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Reviewers' comments:

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Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Partly

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available??>

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.-->

Reviewer #1: No

Reviewer #2: Yes

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Reviewer #2: Yes

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Reviewer #1: Diet and gut microbiome of skipjack tuna (Katsuwonus pelamis) as indicators of environmental changes

Manuscript Number: PONE-D-25-46392

Summary & Overall Assessment

This manuscript examines whether the diet and gut microbiome of skipjack tuna can act as indicators of rapid environmental change across a four-month transition from La Niña (Dec 2022) to the onset of El Niño (Mar 2023) near the Solomon Islands. The study sampled 15 tuna schools (∼10 fish per school), preserved gut lining for both diet metabarcoding (COI) and 16S rRNA microbiome profiling, and related community patterns to ENSO phase, SOI, SST, and chlorophyll-a. Diet composition showed no significant ENSO signal, whereas the microbiome displayed significant shifts in alpha and beta diversity, with five bacterial families differing between phases and supporting SOI prediction via a random-forest model.

The work is timely and potentially useful to ecosystem monitoring. Methodologically, it is generally careful (negative controls, standards, dual assays, transparent pipelines). However, several analytical and reporting issues need attention—especially study design/replication, statistical handling (PERMANOVA assumptions, alpha-diversity modeling), model validation for SOI prediction with very small training sets, and fuller ethics/data/code reporting. I recommend major revision.

Title and Abstract

Strengths: Clear, accurate, and aligned with results; avoids overstating novelty. The abstract correctly contrasts weak diet signals with stronger microbiome responses, and it names the five key families and the modeling approach.

Suggestions:

1. Tone down “successfully predicted SOI” and add a brief caveat that external validation was mixed (good on TGM, poor on GMB), likely due to range mismatch and storage effects.

2. Consider noting the short, two-time-point design to set expectations.

Introduction

Strengths: The motivation for using predator guts (diet + microbiome) as sentinel readouts is well framed; the ENSO context is clear; the gap (microbiome responses in skipjack) is articulated.

Suggestions: When attributing functional roles to higher-taxonomic ranks (e.g., family-level “probiotic” or immune associations), emphasize that function cannot be inferred directly from amplicon data and that families are ecologically broad. (You can preserve these links but frame them as hypotheses, supported by cited literature.)

Materials and Methods

Study design and sampling

Strengths: School-based design spanning a strong phase transition is compelling; within-school replication (∼10 fish) is practical.

Major points to address:

1. Temporal/Spatial confounding: All La Niña schools were sampled in December and all El Niño schools in March; locations span 05–09°S, 158–161°E. Please discuss potential spatial confounding and time-lag effects explicitly (ENSO signals propagate, and ecological responses can lag weeks–months). A map with school positions and dates would help.

2. Independence & hierarchical structure: Analyses sometimes operate at the individual level and sometimes at the school level (e.g., SOI models use school-level log10 abundances). Given the evident school effect in microbiome beta diversity (R² ≈ 0.15), please account for school as a grouping factor (random effect or blocking) wherever appropriate.

Laboratory and library prep

Strengths: Clear protocols; blocking primer for host COI; triplicate PCRs; negative controls at every stage; inclusion of ZymoBIOMICS community standards.

Suggestions: State explicitly whether any decontamination algorithm (e.g., decontam) was applied in addition to negative-control screening, especially relevant for families such as Propionibacteriaceae/Cutibacteriaceae that can be skin-associated. (You do note clean negatives.)

Bioinformatics and normalization

Strengths: DADA2, unambiguous phylum-level assignment, chloroplast/mitochondria removal, ANCOM-BC2 for differential abundance, and UniFrac for beta diversity—all standards.

Major points to address:

1. Alpha diversity computed on non-normalized counts: The text says alpha diversity indices were computed on non-normalized data. This can confound diversity with sequencing depth. Please either rarefy, include depth as a covariate, or use estimators robust to depth (e.g., breakaway/DivNet).

