Review on microbial metabolomics of probiotics and pathogens: Methodologies and applications

In recent years, microbial metabolomics, a new field that has attracted wide attention, provides a map of metabolic pathways and clarifies the interaction mechanism between microorganisms and hosts. Many microorganisms are found in the human intestine, oral cavity, vagina, etc. Probiotics could maintain the good health of the host, while pathogens and an imbalance of bacterial flora lead to a series of diseases of the body and mind. Metabolomics is a science for qualitative and quantitative analysis of all metabolites in an organism or biological system, which could provide key information to understand the related metabolic pathways and associated changes. This approach analyzes the final products of cellular regulatory processes, the level of which can be regarded as the ultimate response of the biological system to genetic or environmental changes. Microbial metabolomics has been widely used in different research fields, such as microbial phenotypic classification, mutant screening, metabolic pathways, microbial metabolic engineering, fermentation engineering monitoring and optimization, microbial environmental pollution, and so on. However, there are only a few reviews on microbial metabolomics of probiotics and pathogens. This review summarizes the main methodologies, including sample preparation, identification of metabolites, data processing, and analysis. Recent applications in microbial metabolomics of probiotics and pathogens are also described. This paper first summarized the research progress and application of microbial metabolomics from two aspects: probiotics and pathogenic bacteria. Probiotics and pathogenic bacteria do not exist independently most of the time; hence, these were reviewed in the research field of coexistence of probiotics and pathogenic bacteria, which was subdivided into important microbial research fields closely related to human health, including the human gut, oral cavity, food, and nutrition-related microorganisms. Then, the main problems and trends associated with microbial metabolomics are discussed.     

Mass spectrometry-based metabolomics

This review presents an overview of the dynamically developing field of mass spectrometry-based metabolomics. Metabolomics aims at the comprehensive and quantitative analysis of wide arrays of metabolites in biological samples. These numerous analytes have very diverse physico-chemical properties and occur at different abundance levels. Consequently, comprehensive metabolomics investigations are primarily a challenge for analytical chemistry and specifically mass spectrometry has vast potential as a tool for this type of investigation. Metabolomics require special approaches for sample preparation, separation, and mass spectrometric analysis. Current examples of those approaches are described in this review. It primarily focuses on metabolic fingerprinting, a technique that analyzes all detectable analytes in a given sample with subsequent classification of samples and identification of differentially expressed metabolites, which define the sample classes. To perform this complex task, data analysis tools, metabolite libraries, and databases are required. Therefore, recent advances in metabolomics bioinformatics are also discussed.     

Mass spectrometry‐based metabolomics towards understanding of gene functions with a diversity of biological contexts

Currently, mass spectrometry‐based metabolomics studies extend beyond conventional chemical categorization and metabolic phenotype analysis to understanding gene function in various biological contexts (e.g., mammalian, plant, and microbial). These novel utilities have led to many innovative discoveries in the following areas: disease pathogenesis, therapeutic pathway or target identification, the biochemistry of animal and plant physiological and pathological activities in response to diverse stimuli, and molecular signatures of host–pathogen interactions during microbial infection. In this review, we critically evaluate the representative applications of mass spectrometry‐based metabolomics to better understand gene function in diverse biological contexts, with special emphasis on working principles, study protocols, and possible future development of this technique. Collectively, this review raises awareness within the biomedical community of the scientific value and applicability of mass spectrometry‐based metabolomics strategies to better understand gene function, thus advancing this application's utility in a broad range of biological fields. © 2012 Wiley Periodicals, Inc., Mass Spec Rev 32:118–128, 2013     

基于质谱技术的代谢组学在体外药物肝毒性评价中的研究进展

药物肝毒性是药物安全性评价的重要内容之一，研发早期对药物及其代谢产物潜在的肝毒性进行准确预测和评价，可以提高药物研发的成功率。将代谢组学技术与体外细胞模型相结合，以细胞代谢表型的变化为指标直接反映药物的毒性效应及毒性机制，能够改善临床前药物肝毒性的预测准确性，在药物肝毒性筛选研究中极具应用价值和发展潜力。本文综述了目前肝毒性研究中的细胞模型与培养方法，介绍了三维细胞培养模型在体外研究中的优势，并总结了基于质谱技术的代谢组学研究在体外细胞模型中的分析策略及其在药物肝毒性评价中的应用，其中基于质谱成像技术的空间分辨代谢组学方法在体外细胞模型研究中具有独特优势，有望发展成为体外肝毒性研究的有力工具。     

Eight key rules for successful data-dependent acquisition in mass spectrometry-based metabolomics

