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

Angelidis, Ilias; Simon, Lukas M.; Fernandez, Isis E.; Strunz, Maximilian; Mayr, Christoph H.; Greiffo, Flavia R.; Tsitsiridis, George; Graf, Elisabeth; Strom, Tim-Matthias; Eickelberg, Oliver; Mann, Matthias; Theis, Fabian J.; Schiller, Herbert B.

doi:10.1101/351353

Cited by 106 publications

(197 citation statements)

References 63 publications

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“…The recently developed SoupX (preprint: Young & Behjati, 2018) uses this approach to directly correct the count data. Pragmatic approaches that ignore strongly ambient genes in downstream analysis have also been used to tackle this problem (Angelidis et al, 2019).…”

Section: Quality Controlmentioning

confidence: 99%

Current best practices in single‐cell RNA‐seq analysis: a tutorial

Luecken

Theis

2019

Molecular Systems Biology

1,604

1,386

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Single‐cell RNA ‐seq has enabled gene expression to be studied at an unprecedented resolution. The promise of this technology is attracting a growing user base for single‐cell analysis methods. As more analysis tools are becoming available, it is becoming increasingly difficult to navigate this landscape and produce an up‐to‐date workflow to analyse one's data. Here, we detail the steps of a typical single‐cell RNA ‐seq analysis, including pre‐processing (quality control, normalization, data correction, feature selection, and dimensionality reduction) and cell‐ and gene‐level downstream analysis. We formulate current best‐practice recommendations for these steps based on independent comparison studies. We have integrated these best‐practice recommendations into a workflow, which we apply to a public dataset to further illustrate how these steps work in practice. Our documented case study can be found at https://www.github.com/theislab/single-cell-tutorial . This review will serve as a workflow tutorial for new entrants into the field, and help established users update their analysis pipelines.

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Section: Quality Controlmentioning

confidence: 99%

Current best practices in single‐cell RNA‐seq analysis: a tutorial

Luecken

Theis

2019

Molecular Systems Biology

1,604

1,386

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“…The 58 identified cell populations included 15 epithelial (clusters 1-15), 9 endothelial (16-24), 9 stromal (25)(26)(27)(28)(29)(30)(31)(32)(33), and 25 immune populations, greater than the number of classical cell types in each compartment (11 epithelial, 5 endothelial, 7 stromal, 20 immune, and 2 neuronal cell types) (Table S2). Using extant markers for the classical cell types and/or the homologous cell types in mice (Table S1) and single molecule fluorescence in situ hybridization, Travaglini et al,p.…”

Section: Transcriptomes Of Nearly All Of the 45 Previously Known Humamentioning

confidence: 99%

“…Although initial scRNAseq studies focused on specific cell types, tissue compartments, and biological processes, large scale molecular cell atlases of organs and even whole organisms are now possible because of improvements in throughput and cost that allow expression profiling of thousands of individual cells, without cell purification or prior knowledge of cell identity to obtain expression profiles of at least the most abundant and easy to isolate cell types [15][16][17][18][19][20][21][22][23][24][25][26][27] . Perhaps the greatest current challenge is obtaining profiles of rare and fragile cell types, or even just assessing the "completeness" of a molecular cell atlas.…”

