Article(id=1198628673407512821, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1198628666650493481, articleNumber=null, orderNo=null, doi=10.16438/j.0513-4870.2022-1082, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1664380800000, receivedDateStr=2022-09-29, revisedDate=1674057600000, revisedDateStr=2023-01-19, acceptedDate=null, acceptedDateStr=null, onlineDate=1763704945184, onlineDateStr=2025-11-21, pubDate=1689091200000, pubDateStr=2023-07-12, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1763704945184, onlineIssueDateStr=2025-11-21, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1763704945184, creator=13701087609, updateTime=1763704945184, updator=13701087609, issue=Issue{id=1198628666650493481, tenantId=1146029695717560320, journalId=1189982191388893191, year='2023', volume='58', issue='7', pageStart='0', pageEnd='1980', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1763704943573, creator=13701087609, updateTime=1766137716668, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1208832456644490122, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1198628666650493481, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1208832456644490123, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1198628666650493481, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1780, endPage=1789, ext={EN=ArticleExt(id=1198628673797583104, articleId=1198628673407512821, tenantId=1146029695717560320, journalId=1189982191388893191, language=EN, title=Effect of Scutellaria baicalensis Georgi on metabolism in RSV infection mice based on metabolomics, columnId=1190335348761793317, journalTitle=Acta Pharmaceutica Sinica, columnName=Original Articles, runingTitle=null, highlight=null, articleAbstract=

This study, aiming at finding biomarkers which can assist in the diagnosis of respiratory syncytial virus (RSV) pneumonia and analyzing the metabolic pathways of anti-RSV activity of Scutellaria baicalensis Georgi (SG)., explores the improvement effect of SG on mice models infected by RSV with the metabolomics technology based on UPLC-Q-Exactive HF X-MS. Mice models affected by RSV are established by nasal drip method and the changes of body weight, rectal temperature and pathological damage of lung tissue are evaluated. The lung tissue samples of mice in each group are collected and analyzed by UPLC-Q-Exactive HF X-MS. The differential metabolites of SG drug intervention are explored by metabolomics technology, and the metabolic pathways regulated by SG are analyzed. The results show that SG can significantly improve the pathological state of the lung tissue of the mice and make its body weight and rectal temperature tend to be normal. In the lung tissue samples, 46 biomarkers, such as guanine, L-asparagine, and arachidonic acid, are screened for disease development in RSV model mice. SG improved RSV infection by recalling 22 potential biomarkers, such as uric acid, arachidonic acid, and alanine. The 22 potential markers mainly involved 11 abnormal metabolic pathways, including phenylalanine, tyrosine, and tryptophan biosynthesis, and arachidonic acid metabolism, alanine, aspartic acid and glutamate metabolism are closely related to the five metabolic pathways. SG improves RSV-infected mice mainly by regulating amino acids, lipids, cofactors and vitamins and nucleotide metabolites. All animal experiments were conducted under the guidance and approval of the Animal Ethics Review Committee of Shandong University of Traditional Chinese Medicine. (approval number: SDUTCM20210311001).

, correspAuthors=Bo-nian ZHAO, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright ©2023 Acta Pharmaceutica Sinica. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Ming-qian JIA, Yan GAO, Lu LIU, Lu-lan MA, Xi CHEN, Yue ZHANG, Yang-hai WANG, Bo-nian ZHAO), CN=ArticleExt(id=1198628675789877615, articleId=1198628673407512821, tenantId=1146029695717560320, journalId=1189982191388893191, language=CN, title=基于代谢组学的黄芩抗RSV肺炎作用机制研究, columnId=1190335348896011050, journalTitle=药学学报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=

本研究基于UPLC-Q-Exactive HF X-MS的代谢组学技术探讨黄芩(Scutellaria baicalensis Georgi, SG) 对呼吸道合胞病毒(respiratory syncytial virus, RSV) 感染模型小鼠的改善作用, 寻找可协助RSV肺炎诊断的生物标记物, 分析黄芩发挥抗RSV活性的代谢途径。采用滴鼻感染RSV方法建立RSV肺炎小鼠模型, 评价小鼠体重变化、肛温变化以及肺组织病理损伤。采集各组小鼠的肺组织样品, 进行UPLC-Q-Exactive HF X-MS分析, 通过代谢组学技术挖掘黄芩药物干预的差异性代谢物, 并对黄芩调控的代谢通路进行分析。结果表明, 黄芩能显著改善模型小鼠肺组织病理状态, 使模型小鼠体重、肛温趋于正常; 肺组织样本中, 筛选出RSV模型小鼠疾病发展的生物标志物鸟嘌呤、L-天冬酰胺、花生四烯酸等46个, 黄芩通过回调其中的尿酸、花生四烯酸、丙氨酸等22个潜在生物标志物发挥改善RSV感染作用, 22个潜在标志物主要涉及11条异常代谢通路, 其中与苯丙氨酸、酪氨酸和色氨酸生物合成, 花生四烯酸代谢, 丙氨酸、天冬氨酸和谷氨酸代谢等5条代谢通路密切相关。黄芩主要通过调节氨基酸类、脂类、辅因子和维生素以及核苷酸类代谢物发挥改善RSV感染小鼠的作用。所有动物实验均在山东中医药大学动物伦理审查委员会的指导和批准下进行(批准号: SDUTCM20210311001)。

