Assigning product ions from complex MS/MS spectra: the importance of mass uncertainty and resolving power

Determining the parent and associated fragment formulae in mass spectrometry via the parent subformula graph

BACKGROUND

Identifying the molecular formula and fragmentation reactions of an unknown compound from its mass spectrum is crucial in areas such as natural product chemistry and metabolomics. We propose a method for identifying the correct candidate formula of an unidentified natural product from its mass spectrum. The method involves scoring the plausibility of parent candidate formulae based on a parent subformula graph (PSG), and two possible metrics relating to the number of edges in the PSG. This method is applicable to both electron-impact mass spectrometry (EI-MS) and tandem mass spectrometry (MS/MS) data. Additionally, this work introduces the two-dimensional fragmentation plot (2DFP) for visualizing PSGs.

RESULTS

Our results suggest that incorporating information regarding the edges of the PSG results in enhanced performance in correctly identifying parent formulae, in comparison to the more well-accepted "MS/MS score", on the 2016 Computational Assessment of Small Molecule Identification (CASMI 2016) data set (76.3 vs 58.9% correct formula identification) and the Research Centre for Toxic Compounds in the Environment (RECETOX) data set (66.2% vs 59.4% correct formula identification). In the extension of our method to identify the correct candidate formula from complex EI-MS data of semiochemicals, our method again performed better (correct formula appearing in the top 4 candidates in 20/23 vs 7/23 cases) than the MS/MS score, and enables the rapid identification of both the correct parent ion mass and the correct parent formula with minimal expert intervention.

CONCLUSION

Our method reliably identifies the correct parent formula even when the mass information is ambiguous. Furthermore, should parent formula identification be successful, the majority of associated fragment formulae can also be correctly identified. Our method can also identify the parent ion and its associated fragments in EI-MS spectra where the identity of the parent ion is unclear due to low quantities and overlapping compounds. Finally, our method does not inherently require empirical fitting of parameters or statistical learning, meaning it is easy to implement and extend upon.

SCIENTIFIC CONTRIBUTION

Developed, implemented and tested new metrics for assessing plausibility of candidate molecular formulae obtained from HR-MS data.

Top-down lignomics analysis of the French oak lignin by atmospheric pressure photoionization and electrospray ionization quadrupole time-of-flight tandem mass spectrometry: Identification of a novel series of lignans

We report herein the top-down lignomic analysis of virgin released lignin (VRL) extracted from the French oak wood using atmospheric pressure photoionization quadrupole orthogonal time-of-flight mass spectrometry (APPI-QqTOF-MS) (+ ion mode). Eight major protonated lignin oligomers were identified using the APPI-QqTOF-MS/MS of this complex VRL mixture without any kind of purification. This series of protonated oligomer ions were identified as neolignan cedrusin (1), five different aryltetralin lignans dimers (2-6), one lignan-dehydroshikimic acid complex (7), and a lignan trimer (8). Similarly, electrospray ionization (ESI)-QqTOF-MS (+ ion mode) allowed us to identify three extra aryltetralin lignan derivatives (9-11). The Kendrick mass defect analysis was used for the simplification of this complex APPI-QqTOF-MS into a compositional map, which displayed clustering points of associated ions possessing analogous elemental composition. This series of novel protonated molecules were selected and subjected to low-energy collision-induced dissociation (CID)-MS/MS analyses. The obtained gas-phase fragmentation patterns helped to tentatively assign their most likely structures. Also, it was found that the use of different APPI and ESI ambient ionization techniques enhances the ionization of different types of lignin oligomers.

Top-down lignomics analysis of the French pine lignin by atmospheric pressure photoionization quadrupole time-of-flight tandem mass spectrometry: Identification of a novel series of lignin-carbohydrate complexes

RATIONALE

We report the top-down lignomics analysis of the virgin released lignin (VRL) extracted from French pine wood by using atmospheric pressure photoionization quadrupole time-of-flight mass spectrometry (APPI-QqTOF-MS) and low-energy collision-induced dissociation tandem mass spectrometry (CID-MS/MS).

METHODS

We used APPI-QqTOF-MS (positive ion mode) for the analysis of the complex mixture of VRL oligomers extracted from French pine wood. Some of the major precursor ions were fished out from the complex VRL oligomeric mixture and subjected to low-energy CID-MS/MS analyses.

RESULTS

Fourteen novel lignin-carbohydrate complexes (LCCs) were identified using APPI-QqTOF-MS/MS of the very complex mixture of virgin released lignins (VRLs), directly extracted from French pine wood without any kind of purification. The low-energy CID-MS/MS analyses allowed us to establish the fragmentation patterns of the precursor ions and to identify the complex structures of the identified LCC molecules. These novel identified series of LCCs were composed of one or two carbohydrate rings to which one, two, or three lignin units were covalently attached. In addition to the fourteen LCCs, acetyl eugenol was identified in the French pine VRL sample. The identification of acetyl eugenol indicates possible lignin degradation and modification (acetylation) during the mild extraction method developed by the Compagnie Industrielle de la Matière Végétale (CIMV).

CONCLUSIONS

The top-down lignomics analysis of the French pine VRLs using APPI-QqTOF-MS and low energy CID-MS/MS allowed us to identify acetylated eugenol and a novel series of fourteen LCCs. These series of LCCs provide evidence that lignins are covalently linked to carbohydrates in the native wood network and act as cross-linkers between cellulose and hemicellulose components of wood.

Matrix-assisted laser desorption/ionization time-of-flight/time-of-flight tandem mass spectrometry (negative ion mode) of French Oak lignin: A novel series of lignin and tricin derivatives attached to carbohydrate and shikimic acid moieties

RATIONALE

We report the top-down lignomic analysis of the virgin released lignin (VRL) small oligomers obtained from French Oak wood.

METHODS

We have used MALDI-TOF-MS in the negative ion mode for the analysis of the complex mixture of lignin oligomers extracted from French Oak wood. High-energy CID-TOF/TOF-MS/MS analyses were used to support the postulated precursor ion structures.

