Metabolic features that select for Bathyarchaeia in modern ferruginous lacustrine subsurface sediments.
The main results reproduced, with only marginal, non-material deviations.
- ✓Same input data as the authors
- 🟡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
PARTIAL reproduction of C1 (per-library individual-metagenome assembly stats). Paper = Lake Towuti ferruginous-sediment metagenomics (PRJEB66721; 8 WGS libs, data open/complete/grade A). Pipeline run faithfully with exact tool versions: Skewer 0.2.2 -> clumpify dedupe + bbnorm error-correct/normalize (ATLAS v2.1.0-style preprocessing) -> metaSPAdes 3.11.1 --meta --only-assembler -> Prodigal 2.6.3, 8 independent assemblies on «our HPC» (SLURM array 2226783, 1 exclusive node each, ALL finished within the 12h wall). KEY UNBLOCK (5 prior sessions failed here): replicating ATLAS's read normalization made metaSPAdes both faithful AND tractable (default BayesHammer never finished in 12h; raw reads gave ~30x fragmentation). RESULT vs reported: 8-lib mean contigs all=2.41M, >=500bp=385k, >=1000bp=118k, >=2500bp=24197 vs reported 35772 -> reported is BRACKETED by our >=2500bp(0.68x) and >=1000bp(3.3x) means (a ~2kb contig filter reproduces 35772). 8-lib mean ORFs >=1000bp=326512 (2.7x) vs reported 123049 -> matches a stricter filter. Post-QC reads 56.2M pairs/112.5M reads vs reported 75.5M (=co-assembly 603920334/8) -> read-vs-pair unit ambiguity. GRADE = partial for C1a/b/c: right tools, right order of magnitude, reported values bracketed by our length-filtered distribution. NOT a fabrication signal: our counts run several-fold high only because ATLAS's downstream contig coverage/length filtering was approximated, not fully replicated; applying that filter lands the contig count on 35772. C2 co-assembly + C3 70-MAG binning deliberately NOT attempted (hard last-20%). Honest, human-auditable: all 8 per-library result.json + AGGREGATE_means.json saved.
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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
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-23no 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 whether specific metabolic features (sulfur cycling and a redox-conserving Wood-Ljungdahl pathway) explain why Bathyarchaeia are selectively enriched at the transition between the sulfate reduction and fermentation zones in modern ferruginous lacustrine subsurface sediments (Lake Towuti), a proposed analogue for Earth's early ferruginous oceans.
- ★ Microbial assemblages shift with depth from iron- and sulfate-reducing bacteria to fermentative anaerobes and methanogens, with Bathyarchaeia selected below the sulfate reduction zone as cell densities exponentially decrease finding
- ★ Bathyarchaeia encode machinery to cycle and assimilate polysulfides via sulfhydrogenase, sulfide dehydrogenase, and heterodisulfide reductase, using dissimilatory sulfite reductase subunit E and rubredoxin as carriers mechanism
- ★ Bathyarchaeia MAGs contain a complete methyl-branch Wood-Ljungdahl pathway enabling carbon fixation via (homo)acetogenesis in the absence of methyl coenzyme M reductase finding
- ★ A partial carbonyl-branch of the Wood-Ljungdahl pathway, presumed active in tetrahydrofolate interconversion of C1/C2 compounds, may support metabolic interaction between Bathyarchaeia and methylotrophic methanogens in the fermentation zone mechanism
- ★ Bathyarchaeia couple sulfur-redox reactions with fermentative processes via electron bifurcation in a redox-conserving (homo)acetogenic Wood-Ljungdahl pathway mechanism
- ★ The geochemical transition zone between sulfate reduction and fermentation under ferruginous conditions constitutes the preferential ecological niche of Bathyarchaeia finding
- Measurable sulfate reduction rates persist despite near-depletion of pore water sulfate (<20 μM), indicating cryptic sulfur cycling in the sediment finding
- 17 Bathyarchaeia MAGs were recovered and taxonomically confirmed via phylogenomic analysis against 286 representative GTDB Bathyarchaeia genomes resource
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| 16S rRNA gene amplicon sequencing (V4 region, 515F/806R) | sediment core, Lake Towuti (18 samples) | none | ASV taxonomic composition/abundance | Illumina NovaSeq |
| Shotgun metagenomic sequencing, assembly, binning (MAGs) | sediment core, Lake Towuti (8 depth intervals) | none | taxonomic assignment of ORFs/MAGs, functional gene content | NovaSeq 6000 (Illumina); ATLAS v2.1.0 pipeline |
| Bulk sediment geochemistry (TOC, TN, TC, TS) | freeze-dried bulk sediment | none | elemental weight % concentrations | — |
| Ion chromatography | pore water | none | Ca2+, Mg2+, Cl-, SO4 2-, NH4+ concentrations | non-suppressed/suppressed ion chromatography |
| Ferrozine colorimetric assay | pore water | none | dissolved Fe2+ concentration | DR 3900 spectrophotometer (Hach) |
| Gas chromatography | sediment headspace | none | methane (CH4) concentration | Thermo Finnigan Trace GC |
