IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0165911.html
   My bibliography  Save this article

Systematic Design of a Metal Ion Biosensor: A Multi-Objective Optimization Approach

Author

Listed:
  • Chih-Yuan Hsu
  • Bor-Sen Chen

Abstract

With the recent industrial expansion, heavy metals and other pollutants have increasingly contaminated our living surroundings. Heavy metals, being non-degradable, tend to accumulate in the food chain, resulting in potentially damaging toxicity to organisms. Thus, techniques to detect metal ions have gradually begun to receive attention. Recent progress in research on synthetic biology offers an alternative means for metal ion detection via the help of promoter elements derived from microorganisms. To make the design easier, it is necessary to develop a systemic design method for evaluating and selecting adequate components to achieve a desired detection performance. A multi-objective (MO) H2/H∞ performance criterion is derived here for design specifications of a metal ion biosensor to achieve the H2 optimal matching of a desired input/output (I/O) response and simultaneous H∞ optimal filtering of intrinsic parameter fluctuations and external cellular noise. According to the two design specifications, a Takagi-Sugeno (T-S) fuzzy model is employed to interpolate several local linear stochastic systems to approximate the nonlinear stochastic metal ion biosensor system so that the multi-objective H2/H∞ design of the metal ion biosensor can be solved by an associated linear matrix inequality (LMI)-constrained multi-objective (MO) design problem. The analysis and design of a metal ion biosensor with optimal I/O response matching and optimal noise filtering ability then can be achieved by solving the multi-objective problem under a set of LMIs. Moreover, a multi-objective evolutionary algorithm (MOEA)-based library search method is employed to find adequate components from corresponding libraries to solve LMI-constrained MO H2/H∞ design problems. It is a useful tool for the design of metal ion biosensors, particularly regarding the tradeoffs between the design factors under consideration.

