Adduct Formation in ESI/MS by Mobile Phase Additives

Development of a targeted method for DNA adductome and its application as sensitive biomarkers of ambient air pollution exposure

DNA adducts are widely recognized as biomarkers of exposure to environmental carcinogens and associated health effects in toxicological and epidemiological studies. This study presents a targeted and sensitive method for comprehensive DNA adductome analysis using ultra-high-performance liquid chromatography coupled with triple-quadrupole tandem mass spectrometry (UHPLC-QqQ-MS/MS). The method was developed using calf thymus DNA, with careful optimization of mass spectrometric parameters, chromatographic separation conditions, and pretreatment methods. Ultimately, a targeted method was established for 41 DNA adducts, which showed good linearity (R2 ≥0.992), recovery (80.1-119.4 %), accuracy (81.3-117.8 %), and precision (relative standard deviation <14.2 %). The established method was employed to analyze DNA adducts in peripheral blood cells from pregnant women in Shanxi and Beijing. Up to 23 DNA adducts were successfully detected in samples of varying sizes. From 2 μg of maternal DNA samples, seven specific adducts were identified: 5-methyl-2'-deoxycytidine (5-MedC), 5-hydroxymethyl-2'-deoxycytidine (5-HmdC), N6-methyl-2'-deoxyadenosine (N6-MedA), 8-hydroxy-2'-deoxyguanosine (8-OHdG), 5-hydroxy-2'-deoxycytidine (5-OHdC), 1,N6-etheno-2'-deoxyadenosine (1,N6-εdA), and N2-methyl-2'-deoxyguanosine (N2-MedG). This study reveals that exposure to higher concentrations of ambient air pollutants may elevate the levels of DNA methylation and oxidative damage at different base sites, highlighting the application potential of DNA adducts as sensitive biomarkers of air pollution exposure.

Identification and quantification of acetyl tributyl citrate (ATBC) metabolites using human liver microsomes and human urine

Plasticizers are chemicals that make plastics flexible, and phthalates are commonly used. Due to the toxic effects of phthalates, there is increasing use of non-phthalate plasticizers like acetyl tributyl citrate (ATBC). ATBC has emerged as a safer alternative, yet concerns about its long-term safety persist due to its high leachability and potential endocrine-disrupting effects. This study aims to identify ATBC metabolites using human liver microsomes and suspect screening methods, and to explore potential urinary biomarkers for ATBC exposure. Using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry, we identified ATBC metabolites, including acetyl dibutyl citrate (ADBC), tributyl citrate (TBC), and dibutyl citrate (DBC). Urine samples from 15 participants revealed the presence of ADBC in 5, TBC in 11, and DBC in all samples, with DBC concentrations pointedly higher than the other metabolites. These metabolites show promise as biomarkers for ATBC exposure, though further validation with human data is required. Our results underscore the need for comprehensive studies on ATBC metabolism, exposure pathways, and urinary excretion to accurately assess human exposure levels.

A Novel UHPLC-MS/MS Based Method for Isomeric Separation and Quantitative Determination of Cyanogenic Glycosides in American Elderberry

LC-MS/MS analyses have been reported as challenging for the reliable separation and quantification of cyanogenic glycosides (CNGs), especially (R)-prunasin and sambunigrin isomers found in American elderberry (Sambucus nigra L. subsp. canadensis (L.) Bolli). Hence, a novel multiple reaction monitoring (MRM)-based ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method was developed and validated in the present study for simultaneous separation and quantification of five CNGs, including amygdalin, dhurrin, linamarin, (R)-prunasin, and (S)-prunasin (commonly referred to as sambunigrin). Initially, the role of ammonium formate was investigated as an aqueous mobile-phase additive in developing MRM-based UHPLC-MS/MS. Later, chromatographic conditions for the resolved separation of (R)-prunasin and sambunigrin were identified. Validation studies confirmed that the developed method has good linearity and acceptable precision and accuracy. A noticeable matrix effect (mainly signal enhancement) was observed in leaf samples only. This method was used to detect and quantify CNGs, including (R)-prunasin and sambunigrin, in leaf and fruit samples of American elderberry. Among the studied CNGs, only (R)-prunasin was detected in the leaf samples. Interestingly, (S)-prunasin (sambunigrin) was not detected in the samples analyzed, even though it has been previously reported in elderberry species.

Polypy: A Framework to Interpret Polymer Properties from Mass Spectroscopy Data

Mass spectroscopy (MS) is a robust technique for polymer characterization, and it can provide the chemical fingerprint of a complete sample regarding polymer distribution chains. Nevertheless, polymer chemical properties such as polydispersity (Pd), average molecular mass (Mn), weight average molecular mass (Mw) and others are not determined by MS, as they are commonly characterized by gel permeation chromatography (GPC). In order to calculate polymer properties from MS, a Python script was developed to interpret polymer properties from spectroscopic raw data. Polypy script can be considered a peak detection and area distribution method, and represents the result of combining the MS raw data filtered using Root Mean Square (RMS) calculation with molecular classification based on theoretical molar masses. Polypy filters out areas corresponding to repetitive units. This approach facilitates the identification of the polymer chains and calculates their properties. The script also integrates visualization graphic tools for data analysis. In this work, aryl resin (poly(2,2-bis(4-oxy-(2-(methyloxirane)phenyl)propan) was the study case polymer molecule, and is composed of oligomer chains distributed mainly in the range of dimers to tetramers, in some cases presenting traces of pentamers and hexamers in the distribution profile of the oligomeric chains. Epoxy resin has Mn = 607 Da, Mw = 631 Da, and polydispersity (Pd) of 1.015 (data given by GPC). With Polypy script, calculations resulted in Mn = 584.42 Da, Mw = 649.29 Da, and Pd = 1.11, which are consistent results if compared with GPC characterization. Additional information, such as the percentage of oligomer distribution, was also calculated and for this polymer matrix it was not possible to retrieve it from the GPC method. Polypy is an approach to characterizing major polymer chemical properties using only MS raw spectra, and it can be utilized with any MS raw data for any polymer matrix.

What is the role of current mass spectrometry in pharmaceutical analysis?

The role of mass spectrometry (MS) has become more important in most application domains in recent years. Pharmaceutical analysis is specific due to its stringent regulation procedures, the need for good laboratory/manufacturing practices, and a large number of routine quality control analyses to be carried out. The role of MS is, therefore, very different throughout the whole drug development cycle. While it dominates within the drug discovery and development phase, in routine quality control, the role of MS is minor and indispensable only for selected applications. Moreover, its role is very different in the case of analysis of small molecule pharmaceuticals and biopharmaceuticals. Our review explains the role of current MS in the analysis of both small-molecule chemical drugs and biopharmaceuticals. Important features of MS-based technologies being implemented, method requirements, and related challenges are discussed. The differences in analytical procedures for small molecule pharmaceuticals and biopharmaceuticals are pointed out. While a single method or a small set of methods is usually sufficient for quality control in the case of small molecule pharmaceuticals and MS is often not indispensable, a large panel of methods including extensive use of MS must be used for quality control of biopharmaceuticals. Finally, expected development and future trends are outlined.

