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Simulation of live-cell imaging system reveals hidden uncertainties in cooperative binding measurements

Masaki Watabe, Satya N. V. Arjunan, Wei Xiang Chew, Kazunari Kaizu, and Koichi Takahashi
Phys. Rev. E 100, 010402(R) – Published 3 July 2019
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    Abstract

    We propose a computational method to quantitatively evaluate the systematic uncertainties that arise from undetectable sources in biological measurements using live-cell imaging techniques. We then demonstrate this method in measuring the biological cooperativity of molecular binding networks, in particular, ligand molecules binding to cell-surface receptor proteins. Our results show how the nonstatistical uncertainties lead to invalid identifications of the measured cooperativity. Through this computational scheme, the biological interpretation can be more objectively evaluated and understood under a specific experimental configuration of interest.

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    • Received 4 October 2018

    DOI:https://doi.org/10.1103/PhysRevE.100.010402

    Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

    Published by the American Physical Society

    Physics Subject Headings (PhySH)

    1. Techniques
    Medical imagingMonte Carlo methodsNetwork ModelsOptical techniquesSingle molecule techniquesStatistical methods
    Physics of Living SystemsInterdisciplinary Physics

    Authors & Affiliations

    Masaki Watabe1,*, Satya N. V. Arjunan1,2, Wei Xiang Chew1,3, Kazunari Kaizu1, and Koichi Takahashi1,4,5,†

    • 1Laboratory for Biologically Inspired Computing, RIKEN Center for Biosystems Dynamics Research, Suita, Osaka 565-0874, Japan
    • 2Lowy Cancer Research Centre, The University of New South Wales, Sydney, Australia
    • 3Physics Department, Faculty of Science, University of Malaya, Kuala Lumpur 50603, Malaysia
    • 4Institute for Advanced Biosciences, Keio University, Fujisawa, Kanagawa 252-8520, Japan
    • 5Department of Biosciences and Informatics, Keio University, Yokohama, Kanagawa 223-8522, Japan

    • *masaki@riken.jp
    • †ktakahashi@riken.jp

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    Vol. 100, Iss. 1 — July 2019

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    • Figure 1
      Figure 1

      Summary of the evaluation results. The reconstructed Hill coefficients are compared with the ground-true Hill coefficients. The top row shows the molecular networks: the simple ligand-receptor binding and the dimer formations of the ligand-induced receptors. The Y-shaped object and black solid circle represent the receptor and the ligand, respectively. Y-bar objects represent an intermediate state of the receptor. The equilibrium binding curves and the Scatchard plots are shown in the middle rows. Red and black lines represent the reconstructed and the ground-true data points. Blue solid lines indicate the best-fit curves. The best-fit values and statistical uncertainties (1σ) of the Hill coefficients are shown in the bottom row. If the Hill coefficient is less than unity (n<1), then the receptor system exhibits negative cooperativity. If n>1, then cooperativity is positive. There is no cooperativity if n=1.

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    • Figure 2
      Figure 2

      More properties of dimer formation II. (a) The restoration efficiency of the area density with respect to the concentration range of 1.0pM to 4.0nM. The black dashed line represents 80% efficiency. (b) Fractional occupancy of false spots (or defects) with respect to the concentration range. The red dashed line represents 15% occupancy. (c) Time-course data for 0.300nM ligand input. The reconstructed data are shown by red crosses. Solid and dashed pink lines represent the ground-true equilibrium state and 80% of the true equilibrium state. The ground-true response of the binding state is shown with black solid lines. The 80% restoration of the true response is shown by the dashed black line. (d) Time-course data for 0.030nM ligand input.

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    • Figure 3
      Figure 3

      The fitting results of dimer formation II. (a) The equilibrium binding curve. (b) Scatchard plot. Red and black lines represent the reconstructed and the ground-true data points. Blue solid and dashed lines indicate the best-fit curves and the curves shifted ±1σ from the best fits, respectively. (c) Confidence levels of data fitting in the full concentration range. (d) Confidence levels of data fitting in the range of high concentration. Pink and black stars represent the ground truth and the best fit, respectively. Black contours around the best fit are allowed at 68%, 95%, and 99% confidence levels.

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