Diabetes ranks among the top 10 causes of death globally, with over 90%90 \% of individuals diagnosed with diabetes having type 2 diabetes mellitus (T2DM). It is acknowledged that a high-fat diet (HFD) poses a serious risk for T2DM. The imbalance of intestinal flora, mediated by HFD, can potentially exacerbate the onset and progression of T2DM. However, the impact of HFD on pathological indicators and the intestinal microbiome in the development of T2DM has not been systematically investigated. Therefore, a HFD mouse model and a T2DM mouse model were established, respectively, in this study. The role of HFD as a driving factor in the development of T2DM was assessed using various measures, including basic pathological indicators of T2DM, lipid metabolism, liver oxidative stress, intestinal permeability, levels of inflammatory factors, gut microbiota, and short-chain fatty acids (SCFAs). The findings indicated that HFD could influence the aforementioned measures to align with T2DM changes, but the contribution of HFD varied across different pathological metrics of T2DM. The impact of HFD on low-density lipoprotein cholesterol, glutathione peroxidase, malondialdehyde, and tumor necrosis factor- alpha\alpha did not show a statistically significant difference from those observed in T2DM during its development. In addition, regarding gut microbes, HFD primarily influenced the alterations in bacteria capable of synthesizing SCFAs. The notable decrease in SCFA content in both serum and cecal matter further underscored the effect of HFD on SCFA-synthesising bacteria in mice. Hence, this research provided a systematic assessment of HFD’s propelling role in T2DM’s progression. It was inferred that gut microbes, particularly those capable of synthesizing SCFAs, could serve as potential targets for the future prevention and treatment of T2DM instigated by HFD. 糖尿病是全球十大死因之一，超过 90%90 \% 被诊断患有糖尿病的个体患有 2 型糖尿病 （T2DM）。众所周知，高脂饮食 （HFD） 会带来 T2DM 的严重风险。HFD 介导的肠道菌群失衡可能会加剧 T2DM 的发生和进展。然而，HFD 对 T2DM 发展中的病理指标和肠道微生物组的影响尚未得到系统研究。因此，本研究分别建立了 HFD 小鼠模型和 T2DM 小鼠模型。使用各种措施评估 HFD 作为 T2DM 发展驱动因素的作用，包括 T2DM 的基本病理指标、脂质代谢、肝脏氧化应激、肠道通透性、炎症因子水平、肠道菌群和短链脂肪酸 （SCFA）。研究结果表明，HFD 可以影响上述措施以与 T2DM 的变化保持一致，但 HFD 的贡献在 T2DM 的不同病理指标中有所不同。HFD 对低密度脂蛋白胆固醇、谷胱甘肽过氧化物酶、丙二醛和肿瘤坏死因子的影响 - alpha\alpha 与 T2DM 在其发育过程中观察到的差异没有统计学上的显着差异。此外，关于肠道微生物，HFD 主要影响能够合成 SCFA 的细菌的改变。血清和盲肠物质中 SCFA 含量的显着降低进一步强调了 HFD 对小鼠 SCFA 合成细菌的影响。因此，本研究系统评估了 HFD 在 T2DM 进展中的推动作用。 据推断，肠道微生物，尤其是那些能够合成 SCFA 的肠道微生物，可以作为未来预防和治疗 HFD 引发的 T2DM 的潜在靶标。
1 Introduction 1 引言
Diabetes poses a major health risk worldwide, and its incidence is rising rapidly. About 537 million adults worldwide have diabetes, a number that is expected to rise to 783 million by 2045.^(1)2045 .{ }^{1} Type 2 diabetes mellitus (T2DM) is the predominant form of diabetes, comprising approximately 90%90 \% of all cases. Alarmingly, the prevalence of T2DM is on the rise among 糖尿病在世界范围内构成重大健康风险，其发病率正在迅速上升。全球约有 5.37 亿成年人患有糖尿病，预计这一数字将上升到 7.83 亿 2 2045.^(1)2045 .{ }^{1} 型糖尿病 （T2DM） 是糖尿病的主要形式，约 90%90 \% 占所有病例。令人担忧的是，T2DM 的患病率正在上升
