Regulation of a Metabolic Gene Signature in Response to Respiratory Viruses and Type I Interferon Signaling

Round 1

Reviewer 1 Report (Previous Reviewer 1)

Comments and Suggestions for Authors

N/A

Comments on the Quality of English Language

Extensive editing of English language required especially the grammar side.

Author Response

Thank you for your time and comments and the English editing service on the grammar has been done.

Reviewer 2 Report (New Reviewer)

Comments and Suggestions for Authors

Regulation of a metabolic gene signature in response to respiratory viruses and type I interferon signaling

 

This manuscript identifies certain metabolic genes that are upregulated during respiratory virus infections. The author attempts to do this by performing a bioinformatic analysis on transcriptomic data from uninfected and infected samples of different cell lines. Upon exploring, along with type-I IFN and other pro-inflammatory cytokines, metabolic gene products like IDO1, CH25H, NAMPT, EIF2AK2 and SAMHD1 were also seen to be upregulated. Even though the correlation seems to be sound, the manuscript suffers  from several drawbacks that needs to be either addressed by rewording some of the sentences or performing additional analyses. The criticisms of this manuscript are listed below.

Major drawbacks

1)      Virus infections upregulate IFN response and pro inflammatory cytokine expressions at varied time points, depending on the virus dosage. Hence along with the time point, it is mandatory to mention the MOI of infection. For example, some of the IFN and ISGs listed, atleast during  SARS-CoV-2 listed in Calu3 and A549-ACE3 cells are barely 2 fold upregulated. However, it is common knowledge that these are upregulated may more than that depending on the MOI and time of infection. (at 0.1 MOI, it takes atleast 36-48 hours post infection to reach peak titers and max ISG production, but that can be achieved betwe 24-36 hours in case of 1MOI infection).

2)      Since this manuscript talks about the upregulation of IFN-I, along with IFNB1, it would prudent to also include one or two IFNA genes during this analysis. IFNA is almost the most prevalent type of IFN in IFN-I response that gets upregulated. This will significantly enhance the quality of this manuscript.

3)      IFN and ISG responses are more enhanced in vivo than in vitro. Given the global impact of metabolic gene signatures, if possible, it will be great to discuss the expression analysis of these genes along with ISGs in animal models in greater detail than mentioned. The expression levels of some of these metabolic genes in specifically epithelial cells are also not completely known. So, highlighting this mild upregulation, to have a significant biological impact will improve the credibility of this paper.

4)      The correlation between the expression of these metabolic genes and IFN-I is still unclear. Only in some cases are they connected to STAT expression levels and IRF9 levels. Hence, instead of saying that these metabolic expression changes are “mediated” by IFN-I expression, saying that these metabolic gene expression changes were observed “concurrently” will make more sense.    

MINOR CONCERNS

1)      In the title, “A metabolic gene signature” can be changed to “metabolic gene signature”

2)      NAMPT and SAMHD1 are implicated in ADP-ribosylation as it determined the NAD+ turnover levels. Since there is increasing literature studying the effect of ADP-ribosylation on virus infections, this should be atleast mentioned in the discussion.

3)      Metabolome changes or atleast their implication during long covid can be discussed in a sentence or two as I feel it will improve the quality of this manuscript.     

  

Author Response

Response to Reviewer #2. I thank the reviewer for comments. Reviewer specific comments and my responses are in bold.

• Virus infections upregulate IFN response and pro inflammatory cytokine expressions at varied time points, depending on the virus dosage. Hence along with the time point, it is mandatory to mention the MOI of infection. For example, some of the IFN and ISGs listed, atleast during  SARS-CoV-2 listed in Calu3 and A549-ACE3 cells are barely 2 fold upregulated. However, it is common knowledge that these are upregulated may more than that depending on the MOI and time of infection. (at 0.1 MOI, it takes atleast 36-48 hours post infection to reach peak titers and max ISG production, but that can be achieved betwe 24-36 hours in case of 1MOI infection).

Response: Virus dose and time responses were optimized in the original publications and also stated in the GEO datasets. This is a bioinformatic study of gene expression data by other investigators. References to original data and accession numbers were provided in the methods section.

