The Secreted Metabolome of Hela Cells under Effect of Crotamine, a Cell-Penetrating Peptide from a Rattlesnake Using NMR-Based Metabolomics Analyses

Round 1

Reviewer 1 Report

In the paper entitled “The secreted metabolome of HeLa cells under effect of Crotamine, a cell-penetrating peptide from a rattlesnake using NMR-3 based metabolomics analyses” by Coronado et al., the authors investigated the metabolomic profile of HeLa cells under treatment with Crotamine, a toxin present in the venom of the South American rattlesnake. Interestingly, authors provide evidence and insights into the metabolic changes triggered by Crotamine, with specific regards to glycolysis and amino acids biosynthesis. In their experiments, authors show a reduction of glucose as well as pyruvate and lactate, in Crotamine-treated cells compared to untreated ones, indicating that an impairment of glycolisis is a major effect of Crotasmine on cancer cells. 

Although the significance is very interesting and the paper is well written, I still have two major comments:

1. "Crotamine interacts with DNA": I would encourage the authors to add some functional assays that may increase the impact of the thier work. For instance, what about the proliferation rate and/or apoptotic events? Are they affected by Crotamine?

2. “Crotamine can affect specific gene expression”: Do the authors think it is possible to “molecularly” characterize the phenotypic/metabolic profile of HeLa cells treated with Crotamine? (g. major signaling pathways known to play a critical role in tumorigenesis. Are they affected/involved in the metabolic changes observed in HeLa cells treated with Crotamine?)

Author Response

Comments and Suggestions for Authors
In the paper entitled “The secreted metabolome of HeLa cells under effect of Crotamine, a cell-
penetrating peptide from a rattlesnake using NMR-3 based metabolomics analyses” by Coronado et
al., the authors investigated the metabolomic profile of HeLa cells under treatment with
Crotamine, a toxin present in the venom of the South American rattlesnake. Interestingly,
authors provide evidence and insights into the metabolic changes triggered by Crotamine,
with specific regards to glycolysis and amino acids biosynthesis. In their experiments, authors
show a reduction of glucose as well as pyruvate and lactate, in Crotamine-treated cells
compared to untreated ones, indicating that an impairment of glycolisis is a major effect of
Crotasmine on cancer cells.
Although the significance is very interesting and the paper is well written, I still have two
major comments:
1. "Crotamine interacts with DNA": I would encourage the authors to add some functional
assays that may increase the impact of the thier work. For instance, what about the
proliferation rate and/or apoptotic events? Are they affected by Crotamine?
The primary topic of our manuscript is to investigate and present the changes in the
metabolism of cells under the influence of Crotamine using NMR. We believe that the results
about metabolic changes presented in this work are very relevant for the researchers of this
scientific field. Crotamine is a very well described snake venom protein that possess several
functions including DNA binding and carrying, selectivity for highly proliferating cells and
inhibition of tumor growth, which is described in the introduction section.
DNA binding, carrying functions and inhibition of tumor cell proliferation of
Crotamine are well described in the literature. Contrary, Crotamine at micromolar range is
nontoxic to any cell cultures tested and did not affect the pluripotency of stem cells or the
development of mouse embryos. Regarding apoptotic events, Crotamine at high
concentrations is able to activate caspase-3 in CHO-K1 cells, which is an enzyme capable of
disassembling the cell. Active caspase-3 in cells and tissues can execute apoptosis.

