Analysis of the Hypoxic Response in a Mouse Cortical Collecting Duct-Derived Cell Line Suggests That Esrra Is Partially Involved in Hif1α-Mediated Hypoxia-Induc
The main results reproduced: recomputed values matched the published ones within tolerance.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
- ✓Same input data as the authors
- ✓Reported values were directly comparable
- ✓No relevant deviation in data/preprocessing
- ✓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
- Every checked point held up.
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 (within tolerance). Primary pipeline result = hypoxia-vs-normoxia DE in mouse mCCDcl1 on the authors' own RNA-seq (PRJEB53226, 6 samples). STAR 2.7.10b -> GRCm38/Ens102 -> edgeR 4.8.2 / DESeq2 1.50.2. Strandedness DETECTED as reverse (fwd_frac=0.072). With the paper's described 0.5-CPM/library filter, edgeR gives 3056/1650/1406 vs reported 3086/1679/1407 (99.0%/98.3%/99.9%); DESeq2 gives 3133/1713/1420 (within ~1.5%). Residual diff explained by STAR/edgeR/DESeq2 version drift + filter-threshold interpretation. Methods text attributes counts to DESeq2 but describes edgeR's filter; both within tolerance, no fabrication concern. Canonical HIF1a targets all correctly induced (biological validity confirmed). NOT attempted: secondary reused-ChIP-seq Venn overlap (out of scope, underspecified).
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Assessment versions
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v1 current initial assessment Score 76assessed: 2026-06-20 ⛓ 524a95d59e58
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Provenance — full disclosure
When this reproduction was carried out, which methodology version was used, and by whom — so the record can be audited and checked independently.
- Reproduced
- 2026-06-20
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-20no 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 cortical collecting duct (CCD) cell line mCCD cl1 is responsive to hypoxia overall and can serve as a model to determine whether Hif-1α (and candidate cofactor Esrra) mediate hypoxia-inducible gene expression, given known links between hypoxia, aldosterone, and ENaC in the aldosterone-sensitive distal nephron.
- ★ mCCD cl1 cells mount a broad transcriptional response to 24 h hypoxia (0.2% O2), with 3086 genes differentially expressed finding
- ★ Hypoxia decreases oxygen-linked pathways (ATP metabolism, oxidative phosphorylation, cellular/aerobic respiration) while inducing canonical hypoxic response pathways and Hif-1α target genes finding
- ★ Epas1 (Hif-2α) is barely detectable in mCCD cl1 cells under normoxia and hypoxia, suggesting Hif-1α rather than Hif-2α mediates the hypoxic response in these cells finding
- ★ shRNA-mediated Hif-1α knockdown abolishes hypoxic up-regulation of Egln1, Egln3, and Serpine1, confirming Hif-1α dependence with no redundancy from Hif-2α finding
- ★ Esrra knockdown reduces hypoxia-induced Egln3 and Serpine1 expression without altering Hif-1α protein levels or Egln1 expression, indicating Esrra acts as a cofactor rather than upstream of Hif-1α stabilization finding
- ★ Comparative ENCODE ChIP-seq analysis in human cell lines identifies ESRRA as a candidate transcription factor co-occurring with HIF-1α/HIF-2α/HIF-β binding sites resource
- ★ mCCD cl1 is proposed as an adequate, non-cancerous cellular model to study hypoxia responses and additional regulatory factors in the collecting duct method
- Scnn1a (αENaC) and Scnn1b (βENaC) mRNA are significantly reduced by hypoxia, consistent with prior reports of hypoxia-driven ENaC down-regulation in CCD cells finding
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| bulk RNA-seq | mCCD cl1 cells | hypoxia (0.2% O2, 24 h) vs normoxia (21% O2) | genome-wide differential gene expression, GO/hallmark pathway enrichment | — |
| RT-qPCR | mCCD cl1 cells | hypoxia (0.2% O2, 24 h) vs normoxia | mRNA levels of Soat2, Fosl1, Rhcg, Hsd11b2, Scnn1a, Scnn1b, Egln1, Egln3, Vegfa, Slc2a1, Pag1, Serpine1, Hif1a, Esrra | — |
| Western blot | mCCD cl1 cells | hypoxia (0.2% O2, 24 h) vs normoxia; shHif-1α and shEsrra knockdown | Hif-1α protein expression | — |
| lentiviral shRNA knockdown | mCCD cl1 cells | shRNA against Hif-1α (3 sequences tested) vs control shRNA | Hif1a mRNA knockdown efficiency; downstream Egln1, Egln3, Serpine1 expression under normoxia/hypoxia | — |
| lentiviral shRNA knockdown | mCCD cl1 cells | shRNA against Esrra (2 sequences) vs control shRNA | Esrra mRNA knockdown efficiency; Hif-1α protein; Egln1, Egln3, Serpine1 expression under normoxia/hypoxia | — |
| ChIP-seq (public ENCODE data, comparative analysis) | human cell lines (HepG2, HKC8, RCC4, K562) | none (public dataset comparison, hypoxia vs normoxia in source data) | overlap of HIF-1α/HIF-2α/HIF-β and ESRRA binding sites, including at SERPINE1 locus | — |
