Mass spectrometric determination of selected microbial constituents using fused silica and chiral glass capillary gas chromatography

Summary Applications of quantitative gas chromatography/mass spectrometry (selected ion monitoring) to clinical and ecological microbiology are described. The technique permits determination of selected microbial metabolites and can be used for the rapid diagnosis of, for example, tuberculosis by ion-focusing of specific branch-chain fatty acids. The technique is also used to determine diaminopimelic and muramic acids, and D- and L-amino acids separated by chiral gas chromatography, in the low picogram range. The latter method has the potential to detect and quantitate microbial populations.Presented at the 14th International Symposium on Chromatography London, September, 1982     

Metabolic profiling of intracellular metabolites in fermentation broths from β-lactam antibiotics production by liquid chromatography–tandem mass spectrometry methods

An analytical platform comprising three LC–ESI-MS/MS methods is presented for qualitative and quantitative profiling of more than 200 intracellular metabolites. Employing a silica based zwitterionic stationary phase in the HILIC mode, in total 223 hydrophilic metabolites can be determined. In particular, amino acids, organic acids as well as nucleotide sugars were found to be well separable and detectable under acidic mobile phase conditions, while in comparison especially phosphates such as nucleotides, coenzymes or sugar phosphates as well as sugars and sugar acids performed better at higher pH. Additionally, 21 less polar analytes turned out to be amenable for separation and analysis on a pentafluorophenyl modified silica stationary phase in RP mode. Solutes were detected by tandem mass spectrometry on a triple quadrupole instrument in the selected reaction monitoring (SRM) mode and specific SRM transitions for 258 metabolites are provided. All three methods were validated with respect to the limit of quantification, linear dynamic range, precision and accuracy. Applicability of the analytical platform was evaluated by analysis of the targeted metabolites in extracts of β-lactam antibiotics fermentation broths. Thereby, 87 metabolites were determined qualitatively in penicillin fermentation broths, and 94 compounds were found in cephalosporin extracts. In addition, a number of selected metabolites that can be determined by at least two of the presented LC–MS/MS methods was analyzed quantitatively by both, external calibration using pure standards as well as by matrix-matched calibration performing standard addition. Quantitative results obtained with the different methods agreed well, however, for some analytes external calibration was found to be ill-suited due to matrix effects.     

Mass spectrometric analysis for carboxylic acids as viable markers of petroleum hydrocarbon biodegradation

The characterization of metabolites, which are considered markers of bacterial degradation of hydrocarbons, is gaining in importance. Over the years, carboxylic acids have served as useful indicators of aerobic and anaerobic hydrocarbon biodegradation. This interest has been accompanied by the extensive and robust development of analytical methods for monitoring, untargeted identification, and specific and sensitive determination of carboxylic acids in complex matrices. This review discusses critically the state-of-the-art of mass spectrometry as a reliable analytical technique to identify and quantify carboxylic acid metabolites. Attention is paid to sample pre-treatment, selective group pre-concentration, and gas and liquid chromatography preceding mass spectrometry to alleviate matrix effects and ionization discrimination. Recent specific applications of mass spectrometry in monitoring carboxylic acids for assessing hydrocarbon biodegradation are reviewed. Presently, no single technique is sufficient for holistic profiling of carboxylic acids. The direct characterization of carboxylic acids by mass spectrometry is the ultimate goal but despite recent significant developments, challenges persist.     

LC-HRMS/MS-Based Metabolomics Approaches Applied to the Detection of Antifungal Compounds and a Metabolic Dynamic Assessment of Orchidaceae

