Alignment of high resolution mass spectra: development of a heuristic approach for metabolomics

One of the challenges of using mass spectrometry for metabolomic analyses of samples consisting of thousands of compounds is that of peak identification and alignment. This paper addresses the issue of aligning mass spectral data from different samples in order to determine average component m/z peak values. The alignment scheme developed takes the instrument m/z measurement error into consideration in order to heuristically align two or more samples using a technique comparable to automated visual inspection and alignment. The results obtained using mass spectral profiles of replicate human urine samples suggest that this heuristic alignment approach is more efficient than other approaches using hierarchical clustering algorithms. The output consists of an average m/z and intensity value for the spectral components together with the number of matches from the different samples. One of the major advantages of using this alignment strategy is that it eliminates the boundary problem that occurs when using predetermined fixed bins to identify and combine peaks for averaging and the efficient runtime allows large datasets to be processed quickly.     

Physiological and environmental parameters associated with mass spectrometry-based salivary metabolomic profiles

Mass spectrometry (MS)-based metabolomic methods enable simultaneous profiling of hundreds of salivary metabolites, and may be useful to diagnose a wide range of diseases using saliva. However, few studies have evaluated the effects of physiological or environmental factors on salivary metabolomic profiles. Therefore, we used capillary electrophoresis-MS to analyze saliva metabolite profiles in 155 subjects with reasonable oral hygiene, and examined the effects of physiological and environmental factors on the metabolite profiles. Overall, 257 metabolites were identified and quantified. The global profiles and individual metabolites were evaluated by principle component analysis and univariate tests, respectively. Collection method, collection time, sex, body mass index, and smoking affected the global metabolite profiles. However, age also might contribute to the bias in sex and collection time. The profiles were relatively unaffected by other parameters, such as alcohol consumption and smoking, tooth brushing, or the use of medications or nutritional supplements. Temporomandibular joint disorders had relatively greater effects on salivary metabolites than other dental abnormalities (e.g., stomatitis, tooth alignment, and dental caries). These findings provide further insight into the diversity and stability of salivary metabolomic profiles, as well as the generalizability of disease-specific biomarkers.     

Development of a metabolomic approach based on urine samples and direct infusion mass spectrometry

The analysis of urine by direct infusion mass spectrometry suffers from ion suppression due to its high salt content and inter-sample variability caused by the differences in urine volume between persons. Thus, urine metabolomics requires a careful selection of the sample preparation procedure and a normalization strategy to deal with these problems. Several approaches were tested for metabolomic analysis of urine samples by direct infusion electrospray mass spectrometry (DI–ESI–MS), including solid phase extraction, liquid–liquid extraction, and sample dilution. In addition, normalization of results based on conductivity values and statistical treatment was performed to minimize sample variability. Both urine dilution and solid phase extraction with mixed mode sorbent considerably reduced the salt content in urine, providing comprehensive metabolomic fingerprints. Moreover, statistical data normalization enabled the correction of inter-sample physiological variability, improving the quality of results obtained. Therefore, high-throughput DI–ESI–MS fingerprinting of urine samples can be achieved with simple pretreatment procedures allowing the use of this noninvasive sampling in metabolomics. Finally, the optimized approach was tested in a pilot metabolomic investigation of urine samples from transgenic mice models of Alzheimer’s disease (APP/PS1) in order to illustrate the potential of the methodology.     

Mass appeal: metabolite identification in mass spectrometry-focused untargeted metabolomics

Metabolomics has advanced significantly in the past 10 years with important developments related to hardware, software and methodologies and an increasing complexity of applications. In discovery-based investigations, applying untargeted analytical methods, thousands of metabolites can be detected with no or limited prior knowledge of the metabolite composition of samples. In these cases, metabolite identification is required following data acquisition and processing. Currently, the process of metabolite identification in untargeted metabolomic studies is a significant bottleneck in deriving biological knowledge from metabolomic studies. In this review we highlight the different traditional and emerging tools and strategies applied to identify subsets of metabolites detected in untargeted metabolomic studies applying various mass spectrometry platforms. We indicate the workflows which are routinely applied and highlight the current limitations which need to be overcome to provide efficient, accurate and robust identification of metabolites in untargeted metabolomic studies. These workflows apply to the identification of metabolites, for which the structure can be assigned based on entries in databases, and for those which are not yet stored in databases and which require a de novo structure elucidation.

