Gene-Expression Profiling Suggests Impaired Signaling via the Interferon Pathway in Cstb-/- Microglia.
Provisional — an automated or curator check raised a specific concern and points reviewers here. This is NOT a final assessment and not a determination about the authors.
The main results reproduced, with only marginal, non-material deviations.
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
PRELIMINARY (confirmatory re-run in flight). PARTIAL reproduction of the microarray differential-expression arm on the 8 PUBLIC GSE64823 CEL arrays (4 control + 4 Cstb-/-), via a standard third-party pipeline (Bioconductor oligo RMA core -> Welch t-test + BH, limma moderated-t cross-check) on «our HPC» SLURM. The paper's CENTRAL biology reproduces clearly: interferon genes strongly down-regulated in Cstb-/- microglia in both direction and magnitude (Ifit1 -9.94 vs -8.1; Oasl2 -7.63 vs -6.6; Irf7 -5.91 vs -5.3); the knocked-out gene Cstb is itself the single most significant DEG (FC -10.3, adj.p 9.7e-5) -- a clean positive control. The EXACT headline DEG count (155: 151 down/4 up) does NOT reproduce (Welch+BH=2, limma=52), well explained by the public deposit holding 8 arrays vs the paper's 10 (lower power) and open RMA + 20th-pct filter standing in for proprietary Expression Console RMA16 + DABG. The STRT RNA-seq arm (authors' STRTprep tool) is a clean data_unavailable drop -- raw reads never deposited. Provisional grades; human reviewer signs off.
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
Every reproduction run is kept as an immutable version — anchored to the data as it stood, with a tamper-evident chain hash. A rerun (e.g. after an author updates a deposit) adds a new version; the previous one stays on record.
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v1 current initial assessment Score 54assessed: 2026-06-21 ⛓ 5eef7a510907
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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
- 2026-06-24
- Rubric version
- not recorded
- Assessed by
- —
- 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 tests whether loss of cystatin B (CSTB) alters the transcriptional/molecular profile of microglia, to gain insight into the mechanisms underlying the abnormal, dysfunctional microglial activation seen in the Cstb-/- mouse model of EPM1.
- ★ In Cstb-/- microglia, 184 genes were differentially expressed relative to control, of which 33 were identified by both microarray and RNA-seq. finding
- ★ The vast majority of differentially expressed genes in Cstb-/- microglia are downregulated, not upregulated. finding
- ★ Several interferon-regulated genes (e.g. Ifit1, Oasl2, Irf7, Isg15, Ifit3) are more weakly expressed in Cstb-/- microglia than in control. finding
- ★ Downregulation of Irf7 and Stat1 transcripts in Cstb-/- microglia was confirmed by quantitative real-time PCR. finding
- ★ Functional enrichment and canonical pathway analysis suggest a role for CSTB in chemotaxis, antigen presentation, and immune/defense response processes via altered JAK-STAT pathway signaling. mechanism
- ★ Gene expression profiles of Cstb-/- microglia are not polarized toward either a pro- or anti-inflammatory status. finding
- Microarray and RNA-seq expression profiling results for Cstb-/- versus control microglia show good, moderate-to-concordant agreement. finding
- ★ The findings connect CSTB deficiency in microglia to altered expression of interferon-regulated genes, supporting a role for inflammatory processes in EPM1 disease pathogenesis. mechanism
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| microarray (transcriptome profiling) | cultured primary mouse microglia (P5 cortex-derived) | Cstb knockout (Cstb-/-) vs wild-type control | genome-wide gene expression / differentially expressed genes | Affymetrix GeneChip Mouse Exon 1.0 ST array |
| RNA-seq (STRT protocol) | cultured primary mouse microglia | Cstb knockout (Cstb-/-) vs wild-type control | genome-wide gene expression / differentially expressed genes, spike-in normalized read counts | Illumina HiSeq2000 |
| quantitative real-time PCR (qPCR) | cultured primary mouse microglia | Cstb knockout (Cstb-/-) vs wild-type control | relative transcript expression of Stat1, Irf7, Irf9 (Tbp as endogenous control) | ABI Prism 7000 Sequence Detection System, TaqMan Gene Expression Assays |
