Collaborative Research: PlantSynBio: Identification and Design of Transcriptional Activation Domains Across Plant Species

每一种植物都是从一粒种子开始的，只有一个细胞和一个基因组。为了让植物生长，细胞必须分裂，并通过打开不同的基因变成不同种类的细胞。叶细胞启动叶基因;根细胞启动根基因。这个开启和关闭基因的过程需要称为转录因子的特殊蛋白质。转录因子还允许植物打开或关闭基因，以应对干旱或害虫和病原体等压力。转录因子使用称为“激活域”的专门区域启动基因。这个项目的第一部分将使用我们开发的技术来确定一个广泛研究的植物物种拟南芥的所有转录因子的激活域。我们收集的数据将为我们的计算模型提供动力，用于预测其他植物中的激活域。该项目的最后一部分将建立合成转录因子，可用于其他植物的基因调控工程。这项研究将为植物生物学家和植物育种家创造有用和强大的工具。三个研究团队之间的这种合作为本科生，研究生和博士后研究员创造了独特的跨学科培训环境。我们的团队致力于建立一个支持性的环境，促进公平，多样性和包容性。这三位PI来自传统上被排除在科学之外的背景。在植物中，转录因子控制着发育、生长和应激反应的基因调控程序。转录因子具有两种功能：1）直接与DNA结合结构域（DBD）或通过含有DBD的蛋白质伴侣结合基因组中的DNA序列，以及2）募集转录机器。DBD已经被很好地表征，并且可以直接从氨基酸序列预测。与此相反，转录因子的区域，结合辅激活因子复合物，激活结构域，仍然很差的特点，不能从氨基酸序列预测。例如，在拟南芥中，有1，717个转录因子，但只有8个已知的激活结构域。因此，当一个新的基因组被测序时，用于预测DBD的模型可以识别推定的转录因子，但没有类似的模型来预测这些转录因子是激活因子还是阻遏因子。本计画将使用高通量筛选方法来鉴定所有拟南芥转录因子的活化区域。这些数据将训练深度学习神经网络从氨基酸序列预测激活结构域，并预测其他不同植物物种的激活结构域。该项目的最后一部分将创建和验证用于植物基因调控的合成转录因子。这些工具将扩展合成生物学工具箱，用于代谢过程的有针对性的假设检验，工程调控网络，促进农业发展，并为解决环境问题的解决方案做出贡献。该奖项与由整合有机体系统部的植物基因组研究计划和分子与细胞生物科学部的系统与合成生物学集群资助。该奖项反映了NSF的基金会的使命是履行其法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Every plant begins life as a seed with one cell and one genome. In order for a plant to grow, the cells must divide and turn into different kinds of cells by turning on different genes. Leaf cells turn on leaf genes; root cells turn on root genes. This process of turning genes on and off requires specialized proteins called transcription factors. Transcription factors also allow plants to turn genes on or off to respond to stresses like drought or pests and pathogens. Transcription factors turn genes on using specialized regions called “activation domains.” The first part of this project will use technologies we developed to identify activation domains on all the transcription factors of one widely studied plant species, Arabidopsis. The data we collect will power our computational models for predicting activation domains in other plants. The final portion of this project will build synthetic transcription factors that can be used to engineer gene regulation in other plants. This research will create useful and powerful tools for plant biologists and plant breeders. This collaboration between three research teams creates a unique interdisciplinary training environment for undergraduates, graduate students, and postdoctoral research fellows. Our team is committed to building a supportive environment that fosters Equity, Diversity and Inclusion. The three PIs come from backgrounds that have been traditionally excluded from science. Two of the PIs are building on the success of their NSF CAREER awards.In plants, transcription factors control gene regulatory programs for development, growth and stress responses. Transcription factors have two functions: 1) to bind DNA sequences in the genome directly with a DNA binding domain (DBD) or through a partner DBD-containing protein and 2) to recruit transcriptional machinery. DBDs have been well characterized and can be predicted directly from amino acid sequence. In contrast, the regions of transcription factors that bind coactivator complexes, activation domains, remain poorly characterized and cannot be predicted from amino acid sequence. For example, in Arabidopsis, there are 1,717 transcription factors, but only 8 known activation domains. As a consequence, when a new genome is sequenced, models for predicting DBDs can identify putative transcription factors, but there are no analogous models for predicting if these transcription factors are activators or repressors. This project will use high throughput screening methods to identify activation domains on all Arabidopsis transcription factors. These data will train deep learning neural networks to predict activation domains from amino acid sequence and predict activation domains in other diverse plant species. The final portion of this project will create and validate synthetic transcription factors for engineering gene regulation in plants. These tools will expand the synthetic biology toolbox for targeted hypothesis testing of metabolic processes, engineering regulatory networks, advancing agriculture and contributing to solutions that could address environmental problems.This award was co-funded by the Plant Genome Research Program in the Division of Integrative Organismal Systems and the Systems and Synthetic Biology Cluster in the Division of Molecular and Cellular Biosciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.