Computing positional isotopomer distributions from tandem mass spectrometric data

The isotopomer distributions of metabolites are invaluable pieces of information in the computation of the flux distribution in a metabolic network. We describe the use of tandem mass spectrometry with the daughter ion scanning technique in the discovery of positional isotopomer distributions (PID). This technique increases the possibilities of mass spectrometry since given the same fragment ions, it uncovers more information than the full scanning mode. The mathematics of the new technique is slightly more complicated than the techniques needed by full scanning mode methods. Our experiments, however, show that in practice the inadequacy of the fragmentation of amino acids in the tandem mass spectrometer does not allow uncovering the PID exactly even if the daughter ion scanning is used. The computational techniques have been implemented in a MATLAB application called PIDC (Positional Isotopomer Distribution Calculator).     

离子阱串联质谱仪质荷比测量误差统计分析

离子阱串联质谱仪是蛋白质组研究中一种高通量,高灵敏度的分析仪器。目前对影响离子阱质谱仪质荷比测量误差的因素和数据产出后系统误差的校正方法还没有系统的分析。利用两批蛋白质标准品的数据和统计方法分析了离子阱质谱仪质荷比测量误差的分布规律,对测量的质荷比和信号强度对测量误差的影响进行了分析。在此基础上,提出了一种对质谱数据进行系统误差再校正的方法和一种根据信号强度确定误差容限的模型。     

Robust estimating functions and bias correction for longitudinal data analysis

Robust methods are useful in making reliable statistical inferences when there are small deviations from the model assumptions. The widely used method of the generalized estimating equations can be "robustified" by replacing the standardized residuals with the M-residuals. If the Pearson residuals are assumed to be unbiased from zero, parameter estimators from the robust approach are asymptotically biased when error distributions are not symmetric. We propose a distribution-free method for correcting this bias. Our extensive numerical studies show that the proposed method can reduce the bias substantially. Examples are given for illustration.     

New tools for mass isotopomer data evaluation in (13)C flux analysis: mass isotope correction, data consistency checking, and precursor relationships

13C metabolic flux analysis (MFA) is based on carbon-labeling experiments where a specifically (13)C labeled substrate is fed. The labeled carbon atoms distribute over the metabolic network and the label enrichment of certain metabolic pools is measured by using different methods. Recently, MS methods have been dramatically improved-large and precise datasets are now available. MS data has to be preprocessed and corrected for natural stable mass isotopes. In this article we present (1). a new elegant method to correct MS measurement data for natural stable mass isotopes by infinite dimensional matrix calculus and (2). we statistically analyze and discuss a reconstruction of labeling pattern in metabolic precursors from biosynthesis molecules. Moreover, we establish a new method for consistency checking of MS spectra that can be applied for automatic error recognition in high-throughput flux analysis procedures. Preprocessing the measurement data changes their statistical properties which have to be considered in the subsequent parameter fitting process for (13)C MFA. We show that correcting for stable mass isotopes leads to rather small correlations. On the other hand, a direct reconstruction of a precursor labeling pattern from an aromatic amino acid measurement turns out to be critical. Reasonable results are only obtained if additional, independent information about the labeling of at least one precursor is available. A versatile MatLab tool for the rapid correction and consistency checking of MS spectra is presented. Practical examples for the described methods are also given.     

Microbead device for isolating biotinylated oligonucleotides for use in mass spectrometric analysis

We describe a prototypical device for isolating biotinylated oligonucleotides for use in mass spectrometric analysis. It consists of monomeric avidin-coated microbeads trapped in a pipette tip and has been used for genotyping single nucleotide polymorphisms (SNPs) with the previously developed solid phase capture-single base extension (SPC-SBE) method. The device reduces processing time for genotyping by SPC-SBE and allows direct spotting of sample for rapid analysis by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). In addition, it allows simultaneous processing of multiple samples and can be reused after regeneration of beads with no carryover effects. These results indicate that the microbead device is a low-cost tool that enhances sample cleanup prior to MS for SNP genotyping.     