In recent years, metabolomics has emerged as a pivotal approach for the holistic analysis of metabolites in biological systems. The rapid progress in analytical equipment, coupled to the rise of powerful data processing tools, now provides unprecedented opportunities to deepen our understanding of the relationships between biochemical processes and physiological or phenotypic conditions in living organisms. However, to obtain unbiased data coverage of hundreds or thousands of metabolites remains a challenging task. Among the panel of available analytical methods, targeted and untargeted mass spectrometry approaches are among the most commonly used. While targeted metabolomics usually relies on multiple-reaction monitoring acquisition, untargeted metabolomics use either data-independent acquisition (DIA) or data-dependent acquisition (DDA) methods. Unlike DIA, DDA offers the possibility to get real, selective MS/MS spectra and thus to improve metabolite assignment when performing untargeted metabolomics. Yet, DDA settings are more complex to establish than DIA settings, and as a result, DDA is more prone to errors in method development and application. Here, we present a tutorial which provides guidelines on how to optimize the technical parameters essential for proper DDA experiments in metabolomics applications. This tutorial is organized as a series of rules describing the impact of the different parameters on data acquisition and data quality. It is primarily intended to metabolomics users and mass spectrometrists that wish to acquire both theoretical background and practical tips for developing effective DDA methods.     

基于高分辨质谱的代谢组学分析技术研究进展

代谢组学研究的目标是对生物体系中所有内源小分子代谢物进行全面的定性和定量表征.由于代谢物组成复杂、种类繁多、理化性质各异、且浓度差异大,给分析工作带来了极大的挑战.高分辨质谱因具有高灵敏度、高质量分辨率和质量精度、宽动态范围等优势,已成为代谢组学研究的主流分析工具.本文综述了近5年来基于高分辨质谱的代谢组学分析技术和方...     

Mass spectrometry‐based holistic analytical approaches for metabolite profiling in systems biology studies

Metabonomics and metabolomics represent one of the three major platforms in systems biology. To perform metabolomics it is necessary to generate comprehensive “global” metabolite profiles from complex samples, for example, biological fluids or tissue extracts. Analytical technologies based on mass spectrometry (MS), and in particular on liquid chromatography–MS (LC–MS), have become a major tool providing a significant source of global metabolite profiling data. In the present review we describe and compare the utility of the different analytical strategies and technologies used for MS‐based metabolomics with a particular focus on LC–MS. Both the advantages offered by the technology and also the challenges and limitations that need to be addressed for the successful application of LC–MS in metabolite analysis are described. Data treatment and approaches resulting in the detection and identification of biomarkers are considered. Special emphasis is given to validation issues, instrument stability, and QA/quality control (QC) procedures. © 2011 Wiley Periodicals, Inc., Mass Spec Rev 30:884–906, 2011     

Protein‐based stable isotope probing (protein‐SIP) in functional metaproteomics

The community phenotype as the sum of molecular functions of organisms living in consortia strongly depends on interactions within these communities. Therefore, the analyses of the most significant molecules in terms of the phenotype, the proteins, have to be performed on samples without disrupting the meta‐species environment. Due to the increasing genomic information, proteins provide insights into a potential molecular function and the phylogenetic structure of the community. Unfortunately, the lists of identified proteins are often based first on the technical capacity of the used methods or instruments, and second on the interpretation of them by the assignment of molecular functions to proteins in databases. Especially in non‐model organisms the functions of many proteins are often not known and an increasing number of studies indicate a significant amount of uncertainty. To decrease the dependency on assumptions and to enable functional insights by metaproteome approaches, the metabolic labeling from an isotopically labeled substrate can be used. Since the metabolites deriving from the substrate are very rarely species‐specific, the incorporation of the stable isotope into proteins can be used as a surrogate marker for metabolic activity. The degree of incorporation can be determined accurately on the peptide level by mass spectrometry; additionally, the peptide sequence provides information on the metabolic active species. Thereby, protein‐stable isotope probing (protein‐SIP) adds functional information to metaproteome approaches. The classical metaproteome approaches will be reviewed with an emphasis on their attempts towards functional interpretation. The gain from functional insights into metaproteomics by using metabolic labeling of stable isotopes of carbon, nitrogen, and sulfur is reviewed with a focus on the techniques of measurement, calculation of incorporation and data processing. © 2012 Wiley Periodicals, Inc. Mass Spec Rev 31:683–697, 2012     

