These are scientific publications for Discovery Metabolomics using an Agilent LC/MS system. Please note that the links below will take you to outside of Agilent’s website to PubMed.
1. Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites.
Wikoff WR, Anfora AT, Liu J, Schultz PG, Lesley SA, Peters EC, Siuzdak G.
Proc Natl Acad Sci U S A. 2009 Mar 10; 106(10):3698-703. Epub 2009 Feb 20.
Although it has long been recognized that the enteric community of bacteria that inhabit the human distal intestinal track broadly impacts human health, the biochemical details that underlie these effects remain largely undefined. Here, we report a broad MS-based metabolomics study that demonstrates a surprisingly large effect of the gut "microbiome" on mammalian blood metabolites. Plasma extracts from germ-free mice were compared with samples from conventional (conv) animals by using various MS-based methods. Hundreds of features were detected in only 1 sample set, with the majority of these being unique to the conv animals, whereas approximately 10% of all features observed in both sample sets showed significant changes in their relative signal intensity. Amino acid metabolites were particularly affected. For example, the bacterial-mediated production of bioactive indole-containing metabolites derived from tryptophan such as indoxyl sulfate and the antioxidant indole-3-propionic acid (IPA) was impacted. Production of IPA was shown to be completely dependent on the presence of gut microflora and could be established by colonization with the bacterium Clostridium sporogenes. Multiple organic acids containing phenyl groups were also greatly increased in the presence of gut microbes. A broad, drug-like phase II metabolic response of the host to metabolites generated by the microbiome was observed, suggesting that the gut microflora has a direct impact on the drug metabolism capacity of the host. Together, these results suggest a significant interplay between bacterial and mammalian metabolism.
2. A multi-analytical approach for metabolomic profiling of zebrafish (Danio rerio) livers.
Ong ES, Chor CF, Zou L, Ong CN.
Mol Biosyst. 2009 Mar;5(3):288-98. Epub 2008 Dec 24.
A metabolomic study was performed to investigate the biochemical profiles of livers from male and female zebrafish (Danio rerio), using a multiple platform approach, incorporating 1H NMR, GC/MS and LC/MS. The reproducibility and reliability of the three methods were validated prior to the assays. Major biomolecules detected using one method were also cross examined using the other techniques. These metabolites included carbohydrates, lipids, amino acids detected using 1H NMR and GC/MS, and acetylcarnitine, choline and various phospholipids determined using 1H NMR and LC/MS. Our findings suggest that 1H NMR provided comprehensive information on glucose, amino acids, pyruvate and other smaller biochemical constituents of the zebrafish liver. On the other hand, GC/MS was able to assay cholesterol, saturated and unsaturated fatty acids, and LC/MS was ideal for the analysis of lipids/phospholipids. These techniques revealed that there are significant differences in the biochemical profiles of male and female zebrafish liver tissue extracts. Specifically, we noted that although there were no significant differences observed for the carbohydrate profile, the amino acid profile was rather different in male and female zebrafish liver. Furthermore, data from all three techniques revealed that although the saturated fatty acid profile was similar, the compositions of unsaturated fatty acids were different in the two phenotypes. The overall findings suggested that this multiplatform approach offers comprehensive coverage of a metabolome as well as provides valuable insight towards understanding the different biochemical profiles of a biosystem.
3. Combination of 1H Nuclear Magnetic Resonance Spectroscopy and Liquid Chromatography/Mass Spectrometry with Pattern Recognition Techniques for Evaluation of Metabolic Profile Associated with Albuminuria.
Law W, Huang P, Ong ES, Sethi S, Saw S, Ong CN, Li S.
