基于质谱技术的代谢组学研究及其在中国的发展

中国科学: 化学 2014年 第44卷 第5期: 724 ~ 731

《中国科学》杂志社

SCIENCE CHINA PRESS

SCIENTIA SINICA Chimica

评 述 质谱分析专刊

基于质谱技术的代谢组学研究及其在中国的发展

王献

①②

, 林树海, 蔡宗苇*

②

②

① 中南民族大学化学与材料学院, 武汉 430074

② 香港浸会大学环境与生物分析国家重点实验室, 香港九龙 *通讯作者, E-mail: zwcai@hkbu.edu.hk

收稿日期: 2014-01-10 ; 接受日期: 2014-02-07; 网络版发表日期: 2014-04-03 doi: 10.1360/N032014-00016

摘要 代谢组学是关于生物系统代谢物组成及变化规律的科学, 是系统生物学的重要组成部分. 质谱技术是目前代谢组学研究中最主要的分析手段之一, 广泛应用于代谢组学各个领域. 本文阐述了基于质谱技术的代谢组学方法及其应用, 重点介绍和评论了近年来我国在该领域取得的进步和成果, 并对基于质谱技术的代谢组学研究目前存在的问题及未来的发展进行了分析与展望.

关键词 代谢组学 质谱技术 系统生物学

1 引言

后基因组时代如何解析基因组功能是生命科学研究的热点问题, 基于基因功能的复杂性和生物系统的完整性, 有必要从整体层面上来理解构成生物体系的各个模块功能[1]. 由基因组衍生出来的转录组学、蛋白质组学以及代谢组学等整体性研究方法成了解析功能基因组的新的重要手段[2~4]. 代谢组学作为系统生物学的重要组成部分, 可定义为对生命体系因环境刺激、病理生理扰动或基因改变等所引起的体现为所有代谢物动态应答的质和量及其变化规律. 由于代谢(物)处于生物系统生化活动调控的末端, 涵盖反映生理表型的直接而全面的生物标记物信息, 因此, 代谢组学作为系统生物学中最下游的“组学”, 可反映生物化学变化的信号放大效应, 且日益成为整体性研究生命体系功能变化的重要学科分支.

由于生物体系的复杂性, 代谢产物数目多、差异大、浓度分布范围广、组成复杂, 代谢组学也是一门技术驱动的科学. 现代质谱技术具有高选择和灵敏性、普适性和分析速度快等特点, 可同时检测鉴定多种代谢物, 提供丰富的数据信息. 因此, 基于质谱技

术的代谢组学研究文献不断增加, 已超过了基于核磁共振技术的文献量, 成为最有效的研究手段之一. 目前, 基于质谱技术的代谢组学研究在药物开发、临床疾病、植物学、营养学和环境毒理学等领域发挥着重要的作用[5].

2 质谱技术在代谢组学中的研究进展

气相色谱-质谱和液相色谱-质谱联用可以检测数千种化合物, 包括糖类、有机酸、氨基酸、脂肪酸、环境外源污染物和植物的次级代谢产物, 这是其他任何一项技术所无法比拟的[5~7].

超高效液相色谱与质谱联用扩展了分析物(代谢物)的覆盖率, 因此成为当今代谢组学的主要方法之一. 多维气-质和液-质联用的发展, 在对复杂体系中的靶标分析(如标记物分析)代谢组学研究中有着突出的优势. 纳升级[8, 9]和芯片纳流液相色谱-质谱系统也成为高效快速、高灵敏度的分离分析复杂代谢组样品的新技术[10]. 2013年, Science报道的高密度芯片-质谱接口技术, 如质谱微阵列芯片, 可解决单细胞代谢组学质谱检测中高通量制备单细胞样本的瓶颈问题[11].

中国科学: 化学 2014年 第44卷 第5期

复杂体系中代谢产物的结构鉴定是富有挑战性的问题, 具有高分辨率的质谱系统(如四极杆串联飞行时间质谱仪[12]、傅里叶变换离子回旋共振质谱 仪[13]和Orbitrap等)在此方面有着突出的优势. 准确质量的质谱和串联质谱检测与数据库检索、标准品验证及其他实验结果相结合, 提供了更高水平的代谢 物结构识别和确认能力, 对生物标记物的确定非常重要.

到目前为止, 大部分整体代谢谱(轮廓)分析采用电喷雾电离源. 最近, Shrestha等[14]以电喷雾电离为基础开发了一种新的激光剥离电喷雾电离方法, 在常压下可用质谱原位分析单细胞的代谢谱图.

质谱分析中, 精确质量测定、化合物元素组成、 串联质谱特征离子碎片信息、气相或液相色谱分离保留时间等大量的多元性数据, 不仅可以帮助鉴定代谢物的结构, 而且与化学计量学结合, 构建合理的数学模型, 选用有效的数理统计方法对数学模型进行计算和归类分析, 挖掘有用信息, 对代谢组学分析结果的解释, 在相关疾病生物标记物的发现、阐明代谢物的生物功能、疾病的发病机理等研究中有重要的意义[15].

