Inhibition of oxygen-mediated opportunistic bacteria overgrowth in the ileum alleviates excessive fatty acid absorption against a high-fat diet

Inhibition of oxygen-mediated opportunistic bacteria overgrowth in the ileum alleviates excessive fatty acid absorption against a high-fat diet | 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 Inhibition of oxygen-mediated opportunistic bacteria overgrowth in the ileum alleviates excessive fatty acid absorption against a high-fat diet Xiao Guan, Yongyong Liu, Kai Huang, Yu Zhang, Sen Li, Jing Liu, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7956394/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 High-fat diet-induced gut microbiota disorder leads to excessive fat absorption, especially in the lower part of the small intestine. A critical but unclear aspect is how the interactions between microbial communities and fat absorption. Using a mouse model, we show that prolonged high-fat intake is linked to increased luminal oxygen bioavailability, promoting the overgrowth of oxygen-mediated opportunistic bacteria ( Staphylococcus xylosus ) in the small intestine. S. xylosus effectively produces a saturated medium-chain fatty acid (dodecanoic acid) by its substrate-specific Acyl-CoA thioesterase (ACOT). Moreover, this microbe-derived dodecanoic acid (DA) shows an appropriate amount for activating the intestinal PPARα-CD36 signaling, enhancing the fatty acid uptake. Interestingly, we also show that avenanthramide B (AVN B), a novel antioxidant derived from oat, increases ileal epithelial hypoxia, and selectively inhibits S. xylosus proliferation. This alleviates excessive fat absorption, providing an alternative dietary intervention for treating obesity. Health sciences/Health care/Nutrition Health sciences/Diseases/Nutrition disorders/Obesity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 INTRODUCTION Dietary fat serves as a primary energy source for the human body. The recommended dietary fat intake ranges from 20% to 35% of total daily energy consumption. However, in Western diets, fat contributes 40% to 55% of daily caloric intake 1 – 3 . Over 95% of ingested lipids are triglycerides, which are formed by the esterification of glycerol with long-chain fatty acids (containing 16 or 18 carbon atoms) 3 , 4 . These triglycerides are hydrolyzed into fatty acids in the small intestine by the combined action of bile salts and pancreatic enzymes 5 , 6 . Fatty acid absorption by intestinal epithelial cells primarily occurs via simple diffusion, and transmembrane proteins such as CD36 and fatty acid transporter 4 (FATP-4) have been shown to facilitate this process 3 , 7 – 9 . Once absorbed, free fatty acids are either oxidized for energy production or re-esterified into triglycerides, which are then transported via the systemic circulation to extravascular tissues (e.g., liver and adipose tissue) for storage 2 , 10 . Excessive fat absorption and storage contribute to obesity, which significantly increases the risk of type 2 diabetes, non-alcoholic fatty liver disease, cardiovascular disorders, and various cancers 11 – 14 . A high-fat diet (HFD) can rapidly and continuously alter the human gut microbiota within 24–48 hours, thereby profoundly affecting dietary fat absorption 15 , 16 . Germ-free (GF) mice are resistant to diet-induced obesity and impaired fat absorption, and similar results have been also observed in the antibiotic-treated pseudo-sterile mice 17 , 18 . Historically, most studies have focused on cecal or fecal microbiota, with relatively little attention paid to the small intestinal microbiota 19 , 20 . However, recent evidence suggests that the small intestinal microbiota plays a critical role in lipid absorption 3 , 15 , 16 , 21 . The composition and abundance of small intestinal microbiota are shaped by environmental factors such as pH, oxygen levels, bile acids, and antimicrobial peptides, which differs from the large intestinal microbiota 3 , 16 , 22 . The microbial load in the small intestine (approximately 10³-10⁷ cells per gram of tissue) is much lower than that in the large intestine (≈ 10¹² cells per gram) 16 , 23 . At the phylum level, Firmicutes and Proteobacteria dominate the small intestine, whereas Firmicutes and Bacteroidetes are the major phyla in the large intestine 3 , 24 , 25 . Significant differences also exist at the specific level: Lactobacillus , Veillonella , Enterococcus , and Clostridium are predominant in the small intestine, while Lachnospiraceae , Ruminococcaceae , Bacteroidaceae , and Prevotellaceae are the main families in the large intestine 26 – 28 . The gut microbiota modulates host fat absorption through its metabolites, including short-chain fatty acids, lactic acid, and bile acids 1 , 29 – 31 . However, individual variations in HFD-induced intestinal flora dysbiosis pose a challenge for targeted regulation, which remains a key limitation in current research. Typically, most fatty acids derived from triglyceride hydrolysis are absorbed in the proximal and middle jejunum, with only a small fraction reaching the distal small intestine 3 , 32 . Nevertheless, studies have shown that HFD-associated excessive fat absorption is linked to abnormal fatty acid uptake in the ileum 15 , 16 . The composition of the microbiota varies across different segments of the small intestine, with microbial loads estimated to range from 10 3 to 10 8 CFU/ml in the distal ileum, which serves as a transitional zone between the sparse aerobic flora of the jejunum and the dense strict anaerobes of the colon 3 , 33 . Recent studies have demonstrated that an HFD can induce intestinal oxygen leakage, disrupting the ecological balance between aerobic bacteria (e.g., Escherichia coli , Staphylococcus spp.) and anaerobic bacteria (e.g., Bacteroides , Lactobacillus spp.) in the ileum and leading to microbiota dysbiosis 34 – 38 . However, the intrinsic mechanism by which ileal microbiota drives excessive fatty acid absorption remains unclear. In this study, we investigated how ileal microbes and their metabolites regulate intestinal lipid absorption and contribute to obesity. We found that HFD induced epithelial oxygenation in the small intestine, leading to the oxygen-mediated opportunistic bacteria ( S. xylosus ) overgrowth. S. xylosus specifically produced DA by mediating its ACOT activity, which in turn activated intestinal PPARα-CD36 signaling, thereby enhancing the excessive fatty acid absorption in ileum. Furthermore, oat avenanthramides (AVNs), as the potent plant-derived antioxidants, have been shown to significantly reduce the incidence of obesity in clinical trials 39 , 40 . We found that the intake of AVN B inhibited the colonization of S. xylosus , consequently preventing weight gain. This study offers a novel perspective on mitigating obesity and metabolic disorders through dietary interventions on a global scale. RESULTS HFD induced excessive lipid absorption linked to S. xylosus overgrowth To investigate the effects of different diets and oat AVNs on intestinal lipid absorption, we established an HFD-induced mouse obesity model with various dietary treatments and AVN B intervention (Fig. 1a). After 10 weeks, compared with the control and AVN B groups, the HFD group exhibited significantly increased body weight, fat mass index, liver and epididymal fat weights, and serum and hepatic levels of total cholesterol (TC), triglycerides (TG), and low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) levels were significantly decreased (Fig. 1b, d, e; Extended Data Fig. 1a-c, h-j, k-m). Histopathological analysis of epididymal fat and liver tissues revealed larger epididymal adipocytes, massive lipid accumulation in hepatocytes, and severe liver tissue damage in the HFD group (Extended Data Fig. 1f, g). Despite similar energy intake, there were no significant differences in fecal TC and TG levels between the HFD and control groups (p > 0.05) (Fig. 1c; Extended Data Fig. 1n, o). In contrast, the AVN B group showed increased fecal TG excretion, suggesting that the HFD group may have enhanced lipid absorption capacity. We further measured small intestine length and intestinal villus length (Fig. 1f, g; Extended Data Fig. 1d, e). Mice in the HFD group had longer small intestines and intestinal villi than those in the control and AVN B groups. Oil Red O staining revealed greater lipid accumulation in intestinal epithelial cells of the HFD group (Fig. 1h). A lipid tolerance test (after 12 hours of fasting) showed that within 4 hours of ingesting the same lipid dose, the HFD group had higher serum TG levels and a larger lipid tolerance area under the curve (AUC) than the control and AVN B groups (Fig. 1i, j). These results indicate that an HFD promotes intestinal villus elongation, thereby enhancing lipid absorption and contributing to obesity. Additionally, we hypothesized that HFD increases lipid delivery to the distal small intestine, leading to excessive absorption. 16S rRNA sequencing analysis revealed significant differences in gut microbial composition among the treatment groups (Fig. 1l-q; Extended Data Fig. 1p, q). The abundance of S. xylosus was significantly higher in the HFD group than in the control and AVN B groups (p < 0.001), whereas AVN B increased the abundance of Lactobacillus reuteri and Lactobacillus johnsonii . Correlation analysis showed a strong positive correlation between gut S. xylosus abundance and mouse lipid tolerance (AUC) (r = 0.7884, p = 0.0133) (Fig. 1r). Furthermore, analysis of the GMrepo database ( https://gmrepo.humangut.info ) revealed that fecal S. xylosus abundance was significantly higher in obese individuals than in healthy controls (p = 0.0279), which is consistent with our mouse experimental results (Fig. 1s). HFD activated the ileal PPARα-CD36 Signaling To explore the mechanism by which an HFD enhances lipid absorption, we performed transcriptomic analysis of mouse ileum tissue. The results showed that the PPARα-CD36 signaling pathway was activated in the HFD group (Fig. 2a-e). To validate this finding, we used immunofluorescence (IF) to detect PPARα signaling in different segments of the small intestine (duodenum, jejunum, and ileum) (Fig. 2f-i). PPARα expression in the ileum of the HFD group was significantly higher than that in the control and AVN B groups (p < 0.001), with a more pronounced difference than in the duodenum and jejunum (p < 0.05). RT-qPCR analysis confirmed the reliability of the transcriptomic results (Fig. 2j). Compared with the control and AVN B groups, the HFD group showed upregulated expression of Pparα , Cd36 , Srebp1c , Rxr , Cpt1 , and Hmgcs2 in the ileum. Notably, Fatp4 was not activated in the HFD group but was upregulated in the AVN B group relative to the control group (Fig. 2e, j). IF staining also revealed significantly higher ileal CD36 expression in the HFD group (p < 0.001) (Fig. 2k, l). Additionally, HMGCS2, a downstream target of PPARα signaling, was activated in the HFD group, potentially contributing to intestinal villus elongation (p < 0.001) (Extended Data Fig. 1r, s). These results suggest that HFD enhances lipid absorption by activating intestinal PPARα signaling and regulating CD36 expression, rather than by upregulating FATP4 (Fig. 2m). The relationship between S. xylosus overgrowth and PPARα-CD36 Signaling To identify metabolites regulating small intestinal lipid absorption, we performed untargeted metabolomics analysis. The HFD group showed significantly elevated DA levels (Fig. 3a-c), which was supported by increased expression of the medium- and long-chain fatty acid receptor FFAR4 in this group (Extended Data Fig. 1t). In contrast, the AVN B group had significantly higher intestinal lactic acid levels, consistent with the increased abundance of L. reuteri and L. johnsonii (Extended Data Fig. 1p, q). Correlation analysis revealed a significant positive correlation between S. xylosus abundance and intestinal DA levels, as well as between L. reuteri abundance and intestinal lactic acid levels (Fig. 3d, e). Network analysis further confirmed the association between Staphylococcus and DA (Fig. 3f). Heatmap analysis showed strong positive correlations between S. xylosus abundance and the expression of Pparα (r = 0.8441, p < 0.0001) and Cd36 (r = 0.8584, p < 0.001) (Fig. 3g). Notably, DA was not detected in either normal or high-fat diets, suggesting that HFD intake creates a favorable environment for S. xylosus proliferation, and the resulting microbe-derived DA activates intestinal PPARα signaling and upregulates CD36, thereby promoting lipid absorption in the distal small intestine (Fig. 3h). Ileal PPARα activation promoted excessive lipid absorption To verify the role of ileal PPARα signaling in intestinal lipid absorption in HFD-fed mice, we administered the PPARα agonist GW590735 and antagonist GW6471 (Fig. 3i). After 4 weeks, compared with the HFD group, supplementation with the PPARα agonist significantly increased body weight, fat mass index, epididymal fat weight, and liver weight (p < 0.05) (Fig. 3j, k; Extended Data Fig. 2e, h). In contrast, supplementation with the PPARα antagonist and/or AVN B reversed HFD-induced weight gain (p < 0.05) (Fig. 3j). The PPARα agonist group had the highest serum TC, TG, and LDL-C levels and the lowest HDL-C levels (Fig. 3l; Extended Data Fig. 2b-d), with corresponding histopathological changes in epididymal fat and liver (Extended Data Fig. 2e-k). Despite similar energy intake, the agonist group had lower fecal TC and TG excretion (Extended Data Fig. 2a, l, m) and longer small intestine and villus lengths (Extended Data Fig. 2o-r), indicating enhanced lipid absorption. It should be noted that the limited dosage of the agonist or antagonist does not impact hepatic PPARα signaling (Extended Data Fig. 2n). Oil Red O staining of the ileum showed the highest lipid accumulation in the agonist group, followed by the HFD group, and minimal lipid droplets were observed in the agonist + AVN B, antagonist, and antagonist + AVN B groups (Fig. 3n). Within 4 hours of ingesting the same lipid dose, the agonist group had the highest serum TG levels and a larger lipid tolerance AUC than the HFD group (Fig. 3o, p). RT-qPCR and IF analysis confirmed significantly higher ileal PPARα and CD36 expression in the agonist group than in the HFD group (p < 0.05) (Fig. 3q-u; Extended Data Fig. 2s). These results further suggest that the activation of ileal Pparα favors lipid absorption by intestinal epithelial cells. Microbe-derived DA specifically activated intestinal PPARα To investigate the effect of DA on lipid absorption, we administered low and high doses of DA to HFD-fed mice via gavage for 4 weeks (Fig. 4a). A low dose of DA increased body weight, epididymal fat mass, fat mass index, and serum and hepatic TC, TG, and LDL-C levels (Fig. 4b, c; Extended Data Fig. 3b-e, h-m). Both low- and high-dose DA groups had longer small intestines and intestinal villi than the HFD group (Extended Data Fig. 3o-r). RT-qPCR and IF analysis confirmed upregulated ileal PPARα and CD36 expression in both DA groups (Fig. 4f-i; Extended Data Fig. 3v). Notably, the high-dose DA group showed decreased body weight, serum and hepatic TC/TG/LDL-C levels, and fecal TC/TG excretion (Fig. 4b, c; Extended Data Fig. 3b-e, j-m, s, t). Histopathological analysis of the liver revealed well-organized hepatocytes in the high-dose DA group (similar to the control group) (Extended Data Fig. 3f, g). RT-qPCR showed activated liver PPARα and CPT1 expression in the high-dose DA group, indicating enhanced hepatic lipid metabolism (Fig. 4j; Extended Data Fig. 3n). In contrast, low-dose DA did not activate hepatic PPARα or CPT1, leading to lipid accumulation due to impaired systemic lipid metabolism. Oil Red O staining and lipid tolerance tests confirmed these findings (Fig. 4d, e; Extended Data Fig. 3u). Compared with the high-dose DA group, the low-dose group showed significant lipid accumulation in intestinal epithelial cells. At 3 hours after gavage with the same lipid dose, serum TG levels in the high-dose DA group decreased rapidly (even lower than the HFD group). The low-dose DA group had a significantly larger lipid tolerance AUC than the HFD group (p 0.05). To confirm that low-dose DA-induced weight gain is due to excessive lipid absorption, we fed mice a low-fat normal diet (11.1% fat) supplemented with low-dose DA (Fig. 4k). After 4 weeks, there were no significant differences in body weight, fat mass index, epididymal fat weight, serum TC/TG levels, or liver weight