IDEAS home Printed from https://ideas.repec.org/a/plo/pcbi00/1006368.html
   My bibliography  Save this article

Quantitative single cell analysis uncovers the life/death decision in CD95 network

Author

Listed:
  • Jörn H Buchbinder
  • Dennis Pischel
  • Kai Sundmacher
  • Robert J Flassig
  • Inna N Lavrik

Abstract

CD95/Fas/APO-1 is a member of the death receptor family that triggers apoptotic and anti-apoptotic responses in particular, NF-κB. These responses are characterized by a strong heterogeneity within a population of cells. To determine how the cell decides between life and death we developed a computational model supported by imaging flow cytometry analysis of CD95 signaling. Here we show that CD95 stimulation leads to the induction of caspase and NF-κB pathways simultaneously in one cell. The related life/death decision strictly depends on cell-to-cell variability in the formation of the death-inducing complex (DISC) on one side (extrinsic noise) vs. stochastic gene expression of the NF-κB pathway on the other side (intrinsic noise). Moreover, our analysis has uncovered that the stochasticity in apoptosis and NF-kB pathways leads not only to survival or death of a cell, but also causes a third type of response to CD95 stimulation that we termed ambivalent response. Cells in the ambivalent state can undergo cell death or survive which was subsequently validated by experiments. Taken together, we have uncovered how these two competing pathways control the fate of a cell, which in turn plays an important role for development of anti-cancer therapies.Author summary: Activation of death receptor (DR) family has been reported to activate both apoptotic as well as anti-apoptotic responses. Molecular mechanisms underlying the intricate details of this crosstalk have not been established yet. Here we show that these pathways are triggered simultaneously in one cell. Furthermore, using stochastic computational modeling we uncovered how an individual cell undergoes apoptosis, while other cells survive upon the same DR activation conditions. This was only possible by combination of computational modeling supported by experimental validation based on the state of the art single cell analysis. The latter included cutting edge technology of imaging flow cytometry, which combines microscopy and flow cytometry in one measurement circuit enabling quantitative analysis of endogenous cellular protein levels estimated from a large number of cells simultaneously. This allowed to shed the light on the question how a single cell possibly avoids apoptosis, which is a highly actual topic in the field of cancer research and development of efficient anti-cancer therapies.

Suggested Citation

  • Jörn H Buchbinder & Dennis Pischel & Kai Sundmacher & Robert J Flassig & Inna N Lavrik, 2018. "Quantitative single cell analysis uncovers the life/death decision in CD95 network," PLOS Computational Biology, Public Library of Science, vol. 14(9), pages 1-21, September.
  • Handle: RePEc:plo:pcbi00:1006368
    DOI: 10.1371/journal.pcbi.1006368
    as

    Download full text from publisher

    File URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006368
    Download Restriction: no

