Integrated RNA-seq and scRNA-seq to explore the biological mechanisms of mitophagy-related genes in ulcerative colitis

PLOS ONE

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2. Thank you for stating the following financial disclosure:

“The National Natural Science Foundation of China (Grant number [81960868]) and the Yunnan Provincial Science and Technology Department, funded by the Applied Basic Research Joint SpecialFunds of Yunnan University of Chinese Medicine (Grant numbers [202001AZ070001-051] and [202101AZ070001-013]), High-level TCM talents: (reserve talents) project of Yunnan (2021. No. 1), Xingdian Talent Support Program-Youth Talent Special Project (2023. No. 166), Yunnan Provincial Science and Technology Department - Yunnan University of Traditional Chinese Medicine Joint special Project (Grant numbers [202201AG070192]), Applied Basic Research Key Project of Yunnan (202501AS070155), Yunnan Applied Basic Research Project--Joint Project of Traditional Chinese Medicine and Surface(202001AZ070001-051).”

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Additional Editor Comments:

Please revise all reviewers' comments and respond to them accordingly. In addition, please be sure to describe if you applied p-adjustment for multiple comparisons (for example, for generating the volcano plot). If so, please include the strategy applied (BH, FDR, Others).

According to the figure shown in the Nomogram, there is no clear reference to the risk related to these markers. Perhaps it is relevant to test the MRG-based score in combination with other clinical profiles instead of combining all relevant genes? How can it be applied to the routine? In the current Figure 6D, it is hard to see the contribution of each gene, particularly in the cases of PPARGC1A and MIF. Please revise it.

Please describe in high-level details the methods followed to annotate potential cell types in the single-cell dataset. How did you define which cell types could be present in your sample? Following the previous comment, I suggest showing a dotplot with relevant genes from Figure 9, organized by cell type and donor type (UC or control).

Finally, please add statistical comparisons in Figure 10C and attach the melting curves for SYBR-amplified regions.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

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

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: In this manuscript, Ma et al. identified 13 key genes involved in ulcerative colitis through bioinformatic analysis of publicly available next-generation DNA sequencing raw data. Furthermore, the authors validated their observations on a bench using a mouse model of ulcerative colitis. The strengths of the study design are as follows: 1) Gene prioritization was performed using RNA-seq data from human tissues, narrowing down to hub and key genes; 2) single-cell RNA-seq data were used; and 3) expression changes in mice were confirmed by RT-qPCR and Western blotting. However, mechanistic verification is lacking in research design. In other words, experiments such as using the identified gene knock-out mice, knock-down experiment using siRNA, or experiments using inhibitors of the identified protein. However, the reviewer has never requested additional experiments for any review. Such so-called "Reviewer Experiments" are, in fact, not very meaningful in academic papers (Nature 2011;472:391). The authors should construct their logic and draw conclusions based solely on the data presented. Furthermore, most PLOS ONE values represent the validity and robustness of the methodology. Therefore, reviewers should point out the following aspects concerning the validity of the methods rather than the significance of the author's research results.

Overall, the proposed methodology is reasonable. However, as the authors themselves indicate in the title, the most controversial point is the integration of RNA-seq and scRNA-seq results as well as subsequent gene prioritization. There is still no established consensus on this methodology, with various reports and debates. The authors should discuss this issue in the Discussion section.

Reviewer #2: Ma et al aims to decipher the mechanism of mitophagy related genes in ulcerative colitis. Overall, it is a well designed, executed and validated work. Multi-modal tools were utilized to expand spectrum of evidence representation.

Here are some points to note:

1. It is understandable that the diagnostic model developed by the authors is still in the early stage, given that more datasets have to be used for cross-validation. Could the authors deliberate more of the potential use, as well as the sensitivity and specificity of limitation of detection?

2. Following point 1, what kind of human samples to be needed for such a test? Turnaround duration from sample to data, and to diagnostic result? Estimated cost per test? Benefit population figures from such a test of UC patients?

Reviewer #3: Dear Authors,

I think that this manuscript could benefit from a substantial revision - because of the points below, the main flow of the argument is made difficult to follow.

