Human Lung Cell Atlas Project: genetic regulation of foetal and healthy adult lung cell states in 3D spatial resolution

细胞是我们身体的功能单位。不同的疾病是由我们体内细胞类型的变化或细胞行为(细胞状态)的变化引起的。人类细胞图谱是一项国际合作，旨在描述人体的所有细胞类型和状态，以了解健康的身体是如何运作的。它将提供一个参考图，以确定与疾病相关的细胞变化。我们建议研究健康人肺中的细胞类型和细胞状态，以帮助了解肺癌和退行性疾病(如肺纤维化和慢性阻塞性肺疾病)中发生的变化。重要的是，我们将研究发育中的(胎儿)人肺和健康的成人肺。这将使我们能够对未成熟和成熟的细胞状态进行比较，并从长远来看，提供可用作再生医学基础的信息。细胞类型和细胞状态由每个细胞中表达的不同基因决定。单细胞RNA测序技术，简称scRNA-seq，可以准确地确定数千个并行细胞中任何细胞中哪些基因是活跃的。使用scRNA-seq将使我们能够识别和鉴定发育中的和成人肺中的细胞。我们将在我们最近在成人肺上所做的工作的基础上，识别出一种全新的细胞类型--离子细胞，以了解不同的细胞如何合作来建立和维持肺功能。首先，我们将在不同的空间位置进行scRNA-seq，以鉴定发育中的肺的所有细胞类型。通过观察单个细胞，可以识别与每个细胞相关联的特征。例如，它是否仍然不成熟，或者已经获得了更成熟的细胞类型的特征。这使得scRNA-seq成为研究人类发育的一个非常强大的工具。我们将询问受孕后6-20周内人类肺部的发育情况。我们将把我们在胎儿身上的结果与成人肺中细胞类型和状态的维持方式进行比较，利用我们已经获得的资金来研究成人组织。其次，我们将使用一种新的单细胞技术(单细胞ATAC-SEQ)，它将允许我们识别控制每个细胞中哪些基因打开或关闭的DNA区域。这些实验将帮助我们更好地定义细胞状态，并提供有关这些状态如何控制的信息。在未来，这些知识将被用来寻找改变细胞状态的方法，以开发新的疾病治疗方法。地图集不仅仅是一个清单，它还提供了地图意义上的空间信息。在我们的建议的第三部分中，我们将把识别出的单元类型放回它们的空间上下文中。这对于研究发育和成体干细胞或祖细胞尤其重要，在这些细胞中，邻近细胞的存在强烈影响行为。我们将使用空间转录学，它允许在太空中研究所有基因的活动，但目前不是在单个细胞的分辨率下。我们还将使用一种名为HCR的技术，结合高性能显微镜，这种技术测量的基因更少，但只有单细胞分辨率。通过将这两种技术结合起来，我们将构建一张肺的3D地图。我们的工作将产生大量复杂的数据集，需要在计算上进行整合。在惠康基因园区，我们拥有世界领先的计算专业知识和基础设施。我们(迈耶)已经在与人类细胞图谱密切合作，以最大限度地发挥这一项目对国际生物医学研究的好处。这项工作将为更好地了解许多肺部疾病奠定基础。它将通过揭示控制肺发育和维持的途径，帮助我们解释肺部疾病的基因研究结果以及对再生医学和治疗发展的影响。

Cells are the functional units of our bodies. Different diseases are caused by changes in the types of cells in our bodies, or by changes in cell behaviour (cell state). The Human Cell Atlas is an international collaboration to characterise all cell types and states of the human body to understand how the healthy body functions. It will provide a reference map to identify cell changes that are associated with disease. We propose to study cell types and cell states in the healthy human lung to contribute to understanding of changes that occur in lung cancer and degenerative diseases, like pulmonary fibrosis and chronic obstructive pulmonary disease. Importantly, we will study the developing (foetal) human lung alongside the healthy adult lung. This will allow us to make comparisons between immature and mature cell states and, in the long-term, provide information that can be used as the basis for regenerative medicine. Cell type and cell state are defined by the different genes expressed in each cell. Single cell RNA sequencing technology, scRNA-seq for short, makes it possible to determine exactly which genes are active in any cell for thousands of cells in parallel. Using scRNA-seq will allow us to identify and characterise cells in the developing and adult human lung. We will build on our recent work in the adult lung that has identified an entirely new cell type, the ionocyte, to understand how different cells cooperate to build and maintain lung function. Firstly, we will carry out scRNA-seq in distinct spatial locations to identify all cell types of the developing lung. By looking at individual cells it becomes possible to identify characteristics that are associated with each cell. For example, whether it is still immature or has already acquired the characteristics of a more mature cell type. This makes scRNA-seq a very powerful tool to study human development. We will be asking how the human lungs develop during weeks 6-20 post-conception. We will compare our results from the foetus to how cell types and states are maintained in the adult human lung, leveraging funding that we have already obtained to study the adult tissue. Secondly, we will use a new single cell technology (single cell ATAC-seq) which will allow us to identify regions of DNA that control which genes are turned on or off in each cell. These experiments will help us to better define cell states and provide information about how these states are controlled. In the future, this knowledge will be used to find ways of modifying cell states to develop new treatments for disease. An atlas is not just a list, but also provides spatial information in the sense of a map. In the third part of our proposal we will place the identified cell types back into their spatial context. This is of particular importance for studying development and adult stem or progenitor cells, where the presence of neighbouring cells strongly influences behaviour. We will use spatial transcriptomics which allows the activity of all genes to be studied in space, but currently not at the resolution of individual cells. We will also use a technique called HCR, coupled with high performance microscopy, which measures fewer genes, but at single cell resolution. By combining these two techniques we will build a 3D map of the lung. Our work will generate large and complex data-sets that need to be integrated computationally. At the Wellcome Genome Campus we have world-leading computational expertise and infrastructure. We (Meyer) are already working in close collaboration with the Human Cell Atlas to maximise the benefits of this project for international biomedical research. This work will lay the foundations for a better understanding of many lung diseases. It will help us to interpret results from genetic studies of lung disease and impact on regenerative medicine and therapeutics development by revealing pathways controlling lung development and maintenance.