A review of analytical parameters in 'rapid' liquid chromatographic methods for bioanalysis: Can we do better?

Rapid bioanalysis is beneficial to many applications. However, how 'rapid' a method is, or could be, is often an unanswered question. In this statistical review, the authors have assessed multiple pre-analytical (i.e. sample preparation), and analytical method parameters specifically for liquid chromatography to assist researchers in developing and validating 'rapid' bioanalytical methods. We restricted the search to urine and plasma matrices only. Data were extracted from over 2,000 recent studies and evaluated to assess how these parameters affected the 'on-instrument' analysis time. In addition to methods using ultra-violet (UV) detection, there were a large number of mass spectrometric (MS) methods, allowing additional review of the differences between high- and low-resolution MS on analysis time. We observed that most (N = 922, 70 %) methods used 5 or 10 cm columns, and that whilst uptake of ultra-high performance (U)HPLC columns was good, the use of sub-5 cm columns and/or flow rates in excess of 1 mL/min was incredibly rare (N = 25, 3 %). The detector of choice for quantitative (U)HPLC-MS remains the triple quadrupole, although a number of groups report the use of high-resolution MS for such methods.

Heterogeneous interactions and transformations of dibasic esters with indoor relevant surfaces

Dibasic esters (DBEs) have recently become emerging indoor air pollutants due to their usage as a solvent for mixtures of paints and coatings. In this study, we explored the adsorption/desorption kinetics, heterogeneous interactions, and chemical transformations of dimethyl succinate (DMS, C6H10O4), a component of commercial dibasic ester solvent mixtures, on indoor relevant surfaces using transmission Fourier-transform infrared (FTIR) spectroscopy and high-resolution mass spectrometry (HRMS). Silica (SiO2) and rutile (TiO2) were used as proxies for window glass, and an active component in paint and self-cleaning surfaces, respectively. FTIR spectroscopy of these surfaces shows that DMS can interact with SiO2 and TiO2 through hydrogen bonding between the carbonyl oxygen and surface hydroxyl groups. The kinetics show fast adsorption of DMS onto these surfaces followed by slow desorption. Furthermore, new products formed observed on TiO2 surfaces in addition to molecularly adsorbed DMS. In particular, succinate (C5H7O) was observed binding to the surface in a bidentate chelating coordination mode as indicated by the appearance of νas(COO-) and νs(COO-) bands in the FTIR spectra. These absorption bands grow in intensity over time and the resulting product remains strongly adsorbed on the surface. The formation of adsorbed succinate is a result of a reaction with DMS on Lewis acid sites of the TiO2 surface. Overall, the slow desorption of these adsorbed species indicates that indoor surfaces can become long term reservoirs for dibasic esters and their surface products. Moreover, in the presence of ∼50% relative humidity, water displaces outer layers of adsorbed DMS on SiO2 and TiO2, while having no impact on the more strongly bound surface species.

Coated Blade Spray Ion Mobility Spectrometry

Coated blade spray (CBS) is a microextraction technology with blades that serve as both the extraction device and the electrospray ionization (ESI) emitter. CBS is designed for easy and rapid extraction of analytes in complex matrices as well as ESI directly from the blade. The technology selectively enriches the components of interest on a coated metal blade. The coating consists of a selective polymer. So far, CBS has only been coupled with mass spectrometry but never with ion mobility spectrometry (IMS), where ions are separated and detected based on their ion mobility in a drift gas under the influence of an electric field, while instrumentation is compact and easy to operate so that the advantages of CBS can be particularly well exploited. Therefore, this work focuses on coupling CBS with our previously described ESI-IMS. The ion mobility spectrometer has a drift length of only 75 mm and provides a high resolving power of RP = 100. In this work, preliminary measurements of CBS-IMS are presented. In particular, the detection of benzodiazepines and ketamine in drinks and the pesticide isoproturon in water samples is shown to demonstrate the feasibility of CBS-IMS.

Improved method robustness and ruggedness in liquid chromatography-mass spectrometry by increasing the acid content of the mobile phase

A routine multiresidue method developed for the detection and quantification of veterinary drug residues in animal-based food was used to analyze sheep (ovine) liver. Unlike when working with previously validated matrices (e.g., bovine liver), some of the analytes of interest chromatographed in the form of split- or even fully baseline separated peaks. In other cases a significantly longer retention times (tR) was observed. A detailed investigation led to the elucidation of taurocholic acid as the causative agent. This compound is present in sheep liver at significantly higher concentrations than in most other animal tissues. Taurocholic acid is a zwitterionic compound and likely acts as an ion pairing agent, which modifies the selectivity of the stationary phase in a highly spatial and dynamic way. Injecting smaller volumes of matrix extract or the use of a significantly higher formic acid concentration in the mobile phase reduced or even completely eliminated the peak splitting. A more detailed examination led to the observation that the problem is not restricted to this particular matrix and extraction procedure or the used stationary phase. In fact, a higher formic acid concentration (e.g., 1.0 % versus 0.1 %) significantly improves the peak shape of many analytes present in fortified matrix samples as well as in pure standard solutions. In addition, analytical column aging was observed as being slower with a higher formic acid concentration. Finally the peak shape of analytes interacting with the metallic parts along the flow path of the liquid chromatograph was also significantly improved. Use of 0.1 % acid in mobile phases is often taken for granted in LC-MS. Regardless of the stationary phase, a higher ionic strength better stabilizes the pH and reduces unwanted interactions, which ultimately improves the method robustness. Flow injection experiments often show that 0.1 % acid concentrations produce the highest analyte signals. Yet, the use of 1 % acid in the mobile phase often leads to narrower and therefore taller chromatographic peaks, which may lead to lower detection limits for many analytes and to an improved separation efficiency.

Synthesis, Structural Elucidation, In Silico and In Vitro Studies of New Class of Methylenedioxyphenyl-Based Amide Derivatives as Potential Myeloperoxidase Inhibitors for Cardiovascular Protection

Novel methylenedioxyphenyl-based amides, especially N-(4-methoxybenzyl)-6-nitrobenzo-[1,3]-dioxole-5-carboxamide (MDC) and N-(3-acetylphenyl)-6-nitrobenzo-[1,3]-dioxole-5-carboxamide (ADC), potential cardiovascular preventive agents, are successfully synthesized, and their chemical structures are verified by 1H and 13C NMR, Fourier transform infrared (FT-IR), high-resolution mass spectrometry (HRMS), and single-crystal X-ray diffraction (SC-XRD) analyses. Data obtained from SC-XRD reveal that MDC and ADC are both monoclinic molecules with Z = 2 and 4, respectively. From density functional theory (DFT) calculations, 3.54 and 3.96 eV are the energy gaps of the optimized MDC and ADC structures, respectively. MDC and ADC exhibit an electrophilicity index value of more than 1.5 eV, suggesting that they can act as an electrophile, facilitating bond formation with biomolecules. Hirshfeld surface analysis demonstrates that more than 25% of atomic interactions in both MDC and ADC are from H···H interactions. Based on pharmacokinetic predictions, MDC and ADC exhibit drug-like properties, and molecular docking simulations revealed favorable interactions with active site pockets. Both MDC and ADC achieved higher docking scores of -7.74 and -7.79 kcal/mol, respectively, with myeloperoxidase (MPO) protein. From docking results, MPO was found to be most favorable followed by dipeptidyl peptidase-4 (DPP-4) and α-glucosidase (α-GD). Antioxidant, anti-inflammatory, and in vitro enzymatic studies of MDC and ADC indicate that MDC is more selective toward MPO and more potent than ADC. The application of MDC to inhibit myeloperoxidase could be ascertained to reduce the cardiovascular risk factor. This can be supported from the results of computational docking (based on hydrogen bonding and docking score), in vitro antioxidant and anti-inflammatory properties, and MPO enzymatic inhibition (based on the percentage of inhibition and IC50 values).

