Article(id=1198652620442267758, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1198652605778985059, articleNumber=null, orderNo=null, doi=10.16438/j.0513-4870.2023-0521, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1682524800000, receivedDateStr=2023-04-27, revisedDate=1685980800000, revisedDateStr=2023-06-06, acceptedDate=null, acceptedDateStr=null, onlineDate=1763710654601, onlineDateStr=2025-11-21, pubDate=1691769600000, pubDateStr=2023-08-12, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1763710654601, onlineIssueDateStr=2025-11-21, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1763710654601, creator=13701087609, updateTime=1763710654601, updator=13701087609, issue=Issue{id=1198652605778985059, tenantId=1146029695717560320, journalId=1189982191388893191, year='2023', volume='58', issue='8', pageStart='0', pageEnd='2540', issueExtLink='null', onlineDate='null', pubDate='1691769600000', pubDateStr='2023-08-12', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1763710651106, creator='13701087609', updateTime=1763710739504, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1198652976601596347, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1198652605778985059, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1198652976601596348, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1198652605778985059, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2271, endPage=2282, ext={EN=ArticleExt(id=1198652620874281124, articleId=1198652620442267758, tenantId=1146029695717560320, journalId=1189982191388893191, language=EN, title=Innovation and application of metabolomics technology for research in the biomedical field, columnId=null, journalTitle=Acta Pharmaceutica Sinica, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Metabolomics technology played an important role in the field of biomedical research, such as disease diagnosis, pathogenesis analysis, drug target exploration, formulation of treatment guidelines, etc. Due to the systematic and holistic characteristics of metabolomics research, it has shown certain advantages in the analysis of the basis of pharmacodynamic substances of traditional Chinese medicines and the development of new medicines from traditional Chinese medicines. With the continuous innovation of metabolomics research, many advanced technologies have been developed, which make up for the shortcomings of conventional metabolomics studies in searching for disease targets, identifying functional compounds and interpreting biological significance. Furthermore, the rapid development of metabolomics technology has created new opportunities for the diagnosis of diseases and the development of new drugs in traditional Chinese