Untargeted Metabolomics-Based Network Pharmacology Reveals Fermented Brown Rice Towards Anti-Obesity Efficacy

Obesity is a chronic disease caused by significant fat accumulation in the body, and by 2025, 167 million people and children are projected to be unhealthy due to obesity (WHO). Dietary guidelines encourage whole grains, especially brown rice (BR), to minimize risks of obesity, CVD, and type 2 diabetes. BR is nutrient-dense, rich in antioxidants, minerals, and beneficial compounds, and has a low glycemic index beneficial to overweight individuals. Bioprocessing, such as probiotic fermentation, can enhance bioactive constituents including GABA, ferulic acid, tocotrienols, minerals, and amino acids. Fermentation is recognized for improving dietary, sensory, and functional qualities and is cost-effective for enhancing food bioactive compounds. Cereal-based fermentations produce organic acids, bacteriocins, and volatiles that aid safety, shelf-life, and flavor, with lactic acid bacteria like L. plantarum, L. fermentum, L. lactis, Leuconostoc spp., Levilactobacillus brevis, and Pediococcus spp. playing key roles. Metabolomics enables comprehensive profiling of metabolites in complex biological or fermentation systems; UHPLC-MS/MS and NMR uncover overlapped metabolites. Multi-omics approaches identify biomarkers and targets for disease and drug discovery, with bioinformatics facilitating biomarker discovery. Network pharmacology investigates pharmacological processes within complex systems; DEGs and hub genes elucidate disease-related networks, and molecular docking examines ligand-protein interactions at atomic levels. Caenorhabditis elegans is a valuable in vivo model for metabolic and nutritional studies due to conserved lipid metabolism, genetic manipulability, short lifecycle, and ease of fat visualization; numerous genes modulate fat storage and lifespan pathways such as insulin/IGF-1 via DAF-16. In this work, fermentation was used to enhance BR bioactives and antioxidants to develop anti-obesity functional foods. The study evaluated in vitro lipase inhibition and antioxidant properties, identified metabolites via UHPLC Q-TOF MS/MS, applied network pharmacology to obesity-related targets, and validated effects in a C. elegans obesity model by assessing lipid metabolism, fat accumulation, and lifespan.

Prior research indicates fermentation enhances bioactive compounds and antioxidant potential in cereals and plant substrates, improving nutritional and functional qualities. Polyphenols from fermented products have physiological benefits including cholesterol reduction. Metabolomics (NMR, UHPLC-MS/MS) provides comprehensive metabolite profiling; multi-omics integrates environmental factors such as diet with disease outcomes. Network pharmacology reveals interactions among compounds, targets, and pathways, identifying hub genes and drug candidates. Molecular docking has long supported drug discovery by characterizing ligand-protein interactions. C. elegans shares conserved lipid metabolic genes (e.g., sbp-1, fat-4/5/6/7) and pathways (insulin/IGF-1 via DAF-16) relevant to obesity, with fat accumulation measurable via dyes (Nile red, Oil Red O). Prior findings link phenolics like ferulic acid, quercetin, isorhamnetin, and caffeic acid with anti-adipogenic, anti-hyperglycemic, and lipolysis-promoting effects; isorhamnetin modulates fat oxidation via NHR-49-dependent pathways in C. elegans. Studies also suggest VEGF-A, AKT1, IL-6, and MMP9 relate to obesity pathophysiology. These foundations motivate applying fermentation, metabolomics, network pharmacology, and in vivo nematode validation to assess anti-obesity potential of fermented brown rice.