The liquid chromatography–mass spectrometry (LC-MS)-based metabolomics approach is a powerful technology for discovering novel biologically active molecules. In this study, we investigated the metabolic profiling of Orchidaceae species using LC-HRMS/MS data combined with chemometric methods and dereplication tools to discover antifungal compounds. We analyze twenty ethanolic plant extracts from Vanda and Cattleya (Orchidaceae) genera. Molecular networking and chemometric methods were used to discriminate ions that differentiate healthy and fungal-infected plant samples. Fifty-three metabolites were rapidly annotated through spectral library matching and in silico fragmentation tools. The metabolomic profiling showed a large production of polyphenols, including flavonoids, phenolic acids, chromones, stilbenoids, and tannins, which varied in relative abundance across species. Considering the presence and abundance of metabolites in both groups of samples, we can infer that these constituents are associated with biochemical responses to microbial attacks. In addition, we evaluated the metabolic dynamic through the synthesis of stilbenoids in fungal-infected plants. The tricin derivative flavonoid- and the loliolide terpenoidfound only in healthy plant samples, are promising antifungal metabolites. LC-HRMS/MS, combined with state-of-the-art tools, proved to be a rapid and reliable technique for fingerprinting medicinal plants and discovering new hits and leads.     

Monitoring of metabolic profiling and water status of Hayward kiwifruits by nuclear magnetic resonance

The metabolic profiling of kiwifruit (Actinidia deliciosa, Hayward cultivar) aqueous extracts and the water status of entire kiwifruits were monitored over the season (June-December) using nuclear magnetic resonance (NMR) methodologies. The metabolic profiling of aqueous kiwifruit extracts was investigated by means of high field NMR spectroscopy. A large number of water-soluble metabolites were assigned by means of 1D and 2D NMR experiments. The change in the metabolic profiles monitored over the season allowed the kiwifruit development to be investigated. Specific temporal trends of aminoacids, sugars, organic acids and other metabolites were observed.The water status of kiwifruits was monitored directly on the intact fruit measuring the T₂ spin-spin relaxation time by means of a portable unilateral NMR instrument, fully non-invasive. Again, clear trends of the relaxation time were observed during the monitoring period.The results show that the monitoring of the metabolic profiling and the monitoring of the water status are two complementary means suitable to have a complete view of the investigated fruit.     

Multitarget quantitative metabolic profiling of hydrophilic metabolites in fermentation broths of β-lactam antibiotics production by HILIC–ESI–MS/MS

The presented work deals with the development and comprehensive validation of a quantitative LC–electrospray ionization (ESI)–tandem mass spectrometry (MS/MS) method using a triple quadrupole instrument in the MRM mode for the metabolic profiling of amino acids, organic acids, vitamins, some biogenic amines, secondary metabolites of β-lactam antibiotics biosynthesis as well as their intermediates, and degradation products in fermentation broths of β-lactam antibiotics production (in total 57 hydrophilic compounds). A great number of chromatographic systems (22 different stationary phase/mobile phase conditions) were screened for their adequate chromatographic selectivity to cope with isobaric compounds and other critical analyte pairs. Finally, a hydrophilic interaction liquid chromatography (HILIC) method employing a zwitterionic ZIC-HILIC column was selected as best compromise. Particular focus was given on the elucidation of absolute and relative matrix effects via comparison of slopes of calibration functions of spiked matrix and standard solutions. These data as well as precision and accuracy data confirm suitability of the HILIC–ESI–MS/MS assay for metabolic profiling studies in fermentation samples. Detailed comprehensive data sets are presented which should illustrate critical issues, problems, and challenges of multitarget quantitative metabolic profiling and should outline possible strategies to circumvent pitfalls and overcome common problems.     

Method for rapid metabolite profiling of drug candidates in fresh hepatocytes using liquid chromatography coupled with a hybrid quadrupole linear ion trap

