IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0001693.html
   My bibliography  Save this article

Differential Dynamic Properties of Scleroderma Fibroblasts in Response to Perturbation of Environmental Stimuli

Author

Listed:
  • Momiao Xiong
  • Frank C Arnett
  • Xinjian Guo
  • Hao Xiong
  • Xiaodong Zhou

Abstract

Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-β pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-β pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.

Suggested Citation

  • Momiao Xiong & Frank C Arnett & Xinjian Guo & Hao Xiong & Xiaodong Zhou, 2008. "Differential Dynamic Properties of Scleroderma Fibroblasts in Response to Perturbation of Environmental Stimuli," PLOS ONE, Public Library of Science, vol. 3(2), pages 1-12, February.
  • Handle: RePEc:plo:pone00:0001693
    DOI: 10.1371/journal.pone.0001693
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0001693
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0001693&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0001693?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. Werhli Adriano V & Husmeier Dirk, 2007. "Reconstructing Gene Regulatory Networks with Bayesian Networks by Combining Expression Data with Multiple Sources of Prior Knowledge," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 6(1), pages 1-47, May.
    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. Villers Fanny & Schaeffer Brigitte & Bertin Caroline & Huet Sylvie, 2008. "Assessing the Validity Domains of Graphical Gaussian Models in Order to Infer Relationships among Components of Complex Biological Systems," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 7(2), pages 1-37, September.
    2. Ambroise Jérôme & Robert Annie & Macq Benoit & Gala Jean-Luc, 2012. "Transcriptional Network Inference from Functional Similarity and Expression Data: A Global Supervised Approach," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(1), pages 1-24, January.

    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:pone00:0001693. 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.