Testis‐specific serine kinase 3 is required for sperm morphogenesis and male fertility
Bibliographic record
Abstract
BACKGROUND: The importance of phosphorylation in sperm during spermatogenesis has not been pursued extensively. Testis-specific serine kinase 3 (Tssk3) is a conserved gene, but TSSK3 kinase functions and phosphorylation substrates of TSSK3 are not known. OBJECTIVE: The goals of our studies were to understand the mechanism of action of TSSK3. MATERIALS AND METHODS: We analyzed the localization of TSSK3 in sperm, used CRISPR/Cas9 to generate Tssk3 knockout (KO) mice in which nearly all of the Tssk3 open reading frame was deleted (ensuring it is a null mutation), analyzed the fertility of Tssk3 KO mice by breeding mice for 4 months, and conducted phosphoproteomics analysis of male testicular germ cells. RESULTS: TSSK3 is expressed in elongating sperm and localizes to the sperm tail. To define the essential roles of TSSK3 in vivo, heterozygous (HET) or homozygous KO male mice were mated with wild-type females, and fertility was assessed over 4 months; Tssk3 KO males are sterile, whereas HET males produced normal litter sizes. The absence of TSSK3 results in disorganization of all stages of testicular seminiferous epithelium and significantly increased vacuolization of germ cells, leading to dramatically reduced sperm counts and abnormal sperm morphology; despite these histologic changes, Tssk3 null mice have normal testis size. To elucidate the mechanisms causing the KO phenotype, we conducted phosphoproteomics using purified germ cells from Tssk3 HET and KO testes. We found that proteins implicated in male infertility, such as GAPDHS, ACTL7A, ACTL9, and REEP6, showed significantly reduced phosphorylation in KO testes compared to HET testes, despite unaltered total protein levels. CONCLUSIONS: We demonstrated that TSSK3 is essential for male fertility and crucial for phosphorylation of multiple infertility-related proteins. These studies and the pathways in which TSSK3 functions have implications for human male infertility and nonhormonal contraception.
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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) | 0.003 | 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".