Aucubin improves glucolipid metabolic disorder in T2DM mice via the miR-505- 5p/IGF1/FIT1/IRS1/PI3K signaling pathway

Aucubin improves glucolipid metabolic disorder in T2DM mice via the miR-505- 5p/IGF1/FIT1/IRS1/PI3K signaling pathway | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Aucubin improves glucolipid metabolic disorder in T2DM mice via the miR-505- 5p/IGF1/FIT1/IRS1/PI3K signaling pathway Mengyuan Qin, Yumeng Liu, Zenglong Chen, Xin Ren This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8202756/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Diabetes is characterized by impaired glucolipid metabolism and chronic inflammation. Aucubin, a natural compound, has shown potential for improving metabolic disorders, but its mechanisms remain unclear. To investigate the effects of aucubin on glucolipid metabolism and the underlying mechanisms in diabetic mice. Diabetic mice were induced by a high-fat diet and streptozotocin. Aucubin was administered, and its effects on metabolic parameters, tissue injury, and molecular profiles were assessed. Fasting blood glucose, insulin, lipid levels, and inflammatory markers were measured. Liver and pancreatic tissues were examined for histological changes. MiRNA and mRNA expression profiles were analyzed using sequencing, and miRNA-mRNA regulatory pairs were identified. Cell transfection and western blotting were performed to validate the regulatory mechanisms. Aucubin significantly reduced fasting blood glucose, triglycerides, total cholesterol, and inflammatory factors, while increasing fasting insulin, pancreatic β-cell function, and high-density lipoprotein cholesterol. It also alleviated liver and pancreatic tissue injury. Transcriptomic analysis identified 143 differentially expressed miRNAs and 2835 differentially expressed mRNAs, with 69 mRNAs enriched in the PI3K/AKT and insulin resistance pathways. Aucubin downregulated miR-505-5p, which negatively regulated IGF1 expression, thereby affecting the FIT1/IRS1/PI3K signaling pathway. Aucubin exerts anti-diabetic effects by mediating miR-505-5p targeting IGF1 to regulate the FIT1/IRS1/PI3K signaling pathway, offering a potential therapeutic strategy for diabetes. Biological sciences/Biochemistry Biological sciences/Cell biology Health sciences/Diseases Health sciences/Endocrinology Biological sciences/Molecular biology Biological sciences/Physiology Aucubin Glycolipid metabolism Type 2 Diabetes mellitus microRNA mRNA Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Natural bioactive compounds have emerged as promising therapeutic candidates for diabetes management [ 1 ]. Aucubin, a cyclopentanoid monoterpene glucoside, demonstrates multifaceted bioactivities including hypolipidemic, antioxidant, and anti-inflammatory effects, along with hepatopancreatic protection and metabolic regulation [ 2 , 3 ]. Notably, its antidiabetic potential has been evidenced through enhanced insulin sensitivity, pancreatic β-cell preservation, and blood glucose normalization in diabetic models [ 4 ]. Vaidya et al. [ 5 ] indicated that aucubin had a strong affinity with the pyridoxal phosphate binding site of glycogen phosphorylase, effectively inhibiting glycogen decomposition. Shen et al. [ 6 ] reported that aucubin could alleviate fat accumulation and oxidative stress caused by long-term hyperglycemia through Nrf2/HO-1 and AMPK signalling pathways. However, the precise molecular mechanisms underlying its glucoregulatory effects remain incompletely elucidated. Emerging evidence implicates microRNAs (miRNAs) ascritical regulators in type 2 diabetes mellitus (T2DM) pathogenesis, functioning through post-transcriptional gene silencing via 3'UTR targeting [ 7 ]. These non-coding RNAs have emerged as promising diagnostic biomarkers and therapeutic targets [ 7 ]. For example, Su et al. [ 8 ] reported that miR-34a-5p affected pancreatic β-cell proliferation through the Wnt signaling pathway and regulated insulin secretion through the insulin signaling pathway, further altering blood glucose levels. Recent advances in omics technologies have enabled systematic exploration of miRNA-mediated antidiabetic mechanisms. Whole Grain Proso Millet could inhibit gluconeogenesis by improving miRNA expression profile and activating PI3K/AKT signaling pathway, thus playing an anti-diabetic role [ 9 ]. whole grain highland barley improved glycogen synthesis and alleviated IR by regulating the IRS-1/PI3K/ AKT pathway and associated miRNAs such as increasing the expression of miRNA-26a and miRNA-451 as well as decreasing the expression of miRNA-126a and miRNA-29a [ 10 ]. Despite these advances, the miRNA-dependent mechanisms of aucubin's antidiabetic action remain uncharacterized. This study therefore investigates the therapeutic potential of aucubin in HFD/STZ-induced diabetic mice, employing multi-omics approaches to elucidate its novel miRNA-mediated regulatory mechanisms. Our findings aim to provide mechanistic insights for developing miRNA-targeted therapies against T2DM. 2. Material and methods 2.1 Animals and experimental design Six-week-old SPF-grade male C57BL/6J mice were purchased from Beijing Vital River Laboratory Animal Technology Co Ltd (SCXK(Beijing)2021-0006). All mice had free access to food and water. They were kept in a laboratory with 55 ± 5% humidity and 12:12 light/dark cycle 22 ± 2°C. The animal experiments were approved by the Animal Ethics Committee of Pony Testing Group (PONY-2022-FL-90). The whole experimental process paid attention to animal welfare and strictly complied with the relevant regulations and provisions required by the International Council for Animal Welfare. After one week's adaptive feeding, 8 mice were randomly selected as normal control group (NC) with 10% low-fat chow. The remaining mice were fed 60% high-fat chow. After 4 weeks, 0.5% streptozotocin (STZ) was injected intraperitoneally for 4 days at a dose of 45 mg/kg based on mice body weight to induce the diabetic mice model. During this period, mice in NC were injected with equal volumes of saline based on body weight. Then, diabetic mice with fasting blood glucose concentration > 11.1 mmol/L were randomly assigned to 2 groups: model control group (MC, n = 8) with an equal volume of saline; and aucubin-treated group (AU, n = 8) with 10 mg/kg of aucubin solution. 60% high fat chow was purchased from Beijing Keao Xieli Feed Co., Ltd. as shown in Table 1 . After 6 weeks of intervention, oral glucose tolerance test (OGTT) was performed. Then, blood was taken from retro-orbital vein to collect serum and stored at -80°C. After execution of the mice, partial liver and pancreas tissues were collected in 4% paraformaldehyde, and the rest of the tissues were stored at − 80°C for subsequent experiments. Table 1 Nutritional content of experimental feed components Ingredient (g) 60% high-fat chow(g) 10% low-fat chow(g) Casein 2584.5 1895.6 L-cystine 38.8 28.4 Corn starch 0 4797.9 Maltodextrin 1615.5 1184.8 Sucrose 889.3 652.1 Cellulose 646.2 473.9 Soybean oil 323.2 237 Lard 3166 189.6 Mineral mix S10026 129.2 94.8 Calcium hydrogenphosphate 168 123.2 Raffinose 71.1 52.1 Potassium citrate monohydrate 213.2 156.4 Vitamin mix V10001 129.2 94.8 Choline bitartrate 25.8 19 Total 10000 10000 Protein(kcal %) 20 20 Fat(kcal %) 60 10 Carbohydrate(kcal %) 20 70 2.2 Detection of blood glucose and oral glucose tolerance test After 6 weeks of aucubin intervention and 12h fasting, tail vein blood was used for measuring fasting blood glucose (FBG) using Performa Blood Glucometer (Shanghai Roche Pharmaceuticals, China). All mice were gavaged with 20% glucose solution (2 g kg − 1 bw − 1 ) and blood glucose at 30, 60, 90 and 120 min were recorded. Area under the glucose tolerance curve (AUC) was then calculated [ 11 ]. 2.3 Serum Biochemical Analysis The concentration of tumor necrosis factor-alpha (TNF‑α), interleukin-1β (IL-1β), interleukin-6 (IL-6) and fasting insulin (FINS) in the serum were measured with the corresponding ELISA kits purchased from the Shanghai Enzyme-linked Biotechnology Co., Ltd (Shanghai, China). Insulin resistance index (HOMA-IR) and pancreatic β-cell function index (HOMA-β) were calculated using an in vivo homeostasis model assessment based on formula (1) and (2). The serum triglyceride (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C) was performed according to the manufacturer’s instruction (Nanjing Jiancheng Bioengineering Institute, Nanjing, China). $$\:HOMA-IR=(FBG\times\:FINS)/22.5$$ 1 $$\:HOMA-\beta\:=(20\times\:FINS)/(FBG-3.5)$$ 2 2.4 Hematoxylin and Eosin (H&E) staining The collected tissue samples were fixed with 4% paraformaldehyde followed by dehydration with graded ethanol and embedded in paraffin. Tissues were cut into 5 µm and then stained with H&E. Structural changes in liver and pancreatic tissue were observed under a microscope (Leica, Germany). 2.5 Small RNA libraries preparation and sequencing Illumina TruSeq Small RNA kits (Illumina, San Diego, CA) were used to generate sequencing libraries. After the 3' and 5' end junctions were ligated, 1st cDNA was synthesised by reverse transcription and used for PCR amplification. PCR amplification products were purified and recovered by 8% polyacrylamide gel electrophoresis to construct small RNA libraries. The Illumina Hiseq 2000 platform would be used for miRNA sequencing. 2.6 mRNA libraries preparation and sequencing Illumina TruSeqTM RNA sample prep Kit (Illumina, San Diego, CA) was performed for mRNA transcriptome library construction. The mRNA was isolated by A-T pairing of Oligo (dT) magnetic beads with polyA. Double-stranded cDNA was further synthesised using the SuperScript double-stranded cDNA synthesis kit (Invitrogen, CA) and random hexamers followed by end repair, phosphorylation and 'A' base addition. The 300 bp cDNA target fragment was selected for PCR amplification. RNA-seq sequencing libraries were sequenced using Illumina NovaSeq 6000. 2.7 Bioinformatics Analysis After quality control analysis of the raw reads to get clean reads, it was further compared to the reference genome. In terms of miRNAs, the clean reads from the ratio were further compared to the miRBase ( http://www.mirbase.org/ ) and Rfam ( http://rfam.xfam.org/ ) databases to identify the miRNAs. MiRNA and mRNA expression levels were then quantified based on TPM. Differential miRNAs (DEM) and differential mRNAs (DEG) were screened by |log2FC|≥2, P -value < 0.05. DEM was directly analysed for functional enrichment analysis. Target genes predicted by differential miRNAs using miRanda served for functional enrichment analysis. 2.8 miRNA-mRNA regulatory networks The miRNA-mRNA regulatory network was constructed from DEM and DEG enriched on AMPK, IR, and T2DM signalling pathway. After clustering analysis of DEM and DEG in the regulatory network, the regulatory pairs of miRNA-targeted negatively regulated mRNA were shown in a mulberry diagram. 2.9 Cells transfection Hepa1-6 cells in the well-grown state were seeded in 6-well plates at 5×10 5 cells/well. Cells were cultured using serum-free DMEM medium for 2h prior to transfection. The miR-505-5p mimic and its negative NC (RiboBio, Guangzhou, China) were transfected into Hepa1-6 cells using the lipofectamine2000 (Invitrogen, USA) named AU minic and AU minic NC groups. Cells were intervened after transfection with medium containing aucubin. The transfection efficiency was assessed based on qRT-PCR and Western Blot experiments. 