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

Structural cells are key regulators of organ-specific immune responses

Open access
Krausgruber, Thomas, Fortelny, Nikolaus, Fife-Gernedl, Victoria, Senekowitsch, Martin, Schuster, Linda C., Lercher, Alexander, Nemc, Amelie, Schmidl, Christian +3 more·2020·Nature
DOI 10.1038/s41586-020-2424-4PMC PMC7610345
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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.

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.

Model-written summary. Check it against the paper before relying on it.

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.

Claims the paper makes

0 of 13 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    The epigenetically encoded immune potential in structural cells was triggered in response to systemic viral infection.

    “Moreover, we identified an epigenetically encoded immune potential in structural cells under tissue homeostasis, which was triggered in response to systemic viral infection.”
    Quote in the paperSubstantial claim
  • Findingown data

    Structural cells have unexpectedly diverse capabilities for interacting with hematopoietic cells.

    “We observed widespread expression of immune regulators and cytokine signaling molecules in structural cells, organ-specific adaptation to the tissue environment, and unexpectedly diverse capabilities for interacting with hematopoietic cells.”
    Quote in the paperSubstantial claim
  • Findingown data

    Differences across cell types and organs in the interaction network were driven by characteristic expression patterns of cell-surface proteins and secreted factors in structural cells.

    “Differences across cell types and organs were driven by the characteristic expression patterns of cell-surface proteins and secreted factors in structural cells (Fig. 2b).”
    Quote in the paperSubstantial claim
  • Findingown data

    The inferred cell-cell interaction network predicted frequent crosstalk between structural cells and haematopoietic cells under homeostasis.

    “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).”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Expression of a receptor and its ligand in structural and hematopoietic cells implies potential cell-cell interaction.
  • Findingown data

    Genes affected by the epigenetically encoded immune potential were preferentially upregulated in response to systemic viral infection.

    “Most notably, we found evidence of an epigenetically encoded immune potential under homeostatic conditions, and the affected genes were preferentially upregulated in response to an immunological challenge induced by systemic viral infection.”
    Quote in the paperSubstantial claim
  • May combine two claims. 18
  • Classified as probably not a substantial claim. 26

  • May combine two claims.

    Findingown data

    Structural cells showed expected expression patterns for cell-type-specific marker genes, but with high transcriptional heterogeneity across organs.

    “We also observed the expected expression patterns for various cell-type-specific marker genes, but with a high degree of transcriptional heterogeneity across organs (Extended Data Fig. 3c, Supplementary Table 2).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    All three types of structural cells were detectable in all 12 organs, with strong differences in their relative frequencies.

    “All three types of structural cells were detectable in all 12 organs, with strong differences in their relative frequencies (Fig. 1b, Extended Data Fig. 1c).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    These genes were enriched for immune functions and preferentially upregulated in response to LCMV infection and cytokine administration in vivo.

    “These genes were enriched for immune functions, and they were preferentially upregulated in response to LCMV infection and cytokine administration in vivo.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Low expression with high promoter accessibility indicates an unrealized potential for increased expression.

  • May combine two claims.

    Findingown data

    Genome-wide analysis of chromatin accessibility uncovered a regulatory basis of immune functions of structural cells and an initial assessment of transcriptional regulators that confer cellular identity to endothelial cells, epithelial cells and fibroblasts across 12 organs.

    “Second, our genome-wide analysis of chromatin accessibility in structural cells uncovered not only a regulatory basis of their immune functions, but also an initial assessment of the transcriptional regulators that confer cellular identity to endothelial cells, epithelial cells and fibroblasts across 12 organs.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Organ-specific differences in the association between epigenetic potential and LCMV-induced activation showed no clear correlation with differences in viral load and appear to constitute intrinsic regulatory differences between cell types and organs.

    “These organ-specific differences showed no clear correlation with differences in viral load (Extended Data Fig. 9c) and appear to constitute intrinsic regulatory differences between cell types and organs (Extended Data Fig. 9d).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Together, these data reveal widespread activity of immune genes and regulatory modules in structural cells, which are expected to mediate cell-type-specific and organ-specific interactions with haematopoietic immune cells.