, correspAuthors=赵渤年, authorNote=null, correspAuthorsNote=
*赵渤年, E-mail:
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Immun Inflamm Dis, 2020, 8: 753-762., articleTitle=Transcriptomic analysis reveals novel mechanisms of SARS-CoV-2 infection in human lung cells, refAbstract=null)], funds=[Fund(id=1198960148011118683, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, awardId=2017YFC1701501, language=CN, fundingSource=国家重点研发计划子课题(2017YFC1701501), fundOrder=null, country=null), Fund(id=1198960148115976293, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, awardId=ZR2021LZY021, language=CN, fundingSource=山东省自然科学基金联合基金项目(ZR2021LZY021), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1198960139840614745, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, xref=null, ext=[AuthorCompanyExt(id=1198960139865780572, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, companyId=1198960139840614745, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. College of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China), AuthorCompanyExt(id=1198960139890946401, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, companyId=1198960139840614745, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.山东中医药大学药学院, 山东 济南 250355)]), AuthorCompany(id=1198960140025164139, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, xref=null, ext=[AuthorCompanyExt(id=1198960140058718573, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, companyId=1198960140025164139, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2. Institute of Innovation in Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250355, China), AuthorCompanyExt(id=1198960140075495793, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, companyId=1198960140025164139, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.山东中医药大学中医药创新研究院, 山东 济南 250355)])], figs=[ArticleFig(id=1198960145045746553, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, language=EN, label=null, caption=null, figureFileSmall=96pmHeP2cxPdXwNJjKVrgg==, figureFileBig=SKdu/KvXtrGhJaBQNZjnBA==, tableContent=null), ArticleFig(id=1198960145179964291, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, language=CN, label=Figure 1, caption= Effects of SG on various indexes in RSV-infected mice. SG: <i>Scutellaria baicalensis</i> Georgi; RSV: Respiratory syncytial virus; Control: Control group; M: Model group; H: SG group. <i>n</i> = 6, <span class="mag-xml-inline-formula">$\bar{x}$</span> ± <i>s</i>. A: Body weight changes of mice in each group; B: Rectal temperature changes of mice in each group; C: Hematoxylin and eosin (H & E) pathological sections and histological scores of mouse lung in each group. Scale bar: 50 μm (200×). Red arrow: Alveolar septum; Black arrow: Inflammatory infiltration , figureFileSmall=96pmHeP2cxPdXwNJjKVrgg==, figureFileBig=SKdu/KvXtrGhJaBQNZjnBA==, tableContent=null), ArticleFig(id=1198960145356125080, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, language=EN, label=null, caption=null, figureFileSmall=S+q4NLhyp/nJ9puNpWaKZw==, figureFileBig=gdP19cbSr40zECfoHRmZmQ==, tableContent=null), ArticleFig(id=1198960145460982690, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, language=CN, label=Figure 2, caption= Principal component analysis (PCA) results in quality control (QC) sample. A: Positive ion mode; B: Negative ion mode , figureFileSmall=S+q4NLhyp/nJ9puNpWaKZw==, figureFileBig=gdP19cbSr40zECfoHRmZmQ==, tableContent=null), ArticleFig(id=1198960145591006123, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, language=EN, label=null, caption=null, figureFileSmall=/M+Vk224i7VX5/lIQ1e7Vw==, figureFileBig=kDsGUq2F+LlQNwivN3ir7g==, tableContent=null), ArticleFig(id=1198960145721029557, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, language=CN, label=Figure 3, caption= Total ion current diagram of Control, M and H groups in positive and negative ion modes. Positive ion mode: Control group (A), M group (B), and H group (C); Negative ion mode: Control group (D), M group (E), and H group (F) , figureFileSmall=/M+Vk224i7VX5/lIQ1e7Vw==, figureFileBig=kDsGUq2F+LlQNwivN3ir7g==, tableContent=null), ArticleFig(id=1198960145867830209, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, language=EN, label=null, caption=null, figureFileSmall=p0f2dLI2z2sLJeIZK+mDCA==, figureFileBig=UnL2KkRWUpoiHXxUMiHvrA==, tableContent=null), ArticleFig(id=1198960146027213773, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, language=CN, label=Figure 4, caption= Orthogonal partial least-squares discrimination analysis (OPLS-DA) score map in positive (A) and negative (B) ion modes. C: Control group , figureFileSmall=p0f2dLI2z2sLJeIZK+mDCA==, figureFileBig=UnL2KkRWUpoiHXxUMiHvrA==, tableContent=null), ArticleFig(id=1198960146140459986, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, language=EN, label=null, caption=null, figureFileSmall=9p6/Z2Xw6VohZcjT8xGPaQ==, figureFileBig=6NSM8E+PLMD/xSWmW5AqgQ==, tableContent=null), ArticleFig(id=1198960146224346071, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, language=CN, label=Figure 5, caption= The regulatory effect of SG on biomarkers. <sup>Δ</sup><i>P</i> < 0.05, <sup>ΔΔ</sup><i>P</i> < 0.01, <sup>ΔΔΔ</sup><i>P</i> < 0.001 <i>vs</i> Model group. ADP: Adenosine diphosphate; UMP: Uridine monophosphate , figureFileSmall=9p6/Z2Xw6VohZcjT8xGPaQ==, figureFileBig=6NSM8E+PLMD/xSWmW5AqgQ==, tableContent=null), ArticleFig(id=1198960146304037857, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, language=EN, label=null, caption=null, figureFileSmall=JMN7qTNt+TSfX9NIhsuBmw==, figureFileBig=oMOJlDUdLmtud2NaWQPztw==, tableContent=null), ArticleFig(id=1198960146429866984, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, language=CN, label=Figure 6, caption= Summary of metabolic pathway analysis of C <i>vs</i> M (A) and M <i>vs</i> H (B) , figureFileSmall=JMN7qTNt+TSfX9NIhsuBmw==, figureFileBig=oMOJlDUdLmtud2NaWQPztw==, tableContent=null), ArticleFig(id=1198960146559890419, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, language=EN, label=null, caption=null, figureFileSmall=9RtlgXdismruiXgdxE9U1A==, figureFileBig=Oi4OuutkFIJMu9gJFioL6A==, tableContent=null), ArticleFig(id=1198960146664748027, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, language=CN, label=Figure 7, caption= Schematic diagram of metabolic pathway network of potential biomarkers of SG in treating RSV infected pneumonia. TCA cycle: Tricarboxylic acid cycle; COX: Cyclooxygenase; LOX: Lipoxygenase; CYP: Cytochrome; PGs: Prostaglandin; TX: Thromboxane; LTs: Leukotriene; HETEs: Hydroxy-eicosatetraenoic acid; EETs: Epoxyeicosatrienenoic acids; PRPP: 5-Phosphoribosyl 1-pyrophosphate; HGPRT: Hypoxanthine-guanine phosphoribosyl transferase; APRT: Adenine phosphoribosyl transferase; ATP: Adenosine triphosphate; GMP: Guanosine monophosphate; XMP: Xanthylic acid; IMP: Inosine monophosphate , figureFileSmall=9RtlgXdismruiXgdxE9U1A==, figureFileBig=Oi4OuutkFIJMu9gJFioL6A==, tableContent=null), ArticleFig(id=1198960146824130566, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
Group Pre Mode R2X/cum R2Y/cum Q2/cum
C vs M vs H 1+2+0 Positive 0.312 0.991 0.838
C vs M vs H 1+3+0 Negative 0.410 0.995 0.796
), ArticleFig(id=1198960146962542607, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, language=CN, label=Table 1, caption=

Orthogonal partial least-squares discrimination analysis (OPLS-DA) model validation parameters. C: Control group; M: Model group; H: SG group. Pre: Principal components; R2X: Model (for X variable data set) interpretability; R2Y: Model (for Y variable data set) interpretability; Q2: Model predictability

