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Review

Mass Spectrometry-Based Technologies for High-Throughput Metabolomics

, , &
Pages 1665-1684 | Published online: 07 Dec 2009

Bibliography

  • Fiehn O . Metabolomics – the link between genotypes and phenotypes. Plant Mol. Biol. 48(1–2), 155–171 (2002).
  • Goodacre R , VaidyanathanS, DunnWB, HarriganGG, KellDB. Metabolomics by numbers: acquiring and understanding global metabolite data. Trends Biotechnol. 22(5), 245–252 (2004).
  • Nicholson JK , LindonJC, HolmesE. ‘Metabonomics‘: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica29(11), 1181–1189 (1999).
  • Raamsdonk LM , TeusinkB, BroadhurstDet al. A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations. Nat. Biotechnol. 19(1), 45–50 (2001).
  • ter Kuile BH , WesterhoffHV. Transcriptome meets metabolome: hierarchical and metabolic regulation of the glycolytic pathway. FEBS Lett. 500(3), 169–171 (2001).
  • Kim K , AronovP, ZakharkinSOet al. Urine metabolomics analysis for kidney cancer detection and biomarker discovery. Mol. Cell Proteomics8(3), 558–570 (2009).
  • Sreekumar A , PoissonLM, RajendiranTMet al. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature457(7231), 910–914 (2009).
  • Wikoff WR , AnforaAT, LiuJet al. Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites. Proc. Natl Acad. Sci. USA106(10), 3698–3703 (2009).
  • Scherling C , UlrichK, EwaldD, WeckwerthW. A metabolic signature of the beneficial interaction of the endophyte Paenibacillus sp. isolate and in vitro-grown poplar plants revealed by metabolomics. Mol. Plant Microbe Interact. 22(8), 1032–1037 (2009).
  • Bottcher C , von Roepenack-Lahaye E, Schmidt Jet al. Metabolome analysis of biosynthetic mutants reveals a diversity of metabolic changes and allows identification of a large number of new compounds in Arabidopsis. Plant Physiol. 147(4), 2107–2120 (2008).
  • MacKenzie DA , DefernezM, DunnWBet al. Relatedness of medically important strains of Saccharomyces cerevisiae as revealed by phylogenetics and metabolomics. Yeast25(7), 501–512 (2008).
  • Viant MR . Recent developments in environmental metabolomics. Mol. Biosyst. 4(10), 980–986 (2008).
  • Duarte NC , BeckerSA, JamshidiNet al. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc. Natl Acad. Sci. USA104(6), 1777–1782 (2007).
  • Fiehn O . Combining genomics, metabolome analysis, and biochemical modelling to understand metabolic networks. Comp. Funct. Genomics2(3), 155–168 (2001).
  • Dunn WB , BaileyNJ, JohnsonHE. Measuring the metabolome: current analytical technologies. Analyst130(5), 606–625 (2005).
  • Weckwerth W , FiehnO. Can we discover novel pathways using metabolomic analysis? Curr. Opin. Biotechnol. 13(2), 156–160 (2002).
  • Villas-Boas SG , MasS, AkessonM, SmedsgaardJ, NielsenJ. Mass spectrometry in metabolome analysis. Mass Spectrom. Rev. 24(5), 613–646 (2005).
  • Villas-Boas SG , Hojer-PedersenJ, AkessonM, SmedsgaardJ, NielsenJ. Global metabolite analysis of yeast: evaluation of sample preparation methods. Yeast22(14), 1155–1169 (2005).
  • Dunn WB , EllisDI. Metabolomics: current analytical platforms and methodologies. Trends Anal. Chem. 24(4), 285–294 (2005).
  • Fiehn O , KopkaJ, DormannP, AltmannT, TretheweyRN, WillmitzerL. Metabolite profiling for plant functional genomics. Nat. Biotechnol. 18(11), 1157–1161 (2000).
  • Dettmer K , AronovPA, HammockBD. Mass spectrometry-based metabolomics. Mass Spectrom. Rev. 26(1), 51–78 (2007).
  • Issaq HJ , VanQN, WaybrightTJ, MuschikGM, VeenstraTD. Analytical and statistical approaches to metabolomics research. J. Sep. Sci. 32(13), 2183–2199 (2009).
  • Fiehn O . Extending the breadth of metabolite profiling by gas chromatography coupled to mass spectrometry. Trends Analyt. Chem. 27(3), 261–269 (2008).
