Accurate Mass Matching Research Articles

PolyMatch: Novel Libraries, Algorithms, and Visualizations for Discovering Polymers and Chemical Series.

Polymers are integral components of everyday products, ranging from plastics and emulsifiers to lubricants and detergents. Characterization of these materials at the molecular level is essential to understanding their physicochemical properties and potential health impacts, considering factors such as the number of repeating units, chemical moieties, functional groups, and degree of unsaturation. This study introduces a free open-source vendor neutral software, PolyMatch, designed to annotate polysorbates, polysorbides, polyethylene glycols (PEGs), fatty acid esterified species, and related chemical species based on mass spectral and chromatographic patterns inherent in the repeating nature of chemical moieties. PolyMatch facilitates the generation of MS/MS libraries for polymeric chemical species characterization (with over 800 000 structures with associated fragment masses already built in) and covers the entire liquid chromatography-high-resolution mass spectrometry (LC-HRMS/MS) data-processing workflow. PolyMatch covers peak picking, blank filtering, annotation, data visualization, and sharing of interactive data sets via an HTML link to the community. The software was applied to a Tween 80 mixture, using LC-HRMS/MS on an Agilent 6546 Q-TOF instrument with iterative exclusion for comprehensive fragmentation coverage. PolyMatch automatically assigned 86 features with high confidence at the species level, 362 based on PEG containing fragments and accurate mass matching to a simulated polymer database, and over 10 000 based on being a member of a homologous series (three or more) with CH2CH2O repeating units. The ease of use of PolyMatch and comprehensive coverage with species level assignment is expected to contribute to the advancement of materials science, health research, and product development.

Highly sensitive determination of multiple pesticide residues in foods by supercritical fluid chromatography coupled with ion mobility quadrupole time-of-flight mass spectrometry

This experiment aimed to establish a green, simple and highly sensitive method (supercritical fluid chromatography (SFC) coupled with ion mobility quadrupole time-of-flight mass spectrometry (IM-Q-TOF/MS)) for the detection of multiple pesticides in foods. During the experiments, several important SFC parameters, such as stationary phase, modifier, make-up solution, back-temperature and back-pressure were optimized. Here, single-field collision cross section (CCS) values and multifield CCS values of 20 pesticides were examined by IM-Q-TOF/MS as highly specific parameters with excellent experimental precision. In addition, based on accurate mass matching and fragment ion comparison, mass fragments were obtained by IM-Q-TOF/MS, which elucidated the regularities of compound structure and characteristic fragment ions. Under the optimized conditions, satisfactory linearity (R2 ≥ 0.9989) and recoveries (79.60% to 112.97%) were obtained. The intra- and interday precisions were favorable, with RSDs lower than 4.91 and 7.65%, respectively. Additionally, the method showed low limits of detection (0.1-8.8 ng/mL). The proposed method has been successfully applied to the highly sensitive detection of phenylurea herbicide, triazine herbicides, organophosphorus pesticide, pyrethroid insecticide and acaricide in yam and potato.

Quantification of Serum Metabolites in Early Colorectal Adenomas Using Isobaric Labeling Mass Spectrometry.

A major challenge in reducing the death rate of colorectal cancer is to screen patients using low-invasive testing. A blood test shows a high compliance rate with reduced invasiveness. In this work, a multiplex isobaric tag labeling strategy coupled with mass spectrometry is adopted to relatively quantify primary and secondary amine-containing metabolites in serum for the discovery of metabolite level changes of colorectal cancer. Serum samples from patients at different risk statuses and colorectal cancer growth statuses are studied. Metabolite identification is based on accurate mass matching and/or retention time of labeled metabolite standards. We quantify 40 metabolites across all the serum samples, including 18 metabolites validated with standards. We find significantly decreased levels of threonine and asparagine in the patients with growing adenomas or high-risk adenomas (p < 0.05). Glutamine levels decrease in patients with adenomas of unknown growth status or high-risk adenomas. In contrast, arginine levels are elevated in patients with low-risk adenoma. Receiver operating characteristic analysis shows high sensitivity and specificity of these metabolites for detecting growing adenomas. Based on these results, we conclude that a few metabolites identified here might contribute to distinguishing colorectal patients with growing adenomas from normal individuals and patients with unknown growth status of adenomas.

