Conference Program - ABRF 2011 - Association of Biomolecular ...

Poster Abstracts222 UHR-Q-TOF Analysis Can AddressCommon Challenges in Targeted andUntargeted MetabolomicsA. Barsch 1 , G. Zurek 1 , D. Krug 2 , R. Müller 21Bruker Daltonics, Bremen, Germany; 2 Universitätdes Saarlandes, Saarbrücken, GermanyHere, we present an ESI-UHR-Q-TOF based analysis of myxobacterialsecondary metabolites, which permits to solve several challengesfrequently encountered in metabolite profiling studies. Myxobacteriaare promising producers of natural products exhibiting potentbiological activities, and several myxobacterial metabolites are currentlyunder investigation as potential leads for novel drugs. However, themyxobacteria are also a striking example for the divergence betweenthe genetic capacity for the production of secondary metabolitesand the number of compounds that could be characterised to date.Wildtype and mutant strains were analyzed concerning the productionpatterns of known metabolites and with regard to the discoveryof new metabolites. Sample throughput: Since mass accuracy andresolution of TOF instruments are independent of the acquisition rate,they are perfectly suited for a coupling to UHPLC separations. Thesehyphenations enable a reduction of analysis time in combination witha high chromatographic resolution and therefore permit an increasedsample throughput. The UHR-TOF analysis revealed that an acquisitionrate of up to 20Hz did not compromise the achieved mass accuracy orresolution. Targeted and untargeted metabolite profiling: Acquisition offull scan accurate mass spectra enable the targeted screening for knowncompounds e.g. from the class of DKxanthenes based on very selectivehigh resolution EIC (hrEIC) traces with small mass windows of 1.0 - 0.5mDa. A comparison of several datasets following a “comprehensivefeature extraction” combined with a statistical analysis permits anuntargeted discovery of novel biomarkers using the same data filesas for the targeted analysis. Identification: Even a mass accuracy of 0.1ppm is not sufficient for an unambiguous formula identification for m/zvalues above 500. A combination of accurate mass data and isotopicpattern information in MS and MS/MS spectra can extend this m/z rangefor reliable formula suggestions. Examples for novel metabolites fromMyxobacteria will be shown.223 Metabolic Profiling of aCorynebacterium Glutamicum DeltaprpD2by GC-APCI High ResolutionQ-TOF AnalysisA. Barsch 1 , G. Zurek 1 , M. Persike 2 , J. Plassmeier 2 ,K. Niehaus 21Bruker Daltonik GmbH, Bremen, Germany;2Centrum für Biotechnologie, Universität Bielefeld,GermanyMetabolomics studies based on Gas chromatography -Massspectrometry (GC-MS) are well established and typically employelectron impact (EI) ionisation. Target compounds of interest canbe identified by comparison to commercial or public databases.Unfortunately, many possible biomarkers detected in metabolicprofiling experiments cannot be identified due to the lack of referencespectra for a majority of biologically relevant compounds. Therefore,many possible biomarkers remain “unknowns” up till now. Hyphenatinggas chromatography with high resolution TOF-MS technology with softatmospheric pressure ionisation (APCI) can preserve the molecularion information and delivers accurate mass and isotopic patterninformation. This data enables a sum formula generation for knownand unknown target compounds.Additionally, optionally acquired MS/MS data can extend the capabilities for structural elucidation. Massaccuracy, resolution and isotopic fidelity are independent of the TOF-MS acquisition rate. Therefore, these instruments can be coupled to gaschromatography, which typically delivers narrow peak width requiringfast MS scan speeds. Corynebactrium glutamicum, a gram positive, nontoxicbacterium, is used in the industrial production of amino acids likelysine and glutamate. C. glutamicum can be grown on different carbonsources. Glucose is metabolised via glycolysis and the tricarboxylic acid(TCA) cycle, whereas propionate is catabolised through the methylcitricacid pathway. The prpD2 gene encodes a 2-methylcitrate dehydratasewhich is involved in the degradation of propionate. Metabolic profilingof Corynebacterium glutamicum delta-prpD2 extracts of cells grownon glucose or glucose and propionate analyzed by GC-APCI-TOF-MSrevealed several compounds elevated in cells grown on propionate.Identification of 2-methylcitric acid and alanine using accurate massand isotopic pattern information in MS and MS/MS spectra provided aproof of concept for the identification of target compounds using highresolution MS technology.224 Biomarker Discovery Using NewMetabolomics Software forAutomated Processing of HighResolution LC-MS DataD. Peake 1 , S. Hnatyshyn 2 ; M. Reily 2 ; P. Shipkova 2 ;T. McClure 1 ; M. Sanders 11Thermo Fisher Scientific, San Jose, CA, UnitedStates; 2 Bristol Myers Squibb, Princeton, NJ, UnitedStatesRobust biomarkers of target engagement and efficacy are required indifferent stages of drug discovery. Liquid chromatography coupledto high resolution mass spectrometry provides sensitivity, accuracyand wide dynamic range required for identification of endogenousmetabolites in biological matrices. LCMS is widely-used tool forbiomarker identification and validation. Typical high resolution LCMSprofiles from biological samples may contain greater than a millionmass spectral peaks corresponding to several thousand endogenousmetabolites. Reduction of the total number of peaks, componentidentification and statistical comparison across sample groups remainsto be a difficult and time consuming challenge. Blood samples fromfourgroups of rats (male vs. female, fully satiated and food deprived)were analyzed using high resolution accurate mass (HRAM) LCMS.All samples were separated using a 15 minute reversed-phase C18LC gradient and analyzed in both positive and negative ion modes.Data was acquired using 15K resolution and 5ppm mass measurementaccuracy. The entire data set was analyzed using software developedin collaboration between Bristol Meyers Squibb and Thermo FisherScientific to determine the metabolic effects of food deprivationon rats. Metabolomic LC-MS data files are extraordinarily complexand appropriate reduction of the number of spectral peaks viaidentification of related peaks and background removal is essential. Asingle component such as hippuric acid generates more than 20 relatedpeaks including isotopic clusters, adducts and dimers. Plasma andurine may contain 500-1500 unique quantifiable metabolites. Noisefiltering approaches including blank subtraction were used to reducethe number of irrelevant peaks. By grouping related signals such asisotopic peaks and alkali adducts, data processing was greatly simplifiedby reducing the total number of components by 10-fold. The softwareprocesses 48 samples inunder 60minutes. Principle ComponentAnalysis showed substantial differences in endogenous metabolites94 • ABRF 2011 — Technologies to Enable Personalized Medicine