Mining the tRNA genome by live-cell imaging

通过活细胞成像挖掘 tRNA 基因组

基本信息

  • 批准号:
    10005950
  • 负责人:
  • 金额:
    $ 23.49万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-09-01 至 2022-08-31
  • 项目状态:
    已结题

项目摘要

Project Summary Transfer RNAs (tRNAs) are central to translation of the genetic code to amino acid building blocks during protein synthesis on the ribosome. The human genome encodes 417 tRNA genes (gtrnadb.ucsc.edu), more than what is needed to translate the 61 sense codons. The diversity of tRNA genes in the human genome is previously unanticipated. We do not yet know which tRNA genes support protein synthesis and how we can image their activity and dynamics. While there is a strong need for robust labeling and imaging of tRNAs in live cells, progress has been slow. Without the convenience of making genetic fusions, such as protein fusions with fluorescent tags (GFP, YFP, etc), the current technology of tRNA labeling is limited to ex vivo conjugation with a fluorophore, followed by transfection or electroporation of the labeled tRNA into a cell. The disadvantage of the ex vivo approach is that the labeled tRNA is not synchronized with cell division. We were the first to develop a genetic fusion technology of tRNA with an RNA aptamer in an approach that is entirely based on nucleic acid replication to express and monitor tRNA for live-cell imaging. We have shown that an E. coli tRNA fused with a “Spinach” aptamer emits spinach-like fluorescence when expressed in E. coli. We have further shown that this Spinach- tRNA is accommodated by the E. coli endogenous protein synthesis machinery, including amino-acid charging by an aminoacyl-tRNA synthetase, access to the ribosome by translation factors, and interaction with the ribosome to make a peptide bond at both the A (aminoacyl-tRNA)- and P (peptidyl-tRNA)-site. The success of the Spinach-tRNA technology was unexpected, given that both the tRNA and the aptamer are of a similar size and that each has a well-defined tertiary structure. We propose to bring this technology to human cells and explore additional aptamers, such as “Mango” that emits a mango-like color. In Aim 1, we will use our genome- wide screening platform to identify tRNA genes that support protein synthesis by the ability to suppress a pre- mature termination codon in a reporter gene. All of the 417 tRNA genes will be screened for suppression at all three stop codons (UAG, UGA, and UAA) to identify the subset that are active in protein synthesis as tools for genome research. In Aim 2, we will perform another genome-wide screen to identify tRNAs that can be fused with an aptamer for live-cell imaging. We will generate a Spinach- and a Mango-library and screen for fusions in each that are active for protein synthesis. This will allow us to pair a Spinach- with a Mango-tRNA in a novel design that monitors FRET (Foster resonance energy transfer) when they occupy adjacent sites on the same ribosome during the making of a nascent peptide bond. By using FRET to focus on tRNAs in association with ribosomes, rather than those non-associated, we will quantify levels of protein synthesis in response to drug treatment and determine how protein synthesis may oscillate in the progression of a cell cycle. This project is at the forefront of powerful developments of new technologies for live-cell imaging of tRNA in the human genome.
项目摘要 转运RNA(tRNA)是在细胞内将遗传密码翻译成氨基酸结构单元的核心。 核糖体上的蛋白质合成。人类基因组编码417个tRNA基因(gtrnadb.ucsc.edu), 翻译61个有义密码子所需的信息人类基因组中tRNA基因的多样性以前是 出乎意料我们还不知道哪些tRNA基因支持蛋白质合成,以及我们如何对其进行成像。 活动和动态。虽然存在对活细胞中的tRNA的稳健标记和成像的强烈需求,但进展 进展缓慢如果不方便进行基因融合,如蛋白质与荧光标签的融合 (GFP YFP等),目前的tRNA标记技术限于与荧光团的离体缀合, 随后将标记的tRNA转染或电穿孔到细胞中。体外培养的缺点是 这种方法的另一个缺点是标记的tRNA与细胞分裂不同步。我们是第一个开发出 tRNA与RNA适体的融合技术,其方法完全基于核酸复制 来表达和监测tRNA用于活细胞成像。我们已经证明,一个E。与“菠菜”融合的大肠杆菌tRNA 适体在大肠杆菌中表达时发出类似菠菜的荧光。杆菌我们进一步表明,这种菠菜- tRNA由E.大肠杆菌内源性蛋白质合成机制,包括氨基酸充电 通过氨酰-tRNA合成酶,通过翻译因子进入核糖体,并与 核糖体在A(氨酰基-tRNA)-和P(肽基-tRNA)-位点处形成肽键。的成功 Spinach-tRNA技术是出乎意料的,因为tRNA和适体的大小相似 并且每个都具有明确的三级结构。我们建议将这项技术应用于人类细胞, 探索额外的适体,如“芒果”,发出类似芒果的颜色。在目标1中,我们将使用我们的基因组- 广泛的筛选平台,以确定tRNA基因,支持蛋白质合成的能力,抑制前, 成熟终止密码子。所有的417个tRNA基因将被筛选抑制在所有 三个终止密码子(UAG、UGA和UAA)用于识别在蛋白质合成中活跃的子集,作为工具 基因组研究在目标2中,我们将进行另一个全基因组筛选,以确定可以融合的tRNA 用于活细胞成像我们将产生一个菠菜和芒果文库,并筛选融合基因。 每一个都对蛋白质合成有活性。这将使我们能够在小说中将菠菜与芒果tRNA配对 设计监测FRET(福斯特共振能量转移)时,他们占据相邻网站上相同的 在形成新生肽键的过程中与核糖体结合。通过使用FRET聚焦于与 核糖体,而不是那些非相关的,我们将量化蛋白质合成水平,以响应药物 治疗和确定蛋白质合成如何在细胞周期的进程中振荡。该项目在 人类基因组中tRNA活细胞成像新技术的强大发展前沿。