基于离子淌度质谱的代谢物碰撞截面积测量方法和数据库研究进展

代谢组学旨在全面系统地分析复杂生物样本中的代谢物。近年来,离子淌度质谱（IM-MS）技术快速发展,为代谢组学分析提供了强大的技术支撑。离子淌度质谱根据代谢物的化学结构进行气相分离,其衍生的碰撞截面积（CCS）可作为一种新的物理化学性质,辅助用于鉴定已知和未知代谢物的化学结构。碰撞截面积在代谢组学中的应用需要确保对其准确测量,同时需要构建高覆盖、高准确的碰撞截面积数据库。本文旨在介绍常见的不同类型商业化离子淌度质谱及其对小分子代谢物碰撞截面积测量和校正的原理,归纳目前可用于代谢组学应用的碰撞截面积数据库,并展望碰撞截面积在代谢组学中的应用。     

Mass spectrometric based approaches in urine metabolomics and biomarker discovery

Urine metabolomics has recently emerged as a prominent field for the discovery of non‐invasive biomarkers that can detect subtle metabolic discrepancies in response to a specific disease or therapeutic intervention. Urine, compared to other biofluids, is characterized by its ease of collection, richness in metabolites and its ability to reflect imbalances of all biochemical pathways within the body. Following urine collection for metabolomic analysis, samples must be immediately frozen to quench any biogenic and/or non‐biogenic chemical reactions. According to the aim of the experiment; sample preparation can vary from simple procedures such as filtration to more specific extraction protocols such as liquid‐liquid extraction. Due to the lack of comprehensive studies on urine metabolome stability, higher storage temperatures (i.e. 4°C) and repetitive freeze‐thaw cycles should be avoided. To date, among all analytical techniques, mass spectrometry (MS) provides the best sensitivity, selectivity and identification capabilities to analyze the majority of the metabolite composition in the urine. Combined with the qualitative and quantitative capabilities of MS, and due to the continuous improvements in its related technologies (i.e. ultra high‐performance liquid chromatography [UPLC] and hydrophilic interaction liquid chromatography [HILIC]), liquid chromatography (LC)‐MS is unequivocally the most utilized and the most informative analytical tool employed in urine metabolomics. Furthermore, differential isotope tagging techniques has provided a solution to ion suppression from urine matrix thus allowing for quantitative analysis. In addition to LC‐MS, other MS‐based technologies have been utilized in urine metabolomics. These include direct injection (infusion)‐MS, capillary electrophoresis‐MS and gas chromatography‐MS. In this article, the current progresses of different MS‐based techniques in exploring the urine metabolome as well as the recent findings in providing potentially diagnostic urinary biomarkers are discussed. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:115–134, 2017.     

MS-based analytical methodologies to characterize genetically modified crops

The development of genetically modified crops has had a great impact on the agriculture and food industries. However, the development of any genetically modified organism (GMO) requires the application of analytical procedures to confirm the equivalence of the GMO compared to its isogenic non-transgenic counterpart. Moreover, the use of GMOs in foods and agriculture faces numerous criticisms from consumers and ecological organizations that have led some countries to regulate their production, growth, and commercialization. These regulations have brought about the need of new and more powerful analytical methods to face the complexity of this topic. In this regard, MS-based technologies are increasingly used for GMOs analysis to provide very useful information on GMO composition (e.g., metabolites, proteins). This review focuses on the MS-based analytical methodologies used to characterize genetically modified crops (also called transgenic crops). First, an overview on genetically modified crops development is provided, together with the main difficulties of their analysis. Next, the different MS-based analytical approaches applied to characterize GM crops are critically discussed, and include "-omics" approaches and target-based approaches. These methodologies allow the study of intended and unintended effects that result from the genetic transformation. This information is considered to be essential to corroborate (or not) the equivalence of the GM crop with its isogenic non-transgenic counterpart.     

The role of mass spectrometry in plant systems biology

Large-scale analyses of proteins and metabolites are intimately bound to advancements in MS technologies. The aim of these non-targeted "omic" technologies is to extend our understanding beyond the analysis of only parts of the system. Here, metabolomics and proteomics emerged in parallel with the development of novel mass analyzers and hyphenated techniques such as gas chromatography coupled to time-of-flight mass spectrometry (GC-TOF-MS) and multidimensional liquid chromatography coupled to mass spectrometry (LC-MS). The analysis of (i) proteins (ii) phosphoproteins, and (iii) metabolites is discussed in the context of plant physiology and environment and with a focus on novel method developments. Recently published studies measuring dynamic (quantitative) behavior at these levels are summarized; for these works, the completely sequenced plants Arabidopsis thaliana and Oryza sativa (rice) have been the primary models of choice. Particular emphasis is given to key physiological processes such as metabolism, development, stress, and defense. Moreover, attempts to combine spatial, tissue-specific resolution with systematic profiling are described. Finally, we summarize the initial steps to characterize the molecular plant phenotype as a corollary of environment and genotype.     