J Proteome Res. 2009 Feb 2. [Epub ahead of print]
A method using 1H NMR and LC/MS with pattern recognition tools such as principal component analysis (PCA) and orthogonal projection to latent structure discriminant analysis (O-PLS-DA) was used to study the urinary metabolic profiles associated with an increase in urinary albumin in a general population. The normalized peak intensities obtained from 1H NMR and LC/MS with non parametric two-tailed Mann-Whitney analysis was used for the identification of network of potential biomarkers corresponding to the increase of albumin in urine. The specificity of detecting the stated metabolites by 1H NMR and LC/MS was demonstrated. Our preliminary data obtained demonstrated that LC/MS may produce more distinctive metabolic profiles. For the patient group, changes in alanine, kyneurnic acid and xanthurenic acid might be associated with changes in the tryptophan metabolism. At the same time, other metabolites that were involved in citric acid cycle, amino acid metabolism and cellular functions were affected in the patient group. The proposed approach provided a comprehensive picture of the metabolic changes induced by the increase of protein in urine and demonstrated the advantages of using multiple diagnostic biomarkers. At the same time, the current work demonstrated as a potential cost effective solution of high throughput analytics with pattern recognition tools as applied here in a real clinical situation.
4. Identification of a new endogenous metabolite and the characterization of its protein interactions through an immobilization approach.
Kalisiak J, Trauger SA, Kalisiak E, Morita H, Fokin VV, Adams MW, Sharpless KB, Siuzdak G.
J Am Chem Soc. 2009 Jan 14; 131(1):378-86.
The emerging field of global mass-based metabolomics provides a platform for discovering unknown metabolites and their specific biochemical pathways. We report the identification of a new endogenous metabolite, N (4)-(N-acetylaminopropyl) spermidine and the use of a novel proteomics based method for the investigation of its protein interaction using metabolite immobilization on agarose beads. The metabolite was isolated from the organism Pyrococcus furiosus, and structurally characterized through an iterative process of synthesizing candidate molecules and comparative analysis using accurate mass LC-MS/MS. An approach developed for the selective preparation of N(1)-acetylthermospermine, one of the possible structures of the unknown metabolite, provides a convenient route to new polyamine derivatives through methylation on the N(8) and N(4) of the thermospermine scaffold. The biochemical role of the novel metabolite as well as that of two other polyamines: spermidine and agmatine is investigated through metabolite immobilization and incubation with native proteins. The identification of eleven proteins that uniquely bind with N(4)-(N-acetylaminopropyl)spermidine, provides information on the role of this novel metabolite in the native organism. Identified proteins included hypothetical ones such as PF0607 and PF1199, and those involved in translation, DNA synthesis and the urea cycle like translation initiation factor IF-2, 50S ribosomal protein L14e, DNA-directed RNA polymerase, and ornithine carbamoyltransferase. The immobilization approach demonstrated here has the potential for application to other newly discovered endogenous metabolites found through untargeted metabolomics, as a preliminary screen for generating a list of proteins that could be further investigated for specific activity.
5. Cross-platform Q-TOF validation of global exo-metabolomic analysis: Application to human glioblastoma cells treated with the standard PI 3-Kinase inhibitor LY294002.
Pandher R, Ducruix C, Eccles SA, Raynaud FI.
J Chromatogr B Analyt Technol Biomed Life Sci. 2008 Dec 6. [Epub ahead of print]
The reproducibility of a metabolomics method has been assessed to identify changes in tumour cell metabolites. Tissue culture media extracts were analyzed by reverse phase chromatography on a Waters Acquity T3 column with a 13min 0.1% formic acid: acetonitrile gradient on Agilent and Waters LC-Q-TOF instruments. Features (m/z, RT) were extracted by MarkerLynxtrade mark (Waters) and Molecular Feature Extractor (Agilent) in positive and negative ionization modes. The number of features were similar on both instruments and the reproducibility of ten replicates was <35% signal variability for approximately 50% and 40% of all ions detected in positive and negative ionization modes, respectively. External standards spiked to the matrix showed CVs <25% in peak areas within and between days. U87MG glioblastoma cells exposed to the PI 3-Kinase inhibitor LY294002 showed significant alterations of several confirmed features. These included glycerophosphocholine, already shown by NMR to be modulated by LY294002, highlighting the power of this technology for biomarker discovery.