目前, 基于质谱技术的代谢组学研究已广泛应用于疾病诊断、药物毒性和效果评价、微生物和植物的细胞代谢以及基因功能的阐明等. 作为新的研究思路和手段, 基于质谱技术的代谢组学方法近年来又在中药成分的安全性评价、环境毒理分析、营养基因组学、整合药物代谢和系统毒理学等方面取得了新的突破和进展. 例如, 最近在癌症代谢组学方面的新突破包括发现细胞的快速增殖需要大量的非必需甘氨酸, 对癌症治疗有着清晰直接的影响[16]. 在这项工作中, Jain等[17]首次采用液相色谱-串联质谱方法从60种不同的人体癌细胞株中检测了219种代谢产物.

3 我国的研究成果

近年来, 基于质谱技术的代谢组学研究在中国快速发展, 建立了多个代谢组学技术平台和研究组, 开展了与重大疾病、中药和环境等相关的一系列各具特色的代谢组学研究, 在技术突破和应用方面取得了一定的成果.

许国旺研究组针对代谢组的特点, 采用“分而治之”的策略, 建立完善了一系列基于色-质联用技术的代谢组学分析平台, 其中包括非靶向的代谢组、脂类

的组学分析平台以及针对痕量代谢物的靶向分析平台等, 并在提高代谢组学分析覆盖的化合物种类, 实现高通量、高灵敏度代谢组分析以及发展复杂代谢组数据解析方法, 解决代谢物定量及未知代谢物结构定性等关键问题上开展了一些创新性研究. 通过发展新型同位素标记衍生化液-质联用方法, 实现了24种类固醇激素的快速高灵敏检测[18]; 发展了多维色-质联用技术, 提高了色谱的分离能力[19~21]. 结合代谢组学非靶向分析及靶向分析的特点, 该研究组提出了一种“拟靶向”的分析策略, 以多反应监测方式实现一次进样定量超过500种代谢物, 显著提高了代谢组分析的数据质量[22]，发展了包括色谱峰匹配策略[23]、代谢表型识别以及筛选潜在标志物的新算法等[24~26]. 该研究组将色-质联用和高分辨质谱代谢组学方法应用在疾病诊疗的领域, 如糖尿病及其并发症的相关代谢标志物[27~40], 以及开展了肝癌[41~43]、卵巢癌[44], 肺癌[45]、大肠癌及其他肿瘤[46~49]的代谢组学研究. 同时研究了中医证候[50, 51]、中药配伍以及疗效评价 等[20, 28, 29, 52]中医药相关的代谢组学, 以及不同水稻亚种的代谢特征以及转基因水稻代谢组特征[53, 54]等. 该研究组近年来也注重关键差异代谢物的功能研究, 揭示了代谢组对复杂生物现象的影响[55], 开发了基于脂质代谢动力学的分析策略[56~58], 为功能代谢组研究提供了新的研究思路.

再帕尔课题组研究了恶性肿瘤代谢组学的分析方法和生物标志物的发现. 以快速高分辨液-质联用技术为主要分析手段, 通过构建高效、整合式的高通量分析技术平台, 开展了食管癌[59]、肺癌[60]、乳腺 癌[61]和宫颈癌[62]等恶性肿瘤的代谢组学分析方法及发现小分子生物标志物的研究. 分别建立了“组合式”离子化方式的代谢组学新型分析方法[60]、模式识别与偏相关网络分析相结合的“整合式”数据处理方法[61]、 整体轮廓与靶向代谢组学相结合的分析方法和定量代谢轮廓分析方法[59], 以及尿液代谢组学的前处理及数据分析与校正新方法[63]. 运用这些方法在更可靠、更全面地发现与恶性肿瘤诊断或疗效评价密切相关的潜在小分子标志物方面取得了重要进展. 通过基于动物肿瘤模型的差异代谢物动态行为分析与药物代谢组学相结合的方法研究[64], 发现了与肿瘤发展密切相关的潜在生物标志物以及与药物药效或毒性作用相关的药物敏感性标志物. 研究了血浆中内源性代谢物稳定性以及相关代谢物的变化规律,

725

王献等: 基于质谱技术的代谢组学研究及其在中国的发展

发现了显著性变化的不稳定代谢物, 从而辅助潜在生物标志物的正确识别[65].

近6年来, 本研究组通过开发和建立基于质谱技术代谢组学方法, 开展了与环境毒理和重大疾病相关的代谢组学研究[66~78]. 采用超高效液相色谱-四极杆串联飞行时间质谱分析了2,3,7,8-二口恶英在芳香烃受体敏感型的C57BL/6J小鼠与不敏感型的DBA/2J小鼠中的不同毒性反应[72, 74]. 同时, 还对大脑中的海马组织与小脑组织的代谢物解析中发现, 这两个组织有诸多类似的地方, 也呈现出二口恶英可促进衰老的现象[67, 73]. 用高分辨液-质联用法研究了体内代谢中马兜铃酸的毒性和致毒机制[70, 76, 78]. 结合动物模型与生物标记物的发现, 研究了灌胃葡萄糖的健康大鼠与糖尿病大鼠的代谢表型的相似度[71].本研究组还对流感病毒感染的细胞模型[69]、阿尔茨海默病转基因小鼠[68]及人类肝癌手术后的血清进行了代谢组学分析[77]. 此外, 本研究组与德国赫姆霍兹中心合作, 建立了超高分辨的傅里叶变换离子回旋共振质谱代谢组学分析方法, 高准确度的质谱数据有利于快速鉴定代谢物作为潜在的生物标记物.

