引言溃疡性结肠炎（UC）是一种慢性炎症性肠病（IBD），其特征是结肠和直肠黏膜的持续性炎症，导致血性腹泻和体重减轻等症状，严重损害患者的生活质量。当前的治疗策略常受到长期疗效和安全性的限制。LTr1是一种源自吲哚-3-甲醇（I3C）的三聚体化合物，已显示出抗癌潜力，但其在炎症性疾病中的作用尚不清楚。本研究旨在探究LTr1在葡聚糖硫酸钠（DSS）诱导的结肠炎小鼠模型中的保护作用及潜在机制。巨噬细胞在先天免疫、炎症调节和组织修复中发挥核心作用。其功能多样性受极化过程调控，这是一个动态过程，巨噬细胞在微环境刺激（包括细胞因子和微生物产物）下采用不同的表型。 broadly，巨噬细胞分为两种表型：经典激活的（M1）和替代激活的（M2）。M1巨噬细胞由脂多糖（LPS）和干扰素-γ（IFN-γ）等刺激诱导，通过增加白细胞介素-1β（IL-1β）、IL-6、肿瘤坏死因子-α（TNF-α）和诱导型一氧化氮合酶（iNOS）的产生来驱动促炎反应。相反，替代激活的M2巨噬细胞由IL-4、IL-10、IL-13或转化生长因子-β（TGF-β）刺激，表现出抗炎和组织修复功能。这些细胞分泌IL-10，表达精氨酸酶-1（Arg-1）和CD206，促进炎症消退和组织修复。在肠黏膜中，巨噬细胞通过区分无害抗原和有害病原体来维持免疫平衡。然而，在UC中，这种平衡被打破：巨噬细胞的丰度和激活显著增加，并且 often polarizing macrophages toward the M1 phenotype。研究表明，UC患者的巨噬细胞表现出异常的信号和功能谱，导致炎症反应的过度激活和组织损伤的持续。这包括活性氧（ROS）的产生以及其他免疫细胞（如中性粒细胞）的招募，这些细胞释放ROS和蛋白酶，以及T淋巴细胞到发炎的黏膜。这些过程进一步传播炎症，导致UC的特征性 features，包括黏膜溃疡、隐窝脓肿和炎症浸润。因此，巨噬细胞被认为在UC中发挥关键作用，并已成为开发IBD新治疗方法的 novel target。LTr1是一种源自I3C的三聚体化合物，I3C是一种天然生物活性化合物，富含于十字花科蔬菜中，以其抗癌特性而闻名。大量研究和荟萃分析表明，十字花科蔬菜摄入量与各种常见癌症（如结直肠癌和乳腺癌）的风险呈负相关。此外，研究显示LTr1可以通过抑制FMS样酪氨酸激酶3（FLT3）受体的磷酸化和下游蛋白的表达，有效对抗携带FLT3受体突变的急性髓系白血病（AML）细胞。进一步 investigation revealed that LTr1 exhibits broad-spectrum anti-cancer activity across several cancer cell lines, including MCF-7 (breast cancer), A549 (lung cancer), and HepG2 (liver cancer)。因此，LTr1被认为是一种有效的癌症抑制剂，优于I3C和3,3′-二吲?基甲烷（DIM），后者是I3C最活跃和有效的代谢物，目前正在进行II/III期临床试验，以评估其在乳腺癌患者中的疗效。尽管LTr1的抗癌潜力证据日益增多，但其在炎症性疾病如UC中的治疗价值尚未 explored。材料与方法2.1 小鼠雄性BALB/c小鼠（6周龄）购自南京大学模式动物遗传研究中心。小鼠在标准实验室条件下饲养，自由获取标准颗粒饲料和无菌蒸馏水，光照/黑暗周期为12/12小时。2.2 DSS诱导的结肠炎模型构建2.2.1 DSS处理和LTr1给药小鼠在实验前适应7天，自由获取食物和水。它们被随机分为三组（每组n=5）：对照组、DSS组和DSS+LTr1组。根据参考文献，通过给小鼠自由饮用2.5%（w/v）葡聚糖硫酸钠（DSS）溶液（Sigma-Aldrich, Cat# 42867）7天来诱导结肠炎，随后正常饮水3天，直至在麻醉下处死。DSS溶液每两天更换一次。对于LTr1处理，LTr1（根据参考文献合成，溶解在玉米油中制备储备溶液）通过口服灌胃以100 mg/kg的剂量每日一次给予小鼠。对照组和DSS组的小鼠接受等体积的玉米油作为 vehicle。2.2.2 疾病活动指数评估在DSS处理期间，使用DAI评分系统评估UC的严重程度，该系统结合了体重减轻、粪便 consistency 和血便的评分。DAI评分标准如下：体重减轻：0表示体重减轻 within 1%；1表示1-5%体重减轻；2表示5-10%体重减轻；3表示10-15%体重减轻；4表示体重减轻>15%。粪便 consistency：0表示正常粪便；2表示软便；4表示水样腹泻。血便：0表示正常粪便；2表示中度出血；4表示严重出血。三个评分的平均值表示为DAI。2.2.3 样本收集实验结束时，小鼠在异氟烷麻醉下处死。将小鼠置于诱导室中，使用3%异氟烷 in oxygen until complete loss of consciousness and cessation of respiratory movement were observed。然后进行颈椎脱位作为 secondary method to ensure death before tissue collection。收集整个结肠，测量长度和重量并拍照。 also harvested spleen，并记录湿重。2.3 组织病理学分析结肠组织在4%甲醛（Sigma-Aldrich, Cat# 1.00496）中固定，石蜡（Sigma-Aldrich, Cat# 327212）包埋，切片厚度为5 μm。切片用苏木精（Sigma-Aldrich, Cat# H3136）和伊红（Sigma-Aldrich, Cat# HT110116）（H&E）溶液染色，然后在光学显微镜下检查以评估组织病理学变化。2.4 免疫组织化学对于免疫组织化学染色，石蜡包埋的结肠组织切片进行脱蜡、水化，并用3% H2O2（Sigma-Aldrich, Cat# H1009）处理以阻断内源性过氧化物酶活性。通过微波加热进行抗原修复，随后用5%牛血清白蛋白（Sigma-Aldrich, Cat# 05470）封闭30分钟。封闭后，切片在4°C下与一抗 against Clandin4（稀释1:200）（Cell signaling, Cat# 94478）、Occludin（稀释1:200）（Cell signaling, Cat# 91131）、ZO-1（稀释1:300）（Cell signaling, Cat# 13663）、CD3（稀释1:100）（Cell signaling, Cat# 78588）和F4/80（稀释1:100）（Cell signaling, Cat# 70076）孵育过夜。 