between the control and low-dose DA groups (Fig. 4l; Extended Data Fig. 4a-f). However, RT-qPCR and IF analysis showed upregulated ileal PPARα and CD36 expression in the low-dose DA group (Fig. 4o; Extended Data Fig. 4i, m, n-q), with no significant changes in liver PPARα or CD36 expression (p > 0.05) (Extended Data Fig. 4j). The low-dose DA group also had longer small intestines and intestinal villi (Extended Data Fig. 4g, h, k, l). Within 2–4 hours of lipid ingestion, the low-dose DA group had higher serum TG levels and a larger lipid tolerance AUC than the control group (p < 0.05) (Fig. 4m, n). These results indicate that low-dose DA promotes intestinal lipid absorption and weight gain, with HFD intake being a prerequisite. To verify that DA directly activates intestinal PPARα, we established a pseudo-sterile mouse model using antibiotic (ABX)-containing drinking water. Mice were gavaged with low-dose DA (1 mg/kg BW/day) or the PPARα agonist GW590735 to eliminate the influence of gut microbiota (Fig. 4p). After 6 weeks, the DA and PPARα agonist groups had higher body weights than the HFX (HFD + ABX) group (Fig. 4q), with corresponding changes in fat mass index, serum/liver TC/TG/HDL-C/LDL-C levels, fecal TC/TG levels, and histopathology of liver and epididymal fat (Extended Data Fig. 5a-o, r, u). Ileal histology showed longer intestinal villi in the DA and agonist groups (Extended Data Fig. 5p, q), with similar trends in small intestine length, Oil Red O staining, and fecal TC/TG levels (Extended Data Fig. 5s, t, v). RT-qPCR and IF analysis confirmed upregulated ileal PPARα and CD36 expression (at both transcriptional and translational levels) in the DA and agonist groups (p < 0.05) (Fig. 4t; Extended Data Fig. 5w-bb). Additionally, the DA and agonist groups had significantly enhanced lipid tolerance (Fig. 4r, s). To determine whether AVN B directly inhibits PPARα and CD36, we co-incubated AVN B with oleic acid (OA)-induced Caco-2 cells (Fig. 4u; Extended Data Fig. 6e, f). AVN B did not significantly inhibit PPARα or CD36 expression (p > 0.05). We then induced Caco-2 cells with fatty acids of different chain lengths (all supplemented with 500 µM OA). RT-qPCR showed that 100 µM caprylic acid (C8), DA (C12), myristic acid (C14), and arachidic acid (C20) significantly activated PPARα, CD36, and HMGCS2 (p < 0.05) (Fig. 4v; Extended Data Fig. 6a, b). DA exhibited the strongest activation capacity, significantly activating PPARα and CD36 even at 50 µM (p < 0.05), which was consistent with previous findings in HepG2 cells 41 . We used siRNA to knock out PPARα in Caco-2 cells. Oil Red O staining and lipid droplet quantification showed that DA induced excessive lipid uptake in Caco-2 cells (compared with the OA group) (Fig. 4w; Extended Data Fig. 6c), but this effect was abolished in PPARα-knockout (PPARα-KO) cells. Intracellular TG quantification yielded similar results (Fig. 4x). RT-qPCR showed that OA significantly activated PPARα and CD36 (p < 0.05), with further upregulation in the OA + DA group (Fig. 4y; Extended Data Fig. 6d). PPARα knockout significantly inhibited PPARα expression and abolished OA/DA-induced activation of PPARα and CD36 (though CD36 expression itself was not affected). These results confirm that DA enhances lipid uptake by Caco-2 cells via activating PPARα signaling. HFD promoted S. xylosus overgrowth by increasing the bioavailability of oxygen To explore why S. xylosus abundance is higher in obese mice, we used Hypoxyprobe to detect ileal hypoxia. The HFD group showed loss of intestinal epithelial hypoxia and a significantly lower hypoxia score than the control and AVN B groups (p < 0.01) (Fig. 5a, b). Further analysis revealed significant downregulation of hypoxia-inducible factor 2α (HIF-2α) in the HFD group (Fig. 5c). Growth curve analysis showed that S. xylosus proliferated rapidly under aerobic conditions but was inhibited under hypoxic conditions (Fig. 5d, e). In contrast, L. reuteri exhibited stronger proliferation under anaerobic conditions (Fig. 5f, g). Previous studies have shown that intestinal inflammation increases gut permeability ("leaky gut"), allowing oxygen-mediated opportunistic pathogens (e.g., E. coli , Salmonella , Enterococcus ) to use oxygen as an electron acceptor, providing a metabolic advantage for growth 42 – 44 . Consistent with this result, the HFD group had significantly higher ileal levels of the inflammatory factors TNF-α and IL-6 than the control and AVN B groups (p < 0.05) (Extended Data Fig. 1u, v). Additionally, the HFD group showed decreased ileal total superoxide dismutase (T-SOD) activity and increased malondialdehyde (MDA) levels (Extended Data Fig. 1w, x). These results suggest that HFD intake induces intestinal inflammation, disrupts the intestinal hypoxic environment, and increases S. xylosus abundance while decreasing L. reuteri abundance (Fig. 5h). S. xylosus overgrowth promoted lipid absorption To verify the contribution of S. xylosus to intestinal lipid absorption, we established a pseudo-sterile mouse model using 2 weeks of ABX-containing drinking water. Mice were then gavaged with S. xylosus for 2 weeks, followed by 4 weeks of gavage with saline, L. reuteri , AVN B, or 5-aminosalicylic acid (5-ASA) (Fig. 5i). At the end of the experiment, despite similar energy intake, the S. xylosus -gavaged group had higher body weight than the HFX (HFD + ABX), L. reuteri -, AVN B-, and 5-ASA-gavaged groups (Fig. 5j; Extended Data Fig. 7a). Compared with the HFX group, the S. xylosus group showed increased fat mass index, epididymal fat weight, serum/hepatic TC/TG/LDL-C levels, and severe hepatic lipid accumulation; conversely, HDL-C levels and fecal TC/TG excretion were decreased (Fig. 5k; Extended Data Fig. 7b-j, m, n, q, r, u). The L. reuteri -, AVN B-, and 5-ASA-gavaged groups showed the opposite trends. The S. xylosus group had longer intestinal villi and small intestines, with greater lipid accumulation in intestinal epithelial cells (Extended Data Fig. 7k, l, o, p). Lipid tolerance tests showed higher serum TG levels and a larger lipid tolerance AUC in the S. xylosus group within 4 hours (Fig. 5l, m). RT-qPCR and IF analysis confirmed upregulated ileal PPARα and CD36 expression in the S. xylosus group, with downregulation in the L. reuteri -, AVN B-, and 5-ASA-gavaged groups (Fig. 5n-q; Extended Data Fig. 7t). CPT1 expression showed a similar trend to PPARα and CD36, which was potentially related to DA oxidation in small intestinal cells. Additionally, the S. xylosus group had significantly lower ileal HIF-1α expression than the L. reuteri -, AVN B-, and 5-ASA-gavaged groups (p < 0.05) (Fig. 5s). Hypoxyprobe staining showed lower ileal hypoxia scores in the HFX and S. xylosus -gavaged groups (Fig. 5o, r). The S. xylosus group also had higher ileal TNF-α and IL-6 levels than the other groups (Extended Data Fig. 7x, y). 16S rRNA sequencing of ileal contents confirmed S. xylosus colonization (Fig. 5t-v; Extended Data Fig. 7v, w). The S. xylosus - and L. reuteri -gavaged groups had the fewest unique operational taxonomic units (OTUs; 14, 7.45%), indicating that these bacteria influence the colonization of other intestinal microbes. The AVN B and 5-ASA groups had the most unique OTUs (28, 12.12%)-possibly due to AVN B’s strong free radical scavenging activity and 5-ASA-induced reduction in intestinal oxygen tension. At the species level, the S. xylosus group had significantly higher S. xylosus abundance (p < 0.001) and lower L. reuteri abundance (p < 0.05) than the other groups. The HFX group also had higher S. xylosus abundance and lower L. reuteri abundance than the L. reuteri -, AVN B-, and 5-ASA-gavaged groups. These results confirm that intestinal S. xylosus enhances lipid absorption by activating PPARα, which is likely via rapid proliferation following the loss of intestinal hypoxia. S. xylosus specifically produced the metabolite of DA To determine whether S. xylosus produces DA, we performed whole-genome sequencing of S. xylosus (Fig. 6a). The genome contains genes encoding key fatty acid synthesis enzymes: acetyl-CoA carboxylase (ACC), FabD, FabH, FabF, FabG, FabA, FabZ, FabI, and ACOT (which is responsible for fatty acid chain elongation and acyl-CoA hydrolysis), respectively (Fig. 6c). We conducted in vitro fermentation of S. xylosus and E. coli str. K-12 substr. MG1655 for 48 hours, with metabolite quantification by gas chromatography-mass spectrometry (GC-MS) (Fig. 6b). S. xylosus specifically produced DA under aerobic conditions (Fig. 6d), with no significant production under anaerobic conditions (p > 0.05). E. coli showed stronger DA production under aerobic conditions than S. xylosus (p < 0.05 vs. p < 0.001). Under anaerobic conditions, L. reuteri did not produce DA (Extended Data Fig. 8a). Using acyl-p-nitrophenyl (acyl-pNP) esters of different chain lengths as substrates, we tested the hydrolytic activity of S. xylosus and E. coli (Fig. 6e). Both bacteria showed substrate selectivity for C12-pNP, indicating that their ACOT enzymes specifically hydrolyze dodecanoyl-CoA. We cloned the S. xylosus ACOT genes ( ACOT1312 and ACOT2244 ) and the E. coli TesA gene ( TesA945127 ) into the recombinant plasmid pET-28a (+), with verification of recombinant genes and proteins (Fig. 6f, g; Extended Data Fig. 8b). The S. xylosus ACOT2244 enzyme exhibited the highest substrate selectivity for C12-pNP (Fig. 6h, i). Oat AVN B inhibits S. xylosus colonization by disrupting oxidative phosphorylation To investigate how AVN B inhibits HFD-induced obesity, we assessed its effect on S. xylosus and E. coli growth in vitro (Fig. 6j-l; Extended Data Fig. 8c-f). Bacterial growth curves and plate colony counting showed that AVN B significantly inhibited S. xylosus proliferation in a dose-dependent manner (half-maximal inhibitory concentration [IC₅₀] = 2.616 mg/mL), with similar effects on E. coli (IC₅₀ = 1.483 mg/mL) (Extended Data Fig. 8c-e). Transmission electron microscopy (TEM) revealed that S. xylosus cells without AVN B treatment were intact, with clear cell boundaries, intact cell walls/membranes, and normal intracellular contents (Fig. 6m). After 12 hours of treatment with 1 mg/mL AVN B, S. xylosus cells showed cell wall loss, disrupted cell contours, cytoplasmic vacuolization, and intracellular damage. Transcriptomic analysis of AVN B-treated S. xylosus (KEGG pathway enrichment) showed that AVN B affected oxidative phosphorylation and downregulated the related genes, such as qoxA , qoxB , qoxC , qoxD , sdhA , and atpE (Fig. 6n, o). These genes encode terminal oxidases of the bacterial respiratory chain, which are critical for energy metabolism and electron transport. Notably, in vitro tests showed that AVN B (0.5-5 mg/mL) did not inhibit the growth of L. reuteri or L. johnsonii (Extended Data Fig. 8g, h). DISCUSSION Previous studies have demonstrated that small intestinal microbes, such as Faecalibaculum rodentium , play a significant role in fat overabsorption 16,38,45 . GF mice conventionalized with HFD-induced small intestinal microbiota exhibit increased fat absorption even when fed a low-fat diet 16 . In this study, based on 16S rRNA sequencing analysis, we show for the first time that an HFD leads to the proliferation of S. xylosus in the ileum of mice, with a similar trend observed in human data. Notably, AVNB significantly reduces the level of fat absorption and effectively inhibits the proliferation of S. xylosus . Consequently, we utilized S. xylosus as a biomarker. Consistent with our findings, a previous study indicated that obese mice are more susceptible to Staphylococcus aureus infection 36 . Like Enterococcus , Streptococcus , and Lactobacillus , Staphylococcus are commensal bacteria present in the small intestine 3,46,47 . Unlike S. aureus , S. xylosus is a rennet-negative and safe strain that is frequently utilized in the enhancement of meat flavor during processing 48,49 . Therefore, obese individuals may also have a higher risk of contact, exposure, and infection with S. xylosus . When an HFD is consumed, the concentration of fatty acids in the intestinal epithelium becomes excessively elevated, leading to an overabsorption of fatty acids facilitated by the regulated intestinal epithelium 15,32 . Kawano et al. demonstrated that normal dietary fat is primarily absorbed in the jejunum, whereas an HFD transports fat into the ileum, resulting in overabsorption 15 . Through transcriptomic analysis, we discovered that HFD activates intestinal PPARα signaling. As a nuclear receptor, PPARα has been extensively studied regarding its role in lipid metabolism, yet the focus has predominantly been on the liver and adipose tissue 50-53 . Recent studies have indicated that intestinal PPARα signaling is crucial in regulating intestinal fat absorption 54-56 . Currently, two explanations exist for this phenomenon. Firstly, activation of intestinal PPARα can increase the length of the small intestine, thereby enhancing fat absorption by expanding the absorptive area 56,57 . The activation of intestinal HMGCS2 stimulates the Notch signaling pathway, promoting intestinal epithelial self-renewal, which further enlarges the intestinal surface area and enhances lipid absorption 58 . Similar findings were observed in the present study. Secondly, the activation of intestinal PPARα signaling leads to the upregulation of downstream fatty acid transporters, such as FATP4 and CD36, which accelerates fatty acid absorption 3,59,60 . In this study, we report for the first time that HFD selectively activates PPARα-CD36 signaling in the ileum, while PPARα-FATP4 signaling remains unaffected, which contrasts with previous reports 59,61 . We speculate that this discrepancy may be attributed to the differing microecological conditions of the small intestine segments, as the jejunum was the focus of the prior study 59,60 . This study focuses on how S. xylosus regulates ileal PPARα. Through metabolomics and correlation analysis, we identified a significant positive correlation between DA, S. xylosus , and PPARα-CD36 in the ileum. Therefore, we hypothesize that the proliferation of S. xylosus activates intestinal PPARα-CD36 via the DA produced, leading to excessive fat intake. To thoroughly validate this hypothesis, we conducted a series of experiments, including: 1) Utilizing PPARα agonist and antagonist, we found that activation of intestinal PPARα signaling, but not hepatic PPARα activation, significantly increased fat absorption. Conversely, inhibition of intestinal PPARα reduced fat absorption and increased fecal lipid excretion. Similar results have been validated in various model organisms. For instance, specific knockout of PPARα in the intestine significantly reduced body weight and metabolic disorders associated with obesity and non-alcoholic steatohepatitis in mice, whereas knockout of PPARα in the liver yielded the opposite effect 50,51,62-65 . This discrepancy underscores the complex roles of PPARα across different tissues and its essential involvement in regulating host metabolism and energy homeostasis 66,67 . 2) DA can effectively activate the intestinal PPARα-CD36 pathway, significantly increasing fat absorption and contributing to obesity. However, high doses of DA also activate the intestinal PPARα signaling pathway, which functions to inhibit obesity. This counterintuitive result occurs because high levels of DA, absorbed into the liver via the intestine, activate hepatic PPARα signaling and accelerate β-oxidation of fatty acids. Consequently, the rate of liver fat metabolism exceeds that of intestinal absorption. Furthermore, DA, as a potent signaling molecule, was able to activate PPARα signaling in the gut at low doses, thereby enhancing fat absorption in mice that were either fed a normal diet or treated with antibiotics. Notably, PPARα knockout cells demonstrated that PPARα is a significant target of DA. Fatty acids and eicosanoids serve as strong indicators of PPARα activity; however, different fatty acids exert varying effects on PPARα activation 56,68 . Our findings indicate that among a range of saturated fatty acids, DA exhibits a pronounced activation effect, aligning with previous studies 41,69,70 . 