唐惠儒研究组[79~81]建立了液-质与核磁共振联用代谢组学研究技术平台, 开展了多方面研究: 与重要疾病发生发展及治疗愈后相关的代谢变化规律与机制、宿主代谢组和寄生生物间相互作用的机制及其与健康的关系, 以及应激对生长发育过程中代谢组的影响规律及其与健康的关系等代谢基础研究. 刘虎威研究组首次将基于停流技术的反相色谱和正相色谱的二维分析系统与质谱联用应用于代谢物分析[82], 开展了生物样本的脂质轮廓图谱分析等脂质组学研究[82~85]. 陈焕文研究组[86, 87]致力于质谱仪器和方法的开发研究, 将质谱技术应用于生物样品的代谢指纹图谱和癌症诊断中等研究工作. 林金明研究组[88]开发了微流控芯片与质谱联用技术, 对细胞分泌物进行检测分析以期得到细胞生命活动中扮演重要角色的物质的结构和含量信息. 张金兰研究组[89]研究

致谢

和建立了一种中药体内成分和代谢产物发现和鉴定的新策略(质谱树状图过滤技术), 研究了淫羊藿的代谢物和代谢途径. 鞘脂类的代谢研究为麻风病和肺结核等过敏性疾病的发病机制和病理机制提供了证据[90]. 王喜军研究组[91~94]采用多维色谱-质谱及高分辨质谱联用的方法开展了中医方证代谢组学的研究, 考察了中药体内代谢物及其动态变化规律, 利用代谢组学对整体代谢轮廓的描述来评价复杂性多元效应. 我国从事代谢组学和质谱学研究的学者和团队众多, 由于篇幅有限, 在此无法一一介绍.

4 结论和展望

代谢组学是研究基因组功能的重要手段之一, 是系统生物学不可或缺的部分. 基于质谱技术的代谢组学方法, 如超高效液相色谱-高分辨质谱、毛细管电泳-质谱联用、多维色谱-质谱联用、质谱-核磁共振联用和超高分辨质谱等技术, 在灵敏度、分辨率、动态范围和高通量等方面均有显著的改善, 并且与其他学科方法的配合和交叉, 推动了代谢组学的发展.近10年来, 中国研究者在基于质谱技术的代谢组学新方法的创新和完善方面取得了一定成果, 并将其应用于更广泛的代谢组学相关研究领域.

整体代谢组学研究范围的不断拓宽导致新生物标记物的发现和新生化现象的阐释. 因此, 质谱技术将继续发挥主导作用. 但是, 功能完善的代谢产物数据库的构建、多维数据验证方法、代谢组学研究的标准化和进一步的技术突破仍是代谢组学尚需解决 的问题. 另一方面, 只有将代谢组学技术与基因组学、蛋白质组学数据整合在一起, 才能提供完整的系统生物学认知. 这样的平台必将产生庞大的数据, 如何合理有效地对基于质谱技术的代谢组学方法进行数据挖掘, 与不同平台和不同组学的数据进行整合, 尽量全面准确地对代谢物定性定量分析也是未来代谢组学的研究重点.

本工作得到国家自然科学基金(21275167)和香港研究资助局(HKBU5/CRF/10)资助, 特此一并致谢.

参考文献

1 Kitano H. Systems biology: a brief overview. Science, 2002, 295: 1662–1664

2 Liu ET. Systems biology, integrative biology, predictive biology. Cell, 2005, 121: 505–506

726

中国科学: 化学 2014年 第44卷 第5期

3 Jansson A, Jirstrand M. Biochemical modeling with systems biology graphical notation. Drug Discov Today, 2010, 15: 365–370 4 Joyce AR, Palsson BØ. The model organism as a system: integrating “omics” data sets. Nat Rev Mol Cell Biol, 2006, 7: 198–210

5 Gika GH, Theodoridis GA, Plumb RS, Wilson ID. Current practice of liquid chromatography-mass spectrometry in metabolomics and

metabonomics. J Pharmaceut Biomed Anal, 2014, 87: 12–25

6 Vaint MR, Sommer U. Mass spectrometry based environmental metabolomics: a primer and review. Metabolomics, 2013, 9: 144–158 7 Dettmer K, Aronov PA, Hamock BD. Mass spectrometry-based metabolomics. Mass Spectrom Rev, 2007, 26: 51–78

8 Uehara T, Yokoi A, Aoshima K, Tanaka S, Kadowaki T, Tanaka M, Oda Y. Quantitative phosphorus metabolomics using nanoflow liquid

chromatography-tandem mass spectrometry and culture-derived comprehensive global internal standards. Anal Chem, 2009, 81: 3836–3842 9 Myint KT, Uehara T, Aoshima K, Oda Y. Polar anionic metabolome analysis by nano-LC/MS with a metal chelating agent. Anal Chem,

2009, 81: 7766–7772

10 Boernsen KO, Gatzek S, Imbert G. Controlled protein precipitation in combination with chip-based nanospray infusion mass spectrometry.