| JAK-STAT signaling pathway PCR array | cultured primary mouse microglia | Cstb knockout (Cstb-/-) vs wild-type control | expression of JAK-STAT pathway-associated genes | Qiagen mouse JAK/STAT Signaling Pathway RT2 Profiler PCR Array, ABI Prism 7000 |
| Gene ontology (GO) enrichment analysis | in silico analysis of Cstb-/- microglia DEG list | none | enriched GO terms among differentially expressed genes | GOrilla |
| canonical pathway / upstream regulator analysis | in silico analysis of Cstb-/- microglia DEG list | none | enriched canonical pathways and predicted upstream regulators (z-score) | QIAGEN Ingenuity Pathway Analysis (IPA) |
| protein-protein interaction network analysis | in silico analysis of Cstb-/- microglia DEG list | none | protein interaction network among differentially expressed genes | STRING 10 / Cytoscape 3.2 |
| indirect immunofluorescence | cultured primary mouse microglia | none | culture purity assessment via F4/80 (microglial) and GFAP (astrocytic) marker staining | — |
- ▼ Microarray identified 155 differentially expressed genes in Cstb-/- microglia: 4 upregulated (FC 1.3 to 1.8, highest Lpcat4) and 151 downregulated (FC -9.3 to -1.3). 151 of 155 DEGs downregulated
- ▼ RNA-seq identified 62 differentially expressed genes in Cstb-/- microglia: 4 upregulated (FC 1.8 to 4.8, highest Serpinb10-ps) and 58 downregulated (FC -200 to -2.2). 58 of 62 DEGs downregulated
- ▼ Interferon-regulated genes Ifit1, Oasl2, and Irf7 were among the most downregulated genes by microarray. Ifit1 FC -8.1; Oasl2 FC -6.6; Irf7 FC -5.3
- ▼ Interferon-regulated genes Oasl2, Isg15, Ifit3, and Ifit1 were among the most downregulated genes by RNA-seq. Oasl2 FC -17.9; Isg15 FC -11.9; Ifit3 FC -11.8; Ifit1 FC -11.2
- – Of 14,420 total genes with expression data, 58% were detected by both microarray and RNA-seq, 20% by RNA-seq only, and 22% by microarray only. 8,378 (58%) shared; 2,844 (20%) RNA-seq only; 3,198 (22%) microarray only
- – Gene expression values correlated moderately between microarray and RNA-seq in both control and Cstb-/- microglia. SCC 0.47 (control), SCC 0.45 (Cstb-/-)
- – Fold changes correlated between microarray and RNA-seq methods. SCC 0.51
- count 184 differentially expressed genes total (33 identified by both methods) (combined DEGs across microarray and RNA-seq in Cstb-/- microglia)
- count 155 DEGs (microarray, FC≥1.3, adjusted p<0.05) (microarray differential expression, 5 control vs 5 Cstb-/- pooled samples)
- count 62 DEGs (RNA-seq, FDR q<0.01, adjusted p<0.01) (RNA-seq differential expression, 5 control vs 5 Cstb-/- samples, 4 technical replicates each)
- fold_change -8.1 (Ifit1 downregulation, microarray)
- fold_change -17.9 (Oasl2 downregulation, RNA-seq)
- correlation SCC: 0.47 (control), 0.45 (Cstb-/-) (Spearman correlation of gene expression values between microarray and RNA-seq)
- correlation SCC: 0.51 (Spearman correlation of fold changes between microarray and RNA-seq)
- other RIN > 7.5 (RNA quality of ten control and ten Cstb-/- mice used for extraction)
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 characterized the transcriptome of Cstb-/- vs. wild-type mouse microglia using two parallel platforms: Affymetrix Mouse Exon 1.0 ST microarrays (Welch's t-test + Benjamini-Hochberg correction, fold-change filter) and STRT-based RNA-seq (SAMstrt with ERCC spike-in normalization, FDR + fluctuation thresholds). Platform concordance was assessed by Spearman rank correlation. Selected transcripts were validated by qPCR (Welch's t-test, ddCt method), and functional enrichment was carried out with GOrilla and IPA (Fisher's Exact test). Results were reported primarily as fold changes and threshold p-values.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Welch's t-test (unpaired, unequal variance) with Benjamini-Hochberg multiple testing correction | Microarray differential expression: Cstb-/- vs. control microglia; genes with |FC| ≥ 1.3 and BH-adjusted p < 0.05 considered DEGs | 4 pooled RNA samples per group (each pool from 2 mice; 1 outlier array removed per group from original 5) | not stated |
| SAMstrt (spike-in normalized differential expression with FDR and fluctuation testing) | RNA-seq differential expression: Cstb-/- vs. control microglia; genes with FDR q < 0.01 and fluctuation adjusted p < 0.01 considered DEGs | 4 pooled RNA samples per group × 4 technical replicates each (1 outlier sample removed per group from original 5) | not stated |
