Metabolomics and its application to studying metal toxicity

Here we explain the omics approach of metabolomics and how it can be applied to study a physiological response to toxic metal exposure. This review aims to educate the metallomics field to the tool of metabolomics. Metabolomics is becoming an increasingly used tool to compare natural and challenged states of various organisms, from disease states in humans to toxin exposure to environmental systems. This approach is key to understanding and identifying the cellular or biochemical targets of metals and the underlying physiological response. Metabolomics steps are described and overviews of its application to metal toxicity to organisms are given. As this approach is very new there are yet only a small number of total studies and therefore only a brief overview of some metal metabolomics studies is described. A frank critical evaluation of the approach is given to provide newcomers to the method a clear idea of the challenges and the rewards of applying metabolomics to their research.     

代谢组学及其在微藻研究中的应用

代谢组学以完整的生物体为研究对象,运用合适的分析测试手段检测靶向或非靶向代谢物,结合统计模型进行分析解释。随着微藻研究的深入,微藻与代谢组学结合探究分子作用机理的研究日益增多。本文总结代谢组学的发展概况、研究流程及常用分析技术特点和代谢组学在微藻领域的研究进展,展望代谢组学在微藻研究的应用前景与发展趋势,并提出实际应用中所面临的困难与挑战。     

果树代谢组学研究进展

果树代谢组学是继基因组学、蛋白质组学之后又一新兴的组学技术,主要是从代谢水平研究果树整体或局部代谢物变化差异,帮助发现新功能基因和了解代谢网络。目前果树代谢组学研究刚刚起步,相关研究相对较少,该文介绍了果树代谢组学的主要研究内容与方法以及在果树上的相关应用。     

Standard reporting requirements for biological samples in metabolomics experiments: microbial and in vitro biology experiments

With the increasing use of metabolomics as a means to study a large number of different biological research questions, there is a need for a minimal set of reporting standards that allow the scientific community to evaluate, understand, repeat, compare and re-investigate metabolomics studies. Here we propose, a first draft of minimal requirements to effectively describe the biological context of metabolomics studies that involve microbial or in vitro biological subjects. This recommendation has been produced by the microbiology and in vitro biology working subgroup of the Metabolomics Standards Initiative in collaboration with the yeast systems biology network as part of a wider standardization initiative led by the Metabolomics Society. Microbial and in vitro biology metabolomics is defined by this sub-working group as studies with any cell or organism that require a defined external medium to facilitate growth and propagation. Both a minimal set and a best practice set of reporting standards for metabolomics experiments have been defined. The minimal set of reporting standards for microbial or in vitro biology metabolomics experiments includes those factors that are specific for metabolomics experiments and that critically determine the outcome of the experiments. The best practice set of reporting standards contains both the factors that are specific for metabolomics experiments and general aspects that critically determine the outcome of any microbial or in vitro biological experiment.     

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。     

Patterns of time since last meal revealed by sparse PCA in an observational LC–MS based metabolomics study

In metabolomics studies, liquid chromatography mass spectrometry (LC–MS) provides comprehensive information on biological samples. However, extraction of few relevant metabolites from this large and complex data is cumbersome. To resolve this issue, we have employed sparse principal component analysis (SPCA) to capture the underlying patterns and select relevant metabolites from LC–MS plasma profiles. The study involves a small pilot cohort with 270 subjects where each subject’s time since last meal (TSLM) has been recorded prior to plasma sampling. Our results have demonstrated that both PCA and SPCA can capture the TSLM patterns. Nevertheless, SPCA provides more easily interpretable loadings in terms of selection of relevant metabolites, which are identified as amino acids and lyso-lipids. This study demonstrates the utility of SPCA as a pattern recognition and variable selection tool in metabolomics. Furthermore, amino acids and lyso-lipids are determined as dominating compounds in response to TSLM.     

Environmental metabolomics: a critical review and future perspectives

Environmental metabolomics is the application of metabolomics to characterise the interactions of organisms with their environment. This approach has many advantages for studying organism–environment interactions and for assessing organism function and health at the molecular level. As such, metabolomics is finding an increasing number of applications in the environmental sciences, ranging from understanding organismal responses to abiotic pressures, to investigating the responses of organisms to other biota. These interactions can be studied from individuals to populations, which can be related to the traditional fields of ecophysiology and ecology, and from instantaneous effects to those over evolutionary time scales, the latter enabling studies of genetic adaptation. This review provides a comprehensive and current overview of environmental metabolomics research. We begin with an overview of metabolomic studies into the effects of abiotic pressures on organisms. In the field of ecophysiology, studies on the metabolic responses to temperature, water, food availability, light and circadian rhythms, atmospheric gases and season are reviewed. A section on ecotoxicogenomics discusses research in aquatic and terrestrial ecotoxicology, assessing organismal responses to anthropogenic pollutants in both the laboratory and field. We then discuss environmental metabolomic studies of diseases and biotic–biotic interactions, in particular herbivory. Finally, we critically evaluate the contribution that metabolomics has made to the environmental sciences, and highlight and discuss recommendations to advance our understanding of the environment, ecology and evolution using a metabolomics approach.     

