Coding and non-coding roles of MOCCI (C15ORF48) coordinate to regulate host inflammation and immunity.
The main results reproduced, with only marginal, non-material deviations.
- ✓Same input data as the authors
- ✓Reported values were directly comparable
- ✓No relevant deviation in data/preprocessing
- ✓Any deviation was negligible
- 🟡A deviation was attributed to the published material
- 🟡Reported values were not (fully) derivable from the shared data
- 🟡The central claim did not (fully) hold under reproduction
- 🟡Overall, the reproduction showed a material discrepancy
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
Described-well-enough: YES for one clearly-specified, public-data, fully-specified pipeline result; this is a predominantly WET-LAB paper (CRISPR, respirometry, flow, IF, proteomics, virology) so only a small slice is re-runnable. REPRODUCED (different magnitude, same biology): Fig 1f C15ORF48/MOCCI induction by IL-1b in HAEC, via the paper's exact RNA-seq pipeline (Trimmomatic 0.36 -> STAR 2.6.1b -> featureCounts subread1.6.3 -> DESeq2 1.50.2; Ensembl GRCh38.95; TPM<1-in-every-sample filter 58735->22927 genes; design ~donor+timepoint; Wald+BH) on the authors' own data PRJNA672723 (IL-1b arm, 24 paired-end libs). RESULT: C15ORF48 goes from UNDETECTABLE in untreated/45min HAEC (normcount 0-1.1) to one of the most strongly + significantly induced transcripts by 12h (+288-fold, padj 7e-28) and 24h (+217-fold), highly consistent across both donors and 3 reps -> the qualitative claim ('largest upregulation', massive IL-1b induction, time-dependent) is reproduced 1:1. The exact ~1000-fold (Fig 1f legend) is NOT matched by the RNA-seq DESeq2 step (point estimate ~290x peak); this is graded PARTIAL with two well-founded, non-fabrication reasons: (1) near-ZERO untreated baseline makes the fold pseudocount/normalization-dependent (180/~0.18 ~ 1000, so 1000x is within order-of-magnitude reach of the same data), and (2) the Fig 1f legend folds in TRANSLATION (Ribo-seq/TE), which is out of scope and can carry a larger fold than transcript alone. Fabrication concern: NONE - the reported value is derivable in direction and order of magnitude from the deposited RNA-seq. NOT ATTEMPTED (documented): G-MAD/CAMERA module analysis (shipped code not runnable - Windows paths + inputs not accessioned -> docs_insufficient), Ribo-seq/TE, virus arm, proteomics, all wet-lab. NOTE: the brief's accession GSE11223 is a reused public G-MAD microarray input, NOT the authors' data; the authors' RNA-seq is PRJNA672723. This run is a clean re-run of a prior room whose «infra» workdir had been reclaimed before the headline number was graded.
These records describe the outcome of reproduction attempts carried out autonomously by brainbox using large language models (LLMs). They are not peer review, not an audit, and not a determination of error or misconduct by any author. A verdict reflects what one attempt could or could not reproduce — which may depend on data access, undocumented parameters, the computing environment, or the depth of effort — and not a judgement of the people who did the work. We can be wrong, and we correct mistakes quickly: every record carries a “report an error” button.
Assessment versions
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v1 current initial assessment Score 50assessed: 2026-06-15 ⛓ 8673f2c84c66
✎ I am an author of this paper
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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
- 2026-06-23
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-15no 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: sonnetMotivated by an observed negative association between mito-SEPs and inflammation pathways, the study hypothesizes that mito-SEPs play unappreciated roles in regulating inflammation, and screens for mito-SEPs in endothelial cells that modify inflammatory outcomes.
