Immune cell landscaping reveals a protective role for regulatory T cells during kidney injury and fibrosis

Durães, Fernanda do Valle; Lafont, Armelle; Beibel, Martin; Martin, Kea; Darribat, Katy; Cuttat, Rachel; Waldt, Annick; Naumann, Ulrike; Wieczorek, Grazyna; Gaulis, Swann; Pfister, Sabina; Mertz, Kirsten D.; Li, Jianping; Roma, Guglielmo; Warncke, Max

doi:10.1172/jci.insight.130651

Cited by 76 publications

(69 citation statements)

References 64 publications

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“…We first demonstrate that scMappR can identify validated cell-type specific gene expression by taking advantage of a reference data set (23) where bulk RNA-seq was performed on cell-sorted samples. We show that scMappR can identify bonafide differential gene expression changes emanating from a minority cell population present in the mouse kidney during regeneration (13).…”

Section: Introductionmentioning

confidence: 95%

“…Despite many advances, technical limitations (e.g., low gene detection per cell, cell dissociation optimization) and cost currently limit the use of scRNA-seq for hard-todissociate cell types and large study designs (5,6). Importantly, bioinformatics methods that integrate bulk RNA-seq and scRNA-seq demonstrate the highly complementary nature of these two technologies (7)(8)(9)(10)(11)(12)(13)(14)(15)(16).…”

Section: Introductionmentioning

confidence: 99%

“…Valle Duraes et al, 2020 (13) who interrogated gene expression changes involved in mouse kidney regeneration before and after injury (13). Kidney regeneration involves multiple cell-type specific processes (49-52), and importantly Valle Duraes et al, 2020 used bulk RNA-seq in conjunction with histopathology, cell sorting, and scRNA-seq to implicate T-Cell recruitment as a critical part of the regeneration process(13). We reasoned that this is an ideal model RNA-seq study to showcase scMappR as Valle Duraes et al, 2020 is well-powered, and includes detailed experimental follow-up of celltype specific responses(13).…”

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confidence: 99%

“…This cell-type contains 430 cell-type markers that enrich for many immune related processes (immune system processes: precision = 0.537, one-tailed hypergeometric test adjusted p-value = 3.65 x 10 -87 ; innate immune response: precision = 0.223, one-tailed hypergeometric test adjusted p-value = 1.78 x 10 -38 ; adaptive immune response: precision = 0.184, one-tailed hypergeometric test adjusted p-value = 7.95 x 10 -36 ; T-cell activation: precision = 0.161, onetailed hypergeometric test adjusted p-value = 2.10 x 10 -32 ). Furthermore, the original Tabula Muris, 2018 study labelled this cell-type population as "Macrophage and Natural Killer"(53).Interestingly, many cells within this population contain a high expression of naive T-cell markers like Ccr7 and Nkg7(13,53). These results are unsurprising as T-cells are present in the uninjured kidney(55).…”

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confidence: 99%

“…In our bulk RNA-seq analysis, we identified three genes, Il1rl1, Rgs16, and Ccr7 as DEGs when naive day 0 and regeneration day 3 were compared. Valle Duraes et al, 2020 used three genes as T-cell markers in the CD4 + sorted scRNA-seq experiment of naive, regenerating,and damaged kidney(13,56). We identified an increase in the rank-order of these three DEGs between bulk RNA-seq and "Macrophage, dendritic" cwFold-changes (P-value one-tailed Wilcoxon's test = 0.047; Il1rl1: bulk rank 1545; "Macrophage, dendritic" cell rank 1029;…”

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confidence: 99%

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Single-cell mapper (scMappR): using scRNA-seq to infer cell-type specificities of differentially expressed genes

Sokolowski

Faykoo-Martinez

Erdman

et al. 2020

Preprint

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RNA sequencing (RNA-seq) is widely used to identify differentially expressed genes (DEGs) and reveal biological mechanisms underlying complex biological processes. RNA-seq is often performed on heterogeneous samples and the resulting DEGs do not necessarily indicate the cell types where the differential expression occurred. While single-cell RNA-seq (scRNA-seq) methods solve this problem, technical and cost constraints currently limit its widespread use. Here we present single cell Mapper (scMappR), a method that assigns cell-type specificity scores to DEGs obtained from bulk RNA-seq by integrating cell-type expression data generated by scRNA-seq and existing deconvolution methods. After benchmarking scMappR using RNA-seq data obtained from sorted blood cells, we asked if scMappR could reveal known cell-type specific changes that occur during kidney regeneration. We found that scMappR appropriately assigned DEGs to cell-types involved in kidney regeneration, including a relatively small proportion of immune cells. While scMappR can work with any user supplied scRNA-seq data, we curated scRNA-seq expression matrices for ~100 human and mouse tissues to facilitate its use with bulk RNA-seq data alone. Overall, scMappR is a user-friendly R package that complements traditional differential expression analysis available at CRAN.

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Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Single-cell mapper (scMappR): using scRNA-seq to infer cell-type specificities of differentially expressed genes

Sokolowski

Faykoo-Martinez

Erdman

et al. 2020

Preprint

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Crosstalk between fibroblasts and immunocytes in fibrosis: From molecular mechanisms to clinical trials

Di,

Chen,

et al. 2024

Clinical & Translational Med

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BackgroundThe impact of fibroblasts on the immune system provides insight into the function of fibroblasts. In various tissue microenvironments, multiple fibroblast subtypes interact with immunocytes by secreting growth factors, cytokines, and chemokines, leading to wound healing, fibrosis, and escape of cancer immune surveillance. However, the specific mechanisms involved in the fibroblast‐immunocyte interaction network have not yet been fully elucidated.Main body and conclusionTherefore, we systematically reviewed the molecular mechanisms of fibroblast‐immunocyte interactions in fibrosis, from the history of cellular evolution and cell subtype divisions to the regulatory networks between fibroblasts and immunocytes. We also discuss how these communications function in different tissue and organ statuses, as well as potential therapies targeting the reciprocal fibroblast‐immunocyte interplay in fibrosis. A comprehensive understanding of these functional cells under pathophysiological conditions and the mechanisms by which they communicate may lead to the development of effective and specific therapies targeting fibrosis.

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Development of Adaptive Immunity and Its Role in Lung Remodeling

Esnault

Jarjour

2023

Precision Approaches to Heterogeneity in Asthma

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Immune cell landscaping reveals a protective role for regulatory T cells during kidney injury and fibrosis

Cited by 76 publications

References 64 publications

Single-cell mapper (scMappR): using scRNA-seq to infer cell-type specificities of differentially expressed genes

Single-cell mapper (scMappR): using scRNA-seq to infer cell-type specificities of differentially expressed genes

Crosstalk between fibroblasts and immunocytes in fibrosis: From molecular mechanisms to clinical trials

Development of Adaptive Immunity and Its Role in Lung Remodeling

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