-->PONE-D-26-15087-->-->Loss of Fmr1 reorganizes the multi-elemental composition of neural and somatic tissues in Fragile X Syndrome mice-->-->PLOS One

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Additional Editor Comments:

While both reviewers appreciate the importance of this study to FXS field, Reviewer 2 has raised concerns about the clarity of data presentation and statistical analysis performed in this study. The authors are recommended to consider the suggestions provided by both reviewers when revising their manuscript.

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Reviewers' comments:

Reviewer's Responses to Questions

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

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Reviewer #1: Yes

Reviewer #2: Partly

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

Reviewer #1: I Don't Know

Reviewer #2: No

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Reviewer #1: Yes

Reviewer #2: No

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Reviewer #1: Yes

Reviewer #2: No

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-->5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)-->

Reviewer #1: This is a very interesting study measuring the multivariate balance of 10 elements in tissues of WT and Fmr1KO mice. The authors compared ion composition of gut, brain, fur and feces in WT and Fmr1KO mice. Differences are found as a function of brain region and genotype. Of note, higher iron is found in the olfactory bulb of Fmr1KO and higher magnesium and zinc in the feces of WT mice. The authors discuss the findings considering autism spectrum disorders. Overall, the study of ionomics is important, and relatively new, to the fragile X field potentially offering new biomarkers.

Issues to Address:

Abstract

Line 13: recommend changing “and ion flux” to “including mRNAs that code for proteins regulating ion flux”.

Lines 13-14: The statement, “a comprehensive comparison of elemental balance between FXS genotypes and tissues remains absent from the literature”, does not seem fair considering the work by Talvio et al measuring Na, Mg, P, K, Mn, Fe and Cu in cortex, cerebellum, liver, spleen and heart.

Introduction

Line 72: Since there is no global mechanism enforcing a fixed total elemental constant, why would elements be constrained to a constant sum? Aren’t elements regulated independently, i.e., sodium via kidneys and aldosterone; calcium via bone remodeling, PTH and vitamin D; and iron via absorption and recycling? In a related publication by Talvio and colleagues, they compared absolute amounts of elements in WT versus Fmr1KO mice.

Methods

More detail should be added on animal husbandry. Were littermate mice used? What was the diet/bedding/etc. that may have affected mineral levels.

Discussion

Can the authors add to the discussion: (1) any limitations associated with the use of isoflurane that may affect mineral, particularly iron, levels? (2) compare/contrast methods with Talvio such as CO2 versus isoflurane. (3) Discuss the large difference in absolute mineral content between the current study and the Talvio study Table 3. Talvio has data for cortex and cerebellum, and the authors have PMHTH and olfactory brain. It looks like about a 10-fold difference for iron, and other elements also exhibit large differences. (4) Discuss future directions including the need to assess labile mineral content. The extent of iron toxicity depends on localization of the iron within the cell and its biochemical form. (5) The olfactory bulb is one of the most iron sensitive regions of the brain. The authors could discuss how their results fit with the Fmr1KO mouse literature on olfactory bulb outcomes.

Reviewer #2: This study by Alam et al. carries out a comparison of elemental ion balance between male Fmr1 KO mice and WT mice of 3-5 months of age, sampling from several brain regions and somatic tissue. Given prior findings of ionic dyregulation in FXS literature, these results and approach to evaluate global ionomics is of interest to a broader FXS and ASD audience. The measurements across the brain regions and gut (ceacal and fecal) is novel, the analytical framework useful and the potential for multi domain comparisons intriguing.

Given the novelty of assessing applicability of 'ionomic' analysis to ASD and FXS literature, I would support publication, if the following concerns are addressed.

Broadly, the major concern are analytical discrepancies (which seem typographical errors) and unshared data which raise concerns. Moderate concerns are incorrect citations, toning downs conclusion the writing (especially) in the discussion which should be more precise rigorous.

Major Concern 1)

1. Although, the data availability statement states that data is available and relevant data within the manuscript, I could not find

1) average element concentrations for each sample.

2) the ALR-transformed values.

3) details about both the missing values (which samples, tissue and genotype), and tables of imputed numbers. This is especially critical for Zn as there were 7 missing values and Zn was one of the elements that was significantly dysregulated in a genotype specific manner.

The only available data set was the Mean SEM in Table S8 and S9 and here there a couple of glaring inconsistencies,

1. Table S9- large numbers. For example, striatum WT is 74.6 ± 0.006 µg/mg whereas KO is 0.067 ± 0.004 µg/mg. (Is this a typo? 0.074 would match their results). Similarly, fur calcium is transcribed as WT 39.2, KO 6.2. These numbers are unusually large.

2. Table S8, if derived from S9 (by normalizing to Fv), do not reflect these proportions.

The results in the table S8, for most parts match the conclusions. However, none of the mean difference findings reach significance when tested from Table S8 values (since the test were on ALR transformed values). Without the availability of ALR transformed values, which is missing, these results cannot be verified.

Methodological concerns.

Study design:

1. Please expand on the breeding strategy (Hom x Hom, Hom x WT) and housing information (were mice single or grouped housed). Gut microbiome would normalize if grouped housed and cage effects would need to be considered.

2. Please state in the methods that all samples are from the same individual (if this is the case)

If samples are from within an individual mouse, it is unclear why the authors did not model

this into their analysis. The MANOVA pools all observations together, but those observations are not truly independent, violating the independence assumption. A multivariate mixed model would have been more appropriate. If the authors did try this, and did not have sufficient power, this should be acknowledged in the results.

