Microbial metabolomics: toward a platform with full metabolome coverage

Achieving metabolome data with satisfactory coverage is a formidable challenge in metabolomics because metabolites are a chemically highly diverse group of compounds. Here we present a strategy for the development of an advanced analytical platform that allows the comprehensive analysis of microbial metabolomes. Our approach started with in silico metabolome information from three microorganisms-Escherichia coli, Bacillus subtilis, and Saccharomyces cerevisiae-and resulted in a list of 905 different metabolites. Subsequently, these metabolites were classified based on their physicochemical properties, followed by the development of complementary gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry methods, each of which analyzes different metabolite classes. This metabolomics platform, consisting of six different analytical methods, was applied for the analysis of the metabolites for which commercial standards could be purchased (399 compounds). Of these 399 metabolites, 380 could be analyzed with the platform. To demonstrate the potential of this metabolomics platform, we report on its application to the analysis of the metabolome composition of mid-logarithmic E. coli cells grown on a mineral salts medium using glucose as the carbon source. Of the 431 peaks detected, 235 (=176 unique metabolites) could be identified. These include 61 metabolites that were not previously identified or annotated in existing E. coli databases.     

Multiomics metabolic and epigenetics regulatory network in cancer: A systems biology perspective

Genetic, epigenetic, and metabolic alterations are all hallmarks of cancer. However, the epigenome and metabolome are both highly complex and dynamic biological networks in vivo. The interplay between the epigenome and metabolome contributes to a biological system that is responsive to the tumor microenvironment and possesses a wealth of unknown biomarkers and targets of cancer therapy. From this perspective, we first review the state of high-throughput biological data acquisition(i.e. multiomics data)and analysis(i.e. computational tools) and then propose a conceptual in silico metabolic and epigenetic regulatory network(MER-Net) that is based on these current high-throughput methods. The conceptual MER-Net is aimed at linking metabolomic and epigenomic networks through observation of biological processes, omics data acquisition, analysis of network information, and integration with validated database knowledge. Thus, MER-Net could be used to reveal new potential biomarkers and therapeutic targets using deep learning models to integrate and analyze large multiomics networks. We propose that MER-Net can serve as a tool to guide integrated metabolomics and epigenomics research or can be modified to answer other complex biological and clinical questions using multiomics data.     

慢性乙型肝炎舌红苔黄和舌淡苔白不同舌象的尿代谢组研究

目的：探索慢性乙型肝炎舌红苔黄和舌淡苔白不同舌象者的尿代谢差异指标,为中医舌象生物学物质基础微观辨证提供证据。方法：采用气相色谱／质谱联用（GC／MS ）技术方法获取慢性乙型肝炎舌红苔黄和舌淡苔白不同舌象者的尿液样本代谢指纹谱,用无监督的学习模式进行多变量统计分析,观察不同组别的人群之间是否存在“自然”的分类结构。利用有监督的学习模式进行数据分类模型的建立和检验,寻找造成样本聚集和离散的主要差异变量。利用商业化的代谢物谱库以及标准品数据库,进行物质鉴定。结果：慢性乙型肝炎舌红苔黄和舌淡苔白者在有监督的学习模式下具有良好的分开趋势,慢乙肝不同舌象者较健康者的差异代谢物谱主要与能量代谢、氨基酸代谢、核苷酸代谢以及肠道菌群代谢相关。结论：舌象是机体变化的重要窗口,不同舌象的外在表观潜在体内的代谢差异。     

Analysis of skeletal muscle metabolome: Evaluation of extraction methods for targeted metabolite quantification using liquid chromatography tandem mass spectrometry