medicine. Herein, different from conventional metabolomics techniques and methods, nine new metabolomics technologies with wide application prospects in the past 10 years were reviewed from the perspective of new tools, new ideas and new samples, with a view to providing new insights on relevant metabolomics research in the biomedical field and providing new motivation for innovation and development of metabolomics technologies.

, authors=null, authorsList=Jia-jun CHEN, Yu-zhi ZHOU, Xue-mei QIN, authorCompany=null, correspAuthors=Yu-zhi ZHOU, Xue-mei QIN, 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, fund=null), CN=ArticleExt(id=1198652625731285438, articleId=1198652620442267758, tenantId=1146029695717560320, journalId=1189982191388893191, language=CN, title=代谢组学技术在生物医药领域研究中的创新与应用, columnId=1190335349655180086, journalTitle=药学学报, columnName=综述, runingTitle=null, highlight=null, articleAbstract=

代谢组学技术在生物医药领域研究中发挥着重要作用, 如疾病诊断、发病机制解析、药物靶点探索、治疗指南制定等, 由于代谢组学研究有系统性、整体性等特点, 所以在剖析中药药效物质基础和开发中药新药方面表现出了一定优势。随着代谢组学研究的持续创新, 目前已经开发出许多先进的新技术, 弥补了常规代谢组学研究在寻找疾病靶点、识别功能化合物、阐释生物学意义等方面的不足。此外, 代谢组学技术的快速发展, 为疾病诊断和中药新药开发创造了新的机遇。在此基础上, 有别于常规代谢组学技术和方法, 本文从新工具、新思路和新样本角度综述了近10年具有广泛应用前景的9种代谢组学新技术, 以期为生物医药领域相关代谢组学研究提供新视角, 为代谢组学技术的创新和发展提供新动力。

, authors=null, authorsList=陈佳俊, 周玉枝, 秦雪梅, authorCompany=null, correspAuthors=周玉枝, 秦雪梅, authorNote=null, correspAuthorsNote=
*周玉枝, E-mail: ;
秦雪梅,
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代谢组学技术在生物医药领域研究中的创新与应用
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陈佳俊 1, 2, 3 , 周玉枝 1, 2, 3, * , 秦雪梅 1, 2, 3, *
药学学报 | 综述 2023,58(8): 2271-2282
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药学学报 |综述 2023 , 58 (8) : 2271 -2282
代谢组学技术在生物医药领域研究中的创新与应用
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陈佳俊1, 2, 3, 周玉枝1, 2, 3, * , 秦雪梅1, 2, 3, *
作者信息
  • 1.山西大学中医药现代研究中心, 山西 太原 030006
  • 2.山西大学化学生物学与分子工程教育部重点实验室, 山西 太原 030006
  • 3.地产中药功效物质研究与利用山西省重点实验室, 山西 太原 030006
通讯作者:
*周玉枝, E-mail: ;
秦雪梅,
Innovation and application of metabolomics technology for research in the biomedical field
Jia-jun CHEN1, 2, 3, Yu-zhi ZHOU1, 2, 3, * , Xue-mei QIN1, 2, 3, *
Affiliations
  • 1. Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan 030006, China
  • 2. The Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Shanxi University, Taiyuan 030006, China
  • 3. The Key Laboratory of Effective Substances Research and Utilization in TCM of Shanxi Province, Taiyuan 030006, China
出版时间: 2023-08-12 doi: 10.16438/j.0513-4870.2023-0521
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代谢组学技术在生物医药领域研究中发挥着重要作用, 如疾病诊断、发病机制解析、药物靶点探索、治疗指南制定等, 由于代谢组学研究有系统性、整体性等特点, 所以在剖析中药药效物质基础和开发中药新药方面表现出了一定优势。随着代谢组学研究的持续创新, 目前已经开发出许多先进的新技术, 弥补了常规代谢组学研究在寻找疾病靶点、识别功能化合物、阐释生物学意义等方面的不足。此外, 代谢组学技术的快速发展, 为疾病诊断和中药新药开发创造了新的机遇。在此基础上, 有别于常规代谢组学技术和方法, 本文从新工具、新思路和新样本角度综述了近10年具有广泛应用前景的9种代谢组学新技术, 以期为生物医药领域相关代谢组学研究提供新视角, 为代谢组学技术的创新和发展提供新动力。

