Study on the Blood glucose Regulation function of Lactobacillus plantarum NXU0011 Powder

Study on the Blood glucose Regulation function of Lactobacillus plantarum NXU0011 Powder | 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 Study on the Blood glucose Regulation function of Lactobacillus plantarum NXU0011 Powder Quan Ji, Ru Zhai, Haiyan Zhang, Longxuan Huo, Chen Qiao, Lin Pan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5425572/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 C57BL/6J mice were studied to evaluate the hypoglycemic function of bacterial powder. The results showed that the bacterial powder had good inhibition ability to α-amylase and α-glucosidase. After the intervention of bacterial powder in diabetic mice, the indexes of fasting blood glucose and insulin level were reduced, and glucose tolerance was improved; the histological results showed that: the alpha diversity of the bacterial powder group (HLP) was improved, and the Shannon index was higher than that of the blank group (CN), Bifidobacterium animaliss , Lactobacillus acidophilus and Akkermansia muciniphila were enriched and had significant differences. Compared with CN group, the expression levels of Hydroxyphenyllactic acid, L-2-Hydroxy-glutaric acid and Glutamic acid in HLP group were significantly increased. Meanwhile, Carbohydrate metabolism, Amino acid metabolism, Nucleotide metabolism and other related pathways were improved. In summary, the Lactobacillus plantarum NXU0011 powder alleviates diabetes by regulating the intestinal flora and metabolites of mice. Type 2 diabetes mellitus Lactobacillus plantarum NXU0011 hypoglycemia metagenomics metabolomics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Introduction Type 2 diabetes mellitus (T2DM) is a type of metabolic disorder with insulin resistance and insulin release disorder as its main clinical manifestations (Chen et al., 2022). More than 500 million people worldwide are estimated to have diabetes, affecting men, women and children of all ages and covering every country (Wang et al., 2021). This number is expected to soar over the next 30 years, according to reports, with every country involved . In recent years, probiotics have received extensive research attention due to their important role in the pathophysiology of T2DM, such as improving intestinal flora and lowering blood sugar (Wu et al., 2023; Zhang et al., 2021). When there are a large number of probiotics in the intestine, they form a protective layer on the intestinal epithelial cells, consume glucose, and prevent a large amount of glucose from being absorbed by the intestine. Therefore, greatly reducing the amount of glucose in the blood will lower the blood sugar concentration (Paquette et al., 2023; Salgaço et al., 2019). In addition, probiotics can also reduce the concentration of lipopolysaccharide (LPS), reduce inflammatory response (Liu et al., 2024), improve insulin sensitivity, improve insulin resistance blood sugar, and thus achieve the purpose of preventing diabetes (Arriaga-Morales et al., 2023; Wang et al., 2020). Materials and equipment 1.1 Materials and reagents Lactobacillus plantarum NXU0011 ( L. plantarum NXU0011) was obtained from Ningxia Key Laboratory of Characteristic Resources Food and biological Manufacturing Control (Yinchuan, China). It is now preserved in the Preservation and Management Center of the China General Microbiological Culture Collection Center (CGMCC No. 26970). α-amylase, α-glucosidase were purchased from Qingdao Haibo Biotechnology Co., LTd. Metformin hydrochloride and streptozotocin (STZ) were purchased from Shanghai McLean Biochemical Technology Co., Ltd. Glutathione peroxidase (GSH-Px) and total superoxide dismutase (SOD) determination kits were purchased from Nanjing Jiancheng Institute of Biological Engineering. Enzyme-linked immunosorbent assay (ELISA) kits Rat FINS ELISA Kit, Rat GHbA1c ELISA Kit were purchased from Shanghai Zucai Biotechnology Co., Ltd. Methanol and acetonitrile were purchased from Thermo Fisher Scientific. 2-chloro-L-phenylalanine (internal standard reference material) were purchased from Aladdin. Formic acid were purchased from TCI. Ammonium formate were purchased from Sigma. Agarose were purchased from Invitrogen. Marker were purchased from Takara. Omega E.Z.N.A.® Soil DNA Kit were purchased from Omega. Fast Pfu Polymerase were purchased from TransStart. AMPure XP beads were purchased from Beckman. Quant-iT PicoGreen dsDNA Assay Kit were purchased from Invitrogen. TAE Buffer were purchased from Invitrogen. Gel DNA recovery kit were purchased from Axygen. Vazyme VAHTSTMDNA Clean Beads were purchased from Nanjing Nuovezan Biotechnology Co., Ltd. NovaSeq 6000 SP Reagent Kit were purchased from Illlumina. Twenty four 3-week-old SPF male C57BL/6J mice were purchased from Chengdu Dashuo Experimental Animal Co., Ltd. (Chengdu, China) and kept under a constant temperature of 20-26℃, a relative humidity of 40%–60%, and a 12 h light/dark cycle. The ethical approval number for the animal experiments is LLSN-2023005. Maintenance feed was provided by Chengdu Dashuo Experimental Animal Co., Ltd. High-fat feed (XTHF60) was from Jiangsu Cooperative Pharmaceutical and Biological Engineering Co., Ltd. 1.2 Instruments and equipment GA-3 blood glucose meter purchased in Sannuo Biosensor Co., Ltd. Finally an enzyme-labeling instrument (SpectraMAX Plus384) purchased in Meigu Molecular Instrument Co., Ltd. Refrigerated centrifuge and Vacuum concentrator purchased in eppendorf. Multi-tube vortex mixer purchased in Hangzhou Aosheng Instrument Co., Ltd. Membranes purchased in Tianjin Jinteng Experimental Equipment Co., Ltd. Liquid chromatography, mass spectrometry and Nanodrop purchased in Thermo Fisher Scientific. Electrophoresis apparatus purchased in Beijing Liuyi Biotechnology Co., Ltd. Gel imaging system purchased in Beijing Baijing Biotechnology Co., Ltd. Fluorescence spectrophotometer purchased in Hitachi Scientific Instruments (Beijing) Co., Ltd. 1.3 Experimental methods 1.3.1 Measurement of blood glucose lowering index and digestive stress ability For details of the method used to determine the inhibition rates of α-amylase and α-glucosidase, please refer to Hongyu Wang (Wang & Li, 2022). Lysozymes (100 mg), pepsin (3 g/L), 0.1% trypsin, and 0.15% bovine bile salt were added to simulated saliva, gastric juice, and intestinal buffer, respectively, followed by stirring (Table 1). Hydrochloric acid was used to adjust the pH to 7.0, 3.0, and 8.0, with a 0.22 μm filter membrane used to remove bacteria. Table 1 Simulated buffer ratio Ingredient Saliva（pH 7.0）mmol/L Gastric fluid（pH 3.0）mmol/L Intestinal fluid（pH 8.0）mmol/L KCl 15.1 6.9 6.8 KH 2 PO 4 3.7 0.9 0.8 NaCl - 47.2 38.48 NaHCO 3 13.60 25 85 MgCl 2 (H 2 O) 6 0.15 0.1 0.33 (NH 4 ) 2 CO 3 0.06 0.5 - CaCl 2 0.75 0.075 0.3 L. plantarum NXU0011 bacterial suspension was incubated in simulated saliva, gastric juice, and intestinal juice at 37℃ for 5 min, 3 h and 2 h, respectively, and survival rates were then calculated. 1.3.2 Design of animal experiments All mice had free access to a normal diet and water during the 3-day adaptation period. Subsequently, 24 mice were randomly divided into a control group (CN), model group (DM), metformin hydrochloride group (MH), L. plantarum NXU0011 group (HLP; 1 × 10 9 colony-forming units CFU/mL). For 6 weeks, the CN group was fed a normal maintenance diet (10% energy from fat), and the other groups were fed a high-fat diet (60% energy from fat). STZ was dissolved in 50 mmol/L citric acid buffer and protected from light. Experimental group animals were injected intraperitoneally with 100 mg/kg fresh STZ, and the same dose of citric acid/sodium citrate buffer salt was injected into CN group animals. T2DM was established via two injections with a 3-day interval. The model was considered successful when the fasting blood glucose of the mice was 7.0 mmol/L, the 2-h postprandial blood glucose level was 11.0 mmol/L, or the blood glucose level of the DM group was > 50% higher than that of the CN group. In week 8, 10 mg/kg body weight (BW) metformin hydrochloride was given to the MH group, whereas the HLP groups were fed 1 × 10 9 CFU/mL L. plantarum NXU0011 powder, respectively, for 4 weeks. The experimental methods and groups are detailed in Table 2. Table 2 Animal experiments and grouping methods Group Modeling period (6 weeks) STZ stage (1 week) Gavage period (4 weeks) Control group（CN） Maintenance feed and distilled water Citric acid - Sodium citrate buffer salt Normal saline 10 mg/(kg·bw) Model group（DM） High-fat feed and distilled water STZ 100 mg/kg Normal saline 10 mg/(kg·bw) Metformin hydrochloride group（MH） High-fat feed and distilled water STZ 100 mg/kg Metformin hydrochloride 10 mg/(kg·bw) L. plantarum NXU0011 group（HLP） High-at feed and distilled water STZ 100 mg/kg L. plantarum NXU00111×10 9 CFU/mL After the final intragastric administration, the mice fasted for 12 h, blood was taken from the orbit, and the mice were killed via intraperitoneal injection of 0.5 mL (10 g/kg BW) of pentobarbital sodium solution. One blood sample was added to each anticoagulant tube, and the serum was centrifuged and stored at -80℃. Fresh fecal samples were preserved at -80°C for testing. Pancreatic tissue was rinsed with precooled saline and stored in formalin. The liver and colon tissues were weighed and divided into two parts, one preserved in formalin and the other in liquid nitrogen. 1.3.3 Test index BW and food intake were recorded every 7 days. After the last gavage, the mice fasted for 8 h and were given a 2 g/kg BW glucose solution. Blood glucose was measured at 15, 30, 60, 90 and 120 min. Based on oral glucose tolerance test (OGTT) data, a change curve was drawn, and the area under the curve (AUC) was calculated. Fasting serum insulin (FINS), glycosylated hemoglobin (HbAlc), total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C). 1.3.4 Metagenomics methods Mo Bio/QIAGEN's Omega E.Z.N.A.® Soil DNA Kit was used for extraction, and the extracted DNA was tested. Quantifluor-ST fluorometer (Promega, E6090; Quant-iT Pico Green dsDNA Assay Kit, Invitrogen, P7589), to determine the absorbance value of DNA at 260 nm and 280 nm, respectively, to detect the concentration of DNA, and to determine the quality of DNA by 1% agarose-gel electrophoresis. The concentration of DNA solution was adjusted, the DNA working solution was stored at 4℃, and the storage solution was stored at -20℃. The standard Illumina TruSeq DNA Sample Preparation Guide was used to construct the required genomic computer library. 1.3.5 Non-targeted metabolomics approaches The experimental samples were thawed at 4℃, and after thawing, the samples swirled for 1 min and were mixed evenly. Precise transfer of appropriate sample into 2 mL centrifuge tube; Add 400 µL methanol solution and swirl for 1 min. Centrifuge at 12000 rpm for 10 min at 4℃, take all the supernatant, transfer it to a new 2 mL centrifuge tube, concentrate and dry; The sample was accurately redissolved with a 2-chlorine-L-phenylalanine (4 ppm) solution prepared with 150µL 80% methanol water. The supernatant was filtered through a 0.22μm membrane, and the filtrate was added to the test bottle for LC-MS detection. For chromatographic conditions and for mass spectrometry refer to the method of Zhang Q et al. (Zhang et al., 2016). 1.4 Statistical analysis SPSS software (ver. 27.0; IBM Corp., Armonk, NY, USA) was used to analyze the data. Analysis of variance (ANOVA) was performed, with Tukey’s post hoc test applied for multiple comparisons. Depending on the homogeneity of variance, Tamhane's T2 test or the least significant differences test was performed for between- and within-group analyses. RXCMS software package was used for peak detection, peak filtering and peak alignment processing, R language Ropls package was used for multivariate statistical analysis, excel was used for metabolite screening, MEGA7 and Origin 2021 were used for mapping. Results 2.1 Results of digestive stress capacity measurement The inhibition rates of α-amylase and α-glucosidase were 85.35% and 51.74%, respectively. The survival rates of L. plantarum NXU0011 after exposure to simulated saliva, gastric juice, and intestinal juice were 119.81%, 39.27%, and 122.52%, respectively. 2.2 Determination of fasting and postprandial blood glucose concentrations After 7 weeks of STZ injections, the fasting and 2-h postprandial blood glucose concentrations were measured (Figure1). As shown in Table 3, the fasting blood glucose level in the CN group was 4.48 mmol/L, and the 2-h postprandial blood glucose level was 7.77 mmol/L. In the other groups, fasting blood glucose exceeded 7 mmol/L, and the 2-h postprandial blood glucose exceeded 11 mmol/L. Therefore, the T2DM mouse model was established successfully. Table 3 Blood glucose changes in mice during the STZ period (±SD ) Group Fasting blood glucose（mmol/L） 2h postprandial blood glucose（mmol/L） CN 4.48±0.81 7.77±1.20 DM 12.98±1.26* 14.82±2.13* MH 12.13±0.70* 14.47±1.97* HLP 13.42±1.72* 15.00±2.84* During the drug and probiotic intervention, the fasting blood glucose and 2 h postprandial blood glucose changes of the mice were monitored regularly every week, as shown in Figure 1. The fasting blood glucose of mice in CN group was basically maintained within the range of 4.48-5.47 mmol/L, which was significantly different from that in DM group. At the 11th week, DM and HLP showed a significant downward trend, in which the fasting blood glucose in the DM group was decreased due to the non-continuous intake of high-fat diets, and the fasting blood glucose in the HLP group dropped to 6.13 mmol/L, which was close to the value of the CN group and significantly lower than that of the DM and MH groups (p<0.05). The intervention effect of the HLP group was significant. 2 h postprandial blood glucose was significantly different between CN group and DM group (p<0.05), and decreased to 11.57mmol/L in HLP group, which was significantly different from MH group. The results showed that NXU0011 has a potential effect on the reduction of fasting and 2 h postprandial blood glucose levels in diabetic mice. 2.3 Determination of biochemical indexes As shown in Figure 2, the HbAlc and FINS levels of the DM group were significantly different to those of the CN group (p < 0.05). After the intervention, the HbAlc and FINS levels of the MH and HLP groups decreased significantly (p < 0.05). The results indicate that the effect of L. plantarum on HbAlc and FINS levels in mice is comparable to that of drugs, and the bacteria can improve the biochemical indices of diabetes and alleviate metabolic disorder in diabetic mice. 2.4 Determination of blood lipid levels Dyslipidemia is an important cause of T2DM, and the results are shown in Table 4. Dyslipidemia is a major cause of T2DM. As shown in Table 4, the blood lipid levels in the DM group were significantly different to those in the CN group (p < 0.05), and the levels of TC, TG and HDL-C in the HLP group were significantly different to those in the DM group (p < 0.05). Overall, the data indicate that L. plantarum NXU0011 can improve blood lipid levels in diabetic mice. 2.5 Metagenomics results 2.5.1 Species composition In order to explore whether L. plantarum NXU0011 can improve the intestinal flora structure and abundance of diabetic mice, the top 20 species in overall abundance of the 4 groups of mice were compared respectively, and the results were shown in Figure 3. According to Figure 3, the relative abundance of Ulum rodentium in the CN group was the lowest, while the relative abundance of Ulum rodentium in MH and HLP groups decreased compared with that in DM group. Leclercia adecarboxylata had the highest relative abundance in CN group. Diabetes mellitus caused a sharp decline in Leclercia adecarboxylata relative abundance, and the relative abundance of Leclercia adecarboxylata could be reversed after bacterial powder intervention. The relative abundance of Leclercia adecarboxylata in MH group is lower (Scheithauer et al., 2020). 2.5.2 Species Alpha diversity In order to compare the intestinal flora richness of mice in different groups, explore the change trend of Alpha diversity of selected samples with the extraction depth, and Shannon index is more sensitive to flora richness and rare species, ASV/OTU number of samples in different groups can be compared under the same sequencing depth. To some extent, the diversity of each sample can be measured, and the results are shown in Figure 4. The Shannon exponential curve in Figure 4A shows that with the increase of sequencing depth, the number of species detected in the sample increases rapidly. Apha diversity analysis reflected the species diversity of a single sample. Under the intervention of bacterial powder, the Alpha diversity of HLP group was higher than that of CN group. With the continuous increase of sequencing volume, Shannon curve has become flat. Even with the increase of sequencing volume, the increase of microbial diversity makes little contribution, indicating that the sequencing volume of this experiment is sufficient to reflect the majority of species information in the samples, and also indicates that the sequencing data volume of this experiment meets the requirements. The species accumulation curve is shown in Figure 4B. The curve has a significant upward trend, indicating that the total number of species in the mouse intestine is increasing. The accumulation curve then shows a steady trend, indicating that the current sample size (12 samples) is sufficient to reflect the richness of intestinal flora. In the sparse curve, the Shannon index of the HLP group was close to that of the CN group, while that of the DM group was close to that of the MH group, which might be because drugs could not regulate the intestinal flora of diabetic mice, while the bacterial powder made the intestinal flora Shannon index of the HLP group more normal. 