Ligilactobacillus salivarius regulating translocation of core bacteria to enrich mouse intrinsic microbiota of heart and liver in defense of
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”.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
- 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
▸Reproduction agent’s raw note
DROP (docs_insufficient; secondary no_expected_result). Data is public and obtainable: RU accession PRJNA1117782 = single run SRR29213176, an Illumina shotgun metagenome (191,183,328 read pairs, 57.7 Gbp, ~24.4 GB gzip; ENA fastq_ftp resolves). Code is public: the RU link is upstream MEGAHIT (GPL-3.0, active). NOT described well enough to reproduce 1:1: the paper gives no code-availability statement and no authors' pipeline, names tools (MEGAHIT v1.1.2, CD-HIT v4.6.1, BWA, SOAPaligner, QIIME2, PICRUSt) with ZERO parameters/commands, and reports NO MEGAHIT/CD-HIT-derived value at all (no assembly length, contig count, N50, gene-catalog size, or COG counts). The numbers it does report -- clean-read 99.39%, OTUs 157/159/218/431, PCoA 56.50%/26.04% -- come from undocumented downstream steps and are not regenerable 1:1 (and OTUs are not a MEGAHIT output). The paper's headline OTU/phyla numbers actually derive from a separate 16S amplicon pipeline (QIIME2) on different data (PRJNA811797), outside this RU's code x data pairing. DID NOT ATTEMPT: a default-parameter MEGAHIT assembly of SRR29213176 -- it would produce a real artifact but with nothing in the paper to grade it against (ungradeable), so per the 80/20 rule no «our HPC» compute was spent and no grade was fabricated. Possible-fabrication note for the human auditor: the WGS clean-read figure '842,179,176 valid clean reads / 99.39% of the total genome' is not clearly derivable from the single deposited run (191.18 M pairs).
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
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v1 current initial assessmentassessed: 2026-06-15 ⛓ 8e817191f49f
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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
- 2026-06-15
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-15no 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: opusDo intrinsic microbiota reside in the heart and liver of healthy mice and constitute a microbiological barrier against pathogens, and does dietary Ligilactobacillus salivarius supplementation drive translocation of intestinal core bacteria to these organs to enhance anti-oxidative defense against heat stress?
- ★ Intrinsic microbiota (chiefly genera Burkholderia and Ralstonia) reside in the heart and liver of SPF mice, with the heart having lower bacterial abundance than the liver finding
- ★ Intrinsic bacteria in the heart exert inhibitory action against pathogenic E. coli, acting as a microbiological barrier finding
- ★ Oral Ligilactobacillus salivarius supplementation regulates translocation of core bacteria (e.g., Lactobacillus reuteri) from the intestine to the heart and liver mechanism
- ★ The enriched bacterial composition up-regulates anti-oxidation capacity (increased SOD, altered ROS) in heart and liver under heat stress finding
- Lactobacillus sp. were detected in the liver but not in the heart of SPF mice finding
- Culturomics combined with metagenomic sequencing verifies presence of bacteria in heart flushing liquid method
- FISH and qPCR with a Lactobacillus reuteri 16S-based probe/primers quantify translocation of L. reuteri to organs method
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| Metagenomic (shotgun) sequencing | SPF BALB/c mouse heart, liver, and lung flushing liquid | none (healthy/intrinsic baseline) | bacterial taxonomic composition, OTUs, COG functional prediction | Illumina HiSeq; MEGAHIT, CD-HIT, BWA, SOAPaligner |
| Culturomics with inhibition (cylinder-plate) assay | Mouse heart flushing liquid; pathogenic E. coli ATCC 25922 | culture in MRS/YEPD, ferment then test on E. coli | bacterial flora, inhibitory zone against E. coli, fermentation pH | MRS broth, YEPD, LB, MacConkey medium |
| 16S rRNA gene (V3-V4) amplicon sequencing | Heart, liver, and ileum of heat-stressed mice ± L. salivarius | oral L. salivarius supplementation (1×10^8 CFU/mL, 0.4 mL) under 37°C heat stress | OTUs, alpha/beta diversity, KEGG functional prediction (PICRUSt) | Illumina MiSeq (2×300); primers 338F/806R; QIIME2 |