Rapid information on metabolic profiling is required to evaluate the structural liabilities of drug candidates in early drug discovery. In this study, a sensitive and rapid semi-quantitative method was developed to simultaneously monitor the drug candidate and metabolites as well as collect tandem mass (MS/MS) spectra for subsequent metabolite identification. The simultaneous semi-quantitation and identification of metabolites in fresh hepatocytes is achieved using high-performance liquid chromatography (HPLC) coupled with a hybrid quadrupole linear ion trap. The survey experiment consists of monitoring multiple-reaction monitoring (MRM) transitions for the internal standard, the parent, and 48 MRM transitions designed to cover the most common phase I and II biotransformations. An information-dependent acquisition (IDA) method was employed to trigger product ion scans above the MRM signal threshold. Three biotransformations of a lead compound have been identified through enhanced product ion scans and the respective MRM transitions of those metabolites were selected for semi-quantitation. Parent disappearance and formation of the metabolites as a function of incubation time in five different species were monitored by their respective MRM responses. The method provides the necessary sensitivity to detect minor metabolites in a relevant therapeutic concentration range. Enzymatic turnover of the parent and the metabolites in different species are revealed based on the different initial concentrations of the parent. This methodology integrates the parent disappearance, metabolite identification, and the formation of the metabolites along the time course using a single rapid LC/MS/MS analysis. This method can be used as a complementary tool to the conventional method of metabolic profiling. It provides a rapid and sensitive initial profile of the metabolism of potential structural series at the lead selection stage. The method can also be incorporated into the overall metabolite profiling scheme to evaluate the drug candidates in drug discovery.     

NMR metabolic profiling of organic and aqueous sea bass extracts: implications in the discrimination of wild and cultured sea bass

The nuclear magnetic resonance (NMR) technique was used as analytical tool to determine the complete metabolic profiling of sea bass extracts: water-soluble metabolites belonging to different classes such as sugars, amino acids, dipeptides and organic acids as well as metabolites soluble in organic solvent such as lipids, sterols and fatty acids were identified. The metabolite profiling together with a suitable statistical analysis were used to discriminate between wild and cultured sea bass samples. Preliminary results show that discrimination between wild and cultured sea bass was obtained not only using fatty acid composition but also cholesterol and phosphatidylethanolamine and some water-soluble metabolites such as choline, trimethylamine oxide, glutamine, fumaric and malic acids.     

导电聚合物喷雾电离质谱法对微量全血代谢轮廓即时监测

血液代谢物水平可用于术后生理代谢状况的个体化精准评估,这对体液整体代谢轮廓的即时检验提出了迫切的技术需求.该文介绍了导电聚合物喷雾电离质谱(CPSI-MS)在体液代谢物多重监测中的应用价值.该技术采用由碳纳米管(CNT)和聚甲基丙烯酸甲酯(PMMA)组成的导电聚合物作为血液加载与原位电离喷头.当对该聚合物施加4.5 k...     

基于气相色谱-质谱联用技术的水稻代谢轮廓分析方法的建立

开展了基于衍生化气相色谱-质谱联用的水稻代谢物分析方法的研究。采用D-最优试验设计对代谢物的提取溶剂进行优化,考察了水、甲醇、乙腈和异丙醇的提取效率,通过多元统计分析评价提取效能和溶剂配比的相关性,最终确立以80%(v/v)甲醇/水作为代谢物提取的最适溶剂。在此基础上对该方法的分析性能进行评价,发现绝大多数代谢物(＞90%)具有良好的精密度、重现性和稳定性(相对标准偏差小于30%),且占总峰面积88.0%的代谢物的响应值与其浓度间呈线性关系(相关系数＞0.9)。采用气相色谱-质谱联用方法从水稻种子中共鉴定出86个代谢物,涵盖糖、氨基酸、有机酸、甾体等多类浓度差异大的物质,适合于水稻的代谢表型差异研究。     

Simultaneous determination by GC-MS-SIM of o-, m-, p-hydroxyphenylacetic acid, 3:4-dihydroxyphenylacetic acid and homovanillic acid in biological samples using a common selected ion

A GC-MS-SIM method is described for the simultaneous determination of five acid metabolites, o-, m-, and p-hydroxyphenylacetic acid, 3:4-dihydroxyphenylacetic acid and homovanillic acid in biological samples using a common selected ion for all the acids. The TMS ethers of methyl or ethyl esters of these compounds have a common ion at m/e 179 which is used for their quantitation by selected ion monitoring. The molecular ion at m/e 238 of the three monohydroxy phenylacetic acids, which is also the M-30 ion for homovanillic acid, is also used for their quantitation. The GC conditions for their separation, the relative sensitivities and some advantages of TMS ethers over other derivatives are described. The application of this method to biological samples is illustrated by data on human urine and plasma.     

