All-ion Fragmentation Research Articles

Multi-dimensional characterization and identification of sterols in untargeted LC-MS analysis using all ion fragmentation technology

Sterols are an important type of lipids, and play many important roles in physiological and pathological processes. However, comprehensive analysis of sterols especially identification of unknown sterols is challenging. In this work, LC-MS with all ion fragmentation (AIF) technology was developed for untargeted analysis of sterols in biological samples. AIF technology provided holistic and multi-dimensional characterization for both knowns and unknowns sterols, including accurate m/z, isotope pattern, retention time (RT), and co-eluted peak profiles between MS1 and MS2 ions in one analysis. We further developed an analysis strategy by integrating the multi-dimensional properties to support unambiguous identification of sterols, including distinguishing sterol isomers. The developed strategy enabled to identify a total of 23 sterols in mouse samples, and quantified 19 sterols in mouse liver tissues. More importantly, we demonstrated that AIF based multi-dimensional analysis provided a possibility to identify sterols without chemical standards and facilitated to discover novel compounds with sterol-like structures in biological samples. In summary, we employed the LC-MS based AIF technology to develop multi-dimensional characterization and identification of both known and unknown sterols in complex biological samples. The comprehensive analysis of sterols facilitates to provide molecular insights to many physiological and pathological activities in biology.

Chemical characterization of eight herbal liqueurs by means of liquid chromatography coupled with ion mobility quadrupole time-of-flight mass spectrometry

Herbal liqueurs are a large group of diverse alcoholic beverages with an ancient tradition produced by maceration of various herbs and spices and are commonly drunken before or after a meal to aid in the digestion because of their potential functional properties. In the presented work, eight different commercial herbal liqueurs were investigated with regard to their composition of phenolic compounds by liquid chromatography ion mobility quadrupole time-of-flight mass spectrometry (LC-IM-QTOF-MS). This multidimensional analytical platform uses all-ion fragmentation for a deep coverage of the foodome. After an extensive data clean-up, 3225 features were found. 213 features were manually annotated due to the absence of databases and software tools able to consider the drift time or Collison Cross Section (CCS) together with high resolution MS/MS spectra for identification. The identified compounds reflected the large variance between the investigated samples and a wealth of potential bioactive compounds that these liqueurs harbor.

Phospholipidomics of peripheral blood mononuclear cells (PBMCs): the tricky case of children with autism spectrum disorder (ASD) and their healthy siblings.

Autism spectrum disorder (ASD) is a broad and heterogeneous group of neurological developmental disorders characterized by impaired social interaction and communication, restricted and repetitive behavioural patterns, and altered sensory processing. Currently, no reliable ASD molecular biomarkers are available. Since immune dysregulation has been supposed to be related with ASD onset and dyslipidaemia has been recognized as an early symptom of biological perturbation, lipid extracts from peripheral blood mononuclear cells (PBMCs), consisting primarily of lymphocytes (T cells, B cells, and NK cells) and monocytes, of 38 children with ASD and their non-autistic siblings were investigated by hydrophilic interaction liquid chromatography (HILIC) coupled with electrospray ionization and Fourier-transform mass spectrometry (ESI-FTMS). Performances of two freeware software for data extraction and processing were compared with acquired reliable data regardless of the used informatics. A reduction of variables from 1460 by the untargeted XCMS to 324 by the semi-untargeted Alex123 software was attained. All-ion fragmentation (AIF) MS scans along with Alex123 software were successfully applied to obtain information related to fatty acyl chain composition of six glycerophospholipid classes occurring in PBMC. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were explored to verify the occurrence of significant differences in the lipid pool composition of ASD children compared with 36 healthy siblings. After rigorous statistical validation, we conclude that phospholipids extracted from PBMC of children affected by ASD do not exhibit diagnostic biomarkers. Yet interindividual variability comes forth from this study as the dominant effect in keeping with the existing phenotypic and etiological heterogeneity among ASD individuals. Graphical abstract.