, figureFileSmall=null, figureFileBig=null, tableContent=
Group Pre Mode R2X/cum R2Y/cum Q2/cum
C vs M vs H 1+2+0 Positive 0.312 0.991 0.838
C vs M vs H 1+3+0 Negative 0.410 0.995 0.796
), ArticleFig(id=1198960147092566039, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
No. Metabolite Formula m/z tR/min ESI mod VIP Trend
C/M
1 Guanine C5H5N5O 176.103 1.48 + 2.068 ↓***
2 Thymidine C10H14N2O5 223.028 10.21 - 2.026 ↑*
3 L-Homophenylalanine C10H13NO2 180.102 11.32 + 1.936 ↑**
4 Thymine C5H6N2O2 127.050 4.67 + 1.687 ↓**
5 Taurocholic acid C26H45NO7S 516.297 10.86 + 1.674 ↑**
6 Uric acid C5H4N4O3 169.035 1.66 + 1.603 ↑**
7 ADP C10H15N5O10P2 428.036 1.66 + 1.469 ↑*
8 Adenosine diphosphate ribose C15H23N5O14P2 560.081 2.21 + 1.415 ↑*
9 Imidazol-5-yl-pyruvate C6H6N2O3 155.043 1.40 + 1.413 ↑**
10 Pyrimidodiazepine C9H11N5O2 221.092 5.76 + 1.413 ↓*
11 Dehydroepiandrosterone C19H28O2 288.289 12.59 + 1.394 ↓*
12 6-Phosphogluconic acid C6H13O10P 259.169 12.63 + 1.370 ↑**
13 Pyrrolidonecarboxylic acid C5H7NO3 130.050 7.51 + 1.358 ↑**
14 N6-(L-1, 3-Dicarboxypropyl)-L-lysine C11H20N2O6 277.139 1.40 + 1.340 ↑**
15 D-Allulose 6-phosphate C6H13O9P 261.058 1.71 + 1.337 ↑**
16 Ciliatine C2H8NO3P 125.986 1.25 + 1.325 ↑**
17 Choline C5H14NO 104.106 3.48 + 1.316 ↑**
18 Argininosuccinic acid C10H18N4O6 291.129 1.46 + 1.296 ↑*
19 L-Tyrosine C9H11NO3 182.081 3.80 + 1.292 ↓*
20 Citrulline C6H13N3O3 176.103 1.48 + 1.278 ↑***
21 L-Asparagine C4H8N2O3 133.061 1.41 + 1.255 ↑**
22 L-Glutamine C5H10N2O3 147.076 1.42 + 1.253 ↑**
23 Myristic acid C14H28O2 229.180 12.34 + 1.252 ↑**
24 L-Isoleucine C6H13NO2 132.066 3.71 + 1.241 ↑**
25 D-Glucose 1-phosphate C6H13O9P 261.037 1.49 + 1.239 ↑**
26 Glutathione C10H17N3O6S 308.091 2.52 + 1.195 ↑*
27 UMP C9H13N2O9P 325.043 2.35 + 1.193 ↑**
28 Phosphorylcholine C5H15NO4P 184.073 1.42 + 1.183 ↑**
29 Betaine C5H11NO2 118.061 1.48 + 1.159 ↑**
30 Dodecanoic acid C12H24O2 199.976 0.74 + 1.146 ↑*
31 Thiamine C12H17N4OS 265.112 1.45 + 1.130 ↑**
32 CMP C9H14N3O8P 324.059 1.64 + 1.123 ↑**
33 Phenol C6H6O 94.046 7.93 + 1.117 ↑*
34 1, 1-Dimethylbiguanide C4H11N5 129.103 1.26 + 1.114 ↑**
35 O-Phosphoethanolamine C2H8NO4P 141.959 1.04 + 1.111 ↑*
36 L-Lysine C6H14N2O2 147.113 1.26 + 1.109 ↑**
37 L-Glutamic acid C5H9NO4 148.059 1.48 + 1.106 ↑**
38 Citicoline C14H26N4O11P2 489.113 1.50 + 1.106 ↑*
39 Pyridoxamine C8H12N2O2 169.095 1.28 + 1.099 ↑**
40 Acetylcholine C7H16NO2 146.117 1.59 + 1.090 ↑**
41 D-4-Phosphopantothenate C9H18NO8P 299.081 5.25 + 1.079 ↑*
42 Norepinephrine C8H11NO3 169.977 2.24 + 1.077 ↑*
43 Stearidonic acid C18H28O2 277.216 12.07 + 1.067 ↑**
44 Caffeine C8H10N4O2 195.085 12.93 + 1.055 ↑*
45 AICAR C9H15N4O8P 339.069 2.38 + 1.043 ↑**
46 1-Methylhistamine C6H11N3 126.103 1.24 + 1.038 ↑**
), ArticleFig(id=1198960147222589473, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628673407512821, language=CN, label=Table 2, caption=

RSV-infected mice lung tissue biomarkers. *P < 0.05, **P < 0.01, ***P < 0.001 vs Control group. ↓: Down; ↑: Up; VIP: Variable importance for the projection; ESI: Electrospray ionization; ADP: Adenosine diphosphate; UMP: Uridine monophosphate; CMP: Cytidine monophosphate