Suggested Citation

  • Chih-Yuan Hsu & Bor-Sen Chen, 2016. "Systematic Design of a Metal Ion Biosensor: A Multi-Objective Optimization Approach," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-16, November.
    • Handle: RePEc:plo:pone00:0165911
    DOI: 10.1371/journal.pone.0165911
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0165911
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0165911&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0165911?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. William J. Blake & Mads KÆrn & Charles R. Cantor & J. J. Collins, 2003. "Noise in eukaryotic gene expression," Nature, Nature, vol. 422(6932), pages 633-637, April.
    2. Drew Endy, 2005. "Foundations for engineering biology," Nature, Nature, vol. 438(7067), pages 449-453, November.
    3. 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.
    4. Jeff Hasty & David McMillen & J. J. Collins, 2002. "Engineered gene circuits," Nature, Nature, vol. 420(6912), pages 224-230, November.
    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. Tobias May & Lee Eccleston & Sabrina Herrmann & Hansjörg Hauser & Jorge Goncalves & Dagmar Wirth, 2008. "Bimodal and Hysteretic Expression in Mammalian Cells from a Synthetic Gene Circuit," PLOS ONE, Public Library of Science, vol. 3(6), pages 1-7, June.
    2. repec:plo:pone00:0026302 is not listed on IDEAS
    3. Blasi, Monica Francesca & Casorelli, Ida & Colosimo, Alfredo & Blasi, Francesco Simone & Bignami, Margherita & Giuliani, Alessandro, 2005. "A recursive network approach can identify constitutive regulatory circuits in gene expression data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 348(C), pages 349-370.
    4. Guo, Shengli & Xu, Ying & Wang, Chunni & Jin, Wuyin & Hobiny, Aatef & Ma, Jun, 2017. "Collective response, synapse coupling and field coupling in neuronal network," Chaos, Solitons & Fractals, Elsevier, vol. 105(C), pages 120-127.
    5. Simeon D. Castle & Michiel Stock & Thomas E. Gorochowski, 2024. "Engineering is evolution: a perspective on design processes to engineer biology," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    6. Valenti, D. & Tranchina, L. & Brai, M. & Caruso, A. & Cosentino, C. & Spagnolo, B., 2008. "Environmental metal pollution considered as noise: Effects on the spatial distribution of benthic foraminifera in two coastal marine areas of Sicily (Southern Italy)," Ecological Modelling, Elsevier, vol. 213(3), pages 449-462.
    7. repec:plo:pone00:0043231 is not listed on IDEAS
    8. Seyed Yahya Anvar & Allan Tucker & Veronica Vinciotti & Andrea Venema & Gert-Jan B van Ommen & Silvere M van der Maarel & Vered Raz & Peter A C ‘t Hoen, 2011. "Interspecies Translation of Disease Networks Increases Robustness and Predictive Accuracy," PLOS Computational Biology, Public Library of Science, vol. 7(11), pages 1-14, November.
    9. Michael W Klymkowsky & Kathy Garvin-Doxas, 2008. "Recognizing Student Misconceptions through Ed's Tools and the Biology Concept Inventory," PLOS Biology, Public Library of Science, vol. 6(1), pages 1-4, January.
    10. Diana Monteoliva & Christina B McCarthy & Luis Diambra, 2013. "Noise Minimisation in Gene Expression Switches," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-9, December.
    11. 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.
    12. Chen, Aimin & Tian, Tianhai & Chen, Yiren & Zhou, Tianshou, 2022. "Stochastic analysis of a complex gene-expression model," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    13. Adam F Prasanphanich & Douglas E White & Margaret A Gran & Melissa L Kemp, 2016. "Kinetic Modeling of ABCG2 Transporter Heterogeneity: A Quantitative, Single-Cell Analysis of the Side Population Assay," PLOS Computational Biology, Public Library of Science, vol. 12(11), pages 1-35, November.
    14. 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.
    15. Kanakov, Oleg & Chen, Shangbin & Zaikin, Alexey, 2024. "Learning by selective plasmid loss for intracellular synthetic classifiers," Chaos, Solitons & Fractals, Elsevier, vol. 179(C).
    16. Torgersen, Helge & Bogner, Alexander & Kastenhofer, Karen, 2013. "The Power of Framing in Technology Governance: The Case of Biotechnologies (ITA-manu:script 13-01)," ITA manu:scripts 13_01, Institute of Technology Assessment (ITA).
    17. David M Holloway & Alexander V Spirov, 2017. "Transcriptional bursting in Drosophila development: Stochastic dynamics of eve stripe 2 expression," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-24, April.
    18. repec:plo:pone00:0008432 is not listed on IDEAS
    19. Javier Macia & Romilde Manzoni & Núria Conde & Arturo Urrios & Eulàlia de Nadal & Ricard Solé & Francesc Posas, 2016. "Implementation of Complex Biological Logic Circuits Using Spatially Distributed Multicellular Consortia," PLOS Computational Biology, Public Library of Science, vol. 12(2), pages 1-24, February.
    20. Karl P. Gerhardt & Satyajit D. Rao & Evan J. Olson & Oleg A. Igoshin & Jeffrey J. Tabor, 2021. "Independent control of mean and noise by convolution of gene expression distributions," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    21. Enrico Orsi & Helena Schulz-Mirbach & Charles A. R. Cotton & Ari Satanowski & Henrik M. Petri & Susanne L. Arnold & Natalia Grabarczyk & Rutger Verbakel & Karsten S. Jensen & Stefano Donati & Nicole P, 2025. "Computation-aided designs enable developing auxotrophic metabolic sensors for wide-range glyoxylate and glycolate detection," Nature Communications, Nature, vol. 16(1), pages 1-16, December.
    22. Arjun Raj & Charles S Peskin & Daniel Tranchina & Diana Y Vargas & Sanjay Tyagi, 2006. "Stochastic mRNA Synthesis in Mammalian Cells," PLOS Biology, Public Library of Science, vol. 4(10), pages 1-13, September.
    23. Krishnan, Arun & Tomita, Masaru & Giuliani, Alessandro, 2008. "Evolution of gene regulatory networks: Robustness as an emergent property of evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(8), pages 2170-2186.

    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:pone00:0165911. 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.