代谢组学  /  新技术  /  新工具  /  新思路  /  新样本  /  精准医学

Metabolomics technology played an important role in the field of biomedical research, such as disease diagnosis, pathogenesis analysis, drug target exploration, formulation of treatment guidelines, etc. Due to the systematic and holistic characteristics of metabolomics research, it has shown certain advantages in the analysis of the basis of pharmacodynamic substances of traditional Chinese medicines and the development of new medicines from traditional Chinese medicines. With the continuous innovation of metabolomics research, many advanced technologies have been developed, which make up for the shortcomings of conventional metabolomics studies in searching for disease targets, identifying functional compounds and interpreting biological significance. Furthermore, the rapid development of metabolomics technology has created new opportunities for the diagnosis of diseases and the development of new drugs in traditional Chinese medicine. Herein, different from conventional metabolomics techniques and methods, nine new metabolomics technologies with wide application prospects in the past 10 years were reviewed from the perspective of new tools, new ideas and new samples, with a view to providing new insights on relevant metabolomics research in the biomedical field and providing new motivation for innovation and development of metabolomics technologies.

metabolomics  /  new technology  /  new tool  /  new idea  /  new sample  /  precision medicine
陈佳俊, 周玉枝, 秦雪梅. 代谢组学技术在生物医药领域研究中的创新与应用. 药学学报, 2023 , 58 (8) : 2271 -2282 . DOI: 10.16438/j.0513-4870.2023-0521
Jia-jun CHEN, Yu-zhi ZHOU, Xue-mei QIN. Innovation and application of metabolomics technology for research in the biomedical field[J]. Acta Pharmaceutica Sinica, 2023 , 58 (8) : 2271 -2282 . DOI: 10.16438/j.0513-4870.2023-0521
近几十年来, 代谢组学技术在生物医药领域研究中的应用逐渐增加, 如探索药物靶点、开发新药、制定治疗指南等[1]。随着代谢组学技术的持续创新, 生物医药领域研究者不断开发出高效的代谢组学新技术, 毫无疑问, 这将推动精准医疗的高质量发展。在过去的探索中, 许多研究者提出了代谢组学研究新工具和新思路, 如稳定同位素示踪代谢组学、质谱成像空间代谢组学、中医方证代谢组学和功能代谢组学, 有效弥补了常规代谢组学在精准识别标志物方面的不足。此外, 以血液、尿液、粪便、组织等经典样本为研究对象的常规代谢组学研究虽然能够表征疾病和药物影响的代谢轮廓, 但因缺乏特异性, 可能会导致真实受刺激或药物影响的代谢途径失去重视, 进而耽误研究进程。近年来, 基于疾病特异性的新样本代谢组学研究得到了广泛的关注和应用, 如外周血单个核细胞代谢组学、单细胞代谢组学、细胞器代谢组学(线粒体代谢组学、溶酶体代谢组学)、微生物代谢组学, 为病理机制和药效基础研究提供了新视角。众所周知, 常规代谢组学技术通常受限于表型研究, 无法深入解析生物学问题, 发展基于多学科交叉新工具和新思路的代谢组学新技术将能更全面地阐释生物医药领域研究的科学内涵。同时, 样本的选择是代谢组学研究考虑的最基本内容, 应直接基于研究目的, 发展基于疾病特异性新样本的代谢组学新技术将能更高效地反映不同环境下代谢轮廓的真实变化。因此, 笔者将围绕新工具、新思路和新样本3个角度对代谢组学新技术进行整理综述, 并侧重于分析中医药和大健康领域的研究, 以期为代谢组学新技术的应用和发展提供参考。
