An archaeal histone-like protein regulates gene expression in response to salt stress.
The main results reproduced: recomputed values matched the published ones within tolerance.
- Nothing in this column.
- 🟡Could not use the authors’ exact input data
- 🟡Reported values were only indirectly comparable
- 🟡A deviation arose in the data or preprocessing
- 🟡A deviation was attributed to the published material
- 🟡Reported values were not (fully) derivable from the shared data
- 🟡The deviation was non-trivial in magnitude
- 🟡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
REPRODUCED (partial->strong, 1:1 where the deposit allows). Authors' own repo (amyschmid/HpyA_codes, HEAD 7babe18) ships commented R-markdown alongside its processed inputs and final supplementary tables. All 10 in-scope pipeline claims attempted and graded on «our HPC» with paper-pinned environments (DESeq2 1.30.1 / R 4.0.5 «job»; grofit 1.1-1 from shipped tarball; IRanges/GenomicRanges/rtracklayer): 6 EXACT, 4 WITHIN-TOL, 0 mismatch. RNA-seq DEG counts 168/143/46/21 are exactly consistent with shipped TableS4 (Condition tally), and an independent DESeq2 1.30.1 re-run recovers 140/143 (98%) of the final low-salt DEGs (the final = intersection of the shipped 21-sample arm with a 5-outlier arm whose input combineddata_5reps.csv is NOT deposited, so the single shipped matrix yields larger pre-intersection counts 221/52/248). ChIP 59 peaks is exact in shipped TableS3 (Basic_S3=59 rows); independent IRanges annotation of the shipped BEDs gives 64 peaks / 96 genes vs reported 59 / 86, the ~8-12% excess being the documented manual artifact-curation. Growth: grofit logistic on shipped curves gives WT 88-93% (paper 89%, exact when the one flagged outlier is excluded), KO 66.4% median (paper 67%), and t-test P=0.0011-0.0013 satisfying the reported P<0.008. No fabrication signal: every reported value is auditable against the deposited final tables. NOT attempted (out of scope): raw-read upstream alignment/trimming/peak-calling from GSE182514 (TrimGalore/Bowtie2/HTSeq/MACS2), wet-lab assays, microscopy/circularity, qPCR.
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 94assessed: 2026-06-21 ⛓ e4b1a320c48e
✎ I am an author of this paper
Updated or fixed a deposit, or is there an erratum? Ask us to re-run the metrics. We verify by email first; the new result is published as a new version with full history — nothing is overwritten.
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
- 2026-06-21
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-19no 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: sonnetGiven the unusual negatively charged, highly ionic haloarchaeal cytoplasm, HpyA's non-canonical gene-regulatory function (rather than DNA-packaging) is hypothesized to be linked to the unique hypersaline cytoplasmic environment of Halobacterium salinarum.
- ★ HpyA is important for maintaining wild-type growth rate under reduced salinity finding
- ★ HpyA is important for maintaining rod-shaped cell morphology under reduced salinity finding
- ★ HpyA preferentially binds DNA at ~60 discrete genomic sites under low salt in a reproducible, salt-dependent manner finding
- ★ HpyA binding is too sparse to coat or compact the genome, unlike canonical archaeal histones mechanism
- ★ High prevalence of HpyA binding within gene bodies suggests a regulatory mechanism distinct from canonical transcription factors mechanism
- ★ HpyA directly regulates iron/ion uptake genes via DNA binding mechanism
- ★ HpyA globally and indirectly activates other ion uptake, purine biosynthesis, and DNA replication/repair pathways in a salt-dependent manner finding
- ★ HpyA functions as a specific transcriptional regulator of metal ion balance rather than a genome-packaging histone mechanism
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| growth curve phenotyping | Hbt. salinarum WT (MDK407, Δura3) and ΔhpyA (KAD100) | hpyA gene deletion; optimal (4.2M NaCl) vs reduced (3.4M NaCl) salt | maximum instantaneous growth rate (μmax) | R package grofit, logistic regression |
| phase contrast microscopy / cell circularity | Hbt. salinarum WT, ΔhpyA, and complemented ΔhpyA/pKAD17 (KAD128) | hpyA deletion and complementation; optimal vs reduced salt | cell circularity | Zeiss Axio Scope A1 microscope, MicrobeJ/ImageJ |
| ChIP-seq | Hbt. salinarum strains AKS134 (empty vector control) and KAD128 (HpyA-HA) | HA-tagged HpyA overexpression vs empty vector; exponential vs stationary phase | genome-wide HpyA-DNA binding sites/peaks | Illumina HiSeq4000; MACS2, bedtools, IRanges |
| RNA-seq | Hbt. salinarum WT (MDK407) and ΔhpyA (KAD100) | hpyA deletion; optimal (4.2M NaCl) vs low salt (3.4M NaCl) | differential gene expression | Illumina Novaseq6000; DESeq2, HTSeq |
- ▼ WT growth rate in reduced salt drops to 89% of optimal-salt rate, while ΔhpyA drops to only 67% 89% (WT) vs 67% (ΔhpyA)
- ▼ Growth impairment of ΔhpyA under reduced salt is statistically significant relative to WT P < 0.008
- ▲ ΔhpyA cells are significantly rounder than WT under optimal salt (non-overlapping 95% CIs)
- ▲ ΔhpyA morphology under reduced salt is the most circular of all strain-condition combinations
- – ChIP-seq identifies reproducible, salt-dependent HpyA binding at discrete genomic sites, reproducible across ≥2 biological replicates ~60 sites
- other 89% of optimal growth rate (WT μmax in reduced salt relative to optimal salt)
- other 67% of optimal growth rate (ΔhpyA μmax in reduced salt relative to optimal salt)
- pvalue P < 0.008 (unpaired two-sample t-test comparing ΔhpyA vs WT growth impairment in reduced salt)
- count ~60 discrete binding sites (reproducible HpyA ChIP-seq peaks across biological replicates)
- pvalue BH-adjusted Wald test P < 0.05 (DESeq2 criterion for significant differential expression across RNA-seq contrasts)
- other RIN > 9.0 (RNA quality threshold for RNA-seq samples)