For the described functions of Crotamine, please see the references below
• https://doi.org/10.1096/fj.03-1459fje
• https://doi.org/10.1074/jbc.M604876200
• https://doi.org/10.1155/2014/675985
• https://doi.org/10.1517/13543784.2011.602064
• https://doi.org/10.1016/j.toxicon.2008.06.029
2. “Crotamine can affect specific gene expression”: Do the authors think it is possible to
“molecularly” characterize the phenotypic/metabolic profile of HeLa cells treated with
Crotamine? (g. major signaling pathways known to play a critical role in tumorigenesis. Are
they affected/involved in the metabolic changes observed in HeLa cells treated with
Crotamine?)
We think it is possible to “molecularly” characterize the metabolic profile of HeLa cells
treated with crotamine once all major tumor suppressors and oncogenes have intimate
connections with metabolic pathways [1-3]. For example, oncogenic mutations can result in
the uptake of nutrients, particularly glucose, that meet or exceed the bioenergetic demands of
cell growth and proliferation. It has brought attention to Otto Warburg’s observation in 1924
that cancer cells metabolize glucose in a manner that is distinct from that of cells in normal
tissues [4]. Warburg found that unlike most normal tissues, cancer cells tend to “ferment”
glucose into lactate even in the presence of sufficient oxygen to support mitochondrial
oxidative phosphorylation and the link between the gene Myc and regulation of glucose
metabolism was first established when an early unbiased screen for Myc target genes
uncovered lactate dehydrogenase A (LDHA) among 20 other putative Myc target genes [5,6].
LDHA converts pyruvate, which is derived from glucose through glycolysis or other sources,
to lactate. Many other glucose metabolism genes were subsequently documented to be directly
regulated by Myc. Chief among these are the glucose transporter GLUT1, hexokinase 2 (HK2),
phosphofructokinase (PFKM), and enolase 1 [7,8]. Myc is hence able to stimulate genes that
increase the transport of glucose, its catabolism to trioses and pyruvate, and ultimately to
lactate. Because glycolytic genes are also directly responsive to HIF-1, the interplay between
Myc and HIF was documented through genes that could be regulated by both transcription
factors [9]. Collectively, these studies suggest that HIF-1 transactivates glucose transporter and

glycolytic genes in common with Myc; HIF-1 transactivates these genes under hypoxic
conditions (anaerobic glycolysis), whereas Myc regulates the same set of genes under
nonhypoxic conditions. These observations imply that Myc could contribute to the Warburg
effect (aerobic glycolysis) or the ability to convert glucose to pyruvate and in turn to lactate
even under adequate oxygen tension.
In our study we observed a decrease in the levels of glucose and lactate in HeLa cells
treated with crotamine. Probably, the treatment with crotamine decreased the levels of glucose
that is converted in lactate. Besides, the treatment with crotamine decreased the expression of
the genes Myc and HIF, which in turn regulate the transactivation of glucose transporting
genes and glycolytic genes. Therefore, crotamine might suppress cell growth by inhibiting
glycolysis.
References:
1. Vander Heiden MG, Cantley LC, Thompson CB (2009) Understanding the Warburg effect:
the metabolic requirements of cell proliferation. Science 324: 1029-1033.
2. Hsu PP, Sabatini DM (2008) Cancer cell metabolism: Warburg and beyond. Cell 134: 703-
707.
3. Levine AJ, Puzio-Kuter AM (2010) The control of the metabolic switch in cancers by
oncogenes and tumor suppressor genes. Science 330: 1340-1344.
4. Warburg O (1956) On the origin of cancer cells. Science 123: 309-314.
5. Lewis BC, Shim H, Li Q, Wu CS, Lee LA, et al. (1997) Identification of putative c-Myc
Responsive genes: characterization of rcl, a novel growth-related gene. Mol Cell Biol 17: 4967-
4978.
6. Shim H, Dolde C, Lewis BC, Wu CS, Dang G, et al. (1997) c-Myc transactivation of LDH-A:
implications for tumor metabolism and growth. Proc Natl Acad Sci U S A 94: 6658-6663.
7. Kim JW, Gao P, Liu YC, Semenza GL, Dang CV (2007) Hypoxia-inducible factor 1 and dysregulated
c-Myc cooperatively induce vascular endothelial growth factor and metabolic switches hexokinase 2
and pyruvate dehydrogenase kinase 1. Mol Cell Biol 27: 7381-7393.
8. Osthus RC, Shim H, Kim S, Li Q, Reddy R, et al. (2000) Deregulation of glucose transporter 1 and
glycolytic gene expression by c-Myc. J Biol Chem 275: 21797-21800.
9. Dang CV, Kim JW, Gao P, Yustein J (2008) The interplay between MYC and HIF in cancer. Nat Rev
Cancer 8: 51-56

