Metabolomics Standards Workshop and the development of international standards for reporting metabolomics experimental results

Informatics standards and controlled vocabularies are essentialfor allowing information technology to help exchange, manage,interpret and compare large data collections. In a rapidly evolvingfield, the challenge is to work out how best to describe, butnot prescribe, the use of these technologies and methods. AMetabolomics Standards Workshop was held by the US NationalInstitutes of Health (NIH) to bring together multiple ongoingstandards efforts in metabolomics with the NIH research community.The goals were to discuss metabolomics workflows (methods, technologiesand data treatments) and the needs, challenges and potentialapproaches to developing a Metabolomics Standards Initiativethat will help facilitate this rapidly growing field which hasbeen a focus of the NIH roadmap effort. This report highlightsspecific aspects of what was presented and discussed at the1st and 2nd August 2005 Metabolomics Standards Workshop.      

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。     

Metabolomics and its role in understanding cellular responses in plants

A natural shift is taking place in the approaches being adopted by plant scientists in response to the accessibility of systems-based technology platforms. Metabolomics is one such field, which involves a comprehensive non-biased analysis of metabolites in a given cell at a specific time. This review briefly introduces the emerging field and a range of analytical techniques that are most useful in metabolomics when combined with computational approaches in data analyses. Using cases from Arabidopsis and other selected plant systems, this review highlights how information can be integrated from metabolomics and other functional genomics platforms to obtain a global picture of plant cellular responses. We discuss how metabolomics is enabling large-scale and parallel interrogation of cell states under different stages of development and defined environmental conditions to uncover novel interactions among various pathways. Finally, we discuss selected applications of metabolomics. This special review article is dedicated to the commemoration of the retirement of Dr. Oluf L. Gamborg after 25 years of service as Founding Managing Editor of Plant Cell Reports. RB and KN have contributed equally to this review.     

Metabolomics meets lipidomics: Assessing the small molecule component of metabolism

Metabolomics, including lipidomics, is emerging as a quantitative biology approach for the assessment of energy flow through metabolism and information flow through metabolic signaling; thus, providing novel insights into metabolism and its regulation, in health, healthy ageing and disease. In this forward-looking review we provide an overview on the origins of metabolomics, on its role in this postgenomic era of biochemistry and its application to investigate metabolite role and (bio)activity, from model systems to human population studies. We present the challenges inherent to this analytical science, and approaches and modes of analysis that are used to resolve, characterize and measure the infinite chemical diversity contained in the metabolome (including lipidome) of complex biological matrices. In the current outbreak of metabolic diseases such as cardiometabolic disorders, cancer and neurodegenerative diseases, metabolomics appears to be ideally situated for the investigation of disease pathophysiology from a metabolite perspective.     

代谢组学及其在环境毒理学中的应用

代谢组学作为系统生物学的一部分,因其具有分析速度快的特点,被广泛用于生物医学等方面的研究。目前代谢组学在环境毒理学方面的研究主要针对单一污染物,但也需要考虑到被污染地的复杂情况。通过介绍代谢组学及其发展历程,总结了目前主流代谢组学技术的各自特点,讨论了代谢组学在环境重金属、有机污染物和抗生素中的毒性评估以及环境胁迫耐受性中的评价等方面内容,综述了其在环境毒理学中的应用,并指出其应用不足,旨在为代谢组学应用于环境毒理学的研究提供参考。     

Metabolomics: building on a century of biochemistry to guide human health

Medical diagnosis and treatment efficacy will improve significantly when a more personalized system for health assessment is implemented. This system will require diagnostics that provide sufficiently detailed information about the metabolic status of individuals such that assay results will be able to guide food, drug and lifestyle choices to maintain or improve distinct aspects of health without compromising others. Achieving this goal will use the new science of metabolomics – comprehensive metabolic profiling of individuals linked to the biological understanding of human integrative metabolism. Candidate technologies to accomplish this goal are largely available, yet they have not been brought into practice for this purpose. Metabolomic technologies must be sufficiently rapid, accurate and affordable to be routinely accessible to both healthy and acutely ill individuals. The use of metabolomic data to predict the health trajectories of individuals will require bioinformatic tools and quantitative reference databases. These databases containing metabolite profiles from the population must be built, stored and indexed according to metabolic and health status. Building and annotating these databases with the knowledge to predict how a specific metabolic pattern from an individual can be adjusted with diet, drugs and lifestyle to improve health represents a logical application of the biochemistry knowledge that the life sciences have produced over the past 100 years.     

Comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry (GC × GC-TOF) for high resolution metabolomics: biomarker discovery on spleen tissue extracts of obese NZO compared to lean C57BL/6 mice

Comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry (GC × GC-TOF) was applied for the analysis of complex metabolite profiles from mouse spleen. The resulting two-dimensional chromatograms proved that mass spectral quality and sensitivity were largely improved by the enhanced resolution and zone compression, which are features of GC × GC operation, when compared to classical one-dimensional GC-TOF methods. The improved peak capacity of GC × GC allowed for peaks to be detected that could previously not be separated in one-dimensional GC. A measure of the combined power of chromatographic and mass spectral deconvolution resolution is called “analytical purity”, with higher values indicating less pure peaks. GC × GC-TOF lead to the detection of 1200 compounds with purity better than 0.2, compared to 500 compounds with purity up to 2.5 in one-dimensional GC-TOF. The compounds identified include many of the compounds previously reported in NMR studies and other methods on mammalian tissues. Spleen samples of several obese NZO mice and lean C57BL/6 control strains were analyzed in order to demonstrate the applicability of GC × GC-TOF for biomarker identification.This revised version was published online in June 2005. The previous version did not contain colour images.     

代谢异速生长理论及其在微生物生态学领域的应用

新陈代谢是生物的基本生理过程,影响生物在不同环境中参与物质循环和能量转化的过程.代谢速率作为生物体重要的生命过程指标,几乎影响所有的生物活性速率,且在很多研究中均表现出异速生长现象.所谓代谢异速是指生物体代谢速率与其个体大小(或质量)之间存在的幂函数关系.代谢异速生长理论的提出,从机制模型角度解释了代谢异速关系这一普遍存在的生命现象.该理论利用分形几何学及流体动力学等原理,从生物能量学角度阐释了异速生长规律的机理,证实了3/4权度指数的存在;但同时有研究表明,权度指数因环境因素等影响处于2/3-1范围之间而非定值.随着研究工作的深入,代谢异速生长理论研究从起初的宏观动植物领域拓展到了微生物领域,在研究微生物的代谢异速生长理论时,可将微生物的可操作分类单元(Operational taxonomic unit,OTU)或具有特定功能的功能群视为一个微生物个体,基于其遗传多样性和功能多样性特征进行表征,以便于将微生物群落多样性与其生态功能性联系起来,使该理论在微生物生态学领域得到有效的补充和完善.尽管细菌具有独特的生物学特性,但与宏观生物系统中观测到的现象表现出明显的一致性.有研究表明,3个农田土壤细菌基于遗传多样性的OTU数的平均周转率分别为0.71、0.80和0.84,介于2/3与1之间,可能与生物代谢异速指数有一定关联,为微生物代谢异速指数的研究提出了一个参考解决方案.鉴于微生物个体特征和生物学特性,在分析代谢速率与个体大小关系中,从微生物单位个体的定义、个体大小表征到计量单位的统一,仍需更多的理论支持.分析了代谢异速生长理论在微生物与生态系统功能关系研究中的可能应用,延伸了该理论的应用范围,并对尚待加强的研究问题进行了评述和展望.     

代谢组及其在真菌研究中的应用

代谢组学是利用现代分析化学手段对一定条件下生物体内小分子代谢产物（初级和次级代谢产物）定性及定量,从而揭示生命现象及其内在规律的学科。相对于基因组、转录组和蛋白质组,代谢组是一定条件下生物学过程完成后的最终代谢产物的集合,因而是各种组学研究中最接近表型的一种组学,可以直接动态地反映出细胞的生理生化过程,从而有效地检测和发现特定的生化途径,准确地解释生理或者病理现象。代谢组学作为系统生物学中基因组学、转录组学以及蛋白质组学三大组学的延伸和补充,是目前的研究热点之一。目前代谢组学在真菌领域的研究得到日益重视和发展。本文首先从历史发展和技术路线简述了代谢组学的发展历程和常见的代谢组学研究方法。接着从真菌的分类鉴定、生物膜研究、代谢途径、代谢工程、天然产物发现与植物互作这6个方面介绍了代谢组学在真菌研究领域的应用。     

Metabolomics data reveal a crucial role of cytosolic glutamine synthetase 1;1 in coordinating metabolic balance in rice

Rice plants grown in paddy fields preferentially use ammonium as a source of inorganic nitrogen. Glutamine synthetase (GS) catalyses the conversion of ammonium to glutamine. Of the three genes encoding cytosolic GS in rice, OsGS1;1 is critical for normal growth and grain filling. However, the basis of its physiological function that may alter the rate of nitrogen assimilation and carbon metabolism within the context of metabolic networks remains unclear. To address this issue, we carried out quantitative comparative analyses between the metabolite profiles of a rice mutant lacking OsGS1;1 and its background wild type (WT). The mutant plants exhibited severe retardation of shoot growth in the presence of ammonium compared with the WT. Overaccumulation of free ammonium in the leaf sheath and roots of the mutant indicated the importance of OsGS1;1 for ammonium assimilation in both organs. The metabolite profiles of the mutant line revealed: (i) an imbalance in levels of sugars, amino acids and metabolites in the tricarboxylic acid cycle, and (ii) overaccumulation of secondary metabolites, particularly in the roots under a continuous supply of ammonium. Metabolite-to-metabolite correlation analysis revealed the presence of mutant-specific networks between tryptamine and other primary metabolites in the roots. These results demonstrated a crucial function of OsGS1;1 in coordinating the global metabolic network in rice plants grown using ammonium as the nitrogen source.     

