Below an overview of the discovAIR publications

Integrative analysis of cell state changes in lung fibrosis with peripheral protein biomarkers

Christoph H Mayr, Lukas M Simon, Gabriela Leuschner, Meshal Ansari, Janine Schniering, Philipp E Geyer, Ilias Angelidis, Maximilian Strunz, Pawandeep Singh, Nikolaus Kneidinger, Frank Reichenberger, Edith Silbernagel, Stephan Böhm, Heiko Adler, Michael Lindner, Britta Maurer, Anne Hilgendorff, Antje Prasse, Jürgen Behr, Matthias Mann, Oliver Eickelberg, Fabian J Theis, Herbert B Schiller

The correspondence of cell state changes in diseased organs to peripheral protein signatures is currently unknown. Here, we generated and integrated single‐cell transcriptomic and proteomic data from multiple large pulmonary fibrosis patient cohorts. Integration of 233,638 single‐cell transcriptomes (n = 61) across three independent cohorts enabled us to derive shifts in cell type proportions and a robust core set of genes altered in lung fibrosis for 45 cell types. Mass spectrometry analysis of lung lavage fluid (n = 124) and plasma (n = 141) proteomes identified distinct protein signatures correlated with diagnosis, lung function, and injury status. A novel SSTR2+ pericyte state correlated with disease severity and was reflected in lavage fluid by increased levels of the complement regulatory factor CFHR1. We further discovered CRTAC1 as a biomarker of alveolar type‐2 epithelial cell health status in lavage fluid and plasma. Using cross‐modal analysis and machine learning, we identified the cellular source of biomarkers and demonstrated that information transfer between modalities correctly predicts disease status, suggesting feasibility of clinical cell state monitoring through longitudinal sampling of body fluid proteomes.

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Single-cell meta-analysis of SARS-CoV-2 entry genes across tissues and demographics

Christoph Muus, Malte D. Luecken, Gökcen Eraslan, Lisa Sikkema, Avinash Waghray, Graham Heimberg, Yoshihiko Kobayashi, Eeshit Dhaval Vaishnav, Ayshwarya Subramanian, Christopher Smillie, Karthik A. Jagadeesh, Elizabeth Thu Duong, Evgenij Fiskin, Elena Torlai Triglia, Meshal Ansari, Peiwen Cai, Brian Lin, Justin Buchanan, Sijia Chen, Jian Shu, Adam L. Haber, Hattie Chung, Daniel T. Montoro, Taylor Adams, Hananeh Aliee, Samuel J. Allon, Zaneta Andrusivova, Ilias Angelidis, Orr Ashenberg, Kevin Bassler, Christophe Bécavin, Inbal Benhar, Joseph Bergenstråhle, Ludvig Bergenstråhle, Liam Bolt, Emelie Braun, Linh T. Bui, Steven Callori, Mark Chaffin, Evgeny Chichelnitskiy, Joshua Chiou, Thomas M. Conlon, Michael S. Cuoco, Anna S. E. Cuomo, Marie Deprez, Grant Duclos, Denise Fine, David S. Fischer, Shila Ghazanfar, Astrid Gillich, Bruno Giotti, Joshua Gould, Minzhe Guo, Austin J. Gutierrez, Arun C. Habermann, Tyler Harvey, Peng He, Xiaomeng Hou, Lijuan Hu, Yan Hu, Alok Jaiswal, Lu Ji, Peiyong Jiang, Theodoros S. Kapellos, Christin S. Kuo, Ludvig Larsson, Michael A. Leney-Greene, Kyungtae Lim, Monika Litviňuková, Leif S. Ludwig, Soeren Lukassen, Wendy Luo, Henrike Maatz, Elo Madissoon, Lira Mamanova, Kasidet Manakongtreecheep, Sylvie Leroy, Christoph H. Mayr, Ian M. Mbano, Alexi M. McAdams, Ahmad N. Nabhan, Sarah K. Nyquist, Lolita Penland, Olivier B. Poirion, Sergio Poli, CanCan Qi, Rachel Queen, Daniel Reichart, Ivan Rosas, Jonas C. Schupp, Conor V. Shea, Xingyi Shi, Rahul Sinha, Rene V. Sit, Kamil Slowikowski, Michal Slyper, Neal P. Smith, Alex Sountoulidis, Maximilian Strunz, Travis B. Sullivan, Dawei Sun, Carlos Talavera-López, Peng Tan, Jessica Tantivit, Kyle J. Travaglini, Nathan R. Tucker, Katherine A. Vernon, Marc H. Wadsworth, Julia Waldman, Xiuting Wang, Ke Xu, Wenjun Yan, William Zhao, Carly G. K. Ziegler, The NHLBI LungMap Consortium & The Human Cell Atlas Lung Biological Network