• Since this manuscript talks about the upregulation of IFN-I, along with IFNB1, it would prudent to also include one or two IFNA genes during this analysis. IFNA is almost the most prevalent type of IFN in IFN-I response that gets upregulated. This will significantly enhance the quality of this manuscript.

 Response: The choice of IFN-a versus IFN-b  in the data analysis of gene expression was made on the observation that IFN-b is encoded by a single gene (IFNB1), whereas IFN-a has multiple isotypes (IFNA1-14). There is no consensus on which isotype of IFNA locus is important for biological responses. Additionally, IFN-b is more potent than IFN-a in gene expression analysis (ref: Der SD, Zhou A, Williams BR, Silverman RH. Identification of genes differentially regulated by interferon alpha, beta, or gamma using oligonucleotide arrays. Proc Natl Acad Sci U S A. 1998 Dec 22;95(26):15623-8.). Both IFN-a and IFN-b (IFN a/b) signaling through the common receptor were important for metabolic regulation, as emphasized in the graphic abstract.

 

3. IFN and ISG responses are more enhanced in vivothan in vitro. Given the global impact of metabolic gene signatures, if possible, it will be great to discuss the expression analysis of these genes along with ISGs in animal models in greater detail than mentioned. The expression levels of some of these metabolic genes in specifically epithelial cells are also not completely known. So, highlighting this mild upregulation, to have a significant biological impact will improve the credibility of this paper.

Response : There is no consensus on fold-change importance in gene regulation. In many cases, a 2-fold regulation of a regulatory gene may have important biological effects. The topic was discussed (ref: Wiebe DS, Omelyanchuk NA, Mukhin AM, Grosse I, Lashin SA, Zemlyanskaya EV, Mironova VV. Fold-Change-Specific Enrichment Analysis (FSEA): Quantification of Transcriptional Response Magnitude for Functional Gene Groups. Genes (Basel). 2020 Apr 17;11(4):434).

Classification of gene expression as weak, moderate, or high is inherently arbitrary.

• The correlation between the expression of these metabolic genes and IFN-I is still unclear. Only in some cases are they connected to STAT expression levels and IRF9 levels. Hence, instead of saying that these metabolic expression changes are “mediated” by IFN-I expression, saying that these metabolic gene expression changes were observed “concurrently” will make more sense.    

Response: Correlation is a scientific  and appropriate word, according to my scientific colleagues.  Their point is that correlation can be causal or not, and it can indicate any type of association. English language service will edit the final version of the manuscript.

MINOR CONCERNS

• In the title, “A metabolic gene signature” can be changed to “metabolic gene signature”

Response: English language service will edit the final accepted manuscript.

• NAMPT and SAMHD1 are implicated in ADP-ribosylation as it determined the NAD+ turnover levels. Since there is increasing literature studying the effect of ADP-ribosylation on virus infections, this should be atleast mentioned in the discussion.

Response: The role of ADP ribosylation and its role in antiviral interferon response is a new area of investigation that needs further confirmation. Recent study by Guo et al. identified PARP11  to be important for ADP-ribosylation and antivral response (Guo T, Zuo Y,  et al.Qian L, Liu J, Yuan Y, Xu K, Miao Y, Feng Q, Chen X, Jin L, Zhang L, Dong C, Xiong S, Zheng H. ADP-ribosyltransferase PARP11 modulates the interferon antiviral response by mono-ADP-ribosylating the ubiquitin E3 ligase β-TrCP. Nat Microbiol. 2019 Nov;4(11):1872-1884). Furthermore, PubMed (NCBI) search of ADP ribosylation and antiviral response with NAMPT or SAMHD1 terms retrieved no documents.

• Metabolome changes or atleast their implication during long covid can be discussed in a sentence or two as I feel it will improve the quality of this manuscript.  

Response: Long COVID is a new and emerging area of investigation, with potential significance for cell types such as microglia, astrocytes, as well as neurons. (Ref: Tan PH, Ji J, Hsing CH, Tan R, Ji RR. Emerging Roles of Type-I Interferons in Neuroinflammation, Neurological Diseases, and Long-Haul COVID. Int J Mol Sci. 2022 Nov 19;23(22):14394). The role of lung epithelial cells in long COVID remains to be investigated.