A review on metabolic pathway analysis with emphasis on isotope labeling approach

The recent progress on metabolic systems engineering was reviewed based on our recent research results in terms of (1) metabolic signal flow diagram approach, (2) metabolic flux analysis (MFA) in particular with intracellular isotopomer distribution using NMR and/or GC-MS, (3) synthesis and optimization of metabolic flux distribution (MFD), (4) modification of MFD by gene manipulation and by controlling culture environment, (5) metabolic control analysis (MCA), (6) design of metabolic regulation structure, and (7) identification of unknown pathways with isotope tracing by NMR. The main characteristics of metabolic engineering is to treat metabolism as a network or entirety instead of individual reactions. The applications were made for poly-3-hydroxybutyrate (PHB) production usingRalstonia eutropha and recombinantEscherichia coli, lactate production by recombinantSaccharomyces cerevisiae, pyruvate production by vitamin auxotrophic yeastToluropsis glabrata, lysine production usingCorynebacterium glutamicum, and energetic analysis of photosynthesic microorganisms such as Cyanobateria. The characteristics of each approach were reviewed with their applications. The approach based on isotope labeling experiments gives reliable and quantitative results for metabolic flux analysis. It should be recognized that the next stage should be toward the investigation of metabolic flux analysis with gene and protein expressions to uncover the metabolic regulation in relation to genetic modification and/or the change in the culture condition.     

Metabolic-flux analysis of Saccharomyces cerevisiae CEN.PK113-7D based on mass isotopomer measurements of (13)C-labeled primary metabolites

Metabolic-flux analyses in microorganisms are increasingly based on (13)C-labeling data. In this paper a new approach for the measurement of (13)C-label distributions is presented: rapid sampling and quenching of microorganisms from a cultivation, followed by extraction and detection by liquid chromatography-mass spectrometry of free intracellular metabolites. This approach allows the direct assessment of mass isotopomer distributions of primary metabolites. The method is applied to the glycolytic and pentose phosphate pathways of Saccharomyces cerevisiae strain CEN.PK113-7D grown in an aerobic, glucose-limited chemostat culture. Detailed investigations of the measured mass isotopomer distributions demonstrate the accuracy and information-richness of the obtained data. The mass fractions are fitted with a cumomer model to yield the metabolic fluxes. It is estimated that 24% of the consumed glucose is catabolized via the pentose phosphate pathway. Furthermore, it is found that turnover of storage carbohydrates occurs. Inclusion of this turnover in the model leads to a large confidence interval of the estimated split ratio.     

Quantitative high-performance liquid chromatography/electrospray ionization tandem mass spectrometric analysis of 2- and 3-series prostaglandins in cultured tumor cells

This paper describes a rapid and simple technique for the simultaneous quantitative analysis of PGE(2), PGE(3), and other closely related prostaglandins from cultured cells using liquid chromatography/electrospray ionization tandem mass spectrometry. This method permits quantification of selected individual prostaglandins derived either from arachidonic acid (AA) or eicosapentaenoic acid (EPA) from cell extracts without tedious derivatization, lengthy sample preparation, and separation required by GC-MS- or HPLC-UV-based methods. The validation assessment showed that the quantitative determination is linear (r(2)>0.999) for both PGE(2) and PGE(3) in the range tested (1-500 ng/ml, 0.0028-1.4 microM) and a coefficient of variation lower than 10% was obtained for samples analyzed on 3 separate days. The detection limit was 2.5 pg for both PGE(2) and PGE(3). Extraction efficiency of PGE(2) and PGE(3) from cell suspensions ranged from 89.4 to 98.2%. As an application of the method, prostaglandins formed by EPA in human lung cancer A549 cells were determined. A 62% reduction of PGE(2) formation was noted when A549 cells were treated with 10 microM of EPA. Concomitantly, EPA increased formation of PGE(3) by 10-fold in A549 cells. This is the first report that unequivocally demonstrates that EPA can be converted to PGE(3) by cyclooxygenase in human cancer cells.     

