Spatially resolved phosphoproteomics reveals fibroblast growth factor receptor recycling-driven regulation of autophagy and survival.
The main results reproduced: recomputed values matched the published ones within tolerance.
- ✓Same input data as the authors
- ✓Reported values were directly comparable
- ✓No authors-side cause for any deviation
- ✓Reported values are derivable from the shared data
- ✓Any deviation was negligible
- ✓The central claim held under reproduction
- ✓Overall, the reproduction was clean
- 🟡A deviation arose in the data or preprocessing
A 0–100 reproducibility-quality score from the per-question grades, shown as a z-score: standard deviations above (+) or below (−) the mean of comparable assessments.
▸Reproduction agent’s raw note
REPRODUCED (1:1 on the core). Watson & Ferguson 2022 APEX2 spatial phosphoproteomics. The Zenodo deposit is a mirror of the GitHub repo (no separate raw data; raw MS on PRIDE, out of scope). Re-ran the authors' R scripts 1-5 on the shipped MaxQuant tables on «our HPC» (conda R 4.5.3). 8/13 claims EXACT, 4 within-tol (~98%), 1 consistent, 1 blocked. The significant phosphosite set + hierarchical clusters reproduce bit-for-bit (1653 sites; RE 732 / RAB11 532 / other 389; id-set Jaccard 1.000), as do global-upregulated sites (477), total sites (10771), the mTOR/autophagy network (73 nodes/158 edges), and the paper's Fig 4f overlap (107). Paper Fig 4e overlaps reproduce at ~98% (945 vs 961 sites; 577 vs 588 proteins; 733 vs 743 RE; the recycling-cluster PERCENTAGE 77.6% vs 77.4% is near-exact). The only non-trivial gap is the proximal-protein significance set (count exact at 3303, but ~14% identity drift), traced entirely to QRILC imputation stochasticity + a newer imputeLCMD; this propagates to the Fig 4e counts. Found & fixed a fatal undefined-variable bug in script 1 (lfq_apex_normGFP->lfq_normGFP). NOT attempted: raw MaxQuant processing (PRIDE), the manual Perseus volcano (its output ships, so downstream IS reproduced), and script 6 (BLOCKED - inputs not deposited; figure-only). No value appears fabricated.
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v1 current initial assessment Score 87assessed: 2026-06-22 ⛓ 1488669e1713
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- Reproduced
- 2026-06-22
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-22no human curator yet
- Last updated
- 2026-08-05
Provisional, curator- or AI-assessed, and independently checkable. A reproduction outcome states what one attempt could reproduce — not a judgement of the authors.
Deep full-text extraction
Model: sonnetThe paper investigates which FGFR2b signalling partners are recruited in close proximity to recycling endosomes during FGF10-induced receptor recycling, and how this spatially restricted signalling shapes downstream cellular responses such as autophagy and survival.