Reviewer 2 Report

In this manuscript, Coronado et al described the use of NMR spectroscopy to identify & (semi-)quantify secreted metabolites in HeLa cells treated with snake venom toxin Crotamine. 15 metabolites were identified to be differentiated between treated vs untreated cells in multivariate analyses (PCA/PLS/OPLS). Relative concentrations of these 15 metabolites were quantified and subjected to classifications (SVM, random forest & PLS) to measure classification probability. Pathway analysis for this set of metabolites was performed using a metabolite database (MetExplore) with HeLa cells metabolic model to identify enriched pathways. Based on the results, the authors concluded that Crotamine primarily inhibited glycolysis, which in turn affected glutathione metabolism, TCA cycle and pyruvate metabolism.

The use of NMR spectroscopy to analyse secreted metabolome of cells treated with snake venom toxins is an interesting idea and has not been frequently reported (this may be a first in my limited knowledge). However, since this approach is relatively new I think the authors should provide more validation data to validate and support their methods. Here are some specific points that I would like to comment on:

1. As I am not familiar enough with the procedures and with NMR in general (as I suspect many of the readers of this journal are), it would be really helpful if the authors can have a paragraph or two to present and discuss the methods and parameters used to validate changes in NMR spectra observed are specific to metabolites secreted by the cells but not due to secreted (or released due to cell lysis) proteins/peptides (especially seeing many identified metabolites are amino acids), or even Crotamine added into the culture but not completely taken up by cells.
2. All 15 metabolites that were identified were lowered in Crotamine-treated cells. Considering cell viability is at least 10% lower in treated cells compared to control, could the observed difference be at least partially due to lower viability? Is it necessary to perform any adjustment/normalization with respect to cell viability?
3. Spectra assignments of the 15 metabolites should be provided as supplemental data.
4. While the authors identified 15 metabolites, there seems to be less than 15 in each clusters/groups in the PCA plots in Figure 4. Labeling in Figure 4 should be improved. I would assumed 1 vs 2 are control vs Crotamine but that should be clearly identified in labels and on the plots, not left for the readers to make assumptions. Panel A vs B has been labeled to be full-spectra vs concentrations but the legends seems to suggest Panel A vs B vs C should be running horizontally (ie. PCA vs OPLS vs PLS)? There is a missing ‘C’ in both the figure and in legend.
5. P8 L240 appears to suggest Table 1 list individual metabolites but it is a table of enriched pathways instead – please consider to write more clearly.
6. In Figure 6, the labels are miss-aligned in both panels.
7. For many, if not all, of the metabolites, relative quantifications using other methods should be easy. I would urge the authors to consider using other more established methods eg. LC-MS/MS or even assays testing glucose or lactate levels to do cross-validations of at least selected metabolites. The authors probably have some data pointing to decrease glucose level in the media and the results may be presented but more of such experiments (especially with mass spec data) would strengthen the manuscript considerably.