3) Transplantation of S. xylosus revealed that its intervention significantly activates intestinal PPARα signaling and leads to excessive fat absorption. Genomic profiling indicated that S. xylosus possesses a set of genes associated with de novo fatty acid synthesis. Furthermore, in vitro experiments demonstrated that S. xylosus can efficiently synthesize DA through specific ACOT enzymes. These findings suggest that S. xylosus regulates PPARα signaling by producing DA. The interaction between gut microbiota and the host is reciprocal 2,30 . Another focus of this study is to investigate why an HFD leads to the proliferation of S. xylosus . Previous research has shown that HFD increases the oxygen concentration in the intestinal lumen 34,43,44 . The ileal flora resides in an intestinal segment where anaerobic and aerobic bacteria maintain a delicate balance 3 . Changes in oxygen concentration can disrupt this equilibrium. Given that S. xylosus is an aerobic Gram-positive bacterium, we hypothesize that HFD accelerates the proliferation of S. xylosus by inducing an increase in intestinal oxygen concentration. To test this hypothesis, both in vitro and in vivo studies demonstrated that elevated oxygen levels effectively promote the proliferation and colonization of S. xylosus , while L. reuteri , serving as a control, exhibited opposite results. Furthermore, the rapid proliferation of S. xylosus enhances DA synthesis. Previous studies indicate that HFD can induce intestinal inflammation and alter permeability, leading to oxygen leakage 42,43,71 . Additionally, DA accelerates oxygen consumption, which increases the oxygen demand in intestinal epithelial cells 72 . This further exacerbates the rise in oxygen concentration in the intestinal lumen through oxygen leakage, thereby promoting the proliferation of S. xylosus . Moreover, we investigated a specific antioxidant active ingredient in oats, AVN B, formed from ferulic acid and 5-hydroxyanthranilic acid through an amide bond (Extended Data Fig. 10). AVN B exhibits potent antioxidant activity by degrading into dehydro-AVNs (dehydro-2f) and forming phenolic acids 39 . Due to their structural similarities, the antioxidant mechanisms of AVN B are analogous to those of ascorbic acid (VC), also involving the generation of dehydroascorbic acid 73 . The results of this study indicate that AVN B can selectively inhibit the proliferation of oxygen-opportunistic bacteria such as S. xylosus and E. coli , with an inhibitory effect comparable to that of 5-ASA 35 . Our findings demonstrate that oat-derived AVN B disrupts energy metabolism and electron transfer within the respiratory chain by inhibiting oxidative phosphorylation in S. xylosus , which leads to bacterial damage and consequently exerts an effect on fat absorption inhibition. Furthermore, AVN B significantly enhances the abundance of L. reuteri and promotes an increase in lactate levels in the gut. Previous studies have shown that elevated lactate can be converted to malonyl-CoA by intestinal epithelial cells, thereby inhibiting chylomicron secretion and reducing fat absorption. This finding is consistent with our results 1 . In summary, we employed a multipronged approach to elucidate how S. xylosus induces obesity through the production of the metabolite DA. The activation of PPARα by DA promotes the expression of CD36, thereby enhancing lipid absorption in the small intestine. We established a direct link between S. xylosus , DA, and the PPARα signaling pathways. Furthermore, oat AVN B reduces small intestinal lipid absorption by inhibiting the intestinal colonization of S. xylosus , suggesting that dietary compounds may offer new strategies for alleviating HFD-induced obesity. In the context of overnutrition, this study contributes to a clearer understanding of the intrinsic mechanisms underlying the development of obesity and metabolic diseases associated with HFD intake. Conversely, S. xylosus and DA may also be beneficial in malnourished populations, promoting more efficient fat absorption. Limitations of the study Although the present study confirmed that an HFD leads to an increase in oxygen concentration in the gut, the mechanisms by which oxygen permeates intestinal epithelial cells into the intestinal lumen remain unresolved. Previous studies have indicated that this oxygen permeability is associated with intestinal permeability, inflammation, and immunity. However, the specific mechanisms by which HFD triggers these changes are still unclear. Some research has shown that many microorganisms in the phylum Proteobacteria and the family Enterococcus are facultative anaerobes, which can dominate under high oxygen conditions. Human data indicate that the abundance of E. coli is also elevated in obese individuals, and E. coli can metabolize DA. Therefore, it remains to be determined whether the mechanism described in this study is generalizable to E. coli . Additionally, while this study confirmed the inhibitory activity of AVN B against S. xylosus , the specific mechanisms and targets require further elucidation. Methods Animal experiments All animal experiments were approved by the Animal Ethics Committee of Shanghai Yangpu District Shidong Hospital (Ethics Approval Number: IRB-AF63-V1.0) and conducted in accordance with the Guidelines for the Care and Use of Laboratory Animals of the People’s Republic of China. Male C57BL/6 mice (6-8 weeks old, 20 ± 2 g) were purchased from Shanghai JieSiJie Laboratory Animal Co., Ltd. (Shanghai, China). Diets were purchased from Jiangsu Collaborative Pharmaceutical Bioengineering Co., Ltd. (Nanjing, China), with compositions and energy densities listed in Extended Data Table 1. Mice were housed in a standard laboratory animal facility (50 ± 15% humidity, 20 ± 5°C) with a 12-hour light/dark cycle. After a 2-week acclimatization period with ad libitum feeding, experiments were initiated. Model 1 : 18 mice were randomly divided into 3 groups (n = 6/group). The control group received a normal diet; the HFD and AVN B groups received a 60% HFD. The AVN B group was gavaged with 100 mg/kg BW/day AVN B; the control and HFD groups received an equal volume of normal saline. Mice were sacrificed after 10 weeks of intervention. Model 2 : 30 mice were randomly divided into 5 groups (n = 6/group), all fed a 60% HFD. The HFD group was gavaged with 1% DMSO in normal saline; the ACT group with 0.3 mg/kg/day GW590735; the AAB group with 0.3 mg/kg/day GW590735 + 100 mg/kg BW/day AVN B; the INB group with 1 mg/kg BW/day GW6471; the IAB group with 1 mg/kg BW/day GW6471 + 100 mg/kg BW/day AVN B. Mice were sacrificed after 4 weeks. Model 3 : 24 mice were randomly divided into 4 groups (n = 6/group). The control group received a normal diet; the HFD, L-DA, and H-DA groups received a 60% HFD. The control and HFD groups were gavaged with 2% ethanol in normal saline; the L-DA group with 1 mg/kg BW/day DA; the H-DA group with 100 mg/kg BW/day DA. Mice were sacrificed after 4 weeks. Model 4 : 12 mice were randomly divided into 2 groups (n = 6/group), both fed a normal diet. The control group was gavaged with 2% ethanol in normal saline; the CDA group with 1 mg/kg BW/day DA. Mice were sacrificed after 4 weeks. Model 5 : 18 mice were randomly divided into 3 groups (n = 6/group), all fed a 60% HFD. Mice received ABX-containing drinking water (1 g/L ampicillin, 1 g/L neomycin sulfate, 1 g/L metronidazole, 0.5 g/L vancomycin) for 1 week before the experiment, with additional 2-day ABX treatment every week during the experiment 18 . The HFX group was gavaged with 1% DMSO in normal saline; the DAX group with 1 mg/kg BW/day DA; the ACX group with 0.3 mg/kg/day GW590735. Mice were sacrificed after 6 weeks. Model 6 : 30 mice were randomly divided into 5 groups (n = 6/group), all fed a 60% HFD. Mice received ABX-containing drinking water for 2 weeks before the experiment, with fecal sampling for plate coating. Except for the HFX group (gavaged with normal saline), the other groups were gavaged with 1×10⁹ CFU S. xylosus for 2 weeks. Subsequently, the HFS group continued to receive normal saline; the HSL group 1×10⁹ CFU L. reuteri ; the HSB group 100 mg/kg BW/day AVN B; the ASA group 400 mg/kg BW/day 5-ASA. Intervention lasted 4 weeks, with sacrifice 1 week after gavage cessation. At the end of each intervention, mice were fasted for 12 hours, and blood was collected via orbital plexus puncture. Serum was obtained by centrifugation at 4000 rpm/min. Mice were then dissected, and liver, epididymal fat, and intestinal tissues were collected and stored in liquid nitrogen or 4% paraformaldehyde. Histopathology and Oil Red O Staining of the Terminal Ileum Fresh liver, epididymal fat, and ileum tissues were fixed in 4% paraformaldehyde, embedded in paraffin, and sectioned. Hematoxylin-eosin (H&E) staining and Oil Red O staining were performed. Images were captured at 200× magnification using a biological digital microscope (Nikon, Tokyo, Japan) by Shanghai Xindi Biotechnology Co., Ltd. (Shanghai, China). Biochemical Parameter Determination Liver and terminal ileum samples were homogenized according to kit instructions, and supernatants were collected by centrifugation at 4000 rpm/min (4°C) for analysis. Protein concentration was determined using a BCA Protein Assay Kit (Beyotime Biotechnology, Shanghai, China). Serum and hepatic TC, TG, HDL-C, and LDL-C levels, as well as fecal TC and TG levels, were measured using commercial kits (Beyotime Biotechnology) according to standard protocols. Ileal T-SOD and MDA levels were determined using kits (Beyotime Biotechnology). Ileal TNF-α levels were measured using an ELISA kit (Beyotime Biotechnology). OD values were detected using a SYNERGY HITX multi-mode reader (BioTek, Winooski, VT, USA). Lipid Tolerance Test One week before sacrifice, mice were fasted for 12 hours and gavaged with 200 μL soybean oil per mouse 16 . Tail vein blood was collected at 0, 1, 2, 3, and 4 hours after gavage. Serum was obtained by centrifugation at 4000 rpm/min, and serum TG levels were measured using a kit (Beyotime Biotechnology). The lipid tolerance AUC was calculated. Ileum RNA Sequencing Analysis RNA sequencing of the terminal ileum was performed by Shanghai Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China). Total RNA was extracted, and concentration/purity was assessed using a Nanodrop 2000 (Thermo Fisher Scientific, Waltham, MA, USA). RNA integrity was verified by agarose gel electrophoresis and Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Libraries were constructed, enriched, and quantified using a TBS380 (Picogreen; Thermo Fisher Scientific). Cluster generation was performed via bridge PCR on a cBot (Illumina, San Diego, CA, USA), followed by sequencing on an Illumina Novaseq 6000 platform. Genes/transcripts and samples were clustered using an iterative approach. RNA Extraction, Reverse Transcription, and RT-qPCR Total RNA was extracted from liver and terminal ileum tissues using a kit (Thermo Fisher Scientific). RNA purity and concentration were determined by measuring the OD₂₆₀/OD₂₈₀ ratio using a microplate reader. RNA integrity was verified by 1% agarose gel electrophoresis 74 . cDNA was synthesized using a HiScript® II Q RT SuperMix for qPCR (+gDNA wiper) kit (Vazyme Biotech, Nanjing, China). RT-qPCR was performed using a ChamQ Universal SYBR qPCR Master Mix kit (Vazyme Biotech) on a Thermo Lifetech ABI QuantStudio 3 instrument (Thermo Fisher Scientific). Primers were synthesized by Sangon Biotech (Shanghai, China), with sequences listed in Extended Data Table 2. Immunofluorescence Staining Frozen ileum sections (4 μm) were fixed in 4% paraformaldehyde, dewaxed with xylene (20 minutes), and rehydrated with gradient ethanol (5 minutes each). Sections were heated in ethylenediaminetetraacetic acid (EDTA) buffer for 23 minutes, cooled to room temperature, and washed with PBS. After treatment with sodium borohydride solution and Sudan black dye, sections were blocked with 5% BSA for 1 hour. Primary antibodies against PPARα (Affinity Biosciences, Cincinnati, OH, USA), HMGCS2 (ABclonal, Woburn, MA, USA), and CD36 (Abcam, Cambridge, UK) were incubated overnight at 4°C, followed by incubation with secondary antibodies (Proteintech, Rosemont, IL, USA) for 1 hour. Sections were stained with 4′,6-diamidino-2-phenylindole (DAPI) and imaged at 200× magnification using a fluorescence microscope (CX41; Guangzhou Mingmei Optoelectronics Technology Co., Ltd., Guangzhou, China). Image analysis was performed using Image J software (Media Cybernetics Inc., Rockville, MD, USA). Untargeted Metabolomics Profiling Untargeted metabolomics of ileal contents was performed by Shanghai Majorbio Bio-Pharm Technology Co., Ltd. After sample pretreatment, metabolites were analyzed using an Agilent 8890B-5977B gas chromatography-mass spectrometry (GC-MS) system (Agilent Technologies). Separation was performed on a DB-5MS capillary column (40 m × 0.25 mm × 0.25 μm; Agilent Technologies). The inlet temperature was 260°C, with high-purity helium as the carrier gas (flow rate: 1 mL/min). The solvent delay was 5.5 minutes. The temperature program was: 60°C for 0.5 minutes, ramp to 310°C at 8°C/min, and hold for 6 minutes. Raw data were analyzed using a MassHunter workstation Quantitative Analyzer (Agilent Technologies). Metabolites were identified by searching the NIST (2017), Fiehn (2013), and MS-DIAL (2021) databases. Metabolic pathways were annotated using the KEGG database (https://www.kegg.jp/kegg/pathway.html). 16S rRNA Sequencing 16S rRNA sequencing was performed by Shanghai Majorbio Bio-Pharm Technology Co., Ltd. Genomic DNA was extracted from terminal ileum contents, with integrity verified by agarose gel electrophoresis and purity/concentration determined by a Nanodrop ND-2000 (Thermo Fisher Scientific). The V3-V4 region of the 16S rRNA gene was amplified using primers 338F (5′-ACCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′). PCR products were quantified using a QuantiFluor™ - ST blue fluorescence quantification system (Promega, Madison, WI, USA). Libraries were constructed using a NEXTFLEX Rapid DNA-Seq Kit (Bioo Scientific, Austin, TX, USA) and sequenced on an Illumina MiSeq platform (PE 300; Illumina) using a MiSeq Reagent Kit v3 (Illumina). PPARα Gene Knockdown in Caco-2 Cells PPARα-siRNA (forward: 5′-GGAGCAUUGAACAUCGAAUTT-3′; reverse: 5′-AUUCGAUGUUCAAUGCUCCTT-3′) and non-targeting siRNA (NT; forward: 5′-UUCUCCGAACGUGUCACGUTT-3′; reverse: 5′-ACGUGACACGUUCGGAGAATT-3′) were synthesized by Sangon Biotech. siRNA was transfected into Caco-2 cells using RNATransMate (Sangon Biotech). Transfection efficiency was verified by RT-qPCR. Cells were induced with OA and DA for 12 hours, and gene expression was detected. Oil Red O Staining of Caco-2 Cells Caco-2 cells were divided into 9 groups: control, OA (500 μM), OA + DA (500 μM OA + 100 μM DA), PPARα-KO, PPARα-KO + OA, PPARα-KO + OA + DA, NT, NT + OA, NT + OA + DA. After 12 hours of incubation, cells were fixed in 4% paraformaldehyde or 10% formaldehyde for 10 minutes, washed with PBS, and stained with Oil Red O working solution (Beyotime Biotechnology) for 10-20 minutes. After washing, cells were stained with hematoxylin for 5-10 minutes and rinsed with tap water. Images were captured using a DSZ2000X microscope (Opal, Shanghai, China). Bacterial Whole-Genome Sequencing S. xylosus cells were centrifuged, snap-frozen in liquid nitrogen, and sent to Shanghai Majorbio Bio-Pharm Technology Co., Ltd. for whole-genome sequencing. Genomic DNA was extracted using a Wizard® Genomic DNA Purification Kit (Promega). Sequencing was performed using a combination of PacBio RS II Single Molecule Real-Time (SMRT) sequencing and Illumina sequencing. Genomic DNA was fragmented to ~400 bp using a Covaris instrument (Covaris, Woburn, MA, USA). Libraries were constructed using a NEXTflexTMRapid DNA-Seq Kit (Bioo Scientific) and sequenced on an Illumina HiSeq X Ten/NovaSeq 600 instrument (Illumina) (2×150 bp paired-end reads). Data from PacBio RS II and Illumina platforms were analyzed bioinformatically. ACOT Enzyme Overexpression and Specificity Analysis Plasmids were constructed by Sangon Biotech. S. xylosus ACOT1312 and ACOT2244 genes, and E. coli str. K-12 substr. MG1655 TesA945127 gene (Gene ID: 945127) were cloned into the pET-28a (+) vector, with E. coli BL21 (DE3) as the expression host. Plasmids were extracted from E. coli Top10 and verified by restriction enzyme digestion. Recombinant E. coli BL21 was cultured at 37°C to OD₆₀₀ = 0.6-0.8, then induced with 0.5 mM IPTG at 30°C for 6 hours. Cells were centrifuged (4000 × g, 20 minutes), washed twice, and sonicated to obtain crude enzyme extracts. Protein concentration was determined using a BCA kit (Beyotime Biotechnology). SDS-PAGE was performed to verify protein expression. Enzyme activity was measured using a 90 μL reaction system containing Solution B (50 mM phosphate buffer [pH 7.6], 0.1 M NaCl, 10% DMSO) and 100 μM acyl-pNP substrates (C2-, C4-, C8-, C10-, C12-, C14-, C16-, C18-pNP). 