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Review 3: "Protein arginylation is regulated during SARS-CoV-2 infection"

This preprint looks at how SARS-CoV-2 infection modulates arginylation, a modification that tags proteins for degradation, and finds a specific arginylation signature in some cell types. The reviewers found the claims potentially informative.

Published onFeb 09, 2022
Review 3: "Protein arginylation is regulated during SARS-CoV-2 infection"
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key-enterThis Pub is a Review of
Protein arginylation is regulated during SARS-CoV-2 infection
Description

ABSTRACTIn 2019, the world witnessed the onset of an unprecedented pandemic. In September 2021, the infection by SARS-CoV-2 had already been responsible for the death of more than 4 million people worldwide. Recently, we and other groups discovered that SARS-CoV-2 infection induces ER-stress and activation of unfolded protein response (UPR) pathway. The degradation of misfolded/unfolded proteins is an essential element of proteostasis and occurs mainly in lysosomes or proteasomes. The N-terminal arginylation of proteins is characterized as an inducer of ubiquitination and proteasomal degradation by the N-end rule pathway. Here we present, for the first time, data on the role of arginylation during SARS-CoV-2 infection. We studied the modulation of protein arginylation in Vero CCL-81 and Calu-3 cells infected after 2h, 6h, 12h, 24h, and 48h. A reanalysis of in vivo and in vitro public omics data combined with immunoblotting was performed to measure the levels of ATE1 and arginylated proteins. This regulation is seen specifically during infections by coronaviruses. We demonstrate that during SARS-CoV-2 infection there is an increase in the expression of the ATE1 enzyme associated with regulated levels of specific arginylated proteins. On the other hand, infected macrophages showed no ATE1 regulation. An important finding revealed that modulation of the N-end rule pathway differs between different types of infected cells. We also confirmed the potential of tannic acid to reduce viral load, and furthermore, to modulate ATE1 levels during infection. In addition, the arginylation inhibitor merbromin (MER) is also capable of both reducing viral load and reducing ATE1 levels. Taken together, these data show the importance of arginylation during the progression of SARS-CoV-2 infection and open the door for future studies that may unravel the role of ATE1 and its inhibitors in pathogen infection.

RR:C19 Evidence Scale rating by reviewer:

Not informative. The flaws in the data and methods in this study are sufficiently serious that they do not substantially justify the claims made. It is not possible to say whether the results and conclusions would match that of the hypothetical ideal study. The study should not be considered as evidence by decision-makers.

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Review:

I believe that the paper entitled “Protein arginylation is regulated during SARS-CoV-2 infection” needs significant corrections and additional experiments before publication.

  1. Page 9, last sentence: I agree with a similar expression pattern of potential arginylated-proteins, but it is unclear why the author chose the various cell types.  For example, the Vero E6 cell line is from monkey kidney tissue, and Caco-2 is from the human colon.  The relationship between these cell lines or the reasoning behind their selection should be explained in the manuscript.  If the author chose these based on the available datasets, please explain this limitation in the manuscript.  Also, the last words ‘Green Monkey and Human’ should be changed to ‘human (Green) and monkey (Yellow).


  2. Figure 2 micrograph B:  Please replace the western blots provided.  The current blots shown are of low quality and not fully convincing.  For instance, the 24 hour time point in the Calu-3 blot seems significantly down-regulated even compared with the GAPDH level.  Analysis with software such as ImageJ would be helpful to see the actual pattern of ATE1 expression, but given the poor quality of these blots, accurate results may be hard to obtain.


  3. Page 11, last paragraph:  According to the argument, Calu-3 cells are less susceptible to infection, but what evidence supports this?  For Figure S1, micrographs A and B,  please add size markers on western blot results.  Please ensure the minimal size marker, at least >140kDa, for showing poly-ubiquitination. 


  4. The authors mentioned that SARS-Cov-2 infection induces ER stress, but BiP, a representative marker/indicator of ER stress, was not upregulated as expected.  Furthermore, the authors’ claim that SARS-Cov-2 infection upregulated arginylated BiP is not supported by the data shown in Figure 4. Western blots showing arginylated ER chaperones (BiP, CALR, and PDI) need an ATE1 knockdown control proving that the antibodies detect the chaperones’ arginylated form.


  5. Page 19, Figure 6:  The western blot labeling is missing.  This problem is repeated in Figure 7.  In addition, the poor quality of the western blots and contrast manipulation make interpretation difficult when scanning for quantification.   Visually there seems to be no difference between the infected 24h sample and the infected t.acid 24h sample in terms of ATE1 expression, but the quantification shows a drastic decrease.  Why does the ATE1  quantification show a drastic increase in ATE1 expression in the tannic acid control compared with the normal untreated control?  Looking at the blot, the GAPDH for the untreated control is magnitudes less than the tannic acid control, and the difference is greater than the difference in ATE1 bands for these samples.  The expected quantification result would be a similar ATE1 expression between the untreated and tannic acid controls.  This calls into question the quantification methods being used to quantified these blots and the conclusion being drawn.  There are similar issues with the other blots. 


  6. There is no direct evidence that both Tannic acid and Merborin are specific inhibitors of ATE1.  Therefore, in addition to these inhibitors, ATE1 RNA interference using either siRNA or shRNA should be used to determine ATE1’s specific influence on viral load. 

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