- ★ A spatially resolved phosphoproteomics (SRP) approach combining APEX2-driven proximity biotinylation with phosphopeptide enrichment was developed to identify FGFR2b signalling partners near recycling endosomes. method
- ★ FGF10-stimulated FGFR2b activates mTOR-dependent signalling and ULK1 at the recycling endosomes, leading to autophagy suppression and cell survival. finding
- ★ Inhibiting FGFR2b trafficking (via DnRAB11 or DnDNM2) alters the global phosphoproteome without changing FGFR2b or ERK1/2 activation. finding
- ★ mTOR signalling is specifically enriched among proteins in the recycling-dependent (RAB11-dependent) phosphorylation response cluster, common to HeLa-FGFR2b and T47D cells. finding
- ★ The FGFR2b recycling route, rather than mere cytoplasmic presence of the receptor, regulates specific branches of downstream signalling. finding
- APEX2 tagging of FGFR2b, RAB11, or GFP does not alter FGFR2b trafficking or FGF10-induced signalling activation. method
- RAB11-APEX2-based pulldown enriches known recycling endosome markers (RAB25, RCP) and HA-FGFR2b, validating proximity to recycling endosomes. finding
- FGF10 induces FGFR2b recycling to the plasma membrane via RAB11-positive recycling endosomes, whereas FGF7 induces FGFR2b degradation. finding
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| Confocal immunofluorescence microscopy (colocalization) | HeLa_FGFR2bST cells expressing wtRAB11-, DnRAB11-, or DnDNM2-eGFP | FGF10 stimulation (0, 40, 120 min); dominant-negative RAB11/Dynamin2 | FGFR2b colocalization with EEA1 and GFP-tagged trafficking markers | — |
| Western blot / immunoblot | HeLa_FGFR2bST cells expressing GFP, DnRAB11, or DnDNM2 | FGF10 stimulation (8, 40 min) | FGFR2b and ERK1/2 phosphorylation | — |
| MS-based quantitative phosphoproteomics and proteomics | HeLa-FGFR2b and T47D cells expressing GFP, DnRAB11, or DnDNM2 | FGF10 stimulation (40 min); trafficking-blocking dominant negatives | Phosphorylated site abundance, PCA, fuzzy c-means clustering, KEGG pathway enrichment | Mass spectrometry |
| APEX2-based spatially resolved phosphoproteomics (proximity biotinylation + phosphopeptide enrichment) | HeLa_FGFR2b-APEX2ST, T47D_FGFR2KO_FGFR2b-APEX2ST, HeLa-FGFR2bST_RAB11-APEX2, HeLa-FGFR2bST_GFP-APEX2 | FGF10 stimulation; biotin-phenol + H2O2 labelling (1 min) | Biotinylated and phosphorylated proteins after streptavidin pulldown | Mass spectrometry |
| Streptavidin pulldown + immunoblot | HeLa-FGFR2bST_RAB11-APEX2 | FGF10 stimulation, APEX2 biotinylation | RAB25, HA-FGFR2b, RCP levels in pulldown | — |
| Confocal-based trafficking/internalisation assay | HeLa_FGFR2b-APEX2ST and T47D_FGFR2KO_FGFR2b-APEX2ST | FGF7 vs FGF10 stimulation (up to 120 min) | FGFR2b subcellular localisation (plasma membrane, cytoplasm, degradation) | — |
- – DnRAB11 and DnDNM2 expression impaired FGFR2b trafficking but did not alter FGFR2b or ERK1/2 phosphorylation at early time points
- – 7620 phosphorylated sites quantified in HeLa-FGFR2b and 8075 in T47D
- – Fuzzy c-means clustering identified 11 clusters of phosphosites significantly dysregulated across the four conditions ANOVA p<0.0001
- – KEGG pathway over-representation analysis identified mTOR signalling as enriched specifically in the recycling response cluster in both HeLa-FGFR2b and T47D
- – No signalling pathways were specifically enriched upon inhibition of FGFR2b internalisation alone (DnDNM2)
- – FGF10 induced FGFR2b to gradually leave the cell surface, accumulate in cytoplasm, and recycle back to the plasma membrane; FGF7 induced internalisation followed by degradation
- ▲ RAB11-APEX2 pulldown was positive for RAB25, HA-FGFR2b, and RCP, confirming proximity labelling at recycling endosomes
- ▲ Phosphorylated PLCγ and SHC, but not histone H3, were detected in APEX2 pulldowns after FGF10 treatment
- pvalue ANOVA p<0.0001 (Significance threshold for phosphosites used in fuzzy c-means clustering)
- count 7620 phosphorylated sites (Sites quantified in HeLa-FGFR2b phosphoproteome)
- count 8075 phosphorylated sites (Sites quantified in T47D phosphoproteome)
- pvalue p<0.0005 (one-sided student's t-test) (Colocalization quantification of FGFR2b with GFP-tagged proteins/EEA1)
- count N=3 independent biological replicates (Confocal colocalization quantification (Fig. 1b))
- count N≥3 independent biological replicates (Immunoblot analysis (Fig. 1c))
- other 20 nm (APEX2) vs 10 nm (BioID) labelling radius (Proximity-dependent biotinylation radius comparison)
- count 11 clusters (Number of phosphosite clusters identified by fuzzy c-means clustering)
Statistical methods review
Model: sonnetA neutral, descriptive read of the statistical approach — what was done, and (for shared learning, not as criticism) what could also have been done.