, figureFileSmall=null, figureFileBig=null, tableContent=
No. Metabolite Formula m/z tR/min ESI mod VIP Trend
C/M
1 Guanine C5H5N5O 176.103 1.48 + 2.068 ↓***
2 Thymidine C10H14N2O5 223.028 10.21 - 2.026 ↑*
3 L-Homophenylalanine C10H13NO2 180.102 11.32 + 1.936 ↑**
4 Thymine C5H6N2O2 127.050 4.67 + 1.687 ↓**
5 Taurocholic acid C26H45NO7S 516.297 10.86 + 1.674 ↑**
6 Uric acid C5H4N4O3 169.035 1.66 + 1.603 ↑**
7 ADP C10H15N5O10P2 428.036 1.66 + 1.469 ↑*
8 Adenosine diphosphate ribose C15H23N5O14P2 560.081 2.21 + 1.415 ↑*
9 Imidazol-5-yl-pyruvate C6H6N2O3 155.043 1.40 + 1.413 ↑**
10 Pyrimidodiazepine C9H11N5O2 221.092 5.76 + 1.413 ↓*
11 Dehydroepiandrosterone C19H28O2 288.289 12.59 + 1.394 ↓*
12 6-Phosphogluconic acid C6H13O10P 259.169 12.63 + 1.370 ↑**
13 Pyrrolidonecarboxylic acid C5H7NO3 130.050 7.51 + 1.358 ↑**
14 N6-(L-1, 3-Dicarboxypropyl)-L-lysine C11H20N2O6 277.139 1.40 + 1.340 ↑**
15 D-Allulose 6-phosphate C6H13O9P 261.058 1.71 + 1.337 ↑**
16 Ciliatine C2H8NO3P 125.986 1.25 + 1.325 ↑**
17 Choline C5H14NO 104.106 3.48 + 1.316 ↑**
18 Argininosuccinic acid C10H18N4O6 291.129 1.46 + 1.296 ↑*
19 L-Tyrosine C9H11NO3 182.081 3.80 + 1.292 ↓*
20 Citrulline C6H13N3O3 176.103 1.48 + 1.278 ↑***
21 L-Asparagine C4H8N2O3 133.061 1.41 + 1.255 ↑**
22 L-Glutamine C5H10N2O3 147.076 1.42 + 1.253 ↑**
23 Myristic acid C14H28O2 229.180 12.34 + 1.252 ↑**
24 L-Isoleucine C6H13NO2 132.066 3.71 + 1.241 ↑**
25 D-Glucose 1-phosphate C6H13O9P 261.037 1.49 + 1.239 ↑**
26 Glutathione C10H17N3O6S 308.091 2.52 + 1.195 ↑*
27 UMP C9H13N2O9P 325.043 2.35 + 1.193 ↑**
28 Phosphorylcholine C5H15NO4P 184.073 1.42 + 1.183 ↑**
29 Betaine C5H11NO2 118.061 1.48 + 1.159 ↑**
30 Dodecanoic acid C12H24O2 199.976 0.74 + 1.146 ↑*
31 Thiamine C12H17N4OS 265.112 1.45 + 1.130 ↑**
32 CMP C9H14N3O8P 324.059 1.64 + 1.123 ↑**
33 Phenol C6H6O 94.046 7.93 + 1.117 ↑*
34 1, 1-Dimethylbiguanide C4H11N5 129.103 1.26 + 1.114 ↑**
35 O-Phosphoethanolamine C2H8NO4P 141.959 1.04 + 1.111 ↑*
36 L-Lysine C6H14N2O2 147.113 1.26 + 1.109 ↑**
37 L-Glutamic acid C5H9NO4 148.059 1.48 + 1.106 ↑**
38 Citicoline C14H26N4O11P2 489.113 1.50 + 1.106 ↑*
39 Pyridoxamine C8H12N2O2 169.095 1.28 + 1.099 ↑**
40 Acetylcholine C7H16NO2 146.117 1.59 + 1.090 ↑**
41 D-4-Phosphopantothenate C9H18NO8P 299.081 5.25 + 1.079 ↑*
42 Norepinephrine C8H11NO3 169.977 2.24 + 1.077 ↑*
43 Stearidonic acid C18H28O2 277.216 12.07 + 1.067 ↑**
44 Caffeine C8H10N4O2 195.085 12.93 + 1.055 ↑*
45 AICAR C9H15N4O8P 339.069 2.38 + 1.043 ↑**
46 1-Methylhistamine C6H11N3 126.103 1.24 + 1.038 ↑**
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No. Pathway name Total Hits Raw P FDR Impact
1 D-Glutamine and D-glutamate metabolism 5 2 0.002 0.015 0.500
2 Phenylalanine, tyrosine and tryptophan biosynthesis 8 2 0.005 0.858 0.500
3 Arginine biosynthesis 9 2 0.006 0.015 0.462
4 Alanine, aspartate and glutamate metabolism 11 3 0.000 0.077 0.333
5 Glutathione metabolism 13 3 0.001 0.947 0.276
6 Tyrosine metabolism 12 2 0.011 1.000 0.228
7 Pyrimidine metabolism 23 4 0.000 0.051 0.191
8 Starch and sucrose metabolism 7 2 0.004 1.000 0.162
9 Purine metabolism 38 2 0.097 0.080 0.124
10 Pentose phosphate pathway 12 3 0.001 1.000 0.120
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Result of metabolic pathway analysis of C vs M. Total: The total number of metabolites in the target metabolic pathway; Hits: Number of differential metabolites in target metabolic pathways; Raw P: The P value for the hypergeometric distribution test; FDR: The false positive corrected value; Impact: The metabolic pathway impact value

, figureFileSmall=null, figureFileBig=null, tableContent=
No. Pathway name Total Hits Raw P FDR Impact
1 D-Glutamine and D-glutamate metabolism 5 2 0.002 0.015 0.500
2 Phenylalanine, tyrosine and tryptophan biosynthesis 8 2 0.005 0.858 0.500
3 Arginine biosynthesis 9 2 0.006 0.015 0.462
4 Alanine, aspartate and glutamate metabolism 11 3 0.000 0.077 0.333
5 Glutathione metabolism 13 3 0.001 0.947 0.276
6 Tyrosine metabolism 12 2 0.011 1.000 0.228
7 Pyrimidine metabolism 23 4 0.000 0.051 0.191
8 Starch and sucrose metabolism 7 2 0.004 1.000 0.162
9 Purine metabolism 38 2 0.097 0.080 0.124
10 Pentose phosphate pathway 12 3 0.001 1.000 0.120
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No. Pathway name Raw P -lgP Impact Super pathway
1 Phenylalanine, tyrosine and tryptophan biosynthesis 0.047 1.328 0.500 Amino acid
2 Arachidonic acid metabolism 0.355 0.450 0.333 Lipid
3 Histidine metabolism 0.288 0.541 0.224 Amino acid
4 Tyrosine metabolism 0.015 1.834 0.189 Amino acid
5 Alanine, aspartate and glutamate metabolism 0.401 0.397 0.140 Amino acid
6 Pyrimidine metabolism 0.077 1.113 0.097 Nucleotide
7 Purine metabolism 0.305 0.515 0.086 Nucleotide
8 Lysine degradation 0.261 0.583 0.047 Amino acid
9 Steroid hormone biosynthesis 0.613 0.212 0.041 Lipid
10 Primary bile acid biosynthesis 0.041 1.388 0.035 Lipid
11 Pantothenate and CoA biosynthesis 0.370 0.431 0.034 Cofactors and vitamin
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The main metabolic pathway and belonging of different metabolites of M vs H. -lgP: Negative natural logarithm of P

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No. Pathway name Raw P -lgP Impact Super pathway
1 Phenylalanine, tyrosine and tryptophan biosynthesis 0.047 1.328 0.500 Amino acid
2 Arachidonic acid metabolism 0.355 0.450 0.333 Lipid
3 Histidine metabolism 0.288 0.541 0.224 Amino acid
4 Tyrosine metabolism 0.015 1.834 0.189 Amino acid
5 Alanine, aspartate and glutamate metabolism 0.401 0.397 0.140 Amino acid
6 Pyrimidine metabolism 0.077 1.113 0.097 Nucleotide
7 Purine metabolism 0.305 0.515 0.086 Nucleotide
8 Lysine degradation 0.261 0.583 0.047 Amino acid
9 Steroid hormone biosynthesis 0.613 0.212 0.041 Lipid
10 Primary bile acid biosynthesis 0.041 1.388 0.035 Lipid
11 Pantothenate and CoA biosynthesis 0.370 0.431 0.034 Cofactors and vitamin
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基于代谢组学的黄芩抗RSV肺炎作用机制研究
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贾明倩 1 , 高燕 2 , 刘璐 2 , 马露兰 1 , 陈曦 1 , 张悦 2 , 王杨海 1 , 赵渤年 2, *
药学学报 | 研究论文 2023,58(7): 1780-1789
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药学学报 | 研究论文 2023, 58(7): 1780-1789
基于代谢组学的黄芩抗RSV肺炎作用机制研究
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贾明倩1, 高燕2, 刘璐2, 马露兰1, 陈曦1, 张悦2, 王杨海1, 赵渤年2, *
作者信息
  • 1.山东中医药大学药学院, 山东 济南 250355
  • 2.山东中医药大学中医药创新研究院, 山东 济南 250355