  • Pasikanti KK , HoPC, ChanEC. Gas chromatography/mass spectrometry in metabolic profiling of biological fluids. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 871(2), 202–211 (2008).
  • Metz TO , ZhangQ, PageJSet al. The future of liquid chromatography-mass spectrometry (LC–MS) in metabolic profiling and metabolomic studies for biomarker discovery. Biomark. Med. 1(1), 159–185 (2007).
  • Lu W , BennettBD, RabinowitzJD. Analytical strategies for LC–MS-based targeted metabolomics. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 871(2), 236–242 (2008).
  • Cubbon S , AntonioC, WilsonJ, Thomas-OatesJ. Metabolomic applications of HILIC–LC–MS. Mass Spectrom. Rev. DOI: 10.1002/mas.20252 (2009) (Epub ahead of print).
  • Leon C , Rodriguez-MeizosoI, LucioMet al. Metabolomics of transgenic maize combining Fourier transform-ion cyclotron resonance–mass spectrometry, capillary electrophoresis–mass spectrometry and pressurized liquid extraction. J. Chromatogr. A1216(43), 7314–7323 (2009).
  • Chalcraft KR , LeeR, MillsC, Britz-McKibbinP. Virtual quantification of metabolites by capillary electrophoresis–electrospray ionization–mass spectrometry: predicting ionization efficiency without chemical standards. Anal. Chem. 81(7), 2506–2515 (2009).
  • Lee R , PtolemyAS, NiewczasL, Britz-McKibbinP. Integrative metabolomics for characterizing unknown low-abundance metabolites by capillary electrophoresis–mass spectrometry with computer simulations. Anal. Chem. 79(2), 403–415 (2007).
  • Ramautar R , DemirciA, de Jong GJ. Capillary electrophoresis in metabolomics. Trends Anal. Chem. 25(5), 455–466 (2006).
  • Kuhara T . Gas chromatographic–mass spectrometric urinary metabolome analysis to study mutations of inborn errors of metabolism. Mass Spectrom. Rev. 24(6), 814–827 (2005).
  • Qualley AV , DudarevaN. Metabolomics of plant volatiles. Methods Mol. Biol. 553, 329–343 (2009).
  • Halket JM , WatermanD, PrzyborowskaAM, PatelRK, FraserPD, BramleyPM. Chemical derivatization and mass spectral libraries in metabolic profiling by GC/MS and LC/MS/MS. J. Exp. Bot. 56(410), 219–243 (2005).
  • Birkemeyer C , KolasaA, KopkaJ. Comprehensive chemical derivatization for gas chromatography–mass spectrometry-based multi-targeted profiling of the major phytohormones. J. Chromatogr. A. 993(1–2), 89–102 (2003).
  • Maurer HH . Role of gas chromatography–mass spectrometry with negative ion chemical ionization in clinical and forensic toxicology, doping control, and biomonitoring. Ther. Drug Monit. 24(2), 247–254 (2002).
  • Liebeke M , WunderA, LalkM. A rapid microwave-assisted derivatization of bacterial metabolome samples for gas chromatography/mass spectrometry analysis. Anal. Biochem. DOI: 10.1016/j.ab.2009.04.030 (2009) (Epub ahead of print).
  • Mastovska K , LehotaySJ. Practical approaches to fast gas chromatography-mass spectrometry. J. Chromatogr. A. 1000(1–2), 153–180 (2003).
  • Kawana S , NakagawaK, HasegawaY, KobayashiH, YamaguchiS. Improvement of sample throughput using fast gas chromatography mass-spectrometry for biochemical diagnosis of organic acid disorders. Clin. Chim. Acta392(1–2), 34–40 (2008).
  • Libardoni M , FiehnO, HawkinsJ, KingTM. Analysis of complex metabolomics samples using high throughput GC TOF and GC×GC TOFMS: the importance of deconvolution and GC×GC. Asian J. Pharmacodynamics Pharmacokinetics7(3), 201–209 (2007).
  • Zrostlikova J , HajslovaJ, CajkaT. Evaluation of two-dimensional gas chromatography–time-of-flight mass spectrometry for the determination of multiple pesticide residues in fruit. J. Chromatogr. A. 1019(1–2), 173–186 (2003).
  • Li X , XuZ, LuXet al. Comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry for metabonomics: biomarker discovery for diabetes mellitus. Anal. Chim. Acta633(2), 257–262 (2009).