An approach for metabolomics profiling of plasma. Anal Chem, 2005, 77: 7255–7264

11 Zenobi R. Single-cell metabolomics: analytical and biological perspectives. Science, 2013, 342: 1201–1211

12 Kirkwood JS, Maier C, Stevens JF. Simultaneous, untargeted metabolic profiling of polar and nonpolar metabolites by LC-Q-TOF mass

spectrometry. Curr Protoc Toxicol, 2013, 56: 4.39.1–4.39.12

13 Moritz F, Forcisi S, Harir M, Kanawati B, Lucio M, Tziotis D, Schmitt-Kopplin P. The potential of ultrahigh resolution MS (FTlCR-MS) in

metabolomics. In: Lammerhofer M, Veckwerth W, Eds. Metabolomics in Practice: Successful Strategies to Generate and Analyze Metabolic Data. Weinheim: Wiley, 2013

14 Shrestha B, Vertes A. In situ metabolic profiling of single cells by laser ablation electrospray ionization mass spectrometry. Anal Chem,

2009, 81: 8265–8271

15 Issaq HJ, Van QN, Waybright TJ, Muschik GM, Veenstra TD. Analytical and statistical approaches to metabolomics research. J Sep Sci,

2009, 32: 2183–2199

16 Tomita M, KamiK. Systems biology, metabolomics, and cancer metabolism. Science, 2013, 336: 990–991

17 Jain M, Nilsson R, Sharma S, Madhusudhan N, Kitami T, Souza AL, Kafri R, Kirschner MW, Clish CB, Mootha VK. Metabolite profiling

identifies a key role for glycine in rapid cancer cell proliferation. Science, 2012, 336: 1040–1044

18 Dai WD, Huang Q, Yin PY, Li J, Zhou J, Kong HW, Zhao CX, Lu X, Xu GW. Comprehensive and highly sensitive urinary steroid hormone

profiling method based on stable isotope-labeling liquid chromatography-mass spectrometry. Anal Chem, 2012, 84: 10245–10251

19 Wang Y, Lu X, Xu GW. Development of a comprehensive two-dimensional hydrophilic interaction chromatography/quadrupole

time-of-flight mass spectrometry system and its application in separation and identification of saponins from quillaja saponaria. J Chromatogr A, 2008, 1181: 51–59

20 Wang Y, Wang JS, Yao M, Zhao XJ, Fritsche J, Schmitt-Kopplin P, Cai ZW, Wan DF, Lu X, Yang SL, Gu JR, Häring HU, Schleicher ED,

Lehmann R, Xu GW. Metabonomics study on the effects of the ginsenoside Rg3 in a beta-cyclodextrin-based formulation on tumor-bearing rats by a fully automatic hydrophilic interaction/reversed-phase column-switching HPLC-ESI-MS approach. Anal Chem, 2008, 80: 4680–4688

21 Wang SY, Li J, Shi XZ, Qiao LZ, Lu X, Xu GW. A novel stop-flow two-dimensional liquid chromatography-mass spectrometry method for

lipid analysis. J Chromatogr A, 2013, 1321: 65–72

22 Chen SL, Kong HW, Lu X, Li Y, Yin PY, Zeng ZD, Xu GW. Pseudotargeted metabolomics method and its application in serum biomarker

discovery for hepatocellular carcinoma based on ultra high-performance liquid chromatography/triple quadrupole mass spectrometry. Anal Chem, 2013, 85: 8326–8333

23 Yang J, Xu GW, Zheng YF, Kong HW, Wang C, Zhao XJ, Pang T. Strategy for metabonomics research based on high-performance liquid

chromatography and liquid chromatography coupled with tandem mass spectrometry. J Chromatogr A, 2005, 1084: 214–221

24 Lin XH, Yang FF, Zhou LN, Yin PY, Kong HW, Xing WB, Lu X, Jia LW, Wang QC, Xu GW. A support vector machine-recursive feature

elimination feature selection method based on artificial contrast variables and mutual information. J Chromatogr B, 2012, 910: 149–155 25 Lin XH, Wang QC, Yin PY, Tang L, Tan YX, Li H, Yan K, Xu GW. A method for handling metabonomics data from liquid

chromatography/mass spectrometry: combinational use of support vector machine recursive feature elimination, genetic algorithm and random forest for feature selection. Metabolomics, 2011, 7: 549–558

26 Li X, Lu X, Tian J, Gao P, Kong HW, Xu GW. Application of fuzzy c-means clustering in data analysis of metabolomics. Anal Chem, 2009,

81: 4468–4475

27 Chen J, Zhao XJ, Fritsche J, Yin PW, Schmitt-Kopplin P, Wang WZ, Lu X, Häring HU, Schleicher ED, Lehmann R, Xu GW. Practical

727

王献等: 基于质谱技术的代谢组学研究及其在中国的发展

approach for the identification and isomer elucidation of biomarkers detected in a metabonomic study for the discovery of individuals at risk for diabetes by integrating the chromatographic and mass spectrometric information. Anal Chem, 2008, 80: 1280–1289

28 Gu Y, Zhang YF, Shi XZ, Li XY, Hong J, Chen J, Gu WQ, Lu X, Xu GW, Ning G. Effect of traditional Chinese medicine berberine on type

2 diabetes based on comprehensive metabonomics. Talanta, 2010, 81: 766–772

29 Hu CX, Wei H, Kong HW, Bouwman J, Gonzalez-Covarrubias V, van der Heijden R, Reijmers TH, Bao X, Verheij ER, Hankemeier T, Xu

GW, van der Greef J, Wang M. Linking biological activity with herbal constituents by systems biology-based approaches: effects of panax ginseng in type 2 diabetic Goto-Kakizaki rats. Mol Biosyst, 2011, 7: 3094–3103

30 Hu CX, Wei H, van den Hoek AM, Wang M, van der Heijden R, Spijksma G, Reijmers TH, Bouwman J, Wopereis S, Havekes LM, Verheij