| Fluorescence in situ hybridization (FISH) | Heart, liver, ileal mucosa of L. salivarius-supplemented mice | L. salivarius supplementation under heat stress | localization/translocation of Lactobacillus reuteri | carboxytetramethylrhodamine probe; Olympus BX53 microscope |
| Quantitative PCR (qPCR/qRT-PCR) | Ileum, heart, liver of mice ± L. salivarius | L. salivarius supplementation under heat stress | L. reuteri abundance via standard curve (2^-ΔΔCT, normalized to β-actin) | ABI 7900HT; SuperReal PreMix Plus SYBR Green |
| Anti-oxidation assays (ROS and SOD) | Heart, liver, ileal mucosa cell suspensions | L. salivarius supplementation under heat stress vs control | ROS fluorescence values and SOD levels | DCFH-DA fluorescence (488/525 nm); SOD kit (Nanjing Jiancheng) |
- ▲ ROS and SOD levels significantly improved with L. salivarius supplementation versus control
- – Dominant phyla (Bacillota, Bacteroidota, Pseudomonadota, Thermodesulfobacteriota, Actinomycetota) comprised 98.2% of total bacteria in liver and heart after supplementation 98.2%
- ▼ Heart had lowest bacterial richness with only 157 OTUs detected (159 OTUs in culture) 157 OTUs
- – Intrinsic heart/liver bacteria are primarily genera Burkholderia and Ralstonia
- – After host read removal, 842, 179, and 176 valid clean reads obtained, comprising 99.39% of total genome 99.39%
- ▲ Lactobacillus reuteri translocated from intestine to heart and liver upon supplementation
- pvalue P < 0.01 (ROS and SOD significantly improved vs control)
- other 98.2% (proportion of total bacteria from five dominant phyla in liver and heart)
- count 157 OTUs (OTUs detected in heart (lowest richness))
- count 159 OTUs (OTUs found in culture of heart)
- other 99.39% (valid clean reads as proportion of total genome after host removal)
- count 842, 179, 176 (valid clean reads from heart/liver/lung)
- count 1.6×10^10 CFU/mL (live L. salivarius after 16 h culture)
- mean 27.93 ± 0.39 g (average body weight of mice selected after 7 d supplementation)
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 used two animal experiments in SPF BALB/c mice: one characterizing intrinsic organ microbiota via metagenomic and culturomic assays, and a second comparing Ligilactobacillus salivarius supplementation versus control under heat stress (n=20/group, 4 replicates of 5 mice). Primary comparisons of body weight, qRT-PCR, and sequencing-derived outcomes were tested with one-way ANOVA; microbial community structure was assessed via weighted UniFrac with PCoA/PCA visualization; and correlations between bacterial composition and antioxidation indexes were evaluated with Spearman's rank correlation. Results were reported using significance thresholds (P<0.05 or P<0.01) without exact p-values or effect sizes.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| One-way ANOVA (GLM procedure) | Body weight, qRT-PCR (Lactobacillus reuteri quantification), and sequencing-derived data comparisons between supplemented and control groups | 8 mice per group (2 selected from each of 4 replicates) | not stated |
| Spearman's rank correlation | Correlation between bacterial composition and antioxidation indexes (ROS, SOD) across groups | — | not stated |
| Weighted UniFrac distance with PCoA and PCA visualization | Beta diversity of microbial communities across heart, liver, and lung samples | 10 mice (first experiment); 8 mice per group (second experiment) | not stated |
| OTU-based alpha diversity metrics (pan/core analysis via QIIME2) | Within-sample microbial diversity in heart, liver, ileum | — | not stated |
| PICRUSt functional prediction | Predicted KEGG ortholog functional profiles from 16S rDNA community data | — | na |
| Cylinder-plate inhibition assay (zone measurement) | Inhibitory action of heart flushing liquid fermentate against pathogenic E. coli 25922 | — | na |
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Multiple outcome variables (body weight, ROS, SOD, qRT-PCR, sequencing metrics) were each tested with separate one-way ANOVAs without a stated multiplicity correction↳ Could also: Apply a false discovery rate correction (e.g., Benjamini-Hochberg) or a family-wise error correction (e.g., Bonferroni) across the family of tests — When several outcomes are tested simultaneously, a correction procedure would also control the expected proportion of false positives across the test family, which is a common reporting standard in multi-outcome studies