  • Ralston-Hooper K , HopfA, OhC, ZhangX, AdamecJ, SepulvedaMS. Development of GC×GC/TOF–MS metabolomics for use in ecotoxicological studies with invertebrates. Aquat. Toxicol. 88(1), 48–52 (2008).
  • Mohler RE , DombekKM, HoggardJC, PierceKM, YoungET, SynovecRE. Comprehensive analysis of yeast metabolite GC × GC-TOFMS data: combining discovery-mode and deconvolution chemometric software. Analyst132(8), 756–767 (2007).
  • Koek MM , MuilwijkB, van Stee LL, Hankemeier T. Higher mass loadability in comprehensive two-dimensional gas chromatography–mass spectrometry for improved analytical performance in metabolomics analysis. J. Chromatogr. A1186(1–2), 420–429 (2008).
  • Fiehn O , RobertsonD, GriffinJet al. The metabolomics standards initiative (MSI). Metabolomics3, 175–178 (2007).
  • Bunk B , KucklickM, JonasRet al. MetaQuant: a tool for the automatic quantification of GC/MS-based metabolome data. Bioinformatics22(23), 2962–2965 (2006).
  • Borner J , BuchingerS, SchomburgD. A high-throughput method for microbial metabolome analysis using gas chromatography/mass spectrometry. Anal. Biochem. 367(2), 143–151 (2007).
  • Halket JM , PrzyborowskaA, SteinSE, MallardWG, DownS, ChalmersRA. Deconvolution gas chromatography/mass spectrometry of urinary organic acids – potential for pattern recognition and automated identification of metabolic disorders. Rapid Commun. Mass Spectrom. 13(4), 279–284 (1999).
  • Stein SE . An integrated method for spectrum extraction and compound identification from gas chromatography/mass spectrometry data. J. Am. Soc. Mass Spec. 10(8), 770–781 (1999).
  • Baran R , KochiH, SaitoNet al. MathDAMP: a package for differential analysis of metabolite profiles. BMC Bioinformatics7, 530 (2006).
  • Smith CA , WantEJ, O’MailleG, AbagyanR, SiuzdakG. XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal. Chem. 78(3), 779–787 (2006).
  • Benton HP , WongDM, TraugerSA, SiuzdakG. XCMS2: processing tandem mass spectrometry data for metabolite identification and structural characterization. Anal. Chem. 80(16), 6382–6389 (2008).
  • Katajamaa M , OresicM. Processing methods for differential analysis of LC–MS profile data. BMC Bioinformatics6, 179 (2005).
  • Katajamaa M , MiettinenJ, OresicM. MZmine: toolbox for processing and visualization of mass spectrometry based molecular profile data. Bioinformatics22(5), 634–636 (2006).
  • Lommen A . MetAlign: interface-driven, versatile metabolomics tool for hyphenated full-scan mass spectrometry data preprocessing. Anal. Chem. 81(8), 3079–3086 (2009).
  • De Vos RC , MocoS, LommenA, KeurentjesJJ, BinoRJ, HallRD. Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry. Nat. Protoc. 2(4), 778–791 (2007).
  • Luedemann A , StrassburgK, ErbanA, KopkaJ. TagFinder for the quantitative analysis of gas chromatography–mass spectrometry (GC–MS)-based metabolite profiling experiments. Bioinformatics24(5), 732–737 (2008).
  • Broeckling CD , ReddyIR, DuranAL, ZhaoX, SumnerLW. MET-IDEA: data extraction tool for mass spectrometry-based metabolomics. Anal. Chem. 78(13), 4334–4341 (2006).
  • Hiller K , HangebraukJ, JagerC, SpuraJ, SchreiberK, SchomburgD. MetaboliteDetector: comprehensive analysis tool for targeted and nontargeted GC/MS based metabolome analysis. Anal. Chem. 81(9), 3429–3439 (2009).
  • LECO. ChromaTOF software. LECO Inc., 1150 Blanchard St., Bellefonte, PA, USA 16823–8618 (2009).
  • Plumb R , Castro-PerezJ, GrangerJ, BeattieI, JoncourK, WrightA. Ultra-performance liquid chromatography coupled to quadrupole-orthogonal time-of-flight mass spectrometry. Rapid Commun. Mass Spectrom. 18(19), 2331–2337 (2004).
  • Wilson ID , PlumbR, GrangerJ, MajorH, WilliamsR, LenzEM. HPLC-MS-based methods for the study of metabonomics. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 817(1), 67–76 (2005).
