Collaborative Research: RoL: Revealing a new mechanism of action for eukaryotic transcriptional activation domains

合作研究:RoL:揭示真核转录激活域的新作用机制

基本信息

  • 批准号:
    1925643
  • 负责人:
  • 金额:
    $ 22.62万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-08-15 至 2023-07-31
  • 项目状态:
    已结题

项目摘要

This Rules of Life project seeks to discover new molecular mechanisms for turning genes on in eukaryotic cells. Decades of previous research have led to the conventional belief that the proteins responsible for turning on, or activating, genes are locked into rigid shapes. These shapes allow the proteins to interact with DNA, or with other proteins, like a key fits into a lock. By contrast, this project will explore a new idea that the shape of activating proteins is not a rigid structure and that this lack of rigidity gives the proteins the ability to operate in extremely crowded cellular space and to interact in flexible ways with gene DNA. This idea will be tested using a combination of laboratory experiments and computational approaches. The results will improve fundamental understanding of how molecules interact with each other in the cell, thereby providing a conceptual foundation for applications such as advanced gene editing, personalized medicine or drug development. The project will also have educational impact by providing multidisciplinary graduate and undergraduate STEM training at Butler University and Purdue University and by building a network of bioinformatics research communities in Indiana and other neighboring states through participation and organization of seminar series and workshops.Transcriptional activation domains in transcription factors are widely believed to work via direct recruitment of coactivators and transcription initiation complex components. Transcriptional activation domains are known to be very heterogeneous in their amino acid sequences, they have intrinsically disordered structure, and they have low affinity and specificity. However, details of their mechanism of action remain elusive. This project will test the novel idea that when coupled in the same transcription factor with a high-affinity DNA binding domain, transcriptional activation domains function to trigger chromatin remodeling through low-affinity interactions with nucleosomes, which then enable subsequent recruitment of nucleosome remodelers and transcriptional co-activators. Experiments are designed to discriminate between the so-called "nucleosome detergent" model and the traditional direct recruitment model. Gene activation mechanisms will be studied by the creation and screening of large complexity libraries of cells identical in all parameters other than the short (10-20 amino acids) transcription activation domain of the key gene activator, that is necessary for cell survival. Individual libraries will be screened in vivo, sequenced at the DNA level using next generation sequencing techniques, and analyzed utilizing bioinformatics and machine learning. Modifications related to the change of the intramolecular context of the key library-carrying gene activator, or the change of the reporter gene context, will help to extract key features of the transcriptional activation domains and the biological rules of eukaryotic gene activation. This award was jointly funded by the Genetic Mechanisms Program in the Division of Molecular and Cellular Biosciences, by the Infrastructure Innovations for Biological Research Program in the Division of Biological Infrastructure, and by the Rules of Life initiative of the Division of Emerging Frontiers in the Biological Sciences Directorate.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.
这个生命法则项目试图发现在真核细胞中开启基因的新分子机制。此前数十年的研究使人们普遍认为,负责启动或激活基因的蛋白质被锁定在僵硬的形状中。这些形状允许蛋白质与DNA或其他蛋白质相互作用,就像钥匙可以插入锁中一样。相比之下,这个项目将探索一种新的想法,即激活蛋白质的形状不是一个刚性结构,这种刚性的缺乏使蛋白质能够在极其拥挤的细胞空间中操作,并以灵活的方式与基因DNA相互作用。这一想法将使用实验室实验和计算方法相结合的方式进行测试。这些结果将提高对分子在细胞内如何相互作用的基本理解,从而为先进的基因编辑、个性化药物或药物开发等应用提供概念基础。该项目还将产生教育影响,在巴特勒大学和普渡大学提供多学科的研究生和本科生STEM培训,并通过参与和组织研讨会系列和工作坊,在印第安纳州和其他邻近州建立生物信息学研究社区网络。转录因子中的转录激活域被广泛认为是通过直接招募辅助激活因子和转录起始复合体组件发挥作用的。已知转录激活结构域的氨基酸序列具有很强的异质性,具有内在的无序结构,亲和力和特异性低。然而,他们的行动机制的细节仍然难以捉摸。该项目将测试这一新想法,即当与相同的转录因子与高亲和力DNA结合域结合时,转录激活域通过与核小体的低亲和力相互作用来触发染色质重塑,从而使随后能够招募核小体重构体和转录共激活子。实验旨在区分所谓的核小体洗涤剂模式和传统的直接招募模式。基因激活机制将通过创建和筛选除关键基因激活剂的短(10-20个氨基酸)转录激活域以外的所有参数相同的大型复杂细胞文库来研究,这是细胞生存所必需的。单个文库将在体内进行筛选,使用下一代测序技术在DNA水平上进行测序,并利用生物信息学和机器学习进行分析。与携带关键文库的基因激活子的分子内上下文的变化或报告基因上下文的变化相关的修饰将有助于提取转录激活域的关键特征和真核基因激活的生物学规律。该奖项由分子和细胞生物科学部的遗传机制计划、生物基础设施部的生物研究基础设施创新计划和生物科学总监新兴前沿部门的生命规则倡议共同资助。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(6)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Essential amino acids in the Plant-Conserved and Class-Specific Regions of cellulose synthases
  • DOI:
    10.1093/plphys/kiac479
  • 发表时间:
    2022-10-17
  • 期刊:
  • 影响因子:
    7.4
  • 作者:
    Olek,Anna T.;Rushton,Phillip S.;Carpita,Nicholas C.
  • 通讯作者:
    Carpita,Nicholas C.
PDA-Pred: Predicting the binding affinity of protein-DNA complexes using machine learning techniques and structural features
  • DOI:
    10.1016/j.ymeth.2023.03.002
  • 发表时间:
    2023-03-23
  • 期刊:
  • 影响因子:
    4.8
  • 作者:
    Harini, K.;Kihara, Daisuke;Gromiha, M. Michael
  • 通讯作者:
    Gromiha, M. Michael
Protein docking model evaluation by 3D deep convolutional neural networks
  • DOI:
    10.1093/bioinformatics/btz870
  • 发表时间:
    2020-04-01
  • 期刊:
  • 影响因子:
    5.8
  • 作者:
    Wang, Xiao;Terashi, Genki;Kihara, Daisuke
  • 通讯作者:
    Kihara, Daisuke
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Daisuke Kihara其他文献