Section: Introductionmentioning

confidence: 99%

A molecular cell atlas of the human lung from single cell RNA sequencing

Travaglini

Nabhan

Penland

et al. 2019

Preprint

140

182

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Although single cell RNA sequencing studies have begun providing compendia of cell expression profiles, it has proven more difficult to systematically identify and localize all molecular cell types in individual organs to create a full molecular cell atlas. Here we describe droplet-and plate-based single cell RNA sequencing applied to ~70,000 human lung and blood cells, combined with a multi-pronged cell annotation approach, which have allowed us to define the gene expression profiles and anatomical locations of 58 cell populations in the human lung, including 41 of 45 previously known cell types or subtypes and 14 new ones. This comprehensive molecular atlas elucidates the biochemical functions of lung cell types and the cell-selective transcription factors and optimal markers for making and monitoring them; defines the cell targets of circulating hormones and predicts local signaling interactions including sources and targets of chemokines in immune cell trafficking and expression changes on lung homing; and identifies the cell types directly affected by lung disease genes. Comparison to mouse identified 17 molecular types that appear to have been gained or lost during lung evolution and others whose expression profiles have been substantially altered, revealing extensive plasticity of cell types and cell-type-specific gene expression during organ evolution including expression switches between cell types. This lung atlas provides the molecular foundation for investigating how lung cell identities, functions, and interactions are achieved in development and tissue engineering and altered in disease and evolution. certified by peer review)

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“…While the pulmonary tissue is capable of surviving influenza-associated challenges, elderly patients have an increased risk of developing agerelated disorders including persistent lung injury, skeletal muscle dysfunction leading to immobility, dementia, and cognitive impairment. Although recent transcriptomic and proteomics analyses have begun to highlight differences among the more than 40 cell types that comprise the lungs (3,7) as well as their respective response to aging (7), the complexity of this organ complicates our ability to ascertain the underlying cause for this increased susceptibility to pneumonia and other diseases (6,8,9).…”

Section: Introductionmentioning

confidence: 99%

“…Recently, the lifespan extending drug, metformin, was shown to protect the lung from oxidative stress by inhibiting the activity of the mitochondrial complex I leading to a reduction in reactive oxygen species (ROS) emergent from the complex I machinery (35,38,39). It is now apparent that changes in the cellular transcriptome (3,7,40), proteome (7,40), stress-related PN pathways (2,6,17,41) and mitochondrial pathways (12,(34)(35)(36)39,(42)(43)(44)(45)(46) can have complex effects on the functionality of the lung (19,(47)(48)(49)(50)(51). However, the nature of the age-associated changes that contribute to the differential sensitivity of young and old lungs to influenza and resulting pneumonia pathophysiology remain enigmatic.…”

Section: Introductionmentioning

confidence: 99%

Proteostasis and Energetics as Proteome Hallmarks of Aging and Influenza Challenge in Pulmonary Disease

Loguercio

Hutt

Campos

et al. 2019

Preprint

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Aging is associated with an increased risk for the development of many diseases. This is exemplified by the increased incidence of lung injury, muscle dysfunction and cognitive impairment in the elderly following influenza infection. Because the infectious cycle of flu is dependent upon the properties of the host, we examined the proteome of alveolar macrophages (AM) and type 2 cells (AT2) obtained from young (3 months) and old (18 months) naïve mice and mice exposed to influenza A. Our proteomics data show that there is a maladaptive collapse of the proteostasis network (PN) and changes in mitochondrial pathways in the aged naïve AM and AT2 proteomes. The mitochondrial imbalance and proteostatic collapse seen in aged cells places an excessive folding burden on these cells, which is further exacerbated following exposure to influenza A. Specifically, we see an imbalance in Hsp70 co-chaperones involved in protein folding and Hsp90 co-chaperones important for stress signaling pathways that are essential for cellular protection during aging. The acute challenge of influenza A infection of young and aged AM and AT2 cells reveals that age-associated changes in the chaperome affect the ability of these cells to properly manage the infection and post-infection biology, contributing to cytotoxicity. We posit that proteomic profiling of individual cell type specific responses provides a high impact approach to pinpoint fundamental molecular relationships that may contribute to the susceptibility to aging and environmental stress, providing a platform to identify new targets for therapeutic intervention to improve resiliency in the elderly.

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

Cited by 106 publications

References 63 publications

Current best practices in single‐cell RNA‐seq analysis: a tutorial

Current best practices in single‐cell RNA‐seq analysis: a tutorial

A molecular cell atlas of the human lung from single cell RNA sequencing

Proteostasis and Energetics as Proteome Hallmarks of Aging and Influenza Challenge in Pulmonary Disease

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