Is it Time to Migrate to Liquid Chromatography Automated Platforms in the Clinical Laboratory? A Brief Point of View

Liquid chromatography coupled to mass spectrometry already started to surpass the major drawbacks in terms of sensitivity, specificity and cross-reactivity that some analytical methods used in the clinical laboratory exhibit. This hyphenated technique is already preferred for specific applications while finding its own place in the clinical laboratory setting. However, large-scale usage, high-throughput analysis and lack of automation emerge as shortcomings that liquid chromatography coupled to mass spectrometry still has to overrun in order to be used on a larger scale in the clinical laboratory. The aim of this review article is to point out the present-day position of the liquid chromatography coupled to mass spectrometry technique while trying to understand how this analytical method relates to the basic working framework of the clinical laboratory. This paper offers insights about the main regulation and traceability criteria that this coupling method has to align and comply to, automation and standardization issues and finally the critical steps in sample preparation workflows all related to the high-throughput analysis framework. Further steps are to be made toward automation, speed and easy-to-use concept; however, the current technological and quality premises are favorable for chromatographic coupled to mass spectral methods.

Improving Quantitative Accuracy in Nontargeted Lipidomics by Evaluating Adduct Formation

For large-scale lipidomic analyses, accurate and reproducible quantification of endogenous lipids is crucial for comparing results within and across studies. Many lipids present in liquid chromatography-electrospray ionization-mass spectrometry form various adducts with buffer components. The mechanisms and conditions that dictate adduct formation are still poorly understood. In a positive mode, neutral lipids like mono-, di-, and triacylglycerides and cholesteryl esters typically generate [M + NH4]+ adduct ions, although [M + Na]+, [M + K]+, and other (more complex) species can also be significantly abundant in MS1 precursor ion spectra. Variations in the ratios of these adducts (within and between matrices) can lead to dramatic inaccuracies during quantification. Here, we examine 48 unique diacylglycerol (DAG) species across 2366 mouse samples for eight matrix-specific data sets of plasma, liver, kidney, brain, heart muscle, gastrocnemius muscle, gonadal, and inguinal fat. Typically, no single adduct ion species accounted for more than 60% of the total observed abundance across each data set. Even within a single matrix, DAGs showed a high variability of adduct ratios. The ratio of [M + NH4]+ adduct ions was increased for longer-chain DAGs and for polyunsaturated DAGs, at the expense of reduced ratios of [M + Na]+ adducts. When using three deuterated internal DAG standards, we found that absolute concentrations were estimated with up to 70% error when only one adduct ion was used instead of all adducts combined. Importantly, when combining [M + NH4]+ and [M + Na]+ adduct ions, quantification results were within 5% accuracy compared to all adduct ions combined. Additional variance can be caused by other factors, such as instrument conditions or matrix effects.

A Critical Overview of HPLC-MS-Based Lipidomics in Determining Triacylglycerol and Phospholipid in Foods

With the current advancement in mass spectrometry (MS)-based lipidomics, the knowledge of lipidomes and their diverse roles has greatly increased, enabling a deeper understanding of the action of bioactive lipid molecules in plant- and animal-based foods. This review provides in-depth information on the practical use of MS techniques in lipidomics, including lipid extraction, adduct formation, MS analysis, data processing, statistical analysis, and bioinformatics. Moreover, this contribution demonstrates the effectiveness of MS-based lipidomics for identifying and quantifying diverse lipid species, especially triacylglycerols and phospholipids, in foods. Further, it summarizes the wide applications of MS-based lipidomics in food science, such as for assessing food processing methods, detecting food adulteration, and measuring lipid oxidation in foods. Thus, MS-based lipidomics may be a useful method for identifying the action of individual lipid species in foods.

Exploring the Impact of Organic Solvent Quality and Unusual Adduct Formation during LC-MS-Based Lipidomic Profiling

Liquid chromatography-mass spectrometry (LC-MS) is the key technique for analyzing complex lipids in biological samples. Various LC-MS modes are used for lipid separation, including different stationary phases, mobile-phase solvents, and modifiers. Quality control in lipidomics analysis is crucial to ensuring the generated data's reliability, reproducibility, and accuracy. While several quality control measures are commonly discussed, the impact of organic solvent quality during LC-MS analysis is often overlooked. Additionally, the annotation of complex lipids remains prone to biases, leading to potential misidentifications and incomplete characterization of lipid species. In this study, we investigate how LC-MS-grade isopropanol from different vendors may influence the quality of the mobile phase used in LC-MS-based untargeted lipidomic profiling of biological samples. Furthermore, we report the occurrence of an unusual, yet highly abundant, ethylamine adduct [M+46.0651]+ that may form for specific lipid subclasses during LC-MS analysis in positive electrospray ionization mode when acetonitrile is part of the mobile phase, potentially leading to lipid misidentification. These findings emphasize the importance of considering solvent quality in LC-MS analysis and highlight challenges in lipid annotation.

Bypassing the Identification: MS2Quant for Concentration Estimations of Chemicals Detected with Nontarget LC-HRMS from MS2 Data

Nontarget analysis by liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is now widely used to detect pollutants in the environment. Shifting away from targeted methods has led to detection of previously unseen chemicals, and assessing the risk posed by these newly detected chemicals is an important challenge. Assessing exposure and toxicity of chemicals detected with nontarget HRMS is highly dependent on the knowledge of the structure of the chemical. However, the majority of features detected in nontarget screening remain unidentified and therefore the risk assessment with conventional tools is hampered. Here, we developed MS2Quant, a machine learning model that enables prediction of concentration from fragmentation (MS2) spectra of detected, but unidentified chemicals. MS2Quant is an xgbTree algorithm-based regression model developed using ionization efficiency data for 1191 unique chemicals that spans 8 orders of magnitude. The ionization efficiency values are predicted from structural fingerprints that can be computed from the SMILES notation of the identified chemicals or from MS2 spectra of unidentified chemicals using SIRIUS+CSI:FingerID software. The root mean square errors of the training and test sets were 0.55 (3.5×) and 0.80 (6.3×) log-units, respectively. In comparison, ionization efficiency prediction approaches that depend on assigning an unequivocal structure typically yield errors from 2× to 6×. The MS2Quant quantification model was validated on a set of 39 environmental pollutants and resulted in a mean prediction error of 7.4×, a geometric mean of 4.5×, and a median of 4.0×. For comparison, a model based on PaDEL descriptors that depends on unequivocal structural assignment was developed using the same dataset. The latter approach yielded a comparable mean prediction error of 9.5×, a geometric mean of 5.6×, and a median of 5.2× on the validation set chemicals when the top structural assignment was used as input. This confirms that MS2Quant enables to extract exposure information for unidentified chemicals which, although detected, have thus far been disregarded due to lack of accurate tools for quantification. The MS2Quant model is available as an R-package in GitHub for improving discovery and monitoring of potentially hazardous environmental pollutants with nontarget screening.