    File URL: https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1006368&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pcbi.1006368?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Avigdor Eldar & Michael B. Elowitz, 2010. "Functional roles for noise in genetic circuits," Nature, Nature, vol. 467(7312), pages 167-173, September.
    2. Dennis Pischel & Jörn H Buchbinder & Kai Sundmacher & Inna N Lavrik & Robert J Flassig, 2018. "A guide to automated apoptosis detection: How to make sense of imaging flow cytometry data," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-17, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohammad Soltani & Cesar A Vargas-Garcia & Duarte Antunes & Abhyudai Singh, 2016. "Intercellular Variability in Protein Levels from Stochastic Expression and Noisy Cell Cycle Processes," PLOS Computational Biology, Public Library of Science, vol. 12(8), pages 1-23, August.
    2. Kazunari Iwamoto & Yuki Shindo & Koichi Takahashi, 2016. "Modeling Cellular Noise Underlying Heterogeneous Cell Responses in the Epidermal Growth Factor Signaling Pathway," PLOS Computational Biology, Public Library of Science, vol. 12(11), pages 1-18, November.
    3. Lee, Julian, 2023. "Poisson distributions in stochastic dynamics of gene expression: What events do they count?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    4. Lucy Ham & Megan A. Coomer & Kaan Öcal & Ramon Grima & Michael P. H. Stumpf, 2024. "A stochastic vs deterministic perspective on the timing of cellular events," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    5. Georg Fritz & Judith A Megerle & Sonja A Westermayer & Delia Brick & Ralf Heermann & Kirsten Jung & Joachim O Rädler & Ulrich Gerland, 2014. "Single Cell Kinetics of Phenotypic Switching in the Arabinose Utilization System of E. coli," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-12, February.
    6. Laura Corrales-Guerrero & Asaf Tal & Rinat Arbel-Goren & Vicente Mariscal & Enrique Flores & Antonia Herrero & Joel Stavans, 2015. "Spatial Fluctuations in Expression of the Heterocyst Differentiation Regulatory Gene hetR in Anabaena Filaments," PLOS Genetics, Public Library of Science, vol. 11(4), pages 1-21, April.
    7. Singh, Abhyudai & Vahdat, Zahra & Xu, Zikai, 2019. "Time-triggered stochastic hybrid systems with two timer-dependent resets," OSF Preprints u8fzg, Center for Open Science.
    8. Ming Ni & Antoine L Decrulle & Fanette Fontaine & Alice Demarez & Francois Taddei & Ariel B Lindner, 2012. "Pre-Disposition and Epigenetics Govern Variation in Bacterial Survival upon Stress," PLOS Genetics, Public Library of Science, vol. 8(12), pages 1-11, December.
    9. Jan Hasenauer & Christine Hasenauer & Tim Hucho & Fabian J Theis, 2014. "ODE Constrained Mixture Modelling: A Method for Unraveling Subpopulation Structures and Dynamics," PLOS Computational Biology, Public Library of Science, vol. 10(7), pages 1-17, July.
    10. Mahdi Golkaram & Stefan Hellander & Brian Drawert & Linda R Petzold, 2016. "Macromolecular Crowding Regulates the Gene Expression Profile by Limiting Diffusion," PLOS Computational Biology, Public Library of Science, vol. 12(11), pages 1-16, November.
    11. Martiny, Emil S. & Jensen, Mogens H. & Heltberg, Mathias S., 2022. "Detecting limit cycles in stochastic time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    12. Koji Iwamoto & Satomi Matsuoka & Masahiro Ueda, 2025. "Excitable Ras dynamics-based screens reveal RasGEFX is required for macropinocytosis and random cell migration," Nature Communications, Nature, vol. 16(1), pages 1-20, December.
    13. Ziya Kalay & Takahiro K Fujiwara & Akihiro Kusumi, 2012. "Confining Domains Lead to Reaction Bursts: Reaction Kinetics in the Plasma Membrane," PLOS ONE, Public Library of Science, vol. 7(3), pages 1-8, March.
    14. Margaritis Voliotis & Philipp Thomas & Ramon Grima & Clive G Bowsher, 2016. "Stochastic Simulation of Biomolecular Networks in Dynamic Environments," PLOS Computational Biology, Public Library of Science, vol. 12(6), pages 1-18, June.
    15. Vera Bettenworth & Simon Vliet & Bartosz Turkowyd & Annika Bamberger & Heiko Wendt & Matthew McIntosh & Wieland Steinchen & Ulrike Endesfelder & Anke Becker, 2022. "Frequency modulation of a bacterial quorum sensing response," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    16. Gabriele Micali & Gerardo Aquino & David M Richards & Robert G Endres, 2015. "Accurate Encoding and Decoding by Single Cells: Amplitude Versus Frequency Modulation," PLOS Computational Biology, Public Library of Science, vol. 11(6), pages 1-21, June.
    17. Jessica A Lee & Siavash Riazi & Shahla Nemati & Jannell V Bazurto & Andreas E Vasdekis & Benjamin J Ridenhour & Christopher H Remien & Christopher J Marx, 2019. "Microbial phenotypic heterogeneity in response to a metabolic toxin: Continuous, dynamically shifting distribution of formaldehyde tolerance in Methylobacterium extorquens populations," PLOS Genetics, Public Library of Science, vol. 15(11), pages 1-38, November.
    18. Chen, Aimin & Tian, Tianhai & Chen, Yiren & Zhou, Tianshou, 2022. "Stochastic analysis of a complex gene-expression model," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    19. Abhyudai Singh & Mohammad Soltani, 2013. "Quantifying Intrinsic and Extrinsic Variability in Stochastic Gene Expression Models," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-12, December.
    20. Angélique Richard & Loïs Boullu & Ulysse Herbach & Arnaud Bonnafoux & Valérie Morin & Elodie Vallin & Anissa Guillemin & Nan Papili Gao & Rudiyanto Gunawan & Jérémie Cosette & Ophélie Arnaud & Jean-Ja, 2016. "Single-Cell-Based Analysis Highlights a Surge in Cell-to-Cell Molecular Variability Preceding Irreversible Commitment in a Differentiation Process," PLOS Biology, Public Library of Science, vol. 14(12), pages 1-35, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pcbi00:1006368. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ploscompbiol (email available below). General contact details of provider: https://journals.plos.org/ploscompbiol/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.