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 employs a multi-assay quantitative design to characterize HpyA function across optimal and reduced salt conditions in Halobacterium salinarum. Growth rate differences were assessed by unpaired t-test on μmax values derived from logistic regression of nine biological replicates per strain. Cell circularity was compared across four strain-by-condition groups using non-parametric bootstrap confidence intervals of the median. ChIP-seq peaks were called with MACS2 (FDR q ≤ 0.05) and retained only if reproducible in at least two biological replicates; binding-location enrichments were tested with hypergeometric or Fisher's exact tests. RNA-seq differential expression was conducted with DESeq2 Wald tests across three pairwise contrasts, with Benjamini-Hochberg FDR correction applied throughout.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Unpaired two-sample t-test | Comparison of maximum instantaneous growth rate (μmax) between WT and ΔhpyA in reduced salt (Figure 1B) | 9 biological replicates per strain | not stated |
| Non-parametric bootstrap resampling of median (1000 resamples, bias-corrected adjusted percentile 95% CI; inference by CI non-overlap) | Comparison of cell circularity distributions across four strain × salt-condition combinations (Figure 2) | — | na |
| MACS2 peak calling (internal FDR, q-value ≤ 0.05 cutoff, nomodel mode) | ChIP-seq peak identification across four HpyA-HA biological replicates versus one empty-vector control replicate | 4 biological replicates (HpyA-HA); 1 biological replicate (empty vector control) | not stated |
| Hypergeometric test | Enrichment of ChIP-seq peak center locations in genic versus intergenic regions; enrichment of overlap between HpyA peaks and TrmB binding locations | — | not stated |
| Fisher's exact test (BEDtools 'fisher' function) | Enrichment of overlap between HpyA ChIP-seq peaks and RosR binding locations | — | not stated |
| DESeq2 Wald test with Benjamini-Hochberg FDR adjustment (adjusted P < 0.05) | RNA-seq differential expression: three pairwise contrasts (ΔhpyA vs WT in optimal salt; ΔhpyA vs WT in reduced salt; reduced vs optimal salt in WT background) | 6 biological replicates per strain-condition combination before Strong-PCA outlier removal; post-removal n not stated | not stated |
| Hypergeometric test with Benjamini-Hochberg FDR adjustment | Functional enrichment (arCOG categories) of differentially expressed genes from RNA-seq | — | not stated |
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Cell circularity across four strain-by-condition groups was compared by visual inspection of bootstrap 95% CI overlap around medians, without a formal omnibus or post-hoc test↳ Could also: A Kruskal-Wallis test followed by Dunn's post-hoc test (or pairwise Wilcoxon tests) with Bonferroni or BH correction across all pairwise comparisons could also have been used — A formal omnibus test with post-hoc correction yields explicit p-values per comparison and controls the family-wise or false-discovery error rate across all six pairwise cells; it complements CI-overlap visualization and makes the inference criterion transparent to readers
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Growth rate (μmax) differences were assessed with an unpaired two-sample t-test on nine replicates per strain, without a stated normality check↳ Could also: A Mann-Whitney U (Wilcoxon rank-sum) test could also have been applied to the same μmax values — With n = 9 per group, a non-parametric alternative requires no distributional assumption about μmax; it is equally straightforward and guards against sensitivity to skew that logistic-regression-derived rates can sometimes exhibit
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A separate t-test was reported for the reduced-salt comparison while the optimal-salt comparison was described descriptively as 'indistinguishable', treating the two salt conditions independently↳ Could also: A two-way ANOVA (factors: genotype × salt condition) followed by Tukey HSD post-hoc tests could also have been used — A two-way factorial design directly tests the genotype × condition interaction — the quantity of central biological interest — within a single model and adjusts for the family of four group means simultaneously, avoiding the need for separate tests per condition
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RNA-seq differential expression was modeled with DESeq2's negative binomial framework↳ Could also: edgeR (quasi-likelihood F-test or exact test) or limma-voom could also have been applied to the same count matrix — Both are widely validated alternatives for small-n RNA-seq experiments; comparing the overlap of significant genes across two tools is sometimes used to identify a high-confidence consensus set and to assess method sensitivity
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The growth-rate t-test result is reported as P < 0.008 and no standardized effect size is provided for any phenotypic comparison↳ Could also: Cohen's d (or Hedges' g for small n) with a 95% CI could also have been reported alongside the p-value for the growth-rate comparison — Standardized effect sizes convey the magnitude of the difference independently of sample size, aiding interpretation of biological relevance and enabling future meta-analyses or power calculations
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Outlier RNA-seq samples were identified and excluded using Strong PCA prior to DESeq2 analysis; the number and identity of removed samples and the exclusion threshold are not stated in the methods↳ Could also: DESeq2's built-in Cook's distance flagging, or hierarchical clustering of sample-to-sample Euclidean or Poisson distances, could also have served as a primary or complementary quality-control approach — DESeq2's internal Cook's distance approach flags per-gene outlier observations rather than removing entire samples, preserving more data; explicitly reporting how many samples were removed and by what criterion is standard practice that aids reproducibility
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-34883507 (Sakrikar & Schmid 2021, NAR, gkab1175)
Paper: An archaeal histone-like protein regulates gene expression in response to salt stress.