further, after washing with PBS（Gibco, Cat #14190144），切片在室温下与多聚过氧化物酶-抗兔IgG二抗（稀释1:1000）（Sigma-Aldrich, Cat# A8275）孵育1小时。细胞核用DAPI（4′,6-二脒基-2-苯基吲哚）（稀释1:10000）（Thermo Fisher, Cat# D1306）复染，切片在荧光显微镜下成像。2.5 高碘酸希夫和阿尔新蓝染色新鲜结肠在10%缓冲福尔马林中固定，石蜡包埋，切片厚度为5 μm，并使用高碘酸-希夫和阿尔新蓝染色试剂盒（Abcam, Cat# ab245876）按照制造商说明进行染色。最后，所有样本在显微镜下观察和拍照，杯状细胞数量 normalized to the number of crypt units。2.6 细胞因子测定使用酶联免疫吸附测定（ELISA）评估细胞因子水平。血清样本通过眶静脉丛在异氟烷麻醉下收集。 additionally, RAW264.7 cells were pre-treated with the indicated concentration of LTr1 for 1h and then stimulated with 1 μg/ml LPS（Beyotime, Cat# S1732） for 24h。收集条件培养基用于通过ELISA进行 further analysis。本研究使用肿瘤坏死因子-α（TNF-α）（R&D, Cat# MTA00B）、白细胞介素-6（IL-6）（R&D, Cat# M6000B）、白细胞介素-1β（IL-1β）（R&D, Cat# MLB00C）、白细胞介素-12（R&D, Cat# M1270）试剂盒测量结肠组织和细胞培养基中的细胞因子水平。2.7 定量逆转录-PCR使用总RNA提取试剂盒（QIAGEN, Cat# 74104）分离和纯化结肠组织和处理细胞的总RNA。使用Prime Script TM RT-PCR试剂盒（Takara, Cat# RR014A）进行逆转录，并使用Biorad CFX Connect（Biorad）按照制造商说明进行qRT-PCR。通过使用2-ΔΔCT方法，将每个靶基因mRNA的相对表达 normalized to the housekeeping gene Hypoxanthine-guanine phosphoribosyltransferase（Hprt）。以下基因的引物由GenScript Biotech合成：小鼠IL-1β，正向，ATGCCACCTTTTGACAGTGATG，和反向，TGATGTGCTGCTGCGAGATT；小鼠IL-6，正向，TAGTCCTTCCTACCCCAATTTCC，和反向，TTGGTCCTTAGCCACTCCTTC；小鼠TNFα，正向，CCTGTAGCCCACGTCGTAG，和反向，GGGAGTAGACAAGGTACAACCC；小鼠IL-10，TTCTTTCAAACAAAGGACCAGC，和反向，GCAACCCAAGTAACCCTTAAAG；小鼠IL-12，ACGAGAGTTGCCTGGCTACTAG，和反向，CCTCATAGATGCTACCAAGGCAC；小鼠IFN-γ，CAGCAACAGCAAGGCGAAAAAGG，和反向，TTTCCGCTTCCTGAGGCTGGAT；Hprt，正向，GTCCCAGCGTCGTGATTAGC，和反向，TGGCCTCCCATCTCCTTCA。2.8 固有层淋巴细胞制备新鲜收获的结肠组织用PBS洗涤，切成1 x 1cm片段。通过 sequential incubation 去除上皮细胞：两次在含有3 mM EDTA（Sigma-Aldrich, Cat# EDS）的PBS中在37°C下孵育10分钟，随后两次在补充有1%胎牛血清（FBS）（Gibco, Cat# 16000044）、1 mM EDTA和1.5 mM MgCl2（Sigma-Aldrich, Cat# 208337）的RPMI 1640培养基（Thermo Fisher, Cat# 11875093）中孵育15分钟。剩余组织在含有20% FBS、100 U/mL胶原酶D（Roche, Cat# 11088858001）和5 U/mL DNase I（Sigma-Aldrich, Cat# D8515）的RPMI 1640培养基中在37°C下消化90分钟，偶尔通过注射器抽吸（40-50次）进行机械 disruption。 resulting cell suspension was subjected to density gradient centrifugation using a 45%/66.6% discontinuous Percoll gradient（Solarbio） at 2500 rpm for 20 minutes。使用台盼蓝排除 assay 计数 viable LPLs。2.9 脾细胞制备收获脾脏，并使用注射器后端 mechanically disrupted。将组织在50 mL新鲜RPMI 1640培养基中与100 U/mL胶原酶D和5 U/mL DNase I在37°C、5% CO2下孵育20分钟。消化后，将 suspension filtered through 70–100 μm sterile filters and centrifuged。使用RBC裂解缓冲液（Biolegend, Cat# 420301）在室温下裂解红细胞5分钟。然后将细胞用新鲜培养基洗涤，以1500 rpm离心5分钟，并 resuspended in fresh medium。通过台盼蓝排除 assay 评估细胞活力。2.10 流式细胞术分析分离的LPLs和脾细胞与单克隆抗体2.4G2（抗小鼠CD16/CD32 mAb）（BD Biosciences, Cat# 553141）预孵育以阻断Fcγ受体。然后将细胞在含有2 mM EDTA和2% FBS的PBS中用荧光染料标记的单克隆抗体染色40分钟。在LSRFortessa II仪器（BD Biosciences）上使用FlowJo软件（TreeStar）分析细胞。