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Introduction:

The introduction presents a comprehensive overview of Type I interferons (IFNs) and their pivotal role in the host immune response against respiratory viruses, specifically emphasizing their involvement in combating viruses like Respiratory Syncytial Virus (RSV), Influenza, and Coronaviruses such as SARS-CoV-2. It delves into the significant impact of SARS-CoV-2, leading to the global pandemic of severe coronavirus disease 19 (COVID-19), underlining the importance of understanding host-virus interactions and immune responses.

However, the introduction appears to be overly detailed, resulting in a lack of focus and clarity. Here are some points and suggestions for improvement:

·       Streamlining the introduction will enhance readability. Focus on core concepts related to IFNs, their role in host defense against respiratory viruses, and recent advancements in understanding these interactions. Eliminate overly specific details that might overwhelm readers.

·       Consider breaking down the information into more digestible segments or paragraphs. Create clear subsections or headers to delineate different aspects of IFN involvement in viral infections, such as gene expression profiling, metabolic studies, and signalling pathways.

·       Ensure each piece of information directly connects to the central theme of Type I interferons and their impact on host-virus interactions. Remove tangential details that do not directly contribute to the focus of the study.

·       While comprehensive, the introduction might overwhelm readers with an excess of technical details. Aim for a balance between providing relevant background information and maintaining readability for a broader audience.

·       Clearly state the objectives of the study at the end of the introduction to provide a roadmap for readers regarding what the research aims to achieve.

·       Enhance the transition between sentences and paragraphs for smoother readability. Connect ideas logically to maintain the flow of information.

Materials and methods:

The Materials and Methods section provides a comprehensive overview of the sources and databases used for gene expression analysis and bioinformatics. However, there are areas where the section could be improved

·       The section lacks clear structure and organization. Consider breaking down the information into subsections based on the types of datasets used (e.g., human lung cell lines, COVID-19 patient data, mouse models), making it easier for readers to follow the methodology.

·       While mentioning the datasets and databases is essential, the section lacks specific details regarding the methodologies used within each dataset. For instance, describe the techniques employed to extract and analyze the gene expression data from each dataset, providing clarity on how the data was processed, normalized, and validated.

·       Include a brief explanation or rationale behind the choice of each dataset or database. Explain why these particular datasets were selected, how they align with the research objectives, and what specific information was extracted from each resource.

·       While mentioning the software tools used for analysis, provide a brief explanation of each tool's functionalities and how they were applied in the analysis. Specify the parameters or criteria used for data interpretation, clustering, and pathway analysis.

·       When mentioning the retrieval of gene-specific information from bioinformatics websites like MGI and Genecards, consider briefly outlining the protocols used to extract this information. Highlight any criteria used for data filtration or validation

·       Emphasize the reproducibility of the methods employed for the benefit of future research.

·       Discuss how the datasets were integrated, considering any limitations or biases associated with combining data from diverse sources. Address any potential shortcomings in the chosen datasets or methodologies.

·       Briefly mention any quality control measures taken to ensure the reliability and validity of the extracted data from the various databases and datasets.

 

Results:

The section provides a detailed account of metabolic gene expression profiles in response to respiratory viruses and type I interferon signalling. However, several aspects could benefit from refinement and enhancement:

·       The section is extensive and lacks clear subsections, making it challenging for readers to navigate. Organizing it into distinct sections based on virus types or experimental methods could enhance readability and understanding.

·       The objectives and hypotheses guiding the research could be explicitly stated at the beginning of each subsection to provide a clearer roadmap for readers.

·       While there is a plethora of information provided, the methodology or techniques used to derive these results need more explicit explanation. Details about the analysis pipelines, statistical methods, and validation strategies should be included to ensure reproducibility and validity of findings.

·       Introducing each subsection with a brief background and context for the reader can aid comprehension. This could include why specific viruses or models were chosen and how they relate to the overarching research aims.

·       Address the limitations of each experimental approach, dataset, or model used. Acknowledging these constraints provides a balanced perspective on the findings.

·       While each subsection discusses specific viruses or stimuli, tying these results together or providing a brief recap of overarching trends across different viruses could enhance the section's coherence.

·       Highlighting key findings or novel discoveries within each subsection would draw attention to the study's main contributions.

·       Introducing comparative elements between different viruses or stimuli could elucidate unique responses and similarities among the various scenarios studied.

