A geometric approach for the alignment of liquid chromatography-mass spectrometry data

MOTIVATION: Liquid chromatography coupled to mass spectrometry (LC-MS) and combined with tandem mass spectrometry (LC-MS/MS) have become a prominent tool for the analysis of complex proteomic samples. An important step in a typical workflow is the combination of results from multiple LC-MS experiments to improve confidence in the obtained measurements or to compare results from different samples. To do so, a suitable mapping or alignment between the data sets needs to be estimated. The alignment has to correct for variations in mass and elution time which are present in all mass spectrometry experiments. RESULTS: We propose a novel algorithm to align LC-MS samples and to match corresponding ion species across samples. Our algorithm matches landmark signals between two data sets using a geometric technique based on pose clustering. Variations in mass and retention time are corrected by an affine dewarping function estimated from matched landmarks. We use the pairwise dewarping in an algorithm for aligning multiple samples. We show that our pose clustering approach is fast and reliable as compared to previous approaches. It is robust in the presence of noise and able to accurately align samples with only few common ion species. In addition, we can easily handle different kinds of LC-MS data and adopt our algorithm to new mass spectrometry technologies. AVAILABILITY: This algorithm is implemented as part of the OpenMS software library for shotgun proteomics and available under the Lesser GNU Public License (LGPL) at www.openms.de.     

Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometric (LC/ESI-MS/MS) Study for the Identification and Characterization of In Vivo Metabolites of Cisplatin in Rat Kidney Cancer Tissues: Online Hydrogen/Deuterium (H/D) Exchange Study

In vivo rat kidney tissue metabolites of an anticancer drug, cisplatin (cis-diamminedichloroplatinum [II]) (CP) which is used for the treatment of testicular, ovarian, bladder, cervical, esophageal, small cell lung, head and neck cancers, have been identified and characterized by using liquid chromatography positive ion electrospray ionization tandem mass spectrometry (LC/ESI-MS/MS) in combination with on line hydrogen/deuterium exchange (HDX) experiments. To identify in vivo metabolites, kidney tissues were collected after intravenous administration of CP to adult male Sprague-Dawley rats (n = 3 per group). The tissue samples were homogenized and extracted using newly optimized metabolite extraction procedure which involves liquid extraction with phosphate buffer containing ethyl acetate and protein precipitation with mixed solvents of methanol-water-chloroform followed by solid-phase clean-up procedure on Oasis HLB 3cc cartridges and then subjected to LC/ESI-HRMS analysis. A total of thirty one unknown in vivo metabolites have been identified and the structures of metabolites were elucidated using LC-MS/MS experiments combined with accurate mass measurements. Online HDX experiments have been used to further support the structural characterization of metabolites. The results showed that CP undergoes a series of ligand exchange biotransformation reactions with water and other nucleophiles like thio groups of methionine, cysteine, acetylcysteine, glutathione and thioether. This is the first research approach focused on the structure elucidation of biotransformation products of CP in rats, and the identification of metabolites provides essential information for further pharmacological and clinical studies of CP, and may also be useful to develop various effective new anticancer agents.     

Structural identification of the metabolites for strictosamide in rats bile by an ion trap-TOF mass spectrometer and mass defect filter technique

We report herein, a facile metabolite identification workflow on the antimicrobial strictosamide, which is derived from accurate mass measurement by a hybrid ion trap-TOF mass spectrometer. In step 1, the parent drug and metabolites in rat bile were separated on an HPLC column followed by ion trap-TOF mass spectrometer analysis after a single oral dose of 50mg/kg strictosamide. In step 2, mass defect filter technique, which enables high-resolution mass spectrometers to be utilized for detecting drug metabolites based on well-defined mass defect ranges, was used to find metabolites in the mass spectrum. In step 3, the differences of accurate masses and their mass fragmentation pattern among the parent drug and metabolites used to assign structures for the metabolites successfully. As a result, five metabolites of strictosamide were found in rat bile, and all the metabolites were reported for the first time.     