Author Response

Comments and Suggestions for Authors
In this manuscript, Coronado et al described the use of NMR spectroscopy to identify & (semi)
quantify secreted metabolites in HeLa cells treated with snake venom toxin Crotamine. 15
metabolites were identified to be differentiated between treated vs untreated cells in
multivariate analyses (PCA/PLS/OPLS). Relative concentrations of these 15 metabolites were
quantified and subjected to classifications (SVM, random forest & PLS) to measure
classification probability. Pathway analysis for this set of metabolites was performed using a
metabolite database (MetExplore) with HeLa cells metabolic model to identify enriched
pathways. Based on the results, the authors concluded that Crotamine primarily inhibited
glycolysis, which in turn affected glutathione metabolism, TCA cycle and pyruvate
metabolism.
The use of NMR spectroscopy to analyse secreted metabolome of cells treated with snake
venom toxins is an interesting idea and has not been frequently reported (this may be a first
in my limited knowledge). However, since this approach is relatively new I think the authors
should provide more validation data to validate and support their methods. Here are some
specific points that I would like to comment on:
1. As I am not familiar enough with the procedures and with NMR in general (as I suspect
many of the readers of this journal are), it would be really helpful if the authors can have a
paragraph or two to present and discuss the methods and parameters used to validate
changes in NMR spectra observed are specific to metabolites secreted by the cells but not
due to secreted (or released due to cell lysis) proteins/peptides (especially seeing many
identified metabolites are amino acids), or even Crotamine added into the culture but not
completely taken up by cells.
The authors added two paragraphs in the discussion section to clear the methods used
and already very well described in the literature (Lines 287 to 304).
2. All 15 metabolites that were identified were lowered in Crotamine-treated cells.
Considering cell viability is at least 10% lower in treated cells compared to control, could  

the observed difference be at least partially due to lower viability? Is it necessary to perform
any adjustment/normalization with respect to cell viability?
Great efforts have been devoted to the development of molecules that, by inhibiting
prosurvival protein functions, promote apoptosis in cancer cells. With the almost systematic
influence of mitochondrial apoptotic stress on inflammation, chemosensitivity, immune
response and tumor progression after therapy, it can be argued that treatments remodel the
tumor microenvironment and adaptive immunity. In particular, their influence on
intercellular communication between malignant clones and non-malignant cells is critical:
compromised or dying cells can generate active signals that drive tumor response to anticancer
treatments.
It is already described in the literature that exposure to chemotherapeutic agents can change
the types and abundance of components of the tumor secretome. For example, IL-6 and IL-8
are frequently induced, and their expression is strongly correlated with tumor recurrence [1].
The MTT assay is used to measure cellular metabolic activity as an indicator of cell
viability, proliferation, and cytotoxicity. It has been widely used and is considered a gold
standard.
Most cellular assays currently available have readings at a standard time of 48 h to 72
h after drug treatment. Due to this extended incubation time, most cells that are responding at
early times after treatment are lost by the time the assay is performed due to the disintegration
of the cells into particulate debris; we understand that this changes the ratio between the
populations of live and dead cells present at the time of analysis. Thus, to identify an optimal
time point required to perform the assay reading to report significant results in response to
crotamine treatment, we performed time point experiments using the MTT assay. Instead of a
conventional single late time point experiment, we performed early time points (at 4 h, 12 h,
and 24 h) for evaluation; we decided to evaluate the secreted metabolite profile in HeLa cells
treated with 10 μM Crotamine for 24 h to better understand the cross-talk between crotamine
and the cell, yet avoid cell apoptosis over time.
References:
1. Madden EC, Gorman AM, Logue SE, Samali A. Trends Cancer. 2020 Jun; 6(6):489-505.Tumour Cell
Secretome in Chemoresistance and Tumour Recurrence.

