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Computer modelling of neural tube defects

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Abstract

Neurulation, the curling of the neuroepithelium to form the neural tube, is an essential component of the development of animal embryos. Defects of neural tube formation, which occur with an overall frequency of one in 500 human births, are the cause of severe and distressing congenital abnormalities. However, despite the fact that there is increasing information from animal experiments about the mechanisms which effect neural tube formation, much less is known about the fundamental causes of neural tube defects (NTD). The use of computer models provides one way of gaining clues about the ways in which neurulation may be compromised. Here we employ one computer model to examine the robustness of different cellular mechanisms which are thought to contribute to neurulation. The model, modified from that of Odell et al (Odell, G.M., Oster, G., Alberch, P. and Burnside, B., (1981)) mimics neurulation by laterally propagating a wave of apical contraction along an active zone within a ring of cells. We link the results to experimental evidence gained from studies of embryos in which neurulation has been perturbed. The results indicate that alteration of one of the properties of non-neural tissue can delay or inhibit neurulation, supporting the idea, gained from observation of embryos bearing genes which predispose to NTD, that the tissue underlying the neuroepithelium may contribute to the elevation of the neural folds. The results also show that reduction of the contractile properties of a small proportion of the neuroepithelial cell population may have a profound effect on overall tissue profiling. The results suggest that the elevation of the neural folds, and hence successful neurulation, may be vulnerable to relatively minor deficiencies in cell properties.

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Authors and Affiliations

  1. Department of Applied Mathematics and Theoretical Physics, University of Liverpool, L69 3BX, Liverpool, England

    David Dunnett & Anthony Goodbody

  2. School of Life Sciences, University of Liverpool, L69 3BX, Liverpool, England

    Martin Stanisstreet

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  1. David Dunnett
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  2. Anthony Goodbody
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  3. Martin Stanisstreet
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Dunnett, D., Goodbody, A. & Stanisstreet, M. Computer modelling of neural tube defects. Acta Biotheor 39, 63–79 (1991). https://doi.org/10.1007/BF00046408

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