Nearline acquisition and processing of liquid chromatography-tandem mass spectrometry data

Liquid chromatography–mass spectrometry (LC–MS) is a commonly used analytical platform for non-targeted metabolite profiling experiments. Although data acquisition, processing and statistical analyses are almost routine in such experiments, further annotation and subsequent identification of chemical compounds are not. For identification, tandem mass spectra provide valuable information towards the structure of chemical compounds. These are typically acquired online, in data-dependent mode, or offline, using handcrafted acquisition methods and manually extracted from raw data. Here, we present several methods to fast-track and improve both the acquisition and processing of LC–MS/MS data. Our nearly online (nearline) data-dependent tandem MS strategy creates a minimal set of LC–MS/MS acquisition methods for relevant features revealed by a preceding non-targeted profiling experiment. Using different filtering criteria, such as intensity or ion type, the acquisition of irrelevant spectra is minimized. Afterwards, LC–MS/MS raw data are processed with feature detection and grouping algorithms. The extracted tandem mass spectra can be used for both library search and de-novo identification methods. The algorithms are implemented in the R package MetShot and support the export to Bruker, Agilent or Waters QTOF instruments and the vendor-independent TraML standard. We evaluate the performance of our workflow on a Bruker micrOTOF-Q by comparison of automatically acquired and extracted tandem mass spectra obtained from a mixture of natural product standards against manually extracted reference spectra. Using Arabidopsis thaliana wild-type and biosynthetic gene knockout plants, we characterize the metabolic products of a biosynthetic pathway and demonstrate the integration of our approach into a typical non-targeted metabolite profiling workflow.

     

Nearline acquisition and processing of liquid chromatography-tandem mass spectrometry data

Liquid chromatography–mass spectrometry (LC–MS) is a commonly used analytical platform for non-targeted metabolite profiling experiments. Although data acquisition, processing and statistical analyses are almost routine in such experiments, further annotation and subsequent identification of chemical compounds are not. For identification, tandem mass spectra provide valuable information towards the structure of chemical compounds. These are typically acquired online, in data-dependent mode, or offline, using handcrafted acquisition methods and manually extracted from raw data. Here, we present several methods to fast-track and improve both the acquisition and processing of LC–MS/MS data. Our nearly online (nearline) data-dependent tandem MS strategy creates a minimal set of LC–MS/MS acquisition methods for relevant features revealed by a preceding non-targeted profiling experiment. Using different filtering criteria, such as intensity or ion type, the acquisition of irrelevant spectra is minimized. Afterwards, LC–MS/MS raw data are processed with feature detection and grouping algorithms. The extracted tandem mass spectra can be used for both library search and de-novo identification methods. The algorithms are implemented in the R package MetShot and support the export to Bruker, Agilent or Waters QTOF instruments and the vendor-independent TraML standard. We evaluate the performance of our workflow on a Bruker micrOTOF-Q by comparison of automatically acquired and extracted tandem mass spectra obtained from a mixture of natural product standards against manually extracted reference spectra. Using Arabidopsis thaliana wild-type and biosynthetic gene knockout plants, we characterize the metabolic products of a biosynthetic pathway and demonstrate the integration of our approach into a typical non-targeted metabolite profiling workflow.     

Identification of protein fragments as pattern features in MALDI-MS analyses of serum

The use of matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) to acquire spectral profiles has become a common approach to detect proteomic biomarkers of disease. MALDI-MS signals may represent both intact proteins as well as proteolysis products. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis can tentatively identify the corresponding proteins Here, we describe the application of a data analysis utility called FragMint, which combines MALDI-MS spectral data with LC-MS/MS based protein identifications to generate candidate protein fragments consistent with both types of data. This approach was used to identify protein fragments corresponding to spectral signals in MALDI-MS analyses of unfractionated human serum. The serum also was analyzed by one-dimensional SDS-PAGE and bands corresponding to the MALDI-MS signal masses were excised and subjected to in-gel digestion and LC-MS/MS analysis. Database searches mapped all of the identified peptides to abundant blood proteins larger than the observed MALDI-MS signals. FragMint identified fragments of these proteins that contained the MS/MS identified sequences and were consistent with the observed MALDI-MS signals. This approach should be generally applicable to identify protein species corresponding to MALDI-MS signals.     

