Genomic profiling of Streptococcus agalactiae (Group B Streptococcus) isolates from pregnant women in northeastern Mexico:
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.
▸Reproduction agent’s raw note
GBS genomic profiling (Vazquez-Guillen 2025, PeerJ 13:e19454) reproduces faithfully. PRIMARY code-pinned result MLST (tseemann/mlst on the paper's own 51 supplement genomes = GenBank PRJNA892112+PRJNA551699): COMPLETE 1:1 EXACT match — 13 STs, ST8 12 (23.5%), ST88 8 (15.7%), all 6 CCs (CC12 12, CC452 10, CC23 9, CC19 5, CC1 4, CC17 4) + 7 unassigned; the fresh re-run («job») reproduced all 51 per-isolate ST calls IDENTICALLY to the prior run. QUAST Table S1 within-tol (fresh; median rel-diff 0 on all 6 metrics, 37-50/51 exact). AMR via RGI/CARD reproduces the Table 5 gene set, 6/11 genes EXACT (aac(6')-aph(2''), tet(45), ermB, sat4, lsaE, aph(3')-IIIa), rest within-tol or differing only by CARD-database-version gene labels (paper 2013 CARD: mreA reclassified, tet(W/N/W)->tet(L), qacJ->qacG) — graded from the prior real «our HPC» RGI run, cross-checked by fresh abricate-CARD. NOT 1:1: BRIG virulence percentages (custom refs/thresholds unshipped). Out of scope: latex-agglutination serotype + AST phenotypes (wet-lab). Data note: brief's 'sra:PRJNA892112' has NO reads; the 51 genomes are GenBank assemblies == the paper's supplement FASTAs. No fabrication indicators — every reproduced value derives from the deposited genomes.
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 84assessed: 2026-06-16 ⛓ 04d8c443b7c9
✎ 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
- 2026-06-22
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-18👤 1 human curator(s) · Level L2 2026-06-16
- 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 study aimed to determine the prevalence of Streptococcus agalactiae (GBS) colonization in pregnant women attending a referral hospital in Northeastern Mexico and to characterize the genomic diversity of the isolates (sequence type, clonal complex, capsular polysaccharide genotype, virulence factors, and antibiotic resistance genes).
- ★ GBS colonization was detected in 51 of 1,924 (2.7%) pregnant women screened finding
- ★ The most common sequence types among colonizing isolates were ST8 (23.5%) and ST88 (15.7%) finding
- ★ Capsular polysaccharide (Cps) genotyping by whole-genome sequencing showed high concordance with serological serotyping finding
- ★ The tetracycline resistance gene tetM was present in 60.1% of isolates and the macrolide/clindamycin resistance gene mreA was present in 100% of isolates finding
- ★ Key virulence factor genes cylE, bca, and scpB were present in over 90% of the isolates finding
- ★ Whole-genome sequencing and comparative genome analysis can determine ST, CC, Cps genotype, virulence factors, and antibiotic resistance genes of GBS isolates method
- Molecular/genomic techniques are important complements to serological methods for GBS epidemiological surveillance and infection control finding
- Isolate genomic data were deposited under NCBI BioProjects PRJNA892112 and PRJNA551699 resource
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| Microbiological/biochemical identification (Gram stain, catalase test, hippurate hydrolysis, CAMP factor test) | Vaginal-rectal swab isolates from pregnant women | none | Confirmation of S. agalactiae identity | Strep B Carrot Broth (Hardy Diagnostics); StrepPRO Streptococcal Grouping Kit |
| Latex agglutination serotyping | 51 S. agalactiae isolates | none | Capsular serotype (Ia, Ib, II-IX) | ImmuLex Strep-B Latex (Statens Serum Institute) |
| Whole-genome sequencing | 51 S. agalactiae isolates cultured in Todd-Hewitt broth | none | Draft genome assembly for downstream genomic analysis | Illumina MiSeq with Nextera DNA Flex Library Prep Kit, MiSeq Reagent Kit V2 |
| Multi-locus sequence typing (MLST) | S. agalactiae draft genomes (seven housekeeping genes: adhP, pheS, atr, glnA, sdhA, glcK, tkt) | none | Sequence type (ST) and clonal complex (CC) | MLST software (github.com/tseemann/mlst); PubMLST database |
| BLAST homology comparative genomics | S. agalactiae draft genomes | none | Presence/absence of Cps loci, virulence factor genes, and PI-1/PI-2a/PI-2b pilus loci | BRIG version 0.95 |
| Antimicrobial resistance gene screening | S. agalactiae draft genomes | none | Presence of resistance genes (perfect vs strict identity matches) | Comprehensive Antibiotic Resistance Database (CARD) |
- – GBS colonization prevalence among pregnant women 51/1,924 (2.7%)
- – 13 distinct STs grouped into six clonal complexes: CC12 (23.5%), CC452 (19.6%), CC23 (17.6%), CC19 (9.8%), CC1 (7.8%), CC17 (7.8%); 13.7% unassigned
- – Cps loci detected in 50/51 (98%) isolates; genotyping and serotyping concordant in 84.8% of isolates 84.8% concordance
- – tetM detected in 31/51 isolates 60.1%
- – mreA detected in all isolates 100% (51/51)
- – cylE and cfb present in all isolates; scpB, sodA, cspA present in all isolates; bca present in 37/51 isolates cylE 100%, scpB 100%, bca 72.5%
- – Most frequent serotypes by latex agglutination were II (19.6%), III (17.6%), IV (17.6%), and Ia (15.7%)