3. Spectra assignments of the 15 metabolites should be provided as supplemental data.
Data was added as supplementary material.
4. While the authors identified 15 metabolites, there seems to be less than 15 in each
clusters/groups in the PCA plots in Figure 4. Labeling in Figure 4 should be improved. I
would assumed 1 vs 2 are control vs Crotamine but that should be clearly identified in labels
and on the plots, not left for the readers to make assumptions. Panel A vs B has been labeled
to be full-spectra vs concentrations but the legends seems to suggest Panel A vs B vs C
should be running horizontally (ie. PCA vs OPLS vs PLS)? There is a missing ‘C’ in both the
figure and in legend.
Each point in the PCA score plot shown in figure 4 is a replicate sample, not a
metabolite. Figure 4 was also changed in order to address the reviewer comment and, now,
control and crotamine treated cells are better identified. Also, panels a, b and c are now better
organized (Lines 245 to 248).
5. P8 L240 appears to suggest Table 1 list individual metabolites but it is a table of enriched
pathways instead – please consider to write more clearly.
We have performed the changes. Individual metabolites are shown in figure 5.
6. In Figure 6, the labels are miss-aligned in both panels.
Changed accordingly.
7. For many, if not all, of the metabolites, relative quantifications using other methods should
be easy. I would urge the authors to consider using other more established methods eg. LC-
MS/MS or even assays testing glucose or lactate levels to do cross-validations of at least
selected metabolites. The authors probably have some data pointing to decrease glucose
level in the media and the results may be presented but more of such experiments
(especially with mass spec data) would strengthen the manuscript considerably.
Thank you for the comment. Unfortunately, access to LC-MS/MS instrumentation is
not easy for our centre. Although we do understand that having more than one technique to

perform metabolite profiling is very interesting and adequate, we also see that only a limited
number of papers combine both techniques. NMR has been listed as the most precise in
quantifying specific metabolites, since isolated signals are available for a number of different
molecules [1].
References:
1. Bouatra S, Aziat F, Mandal R, Guo AC, Wilson MR, Knox C, Bjorndahl TC, Krishnamurthy R, Saleem
F, Liu P, Dame ZT, Poelzer J, Huynh J, Yallou FS, Psychogios N, Dong E, Bogumil R, Roehring C, Wishart
DS. The human urine metabolome. PLoS One. 2013 Sep 4;8(9):e73076.
Response to Open Review regarding the “English language and Style”
The manuscript was copyedited by Prof. Dr. R.K. Arni to improve the readability of the
manuscript.

Reviewer 3 Report

The presented work deals with a complicated study on the metabolic pathways of Hella-cancer cells treated with Crotamine. The use of proton-NMR makes it even more complicated and one would be interested to read in this paper if any similar studies based on other methods, such as LCMS or similar, are available and whether any comparison can be provided.

I would suggest to the authors to reduce lengthy and irrelevant basic information, which doesn't contribute for better clarity. While metabolic pathways are interesting, it would be also relevant to compare the results from their NMR data analyses with similar studies employing other analytical methods.   

Therefore, I suggest minor revision of this manuscript before acceptance. I also attach a pdf-file with my comments - highlighted places where improvement is needed or crossed text, which will be better to be removed.

Comments for author File: Comments.pdf

Author Response

The presented work deals with a complicated study on the metabolic pathways of Hella-cancer cells
treated with Crotamine. The use of proton-NMR makes it even more complicated and one would be
interested to read in this paper if any similar studies based on other methods, such as LCMS or similar,
are available and whether any comparison can be provided.
Comment 1
I would suggest to the authors to reduce lengthy and irrelevant basic information, which doesn't
contribute for better clarity. While metabolic pathways are interesting, it would be also relevant to
compare the results from their NMR data analyses with similar studies employing other analytical
methods.
Response 1
Unfortunately, there are no metabolomic studies on the effect of Crotamine against HeLa cells or other
cell lines using Mass spectrometry or NMR spectroscopy. The following studies:
Citation 29: “Oral treatment with a rattlesnake native polypeptide crotamine efficiently inhibits the tumor
growth with no potential toxicity for the host animal and with suggestive positive effects on animal
metabolic profile”
Citation 46: “Crotamine induces browning of adipose tissue and increases energy expenditure in mice”
performed biochemical blood and urine tests to demonstrate an effect of crotamine on the glucose
metabolism, in which we have cited in the manuscript.
Comment 2
Therefore, I suggest minor revision of this manuscript before acceptance. I also attach a pdf-file with my
comments - highlighted places where improvement is needed or crossed text, which will be better to be
removed.
Response 2
Based on the suggestions of the reviewer, we performed the changes accordingly

Reviewer 4 Report

Coronado et al. have described the changes in metabolites upon crotamine treatment to cervical cancer model system HeLa cells. Their data is clear, showing crotamine adveresly effecting glycolysis which is the major means of cancer cell survival. It will be interesting to see whether crotamine also adversely affects glycolysis or oxphos in normal cervical cells, or in vivo using animal models. The data per se is interesting for the scientific community, and will likely instigate several follow up studies.

