Identification of metabolomic markers of lavender and lavandin essential oils using mid-infrared spectroscopy

Lavender (Lavandula angustifolia) and lavandin (sterile hybrid of L. angustifolia P. Mill. × Lavandula latifolia (L.f.) Medikus) are widely cultivated in the Mediterranean area for produce essential oils. In this study, 80 lavandin and 55 lavender essential oil samples from various varieties were analyzed. Firstly, a chemometric treatment of mid-infrared spectra was used to evaluate the capacity of Partial Least Squares Discriminant Analysis (PLS-DA) regression to discriminate French lavandin and lavender essential oil (EO) samples and their varieties (Abrial, Fine, Grosso, Maillette, Matherone, Sumian and Super), and secondly, to quantify the main compounds such as linalyl acetate, linalool, eucalyptol and camphor by PLS regression using reference data from gas chromatography. The examination of PLS and PLS-DA regression coefficients allowed the identification of metabolomic markers. The lavender/lavandin EOs and their varieties were very well classified (100% for lavender/lavandin EOs and between 98 and 100% for varieties). The calibration models obtained by PLS regression for the determination of the main compound contents revealed good correlation (≥0.86) between the predicted and reference values. This method can be used to control the authenticity and traceability of lavender/lavandin and their varieties. Finally, mid-infrared and Raman spectroscopy results were compared.     

Metabolomics of meat exudate: Its potential to evaluate beef meat conservation and aging

In this study we analyzed the exudate of beef to evaluate its potential as non invasive sampling for nuclear magnetic resonance (NMR) based metabolomic analysis of meat samples. Exudate, as the natural juice from raw meat, is an easy to obtain matrix that it is usually collected in small amounts in commercial meat packages. Although meat exudate could provide complete and homogeneous metabolic information about the whole meat piece, this sample has been poorly studied. Exudates from 48 beef samples of different breeds, cattle and storage times have been studied by ¹H NMR spectroscopy. The liquid exudate spectra were compared with those obtained by High Resolution Magic Angle Spinning (HRMAS) of the original meat pieces. The close correlation found between both spectra (>95% of coincident peaks in both registers; Spearman correlation coefficient = 0.945) lead us to propose the exudate as an excellent alternative analytical matrix with a view to apply meat metabolomics. 60 metabolites could be identified through the analysis of mono and bidimensional exudate spectra, 23 of them for the first time in NMR meat studies. The application of chemometric tools to analyze exudate dataset has revealed significant metabolite variations associated with meat aging. Hence, NMR based metabolomics have made it possible both to classify meat samples according to their storage time through Principal Component Analysis (PCA), and to predict that storage time through Partial Least Squares (PLS) regression.     

基于超高效液相色谱-四极杆飞行时间质谱的缺血性脑卒中的代谢组学研究

采用基于超高效液相色谱-四极杆飞行时间质谱的代谢组学方法,研究缺血性脑卒中患者和健康人群的血浆,分析了缺血性脑卒中的生物标志物.实验收集30例缺血性脑卒中患者和17例健康志愿者的血浆样品,采用主成分分析和正交偏最小二乘判别分析,研究了缺血性脑卒中患者组和健康对照组血浆中的代谢物差异,并进行了代谢通路分析.实验结果表明,患者组血浆中的二氢神经鞘氨醇、植物鞘氨醇等物质含量升高,谷氨酰胺、焦谷氨酸和2-酮丁酸等物质含量降低.结果表明,脑卒中不仅影响了鞘脂类和氨基酸的代谢,还对能量代谢产生了显著的影响.     

Knowledge discovery in metabolomics: An overview of MS data handling

While metabolomics attempts to comprehensively analyse the small molecules characterising a biological system, MS has been promoted as the gold standard to study the wide chemical diversity and range of concentrations of the metabolome. On the other hand, extracting the relevant information from the overwhelming amount of data generated by modern analytical platforms has become an important issue for knowledge discovery in this research field. The appropriate treatment of such data is therefore of crucial importance in order, for the data, to provide valuable information. The aim of this review is to provide a broad overview of the methodologies developed to handle and process MS metabolomic data, compare the samples and highlight the relevant metabolites, starting from the raw data to the biomarker discovery. As data handling can be further separated into data processing, data pre‐treatment and data analysis, recent advances in each of these steps are detailed separately.     

黄芪口服液降低大鼠顺铂毒性作用机制的尿液代谢组学研究

采用基于液相色谱-飞行时间质谱联用(LC-TOF-MS)技术的代谢组学方法,分析大鼠尿液内源性代谢物的变化,研究黄芪口服液(HO)降低大鼠顺铂(CDDP)毒性的作用机制.采用低剂量多次腹腔注射CDDP的方法建立CDDP染毒大鼠模型,并连续给予16天HO.于第18天收集正常对照(Control)组、顺铂模型(CDDP)组和黄芪口服液(HO)组大鼠的24 h尿液, 进行LC-TOF-MS分析,以获取尿液代谢物组数据集,对所得数据进行主成分分析(PCA)和正交偏最小二乘法-判别分析(OPLS-DA)等多元统计分析,以筛选潜在生物标志物.于第20天采集大鼠血清测定肌酐和尿素氮水平.血清指标测定结果表明, HO可以显著降低CDDP染毒大鼠的肌酐和尿素氮水平(p<0.05).PCA得分图显示,3组可分别聚类,HO组位于Control组和CDDP组中间,表明HO可部分改善CDDP所致大鼠尿液代谢产物的异常变化.综合OPLS-DA分析、t检验和倍数变化分析结果,最终共筛选并初步鉴定出35个尿液代谢产物作为HO减毒相关的潜在生物标记物.代谢通路分析结果表明,HO可通过纠正体内氨基酸代谢、能量代谢和核苷酸代谢等通路的紊乱,降低CDDP所致机体毒性.     