Electrospray ionization mass spectrometry adduct formation by mobile phase additives: A case study using nitrile functional groups containing selective androgen receptor modulators

RATIONALE

The formation of mass adducts is common during electrospray ionization mass spectrometry (ESI-MS). However, the mechanism that leads to adduct formation is poorly understood and difficult to control. Multiplication of mass adducts at once will adversely impact the sensitivity of mass analysis and cause misinterpretation of the level of detection. Prior studies on selective androgen receptor modulators (SARMs) revealed an immense mass adduct formation in both positive and negative ESI modes.

METHODS

In this study, additives in the mobile phases are investigated as a potential means of controlling mass adduct formation in various SARMs.

RESULTS

The first evidence of chloride adduct formation when SARMs are detected via ESI-MS has been reported in this research. A series of mobile phase combinations were tested to achieve the optimal condition for HPLC-MS. A comparison was also made between adduct formation on various grades of water used for preparing the mobile phase. A validation study using equine urine and plasma was also conducted to assess the suitability of the developed method.

CONCLUSION

The results of this study will allow for a more accurate identification of SARMs, which will make it easier to investigate their illicit use in horse racing.

Enhancement of Lipid Signals in Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry with Ammonium Fluoride as a Matrix Additive

Lipids are essential macromolecules that play a crucial role in numerous biological events. Lipids are structurally diverse which allows them to fulfill multiple functional roles. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a powerful tool to understand the spatial localization of lipids within biological systems. Herein, we report the use of ammonium fluoride (NH4F) as a comatrix additive to enhance lipid detection in biological samples, with a signal increase of up to 200%. Emphasis was placed on anionic lipid enhancement with negative polarity measurements, with some preliminary work on cationic lipids detailed. We observed lipid signal enhancement of [M-H]- ions with the addition of NH4F additive attributed to a proton transfer reaction in several different lipid classes. Overall, our study demonstrates that the use of the NH4F comatrix additive substantially improves sensitivity for lipid detection in a MALDI system and is capable of being applied to a variety of different applications.

Boron-based octahedral dication experimentally detected: DFT surface confirms its availability

Borane and heteroborane clusters have been known as neutral or anionic species. In contrast to them, several ten-vertex monocationic nido and closo dicarbaborane-based systems have recently emerged from the reaction of the parent bicapped-square antiprismatic dicarbaboranes with N-heterocyclic carbenes followed by the protonization of the corresponding nido intermediates. The expansion of these efforts has afforded the very first closo-dicationic octahedral phosphahexaborane along with new closo-monocationic pnictogenahexaboranes of the same shapes. All are the products of the one-pot procedure that consists in the reaction of the same carbenes with the parent closo-1,2-Pn₂B₄Br₄ (Pn = As, P). Whereas in the case of phosphorus such a monocation appears to be a mixture of stable intermediates, and arsenahexaboranyl monocation has occurred as the final product, all of them without using any subsequent reaction. The well-established DFT/ZORA/NMR approach has unambiguously confirmed the existence of these species in solution, and computed electrostatic potentials have revealed the delocalization of the positive charge in these monocations and in the very first dication, namely within the octahedral shapes in both cases.

Regarding the Influence of Additives and Additional Plasma-Induced Chemical Ionization on Adduct Formation in ESI/IMS/MS

Ion mobility spectrometers (IMS) separate ions based on their ion mobility, which depends mainly on collision cross-section, mass, and charge of the ions. However, the performance is often hampered in electrospray ionization (ESI) by the appearance of multiple ion mobility peaks in the spectrum for the same analyte due to clustering and additional sodium adducts. In this work, we investigate the influence of solvents and buffer additives on the detected ion mobility peaks using ESI. Additionally, we investigate the effects of an additional chemical ionization (CI) induced by plasma ionization on the ions formed by electrospray. For this purpose, we coupled our high-resolution IMS with a resolving power of R_p = 100 to a time-of-flight mass spectrometer. Depending on the analyte and the chosen additives, the ionization process can be influenced during the electrospray process. For the herbicide isoproturon, the addition of 5 mM sodium acetate results in the formation of the sodium adduct [M + Na]⁺, which is reflected in the ion mobility K₀ of 1.22 cm²/(V·s). In contrast, the addition of 5 mM ammonium acetate yields the protonated species [M + H]⁺ and a correspondingly higher K₀ of 1.29 cm²/(V·s). In some cases, as with the herbicide pyrimethanil, the addition of sodium acetate can completely suppress ionizations. By carefully choosing the solvent additive for ESI-IMS or additional CI, the formation of different ion mobility peaks can be observed. This can facilitate the assignment of ions to ion mobility peaks using IMS as a compact, stand-alone instrument, e.g., for on-site analysis.

Logistic Regression Analysis of LC-MS/MS Data of Monomers Eluted from Aged Dental Composites: A Supervised Machine-Learning Approach

Compound identification by database searching that matches experimental with library mass spectra is commonly used in mass spectrometric (MS) data analysis. Vendor software often outputs scores that represent the quality of each spectral match for the identified compounds. However, software-generated identification results can differ drastically depending on the initial search parameters. Machine learning is applied here to provide a statistical evaluation of software-generated compound identification results from experimental tandem MS data. This task was accomplished using the logistic regression algorithm to assign an identification probability value to each identified compound. Logistic regression is usually used for classification, but here it is used to generate identification probabilities without setting a threshold for classification. Liquid chromatography coupled with quadrupole-time-of-flight tandem MS was used to analyze the organic monomers leached from resin-based dental composites in a simulated oral environment. The collected tandem MS data were processed with vendor software, followed by statistical evaluation of these results using logistic regression. The assigned identification probability to each compound provides more confidence in identification beyond solely by database matching. A total of 21 distinct monomers were identified among all samples, including five intact monomers and chemical degradation products of bisphenol A glycidyl methacrylate (BisGMA), oligomers of bisphenol-A ethoxylate methacrylate (BisEMA), triethylene glycol dimethacrylate (TEGDMA), and urethane dimethacrylate (UDMA). The logistic regression model can be used to evaluate any database-matched liquid chromatography-tandem MS result by training a new model using analytical standards of compounds present in a chosen database and then generating identification probabilities for candidates from unknown data using the new model.