Untargeted metabolomic analysis of metabolites related to body dysmorphic disorder (BDD)

Body dysmorphic disorder (BDD) is a disorder associated with depression and eating disorders. It often arises from minor defects in appearance or an individual imagining that he or she is defective. However, the mechanisms causing BDD remain unclear, and its pathogenesis and adjuvant treatment methods still need to be explored. Here, we employed a liquid chromatography-mass spectrometry (LC–MS)-based metabolomics approach to identify key metabolic differences in BDD versus healthy patients. We obtained plasma samples from two independent cohorts (including eight BDD patients and eight healthy control patients). Raw data were analyzed using Compound Discoverer to determine peak alignment, retention time correction, and extraction of peak areas. Metabolite structure identification was also obtained using Compound Discoverer by of accurate mass matching (< 10 ppm) and secondary spectral matching queries of compound databases. Next, multidimensional statistical analyses were performed using the ropls R package. These analyses included: unsupervised principal component analysis, supervised partial Least-Squares Discriminant Analysis, and orthogonal partial Least-Squares Discriminant Analysis. We then identified the most promising metabolic signatures associated with BDD across all metabolomic datasets. Principal component analysis showed changes in small-molecule metabolites in patients, and we also found significant differences in metabolite abundance between the BDD and normal groups. Our findings suggest that the occurrence of BDD may be related to metabolites participating in the following KEGG pathways: ABC transporters, purine metabolism, glycine, serine and threonine metabolism, pyrimidine, pyrimidine metabolism, biosynthesis of 12-, 14-, and 16-membered macrolides, microbial metabolism in diverse environments, biosynthesis of secondary metabolites, and caffeine and insect hormone biosynthesis.

193 nm Ultraviolet Photodissociation for the Characterization of Singly Charged Proteoforms Generated by MALDI.

MALDI imaging allows for the near-cellular profiling of proteoforms directly from microbial, plant, and mammalian samples. Despite detecting hundreds of proteoforms, identification of unknowns with only intact mass information remains a distinct challenge, even with high mass resolving power and mass accuracy. To this end, many supplementary methods have been used to create experimental databases for accurate mass matching, including bulk or spatially resolved bottom-up and/or top-down proteomics. Herein, we describe the application of 193 nm ultraviolet photodissociation (UVPD) for fragmentation of quadrupole isolated singly charged ubiquitin (m/z 8565) by MALDI-UVPD on a UHMR HF Orbitrap. This platform permitted the high-resolution accurate mass measurement of not just terminal fragments but also large internal fragments. The outlined workflow demonstrates the feasibility of top-down analyses of isolated MALDI protein ions and the potential toward more comprehensive characterization of proteoforms in MALDI imaging applications.

Association of environmental chemical exposure during pregnancy with subsequent breast cancer risk