2.10 Quantitative real-time polymerase chain reaction (qRT-PCR) RNA was extracted from liver tissues and cells using TransZol Up Plus RNA Kit (TransGen Biotech, Beijing, China) according to the manufacturer's manual. The RNA was then reverse transcribed into cDNA with miRNA 1st Strand cDNA Synthesis Kit (by stem-loop) (Vazyme; MR101) and HiScript® III All-in-one RT SuperMix Perfect (Vazyme; R333-01), respectively. The qRT-PCR was performed on ABI QuantStudio 3 (Applied Biosystems, Thermo Fisher, USA) using miRNA Universal SYBR qPCR Master Mix (Vazyme; MQ101) and Taq Pro Universal SYBR qPCR Master Mix (Vazyme; Q712). The relative abundance of miRNA and mRNA was normalized to U6 and β-actin. The relative amounts of the miRNAs and mRNA were measured using the 2 −ΔΔCt method. The miRNA and mRNA primers were designed and synthesised by RiboBio (Guangzhou, China) and Tsingke Biotech Co., Ltd (Beijing, China). The sequences of primers were shown in Table 2. Table.2 Specific gene primers used for qRT-PCR Gene Forward primer Reward primer IRS1 ATTAACCCCATCAGACGCCA AGGAGGTTTGGCATGAGGAA PI3K AATGCACGGCGATTACACTC GGACACTGGGTAGAGCAACT IGF1 CAGCTGGACCAGAGACCCTTT GAATGCTGGAGCCATAGCCTG FIT1 TTACCTGGATTCTGCTACGGAC GGTTCAGAGTGATGGAGTAATCTTG Egfr TCCCAGACAGACGACAGGTCA ACAGACGGAGTCCCACGGTT SOCS3 TTTCTTTGCCACCCACGGA AGGAGAGAGGTCGGCTCAGTAC β-actin TCAAGATCATTGCTCCTCCTGAG ACATCTGCTGGAAGGTGGACA 2.11 Western blotting Total protein was extracted from Hepa1-6 cells using RIPA lysis buffer (Servicebio, Wuhan, China). And the concentration was measured with BCA protein assay kit (Jiebes, Guangzhou, China). Proteins were separated by 10% SDS-PAGE gel and further transferred to polyvinylidene difluoride membrane (Millipore, Massachusetts, USA). Membrane was blocked by 5% skimmed milk powder for 2 h at room temperature. And membrane was incubated first with primary antibodies (Igf1, FIT1, IRS1 and PI3K) overnight at 4°C and then with HRP labeled secondary antibodies for 2 h at room temperature. The Proteins were detected by ECL substrate solution (Servicebio, Wuhan, China) and were quantified by ImageJ software. 2.12 Statistical analysis One-way analysis of variance was used when comparing between at least three groups. When two groups were compared, student’s t-test was used. Images were drawn and typeset using Adobe Illustrator CS6 (Adobe, San Jose, CA, USA) and GraphPad Prism 8.02 (GraphPad Prism, La Jolla, CA, USA) software. P < 0.05 was considered a statistically significant difference. 3. Results 3.1 Effects of aucubin on blood glucose metabolism in T2DM mice As shown in Fig. 1 A, the FBG of mice in the MC group was significantly higher than that in the NC group, whereas the intervention of aucubin significantly reduced the FBG of mice. The glucose tolerance of mice by oral glucose tolerance test was examined and shown in Fig. 1 B. All groups displayed peak blood glucose concentrations at 30 min post-gavage, with NC mice achieving baseline recovery by 90 min. In contrast, MC group maintained persistent hyperglycemia, demonstrating impaired glucose clearance. Notably, aucubin-treated mice exhibited accelerated glucose normalization, showing significantly lower blood glucose levels than MC group at 120 min ( P < 0.05). In addition, the AUC levels of mice in the MC group were significantly higher than those in the NC group, whereas they were significantly lower in the AU group. These results suggested that aucubin improved blood glucose tolerance and enhanced the ability to regulate blood glucose in diabetic mice. Compared with the NC group, mice in the MC group had significantly higher HOMA-IR ( P < 0.01) and lower FINS and HOMA-β ( P < 0.01). Interestingly, aucubin reversed these changes, with significantly increased levels of FINS ( P < 0.01) and HOMA-β ( P < 0.05), and decreased levels of HOMA-IR. 3.2 Effects of aucubin on dyslipidemia and inflammation in T2DM mice Compared to controls, MC group mice exhibited significantly elevated serum TG and TC levels (Figs. 1 G and H) accompanied by reduced HDL-C concentrations (Fig. 1 I). Aucubin supplementation markedly reversed these metabolic alterations in T2DM mice. Furthermore, aucubin administration significantly attenuated serum pro-inflammatory cytokine levels (TNF-α, IL-1β, IL-6) in the MC group (Figs. 1 J-L). 3.3 Effects of aucubin on injury of livers and pancreas in T2DM mice Histopathological analysis was performed to evaluate the hepatoprotective and pancreoprotective effects of aucubin in T2DM-induced tissue damage (Fig. 2 ) The results showed that the MC group exhibited marked structural disorganization of hepatocytes, characterized by microvesicular and macrovesicular steatosis accompanied by diffuse inflammatory cell infiltration with focal aggregation. Hepatic histological examination revealed that compared to NC group, aucubin treatment markedly attenuated these hepatic pathological changes, demonstrating significant reduction in both lipid accumulation and inflammatory responses. Furthermore, pancreatic histomorphometric analysis indicated that aucubin supplementation effectively mitigated diabetes-associated pathological alterations in islet architecture, including substantial alleviation of inflammatory infiltration, preservation of normal islet morphology, and prevention of β-cell mass depletion observed in MC group animals. 3.5 Effect of aucubin on hepatic miRNA expression profile in T2DM Mice To investigate the effect of aucubin on miRNA expression profiles in T2DM mice, miRNA libraries from mice liver (NC = 3, MC = 3 and AU = 3) were constructed by small RNA sequencing. More than 10.19 M raw reads were obtained from each sample, and more than 8.92 M clean reads were obtained after quality control, which was over 96% of Q30 (Table S1 ) and mainly distributed in the range of 21–23 nt (Figure S1 ). Then, mapped miRNAs on the reference genome were identified as known miRNA and predicted new miRNA. As shown in the table S2, the miRNA identified in the nine libraries ranged from 566 to 671, with known miRNA within 478–632 and novel miRNAs in 35–88. These miRNAs were subjected to subsequent screening of DEM to analyse the mechanism by which aucubin regulated glucose metabolism in T2DM mice. The DEM of each group were screened by |log2FC|≥2, P -value < 0.05, with results shown in Fig. 3 A. A total of 143 DEM was screened in different groups (AU vs MC, AU vs NC, MC vs NC). Compared with the NC group, 25 miRNAs were significantly upregulated and 64 miRNAs were significantly downregulated, whereas 36 were significantly upregulated and 80 were significantly downregulated in the AU group. And 6 miRNAs were significantly upregulated and 9 miRNAs were significantly downregulated in the AU group compared with the MC group. 3.6 Effect of aucubin on hepatic mRNA expression profile in T2DM Mice RNA from 9 mice livers (NC = 3, MC = 3 and AU = 3) was extracted for mRNA library construction. A total of 59.85G clean reads were obtained, with Q30 over 96.23% (Table S3). The clean reads were aligned with the reference genome, and the mapped rate ranged from 92.33% to 97.14% (Table S4), indicating that the sequencing quality was high and the library construction was successful. The mapped data were then further quantified to identify DEG among the different groups. As shown in Fig. 3 B, a total of 2835 DEG were screened in different groups (AU vs MC, AU vs NC, MC vs NC). Compared with the NC group, 823 mRNAs were significantly upregulated and 1187 mRNAs were significantly downregulated, whereas 844 were significantly upregulated and 884 were significantly downregulated in the AU group. And 294 mRNAs were significantly upregulated and 92 mRNAs were significantly downregulated in the AU group compared with the MC group. These DEG provided important evidence for investigating further the mechanism of glucose metabolism regulation by aucubin. 3.7 Functional analysis KEGG enrichment analysis was performed on the above 2835 DEG. These DEG were enriched into 336 signalling pathways in total, with 83 signalling pathways significantly enriched (Pvalue < 0.05). The top 66 significantly enriched signalling pathways were visualized by bubble plots (Fig. 3 C). Notably, these DEG were significantly enriched in signalling pathways related to glucose metabolism, such as PI3K/AKT (55 genes), AMPK (21 genes), IR (19 genes), and T2DM (10 genes) signalling pathway. Total 82 DEG enriched in these signalling pathways were used to construct miRNA-mRNA regulatory networks. 3.8 Validation of predicted differential miRNA and mRNA Four miRNA (miR-205-5p, miR-672-5p, miR-505-5p and miR-455-5p) and four mRNA (FIT1, Egfr, IGF1 and SOCS3) associated with glucose metabolism were subjected to qRT-PCR. Their expression trends were consistent with the transcriptome (Fig. 4 ). The results suggested that aucubin might mediate these miRNA and mRNA to ameliorate T2DM. 3.9 miRNA-mRNA regulatory network The miRNAs played a functional role by targeting mRNA. Therefore, the above 143 DEM and 69 DEG enriched in PI3K/AKT and IR were subjected to miRNA-mRNA regulatory network construction. As shown in Fig. 5 A, there were 122 miRNA-mRNA pairs, with 68 DEM and 45 DEG in miRNA-mRNA regulatory network. After hierarchical clustering analysis, a heatmap of the expression of these miRNAs and miRNAs in different treatment groups was obtained (Fig. 5 B and 5 C). Eventually, 13 regulatory pairs that satisfying miRNA to negatively regulate mRNA were obtained, i.e. miR-455-5p-Prkca, miR-744-5p-Itga10, miR-505-5p-Igf1, miR-205-5p-Gng11, miR-138-5p-FIT1, miR-664-5p-Egfr, miR-499-5p-Egfr, miR-505-5p-Col6a1, miR-541-5p-Chrm1, miR-1949-Chrm1, 17_16061-Slc2a4, 4_24287-prkca, 17_16061-Pik3r3 (Fig. 5 D). 3.10 miR-505-5p negatively regulated IGF1 IGF1 was significantly downregulated in T2DM mice and significantly upregulated after aucubin intervention (Fig. 4 ). Moreover, miR-505-5p could negatively regulate IFG1 from miRNA-mRNA analysis (Fig. 5 D). We hypothesized that aucubin mediated miR-505-5p- targeted regulation of IFG1 participating in the improve glucose metabolism of aucubin in T2DM mice. To validate this mechanism, we established a miR-505-5p overexpression model through transfection with miR-505-5p mimic in Hepa1-6 cells. As shown in Fig. 6 , expression of miR-505-5p after transfecting miR-505-5p minic NC was no significant difference comparing with AU group, but after transfecting miR-505-5p minic, it was significantly higher than that in AU and AU minic NC group. However, transfection with miR-505-5p mimic resulted in significantly elevated miR-505-5p levels compared to both AU and AU mimic NC groups, confirming successful transfection efficiency. Notably, IGF1 expression at both mRNA and protein levels exhibited significant suppression in the miR-505-5p mimic group relative to control groups. This post-transcriptional regulation of IGF1 protein expression strongly suggests that miR-505-5p inhibits IGF1 translation, thereby corroborating our bioinformatics predictions regarding miRNA-mediated negative regulation of IGF1. To further investigate the downstream consequences of this regulatory axis, we analyzed expression patterns of key glucose metabolism mediators (FIT1, IRS1, and PI3K) following miR-505-5p mimic transfection. These examinations aim to elucidate the functional pathway through which the aucubin-miR-505-5p-IGF1 axis modulates glycemic control. 