| cell viability assay (trypan blue exclusion) | mCCD cl1 cells | hypoxia (0.2% O2, 24 h) | cell viability | TC20 automated cell counter (Biorad) |
- – 3086 genes differentially expressed after 24 h hypoxia (1679 up, logFC>1; 1407 down, logFC<-1) logFC >1 or <-1
- – GO/hallmark analysis shows decreased ATP metabolism, oxidative phosphorylation, cellular/aerobic respiration and increased hypoxia-response pathways, including Hif-1α target genes (Serpine1, Vegfa, Fam162a, Pfkp, Gbe1)
- – Epas1 expression barely detectable in mCCD cl1 under normoxia and hypoxia at both mRNA and protein level
- ▼ shHif-1α-2 reduced Hif1a expression by 80-85% vs control shRNA under normoxia and hypoxia 80-85%
- ▼ Hif-1α knockdown suppressed hypoxic up-regulation of Egln1 and Egln3 and significantly reduced Serpine1 expression under hypoxia
- ▼ shEsrra-1 and shEsrra-2 reduced Esrra mRNA by 87% and 73%, respectively, under normoxia 87% (shEsrra-1), 73% (shEsrra-2)
- ▼ Esrra knockdown significantly reduced Egln3 and Serpine1 expression after 24 h hypoxia despite unchanged Hif-1α protein and unchanged Egln1 mRNA
- ▼ Scnn1a and Scnn1b mRNA significantly reduced following hypoxia, consistent with RNAseq data
- count 3086 differentially expressed genes (logFC<-1 or >1) (total DEGs after 24 h hypoxia vs normoxia in mCCD cl1 RNAseq)
- count 1679 up-regulated genes (logFC>1); 1407 down-regulated genes (logFC<-1) (breakdown of hypoxia-responsive DEGs)
- fold_change 80-85% reduction (shHif-1α-2 knockdown efficiency of Hif1a expression vs control shRNA)
- fold_change 87% reduction (shEsrra-1), 73% reduction (shEsrra-2) (Esrra mRNA knockdown efficiency under normoxia)
- fold_change ~4-fold lower (normoxia), >33-fold lower (hypoxia) (Esrrg normalized RNAseq counts relative to Esrra in mCCD cl1 cells)
- other Esrrg expression reduced to about 7% remaining under hypoxia (hypoxic down-regulation of Esrrg in mCCD cl1 RNAseq data)
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 compares mCCD cl1 cell transcriptomes and gene/protein expression under normoxic versus 24 h hypoxic (0.2% O2) conditions, using RNAseq for genome-wide differential expression and gene ontology/gene set enrichment analysis, followed by RT-qPCR and Western blot validation of selected genes in shRNA-mediated Hif-1α and Esrra knockdown cell lines. Differential expression was reported using a log fold-change threshold (logFC < -1 or > 1), and validation experiments describe outcomes as 'significantly' regulated or reduced, but the specific statistical test(s), exact p-values, sample sizes, and software used for these comparisons are not stated in the portion of the text provided (the Materials and Methods section is truncated before a statistics subsection appears). Results are presented as fold-change/expression values across figures without visible detail on error metrics or multiplicity handling.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| not stated (RNAseq differential expression analysis) | normoxia vs. 24 h hypoxia transcriptome comparison, Figure 1A,B / Table S1 | — | not stated |
| not stated (comparison underlying 'significantly regulated/reduced' claims) | RT-qPCR validation of Soat2, Fosl1, Rhcg, Hsd11b2, Scnn1a, Scnn1b, Figure 2 | — | not stated |
| not stated | shHif-1α knockdown effect on Egln1, Egln3, Serpine1 expression, Figure 4C-E | — | not stated |
| not stated | shEsrra knockdown effect on Egln3, Serpine1, Hif1a mRNA/protein, Figure 5A-E | — | not stated |
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Differentially-expressed genes from RNAseq were defined using a logFC threshold (>1 or <-1) without a stated significance/FDR cutoff in the visible text.↳ Could also: Pairing the fold-change threshold with an explicitly reported adjusted p-value cutoff (e.g., Benjamini-Hochberg FDR < 0.05) from a tool such as DESeq2 or edgeR — Explicitly stating the statistical significance threshold alongside the fold-change cutoff helps readers gauge how many of the reported genes are supported by both magnitude and statistical confidence, and clarifies how multiple testing across thousands of genes was handled.
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RT-qPCR and knockdown experiments describe gene expression changes as 'significantly' altered without naming the specific statistical test in the provided text.↳ Could also: Reporting the specific test used (e.g., two-tailed Student's t-test, Mann-Whitney U, or one-/two-way ANOVA with post-hoc comparisons) along with exact p-values — Naming the test and reporting exact p-values allows readers to evaluate the assumptions (e.g., normality, variance homogeneity) underlying the comparison and to compare effect sizes across studies.
