基于稳定同位素的代谢组学临床研究进展

基于稳定同位素示踪的代谢组学不仅能检测疾病发生发展及治疗过程中相关代谢物的变化,还可以对生物体系的代谢物进行定量分析并描述代谢特性。目前,稳定同位素示踪的代谢组学技术可在受试者体内直接追踪到代谢网络的单个原子,更有利于发现与疾病病因和诊断及药物疗效评估相关的生物标志物。现就稳定同位素示踪代谢组学在临床研究中的应用做简要概述,以期为将来更好地开展代谢组学在临床方面的研究提供重要依据。     

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。     

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。     

代谢组学技术及其在毒理学研究领域中的应用

代谢组学是近几年发展起来的对某一生物或细胞所有低分子量代谢产物进行定性和定量分析的一门新学科,其研究对象主要是生物体液,研究手段主要是核磁共振和质谱。简要综述了代谢组学的概念、代谢组学在毒理学研究领域中的应用、当前代谢组学研究中存在的问题及今后的发展趋势,并探讨了代谢组学在研究毒物作用机制、药物的临床前安全性评价、确定毒物作用靶器官及器官特异性新的生物标志物中的实际应用。     

生物组学在污染环境微生物修复研究中的应用

随着分子生物学、生物信息学和各种理化检测技术的发展,特别是人类基因组计划成功实施以来,基因组学研究取得了重大突破与进展。而包括转录组学、蛋白组学和代谢组学在内的后基因组学也相继出现,并被广泛应用在环境微生物学的各个研究领域。本文主要概述了当前基因组学、转录组学、蛋白质组学和代谢组学在污染环境生物修复研究中的最新研究进展,分析比较了各组学的优势与不足,同时结合本课题组的主要研究方向探讨了各生物组学在赤潮生消过程和有机污染物降解机理等研究中的应用。     

代谢组学在呼吸系统疾病研究中的应用进展

代谢组学是继基因组学、蛋白质组学、转录组学之后发展起来的一门新兴学科,是系统生物学的重要组成部分。随内外界条件的改变,生物样本(生物体、细胞和组织等)中内源性小分子代谢物的组成、含量也发生相应的变化,通过各种高通量的分析手段对生物样本进行分析,从而找出与疾病相关的生物标志物,为疾病相关机制研究提供了新的途径。疾病诊断相关生物标志物的研究是代谢组学主要应用领域之一。呼吸系统疾病是一直困扰人们健康的常见疾病,我们对近年来代谢组学在几类常见的呼吸系统疾病诊断或鉴别方面取得的进展进行简要综述。     

代谢组学在乳酸菌研究中的应用

代谢组学是系统生物学的重要分支,因其高效、高通量等特点而广泛应用于食品科学、药物学等研究领域。本文概述了代谢组学的分离和检测技术,综述了代谢组学在乳酸菌鉴定、发酵调控、肠道菌群研究等方面中的应用,对代谢组学在乳酸菌研究中潜在的问题和未来发展趋势进行了讨论,期望为代谢组学在食品工业微生物中的应用提供参考。     

代谢组学与营养学研究

代谢组学(metabonomics)是近几年来基于核磁共振(nuclear magnetic resonance,NMR)、质谱(mass spectrometry,MS)和高效液相色谱(HPLC)等发展起来的一种新的"组学"技术,是通过分析生物体液及组织中所有小分子物质来研究有机体内物质代谢规律和健康状况的一门学科。代谢组学在功能基因组学、病理生理学、药理毒理学和营养学等方面有着广泛的应用前景。本文综述了代谢组学的研究进展和在营养学方面的应用。     