10 μL of crude enzyme extract (equal protein concentration) was added, and the reaction was incubated at 37°C for 10 minutes. OD₄₀₅ values were measured using a SYNERGY HITX multi-mode reader (BioTek). Hypoxia Staining and Imaging Mice were intraperitoneally injected with 100 mg/kg pimozole (PMDZ) HCl (Hypoxyprobe) in PBS 30-90 minutes before sacrifice 35,42 . Staining was performed using a Hypoxyprobe Kit. Paraffin-embedded sections were dewaxed with xylene (2×10 minutes) and rehydrated with gradient ethanol (3 minutes each). Sections were treated with TE buffer containing 20 mg/mL proteinase K at 37°C for 15 minutes, blocked with serum for 1 hour, and incubated with mouse IgG1 anti-PMDZ monoclonal antibody (Hypoxyprobe) overnight at 4°C. Sections were stained with cyanine3-labeled goat anti-mouse IgG (Jackson ImmunoResearch, West Grove, PA, USA) for 90 minutes at room temperature. Sections were washed with PBS (3×5 minutes) between steps, mounted with Shantung Immunopatch (Thermo Scientific), and imaged using a fluorescence microscope (CX41; Guangzhou Mingmei Optoelectronics Technology Co., Ltd.). Images were numbered randomly in a blinded manner. Bacterial Culture and AVN B Antibacterial Assay S. xylosus (BNCC337469) and L. reuteri (BNCC192190) were purchased from BNCC (Henan, China); E. coli str. K-12 substr. MG1655 (ATCC 700926) from Beijing Baiou Bowei Biotechnology Co., Ltd. (Beijing, China); L. johnsonii (SHBCC D0568 = AS1.3221) from the Shanghai Bioresource Collection Center (Shanghai, China). Bacteria were cultured in LB or MRS medium (Sangon Biotech) at 37°C in a 5% CO₂ anaerobic workstation (LAI-D2; Shanghai Longyue Instrument & Equipment Co., Ltd., Shanghai, China). L. reuteri , L. johnsonii , S. xylosus , and E. coli were inoculated into 96-well plates containing MRS or LB medium with different AVN B concentrations (0, 0.5, 1, 1.5, 2, 2.5, 5 mg/mL) and cultured at 37°C for 24 hours. OD₆₀₀ values were measured every 4 hours. Bacterial solutions were diluted, spread on solid medium, cultured at 37°C for 48 hours, and colony-forming units (CFUs) were counted. In Vitro Fermentation and GC-MS-Based DA Quantification Medium was prepared by suspending an HFD in PBS, followed by shearing and homogenization 6 . After two rounds of activation, S. xylosus was inoculated into sterilized medium, anaerobically fermented for 48 hours, and centrifuged. Supernatants were collected, pretreated, and derivatized. Analysis was performed using an Agilent 6890A-5975C GC-MS system (Agilent Technologies) with a CP-Sil 88 column (100 m × 0.25 mm × 0.25 μm; Agilent Technologies). The injection volume was 1 μL (split ratio 10:1), with high-purity helium as the carrier gas (flow rate: 1.0 mL/min). The column temperature program was: 100°C for 5.0 minutes, ramp to 240°C at 4°C/min, then ramp to 240°C at 15°C/min and hold for 15 minutes. The mass spectrometer was operated in electron ionization (EI) mode with full-scan (SCAN) detection (m/z 30-550). A MassHunter workstation (Agilent Technologies) was used for data analysis. Biological Transmission Electron Microscopy (TEM) S. xylosus and E. coli were treated with 1 mg/mL AVN B for 24 hours. Bacterial cultures (OD₆₀₀ = 0.5-0.8) were centrifuged, and pellets were washed with PBS (1-2 times). Pre-cooled 2.5% glutaraldehyde was added, and samples were stored at 4°C. After fixing with 1% osmium tetroxide for 1-2 hours, samples were dehydrated with gradient acetone (30%-50%-70%-80%-95% for 15 minutes each, then 100% for 20 minutes twice). Samples were embedded in resin (acetone:resin = 3:1 for 1 hour at 37°C; acetone:resin = 1:1 for 3 hours at 37°C; pure resin overnight at 37°C), polymerized at 60°C for 48 hours, and sectioned into 70-90 nm slices using an ultra-thin microtome. Slices were stained with uranyl acetate (8-15 minutes) and lead citrate (8-10 minutes), then imaged using a Hitachi-7800 TEM (Hitachi, Tokyo, Japan). Prokaryotic Transcriptome Analysis S. xylosus samples (control: no AVN B; treatment: 1 mg/mL AVN B) were sent to Shanghai Majorbio Bio-Pharm Technology Co., Ltd. for transcriptome analysis. Total RNA was extracted, and libraries were constructed using a TruSeqTM Stranded Total RNA Library Prep Kit (Illumina). dUTP was used instead of dTTP to synthesize the second cDNA strand, which was digested with UNG enzyme before PCR amplification. Sequencing was performed on a NovaSeqXPlus platform (Illumina). Raw counts were normalized using the TMM method. Differential expression analysis was performed using the DEGseq software package, with thresholds of P < 0.05 and |log₂FC| ≥ 1. Statistical Analysis Gut microbiota, bacterial whole-genome, mouse ileum transcriptome, prokaryotic transcriptome, and untargeted metabolomics data were analyzed using the Majorbio Cloud Platform (cloud.majorbio.com). Data are presented as mean ± standard deviation (SD) or mean ± standard error of the mean (SEM). Multiple comparisons were performed using one-way analysis of variance (ANOVA) with Tukey’s post hoc test or two-tailed Student’s t-test. Correlation analysis was performed using the Mantel test and Pearson correlation. Statistical analysis was conducted using SPSS software (v27.0; IBM, Armonk, NY, USA) and GraphPad Prism 10.0 (GraphPad Software, San Diego, CA, USA). P < 0.05 was considered statistically significant (*p < 0.05, **p < 0.01, ***p < 0.001). Declarations Data Availability The original RNA-seq dataset and differential expression analysis of the terminal ileum in Model 1 have been deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) under accession ID SRP604155. The 16S rRNA datasets for Models 1 and 6 are available under SRP567486 and SRP567504, respectively. The bacterial whole-genome sequencing dataset is available under SRP567515. The prokaryotic transcriptome dataset is available under SRP567545. All other data are provided in the main text, extended data, or supplementary materials. Acknowledgments We are grateful to the Center for Instrumental Analysis, University of Shanghai for Science and Technology for the facilities, and the scientific and technical assistance. This work was supported by the National Natural Science Foundation of China (32202054), the Program of Shanghai Academic/Technology Research Leader (23XD1430500), and the National Key Research and Development Program of China (2022YFF1100102). Author Contributions Yongyong Liu and Kai Huang contributed equally to this work. Yongyong Liu, Kai Huang, Juan Chen, Fazheng Ren and Xiao Guan designed the experiments. Yongyong Liu and Kai Huang performed the experiments and generated the figures and extended data figures. Yu Zhang, Sen Li, Jing Liu, and Hongdong Song conducted the literature review and assisted with the data analysis. Ying Zhang and Hongwei Cao guided the biological analyses. Yongyong Liu drafted the manuscript. Kai Huang and Juan Chen revised and edited the manuscript. 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Alistipes indistinctus-derived hippuric acid promotes intestinal urate excretion to alleviate hyperuricemia. Cell Host Microbe 32 , 366-381.e9 (2024). Additional Declarations There is NO Competing Interest. Supplementary Files Graphicalabstract.docx Graphical abstract Highlights.docx Highlights ExtendedDataTables.docx Extended Data Tables Rawdata.xlsx Rawdata Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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abstract","description":"","filename":"Graphicalabstract.docx","url":"https://assets-eu.researchsquare.com/files/rs-7956394/v1/8dd69a8bd6930100f662ffb1.docx"},{"id":95314873,"identity":"317bdc93-8feb-4aa9-a179-1d5c6c1f9d20","added_by":"auto","created_at":"2025-11-06 15:53:25","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":19073,"visible":true,"origin":"","legend":"Highlights","description":"","filename":"Highlights.docx","url":"https://assets-eu.researchsquare.com/files/rs-7956394/v1/15539cb7449e1040c4a44317.docx"},{"id":95314517,"identity":"54381098-c646-4e8c-89fc-54ed1fff5269","added_by":"auto","created_at":"2025-11-06 15:52:58","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":19729,"visible":true,"origin":"","legend":"Extended Data Tables","description":"","filename":"ExtendedDataTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-7956394/v1/0d755da75af055b7315b2665.docx"},{"id":95314723,"identity":"49cd8856-7c58-4a2a-8df3-6508cefb0a81","added_by":"auto","created_at":"2025-11-06 15:53:15","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":140049,"visible":true,"origin":"","legend":"Rawdata","description":"","filename":"Rawdata.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7956394/v1/c453d0ab345a02b0efdb0683.xlsx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Inhibition of oxygen-mediated opportunistic bacteria overgrowth in the ileum alleviates excessive fatty acid absorption against a high-fat diet","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eDietary fat serves as a primary energy source for the human body. The recommended dietary fat intake ranges from 20% to 35% of total daily energy consumption. However, in Western diets, fat contributes 40% to 55% of daily caloric intake\u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Over 95% of ingested lipids are triglycerides, which are formed by the esterification of glycerol with long-chain fatty acids (containing 16 or 18 carbon atoms)\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. These triglycerides are hydrolyzed into fatty acids in the small intestine by the combined action of bile salts and pancreatic enzymes\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Fatty acid absorption by intestinal epithelial cells primarily occurs \u003cem\u003evia\u003c/em\u003e simple diffusion, and transmembrane proteins such as CD36 and fatty acid transporter 4 (FATP-4) have been shown to facilitate this process\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Once absorbed, free fatty acids are either oxidized for energy production or re-esterified into triglycerides, which are then transported \u003cem\u003evia\u003c/em\u003e the systemic circulation to extravascular tissues (e.g., liver and adipose tissue) for storage\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Excessive fat absorption and storage contribute to obesity, which significantly increases the risk of type 2 diabetes, non-alcoholic fatty liver disease, cardiovascular disorders, and various cancers\u003csup\u003e\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eA high-fat diet (HFD) can rapidly and continuously alter the human gut microbiota within 24\u0026ndash;48 hours, thereby profoundly affecting dietary fat absorption\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Germ-free (GF) mice are resistant to diet-induced obesity and impaired fat absorption, and similar results have been also observed in the antibiotic-treated pseudo-sterile mice\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Historically, most studies have focused on cecal or fecal microbiota, with relatively little attention paid to the small intestinal microbiota\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. However, recent evidence suggests that the small intestinal microbiota plays a critical role in lipid absorption\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The composition and abundance of small intestinal microbiota are shaped by environmental factors such as pH, oxygen levels, bile acids, and antimicrobial peptides, which differs from the large intestinal microbiota\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. The microbial load in the small intestine (approximately 10\u0026sup3;-10⁷ cells per gram of tissue) is much lower than that in the large intestine (\u0026asymp;\u0026thinsp;10\u0026sup1;\u0026sup2; cells per gram)\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. At the phylum level, Firmicutes and Proteobacteria dominate the small intestine, whereas Firmicutes and Bacteroidetes are the major phyla in the large intestine\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Significant differences also exist at the specific level: \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eVeillonella\u003c/em\u003e, \u003cem\u003eEnterococcus\u003c/em\u003e, and \u003cem\u003eClostridium\u003c/em\u003e are predominant in the small intestine, while \u003cem\u003eLachnospiraceae\u003c/em\u003e, \u003cem\u003eRuminococcaceae\u003c/em\u003e, \u003cem\u003eBacteroidaceae\u003c/em\u003e, and \u003cem\u003ePrevotellaceae\u003c/em\u003e are the main families in the large intestine\u003csup\u003e\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. The gut microbiota modulates host fat absorption through its metabolites, including short-chain fatty acids, lactic acid, and bile acids\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. However, individual variations in HFD-induced intestinal flora dysbiosis pose a challenge for targeted regulation, which remains a key limitation in current research.\u003c/p\u003e\u003cp\u003eTypically, most fatty acids derived from triglyceride hydrolysis are absorbed in the proximal and middle jejunum, with only a small fraction reaching the distal small intestine\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Nevertheless, studies have shown that HFD-associated excessive fat absorption is linked to abnormal fatty acid uptake in the ileum\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. The composition of the microbiota varies across different segments of the small intestine, with microbial loads estimated to range from 10\u003csup\u003e3\u003c/sup\u003e to 10\u003csup\u003e8\u003c/sup\u003e CFU/ml in the distal ileum, which serves as a transitional zone between the sparse aerobic flora of the jejunum and the dense strict anaerobes of the colon\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Recent studies have demonstrated that an HFD can induce intestinal oxygen leakage, disrupting the ecological balance between aerobic bacteria (e.g., \u003cem\u003eEscherichia coli\u003c/em\u003e, \u003cem\u003eStaphylococcus\u003c/em\u003e spp.) and anaerobic bacteria (e.g., \u003cem\u003eBacteroides\u003c/em\u003e, \u003cem\u003eLactobacillus\u003c/em\u003e spp.) in the ileum and leading to microbiota dysbiosis\u003csup\u003e\u003cspan additionalcitationids=\"CR35 CR36 CR37\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. However, the intrinsic mechanism by which ileal microbiota drives excessive fatty acid absorption remains unclear.\u003c/p\u003e\u003cp\u003eIn this study, we investigated how ileal microbes and their metabolites regulate intestinal lipid absorption and contribute to obesity. We found that HFD induced epithelial oxygenation in the small intestine, leading to the oxygen-mediated opportunistic bacteria (\u003cem\u003eS. xylosus\u003c/em\u003e) overgrowth. \u003cem\u003eS. xylosus\u003c/em\u003e specifically produced DA by mediating its ACOT activity, which in turn activated intestinal PPARα-CD36 signaling, thereby enhancing the excessive fatty acid absorption in ileum. Furthermore, oat avenanthramides (AVNs), as the potent plant-derived antioxidants, have been shown to significantly reduce the incidence of obesity in clinical trials\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. We found that the intake of AVN B inhibited the colonization of \u003cem\u003eS. xylosus\u003c/em\u003e, consequently preventing weight gain. This study offers a novel perspective on mitigating obesity and metabolic disorders through dietary interventions on a global scale.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cb\u003eHFD induced excessive lipid absorption linked to\u003c/b\u003e \u003cb\u003eS. xylosus\u003c/b\u003e \u003cb\u003eovergrowth\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo investigate the effects of different diets and oat AVNs on intestinal lipid absorption, we established an HFD-induced mouse obesity model with various dietary treatments and AVN B intervention (Fig.\u0026nbsp;1a). After 10 weeks, compared with the control and AVN B groups, the HFD group exhibited significantly increased body weight, fat mass index, liver and epididymal fat weights, and serum and hepatic levels of total cholesterol (TC), triglycerides (TG), and low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) levels were significantly decreased (Fig.\u0026nbsp;1b, d, e; Extended Data Fig.