Angiotensin-converting enzyme 2 (ACE2) and accessory proteases (TMPRSS2 and CTSL) are needed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cellular entry, and their expression may shed light on viral tropism and impact across the body. We assessed the cell-type-specific expression of ACE2, TMPRSS2 and CTSL across 107 single-cell RNA-sequencing studies from different tissues. ACE2, TMPRSS2 and CTSL are coexpressed in specific subsets of respiratory epithelial cells in the nasal passages, airways and alveoli, and in cells from other organs associated with coronavirus disease 2019 (COVID-19) transmission or pathology. We performed a meta-analysis of 31 lung single-cell RNA-sequencing studies with 1,320,896 cells from 377 nasal, airway and lung parenchyma samples from 228 individuals. This revealed cell-type-specific associations of age, sex and smoking with expression levels of ACE2, TMPRSS2 and CTSL. Expression of entry factors increased with age and in males, including in airway secretory cells and alveolar type 2 cells. Expression programs shared by ACE2+TMPRSS2+ cells in nasal, lung and gut tissues included genes that may mediate viral entry, key immune functions and epithelial–macrophage cross-talk, such as genes involved in the interleukin-6, interleukin-1, tumor necrosis factor and complement pathways. Cell-type-specific expression patterns may contribute to the pathogenesis of COVID-19, and our work highlights putative molecular pathways for therapeutic intervention.

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A Single-Cell Atlas of the Human Healthy Airways

Marie Deprez, Laure-Emmanuelle Zaragosi, Marin Truchi, Christophe Becavin, Sandra Ruiz García, Marie-Jeanne Arguel, Magali Plaisant, Virginie Magnone, Kevin Lebrigand, Sophie Abelanet, Frédéric Brau, Agnès Paquet, Dana Pe'er, Charles-Hugo Marquette, Sylvie Leroy, Pascal Barbry

Rationale: The respiratory tract constitutes an elaborate line of defense that is based on a unique cellular ecosystem.
Objectives: We aimed to investigate cell population distributions and transcriptional changes along the airways by using single-cell RNA profiling.
Methods: We have explored the cellular heterogeneity of the human airway epithelium in 10 healthy living volunteers by single-cell RNA profiling. A total of 77,969 cells were collected at 35 distinct locations, from the nose to the 12th division of the airway tree.
Measurements and Main Results: The resulting atlas is composed of a high percentage of epithelial cells (89.1%) but also immune (6.2%) and stromal (4.7%) cells with distinct cellular proportions in different regions of the airways. It reveals differential gene expression between identical cell types (suprabasal, secretory, and multiciliated cells) from the nose (MUC4, PI3, SIX3) and tracheobronchial (SCGB1A1, TFF3) airways. By contrast, cell-type-specific gene expression is stable across all tracheobronchial samples. Our atlas improves the description of ionocytes, pulmonary neuroendocrine cells, and brush cells and identifies a related population of NREP-positive cells. We also report the association of KRT13 with dividing cells that are reminiscent of previously described mouse "hillock" cells and with squamous cells expressing SCEL and SPRR1A/B.
Conclusions: Robust characterization of a single-cell cohort in healthy airways establishes a valuable resource for future investigations. The precise description of the continuum existing from the nasal epithelium to successive divisions of the airways and the stable gene expression profile of these regions better defines conditions under which relevant tracheobronchial proxies of human respiratory diseases can be developed.