Background and Aim: Breast cancer became the most common cancer globally as of 2021, accounting for 12% of all new annual cancer cases worldwide, according to the World Health Organization. Despite epidemiologic studies establishing a number of risk factors for breast cancer, additional research is needed to elucidate environmental exposures that increase breast cancer risk. In this study, we used highly informative, existing pregnancy cohort biospecimens with an untargeted high-resolution mass spectrometry (HRMS) approach to discover possible environmental chemical exposures associated with subsequent breast cancer occurrence. Methods: Archived pregnancy samples, collected between 1959-1967, from the Child Health and Development Studies in California, one of the largest prospective pregnancy cohorts, were analyzed and searched against the Toxic Exposome Database (T3DB). The samples included 2nd (T2) and 3rd (T3) trimester archival samples of 182 women who subsequently developed breast cancer, compared to T2 and T3 samples from 384 women who did not develop breast cancer. Metabolites and environmental chemicals extracted from 50 &amp;#x3bc;L aliquots of thawed pregnancy serum (n=1,148) were analyzed by HRMS with liquid chromatography followed by advanced data extraction, annotation and pathway enrichment analysis. Results: A large number of mass spectral features differed between cases and controls at p&amp;#x3c;0.05. Annotation of the discriminatory metabolites with T3DB showed increased abundance of accurate mass matches (within 5 ppm) to methylmercury and the organophosphate insecticide, tebupirimfos, in both T2 and T3 breast cancer cases compared to controls (P&amp;#x3c;0.05). Additional verification of chemical identities is ongoing. Available literature is mixed for mercury association with breast cancer; however, methylmercury has been found to stimulate proliferation of breast cancer cells in culture. Conclusions: In addition to a significant metabolic disruption, exposure to methylmercury or/and organophosphate insecticide during pregnancy is associated with subsequent breast cancer risk. Keyword: Breast cancer, environmental chemical exposure, metabolic disruption, high-resolution metabolomics, pregnancy.

Novel per- and polyfluoroalkyl substances in an active-use C6-based aqueous film forming foam

Studies have identified hundreds of per- and polyfluoroalkyl substances (PFAS) in aqueous film forming foam (AFFF) using high resolution mass spectrometry (HRMS), and there is increasing reliance on HRMS with suspect screening in areas such as PFAS fate and transport. Characterization of active-use AFFF formulations is crucial for maintaining representative lists of PFAS for such efforts. Herein, targeted analysis, total oxidizable precursor assay (TOP), suspect screening, and non-targeted analysis were used to characterize PFAS in an AFFF currently certified for use by the U.S. military. The sum of PFAS identified during targeted analysis and suspect screening was compared to TOP, demonstrating that > 90% (20.2 mM) of the estimated total PFAS concentration (22.4 mM) was comprised of "unknown" PFAS. Tandem and multi-stage tandem mass spectra were used to annotate 10 PFAS within 9 classes, 8 of which have never been reported. A subset are fluorotelomer-based isomers of legacy, electrochemically synthesized PFAS. Thus, suspect screening efforts that rely solely on accurate mass matching may mis-annotate PFAS presented here as isomers that will have key differences in properties such as biotransformation pathways. The total estimated concentration of the 10 PFAS was ~20 mM, which agrees with the "unknown" fraction (20.2 mM) identified by TOP.

The combination of RPLC-ESI-FTMS/MS and m-CPBA epoxidation for the location and geometry assignment of double bonds in unsaturated fatty acyl chains of drying oils

Abstract Oil painting is the process of painting with drying oils as binders. Such oils mainly consist of triacylglycerols characterized by high levels of unsaturated fatty acyl chains. For instance, poppy seed oils have received much attention for their use as oil paints since very ancient time. Upon exposure to oxygen, not only do drying oils harden to a densely cross-linked polymer network through radical reactions, but their fatty acids also interact with cations of some pigments forming the related carboxylate salts. These so-called metal soaps lead to severe degradation phenomena because they can migrate and aggregate, breaking through the surface of the paint. Since the fatty-acidome of a drying oil is involved in these processes, the current study is chiefly devoted to the identification of both free and total fatty acids in poppy seed oil by reversed-phase liquid chromatography coupled with high-resolution mass spectrometry by an electrospray ionization source (RPLC-ESI-FTMS). Total fatty acids (TFA) were investigated by enzymatic hydrolysis and comparisons were made between the free fatty acid (FFA) profile and the total one resulting from the digestion on the same poppy seed oil. A key component of our approach was the double bond (C=C) epoxidation reaction, which was carried out on unsaturated fatty acids by meta-chloroperoxybenzoic acid (m-CPBA). A chromatographic set up was developed to separate such oxidized lipids, that were identified as deprotonated molecules [epoM-H]− by accurate mass matching in full mass spectra. Their epoxide ring was subsequently cleaved upon tandem mass fragmentation to yield a pair of diagnostic product ions for C=C double bond localization. Interestingly, the double bond geometry (i.e., cis/trans) was also assigned based on the retention times of derivatized-FA. The present approach opens new avenues for the analysis of artworks whether affected by metal soap-related degradation phenomena.