\u0026nbsp;1a-c, h-j, k-m). Histopathological analysis of epididymal fat and liver tissues revealed larger epididymal adipocytes, massive lipid accumulation in hepatocytes, and severe liver tissue damage in the HFD group (Extended Data Fig.\u0026nbsp;1f, g). Despite similar energy intake, there were no significant differences in fecal TC and TG levels between the HFD and control groups (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig.\u0026nbsp;1c; Extended Data Fig.\u0026nbsp;1n, o). In contrast, the AVN B group showed increased fecal TG excretion, suggesting that the HFD group may have enhanced lipid absorption capacity. We further measured small intestine length and intestinal villus length (Fig.\u0026nbsp;1f, g; Extended Data Fig.\u0026nbsp;1d, e). Mice in the HFD group had longer small intestines and intestinal villi than those in the control and AVN B groups. Oil Red O staining revealed greater lipid accumulation in intestinal epithelial cells of the HFD group (Fig.\u0026nbsp;1h). A lipid tolerance test (after 12 hours of fasting) showed that within 4 hours of ingesting the same lipid dose, the HFD group had higher serum TG levels and a larger lipid tolerance area under the curve (AUC) than the control and AVN B groups (Fig.\u0026nbsp;1i, j). These results indicate that an HFD promotes intestinal villus elongation, thereby enhancing lipid absorption and contributing to obesity. Additionally, we hypothesized that HFD increases lipid delivery to the distal small intestine, leading to excessive absorption.\u003c/p\u003e\u003cp\u003e16S rRNA sequencing analysis revealed significant differences in gut microbial composition among the treatment groups (Fig.\u0026nbsp;1l-q; Extended Data Fig.\u0026nbsp;1p, q). The abundance of \u003cem\u003eS. xylosus\u003c/em\u003e was significantly higher in the HFD group than in the control and AVN B groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), whereas AVN B increased the abundance of \u003cem\u003eLactobacillus reuteri\u003c/em\u003e and \u003cem\u003eLactobacillus johnsonii\u003c/em\u003e. Correlation analysis showed a strong positive correlation between gut \u003cem\u003eS. xylosus\u003c/em\u003e abundance and mouse lipid tolerance (AUC) (r\u0026thinsp;=\u0026thinsp;0.7884, p\u0026thinsp;=\u0026thinsp;0.0133) (Fig.\u0026nbsp;1r). Furthermore, analysis of the GMrepo database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gmrepo.humangut.info\u003c/span\u003e\u003cspan address=\"https://gmrepo.humangut.info\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) revealed that fecal \u003cem\u003eS. xylosus\u003c/em\u003e abundance was significantly higher in obese individuals than in healthy controls (p\u0026thinsp;=\u0026thinsp;0.0279), which is consistent with our mouse experimental results (Fig.\u0026nbsp;1s).\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eHFD activated the ileal PPARα-CD36 Signaling\u003c/h2\u003e\u003cp\u003eTo explore the mechanism by which an HFD enhances lipid absorption, we performed transcriptomic analysis of mouse ileum tissue. The results showed that the PPARα-CD36 signaling pathway was activated in the HFD group (Fig.\u0026nbsp;2a-e). To validate this finding, we used immunofluorescence (IF) to detect PPARα signaling in different segments of the small intestine (duodenum, jejunum, and ileum) (Fig.\u0026nbsp;2f-i). PPARα expression in the ileum of the HFD group was significantly higher than that in the control and AVN B groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with a more pronounced difference than in the duodenum and jejunum (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). RT-qPCR analysis confirmed the reliability of the transcriptomic results (Fig.\u0026nbsp;2j). Compared with the control and AVN B groups, the HFD group showed upregulated expression of \u003cem\u003ePparα\u003c/em\u003e, \u003cem\u003eCd36\u003c/em\u003e, \u003cem\u003eSrebp1c\u003c/em\u003e, \u003cem\u003eRxr\u003c/em\u003e, \u003cem\u003eCpt1\u003c/em\u003e, and \u003cem\u003eHmgcs2\u003c/em\u003e in the ileum. Notably, \u003cem\u003eFatp4\u003c/em\u003e was not activated in the HFD group but was upregulated in the AVN B group relative to the control group (Fig.\u0026nbsp;2e, j). IF staining also revealed significantly higher ileal CD36 expression in the HFD group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;2k, l). Additionally, HMGCS2, a downstream target of PPARα signaling, was activated in the HFD group, potentially contributing to intestinal villus elongation (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Extended Data Fig.\u0026nbsp;1r, s). These results suggest that HFD enhances lipid absorption by activating intestinal PPARα signaling and regulating CD36 expression, rather than by upregulating FATP4 (Fig.\u0026nbsp;2m).\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe relationship between\u003c/b\u003e \u003cb\u003eS. xylosus\u003c/b\u003e \u003cb\u003eovergrowth and PPARα-CD36 Signaling\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo identify metabolites regulating small intestinal lipid absorption, we performed untargeted metabolomics analysis. The HFD group showed significantly elevated DA levels (Fig.\u0026nbsp;3a-c), which was supported by increased expression of the medium- and long-chain fatty acid receptor FFAR4 in this group (Extended Data Fig.\u0026nbsp;1t). In contrast, the AVN B group had significantly higher intestinal lactic acid levels, consistent with the increased abundance of \u003cem\u003eL. reuteri\u003c/em\u003e and \u003cem\u003eL. johnsonii\u003c/em\u003e (Extended Data Fig.\u0026nbsp;1p, q). Correlation analysis revealed a significant positive correlation between \u003cem\u003eS. xylosus\u003c/em\u003e abundance and intestinal DA levels, as well as between \u003cem\u003eL. reuteri\u003c/em\u003e abundance and intestinal lactic acid levels (Fig.\u0026nbsp;3d, e). Network analysis further confirmed the association between \u003cem\u003eStaphylococcus\u003c/em\u003e and DA (Fig.\u0026nbsp;3f). Heatmap analysis showed strong positive correlations between \u003cem\u003eS. xylosus\u003c/em\u003e abundance and the expression of \u003cem\u003ePparα\u003c/em\u003e (r\u0026thinsp;=\u0026thinsp;0.8441, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and \u003cem\u003eCd36\u003c/em\u003e (r\u0026thinsp;=\u0026thinsp;0.8584, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;3g). Notably, DA was not detected in either normal or high-fat diets, suggesting that HFD intake creates a favorable environment for \u003cem\u003eS. xylosus\u003c/em\u003e proliferation, and the resulting microbe-derived DA activates intestinal PPARα signaling and upregulates CD36, thereby promoting lipid absorption in the distal small intestine (Fig.\u0026nbsp;3h).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eIleal PPARα activation promoted excessive lipid absorption\u003c/h3\u003e\n\u003cp\u003eTo verify the role of ileal PPARα signaling in intestinal lipid absorption in HFD-fed mice, we administered the PPARα agonist GW590735 and antagonist GW6471 (Fig.\u0026nbsp;3i). After 4 weeks, compared with the HFD group, supplementation with the PPARα agonist significantly increased body weight, fat mass index, epididymal fat weight, and liver weight (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;3j, k; Extended Data Fig.\u0026nbsp;2e, h). In contrast, supplementation with the PPARα antagonist and/or AVN B reversed HFD-induced weight gain (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;3j). The PPARα agonist group had the highest serum TC, TG, and LDL-C levels and the lowest HDL-C levels (Fig.\u0026nbsp;3l; Extended Data Fig.\u0026nbsp;2b-d), with corresponding histopathological changes in epididymal fat and liver (Extended Data Fig.\u0026nbsp;2e-k). Despite similar energy intake, the agonist group had lower fecal TC and TG excretion (Extended Data Fig.\u0026nbsp;2a, l, m) and longer small intestine and villus lengths (Extended Data Fig.\u0026nbsp;2o-r), indicating enhanced lipid absorption. It should be noted that the limited dosage of the agonist or antagonist does not impact hepatic PPARα signaling (Extended Data Fig.\u0026nbsp;2n). Oil Red O staining of the ileum showed the highest lipid accumulation in the agonist group, followed by the HFD group, and minimal lipid droplets were observed in the agonist\u0026thinsp;+\u0026thinsp;AVN B, antagonist, and antagonist\u0026thinsp;+\u0026thinsp;AVN B groups (Fig.\u0026nbsp;3n). Within 4 hours of ingesting the same lipid dose, the agonist group had the highest serum TG levels and a larger lipid tolerance AUC than the HFD group (Fig.\u0026nbsp;3o, p). RT-qPCR and IF analysis confirmed significantly higher ileal PPARα and CD36 expression in the agonist group than in the HFD group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;3q-u; Extended Data Fig.\u0026nbsp;2s). These results further suggest that the activation of ileal Pparα favors lipid absorption by intestinal epithelial cells.\u003c/p\u003e\n\u003ch3\u003eMicrobe-derived DA specifically activated intestinal PPARα\u003c/h3\u003e\n\u003cp\u003eTo investigate the effect of DA on lipid absorption, we administered low and high doses of DA to HFD-fed mice \u003cem\u003evia\u003c/em\u003e gavage for 4 weeks (Fig.\u0026nbsp;4a). A low dose of DA increased body weight, epididymal fat mass, fat mass index, and serum and hepatic TC, TG, and LDL-C levels (Fig.\u0026nbsp;4b, c; Extended Data Fig.\u0026nbsp;3b-e, h-m). Both low- and high-dose DA groups had longer small intestines and intestinal villi than the HFD group (Extended Data Fig.\u0026nbsp;3o-r). RT-qPCR and IF analysis confirmed upregulated ileal PPARα and CD36 expression in both DA groups (Fig.\u0026nbsp;4f-i; Extended Data Fig.\u0026nbsp;3v). Notably, the high-dose DA group showed decreased body weight, serum and hepatic TC/TG/LDL-C levels, and fecal TC/TG excretion (Fig.\u0026nbsp;4b, c; Extended Data Fig.\u0026nbsp;3b-e, j-m, s, t). Histopathological analysis of the liver revealed well-organized hepatocytes in the high-dose DA group (similar to the control group) (Extended Data Fig.\u0026nbsp;3f, g). RT-qPCR showed activated liver PPARα and CPT1 expression in the high-dose DA group, indicating enhanced hepatic lipid metabolism (Fig.\u0026nbsp;4j; Extended Data Fig.\u0026nbsp;3n). In contrast, low-dose DA did not activate hepatic PPARα or CPT1, leading to lipid accumulation due to impaired systemic lipid metabolism. Oil Red O staining and lipid tolerance tests confirmed these findings (Fig.\u0026nbsp;4d, e; Extended Data Fig.\u0026nbsp;3u). Compared with the high-dose DA group, the low-dose group showed significant lipid accumulation in intestinal epithelial cells. At 3 hours after gavage with the same lipid dose, serum TG levels in the high-dose DA group decreased rapidly (even lower than the HFD group). The low-dose DA group had a significantly larger lipid tolerance AUC than the HFD group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), whereas the high-dose group showed no significant difference (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003eTo confirm that low-dose DA-induced weight gain is due to excessive lipid absorption, we fed mice a low-fat normal diet (11.1% fat) supplemented with low-dose DA (Fig.\u0026nbsp;4k). After 4 weeks, there were no significant differences in body weight, fat mass index, epididymal fat weight, serum TC/TG levels, or liver weight between the control and low-dose DA groups (Fig.\u0026nbsp;4l; Extended Data Fig.\u0026nbsp;4a-f). However, RT-qPCR and IF analysis showed upregulated ileal PPARα and CD36 expression in the low-dose DA group (Fig.\u0026nbsp;4o; Extended Data Fig.\u0026nbsp;4i, m, n-q), with no significant changes in liver PPARα or CD36 expression (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Extended Data Fig.\u0026nbsp;4j). The low-dose DA group also had longer small intestines and intestinal villi (Extended Data Fig.\u0026nbsp;4g, h, k, l). Within 2\u0026ndash;4 hours of lipid ingestion, the low-dose DA group had higher serum TG levels and a larger lipid tolerance AUC than the control group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;4m, n). These results indicate that low-dose DA promotes intestinal lipid absorption and weight gain, with HFD intake being a prerequisite.\u003c/p\u003e\u003cp\u003eTo verify that DA directly activates intestinal PPARα, we established a pseudo-sterile mouse model using antibiotic (ABX)-containing drinking water. Mice were gavaged with low-dose DA (1 mg/kg BW/day) or the PPARα agonist GW590735 to eliminate the influence of gut microbiota (Fig.\u0026nbsp;4p). After 6 weeks, the DA and PPARα agonist groups had higher body weights than the HFX (HFD\u0026thinsp;+\u0026thinsp;ABX) group (Fig.\u0026nbsp;4q), with corresponding changes in fat mass index, serum/liver TC/TG/HDL-C/LDL-C levels, fecal TC/TG levels, and histopathology of liver and epididymal fat (Extended Data Fig.\u0026nbsp;5a-o, r, u). Ileal histology showed longer intestinal villi in the DA and agonist groups (Extended Data Fig.\u0026nbsp;5p, q), with similar trends in small intestine length, Oil Red O staining, and fecal TC/TG levels (Extended Data Fig.\u0026nbsp;5s, t, v). RT-qPCR and IF analysis confirmed upregulated ileal PPARα and CD36 expression (at both transcriptional and translational levels) in the DA and agonist groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;4t; Extended Data Fig.\u0026nbsp;5w-bb). Additionally, the DA and agonist groups had significantly enhanced lipid tolerance (Fig.\u0026nbsp;4r, s). To determine whether AVN B directly inhibits PPARα and CD36, we co-incubated AVN B with oleic acid (OA)-induced Caco-2 cells (Fig.\u0026nbsp;4u; Extended Data Fig.\u0026nbsp;6e, f). AVN B did not significantly inhibit PPARα or CD36 expression (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). We then induced Caco-2 cells with fatty acids of different chain lengths (all supplemented with 500 \u0026micro;M OA). RT-qPCR showed that 100 \u0026micro;M caprylic acid (C8), DA (C12), myristic acid (C14), and arachidic acid (C20) significantly activated PPARα, CD36, and HMGCS2 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;4v; Extended Data Fig.\u0026nbsp;6a, b). DA exhibited the strongest activation capacity, significantly activating PPARα and CD36 even at 50 \u0026micro;M (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), which was consistent with previous findings in HepG2 cells\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. We used siRNA to knock out \u003cem\u003ePPARα\u003c/em\u003e in Caco-2 cells. Oil Red O staining and lipid droplet quantification showed that DA induced excessive lipid uptake in Caco-2 cells (compared with the OA group) (Fig.\u0026nbsp;4w; Extended Data Fig.\u0026nbsp;6c), but this effect was abolished in PPARα-knockout (PPARα-KO) cells. Intracellular TG quantification yielded similar results (Fig.\u0026nbsp;4x). RT-qPCR showed that OA significantly activated PPARα and CD36 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with further upregulation in the OA\u0026thinsp;+\u0026thinsp;DA group (Fig.\u0026nbsp;4y; Extended Data Fig.\u0026nbsp;6d). PPARα knockout significantly inhibited PPARα expression and abolished OA/DA-induced activation of PPARα and CD36 (though CD36 expression itself was not affected). These results confirm that DA enhances lipid uptake by Caco-2 cells \u003cem\u003evia\u003c/em\u003e activating PPARα signaling.\u003c/p\u003e\u003cp\u003e\u003cb\u003eHFD promoted\u003c/b\u003e \u003cb\u003eS. xylosus\u003c/b\u003e \u003cb\u003eovergrowth by increasing the bioavailability of oxygen\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo explore why \u003cem\u003eS. xylosus\u003c/em\u003e abundance is higher in obese mice, we used Hypoxyprobe to detect ileal hypoxia. The HFD group showed loss of intestinal epithelial hypoxia and a significantly lower hypoxia score than the control and AVN B groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;5a, b). Further analysis revealed significant downregulation of hypoxia-inducible factor 2α (HIF-2α) in the HFD group (Fig.\u0026nbsp;5c). Growth curve analysis showed that \u003cem\u003eS. xylosus\u003c/em\u003e proliferated rapidly under aerobic conditions but was inhibited under hypoxic conditions (Fig.\u0026nbsp;5d, e). In contrast, \u003cem\u003eL. reuteri\u003c/em\u003e exhibited stronger proliferation under anaerobic conditions (Fig.