2.5.3 Species β diversity β diversity analysis can directly reflect the difference of intestinal flora community composition between different experimental groups, reflecting the diversity difference degree between samples. PCoA analyzed the impact of different intervention methods on the intestinal flora community composition of diabetic rats, and the results are shown in Figure 5. As can be seen from Figure 5A, in the principal coordinate analysis, the contribution rate of the first and second principal coordinates was 23.8% and 15.2%, respectively, and the cumulative contribution rate was 39%. A small number of samples overlapped between MH group and DM group, and the blank group was obviously separated from DM group, indicating that the intestinal flora of diabetic mice had undergone significant changes, and there was a small overlap between MH group and DM group. However, the separation effect of HLP group and DM group was better, indicating that the effect of bacterial powder intervention was better than that of metformin hydrochloride to a certain extent, which played a regulatory role in intestinal flora. In addition, the intestinal flora samples of CN group were furthest away from those of HLP group after the intervention of bacteria powder, indicating that the structure and composition of intestinal flora were the most different. The distance between MH group and HLP group was similar, which proved that the effects of L. plantarum powder and drugs were similar, and both could intervene in diabetes. Figure 5B The distribution and distance of each group of sample points in the NMDS diagram showed differences in microbial communities that were roughly the same as those in the PCoA diagram. Meanwhile, the Stress of the analysis was 0.073<0.2, indicating that the analysis results were accurate and reliable. 2.5.4 Species differences At the species level, LEfSe and PLS-DA were used to further analyze the differences of common and unique species in each group, and the results were shown in Figure 6. As can be seen from Figure 6A, 228 microbial species overlapped in each group at the species level, while 82, 77, 192 and 34 microbial species were unique to DM, CN, MH and HLP groups. The evolutionary branching tree of microbial community structure differences in each group was obtained by LEfse, which showed that the sample microbial communities in each group had relatively large differences in various taxonomic levels. The results in Figure 6B showed the classification and rank relationship of the main taxonomic units of mouse intestinal colonies from phylum to species (from inner circle to outer circle). Bifidobacterium animaliss , Lactobacillus acidophilus and Akkermansia-muciniphila in HLP group were significantly different and enriched. There were significant differences among the 17 strains of Rhodococcus pyridinivorans and Rhodococcus gingshengif in MH group (p<0.05) and they were enriched. DM group Staphylococcuscohniis , Staphwlococcus haemolyticus , Staphylococcu-snepalensis , Staphylococcu-spseudintermedius , Staphyloc occu-spseudoxylosus and other species levels were significantly different among 13 strains (p<0.05) and enriched. At the species level of CN group, Bacteroides-zoogleoformans , Chryseobacterium-indoloqenes , Lactobacillus-johnsonii and Limosilactobacillus-reuteri were present Differences and enrichment between groups. Studies have shown that Akkermansia-muciniphila is negatively correlated with T2DM (Gurung et al., 2020). Through species difference analysis, it was found that bacteria powder enriched Akkermansia-muciniphila in mice with T2DM and had a significant difference (p<0.05). 2.5.5 Function Components In order to further compare the effects of different intervention methods on diabetic mice, KO abundance corresponding to each protein was obtained through KO results, and the number of annotated KEGG metabolic pathways of different grades and classifications was counted, as shown in Figure 7. As can be seen from Figure 7, after the inadministration of bacterial powder of L. plantarum NXU0011, the functional annotation of intestinal flora in diabetic mice was put into the pathway. Carbohydrate metabolism, Amino acid metabolism, and Energy metabolism are secondary metabolites in the metabolism pathway metabolism, Nucleotide metabolism and other pathways related to the remission of diabetes have been improved (Li et al., 2020). It is concluded that the bacterial powder of L. plantarum NXU0011 can alleviate diabetes by regulating the structure of intestinal flora and activating related metabolic pathways. Sun et al. (Jang et al., 2017) studied the fermented red ginseng with probiotics, which can reduce the elevated blood sugar caused by diabetes and enhance the low sugar tolerance. More and more articles have shown that probiotics can alleviate T2DM(Gu et al., 2022; Hampe & Roth, 2017). 2.6 Metabolomics results 2.6.1 Data inspection and quality control In order to obtain metabolomic results with stability and accuracy, the ion base peak chromatogram was visually examined, and all BPC maps of each group were overlapped under the same conditions, as shown in Figure 8. The basic peak chromatogram of the positive ion mode is shown in Figure 8A. The signal strength and retention time of the obtained total ion chromatogram are basically consistent, indicating that the sample detection stability is good, and the experimental data are reliable and true. Figure 8B is the PCA score chart of QC samples in positive ion mode. In QC samples, the proportion of characteristic peaks with RSD<30% reached 82.1%, indicating good data. For negative ion mode, Figure A1. In Figure 8C, the QC sample aggregation trend is obvious, and the 95% confidence interval proves that the sample data is reliable, and the experimental results are less affected by external factors. 2.6.2 Multivariate statistics In order to master the overall situation of the data, samples with poor repeatability (outlier samples) or abnormal samples were found and removed to improve the accuracy of the model and multivariate statistical analysis was carried out on the samples. The results are shown in Figure 9 and 10. As can be seen from Figure 9, the R 2 X of PCA score plots for positive ion mode were all greater than 0.5, and the aggregation and repeatability within each group were good, and the differentiation between groups was obvious (p<0.05), so there were significant differences among all groups. For negative ion mode, see Figure A2. OPLS-DA was used to further analyze the data of each group. In the OPLS-DA score chart, the values of R 2 X, R 2 Y and Q 2 in positive ion mode were 0.287, 0.995 and 0.719, respectively (Fig. 10A). In the negative ion mode, the R 2 X, R 2 Y and Q 2 values are 0.376, 0.990 and 0.801, respectively (Figure A3 A). In order to further verify whether the model is overfitting, the replacement method is used to verify the OPLS-DA model. The results show that R 2 is 0.99 and 0.98 respectively in positive and negative ions, and the intercept of Q 2 regression line is -0.06 and -0.02 respectively in positive and negative ions, indicating good prediction ability and no overfitting phenomenon. The negative ion model is shown in Figure A3 B. 2.6.3 Serum differential metabolite screening Based on OPLS-DA model, different groups were compared with VIP>1 and P<0.01 as screening criteria, and the results were shown in Table 5. Table 5 compares different metabolites in different groups Compare groups name mz FC P.value VIP DM vs CN Agmatine 130.12 0.49 0.000 2.24 Homocitrulline 190.11 3.51 0.007 1.99 Dodecanoic acid 199.99 7.19 0.008 1.96 Porphobilinogen 226.18 2.20 0.002 1.99 L-Formylkynurenine 237.09 0.25 0.002 1.99 Anserine 241.13 0.09 0.000 2.29 N2-Succinyl-L-arginine 275.14 0.14 0.003 2.13 10-Nitrolinoleic acid 308.22 5.37 0.005 1.89 5-Aminopentanoic acid 116.93 4.56 0.006 1.60 Tartaric acid 149.01 8.59 0.010 1.64 L-Gulose 161.04 2.11 0.003 1.62 Phenyllactate 165.06 5.46 0.002 1.80 Oxalosuccinic acid 190.01 0.04 0.002 1.71 D-Tryptophan 204.09 0.03 0.000 2.01 1,3,7-Trimethyluric acid 209.07 0.38 0.002 1.87 1-Hexadecanol 242.06 3.54 0.001 1.75 Stearidonic acid 275.20 0.24 0.002 1.65 Guanosine 283.27 0.40 0.003 1.63 Erucic acid 337.31 0.09 0.001 1.78 Sphingosine 1-phosphate 378.24 3.70 0.000 2.03 Celecoxib 380.07 2.94 0.009 1.64 HLP vs CN p-Aminobenzoic acid 138.05 0.47 0.006 1.86 O-Phosphoethanolamine 141.96 0.4 0.001 1.94 N-Methyl-L-glutamic acid 144.07 0.38 0.007 1.70 (S)-5-Amino-3-oxohexanoate 146.08 0.14 0.004 1.85 3-Amino-4-hydroxybenzoate 154.05 0.24 0.006 1.75 L-Histidine 156.04 0.34 0.005 1.86 Suberic acid 157.08 0.49 0.004 1.86 Quinolinic acid 167.01 0.18 0.003 1.98 Quinaldic acid 174.05 0.22 0.002 1.92 Azelaic acid 188.13 0.08 0.003 2.04 Anserine 241.13 0.2 0.001 1.87 Phenylacetylglutamine 265.12 0.26 0.002 1.84 Palmitoylethanolamide 300.29 2.08 0.004 1.87 Dihydrocapsaicin 308.22 0.29 0.001 2.01 10-Nitrolinoleic acid 308.22 10.75 0.000 2.07 Prostaglandin E3 350.20 0.16 0.007 1.75 S-Adenosylhomocysteine 384.35 2.11 0.007 1.79 Avermectin B1b aglycone 570.36 3.3 0.000 2.14 Ethylmethylacetic acid 101.02 3.16 0.000 1.99 o-Toluate 135.05 0.25 0.002 1.85 Threonic acid 135.03 0.4 0.009 1.56 Oxalosuccinic acid 190.01 0 0.000 1.97 D-Erythritol 4-phosphate 201.02 0.47 0.001 1.79 D-Tryptophan 204.09 0.02 0.000 1.92 alpha-D-Ribose 1-phosphate 229.01 0.2 0.002 1.88 Uridine 243.06 2.27 0.000 1.74 Stearidonic acid 275.20 0.14 0.000 1.81 Guanosine 283.27 0.4 0.003 1.60 Arachidonic acid 303.23 0.26 0.000 1.92 PGA1 335.22 0.11 0.000 1.86 Erucic acid 337.31 0.06 0.000 1.79 Sphingosine 1-phosphate 378.24 3.21 0.001 1.80 Sildenafil 474.20 0.03 0.000 1.97 As can be seen from Table 5, there are 21 metabolites in DM group that are significantly different from CN group. After intervention, a total of 11 metabolites in DM group, such as Homocitrulline, Dodecanoic acid and Porphobilinogen, are significantly upregulated. Agmatine, L-Formylkynurenine, Anserine and other 10 substances were significantly down-regulated. These substances may be involved in the pathogenesis of T2DM (Chen & Gerszten, 2020). The results of HLP and CN groups showed a total of 34 metabolites with significant differences, among which 7 substances such as Palmitoylethanolamide, 10-Nitrolinoleic acid and S-Adenosylhomocysteine were significantly up-regulated (p<0.05). 26 substances, including p-Aminobenzoic acid, O-Phosphoethanolamine, N-Methyl-L-glutamic acid, (S) -5-amino -3-oxohexanoate, were significantly down-regulated. Among them, Guanosine did not change, and Guanserine and 10-Nitrolinoleic acid were higher than those in the model group after bacterial powder intervention. These two substances are highly likely to improve diabetes. The contents of Oxalosuccinic acid, D-Tryptophan, Stearidonic acid, Guanosine, Erucic acid and Sphingosine 1-phosphate decreased after the regulation of the powder. These 6 substances may be associated with the exacerbation of diabetes. The secondary differential metabolites and groups were bidirectional clustering, and the content of differential metabolites among different groups was compared, as shown in Figure 11. As can be seen from Figure 11, compared with DM group, metabolites in MH and HLP groups had different degrees of callback after intervention, and gradually approached CN group. And by comparing the metabolites of MH group and HLP group, it can be seen that the expression levels of Hydroxyphenyllactic acid, L-2-Hydroxyglutaric acid, Glutamic acid and N-Acetvlalutamic acid in HLP group were significantly increased. These results indicated that the bacterial powder of Lactobacillus plantarum NXU0011 could regulate and improve the metabolite level of diabetic mice. To further understand the expression and change trend of substances between the groups, T test was used to analyze significant metabolites between the two groups, as shown in Figure 12. As shown in Figure 12, 46 substances, including Palmitoylethanolamide and Sphingosine 1-phosphate, were significantly up-regulated in DM group compared with CN group (p<0.05). There were 35 substances, including D-Tryptophan, Anserine, Palmitoylethanolamide, Sphingosine 1-phosphate and Agmatine, which were significantly down-regulated (p<0.05). Compared with CN group, 34 substances including Ciliatine, 8-Hydroxyquinoline, 2, 3-butanediol in MH group were significantly up-regulated (p<0.05). Agmatine, Acetylphosphate, Acetylcholine and D-2-Hydroxyglutaric acid were significantly down-regulated (p<0.05); However, Ethylmethylacetic acid, Avermectin B1 baglycone and other 25 substances in HLP group were significantly up-regulated compared with CN group (p<0.05). There were 68 substances, such as 2-Hydroxybutyric acid, Arachidonic acid and PGA1, which were significantly down-regulated (p<0.05). 2.6.4 KEGG path analysis MetaboAnalyst was used to conduct KEGG pathway enrichment analysis on the list of differential metabolites, and the results were shown in Table 6. Table 6 Characteristic metabolic pathways in DM group compared with CN group Pathway-name Total Hits Pvalue Compound-name ABC transporters 138 9 0.0059 D-Ribose; L-Leucine; L-Histidine; N-Acetyl-D-glucosamine; D-Xylose; Guanosine; 2'-Deoxyadenosine; Ciliatine; Methyl beta-D-galactoside GnRH signaling pathway 6 2 0.0083 Arachidonic acid; Cyclic AMP Fc gamma R-mediated phagocytosis 8 2 0.0150 Arachidonic acid; Sphingosine 1-phosphate Apelin signaling pathway 9 2 0.0190 Cyclic AMP; Sphingosine 1-phosphate Ovarian steroidogenesis 24 3 0.0197 Arachidonic acid; Cyclic AMP; Dehydroepiandrosterone Hedgehog signaling pathway 1 1 0.0244 Cyclic AMP Amino acid metabolism 47 4 0.0266 L-Histidine; Anserine; N-Acetylhistamine ; 4-Oxoglutaramate Phospholipase D signaling pathway 11 2 0.0281 Cyclic AMP; Sphingosine 1-phosphate Calcium signaling pathway 11 2 0.0281 Cyclic AMP; Sphingosine 1-phosphate Linoleic acid metabolism 28 3 0.0297 Arachidonic acid; 13-L-Hydroperoxylinoleic acid; 9(S)-HPODE Insulin secretion 12 2 0.0332 Cyclic AMP; Acetylcholine Oxytocin signaling pathway 12 2 0.0332 Arachidonic acid; Cyclic AMP Cholinergic synapse 12 2 0.0332 Cyclic AMP; Acetylcholine Amoebiasis 13 2 0.0386 Arachidonic acid; Cyclic AMP Pathways in cancer 31 3 0.0387 Fumaric acid; Cyclic AMP; Dehydroepiandrosterone Gastric acid secretion 14 2 0.0444 Cyclic AMP; Acetylcholine Regulation of lipolysis in adipocytes 14 2 0.0444 Arachidonic acid; Cyclic AMP Platelet activation 14 2 0.0444 Arachidonic acid; Cyclic AMP Longevity regulating pathway - multiple species 2 1 0.0483 Cyclic AMP Circadian rhythm 2 1 0.0483 Cyclic AMP Vasopressin-regulated water reabsorption 2 1 0.0483 Cyclic AMP As shown in Table 6, differences between DM group and CN group are significantly enriched in 21 metabolic pathways (p<0.05), and ABC transporters and GnRH signaling pathway are extremely significantly enriched (p<0.01). The Amino acid metabolism pathway was consistent with the metagenomic analysis. There is evidence (Behl et al., 2021) that the overproduction and reduced clearance of lipids and glucose contribute to the emergence of diabetes, and that ABC transporters play a key role in the metabolism and transport of both substances. In the GnRH signaling pathway, Arachidonic acid belongs to the eicosane polyunsaturated fatty acid, which exists in the form of phospholipid on the inner surface of cell membrane and produces nearly 100 small molecule metabolites with different biological activities during metabolism. These metabolites play an extremely important role in the occurrence and development of diabetes (Cardoso et al., 2021; Kosmalski et al., 2022). These results indicate that the body of diabetic mice is in a serious metabolic disorder, and several key metabolic pathways are affected. The metabolic pathways of MH group and CN group were significantly enriched after screening, as shown in schedule 1. A total of 16 metabolic pathways were significantly enriched (p<0.05), among which the first six were extremely significantly enriched (p<0.01). Oxalacetic acid, Fumaric acid, L-Malic acid, Arachidonic acid and other substances participate in many metabolic pathways. In addition, Arachidonic acid can improve T2DM induced by streptomycin in Wistar rats. Analysis of different metabolite pathways between HLP group and CN group showed that a total of 14 metabolic pathways were significantly enriched (p<0.05), and Neuroactive ligand-receptor interaction and Tyrosine metabolism were extremely significantly enriched (p<0.01). The metabolic pathway of HLP and CN groups was compared with that of DM and CN groups, and P value of ABC transporters pathway was increased, from significant enrichment to extremely significant enrichment, indicating that NXU0011 had a alleviating effect on T2DM mice. After comparison between HLP group and MH group, a total of 28 metabolic pathways were significantly enriched (p<0.05), and 13 of them were extremely significantly enriched (p<0.01). L-Glutamic acid and L-Glutamine were involved in multiple metabolic pathways. L-Glutamic acid and L-Glutamine participate in multiple metabolic pathways. Studies have shown that (Padilha et al., 2016) glutamine (Gln) is an important precursor for macromolecule synthesis in the body and a nutrient source for intestinal mucosal cells. It may increase the secretion of glucagon-like peptide-1 (GLP-1) by intestinal L cells, promote the synthesis of liver glycogen, inhibit lipolysis and oxidation, and thus reduce blood sugar. Naveen K V Gundala et al. (Gundala et al., 2018) showed enhanced expression of pro-inflammatory genes, including NF-κB in the pancreas, in laboratory animals with T2DM. NF-κB, one of the nuclear transcription factors, is involved in a variety of biological processes and exists in almost all types of mammalian cells. At the same time, NF-κB can regulate cell survival, differentiation and proliferation, and its functions are related to the regulation of gene expression during body defense, tissue injury, stress and inflammation (Tiderencel et al., 2020). Activation of NF-κB leads to the transcription of multiple target genes, including cytokines, such as TNF-a, IL-6, and IL-1 (Ye et al., 2024). These pro-inflammatory factors inhibit insulin-induced RS tyrosine phosphorylation and further activate NF-κB. The NF-κB pathway is widely recognized as a participant in chronic inflammation and many autoimmune diseases(Lee et al., 2022), with key mechanisms associated with obesity, inflammation, and various metabolic disorders. Studies have further confirmed that down-regulation or inhibition of NF-κB signaling pathway can weaken Insulin Resistance (IR) in T2DM rats and alleviate symptoms such as obesity and glucose intolerance caused by high fat diet (Chu et al., 2024). 