Magnesium isoglycyrrhizinate alleviates alcohol-associated liver disease through targeting HSD11B1

Reviewer #1 (Public review):

Summary:

In this article by Xiao et al. the authors aimed to identify the precise targets by which magnesium isoglycyrrhizinate (MgIG) functions to improve liver injury in response to ethanol treatment. The authors found through a series of in-vivo and molecular approaches that MgIG treatment attenuates alcohol-induced liver injury through a potential SREBP2-IdI1 axis. The revised manuscript adds to a previous set of literature showing MgIG improves liver function across a variety of etiologies, and also provides mechanistic insight into its mechanism of action. All major weaknesses were addressed in the revised submission.

Strengths:

(1) The authors use a combination of approaches from both in-vivo mouse models to in-vitro approaches with AML12 hepatocytes to support the notion that MgIG does improve liver function in response to ethanol treatment.

(2) The authors use both knockdown and overexpression approaches, in-vivo and in-vitro, to support most of the claims provided.

(3) Identification of HSD11B1 as the protein target of MgIG, as well as confirmation of direct protein-protein interactions between HSD11B1/SREBP2/IDI1 is novel.

Weaknesses:

The authors addressed all my concerns.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors investigated magnesium isoglycyrrhizinate (MgIG)'s hepatoprotective actions in chronic-binge alcohol-associated liver disease (ALD) mouse models and ethanol/palmitic acid-challenged AML-12 hepatocytes. They found that MgIG markedly attenuated alcohol-induced liver injury, evidenced by ameliorated histological damage, reduced hepatic steatosis, and normalized liver-to-body weight ratios. RNA sequencing identified isopentenyl diphosphate delta isomerase 1 (IDI1) as a key downstream effector. Hepatocyte-specific genetic manipulations confirmed that MgIG modulates the SREBP2-IDI1 axis. The mechanistic studies suggested that MgIG could directly target HSD11B1 and modulate the HSD11B1-SREBP2-IDI1 axis to attenuate ALD. This manuscript is of interest to the research field of ALD.

Strengths:

The authors have performed both in vivo and in vitro studies to demonstrate the action of magnesium isoglycyrrhizinate on hepatocytes and an animal model of alcohol-associated liver disease.

Original comment (1):

In Supplemental Figure 1A, all the treatment arms (A-control, MgIG-25 mg/kg, MgIG-50 mg/kg) showed body weight loss compared to the untreated controls. However, Figure 1E showed body weight gain in the treatment arms (A-control and MgIG-25 mg/kg), why? In Supplemental Figure 1A, the mice with MgIG (25 mg/kg) showed the lowest body weight, compared to either A-control or MgIG (50 mg/kg) treatment. Can the authors explain why MgIG (25 mg/kg) causes bodyweight loss more than MgIG (50 mg/kg)? What about the other parameters (ALT, ALS, NAS, etc.) for the mice with MgIG (50 mg/kg)?

Author's response:

We agree that this observation does not strictly follow a dose-dependent pattern. In vivo responses to pharmacological interventions, particularly in metabolic and liver disease models, are not always linear. The relatively greater body weight reduction observed in the 25 mg/kg group may be influenced by inter-individual variability, differences in metabolic adaptation, or sample size-related variation. Importantly, these differences in body weight were not statistically significant. Therefore, we selected the 50 mg/kg dose for subsequent animal experiments, as it demonstrated more consistent and stable improvements across multiple parameters, including body weight, ALT, AST, TG, and TC.

New comment:

My first question: All the treatment arms (A-control, MgIG-25 mg/kg, MgIG-50 mg/kg) showed significant body weight loss compared to the untreated controls (Supplemental Figure 1A), but the body weight significantly increased in the treatment arms (A-control and MgIG-50 mg/kg) compared to the untreated controls (Figure 1E). Why?