·       Although mentioned briefly, emphasizing the potential translational or clinical implications of these findings would add significance to the study's broader implications.

·        

 

Discussion:

The discussion provides valuable insights into the role of interferon-stimulated metabolic gene signatures in response to respiratory viruses. However, there are some areas that can be refined and expanded upon:

·       The main contributions of the study could be explicitly stated at the beginning to provide a clear overview for the reader.

·       Align each paragraph or section more explicitly with the study's objectives. This helps in maintaining focus and coherence in discussing findings.

·       While referencing previous studies and their findings, it's essential to discuss how these findings align or diverge from the current study's results. This adds depth and context to the discussion.

·       Instead of listing findings sequentially, integrate them into thematic sections or themes to establish connections between different aspects of the study.

·       Elaborate more on the clinical implications of the findings. How can the understanding of these metabolic gene signatures influence diagnostic or therapeutic approaches

·       If there are conflicting reports or divergent opinions in the field, acknowledging these discrepancies and discussing potential reasons for differences can strengthen the discussion.

·       While mentioning the involvement of various enzymes and pathways, provide more detailed explanations of how these enzymes function and interact within the context of the immune response to viral infections.

·       Expand the discussion to encompass broader implications beyond the immediate findings. What are the potential future directions or further investigations warranted by these results?

·       Summarize the key findings and their significance in a concise manner at the end of the discussion section, reinforcing their relevance to the study's objectives.

 

Finally, I would recommend the authors to read this manuscript:

https://www.sciencedirect.com/science/article/pii/S0890850822000317

 

Comments on the Quality of English Language

 Moderate editing of English language required

Author Response

Reviewer #1

I thank the reviewers for their valuable time and thoughtful suggestions. After 30-years of research, I have made the decision to retire. This is my last research paper. I have made several corrections to the manuscript (in bold and indicated by line numbers below).

Response to reviewer #1

1. Introduction section
The introduction presents a comprehensive overview of Type I interferons (IFNs) and their pivotal role in the host immune response against respiratory viruses, specifically emphasizing their involvement in combating viruses like Respiratory Syncytial Virus (RSV), Influenza, and Coronaviruses such as SARS-CoV-2. It delves into the significant impact of SARS-CoV-2, leading to the global pandemic of severe coronavirus disease 19 (COVID-19), underlining the importance of understanding host-virus interactions and immune responses.
However, the introduction appears to be overly detailed, resulting in a lack of focus and clarity. Here are some points and suggestions for improvement: Streamlining the introduction will enhance readability. Focus on core concepts related to IFNs, their role in host defense against respiratory viruses, and recent advancements in understanding these interactions. Eliminate overly specific details that might overwhelm readers. Consider breaking down the information into more digestible segments or paragraphs. Create clear subsections or headers to delineate different aspects of IFN involvement in viral infections, such as gene expression profiling, metabolic studies, and signalling pathways. While comprehensive, the introduction might overwhelm readers with an excess of technical details. Aim for a balance between providing relevant background information and maintaining readability for a broader audience.

Response

I completely agree with the reviewer. However, these aspects of type I interferon signaling and metabolism in response to respiratory viruses were covered in reviews mentioned in references section such as

1. Kohlmeier JE, Woodland DL. Immunity to respiratory viruses. Annu Rev Immunol. 2009;27:61-82.

2. Stark GR, Kerr IM, Williams BR, Silverman RH, Schreiber RD. How cells respond to interferons. Annu Rev Biochem. 1998;67:227-264.

3. Kerr CH, Skinnider MA, Andrews DDT, Madero AM, Chan QWT, Stacey RG, Stoynov N, Jan E, Foster LJ. Dynamic rewiring of the human interactome by interferon signaling. Genome Biol. 2020; 21(1):140

4. Raniga, K.; Liang, C. Interferons: Reprogramming the Metabolic Network against Viral Infection. Viruses 2018; 10:36.

Materials and methods:
The Materials and Methods section provides a comprehensive overview of the sources and databases used for gene expression analysis and bioinformatics. However, there are areas where the section could be improved. The section lacks clear structure and organization. Consider breaking down the information into subsections based on the types of datasets used (e.g., human lung cell lines, COVID-19 patient data, mouse models), making it easier for readers to follow the methodology.