Functional metabolomics of skeletal muscle involves the simultaneous identification and quantification of a large number of metabolites. For this purpose, the extraction of metabolites from animal tissues is a crucial technical step that needs to be optimized. In this work, five extraction methods for skeletal muscle metabolome analysis using liquid chromatography tandem mass spectrometry (LC-MS/MS) were tested. Bird skeletal muscles sampled postmortem and quenched in liquid nitrogen were used. Three replicates of the same sample were extracted using the following solvent systems of varying polarity: boiling water (BW, +100 °C), cold pure methanol (CPM, −80 °C), methanol/chloroform/water (MCW, −20 °C), boiling ethanol (BE, +80 °C), and perchloric acid (PCA, −20 °C). Three injections by extraction were performed. The BW extraction showed the highest recovery of metabolites with the lowest variability (<10%) except for creatine-phosphate (creatine-P). Considering yield (area of the peaks), reproducibility, and ease, the current experiment drew a scale for the muscle metabolome extraction starting from the best to the least convenient: BW > MCW > CPM > PCA ? BE. In addition, the semiquantification of metabolites in two muscles showing different metabolic and contractile properties was carried out after BW extraction and showed expected differences in metabolite contents, thereby validating the technique for biological investigations. In conclusion, the BW extraction is recommended for analysis of skeletal muscle metabolome except for creatine-P, which was poorly recovered with this technique.     

Cold glycerol-saline: the promising quenching solution for accurate intracellular metabolite analysis of microbial cells

Microbial metabolomics has been seriously limited by our inability to perform a reliable separation of intra- and extracellular metabolites with efficient quenching of cell metabolism. Microbial cells are sensitive to most (if not all) quenching agents developed to date, resulting in leakage of intracellular metabolites to the extracellular medium during quenching. Therefore, as yet we are unable to obtain an accurate concentration of intracellular metabolites from microbial cell cultures. However, knowledge of the in vivo concentrations of intermediary metabolites is of fundamental importance for the characterization of microbial metabolism so as to integrate meaningful metabolomics data with other levels of functional genomics analysis. In this article, we report a novel and robust quenching method for microbial cell cultures based on cold glycerol-saline solution as the quenching agent that prevents significant leakage of intracellular metabolites and, therefore, permits more accurate measurement of intracellular metabolite concentrations in microbial cells.     

A Mass Spectrometric Study for Comparative Analysis and Evaluation of Metabolite Recovery from Plasma by Various Solvent Systems

A solvent system that extracts a maximum number of metabolites belonging to diverse chemical classes from complex biofluids, such as plasma, may offer useful inputs to understand the metabolic and physiological state of an individual. The present study compared seven solvent systems for extraction of metabolites from plasma. The extracts were analyzed by mass spectrometry (MS) and MS/MS (MS2) using a quadrupole time-of-flight liquid chromatography/MS system in positive and negative modes of ionization. Metabolites with molecular mass below 400 were identified using Human Metabolome Database MS2 and MS search interfaces. The acetone/isopropanol (2:1) system yielded promising results in positive ionization mode, as the maximum number of MS and MS2 features was detected in the extract. It was found to be superior in extraction of various classes of metabolites, especially organic acids, nucleosides and nucleoside derivatives, and heterocyclic molecules. Glycerophosphocholines in the mass range of 400–700 were found to be efficiently extracted by the methanol/chloroform/water (8:1:1) system. In negative mode as well, the maximum number of MS2 features was detected in methanol/chloroform/water and acetone/isopropanol extracts. The fingerprints of molecular features obtained in the negative and positive modes differed from each other to a significant extent.     

Metabolomic markers of fatigue: Association between circulating metabolome and fatigue in women with chronic widespread pain

Background

Fatigue is a sensation of unbearable tiredness that frequently accompanies chronic widespread musculoskeletal pain (CWP) and inflammatory joint disease. Its mechanisms are poorly understood and there is a lack of effective biomarkers for diagnosis and onset prediction. We studied the circulating metabolome in a population sample characterised for CWP to identify biomarkers showing specificity for fatigue.

代谢组研究的生物信息学方法

代谢组是细胞新陈代谢过程中小分子代谢物的集合。新陈代谢为细胞提供生理活动必需的物质和能量。代谢组直接反映细胞的新陈代谢过程,对代谢组的研究体现细胞的功能。细胞功能的异常会导致代谢组的异常,因此通过代谢组数据即可分析出细胞的健康状况。对代谢组物质的提取鉴定过程和代谢组数据的分析方法,主要是对代谢组数据整理和代谢网络推断过程进行综述。