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Enhancing multi-omic single cell sequencing to resolve fundamental biological mechanisms in humans and non-human organisms

Enhancing multi-omic single cell sequencing to resolve fundamental biological mechanisms in humans and non-human organisms
增强多组学单细胞测序以解决人类和非人类生物体的基本生物学机制
批准号:
BB/W019922/1
负责人:
Andrew Beggs
金额:
$70.67万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2022
资助国家:
英国
项目状态:
已结题
起止时间:
2022 至 --

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中文摘要
翻译
在过去的50年里,生物学和医学领域发生了巨大的变化,因为我们越来越了解细胞的遗传密码是如何组成的,DNA是RNA的模板,它调节细胞功能的各个方面。随着研究DNA和RNA的技术的改进,我们对这些过程的理解导致了影响生物技术的深远发现和技术进步,我们对细胞的基础生物学以及整个器官和生物体的正常发育生物学的理解。重要的是,它们还为感染、炎症和癌症等疾病过程提供了深刻的见解,这些疾病对人类和动物世界都有影响。每个细胞都有自己的指挥中心,它以DNA的形式存在于细胞核中,我们理想地想知道每个细胞是如何运作的,因为它总是与影响其生理的许多其他细胞接触。因此,到目前为止,这些技术的分辨率相对较低,因为我们只能采集多个细胞的样本并将其作为一个组进行分析。每个细胞对整个生物体的作用是这些细胞如何合作以及它们在器官中的位置的总和,将它们全部集中在一起并不能给我们提供理解基本生物过程所需的信息。我们现在可以分析一组细胞中每个单细胞的DNA和RNA变化,帮助我们了解这些细胞如何协同工作。使用第一代单细胞技术,我们现在知道,在人类、动物或植物细胞中,看似相同的细胞群体在同一时间点处于不同的状态。几年前,我们在伯明翰大学建立了一个设施,对每个单细胞内的所有RNA进行分析,告诉我们每个细胞处于什么状态。然而,技术已经迅速发展,现在可以在一个细胞内研究多种特征,例如我们的遗传密码的组成和完整性,以及这些细胞包含哪些蛋白质。我们还可以将这些数据与显示单个细胞在器官内位置的数据联系起来,从而得出它们的环境如何影响它们行为的结论。在这项提案中,我们申请资金购买设备,使我们能够建立这些新颖的单细胞技术。我们相信,如果不能扩大我们的设施并采用这些新技术,我们将无法参与全球竞争的科学,我们将无法解决最紧迫的生物学问题。这一应用将使我们能够实现这些目标。它将扩大我们的用户群,并首次将这些尖端技术提供给中部地区的多个用户。
英文摘要
The fields of biology and medicine have been dramatically changed over the past 50 years by our increasing knowledge of how the genetic code of cells which consists of DNA which serves as a template for RNA regulates all aspects of cellular function. As the technologies to study DNA and RNA have improved, our understanding of these processes have led to far-reaching discoveries and technological advances impacting on biotechnology, our understanding of the basic biology of cells and of normal developmental biology of whole organs and organisms. Importantly, they also have provided deep insights into disease processes such as infection, inflammation and cancer with an impact on both the human and the animal world. Each cell has its own command center which resides in the nucleus in form of DNA and we ideally want to know how each individual cell functions as it is always in contact with a multitude of other cells who impact on its physiology. Therefore, until now, these technologies have been relatively low resolution, because we have only been able to take a sample of multiple cells and analyse them as a group. The effect of what each cell does on the whole organism is the sum of how these cells cooperate and where they are within an organ, and lumping them all together does not give us the information we need to understand fundamental biological processes. We can now perform analysis of the DNA and RNA changes in each single cell within a group of cells, helping us to understand how these cells work together. Using first generation single cell technology, we now know that within a population of seemingly identical cells in a human, animal or plant cells are in different states at a single point in time. A few years ago, we have established a facility within the University of Birmingham that carries out an analysis of all RNA that is within each single cell which tells us in what state each cell is in. However, technology has rapidly progressed and it is now possible to study multiple features all within one cell, such as the composition and intactness our genetic code, and which proteins these cells contain. We can also link such data with data showing where within an organ single cells are located and can thus draw conclusions of how their surroundings influence their behaviour. In this proposal we apply for funds to buy the equipment enabling us to establish these novel single cell technologies. We believe that without being able to expand our facility and incorporate these new techniques, we will not be able to participate in globally competitive science and we will not be able to address the most pressing biological questions. This application will enable us to carry out these aims. It will widen our user base and for the first time will make these cutting edge technologies available to multiple users within the Midlands.
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Understanding the mechanisms of treatment resistance in colorectal cancer using organoid models
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  • 项目类别:
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  • 财政年份:
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  • 项目类别:
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