Liquid chromatography-mass spectrometry/mass spectrometry method development for drug metabolism studies: Examining lipid matrix ionization effects in plasma

Glycerophosphocholines (GPCho's) are known to cause liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) matrix ionization effects during the analysis of biological samples (i.e. blood, plasma). We have developed a convenient new method, which we refer to as "in-source multiple reaction monitoring" (IS-MRM), for detecting GPCho's during LC-MS/MS method development. The approach uses high energy in-source collisionally induced dissociation (CID) to yield trimethylammonium-ethyl phosphate ions (m/z 184), which are formed from mono- and disubstituted GPCho's. The resulting ion is selected by the first quadrupole (Q1), passed through the collision cell (Q2) in the presence of collision gas at low energy to minimize fragmentation, and m/z 184 selected by the third quadrupole. This approach can be combined with standard multiple reaction monitoring (MRM) transitions with little compromise in sensitivity during method development and sample analysis. Hence, this approach was used to probe ionization matrix effects in plasma samples. The resulting information was employed to develop LC-MS/MS analyses for drugs and their metabolites with cycle times less than 5 min.     

A platform for accurate mass and time analyses of mass spectrometry data

We describe an integrated suite of algorithms and software for general accurate mass and time (AMT) tagging data analysis of mass spectrometry data. The AMT approach combines identifications from liquid chromatography (LC) tandem mass spectrometry (MS/MS) data with peptide accurate mass and retention time locations from high-resolution LC-MS data. Our workflow includes the traditional AMT approach, in which MS/MS identifications are located in external databases, as well as methods based on more recent hybrid instruments such as the LTQ-FT or Orbitrap, where MS/MS identifications are embedded with the MS data. We demonstrate our AMT workflow's utility for general data synthesis by combining data from two dissimilar biospecimens. Specifically, we demonstrate its use relevant to serum biomarker discovery by identifying which peptides sequenced by MS/MS analysis of tumor tissue may also be present in the plasma of tumor-bearing and control mice. The analysis workflow, referred to as msInspect/AMT, extends and combines existing open-source platforms for LC-MS/MS (CPAS) and LC-MS (msInspect) data analysis and is available in an unrestricted open-source distribution.     

Detection of new exemestane metabolites by liquid chromatography interfaced to electrospray-tandem mass spectrometry

Exemestane is an irreversible aromatase inhibitor used for anticancer therapy. Unfortunately, this drug is also misused in sports to avoid some adverse effects caused by steroids administration. For this reason exemestane has been included in World Anti-Doping Agency prohibited list. Usually, doping control laboratories monitor prohibited substances through their metabolites, because parent compounds are readily metabolized. Thus metabolism studies of these substances are very important. Metabolism of exemestane in humans is not clearly reported and this drug is detected indirectly through analysis of its only known metabolite: 17β-hydroxyexemestane using liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) and gas chromatography coupled to mass spectrometry (GC-MS). This drug is extensively metabolized to several unknown oxidized metabolites. For this purpose LC-MS/MS has been used to propose new urinary exemestane metabolites, mainly oxidized in C6-exomethylene and simultaneously reduced in 17-keto group. Urine samples from four volunteers obtained after administration of a 25mg dose of exemestane were analyzed separately by LC-MS/MS. Urine samples of each volunteer were hydrolyzed followed by liquid-liquid extraction and injected into a LC-MS/MS system. Three unreported metabolites were detected in all urine samples by LC-MS/MS. The postulated structures of the detected metabolites were based on molecular formulae composition obtained through high accuracy mass determination by liquid chromatography coupled to hybrid quadrupole-time of flight mass spectrometry (LC-QTOF MS) (all mass errors below 2ppm), electrospray (ESI) product ion spectra and chromatographic behavior.     

