Arginase 1 promotes hepatic lipogenesis by regulating ERK2/PPARγ signaling in a non-canonical manner

Domain: chemistry
Published: 2026-02-18
Editorial outcome: major_revision

Abstract
Obesity and related metabolic disorders, including metabolic dysfunction-associated steatohepatitis (MASLD), have reached epidemic proportions worldwide. We unveil a previously unknown moonlighting role for arginase 1 (Arg1) in facilitating hepatic lipogenesis. Male mice lacking hepatic Arg1 exhibit diminished lipid accumulation in both liver and adipocytes, an effect mirrored in genetically- or diet-induced obesity models following Arg1 inhibitor treatment. Mechanistically, Arg1 competes with RSK2 and Elk1 for binding to the substrate-binding pocket of extracellular signal-regulated kinase 2 (ERK2) via its S-shaped motif, thereby enhancing ERK2 ubiquitination and degradation and upregulating the AKT/mTOR/PPARγ and Elk1/c-Fos/PPARγ cascades, ultimately augmenting lipogenesis. Peptides designed to mimic the ERK2 substrate-binding pocket disrupt the Arg1-ERK2 interaction and improve metabolic profiles in obesity and MASLD models. Our findings implicate Arg1 regulates hepatic lipid metabolism via its physical interaction with ERK2, highlighting the Arg1-ERK2 interaction as a promising therapeutic target for obesity and related metabolic disorders in male mice.

Introduction
Obesity and its associated metabolic disorders, including metabolic dysfunction-associated steatotic liver disease (MASLD), type 2 diabetes (T2DM), and cardiovascular disease, have emerged as global health crises with escalating prevalence1–5. MASLD, a spectrum disorder ranging from simple steatosis (MAFLD) to metabolic dysfunction-associated steatohepatitis (MASH), poses a particularly severe threat due to its potential progression to advanced fibrosis, cirrhosis, and hepatocellular carcinoma (HCC)1,6. This condition is closely intertwined with systemic metabolic dysregulation, such as insulin resistance and cardiometabolic comorbidities4–6. Despite recent therapeutic advances—including the FDA approval of resmetirom (the first MASH-specific drug)7 and several T2DM/obesity medications (e.g., pioglitazone, GLP-1 receptor agonizts)8,9—a critical gap remains: no pharmacotherapies are directly approved for MASLD, largely due to an incomplete understanding of its initiation and progression mechanisms.

Arginase, primarily existing as arginase 1 (Arg1) in mammals, is a cytoplasmic enzyme predominantly expressed in hepatocytes. Its canonical function is catalyzing the conversion of L-arginine to L-ornithine and urea, a critical step in the urea cycle for ammonia detoxification10. Children with congenital deficiency of Arg1 exhibit hyperargininemia, accompanied by spastic paraparesis, progressive neurological and intellectual deficits, and, notably, persistent growth retardation11. Beyond its classical role, accumulating evidence suggests that Arg1 could act as both a candidate biomarker and a regulator in obesity and MASLD. For instance, circulating Arg1 levels are significantly elevated in overweight individuals compared to normal-weight controls10,12, likely due to increased exosomal Arg1 release12. Moreover, upregulated hepatic Arg1 expression contributes to vascular endothelial dysfunction in early obesity13,14. Mechanistically, Arg1 may influence lipid metabolism through both its canonical urea cycle function and its role in polyamine synthesis (e.g., putrescine, spermidine) derived from its metabolite ornithine15,16. Polyamines, critical for fat metabolism, are secreted by cells to interact with adipocytes, promoting adipose tissue vascularization and lipolysis17,18. Spermidine, for example, enhances cAMP production (the second messenger of β-adrenergic receptors), thereby augmenting lipolysis18. By facilitating lipolysis and angiogenesis, polyamines help maintain white adipose tissue (WAT) homeostasis, potentially preventing obesity and insulin resistance18. Conversely, in the alternative L-arginine metabolic pathway, Arg1 competes with nitric oxide synthase (NOS) for the shared substrate L-arginine19. NOS metabolizes L-arginine into nitric oxide (NO) and L-citrulline, and an imbalance between Arg1 and NOS can disrupt NO production, leading to reactive oxygen species (ROS) accumulation—a key driver of MASLD progression20,21. Supplementation with L-arginine has been shown to mitigate hepatic inflammation in a methionine-choline-deficient (MCD) diet-induced mouse model, via NOS-mediated elevation of NO production22. These observations suggest that Arg1 may influence obesity/MASLD development by modulating polyamine- or NO-mediated pathways, though the exact mechanisms remain underexplored.

Obesity, characterized by excessive adipose tissue accumulation, arises from dysregulation of signaling pathways critical for metabolic homeostasis, such as phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT), mitogen-activated protein kinase (MAPK), and AMP-activated protein kinase (AMPK)23–25. Among these, the PI3K/AKT pathway plays a dual role in adipose tissue: enhancing lipid biogenesis while inhibiting lipid degradation23. In the liver, AKT stimulates lipogenesis via the mammalian target of rapamycin (mTOR), which upregulates peroxisome proliferator-activated receptor gamma (PPARγ)—a key transcription factor driving adipogenesis26,27. AKT also regulates hepatic lipogenesis through mTOR-independent pathways25–27.

The MAPK pathway, another critical metabolic regulator, maintains lipid homeostasis by modulating enzymes and transcription factors involved in fatty acid synthesis and catabolism25,27. Notably, the MAPK family, particularly ERK, p38, JNK, and BMK1, represents a highly conserved group of serine-threonine kinases28. Among them, the ERK1/ERK2 kinases have garnered significant attention due to their extensive involvement in diverse physiological and pathological processes. Upon Ras/Raf/MEK-dependent activation, ERK2 undergoes phosphorylation and translocates to the nucleus, where it phosphorylates a suite of transcription factors—including Elk1, ETS, c-Fos, Jun, and Myc—thereby initiating downstream responses that govern cellular processes such as proliferation, differentiation, and metabolic reprogramming29–31.

The MAPK and PI3K/AKT pathways intersect intricately, often sharing upstream regulators and engaging in cross-regulatory interactions25,28. For example, upon glucose stimulation, insulin binds to its receptor, triggering phosphorylation and activation of insulin receptor substrate-1 (IRS-1). Activated IRS-1 subsequently activates the PI3K/AKT signaling pathway, which enhances glucose utilization and storage in hepatocytes through glycogen synthesis promotion and gluconeogenesis inhibition. However, sustained high glucose intake enhances AKT-mediated activation of the MAPK pathway, particularly affecting ERK2 (MAPK1). Excessive ERK2 activation phosphorylates IRS-1 at serine residues (e.g., Ser636/639), further inhibiting IRS-1 binding to insulin receptors. This severely disrupts normal PI3K/AKT pathway function and ultimately reduces insulin-stimulated glucose utilization efficiency32. These mechanisms collectively contribute to insulin resistance development and type 2 diabetes mellitus (T2DM). This interplay is particularly relevant to obesity, where insulin resistance exacerbates metabolic dysfunction.

Arg1, transcriptionally regulated by STAT633, is intricately linked to these pathways. For instance, AKT can modulate STAT6 activation34, potentially indirectly regulating Arg1 expression. PPARγ is a nuclear hormone receptor known to govern lipid metabolism in hepatocytes and adipocytes35,36, can also modulate Arg1: PPARγ activators specifically regulate Arg1 expression and activity in macrophages37. In the liver, PPARγ promotes fatty acid synthesis, free fatty acid uptake, and triglyceride accumulation38,39, further linking Arg1 to lipid metabolic dysregulation.

In this study, we uncover a “moonlighting” function of Arg1 beyond its canonical role in L-arginine metabolism: Arg1 physically interacts with ERK2 (a key MAPK kinase) through its S-shaped motif, competing with RSK2 and Elk1 for binding to ERK2’s substrate-binding pocket. This competition enhances ERK2 ubiquitination and degradation, thereby upregulating both the AKT/mTOR/PPARγ and Elk1/c-Fos/PPARγ signaling cascades, ultimately promoting lipogenesis. Targeting the Arg1-ERK2 interaction represents a promising therapeutic strategy for obesity and MASLD.

Results
Disruption of Arg1 reduces lipid accumulation in hepatocytes and adipocytes
To delve into the role of hepatic Arg1 in vivo in modulating hepatic lipid metabolism, we generated liver-specific Arg1 knockout mice using the Alb-Cre-loxP system (AlbcreArg1fl/fl; Supplementary Fig. S1A–D). Postnatally, the AlbcreArg1fl/fl mice began to display characteristic symptoms of Arg1 deficiency, including lethargy, sluggish movement, and growth retardation, culminating in a 52% mortality rate within the first four weeks (Supplementary Fig. S1E). Consequently, only mice that survived until eight weeks were chosen for subsequent experimentation. Despite exhibiting no significant difference in food intake (Supplementary Fig. S1F), the AlbcreArg1fl/fl mice notably had lower body weight and size compared to their same-sex littermate controls (Supplementary Fig. S1G, H). Although the hepatic lobular structure, zonation, and glycogen synthesis appeared relatively normal, as evidenced by H&E (hematoxylin and eosin) staining, immunohistochemistry (IHC) staining for glutamine synthetase (GS) and cytokeratin 19 (CK19), and periodic acid-Schiff (PAS) staining, respectively (Supplementary Fig. S1C), the ablation of Arg1 led to a marked decrease in liver size, weight, and hepatocyte size (highlighted by IHC staining for β-catenin) (Supplementary Fig. S1I–K). Strikingly, hepatocytes in Arg1fl/fl mice, which remained intact Arg1 expression and served as a wild type control, contained uniformly distributed fine lipid droplets. In contrast, these lipid droplets were scarcely observed in the hepatocytes from AlbcreArg1fl/fl mice, as revealed by oil red O staining (Supplementary Fig. S1K). Furthermore, this deletion also induced mild liver injury, manifested by slightly elevated serum enzyme levels (Supplementary Fig. S1L).

The liver primarily synthesizes TG, which is then transported into and stored in adipose tissue for future energy use. We observed that AlbcreArg1fl/fl mice had a significantly reduced mass of adipose tissue in the visceral adipose tissue (VAT) region, encompassing the epididymal fat, renal fat capsules, and mesenteric adipose tissue, compared to Arg1fl/fl mice (Supplementary Fig. S2A). This finding was corroborated by a microcomputed tomography (micro-CT) scan, which captured abdominal fat accumulation at the level of the fourth lumbar vertebra and revealed a marked decrease in the volume of both VAT and subcutaneous adipose tissue (SAT) in the Arg1-deficient mice (Supplementary Fig. S2B). This was further substantiated by the weight of the collected VAT and SAT, revealing that the Arg1-deficient mice had less than one-sixth of the adipose fat and a significantly reduced ratio of fat tissue weight to body weight compared to the control mice (Supplementary Fig. S2C). Histological analysis revealed that adipocytes in AlbcreArg1fl/fl mice were significantly smaller in size compared to those in control mice (Supplementary Fig. S1D). In addition, Arg1-deficiency resulted in a notable decrease in both serum and liver tissue levels of TG and FFA (Supplementary Fig. S2E, F). Consistent with these observations, the livers of AlbcreArg1fl/fl mice exhibited a marked downregulation of genes involved in fatty acid synthesis, particularly those in the PPARγ pathway, including PPARγ itself and its downstream targets such as SREBP1, FASN, CD36, and AP2, as evidenced by both western blotting and quantitative PCR analysis (Supplementary Fig. S2G, H). Since male and female Arg1-deficient mice displayed comparable phenotypic profiles in survival, development, growth, and lipid metabolism regulation, and given the established role of sex hormones in modulating lipid metabolic processes, we opted to utilize exclusively male mice for subsequent experimental analyses.

To eliminate the toxic effect of hyperargininemia on the early development, growth, and fat metabolism of mice, we established an inducible Arg1-knockout mouse model designated as TBGcreArg1fl/fl. This was achieved by administering AAV8-TBG-Cre via tail vein injection to adult Arg1fl/fl mice (Fig. 1A). Four weeks after injection, the TBGcreArg1fl/fl mice exhibited normal behavior and did not show any signs of mortality or liver damage, as evidenced by normal levels of ALT and AST (Fig. 1B). Similar to the AlbcreArg1fl/fl mice, the TBGcreArg1fl/fl mice displayed a decrease in body weight, liver weight, and lipid accumulation in both the liver and adipose tissue (Fig. 1C–J). In addition, there was a reduction in the levels of TG and FFA in both the serum and liver (Fig. 1K). Notably, the inducible deficiency of Arg1 led to a profound downregulation of the expression of PPARγ, FASN, and SREBP1 (Fig. 1L).

To exclude the possibility that the metabolic phenotypes observed in Arg1-deficient mice—particularly reduced abdominal fat accumulation—were caused by systemic imbalances in energy expenditure or intake, we conducted metabolic cage experiments. These experiments revealed no significant differences in food intake, oxygen consumption (VO₂), carbon dioxide production (VCO₂), or energy expenditure between TBGcreArg1fl/fl mice and Arg1fl/fl mice (Supplementary Fig. S3).

Although serum L-arginine levels in the inducible Arg1-deficient mice were significantly lower than those in AlbcreArg1fl/fl mice, they remained markedly elevated compared to baseline levels in WT controls (Fig. 1M). To further investigate the impact of Arg1 inhibition on lipid metabolism without the interference of high L-arginine concentration, we treated cultured mouse AML12 hepatocytes with the arginase inhibitor S-(2-bromoethyl)-L-cysteine (BEC). The tetrahedral BEC boronate anion mimics the tetrahedral intermediate stage of the L-arginine hydrolysis reaction, enabling it to bind tightly to the arginase active site (Fig. 2A)40. This ultimately results in the formation of an enzyme-inhibitor complex, thereby impeding arginase activity. AML12 hepatocytes, when treated with oleic acid (OA), exhibited a significant increase in both the number and size of lipid droplets. However, BEC treatment dramatically reduced this lipid droplet accumulation (Supplementary Fig. S4A). In parallel, we observed a decrease in the protein levels of PPARγ, FASN, and SREBP1 (Supplementary Fig. S4B).

Arg1 disruption protects against genetically- or diet-induced obesity and MASLD
We next evaluated the in vivo function of BEC on lipid metabolic regulation. We noted that BEC treatment significantly reduced L-arginine consumption in cultured cells (Supplementary Fig. S4C), potentially leading to L-arginine accumulation in the animals. We subsequently administered BEC to db/db mice (Fig. 2B). Db/db mice (leptin-deficient, a well-established model for severe obesity and metabolic dysfunction) were selected for in vivo studies because they compensate by elevating L-arginine consumption to achieve cardioprotection, making them an ideal model for studying the effects of Arg1 inhibition41. In addition, since leptin itself possesses pro-fibrotic properties (e.g., by activating hepatic stellate cells), leptin signaling deficiency in db/db mice results in the development of simple fatty liver without fibrosis progression. We initiated BEC treatment in db/db mice at 8 weeks of age and continued the treatment for 4 weeks. BEC treatment significantly suppressed body weight gain, resulting in a final body weight that was approximately two-thirds of that observed in untreated mice (Fig. 2C and Supplementary Fig. S4D). Moreover, BEC-treated mice displayed a remarkable reduction in lipid accumulation in the liver and adipose tissue, accompanied by decreased adipocyte size, reduced serum and hepatic TG and FFA levels, and downregulated expression of PPARγ, FASN, and SREBP1 (Fig. 2D–G and Supplementary Fig. S4E–J). Notably, BEC treatment did not alter serum L-arginine levels (Fig. 2H), possibly due to excessive L-arginine consumption by other tissues.

To investigate whether Arg1 disruption plays a role in improving diet-induced obesity and fatty liver, we initiated a 12-week high-fat diet (HFD) regimen for both the TBGcreArg1fl/fl mice and Arg1fl/fl mouse model (Fig. 2I). Notably, the TBGcreArg1fl/fl mice demonstrated a marked reduction in body weight and liver size compared to their Arg1fl/fl counterparts (Fig. 2J, K and Supplementary Fig. S4K, L). Moreover, these mice displayed a significantly diminished accumulation of lipids in both the liver and adipose tissue, along with decreased serum and hepatic concentrations of TG and FFA (Fig. 2L–O and Supplementary Fig. S4M–P).

In contrast to HFD-induced obesity-associated MASLD, which manifests as prominent macrovesicular steatosis in the liver along with a marked increase in both body weight and visceral fat mass (Fig. 2L), mice subjected to a methionine- and choline-deficient (MCD) diet typically exhibit an earlier onset of steatosis and inflammatory cell infiltration in the liver. Paradoxically, however, this is accompanied by a decrease in body weight. To investigate this further, we administered MCD to TBGcreArg1fl/fl mice (Fig. 2P). After two weeks of MCD administration, Arg1fl/fl mice exhibited a drastic exacerbation of liver steatosis, characterized by an enlarged liver size, increased weight, and a yellowish, oily appearance (Fig. 2Q and Supplementary Fig. S4Q). This was further substantiated histologically by the presence of macrovesicular steatosis, hepatocellular ballooning, and frequent infiltration of inflammatory cells, as evidenced by an immunohistochemistry staining for the pan-leukocyte marker CD45 (Fig. 2R). Notably, the ablation of Arg1 led to a significant improvement in liver histology (Fig. 2Q, R). Consistent with this, serum and hepatic levels of TG and FFA were also markedly lower in TBGcreArg1fl/fl mice (Supplementary Fig. S4R). In addition, proteins involved in lipogenesis were decreased in response to Arg1 ablation (Supplementary Fig. S4S).

