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Central dogma at the single-molecule level in living cells

Author

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  • Gene-Wei Li

    (Harvard University
    Present address: Department of Cellular and Molecular Pharmacology, University of California, San Francisco, California 94158, USA.)

  • X. Sunney Xie

    (Harvard University)

Abstract

Gene expression originates from individual DNA molecules within living cells. Like many single-molecule processes, gene expression and regulation are stochastic, that is, sporadic in time. This leads to heterogeneity in the messenger-RNA and protein copy numbers in a population of cells with identical genomes. With advanced single-cell fluorescence microscopy, it is now possible to quantify transcriptomes and proteomes with single-molecule sensitivity. Dynamic processes such as transcription-factor binding, transcription and translation can be monitored in real time, providing quantitative descriptions of the central dogma of molecular biology and the demonstration that a stochastic single-molecule event can determine the phenotype of a cell.

Suggested Citation

  • Gene-Wei Li & X. Sunney Xie, 2011. "Central dogma at the single-molecule level in living cells," Nature, Nature, vol. 475(7356), pages 308-315, July.
    • Handle: RePEc:nat:nature:v:475:y:2011:i:7356:d:10.1038_nature10315
    DOI: 10.1038/nature10315
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    Cited by:

    1. Anthony Delaune & Armelle Cabin-Flaman & Guillaume Legent & David Gibouin & Caroline Smet-Nocca & Fabrice Lefebvre & Arndt Benecke & Marc Vasse & Camille Ripoll, 2013. "50nm-Scale Localization of Single Unmodified, Isotopically Enriched, Proteins in Cells," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-12, February.
    2. 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.
    3. Hao Ge & Pingping Wu & Hong Qian & Xiaoliang Sunney Xie, 2018. "Relatively slow stochastic gene-state switching in the presence of positive feedback significantly broadens the region of bimodality through stabilizing the uninduced phenotypic state," PLOS Computational Biology, Public Library of Science, vol. 14(3), pages 1-24, March.
    4. Femke L Groeneweg & Martin E van Royen & Susanne Fenz & Veer I P Keizer & Bart Geverts & Jurrien Prins & E Ron de Kloet & Adriaan B Houtsmuller & Thomas S Schmidt & Marcel J M Schaaf, 2014. "Quantitation of Glucocorticoid Receptor DNA-Binding Dynamics by Single-Molecule Microscopy and FRAP," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-12, March.
    5. Marc S Sherman & Barak A Cohen, 2014. "A Computational Framework for Analyzing Stochasticity in Gene Expression," PLOS Computational Biology, Public Library of Science, vol. 10(5), pages 1-13, May.

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