Abstract
Single-cell ribonucleic acid sequencing is becoming widely employed to study biological processes at a novel resolution depth. The ability to analyse transcriptomes of multiple heterogeneous cell types in parallel is especially valuable for cell-focused lung research where a variety of resident and recruited cells are essential for maintaining organ functionality. We compared the single-cell transcriptomes from publicly available and unpublished datasets of the lungs in six different species: human (Homo sapiens), African green monkey (Chlorocebus sabaeus), pig (Sus domesticus), hamster (Mesocricetus auratus), rat (Rattus norvegicus) and mouse (Mus musculus) by employing RNA velocity and intercellular communication based on ligand–receptor co-expression, among other techniques. Specifically, we demonstrated a workflow for interspecies data integration, applied a single unified gene nomenclature, performed cell-specific clustering and identified marker genes for each species. Overall, integrative approaches combining newly sequenced as well as publicly available datasets could help identify species-specific transcriptomic signatures in both healthy and diseased lung tissue and select appropriate models for future respiratory research.
Abstract
The COVID-19 pandemic led to an increase in publicly available single-cell RNA sequencing data. This review provides an up-to-date framework and readily adoptable tools to measure such data in lungs and compare it with existing data across species. https://bit.ly/3wHCoHe
Footnotes
Provenance: Submitted article, peer reviewed.
Conflict of interest: H. Kirsten reports support for the present manuscript from German Federal Ministry of Education and Research (BMBF) grants e:Med CAPSyS (01ZX1304A) and e:Med SYMPATH (01ZX1906B). E. Wyler has received payment or honoraria for lectures, presentations, speakers’ bureaus, manuscript writing or educational events from Podcast Gegenblende by DGB, outside the submitted work. M. Landthaler reports support for the present manuscript from Berlin Institute of Health. M. Scholz has received grants or contracts from Pfizer Inc. for a project not related to this research. W.M. Kuebler reports support for the present manuscript from German Research Foundation (KU 1218/9-1, KU 1218/11-1, CRC TR84 A02, CRC TR84 C09, CRC 1449 B01), Germany Ministry for Research and Education (SYMPATH, PROVID consortia), German Center for Cardiovascular Research (Partner site project Berlin) and Berlin Institute of Health (Focus Area Vascular Biology). M. Witzenrath has received grants or contracts from Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, Deutsche Gesellschaft für Pneumologie, European Respiratory Society, Marie Curie Foundation, Else Kröner Fresenius Stiftung, Capnetz Stiftung, International Max Planck Research School, Quark Pharma, Takeda Pharma, Noxxon, Pantherna, Silence Therapeutics, Vaxxilon, Actelion, Bayer Health Care, Biotest and Boehringer Ingelheim, outside the submitted work. M. Witzenrath has received personal fees for consulting from Noxxon, Pantherna, Silence Therapeutics, Vaxxilon, Aptarion, GlaxoSmithKline, Sinoxa and Biotest, and for lectures, presentations, speakers’ bureaus, manuscript writing or educational events from AstraZeneca, Berlin Chemie, Chiesi, Novartis, Teva, Actelion, Boehringer Ingelheim, GlaxoSmithKline, Biotest and Bayer Health Care, outside the submitted work. M. Witzenrath has the following patents planned, issued or pending: EPO 12181535.1: IL-27 for modulation of immune response in acute lung injury (issued: 2012); WO/2010/094491: Means for inhibiting the expression of Ang-2 (issued: 2010); and DE 102020116249.9: Camostat/Niclosamide cotreatment in SARS-CoV-2 infected human lung cells (issued: 2020/21). G. Nouailles receives funding from Biotest AG for a project not related to this work. All other authors have nothing to disclose.
Support statement: G. Nouailles and M. Witzenrath are supported by the German Federal Ministry of Education and Research (BMBF) and the Agence nationale de la recherche (ANR) in the framework of MAPVAP (16GW0247). M. Witzenrath is supported by the German Research Foundation (DFG) grants SFB-TR84 C06, C09, and SFB-1449 B02; the BMBF in the framework of e:Med CAPSyS (01ZX1604B), PROVID (01KI20160A), e:Med SYMPATH (01ZX1906A) and NUM-NAPKON (01KX2021); the BIH (CM-COVID). J. Trimpert is supported by DFG grant number SFB-TR84 Z01b. M-F. Mashreghi receives funding from the State of Berlin and the “European Regional Development Fund” with grant ERDF 2014-2020, EFRE 1.8/11. M-F. Mashreghi is part of the Leibniz Association (Leibniz Collaborative Excellence, TargArt). W.M. Kuebler receives funding from the DFG (SFB-TR84 A02 and C09, SFB 1449 B01, KU1218/9-1 and KU1218/11-1), the BMBF in the framework of e:Med SYMPATH (01ZX1906A), PROVID (01KI20160A), and the German Center for Cardiovascular Research (DZHK) Partner site Berlin. N. Suttorp is supported by DFG (grant number SFB-TR84 B01, C09 and Z02) and BMBF (e:Med CAPSyS grants 01ZX1304B and 01ZX1604B). M. Scholz and H. Kirsten are supported by the BMBF in the framework of e:Med CAPSyS (01ZX1304A), e:Med SYMPATH (01ZX1906B) and V.D. Friedrich within the project “Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) Dresden/Leipzig” (01IS18026B). K. Hoenzke was supported by the SFB-TR84 (DFG), “NUM-COVID 19 Organo-Strat” (BMBF), Charité 3R and the “Einstein Center 3R” (Einstein Foundation Berlin). A.C. Hocke and S. Hippenstiel were supported by Berlin University Alliance GC2 Global Health (Corona Virus Pre-Exploration Project), the SFB-TR84 (DFG), RAPID and “NUM-COVID 19 Organo-Strat” (BMBF) as well as the Berlin Institute of Health (BIH), Charité 3R and the “Einstein Center 3R” (Einstein Foundation Berlin). P. Pennitz and C. Goekeri are supported by Charité 3R. Funding information for this article has been deposited with the Crossref Funder Registry.
- Received March 28, 2022.
- Accepted May 16, 2022.
- Copyright ©The authors 2022
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- Article
- Abstract
- Abstract
- Introduction
- Basic principles of pulmonary single-cell isolation, barcoding and sequencing
- Data processing and analysis
- Exemplary workflow for multispecies data pre-processing and integration
- Cross-species analysis of human and nonhuman scRNA-seq data
- Outlook
- Supplementary material
- Acknowledgements
- Footnotes
- References
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