Deficiency of Arg1 downregulates the AKT/mTOR/PPARγ signaling pathway
Our findings suggest that disruption of hepatic Arg1 has the potential to ameliorate genetic- or diet-induced obesity and MASLD by inhibiting the PPARγ pathway. Importantly, this effect appears to be independent of hyperargininemia and is specifically attributable to the inhibition of Arg1 itself. To further elucidate the mechanism underlying Arg1’s regulation of lipid metabolism in hepatocytes, we conducted RNA sequencing analysis on liver tissues from TBGcreArg1fl/fl and Arg1fl/fl mice. The resulting heatmap revealed that genes targeted by PPARγ or those involved in adipogenesis regulation were among the most downregulated in TBGcreArg1fl/fl liver (Fig. 3A, B). This observation was further corroborated by gene set-enrichment analysis (GSEA), which demonstrated a marked inhibition of PPARγ target gene expression in hepatocytes from TBGcreArg1fl/fl mice compared to controls (Fig. 3C). Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that Arg1 deficiency significantly inhibited the PI3K/AKT signaling pathways (Fig. 3D). PI3K/AKT/mTOR signaling cascade plays a pivotal role in balancing lipogenesis and oxidation by modulating the PPARγ pathways, specifically via phosphorylation of mTOR, ultimately enhancing the uptake of FFA and promoting TG accumulation42. Consistent with the observed decrease in PPARγ expression in the TBGcreArg1fl/fl liver, there was a corresponding reduction in the protein levels of hepatic p-AKT, p-mTOR, as well as its downstream proteins p70-S6K and p-4E-BP (Fig. 3E). These findings were further substantiated in AlbcreArg1fl/fl mice and db/db mice treated with BEC (Supplementary Fig. S5A, B). In addition, knocking down the Arg1 gene in AML12 cells using a small-interfering RNA specifically targeting Arg1 (siArg1) attenuated lipid droplets and suppressed the AKT/mTOR/PPARγ signaling pathway (Fig. S5C–E).

We conducted a further analysis of mRNA sequencing data from HFD-fed Arg1fl/fl and TBGcreArg1fl/fl mice. The results revealed that, compared to Arg1fl/fl mice, HFD-induced TBGcreArg1fl/fl mice exhibited a marked downregulation of PPARγ pathways and adipogenesis-related genes (Fig. 3F–H, and Supplementary Fig. S5F). Notably, GSEA indicated that genes involved in the oxidative damage response were suppressed in TBGcreArg1fl/fl mice, providing further evidence of reduced lipid accumulation in the Arg1-deficient liver (Fig. 3G).

Collectively, our findings present compelling evidence that the absence of Arg1 inhibits the AKT/mTOR/PPARγ signaling pathway, leading to a significant downregulation of genes crucial for lipogenesis. However, the precise mechanism underlying how Arg1 activates this signaling pathway to regulate hepatic lipid metabolism remains elusive.

Arg1 binds to and promotes ERK2 ubiquitination-mediated degradation
To delve deeper into the underlying mechanism of Arg1’s involvement in lipid metabolism, we conducted co-immunoprecipitation (co-IP) and mass spectrometry analysis to identify proteins that interact with Arg1. A total of 1444 peptides corresponding to 338 proteins were identified (Supplementary Data 1). KEGG pathway analysis indicated that the top 100 proteins, ranked by peptide spectrum match (PSM), were enriched in metabolism signaling pathways, including MAPK signaling, arginine biosynthesis, insulin signaling, the TCA cycle, and glycose metabolism (Fig. 4A).

Among the proteins that potentially interact with Arg1, ERK2 emerged as the most likely candidate due to several reasons: (1) Four peptides with high-scoring PSMs belonged to ERK2. Notably, the peptide with the highest affinity featured a unique substrate-binding pocket structure, consisting of Ala187-Thr188-Arg189-Trp190 (or ATRW)43,44, which serves as a versatile and flexible binding site for ERK2 and its interacting proteins (Figs. 4B, C). The binding of these partner proteins to ERK2, including activators (such as MEK1/2), inactivators (such as MKP3), and substrates (such as RSK2 and Elk1)45–47, occurs in a mutually exclusive manner, each mediating distinct cellular processes; (2) In the proteins detected by co-IP, a clear band located between 35-55 kDa was observed in the strips pulled down by the Arg1 antibody. ERK2, with a molecular weight of 42 kDa, matches the size of this corresponding protein band (Fig. 4A); (3) As a crucial member of the MAPK family, ERK2 plays pivotal roles in various cellular processes, including glucose and lipid metabolism. Hepatocyte-specific ERK2 knockout mice fed a high-fat/high-sucrose diet (HFHSD) exhibited aggravated hepatosteatosis24. This phenotype was mediated by enhanced hepatic fatty acid synthesis, which subsequently led to visceral adipocyte enlargement.

We subsequently delved into whether Arg1 directly binds to ERK2. As anticipated, the co-IP results demonstrated that Arg1 interacts with ERK2 in liver tissue extracted from Arg1fl/fl mice (Fig. 4D). This direct binding was further validated by the Duolink in situ proximity ligation assay (PLA) in AML12 cells (Fig. 4E). Furthermore, in AML12 cells transfected with Flag-tagged ERK2 plasmid, Flag pull-down and co-IP experiments confirmed the interaction between exogenous Arg1 and Flag-ERK2 (Fig. 4F).

Next, we investigated whether BEC—the covalent Arg1 inhibitor that irreversibly binds to Arg1—could disrupt the Arg1-ERK2 interaction. In BEC-treated AML12 cells, we observed a disruption of Arg1-ERK2 binding, as evidenced by results from both co-IP and Duolink in situ PLA experiments (Fig. 4G, H). Because BEC acts as a structural mimic of the intermediate formed during L-arginine hydrolysis, we tested whether L-arginine supplementation affects the Arg1-ERK2 interaction. AML12 cells were treated with 100µM L-arginine for 24 hours48. Co-IP assays showed that L-arginine supplementation did not alter the Arg1-ERK2 interaction, potentially by inducing a compensatory increase in Arg1 expression (Supplementary Fig. S5G). These findings suggest that endogenous Arg1 is present in sufficient amounts to simultaneously maintain both its enzymatic activity and its regulatory role in ERK2-associated signaling. However, the precise stoichiometric distribution of Arg1 between these functions requires further investigation.

To further determine whether Arg1 promotes hepatic lipogenesis by suppressing ERK2 activity, we employed the ERK-selective inhibitor VX-11e to inhibit ERK2 activation in HFD-induced TBGcreArg1fl/fl mice (Fig. 4I). Administration of VX-11e for 4 weeks significantly reversed the decreases in body weight, liver weight, and liver-to-body weight ratio observed in TBGcreArg1fl/fl mice (Supplementary Fig. S6A, B). In addition, by augmenting the PPARγ pathway, VX-11e exacerbated hepatic steatosis and lipid accumulation in adipose tissue (Fig. 4J–N, Supplementary Fig. S6C–G). In MCD-treated TBGcreArg1fl/fl mice, VX-11e administration similarly impacted hepatic lipogenesis and the expression of the PPARγ pathway (Supplementary Fig. S6H–N). Our findings suggest that Arg1 fosters hepatic lipogenesis in an ERK2-dependent manner.

We discovered that knocking down Arg1 led to increased protein levels of ERK2 in both AML12 cells and TBGcreArg1fl/fl mice, while ERK2 mRNA expression remained unchanged (Fig. 4O, P and Supplementary Fig. S6O). Previous studies have demonstrated that ERK2 undergoes ubiquitination-mediated degradation. MG132, a proteasome inhibitor, promotes the accumulation of ubiquitinated proteins49. Using systematic co-IP assays, we screened known ERK-related E3 ligases (e.g., NEDD4L, MEKK1, and TRIM21) and identified MEKK1 as specifically binding to ERK2 in Arg1fl/fl mice (Supplementary Fig. S6P).50–53 In AML12 cells, treatment with MG132 reduced both the accumulation of ubiquitinated ERK2 and the binding of ERK2-associated E3 ubiquitin ligases following Arg1 knockdown, as confirmed by in vitro ubiquitination assays (Fig. 4Q). These findings suggest that Arg1 may promote ERK2 degradation via the ubiquitin-proteasome pathway.

The S-shaped motif of Arg1 selectively binds to the substrate binding pocket of ERK2
We next set out to unravel the binding mechanism between Arg1 and ERK2. We expressed glutathione-S-transferase (GST)-tagged Arg1, His-tagged ERK2 mutants, and ERK2-derived amino acid fragments in E. coli. Our findings demonstrate that Arg1 is capable of directly binding to the full-length ERK2 protein without requiring any additional mediators (Fig. 5A). An ERK2 mutant, harboring mutations in three peptides but retaining its critical ATRW sequence, displayed robust binding affinity to Arg1. In contrast, an ERK2 mutant carrying mutations within the critical 170–190 amino acid sequence exhibited significantly diminished binding to Arg1 (Fig. 5A). Furthermore, the molecular mapping assay revealed that Arg1 interacts with the ERK2 amino acid fragment spanning residues 170–190 in E. coli (Fig. 5B). The substrate-binding pocket structure, ATRW, located within the peptide sequences spanning residual 170–190 of ERK2, is integral for binding and activating enzymes such as ribosomal S6 kinase 2 (RSK2) and ETS-domain containing protein (Elk1)45. To identify the exact site of Arg1 binding to the ERK2 substrate-binding pocket, we transfected AML12 cells with plasmids expressing various ERK2 mutations. In comparison to the non-mutated control (NC), mutations in the A, T, or R residues of ERK2 considerably diminished its binding to Arg1, except for mutations affecting the W residue. Notably, mutations in the R residue and those encompassing the entire ATRW region resulted in the most significant decrease in Arg1 binding (Fig. 5C). Intriguingly, mutating the ATRW sequence in ERK2 resulted in reduced ERK2 ubiquitination and decreased binding of ERK2-related E3 ligases (Fig. 5C).

Both RSK2 and Elk1 are known to bind to ERK2 via its substrate-binding pocket. Based on this, we hypothesized that Arg1 would compete with them for this binding site. Our data revealed that ERK2 carrying the ATRW mutation prevented its binding to both RSK2 and Elk1 (Fig. 5C). When Arg1 was knocked down, ERK2 was able to associate with a higher amount of RSK2 and Elk1, as evidenced by co-IP experiments in AML12 cell (Fig. 5D). Similarly, we observed consistent results in AML12 cells treated with Arg1 inhibitor BEC (Fig. 4G).

Arg1 is a metalloproteinase featuring a unique α/β fold structure and a binuclear manganese center. It is well established that three key regions within the Arg1 molecule are essential for L-arginine hydrolysis: the hydrolytic site, the L-R amino acid site (composed of Arg21 and Asp181, which bind to the charged carboxyl group and the R-amino group of L-arginine, respectively), and the double hydrogen site (formed by His101 and His126)54,55. In addition, all mammalian arginases share a C-terminal S-shaped motif spanning residues 304-32256,57. The proper assembly of this motif into a homotrimer is essential for Arg1’s normal enzymatic activity, quaternary structure, and cooperative properties. Therefore, the amino acid residues His101 and His126, Arg21 and Asp181, as well as the sequence spanning residues 304–322, are indispensable for L-arginine binding in Arg1. We successfully synthesized the Arg1 mutants in the E. coli system. Notably, mutating the S-shaped motif (residues 304–322) in Arg1 completely abolished its binding affinity to ERK2, whereas mutations in the other regions exhibited minimal impact on binding (Fig. 5E).

To assess the significance of the S-shaped motif in Arg1 for hepatic lipogenesis, we administered AAV8 viruses expressing Arg121&181-mut (AAV8-TBG-Arg1-mut21&181-His) or Arg1304-322-mut (AAV8-TBG-Arg1304-322-mut-His) into TBGcreArg1fl/fl mice (Fig. 5F). The levels of His-tagged protein in the liver extracts from the Arg1-mutant groups were stably expressed (Fig. 5G). The Arg121&181-mut protein, which could bind to ERK2 but was unable to recognize L-arginine, partially mitigated the reduction in hepatic lipogenesis observed in TBGCreArg1fl/fl mice. This was evidenced by higher liver weight, body weight, and liver-to-body weight ratios compared to those injected with a vector (Fig. 5H, I). Furthermore, AAV8-Arg121&181-mut treatment substantially increased hepatic lipid accumulation (Fig. 5J), elevated TG and FFA levels in both serum and liver tissue (Fig. 5K) and enhanced the PPARγ pathway in the TBGcreArg1fl/fl mice (Fig. 5L). On the contrary, the AAV8-Arg1304-322-mut protein, which could not combine with ERK2, exhibited a negative effect on reversing the phenotype in response to Arg1 ablation. Interestingly, treatment with neither mutant virus significantly reduced serum L-arginine levels, demonstrating that a mutation in the binding site of Arg1 also compromises its enzymatic function (Fig. 5M). These data further support our hypothesis that the role of Arg1 in regulating lipogenesis is independent of its enzymatic activity, but rather depends on a physical combination with ERK2.

Arg1 enhances lipogenesis in hepatocytes via AKT/mTOR/PPARγ and Elk1/c-Fos/PPARγ signaling pathways
We have observed that the disruption of Arg1 leads to the suppression of the AKT/mTOR/PPARγ signaling pathway (Fig. 3 and Supplementary Fig. S5). However, the crosstalk between Arg1, mediated by ERK2, and the AKT/mTOR/PPARγ pathways remains elusive. In addition to decreasing EKR2 ubiquitination and degradation, we discovered that the disruption of Arg1 facilitates the nuclear translocation of ERK2 (Fig. 6A, B). Overactivation of ERK2 has been reported to impede lipogenesis through at least two distinct mechanisms, as depicted in Fig. 6C: (1) In the cytoplasm, ERK2 undergoes phosphorylation via the Ras-Raf-MEK cascade, enabling its substrate-binding pocket to bind to RSK2. This interaction initiates a negative feedback loop that suppresses the overactivation of Ras-Raf-MEK signaling, further inhibiting the AKT/mTOR signaling cascade and ultimately suppressing PPARγ. (2) Phosphorylated ERK2 translocates to the nucleus, where its substrate-binding pocket binds to Elk1, promoting the ERK2/Elk1/c-Fos signaling pathway, which in turn inhibit the PPARγ signaling45,46,58. Western blot results revealed that in the livers of TBGcreArg1fl/fl mice, Ras, p-Raf, and p-MEK were obviously decreased in the cytoplasm, whereas c-Fos and Elk1 in the nucleus were significantly elevated (Fig. 6A, B). Furthermore, HFD-fed TBGcreArg1fl/fl and Arg1fl/fl mice confirmed that Arg1 promotes hepatic lipid accumulation and adipose tissue lipid deposition through ERK2/PPARγ pathways, as elucidated by western blotting and immunohistochemistry staining in the mouse liver (Fig. 6D–G).

We next treated AML12 cells with ERK2 inhibitor VX-11e, ERK2 activator TBHQ, Arg1 siRNA, and Arg1 overexpression virus (OE), respectively. The results confirmed that the absence of Arg1 leads to excessive upregulation of ERK2, which in turn downregulates the PPARγ signaling pathway, thereby inhibiting hepatic lipogenesis. Importantly, this inhibition can be partially reversed by the ERK2 inhibitor. Conversely, Arg1 overexpression downregulates ERK2 protein levels and upregulates the PPARγ pathway, promoting hepatic lipogenesis. Notably, the ERK2 activator attenuates this promotional effect (Fig. 6H, I).

Peptide targeting Arg1-ERK2 interaction improves the metabolic profile of obesity and MASLD in mice
Our data, obtained from a male mouse model, support the notion that Arg1 is a potential therapeutic target for obesity and MASLD. In contrast to small-molecule drugs, peptides can be precisely engineered to target specific molecular receptors, offering enhanced selectivity.59,60 We synthesized two peptides: one biologically derived (ERK2170-200-Bio peptide) and one chemically synthesized (ERK2170-200-Chem peptide). These peptides encompass amino acids 170 to 190 within the ERK2 substrate-binding pocket of ERK2, which are essential for its interaction with Arg1. In addition, the Arg192 residual was included due to its importance for the conformational stability and functionality of the pocket structure. In the inactive state, the substrate-binding pocket of ERK2 is blocked by Arg192. However, phosphorylation of Thr183 and Tyr185 triggers a conformational change, enabling the pocket to become exposed and accessible for substrate recognition and binding.