Metabolomic Method: UPLC-q-ToF Polar and Non-Polar Metabolites in the Healthy Rat Cerebellum Using an In-Vial Dual Extraction

Unbiased metabolomic analysis of biological samples is a powerful and increasingly commonly utilised tool, especially for the analysis of bio-fluids to identify candidate biomarkers. To date however only a small number of metabolomic studies have been applied to studying the metabolite composition of tissue samples, this is due, in part to a number of technical challenges including scarcity of material and difficulty in extracting metabolites. The aim of this study was to develop a method for maximising the biological information obtained from small tissue samples by optimising sample preparation, LC-MS analysis and metabolite identification. Here we describe an in-vial dual extraction (IVDE) method, with reversed phase and hydrophilic liquid interaction chromatography (HILIC) which reproducibly measured over 4,000 metabolite features from as little as 3mg of brain tissue. The aqueous phase was analysed in positive and negative modes following HILIC separation in which 2,838 metabolite features were consistently measured including amino acids, sugars and purine bases. The non-aqueous phase was also analysed in positive and negative modes following reversed phase separation gradients respectively from which 1,183 metabolite features were consistently measured representing metabolites such as phosphatidylcholines, sphingolipids and triacylglycerides. The described metabolomics method includes a database for 200 metabolites, retention time, mass and relative intensity, and presents the basal metabolite composition for brain tissue in the healthy rat cerebellum.     

Tandem mass spectrometry for on-line fermentation monitoring

Summary Membrane introduction mass spectrometry has been employed for on-line determination of the major products and volatile metabolites ofBacillus polymyxa fermentation. Samples were introduced into the mass spectrometer via a direct insertion membrane probe in which the aqueous solution flowed past a membrane located in the ion source of the mass spectrometer. Concentrations of the products 2,3-butanediol, acetoin, ethanol and acetic acid in fermentation broth were measured by tandem mass spectrometry after permeation through the membrane and ionization by chemical ionization. External standards were employed for quantification and a large linear response range was available for each of the major products observed. Dissolved CO₂ and O₂, as well as CO₂ in the off gases, were also monitored on-line by mass spectrometry. The use of tandem mass spectrometry has allowed the identification of products that were not previously known to be present in measurable amounts.     

MetaboSearch: tool for mass-based metabolite identification using multiple databases

Searching metabolites against databases according to their masses is often the first step in metabolite identification for a mass spectrometry-based untargeted metabolomics study. Major metabolite databases include Human Metabolome DataBase (HMDB), Madison Metabolomics Consortium Database (MMCD), Metlin, and LIPID MAPS. Since each one of these databases covers only a fraction of the metabolome, integration of the search results from these databases is expected to yield a more comprehensive coverage. However, the manual combination of multiple search results is generally difficult when identification of hundreds of metabolites is desired. We have implemented a web-based software tool that enables simultaneous mass-based search against the four major databases, and the integration of the results. In addition, more complete chemical identifier information for the metabolites is retrieved by cross-referencing multiple databases. The search results are merged based on IUPAC International Chemical Identifier (InChI) keys. Besides a simple list of m/z values, the software can accept the ion annotation information as input for enhanced metabolite identification. The performance of the software is demonstrated on mass spectrometry data acquired in both positive and negative ionization modes. Compared with search results from individual databases, MetaboSearch provides better coverage of the metabolome and more complete chemical identifier information. Availability: The software tool is available at http://omics.georgetown.edu/MetaboSearch.html.     

MSClust: a tool for unsupervised mass spectra extraction of chromatography-mass spectrometry ion-wise aligned data

Mass peak alignment (ion-wise alignment) has recently become a popular method for unsupervised data analysis in untargeted metabolic profiling. Here we present MSClust-a software tool for analysis GC-MS and LC-MS datasets derived from untargeted profiling. MSClust performs data reduction using unsupervised clustering and extraction of putative metabolite mass spectra from ion-wise chromatographic alignment data. The algorithm is based on the subtractive fuzzy clustering method that allows unsupervised determination of a number of metabolites in a data set and can deal with uncertain memberships of mass peaks in overlapping mass spectra. This approach is based purely on the actual information present in the data and does not require any prior metabolite knowledge. MSClust can be applied for both GC-MS and LC-MS alignment data sets. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0368-2) contains supplementary material, which is available to authorized users.     

