Co-imaging of RelA and c-Rel reveals features of NF-κB signaling for ligand discrimination.

CP: Molecular biology NF-κB RelA c-Rel endogenous knockin fluorescent fusion reporter mice inflammatory signaling live microscopy macrophages mathematical modeling

Journal

Cell reports
ISSN: 2211-1247
Titre abrégé: Cell Rep
Pays: United States
ID NLM: 101573691

Informations de publication

Date de publication:
12 Mar 2024
Historique:
received: 07 06 2023
revised: 11 12 2023
accepted: 23 02 2024
medline: 14 3 2024
pubmed: 14 3 2024
entrez: 14 3 2024
Statut: aheadofprint

Résumé

Individual cell sensing of external cues has evolved through the temporal patterns in signaling. Since nuclear factor κB (NF-κB) signaling dynamics have been examined using a single subunit, RelA, it remains unclear whether more information might be transmitted via other subunits. Using NF-κB double-knockin reporter mice, we monitored both canonical NF-κB subunits, RelA and c-Rel, simultaneously in single macrophages by quantitative live-cell imaging. We show that signaling features of RelA and c-Rel convey more information about the stimuli than those of either subunit alone. Machine learning is used to predict the ligand identity accurately based on RelA and c-Rel signaling features without considering the co-activated factors. Ligand discrimination is achieved through selective non-redundancy of RelA and c-Rel signaling dynamics, as well as their temporal coordination. These results suggest a potential role of c-Rel in fine-tuning immune responses and highlight the need for approaches that will elucidate the mechanisms regulating NF-κB subunit specificity.

Identifiants

pubmed: 38483906
pii: S2211-1247(24)00268-7
doi: 10.1016/j.celrep.2024.113940
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

113940

Informations de copyright

Published by Elsevier Inc.

Déclaration de conflit d'intérêts

Declaration of interests The authors declare no competing interests.

Auteurs

Shah Md Toufiqur Rahman (SMT)

Laboratory of Molecular Biology and Immunology, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.

Apeksha Singh (A)

Institute for Quantitative and Computational Biosciences and Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, USA.

Sarina Lowe (S)

Institute for Quantitative and Computational Biosciences and Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, USA.

Mohammad Aqdas (M)

Laboratory of Molecular Biology and Immunology, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.

Kevin Jiang (K)

Institute for Quantitative and Computational Biosciences and Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, USA.

Haripriya Vaidehi Narayanan (H)

Institute for Quantitative and Computational Biosciences and Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, USA.

Alexander Hoffmann (A)

Institute for Quantitative and Computational Biosciences and Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, USA.

Myong-Hee Sung (MH)

Laboratory of Molecular Biology and Immunology, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA. Electronic address: sungm@nih.gov.

Classifications MeSH