A Robust Purity Method for Biotherapeutics Using New Peak Detection in an LC-MS-Based Multi-Attribute Method

New peak detection (NPD), as part of the LC-MS-based multi-attribute method (MAM), allows for sensitive and unbiased detection of new or changing site-specific attributes between a sample and reference that is not possible with conventional UV or fluorescence detection-based methods. MAM with NPD can serve as a purity test that can establish whether a sample and the reference are similar. The broad implementation of NPD in the biopharmaceutical industry has been limited by the potential presence of false positives or artifacts, which increase the analysis time and can trigger unnecessary investigations of product quality. Our novel contributions to the success of NPD are the curation of false positives, use of the known peak list concept, pairwise analysis approach, and the development of a NPD system suitability control strategy. In this report, we also introduce a unique experimental design utilizing sequence variant co-mixes to measure NPD performance. We show that NPD has superior performance relative to conventional control system methods in the detection of an unexpected change as compared with the reference. NPD is a new frontier in purity testing that reduces subjectivity, need for analyst intervention, and potential for missing unexpected product quality changes.

Development of a rapid, in-situ analysis method using sheath-flow probe electrospray ionisation-mass spectrometry for the direct identification of cocaine metabolites in dried blood spots

RATIONALE

Small amounts of biofluid samples are frequently found at crime scenes; however, existing gold standard methods such as LC-MS frequently require destructive extraction of the sample before a time-consuming analysis which puts strain on forensic analysis providers and can preclude further sample analysis. This study presents the application of sheath-flow probe electrospray ionization-mass spectrometry (sfPESI-MS) to the direct analysis of drug metabolites in dried blood spots (DBS) as a high throughput, minimally destructive alternative.

METHODS

A rapid direct analysis method using a sfPESI ionisation source coupled to an Orbitrap Exactive mass spectrometer was applied to detect cocaine metabolites (benzoylecgonine, BZE, cocaethylene, CE, and ecgonine methyl ester, EME) from DBS. An optimisation study exploring the use of different chemical modifiers (formic acid and sodium acetate) in the sfPESI probe extraction solvent was conducted to enhance the sensitivity and reproducibility of the sfPESI-MS method.

RESULTS

Optimisation of the extraction solvent significantly enhanced the sensitivity and reproducibility of the sfPESI-MS method. A quantitative response over a five-point calibration range 0.5 to 10 μg/ml was obtained for BZE (R²  = 0.9979) and CE (R²  = 0.9948). Limits of detection (LOD) of 1.31, 0.29 and 0.15 μg/ml were achieved for EME, BZE and CE, respectively, from 48 h aged DBSs with % RSD (relative standard deviation) across the calibration range ranging between 19%-28% for [BZE + H]⁺ , 13%-21% for [CE + H]⁺ and 12%-29% for [EME + H]⁺ .

CONCLUSIONS

A rapid (< 20 s) quantitative method for the direct analysis of cocaine metabolites from DBS which requires no prior sample preparation was developed. Although the LOD achieved for BZE (LOD: 0.29 μg/ml) was above the UK threshold limit of exposure for drug driving (0.05 μg/ml), the method may be suitable for use in identifying overdose in forensic analysis.

Comparative in vitro metabolism of short chain chlorinated paraffins (SCCPs) by human and chicken liver microsomes: First insight into heptachlorodecanes

Short chain chlorinated paraffins (SCCPs) are emerging persistent organic pollutants of great concern due to their ubiquitous distribution in the environment. However, little information is available on the biotransformation of SCCPs in organisms. In this study, a chlorinated decane: 1, 2, 5, 5, 6, 9, 10-heptachlorodecanes (HeptaCDs) was subjected to in vitro metabolism by human and chicken liver microsomes at environmentally relevant concentration. Using ultra-performance liquid chromatography-Q-Exactive Orbitrap mass spectrometry, two metabolites: monohydroxylated hexachlorodecane (HO-HexCD) and monohydroxy heptachlorodecane (HO-HeptaCD) were detected in human liver microsomal assays, while only one metabolite (HO-HexCD) was identified in chicken liver microsomal assays. The formation of HO-HexCD was fitted to a Michaelis-Menten model for chicken liver microsomes with a V_max (maximum metabolic rate) value of 4.52 pmol/mg/min. Metabolic kinetic parameters could not be obtained for human liver microsomes as steady state conditions were not reached under our experimental conditions. Notwithstanding this, the observed average biotransformation rate of HeptaCDs was much faster for human liver microsomes than for chicken liver microsomes. Due to the lack of authentic standards for the identified metabolites, the detailed structure of each metabolite could not be confirmed due to the possibility of conformational isomers. This study provides first insights into the biotransformation of SCCPs, providing potential biomarkers and enhancing understanding of bioaccumulation studies.

Mass Spectrometric Methods for Non-Targeted Screening of Metabolites: A Future Perspective for the Identification of Unknown Compounds in Plant Extracts

Phyto products are widely used in natural products, such as medicines, cosmetics or as so-called “superfoods”. However, the exact metabolite composition of these products is still unknown, due to the time-consuming process of metabolite identification. Non-target screening by LC-HRMS/MS could be a technique to overcome these problems with its capacity to identify compounds based on their retention time, accurate mass and fragmentation pattern. In particular, the use of computational tools, such as deconvolution algorithms, retention time prediction, in silico fragmentation and sophisticated search algorithms, for comparison of spectra similarity with mass spectral databases facilitate researchers to conduct a more exhaustive profiling of metabolic contents. This review aims to provide an overview of various techniques and tools for non-target screening of phyto samples using LC-HRMS/MS.

Essentials of LC Troubleshooting, Part V: What Happened to My Sensitivity?

Some liquid chromatography (LC) troubleshooting topics never get old because there are some problems that persist in the practice of LC, even as instrument technology improves over time. There are many ways for things to go wrong in an LC system that ultimately manifests as detection sensitivity that is lower than expected. Developing a short list of the likely causes of these results can help streamline our troubleshooting experience when sensitivity-related problems occur.

The Key Role of Metal Adducts in the Differentiation of Phosphopeptide from Sulfopeptide Sequences by High-Resolution Mass Spectrometry

Site localization of protein sulfation by high-throughput proteomics remains challenging despite the technological improvements. In this study, sequence analysis and site localization of sulfation in tryptic peptides were determined under a conventional nano-liquid chromatography-mass spectrometry configuration. Tryptic sulfopeptide standards were used to study different fragmentation strategies, including collision-induced dissociation (CID), higher-energy collisional dissociation (HCD), electron-transfer dissociation (ETD), electron-transfer/higher-energy collision dissociation (EThcD), and electron-transfer/collision-induced dissociation (ETciD), in the positive ionization mode. Sulfopeptides displayed only neutral loss of SO₃ under CID, while the sequence could be determined for all other tested fragmentation techniques. Results were compared to the same sequences with phosphotyrosine, indicating important differences, as the sequence and modification localization could be studied by all fragmentation strategies. However, the use of metal adducts, especially potassium, provided valuable information for sulfopeptide localization in ETD and ETD-hybrid strategies by stabilizing the modification and increasing the charge state of sulfopeptides. In these conditions, both the sequence and localization could be obtained. In-source neutral loss of SO₃ under EThcD provided diagnostic peaks suitable to distinguish the sulfopeptides from the nearly isobaric phosphopeptides. Further confirmation on the modification type was found in the negative ionization mode, where phosphopeptides always had the typical phosphate product ion corresponding to PO₃^-.

