Transcriptomic and Metabolic Analyses Elucidate the Metabolomic Variation in Leaf Development of a Calcium-Rich Vegetable (Primulina eburnea)

Round 1

Reviewer 1 Report

Transcriptomic and metabolic analyses Primulina  review 30.06.2023

The studies presented in the manuscript “Transcriptomic and metabolic analyses elucidate the metabolomics variation in leaf development if the calcium-rich vegetable (Primulina eburnea)” fit perfectly to the scope of the Special Issue. It aims at describing the molecular and metabolic mechanisms of flavour and nutritional quality development in the leaves of Primulina eburnea.
In general the manuscript is well prepared, graphical presentation of the results is of high quality, the discussion section, however, could have been more extended. In the first part of the manuscript the uniqueness of that plant is underlined as being a calcium-rich species. However in further parts that characteristics is little referred to. Also in the discussion section I would put more emphasis on those genes, factors, compounds that are not so popular in plant biochemistry while specific for Primulina eburnea, it will build up the novelty of the obtained information and the value of that species.

The authors also mention that some selection has been previously conducted (lines 54-55), however no detailed information on that matter is provided, nor the type of cultivar/genotype is given in the methodology section. I could not also find the information what are the key compounds responsible specifically for the flavour and nutrition quality in that plant species. The Authors focus on flavonoids, amino acids and sugars, but are they the main groups responsible for the nutritional and flavour quality of that vegetable? In that case, the big unknown is calcium and its uptake/metabolism (calcium-rich plant). To be clear, I do not undermine the study and its results, I only give my concerns and expectations that I had when started reading the manuscript. Also the title suggests that the calcium involvement is somehow important for the study.

In section 2.2 Determination of physiological traits you do not mention the method of starch analysis the results of which is presented in Figure S2 and Table S5).
Also further in the manuscript you mention the contents of glucose and fructose (l. 200), galactose (I. 339) cannot find the respective contents in Table S2 or elsewhere.

In the discussion section the statement of higher vulnerability of mature leaves as compared to young leaves and buds is too far-fetched as referring only to the differences in sugar contents.

 Line 333 – “1041 unique metabolites” – I would not typical sugars, amino acids, flavonoids as unique compounds as they are commonly found in all plant tissues.

Line 384 – “increased the taste “ – The Authors did not evaluate the organoleptic properties of plants.

Apart from what is stated above I do not have any additional comments on the work. I think the manuscript needs a minor revision.

Author Response

The studies presented in the manuscript “Transcriptomic and metabolic analyses elucidate the metabolomics variation in leaf development if the calcium-rich vegetable (Primulina eburnea)” fit perfectly to the scope of the Special Issue. It aims at describing the molecular and metabolic mechanisms of flavour and nutritional quality development in the leaves of Primulina eburnea.

In general the manuscript is well prepared, graphical presentation of the results is of high quality, the discussion section, however, could have been more extended. In the first part of the manuscript the uniqueness of that plant is underlined as being a calcium-rich species. However in further parts that characteristics is little referred to. Also in the discussion section I would put more emphasis on those genes, factors, compounds that are not so popular in plant biochemistry while specific for Primulina eburnea, it will build up the novelty of the obtained information and the value of that species.

We appreciate this comment. We have revised our manuscript according to your suggestions. We detected the calcium content variation during the leaf development of the calcium-rich vegetable. We also analyzed the expression profiles of all calcium membrane transporter genes and found that CaCA played important roles for the water-soluble calcium accumulation.

The authors also mention that some selection has been previously conducted (lines 54-55), however no detailed information on that matter is provided, nor the type of cultivar/genotype is given in the methodology section. I could not also find the information what are the key compounds responsible specifically for the flavour and nutrition quality in that plant species. The Authors focus on flavonoids, amino acids and sugars, but are they the main groups responsible for the nutritional and flavour quality of that vegetable? In that case, the big unknown is calcium and its uptake/metabolism (calcium-rich plant). To be clear, I do not undermine the study and its results, I only give my concerns and expectations that I had when started reading the manuscript. Also the title suggests that the calcium involvement is somehow important for the study.

The major medicinal compound of P. eburnea is naphthaquinone. However, metabolomics could not detect this kind of substances. However, we are conducting the analysis of medicinal ingredients including naphthaquinones in our lab now. We analysed the network of sugar, amino acid, an flavonoids as the flavour and nutrition compounds according to published work such as that in kiwifruits (Xiong et al., 2020), passion fruit (Xin et al., 2021), Torreya grandis (Lou et al., 2022).

We conducted an additional analysis and detecting of the water-soluble calcium (which is the major bioavailable calcium in vegetable crops) content in P. eburnea leaves during the development. The water-soluble calcium content increased during the development (Figure 8A). We then investigated the expression profiles of the related genes and found that some CaCA genes differentially accumulated their transcript levels between bud and mature buds. However, other genes didn’t show a significant difference. And we revised the discussion section.

Xiong et al. Nutritional component analyses of kiwifruit in different development stages by metabolomic and transcriptomic approaches. J Sci Food Agric 2020; 100: 2399–2409.