Information and its use by animals in evolutionary ecology

Information is a crucial currency for animals from both a behavioural and evolutionary perspective. Adaptive behaviour relies upon accurate estimation of relevant ecological parameters; the better informed an individual, the better it can develop and adjust its behaviour to meet the demands of a variable world. Here, we focus on the burgeoning interest in the impact of ecological uncertainty on adaptation, and the means by which it can be reduced by gathering information, from both 'passive' and 'responsive' sources. Our overview demonstrates the value of adopting an explicitly informational approach, and highlights the components that one needs to develop useful approaches to studying information use by animals. We propose a quantitative framework, based on statistical decision theory, for analysing animal information use in evolutionary ecology. Our purpose is to promote an integrative approach to studying information use by animals, which is itself integral to adaptive animal behaviour and organismal biology.     

磷脂脂肪酸谱图分析方法及其在微生物生态学领域的应用

应用磷脂脂肪酸谱图分析技术对微生物群落进行定量分布,克服了传统的微生物培养方法和显微技术的局限性。介绍了磷脂脂肪酸谱图分析方法及其在微生物生态学领域中的应用,包括对微生物群落的生物量、群落结构、营养状况和新陈代谢活动等方面的研究。     

Metabolomics assisted metabolic network modeling and network wide analysis of metabolites in microbiology

Metabolomics is the science of qualitatively and quantitatively analyzing low molecular weight metabolites occur in a given biological system. It provides valuable information to elucidate the functional roles and relations of different metabolites in a metabolic pathway. In recent years, a large amount of research on microbial metabolomics has been conducted. It has become a useful tool for achieving highly efficient synthesis of target metabolites. At the same time, many studies have been conducted over the years in order to integrate metabolomics data into metabolic network modeling, which has yielded many exciting results. Additionally, metabolomics also shows great advantages in analyzing the relationship of metabolites network wide. Integrating metabolomics data into metabolic network construction and applying it in network wide analysis of cell metabolism would further improve our ability to control cellular metabolism and optimize the design of cell factories for the overproduction of valuable biochemicals. This review will examine recent progress in the application of metabolomics approaches in metabolic network modeling and network wide analysis of microbial cell metabolism.     

植物代谢组学研究进展

代谢组学是继基因组学、转录组学和蛋白质组学之后发展起来的一门学科,通过对细胞内的基因表达最终代谢产物的定性和定量分析以及定义细胞或器官的生化表现类型来解释功能基因的表达过程。文中就代谢组学的发展历史、主要研究内容、技术特点、数据处理过程及在植物领域中的应用的最新进展几方面进行阐述,以供读者参考。     

Mass spectrometry methods in metabolomics

The review deals with metabolomics, a new and rapidly growing area directed to the comprehensive analysis of metabolites of biological objects. Metabolites are characterized by various physical and chemical properties, traditionally studied by methods of analytical chemistry focused on certain groups of chemical substances. However, current progress in mass spectrometry has led to formation of rather unified methods, such as metabolic fingerprinting and metabolomic profiling, which allow defining thousands of metabolites in one biological sample and therefore draw “a modern portrait of metabolomics.” This review describes basic characteristics of these methods, ways of metabolite separation, and analysis of metabolites by mass spectrometry. The examples shown in this review, allow to estimate these methods and to compare their advantages and disadvantages. Besides that, we consider the methods, which are of the most frequent use in metabolomics; these include the methods for data processing and the required resources, such as software for mass spectra processing and metabolite search database. In the conclusion, general suggestions for successful metabolomic experiments are given.     

代谢组学在肿瘤药物靶点筛选中的应用进展

肿瘤是一种多因素参与造成机体各系统功能平衡紊乱的代谢性疾病,代谢重编程是恶性肿瘤的重要特征之一.研究"代谢指纹图谱"的代谢组学,通过揭示肿瘤或药物引起的宿主内源性代谢物的变化,为肿瘤药物靶点的筛选提供了可能.但目前对代谢组在肿瘤药物靶点筛选中的整体性综述并不多见,因此,本文在介绍了代谢组学筛选肿瘤药物靶点的流程的基础上...