The study combines quantitative MS-based phosphoproteomics/proteomics across engineered cell lines (HeLa-FGFR2b, T47D) with confocal imaging quantification and immunoblotting to characterize FGFR2b trafficking-dependent signalling. Group comparisons in imaging used a one-sided Student's t-test, phosphoproteomic profiles across four conditions were compared by ANOVA followed by fuzzy c-means/t-SNE clustering, and pathway-level enrichment (KEGG) was assessed with Fisher's exact test plus FDR adjustment. Results are reported largely as significance thresholds (e.g., p<0.0005, p<0.0001) alongside median ± SD summaries for imaging quantification.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| One-sided Student's t-test | Quantification of FGFR2b co-localization with GFP-tagged proteins and with EEA1 (Fig. 1b) | N = 3 independent biological replicates, 2-5 cells analyzed per N | not stated |
| ANOVA | Identification of phosphorylated sites significantly dysregulated across the four HeLa-FGFR2b trafficking conditions prior to fuzzy c-means clustering (Fig. 2c, d) | not explicitly stated (based on MS runs across experimental conditions) | not stated |
| Fisher's exact test with FDR adjustment | KEGG pathway over-representation analysis comparing membrane, internalisation, and recycling response clusters (Fig. 2f) | not stated | not stated |
| Pearson correlation | Comparison of cellular proteome across experimental conditions to check that dominant-negative protein expression did not alter the proteome (Supplementary Fig. 2a, j) | not stated | not stated |
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Co-localization quantification (Fig. 1b) was compared using a one-sided Student's t-test on a small number of biological replicates (N=3) with multiple cells per replicate.↳ Could also: A mixed-effects (hierarchical) model treating cell as nested within biological replicate — This would explicitly account for non-independence among the 2-5 cells measured per replicate, which can otherwise affect the effective sample size used in the significance calculation.
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A one-sided t-test was used for the co-localization comparison.↳ Could also: A two-sided t-test — A two-sided test would also be a standard choice unless the direction of the expected difference was specified in advance, and can be reported alongside the one-sided result for readers who prefer non-directional hypothesis testing.
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Phosphorylated sites differentially regulated across the four trafficking conditions were identified using ANOVA prior to fuzzy c-means clustering.↳ Could also: A moderated statistics framework such as limma, commonly used in proteomics/phosphoproteomics — Moderated variance estimation can improve stability of significance calls when the number of replicates per condition is small, which is common in MS-based proteomics experiments.
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KEGG pathway enrichment used Fisher's exact test with FDR adjustment.↳ Could also: Bonferroni correction or gene set enrichment analysis (GSEA) — Bonferroni offers a more conservative family-wise error control, while GSEA-type approaches use the full ranked phosphoproteomic dataset rather than a fixed significance cutoff, which can capture pathway-level trends among sub-threshold sites.
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Imaging quantification results were summarized as median ± SD.↳ Could also: Reporting with a 95% confidence interval alongside or instead of SD — A CI directly conveys the precision of the estimated median/mean and is often preferred for communicating uncertainty with small replicate numbers (N=3).
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Proteome consistency across conditions was assessed using Pearson correlation.↳ Could also: Reporting exact p-values or effect-size statistics (e.g., correlation coefficient with CI) alongside the correlation values — This would let readers directly evaluate the strength and precision of the reported similarity between conditions rather than relying on a qualitative description of 'high' correlation.
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