Analytical strategies for the direct mass spectrometric analysis of steroid and corticosteroid phase II metabolites

The use of steroid hormones as growth promoters remains illegal in Europe. A classical approach used to control their utilization consists to measure the parent drug in target biological matrices. However, this strategy may fail when the parent drug is submitted to extensive metabolism reactions. For urine and tissue samples, chemical or enzymatic hydrolysis is usually applied in order to deconjugate glucuronide and sulfate phase II metabolites. But this treatment lead to the loss of information such as nature and relative proportions of the different conjugated forms, which can be useful, for example, to discriminate an endogenous production from an exogenous administration for natural hormones, or for other clinical or biochemical specific applications. For these purposes, direct measurement of conjugated metabolites using liquid chromatography-tandem mass spectrometry may represent a solution of choice. In this context, the mass spectrometric behavior of 14 steroid and corticosteroid phase II metabolites after electrospray ionization was investigated. Their fragmentation pathways in tandem mass spectrometry revealed some specificities within the different group of conjugates. A specific acquisition program (MRM mode) was developed for the unambiguous identification of the studied reference compounds. A more generic method (Parent Scan mode) was also developed for fishing approaches consisting to monitor several fragment ions typical of each conjugate class. A reverse phase HPLC procedure was also proposed for efficient retention and separation of the studied compounds. Finally, a protocol based on quaternary amine SPE was developed, permitting the separation of free, glucuronide, and sulfate fractions. Preliminary results on biological samples demonstrated the suitability of this analytical strategy for direct measurement of dexamethasone glucuronide and sulfate residues in bovine urine.     

Membrane inlet mass spectrometric analysis of N-isotope labelling for aquatic denitrification studies

Abstract: Techniques are described for measuring the isotope distribution in dissolved nitrate and N₂ using membrane inlet mass spectrometry, which allows several gases to be measured in a water sample without the need for any separation steps. The isotope distribution in dissolved nitrate was measured using denitrifying Pseudomonas nautica to reduce the nitrate to N₂ which was then measured by mass spectrometry. Pseudomonas nautica NCIMB 1967 was easily grown in nitrate-limited continuous culture minimising intra- or extracellular nitrate or nitrite pools, and the bioassay was tolerant of a range of salinities. The precision of the bioassay when measuring samples with high ¹⁵NO₃⁻ contents (0.5 μmol) was 0.05 atom%; with 0.1 μmol ¹⁵NO₃⁻, the precision was around 0.2 atom%. Differences in labelling of N₂ in preserved samples obtained from ¹⁵NO₃⁻ incubations of water-covered sediment cores were measured on parallel samples with membrane inlet MS and GC-MS. The membrane inlet technique was accurate but the precision on ratio measurements was lower than by GC-MS.     

On the Estimation of the Nearest Neighbour Distribution,G(t), for Point Processes

A new method is proposed for estimating G(t), the distribution function of the distance from an object to its nearest neighbour in a spatial point process. The new method makes more complete use of the information available and has a smaller mean squared error than that of the existing alternatives. The method appears equally effective with random, clustered and regular patterns.     

Carboxy group derivatization for enhanced electron‐transfer dissociation mass spectrometric analysis of phosphopeptides

A novel strategy based on carboxy group derivatization is presented for specific characterization of phosphopeptides. By tagging the carboxy group with 1‐(2‐pyrimidyl) piperazine (PP), the ion charge states of phosphopeptides can be largely enhanced, showing great advantages for sequencing phosphorylated peptides with electron‐transfer dissociation MS. Besides, after PP‐derivatization, most non‐specific bindings can be avoided by eliminating the interaction between the carboxy group and TiO₂, greatly improving the specificity of TiO₂‐based phosphopeptide enrichment strategy. Moreover, being tagged with a hydrophobic group, the retention time of phosphopeptides in RPLC can be prolonged, overcoming the difficulty of separating phosphopeptides in RPLC‐based approach. Together with several other advantages, such as ease of handling, rapid reaction time, broad applicability and good reproducibility, this PP‐derivatization method is promising for high‐throughput phosphoproteome research.     

Derivatization of carbohydrates for chromatographic,electrophoretic and mass spectrometric structure analysis

Carbohydrates, either alone or as constituents of glycoproteins, proteoglycans and glycolipids, are mediators of several cellular events and (patho)physiological processes. Progress in the "glycome" project is closely related to the analytical tools used to define carbohydrate structure and correlate structure with function. Chromatography, electrophoresis and mass spectrometry are the indispensable analytical tools of the on-going research. Carbohydrate derivatization is required for most of these analytical procedures. This review article gives an overview of derivatization methods of carbohydrates for their liquid chromatographic and electrophoretic separation, as well as the mass spectrometric characterization. Pre-column and on-capillary derivatization methods are presented with special emphasis on the derivatization of large carbohydrates.     