6. Molecular formula and METLIN Personal Metabolite Database matching applied to the identification of compounds generated by LC/TOF-MS.
Sana TR, Roark JC, Li X, Waddell K, Fischer SM.
J Biomol Tech. 2008 Sep;19(4):258-66.
In an effort to simplify and streamline compound identification from metabolomics data generated by liquid chromatography time-of-flight mass spectrometry, we have created software for constructing Personalized Metabolite Databases with content from over 15,000 compounds pulled from the public METLIN database (http://metlin.scripps.edu/). Moreover, we have added extra functionalities to the database that (a) permit the addition of user-defined retention times as an orthogonal searchable parameter to complement accurate mass data; and (b) allow interfacing to separate software, a Molecular Formula Generator (MFG), that facilitates reliable interpretation of any database matches from the accurate mass spectral data. To test the utility of this identification strategy, we added retention times to a subset of masses in this database, representing a mixture of 78 synthetic urine standards. The synthetic mixture was analyzed and screened against this METLIN urine database, resulting in 46 accurate mass and retention time matches. Human urine samples were subsequently analyzed under the same analytical conditions and screened against this database. A total of 1387 ions were detected in human urine; 16 of these ions matched both accurate mass and retention time parameters for the 78 urine standards in the database. Another 374 had only an accurate mass match to the database, with 163 of those masses also having the highest MFG score. Furthermore, MFG calculated a formula for a further 849 ions that had no match to the database. Taken together, these results suggest that the METLIN Personal Metabolite database and MFG software offer a robust strategy for confirming the formula of database matches. In the event of no database match, it also suggests possible formulas that may be helpful in interpreting the experimental results.
7. Analysis of hydrophilic metabolites by high-performance liquid chromatography-mass spectrometry using a silica hydride-based stationary phase.
Pesek JJ, Matyska MT, Fischer SM, Sana TR.
J Chromatogr A. 2008 Sep 12;1204(1):48-55. Epub 2008 Jul 31.
A novel silica hydride-based stationary phase was used to evaluate the retention behavior in the aqueous normal-phase (ANP) mode of standards representing three classes of metabolites. The effects on retention behavior of amino acids, carbohydrates and small organic acids were examined by altering the column temperature, and by adding different additives to both the mobile phase and sample solvent. Gradient mode results revealed the repeatability of retention times to be very stable for these compound classes. At both 15 and 30 degrees C, excellent RSD values were obtained with less than 1% variation for over 50 injections of an amino acid mixture. The ability to separate the 19 nonderivatized amino acid standards, organic acids and carbohydrates was demonstrated as well as the potential for this material to separate polar metabolites in complex fluids such as urine.
8. A sample extraction and chromatographic strategy for increasing LC/MS detection coverage of the erythrocyte metabolome.
Sana TR, Waddell K, Fischer SM.
J Chromatogr B Analyt Technol Biomed Life Sci. 2008 Aug 15; 871(2):314-21. Epub 2008 Apr 26.
Reproducible and comprehensive sample extraction and detection of metabolites with a broad range of physico-chemical properties from biological matrices can be a highly challenging process. A single LC/MS separation method was developed for a 2.1 mm x 100 mm, 1.8 micron ZORBAX SB-Aq column that was used to separate human erythrocyte metabolites extracted under sample extraction solvent conditions where the pH was neutral or had been adjusted to either, pH 2, 6 or 9. Internal standards were included and evaluated for tracking sample extraction efficiency. Through the combination of electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) techniques in both positive (+) and negative (-) ion modes, a total of 2370 features (compounds and associated compound related components: isotopes, adducts and dimers) were detected across all pHs. Broader coverage of the detected metabolome was achieved by observing that (1) performing extractions at pH 2 and 9, leads to a combined 92% increase in detected features over pH 7 alone; and (2) including APCI in the analysis results in a 34% increase in detected features, across all pHs, than the total number detected by ESI. A significant dependency of extraction solvent pH on the recovery of heme and other compounds was observed in erythrocytes and underscores the need for a comprehensive sample extraction strategy and LC/MS analysis in metabolomics profiling experiments.