young children and adolescents. ^(2){ }^{2} Furthermore, rising healthcare costs and productivity losses are placing a significant burden on public health and the socio-economic landscape, a burden that is predicted to increase in the future. ^(3){ }^{3} The clinical hallmarks of T2DM include hyperglycemia, insulin resistance (IR), and pancreatic beta\beta-cell decompensation. Current research suggests that the primary risk factors include age, genetics, lifestyle choices (such as smoking, a high-fat diet (HFD), and sedentary behavior), and physiological factors (like obesity, hypertension, and high cholesterol). ^(4){ }^{4} Among these, the adoption of unhealthy eating habits, driven by the low cost and high availability of high-calorie foods, is becoming a bigger factor in the development of T2DM. ^(5){ }^{5} Specifically, a HFD can disrupt problems with the metabolism of fat and glucose, damage the liver and other key metabolic organs, and gradually lead to conditions such as hyperglycemia, hyperinsulinemia, and progressive IR. ^(6){ }^{6} 幼儿和青少年。 ^(2){ }^{2} 此外，不断上升的医疗保健成本和生产力损失给公共卫生和社会经济格局带来了沉重的负担，预计未来这一负担将会增加。 ^(3){ }^{3} T2DM 的临床特征包括高血糖、胰岛素抵抗 （IR） 和胰腺 beta\beta 细胞失代偿。目前的研究表明，主要风险因素包括年龄、遗传、生活方式选择（如吸烟、高脂肪饮食 （HFD） 和久坐行为）和生理因素（如肥胖、高血压和高胆固醇）。 ^(4){ }^{4} 其中，在高热量食物的低成本和高可用性的推动下，不健康的饮食习惯的采用正在成为 T2DM 发展的更大因素。 ^(5){ }^{5} 具体来说，HFD 会破坏脂肪和葡萄糖的代谢问题，损害肝脏和其他关键代谢器官，并逐渐导致高血糖、高胰岛素血症和进行性 IR 等疾病。 ^(6){ }^{6}
In particular, an HFD can cause problems with the metabolism of fat and glucose, and damage the liver. An increasing 特别是，HFD 会导致脂肪和葡萄糖的代谢问题，并损害肝脏。一个日益增长的
amount of research, both in humans and animals, has highlighted the crucial role that the gut microbiota play in T2DM. The composition of the intestinal microbiome and its interaction with dietary components substantially influence intestinal permeability, glucose and lipid metabolism, insulin sensitivity, and overall energy balance. They also stimulate inflammatory responses, which in turn contribute to the development of T2DM. ^(7){ }^{7} A study by Varela-Trinidad et al. in 2022 has reported differences in the composition of the gut microbiota between adults with diabetes mellitus and healthy control subjects. ^(8){ }^{8} Specifically, reduced by Roseburia intestinalis (butyrateproducing bacteria), Bifidobacterium, Bacteroidetes, Faecalibacterium, Akkermansia, Roseburia, Ruminococcus, Fusobacterium, and Blautia, opportunistic pathogens such as Bacteroides caccae, Clostridium hathewayi, Clostridium ramosum, and EE. coli were added. According to Zeng et al., patients with T2DM have a higher relative abundance of opportunistic pathogenic bacteria and a lower abundance of butyrate-producing bacteria compared to normal subjects. ^(9){ }^{9} Furthermore, it has been reported that microbially