3.11 Aucubin mediate miR-505-5P regulating IGF1/FIT1/IRS1/PI3K signalling pathway The relative mRNA and protein expression of FIT1/IRS1/PI3K after transfection with miR-505-5p minic were shown in Fig. 6 . The relative mRNA and protein expression of FIT1/IRS1/PI3K in AU minic group was significantly increased than that in AU and AU minic NC groups. These results indicated that miR-505-5p could mediate IGF1 to regulate the FIT1/IRS1/PI3K signalling pathway. Moreover, the expression of miR-505-5p in the livers of T2DM mice was significantly decreased after aucubin intervention (Fig. 4 ). Thus, aucubin could mediate miR-505-5p regulating IGF1 to further modulate the IGF1/FIT1/IRS1/PI3K signalling pathway to improve glucose metabolism in T2DM mice. 4 Discussion Type 2 diabetes mellitus (T2DM) is a prevalent metabolic disorder characterized by chronic hyperglycemia, whose multifactorial pathogenesis has established it as a global public health challenge [ 12 ]. This condition imposes not only significant health risks to individuals but also substantial economic burdens on healthcare systems worldwide [ 13 ]. Developing effective strategies to prevent disease progression, mitigate complications, and reduce diabetes-related morbidity therefore remains a critical research priority. As a kind of iridoid compound, aucubin has been reported to have antidiabetic activity [ 2 ]. This study further revealed the potential mechanism of its anti-diabetes based on transcriptomic, that is, it could regulate the expression profile of miRNA and mRNA in T2DM mice, thereby alleviating liver and pancreas damage, abnormal glucose and lipid metabolism, and IR in T2DM mice. Clinically, fasting blood glucose has been established as a crucial diagnostic biomarker for diabetes mellitus [ 14 ]. In this study, aucubin administration markedly reduced FBG levels in HFD/STZ-induced diabetic mice, suggesting its therapeutic potential for T2DM management. Notably, IR represents the primary pathophysiological mechanism underlying T2DM development. Hepatic insulin resistance leads to impaired insulin sensitivity, subsequently triggering compensatory hyperinsulinemia that progressively damages pancreatic β-cell function. This pathological cascade ultimately manifests as glucose intolerance, dysregulated glucose-lipid homeostasis, and full progression to T2DM [ 15 ]. Consistent with previous findings by Jin et al. [ 4 ] showing β-cell protective effects of aucubin in diabetic rat models. The present study revealed significant improvements in glucose regulation. Specifically, while the model control (MC) group exhibited persistent hyperglycemia with significantly elevated AUC values compared to normal controls (NC), aucubin-treated mice displayed rapid glucose normalization within 30 minutes post-administration, indicating restored glucose tolerance. Moreover, aucubin significantly increased FINS, HOMA-β and HDL-C, and significantly reduced TG, TC and HOMA-IR concentration in T2DM mice. These collective findings provide compelling evidence that aucubin effectively ameliorates diabetic metabolic dysregulation through dual mechanisms of enhancing insulin sensitivity and preserving β-cell functionality. The liver and pancreas are well-established as central regulators of glycolipid metabolism and insulin homeostasis, respectively. Clinical observations indicate that patients with T2DM typically present with hepatic and pancreatic dysfunction, creating a pathological cycle that exacerbates disease progression. Histopathological analysis revealed significant inflammatory infiltration and structural abnormalities in both hepatic and pancreatic tissues of MC group mice. Notably, aucubin administration markedly attenuated these pathological alterations. Consistent with histological findings, HE staining further confirmed the presence of systemic inflammation in diabetic mice. Mechanistically, chronic inflammation has been extensively documented to induce IR through multiple pathways, while persistent hyperglycemia reciprocally amplifies inflammatory responses - a vicious cycle contributing to diabetic complications [ 16 ]. The results demonstrated that aucubin treatment significantly downregulated serum levels of key pro-inflammatory mediators (TNF-α, IL-1β, IL-6). Importantly, this anti-inflammatory effect correlated with improved insulin sensitivity and restoration of pancreatic β-cell function. Collectively, our findings establish that aucubin exerts multimodal therapeutic effects on HFD/STZ-induced T2DM mice by ameliorating hepatic steatosis and pancreatic β-cell dysfunction, promoting insulin biosynthesis and secretion, and disrupting inflammation. These results provide preclinical evidence supporting aucubin's potential as a multi-target therapeutic agent for T2DM management. Emerging evidence underscores the regulatory significance of miRNA-mediated mechanisms in natural bioactive compounds' therapeutic effects through multilayer modulation of mRNA transcription and post-transcriptional processes. It was reported that flavonoid administration significantly enhances hepatic and adipose tissue miR-146a expression while suppressing NF-κB levels in T2DM rats [ 17 ]. Similarly, gallic acid demonstrates insulin-sensitizing effects through miR-1271 downregulation, subsequently activating key insulin signaling mediators including phosphorylated IRS, PI3K, AKT, and FoxO1[ 18 ]. In this study, aucubin administration induces significant alterations in both miRNA and mRNA expression profiles in diabetic mice, with 143 DEMs and 2835 DEGs identified through systematic screening. These molecular alterations establish a foundation for elucidating aucubin's therapeutic mechanisms in T2DM-associated metabolic dysregulation. KEGG pathway analysis revealed significant enrichment of identified DEGs in critical metabolic pathways, particularly IR, PI3K/AKT, AMPK and T2DM. The insulin-mediated PI3K/AKT pathway serves as a central regulator of systemic metabolic homeostasis, coordinating hepatic glucose production, peripheral glucose utilization, and lipid metabolism [ 19 ]. Mechanistically, insulin resistance manifests through impaired phosphorylation cascades in insulin receptor substrates and subsequent dysregulation of PI3K/AKT signaling activation [ 20 ]. Current research highlights natural compounds' capacity to modulate this critical pathway through miRNA regulation. In the study by He et al. [ 21 ] ferulic acid derivatives exhibit regulatory effects by upregulating miR-200c-3p to enhance PI3K/AKT activation via PTEN modulation. Additionally, Zhang et al. [ 22 ] also found that ferulic acid could inhibit the insulin signaling pathway by up-regulating miR-17 targeting negative regulation of PTEN. Complementary findings demonstrate caffeic acid's multi-target effects through regulation of miR-30a, miR-342, and miR-133b to activate both AMPK and PI3K signaling axes [ 23 ]. Based on these collective insights and our experimental evidence, we propose that aucubin ameliorates T2DM metabolic disturbances through coordinated modulation of miRNA-mRNA networks, particularly targeting IR amelioration and PI3K/AKT pathway restoration. To investigate the molecular mechanisms underlying aucubin-mediated miRNA regulation in T2DM, 143 DEM and 69 DEG enriched in IR and PI3K/AKT were used to construct miRNA-mRNA regulatory network. Hierarchical cluster analysis identified 13 miRNA-mRNA pairs exhibiting miRNA-targeted negative regulatory relationships, including miR-205-5p-Gng11, miR-455-5p-Prkca; miR-744-5p-Itga10; miR-505-5p-Igf1; miR-138-5p-FIT1; miR-541-5p-Chrm1; miR-1949-Chrm1; miR-505-5p-Col6a1; miR-664-5p-Egfr; miR-499-5p-Egfr; 17_16061-Slc2a4; 4_24287-prkca; and 17_16061-Pik3r3. Notably, several components within these regulatory pairs demonstrate established associations with T2DM pathophysiology. For example, miR-205-5p could inhibit the diabetic gene Tcf7l2 to regulate β-cell function and insulin secretion [ 24 ]. The Gng11, a miR-205-5p target gene in this study, was reported to be able to distinguish between gestational diabetes mellitus patients and normal people, and might be a therapeutic target for gestational diabetes mellitus [ 25 ]. However, the research on miR-205-5p mediated Gng11 to improve T2DM had not been explored in depth. In addition, our previous study revealed that whole grain highland barley could regulate miR-455-5p-Igf1r to improve glucose metabolism in diabetic mice [ 26 ]. Interestingly, another target gene Prkca of miR-455-5p was found in this study, which was also reported to be involved in the occurrence and development of T2DM [ 27 ]. It could be considered to further explore that aucubin might mediate miR-455-5p-Prkca to improve T2DM mice. Upregulation of miR-744-5p was identified as IR and as an important biomarker of T2DM [ 28 ]. In this study, miR-744-5p was upregulated in the MC group, while significantly downregulated in aucubin, indicating that aucubin could mediate miR-744-5p to improve T2DM. The target gene Itga10 predicted by miR-744-5p in this study was found to play a key role in T2DM osseointegration [ 29 ]. However, direct evidence of miR-744-5p/Itga10 involvement in T2DM pathogenesis remains unreported. Of particular interest, Orang et al. [ 30 ] found that metformin induced miR-132-3p to regulate PI3K/AKT signaling pathway by targeting PIK3R3. Collectively, these miRNA-mRNA found in this study have the potential to be targets for aucubin improving T2DM mice. Our findings suggest that aucubin may exert hypoglycemic effects through coordinated modulation of the PI3K/AKT and IR signaling pathways via specific miRNA-mRNA regulatory networks. Notably, IGF1, a key mediator with established insulin-mimetic properties in glucose homeostasis, emerged as a critical node in this regulatory cascade [ 31 ]. Bioinformatics analysis revealed that miR-505-5p possesses complementary binding sites to the 3'UTR of IGF1 mRNA, suggesting direct post-transcriptional regulation. In the insulin signaling cascade, IGF1 activation triggers a phosphorylation cascade through FIT1 and IRS1, ultimately activating the PI3K/AKT pathway [ 32 ]. Aucubin supplementation significantly upregulated the expression of IGF1 in the MC group. And miRNA-mRNA analysis showed that miR-505-5p negatively regulated IFG1. Therefore, we hypothesized that aucubin could mediate miR-505-5p targeting IGF1 to regulate FIT1/IRS1/PI3K signaling pathway. To this end, we first needed to validate the targeting regulatory effect of miR-505-5p on IGF1. The miR-505-5p minic was then transfected into Hepa1-6 cells. We found that the expression of IGF1 mRNA and protein after transfection with miR-505-5p minic was significantly lower than that in the AU and AU minic NC groups, suggesting that miR-505-5p does indeed target IGF1, thereby inhibiting its function. Interestingly, the relative mRNA and protein expression levels of FIT1, IRS1 and PI3K in the AU minic group were significantly higher than those in the AU and AU minic NC groups. These results suggested that miR-505-5p could target IGF1 and then mediated FIT1/IRS1/PI3K signaling pathway to improve T2DM mice. In addition, aucubin downregulated the expression of miR-505-5p in T2DM mice. Our data collectively support a model where aucubin ameliorates diabetic phenotypes through miR-505-5p/IGF1 axis-mediated potentiation of the FIT1/IRS1/PI3K signaling pathway. 