流式细胞术使用以下抗体：CD3-Brilliant Violet 510（eBiosciences, Cat# 464882）、CD11b-Brilliant Violet 421（Biolegend, Cat# 101235）、CD19-Brilliant Violet 650（BD Biosciences, Cat# 563235）、CD45-FITC（Biolegend, Cat# 103108）、F4/80-PE（BD Biosciences, Cat# 565410）。 iNOS-APC（Miltenyibiotec, Cat# 130-116-423）、CD80-Brilliant Violet 711（Biolegend, Cat# 104743）、CD206-PE/Cyanine7（Biolegend, Cat# 141720）。2.11 细胞培养RAW264.7小鼠巨噬细胞购自ATCC，并在高葡萄糖杜尔贝科改良 Eagle 培养基（DMEM）（Sigma-Aldrich, Cat# D5796）中培养，培养基含有10%（v/v）FBS、100 U/ml青霉素和100 U/ml链霉素（Gibco, Cat# 12090216）。细胞在37°C、5% CO2的湿润培养箱中培养。2.12 细胞药物递送浓度筛选将RAW264.7细胞以每孔5000个细胞的密度接种在96孔板中。孵育24小时后，用指定浓度的LTr1处理细胞24小时。将CCK-8溶液（MedChemExpress, Cat# HY-K0301）加入孔中，并将板放回37°C、5% CO2的湿润培养箱中1小时。使用酶标仪在450 nm处评估细胞的吸光度（A）值，并计算细胞活力。细胞活力（%）=（A sample ? A blank）/（A control ? A blank） * 100%。通过剂量反应曲线插值确定LTr1对细胞活力的半数抑制浓度（IC50）。2.13 LTr1对结肠炎的网络药理学分析2.13.1 UC相关治疗靶基因的收集从Genecards（https://www.genecards.org/）和DisGeNET（https://www.disgenet.org/）数据库中使用关键词“Ulcerative Colitis”收集UC的治疗靶基因。整合数据并去除重复靶基因后，建立了与UC相关的 comprehensive set of target genes。2.13.2 LTr1的靶点预测从PubChem数据库（https://pubchem.ncbi.nlm.nih.gov/）检索LTr1的SMILES化学结构。该结构用作chEMBL（https://www.ebi.ac.uk/chembl/）和DGIdb（https://www.dgidb.org/）数据库的输入以预测靶基因。整合数据并去除重复靶基因后，建立了LTr1相关的 comprehensive set of target genes。2.13.3 LTr1对UC的靶基因预测整合302个LTr1相关靶基因和5752个UC相关基因，发现189个基因在这些数据集中共享，并用R语言Venn Diagram包绘制的维恩图进行直观展示。2.13.4 进行蛋白质-蛋白质相互作用网络使用STRING数据库（https://cn.string-db.org/）分析 identified 189 intersecting target genes for PPI network。通过Cytoscape软件（版本3.9.1）使用图形表示可视化PPI网络。同时，使用Cytohubba插件，利用Maximum Clique Centrality（MCC）算法识别前20个核心靶蛋白。Layout部分配置为Degree Sorted Circle layout。2.13.5 功能和通路富集分析使用R软件（版本4.2.0）安装“colorspace”、“stringi”和“ggplot2”包。应用Bioconductor包，包括“DOSE”、“clusterProfiler”和“enrichplot”，对 identified Top 20 intersecting target genes 进行基因本体（GO）和京都基因与基因组百科全书（KEGG）富集分析。使用“enrichGO”函数进行基因本体（GO）富集分析，参数设置为OrgDb = “org.Hs.eg.db，” keyType = “ENTREZID，” and ont = “ALL。” additionally, the “enrichKEGG” function was utilized for the Kyoto Encyclopedia of Genes and Genomes（KEGG） enrichment analysis，参数设置为organism = “hsa” and keyType = “kegg。” both functions的P值过滤器设置为0.05。GO富集和KEGG富集的前10个富集结果分别以点图和条形图可视化。2.14 统计分析使用单因素方差分析（ANOVA）和LSD多重比较检验确定组间统计差异。所有统计分析使用IBM SPSS Statistics软件25.0进行，图表使用GraphPad Prism软件10.2制备。所有实验数据表示为至少三个独立实验的平均值±标准差（SD），统计显著性设定为p-值 < 0.05。结果3.1 LTr1逆转了DSS诱导的小鼠结肠炎的症状和组织学损伤为了研究LTr1在UC中的治疗潜力，我们 initially established a DSS-induced murine colitis model。小鼠接受2.5% DSS饮用水7天，表现出 characteristic disease progression，包括进行性体重减轻、 developed severe colitis，如 elevated disease activity index（DAI） score、 reduced colon length、 and extensive histopathological damage compared to the control group。 Notably, LTr1 treatment effectively reversed these colitis-induced effects， with the most pronounced effects observed in body weight and colon length。 Specifically, the extent of DSS-induced weight loss was reduced by approximately 50%， and the colon length was restored to a level comparable to that of the healthy control group。 After confirming that LTr1 plays a protective role in the DSS-induced colitis model， we further examined the expression of tight junction proteins in intestinal tissues to test the gut barrier function。 DSS exposure led to a significant reduction in tight junction proteins Claudin4, Occludin, and ZO-1 expression levels， which was reversed by LTr1 treatment。 Similarly, RT-PCR analysis further confirmed that DSS exposure led to a more than 50% decrease in Claudin-4, Occludin, and ZO-1 mRNA expression， and LTr1 treatment reversed the transcriptional downregulation of ZO-1 and Occludin mRNA。 In addition, goblet cells play an important role in maintaining intestinal homeostasis and repair， PAS staining revealed more than 60% depletion of goblet cells in DSS-treated mice compared to the control group， which was significantly reversed by LTr1， indicating its role in preserving mucosal integrity。 Collectively, these results indicate that LTr1 can effectively protect mice from clinical manifestations of colitis and intestinal tissue damage due to DSS。3.2 LTr1减少DSS诱导的结肠炎的局部和全身炎症Dysregulated immune response constitutes a hallmark of UC pathogenesis。 Our results demonstrated that DSS-induced colitis was associated with pronounced splenomegaly， as reflected by a spleen weight approximately threefold higher than that of normal controls。 Remarkably, LTr1 treatment restored spleen weight to levels comparable to the control group。 Given the spleen’s critical role in immune regulation， we hypothesized that LTr1 could modulate the inflammatory response induced by DSS。 To assess the anti-inflammatory effect of LTr1， we performed ELISA assay to determine the protein levels of cytokines present in the serum and RT-PCR was conducted to determine the mRNA level of cytokines in the colon of the mice。 ELISA results showed serum levels of pro-inflammatory cytokines IL-1β, IL-6, IL-12, and TNF-α were significantly increased in the DSS group compared to those in the control group。 LTr1 treatment led to an approximate 50% reduction in the levels of IL-1β, IL-6, and IL-12， although TNF-α levels remained unchanged。 Concordantly, RT-PCR results indicated that DSS-induced mRNA transcription of pro-inflammatory cytokines in colon tissue， including IL-1β, IL-6, IL-12, and IFN-γ were inhibited by the LTr1 treatment， while TNF-α expression was unaffected。 Additionally, the mRNA expression of the anti-inflammatory cytokine IL-10， whose expression was significantly increased by LTr1 treatment compared to the DSS group。 A large infiltration of immune cells in intestinal tissues is another characteristic of colitis。 To further confirm the anti-inflammatory effect of LTr1， we used immunohistochemistry to detect the infiltration of immune cells in colon tissues。 The results demonstrated that DSS stimulation significantly enhanced the infiltration and accumulation of CD3+ T cells and F4/80+ macrophages in intestinal tissue compared with the control group。 Notably, LTr1 treatment failed to reduce DSS-induced T cells accumulation， but significantly reduced macrophages infiltration in colon tissues。 These findings suggest that LTr1 confers a potent anti-inflammatory effect in DSS-induced colitis， potentially by modulating cytokine production and macrophage infiltration。3.3 LTr1减少巨噬细胞浸润和M1极化Macrophages play a crucial role in maintaining homeostasis and the development of inflammation in gut。 Immunohistochemical analysis revealed reduced macrophage infiltration in intestinal tissues following LTr1 treatment。 To further explore the impact of LTr1 on macrophage dynamics， we used flow cytometry to quantify macrophage infiltration in spleen and colon tissues。 The gating strategy is detailed in Supplementary Figure 1， and macrophages were identified as ZombieNIR-CD45+CD3-CD19- CD11b+F4/80+ cells。 Under physiological conditions， macrophages constituted approximately 1% of the cellular population in spleen and colon tissues。 DSS challenge elevated the proportion of macrophages to about 7% in both tissues while LTr1 treatment markedly reduced this increase in both spleen and colon tissue。 Dysregulation of macrophage polarization plays a critical role for the development of UC。 To assess this， we examined colonic infiltrating macrophages， using iNOS and CD80 as M1-polarization markers。 Flow cytometry revealed that only approximately 5% of macrophages were iNOS+， while around 2% were CD80+ in the control group， while DSS-induced macrophages exhibited an M1-polarized phenotype， with over 50% iNOS+ and 40% CD80+ macrophages。 In contrast, LTr1 treatment significantly reduced the proportion of both iNOS+ and CD80+ macrophages， along with a decrease in their protein expression levels。 RT-PCR analysis corroborated these findings， the mRNA levels of iNOS and CD80 were reduced， while the mRNA levels of M2-polarization markers CD206 and Arg1 were increased after the LTr1 treatment compared to the DSS group。 These data suggest that LTr1 not only inhibits macrophage infiltration but also promotes a shift from pro-inflammatory M1 to anti-inflammatory M2 phenotypes in DSS-induced colitis。3.4 LTr1在体外直接抑制巨噬细胞的M1极化为了确定LTr1是否直接影响巨噬细胞极化，我们使用小鼠巨噬细胞RAW264.7细胞系进行了体外实验。细胞活力测定 confirmed that LTr1 up to 20 μM had no cytotoxic effect on cell viability。 We then established an M1-like inflammation model in RAW264.7 cells by stimulating cells with LPS to mimic the in vivo DSS-induced colitis model。 Flow cytometry analysis showed that LPS robustly induced iNOS and CD80 expression with minimal effects on CD206， indicative of M1 polarization compared to NT。 LTr1 significantly inhibited LPS-induced cellular inflammation by downregulating iNOS and CD80 in a concentration-dependent manner， and notably, treatment with 10 μM LTr1 reduced the expression of iNOS and CD80 by over 50%， while showing no notable effect on CD206 expression。 Additionally, LTr1 treatment also inhibited the LPS-induced pro-inflammatory cytokine IL-1β and IL-6 production， as well as suppressed LPS-induced transcriptional activation of pro-inflammatory genes， including iNOS, IL-1β, and IL-6。 These results confirm that LTr1 directly restrains M1 polarization and inflammatory cytokine expression in macrophages under inflammatory conditions。3.5 LTr1在结肠炎中的网络药理学分析为了分析LTr1在UC中治疗作用的潜在分子机制，进行了网络药理学分析以 identify predicted protein targets correlated with LTr1。 Firstly, we obtained the SMILES representation of LTr1 from the PubChem database。 Computational predictions for target genes were performed using the SwissTargetPrediction and Pharmaceutical Target Seeker databases。 After merging both datasets and removing duplicates， we identified 302 potential target genes。 To identify UC-associated genes， we retrieved data from the GeneCards（Relevance score ≥ 1） and DisGeNET databases using the keyword “Ulcerative Colitis”。 This search yielded 5,332 genes from GeneCards and 1,682 genes from DisGeNET。 After consolidating the datasets and removing duplicates， we compiled a total of 5,752 UC-related genes。 Subsequently, intersection analysis was performed using VennDiagram to identify shared genes among the 5752 UC-related genes and the 302 LTr1 target genes。 This analysis revealed 189 overlapping genes， which were designated as key targets for further investigation。 Furthermore, we used the CytoHubba plugin with the Maximum Neighborhood Component（MCC） algorithm to identify the top 20 core target genes。 In this visualization， nodes transition from orange to red， with darker colors indicating a higher correlation coefficient of action。 Additionally, we constructed a compound-target network graph in Cytoscape， consisting of 190 nodes and 189 edges， where nodes represent targets and edges indicate the interactions between components and targets。 Finally, we built a constituent-core target-pathway network to illustrate the relationship between target constituents， core targets and their associated pathways。 As shown， the component-core target-pathway interaction network has 41 nodes and