Procurement of chemicals and plant materials: Media and chemicals were obtained from Daejung Chemicals and Metals Co., Ltd (Korea). A PicoSens Triglyceride and Free Fatty Acid Assay Kit was purchased from BIOMAX (Seoul, Korea). Metabolite classification utilized METLIN and Metabolomics Workbench. Brown rice was sourced from the Rural Development Administration (RDA), Republic of Korea. Samples were powdered and sieved (40 mm). Bacterial growth and optimization of brown rice fermentation: Sterilized rice powder was mixed with distilled water (1:6), autoclaved (121 °C, 15 min), and inoculated with Pediococcus acidilactici MNL5 (KCTC15156BP) at 2 × 10^7 CFU/mL. Fermentations proceeded 48 h at 37 °C, 200 rpm, followed by freeze-drying and storage at -20 °C. Solvent extraction: 50 g fermented powder was extracted with 100 mL 70% ethanol (1:20 w/v) at -50 °C for 4 h on an electric shaker. After centrifugation (4000 g, 10–15 min), extraction was repeated three times. Supernatants were evaporated (50–55 °C), freeze-dried, stored at -20 °C, and reconstituted to 1 mg/mL. In vitro pancreatic lipase inhibition assay: Assays were conducted in 36-well plates with minor modifications; fluorescence readings with/without substrate assessed percentage inhibition at 1 mg/mL. Total phenolic content (TPC) and total flavonoid content (TFC): In 36-well format per Glorybai et al. For TPC, 100 µL extract/standard/blank + 200 µL Folin-Ciocalteu, incubate 2 h at RT; add 800 µL 700 mM Na2CO3; read A765 nm. For TFC, 250 µL extract + 75 µL NaNO2 (50 g/L) + 1 mL water; after 5 min add 75 µL AlCl3 (100 g/L); then 500 µL 1 M NaOH + 600 µL water; incubate 6 min; shake 30 s; read A510 nm (SpectraMax i3). Results expressed as mg gallic acid or catechin equivalents per 100 g DW. DPPH, ABTS, FRAP assays: DPPH: 100 µL extract/standard/blank + freshly prepared 500 µM DPPH; incubate 30 min RT; read A515 nm; Trolox standard curve. ABTS: Prepare ABTS+ by mixing 2.45 mM K2S2O8 with 7 mM ABTS (1:1) in dark 12–16 h; dilute to A734 = 0.700 ± 0.020; mix 100 µL extract with 1 mL ABTS+; read A734. FRAP: 0.1 mL extract + 3.9 mL acetate buffer (0.3 M, pH 3.6), TPTZ (10 mM in 40 mM HCl), FeCl3·6H2O (20 mM); incubate 10 min at 37 °C; read A593. Values expressed as mg Trolox equiv./100 g DW. Radical scavenging (%) = (Ac - Ae)/Ac × 100. UHPLC-Q-TOF-MS/MS untargeted metabolomics: Filtered samples were injected through 0.22 µm filters. MS in negative mode; m/z 100–1000; resolution 5000; capillary 1.45 kV; cone 30 V; N2 desolvation 900 L/h; cone gas He 45 L/h; source 120 °C; desolvation 250 °C. MS/MS at 15, 20, 30 V collision energies. Metabolites identified by RT and spectra vs databases (XCMS Online/METLIN; Metabolomics Workbench). Network pharmacology: UHPLC-identified metabolites were assessed in TCMSP for oral bioavailability (OB), drug-likeness (DL), and BBB parameters; chemical/bio data from PubChem and DrugBank. Obesity-related gene targets obtained from TCMSP, DisGeNET, and GeneCards using keyword “obesity.” STRING 11.0 constructed protein–protein interaction networks (confidence 0.700). GO and KEGG enrichment performed for BP, MF, CC. Networks of hub genes and target–compound interactions were built in Cytoscape. In silico molecular docking: 3D structures of hub proteins from RCSB PDB and ligands from DrugBank/PubChem. Protein preparation included hydrogen addition and water removal. AutoDock Vina (flexible docking) used to dock ligands into auto-identified binding pockets. Discovery Studio analyzed 2D/3D interactions; docking scores and H-bonds recorded. C. elegans model—lifespan and lipid assays: C. elegans N2 and E. coli OP50 from CGC. Worms maintained at 20 °C on NGM; plates contained FUDR (140 µM). Obesity induced with 10% glucose; treatments included FBR-1741 (1 mg/plate) and specific metabolites at doses guided by UHPLC quantification per 1 mg/mL FBR-1741: quercetin 0.19 µg/plate, isorhamnetin 0.18 µg/plate, irisflorentin 0.18 µg/plate, ferulic acid 0.57 µg/plate, protocatechuic acid 0.19 µg/plate. Lifespan: synchronized L1 larvae grown to L4; 50 worms/plate at 20 °C; daily scoring; transferred to fresh plates every 3 days. Lipid staining and quantification: L4 worms washed in M9; Nile red (0.05 µg/mL) incubated 30 min; rinsed with 25% ethanol; 60% isopropanol 5 min; imaged by fluorescence microscopy (Olympus CKX53, SZ61; HK3.1 CMOS). Oil Red O (0.05 µg/mL) used similarly. ImageJ quantified fluorescence from anterior intestine to vulva; n=6 worms per group. Triglycerides (TG) and free fatty acids (FFA): At 50% lifespan, TG and FFA measured using Biomax colorimetric kits per manufacturer instructions. Gene expression (qPCR): ~1000 worms per treatment collected on day 7 (50% lifespan), washed, and lysed with TRIzol and Lysing Matrix Z. cDNA prepared using high-capacity kit; qPCR with StepOnePlus and GoTaq qPCR Master Mix. Reactions: 10 µL GoTaq Mix, 2 µL cDNA (10 ng/µL), 0.4 µL each primer (10 pg/µL), 7 µL water. Relative expression by 2^-ΔΔCT normalized to act-1. Targets included sbp-1, fat-4, fat-5, fat-6, fat-7, hosl-1, daf-16. Worm metabolomics: ~1000 worms homogenized in 70% methanol; supernatant centrifuged (10,000 rpm, 10 min), filtered (0.45 µm), and analyzed as above. Statistics: All experiments at least in triplicate; results as mean ± SD. Graphs in Microsoft Excel 365. Heatmaps via ClustVis. Docking utilized AutoDock Vina 4.2.6. Chemical formulae cross-checked in PubChem and ChemSpider.