    “Together, these data reveal widespread activity of immune genes and regulatory modules in structural cells, which are expected to mediate cell-type-specific and organ-specific interactions with haematopoietic immune cells.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Expression of a receptor and its ligand in structural and hematopoietic cells implies potential cell-cell interaction.

  • May combine two claims.

    Findingown data

    In total, 1,665 genes fulfilled the definition of 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).

    “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).”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Low expression with high promoter accessibility indicates an unrealized potential for increased expression.

  • Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

    Findingown data

    The study provides a comprehensive characterization of immune gene regulation in structural cells and an initial step towards systematic, organism-scale dissection of immune functions beyond haematopoietic cells.

    “In conclusion, our study provides a comprehensive characterization of immune gene regulation in structural cells, and an initial step towards the systematic, organism-scale dissection of immune functions beyond haematopoietic cells.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    IFN-α treatment had the strongest effect among the six cytokines, inducing known interferon target genes and several genes associated with antiviral immunity.

    “IFN-α treatment had the strongest effect, inducing known interferon target genes and several genes associated with antiviral immunity (Fig. 5b, Extended Data Fig. 10; Supplementary Table 11).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Multi-omics profiling has emerged as a promising approach to dissecting immune regulation in a systematic, genome-wide manner.

    “Multi-omics profiling has emerged as a promising approach to dissecting immune regulation in a systematic, genome-wide manner, as illustrated by recent work on the systems immunology of hematopoietic immune cells12, 13.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [12] Davis, M. M., Tato, C. M. & Furman, D. Systems immunology: just getting started. Nat. Immunol. 18, 725–732 (2017). source

      Not checked in the free run.

    • cites [13] Villani, A. C., Sarkizova, S. & Hacohen, N. Systems immunology: learning the rules of the immune system. Annu. Rev. Immunol. 36, 813–842 (2018). source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Immune functions are not unique to hematopoietic cells; many other cell types display basic mechanisms of pathogen defence.

    “However, immune functions are not unique to hematopoietic cells, and many other cell types display basic mechanisms of pathogen defence3–5.”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [3] Buckley, C. D., Barone, F., Nayar, S., Bénézech, C. & Caamaño, J. Stromal cells in chronic inflammation and tertiary lymphoid organ formation. Annu. Rev. Immunol. 33, 715–745 (2015). source

      Not checked in the free run.

    • cites [4] Pober, J. S. & Sessa, W. C. Evolving functions of endothelial cells in inflammation. Nat. Rev. Immunol. 7, 803–815 (2007). source

      Not checked in the free run.

    • cites [5] Schleimer, R. P., Kato, A., Kern, R., Kuperman, D. & Avila, P. C. Epithelium: at the interface of innate and adaptive immune responses. J. Allergy Clin. Immunol. 120, 1279–1284 (2007). source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Specific emphasis was put on ensuring high purity of the structural cell transcriptomes while minimizing the risk and impact of potential contaminations.

    “Specific emphasis was put on ensuring high purity of the structural cell transcriptomes, while minimizing the risk and impact of potential contaminations (e.g., due to cell-free RNA released by dying cells or as the result of potential impurities during FACS purification of the structural cell populations).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    To avoid biases due to differences in peak size, all regions were standardized to 500 base pairs around the center of the peak.

    “To avoid biases due to differences in peak size, all regions were standardized to 500 base pairs around the center of the peak.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    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.

    “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.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Transcription factors can play a relevant regulatory role despite low or undetectable RNA expression levels.

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductreasoning

    Samples with detectable contamination by hematopoietic immune cells were automatically discarded, and replacement samples were generated until three uncontaminated samples were available for each cell type in each organ.

    “Samples with detectable contamination by hematopoietic immune cells were automatically discarded, and replacement samples were generated until three uncontaminated samples were available for each cell type in each organ.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    Residual contamination in retained ATAC-seq and ChIPmentation samples was computationally corrected by regressing out epigenomic signatures of hematopoietic immune cells from the matrix of signal intensity values across peaks.