RESULTS

Twenty compounds were identified using MALDI-TOF-MS/MS of the VRL extracted from French Oak wood: seven tricin derivatives and/or flavonoids, three syringylglycerol derivatives, two syringol derivatives, two flavonolignin derivatives, and six miscellaneous compounds: luteoferol, lariciresinol isomer, 5-hydroxy guaiacyl derivative, syringyl -C₁₀ H₁₀ O₂ dimer, trihydroxy benzaldehyde derivative, and aryl tetralin lignan derivative. Most of the identified compounds were in the form of carbohydrate and/or shikimic acid complexes.

CONCLUSIONS

The analysis of this complex mixture led to the identification of a series of lignin dimers, novel lignin-carbohydrate complexes (LCC), and unique tricin derivatives linked to different types of carbohydrates and shikimic acid moieties. This finding supports the presence of lignin-carbohydrate complexes in the isolated VRL. These analyses also showed that French Oak lignin is abundant in syringol moieties present in the lignin syringyl units or tricin derivatives. Moreover, the identification of some lignin-carbohydrate and/or flavonoid-shikimic acid complexes could provide new insight into the relationship between the biosynthesis of lignin and tricin.

Dereplication of microbial metabolites through database search of mass spectra

Natural products have traditionally been rich sources for drug discovery. In order to clear the road toward the discovery of unknown natural products, biologists need dereplication strategies that identify known ones. Here we report DEREPLICATOR+, an algorithm that improves on the previous approaches for identifying peptidic natural products, and extends them for identification of polyketides, terpenes, benzenoids, alkaloids, flavonoids, and other classes of natural products. We show that DEREPLICATOR+ can search all spectra in the recently launched Global Natural Products Social molecular network and identify an order of magnitude more natural products than previous dereplication efforts. We further demonstrate that DEREPLICATOR+ enables cross-validation of genome-mining and peptidogenomics/glycogenomics results.

Comparative mass spectrometry-based metabolomics strategies for the investigation of microbial secondary metabolites

Covering: 2000 to 2016The labor-intensive process of microbial natural product discovery is contingent upon identifying discrete secondary metabolites of interest within complex biological extracts, which contain inventories of all extractable small molecules produced by an organism or consortium. Historically, compound isolation prioritization has been driven by observed biological activity and/or relative metabolite abundance and followed by dereplication via accurate mass analysis. Decades of discovery using variants of these methods has generated the natural pharmacopeia but also contributes to recent high rediscovery rates. However, genomic sequencing reveals substantial untapped potential in previously mined organisms, and can provide useful prescience of potentially new secondary metabolites that ultimately enables isolation. Recently, advances in comparative metabolomics analyses have been coupled to secondary metabolic predictions to accelerate bioactivity and abundance-independent discovery work flows. In this review we will discuss the various analytical and computational techniques that enable MS-based metabolomic applications to natural product discovery and discuss the future prospects for comparative metabolomics in natural product discovery.

A high-resolution accurate mass (HR/AM) approach to identification, profiling and characterization of in vitro nefazodone metabolites using a hybrid quadrupole Orbitrap (Q-Exactive)

RATIONALE

This paper describes a strategy for the profiling and identification of metabolites based on chemical group classification using high-resolution accurate mass (HR/AM) full scan mass spectrometry (MS) and All-Ion fragmentation (AIF) MS² data.

METHODS

The proposed strategy uses a hybrid quadrupole Orbitrap (Q-Exactive) employing stepped normalised collision energy (NCE) at 35% and 80% to produce key chemically diagnostic product ions from full coverage of the product ion spectrum. This approach allows filtering of high-resolution AIF MS² data in order to identify parent-related compounds produced following incubation in rat liver microsomes (RLMs).

RESULTS

An antidepressant drug, nefazodone (NEF), was selected as the model test compound to demonstrate the proposed workflow for metabolite profiling. This resulted in the identification of three indicative chemical groups within NEF: triazolone, phenoxy and chlorophenylpiperazine. High-resolution mass spectrometry provides increased specificity to distinguish between two characteristic product ion masses m/z 154.0975 (C₇ H₁₂ N₃ O) and 154.0419 (C₈ H₉ NCl), which are not fully resolved by spectrometers operating at nominal mass resolution, indicative of compounds containing the triazolone and chlorophenylpiperazine moieties, respectively.

CONCLUSIONS

This post-acquisition processing strategy provides comprehensive detection and identification of high- and low-level metabolites from an 'all-in-one' analysis. This enables functional groups to be systematically traced across a wide range of metabolites, leading to the successful identification of 28 in vitro NEF-related metabolites. In our hands this approach has been applied to agrochemical environmental fate and dietary metabolism studies, as well as metabolomics and biomarker analysis. Copyright © 2015 John Wiley & Sons, Ltd.

Analysis of vitamin D metabolic markers by mass spectrometry: current techniques, limitations of the "gold standard" method, and anticipated future directions

Vitamin D compounds belong to a group of secosteroids, which occur naturally as vitamin D3 in mammals and D2 in plants. Vitamin D is vital for bone health but recent studies have shown a much wider role in the pathologies of diseases such as diabetes, cancer, autoimmune, neurodegenerative, mental and cardiovascular diseases. Photosynthesis of vitamin D in the human skin and subsequent hepatic and renal metabolism generate a wide range of transformation products occurring over a large dynamic range spanning from picomolar to nanomolar levels. This necessitates selective and sensitive analytical methods to quantitatively capture these low concentration levels in relevant tissues such as blood. Ideally, vitamin D assessment would be performed using a universal and standardized analytical method available to clinical laboratories that provides reliable and accurate quantitative results for all relevant vitamin D metabolites with sufficiently high throughput. At present, LC-MS/MS assays are the most promising techniques for vitamin D analysis. The present review focuses on developments in mass spectrometry methodologies of the past 12 years. It will highlight detrimental influences of the biological matrix, epimer contributions, pitfalls of specific mass spectrometry data acquisition routines (in particular multiple reaction monitoring, MRM), influence of ionization source, derivatization reactions, inter-laboratory comparisons on precision, accuracy, and application range of vitamin D metabolites.