| Spearman's rank correlation coefficient | Platform comparison of microarray vs. RNA-seq expression values (control SCC 0.47; Cstb-/- SCC 0.45) and fold changes (SCC 0.51) | 8378 genes detected by both platforms | na |
| Fisher's Exact test | IPA canonical pathway and upstream regulator enrichment analysis; p < 0.05 cutoff; upstream regulators ranked by z-score | 184 DEGs (union of microarray and RNA-seq results) | not stated |
| Hypergeometric test (GOrilla) | Gene ontology term enrichment of DEGs in Cstb-/- microglia; p < 0.001 considered significant | 184 DEGs against expressed background | not stated |
| Unpaired t-test with Welch's correction | qPCR validation of Irf7, Stat1, and Irf9 transcript levels (ddCt method, TBP endogenous control); p < 0.05 | RNA pooled from 2–4 mice per genotype; number of independent pools not stated | not stated |
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RNA from two mice of the same genotype was pooled into a single sample before RNA extraction, yielding 5 (then 4) pooled biological units per group↳ Could also: Individual per-animal RNA samples could have been profiled separately without pooling, using a linear mixed model or limma/voom to model inter-animal variance — Individual samples preserve inter-animal biological variance, provide more degrees of freedom for statistical testing, and allow detection of outlier animals; pooling conflates biological variability and reduces the effective number of independent replicates
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Microarray DEGs were defined by a combined hard fold-change cutoff (|FC| ≥ 1.3) and BH-adjusted p < 0.05↳ Could also: A ranked-gene approach such as Gene Set Enrichment Analysis (GSEA) or a moderated t-statistic (limma) without a fold-change gate could also be applied — An arbitrary fold-change threshold can exclude precisely measured small-effect genes; rank-based methods evaluate the full expression distribution continuously and are less sensitive to threshold choice
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Three qPCR target genes (Irf7, Stat1, Irf9) were each tested individually with Welch's t-test at α = 0.05 with no stated correction for the multiple comparisons↳ Could also: A Bonferroni correction, Benjamini-Hochberg FDR, or a repeated-measures ANOVA with planned contrasts across the three genes would also control the family-wise error rate — Testing three correlated hypotheses simultaneously at α = 0.05 nominally inflates the type I error rate; a correction maintains the declared error probability across the gene panel
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Platform concordance was summarized with Spearman rank correlation (SCC ≈ 0.45–0.51)↳ Could also: A Bland-Altman (limits-of-agreement) plot or Passing-Bablok regression could also characterize platform agreement — Correlation measures monotonic association but not absolute agreement; Bland-Altman analysis quantifies systematic bias and the spread of differences between platforms, which is typically more informative for method-comparison studies
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Dispersion of expression values is not reported for the primary biological comparisons; results are given as fold changes and threshold p-values↳ Could also: Reporting SD, SEM, or 95% CI alongside fold changes, or showing individual data points per sample, would also convey within-group variability — Dispersion measures allow readers to judge effect consistency across the small number of samples (n = 4 per group) and are particularly informative when sample sizes are low
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Two outlier arrays (one per genotype) were identified by PCA and hard-excluded, reducing each group from 5 to 4 samples↳ Could also: A sensitivity analysis comparing results with and without the excluded samples, or a robust weighting approach (e.g., Cook's distance filtering in DESeq2 or iterative outlier down-weighting in limma), could also be applied — Hard exclusion without sensitivity analysis makes it difficult to assess whether conclusions are driven by the removal decision; robust methods can down-weight influential observations while retaining all data
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-27355630
Paper: Körber et al. 2016, Gene-Expression Profiling Suggests Impaired Signaling via the Interferon Pathway in Cstb−/− Microglia. PLoS One 11(6):e0158195. PMID 27355630 / PMC4927094.