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The two-group comparison (supplemented vs. control) was analyzed with one-way ANOVA↳ Could also: Use an independent-samples t-test (or its non-parametric analogue, Mann-Whitney U) for each two-group continuous outcome — For a single two-level factor, a two-sample t-test and one-way ANOVA are mathematically equivalent; making this explicit can clarify the test structure, and Mann-Whitney U would also be applicable if normality cannot be assumed given the small per-group n (8)
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Dispersion in continuous outcomes was reported as mean ± SD for body weight; no dispersion measure was reported for ROS or SOD values↳ Could also: Report 95% confidence intervals or show individual data points alongside group means for all outcomes — Confidence intervals would also convey both the magnitude of the estimate and its precision, and are particularly informative when group sizes are small (n=8 per group); showing individual data points allows readers to assess distributional spread directly
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Beta diversity was visualized with PCoA and PCA of weighted UniFrac distances, but no formal statistical test of group separation was stated↳ Could also: Accompany ordination plots with a permutation-based multivariate test such as PERMANOVA (adonis in R vegan) or ANOSIM — A permutation test on the distance matrix would also provide a p-value for whether microbial community composition differs significantly between groups, complementing the visual ordination
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Functional profiles of microbial communities were predicted from 16S rDNA data using PICRUSt↳ Could also: Use Tax4Fun2, PICRUSt2, or direct shotgun metagenomics (which was also performed in experiment 1) for functional annotation of the 16S-based communities — PICRUSt2 and Tax4Fun2 use updated reference databases and ASV-level inputs; since the study also generated whole-genome shotgun metagenomics data for the first experiment, direct functional annotation from those reads (e.g., via HUMAnN) would also be applicable to that dataset without relying on reference-based prediction
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OTU clustering was used for 16S rDNA diversity analysis↳ Could also: Use amplicon sequence variants (ASVs) via DADA2 or Deblur as an alternative to OTU clustering — ASV-based approaches resolve sequences to single-nucleotide resolution without a similarity threshold, which can improve taxonomic precision and reproducibility across studies; this is now a common alternative to 97%-similarity OTU clustering
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.
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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.
Downstream reach in the literature
0 downstream papers · 6 datasetsHow widely the datasets deposited by this paper are reused across the whole literature (Europe PMC), beyond our assessed set. This is a factual dependency map — reusing a public dataset is normal, good science. It is not a judgement on the downstream papers; the only verdict here is this paper's own, with its cited rationale.
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-40276518
Paper: Yang J, Shang P, Liu Z, Wang J, Zhang B, Zhang H. Ligilactobacillus salivarius regulating translocation of core bacteria to enrich mouse intrinsic microbiota of heart and liver in defense of [oxidative stress]. Front Immunol 2025. PMID 40276518 · PMCID PMC12018310 · DOI 10.3389/fimmu.2025.1540548.
RU pairing as spawned: code = https://github.com/voutcn/megahit (upstream
MEGAHIT assembler) · data = sra:PRJNA1117782.
Datasets in the paper (Data Availability Statement, verbatim accessions)
| Data | Accession | BioProject | Type |
|---|---|---|---|
| 16S rRNA (V3–V4, 338F/806R, MiSeq) | SRR18190482 | PRJNA811797 | amplicon |
| Culturomics, heart | SRR29254823 | PRJNA1119040 | WGS |
| Whole genetic seq (heart/liver/lung), HiSeq | SRR29213176, SRR29234301, SRR29240348 | PRJNA1117782, PRJNA1118213, PRJNA1118345 | shotgun metagenome |
The RU's data accession PRJNA1117782 = exactly one run, SRR29213176
(ENA: metagenome, WGS, ILLUMINA, 191,183,328 paired reads, 57.7 Gbp,
~24.4 GB gzip FASTQ; fastq_ftp resolves, byte sizes present → data is public
and obtainable).