derived metabolites, including those derived from amino acids, short-chain fatty acids (SCFAs), trimethylamine NN-oxides, and bile acids, can either protect against or contribute to the development of T2DM. ^(10){ }^{10} However, the specific microbiome implicated in T2DM and the characteristics of its metabolites have been found to vary across different studies. Nonetheless, a consistent finding across T2DM studies is that the microbial flora involved in the synthesis of SCFAs in the gut, as well as the content and composition of SCFAs, undergo significant changes, particularly in the case of butyrate. ^(11){ }^{11} Growing data in recent years have indicated that T2DM may be influenced by the relationship between the gut microbiota and a HFD. ^(12){ }^{12} However, the role of HFD in promoting T2DM development through the gut microbiome and its associated SCFAs has not been thoroughly investigated. To obtain more thorough knowledge of the pathophysiology of HFD-induced T2DM, additional study is necessary to figure out the specific function of HFD in triggering T2DM and to identify markers within the gut microbiome. 对人类和动物的大量研究强调了肠道微生物群在 T2DM 中发挥的关键作用。肠道微生物组的组成及其与膳食成分的相互作用对肠道通透性、葡萄糖和脂质代谢、胰岛素敏感性和整体能量平衡有很大影响。它们还会刺激炎症反应，进而导致 T2DM 的发展。 ^(7){ }^{7} Varela-Trinidad 等人在 2022 年的一项研究报告了成人糖尿病患者和健康对照受试者之间肠道微生物群组成的差异。 ^(8){ }^{8} 具体来说，由肠玫瑰杆菌（产生丁酸盐的细菌）、双歧杆菌、拟杆菌门、粪杆菌门、阿克曼氏菌、玫瑰杆菌、瘤胃球菌、梭杆菌和布劳蒂亚、机会性病原体如芽胞杆菌、哈特瓦伊梭菌、拉莫梭菌和 EE 。大肠杆菌。根据 Zeng 等人的说法，与正常受试者相比，T2DM 患者的机会性病原菌相对丰度较高，产丁酸盐细菌的丰度较低。 ^(9){ }^{9} 此外，据报道，微生物衍生的代谢物，包括来自氨基酸、短链脂肪酸 （SCFA）、三甲胺 NN 氧化物和胆汁酸的代谢物，可以预防或促进 T2DM 的发展。 ^(10){ }^{10} 然而，已发现与 T2DM 相关的特定微生物组及其代谢物的特征在不同的研究中有所不同。 尽管如此，T2DM 研究的一个一致发现是，肠道中 SCFA 合成所涉及的微生物菌群以及 SCFA 的含量和组成发生了显着变化，尤其是在丁酸盐的情况下。 ^(11){ }^{11} 近年来越来越多的数据表明，T2DM 可能受到肠道微生物群与 HFD 之间关系的影响。 ^(12){ }^{12} 然而，HFD 通过肠道微生物组及其相关的 SCFA 促进 T2DM 发展的作用尚未得到彻底研究。为了更全面地了解 HFD 诱导的 T2DM 的病理生理学，需要额外的研究来弄清楚 HFD 在触发 T2DM 中的具体功能并识别肠道微生物组中的标志物。
In this research, a HFD mouse model and a T2DM mouse model were established, respectively. The influence of a HFD on the progression of T2DM was assessed using several parameters. These included basic pathological indicators of T2DM, lipid metabolism, liver oxidative stress, intestinal permeability, gut microbiota, and SCFAs in serum and cecal contents. This was done with the aim of identifying potential therapeutic targets to address this growing healthcare crisis. 在本研究中，分别建立了 HFD 小鼠模型和 T2DM 小鼠模型。使用几个参数评估 HFD 对 T2DM 进展的影响。这些包括 T2DM 的基本病理指标、脂质代谢、肝脏氧化应激、肠道通透性、肠道菌群以及血清和盲肠内容物中的 SCFAs。这样做的目的是确定潜在的治疗靶点，以应对这一日益严重的医疗保健危机。
2 Materials and methods 2 材料和方法
2.1 Animals and experimental design 2.1 动物和实验设计
Fifty C57BL/6J mice (three-weeks-old) were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd (Beijing, China). Mice were kept in an animal housing of SPF grade at 22+-2^(@)C22 \pm 2{ }^{\circ} \mathrm{C}, under 55+-5%55 \pm 5 \% humidity, and under light from 7:00 to 19:00. The mice were split into 5 groups at 50 只 C57BL/6J 小鼠 （3 周龄） 购自北京维塔河实验动物科技有限公司 （中国北京）。将小鼠饲养在 SPF 级动物饲养箱中，在 22+-2^(@)C22 \pm 2{ }^{\circ} \mathrm{C} 7：00 至 19：00 的 55+-5%55 \pm 5 \% 湿度和光照下。将小鼠分成 5 组
