Metagenetic and Volatilomic Approaches to Elucidate the Effect of Lactiplantibacillus plantarum Starter Cultures on Sicilian Table Olives.
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 result did not reproduce in this reproduction attempt. Where our recomputation produced values that differ from the published ones, those discrepancies are listed below. This is a single automated attempt — not peer review and not a finding of error or misconduct — and differences can also arise from data access, undocumented parameters or the computing environment. The verdict can be contested via “report an error”.
- 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
DECISIVE MISMATCH (data-deposit error). The in-scope 16S metabarcoding pipeline ran end-to-end on «our HPC» (QIIME2 2024.10: cutadapt -> DADA2 -> SILVA138 vsearch -> diversity) on all 15 deposited PRJNA675996 runs (1,146 ASVs, 981,226 non-chimeric reads). HEADLINE: the deposited reads are MOUSE GUT microbiota, not Sicilian table olives — dominated by Muribaculaceae 39% / Muribaculum 38% / Bacteroidota 58% (canonical murine gut), while the paper's olive taxa are essentially absent (Weissella 0.02% vs reported 85%; Enterobacter 0.01% vs reported ~57%; Lactobacillus 13%, not dominant). This CONFIRMS the SRA run metadata 'Mus musculus flora' (previously presumed a copy-paste error) and means the paper's reported 16S taxonomic results are not derivable from the cited accession. Only Good's coverage (C6, >99.98%) agrees, and that merely reflects sequencing depth. Secondary discrepancies: N=15 (C/L/H x5) vs paper 24/8; deposited amplicon is V3-V4 (341F/806R) vs the paper's stated V3-only Probio_Uni/Probio_Rev (341F/518R). FABRICATION/WRONG-DATA CONCERN flagged on C7-C9 (reported abundances absent from the data). NOT ATTEMPTED (out of scope): volatilomics (HS-SPME-GC/MS, wet-lab) and the corrplot microbiota-VOC correlation figure (needs the out-of-scope VOC table). Verdict provisional; a human reviewer should confirm and determine whether the real olive data exist under another accession.
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Assessment versions
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v1 current initial assessment Score 50assessed: 2026-06-19 ⛓ 57cbba7689e4
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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
- 2026-06-25
- 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: sonnetThe study tests whether inoculation of Sicilian table olives (Nocellara Etnea cv.) with selected Lactiplantibacillus plantarum starter cultures, at reduced (5%) NaCl content, affects microbiota composition and volatile organic compound (VOC) profile compared with uninoculated controls at 5 and 8% NaCl.
- ★ Inoculation with L. plantarum starter cultures (O1, O2) accelerates acidification, producing a faster and more pronounced pH drop than uninoculated controls (C5, C8). finding
- ★ 16S metagenetic analysis shows lactobacilli dominate the microbiota of both starter-inoculated samples (O1, O2). finding
- ★ Enterobacter genus occurs at high levels only in uninoculated control samples with 5% NaCl (C5). finding
- ★ Bacteroides, Faecalibacterium, Klebsiella, and Raoultella genera are present only in uninoculated control samples with 8% NaCl (C8). finding
- ★ Microbiota composition dynamics during fermentation significantly affect the volatile organic compound profile of the final products. finding
- ★ No off-odor-associated volatile compounds were detected in any sample investigated. finding
- ★ A dual approach combining 16S amplicon-based metagenetics and HS-SPME/GC-MS volatilomics can link microbial dynamics to VOC profiles in table olive fermentation. method
- ★ Use of low NaCl (5%) concentration together with the proposed L. plantarum starter cultures positively affects microbiota and VOCs, ensuring microbiological safety and pleasant flavor of the final product. finding
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| 16S rRNA amplicon-based sequencing (V3 region) | Table olive drupes, Nocellara Etnea cultivar | L. plantarum starter culture inoculation (O1, O2) vs uninoculated control at 5% or 8% NaCl (C5, C8) | Microbiota composition/taxonomy, alpha (Shannon, Chao1) and beta diversity (weighted UniFrac, PCoA) | MiSeq (Illumina); Probio_Uni/Probio_Rev primers; QIIME2/DADA2; SILVA 138 |
