Evolution of urea transporters in vertebrates: adaptation to urea's multiple roles and metabolic sources
Bibliographic record
Abstract
In the two decades since the first cloning of the mammalian kidney urea transporter (UT-A), UT genes have been identified in a plethora of organisms, ranging from single-celled bacteria to metazoans. In this review, focusing mainly on vertebrates, we first reiterate the multiple catabolic and anabolic pathways that produce urea, then we reconstruct the phylogenetic history of UTs, and finally we examine the tissue distribution of UTs in selected vertebrate species. Our analysis reveals that from an ancestral UT, three homologues evolved in piscine lineages (UT-A, UT-C and UT-D), followed by a subsequent reduction to a single UT-A in lobe-finned fish and amphibians. A later internal tandem duplication of UT-A occurred in the amniote lineage (UT-A1), followed by a second tandem duplication in mammals to give rise to UT-B. While the expected UT expression is evident in excretory and osmoregulatory tissues in ureotelic taxa, UTs are also expressed ubiquitously in non-ureotelic taxa, and in tissues without a complete ornithine-urea cycle (OUC). We posit that non-OUC production of urea from arginine by arginase, an important pathway to generate ornithine for synthesis of molecules such as polyamines for highly proliferative tissues (e.g. testis, embryos), and neurotransmitters such as glutamate for neural tissues, is an important evolutionary driving force for the expression of UTs in these taxa and tissues.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".