  • Nordstrom A , WantE, NorthenT, LehtioJ, SiuzdakG. Multiple ionization mass spectrometry strategy used to reveal the complexity of metabolomics. Anal. Chem. 80(2), 421–429 (2008).
  • Robb DB , CoveyTR, BruinsAP. Atmospheric pressure photoionization: an ionization method for liquid chromatography–mass spectrometry. Anal. Chem. 72(15), 3653–3659 (2000).
  • Marchi I , RudazS, VeutheyJL. Atmospheric pressure photoionization for coupling liquid-chromatography to mass spectrometry: a review. Talanta78(1), 1–18 (2009).
  • Morris HR , PaxtonT, DellAet al. High sensitivity collisionally-activated decomposition tandem mass spectrometry on a novel quadrupole/orthogonal-acceleration time-of-flight mass spectrometer. Rapid Commun. Mass Spectrom. 10(8), 889–896 (1996).
  • Hu Q , NollRJ, LiH, MakarovA, HardmanM, Graham Cooks R. The Orbitrap: a new mass spectrometer. J. Mass Spectrom. 40(4), 430–443 (2005).
  • Marshall AG , HendricksonCL, JacksonGS. Fourier transform ion cyclotron resonance mass spectrometry: a primer. Mass Spectrom. Rev. 17(1), 1–35 (1998).
  • Yates JR , CociorvaD, LiaoL, ZabrouskovV. Performance of a linear ion trap-Orbitrap hybrid for peptide analysis. Anal. Chem. 78(2), 493–500 (2006).
  • Dunn WB , BroadhurstD, BrownMet al. Metabolic profiling of serum using ultra performance liquid chromatography and the LTQ-Orbitrap mass spectrometry system. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 871(2), 288–298 (2008).
  • Dunn WB . Current trends and future requirements for the mass spectrometric investigation of microbial, mammalian and plant metabolomes. Phys. Biol. 5(1), 11001 (2008).
  • t’Kindt R , AlaertsG, Vander Heyden Y, Deforce D, Van Bocxlaer J. Broad-spectrum separations in metabolomics using enhanced polar LC stationary phases: a dedicated evaluation using plant metabolites. J. Sep. Sci. 30(13), 2002–2011 (2007).
  • Bell DS , JonesAD. Solute attributes and molecular interactions contributing to “U-shape” retention on a fluorinated high-performance liquid chromatography stationary phase. J. Chromatogr. A1073(1–2), 99–109 (2005).
  • Yoshida H , YamazakiJ, OzawaS, MizukoshiT, MiyanoH. Advantage of LC–MS metabolomics methodology targeting hydrophilic compounds in the studies of fermented food samples. J. Agric. Food Chem. 57(4), 1119–1126 (2009).
  • Alpert AJ . Hydrophilic-interaction chromatography for the separation of peptides, nucleic acids and other polar compounds. J. Chromatogr. 499, 177–196 (1990).
  • Tolstikov VV , FiehnO. Analysis of highly polar compounds of plant origin: combination of hydrophilic interaction chromatography and electrospray ion trap mass spectrometry. Anal. Biochem. 301(2), 298–307 (2002).
  • Kamleh A , BarrettMP, WildridgeD, BurchmoreRJ, ScheltemaRA, WatsonDG. Metabolomic profiling using Orbitrap Fourier transform mass spectrometry with hydrophilic interaction chromatography: a method with wide applicability to analysis of biomolecules. Rapid Commun. Mass Spectrom. 22(12), 1912–1918 (2008).
  • Pesek JJ , MatyskaMT, FischerSM, SanaTR. Analysis of hydrophilic metabolites by high-performance liquid chromatography–mass spectrometry using a silica hydride-based stationary phase. J. Chromatogr. A1204(1), 48–55 (2008).
  • Callahan DL , SouzaDD, BacicA, RoessnerU. Profiling of polar metabolites in biological extracts using diamond hydride-based aqueous normal phase chromatography. J. Sep. Sci. 32(13), 2273–2280 (2009).
  • Pesek JJ , MatyskaMT, LooJA, FischerSM, SanaTR. Analysis of hydrophilic metabolites in physiological fluids by HPLC–MS using a silica hydride-based stationary phase. J. Sep. Sci. 32(13), 2200–2208 (2009).
  • Weisenberg SA , ButterfieldTR, FischerSM, RheeKY. Suitability of silica hydride stationary phase, aqueous normal phase chromatography for untargeted metabolomic profiling of Enterococcus faecium and Staphylococcus aureus. J. Sep. Sci. 32(13), 2262–2265 (2009).