A new aminopeptidase inhibitor from Streptomyces strain HCCB10043 found by UPLC-MS

The diversity of microbial metabolites has been of interest and concern for a long time, yet a suitable method for discovering these is still unavailable. In the work discussed in this report, ultra-performance liquid chromatography coupled with tandem quadrupole and time of flight high-resolution mass spectrometry (UPLC–Q–TOF-HRMS), with MS data analysis, was set up to study the metabolites of Streptomyces strain HCCB10043. It was found that besides antibacterial substances (A21978C complex) and two anti-aminopeptidase compounds (valistatin and bestatin), this strain can produce a new aminopeptidase inhibitor, identified as 3-amino-2-hydroxy-4-phenylbutanoylvalylisoleucine. This new compound had greater activity than valistatin or bestatin in aminopeptidase N (APN) inhibition assay. The results proved that combination of UPLC–Q–TOF-MS analysis and classic purification and identification steps as complementary strategies can provide a method with high reliability for research on microbial secondary metabolites. Furthermore, it has shown that the study of secondary metabolic profiling might be the key to discovering new drugs.     

Microextraction of Aromatic Microbial Metabolites by Packed Sorbent (MEPS) from Model Solutions Followed by Gas Chromatography/Mass Spectrometry Analysis of Their Silyl Derivatives

The paper describes the results of extraction of aromatic microbial metabolites (phenylcarboxylic acids) from model aqueous solutions using microextraction by packed sorbent (MEPS), followed by the determination of their silyl derivatives by gas chromatography/mass spectrometry. The selected conditions of adsorption–desorption, derivatization, and gas chromatography determination enable the detection of a number of compounds, which are proved and prospective disease markers. This detection could be performed at the level of their concentration in blood of healthy donors (0.5 μmol L^–1) and patients of intensive care units, having an initial stage of sepsis (2–3 μmol L^–1) or other serious diseases caused by significant microbial load and led to the development of multiple organ failure. The recoveries of phenylcarboxylic acids using nonpolar sorbent (C18) reached 20–65% for hydroxylated acids (phenyllactic, 4-hydroxybenzoic, 4-hydroxyphenylacetic, 4-hydroxyphenylpropanoic, homovanillic, and 4-hydroxyphenyllactic acids) and 100% for more nonpolar acids (benzoic, phenylpropanoic, and cinnamic acids).     

Regulation of common neurological disorders by gut microbial metabolites

The gut is connected to the CNS by immunological mediators, lymphocytes, neurotransmitters, microbes and microbial metabolites. A mounting body of evidence indicates that the microbiome exerts significant effects on immune cells and CNS cells. These effects frequently result in the suppression or exacerbation of inflammatory responses, the latter of which can lead to severe tissue damage, altered synapse formation and disrupted maintenance of the CNS. Herein, we review recent progress in research on the microbial regulation of CNS diseases with a focus on major gut microbial metabolites, such as short-chain fatty acids, tryptophan metabolites, and secondary bile acids. Pathological changes in the CNS are associated with dysbiosis and altered levels of microbial metabolites, which can further exacerbate various neurological disorders. The cellular and molecular mechanisms by which these gut microbial metabolites regulate inflammatory diseases in the CNS are discussed. We highlight the similarities and differences in the impact on four major CNS diseases, i.e., multiple sclerosis, Parkinson’s disease, Alzheimer’s disease, and autism spectrum disorder, to identify common cellular and molecular networks governing the regulation of cellular constituents and pathogenesis in the CNS by microbial metabolites.Subject terms: Autoimmune diseases, Chronic inflammation     