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Longitudinal Multi-omics Analyses Identify Responses of Megakaryocytes, Erythroid Cells, and Plasmablasts as Hallmarks of Severe COVID-19

Joana P. Bernardes, Neha Mishra, Florian Tran, Thomas Bahmer, Lena Best, Johanna I. Blase, Dora Bordoni, Jeanette Franzenburg, Ulf Geisen, Jonathan Josephs-Spaulding, Philipp Köhler, Axel Künstner, Elisa Rosati, Anna C. Aschenbrenner, Petra Bacher, Nathan Baran, Teide Boysen, Burkhard Brandt, Niklas Bruse, Jonathan Dörr, Andreas Dräger, Gunnar Elke, David Ellinghaus, Julia Fischer, Michael Forster, Andre Franke, Sören Franzenburg, Norbert Frey, Anette Friedrichs, Janina Fuß, Andreas Glück, Jacob Hamm, Finn Hinrichsen, Marc P. Hoeppner, Simon Imm, Ralf Junker, Sina Kaiser, Ying H. Kan, Rainer Knoll, Christoph Lange, Georg Laue, Clemens Lier, Matthias Lindner, Georgios Marinos, Robert Markewitz, Jacob Nattermann, Rainer Noth, Peter Pickkers, Klaus F. Rabe, Alina Renz, Christoph Röcken, Jan Rupp, Annika Schaffarzyk, Alexander Scheffold, Jonas Schulte-Schrepping, Domagoj Schunk, Dirk Skowasch, Thomas Ulas, Klaus-Peter Wandinger, Michael Wittig, Johannes Zimmermann, Hauke Busch, Bimba F. Hoyer, Christoph Kaleta, Jan Heyckendorf, Matthijs Kox, Jan Rybniker, Stefan Schreiber, Joachim L. Schultze, and Philip Rosenstiel, HCA Lung Biological Network, and the Deutsche COVID-19 Omics Initiative (DeCOI)

Temporal resolution of cellular features associated with a severe COVID-19 disease trajectory is needed for understanding skewed immune responses and defining predictors of outcome. Here, we performed a longi- tudinal multi-omics study using a two-center cohort of 14 patients. We analyzed the bulk transcriptome, bulk DNA methylome, and single-cell transcriptome (>358,000 cells, including BCR profiles) of peripheral blood samples harvested from up to 5 time points. Validation was performed in two independent cohorts of COVID-19 patients. Severe COVID-19 was characterized by an increase of proliferating, metabolically hyper- active plasmablasts. Coinciding with critical illness, we also identified an expansion of interferon-activated circulating megakaryocytes and increased erythropoiesis with features of hypoxic signaling. Megakaryo- cyte- and erythroid-cell-derived co-expression modules were predictive of fatal disease outcome. The study demonstrates broad cellular effects of SARS-CoV-2 infection beyond adaptive immune cells and provides an entry point toward developing biomarkers and targeted treatments of patients with COVID-19.

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SCRINSHOT enables spatial mapping of cell states in tissue sections with single-cell resolution

Alexandros Sountoulidis, Andreas Liontos, Hong Phuong Nguyen, Alexandra B. Firsova, Athanasios Fysikopoulos, Xiaoyan Qian, Werner Seeger, Erik Sundström, Mats Nilsson, Christos Samakovlis 

Changes in cell identities and positions underlie tissue development and disease progression. Although single-cell mRNA sequencing (scRNA-Seq) methods rapidly generate extensive lists of cell states, spatially resolved single-cell mapping presents a challenging task. We developed SCRINSHOT (Single-Cell Resolution IN Situ Hybridization On Tissues), a sensitive, multiplex RNA mapping approach. Direct hybridization of padlock probes on mRNA is followed by circularization with SplintR ligase and rolling circle amplification (RCA) of the hybridized padlock probes. Sequential detection of RCA-products using fluorophore-labeled oligonucleotides profiles thousands of cells in tissue sections. We evaluated SCRINSHOT specificity and sensitivity on murine and human organs. SCRINSHOT quantification of marker gene expression shows high correlation with published scRNA-Seq data over a broad range of gene expression levels. We demonstrate the utility of SCRINSHOT by mapping the locations of abundant and rare cell types along the murine airways. The amenability, multiplexity, and quantitative qualities of SCRINSHOT facilitate single-cell mRNA profiling of cell-state alterations in tissues under a variety of native and experimental conditions.

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Benchmarking atlas-level data integration in single-cell genomics

Luecken MD(1)​,​ Büttner M​(1),​ Chaichoompu K(1),​ Danese A(1),​ Interlandi M(2),​ Mueller MF(1),​ Strobl DC(1),​ Zappia L(1,3),​ Dugas M(2),​ Colomé-Tatché M(1,4,5*), Theis FJ​(1,3,5*)

Cell atlases often include samples that span locations, labs, and conditions, leading to complex, nested batch effects in data. Thus, joint analysis of atlas datasets requires reliable data integration.