    “Finally, we computationally corrected for residual contamination in the retained samples by regressed out epigenomic signatures of hematopoietic immune cells from the matrix of signal intensity values across peaks, using the function removeBatchEffect from the limma package in R.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    To make the gene-regulatory network inference more robust and interpretable, ATAC-seq data were used to exclude motifs most likely inactive in the investigated cell types.

    “To make these coarse approximations more robust and interpretable, we used the ATAC-seq data to exclude motifs that are most likely inactive in the investigated cell types.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    Given the scale of the study, it was not possible to validate the inferred cell-cell interactions experimentally.

    “Given the scale of our study, it was not possible to validate the inferred cell-cell interactions experimentally; however, the identification of many well-established interactions and of biologically plausible differences between cell types and organs provides support for these predictions.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    The cytokine response allowed functional dissection of systemic LCMV infection and provides further validation of the observed epigenetic potential for immune gene activity in structural cells.

    “In summary, structural cells responded in cell-type-specific and organ-specific ways to in vivo stimulation with individual cytokines, which allowed us to functionally dissect the effects of systemic LCMV infection and provides further validation of the observed epigenetic potential for immune gene activity in structural cells.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Low expression with high promoter accessibility indicates an unrealized potential for increased expression.

  • Classified as probably not a substantial claim.

    Study design and conductown data

    To detect and remove potential biases from contaminating hematopoietic RNA, all transcriptome profiles were screened for gene expression signatures associated with eight types of hematopoietic immune cells.

    “To detect and remove potential biases arising from contaminating RNA of hematopoietic immune cells among the sorted structural cell populations, we screened all transcriptome profiles for gene expression signatures associated with eight types of hematopoietic immune cells.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    Residual contamination by hematopoietic immune cell RNA was computationally corrected by regressing out hematopoietic immune cell gene signatures from the matrix of structural cell transcriptomes.

    “As an additional precaution, we computationally corrected for residual contamination by RNA from hematopoietic immune cells, regressing out the gene signatures of hematopoietic immune cells from the matrix of structural cell transcriptomes using the function removeBatchEffect from the limma package in R.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductown data

    A sorting scheme was optimized that produced consistent results for all 12 investigated organs, while excluding cell types detectable only in one or a few tissues.

    “We therefore tested multiple surface markers across organs and optimized a sorting scheme that produced consistent results for all 12 investigated organs, while excluding cell types that were detectable only in one or a few tissues (most notably lymphatic endothelial cells).”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    Samples with detectable contamination by hematopoietic immune cells in ATAC-seq and ChIPmentation data were identified using epigenomic signals in promoter peaks to calculate immune cell signatures.

    “Samples with detectable contamination by hematopoietic immune cells were identified in the same way as for the RNA-seq data, using epigenomic signals in promoter peaks to calculate immune cell signatures.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    The LCMV qPCR results should be regarded as an indication rather than a precise quantitative measure of the degree to which structural cells in different organs are directly and indirectly affected by LCMV infections.

    “The results should therefore be regarded as an indication (rather than as a precise quantitative measure) of the degree to which structural cells in different organs are directly and indirectly affected by the LCMV infections.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    No statistical methods were used to predetermine sample size.

    “No statistical methods were used to predetermine sample size.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    The RNA-seq data were processed and quality-controlled using established bioinformatics software and custom analysis scripts.

    “The RNA-seq data were processed and quality-controlled using established bioinformatics software and custom analysis scripts.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    The same digestion solution was used for all organs, to avoid organ-specific technical confounders.

    “The same digestion solution was used for all organs, to avoid organ-specific technical confounders.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Transcriptome profiling by Smart-seq2 was done in three biologically independent experiments.

    “Transcriptome profiling by Smart-seq2 was done in three biologically independent experiments.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    All mouse experiments were performed according to approved animal experiment licenses and institutional guidelines.

    “All mouse experiments were performed in individually ventilated cages according to the respective animal experiment licenses (BMWFW-66.009/0199-WF/V/3v/2015 and BMWFW-66.009/0361-WF/V/3b/2017) approved by the institutional ethical committees and the institutional guidelines at the Department for Biomedical Research of the Medical University of Vienna.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    ATAC-seq and H3K4me2 ChIPmentation data were processed using well-established bioinformatics pipelines, followed by quality control following the same approach as for the RNA-seq data.