Main points:

1. References in the text to figures and tables are sometimes incorrect and confused, making the flow of the text difficult to follow. In particular:

- Line 248 - Supplementary Figure S1 is not a flowchart of the study, but bar plots of gene ontology analyses

- Line 257 states 21665 DEGs, but there are only 1802 shown in figure 2B (this might be a misreading on my part) - and also the reference to the comparison between MRGs and DEGs should refer to figure 2B rather than 2A

- Line 311-317 - the genes in figure S3A are ALDH6A1, ACADSB, ALDH2, PC, ALDH1A1, and ACSL1 but the text around these lines does not refer to these, but to other datasets

- Lines 325-335 refer to cluster analysis for the genes, but this is not labelled on the plot in 4B

- Line 343/figure 4G - the figure contains genes not written in the text here.

- Line 317 - Table S5 in the text is actually Table S6

- Line 323 - Table S6 in the text is actually Table S7

- Line 391 - Table S7 in the text is actually Table S8

- Line 408-409 mentioned 15000 variable genes in the scRNA analysis, but the figure 7B shows 2000 variable genes

- Lines 429-430 have the labels for figures 8B and 8C swapped in the text

- Also Figure 8D is referred to as a heat map, but it is a plot of the expression of seven chosen genes shown on the UMAP

2. Supplementary Figure S1 and Supplementary Table S5 both report gene ontology analysis results but are not referred to in the text, in the methods, results or the discussion. If this analysis was performed on this data and is to be presented in the manuscript, then it should be reported on and discussed in the context of MRGs and/or ulcerative colitis.

3. Figure 6D shows the nomogram for the predictor - I'm not certain what the point of this diagram is in the manuscript. What if the ranges of expression of these genes are outside the values on the scales? Do we take the minimum or the maximum of the point score? How does the linear predictor and the risk get calculated from the values here?

4. The main figures are low resolution (as they currently stand, maybe a high resolution version is available?). This particularly affects figure 9A and 9B where the gene labels are difficult to read because of resolution and the compression artefacts.

5. The materials and methods appear to consistently refer to raw p-values. It it clear from some of the later text in the results that some of these have been adjusted for multiple comparisons - this is not mentioned in the methods section and should be made clear here.

Some more specific points to make:

1. Figure 1C - PC2 is shown as explaining 'a5.8%' of the variance.

2. In figure 2C, what is the score that is plotted in the heatmap?

3. Figure 2D has the word 'adataset' (possible typo) in the title. There is also no label on the red-white-blue scale

4. Figure 5B/line 358-359: place the labels on figure 5B in the order they are in the text, or write the text in the same order as the labels on Figure 5B

5. Figure 6C - this would be better shown as log-HRs on the x axis because of the scales on the x axis. This would make the difference between the calculated CIs and the HR 0 line clearer to see

6. Figure 10A - label on the colon images which is the diseased and which is the normal.

7. Figure 11 - order the datastet by placing the significant genes first: also place the gene name as a title on each pair of bars for the bar plot

8. Figure 12A - What are the two bands that appear on the blot for the MIF protein? Which one has been taken as the one to quantify?

9. Figure 12B - this would benefit from the individual blot quantifications in the two conditions shown on each bar - the blot images show significant variation (eg NAMPT in the NC condition, and the top MIF band in the UC condition). It is also not mentioned what the intensity was quantified relative to.

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Reviewer #1: Yes: Shigekazu SuginoShigekazu SuginoShigekazu SuginoShigekazu Sugino

Reviewer #2: No

Reviewer #3: No

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Dear Dr. Qi,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jan 31 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.

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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

Reviewer #4: (No Response)

Reviewer #5: (No Response)

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

Reviewer #1: (No Response)

Reviewer #2: Yes

Reviewer #4: Yes

Reviewer #5: No

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

Reviewer #1: (No Response)

Reviewer #2: Yes

Reviewer #4: Yes

Reviewer #5: No

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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 Response)

Reviewer #2: Yes

Reviewer #4: Yes

Reviewer #5: No

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

Reviewer #1: (No Response)

Reviewer #2: Yes

Reviewer #4: Yes

Reviewer #5: No

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Reviewer #1: Well done! I (reviewer 1) have checked your improvement in the revised manuscript. In line 631, I have found a typo: a double period.