代谢组学在一氧化碳中毒研究的应用和展望

一氧化碳中毒是常见的以中枢神经系统损害为主的全身性疾病。一氧化碳作为一个脂溶性分子,进入细胞内造成组织缺氧。一氧化碳是否可以诱导产生其他特定的生物学效应,还需要我们去研究。代谢组学是继基因组学、转录组学、蛋白质组学后的又一新兴学科,在肿瘤、糖尿病、冠心病、肥胖症、脑卒中等多种临床疾病的相关研究中显示出巨大的潜力。将代谢组学技术应用到一氧化碳中毒研究中,可以加深对一氧化碳中毒发病机制的认识,丰富早期诊断方法,改善治疗效果的监测手段。但代谢组学技术在一氧化碳中毒研究中的应用仍是凤毛麟角,我们在此对代谢组学在一氧化碳中毒研究中应用及前景作一展望。     

脂质组学分析方法进展及其在癌症研究中的应用

脂质占人体内源性代谢物的一半以上,种类繁多,结构复杂,因而具有多种生物功能,与多种生命活动密切相关。脂质组学是代谢组学分支的新兴学科,它可以通过比较不同生理状态下脂质含量的变化,寻找代谢通路中关键的脂质生物标志物,最终揭示脂质在各种生命活动中的作用机制。随着质谱技术的进步,脂质组学在疾病脂类生物标志物的识别、疾病诊断、药物作用机制的研究等方面已展现出广泛的应用前景。本文主要就脂质组学近几年的分析方法进展及其在癌症中的最新应用进行了综述。     

Trend analysis of metabonomics and systematic review of metabonomics-derived cancer marker metabolites

In this paper, trend analyses were performed to compare the different ‘omic’ technologies and the different analytical platforms and biological matrices exploited in metabonomic studies. While common and differential marker metabolites had been identified using various analytical platforms in metabonomics, little research was directed to review and consolidate marker metabolites in each disease state. A systematic review of metabonomics-derived marker metabolites in different cancers was performed to understand the significance of metabonomics in elucidating cancer biochemistry. The biological pathways associated with the cancer marker metabolites were further correlated to the pathology of cancers. Our trend analyses indicated that metabonomic publications increased exponentially in recent years, with nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography/mass spectrometry (LC/MS) being the most popular analytical platforms while blood, urine and tissue are the most commonly profiled biological matrices. Based on the consolidated cancer marker metabolites, it is reinforced that different cancers possess some common and yet distinct metabolic phenotypes, exhibiting numerous perturbed biochemical pathways related to their needs to support cell growth and proliferation and facilitate cancer cell survival.     

Metabonomics Study of the Therapeutic Mechanism of Gynostemma pentaphyllum and Atorvastatin for Hyperlipidemia in Rats

Gynostemma pentaphyllum (GP) is widely used for the treatment of diseases such as hyperlipidemia, fatty liver and obesity in China, and atorvastatin is broadly used as an anti-hyperlipidemia drug. This research focuses on the plasma and liver metabolites in the following four groups of rats: control, a hyperlipidemia model, a hyperlipidemia model treated with GP and a hyperlipidemia model treated with atorvastatin. Using ¹H-NMR-based metabonomics, we elucidated the therapeutic mechanisms of GP and atorvastatin. Orthogonal Partial Least Squares-Discriminant analysis (OPLS-DA) plotting of the metabolic state and analysis of potential biomarkers in the plasma and liver correlated well with the results of biochemical assays. GP can effectively affect lipid metabolism, and it exerts its anti-hyperlipidemia effect by elevating the level of phosphatidylcholine and decreasing the level of trimethylamine N-oxide (TMAO). In contrast, atorvastatin affects hyperlipidemia mainly during lipid metabolism and protein metabolism in vivo.     