| Volatile organic compound analysis by HS-SPME GC-MS | Table olive pulp/drupes, Nocellara Etnea cultivar | L. plantarum starter culture inoculation (O1, O2) vs uninoculated control at 5% or 8% NaCl (C5, C8) | VOC profile/identification and abundance | Clarus 680 GC with Clarus SQ8MS single-quadrupole MS, Rtx-WAX column, PAL COMBI-xt autosampler |
| Classical microbiological plate counts | Brine and olive drupe samples, Nocellara Etnea cultivar | L. plantarum starter culture inoculation (O1, O2) vs uninoculated control at 5% or 8% NaCl (C5, C8) | Log10 CFU/mL or CFU/g of total mesophilic bacteria, LAB, yeasts, Enterobacteriaceae, staphylococci, E. coli, sulfite-reducing clostridia | Selective agar media (PCA, MRS, Sabouraud, VRBGA, mannitol salt agar, MacConkey, SPS agar) |
| pH measurement | Brine samples | L. plantarum starter culture inoculation (O1, O2) vs uninoculated control at 5% or 8% NaCl (C5, C8) | pH value over fermentation time (0-80 days) | MettlerDL25 pH meter |
- ▼ Inoculated samples (O1, O2) reached pH ~4.5 by day 24, whereas controls only reached a comparable pH by day 60.
- – At the end of fermentation, pH fell below the 4.3 safety threshold in all samples except control C5 (5% NaCl), which remained at 5.04. final pH: O1=4.23, O2=4.10, C8=4.36, C5=5.04
- ▼ Enterobacteriaceae counts decreased significantly from day 30 in inoculated samples, especially O2, becoming undetectable (<1 log CFU/g) earlier than in controls.
- – LAB counts increased by about 1 log unit in inoculated samples by the end of fermentation, while decreasing by about 1 log unit in control samples. ~1 log CFU/g
- – Yeast population increased by approximately 6 log units by day 15 in all samples, especially C8 (reaching 8 log CFU/g), then declined by day 80 to ~3.9 (inoculated) and ~5.2 (controls) log CFU/g. ~6 log unit increase
- – E. coli and sulfite-reducing clostridia were never detected in any sample at any fermentation time point.
- – No compounds associated with off-odor metabolites were detected in any of the investigated samples.
- pvalue p < 0.05 (Significance threshold for ANOVA/Tukey post hoc on pH, microbiological, and VOC data across biological replicates)
- pvalue p < 0.05 (Welch t-test, Benjamini-Hochberg FDR corrected) (Significance threshold for differences among fermentation processes in detected genera (STAMP software))
- mean 6.17 ± 0.08 (O1 brine pH at day 0 of fermentation)
- mean 4.36 ± 0.06 (C8 brine pH at day 80 (end of fermentation))
- count 7.85 ± 0.07 log10 CFU/g (LAB count in O2 olive samples at day 80)
- count 8.08 ± 0.11 log10 CFU/g (Peak yeast count in C8 olive samples at day 15)
- other 0 to 1 (Range of weighted UniFrac similarity values used for beta diversity/PCoA)
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 employed a multi-assay design with four fermentation conditions (O1, O2, C5, C8), each conducted in biological triplicate and monitored over 80 days. Physicochemical, microbiological, and volatile organic compound (VOC) data were compared across groups using one-way ANOVA with Tukey post hoc correction, while 16S metagenetics genus-level differences were assessed with a two-sided Welch t-test under Benjamini–Hochberg FDR. Ordination methods (PCA, PCoA on UniFrac distances) and Spearman rank correlation were used to explore multivariate relationships between microbial groups and VOC profiles. Results were reported as means ± standard deviations with a significance threshold of p < 0.05.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| One-way ANOVA with Tukey HSD post hoc test | pH values, microbiological counts (CFU/mL or CFU/g), and VOC data across fermentation groups and time points | 3 biological replicates per group | not stated |
| Two-sided Welch t-test with Benjamini–Hochberg FDR correction | Genus-level differences among fermentation processes (16S rRNA metagenetics), implemented in STAMP | — | not stated |
| Principal Component Analysis (PCA) | VOC profiles at T15 and T80 across inoculated and control samples | 3 biological replicates per group per time point | na |
| Permutation analysis (PermutMatrix) | Similarities between volatile profiles of inoculated (O1, O2) and control (C5, C8) samples at T15 and T80 | — | na |
| Principal Coordinate Analysis (PCoA) on weighted UniFrac distance matrices | Beta diversity among 16S rRNA amplicon samples | — | na |
| Spearman rank correlation | Correlation between microbial group cell densities and VOCs at T15 and T80 | — | not stated |
