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Developing genetically encoded ultra-correlative tags for functional studies employing light and electron microscopy

Developing genetically encoded ultra-correlative tags for functional studies employing light and electron microscopy
使用光学和电子显微镜开发用于功能研究的基因编码超相关标签
批准号:
BB/T012005/1
负责人:
Christian Pinali
金额:
$16.05万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2021
资助国家:
英国
项目状态:
已结题
起止时间:
2021 至 --

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英文摘要
A key biomedical goal is to understand how organelles and proteins cooperate to make organs work, in both 'normal' and diseased conditions, with the ultimate aim to improve our health. However, current methods to explore these structure-function relationships have a number of drawbacks. Not least amongst these limitations are the resolution limit set by standard electron microscopy approaches and the difficulty associated with correlating functional and structural data across tissue and molecular scale length. We propose to develop a genetically encoded ultra-correlative tag for multiplexing structural and functional analysis of labelled genes. We will develop novel genetic tags based on heavy metal binding peptides detectable with electron microscopy. This method will give protein localisation precision an order of magnitude greater than established methods and mitigate many of the drawbacks associated with classic electron microscopy approaches. Further, we will combine it with established light microscopy methods to create a 'dual tag' that enables both correlative light and electron microscopy (CLEM) structural assessments as well as live cell functional imaging on the same genes. Finally, by integrating this new functional CLEM genetic tagging strategy using gene editing techniques we will achieve truly correlative molecular level resolution and provide quantitative structure-function information. Importantly, this method is not limited to study the structure-function relationship of a single target protein, in fact using a wide array of compatible covalent labelling tags and specific metal binding peptides, multiple proteins can be simultaneously assessed with precision. The proposed approaches are readily applicable across different biological and disease relevant systems spanning single cell systems through to whole organism physiology.
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