2. PERMANOVA assumptions: Before interpreting PERMANOVA, test multivariate dispersion (PERMDISP/betadisper). Unequal dispersion across groups (e.g., ENSO phases) can inflate Type I error. Please add the results or clarify whether they have already been provided.

3. Choice of distance & compositionality: You used unweighted UniFrac (presence/absence) after TSS normalization. Consider complementing with a compositional approach (Aitchison/CLR + Euclidean or PhILR) to ensure results are not an artifact of prevalence filtering or sequencing depth.

4. Multiple testing and effect sizes in ANCOM-BC2: Please report the false discovery rate (FDR) adjustment and the effect sizes, which are bias-corrected log-fold changes with confidence intervals (CIs), for the five significant families.

Environmental data

Suggestions: Specify the exact products for SST/CHLA (e.g., MODIS/VIIRS product IDs), temporal windows used for extraction (8-day composites are listed), and any spatial averaging buffers around coordinates. Consider testing time-lagged windows (e.g., 2–8 weeks) to match biological integration times.

Statistics and modeling

Major points to address:

1. Alpha-diversity GAMs vs. non-normality: You note indices are non-normal but then fit Gaussian GAMs to continuous covariates. Either transform, fit appropriate distributions, or use non-parametric smoothers with robust inference; report diagnostics.

2. SOI prediction with tiny n: The SOI models use five family-level predictors at the school level with n≈15—very small for random forests. Please conduct internal cross-validation that respects grouping (e.g., leave-one-school-out) and report those metrics. Current external validation is mixed (excellent for TGM; poor for GMB), consistent with overfitting and domain shift. Include permutation importance and partial-dependence plots.

Ethics: The submission form says, “All necessary permits … were obtained,” but PLOS ONE requires details for field research/animal work (permit numbers, issuing authority, and capture, handling, and euthanasia methods or rationale). Please add these in the Methods and Ethics Statement.

Results

Diet

Strengths include solid lab throughput, 16.3 million raw reads for diet analysis, 60 out of 75 samples containing non-Scombridae prey, and a dominance of fish species such as Myctophidae and Acanthuridae, with Cavoliniidae (pelagic gastropods) being particularly notable—this highlights the sensitivity of high-throughput sequencing (HTS). No prey family showed differences due to ENSO, which you interpret with caution.

Suggestions: Remind readers that read-based RA is semi-quantitative; you do use FOO and RA appropriately. Consider presenting Hill numbers and reporting sequencing depth summaries per sample alongside alpha metrics.

Microbiome

Strengths: 2.9 M post-QC reads across 142 samples; significant effects of ENSO/SOI on richness/evenness and beta diversity; clear visualization; Vibrionaceae dominance supports freshness.

Major points to address:

1. Add PERMDISP results; include effect sizes (e.g., R² with CIs) and 95% CIs/ribbons on GAM plots; annotate group n’s on figures.

2. Report ANCOM-BC2 statistics (adjusted p, LFC, CI) for the five families; indicate filtering thresholds and prevalence explicitly in the figure caption.

SOI prediction

Strength: Innovative use of microbiome to predict an environmental index; comparative modeling.

Concerns and requests:

1. Provide internal cross-validation that leaves out schools; with n≈15, report repeated CV variance.

2. Calibrate expectations in the text: training R²=0.991 and MSE=4.9 vs. poor performance on GMB suggests overfitting/domain mismatch; discuss implications for operational use.

Discussion and Conclusions

Strengths: Balanced interpretation; limitations acknowledged (limited timeframe, storage/time-range discrepancies in validation sets).

Suggestions:

1. Expand discussion of spatial/temporal confounding and school effects; emphasize that two time points cannot separate ENSO from seasonal or spatial gradients.

2. Reframe functional inferences as hypotheses (immune vs. “probiotic” roles) given family-level resolution; suggest future metagenomics/metatranscriptomics.