基于柱前衍生-超高效液相色谱-质谱联用技术的植物提取液中氨基化合物代谢谱分析

氨基化合物在植物生长发育中起着重要作用。本文建立了一种基于柱前衍生-超高效液相色谱-质谱联用技术的植物提取液中氨基化合物代谢谱的分析方法。以烟草鲜叶为例,共检测出87种氨基化合物。其中43种氨基化合物的定量分析结果表明,方法的线性相关系数在0.993~0.999之间,线性范围可达到4个数量级,检出限为0.03~6.58 ng/mL,日内、日间精密度分别为0.7%~15.6%、0.8%~22.9%,回收率为74.4%~122.7%。采用该方法考察了打顶对不同部位烟草鲜叶中氨基化合物代谢谱的影响,结果显示打顶处理对上部叶影响最大,打顶后上部叶氮代谢主要流向生物碱合成方向。该方法充分利用了三重四极杆串联质谱和高分辨串联质谱技术的优势,可实现植物提取液中氨基代谢物的高选择性、高灵敏度分析。     

Integrating multiple analytical platforms and chemometrics for comprehensive metabolic profiling: application to meat spoilage detection

Untargeted metabolic profiling has become a common approach to attempt to understand biological systems. However, due to the large chemical diversity in the metabolites it is generally necessary to employ multiple analytical platforms so as to encompass a wide range of metabolites. Thus it is beneficial to find chemometrics approaches which can effectively integrate data generated from multiple platforms and ideally combine the strength of each platform and overcome their inherent weaknesses; most pertinent is with respect to limited chemistries. We have reported a few studies using untargeted metabolic profiling techniques to monitor the natural spoilage process in pork and also to detect specific metabolites associated with contaminations with the pathogen Salmonella typhimurium. One method used was to analyse the volatile organic compounds (VoCs) generated throughout the spoilage process while the other was to analyse the soluble small molecule metabolites (SMM) extracted from the microbial community, as well as from the surface of the spoiled/contaminated meat. In this study, we exploit multi-block principal component analysis (MB-PCA) and multi-block partial least squares (MB-PLS) to combine the VoCs and SMM data together and compare the results obtained by analysing each data set individually. We show that by combining the two data sets and applying appropriate chemometrics, a model with much better prediction and importantly with improved interpretability was obtained. The MB-PCA model was able to combine the strength of both platforms together and generated a model with high consistency with the biological expectations, despite its unsupervised nature. MB-PLS models also achieved the best over-all performance in modelling the spoilage progression and discriminating the naturally spoiled samples and the pathogen contaminated samples. Correlation analysis and Bayesian network analysis were also performed to elucidate which metabolites were correlated strongly in the two data sets and such information could add additional information in understanding the meat spoilage process.     

Comprehensive mass spectrometry based metabolic profiling of blood plasma reveals potent discriminatory classifiers of pancreatic cancer

Poor outcome of pancreatic cancer necessitates development of an early diagnostic method to reduce mortality. No reliable early diagnostic test for pancreatic cancer detection has been developed and validated to date. In the current study, metabolic profiling of plasma samples from selected cancer patients and noncancerous controls was performed to seek novel metabolic biomarkers of pancreatic cancer. A comprehensive mass spectrometry based analytical platform established at the Metabolomics Core of the UC Davis Genome Center allowed detection of multiple compounds previously unreported in plasma from pancreatic cancer patients. It was found that selective amino acids, bile acids, and polar lipids were detected with increased or decreased levels in pancreatic cancer samples compared to controls. These findings on blood plasma levels of the relevant metabolites might be very useful clinical parameters for early diagnosis of pancreatic cancer. Copyright © 2010 John Wiley & Sons, Ltd.     

Utilization of metabolomics to identify serum biomarkers for hepatocellular carcinoma in patients with liver cirrhosis

