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对植物中控制氮（N）吸收/同化的调控网络进行动态建模。整合基因组数据的系统生物学方法已经为控制氮吸收/同化响应氮传感的调节基序产生了可检验的假设。正在测试的最重要的假设是无机氮信号（硝酸盐）激活参与调节硝酸盐吸收、还原和同化为用于生物合成反应的 Glu/Gln 的基序。有机氮产物（Glu/Gln）反过来激活控制为氮储存而合成的天冬氨酸的基序，并抑制控制氮吸收/同化的基序。由于氮同化的关键基因利用 ATP 和 NADH，我们假设相关的调节基序成分构成了一种“能量”守恒机制，当无机氮可用时激活氮同化，并在有机氮水平较高时抑制/储存它。使用突变体、转基因和染色质 IP，验证了转录因子 (TF) 中心、TF-TF 基序和 miRNA-TF 基序调节基因在 N 同化中的作用。本次更新提议使用这些经过验证的调节组件（称为哨兵）来推动新一轮的基因组规模测试和基因特异性实验，以促进网络的增长，并创建一个依赖于时间的动态视觉呈现模型，该模型将详细说明 N 信号通过 N 同化调节网络传播的流程，有四个目标： 1. 测试经过验证的 TF 和 TF 基序在调节 N 吸收/同化以响应无机 N 或有机氮传感。 2. 使用经过验证的 TF 作为哨兵，促进相互作用伙伴的全基因组发现。生成时程转录组数据并使用诱导转基因系统来识别全系统的直接和间接目标。 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，以生成核心调节机制（无论是转录、转录后还是翻译后）的时变（动态）组合视图，及其对通过 N 同化调节网络传播 N 信号的影响。第一个经过验证的植物代谢调节网络的生长将揭示：i）植物调节网络的拓扑结构，包括与其他生物体比较的网络基序的作用，ii）控制氮利用效率的机制。这些目标的综合应允许建模、预测和测试如何利用“系统”的扰动来提高氮利用效率，这会影响能源使用（肥料/生物燃料）、环境的硝酸盐污染和人类营养。该系统方法、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具有可用基因组数据的任何物种，并使研究人员能够建模和操作生物学中广泛的调节电路并应用于医学。 公共健康相关性：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来模拟控制氮吸收/同化以响应氮信号和相互作用的调控网络。我们的提案旨在使我们能够模拟、预测和测试如何利用这些调控网络的扰动来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可获得基因组数据的物种，这些研究将使研究人员能够建模和操纵生物学中广泛的调节回路，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.