Figures, Tables, and Presentation

Positives: The heatmap and NMDS are clear; the feeding-strategy plot is helpful.

Edits:

1. Add sample-size annotations, CIs on GAM smooths, and color-blind-safe palettes.

2. Minor language edits: “drifting or anchored FADs” (not “of anchored”), “Actinopterygii” (spelling), and “were sequenced” (verb agreement).

Reviewer #2: This is a strong and timely study linking ENSO events with skipjack tuna diet and gut microbiomes. The dual use of diet and microbiome data, coupled with high-throughput sequencing and predictive modeling, makes the work novel and valuable. The paper is well structured, but it would benefit from clearer framing of limitations, more cautious interpretation of microbiome functions, and improved presentation.

1. Scope and Limitations

Highlight more clearly in the Discussion and Conclusion that the study covers only 15 schools over 4 months. Emphasize the need for longer-term, multi-year sampling.

2. Diet Analysis

In the Results, acknowledge the low proportion of successful prey detection (40%).

In the Discussion, expand on causes (empty stomachs, degraded DNA, host DNA dominance) and suggest solutions (alternative markers, host DNA depletion).

In the Conclusion, note that diet results are preliminary compared to microbiome findings.

3. Gut Microbiome

Add caution in the Discussion when linking bacterial families to immune or probiotic functions. Suggest future validation with metagenomics/metatranscriptomics.

4. Modeling

Expand in the Results/Discussion on why the Random Forest model failed with the GMB dataset (dataset differences, SOI range, storage issues).

Suggest adding environmental covariates and full ENSO cycle sampling for stronger predictive models.

5. Figures

Expand figure legends for clarity.

Add a workflow diagram (Methods) and a conceptual diagram (Discussion/Conclusion).

6. Methods & Ethics

Move detailed PCR conditions to Supplementary Material.

Add permit numbers in the Ethics Statement.

7. Language

Avoid repeating statistics in both Results and Discussion.

Correct minor grammar (e.g., “in study” → “in this study”) and standardize references.

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what does this mean?). If published, this will include your full peer review and any attached files.). If published, this will include your full peer review and any attached files.). If published, this will include your full peer review and any attached files.). If published, this will include your full peer review and any attached files.

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Reviewer #1: Yes: Aratrika RayAratrika RayAratrika RayAratrika Ray

Reviewer #2: No

**********

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Dear Dr. Zhou,

Please submit your revised manuscript by Mar 16 2026 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

• A letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
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Senior Staff Editor

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions??>

Reviewer #1: Partly

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available??>

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.-->

Reviewer #1: No

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

Reviewer #2: Yes

**********

Reviewer #1: I thank the authors for their detailed and thoughtful responses to the initial review and for the substantial revisions made to the manuscript. Overall, the revised version shows a clear improvement in statistical rigour, transparency, and balanced interpretation. Many of the methodological and interpretative concerns raised in the first round have been carefully addressed, and I appreciate the effort invested in strengthening the analyses and presentation.

The authors deserve special recognition for their efforts:

(i) adding PERMDISP tests to support PERMANOVA interpretations;

(ii) incorporating a compositional (CLR-based) beta-diversity analysis alongside UniFrac;

(iii) revising alpha-diversity analyses to account for sequencing depth;

(iv) expanding ANCOM-BC2 reporting to include effect sizes and multiple-testing correction; and

(v) substantially improving the Discussion by acknowledging design limitations and reframing functional inferences more cautiously.

Most of my original comments have therefore been satisfactorily addressed. I have only a small number of remaining points, primarily related to clarity and consistency of interpretation rather than additional analyses.

1. Interpretation of microbiome vs. diet responses

The manuscript now appropriately emphasises the short, two-time-point sampling design and its limitations. However, in a few places, the text still implies that the absence of detectable diet changes, combined with microbiome shifts, provides evidence that gut microbiomes respond more rapidly or directly to ENSO forcing. While this interpretation is plausible, it cannot be demonstrated with the current design and remains inferential.

