Wnt5a is a cell-extrinsic factor that supports self-renewal of mouse spermatogonial stem cells
Bibliographic record
Abstract
The maintenance of spermatogonial stem cells (SSCs) provides the foundation for life-long spermatogenesis. Although glial-cell-line-derived neurotrophic factor and fibroblast growth factor 2 are crucial for self-renewal of SSCs, recent studies have suggested that other growth factors have important roles in controlling SSC fate. Because β-catenin-dependent Wnt signaling promotes self-renewal of various stem cell types, we hypothesized that this pathway contributes to SSC maintenance. Using transgenic reporter mice for β-catenin-dependent signaling, we found that this signaling was not active in SSCs in vitro and in most spermatogonia in vivo. Nonetheless, a pan-Wnt antagonist significantly reduced SSC activity in vitro, suggesting that some Wnt molecules exist in our serum-free culture system and contribute to SSC maintenance. Here, we report that Wnt5a promotes SSC activity. We found that Wnt5a-expressing fibroblasts supported SSC activity better than those not expressing Wnt5a in culture, and that recombinant Wnt5a stimulated SSC maintenance. Furthermore, Wnt5a promoted SSC survival in the absence of feeder cells, and this effect was abolished by inhibiting the Jun N-terminal kinase cascade. In addition, Wnt5a blocked β-catenin-dependent signaling. We detected the expression of Wnt5a and potential Wnt5a receptors in Sertoli cells and stem/progenitor spermatogonia, respectively. These results indicate that Wnt5a is a cell-extrinsic factor that supports SSC self-renewal through β-catenin-independent mechanisms.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".