Single cell G‐protein coupled receptor profiling of activated kidney fibroblasts expressing transcription factor 21
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Activated fibroblasts deposit fibrotic matrix in chronic kidney disease (CKD) and G-protein coupled receptors (GPCRs) are the most druggable therapeutic targets. Here, we set out to establish a transcriptional profile that identifies activated kidney fibroblasts and the GPCRs that they express. EXPERIMENTAL APPROACH: RNA sequencing and single cell qRT-PCR were performed on mouse kidneys after unilateral ureteral obstruction (UUO). Candidate expression was evaluated in mice with UUO or diabetes or injected with adriamycin or folic acid. Intervention studies were conducted in mice with diabetes or UUO. Correlative histology was performed in human kidney tissue. KEY RESULTS: Transcription factor 21 (Tcf21)+ cells that expressed 2 or 3 of Postn, Acta2 and Pdgfra were highly enriched for fibrogenic genes and were defined as activated kidney fibroblasts. Tcf21+ α-smooth muscle actin (α-SMA)+ interstitial cells accumulated in kidneys of mice with UUO or diabetes or injected with adriamycin or folic acid, whereas renin-angiotensin system blockade attenuated increases in Tcf21 in diabetic mice. Fifty-six GPCRs were up-regulated in single Tcf21+ kidney fibroblasts, the most up-regulated being Adgra2 and S1pr3. Adenosine receptors, Adora2a/2b, were up-regulated in Tcf21+ fibroblasts and the adenosine receptor antagonist, caffeine decreased Tcf21 upregulation and kidney fibrosis in UUO mice. TCF21, ADGRA2, S1PR3 and ADORA2A/2B were each detectable in α-SMA+ interstitial cells in human kidney samples. CONCLUSION AND IMPLICATIONS: Tcf21 is a marker of kidney fibroblasts that are enriched for fibrogenic genes in CKD. Further analysis of the GPCRs expressed by these cells may identify new targets for treating CKD. LINKED ARTICLES: This article is part of a themed issue on Translational Advances in Fibrosis as a Therapeutic Target. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v180.22/issuetoc.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".