Towards quantitative metabolomics of mammalian cells: Development of a metabolite extraction protocol

Metabolomics aims to quantify all metabolites within an organism, thereby providing valuable insight into the metabolism of cells. To study intracellular metabolites, they are first extracted from the cells. The ideal extraction procedure should immediately quench metabolism and quantitatively extract all metabolites, a significant challenge given the rapid turnover and physicochemical diversity of intracellular metabolites. We have evaluated several quenching and extraction solutions for their suitability for mammalian cells grown in suspension. Quenching with 60% methanol (buffered or unbuffered) resulted in leakage of intracellular metabolites from the cells. In contrast, quenching with cold isotonic saline (0.9% [w/v] NaCl, 0.5 °C) did not damage cells and effectively halted conversion of ATP to ADP and AMP, indicative of metabolic arrest. Of the 12 different extraction methods tested, cold extraction in 50% aqueous acetonitrile was superior to other methods. The recovery of a mixture of standards was excellent, and the concentration of extracted intracellular metabolites was higher than for the other methods tested. The final protocol is easy to implement and can be used to study the intracellular metabolomes of mammalian cells.     

High-throughput tissue extraction protocol for NMR- and MS-based metabolomics

In metabolomics, tissues typically are extracted by grinding in liquid nitrogen followed by the stepwise addition of solvents. This is time-consuming and difficult to automate, and the multiple steps can introduce variability. Here we optimize tissue extraction methods compatible with high-throughput, reproducible nuclear magnetic resonance (NMR) spectroscopy- and mass spectrometry (MS)-based metabolomics. Previously, we concluded that methanol/chloroform/water extraction is preferable for metabolomics, and we further optimized this here using fish liver and an automated Precellys 24 bead-based homogenizer, allowing rapid extraction of multiple samples without carryover. We compared three solvent addition strategies: stepwise, two-step, and all solvents simultaneously. Then we evaluated strategies for improved partitioning of metabolites between solvent phases, including the addition of extra water and different partition times. Polar extracts were analyzed by NMR and principal components analysis, and the two-step approach was preferable based on lipid partitioning, reproducibility, yield, and throughput. Longer partitioning or extra water increased yield and decreased lipids in the polar phase but caused metabolic decay in these extracts. Overall, we conclude that the two-step method with extra water provides good quality data but that the two-step method with 10 min partitioning provides a more accurate snapshot of the metabolome. Finally, when validating the two-step strategy using NMR and MS metabolomics, we showed that technical variability was considerably smaller than biological variability.     

Microbial metabolomics

Microbial metabolomics constitutes an integrated component of systems biology. By studying the complete set of metabolites within a microorganism and monitoring the global outcome of interactions between its development processes and the environment, metabolomics can potentially provide a more accurate snap shot of the actual physiological state of the cell. Recent advancement of technologies and post-genomic developments enable the study and analysis of metabolome. This unique contribution resulted in many scientific disciplines incorporating metabolomics as one of their "omics" platforms. This review focuses on metabolomics in microorganisms and utilizes selected topics to illustrate its impact on the understanding of systems microbiology.     

HORA suite: a database and software for human metabolomics

HORA suite (Human blOod Range vAlidator) consists of a Java application used to validate the metabolomic analysis of human blood against a database that stores the normal plasma and serum range concentrations of metabolites. The goal of HORA is to find the metabolites that are outside the normal range and to show those not present in the list provided by the user, for different thresholds of concentration. Moreover it supplies a graphical interface to manage the data. The software can also be used to compare different metabolomic techniques. HORA is open-source software and it can be accessed at . A separate file contains instructions for the installation and a brief tutorial.     

Sampling methods for NMR-based metabolomics of Staphylococcus aureus

To select an appropriate sampling method for comparison of metabolite profiles between planktonic and biofilm Staphylococcus aureus using NMR techniques, we evaluated three methods: quenching-centrifugation (QC), filtration-quenching (FQ) and filtration-quenching-lyophilization (FQL). We found differences in metabolite loss, yield, reproducibility and metabolite profile. QC caused severe metabolite leakage and possible decomposition of nucleotides. FQ achieved high yields and reproducibility, although it had the disadvantages of long filtration and rinse times before quenching. FQL resulted in a loss of a few metabolites and a lower yield due to lyophilization. Although the biomarkers discovered by each method were nearly the same and seemed insensitive to technical variances, we conclude that FQ is the most appropriate sampling method because of its high yield and reproducibility.     