Pyrrolizidine alkaloid profiling of four Boraginaceae species from Northern Germany and implications for the analytical scope proposed for monitoring of maximum levels

ABSTRACT Pyrrolizidine alkaloids (PAs) and their corresponding N-oxides (PANOs) have been determined in food and feed at levels relevant for consumer health. More than 660 different PAs have been detected, but few are available as reference substances for analytical demands. In the context of the European legislation on maximum levels of PAs in food products, a defined analytical scope of 21 PAs for determination has been suggested. An expansion of the scope from 21 to 35 PAs, including 14 structural isomers, is currently under discussion. In the present study, a target screening method was established for a comprehensive characterisation of PA profiles of the species Echium vulgare, Heliotropium europaeum, Cynoglossum officinale and Symphytum spp. to assess whether an expansion of the analytical scope is required to quantitatively cover the total PA contents of Boraginaceae species. The scope of the method comprised known and unknown PAs previously screened and confirmed in the respective plant extracts. A total of 176 PAs and PANOs were detected. The toxic 1,2-unsaturated PAs represent the predominant PA type with about 98% of the mean total content. This PA profiling demonstrates that an expansion of the scope from 21 to 35 PAs is required to adequately cover the mean total PA contents of Cynoglossum officinale and H. europaeum, whereas in the case of Symphytum spp. and Echium vulgare an expansion would not be necessary. Abbreviations Pyrrolizidine alkaloid: PA, Pyrrolizidine alkaloid N-oxide: PANO, European Food Safety Authority: EFSA, German Federal Institute for Risk Assessment: BfR, ultra-high performance liquid chromatography: UHPLC, high-resolution: HR, tandem mass spectrometer: MS/MS, multiple reaction monitoring: MRM, data-independent MS2: ddms2, electrospray ionisation: ESI, limit of detection: LOD, limit of quantification: LOQ, gas chromatography coupled with mass spectrometry: GC-MS, fragmentation (data): MS2 (data), full scan: MS1, variable data-independent acquisition: vDIA, monoester esterified with a necic acid at position C9 of the necine base: O9-monoester, relative proportion: rel. prop., intraperitoneal: i.p., intravenous: i.v., higher-energy C-trap dissociation: HCD, all-ion fragmentation: AIF, parallel reaction monitoring: PRM

HILIC-ESI-FTMS with All Ion Fragmentation (AIF) Scans as a Tool for Fast Lipidome Investigations.

Lipidomics suffers from the lack of fast and reproducible tools to obtain both structural information on intact phospholipids (PL) and fatty acyl chain composition. Hydrophilic interaction liquid chromatography with electrospray ionization coupled to an orbital-trap Fourier-transform analyzer operating using all ion fragmentation mode (HILIC-ESI-FTMS-AIF MS) is seemingly a valuable resource in this respect. Here, accurate m/z values, HILIC retention times and AIF MS scan data were combined for PL assignment in standard mixtures or real lipid extracts. AIF scans in both positive and negative ESI mode, achieved using collisional induced dissociation for fragmentation, were applied to identify both the head-group of each PL class and the fatty acyl chains, respectively. An advantage of the AIF approach was the concurrent collection of tandem MS-like data, enabling the identification of linked fatty acyl chains of precursor phospholipids through the corresponding carboxylate anions. To illustrate the ability of AIF in the field of lipidomics, two different types of real samples, i.e., the lipid extracts obtained from human plasma and dermal fibroblasts, were examined. Using AIF scans, a total of 253 intact lipid species and 18 fatty acids across 4 lipid classes were recognized in plasma samples, while FA C20:3 was confirmed as the fatty acyl chain belonging to phosphatidylinositol, PI 38:3, which was found to be down-regulated in fibroblast samples of Parkinson’s disease patients.

Drug metabolite identification using ultrahigh-performance liquid chromatography-ultraviolet spectroscopy and parallelized scans on a tribrid Orbitrap mass spectrometer.