     

Complexity and pitfalls of mass spectrometry-based targeted metabolomics in brain research

Current quantitative metabolomic research in brain tissue is challenged by several analytical issues. To compare data of metabolite pattern, ratios of individual metabolite concentrations and composed classifiers characterizing a distinct state, standardized workup conditions, and extraction medium are crucial. Differences in physicochemical properties of individual compounds and compound classes such as polarity determine extraction yields and, thus, ratios of compounds with varying properties. Also, variations in suppressive effects related to coextracted matrix components affect standards or references and their concentration-dependent responses.The selection of a common tissue extraction protocol is an ill-posed problem because it can be regarded as a multiple objective decision depending on factors such as sample handling practicability, measurement precision, control of matrix effects, and relevance of the chemical assay. This study systematically evaluates the impact of extraction solvents and the impact of the complex brain tissue on measured metabolite levels, taking into account ionization efficiency as well as challenges encountered in the trace-level quantification of the analytes in brain matrices. In comparison with previous studies that relied on nontargeted platforms, consequently emphasizing the global behavior of the metabolomic fingerprint, here we focus on several series of metabolites spanning over extensive polarity, concentration, and molecular mass ranges.     

Simultaneous acquisition of PAR and PAIN spectra

We present a scheme that allows the simultaneous detection of PAR and PAIN correlation spectra in a single two-dimensional experiment. For both spectra, we obtain almost the same signal-to-noise ratio as if a PAR or PAIN spectrum is recorded separately, which in turn implies that one of the spectra may be considered additional information for free. The experiment is based on the observation that in a PAIN experiment, the PAR condition is always also fulfilled. The performance is demonstrated experimentally using uniformly ¹³C,¹⁵N-labeled samples of N–f–MLF–OH and ubiquitin.     

Gas chromatography time-of-flight mass spectrometry based metabolomic approach to evaluating toxicity of triptolide

Metabolomics allows high-throughput analysis of low-molecular-weight compounds in biofluids that reflect the physiological status and biochemical metabolism of living systems. Hence it has the potential to evaluate toxicity and clarifies the metabolism-related toxic mechanisms. In this study a promising candidate drug parent, triptolide, was given to Sprague?CDawley rats as a model toxicant at a single dose of 0.6, or 2.4?mg/kg, i.g. Both routine biochemical assays and histopathological inspection showed time-dependent hepatic toxicity at the higher dose, but no obvious toxicity at the lower dose. Meanwhile, serum metabolome was profiled using the non-targeted metabolomic tool, gas chromatography time-of-flight mass spectrometry. Based on the acquired metabolomic data, mathematical models were calculated and the metabolic patterns of serum were evaluated using projection to latent structure-discriminant analysis. The relative distance of each treated group from the normal control was calculated to provide a measure of toxicity. Treatment with triptolide at either the higher or lower dose caused deviations in the metabolic pattern and resulted in perturbation of taurine, creatinine, free fatty acids, ??-hydroxybutyrate, tricarboxylic acid cycle intermediates, and amino acids. This finding indicates the dysfunction of ??-oxidation of free fatty acids and impairment of the mitochondria and confirms the hepatic toxicity of triptolide. The identified toxic markers and the calculated relative distance values quantitatively demonstrated dose- and time-dependent toxicity, whereas the scores plot of the model provided the qualitative information. The metabolomic approach was non-invasive and more sensitive than routine toxic assessment, and the results of both methods correlated well.     

Global analysis of metabolites in rat and human urine based on gas chromatography/time-of-flight mass spectrometry

Sediment in urine may contain low-molecular-weight compounds that should be included in the analysis. To date, no systematic investigation has addressed this issue. We investigated three primary factors that influence the extraction efficiency of metabolites during preparation of urine samples for metabolomic research: centrifugation, pH, and extraction solvents. Obtained with the use of gas chromatography/time-of-flight mass spectrometry (GC/TOFMS) technique and principal component analysis (PCA), our results indicate that (1) conventional centrifugation causes an apparent loss of some metabolites, indicating that urine samples for metabolomic research should not be centrifuged before procedures are undertaken to recover the metabolites; (2) pH adjustment has a large impact on the recovery of metabolites and is therefore not encouraged; (3) with design of experiment analysis, methanol and water yield the optimal extraction efficiency. Differences between rat and human urine were observed and are discussed. Ninety-nine metabolites identified in rat and human urine are presented. An efficient protocol is proposed for the pretreatment of urine samples.     

Metabolite-based clustering and visualization of mass spectrometry data using one-dimensional self-organizing maps

Background  

One of the goals of global metabolomic analysis is to identify metabolic markers that are hidden within a large background of data originating from high-throughput analytical measurements. Metabolite-based clustering is an unsupervised approach for marker identification based on grouping similar concentration profiles of putative metabolites. A major problem of this approach is that in general there is no prior information about an adequate number of clusters.     

Metabolomics study on the toxicity of aconite root and its processed products using ultraperformance liquid-chromatography/electrospray-ionization synapt high-definition mass spectrometry coupled with pattern recognition approach and ingenuity pathways analysis

The mother and lateral root of Aconitum carmichaelii Debx, named "Chuanwu" (CW) and "Fuzi", respectively, has been used to relieve joint pain and treat rheumatic diseases for over 2000 years. However, it has a very narrow therapeutic range, and the toxicological risk of its usage remains very high. The traditional Chinese processing approach, Paozhi (detoxifying measure),can decompose poisonous Aconitum alkaloids into less or nontoxic derivatives and plays an important role in detoxification. The difference in metabolomic characters among the crude and processed preparations is still unclear, limited by the lack of sensitive and reliable biomarkers. Therefore, this paper was designed to investigate comprehensive metabolomic characters of the crude and its processed products by UPLC-Q-TOF-HDMS combined with pattern recognition methods and ingenuity pathway analysis (IPA). The significant difference in metabolic profiles and changes of metabolite biomarkers of interest between the crude and processed preparations were well observed. The underlying regulations of Paozhi-perturbed metabolic pathways are discussed according to the identified metabolites, and four metabolic pathways are identified using IPA. The present study demonstrates that metabolomic analysis could greatly facilitate and provide useful information to further comprehensively understand the pharmacological activity and potential toxicity of processed Aconite roots in the clinic.     

Towards high-throughput metabolomics using ultrahigh-field Fourier transform ion cyclotron resonance mass spectrometry

With unmatched mass resolution, mass accuracy, and exceptional detection sensitivity, Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS) has the potential to be a powerful new technique for high-throughput metabolomic analysis. In this study, we examine the properties of an ultrahigh-field 12-Tesla (12T) FTICR-MS for the identification and absolute quantitation of human plasma metabolites, and for the untargeted metabolic fingerprinting of inbred-strain mouse serum by direct infusion (DI). Using internal mass calibration (mass error ≤1 ppm), we determined the rational elemental compositions (incorporating unlimited C, H, N and O, and a maximum of two S, three P, two Na, and one K per formula) of approximately 250 out of 570 metabolite features detected in a 3-min infusion analysis of aqueous extract of human plasma, and were able to identify more than 100 metabolites. Using isotopically-labeled internal standards, we were able to obtain excellent calibration curves for the absolute quantitation of choline with sub-pmol sensitivity, using 500 times less sample than previous LC/MS analyses. Under optimized serum dilution conditions, chemical compounds spiked into mouse serum as metabolite mimics showed a linear response over a 600-fold concentration range. DI/FTICR-MS analysis of serum from 26 mice from 2 inbred strains, with and without acute trichloroethylene (TCE) treatment, gave a relative standard deviation (RSD) of 4.5%. Finally, we extended this method to the metabolomic fingerprinting of serum samples from 49 mice from 5 inbred strains involved in an acute alcohol toxicity study, using both positive and negative electrospray ionization (ESI). Using these samples, we demonstrated the utility of this method for high-throughput metabolomics, with more than 400 metabolites profiled in only 24 h. Our experiments demonstrate that DI/FTICR-MS is well-suited for high-throughput metabolomic analysis. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Metabolomic assays of the concentration and mass isotopomer distribution of gluconeogenic and citric acid cycle intermediates