A liquid chromatography-tandem mass spectrometric method for quantitative determination of native 5-methyltetrahydrofolate and its polyglutamyl derivatives in raw vegetables

Folate deficiency is a prevalent phenomenon worldwide especially in underprivileged countries. Polyglutamyl 5-methyltetrahydrofolate (5MTHF) species are the naturally occurring principle folate in store-bought vegetables. Here we report a simple and complete extraction method for the determination of native polyglutamyl 5-methyltetrahydrofolate in vegetables using high performance liquid chromatography with tandem mass spectrometric detection (HPLC-MS/MS). Coarsely chopped samples (18 different vegetables) were steamed to inactivate glutamylase enzymes and liberate folate from binding proteins and extracted in a reducing buffer with (13)C(5) 5MTHF stable isotope added as internal standard. The polyglutamyl 5-methyltetrahydrofolate species were separated in 9 min on a C(18) column using a reversed phase system. HPLC eluate was interfaced with a triple quadrupole mass spectrometer operated in electrospray positive mode. The respective pseudomolecular cation of each polyglutamyl 5-methyltetrahydrofolate species was selected for fragmentation to a common daughter ion for detection. We quantitated polyglutamyl 5-methyltetrahydrofolate in store-bought vegetables from families Brassicaceae, Asteraceae and Amaranthaceae (including mustard greens, romaine lettuce and Swiss chard) of which most have not been quantitated previously. Most vegetables from Asteraceae and those from Amaranthaceae contained similar amounts of monoglutamyl 5MTHF and polyglutamyl 5MTHF while Brassicaceae were dominated by polyglutamyls and endive species (Asteraceae) contained mainly monoglutamyl 5MTHF. The precision of the method for the various polyglutamyl 5-methyltetrahydrofolate forms was 1-9% RSD, recovery 84-91%, limit of detection 64-658 fmol and limit of quantitation 193-1994 fmol. Herein we describe a rapid, sensitive and selective HPLC-MS/MS technique to quantitate polyglutamyl 5-methyltetrahydrofolate species. This method may be suitable for analyzing the polyglutamyl 5-methyltetrahydrofolate profile of inherent folates in a wide range of leafy green vegetables.     

Conditional estimation for generalized linear models when covariates are subject-specific parameters in a mixed model for longitudinal measurements

The relationship between a primary endpoint and features of longitudinal profiles of a continuous response is often of interest, and a relevant framework is that of a generalized linear model with covariates that are subject-specific random effects in a linear mixed model for the longitudinal measurements. Naive implementation by imputing subject-specific effects from individual regression fits yields biased inference, and several methods for reducing this bias have been proposed. These require a parametric (normality) assumption on the random effects, which may be unrealistic. Adapting a strategy of Stefanski and Carroll (1987, Biometrika74, 703-716), we propose estimators for the generalized linear model parameters that require no assumptions on the random effects and yield consistent inference regardless of the true distribution. The methods are illustrated via simulation and by application to a study of bone mineral density in women transitioning to menopause.     

Bayesian analysis of mass spectrometry proteomic data using wavelet-based functional mixed models

Summary .   In this article, we apply the recently developed Bayesian wavelet-based functional mixed model methodology to analyze MALDI-TOF mass spectrometry proteomic data. By modeling mass spectra as functions, this approach avoids reliance on peak detection methods. The flexibility of this framework in modeling nonparametric fixed and random effect functions enables it to model the effects of multiple factors simultaneously, allowing one to perform inference on multiple factors of interest using the same model fit, while adjusting for clinical or experimental covariates that may affect both the intensities and locations of peaks in the spectra. For example, this provides a straightforward way to account for systematic block and batch effects that characterize these data. From the model output, we identify spectral regions that are differentially expressed across experimental conditions, in a way that takes both statistical and clinical significance into account and controls the Bayesian false discovery rate to a prespecified level. We apply this method to two cancer studies.     