Neuropeptidomic Profiling and Localization in the Crustacean Cardiac Ganglion Using Mass Spectrometry Imaging with Multiple Platforms.

The crustacean cardiac neuromuscular system is a useful model for studying how neural circuits generate behavior, as it is comprised of a simple ganglion containing nine neurons, yet acts as a robust central pattern generator. The crustacean heart is neurogenic, receiving input from neuropeptides. However, the specific effects of neuropeptides on cardiac output is not fully understood, and the large degree of comodulation between multiple neuropeptides makes studying these effects more challenging. To address this challenge, matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) imaging was used to localize neuropeptides within the cardiac ganglion (CG), providing information about the identity and localization of neuropeptides being present. CG extracts were also profiled using liquid chromatography coupled to tandem mass spectrometry (MS/MS) with a data independent acquisition method, resulting in the confirmation of 316 neuropeptides. Two MS imaging (MSI) platforms were compared to provide comprehensive results, including a MALDI-Orbitrap instrument for high mass spectral resolution for accurate identifications and a MALDI TOF/TOF instrument for improved spatial resolution and sensitivity, providing more descriptive MS images. MS images for 235 putative neuropeptides were obtained, with the identification of 145 of these being confirmed by either complementary MS/MS data or accurate mass matching. The MSI studies demonstrate the sensitivity and power of this MALDI-based in situ analytical strategy for unraveling the chemical complexity present in a small nine-cell neuronal system. The results of this study will enable more informative assays of the functions of neuropeptides within this important neural circuit.

Profiling the constituents of Dachuanxiong decoction by liquid chromatography with high-resolution tandem mass spectrometry using target and nontarget data mining.

Comprehensive characterization of the large number of compounds existing in traditional Chinese medicines is still a great challenge. In this study, a strategy of precursor ion selected acquisition coupled with target and nontarget data mining was established to systematically characterize the chemical constituents of traditional Chinese medicines. This strategy consisted of four steps: (1) precursor ion selected acquisition was developed to trigger additional tandem mass spectrometry fragmentation reactions, especially for trace constituents; (2) in-house database of compounds was established and diagnostic characteristics were summarized; (3) compounds were identified by target and nontarget data mining; and (4) compound structures were elucidated based on accurate mass matching and comparison of fragment ions, and isomers were discriminated by the intensity of fragment ions, fragmentation pattern analysis, and calculated log P values. This strategy was successfully applied to comprehensively identify the constituents in Dachuanxiong decoction. Finally, a total of 218 compounds assigned to six categories were characterized, and 107 compounds were characterized by nontarget analysis for the first time. In addition, three new diagnostic characteristics of esters of citric acids were elucidated. This research enriched the material basis of Dachuanxiong decoction and provided a new strategy for identifying the chemical constituents of other traditional Chinese medicines.

MicroLESA: Integrating Autofluorescence Microscopy, In Situ Micro-Digestions, and Liquid Extraction Surface Analysis for High Spatial Resolution Targeted Proteomic Studies.

The ability to target discrete features within tissue using liquid surface extractions enables the identification of proteins while maintaining the spatial integrity of the sample. Here, we present a liquid extraction surface analysis (LESA) workflow, termed microLESA, that allows proteomic profiling from discrete tissue features of ∼110 μm in diameter by integrating nondestructive autofluorescence microscopy and spatially targeted liquid droplet micro-digestion. Autofluorescence microscopy provides the visualization of tissue foci without the need for chemical stains or the use of serial tissue sections. Tryptic peptides are generated from tissue foci by applying small volume droplets (∼250 pL) of enzyme onto the surface prior to LESA. The microLESA workflow reduced the diameter of the sampled area almost 5-fold compared to previous LESA approaches. Experimental parameters, such as tissue thickness, trypsin concentration, and enzyme incubation duration, were tested to maximize proteomics analysis. The microLESA workflow was applied to the study of fluorescently labeled Staphylococcus aureus infected murine kidney to identify unique proteins related to host defense and bacterial pathogenesis. Proteins related to nutritional immunity and host immune response were identified by performing microLESA at the infectious foci and surrounding abscess. These identifications were then used to annotate specific proteins observed in infected kidney tissue by MALDI FT-ICR IMS through accurate mass matching.