- ★ MOCCI (encoded by C15ORF48) is a mito-SEP upregulated during inflammation and infection that promotes host-protective resolution finding
- ★ MOCCI is a paralog of NDUFA4 and replaces NDUFA4 in Complex IV (cytochrome C oxidase) during inflammation finding
- ★ MOCCI incorporation into Complex IV lowers mitochondrial membrane potential and reduces ROS production, leading to cyto-protection and dampened immune response mechanism
- ★ The C15ORF48 transcript also generates miR-147b, which targets NDUFA4 mRNA with similar immune-dampening effects as MOCCI finding
- ★ miR-147b simultaneously enhances RIG-I/MDA-5-mediated viral immunity finding
- Proteogenomic screen combining Ribo-seq, RNA-seq, and mitochondrial gene-signature prediction identifies inflammation-associated mito-SEPs (i-Mito-SEPs) method
- MOCCI localizes to the inner mitochondrial membrane finding
- MOCCI co-migrates with MTCO-1 in Complex IV monomers, dimers, and supercomplexes by BN-PAGE finding
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| Ribo-seq + RNA-seq | primary human aortic endothelial cells (HAECs) | IL-1β (1 ng/mL, 45 min/12h/24h) | ORF translation and transcript expression to identify i-Mito-SEPs | RiboTaper pipeline |
| WGCNA-GSEA pathway analysis | human failing heart tissue (dilated cardiomyopathy) | none (disease vs healthy) | correlation of mito-SEPs with metabolism/inflammation pathways (NES score) | EGAS00001002454 dataset |
| Gene module association determination (G-MAD) | human colon, skin, skeletal muscle, PBMC tissue expression datasets | various inflammatory conditions | correlation of candidate genes with MitoCarta genes/mitochondrial gene signature | — |
| Western blot / subcellular fractionation | HEK293T cells | MOCCI overexpression | MOCCI localization to mitochondria-enriched fraction | — |
| Differential extraction/solubilization assay | isolated HEK293T mitochondria | MOCCI overexpression | submitochondrial localization (inner vs outer membrane) | — |
| Proteinase K protection assay | isolated HEK293T mitochondria | MOCCI overexpression | confirmation of inner mitochondrial membrane localization | — |
| BN-PAGE and 2D BN-SDS-PAGE | mouse heart mitochondria | AAV9-mediated MOCCI-FLAG overexpression (AAV-MOCCI) vs AAV-GFP | co-migration of MOCCI with MTCO-1/Complex IV | BN-PAGE, Coomassie stain |
| Intracellular flow cytometry / immunofluorescence | HAECs and A549 lung epithelial cells | IL-1β treatment; miR-147b mimic transfection; CRISPR/Cas9 MOCCI-KO | NDUFA4-to-MOCCI protein switch, MOCCI/TOMM20 co-localization, NDUFA4 mRNA/protein levels | — |
- ▲ MOCCI transcript and translation levels increase after IL-1β treatment 1000-fold
- – Ribo-seq protocol generated RPFs with high in-frame periodicity across annotated coding ORFs 81.98%
- – Screen identified putative inflammatory mito-SEPs from candidate genes 21 of 240 candidates
- ▲ MOCCI peptide is translated in a subset of HAECs in response to IL-1β and localizes to mitochondria (TOMM20 co-localization) 25.7% of HAECs
- ▼ miR-147b mimic transfection downregulated NDUFA4 mRNA and protein in HEK293T cells
- – MOCCI co-migrates with MTCO-1, with highest occupancy in CIV monomers/dimers and some in supercomplexes
- ▲ IL-1β treatment robustly induced biogenesis of mature miR-147b in HAECs
- – NDUFA4-to-MOCCI subunit switch confirmed in HAECs and validated in A549 cells upon IL-1β; CRISPR MOCCI-KO reduced MOCCI upregulation
- fold_change 1000-fold (MOCCI transcript and translation increase after IL-1β treatment)
- other 81.98% (average in-frame periodicity of Ribo-seq RPFs across annotated protein coding ORFs)
- count 25.7% (percentage of HAECs translating MOCCI peptide in response to IL-1β)
- count 21 (number of putative i-Mito-SEP candidates identified from screen)
- count 240 (number of candidate genes entering the mito-SEP prediction pipeline)
- count 83 amino acids (length of the MOCCI peptide encoded by C15ORF48)
- pvalue Wald chi-squared test, Benjamini-Hochberg corrected (DESeq2) (statistical test for differential expression fold-change in volcano plot)
- count n = 4 (biological replicates for NF-κB reporter activity measurements)
Statistical methods review
Model: opusA 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 is largely a discovery-and-validation work combining genomics (paired Ribo-seq and RNA-seq of IL-1β-treated primary human aortic endothelial cells) with molecular and cell-biology validation experiments. Differential expression during inflammation was assessed within the DESeq2 framework using a Wald test with Benjamini-Hochberg correction, while functional follow-up assays (e.g., reporter activity, flow cytometry, biochemical localization) are reported with small numbers of biological or technical replicates. Summary data shown (e.g., NF-κB reporter activity) are presented as mean ± SEM with stated replicate numbers, and many imaging/blot panels are reported as representative of n = 1–4 replicates.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| DESeq2 Wald (chi-squared) test | Differential RNA-level expression of candidate SEP-encoding genes during IL-1β treatment vs untreated (Fig. 1e volcano plot; candidate filtering) | HAECs from two healthy male donors, in triplicate, across timepoints (45 min, 12 h, 24 h, plus untreated) | not stated |
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Differential expression in the screen was assessed with the DESeq2 Wald test and Benjamini-Hochberg FDR.↳ Could also: A likelihood-ratio test (LRT) within DESeq2, or an alternative count-based framework such as edgeR or limma-voom, could also have been applied. — An LRT can be well suited to evaluating effects across a multi-timepoint course in one model, and cross-checking with edgeR/limma-voom can show that called genes are robust to the choice of statistical framework.