Post-acquisition data processing for the screening of transformation products of different organic contaminants. Two-year monitoring of river water using LC-ESI-QTOF-MS and GCxGC-EI-TOF-MS

This study describes a comprehensive strategy for detecting and elucidating the chemical structures of expected and unexpected transformation products (TPs) from chemicals found in river water and effluent wastewater samples, using liquid chromatography coupled to electrospray ionization quadrupole-time-of-flight mass spectrometer (LC-ESI-QTOF-MS), with post-acquisition data processing and an automated search using an in-house database. The efficacy of the mass defect filtering (MDF) approach to screen metabolites from common biotransformation pathways was tested, and it was shown to be sufficiently sensitive and applicable for detecting metabolites in environmental samples. Four omeprazole metabolites and two venlafaxine metabolites were identified in river water samples. This paper reports the analytical results obtained during 2 years of monitoring, carried out at eight sampling points along the Henares River (Spain). Multiresidue monitoring, for targeted analysis, includes a group of 122 chemicals, amongst which are pharmaceuticals, personal care products, pesticides and PAHs. For this purpose, two analytical methods were used based on direct injection with a LC-ESI-QTOF-MS system and stir bar sorptive extraction (SBSE) with bi-dimensional gas chromatography coupled with a time-of-flight spectrometer (GCxGC-EI-TOF-MS).

Multidimensional gas chromatography in combination with accurate mass, tandem mass spectrometry, and element-specific detection for identification of sulfur compounds in tobacco smoke

A method is developed for identification of sulfur compounds in tobacco smoke extract. The method is based on large volume injection (LVI) of 10μL of tobacco smoke extract followed by selectable one-dimensional ((1)D) or two-dimensional ((2)D) gas chromatography (GC) coupled to a hybrid quadrupole time-of-flight mass spectrometer (Q-TOF-MS) using electron ionization (EI) and positive chemical ionization (PCI), with parallel sulfur chemiluminescence detection (SCD). In order to identify each individual sulfur compound, sequential heart-cuts of 28 sulfur fractions from (1)D GC to (2)D GC were performed with the three MS detection modes (SCD/EI-TOF-MS, SCD/PCI-TOF-MS, and SCD/PCI-Q-TOF-MS). Thirty sulfur compounds were positively identified by MS library search, linear retention indices (LRI), molecular mass determination using PCI accurate mass spectra, formula calculation using EI and PCI accurate mass spectra, and structure elucidation using collision activated dissociation (CAD) of the protonated molecule. Additionally, 11 molecular formulas were obtained for unknown sulfur compounds. The determined values of the identified and unknown sulfur compounds were in the range of 10-740ngmg total particulate matter (TPM) (RSD: 1.2-12%, n=3).

Account: characterization and identification of microcystins by mass spectrometry

In this brief overview, the authors describe mass spectral techniques for the detection and identification of microcystin toxins. Microcystins are secondary metabolites produced by cyanobacteria. Determination of these toxic compounds and discovery of new variants is very important as they pose a great danger to the human food chain. Cyanobacterial blooms frequently occur in many areas worldwide and have the potential to contaminate the water via cyanotoxin release, especially microcystins. Among the various analytical techniques used for analysis, mass spectrometry has become the most important method as it allows simultaneous quantification and structural characterization of multiple microcystin variants. This brief overview article focuses on mass spectrometry techniques for identification of microcystins, including ionization methods, mass spectral fragmentation routes, profiling techniques, tandem and high-resolution mass spectrometry as well as typing of cyanobacterial strains.

Neutral fragment filtering for rapid identification of new diester-diterpenoid alkaloids in roots of Aconitum carmichaeli by ultra-high-pressure liquid chromatography coupled with linear ion trap-orbitrap mass spectrometry

A rapid and effective method was developed for separation and identification of diester-diterpenoid alkaloids (DDA) in the roots of Aconitum carmichaeli by ultra-high-pressure liquid chromatography coupled with high resolution LTQ-Orbitrap tandem mass spectrometry (UHPLC-LTQ-Orbitrap-MSⁿ). According to accurate mass measurement and the characteristic neutral loss filtering strategy, a total of 42 diester-diterpenoid alkaloids (DDA) were rapidly detected and characterized or tentatively identified. Meanwhile, the proposed fragmentation pathways and the major diagnostic fragment ions of aconitine, mesaconitine and hypaconitine were investigated to trace DDA derivatives in crude plant extracts. 23 potential new compounds were successfully screened and characterized in Aconitum carmichaeli, including 16 short chain fatty acyls DDA, 4 N-dealkyl DDA and several isomers of aconitine, mesaconitine and hypaconitine.

Structural Characterization of Carbohydrates by Fourier Transform Tandem Mass Spectrometry

Fourier transform tandem mass spectrometry (MS/MS) provides high mass accuracy, high sensitivity, and analytical versatility and has therefore emerged as an indispensable tool for structural elucidation of biomolecules. Glycosylation is one of the most common posttranslational modifications, occurring in ~50% of proteins. However, due to the structural diversity of carbohydrates, arising from non-template driven biosynthesis, achievement of detailed structural insight is highly challenging. This review briefly discusses carbohydrate sample preparation and ionization methods, and highlights recent developments in alternative high-resolution MS/MS strategies, including infrared multiphoton dissociation (IRMPD), electron capture dissociation (ECD), and electron detachment dissociation (EDD), for carbohydrates with a focus on glycans and proteoglycans from mammalian glycoproteins.

Intriguing differences in the gas-phase dissociation behavior of protonated and deprotonated gonyautoxin epimers

The aim of this study was to investigate the unusual gas-phase dissociation behavior of two epimer pairs of protonated gonyautoxins (GTX) following electrospray ionization in comparison to their deprotonated counterparts. The chemical structures of the investigated GTX1-4 variants vary in their substitution pattern at N-1 and the stereochemical orientation of the hydroxysulfate group at C-11 (11α for GTX1/2 versus 11β for GTX3/4). The direct comparison of mass spectra in positive and negative ion modes illustrated two distinct features: first, an intriguing difference between protonated 11α and 11β species, where 11α conformations exhibited almost complete dissociation of [M + H](+) ions via facile SO(3) elimination, while 11β species remained mostly intact as [M + H](+); and second, the lack of such differences for the deprotonated counterparts. In this study, we propose an acid-catalyzed elimination mechanism from density functional theory calculations, initiated by a proton transfer of a guanidinium proton to the hydroxysulfate group with simultaneous SO(3) release, which is only possible for the 11α conformation based on intramolecular distances. The same mechanism explains the lack of a comparable SO(3) loss in the negative ion mode. CID experiments supported this proposed mechanism for GTX1 and GTX2. Computational modeling of product ions seen in the CID spectra of GTX3 and GTX4 established that the lowest energy dissociation pathway for the 11β epimers is elimination of water with the possibility for further SO(3) release from the intermediate product. Experimental data for structurally analogous decarbamoyl gonyautoxins confirmed the evidence for the GTX compounds as well as the proposed elimination mechanisms.

Metabolite characterization of a novel anti-cancer agent, icotinib, in humans through liquid chromatography/quadrupole time-of-flight tandem mass spectrometry

Icotinib is a novel anti-cancer drug that has shown promising clinical efficacy and safety in patients with non-small-cell lung cancer (NSCLC). At this time, the metabolic fate of icotinib in humans is unknown. In the present study, a liquid chromatography/quadrupole time-of-flight tandem mass spectrometry (LC/Q-TOF MS) method was established to characterize metabolites of icotinib in human plasma, urine and feces. In addition, nuclear magnetic resonance (NMR) detection was utilized to determine the connection between side-chain and quinazoline groups for some complex metabolites. In total, 29 human metabolites (21 isomer metabolites) were characterized, of which 23 metabolites are novel compared to the metabolites in rats. This metabolic study revealed that icotinib was extensively metabolized at the 12-crown-4 ether moiety (ring-opening and further oxidation), carbon 15 (hydroxylation) and an acetylene moiety (oxidation) to yield 19 oxidized metabolites and to further form 10 conjugates with sulfate acid or glucuronic acid. To our knowledge, this is the first report of the human metabolic profile of icotinib. Study results indicated that significant attention should be paid to the metabolic profiles of NSCLC patients during the development of icotinib.

Physical signal modulation of time-of-flight mass analyzers increases precision and decreases noise

Recently, an increased emphasis has been placed on the ability to make mass measurements with high accuracy and precision. The motivation for this is that high-precision mass measurements, together with isotope intensity matching, permit confirmation of molecular formulas and de novo molecular formula prediction, both of which enhance the value of proteomics and metabolomics data. The confidence of mass-based conclusions also depends on reliable estimates of uncertainty. However, determining the precision of a particular measurement remains a complicated process. For signals which are well-resolved and of sufficient intensity, an often-overlooked factor for high precision is the mass sampling frequency (abscissa, Δx). We have analyzed the impact of Δx on the centroid calculation of peak position, and find that existing quality standards, such as 4 or 5 samples per peak, may not be sufficient to achieve high precision. Time-domain and m/z-domain sampling frequency on time-of-flight (TOF) mass analyzers can be improved using a new method that we call Physical Signal Modulation (PSM). PSM allows very substantial improvements by decreasing Δx without requiring specialized hardware or digitizers. In addition to providing accuracy improvements, PSM also dramatically improves signal-to-noise ratios by removing coherent noise. Software to perform PSM data processing is available as part of the PySpecTools package.

Evaluation of a high resolving power time-of-flight mass spectrometer for drug analysis in terms of resolving power and acquisition rate

Liquid chromatography time-of-flight mass spectrometry (LC-TOFMS) is applied increasingly to various fields of small molecule analysis. The moderate resolving power (RP) of standard TOFMS instruments poses a risk of false negative results when complex biological matrices are to be analyzed. In this study, the performance of a high resolving power TOFMS instrument (maXis by Bruker Daltonik, Bremen, Germany) was evaluated for drug analysis. By flow injection analysis of critical drug mixtures, including a total of 17 compounds with nominal masses of 212-415 Da and with mass differences of 8.8-23.5 mDa, RP varied from 34,400 to 51,900 (FWHM). The effect of acquisition rate on RP, mass accuracy, and isotopic pattern fit was studied by applying 1, 2, 5, 10, and 20 Hz acquisition rates in a 16 min gradient elution LC separation. All three variables were independent of the acquisition rate, with an average mass accuracy and isotopic pattern fit factor (mSigma) of 0.33 ppm and 5.9, respectively. The average relative standard deviation of RP was 1.8%, showing high repeatability. The performance was tested further with authentic urine extracts containing a co-eluting compound pair with a nominal mass of 296 Da and an 11.2 mDa mass difference. The authentic sample components were readily resolved and correctly identified by the automated data analysis. The average RP, mass accuracy, and isotopic pattern fit were 36,600, 0.9 ppm, and 7.3 mSigma, respectively.

Construction of confidence regions for isotopic abundance patterns in LC/MS data sets for rigorous determination of molecular formulas

It has long been recognized that estimates of isotopic abundance patterns may be instrumental in identifying the many unknown compounds encountered when conducting untargeted metabolic profiling using liquid chromatography/mass spectrometry. While numerous methods have been developed for assigning heuristic scores to rank the degree of fit of the observed abundance patterns with theoretical ones, little work has been done to quantify the errors that are associated with the measurements made. Thus, it is generally not possible to determine, in a statistically meaningful manner, whether a given chemical formula would likely be capable of producing the observed data. In this paper, we present a method for constructing confidence regions for the isotopic abundance patterns based on the fundamental distribution of the ion arrivals. Moreover, we develop a method for doing so that makes use of the information pooled together from the measurements obtained across an entire chromatographic peak, as well as from any adducts, dimers, and fragments observed in the mass spectra. This greatly increases the statistical power, thus enabling the analyst to rule out a potentially much larger number of candidate formulas while explicitly guarding against false positives. In practice, small departures from the model assumptions are possible due to detector saturation and interferences between adjacent isotopologues. While these factors form impediments to statistical rigor, they can to a large extent be overcome by restricting the analysis to moderate ion counts and by applying robust statistical methods. Using real metabolic data, we demonstrate that the method is capable of reducing the number of candidate formulas by a substantial amount, even when no bromine or chlorine atoms are present. We argue that further developments in our ability to characterize the data mathematically could enable much more powerful statistical analyses.