random after the 1-week acclimation phase with one another: the 0-day blank group (NC0), the 4 -week blank group (NC4), the HFD model group (HFD), the 5 -week blank group (NC5), and the T2DM model group (T2DM), with 10 mice in each group. The NC0 group was a normal blank group at the end of the acclimatization period. The NC4 and NC5 groups were fed the basal ration for 4 and 5 weeks, respectively. The HFD group was fed a high-fat diet (HFD) for 4 weeks. Mice in the T2DM group were fed a HFD for 4 weeks and then injected intraperitoneally with streptozotocin ( 100 mg per kg bw ) for 1 week. The composition of basic feed and high-fat feed is shown in Table S1, ESI. †\dagger The Northeast Agricultural University’s Guidelines for Care and Use of Laboratory Animals were followed in all animal operations, and the Animal Ethics Committee of the university authorized the research (approval no. SRM-06). 1 周适应期后彼此随机：0 天空白组 （NC0）、4 周空白组 （NC4）、HFD 模型组 （HFD）、5 周空白组 （NC5） 和 T2DM 模型组 （T2DM），每组 10 只小鼠。NC0 组在适应期结束时为正常空白组。NC4 和 NC5 组分别饲喂基础口粮 4 和 5 周。HFD 组饲喂高脂饮食 （HFD） 4 周。T2DM 组小鼠喂食 HFD 4 周，然后腹膜内注射链脲佐菌素 （100 mg/kg bw） 1 周。碱性饲料和高脂饲料的成分如表 S1 所示，ESI。 †\dagger 东北农业大学的所有动物作都遵循了《实验动物护理和使用指南》，该大学的动物伦理委员会授权了这项研究（批准号。SRM-06）。
2.2 Body weight and fasting blood glucose (FBG) 2.2 体重和空腹血糖 （FBG）
When the experiment came to an end, following a 16 -hour fast, the mouse weight was recorded, and a glucose meter (Roche Diagnostics, Germany) was used to calculate their FBG. 当实验结束时，在禁食 16 小时后，记录小鼠体重，并使用葡萄糖仪（Roche Diagnostics，德国）计算它们的 FBG。
2.3 Oral glucose tolerance test (OGTT) 2.3 口服葡萄糖耐量试验 （OGTT）
Prior to the experiment’s termination, mice were administered a glucose solution at a dose of 2gkg^(-1)2 \mathrm{~g} \mathrm{~kg}^{-1} after being weaned from water for 16 h . The mouse blood glucose levels were assessed at 0,30,60,900,30,60,90, and 120 minutes following intragastric injection, and the area under the curve (AUC) was calculated. 在实验结束前，小鼠在断奶 16 小时后给予一定剂量的 2gkg^(-1)2 \mathrm{~g} \mathrm{~kg}^{-1} 葡萄糖溶液。在胃内注射后 和 120 分钟评估 0,30,60,900,30,60,90 小鼠血糖水平，并计算曲线下面积 （AUC）。
2.4 Collection of samples 2.4 样本采集
Mice were killed with ether anesthesia after eyeball blood extraction, and were left at room temperature for 2 h to wait for serum precipitation. Centrifugation was performed at 3000 g at 4^(@)C4^{\circ} \mathrm{C} for 10 min , and the upper serum was carefully absorbed and stored in a frozen tube at -80^(@)C-80^{\circ} \mathrm{C} for later use. Pancreas, colon tissues, and cecal contents were isolated from every animal for further measurement. 提取眼球血后用乙醚麻醉杀死小鼠，并在室温下放置 2 小时等待血清沉淀。以 3000 g 离心 4^(@)C4^{\circ} \mathrm{C} 10 分钟，小心吸收上层血清并储存在冷冻管中 -80^(@)C-80^{\circ} \mathrm{C} 以备后用。从每只动物中分离胰腺、结肠组织和盲肠内容物以供进一步测量。
