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Organism-scale modeling of early Drosophila patterning via bone morphogenetic proteins.

机译:通过骨形态发生蛋白的果蝇早期模式的生物规模建模。

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Advances in image acquisition and informatics technology have led to organism-scale spatiotemporal atlases of gene expression and protein distributions. To maximize the utility of this information for the study of developmental processes, a new generation of mathematical models is needed for discovery and hypothesis testing. Here, we develop a data-driven, geometrically accurate model of early Drosophila embryonic bone morphogenetic protein (BMP)-mediated patterning. We tested nine different mechanisms for signal transduction with feedback, eight combinations of geometry and gene expression prepatterns, and two scale-invariance mechanisms for their ability to reproduce proper BMP signaling output in wild-type and mutant embryos. We found that a model based on positive feedback of a secreted BMP-binding protein, coupled with the experimentally measured embryo geometry, provides the best agreement with population mean image data. Our results demonstrate that using bioimages to build and optimize a three-dimensional model provides significant insights into mechanisms that guide tissue patterning.
机译:图像采集和信息技术的进步导致了基因表达和蛋白质分布的生物体时空图集。为了最大限度地利用这些信息来研究发展过程,需要新一代的数学模型进行发现和假设检验。在这里,我们开发的数据驱动,早期果蝇胚胎骨形态发生蛋白(BMP)介导的图案的几何精确模型。我们测试了具有反馈的信号传导的九种不同机制,几何形状和基因表达模式的八种组合,以及两种尺度不变机制,以在野生型和突变型胚胎中复制适当的BMP信号输出。我们发现,基于分泌的BMP结合蛋白的正反馈的模型,再加上实验测量的胚胎几何形状,可提供与群体平均图像数据的最佳一致性。我们的结果表明,使用生物图像来构建和优化三维模型可为指导组织图案形成的机制提供重要见解。

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