To capture all metabolites in metabolite identification studies, MS/MS information is required in both positive and negative ionization mode, usually involving several sample injections to gain all information about samples. A high-resolution and high mass accuracy quadrupole/linear trap/Orbitrap tribrid instrument was used to gain this information in a novel single injection 'capture-all' approach to metabolite identification. Diclofenac, a model compound, was incubated in human and rat hepatocytes. These incubated samples were run using an ultrahigh-performance liquid chromatography/ultraviolet (UHPLC-UV) system coupled to a Thermo Fusion tribrid mass spectrometer. Five parallel scans were used: positive and negative ion full scan, data-dependent MS/MS, both high energy dissociation and collision-induced dissociation, and data-independent all ion fragmentation (AIF) spectra were collected in positive and negative ion mode. Nine metabolites were identified; a metabolite observed in the UV trace, but not positive ion full scan MS, was detected in the same sample injection by negative ion full scan MS. This was identified as a sulphate metabolite, and the corresponding negative ion AIF allowed for some structural elucidation. The use of a photo-diode array (PDA) detector allowed for spectral assessment in case of changes in absorbance spectra, and the subsequent semi-quantification of metabolites. This method provided good-quality MS/MS data across the m/z range in both positive and negative ion mode. The addition of both negative ion full scan MS and negative ion MS/MS allowed for the detection and structural elucidation of metabolites not observed in positive ion mode. The use of the PDA detector allowed for the semi-quantification of metabolites.

Creating a Reliable Mass Spectral-Retention Time Library for All Ion Fragmentation-Based Metabolomics.

Accurate metabolite identification remains one of the primary challenges in a metabolomics study. A reliable chemical spectral library increases the confidence in annotation, and the availability of raw and annotated data in public databases facilitates the transfer of Liquid chromatography coupled to mass spectrometry (LC–MS) methods across laboratories. Here, we illustrate how the combination of MS2 spectra, accurate mass, and retention time can improve the confidence of annotation and provide techniques to create a reliable library for all ion fragmentation (AIF) data with a focus on the characterization of the retention time. The resulting spectral library incorporates information on adducts and in-source fragmentation in AIF data, while noise peaks are effectively minimized through multiple deconvolution processes. We also report the development of the Mass Spectral LIbrary MAnager (MS-LIMA) tool to accelerate library sharing and transfer across laboratories. This library construction strategy improves the confidence in annotation for AIF data in LC–MS-based metabolomics and will facilitate the sharing of retention time and mass spectral data in the metabolomics community.

Advancing untargeted metabolomics using data-independent acquisition mass spectrometry technology.

Metabolomics quantitatively measures metabolites in a given biological system and facilitates the understanding of physiological and pathological activities. With the recent advancement of mass spectrometry (MS) technology, liquid chromatography-mass spectrometry (LC-MS) with data-independent acquisition (DIA) has been emerged as a powerful technology for untargeted metabolomics due to its capability to acquire all MS2 spectra and high quantitative accuracy. In this trend article, we first introduced the basic principles of several common DIA techniques including MSE, all ion fragmentation (AIF), SWATH, and MSX. Then, we summarized and compared the data analysis strategies to process DIA-based untargeted metabolomics data, including metabolite identification and quantification. We think the advantages of the DIA technique will enable its broad application in untargeted metabolomics.

Metabolomic Analysis of Yeast and Human Cells: Latest Advances and Challenges.

Liquid chromatography-mass spectrometry (LC-MS) based nontargeted metabolomics has been applied to a wide range of biological samples and can provide information on thousands of compounds. However, reliable identification of the compounds remains a challenge affecting result interpretation. In this protocol, we describe comparable yeast cell and whole blood metabolome sample preparation for extracting similar compound groups, and we present a LC-MS method using the all ion fragmentation (AIF) approach for the purposes of increasing accuracy in metabolite annotation. Our method enables database-dependent targeted as well as nontargeted metabolomics analysis from the same data acquisition, while simultaneously improving the accuracy in metabolite identification to increase the quality of the resulting biological information.

Development of simultaneous targeted metabolite quantification and untargeted metabolomics strategy using dual-column liquid chromatography coupled with tandem mass spectrometry