2.5 Biochemical analyses 2.5 生化分析
The levels of fasting serum insulin (FINS) were determined by using enzyme-linked immunosorbent assay (ELISA) kits (Chenglin Bioengineering Institute, Beijing, China), according to the manufacturer’s instructions. Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated with reference to Yan et al. ^(13){ }^{13} HOMA-IR == FBG xx\times FINS/22.5. 根据制造商的说明，使用酶联免疫吸附测定 （ELISA） 试剂盒（Chenglin Bioengineering Institute，Beijing，China）测定空腹血清胰岛素 （FINS） 的水平。胰岛素抵抗的稳态模型评估 （HOMA-IR） 参考 Yan 等人计算。 ^(13){ }^{13} HOMA-IR == FBG xx\times FINS/22.5。
2.6 Histopathologic examination and analysis 2.6 组织病理学检查和分析
The pancreases were fixed in 10%10 \% neutral formalin for 48 h , after being dehydrated in graded alcohol, made transparent in xylene, and then embedded in paraffin wax. Tissue sections of 5mum5 \mu \mathrm{~m} thickness were sliced and routinely stained with hema-toxylin-eosin (HE). Histological differences between the groups were viewed and photographed at 400 magnifications with a microscope (DM1000, Leica, Germany). 胰腺在中性福尔马林中 10%10 \% 固定 48 h，在分级醇中脱水后，在二甲苯中透明，然后包埋在石蜡中。将厚度的组织 5mum5 \mu \mathrm{~m} 切片并常规用 hema-toxylin-yosin （HE） 染色。用显微镜 （DM1000， Leica， Germany） 以 400 倍放大倍数观察和拍摄各组之间的组织学差异。
2.7 Serum lipid levels 2.7 血脂水平
Serum total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) levels were assayed using ELISA kits according to the manufacturer’s instructions, respectively. 根据制造商的说明，使用 ELISA 试剂盒分别测定血清总胆固醇 （TC） 、甘油三酯 （TG） 、高密度脂蛋白胆固醇 （HDL-C） 和低密度脂蛋白胆固醇 （LDL-C） 水平。
2.8 Determination of oxidative stress in the liver 2.8 肝脏中氧化应激的测定
The test ELISA kits were utilized to assess the levels of glutathione (GSH) and malondialdehyde (MDA) in the livers, as well as the activities of SOD and glutathione peroxidase (GSH-px), according to the manufacturer’s guidelines. 根据制造商的指南，使用 ELISA 试剂盒检测试剂盒评估肝脏中谷胱甘肽 （GSH） 和丙二醛 （MDA） 的水平，以及 SOD 和谷胱甘肽过氧化物酶 （GSH-px） 的活性。
2.9 Lipopolysaccharide (LPS), D(-)\mathrm{D}(-)-lactic acid (D-LAC) and cytokine levels in the serum and colon 2.9 血清和结肠中的脂多糖 （LPS）、 D(-)\mathrm{D}(-) 乳酸 （D-LAC） 和细胞因子水平
By following the manufacturer’s instructions, ELISA was used to measure the levels of LPS, D-LAC in the serum, interleukin8 (IL-8), tumor necrosis factor- alpha\alpha (TNF- alpha\alpha ), interleukin-1 beta ( IL-1beta\mathrm{IL}-1 \beta ), and interleukin 10 (IL-10) in the colon. 按照制造商的说明，ELISA 用于测量血清中 LPS、D-LAC、白细胞介素 8 （IL-8）、肿瘤坏死因子 （ alpha\alpha TNF- alpha\alpha ）、白细胞介素-1 β （ IL-1beta\mathrm{IL}-1 \beta ） 和白细胞介素 10 （IL-10） 的水平结肠。
2.10 Microbial analysis of cecal contents 2.10 盲肠内容物的微生物分析
The genomic DNA was extracted from each cecal fecal sample using a QIAamp DNA stool mini kit (Qiagen, Dusseldorf, Germany) following the manufacturer’s instructions. The quantity and quality of DNA were examined by agarose gel electrophoresis and by using a spectrophotometer (Thermo Fisher Scientific, Waltham, USA, ND-2000C). The microbiota V3-V4 region of 16 S rDNA was selected to amplify by PCR. The primer sequences were 338F, 5’-ACTCCTACGGGAGGCAGCAG-3’ and 806R, 3’-GACTACHVGGGTWTCTAAT-5’. The PCR products were purified with Vazyme VAHTSTM DNA clean beads (Vazyme, Nanjing, China) and quantified using a FLx800 fluorescence microplate reader (BioTek, Winooski, VT, USA) using a Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen, Carlsbad, CA, USA). Refer to Li et al. for the microbial analysis of cecal contents. ^(14){ }^{14} Specifically, purified amplicons were prepared into a sequencing library using a TruSeq Nano DNA LT Library Prep Kit (Illumina, San Diego, CA, USA), and PCR amplicons were sequenced using an Illumina Miseq (Illumina, Santiago, USA). FLASH and QIIME software are used to merge and filter the raw data. Operational taxonomic unit (OUT) representative sequences were annotated against a database using PyNAST software. Alpha and beta diversity analyses were performed using QIIME version 1.9.1. Microbial functional predictions were made by normalizing species abundance in the raw 16 S sequencing data using PICRUSt software. STAMP software was used to analyze the functional profiling between different groups. 按照制造商的说明，使用 QIAamp DNA stool mini kit（Qiagen，Dusseldorf，Germany）从每个盲肠粪便样本中提取基因组 DNA。通过琼脂糖凝胶电泳和分光光度计 （Thermo Fisher Scientific， Waltham， USA， ND-2000C） 检查 DNA 的数量和质量。选择 16 S rDNA 的微生物群 V3-V4 区进行 PCR 扩增。引物序列为 338F， 5'-ACTCCTACGGGAGGCAGCAG-3' 和 806R， 3'-GACTACHVGGGTWTCTAAT-5'。用 Vazyme VAHTSTM DNA 干净珠 （Vazyme， Nanjing， China） 纯化 PCR 产物，并使用 FLx800 荧光酶标仪 （BioTek， Winooski， VT， USA） 和 Quant-iT PicoGreen dsDNA 检测试剂盒 （Invitrogen， Carlsbad， CA， USA） 定量。参考 Li 等人对盲肠内容物的微生物分析。 ^(14){ }^{14} 具体来说，使用 TruSeq Nano DNA LT 文库制备试剂盒（Illumina，San Diego，CA，USA）将纯化的扩增子制备到测序文库中，并使用 Illumina Miseq（Illumina，Santiago，USA）对 PCR 扩增子进行测序。FLASH 和 QIIME 软件用于合并和过滤原始数据。使用 PyNAST 软件对作分类单元 （OUT） 代表性序列进行数据库注释。使用 QIIME 1.9.1 版本进行 alpha 和 beta 多样性分析。通过使用 PICRUSt 软件对原始 16 S 测序数据中的物种丰度进行归一化，进行微生物功能预测。采用 STAMP 软件分析不同组间的功能分析。
2.11 SCFA quantification of serum and cecal contents 2.11 血清和盲肠内容物的 SCFA 定量
SCFAs of serum and cecal contents were measured as described in a previous report. ^(13){ }^{13} In a nutshell, cecal contents ( 50 mg ) were mixed with 0.3 mL of pure water vortex and centrifuged at 5000 g at 4^(@)C4^{\circ} \mathrm{C} for 20 min . The supernatant was filtered with a 0.22 mum0.22 \mu \mathrm{~m} filter membrane and acidified with 按照先前报告中所述测量血清和盲肠内容物的 SCFA。 ^(13){ }^{13} 简而言之，将盲肠内容物 （ 50 mg ） 与 0.3 mL 纯水涡旋混合，并以 5000 g 4^(@)C4^{\circ} \mathrm{C} 离心 20 分钟。用 0.22 mum0.22 \mu \mathrm{~m} 滤膜过滤上清液，并用
