Multi-layered stochasticity and paracrine signal propagation shape the type-I interferon response
Open accessAbstract
The cellular recognition of viruses evokes the secretion of type‐I interferons (IFNs) that induce an antiviral protective state. By live‐cell imaging, we show that key steps of virus‐induced signal transduction, IFN‐β expression, and induction of IFN‐stimulated genes (ISGs) are stochastic events in individual cells. The heterogeneity in IFN production is of cellular—and not viral—origin, and temporal unpredictability of IFN‐β expression is largely due to cell‐intrinsic noise generated both upstream and downstream of the activation of nuclear factor‐κB and IFN regulatory factor transcription factors. Subsequent ISG induction occurs as a stochastic all‐or‐nothing switch, where the responding cells are protected against virus replication. Mathematical modelling and experimental validation show that reliable antiviral protection in the face of multi‐layered cellular stochasticity is achieved by paracrine response amplification. Achieving coherent responses through intercellular communication is likely to be a more widely used strategy by mammalian cells to cope with pervasive stochasticity in signalling and gene expression. Live‐cell imaging and mathematical modelling of the type‐I interferon response to viral infection reveal that multiple layers of the cellular response are stochastic events in individual cells, while paracrine propagation of the IFN signal results in reliable antiviral protection. Live‐cell imaging and mathematical modelling of the type‐I interferon response to viral infection reveal that multiple layers of the cellular response are stochastic events in individual cells, while paracrine propagation of the IFN signal results in reliable antiviral protection.
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The type I IFN response can be heterogeneous: it depends on the reacting cell's state, is at least partly stochastic, varies among cell types and microenvironments, and shows interindividual heterogeneity in amplitude and kinetics.
“Importantly, the type I IFN response can be rather heterogeneous. Depending on the state of the reacting cell (e.g., with respect to its metabolic or general activation state) (Talemi and Höfer, 2018), it is at least in part stochastic (Rand et al., 2012; Wimmers et al., 2018), it varies among different cell types and microenvironments, and it shows interindividual heterogeneity concerning the”
From COVID-19 and the human innate immune system (2021) · cites this paper as Rand et al., 2012
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- Authors
- Rand, U., Rinas, M., Schwerk, J., Nöhren, G., Linnes, M., Kröger, A., Flossdorf, M., Kály‐Kullai, K., Hauser, H., Höfer, T., & Köster, M.
- Affiliations
- German Cancer Research Center (DE)
- Helmholtz Centre for Infection Research (DE)
- Corresponding author
- Höfer, Thomas
- Köster, Mario
- Venue
- Molecular Systems Biology
- Published
- 2012-05-22
- Volume
- 8
- Issue
- 1
- Pages
- 584-584
- ISSN
- 1744-4292 (ISSN-L)
- PMC
- PMC3377992
- OpenAlex
- W2167213467
- Cited by
- 147
- References
- 47
- Citations by year
- 2026: 9 · 2025: 6 · 2024: 5 · 2023: 14 · 2022: 8 · 2021: 7 · 2020: 12 · 2019: 11 · 2018: 18 · 2017: 12 · 2016: 7 · 2015: 15 · 2014: 11 · 2013: 9 · 2012: 3
- FWCI
- 5.29
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Molecular Systems Biology (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- HZI (Helmholtz Centre for Infection Research) (submittedVersion)
- Funders
- Deutsche Forschungsgemeinschaft (SFB 900)
- Bundesministerium für Bildung und Forschung
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › interferon and immune responses
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Immunology and Microbiology › Immunology › Immune Response and Inflammation
- Keywords
- type I interferon response, stochastic gene expression, intercellular communication, IFN-stimulated genes, NF-κB, IRF transcription factors, antiviral defense, viral infection
- MeSH terms
- Animals, Cell Line, Gene Expression Regulation, Interferon Type I, Models, Biological, Newcastle disease virus, Stochastic Processes, Transcription Factors, Signal Transduction, NF-kappa B, Interferon-beta, Paracrine Communication, Chromosomes, Artificial, Bacterial, Mice, Host-Pathogen Interactions, Single-Cell Analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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