Stochastic dynamics of Type-I interferon responses Article Swipe
Benjamin Dominik Maier
,
Luis U. Aguilera
,
Sven Sahle
,
Pascal Mutz
,
Priyata Kalra
,
Christopher Dächert
,
Ralf Bartenschlager
,
Marco Binder
,
Ursula Kummer
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pcbi.1010623
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pcbi.1010623
Interferon (IFN) activates the transcription of several hundred of IFN stimulated genes (ISGs) that constitute a highly effective antiviral defense program. Cell-to-cell variability in the induction of ISGs is well documented, but its source and effects are not completely understood. The molecular mechanisms behind this heterogeneity have been related to randomness in molecular events taking place during the JAK-STAT signaling pathway. Here, we study the sources of variability in the induction of the IFN-alpha response by using MxA and IFIT1 activation as read-out. To this end, we integrate time-resolved flow cytometry data and stochastic modeling of the JAK-STAT signaling pathway. The complexity of the IFN response was matched by fitting probability distributions to time-course flow cytometry snapshots. Both, experimental data and simulations confirmed that the MxA and IFIT1 induction circuits generate graded responses rather than all-or-none responses. Subsequently, we quantify the size of the intrinsic variability at different steps in the pathway. We found that stochastic effects are transiently strong during the ligand-receptor activation steps and the formation of the ISGF3 complex, but negligible for the final induction of the studied ISGs. We conclude that the JAK-STAT signaling pathway is a robust biological circuit that efficiently transmits information under stochastic environments.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1371/journal.pcbi.1010623
- https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1010623&type=printable
- OA Status
- gold
- Cited By
- 10
- References
- 87
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4307001980
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Raw OpenAlex JSON
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https://openalex.org/W4307001980Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1371/journal.pcbi.1010623Digital Object Identifier
- Title
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Stochastic dynamics of Type-I interferon responsesWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-10-21Full publication date if available
- Authors
-
Benjamin Dominik Maier, Luis U. Aguilera, Sven Sahle, Pascal Mutz, Priyata Kalra, Christopher Dächert, Ralf Bartenschlager, Marco Binder, Ursula KummerList of authors in order
- Landing page
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https://doi.org/10.1371/journal.pcbi.1010623Publisher landing page
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https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1010623&type=printableDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
- OA URL
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https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1010623&type=printableDirect OA link when available
- Concepts
-
Biology, Flow cytometry, Interferon, Signal transduction, Randomness, Computational biology, stat, Interferon type I, Cell biology, Genetics, Mathematics, STAT3, StatisticsTop concepts (fields/topics) attached by OpenAlex
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10Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 2, 2023: 5, 2022: 1Per-year citation counts (last 5 years)
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87Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| countries_distinct_count | 1 |
| institutions_distinct_count | 9 |
| corresponding_institution_ids | https://openalex.org/I17937529, https://openalex.org/I223822909, https://openalex.org/I2802164966 |
| citation_normalized_percentile.value | 0.73935706 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |