From exogenous to endogenous: the inevitable imprint of mass spectrometry in metabolomics

Mass spectrometry (MS) is an established technology in drug metabolite analysis and is now expanding into endogenous metabolite research. Its utility derives from its wide dynamic range, reproducible quantitative analysis, and the ability to analyze biofluids with extreme molecular complexity. The aims of developing mass spectrometry for metabolomics range from understanding basic biochemistry to biomarker discovery and the structural characterization of physiologically important metabolites. In this review, we will discuss the techniques involved in this exciting area and the current and future applications of this field.     

代谢组学技术及其在临床研究中的应用

在后基因组时代, 系统生物学研究成为人们关注的焦点。转录组学、蛋白质组学等功能基因组学研究方法可同时检测药物或其他因素影响下大量基因或蛋白质的表达变化情况, 但这些变化不能与生物学功能的变化建立直接联系。代谢组学方法则可为代谢物含量变化与生物表型变化建立直接相关性。代谢组学研究的目的是定量分析一个生物系统内所有代谢物的含量, 进行全面代谢物分析需要分析化学技术的支撑, 核磁共振和基于质谱的分析技术是代谢组学研究的两种主要技术手段。代谢组学研究可产生大量数据信息, 对这些数据进行分析离不开化学统计学的应用, 比如主成分分析、多维缩放、各种聚类分析技术以及功能差异分析等。文章综述了近年来代谢组学分析技术及数据分析技术的研究进展, 在此基础上, 对代谢组学在临床研究及临床前研究中的应用研究进展进行了综述。对疾病代谢表型图谱的研究有助于人们了解疾病发生、发展以及致死的机制; 在临床条件下, 这些代谢图谱可以作为疾病诊断、预后以及治疗的评判标准。代谢物组成的变化是毒物胁迫对机体造成的最终影响, 利用代谢组技术可以直接反映毒物对机体的影响。质谱技术、核磁共振技术的应用使得药物筛选过程可以快速完成, 并有助于实现个性化用药。此外, 利用代谢组学技术还可以进行已知酶的新活性研究, 也可以研究未知酶。     

Analytical strategies in metabonomics

To perform metabonomics investigations, it is necessary to generate comprehensive metabolite profiles for complex samples such as biofluids and tissue/tissue extracts. Analytical technologies that can be used to achieve this aim are constantly evolving, and new developments are changing the way in which such profiles' metabolite profiles can be generated. Here, the utility of various analytical techniques for global metabolite profiling, such as, e.g., 1H NMR, MS, HPLC-MS, and GC-MS, are explored and compared.     

代谢组学技术在水产动物疾病研究中的应用

代谢组学是定量描述生物内源性代谢物质的整体及其对内因和外因变化应答规律的的一门新学科。近年来,代谢组学技术在水产动物疾病中的研究备受关注,特别是为感染性疾病发生机制及防控研究提供了一种新的手段。本文介绍了代谢组学技术及其在水产动物研究中的应用,包括代谢组学技术在水产动物感染性疾病、细菌耐药及环境应激等方面应用进行综述,分析了代谢组学在水产动物疾病研究中面临的问题与挑战,并对未来水产动物代谢组学研究趋势进行了展望,以期为代谢组学技术在水产动物疾病发病机制和药物研发方面更深入的运用提供参考。     

Widely Targeted Metabolomics Based on Large-Scale MS/MS Data for Elucidating Metabolite Accumulation Patterns in Plants

Metabolomics is an ‘omics’ approach that aims toanalyze all metabolites in a biological sample comprehensively.The detailed metabolite profiling of thousands of plant sampleshas great potential for directly elucidating plant metabolicprocesses. However, both a comprehensive analysis and a highthroughput are difficult to achieve at the same time due tothe wide diversity of metabolites in plants. Here, we have establisheda novel and practical metabolomics methodology for quantifyinghundreds of targeted metabolites in a high-throughput manner.Multiple reaction monitoring (MRM) using tandem quadrupole massspectrometry (TQMS), which monitors both the specific precursorions and product ions of each metabolite, is a standard techniquein targeted metabolomics, as it enables high sensitivity, reproducibilityand a broad dynamic range. In this study, we optimized the MRMconditions for specific compounds by performing automated flowinjection analyses with TQMS. Based on a total of 61,920 spectrafor 860 authentic compounds, the MRM conditions of 497 compoundswere successfully optimized. These were applied to high-throughputautomated analysis of biological samples using TQMS coupledwith ultra performance liquid chromatography (UPLC). By thisanalysis, approximately 100 metabolites were quantified in eachof 14 plant accessions from Brassicaceae, Gramineae and Fabaceae.A hierarchical cluster analysis based on the metabolite accumulationpatterns clearly showed differences among the plant families,and family-specific metabolites could be predicted using a batch-learningself-organizing map analysis. Thus, the automated widely targetedmetabolomics approach established here should pave the way forlarge-scale metabolite profiling and comparative metabolomics.     

代谢组学及其应用

对代谢组学的概念、特性、发展历史做了简要介绍,综述了当前代谢组学研究中的数据采集、数据分析中采用的技术,及代谢组学在疾病诊断、药物毒性研究、植物和微生物等邻域的应用,并对代谢组学的发展作了展望。     

High performance liquid chromatography-mass spectrometry for metabonomics: potential biomarkers for acute deterioration of liver function in chronic hepatitis B

Metabonomics methods have been successfully applied to the drug discovery, toxicology, phytochemistry, and clinical fields. Here, we report a self-developed metabonomics platform which is based on high performance liquid chromatography-mass spectrometry (HPLC-MS) technique and applied to the investigation of acute deterioration of liver function in chronic hepatitis B to find the potential biomarkers. Sera from 50 healthy persons and 37 patients with acute deterioration of liver function in chronic hepatitis B were analyzed by HPLC-MS after removal of proteins. After de-noise, peak detection and peak alignment, the data of metabolites were fed to partial least squares discriminant analysis (PLS-DA) to find the potential biomarkers. According to the corresponding tandem mass results, several potential biomarkers were identified: Lysophosphatidyl Choline (LPC) C18:0, LPC C16:0, LPC C18:1, LPC C18:2, and glycochenodeoxycholic acid (GCDCA) (or its isomer glycodeoxycholic acid (GDCA)). On the basis of the relevant literature and pathway databases, the biological significance of the present study is discussed.     

气相色谱-质谱联用技术及其在代谢组学中的应用

代谢组学是以高通量、高灵敏度、高分辨率的现代仪器分析方法为手段,对细胞、体液、组织中所有代谢物进行无偏向的定性与定量分析的一门学科。气相色谱-质谱联用技术具有较高的检测灵敏度和鉴定准确度,通过标准谱图库的比对可对代谢物进行快速的鉴定,因此被广泛应用于生物样品的代谢产物的检测中。文中对近年来气相色谱-质谱联用技术的发展以及在代谢组学研究中取得的成果进行了综述。首先介绍了气相色谱-质谱联用技术的分类和常用的样品衍生化方法;继而从样品预处理、定性与定量分析、数据分析三方面介绍了气相色谱-质谱联用技术分析代谢物的方法,并系统地对该技术在微生物、植物、疾病诊断领域的应用实例进行了评述;最后提出了当前气相色谱-质谱联用技术在代谢组学研究中存在的问题并对后续的研究进行了展望。     

Safety assessment of transgenic Bacillus thuringiensis rice T1c-19 in Sprague-Dawley rats from metabonomics and bacterial profile perspectives

Bacillus thuringiensis rice is facing commercialization as the main food source in the near future. The unintended effects of genetically modified (GM) organisms are the most important barriers to their promotion. We aimed to establish a new in vivo evaluation model for genetically modified foods by using metabonomics and bacterial profile approaches. T1c-19 rice flour or its transgenic parent MH63 was used at 70% wt/wt to produce diets that were fed to rats for ～ 90 days. Urine metabolite changes were detected using (1)H NMR. Denaturing gradient gel electrophoresis and real-time polymerase chain reaction (RT-PCR) were used to detect the bacterial profiles between the two groups. The metabonomics was analyzed for metabolite changes in rat urine, when compared with the non-GM rice group, where rats were fed a GM rice diet. Several metabolites correlated with rat age and sex but not with GM rice diet. Significant biological differences were not identified between the GM rice diet and the non-GM rice diet. The bacteria related to rat urine metabolites were also discussed. The results from metabonomics and bacterial profile analyses were comparable with the results attained using the traditional method. Because metabonomics and bacterial profiling offer noninvasive, dynamic approaches for monitoring food safety, they provide a novel process for assessing the safety of GM foods.     