在常规代谢组学研究中, 液相色谱(liquid chromatography, LC) 和气相色谱(gas chromatography, GC) 是代谢物分离最常用的工具, 核磁共振(nuclear magnetic resonance, NMR) 和质谱(mass spectrometry, MS) 则在检测部分占主导地位[2]。LC和GC往往与MS联用(LC-MS、GC-MS) 进行代谢组学分析, 而NMR通常单独作为一种代谢组学分析工具。其中, LC-MS和GC-MS灵敏度较高, LC-MS检测物质范围较广, 而GC-MS更适合检测易挥发且对热稳定的物质, 样品通常需要衍生化, 限制了应用范围[1]。NMR对样品限制少, 同时, 对样品不会造成破坏, 但灵敏度较低, 仪器占地面积大, 成本高[1]。代谢组学研究的检测对象包括内源性和外源性的代谢物, 它们是化学反应的底物或产物[3], 分子量通常小于1 800 Da[4]。代谢组学研究方法主要有两种, 分别为非靶向代谢组学和靶向代谢组学[5]。非靶向代谢组学主要用于寻找差异代谢物, 代谢物检测范围广, 但不能准确反映代谢物的含量变化, 即半定量, 可用于识别新的代谢物。相反, 靶向代谢组学则更关注感兴趣的代谢物, 一般仅分析同种类型的代谢物, 检测范围有限, 但因结合代谢物标准品而能够对目标代谢物进行准确定量, 同时, 还能反映代谢物之间的作用关系[6, 7]。代谢组学研究的流程一般分为6个步骤[2]: 样本制备、代谢物测定与数据获取、数据处理、多变量分析、代谢物鉴定、生物功能挖掘(解释生物学意义), 如图 1所示。代谢组学研究的生物样本类型多样, 如细胞、组织、生物流体均可作为分析对象[7]。在数据处理方面, 非靶向代谢组学常用的数据处理平台有XCMS、Compound Discoverer、Mzmine等[8], 靶向代谢组学常用的数据处理平台有XCMS-MRM、MRMAnalyzer等[9]。此外, 多变量分析工具通常为SIMCA软件, 常用代谢物鉴定平台为HMDB、MetLine、BMRB等, 常用的生物功能挖掘平台为MetaboAnalyst、KEGG等[10-12]。目前, 代谢组学技术已被广泛应用于医药、环境和食品等领域[7], 值得注意的是, 代谢组学技术的理念与中医理论、中药化学成分的复杂性不谋而合, 因此, 代谢组学技术在中医药研究领域有着不可限量的研究前景[13]。代谢组学技术虽然是促进生物医药发展的有力工具, 但在应用过程中也面临着许多不足与挑战。例如, 在过往研究中筛选出的众多差异代谢物, 几乎很少能转化应用为临床诊断的生物标志物, 缺乏准确性。同时, 常规代谢组学研究的样本往往局限于组织匀浆和多细胞水平, 获取的结果尚不能直观表现代谢分布的特异性, 所以还需要进一步发展和创新。在生物功能挖掘方面, 基于数据库的代谢通路富集分析大多来源于已知通路, 容易出现假阳性结果, 并且很难再发现新途径。简而言之, 常规代谢组学技术已不能满足生物医药领域的应用需求, 因此亟需开发并应用代谢组学新技术解决当下的关键科学问题, 以促进精准医疗的快速发展。
非靶向和靶向代谢组学技术虽然能够表征疾病或药物引起的代谢轮廓变化, 但并不能提供细胞代谢率和代谢途径相对活性等信息, 例如, 一种代谢物水平的升高可能是产生该代谢物的酶活性增加或降解该代谢物的酶活性降低引起的, 而常规代谢组学技术无法准确解释代谢物水平发生变化的原因[14]。采用稳定的同位素示踪剂跟踪代谢物, 从而确定代谢物在代谢途径中的作用是攻克该瓶颈最具前景的研究方法之一, 因此, 稳定同位素标记在代谢流分析中的应用逐渐受到关注, 并发展为稳定同位素示踪代谢组学技术[15]。稳定同位素示踪代谢组学技术是一种通过分析稳定同位素示踪前体物质到产物的变化规律, 进而推导代谢通路和代谢活性的方法[16]。目前商业途径可获取的标记有稳定同位素的代谢物有多种类型, 如碳(13C)、氮(15N) 和氘(2H) 标记的代谢物[14]。稳定同位素示踪代谢组学技术的操作流程主要由选择稳定同位素示踪剂、引入稳定同位素示踪剂、制备分析样本、数据处理、代谢物鉴定、同位素分析、挖掘生物功能7部分构成[17], 如图 2所示。在数据处理方面, 稳定同位素示踪代谢组学采集的数据可通过Compond Discoverer软件进行处理, 并利用在线数据库和实验室自建数据库对代谢物进行鉴定。此外, 可通过Python平台编码的枚举算法从数据矩阵中提取同位素峰列表(去除没有同位素峰的代谢物), 并在各组之间对同位素峰比重进行统计学分析[18]。在挖掘生物学功能方面, 通常采用文献调研寻找靶点, 并采用分子生物学技术对靶点进行验证。目前, 向动物体内引入稳定同位素示踪剂仍然是艰巨的挑战。为此, 本课题组首次采用13C6-葡萄糖稳定同位素示踪代谢组学技术在大鼠体内研究抑郁症的发病机制, 通过尾静脉注射向大鼠体内引入13C6-葡萄糖, 并进一步确定引入13C6-葡萄糖的最佳条件: 以8 mg·kg-1·min-1的剂量持续注射6 h[18]。随后, 本课题组基于LC-MS的13C6-葡萄糖稳定同位素示踪代谢组学研究发现, 该技术能够表征代谢物的命运, 如血清中的丙酮酸[18]。此外, 通过分析同位素标记的代谢物走势, 本团队还发现抑郁大鼠海马和肝脏丙酮酸的减少与TCA循环受阻和糖异生途径激活有密切联系[19, 20]。近期, 本团队将13C6-葡萄糖稳定同位素示踪代谢组学技术应用于中药复方逍遥散的抗抑郁机制研究, 结果表明逍遥散的抗抑郁作用与海马线粒体结构和功能的修复、葡萄糖分解代谢的调节有关, 并且还发现了逍遥散区别于抗抑郁化学药文拉法辛的特异性靶点: 丙酮酸-乳酸轴、丙酮酸羧化酶和琥珀酸脱氢酶[21]。除了动物方面的探索, 本团队在细胞水平上也开展了相关研究, 课题组曾采用13C6-葡萄糖稳定同位素示踪代谢组学技术考察不同细胞模型的能量代谢差异, 结果表明皮质酮损伤的PC12细胞糖异生途径被激活, 而多柔比星刺激的肾小球足细胞糖异生途径被抑制, 提示不同疾病能量代谢障碍存在特异性[22]。尽管稳定同位素示踪代谢组学技术表现出了明显的优势, 仍存在一定局限性, 如目前代谢物检测范围仅限于特定/目标途径。有趣的是, 近期, 国内研究者开发了一种全面稳定同位素示踪代谢组学技术MetTracer, MetTracer根据未标记样本的非靶向代谢组学结果提前计算并列出每个代谢物所有可能的同位素理论质谱信息, 并通过设置离子色谱条件、进行相关性分析和层次聚类分析等方法参照列出的理论质谱信息从同位素标记样本的代谢组学结果中靶向提取同位素峰, 在很大程度上提高了代谢物的覆盖率和同位素峰的准确度, 该技术整合了非靶向代谢物注释和靶向同位素提取的策略, 为发现新的代谢转化途径提供了更多的可能[23]