Targeted quantification and untargeted global profiling are the two mainstream approaches, a merging of which could provide enhanced analytical potential in metabolomics research. Here, a simultaneous targeted quantification and untargeted metabolomics (STQUM) strategy was developed for more efficient, accurate and comprehensive metabolomics research by using ultra-high-performance liquid chromatography coupled with high-resolution tandem mass spectrometry (UPLC-HRMS/MS). First, we selected 110 cancer-related metabolites as targets and established a dual LC sequential separation method for simultaneous analysis of strong and weak polar metabolites. In order to achieve efficient acquisition for synchronous qualitative and quantitative analysis, high-resolution, data-dependent parallel reaction monitoring (PRM) method and data-independent all ion fragmentation (AIF) method were established. Their performance in targeted confirmation and quantification, and untargeted analysis were systematically investigated and assessed. In total, 78 metabolites were confidently confirmed in positive ion mode in both PRM and AIF assays, in which 73 metabolites can be accurately quantified. In addition, simultaneously untargeted profiling of 4651 features of high reliability and validity were achieved. Both AIF and PRM methods revealed high confidence, sensitivity and accuracy. In the STQUM approach, another 15 metabolites could be accurately quantified in negative ion mode. The method offers a new perspective for merging the hypothesis-based targeted quantitative validation and untargeted biomarkers discovery in one run for improved analysis efficiency and integrity.

Comprehensive analysis by liquid chromatography Q-Orbitrap mass spectrometry: Fast screening of peptides and organic molecules.

The number of substances nominally listed in the prohibited list of the World Anti-Doping Agency increases each year. Moreover, many of these substances do not have a single analytical target and must be monitored through different metabolites, artifacts, degradation products, or biomarkers. A new analytical method was developed and validated for the simultaneous analysis of peptides and organic molecules using a single sample preparation and LC-Q-HRMS detection. The simultaneous analysis of 450 target molecules was performed after cleanup on a mixed-mode solid-phase extraction cartridge, combined with untreated urine. The cleanup solvent and reconstitution solvent were the most important parameters for achieving a comprehensive sample preparation approach. A fast chromatographic run based on a multistep gradient was optimized under different flows; the detection of all substances without isomeric coelution was achieved in 11minutes, and the chromatographic resolution was considered a critical parameter, even in high-resolution mass spectrometry detection. The mass spectrometer was set to operate by switching between positive and negative ionization mode for FULL-MS, all-ion fragmentation, and FULL-MS/MS2 . The suitable parameters for the curved linear trap (c-trap) conditions were determined and found to be the most important factors for the development of the method. Only FULL-MS/MS2 enables the detection of steroids and peptides at concentrations lower than the minimum required performance levels set by World Anti-Doping Agency (1ngmL-1 ). The combination of the maximum injection time of the ions into the c-trap, multiplexing experiments, and loop count under optimized conditions enabled the method to be applied to over 10000 samples in only 2months during the 2016 Rio Summer Olympic and Paralympic Games. The procedure details all aspects, from sample preparation to mass spectrometry detection. FULL-MS data acquisition is performed in positive and negative ion mode simultaneously and can be applied to untargeted approaches.

The black market for anorectic agents: A case study of amfepramone

The black market for pharmaceuticals has grown in recent years, largely due to the easy trade of products over the Internet. This trend poses a potential risk to consumers’ health, as it is not always possible to identify the origin of the products, which can be counterfeit. This study was designed to identify capsule components by full-scan mass spectrometry analyses coupled to liquid chromatography based on a single injection of the capsule material previously solubilized in methanol. The simultaneous analysis of other compounds that could be used as adulterants was performed in a fast chromatographic run based in a multi-step gradient, only 11 minutes were necessary to evaluated all the substance without isomeric co-elution. The mass spectrometer was set to operate switching the ionization mode: positive and negative, for FULL HRMS and all-ion fragmentation acquisition, simultaneously. By WhatsApp groups, the GloboNews reporting team purchased a box of amfepramone capsules from dealers of counterfeit controlled drugs. The contents of the capsules analyzed did not contain any traces of amfepramone or any anorectic agents. The result of this study suggest the need for greater and more effective control by competent authorities to avoid black market medicines and to combat drug smuggling and counterfeiting.

A Generic HPLC Method for Absolute Quantification of Oxidation in Monoclonal Antibodies and Fc-Fusion Proteins Using UV and MS Detection.