5. Conclusion In conclusion, this investigation systematically demonstrates that aucubin significantly ameliorates metabolic dysregulation in T2DM mice through multi-faceted therapeutic effects, including glycolipid metabolism normalization, histopathological restoration of hepatic and pancreatic tissues, and anti-inflammatory modulation. Integrative bioinformatics analysis of miRNA-mRNA sequencing datasets identified 13 functionally correlated miRNA-mRNA pairs potentially mediating the therapeutic actions of aucubin. Mechanistic validation through gain-of-function experiments with miR-505-5p revealed that aucubin exerts its antidiabetic effects via miR-505-5p/IGF1 axis-mediated regulation of the FIT1/IRS1/PI3K signaling pathway. These findings position aucubin as a promising phytochemical candidate for T2DM prevention and management. This study further suggests that targeting disease-associated miRNA networks through natural bioactive compounds may represent a novel therapeutic paradigm for combating T2DM pathogenesis. Abbreviations AU Aucubin-treated group AUC Area under the glucose tolerance curve DEM Differential miRNAs DEG Differential mRNAs FBG Fasting blood glucose FINS Fasting insulin HFD/STZ High-fat diet and streptozotocin HDL-C High density lipoprotein cholesterol H&E Hematoxylin and Eosin HOMA-IR Insulin resistance index HOMA-β Pancreatic β-cell function index LDL-C Low density lipoprotein cholesterol IL-1β Interleukin-1β IL-6 Interleukin-6 MiRNA MicroRNA MC Model control group NC Normal control group OGTT Oral glucose tolerance test qRT-PCR Quantitative real-time polymerase chain reaction T2DM Type 2 diabetes milieus TNF‑α Tumor necrosis factor-alpha TG Triglyceride TC Total cholesterol Declarations Competing interests All authors have no confcts of interest to declare. Funding: This research was funded by the National Natural Science Foundation of China (No. 32101876). Author Contribution M.Y.Q, X.R. methodology, formal analysis and writing—review and editing. M.Y.Q. software, validation and writing—original draft preparation. X.R. conceptualization, investigation, project administration and funding acquisition. Y.M.L, X.R. data curation. Y.M.L. supervision. Z.L.C, X.R. resources. Z.L.C. visualization. Data Availability Data available on request from the authors References Roy D, Kaur P, Ghosh M, Choudhary D, Rangra NK. The therapeutic potential of typical plant-derived compounds for the management of metabolic disorders. Phytother Res 38(8): 3986–4008, 2024. Zeng X, Guo F, Ouyang D. A review of the pharmacology and toxicology of aucubin. Fitoterapia 140(104443, 2020. Potacnjak I, Marinic J, Baticic L, Simic L, Broznic D, Domitrovic R. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8202756","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":559185441,"identity":"adb3f375-7001-4c3a-84ac-2a31c18eb834","order_by":0,"name":"Mengyuan Qin","email":"","orcid":"","institution":"beijing technolpgy and business university","correspondingAuthor":false,"prefix":"","firstName":"Mengyuan","middleName":"","lastName":"Qin","suffix":""},{"id":559185442,"identity":"8f05ed66-3f53-4dbc-89d1-f4aea849623a","order_by":1,"name":"Yumeng Liu","email":"","orcid":"","institution":"beijing technolpgy and business 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B, Oral glucose tolerance curve, C, Area under the glucose tolerance curve (AUC). D, Fasting insulin (FINS). E, HOMA-IR index. F, HOMA-β index. G, Triglyceride (TG). H, Total cholesterol (TC). I, High density lipoprotein cholesterol (HDL-C). J, Tumor necrosis factor-alpha (TNF-α). K, Interleukin-1β (IL-1β). L, Interleukin-6 (IL-6). \u003csup\u003e*\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05, \u003csup\u003e**\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.01. NC means normal control group, MC means model group, and AU means the aucubin intervention group.\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8202756/v1/f59eb6fa86c294709255f096.png"},{"id":98314701,"identity":"edc18f7b-0952-4c43-9bb5-70d76d903f3d","added_by":"auto","created_at":"2025-12-16 13:06:57","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":319144,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffects of aucubin on injury of livers and pancreas in T2DM mice.\u003c/strong\u003e NC means normal control group, MC means model group, and AU means aucubin intervention group.\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8202756/v1/3ce6f380e9fbc161006c521d.png"},{"id":98314697,"identity":"851c8eb9-17ff-49d4-bbe4-2c39f45d15f4","added_by":"auto","created_at":"2025-12-16 13:06:57","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":49197,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffects of aucubin on injury of hepatic miRNA and mRNA expression profiles in T2DM mice.\u003c/strong\u003e A, Volcano plot of differentially expressed mRNA. B, Volcano plot of differentially expressed miRNA. C, KEGG pathway enrichment of differential mRNA. NC means the normal control group, MC means the model group, and AU means the aucubin group.\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8202756/v1/e4ce27e7420e23c022fa4a57.png"},{"id":98314706,"identity":"16ffc0b2-5bf1-43ff-b28e-d1465dd3e9ad","added_by":"auto","created_at":"2025-12-16 13:06:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":25325,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eqRT-PCR validation of differential miRNA and mRNA.\u003c/strong\u003e NC means the normal control group, MC means the model group, and AU means the aucubin group. Compared with normal control group, *\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05, **\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.01. Compared with model group, \u003csup\u003e#\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05, \u003csup\u003e##\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8202756/v1/96ae9617b72f8ab6647e3180.png"},{"id":98436063,"identity":"e346624e-531d-4d65-8264-e4bd9d26279e","added_by":"auto","created_at":"2025-12-17 16:54:50","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":93129,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003emiRNA-mediated mRNA regulating glucose metabolism. \u003c/strong\u003eA, miRNA-mRNA regulatory network. B, Clustering heatmap of 68 DEM in the miRNA-mRNA regulatory network. C, Clustering heatmap of 45 DEG in the miRNA-mRNA regulatory network. D, Sankey plot of miRNA targeted negatively regulated mRNA. NC means the normal control group, MC means the model group, and AU means the aucubin group.\u003c/p\u003e","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8202756/v1/939445f29a337f157e652e64.png"},{"id":98437241,"identity":"ac170039-c33d-4aab-99e0-181b06793b4e","added_by":"auto","created_at":"2025-12-17 16:57:10","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":36645,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eqRT-PCR and Western blot detect the expression of related mRNA and proteins. \u003c/strong\u003eA, the bind site between miR-505-5p and IGF1. B, Representative western blots. C, IRS1 protein level. D, PI3K protein level. E, FIT1 protein level. F, IGF1 protein level. G, miR-505-5p level. H, IRS1 mRNA level. I, PI3K mRNA level. J, FIT1 mRNA level. K, IGF1 mRNA level. \u003csup\u003e*\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05, \u003csup\u003e**\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.01. NC means the normal control group, MC means the model group, and AU means the aucubin group.\u003c/p\u003e","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8202756/v1/cdf9f46e80a9b0fb7d3b5eed.png"},{"id":105034861,"identity":"a7aa7ad9-4868-4ef0-80b3-caa263f0cc6f","added_by":"auto","created_at":"2026-03-20 07:24:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1963115,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8202756/v1/e00c3860-e37e-4740-ac14-508e8c89be06.pdf"},{"id":98314691,"identity":"51a1dfac-aec6-44c0-9466-91ddd956d6dc","added_by":"auto","created_at":"2025-12-16 13:06:57","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":211922,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-8202756/v1/006f633a7c5a04f696235257.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Aucubin improves glucolipid metabolic disorder in T2DM mice via the miR-505- 5p/IGF1/FIT1/IRS1/PI3K signaling pathway","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eNatural bioactive compounds have emerged as promising therapeutic candidates for diabetes management [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Aucubin, a cyclopentanoid monoterpene glucoside, demonstrates multifaceted bioactivities including hypolipidemic, antioxidant, and anti-inflammatory effects, along with hepatopancreatic protection and metabolic regulation [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Notably, its antidiabetic potential has been evidenced through enhanced insulin sensitivity, pancreatic β-cell preservation, and blood glucose normalization in diabetic models [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Vaidya et al. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] indicated that aucubin had a strong affinity with the pyridoxal phosphate binding site of glycogen phosphorylase, effectively inhibiting glycogen decomposition. Shen et al. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] reported that aucubin could alleviate fat accumulation and oxidative stress caused by long-term hyperglycemia through Nrf2/HO-1 and AMPK signalling pathways. However, the precise molecular mechanisms underlying its glucoregulatory effects remain incompletely elucidated.\u003c/p\u003e \u003cp\u003eEmerging evidence implicates microRNAs (miRNAs) ascritical regulators in type 2 diabetes mellitus (T2DM) pathogenesis, functioning through post-transcriptional gene silencing via 3'UTR targeting [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These non-coding RNAs have emerged as promising diagnostic biomarkers and therapeutic targets [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. For example, Su et al. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] reported that miR-34a-5p affected pancreatic β-cell proliferation through the Wnt signaling pathway and regulated insulin secretion through the insulin signaling pathway, further altering blood glucose levels. Recent advances in omics technologies have enabled systematic exploration of miRNA-mediated antidiabetic mechanisms. Whole Grain Proso Millet could inhibit gluconeogenesis by improving miRNA expression profile and activating PI3K/AKT signaling pathway, thus playing an anti-diabetic role [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. whole grain highland barley improved glycogen synthesis and alleviated IR by regulating the IRS-1/PI3K/ AKT pathway and associated miRNAs such as increasing the expression of miRNA-26a and miRNA-451 as well as decreasing the expression of miRNA-126a and miRNA-29a [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Despite these advances, the miRNA-dependent mechanisms of aucubin's antidiabetic action remain uncharacterized.\u003c/p\u003e \u003cp\u003eThis study therefore investigates the therapeutic potential of aucubin in HFD/STZ-induced diabetic mice, employing multi-omics approaches to elucidate its novel miRNA-mediated regulatory mechanisms. Our findings aim to provide mechanistic insights for developing miRNA-targeted therapies against T2DM.\u003c/p\u003e"},{"header":"2. Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Animals and experimental design\u003c/h2\u003e \u003cp\u003eSix-week-old SPF-grade male C57BL/6J mice were purchased from Beijing Vital River Laboratory Animal Technology Co Ltd (SCXK(Beijing)2021-0006). All mice had free access to food and water. They were kept in a laboratory with 55\u0026thinsp;\u0026plusmn;\u0026thinsp;5% humidity and 12:12 light/dark cycle 22\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C. The animal experiments were approved by the Animal Ethics Committee of Pony Testing Group (PONY-2022-FL-90). The whole experimental process paid attention to animal welfare and strictly complied with the relevant regulations and provisions required by the International Council for Animal Welfare.\u003c/p\u003e \u003cp\u003eAfter one week's adaptive feeding, 8 mice were randomly selected as normal control group (NC) with 10% low-fat chow. The remaining mice were fed 60% high-fat chow. After 4 weeks, 0.5% streptozotocin (STZ) was injected intraperitoneally for 4 days at a dose of 45 mg/kg based on mice body weight to induce the diabetic mice model. During this period, mice in NC were injected with equal volumes of saline based on body weight. Then, diabetic mice with fasting blood glucose concentration\u0026thinsp;\u0026gt;\u0026thinsp;11.1 mmol/L were randomly assigned to 2 groups: model control group (MC, n\u0026thinsp;=\u0026thinsp;8) with an equal volume of saline; and aucubin-treated group (AU, n\u0026thinsp;=\u0026thinsp;8) with 10 mg/kg of aucubin solution. 60% high fat chow was purchased from Beijing Keao Xieli Feed Co., Ltd. as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eAfter 6 weeks of intervention, oral glucose tolerance test (OGTT) was performed. Then, blood was taken from retro-orbital vein to collect serum and stored at -80\u0026deg;C. After execution of the mice, partial liver and pancreas tissues were collected in 4% paraformaldehyde, and the rest of the tissues were stored at \u0026minus;\u0026thinsp;80\u0026deg;C for subsequent experiments.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNutritional content of experimental feed components\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIngredient (g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60% high-fat chow(g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10% low-fat chow(g)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCasein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2584.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1895.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL-cystine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorn starch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4797.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaltodextrin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1615.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1184.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSucrose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e889.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e652.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCellulose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e646.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e473.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoybean oil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e323.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e237\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e189.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMineral mix S10026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalcium hydrogenphosphate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRaffinose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotassium citrate monohydrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e213.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e156.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitamin mix V10001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCholine bitartrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein(kcal %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat(kcal %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbohydrate(kcal %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Detection of blood glucose and oral glucose tolerance test\u003c/h2\u003e \u003cp\u003eAfter 6 weeks of aucubin intervention and 12h fasting, tail vein blood was used for measuring fasting blood glucose (FBG) using Performa Blood Glucometer (Shanghai Roche Pharmaceuticals, China). All mice were gavaged with 20% glucose solution (2 g kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e bw\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and blood glucose at 30, 60, 90 and 120 min were recorded. Area under the glucose tolerance curve (AUC) was then calculated [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Serum Biochemical Analysis\u003c/h2\u003e \u003cp\u003eThe concentration of tumor necrosis factor-alpha (TNF‑α), interleukin-1β (IL-1β), interleukin-6 (IL-6) and fasting insulin (FINS) in the serum were measured with the corresponding ELISA kits purchased from the Shanghai Enzyme-linked Biotechnology Co., Ltd (Shanghai, China). Insulin resistance index (HOMA-IR) and pancreatic β-cell function index (HOMA-β) were calculated using an \u003cem\u003ein vivo\u003c/em\u003e homeostasis model assessment based on formula (1) and (2). The serum triglyceride (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C) was performed according to the manufacturer\u0026rsquo;s instruction (Nanjing Jiancheng Bioengineering Institute, Nanjing, China).\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:HOMA-IR=(FBG\\times\\:FINS)/22.5$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:HOMA-\\beta\\:=(20\\times\\:FINS)/(FBG-3.5)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Hematoxylin and Eosin (H\u0026amp;E) staining\u003c/h2\u003e \u003cp\u003eThe collected tissue samples were fixed with 4% paraformaldehyde followed by dehydration with graded ethanol and embedded in paraffin. Tissues were cut into 5 \u0026micro;m and then stained with H\u0026amp;E. Structural changes in liver and pancreatic tissue were observed under a microscope (Leica, Germany).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Small RNA libraries preparation and sequencing\u003c/h2\u003e \u003cp\u003eIllumina TruSeq Small RNA kits (Illumina, San Diego, CA) were used to generate sequencing libraries. After the 3' and 5' end junctions were ligated, 1st cDNA was synthesised by reverse transcription and used for PCR amplification. PCR amplification products were purified and recovered by 8% polyacrylamide gel electrophoresis to construct small RNA libraries. The Illumina Hiseq 2000 platform would be used for miRNA sequencing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 mRNA libraries preparation and sequencing\u003c/h2\u003e \u003cp\u003eIllumina TruSeqTM RNA sample prep Kit (Illumina, San Diego, CA) was performed for mRNA transcriptome library construction. The mRNA was isolated by A-T pairing of Oligo (dT) magnetic beads with polyA. Double-stranded cDNA was further synthesised using the SuperScript double-stranded cDNA synthesis kit (Invitrogen, CA) and random hexamers followed by end repair, phosphorylation and 'A' base addition. The 300 bp cDNA target fragment was selected for PCR amplification. RNA-seq sequencing libraries were sequenced using Illumina NovaSeq 6000.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Bioinformatics Analysis\u003c/h2\u003e \u003cp\u003eAfter quality control analysis of the raw reads to get clean reads, it was further compared to the reference genome. In terms of miRNAs, the clean reads from the ratio were further compared to the miRBase (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.mirbase.org/\u003c/span\u003e\u003cspan address=\"http://www.mirbase.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and Rfam (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://rfam.xfam.org/\u003c/span\u003e\u003cspan address=\"http://rfam.xfam.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) databases to identify the miRNAs. MiRNA and mRNA expression levels were then quantified based on TPM. Differential miRNAs (DEM) and differential mRNAs (DEG) were screened by |log2FC|\u0026ge;2, \u003cem\u003eP\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. DEM was directly analysed for functional enrichment analysis. Target genes predicted by differential miRNAs using miRanda served for functional enrichment analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 miRNA-mRNA regulatory networks\u003c/h2\u003e \u003cp\u003eThe miRNA-mRNA regulatory network was constructed from DEM and DEG enriched on AMPK, IR, and T2DM signalling pathway. After clustering analysis of DEM and DEG in the regulatory network, the regulatory pairs of miRNA-targeted negatively regulated mRNA were shown in a mulberry diagram.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9 Cells transfection\u003c/h2\u003e \u003cp\u003eHepa1-6 cells in the well-grown state were seeded in 6-well plates at 5\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells/well. Cells were cultured using serum-free DMEM medium for 2h prior to transfection. The miR-505-5p mimic and its negative NC (RiboBio, Guangzhou, China) were transfected into Hepa1-6 cells using the lipofectamine2000 (Invitrogen, USA) named AU minic and AU minic NC groups. Cells were intervened after transfection with medium containing aucubin. The transfection efficiency was assessed based on qRT-PCR and Western Blot experiments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.10 Quantitative real-time polymerase chain reaction (qRT-PCR)\u003c/h2\u003e \u003cp\u003eRNA was extracted from liver tissues and cells using \u003cem\u003eTransZol\u003c/em\u003e Up Plus RNA Kit (TransGen Biotech, Beijing, China) according to the manufacturer's manual. The RNA was then reverse transcribed into cDNA with miRNA 1st Strand cDNA Synthesis Kit (by stem-loop) (Vazyme; MR101) and HiScript\u0026reg; III All-in-one RT SuperMix Perfect (Vazyme; R333-01), respectively. The qRT-PCR was performed on ABI QuantStudio 3 (Applied Biosystems, Thermo Fisher, USA) using miRNA Universal SYBR qPCR Master Mix (Vazyme; MQ101) and Taq Pro Universal SYBR qPCR Master Mix (Vazyme; Q712). The relative abundance of miRNA and mRNA was normalized to U6 and β-actin. The relative amounts of the miRNAs and mRNA were measured using the 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method. The miRNA and mRNA primers were designed and synthesised by RiboBio (Guangzhou, China) and Tsingke Biotech Co., Ltd (Beijing, China). The sequences of primers were shown in Table\u0026nbsp;2.