Trends in environmental monitoring of high explosives present in soil/sediment/groundwater using LC-MS/MS

Environmental contamination by explosives occurs due to improper handling and disposal procedures. Explosives and their transformation products pose threat to human health and the ecosystem. Trace level detection of explosives present in different environmental matrices is a challenge, due to the interference caused by matrix components and the presence of cocontaminants. Liquid chromatography combined with tandem mass spectrometry (LC-MS/MS) is an advanced analytical tool, which is ideal for quantitative and qualitative detection of explosives and its metabolites at trace levels. This review aims to showcase the current trends in the application of LC-MS/MS for detecting explosives present in soil, sediment, and groundwater with detection limits ranging from nano to femtogram levels. Specificity and advantages of using LC-MS/MS over conventional analytical methods and various processing methods and techniques used for sample preparation are discussed in this article. Important application aspects of LC-MS/MS on environmental monitoring include site characterization and degradation evaluation. Studies on qualitative and quantitative LC-MS/MS analysis in determining the efficiency of treatment processes and contamination mapping, optimized conditions of LC and MS/MS adopted, role of different ionization techniques and mass analyzers in detection of explosives and its metabolites, relative abundance of various product ions formed on dissociation and the levels of detection achieved are reviewed. Ionization suppression, matrix effect, additive selection are some of the major factors which influence MS/MS detection. A summary of challenges and future research insights for effective utilization of this technique in the environmental monitoring of explosives are presented.

Trap column-based intact mass spectrometry for rapid and accurate evaluation of protein molecular weight

The determination of the molecular weight (MW) of a protein using high-resolution mass spectrometry (MS) is a crucial tool used to confirm whether the protein was correctly expressed and adequately purified. However, a non-volatile buffer is normally used for protein purification and storage. Therefore, a pre-treatment step using ultrafiltration (UF) is required to exchange the buffer with a volatile buffer prior to the introduction of the protein sample into the MS equipment. This pre-treatment step is time-consuming. In this study, a trap column-based pre-treatment method applied in a nano-LC system was developed for rapid and convenient analysis of the MW of proteins. First, the trap column system was compared with the conventional UF treatment system and non-treatment system using bovine serum albumin. Subsequently, the trap column system was applied to analyze the MW of commercially available and lab-synthesized recombinant proteins. The intensity of the base peak and signal-to-noise ratio of the trap column-based pre-treated protein were higher than those of the UF-treated protein. Moreover, the entire automated procedure of the trap column-based system was conducted within 20 min, which confirms its use in versatile and accurate protein identification.

Trap column-based intact mass spectrometry for estimating the molecular weight of proteins.

Sodium adduct formation with graph-based machine learning can aid structural elucidation in non-targeted LC/ESI/HRMS

Non-targeted screening with LC/ESI/HRMS aims to identify the structure of the detected compounds using their retention time, exact mass, and fragmentation pattern. Challenges remain in differentiating between isomeric compounds. One untapped possibility to facilitate identification of isomers relies on different ionic species formed in electrospray. In positive ESI mode, both protonated molecules and adducts can be formed; however, not all isomeric structures form the same ionic species. The complicated mechanism of adduct formation has hindered the use of this molecular characteristic in the structural elucidation in non-targeted screening. Here, we have studied the adduct formation for 94 small molecules with ion mobility spectra and compared collision cross-sections of the respective ions. Based on the results we developed a fast support vector machine classifier with polynomial kernels for accurately predicting the sodium adduct formation in ESI/HRMS. The model is trained on five independent data sets from different laboratories and uses the graph-based connectivity of functional groups and PubChem fingerprints to predict the sodium adduct formation in ESI/HRMS. The validation of the model showed an accuracy of 74.7% (balanced accuracy 70.0%) on a dataset from an independent laboratory, which was not used in the training of the model. Lastly, we applied the classification algorithm to the SusDat database by NORMAN network to evaluate the proportion of isomeric compounds that could be distinguished based on predicted sodium adduct formation. It was observed that sodium adduct formation probability can provide additional selectivity for about one quarter of the exact masses and, therefore, shows practical utility for structural assignment in non-targeted screening.

Sensitive LC-MS/MS quantification of unconjugated maytansinoid DM4 and its metabolite S-methyl-DM4 in human plasma

Aim: To report the development and validation of an LC-MS/MS method for the simultaneous determination of unconjugated payload DM4 and its metabolite S-methyl-DM4 in human plasma. Methodology: A workflow of protein precipitation followed by reduction and solid phase extraction was employed to remove antibody-maytansinoid conjugates from plasma matrix, release DM4 from endogenous conjugates, and generate a clean sample extract for analysis, respectively. Sodium adduct species of both analytes were selected for multiple reaction monitoring to meet the assay sensitivity requirement in liquid chromatography with tandem mass spectrometry. Conclusion: The method was fully validated for a dynamic range of 0.100-50.0 ng/ml for both analytes along with desired stability and acceptable incurred sample reanalysis.

Acetonitrile Adducts of Tranexamic Acid as Sensitive Ions for Quantification at Residue Levels in Human Plasma by UHPLC-MS/MS

The quantitative analysis of pharmaceuticals in biomatrices by liquid chromatography coupled with electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) is often hampered by adduct formation. The use of the molecular ion resulting from solvent adducts for quantification is uncommon, even if formed in high abundance. In this work, we propose the use of a protonated acetonitrile adduct for the quantitative analysis of tranexamic acid (TXA) by LC-MS/MS. The high abundance of the protonated acetonitrile adduct [M + ACN + H]⁺ was found to be independent of source-dependent parameters and mobile phase composition. The results obtained for TXA analysis in clinical samples were comparable for both [M + ACN + H]⁺ and [M + H]⁺, and no statistically significant differences were observed. The relative stability and structure of the [M + ACN + H]⁺ ions were also studied by analyzing probable structures from an energetic point of view and by quantum chemical calculations. These findings, and the studied fragmentation pathways, allowed the definition of an acetimidium structure as the best ion to describe the observed acetonitrile protonated adduct of TXA.

Quantitative electrospray ionization efficiency scale: 10 years after

RATIONALE

The first comprehensive quantitative scale of the efficiency of electrospray ionization (ESI) in the positive mode by monoprotonation, containing 62 compounds, was published in 2010. Several trends were found between the compound structure and ionization efficiency (IE) but, possibly because of the limited diversity of the compounds, some questions remained. This work undertakes to align the new data with the originally published IE scale and carry out statistical analysis of the resulting more extensive and diverse data set to derive more grounded relationships and offer a possibility of predicting logIE values.