Technical advance: simultaneous analysis of metabolites in potato tuber by gas chromatography-mass spectrometry

A new method is presented in which gas chromatography coupled to mass spectrometry (GC-MS) allows the quantitative and qualitative detection of more than 150 compounds within a potato tuber, in a highly sensitive and specific manner. In contrast to other methods developed for metabolite analysis in plant systems, this method represents an unbiased and open approach that allows the detection of unexpected changes in metabolite levels. Although the method represents a compromise for a wide range of metabolites in terms of extraction, chemical modification and GC-MS analysis, for 25 metabolites analysed in detail the recoveries were found to be within the generally accepted range of 70-140%. Further, the reproducibility of the method was high: the error occurring in the analysis procedures was found to be less than 6% for 30 out of 33 compounds tested. Biological variability exceeded the systematic error of the analysis by a factor of up to 10. The method is also suited for upscaling, potentially allowing the simultaneous analysis of a large number of samples. As a first example this method has been applied to soil- and in vitro-grown tubers. Due to the simultaneous analysis of a wide range of metabolites it was immediately apparent that these systems differ significantly in their metabolism. Furthermore, the parallel insight into many pathways allows some conclusions to be drawn about the underlying physiological differences between both tuber systems. As a second example, transgenic lines modified in sucrose catabolism or starch synthesis were analysed. This example illustrates the power of an unbiased approach to detecting unexpected changes in transgenic lines.     

Metabonomics evaluation of urine from rats given acute and chronic doses of acetaminophen using NMR and UPLC/MS

Urinary metabolic perturbations associated with acute and chronic acetaminophen-induced hepatotoxicity were investigated using nuclear magnetic resonance (NMR) spectroscopy and ultra performance liquid chromatography/mass spectrometry (UPLC/MS) metabonomics approaches to determine biomarkers of hepatotoxicity. Acute and chronic doses of acetaminophen (APAP) were administered to male Sprague-Dawley rats. NMR and UPLC/MS were able to detect both drug metabolites and endogenous metabolites simultaneously. The principal component analysis (PCA) of NMR or UPLC/MS spectra showed that metabolic changes observed in both acute and chronic dosing of acetaminophen were similar. Histopathology and clinical chemistry studies were performed and correlated well with the PCA analysis and magnitude of metabolite changes. Depletion of antioxidants (e.g. ferulic acid), trigonelline, S-adenosyl-l-methionine, and energy-related metabolites indicated that oxidative stress was caused by acute and chronic acetaminophen administration. Similar patterns of metabolic changes in response to acute or chronic dosing suggest similar detoxification and recovery mechanisms following APAP administration.     

Metabonomics study of transgenic Bacillus thuringiensis rice (T2A-1) meal in a 90-day dietary toxicity study in rats

Rice is one of the most important staple foods in the world. The Cry2A gene was inserted into the rice genome to help the plant combat insects. As the unintended effects of the genetically modified (GM) organisms are the most important barriers to the promotion of GM organisms, we have carried out a useful exploration to establish a new in vivo evaluation model for genetically modified foods by metabonomics methods. In this study, the rats were fed for 90 days with the GM and NON-GM rice diets. The changes in metabolites of the urine were detected using (1)H-NMR. The metabonomics were analyzed to see whether the GM rice can induce the metabolite changes in the rats' urine when compared with the NON-GM rice group. The multivariate analysis and ANOVA were used to determine the differences and the significance of differences respectively, and eventually we concluded that these differences did not have a biological significance. The conclusion of the metabonomics was comparable with that from the traditional method. As a non-invasive and dynamic monitoring method, metabonomics will be a new way of assessing the food safety of GM foods.     

Metabolic regulatory network alterations in response to acute cold stress and ginsenoside intervention

Acute stress may trigger systemic biochemical and physiological changes in living organisms, leading to a rapid loss of homeostasis, which can be gradually reinstated by self-regulatory mechanisms and/or drug intervention strategy. However, such a sophisticated metabolic regulatory process has so far been poorly understood, especially from a holistic view. Urinary metabolite profiling of Sprague-Dawley rats exposed to cold temperature (-10 degrees C) for 2 h using GC/MS in conjunction with modern multivariate statistical techniques revealed drastic biochemical changes as evidenced by fluctuations of urinary metabolites and demonstrated the protective effect of total ginsenosides (TGs) in ginseng extracts on stressed rats. The metabonomics approach enables us to visualize significant alterations in metabolite expression patterns as a result of stress-induced metabolic responses and post-stress compensation, and drug intervention. Several major metabolic pathways including catecholamines, glucocorticoids, the tricarboxylic acid (TCA) cycle, tryptophan (nicotinate), and gut microbiota metabolites were identified to be involved in metabolic regulation and compensation required to restore homeostasis.     

Dissection of genotype-phenotype associations in rice grains using metabolome quantitative trait loci analysis

A comprehensive and large‐scale metabolome quantitative trait loci (mQTL) analysis was performed to investigate the genetic backgrounds associated with metabolic phenotypes in rice grains. The metabolome dataset consisted of 759 metabolite signals obtained from the grains of 85 lines of rice (Oryza sativa, Sasanishiki × Habataki back‐crossed inbred lines). Metabolome analysis was performed using four mass spectrometry pipelines to enhance detection of different classes of metabolites. This mQTL analysis of a wide range of metabolites highlighted an uneven distribution of 802 mQTLs on the rice genome, as well as different modes of metabolic trait (m‐trait) control among various types of metabolites. The levels of most metabolites within rice grains were highly sensitive to environmental factors, but only weakly associated with mQTLs. Coordinated control was observed for several groups of metabolites, such as amino acids linked to the mQTL hotspot on chromosome 3. For flavonoids, m‐trait variation among the experimental lines was tightly governed by genetic factors that alter the glycosylation of flavones. Many loci affecting levels of metabolites were detected by QTL analysis, and plausible gene candidates were evaluated by in silico analysis. Several mQTLs profoundly influenced metabolite levels, providing insight into the control of rice metabolism. The genomic region and genes potentially responsible for the biosynthesis of apigenin‐6,8‐di‐C‐α‐l‐ arabinoside are presented as an example of a critical mQTL identified by the analysis.     

