Evidence map›Paper›PMID 40794834›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

Gene regulatory logic of the interferon-β enhancer is characterized by two selectively deployed modes of transcription factor synergy.

Allison Schiffman, Zhang Cheng, Diana Ourthiague, Alexander Hoffmann

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Allison SchiffmanSignaling Systems Laboratory, Department of Microbiology, Immunology and Molecular Genetics, and the Institute for Quantitative and Computational Biosciences, University of California Los Angeles, CA 90095.
Zhang ChengSignaling Systems Laboratory, Department of Microbiology, Immunology and Molecular Genetics, and the Institute for Quantitative and Computational Biosciences, University of California Los Angeles, CA 90095.
Diana OurthiagueSignaling Systems Laboratory, Department of Microbiology, Immunology and Molecular Genetics, and the Institute for Quantitative and Computational Biosciences, University of California Los Angeles, CA 90095.
Alexander HoffmannSignaling Systems Laboratory, Department of Microbiology, Immunology and Molecular Genetics, and the Institute for Quantitative and Computational Biosciences, University of California Los Angeles, CA 90095.ORCID 0000-0002-5607-3845

Funding

Systems Epigenomics of Persistent Bloodstream InfectionU19AI172713 · NIAID · LUNDQUIST INSTITUTE FOR BIOMEDICAL INNOVATION AT HARBOR-UCLA MEDICAL CENTER · PI David Gjertson · 2023 to 2026
$11.6M
Characterizing functional states of macrophages via their stimulus-responsesR01AI173214 · NIAID · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Alexander Hoffmann · 2023 to 2026
$2.8M
The IRF regulatory network in innate immune training of macrophagesR01AI185026 · NIAID · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Alexander Hoffmann · 2025 to 2026
$1.3M
HHS | National Institutes of Health (NIH) R01AI173214HHS | National Institutes of Health (NIH) R01AI185026National Science Foundation (NSF) DGE-2034835NIAID NIH HHS R01 AI173214NIAID NIH HHS R01 AI185026NIAID NIH HHS U19 AI172713
6 · The paper itself

Abstract

Type I interferon IFNβ is a key immune response cytokine, and when its expression is dysregulated, it causes disease. The regulation of IFNβ enhancer has been a touchpoint of mammalian gene control research since the discovery of functional synergy between two stimulus-responsive transcription factors (TFs), nuclear factor kappa B (NFκB) and interferon regulatory factors (IRF). However, subsequent gene knockout studies revealed that in some conditions either NFκB or IRF activation can be dispensable, leaving the precise regulatory logic of IFNβ transcription an open question. Here, we developed a series of quantitative enhancer states models of IFNβ expression control and evaluated them with stimulus-response data from TF knockouts. Of these, our analysis reveals that two modes of TF synergy account for the available data and neither is based on binding cooperativity. The first involves two adjacent IRF dimers, with a sigmoidal binding curve at the distal site rendering it ultrasensitive and restricting it to conditions of high IRF activity upon viral infection. The second is driven by the proximal site, which has high affinity and synergizes with NFκB to enable about half-maximal expression in response to bacterial exposure. Its accessibility is controlled by the competitive repressor p50:p50, which prevents basal IRF from binding, such that NFκB-only stimuli do not induce IFNβ expression and may allow for prior-exposure-dependent tuning. The model explains how the regulatory logic of the IFNβ enhancer ensures invariant IFNβ expression in response to viral exposure, while providing tunable, context-dependent expression in response to bacterial exposure.

Indexed as

Enhancer Elements, GeneticGene Expression RegulationInterferon-betaInterferon Regulatory FactorsTranscription FactorsAnimalsHumansMiceNF-kappa BInterferon-betaInterferon Regulatory FactorsNF-kappa BTranscription Factorsboolean logic gatesinterferon regulatory factors (IRF)interferon-βNFκBthermodynamic state ensemble models

Identifiers

PMID40794834
PMCPMC12377728

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.