Potential bias and mitigations when using stable isotope labeled parent drug as internal standard for LC-MS/MS quantitation of metabolites

In recent years, increasing emphasis has been placed on quantitative characterization of drug metabolites for better insight into the correlation between metabolite exposure and toxicological observations or pharmacological efficacy. One common strategy for metabolite quantitation is to adopt the stable isotope labeled (STIL) parent drug as the internal standard in an isotope dilution liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay. In the current work, we demonstrate this strategy could have a potential pitfall resulting in quantitation bias if the internal standard is subject to ion suppression from the co-eluting parent drug in the incurred samples. Propranolol and its metabolite 4-hydroxypropranolol were used as model compounds to demonstrate this phenomenon and to systematically evaluate different approaches to mitigate the issue, including atmospheric pressure chemical ionization (APCI) mode of ionization, increased internal standard concentration, quantitation without internal standard, the use of a structural analog as internal standard, and dilution of the samples. Case studies of metabolite quantitation in nonclinical and clinical studies in drug development were also included to demonstrate the importance of using an appropriate bioanalytical strategy for metabolite quantitation in the real world. We present that bias of metabolite concentrations could pose a potential for poor estimation of safety risk. A strategy for quantitation of metabolites in support of drug safety assessment is proposed.     

LC-MS-based metabolomics

Metabolomics aims at identification and quantitation of small molecules involved in metabolic reactions. LC-MS has enjoyed a growing popularity as the platform for metabolomic studies due to its high throughput, soft ionization, and good coverage of metabolites. The success of a LC-MS-based metabolomic study often depends on multiple experimental, analytical, and computational steps. This review presents a workflow of a typical LC-MS-based metabolomic analysis for identification and quantitation of metabolites indicative of biological/environmental perturbations. Challenges and current solutions in each step of the workflow are reviewed. The review intends to help investigators understand the challenges in metabolomic studies and to determine appropriate experimental, analytical, and computational methods to address these challenges.     

Metabolism of leukotriene B4 in isolated rat hepatocytes. Involvement of 2,4-dienoyl-coenzyme A reductase in leukotriene B4 metabolism

Radiolabeled leukotriene (LT) B4 was incubated with isolated rat hepatocytes in order to assess the metabolism of this chemotactic leukotriene by the liver. At least eight radioactive metabolites were observed, three of which were previously identified as 20-hydroxy-, 20-carboxy-, and 18-carboxy-19,20-dinor-LTB4. A less lipophilic major metabolite (designated HIV) was purified by two reverse phase high performance liquid chromatography separations and was found to exhibit maximal UV absorbance at 269 nm with shoulders at 260 and 280 indicating the presence of a conjugated triene chromophore. Negative ion electron capture gas chromatography/mass spectrometry analysis of the pentafluorobenzyl ester, trimethylsilyl ether derivative of HIV, and positive ion electron ionization mass spectra of the methyl ester trimethylsilyl derivative were consistent with a structure of this metabolite being 16-carboxy-14,15-dihydro-17,18,19,20-tetranor-LTB3. The appearance of this metabolite supports the concept of further beta-oxidation of LTB4 to the carbon 16 which requires the action of 2,4-dienoyl-CoA reductase to remove the 14,15-double bond located two carbon atoms removed from the CoA thioester moiety. One minor metabolite was analyzed by negative ion continuous flow fast atom bombardment mass spectrometry which revealed an ion at m/z 444 which by high resolution mass spectrometry was shown to contain both nitrogen and sulfur. Tandem mass spectrometry suggested the presence of SO3- as well as other fragments corresponding to the amino acid taurine. Incubation of isolated rat hepatocytes with [14C]taurine as well as [3H]LTB4 revealed the incorporation of both radioactive isotopes into this metabolite. The data supported the identification of this metabolite as tauro-18-carboxy-19,20-dinor-LTB4. Amino acid conjugation of leukotrienes has not been previously reported and suggests that such intermediates might participate in enterohepatic circulation of LTB4 metabolites in the intact animal and thus serve as an alternative metabolic route for LTB4 elimination.     