Large-Scale metabolomics: Predicting biological age using 10,133 routine untargeted LC–MS measurements

Untargeted metabolomics is the study of all detectable small molecules, and in geroscience, metabolomics has shown great potential to describe the biological age—a complex trait impacted by many factors. Unfortunately, the sample sizes are often insufficient to achieve sufficient power and minimize potential biases caused by, for example, demographic factors. In this study, we present the analysis of biological age in ~10,000 toxicologic routine blood measurements. The untargeted screening samples obtained from ultra-high pressure liquid chromatography-quadruple time of flight mass spectrometry (UHPLC- QTOF) cover + 300 batches and + 30 months, lack pooled quality controls, lack controlled sample collection, and has previously only been used in small-scale studies. To overcome experimental effects, we developed and tested a custom neural network model and compared it with existing prediction methods. Overall, the neural network was able to predict the chronological age with an rmse of 5.88 years (r² = 0.63) improving upon the 6.15 years achieved by existing normalization methods. We used the feature importance algorithm, Shapley Additive exPlanations (SHAP), to identify compounds related to the biological age. Most importantly, the model returned known aging markers such as kynurenine, indole-3-aldehyde, and acylcarnitines along with a potential novel aging marker, cyclo (leu-pro). Our results validate the association of tryptophan and acylcarnitine metabolism to aging in a highly uncontrolled large-s cale sample. Also, we have shown that by using robust computational methods it is possible to deploy large LC-MS datasets for metabolomics studies to reduce the risk of bias and empower aging studies.     

Basics of mass spectrometry based metabolomics

The emerging field of metabolomics, aiming to characterize small molecule metabolites present in biological systems, promises immense potential for different areas such as medicine, environmental sciences, agronomy, etc. The purpose of this article is to guide the reader through the history of the field, then through the main steps of the metabolomics workflow, from study design to structure elucidation, and help the reader to understand the key phases of a metabolomics investigation and the rationale underlying the protocols and techniques used. This article is not intended to give standard operating procedures as several papers related to this topic were already provided, but is designed as a tutorial aiming to help beginners understand the concept and challenges of MS‐based metabolomics. A real case example is taken from the literature to illustrate the application of the metabolomics approach in the field of doping analysis. Challenges and limitations of the approach are then discussed along with future directions in research to cope with these limitations. This tutorial is part of the International Proteomics Tutorial Programme (IPTP18).     

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.     

Ethical priority of the most actionable system of biomolecules: the metabolome

The metabolome is a system of small biomolecules (metabolites) and a direct result of human bioculture. Consequently, metabolomics is well poised to impact anthropological and biomedical research for the foreseeable future. Overall, we provide a perspective on the ethical, legal, and social implications (ELSI) of metabolomics, which we argue are often more alarming than those of genomics. Given the current mechanisms to fund research, ELSI beyond human DNA is stifled and in need of considerable attention.     

Metabolomics – an overview. From basic principles to potential biomarkers (part 2)

The metabolome, which represents the complete set of molecules (metabolites) of a biological sample (cell, tissue, organ, organism), is the final downstream product of the metabolic cell process that involves the genome and exogenous sources. The metabolome is characterized by a large number of small molecules with a huge diversity of chemical structures and abundances. Exploring the metabolome requires complementary analytical platforms to reach its extensive coverage. The metabolome is continually evolving, reflecting the continuous flux of metabolic and signaling pathways. Metabolomic research aims to study the biochemical processes by detecting and quantifying metabolites to obtain a metabolic picture able to give a functional readout of the physiological state. Recent advances in mass spectrometry (one of the mostly used technologies for metabolomics studies) have given the opportunity to determine the spatial distribution of metabolites in tissues. In a two-part article, we describe the usual metabolomics technologies, workflows and strategies leading to the implementation of new clinical biomarkers. In this second part, we first develop the steps of a metabolomic analysis from sample collection to biomarker validation. Then with two examples, autism spectrum disorders and Alzheimer's disease, we illustrate the contributions of metabolomics to clinical practice. Finally, we discuss the complementarity of in vivo (positron emission tomography) and in vitro (metabolomics) molecular explorations for biomarker research.     

Multivariate classification analysis of metabolomic data for candidate biomarker discovery in type 2 diabetes mellitus

Recent advances in genomics, metabolomics and proteomics have made it possible to interrogate disease pathophysiology and drug response on a systems level. The analysis and interpretation of the complex data obtained using these techniques is potentially fertile but equally challenging. We conducted a small clinical trial to explore the application of metabolomics data in candidate biomarker discovery. Specifically, serum and urine samples from patients with type 2 diabetes mellitus (T2DM) were profiled on metabolomics platforms before and after 8 weeks of treatment with one of three commonly used oral antidiabetic agents, the sulfonyurea glyburide, the biguanide metformin, or the thiazolidinedione rosiglitazone. Multivariate classification techniques were used to detect serum or urine analytes, obtained at baseline (pre-treatment) that could predict a significant treatment response after 8 weeks. Using this approach, we identified three analytes, measured at baseline, that were associated with response to a thiazolidinedione after 8 weeks of treatment. Although larger and longer-term studies are required to validate any of the candidate biomarkers, pharmacometabolomic profiling, in combination with multivariate classification, is worthy of further exploration as an adjunct to clinical decision making regarding treatment selection and for patient stratification within clinical trials. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