Studies have shown that peptides can enter cells via free diffusion, facilitated diffusion, or endocytosis61,62. To determine whether these peptides also internalize into hepatocytes, we performed further experimental validation. Cy3 offers superior sensitivity for real-time monitoring of the intracellular distribution of the ERK2170-200 peptide-Cy3 conjugate. Red fluorescence was detected in AML12 cells, indicating successful internalization of the peptide conjugate (Fig. 7A). Green Fluorescent Protein (GFP) is an ideal marker for long-term tracking of peptide drugs in animal models. We administered daily tail vein injections of the ERK2170-200 peptide-GFP conjugate (50µg/kg per day) to HFD-fed wild-type mice for 4 weeks (Fig. 7B). GFP fluorescence was clearly observed in cryosectioned liver tissues, confirming hepatocyte uptake of the conjugate (Fig. 7C). Our findings indicated that GST-tagged peptides effectively bound to Arg1 in AML12 cells (Fig. 7D). Co-IP and Duolink in situ PLA assays revealed that these peptides inhibited Arg1-ERK2 interaction while enhancing ERK2 binding to RSK2 and Elk1 in AML12 cells (Fig. 7E, F). Specifically, the peptide enhanced cytoplasmic RSK2 levels, thereby inhibiting Ras/Raf and AKT/mTOR signaling pathways. In the nucleus, Elk1 activation elevated c-Fos expression, which ultimately reduced PPARγ levels (Figs. 7G, H and Supplementary Fig. S7A). Collectively, these data indicated that the peptide modulates the PPARγ signaling by disrupting Arg1-ERK2 interaction, as shown in Fig. 7I.

We next evaluated the efficacy of disrupting the Arg1-ERK2 interaction in vivo by administering 50µg/kg of either the ERK2170-200-Bio peptide, the ERK2170-200-Chem peptide, or saline via daily tail vein injections into wild-type mice fed a HFD for 4 weeks (Fig. 7B). Most notably, peptide treatment conferred significant protection against Arg1-mediated ERK2 degradation in obese mice. Importantly, neither peptide induced hyperargininemia (Supplementary Fig. S7B). Compared to the HFD-saline group, both the ERK2170-200-Bio peptide and the ERK2170-200-Chem peptide significantly reduced body weight, liver weight, liver-to-body weight ratio, and serum levels of ALT and AST (Fig. 8A–D and Supplementary Fig. S7C). In addition, histological analysis, micro-CT imaging, and quantification of TG and FFA in serum and liver tissues revealed significantly lower lipid accumulation in the liver and adipose tissue of peptide-treated mice (Fig. 8E–J and Supplementary Fig. S7D, E).

Next, we explored whether peptide injections could attenuate the progression of MCD-induced MASLD. Wild-type mice received daily injections of peptides or saline to for 2 weeks, administered concurrently with the MCD diet (Supplementary Fig. S8A). Our observations revealed that peptide treatment improved metabolic profiles in MCD-fed mice compared to those treated with saline (Supplementary Fig. S8B–F). These results indicate that both peptides effectively treat MASLD by disrupting the Arg1-ERK2 interaction.

Methods
EXPERIMENTAL MODEL DETAILS
Mice and diets. The Arg1fl/fl mice were provided by Dr. Pan Cong. Albumin-Cre transgenic mice were purchased from Shanghai Biomodel Organism Science. Liver-specific and hepatocyte-specific Arg1 knockout mice were generated by crossing the Arg1fl/fl mice with Albumin-Cre mice (AlbcreArg1fl/fl) or by injecting 1×1011 GC/mouse of AAV8-TBG-cre (provided by WZ Biosciences Inc.) (TBGcreArg1fl/fl), respectively (Supplementary Table 1). Eight-week-old male C57BL/6 mice and db/db mice were purchased from GemPharmatech, Nanjing, China (Supplementary Table 1). All mice were male and housed under specific pathogen-free (SPF) conditions in individually ventilated cages with corncob bedding. The animal room was maintained at 22±2°C and 55±10% humidity with a fixed 12 h/12 h light/dark cycle (light on at 7:00 AM). All animal care and experimental procedures were approved by the Animal Care and Use Committee of Sichuan University (Approval No. 20220302037) and were conducted in accordance with the NIH Guide for the Care and Use of Laboratory Animals.

Mice were maintained on either a chow diet as a control, a 45% lard high-fat diet (HFD), or a methionine-choline-deficient diet (MCD). All diets were purchased from Readydietech Co., Ltd., Shenzhen, China (Supplementary Table 2). The HFD was used to establish animal models of obesity and MAFLD induced by obesity74. Six-to eight-week-old male mice were fed the HFD for 12 weeks. The MCD diet was used to establish the MAFLD model75, and 6–8-week-old male mice were fed the MCD diet for 2 weeks.

The dose of BEC (CAS# 222638-67-7, purity: 99.28%, TargetMol, USA) was calculated based on previous studies that reported a 50% reduction in arginase activity in cells isolated from treated animals (Supplementary Table 3). A daily dose of 0.012 g of BEC was administered in 100 μL of water via oral gavage, to match the dosing equivalent used in studies where mice were exposed to BEC in their drinking water. Tert-butylhydroquinone (TBHQ) (CAS # 1948-33-0, purity: ≥95%, TargetMol, USA) is an ERK activator76. VX-11e (CAS # 896720-20-0, purity: ≥98%, TargetMol, USA) is a potent, selective, and orally bioavailable inhibitor of ERK77. The mice were given VX-11e in their drinking water at a concentration of 0.5 mg/mL.

METHOD DETAILS
Tissue and blood collection. Mice were sacrificed at the indicated times, and blood was collected. Tissues were collected and rapidly frozen using liquid nitrogen for long-term storage at −80°C. These frozen samples will be utilized for subsequent proteomic or immunoblot analysis. Furthermore, a portion of these tissues was fixed with 4% paraformaldehyde for 24 h and subsequently embedded in paraffin for pathological staining analysis. In addition, a part of the liver was fixed in 4% paraformaldehyde overnight at 4°C. Afterward, it was infiltrated with 30% sucrose at 4°C overnight. The liver tissue was then embedded in Tissue-Tek OCT compound (Sakura; cat. no. 4583) for subsequent frozen sectioning.

Measurement of biochemical parameters. Collect serum samples and send them to the GLP laboratory at West China Hospital for testing of mouse liver function indicators, including ALT and AST.

Hepatic lipid analysis. The stored liver samples (100 mg) were lysed and homogenized in 2 mL of a solution containing 150 mmol/L NaCl, 0.1% Triton X-100, and 10 mmol/L Tris using a polytron homogenizer (cat. no. NS-310E; Microtec Co., Ltd., Chiba, Japan) for 1 minute at room temperature. The liver TG level was analyzed using a Tissue Triglyceride Assay Kit (Applygen Technologies, Beijing, China), and the results were obtained by the GLP laboratory at West China Hospital. The liver homogenate FFA level was determined using an FFA Detection Kit based on the ACS-ACOD method (Wako Pure Chemical Industries, Ltd.) and normalized to the protein levels, as previously described. Those kits are described in Supplementary Table 4.

Cell Culture. The AML12 cell line were purchased from Wuhan Pricella Biotechnology Co., Ltd (Catalog Number: CL-0602). The AML12 mouse liver cell line was maintained in a 1:1 mixture of DMEM and Ham’s F12 Medium, supplemented with 10% fetal bovine serum, 5 μg/mL insulin, 5 μg/mL transferrin, 5 ng/mL selenium, and 40 ng/mL dexamethasone. The cells were cultured at 37°C in a 5% (v/v) CO2 atmosphere and subcultured every 3 days. MG132, a proteasome inhibitor, effectively blocks the proteolytic activity of the 26S proteasome complex, allowing ubiquitinated proteins to accumulate. The concentration of MG132 (CAS #133407-82-6, purity: 99.99%, supplied by TargetMol, USA) used in cell experiments was 10 μM, with a duration of action of 48 h. In cell experiments, BEC was administered at a concentration of 0.31 μM, TBHQ at 5 μM, and VX-11e at 50 nM.

Protein digestion and mass spectrometry. Total protein was extracted from a liver sample of one male mouse, with three technical replicates. Subsequently, a Co-Immunoprecipitation (co-IP) experiment was conducted using an Arg1 antibody to isolate proteins specifically interacting with Arg1. The protein complex was subjected to SDS-PAGE for separation based on their molecular weights. The gel was stained with Coomassie Brilliant Blue to visualize the protein bands. Images of the stained gel were captured for documentation. Specific gel slices containing bands of interest were excised. The excised gel pieces were processed to extract the peptides, which were subsequently analyzed by LC-MS/MS by Shanghai OeBiotech Co., Ltd. The LC-MS/MS proteomic analysis was performed using an integrated platform coupling the Easy-nLC 1200 Ultra-High-Performance Liquid Chromatography (UHPLC) system with a Q Exactive High-Resolution Mass Spectrometer. Protein identification and relative quantification across different experimental groups were achieved through data processing with ProteomeDiscover software. The results obtained from this analysis are presented in Supplementary Data 1.

Proximity ligation assay. AML12 cells were fixed using 3.7% paraformaldehyde and then blocked with the blocking solution provided by the Duolink PLA kit (Sigma-Aldrich, USA)78, following the manufacturer’s instructions (Supplementary Table 4). In summary, the fixed cells were incubated overnight with both anti-ERK2 (HUABIO, EM1910-53, Mouse, 1:500) and anti-Arg1 (Cell Signaling Technology, 93668, Rabbit, 1:1000) antibodies. After thorough washing to remove unbound antibodies, the cells were sequentially incubated with PLA probes, ligation solution, and amplification solution, all at 37°C. Finally, coverslips were mounted, and the resulting images were examined using a Leica TCS SP5 confocal microscope (Leica Microsystems, Mannheim, Germany).

Measurement of fat mass by microcomputed tomography (micro-CT). After being anaesthetized with isoflurane (1.5–2%) administered via air, the mice were positioned supine in an imaging cell where they were kept anaesthetized, warmed, and continuously monitored. Three-dimensional X-ray images were acquired using the CT component of a Quantum GX microCT Imaging System. The total acquisition time for these images was 15 min. The tube voltage was set at 80 kV, with a constant current of 32 mA. Representative micro-CT images were used to analyze the ratios of SAT (subcutaneous adipose tissue) and VAT (visceral adipose tissue) areas to the total area using ImageJ software.

Measurement of fat mass by autopsy. At the end of the different procedures, anaesthetized mice were sacrificed with a lethal dose of pentobarbital (120 mg/kg, intraperitoneally). Adipose tissues (visceral and subcutaneous) were harvested and weighed on a precision scale.

Knockdown of Arg1. The siRNA targeting Arg1 (siArg1) was designed and synthesized by RiboBio. The target sequences utilized were: (1) GACTGAAGTGGACAGACTA; (2) CAAGCCTATTGACTACCTT; and (3) CTGGGTGACTCCCTGTATA. AML12 cells were treated with siArg1, and after a 72 h incubation period, the cells were collected for subsequent western blot analysis.

Construction of plasmids and viruses. The plasmids encoding Flag-ERK2, Flag-ERK2 mut, and His-Arg1 were designed and synthesized by HUABIO, China (Supplementary Table 3). These plasmids were subsequently transfected into AML12 cells for a period of 48 h. Following transfection, the cells were collected by centrifugation at 800 × g for 10 min at 4°C. In addition, plasmids for full-length mouse Arg1, mutant Arg1, full-length ERK2, and various ERK2 mapping constructs were also designed and synthesized by HUABIO, China. These plasmids were expressed and purified in E. coli. WZ Biosciences Inc. (Shandong, China) designed and synthesized recombinant AAV8 vectors carrying TBG-Arg1-mut21&181-His and AAV8-TBG-Arg1304-322-mut-His plasmids. These plasmids harbor mutations in the hydrolytic site or S-motif coding sequence of mouse Arg1, respectively. The recombinant AAV8 vectors were administered to animals via tail vein injection at a dose of 2×1011 per animal. One month post-injection, the samples were collected for further analysis.

Peptide-drug synthesis. Peptides were obtained through Chemical Peptide Synthesis or Biological Peptide Synthesis (HUABIO, China). (1) Sequence of Chemical Peptide Synthesis: 170-200: RVADPDHDHTGFLTEYVATRWYRAPEIMLNS, and the purity is greater than 85%; (2) Biological Peptide Synthesis: recombinant synthesis involves the expression of the peptide within a specialized system from an artificial gene. The PET28A vector with a GST or GFP tag was constructed to transform E. coli, and the protein was extracted and purified (Supplementary Table 3). The main sequence was RVADPDHDHTGFLTEYVATRW YRAPEIMLNS, and the purity was greater than 85%. Mice were injected with 50µg/kg via the tail vein every day. GFP (Green Fluorescent Protein) is an endogenous fluorescent protein extensively utilized in biological research, particularly for live-cell imaging and labeling in transgenic animal models. Its high stability and brightness render it suitable for long-term observation and labeling in animals. Mouse liver tissues were collected fresh, embedded in OCT compound, and cryosectioned. GFP fluorescence was detected using a Leica DMi8 fluorescence microscope.

We selected Cy3, an exogenous fluorescent dye, for cellular labeling and imaging. Peptide-Cy3 is generated by covalently conjugating Cy3 dye to the peptide. We add 5 mg/mL Peptide-Cy3, after 48 h of co-incubation with the AML12 cell line, the distribution of the labeled peptide within the AML12 cells was visualized using fluorescence microscopy.

Oil red O staining. Liver tissues or cells were washed with phosphate-buffered saline (PBS) and fixed in 4% paraformaldehyde for 10 min. After being washed twice with distilled water, they were immersed in 60% isopropyl alcohol for 5 min, and then fixed in oil red O dye solution for 20 min. Finally, they were washed with distilled water 2–5 times until there was no excess oil red O staining fluid, and observed and photographed under an optical microscope.

L-arginine Concentration in serum and cell supernatant. The concentration of L-arginine in serum was determined by high-performance liquid chromatography (HPLC) as previously described79. Vortex and mix the serum or cell supernatant thoroughly for 3 minutes. Transfer 50 μL of the sample into an Eppendorf tube; add 250 μL of spiked methanol-water solution, then vortex the mixture at 4°C and 100 x g for 3 min. Place the tube in a −20°C freezer for 20 min. Sonicate the sample in an ice-water bath for 15 min. Vortex the sample again at 4°C for 3 min, then centrifuge it at 4°C and 11000 x g for 10 min. Transfer 150 μL of the supernatant into a new Eppendorf tube, concentrate it to dryness under vacuum at 30°C for 2 h, and then reconstitute the dried sample in 0.5 mL of HILIC solution. Vortex the reconstituted sample for 3 min, sonicate it in an ice-water bath for 10 min, vortex it again for 10 min, and then centrifuge it at 11000 x g and 4°C for 10 min. Transfer 150 μL of the supernatant into an injection vial for analysis. The mass spectrometry instrument used is the Q-Trap 5500 LC/MS/MS system from SCIEX, USA; the high-performance liquid chromatography (HPLC) instrument is the LC-30AD HPLC from Shimadzu; and the chromatography column is the Acquity UPLC BEH Amide column from Waters.

Histology and Immunohistochemistry. Liver specimens were fixed in 10% neutral buffered formalin for a duration of 48 hours. Paraffin-embedded sections, each 4 μm thick, were prepared and subsequently subjected to a series of steps including dewaxing, rehydration, antigen retrieval, and quenching of endogenous peroxidase activity. The sections were then incubated with the appropriate primary antibody at 4°C overnight, followed by incubation with an anti-mouse/rabbit secondary antibody (Dako REAL EnVision Detection System, Glostrup, Denmark) for 1 h at room temperature. The immunohistochemical analysis utilized the following primary antibodies: Arg1 (Cell Signaling Technology, 93668, 1:200), GS (GeneTex, GTX109121, 1:500), CK19 (Abcam, ab7754, 1:500), β-catenin (Thermo fisher, MA12001, 1:50), CD45 (HUABIO, ET7111-03, 1:2000), eIF4EBP1 (phospho S65) (Abcam, ab259329, 1:200), Phospho-p70 S6 Kinase (S434) (HUABIO, RT1456, 1:100), Ras (HUABIO, ET1702-94, 1:200), RSK2 (HUABIO, HA721033, 1:200), c-FOS (HUABIO, ET1701-95, 1:100). Detection was achieved using 3,3′-diaminobenzidine (DAB) as a substrate. Standard protocols were employed for H&E and PAS staining. The HE and immunostaining images were chosen by three experienced pathologists who were blinded to the study details.

