Viral Targets in the Human Interactome with Comprehensive Centrality Analysis: SARS-CoV-2, a Case Study
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsIn the current manuscript the authors have discussed different methods for network analysis to identify the targets of SARS-CoV2 in the human interactome. The methods described in the manuscript appear to be quite promising for identifying human protein targets of different viruses. However, the authors must address the following concerns to make the manuscript suitable for publication.
1. The different methods of network analysis have ranked the protein targets of SARS-CoV2. Are there any biochemical evidence of the interactions of these human proteins prioritized in the analysis, with the SARS-CoV2 proteins?
2. In the past few years, there has been a couple of reports on network analysis and proteome wide analysis to identify human protein targets of SARS-CoV2. A few of these reports are as follows.
Li Feng, Yuan-Yuan Yin, Cong-Hui Liu, Ke-Ren Xu, Qing-Run Li, Jia-Rui Wu, Rong Zeng, Proteome-wide data analysis reveals tissue-specific network associated with SARS-CoV-2 infection, Journal of Molecular Cell Biology, 12, 12(2020), 946–957.
Kim, DK., Weller, B., Lin, CW. et al. A proteome-scale map of the SARS-CoV-2–human contactome. Nat Biotechnol 41, 140–149 (2023).
The authors should briefly summarize the results of the above articles or other recent articles that deliberate on interactions between human proteome and SARS-CoV2. The authors must discuss whether the methods they have reported identify the similar protein targets as the above reports or are the targets different. If the targets are different the authors must address why it is so.
Comments on the Quality of English Language
Listed below are a few suggestions to correct some mistakes in the English language of the manuscript.
a. Legend to Figure 2, lines 272-273: The following sentence is wrongly worded. ‘UpSet Plot of Node Set Intersections in the Wk-Shell One thrid and one third nodes.’ It is not clear from the sentence what the authors are trying to communicate. The authors should correct the sentence.
b. Legend to Figure 4, lines 310, 312, 317, and 323: Correct ‘Centality’ to ‘Centrality’.
c. Lines 339-340: Start the sentence as ‘This approach allows the ranking of nodes based on……..’
d. Lines 343-344: The following sentence is wrongly worded, ‘This was compared with target seed 100 representing what if we use all known host targets.’ The authors must clarify if they are representing all known host targets with the target seed 100.
Author Response
- The different methods of network analysis have ranked the protein targets of SARS-CoV2. Are there any biochemical evidence of the interactions of these human proteins prioritized in the analysis, with the SARS-CoV2 proteins?
Thank you for your insightful question regarding the biochemical evidence for the interactions between the prioritized human proteins and SARS-CoV-2 proteins. I appreciate the opportunity to clarify this important aspect of our study. In response to your query, I would like to emphasize that our network analysis and protein prioritization were indeed built upon a foundation of experimentally validated interactions. As mentioned in the manuscript (line 172 to 189).
We discussed the following paragraph in the revised version
“While our network analysis methods provided a ranking of potential protein targets, it is important to note that these rankings were derived from and supported by underlying experimentally validated interactions. We acknowledge that experimental validation of all predicted interactions is beyond the scope of this computational study. However, our approach leverages a wealth of existing experimental data to make informed predictions about potential SARS-CoV-2 targets. These predictions can serve as valuable hypotheses for future experimental studies focused on validating specific virus-host protein interactions”.
- In the past few years, there has been a couple of reports on network analysis and proteome wide analysis to identify human protein targets of SARS-CoV2. A few of these reports are as follows.
Li Feng, Yuan-Yuan Yin, Cong-Hui Liu, Ke-Ren Xu, Qing-Run Li, Jia-Rui Wu, Rong Zeng, Proteome-wide data analysis reveals tissue-specific network associated with SARS-CoV-2 infection, Journal of Molecular Cell Biology, 12, 12(2020), 946–957.
Kim, DK., Weller, B., Lin, CW. et al. A proteome-scale map of the SARS-CoV-2–human contactome. Nat Biotechnol 41, 140–149 (2023).
The authors should briefly summarize the results of the above articles or other recent articles that deliberate on interactions between human proteome and SARS-CoV2. The authors must discuss whether the methods they have reported identify the similar protein targets as the above reports or are the targets different. If the targets are different the authors must address why it is so.
We have provided the following text in the revised manuscript. We analyzed the data and added Figure S2.
“Previous studies have made significant contributions to our understanding of SARS-CoV-2-host protein interactions [42, 43]. A tissue-specific network analysis approach identified potential SARS-CoV-2 targets across different human tissues. This study highlighted the importance of considering tissue specificity in virus-host interactions and identified several key proteins and pathways involved in SARS-CoV-2 infection [43]. Using multiple experimental approaches, including affinity purification mass spectrometry and proximity labeling, a comprehensive map of the SARS-CoV-2-human 'contactome' was provided. This study identified both previously known and novel virus-host protein interactions, offering insights into the molecular mechanisms of SARS-CoV-2 infection [42]. Our study builds upon previous works by integrating a broader range of experimental datasets and employing different algorithms and prioritization methods, potentially leading to the identification of both overlapping and novel targets. Additionally, our analysis incorporates the latest available data, capturing interactions that may not have been known or considered in earlier studies. We observed both overlaps and differences in the protein targets identified by our analysis compared to previous studies. The overlapping targets validate our approach and highlight the significance of these proteins in SARS-CoV-2 infection. Specifically, 168 out of the 170 HuSCI proteins identified by Kim et al., and all organ-specific proteins identified by Feng et al., are present in our merged network, with a significant overlap of 1,445 SARS-CoV-2 host interactor proteins from both studies (Figure S2). The differences in identified targets can be attributed to dataset differences, methodological variations, and the inherent biological complexity of virus-host interactions.”
We believe that these differences do not necessarily indicate inconsistencies, but rather highlight the complementary nature of various approaches in studying the complex SARS-CoV-2-human interactome. Our study aims to provide additional insights and hypotheses that can be integrated with existing knowledge to guide future experimental work.
We also addressed all the minor comments
Reviewer 2 Report
Comments and Suggestions for AuthorsIn this manuscript Nilesh Kumar et. al. performed the interactome study between human proteins and SARS-Cov-2 host paroteins using comprehensive Centrality CosDist analysis. Further, they evaluated the fnction and pathway associated with the target proteins. Author claims that these pathways can be utilized to undersand the other viral pathogenesis.
Overall manuscript is written clearly and easy to follow. However, I have a few comments below to improve the quality of the manuscript.
Author should reduce the font size of the figure legend to differentiate it from the main text.
Author Response
We have reduced the font size of the figure legend to differentiate it from the main text.
