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Heterogeneity and clonality of kidney-infiltrating T cells in murine lupus nephritis
Shuchi Smita, … , Mark J. Shlomchik, Jeremy S. Tilstra
Shuchi Smita, … , Mark J. Shlomchik, Jeremy S. Tilstra
Published March 10, 2022
Citation Information: JCI Insight. 2022;7(8):e156048. https://doi.org/10.1172/jci.insight.156048.
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Research Article Immunology

Heterogeneity and clonality of kidney-infiltrating T cells in murine lupus nephritis

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Abstract

We previously found that kidney-infiltrating T cells (KITs) in murine lupus nephritis (LN) resembled dysfunctional T cells that infiltrate tumors. This unexpected finding raised the question of how to reconcile the “exhausted” phenotype of KITs with ongoing tissue destruction in LN. To address this, we performed single-cell RNA-Seq and TCR-Seq of KITs in murine lupus models. We found that CD8+ KITs existed first in a transitional state, before clonally expanding and evolving toward exhaustion. On the other hand, CD4+ KITs did not fit into current differentiation paradigms but included both hypoxic and cytotoxic subsets with a pervasive exhaustion signature. Thus, autoimmune nephritis is unlike acute pathogen immunity; rather, the kidney microenvironment suppresses T cells by progressively inducing exhausted states. Our findings suggest that LN, a chronic condition, results from slow evolution of damage caused by dysfunctional T cells and their precursors on the way to exhaustion. These findings have implications for both autoimmunity and tumor immunology.

Authors

Shuchi Smita, Maria Chikina, Mark J. Shlomchik, Jeremy S. Tilstra

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Figure 2

High-resolution clustering of CD4+ T cells uncovers unique transcriptional programs in KITs.

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High-resolution clustering of CD4+ T cells uncovers unique transcription...
(A) UMAP of CD4+ T cells from Main-Seq outlining 13 clusters, with the right panel exhibiting assignment of cell source as determined by HTO. (B–D) Gene set enrichment analysis (GSEA) performed in each cell by Wilcoxon’s test (–log10 [P value]) using published reference gene signatures (Supplemental Table 1) and related TF expression were overlaid onto the UMAP to identify CD4 phenotypes. This included (B) Treg gene signature and Foxp3 expression, (C) Th1 signature and Tbx21/Tbet expression, and (D) Th2 signature and Gata3 expression.

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