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s12566-010-0015-9) contains supplementary material, which is available to authorized users.

Fourier transform ion cyclotron resonance mass spectrometer with coaxial multi-electrode cell ('O-trap'): first experimental demonstration

The conceptual design of the O-trap Fourier transform ion cyclotron resonance (FT-ICR) cell addresses the speed of analysis issue in FT-ICR mass spectrometry. The concept of the O-trap includes separating the functions of ion excitation and detection between two different FT-ICR cell compartments. The detection compartment of the O-trap implements additional internal coaxial electrodes around which ions with excited cyclotron motion revolve. The expected benefits are higher resolving power and the lesser effect of the space charge. In this work we present the first experimental demonstration of the O-trap cell and its features, including the high ion transfer efficiency between two distinct compartments of an ICR cell after excitation of the coherent cyclotron motion. We demonstrate that utilization of the multiple-electrode detection in the O-trap provides mass resolving power enhancement (achieved over a certain time) equal to the order of the frequency multiplication. In an O-trap installed in a 5 T desk-top cryogen-free superconducting magnet, the resolving power of R = 80,000 was achieved for bradykinin [M + 2H](2+) (m/z 531; equivalent to 100,000 when recalculated for m/z 400) in 0.2 s analysis time (transient length), and R = 300,000 at m/z 531 for a 1 s transient. In both cases, detection on the third multiple of the cyclotron frequency was implemented. In terms of the acquisition speed at fixed resolving power, such performance is equivalent to conventional FT-ICR detection using a 15 T magnet.

High-resolution extracted ion chromatography, a new tool for metabolomics and lipidomics using a second-generation orbitrap mass spectrometer

Most analytical methods in metabolomics are based on one of two strategies. The first strategy is aimed at specifically analysing a limited number of known metabolites or compound classes. Alternatively, an unbiased approach can be used for profiling as many features as possible in a given metabolome without prior knowledge of the identity of these features. Using high-resolution mass spectrometry with instruments capable of measuring m/z ratios with sufficiently low mass measurement uncertainties and simultaneous high scan speeds, it is possible to combine these two strategies, allowing unbiased profiling of biological samples and targeted analysis of specific compounds at the same time without compromises. Such high mass accuracy and mass resolving power reduces the number of candidate metabolites occupying the same retention time and m/z ratio space to a minimum. In this study, we demonstrate how targeted analysis of phospholipids as well as unbiased profiling is achievable using a benchtop orbitrap instrument after high-speed reversed-phase chromatography. The ability to apply both strategies in one experiment is an important step forward in comprehensive analysis of the metabolome.

Automated molecular formula determination by tandem mass spectrometry (MS/MS)

Automated software was developed to analyze the molecular formula of organic molecules and peptides based on high-resolution MS/MS spectroscopic data. The software was validated with 96 compounds including a few small peptides in the mass range of 138-1569 Da containing the elements carbon, hydrogen, nitrogen and oxygen. A Micromass Waters Q-TOF Ultima Global mass spectrometer was used to measure the molecular masses of precursor and fragment ions. Our software assigned correct molecular formulas for 91 compounds, incorrect molecular formulas for 3 compounds, and no molecular formula for 2 compounds. The obtained 95% success rate indicates high reliability of the software. The mass accuracy of the precursor ion and the fragment ions, which is critical for the success of the analysis, was high, i.e. the accuracy and the precision of 850 data were 0.0012 Da and 0.0016 Da, respectively. For the precursor and fragment ions below 500 Da, 60% and 90% of the data showed accuracy within < or = 0.001 Da and < or = 0.002 Da, respectively. The precursor and fragment ions above 500 Da showed slightly lower accuracy, i.e. 40% and 70% of them showed accuracy within < or = 0.001 Da and < or = 0.002 Da, respectively. The molecular formulas of the precursor and the fragments were further used to analyze possible mass spectrometric fragmentation pathways, which would be a powerful tool in structural analysis and identification of small molecules. The method is valuable in the rapid screening and identification of small molecules such as the dereplication of natural products, characterization of drug metabolites, and identification of small peptide fragments in proteomics. The analysis was also extended to compounds that contain a chlorine or bromine atom.

Extent of N-terminal modifications in cytosolic proteins from eukaryotes

Most proteins in all organisms undergo crucial N-terminal modifications involving N-terminal methionine excision, N-alpha-acetylation or N-myristoylation (N-Myr), or S-palmitoylation. We investigated the occurrence of these poorly annotated but essential modifications in proteomes, focusing on eukaryotes. Experimental data for the N-terminal sequences of animal, fungi, and archaeal proteins, were used to build dedicated predictive modules in a new software. In vitro N-Myr experiments were performed with both plant and animal N-myristoyltransferases, for accurate prediction of the modification. N-terminal modifications from the fully sequenced genome of Arabidopsis thaliana were determined by MS. We identified 105 new modified protein N-termini, which were used to check the accuracy of predictive data. An accuracy of more than 95% was achieved, demonstrating (i) overall conservation of the specificity of the modification machinery in higher eukaryotes and (ii) robustness of the prediction tool. Predictions were made for various proteomes. Proteins that had undergone both N-terminal methionine (Met) cleavage and N-acetylation were found to be strongly overrepresented among the most abundant proteins, in contrast to those retaining their genuine unblocked Met. Here we propose that the nature of the second residue of an ORF is a key marker of the abundance of the mature protein in eukaryotes.

