Lung diseases, such as COPD (Chronic Obstructive Pulmonary Disease) and asthma, are a leading cause of death. Cases of these diseases are increasing and there are no treatments that can cure them completely. We need to learn more about how these diseases happen and how treatments work so we can prevent and treat them more effectively.
Our bodies are made up of cells, which are like tiny building blocks in all living things. Some living things are very complex and have trillions of different cells. Our lungs are complicated and are made up of lots of different cells. These cells have different roles and react differently to different stimuli. Because of this complexity, it has been difficult to develop new therapies for lung conditions.
To be better able to create new therapies, we need to understand: what types of cells are in the lung, what roles they have and how they communicate with each other. We also need to understand the differences between healthy lungs and lungs with a disease. To achieve this, discovAIR will create an Atlas of the Human Lung. The Human Lung Cell Atlas will be a 3D reconstruction of the lungs and contain detailed information about the cells.
DiscovAIR will use tissue from people with lung disease and healthy individuals. This tissue will help to identify specific properties of different types of cells. We will also learn how these properties change from a healthy to a diseased state. We will create a map of these different cell types. DiscovAIR will use new computer methods to combine all this information and create the first draft of the human lung cell atlas.
We will share the results using a free-to-access, online platform. Scientists, clinical experts, diagnostic and pharmaceutical industries will have access to this platform. The information will enable progress in medicine. And identify new candidates for precision diagnostics and treatments in lung disease. This will contribute to healthy ageing and active living in Europe.
To shed light on the cellular landscape of the lungs, the discovAIR project makes use of several of the latest and most advanced scientific methods. These methods help us to see how genes are expressed on a cellular and spatial level. These cutting-edge methods include single-cell genomics, which was the foundation for the Science Breakthrough of the Year 2018, single-cell multimodal omics, Method of the Year 2019 by Nature Magazine, and spatial transcriptomics, Method of the Year 2020 by Nature Magazine.
We will use two approaches, the “cellular branch” and the “spatial branch” of the project. Together, these approaches will allow us to better understand the identities of the cells and the associated cell types. We will also learn how these different cell types are distributed within the healthy and diseased lung.
The Human Lung Cell Atlas, which is the main outcome of the discovAIR project, is the combination of the results from these two approaches. It can be thought of as an atlas or database that contains all characteristic properties of each cell in the lung.
The results come from an unprecedentedly large number of specimens that were analysed in multiple labs across Europe. The Human Lung Cell Atlas will help researchers around the globe to better understand their own data by mapping their results against the Human Lung Cell Atlas as a reference.
Every single one of the approximately 37 trillion cells in our body carries the same genetic information. Yet, every cell is unique. They divide into many different cell classes and types:
Each cell type has specific morphologies and tasks within our body. On top of that, there are many subtypes and cell states that are still not understood, and which only became observable with the help of single-cell genomics.
The root cause for the vast amount of different cell types – despite them having the same underlying genetic information – lies in how this genetic information is expressed. In fact, many – if not most – of the 25,000 human genes remain inactive within one cell. Only the set of active genes defines the phenotype, which is the set of observable, individual traits and characteristics of a cell. Single-cell genomics now makes it possible to detect and analyse how the genes in each cell are expressed. This enables deep insights into the composition of tissue, the interaction between cells, and into the evolution of dynamic biochemical processes on the resolution of single cells. Results based on single-cell genomics have recently been awarded the Science Breakthrough of the Year 2018.
DiscovAIR will use single-nucleus RNA-Sequencing and single-nucleus ATAC-Seq to analyse the properties of the cells in multiple locations of the healthy and diseased lung. This will help us to understand how different cell types are distributed within the lung and its several structures. The results of these two methods will be combined to provide a multimodal perspective. Researchers will analyse how specific cells react to stimuli that mimic disease. This will allow us to research and map how cells transition from being healthy to diseased.
Spatially resolved genomics has evolved very recently after the huge successes of single-cell genomics. Just in 2020, spatially resolved transcriptomics was named Method of the Year by Nature Magazine. In general, spatially resolved genomics allow us to analyse where certain genes are expressed. This sheds light on the composition of healthy and diseased tissue. This will prove especially useful not only in oncology, where the composition of tumours can now be analysed, but also in healthy tissue as the spatial organisation of cells is important to understand how they function.
Researchers in the discovAIR project will use several methods of spatially resolved genomics:
Results from the cellular branch will provide the information and genes to look for in more detail on a spatial level.
The results from the spatial branch will be 3D reconstructions of the genetic expression of the tissue we have analysed. We will map cell types that we have identified in the cellular branch to locations within the microstructures of the lung. We will make the results publicly available on a newly formed platform for imaging data to share knowledge, to allow for scientific re-use, and to accelerate the development of novel therapeutic approaches.
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