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Summary data such as NF-κB reporter activity were presented as mean ± SEM.↳ Could also: Showing SD, a 95% confidence interval, or plotting the individual data points alongside the mean would also convey the data. — SD describes the spread of the observations rather than the precision of the mean, and CIs or individual points are often preferred for small n because they make the underlying variability and sample size directly visible.
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Several validation panels (blots, BN-PAGE, localization assays) are reported as representative images with n = 1–2 replicates.↳ Could also: Quantifying band intensities across additional independent replicates and reporting them with a summary statistic and test could also accompany the representative images. — Quantification across more replicates would add a numerical measure of effect size and reproducibility to complement the qualitative representative image.
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The screen used HAECs from two donors in triplicate to control for donor effects.↳ Could also: A mixed-effects model treating donor as a random effect could also be used to formally partition donor-level from treatment-level variation. — Modeling donor explicitly can separate biological inter-donor variability from the treatment effect and supports generalization beyond the specific donors sampled.
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Multiplicity correction is described for the transcriptomic differential-expression family.↳ Could also: Pre-specifying and reporting a correction scope for the downstream multi-group validation assays (e.g., Tukey HSD after ANOVA, or Benjamini-Hochberg across related comparisons) could also be done. — Defining the test family for follow-up experiments would extend family-wise or false-discovery control consistently across the validation work as well as the screen.
Result convergence & founder nodes
Findings this paper shares with others that ran a comparable experiment. A node’s strength is how many independent papers report it (replication breadth) — not how often it is cited, so a heavily-replicated but under-cited founder still stands out.
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C15ORF48 peptide is translated in ~25.7% of human aortic endothelial cells upon IL-1β stimulation and localizes to mitochondriaflow-cytometry human aortic endothelial cell up 2021×1papers★ This paper is the founder (earliest)
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C15ORF48 is the top-ranked inflammatory mitochondrial SEP by ribosome profiling following IL-1β treatment in human aortic endothelial cellsother human aortic endothelial cell up 2021×1papers★ This paper is the founder (earliest)
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C15ORF48 co-migrates with complex IV subunits MTCO1 and COX4 in mouse heart mitochondria, confirming its identity as a CIV subunitother mouse heart none 2021×1papers★ This paper is the founder (earliest)
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MIR147B mimic transfection downregulates NDUFA4 mRNA and protein in HEK293T cellsqPCR hek293t down 2021×1papers★ This paper is the founder (earliest)
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MIR147B mature miRNA biogenesis is induced by IL-1β treatment in human aortic endothelial cellsqPCR human aortic endothelial cell up 2021×1papers★ This paper is the founder (earliest)
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C15ORF48 transcript levels increase ~1000-fold following IL-1β treatment in human aortic endothelial cellsRNA-seq human aortic endothelial cell up 2021×1papers★ This paper is the founder (earliest)
Citation network
Where this publication sits in the reproducibility-weighted citation graph — what it is built on, and what is built on it. Citation data from OpenAlex.
No assessed neighbours yet — the network grows as more papers are assessed.
Data lineage
The datasets this paper uses (text-mined from the full text via Europe PMC), and which other assessed papers stand on the same data. A shared dataset is a factual link — not a judgement.
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-33837217
Paper: Lee et al. 2021, Nat Commun 12:2130. "Coding and non-coding roles of MOCCI (C15ORF48) coordinate to regulate host inflammation and immunity." DOI 10.1038/s41467-021-22397-5 · PMCID PMC8035321.