Western blot. Liver tissues were homogenized for protein extraction. Sodium dodecyl sulfate‒polyacrylamide gel electrophoresis and immunoblotting were performed, and an electro chemiluminescent reagent was used for chemiluminescence detection. Both secondary antibodies (goat anti-rabbit and goat anti-mouse) were used at a dilution of 1:5000. The following primary antibodies were used for western blotting: Arg1 (Cell Signaling Technology, 93668, 1:1000), Arg1 (HUABIO, ET1605-8, 1:1000), β-actin (HUABIO, ET1701-80, 1:5000), p-AKT (ser473) (HUABIO, ET1607-73, 1:500), AKT1 (HUABIO, ET1609-47, 1:1000), p-ERK1 (pT202/pY204)/2 (pT185/pY187) (HUABIO, ET1610-13, 1:1000), ERK1/2 (HUABIO, ET1601-29, 1:500), ERK2 (HUABIO, ET1603-23, 1:500), ERK2 (HUABIO, EM1910-53, 1:500), p-mTOR (ser2448) (ImmunoWay Biotechnology, YP0176, 1:500), mTOR (HUABIO, ET1608-5, 1:1000), p-MEK (S218/S222) (HUABIO, ET1609-50, 1:500), MEK1/2 (HUABIO, ET1602-3, 1:1000), eIF4EBP1 (phospho S65) (Abcam, ab259329, 1:500), SREBP-1 (HUABIO, ER1917-19, 1:500), Phospho-p70 S6 Kinase (S434) (HUABIO, RT1456, 1:500), Ubiquitin (HUABIO, ET1609-21, 1:500), FASN (HUABIO, ET1701-91, 1:1000), RSK2 (HUABIO, HA721033, 1:500), c-FOS (HUABIO, ET1701-95, 1:500), Elk1 (HUABIO, ET1608-19, 1:1000), PPARγ (HUABIO, ET1702-57, 1:200), Phospho-Raf (HUABIO, ET1612-87, 1:500), Ras (HUABIO, ET1702-94, 1:1000), 6X His-tag (HUABIO, HA601079, 1:5000), GST (HUABIO, ET1611-47, 1:1000), Flag (HUABIO, M1403-2, 1:5000), NEDD4L (HUABIO, ET1611-42, 1:1000), MEKK1 (HUABIO, HA722507, 1:1000), Trim21 (HUABIO, HA721832, 1:1000).

mRNA Isolation and real-time PCR. Total mRNA was purified from 25 mg of liver tissue using an RNA Isolation kit (cat. RE-03011; Foregene, Chengdu, China). mRNA was reverse transcribed to cDNA using the iScript cDNA Synthesis kit (cat. 179-8890; Bio-Rad, Hercules, CA). Quantitative RT-PCR was performed using a SYBR Green PCR master mix kit with specific primers (Supplementary Table 5) on a Chromo4 cycler (Bio-Rad, Hercules, CA, USA). Data analysis was performed by using the ΔΔCt method. The change in mRNA levels in the samples was determined using the delta-delta Ct method with β-actin as the reference gene.

Indirect calorimetry. Food intake, oxygen consumption (VO2), carbon dioxide production (VCO2) and locomotor activity were measured in a subgroup of mice using a Comprehensive Lab Animal Monitoring System (Columbus Instruments, Columbus, OH) and VitalView System (MiniMitter, Bend, Oregon, USA). In brief, male mice housed individually with free access to food and water were acclimatized to the metabolic cages for 24 h prior to a 24 h period of automated recordings every 15 min. Sample air from individual cages was passed through sensors to determine O2 and CO2 content by an open-circuit Oxymax.