\u0026nbsp;5f, g). Previous studies have shown that intestinal inflammation increases gut permeability (\"leaky gut\"), allowing oxygen-mediated opportunistic pathogens (e.g., \u003cem\u003eE. coli\u003c/em\u003e, \u003cem\u003eSalmonella\u003c/em\u003e, \u003cem\u003eEnterococcus\u003c/em\u003e) to use oxygen as an electron acceptor, providing a metabolic advantage for growth\u003csup\u003e\u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Consistent with this result, the HFD group had significantly higher ileal levels of the inflammatory factors TNF-α and IL-6 than the control and AVN B groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Extended Data Fig.\u0026nbsp;1u, v). Additionally, the HFD group showed decreased ileal total superoxide dismutase (T-SOD) activity and increased malondialdehyde (MDA) levels (Extended Data Fig.\u0026nbsp;1w, x). These results suggest that HFD intake induces intestinal inflammation, disrupts the intestinal hypoxic environment, and increases \u003cem\u003eS. xylosus\u003c/em\u003e abundance while decreasing \u003cem\u003eL. reuteri\u003c/em\u003e abundance (Fig.\u0026nbsp;5h).\u003c/p\u003e\u003cp\u003e\u003cb\u003eS. xylosus\u003c/b\u003e \u003cb\u003eovergrowth promoted lipid absorption\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo verify the contribution of \u003cem\u003eS. xylosus\u003c/em\u003e to intestinal lipid absorption, we established a pseudo-sterile mouse model using 2 weeks of ABX-containing drinking water. Mice were then gavaged with \u003cem\u003eS. xylosus\u003c/em\u003e for 2 weeks, followed by 4 weeks of gavage with saline, \u003cem\u003eL. reuteri\u003c/em\u003e, AVN B, or 5-aminosalicylic acid (5-ASA) (Fig.\u0026nbsp;5i). At the end of the experiment, despite similar energy intake, the \u003cem\u003eS. xylosus\u003c/em\u003e-gavaged group had higher body weight than the HFX (HFD\u0026thinsp;+\u0026thinsp;ABX), \u003cem\u003eL. reuteri\u003c/em\u003e-, AVN B-, and 5-ASA-gavaged groups (Fig.\u0026nbsp;5j; Extended Data Fig.\u0026nbsp;7a). Compared with the HFX group, the \u003cem\u003eS. xylosus\u003c/em\u003e group showed increased fat mass index, epididymal fat weight, serum/hepatic TC/TG/LDL-C levels, and severe hepatic lipid accumulation; conversely, HDL-C levels and fecal TC/TG excretion were decreased (Fig.\u0026nbsp;5k; Extended Data Fig.\u0026nbsp;7b-j, m, n, q, r, u). The \u003cem\u003eL. reuteri\u003c/em\u003e-, AVN B-, and 5-ASA-gavaged groups showed the opposite trends. The \u003cem\u003eS. xylosus\u003c/em\u003e group had longer intestinal villi and small intestines, with greater lipid accumulation in intestinal epithelial cells (Extended Data Fig.\u0026nbsp;7k, l, o, p). Lipid tolerance tests showed higher serum TG levels and a larger lipid tolerance AUC in the \u003cem\u003eS. xylosus\u003c/em\u003e group within 4 hours (Fig.\u0026nbsp;5l, m). RT-qPCR and IF analysis confirmed upregulated ileal PPARα and CD36 expression in the \u003cem\u003eS. xylosus\u003c/em\u003e group, with downregulation in the \u003cem\u003eL. reuteri\u003c/em\u003e-, AVN B-, and 5-ASA-gavaged groups (Fig.\u0026nbsp;5n-q; Extended Data Fig.\u0026nbsp;7t). CPT1 expression showed a similar trend to PPARα and CD36, which was potentially related to DA oxidation in small intestinal cells. Additionally, the \u003cem\u003eS. xylosus\u003c/em\u003e group had significantly lower ileal HIF-1α expression than the \u003cem\u003eL. reuteri\u003c/em\u003e-, AVN B-, and 5-ASA-gavaged groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;5s). Hypoxyprobe staining showed lower ileal hypoxia scores in the HFX and \u003cem\u003eS. xylosus\u003c/em\u003e-gavaged groups (Fig.\u0026nbsp;5o, r). The \u003cem\u003eS. xylosus\u003c/em\u003e group also had higher ileal TNF-α and IL-6 levels than the other groups (Extended Data Fig.\u0026nbsp;7x, y).\u003c/p\u003e\u003cp\u003e16S rRNA sequencing of ileal contents confirmed \u003cem\u003eS. xylosus\u003c/em\u003e colonization (Fig.\u0026nbsp;5t-v; Extended Data Fig.\u0026nbsp;7v, w). The \u003cem\u003eS. xylosus\u003c/em\u003e- and \u003cem\u003eL. reuteri\u003c/em\u003e-gavaged groups had the fewest unique operational taxonomic units (OTUs; 14, 7.45%), indicating that these bacteria influence the colonization of other intestinal microbes. The AVN B and 5-ASA groups had the most unique OTUs (28, 12.12%)-possibly due to AVN B\u0026rsquo;s strong free radical scavenging activity and 5-ASA-induced reduction in intestinal oxygen tension. At the species level, the \u003cem\u003eS. xylosus\u003c/em\u003e group had significantly higher \u003cem\u003eS. xylosus\u003c/em\u003e abundance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and lower \u003cem\u003eL. reuteri\u003c/em\u003e abundance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) than the other groups. The HFX group also had higher \u003cem\u003eS. xylosus\u003c/em\u003e abundance and lower \u003cem\u003eL. reuteri\u003c/em\u003e abundance than the \u003cem\u003eL. reuteri\u003c/em\u003e-, AVN B-, and 5-ASA-gavaged groups. These results confirm that intestinal \u003cem\u003eS. xylosus\u003c/em\u003e enhances lipid absorption by activating PPARα, which is likely \u003cem\u003evia\u003c/em\u003e rapid proliferation following the loss of intestinal hypoxia.\u003c/p\u003e\u003cp\u003e\u003cb\u003eS. xylosus\u003c/b\u003e \u003cb\u003especifically produced the metabolite of DA\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo determine whether \u003cem\u003eS. xylosus\u003c/em\u003e produces DA, we performed whole-genome sequencing of \u003cem\u003eS. xylosus\u003c/em\u003e (Fig.\u0026nbsp;6a). The genome contains genes encoding key fatty acid synthesis enzymes: acetyl-CoA carboxylase (ACC), FabD, FabH, FabF, FabG, FabA, FabZ, FabI, and ACOT (which is responsible for fatty acid chain elongation and acyl-CoA hydrolysis), respectively (Fig.\u0026nbsp;6c). We conducted \u003cem\u003ein vitro\u003c/em\u003e fermentation of \u003cem\u003eS. xylosus\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e str. K-12 substr. MG1655 for 48 hours, with metabolite quantification by gas chromatography-mass spectrometry (GC-MS) (Fig.\u0026nbsp;6b). \u003cem\u003eS. xylosus\u003c/em\u003e specifically produced DA under aerobic conditions (Fig.\u0026nbsp;6d), with no significant production under anaerobic conditions (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). \u003cem\u003eE. coli\u003c/em\u003e showed stronger DA production under aerobic conditions than \u003cem\u003eS. xylosus\u003c/em\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 vs. p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Under anaerobic conditions, \u003cem\u003eL. reuteri\u003c/em\u003e did not produce DA (Extended Data Fig.\u0026nbsp;8a). Using acyl-p-nitrophenyl (acyl-pNP) esters of different chain lengths as substrates, we tested the hydrolytic activity of \u003cem\u003eS. xylosus\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e (Fig.\u0026nbsp;6e). Both bacteria showed substrate selectivity for C12-pNP, indicating that their ACOT enzymes specifically hydrolyze dodecanoyl-CoA. We cloned the \u003cem\u003eS. xylosus\u003c/em\u003e ACOT genes (\u003cem\u003eACOT1312\u003c/em\u003e and \u003cem\u003eACOT2244\u003c/em\u003e) and the \u003cem\u003eE. coli TesA\u003c/em\u003e gene (\u003cem\u003eTesA945127\u003c/em\u003e) into the recombinant plasmid pET-28a (+), with verification of recombinant genes and proteins (Fig.\u0026nbsp;6f, g; Extended Data Fig.\u0026nbsp;8b). The \u003cem\u003eS. xylosus\u003c/em\u003e ACOT2244 enzyme exhibited the highest substrate selectivity for C12-pNP (Fig.\u0026nbsp;6h, i).\u003c/p\u003e\u003cp\u003e\u003cb\u003eOat AVN B inhibits\u003c/b\u003e \u003cb\u003eS. xylosus\u003c/b\u003e \u003cb\u003ecolonization by disrupting oxidative phosphorylation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo investigate how AVN B inhibits HFD-induced obesity, we assessed its effect on \u003cem\u003eS. xylosus\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e growth \u003cem\u003ein vitro\u003c/em\u003e (Fig.\u0026nbsp;6j-l; Extended Data Fig.\u0026nbsp;8c-f). Bacterial growth curves and plate colony counting showed that AVN B significantly inhibited \u003cem\u003eS. xylosus\u003c/em\u003e proliferation in a dose-dependent manner (half-maximal inhibitory concentration [IC₅₀]\u0026thinsp;=\u0026thinsp;2.616 mg/mL), with similar effects on \u003cem\u003eE. coli\u003c/em\u003e (IC₅₀ = 1.483 mg/mL) (Extended Data Fig.\u0026nbsp;8c-e). Transmission electron microscopy (TEM) revealed that \u003cem\u003eS. xylosus\u003c/em\u003e cells without AVN B treatment were intact, with clear cell boundaries, intact cell walls/membranes, and normal intracellular contents (Fig.\u0026nbsp;6m). After 12 hours of treatment with 1 mg/mL AVN B, \u003cem\u003eS. xylosus\u003c/em\u003e cells showed cell wall loss, disrupted cell contours, cytoplasmic vacuolization, and intracellular damage. Transcriptomic analysis of AVN B-treated \u003cem\u003eS. xylosus\u003c/em\u003e (KEGG pathway enrichment) showed that AVN B affected oxidative phosphorylation and downregulated the related genes, such as \u003cem\u003eqoxA\u003c/em\u003e, \u003cem\u003eqoxB\u003c/em\u003e, \u003cem\u003eqoxC\u003c/em\u003e, \u003cem\u003eqoxD\u003c/em\u003e, \u003cem\u003esdhA\u003c/em\u003e, and \u003cem\u003eatpE\u003c/em\u003e (Fig.\u0026nbsp;6n, o). These genes encode terminal oxidases of the bacterial respiratory chain, which are critical for energy metabolism and electron transport. Notably, \u003cem\u003ein vitro\u003c/em\u003e tests showed that AVN B (0.5-5 mg/mL) did not inhibit the growth of \u003cem\u003eL. reuteri\u003c/em\u003e or \u003cem\u003eL. johnsonii\u003c/em\u003e (Extended Data Fig.\u0026nbsp;8g, h).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003ePrevious studies have demonstrated that small intestinal microbes, such as \u003cem\u003eFaecalibaculum rodentium\u003c/em\u003e, play a significant role in fat overabsorption\u003csup\u003e16,38,45\u003c/sup\u003e.\u0026nbsp;GF mice conventionalized with HFD-induced small intestinal microbiota exhibit increased fat absorption even when fed a low-fat diet\u003csup\u003e16\u003c/sup\u003e. In this study, based on 16S rRNA sequencing analysis, we show for the first time that an HFD leads to the proliferation of \u003cem\u003eS. xylosus\u003c/em\u003e in the ileum of mice, with a similar trend observed in human data. Notably, AVNB significantly reduces the level of fat absorption and effectively inhibits the proliferation of \u003cem\u003eS. xylosus\u003c/em\u003e. Consequently, we utilized \u003cem\u003eS. xylosus\u003c/em\u003e as a biomarker. Consistent with our findings, a previous study indicated that obese mice are more susceptible to \u003cem\u003eStaphylococcus aureus\u0026nbsp;\u003c/em\u003einfection\u003csup\u003e36\u003c/sup\u003e. Like \u003cem\u003eEnterococcus\u003c/em\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e, and \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eStaphylococcus\u0026nbsp;\u003c/em\u003eare commensal bacteria present in the small intestine\u003csup\u003e3,46,47\u003c/sup\u003e. Unlike \u003cem\u003eS. aureus\u003c/em\u003e, \u003cem\u003eS. xylosus\u0026nbsp;\u003c/em\u003eis a rennet-negative and safe strain that is frequently utilized in the enhancement of meat flavor during processing\u003csup\u003e48,49\u003c/sup\u003e. Therefore, obese individuals may also have a higher risk of contact, exposure, and infection with \u003cem\u003eS. xylosus\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eWhen an HFD is consumed, the concentration of fatty acids in the intestinal epithelium becomes excessively elevated, leading to an overabsorption of fatty acids facilitated by the regulated intestinal epithelium\u003csup\u003e15,32\u003c/sup\u003e. Kawano et al. demonstrated that normal dietary fat is primarily absorbed in the jejunum, whereas an HFD transports fat into the ileum, resulting in overabsorption\u003csup\u003e15\u003c/sup\u003e. Through transcriptomic analysis, we discovered that HFD activates intestinal PPARα signaling. As a nuclear receptor, PPARα has been extensively studied regarding its role in lipid metabolism, yet the focus has predominantly been on the liver and adipose tissue\u003csup\u003e50-53\u003c/sup\u003e. Recent studies have indicated that intestinal PPARα signaling is crucial in regulating intestinal fat absorption\u003csup\u003e54-56\u003c/sup\u003e. Currently, two explanations exist for this phenomenon. Firstly, activation of intestinal PPARα can increase the length of the small intestine, thereby enhancing fat absorption by expanding the absorptive area\u003csup\u003e56,57\u003c/sup\u003e. The activation of intestinal HMGCS2 stimulates the Notch signaling pathway, promoting intestinal epithelial self-renewal, which further enlarges the intestinal surface area and enhances lipid absorption\u003csup\u003e58\u003c/sup\u003e.\u0026nbsp;Similar findings were observed in the present study. Secondly, the activation of intestinal PPARα signaling leads to the upregulation of downstream fatty acid transporters, such as FATP4 and CD36, which accelerates fatty acid absorption\u003csup\u003e3,59,60\u003c/sup\u003e.\u0026nbsp;In this study, we report for the first time that HFD selectively activates PPARα-CD36 signaling in the ileum, while PPARα-FATP4 signaling remains unaffected, which contrasts with previous reports\u003csup\u003e59,61\u003c/sup\u003e.\u0026nbsp;We speculate that this discrepancy may be attributed to the differing microecological conditions of the small intestine segments, as the jejunum was the focus of the prior study\u003csup\u003e59,60\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThis study focuses on how \u003cem\u003eS. xylosus\u003c/em\u003e regulates ileal PPARα. Through metabolomics and correlation analysis, we identified a significant positive correlation between DA, \u003cem\u003eS. xylosus\u003c/em\u003e, and PPARα-CD36 in the ileum. Therefore, we hypothesize that the proliferation of \u003cem\u003eS. xylosus\u003c/em\u003e activates intestinal PPARα-CD36 \u003cem\u003evia\u003c/em\u003e the DA produced, leading to excessive fat intake. To thoroughly validate this hypothesis, we conducted a series of experiments, including: 1) Utilizing PPARα agonist and antagonist, we found that activation of intestinal PPARα signaling, but not hepatic PPARα activation, significantly increased fat absorption. Conversely, inhibition of intestinal PPARα reduced fat absorption and increased fecal lipid excretion. Similar results have been validated in various model organisms. For instance, specific knockout of PPARα in the intestine significantly reduced body weight and metabolic disorders associated with obesity and non-alcoholic steatohepatitis in mice, whereas knockout of PPARα in the liver yielded the opposite effect\u003csup\u003e50,51,62-65\u003c/sup\u003e. This discrepancy underscores the complex roles of PPARα across different tissues and its essential involvement in regulating host metabolism and energy homeostasis\u003csup\u003e66,67\u003c/sup\u003e. 2) DA can effectively activate the intestinal PPARα-CD36 pathway, significantly increasing fat absorption and contributing to obesity. However, high doses of DA also activate the intestinal PPARα signaling pathway, which functions to inhibit obesity. This counterintuitive result occurs because high levels of DA, absorbed into the liver \u003cem\u003evia\u003c/em\u003e the intestine, activate hepatic PPARα signaling and accelerate β-oxidation of fatty acids. Consequently, the rate of liver fat metabolism exceeds that of intestinal absorption. Furthermore, DA, as a potent signaling molecule, was able to activate PPARα signaling in the gut at low doses, thereby enhancing fat absorption in mice that were either fed a normal diet or treated with antibiotics. Notably, PPARα knockout cells demonstrated that PPARα is a significant target of DA. Fatty acids and eicosanoids serve as strong indicators of PPARα activity; however, different fatty acids exert varying effects on PPARα activation\u003csup\u003e56,68\u003c/sup\u003e. Our findings indicate that among a range of saturated fatty acids, DA exhibits a pronounced activation effect, aligning with previous studies\u003csup\u003e41,69,70\u003c/sup\u003e. 3) Transplantation of \u003cem\u003eS. xylosus\u0026nbsp;\u003c/em\u003erevealed that its intervention significantly activates intestinal PPARα signaling and leads to excessive fat absorption. Genomic profiling indicated that \u003cem\u003eS. xylosus\u003c/em\u003e possesses a set of genes associated with \u003cem\u003ede novo\u003c/em\u003e fatty acid synthesis. Furthermore, \u003cem\u003ein vitro\u003c/em\u003e experiments demonstrated that \u003cem\u003eS. xylosus\u003c/em\u003e can efficiently synthesize DA through specific ACOT enzymes. These findings suggest that \u003cem\u003eS. xylosus\u003c/em\u003e regulates PPARα signaling by producing DA.