E, Hankemeier T, Xu GW, van der Greef J. Plasma and liver lipidomics response to an intervention of rimonabant in ApoE*3Leiden.CETP transgenic mice. PloS One, 2011, 6: e19423

31 Huang Q, Yin PY, Wang J, Chen J, Kong HW, Lu X, Xu GW. Method for liver tissue metabolic profiling study and its application in type 2

diabetic rats based on ultra performance liquid chromatography-mass spectrometry. J Chromatogr B, 2011, 879: 961–967

32 Lehmann R, Zhao XJ, Weigert C, Simon P, Fehrenbach E, Fritsche J, Machann J, Schick F, Wang JS, Hoene M, Schleicher ED, Häring HU,

Xu GW, Niess AM. Medium chain acylcarnitines dominate the metabolite pattern in humans under moderate intensity exercise and support lipid oxidation. PloS One, 2010, 5: e11519

33 Li X, Luo XX, Lu X, Duan JG, Xu GW. Metabolomics study of diabetic retinopathy using gas chromatography-mass spectrometry: a

comparison of stages and subtypes diagnosed by Western and Chinese medicine. Mol Biosyst, 2011, 7: 2228–2237

34 Li X, Xu ZL, Lu X, Yang XH, Yin PY, Kong HW, Yu Y, Xu GW. Comprehensive two-dimensional gas chromatography/time-of-flight

mass spectrometry for metabonomics: biomarker discovery for diabetes mellitus. Anal Chim Acta, 2009, 633: 257–262

35 Lucio M, Fekete A, Weigert C, Wagele B, Zhao XJ, Chen J, Fritsche A, Häring HU, Schleicher ED, Xu GW, Schmitt-Kopplin P, Lehmann

R. Insulin sensitivity is reflected by characteristic metabolic fingerprints: a Fourier transform mass spectrometric non-targeted metabolomics approach. PloS One, 2010, 5: e13317

36 Wang C, Kong HW, Guan YF, Yang J, Gu JR, Yang SL, Xu GW. Plasma phospholipid metabolic profiling and biomarkers of type 2

diabetes mellitus based on high-performance liquid chromatography/electrospray mass spectrometry and multivariate statistical analysis. Anal Chem, 2005, 77: 4108–4116

37 Yang J, Xu GW, Hong QF, Liebich HM, Lutz K, Schmulling RM, Wahl HG. Discrimination of type 2 diabetic patients from healthy

controls by using metabonomics method based on their serum fatty acid profiles. J Chromatogr B, 2004, 813: 53–58

38 Yuan KL, Kong HW, Guan YF, Yang J, Xu GW. A GC-based metabonomics investigation of type 2 diabetes by organic acids metabolic

profile. J Chromatogr B, 2007, 850: 236–240

39 Zhao XJ, Fritsche J, Wang JS, Chen J, Rittig K, Schmitt-Kopplin P, Fritsche A, Häring HU, Schleicher ED, Xu GW, Lehmann R.

Metabonomic fingerprints of fasting plasma and spot urine reveal human pre-diabetic metabolic traits. Metabolomics, 2010, 6: 362–374 40 Zhao XJ, Peter A, Fritsche J, Elcnerova M, Fritsche A, Häring HU, Schleicher ED, Xu GW, Lehmann R. Changes of the plasma

metabolome during an oral glucose tolerance test: is there more than glucose to look at? Am J Physiol Endocrinol Metab, 2009, 296: E384–E393

41 Huang Q, Tan YX, Yin PY, Ye GZ, Gao P, Lu X, Wang HY, Xu GW. Metabolic characterization of hepatocellular carcinoma using

nontargeted tissue metabolomics. Cancer Res, 2013, 73: 4992–5002

42 Tan YX, Yin PY, Tang L, Xing WB, Huang Q, Cao D, Zhao XJ, Wang WZ, Lu X, Xu ZL, Wang HY, Xu GW. Metabolomics study of

stepwise hepatocarcinogenesis from the model rats to patients: potential biomarkers effective for small hepatocellular carcinoma diagnosis. Mol Cell Proteomics, 2012, 11: M111.010694

43 Ye GZ, Zhu B, Yao ZZ, Yin PY, Lu X, Kong HW, Fan F, Jiao BH, Xu GW. Analysis of urinary metabolic signatures of early hepatocellular

carcinoma recurrence after surgical removal using gas chromatography-mass spectrometry. J Proteome Res, 2012, 11: 4361–4372

44 Chen J, Zhang XY, Cao R, Lu X, Zhao SM, Fekete A, Huang Q, Schmitt-Kopplin P, Wang YS, Xu ZL, Wan XP, Wu XH, Zhao NQ, Xu CJ,

Xu GW. Serum 27-nor-5 beta-cholestane-3, 7, 12, 24, 25 pentol glucuronide discovered by metabolomics as potential diagnostic biomarker for epithelium ovarian cancer. J Proteome Res, 2011, 10: 2625–2632

45 Yang Q, Shi XZ, Wang Y, Wang WZ, He HB, Lu X, Xu GW. Urinary metabonomic study of lung cancer by a fully automatic hyphenated

hydrophilic interaction/RPLC-MS system. J Sep Sci, 2010, 33: 1495–1503

46 Li HY, Wang SM, Liu HM, Li J, Han D, Bu SS, Zhang MZ. Analysis of modified nucleosides in the urine of patients with malignant cancer

by liquid chromatography/electrospray ionization mass spectrometry. Rapid Commun Mass Spectrom, 2008, 22: 3161–3171

