A systems approach to regulatory networks controlling N-assimilation

描述（由申请人提供）：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检验的假说，调控基序控制N-吸收/同化响应氮传感。正在测试的最重要的假设是，无机氮信号（硝酸盐）激活图案参与调节硝酸盐的吸收，还原和同化成Glu/Gln，用于生物合成反应。有机N产物（Glu/Gln）反过来激活控制合成用于N储存的Asn的基序，并抑制控制N吸收/同化的基序。由于氮同化的关键基因利用ATP和NADH，我们认为，相关的调控基序组件构成了一个“能量”的保护机制，激活氮同化时，无机氮是可用的，抑制/存储它时，有机氮水平高。使用突变体，转基因，和染色质IP，转录因子（TF）枢纽，TF-TF基序，和miRNA-TF基序调节基因在N-同化的作用进行了验证。这种更新建议使用这些经过验证的调控组件，表示哨兵，以推动新一轮的基因组规模的测试和基因特异性实验，以播种网络的增长，并创建一个时间依赖的动态视觉呈现模型，将详细说明N-信号传播通过N-同化调控网络的四个目标：1。验证TF和TF基序在调节氮吸收/同化响应无机氮或有机氮传感的功能的测试假设。2.使用经过验证的TF作为哨兵，以推动全基因组发现相互作用的伴侣。生成时程转录组数据，并使用诱导型转基因系统在系统范围内识别直接和间接靶标。3.测试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纳入这些模型。4.分析和可视化来自时间进程和转基因研究的基因组数据集，以生成核心调控机制的时变（动态）组合视图，无论是转录、转录后还是翻译后，以及它们对通过N同化调控网络传播N信号的影响。这一首次验证的植物代谢调控网络的发展将揭示：i）植物中调控网络的拓扑结构，包括与其他生物体比较的网络基序的作用，ii）控制N-利用效率的机制。这些目标的综合应允许建模，预测和测试如何扰动的“系统”可能被用来提高氮的使用效率，影响能源使用（化肥/生物燃料），硝酸盐污染的环境和人类营养。系统方法，识别哨兵基因，相关的邻居，条件表达分析和电路形成可以应用于任何物种与可用的基因组数据，并将使研究人员能够建模和操纵生物学中的广泛的调控电路与医学应用。 公共卫生相关性：我们的长期目标是结合联合收割机系统生物学，基因组学和遗传学的方法来模拟控制氮的吸收/同化反应的氮信号和相互作用的调节网络。我们的建议旨在使我们能够建模，预测和测试这些调控网络的扰动如何用于提高植物的氮利用效率，这将对能源使用产生重大影响，减少环境中的硝酸盐污染并改善人类营养。此外，由于我们拥有并将继续开发的系统生物学方法和工具可以应用于任何基因组数据可用的物种，这些研究将使研究人员能够模拟和操纵生物学中广泛的调控回路，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.