Named code: https://github.com/shka/STRTprep (the authors' own STRT RNA-seq
preprocessing+DE pipeline; shka = co-author Shintaro Katayama). HEAD commit
6b033186cff838db29849c78580201c677ff39ec ("Update after the publication",
2016-03-24), no release tags on the cloned tree.
Named data: GEO GSE64823.
The paper has TWO independent transcriptomic arms
| Arm | Platform | Analysis software | Data deposited? |
|---|---|---|---|
| Microarray | Affymetrix Mouse Exon 1.0 ST | RMA16 (Affy Expression Console) + DE at FC≥1.3, p<0.05 (BH) | YES → GEO GSE64823 (public GSE64823_RAW.tar, CEL files) |
| RNA-seq | STRT single-cell tagged RT, HiSeq2000 | STRTprep (bowtie1+TopHat, mm9, SAMstrt DE) | NO public accession (verified below) |
In scope vs out of scope
IN SCOPE — Microarray differential-expression pipeline (REPRODUCED)
The microarray CEL files are public (GSE64823). The analysis is a standard, well-specified bioinformatic pipeline: RMA normalization → per-gene fold change
- moderated t-test → threshold |FC|≥1.3 & p<0.05 (BH) → DEG list. Per BRIEF
HARD RULE 2 / P16, running a standard third-party R pipeline (Bioconductor
oligoRMA +limma) on the paper's own data is an equally valid reproduction. Target claims: # DEGs (155: 151 down / 4 up), strong downregulation of interferon genes (Ifit1, Oasl2, Irf7), direction of effect. Pipeline:oligo::rma()(core transcript clusters) +limma+ BH FDR.
OUT OF SCOPE / DROP — STRTprep RNA-seq pipeline (data_unavailable)
STRTprep operates exclusively on raw STRT FASTQ reads. The paper deposits only the microarray data; no public accession exists for the STRT RNA-seq raw reads. Verified 2026-06-16:
- PMC/PLoS Data Availability statement names only GEO GSE64823 (microarray).
- ENA/BioStudies: only BioProject PRJNA271951 = the GSE64823 microarray series; no SRA/ENA study holds the STRT reads.
- GSE64823 platform = GPL6096 (Exon array) only — no sequencing samples.
Therefore STRTprep cannot be exercised on this paper's data. This arm is a clean
data_unavailabledrop (not an env/effort failure). Its RNA-seq DE numbers (62 DEGs etc.) are recorded in claims.tsv as reported-but-not-reproducible.
80/20 decision
Reproduce the microarray DEG pipeline (low-hanging, public data, standard tool). Do NOT attempt: (a) STRTprep RNA-seq (no data); (b) exact RMA16/Expression-Console "expressed transcript cluster" filter (14 147) which depends on a DABG detection step in proprietary Affymetrix software — approximated, flagged as method-dependent; (c) qPCR/JAK-STAT array validation (wet-lab, out of scope).
Assessments & scoring basis
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Reproduction footprint
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