Oxidation of biopharmaceuticals may affect their bioactivity, serum half-life, and (bio)chemical stability. The Fc domain of IgG monoclonal antibodies (mAbs) contains two methionine residues which are susceptible to oxidation. Here, we present a middle-down approach employing the cysteine protease IdeS under reducing conditions to obtain three mAb subunits of approximately 25 kDa: Fc/2, Fd', and LC. These subunits were separated by ion-pair reversed-phase high-performance liquid chromatography (IP-RP-HPLC) and detected by UV spectroscopy as well as Orbitrap mass spectrometry (MS), as well as MS upon all-ion fragmentation (AIF-MS). We evaluated the feasibility of three strategies for absolute quantification of oxidation in the Fc region of hydrogen peroxide-stressed Rituximab, using a single, commercially available software platform both for data acquisition and evaluation: UV spectroscopy, full-scan MS, and monitoring of product ions obtained by AIF-MS. UV spectroscopy showed the lowest limits of quantification (LOQ) (0.96 ng μL-1) and featured the lowest relative process standard deviation (Vx0%) of 7.2% compared to MS and AIF-MS with LOQs of 1.24-4.32 ng μL-1 and relative process standard deviations of 9.0-14%, respectively. Our approach is generic in that it allows monitoring and quantification of oxidation in the Fc regions of fully human and humanized IgG1 mAbs as well as of Fc-fusion proteins. This is exemplified by limits of detection of 1.2%, 1.0%, and 1.2% of oxidation in drug products containing the biopharmaceuticals Rituximab, Adalimumab, and Etanercept, respectively. The presented method is an attractive alternative to conventional time-intensive peptide mapping which is prone to artificial oxidation due to extensive sample preparation.

Development of a Liquid Chromatography-High Resolution Mass Spectrometry Metabolomics Method with High Specificity for Metabolite Identification Using All Ion Fragmentation Acquisition.

High-resolution mass spectrometry (HRMS)-based metabolomics approaches have made significant advances. However, metabolite identification is still a major challenge with significant bottleneck in translating metabolomics data into biological context. In the current study, a liquid chromatography (LC)-HRMS metabolomics method was developed using an all ion fragmentation (AIF) acquisition approach. To increase the specificity in metabolite annotation, four criteria were considered: (i) accurate mass (AM), (ii) retention time (RT), (iii) MS/MS spectrum, and (iv) product/precursor ion intensity ratios. We constructed an in-house mass spectral library of 408 metabolites containing AMRT and MS/MS spectra information at four collision energies. The percent relative standard deviations between ion ratios of a metabolite in an analytical standard vs sample matrix were used as an additional metric for establishing metabolite identity. A data processing method for targeted metabolite screening was then created, merging m/z, RT, MS/MS, and ion ratio information for each of the 413 metabolites. In the data processing method, the precursor ion and product ion were considered as the quantifier and qualifier ion, respectively. We also included a scheme to distinguish coeluting isobaric compounds by selecting a specific product ion as the quantifier ion instead of the precursor ion. An advantage of the current AIF approach is the concurrent collection of full scan data, enabling identification of metabolites not included in the database. Our data acquisition strategy enables a simultaneous mixture of database-dependent targeted and nontargeted metabolomics in combination with improved accuracy in metabolite identification, increasing the quality of the biological information acquired in a metabolomics experiment.

Variable-Velocity Traveling-Wave Ion Mobility Separation Enhancing Peak Capacity for Data-Independent Acquisition Proteomics.

High mass accuracy, data-dependent acquisition is the current standard method in mass spectrometry-based peptide annotation and quantification. In high complexity samples, limited instrument scan speeds often result in under-sampling. In contrast, all-ion data-independent acquisition methods bypass precursor selection, alternating high and low collision energies to analyze product and precursor ions across wide mass ranges. Despite capturing data for all events, peptide annotation is limited by inadequate alignment algorithms or overlapping ions. Ion mobility separation can add an orthogonal analytical dimension, reducing ion interference to improve reproducibility, peak capacity, and peptide identifications to rival modern hybrid quadrupole orbitrap systems. Despite the advantages of ion mobility separation in complex proteomics analyses, there has been no quantitative measure of ion mobility resolution in a complex proteomic sample. Here, we present TWIMExtract, a data extraction tool to export defined slices of liquid chromatography/ion mobility/mass spectrometry (LC-IM-MS) data, providing a route to quantify ion mobility resolution from a commercial traveling-wave ion mobility time-of-flight mass spectrometer. Using standard traveling-wave ion mobility parameters (600 m/s, 40 V), 90% of the annotated peptides occupied just 23% of the ion mobility drift space, yet inclusion of ion mobility nearly doubled the overall peak capacity. Relative to fixed velocity traveling-wave ion mobility settings, ramping the traveling-wave velocity increased drift space occupancy, amplifying resolution by 16%, peak capacity by nearly 50%, and peptide/protein identifications by 40%. Overall, variable-velocity traveling-wave ion mobility-mass spectrometry significantly enhances proteomics analysis in all-ion fragmentation acquisition.

