植物代谢组学的研究方法及其应用

代谢组是指某一生物或细胞在一特定生理时期内所有的低分子量代谢产物.植物代谢组学是指对植物抽提物中代谢组进行高通量、无偏差全面分析的技术.近年来,植物代谢组学研究取得了很大进展.本文介绍了其含义、历史沿革及研究方法,并用典型实例阐释了它的应用方向.     

植物应答非生物胁迫的代谢组学研究进展

代谢组学技术是研究植物代谢的理想平台, 通过现代检测分析技术对胁迫环境下植物中代谢产物进行定性和定量分析, 可以监测其随时间变化的规律。而各种组学平台包括基因组学、转录组学及代谢组学的整合, 更是一个强有力的工具箱, 将所获得的不同组学的信息联系起来, 有利于从整体研究生物系统对基因或环境变化的响应, 如可判断代谢物的变化是从哪一个层面开始发生的, 帮助人们揭开复杂的植物胁迫应答机制。该文对近期代谢组学技术及其与蛋白质组学、基因组学技术相结合探索植物应答非生物胁迫的研究进行了综述。代谢组学的应用, 拓展了对植物耐受非生物胁迫分子机制的认识, 开展更多这方面的研究, 再通过植物代谢组学、转录组学、蛋白质组学和基因组学整合, 有助于从整体水平上把握植物胁迫应答机制。     

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。     

植物对非生物逆境响应的转录调控和代谢谱分析的研究进展

非生物逆境严重影响植物的生长发育,植物响应非生物逆境是通过复杂的转录调控网络和代谢网络实现的。植物转录组学和代谢组学的技术方法有助于研究植物对非生物逆境的应答机制。本文对植物非生物逆境响应中的转录调控和代谢谱分析的研究进展进行了综述。     

基于代谢组学技术的植物抗病相关代谢物研究进展

植物受到病原真菌侵染时往往通过调节体内代谢物的产生来增强自身抗性,代谢组学技术是研究植物抗病相关代谢物的重要工具。指认植物抗病相关代谢物不仅利于深入探讨其抗病机制,还可与其他组学技术结合,辅助抗性品种鉴定和抗病品种培育。该研究对近年来国内外有关基于代谢组学技术指认植物抗病相关代谢物的流程、已发现的抗病相关代谢物及其作用机制的研究进展进行综述,并探讨了目前应用代谢组学技术研究植物抗病相关代谢物过程中面临的挑战。     

空间分辨代谢组学进展和挑战

空间分辨代谢组学即整合质谱成像和代谢组学技术,对动/植物组织和细胞中内/外源性代谢物的种类、含量和差异性空间分布进行精准测定。质谱成像技术因其具有无标记、非特异、高灵敏度、高化学覆盖、元素/分子同时检测等优势,被广泛应用于动/植物组织中各类代谢物、多肽和蛋白的时空分布研究。首先介绍了代谢组学和质谱成像技术的研究现状,然后重点综述了空间分辨代谢组学在动物组织、植物组织和单细胞水平上的前沿应用。最后展望了空间分辨代谢组学技术的现有瓶颈和未来发展方向。空间分辨代谢组学是继代谢组学之后又一门新兴的分子成像组学技术,能够无标记、可视化检测动物组织中外源性药物的吸收、分布、代谢和排泄,以及植物组织中多种代谢产物的生物合成、转运途径和积累规律。该技术将推动靶向药物发现、病理机制解析和动植物生长发育密切关联的空间代谢网络调控等前沿应用研究。     

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。     

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。     

植物响应盐胁迫组学研究进展

盐胁迫对植物生长的影响主要表现在离子毒害、渗透胁迫以及次级氧化胁迫等,植物遭受盐胁迫时迅速启动相关基因,进行转录调控,进而合成相应蛋白质来控制代谢物合成和离子转运以调节渗透平衡。随着现代分子生物学迅速发展,对植物耐盐机理研究也深入到了转录组、蛋白质组、代谢组及离子组等水平,"组学"研究为耐盐基因鉴定及标志性代谢物的挖掘等提供了有力手段。该文对近年来国内外有关转录组学、蛋白质组学、代谢组学、离子组学的主要研究方法及在盐胁迫中的应用研究进展进行综述,以揭示植物耐盐机理,为优良耐盐碱植物的筛选与培育提供支持。     

生态代谢组学研究进展

代谢组学指某一生物系统中产生的或已存在的代谢物组的研究,以质谱和核磁共振技术为分析平台,以信息建模与系统整合为目标。随着代谢组学中的研究方法与技术成为生态学研究的有力工具,生态代谢组学概念应运而生,即研究某一个生物体对环境变化的代谢物组水平的响应。理清代谢组学与生态代谢组学学科发展的脉络,综述代谢组学研究中的常用技术及其优势与局限性,论述代谢组学技术在生态学研究中的应用现状,展望代谢组学技术与其他系统生物学组学技术的结合在生态学中的应用前景,提出生态代谢组学研究者未来要完成的任务和面对的挑战。     