- Among nine fermented brown rice (FBR) varieties fermented with P. acidilactici MNL5, FBR-1741 showed the highest pancreatic lipase inhibition (87.6 ± 2.1%). - Antioxidant capacities were maximal in FBR-1741: DPPH 358.5 ± 2.8 mg Trolox equiv./100 g DW; ABTS 362.5 ± 3.3 mg Trolox equiv./100 g DW; FRAP 295.5 ± 3.3 mg Trolox equiv./100 g DW. TPC and TFC were also highest (TPC 343.5 ± 3.89 mg GAE/100 g DW; TFC 220.5 ± 3.81 mg catechin equiv./100 g DW). - UHPLC-Q-TOF-MS/MS identified 17 phenolic/related metabolites in FBR-1741 (including ferulic acid, cinnamic acid, p-coumaric acid, protocatechuic acid, ethyl 4-hydroxybenzoate, caffeic acid, homovanillic acid, butylparaben, gallic acid, quercetin, isorhamnetin, sophoricoside, phenprobamate, daphnetin, cantharidin, genipin, irisflorentin). Many are implicated in lipid metabolism homeostasis. - Fermentation markedly increased ferulic acid in 1741: RBR-1741 175.2 µg/g to FBR-1741 570.2 µg/g after 48 h. - Network pharmacology mapped 17 compounds to 132 obesity-related target genes; top hub proteins were VEGFA, AKT1, JUN, IL-6, and MMP9. Five compounds (ferulic acid, quercetin, isorhamnetin, protocatechuic acid, irisflorentin) showed significant interactions with hub proteins. - Molecular docking: Quercetin had highest binding scores with AKT1 (-6.8), IL-6 (-7.2), and MMP9 (-8.0); isorhamnetin docked best with VEGFA (-8.5) and JUN (-5.3); irisflorentin also showed favorable VEGFA docking (-7.4). Ferulic acid showed moderate docking across hubs (e.g., VEGFA -6.9 with two H-bonds). Protocatechuic acid docked with MMP9 showed a reported binding score of 7.1 with five H-bond interactions. - In vivo C. elegans model (glucose-induced obesity): FBR-1741 extended mean/maximum longevity (34.5 ± 1.5%) vs negative controls (30.2 ± 1%). Lifespan benefits for key metabolites: ferulic acid (31.5 ± 1.4), quercetin (28.5 ± 1), irisflorentin (22.5 ± 0.8), isorhamnetin (11.5 ± 0.9), protocatechuic acid (6.5 ± 1) (as reported). - FBR-1741 and ferulic acid reduced fat accumulation (Nile red and Oil Red O staining), decreased triglycerides dose-dependently, and altered FFA/TG profiles. Reported FFA levels (nmol/mg) for groups included 3.86 (normal), 4.15 (obese), 9.23, and 6.59 (FA and/or orlistat groups as reported). TG increased with obesity and was significantly reduced by FBR-1741 and ferulic acid. - Gene expression in C. elegans: FBR-1741 down-regulated lipogenesis genes sbp-1, fat-4, fat-5, fat-6, fat-7; upregulated lipolysis/longevity genes hosl-1 and daf-16. DAF-16 activity associated with >20% lifespan extension. Fatty acid metabolite profiles indicated increases in several fatty acids in FBR-1741 and FA groups, with concomitant amino acid changes (serine, arginine, histidine, threonine, methionine, glycolic acid).

