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素吸收/同化的调控网络。整合基因组数据的系统生物学方法已经为控制氮吸收/同化的调控基序产生了可检验的假说，以响应氮传感。正在测试的压倒一切的假设是，无机氮信号(硝酸盐)激活了参与调节硝酸盐吸收、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)依次激活控制合成用于氮素储存的ASN的基序，抑制控制氮素吸收/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组成一个“能量”守恒机制，当无机氮可用时激活N同化，当有机N水平较高时抑制/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)中心、TF-TF基序和miRNA-TFS基序在N同化过程中的调控作用。这次更新建议使用这些经过验证的调控元件，表示为哨兵，以推动新一轮的基因组规模的测试和基因特异性的实验，以种子的网络的生长，并创建一个依赖于时间的动态视觉呈现模型，将详细说明N信号通过N同化调控网络的流动在四个目标：1.测试假设验证的TF和TF基序在调节N吸收/同化响应无机N或有机N的感知。2.使用有效的转录因子作为哨兵，在全基因组范围内发现相互作用的伙伴。生成时间进程转录组数据，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，并生成代谢组数据以并入这些模型。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，以及它们在通过N-同化调控网络传播N-信号方面的作用。第一个被证实的代谢调控网络在植物中的生长将揭示：i)植物中调控网络的拓扑结构，包括网络基序的作用，以便与其他生物进行比较；ii)控制氮素利用效率的机制。这些目标的综合应可用于建模、预测和测试如何利用“系统”的扰动来提高氮素利用效率，从而影响能源使用(化肥/生物燃料)、环境中的硝酸盐污染和人类营养。系统方法、识别前哨基因、相关邻居、条件表达分析和电路形成可以应用于任何拥有现有基因组数据的物种，并将使研究人员能够建模和操纵生物学中广泛的调控电路，并将其应用于医学。 公共卫生相关性：我们的长期目标是结合系统生物学、基因组学和遗传学方法，对控制氮吸收/同化的调控网络进行建模，以响应氮信号和相互作用。我们的建议旨在使我们能够模拟、预测和测试这些调控网络的扰动如何被用来提高植物的氮素利用效率，这将对能源利用产生重大影响，减少环境中的硝酸盐污染，并改善人类营养。此外，随着系统生物学的临近，我们已经并将继续开发的工具可以应用于任何可获得基因组数据的物种，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.