- count 51/1,924 (2.7%) (GBS colonization prevalence in pregnant women)
- other ST8 23.5%; ST88 15.7% (most common sequence types)
- other CC12 23.5%, CC452 19.6%, CC23 17.6%, CC19 9.8%, CC1 7.8%, CC17 7.8%, unassigned 13.7% (clonal complex distribution)
- fold_change tetM 60.1% (tetracycline resistance gene frequency)
- fold_change mreA 100% (macrolide/clindamycin resistance gene frequency)
- fold_change cylE 100%, cfb 100%, bca 72.5%, scpB 100% (virulence gene frequencies)
- correlation 84.8% concordance between Cps genotyping and serotyping (molecular vs serological typing agreement)
- count 50/51 (98%) (isolates with detectable Cps loci)
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 cross-sectional, descriptive genomic-epidemiology study of S. agalactiae colonization in 1,924 pregnant women; no formal inferential statistical tests were reported. Results were summarized exclusively as absolute frequencies, proportions, and medians with range (age, gestational week). Bioinformatic tools (MLST, BLAST/BRIG, CARD) were used to characterize sequence types, virulence genes, and resistance genes, and concordance between serological and molecular capsular typing was reported as simple percent agreement.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Simple percent agreement (concordance calculation) | Comparison of latex-agglutination serotyping vs. Cps locus sequencing for capsular polysaccharide typing (Table 3 and Discussion) | 47 serotypeable isolates of 51 total | not stated |
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GBS colonization prevalence was reported as a single point estimate (51/1,924 = 2.7%) with no measure of uncertainty↳ Could also: Report a 95% binomial confidence interval (e.g., Clopper-Pearson exact or Wilson score method) around the prevalence estimate — A confidence interval conveys the precision of the prevalence estimate given the sample size and is standard practice in epidemiological prevalence studies
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Concordance between serological (latex agglutination) and molecular (Cps locus sequencing) capsular typing was quantified as simple percent agreement (84.8%)↳ Could also: Calculate Cohen's kappa (κ) or the prevalence-adjusted bias-adjusted kappa (PABAK) to measure inter-method agreement — Kappa accounts for agreement expected by chance alone, which simple percent agreement does not; it is the standard metric when comparing two classification methods on the same samples
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Virulence gene and resistance gene frequencies were described per isolate overall, and distributions across clonal complexes and serotypes were visualized in a heat map (Fig. 1) without formal testing↳ Could also: Apply Fisher's exact test (or chi-square with appropriate correction) to test whether specific gene carriage rates differ across CCs or serotypes — Formal association tests with multiple-comparison correction (e.g., Benjamini-Hochberg FDR) would allow distinction between observed distributional differences that may be attributable to sampling variation versus those less likely to be so
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No formal power or sample-size calculation was reported for the prevalence estimate↳ Could also: Include a prospective or post-hoc sample-size calculation specifying the expected prevalence, desired precision (CI half-width), and resulting minimum n — A sample-size justification is recommended by reporting guidelines (e.g., STROBE) for observational studies and helps readers assess whether the study was sized to detect the expected effect with adequate precision
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Genetic diversity and relatedness were described using MLST-derived CC assignments alone↳ Could also: Construct a core-genome SNP or cgMLST phylogeny (e.g., with RAxML, IQ-TREE, or Roary) and compute a diversity index (e.g., Simpson's index of diversity) — Core-genome phylogenetics provides finer resolution of clonal relationships than 7-locus MLST and quantitative diversity indices allow direct numerical comparison of diversity across studies or subgroups
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Patient-level covariates (age, gestational week, urinary tract infection history) were listed descriptively but not analyzed in relation to colonization or isolate characteristics↳ Could also: Apply logistic regression or exact logistic regression to examine associations between these covariates and GBS colonization, or between isolate-level genomic features and serotype/CC — Regression would allow estimation of odds ratios with confidence intervals, enabling identification of host factors associated with colonization while adjusting for potential confounders
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-40416609
Paper: Vazquez-Guillen et al. 2025, PeerJ 13:e19454. "Genomic profiling of Streptococcus agalactiae (Group B Streptococcus) isolates from pregnant women in northeastern Mexico." DOI 10.7717/peerj.19454 · PMCID PMC12103846.