Reviewer #2: Please consider including authors' response to my point 2 comment into the Discussions part. Thanks.

Reviewer #4: The authors first screened differentially expressed genes and key modules via bulk RNA-seq, then employed scRNA-seq for cell type localization and functional annotation. This common “global-to-local” analytical approach facilitates revealing cellular heterogeneity while preserving tissue-wide expression patterns. Similar integration strategies have been applied in high-impact papers in recent years, particularly in disease mechanism studies, providing more refined cell-level insights. Key genes were validated in animal models via qPCR and WB, enhancing the credibility of findings. Clinically, four public transcriptomic datasets and one single-cell dataset were utilized, ensuring substantial sample size, with experimental validation through animal models. The constructed gene diagnostic model achieved an AUC of 0.974, demonstrating strong discriminatory power and potential clinical translational value. As an immune-mediated inflammatory disease, UC exhibits significant correlations between key genes and M1 macrophages, activated T cells, and others identified via CIBERSORT analysis, consistent with its immunopathological characteristics. Some key genes—such as BNIP3, NAMPT, and MIF—have established links to UC pathogenesis through established research in pathways including inflammation, apoptosis, and metabolism.

Main issues:

No standardized workflow currently exists for integrating bulk and scRNA-seq data, with differing methodologies potentially yielding inconsistent results. Bulk data primarily originate from public databases (often tissue samples), while scRNA-seq data may derive from diverse platforms or sample types, introducing batch effects and platform biases. Relying solely on bulk data for gene selection risks overlooking genes highly expressed in specific cell subpopulations but exhibiting weak overall signals. Single-cell annotation relies on known marker genes; incomplete labeling or cell state transitions may introduce annotation errors. These issues warrant close attention from authors to identify and reduce potential biases.

Limitations and discussion:

All data originate from colon tissue, neglecting the clinical potential of non-invasive samples like blood or stool, resulting in limited sample diversity. Additionally, the diagnostic model was validated only within internal data, requiring external cohorts or multicenter data to further validate its generalizability. While key genes were found to correlate with immune cell infiltration, subsequent functional experiments did not elucidate specific regulatory mechanisms. The dataset lacks detailed information on clinical staging, medication history, and disease activity, limiting the model's clinical stratification capability.

Reviewer #5: Thank you for the opportunity to review your manuscript. While I see this is a second submission (a revision), I think there are few overarching areas that still require attention.

The first is that the introduction needs some re-framing and could be more streamlined. Most notably is that mitophagy needs to be clearly defined. The role of mitophagy in IBD (or what is known to date) also needs to be more explicit (e.g. lines 54-61 seem contradictory to lines 61-63, and lines 63-65 is vague and requires a reference).

Second, I have a few concerns/questions regarding the methodological approach and related results:

1) The mitophagy related genes (MRGs), were empirically picked from an online database (GeneCards), and the ones that overlapped with your DEGs were picked for further analysis – but overall there was no evidence to support these 722 genes over any other grouping of genes. An enrichment (hypergeometric) test (from 21,000 genes with 1,800 passing p<0.05, and then looking for overlap with the 722 empirically derived list) indicates that one would expect ~>=61 genes overlapping by chance alone. This exceeds the n=50 gene overlap. Furthermore, it looks as though it was an approx. 50/50 split between those 50 MRGs with increased expression and decreased expression in UC vs control. Overall, this leads me to believe that the overall expression pattern or biology of these transcripts is not that relevant to the GEO samples used in this study. Can the authors please explain why the above 50 MRGs might still be of biological relevance in IBD? How many of the 50 MRGs had an FDR>0.05 from the initial comparison (UC vs control) above?

