Cited by 434Genomics and Chromatin DynamicsT-cell and B-cell ImmunologySingle-cell and spatial transcriptomics

The DOI matches its Crossref record; 43 of the 44 references it cites were found in a registry or an index; none of the 13 sources its claims cite is checked for support yet.

Structural cells are key regulators of organ-specific immune responses

Open access

Abstract

The mammalian immune system implements a remarkably effective set of mechanisms for fighting pathogens1. Its main components are haematopoietic immune cells, including myeloid cells that control innate immunity, and lymphoid cells that constitute adaptive immunity2. However, immune functions are not unique to haematopoietic cells, and many other cell types display basic mechanisms of pathogen defence3–5. To advance our understanding of immunology outside the haematopoietic system, here we systematically investigate the regulation of immune genes in the three major types of structural cells: epithelium, endothelium and fibroblasts. We characterize these cell types across twelve organs in mice, using cellular phenotyping, transcriptome sequencing, chromatin accessibility profiling and epigenome mapping. This comprehensive dataset revealed complex immune gene activity and regulation in structural cells. The observed patterns were highly organ-specific and seem to modulate the extensive interactions between structural cells and haematopoietic immune cells. Moreover, we identified an epigenetically encoded immune potential in structural cells under tissue homeostasis, which was triggered in response to systemic viral infection. This study highlights the prevalence and organ-specific complexity of immune gene activity in non-haematopoietic structural cells, and it provides a high-resolution, multi-omics atlas of the epigenetic and transcriptional networks that regulate structural cells in the mouse. Structural cells implement a broad range of immune-regulatory functions beyond their roles as barriers and connective tissues, and they utilize an epigenetically encoded potential for immune gene activation in their rapid response to viral infection.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This study profiles endothelium, epithelium, and fibroblasts across 12 mouse organs and shows that structural cells have widespread, organ-specific immune gene activity and an epigenetically encoded immune potential. This potential is preferentially realized after systemic viral infection and cytokine treatment.

Key findings

  • Multi-omics profiling of three structural cell types across 12 mouse organs revealed extensive cell-type-specific and organ-specific immune gene activity; structural cells from the same organ were globally more similar to each other than to the same cell type across organs.
  • The authors identified 1,665 genes with unrealized epigenetic potential, of which 335 were annotated with at least one immunological term (odds ratio 1.37, P < 10−5, Fisher’s exact test).
  • Genes with unrealized epigenetic potential were overrepresented among genes upregulated after LCMV infection, with the strongest association in liver, lung, and spleen.
  • In cytokine-treatment experiments, IFN-α had the strongest effect; for five of six cytokines (not including IL-3), upregulated genes in spleen endothelium significantly overlapped with genes carrying unrealized epigenetic potential under homeostasis.

Methods

  • C57BL/6J male mice (8–13 weeks old) were used under homeostatic conditions, after intravenous LCMV Clone 13 infection (2×10⁶ focus-forming units, day 8), or after intravenous cytokine treatment (100 μg/kg; IFN-α, IFN-γ, IL-3, IL-6, TGF-β, or TNF; 2 h).
  • Structural cells were purified by standardized FACS sorting using CD31, EpCAM, and GP38 across 12 organs and profiled by Smart-seq2 RNA-seq, ATAC-seq, and H3K4me2 ChIPmentation.
  • Integrative bioinformatics included limma-based differential analysis, Fisher’s exact tests, HOMER motif analysis, gene-regulatory network inference, and receptor–ligand interaction prediction; findings were independently checked against the Tabula Muris dataset.

Limitations

  • The paper states that inferred cell–cell interactions were not experimentally validated, that LCMV viral load was measured by bulk-tissue qPCR and cannot precisely account for organ-specific susceptible-cell frequencies, and that sample size was not statistically predetermined, experiments were not randomized, and investigators were not blinded.
  • The paper notes that structural cells were not well covered in the Tabula Muris validation dataset, and that for lymph node endothelium and thymus fibroblasts only one high-quality ChIPmentation profile could be obtained.
  • Evident from the text: the study is limited to mice, uses male mice, and was performed under specific pathogen-free conditions, which may restrict generalizability.

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Integrity signals

Registry

Crossref · 10.1038/s41586-020-2424-4

Cites

43 of 43 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

62 Own result · 31 Own method · 16 Own interpretation · 5 Not checked yet

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Show all 75 claims

  • It may state two separate claims as one. 18
  • Probably not a substantial claim. 26
39 of 39
  • The paper relies on this without support.