NuFold: end-to-end approach for RNA tertiary structure prediction with flexible nucleobase center representation
NuFold:具有灵活核碱基中心表示的 RNA 三级结构预测的端到端方法
  • DOI:
    10.1038/s41467-025-56261-7
  • 发表时间:
    2025-01-21
  • 期刊:
  • 影响因子:
    15.700
  • 作者:
    Yuki Kagaya;Zicong Zhang;Nabil Ibtehaz;Xiao Wang;Tsukasa Nakamura;Pranav Deep Punuru;Daisuke Kihara
  • 通讯作者:
    Daisuke Kihara
Local surface shape-based protein function prediction using Zernike descriptors
  • DOI:
    10.1016/j.bpj.2008.12.3435
  • 发表时间:
    2009-02-01
  • 期刊:
  • 影响因子:
  • 作者:
    Daisuke Kihara;Lee Sael;Rayan Chikhi
  • 通讯作者:
    Rayan Chikhi
Effect of phosphorylation barcodes on arrestin binding to a chemokine receptor
磷酸化条形码对 arrestin 与趋化因子受体结合的影响
  • DOI:
    10.1038/s41586-025-09024-9
  • 发表时间:
    2025-05-21
  • 期刊:
  • 影响因子:
    48.500
  • 作者:
    Qiuyan Chen;Christopher T. Schafer;Somnath Mukherjee;Kai Wang;Martin Gustavsson;James R. Fuller;Katelyn Tepper;Thomas D. Lamme;Yasmin Aydin;Parth Agrawal;Genki Terashi;Xin-Qiu Yao;Daisuke Kihara;Anthony A. Kossiakoff;Tracy M. Handel;John J. G. Tesmer
  • 通讯作者:
    John J. G. Tesmer
Improved De Novo Main-Chain Tracing Method Mainmast for Multi-Chain Modeling, Local Refinement, and Graphical User Interface
  • DOI:
    10.1016/j.bpj.2018.11.3094
  • 发表时间:
    2019-02-15
  • 期刊:
  • 影响因子:
  • 作者:
    Genki Terashi;Yuhong Zha;Daisuke Kihara
  • 通讯作者:
    Daisuke Kihara
De Novo Computational Protein Tertiary Structure Modeling Pipeline for Cryo-EM Maps of Intermediate Resolution
  • DOI:
    10.1016/j.bpj.2019.11.1657
  • 发表时间:
    2020-02-07
  • 期刊:
  • 影响因子:
  • 作者:
    Daisuke Kihara;Genki Terashi;Sai Raghavendra Maddhuri Venkata Subramaniya
  • 通讯作者:
    Sai Raghavendra Maddhuri Venkata Subramaniya