My second question: Mice with MgIG (25 mg/kg) showed the lowest body weight, compared to either A-control or MgIG (50 mg/kg) treatment. According to the authors' explanation, the MgIG (25 mg/kg) caused bodyweight loss are attributed to inter-individual variability, differences in metabolic adaptation, or sample size-related variation. Did these differences happen in MgIG (25 mg/kg) only? or in all other groups? The mouse group assignment should be randomized; however, a large variation in bodyweight was seen in MgIG (25 mg/kg) group. It is not convincing for the author to select MgIG (50 mg/kg) group for subsequent animal experiments, because of a large variation in MgIG (25 mg/kg) group, and because that MgIG (50 mg/kg) group demonstrated more consistent and stable improvements across multiple parameters. The author should reanalyze and compare all the raw data between MgIG (50 mg/kg) group and MgIG (25 mg/kg) group, and address the issues being pointed out and justify rationale for the animal group assignment.

Original comment (2):

IL-6 is a key pro-inflammatory cytokine significantly involved in ALD, acting as a marker of ALD severity. Can the authors explain why MgIG 1.0 mg/ml shows higher IL-6 gene expression than MgIG (0.1-0.5 mg/ml)? Same question for the mRNA levels of lipid metabolic enzymes Acc1 and Scd1.

Author's response:

Thank you for this important comment. We agree that IL-6, as well as lipid metabolism-related genes such as Acc1 and Scd1, are key indicators in ALD. The relatively higher expression observed at 1.0 mg/mL MgIG compared to lower concentrations (0.1-0.5 mg/mL) may be related to experimental constraints associated with the MgIG formulation used in this study. Specifically, to maintain consistency with our in vivo experiments, we used a clinically available liquid formulation of MgIG (5 mg/mL), which is approved for intravenous administration in China. Due to its relatively low stock concentration, achieving higher working concentrations (e.g., 1.0 mg/mL) in vitro required a larger volume of the MgIG solution, thereby proportionally reducing the volume of culture medium. This reduction in effective culture conditions may adversely affect hepatocyte viability and function. Supporting this, our CCK-8 and LDH assays indicated that higher MgIG concentrations were associated with subtle cytotoxicity or impaired cell status.

New comment:

The author's response did not answer my question. If the authors believe it could be experimental constraints associated with the MgIG formulation, then it is questionable for this MgIG formulation used in all other associated experiments. The experiments, at least those the MgIG formulation associated experiments, need to be repeated.

Original comment (3):

For the qPCR results of Hsd11b1 knockdown (siRNA) and Hsd11b1 overexpression (plasmid) in AML-12 cells (Figure 5B), what is the description for the gene expression level (Y axis)? Fold changes versus GAPDH? Hsd11b1 overexpression showed non-efficiency (20-23, units on Y axis), even lower than the Hsd11b1 knockdown (above 50, units on Y axis). The authors need to explain this. For the plasmid-based Hsd11b1 overexpression, why does the scramble control inhibit Hsd11b1 gene expression (less than 2, units on the Y axis)? Again, this needs to be explained.

Author's response:

Thank you for this important comment, and we apologize for the lack of clarity in the Y-axis labeling, which may have led to misunderstanding.

As shown in Figures 5A and 5B, we have revised the Y-axis description to clearly indicate that gene expression levels are presented as relative expression normalized to GAPDH (fold change relative to the control group).

New comment:

The author explained the relative expression was normalized to GAPDH (fold change), but they did not answer my question. My question is for Figure 5B. in Figure 5B (left, Hsd11b1-KD), scramble control showed over 100 (unit), however, in Figure 5B (right, Hsd11b1-OE), scramble control showed only 0.5-1 (unit). The data seemed that authors used same scramble control for both KD and OE? If yes, they should provide more details of the KD and OE experiments and explain why this happened. If they used plasmid for OE control, they also need to clarify it. In addition, qPCR is not a good assay to show the success of KD or OE, Western blotting should be done as convincing data to show the success of KD or OE.

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public review):

(1) A few of the claims made are not supported by the references provided. For instance, line 76 states MgIG has hepatoprotective properties and improved liver function, but the reference provided is in the context of myocardial fibrosis.

Thank you for the correction. We have made the revision on page 4, line74.

(2) MgIG is clinically used for the treatment of liver inflammatory disease in China and Japan. In the first line of the abstract, the authors noted that MgIG is clinically approved for ALD. In which countries is MgIG approved for clinical utility in this space?

Thank you for this important comment. MgIG has been recommended for the treatment of alcoholic liver disease (ALD) in Chinese clinical guidelines (2018). We have clarified this point in the manuscript (Page 5, Line 79-80).

