Optically Gated Discovery of Protein-Biomolecule Interactions
蛋白质-生物分子相互作用的光门发现
基本信息
- 批准号:10709546
- 负责人:
- 金额:$ 42.38万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-24 至 2027-07-31
- 项目状态:未结题
- 来源:
- 关键词:AffinityAutomobile DrivingBiological ProcessCellsChemicalsCommunitiesDataDependenceDevelopmentDimensionsDiseaseExocytosisGoalsHealthHumanImmunologyLabelLightLocationLymphocyte FunctionMalignant NeoplasmsMapsMass Spectrum AnalysisMembraneMethodsMicroscopyMolecular BiologyMotivationNeurologyNeuronsOpticsOrphanPatternPeptidesProteinsProteomicsResearchResolutionSpecificitySystemTechnologyThymus GlandTimeTissue SampleTonsilWorkcatalystcrosslinkdesigndiagnostic strategydrug developmenthuman tissueimprovedinterestion mobilitymillisecondnew technologynew therapeutic targetnovel diagnosticsnovel therapeuticsoptogeneticsreceptorspatiotemporaltemporal measurementtooltranscriptomics
项目摘要
The overall goal of research in the Geri lab is to map protein interactomes using discovery technologies that
provide orders of magnitude improvements in spatiotemporal resolution over the current state-of-the-art. The
motivation for this work is that advancing the resolution of protein interactome discovery technology beyond key
milestones, such as single cell and single protein thresholds, will have a field-wide impact analogous to similar
advances in transcriptomics and microscopy. The first three years of work in the lab will be focused on creating
new technologies by combining photocatalytic proximity labeling, in which light-powered catalysts attached to an
affinity handle drive the crosslinking of synthetic affinity probes with nearby proteins, with patterned light and
interaction-gated activation to simultaneously enforce multiple dimensions of specificity. The fourth and fifth
years of work will focus on applying the mature technologies. The overall strategy is divided along two thrusts,
in which labeling specificity is obtained through extrinsic optical control or intrinsic chemical control, and has
been designed to be programmatically robust by minimizing project interdependency. Intrinsically selective
systems will exploit the high spatial resolution of photocatalytic labeling (5 nm) and use “split” systems that
operate when defined protein targets are in proximity. Initial work will use natively expressed orphan peptides as
proximity labeling loci to discover their currently unknown receptors. The effort will cover thousands of peptides
by using label free ion mobility mass spectrometry for proteomics, maximally leveraged by using optimized
labeling probe designs. Split systems will combine multiple photocatalysts targeted to different proteins of interest
to make colocalization a dimension of specificity, and will be initially applied to map proteins present at membrane
junctions. Extrinsically controlled systems will enable subcellular resolution labeling in human tissue sections
and ms-resolution temporal control for the study of transient protein interactions. Both approaches are enabled
by combining optical tools for spatiotemporal control of light itself with the total and instantaneously responsive
(<1µs) dependence between photocatalytic efficiency and the local supply of light, and each allow for a three
order of magnitude increase in resolution vs current tools. Spatially selective labeling will focus on identifying
protein interactions unique to cell subpopulations in human tissues, with initial studies focusing on discovering
location-conditional interactions driving lymphocyte function in human tonsil and thymus. Later studies will focus
on discovering interactome differences between translationally relevant tissue samples. Temporally resolved
labeling will combine optogenetic tools and photocatalytic proximity labeling to synchronize and interrogate
transient protein interactions. The power of this approach will be fully exploited by studying exocytosis in neurons
with millisecond resolution, one of the fastest dynamic biological processes known. Successful development and
deployment of these systems for protein interaction discovery will enable the study of large interactome spaces
for the first time, and is expected to have a broad impact on the molecular biology community.
