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Algorithm for processing raw mass spectrometric data to identify and quantitate complex lipid molecular species in mixtures by data-dependent scanning and fragment ion database searching.

ABSTRACT: We developed the Lipid Qualitative/Quantitative Analysis (LipidQA) software platform to identify and quantitate complex lipid molecular species in biological mixtures. LipidQA can process raw electronic data files from the TSQ-7000 triple stage quadrupole and LTQ linear ion trap mass spectrometers from Thermo-Finnigan and the Q-TOF hybrid quadrupole/time-of-flight instrument from Waters-Micromass and could readily be modified to accommodate data from others. The program processes multiple spectra in a few seconds and includes a deisotoping algorithm that increases the accuracy of structural identification and quantitation. Identification is achieved by comparing MS(2) spectra obtained in a data-dependent manner to a library of reference spectra of complex lipids that we have acquired or constructed from established fragmentation rules. The current form of the algorithm can process data acquired in negative or positive ion mode for glycerophospholipid species of all major head-group classes.

SUBMITTER: Song H

PROVIDER: S-EPMC2044497 | biostudies-literature | 2007 Oct

REPOSITORIES: biostudies-literature

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Algorithm for processing raw mass spectrometric data to identify and quantitate complex lipid molecular species in mixtures by data-dependent scanning and fragment ion database searching.

Song Haowei H Hsu Fong-Fu FF Ladenson Jack J Turk John J

Journal of the American Society for Mass Spectrometry 20070729 10

We developed the Lipid Qualitative/Quantitative Analysis (LipidQA) software platform to identify and quantitate complex lipid molecular species in biological mixtures. LipidQA can process raw electronic data files from the TSQ-7000 triple stage quadrupole and LTQ linear ion trap mass spectrometers from Thermo-Finnigan and the Q-TOF hybrid quadrupole/time-of-flight instrument from Waters-Micromass and could readily be modified to accommodate data from others. The program processes multiple spectr ...[more]

PMID: 17720531

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Project description:The accurate determination of mass isotopomer distributions (MID) is of great significance for stable isotope-labeling experiments. Most commonly, MIDs are derived from gas chromatography/electron ionization mass spectrometry (GC/EI-MS) measurements. The analysis of fragment ions formed during EI, which contain only specific parts of the original molecule can provide valuable information on the positional distribution of the label. The chemical formula of a fragment ion is usually applied to derive the correction matrix for accurate MID calculation. Hence, the correct assignment of chemical formulas to fragment ions is of crucial importance for correct MIDs. Moreover, the positional distribution of stable isotopes within a fragment ion is of high interest for stable isotope-assisted metabolomics techniques. For example, (13)C-metabolic flux analyses ((13)C-MFA) are dependent on the exact knowledge of the number and position of retained carbon atoms of the unfragmented molecule. Fragment ions containing different carbon atoms are of special interest, since they can carry different flux information. However, the process of mass spectral fragmentation is complex, and identifying the substructures and chemical formulas for these fragment ions is nontrivial. For that reason, we developed an algorithm, based on a systematic bond cleavage, to determine chemical formulas and retained atoms for EI derived fragment ions. Here, we present the fragment formula calculator (FFC) algorithm that can calculate chemical formulas for fragment ions where the chemical bonding (e.g., Lewis structures) of the intact molecule is known. The proposed algorithm is able to cope with general molecular rearrangement reactions occurring during EI in GC/MS measurements. The FFC algorithm is able to integrate stable isotope labeling experiments into the analysis and can automatically exclude candidate formulas that do not fit the observed labeling patterns.1 We applied the FFC algorithm to create a fragment ion repository that contains the chemical formulas and retained carbon atoms of a wide range of trimethylsilyl and tert-butyldimethylsilyl derivatized compounds. In total, we report the chemical formulas and backbone carbon compositions for 160 fragment ions of 43 alkylsilyl-derivatives of primary metabolites. Finally, we implemented the FFC algorithm in an easy-to-use graphical user interface and made it publicly available at http://www.ffc.lu .

Project description:BackgroundMany dose calculation algorithms for radiotherapy planning need to be configured for each clinical beam using pre-defined measurements. An optimization process adjusts the physical parameters able to estimate the energy released in the medium in any geometrical condition. This work investigates the impact of measured input data quality on the configuration of the type "c" Acuros-XB dose calculation algorithm in the Eclipse (Varian Medical Systems) treatment planning system.MethodsDifferent datasets were acquired with the BeamScan water phantom (PTW) to configure 6 MV beams, for both flattened (6X) and flattening filter free mode (6FFF) for a Varian TrueBeam: (i) a correct dataset measured using a Semiflex-3D ion chamber, (ii) a set in missing lateral scatter conditions (MLS), (iii) a set with incorrect effective point of measurement (EPoM), (iv) sets acquired with PinPoint-3D chamber, DiodeP, microDiamond detectors. The Acuros-XB dose calculation algorithm (version 15.6) was configured using the reference dataset, the sets measured with the different detectors, with intentional errors, and using the representative beam data (RBD) made available by the vendor. The physical parameters obtained from each optimization process (spectrum, mean radial energy, electron contamination), were analyzed and compared. Calculated data were finally compared against the input and reference measurements.ResultsConcerning the physical parameters, the configurations presenting the largest differences were the MLS conditions (mean radial energy) and the incorrect EPoM (electron contamination). The calculation doses relative to the input data present low accuracy, with mean differences > 2% in some conditions. The PinPoint-3D ion chamber presented lower accuracy for the 6FFF beam. Regarding the RBD, calculations compared well with the input data used for the configuration, but not with the reference data.ConclusionThe MLS conditions and the incorrect setting of the EPoM lead to erroneous configurations and should be avoided. The choice of an appropriate detector is important. Whenever the representative beam data is used, a careful check under more clinical geometrical conditions is advised.

Dataset Information

Algorithm for processing raw mass spectrometric data to identify and quantitate complex lipid molecular species in mixtures by data-dependent scanning and fragment ion database searching.

Publications

Algorithm for processing raw mass spectrometric data to identify and quantitate complex lipid molecular species in mixtures by data-dependent scanning and fragment ion database searching.

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