We developed gas chromatography-mass spectrometry assays for the relative concentration and for the mass isotopomer distribution of gluconeogenic and citric acid cycle intermediates in tissues. The assay involves (i) spiking the sample with one or more internal standards, (ii) chloroform–methanol extraction at −25 °C, (iii) Folch wash of the extract, (iv) treatment of the water-methanol phase with methoxylamine, (v) evaporation and trimethylsilyl derivatization, and (vi) ammonia positive chemical ionization gas chromatography-mass spectrometry. For metabolomic computations, indices of concentrations for all compounds assayed are calculated as (Area of analyte)/(Area of reference compound). The assay was applied to a study of the effect of mercaptopicolinate, an inhibitor of phosphoenolpyruvate carboxykinase, on the profile of gluconeogenic intermediates in rat livers perfused with pyruvate. Crossover analysis of concentrations indices, compared to a control group, yielded very similar profiles as previous enzymatic assays, and correctly identified the site of action of mercaptopicolinate. Principal component analysis distinguished between control and drug treated samples. A loadings plot was used to identify the site of action of the drug in the metabolic pathway. Since metabolite concentrations do not address the flux through a pathway, perfusions with [1,4-¹³C₂] succinate dimethylester were conducted to assess fluxes around PEPCK. This allowed a dynamic metabolomics analysis which indicated that considerable flux through the pathway remained in the presence of mercaptopicolinate. This study illustrates the power of dynamic metabolomics to complement concentration based metabolomic studies.

---

     

Normal acquisition and loss of bone mass

The natural patterns of bone mass accumulation and loss with age represent the templates of individual life cycle periods that are distinguished by marked, physiologically and genetically identifiable, changes in bone mass. During the third trimester of pregnancy, maternal calcium absorption increases and the fetus accumulates about two-thirds of the total bone mass of the term infant. In early infancy, human milk calcium is derived primarily from maternal bone stores, which incur substantial bone losses that are quickly replenished during and after weaning. At puberty, a marked increase in bone mass occurs in conjunction with the initial physical and hormonal changes that characterize this stage. Calcium absorption and bone calcium deposition rates peak in females shortly before menarche. At that time, the bone calcium deposition rate is approximately five times that of adulthood. Skeletal bone mass reaches over 90% of its maximum by age 18 (earlier in females) but does not peak until age 25-30. At some point in mid-life, women experience perimenopause, the 3- to 5-year period prior to menopause during which estrogen levels begin to drop and there are marked increases in bone resorption and loss. Throughout adulthood, calcium absorption efficiency from the diet gradually declines.     

Metabolomic profiling of Drosophila using liquid chromatography Fourier transform mass spectrometry

Hydrophilic interaction chromatography (HILIC) interfaced with an Orbitrap Fourier transform mass spectrometer (FT-MS) was used to carry out metabolomic profiling of the classical Drosophila mutation, rosy (ry). This gene encodes a xanthine oxidase/dehydrogenase. In addition to validating the technology by detecting the same changes in xanthine, hypoxanthine, urate and allantoin that have been reported classically, completely unsuspected changes were detected in each of the tryptophan, arginine, pyrimidine and glycerophospholipid metabolism pathways. The rosy mutation thus ramifies far more widely than previously detected.     

Applications of mass spectrometry in metabolomic studies of animal model and invertebrate systems

Metabolomics provides rich datasets for systems biology. Massspectrometric (MS) techniques are rapidly gaining in importancefor untargeted metabolic profiling. In this review, we surveythe various techniques for sample preparation and analysis relatingto the various MS techniques and illustrate the potential ofthese techniques for both observing complete metabolomes anddetecting changes in the metabolism resulting from genetic mutationof other perturbations. The use of some of these techniquesin the study of model organisms including rodent and variousinvertebrate models is described. The invertebrate systems areof particular interest since such organisms have valuable mutantresources, such as RNAi panels directed against nearly all thegenes in the genome. The demonstration that they are readilycompatible with metabolomic approaches is particularly importantfor systems approaches to metabolic pathways.      