\u003c/p\u003e\n\u003cp\u003eThe interaction between gut microbiota and the host is reciprocal\u003csup\u003e2,30\u003c/sup\u003e. Another focus of this study is to investigate why an HFD leads to the proliferation of\u0026nbsp;\u003cem\u003eS. xylosus\u003c/em\u003e.\u0026nbsp;Previous research has shown that HFD increases the oxygen concentration in the intestinal lumen\u003csup\u003e34,43,44\u003c/sup\u003e. The ileal flora resides in an intestinal segment where anaerobic and aerobic bacteria maintain a delicate balance\u003csup\u003e3\u003c/sup\u003e. Changes in oxygen concentration can disrupt this equilibrium. Given that \u003cem\u003eS. xylosus\u003c/em\u003e is an aerobic Gram-positive bacterium, we hypothesize that HFD accelerates the proliferation of\u003cem\u003e\u0026nbsp;S. xylosus\u003c/em\u003e by inducing an increase in intestinal oxygen concentration. To test this hypothesis, both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u0026nbsp;\u003c/em\u003estudies demonstrated that elevated oxygen levels effectively promote the proliferation and colonization of \u003cem\u003eS. xylosus\u003c/em\u003e, while \u003cem\u003eL. reuteri\u003c/em\u003e, serving as a control, exhibited opposite results. Furthermore, the rapid proliferation of \u003cem\u003eS. xylosus\u003c/em\u003e enhances DA synthesis. Previous studies indicate that HFD can induce intestinal inflammation and alter permeability, leading to oxygen leakage\u003csup\u003e42,43,71\u003c/sup\u003e. Additionally, DA accelerates oxygen consumption, which increases the oxygen demand in intestinal epithelial cells\u003csup\u003e72\u003c/sup\u003e. This further exacerbates the rise in oxygen concentration in the intestinal lumen through oxygen leakage, thereby promoting the proliferation of \u003cem\u003eS. xylosus\u003c/em\u003e. Moreover, we investigated a specific antioxidant active ingredient in oats, AVN B, formed from ferulic acid and 5-hydroxyanthranilic acid through an amide bond (Extended Data Fig. 10). AVN B exhibits potent antioxidant activity by degrading into dehydro-AVNs (dehydro-2f) and forming phenolic acids\u003csup\u003e39\u003c/sup\u003e. Due to their structural similarities, the antioxidant mechanisms of AVN B are analogous to those of ascorbic acid (VC), also involving the generation of dehydroascorbic acid\u003csup\u003e73\u003c/sup\u003e. The results of this study indicate that AVN B can selectively inhibit the proliferation of oxygen-opportunistic bacteria such as\u003cem\u003e\u0026nbsp;S. xylosus\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e, with an inhibitory effect comparable to that of 5-ASA\u003csup\u003e35\u003c/sup\u003e. Our findings demonstrate that oat-derived AVN B disrupts energy metabolism and electron transfer within the respiratory chain by inhibiting oxidative phosphorylation in \u003cem\u003eS. xylosus\u003c/em\u003e, which leads to bacterial damage and consequently exerts an effect on fat absorption inhibition. Furthermore, AVN B significantly enhances the abundance of \u003cem\u003eL. reuteri\u003c/em\u003e and promotes an increase in lactate levels in the gut. Previous studies have shown that elevated lactate can be converted to malonyl-CoA by intestinal epithelial cells, thereby inhibiting chylomicron secretion and reducing fat absorption. This finding is consistent with our results\u003csup\u003e1\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn summary, we employed a multipronged approach to elucidate how \u003cem\u003eS. xylosus\u003c/em\u003e induces obesity through the production of the metabolite DA. The activation of PPARα by DA promotes the expression of CD36, thereby enhancing lipid absorption in the small intestine. We established a direct link between \u003cem\u003eS. xylosus\u003c/em\u003e, DA, and the PPARα signaling pathways. Furthermore, oat AVN B reduces small intestinal lipid absorption by inhibiting the intestinal colonization of \u003cem\u003eS. xylosus\u003c/em\u003e, suggesting that dietary compounds may offer new strategies for alleviating HFD-induced obesity. In the context of overnutrition, this study contributes to a clearer understanding of the intrinsic mechanisms underlying the development of obesity and metabolic diseases associated with HFD intake. Conversely, \u003cem\u003eS. xylosus\u003c/em\u003e and DA may also be beneficial in malnourished populations, promoting more efficient fat absorption.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations of the study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlthough the present study confirmed that an HFD leads to an increase in oxygen concentration in the gut, the mechanisms by which oxygen permeates intestinal epithelial cells into the intestinal lumen remain unresolved. Previous studies have indicated that this oxygen permeability is associated with intestinal permeability, inflammation, and immunity. However, the specific mechanisms by which HFD triggers these changes are still unclear. Some research has shown that many microorganisms in the phylum Proteobacteria and the family \u003cem\u003eEnterococcus\u003c/em\u003e are facultative anaerobes, which can dominate under high oxygen conditions. Human data indicate that the abundance of \u003cem\u003eE. coli\u0026nbsp;\u003c/em\u003eis also elevated in obese individuals, and \u003cem\u003eE. coli\u0026nbsp;\u003c/em\u003ecan metabolize DA. Therefore, it remains to be determined whether the mechanism described in this study is generalizable to \u003cem\u003eE. coli\u003c/em\u003e. Additionally, while this study confirmed the inhibitory activity of AVN B against \u003cem\u003eS. xylosus\u003c/em\u003e, the specific mechanisms and targets require further elucidation.\u003c/p\u003e"},{"header":"Methods ","content":"\u003cp\u003e\u003cstrong\u003eAnimal experiments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll animal experiments were approved by the Animal Ethics Committee of Shanghai Yangpu District Shidong Hospital (Ethics Approval Number: IRB-AF63-V1.0) and conducted in accordance with the Guidelines for the Care and Use of Laboratory Animals of the People\u0026rsquo;s Republic of China. Male C57BL/6 mice (6-8 weeks old, 20 \u0026plusmn; 2 g) were purchased from Shanghai JieSiJie Laboratory Animal Co., Ltd. (Shanghai, China). Diets were purchased from Jiangsu Collaborative Pharmaceutical Bioengineering Co., Ltd. (Nanjing, China), with compositions and energy densities listed in Extended Data Table 1. Mice were housed in a standard laboratory animal facility (50 \u0026plusmn; 15% humidity, 20 \u0026plusmn; 5\u0026deg;C) with a 12-hour light/dark cycle. After a 2-week acclimatization period with ad libitum feeding, experiments were initiated.\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003e\u003cstrong\u003eModel 1\u003c/strong\u003e: 18 mice were randomly divided into 3 groups (n = 6/group). The control group received a normal diet; the HFD and AVN B groups received a 60% HFD. The AVN B group was gavaged with 100 mg/kg BW/day AVN B; the control and HFD groups received an equal volume of normal saline. Mice were sacrificed after 10 weeks of intervention.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eModel 2\u003c/strong\u003e: 30 mice were randomly divided into 5 groups (n = 6/group), all fed a 60% HFD. The HFD group was gavaged with 1% DMSO in normal saline; the ACT group with 0.3 mg/kg/day GW590735; the AAB group with 0.3 mg/kg/day GW590735 + 100 mg/kg BW/day AVN B; the INB group with 1 mg/kg BW/day GW6471; the IAB group with 1 mg/kg BW/day GW6471 + 100 mg/kg BW/day AVN B. Mice were sacrificed after 4 weeks.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eModel 3\u003c/strong\u003e: 24 mice were randomly divided into 4 groups (n = 6/group). The control group received a normal diet; the HFD, L-DA, and H-DA groups received a 60% HFD. The control and HFD groups were gavaged with 2% ethanol in normal saline; the L-DA group with 1 mg/kg BW/day DA; the H-DA group with 100 mg/kg BW/day DA. Mice were sacrificed after 4 weeks.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eModel 4\u003c/strong\u003e: 12 mice were randomly divided into 2 groups (n = 6/group), both fed a normal diet. The control group was gavaged with 2% ethanol in normal saline; the CDA group with 1 mg/kg BW/day DA. Mice were sacrificed after 4 weeks.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eModel 5\u003c/strong\u003e: 18 mice were randomly divided into 3 groups (n = 6/group), all fed a 60% HFD. Mice received ABX-containing drinking water (1 g/L ampicillin, 1 g/L neomycin sulfate, 1 g/L metronidazole, 0.5 g/L vancomycin) for 1 week before the experiment, with additional 2-day ABX treatment every week during the experiment\u003csup\u003e18\u003c/sup\u003e.\u0026nbsp;The\u0026nbsp;HFX group was gavaged with 1% DMSO\u0026nbsp;in normal saline; the DAX group with 1 mg/kg BW/day DA; the ACX group with 0.3 mg/kg/day GW590735.\u0026nbsp;Mice were sacrificed after\u0026nbsp;6 weeks.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eModel 6\u003c/strong\u003e: 30 mice were randomly divided into 5 groups (n = 6/group), all fed a 60% HFD. Mice received ABX-containing drinking water for 2 weeks before the experiment, with fecal sampling for plate coating. Except for the HFX group (gavaged with normal saline), the other groups were gavaged with 1\u0026times;10⁹ CFU \u003cem\u003eS. xylosus\u003c/em\u003e for 2 weeks. Subsequently, the HFS group continued to receive normal saline; the HSL group 1\u0026times;10⁹ CFU \u003cem\u003eL. reuteri\u003c/em\u003e; the HSB group 100 mg/kg BW/day AVN B; the ASA group 400 mg/kg BW/day 5-ASA. Intervention lasted 4 weeks, with sacrifice 1 week after gavage cessation.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eAt the end of each intervention, mice were fasted for 12 hours, and blood was collected via orbital plexus puncture. Serum was obtained by centrifugation at 4000 rpm/min. Mice were then dissected, and liver, epididymal fat, and intestinal tissues were collected and stored in liquid nitrogen or 4% paraformaldehyde.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHistopathology and Oil Red O Staining of the Terminal Ileum\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFresh liver, epididymal fat, and ileum tissues were fixed in 4% paraformaldehyde, embedded in paraffin, and sectioned. Hematoxylin-eosin (H\u0026amp;E) staining and Oil Red O staining were performed. Images were captured at 200\u0026times; magnification using a biological digital microscope (Nikon, Tokyo, Japan) by Shanghai Xindi Biotechnology Co., Ltd. (Shanghai, China).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiochemical Parameter Determination\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLiver and terminal ileum samples were homogenized according to kit instructions, and supernatants were collected by centrifugation at 4000 rpm/min (4\u0026deg;C) for analysis. Protein concentration was determined using a BCA Protein Assay Kit (Beyotime Biotechnology, Shanghai, China). Serum and hepatic TC, TG, HDL-C, and LDL-C levels, as well as fecal TC and TG levels, were measured using commercial kits (Beyotime Biotechnology) according to standard protocols. Ileal T-SOD and MDA levels were determined using kits (Beyotime Biotechnology). Ileal TNF-\u0026alpha; levels were measured using an ELISA kit (Beyotime Biotechnology). OD values were detected using a SYNERGY HITX multi-mode reader (BioTek, Winooski, VT, USA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLipid Tolerance Test\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne week before sacrifice, mice were fasted for 12 hours and gavaged with 200 \u0026mu;L soybean oil per mouse\u003csup\u003e16\u003c/sup\u003e.\u0026nbsp;Tail vein blood was collected at 0, 1, 2, 3, and 4 hours after gavage. Serum was obtained by centrifugation at 4000 rpm/min, and serum TG levels were measured using a kit (Beyotime Biotechnology). The lipid tolerance AUC was calculated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIleum RNA Sequencing Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRNA sequencing of the terminal ileum was performed by Shanghai Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China). Total RNA was extracted, and concentration/purity was assessed using a Nanodrop 2000 (Thermo Fisher Scientific, Waltham, MA, USA). RNA integrity was verified by agarose gel electrophoresis and Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Libraries were constructed, enriched, and quantified using a TBS380 (Picogreen; Thermo Fisher Scientific). Cluster generation was performed \u003cem\u003evia\u003c/em\u003e bridge PCR on a cBot (Illumina, San Diego, CA, USA), followed by sequencing on an Illumina Novaseq 6000 platform. Genes/transcripts and samples were clustered using an iterative approach.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA Extraction, Reverse Transcription, and RT-qPCR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA was extracted from liver and terminal ileum tissues using a kit (Thermo Fisher Scientific). RNA purity and concentration were determined by measuring the OD₂₆₀/OD₂₈₀ ratio using a microplate reader. RNA integrity was verified by 1% agarose gel electrophoresis\u003csup\u003e74\u003c/sup\u003e.\u0026nbsp;cDNA was synthesized using a HiScript\u0026reg; II Q RT SuperMix for qPCR (+gDNA wiper) kit (Vazyme Biotech, Nanjing, China). RT-qPCR was performed using a ChamQ Universal SYBR qPCR Master Mix kit (Vazyme Biotech) on a Thermo Lifetech ABI QuantStudio 3 instrument (Thermo Fisher Scientific). Primers were synthesized by Sangon Biotech (Shanghai, China), with sequences listed in Extended Data Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunofluorescence Staining\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFrozen ileum sections (4 \u0026mu;m) were fixed in 4% paraformaldehyde, dewaxed with xylene (20 minutes), and rehydrated with gradient ethanol (5 minutes each). Sections were heated in ethylenediaminetetraacetic acid (EDTA) buffer for 23 minutes, cooled to room temperature, and washed with PBS. After treatment with sodium borohydride solution and Sudan black dye, sections were blocked with 5% BSA for 1 hour. Primary antibodies against PPAR\u0026alpha; (Affinity Biosciences, Cincinnati, OH, USA), HMGCS2 (ABclonal, Woburn, MA, USA), and CD36 (Abcam, Cambridge, UK) were incubated overnight at 4\u0026deg;C, followed by incubation with secondary antibodies (Proteintech, Rosemont, IL, USA) for 1 hour. Sections were stained with 4\u0026prime;,6-diamidino-2-phenylindole (DAPI) and imaged at 200\u0026times; magnification using a fluorescence microscope (CX41; Guangzhou Mingmei Optoelectronics Technology Co., Ltd., Guangzhou, China). Image analysis was performed using Image J software (Media Cybernetics Inc., Rockville, MD, USA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUntargeted Metabolomics Profiling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUntargeted metabolomics of ileal contents was performed by Shanghai Majorbio Bio-Pharm Technology Co., Ltd. After sample pretreatment, metabolites were analyzed using an Agilent 8890B-5977B gas chromatography-mass spectrometry (GC-MS) system (Agilent Technologies). Separation was performed on a DB-5MS capillary column (40 m \u0026times; 0.25 mm \u0026times; 0.25 \u0026mu;m; Agilent Technologies). The inlet temperature was 260\u0026deg;C, with high-purity helium as the carrier gas (flow rate: 1 mL/min). The solvent delay was 5.5 minutes. The temperature program was: 60\u0026deg;C for 0.5 minutes, ramp to 310\u0026deg;C at 8\u0026deg;C/min, and hold for 6 minutes. Raw data were analyzed using a MassHunter workstation Quantitative Analyzer (Agilent Technologies). Metabolites were identified by searching the NIST (2017), Fiehn (2013), and MS-DIAL (2021) databases. Metabolic pathways were annotated using the KEGG database (https://www.kegg.jp/kegg/pathway.html).