TMT-Based Quantitative Proteomic Analysis Reveals the Response of Tomato (Solanum lycopersicum L.) Seedlings to Ebb-and-Flow Subirrigation

Round 1

Reviewer 1 Report

This manuscript entitled “TMT-Based Quantitative Proteomic Analysis Reveals the Response of Tomato (Solanum lycopersicum L.) Seedlings to Ebb-and-Flow Subirrigation” aims to provide a update and evidence supporting the improvement of water use efficiency by ebb-and-flow subirrigation (EFI) as comparison with top sprinkle irrigation (TSI) on proteome level by TMT labeling based quantitative analysis. This study is important for understanding the viability of tomato seedlings by different water distribution (irrigation) system.

-          Author need to provide information regarding appropriate normalization approach for TMT labeling. In case of proteome analysis through TMT labeling need to handle the distortions referred to as “batch effects”. Therefore, data must be corrected for these batch effects by normalization steps before statistical modeling is done.

-          Results section 3.2, It is difficult to understand why authors provided the functional annotation of whole identified proteins. Those proteins still contain statistically less significant proteins as well, if so authors want to summarize the global proteome profile of whole identified proteins, minimize this section is better. It occurs confusion with main functional annotation data provided from section 3.3.

-          Moreover, the results were difficult to follow, mostly because there were not enough descriptions of functional classification and importance of identified proteins. Although summarization of a wide range of proteomic analyses possibly provides a useful information, the research question in this study is not clear.

-          Moreover, Authors need to mentioned more detailed information regarding statistical test.

-          Section 3.5, This section is not clearly understandable. Maybe author provide this kind of information in discussion section.

-          One of the weakest points of this study is related to the way the data are presented and discussed. My suggestion is providing some additional figure to summarize the major results of DAPs regarding stress resistance, defense response, amino acid metabolism, hormone, and secondary metabolism.

-          Line 139-141: Please check manufacturer’s information

-          Line 141: data-DAPendent acquisition (DDA) -> data-dependent acquisition (DDA)

-          Line 155-156: Which version of proteome library was used?

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

Authors have provided a detailed proteomic analysis/comparison between tomato seedlings grown in two different greenhouse irrigation systems. The results of the proteomic analysis seem to be quite promising. Benefits of the EFI subirrigation are quite well known already, however tests on a new crop is always useful. On the other hand, the most important results of such experiments, are: water use, use of fertilizer, yield per square meter of a greenhouse and crop quality. Without these data, the work is a bit partial and speculative. I would suggest to add some data which describe the efficiency of EFI subirrigation in the experiment presented or to cite papers which describe in more detail tomato yields and crop quality, compaing EFI to standard sprinkle irrigation.

Author Response

Please see the attachment

Author Response File: Author Response.docx

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

Manuscript submitted by Wang et al. entitled “TMT-Based Quantitative Proteomic Analysis Reveals the Response of Tomato (Solanum lycopersicum L.) Seedlings to Ebb-and-Flow Subirrigation” aims to provide a update and evidence supporting the improvement of water use efficiency by ebb-and-flow subirrigation (EFI) as comparison with top sprinkle irrigation (TSI) on proteome level by TMT labeling based quantitative analysis. This study is important for understanding the viability of tomato seedlings by different water distribution (irrigation) system.