Statistics and reproducibility. The data are presented as the means ± standard errors of the mean (SEMs). Statistical comparisons were conducted using Student’s t test with Welch’s correction, which was performed by GraphPad Prism Software version 10 (San Diego, CA) (Supplementary Table 6). The P value less than 0.05 was considered statistically significant. To ensure reproducibility, all the H&E, immunofluorescence and immunohistochemical staining, and micro-CT images in the liver, and western blot were conducted in at least three biological replicates, unless mentioned otherwise. For the analysis of the western blot, the same experiment and that gels/blots were processed in parallel.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "First of all, thank you for allowing me to review this interesting paper. In this manuscript, the authors investigate the role of Arginase1 (Arg1) in hepatic lipogenesis. Arg1 is an enzyme that converts arginine to ornithine and urea. The authors use liver-specific Arg1 knockout mice and AML12 hepatocyte cells, finding that Arg1 is critical for lipogenesis. Interestingly, the authors revealed that the lipogenesis-regulating role of Arg1 is not dependent on the arginase activity. Instead, Arg1 interacts with extracellular signal-regulated kinase 2 (ERK2) to regulate peroxisome proliferator-activated receptor gamma (PPARγ) signaling. Their findings suggest that Arg1 enhances ERK2 ubiquitination and degradation, promoting lipogenesis through the AKT/mTOR/PPARγ and Elk1/c-Fos/PPARγ cascades. The authors further demonstrate that peptides that disrupt the Arg1-ERK2 interaction improve metabolic profiles in obesity and metabolic dysfunction-associated steatohepatitis (MASLD) models. This study is quite interesting and well-conducted. The amount of data is even impressive. Thus, I recommend the publication of this paper at Nature Communications after addressing the points described below.\n[Major points]\n1. Given Arg1's important role in lipid metabolism, understanding how Arg1 expression is regulated under different conditions (e.g., HFD, MCD diet…, etc.) is important. Does the protein expression level of Arg1 correlate with the activity of ERK2 under various conditions? In other words, can the expression of Arg1 be a marker for diseases?\n2. The non-enzymatic function of Arg1 is the core of this paper. Still, arginine, a substrate of Arg1, may play a role in regulating Arg1 stability and/or binding capacity to ERK2. Does the administration of arginine alter the Arg1-ERK2 interaction? Addressing if the enzymatic and non-enzymatic functions of Arg1 interfere with each other would further deepen our understanding of this interesting phenomenon.\n3. Selectivity regarding the Arg1-ERK2 interaction would be an interesting topic. For example, how specific are binding motifs/peptide sequences? How many other enzymes, such as Arg2, can be like Arg1? Addressing these using informatics would further generalize the author’s discovery. It would be interesting to model the Arg1-ERK2 interaction and how the peptides inhibit it using AlphaFold, which probably refines Fig. 8.\n4. It would be ideal to make western blot semi-quantitative. It was a bit hard to interpret Figure 4Q and Figure 5C particularly. Regarding Figure 4Q, reductions were not clear at all. Moreover, wouldn’t the addition of MG132 further increase ubiquitinated ERK2 levels?\n[Minor points]\n1. Typographical error in Figure 1I “p- 0 . 0 1 3 5”. – should be =.\n2. In Figure 5A, the schematic diagram uses an orange highlight to indicate the mutation sites. According to this understanding, it appears that all mutants lack 53-66. Please verify.\n3. In Figure 3F, it is unclear how the highlighted region was selected. Was the selection based on areas with a high concentration of lipogenesis-related genes? Providing this information would improve interpretability.\n4. In histology datasets, it would be better to describe how a region of interest was chosen.\n5. The method section is relatively reader unfriendly. For example, regarding mass spectrometry, please specify a platform the authors used. Dilution information of antibodies must be described.", "reviewer_2": "The paper describes the role of arginase 1 in obesity and MASLD. The authors identify Arg1 as a regulator of the Erk/PPARg pathway and propose that this mechanism drives the observed phenotype. The molecular data presented is intriguing however the physiological data is very fragmented and the mechanism proposed here in my opinion cannot explain the observed phenotype.\nMajor Points:\nThe liver specific arginase 1 ko mice have been described previously and given the severity of the developmental phenotype, which is possibly due to toxicity precludes the possibility to gain any insight into the molecular of physiological mechanisms. They should be removed completely from the manuscript.\nThe data on weight gain using the Arg1 inhibitor is very problematic as the mechanisms is difficult to delineate. This should be reflected in the statements which are often way stronger than the data actually is.\nThe inducible model is convincing and underscores the importance for obesity and MASLD, however the mechanism by which this phenotype is explained cannot by Erk mediated Akt/PPARg activation linked to lipogenesis. Without a proper analysis on the energy expenditure/uptake it is difficult to draw any conclusion on physiology.\nThe injected peptide data and the effect on whole body physiology is very interesting, still the mechanism by which they achieve this effect is completely lacking here. Also how do the authors envisage that these peptides enter the liver? This would need to be studied in more detail.\nMinor points\nLine 183, I am unsure about the statement oArg1 deficiency vs hyperargininemia. The cell culture data cannot be used to infer a mechanistic statement on the in vivo situation and secondly the authors didn’t check any arginine levels in the cell culture experiment. The statement if at all can be made in relation to the BEC in vivo treatment. This has to be adapted.\nPlease show weight graphs using the whole range and not starting at 20gs. Please also show the individual data points for all bar graphs to the variation can be judged.", "reviewer_3": "The present study focuses on the role of Arginase 1 (Arg1) in hepatic lipogenesis, obesity, and metabolic dysfunction-associated steatohepatitis (MASLD). The novel aspect of the study is identifying Arg1 “moonlighting” role in facilitating hepatic lipid accumulation. Mice lacking Arg1 exhibited lower lipid accumulation in the liver. Arg 1 inhibition resulted in similar results.\nPeptides mimicking the ERK2 substrate binding pocket disrupt the Arg1-ERK2 interaction. These peptides improved metabolic profiles in obesity and MASLD models. These findings highlight Arg1-ERK2 as potential therapeutic targets for metabolic diseases.\nNoteworthy results:\n1. Arg1 deletion decreases lipid accumulation in liver and adipose tissue.\n2. Pharmacological arg1 inhibition protects against obesity and MASLD.\n3. Arg1 regulates lipid metabolism via AKT/mTOR/ PPAR pathways.\n4. Arg1 directly binds to ERK2 and promotes its degradation and ubiquitination.\n5. The S-shaped motif of Arg1 mediates ERK2 binding\n6. Arg1 enhances lipogenesis via ERK2/AKT/mTOR/ PPAR pathways.\n7. Peptide-based targeting of Arg1 interaction improves obesity and MASLD.\nStudy significance:\n1. Arg1 promotes hepatic lipogenesis independently of its enzyme activity.\n2. The physical interaction of Arg1 and ERK2 might provide a regulatory link between Arg1 and lipid metabolism.\n3. Synthetic peptide targeting of Arg1 -ERK2 interaction gives a therapeutic strategy for obesity and MASLD.\nDoes the work support the conclusions and claims, or is additional evidence needed?\nThe work supports the conclusion and claims in part. See the review comments for more clarity.\nReview questions:\nIntroduction:\nLine 67-69: The authors must run a grammar check in these lines. There is some redundancy of words such as “attracted” and “garnered.” Also, change “extensive involved” to “extensive involvement” to make the sentence less complex.\nLine 78-80: Please state at least one example of how the negative feedback mechanism influences lipid metabolism regulation for ease of understanding. I also want to point out the over complex and lengthy sentence used. I suggest breaking the sentence into two separate lines to deliver the message.\nLine 107-108: please add a reference.\nAlthough the introduction is well written, my concern is with the flow or structure. It should start with an overview of obesity and MASLD and then discuss Arg1 and its role in MASLD, the signaling pathways PI3K-AKT /MAPK (with Arg1 interaction), and so on. Some sentences are excessively long. Try clarifying them in two sentences (Line 40-43).\nLine 91-96: While authors have discussed the canonical role of Arg1 in the urea cycle, little insight has been provided into its role in lipid metabolism regulation. Previously, no studies have linked Arg1 to obesity/ MASLD?\nThe introduction should clearly state the study's hypothesis (Arg1 interacts with ERK2 to regulate lipid metabolism.\nThe authors have introduced Arg1 as a potential target but do not mention any previous studies that studied Arg1 modulation in metabolic diseases.\nMethods and Results:\n1. Major: There is no indication where the proteomics raw data were deposited (they should be available in the public database with access for reviewers, not “per request” and upon acceptance made public. The ProteomeXchange has data repositories in different places of the world and is the recommended database).\n2. Major: Moreover, there is no supplemental table containing the proteomics data from the co-IP so the claims of the binding aren’t really supported.\n3. The authors should really make the complete western blots available in addition to the cutouts presented in figures. Many of the WB images do not indicate the size marker (example: figure 4D and F).\n4. There is no loading control and no way to know if equal amounts of total protein were loaded in the co-IP gel (Figure 4A) which is essential for the argument of specific binding.\n5. The authors conclude that the binding pocket is the place of interaction because of the mutations they introduced which abolished binding. This is not direct evidence of binding within this site. It may cause folding changes or other interaction changes which will prevent binding within another area of the protein. There are experimental ways to show the interaction within a specific area or peptide and this kind of experiment would greatly improve the argument. Or, they at least should use AlphaFold or similar modeling to show this may be the case.\n6. The authors need to specify whether they also examined the sex of the mice in this experiment or whether only male mice were used. Lipid metabolism differs between males and females due to hormonal regulation; PPARϒ activity is sex-dependent in metabolic disorders.\nDiscussion:\n1. The study focuses on Arg1 enhancing the ubiquitination of ERK2; however, it fails to identify the specific E3 ligase involved in this process (authors can do a co-IP with known E3 ligases).\n2. This study primarily examines the liver, but Arg1 is also expressed in adipose (fat) and muscle tissues, which may affect systemic lipid metabolism. Does systemic Arg1 inhibition also impact energy balance, fatty acid oxidation, or glucose metabolism beyond the liver?\n3. Since leptin regulates hepatic lipid metabolism, leptin mutation might partly influence any metabolic changes seen with Arg1 inhibition. Using DB/db mice to study Arg1 inhibition in obesity and MASLD is reasonable due to their characteristic metabolic dysfunctions, such as obesity and insulin resistance. However, their leptin receptor mutation may limit how well they mimic MASLD progression. The authors should clarify this in the discussion.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Response to Reviewer #1:\n[Major points]\n1. Given Arg1's important role in lipid metabolism, understanding how Arg1 expression is regulated under different conditions (e.g., HFD, MCD diet…, etc.) is important. Does the protein expression level of Arg1 correlate with the activity of ERK2 under various conditions? In other words, can the expression of Arg1 be a marker for diseases?\nAnswer: We sincerely appreciate the reviewer's positive feedback and constructive comments, which have greatly helped improve our manuscript.\nCurrent literature suggests that Arg1 shows promise as a biomarker for metabolic diseases. For instance, Kim et al. demonstrated significantly elevated circulating Arg1 levels in overweight adolescents compared to their normal-weight peers.1 Furthermore, Alisi et al. observed that increased Arg1 expression may serve as an indicator of shared steatosis patterns in both HCV and MASLD when lipid metabolism dysregulation has already occurred.2\nIn our animal experiments, we observed a significant upregulation of Arg1 protein expression coinciding with reduced ERK2 activity in MASLD models, as demonstrated in Figure 1 below. However, due to limited availability of clinical samples from normal and fatty liver tissues, we were unable to validate Arg1 expression in human subjects. Consequently, we cannot definitively establish Arg1 as a biomarker for obesity and MASLD. To maintain scientific accuracy, we have cautiously phrased our conclusion in the Introduction as follows: “Beyond this classical role, accumulating evidence highlights Arg1 as a potential biomarker and regulator of obesity and MASLD.”\nMouse liver tissue exhibits upregulated Arg1 and downregulated ERK2 after exposure to HFD and MCD diet (only for review).\n[1] Kim, O. Y., Lee, S. M., Chung, J. H., Do, H. J., Moon, J., & Shin, M. J. (2012). Arginase I and the very low-density lipoprotein receptor are associated with phenotypic biomarkers for obesity. Nutrition (Burbank, Los Angeles County, Calif.), 28(6), 635–639. https://doi.org/10.1016/j.nut.2011.09.012\n[2] Alisi, A., Comparcola, D., De Stefanis, C., & Nobili, V. (2015). Arginase 1: a potential marker of a common pattern of liver steatosis in HCV and NAFLD children. Journal of hepatology, 62(5), 1207–1208. https://doi.org/10.1016/j.jhep.2014.12.036\n2. The non-enzymatic function of Arg1 is the core of this paper. Still, arginine, a substrate of Arg1, may play a role in regulating Arg1 stability and/or binding capacity to ERK2. Does the administration of arginine alter the Arg1-ERK2 interaction? Addressing if the enzymatic and non-enzymatic functions of Arg1 interfere with each other would further deepen our understanding of this interesting phenomenon.\nAnswer: Thank you for your valuable suggestions. To determine whether arginine disrupts the Arg1-ERK2 interaction by binding to Arg1, we treated AML12 cells with 100 µmol/L L-arginine for 24 hours, using untreated AML12 cells as a control, as previously described.1 Co-IP results showed that while L-arginine supplementation increased Arg1 expression in AML12 cells, it did not alter the Arg1-ERK2 interaction (Figure below). These results have been incorporated into the revised manuscript with corresponding illustrations shown in Figure S5G.\nFurther analysis demonstrated that arginine treatment upregulated Arg1 expression; however, quantity of ERK2-bound Arg1 remained unchanged. This suggests that under physiological conditions, endogenous Arg1 is present in sufficient amounts to simultaneously maintain both its enzymatic activity and its regulatory role in ERK2-associated signaling, though the precise stoichiometric allocation of Arg1 between these roles requires further investigation. Notably, genetic ablation of hepatic Arg1 completely abolished both its catalytic activity and ERK2-binding capacity due to the absolute absence of Arg1 protein.\nWe further identified that the critical sequence mediating Arg1-ERK2 interaction resides outside its enzymatic active site. However, substrate or inhibitor binding (e.g., with BEC) to the active site possibly induces conformational changes in Arg1, indirectly impairing its interaction with ERK2. This mechanism was validated using BEC, a transition-state analog that specifically occupies Arg1’s catalytic site. BEC not only inhibited Arg1’s enzymatic activity but also markedly reduced its association with ERK2. These findings support a model where Arg1’s enzymatic function and ERK2-binding activity are structurally mutually exclusive.\nThis study developed a peptide-based drug targeting the Arg1-ERK2 interaction. One month after treatment, the peptide did not significantly alter Arg1 enzymatic activity, as plasma arginine levels remained unchanged. These results suggest that Arg1 represents a promising therapeutic target for MASLD, and its enzymatic function remains unaffected under this intervention strategy. We have made the corresponding revisions in lines 300–308 of the manuscript.\nCo-IP assays demonstrated that arginine supplementation does not affect the Arg1-ERK2 interaction in AML12 cells, as shown in Figure S5G of the main text.\n[1] Adams, M. R., Jessup, W., Hailstones, D., & Celermajer, D. S. (1997). L-arginine reduces human monocyte adhesion to vascular endothelium and endothelial expression of cell adhesion molecules. Circulation, 95(3), 662–668. https://doi.org/10.1161/01.cir.95.3.662\n3. Selectivity regarding the Arg1-ERK2 interaction would be an interesting topic. For example, how specific are binding motifs/peptide sequences? How many other enzymes, such as Arg2, can be like Arg1? Addressing these using informatics would further generalize the author’s discovery. It would be interesting to model the Arg1-ERK2 interaction and how the peptides inhibit it using AlphaFold, which probably refines Fig. 8.\nAnswer: We sincerely appreciate the reviewer’s insightful suggestions regarding the selectivity of the Arg1-ERK2 interaction and the potential to generalize these findings.\nTo address this concern, we performed a 1:1 protein complex structure prediction using AlphaFold-Multimer (as suggested). However, the predicted ipTM score for Arg1-ERK2 (0.21) fell below the typical confidence threshold of 0.6,1-4 indicating low confidence in the accuracy of these structural models. Interestingly, despite the wide variation in predicted ipTM scores between RSK2-ERK2 (0.17) and Elk1-ERK2 (0.81), both RSK2 and Elk1 are well-documented to bind the ERK2 pocket structure. This discrepancy underscores that while computational predictions provide useful guidance, experimental validation remains critical for confirming protein interactions, particularly when scores fall below the confidence threshold. For instance, previous study by Dongliang Ma et al.⁵ have demonstrated that co-IP assays can validate protein interactions even when AlphaFold-Multimer predictions yield low confidence scores. This example validates the reliability of our experimental approach in confirming the Arg1-ERK2 interaction.\nWe also attempted to crystallize the Arg1-ERK2 complex for structure validation. Although pull-down assays confirmed the interaction, crystallization attempts did not yield positive results, likely due to the use of recombinant proteins in the pull-down experiment and the transient and weak nature of the binding. These data were not included in the final presentation.\nTo acknowledge potential limitations, we have explicitly stated in the revised Discussion section line 527-531.\nTo address the reviewer’s valid concerns, we have moderated conclusions in the Abstract and Results to emphasize that our data suggest—rather than definitively prove—the pocket’s role in binding.\nArg2 is widely distributed in extrahepatic tissues, with the highest expression levels observed in the kidneys. Unlike Arg1, which is highly liver-specific, Arg2 is nearly undetectable in normal liver tissue. While Arg2 shares functional similarities with Arg1, our initial co-IP data suggest that it does not interact with ERK2 in the kidney, as demonstrated in Figure below. This implies that the Arg1-ERK2 interaction may be highly specific.\nImportantly, our experimental studies confirm that Arg1 interacts with ERK2 through its substrate-binding pocket, and this interaction is critical for mediating Arg1’s regulatory role in lipid metabolism. Based on these findings, we plan to further explore this interaction from both therapeutic and mechanistic perspectives, with structural studies as a priority for future work. We are committed to pursuing crystallization of the Arg1–ERK2 complex and determining its three-dimensional architecture to resolve these questions definitively.\nCo-IP validation shows no interaction between Arg2 and ERK2 in mouse kidney. Primary antibody: mouse anti-ARG2 (Santa Cruz Biotechnology, sc-271430) (only for review).\n[1] Wong, F., Krishnan, A., Zheng, E. J., Stärk, H., Manson, A. L., Earl, A. M., Jaakkola, T., & Collins, J. J. (2022). Benchmarking AlphaFold-enabled molecular docking predictions for antibiotic discovery. Molecular systems biology, 18(9), e11081. https://doi.org/10.15252/msb.202211081\n[2] Nussinov, R., Zhang, M., Liu, Y., & Jang, H. (2023). AlphaFold, allosteric, and orthosteric drug discovery: Ways forward. Drug discovery today, 28(6), 103551. https://doi.org/10.1016/j.drudis.2023.103551\n[3] Lee, C. Y., Hubrich, D., Varga, J. K., Schäfer, C., Welzel, M., Schumbera, E., Djokic, M., Strom, J. M., Schönfeld, J., Geist, J. L., Polat, F., Gibson, T. J., Keller Valsecchi, C. I., Kumar, M., Schueler-Furman, O., & Luck, K. (2024). Systematic discovery of protein interaction interfaces using AlphaFold and experimental validation. Molecular systems biology, 20(2), 75–97. https://doi.org/10.1038/s44320-023-00005-6\n[4] Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., Bridgland, A., Meyer, C., Kohl, S. A. A., Ballard, A. J., Cowie, A., Romera-Paredes, B., Nikolov, S., Jain, R., Adler, J., Back, T., … Hassabis, D. (2021). Highly accurate protein structure prediction with AlphaFold. Nature, 596(7873), 583–589. https://doi.org/10.1038/s41586-021-03819-2\n[5] Ma, D., Lin, K. Y., Suresh, D., Lin, J., Gujar, M. R., Aung, H. Y., Tan, Y. S., Gao, Y., Vincent, A. S., Chen, T., & Wang, H. (2024). Arl2 GTPase associates with the centrosomal protein Cdk5rap2 to regulate cortical development via microtubule organization. PLoS biology, 22(8), e3002751. https://doi.org/10.1371/journal.pbio.3002751\n4. It would be ideal to make western blot semi-quantitative. It was a bit hard to interpret Figure 4Q and Figure 5C particularly. Regarding Figure 4Q, reductions were not clear at all. Moreover, wouldn’t the addition of MG132 further increase ubiquitinated ERK2 levels?