Heparan Sulfation–Dependent Fibroblast Growth Factor Signaling Maintains Embryonic Stem Cells Primed for Differentiation in a Heterogeneous State
Bibliographic record
Abstract
Embryonic stem (ES) cells continuously decide whether to maintain pluripotency or differentiate. While exogenous leukemia inhibitory factor and BMP4 perpetuate a pluripotent state, less is known about the factors initiating differentiation. We show that heparan sulfate (HS) proteoglycans are critical coreceptors for signals inducing ES cell differentiation. Genetic targeting of NDST1 and NDST2, two enzymes required for N-sulfation of proteoglycans, blocked differentiation. This phenotype was rescued by HS presented in trans or by soluble heparin. NaClO(3) (-), which reduces sulfation of proteoglycans, potently blocked differentiation of wild-type cells. Mechanistically, N-sulfation was identified to be critical for functional autocrine fibroblast growth factor 4 (FGF4) signaling. Microarray analysis identified the pluripotency maintaining transcription factors Nanog, KLF2/4/8, Tbx3, and Tcf3 to be negatively regulated, whereas markers of differentiation such as Gbx2, Dnmt3b, FGF5, and Brachyury were induced by sulfation-dependent FGF receptor (FGFR) signaling. We show that several of these genes are heterogeneously expressed in ES cells, and that targeting of heparan sulfation or FGFR-signaling facilitated a homogenous Nanog/KLF4/Tbx3 positive ES cell state. This finding suggests that the recently discovered heterogeneous state of ES cells is regulated by HS-dependent FGFR signaling. Similarly, culturing blastocysts with NaClO(3) (-) eliminated GATA6-positive primitive endoderm progenitors generating a homogenous Nanog-positive inner cell mass. Functionally, reduction of sulfation robustly improved de novo ES cell derivation efficiency. We conclude that N-sulfated HS is required for FGF4 signaling to maintain ES cells primed for differentiation in a heterogeneous state. Inhibiting this pathway facilitates a more naïve ground state.
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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".