47 Wang WZ, Feng B, Li X, Yin PY, Gao P, Zhao XJ, Lu X, Zheng MH, Xu GW. Urinary metabolic profiling of colorectal carcinoma based

728

中国科学: 化学 2014年 第44卷 第5期

on online affinity solid phase extraction-high performance liquid chromatography and ultra performance liquid chromatography-mass spectrometry. Mol Biosyst, 2010, 6: 1947–1955

48 Xu G, Di Stefano C, Liebich HM, Zhang Y, Lu P. Reversed-phase high-performance liquid chromatographic investigation of urinary normal

and modified nucleosides of cancer patients. J Chromatogr B, 1999, 732: 307–313

49 Zhao XJ, Wang WZ, Wang JS, Yang J, Xu GW. Urinary profiling investigation of metabolites with cis-diol structure from cancer patients

based on UPLC-MS and HPLC-MS as well as multivariate statistical analysis. J Sep Sci, 2006, 29: 2444–2451

50 Gu Y, Lu C, Zha QL, Kong HW, Lu X, Lu AP, Xu GW. Plasma metabonomics study of rheumatoid arthritis and its Chinese medicine

subtypes by using liquid chromatography and gas chromatography coupled with mass spectrometry. Mol Biosyst, 2012, 8: 1535–1543 51 He HB, Ren XB, Wang XY, Shi XZ, Wang XL, Ding ZJ, Gao P, Xu GW. Therapeutic effect of Yunnan Baiyao on rheumatoid arthritis was

partially due to regulating arachidonic acid metabolism in osteoblasts. J Pharmaceut Biomed Anal, 2012, 59: 130–137

52 Zhao XJ, Zhang Y, Meng XL, Yin PY, Deng C, Chen J, Wang Z, Xu GW. Effect of a traditional Chinese medicine preparation Xindi soft

capsule on rat model of acute blood stasis: a urinary metabonomics study based on liquid chromatography-mass spectrometry. J Chromatogr B, 2008, 873: 151–158

53 Zhou J, Zhang L, Chang YW, Lu X, Zhu Z, Xu GW. Alteration of leaf metabolism in Bt-transgenic rice (Oryza sativa L.) and its wild type

under insecticide stress. J Proteome Res, 2012, 11: 4351–4360

54 Chang YW, Zhao CX, Zhu Z, Wu ZM, Zhou J, Zhao YN, Lu X, Xu GW. Metabolic profiling based on LC/MS to evaluate unintended

effects of transgenic rice with cry1Ac and sck genes. Plant Mol Biol, 2012, 78: 477–487

55 Wu R, Wu ZM, Wang XH, Yang PC, Yu D, Zhao CX, Xu GW, Kang L. Metabolomic analysis reveals that carnitines are key regulatory

metabolites in phase transition of the locusts. Proc Natl Acad Sci USA, 2012, 109: 3259–3263

56 Li J, Hoene M, Zhao XJ, Chen SL, Wei H, Häring HU, Lin XH, Zeng ZD, Weigert C, Lehmann R, Xu GW. Stable isotope-assisted

lipidomics combined with nontargeted isotopomer filtering, a tool to unravel the complex dynamics of lipid metabolism. Anal Chem, 2013, 85: 4651–4657

57 Wolf M, Chen S, Zhao X, Scheler M, Irmler M, Staiger H, Beckers J, de Angelis MH, Fritsche A, Häring HU, Schleicher ED, Xu GW,

Lehmann R, Weigert C. Production and release of acylcarnitines by primary myotubes reflect the differences in fasting fat oxidation of the donors. J Clin Endocrinol Metab, 2013, 98: E1137–E1142

58 Lehmann R, Franken H, Dammeier S, Rosenbaum L, Kantartzis K, Peter A, Zell A, Adam P, Li J, Xu GW, Konigsrainer A, Machann J,

Schick F, Hrabe de Angelis M, Schwab M, Staiger H, Schleicher E, Gastaldelli A, Fritsche A, Haring HU, Stefan N. Circulating lysophosphatidylcholines are markers of a metabolically benign nonalcoholic fatty liver. Diabetes Care, 2013, 36: 2331–2338

59 Xu J, Chen YH, Zhang RP, Song YM, Cao JZ, Bi N, Wang JB, He JM, Bai JF, Dong LJ, Wang LH, Zhan QM, Abliz Z. Global and targeted

metabolomics of esophageal squamous cell carcinoma discovers potential diagnostic and therapeutic biomarkers. Mol Cell Proteomics, 2013, 12: 1306–1318

60 An ZL, Chen YH, Zhang RP, Song YM, Sun JH, He JM, Bai JF, Dong LJ, Zhan QM, Abliz Z. Integrated ionization approach for

RRLC-MS/MS-based metabonomics: finding potential biomarkers for lung cancer. J Proteome Res, 2010, 9: 4071–4081

61 Chen YH, Zhang RP, Song YM, He JM, Sun JH, Bai JF, An ZL, Dong LJ, Zhan QM, Abliz Z. RRLC-MS/MS-based metabonomics

combined with in-depth analysis of metabolic correlation network: finding potential biomarkers for breast cancer. Analyst, 2009, 134: 2003–2011

62 Chen YH, Xu J, Zhang RP, Shen GQ, Song YM, Sun JH, He JM, Zhan QM, Abliz Z. Assessment of data pre-processing methods for