\nAnswer: We conducted semi-quantitative analysis on all Western blot data and incorporated the quantified results (e.g., bar graphs, fold changes) into the corresponding figure panels and raw data tables. For key results, such as those in Figure 4Q and Figure 5C, semi-quantitative data (e.g., fold changes in protein expression) are clearly presented adjacent to the WB bands for clarity.\nRegarding the effect of MG132 in Figure 4Q: As anticipated, treatment with the proteasome inhibitor MG132 alone significantly increased ERK2 ubiquitination levels. Notably, Arg1 knockdown (via siArg1 treatment) reduced ERK2 ubiquitination levels compared to MG132 treatment alone. These results suggest that Arg1 may enhance ERK2 ubiquitination through direct binding, thereby modulating its stability.\n[Minor points]\n1. Typographical error in Figure 1I “p- 0 . 0 1 3 5”. – should be =.\nAnswer: Thank you for your valuable assistance in enhancing the precision and professionalism of our manuscript's presentation. We have thoroughly reviewed all statistical annotations throughout the manuscript to ensure no similar formatting errors are present in other figures or tables. Specifically, p-values are now consistently presented with proper spacing and equals signs.\n2. In Figure 5A, the schematic diagram uses an orange highlight to indicate the mutation sites. According to this understanding, it appears that all mutants lack 53-66. Please verify.\nAnswer: We sincerely apologize for the labeling error in Figure 5A. We have corrected the color-coding to accurately indicate that only specific mutants (not all) lack residues 53-66. In the revised figure, mutation sites are highlighted in orange, while the normally expressed 53-66 region is clearly marked in blue. The corrected version has been updated in the main figure, thoroughly verified against experimental data, and cross-checked in the figure legend to ensure accuracy.\n3. In Figure 3F, it is unclear how the highlighted region was selected. Was the selection based on areas with a high concentration of lipogenesis-related genes? Providing this information would improve interpretability.\nAnswer: We sincerely appreciate this insightful suggestion. In the revised Figure 3F, we have implemented the following revisions to enhance clarity: (1) The highlighted genomic region has been explicitly labeled as \"Lipogenesis-related gene cluster.\" (2) A corresponding note has been added to the figure legend, specifying: \" The highlighted region, identified through KEGG pathway analysis, was defined as a genomic locus significantly enriched for genes involved in lipogenesis pathways.\"\n4. In histology datasets, it would be better to describe how a region of interest was chosen.\nAnswer: We appreciate the reviewer's suggestion regarding the selection criteria for ROI. We have implemented a standardized ROI selection protocol, which is now detailed in the revised Methods section. Briefly, ROIs were selected based on characteristic pathological features of MASLD, including: (1) steatosis ≥ 5%; (2) hepatocyte ballooning, and (3) lobular inflammation. Three certified pathologists independently annotated these features using 40X whole-slide images, explicitly excluding areas with artifacts (e.g., tissue folding, staining irregularities). To ensure consistency, a consensus review was then conducted for final determination, with a requirement of ≥ 2/3 inter-rater agreement. These methodological details have been fully documented in the revised Methods section to ensure transparency and reproducibility.\n5. The method section is relatively reader unfriendly. For example, regarding mass spectrometry, please specify a platform the authors used. Dilution information of antibodies must be described.\nAnswer: We sincerely appreciate the constructive feedback on improving the clarity of our methodological descriptions. We have thoroughly revised the Methods section to enhance readability and ensure compliance with reporting standards. Specifically:\n(1) Mass Spectrometry Platform: The LC-MS/MS-based proteomic analysis was conducted using an integrated system comprising the Easy-nLC 1200 Ultra-High-Performance Liquid Chromatography (UHPLC) system (Thermo Fisher Scientific) coupled to a Q Exactive High-Resolution Mass Spectrometer.\n(2) Antibody details: The Methods section now explicitly lists the manufacturers, catalog numbers, and dilution ratios for each antibody used in Western blot and Immunohistochemistry experiments.\n(3) Supplementary Documentation: to further improve transparency, we have compiled comprehensive information on mouse strains, reagents, and experimental protocols into Supplementary Table.\nThese revisions aim to address the reviewers’ concerns and facilitate study replication by providing precise technical details.\nResponse to Reviewer #2:\nMajor Points:\n1. The liver specific arginase 1 ko mice have been described previously and given the severity of the developmental phenotype, which is possibly due to toxicity precludes the possibility to gain any insight into the molecular of physiological mechanisms. They should be removed completely from the manuscript.\nAnswer: We sincerely appreciate the reviewer's critical feedback regarding the limitations of liver-specific Arg1 knockout mice. We fully acknowledge that constitutive knockout systems (e.g., AlbcreArg1fl/fl mice) exhibit developmental and metabolic phenotypes attributable to Arg1’s canonical enzymatic role in urea cycle metabolism, as previously documented (Refs 1-7). However, our study uncovers a previously unreported non-enzymatic function of Arg1: its role in physically binding with ERK2, thereby modulating the ERK2/PPARγ signaling axis in hepatic lipid metabolism.\nWhile we recognize the potential confounding effects of developmental defects in constitutive models, the following points justify retaining these data:\n(1) Phenotypic consistency: The significant reduction in abdominal fat observed in AlbCre Arg1fl/fl mice (validated through ≥ 3 independent experiments using littermate controls) provided the critical rationale for developing the inducible TBG-Cre model. This temporal control system (TBG-CreERT2) enabled us to isolate Arg1’s post-developmental role, thereby strengthening our mechanistic conclusions.\n(2) Complementary model systems: The parallel use of constitutive (Alb-Cre) and inducible (TBG-Cre) models enhances experimental rigor. Both systems demonstrated phenotypic consistency in lipid metabolism dysregulation, supporting the robustness of our findings.\n(3) Scientific novelty: Retaining these data is essential to highlight the dual functional roles of Arg1 (enzymatic vs. non-enzymatic), which represents the core innovation of our study.\nWe agree that constitutive knockout models have inherent limitations, which we explicitly address in the revised Discussion. To further substantiate our conclusions, we would be pleased to conduct additional validation experiments as recommended by the reviewer.\nIn line with the reviewer’s advice, we de-emphasized the developmental and survival effects of Arg1 knockout while emphasizing its metabolic consequences by exchanging the original Figure 1 (related to constitutive Arg1-knockout mouse experiments) with supplementary Figure 2 (generated via the TBG-Cre system, representing an inducible Arg1-knockout model).\n[1] Ballantyne, L. L., Sin, Y. Y., Al-Dirbashi, O. Y., Li, X., Hurlbut, D. J., & Funk, C. D. (2016). Liver-specific knockout of arginase-1 leads to a profound phenotype similar to inducible whole body arginase-1 deficiency. Molecular genetics and metabolism reports, 9, 54–60. https://doi.org/10.1016/j.ymgmr.2016.10.003.\n[2] Gau, C. L., Rosenblatt, R. A., Cerullo, V., Lay, F. D., Dow, A. C., Livesay, J., Brunetti-Pierri, N., Lee, B., Cederbaum, S. D., Grody, W. W., & Lipshutz, G. S. (2009). Short-term correction of arginase deficiency in a neonatal murine model with a helper-dependent adenoviral vector. Molecular therapy : the journal of the American Society of Gene Therapy, 17(7), 1155–1163. https://doi.org/10.1038/mt.2009.65.\n[3] Lee, E. K., Hu, C., Bhargava, R., Rozengurt, N., Stout, D., Grody, W. W., Cederbaum, S. D., & Lipshutz, G. S. (2012). Long-term survival of the juvenile lethal arginase-deficient mouse with AAV gene therapy. Molecular therapy : the journal of the American Society of Gene Therapy, 20(10), 1844–1851. https://doi.org/10.1038/mt.2012.129.\n[4] Lee, E. K., Hu, C., Bhargava, R., Ponnusamy, R., Park, H., Novicoff, S., Rozengurt, N., Marescau, B., De Deyn, P., Stout, D., Schlichting, L., Grody, W. W., Cederbaum, S. D., & Lipshutz, G. S. (2013). AAV-based gene therapy prevents neuropathology and results in normal cognitive development in the hyperargininemic mouse. Gene therapy, 20(8), 785–796. https://doi.org/10.1038/gt.2012.99.\n[5] Hu, C., Kasten, J., Park, H., Bhargava, R., Tai, D. S., Grody, W. W., Nguyen, Q. G., Hauschka, S. D., Cederbaum, S. D., & Lipshutz, G. S. (2014). Myocyte-mediated arginase expression controls hyperargininemia but not hyperammonemia in arginase-deficient mice. Molecular therapy : the journal of the American Society of Gene Therapy, 22(10), 1792–1802. https://doi.org/10.1038/mt.2014.99.\n[6] Hu, C., Tai, D. S., Park, H., Cantero, G., Cantero-Nieto, G., Chan, E., Yudkoff, M., Cederbaum, S. D., & Lipshutz, G. S. (2015). Minimal ureagenesis is necessary for survival in the murine model of hyperargininemia treated by AAV-based gene therapy. Gene therapy, 22(2), 111–115. https://doi.org/10.1038/gt.2014.106.\n[7] Truong, B., Allegri, G., Liu, X. B., Burke, K. E., Zhu, X., Cederbaum, S. D., Häberle, J., Martini, P. G. V., & Lipshutz, G. S. (2019). Lipid nanoparticle-targeted mRNA therapy as a treatment for the inherited metabolic liver disorder arginase deficiency. Proceedings of the National Academy of Sciences of the United States of America, 116(42), 21150–21159. https://doi.org/10.1073/pnas.1906182116.\n2. The data on weight gain using the Arg1 inhibitor is very problematic as the mechanisms is difficult to delineate. This should be reflected in the statements which are often way stronger than the data actually is.\nAnswer: We sincerely appreciate the reviewer's insightful critique regarding the interpretation of weight gain data following Arg1 inhibitor treatment.\nAs a transition-state analog inhibitor, BEC contains a tetrahedral boronate anion that structurally mimics the intermediate formed during L-arginine hydrolysis. Notably, the α-carboxylate and α-amino groups of BEC form three direct hydrogen bonds and four water-mediated hydrogen bonds with the manganese-containing active site of human Arg1, exhibiting a binding pattern that closely resembles substrate interactions.1 By inducing a possible conformational change in Arg1, this binding effectively disrupts the Arg1-ERK2 interaction, yielding functional outcomes analogous to genetic Arg1 ablation (as illustrated in Figure below).\nHypothesis for the mechanism of the Arg1 inhibitor BEC (only for review). The revised figure is now presented as Figure 2A in the main text.\nWe performed cell experiments which revealed that BEC treatment effectively inhibited lipid droplet formation and modulated the expression of lipogenesis-related proteins in AML12 cells, findings that aligned with our in vivo observations (Figure S4A, B). These results suggested that the impact of Arg1 inhibition on lipid metabolism occurs independently of L-arginine accumulation. Notably, we also observed that a 3-day BEC treatment significantly reduced L-arginine consumption (Figure S4C). Based on these data, we hypothesize that BEC administration may similarly inhibit L-arginine metabolism in animals, potentially leading to its systemic accumulation.\nFor in vivo investigations, we selected db/db mice (leptin-deficient, a well-established model for severe obesity and metabolic dysfunction) due to their documented cardioprotective response to L-arginine supplementation, making them an ideal model to study the effects of Arg1 inhibition.2 BEC administration to db/db mice significantly attenuated body weight gain and reduced visceral adipose tissue accumulation compared with untreated controls. Critically, BEC treatment did not induce hyperargininemia (Figure 2H), confirming that its metabolic benefits are independent of arginine accumulation.\nGene and protein analyses further indicated that BEC may modulate lipid metabolism via the PPARγ signaling pathway, exhibiting signaling alterations comparable to those induced by genetic Arg1 inactivation.\nCollectively, these results demonstrate that BEC-mediated Arg1 inhibition suppresses lipogenesis and reduces weight gain in db/db mice through a mechanism unrelated to hyperargininemia. However, we acknowledge that the precise conformational dynamics of Arg1 upon BEC binding require further structural elucidation through high-resolution studies.\nBoth the text and figures in the original manuscript have been revised accordingly, with specific modifications made to lines 194 to 202 and Figure 4C.\n[1] Haydar, D., Gonzalez, R., Garvy, B. A., Garneau-Tsodikova, S., Thamban Chandrika, N., Bocklage, T. J., & Feola, D. J. (2021). Myeloid arginase-1 controls excessive inflammation and modulates T cell responses in Pseudomonas aeruginosa pneumonia. Immunobiology, 226(1), 152034. https://doi.org/10.1016/j.imbio.2020.152034\n[2] Khaidar, A., Marx, M., Lubec, B., & Lubec, G. (1994). L-arginine reduces heart collagen accumulation in the diabetic db/db mouse. Circulation, 90(1), 479–483. https://doi.org/10.1161/01.cir.90.1.479\n3. The inducible model is convincing and underscores the importance for obesity and MASLD, however the mechanism by which this phenotype is explained cannot by Erk mediated Akt/PPARg activation linked to lipogenesis. Without a proper analysis on the energy expenditure/uptake it is difficult to draw any conclusion on physiology.\nAnswer: We sincerely appreciate the reviewer’s insightful comments. To address these concerns, we conducted a comprehensive analysis of energy homeostasis in TBGcreArg1fl/fl mice and Arg1fl/fl mice using metabolic cage experiments. Specifically, we systematically evaluated the daily food intake, oxygen consumption (VO₂), carbon dioxide production (VCO₂), and overall energy metabolism. The data revealed no significant differences in these parameters between TBGcreArg1fl/fl mice and Arg1fl/fl mice (Figure below), suggesting that the observed metabolic phenotype—particularly the marked reduction in abdominal fat accumulation—is not driven by systemic energy expenditure or caloric intake. These results further support our hypothesis that Arg1 deletion specifically attenuates hepatic lipogenesis.\nThis study employed two distinct conditional knockout mouse models and db/db mice to demonstrate that Arg1 deficiency or pharmacological inhibition attenuates hepatic lipid synthesis. Through co-IP, Duolink PLA, and mutant plasmid construction experiments, we confirmed the physical interaction between Arg1 and ERK2. Subsequent transcriptomic analysis, immunohistochemistry, and Western blot experiments indicated that Arg1 promotes hepatic lipogenesis by inhibiting ERK2-mediated repression of PPARγ signaling.\nIn summary, this research elucidates the molecular mechanism whereby Arg1 binds to and inhibits ERK2 activation, thereby enhancing PPARγ signaling activity. This process ultimately accelerates hepatic lipid synthesis and adipose tissue lipid accumulation, highlighting the critical role of Arg1 in pathogenesis obesity and MASLD.\nThe modifications have been incorporated into lines 174–179 of the Results section.\nTemporary inactivation of Arg1 in the liver does not alter the energy expenditure or food intake in mice, as shown by the metabolic data incorporated into Figure S3 of the main text.\n4. The injected peptide data and the effect on whole body physiology is very interesting, still the mechanism by which they achieve this effect is completely lacking here. Also how do the authors envisage that these peptides enter the liver? This would need to be studied in more detail.\nAnswer: We sincerely appreciate the reviewer's insightful questions regarding the peptide delivery mechanism and therapeutic action. To address these concerns, we have systematically elaborated on the following aspects:\n(1) Transmembrane transport mechanism: Currently, the FDA has approved over 60 peptide drugs, including semaglutide (Rybelsus®, Novo Nordisk), the first oral GLP-1 receptor agonist for type 2 diabetes and obesity treatment.1 Peptide drugs, as hydrophilic macromolecules, utilize distinct transmembrane transport pathways compared to small molecules. In addition to free diffusion and facilitated diffusion, endocytosis plays a pivotal role in cellular uptake.2,3 This is exemplified by insulin's cellular entry via receptor-mediated endocytosis.4 Our designed peptides (MW ~3.5 kDa) likely employ similar mechanisms, given their molecular weight range (0.5-5 kDa) typically associated with endocytic transport, though this mechanism still requires further determination.\n(2) The peptide is capable of being taken up by hepatocytes: Despite directly entering the bloodstream and systemic distribution via intravenous injection, most peptide drugs inevitably accumulate in the liver—the primary detoxification organ—as confirmed by animal studies, irrespective of their structure or function.5-8 We have strengthened the evidence that our designed peptide can be delivered to hepatocytes through in vitro and in vivo experiments. 1) In vitro validation: Cy3-labeled ERK2170-200 peptide showed distinct intracellular red fluorescence in AML12 hepatocytes after 24-h co-incubation; 2) In vivo biodistribution: GFP-tagged peptides exhibited specific green fluorescence in liver cryosections of HFD-fed mice. These results verify effective hepatic cellular uptake of our designed peptide.\n(3) Molecular mechanism elucidation: The therapeutic peptide was specifically designed to disrupt the Arg1-ERK2 protein interaction. As illustrated in revised Figure 7, GST pull-down assays confirmed peptide binding to Arg1 in AML12 cells. Co-IP and Duolink PLA assays demonstrated the disruption of Arg1-ERK2 binding and enhanced ERK2 interaction with its downstream effectors RSK2 and Elk1. Additionally, the HFD mouse model demonstrated significantly elevated ERK2 expression, suppressed hepatic lipogenesis via the ERK2/PPARγ pathway, and superior efficacy compared to the saline control group. Therefore, the therapeutic peptide inhibited hepatic lipogenesis by disrupting the Arg1-ERK2 interaction, which maintained ERK2 expression and consequently modulated the ERK2/PPARγ pathway.\nThese findings not only confirm hepatic targeting but also elucidate the molecular mechanism underlying the therapeutic effect, specifically through modulation of the ERK2/PPARγ pathway.\nWe have incorporated these revisions into Figure 7 and into the corresponding manuscript text (lines 427–444).\nThe peptide is internalized by hepatocytes and modulated the ERK2/PPARγ signaling pathway in the liver. These findings have been incorporated into the revised Figure 7.\n[1] Xiao, W., Jiang, W., Chen, Z., Huang, Y., Mao, J., Zheng, W., Hu, Y., & Shi, J. (2025). Advance in peptide-based drug development: delivery platforms, therapeutics and vaccines. Signal transduction and targeted therapy, 10(1), 74. https://doi.org/10.1038/s41392-024-02107-5\n[2] Linker, S. M., Schellhaas, C., Kamenik, A. S., Veldhuizen, M. M., Waibl, F., Roth, H. J., Fouché, M., Rodde, S., & Riniker, S. (2023). Lessons for Oral Bioavailability: How Conformationally Flexible Cyclic Peptides Enter and Cross Lipid Membranes. Journal of medicinal chemistry, 66(4), 2773–2788. https://doi.org/10.1021/acs.jmedchem.2c01837\n[3] Kovalainen, M., Mönkäre, J., Riikonen, J., Pesonen, U., Vlasova, M., Salonen, J., Lehto, V. P., Järvinen, K., & Herzig, K. H. (2015). Novel delivery systems for improving the clinical use of peptides. Pharmacological reviews, 67(3), 541–561. https://doi.org/10.1124/pr.113.008367\n[4] Artunc, F., Schleicher, E., Weigert, C., Fritsche, A., Stefan, N., & Häring, H. U. (2016). The impact of insulin resistance on the kidney and vasculature. Nature reviews. Nephrology, 12(12), 721–737. https://doi.org/10.1038/nrneph.2016.145\n[5] Zhou, R., Zhang, M., He, J., Liu, J., Sun, X., & Ni, P. (2022). Functional cRGD-Conjugated Polymer Prodrug for Targeted Drug Delivery to Liver Cancer Cells. ACS omega, 7(24), 21325–21336. https://doi.org/10.1021/acsomega.2c02683\n[6] Li, M., Tang, Z., Zhang, Y., Lv, S., Yu, H., Zhang, D., Hong, H., & Chen, X., (2014). LHRH-peptide conjugated dextran nanoparticles for targeted delivery of cisplatin to breast cancer. Journal of materials chemistry. B, 2(22), 3490–3499. https://doi.org/10.1039/c4tb00077c\n[7] Chen, X., Park, R., Tohme, M., Shahinian, A. H., Bading, J. R., & Conti, P. S. (2004). MicroPET and autoradiographic imaging of breast cancer alpha v-integrin expression using 18F- and 64Cu-labeled RGD peptide. Bioconjugate chemistry, 15(1), 41–49. https://doi.org/10.1021/bc0300403\n[8] Fan, J. Q., Li, Y. J., Wei, Z. J., Fan, Y., Li, X. D., Chen, Z. M., Hou, D. Y., Xiao, W. Y., Ding, M. R., Wang, H., & Wang, L. (2021). Binding-Induced Fibrillogenesis Peptides Recognize and Block Intracellular Vimentin Skeletonization against Breast Cancer. Nano letters, 21(14), 6202–6210. https://doi.org/10.1021/acs.nanolett.1c01950\nMinor points\n1. Line 183, I am unsure about the statement of Arg1 deficiency vs hyperargininemia. The cell culture data cannot be used to infer a mechanistic statement on the in vivo situation and secondly the authors didn’t check any arginine levels in the cell culture experiment. The statement if at all can be made in relation to the BEC in vivo treatment. This has to be adapted.