The authors can further improve the discussion section by suggesting links to each metabolite change with regards to the biochemical pathways, based on their data. The readers currently get lost by citation of other research work, which are not directly related to the current data presented.

Author Response

Comment 1
Coronado et al. have described the changes in metabolites upon crotamine treatment to cervical cancer
model system HeLa cells. Their data is clear, showing crotamine adveresly effecting glycolysis which is the
major means of cancer cell survival. It will be interesting to see whether crotamine also adversely affects
glycolysis or oxphos in normal cervical cells, or in vivo using animal models. The data per se is interesting
for the scientific community, and will likely instigate several follow up studies.
Response 1
Thank you for suggesting to investigate whether crotamine would affect normal cervical cells. This is
actually an interesting point and we would like to study it in a forthcoming paper. Unfortunately,
completing this for the presented paper would be time consuming, since crotamine would have to be
purified from crude venom. Even the venom itself would have to be purchased, and the whole process
would take a much longer time.
Comment 2
The authors can further improve the discussion section by suggesting links to each metabolite change with
regards to the biochemical pathways, based on their data. The readers currently get lost by citation of
other research work, which are not directly related to the current data presented.
Response 1
Thank you for the suggestion. We do believe that some metabolites have been correctly discussed using
our data and literature information. This is the case for Lactate (ranked #1 in figure 6), Threonine (ranked
#2), Glucose (ranked #3), Pyruglutamate (ranked #4), Tyrosine (ranked #5) and Acetate (ranked #15).
Concerning 1-methylhistidine, it is a challenge to evaluate their role and, as pointed out in the text, there
are only a few studies that deal with the role of this metabolite in cancer cells. Valine, Isoleucine and
Leucine are discussed altogether in regards to Branched-Chain Amino Acid (BCAAs). Their role on cancer
cells are remarkable, being essential nutrients for cancer growth. Discussion over pyruvate and formate
roles have been improved.
It is important to state, although, that our findings shed some light on the impact of crotamine in a cancer
cell line. Literature, up to now, has only described that crotamine is selective to high proliferating cells,
and, thus, may be studied to assess their impact on cancer. We have found what metabolic pathways are
affected and further studies may confirm if genes related to the described pathways are up or down
regulated in crotamine treated cells.

Round 2

Reviewer 1 Report

The authors answered most on my questions. 

I think the manuscript can be accepted 

Author Response

Thank you

Reviewer 2 Report

I would like to thank the authors for making changes in the revision. However, it is in my opinion that the authors have not adequately addressed the following points bought up in the earlier review:

1. I understand NMR is a common technique and appreciate the authors for explaining the basic of NMR in their discussion. However, Comment 1 is requesting the authors to provide necessary evidences, rationale, and explanation to convince the readers that the observed signals were due to secreted metabolites, but not due to other biomolecules eg. amino acids/proteins/peptides/extracellular crotamine?
2. With regards to Comment 2: I understand that in such experiments, especially after treatment with crotamine, there will be some cell death and appreciate the experiments to determine concentrations of crotamine and duration of treatment. However, did the authors considered that the decrease in the level of all the 15 metabolites identified was not due to the direct effect of crotamine but maybe due to the approximately 10% of cell death? What evidence or explanation the authors have that can convince the readers?
3. The supplement that the authors submitted appeared to be NMR data acquired which is not what I asked for. The authors should consider that these data has limited meaning to average readers of the journal. All that were needed would be NMR spectrum of the individual metabolites with appropriate assignments in .pdf format.
4. With regards to Comment 7: I understand LC-MS/MS may not be readily available but even other simple tests for a couple of metabolites eg. glucose & lactate could be easily performed without specialized equipment. Cross-validations even for just a sub-set of hits is in fact very commonly employed and would really improve the manuscript. I would suggest the authors consider to perform such assays.