··
1. While mentioning the software tools used for analysis, provide a brief explanation of each tool's functionalities and how they were applied in the analysis. Specify the parameters or criteria used for data interpretation, clustering, and pathway analysis.

Response

Data analysis tools such as Cluster analysis using Heatmapper and pathway analysis using Metascape were discussed extensively in the original papers by the authors (References provided in the manuscript ). Furthermore websites set up by the authors (www.heatmapper.ca and www.metascape.org) contain methodologies and examples.

Standard bioinformatic methods were used. References were given (line 113).

·
2. When mentioning the retrieval of gene-specific information from bioinformatics websites like MGI and Genecards, consider briefly outlining the protocols used to extract this information. Highlight any criteria used for data filtration or validation

Response
I used MGI and Gencards databases to check for general information on mouse and human

genes. These are more reliable and curated by scientists than Wikipedia edited by general audience.

3. Emphasize the reproducibility of the methods employed for the benefit of future ·Briefly mention any quality control measures taken to ensure the reliability and validity of the extracted data from the various databases and datasets.

Response

Corresponding mock and treatment and multiple datasets were used. Outliers of expression were excluded in the data analysis (methods line 128)

Results:
The section provides a detailed account of metabolic gene expression profiles in response to respiratory viruses and type I interferon signalling. However, several aspects could benefit from refinement and enhancement:

· 1.The section is extensive and lacks clear subsections, making it challenging for readers to navigate. Organizing it into distinct sections based on virus types or experimental methods could enhance readability and understanding.

Response

Results section was organizes according to the virus type such as RSV, HPIV3, Influenza and, Coronaviruses. This is followed by the requirements of double- stranded RNA (a viral intermediate mimicked by Poly IC), and double-stranded RNA serine kinase EIF2AK2 for the metabolic gene signature induction. Furthermore, direct type I interferon treatment can induce the metabolic gene signature in the lung epithelial cells. This was schematically shown in the graphical abstract. LPS and UPR are inflammatory and stress-responsive pathways implicated in respiratory virus and secondary bacterial infections and acute lung injury.

2. The objectives and hypotheses guiding the research could be explicitly stated at the beginning of each subsection to provide a clearer roadmap for readers.

Response

The subheadings of the results section state the objectives- induction of the metabolic gene signature by RSV, HPIV3, Influenza viruses followed by mechanisms (PolyIC, PKR, type I interferon, and protein interaction network), Involvement in LPS, UPR, and COVID-19 etc.

·

· ·

·

3. Although mentioned briefly, emphasizing the potential translational or clinical implications of these findings would add significance to the study's broader implications.

Response
This point was addressed in the discussion section.

Discussion:
The discussion provides valuable insights into the role of interferon-stimulated metabolic gene signatures in response to respiratory viruses. However, there are some areas that can be refined and expanded upon:

·
1.The main contributions of the study could be explicitly stated at the beginning to

provide a clear overview for the reader.

Response
Added to discussion

In this study, transcriptome profiling revealed a common metabolic gene signature mediated by type I interferon signaling in the host response to several respiratory viruses. Identification of the same metabolic signature was observed in response to double-stranded RNA, bacterial LPS, and UPR. This metabolic module is part of a protein interaction network with transcription factors of type I interferon signaling. Furthermore, EIF2AK2/PKR was identified as a key node in the metabolic module as suggested by the attenuation of the metabolic gene signature in Eif2ak2 KO mice in response to RSV.

·

· ·

· ·

,

·

Added at Line 507

A graphical abstract was added to summarize the schematic view of the paper and its findings.

2. Align each paragraph or section more explicitly with the study's objectives. This helps in maintaining focus and coherence in discussing findings. While referencing previous studies and their findings, it's essential to discuss how these findings align or diverge from the current study's results. This adds depth and context to the discussion.

Instead of listing findings sequentially, integrate them into thematic sections or themes to establish connections between different aspects of the study.

Thanks for the helpful suggestions and I reorganized the manuscript discussion accordingly.

3. Elaborate more on the clinical implications of the findings. How can the understanding of these metabolic gene signatures influence diagnostic or therapeutic approaches Expand the discussion to encompass broader implications beyond the immediate findings. What are the potential future directions or further investigations warranted by these results?