Analytical metabolomics: nutritional opportunities for personalized health

Nutrition is the cornerstone of health; survival depends on acquiring essential nutrients, and dietary components can both prevent and promote disease. Metabolomics, the study of all small molecule metabolic products in a system, has been shown to provide a detailed snapshot of the body's processes at any particular point in time, opening up the possibility of monitoring health and disease, prevention and treatment. Metabolomics has the potential to fundamentally change clinical chemistry and, by extension, the fields of nutrition, toxicology and medicine. Technological advances, combined with new knowledge of the human genome and gut microbiome, have made and will continue to make possible earlier, more accurate, less invasive diagnoses, all while enhancing our understanding of the root causes of disease and leading to a generation of dietary recommendations that enable optimal health. This article reviews the recent contributions of metabolomics to the fields of nutrition, toxicology and medicine. It is expected that these fields will eventually blend together through development of new technologies in metabolomics and genomics into a new area of clinical chemistry: personalized medicine.     

Extraction of adenine nucleotides from cultured endothelial cells

The goal of this work was to find a method suitable for the extraction of adenine nucleotides from cultured vascular endothelial cells. Extraction of cell monolayers with 80% methanol in water yielded extracts with a higher content of ATP than did extraction of cells with perchloric acid, trichloroacetic acid, or boiling water. The optimal extraction solution was 80% methanol with 0.5 mM ethylene glycol bis(beta-aminoethyl ether) N,N'-tetraacetic acid (EGTA) or EDTA, heated to 70 degrees C immediately before use. Extraction of nucleotides by this solution was rapid and the recovery of exogenous ATP added during the extraction process was generally greater than 90%. An aqueous methanol or ethanol solution may be applicable for the extraction of nucleotides and other metabolites from cultured animal cells, dispersed cells, and frozen, powdered tissues.     

Hyperpolarized NMR metabolomics

Hyperpolarized NMR is a promising approach to address the sensitivity limits of conventional NMR metabolomics approaches, which currently fails to detect minute metabolite concentrations in biological samples. This review describes how tremendous signal enhancement offered by dissolution-dynamic nuclear polarization and parahydrogen-based techniques can be fully exploited for molecular omics sciences. Recent developments, including the combination of hyperpolarization techniques with fast multi-dimensional NMR implementation and quantitative workflows are described, and a comprehensive comparison of existing hyperpolarization techniques is proposed. High-throughput, sensitivity, resolution and other relevant challenges that should be tackled for a general application of hyperpolarized NMR in metabolomics are discussed.     

乳酸菌代谢组学研究进展

代谢组学作为系统生物学的重要分支,近年来在微生物研究领域受到广泛关注,并取得了重要进展。目前乳酸菌代谢组学正日益成为研究的热点,就乳酸菌代谢组学研究中有关样品的制备、分析鉴定和数据分析等涉及的主要方法进行概述,并介绍一些乳酸菌代谢组学应用的典型实例,对乳酸菌代谢组学研究中潜在的问题和未来发展趋势进行讨论。     

Integration of wavelet transform with PCA and ANN for metabolomics data-mining

PCA (principal components analysis) and ANN (artificial neural network) are two broadly used pattern recognition methods in metabolomics data-mining. Yet their limitations sometimes are great obstacles for researchers. In this paper the wavelet transform (WT) method was used to integrate with PCA and ANN to improve their performance in manipulating metabolomics data. A dataset was decomposed by wavelets and then reconstructed. The "hard thresholding" algorithm was used, through which the detail information was discarded, and the entire "metabolomics image" reconstructed on the significant information. It was supposed that the most relevant information was captured after this process. It was found that, thanks to its ability in denoising data, the WT method could significantly improve the performance of the non-linear essence-extracting method ANN in classifying samples; further integration of WT with PCA showed that WT could greatly enhance the ability of PCA in distinguishing one group of samples from another and also its ability in identifying potential biomarkers. The results highlighted WT as a promising resolution in bridging the gap between huge bytes of data and the instructive biological information.     