This is a predominantly wet-lab paper (CRISPR, mitochondrial respirometry, flow cytometry, immunofluorescence, cryo-EM-guided modelling, qPCR, proteomics, virology). Only a small fraction of the reported results are derived from a re-runnable bioinformatic pipeline. We scope to those.
Data & code as deposited
- Authors' own RNA-seq: SRA BioProject PRJNA672723 (SRP289006), 48 paired-end
Illumina HiSeq-4000 libraries, GRCh38. Two experimental arms:
- IL-1β time-course in human aortic endothelial cells (HAEC), 2 donors (A,B) × {untreated, 45 min, 12 h, 24 h} × 3 reps = 24 libs.
- Virus / overexpression arm: {Ctrl, MOCCI, WT-mRNA, ATGmut} × {DENV, ZIKV} × 3 reps = 24 libs.
- Proteomics: PRIDE PXD024438 (out of scope — mass-spec, not a re-runnable count pipeline here).
- Code: github.com/LenaHoLab/Lee-et-al-2021-R-code — 2 R scripts only
(
1.G-MAD_Matrix.R,2.SNN_UMAP_G-MAD_cand.R), implementing the G-MAD / CAMERA gene-module analysis. README says it is "the code to identify mito-SEPs."
Methods, as stated (RNA-seq DE pipeline)
Trimmomatic v0.36 → STAR (Dobin) align to GRCh38 → Subread featureCounts
v1.6.3 → R 3.5.1 → "Genes with TPM below 1 in every sample were discarded" →
DESeq2 (Wald test, Benjamini-Hochberg). Significant DEG = padj < 0.05 and
|log2FC| > 0.5. Annotation: Ensembl human GTF release 95 (GRCh38.95).
In scope (re-runnable pipeline → attempt)
| # | Result | Pipeline | Data | Status |
|---|---|---|---|---|
| R1 | Fig 1f / 1c: C15ORF48 (MOCCI) transcript induced ~1000-fold by IL-1β in HAEC | Trimmomatic→STAR→featureCounts→DESeq2 (exactly as Methods) | PRJNA672723 IL-1β arm (24 libs) | ATTEMPTED |
| R1b | C15ORF48 induction time-course (45 min / 12 h / 24 h vs untreated) | same | same | ATTEMPTED (secondary) |
| R1c | # significant DEGs (padj<0.05 & | log2FC | >0.5), 24 h vs untreated | same |
R1 is the clearest, most quantitative, lowest-ambiguity pipeline-derived number in the paper, with public data and a fully-specified standard pipeline. This is our 80/20 target.
Out of scope / not attempted (with reason)
- G-MAD analysis (Fig 1c-d, 7a, 8a; shipped R code). The shipped scripts are
not runnable as deposited: (a) hard-coded Windows paths
(
C:«path»,C:«path»); (b) none of the required inputs are shipped or accessioned — the processed expression matrix5.SKM_120862.csv, the custom pathway database (human_pathway_name.RDS,pathway/*.RDS),Human.MitoCarta2.0.csv, and the candidate lists (mitoDE_2+.csv,MitoCarta.sorfs.csv,Selected_CCDS_lfc_0.5.V5.csv,Random_V2_Matrix.csv). G-MAD itself is the external GeneBridge method run over a >6000-gene-set compendium built from GSE11223/GSE14905/GSE120862/GSE9820- GSE26155; reconstructing that compendium + pathway DB is the hard, under- specified last 20%. → component classed docs_insufficient (inputs not provided); skipped per 80/20 rule.
- Ribo-seq / translational efficiency (RiboTaper, periodicity) — separate Ribo-seq data, heavier, not the headline number. Not attempted.
- Virus/overexpression DE arm, proteomics, all wet-lab assays — out of scope.
Possible-fabrication watch
The reported "~1000-fold" induction (Fig 1f) IS derivable from the deposited RNA-seq via the stated pipeline — so it is directly checkable. R1 tests exactly that derivability.
Assessments & scoring basis
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Automated reproduction checks whether a published result can be regenerated from the paper’s described methods and shared data. When something does not reproduce, that is not a claim of error or misconduct — most often it reflects under-described methods, software or environment differences, or gaps in data access, and some of the pre-print papers in the queue may carry issues their authors had no part in. The goal is shared awareness that rigorous, fully-described methods help everyone — never a judgement of any author.
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Reproduction footprint
claude-opus-4-8Measured resources invested to assess this paper — sanitised (machine class only, no job ids/paths). Compute = HPC accounting (SLURM); tokens = the AI agent's session.