通讯作者:

*赵渤年, E-mail:
Effect of Scutellaria baicalensis Georgi on metabolism in RSV infection mice based on metabolomics
Ming-qian JIA1, Yan GAO2, Lu LIU2, Lu-lan MA1, Xi CHEN1, Yue ZHANG2, Yang-hai WANG1, Bo-nian ZHAO2, *
Affiliations
  • 1. College of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China
  • 2. Institute of Innovation in Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250355, China
出版时间: 2023-07-12 doi: 10.16438/j.0513-4870.2022-1082
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本研究基于UPLC-Q-Exactive HF X-MS的代谢组学技术探讨黄芩(Scutellaria baicalensis Georgi, SG) 对呼吸道合胞病毒(respiratory syncytial virus, RSV) 感染模型小鼠的改善作用, 寻找可协助RSV肺炎诊断的生物标记物, 分析黄芩发挥抗RSV活性的代谢途径。采用滴鼻感染RSV方法建立RSV肺炎小鼠模型, 评价小鼠体重变化、肛温变化以及肺组织病理损伤。采集各组小鼠的肺组织样品, 进行UPLC-Q-Exactive HF X-MS分析, 通过代谢组学技术挖掘黄芩药物干预的差异性代谢物, 并对黄芩调控的代谢通路进行分析。结果表明, 黄芩能显著改善模型小鼠肺组织病理状态, 使模型小鼠体重、肛温趋于正常; 肺组织样本中, 筛选出RSV模型小鼠疾病发展的生物标志物鸟嘌呤、L-天冬酰胺、花生四烯酸等46个, 黄芩通过回调其中的尿酸、花生四烯酸、丙氨酸等22个潜在生物标志物发挥改善RSV感染作用, 22个潜在标志物主要涉及11条异常代谢通路, 其中与苯丙氨酸、酪氨酸和色氨酸生物合成, 花生四烯酸代谢, 丙氨酸、天冬氨酸和谷氨酸代谢等5条代谢通路密切相关。黄芩主要通过调节氨基酸类、脂类、辅因子和维生素以及核苷酸类代谢物发挥改善RSV感染小鼠的作用。所有动物实验均在山东中医药大学动物伦理审查委员会的指导和批准下进行(批准号: SDUTCM20210311001)。

黄芩  /  呼吸道合胞病毒  /  代谢组学  /  作用机制

This study, aiming at finding biomarkers which can assist in the diagnosis of respiratory syncytial virus (RSV) pneumonia and analyzing the metabolic pathways of anti-RSV activity of Scutellaria baicalensis Georgi (SG)., explores the improvement effect of SG on mice models infected by RSV with the metabolomics technology based on UPLC-Q-Exactive HF X-MS. Mice models affected by RSV are established by nasal drip method and the changes of body weight, rectal temperature and pathological damage of lung tissue are evaluated. The lung tissue samples of mice in each group are collected and analyzed by UPLC-Q-Exactive HF X-MS. The differential metabolites of SG drug intervention are explored by metabolomics technology, and the metabolic pathways regulated by SG are analyzed. The results show that SG can significantly improve the pathological state of the lung tissue of the mice and make its body weight and rectal temperature tend to be normal. In the lung tissue samples, 46 biomarkers, such as guanine, L-asparagine, and arachidonic acid, are screened for disease development in RSV model mice. SG improved RSV infection by recalling 22 potential biomarkers, such as uric acid, arachidonic acid, and alanine. The 22 potential markers mainly involved 11 abnormal metabolic pathways, including phenylalanine, tyrosine, and tryptophan biosynthesis, and arachidonic acid metabolism, alanine, aspartic acid and glutamate metabolism are closely related to the five metabolic pathways. SG improves RSV-infected mice mainly by regulating amino acids, lipids, cofactors and vitamins and nucleotide metabolites. All animal experiments were conducted under the guidance and approval of the Animal Ethics Review Committee of Shandong University of Traditional Chinese Medicine. (approval number: SDUTCM20210311001).