Development of LC/MS Techniques for Comprehensive Metabolome Analysis

Metabolomics is a rapidly evolving field for studying biological systems and discovering potential disease biomarkers. For any metabolomics application, metabolome analysis with adequate sensitivity and specificity is essential in defining the metabolome. Ideally, all metabolites present in a biological system are qualitatively and quantitatively profiled. Unfortunately, due to technical limitations, only a fraction of metabolites are currently analyzed by using techniques such as NMR and mass spectrometry (MS). Due to limited metabolome coverage, many important metabolome networks and some subdue changes in the metabolome may not be revealed with current techniques. In this presentation, several technical issues related to the development of LC/MS for enabling metabolome analysis will be discussed. Because of great diversity of chemical and physical properties of metabolites, we have been developing an isotope labeling LC/MS workflow with a goal of improving the metabolome coverage in analyzing biological samples such as human biofluids and tissue samples. Several labeling chemistries will be described to provide isotope tags to the metabolites for sensitive detection and accurate quantification. LC methods including multi-dimensional separation to separate the labeled metabolites with high efficiency will be discussed. New protocols for MS analysis, metabolite identification and quantitative data processing will be presented.     

Differential metabolome landscape of <i>Kadsura coccinea</i> fruit tissues and potential valorization of the peel and seed tissues

Kadsura coccinea (Lem.) is a woody wine plant with a peculiar fruit enriched in important health-promoting compounds. The non-editable part of the fruit, i.e., the seed and peel, represents more than 60% of the fruit and is considered a biowaste. This significantly restricts the development of the K. coccinea fruit industry. Clarifying the metabolic components of the different fruit parts can help to improve the utilization rate and valorization of K. coccinea. Herein, we evaluated K. coccinea fruit peel, pulp, and seed using widely-targeted metabolomics and quantified a set of 736 bioactive compounds from 11 major metabolite classes. The most prominent metabolite classes included lipids, amino acids, flavonoids, and lignans. Furthermore, our results emphasized a significant accumulation of flavonoids in pulp tissues, while alkaloids and lignans were abundant in peel and seed tissues, respectively. A total of 183 metabolites were differentially accumulated among the three tissues. Procyanidin C2, rutinoside, 2-hydroxyoleanolic acid, 5-hydroxymethyluracil, nootkatol, isoquercitrin, isohyperoside, quercetin-7-O-glucoside, hyperin, and rutin showed elevated accumulation in the peel. In the seed, kadsuralignan G, kadcoccilactone A, kadsuralignan H, lysoPE 20:5, iso-schisandrin ethyl alcohol, and kadangustin were significantly enriched. Our results highlight the diverse metabolome composition of K. coccinea fruit parts, which can be further exploited for its valorization in various industries.     

NMR代谢组学技术在环境污染评价中的应用

随着环境污染日益严重,对环境污染评价的研究亦愈发深入。基于核磁共振(Nuclear Magnetic Resonance,NMR)代谢组学是近年发展起来的一种新型环境污染评价方法,它是以核磁共振为技术手段,从生物角度研究生物体暴露在环境污染物下,生物体内源性代谢产物谱的变化,以期预警环境污染的程度。本文将综述基于核磁共振的代谢组学在环境污染评价上的原理、研究思路、以及国内外研究新进展。     

The role of mass spectrometry‐based metabolomics in medical countermeasures against radiation

Radiation metabolomics can be defined as the global profiling of biological fluids to uncover latent, endogenous small molecules whose concentrations change in a dose–response manner following exposure to ionizing radiation. In response to the potential threat of nuclear or radiological terrorism, the Center for High‐Throughput Minimally Invasive Radiation Biodosimetry was established to develop field‐deployable biodosimeters based, in part, on rapid analysis by mass spectrometry of readily and easily obtainable biofluids. In this review, we briefly summarize radiation biology and key events related to actual and potential nuclear disasters, discuss the important contributions the field of mass spectrometry has made to the field of radiation metabolomics, and summarize current discovery efforts to use mass spectrometry‐based metabolomics to identify dose‐responsive urinary constituents, and ultimately to build and deploy a noninvasive high‐throughput biodosimeter. © 2009 Wiley Periodicals, Inc. Mass Spec Rev 29:503‐521, 2010