Recent advances of metabolomics in plant biotechnology

Biotechnology, including genetic modification, is a very important approach to regulate the production of particular metabolites in plants to improve their adaptation to environmental stress, to improve food quality, and to increase crop yield. Unfortunately, these approaches do not necessarily lead to the expected results due to the highly complex mechanisms underlying metabolic regulation in plants. In this context, metabolomics plays a key role in plant molecular biotechnology, where plant cells are modified by the expression of engineered genes, because we can obtain information on the metabolic status of cells via a snapshot of their metabolome. Although metabolome analysis could be used to evaluate the effect of foreign genes and understand the metabolic state of cells, there is no single analytical method for metabolomics because of the wide range of chemicals synthesized in plants. Here, we describe the basic analytical advancements in plant metabolomics and bioinformatics and the application of metabolomics to the biological study of plants.     

Mealtime,Temporal, and Daily Variability of the Human Urinary and Plasma Metabolomes in a Tightly Controlled Environment

While metabolomics has tremendous potential for diagnostic biomarker and therapeutic target discovery, its utility may be diminished by the variability that occurs due to environmental exposures including diet and the influences of the human circadian rhythm. For successful translation of metabolomics findings into the clinical setting, it is necessary to exhaustively define the sources of metabolome variation. To address these issues and to measure the variability of urinary and plasma metabolomes throughout the day, we have undertaken a comprehensive inpatient study in which we have performed non-targeted metabolomics analysis of blood and urine in 26 volunteers (13 healthy subjects with no known disease and 13 healthy subjects with autosomal dominant polycystic kidney disease not taking medication). These individuals were evaluated in a clinical research facility on two separate occasions, over three days, while on a standardized, weight-based diet. Subjects provided pre- and post-prandial blood and urine samples at the same time of day, and all samples were analyzed by “fast lane” LC-MS-based global metabolomics. The largest source of variability in blood and urine metabolomes was attributable to technical issues such as sample preparation and analysis, and less variability was due to biological variables, meals, and time of day. Higher metabolome variability was observed after the morning as compared to the evening meal, yet day-to-day variability was minimal and urine metabolome variability was greater than that of blood. Thus we suggest that blood and urine are suitable biofluids for metabolomics studies, though nontargeted mass spectrometry alone may not offer sufficient precision to reveal subtle changes in the metabolome. Additional targeted analyses may be needed to support the data from nontargeted mass spectrometric analyses. In light of these findings, future metabolomics studies should consider these sources of variability to allow for appropriate metabolomics testing and reliable clinical translation of metabolomics data.     

Metabolic Profiling in Banana Pseudo-Stem Reveals a Diverse Set of Bioactive Compounds with Potential Nutritional and Industrial Applications

Banana (Musa spp.) is an ancient and popular fruit plant with highly nutritious fruit. The pseudo-stem of banana represents on average 75% of the total dry mass but its valorization as a nutritional and industrial by-product is limited. Recent advances in metabolomics have paved the way to understand and evaluate the presence of diverse sets of metabolites in different plant parts. This study aimed at exploring the diversity of primary and secondary metabolites in the banana pseudo-stem. Hereby, we identified and quantified 373 metabolites from a diverse range of classes including, alkaloids, flavonoids, lipids, phenolic acids, amino acids and its derivatives, nucleotide and its derivatives, organic acids, lignans and coumarins, tannins, and terpene using the widely-targeted metabolomics approach. Banana pseudo-stem is enriched in metabolites for utilization in the food industry (L-lysine and L-tryptophan, L-glutamic acid, Phenylalanine, Palmitoleic acid, α-Linolenic acid, and Lauric acid, and Adenine) and pharmaceutical industry (Guanosine and Cimidahurinine, Bergapten, Coumarins, Procyanidin A2, Procyanidin B1, Procyanidin B3, Procyanidin B2, and Procyanidin B4, Asiatic acid). The metabolome of banana pseudo-stem with integration across multiomics data may provide the opportunity to exploit the rich metabolome of banana pseudo-stem for industrial and nutritional applications.     

Mass spectrometry strategies in metabolomics

MS has evolved as a critical component in metabolomics, which seeks to answer biological questions through large-scale qualitative and quantitative analyses of the metabolome. MS-based metabolomics techniques offer an excellent combination of sensitivity and selectivity, and they have become an indispensable platform in biology and metabolomics. In this minireview, various MS technologies used in metabolomics are briefly discussed, and future needs are suggested.