Combining intensity correlation analysis and MALDI imaging to study the distribution of flavonols and dihydrochalcones in Golden Delicious apples

Mass spectrometry-based imaging techniques applied to small molecules complement the growing research field of metabolomics and can be used to interpret many important biological processes occurring in plants. In untargeted imaging applications, chemical identification is a critical step since it cannot take advantage of separative techniques applied to neutral molecules (e.g. liquid chromatography). The use of high resolution spectrometers is of great help, but fragmentation experiments are often necessary. In many cases, the information on ion fragmentation is embedded in the data sets, because analytes break up during ionization, but the extraction of this information is not easy considering the complexity of the imaging data files. Here an approach is proposed for applying conventional untargeted MALDI (matrix-assisted laser desorption ionization) profiling and advanced data analysis to perform imaging of metabolites in apple tissues. The pipeline, based on intensity correlation analysis, is used to extract fragmentation information from untargeted, high resolution, wide range mass spectra and to reconstruct compound-specific images which can be used for interpretation purposes. The proposed approach was used to investigate the distribution of glycosylated flavonols and dihydrochalcones in Golden Delicious apples. The results indicate that the method is effective, showing a high potential for ascertaining detailed metabolite localization.     

Metabolomics approach for enzyme discovery

The search for novel enzymes is an important but difficult task in functional genomics. Here, we present a systematic method based on in vitro assays in combination with metabolite profiling to discover novel enzymatic activities. A complex mixture of metabolites is incubated with purified candidate proteins and the reaction mixture is subsequently profiled by capillary electrophoresis electrospray ionization mass spectrometry (CE-MS). Specific changes in the metabolite composition can directly suggest the presence of an enzymatic activity while subsequent identification of the compounds whose level changed specifically can pinpoint the actual substrate(s) and product(s) of the reaction. We first evaluated the method using several Escherichia coli metabolic enzymes and then applied it to the functional screening of uncharacterized proteins. In this manner, YbhA and YbiV proteins were found to display both phosphotransferase and phosphatase activity toward different sugars/sugar phosphates. Our approach should be broadly applicable and useful for enzyme discovery in any system.     

A multimodal metabolomics approach using imaging mass spectrometry and liquid chromatography-tandem mass spectrometry for spatially characterizing monoterpene indole alkaloids secreted from roots

Plants release specialized (secondary) metabolites from their roots to communicate with other organisms, including soil microorganisms. The spatial behavior of such metabolites around these roots can help us understand roles for the communication; however, currently, they are unclear because soil-based studies are complex. Here, we established a multimodal metabolomics approach using imaging mass spectrometry (IMS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) to spatially assign metabolites under laboratory conditions using agar. In a case study using Catharanthus roseus, we showed that 58 nitrogen (N)-containing metabolites are released from the roots into the agar. For the metabolite assignment, we used ¹⁵N-labeled and non-labeled LC-MS/MS data, previously reported. Four metabolite ions were identified using authentic standard compounds as derived from monoterpene indole alkaloids (MIAs) such as ajmalicine, catharanthine, serpentine, and yohimbine. An alkaloid network analysis using dot products and spinglass methods characterized five clusters to which the 58 ions belong. The analysis clustered ions from the indolic skeleton-type MIAs to a cluster, suggesting that other communities may represent distinct metabolite groups. For future chemical assignments of the serpentine community, key fragmentation patterns were characterized using the ¹⁵N-labeled and non-labeled MS/MS spectra.