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e16S rRNA Sequencing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e16S rRNA sequencing was performed by Shanghai Majorbio Bio-Pharm Technology Co., Ltd. Genomic DNA was extracted from terminal ileum contents, with integrity verified by agarose gel electrophoresis and purity/concentration determined by a Nanodrop ND-2000 (Thermo Fisher Scientific). The V3-V4 region of the 16S rRNA gene was amplified using primers 338F (5\u0026prime;-ACCTACGGGAGGCAGCAG-3\u0026prime;) and 806R (5\u0026prime;-GGACTACHVGGGTWTCTAAT-3\u0026prime;). PCR products were quantified using a QuantiFluor\u0026trade; - ST blue fluorescence quantification system (Promega, Madison, WI, USA). Libraries were constructed using a NEXTFLEX Rapid DNA-Seq Kit (Bioo Scientific, Austin, TX, USA) and sequenced on an Illumina MiSeq platform (PE 300; Illumina) using a MiSeq Reagent Kit v3 (Illumina).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePPAR\u0026alpha; Gene Knockdown in Caco-2 Cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePPAR\u0026alpha;-siRNA (forward: 5\u0026prime;-GGAGCAUUGAACAUCGAAUTT-3\u0026prime;; reverse: 5\u0026prime;-AUUCGAUGUUCAAUGCUCCTT-3\u0026prime;) and non-targeting siRNA (NT; forward: 5\u0026prime;-UUCUCCGAACGUGUCACGUTT-3\u0026prime;; reverse: 5\u0026prime;-ACGUGACACGUUCGGAGAATT-3\u0026prime;) were synthesized by Sangon Biotech. siRNA was transfected into Caco-2 cells using RNATransMate (Sangon Biotech). Transfection efficiency was verified by RT-qPCR. Cells were induced with OA and DA for 12 hours, and gene expression was detected.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOil Red O Staining of Caco-2 Cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCaco-2 cells were divided into 9 groups: control, OA (500 \u0026mu;M), OA + DA (500 \u0026mu;M OA + 100 \u0026mu;M DA), PPAR\u0026alpha;-KO, PPAR\u0026alpha;-KO + OA, PPAR\u0026alpha;-KO + OA + DA, NT, NT + OA, NT + OA + DA. After 12 hours of incubation, cells were fixed in 4% paraformaldehyde or 10% formaldehyde for 10 minutes, washed with PBS, and stained with Oil Red O working solution (Beyotime Biotechnology) for 10-20 minutes. After washing, cells were stained with hematoxylin for 5-10 minutes and rinsed with tap water. Images were captured using a DSZ2000X microscope (Opal, Shanghai, China).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBacterial Whole-Genome Sequencing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eS.\u003c/em\u003e\u003cem\u003e\u0026nbsp;xylosus\u003c/em\u003e cells were centrifuged, snap-frozen in liquid nitrogen, and sent to Shanghai Majorbio Bio-Pharm Technology Co., Ltd. for whole-genome sequencing. Genomic DNA was extracted using a Wizard\u0026reg; Genomic DNA Purification Kit (Promega). Sequencing was performed using a combination of PacBio RS II Single Molecule Real-Time (SMRT) sequencing and Illumina sequencing. Genomic DNA was fragmented to ~400 bp using a Covaris instrument (Covaris, Woburn, MA, USA). Libraries were constructed using a NEXTflexTMRapid DNA-Seq Kit (Bioo Scientific) and sequenced on an Illumina HiSeq X Ten/NovaSeq 600 instrument (Illumina) (2\u0026times;150 bp paired-end reads). Data from PacBio RS II and Illumina platforms were analyzed bioinformatically.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eACOT Enzyme Overexpression and Specificity Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlasmids were constructed by Sangon Biotech. \u003cem\u003eS. xylosus\u003c/em\u003e \u003cem\u003eACOT1312\u003c/em\u003e and \u003cem\u003eACOT2244\u003c/em\u003e genes, and \u003cem\u003eE. coli\u003c/em\u003e str. K-12 substr. MG1655 \u003cem\u003eTesA945127\u003c/em\u003e gene (Gene ID: 945127) were cloned into the pET-28a (+) vector, with \u003cem\u003eE.\u0026nbsp;\u003c/em\u003e\u003cem\u003ecoli\u003c/em\u003e BL21 (DE3) as the expression host. Plasmids were extracted from \u003cem\u003eE. coli\u003c/em\u003e Top10 and verified by restriction enzyme digestion. Recombinant \u003cem\u003eE.\u0026nbsp;\u003c/em\u003e\u003cem\u003ecoli\u003c/em\u003e BL21 was cultured at 37\u0026deg;C to OD₆₀₀ = 0.6-0.8, then induced with 0.5 mM IPTG at 30\u0026deg;C for 6 hours. Cells were centrifuged (4000 \u0026times; g, 20 minutes), washed twice, and sonicated to obtain crude enzyme extracts. Protein concentration was determined using a BCA kit (Beyotime Biotechnology). SDS-PAGE was performed to verify protein expression.\u003c/p\u003e\n\u003cp\u003eEnzyme activity was measured using a 90 \u0026mu;L reaction system containing Solution B (50 mM phosphate buffer [pH 7.6], 0.1 M NaCl, 10% DMSO) and 100 \u0026mu;M acyl-pNP substrates (C2-, C4-, C8-, C10-, C12-, C14-, C16-, C18-pNP). 10 \u0026mu;L of crude enzyme extract (equal protein concentration) was added, and the reaction was incubated at 37\u0026deg;C for 10 minutes. OD₄₀₅ values were measured using a SYNERGY HITX multi-mode reader (BioTek).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypoxia Staining and Imaging\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMice were intraperitoneally injected with 100 mg/kg pimozole (PMDZ) HCl (Hypoxyprobe) in PBS 30-90 minutes before sacrifice\u003csup\u003e35,42\u003c/sup\u003e.\u0026nbsp;Staining was performed using\u0026nbsp;a Hypoxyprobe\u0026nbsp;Kit.\u0026nbsp;Paraffin-embedded\u0026nbsp;sections\u0026nbsp;were\u0026nbsp;dewaxed\u0026nbsp;with xylene (2\u0026times;10\u0026nbsp;minutes) and\u0026nbsp;rehydrated with gradient\u0026nbsp;ethanol (3\u0026nbsp;minutes\u0026nbsp;each). Sections\u0026nbsp;were treated with TE buffer containing\u0026nbsp;20 mg/mL\u0026nbsp;proteinase K\u0026nbsp;at 37\u0026deg;C\u0026nbsp;for 15\u0026nbsp;minutes, blocked with serum for 1\u0026nbsp;hour, and\u0026nbsp;incubated\u0026nbsp;with mouse IgG1 anti-PMDZ\u0026nbsp;monoclonal antibody (Hypoxyprobe) overnight at 4\u0026deg;C. Sections were stained with cyanine3-labeled goat anti-mouse IgG (Jackson ImmunoResearch, West Grove, PA, USA) for 90\u0026nbsp;minutes\u0026nbsp;at room temperature. Sections were washed\u0026nbsp;with\u0026nbsp;PBS\u0026nbsp;(3\u0026times;5 minutes)\u0026nbsp;between\u0026nbsp;steps,\u0026nbsp;mounted\u0026nbsp;with\u0026nbsp;Shantung Immunopatch (Thermo Scientific), and imaged\u0026nbsp;using a fluorescence microscope (CX41;\u0026nbsp;Guangzhou Mingmei Optoelectronics Technology Co.,\u0026nbsp;Ltd.). Images were numbered randomly in a blinded manner.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBacterial Culture and AVN B Antibacterial Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eS. xylosus\u003c/em\u003e (BNCC337469) and \u003cem\u003eL. reuteri\u003c/em\u003e (BNCC192190) were purchased from BNCC (Henan, China); \u003cem\u003eE.\u0026nbsp;\u003c/em\u003e\u003cem\u003ecoli\u003c/em\u003e str. K-12 substr. MG1655 (ATCC 700926) from Beijing\u0026nbsp;Baiou\u0026nbsp;Bowei\u0026nbsp;Biotechnology\u0026nbsp;Co.,\u0026nbsp;Ltd.\u0026nbsp;(Beijing, China);\u0026nbsp;\u003cem\u003eL. johnsonii\u003c/em\u003e (SHBCC D0568 = AS1.3221) from\u0026nbsp;the\u0026nbsp;Shanghai Bioresource Collection Center (Shanghai, China). Bacteria were cultured in LB or MRS\u0026nbsp;medium\u0026nbsp;(Sangon Biotech)\u0026nbsp;at 37\u0026deg;C\u0026nbsp;in a\u0026nbsp;5%\u0026nbsp;CO₂\u0026nbsp;anaerobic workstation (LAI-D2;\u0026nbsp;Shanghai Longyue Instrument \u0026amp; Equipment Co., Ltd., Shanghai, China).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eL. reuteri\u003c/em\u003e, \u003cem\u003eL. johnsonii\u003c/em\u003e, \u003cem\u003eS. xylosus\u003c/em\u003e, and \u003cem\u003eE. coli\u003c/em\u003e were inoculated into 96-well plates containing MRS or LB medium with different AVN B concentrations (0, 0.5, 1, 1.5, 2, 2.5, 5 mg/mL) and cultured at 37\u0026deg;C for 24 hours. OD₆₀₀ values were measured every 4 hours. Bacterial solutions were diluted, spread on solid medium, cultured at 37\u0026deg;C for 48 hours, and colony-forming units (CFUs) were counted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eIn Vitro\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Fermentation and GC-MS-Based DA Quantification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMedium was prepared by suspending an HFD in PBS, followed by shearing and homogenization\u003csup\u003e6\u003c/sup\u003e.\u0026nbsp;After\u0026nbsp;two rounds of\u0026nbsp;activation, \u003cem\u003eS. xylosus\u003c/em\u003e was inoculated into sterilized medium,\u0026nbsp;anaerobically fermented for 48 hours, and\u0026nbsp;centrifuged. Supernatants were collected, pretreated,\u0026nbsp;and derivatized. Analysis was performed using an Agilent\u0026nbsp;6890A-5975C\u0026nbsp;GC-MS system (Agilent Technologies) with a\u0026nbsp;CP-Sil 88 column\u0026nbsp;(100 m \u0026times; 0.25 mm \u0026times; 0.25 \u0026mu;m; Agilent Technologies). The\u0026nbsp;injection volume\u0026nbsp;was\u0026nbsp;1\u0026nbsp;\u0026mu;L (split ratio 10:1), with\u0026nbsp;high-purity helium\u0026nbsp;as the carrier gas (flow rate:\u0026nbsp;1.0\u0026nbsp;mL/min). The\u0026nbsp;column temperature\u0026nbsp;program\u0026nbsp;was:\u0026nbsp;100\u0026deg;C\u0026nbsp;for 5.0\u0026nbsp;minutes, ramp\u0026nbsp;to 240\u0026deg;C at\u0026nbsp;4\u0026deg;C/min, then ramp\u0026nbsp;to 240\u0026deg;C at\u0026nbsp;15\u0026deg;C/min\u0026nbsp;and hold\u0026nbsp;for 15\u0026nbsp;minutes. The mass spectrometer was operated in\u0026nbsp;electron\u0026nbsp;ionization\u0026nbsp;(EI)\u0026nbsp;mode with\u0026nbsp;full-scan (SCAN)\u0026nbsp;detection\u0026nbsp;(m/z 30-550). A MassHunter workstation (Agilent Technologies) was used for data analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiological Transmission Electron Microscopy (TEM)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eS. xylosus\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e were treated with 1 mg/mL AVN B for 24 hours. Bacterial cultures (OD₆₀₀ = 0.5-0.8) were centrifuged, and pellets were washed with PBS (1-2 times). Pre-cooled 2.5% glutaraldehyde was added, and samples were stored at 4\u0026deg;C. After fixing with 1% osmium tetroxide for 1-2 hours, samples were dehydrated with gradient acetone (30%-50%-70%-80%-95% for 15 minutes each, then 100% for 20 minutes twice). Samples were embedded in resin (acetone:resin = 3:1 for 1 hour at 37\u0026deg;C; acetone:resin = 1:1 for 3 hours at 37\u0026deg;C; pure resin overnight at 37\u0026deg;C), polymerized at 60\u0026deg;C for 48 hours, and sectioned into 70-90 nm slices using an ultra-thin microtome. Slices were stained with uranyl acetate (8-15 minutes) and lead citrate (8-10 minutes), then imaged using a Hitachi-7800 TEM (Hitachi, Tokyo, Japan).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProkaryotic Transcriptome Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eS. xylosus\u003c/em\u003e samples (control: no AVN B; treatment: 1 mg/mL AVN B) were sent to Shanghai Majorbio Bio-Pharm Technology Co., Ltd. for transcriptome analysis. Total RNA was extracted, and libraries were constructed using a TruSeqTM Stranded Total RNA Library Prep Kit (Illumina). dUTP was used instead of dTTP to synthesize the second cDNA strand, which was digested with UNG enzyme before PCR amplification. Sequencing was performed on a NovaSeqXPlus platform (Illumina). Raw counts were normalized using the TMM method. Differential expression analysis was performed using the DEGseq software package, with thresholds of P \u0026lt; 0.05 and |log₂FC| \u0026ge; 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGut microbiota, bacterial whole-genome, mouse ileum transcriptome, prokaryotic transcriptome, and untargeted metabolomics data were analyzed using the Majorbio Cloud Platform (cloud.majorbio.com). Data are presented as mean \u0026plusmn; standard deviation (SD) or mean \u0026plusmn; standard error of the mean (SEM). Multiple comparisons were performed using one-way analysis of variance (ANOVA) with Tukey\u0026rsquo;s post hoc test or two-tailed Student\u0026rsquo;s t-test. Correlation analysis was performed using the Mantel test and Pearson correlation. Statistical analysis was conducted using SPSS software (v27.0; IBM, Armonk, NY, USA) and GraphPad Prism 10.0 (GraphPad Software, San Diego, CA, USA). P \u0026lt; 0.05 was considered statistically significant (*p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe original RNA-seq dataset and differential expression analysis of the terminal ileum in Model 1 have been deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) under accession ID SRP604155. The 16S rRNA datasets for Models 1 and 6 are available under SRP567486 and SRP567504, respectively. The bacterial whole-genome sequencing dataset is available under SRP567515. The prokaryotic transcriptome dataset is available under SRP567545. All other data are provided in the main text, extended data, or supplementary materials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to the Center for Instrumental Analysis, University of Shanghai for Science and Technology for the facilities, and the scientific and technical assistance. This work was supported by the National Natural Science Foundation of China (32202054), the Program of Shanghai Academic/Technology Research Leader (23XD1430500), and the National Key Research and Development Program of China (2022YFF1100102).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYongyong Liu and Kai Huang contributed equally to this work. Yongyong Liu, Kai Huang, Juan Chen, Fazheng Ren and Xiao Guan designed the experiments. Yongyong Liu and Kai Huang performed the experiments and generated the figures and extended data figures. Yu Zhang, Sen Li, Jing Liu, and Hongdong Song conducted the literature review and assisted with the data analysis. Ying Zhang and Hongwei Cao guided the biological analyses. Yongyong Liu drafted the manuscript. Kai Huang and Juan Chen revised and edited the manuscript. Kai Huang, Juan Chen, Fazheng Ren, and Xiao Guan supervised the project and funded the project. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing financial or non-financial interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAra\u0026uacute;jo, J. R. \u003cem\u003eet al.\u003c/em\u003e Fermentation products of commensal bacteria alter enterocyte lipid metabolism. \u003cem\u003eCell Host Microbe\u003c/em\u003e \u003cstrong\u003e27\u003c/strong\u003e, 358-375. 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X. \u003cem\u003eet al.\u003c/em\u003e \u003cem\u003eAlistipes\u003c/em\u003e indistinctus-derived hippuric acid promotes intestinal urate excretion to alleviate hyperuricemia. \u003cem\u003eCell Host Microbe\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 366-381.e9 (2024).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"","lastPublishedDoi":"10.21203/rs.3.rs-7956394/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7956394/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHigh-fat diet-induced gut microbiota disorder leads to excessive fat absorption, especially in the lower part of the small intestine. A critical but unclear aspect is how the interactions between microbial communities and fat absorption. Using a mouse model, we show that prolonged high-fat intake is linked to increased luminal oxygen bioavailability, promoting the overgrowth of oxygen-mediated opportunistic bacteria (\u003cem\u003eStaphylococcus xylosus\u003c/em\u003e) in the small intestine. \u003cem\u003eS. xylosus\u003c/em\u003eeffectively produces a saturated medium-chain fatty acid (dodecanoic acid) by its substrate-specific Acyl-CoA thioesterase (ACOT). Moreover, this microbe-derived dodecanoic acid (DA) shows an appropriate amount for activating the intestinal PPARα-CD36 signaling, enhancing the fatty acid uptake. Interestingly, we also show that avenanthramide B (AVN B), a novel antioxidant derived from oat, increases ileal epithelial hypoxia, and selectively inhibits \u003cem\u003eS. xylosus\u003c/em\u003eproliferation. This alleviates excessive fat absorption, providing an alternative dietary intervention for treating obesity.\u003c/p\u003e","manuscriptTitle":"Inhibition of oxygen-mediated opportunistic bacteria overgrowth in the ileum alleviates excessive fatty acid absorption against a high-fat diet","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-06 14:14:41","doi":"10.21203/rs.3.rs-7956394/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":"9b1c4341-0186-4f50-8dbf-9d20feee763c","owner":[],"postedDate":"November 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57463763,"name":"Health sciences/Health care/Nutrition"},{"id":57463764,"name":"Health sciences/Diseases/Nutrition disorders/Obesity"}],"tags":[],"updatedAt":"2025-12-11T06:35:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-06 14:14:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7956394","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7956394","identity":"rs-7956394","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}