METHODS

Recently, several new IE studies with numerous compounds have been conducted. In several of them, more detailed investigations of the influence of compound structure, solvent properties, or instrument settings have been conducted. IE data from these studies and results from this work were combined, and the multilinear regression method was applied to relate IE to various compound parameters.

RESULTS

The most comprehensive IE scale available, containing 334 compounds of highly diverse chemical nature and spanning 6 orders of magnitude of IE, has been compiled. Several useful trends were revealed.

CONCLUSIONS

The ESI ionization efficiency of a compound by protonation is mainly affected by three factors: basicity (expressed by pK_aH in water), molecular size (expressed by molar volume or surface area), and hydrophobicity of the ion (expressed by charge delocalization in the ion or its partition coefficient between a water-acetonitrile mixture and hexane). The presented models can be used for tentative prediction of logIE of new compounds (under the used conditions) from parameters that can be computed using commercially available software. The root mean square error of prediction is in the range of 0.7-0.8 log units.

Practical aspect of dimer adduct formation in small-molecule drug analysis with LC-MS/MS

Aim: Since the MS/MS based detection of small-molecule drugs with poor or even no ion fragmentation is a challenge in bioanalysis, alternative MS/MS detection strategies were in focus of this study and applied in the field of forensic toxicology. Material & methods: Analyte quantification with liquid chromatography-tandem mass spectrometry of problematic drugs was studied by the application of dimer adduct formation and valproic acid (VPA) was used as a model drug. VPA adduct ions could be identified during infusion experiments and the VPA dimer adduct ion was optimized for the detection. Conclusion: Dimer adduct ion formation can be used as an effective way of VPA quantification in human serum. Further, the parallel detection of dimer adduct ions with other adduct ion types can be stated as advantage in LC-MS/MS analysis of problematic drugs.

Overview, consequences, and strategies for overcoming matrix effects in LC-MS analysis: a critical review

The high-performance liquid chromatography-mass spectrometry (LC-MS) technique is widely applied to routine analysis in many matrices. Despite the enormous application of LC/MS, this technique is subjected to drawbacks called matrix effects (MEs) that could lead to ion suppression or ion enhancement. This phenomenon can exert a deleterious impact on the ionization efficacy of an analyte and subsequently on the important method performance parameters. LC-MS susceptibility to MEs is the main challenge of this technique in the analysis of complex matrices such as biological and food samples. Nowadays, the assessment, estimation, and overcoming of the MEs before developing a method is mandatory in any analysis. Two main approaches including the post-column infusion and post-extraction spike are proposed to determine the degree of MEs. Different strategies can be adopted to reduce or eliminate MEs depending on the complexity of the matrix. This could be done by improving extraction and clean-up methods, changing the type of ionization employed, optimization of liquid chromatography conditions, and using corrective calibration methods. This review article will provide an overview of the MEs as the Achilles heel of the LC-MS technique, the causes of ME occurrence, their consequences, and systemic approaches towards overcoming MEs during LC-MS-based multi-analyte procedures.

Cutting-edge approach using dual-channel chromatography to overcome the sensitivity issues associated with polarity switching in pesticide residues analysis

A fast and sensitive method was validated for the analysis of pesticide residues in baby food. After an QuEChERS-based extraction, the samples were analysed with a dual-channel liquid chromatography instrument coupled to a triple quadrupole mass spectrometer. The method consisted of two independent injections per sample. In the first injection the sample was analysed with a mobile phase optimal for the positive polarity ionisation (water, methanol, formic acid, and ammonium formate), whereas in the second injection the mobile phase was optimised for the negative polarity ionisation (water, acetonitrile, acetic acid). The total number of pesticides was 264, out of which 238 were analysed with the methanol gradient and 26 with the acetonitrile gradient. The dual-channel instrument allowed for sample multiplexing. Thus, sample throughput was equivalent to that of a single-channel system. The limit of quantitation, determined according to the DG SANTE guidance document, was 0.003 mg/kg for 97% of the evaluated compounds. The validation study was followed by a real sample survey. In 42 samples, 16 positives were found.

Cocaine profiling method retrospectively developed with nontargeted discovery of markers using liquid chromatography with time-of-flight mass spectrometry data

Illicit drug profiling performed by forensic laboratories assists law enforcement agencies through providing information about chemical and/or physical characteristics of seized specimens. In this article, a model was developed for the comparison of seized cocaine based on retrospective analysis of data generated from ultrahigh performance liquid chromatography with time‐of‐flight mass spectrometry (UHPLC‐TOF‐MS) comprehensive drug screening. A nontargeted approach to discover target compounds was employed, which generated 53 potential markers using data from cocaine positive samples. Twelve marker compounds were selected for the development of the final profiling model. The selection included a mixture of commonly used cocaine profiling targets and other cocaine‐related compounds. Combinations of pretreatments and comparison metrics were assessed using receiver operating characteristic curves to determine the combination with the best discrimination between linked and unlinked populations. Using data from 382 linked and 34,519 unlinked distances, a classification model was developed using a combination of the standardization and normalization transformations with Canberra distance, resulting in a linked cut‐off with a 0.5% false positive rate. The present study demonstrates the applicability of retrospectively developing a cocaine profiling model using data generated from UHPLC‐TOF‐MS nontargeted drug screening without pre‐existing information about cocaine impurities. The developed workflow was not specific to cocaine and thus could potentially be applied to any seized drug in which there are both sufficient data and impurities present.

Quantum Chemistry Calculations for Metabolomics

A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials ("standards"), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for "standards-free" identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.

Development of One-Step Non-Solvent Extraction and Sensitive UHPLC-MS/MS Method for Assessment of N-(n-Butyl) Thiophosphoric Triamide (NBPT) and N-(n-Butyl) Phosphoric Triamide (NBPTo) in Milk

N-(n-butyl) thiophosphoric triamide (NBPT) is a urease inhibitor utilised in urea-based fertilizers. In Ireland, fertilizer treated with NBPT is applied to pasture to mitigate both ammonia and nitrous oxide emissions, but concerns arise as to the potential for residues in milk products. A quick ultrafiltration extraction and ultra-high performance liquid chromatography coupled with mass spectrometry triple quadrupole (UHPLC-MS/MS) quantitation method was developed and validated in this study. The method was applied in the analysis of samples collected from a field study investigating potential transfer of NBPT residues into milk. NBPT and NBPTo residues, were extracted from fortified milk samples and analysed on a UHPLC-MS/MS with recoveries ranging from 74 to 114%. Validation of the UHPLC-MS/MS method at low (0.0020 mg kg⁻¹) and high (0.0250 mg kg⁻¹) concentration levels in line with SANTE/12682/2019 showed overall trueness in the range of 99 to 104% and precision between 1 and 10%, RSD for both compounds. The limit of quantitation (LOQ) was 0.0020 mg kg⁻¹ and other tested parameters (linearity, sensitivity, specificity, matrix effect, robustness, etc.) satisfied acceptance criteria. Stability assessment using spiked samples revealed the compounds were stable in raw and pasteurised milk for 4 weeks at –80 °C storage temperature. Maintaining samples at pH 8.5–9.0 further improved stability. Analysis of 516 milk samples from the field study found that NBPT and NBPTo concentrations were below the LOQ of 0.0020 mg kg⁻¹, thus suggesting very low risk of residues occurring in the milk. The method developed is quick, robust, and sensitive. The method is deemed fit-for-purpose for the simultaneous determination of NBPT and NBPTo in milk.