事实上, 细胞内代谢物的合成和积累通常具有一定的空间分布特性, 同时, 代谢物的生理功能与其在组织和细胞中的空间分布紧密相关。分子成像技术可以直观地反映代谢物在组织或细胞的分布情况, 目前已有许多有潜力的分子成像技术可应用于代谢分布研究, 如磁共振成像、放射性成像、拉曼成像等[24], 但是其中很少有技术能够在无标记基础上同时检测数千个分子[25]。相比之下, 质谱成像(mass spectrometry imaging, MSI) 作为一种先进的分子成像技术, 不仅无需标记, 能够利用离子源直接扫描生物样品进行成像, 更关键的是, 该技术还能实现上千代谢物的定性、定量和定位分析, 对阐明代谢物的调控机理有重要意义[26], 将MSI和常规代谢组学技术整合到一起便产生了质谱成像空间代谢组学技术。质谱成像空间代谢组学研究通常由样品制备、MSI分析(原位电离、质谱信息采集、代谢物成像)、多变量分析、代谢物鉴定、生物功能挖掘5个部分组成, 如图 3所示, 其中, 最关键的步骤为样品制备和原位电离[25, 27, 28]。理论上, 能制成切片的样本均可开展质谱成像空间代谢组学分析, 如动物[29]、植物[30]和临床[31]组织样本。组织样本收集后, 主要有两种预处理方法, 一种是用福尔马林固定和石蜡包埋, 另一种是用液氮新鲜冷冻(组织需要用羧甲基纤维素、明胶等包埋剂处理), 选择其中一种方式处理后保存于-80 ℃备用[32]。在质谱成像空间代谢组学分析之前, 包埋的组织样本需要在低温冷冻切片机进行组织切片[33], 制备的组织切片将用于后续分析。在MSI分析的原位电离过程中, 基质辅助激光解吸/电离(matrix-assisted laser desorption/ionization, MALDI)、解吸电喷雾电离(desorption electrospray ionization, DESI) 和二次离子质谱(secondary ion mass spectrometry, SIMS) 是最常用的3种电离方法[25, 33], 其中, MALDI电离方法需要喷涂基质。除了以上3种电离方法, 激光烧蚀电喷雾电离、表面辅助激光解吸/电离等技术也可用于MSI分析[34]。目前, 质谱成像空间代谢组学技术已广泛应用于天然药物开发和中药药效、毒性物质基础研究。在天然药物开发研究方面, Li等[35]采用MALDI-MSI空间代谢组学技术揭示了牡丹和芍药根中代谢物空间分布差异, 该研究首先采用MALDI-MS对牡丹和芍药根中代表性部位木栓层、皮层、韧皮部和木质部的代谢物谱进行原位分析, 有趣的是, 除了常见的代谢物, Li等[35]发现牡丹根中还具有特异性成分丹皮酚苷类物质, 随后进一步采用MALDI-MSI技术对牡丹和芍药根中丹皮酚苷类代谢物进行空间分布分析, 结果表明仅在牡丹根部的木栓层和韧皮部检测到丹皮酚苷类代谢物, 而在芍药根中尚未观察到此类物质。在中药药效研究方面, Cui等[28]采用DESI-MSI空间代谢组学技术阐明延胡索乙素促血管生成的全新机制, 结果表明延胡索乙素可通过依次影响瓜氨酸到精氨酸的流量、精氨酸的生物合成和血管内皮生长因子R2的表达促进血管生成。在毒性物质基础研究方面, Jiang等[27]采用空气流动辅助DESI-MSI空间代谢组学技术考察何首乌D组分的肝毒性生物标志物, 结果表明何首乌D组分的肝毒性标志物包括氨基酸、酰基肉碱和胆汁酸等化合物。相比于往常用于标记组织中遗传物质、蛋白质的荧光染料和探针可视化方法, 质谱成像空间代谢组学技术能够更好地反映结构多样的小分子物质, 这将促进研究者对中药复杂成分、疾病发病过程和药物作用机制产生新的认识。
在中药研究领域, 中药疗效评价是寻找中药中有效物质、先导化合物和质量标志物的重要前提, 然而, 中医药理论尤为复杂, 目前有限的药理指标尚不能全面体现中药的疗效, 导致国内外医药科学家难以充分认识和接受中药在临床用药经验的实用价值[36]。在此基础上, 王喜军教授团队[37]在2012年正式提出中医方证代谢组学研究新策略, 即通过整合代谢组学和中药血清药物化学研究技术, 以发现证候生物标记物为切入点, 以中药方剂为研究对象, 集阐明效应、解释效应机制及鉴定效应成分于一体的中药有效性研究策略, 旨在从“证候-方剂”相关性角度阐释中药科学内涵[36]。中医方证代谢组学技术主要由3部分研究内容组成, 分别为代谢组学分析(发现证候生物标记物)、血清药物化学分析(寻找方剂在体内的显效成分) 和“证候-方剂”相关性分析(如皮尔逊相关分析), 如图 4所示, 具体操作方法可参考王喜军教授团队[38]已发表专著《Chinmedomics》的第二章内容。截至目前, 不断有研究证实, 中医方证代谢组学技术在寻找中药效应质控标志物和揭示中药效应机制方面起着重要作用。在寻找中药效应质控标志物方面, 首先, 通过生物样本的代谢组学分析筛选差异代谢物并作为证候生物标志物, 紧接着, 通过血清样本的药物化学成分分析筛选原型成分并作为中药显效成分, 在此基础上, 将筛选的证候生物标志物与中药显效成分进行相关性分析确定候选的中药显效质控标志物, 这些候选的化合物经鉴定后可作为最终的中药质控标志物, 目前, 研究已经发现獐牙菜苷、绿原酸等7种化合物是脉络疏通颗粒治疗血栓闭塞性脉管炎的潜在质控标志物[39], 乌头碱、麻黄碱等12种化合物是乌头汤治疗类风湿性关节炎的潜在质控标志物[40], 人参皂苷Rb1、肉桂酸等4种化合物是稳心方治疗心肌缺血的潜在质控标志物[41]。在揭示中药效应机制方面, 有研究整合中医方证代谢组学和生物信息学研究发现渴络欣改善糖尿病性视网膜病变的作用可能与哺乳动物雷帕霉素靶蛋白信号通路和腺苷单磷酸活化蛋白激酶信号通路的调节有关[42], 而补肾活血方改善糖尿病性视网膜病变的作用可能与炎症反应的调节有关[43]。除此之外, 中医方证代谢组学技术还被应用于中药药效学物质基础研究和中药毒性、安全性评价[44]。意义深远的是, 中医方证代谢组学研究策略的提出得到了国内外医药工作者的普遍认可, 《Nature》杂志曾将该研究策略评价为“搭建中医学与现代医学科学沟通的语言桥梁”[45], 在未来, 中医方证代谢组学技术有潜力成为小分子代谢水平上促进中医药发展的重要工具[46]
常规代谢组学研究通常只能提供表型数据, 并不能揭示相关代谢物的生化功能和调节机制, 这在很大程度上限制了代谢组学技术在生命科学领域中的应用[47]。此外, 在中药研究领域, 为了更好地理解中药的系统药理作用, 需要表征中药功能化合物治疗下代谢标志物及其相关代谢途径的修饰和调控[48]。因此, 亟需一种先进技术, 面对中药化学成分和疾病发病过程的复杂性, 能准确筛选中药中具有疗效的功能化合物, 并精准识别该化合物作用的靶点。为了满足以上需求, 功能代谢组学研究策略由此诞生。基于质谱的靶向代谢组学与尖端生化方法(功能基因组学、化学蛋白质组学和遗传学等) 相结合, 旨在阐明不同生物背景下代谢产物的生化功能, 被定义为功能代谢组学[48], 研究策略如图 5所示。值得注意的是, 代谢组作为系统生物学中心法则的最终功能环节, 脱离了基因组和蛋白组的生物学表征, 因此单纯的代谢组学研究通常意义有限, 难以串联出生物学的核心逻辑, 该不足在近十年的重要生物医学研究中体现得尤为明显。在此基础上, 功能代谢组学以代谢组学研究发现的代谢差异为基础, 结合表征基因组和蛋白组的前沿技术手段, 从基因、蛋白和代谢不同角度更系统全面地剖析差异代谢物的生物学功能及差异代谢物调控的疾病发病机制、药效作用机制, 极大地优化了代谢组学研究的广度和深度。目前, 功能代谢组学技术已被广泛应用于生物合成、病理特征、药物机制等方面研究。在生物合成研究方面, Mulleder等[49]采用LC-MS靶向代谢组学技术结合雷帕霉素敏感性测定等生化方法考察酵母的生物合成过程, 该研究以基因缺失酵母菌株中氨基酸代谢失调为线索, 通过在基因组水平构建多种分子网络寻找“基因-氨基酸代谢”的调控关系, 结合尖端生化技术的分子验证, 最终结果表明雷帕霉素靶蛋白复合物相关基因可通过影响囊泡介导的转运来调节氨基酸代谢, 从而干预酵母生物合成的稳态。在病理特征方面, Wang等[50]采用超高效LC-MS靶向代谢组学技术、靶向脂质组学技术、16S rDNA扩增子测序技术和转录组学技术考察慢性肝炎和急性肝炎机体的代谢特征, 结果表明慢性肝炎的发展与牛磺酸结合胆汁酸代谢有关, 而急性肝炎的发展与嘌呤降解有关。在药物机制研究方面, Li等[51]采用血清和肝脏GC-MS非靶向代谢组学、LC-MS靶向代谢组学技术结合油红染色等生化方法考察黄芪多糖改善小鼠肥胖的药理机制, 结果表明黄芪多糖通过增加功能代谢产物2-羟基丁酸改善肥胖小鼠的脂质代谢, 最终发挥抗肥胖作用。除了以上应用, 功能代谢组学技术还为中药毒性评价研究提供了新思路, 形成了“毒性成分-内源性代谢物-直接靶标-毒性机制”的研究新策略[52]。吕海涛研究团队[48]长期致力于功能代谢组学研究, 不久前, 该课题组率先提出2种新型功能代谢组学研究新策略, 即精准修饰代谢组学[53]和时空操作真实代谢组学(spatial temporal operative real metabolomics, STORM), 并首次采用STORM研究策略识别胰腺癌的治疗靶点[54], 推动了代谢组学技术在医药领域的高质量发展。
PBMCs是具有单个细胞核的外周血细胞, 主要由淋巴细胞(T细胞、B细胞、NK细胞) 和单核细胞组成, 是多种免疫细胞的合称[55]。PBMCs在体内免疫、代谢和细胞通讯中发挥着重要作用, 还能反映中枢神经系统中的生物学过程, 因此可作为免疫、代谢失调和神经损伤相关疾病的研究对象, 目前已被报道在抑郁症的发病过程中扮演着关键角色[56, 57]。PBMCs在抑郁症病理机制研究中, 相比于难以获得的脑脊液、脑活检样本, 具有采样便捷、成本低等现实优势, 并且比血浆、血清、组织等样本更能反映抑郁症相关的病理变化, 因此在临床抑郁症诊断生物标志物的探索上具有不容小觑的研究前景。PBMCs的提取通常需要将新鲜血液与淋巴细胞分离液(可直接从商业试剂盒中获取) 以适宜比例混合进行密度梯度离心, 并通过分离纯化、细胞计数、超声破碎等过程制备代谢组学分析的PBMCs样本。不久前, 中国医药生物技术协会已发布人体PBMCs采集、分离和保存的团体标准, 同时还介绍了PBMCs的质量控制方法(活细胞计数、RNA和DNA质量控制)[58]。有趣的是, 近期有研究者研发了一种PBMCs分离装置(PBMC-mCap), 仅需采集10~120 μL的外周血样本, 极大地提升了PBMCs的提取效率, 并降低了外周血的损耗[59]。在过去, 基于GC-MS的PBMCs代谢组学研究表明, 抑郁大鼠PBMCs神经递质代谢、能量代谢、氧化应激代谢和嘌呤代谢等代谢途径中相关代谢物的含量出现异常[56, 60]。在临床上, 基于GC-MS的PBMCs代谢组学研究也发现抑郁症患者PBMCs的代谢轮廓相比于健康人发生明显紊乱[57, 61], 然而, PBMCs中与抑郁症发病过程最为相关的代谢途径仍不清楚。在此基础上, 本课题组近期基于LC-MS的PBMCs代谢组学研究进一步表明, PBMCs嘌呤代谢与抑郁症的发病密切相关, 并且抗抑郁新药柴归颗粒在发挥抗抑郁作用的同时能够显著改善PBMCs嘌呤代谢[62], 提示PBMCs嘌呤代谢中可能存在抑郁症发病的生物标志物, 而这些生物标志物则是柴归颗粒发挥抗抑郁作用调控的潜在靶点。精神分裂症是与抑郁症类似的精神疾病, 有研究者曾采用PBMCs代谢组学技术寻找精神分裂症患者的潜在生物标志物, 结果表明与健康人相比精神分裂症患者PBMCs糖代谢高度异常[57, 63], 提示PBMCs糖代谢中可能存在精神分裂症患者的临床诊断标志物。除了精神疾病, PBMCs代谢组学技术还应用于研究肠道微生物蛋白质[64]和流感病毒[65]对外周免疫系统的影响, 提示PBMCs可同时作为神经系统和免疫系统失调相关疾病的重要研究样本。总体而言, PBMCs对体内外刺激较为敏感[59], 在一定程度上可反映大脑中的生物学变化, 有潜力作为精神疾病研究的切入点, 为抑郁症等疾病的临床监测提供了新的机遇。