0.1 mL of sulfuric acid ( 50%50 \% ). 0.4 mL of internal standard solution (2-methylvalerate acid, 50 mugmL^(-1)50 \mu \mathrm{~g} \mathrm{~mL}{ }^{-1} ) was added to the sample, vortexed for 10 s , oscillated for 10 min , and the sample was subjected to ultrasound for 10 min and was centrifuged at 4^(@)C4^{\circ} \mathrm{C} at 12000 g for 15 min . The supernatant was analyzed by gas chromatograph-mass spectrometry (GC-MS) (Agilent Technologies, Santa Clara, USA). The program parameters of GC-MS were as follows: helium was the carrier gas, the front inlet purge flow was 3mLmin^(-1)3 \mathrm{~mL} \mathrm{~min}{ }^{-1}, the gas flow rate in the column was 1mLmin^(-1)1 \mathrm{~mL} \mathrm{~min}{ }^{-1}, and the sample size was 1muL1 \mu \mathrm{~L}. The initial temperature was maintained at 80^(@)C80^{\circ} \mathrm{C} for 1 min and increased to 150^(@)C150{ }^{\circ} \mathrm{C} at 5^(@)Cmin^(-1)5^{\circ} \mathrm{C} \mathrm{min}{ }^{-1}, and then maintained at 230^(@)C230^{\circ} \mathrm{C} at 40^(@)Cmin^(-1)40^{\circ} \mathrm{C} \mathrm{min}{ }^{-1} for 12 min . 0.1 mL 硫酸 （ 50%50 \% ）。向样品中加入 0.4 mL 内标溶液（2-甲基戊酸， 50 mugmL^(-1)50 \mu \mathrm{~g} \mathrm{~mL}{ }^{-1} ），涡旋 10 s，振荡 10 min，样品超声 10 min，12000 g 离心 4^(@)C4^{\circ} \mathrm{C} 15 min。通过气相色谱-质谱法 （GC-MS） （Agilent Technologies， Santa Clara， USA） 分析上清液。GC-MS 的程序参数如下：氦气为载气，前入口吹扫流量为 3mLmin^(-1)3 \mathrm{~mL} \mathrm{~min}{ }^{-1} ，色谱柱内气体流速为 1mLmin^(-1)1 \mathrm{~mL} \mathrm{~min}{ }^{-1} ，样品量为 1muL1 \mu \mathrm{~L} 。初始温度维持 80^(@)C80^{\circ} \mathrm{C} 1 min，然后升至 150^(@)C150{ }^{\circ} \mathrm{C} ， 5^(@)Cmin^(-1)5^{\circ} \mathrm{C} \mathrm{min}{ }^{-1} 然后维持 230^(@)C230^{\circ} \mathrm{C} at 40^(@)Cmin^(-1)40^{\circ} \mathrm{C} \mathrm{min}{ }^{-1} 12 min。
2.12 Statistical analysis 2.12 统计分析
The data were analyzed using SPSS 17.0, Origin 2019b and GraphPad Prism 9.5 software. In all studies, pp-values less than 0.05 were deemed statistically significant (^(******)p < 0.005,^(****)p < :}\left({ }^{* * *} p<0.005,{ }^{* *} p<\right.{: 0.01,^(**)p < 0.05)\left.0.01,{ }^{*} p<0.05\right). 使用 SPSS 17.0 、 Origin 2019b 和 GraphPad Prism 9.5 软件对数据进行分析。在所有研究中， pp 小于 0.05 的 - 值被认为具有统计学意义 (^(******)p < 0.005,^(****)p < :}\left({ }^{* * *} p<0.005,{ }^{* *} p<\right.{: 0.01,^(**)p < 0.05)\left.0.01,{ }^{*} p<0.05\right) 。
3 Results 3 结果
3.1 Effects of a HFD on the basic pathological indexes of T2DM 3.1 HFD 对 T2DM 基本病理指标的影响
To elucidate the contributory role of HFD in T2DM, the protocol depicted in Fig. 1A was followed for conducting animal tests. During the acclimatization feeding phase, the mouse body weight, diet, coat color, or mental status did not significantly differ across the groups. The effect of HFD on the basic pathological indices of T2DM was assessed by measuring the body weight, FBG, OGTT, insulin levels, and HOMA-IR in mice. 为了阐明 HFD 在 T2DM 中的贡献作用，遵循图 1A 中描述的方案进行动物试验。在驯化摄食阶段，小鼠体重、饮食、毛色或精神状态在各组之间没有显著差异。通过测量小鼠体重、 FBG 、 OGTT 、 胰岛素水平和 HOMA-IR 来评估 HFD 对 T2DM 基本病理指标的影响。