9. XCMS2: processing tandem mass spectrometry data for metabolite identification and structural characterization.
Benton HP, Wong DM, Trauger SA, Siuzdak G.
Anal Chem. 2008 Aug 15; 80(16):6382-9. Epub 2008 Jul 16.
Mass spectrometry based metabolomics represents a new area for bioinformatics technology development. While the computational tools currently available such as XCMS statistically assess and rank LC-MS features, they do not provide information about their structural identity. XCMS(2) is an open source software package which has been developed to automatically search tandem mass spectrometry (MS/MS) data against high quality experimental MS/MS data from known metabolites contained in a reference library (METLIN). Scoring of hits is based on a "shared peak count" method that identifies masses of fragment ions shared between the analytical and reference MS/MS spectra. Another functional component of XCMS(2) is the capability of providing structural information for unknown metabolites, which are not in the METLIN database. This "similarity search" algorithm has been developed to detect possible structural motifs in the unknown metabolite which may produce characteristic fragment ions and neutral losses to related reference compounds contained in METLIN, even if the precursor masses are not the same.
10. Metabolomic analysis of the cerebrospinal fluid reveals changes in phospholipase expression in the CNS of SIV-infected macaques.
Wikoff WR, Pendyala G, Siuzdak G, Fox HS.
J Clin Invest. 2008 Jul; 118(7):2661-9.
HIV infiltrates the CNS soon after an individual has become infected with the virus, and can cause dementia and encephalitis in late-stage disease. Here, a global metabolomics approach was used to find and identify metabolites differentially regulated in the cerebrospinal fluid (CSF) of rhesus macaques with SIV-induced CNS disease, as we hypothesized that this might provide biomarkers of virus-induced CNS damage. The screening platform used a non-targeted, mass-based metabolomics approach beginning with capillary reverse phase chromatography and electrospray ionization with accurate mass determination, followed by novel, nonlinear data alignment and online database screening to identify metabolites. CSF was compared before and after viral infection. Significant changes in the metabolome specific to SIV-induced encephalitis were observed. Metabolites that were increased during infection-induced encephalitis included carnitine, acyl-carnitines, fatty acids, and phospholipid molecules. The elevation in free fatty acids and lysophospholipids correlated with increased expression of specific phospholipases in the brains of animals with encephalitis. One of these, a phospholipase A2 isoenzyme, is capable of releasing a number of the fatty acids identified. It was expressed in different areas of the brain in conjunction with glial activation, rather than linked to regions of SIV infection and inflammation, indicating widespread alterations in infected brains. The identification of specific metabolites as well as mechanisms of their increase illustrates the potential of mass-based metabolomics to address problems in CNS biochemistry and neurovirology, as well as neurodegenerative diseases.
11. Rapid analysis of fungal cultures and dried figs for secondary metabolites by LC/TOF-MS.
Senyuva HZ, Gilbert J, Oztürkoğlu S.
Anal Chim Acta. 2008 Jun 9; 617(1-2):97-106. Epub 2008 Jan 16.