Scutellaria baicalensis Georgi  /  respirator syncytial virus  /  metabolomics  /  mechanism
贾明倩, 高燕, 刘璐, 马露兰, 陈曦, 张悦, 王杨海, 赵渤年. 基于代谢组学的黄芩抗RSV肺炎作用机制研究. 药学学报, 2023 , 58 (7) : 1780 -1789 . DOI: 10.16438/j.0513-4870.2022-1082
Ming-qian JIA, Yan GAO, Lu LIU, Lu-lan MA, Xi CHEN, Yue ZHANG, Yang-hai WANG, Bo-nian ZHAO. Effect of Scutellaria baicalensis Georgi on metabolism in RSV infection mice based on metabolomics[J]. Acta Pharmaceutica Sinica, 2023 , 58 (7) : 1780 -1789 . DOI: 10.16438/j.0513-4870.2022-1082
呼吸道合胞病毒(respiratory syncytial virus, RSV) 为副黏病毒科、肺炎病毒属单股负链RNA病毒, 是引起呼吸道感染最常见的病原之一[1, 2]。RSV感染后引起呼吸道纤毛上皮细胞损伤, 促使机体产生过度的免疫反应, 支气管、细支气管、肺泡受损进而导致肺炎, 严重时可危及生命, 对婴幼儿、老年人和免疫力低下的患者来说是首要威胁[3-5]
中药黄芩(Scutellaria baicalensis Georgi, SG) 是唇形科黄芩属多年生草本植物, 别名山茶根、土金茶根。黄芩的临床应用历史悠久, 在诸多经典专著和名方中均有记载, 也是临床常用中成药双黄连制剂、蓝芩口服液的重要成分。黄芩有清热燥湿、泻火解毒等功效, 其临床组方通常用于治疗呼吸系统疾病, 在抗呼吸道感染、抗病毒方面作用尤其显著[6, 7], 大量文献报道显示, 黄芩具有较强抗病毒作用。Li等[8]采用MTT法和细胞病变程度法, 考察8批不同产地黄芩水提物样品及其对应的模拟样品对人喉癌细胞Hep-2的TD50和对呼吸道合胞病毒(RSV) 的IC50, 并计算TI, 发现8批不同产地黄芩水提物对RSV均具有抑制作用; Wang等[9]采用细胞体外抗病毒实验, 通过CPE法结合MTT法得出TC50、EC50, 并且以治疗指数作为评价指标, 结果表明黄芩提取物对RSV有抗病毒活性; Du等[10]通过建立RSV感染小鼠的脂质代谢组学研究方法, 对血浆和肺组织样品中黄芩干预前后脂质代谢物组的变化进行考察, 结果显示, RSV感染可能与甘油磷脂酰胆碱(PC)、鞘磷脂(SM)、甘油三酯(TG) 代谢密切相关, 黄芩水提液干预后能通过调节紊乱的脂质代谢起抗病毒作用; Gao等[11]采用CPE法对黄芩抗病毒疗效进行筛选, 发现黄芩对呼吸道合胞病毒作用明显。但目前针对黄芩抗RSV感染作用机制方面的研究较少。代谢组学是以组群指标分析为基础、以高通量检测和数据处理为手段、以信息建模与系统整合为目标的系统生物学的一个分支, 旨在检测外界干扰后内源性代谢物的变化, 找出与干扰相关的差异代谢物, 阐释机体疾病代谢机制[12]。本研究应用基于UPLC-Q-Exactive Orbitrap-MS的非靶向代谢组学技术, 对小鼠的肺部组织进行研究, 分析小鼠RSV肺炎感染相关的差异表达内源性代谢物与代谢通路, 并进一步分析差异表达代谢物在黄芩给药干预后的回调状态, 阐述黄芩抗RSV作用在影响体内代谢层面的作用方式。
仪器  Q-Exactive Focus质谱仪和UltiMate 3000 UPLC系统(美国Thermo公司); SCIENTZ-48组织研磨器(宁波新芝生物科技股份有限公司); QL-866混匀仪(德国Vortex Mixer公司); H1850-R冷冻离心机(湖南湘仪有限公司)。
药物与试剂  黄芩药材(批号: 20210914, 购自山东济南黄芩种植基地, 经山东省中医药研究院研究员林慧彬研究员鉴定均为唇形科植物黄芩Scutellaria baicalensis Georgi的干燥根); 呼吸道合胞病毒(山东省医学科学院提供); cholic acid-2, 2, 3, 4, 4, -d5 (CAS: 53007-09-3; 纯度≥98%)、succinic acid-2, 2, 3, 3, -d4 (CAS: 14493-42-6; 纯度≥99%) 购自Sigma公司; DL-tryptophan-2, 3, 3-d3 (CAS: 340257-61-6); DL-methionine-3, 3, 4, 4-d4 (CAS: 93709-61-6) 购自CDN公司; L-phenylalanine (ring-d5) (CAS: 14493-42-6; 纯度≥98%)、choline chloride (trimethyl-d9) (纯度≥98%) 购自美国CIL公司。甲醇、乙腈(≥99.0%) 均购自美国Thermo公司; 甲酸铵(≥99.0%) 购自美国Sigma公司; 甲酸为LC-MS级, 其他试剂均为分析纯。
实验动物  雄性SPF级BALB/c小鼠(10~12 g), 二周龄, 由北京维通利华实验动物技术有限公司提供, 动物许可证号SCXK (京) 2021-0006。动物福利和实验过程均遵循山东中医药大学动物伦理委员会的规定(批准号: SDUTCM20210311001)。
黄芩水提液的制备  黄芩药材粉碎后过筛(4号筛) 制得药材中粉, 根据实验室前期研究基础对其进行了化学成分表征。精密称取黄芩中粉2.836 g, 置圆底烧瓶内, 加入沸水(料液比1∶80), 称定重量后加热回流提取40 min, 每10 min振摇一次, 取出放至室温, 用蒸馏水补足失重, 滤过, 离心(转速2 500 r·min-1) 15 min, 取上清液于蒸发皿浓缩至适量, 转移至量瓶中, 加水定容至10 mL, 置于离心管冻存备用(283.6 mg·mL-1)。
动物分组与给药  选用雄性BALB/c (2周龄或10~12 g)小鼠, 检疫合格后, 随机分为空白组(C)、模型组(M)、黄芩给药组(H), 每组8只, 称重, 于清洁环境适应性生长2天。预给药2天, 于第3天通过滴鼻感染方式接种RSV病毒(TCID50 = 1×10-6), 每只35 µL, 正常组小鼠滴鼻接种等量的生理盐水, 于接种后开始灌胃给药治疗, 每天1次, 连续3天。其中空白组和模型组灌胃给与蒸馏水, 给药组灌胃给予黄芩水提液(10 µL·g-1), 期间观察小鼠精神状态, 毛色光泽、饮食情况等, 记录每日小鼠体重、测量肛温。
观察指标  根据实验室前期研究基础, 于末次给药6 h后解剖, 取肺进行称重。每组8份生物学重复样本, 分别记作C1~C8、M1~M8、H1~H8。取小鼠左肺以4%多聚甲醛溶液固定, 石蜡包埋, 切片, HE染色, 于光学显微镜下观察其病理变化; 小鼠右肺进行代谢组学研究。