1. Authors applied proteome analysis using TMT 6-plex kit and sequentially analyzed the sample with Q-Exactive HF-X MS instrument. Moreover, raw data was subjected to search engines; PD 2.2. However, Authors don’t provide information regarding appropriate normalization approach for TMT sample. In case of proteome analysis through TMT labeling need to handle the distortions referred to as “batch effects”. Therefore, data must be corrected for these batch effects by normalization steps before statistical modeling is done. If so, authors of this review should check and mentioned about detailed normalization processes in materials & method and results sections.
2. Results section 2.2, It is difficult to understand why authors provided the functional annotation of whole identified proteins. Those proteins still contain statistically less significant proteins as well, if so authors want to summarize the global proteome profile of whole identified proteins, minimize this section is better. It occurs confusion with main functional annotation data provided from section 2.3.
3. All raw files must be deposit to PRIDE or other available open source database. Authors should provide all statistical data in supplementary table for TMT analysis.
4. Moreover, Authors need to mentioned more detailed information regarding statistical test. For example, statistical test was applied by student t-test, one-way ANOVA, Multiple sample test by permutation-based FDR or Benjamini-Hochberg FDR.
5. Section 2.5, This section is not clearly understandable. Maybe author provide this kind of information in discussion section.
6. In my opinion, one the weakest point of this work is related to the way the data are presented and discussed. My suggestion is providing some additional figure to summarize the major results of DAPs regarding stress resistance, defense response, amino acid metabolism, hormone, and secondary metabolism
7. Section 4.3, For second peptide search by MS/MS author selected top10 or top15 method? Please check.
8. Line 363-364: Please check manufacturer’s information
9. Line 365: data-DAPendent acquisition (DDA) -> data-dependent acquisition (DDA)
10. Line 379-380: Which version of proteome library was used?
11. Line 381: Please check manufacturer’s information
12. All the tools (Pfam, PRINTS, ProDom, SMART, ProSite, PANTHER etc) need appropriate citations

Reviewer 2 Report

This manuscript describes a TMT-based quantitative study to investigate the proteomic changes using EFI and TSI treatments in tomato seedlings. The authors focused on the expression differences of DAPs in the two treatments, and they compared the GO terms enriched in significantly changed DAPs. Several GO terms and KEGG pathways were enriched, which are mainly related to the metabolic processes. The authors identified some DAP candidates that might regulate EFI-induced enzymes, which could assist tomato to survive from environmental stress.

Comments:

1.All the MS raw files are needed to be uploaded into online proteomics repository.

2.It would be better to provide the PD search and TMT quantitative results as supplemental tables.

3. Provide the detailed data of Figure 7 in supplemental table. 

Reviewer 3 Report

In this manuscript, the author did TMT-based quantitative proteomic analysis reveals the Response of tomato (Solanum lycopersicum L.) seedlings to Ebb-and-Flow subirrigation. In this study, the authors elucidated the effects of ebb-and-flow subirrigation on the protein levels in tomato roots in comparison with top sprinkle irrigation (TSI). They used an integrated approach involving tandem mass tag (TMT) labeling, high-performance liquid chromatography (HPLC) fractionation, and mass spectrometry (MS) based analysis. A total of 8,510 quantifiable proteins and 513 differentially accumulated proteins (DAPs) were identified, of which the expressions of 283 DAPs were up-regulated, and 230 DAPs were down-regulated in the EFI vs TSI treatment comparison. The authors performed a systematic bioinformatics analysis of all identified proteins and DAPs according to proteomic data. The DAPs were most significantly associated with the terms “metabolic process”, “anchored component of membrane”, “oxidoreductase activity”, “phenylpropanoid biosynthesis” and “biosynthesis of secondary metabolites” according to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes enrichment (KEGG) analysis. The 272 DAPs were classified into 12 subcellular components according to their subcellular localization. Furthermore, the activities of SOD, POD, CAT, GR, and APX in tomato roots were remarkably increased under EFI, while the MDA content was decreased compared with TSI. Correlation analysis among enzymes and their related DAPs showed that 30 DAPs were might be responsible for the regulation of these enzymes.

The article is poorly written and has plagiarism of the highest order also, and the authors did not validate their expression result of DEGs, which is a must. Also, the author should ideally characterize at least one gene function found in this study. Therefore, I did not find any merit in this study to publish in plants.

In this manuscript I found plagiarism of highest level at L2, L16-L18, L20-21, L24-25, L27-28, L35, L38-39, L41-43, L46-47, L50-L53, L56-L61, L64-68, L70-71, L74, L76, L91, L93, L94-99, L101-102, L103, L105-106, L117-118, L127, L129-130, L132, L133-134, L148-149, L150-151, L152-153, L160, L162, L171, L180, L206, L216-218, L271-272, L273-275, L286-287, L291-292, L305-306, L308, L332, L341-344, L345-349, L353-356, L359-362, L365-368, L369-378, L380-385, L386-387, L390-394, L397-398, L400-401