功能代谢组学技术在微生物研究中的应用

功能代谢组学是以代谢组学技术发现关键代谢物为基础,结合体内体外实验和分子生物学等技术手段,研究差异代谢物及相关蛋白、酶和基因的功能,从而揭示生物体内在的分子调控机制。功能代谢组学技术具有精准识别关键调控代谢物及其相关基因或酶的特性,近年来在微生物相关疾病的防控和工业化生产等方面受到了广泛的关注。本文介绍了功能代谢组学技术的分析流程、相关研究方法与平台及其在微生物研究方面的应用,其中重点阐述了真核、原核以及病毒微生物的代谢特性、调控靶点及相关防控策略等。最后,提出功能代谢组学研究在未来面临的问题与挑战,为后续功能代谢组学的研究与发展提供新的思路。     

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。     

Minimum reporting standards for plant biology context information in metabolomic studies

Plant metabolomics has matured over the past 8 years. Plant biologists routinely use comprehensive analyses of plant metabolites to discover new responses to genetic or environmental perturbation, or to validate initial hypotheses on the function and in vivo action of gene products. The wealth of scientific findings has increasingly provoked interest to share and review raw or processed data from plant metabolomics reports. We here suggest a minimum of parameters to be reported in order to define details of experimental study designs in plant metabolomics studies.     

Challenges and Opportunities in Cancer Metabolomics

Challenges in metabolomics for a given spectrum of disease are more or less comparable, ranging from the accurate measurement of metabolite abundance, compound annotation, identification of unknown constituents, and interpretation of untargeted and analysis of high throughput targeted metabolomics data leading to the identification of biomarkers. However, metabolomics approaches in cancer studies specifically suffer from several additional challenges and require robust ways to sample the cells and tissues in order to tackle the constantly evolving cancer landscape. These constraints include, but are not limited to, discriminating the signals from given cell types and those that are cancer specific, discerning signals that are systemic and confounded, cell culture‐based challenges associated with cell line identities and media standardizations, the need to look beyond Warburg effects, citrate cycle, lactate metabolism, and identifying and developing technologies to precisely and effectively sample and profile the heterogeneous tumor environment. This review article discusses some of the current and pertinent hurdles in cancer metabolomics studies. In addition, it addresses some of the most recent and exciting developments in metabolomics that may address some of these issues. The aim of this article is to update the oncometabolomics research community about the challenges and potential solutions to these issues.     

Metabolomics Analysis of Metabolic Effects of Nicotinamide Phosphoribosyltransferase (NAMPT) Inhibition on Human Cancer Cells

Nicotinamide phosphoribosyltransferase (NAMPT) plays an important role in cellular bioenergetics. It is responsible for converting nicotinamide to nicotinamide adenine dinucleotide, an essential molecule in cellular metabolism. NAMPT has been extensively studied over the past decade due to its role as a key regulator of nicotinamide adenine dinucleotide–consuming enzymes. NAMPT is also known as a potential target for therapeutic intervention due to its involvement in disease. In the current study, we used a global mass spectrometry–based metabolomic approach to investigate the effects of FK866, a small molecule inhibitor of NAMPT currently in clinical trials, on metabolic perturbations in human cancer cells. We treated A2780 (ovarian cancer) and HCT-116 (colorectal cancer) cell lines with FK866 in the presence and absence of nicotinic acid. Significant changes were observed in the amino acids metabolism and the purine and pyrimidine metabolism. We also observed metabolic alterations in glycolysis, the citric acid cycle (TCA), and the pentose phosphate pathway. To expand the range of the detected polar metabolites and improve data confidence, we applied a global metabolomics profiling platform by using both non-targeted and targeted hydrophilic (HILIC)-LC-MS and GC-MS analysis. We used Ingenuity Knowledge Base to facilitate the projection of metabolomics data onto metabolic pathways. Several metabolic pathways showed differential responses to FK866 based on several matches to the list of annotated metabolites. This study suggests that global metabolomics can be a useful tool in pharmacological studies of the mechanism of action of drugs at a cellular level.     

New insights into cardiovascular and lipid metabolomics

Metabolomics is the study of metabolite profiles in biological samples, particularly urine, saliva, blood plasma and fat biopsies. The metabolome is now considered by some to be the most predictive phenotype: consequently, the comprehensive and quantitative study of metabolites is a desirable tool for diagnosing disease, identifying new therapeutic targets and enabling appropriate treatments. A wealth of information about metabolites has been accumulated with global profiling tools and several candidate technologies for metabolomic studies are now available. Many high-throughput metabolomics methodologies are currently under development and have yet to be applied in clinical practice on a routine basis. In the cardiovascular field, few recent metabolomic studies have been reported so far. This minireview provides an updated overview of alternative technical approaches for metabolomics studies and reviews initial applications of metabolomics that relate to both cardiovascular disease and lipid metabolism research.