代谢组指一个生物样本中包含的所有小分子代谢物, 从单个细胞到整个生物体, 常规代谢组学技术仅局限于组织匀浆水平和多细胞水平代谢轮廓的检测, 然而组织中存在多种不同类型的细胞, 即使相同的细胞也可能具备不同的功能, 常规代谢组学研究无法区分这些细胞的类型和异同[66]。在过去, 单细胞基因组学[67]和蛋白组学[68]研究为细胞异质性提供了证据, 弥补了以往多细胞研究的不足, 然而遗憾的是, 高昂的成本使其难以应用于临床[69]。相比之下, 基于质谱的代谢组学技术用于分析单细胞生物学具有高性价比的优势[69], 因此受到了广泛关注, 如今, 单细胞代谢组学技术已成为2023年深受瞩目的7项先进技术之一[70]。对于单细胞代谢组学研究而言, 单细胞样品的制备需要复杂的技术来实现, 目前常用的技术是微流控分选技术和荧光激活细胞分选技术[71], 这两种方法均能保留整个细胞的原始形态。细胞分离后, 应立即采用液氮快速冷冻的方法猝灭细胞, 促进细胞裂解, 防止代谢物发生转化, 同时, 也可以采用有机试剂(如甲醇和乙腈) 进行猝灭[72]。随着纳米材料基质的快速发展, MALDI-MS技术已成为单细胞代谢组学分析中的主流技术, 此外, 电喷雾电离(electrospray ionization, ESI)-MS技术也常用于单细胞代谢组学分析, 通常是将样品从探针或毛细管直接输送到质谱, 具有防止样品破坏的优势[66]。作为一种不断发展且强大的分析技术, 单细胞代谢组学技术已被广泛应用于植物学、神经病学、肿瘤学等研究领域[66]。遗憾的是, 常用的单细胞代谢组学研究工具存在代谢物检测数量少、灵敏度和覆盖率低等不足, 为了弥补缺陷, 近期已有研究者开发出高效的新兴技术, 如Nano-ESI-MS单细胞代谢组学技术(增加单细胞中检测到的代谢物数量) 和CyESI-MS单细胞代谢组学技术(质谱流式细胞术, 提高了检测效率和代谢物覆盖率)[73]。对于分子生物学和临床应用来说, 通量限制是迫切需要改善的瓶颈, 在此基础上, Feng等[74]开发了一种非对称蛇形通道微流控芯片, 单次能分析3 000多个单细胞, 达到了高通量单细胞代谢组学研究水平, 推动了生命科学研究的进程。
线粒体是细胞代谢的中心, 线粒体丰富的功能使其与多个学科领域高度相关, 如神经病学、肿瘤学、免疫学等, 然而线粒体功能的生物学原理尚未完全清晰, 因此成为了当下的研究热点[75]。在不受其他细胞器干扰的情况下, 对细胞中线粒体的代谢轮廓进行精确表征, 将有助于更好地理解线粒体障碍相关疾病的发病机制和诊断措施[76]。在进行线粒体代谢组学研究之前, 需要提前用线粒体分离试剂盒从细胞或组织样本中提取线粒体, 通常采用的两种方法是差速离心和超速离心, 但这两种方法均有缺陷[77, 78]。差速离心法虽能简单且快速地提取完整的线粒体, 但容易受其他细胞器污染, 超速离心法虽能提取高纯度的线粒体, 但相对费时费力, 获取的线粒体浓度较低。目前, 线粒体的提取方法得到了优化, Chen等[79]已经开发出一种高效分离线粒体的免疫纯化策略(将线粒体外膜蛋白作为免疫捕获的目标)。此外, 还有课题组开发了新型免疫亲和磁性复合材料(MagG@PD@ Avidin@TOM20), 可高选择性免疫纯化线粒体, 在此基础上, 该研究团队采用超高效液相串联高分辨质谱线粒体代谢组学技术区分3种肝细胞(L02、HepG2、Huh7) 全细胞代谢组与线粒体代谢组的差异, 研究发现线粒体代谢轮廓存在特异性变化, 然而往往会被全细胞代谢组(常规代谢组学) 的结果覆盖[76], 提示细胞器代谢组学与常规代谢组学相比更能反映疾病特异性, 明确了单细胞器代谢组学发展的必要性。在过去的研究中, 线粒体代谢组学在中药药效机制、生物化学、环境污染等领域均有应用。在中药药效机制研究方面, 本课题组曾采用超高效LC-MS线粒体代谢组学技术考察黄芪健中汤治疗胃炎的机制, 结果表明黄芪健中汤可通过修复线粒体功能改善慢性萎缩性胃炎[80]。在生物化学研究方面, 主要聚焦于线粒体功能研究, Xu等[81]采用NMR实时线粒体代谢组学技术表征了哺乳动物线粒体中乙酰磷酸的形成过程, Nomiyama等[82]采用LC-MS线粒体代谢组学技术发现β-烟酰胺单核苷酸代谢在线粒体DNA复制中具有重要作用, 此外, 烟酰胺腺嘌呤二核苷酸和谷胱甘肽在线粒体氧化还原反应中扮演着重要角色, 经研究发现, LC-MS线粒体代谢组学技术有助于阐明线粒体转运烟酰胺腺嘌呤二核苷酸[83]和谷胱甘肽[84]的机制。在环境污染研究方面, Go等[85]采用LC-MS线粒体代谢组学技术考察重金属镉的毒性机制, 结果表明镉能够通过影响肝脏线粒体支链氨基酸代谢导致肝损伤。总而言之, 线粒体代谢组学技术在生物医药领域研究中提供了许多不同寻常的机会和挑战, 这将会促进疾病发病机制的了解和药效物质基础的阐释。
溶酶体作为细胞内的清道夫, 可以对运至其中的糖、蛋白质、核酸等物质和受损的细胞器进行降解, 并通过不同形式的自噬和内吞作用对产物进行再利用, 维持着细胞内环境稳态[86]。越来越多的证据表明, 溶酶体在传递和感知代谢物信号方面起着关键作用, 溶酶体功能的缺失影响许多神经退行性疾病的生物学过程, 相关调控机制可参考Yang等[87]的综述。溶酶体代谢组学技术的发展对阐明溶酶体代谢物信号调控神经退行性疾病的内在机制有重要意义。在溶酶体提取方面, 传统溶酶体纯化技术存在诸多弊端, 如提取速度慢、稳定性差, 目前Abu-Remaileh等[88]已经开发出一种快速分离哺乳动物溶酶体的方法: LysoIP法, 约10 min即可分离纯化出完整的溶酶体, 并且该方法采用了与LC-MS代谢组学技术兼容的缓冲液, 适于进行LC-MS代谢组学研究。LysoIP法制备的溶酶体结合LC-MS代谢组学技术已被应用于研究溶酶体的新功能, 研究发现溶酶体能动态调控细胞质中的氨基酸, 并且调控过程与mTOR活性有关[88]。在细胞中, 溶酶体存在多种类型, 然而多溶酶体代谢组学技术尚不能反映溶酶体之间的异质性。令人振奋的是, 近期, 中国科学技术大学熊伟教授团队[89]首次开发出了单个细胞器水平的代谢组学检测技术, 即单个溶酶体代谢组学技术。该技术主要通过结合膜片钳和Nano-ESI质谱技术进行代谢组学分析, 适用于多种类型细胞(如星形胶质细胞、神经元、心肌细胞、巨噬细胞、成纤维细胞) 单个溶酶体的代谢组学研究。最终, 熊伟教授团队采用单个溶酶体代谢组学技术将细胞中溶酶体分为5种类型, 结果表明每种类型都具有截然不同的代谢特征[89]。同时, 还发现衰老细胞和肿瘤细胞中溶酶体存在代谢异质性, 表明溶酶体功能障碍相关疾病的机制研究确实需要精确到单个细胞器水平[89]。目前, 溶酶体代谢组学的应用尚未完全普及, 但溶酶体作为传递代谢信号的枢纽[86], 在未来的生物医药领域研究中仍然具有广泛的研究前景。