3.1.1 Body weight. Fig. 1B presents the body weight of mice in each group. The data revealed an increase in the weights of mice in the NC group throughout the experiment, suggesting that the selected mice were free from abnormalities. The body weight of HFD mice was significantly increased (24.14%) ( P <P< 0.05 ). The body weight of T2DM mice increased by 2.9%2.9 \% relative to the NC5 group - a little rise; however, comparing the two groups, there was no statistically significant difference ( P >P>0.05)0.05). In addition, compared to mice in the HFD group, the body weight of mice in the T2DM group saw a significant decrease ( P < 0.05P<0.05 ), amounting to a reduction of 13.88%13.88 \%. 3.1.1 体重。图 1B 显示了每组中小鼠的体重。数据显示，在整个实验过程中，NC 组小鼠的体重有所增加，表明选定的小鼠没有异常。HFD 小鼠体重显著增加 （24.14%） （ P <P< 0.05 ）。T2DM 小鼠的体重 2.9%2.9 \% 相对于 NC5 组增加 - 略有增加;然而，比较两组，没有统计学上的显著差异 （ P >P>0.05)0.05) .此外，与 HFD 组的小鼠相比，T2DM 组小鼠的体重显着下降 （ P < 0.05P<0.05 ），相当于减少了 13.88%13.88 \% 。
3.1.2 FBG. The most prominent characteristic of diabetes is an elevated FBG level, a standard commonly employed in the medical diagnosis of diabetes. ^(15){ }^{15} Fig. 1C illustrates the impact of a HFD on the FBG level in mice, serving as a measure to assess the role of a HFD in glucose metabolism in T2DM mice. The FBG levels in the blank control group of mice were found to be similar. The FBG levels in the NC0, NC4, and NC5 groups of mice were recorded as 4.49+-0.59,4.48+-0.624.49 \pm 0.59,4.48 \pm 0.62, and 4.48+-0.7mmolL^(-1)4.48 \pm 0.7 \mathrm{mmol} \mathrm{L}^{-1}, respectively, suggesting the stability of FBG in the chosen mice. The FBG level in the HFD group increased to 5.49+-0.6mmolL^(-1)(P < 0.05)5.49 \pm 0.6 \mathrm{mmol} \mathrm{L}^{-1}(P<0.05), substantially higher than that in the NC4 group. Compared to the 3.1.2 FBG.糖尿病最突出的特征是 FBG 水平升高，这是糖尿病医学诊断中常用的标准。 ^(15){ }^{15} 图 1C 说明了 HFD 对小鼠 FBG 水平的影响，可作为评估 HFD 在 T2DM 小鼠葡萄糖代谢中的作用的指标。发现空白对照组小鼠的 FBG 水平相似。NC0 、 NC4 和 NC5 组小鼠的 FBG 水平分别记录为 4.49+-0.59,4.48+-0.624.49 \pm 0.59,4.48 \pm 0.62 和 4.48+-0.7mmolL^(-1)4.48 \pm 0.7 \mathrm{mmol} \mathrm{L}^{-1} ，表明 FBG 在所选小鼠中的稳定性。HFD 组的 FBG 水平增加到 5.49+-0.6mmolL^(-1)(P < 0.05)5.49 \pm 0.6 \mathrm{mmol} \mathrm{L}^{-1}(P<0.05) ，显著高于 NC4 组。与
^(a){ }^{a} Food College, Northeast Agricultural University, Harbin, Heilongjiang, 150030, China. E-mail: 15846092362@163.com ^(a){ }^{a} 东北农业大学 食品学院， 黑龙江 哈尔滨 150030， 中国电子邮件： 15846092362@163.com ^(b){ }^{b} Key Laboratory of Dairy Science, Ministry of Education, Northeast Agricultural University, Harbin, Heilongjiang, 150030, China ^(b){ }^{b} 东北农业大学 乳品科学教育部重点实验室， 黑龙江 哈尔滨 150030 ^(c){ }^{c} Shandong Yuwang Ecological Food Industry Co., Ltd, Dezhou, Shandong, 251200, China ^(c){ }^{c} 山东玉王生态食品工业有限公司， 山东 德州， 251200， 中国 ^(d){ }^{d} School of Food and Biology Engineering, Xuzhou University of Technology, Xuzhou, Jiangsu, 221018, China ^(d){ }^{d} 徐州理工大学食品与生物工程学院， 徐州， 江苏， 221018 ^(e){ }^{e} Shanghai Binhan International Trade Co., Ltd, Shanghai200000, China ^(e){ }^{e} 上海滨汉国际贸易有限公司， 上海 200000 †\dagger Electronic supplementary information (ESI) available. See DOI: https://doi.org/ 10.1039/d4fo02957g †\dagger 提供电子补充信息 （ESI）。请参阅 DOI： https://doi.org/ 10.1039/d4fo02957g