LC-MS/MS-based metabolomics of uterine cervix cancer. Analyst, 2013, 138: 2669–2677

63 Chen YH, Shen G,Q Zhang RP, He JM, Zhang Y, Xu J, Yang W, Chen XJ, Song YM, Abliz Z. Combination of injection volume calibration

by creatinine and MS signals’ normalization to overcome urine variability in LC-MS-based metabolomics studies. Anal Chem, 2013, 85: 7659–7665

64 Shen GQ, Chen YH, Sun JH, Zhang RP, Zhang Y, He JM, Tian YP, Song YM, Chen XJ, Abliz Z. Time-course changes in potential

biomarkers detected using a metabonomic approach in Walker 256 tumor-bearing rats. J Proteome Res, 2011, 10: 1953–1961

65 Yang W, Chen YH, Xi C, Zhang RP, Song YM, Zhan QM, Bi XF, Abliz Z. Liquid chromatography-tandem mass spectrometry-based

plasma metabonomics delineate the effect of metabolites’ stability on reliability of potential biomarkers. Anal Chem, 2013, 85: 2606–2610 66 Li SF, Liu HX, Jin YB, Lin SH, Cai ZW, Jiang YY. Metabolomics study of alcohol-induced liver injury and hepatocellular carcinoma

xenografts in mice. J Chromatogr B, 2011, 879: 2369–2375

67 Lin SH, Kanawati B, Liu LF, Witting M, Li M, Huang JD, Schmitt-Kopplin P, Cai ZW. Ultrahigh resolution mass spectrometry-based

metabolic characterization reveals cerebellum as a disturbed region in two animal models. Talanta, 2014, 118: 45–53

729

王献等: 基于质谱技术的代谢组学研究及其在中国的发展

68 Lin SH, Liu HD, Kanawati B, Liu LF, Dong JY, Li M, Huang JD, Schmitt-Kopplin P, Cai ZW. Hippocampal metabolomics using

ultrahigh-resolution mass spectrometry reveals neuroinflammation from Alzheimer’s disease in CRND8 mice. Anal Bioanal Chem, 2013, 405: 5105–5117

69 Lin SH, Liu N, Yang Z, Song WJ, Wang P, Chen HL, Lucio M, Schmitt-Kopplin P, Chen GN, Cai ZW. GC/MS-based metabolomics reveals

fatty acid biosynthesis and cholesterol metabolism in cell lines infected with influenza A virus. Talanta, 2010, 83: 262–268

70 Lin SH, Chan W, Li JH, Cai ZW. Liquid chromatography/mass spectrometry for investigating the biochemical effects induced by

aristolochic acid in rats: the plasma metabolome. Rapid Commun Mass Spectrom, 2010, 24: 1312–1318

71 Lin SH, Yang Z, Liu HD, Tang LH, Cai ZW. Beyond glucose: metabolic shifts in responses to the effects of the oral glucose tolerance test

and the high-fructose diet in rats. Mol Biosyst, 2011, 7: 1537–1548

72 Lin SH, Yang Z, Liu HD, Cai ZW. Metabolomic analysis of liver and skeletal muscle tissues in C57BL/6J and DBA/2J mice exposed to

2,3,7,8- tetrachlorodibenzo-p-dioxin. Mol Biosyst, 2011, 7: 1956–1965

73 Lin SH, Yang Z, Zhang XJ, Bian ZX, Cai ZW. Hippocampal metabolomics reveals 2,3,7,8-tetrachlorodibenzo-p-dioxin toxicity associated

with ageing in Sprague-Dawley rats. Talanta, 2011, 85: 1007–1012

74 Lin SH, Yang Z, Shen Y, Cai ZW. LC/MS-based non-targeted metabolomics for the investigation of general toxicity of 2,3,7,8-

tetrachlorodibenzo-p-dioxin in C57BL/6J and DBA/2J mice. Int J Mass Spectrom, 2011, 301: 29–36

75 Zhang XJ, Choi FFK, Zhou Y, Leung FP, Tan S, Lin SH, Xu HX, Jia W, Sung JJY, Cai ZW, Bian ZX. Metabolite profiling iof plasma and

urine from rats with TNBS-induced acute colitis using UPLC-ESI-QTOF-MS-based metabonomics: a pilot study. FEBS J, 2012, 279: 2322–2338

76 Chan W, Lee KC, Liu N, Wong RNS, Liu HW, Cai ZW. Liquid chromatography/mass spectrometry for metabonomics investigation of the

biochemical effects induced by aristolochic acid in rats: the uise of information dependent acquistion for biomarker identification. Rapid Commun Mass Spectrom, 2008, 22: 873–880

77 Chan W, Lin SH, Sun S, Liu HD, Luk JM, Cai ZW. Metabolomics analysis of the responses to partial hepatectomy in hepatocellular

carcinoma patients. Am J Anal Chem, 2011, 2: 142–151

78 Chan W, Cai ZW. Aristolochic acid induced changes in the metabolic profile of rat urine. J Pharmaceut Biomed Anal, 2008, 46: 757–762 79 Dai H, Xiao CN, Liu HB, Hao FH, Tang HR. Combined NMR and LC-DAD-MS analysis reveals comprehensive metabonomic variations

for three phenotypic cultivars of Salvia Miltiorrhiza Bunge. J Proteome Res, 2010, 9: 1565–1578