This study demonstrates that lactic fermentation of brown rice with P. acidilactici MNL5 substantially enhances polyphenolic profiles and antioxidant capacities, translating to elevated in vitro pancreatic lipase inhibition. Untargeted metabolomics identified 17 key metabolites in FBR-1741, several with known anti-adipogenic and metabolic benefits. Network pharmacology linked these metabolites to 132 obesity-related targets with hub nodes VEGFA, AKT1, JUN, IL-6, and MMP9, suggesting multi-target modulation of angiogenesis, insulin signaling, inflammation, and matrix remodeling. Docking analyses supported plausible ligand–protein interactions for quercetin, isorhamnetin, irisflorentin, ferulic acid, and protocatechuic acid at these hubs. In vivo validation in C. elegans confirmed physiological relevance: FBR-1741 and ferulic acid extended lifespan, reduced fat deposition, lowered triglycerides, and modulated lipid metabolism genes by down-regulating lipogenesis (sbp-1; fat-4/5/6/7) and up-regulating lipolysis and longevity pathways (hosl-1; daf-16). The marked increase of ferulic acid upon fermentation likely contributes to these benefits, though synergistic effects among multiple metabolites are probable. Collectively, results support the initial hypothesis that fermenting selected brown rice varieties enhances bioactive constituents with anti-obesity efficacy and that systems-level analyses plus a nematode model can identify candidate mechanisms and compounds.

Fermenting brown rice with Pediococcus acidilactici MNL5 yields a functional ingredient with enhanced anti-obesity potential. Among nine varieties, FBR-1741 exhibited the strongest pancreatic lipase inhibition, antioxidant capacity, and a rich profile of 17 metabolites, notably increased ferulic acid. Network pharmacology identified 132 obesity-related targets and hub genes (VEGFA, AKT1, JUN, IL-6, MMP9) engaged by key metabolites, which docking corroborated. In C. elegans, FBR-1741 and ferulic acid extended lifespan, reduced lipid accumulation, lowered TGs, and favorably regulated lipid metabolism genes. These findings support developing fermented brown rice products as obesity-targeted functional foods. Future work should include: (1) validation in mammalian models to assess efficacy, dose–response, and safety; (2) gut microbiota analyses to elucidate host–microbe–metabolite interactions; (3) pharmacokinetics and bioavailability studies of key metabolites from FBR-1741; and (4) optimization of fermentation parameters to standardize bioactive profiles.

- Affiliation for one author (superscript 8) was not provided in the text excerpt. - Some reported numerical data (e.g., free fatty acid group values) appear inconsistent or incomplete in sequence. - Findings are primarily from in vitro assays, in silico analyses, and a C. elegans model; translational relevance to humans requires validation in mammalian models and clinical studies. - The network pharmacology and docking results indicate potential interactions but do not confirm in vivo target engagement or causality for each compound. - Metabolomic validation in vivo (within C. elegans) for fermented materials requires further investigation as noted by the authors.