Extracellular Matrix Imaging of Breast Tissue Pathologies by MALDI-Imaging Mass Spectrometry.

A new method accessing proteins from extracellular matrix by imaging mass spectrometry (ECM IMS) has been recently reported. ECM IMS is evaluated for use in exploring breast tissue pathologies. A tissue microarray (TMA) is analyzed that has 176 cores of biopsies and lumpectomies spanning breast pathologies of inflammation, hyperplasia, fibroadenoma, invasive ductal carcinoma, and invasive lobular carcinoma and normal adjacent to tumor (NAT). NAT is compared to subtypes by area under the receiver operating curve (ROC) >0.7. A lumpectomy is also characterized for collagen organization by microscopy and stromal protein distribution by IMS. LC-based high-resolution accurate mass (HRAM) proteomics is used to identify proteins from the lumpectomy. TMA analysis shows distinct spectral signatures reflecting a heterogeneous tissue microenvironment. Ninety-four peaks show an ROC >0.7 compared to NAT; NAT has overall higher intensities. Lumpectomy analysis by IMS visualizes a complex central tumor region with distal tumor regions. A total of 39 stromal proteins are identified by HRAM LC-based proteomics. Accurate mass matches between image data and LC-based proteomics demonstrate a heterogeneous collagen type environment in the central tumor. Data portray the heterogeneous stromal microenvironment of breast pathologies, including alteration of multiple collagen-type patterns. ECM IMS is a promising new tool for investigating the stromal microenvironment of breast tissue including cancer.

Application of GC/Q-ToF Combined with Advanced Data Mining and Chemometric Tools in the Characterization and Quality Control of Bay Leaves.

Correct identification of the true bay leaf (Laurus nobilis) and its substitutes is important not only for the quality control of the products, but also for the safety of the consumers. L.nobilis is often substituted or confused with other species, such as Cinnamomum tamala, Pimenta racemosa, Syzygium polyanthum, and Umbellularia californica. In the present study, the potential of gas chromatography combined with quadrupole time-of-flight mass spectrometry for the profiling of various bay leaf products was evaluated for the first time. Thirty-nine authenticated samples representing the true bay leaf and the four commonly substituted species were analyzed. An automatic feature extraction algorithm was applied for data mining and pretreatment in order to identify the most characteristic compounds representing different bay leaf groups. This set of data was employed to construct a sample class prediction model based on stepwise reduction of data dimensionality followed by principal component analysis and partial least squares discriminant analysis. The statistical model, with demonstrated excellent accuracies in recognition and prediction abilities, enabled the correct classification of commercial samples including complex mixtures and essential oils. In addition, in-house developed personal compound database and library with retention time locking offered the advantage of combining retention time matching with accurate mass matching, resulting in high confidence of compound identification for each bay leaf subgroup. At least three marker compounds were identified for each bay leaf species that could be used to discriminate among them.

High-Resolution Metabolomics Assessment of Military Personnel: Evaluating Analytical Strategies for Chemical Detection.

The aim of this study was to maximize detection of serum metabolites with high-resolution metabolomics (HRM). Department of Defense Serum Repository (DoDSR) samples were analyzed using ultrahigh resolution mass spectrometry with three complementary chromatographic phases and four ionization modes. Chemical coverage was evaluated by number of ions detected and accurate mass matches to a human metabolomics database. Individual HRM platforms provided accurate mass matches for up to 58% of the KEGG metabolite database. Combining two analytical methods increased matches to 72% and included metabolites in most major human metabolic pathways and chemical classes. Detection and feature quality varied by analytical configuration. Dual chromatography HRM with positive and negative electrospray ionization provides an effective generalized method for metabolic assessment of military personnel.