A liquid chromatography-time-of-flight mass spectrometry (LC/TOF-MS) method has been developed for profiling fungal metabolites. The performance of the procedure in terms of mass accuracy, selectivity (specificity) and repeatability was established by spiking aflatoxins, ochratoxins, trichothecenes and other metabolites into blank growth media. After extracting, and carrying out LC/TOF-MS analysis, the standards were correctly identified by searching a specially constructed database of 465 secondary metabolites. To demonstrate the viability of this approach 11 toxigenic and four non-toxigenic fungi from reference collections were grown on various media, for 7-14 days. The method was also applied to two toxigenic fungi, A. flavus (200-138) and A. parasiticus (2999-465) grown on gamma radiation sterilised dried figs, for 7-14 days. The fungal hyphae plus a portion of growth media or portions of dried figs were solvent extracted and analysed by LC/TOF-MS using a rapid resolution microbore LC column. Data processing based on cluster analysis, showed that electrospray ionization (ESI)-TOF-MS could be used to unequivocally identify metabolites in crude extracts. Using the elemental metabolite database, it was demonstrated that from culture collection isolates, anticipated metabolites. The speed and simplicity of the method has meant that levels of these metabolites could be monitored daily in sterilised figs. Over a 14-day period, levels of aflatoxins and kojic acid maximised at 5-6 days, whilst levels of 5-methoxysterigmatocystin remained relatively constant. In addition to the known metabolites expected to be produced by these fungi, roquefortine A, fumagillin, fumigaclavine B, malformins (peptides), aspergillic acid, nigragillin, terrein, terrestric acid and penicillic acid were also identified.
12. DNA immunization perturbs lipid metabolites and increases risk of atherogenesis.
Yang F, Yan S, Wang F, He Y, Guo Y, Zhou Q, Wang Y, Zhang X, Zhang W, Sun S.
J Proteome Res. 2008 Feb;7(2):741-8. Epub 2008 Jan 1.
In addition to conventional vaccination, DNA-mediated immunization has been developed as an alternative approach in the prevention and treatment of different infectious diseases, including hepatitis B. To define sets of serum protein and metabolite biomarkers that could be employed to determine the efficacy and safety of DNA vaccines, an integrated multiple systems biology approach was undertaken on mice immunized with DNA vaccine, recombinant protein, plasmid vector, and phosphate-buffered solution. Their sera were analyzed by two-dimensional electrophoresis and HPLC coupled with time-of-flight mass spectrometry. We detected an increase in phytosphingosine, dihydrosphingosine, palmitoylcarnitine, and ceramide in the sera of DNA-vaccinated mice. Several protein molecules were found to be altered in DNA-vaccinated mice, including apolipoprotein A-I precursor. Taken together, these results indicated that DNA vaccine stimulated hepatic sphingolipid synthesis, which may have altered the structure of circulating lipoproteins and promoted atherogenesis. This study also underscores the power of metabolomics and proteomics in the definition of DNA-vaccine-mediated metabolic phenotypes.
13. Multiple ionization mass spectrometry strategy used to reveal the complexity of metabolomics.
Nordström A, Want E, Northen T, Lehtiö J, Siuzdak G.
Anal Chem. 2008 Jan 15; 80(2):421-9. Epub 2007 Dec 18.
A multiple ionization mass spectrometry strategy is presented based on the analysis of human serum extracts. Chromatographic separation was interfaced inline with the atmospheric pressure ionization techniques electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) in both positive (+) and negative (-) ionization modes. Furthermore, surface-based matrix-assisted laser desorption/ionization (MALDI) and desorption ionization on silicon (DIOS) mass spectrometry were also integrated with the separation through fraction collection and offline mass spectrometry. Processing of raw data using the XCMS software resulted in time-aligned ion features, which are defined as a unique m/z at a unique retention time. The ion feature lists obtained through LC-MS with ESI and APCI interfaces in both +/- ionization modes were compared, and unique ion tables were generated. Nonredundant, unique ion features, were defined as mass numbers for which no mass numbers corresponding to [M + H](+), [M - H](-), or [M + Na](+) were observed in the other ionization methods at the same retention time. Analysis of the extracted serum using ESI for both (+) and (-) ions resulted in >90% additional unique ions being detected in the (-) ESI mode. Complementing the ESI analysis with APCI resulted in an additional approximately 20% increase in unique ions. Finally, ESI/APCI ionization was combined with fraction collection and offline-MALDI and DIOS mass spectrometry. The parts of the total ion current chromatograms in the LC-MS acquired data corresponding to collected fractions were summed, and m/z lists were compiled and compared to the m/z lists obtained from the DIOS/MALDI spectra. It was observed that, for each fraction, DIOS accounted for approximately 50% of the unique ions detected. These results suggest that true global metabolomics will require multiple ionization technologies to address the inherent metabolite diversity and therefore the complexity in and of metabolomics studies.
