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Robustness in simple biochemical networks

Author

Listed:
  • N. Barkai

    (Princeton University)

  • S. Leibler

    (Princeton University)

Abstract

Cells use complex networks of interacting molecular components to transfer and process information. These “computational devices of living cells”1 are responsible for many important cellular processes, including cell-cycle regulation and signal transduction. Here we address the issue of the sensitivity of the networks to variations in their biochemical parameters. We propose a mechanism for robust adaptation in simple signal transduction networks. We show that this mechanism applies in particular to bacterial chemotaxis2,3,4,5,6,7. This is demonstrated within a quantitative model which explains, in a unified way, many aspects of chemotaxis, including proper responses to chemical gradients8,9,10,11,12. The adaptation property10,13,14,15,16 is a consequence of the network's connectivity and does not require the ‘fine-tuning’ of parameters. We argue that the key properties of biochemical networks should be robust in order to ensure their proper functioning.

Suggested Citation

  • N. Barkai & S. Leibler, 1997. "Robustness in simple biochemical networks," Nature, Nature, vol. 387(6636), pages 913-917, June.
    • Handle: RePEc:nat:nature:v:387:y:1997:i:6636:d:10.1038_43199
    DOI: 10.1038/43199
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    Cited by:

    1. Diana Clausznitzer & Olga Oleksiuk & Linda Løvdok & Victor Sourjik & Robert G Endres, 2010. "Chemotactic Response and Adaptation Dynamics in Escherichia coli," PLOS Computational Biology, Public Library of Science, vol. 6(5), pages 1-11, May.
    2. Robert Planqué & Josephus Hulshof & Bas Teusink & Johannes C Hendriks & Frank J Bruggeman, 2018. "Maintaining maximal metabolic flux by gene expression control," PLOS Computational Biology, Public Library of Science, vol. 14(9), pages 1-20, September.
    3. Robert M Cooper & Ned S Wingreen & Edward C Cox, 2012. "An Excitable Cortex and Memory Model Successfully Predicts New Pseudopod Dynamics," PLOS ONE, Public Library of Science, vol. 7(3), pages 1-12, March.
    4. Jinlong Yuan & Lei Wang & Xu Zhang & Enmin Feng & Hongchao Yin & Zhilong Xiu, 2015. "Parameter identification for a nonlinear enzyme-catalytic dynamic system with time-delays," Journal of Global Optimization, Springer, vol. 62(4), pages 791-810, August.
    5. 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.
    6. Jae Kyoung Kim & Trachette L Jackson, 2013. "Mechanisms That Enhance Sustainability of p53 Pulses," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-11, June.
    7. Robyn P. Araujo & Lance A. Liotta, 2023. "Universal structures for adaptation in biochemical reaction networks," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    8. Guillermo Rodrigo & Santiago F Elena, 2011. "Structural Discrimination of Robustness in Transcriptional Feedforward Loops for Pattern Formation," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-7, February.
    9. Zeina Shreif & Vipul Periwal, 2014. "A Network Characteristic That Correlates Environmental and Genetic Robustness," PLOS Computational Biology, Public Library of Science, vol. 10(2), pages 1-23, February.
    10. Dong, Gaogao & Tian, Lixin & Du, Ruijin & Fu, Min & Stanley, H. Eugene, 2014. "Analysis of percolation behaviors of clustered networks with partial support–dependence relations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 370-378.
    11. Junjie Luo & Jun Wang & Ting Martin Ma & Zhirong Sun, 2010. "Reverse Engineering of Bacterial Chemotaxis Pathway via Frequency Domain Analysis," PLOS ONE, Public Library of Science, vol. 5(3), pages 1-8, March.
    12. Kirstin Meyer & Nicholas C. Lammers & Lukasz J. Bugaj & Hernan G. Garcia & Orion D. Weiner, 2023. "Optogenetic control of YAP reveals a dynamic communication code for stem cell fate and proliferation," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    13. Jalili, Mahdi, 2011. "Error and attack tolerance of small-worldness in complex networks," Journal of Informetrics, Elsevier, vol. 5(3), pages 422-430.
    14. Miri Adler & Avi Mayo & Uri Alon, 2014. "Logarithmic and Power Law Input-Output Relations in Sensory Systems with Fold-Change Detection," PLOS Computational Biology, Public Library of Science, vol. 10(8), pages 1-14, August.
    15. Niklas Korsbo & Henrik Jönsson, 2020. "It’s about time: Analysing simplifying assumptions for modelling multi-step pathways in systems biology," PLOS Computational Biology, Public Library of Science, vol. 16(6), pages 1-29, June.
    16. Yuan, Jinlong & Zhu, Xi & Zhang, Xu & Yin, Hongchao & Feng, Enmin & Xiu, Zhilong, 2014. "Robust identification of enzymatic nonlinear dynamical systems for 1,3-propanediol transport mechanisms in microbial batch culture," Applied Mathematics and Computation, Elsevier, vol. 232(C), pages 150-163.
    17. 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.
    18. Jonathan R Karr & Alex H Williams & Jeremy D Zucker & Andreas Raue & Bernhard Steiert & Jens Timmer & Clemens Kreutz & DREAM8 Parameter Estimation Challenge Consortium & Simon Wilkinson & Brandon A Al, 2015. "Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models," PLOS Computational Biology, Public Library of Science, vol. 11(5), pages 1-21, May.
    19. Jiang, Xiong-Fei & Xiong, Long & Bai, Ling & Lin, Jie & Zhang, Jing-Feng & Yan, Kun & Zhu, Jia-Zhen & Zheng, Bo & Zheng, Jian-Jun, 2022. "Structure and dynamics of human complication-disease network," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    20. Burton W Andrews & Tau-Mu Yi & Pablo A Iglesias, 2006. "Optimal Noise Filtering in the Chemotactic Response of Escherichia coli," PLOS Computational Biology, Public Library of Science, vol. 2(11), pages 1-12, November.
    21. Diana Clausznitzer & Gabriele Micali & Silke Neumann & Victor Sourjik & Robert G Endres, 2014. "Predicting Chemical Environments of Bacteria from Receptor Signaling," PLOS Computational Biology, Public Library of Science, vol. 10(10), pages 1-14, October.

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