Response
Added to discussion
Identification of a metabolic gene signature in the lung epithelial response to respiratory

viruses indicates that a comparative transcriptome analysis for metabolic gene signatures in a variety of lung diseases such as asthma, acute respiratory distress syndrome (ARDS), and septic shock is warranted. Further investigations are required to test the role of EIF2AK2/PKR inhibitors in response to respiratory viruses and inflammatory diseases.

(line 553).

4. While mentioning the involvement of various enzymes and pathways, provide more detailed explanations of how these enzymes function and interact within the context of the immune response to viral infections. If there are conflicting reports or divergent opinions in the field, acknowledging these discrepancies and discussing potential reasons for differences can strengthen the discussion.

Response
Limitations of the study added to discussion

A major limitation of this study is the lack of direct experimental evidence for a particular metabolic state induced by type I interferon in cells. However, the activation of several transcription factors known to be involved in redox regulation, such as NF-kB, Stat1, Stat3, p53, ATF4, and NRF2, by the identified metabolic module strongly suggests that redox regulation may plays a major role (45,87).

Added at Line 622.

5. Summarize the key findings and their significance in a concise manner at the end of the discussion section, reinforcing their relevance to the study's objectives.

Response

Conclusions section was added at the end to summarize the key findings and emphasize their significance. A graphical abstract was added to summarize the schematic view of the paper and its findings.

Conclusions

Identifying a lung epithelial metabolic gene signature regulated by type I interferon signal ing in the host response to respiratory viruses holds significant applications for:

1. This metabolic gene signature could potentially serve as a biomarker for early detection of respiratory pathogens.

2. Tracking changes in the metabolic gene signature by RT-PCR, clinicians could monitor the respiratory disease severity and response to therapy.

3. Screening for chemical inhibitors of the metabolic gene signature could lead to novel therapeutic drugs.

   Further research is required to test the presence of similar metabolic gene signatures in other bacterial, viral and inflammatory diseases where type I interferon signaling plays a critical role.

6. Finally, I would recommend the authors to read this manuscript:

https://www.sciencedirect.com/science/article/pii/S0890850822000317

I thank the reviewer for bringing attention to the excellent article by

Munir M. (Mapping molecular gene signatures mediated by SARS-COV-2 and large-scale and

genome-wide transcriptomics comparative analysis among respiratory viruses of medical

importance. Mol Cell Probes. 2022. doi: 10.1016/j.mcp.2022.101820).

Added to references (23)

Smith T, Rohaim MA,

I hope the modifications are acceptable to the reviewer.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript revisits analyses previously performed by others to try to proclaim a transcriptional response to virus infection that is termed a metabolic gene signature. The character or consequence of this metabolic gene signature is not established. Many of the factors included are at best indirectly related to the metabolism and no analysis is performed to identify a particular metabolic state that is established by the coordinately induced factors. No consequence of the proclaimed signature is established beyond the established antiviral effects of the factors that are focussed on. All factors have been previously identified as part of the response to virus and type I interferon response. All have previously been investigated for their particular antiviral activity. There isn’t anything new here and it isn’t clear what the manuscript is trying to convey. The authors need to develop a more coherent concept of what they are trying to contribute, most crucially by identifying a metabolic gene signature that establishes a particular metabolic state.

Comments on the Quality of English Language

The English is good, apart from a very few typing errors. However, the parts of the manuscript do not achieve their expected function. The abstract contains too much introduction. The introduction lists findings from similar studies rather than establishing the topic. The Discussion is also a disconnected list of topics/findings.

Author Response

Reviewer #2 The manuscript revisits analyses previously performed by others to try to proclaim a transcriptional response to virus infection that is termed a metabolic gene signature. The character or consequence of this metabolic gene signature is not established. Many of the factors included are at best indirectly related to the metabolism and no analysis is performed to identify a particular metabolic state that is established by the coordinately induced factors. No consequence of the proclaimed signature is established beyond the established antiviral effects of the factors that are focussed on. All factors have been previously identified as part of the response to virus and type I interferon response. All have previously been investigated for their particular antiviral activity. There isn’t anything new here and it isn’t clear what the manuscript is trying to convey. Response to reviewer # 2

I thank the reviewers for their valuable time and thoughtful suggestions. After 30-years of research, I have made the decision to retire. This is my last research paper. I have made several corrections (in bold and indicated by line numbers below).