(3) Serum TGs are not an indicator of liver function. Alterations in serum TGs can occur despite changes in liver function.

Thank you for this important comment. We fully agree that serum triglycerides (TGs) are not a direct indicator of liver function. ALT and AST are more appropriate markers for hepatocellular injury, whereas TG and TC primarily reflect systemic and hepatic lipid metabolism status. We have made the necessary revisions as suggested on page 12, lines 285-288

(4) There are discrepancies in the results section and the figure legends. For example, line 302 states Idil is upregulated in alcohol fed mice relative to the control group. The figure legend states that the comparison for Figure 2A is that of ALD+MgIG and ALD only.

We thank the reviewer for the valuable suggestion. Accordingly, we have revised the legend for Figures 2A and 2B as suggested.

(5) Oil Red O staining provided does not appear to be consistent with the quantification in Figure 1D. ORO is nonspecific and can be highly subjective. The representative image in Figure 1C appears to have a much greater than 30% ORO (+) area.

Thank you for this insightful comment. We acknowledge that Oil Red O (ORO) staining can be influenced by background signal and may appear subjective in representative images. In our quantification, only well-defined lipid droplets with strong positive staining were included, while diffuse background staining (e.g., light reddish hue) was excluded. This may explain the apparent discrepancy between the representative image and the quantified ORO-positive area. To further strengthen the reliability of our findings, we additionally measured hepatic triglyceride (TG) and total cholesterol (TC) levels. These biochemical assays yielded results consistent with the ORO quantification, thereby supporting our conclusion regarding lipid accumulation. Please refer to page12, lines 285-288. As requested, we have added the required information to Figures 1G.

(6) The connection between Idil expression in response to EtOH/PA treatment in AML12 cells with viability and apoptosis isn't entirely clear. MgIG treatment completely reduces Idi1 expression in response to EtOH/PA, but only moderate changes, at best, are observed in viability and apoptosis. This suggests the primary mechanism related to MgIG treatment may not be via Idi1.

Thank you very much. We agree that although MgIG almost completely reverses Idi1 expression induced by EtOH/PA, the improvements in cell viability and apoptosis are only moderate, suggesting a potential discrepancy between these observations. This may indicate that Idi1 functions as a permissive factor, rather than the sole mediator, in this pathological process. In other words, while modulation of Idi1 contributes to the protective effects of MgIG, additional pathways are likely involved in mediating its overall impact on hepatocyte viability and apoptosis. We have clarified this point in the revised manuscript (Page 12, Lines 325–335), stating that MgIG exerts its protective effects against ethanol-induced hepatocellular injury, at least in part, through the regulation of Idi1.

(7) The nile red stained images also do not appear representative with its quantification. Several claims about more or less lipid accumulation across these studies are not supported by clear differences in nile red.

Thanks a lot. We acknowledge that Nile Red staining can be influenced by imaging conditions and may appear less distinct in representative images, which could affect visual interpretation. To minimize subjectivity, all images were analyzed using a consistent and standardized thresholding method across groups. We agree that the visual differences in Nile Red staining alone may not be sufficiently pronounced to fully support the quantitative conclusions. Therefore, to strengthen the reliability of our findings, we have included additional biochemical measurements, including serum TG and TC levels, as well as hepatic TG and TC content. These independent assays consistently support the observed changes in lipid accumulation. The corresponding data have been added to the revised manuscript (page 12, lines 285-288)

(8) The authors make a comment that Hsd11b1 expression is quite low in AML12 cells. So why did the authors choose to knockdown Hsd11b1 in this model?

Thank you for this important comment. Although the basal expression of Hsd11b1 in untreated AML-12 cells is relatively low, we observed that it is inducible upon EtOH/PA stimulation, indicating its functional relevance under stress conditions. Therefore, knockdown experiments were performed to assess its contribution to EtOH/PA-induced hepatocellular injury. We have clarified this point in the revised manuscript (page 15, lines 281-382).

(9) Line 380 - the claim that MGIG weakens the interaction between HSD11b1 and SREBP2 cannot be made solely based on one Western blot.