    “The ATAC-seq and H3K4me2 ChIPmentation data were processed using well-established bioinformatics pipelines, followed by quality control following the same approach as for the RNA-seq data (described above).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    The experiments were not randomized, and investigators were not blinded to treatment status during experiments and outcome assessment.

    “The experiments were not randomized, and investigators were not blinded to treatment status during experiments and outcome assessment.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Interpretationreasoning

    The gene expression analysis of structural cells after LCMV infection likely reflects a superposition of several effects, including direct and indirect effects of the infection.

    “Our gene expression analysis likely reflects a superposition of several such effects.”
    Quote in the paperSubstantial claim
    • 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).

  • May combine two claims.

    Study design and conductreasoning

    The LCMV qPCR assay estimates infection levels based on LCMV viral RNA in bulk tissue and cannot account for organ-specific differences in the relative frequencies of cells susceptible to LCMV infection.

    “Importantly, this qPCR assay estimates infection levels based on LCMV viral RNA in bulk tissue, and it cannot account for organ-specific differences in the relative frequencies of cells that are susceptible to LCMV infection.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    The experimental workflow followed the recommendations of the Immunological Genome Project regarding sample collection schedule, antibody staining, and sample pooling.

    “The experimental workflow followed the recommendations of the Immunological Genome Project34 regarding sample collection schedule, antibody staining, and sample pooling.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [34] ImmGen Consortium. Final ImmGen sorting SOP; http://www.immgen.org/Protocols/ImmGen%20Cell%20prep%20and%20sorting%20SOP.pdf (accessed 24 March 2020).

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    Inferred gene-regulatory networks support a model in which constitutively active regulators establish a shared core of immune functions, while additional factors contribute cell-type-specific and organ-specific adaptations.

    “Our inferred gene-regulatory networks support a model in which constitutively active regulators establish a shared core of immune functions, while additional factors contribute cell-type-specific and organ-specific adaptions.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Contaminated ATAC-seq and ChIPmentation samples were automatically removed and replaced by new samples.

    “Contaminated samples were automatically removed and replaced by new samples.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    Epigenome mapping by ChIPmentation for H3K4me2 was done in two biologically independent experiments, except for endothelium from lymph node and fibroblasts from thymus, for which only one high-quality profile could be obtained.

    “Epigenome mapping by ChIPmentation was done in two biologically independent experiments, with two exceptions: for endothelium from lymph node and fibroblasts from thymus, only one high-quality profile could be obtained).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    The experimental results do not account for differences in the relative frequencies of cells that are susceptible to LCMV infection in each organ.

    “nor do they account for differences in the relative frequencies of cells that are susceptible to LCMV infection in each organ”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Chromatin accessibility mapping by ATAC-seq was done in two biologically independent experiments.

    “Chromatin accessibility mapping by ATAC-seq was done in two biologically independent experiments.”
    Quote in the paperNot a substantial claim
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

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Several interactions were predicted across all ventricles and ages between immune cells and structural cells (epithelial, mesenchymal and endothelial).

    “Several interactions were predicted across all ventricles and ages, between immune cells and structural cells (epithelial, mesenchymal and endothelial), in line with the diverse functions assigned to immune cells in other barrier systems (Krausgruber et al., 2020).”

    From A cellular and spatial map of the choroid plexus across brain ventricles and ages (2021) · cites this paper as Krausgruber et al., 2020

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • PCR mixture exceeds the stated reaction volume

    Minor

    A 50 μl reaction cannot contain 25 ml of Kapa HiFi HotStart ReadyMix; that ingredient alone is 500 times the stated total volume.

1 of 1

Cites

Flagged first, then by citations

1 of the 44 references couldn’t be matched to a known paper.

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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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
ORCID
Venue
Nature
Publisher
Springer Science and Business Media LLC
Published
2020-07-01
Volume
583
Issue
7815
Pages
296-302
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
DOI
10.1038/s41586-020-2424-4
PMC
PMC7610345
OpenAlex
W3038974679
Semantic Scholar
fa9e61acc18c1bab6a4dd7d909097c9b875eb4ac
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
Licence
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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Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-10.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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