A systems approach to regulatory networks controlling N-assimilation

描述（申请人提供）：该项目的长期目标是动态模拟控制植物氮(N)吸收/同化的调节网络。整合基因组数据的系统生物学方法已经产生了可测试的假设，即在响应氮传感的过程中控制氮吸收/同化的调节基序。最重要的假设是，无机氮信号（硝酸盐）激活了参与调节硝酸盐摄取、还原和同化为Glu/Gln的基序，用于生物合成反应。有机氮产物（Glu/Gln）反过来激活控制氮储存合成的Asn基序，并抑制控制氮吸收/同化的基序。由于n同化的关键基因利用ATP和NADH，我们假设相关的调控基序成分构成了一种“能量”守恒机制，当无机氮可用时激活n同化，当有机氮水平高时抑制/储存n同化。利用突变体、转基因和染色质ip，验证了转录因子（TF）枢纽、TF-TF基序和mirna -TF基序调节基因在n同化中的作用。这一更新建议使用这些经过验证的调控成分，即哨兵，来推动新一轮的基因组规模测试和基因特异性实验，为网络的增长播种，并创建一个时间依赖的动态视觉呈现模型，该模型将详细描述通过n同化调控网络的n信号传播流，有四个目标：1。验证已验证的tf和tf基序在响应无机氮或有机氮感知时调节n吸收/同化的功能假设。2. 使用经过验证的tf作为哨兵，促进全基因组发现相互作用的伙伴。生成时间过程转录组数据，并使用可诱导的转基因系统来识别系统范围内的直接和间接目标。3. 验证当前网络模型预测的转录后和翻译后机制的假设，并生成代谢组学数据，以便纳入这些模型。4. 分析和可视化来自时间过程和转基因研究的基因组数据集，以生成一个时变（动态）的核心调控机制组合视图，无论是转录，转录后或翻译后，以及它们对通过n同化调控网络传播n信号的影响。这一首次在植物中得到验证的代谢调节网络的发展将揭示：i)植物中调节网络的拓扑结构，包括与其他生物比较的网络基序的作用；ii)控制氮利用效率的机制。这些目标的综合应该允许建模、预测和测试如何利用“系统”的扰动来提高氮的使用效率，从而影响能源使用（肥料/生物燃料）、环境的硝酸盐污染和人类营养。系统方法、前哨基因的识别、相关邻居、条件表达分析和电路形成可以应用于任何具有可用基因组数据的物种，并将使研究人员能够模拟和操纵生物学中广泛的调控电路，并将其应用于医学。

DESCRIPTION (provided by applicant): The long-term goal of this project is to dynamically model the regulatory networks controlling nitrogen (N) uptake/assimilation in plants. The systems biology approaches that integrate genomic data have generated testable hypotheses for regulatory motifs controlling N-uptake/assimilation in response to nitrogen sensing. The overriding hypothesis being tested is that inorganic-N signals (nitrate) activate motifs involved in regulating nitrate uptake, reduction and assimilation into Glu/Gln, used for biosynthetic reactions. The organic-N products (Glu/Gln) in turn activate motifs controlling Asn synthesized for N-storage, and repress ones controlling N- uptake/assimilation. As the key genes for N-assimilation utilize ATP and NADH, we posit that the associated regulatory motif components constitute an "energy" conservation mechanism, activating N-assimilation when inorganic-N is available, and repressing/storing it when organic-N levels are high. Using mutants, transgenics, and chromatin-IP, roles for transcription factor (TF) hubs, TF-TF motifs, and miRNA-TFs motifs regulating genes in N-assimilation were validated. This renewal proposes to use these validated regulatory components, denoted sentinels, to fuel a new round of genome-scale testing and gene-specific experimentation to seed the growth of the network and to create a time-dependent dynamic visual presentation model that will detail the flow of N-signal propagation through the N-assimilatory regulatory network in four aims: 1. Test hypotheses for the function of validated TFs and TF-motifs in regulating N-uptake/assimilation in response to inorganic-N or organic-N sensing. 2. Use validated TFs as sentinels to fuel genome-wide discovery of interacting partners. Generate time-course transcriptome data and use an inducible transgenic system to identify both direct and indirect targets system-wide. 3. Test hypotheses for post-transcriptional and post-translational mechanisms predicted by the current network models and generate metabolomic data for incorporation into these models. 4. Analyze and visualize the genomic datasets from time-course and transgenic studies, to generate a time- varying (dynamic) combinatorial view of the core regulatory mechanisms, whether transcriptional, post- transcriptional or post-translational, and their effect on propagating the N-signal through the N-assimilation regulatory network. The growth of this first validated metabolic regulatory network in plants will uncover: i) the topology of regulatory networks in plants including the role of network motifs for comparison to other organisms, ii) mechanisms that control N-use efficiency. The synthesis of these aims should allow for modeling, predicting and testing how perturbations of the "system" may be used to enhance N-use efficiency, which impacts energy-use (fertilizers/biofuels), nitrate contamination of the environment and human nutrition. The systems approach, identification of sentinel genes, related neighbors, conditional expression analysis, and circuit formation can be applied to any species with available genome data and will enable researchers to model and manipulate a broad spectrum of regulatory circuits in biology with applications to medicine. PUBLIC HEALTH RELEVANCE: Our long-term goal is to combine systems biology, genomic and genetic approaches to model the regulatory networks controlling nitrogen-uptake/assimilation in response to nitrogen signals and interactions. Our proposal aims to allow us to model, predict and test how perturbations of these regulatory networks may be used to enhance N-use efficiency in plants, which will have a significant impact on energy-use, reduce nitrate contamination of the environment and improve human nutrition. Moreover, as the systems biology approaches and tools we have and will continue to develop can be applied to any species for which genome data is available, these studies will enable researchers to model and manipulate a broad spectrum of regulatory circuits in biology with applications to medicine.