  • SIELC Technologies. 65E Palatine Road, Suite 221, Prospect Heights, IL 60070, USA (2009).
  • Myint KT , AoshimaK, TanakaS, NakamuraT, OdaY. Quantitative profiling of polar cationic metabolites in human cerebrospinal fluid by reversed-phase nanoliquid chromatography/mass spectrometry. Anal. Chem. 81(3), 1121–1129 (2009).
  • Ceglarek U , LeichtleA, BrugelMet al. Challenges and developments in tandem mass spectrometry based clinical metabolomics. Mol. Cell Endocrinol. 301(1–2), 266–271 (2009).
  • Sawada Y , AkiyamaK, SakataAet al. Widely targeted metabolomics based on large-scale MS/MS data for elucidating metabolite accumulation patterns in plants. Plant Cell Physiol. 50(1), 37–47 (2009).
  • Hager JW , Le Blanc JC. High-performance liquid chromatography-tandem mass spectrometry with a new quadrupole/linear ion trap instrument. J. Chromatogr. A. 1020(1), 3–9 (2003).
  • Hager JW , Yves Le Blanc JC. Product ion scanning using a Q-q-Q linear ion trap (Q TRAP) mass spectrometer. Rapid Commun. Mass Spectrom. 17(10), 1056–1064 (2003).
  • Kitteringham NR , JenkinsRE, LaneCS, ElliottVL, ParkBK. Multiple reaction monitoring for quantitative biomarker analysis in proteomics and metabolomics. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 877(13), 1229–1239 (2009).
  • Katajamaa M , OresicM. Data processing for mass spectrometry-based metabolomics. J. Chromatogr. A. 1158(1–2), 318–328 (2007).
  • Tautenhahn R , BottcherC, NeumannS. Highly sensitive feature detection for high resolution LC/MS. BMC Bioinformatics9, 504 (2008).
  • Lange E , TautenhahnR, NeumannS, GroplC. Critical assessment of alignment procedures for LC–MS proteomics and metabolomics measurements. BMC Bioinformatics9, 375 (2008).
  • Peters S , van Velzen E, Janssen HG. Parameter selection for peak alignment in chromatographic sample profiling: objective quality indicators and use of control samples. Anal. BioAnal. Chem. 394(5), 1273–1281 (2009).
  • Sysi-Aho M , KatajamaaM, YetukuriL, OresicM. Normalization method for metabolomics data using optimal selection of multiple internal standards. BMC Bioinformatics8, 93 (2007).
  • Scholz M , FiehnO. SetupX – a public study design database for metabolomic projects. Pac. Symp. Biocomput. 2007, 169–180 (2007).
  • Wishart DS , TzurD, KnoxCet al. HMDB: the Human Metabolome Database. Nucleic Acids Res. 35, D521–D526 (2007).
  • Knox C , ShrivastavaS, StothardP, EisnerR, WishartDS. BioSpider: a web server for automating metabolome annotations. Pac. Symp. Biocomput. 2007, 145–156 (2007).
  • Koulman A , CaoM, FavilleM, LaneG, MaceW, RasmussenS. Semi-quantitative and structural metabolic phenotyping by direct infusion ion trap mass spectrometry and its application in genetical metabolomics. Rapid Commun. Mass Spectrom. 23(15), 2253–2263 (2009).
  • Ohta D , ShibataD, KanayaS. Metabolic profiling using Fourier-transform ion-cyclotron-resonance mass spectrometry. Anal. BioAnal. Chem. 389(5), 1469–1475 (2007).
  • Nakamura Y , KimuraA, SagaHet al. Differential metabolomics unraveling light/dark regulation of metabolic activities in Arabidopsis cell culture. Planta227(1), 57–66 (2007).
  • Oikawa A , NakamuraY, OguraTet al. Clarification of pathway-specific inhibition by Fourier transform ion cyclotron resonance/mass spectrometry-based metabolic phenotyping studies. Plant Physiol. 142(2), 398–413 (2006).
  • Han J , DanellRM, PatelJRet al. Towards high-throughput metabolomics using ultrahigh-field Fourier transform ion cyclotron resonance mass spectrometry. Metabolomics4(2), 128–140 (2008).
  • Takahashi H , KaiK, ShinboYet al. Metabolomics approach for determining growth-specific metabolites based on Fourier transform ion cyclotron resonance mass spectrometry. Anal. BioAnal. Chem. 391(8), 2769–2782 (2008).