Data: 51 GBS isolates, whole-genome sequenced (Illumina MiSeq), assembled with
A5-miseq. Deposited as 51 GenBank assemblies under BioProjects PRJNA892112
(37 isolates, strain prefix S####) + PRJNA551699 (14 isolates, EGB-Mty####).
The brief's sra:PRJNA892112 contains no SRA reads — both BioProjects are
genome-assembly submissions (LOCUS_TAG_PREFIX only; ENA read_run = 0,
NCBI SRA esearch = 0). The same 51 assemblies are also shipped verbatim as the
paper's Supplemental Information (s002.zip + s003.zip, files NN Px####.fasta,
numbered 01–51). Cross-check: supplement isolate 51 total length 2,038,346 bp ==
NCBI S1890 (GCA_043948995.1) sequence length → supplement FASTA == deposited
assembly. We type the supplement FASTAs (the authors' exact pipeline input).
Crosswalk isolate# ↔ Px#### ↔ NCBI strain ↔ GCA in data/crosswalk.tsv.
Named code: github.com/tseemann/mlst (third-party tool; P16 — applying it to the paper's own data is a fully valid reproduction).
IN SCOPE (pipeline-derived computational results)
| # | Result | Pipeline / tool (as in Methods) | Where reported |
|---|---|---|---|
| C1 | MLST sequence types: 13 distinct STs; top STs ST8 (23.5%, 12), ST88 (15.7%, 8) | mlst (tseemann/mlst), PubMLST sagalactiae scheme (adhP,pheS,atr,glnA,sdhA,glcK,tkt) | Results / text |
| C2 | Clonal-complex distribution: CC12 23.5%(12), CC452 19.6%(10), CC23 17.6%(9), CC19 9.8%(5), CC1 7.8%(4), CC17 7.8%(4), unassigned 13.7%(7) | mlst ST → PubMLST CC lookup | Results / text |
| C3 | AMR genes (RGI/CARD, Perfect+Strict), Table 5: mreA 100%(51), mprF 98%(50), tetM 60.1%(31), aac(6′)-Ie-aph(2″)-Ia 19.6%(10), tet(W/N/W) 3.9%(2), tet(45) 3.9%(2), ermB 2%(1), qacJ 2%(1), sat4 2%(1), lsaE 2%(1), aph(3′)-IIIa 2%(1) | CARD / RGI (Perfect/Strict labels are RGI terms) | Table 5 |
| C4 | Per-isolate assembly QUAST stats (51 isolates): %GC, #contigs, largest contig, total length, N50, L50 | QUAST 5.0.2 on A5-miseq assemblies | Table S1 |
| C5 (bonus) | Virulence-gene carriage (e.g. scpB/cylE/cfb/lmb 100%, fbsA 90.2%(46), bca 72.5%(37), srr-1 70.6%(36), PI-1 76.5%(39), PI-2a 68.6%(35)) | "BLAST homology with BRIG v0.95" (visualization tool); approximated with abricate --db vfdb | text/Fig |
OUT OF SCOPE (wet-lab / manual / not a pipeline)
- Capsular serotype — determined by ImmuLex Strep-B latex agglutination (wet-lab immunoassay), not in-silico. (Genomic cps loci only visualized with BRIG.) Not reproducible computationally. Sequencing↔latex concordance 84.8% is a wet-lab vs genomic comparison, not a pipeline output.
- Antibiotic susceptibility phenotypes (disk diffusion / MIC) — wet-lab.
- BRIG ring figures — manual visualization, not a quantitative pipeline output.
- DNA extraction, library prep, sequencing — wet-lab.
Approach
One «our HPC» SLURM job, conda prefix-env on «infra» (mlst, rgi, quast,
abricate). Input = 51 supplement FASTAs fetched on the compute node to «infra».
Outputs (small TSVs) pulled back to reproduction/outputs/.
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.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
The 51 input genomes are fully public (supplement FASTAs == deposited GenBank assemblies == the authors' exact pipeline input), so this is a true 1:1 setting. The primary code-pinned MLST result is an exact match (13 STs, ST8 12/23.5%, ST88 8/15.7%, all 6 CCs) and QUAST Table S1 is median-exact. Remaining deviations are on the technical/version side (2013 vs 2025 CARD relabelling and small AMR count drifts) plus one underspecified-method gap on the authors' side (BRIG virulence refs/thresholds not deposited, so those percentages are not 1:1 comparable). No fabrication indicators; overall a solid reproduction with fully explainable, non-substantive deviations.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
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.