Daisuke Kihara的其他文献

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{{ truncateString('Daisuke Kihara', 18)}}的其他基金

Collaborative Research: Integrated Moment-Based Descriptors and Deep Neural Network for Screening Three-Dimensional Biological Data
合作研究:集成基于矩的描述符和深度神经网络用于筛选三维生物数据
  • 批准号:
    2151678
  • 财政年份:
    2022
  • 资助金额:
    $ 22.62万
  • 项目类别:
    Standard Grant
Collaborative Research: III: Medium: Systematic De Novo Identification of Macromolecular Complexes in Cryo-Electron Tomography Images
合作研究:III:介质:冷冻电子断层扫描图像中大分子复合物的系统从头识别
  • 批准号:
    2211598
  • 财政年份:
    2022
  • 资助金额:
    $ 22.62万
  • 项目类别:
    Standard Grant
Collaborative Research: Identification and Structural Modeling of Intrinsically Disordered Protein-Protein and Protein-Nucleic Acids Interactions
合作研究:本质无序的蛋白质-蛋白质和蛋白质-核酸相互作用的识别和结构建模
  • 批准号:
    2146026
  • 财政年份:
    2022
  • 资助金额:
    $ 22.62万
  • 项目类别:
    Standard Grant
IIBR Informatics: Development of Multimodal approaches for protein function prediction
IIBR 信息学:蛋白质功能预测多模式方法的开发
  • 批准号:
    2003635
  • 财政年份:
    2020
  • 资助金额:
    $ 22.62万
  • 项目类别:
    Standard Grant
Collaborative Research: Efficient mathematical and computational framework for biological 3D image data retrieval
协作研究:生物 3D 图像数据检索的高效数学和计算框架
  • 批准号:
    1614777
  • 财政年份:
    2016
  • 资助金额:
    $ 22.62万
  • 项目类别:
    Standard Grant
ABI Innovation: Protein Functional Sites Identification Using Sequence Variation
ABI Innovation:利用序列变异识别蛋白质功能位点
  • 批准号:
    1262189
  • 财政年份:
    2013
  • 资助金额:
    $ 22.62万
  • 项目类别:
    Standard Grant
III: Small: Rapid screening of interacting ligands and proteins
III:小:快速筛选相互作用的配体和蛋白质
  • 批准号:
    1319551
  • 财政年份:
    2013
  • 资助金额:
    $ 22.62万
  • 项目类别:
    Continuing Grant
III: Small: Quality Assessment of Computational Protein Models
III:小:计算蛋白质模型的质量评估
  • 批准号:
    0915801
  • 财政年份:
    2009
  • 资助金额:
    $ 22.62万
  • 项目类别:
    Standard Grant
Template-Based Protein Structure Prediction Beyond Sequence Homology
超越序列同源性的基于模板的蛋白质结构预测
  • 批准号:
    0850009
  • 财政年份:
    2009
  • 资助金额:
    $ 22.62万
  • 项目类别:
    Standard Grant

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RoL: COLLABORATIVE RESEARCH: EXTREME ENVIRONMENTS, PHYSIOLOGICAL ADAPTATION, AND THE ORIGIN OF SPECIES
ROL:合作研究:极端环境、生理适应和物种起源
  • 批准号:
    2423844
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Collaborative Research: RoL: The intersection between cell fate decisions and phenotypic diversification in a rapidly radiating butterfly lineage
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合作研究:基因组动态光环境塑造的 RoL 规则
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Collaborative Research: RoL-Rules for Dynamic-Light Environmental Sculpting of Genomes
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