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Multiple genes (Egln1, Egln3, Serpine1, etc.) were each compared individually between shControl and shRNA knockdown conditions across several figures.↳ Could also: A two-way ANOVA (genotype x oxygen condition) with a post-hoc multiple-comparison correction (e.g., Tukey HSD or Sidak) applied across the gene panel — When many individual comparisons are run across a shared experimental design, an ANOVA-based framework with correction for multiple comparisons can control the family-wise error rate while also testing for interaction effects between knockdown and hypoxia.
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Expression differences are described qualitatively (e.g., 'strong and robust up-regulation') without visible confidence intervals or effect-size measures in the extracted text.↳ Could also: Reporting fold-change with 95% confidence intervals or standardized effect sizes (e.g., Cohen's d) alongside significance tests — Confidence intervals and effect sizes convey the magnitude and precision of an effect in addition to whether it is statistically distinguishable from zero, which can be informative when sample sizes are small.
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Replication type (biological vs. technical replicates) and exact sample sizes underlying each comparison are not specified in the visible text.↳ Could also: Explicitly stating the number of independent biological replicates per condition and the replicate structure used in each statistical test — Clarifying replicate structure helps readers assess the generalizability of the findings and whether the chosen statistical test appropriately accounts for any nested or repeated-measures structure in the data.
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-35806266
Paper: Keppner et al. 2022, Int J Mol Sci 23(13):7262. "Analysis of the Hypoxic Response in a Mouse Cortical Collecting Duct-Derived Cell Line Suggests That Esrra Is Partially Involved in Hif1α-Mediated Hypoxia-Inducible Gene Expression." PMID 35806266 · PMCID PMC9267015 · DOI 10.3390/ijms23137262
Datasets the paper relies on
| Accession | Source | What it is | Role | In scope |
|---|---|---|---|---|
| PRJEB53226 (ERP138014) | ENA/EBI-SRA | Authors' OWN bulk RNA-seq, mouse mCCDcl1 cells, 100bp PE NovaSeq 6000, 3 normoxia + 3 hypoxia (0.2% O2, 24h) | PRIMARY reproduction target | YES |
| GSE91805 | GEO | Public ChIP-seq, ESRRA in K562 (human) — reused | ChIP-seq overlap (Venn) | partial / secondary |
| GSE120885 | GEO | Public ChIP-seq, HIF-1α/2α/β in RCC4/HepG2/HKC8 (human) — reused | ChIP-seq overlap (Venn) | partial / secondary |
NOTE: the room BRIEF lists "data: GSE91805", but per the paper's Methods that is a reused public ChIP-seq set, not the core data. The reproducible quantitative result comes from the authors' own RNA-seq (PRJEB53226).
In-scope, pipeline-derived results
Primary claim (C1). Differential expression hypoxia vs normoxia in mCCDcl1:
- Pipeline (Methods §4.6–4.7): STAR v2.7.3a align to GRCm38.p6 (ENSEMBL) with
--quantMode GeneCounts --outFilterMultimapNmax 2; DE with DESeq2, thresholds FDR 0.1, |logFC| > 1, adjusted p-value < 0.05. - Reported: 3086 DEGs total, 1679 up-regulated, 1407 down-regulated (Results §2.1 / Methods §4.7).
- Source: paper text + Supplementary Table S1.
Secondary (C2, attempt if feasible). Top-15 up / top-15 down genes in the volcano plot (Figure 1B) — specific gene identities + direction.
Out of scope (not pipeline-derived → not attempted)
- RT-qPCR validation of 6 genes (Fig 2) — wet-lab.
- Western blots, HIF1A/ESRRA knockdown experiments — wet-lab.
- ChIP-seq Venn overlap (Fig with GSE91805/GSE120885) is plotting via the third-party Venn-Diagram-Plotter tool; only attempted as a secondary if the primary lands cleanly, because the inputs (called peaks) and the exact overlap definition are underspecified.
Pipeline named per result
- C1: STAR 2.7.3a (align/count) → DESeq2 (DE). Method cards: STAR 87% clean, DESeq2 78% clean.
- C2: derived from C1's DESeq2 result table (ranking by padj/logFC).
Assessments & scoring basis
Each contributor’s verdict, the per-question basis, and the auditable, itemised worksheet behind it.
An automated assessment. It can flag an open question for review but can never, on its own, record a discrepancy verdict (C5) against a paper.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
Clean within-tolerance reproduction on the authors' own deposited RNA-seq (PRJEB53226): edgeR recovers 3056/1650/1406 vs the reported 3086/1679/1407 (99.0%/98.3%/99.9%) and DESeq2 is within ~1.5%, with all 9 canonical HIF1a targets correctly induced and Esrra mildly down — matching the paper's 'partially involved' framing. The only deviations are technical (STAR/edgeR/DESeq2 version drift and exact 0.5-CPM filter interpretation), all on our side, none affecting the conclusion. One paper-side blemish: the Methods attribute the counts to DESeq2 but describe edgeR's filter — a description inconsistency, not a derivability problem. Overall a solid green reproduction.
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Reproduction footprint
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