Evaluation of MS2 workflows in LC-Q-Orbitrap for pesticide multi-residue methods in fruits and vegetables.

LC-Q-Orbitrap efficiency was evaluated for pesticide multi-residue analysis by using three workflows involving simultaneous MS and MS2 analysis. They were as follows: data-dependent MS2 (dd-MS2), all-ion fragmentation (AIF) and variable data-independent analysis (vDIA). These MS2 workflows were tested for the main method validation parameters such as detection and identification capabilities, repeatability, linear range and quantitation. QuEChER acetonitrile extracts (blanks and spiked with 166 pesticides) of 11 different fruits and vegetables were used for this evaluation. Blank extracts were analysed to evaluate isobaric compounds and potential false identification. Spiked extracts (at 0.01 and 0.1mgkg-1) were analysed to evaluate the false negatives potentially produced (considering a retention mass window of 0.2min). At 0.01mgkg-1, dd-MS2 had the highest identification rate (96-100%, depending on the matrix). In vDIA, it was 86-100% and in AIF 81-100%. But these two last workflows offered more possibilities for applying screening analysis. It was observed that application of the ion ratio criterion established in the SANTE Guidelines for identification can generate some artificial false negative results. It could be overcome by considering a mass error threshold (i.e. 5ppm) as a selected criterion. Detection and quantitation were carried out in full-scan MS. MS2 data were used for identification. Dd-MS2 provided the highest number of points per chromatographic peak, and by that peak area, repeatability was the best (typically <10%). AIF and vDIA were characterised by longer cycle times; thus, the obtained peak area repeatability was slightly worse, but acceptable (<20%). All workflows showed very good linearity in the range 0.01-0.5mgkg-1. The three MS2 workflows were applied to real samples with good results. Graphical abstract LC-Q-Orbitrap was used for pesticide residues analysis in fruit and vegetables. Three approaches to MS2 identificaton were evaluated.

Spectral Counting Approach to Measure Selectivity of High-Resolution LC-MS Methods for Environmental Analysis.

Advances in high-resolution mass spectrometers have allowed for the development of nontargeted screening methods, where data sets can be archived and retrospectively mined as new environmental contaminants are identified. We have developed a spectral counting approach to calculate the selectivities of LC-MS acquisition modes taking mass accuracy, sample matrix, and the analyte properties into account. The selectivities of high-resolution MS (HRMS) alone or in combination with all-ion-fragmentation (AIF), data-independent-acquisition (DIA), and data-dependent-acquisition (DDA) modes, performed on a Q-Exactive Orbitrap were compared by retrospectively screening surface water samples for 95 pharmaceuticals. Samples were reanalyzed using targeted LC-MS/MS to confirm the accuracy of each acquisition method and to quantitate the 29 putatively detected drugs. LC-HRMS provided the lowest calculated selectivities and accordingly produced the highest number of false positives (6). In contrast, DDA provided the highest selectivities, yielding only one false positive; however, it was bias toward the most intense signals resulting in the detection of only 10 compounds. AIF had lower selectivities than traditional LC-MS/MS, produced one false positive and did not detect 6 confirmed compounds. Because of the high-quality archived data, DIA selectivities were better than traditional LC-MS/MS, showed no bias toward the most intense signals, achieved low limits of detection, and confidently detected the greatest number of pharmaceuticals (22) with only one false positive. This spectral counting method can be used across different instrument platforms or samples and provides a robust and empirical estimation of selectivities to give more confident detection of trace analytes.

Metabolomic analysis of the effects of cadmium and copper treatment in Oryza sativa L. using untargeted liquid chromatography coupled to high resolution mass spectrometry and all-ion fragmentation.