项目成果

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Christopher A Ahern其他文献

Christopher A Ahern的其他文献

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{{ truncateString('Christopher A Ahern', 18)}}的其他基金

Chemical biology of voltage-gated cation channels
电压门控阳离子通道的化学生物学
  • 批准号:
    10552311
  • 财政年份:
    2023
  • 资助金额:
    $ 23.49万
  • 项目类别:
A Versatile Chemical-Genetic Approach to Determine Bases for Arrhythmogenesis and Sodium Channelopathies
确定心律失常发生和钠离子通道病基础的多功能化学遗传学方法
  • 批准号:
    10608370
  • 财政年份:
    2022
  • 资助金额:
    $ 23.49万
  • 项目类别:
Restoring Vision with High-Fidelity Nonsense Codon Correction
通过高保真无义密码子校正恢复视力
  • 批准号:
    10334544
  • 财政年份:
    2021
  • 资助金额:
    $ 23.49万
  • 项目类别:
Restoring Vision with High-Fidelity Nonsense Codon Correction
通过高保真无义密码子校正恢复视力
  • 批准号:
    10156779
  • 财政年份:
    2021
  • 资助金额:
    $ 23.49万
  • 项目类别:
Restoring Vision with High-Fidelity Nonsense Codon Correction
通过高保真无义密码子校正恢复视力
  • 批准号:
    10550272
  • 财政年份:
    2021
  • 资助金额:
    $ 23.49万
  • 项目类别:
Restoring Vision with High-Fidelity Nonsense Codon Correction
通过高保真无义密码子校正恢复视力
  • 批准号:
    10407714
  • 财政年份:
    2021
  • 资助金额:
    $ 23.49万
  • 项目类别:
Restoring Vision with High-Fidelity Nonsense Codon Correction
通过高保真无义密码子校正恢复视力
  • 批准号:
    10627046
  • 财政年份:
    2021
  • 资助金额:
    $ 23.49万
  • 项目类别:
Photochemical determination of sodium channel voltage-dependent gating and composition
钠通道电压依赖性门控和成分的光化学测定
  • 批准号:
    9402276
  • 财政年份:
    2017
  • 资助金额:
    $ 23.49万
  • 项目类别:
Photochemical determination of sodium channel voltage-dependent gating and composition
钠通道电压依赖性门控和成分的光化学测定
  • 批准号:
    10004154
  • 财政年份:
    2017
  • 资助金额:
    $ 23.49万
  • 项目类别:
The Facility for Atomic Mutagenesis
原子诱变设施
  • 批准号:
    10063065
  • 财政年份:
    2017
  • 资助金额:
    $ 23.49万
  • 项目类别:

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