代谢组学：一个迅速发展的新兴学科

对代谢组学的含义,中心任务,研究方法,样品要求,应用及其发展方向进行了简要综述. 系统生物学概念的诞生标志着研究哲学由“还原论”向“整体论”的变化. 系统生物学的中心任务就是要针对生物系统整体 (无论它是生物细胞,多细胞组织,器官还是生物整体),建立定量,普适,整体和可预测 (QUIP) 的认知. 具体而言,系统生物学研究就是要将给定生物系统的基因,转录,蛋白质和代谢水平所发生的事件,相关性及其对所涉及生物过程的意义进行整体性认识. 从而出现了许多的“组”和“组学”的新概念. 但是现已提出的一百多个“组”和“组学”,可以大体归纳为“基因组”/“基因组学”,“转录组”/“转录组学”,“蛋白质组”/“蛋白质组学”和“代谢组”/“代谢组学”四个方面. 显而易见,DNA,mRNA 以及蛋白质的存在为生物过程的发生提供了物质基础 (但这个过程有可能不发生!),而代谢物质所反映的是已经发生了的生物学事件. 因此代谢组学是对一个生物系统进行全面认识的不可缺少的一部分,是全局系统生物学 (global systems biology) 的重要基础,也是系统生物学的一个重要组成部分. 在现有的英文表述中,代谢组学同时存在两个不同的词汇和概念,即metabonomics 和 metabolomics. 尽管前者多用在动物系统而后者多用于植物和微生物系统,但这些概念的本质从他们的定义中能够得到较细致的了解. Metabonomics 的最初定义是就生物系统对生理和病理刺激以及基因改变的代谢应答的定量测定(“the quantitative measurement of the multi-parametric metabolic response of living systems to pathophysiological stimuli or geneticmodifications”). 我们认为这个定义现在可以更广泛地表述为:代谢组学是关于定量描述生物内源性代谢物质的整体及其对内因和外因变化应答规律的科学 (“Metabonomics is the branch of science concerned with the quantitative understandings of themetabolite complement of integrated living systems and its dynamic responses to the changes of both endogenous factors (such asphysiology and development) and exogenous factors (such as environmental factors and xenobiotics).”). 其中心任务包括 (1) 对内源性代谢物质的整体及其动态变化规律进行检测,量化和编录,(2) 确定此变化规律和生物过程的有机联系. Metabolomics 存在多个定义,但其精髓是:对一个生物系统的细胞在给定时间和给定条件下所有小分子代谢物质的定量分析(the quantitativemeasurement of all low molecular weight metabolites in an organism's cells at a specified time under specific environmentalconditions). 因此,metabolomics 可以译作“代谢物组学”. 不难看出,前者是对生物系统进行的整体和动态的认识 (不仅关心代谢物质的整体也关注其动态变化规律),而后者强调分析而且是个静态的认识概念. 因此可以认为,metabolomics 是metabonomics 的一个组成部分 (参看定义). 近年又有人提出了“dynamic metabolomics”的概念,这个概念所表达的含义十分接近“metabonomics”本身的含义. 所以,可以预见,随着这门新兴学科的发展和更深入讨论,这两个概念必将趋向一致. 因此我们建议,在中文表述中将“代谢组学”一词和英文中的 metabonomics 相对应,以避免不必要的混淆和争议. 就细胞系统而言,不仅存在细胞自身的代谢物质组成问题,存在细胞之间代谢物质交换的问题,也存在代谢过程所发生的位点问题. 因此,简单地分析代谢物质的总组成 (即代谢组) 缺乏“整体论”所要求的全面性,其意义有一定局限. 代谢组学属于全局系统生物学 (Global systems biology) 研究方法,便于对复杂体系的整体进行认识. 譬如,一个正常工作的人体包括“人体”本身和与之共同进化而来且共生的消化道微生物群体 (或称菌群),孤立地研究“人体”本身的基因,转录子以及蛋白质当然可以为人们认识人体生物学提供重要信息,但无法提供使人体正常工作不可缺少的菌群的信息. 人体血液和尿液的代谢组却携带着包括菌群在内的每一个细胞的信息,因此代谢组学方法对研究如人体这样复杂的进化杂合体十分有效. 正因如此,代谢组学已经广泛地应用到了包括药物研发,分子生理学,分子病理学,基因功能组学,营养学,环境科学等重要领域. 在代谢组学诞生的过去 6 年里,有关代谢组学的研究论文和专利以指数的形式逐年增长. 可以预见,这门新兴学科将应用到更为广泛的领域.     

HPLC-MS-based methods for the study of metabonomics

The development and use of HPLC-MS for the study of metabonomics is reviewed. To date the technique has been applied to the analysis of urine samples obtained from studies in rodents in investigations of physiological variation (e.g., factors such as strain, gender, diurnal variation, etc.) and toxicity. Examples are provided of the use of conventional HPLC, capillary methods and the recently introduced high-resolution systems based on a combination of high pressure and small particle size ("UPLC"). Comparison is also made of the use of 1H NMR spectroscopy and HPLC-MS for the analysis of biofluid samples and the advantages and limitations of the two approaches are assessed. Likely future developments are considered.     