| Shannon and Chao1 indices | Alpha diversity within 16S rRNA amplicon samples (QIIME2) | — | na |
| Weighted UniFrac | Beta diversity between 16S rRNA amplicon samples (QIIME2) | — | na |
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One-way ANOVA was applied separately at each time point to compare groups, treating repeated longitudinal measurements (T0 through T80) as independent cross-sections↳ Could also: A linear mixed-effects model or repeated-measures ANOVA could also be used, treating fermentation batch as the repeated unit and time as a within-subject factor — A mixed-effects or repeated-measures approach explicitly models the temporal autocorrelation within each fermentation replicate, which can improve statistical power and more directly address the time-by-treatment interaction that is central to the study's aims
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Genus-level differences in the 16S metagenetics data were tested with a Welch t-test on relative-abundance or count data in STAMP↳ Could also: Negative-binomial models implemented in tools such as DESeq2 or edgeR, or compositional methods such as ANCOM-BC, could also be applied to amplicon count data — 16S amplicon data are count-based and compositional; negative-binomial or compositional methods are designed for this data structure and can handle overdispersion and sequencing-depth variation without requiring transformation
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Spearman rank correlations between microbial cell densities and VOCs were computed across many pairs without a stated multiplicity correction↳ Could also: Applying a Benjamini–Hochberg FDR correction to the full set of pairwise Spearman tests would also control the expected proportion of false discoveries — With a large correlation matrix, the number of simultaneous tests inflates the family-wise false-positive rate; FDR correction—already used elsewhere in the paper for the STAMP analyses—would make the inferential standards consistent across the two analyses
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PCA was used to visualize separation of VOC profiles among the four fermentation conditions↳ Could also: A permutation-based multivariate test such as PERMANOVA (adonis in R's vegan package) could also formally test whether group membership explains a significant proportion of VOC profile variance — PCA is an exploratory visualization; PERMANOVA provides an inferential test of group separation with a p-value and an R² effect size, complementing the ordination plot with a formal statistical statement
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Alpha diversity was summarized using Shannon entropy and Chao1 richness, with no between-group statistical test of alpha diversity explicitly described↳ Could also: A Kruskal–Wallis test (or one-way ANOVA if assumptions hold) on Shannon or Chao1 values across the four conditions could also formally test whether inoculation or salt level alters within-sample diversity — Reporting index values without a significance test leaves it unclear whether observed differences in alpha diversity exceed what would be expected by chance; a formal test would distinguish meaningful diversity shifts from sampling variability
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Results throughout were reported as means ± SD with a binary significance indicator (p < 0.05 / letter groupings), without effect sizes or confidence intervals↳ Could also: Reporting 95% confidence intervals or a standardized effect size such as Cohen's d or eta-squared alongside p-values would also convey the magnitude and precision of observed differences — Effect sizes and confidence intervals communicate practical significance and estimation uncertainty, allowing readers to judge whether statistically significant differences are also biologically meaningful, which is especially useful when n = 3 per group
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-35281313
Title: Metagenetic and Volatilomic Approaches to Elucidate the Effect of Lactiplantibacillus plantarum Starter Cultures on Sicilian Table Olives. Vaccalluzzo et al., Front Microbiol 2022. DOI: 10.3389/fmicb.2021.771636. PMCID PMC8914321. Data: PRJNA675996 (NCBI SRA). "Code": https://github.com/taiyun/corrplot (generic R correlation-plot package — third-party, used for Fig. correlation heatmaps).