Thank you for this important comment. We agree that the conclusion that MgIG weakens the interaction between HSD11B1 and SREBP2 should not be based solely on a single co-IP/Western blot experiment. In the revised manuscript, we have therefore toned down this statement to more appropriately reflect the data. Specifically, we now describe this result as a preliminary observation suggesting a potential modulation of the interaction, rather than a definitive conclusion. Please refer to Page 15, line 391.

(10) It's not clear what the numbers represent on top of the Western blots. Are these averages over the course of three independent experiments?

Thank you for this helpful comment. We apologize for the lack of clarity in the original figure presentation. The numbers shown above the Western blot bands represent the densitometric quantification of protein expression normalized to GAPDH, calculated from three independent experiments. However, this information was not clearly specified in the original figure, which may have led to confusion. To address this concern, we have now revised the manuscript by explicitly clarifying the meaning of these values in the figure legends. In addition, we have added bar graphs showing the quantified results from three independent experiments for Figures S3A, S4D, S6B, and S8H to improve transparency and data presentation.

(11) The claim in line 382 that knockdown of Hsd11b1 resulted in accumulation of pSREBP2 is not supported by the data provided in Figure 6D.

Thank you for pointing out this issue. We sincerely apologize for the incorrect description in the original manuscript. This was a wording error. We have made the revision on page 15, line394-396.

(12) None of the images provided in Figure 6E support the claims stated in the results. Activation of SREBP2 leads to nuclear translocation and subsequent induction of genes involved in cholesterol biosynthesis and uptake. Manipulation of Hsd11b1 via OE or KD does not show any nuclear localization with DAPI.

Thank you for this important comment. We agree that the original description was not sufficiently clear, which may have led to misunderstanding of the results. To clarify, Figure 6E includes two experimental contexts. Under basal (physiological) conditions in AML-12 cells, manipulation of Hsd11b1 (overexpression or knockdown) does not significantly affect the subcellular distribution of SREBP2. However, under EtOH/PA-induced stress conditions, Hsd11b1 overexpression promotes both nuclear and cytoplasmic levels of SREBP2, whereas Hsd11b1 knockdown reduces SREBP2 expression in both compartments. We have made the revision on page 16, line399.

(13) The entire manuscript is focused on this axis of MgIG-Hsd11b1-Srebp2, but no Srebp2 transcriptional targets are ever measured.

We sincerely appreciate this great suggestion. We have made the necessary revisions as suggested on page 12, lines 285-288, line 292 by adding the mRNA changes of Lcn2 and Ldlr, which are SREBP2 target genes. As requested, we have added the required information to Figures 1F and 1H.

(14) Acc1 and Scd1 are Srebp1 targets, not Srebp2.

Thank you for this important comment. We agree that Acc1 and Scd1 are well-established downstream target genes of SREBP1 rather than SREBP2. To better support our proposed SREBP2-related mechanism, we further examined canonical SREBP2 downstream target genes, including Lcn2 and Ldlr. The results are consistent with activation of SREBP2 signaling in our model. These data have now been included in the revised manuscript (Page 12, Lines 285–288 and 292; Figures 1F and 1H).

(15) A major weakness of this manuscript is the lack of studies providing quantitative assessments of Srebp2 activation and true liver lipid measurements.

Thank you for this important comment. We acknowledge the concern regarding the lack of direct quantitative assessment of SREBP2 activation in the original version of the manuscript. To address this limitation, we have strengthened the evidence supporting SREBP2 activation using multiple complementary approaches. Specifically, we assessed the expression of canonical SREBP2 downstream target genes (Page 12, Lines 285–288 and 292; Figures 1F and 1H), together with Western blot analysis (Figure 6D) and immunofluorescence staining (Figure 6F), which collectively support activation of SREBP2 signaling in the EtOH/PA-induced ALD model.

In addition, to provide a more comprehensive evaluation of hepatic lipid accumulation, we measured serum TG and TC levels, as well as hepatic TG and TC content. These biochemical analyses further confirm the presence of significant lipid accumulation in our model. We have made the necessary revisions as suggested on page 12, lines 285-288 (Figure 1G).