While the knowledge of plant metabolomes has increased in the last few years, their response to the presence of toxicants is still poorly understood. Here, we analyse the metabolomic changes in Japanese rice (Oryza sativa var. Japonica) upon exposure to heavy metals (Cd(ii) and Cu(ii)) in concentrations from 10 to 1000 μM. After harvesting, rice metabolites were extracted from aerial parts of the plants and analysed by HPLC (HILIC TSK gel amide-80 column) coupled to a mass spectrometer quadrupole-Orbitrap (Q-Exactive). Full scan and all ion fragmentation (AIF) mass spectrometry modes were used during the analysis. The proposed untargeted metabolomics data analysis strategy is based on the application of the multivariate curve resolution alternating least squares (MCR-ALS) method for feature detection, allowing the simultaneous resolution of pure chromatographic profiles and mass spectra of all metabolites present in the analysed rice extracts. All-ion fragmentation data were used to confirm the identification of MCR-ALS resolved metabolites. A total of 112 metabolites were detected, and 97 of them were subsequently identified and confirmed. Pathway analysis of the observed metabolic changes suggested an underlying similarity of the responses of the plant to Cd(ii) and Cu(ii), although the former treatment appeared to be the more severe of the two. In both cases, secondary metabolism and amino acid-, purine-, carbon- and glycerolipid-metabolism pathways were affected, in a pattern consistent with reduction in plant growth and/or photosynthetic capacity and with induction of defence mechanisms to reduce cell damage.

Development of data-independent acquisition workflows for metabolomic analysis on a quadrupole-orbitrap platform

Untargeted metabolomic profiling has been widely used in recent years. However, the low reproducibility of the data-dependent acquisition (DDA) strategy presents a major bottleneck that considerably limits the reliability of metabolomic studies in biological and clinical research. The data-independent acquisition (DIA) strategy is proposed to solve the above-mentioned problem, and it is gaining popularity. This paper presents a novel approach for performing metabolomic analysis using an untargeted, liquid chromatography–data independent-mass spectrometry (LC-DIA-MS) strategy on a quadrupole-Orbitrap platform. Using chemical standards and metabolites extracted from serum samples, we optimized the LC-DIA-MS parameters to analyze hydrophilic metabolites and lipids. The quantitative performance and analytical reliability were evaluated, and the performances of DIA, DDA, and all-ion fragmentation mode were compared. Finally, as a proof of concept, we applied the constructed DIA workflow to a comparative metabolomic study of papillary thyroid carcinoma (TC) serum samples. Several metabolites, including carnitine, trimethylamine N-oxide, and some amino acids, significantly changed between patients and healthy controls. This study demonstrated the feasibility and advantage of the DIA strategy on untargeted metabolomic analysis for biological study and clinical biomarker screening.

Identification of Unanticipated and Novel N-Acyl L-Homoserine Lactones (AHLs) Using a Sensitive Non-Targeted LC-MS/MS Method.

N-acyl L-homoserine lactones (AHLs) constitute a predominant class of quorum-sensing signaling molecules used by Gram-negative bacteria. Here, we report a sensitive and non-targeted HPLC-MS/MS method based on parallel reaction monitoring (PRM) to identify and quantitate known, unanticipated, and novel AHLs in microbial samples. Using a hybrid quadrupole-high resolution mass analyzer, this method integrates MS scans and all-ion fragmentation MS/MS scans to allow simultaneous detection of AHL parent-ion masses and generation of full mass spectra at high resolution and high mass accuracy in a single chromatographic run. We applied this method to screen for AHL production in a variety of Gram-negative bacteria (i.e. B. cepacia, E. tarda, E. carotovora, E. herbicola, P. stewartii, P. aeruginosa, P. aureofaciens, and R. sphaeroides) and discovered that nearly all of them produce a larger set of AHLs than previously reported. Furthermore, we identified production of an uncommon AHL (i.e. 3-oxo-C7-HL) in E. carotovora and P. stewartii, whose production has only been previously observed within the genera Serratia and Yersinia. Finally, we used our method to quantitate AHL degradation in B. cepacia, E. carotovora, E. herbicola, P. stewartii, P. aeruginosa, P. aureofaciens, the non-AHL producer E. coli, and the Gram-positive bacterium B. subtilis. We found that AHL degradation ability varies widely across these microbes, of which B. subtilis and E. carotovora are the best degraders, and observed that there is a general trend for AHLs containing long acyl chains (≥10 carbons) to be degraded at faster rates than AHLs with short acyl chains (≤6 carbons).