Author Response

Please see the attachement.

Round 3

Reviewer 2 Report

I did not see any replies to my comments after reviewing the revised manuscript.

Author Response

Dear reviewer, sorry for the delay. The response to your questions and suggestions are now available. 

Comment 1. I understand NMR is a common technique and appreciate the authors for explaining the basic of
NMR in their discussion. However, Comment 1 is requesting the authors to provide necessary evidences,
rationale, and explanation to convince the readers that the observed signals were due to secreted metabolites,
but not due to other biomolecules eg. amino acids/proteins/peptides/extracellular crotamine?
The metabolites measured in the present study is the interplay of initial culture medium concentrations, cellular intake
and cellular secretome. As shown, under control conditions, metabolite concentrations follow a normal distribution,
indicating that medium preparation was handled correctly. Also, what is shown is that crotamine treated cells also
follow a normal distribution that is different (lower, in our findings). Thus, the effect of crotamine in HeLa cells
reduces the observed metabolite levels. The cited literature relates internal metabolism and available molecules in the
culture medium; therefore, we show the evidence of which metabolic pathways are affected by crotamine treatment.
Statistical testing also points that the observed differences are not by chance, at least in the 0,05% of confidence. It
is also important to state that proteins, even peptides (as crotamine), do not have the same signals in NMR spectra as
free amino acids. Due to relaxation issues of macromolecules, their signals are broader than free amino acids.
Comment 2. With regards to Comment 2: I understand that in such experiments, especially after treatment
with crotamine, there will be some cell death and appreciate the experiments to determine concentrations of
crotamine and duration of treatment. However, did the authors considered that the decrease in the level of all
the 15 metabolites identified was not due to the direct effect of crotamine but maybe due to the approximately
10% of cell death? What evidence or explanation the authors have that can convince the readers?
The selected crotamine levels and incubation time follows standard practices in the MTT assays. As always, cell
death plays a role in the observed outcome, but the selected parameters are set in order to associate the observed
effect to the treatment performed. It is hard to affirm that the total effect in reducing metabolites levels are due to
crotamine treatment only. Nevertheless, the main goal of our findings is to shed light into what metabolic pathways
are affected after crotamine incorporation. The cited literature also presents three information beforehand: 1)
crotamine is a cell penetrating peptide; 2) Crotamine is selective to high proliferating cells; 3) crotamine is found to
interact with DNA. Our goal was to find if crotamine interaction was disturbing some particular pathway or a more
general response.
Comment 3. The supplement that the authors submitted appeared to be NMR data acquired which is not what
I asked for. The authors should consider that these data has limited meaning to average readers of the journal.
All that were needed would be NMR spectrum of the individual metabolites with appropriate assignments in
.pdf format.
File attached in supplementary materials.
Comment 4. With regards to Comment 7: I understand LC-MS/MS may not be readily available but even
other simple tests for a couple of metabolites e.g. glucose & lactate could be easily performed without
specialized equipment. Cross-validations even for just a sub-set of hits is in fact very commonly employed and
would really improve the manuscript. I would suggest the authors consider to perform such assays.
Although we understand the request. Unfortunately, carrying out the experiments necessary to incorporate this
information would take much longer. Crotamine is no longer available in the lab, and the purchase of venom and
further purification is impossible to accomplish, at least in a reasonable time. We would like to point out that we
follow standard approaches as seen in the cited literature, where other techniques are not incorporated to validate the
results obtained.