2.7 Metagenomics combined with metabolomics analysis Spearman correlation test was used for correlation analysis, and the results were shown in Figure 13. As can be seen from Figure 13A, Muribaculum intestinale , Duncaniella dubosii and Muribaculaceae bacterium MF13079 were negatively correlated with 3-Hydroxymethylglutaric acid. Sphingosine 1-phosphate (S1P) was positively correlated with Faecalibaculum rodentium , Duncaniella dubosii and Muribaculaceae bacterium MF13079 . Faecalibaculum rodentium was positively associated with Stearolic acid and Homocitrulline, which have been shown by many authors to be markers of worsening T2DM, Stearolic acid and Homocitrulline inhibit islet cells or induce apoptosis (Slieker et al., 2023). N-benzoyl-d-phenylalanine, a derivative of D-beta-Phenylalanine that is negatively correlated with Faecalibaculum rodentium , has the same effect as metformin hydrochloride. As can be seen from Figure 11B, Comamonas terrigena was positively correlated with Oleamide and pointed to HLP group and MH group, indicating that this substance and this strain may have a alleviating effect on diabetes. Leclercia adecarboxylata , Ligilactobacitus murus , Pseudomonas putida , Lumichrome, Homocitrulline, (4Z.7Z,10Z,13Z,16Z,19Z)-Docosahexaenoic acid ethyl ester were all positively correlated and more correlated with DM group. These bacteria and substances may be markers of diabetes. Camila Aguilar Delgado et al. (Delgado et al., 2019) analyzed by alkaline cometometry that 3-Hydroxymethylglutaric acid can damage body DNA. However, the mechanism of 3-Hydroxymethylglutaric acid on diabetes remains to be further studied. RENZO DEANA et al.(Deana et al., 1982) demonstrated through gas-liquid chromatography(GLC) that urine excretion of 3-Hydroxymethylglutaric acid was increased in diabetic people and rats. Therefore, 3-Hydroxymethylglutaric acid is a hallmark metabolite of diabetes.S1P, which is mainly produced by the plasma membrane, is a pleiotropic lipid mediator and phosphorylated product of sphingo kinase 1, mainly expressed in macrophages and mast cells. S1P, after binding with its receptors S1PR1 and S1PR2, can inhibit the apoptosis of islet beta cells, alleviate the inflammatory damage of islet beta cells, promote insulin secretion and increase insulin sensitivity. Slow the progression of diabetes. Sphingosine 1-phosphate (S1P) is positively correlated with Faecalibaculum rodentium . Jamie Cantrell Stanford et al. (Cantrell Stanford et al., 2012) demonstrated in mice that high sugar can stimulate the production of S1P. S1P plays an important role in regulating glucose homeostasis. A large number of literatures have shown that S1P and ceramide levels increase in liver, adipose tissue, skeletal muscle, pancreas and plasma in obese mice, which is consistent with the results of this study, indicating that S1P can regulate diabetes (Choi & Snider, 2015; Kobayashi et al., 2021; Turner et al., 2013). Discussion Probiotics adopted in 2002 are recognized as living microorganisms with health benefits for human intake, and the probiotics must maintain vitality in the digestive tract, especially to resist bile salts in the gastrointestinal tract (Hill et al., 2014). Gastric acid has an inhibitory effect on the growth and reproduction of lactic acid bacteria (Wang & Li, 2022). Unfortunately, NXU0011 has a low tolerance to gastric acid, but a good tolerance to bile salt. The survival rate reached 122.52% after simulating the tolerance of saliva-gastric fluid-intestinal fluid. Lactic acid bacteria promote resistance to bile salts by maintaining membrane integrity through surface proteins. Only after the stress of simulated digestion test in vitro, probiotics with high survival rate can better play a role in the human gastrointestinal tract. α-glucosidase and α-amylase are two key enzymes involved in carbohydrate digestion. Inhibition of the activity of the two key enzymes can prevent glucose from entering the circulation and reduce blood sugar concentration (Gong et al., 2020). Therefore, the inhibition rate of the two key enzymes is an important indicator of the hypoglycemic ability of probiotics in vitro screening. The results of this study showed that Lactobacillus plantarum NXU0011 has a good inhibitory effect on α-amylase and α-glucosidase, which slows down the degradation and absorption of carbohydrates and reduces blood glucose level more efficiently. In recent years, many lactic acid bacteria have shown their potential to alleviate diabetes symptoms, which has been verified in animal experiments (Wang et al., 2020; Youn et al., 2021). Some lactic acid bacteria can alleviate insulin resistance, lower fasting blood sugar, reduce blood lipids, inflammation and oxidative stress symptoms, and improve apparent symptoms (Wang et al., 2017). In this study, C57BL/6J mice were used to establish a T2DM model. After modeling, mice in each group showed the conditions of polyuria, lethargy, dark yellow dishevelled hair, and emotional irritability. With the intervention of lactic acid bacteria and drugs, the above adverse states of mice in MH and HLP groups could be alleviated and improved. The study also analyzed the fasting and 2h postprandial blood glucose levels of mice, insulin resistance, immune regulation, etc. The results showed that L. plantarum NXU0011 can significantly alleviate the glucose load capacity of diabetic mice and improve the function of islet cells. In addition, HbA1c can reflect the blood sugar level of diabetic patients for a period of time, that is, the significantly reduced HBA1c of mice in the HLP group also reflects that the symptoms of diabetes are well controlled. T2DM mellitus is accompanied by persistent chronic low-grade inflammation. Although there are no typical signs of inflammation, it involves the same inflammatory pathways and signals, usually manifested as elevated levels of IL-6 and TNF-α, which may interfere with insulin action by inhibiting insulin signaling pathways. NXU0011 can also alleviate inflammation in mice. It is difficult for a single omics to fully understand the mechanism of T2DM, and multi-omics studies have greater advantages than single omics studies(Yan et al., 2022). Therefore, the aim of this study was to investigate the effect of L. plantarum NXU0011 on a high-fat diet and streptozotocin induced diabetic mouse model. Conclusions The α-amylase (85.35%) and α-glucosidase (51.74%) were inhibited by Lactobacillus plantarum NXU0011. After simulated saliva-gastro-intestinal fluid stress, the survival rate was 122.52%, and the vitality remained high. C57BL/6J T2DM mice co-induced by high-fat diet and streptozotocin were treated with L. plantarum NXU0011 bacterial powder, the weight of the mice tended to be stable, the fasting blood glucose was significantly reduced, and the glucose loading capacity was improved, which played a good role in controlling and improving the symptoms of T2DM. Lactobacillus plantarum NXU0011 can regulate the relative abundance of Leclercia adecarboxylata , regulate intestinal flora, regulate metabolites to alleviate diabetes, and improve the pathways associated with alleviating diabetes. Studies have shown that 3-Hydroxymethylglutaric acid may be an indicator of T2DM, Stearolic acid and Homocitrulline are markers of T2DM progression, Faecalibaculum rodentium was found to be associated with a variety of substances, and the bacteria can affect diabetes. The relationship between Faecalibaculum rodentium and diabetes can be further explored in the future. Declarations CRediT authorship contribution statement Quan Ji: Conceptualization, Formal analysis, Methodology, Software, Writing – original draft. Ru Zhai :Conceptualization, Formal analysis, Methodology, Software, Writing – original draft. Haiyan Zhang: Data curation, Methodology, Software, Visualization. Longxuan Huo: Investigation, Formal analysis, Resources. Chen Qiao: Data curation, Formal analysis, Resources. Lin Pan: Funding acquisition, Supervision, Writing – review & editing, All authors have read and agreed to the published version of the manuscript. Declaration of competing interest The authors declare that they have no known competing financial The authors declare that they have no known competing financial. Acknowledgements This work was supported by the Key R & D Program of Ningxia Hui Autonomous Region (Grant number: 2023BCF01028 & 2023BCF01029 & NYG2024042). References Chen, K., Wei, X., Kortesniemi, M., Pariyani, R., Zhang, Y., & Yang, B. (2022). Effects of acylated and nonacylated anthocyanins extracts on gut metabolites and microbiota in diabetic Zucker rats: A metabolomic and metagenomic study. Food Research International, 153, 110978. http://doi.org/10.1016/j.foodres.2022.110978 Wang, G., Liu, J., Xia, Y., & Ai, L. (2021). Probiotics-based interventions for diabetes mellitus: A review. Food Bioscience, 43, 101172. http://doi.org/10.1016/j.fbio.2021.101172 Zhang, L., Chu, J., Hao, W., Zhang, J., Li, H., Yang, C., Yang, J., Chen, X., & Wang, H. (2021). Gut Microbiota and Type 2 Diabetes Mellitus: Association, Mechanism, and Translational Applications [Journal Article; Review]. Mediators of Inflammation, 2021, 5110276. http://doi.org/10.1155/2021/5110276 Wu, J., Yang, K., Fan, H., Wei, M., & Xiong, Q. (2023). Targeting the gut microbiota and its metabolites for type 2 diabetes mellitus. Frontiers in Endocrinology (Lausanne), 14, 1114424. http://doi.org/10.3389/fendo.2023.1114424 Paquette, S., Thomas, S. C., Venkataraman, K., Appanna, V. D., & Tharmalingam, S. (2023). The Effects of Oral Probiotics on Type 2 Diabetes Mellitus (T2DM): A Clinical Trial Systematic Literature Review. Nutrients, 15(21), 4690. http://doi.org/10.3390/nu15214690 Salgaço, M. K., Oliveira, L. G. S., Costa, G. N., Bianchi, F., & Sivieri, K. (2019). Relationship between gut microbiota, probiotics, and type 2 diabetes mellitus. Applied Microbiology and Biotechnology, 103(23-24), 9229-9238. http://doi.org/10.1007/s00253-019-10156-y Liu, N., Yan, X., Lv, B., Wu, Y., Hu, X., Zheng, C., Tao, S., Deng, R., Dou, J., Zeng, B., & Jiang, G. (2024). A study on the association between gut microbiota, inflammation, and type 2 diabetes. Applied Microbiology and Biotechnology, 108(1) http://doi.org/10.1007/s00253-024-13041-5 Arriaga-Morales, J. J., Ordaz-Pichardo, C., Castro Muñoz, R., & Durán-Páramo, E. (2023). Attenuation of Hyperglycemia in Diabetic Rats Assisted by Immobilized Probiotic in Sodium Alginate. Probiotics and Antimicrobial Proteins http://doi.org/10.1007/s12602-023-10166-3 Wang, L., Shang, Q., Guo, W., Wu, X., Wu, L., Wu, L., & Chen, T. (2020). Evaluation of the hypoglycemic effect of probiotics via directly consuming glucose in intestines of STZ-induced diabetic mice and glucose water-induced diabetic mice. Journal of Functional Foods, 64, 103614. http://doi.org/10.1016/j.jff.2019.103614 Wang, H., & Li, L. (2022). Comprehensive Evaluation of Probiotic Property, Hypoglycemic Ability and Antioxidant Activity of Lactic Acid Bacteria. Foods, 11(9), 1363. http://doi.org/10.3390/foods11091363 Zhang, Q., Wu, Y., & Fei, X. (2016). Effect of probiotics on glucose metabolism in patients with type 2 diabetes mellitus: A meta-analysis of randomized controlled trials. Medicina, 52(1), 28-34. http://doi.org/10.1016/j.medici.2015.11.008 Scheithauer, T. P. M., Rampanelli, E., Nieuwdorp, M., Vallance, B. A., Verchere, C. B., van Raalte, D. H., & Herrema, H. (2020). Gut Microbiota as a Trigger for Metabolic Inflammation in Obesity and Type 2 Diabetes. Frontiers in Immunology, 11, 571731. http://doi.org/10.3389/fimmu.2020.571731 Gurung, M., Li, Z., You, H., Rodrigues, R., Jump, D. B., Morgun, A., & Shulzhenko, N. (2020). Role of gut microbiota in type 2 diabetes pathophysiology. Ebiomedicine, 51, 102590. http://doi.org/10.1016/j.ebiom.2019.11.051 Li, X., Wu, Y., Zhao, J., Wang, H., Tan, J., Yang, M., Li, Y., Deng, S., Gao, S., Li, H., Yang, Z., Yang, F., Ma, J., Cheng, J., & Cai, W. (2020). Distinct cardiac energy metabolism and oxidative stress adaptations between obese and non-obese type 2 diabetes mellitus. Theranostics, 10(6), 2675-2695. http://doi.org/10.7150/thno.40735 Jang, S., Park, J., Kim, S., Choi, K., Ko, E., Cha, J., Lee, Y., Jang, H., & Jang, Y. (2017). Red ginseng powder fermented with probiotics exerts antidiabetic effects in the streptozotocin-induced mouse diabetes model. Pharmaceutical Biology, 55(1), 317-323. http://doi.org/10.1080/13880209.2016.1237978 Gu, Y., Li, X., Chen, H., Sun, Y., Yang, L., Ma, Y., & Yong Chan, E. C. (2022). Antidiabetic effects of multi-species probiotic and its fermented milk in mice via restoring gut microbiota and intestinal barrier. Food Bioscience, 47, 101619. http://doi.org/10.1016/j.fbio.2022.101619 Hampe, C. S., & Roth, C. L. (2017). Probiotic strains and mechanistic insights for the treatment of type 2 diabetes. Endocrine, 58(2), 207-227. http://doi.org/10.1007/s12020-017-1433-z Chen, Z., & Gerszten, R. E. (2020). Metabolomics and Proteomics in Type 2 Diabetes. Circulation Research, 126(11), 1613-1627. http://doi.org/10.1161/CIRCRESAHA.120.315898 Behl, T., Sehgal, A., Grover, M., Singh, S., Sharma, N., Bhatia, S., Al-Harrasi, A., Aleya, L., & Bungau, S. (2021). Uncurtaining the pivotal role of ABC transporters in diabetes mellitus. Environmental Science and Pollution Research International, 28(31), 41533-41551. http://doi.org/10.1007/s11356-021-14675-y Cardoso, N. S., Cruz, J. R. D. S., Paula, R. A. D. O., Duarte, S. M. D. S., Rodrigues, M. R., & Paula, F. B. D. A. (2021). Unsaturated fatty acid as functional food for the treatment of Diabetes mellitus type 2. Research, Society and Development, 10(9), e1538755729. http://doi.org/10.33448/rsd-v10i9.17231 Kosmalski, M., Pękala-Wojciechowska, A., Sut, A., Pietras, T., & Luzak, B. (2022). Dietary Intake of Polyphenols or Polyunsaturated Fatty Acids and Its Relationship with Metabolic and Inflammatory State in Patients with Type 2 Diabetes Mellitus. Nutrients, 14(5), 1083. http://doi.org/10.3390/nu14051083 Padilha, K., Venturini, G., de Farias Pires, T., Horimoto, A. R. V. R., Malagrino, P. A., Gois, T. C., Kiers, B., Oliveira, C. M., de Oliveira Alvim, R., Blatt, C., Krieger, J. E., & Pereira, A. C. (2016). Serum metabolomics profile of type 2 diabetes mellitus in a Brazilian rural population. Metabolomics, 12(10), 1. http://doi.org/10.1007/s11306-016-1107-5 Gundala, N., Naidu, V., & Das, U. N. (2018). Amelioration of streptozotocin-induced type 2 diabetes mellitus in Wistar rats by arachidonic acid [Journal Article]. Biochemical and Biophysical Research Communications, 496(1), 105-113. http://doi.org/10.1016/j.bbrc.2018.01.007 Tiderencel, K. A., Hutcheon, D. A., & Ziegler, J. (2020). Probiotics for the treatment of type 2 diabetes: A review of randomized controlled trials. Diabetes/Metabolism Research and Reviews, 36(1), e3213. http://doi.org/10.1002/dmrr.3213 Ye, J., Ma, J., Rozi, P., Kong, L., Zhou, J., Luo, Y., & Yang, H. (2024). The polysaccharides from seeds of Glycyrrhiza uralensis ameliorate metabolic disorders and restructure gut microbiota in type 2 diabetic mice. International Journal of Biological Macromolecules, 264(Pt 1), 130622. http://doi.org/10.1016/j.ijbiomac.2024.130622 Lee, J., Yang, Y., Tao, Y., Yi, Y., & Cho, J. Y. (2022). Korean Red Ginseng saponin fraction exerts anti-inflammatory effects by targeting the NF-κB and AP-1 pathways. Journal of Ginseng Research, 46(3), 489-495. http://doi.org/10.1016/j.jgr.2022.02.004 Chu, C., Ru, H., Chen, Y., Xu, J., Wang, C., & Jin, Y. (2024). Gallic acid attenuates LPS-induced inflammation in Caco-2 cells by suppressing the activation of the NF-κB/MAPK signaling pathway. Acta Biochimica Et Biophysica Sinica http://doi.org/10.3724/abbs.2024008 Delgado, C. A., Balbueno Guerreiro, G. B., Diaz Jacques, C. E., de