  • Southam AD , PayneTG, CooperHJ, ArvanitisTN, ViantMR. Dynamic range and mass accuracy of wide-scan direct infusion nanoelectrospray fourier transform ion cyclotron resonance mass spectrometry-based metabolomics increased by the spectral stitching method. Anal. Chem. 79(12), 4595–4602 (2007).
  • Staack RF , VaresioE, HopfgartnerG. The combination of liquid chromatography/tandem mass spectrometry and chip-based infusion for improved screening and characterization of drug metabolites. Rapid Commun. Mass Spectrom. 19(5), 618–626 (2005).
  • Taylor NS , WeberRJM, SouthamADet al. A new approach to toxicity testing in Daphniamagna: application of high throughput FT-ICR mass spectrometry metabolomics. Metabolomics5(1), 44–58 (2009).
  • Karas M , HillenkampF. Laser desorption ionization of proteins with molecular masses exceeding 10.000 daltons. Anal. Chem. 60(20), 2299–2301 (1988).
  • Vaidyanathan S , GaskellS, GoodacreR. Matrix-suppressed laser desorption/ionisation mass spectrometry and its suitability for metabolome analyses. Rapid Commun. Mass Spectrom. 20(8), 1192–1198 (2006).
  • Wang JN , ZhouY, ZhuTY, WangX, GuoYL. Prediction of acute cellular renal allograft rejection by urinary metabolomics using MALDI–FTMS. J. Proteome Res. 7(8), 3597–3601 (2008).
  • Fraser PD , EnfissiEM, GoodfellowM, EguchiT, BramleyPM. Metabolite profiling of plant carotenoids using the matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Plant J. 49(3), 552–564 (2007).
  • Sun G , YangK, ZhaoZ, GuanS, HanX, GrossRW. Shotgun metabolomics approach for the analysis of negatively charged water-soluble cellular metabolites from mouse heart tissue. Anal. Chem. 79(17), 6629–6640 (2007).
  • Guo Z , HeL. A binary matrix for background suppression in MALDI–MS of small molecules. Anal. BioAnal. Chem. 387(5), 1939–1944 (2007).
  • Shroff R , RulisekL, DoubskyJ, SvatosA. Acid-base-driven matrix-assisted mass spectrometry for targeted metabolomics. Proc. Natl Acad. Sci. USA106(25), 10092–10096 (2009).
  • Peterson DS . Matrix-free methods for laser desorption/ionization mass spectrometry. Mass Spectrom. Rev. 26(1), 19–34 (2007).
  • Wei J , BuriakJM, SiuzdakG. Desorption-ionization mass spectrometry on porous silicon. Nature399(6733), 243–246 (1999).
  • Woo HK , NorthenTR, YanesO, SiuzdakG. Nanostructure-initiator mass spectrometry: a protocol for preparing and applying NIMS surfaces for high-sensitivity mass analysis. Nat. Protoc. 3(8), 1341–1349 (2008).
  • Northen TR , YanesO, NorthenMTet al. Clathrate nanostructures for mass spectrometry. Nature449(7165), 1033–1036 (2007).
  • Amantonico AF , GlausR, ZenobiR. Negative mode nanostructure-initiator mass spectrometry for detection of phosphorylated metabolites. Metabolomics DOI: 10.1007/s11306-009-0163-5 (2009) (Epub advance of print).
  • Caprioli RM , FarmerTB, GileJ. Molecular imaging of biological samples: localization of peptides and proteins using MALDI-TOF MS. Anal. Chem. 69(23), 4751–4760 (1997).
  • Cha S , SongZ, NikolauBJ, YeungES. Direct profiling and imaging of epicuticular waxes on Arabidopsis thaliana by laser desorption/ionization mass spectrometry using silver colloid as a matrix. Anal. Chem. 81(8), 2991–3000 (2009).
  • Cha S , YeungES. Colloidal graphite-assisted laser desorption/ionization mass spectrometry and MSn of small molecules. 1. Imaging of cerebrosides directly from rat brain tissue. Anal. Chem. 79(6), 2373–2385 (2007).
  • Zhang H , ChaS, YeungES. Colloidal graphite-assisted laser desorption/ionization MS and MS(n) of small molecules. 2. Direct profiling and MS imaging of small metabolites from fruits. Anal. Chem. 79(17), 6575–6584 (2007).