3. The authors missed an opportunity to compare within individual, cross-tissue correlations (which would have been possible with a mixed model). This would have been a good comparison to have given the individual variabilities seen in Fmr1 KO mice.

4. The MANOVA's are multiple comparisons, and multi-measure corrections are absent.

5. Although, the authors do justify the use of male mice in the methods, sex differences (especially in behavior) have been observed, and would should be acknowledged as a caveat.

Tissue collection: The authors mention the collection of several regions, but it's unclear why these regions were excluded from the results. Similarly, the rationale for mixing anatomically diverse regions, with variable cellular composition was not explained.

1. I am surprised the authors did not evaluate serum levels. That would have been informative and complemented their other measurements. Especially, since the authors seem to be directly extracting tissue (with no ACSF or saline perfusions which would normalize ionic balances across mice), tissue specific dysregulation could be a reflection of circulatory changes.

2. For clarity, consider re-ordering the order of sample collection. I am assuming the fecal collection was done first, followed by brain, cecal and fur.

3. I may have missed it, but there is no records of ages of mice from which samples were collected. It is unclear if ionic compositions are consistent across age and if this was assessed.

Figures

Figure 1- It would be clearer if the genotype were identified by symbols and tissue by color. That would give a good sense of the genotype differences.

Figure 2- Maybe the authors could change the symbol of the entries, or state that the black dots indicate outliers. Otherwise it gets confusing.

Confusing statements or references:

1. Line 13- 'comprehensive' is an overclaim. The study is a good 'proof of principle' of assessing ionomics as a viable and informative approach in FXS. A comprehensive study would require a lot more statistical power and precision in tissue extraction.

2. Line 28- typo. Salcedo-Arellano et al., is 2020 not 2023.

3. Line 40 This argument is confusing and logic inverted.

1. The references they use are bulk RNAseq and proteomic studies. These do not track single molecular pathways but capture system wide cellular perturbations. The ionome would reflect altered cellular processing (especially brain ionome), and hence would be a good complement but not be a substitute to transcriptomic or proteomic approaches.

2. Donnard 2022 is a single cell RNAseq study, not a bulk RNAseq study.

3. Missing references. For the bulk RNAseq Jung et al., 2023 PMID: 38048343 would support their results.

4. For proteomics Tang et al., PMID 26307763 should also be cited.

4. Line 45 Fmr1 should be italicized.

5. Line 49: Stefani 2004 does not link FMRP to identity of transcripts. HIT-clips studies Darnell 2011 and Maurin 2018 would be more appropriate references. Similarly Zhou et al., 2025 is not a neuronal paper, but a paper about the role of FMRP in tumor microenvironment.

6. Line 79; location of the reference (Greenacre 2021) is confusing as it seems to imply the reference refers to elemental reorganization in FXS. Maybe the placement was meant to be before?

7. Line 228: '... indicated ionomic similarity between genotypes, although PMHTH and striatum did not overlap', are the authors talking about genotype or tissue type comparisons?

8. Line 237 (Kooy, 2003) The authors are conflating human animal model face-validity with variability in rodent models. A better reference for the latter is Kat 2022 (PMID: 35690123)

9. Line 239, variance in 'both' not 'either'

10. Line 245: "FXS pathologies may also be expected ..." ionic dysregulation and neural excitability have been observed repeatedly in FXS, across several papers as highlighted in the previous line. Secondly, the references Napoli 2016 is about Zn, which is not affected in the brain. Similarly, D’Antoni et al., 2024, does not link FXS to trace elements or metalloenzymes. There are several links of FXS to metalloproteases and ECM (especially MMP9 among others). Please modify.

11. Line 268, The sentence is confusing and is unclear what the authors are trying to link. They refer to zinc-binding motifs (maybe proteins with zinc-binding motifs) and FMRP-pathways? Secondly, Edbauer 2010 is not an appropriate reference since as it does not link Zn and FXS).

12. Line 289, I disagree with the authors assertion of ionomics as a reverse genetics lens, to provide mechanistic insights, especially in complex multi-cellular tissue such as the brain. The papers the authors cite are papers from homogenous tissue or cell lines, where perturbing genes and linking to elements is possible. However, recent studies with cell specific manipulations (Fmrp knockouts, FMRP reexpression, or RNA translatome studies) suggest cell specific roles of FMRP (across neurons, interneurons and glia). Unless the authors are suggesting cell specific ionome (with cell-sorting), global ionome signals will be hard to resolve to the cellular source (genomic 'haystacks' are now cellular 'haystacks'). At best, the current iteration of ionome would be as a phenotypic tool and its applicability to tissue specific ionomic profiling in identifying tissue-element disruptions I agree. It might also be possible to link behavioral deficits to fecal elemental compostion, would potentially enable biomarker discovery (which the authors state).

13. Line 302, similar to my above comment, integrating global ionome with global transcriptome, proteome screens to identify cellular mechanisms, especially with cell specific dysregulation, is challenging.

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Reviewer #1: Yes: Cara Westmark

Reviewer #2: No

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Loss of Fmr1 reorganizes the multi-elemental composition across tissues in Fragile X Syndrome mice

PONE-D-26-15087R1

Dear Dr. McCullagh,

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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Reviewers' comments:

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Reviewer #2: All comments have been addressed

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

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Reviewer #2: Yes

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Reviewer #2: Yes

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Reviewer #2: Yes

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Reviewer #2: Yes

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Reviewer #2: The authors have addressed all concerns admirably. Their analysis is rigorous, transparent and interpretation appropriate. I am happy to support publication.

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Reviewer #2: No

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