I recommend consistently framing this contrast as a hypothesis or inference, rather than as supporting evidence, throughout the Discussion. This would further align the interpretation with the acknowledged limitations of temporal and spatial confounding.

2. Treatment of school effects across analyses

The rationale for aggregating microbiome data at the school level for SOI modelling is statistically sound, and I agree that SOI is inherently a school-level variable. However, the manuscript alternates between describing school as a fixed effect and as a random effect in different parts of the Methods and Results.

For clarity, I suggest briefly harmonising this language and explicitly stating how school effects are handled in each analytical context (PERMANOVA, GAMs, and predictive models). This will help readers follow the hierarchical structure of the analyses more easily.

3. Predictive modeling and strength of claims

The additional leave-one-school-out cross-validation, permutation importance, and partial-dependence plots substantially strengthen the modelling section. The revised Discussion is also more balanced in acknowledging mixed external validation and domain-shift effects.

That said, given the minimal sample size (n ≈ 15 schools), repeated emphasis on “100% ENSO phase classification accuracy” risks being interpreted as stronger evidence of predictive power than is warranted. I recommend consistently qualifying these results as exploratory and proof-of-concept, rather than predictive in an operational sense, whenever they are mentioned.

4. Effect sizes and variance explained

Many microbiome–environment relationships explain a relatively small proportion of total variance (e.g., R² ≈ 0.02). This is not problematic and is common in ecological microbiome studies, but explicitly acknowledging this in the text would further strengthen the manuscript’s interpretive balance and prevent over-interpretation of statistically significant effects.

Overall assessment

In its current form, the manuscript presents a careful and methodologically sound proof-of-concept study demonstrating that skipjack tuna gut microbiome composition responds detectably to ENSO transitions under the conditions sampled, while diet signals remain comparatively weak. The authors have responded constructively to reviewer feedback, and the revised manuscript now aligns well with PLOS ONE’s emphasis on technical soundness and transparency.

Subject to the minor clarifications outlined above, I believe the manuscript is suitable for publication.

Recommendation: Minor revision.

Reviewer #2: The revisions have resolved all major concerns from the previous round, including statistical robustness, limitation acknowledgments, and balanced interpretations.

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what does this mean?). If published, this will include your full peer review and any attached files.). If published, this will include your full peer review and any attached files.). If published, this will include your full peer review and any attached files.). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

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Reviewer #1: Yes: Aratrika Ray, PostDoc Researcher, Dept. of Aquatic Resources, Swedish University of Agricultural SciencesAratrika Ray, PostDoc Researcher, Dept. of Aquatic Resources, Swedish University of Agricultural SciencesAratrika Ray, PostDoc Researcher, Dept. of Aquatic Resources, Swedish University of Agricultural SciencesAratrika Ray, PostDoc Researcher, Dept. of Aquatic Resources, Swedish University of Agricultural Sciences

Reviewer #2: No

**********

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Diet and gut microbiome of skipjack tuna (Katsuwonus pelamis) as indicators of environmental changes

PONE-D-25-46392R2

Dear Dr. Zhou,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Jianhong Zhou

Staff Editor

PLOS One

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions??>

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: Yes

Reviewer #2: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available??>

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.-->

Reviewer #1: No

Reviewer #2: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: All the comments have been satisfactorily addressed by the authors, therefore I find its uitable now for acceptance and publication.

Reviewer #2: (No Response)

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Reviewer #1: Yes: Aratrika Ray, Ph.D., Dept. of Aquatic Resources, Swedish University of Agricultural SciencesAratrika Ray, Ph.D., Dept. of Aquatic Resources, Swedish University of Agricultural SciencesAratrika Ray, Ph.D., Dept. of Aquatic Resources, Swedish University of Agricultural SciencesAratrika Ray, Ph.D., Dept. of Aquatic Resources, Swedish University of Agricultural Sciences

Reviewer #2: No

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