Specific comments 1.The authors need to develop a more coherent concept of what they are trying to contribute, most crucially by identifying a metabolic gene signature that establishes a particular metabolic state. Response I agree with the reviewer to some extent on this point. Limitation of this study was added to discussion

A major limitation of this study is the lack of direct experimental evidence for a particular metabolic state induced by type I interferon in cells. However, the activation of several transcription factors known to be involved in redox regulation, such as NF-kB, Stat1, Stat3, p53, ATF4, and NRF2, by the identified metabolic module strongly suggests that redox regulation may plays a major role (45,87).

I agree to some extent. I would like to provide some background information on my research career. I was an experimental scientist for twenty-five years and working on the bioinformatics of interferon signaling for the last three years. I am well aware of the limitations and critique of the manuscript such as lack of experimental evidence or the work is a reanalysis of data by others. However, I must point out that Francis Crick’s classic papers in Molecular Biology I read in school such as the DNA double helix structure, adaptor hypothesis of tRNA, and Central Dogma were also interpretation of experimental data generated by others.

3.Comments on the Quality of English Language

Added at Line 622.
Graphic abstract summarized the point.

2. The manuscript revisits analyses previously performed by others

The English is good, apart from a very few typing errors.

4. There isn’t anything new here and it isn’t clear what the manuscript is trying to convey

Response to Reviewer

I diagree with this point.

Previous studies have identified gene signatures for antiviral, chemokine, apoptosis, and transcription factors mediated by type I interferon in lung epithelial cells, in response to respiratory viruses. Most of the alterations in cell metabolism were studied in cancers (ex: Warburg effect). In contrast, metabolism in the context of respiratory viruses and type I interferon signaling is not well understood. I am not aware of any studies that defined a metabolic gene signature of the five genes (EIF2AK2, CH25H, NAMPT, SAMHD1, and IDO1) common in the host response to several respiratory viruses and interacting with transcription factors of type I interferon signaling to form a regulatory protein complex or module, potentially constituting a feedback loop. The identification of a metabolic gene signature and a regulatory module in response to double-stranded RNA, Bacterial LPS, Unfolded Protein Response (UPR) have important implications for acute lung injury and inflammatory diseases.

5. The Discussion is also a disconnected list of topics/findings Response
Discussion was modified as follows

Response

I thank the reviewer for the positive comments on my language skills, considering that English is not my native language. I am also dyslexic, which is a handicap in research.

The main contributions of the study were explicitly stated at the beginning to provide a clear overview for the reader.

Overview was provided at the beginning of the discussion.

In this study, transcriptome profiling revealed a common metabolic gene signature mediated by type I interferon signaling in the host response to several respiratory viruses. Identification of the same metabolic signature was observed in response to double-stranded RNA, bacterial LPS, and UPR. This metabolic module is part of a protein interaction network with transcription factors of type I interferon signaling. Furthermore, EIF2AK2/PKR was identified as a key node in the metabolic module as suggested by the attenuation of the metabolic gene signature in Eif2ak2 KO mice in response to RSV.

( added at line 507).

·

Elaborated more on the clinical implications of the findings.

Identification of a metabolic gene signature in the lung epithelial response to respiratory viruses indicates that a comparative transcriptome analysis for metabolic gene signatures in a variety of lung diseases such as asthma, acute respiratory distress syndrome (ARDS), and septic shock is warranted. Further investigations are required to test the role of EIF2AK2/PKR inhibitors in response to respiratory viruses and inflammatory diseases. (added at line 553).

6. Conclusions added at line 630

Conclusions

Identifying a lung epithelial metabolic gene signature regulated by type I interferon signaling in the host response to respiratory viruses holds significant applications for:

1. This metabolic gene signature could potentially serve as a biomarker for early detection of respiratory pathogens.

2. Tracking changes in the metabolic gene signature by RT-PCR, clinicians could monitor the respiratory disease severity and response to therapy.

3. Screening for chemical inhibitors of the metabolic gene signature could lead to novel therapeutic drugs. Further research is required to test the presence of similar metabolic gene signatures in other bacterial, viral and inflammatory diseases where type I interferon signaling plays a critical role.

I hope the modifications are acceptable to the reviewer.

.