Genomic analysis of bacteria in the Acute Oak Decline pathobiome.
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.
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- Reproduced
- 2026-06-19
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-16no human curator yet
- Last updated
- 2026-07-29
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: opusCan comparative whole-genome analysis of bacteria isolated from Acute Oak Decline (AOD) lesions reveal genome-encoded virulence mechanisms that distinguish primary phytopathogens from secondary/accessory contributors within the AOD lesion pathobiome?
- ★ All studied members of the AOD lesion microbiota possess virulence genes associated with phytopathogens finding
- ★ Brenneria goodwinii has the genome most characteristic of a necrogenic phytopathogen, corroborating its role as the key causal agent of AOD lesions finding
- ★ B. goodwinii and Lonsdalea britannica are potential primary pathogens in a predisposed tree, whereas Gibbsiella quercinecans and others may act as secondary/opportunistic or accessory contributors mechanism
- ★ G. quercinecans may contribute to tissue necrosis through release of necrotizing enzymes and help more dangerous pathogens realize their pathogenic potential mechanism
- ★ Orthologous gene inference can identify shared virulence genes that retain the same function across pathobiome members and reference phytopathogens method
- ★ AOD is caused by an interactive bacterial pathobiome, supporting the concept of tree diseases caused by polymicrobial complexes finding
- Whole genome sequencing combined with ecological data provides insights into pathogenic potential of bacterial species method
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| Whole genome sequencing (WGS) | Gibbsiella quercinecans strains FRB97, FRB124, N78; Brenneria goodwinii strains FRB141, FRB171 (bacterial isolates from AOD-affected oak) | none | genome assembly, contigs, gene count, GC content | Illumina MiSeq Personal Sequencer; Nextera XT library prep |
| Whole genome sequencing (WGS) | Lonsdalea britannica 477 and Rahnella variigena CIP105588T | none | complete genome assembly and motif summary | Pacific Biosciences RSII (SMRT, P6/C4 chemistry) |
| Whole genome sequencing (WGS) | Brenneria alni NCPPB 3934 and Brenneria salicis DSM 30166 (reference phytopathogens) | none | genome assembly metrics | Illumina MiSeq; Nextera XT |
| De novo genome assembly | MiSeq reads of G. quercinecans and B. goodwinii strains | none | contig number and sequencing coverage | SPAdes v3.0 (k-mers 21–231) |
| Comparative genomics / orthologous gene inference | AOD pathobiome genomes vs canonical phytopathogens and non-pathogenic symbionts | none | degree of orthology and degree of virulence orthology | — |
| Functional annotation of virulence genes | AOD lesion microbiota genomes | none | presence of phytopathogen-associated virulence genes (PCWDEs, T3SS, effectors) | — |
| Post-sequencing quality control / read trimming | MiSeq FastQ reads | none | adapter-trimmed, quality-trimmed reads | Cutadapt v1.2.1; Sickle v1.2 (Q20) |
- – B. goodwinii FRB141 (Pectobacteriaceae) genome had degree of virulence orthology of 20, matching reference necrogenic phytopathogens virulence orthology = 20
- ▼ G. quercinecans strains showed lower degree of virulence orthology (16) than B. goodwinii and L. britannica (20) 16 vs 20
- – L. britannica 477 genome had degree of virulence orthology of 20, consistent with primary pathogen potential virulence orthology = 20
- – G. quercinecans FRB124 assembled into 90 contigs at 92x coverage 90 contigs, 92x
- – G. quercinecans N78 assembled into 129 contigs at 75x coverage 129 contigs, 75x
- – B. goodwinii FRB171 assembled into 128 contigs at 52x coverage 128 contigs, 52x
- – All AOD pathobiome members possessed genes associated with phytopathogens
- other GC content 51 mol% (B. goodwinii FRB141) (chromosome G+C content, 5 281 917 bp genome)
- count 4625 genes (85.8% gene density) (B. goodwinii FRB141 chromosomal gene count)
- count 5125 genes (86.9% gene density) (G. quercinecans FRB97, 5 548 506 bp, 56 mol% GC)
- count 3801 genes (87.2%) (L. britannica 477, 4 015 589 bp, 55 mol% GC)
- other degree of virulence orthology = 20 (B. goodwinii, L. britannica, R. variigena, several reference phytopathogens)
- other degree of virulence orthology = 16 (G. quercinecans strains FRB97 and FRB124)
- count 5202 genes (86.4%) (G. quercinecans N78, 5 693 731 bp, 56 mol% GC)
- other sequencing coverage 52x–92x (MiSeq de novo assemblies of AOD strains)
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 uses a comparative genomics design rather than a hypothesis-testing statistical framework: whole genomes of AOD lesion-associated bacteria were sequenced (Illumina MiSeq and PacBio RSII), assembled de novo, annotated, and compared against reference phytopathogen and non-pathogen genomes. Pathogenic potential was assessed descriptively through orthologous gene inference and sequence-similarity searches for shared virulence-gene homologues, summarised as counts such as 'degree of orthology' and 'degree of virulence orthology' per genome. Results are reported as genome metrics and gene/ortholog counts in tables; no inferential statistical tests, p-values, or dispersion measures are described in the available text.