一种棉花线粒体DNA的提取方法

线粒体是重要的细胞器,它有自身的基因组。其基因组DNA与细胞核基因组DNA相比,含量较低。棉花当中富含棉酚、丹宁等物质,这对提取DNA有很大的影响。因此我们根据棉花自身的特点,找到了一种提取棉花线粒体DNA经济有效的方法,其质量可以满足限制性酶切、PCR、分子杂交等实验的要求。     

1H NMR metabolomics analysis of glioblastoma subtypes: correlation between metabolomics and gene expression characteristics

Glioblastoma multiforme (GBM) is the most common form of malignant glioma, characterized by unpredictable clinical behaviors that suggest distinct molecular subtypes. With the tumor metabolic phenotype being one of the hallmarks of cancer, we have set upon to investigate whether GBMs show differences in their metabolic profiles. (1)H NMR analysis was performed on metabolite extracts from a selection of nine glioblastoma cell lines. Analysis was performed directly on spectral data and on relative concentrations of metabolites obtained from spectra using a multivariate regression method developed in this work. Both qualitative and quantitative sample clustering have shown that cell lines can be divided into four groups for which the most significantly different metabolites have been determined. Analysis shows that some of the major cancer metabolic markers (such as choline, lactate, and glutamine) have significantly dissimilar concentrations in different GBM groups. The obtained lists of metabolic markers for subgroups were correlated with gene expression data for the same cell lines. Metabolic analysis generally agrees with gene expression measurements, and in several cases, we have shown in detail how the metabolic results can be correlated with the analysis of gene expression. Combined gene expression and metabolomics analysis have shown differential expression of transporters of metabolic markers in these cells as well as some of the major metabolic pathways leading to accumulation of metabolites. Obtained lists of marker metabolites can be leveraged for subtype determination in glioblastomas.     

Nanostructure Initiator Mass Spectrometry for tissue imaging in metabolomics: future prospects and perspectives

Mass spectrometry-based metabolomics provides a new approach to interrogate mechanistic biochemistry related to natural processes such as health and disease. Physiological and pathological conditions, however, are characterized not only by the identities and concentrations of metabolites present, but also by the location of metabolites within a tissue. Unfortunately, most relevant MS platforms in metabolomics can only measure samples in solution, therefore metabolites are typically extracted by tissue homogenization. Recent developments of imaging-MS technologies, however, have allowed particular metabolites to be spatially localized within biological tissues. In this context, Nanostructure-Initiator Mass Spectrometry (NIMS), a matrix-free technique for surface-based analysis, has proven an alternative approach for tissue imaging of metabolites. Here we review the basic principles of NIMS for tissue imaging and show applications that can complement LC/MS and GC/MS-based metabolomic studies investigating the mechanisms of fundamental biological processes. In addition, the new surface modifications and nanostructured materials herein presented demonstrate the versatility of NIMS surface to expand the range of detectable metabolites.     

常见食源性致病菌代谢组学研究进展

食源性致病菌是一类以食品为传播媒介,可引起食物中毒的致病性微生物,是目前食源性疾病的主要诱因。食源性致病菌代谢组学通过研究致病菌代谢小分子物质产生的规律性和特征性,寻找新的检测靶标和建立基于代谢组学方法的食源性致病菌鉴别技术。随着目前代谢组学研究技术逐渐成熟和微生物挥发性代谢产物数据库的建立,食源性致病菌挥发性代谢产物分析已被建议作为临床和食品中致病菌鉴别的替代方法。本文综述了目前常见食源性致病菌代谢组学主要研究技术及其在临床和食品检测中的研究进展,以期为进一步建立食源性致病菌代谢产物数据库和研发基于代谢组学方法的食源性致病菌检测技术提供参考。     

A novel application of metabolomics in vertebrate development

Many studies have demonstrated the functions of individual genes associated with embryogenesis and have determined the genome sequences of several organisms. Despite the availability of enormous amount of genetic information, dynamic changes that occur during embryogenesis have not yet been completely understood. In order to understand the dynamic processes involved in embryogenesis, we employed the metabolomic approach. The results of our study indicated that there is a close correlation between metabolomes and developmental stages. Our method enables the identification of embryonic stages using metabolomes as “fingerprints.” In this manner, we could successfully predict embryonic development on the basis of metabolomic fingerprints. This is the first report describing a model for predicting vertebrate development by using metabolomics.     

The metabolomics standards initiative (MSI)

In 2005, the Metabolomics Standards Initiative has been formed. An outline and general introduction is provided to inform about the history, structure, working plan and intentions of this initiative. Comments on any of the suggested minimal reporting standards are welcome to be sent to the open email list Msi-workgroups-feedback@lists.sourceforge.net