Fertilization triggers early proteomic symmetry breaking in mammalian embryos
Bibliographic record
Abstract
While non-mammalian embryos often rely on spatial pre-patterning, mammalian development has long been thought to begin with equivalent blastomeres. However, emerging evidence challenges this. Here, using multiplexed and label-free single-cell proteomics, we identify over 300 asymmetrically abundant proteins-many involved in protein degradation and transport-dividing mouse 2-cell-stage blastomeres into two distinct clusters, which we term alpha and beta. These proteomic asymmetries are detectable as early as the zygote stage, intensify by the 4-cell stage, and correlate with the sperm entry site, implicating fertilization as a symmetry-breaking event. Splitting 2-cell-stage embryos into halves reveals that beta blastomeres possess greater developmental potential than alpha blastomeres. Similar clustering and protein enrichment patterns found in human 2-cell embryos suggest this early asymmetry might be conserved. These findings uncover a previously unrecognized proteomic pre-patterning triggered by fertilization in mammalian embryos, with important implications for understanding totipotency and early lineage bias.
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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) | 0.001 | 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".