CTNNB1 Signaling in Sertoli Cells Downregulates Spermatogonial Stem Cell Activity via WNT4
Bibliographic record
Abstract
Constitutive activation of the WNT signaling effector CTNNB1 (β-catenin) in the Sertoli cells of the Ctnnb1(tm1Mmt/+);Amhr2(tm3(cre)Bhr/+) mouse model results in progressive germ cell loss and sterility. In this study, we sought to determine if this phenotype could be due to a loss of spermatogonial stem cell (SSC) activity. Reciprocal SSC transplants between Ctnnb1(tm1Mmt/+);Amhr2(tm3(cre)Bhr/+) and wild-type mice showed that SSC activity is lost in Ctnnb1(tm1Mmt/+);Amhr2(tm3(cre)Bhr/+) testes over time, whereas the mutant testes could not support colonization by wild-type SSCs. Microarray analyses performed on cultured Sertoli cells showed that CTNNB1 induces the expression of genes associated with the female sex determination pathway, which was also found to occur in Ctnnb1(tm1Mmt/+);Amhr2(tm3(cre)Bhr/+) testes. One CTNNB1 target gene encoded the secreted signaling molecule WNT4. We therefore tested the effects of WNT4 on SSC-enriched germ cell cultures, and found that WNT4 induced cell death and reduced SSC activity without affecting cell cycle. Conversely, conditional inactivation of Wnt4 in the Ctnnb1(tm1Mmt/+);Amhr2(tm3(cre)Bhr/+) model rescued spermatogenesis and male fertility, indicating that WNT4 is the major effector downstream of CTNNB1 responsible for germ cell loss. Furthermore, WNT4 was found to signal via the CTNNB1 pathway in Sertoli cells, suggesting a self-reinforcing positive feedback loop. Collectively, these data indicate for the first time that ectopic activation of a signaling cascade in the stem cell niche depletes SSC activity through a paracrine factor. These findings may provide insight into the pathogenesis of male infertility, as well as embryonic gonadal development.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".