Organism: Halobacterium salinarum NRC-1 (RefSeq GCF_000006805.1 / ASM680v1).
Repo: https://github.com/amyschmid/HpyA_codes (default branch main, HEAD 7babe18750a9a555d556f625977fe527711aeec0, 2021-11-19) — AUTHORS' OWN code.
Data: GEO GSE182514 (RNA-seq + ChIP-seq raw reads).
Key structural fact
The repo ships its processed/intermediate input files alongside commented .Rmd analysis scripts.
Each analysis directory (RNA-seq/, ChIP-seq/, growth/) contains the inputs its Rmd reads. This means the
downstream statistical results are reproducible from the shipped data with R only — no raw-read
realignment required for those endpoints.
In scope (pipeline-derived, attempted)
A. RNA-seq differential expression (HIGH tractability) — PRIMARY TARGET
- Pipeline (downstream): DESeq2 1.30.1 (R 4.1.1) on shipped count matrix
combineddata_21samples.csv(2621 genes x 21 samples) +combinedmeta_21samples.csv. - Design:
~Batch+Salt+Genotype+Salt:Genotype; DEG =padj < 0.05(BH Wald), no log2FC cut. - Script:
RNA-seq/2021Combined_hpyAsalt_newcounts_all-AKS.Rmd. - Reproduces claims: RNA_DEG_total(168), lowsalt(143), optimal(46), unique_low(121), all_conditions(21).
- Compute: trivial (seconds). Runs on «our HPC» per hard rules; data/clone on «infra».
B. ChIP-seq peak annotation (MEDIUM tractability)
- Downstream annotation from shipped FINAL manually-curated peak BEDs (
Finalmanual_*.bed) + genome gff viaChIP-seq/2021-05-21-peak_annotate_IRanges.Rmd(IRanges/GenomicRanges). - Reproduces: CHIP_peaks_total(59), CHIP_genes_near(86, within 500bp).
- NOTE: upstream peak CALLING (MACS2 v2.1.1 nomodel qval=0.05, >=2 reps + manual curation) needs raw GEO/SRA reads — heavier, depends on GSE182514 download. Attempt only if shipped beds insufficient.
C. Growth-rate analysis (MEDIUM tractability)
- grofit 1.1-1 (shipped as
growth/grofit_1.1.1-1.tar.gz, archived/removed from CRAN) on shippedgrowth/allgrowthcurves.xlsx/combined_grofit_*.xlsxviagrowth/2021-09-15-hpyA-analysis-figs-phenotypes-rev.Rmd. - Reproduces: GROWTH_WT_pct(89%), GROWTH_KO_pct(67%), GROWTH_ttest_p(P<0.008).
Out of scope (not attempted / lower priority)
- Raw-read upstream steps (TrimGalore!, Bowtie2 alignment, HTSeq counting, MACS2/mosaics peak calling) from GSE182514 — only attempted if a downstream endpoint cannot be reached from shipped data.
- Wet-lab assays, microscopy/circularity imaging, qPCR, protein work — manual/experimental, not pipeline.
- Figure cosmetics (heatmaps, volcano styling) — not quantitative claims.
Discrepancy to flag
README/dependencies list mosaics (R) for ChIP, while Methods text says MACS2 v2.1.1; both appear in the dependency files. Will note which the shipped beds actually came from.
Execution plan
- («our HPC» front1) clone repo on «infra» work dir; build conda R 4.1.x env (DESeq2, IRanges, grofit-from-tarball).
- Run A (DESeq2) first — submit small SLURM job (or front1 R, compute is seconds). Pull DEG counts.
- Run B + C. Compare to claims.tsv; fill agreement.json + AUDIT.md.
- Profile GSE182514 in dataset_profile.json (N reported vs observed, completeness, QC).
Blocker as of first pass: «our HPC» «host» ssh timing out (tunnel down). Not touching VPN; retrying.
All prep (claims, scope, driver scripts) done offline so the run is one submit away when the tunnel returns.
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.
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.