SARS-CoV-2 Viroporins: A Multi-Omics Insight from Nucleotides to Amino Acids
Round 1
Reviewer 1 Report
The manuscript by Sarkar et al relies heavily on predictions based on the use of various bioinformatic tools. The manuscript is very well-written and the analysis performed on the different characteristics of the viroporins Orf3a and E provides a novel perspective. However, the manuscript lacks empiric data.
The transcriptomic results in Figure 1 have been reported before in multiple studies and does not offer novelty. Although the authors hypothesize of a very interesting link to cellular ionic imbalances, there is nothing specific in their analysis to make this association. In other words what was the specific criteria to examine the genes that are predicted to be associated with cellular ionic channeling, given that so many of those genes overlap with antiviral responses. The membrane modeling and superimposition analysis offers a clear visualization of the hydrophobic and hydrophilic interactions between the viroporins ORF3a and E and specific membrane environments in the endosome/lysosomes and ERGIC. The authors would benefit from predicting the incorporation of specific mutations that will destabilize these interactions and serve as targets for antiviral treatments. This will strengthen the manuscript given its heavy reliance on bioinformatics. The names of the lipids in Table 1 should be defined.
Author Response
Our responses to the reviewer's comments are in green:
The manuscript by Sarkar et al relies heavily on predictions based on the use of various bioinformatic tools. The manuscript is very well-written and the analysis performed on the different characteristics of the viroporins Orf3a and E provides a novel perspective. However, the manuscript lacks empiric data.
We thank the reviewer for the kind comments and suggestions. Indeed, its a theoretical study focusing on omics methodologies in a virus like SARS CoV-2 in a systematic manner. We discussed about our limitations in the Discussion, page 30 line # 627-631.
The transcriptomic results in Figure 1 have been reported before in multiple studies and does not offer novelty. Although the authors hypothesize of a very interesting link to cellular ionic imbalances, there is nothing specific in their analysis to make this association. In other words what was the specific criteria to examine the genes that are predicted to be associated with cellular ionic channeling, given that so many of those genes overlap with antiviral responses.
We agree that our study is not very novel from the transcriptomic results. Indeed, it is a re-analysis of a previously published dataset. We have discussed this part in the discussion Page 26-27 line # 531-552. We have spoken about the relevance of the genes differentially regulated that we report in the results.
The membrane modeling and superimposition analysis offers a clear visualization of the hydrophobic and hydrophilic interactions between the viroporins ORF3a and E and specific membrane environments in the endosome/lysosomes and ERGIC. The authors would benefit from predicting the incorporation of specific mutations that will destabilize these interactions and serve as targets for antiviral treatments. This will strengthen the manuscript given its heavy reliance on bioinformatics.
We have addressed this part extensively. We have incorporated a new result in the manuscript, by introducing site specific mutations in E protein and Orf3a and assessed their impact by the DDG values obtained from SDM2. For the changes in the manuscript, please refer to the following parts:
Methods: Page 10-11, line #236-252
Results: Page 24-26, line #509-529
Discussion: Page 30, line #615-626
Acknowledgements: Page 32, line #674-676
References: Page 38, line #875
The names of the lipids in Table 1 should be defined.
Addressed in Page 9, line #202-205.
Reviewer 2 Report
In this manuscript, Sarkar et al. a variety of bioinformatics (transcriptomic, genomic and proteomic), structural modelling and molecular dynamics simulation studies were undertaken to characterize the Orf3a and Envelope (E) protein viroporins of SARCoV-2. The data are clearly and appropriately presented in a readily understandable manner.
Minor comments include the following:
Page 1, line 15 (Abstract). Replace sequential rather with sequence.
In Table, define the abbreviations as a footnote to the Table.
Page 3, line 124: Correct Position specific to Position-specific
Page 8, lines 296-298: Could the authors comment on the importance or not of the higher scores for selected residues observed in the respective variants.
Page 14, Line 422: Change systemic to systematic.
Author Response
Our responses to the reviewer are in green:
In this manuscript, Sarkar et al. a variety of bioinformatics (transcriptomic, genomic and proteomic), structural modelling and molecular dynamics simulation studies were undertaken to characterize the Orf3a and Envelope (E) protein viroporins of SARCoV-2. The data are clearly and appropriately presented in a readily understandable manner.
We thank the reviewer for the kind comments and suggestions.
Minor comments include the following:
Page 1, line 15 (Abstract). Replace sequential rather with sequence.
Addressed in Page 1 line # 21 of the paragraph Abstract.
In Table, define the abbreviations as a footnote to the Table.
Addressed in Page 9, line #202-205.
Page 3, line 124: Correct Position specific to Position-specific
Addressed in Page 4, line #95 and Page. 6, line# 139.
Page 8, lines 296-298: Could the authors comment on the importance or not of the higher scores for selected residues observed in the respective variants.
Addressed in Page 16, line #353-356. We have added a rationale for observing higher values in the position-specific mutations across Orf3a and E protein in respective variants.
Page 14, Line 422: Change systemic to systematic.
Addressed in Page 26, line # 531