Reviewer #2 (Public review):

(1) In Supplemental Figure 1A, all the treatment arms (A-control, MgIG-25 mg/kg, MgIG-50 mg/kg) showed body weight loss compared to the untreated controls. However, Figure 1E showed body weight gain in the treatment arms (A-control and MgIG-25 mg/kg), why? In Supplemental Figure 1A, the mice with MgIG (25 mg/kg) showed the lowest body weight, compared to either A-control or MgIG (50 mg/kg) treatment. Can the authors explain why MgIG (25 mg/kg) causes bodyweight loss more than MgIG (50 mg/kg)? What about the other parameters (ALT, ALS, NAS, etc.) for the mice with MgIG (50 mg/kg)?

We agree that this observation does not strictly follow a dose-dependent pattern. In vivo responses to pharmacological interventions, particularly in metabolic and liver disease models, are not always linear. The relatively greater body weight reduction observed in the 25 mg/kg group may be influenced by inter-individual variability, differences in metabolic adaptation, or sample size–related variation. Importantly, these differences in body weight were not statistically significant. Therefore, we selected the 50 mg/kg dose for subsequent animal experiments, as it demonstrated more consistent and stable improvements across multiple parameters, including body weight, ALT, AST, TG, and TC.

(2) IL-6 is a key pro-inflammatory cytokine significantly involved in ALD, acting as a marker of ALD severity. Can the authors explain why MgIG 1.0 mg/ml shows higher IL-6 gene expression than MgIG (0.1-0.5 mg/ml)? Same question for the mRNA levels of lipid metabolic enzymes Acc1 and Scd1.

Thank you for this important comment. We agree that IL-6, as well as lipid metabolism–related genes such as Acc1 and Scd1, are key indicators in ALD. The relatively higher expression observed at 1.0 mg/mL MgIG compared to lower concentrations (0.1–0.5 mg/mL) may be related to experimental constraints associated with the MgIG formulation used in this study.

Specifically, to maintain consistency with our in vivo experiments, we used a clinically available liquid formulation of MgIG (5 mg/mL), which is approved for intravenous administration in China. Due to its relatively low stock concentration, achieving higher working concentrations (e.g., 1.0 mg/mL) in vitro required a larger volume of the MgIG solution, thereby proportionally reducing the volume of culture medium. This reduction in effective culture conditions may adversely affect hepatocyte viability and function.

Supporting this, our CCK-8 and LDH assays indicated that higher MgIG concentrations were associated with subtle cytotoxicity or impaired cell status.

(3) For the qPCR results of Hsd11b1 knockdown (siRNA) and Hsd11b1 overexpression (plasmid) in AML-12 cells (Figure 5B), what is the description for the gene expression level (Y axis)? Fold changes versus GAPDH? Hsd11b1 overexpression showed non-efficiency (20-23, units on Y axis), even lower than the Hsd11b1 knockdown (above 50, units on Y axis). The authors need to explain this. For the plasmid-based Hsd11b1 overexpression, why does the scramble control inhibit Hsd11b1 gene expression (less than 2, units on the Y axis)? Again, this needs to be explained.

Thank you for this important comment, and we apologize for the lack of clarity in the Y-axis labeling, which may have led to misunderstanding.

As shown in Figures 5A and 5B, we have revised the Y-axis description to clearly indicate that gene expression levels are presented as relative expression normalized to GAPDH (fold change relative to the control group).

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

(1) Use terms that show directionality to help the readers comprehend the data. For instance, Line 295 states MgIG treatment also modulated the expression.... In reality, MgIG treatment reduced the expression of those genes relative to ethanol-fed control mice.

Thank you very much for this precious suggestion. We have thoroughly revised this part as ‘In line with the observed histological and physiological improvements, MgIG treatment also reduced the expression of genes involved in lipid synthesis metabolism (Srebp1, Srebp2, Acc1, and Scd1, Lcn2, and Ldlr), inflammation (Tnf-α and Il-6), and pro-apoptosis (Bax) while restored the level of anti-apoptotic gene (Bcl2) in the liver tissue of EtOH mice (Fig. 1G-1H).’. Please refer to page 12, lines 290-294.

(2) Oil Red O staining is subjective and nonspecific. The authors make a claim that serum TGs are an indicator of liver function; however, measurement of hepatic TGs would be a better measure here and more consistent with the ORO staining.