Choosing a data integration method is a challenge due to the difficulty of defining integration success. Here, we benchmark 38 method and preprocessing combinations on 77 batches of gene expression, chromatin accessibility, and simulation data from 23 publications, altogether representing >1.2 million cells distributed in nine atlas-level integration tasks. Our integration tasks span several common sources of variation such as individuals, species, and experimental labs. We evaluate methods according to scalability, usability, and their ability to remove batch effects while retaining biological variation.

Using 14 evaluation metrics, we find that highly variable gene selection improves the performance of data integration methods, whereas scaling pushes methods to prioritize batch removal over conservation of biological variation. Overall, BBKNN, Scanorama, and scVI perform well, particularly on complex integration tasks; Seurat v3 performs well on simpler tasks with distinct biological signals; and methods that prioritize batch removal perform best for ATAC-seq data integration. Our freely available reproducible python module can be used to identify optimal data integration methods for new data, benchmark new methods, and improve method development.

(1) Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. (2) Institute of Medical Informatics, University of Münster, Münster, Germany. (3) Dep of Mathematics, Technische Universität München, Garching bei München, Germany. (4) European Research Institute for the Biology of Ageing, University of Groningen, University Medical centre Groningen, Groningen, The Netherlands. (5) TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany. *Correspondence: ​​;


Integrated analyses of single-cell atlases reveal age, gender, and smoking status associations with cell type-specific expression of mediators of SARS-CoV-2 viral entry and highlights inflammatory programs in putative target cells

Christoph Muus*, Malte D. Luecken*, Gokcen Eraslan*, Avinash Waghray*, Graham Heimberg*, Lisa Sikkema*, Yoshihiko Kobayashi*, Eeshit Dhaval Vaishnav*, Ayshwarya Subramanian*, Christopher Smilie*, Karthik Jagadeesh*, Elizabeth Thu Duong*, Evgenij Fiskin*, Elena Torlai Triglia*, Meshal Ansari*, Peiwen Cai*, Brian Lin*, Justin Buchanan*, Sijia Chen*, Jian Shu*, Adam L Haber*, Hattie Chung*, Daniel T Montoro*, et al.
* These authors contributed equally

The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, creates an urgent need for identifying molecular mechanisms that mediate viral entry, propagation, and tissue pathology. Cell membrane bound angiotensin-converting enzyme 2 (ACE2) and associated proteases, transmembrane protease serine 2 (TMPRSS2) and Cathepsin L (CTSL), were previously identified as mediators of SARS-CoV2 cellular entry. Here, we assess the cell type-specific RNA expression of ACE2, TMPRSS2, and CTSL through an integrated analysis of 107 single-cell and single-nucleus RNA-Seq studies, including 22 lung and airways datasets (16 unpublished), and 85 datasets from other diverse organs. Joint expression of ACE2 and the accessory proteases identifies specific subsets of respiratory epithelial cells as putative targets of viral infection in the nasal passages, airways, and alveoli. Cells that co-express ACE2 and proteases are also identified in cells from other organs, some of which have been associated with COVID-19 transmission or pathology, including gut enterocytes, corneal epithelial cells, cardiomyocytes, heart pericytes, olfactory sustentacular cells, and renal epithelial cells. Performing the first meta- analyses of scRNA-seq studies, we analyzed 1,176,683 cells from 282 nasal, airway, and lung parenchyma samples from 164 donors spanning fetal, childhood, adult, and elderly age groups, associate increased levels of ACE2, TMPRSS2, and CTSL in specific cell types with increasing age, male gender, and smoking, all of which are epidemiologically linked to COVID-19 susceptibility and outcomes. Notably, there was a particularly low expression of ACE2 in the few young pediatric samples in the analysis. Further analysis reveals a gene expression program shared by ACE2+TMPRSS2+ cells in nasal, lung and gut tissues, including genes that may mediate viral entry, subtend key immune functions, and mediate epithelial-macrophage cross- talk. Amongst these are IL6, its receptor and co-receptor, IL1R, TNF response pathways, and complement genes. Cell type specificity in the lung and airways and smoking effects were conserved in mice. Our analyses suggest that differences in the cell type-specific expression of mediators of SARS-CoV-2 viral entry may be responsible for aspects of COVID-19 epidemiology and clinical course, and point to putative molecular pathways involved in disease susceptibility and pathogenesis.

This project is funded by
Grant no. 874656

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