\u003c/p\u003e \u003cp\u003eTable.2 Specific gene primers used for qRT-PCR\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward primer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReward primer\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIRS1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATTAACCCCATCAGACGCCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGGAGGTTTGGCATGAGGAA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePI3K\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAATGCACGGCGATTACACTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGGACACTGGGTAGAGCAACT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIGF1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCAGCTGGACCAGAGACCCTTT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGAATGCTGGAGCCATAGCCTG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFIT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTTACCTGGATTCTGCTACGGAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGGTTCAGAGTGATGGAGTAATCTTG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEgfr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTCCCAGACAGACGACAGGTCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACAGACGGAGTCCCACGGTT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOCS3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTTTCTTTGCCACCCACGGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGGAGAGAGGTCGGCTCAGTAC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ-actin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTCAAGATCATTGCTCCTCCTGAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACATCTGCTGGAAGGTGGACA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.11 Western blotting\u003c/h2\u003e \u003cp\u003eTotal protein was extracted from Hepa1-6 cells using RIPA lysis buffer (Servicebio, Wuhan, China). And the concentration was measured with BCA protein assay kit (Jiebes, Guangzhou, China). Proteins were separated by 10% SDS-PAGE gel and further transferred to polyvinylidene difluoride membrane (Millipore, Massachusetts, USA). Membrane was blocked by 5% skimmed milk powder for 2 h at room temperature. And membrane was incubated first with primary antibodies (Igf1, FIT1, IRS1 and PI3K) overnight at 4\u0026deg;C and then with HRP labeled secondary antibodies for 2 h at room temperature. The Proteins were detected by ECL substrate solution (Servicebio, Wuhan, China) and were quantified by ImageJ software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.12 Statistical analysis\u003c/h2\u003e \u003cp\u003eOne-way analysis of variance was used when comparing between at least three groups. When two groups were compared, student\u0026rsquo;s t-test was used. Images were drawn and typeset using Adobe Illustrator CS6 (Adobe, San Jose, CA, USA) and GraphPad Prism 8.02 (GraphPad Prism, La Jolla, CA, USA) software. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered a statistically significant difference.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Effects of aucubin on blood glucose metabolism in T2DM mice\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, the FBG of mice in the MC group was significantly higher than that in the NC group, whereas the intervention of aucubin significantly reduced the FBG of mice.\u003c/p\u003e \u003cp\u003eThe glucose tolerance of mice by oral glucose tolerance test was examined and shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB. All groups displayed peak blood glucose concentrations at 30 min post-gavage, with NC mice achieving baseline recovery by 90 min. In contrast, MC group maintained persistent hyperglycemia, demonstrating impaired glucose clearance. Notably, aucubin-treated mice exhibited accelerated glucose normalization, showing significantly lower blood glucose levels than MC group at 120 min (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In addition, the AUC levels of mice in the MC group were significantly higher than those in the NC group, whereas they were significantly lower in the AU group. These results suggested that aucubin improved blood glucose tolerance and enhanced the ability to regulate blood glucose in diabetic mice.\u003c/p\u003e \u003cp\u003eCompared with the NC group, mice in the MC group had significantly higher HOMA-IR (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and lower FINS and HOMA-β (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Interestingly, aucubin reversed these changes, with significantly increased levels of FINS (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and HOMA-β (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and decreased levels of HOMA-IR.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Effects of aucubin on dyslipidemia and inflammation in T2DM mice\u003c/h2\u003e \u003cp\u003eCompared to controls, MC group mice exhibited significantly elevated serum TG and TC levels (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG and H) accompanied by reduced HDL-C concentrations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI). Aucubin supplementation markedly reversed these metabolic alterations in T2DM mice. Furthermore, aucubin administration significantly attenuated serum pro-inflammatory cytokine levels (TNF-α, IL-1β, IL-6) in the MC group (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eJ-L).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Effects of aucubin on injury of livers and pancreas in T2DM mice\u003c/h2\u003e \u003cp\u003eHistopathological analysis was performed to evaluate the hepatoprotective and pancreoprotective effects of aucubin in T2DM-induced tissue damage (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe results showed that the MC group exhibited marked structural disorganization of hepatocytes, characterized by microvesicular and macrovesicular steatosis accompanied by diffuse inflammatory cell infiltration with focal aggregation. Hepatic histological examination revealed that compared to NC group, aucubin treatment markedly attenuated these hepatic pathological changes, demonstrating significant reduction in both lipid accumulation and inflammatory responses. Furthermore, pancreatic histomorphometric analysis indicated that aucubin supplementation effectively mitigated diabetes-associated pathological alterations in islet architecture, including substantial alleviation of inflammatory infiltration, preservation of normal islet morphology, and prevention of β-cell mass depletion observed in MC group animals.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Effect of aucubin on hepatic miRNA expression profile in T2DM Mice\u003c/h2\u003e \u003cp\u003eTo investigate the effect of aucubin on miRNA expression profiles in T2DM mice, miRNA libraries from mice liver (NC\u0026thinsp;=\u0026thinsp;3, MC\u0026thinsp;=\u0026thinsp;3 and AU\u0026thinsp;=\u0026thinsp;3) were constructed by small RNA sequencing. More than 10.19 M raw reads were obtained from each sample, and more than 8.92 M clean reads were obtained after quality control, which was over 96% of Q30 (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) and mainly distributed in the range of 21\u0026ndash;23 nt (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThen, mapped miRNAs on the reference genome were identified as known miRNA and predicted new miRNA. As shown in the table S2, the miRNA identified in the nine libraries ranged from 566 to 671, with known miRNA within 478\u0026ndash;632 and novel miRNAs in 35\u0026ndash;88. These miRNAs were subjected to subsequent screening of DEM to analyse the mechanism by which aucubin regulated glucose metabolism in T2DM mice.\u003c/p\u003e \u003cp\u003eThe DEM of each group were screened by |log2FC|\u0026ge;2, \u003cem\u003eP\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05, with results shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA. A total of 143 DEM was screened in different groups (AU vs MC, AU vs NC, MC vs NC). Compared with the NC group, 25 miRNAs were significantly upregulated and 64 miRNAs were significantly downregulated, whereas 36 were significantly upregulated and 80 were significantly downregulated in the AU group. And 6 miRNAs were significantly upregulated and 9 miRNAs were significantly downregulated in the AU group compared with the MC group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Effect of aucubin on hepatic mRNA expression profile in T2DM Mice\u003c/h2\u003e \u003cp\u003eRNA from 9 mice livers (NC\u0026thinsp;=\u0026thinsp;3, MC\u0026thinsp;=\u0026thinsp;3 and AU\u0026thinsp;=\u0026thinsp;3) was extracted for mRNA library construction. A total of 59.85G clean reads were obtained, with Q30 over 96.23% (Table S3). The clean reads were aligned with the reference genome, and the mapped rate ranged from 92.33% to 97.14% (Table S4), indicating that the sequencing quality was high and the library construction was successful.\u003c/p\u003e \u003cp\u003eThe mapped data were then further quantified to identify DEG among the different groups. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, a total of 2835 DEG were screened in different groups (AU vs MC, AU vs NC, MC vs NC). Compared with the NC group, 823 mRNAs were significantly upregulated and 1187 mRNAs were significantly downregulated, whereas 844 were significantly upregulated and 884 were significantly downregulated in the AU group. And 294 mRNAs were significantly upregulated and 92 mRNAs were significantly downregulated in the AU group compared with the MC group. These DEG provided important evidence for investigating further the mechanism of glucose metabolism regulation by aucubin.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.7 Functional analysis\u003c/h2\u003e \u003cp\u003eKEGG enrichment analysis was performed on the above 2835 DEG. These DEG were enriched into 336 signalling pathways in total, with 83 signalling pathways significantly enriched (Pvalue\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The top 66 significantly enriched signalling pathways were visualized by bubble plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Notably, these DEG were significantly enriched in signalling pathways related to glucose metabolism, such as PI3K/AKT (55 genes), AMPK (21 genes), IR (19 genes), and T2DM (10 genes) signalling pathway. Total 82 DEG enriched in these signalling pathways were used to construct miRNA-mRNA regulatory networks.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e3.8 Validation of predicted differential miRNA and mRNA\u003c/h2\u003e \u003cp\u003eFour miRNA (miR-205-5p, miR-672-5p, miR-505-5p and miR-455-5p) and four mRNA (FIT1, Egfr, IGF1 and SOCS3) associated with glucose metabolism were subjected to qRT-PCR. Their expression trends were consistent with the transcriptome (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The results suggested that aucubin might mediate these miRNA and mRNA to ameliorate T2DM.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e3.9 miRNA-mRNA regulatory network\u003c/h2\u003e \u003cp\u003eThe miRNAs played a functional role by targeting mRNA. Therefore, the above 143 DEM and 69 DEG enriched in PI3K/AKT and IR were subjected to miRNA-mRNA regulatory network construction. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, there were 122 miRNA-mRNA pairs, with 68 DEM and 45 DEG in miRNA-mRNA regulatory network. After hierarchical clustering analysis, a heatmap of the expression of these miRNAs and miRNAs in different treatment groups was obtained (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Eventually, 13 regulatory pairs that satisfying miRNA to negatively regulate mRNA were obtained, i.e. miR-455-5p-Prkca, miR-744-5p-Itga10, miR-505-5p-Igf1, miR-205-5p-Gng11, miR-138-5p-FIT1, miR-664-5p-Egfr, miR-499-5p-Egfr, miR-505-5p-Col6a1, miR-541-5p-Chrm1, miR-1949-Chrm1, 17_16061-Slc2a4, 4_24287-prkca, 17_16061-Pik3r3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e3.10 miR-505-5p negatively regulated IGF1\u003c/h2\u003e \u003cp\u003eIGF1 was significantly downregulated in T2DM mice and significantly upregulated after aucubin intervention (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Moreover, miR-505-5p could negatively regulate IFG1 from miRNA-mRNA analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). We hypothesized that aucubin mediated miR-505-5p- targeted regulation of IFG1 participating in the improve glucose metabolism of aucubin in T2DM mice. To validate this mechanism, we established a miR-505-5p overexpression model through transfection with miR-505-5p mimic in Hepa1-6 cells.