Ambient mass spectrometry employing a DART ion source for metabolomic fingerprinting/profiling: a powerful tool for beer origin recognition

A metabolomic fingerprinting/profiling generated by ambient mass spectrometry (MS) employing a direct analysis in real time (DART) ion source coupled to high-resolution time-of-flight mass spectrometry (TOFMS) was employed as a tool for beer origin recognition. In a first step, the DART–TOFMS instrumental conditions were optimized to obtain the broadest possible representation of ionizable compounds occurring in beer samples (direct measurement, no sample preparation). In the next step, metabolomic profiles (mass spectra) of a large set of different beer brands (Trappist and non-Trappist specialty beers) were acquired. In the final phase, the experimental data were analyzed using partial least squares discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and artificial neural networks with multilayer perceptrons (ANN-MLP) with the aim of distinguishing (i) the beers labeled as Rochefort 8; (ii) a group consisting of Rochefort 6, 8, 10 beers; and (iii) Trappist beers. The best prediction ability was obtained for the model that distinguished the group of Rochefort 6, 8, 10 beers from the rest of beers. In this case, all chemometric tools employed provided ≥95% correct classification. The current study showed that DART–TOFMS metabolomic fingerprinting/profiling is a powerful analytical strategy enabling quality monitoring/authenticity assessment to be conducted in real time.     

Parallel acquisition of multi-dimensional spectra in protein NMR

We introduce the use of multiple receivers applied in parallel for simultaneously recording multi-dimensional data sets of proteins in a single experiment. The utility of the approach is established through the introduction of the 2D (15)N,(1)H(N)||(13)CO HSQC experiment in which a pair of two-dimensional (15)N,(1)H(N) and (15)N,(13)CO spectra are recorded. The methodology is further extended to higher dimensionality via the 3D (1)H(N)||(13)CO HNCA in which a pair of data sets recording (13)C(α),(15)N,(1)H(N) and (13)C(α),(15)N,(13)CO chemical shifts are acquired. With the anticipated increases in probe sensitivity it is expected that multiple receiver experiments will become an important approach for efficient recording of NMR data.     

SpecAlign--processing and alignment of mass spectra datasets

SUMMARY: Pre-processing of chromatographic profile or mass spectral data is an important aspect of many types of proteomics and biomarker discovery experiments. Here we present a graphical computational tool, SpecAlign, that enables simultaneous visualization and manipulation of multiple datasets. SpecAlign not only provides all common processing functions, but also uniquely implements an algorithm that enables the complete alignment of each mass spectrum within a loaded dataset. We demonstrate its utility by aligning two datasets each containing six spectra; one set was acquired prior to instrument calibration and the other following calibration. AVAILABILITY: The software is free of charge and available for download from http://ptcl.chem.ox.ac.uk/~jwong/specalign. Supports Windows operating systems including Windows 9X/NT/2000/XP.     

Design of experiments: an efficient strategy to identify factors influencing extraction and derivatization of Arabidopsis thaliana samples in metabolomic studies with gas chromatography/mass spectrometry

The usual aim in metabolomic studies is to quantify the entire metabolome of each of a series of biological samples. To do this for complex biological matrices, e.g., plant tissues, efficient and reproducible extraction protocols must be developed. However, derivatization protocols must also be developed if GC/MS (one of the mostly widely used analytical methods for metabolomics) is involved. The aim of this study was to investigate how different chemical and physical factors (extraction solvent, derivatization reagents, and temperature) affect the extraction and derivatization of the metabolome from leaves of the plant Arabidopsis thaliana. Using design of experiment procedures, variation was systematically introduced, and the effects of this variation were analyzed using regression models. The results show that this approach allows a reliable protocol for metabolomic analysis of Arabidopsis to be determined with a relatively limited number of experiments. Following two different investigations an extraction and derivatization protocol was chosen. Further, the reproducibility of the analysis of 66 endogenous compounds was investigated, and it was shown that both hydrophilic and lipophilic compounds were detected with high reproducibility.