Moura Coelho, D., Sitta, A., Manfredini, V., Wajner, M., & Vargas, C. R. (2019). Prevention by L-carnitine of DNA damage induced by 3-hydroxy-3-methylglutaric and 3-methylglutaric acids and experimental evidence of lipid and DNA damage in patients with 3-hydroxy-3-methylglutaric aciduria. Archives of Biochemistry and Biophysics, 668, 16-22. http://doi.org/10.1016/j.abb.2019.04.008 Deana, R., Lippe, G., & Galzigna, L. (1982). Urinary excretion of 3-hydroxy-3-methylglutaric acid in the diabetic condition [Journal Article]. Clinical Biochemistry, 15(2), 73-75. http://doi.org/10.1016/s0009-9120(82)90832-3 Cantrell Stanford, J., Morris, A. J., Sunkara, M., Popa, G. J., Larson, K. L., & Özcan, S. (2012). Sphingosine 1-Phosphate (S1P) Regulates Glucose-stimulated Insulin Secretion in Pancreatic Beta Cells. The Journal of Biological Chemistry, 287(16), 13457-13464. http://doi.org/10.1074/jbc.M111.268185 Choi, S., & Snider, A. J. (2015). Sphingolipids in High Fat Diet and Obesity-Related Diseases [Journal Article; Research Support, Non-U.S. Gov't; Review]. Mediators of Inflammation, 2015, 520618. http://doi.org/10.1155/2015/520618 Turner, N., Kowalski, G. M., Leslie, S. J., Risis, S., Yang, C., Lee-Young, R. S., Babb, J. R., Meikle, P. J., Lancaster, G. I., Henstridge, D. C., White, P. J., Kraegen, E. W., Marette, A., Cooney, G. J., Febbraio, M. A., & Bruce, C. R. (2013). Distinct patterns of tissue-specific lipid accumulation during the induction of insulin resistance in mice by high-fat feeding. Diabetologia, 56(7), 1638-1648. http://doi.org/10.1007/s00125-013-2913-1 Kobayashi, K., Sasase, T., Ishii, Y., Katsuda, Y., Miyajima, K., Yamada, T., & Ohta, T. (2021). The sphingosine‐1‐phosphate receptor modulator, FTY720, prevents the incidence of diabetes in Spontaneously Diabetic Torii rats. Clinical and Experimental Pharmacology & Physiology, 48(6), 869-876. http://doi.org/10.1111/1440-1681.13405 Hill, C., Guarner, F., Reid, G., Gibson, G. R., Merenstein, D. J., Pot, B., Morelli, L., Canani, R. B., Flint, H. J., Salminen, S., Calder, P. C., & Sanders, M. E. (2014). Expert consensus document. The International Scientific Association for Probiotics and Prebiotics consensus statement on the scope and appropriate use of the term probiotic [Consensus Development Conference; Journal Article]. Nature Reviews Gastroenterology & Hepatology, 11(8), 506-514. http://doi.org/10.1038/nrgastro.2014.66 Gong, L., Feng, D., Wang, T., Ren, Y., Liu, Y., & Wang, J. (2020). Inhibitors of alpha-amylase and alpha-glucosidase: Potential linkage for whole cereal foods on prevention of hyperglycemia [Journal Article; Review]. Food Science & Nutrition, 8(12), 6320-6337. http://doi.org/10.1002/fsn3.1987 Wang, H., & Li, L. (2022). Comprehensive Evaluation of Probiotic Property, Hypoglycemic Ability and Antioxidant Activity of Lactic Acid Bacteria. Foods, 11(9), 1363. http://doi.org/10.3390/foods11091363 Wang, G., Si, Q., Yang, S., Jiao, T., Zhu, H., Tian, P., Wang, L., Li, X., Gong, L., Zhao, J., Zhang, H., & Chen, W. (2020). Lactic acid bacteria reduce diabetes symptoms in mice by alleviating gut microbiota dysbiosis and inflammation in different manners. Food & Function, 11(7), 5898-5914. http://doi.org/10.1039/c9fo02761k Youn, H. S., Kim, J., Lee, J. S., Yoon, Y. Y., Choi, S. J., Lee, J. Y., Kim, W., Hwang, K. W., Freitag, N. E., & Freitag, N. E. (2021). Lactobacillus plantarum Reduces Low-Grade Inflammation and Glucose Levels in a Mouse Model of Chronic Stress and Diabetes. Infection and Immunity, 89(8), e61520. http://doi.org/10.1128/IAI.00615-20 Yan, J., Li, J., Xue, Q., Xie, S., Jiang, J., Li, P., & Du, B. (2022). Bacillus sp. DU‐106 ameliorates type 2 diabetes by modulating gut microbiota in high‐fat‐fed and streptozotocin‐induced mice. Journal of Applied Microbiology, 133(5), 3126-3138. http://doi.org/10.1111/jam.15773 Additional Declarations No competing interests reported. Supplementary Files Appendix.docx 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5425572","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":377673237,"identity":"52edd1cc-234b-4866-aa53-4ea83f33b3e8","order_by":0,"name":"Quan Ji","email":"","orcid":"","institution":"Ningxia University","correspondingAuthor":false,"prefix":"","firstName":"Quan","middleName":"","lastName":"Ji","suffix":""},{"id":377673238,"identity":"8d302dba-81ca-45ce-b80d-2c2dc8c0fa35","order_by":1,"name":"Ru Zhai","email":"","orcid":"","institution":"Ningxia University","correspondingAuthor":false,"prefix":"","firstName":"Ru","middleName":"","lastName":"Zhai","suffix":""},{"id":377673239,"identity":"c6b57962-f4f6-4c92-b55f-c5bfecac7a3a","order_by":2,"name":"Haiyan Zhang","email":"","orcid":"","institution":"Ningxia University","correspondingAuthor":false,"prefix":"","firstName":"Haiyan","middleName":"","lastName":"Zhang","suffix":""},{"id":377673240,"identity":"fcd657f7-e4cf-4bf8-96e0-ca90a2d6055b","order_by":3,"name":"Longxuan Huo","email":"","orcid":"","institution":"Ningxia University","correspondingAuthor":false,"prefix":"","firstName":"Longxuan","middleName":"","lastName":"Huo","suffix":""},{"id":377673241,"identity":"ef83914d-d258-46c4-9f46-c515839d93d9","order_by":4,"name":"Chen Qiao","email":"","orcid":"","institution":"Ningxia University","correspondingAuthor":false,"prefix":"","firstName":"Chen","middleName":"","lastName":"Qiao","suffix":""},{"id":377673242,"identity":"8533927b-bc84-4ccf-9e78-59e777aab464","order_by":5,"name":"Lin Pan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvUlEQVRIiWNgGAWjYHACxgMJDDYQJg+xeoBa0kjVwsBwmAQt5uxnDxx4uON8nsGNBMYHb9sY5M0JabHsyUs4kHjmdrHkjARmw7ltDIY7GwhoMTiQY3Agse12Yr9EAps0bxtDgsEBQlrOvwFpOZfYJpHA/ps4LTfAthwA28JMlBbLGWBbkhNn9jxslpxzTsJwAyEt5vw5hg9/ttklbjiefPDDmzIbecIOQzAZG4CEBAH1qFpGwSgYBaNgFOAAAMM3Q3tlTzI5AAAAAElFTkSuQmCC","orcid":"","institution":"Ningxia University","correspondingAuthor":true,"prefix":"","firstName":"Lin","middleName":"","lastName":"Pan","suffix":""}],"badges":[],"createdAt":"2024-11-10 11:08:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5425572/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5425572/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":70387927,"identity":"3fed8ebe-ee7f-4c1f-9d27-4407e6356e62","added_by":"auto","created_at":"2024-12-02 17:25:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":228663,"visible":true,"origin":"","legend":"\u003cp\u003eBlood glucose changes in different groups of mice during the experiment\u003c/p\u003e\n\u003cp\u003eNote: a: STZ fasting blood glucose; b: 2h postprandial blood glucose in STZ stage; c: fasting blood glucose in gavage stage; d: 2 h postprandial blood glucose during gavage. * represents significant difference compared with CN group; \u003csup\u003e#\u003c/sup\u003e indicates significant difference compared with DM group, all p\u0026lt;0.05.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5425572/v1/2ec3ab7646873093f683c1ef.png"},{"id":70387834,"identity":"77bd05a8-ddf7-491c-91dc-016d6875b0b2","added_by":"auto","created_at":"2024-12-02 17:24:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":91767,"visible":true,"origin":"","legend":"\u003cp\u003eHbAlc and FINS contents in different groups of mice\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5425572/v1/39f838d6bd31ee607cbce120.png"},{"id":70387918,"identity":"6affd354-1130-484b-8bf2-eaa6912afa30","added_by":"auto","created_at":"2024-12-02 17:25:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":258065,"visible":true,"origin":"","legend":"\u003cp\u003eSpecies-level taxonomic composition bar chart\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5425572/v1/819d028cf09e5bdd3188fedb.png"},{"id":70387876,"identity":"01813c32-13dc-4cbd-9ed7-ed2c1e8cdeb4","added_by":"auto","created_at":"2024-12-02 17:25:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":99786,"visible":true,"origin":"","legend":"\u003cp\u003eSpecies-level sparsity curve (A); Species-level Specaccum species accumulation curve (B)\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5425572/v1/548f3afb2f949919ed086c5f.png"},{"id":70387859,"identity":"238862e7-bcf5-48ff-b49b-7724c04c5f80","added_by":"auto","created_at":"2024-12-02 17:25:00","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":140343,"visible":true,"origin":"","legend":"\u003cp\u003eTwo-dimensional ordering diagram of samples for species PCoA analysis (A); Two-dimensional Ordering diagram of samples for species NMDS analysis (B)\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5425572/v1/8cb4adade08d1cea66f36042.png"},{"id":70387863,"identity":"a7f03b6d-1b38-4348-84be-9f7143bbccab","added_by":"auto","created_at":"2024-12-02 17:25:03","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":605113,"visible":true,"origin":"","legend":"\u003cp\u003eSpecies Venn Diagram (A); LEfSe Species evolutionary Branching Tree (B)\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5425572/v1/592432c32cb7f37f2934e46c.png"},{"id":70387862,"identity":"553ce07f-9f8f-4cb4-9f68-e2c713077d93","added_by":"auto","created_at":"2024-12-02 17:25:02","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":483678,"visible":true,"origin":"","legend":"\u003cp\u003eStatistical map of KEGG metabolic pathway annotation results\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-5425572/v1/969d741cdbf253b02f24d3a6.png"},{"id":70387855,"identity":"a85f5266-46cd-41c3-9968-7dfcf111c809","added_by":"auto","created_at":"2024-12-02 17:24:59","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":394452,"visible":true,"origin":"","legend":"\u003cp\u003ePositive ion peak chromatogram (A); Positive ion QA results-RSD distribution map (B); Positive ion QC sample PCA score map (C)\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-5425572/v1/82258051a2ffa375a016a957.png"},{"id":70387866,"identity":"5f13cda2-1fec-4110-8601-c8b1b7f2c4a1","added_by":"auto","created_at":"2024-12-02 17:25:05","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":88342,"visible":true,"origin":"","legend":"\u003cp\u003ePositive ion principal component analysis diagram\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-5425572/v1/7f7b2c861e0f96b278089646.png"},{"id":70387857,"identity":"bd44f4a9-588c-4b29-a1b1-cc05969cde7b","added_by":"auto","created_at":"2024-12-02 17:24:59","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":181122,"visible":true,"origin":"","legend":"\u003cp\u003ePositive ion OPLS-DA score (A); Positive ion OPLS-DA replacement test (B)\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-5425572/v1/1d2f2173d156cd0f0a6362cb.png"},{"id":70387922,"identity":"b01692f1-4030-47f2-984a-f6c8b7a8af2f","added_by":"auto","created_at":"2024-12-02 17:25:17","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":1522116,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential metabolite clustering heat map\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-5425572/v1/e642e33be0347ca0bf97d5d4.png"},{"id":70387854,"identity":"1fb95126-51c7-4478-b8b0-7cfc2461c16a","added_by":"auto","created_at":"2024-12-02 17:24:58","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":375070,"visible":true,"origin":"","legend":"\u003cp\u003eVolcanic map of differential metabolites\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-5425572/v1/4d8d08f8f2667cb578b19aea.png"},{"id":70387879,"identity":"52fdd7d0-68b9-4c94-9493-d4511eb9cb2d","added_by":"auto","created_at":"2024-12-02 17:25:12","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":558825,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation analysis diagram\u003c/p\u003e","description":"","filename":"13.png","url":"https://assets-eu.researchsquare.com/files/rs-5425572/v1/c1ad12afd96a458e51552333.png"},{"id":82276637,"identity":"72c33e8e-933c-4d06-bf7e-349e74320a82","added_by":"auto","created_at":"2025-05-08 14:46:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7279162,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5425572/v1/5bddadb5-bd46-4fa3-8fa5-85d4188f7341.pdf"},{"id":70387878,"identity":"a1a56966-0cfb-4f08-8d4f-ac9fd0c57b87","added_by":"auto","created_at":"2024-12-02 17:25:12","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":717157,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-5425572/v1/46de56f2ae1e47cf402d4434.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Study on the Blood glucose Regulation function of Lactobacillus plantarum NXU0011 Powder","fulltext":[{"header":"Introduction","content":"\u003cp\u003eType 2 diabetes mellitus (T2DM) is a type of metabolic disorder with insulin resistance and insulin release disorder as its main clinical manifestations (Chen et al., 2022). More than 500 million people worldwide are estimated to have diabetes, affecting men, women and children of all ages and covering every country (Wang et al., 2021). This number is expected to soar over the next 30 years, according to reports, with every country involved\u003csup\u003e\u0026nbsp;\u003c/sup\u003e. In recent years, probiotics have received extensive research attention due to their important role in the pathophysiology of T2DM, such as improving intestinal flora and lowering blood sugar (Wu et al., 2023; Zhang et al., 2021). When there are a large number of probiotics in the intestine, they form a protective layer on the intestinal epithelial cells, consume glucose, and prevent a large amount of glucose from being absorbed by the intestine. Therefore, greatly reducing the amount of glucose in the blood will lower the blood sugar concentration (Paquette et al., 2023; Salga\u0026ccedil;o et al., 2019). In addition, probiotics can also reduce the concentration of lipopolysaccharide (LPS), reduce inflammatory response (Liu et al., 2024), improve insulin sensitivity, improve insulin resistance blood sugar, and thus achieve the purpose of preventing diabetes (Arriaga-Morales et al., 2023; Wang et al., 2020).\u003c/p\u003e\n"},{"header":"Materials and equipment","content":"\u003ch2\u003e1.1 Materials and reagents\u003c/h2\u003e\n\u003cp\u003e\u003cem\u003eLactobacillus plantarum\u003c/em\u003e NXU0011 (\u003cem\u003eL. plantarum\u003c/em\u003e NXU0011) was obtained from Ningxia Key Laboratory of Characteristic Resources Food and biological Manufacturing Control (Yinchuan, China). It is now preserved in the Preservation and Management Center of the China General Microbiological Culture Collection Center (CGMCC No. 26970).\u003c/p\u003e\n\u003cp\u003e\u0026alpha;-amylase, \u0026alpha;-glucosidase were purchased from Qingdao Haibo Biotechnology Co., LTd. Metformin hydrochloride and streptozotocin (STZ) were purchased from Shanghai McLean Biochemical Technology Co., Ltd. Glutathione peroxidase (GSH-Px) and total superoxide dismutase (SOD) determination kits were purchased from Nanjing Jiancheng Institute of Biological Engineering. Enzyme-linked immunosorbent assay (ELISA) kits Rat FINS ELISA Kit, Rat GHbA1c ELISA Kit were purchased from Shanghai Zucai Biotechnology Co., Ltd. Methanol and acetonitrile were purchased from Thermo Fisher Scientific. 2-chloro-L-phenylalanine (internal standard reference material) were purchased from Aladdin. Formic acid were purchased from TCI. Ammonium formate were purchased from Sigma. Agarose were purchased from Invitrogen. Marker were purchased from Takara. Omega E.Z.N.A.\u0026reg; Soil DNA Kit were purchased from Omega. Fast Pfu Polymerase were purchased from TransStart. AMPure XP beads were purchased from Beckman. Quant-iT PicoGreen dsDNA Assay Kit were purchased from Invitrogen. TAE Buffer were purchased from Invitrogen. Gel DNA recovery kit were purchased from Axygen. Vazyme VAHTSTMDNA Clean Beads were purchased from Nanjing Nuovezan Biotechnology Co., Ltd. NovaSeq 6000 SP Reagent Kit were purchased from Illlumina.\u003c/p\u003e\n\u003cp\u003eTwenty four 3-week-old SPF male C57BL/6J mice were purchased from Chengdu Dashuo Experimental Animal Co., Ltd. (Chengdu, China) and kept under a constant temperature of 20-26℃, a relative humidity of 40%\u0026ndash;60%, and a 12 h light/dark cycle. The ethical approval number for the animal experiments is LLSN-2023005.\u003c/p\u003e\n\u003cp\u003eMaintenance feed was provided by Chengdu Dashuo Experimental Animal Co., Ltd. High-fat feed (XTHF60) was from Jiangsu Cooperative Pharmaceutical and Biological Engineering Co., Ltd.\u003c/p\u003e\n\u003ch2\u003e1.2 Instruments and equipment\u003c/h2\u003e\n\u003cp\u003eGA-3 blood glucose meter purchased in Sannuo Biosensor Co., Ltd. Finally an enzyme-labeling instrument (SpectraMAX Plus384) purchased in Meigu Molecular Instrument Co., Ltd. Refrigerated centrifuge and Vacuum concentrator purchased in eppendorf. Multi-tube vortex mixer purchased in Hangzhou Aosheng Instrument Co., Ltd. Membranes purchased in Tianjin Jinteng Experimental Equipment Co., Ltd. Liquid chromatography, mass spectrometry and Nanodrop purchased in Thermo Fisher Scientific. Electrophoresis apparatus purchased in Beijing Liuyi Biotechnology Co., Ltd. Gel imaging system purchased in Beijing Baijing Biotechnology Co., Ltd. Fluorescence spectrophotometer purchased in Hitachi Scientific Instruments (Beijing) Co., Ltd.\u003c/p\u003e\n\u003ch2\u003e1.3 Experimental methods\u003c/h2\u003e\n\u003ch3\u003e1.3.1 Measurement of blood glucose lowering index and digestive stress ability\u003c/h3\u003e\n\u003cp\u003eFor details of the method used to determine the inhibition rates of \u0026alpha;-amylase and \u0026alpha;-glucosidase, please refer to Hongyu Wang (Wang \u0026amp; Li, 2022). Lysozymes (100 mg), pepsin (3 g/L), 0.1% trypsin, and 0.15% bovine bile salt were added to simulated saliva, gastric juice, and intestinal buffer, respectively, followed by stirring (Table 1). Hydrochloric acid was used to adjust the pH to 7.0, 3.0, and 8.0, with a 0.22 \u0026mu;m filter membrane used to remove bacteria.\u003c/p\u003e\n\u003cp\u003eTable 1 Simulated buffer ratio\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eIngredient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eSaliva（pH 7.0）mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eGastric fluid（pH 3.0）mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003eIntestinal fluid（pH 8.0）mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eKCl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e15.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e6.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eKH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eNaCl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e47.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e38.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eNaHCO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e13.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eMgCl\u003csub\u003e2\u003c/sub\u003e(H\u003csub\u003e2\u003c/sub\u003eO)\u003csub\u003e6\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e(NH\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003eCO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eCaCl\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003eL. plantarum\u003c/em\u003e NXU0011 bacterial suspension was incubated in simulated saliva, gastric juice, and intestinal juice at 37℃ for 5 min, 3 h and 2 h, respectively, and survival rates were then calculated.\u003c/p\u003e\n\u003ch3\u003e1.3.2 Design of animal experiments\u003c/h3\u003e\n\u003cp\u003eAll mice had free access to a normal diet and water during the 3-day adaptation period. Subsequently, 24 mice were randomly divided into a control group (CN), model group (DM), metformin hydrochloride group (MH), \u003cem\u003eL. plantarum\u003c/em\u003e NXU0011 group (HLP; 1 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e colony-forming units CFU/mL).\u003c/p\u003e\n\u003cp\u003eFor 6 weeks, the CN group was fed a normal maintenance diet (10% energy from fat), and the other groups were fed a high-fat diet (60% energy from fat). STZ was dissolved in 50 mmol/L citric acid buffer and protected from light. Experimental group animals were injected intraperitoneally with 100 mg/kg fresh STZ, and the same dose of citric acid/sodium citrate buffer salt was injected into CN group animals. T2DM was established via two injections with a 3-day interval. The model was considered successful when the fasting blood glucose of the mice was 7.0 mmol/L, the 2-h postprandial blood glucose level was 11.0 mmol/L, or the blood glucose level of the DM group was \u0026gt; 50% higher than that of the CN group. In week 8, 10 mg/kg body weight (BW) metformin hydrochloride was given to the MH group, whereas the HLP groups were fed 1 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e CFU/mL \u003cem\u003eL. plantarum\u003c/em\u003e NXU0011 powder, respectively, for 4 weeks. The experimental methods and groups are detailed in Table 2.\u003c/p\u003e\n\u003cp\u003eTable 2 Animal experiments and grouping methods\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003eModeling period (6 weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eSTZ stage (1 week)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eGavage period (4 weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003eControl group（CN）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003eMaintenance feed and distilled water\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eCitric acid - Sodium citrate buffer salt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eNormal saline 10\u0026nbsp;mg/(kg\u0026middot;bw)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003eModel group（DM）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003eHigh-fat feed and distilled water\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eSTZ 100 mg/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eNormal saline 10\u0026nbsp;mg/(kg\u0026middot;bw)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003eMetformin hydrochloride group（MH）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003eHigh-fat feed and distilled water\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eSTZ 100 mg/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eMetformin hydrochloride 10\u0026nbsp;mg/(kg\u0026middot;bw)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cem\u003eL. plantarum\u003c/em\u003e NXU0011 group（HLP）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003eHigh-at feed and distilled water\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eSTZ 100 mg/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cem\u003eL. plantarum\u003c/em\u003e NXU00111\u0026times;10\u003csup\u003e9\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003eCFU/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAfter the final intragastric administration, the mice fasted for 12 h, blood was taken from the orbit, and the mice were killed via intraperitoneal injection of 0.5 mL (10 g/kg BW) of pentobarbital sodium solution. One blood sample was added to each anticoagulant tube, and the serum was centrifuged and stored at -80℃. Fresh fecal samples were preserved at -80\u0026deg;C for testing. Pancreatic tissue was rinsed with precooled saline and stored in formalin. The liver and colon tissues were weighed and divided into two parts, one preserved in formalin and the other in liquid nitrogen.\u003c/p\u003e\n\u003ch3\u003e1.3.3 Test index\u003c/h3\u003e\n\u003cp\u003eBW and food intake were recorded every 7 days. After the last gavage, the mice fasted for 8 h and were given a 2 g/kg BW glucose solution. Blood glucose was measured at 15, 30, 60, 90 and 120 min. Based on oral glucose tolerance test (OGTT) data, a change curve was drawn, and the area under the curve (AUC) was calculated.\u003c/p\u003e\n\u003cp\u003eFasting serum insulin (FINS), glycosylated hemoglobin (HbAlc), total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C).\u003c/p\u003e\n\u003ch3\u003e1.3.4 Metagenomics methods\u003c/h3\u003e\n\u003cp\u003eMo Bio/QIAGEN\u0026apos;s Omega E.Z.N.A.\u0026reg; Soil DNA Kit was used for extraction, and the extracted DNA was tested. Quantifluor-ST fluorometer (Promega, E6090; Quant-iT Pico Green dsDNA Assay Kit, Invitrogen, P7589), to determine the absorbance value of DNA at 260 nm and 280 nm, respectively, to detect the concentration of DNA, and to determine the quality of DNA by 1% agarose-gel electrophoresis. The concentration of DNA solution was adjusted, the DNA working solution was stored at 4℃, and the storage solution was stored at -20℃. The standard Illumina TruSeq DNA Sample Preparation Guide was used to construct the required genomic computer library.\u003c/p\u003e\n\u003ch3\u003e1.3.5 Non-targeted metabolomics approaches\u003c/h3\u003e\n\u003cp\u003eThe experimental samples were thawed at 4℃, and after thawing, the samples swirled for 1 min and were mixed evenly. Precise transfer of appropriate sample into 2 mL centrifuge tube; Add 400 \u0026micro;L methanol solution and swirl for 1 min. Centrifuge at 12000 rpm for 10 min at 4℃, take all the supernatant, transfer it to a new 2 mL centrifuge tube, concentrate and dry; The sample was accurately redissolved with a 2-chlorine-L-phenylalanine (4 ppm) solution prepared with 150\u0026micro;L 80% methanol water. The supernatant was filtered through a 0.22\u0026mu;m membrane, and the filtrate was added to the test bottle for LC-MS detection. For chromatographic conditions and for mass spectrometry refer to the method of Zhang Q et al. (Zhang et al., 2016).\u003c/p\u003e\n\u003ch2\u003e1.4 Statistical analysis\u003c/h2\u003e\n\u003cp\u003eSPSS software (ver. 27.0; IBM Corp., Armonk, NY, USA) was used to analyze the data. Analysis of variance (ANOVA) was performed, with Tukey\u0026rsquo;s post hoc test applied for multiple comparisons. Depending on the homogeneity of variance, Tamhane\u0026apos;s T2 test or the least significant differences test was performed for between- and within-group analyses. RXCMS software package was used for peak detection, peak filtering and peak alignment processing, R language Ropls package was used for multivariate statistical analysis, excel was used for metabolite screening, MEGA7 and Origin 2021 were used for mapping.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003e2.1 Results of digestive stress capacity measurement\u003c/h2\u003e\n\u003cp\u003eThe inhibition rates of \u0026alpha;-amylase and \u0026alpha;-glucosidase were 85.35% and 51.74%, respectively. The survival rates of \u003cem\u003eL. plantarum\u003c/em\u003e NXU0011 after exposure to simulated saliva, gastric juice, and intestinal juice were 119.81%, 39.27%, and 122.52%, respectively.\u003c/p\u003e\n\u003ch2\u003e2.2 Determination of fasting and postprandial blood glucose concentrations\u003c/h2\u003e\n\u003cp\u003eAfter 7 weeks of STZ injections, the fasting and 2-h postprandial blood glucose concentrations were measured (Figure1). As shown in Table 3, the fasting blood glucose level in the CN group was 4.48 mmol/L, and the 2-h postprandial blood glucose level was 7.77 mmol/L. In the other groups, fasting blood glucose exceeded 7 mmol/L, and the 2-h postprandial blood glucose exceeded 11 mmol/L. Therefore, the T2DM mouse model was established successfully.\u003c/p\u003e\n\u003cp\u003eTable 3 Blood glucose changes in mice during the STZ period (\u0026plusmn;SD\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eFasting blood glucose（mmol/L）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003e2h postprandial blood glucose（mmol/L）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eCN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003e4.48\u0026plusmn;0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003e7.77\u0026plusmn;1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003e12.98\u0026plusmn;1.26*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003e14.82\u0026plusmn;2.13*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eMH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003e12.13\u0026plusmn;0.70*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003e14.47\u0026plusmn;1.97*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eHLP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003e13.42\u0026plusmn;1.72*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003e15.00\u0026plusmn;2.84*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eDuring the drug and probiotic intervention, the fasting blood glucose and 2 h postprandial blood glucose changes of the mice were monitored regularly every week, as shown in Figure 1. The fasting blood glucose of mice in CN group was basically maintained within the range of 4.48-5.47 mmol/L, which was significantly different from that in DM group. At the 11th week, DM and HLP showed a significant downward trend, in which the fasting blood glucose in the DM group was decreased due to the non-continuous intake of high-fat diets, and the fasting blood glucose in the HLP group dropped to 6.13 mmol/L, which was close to the value of the CN group and significantly lower than that of the DM and MH groups (p\u0026lt;0.05). The intervention effect of the HLP group was significant. 2 h postprandial blood glucose was significantly different between CN group and DM group (p\u0026lt;0.05), and decreased to 11.57mmol/L in HLP group, which was significantly different from MH group. The results showed that NXU0011 has a potential effect on the reduction of fasting and 2 h postprandial blood glucose levels in diabetic mice.\u003c/p\u003e\n\u003cp\u003e2.3 Determination of biochemical indexes\u003c/p\u003e\n\u003cp\u003eAs shown in Figure 2, the HbAlc and FINS levels of the DM group were significantly different to those of the CN group (p \u0026lt; 0.05). After the intervention, the HbAlc and FINS levels of the MH and HLP groups decreased significantly (p \u0026lt; 0.05). The results indicate that the effect of \u003cem\u003eL. plantarum\u0026nbsp;\u003c/em\u003eon HbAlc and FINS levels in mice is comparable to that of drugs, and the bacteria can improve the biochemical indices of diabetes and alleviate metabolic disorder in diabetic mice.\u003c/p\u003e\n\u003ch2\u003e2.4 Determination of blood lipid levels\u003c/h2\u003e\n\u003cp\u003eDyslipidemia is an important cause of T2DM, and the results are shown in Table 4.\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/122228_c8a1650c59388082/122228_custom_files/img1733155990.png\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eDyslipidemia is a major cause of T2DM. As shown in Table 4, the blood lipid levels in the DM group were significantly different to those in the CN group (p \u0026lt; 0.05), and the levels of TC, TG and HDL-C in the HLP group were significantly different to those in the DM group (p \u0026lt; 0.05). Overall, the data indicate that \u003cem\u003eL. plantarum\u003c/em\u003e NXU0011 can improve blood lipid levels in diabetic mice.\u003c/p\u003e\n\u003ch2\u003e2.5 Metagenomics results\u003c/h2\u003e\n\u003ch3\u003e2.5.1 Species composition\u003c/h3\u003e\n\u003cp\u003eIn order to explore whether \u003cem\u003eL. plantarum\u003c/em\u003e NXU0011 can improve the intestinal flora structure and abundance of diabetic mice, the top 20 species in overall abundance of the 4 groups of mice were compared respectively, and the results were shown in Figure 3.\u003c/p\u003e\n\u003cp\u003eAccording to Figure 3, the relative abundance of Ulum rodentium in the CN group was the lowest, while the relative abundance of Ulum rodentium in MH and HLP groups decreased compared with that in DM group. Leclercia adecarboxylata had the highest relative abundance in CN group. Diabetes mellitus caused a sharp decline in Leclercia adecarboxylata relative abundance, and the relative abundance of Leclercia adecarboxylata could be reversed after bacterial powder intervention. The relative abundance of Leclercia adecarboxylata in MH group is lower (Scheithauer et al., 2020).\u003c/p\u003e\n\u003ch3\u003e2.5.2 Species Alpha diversity\u003c/h3\u003e\n\u003cp\u003eIn order to compare the intestinal flora richness of mice in different groups, explore the change trend of Alpha diversity of selected samples with the extraction depth, and Shannon index is more sensitive to flora richness and rare species, ASV/OTU number of samples in different groups can be compared under the same sequencing depth. To some extent, the diversity of each sample can be measured, and the results are shown in Figure 4.\u003c/p\u003e\n\u003cp\u003eThe Shannon exponential curve in Figure 4A shows that with the increase of sequencing depth, the number of species detected in the sample increases rapidly. Apha diversity analysis reflected the species diversity of a single sample. Under the intervention of bacterial powder, the Alpha diversity of HLP group was higher than that of CN group. With the continuous increase of sequencing volume, Shannon curve has become flat. Even with the increase of sequencing volume, the increase of microbial diversity makes little contribution, indicating that the sequencing volume of this experiment is sufficient to reflect the majority of species information in the samples, and also indicates that the sequencing data volume of this experiment meets the requirements. The species accumulation curve is shown in Figure 4B. The curve has a significant upward trend, indicating that the total number of species in the mouse intestine is increasing. The accumulation curve then shows a steady trend, indicating that the current sample size (12 samples) is sufficient to reflect the richness of intestinal flora. In the sparse curve, the Shannon index of the HLP group was close to that of the CN group, while that of the DM group was close to that of the MH group, which might be because drugs could not regulate the intestinal flora of diabetic mice, while the bacterial powder made the intestinal flora Shannon index of the HLP group more normal.\u003c/p\u003e\n\u003ch3\u003e2.5.3 Species \u0026beta; diversity\u003c/h3\u003e\n\u003cp\u003e\u0026beta; diversity analysis can directly reflect the difference of intestinal flora community composition between different experimental groups, reflecting the diversity difference degree between samples. PCoA analyzed the impact of different intervention methods on the intestinal flora community composition of diabetic rats, and the results are shown in Figure 5.\u003c/p\u003e\n\u003cp\u003eAs can be seen from Figure 5A, in the principal coordinate analysis, the contribution rate of the first and second principal coordinates was 23.8% and 15.2%, respectively, and the cumulative contribution rate was 39%. A small number of samples overlapped between MH group and DM group, and the blank group was obviously separated from DM group, indicating that the intestinal flora of diabetic mice had undergone significant changes, and there was a small overlap between MH group and DM group. However, the separation effect of HLP group and DM group was better, indicating that the effect of bacterial powder intervention was better than that of metformin hydrochloride to a certain extent, which played a regulatory role in intestinal flora. In addition, the intestinal flora samples of CN group were furthest away from those of HLP group after the intervention of bacteria powder, indicating that the structure and composition of intestinal flora were the most different. The distance between MH group and HLP group was similar, which proved that the effects of \u003cem\u003eL. plantarum\u003c/em\u003e powder and drugs were similar, and both could intervene in diabetes. Figure 5B The distribution and distance of each group of sample points in the NMDS diagram showed differences in microbial communities that were roughly the same as those in the PCoA diagram. Meanwhile, the Stress of the analysis was 0.073\u0026lt;0.2, indicating that the analysis results were accurate and reliable.