Chronic myeloid leukemia patients sensitive and resistant to imatinib treatment show different metabolic responses

The BCR-ABL tyrosine kinase inhibitor imatinib is highly effective for chronic myeloid leukemia (CML). However, some patients gradually develop resistance to imatinib, resulting in therapeutic failure. Metabonomic and genomic profiling of patients' responses to drug interventions can provide novel information about the in vivo metabolism of low-molecular-weight compounds and extend our insight into the mechanism of drug resistance. Based on a multi-platform of high-throughput metabonomics, SNP array analysis, karyotype and mutation, the metabolic phenotypes and genomic polymorphisms of CML patients and their diverse responses to imatinib were characterized. The untreated CML patients (UCML) showed different metabolic patterns from those of healthy controls, and the discriminatory metabolites suggested the perturbed metabolism of the urea cycle, tricarboxylic acid cycle, lipid metabolism, and amino acid turnover in UCML. After imatinib treatment, patients sensitive to imatinib (SCML) and patients resistant to imatinib (RCML) had similar metabolic phenotypes to those of healthy controls and UCML, respectively. SCML showed a significant metabolic response to imatinib, with marked restoration of the perturbed metabolism. Most of the metabolites characterizing CML were adjusted to normal levels, including the intermediates of the urea cycle and tricarboxylic acid cycle (TCA). In contrast, neither cytogenetic nor metabonomic analysis indicated any positive response to imatinib in RCML. We report for the first time the associated genetic and metabonomic responses of CML patients to imatinib and show that the perturbed in vivo metabolism of UCML is independent of imatinib treatment in resistant patients. Thus, metabonomics can potentially characterize patients' sensitivity or resistance to drug intervention.     

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.     

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.     

Within-day reproducibility of an HPLC-MS-based method for metabonomic analysis: application to human urine

Self-evidently, research in areas supporting "systems biology" such as genomics, proteomics, and metabonomics are critically dependent on the generation of sound analytical data. Metabolic phenotyping using LC-MS-based methods is currently at a relatively early stage of development, and approaches to ensure data quality are still developing. As part of studies on the application of LC-MS in metabonomics, the within-day reproducibility of LC-MS, with both positive and negative electrospray ionization (ESI), has been investigated using a standard "quality control" (QC) sample. The results showed that the first few injections on the system were not representative, and should be discarded, and that reproducibility was critically dependent on signal intensity. On the basis of these findings, an analytical protocol for the metabonomic analysis of human urine has been developed with proposed acceptance criteria based on a step-by-step assessment of the data. Short-term sample stability for human urine was also assessed. Samples were stable for at least 20 h at 4 degrees C in the autosampler while queuing for analysis. Samples stored at either -20 or -80 degrees C for up to 1 month were indistinguishable on subsequent LC-MS analysis. Overall, by careful monitoring of the QC data, it is possible to demonstrate that the "within-day" reproducibility of LC-MS is sufficient to ensure data quality in global metabolic profiling applications.     

血液中氧化三甲胺与相关疾病及检测方法

随着代谢组学技术的不断发展及科学研究的不断深入,生物标志物用于预判或诊断机体疾病的价值被更多的科学家所重视。最近几年,大量文献报道了氧化三甲胺与机体疾病之间的相关性。本文通过对近几年血氧化三甲胺与各种疾病之间的关系研究进展及测量方法(如液质联用法、酶联免疫法、磁共振法等)的系统综述,以期为今后的研究提供便捷的参考途径。     

Serum metabolic profiling of abnormal savda by liquid chromatography/mass spectrometry

Abnormal savda is a special symptom in Uigur medicine. The understanding of its metabolic origins is of great importance for the subsequent treatment. Here, a metabonomic study of this symptom was carried out using LC-MS based human serum metabolic profiling. Orthogonal signal correction partial least-squares discriminant analysis (OSC-PLS-DA) was used for the classification and prediction of abnormal savda. Potential biomarkers from metabonomics were also identified for a metabolic understanding of abnormal savda. As a result, our OSC-PLS-DA model had a satisfactory ability for separation and prediction of abnormal savda. The potential biomarkers including bilirubin, bile acids, tryptophan, phenylalanine and lyso-phosphatidylcholines indicated that abnormal savda could be related to some abnormal metabolisms within the body, including energy metabolism, absorption of nutrition, metabolism of lecithin on cell membrane, etc. To the best of our knowledge, this is the first study of abnormal savda based on serum metabolic profiling. The LC/MS-based metabonomic platform could be a powerful tool for the classification of symptoms and for the development of this traditional medicine into an evidence-based one.