2) This is an inherent issue in using retrospective, publicly available databases (like GEO). But no information is provided on the clinical status/phenotypes of the patients/samples used, e.g. remission vs. active disease, Mayo or Montreal scores (or otherwise). Thus it is impossible to relate any of the molecular findings back to the clinical phenotype. Subsequently, related to the model that was developed, I think any statement claiming “diagnostic” capabilities is an overstatement, thus this needs to be re-worded. Importantly, this model was not tested against relevant differentials (e.g. Crohn’s colitis). The AUC of 0.97 is concerning for overfitting, and a more likely explanation is that the model is measuring inflammation (this makes sense considering the correlation with inflammatory markers/cells), rather any independent process related to mitophagy or mitophagy as causative factor in IBD.

3) the paper discusses integrating bulk RNA and single cell RNA seq, but some of the GEO data was Affymetrix microarray data, was it not? Please clarify the input technologies and any relevant clinical data (see comments above), and adjust the text as appreciate.

4) PCR, Western blot, or other assays are not validation. Validation would be taking an independent cohort (a test set) and seeing how the MRGs perform in that cohort, using the same technology (e.g. Affy microarrays, RNA seq etc) as before. DSS colitis is not UC, differences are expected, but should be explored/explained. I actually think the in vivo model, PCR and Western blot sections weaken the paper, and more emphasis should be made on refining the other sections. But I will leave this up to the authors and AE/EI.

5) the scRNA seq data is confusing to me. Genes that differentiate cell types from one another are highlighted, but it seems like immunoglobulin genes are highlighted in T cells and other non-lymphocytes. I assume this is because these genes are so highly expressed in B cells, and nonexistent in the other cells. This requires further clarification though why you are highlighting this – the lack of immunoglobulin doesn’t define any particular cell type other than tell us we are looking at something that is probably not from a B cell lineage. (but the direction of these genes/transcripts is not clear based on the text.)

6) Line 89 – what was the inclusion/exclusion criteria? What/how were samples deemed irrelevant?

7) Line 101 – how was epigenetics involved in the GeneCards search? What type of epigenetics?

Last, the paper needs to be checked for minor typos, e.g. line 22 – should be a period, not a comma; Line 238 – space missing between “andP”; Line 257 – space missing between “inbatch”.

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Dear Dr. Qi,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by May 07 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.

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Academic Editor

PLOS One

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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

Reviewer #4: All comments have been addressed

Reviewer #5: All comments have been addressed

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

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #4: Yes

Reviewer #5: Partly

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

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #4: Yes

Reviewer #5: 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: Yes

Reviewer #2: Yes

Reviewer #4: Yes

Reviewer #5: 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

Reviewer #4: Yes

Reviewer #5: Yes

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Reviewer #1: The authors improved the sentences the reviewer pointed out. I believe that this research will be published in near future.

Reviewer #2: All good for me. All the comments from me previously have been properly addressed from the authors.

Reviewer #4: The authors have satisfactorily addressed my previous concerns regarding the integration of bulk and single-cell RNA-seq data. The revised manuscript now clearly explains the rationale behind their "global-to-local" analytical strategy and includes a dedicated discussion of its advantages and limitations, which enhances the methodological transparency.

I have only one minor suggestion: there is some repetition in the Discussion section regarding the integration strategy. Streamlining this would improve conciseness.

Overall, the authors have responded adequately to my comments, and the manuscript is now suitable for publication with minor revisions.

Reviewer #5: Thank you for addressing my comments and questions, and making the appropriate changes to the text. The manuscript is now quite long, I estimat approx >11-12,000 words (from Abstract to end of Discussion), and the discussion is approximately 5,000 words itself? (just a rough estimate from looking at the text in word). I think most traditional scientific journals would request that the word count be significantly reduced. But I'll leave this decision up to the journal/Editors.

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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: Shigekazu SuginoShigekazu SuginoShigekazu SuginoShigekazu Sugino

Reviewer #2: No

Reviewer #4: No

Reviewer #5: No

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Integrated RNA-seq and scRNA-seq to explore the biological mechanisms of mitophagy-related genes in ulcerative colitis

PONE-D-25-44869R3

Dear Dr. Qi,

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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Kind regards,

Alexis G. Murillo Carrasco

Academic Editor

PLOS One

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