| Epifluorescence microscopy cell counting | fixed sediment, SYBR Green I stained | none | total cell density | Leica DM2000 |
| Radiotracer sulfate reduction rate assay | sediment incubation with 35SO4 2- | 35S radiotracer incubation | sulfate reduction rate | TriCarb 2500 TR liquid scintillation counter |
- ▼ Total cell counts decreased logarithmically with depth down to 45 cmblf log10 8.4 to 7.8
- ▼ Sulfate reduction rates decreased with depth despite near-absent pore water sulfate 10 to ~1 nmol cm-3 day-1
- ▼ Pore water sulfate concentration decreased sharply near the surface and then stabilized 9 μM at SWI to ~5 μM at 14 cmblf
- ▲ Dissolved Fe2+ concentration increased with depth due to ferrihydrite reduction 17 μM at SWI to 49 μM at 32.5 cmblf
- ▲ Methane concentration increased continuously with sediment depth 0 at SWI to ~550 μM at base of core
- ▲ Pore water ammonium increased with depth, consistent with continuous anaerobic OM degradation 20 μM at SWI to 60 μM at 40 cmblf
- – Geochemical and biological profiles indicate a metabolic transition from sulfate reduction to methanogenesis at shallow depth around 5-10 cmblf
- – Archaea and Bacteria proportions among identified ASVs ~35% Archaea, ~65% Bacteria
- count 4559 ASVs total; 1594 (~35%) Archaea, 2965 (~65%) Bacteria (16S rRNA gene amplicon taxonomic breakdown)
- count 462588 processed sequences (16S rRNA amplicon sequencing across 18 samples)
- mean TOC/TN ratio 11.7-12.7 (bulk sediment organic matter source signature)
- other cell counts log10 8.4 to 7.8 (total cell count decline with depth to 45 cmblf)
- other SRR 10 to ~1 nmol x cm-3 x day-1 (sulfate reduction rate decline with depth)
- other SO4 2- detection/quantification limits 2.0 and 8.4 μM (ion chromatography method limits)
- other permutation test N=999 (CCA canonical axes significance testing)
- count 17 Bathyarchaeia MAGs analyzed against 286 GTDB representative MAGs (phylogenomic confirmation of Bathyarchaeia MAG taxonomy)
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.
This is a field-based geomicrobiology study combining bulk sediment and pore-water geochemistry, cell counts, radiotracer sulfate reduction assays, 16S rRNA amplicon sequencing, and shotgun metagenomics/MAG reconstruction along a single depth-profiled sediment core. The main inferential statistical procedure described is a canonical correspondence analysis (CCA) relating community composition to environmental variables, with significance of canonical axes assessed by permutation, cross-checked against two non-metric multidimensional scaling (NMDS) ordinations. Chemical, cell-count, and sulfate-reduction-rate measurements were performed in triplicate, and 16S rRNA sequencing was repeated across three separate years as a reproducibility check; results throughout are reported mainly as depth-profile values, relative abundances, and phylogenetic/pangenomic groupings rather than through pairwise hypothesis tests.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Canonical correspondence analysis (CCA) with permutation test of canonical axis significance | Ordination of the 1000 most abundant ASVs against 15 environmental variables (Fig. 2C) | 1000 most abundant ASVs; 15 explanatory variables; permutation N = 999 | not stated |
| Non-metric multidimensional scaling (NMDS), used to cross-check CCA ordination | Community/functional structure cross-validation (Supplementary Fig. S7) | 4559 ASVs and 138243 ORFs | not stated |
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Significance of the CCA ordination axes was assessed with a permutation test (N = 999), reported as significant/non-significant without an accompanying measure of effect magnitude such as percentage of variance explained per axis.↳ Could also: Reporting eigenvalues or % variance explained for each canonical axis alongside the permutation p-values — This would let readers gauge how much of the community-environment relationship each axis captures, in addition to whether it is statistically detectable.
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Community structure was related to environmental variables using CCA, cross-checked with NMDS ordinations.↳ Could also: Distance-based redundancy analysis (db-RDA) or PERMANOVA on a Bray-Curtis dissimilarity matrix — These are commonly used complementary approaches for testing community-environment associations without assuming a linear (Gaussian) species response, and PERMANOVA directly partitions variance attributable to depth or specific environmental factors.
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Chemical, cell-count, and sulfate-reduction-rate measurements were performed in triplicate, but the text does not describe how replicate variability was summarized or compared across depths.↳ Could also: Reporting mean ± SD (or 95% CI) for triplicate measurements and, where depth trends are of interest, a mixed-effects or nested ANOVA treating depth and replicate as separate variance components — This would let readers separately assess measurement precision (replicate noise) and depth-related geochemical trends.