\nAnswer: We fully concur with the reviewer's expert assessment. Indeed, data from cell experiments cannot be directly extrapolated to in vivo mechanisms, and the initial experimental design's failure to measure arginine levels in cell culture medium was a significant oversight.\n(1) Revised Cellular Experiments:\nTo avoid the confounding effects of hyperargininemia observed in transgenic models, we treated cultured mouse AML12 hepatocytes with the arginase inhibitor BEC. These experiments confirmed that BEC treatment effectively inhibited lipid droplet formation and modulated the expression of lipogenesis-related proteins, consistent with our in vivo observations (Figure S4A, B).\nUsing HPLC-QqQ-MS, we analyzed culture supernatants from AML12 cells treated with 0.31 μM BEC or siRNA-mediated Arg1 knockdown (siArg1). In cell-based experiments, a 72-hour BEC treatment significantly reduced the consumption of L-arginine (Figure S4C). Based on this finding, we speculate that BEC administration in animals may similarly inhibit L-arginine metabolism, leading to its accumulation in vivo.\nEffect of BEC and Arg1 knockdown on extracellular arginine levels. Following a 72-hour culture period without medium renewal, significantly higher extracellular arginine concentrations were detected in both BEC-treated and Arg1-knockdown cells compared to controls (n = 4). These results are now presented in the revised Figure S4C.\n(2) in vivo validation:\nWe selected db/db mice for in vivo studies, as previously addressed in response to the same reviewer’s major question 2. Notably, BEC treatment did not induce hyperargininemia (Figure 2H), a finding that likely reflects the heightened metabolic demand for arginine in db/db mice—driven by compensatory mechanisms associated with diabetic cardiomyopathy and chronic inflammation—which offsets reduced arginine catabolism due to Arg1 inhibition, as previously observed in metabolic stress models.1\nCollectively, these results demonstrate that BEC-mediated Arg1 inhibition suppresses lipogenesis through a mechanism unrelated to hyperargininemia. We have revised the original manuscript accordingly, particularly lines 185-186, lines 194-202, and Figure S4C.\n[1] Khaidar, A., Marx, M., Lubec, B., & Lubec, G. (1994). L-arginine reduces heart collagen accumulation in the diabetic db/db mouse. Circulation, 90(1), 479–483. https://doi.org/10.1161/01.cir.90.1.479\n2. Please show weight graphs using the whole range and not starting at 20gs. Please also show the individual data points for all bar graphs to the variation can be judged.\nAnswer: We appreciate the reviewer for these valuable suggestions on improving data visualization. We have carefully incorporated specific revisions to our figures to enhance data transparency and clarity of presentation.\nFor all weight-related graphs (Figures 2B, 2I, 8A, and S2C), we have adjusted the y-axis to cover the full range of observed values, ensuring accurate reflection of weight trends.\nAdditionally, we have added individual data points to all bar graphs throughout the manuscript, including key figures such as Figure 1N and Figure 4E. These changes enable readers to better assess data distribution and variability within each experimental group. We believe these revisions will significantly enhance the interpretability and clarity of our data presentation.\nShould further adjustments be required, please do not hesitate to let us know.\nResponse to Reviewer #3:\nReview questions:\nIntroduction:\n1. Line 67-69: The authors must run a grammar check in these lines. There is some redundancy of words such as “attracted” and “garnered.” Also, change “extensive involved” to “extensive involvement” to make the sentence less complex.\nAnswer: We sincerely thank the reviewer's meticulous review and valuable feedback. We have carefully revised the sentence to eliminate redundancy and improve clarity. Specifically, we removed the repetitive verb \"attracted\" while retaining \"garnered\" to maintain precise terminology. Additionally, the phrase \"extensive involved\" has been corrected to \"extensive involvement\" to enhance grammatical accuracy and readability. These adjustments ensure the sentence is both concise and academically rigorous. The aforementioned changes have been made in lines 87-90 of the Introduction.\n2. Line 78-80: Please state at least one example of how the negative feedback mechanism influences lipid metabolism regulation for ease of understanding. I also want to point out the over complex and lengthy sentence used. I suggest breaking the sentence into two separate lines to deliver the message.\nAnswer: We sincerely thank the reviewer's valuable suggestions on improving clarity and scientific communication. In response to these comments:\n(1) We have provided a concrete example of the negative feedback mechanism. Upon glucose stimulation, insulin binds to its receptor, triggering phosphorylation and activation of insulin receptor substrate-1 (IRS-1). Activated IRS-1 subsequently activates the PI3K/AKT signaling pathway, which enhances glucose utilization and storage in hepatocytes through glycogen synthesis promotion and gluconeogenesis inhibition. However, sustained high glucose intake enhances AKT-mediated activation of the MAPK pathway, particularly affecting ERK2 (MAPK1). Excessive ERK2 activation phosphorylates IRS-1 at serine residues (e.g., Ser636/639), further inhibiting IRS-1 binding to insulin receptors. This severely disrupts normal PI3K/Akt pathway function and ultimately reduces insulin-stimulated glucose utilization efficiency.1,2 These mechanisms collectively contribute to insulin resistance development and type 2 diabetes mellitus (T2DM).\n(2) To enhance the readability of the manuscript, we have revised the original text. All modifications have been incorporated into the introduction section (lines 96-107) of the revised manuscript.\n[1] Wang, J., Wu, T., Fang, L., Liu, C., Liu, X., Li, H., Shi, J., Li, M., & Min, W. (2020). Peptides from walnut (Juglans mandshurica Maxim.) protect hepatic HepG2 cells from high glucose-induced insulin resistance and oxidative stress. Food & function, 11(9), 8112–8121. https://doi.org/10.1039/d0fo01753a.\n[2] Artunc, F., Schleicher, E., Weigert, C., Fritsche, A., Stefan, N., & Häring, H. U. (2016). The impact of insulin resistance on the kidney and vasculature. Nature reviews. Nephrology, 12(12), 721–737. https://doi.org/10.1038/nrneph.2016.145\n3. Line 107-108: please add a reference.\nAnswer: The statement originally in lines 107-108 has been moved to lines 71-73 and revised to incorporate a citation: “Supplementation with L-arginine has been shown to mitigate hepatic inflammation in a methionine-choline-deficient (MCD) diet-induced mouse model, via NOS-mediated elevation of NO production.22” This addition strengthens the scientific foundation of the claim while maintaining proper attribution to prior research.\nReference Added:\nKim, D. Y., Park, J. Y., & Gee, H. Y. (2023). Lactobacillus plantarum ameliorates NASH-related inflammation by upregulating L-arginine production. Experimental & molecular medicine, 55(11), 2332–2345. https://doi.org/10.1038/s12276-023-01102-0\n4. Although the introduction is well written, my concern is with the flow or structure. It should start with an overview of obesity and MASLD and then discuss Arg1 and its role in MASLD, the signaling pathways PI3K-AKT /MAPK (with Arg1 interaction), and so on. Some sentences are excessively long. Try clarifying them in two sentences (Line 40-43).\nAnswer: We sincerely appreciate the reviewer's constructive feedback. We have thoroughly revised the introduction by (1) restructuring the content to first provide an overview of obesity and MASLD before detailing Arg1's role and its interactions with PI3K-AKT/MAPK signaling pathways; (2) splitting the lengthy sentences in Lines 40-43 into clearer, more concise statements; and (3) ensuring smooth transitions between sections while maintaining scientific accuracy. These modifications have significantly improved the logical flow and readability of the introduction. We have incorporated all changes into the introduction of the revised manuscript.\n5. Line 91-96: While authors have discussed the canonical role of Arg1 in the urea cycle, little insight has been provided into its role in lipid metabolism regulation. Previously, no studies have linked Arg1 to obesity/ MASLD?\nAnswer: We sincerely thank the reviewer for highlighting this gap. In fact, existing literature has established a link between Arg1 and MASLD or obesity, showing that overweight or obesity is associated with elevated Arg1 levels. For instance, studies have reported significantly higher circulating Arg1 levels in overweight individuals compared to their normal-weight counterparts.1,2 Increased hepatic Arg1 expression has also been complicated in vascular endothelial impairment during early obesity.3,4 Mechanistically, Arg1 may play a critical role in lipid metabolism through its canonical enzymatic functions, such as regulating polyamine synthesis or competing with iNOS for arginine substrate availability.\nAll modifications have been incorporated into the introduction section of the revised manuscript.\nReferences:\n[1] Kim, O. Y., Lee, S. M., Chung, J. H., Do, H. J., Moon, J., & Shin, M. J. (2012). Arginase I and the very low-density lipoprotein receptor are associated with phenotypic biomarkers for obesity. Nutrition, 28(6), 635–639. https://doi.org/10.1016/j.nut.2011.09.012\n[2] Jung, C., Figulla, H. R., Lichtenauer, M., Franz, M., & Pernow, J. (2014). Increased levels of circulating arginase I in overweight compared to normal weight adolescents. Pediatric diabetes, 15(1), 51–56. https://doi.org/10.1111/pedi.12054\n[3] Bhatta, A., Yao, L., Xu, Z., Toque, H. A., Chen, J., Atawia, R. T., Fouda, A. Y., Bagi, Z., Lucas, R., Caldwell, R. B., & Caldwell, R. W. (2017). Obesity-induced vascular dysfunction and arterial stiffening requires endothelial cell arginase 1. Cardiovascular research, 113(13), 1664–1676. https://doi.org/10.1093/cvr/cvx164\n[4] Ito, T., Kubo, M., Nagaoka, K., Funakubo, N., Setiawan, H., Takemoto, K., Eguchi, E., Fujikura, Y., & Ogino, K. (2018). Early obesity leads to increases in hepatic arginase I and related systemic changes in nitric oxide and L-arginine metabolism in mice. Journal of physiology and biochemistry, 74(1), 9–16. https://doi.org/10.1007/s13105-017-0597-6\n6. The introduction should clearly state the study's hypothesis (Arg1 interacts with ERK2 to regulate lipid metabolism.\nAnswer: As recommended, we have now explicitly stated our study hypothesis in the Introduction section: “In this study, we uncover a novel \"moonlighting\" function of Arg1 beyond its canonical role in L-arginine metabolism: Arg1 physically interacts with ERK2 (a key MAPK kinase) through its S-shaped motif, competing with RSK2 and Elk1 for binding to ERK2's substrate-binding pocket. This competition enhances ERK2 ubiquitination and degradation, thereby upregulating both the AKT/mTOR/PPARγ and Elk1/c-Fos/PPARγ signaling cascades, ultimately promoting lipogenesis.” The additional content can be found in the final paragraph of the Introduction section in the revised manuscript.\n7. The authors have introduced Arg1 as a potential target but do not mention any previous studies that studied Arg1 modulation in metabolic diseases.\nAnswer: We appreciate the reviewer’s valuable comment. In response, we have added relevant studies on Arg1 in obesity and obesity-related metabolic diseases to the Introduction section.\nMethods and Results:\n1. Major: There is no indication where the proteomics raw data were deposited (they should be available in the public database with access for reviewers, not “per request” and upon acceptance made public. The ProteomeXchange has data repositories in different places of the world and is the recommended database).\nAnswer: We sincerely appreciate the reviewer’s important comment regarding data availability. In full compliance with journal policy and to ensure transparency, we have now deposited all mass spectrometry proteomics data in the ProteomeXchange Consortium via the PRIDE partner repository. The dataset identifier is PXD059821 (access token: x0SNB20dNVXI), which provides immediate access for reviewers and will be made fully public upon publication.\n2. Major: Moreover, there is no supplemental table containing the proteomics data from the co-IP so the claims of the binding aren’t really supported.\nAnswer: We have included the complete co-IP proteomics results in Supplemental Table S1, which details all peptide-matched proteins identified in our analysis. This table has been uploaded in our revised submission and will help substantiate our interaction findings between Arg1 and ERK2.\n3. The authors should really make the complete western blots available in addition to the cutouts presented in figures. Many of the WB images do not indicate the size marker (example: figure 4D and F).\nAnswer: We appreciate the reviewer’s detailed feedback on our Western blot data. To fully comply with the journal’s transparency policy, we have now:\n(1) Included uncropped, full-length Western blot images for all figures in the Source Data file.\n(2) Clearly labeled molecular weight markers (kDa) on every blot, including Figures 4D and 4F.\n(3) Annotated all target protein positions with arrowheads or brackets for clarity.\nThe updated Source Data file has been uploaded with our resubmission. We deeply regret any oversight in the original submission and thank the reviewer for ensuring this critical improvement.\n4. There is no loading control and no way to know if equal amounts of total protein were loaded in the co-IP gel (Figure 4A) which is essential for the argument of specific binding.\nAnswer: All co-IP groups were loaded with equal quantities of protein (50 µg), as determined via BCA assay quantification. Minor variations in band intensity arose from differences in antibody pull-down efficiency rather than unequal loading.\nAdditionally, due to the exceptional sensitivity of silver staining, we conducted supplementary silver staining experiments to internally validate our preliminary findings internally. Consistent with the Coomassie Brilliant Blue staining, silver staining also revealed a distinct band near 42 kDa in the experimental group samples compared to the control group samples. This finding further corroborates the differences in protein expression we previously observed.\nSilver staining analysis of Arg1-interacting proteins co-immunoprecipitated from wild-type mouse liver homogenates (only for review).\n5. The authors conclude that the binding pocket is the place of interaction because of the mutations they introduced which abolished binding. This is not direct evidence of binding within this site. It may cause folding changes or other interaction changes which will prevent binding within another area of the protein. There are experimental ways to show the interaction within a specific area or peptide and this kind of experiment would greatly improve the argument. Or, they at least should use AlphaFold or similar modeling to show this may be the case.\nAnswer: We sincerely appreciate the reviewer’s insightful critique regarding the interpretation of our mutagenesis data. As the reviewer rightly noted, the observed abolition of binding following pocket mutations could theoretically result from allosteric effects or structural perturbations rather than direct disruption of the binding site itself.\nTo address this concern, we performed a 1:1 protein complex structure prediction using AlphaFold-Multimer (as suggested). However, the predicted ipTM score for Arg1-ERK2 (0.21) fell below the typical confidence threshold of 0.6,1-4 indicating low confidence in the accuracy of these structural models. Interestingly, despite the wide variation in predicted ipTM scores between RSK2-ERK2 (0.17) and Elk1-ERK2 (0.81), both RSK2 and Elk1 are well-documented to bind the ERK2 pocket structure. This discrepancy underscores that while computational predictions provide useful guidance, experimental validation remains critical for confirming protein interactions, particularly when scores fall below the confidence threshold. Notably, previous studies (e.g., Dongliang Ma et al.⁵) have demonstrated that co-IP assays can validate protein interactions even when AlphaFold-Multimer predictions yield low confidence scores. This example validates the reliability of our experimental approach in confirming the Arg1-ERK2 interaction.\nWe also attempted to crystallize the Arg1-Erk2 complex for structure validation. Although pull-down assays confirmed the interaction, crystallization attempts did not yield positive results, likely due to the use of recombinant proteins in the pull-down experiment and the transient and weak nature of the binding. These data were not included in the final presentation.\nTo acknowledge potential limitations, we have explicitly stated in the revised Discussion section line 527-531.\nTo address the reviewer’s valid concerns, we have moderated conclusions in the Abstract and Results to emphasize that our data suggest—rather than definitively prove—the pocket’s role in binding.\nImportantly, our experimental studies confirm that Arg1 interacts with ERK2 through its substrate-binding pocket, and this interaction is critical for mediating Arg1’s regulatory role in lipid metabolism. Based on these findings, we plan to further explore this interaction from both therapeutic and mechanistic perspectives, with structural studies as a priority for future work. We are committed to pursuing crystallization of the Arg1–ERK2 complex and determining its three-dimensional architecture to resolve these questions definitively.\n[1] Wong, F., Krishnan, A., Zheng, E. J., Stärk, H., Manson, A. L., Earl, A. M., Jaakkola, T., & Collins, J. J. (2022). Benchmarking AlphaFold-enabled molecular docking predictions for antibiotic discovery. Molecular systems biology, 18(9), e11081. https://doi.org/10.15252/msb.202211081\n[2] Nussinov, R., Zhang, M., Liu, Y., & Jang, H. (2023). AlphaFold, allosteric, and orthosteric drug discovery: Ways forward. Drug discovery today, 28(6), 103551. https://doi.org/10.1016/j.drudis.2023.103551\n[3] Lee, C. Y., Hubrich, D., Varga, J. K., Schäfer, C., Welzel, M., Schumbera, E., Djokic, M., Strom, J. M., Schönfeld, J., Geist, J. L., Polat, F., Gibson, T. J., Keller Valsecchi, C. I., Kumar, M., Schueler-Furman, O., & Luck, K. (2024). Systematic discovery of protein interaction interfaces using AlphaFold and experimental validation. Molecular systems biology, 20(2), 75–97. https://doi.org/10.1038/s44320-023-00005-6\n[4] Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., Bridgland, A., Meyer, C., Kohl, S. A. A., Ballard, A. J., Cowie, A., Romera-Paredes, B., Nikolov, S., Jain, R., Adler, J., Back, T., … Hassabis, D. (2021). Highly accurate protein structure prediction with AlphaFold. Nature, 596(7873), 583–589. https://doi.org/10.1038/s41586-021-03819-2\n[5] Ma, D., Lin, K. Y., Suresh, D., Lin, J., Gujar, M. R., Aung, H. Y., Tan, Y. S., Gao, Y., Vincent, A. S., Chen, T., & Wang, H. (2024). Arl2 GTPase associates with the centrosomal protein Cdk5rap2 to regulate cortical development via microtubule organization. PLoS biology, 22(8), e3002751. https://doi.org/10.1371/journal.pbio.3002751\n6. The authors need to specify whether they also examined the sex of the mice in this experiment or whether only male mice were used. Lipid metabolism differs between males and females due to hormonal regulation; PPARγ activity is sex-dependent in metabolic disorders.\nAnswer: Recognizing the well-documented influence of hormonal regulation on lipid metabolism and PPARγ activity, we specifically focused this investigation on male mice to avoid potential confounding effects of hormonal variations. Nevertheless, we also observed the same phenotypes in female mice with liver-specific Arg1 knockout as in males, including developmental delay and significant reduction in abdominal fat. This suggests that Arg1 may play a similar role in female mice, which warrants further investigation.\nDiscussion:\n1. The study focuses on Arg1 enhancing the ubiquitination of ERK2; however, it fails to identify the specific E3 ligase involved in this process (authors can do a co-IP with known E3 ligases).\nAnswer: We sincerely appreciate the reviewer's insightful suggestion regarding the identification of the specific E3 ligase involved in Arg1-mediated ERK2 ubiquitination. While our current study has established Arg1's crucial role in promoting ERK2 ubiquitination (as shown in Figures 4 and 5), we fully acknowledge that characterizing the specific E3 ligase would significantly strengthen our mechanistic understanding.\nTo address this gap, we have conducted systematic co-IP screening of established ERK-related E3 ligases (including NEDD4L, MEKK1, and TRIM21).1-4 Our findings, illustrated in the revised figures, include:\n(1) MEKK1 demonstrated robust and consistent binding to ERK2 across multiple experimental conditions (A).\n(2) This interaction was further attenuated following siArg1 treatment (B).\n(3) Mutation of the substrate-binding site on ERK2 attenuated its interaction with ERK2-related E3 ligases (C).\n(4) Neither NEDD4L nor TRIM21 showed detectable binding to ERK2, and this interaction pattern remained unchanged upon Arg1 knockdown (A).\nThese results strongly suggest MEKK1 may serve as the primary E3 ligase mediating Arg1-dependent ERK2 ubiquitination. We believe these data represent meaningful progress toward complete mechanistic elucidation, while honestly acknowledging the need for further validation (e.g., in vitro ubiquitination assays).\nIdentification of MEKK1 as an ERK2-binding E3 ligase and analysis of ERK2 ubiquitination. The relevant data are shown in Figure S6P (supplemental), Figure 4Q, and Figure 5C (main text).