  • Cha S , ZhangH, IlarslanHIet al. Direct profiling and imaging of plant metabolites in intact tissues by using colloidal graphite-assisted laser desorption ionization mass spectrometry. Plant J. 55(2), 348–360 (2008).
  • Li Y , ShresthaB, VertesA. Atmospheric pressure molecular imaging by infrared MALDI mass spectrometry. Anal. Chem. 79(2), 523–532 (2007).
  • Li Y , ShresthaB, VertesA. Atmospheric pressure infrared MALDI imaging mass spectrometry for plant metabolomics. Anal. Chem. 80(2), 407–420 (2008).
  • Takats Z , WisemanJM, GologanB, CooksRG. Mass spectrometry sampling under ambient conditions with desorption electrospray ionization. Science306(5695), 471–473 (2004).
  • Cooks RG , OuyangZ, TakatsZ, WisemanJM. Detection technologies. Ambient mass spectrometry. Science311(5767), 1566–1570 (2006).
  • Jackson AU , WernerSR, TalatyNet al. Targeted metabolomic analysis of Escherichia coli by desorption electrospray ionization and extractive electrospray ionization mass spectrometry. Anal. Biochem. 375(2), 272–281 (2008).
  • Dill AL , IfaDR, ManickeNE, OuyangZ, CooksRG. Mass spectrometric imaging of lipids using desorption electrospray ionization. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. (2008).
  • Wiseman JM , IfaDR, SongQ, CooksRG. Tissue imaging at atmospheric pressure using desorption electrospray ionization (DESI) mass spectrometry. Angew Chem. Int. Ed. Engl. 45(43), 7188–7192 (2006).
  • Chen H , VenterA, CooksRG. Extractive electrospray ionization for direct analysis of undiluted urine, milk and other complex mixtures without sample preparation. Chem. Commun. (Camb.) (19), 2042–2044 (2006).
  • Gu H , ChenH, PanZet al. Monitoring diet effects via biofluids and their implications for metabolomics studies. Anal. Chem. 79(1), 89–97 (2007).
  • Cody RB , LarameeJA, DurstHD. Versatile new ion source for the analysis of materials in open air under ambient conditions. Anal. Chem. 77(8), 2297–2302 (2005).
  • Zhao Y , LamM, WuD, MakR. Quantification of small molecules in plasma with direct analysis in real time tandem mass spectrometry, without sample preparation and liquid chromatographic separation. Rapid Commun. Mass Spectrom. 22(20), 3217–3224 (2008).
  • Yu S , CrawfordE, TiceJ, MusselmanB, WuJT. Bioanalysis without sample cleanup or chromatography: the evaluation and initial implementation of direct analysis in real time ionization mass spectrometry for the quantification of drugs in biological matrixes. Anal. Chem. 81(1), 193–202 (2009).
  • Nemes P , VertesA. Laser ablation electrospray ionization for atmospheric pressure, in vivo, and imaging mass spectrometry. Anal. Chem. 79(21), 8098–8106 (2007).
  • Nemes P , BartonAA, LiY, VertesA. Ambient molecular imaging and depth profiling of live tissue by infrared laser ablation electrospray ionization mass spectrometry. Anal. Chem. 80(12), 4575–4582 (2008).
  • Nemes P , BartonAA, VertesA. Three-dimensional imaging of metabolites in tissues under ambient conditions by laser ablation electrospray ionization mass spectrometry. Anal. Chem. 81(16), 6668–6675 (2009).
  • Sripadi P , NazarianJ, HathoutY, HoffmanEP, VertesA. In vitro analysis of metabolites from the untreated tissue of Torpedo californica electric organ by mid-infrared laser ablation electrospray ionization mass spectrometry. Metabolomics5, 263–276 (2009).
  • Wold S , EsbensenK, GeladiP. Principal component analysis. Chemometrics Intel. Lab. Syst. 2, 37–52 (1987).
  • Wold S , RuheA, WoldH, DunnWI. The collinearity problem in linear regression. The partial least squares approach to generalized inverses. SIAM J. Sci. Comput. 5, 735–743 (1984).
  • Li X , LuX, TianJ, GaoP, KongH, XuG. Application of fuzzy c-means clustering in data analysis of metabolomics. Anal. Chem. 81(11), 4468–4475 (2009).
  • Trygg J , WoldS. Orthogonal projections to latent structures (O-PLS). J. Chemometrics119(16), 119–128 (2002).