Xin et al. Integrated metabolomic and transcriptomic analyses of quality components and associated molecular regulation mechanisms during passion fruit ripening. Postharvest Biology and Technology, 2021, 180: 111601.

Lou et al. Identification of key genes contributing to amino acid biosynthesis in Torreya grandis using transcriptome and metabolome analysis. Food Chemistry 2022, 379, 132078.

In section 2.2 Determination of physiological traits you do not mention the method of starch analysis the results of which is presented in Figure S2 and Table S5). Also further in the manuscript you mention the contents of glucose and fructose (l. 200), galactose (I. 339) cannot find the respective contents in Table S2 or elsewhere.

The method of starch content detecting was provided in the revised manuscript. The contents of glucose, fructose, and galactose were determined by Wuhan MetWare Biotechnology Co., Ltd. in metabolite detecting. We revised the Figure S2 and showed their relative contents. The starch content was determined in our lab.

In the discussion section the statement of higher vulnerability of mature leaves as compared to young leaves and buds is too far-fetched as referring only to the differences in sugar contents.

Thank you for this comment. We have revised this section.

 Line 333 – “1041 unique metabolites” – I would not typical sugars, amino acids, flavonoids as unique compounds as they are commonly found in all plant tissues.

This sentence has been revised.

Line 384 – “increased the taste “ – The Authors did not evaluate the organoleptic properties of plants.

This sentence has been removed in the revised version.

Apart from what is stated above I do not have any additional comments on the work. I think the manuscript needs a minor revision.

Author Response File: Author Response.pdf

Reviewer 2 Report

The authors generated good quality of data, but there are many issues in presenting and interpreting the data. In particular, Introduction and M&M should be revised by adding more information. Results should be reorganized by reflecting M&M. Discussion should contain more interpretation of their results. Please refer to my comments in the file attached.

Comments for author File: Comments.pdf

Author Response

We appreciate these comments from reviewer. The PDF file provided by reviewer could not show very well in our lab's PCs. The highlighted text could not match the notes made by reviewer well. These may be caused by the version or software differences. But we tried our best to match them and revised the manuscript according to the suggestions. Reviewer asked us to list gene names that mentioned in line 25 and other lines. We analyzed three big metabolic pathways that include many genes. They could be well read in the pathways figures, however, not suitable for listing in text especially in abstract section. 

Reviewer 3 Report

Zhang et al. performed transcriptomic and metabolomic analysis in the bud and mature leaves of Primulina eburnea. They have generated rich datasets that could be valuable for future studies of Primulina eburnea. However, I have several concerns regarding their study. The biggest concern is that not enough information has been provided regarding the transcription factors and other key candidate genes identified as controlling the nutritional and flavor traits. What are those sequences? What are the closest Arabidopsis orthologs? Are there any work done for the related orthologs that support the authors' conclusion?

Some minor concerns are listed below:

1. In fig.1, it appears to that authors plan to investigate five different developmental stages (L1 to L5). But in the other figures, it seems like only two developmental stages were studied (bud leaf - L2 and mature leaf - L4). Why not studying all five stages for the metabolome and transcriptome analysis?

2. What is the statistical analysis performed for fig 1b, c, d, and e?

3. The enrichment analysis of KEGG pathways (for both metabolomes and transcriptomes) is missing in the methods.

4. line 234-235: "The DEGs were grouped into four clusters according to their expression dynamism during leaf development (Figure 4A)." The authors didn't specify how those clusters were generated. Is it based on co-expression network analysis (e.g. WGCNA)?

5. line 238-240: "These DEGs were found to encode 270 TFs, mainly HD-ZIP, MYB, bHLH, ERF and so on (Figure 4B), which appeared to play key roles in modulating the expression levels of genes involved in the nutrition and flavor in P. eburnea leaves." These are big TF families that are involved many different biological processes, they are not necessarily controlling the nutrition and flavor traits. Can the authors provide specific TFs and the related references to demonstrate that they are associated with flavor and nutrition traits?

6. line 271-275: the authors used Pearson correlation analysis and binding site analysis to construct potential regulatory networks between 108 TFs and the genes involved in carbohydrate metabolism, amino acid metabolism, and phenylpropanoid metabolism. First, were these 108 TFs differentially expressed between bud and mature leaves? If so, which cluster do they belong? Second, the binding site analysis and Pearson analysis was not included in the methods. Third, what were the closest Arabidopsis orthologs for these TFs? Were those orthologs demonstrated to be involved in carbohydrate, amino acid, and phenylpropanoid analysis?

Minor edits are needed.

Author Response

Zhang et al. performed transcriptomic and metabolomic analysis in the bud and mature leaves of Primulina eburnea. They have generated rich datasets that could be valuable for future studies of Primulina eburnea. However, I have several concerns regarding their study. The biggest concern is that not enough information has been provided regarding the transcription factors and other key candidate genes identified as controlling the nutritional and flavor traits. What are those sequences? What are the closest Arabidopsis orthologs? Are there any work done for the related orthologs that support the authors' conclusion?