\u003c/p\u003e\n\u003ch3\u003e2.5.4 Species differences\u003c/h3\u003e\n\u003cp\u003eAt the species level, LEfSe and PLS-DA were used to further analyze the differences of common and unique species in each group, and the results were shown in Figure 6.\u003c/p\u003e\n\u003cp\u003eAs can be seen from Figure 6A, 228 microbial species overlapped in each group at the species level, while 82, 77, 192 and 34 microbial species were unique to DM, CN, MH and HLP groups. The evolutionary branching tree of microbial community structure differences in each group was obtained by LEfse, which showed that the sample microbial communities in each group had relatively large differences in various taxonomic levels. The results in Figure 6B showed the classification and rank relationship of the main taxonomic units of mouse intestinal colonies from phylum to species (from inner circle to outer circle). \u003cem\u003eBifidobacterium animaliss\u003c/em\u003e, \u003cem\u003eLactobacillus acidophilus\u003c/em\u003e and \u003cem\u003eAkkermansia-muciniphila\u003c/em\u003e in HLP group were significantly different and enriched. There were significant differences among the 17 strains of Rhodococcus pyridinivorans and Rhodococcus gingshengif in MH group (p\u0026lt;0.05) and they were enriched. DM group \u003cem\u003eStaphylococcuscohniis\u003c/em\u003e, \u003cem\u003eStaphwlococcus haemolyticus\u003c/em\u003e, \u003cem\u003eStaphylococcu-snepalensis\u003c/em\u003e, \u003cem\u003eStaphylococcu-spseudintermedius\u003c/em\u003e, \u003cem\u003eStaphyloc occu-spseudoxylosus\u003c/em\u003e and other species levels were significantly different among 13 strains (p\u0026lt;0.05) and enriched. At the species level of CN group, \u003cem\u003eBacteroides-zoogleoformans\u003c/em\u003e, \u003cem\u003eChryseobacterium-indoloqenes\u003c/em\u003e, \u003cem\u003eLactobacillus-johnsonii\u003c/em\u003e and \u003cem\u003eLimosilactobacillus-reuteri\u003c/em\u003e were present Differences and enrichment between groups. Studies have shown that \u003cem\u003eAkkermansia-muciniphila\u003c/em\u003e is negatively correlated with T2DM (Gurung et al., 2020). Through species difference analysis, it was found that bacteria powder enriched \u003cem\u003eAkkermansia-muciniphila\u003c/em\u003e in mice with T2DM and had a significant difference (p\u0026lt;0.05).\u003c/p\u003e\n\u003ch3\u003e2.5.5 Function Components\u003c/h3\u003e\n\u003cp\u003eIn order to further compare the effects of different intervention methods on diabetic mice, KO abundance corresponding to each protein was obtained through KO results, and the number of annotated KEGG metabolic pathways of different grades and classifications was counted, as shown in Figure 7.\u003c/p\u003e\n\u003cp\u003eAs can be seen from Figure 7, after the inadministration of bacterial powder of \u003cem\u003eL. plantarum\u003c/em\u003e NXU0011, the functional annotation of intestinal flora in diabetic mice was put into the pathway. Carbohydrate metabolism, Amino acid metabolism, and Energy metabolism are secondary metabolites in the metabolism pathway metabolism, Nucleotide metabolism and other pathways related to the remission of diabetes have been improved\u003csup\u003e\u0026nbsp;\u003c/sup\u003e(Li et al., 2020). It is concluded that the bacterial powder of \u003cem\u003eL. plantarum\u003c/em\u003e NXU0011 can alleviate diabetes by regulating the structure of intestinal flora and activating related metabolic pathways. Sun et al. (Jang et al., 2017) studied the fermented red ginseng with probiotics, which can reduce the elevated blood sugar caused by diabetes and enhance the low sugar tolerance. More and more articles have shown that probiotics can alleviate T2DM(Gu et al., 2022; Hampe \u0026amp; Roth, 2017).\u003c/p\u003e\n\u003ch2\u003e2.6 Metabolomics results\u003c/h2\u003e\n\u003ch3\u003e2.6.1 Data inspection and quality control\u003c/h3\u003e\n\u003cp\u003eIn order to obtain metabolomic results with stability and accuracy, the ion base peak chromatogram was visually examined, and all BPC maps of each group were overlapped under the same conditions, as shown in Figure 8.\u003c/p\u003e\n\u003cp\u003eThe basic peak chromatogram of the positive ion mode is shown in Figure 8A. The signal strength and retention time of the obtained total ion chromatogram are basically consistent, indicating that the sample detection stability is good, and the experimental data are reliable and true. Figure 8B is the PCA score chart of QC samples in positive ion mode. In QC samples, the proportion of characteristic peaks with RSD\u0026lt;30% reached 82.1%, indicating good data. For negative ion mode, Figure\u0026nbsp;A1. In Figure 8C, the QC sample aggregation trend is obvious, and the 95% confidence interval proves that the sample data is reliable, and the experimental results are less affected by external factors.\u003c/p\u003e\n\u003ch3\u003e2.6.2 Multivariate statistics\u003c/h3\u003e\n\u003cp\u003eIn order to master the overall situation of the data, samples with poor repeatability (outlier samples) or abnormal samples were found and removed to improve the accuracy of the model and multivariate statistical analysis was carried out on the samples. The results are shown in Figure 9 and 10.\u003c/p\u003e\n\u003cp\u003eAs can be seen from Figure 9, the R\u003csup\u003e2\u003c/sup\u003eX of PCA score plots for positive ion mode were all greater than 0.5, and the aggregation and repeatability within each group were good, and the differentiation between groups was obvious (p\u0026lt;0.05), so there were significant differences among all groups. For negative ion mode, see Figure A2. OPLS-DA was used to further analyze the data of each group. In the OPLS-DA score chart, the values of R\u003csup\u003e2\u003c/sup\u003eX, R\u003csup\u003e2\u003c/sup\u003eY and Q\u003csup\u003e2\u003c/sup\u003e in positive ion mode were 0.287, 0.995 and 0.719, respectively (Fig. 10A). In the negative ion mode, the R\u003csup\u003e2\u003c/sup\u003eX, R\u003csup\u003e2\u003c/sup\u003eY and Q\u003csup\u003e2\u003c/sup\u003e values are 0.376, 0.990 and 0.801, respectively (Figure A3 A). In order to further verify whether the model is overfitting, the replacement method is used to verify the OPLS-DA model. The results show that R\u003csup\u003e2\u003c/sup\u003e is 0.99 and 0.98 respectively in positive and negative ions, and the intercept of Q\u003csup\u003e2\u003c/sup\u003e regression line is -0.06 and -0.02 respectively in positive and negative ions, indicating good prediction ability and no overfitting phenomenon. The negative ion model is shown in Figure A3 B.\u003c/p\u003e\n\u003ch3\u003e2.6.3 Serum differential metabolite screening\u003c/h3\u003e\n\u003cp\u003eBased on OPLS-DA model, different groups were compared with VIP\u0026gt;1 and P\u0026lt;0.01 as screening criteria, and the results were shown in Table 5.\u003c/p\u003e\n\u003ch2\u003eTable 5 compares different metabolites in different groups\u003c/h2\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eCompare groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003ename\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003emz\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003eFC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eP.value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eVIP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eDM vs CN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eAgmatine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e130.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e2.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eHomocitrulline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e190.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e3.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eDodecanoic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e199.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e7.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003ePorphobilinogen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e226.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eL-Formylkynurenine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e237.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eAnserine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e241.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e2.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eN2-Succinyl-L-arginine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e275.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e2.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e10-Nitrolinoleic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e308.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e5.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e5-Aminopentanoic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e116.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e4.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eTartaric acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e149.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e8.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eL-Gulose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e161.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003ePhenyllactate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e165.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e5.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eOxalosuccinic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e190.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eD-Tryptophan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e204.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e1,3,7-Trimethyluric acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e209.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e1-Hexadecanol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e242.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e3.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eStearidonic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e275.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eGuanosine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e283.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eErucic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e337.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eSphingosine 1-phosphate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e378.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e3.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eCelecoxib\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e380.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e2.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eHLP vs CN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003ep-Aminobenzoic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e138.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eO-Phosphoethanolamine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e141.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eN-Methyl-L-glutamic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e144.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e(S)-5-Amino-3-oxohexanoate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e146.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e3-Amino-4-hydroxybenzoate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e154.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eL-Histidine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e156.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eSuberic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e157.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eQuinolinic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e167.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eQuinaldic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e174.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eAzelaic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e188.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eAnserine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e241.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003ePhenylacetylglutamine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e265.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003ePalmitoylethanolamide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e300.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e2.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eDihydrocapsaicin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e308.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003e10-Nitrolinoleic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e308.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e10.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eProstaglandin E3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e350.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eS-Adenosylhomocysteine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e384.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eAvermectin B1b aglycone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e570.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e2.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eEthylmethylacetic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e101.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e3.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eo-Toluate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e135.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eThreonic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e135.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eOxalosuccinic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e190.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eD-Erythritol 4-phosphate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e201.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eD-Tryptophan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e204.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003ealpha-D-Ribose 1-phosphate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e229.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eUridine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e243.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e2.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eStearidonic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e275.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eGuanosine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e283.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eArachidonic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e303.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003ePGA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e335.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eErucic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e337.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eSphingosine 1-phosphate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e378.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e3.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31px;\"\u003e\n \u003cp\u003eSildenafil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e474.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAs can be seen from Table 5, there are 21 metabolites in DM group that are significantly different from CN group. After intervention, a total of 11 metabolites in DM group, such as Homocitrulline, Dodecanoic acid and Porphobilinogen, are significantly upregulated. Agmatine, L-Formylkynurenine, Anserine and other 10 substances were significantly down-regulated. These substances may be involved in the pathogenesis of T2DM (Chen \u0026amp; Gerszten, 2020). The results of HLP and CN groups showed a total of 34 metabolites with significant differences, among which 7 substances such as Palmitoylethanolamide, 10-Nitrolinoleic acid and S-Adenosylhomocysteine were significantly up-regulated (p\u0026lt;0.05). 26 substances, including p-Aminobenzoic acid, O-Phosphoethanolamine, N-Methyl-L-glutamic acid, (S) -5-amino -3-oxohexanoate, were significantly down-regulated. Among them, Guanosine did not change, and Guanserine and 10-Nitrolinoleic acid were higher than those in the model group after bacterial powder intervention. These two substances are highly likely to improve diabetes. The contents of Oxalosuccinic acid, D-Tryptophan, Stearidonic acid, Guanosine, Erucic acid and Sphingosine 1-phosphate decreased after the regulation of the powder. These 6 substances may be associated with the exacerbation of diabetes.\u003c/p\u003e\n\u003cp\u003eThe secondary differential metabolites and groups were bidirectional clustering, and the content of differential metabolites among different groups was compared, as shown in Figure 11.