Nutritional metabonomics: applications and perspectives

Nowadays, nutrition focuses on improving health of individuals through diet. Current nutritional research aims at health promotion, disease prevention, and performance improvement. Modern analytical platforms allow the simultaneous measurement of multiple metabolites providing new insights in the understanding of the functionalities of cells and whole organisms. Metabonomics, "the quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modifications", provides a systems approach to understanding global metabolic regulations of organisms. This concept has arisen from various applications of NMR and MS spectroscopies to study the multicomponent metabolic composition of biological fluids, cells, and tissues. The generated metabolic profiles are processed by multivariate statistics to maximize the recovery of information to be correlated with well-determined stimuli such as dietary intervention or with any phenotypic data or diet habits. Metabonomics is thus uniquely suited to assess metabolic responses to deficiencies or excesses of nutrients and bioactive components. Furthermore, metabonomics is used to characterize the metabolic phenotype of individuals integrating genetic polymorphism, metabolic interactions with commensal and symbiotic partners such as gut microflora, as well as environmental and behavioral factors including dietary preferences. This paper reports several experimental key aspects in nutritional metabonomics, reviews its applications employing targeted and holistic approach analysis for the study of the metabolic responses following dietary interventions. It also reports the assessment of intra- and inter-individual variability in animal and human populations. The potentialities of nutritional metabonomics for the discovery of new biomarkers and the characterization of metabolic phenotypes are discussed in a context of their possible utilizations for personalized nutrition to provide health maintenance at the individual level.     

Biotransformation of warfarin by the fungus Beauveria bassiana

Summary Biotransformation of racemic warfarin by the fungus Beauveria bassiana IMI 12939 was studied as part of an investigation into alternative methods for the production of drug metabolites. Resting cell suspensions in buffer were able to biotransform warfarin. High activity occurred within a broad pH range (6.0–9.0) with an optimum at 7.0. The major metabolites were 4-hydroxywarfarin (metabolite I), warfarin alpha-diketone (metabolite B) and diastereomers of novel tautomeric ring-cleaved warfarin (metabolites E and F). The exact quantitative metabolite profile obtained following warfarin metabolism was shown to be highly dependent upon the cell concentration. Kinetic evidence suggested the operation of multiple enzyme activities.     

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

Metabolic markers are the core of metabonomic surveys. Hence selection of differential metabolites is of great importance for either biological or clinical purpose. Here, a feature selection method was developed for complex metabonomic data set. As an effective tool for metabonomics data analysis, support vector machine (SVM) was employed as the basic classifier. To find out meaningful features effectively, support vector machine recursive feature elimination (SVM-RFE) was firstly applied. Then, genetic algorithm (GA) and random forest (RF) which consider the interaction among the metabolites and independent performance of each metabolite in all samples, respectively, were used to obtain more informative metabolic difference and avoid the risk of false positive. A data set from plasma metabonomics study of rat liver diseases developed from hepatitis, cirrhosis to hepatocellular carcinoma was applied for the validation of the method. Besides the good classification results for 3 kinds of liver diseases, 31 important metabolites including lysophosphatidylethanolamine (LPE) C16:0, palmitoylcarnitine, lysophosphatidylethanolamine (LPC) C18:0 were also selected for further studies. A better complementary effect of the three feature selection methods could be seen from the current results. The combinational method also represented more differential metabolites and provided more metabolic information for a “global” understanding of diseases than any single method. Further more, this method is also suitable for other complex biological data sets.     

Prediction of variability in CYP3A4 induction using a combined 1H NMR metabonomics and targeted UPLC-MS approach

The activity of Cytochrome P450 3A4 (CYP3A4) enzyme is associated with many adverse or poor therapeutic responses to drugs. We used (1)H NMR-based metabonomics to identify a metabolic signature associated with variation in induced CYP3A4 activity. A total of 301 female twins, aged 45--84, participated in this study. Each volunteer was administered a potent inducer of CYP3A4 (St. John's Wort) for 14 days and the activity of CYP3A4 was quantified through the metabolism of the exogenously administered probe drug quinine sulfate (300 mg). Pre- and postintervention fasting urine samples were used to obtain metabolite profiles, using (1)H NMR spectroscopy, and were analyzed using UPLC--MS to obtain a marker for CYP3A4 induction, via the ratio of 3-hydroxyquinine to quinine (3OH-Q:Q). Multiple linear regression was used to build a predictive model for 3OH-Q:Q values based on the preintervention metabolite profiles. A combination of seven metabolites and seven covariates showed a strong (r = 0.62) relationship with log(3OH-Q:Q). This regression model demonstrated significant (p < 0.00001) predictive ability when applied to an independent validation set. Our results highlight the promise of metabonomics for predicting CYP3A4-mediated drug response.