High-Performance Chemical Isotope Labeling Liquid Chromatography–Mass Spectrometry for Profiling the Metabolomic Reprogramming Elicited by Ammonium Limitation in Yeast

Information about how yeast metabolism is rewired in response to internal and external cues can inform the development of metabolic engineering strategies for food, fuel, and chemical production in this organism. We report a new metabolomics workflow for the characterization of such metabolic rewiring. The workflow combines efficient cell lysis without using chemicals that may interfere with downstream sample analysis and differential chemical isotope labeling liquid chromatography mass spectrometry (CIL LC-MS) for in-depth yeast metabolome profiling. Using (12)C- and (13)C-dansylation (Dns) labeling to analyze the amine/phenol submetabolome, we detected and quantified a total of 5719 peak pairs or metabolites. Among them, 120 metabolites were positively identified using a library of 275 Dns-metabolite standards, and 2980 metabolites were putatively identified based on accurate mass matches to metabolome databases. We also applied (12)C- and (13)C-dimethylaminophenacyl (DmPA) labeling to profile the carboxylic acid submetabolome and detected over 2286 peak pairs, from which 33 metabolites were positively identified using a library of 188 DmPA-metabolite standards, and 1595 metabolites were putatively identified. Using this workflow for metabolomic profiling of cells challenged by ammonium limitation revealed unexpected links between ammonium assimilation and pantothenate accumulation that might be amenable to engineering for better acetyl-CoA production in yeast. We anticipate that efforts to improve other schemes of metabolic engineering will benefit from application of this workflow to multiple cell types.

Morphologically compatible mass spectrometric analysis of lipids in cytological specimens

Modern lipid analysis requires mass spectrometric techniques, though to date these have been developed and applied primarily to histological serial sections. As such, there has been little emphasis on using mass spectrometry in such a way that the same specimen can yield both chemical and morphological information. Here, we present a mass spectrometric method that enables measurement of lipids from cells on cytospin slides in a way that preserves the cells for subsequent cytomorphologic evaluation. Standardized cultures of MDA-MB-231, a breast cancer cell line, were prepared as cytospins and subjected to analysis using a Prosolia Flowprobe sampling and ionization source attached to a Thermo Scientific Quadrupole-Orbitrap mass spectrometer. Chemical compositions were deduced with accurate mass measurements and fragmentation of high intensity peaks to further determine chemical structure. After mass spectrometry, the slides were stained and cover-slipped, and the cells were reviewed for cytomorphologic features of breast cancer. These were compared to control slides of the same cellular concentration that had not been subjected to this analysis. Spectra from samples of all cellular concentrations demonstrated characteristic qualitative features that were discovered to represent phosphatidylcholines, phosphatidylglycerols, and phosphatidylserines with fragmentation and accurate mass matching. Cytomorphologic analysis demonstrated excellent preservation of the cells subjected to the Flowprobe analysis. Direct extraction, ionization, and identification of lipids is possible from cytologic preparations in such a way that the analyzed material is preserved and useful for subsequent microscopic analysis.