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Pathogenic potential and shared virulence content were assessed by counting orthologous and virulence-orthologous genes per genome (descriptive comparison across genomes).↳ Could also: A statistical enrichment test (e.g., Fisher's exact test or a hypergeometric/over-representation test) comparing virulence-gene categories between lesion isolates and reference groups could also be reported. — Such tests would attach a quantified measure of how unexpected an observed count is relative to a background, complementing the descriptive counts.
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Genomes were grouped and discussed by family and pathogen/symbiont status using ortholog counts.↳ Could also: A clustering or ordination approach (e.g., hierarchical clustering, PCA, or a presence/absence gene-content distance with a phylogenomic tree) could also be used to summarise relationships among genomes. — This would provide a multivariate, reproducible visualisation of how genomes group by gene content and could indicate the relative similarity among isolates and references.
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Comparisons are presented as point counts (e.g., degree of orthology) for single representative genomes per organism.↳ Could also: Where multiple strains per species are available, summarising within-species variation with a range, IQR, or confidence interval could also be reported. — Conveying spread alongside point estimates helps readers gauge how representative a single value is, which is often informative for small numbers of strains.
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Ortholog inference relied on sequence-similarity searches with thresholds described via the linked command set.↳ Could also: Reporting the statistical parameters of the homology search (e.g., E-value cutoffs, percent identity/coverage thresholds) explicitly in the text, and/or a sensitivity analysis across thresholds, could also accompany the counts. — Stating thresholds and their sensitivity makes the basis of each ortholog call transparent and shows how robust the counts are to parameter choice.
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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All AOD pathobiome members (G. quercinecans, B. goodwinii, L. britannica) possess genes associated with phytopathogens, supporting their role in disease.WGS aod pathobiome bacteria 2019×1papers★ This paper is the founder (earliest)
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B. goodwinii FRB141 has a degree of virulence orthology of 20, matching reference necrogenic phytopathogens.WGS brenneria goodwinii 2019×1papers★ This paper is the founder (earliest)
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G. quercinecans strains have a lower degree of virulence orthology (16) compared to B. goodwinii and L. britannica (20).WGS gibbsiella quercinecans down 2019×1papers★ This paper is the founder (earliest)
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L. britannica 477 has a degree of virulence orthology of 20, consistent with primary pathogen potential.WGS lonsdalea britannica 2019×1papers★ This paper is the founder (earliest)
Citation network
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What was reproduced
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Assessments & scoring basis
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Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
All 26 deterministic-core claims reproduced 1:1 from the authors' shipped intermediates (graphml + Yes_no_data.csv) using a faithful port of their own R notebook — Table 1 degrees, component sizes (27/26), the six WG→virulence degree shifts, and the chi-squared (reported P=8.47e-11 vs reproduced 8.468e-11, only rounding). Data identity is strong because the exact analysis intermediates are deposited. The sole gap is the 9 upstream assembly metrics, which stayed PENDING (re-assembly not completed) — that is unverified coverage on our side, not a discrepancy or an authors' defect. Central conclusion holds fully; overall a clean, well-supported reproduction.
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