\u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, expression of miR-505-5p after transfecting miR-505-5p minic NC was no significant difference comparing with AU group, but after transfecting miR-505-5p minic, it was significantly higher than that in AU and AU minic NC group. However, transfection with miR-505-5p mimic resulted in significantly elevated miR-505-5p levels compared to both AU and AU mimic NC groups, confirming successful transfection efficiency. Notably, IGF1 expression at both mRNA and protein levels exhibited significant suppression in the miR-505-5p mimic group relative to control groups. This post-transcriptional regulation of IGF1 protein expression strongly suggests that miR-505-5p inhibits IGF1 translation, thereby corroborating our bioinformatics predictions regarding miRNA-mediated negative regulation of IGF1. To further investigate the downstream consequences of this regulatory axis, we analyzed expression patterns of key glucose metabolism mediators (FIT1, IRS1, and PI3K) following miR-505-5p mimic transfection. These examinations aim to elucidate the functional pathway through which the aucubin-miR-505-5p-IGF1 axis modulates glycemic control.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e3.11 Aucubin mediate miR-505-5P regulating IGF1/FIT1/IRS1/PI3K signalling pathway\u003c/h2\u003e \u003cp\u003eThe relative mRNA and protein expression of FIT1/IRS1/PI3K after transfection with miR-505-5p minic were shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. The relative mRNA and protein expression of FIT1/IRS1/PI3K in AU minic group was significantly increased than that in AU and AU minic NC groups. These results indicated that miR-505-5p could mediate IGF1 to regulate the FIT1/IRS1/PI3K signalling pathway. Moreover, the expression of miR-505-5p in the livers of T2DM mice was significantly decreased after aucubin intervention (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Thus, aucubin could mediate miR-505-5p regulating IGF1 to further modulate the IGF1/FIT1/IRS1/PI3K signalling pathway to improve glucose metabolism in T2DM mice.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eType 2 diabetes mellitus (T2DM) is a prevalent metabolic disorder characterized by chronic hyperglycemia, whose multifactorial pathogenesis has established it as a global public health challenge [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This condition imposes not only significant health risks to individuals but also substantial economic burdens on healthcare systems worldwide [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Developing effective strategies to prevent disease progression, mitigate complications, and reduce diabetes-related morbidity therefore remains a critical research priority. As a kind of iridoid compound, aucubin has been reported to have antidiabetic activity [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This study further revealed the potential mechanism of its anti-diabetes based on transcriptomic, that is, it could regulate the expression profile of miRNA and mRNA in T2DM mice, thereby alleviating liver and pancreas damage, abnormal glucose and lipid metabolism, and IR in T2DM mice.\u003c/p\u003e \u003cp\u003eClinically, fasting blood glucose has been established as a crucial diagnostic biomarker for diabetes mellitus [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In this study, aucubin administration markedly reduced FBG levels in HFD/STZ-induced diabetic mice, suggesting its therapeutic potential for T2DM management. Notably, IR represents the primary pathophysiological mechanism underlying T2DM development. Hepatic insulin resistance leads to impaired insulin sensitivity, subsequently triggering compensatory hyperinsulinemia that progressively damages pancreatic β-cell function. This pathological cascade ultimately manifests as glucose intolerance, dysregulated glucose-lipid homeostasis, and full progression to T2DM [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Consistent with previous findings by Jin et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] showing β-cell protective effects of aucubin in diabetic rat models. The present study revealed significant improvements in glucose regulation. Specifically, while the model control (MC) group exhibited persistent hyperglycemia with significantly elevated AUC values compared to normal controls (NC), aucubin-treated mice displayed rapid glucose normalization within 30 minutes post-administration, indicating restored glucose tolerance. Moreover, aucubin significantly increased FINS, HOMA-β and HDL-C, and significantly reduced TG, TC and HOMA-IR concentration in T2DM mice. These collective findings provide compelling evidence that aucubin effectively ameliorates diabetic metabolic dysregulation through dual mechanisms of enhancing insulin sensitivity and preserving β-cell functionality.\u003c/p\u003e \u003cp\u003eThe liver and pancreas are well-established as central regulators of glycolipid metabolism and insulin homeostasis, respectively. Clinical observations indicate that patients with T2DM typically present with hepatic and pancreatic dysfunction, creating a pathological cycle that exacerbates disease progression. Histopathological analysis revealed significant inflammatory infiltration and structural abnormalities in both hepatic and pancreatic tissues of MC group mice. Notably, aucubin administration markedly attenuated these pathological alterations. Consistent with histological findings, HE staining further confirmed the presence of systemic inflammation in diabetic mice. Mechanistically, chronic inflammation has been extensively documented to induce IR through multiple pathways, while persistent hyperglycemia reciprocally amplifies inflammatory responses - a vicious cycle contributing to diabetic complications [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The results demonstrated that aucubin treatment significantly downregulated serum levels of key pro-inflammatory mediators (TNF-α, IL-1β, IL-6). Importantly, this anti-inflammatory effect correlated with improved insulin sensitivity and restoration of pancreatic β-cell function. Collectively, our findings establish that aucubin exerts multimodal therapeutic effects on HFD/STZ-induced T2DM mice by ameliorating hepatic steatosis and pancreatic β-cell dysfunction, promoting insulin biosynthesis and secretion, and disrupting inflammation. These results provide preclinical evidence supporting aucubin's potential as a multi-target therapeutic agent for T2DM management.\u003c/p\u003e \u003cp\u003eEmerging evidence underscores the regulatory significance of miRNA-mediated mechanisms in natural bioactive compounds' therapeutic effects through multilayer modulation of mRNA transcription and post-transcriptional processes. It was reported that flavonoid administration significantly enhances hepatic and adipose tissue miR-146a expression while suppressing NF-κB levels in T2DM rats [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Similarly, gallic acid demonstrates insulin-sensitizing effects through miR-1271 downregulation, subsequently activating key insulin signaling mediators including phosphorylated IRS, PI3K, AKT, and FoxO1[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In this study, aucubin administration induces significant alterations in both miRNA and mRNA expression profiles in diabetic mice, with 143 DEMs and 2835 DEGs identified through systematic screening. These molecular alterations establish a foundation for elucidating aucubin's therapeutic mechanisms in T2DM-associated metabolic dysregulation. KEGG pathway analysis revealed significant enrichment of identified DEGs in critical metabolic pathways, particularly IR, PI3K/AKT, AMPK and T2DM. The insulin-mediated PI3K/AKT pathway serves as a central regulator of systemic metabolic homeostasis, coordinating hepatic glucose production, peripheral glucose utilization, and lipid metabolism [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Mechanistically, insulin resistance manifests through impaired phosphorylation cascades in insulin receptor substrates and subsequent dysregulation of PI3K/AKT signaling activation [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Current research highlights natural compounds' capacity to modulate this critical pathway through miRNA regulation. In the study by He et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] ferulic acid derivatives exhibit regulatory effects by upregulating miR-200c-3p to enhance PI3K/AKT activation via PTEN modulation. Additionally, Zhang et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] also found that ferulic acid could inhibit the insulin signaling pathway by up-regulating miR-17 targeting negative regulation of PTEN. Complementary findings demonstrate caffeic acid's multi-target effects through regulation of miR-30a, miR-342, and miR-133b to activate both AMPK and PI3K signaling axes [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Based on these collective insights and our experimental evidence, we propose that aucubin ameliorates T2DM metabolic disturbances through coordinated modulation of miRNA-mRNA networks, particularly targeting IR amelioration and PI3K/AKT pathway restoration.\u003c/p\u003e \u003cp\u003eTo investigate the molecular mechanisms underlying aucubin-mediated miRNA regulation in T2DM, 143 DEM and 69 DEG enriched in IR and PI3K/AKT were used to construct miRNA-mRNA regulatory network. Hierarchical cluster analysis identified 13 miRNA-mRNA pairs exhibiting miRNA-targeted negative regulatory relationships, including miR-205-5p-Gng11, miR-455-5p-Prkca; miR-744-5p-Itga10; miR-505-5p-Igf1; miR-138-5p-FIT1; miR-541-5p-Chrm1; miR-1949-Chrm1; miR-505-5p-Col6a1; miR-664-5p-Egfr; miR-499-5p-Egfr; 17_16061-Slc2a4; 4_24287-prkca; and 17_16061-Pik3r3. Notably, several components within these regulatory pairs demonstrate established associations with T2DM pathophysiology. For example, miR-205-5p could inhibit the diabetic gene Tcf7l2 to regulate β-cell function and insulin secretion [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The Gng11, a miR-205-5p target gene in this study, was reported to be able to distinguish between gestational diabetes mellitus patients and normal people, and might be a therapeutic target for gestational diabetes mellitus [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, the research on miR-205-5p mediated Gng11 to improve T2DM had not been explored in depth. In addition, our previous study revealed that whole grain highland barley could regulate miR-455-5p-Igf1r to improve glucose metabolism in diabetic mice [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Interestingly, another target gene Prkca of miR-455-5p was found in this study, which was also reported to be involved in the occurrence and development of T2DM [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. It could be considered to further explore that aucubin might mediate miR-455-5p-Prkca to improve T2DM mice. Upregulation of miR-744-5p was identified as IR and as an important biomarker of T2DM [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In this study, miR-744-5p was upregulated in the MC group, while significantly downregulated in aucubin, indicating that aucubin could mediate miR-744-5p to improve T2DM. The target gene Itga10 predicted by miR-744-5p in this study was found to play a key role in T2DM osseointegration [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. However, direct evidence of miR-744-5p/Itga10 involvement in T2DM pathogenesis remains unreported. Of particular interest, Orang et al. