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An atlas of the aging lung mapped by single cell transcriptomics and deep tissue proteomics

Author

Listed:
  • Ilias Angelidis

    (Member of the German Center for Lung Research (DZL))

  • Lukas M. Simon

    (Institute of Computational Biology)

  • Isis E. Fernandez

    (Member of the German Center for Lung Research (DZL))

  • Maximilian Strunz

    (Member of the German Center for Lung Research (DZL))

  • Christoph H. Mayr

    (Member of the German Center for Lung Research (DZL))

  • Flavia R. Greiffo

    (Member of the German Center for Lung Research (DZL))

  • George Tsitsiridis

    (Institute of Computational Biology)

  • Meshal Ansari

    (Member of the German Center for Lung Research (DZL)
    Institute of Computational Biology)

  • Elisabeth Graf

    (Institute of Human Genetics)

  • Tim-Matthias Strom

    (Institute of Human Genetics)

  • Monica Nagendran

    (Stanford University School of Medicine)

  • Tushar Desai

    (Stanford University School of Medicine)

  • Oliver Eickelberg

    (University of Colorado)

  • Matthias Mann

    (Max Planck Institute of Biochemistry)

  • Fabian J. Theis

    (Institute of Computational Biology
    Technische Universität München)

  • Herbert B. Schiller

    (Member of the German Center for Lung Research (DZL))

Abstract

Aging promotes lung function decline and susceptibility to chronic lung diseases, which are the third leading cause of death worldwide. Here, we use single cell transcriptomics and mass spectrometry-based proteomics to quantify changes in cellular activity states across 30 cell types and chart the lung proteome of young and old mice. We show that aging leads to increased transcriptional noise, indicating deregulated epigenetic control. We observe cell type-specific effects of aging, uncovering increased cholesterol biosynthesis in type-2 pneumocytes and lipofibroblasts and altered relative frequency of airway epithelial cells as hallmarks of lung aging. Proteomic profiling reveals extracellular matrix remodeling in old mice, including increased collagen IV and XVI and decreased Fraser syndrome complex proteins and collagen XIV. Computational integration of the aging proteome with the single cell transcriptomes predicts the cellular source of regulated proteins and creates an unbiased reference map of the aging lung.

Suggested Citation

  • Ilias Angelidis & Lukas M. Simon & Isis E. Fernandez & Maximilian Strunz & Christoph H. Mayr & Flavia R. Greiffo & George Tsitsiridis & Meshal Ansari & Elisabeth Graf & Tim-Matthias Strom & Monica Nag, 2019. "An atlas of the aging lung mapped by single cell transcriptomics and deep tissue proteomics," Nature Communications, Nature, vol. 10(1), pages 1-17, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-08831-9
    DOI: 10.1038/s41467-019-08831-9
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    Cited by:

    1. Yuanyuan Chen & Reka Toth & Sara Chocarro & Dieter Weichenhan & Joschka Hey & Pavlo Lutsik & Stefan Sawall & Georgios T. Stathopoulos & Christoph Plass & Rocio Sotillo, 2022. "Club cells employ regeneration mechanisms during lung tumorigenesis," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    2. Joschka Hey & Michelle Paulsen & Reka Toth & Dieter Weichenhan & Simone Butz & Jolanthe Schatterny & Reinhard Liebers & Pavlo Lutsik & Christoph Plass & Marcus A. Mall, 2021. "Epigenetic reprogramming of airway macrophages promotes polarization and inflammation in muco-obstructive lung disease," Nature Communications, Nature, vol. 12(1), pages 1-18, December.
    3. Moujtaba Y. Kasmani & Paytsar Topchyan & Ashley K. Brown & Ryan J. Brown & Xiaopeng Wu & Yao Chen & Achia Khatun & Donia Alson & Yue Wu & Robert Burns & Chien-Wei Lin & Matthew R. Kudek & Jie Sun & We, 2023. "A spatial sequencing atlas of age-induced changes in the lung during influenza infection," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    4. Aleksandr Ianevski & Anil K. Giri & Tero Aittokallio, 2022. "Fully-automated and ultra-fast cell-type identification using specific marker combinations from single-cell transcriptomic data," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    5. Seoyeon Lee & Mohammad Naimul Islam & Kaveh Boostanpour & Dvir Aran & Guangchun Jin & Stephanie Christenson & Michael A. Matthay & Walter L. Eckalbar & Daryle J. DePianto & Joseph R. Arron & Liam Mage, 2021. "Molecular programs of fibrotic change in aging human lung," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    6. Jianxin Shi & Kouya Shiraishi & Jiyeon Choi & Keitaro Matsuo & Tzu-Yu Chen & Juncheng Dai & Rayjean J. Hung & Kexin Chen & Xiao-Ou Shu & Young Tae Kim & Maria Teresa Landi & Dongxin Lin & Wei Zheng & , 2023. "Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    7. Christopher W. Murray & Jennifer J. Brady & Mingqi Han & Hongchen Cai & Min K. Tsai & Sarah E. Pierce & Ran Cheng & Janos Demeter & David M. Feldser & Peter K. Jackson & David B. Shackelford & Monte M, 2022. "LKB1 drives stasis and C/EBP-mediated reprogramming to an alveolar type II fate in lung cancer," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    8. Zhoufeng Wang & Zhe Li & Kun Zhou & Chengdi Wang & Lili Jiang & Li Zhang & Ying Yang & Wenxin Luo & Wenliang Qiao & Gang Wang & Yinyun Ni & Shuiping Dai & Tingting Guo & Guiyi Ji & Minjie Xu & Yiying , 2021. "Deciphering cell lineage specification of human lung adenocarcinoma with single-cell RNA sequencing," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    9. Sandra Curras-Alonso & Juliette Soulier & Thomas Defard & Christian Weber & Sophie Heinrich & Hugo Laporte & Sophie Leboucher & Sonia Lameiras & Marie Dutreix & Vincent Favaudon & Florian Massip & Tho, 2023. "An interactive murine single-cell atlas of the lung responses to radiation injury," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    10. Yu Wang & Zhi-Ying Guan & Shao-Wen Shi & Yi-Rong Jiang & Jie Zhang & Yi Yang & Qiong Wu & Jie Wu & Jian-Bo Chen & Wei-Xin Ying & Qin-Qin Xu & Qian-Xi Fan & Hui-Feng Wang & Li Zhou & Ling Wang & Jin Fa, 2024. "Pick-up single-cell proteomic analysis for quantifying up to 3000 proteins in a Mammalian cell," Nature Communications, Nature, vol. 15(1), pages 1-13, December.

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