IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0009182.html
   My bibliography  Save this article

Reverse Engineering of Bacterial Chemotaxis Pathway via Frequency Domain Analysis

Author

Listed:
  • Junjie Luo
  • Jun Wang
  • Ting Martin Ma
  • Zhirong Sun

Abstract

Chemotaxis is defined as a behavior involving organisms sensing attractants or repellents and leading towards or away from them. Therefore, it is possible to reengineer chemotaxis network to control the movement of bacteria to our advantage. Understanding the design principles of chemotaxis pathway is a prerequisite and an important topic in synthetic biology. Here, we provide guidelines for chemotaxis pathway design by employing control theory and reverse engineering concept on pathway dynamic design. We first analyzed the mathematical models for two most important kinds of E. coli chemotaxis pathway—adaptive and non-adaptive pathways, and concluded that the control units of the pathway de facto function as a band-pass filter and a low-pass filter, respectively, by abstracting the frequency response properties of the pathways. The advantage of the band-pass filter is established, and we demonstrate how to tune the three key parameters of it—A (max amplification), ω1 (down cut-off frequency) and ω2 (up cut-off frequency) to optimize the chemotactic effect. Finally, we hypothesized a similar but simpler version of the dynamic pathway model based on the principles discovered and show that it leads to similar properties with native E. coli chemotactic behaviors. Our study provides an example of simulating and designing biological dynamics in silico and indicates how to make use of the native pathway's features in this process. Furthermore, the characteristics we discovered and tested through reverse engineering may help to understand the design principles of the pathway and promote the design of artificial chemotaxis pathways.

Suggested Citation

  • 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.
  • Handle: RePEc:plo:pone00:0009182
    DOI: 10.1371/journal.pone.0009182
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0009182
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0009182&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0009182?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. U. Alon & M. G. Surette & N. Barkai & S. Leibler, 1999. "Robustness in bacterial chemotaxis," Nature, Nature, vol. 397(6715), pages 168-171, January.
    2. Nicholas T. Ingolia & Jonathan S. Weissman, 2008. "Reverse engineering the cell," Nature, Nature, vol. 454(7208), pages 1061-1062, August.
    3. N. Barkai & S. Leibler, 1997. "Robustness in simple biochemical networks," Nature, Nature, vol. 387(6636), pages 913-917, June.
    4. Christopher V. Rao & Denise M. Wolf & Adam P. Arkin, 2002. "Control, exploitation and tolerance of intracellular noise," Nature, Nature, vol. 420(6912), pages 231-237, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jean Peccoud & Mark Isalan, 2012. "The PLOS ONE Synthetic Biology Collection: Six Years and Counting," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-7, August.

    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. 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.
    2. Önder Kartal & Oliver Ebenhöh, 2009. "Ground State Robustness as an Evolutionary Design Principle in Signaling Networks," PLOS ONE, Public Library of Science, vol. 4(12), pages 1-8, December.
    3. 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.
    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. 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.
    6. Deyan Luan & Michael Zai & Jeffrey D Varner, 2007. "Computationally Derived Points of Fragility of a Human Cascade Are Consistent with Current Therapeutic Strategies," PLOS Computational Biology, Public Library of Science, vol. 3(7), pages 1-13, July.
    7. Jasmin Fisher & Nir Piterman & Alex Hajnal & Thomas A Henzinger, 2007. "Predictive Modeling of Signaling Crosstalk during C. elegans Vulval Development," PLOS Computational Biology, Public Library of Science, vol. 3(5), pages 1-12, May.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Nikita Vladimirov & Linda Løvdok & Dirk Lebiedz & Victor Sourjik, 2008. "Dependence of Bacterial Chemotaxis on Gradient Shape and Adaptation Rate," PLOS Computational Biology, Public Library of Science, vol. 4(12), pages 1-17, December.
    14. Robert J Prill & Pablo A Iglesias & Andre Levchenko, 2005. "Dynamic Properties of Network Motifs Contribute to Biological Network Organization," PLOS Biology, Public Library of Science, vol. 3(11), pages 1-1, October.
    15. Kazunari Kaizu & Hisao Moriya & Hiroaki Kitano, 2010. "Fragilities Caused by Dosage Imbalance in Regulation of the Budding Yeast Cell Cycle," PLOS Genetics, Public Library of Science, vol. 6(4), pages 1-12, April.
    16. 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.
    17. 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.
    18. 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.
    19. Andrew C Ahn & Muneesh Tewari & Chi-Sang Poon & Russell S Phillips, 2006. "The Limits of Reductionism in Medicine: Could Systems Biology Offer an Alternative?," PLOS Medicine, Public Library of Science, vol. 3(6), pages 1-1, May.
    20. Silke Neumann & Linda Løvdok & Kajetan Bentele & Johannes Meisig & Ekkehard Ullner & Ferencz S Paldy & Victor Sourjik & Markus Kollmann, 2014. "Exponential Signaling Gain at the Receptor Level Enhances Signal-to-Noise Ratio in Bacterial Chemotaxis," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-11, April.

    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:pone00:0009182. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.