Thanks for this comment. Pathways showed in this research were built based on published work. Our works here were elucidating the gene members of these pathways in P. eburnea. The names and functions of these genes were provided by the published P. eburnea genome (Yi et al., 2022). The genome annotation was based mainly on finding Arabidopsis orthologs. Thus, we don’t need to conduct the analysis of function of orthologs. Importantly, we should and will demonstrate the function of the gene members of P. eburnea in our future work.

Some minor concerns are listed below:

1. In fig.1, it appears to that authors plan to investigate five different developmental stages (L1 to L5). But in the other figures, it seems like only two developmental stages were studied (bud leaf - L2 and mature leaf - L4). Why not studying all five stages for the metabolome and transcriptome analysis?

Morphological and physiological analyses were also part of this research, as we illustrated in section 3.1. For the metabolome, we selected two representative stages because the leaves developed fast during these stages. These information also could be found in section 3.1. In addition, studying two representative developmental stages rather than all five stages is feasible for our finance.

2. What is the statistical analysis performed for fig 1b, c, d, and e?

Significant differences were determined by one-way analysis of variance (ANOVA) (P < 0.05) as we illustrated in section 2.7.

3. The enrichment analysis of KEGG pathways (for both metabolomes and transcriptomes) is missing in the methods.

We have revised the method section. KEGG analysis and GO enrichment were performed using KEGG Orthology software and GO-seq R packages, respectively.

4. line 234-235: "The DEGs were grouped into four clusters according to their expression dynamism during leaf development (Figure 4A)." The authors didn't specify how those clusters were generated. Is it based on co-expression network analysis (e.g. WGCNA)?

The clustering was made based on Euclidean distances by Multi Experiment Viewer software. We have revised the method section and we supplement a figure as Figure S4.

5. line 238-240: "These DEGs were found to encode 270 TFs, mainly HD-ZIP, MYB, bHLH, ERF and so on (Figure 4B), which appeared to play key roles in modulating the expression levels of genes involved in the nutrition and flavor in P. eburnea leaves." These are big TF families that are involved many different biological processes, they are not necessarily controlling the nutrition and flavor traits. Can the authors provide specific TFs and the related references to demonstrate that they are associated with flavor and nutrition traits?

We revised this part. MYB has been reported as the most often TFs to modulate or generate the new traits involved in flavor and nutrition in crops (Allan and Espley, 2018). In Brassicales, bHLH has been demonstrated to affect the nutrition by regulation the biosynthesis of glucosinolates (Pireyre and Burow, 2015). So we suspect that some of these 270 TFs may play key roles in modulating the expression levels of genes involved in the nutrition and flavor in P. eburnea leaves.

Allan, A.C.; Espley, R.V. MYBs Drive Novel Consumer Traits in Fruits and Vegetables. Trends in Plant Science 2018, 23, 693-705, doi:https://doi.org/10.1016/j.tplants.2018.06.001.

Pireyre, M.; Burow, M. Regulation of MYB and bHLH transcription factors: a glance at the protein level. Mol Plant 2015, 8, 378-388, doi:10.1016/j.molp.2014.11.022.

6. line 271-275: the authors used Pearson correlation analysis and binding site analysis to construct potential regulatory networks between 108 TFs and the genes involved in carbohydrate metabolism, amino acid metabolism, and phenylpropanoid metabolism. First, were these 108 TFs differentially expressed between bud and mature leaves? If so, which cluster do they belong? Second, the binding site analysis and Pearson analysis was not included in the methods. Third, what were the closest Arabidopsis orthologs for these TFs? Were those orthologs demonstrated to be involved in carbohydrate, amino acid, and phenylpropanoid analysis?

In the regulatory network construction, we used the differentially expressed TFs. We have revised this part in the new version. We supplemented a table (Table S5) to show these TFs information including pathways, gene names, clusters, types, and annotations. We have revised the section 2.7. The Pearson analysis and binding site (cis-element) prediction method were provided.

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Most of my previous comments have been properly addressed. However, for the transcription factor section, it would be great to know SPECIFIC transcription factors that have been demonstrated to control the traits investigated in this study, rather than a broad gene family that can be involved all sorts of metabolic pathways. For example, in the newly submitted Table S5, the authors provided the closest Arabidopsis orthologs, are there any publications showing that those orthologs are involved in amino acid, carbohydrate, and phenylpropanoid metabolism?

Minor edits needed.

Author Response

For the TFs that may regulate the pathways of amino acid, carbohydrate, and phenylpropanoid metabolism, we identified a total of more than 200 TFs through the co-expression network and cis-element prediction. This work could not detect a certain TF which may work in these pathways. The main results of our present work is to identify the potential members of structural genes in these pathways, rather than the TFs. TF-regulation is complex for that they may regulate one or more genes in these pathways. However, according to your suggestion, we add some information in the Table S5 to show the published function analysis of these TFs in these pathways. We listed the predicted functions and references in Table S5.