14. Metabolomics identifies perturbations in human disorders of propionate metabolism.
Wikoff WR, Gangoiti JA, Barshop BA, Siuzdak G.
Clin Chem. 2007 Dec; 53(12):2169-76. Epub 2007 Oct 19.
We applied untargeted mass spectrometry-based metabolomics to the diseases methylmalonic acidemia (MMA) and propionic acidemia (PA). METHODS: We used a screening platform that used untargeted, mass-based metabolomics of methanol-extracted plasma to find significantly different molecular features in human plasma samples from MMA and PA patients and from healthy individuals. Capillary reverse phase liquid chromatography (4 microL/min) was interfaced to a TOF mass spectrometer, and data were processed using nonlinear alignment software (XCMS) and an online database (METLIN) to find and identify metabolites differentially regulated in disease. RESULTS: Of the approximately 3500 features measured, propionyl carnitine was easily identified as the best biomarker of disease (P value 1.3 x 10(-18)), demonstrating the proof-of-concept use of untargeted metabolomics in clinical chemistry discovery. Five additional acylcarnitine metabolites showed significant differentiation between plasma from patients and healthy individuals, and gamma-butyrobetaine was highly increased in a subset of patients. Two acylcarnitine metabolites and numerous unidentified species differentiate MMA and PA. Many metabolites that do not appear in any public database, and that remain unidentified, varied significantly between normal, MMA, and PA, underscoring the complex downstream metabolic effects resulting from the defect in a single enzyme. CONCLUSIONS: This proof-of-concept study demonstrates that metabolomics can expand the range of metabolites associated with human disease and shows that this method may be useful for disease diagnosis and patient clinical evaluation.
15. Stable isotope assisted assignment of elemental compositions for metabolomics.
Hegeman AD, Schulte CF, Cui Q, Lewis IA, Huttlin EL, Eghbalnia H, Harms AC, Ulrich EL, Markley JL, Sussman MR.
Anal Chem. 2007 Sep 15; 79(18):6912-21. Epub 2007 Aug 21.
Assignment of individual compound identities within mixtures of thousands of metabolites in biological extracts is a major challenge for metabolomic technology. Mass spectrometry offers high sensitivity over a large dynamic range of abundances and molecular weights but is limited in its capacity to discriminate isobaric compounds. In this article, we have extended earlier studies using isotopic labeling for elemental composition elucidation (Rodgers, R. P.; Blumer, E. N.; Hendrickson, C. L.; Marshall, A. G. J. Am. Soc. Mass Spectrom. 2000, 11, 835-40) to limit the formulas consistent with any exact mass measurement by comparing observations of metabolites extracted from Arabidopsis thaliana plants grown with (I) (12)C and (14)N (natural abundance), (II) (12)C and (15)N, (III) (13)C and (14)N, or (IV) (13)C and (15)N. Unique elemental compositions were determined over a dramatically enhanced mass range by analyzing exact mass measurement data from the four extracts using two methods. In the first, metabolite masses were matched with a library of 11,000 compounds known to be present in living cells by using values calculated for each of the four isotopic conditions. In the second method, metabolite masses were searched against masses calculated for a constrained subset of possible atomic combinations in all four isotopic regimes. In both methods, the lists of elemental compositions from each labeling regime were compared to find common formulas with similar retention properties by HPLC in at least three of the four regimes. These results demonstrate that metabolic labeling can be used to provide additional constraints for higher confidence formula assignments over an extended mass range.