Mass spectrometry-based metabolomics: accelerating the characterization of discriminating signals by combining statistical correlations and ultrahigh resolution

A strategy combining autocorrelation matrices and ultrahigh resolution mass spectrometry (MS) was developed to optimize the characterization of discriminating ions highlighted by metabolomics. As an example, urine samples from rats treated with phenobarbital (PB) were analyzed by ultrahigh-pressure chromatography with two different eluting conditions coupled to time-of-flight mass spectrometric detection in both the positive and negative electrospray ionization modes. Multivariate data analyses were performed to highlight discriminating variables from several thousand detected signals: a few hundred signals were found to be affected by PB, whereas a few tenths of them were linked to its metabolism. Autocorrelation matrices were then applied to eliminate adduct and fragment ions. Finally, the characterization of the ions of interest was performed with ultrahigh-resolution mass spectrometry and sequential MS(n) experiments, by using a LC-LTQ-Orbitrap system. The use of different eluting conditions was shown to drastically impact on the chromatographic retention and ionization of compounds, thus providing a way to obtain more exhaustive metabolic fingerprints, whereas autocorrelation matrices allowed one to focus the identification work on the most relevant ions. By using such an approach, 14 PB metabolites were characterized in rat urines, some of which have not been reported in the literature.

Biosynthetic intermediate analysis and functional homology reveal a saxitoxin gene cluster in cyanobacteria

Saxitoxin (STX) and its analogues cause the paralytic shellfish poisoning (PSP) syndrome, which afflicts human health and impacts coastal shellfish economies worldwide. PSP toxins are unique alkaloids, being produced by both prokaryotes and eukaryotes. Here we describe a candidate PSP toxin biosynthesis gene cluster (sxt) from Cylindrospermopsis raciborskii T3. The saxitoxin biosynthetic pathway is encoded by more than 35 kb, and comparative sequence analysis assigns 30 catalytic functions to 26 proteins. STX biosynthesis is initiated with arginine, S-adenosylmethionine, and acetate by a new type of polyketide synthase, which can putatively perform a methylation of acetate, and a Claisen condensation reaction between propionate and arginine. Further steps involve enzymes catalyzing three heterocyclizations and various tailoring reactions that result in the numerous isoforms of saxitoxin. In the absence of a gene transfer system in these microorganisms, we have revised the description of the known STX biosynthetic pathway, with in silico functional inferences based on sxt open reading frames combined with liquid chromatography-tandem mass spectrometry analysis of the biosynthetic intermediates. Our results indicate the evolutionary origin for the production of PSP toxins in an ancestral cyanobacterium with genetic contributions from diverse phylogenetic lineages of bacteria and provide a quantum addition to the catalytic collective available for future combinatorial biosyntheses. The distribution of these genes also supports the idea of the involvement of this gene cluster in STX production in various cyanobacteria.

High-resolution mass spectrometers

Over the past decade, mass spectrometry has been revolutionized by access to instruments of increasingly high mass-resolving power. For small molecules up to approximately 400 Da (e.g., drugs, metabolites, and various natural organic mixtures ranging from foods to petroleum), it is possible to determine elemental compositions (C(c)H(h)N(n)O(o)S(s)P(p)...) of thousands of chemical components simultaneously from accurate mass measurements (the same can be done up to 1000 Da if additional information is included). At higher mass, it becomes possible to identify proteins (including posttranslational modifications) from proteolytic peptides, as well as lipids, glycoconjugates, and other biological components. At even higher mass ( approximately 100,000 Da or higher), it is possible to characterize posttranslational modifications of intact proteins and to map the binding surfaces of large biomolecule complexes. Here we review the principles and techniques of the highest-resolution analytical mass spectrometers (time-of-flight and Fourier transform ion cyclotron resonance and orbitrap mass analyzers) and describe some representative high-resolution applications.

Rapid detection of cyanobacterial toxins in precursor ion mode by liquid chromatography tandem mass spectrometry

We established an analytical method based on liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) in the precursor ion mode for simultaneous qualitative monitoring of various groups of cyanobacterial toxins. The toxin groups investigated were paralytic shellfish poisoning (PSP) toxins, anatoxins (ANAs), cylindrospermopsins (CYNs), microcystins (MCs), and nodularins (NODs), including rare and uncharacterized derivatives found in plankton and water matrices. Alternative analytical methods based on tandem mass spectrometry commonly operate in multiple reaction monitoring (MRM) mode and depend on prior knowledge of putative toxigenicity of the cyanobacterium species and strain, and the expected toxin variants. In contrast, the precursor ion mode yields diagnostic mass fragments for the detection of characteristic compounds of the different toxin classes and thus allows monitoring of a large set of unspecified cyanotoxins of various groups, even when the species composition is undetermined or uncertain. This rapid method enables screening for a wide spectrum of toxic cyanobacterial metabolites and degradation products in a single chromatographic separation with detection limits at nanogram levels. The precursor ion technique is a valuable adjunct to existing mass spectrometric methods for cyanotoxins, although it is not a complete replacement for detailed quantitative analysis requiring comprehensive sample cleanup.

New analytical strategies in studying drug metabolism

Identification and elucidation of the structures of metabolites play major roles in drug discovery and in the development of pharmaceutical compounds. These studies are also important in toxicology or doping control with either pharmaceuticals or illicit drugs. This review focuses on: new analytical strategies used to identify potential metabolites in biological matrices with and without radiolabeled drugs; use of software for metabolite profiling; interpretation of product spectra; profiling of reactive metabolites; development of new approaches for generation of metabolites; and detection of metabolites with increased sensitivity and simplicity. Most of the new strategies involve mass spectrometry (MS) combined with liquid chromatography (LC).