肺组织样本处理  取全部样本于2 mL EP管中, 加入2颗钢珠, 放入组织研磨仪中, 55 Hz研磨60 s, 将样本匀浆处理; 精确称量匀浆后样本88.3~101.7 mg于2 mL EP管中, 准确加入0.6 mL甲醇(含内标), 涡旋振荡30 s; 加入2颗钢珠, 放入组织研磨仪中, 50 Hz研磨60 s; 12 000 r·min-1, 4 ℃离心10 min, 取全部上清液过0.22 μm滤膜过滤, 滤液加入到检测瓶中, 进行LC-MS上机检测。
UPLC-Q-Exactive Orbitrap-MS检测方法建立  色谱条件: 色谱柱为Waters ACQUITY UPLC HSS T3 C18 (2.1 mm × 150 mm, 1.8 μm); 流动相: 正离子模式为0.1%甲酸水(C)-0.1%甲酸乙腈(D); 负离子模式为5 mmol·L-1甲酸铵水(A)-乙腈(B)。梯度洗脱程序: 正离子模式: 0~1 min, 2% D; 1~9 min, 2%~50% D; 9~12 min, 50%~98% D; 12~13.5 min, 98% D; 13.5~14 min, 98%~2% D; 14~20 min, 2% D; 负离子模式: 0~1 min, 2% B; 1~9 min, 2%~50% B; 9~12 min, 50%~98% B; 12~13.5 min, 98% B; 13.5~14 min, 98%~2% B; 14~17 min, 2% B。进样量: 2 μL; 流速: 0.25 mL·min-1; 柱温: 40 ℃; 自动进样器温度8 ℃。
质谱条件: 离子源为电喷雾离子源(electrospray ionization, ESI), 扫描模式为正负离子电离模式, 正离子喷雾电压3.50 kV, 负离子喷雾电压为2.50 kV, 鞘气30 L·min-1, 辅助气10 L·min-1, 毛细管温度325 ℃, 以分辨率35 000进行全扫描, 扫描范围81~1 000, 采用HCD进行二级裂解, 碰撞电压为30 eV, 同时采用动态排除去除无必要的MS/MS信息。
数据处理  将LC-MS测得原始数据经Proteowizard软件(v3.0.8789) 转换为mzXML格式, 使用R (v3.3.2) 的XCMS程序包进行峰识别、峰过滤、峰对齐等分析(主要参数有bw = 2, δ = 15, peak width = c(5, 30), mzwid = 0.015, mzdiff = 0.01, method = cent Wave), 获得色谱峰质核比(m/z)、保留时间(retention time, tR) 及峰面积等信息; 将预处理后的数据导入SIMCA-P (v13.0) 进行多元统计分析, 具体方法包括主成分分析(PCA)、偏最小二乘判别分析(PLS-DA)、正交-偏最小二乘判别分析(OPLS-DA), 并采用置换检验和t检验, 分别检测OPLS-DA模型的稳健性和分析标志性代谢物的组间差异。
根据OPLS-DA模型分析所得变量的投影重要性(variable importance for the projection, VIP) 值, 结合组间比较非参数t检验的P值, 将符合VIP ≥ 1且P ≤ 0.05和one-way ANOVA P-value ≤ 0.05的变量进行初步筛选; 然后根据精确分子量(误差δ $ \pm $ 15) 和碎片离子等信息通过查询Metlin数据库(http://metlin.scripps.edu)、MoNA数据库(https://mona.fiehnlab.ucdavis.edu) 和Human Metabolone Database (HMDB, https://hmdb.ca) 获得差异代谢物信息, 对潜在生物标志物进行鉴定; 最终将潜在生物标志物利用KEGG (http://www.genome.jp/kegg/) 网站和MetPA数据库(www.metaboanalyst.ca) 进行生物代谢通路富集分析。
正常组小鼠皮毛干爽有光泽, 行为活泼, 体重增长显著。小鼠感染RSV后, 初期症状主要表现为呼吸短促, 挠鼻子, 行动迟缓等症状; 后期模型组出现食欲下降, 体重降低, 肛温升高, 呼吸急促, 打喷嚏等症状, 给药组小鼠症状有所缓解, 体重对于模型组有所升高, 肛温较模型组降低, 与正常组相比均无显著性差异。具体结果如图 1AB所示。
肺组织病理切片结果如图 1C显示, 空白组(Control) 肺泡及各级支气管结构清晰完整。模型组(M) 血管周围、小血管周围炎性细胞浸润, 弥漫性肺脏炎性细胞浸润, 肺泡隔增厚、肺泡隔炎性细胞浸润(淋巴细胞、中性粒细胞为主)。黄芩给药组(H) 肺组织明显改善, 呈现局灶性肺泡隔增厚、肺泡隔炎性细胞浸润(中性粒细胞、淋巴细胞为主)。
在检测时利用质量控制(quality control, QC) 样本来考察实验器材的稳定性和操作上的可重复性, 从PCA分析图(图 2AB) 可看出QC样本密集分布, 说明仪器稳定、重复性良好、数据可靠。
不同组别样品在正、负离子模式下的谱图如图 3所示。对过滤后的数据进行二级质谱碎片鉴定, 结果显示在负离子模式下共鉴定出12个代谢物, 正离子模式下鉴定出121个代谢物, 这些代谢物主要为氨基酸类和脂肪酸化合物。
为了更好揭示组间差异及代谢轮廓, 采用一种有监督的化学计量方法OPLS-DA进行数据分析。OPLS-DA可以在不降低模型预测能力的前提下, 有效减少模型的复杂性和增强模型的解释能力。分析结果如图 4表 1所示, OPLS-DA得分图中, 正、负离子模式下样本基本处于95%置信区间内, 组间分离趋势明显, 各组样本两两比较区分非常显著, 提示各组间代谢模式存在差异; 验证参数表中, 各组间R2Y值均大于0.9, Q2值均大于0.7, 几乎接近于1, 说明所建的数学模型稳定可靠, 预测能力良好, 且模型不存在过拟合, 数据可信。
通过多元统计分析结果发现不同组别小鼠存在代谢物的明显差异, 基于OPLS-DA模型, 筛选VIP ≥ 1且P ≤ 0.05和one-way ANOVA P-value ≤ 0.05的差异变量, 然后根据差异代谢物精确分子量(分子量误差δ < 15) 和MS/MS模式所得碎片信息在Metlin、MoNA、Human Metabolone Database (HMDB) 数据库中进一步匹配注释完成差异代谢物的鉴定。最终在空白组与模型组间共鉴定出46个潜在差异代谢物, 见表 2, 结果发现RSV感染模型小鼠肺中有多个代谢物群发生了明显变化, 其中胸腺嘧啶核苷、L-高苯丙氨酸、牛磺胆酸、尿酸、二磷酸腺苷、二磷酸腺苷核糖等含量升高, 鸟嘌呤、胸腺嘧啶、嘧啶二氮䓬、脱氢表雄酮、L-酪氨酸等含量降低。RSV感染小鼠经给予黄芩药物干预后, 46个差异代谢物中有22种代谢物发生显著回调, 主要为鸟嘌呤、胸腺嘧啶核苷、L-高苯丙氨酸、胸腺嘧啶、二磷酸腺苷等差异代谢物, 如图 5所示, 说明黄芩对RSV感染小鼠肺组织中的代谢轮廓有一定的调节作用。
将空白组与模型组对比筛选所得差异代谢物进行KEGG代谢通路分析, 并采用MetPA数据库对相关代谢通路进行富集分析和拓扑分析, 结果如图 6A所示, 发现小鼠经RSV感染后, 主要影响(Impact前10位的代谢通路) 了D-谷氨酰胺和D-谷氨酸代谢, 苯丙氨酸、酪氨酸和色氨酸生物合成, 精氨酸生物合成, 丙氨酸、天冬氨酸和谷氨酸代谢, 谷胱甘肽代谢, 酪氨酸代谢, 嘧啶代谢, 淀粉和蔗糖代谢, 嘌呤代谢和戊糖磷酸途径见表 3