Discrimination of Francisella tularensis subspecies using surface enhanced laser desorption ionization mass spectrometry and multivariate data analysis

Francisella tularensis causes the zoonotic disease tularemia, and is considered a potential bioterrorist agent due to its extremely low infection dose and potential for airborne transmission. Presently, F. tularensis is divided into four subspecies; tularensis, holarctica, mediasiatica and novicida. Phenotypic discrimination of the closely related subspecies with traditional methods is difficult and tedious. Furthermore, the results may be vague and they often need to be complemented with virulence tests in animals. Here, we have used surface enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) to discriminate between the four subspecies of F. tularensis. The method is based on the differential binding of protein subsets to chemically modified surfaces. Bacterial thermolysates were added to anionic, cationic, and copper ion-loaded immobilized metal affinity SELDI chip surfaces. After binding, washing, and SELDI-TOF-MS different protein profiles were obtained. The spectra generated from the different surfaces were then used to characterize each bacterial strain. The results showed that the method was reproducible, with an average intensity variation of 21%, and that the mass precision was good (300-450 ppm). Moreover, in subsequent cluster analysis and principal component analysis (PCA) data for the analyzed Francisella strains grouped according to the recognized subspecies. Partial least squares-discriminant analysis (PLS-DA) of the protein profiles also identified proteins that differed between the strains. Thus, the protein profiling approach based on SELDI-TOF-MS holds great promise for rapid high-resolution phenotypic identification of bacteria.     

Chiral analysis of ammuxetine enantiomers in dog plasma using online SPE/liquid chromatography with tandem mass spectrometric detection after precolumn chiral derivatization

Ammuxetine (AMT), a novel chiral antidepressant candidate compound, exhibits better antidepression effects than duloxetine in different animal models. In this article, a chiral derivatization method, combined with online solid phase extraction (online SPE) and liquid chromatography–tandem mass spectrometry (LC–MS/MS), was developed for the chiral separation of AMT enantiomers after administration of racemic AMT to dogs. The derivatization reaction employed 2,3,4,6‐tetra‐O‐acetyl‐b‐glucopyr‐anosyl isothiocyanate (GITC) as a precolumn chiral derivatization reagent. A SPE column Retain PEP Javelin (10 × 2.1 mm) was used to remove proteins and other impurities in plasma samples. The enantiomeric derivatives were separated on a ZORBAX SB‐C₁₈ column (50 × 2.1 mm × 3.5 μm) with an isocratic elution procedure. The selected multiple reaction monitoring mode of the positive ion was performed and the parent to the product transitions m/z 681.0/543.1 and m/z 687.4/543.1 were used to measure the derivatives of AMT and duloxetine (internal standard) with electrospray ionization. The method was validated in terms of specificity, linearity, sensitivity, precision, accuracy, matrix effect, and stability. The method was applied to a pharmacokinetics study of AMT racemate in dogs. The results suggested that the pharmacokinetic of AMT enantiomers might be stereoselective in dogs.     

INCA 2.0: A tool for integrated,dynamic modeling of NMR- and MS-based isotopomer measurements and rigorous metabolic flux analysis

Metabolic flux analysis (MFA) combines experimental measurements and computational modeling to determine biochemical reaction rates in live biological systems. Advancements in analytical instrumentation, such as nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), have facilitated chemical separation and quantification of isotopically enriched metabolites. However, no software packages have been previously described that can integrate isotopomer measurements from both MS and NMR analytical platforms and have the flexibility to estimate metabolic fluxes from either isotopic steady-state or dynamic labeling experiments. By applying physiologically relevant cardiac and hepatic metabolic models to assess NMR isotopomer measurements, we herein test and validate new modeling capabilities of our enhanced flux analysis software tool, INCA 2.0. We demonstrate that INCA 2.0 can simulate and regress steady-state ¹³C NMR datasets from perfused hearts with an accuracy comparable to other established flux assessment tools. Furthermore, by simulating the infusion of three different ¹³C acetate tracers, we show that MFA based on dynamic ¹³C NMR measurements can more precisely resolve cardiac fluxes compared to isotopically steady-state flux analysis. Finally, we show that estimation of hepatic fluxes using combined ¹³C NMR and MS datasets improves the precision of estimated fluxes by up to 50%. Overall, our results illustrate how the recently added NMR data modeling capabilities of INCA 2.0 can enable entirely new experimental designs that lead to improved flux resolution and can be applied to a wide range of biological systems and measurement time courses.