Analysis of N-Glycoproteins Using Genomic N-Glycosite Prediction

Protein glycosylation has long been recognized as one of the most common post-translational modifications. Most membrane proteins and extracellular proteins are N-linked glycosylated, and they account for the majority of current clinical diagnostic markers or therapeutic targets. Quantitative proteomic analysis of detectable N-linked glycoproteins from cells or tissues using mass spectrometry has the potential to provide biological basis for disease development and identify disease associated glycoproteins. However, the information of low abundance but important peptides is lost due to the lack of MS/MS fragmentation or low quality of MS/MS spectra for low abundance peptides. Here, we show the feasibility of formerly N-glycopeptide identification and quantification at MS1 level using genomic N-glycosite prediction (GenoGlyco) coupled with stable isotopic labeling and accurate mass matching. The GenoGlyco Analyzer software uses accurate precursor masses of detected N-deglycopeptide peaks to match them to N-linked deglycopeptides that are predicted from genes expressed in the cells. This method results in more robust glycopeptide identification compared to MS/MS-based identification. Our results showed that over three times the quantity of N-deglycopeptide assignments from the same mass spectrometry data could be produced in ovarian cancer cell lines compared to a MS/MS fragmentation method. Furthermore, the method was also applied to N-deglycopeptide analysis of ovarian tumors using the identified deglycopeptides from the two ovarian cell lines as heavy standards. We show that the described method has a great potential in the analysis of detectable N-glycoproteins from cells and tissues.

Comprehensive chemical analysis of Venenum Bufonis by using liquid chromatography/electrospray ionization tandem mass spectrometry

A rapid, sensitive and versatile liquid chromatography/electrospray ionization tandem mass spectrometry (LC/ESI-MS/MS) method was developed for the comprehensive analyses of the chemical constituents contained in the Chinese medicine-Venenum Bufonis (VB, Chan’ Su in Chinese). LC analysis was carried out on an Agilent Eclipse plus C 18 RRHD column (2.1 × 150 mm, 1.8 μm) with a linear gradient solvent system of water (0.1% formic acid) and acetonitrile (0.1% formic acid) as mobile phase. Detection and quantification were performed by multiple reaction monitoring (MRM) transitions via electrospray ionization (ESI) source operating in the positive ionization mode. Through “Molecular Feature Extraction” (MFE), more than 900 features were detected from VB extracts. Among them, a total of 97 components were identified using the Agilent METLIN accurate mass matching database (DB) established according to those reported in the literatures. Further more, 30 high quality matches were obtained by comparisons of their accurate mass and retention times (AMRT) with those imported out in the developed personal database (METLIN DB with AMRT). The characteristic fragmentation pathways were proposed for the tentative characterization of four representative types of bufadienolides in the present work. The targeted MS/MS experiment of the 30 major compounds was performed for their quantification and semi-quantification. And 7 of them were quantified over the assaying concentration range of 5.0–500 pg/μL. The lowest limit of detection and quantification of them were 0.25–0.50 and 1.25–0.25 pg/μL, respectively. The recoveries varied from 83 to 106% depending on the chemical types and different extraction solvents. The remained 23 bufosteroids were simultaneously semi-quantified using three representative standard compounds as their standard references, respectively.

Ion-pairing reversed-phase liquid chromatography fractionation in combination with isotope labeling reversed-phase liquid chromatography–mass spectrometry for comprehensive metabolome profiling

We report a novel two-dimensional (2D) separation strategy aimed at improving the detectability of liquid chromatography mass spectrometry (LC–MS) for metabolome analysis. It is based on the use of ion-pairing (IP) reversed-phase (RP) LC as the first dimension separation to fractionate the metabolites, followed by isotope labeling of individual fractions using dansylation chemistry to alter the physiochemical properties of the metabolites. The labeled metabolites having different hydrophobicity from their unlabeled counterparts are then separated and analyzed by on-line RPLC Fourier-transform ion-cyclotron resonance mass spectrometry (FTICR-MS). This off-line 2D-LC–MS strategy offers significant improvement over the one-dimensional (1D) RPLC MS technique in terms of the number of detectable metabolites. As an example, in the analysis of a human urine sample, 3564 13C-/ 12C-dansylated ion pairs or metabolites were detected from seven IP RPLC fractions, compared to 1218 metabolites found in 1D-RPLC–MS. Using a library of 220 amine- and phenol-containing metabolite standards, 167 metabolites were positively identified based on retention time and accurate mass matches, which was about 2.5 times the number metabolites identified by 1D-RPLC–MS analysis of the same urine sample.