将模型组与黄芩给药组的差异代谢物进行KEGG和MetPA分析, 如表 4所示, 为22种差异性代谢产物涉及的潜在主要代谢功能, 分别归于氨基酸代谢、脂质代谢、辅酶因子和维生素代谢以及核苷酸代谢。如图 7所示, 为主要代谢物及其可能代谢通路转化图。根据图 6B重要性排名可知, 黄芩给药干预后差异代谢物所涉及的代谢通路以苯丙氨酸、酪氨酸和色氨酸生物合成, 花生四烯酸代谢, 丙氨酸、天冬氨酸和谷氨酸代谢, 组氨酸代谢, 嘌呤代谢等为主, 推测为黄芩抗RSV感染的关键通路。
基于UPLC-Q-Exactive HF X-MS液质联用技术对各组别样本的代谢轮廓进行分析, 筛选差异代谢物和相关代谢通路分析。QC验证实验表明仪器系统稳定, 实验数据可靠。通过对C vs M与M vs H差异性代谢物及代谢通路进行分析发现, 小鼠在受到RSV感染后, 多种内源性物质发生代谢紊乱, 经黄芩给药干预后, 可对鸟嘌呤、胸腺嘧啶核苷、花生四烯酸、脱氢表雄酮、N6-(L-1, 3-二羧丙基)-L-赖氨酸和苯丙氨酸等22个内源性代谢物进行显著回调, 推测其为黄芩抗RSV治疗作用的潜在生物标志物。代谢通路拓扑分析提示, 推测苯丙氨酸、酪氨酸和色氨酸生物合成, 花生四烯酸代谢, 丙氨酸、天冬氨酸和谷氨酸代谢, 组氨酸代谢和嘌呤代谢为黄芩干预RSV感染小鼠的潜在的靶标通路。
氨基酸是构成生物体营养所需蛋白质的基本单位, 在许多代谢通路中起重要作用, 蕴含着重要的反映机体代谢和功能状态的生物化学信息[13]。氨基酸代谢是生命活动的一个重要基础, 任何氨基酸的异常都会影响免疫系统[14]。苯丙氨酸、酪氨酸和色氨酸的生物合成途径与苯丙氨酸有关[15], 苯丙氨酸在体内大部分经苯丙氨酸羟化酶催化作用氧化成酪氨酸, 并与酪氨酸一起合成重要的神经递质和激素, 参与机体糖代谢和脂肪代谢[16]。色氨酸也是人体的必需氨基酸之一, 在代谢网络调控中起重要作用, 色氨酸代谢主要发生于炎症组织中, 具有抗病毒和免疫调节作用。研究发现, RSV肺炎患儿苯丙氨酸、色氨酸含量异常, RSV病毒复制增多, 促进T细胞活化, 诱导免疫反应, 加重炎症反应[17]。丙氨酸、天冬氨酸和谷氨酸代谢与组氨酸代谢均为氨基酸代谢的重要环节。丙、谷氨酸是体内的非必需氨基酸, 谷氨酸可用于合成谷氨酰胺, 调节体内氨水平, 通过谷氨酸脱氢酶反应脱氨为α-酮戊二酸, 并释放到血液中[18]; 天冬氨酸主要存在于脑和内分泌器官中, 是一种兴奋性神经递质, 参与机体内多种代谢过程[19-21]。研究发现[22-24], RSV感染后, 体内谷氨酸、天冬氨酸含量升高, 引发咳嗽、反复喘息和哮喘等并发症, 造成呼吸肌强烈兴奋, 而给予药物治疗后, 含量下降, 说明黄芩可能通过调节丙氨酸、天冬氨酸和谷氨酸代谢通路发挥抗RSV感染作用。组氨酸是一种膳食必需氨基酸, 是形成抗体内血红蛋白、肌肽、组胺等一系列重要物质的来源, 组氨酸的代谢主要是通过水解形成尿酸, 另一方面在组氨酸脱羧酶(HDC) 作用下转化为组胺[25]。黄芩对这些通路的调节结果说明氨基酸代谢可能是黄芩潜在的抗RSV感染机制。
脂质代谢是调节和修饰蛋白质功能及相关生物学过程的重要途径, 并通过不同的机制发挥作用[26]。花生四烯酸是人体必需的脂肪酸, 是一种omega-6多不饱和脂肪酸, 在生物体内分布广泛且含量高, 参与炎症反应和免疫系统的调控, 对肺的生理功能及病理过程具有极其重要的调节作用[27, 28]。前列腺素、血栓烷、白三烯和羟基脂肪酸由花生四烯酸经一系列途径转化而得。这些代谢物在免疫调节、细胞信号转导、血管舒张等方面起重要作用, 如能增加炎症反应时血管通透性, 增加渗出液量并引起白细胞聚集, 改变肺的机械特性等[29, 30]。黄芩给药干预后, 可显著回调RSV感染小鼠的花生四烯酸水平, 推测花生四烯酸代谢可能为黄芩抗RSV感染的潜在代谢通路。
嘌呤和嘧啶是重要的信号分子, 在信号传导中主要通过嘌呤能信号受体发挥调节作用[31]。嘌呤代谢是指核酸碱基腺嘌呤及鸟嘌呤等的嘌呤衍生物的活体合成及分解, 最终形成尿酸的过程。研究表明[32]小鼠在感染流感病毒后产生肺炎, 使肺组织处在缺氧的状态下, 影响机体嘌呤代谢。此外, 代谢过程产生的尿酸对血管细胞具有一定的促炎作用, 使炎症反应加剧从而加重肺炎[33]。嘧啶代谢对细胞信号传导和能量代谢具有重要调节作用。有研究[34, 35]发现, 嘧啶代谢是治疗病毒性肺炎中一项重要调节信号通路, RSV感染后, 嘧啶代谢的基因在人肺细胞中大量表达, 且嘧啶代谢也是RSV感染幼儿愈后发生与不发生反复喘息之间发生变化最显著的通路之一。给药干预后, 黄芩给药组小鼠的鸟嘌呤、胸腺嘧啶核苷、胸腺嘧啶水平较模型组显著回调, 提示, 黄芩可通过影响嘌呤代谢和嘧啶代谢缓解RSV感染小鼠的症状。
综上所述, 本实验利用LC-MS的代谢组学分析方法研究发现, 黄芩通过调节苯丙氨酸、花生四烯酸、嘌呤、腺苷等差异代谢物含量, 干预苯丙氨酸、酪氨酸和色氨酸的生物合成, 组氨酸代谢, 丙氨酸、天冬氨酸和谷氨酸代谢, 花生四烯酸代谢等通路, 发挥治疗RSV感染肺炎的作用。本文提示, 在下一步研究中, 可以围绕主要代谢通路, 展开细致的靶向代谢组学研究, 深入挖掘黄芩抗RSV的作用机制。
作者贡献: 贾明倩负责实验操作、数据处理分析及文章撰写; 高燕负责指导实验实施、论文修改; 赵渤年负责整体实验设计、监督以及论文修改, 刘璐协助实验数据分析; 马露兰、陈曦、张悦和王杨海协助动物实验。
利益冲突: 本研究内容无任何利益冲突。
  • 国家重点研发计划子课题(2017YFC1701501)
  • 山东省自然科学基金联合基金项目(ZR2021LZY021)
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doi: 10.16438/j.0513-4870.2022-1082
  • 接收时间:2022-09-29
  • 首发时间:2025-11-21
  • 出版时间:2023-07-12
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  • 收稿日期:2022-09-29
  • 修回日期:2023-01-19
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国家重点研发计划子课题(2017YFC1701501)
山东省自然科学基金联合基金项目(ZR2021LZY021)
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    1.山东中医药大学药学院, 山东 济南 250355
    2.山东中医药大学中医药创新研究院, 山东 济南 250355

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2种不同金属材料的力学参数

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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