Principles of Robust Developmental Patterning

描述(申请人提供)：形态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。这种模式的形成是许多发育形态发生的基础，并以其准确性和重复性而闻名。事实上，很大一部分人类出生缺陷是模式形成过程中相对较小的干扰的直接结果。在大多数情况下，形态原梯度的形成和细胞对它们的反应，受到相互作用的转录因子、受体和辅助受体网络的复杂调控。这样的调控很可能是为了使空间模式对生物相关的扰动(遗传变异性、环境不确定性、内在随机性等)具有健壮性。聚焦于果蝇翅膀成像盘前后轴图案的BMP梯度，我们将通过将实验生物学与数学建模和分析紧密结合的协作方法，探索和阐明稳健图案的机制基础。将继续进行三个相关的研究领域：首先，我们将量化细胞间的可变性，这种可变性通常会阻碍组织响应浅形态梯度而产生尖锐的基因表达边缘的能力，并研究这种“空间噪声”在控制翼静脉模式的基因调控网络中的不同阶段是如何变化的。其次，我们将寻求最近的证据表明，图案化不仅对梯度中的形态原水平敏感，而且对局部梯度斜率也很敏感。作为这项工作的一部分，我们将测试斜率检测是由脂肪信号通路介导的假设，并服务于减少空间噪声的目的。第三，我们将扩展以前的形态梯度形成和解释的数学模型，以阐明作为针对个别类型扰动实现稳健性的策略的调控机制之间的权衡。特别是，这样的模型将纳入到目前为止还没有进行过数学分析的机制和性能目标。总的来说，这项工作的目标是提供一个更连贯的理解，即如何利用对空间动态生物系统的复杂监管来实现在各种条件下的稳健性能。最终，这些结果应该为导致结构性出生缺陷和其他发育异常的病理过程提供洞察力。) 与公共健康相关：如果不是因为胚胎和胎儿发育的非凡准确性和可靠性，出生缺陷会比现在普遍得多。为了了解可靠性是如何实现的，我们将重点放在果蝇翅膀中的图案形成过程上，关于这一过程有大量的机械知识。通过展示复杂的监管电路如何实现稳健的模式形成，我们将获得对开发如何如此频繁地成功、为什么偶尔会失败以及如何确定此类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.