\nReferences:\n[1] Sala-Gaston, J., Costa-Sastre, L., Pedrazza, L., Martinez-Martinez, A., Ventura, F., & Rosa, J. L. (2023). Regulation of MAPK Signaling Pathways by the Large HERC Ubiquitin Ligases. International journal of molecular sciences, 24(5), 4906. https://doi.org/10.3390/ijms24054906\n[2] Wang, K., Tang, J., Liu, X., Wang, Y., Chen, W., & Zheng, R. (2020). UBR5 regulates proliferation and radiosensitivity in human laryngeal carcinoma via the p38/MAPK signaling pathway. Oncology reports, 44(2), 685–697. https://doi.org/10.3892/or.2020.7620\n[3] Liu, Y., Liu, F., Li, C., Zhang, T., Han, T., Dai, Y., Huang, N., Tang, H., Wang, X., Lin, S., Xue, L., & Wu, Z. B. (2025). TRIM21-mediated ubiquitination and phosphorylation of ERK1/2 promotes cell proliferation and drug resistance in pituitary adenomas. Neuro-oncology, 27(3), 727–742. https://doi.org/10.1093/neuonc/noae241\n[4] Lu, Z., Xu, S., Joazeiro, C., Cobb, M. H., & Hunter, T. (2002). The PHD domain of MEKK1 acts as an E3 ubiquitin ligase and mediates ubiquitination and degradation of ERK1/2. Molecular cell, 9(5), 945–956. https://doi.org/10.1016/s1097-2765(02)00519-1\n2. This study primarily examines the liver, but Arg1 is also expressed in adipose (fat) and muscle tissues, which may affect systemic lipid metabolism. Does systemic Arg1 inhibition also impact energy balance, fatty acid oxidation, or glucose metabolism beyond the liver?\nAnswer: This is an excellent question that gets to the heart of translational research.\nArg1 is predominantly expressed at high levels in hepatocytes. In contrast, its expression in adipose and muscle tissues is restricted to a small population of M2 macrophages and remains very weak in adipocytes or muscle cells. In this study, we generated liver-specific Arg1 knockout mice, and our findings clearly demonstrated that alterations in lipid metabolism resulted from hepatic Arg1 ablation. While we cannot exclude the potential role of Arg1 in lipid metabolism within adipose and muscle tissues, further investigation using adipose tissue-specific or muscle-specific Arg1 knockout mouse models would be required to clarify this possibility.\nIn our supplementary experiments, we compared daily food intake, oxygen consumption (VO₂), carbon dioxide production (VCO₂), and whole-body energy metabolism between TBGcreArg1fl/fl and Arg1fl/fl mice. No significant differences were observed in these parameters (Figure S3).\nConsistent with these findings, TBGcreArg1fl/fl mice exhibited no alterations in energy balance and fasting blood glucose levels.\nOur data suggested that Arg1 ablation modulates lipid metabolism through the ERK2-related signaling pathway. As a transition-state analog inhibitor, BEC features a tetrahedral boronate anion that structurally mimics the intermediate formed during L-arginine hydrolysis. The α-carboxylate and α-amino groups of BEC form three direct hydrogen bonds and four water-mediated hydrogen bonds with the manganese-containing active site of human Arg1, a binding pattern that closely mirrors substrate interactions (Figure below). This binding effectively blocks the Arg1-ERK2 interaction, producing effects analogous to Arg1 ablation.\nGiven that liver-specific inducible Arg1 ablation in TBGcreArg1fl/fl mice does not perturb energy homeostasis or glucose metabolism, systemic BEC administration is unlikely to disrupt these parameters--much less through inhibiting Arg1 in adipocytes and muscle cells to affect energy or glucose metabolism. Furthermore, gene and protein analyses suggest that BEC may regulate lipid metabolism via the PPARγ signaling pathway, sharing signaling changes similar to those observed with genetic Arg1 inactivation.\nHypothesis for the mechanism of the Arg1 inhibitor BEC (only for review). The revised figure is now presented as Figure 2A in the main text.\n3. Since leptin regulates hepatic lipid metabolism, leptin mutation might partly influence any metabolic changes seen with Arg1 inhibition. Using DB/db mice to study Arg1 inhibition in obesity and MASLD is reasonable due to their characteristic metabolic dysfunctions, such as obesity and insulin resistance. However, their leptin receptor mutation may limit how well they mimic MASLD progression. The authors should clarify this in the discussion.\nAnswer: We sincerely appreciate the reviewer's insightful comments. We fully acknowledge that the leptin receptor mutation may limit its ability to fully recapitulate MASLD progression. Since leptin itself possesses pro-fibrotic properties (e.g., by activating hepatic stellate cells), the leptin signaling deficiency in db/db mice may attenuate fibrosis progression, making it challenging to model the transition from simple steatosis to metabolic dysfunction-associated steatohepatitis (MASH) and cirrhosis as observed in human disease. Consequently, this model is more suitable for studying early-stage obesity-related steatosis rather than advanced MASLD phenotypes. To address this limitation, we have written the corresponding explanation in lines 200-202."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have responded in detail to my comments, and I appreciate their efforts. Most of my points have been addressed appropriately: the new data under HFD and MCD conditions and the correlation with ERK2 activity are convincing, the effect of arginine treatment was clarified, the specificity of the Arg1–ERK2 interaction was tested against Arg2 and through AlphaFold predictions, and the quantification of WB data has been improved. Minor issues such as figure labels and methodological details were also corrected. These changes improve the manuscript substantially.\nOne of my most important comments, however, was about whether Arg1 expression could serve as a disease marker. The authors state that they could not validate Arg1 expression in human samples because of limited availability. This explanation is not very clear. At least some attempt using public datasets (for example GTEx or GEO) would have been possible. Without such data, the claim that Arg1 may act as a biomarker or therapeutic target in obesity and MASLD is not well supported.\nI think there are two possible ways forward. Either the authors include some analysis of public human datasets, even if only at the RNA level, or they adjust the sentences in the Abstract and main text to clearly restrict their claims to mouse models. In particular, expressions like “Arg1 as a biomarker and regulator” or “promising therapeutic target” are too strong without human evidence. I recommend the former.\nAt the same time, although disappointing, the lack of human datasets in my opinion does not reduce the value of the study, which is strong in its mechanistic insights. But I think it would be more accurate, and also more transparent to readers, if the claims were phrased with the proper limitations. Whether the biomarker aspect is essential for acceptance is, in the end, for the editor to decide. If the paper is revised accordingly, I would support acceptance.", "reviewer_3": "Thank you for the thorough response. All our comments have been addressed.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_5": "Most of the concerns have been addressed well, however, several concerns remain:\n1. Both genetic models (constitutive and inducible hepatocyte-specific Arg1 knockout) and pharmacological inhibition (BEC) of Arg1 produce similar phenotypes: significantly reduced body weight, decreased hepatic lipid accumulation, and markedly reduced adipose tissue mass and cell size even, even under normal chow conditions. These effects may involve both enzymatic and non-enzymatic function of Arg1, as L-arginine accumulates in these models and the non-enzymatic role Arg1/ERK2 interaction primarily occur in hepatocytes. However, hepatocyte-intrinsic mechanisms (AKT/mTOR/PPARγ and/or Elk1/c-Fos/PPARγ ) cannot fully explain the adipose tissue changes. So, what could be the mechanisms underlying hepatic Arg1 deficiency-induced reduction in adipose tissue? The statement in the current response “This process ultimately accelerates hepatic lipid synthesis and adipose tissue lipid accumulation, highlighting the critical role of Arg1 in pathogenesis obesity and MASLD” is not appropriate. All these should be at least carefully considered and discussed in the manuscript.\n2. Reduced body weight in inducible Arg1 Hep-KO mice cannot be explained by changes in energy expenditure or food intake. Again, what mechanisms balance the energy input and output? Could factors such as physical activity or nutrient absorption contribute? Or still due to the toxic effect?\n3. The statement regarding BEC treatment in cell studies (Figure S4A, B) “occurs independently of L-arginine accumulation” is not supported, as BEC inhibits both Arg1 enzymatic activity and its interaction with ERK2. This conclusion should be revised."}, "author_response": "Response to Reviewer #1:\nThe authors have responded in detail to my comments, and I appreciate their efforts. Most of my points have been addressed appropriately: the new data under HFD and MCD conditions and the correlation with ERK2 activity are convincing, the effect of arginine treatment was clarified, the specificity of the Arg1–ERK2 interaction was tested against Arg2 and through AlphaFold predictions, and the quantification of WB data has been improved. Minor issues such as figure labels and methodological details were also corrected. These changes improve the manuscript substantially.\nOne of my most important comments, however, was about whether Arg1 expression could serve as a disease marker. The authors state that they could not validate Arg1 expression in human samples because of limited availability. This explanation is not very clear. At least some attempt using public datasets (for example GTEx or GEO) would have been possible. Without such data, the claim that Arg1 may act as a biomarker or therapeutic target in obesity and MASLD is not well supported.\nI think there are two possible ways forward. Either the authors include some analysis of public human datasets, even if only at the RNA level, or they adjust the sentences in the Abstract and main text to clearly restrict their claims to mouse models. In particular, expressions like “Arg1 as a biomarker and regulator” or “promising therapeutic target” are too strong without human evidence. I recommend the former.\nAt the same time, although disappointing, the lack of human datasets in my opinion does not reduce the value of the study, which is strong in its mechanistic insights. But I think it would be more accurate, and also more transparent to readers, if the claims were phrased with the proper limitations. Whether the biomarker aspect is essential for acceptance is, in the end, for the editor to decide. If the paper is revised accordingly, I would support acceptance.\nAnswer: We thank the reviewer for this important point. Analysis of human liver transcriptome data (GEO: GSE89632, GSE96936, GSE62267) revealed no significant difference in Arg1 mRNA levels between NAFLD patients and healthy controls. This could be attributed to the already high baseline expression of Arg1, which may have masked any further upregulation. Additionally, we cannot exclude the possibility of post-translational modifications. These findings support our cautious stance. Accordingly, we have revised the manuscript to clarify that our conclusions are primarily based on mouse model data, softened all related claims to indicate \"potential possibilities,\" and removed direct references to Arg1 as a human \"biomarker\" or \"therapeutic target.\"\nKey revisions include:\n1. In the abstract, we have explicitly qualified the relevant conclusions as \"found in a mouse model\" (…in a mouse model…) on lines 24 and 35.\n2. We have revised absolute statements such as \"Arg1 as a biomarker\" to: \"Beyond its classical role, accumulating evidence suggests that Arg1 could act as both a candidate biomarker and a regulator in obesity and MASLD.\" on lines 56-57.\n3. We have revised \"We have identified Arg1 as a promising therapeutic target for obesity and MASLD\" to: \"Our data, obtained from a male mouse model, support the notion that Arg1 is a potential therapeutic target for obesity and MASLD.\" on line 418-419.\nWe believe these revisions have made the manuscript more accurate and rigorous. They preserve the core value of the mechanistic study in mice while clearly communicating to readers the current scope of the conclusions and the direction for future translation.\nOnce again, thank you for helping us improve the quality of the paper.\nReviewer #3 (Remarks to the Author):\nThank you for the thorough response. All our comments have been addressed.\nReviewer #4 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.\nReviewer #5 (Remarks to the Author):\n1. Both genetic models (constitutive and inducible hepatocyte-specific Arg1 knockout) and pharmacological inhibition (BEC) of Arg1 produce similar phenotypes: significantly reduced body weight, decreased hepatic lipid accumulation, and markedly reduced adipose tissue mass and cell size even, even under normal chow conditions. These effects may involve both enzymatic and non-enzymatic function of Arg1, as L-arginine accumulates in these models and the non-enzymatic role Arg1/ERK2 interaction primarily occur in hepatocytes. However, hepatocyte-intrinsic mechanisms (AKT/mTOR/PPARγ and/or Elk1/c-Fos/PPARγ) cannot fully explain the adipose tissue changes. So, what could be the mechanisms underlying hepatic Arg1 deficiency-induced reduction in adipose tissue? The statement in the current response “This process ultimately accelerates hepatic lipid synthesis and adipose tissue lipid accumulation, highlighting the critical role of Arg1 in pathogenesis obesity and MASLD” is not appropriate. All these should be at least carefully considered and discussed in the manuscript.\nAnswer: We sincerely appreciate the reviewer's positive feedback and constructive comments, which have greatly helped improve our manuscript. We have revised the inaccurate statements in the manuscript (see lines 482–494 in the revised version).\nUnder wild-type conditions, adipose tissue accumulation is generally closely associated with food intake and hepatic lipid synthesis. However, in this study, we found that mice with hepatocyte-specific Arg1 knockout exhibited significant reductions in adipose tissue and body weight even under a normal chow diet. According to our data, food intake and total energy expenditure were not increased in the knockout mice (see Figure S3), indicating that the weight loss was not driven by reduced food consumption or enhanced systemic thermogenesis. Our data show that hepatic lipid synthesis is reduced. Therefore, we propose the main hypothesis that Arg1 deficiency in the liver leads to decreased hepatic lipid synthesis, thereby reducing the supply of lipids delivered from the liver to peripheral adipose tissue, ultimately resulting in diminished adipose tissue reserves. This may be the primary reason for the observed phenotype. At the same time, we cannot rule out the possibility that the accumulated excess arginine in peripheral blood may itself exert direct effects on adipose tissue.\nMultiple studies have confirmed that exogenous L-arginine supplementation promotes the reduction of white adipose tissue and enhances energy expenditure.1,2 Furthermore, arginine metabolism is closely associated with liver-secreted hormones such as FGF21, which is a key regulator of adipose tissue metabolism.3 These factors could drive adipose tissue atrophy even under conditions of unchanged systemic energy expenditure.\nAlthough the enzymatic functions of Arg1 might contribute to the observed adipose tissue reduction, emerging evidence suggests that its non-enzymatic functions likely play a more predominant role. We have elaborated on this in the discussion section to provide a more comprehensive explanation of the potential mechanisms.\n[1] Kalezic A, Korac A, Korac B, Jankovic A. L-Arginine Induces White Adipose Tissue Browning-A New Pharmaceutical Alternative to Cold. Pharmaceutics. 2022;14(7):1368. doi:10.3390/pharmaceutics14071368\n[2] Wu Z, Satterfield MC, Bazer FW, Wu G. Regulation of brown adipose tissue development and white fat reduction by L-arginine. Curr Opin Clin Nutr Metab Care. 2012;15(6):529-538. doi:10.1097/MCO.0b013e3283595cff\n[3] Zhang Y, Higgins CB, Van Tine BA, Bomalaski JS, DeBosch BJ. Pegylated arginine deiminase drives arginine turnover and systemic autophagy to dictate energy metabolism. Cell Rep Med. 2022;3(1):100498. doi:10.1016/j.xcrm.2021.100498\n2. Reduced body weight in inducible Arg1 Hep-KO mice cannot be explained by changes in energy expenditure or food intake. Again, what mechanisms balance the energy input and output? Could factors such as physical activity or nutrient absorption contribute? Or still due to the toxic effect?\nAnswer: We thank the reviewer for raising this important point.\nOur analysis of the metabolic cage data show that the total energy expenditure (EE) of the induced Arg1 knockout mice did not significantly differ from that of the control group (data in Figure S3). This strongly indicates that the weight loss is not driven by an increase in basal metabolic rate or overall thermogenesis associated with activity. Regarding the specific mechanisms inquired by the reviewer, we offer the following considerations:\nOur analysis indicates that elevated energy expenditure is unlikely to be a major driver of the observed energy deficit. Total energy expenditure calculated from gas exchange remained unchanged, which largely excludes the possibility that substantial and sustained increases in physical activity are responsible. We note that physical activity was not directly monitored, and therefore cannot completely rule out subtle changes in activity patterns (e.g., a shift in the proportion of low-intensity activity). However, such variations typically contribute minimally to overall energy balance and are unlikely to account for progressive weight loss. As for nutrient absorption, while theoretically a variable in the absence of altered food intake, the absence of direct measurements (e.g., fecal energy determination) precludes a definitive conclusion. We consider it more plausible that any change in absorption efficiency would be a downstream consequence of the hepatic metabolic disturbance (such as altered ammonia levels affecting the intestinal environment), rather than an independent, primary cause.\nOur data indicate that hepatic fatty acid synthesis is significantly suppressed following Arg1 knockout. We hypothesize that when the liver's capacity to synthesize and store lipids is impaired, the ingested energy may be \"redirected\" to other high energy-consuming processes. We found that Arg1 deficiency severely compromises the urea cycle, leading to hyperargininemia and elevated blood ammonia. Under these conditions, the body is forced to activate secondary detoxification pathways, primarily involving glutamine synthetase, which converts ammonia into glutamine in peripheral tissues for subsequent renal excretion.1 Notably, this pathway is energetically less efficient than the urea cycle—estimates suggest that while the urea cycle consumes approximately 1.5 ATP per molecule of ammonia cleared, the glutamine synthesis pathway requires about 2.5 ATP. Therefore, we propose that the body weight loss induced by Arg1 deficiency is primarily driven by the direct suppression of hepatic lipid synthesis, and that the concomitant hyperammonemia forces the organism into a high-energy-cost compensatory state for ammonia detoxification, further exacerbating overall energy expenditure.\nSo，we propose that the weight loss in the inducible Arg1 knockout mice stems primarily from impaired energy storage function and reduced utilization efficiency caused by suppressed hepatic fat synthesis, rather than from increased total energy expenditure. Subtle changes in physical activity or potential effects on nutrient absorption efficiency likely play only secondary or concomitant roles. This study offers one potential mechanistic insight, and further investigation is needed to confirm this interpretation. We have elaborated on this in the discussion section (lines 482–494).\n[1] Oliva L, Alemany M, Remesar X, Fernández-López JA. The Food Energy/Protein Ratio Regulates the Rat Urea Cycle but Not Total Nitrogen Losses. Nutrients. 2019;11(2):316. doi:10.3390/nu11020316\n3. The statement regarding BEC treatment in cell studies (Figure S4A, B) “occurs independently of L-arginine accumulation” is not supported, as BEC inhibits both Arg1 enzymatic activity and its interaction with ERK2. This conclusion should be revised.\nAnswer: Thank you very much for your careful review and further follow-up.\nWe appreciate the reviewer's rigorous critique. We understand that as an inhibitor, BEC has dual effects, making it challenging to precisely distinguish between its inhibition of enzymatic activity and its disruption of protein-protein interactions. However, our data indicate that BEC's regulation of lipid metabolism is at least partially mediated through a unique mechanism involving direct disruption of the Arg1-ERK2 interaction. In BEC-treated AML12 cells, both co-IP and Duolink proximity ligation assays confirmed significant disruption of Arg1-ERK2 binding (Figures 4G and 4H). In contrast, treatment with 100 µmol/L L-arginine alone—which leads to arginine accumulation—did not disrupt this interaction (Figure S5G), indicating that arginine accumulation per se is insufficient to disrupt the binding. Concurrently, BEC treatment effectively inhibited lipid droplet formation and modulated the expression of lipogenesis-related proteins (Figures S4A and S4B). Therefore, BEC’s direct interference with the Arg1-ERK2 complex constitutes an important mechanism underlying its regulatory function, which differs from pathways potentially triggered solely by arginine accumulation due to enzymatic inhibition.\nWe sincerely apologize for any misunderstanding caused by the imprecise wording in our previous response. In light of your valuable feedback, we have carefully revised the relevant content in the Results section (lines 190–192) of the manuscript and removed any overly definitive statements.\nThank you for helping us ensure the precision of academic communication."}, {"round": 3, "reviewer_comments": {"reviewer_5": "Thank you for your efforts in addressing my comments. I have no further concerns."}, "author_response": ""}]

Decision letter