Characterizing the metabolic changes pertaining to hepatocellular carcinoma (HCC) in patients with liver cirrhosis is believed to contribute towards early detection, treatment, and understanding of the molecular mechanisms of HCC. In this study, we compare metabolite levels in sera of 78 HCC cases with 184 cirrhotic controls by using ultra performance liquid chromatography coupled with a hybrid quadrupole time-of-flight mass spectrometry (UPLC–QTOF MS). Following data preprocessing, the most relevant ions in distinguishing HCC cases from patients with cirrhosis are selected by parametric and non-parametric statistical methods. Putative metabolite identifications for these ions are obtained through mass-based database search. Verification of the identities of selected metabolites is conducted by comparing their MS/MS fragmentation patterns and retention time with those from authentic compounds. Quantitation of these metabolites is performed in a subset of the serum samples (10 HCC and 10 cirrhosis) using isotope dilution by selected reaction monitoring (SRM) on triple quadrupole linear ion trap (QqQLIT) and triple quadrupole (QqQ) mass spectrometers. The results of this analysis confirm that metabolites involved in sphingolipid metabolism and phospholipid catabolism such as sphingosine-1-phosphate (S-1-P) and lysophosphatidylcholine (lysoPC 17:0) are up-regulated in sera of HCC vs. those with liver cirrhosis. Down-regulated metabolites include those involved in bile acid biosynthesis (specifically cholesterol metabolism) such as glycochenodeoxycholic acid 3-sulfate (3-sulfo-GCDCA), glycocholic acid (GCA), glycodeoxycholic acid (GDCA), taurocholic acid (TCA), and taurochenodeoxycholate (TCDCA). These results provide useful insights into HCC biomarker discovery utilizing metabolomics as an efficient and cost-effective platform. Our work shows that metabolomic profiling is a promising tool to identify candidate metabolic biomarkers for early detection of HCC cases in high risk population of cirrhotic patients.     

Classification and differential metabolite discovery of liver diseases based on plasma metabolic profiling and support vector machines

Discovery of differential metabolites is the focus of metabonomics study. It has very important applications in pathogenesis and disease classification. The aim of this work is to identify differential metabolites for classifying the patients with hepatocellular carcinoma, cirrhosis and hepatitis based on metabolic profiling data analyzed by gas chromatography-time of flight mass spectrometry. A two-stage feature selection algorithm, F-SVM, combining F-score in analysis of variance and support vector machine (SVM), was applied in discovering discriminative metabolites for three different types of liver diseases. The results show that the accuracy rate of the double cross-validation was 73.68±2.98%. 22 important differential metabolites selected by F-SVM were identified and related pathophysiological process of liver diseases was set forth. We conclude that F-SVM is quite feasible to be applied in the selection of biologically relevant features in metabonomics.     

Profiling of trichorzianines in culture samples of Trichoderma atroviride by liquid chromatography/tandem mass spectrometry

Peptaibols are bioactive linear peptides of 5-20 amino acid residues and contain specific non-proteinogenic amino acids such as alpha-aminoisobutyric acid (Aib). They are antibiotic secondary metabolites of moulds belonging predominantly to the genus Trichoderma, some species of which are successfully used as biocontrol organisms to fight against plant diseases. In the present study we developed a profiling method for the relative quantification of 16 trichorzianine peptaibols in culture samples of T. atroviride and the comparison of their expression patterns by liquid chromatography/electrospray ionisation tandem mass spectrometry (LC/ESI-MS/MS). The method is based on selected reaction monitoring (SRM) in a triple-quadrupole tandem mass spectrometer using three SRM transitions per compound. The trichorzianines were enriched by solid-phase extraction (SPE) on C(18) cartridges. SPE recoveries were evaluated for diluted trichorzianine standard solutions and ranged from 72-97%. Suppression of the ionisation of the peptaibols in the ESI source ranged from 67-128% for most of the trichorzianines in culture filtrates of two different strains of T. atroviride and in spiked culture medium. In the case of trichorzianines TA Vb, TA VIa and TA VIb the presence of matrix components in the fungal culture samples caused a reduction of the SRM signal, with intensities between 34% and 56% relative to pure standard solutions. Finally, the profiling method was successfully applied to culture samples of T. atroviride P1 wild-type and two deletion mutants showing different trichorzianine expression patterns characteristic for the investigated fungal strains. This is the first LC-SRM profiling method for peptaibols for the investigation of peptaibol expression patterns in fungal culture samples. Copyright (c) 2007 John Wiley & Sons, Ltd.