80 Dai H, Xiao CN, Liu HB, Tang HR. Combined NMR and LC-MS analysis reveals the metabonomic changes in Salvia miltiorrhiza Bunge

induced by water depletion. J Proteome Res, 2010, 9: 1460–1475

81 Liu HB, Zheng AM, Liu HL, Yu HY, Wu XY, Xiao CN, Dai H, Hao FH, Zhang LM, Wang YL, Tang HR. Identification of three novel

polyphenolic compounds, origanine A–C, with unique skeleton from Origanum vulgare L. using the hyphenated LC-DAD-SPE-NMR/MS methods. J Agr Food Chem, 2011, 60: 129–135

82 Nie HG, Liu RR, Yang YY, Bai Y, Guan YF, Qian DQ, Wang T, Liu HW. Lipid profiling of rat peritoneal surface layers by online

normal-and reversed-phase 2D LC QTOF-MS. J Lipid Res, 2010, 51: 2833–2844

83 Li M, Yang Li, Bai Y, Liu HW. Analytical methods in lipidomics and their applications. Anal Chem, 2014, 86: 161–175

84 Li M, Zhou ZG, Nie HG, Bai Y, Liu HW. Recent advances of chromatography and mass spectrometry in lipidomics. Anal Bioanal Chem,

2011, 399: 243–249

85 Li M, Feng BS, Liang Y, Zhang W, Bai Y, Tang W, Wang T, Liu HW. Lipid profiling of human plasma from peritoneal dialysis patients

using an improved 2D (NP/RP) LC-QTOF MS method. Anal Bioanal Chem, 2013, 405: 6629–6638

86 Chen HW, Wortmann A, Zenobi R. Neutral desorption sampling coupled to extractive electrospray ionization mass spectrometry for rapid

differentiation of biosamples by metabolomic fingerprinting. J Mass Spectrom, 2007, 42: 1123–1135

87 Gu HW, Qi YP, Xu N, Ding JH, An YB, Chen HW. Nuclear magnetic resonance spectroscopy and mass spectrometry-based metabolomics

for cancer diagnosis. Chin J Anal Chem, 2012, 40: 1933–1937

88 Gao D, Wei H, Guo GS, Lin JM. Microfluidic cell culture and metabolism detection with electrospray ionization quadrupole time-of-flight

mass spectrometer. Anal Chem, 2010, 82: 5679–5685

89 Jin Y, Wu CS, Zhang JL, Li YF. A new strategy for the discovery of epimedium metabolites using high-performance liquid chromatography

with high resolution mass spectrometry. Anal Chim Acta, 2013, 768: 111–117

90 Qu F, Wu CS, Hou JF, Jin Y, Zhang JL. Sphingolipids as new biomarkers for assessment of delayed-type hypersensitivity and response to

triptolide. PloS One, 2012, 7: e52454

91 Yang B, Zhang AH, Sun H, Wei D, Yan GL, Li TL, Wang XJ. Metabolomics study on the hepatoprotective effect of scoparone using ultra-

730

中国科学: 化学 2014年 第44卷 第5期

performance liquid chromatography/electrospray ionization quadruple time-of-flight mass spectrometry. J Pharm Biomed Anal, 2012, 58: 113–124

92 Wang XJ, Zhang AH, Wang P, Sun H, Wu GL, Sun WJ, Lv HT, Jiao GZ, Xu HY, Yuan Y, Liu L, Zou DX, Wu ZM, Han Y, Yan GL, Dong

W, Wu FF, Dong TW, Yu Y, Zhang SX, Wu XH, Tong X, Meng XC. Metabolomics coupled with proteomics advancing drug discovery toward more agile development of targeted combination therapies. Mol Cell Proteom, 2013, 12: 1226–1238

93 Zhang AH, Sun H, Dou SS, Sun WJ, Wu XH, Wang P, Wang XJ. Metabolomics study on the hepatoprotective effect of scoparone using

ultra-performance liquid chromatography/electrospray ionization quadruple time-of-flight mass spectrometry. Analyst, 2013, 138: 353–361 94 Dong H, Zhang AH, Sun H, Wang HY, Lu X, Wang M, Ni B, Wang XJ. Ingenuity pathways analysis of urine metabolomics phenotypes

toxicity of Chuanwu in Wistar rats by UPLC-Q-TOF-HDMS coupled with pattern recognition methods. Mol BioSyst, 2012, 8: 1206–1221

Mass spectrometry-based metabolomics and their developments in China

WANG Xian1, 2, LIN ShuHai2, CAI ZongWei2*

1 College of Chemistry and Materials Science, South-Central University for Nationalities, Wuhan 430074, China 2 State Key Laboratory of Environmental and Biological Analysis, Hong Kong Baptist University, Kowloon, China *Corresponding author (email: zwcai@hkbu.edu.hk)

Abstract: As an important component of systems biology, metabonomics (or metabolomics) is a science of studying metabolites and the corresponding changes in living systems. Mass spectrometry is one of the primary analytical tools of metabolomic studies and has been widely applied in many research areas. This paper overviews the recent developments in technologies and applications of mass spectrometry-based metabolomics, highlights major progress and achievement that have been recently gained in China in this field, and discusses the existing problems of mass spectrometry-based metabolomics and the future perspectives.

Keywords: metabonomics, mass spectrometry, systems biology

731

本文来源：https://www.bwwdw.com/article/nzx1.html