.1101/2024.10.06.616908 bioRxiv
Show abstract

The dimeric NF-{kappa}B family of transcription factors activates transcription by binding sequence-specifically to DNA response elements known as {kappa}B sites, located within the promoters and enhancers of their target genes. While most NF-{kappa}B remain inactive in the cytoplasm of unstimulated cells, a small amount of RelA, one of its members, persists in the nucleus, ensuring low-level expression of genes essential for homeostasis. Several cofactors have been identified that aid in DNA binding of RelA. In this study, we identify NME1 (nucleoside diphosphate kinase 1) as a cofactor that enhances RelAs ability to bind {kappa}B sites within the promoters of a subset of its target genes, promoting their expression under both unstimulated and stimulated conditions. Depletion of NME1 influences activation or repression of several genes that are unresponsive to TNF, despite containing {kappa}B sites in their promoters but not in clusters. This suggests that clustering of kB sites may be necessary for RelA-dependent transcription complex assembly. NME1 appears to act as a cofactor for other transcription factors to regulate these genes. NME1 does not directly contact {kappa}B DNA but interacts with RelA, with this interaction being further strengthened in the presence of {kappa}B DNA. Notably, NME1 alone has a marginal effect in enhancing RelAs DNA binding, suggesting that NME1 likely cooperate with other cofactors to regulate DNA binding and transcription through RelA. These observations underscore the intricate assembly of transcription complexes centered on NF-{kappa}B.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.