Can a human organ be mapped on a single-cell level, to learn about the functionality of each individual cell? And can we learn how different these cells are from person to person? International researchers have taken up this challenge and developed the Human Lung Cell Atlas, using artificial intelligence (AI)-based techniques. This atlas elucidates the diversity of single lung cell types and allows learning about lung biology in health and disease.
Astrid Eckert / TUM Single-cell technologies, developed in the past decade, enable researchers to study tissues at the resolution of individual cells, giving insight into the different functions of cells that make a whole organ do its job. However, generating a single-cell dataset is time-consuming and expensive, and generally, only a few individuals are included in each study. An international team of researchers now created a single-cell atlas of the human lung by combining 49 different published and newly generated datasets. This provided insight into the wide variety of cells and cell types existing in our lungs.
Prof. Fabian Theis, Head of the Computational Health Center, Director of the Institute of Computational Biology at Helmholtz Munich and Professor at the Technical University of Munich (TUM), explains the project: "We have created a first integrated reference atlas of the human lung, which includes data from more than a hundred healthy people and reveals how the cells from individuals vary with age, sex, and smoking history. The sheer numbers of cells and individuals involved now gives us the power to see rare cell types and identify new cell states that have not previously been described." Dr Malte Lücken, Group leader at the Institute of Computational Biology and the Institute of Lung Health & Immunity at Helmholtz Munich adds: "A comprehensive organ atlas requires many datasets to capture the diversity between both cells and individuals, but combining different datasets is a huge challenge. We developed a benchmarking pipeline to find the optimal method to integrate all datasets into the atlas, using artificial intelligence, and combined knowledge and data from almost 40 previous lung studies."
While the core of the Human Lung Cell Atlas is data from healthy lungs, the team also took datasets from more than 10 different lung diseases and used machine learning to project these onto the healthy data, in order to understand disease states. It thereby offers a uniquely rich picture of how diseased lungs differ from healthy ones and provides pointers for potential therapeutic targets.
Prof. Martijn Nawijn, a senior author on the paper and Professor at the University Medical Center Groningen, the Netherlands, said: "This is the first effort to compare healthy and diseased lungs in one study in an integrated way. Our study not only supports the presence of lung fibrosis in COVID-19, it allows us to identify and define a shared cell state between lung fibrosis, COVID-19 and lung cancer patients. Finding these shared disease-associated cells is really exciting, and reveals a totally different way of looking at lung diseases, opening possibilities for novel treatment targets and developing treatment response biomarkers. Our findings also suggest that therapies working for one disease may help alleviate others."
Joining Forces by Joining Datasets
By pooling and integrating all the bits of knowledge and data that had been generated previously, the researchers created the first integrated Human Lung Cell Atlas: For each of the 2.4 million cells in this atlas, they know which genes were active in which cell, thereby learning about the functionality of those cells. This enabled studies of how the cells from individuals vary with age, sex, or disease. For example, first author Lisa Sikkema from the Institute of Computational Biology and the scientific team saw that monocyte-derived macrophages (a specific type of immune cell) showed activity of similar genes in cancer, COVID-19, and lung fibrosis, likely playing a role in scar formation in the lung in all three diseases. Therapies working in one disease may therefore also be effective in mitigating the others. Sikkema remarks: "One of the big problems in creating the integrated lung cell atlas was with cell type annotation. Different research groups used different names for the same cell type, or the same name for different cells, so as a team we worked to standardize them using the data in the atlas. The atlas is a first step towards a consensus annotation of the human lung, which will help bring together the field of lung research."
The Lung Atlas Integration project was a large collaborative effort with nearly 100 partners from more than 60 departments involved internationally, including key researchers from the University Medical Center Groningen and Northwestern University. The team is part of the Human Cell Atlas Lung Biological Network, which has its roots in the Chan Zuckerberg Initiative Seed Networks for the HCA, and the European Union funded lung network DiscovAIR. At the start of the pandemic in 2020, the single-cell lung communities came together rapidly, forming the HCA Lung Biological Network to help understand COVID-19, which then catalyzed the effort to integrate all the data.
A Central Resource for Understanding Human Lungs in Health and Disease
The researchers made the atlas fully publicly available, and it is expected to serve as a central resource for doctors and scientists that want to better understand lung biology in health and disease and develop further studies. Dr Alexander Misharin, a senior author on the paper and Associate Professor of Medicine at Northwestern University Feinberg School of Medicine, USA, said: "The Human Lung Cell Atlas is a huge resource for the scientific and medical community. Openly available to researchers, new disease data can be mapped onto the HLCA, transforming research into lung biology and disease. As the first whole reference atlas of a major organ, the HLCA also represents a milestone towards achieving a full Human Cell Atlas which will transform our understanding of biology and disease and lay the foundation for a new era of healthcare".
Altogether, the Human Lung Cell Atlas serves as the first example of how large-scale human cell atlases can progress current and future research on human health and disease.
L. Sikkema, D. Strobl, L. Zappia, E. Madissoon, N.S. Markov, L. Zaragosi, M. Ansari, M. Arguel, L. Apperloo, C. Bécavin, M. Berg, E. Chichelnitskiy, M. Chung, A. Collin, A.C.A. Gay, B. Hooshiar Kashani, M. Jain, T. Kapellos, T.M. Kole, C. Mayr, M. von Papen, L. Peter, C. Ramírez-Suástegui, J. Schniering, C. Taylor, T. Walzthoeni, C. Xu, LT. Bui, C. de Donno, L. Dony, M. Guo, A.J. Gutierrez, L. Heumos, N. Huang, I. Ibarra, N. Jackson, P. Kadur Lakshminarasimha Murthy, M. Lotfollahi, T. Tabib, C. Talavera-Lopez, K. Travaglini, A. Wilbrey-Clark, K.B. Worlock, M. Yoshida, Lung Biological Network Consortium, T. Desai, O. Eickelberg, C. Falk, N. Kaminski, M. Krasnow, R. Lafyatis, M. Nikolíc, J. Powell, J. Rajagopal, O. Rozenblatt-Rosen, M.A. Seibold, D. Sheppard, S.A. Teichmann, A. Tsankov, J. Whitsett, Y. Xu, N.E. Banovich, P. Barbry, T.E. Duong, K.B. Meyer, J.A. Kropski, D. Pe'er, H.B. Schiller, P.R. Tata, J.L. Schultze, A.V. Misharin, M.C. Nawijn, M.D. Luecken, F. Theis (2023): An integrated cell atlas of the lung in health and disease. Nature Medicine. DOI:10.1038/s41591-023-02327-2
The Human Cell Atlas (HCA) is an international collaborative consortium which is creating comprehensive reference maps of all human cells - the fundamental units of life - as a basis for understanding human health and for diagnosing, monitoring, and treating disease. The HCA is likely to impact every aspect of biology and medicine, propelling translational discoveries and applications and ultimately leading to a new era of precision medicine. The HCA was co-founded in 2016 by Dr. Sarah Teichmann at the Wellcome Sanger Institute (UK) and Dr. Aviv Regev, then at the Broad Institute of MIT and Harvard (USA). A truly global initiative, there are now more than 2,900 HCA members, from 94 countries around the world. https://www.humancellatlas.org/
