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Variability and memory of protein levels in human cells

Author

Listed:
  • Alex Sigal

    (Weizmann Institute of Science)

  • Ron Milo

    (Weizmann Institute of Science
    Harvard Medical School)

  • Ariel Cohen

    (Weizmann Institute of Science)

  • Naama Geva-Zatorsky

    (Weizmann Institute of Science)

  • Yael Klein

    (Weizmann Institute of Science)

  • Yuvalal Liron

    (Weizmann Institute of Science)

  • Nitzan Rosenfeld

    (Weizmann Institute of Science)

  • Tamar Danon

    (Weizmann Institute of Science)

  • Natalie Perzov

    (Weizmann Institute of Science)

  • Uri Alon

    (Weizmann Institute of Science)

Abstract

Feel the noise Genetically identical cells produce variable levels of a given protein at a given time. This 'noise' in genetic expression is implicated in many important processes including cell fate determination and resistance to drugs. So far the phenomenon has been observed directly only in 'snapshots' of populations of microorganisms. But a study published this week breaks new ground by following the dynamics of such noise over time, in human cancer cells, and comparing different proteins. The work reveals surprisingly long-lasting 'memories' of individual cell states, which can last for more than two generations in culture. This fundamental result may be the basis for human cells' heterogeneous and delayed responses to drugs.

Suggested Citation

  • Alex Sigal & Ron Milo & Ariel Cohen & Naama Geva-Zatorsky & Yael Klein & Yuvalal Liron & Nitzan Rosenfeld & Tamar Danon & Natalie Perzov & Uri Alon, 2006. "Variability and memory of protein levels in human cells," Nature, Nature, vol. 444(7119), pages 643-646, November.
    • Handle: RePEc:nat:nature:v:444:y:2006:i:7119:d:10.1038_nature05316
    DOI: 10.1038/nature05316
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    Citations

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    Cited by:

    1. Hui Zhang & Yueling Chen & Yong Chen, 2012. "Noise Propagation in Gene Regulation Networks Involving Interlinked Positive and Negative Feedback Loops," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-8, December.
    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. UnJin Lee & John J Skinner & John Reinitz & Marsha Rich Rosner & Eun-Jin Kim, 2015. "Noise-Driven Phenotypic Heterogeneity with Finite Correlation Time in Clonal Populations," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-17, July.
    4. Alok Maity & Roy Wollman, 2020. "Information transmission from NFkB signaling dynamics to gene expression," PLOS Computational Biology, Public Library of Science, vol. 16(8), pages 1-16, August.
    5. David A Sivak & Matt Thomson, 2014. "Environmental Statistics and Optimal Regulation," PLOS Computational Biology, Public Library of Science, vol. 10(9), pages 1-12, September.
    6. 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.
    7. Liang Qiao & Robert B Nachbar & Ioannis G Kevrekidis & Stanislav Y Shvartsman, 2007. "Bistability and Oscillations in the Huang-Ferrell Model of MAPK Signaling," PLOS Computational Biology, Public Library of Science, vol. 3(9), pages 1-8, September.
    8. Steven A Frank, 2013. "Evolution of Robustness and Cellular Stochasticity of Gene Expression," PLOS Biology, Public Library of Science, vol. 11(6), pages 1-3, June.
    9. Yelyzaveta Shlyakhtina & Bianca Bloechl & Maximiliano M. Portal, 2023. "BdLT-Seq as a barcode decay-based method to unravel lineage-linked transcriptome plasticity," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    10. Monica T. Dayao & Maigan Brusko & Clive Wasserfall & Ziv Bar-Joseph, 2022. "Membrane marker selection for segmenting single cell spatial proteomics data," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    11. Suzanne Gaudet & Sabrina L Spencer & William W Chen & Peter K Sorger, 2012. "Exploring the Contextual Sensitivity of Factors that Determine Cell-to-Cell Variability in Receptor-Mediated Apoptosis," PLOS Computational Biology, Public Library of Science, vol. 8(4), pages 1-15, April.
    12. Anissa Guillemin & Ronan Duchesne & Fabien Crauste & Sandrine Gonin-Giraud & Olivier Gandrillon, 2019. "Drugs modulating stochastic gene expression affect the erythroid differentiation process," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-19, November.

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