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    Bioinformatics, Computational and Systems Biology

    (B-41) Python Agent-Based Modeling to Investigate Neural Rosette Formation

    Thursday, October 12, 2023
    9:30 AM – 10:30 AM PDT
    Location: Exhibit Hall - Row B - Poster # 41

      Co-Author(s)

    • Andre L. Jin

      Graduate Student
      Georgia Institute of Technology
      Atlanta, Georgia, United States

      • Primary Investigator(s)

    • Melissa L. Kemp

      Professor
      Georgia Institute of Technology
      Atlanta, Georgia, United States

      • Presenting Author(s)

    • SK

      Siya Kannan

      Undergraduate Student
      Georgia Institute of Technology
      Watkinsville

    Introduction:: The mechanisms underlying human-induced pluripotent stem cell differentiation are a promising area of study in regenerative medicine. One such mechanism in neural stem cell differentiation is neural rosette formation, a fundamental precursor to potent regenerative processes such as neural tube development. However, much of the current efforts have focused on in vitro modeling that do not adequately consider the spatial and temporal aspects associated with neural cytoarchitecture and rosette formation. Specifically, the role of inter-kinetic nuclear migration (INM) in rosette formation, in which cell morphology is dramatically altered during the nuclear retraction from basal processes during neuronal cell mitosis, has not been investigated with agent-based tools that capture cell division, adhesion, and chemotactic motility.

    Materials and Methods::

    Here, we employ a custom Python agent-based modeling to demonstrate how discrete agents, representing individual neural stem cells, interact spatially to self-organize into neural rosette patterns. We use quantitative radial organization patterns and cell polarity models to develop context-dependent agent rules in order to simulate neural rosette formation in-vivo. Each agent is represented as an elliptical object with the ability to orient its axes according to neighboring cell properties. Although nuclei are not explicitly modeled, rules dictating the shift in major and minor ellipsoid axes during cell division recapitulate the cyclic elongation and rounding of the cellular agents associated with INM.



    Results, Conclusions, and Discussions::

    Our model is designed to investigate how the spatial location of an agent predicts radial organization into neural rosettes. Literature-derived data characterizing the velocity and angular orientation of pluripotent cells during the initial stages of morphogenesis into multicellular rosettes are leveraged in evaluating the computational outcomes and informing agent rules.  


    The increasing use of neural rosettes as in vitro platforms for toxicological screening motivates computational exploration of mechanisms underlying coordination and disruption of morphogenesis. Although INM has been proposed to drive neural rosette formation by facilitating apical constriction, our simulations are designed to test the hierarchy of additional biophysical contributors to this multicellular process.


     



    Acknowledgements (Optional): :

    References (Optional): :

    Harding, Molly et al. The roles and regulation of multicellular rosette structures during morphogenesis. The Company of Biologists 2-14


    Hana Hříbková, et al. Calcium signaling mediated five types of cell morphological changes to form neural rosettes. Journal of Cell Science. Volume 131, Issue 3. 12 February 2018.


    Ziv, Omer et al. Quantitative Live Imaging of Human Embryonic Stem Cell Derived Neural Rosettes Reveals Structure-FunctionDynamics Coupled to Cortical Development. PLOS Computational Biology.  16 October 2015