肠道微生物在焦虑、帕金森病、阿尔茨海默症等中枢神经系统疾病的调节中扮演着重要角色, 肠道微生物可通过多种途径与大脑进行沟通, 如调节细菌代谢物(短链脂肪酸、肽聚糖等)、产生神经递质(γ-氨基丁酸、组胺等)、激活肠内分泌细胞等, 在此基础上, “肠-脑”轴在不同疾病中的作用不断受到重视[90]。然而, 以往大部分研究都只聚焦在复杂的微生物群落上(如肠道菌群测序), 难以确定微生物导致宿主中枢神经系统特定改变的具体途径, 因此, 需要更高效的现代技术解决这一难题。经过长期探索, 微生物代谢组学技术得到了微生物领域研究者的广泛认可, 该技术有潜力为肠道菌群与远端器官的相互作用提供新见解, 在过去20年中, 微生物代谢组学在各个领域的研究已呈指数增长[91]。在1998年, Tweeddale等[92]首次报道关于微生物代谢组学的研究, 该研究采用二维薄层色谱法考察大肠杆菌的代谢谱变化。如今, 除了薄层色谱, NMR、直接注射质谱、毛细管电泳质谱、GC-MS、LC-MS均已成为微生物代谢组学研究的常用工具, 主要工具为GC-MS和LC-MS[91]。由于微生物中活性酶和代谢物能快速转化, 为了获取准确的结果, 微生物代谢组学分析应使用稳定的样品处理方法, 主要包括微生物培养、快速采样、淬灭、代谢物提取4个过程, 详细操作过程可参考Ye等[91]近期发表的综述。在微生物代谢组学技术应用于“肠-脑”轴研究之前, 该技术已在多个领域有所发展, 如药物机制研究和环境污染研究。在药物机制研究方面, 有研究通过GC-MS微生物代谢组学技术发现罗勒精油的抗菌机制与能量代谢、氨基酸代谢、脂质代谢的调节有关, 并进一步识别到了罗勒精油发挥作用的关键成分[93]。在环境污染研究方面, 有研究采用GC-MS微生物代谢组学技术发现碳纳米管和环丙沙星对大肠杆菌产生拮抗毒性的作用与6种代谢途径的调节有关[94], 为理解碳纳米管与共存污染物对环境的影响打下了基础。此外, 微生物代谢组学在功能基因研究、微生物鉴定、抗生素耐药性、工业生物技术、合成生物学和酶发现等领域也有着广泛应用[91]。微生物代谢组学技术在“肠-脑”轴研究的优势毋庸置疑, 近期, Horvath等[90]报道了一项采用LC-MS微生物代谢组学技术进行“肠-脑”轴研究的详细实验方案, 为单一类型微生物影响肠道和大脑的作用机制研究提供了新策略。该方案主要涉及3个阶段, 分别为在特定培养基中培养微生物、显微注射肠道类器官和建立限菌动物模型, 相比于通常仅检测粪便样本的考察方法更有发展前景, 该方案获得的结果更为精准和全面。
本文从新工具、新思路和新样本角度综述了9种代谢组学新技术在生物医药领域研究中的优势和应用现状, 并分别介绍了相应的操作流程, 旨在促进代谢组学新技术的应用和发展。上述代谢组学技术的进步为疾病生物标志物的寻找、病理机制的阐明和天然小分子药物的开发提供了新的见解, 从亚细胞水平研究到临床应用, 推动了精准医疗的快速发展, 虽然取得了可喜的成绩, 但仍存在一些不足, 如应用成本较高、分析精度有限、结构表征能力欠佳等[95], 表明未来的代谢组学技术还需要进一步优化和创新。
在代谢组学技术的创新和应用过程中, 为了更高效地解决科学问题, 多学科前沿技术的交叉应用势在必行。代谢组学是一门交叉学科, 其与生物科学、分析化学及生物信息学等多种学科密切相关[96], 而将先进技术应用于代谢研究将有利于表征机体代谢改变的关键部分[97]。例如, 中药功能小分子与疾病生物标志物的相互作用是动态和多维的, 常规代谢组学研究只能提供相关表型信息, 而功能代谢组学STORM研究策略(涉及质谱成像、同位素标记、生物合成化学方法等前沿技术的交叉应用) 则能突破代谢表型并深入剖析关键代谢物的功能机制[48], 提示多学科交叉的代谢组学新技术有望成为未来研究中药复杂体系的核心工具。此外, 单细胞代谢组学技术结合MALDI成像技术能够使单细胞群体的异质性可视化, 但单细胞体积太小, 无法获取清晰的图像, 在此基础上, 单细胞代谢组学技术与MALDI成像技术、光学显微技术和数码图像处理技术交叉应用, 就能清晰地呈现单细胞群体的异质性图像, 并且质谱数据能够与相应的单细胞精确匹配[69], 再次体现了多学科技术交叉应用在代谢组学研究中的优势。随着具有疾病特异性的新样本在代谢组学研究中的应用逐渐增加, 多学科前沿技术的交叉应用能为生物标志物和功能小分子化合物的精准筛选提供技术保障, 并且还能为临床疾病早期诊断和新药开发提供新动力。
作者贡献: 周玉枝、秦雪梅负责综述思路的提出; 陈佳俊负责文献的检索、分析及初稿的撰写; 周玉枝、秦雪梅负责文稿的指导和修改。
利益冲突: 所有作者均声明不存在任何利益冲突。
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2023年第58卷第8期
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doi: 10.16438/j.0513-4870.2023-0521
  • 接收时间:2023-04-27
  • 首发时间:2025-11-21
  • 出版时间:2023-08-12
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  • 收稿日期:2023-04-27
  • 修回日期:2023-06-06
基金
国家自然科学基金面上项目(82074323)
山西省回国留学人员科研资助项目(2020019)
山西省研究生教育创新项目(2022Y162)
山西省重点研发计划项目(202102130501010)
作者信息
    1.山西大学中医药现代研究中心, 山西 太原 030006
    2.山西大学化学生物学与分子工程教育部重点实验室, 山西 太原 030006
    3.地产中药功效物质研究与利用山西省重点实验室, 山西 太原 030006

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*周玉枝, E-mail: ;
秦雪梅,
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
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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