Pipeline tools named in Methods 2.2
MEGAHIT v1.1.2 · CD-HIT v4.6.1 · BWA v0.7.17 · SOAPaligner (soap2.21) · QIIME2 · PICRUSt · COG (2020). No parameters, no k-mer sizes, no identity thresholds, no command lines, and no workflow/pipeline order are given for any of them. The Methods literally state only: "MEGAHIT (v1.1.2) and CD-HIT software (v4.6.1) were used."
Reported quantitative results, classified
| Reported value | Location | Pipeline | In scope of MEGAHIT×PRJNA1117782? |
|---|---|---|---|
| Clean-read retention 99.39% ("842,179,176 valid clean reads") | §3.1 | read-QC (unnamed) | reported, but no QC tool/params named |
| OTUs: heart 157 / cultured heart 159 / liver 218 / lung 431 | Fig 1A | OTU clustering (unnamed) | reported, but no clustering method/threshold named |
| PCoA factors 56.50% & 26.04% | Fig 1E | ordination (unnamed) | reported, but no distance/ordination params |
| 5 phyla = 98.2% | Fig 3C | 16S amplicon (QIIME2), PRJNA811797 | OUT — different data + pipeline |
| PCoA 82.69% / 72.39% | Fig 3B/3E | 16S ordination | OUT — different data |
| L. reuteri 10⁵ CFU/g; inhibition zones 20.39/18.89 mm; ROS/SOD P<0.01 | Fig 4/5 | wet-lab (qPCR, plating, assays) | OUT — not pipeline-derived |
| Genome assembly length / #contigs / N50 / GC | — | MEGAHIT | NOT REPORTED at all |
| Non-redundant gene-catalog size after CD-HIT | — | CD-HIT | NOT REPORTED at all |
| COG/KEGG category counts | — | annotation | NOT REPORTED at all |
In scope vs out of scope
- In scope (pipeline-derived, RU's code×data): the MEGAHIT v1.1.2 assembly of SRR29213176, and any CD-HIT gene catalog / functional summary derived from it.
- The blocking problem: the paper reports no MEGAHIT/CD-HIT output value at all (no assembly length, contig count, N50, gene count, COG count) → there is no expected result to grade the specified tool against. The numbers the paper does report (OTUs, clean %, PCoA %) come from undocumented downstream steps with zero parameters, so they cannot be regenerated 1:1.
- Out of scope: the 16S phylum/PCoA results (different data PRJNA811797 + QIIME2) and all wet-lab assays (CFU, inhibition zones, ROS/SOD).
Code-availability reality
The paper gives no code-availability statement and links no authors' own pipeline. The RU's GitHub link is upstream MEGAHIT (public, GPL-3.0, active — last push 2025-10-28). This is the P16 "third-party tool on the paper's data" case, which is normally fully valid — but here it is blocked not by the tool's validity, rather by the absence of (a) any reported MEGAHIT-derived value and (b) any parameters/workflow for the values that are reported.
Decision
DROP — docs_insufficient (with no_expected_result for the MEGAHIT
artifact specifically). Data and code both exist and are public;
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.
This is a justified DROP (docs_insufficient): data (SRR29213176) and a generic MEGAHIT repo are public, but the paper gives no code-availability statement, no parameters for any named tool, and reports no MEGAHIT/CD-HIT-derived value to grade against, so nothing could be put against our pipeline (q2 red). The problem sits squarely on the authors' side — the only reported WGS number, '842,179,176 valid clean reads / 99.39%', does not reconcile with the single deposited 191.18M-pair run (fabrication-suspect, q5 red), and the headline OTU/phyla figures actually come from a different 16S accession (PRJNA811797) than the RU's WGS deposit. The central wet-lab/16S conclusion is out of scope here, so it is untested rather than refuted (q7 yellow), but overall reproduction quality is critical (q8 red) given the un-reproducibility plus the unresolved read-count discrepancy.
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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.