Geri实验室研究的总体目标是使用发现技术绘制蛋白质相互作用组,
在时空分辨率上提供了超过当前技术水平的数量级的改进。
这项工作的动机是,推进蛋白质相互作用组发现技术的解决方案,
里程碑,如单细胞和单蛋白阈值,将产生类似于类似的领域范围的影响。
转录组学和显微镜的进展。实验室的前三年工作将集中在创造
通过结合光催化邻近标记的新技术,其中光动力催化剂附着在
亲和手柄驱动合成亲和探针与附近蛋白质的交联,具有图案化的光,
相互作用门控激活,以同时实施多个维度的特异性。第四和第五
多年的工作将集中在应用成熟的技术上。总体战略分为沿着两个重点,
其中标记特异性是通过外部光学控制或内部化学控制获得的,
通过最小化项目的相互依赖性,使其在程序上更加健壮。内选择性
系统将利用光催化标记的高空间分辨率(5nm),并使用“分离”系统,
当确定的蛋白质目标接近时起作用。最初的工作将使用天然表达的孤儿肽,
邻近标记位点以发现它们目前未知的受体。这项工作将涵盖数千种肽
通过使用无标记离子迁移率质谱进行蛋白质组学,最大限度地利用优化的
标记探针设计。分离系统将联合收割机结合多种针对不同蛋白质的光催化剂
使共定位的一个维度的特异性,并将最初应用于地图蛋白质存在于膜
交叉点外部控制系统将使亚细胞分辨率标记在人体组织切片
以及用于瞬时蛋白质相互作用研究的ms分辨率时间控制。这两种方法都是启用的
通过将用于光本身的时空控制的光学工具与总的和瞬时响应的
(<1µs)的光催化效率和本地光供应之间的依赖关系,并且每个都允许三个
与当前工具相比,分辨率提高了一个数量级。空间选择性标记将侧重于识别
人类组织中细胞亚群特有的蛋白质相互作用,最初的研究集中在发现
位置条件相互作用驱动人类扁桃体和胸腺淋巴细胞功能。后续研究将聚焦
发现与病理学相关的组织样本之间的相互作用组差异。在时间上可解析
标记将结合联合收割机光遗传学工具和光催化邻近标记,
瞬时蛋白质相互作用这种方法的力量将通过研究神经元中的胞吐作用得到充分利用
毫秒级的分辨率,这是已知最快的动态生物过程之一。成功开发和
利用这些系统进行蛋白质相互作用的发现,将使大的相互作用空间的研究成为可能
这是第一次,预计将对分子生物学界产生广泛的影响。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Jacob Geri其他文献
Jacob Geri的其他文献
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{{ truncateString('Jacob Geri', 18)}}的其他基金
Supplement for Optically Gated Discovery of Protein-Biomolecule Interactions project.
蛋白质-生物分子相互作用光门发现项目的补充。
- 批准号:
10807688 - 财政年份:2022
- 资助金额:
$ 42.38万 - 项目类别:
Optically Gated Discovery of Protein-Biomolecule Interactions
蛋白质-生物分子相互作用的光门发现
- 批准号:
10501385 - 财政年份:2022
- 资助金额:
$ 42.38万 - 项目类别:
Photoredox-Enabled Applications of Primary Amines as Alkylating Reagents
伯胺作为烷基化试剂的光氧化还原应用
- 批准号:
9760408 - 财政年份:2019
- 资助金额:
$ 42.38万 - 项目类别:
Photoredox-Enabled Applications of Primary Amines as Alkylating Reagents
伯胺作为烷基化试剂的光氧化还原应用
- 批准号:
9978569 - 财政年份:2019
- 资助金额:
$ 42.38万 - 项目类别:
Application of 4D proteomics and super-resolution microscopy in extracellular vesicle and particle-borne biomarker discovery for early pancreatic cancer detection
4D 蛋白质组学和超分辨率显微镜在细胞外囊泡和颗粒传播生物标志物发现中的应用,用于早期胰腺癌检测
- 批准号:
10737386 - 财政年份:2017
- 资助金额:
$ 42.38万 - 项目类别:
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