Principles of Robust Developmental Patterning

描述（由申请人提供）：形态发生梯度被广泛用于为细胞提供创建基因表达的空间模式所需的位置信息。这种模式的形成是大量发育形态发生的基础，并以其准确性和可重复性而闻名。事实上，很大一部分人类出生缺陷是模式形成中相对较小的破坏的直接结果。在大多数情况下，形态发生梯度的形成以及细胞对它们的反应受到相互作用的转录因子、受体和共受体网络的复杂调控。很可能，这种调节进化到使空间模式强大的生物相关的扰动（遗传变异性，环境的不确定性，内在的随机性，等等）。专注于BMP梯度图案的前后轴的果蝇翅膀成虫盘，我们将探索和阐明强大的图案化的机制基础，通过合作的方法，紧密交织的实验生物学与数学建模和分析。三个相关领域的调查将被追求：首先，我们将量化的细胞到细胞的变异性，通常阻碍组织的能力，以产生尖锐的边界的基因表达在响应浅形态梯度，并调查如何在不同阶段的基因调控网络，控制翅静脉图案的“空间噪声”的变化。其次，我们将追求最近的证据表明，图案是敏感的，不仅在梯度形态，但当地的梯度斜率。作为这项工作的一部分，我们将测试的假设，斜率检测是由脂肪信号通路介导的，并服务于减少空间噪声的目的。第三，我们将扩展以前的数学模型的形态梯度的形成和解释，以阐明监管机制之间出现的权衡，作为策略，实现相对于个别类型的扰动的鲁棒性。特别是，这样的模型将纳入机制和性能目标，迄今尚未进行数学分析。从广义上讲，这项工作的目标是提供一个更连贯的理解，如何利用复杂的调节空间动态生物系统，以实现强大的性能在各种条件下。最终，这些结果将为导致结构性出生缺陷和其他发育异常的病理过程提供见解。) 公共卫生相关性：如果不是因为胚胎和胎儿发育的显著准确性和可靠性，出生缺陷将比现在更常见。为了了解可靠性是如何实现的，我们专注于果蝇翅膀中图案形成的过程，关于这一点有大量的机械知识。通过展示复杂的调节回路如何实现强大的模式形成，我们将获得关于发展如何如此频繁地成功，为什么偶尔会失败以及如何识别这种失败的原因的一般见解。

DESCRIPTION (provided by applicant): Morphogen gradients are widely used to provide cells with the positional information needed to create spatial patterns of gene expression. Such pattern formation underlies a great deal of developmental morphogenesis, and is notable for its accuracy and reproducibility. Indeed, a large fraction of human birth defects are the direct result of relatively small disruptions in pattern formation. In most cases, the formation of morphogen gradients, and the responses of cells to them, is subject to complex regulation by networks of interacting transcription factors, receptors, and co-receptors. It is likely that such regulation evolved to make spatial patterning robust to biologically relevant perturbations (genetic variability, environmental uncertainty, intrinsic stochasticity, etc.). Focusing on the BMP gradient that patterns the antero-posterior axis of the Drosophila wing imaginal disc, we will explore and elucidate the mechanistic basis for robust patterning, through a collaborative approach that closely intertwines experimental biology with mathematical modeling and analysis. Three related areas of investigation will be pursued: First, we will quantify the cell-to-cell variability that normally impedes the ability of tissues to generate sharp borders of gene expression in response to shallow morphogen gradients, and investigate how such "spatial noise" changes at different stages within the gene regulatory network that controls wing vein patterning. Second, we will pursue recent evidence suggesting that patterning is sensitive not only to levels of morphogen in a gradient but to the local gradient slope as well. As part of this work we will test the hypothesis that slope detection is mediated by the Fat signaling pathway, and serves the purpose of reducing spatial noise. Third, we will extend previous mathematical models of morphogen gradient formation and interpretation in order to elucidate the tradeoffs that arise among regulatory mechanisms that serve as strategies for achieving robustness with respect to individual types of perturbations. In particular, such models will incorporate mechanisms and performance objectives that have not heretofore been analyzed mathematically. Broadly, the goal of this work is to provide a more coherent understanding of how complex regulation of spatially dynamic biological systems is utilized to achieve robust performance under a wide variety of conditions. Ultimately, the results should provide insights into the pathological processes that lead to structural birth defects and other developmental abnormalities. ) PUBLIC HEALTH RELEVANCE: Were it not for the remarkable accuracy and reliability of embryonic and fetal development, birth defects would be far more common than they are. To understand how reliability is achieved, we are focusing on the process of pattern formation in the fruit fly wing, about which there is a great deal of mechanistic knowledge. By showing how complex regulatory circuitry enables robust pattern formation, we will gain general insights into how development succeeds so often, why it occasionally fails, and how the causes of such failures might be identified.