What the paper reports (two methodological arms)
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Metagenetic (16S rRNA amplicon) — IN SCOPE (pipeline-derived).
- Platform: Illumina MiSeq; target = V3 region of 16S rRNA, primers Probio_Uni / Probio_Rev (Milani et al. 2013).
- Pipeline: QIIME2 + DADA2 (ASVs at 100% homology) + taxonomy vs SILVA release 138.
- QC: keep reads length 140–400 bp, mean Q>20; drop homopolymers>7 bp & primer mismatches.
- Reported computational outputs we will try to reproduce:
- Total 449,654 bacterial sequences; avg 56,207 seq/sample.
- Taxonomy: 3 phyla, 7 families, 10 genera at rel. abund. >0.5%; dominant phyla Firmicutes & Proteobacteria.
- Alpha diversity: Good's coverage >99%; Shannon & Chao1 (Supplementary Table 2); Chao1 ↑ from d15→d80.
- Relative abundances (Results): Weissella 85.09% (C8 d15) / 78.34% (C8 d80); Enterobacter ~57% in C5; Lactobacillus dominant & significantly higher in inoculated (O1/O2) vs controls (Welch p<0.05).
- Beta diversity: PCoA, PC1 explains >75% of variance.
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Volatilomic (HS-SPME-GC/MS) — OUT OF SCOPE (wet-lab/instrumental). Volatile organic compound profiling is bench chemistry, not a bioinformatic pipeline; not reproducible from deposited data. Not attempted.
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Correlation analysis (corrplot) — partially in scope, depends on (1)+(2). The cited "code" repo is the generic R
corrplotpackage used to draw microbiota↔VOC correlation heatmaps. It is a plotting tool, not an analysis pipeline, and requires the VOC table (arm 2, out of scope) as input, so the correlation figure cannot be fully reproduced. Not a primary target.
Primary reproduction target
Run the standard 16S amplicon pipeline (QIIME2/DADA2/SILVA138) on the deposited PRJNA675996 reads and compare: total/avg sequence counts, taxonomic richness (phyla/families/genera >0.5%), dominant genera & their relative abundances, and alpha diversity (Good's coverage, Shannon, Chao1).
CRITICAL DATA CAVEAT (deposit ↔ paper mismatch) — see dataset_profile.json
The paper's Data Availability cites PRJNA675996, and describes the 16S design as
4 treatments (O1,O2,C5,C8) × 2 timepoints (d15,d80) × triplicate = 24 samples
(its own sequence-count arithmetic, 449,654/56,207, implies 8).
The actual SRA deposit contains 15 runs (SRR13048283–297) in 3 groups of 5
with aliases 1-C1-s … 5-C5-s, 6-L1-s … 10-L5-s, 11-H1-s … 15-H5-s, and every
run's description reads "16s rDNA of Mus musculus flora" (an obvious copy-paste
error from another submission). The group labels C/L/H and replicate count (5) do
not map cleanly onto the paper's O1/O2/C5/C8 × d15/d80 × 3 design. This is a
material reproducibility issue: the deposited data cannot be unambiguously aligned
to the paper's reported samples. We will still run the pipeline on the 15 deposited
runs and report what is actually present, grading the N-dependent claims accordingly.
Compute plan
All heavy compute on «our HPC» (SLURM). Download 15 ENA FASTQs to «infra» on front1; build QIIME2 env on front1; submit DADA2/SILVA job; pull back small summary tables (feature table summary, taxa barplot data, alpha-diversity vectors, PCoA eigenvalues).
Status — COMPLETE (2026-06-25)
Pipeline RAN on «our HPC» (QIIME2 2024.10: cutadapt->DADA2->SILVA138 vsearch->diversity) on all 15 deposited runs. DECISIVE FINDING: the deposited data are MOUSE GUT microbiota, not table olives (Muribaculaceae 39%/Muribaculum 38%/Bacteroidota 58%; Weissella 0.02% vs reported
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Reproduction footprint
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