Deciphering the Origins of Kidney Lymphatics
Bibliographic record
Abstract
Background: Lymphatics clear excess tissue fluid, cells and macromolecules from organs, and are emerging as players in kidney diseases and transplant rejection. Lymphatics were thought to solely originate by sprouting from veins. More recently, we showed that kidney lymphatics can arise using a distinct cellular mechanism featuring the formation of lymphatic ‘clusters’, akin to a de novo vasculogenic process. In this study, we designed experiments to decipher where kidney lymphatics come from. Methods: To identify kidney lymphatics origins, we utilised Cre recombinase-dependent expression of tdTomato for lineage tracing in mouse embryos. We used the following Cre lines to determine the contribution of different cell lineages to lymphatics: (i) Tie2-Cre for endothelial precursors; (ii) Osr1-CreERTR for posterior intermediate mesoderm and (iii) Six2-Cre, Tbx18-CreERT2 and Foxd1-Cre for nephron epithelial, ureteral mesenchyme and renal stroma, respectively. Intact, lineage traced kidneys were subject to wholemount immunolabelling for tdTomato and the lymphatic markers, PROX1 and PDPN, before tissue clearing and confocal microscopy. From the resulting high-resolution 3D images, we quantitatively assessed contributions from each origin to kidney lymphatics. Results: We found 85% of kidney lymphatics to derive from endothelial precursors, as assessed by labelling Tie2+ cells and their progeny. Conversely, 15% of kidney lymphatics arose from an Osr1+ cell lineage, whereas lymphatics in the heart, skin and lung did not originate from Osr1+ progenitors. We found that kidney lymphatics did not originate from Six2+ cells, or from Tbx18+ ureteral mesenchyme, both which derive from Osr1+ cells. However, we provide evidence that the Foxd1+ renal stroma is a source of progenitor cells giving rise to kidney lymphatics. No single lineage was exclusive for lymphatic clusters. Conclusions: Our study emphasises the early colonisation of the mammalian kidney by lymphatics. It also points to an unexpected variety of lineages giving rise to kidney lymphatics, including a novel non-endothelial origin specific to the kidney. These insights challenge the paradigm that lymphatics from different origins form through distinct cellular mechanisms. Further, they critically inform future studies of the roles of lymphatics in kidney development and disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".