    There has been little systematic investigation of structural cells across organs.

    “However, there has been little systematic investigation across organs, in part because structural cells are difficult to study by genetic ablation due to their essential structural roles in most organs.”
    “However, comparative multi-organ investigations of structural cells have been lacking.”
  • The paper relies on this without support.

    Structural cells are difficult to study by genetic ablation due to their essential structural roles in most organs.

    “However, there has been little systematic investigation across organs, in part because structural cells are difficult to study by genetic ablation due to their essential structural roles in most organs.”
  • The paper relies on this without support.

    Expression of a receptor and its ligand in structural and hematopoietic cells implies potential cell-cell interaction.

    “by inferring a network of potential cell–cell interactions based on known receptor–ligand pairs”
    “The resulting cell–cell interaction network (Fig. 2a, Supplementary Table 3) predicted frequent crosstalk between structural cells and haematopoietic cells under homeostasis (Fig. 2a, Extended Data Fig. 4a).”
  • The paper relies on this without support.

    Low expression with high promoter accessibility indicates an unrealized potential for increased expression.

    “We then scanned for genes with low expression but high promoter accessibility, indicative of an unrealized potential for increased expression (Fig. 3d, e, Extended Data Fig. 7a).”
    “In total, we identified 1,665 genes that fulfilled our definition of unrealized epigenetic potential, of which 335 genes were annotated with at least one immunological term (odds ratio 1.37, P < 10−5, Fisher’s exact test).”
  • The paper relies on this without support.

    The correlation between gene expression and promoter accessibility can be used to quantify epigenetic potential across cell types and organs.

    “To quantify and compare the epigenetic potential across cell types and organs (Fig. 3g), we exploited that genes with strong unrealized potential are outliers when plotting gene expression against promoter accessibility, which results in a reduced correlation between the two data types (Extended Data Fig. 7a).”
  • The authors state this as an assumption.

    LCMV infection, a systemic infection model, affects structural cells in most or all investigated organs through direct effects (structural cells may get infected) and indirect effects (structural cells respond to aspects of tissue-specific and systemic infection).

    “This analysis was based on the hypothesis that LCMV infection – which is widely regarded as a systemic infection model – will affect structural cells in most or all investigated organs through direct effects (structural cells may get infected) as well as indirect effects (structural cells respond to aspects of tissue-specific and systemic infection).”
  • The paper relies on this without support.

    Transcription factors can play a relevant regulatory role despite low or undetectable RNA expression levels.

    “No regulators were excluded based on low or undetectable RNA expression levels, given that transcription factors can play a relevant regulatory role despite low expression levels.”
7 of 7

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Citations

Cites

Show all 44 references

Research works printed but not linked: 2

  1. Abbas, A. K., Lichtman, A. H. & Pillai, S. Cellular and Molecular Immunology 9th edn (Elsevier, 2017).
  2. Pawlina, W. & Ross, M. H. Histology: a Text and Atlas, International Edition: with Correlated Cell and Molecular Biology (Wolters Kluwer Law & Business, 2019).

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Metadata

Authors
Krausgruber, T., Fortelny, N., Fife-Gernedl, V., Senekowitsch, M., Schuster, L. C., Lercher, A., Nemc, A., Schmidl, C., Rendeiro, A. F., Bergthaler, A., & Bock, C.
Affiliations
Austrian Academy of Sciences (AT)
Corresponding author
Bock, Christoph
Venue
Nature
Published
2020-07-01
Volume
583
Issue
7815
Pages
296-302
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
OpenAlex
W3038974679
Cited by
434
References
44
Citations by year
2026: 39 · 2025: 79 · 2024: 64 · 2023: 63 · 2022: 81 · 2021: 90 · 2020: 18
FWCI
20.44
Type
journal article
Language
en
Open access
Locations
  • Nature (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Keywords
structural cells, epithelium, endothelium, fibroblasts, immune gene regulation, epigenetic regulation, chromatin accessibility, tissue homeostasis, viral infection, mouse organs
MeSH terms
Epigenome, Animals, Chromatin, Endothelium, Epithelial Cells, Female, Fibroblasts, Gene Expression Regulation, Hematopoietic Stem Cells, Immune System, Immunity, Innate, Lymphocytic Choriomeningitis, Lymphocytic choriomeningitis virus, Male, Organ Specificity, Transcription, Genetic, Epigenesis, Genetic, Mice, Gene Regulatory Networks, Adaptive Immunity, Transcriptome

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