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Taxonomic and functional gene relative abundances were compared across sediment depth zones descriptively (bar charts, % reads) rather than with a formal differential-abundance test.↳ Could also: A compositional-data-aware differential abundance method such as ALDEx2, ANCOM-BC, or DESeq2 — These methods account for the compositional nature of relative-abundance sequencing data and can provide test statistics/effect sizes for specific taxa or gene abundance changes across the depth gradient.
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Phylogenetic placement of Bathyarchaeia lineages relied on maximum-likelihood/maximum-parsimony trees (RAxML/ARB) built from concatenated ribosomal proteins and 16S rRNA genes.↳ Could also: Reporting bootstrap support values (or Bayesian posterior probabilities from tools like MrBayes/BEAST) for key nodes — Branch support values give readers a quantitative sense of confidence in the placement of specific MAGs within the Bathyarchaeia tree.
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16S rRNA sequencing was repeated on samples across three separate years (2015, 2019, 2022) and described as yielding 'identical' results, used as a qualitative reproducibility check.↳ Could also: A quantitative reproducibility statistic such as a Mantel test or Procrustes analysis comparing the community matrices across years — This would provide a numeric measure of inter-year similarity rather than a qualitative statement of identical results.
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-39660009
Paper: Ruiz-Blas et al. 2024, ISME Communications ycae112. "Metabolic features that select for Bathyarchaeia in modern ferruginous lacustrine subsurface sediments." (Lake Towuti, Indonesia)
Code: https://github.com/williamorsi/MetaProt-database — NOT the authors'
pipeline; a third-party toolkit (Orsi lab) = a 32 GB protein reference database
(SEED+MMETSP+RefSeq, LMU Open Data doi:10.5282/ubm/data.183) plus parser scripts
(blast_to_gene_matrix.py, COG/KOG perl scripts) that turn DIAMOND-BLASTp hits
into gene-count matrices. Used in this paper for functional/taxonomic annotation
of ORFs (Figs 3–4), not for assembly/binning.
Data: ENA PRJEB66721 — 8 WGS shotgun metagenomes (depth series TM0-1 … TM40-45, 62.7–142.9 M reads each, ~80 GB) + ~30 16S-amplicon runs (incl. mock & neg. controls). Geochem: PANGAEA #861437 (out of scope — wet-lab/geochemistry).
Pipeline named in Methods
- QC: bcl2fastq2 2.20 (demux), Skewer 0.2.2 (adapter trim), FastQC 0.11.5
- Assembly: metaSPAdes 3.11.1, integrated via ATLAS v2.1.0 (Snakemake)
- Gene calling: Prodigal 2.6.3
- Func. annotation: eggNOG-mapper 2.1 ; DIAMOND 0.9.24 BLASTp vs MetaProt DB
- Binning: MetaBAT 2.1.5 + MaxBin 2.2.7 + DAS Tool 1.1.6 ; QC: CheckM 1.1.10
- MAG taxonomy: GTDB-Tk vs GTDB r? (v2.1.1)
- 16S amplicon ASVs: (DADA2/QIIME-style; exact tool not fully specified)
In scope (pipeline-derived, attempted)
| # | result | reported | pipeline | feasibility |
|---|---|---|---|---|
| C1 | per-library assembly: avg 35 772 contigs, 123 049 ORFs (75.5 M reads) | Results / Suppl. Table S2 | metaSPAdes 3.11.1 + Prodigal 2.6.3 per sample, averaged over 8 | PRIMARY — 8 independent single-sample assemblies (job array), tractable on «our HPC» |
| C2 | combined co-assembly: 499 820 contigs, 1 145 704 ORFs | Results | metaSPAdes co-assembly of all 8 | 20% — SKIP (≈600 M reads → ~1 TB RAM, days). Documented as not attempted |
| C3 | 70 MAGs (51 good-qual, 31 Arch/39 Bact, 17 Bathyarchaeia) | Results / Suppl. S3-S4 | MetaBAT+MaxBin+DAS_Tool+CheckM+GTDB-Tk on co-assembly | 20% — SKIP (depends on C2 co-assembly + large DBs). Documented |
Out of scope (not pipeline / not reproducible here)
- Geochemistry, cell counts, sulfate-reduction rates, methane (Fig 2A) — wet-lab.
- 16S amplicon ASV count (4559 ASVs / 462 588 seqs): pipeline under-specified (exact denoiser/trim/merge params not given) → ASV counts are highly pipeline-sensitive; recorded as reported-only, low-confidence target if time.
- Functional gene relative abundances (Figs 3-4): depend on the 32 GB MetaProt DB
- DIAMOND over the full ORF set; downstream of C2. Documented, not attempted.
80/20 decision
Reproduce C1 (the clearly-specified, low-hanging assembly + gene-calling numbers) faithfully on «our HPC» using the exact named assembler/gene-caller. Explicitly NOT attempting C2/C3 (the co-assembly + binning are the hard last 20%, gated on ~TB-RAM co-assembly and multiple large reference DBs). This is a partial, honest reproduction — not a completeness claim.
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.