We sincerely appreciate this great suggestion. We have made the necessary revisions as suggested on page 12, lines 285-288 as ‘Notably, significant differences were observed between the EtOH group and the MgIG-treated (EtOH+M) group in serum levels of liver enzymes (ALT and AST), serum lipid parameters (TG and TC), as well as Liver TG and TC contents—-key indicators of liver function and lipid metabolism.’. As requested, we have added the required information to Figures 1G.

(3) The focus of the paper is on this SREBP2 axis. However, in Figure 1, the authors do not show any SREBP2 target genes. This would be helpful in interpreting SREBP2 activity. Further, hepatic free cholesterol levels would also strengthen these data.

We sincerely appreciate this great suggestion. We have made the necessary revisions as suggested on page 12, lines 285-288, line 292 by adding the mRNA changes of Lcn2 and Ldlr, which are SREBP2 target genes. As requested, we have added the required information to Figures 1F and 1H.

(4) Labels showing directionality on the volcano plots in Figures 2A, B would be of great help here. It's unclear which groups are on the left or right.

Thank you very much! The authors have revised Figures 2A-C as requested. Please refer to the new version of Figures 2A-C.

(5) Ensure consistency in what is written in the results and the figure legends. See Figure 2 volcano plots for examples. The volcano plot in Figure 2B has no figure legend.

We thank the reviewer for the valuable suggestion. Accordingly, we have revised the legend for Figures 2B as suggested.

(6) Ensure consistency in the nomenclature. In some cases, the authors use ALD+MgIG, and in others, they just use MgIG. My recommendation would be to use Ctrl, EtOH, EtOH+M.

We sincerely appreciate this great suggestion. We have made the necessary revisions as suggested on page 6, lines 111-112, page 11, line 280 and page 12, line 282, 284, 293, 298, 301.

(7) The gene enrichment analysis in Figure 2C should also include some text about directionality, either in the figure or the figure legend. Upregulated DEGs in the MgIG group? It's unclear.

We thank the reviewer for the valuable suggestion. Accordingly, we have revised the legend for Figures 2C as suggested.

(8) The authors should consider shuffling the order of some of the figures for better transitions from one panel to the next. For instance, Figure 3B, C shows cell viability responses before showing the siRNA and OE are effective in knocking down and overexpressing their protein of interest.

We thank the reviewer for the valuable suggestion. Accordingly, we have revised the legend for Figures 3B and 3C as suggested.

(9) The authors need to be consistent in the colors that are used in the figures. It's incredibly hard to follow, as presented.

We appreciate the reviewer's comment regarding color consistency. In response, we have carefully revised all figures to ensure consistent use of colors across the manuscript. The updated versions are shown in Figures 3, 6, and 7.

(10) For Nile Red staining, multiple images at a lower objective need to be shown and/or cellular triglycerides and cholesterol levels should be quantified.

We appreciate the reviewer's insightful comment regarding the Nile Red staining. In response, we have quantified triglyceride and total cholesterol levels in the cell supernatant, which are now presented on page 12, line 285-287 and Figures 2F. Furthermore, we have included additional Nile Red staining images at a lower objective in Supplementary Figures 2D, 3B, 4C to better illustrate the lipid droplet distribution.

(11) Line 362 refers to Figure 4 when it should refer to Figure 5.

Thank you very much! The authors have revised on page 14, line 364.

(12) qPCR should be performed on canonical Srebp2 targets throughout the manuscript to tie in the MgG treatment with changes in sterol sensing and Srebp2.

Thank you for your valuable suggestion. The results are now included on page 12, lines 292 and 311, and the corresponding data in Figures 1H and 2G have been enhanced accordingly.

Reviewer #2 (Recommendations for the authors):

(1) The statement, figure labeling, and figure legend for Figure 1A-C are confused. The MgIG dosing on the X-axis for Figure 2D is missing.

Thank you for the correction. We have revised this problem. Please refer to the new version of Figure 1A-C and Figure 2D.

(2) Figure 3E is not well described in the main text and figure legend. What are those numbers on top of the blotting bands? It was guessed that the numbers were the mean for each group. But where is the SD or SE for each group? It is hard to tell the statistical significance without showing SD or SE. The same question applies to Figure 5E, Figure 56C-6D, and Figure 7G.

We sincerely appreciate this great suggestion. We have made the necessary revisions as suggested on page 13, lines 317-322. As suggested, we have added the required information to Figures S3A, S4D, S6B and S8H.