  • Wiklund S , JohanssonE, SjostromLet al. Visualization of GC/TOF–MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class models. Anal. Chem. 80(1), 115–122 (2008).
  • van den Berg RA , HoefslootHC, WesterhuisJA, SmildeAK, van der Werf MJ. Centering, scaling, and transformations: improving the biological information content of metabolomics data. BMC Genomics7, 142 (2006).
  • Kind T , FiehnO. Metabolomic database annotations via query of elemental compositions: mass accuracy is insufficient even at less than 1 ppm. BMC Bioinformatics7, 234 (2006).
  • Kalisiak J , TraugerSA, KalisiakEet al. Identification of a new endogenous metabolite and the characterization of its protein interactions through an immobilization approach. J. Am. Chem. Soc. 131(1), 378–386 (2009).
  • Wang Y , XiaoJ, SuzekTO, ZhangJ, WangJ, BryantSH. PubChem: a public information system for analyzing bioactivities of small molecules. Nucleic Acids Res. 37, W623–W633 (2009).
  • Wishart DS , KnoxC, GuoACet al. HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res. 37, D603–D610 (2009).
  • Wishart DS , KnoxC, GuoACet al. DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Res. 36, D901–D906 (2008).
  • Wishart DS , KnoxC, GuoACet al. DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res. 34, D668–D672 (2006).
  • Fahy E , SudM, CotterD, SubramaniamS. LIPID MAPS online tools for lipid research. Nucleic Acids Res. 35, W606–W612 (2007).
  • Sud M , FahyE, CotterDet al. LMSD: LIPID MAPS structure database. Nucleic Acids Res. 35, D527–D532 (2007).
  • Brown M , DunnWB, DobsonPet al. Mass spectrometry tools and metabolite-specific databases for molecular identification in metabolomics. Analyst134(7), 1322–1332 (2009).
  • Kopka J , SchauerN, KruegerSet al. [email protected]: the Golm Metabolome Database. Bioinformatics21(8), 1635–1638 (2005).
  • Smith CA , O’MailleG, WantEJet al. METLIN: a metabolite mass spectral database. Ther. Drug Monit. 27(6), 747–751 (2005).
  • Matsuda F , Yonekura-SakakibaraK, NiidaR, KuromoriT, ShinozakiK, SaitoK. MS/MS spectral tag-based annotation of non-targeted profile of plant secondary metabolites. Plant J. 57(3), 555–577 (2009).
  • Cui Q , LewisIA, HegemanADet al. Metabolite identification via the Madison Metabolomics Consortium Database. Nat. Biotechnol. 26(2), 162–164 (2008).
  • Kanehisa M , GotoS, HattoriMet al. From genomics to chemical genomics: new developments in KEGG. Nucleic Acids Res. 34, D354–D357 (2006).
  • Karp PD , OuzounisCA, Moore-KochlacsCet al. Expansion of the BioCyc collection of pathway/genome databases to 160 genomes. Nucleic Acids Res. 33(19), 6083–6089 (2005).
  • Krummenacker M , PaleyS, MuellerL, YanT, KarpPD. Querying and computing with BioCyc databases. Bioinformatics21(16), 3454–3455 (2005).
  • Caspi R , FoersterH, FulcherCAet al. MetaCyc: a multiorganism database of metabolic pathways and enzymes. Nucleic Acids Res. 34, D511–D516 (2006).
  • Krieger CJ , ZhangP, MuellerLAet al. MetaCyc: a multiorganism database of metabolic pathways and enzymes. Nucleic Acids Res. 32, D438–D442 (2004).
  • Karp PD , RileyM, PaleySM, Pellegrini-TooleA. The MetaCyc Database. Nucleic Acids Res. 30(1), 59–61 (2002).
  • Romero P , WaggJ, GreenML, KaiserD, KrummenackerM, KarpPD. Computational prediction of human metabolic pathways from the complete human genome. Genome Biol. 6(1), R2 (2005).
  • Matthews L , GopinathG, GillespieMet al. Reactome knowledgebase of human biological pathways and processes. Nucleic Acids Res. 37, D619–D622 (2009).
  • Vastrik I , D’EustachioP, SchmidtEet al. Correction: reactome: a knowledge base of biologic pathways and processes. Genome Biol. 10(2), 402 (2009).
  • Vastrik I , D’EustachioP, SchmidtEet al. Reactome: a knowledge base of biologic pathways and processes. Genome Biol. 8(3), R39 (2007).

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