\u003c/p\u003e\n\u003cp\u003eAs can be seen from Figure 11, compared with DM group, metabolites in MH and HLP groups had different degrees of callback after intervention, and gradually approached CN group. And by comparing the metabolites of MH group and HLP group, it can be seen that the expression levels of Hydroxyphenyllactic acid, L-2-Hydroxyglutaric acid, Glutamic acid and N-Acetvlalutamic acid in HLP group were significantly increased. These results indicated that the bacterial powder of Lactobacillus plantarum NXU0011 could regulate and improve the metabolite level of diabetic mice.\u003c/p\u003e\n\u003cp\u003eTo further understand the expression and change trend of substances between the groups, T test was used to analyze significant metabolites between the two groups, as shown in Figure 12.\u003c/p\u003e\n\u003cp\u003eAs shown in Figure 12, 46 substances, including Palmitoylethanolamide and Sphingosine 1-phosphate, were significantly up-regulated in DM group compared with CN group (p\u0026lt;0.05). There were 35 substances, including D-Tryptophan, Anserine, Palmitoylethanolamide, Sphingosine 1-phosphate and Agmatine, which were significantly down-regulated (p\u0026lt;0.05). Compared with CN group, 34 substances including Ciliatine, 8-Hydroxyquinoline, 2, 3-butanediol in MH group were significantly up-regulated (p\u0026lt;0.05). Agmatine, Acetylphosphate, Acetylcholine and D-2-Hydroxyglutaric acid were significantly down-regulated (p\u0026lt;0.05); However, Ethylmethylacetic acid, Avermectin B1 baglycone and other 25 substances in HLP group were significantly up-regulated compared with CN group (p\u0026lt;0.05). There were 68 substances, such as 2-Hydroxybutyric acid, Arachidonic acid and PGA1, which were significantly down-regulated (p\u0026lt;0.05).\u003c/p\u003e\n\u003ch3\u003e2.6.4 KEGG path analysis\u003c/h3\u003e\n\u003cp\u003eMetaboAnalyst was used to conduct KEGG pathway enrichment analysis on the list of differential metabolites, and the results were shown in Table 6.\u003c/p\u003e\n\u003cp\u003eTable 6 Characteristic metabolic pathways in DM group compared with CN group\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003ePathway-name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003eHits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003ePvalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eCompound-name\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eABC transporters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eD-Ribose; L-Leucine; L-Histidine; N-Acetyl-D-glucosamine; D-Xylose; Guanosine; 2\u0026apos;-Deoxyadenosine; Ciliatine; Methyl beta-D-galactoside\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eGnRH signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eArachidonic acid; Cyclic AMP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eFc gamma R-mediated phagocytosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eArachidonic acid; Sphingosine 1-phosphate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eApelin signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eCyclic AMP; Sphingosine 1-phosphate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eOvarian steroidogenesis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eArachidonic acid; Cyclic AMP; Dehydroepiandrosterone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eHedgehog signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eCyclic AMP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eAmino acid metabolism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eL-Histidine; Anserine; N-Acetylhistamine ; 4-Oxoglutaramate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003ePhospholipase D signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eCyclic AMP; Sphingosine 1-phosphate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eCalcium signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eCyclic AMP; Sphingosine 1-phosphate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eLinoleic acid metabolism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eArachidonic acid; 13-L-Hydroperoxylinoleic acid; 9(S)-HPODE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eInsulin secretion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eCyclic AMP; Acetylcholine\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eOxytocin signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eArachidonic acid; Cyclic AMP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eCholinergic synapse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eCyclic AMP; Acetylcholine\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eAmoebiasis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0386\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eArachidonic acid; Cyclic AMP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003ePathways in cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eFumaric acid; Cyclic AMP; Dehydroepiandrosterone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eGastric acid secretion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0444\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eCyclic AMP; Acetylcholine\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eRegulation of lipolysis in adipocytes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0444\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eArachidonic acid; Cyclic AMP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003ePlatelet activation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0444\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eArachidonic acid; Cyclic AMP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eLongevity regulating pathway - multiple species\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eCyclic AMP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eCircadian rhythm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eCyclic AMP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eVasopressin-regulated water reabsorption\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.0483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003eCyclic AMP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAs shown in Table 6, differences between DM group and CN group are significantly enriched in 21 metabolic pathways (p\u0026lt;0.05), and ABC transporters and GnRH signaling pathway are extremely significantly enriched (p\u0026lt;0.01). The Amino acid metabolism pathway was consistent with the metagenomic analysis. There is evidence (Behl et al., 2021) that the overproduction and reduced clearance of lipids and glucose contribute to the emergence of diabetes, and that ABC transporters play a key role in the metabolism and transport of both substances. In the GnRH signaling pathway, Arachidonic acid belongs to the eicosane polyunsaturated fatty acid, which exists in the form of phospholipid on the inner surface of cell membrane and produces nearly 100 small molecule metabolites with different biological activities during metabolism. These metabolites play an extremely important role in the occurrence and development of diabetes (Cardoso et al., 2021; Kosmalski et al., 2022). These results indicate that the body of diabetic mice is in a serious metabolic disorder, and several key metabolic pathways are affected. The metabolic pathways of MH group and CN group were significantly enriched after screening, as shown in schedule 1. A total of 16 metabolic pathways were significantly enriched (p\u0026lt;0.05), among which the first six were extremely significantly enriched (p\u0026lt;0.01). Oxalacetic acid, Fumaric acid, L-Malic acid, Arachidonic acid and other substances participate in many metabolic pathways. In addition, Arachidonic acid can improve T2DM induced by streptomycin in Wistar rats. Analysis of different metabolite pathways between HLP group and CN group showed that a total of 14 metabolic pathways were significantly enriched (p\u0026lt;0.05), and Neuroactive ligand-receptor interaction and Tyrosine metabolism were extremely significantly enriched (p\u0026lt;0.01). The metabolic pathway of HLP and CN groups was compared with that of DM and CN groups, and P value of ABC transporters pathway was increased, from significant enrichment to extremely significant enrichment, indicating that NXU0011 had a alleviating effect on T2DM mice. After comparison between HLP group and MH group, a total of 28 metabolic pathways were significantly enriched (p\u0026lt;0.05), and 13 of them were extremely significantly enriched (p\u0026lt;0.01). L-Glutamic acid and L-Glutamine were involved in multiple metabolic pathways. L-Glutamic acid and L-Glutamine participate in multiple metabolic pathways. Studies have shown that (Padilha et al., 2016) glutamine (Gln) is an important precursor for macromolecule synthesis in the body and a nutrient source for intestinal mucosal cells. It may increase the secretion of glucagon-like peptide-1 (GLP-1) by intestinal L cells, promote the synthesis of liver glycogen, inhibit lipolysis and oxidation, and thus reduce blood sugar. Naveen K V Gundala et al. (Gundala et al., 2018) showed enhanced expression of pro-inflammatory genes, including NF-\u0026kappa;B in the pancreas, in laboratory animals with T2DM. NF-\u0026kappa;B, one of the nuclear transcription factors, is involved in a variety of biological processes and exists in almost all types of mammalian cells. At the same time, NF-\u0026kappa;B can regulate cell survival, differentiation and proliferation, and its functions are related to the regulation of gene expression during body defense, tissue injury, stress and inflammation (Tiderencel et al., 2020). Activation of NF-\u0026kappa;B leads to the transcription of multiple target genes, including cytokines, such as TNF-a, IL-6, and IL-1 (Ye et al., 2024). These pro-inflammatory factors inhibit insulin-induced RS tyrosine phosphorylation and further activate NF-\u0026kappa;B. The NF-\u0026kappa;B pathway is widely recognized as a participant in chronic inflammation and many autoimmune diseases(Lee et al., 2022), with key mechanisms associated with obesity, inflammation, and various metabolic disorders. Studies have further confirmed that down-regulation or inhibition of NF-\u0026kappa;B signaling pathway can weaken Insulin Resistance (IR) in T2DM rats and alleviate symptoms such as obesity and glucose intolerance caused by high fat diet (Chu et al., 2024).\u003c/p\u003e\n\u003ch2\u003e2.7 Metagenomics combined with metabolomics analysis\u003c/h2\u003e\n\u003cp\u003eSpearman correlation test was used for correlation analysis, and the results were shown in Figure 13.\u003c/p\u003e\n\u003cp\u003eAs can be seen from Figure 13A, \u003cem\u003eMuribaculum intestinale\u003c/em\u003e, \u003cem\u003eDuncaniella dubosii\u003c/em\u003e and \u003cem\u003eMuribaculaceae bacterium MF13079\u003c/em\u003e were negatively correlated with 3-Hydroxymethylglutaric acid. Sphingosine 1-phosphate (S1P) was positively correlated with \u003cem\u003eFaecalibaculum rodentium\u003c/em\u003e, \u003cem\u003eDuncaniella dubosii\u003c/em\u003e and \u003cem\u003eMuribaculaceae bacterium MF13079\u003c/em\u003e. \u003cem\u003eFaecalibaculum rodentium\u003c/em\u003e was positively associated with Stearolic acid and Homocitrulline, which have been shown by many authors to be markers of worsening T2DM, Stearolic acid and Homocitrulline inhibit islet cells or induce apoptosis (Slieker et al., 2023). N-benzoyl-d-phenylalanine, a derivative of D-beta-Phenylalanine that is negatively correlated with \u003cem\u003eFaecalibaculum rodentium\u003c/em\u003e, has the same effect as metformin hydrochloride. As can be seen from Figure 11B, Comamonas terrigena was positively correlated with Oleamide and pointed to HLP group and MH group, indicating that this substance and this strain may have a alleviating effect on diabetes. \u003cem\u003eLeclercia adecarboxylata\u003c/em\u003e, \u003cem\u003eLigilactobacitus murus\u003c/em\u003e, \u003cem\u003ePseudomonas putida\u003c/em\u003e, Lumichrome, Homocitrulline, (4Z.7Z,10Z,13Z,16Z,19Z)-Docosahexaenoic acid ethyl ester were all positively correlated and more correlated with DM group. These bacteria and substances may be markers of diabetes. Camila Aguilar Delgado et al. (Delgado et al., 2019) analyzed by alkaline cometometry that 3-Hydroxymethylglutaric acid can damage body DNA. However, the mechanism of 3-Hydroxymethylglutaric acid on diabetes remains to be further studied. RENZO DEANA et al.(Deana et al., 1982) demonstrated through gas-liquid chromatography(GLC) that urine excretion of 3-Hydroxymethylglutaric acid was increased in diabetic people and rats. Therefore, 3-Hydroxymethylglutaric acid is a hallmark metabolite of diabetes.S1P, which is mainly produced by the plasma membrane, is a pleiotropic lipid mediator and phosphorylated product of sphingo kinase 1, mainly expressed in macrophages and mast cells. S1P, after binding with its receptors S1PR1 and S1PR2, can inhibit the apoptosis of islet beta cells, alleviate the inflammatory damage of islet beta cells, promote insulin secretion and increase insulin sensitivity. Slow the progression of diabetes. Sphingosine 1-phosphate (S1P) is positively correlated with \u003cem\u003eFaecalibaculum rodentium\u003c/em\u003e. Jamie Cantrell Stanford et al. (Cantrell Stanford et al., 2012) demonstrated in mice that high sugar can stimulate the production of S1P. S1P plays an important role in regulating glucose homeostasis. A large number of literatures have shown that S1P and ceramide levels increase in liver, adipose tissue, skeletal muscle, pancreas and plasma in obese mice, which is consistent with the results of this study, indicating that S1P can regulate diabetes (Choi \u0026amp; Snider, 2015; Kobayashi et al., 2021; Turner et al., 2013).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eProbiotics adopted in 2002 are recognized as living microorganisms with health benefits for human intake, and the probiotics must maintain vitality in the digestive tract, especially to resist bile salts in the gastrointestinal tract (Hill et al., 2014). Gastric acid has an inhibitory effect on the growth and reproduction of lactic acid bacteria (Wang \u0026amp; Li, 2022). Unfortunately, NXU0011 has a low tolerance to gastric acid, but a good tolerance to bile salt. The survival rate reached 122.52% after simulating the tolerance of saliva-gastric fluid-intestinal fluid. Lactic acid bacteria promote resistance to bile salts by maintaining membrane integrity through surface proteins. Only after the stress of simulated digestion test in vitro, probiotics with high survival rate can better play a role in the human gastrointestinal tract. \u0026alpha;-glucosidase and \u0026alpha;-amylase are two key enzymes involved in carbohydrate digestion. Inhibition of the activity of the two key enzymes can prevent glucose from entering the circulation and reduce blood sugar concentration (Gong et al., 2020). Therefore, the inhibition rate of the two key enzymes is an important indicator of the hypoglycemic ability of probiotics in vitro screening. The results of this study showed that Lactobacillus plantarum NXU0011 has a good inhibitory effect on \u0026alpha;-amylase and \u0026alpha;-glucosidase, which slows down the degradation and absorption of carbohydrates and reduces blood glucose level more efficiently.\u003c/p\u003e\n\u003cp\u003eIn recent years, many lactic acid bacteria have shown their potential to alleviate diabetes symptoms, which has been verified in animal experiments (Wang et al., 2020; Youn et al., 2021). Some lactic acid bacteria can alleviate insulin resistance, lower fasting blood sugar, reduce blood lipids, inflammation and oxidative stress symptoms, and improve apparent symptoms (Wang et al., 2017). In this study, C57BL/6J mice were used to establish a T2DM model. After modeling, mice in each group showed the conditions of polyuria, lethargy, dark yellow dishevelled hair, and emotional irritability. With the intervention of lactic acid bacteria and drugs, the above adverse states of mice in MH and HLP groups could be alleviated and improved. The study also analyzed the fasting and 2h postprandial blood glucose levels of mice, insulin resistance, immune regulation, etc. The results showed that \u003cem\u003eL. plantarum\u003c/em\u003e NXU0011 can significantly alleviate the glucose load capacity of diabetic mice and improve the function of islet cells. In addition, HbA1c can reflect the blood sugar level of diabetic patients for a period of time, that is, the significantly reduced HBA1c of mice in the HLP group also reflects that the symptoms of diabetes are well controlled. T2DM mellitus is accompanied by persistent chronic low-grade inflammation. Although there are no typical signs of inflammation, it involves the same inflammatory pathways and signals, usually manifested as elevated levels of IL-6 and TNF-\u0026alpha;, which may interfere with insulin action by inhibiting insulin signaling pathways. NXU0011 can also alleviate inflammation in mice. It is difficult for a single omics to fully understand the mechanism of T2DM, and multi-omics studies have greater advantages than single omics studies(Yan et al., 2022). Therefore, the aim of this study was to investigate the effect of \u003cem\u003eL. plantarum\u003c/em\u003e NXU0011 on a high-fat diet and streptozotocin induced diabetic mouse model.