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] found that metformin induced miR-132-3p to regulate PI3K/AKT signaling pathway by targeting PIK3R3. Collectively, these miRNA-mRNA found in this study have the potential to be targets for aucubin improving T2DM mice.\u003c/p\u003e \u003cp\u003eOur findings suggest that aucubin may exert hypoglycemic effects through coordinated modulation of the PI3K/AKT and IR signaling pathways via specific miRNA-mRNA regulatory networks. Notably, IGF1, a key mediator with established insulin-mimetic properties in glucose homeostasis, emerged as a critical node in this regulatory cascade [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Bioinformatics analysis revealed that miR-505-5p possesses complementary binding sites to the 3'UTR of IGF1 mRNA, suggesting direct post-transcriptional regulation. In the insulin signaling cascade, IGF1 activation triggers a phosphorylation cascade through FIT1 and IRS1, ultimately activating the PI3K/AKT pathway [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAucubin supplementation significantly upregulated the expression of IGF1 in the MC group. And miRNA-mRNA analysis showed that miR-505-5p negatively regulated IFG1. Therefore, we hypothesized that aucubin could mediate miR-505-5p targeting IGF1 to regulate FIT1/IRS1/PI3K signaling pathway. To this end, we first needed to validate the targeting regulatory effect of miR-505-5p on IGF1. The miR-505-5p minic was then transfected into Hepa1-6 cells. We found that the expression of IGF1 mRNA and protein after transfection with miR-505-5p minic was significantly lower than that in the AU and AU minic NC groups, suggesting that miR-505-5p does indeed target IGF1, thereby inhibiting its function. Interestingly, the relative mRNA and protein expression levels of FIT1, IRS1 and PI3K in the AU minic group were significantly higher than those in the AU and AU minic NC groups. These results suggested that miR-505-5p could target IGF1 and then mediated FIT1/IRS1/PI3K signaling pathway to improve T2DM mice. In addition, aucubin downregulated the expression of miR-505-5p in T2DM mice. Our data collectively support a model where aucubin ameliorates diabetic phenotypes through miR-505-5p/IGF1 axis-mediated potentiation of the FIT1/IRS1/PI3K signaling pathway.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, this investigation systematically demonstrates that aucubin significantly ameliorates metabolic dysregulation in T2DM mice through multi-faceted therapeutic effects, including glycolipid metabolism normalization, histopathological restoration of hepatic and pancreatic tissues, and anti-inflammatory modulation. Integrative bioinformatics analysis of miRNA-mRNA sequencing datasets identified 13 functionally correlated miRNA-mRNA pairs potentially mediating the therapeutic actions of aucubin. Mechanistic validation through gain-of-function experiments with miR-505-5p revealed that aucubin exerts its antidiabetic effects via miR-505-5p/IGF1 axis-mediated regulation of the FIT1/IRS1/PI3K signaling pathway. These findings position aucubin as a promising phytochemical candidate for T2DM prevention and management. This study further suggests that targeting disease-associated miRNA networks through natural bioactive compounds may represent a novel therapeutic paradigm for combating T2DM pathogenesis.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAucubin-treated group\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAUC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eArea under the glucose tolerance curve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDEM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDifferential miRNAs\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDEG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDifferential mRNAs\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFBG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFasting blood glucose\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFINS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFasting insulin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHFD/STZ\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHigh-fat diet and streptozotocin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHDL-C\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHigh density lipoprotein cholesterol\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eH\u0026amp;E\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHematoxylin and Eosin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHOMA-IR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInsulin resistance index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHOMA-β\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePancreatic β-cell function index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLDL-C\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLow density lipoprotein cholesterol\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIL-1β\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterleukin-1β\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIL-6\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterleukin-6\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMiRNA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMicroRNA\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eModel control group\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNormal control group\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOGTT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOral glucose tolerance test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eqRT-PCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eQuantitative real-time polymerase chain reaction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eT2DM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eType 2 diabetes milieus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTNF‑α\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTumor necrosis factor-alpha\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTriglyceride\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTotal cholesterol\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eAll authors have no confcts of interest to declare.\u003c/p\u003e \u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis research was funded by the National Natural Science Foundation of China (No. 32101876).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eM.Y.Q, X.R. methodology, formal analysis and writing\u0026mdash;review and editing. M.Y.Q. software, validation and writing\u0026mdash;original draft preparation. X.R. conceptualization, investigation, project administration and funding acquisition. Y.M.L, X.R. data curation. Y.M.L. supervision. Z.L.C, X.R. resources. Z.L.C. visualization.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData available on request from the authors\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRoy D, Kaur P, Ghosh M, Choudhary D, Rangra NK. The therapeutic potential of typical plant-derived compounds for the management of metabolic disorders. Phytother Res 38(8): 3986\u0026ndash;4008, 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZeng X, Guo F, Ouyang D. A review of the pharmacology and toxicology of aucubin. Fitoterapia 140(104443, 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePotacnjak I, Marinic J, Baticic L, Simic L, Broznic D, Domitrovic R. 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Mechanisms of disease: metabolic effects of growth hormone and insulin-like growth factor 1. Nat Clin Pract Endocrinol Metab 3(3): 302\u0026thinsp;\u0026ndash;\u0026thinsp;10, 2007.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchultze SM, Hemmings BA, Niessen M, Tschopp O. PI3K/AKT, MAPK and AMPK signalling: protein kinases in glucose homeostasis. Expert Rev Mol Med 14(e1, 2012.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Aucubin, Glycolipid metabolism, Type 2 Diabetes mellitus, microRNA, mRNA","lastPublishedDoi":"10.21203/rs.3.rs-8202756/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8202756/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDiabetes is characterized by impaired glucolipid metabolism and chronic inflammation. Aucubin, a natural compound, has shown potential for improving metabolic disorders, but its mechanisms remain unclear. To investigate the effects of aucubin on glucolipid metabolism and the underlying mechanisms in diabetic mice. Diabetic mice were induced by a high-fat diet and streptozotocin. Aucubin was administered, and its effects on metabolic parameters, tissue injury, and molecular profiles were assessed. Fasting blood glucose, insulin, lipid levels, and inflammatory markers were measured. Liver and pancreatic tissues were examined for histological changes. MiRNA and mRNA expression profiles were analyzed using sequencing, and miRNA-mRNA regulatory pairs were identified. Cell transfection and western blotting were performed to validate the regulatory mechanisms. Aucubin significantly reduced fasting blood glucose, triglycerides, total cholesterol, and inflammatory factors, while increasing fasting insulin, pancreatic β-cell function, and high-density lipoprotein cholesterol. It also alleviated liver and pancreatic tissue injury. Transcriptomic analysis identified 143 differentially expressed miRNAs and 2835 differentially expressed mRNAs, with 69 mRNAs enriched in the PI3K/AKT and insulin resistance pathways. Aucubin downregulated miR-505-5p, which negatively regulated IGF1 expression, thereby affecting the FIT1/IRS1/PI3K signaling pathway. Aucubin exerts anti-diabetic effects by mediating miR-505-5p targeting IGF1 to regulate the FIT1/IRS1/PI3K signaling pathway, offering a potential therapeutic strategy for diabetes.\u003c/p\u003e","manuscriptTitle":"Aucubin improves glucolipid metabolic disorder in T2DM mice via the miR-505- 5p/IGF1/FIT1/IRS1/PI3K signaling pathway","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-16 13:06:52","doi":"10.21203/rs.3.rs-8202756/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a2fbcef1-b0dc-40f4-86e1-1176f0942645","owner":[],"postedDate":"December 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":59530249,"name":"Biological sciences/Biochemistry"},{"id":59530250,"name":"Biological sciences/Cell biology"},{"id":59530251,"name":"Health sciences/Diseases"},{"id":59530252,"name":"Health sciences/Endocrinology"},{"id":59530253,"name":"Biological sciences/Molecular biology"},{"id":59530254,"name":"Biological sciences/Physiology"}],"tags":[],"updatedAt":"2026-03-19T04:55:09+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-16 13:06:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8202756","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8202756","identity":"rs-8202756","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}