Metabolic flux elucidation for large-scale models using 13C labeled isotopes

A key consideration in metabolic engineering is the determination of fluxes of the metabolites within the cell. This determination provides an unambiguous description of metabolism before and/or after engineering interventions. Here, we present a computational framework that combines a constraint-based modeling framework with isotopic label tracing on a large scale. When cells are fed a growth substrate with certain carbon positions labeled with (13)C, the distribution of this label in the intracellular metabolites can be calculated based on the known biochemistry of the participating pathways. Most labeling studies focus on skeletal representations of central metabolism and ignore many flux routes that could contribute to the observed isotopic labeling patterns. In contrast, our approach investigates the importance of carrying out isotopic labeling studies using a more comprehensive reaction network consisting of 350 fluxes and 184 metabolites in Escherichia coli including global metabolite balances on cofactors such as ATP, NADH, and NADPH. The proposed procedure is demonstrated on an E. coli strain engineered to produce amorphadiene, a precursor to the antimalarial drug artemisinin. The cells were grown in continuous culture on glucose containing 20% [U-(13)C]glucose; the measurements are made using GC-MS performed on 13 amino acids extracted from the cells. We identify flux distributions for which the calculated labeling patterns agree well with the measurements alluding to the accuracy of the network reconstruction. Furthermore, we explore the robustness of the flux calculations to variability in the experimental MS measurements, as well as highlight the key experimental measurements necessary for flux determination. Finally, we discuss the effect of reducing the model, as well as shed light onto the customization of the developed computational framework to other systems.

Seven Golden Rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry

Background

Structure elucidation of unknown small molecules by mass spectrometry is a challenge despite advances in instrumentation. The first crucial step is to obtain correct elemental compositions. In order to automatically constrain the thousands of possible candidate structures, rules need to be developed to select the most likely and chemically correct molecular formulas.

Results

An algorithm for filtering molecular formulas is derived from seven heuristic rules: (1) restrictions for the number of elements, (2) LEWIS and SENIOR chemical rules, (3) isotopic patterns, (4) hydrogen/carbon ratios, (5) element ratio of nitrogen, oxygen, phosphor, and sulphur versus carbon, (6) element ratio probabilities and (7) presence of trimethylsilylated compounds. Formulas are ranked according to their isotopic patterns and subsequently constrained by presence in public chemical databases. The seven rules were developed on 68,237 existing molecular formulas and were validated in four experiments. First, 432,968 formulas covering five million PubChem database entries were checked for consistency. Only 0.6% of these compounds did not pass all rules. Next, the rules were shown to effectively reducing the complement all eight billion theoretically possible C, H, N, S, O, P-formulas up to 2000 Da to only 623 million most probable elemental compositions. Thirdly 6,000 pharmaceutical, toxic and natural compounds were selected from DrugBank, TSCA and DNP databases. The correct formulas were retrieved as top hit at 80–99% probability when assuming data acquisition with complete resolution of unique compounds and 5% absolute isotope ratio deviation and 3 ppm mass accuracy. Last, some exemplary compounds were analyzed by Fourier transform ion cyclotron resonance mass spectrometry and by gas chromatography-time of flight mass spectrometry. In each case, the correct formula was ranked as top hit when combining the seven rules with database queries.

Conclusion

The seven rules enable an automatic exclusion of molecular formulas which are either wrong or which contain unlikely high or low number of elements. The correct molecular formula is assigned with a probability of 98% if the formula exists in a compound database. For truly novel compounds that are not present in databases, the correct formula is found in the first three hits with a probability of 65–81%. Corresponding software and supplemental data are available for downloads from the authors' website.

Current and future trends in the application of HPLC-MS to metabolite-identification studies

Metabolic determinations are an integral part of every drug-discovery and drug-development program. Recent emphasis has been to increase sample throughput while, at the same time, increase information content within assays. To this end, screening for potential drug-drug interactions, overall metabolic stability and metabolite profiles are used early in discovery to select compounds for development. The throttle on the metabolism discovery engine is limited by the time required for data processing and reporting of the information-rich assays used in discovery-stage metabolism studies. In this article I examine how to increase throughput screening in drug discovery using novel liquid chromatography and mass spectrometry as the preferred analytical tool, and potential solutions to maximize output.

Elucidating the mode-of-action of compounds from metabolite profiling studies

Metabolite profiling has been carried out for decades and is as such not a new research area. However, the field has attracted increasing attention in the last couple of years, and the term metabolome is now often used to describe the complete pool of metabolites associated with an organism at any given time. Mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy are the best candidates for comprehensive analysis of the metabolome and the application of these technologies is presented in this chapter. In this relation, the importance of efficient metabolite screening for discovery of novel drugs is discussed. Related to metabolite profiling, the principals underlying the application of labeled substrates to quantify in vivo metabolic fluxes are introduced, and the chapter is concluded by discussing the perspectives of metabolite measurements in systems biology.

Toxicity and toxin identification in Colomesus asellus, an Amazonian (Brazil) freshwater puffer fish

Toxicity and toxin identification in Colomesus asellus, an Amazonian (Brazil) freshwater puffer fish. By using four different techniques--mouse bioassay, ELISA, HPLC and mass spectrometry-we evaluated the toxicity in the extracts of C. asellus, a freshwater puffer fish from the rivers of the Amazon, and identified for the first time the components responsible for its toxicity. The T20G10 monoclonal antibody raised against TTX, and employed in an indirect competitive enzyme immunoassay, showed very low affinity for the C. asellus extracts, indicating that TTX and its analogs are not the main toxic components of the extracts. This antibody was efficient in detecting presence of TTX in a total extract of Sphoeroides spengleri, which is one of the most toxic puffer fish found in the Atlantic coast. Extracts of C. asellus were toxic when administered intraperitonially into mice with an average toxicity of 38.6+/-12 mouse unit (MU)/g, while HPLC analysis indicated a lower toxin content (7.6+/-0 5MU/g). The HPLC profile showed no traces of TTX, but only the presence of PSPs (STX, GTX 2 and GTX 3). These toxins were also confirmed by electrospray ionization mass spectrometry.