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe \u0026alpha;-amylase (85.35%) and \u0026alpha;-glucosidase (51.74%) were inhibited by \u003cem\u003eLactobacillus plantarum\u003c/em\u003e NXU0011. After simulated saliva-gastro-intestinal fluid stress, the survival rate was 122.52%, and the vitality remained high. C57BL/6J T2DM mice co-induced by high-fat diet and streptozotocin were treated with \u003cem\u003eL. plantarum\u0026nbsp;\u003c/em\u003eNXU0011 bacterial powder, the weight of the mice tended to be stable, the fasting blood glucose was significantly reduced, and the glucose loading capacity was improved, which played a good role in controlling and improving the symptoms of T2DM.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLactobacillus plantarum\u003c/em\u003e NXU0011 can regulate the relative abundance of \u003cem\u003eLeclercia adecarboxylata\u003c/em\u003e, regulate intestinal flora, regulate metabolites to alleviate diabetes, and improve the pathways associated with alleviating diabetes. Studies have shown that 3-Hydroxymethylglutaric acid may be an indicator of T2DM, Stearolic acid and Homocitrulline are markers of T2DM progression, \u003cem\u003eFaecalibaculum rodentium\u003c/em\u003e was found to be associated with a variety of substances, and the bacteria can affect diabetes. The relationship between \u003cem\u003eFaecalibaculum rodentium\u003c/em\u003e and diabetes can be further explored in the future.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCRediT authorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuan Ji:\u003c/strong\u003e Conceptualization, Formal analysis, Methodology, Software, Writing \u0026ndash; original draft. \u003cstrong\u003eRu Zhai\u003c/strong\u003e:Conceptualization, Formal analysis, Methodology, Software, Writing \u0026ndash; original draft. \u003cstrong\u003eHaiyan Zhang:\u003c/strong\u003e Data curation, Methodology, Software, Visualization. \u003cstrong\u003eLongxuan Huo:\u003c/strong\u003e Investigation, Formal analysis, Resources. \u003cstrong\u003eChen Qiao:\u003c/strong\u003e Data curation, Formal analysis, Resources. \u003cstrong\u003eLin Pan:\u003c/strong\u003e Funding acquisition, Supervision, Writing \u0026ndash; review \u0026amp; editing, All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial The authors declare that they have no known competing financial.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Key R \u0026amp; D Program of Ningxia Hui Autonomous Region (Grant number: 2023BCF01028 \u0026amp; 2023BCF01029 \u0026amp; NYG2024042).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChen, K., Wei, X., Kortesniemi, M., Pariyani, R., Zhang, Y., \u0026amp; Yang, B. (2022). Effects of acylated and nonacylated anthocyanins extracts on gut metabolites and microbiota in diabetic Zucker rats: A metabolomic and metagenomic study. Food Research International, 153, 110978. http://doi.org/10.1016/j.foodres.2022.110978\u003c/li\u003e\n\u003cli\u003eWang, G., Liu, J., Xia, Y., \u0026amp; Ai, L. (2021). Probiotics-based interventions for diabetes mellitus: A review. Food Bioscience, 43, 101172. http://doi.org/10.1016/j.fbio.2021.101172\u003c/li\u003e\n\u003cli\u003eZhang, L., Chu, J., Hao, W., Zhang, J., Li, H., Yang, C., Yang, J., Chen, X., \u0026amp; Wang, H. (2021). Gut Microbiota and Type 2 Diabetes Mellitus: Association, Mechanism, and Translational Applications [Journal Article; Review]. Mediators of Inflammation, 2021, 5110276. http://doi.org/10.1155/2021/5110276\u003c/li\u003e\n\u003cli\u003eWu, J., Yang, K., Fan, H., Wei, M., \u0026amp; Xiong, Q. (2023). Targeting the gut microbiota and its metabolites for type 2 diabetes mellitus. Frontiers in Endocrinology (Lausanne), 14, 1114424. http://doi.org/10.3389/fendo.2023.1114424\u003c/li\u003e\n\u003cli\u003ePaquette, S., Thomas, S. C., Venkataraman, K., Appanna, V. D., \u0026amp; Tharmalingam, S. (2023). The Effects of Oral Probiotics on Type 2 Diabetes Mellitus (T2DM): A Clinical Trial Systematic Literature Review. Nutrients, 15(21), 4690. http://doi.org/10.3390/nu15214690\u003c/li\u003e\n\u003cli\u003eSalga\u0026ccedil;o, M. K., Oliveira, L. G. S., Costa, G. N., Bianchi, F., \u0026amp; Sivieri, K. (2019). Relationship between gut microbiota, probiotics, and type 2 diabetes mellitus. Applied Microbiology and Biotechnology, 103(23-24), 9229-9238. http://doi.org/10.1007/s00253-019-10156-y\u003c/li\u003e\n\u003cli\u003eLiu, N., Yan, X., Lv, B., Wu, Y., Hu, X., Zheng, C., Tao, S., Deng, R., Dou, J., Zeng, B., \u0026amp; Jiang, G. (2024). A study on the association between gut microbiota, inflammation, and type 2 diabetes. Applied Microbiology and Biotechnology, 108(1) http://doi.org/10.1007/s00253-024-13041-5\u003c/li\u003e\n\u003cli\u003eArriaga-Morales, J. J., Ordaz-Pichardo, C., Castro Mu\u0026ntilde;oz, R., \u0026amp; Dur\u0026aacute;n-P\u0026aacute;ramo, E. (2023). Attenuation of Hyperglycemia in Diabetic Rats Assisted by Immobilized Probiotic in Sodium Alginate. Probiotics and Antimicrobial Proteins http://doi.org/10.1007/s12602-023-10166-3\u003c/li\u003e\n\u003cli\u003eWang, L., Shang, Q., Guo, W., Wu, X., Wu, L., Wu, L., \u0026amp; Chen, T. (2020). Evaluation of the hypoglycemic effect of probiotics via directly consuming glucose in intestines of STZ-induced diabetic mice and glucose water-induced diabetic mice. Journal of Functional Foods, 64, 103614. http://doi.org/10.1016/j.jff.2019.103614\u003c/li\u003e\n\u003cli\u003eWang, H., \u0026amp; Li, L. (2022). Comprehensive Evaluation of Probiotic Property, Hypoglycemic Ability and Antioxidant Activity of Lactic Acid Bacteria. Foods, 11(9), 1363. http://doi.org/10.3390/foods11091363\u003c/li\u003e\n\u003cli\u003eZhang, Q., Wu, Y., \u0026amp; Fei, X. (2016). Effect of probiotics on glucose metabolism in patients with type 2 diabetes mellitus: A meta-analysis of randomized controlled trials. Medicina, 52(1), 28-34. http://doi.org/10.1016/j.medici.2015.11.008\u003c/li\u003e\n\u003cli\u003eScheithauer, T. P. M., Rampanelli, E., Nieuwdorp, M., Vallance, B. A., Verchere, C. B., van Raalte, D. H., \u0026amp; Herrema, H. (2020). Gut Microbiota as a Trigger for Metabolic Inflammation in Obesity and Type 2 Diabetes. Frontiers in Immunology, 11, 571731. http://doi.org/10.3389/fimmu.2020.571731\u003c/li\u003e\n\u003cli\u003eGurung, M., Li, Z., You, H., Rodrigues, R., Jump, D. B., Morgun, A., \u0026amp; Shulzhenko, N. (2020). Role of gut microbiota in type 2 diabetes pathophysiology. Ebiomedicine, 51, 102590. http://doi.org/10.1016/j.ebiom.2019.11.051\u003c/li\u003e\n\u003cli\u003eLi, X., Wu, Y., Zhao, J., Wang, H., Tan, J., Yang, M., Li, Y., Deng, S., Gao, S., Li, H., Yang, Z., Yang, F., Ma, J., Cheng, J., \u0026amp; Cai, W. (2020). Distinct cardiac energy metabolism and oxidative stress adaptations between obese and non-obese type 2 diabetes mellitus. Theranostics, 10(6), 2675-2695. http://doi.org/10.7150/thno.40735\u003c/li\u003e\n\u003cli\u003eJang, S., Park, J., Kim, S., Choi, K., Ko, E., Cha, J., Lee, Y., Jang, H., \u0026amp; Jang, Y. (2017). Red ginseng powder fermented with probiotics exerts antidiabetic effects in the streptozotocin-induced mouse diabetes model. Pharmaceutical Biology, 55(1), 317-323. http://doi.org/10.1080/13880209.2016.1237978\u003c/li\u003e\n\u003cli\u003eGu, Y., Li, X., Chen, H., Sun, Y., Yang, L., Ma, Y., \u0026amp; Yong Chan, E. C. (2022). Antidiabetic effects of multi-species probiotic and its fermented milk in mice via restoring gut microbiota and intestinal barrier. Food Bioscience, 47, 101619. http://doi.org/10.1016/j.fbio.2022.101619\u003c/li\u003e\n\u003cli\u003eHampe, C. S., \u0026amp; Roth, C. L. (2017). Probiotic strains and mechanistic insights for the treatment of type 2 diabetes. Endocrine, 58(2), 207-227. http://doi.org/10.1007/s12020-017-1433-z\u003c/li\u003e\n\u003cli\u003eChen, Z., \u0026amp; Gerszten, R. E. (2020). Metabolomics and Proteomics in Type 2 Diabetes. Circulation Research, 126(11), 1613-1627. http://doi.org/10.1161/CIRCRESAHA.120.315898\u003c/li\u003e\n\u003cli\u003eBehl, T., Sehgal, A., Grover, M., Singh, S., Sharma, N., Bhatia, S., Al-Harrasi, A., Aleya, L., \u0026amp; Bungau, S. (2021). Uncurtaining the pivotal role of ABC transporters in diabetes mellitus. Environmental Science and Pollution Research International, 28(31), 41533-41551. http://doi.org/10.1007/s11356-021-14675-y\u003c/li\u003e\n\u003cli\u003eCardoso, N. S., Cruz, J. R. D. S., Paula, R. A. D. O., Duarte, S. M. D. S., Rodrigues, M. R., \u0026amp; Paula, F. B. D. A. (2021). Unsaturated fatty acid as functional food for the treatment of Diabetes mellitus type 2. Research, Society and Development, 10(9), e1538755729. http://doi.org/10.33448/rsd-v10i9.17231\u003c/li\u003e\n\u003cli\u003eKosmalski, M., Pękala-Wojciechowska, A., Sut, A., Pietras, T., \u0026amp; Luzak, B. (2022). Dietary Intake of Polyphenols or Polyunsaturated Fatty Acids and Its Relationship with Metabolic and Inflammatory State in Patients with Type 2 Diabetes Mellitus. Nutrients, 14(5), 1083. http://doi.org/10.3390/nu14051083\u003c/li\u003e\n\u003cli\u003ePadilha, K., Venturini, G., de Farias Pires, T., Horimoto, A. R. V. R., Malagrino, P. A., Gois, T. C., Kiers, B., Oliveira, C. M., de Oliveira Alvim, R., Blatt, C., Krieger, J. E., \u0026amp; Pereira, A. C. (2016). Serum metabolomics profile of type 2 diabetes mellitus in a Brazilian rural population. Metabolomics, 12(10), 1. http://doi.org/10.1007/s11306-016-1107-5\u003c/li\u003e\n\u003cli\u003eGundala, N., Naidu, V., \u0026amp; Das, U. N. (2018). Amelioration of streptozotocin-induced type 2 diabetes mellitus in Wistar rats by arachidonic acid [Journal Article]. Biochemical and Biophysical Research Communications, 496(1), 105-113. http://doi.org/10.1016/j.bbrc.2018.01.007\u003c/li\u003e\n\u003cli\u003eTiderencel, K. A., Hutcheon, D. A., \u0026amp; Ziegler, J. (2020). Probiotics for the treatment of type 2 diabetes: A review of randomized controlled trials. Diabetes/Metabolism Research and Reviews, 36(1), e3213. http://doi.org/10.1002/dmrr.3213\u003c/li\u003e\n\u003cli\u003eYe, J., Ma, J., Rozi, P., Kong, L., Zhou, J., Luo, Y., \u0026amp; Yang, H. (2024). The polysaccharides from seeds of Glycyrrhiza uralensis ameliorate metabolic disorders and restructure gut microbiota in type 2 diabetic mice. International Journal of Biological Macromolecules, 264(Pt 1), 130622. http://doi.org/10.1016/j.ijbiomac.2024.130622\u003c/li\u003e\n\u003cli\u003eLee, J., Yang, Y., Tao, Y., Yi, Y., \u0026amp; Cho, J. Y. (2022). Korean Red Ginseng saponin fraction exerts anti-inflammatory effects by targeting the NF-\u0026kappa;B and AP-1 pathways. Journal of Ginseng Research, 46(3), 489-495. http://doi.org/10.1016/j.jgr.2022.02.004\u003c/li\u003e\n\u003cli\u003eChu, C., Ru, H., Chen, Y., Xu, J., Wang, C., \u0026amp; Jin, Y. (2024). Gallic acid attenuates LPS-induced inflammation in Caco-2 cells by suppressing the activation of the NF-\u0026amp;kappa;B/MAPK signaling pathway. Acta Biochimica Et Biophysica Sinica http://doi.org/10.3724/abbs.2024008\u003c/li\u003e\n\u003cli\u003eDelgado, C. A., Balbueno Guerreiro, G. B., Diaz Jacques, C. E., de Moura Coelho, D., Sitta, A., Manfredini, V., Wajner, M., \u0026amp; Vargas, C. R. (2019). Prevention by L-carnitine of DNA damage induced by 3-hydroxy-3-methylglutaric and 3-methylglutaric acids and experimental evidence of lipid and DNA damage in patients with 3-hydroxy-3-methylglutaric aciduria. Archives of Biochemistry and Biophysics, 668, 16-22. http://doi.org/10.1016/j.abb.2019.04.008\u003c/li\u003e\n\u003cli\u003eDeana, R., Lippe, G., \u0026amp; Galzigna, L. (1982). Urinary excretion of 3-hydroxy-3-methylglutaric acid in the diabetic condition [Journal Article]. Clinical Biochemistry, 15(2), 73-75. http://doi.org/10.1016/s0009-9120(82)90832-3\u003c/li\u003e\n\u003cli\u003eCantrell Stanford, J., Morris, A. J., Sunkara, M., Popa, G. J., Larson, K. L., \u0026amp; \u0026Ouml;zcan, S. (2012). Sphingosine 1-Phosphate (S1P) Regulates Glucose-stimulated Insulin Secretion in Pancreatic Beta Cells. The Journal of Biological Chemistry, 287(16), 13457-13464. http://doi.org/10.1074/jbc.M111.268185\u003c/li\u003e\n\u003cli\u003eChoi, S., \u0026amp; Snider, A. J. (2015). Sphingolipids in High Fat Diet and Obesity-Related Diseases [Journal Article; Research Support, Non-U.S. Gov\u0026apos;t; Review]. Mediators of Inflammation, 2015, 520618. http://doi.org/10.1155/2015/520618\u003c/li\u003e\n\u003cli\u003eTurner, N., Kowalski, G. M., Leslie, S. J., Risis, S., Yang, C., Lee-Young, R. S., Babb, J. R., Meikle, P. J., Lancaster, G. I., Henstridge, D. C., White, P. J., Kraegen, E. W., Marette, A., Cooney, G. J., Febbraio, M. A., \u0026amp; Bruce, C. R. (2013). Distinct patterns of tissue-specific lipid accumulation during the induction of insulin resistance in mice by high-fat feeding. Diabetologia, 56(7), 1638-1648. http://doi.org/10.1007/s00125-013-2913-1\u003c/li\u003e\n\u003cli\u003eKobayashi, K., Sasase, T., Ishii, Y., Katsuda, Y., Miyajima, K., Yamada, T., \u0026amp; Ohta, T. (2021). The sphingosine‐1‐phosphate receptor modulator, FTY720, prevents the incidence of diabetes in Spontaneously Diabetic Torii rats. Clinical and Experimental Pharmacology \u0026amp; Physiology, 48(6), 869-876. http://doi.org/10.1111/1440-1681.13405\u003c/li\u003e\n\u003cli\u003eHill, C., Guarner, F., Reid, G., Gibson, G. R., Merenstein, D. J., Pot, B., Morelli, L., Canani, R. B., Flint, H. J., Salminen, S., Calder, P. C., \u0026amp; Sanders, M. E. (2014). Expert consensus document. The International Scientific Association for Probiotics and Prebiotics consensus statement on the scope and appropriate use of the term probiotic [Consensus Development Conference; Journal Article]. Nature Reviews Gastroenterology \u0026amp; Hepatology, 11(8), 506-514. http://doi.org/10.1038/nrgastro.2014.66\u003c/li\u003e\n\u003cli\u003eGong, L., Feng, D., Wang, T., Ren, Y., Liu, Y., \u0026amp; Wang, J. (2020). Inhibitors of alpha-amylase and alpha-glucosidase: Potential linkage for whole cereal foods on prevention of hyperglycemia [Journal Article; Review]. Food Science \u0026amp; Nutrition, 8(12), 6320-6337. http://doi.org/10.1002/fsn3.1987\u003c/li\u003e\n\u003cli\u003eWang, H., \u0026amp; Li, L. (2022). Comprehensive Evaluation of Probiotic Property, Hypoglycemic Ability and Antioxidant Activity of Lactic Acid Bacteria. Foods, 11(9), 1363. http://doi.org/10.3390/foods11091363\u003c/li\u003e\n\u003cli\u003eWang, G., Si, Q., Yang, S., Jiao, T., Zhu, H., Tian, P., Wang, L., Li, X., Gong, L., Zhao, J., Zhang, H., \u0026amp; Chen, W. (2020). Lactic acid bacteria reduce diabetes symptoms in mice by alleviating gut microbiota dysbiosis and inflammation in different manners. Food \u0026amp; Function, 11(7), 5898-5914. http://doi.org/10.1039/c9fo02761k\u003c/li\u003e\n\u003cli\u003eYoun, H. S., Kim, J., Lee, J. S., Yoon, Y. Y., Choi, S. J., Lee, J. Y., Kim, W., Hwang, K. W., Freitag, N. E., \u0026amp; Freitag, N. E. (2021). Lactobacillus plantarum Reduces Low-Grade Inflammation and Glucose Levels in a Mouse Model of Chronic Stress and Diabetes. Infection and Immunity, 89(8), e61520. http://doi.org/10.1128/IAI.00615-20\u003c/li\u003e\n\u003cli\u003eYan, J., Li, J., Xue, Q., Xie, S., Jiang, J., Li, P., \u0026amp; Du, B. (2022). Bacillus sp. DU‐106 ameliorates type 2 diabetes by modulating gut microbiota in high‐fat‐fed and streptozotocin‐induced mice. Journal of Applied Microbiology, 133(5), 3126-3138. http://doi.org/10.1111/jam.15773\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Type 2 diabetes mellitus, Lactobacillus plantarum NXU0011, hypoglycemia, metagenomics, metabolomics","lastPublishedDoi":"10.21203/rs.3.rs-5425572/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5425572/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eC57BL/6J mice were studied to evaluate the hypoglycemic function of bacterial powder. The results showed that the bacterial powder had good inhibition ability to α-amylase and α-glucosidase. After the intervention of bacterial powder in diabetic mice, the indexes of fasting blood glucose and insulin level were reduced, and glucose tolerance was improved; the histological results showed that: the alpha diversity of the bacterial powder group (HLP) was improved, and the Shannon index was higher than that of the blank group (CN), \u003cem\u003eBifidobacterium animaliss\u003c/em\u003e, \u003cem\u003eLactobacillus acidophilus\u003c/em\u003e and \u003cem\u003eAkkermansia muciniphila\u003c/em\u003e were enriched and had significant differences. Compared with CN group, the expression levels of Hydroxyphenyllactic acid, L-2-Hydroxy-glutaric acid and Glutamic acid in HLP group were significantly increased. Meanwhile, Carbohydrate metabolism, Amino acid metabolism, Nucleotide metabolism and other related pathways were improved. In summary, the \u003cem\u003eLactobacillus plantarum\u003c/em\u003e NXU0011 powder alleviates diabetes by regulating the intestinal flora and metabolites of mice.\u003c/p\u003e","manuscriptTitle":"Study on the Blood glucose Regulation function of Lactobacillus plantarum NXU0011 Powder","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-02 16:48:47","doi":"10.21203/rs.3.rs-5425572/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":"9755c44e-151c-4f04-950e-8f9b71edc903","owner":[],"postedDate":"December 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-05-08T14:38:41+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-02 16:48:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5425572","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5425572","identity":"rs-5425572","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}