亲水作用色谱/质谱联用方法用于膀胱癌患者血清代谢组学研究

膀胱癌是泌尿系统最常见的恶性肿瘤之一,具有高发病率、高复发率和高进展率的特点.本研究应用69个极性代谢物标样选择合适的分离系统,建立了两性离子亲水作用色谱/质谱联用的代谢组学分析方法.本方法线性范围较宽,检出限低于ng/mL数量级.将本方法用于血清代谢组学分析,85%以上代谢物峰面积的RSD<30%.对64例膀胱癌患者和32例正常人的血清进行代谢组学研究,发现溶血磷脂酰胆碱、游离脂肪酸、氨基酸、胆汁酸、有机酸、核苷等在患病组和正常组中存在显著差异.经筛选和验证,甘磷酸胆碱、胱氨酸、十二碳烯酸、二十碳烯酸和鹅去氧胆酸5种代谢物可以作为区分膀胱癌和正常人的潜在标志物.本研究结果表明,基于亲水作用色谱/质谱联用的代谢组学方法是发现癌症诊断潜在生物标志物的有效手段.     

Potential of fermentation profiling via rapid measurement of amino acid metabolism by liquid chromatography-tandem mass spectrometry

Monitoring amino acid metabolism during fermentation has significant potential from the standpoint of strain selection, optimizing growth and production in host strains, and profiling microbial metabolism and growth state. A method has been developed based on rapid quantification of underivatized amino acids using liquid chromatography-electrospray tandem mass spectrometry (LC-MS-MS) to monitor the metabolism of 20 amino acids during microbial fermentation. The use of a teicoplanin-based chiral stationary phase coupled with electrospray tandem mass spectrometry allows complete amino acid analyses in less than 4 min. Quantification is accomplished using five isotopically labeled amino acids as internal standards. Because comprehensive chromatographic separation and derivatization are not required, analysis time is significantly less than traditional reversed- or normal-phase LC-based amino acid assays. Intra-sample precisions for amino acid measurements in fermentation supernatants using this method average 4.9% (R.S.D.). Inter-day (inter-fermentation) precisions for individual amino acid measurements range from 4.2 to 129% (R.S.D.). Calibration curves are linear over the range 0-300 microg/ml, and detection limits are estimated at 50-450 ng/ml. Data visualization techniques for constructing semi-quantitative fermentation profiles of nitrogen source utilization have also been developed and implemented, and demonstrate that amino acid profiles generally correlate with observed growth profiles. Further, cellular growth events, such as lag-time and cell lysis can be detected using this methodology. Correlation coefficients for the time profiles of each amino acid measured illustrate that while several amino acids are differentially metabolized in similar fermentations, a select group of amino acids display strong correlations in these samples, indicating a sub-population of analytes that may be most useful for fermentation profiling.     

The dual trend in histatins research

We review histatins (Hsts) in order to encourage development of analytical platforms to clarify obscure points in knowledge of this family of antimicrobial and antifungal peptides. To explain the present interest, we outline the number and the nature of Hsts and their known functions (i.e. antimicrobial action, wound closure, biomarkers of stress, satiety, body mass and incipient Alzheimer’s disease, and diagnosis and treatment of addiction, including to cocaine).The two aspects of research on Hsts (i.e. their natural effects on living organisms and their potential use for medical applications, including as biomarkers) make it necessary to develop new analytical methods. The variety of matrices in which Hsts exist (e.g., saliva and tooth-surface-protein pellicle) make it essential to develop new sample-preparation steps and to improve identification and quantitation steps as analytical instrumentation evolves.In this context, metabolomics studies could be of great interest, as contributions of analytical chemists could be one of the keys to achieving the role that they deserve within “-omics” research.     

CE‐MS for metabolomics: Developments and applications in the period 2016–2018

In the field of metabolomics, CE‐MS is now recognized as a strong analytical technique for the analysis of (highly) polar and charged metabolites in a wide range of biological samples. Over the past few years, significant attention has been paid to the design and improvement of CE‐MS approaches for (large‐scale) metabolic profiling studies and for establishing protocols in order to further expand the role of CE‐MS in metabolomics. In this paper, which is a follow‐up of a previous review paper covering the years 2014–2016 (Electrophoresis 2017, 38, 190–202), main advances in CE‐MS approaches for metabolomics studies are outlined covering the literature from July 2016 to June 2018. Aspects like developments in interfacing designs and data analysis tools for improving the performance of CE‐MS for metabolomics are discussed. Representative examples highlight the utility of CE‐MS in the fields of biomedical, clinical, microbial, and plant metabolomics. A complete overview of recent CE‐MS‐based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings and MS detection mode. Finally, some general conclusions and perspectives are given.