Detection and Characterization of Metabolites in Biological Matrices Using Mass Defect Filtering of Liquid Chromatography/High Resolution Mass Spectrometry Data

An improved mass defect filter (MDF) method employing both drug and core structure filter templates was applied to the processing of high resolution liquid chromatography/mass spectrometry (LC/MS) data for the detection and structural characterization of oxidative metabolites with mass defects similar to or significantly different from those of the parent drugs. The effectiveness of this approach was investigated using nefazodone as a model compound, which is known to undergo multiple common and uncommon oxidative reactions. Through the selective removal of all ions that fall outside of the preset filter windows, the MDF process facilitated the detection of all 14 nefazodone metabolites presented in human liver microsomes in the MDF-filtered chromatograms. The capability of the MDF approach to remove endogenous interferences from more complex biological matrices was examined by analyzing omeprazole metabolites in human plasma. The unprocessed mass chromatogram showed no distinct indication of metabolite peaks; however, after MDF processing, the metabolite peaks were easily identified in the chromatogram. Compared with precursor ion scan and neutral loss scan techniques, the MDF approach was shown to be more effective for the detection of metabolites in a complex matrix. The comprehensive metabolite detection capability of the MDF approach, together with accurate mass determination, makes high resolution LC/MS a useful tool for the screening and identification of both common and uncommon drug metabolites.

Characterizing the Phospholipid Profiles in Mammalian Tissues by MALDI FTMS

Discussed here is an analytical method for profiling lipids and phospholipids directly from mammalian tissues excised from Mus musculus (house mouse). Biochemical analysis was accomplished through the use of matrix-assisted laser desorption/ionization (MALDI) Fourier transform mass spectrometry, where whole tissue sections of mouse brain, heart, and liver were investigated. Lipid and phospholipid ions create complex MALDI mass spectra containing multiple ions with different m/z values corresponding to the same fundamental chemical species. When a computational sorting approach is used to group these ions, the standard deviation for observed relative chemical abundance can be reduced to 6.02%. Relative standard deviations of 10% are commonly accepted for standard chromatographic phospholipid analyses. Average mass measurement accuracy for 232 spectra representing three tissue types from 12 specimens was calculated to be 0.0053 Da. Further it is observed, that the data and the analysis between all the animals have near-identical phospholipid contents in their brain, heart, and liver tissues, respectively. In addition to the need to accurately measure relative abundances of phospholipid species, it is essential to have adequate mass resolution for complete and accurate overall analysis. It is reasonable to make mass composition assignments with spectral resolving power greater than 8000. However, results from the present study reveal 14 instances (C12 carbon isotope) of multiple m/z ions having the same nominal value that require greater resolution in order that overlap will not occur. Spectra measured here have an average resolving power of 12 000. It is established that high mass resolution and mass accuracy coupled with MALDI ionization provide for rapid and accurate phospholipid analysis of mammalian tissue sections.

Accurate mass measurement using Fourier transform ion cyclotron resonance mass spectrometry for structure elucidation of designer drug analogs of tadalafil, vardenafil and sildenafil in herbal and pharmaceutical matrices

Phosphodiesterase type 5 (PDE-5) inhibitors are a class of drugs used primarily in the treatment of erectile dysfunction. The Food and Drug Administration (FDA) approved PDE-5 inhibitors include sildenafil citrate, vardenafil hydrochloride and tadalafil. In this study, accurate mass measurements were made by electrospray ionization (ESI) using Fourier transform ion cyclotron resonance mass spectrometry (FTICRMS) to elucidate the structures of sildenafil, tadalafil and vardenafil analogs that were found in products marketed as dietary supplements. Initial detection of these analogs was accomplished through routine screening of suspect samples by liquid chromatography/electrospray ionization multi-stage mass spectrometry (LC/ESI-MS(n)) on a low-resolution ion trap instrument. The chromatographic behavior and mass spectrometric fragmentation patterns observed were often similar to those observed for FDA approved PDE-5 inhibitors. The mass accuracy and resolving power associated with FTICRMS allows for the determination of elemental compositions. Elucidation of the product ion structures for the analogs was accomplished through the use of accurate mass measurements with the aid of Mass Frontier software (version 4.0). Using FTICRMS, accurate masses with measurement errors averaging <0.4 ppm were achieved, allowing assignment of one possible elemental formula to each fragment ion. The mass measurement errors associated with [M + H](+) for the analogs aminotadalafil, piperidino vardenafil, hydroxyacetildenafil and piperidino acetildenafil were 0.1, 0.0, 0.1 and 0.5 ppm, respectively. Based on the accuracy of the measurements, structural assignments could be made with a high degree of confidence.

Place of pattern in proteomic biomarker discovery

The role of pattern in biomarker discovery and clinical diagnosis is examined in its historical context. The use of MS-derived pattern is treated as a logical extension of prior applications of non-MS-derived pattern. Criticisms pertaining to specific technology platforms and analytic methodologies are considered separately from the larger issues of pattern utility and deployment in biomarker discovery. We present a hybrid strategy that marries the desirable attributes of high-information content MS pattern with the capability to obtain identity, and explore the key steps in establishing a data analysis pipeline for pattern-based biomarker discovery.

A comprehensive and comparative analysis for MALDI FTMS lipid and phospholipid profiles from biological samples

Described here is a computationally automated method for translating complex accurate mass spectra into biologically relevant and meaningful data. Rapid profiling of detailed high resolution mass spectra resulting from direct analysis of whole cells and tissues by matrix-assisted laser desorption/ionization (MALDI) Fourier transform mass spectrometry (FTMS) is discussed. Lipid and phospholipid ions create complex spectra containing multiple m/z values corresponding to the same fundamental chemical species. A computational approach is employed to sort ions, with mass to charge ratios lower than m/z 1000, into groups of similar lipid and phospholipid compositions for comprehensive and rapid analysis. By sorting or binning ions in this manner, variations in the degree of cation exchange can be avoided, thus increasing the comparability of the data. The result is displayed as a histogram that is easily interpretable and comparable with similar analyses and is particularly useful for direct comparison of similar tissues. Spectra of leaves from a healthy Prunus persica (peach) tree are compared with those from leaves infected by the fungus Taphrina deformans. Although the infection can be seen as a difference in leaf structure and by visual inspection of the mass spectra, the method described here details the chemical difference in phospholipid compositions and their relative abundances.