An Easy Procedure to Quantify Anticoagulant Rodenticides and Pharmaceutical Active Compounds in Soils

A modified QuEChERS (quick, easy, cheap, effective, rugged, and safe) extraction was validated for the extraction of seven coumarin anticoagulant rodenticides (ARs) and 36 pharmaceutical active compounds (PhACs) residues in soil samples using liquid chromatography tandem mass spectrometry (LC-MS/MS). The aim of this work was to develop a method for the monitoring of these compounds in agricultural lands as well as in forensic applications for the determination of ARs poisoning. As far as is known, this is the first time that a QuEChERS-based method is used for the extraction of ARs in soil, as well as on such a quantity of PhACs. A matrix effect study was carried out on samples of soil devoted to agriculture in the midland area of the Canary Islands (clay loam type). It was in house validated (accuracy, precision, and linearity) at seven spiked levels between 0.5 and 50 ng g⁻¹. The limits of quantification (LOQ) ranged between 0.5 and 50.0 ng g⁻¹ and the limits of detection (LOD) ranged from 0.024 to 6.25 ng g⁻¹. The method was then successfully used for both the determination of the target analytes in the soils from the agricultural plots that had been irrigated with regenerated water, and in the soil collected from underneath wild bird carcasses (which had been the subject of forensic investigation).

A map of mass spectrometry-based in silico fragmentation prediction and compound identification in metabolomics

Metabolomics, the comprehensive study of the metabolome, and lipidomics-the large-scale study of pathways and networks of cellular lipids-are major driving forces in enabling personalized medicine. Complicated and error-prone data analysis still remains a bottleneck, however, especially for identifying novel metabolites. Comparing experimental mass spectra to curated databases containing reference spectra has been the gold standard for identification of compounds, but constructing such databases is a costly and time-demanding task. Many software applications try to circumvent this process by utilizing cutting-edge advances in computational methods-including quantum chemistry and machine learning-and simulate mass spectra by performing theoretical, so called in silico fragmentations of compounds. Other solutions concentrate directly on experimental spectra and try to identify structural properties by investigating reoccurring patterns and the relationships between them. The considerable progress made in the field allows recent approaches to provide valuable clues to expedite annotation of experimental mass spectra. This review sheds light on individual strengths and weaknesses of these tools, and attempts to evaluate them-especially in view of lipidomics, when considering complex mixtures found in biological samples as well as mass spectrometer inter-instrument variability.

Enhancing the power of liquid chromatography-Mass spectrometry for chemical fingerprinting of phytotoxins in the environment

Phytotoxins are plant secondary metabolites. They have recently been considered as chemicals of emerging concern (CECs) and there is a growing interest in their environmental fate and potential threat to public health. Dedicated target and non-target screening (NTS) analysis of phytotoxins in environmental samples are sparse, meanwhile phytotoxins are rarely detected in NTS-based analysis due to lack of an efficient methodology. Development of new analytical measurement methods is therefore highly needed. In this study, we for the first time investigated key parameters of reversed phase liquid chromatography-high resolution mass spectrometry (RPLC-HRMS) for five major classes of phytotoxins (alkaloids, steroids, terpenoids, flavonoids and aromatic polyketides) in environmental matrices; the investigation included analytical conditions which have not yet been explored by others, e.g. ionization at alkaline pH above 9. As the outcome we established a new analytical method for target/suspect screening and NTS of phytotoxins in the environment, which significantly improved the detection sensitivity with up to 40 times compared to previous methods, and enabled the discovery of over 30 phytotoxins in a NTS-based environmental study. We also observed that the negative ionization of phenols could be facilitated by the number of hydroxyl groups on the ring rather than their position of substitution. This study is of interest for a better fundamental understanding of the behavior of phytotoxins in LC-MS. Dedicated target/suspect screening and NTS methods will facilitate a better risk characterization of phytotoxins in the environment and stimulate implementation of new public regulation on phytotoxins.

Public LC-Orbitrap Tandem Mass Spectral Library for Metabolite Identification

Liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics studies require high-quality spectral libraries for reliable metabolite identification. We have constructed EMBL-MCF (European Molecular Biology Laboratory-Metabolomics Core Facility), an open LC-MS/MS spectral library that currently contains over 1600 fragmentation spectra from 435 authentic standards of endogenous metabolites and lipids. The unique features of the library include the presence of chromatographic profiles acquired with different LC-MS methods and coverage of different adduct ions. The library covers many biologically important metabolites with some unique metabolites and lipids as compared with other public libraries. The EMBL-MCF spectral library is created and shared using an in-house-developed web application at https://curatr.mcf.embl.de/. The library is freely available online and also integrated with other mass spectral repositories.

Rapid liquid chromatography-mass spectrometry quantitation of glucose-regulating hormones from human islets of Langerhans

Glucose homeostasis is maintained through the secretion of peptide hormones, such as insulin, somatostatin, and glucagon, from islets of Langerhans, clusters of endocrine cells found in the pancreas. This report describes an LC-MS method using multiple reaction monitoring for quantitation of insulin, C-peptide, glucagon, and somatostatin secretion from human islet populations. For rapid analysis, a 5 min separation was achieved using a 2.1 × 30 mm (i.d. x length) C18 column with 2.7 µm diameter core shell particles. A sacrificial protein hydrolysate was used with the sample and found to improve signal magnitude, repeatability, and to reduce carryover between runs. At optimized gradient conditions, the gradient run time was 4.55 min producing an average peak width of 0.3 min, a minimum resolution of 1.2, and a peak capacity of 20. As a proof of concept, the method was used to measure secretions from static incubations of human islets from 2 donors. Insulin and C-peptide were quantified and matched well with literature values of these hormones. We expect that this antibody-free quantitation of multiple hormones secreted from islets will provide insights into the temporal relationships of these peptides in the future.

30 Years of research on ESI/MS response: Trends, contradictions and applications

The variation of ionization efficiency for different compounds has puzzled researchers since the invention of the electrospray mass spectrometry (ESI/MS). Ionization depends on the properties of the compound, eluent, matrix, and instrument. Despite significant research, some aspects have remained unclear. For example, research groups have reached contradicting conclusions regarding the ionization processes. One of the best-known is the significance of the logP value for predicting the ionization efficiency. In this tutorial review, we analyse the methodology used for ionization efficiency measurements as well as the most important trends observed in the data. Additionally, we give suggestions regarding the measurement methodology and modelling strategies to yield meaningful and consistent ionization efficiency data. Finally, we have collected a wide range of ionization efficiency values from the literature and evaluated the consistency of these data. We also make this collection available for everyone for downloading as well as for uploading additional and new ionization efficiency data. We hope this GitHub based ionization efficiency repository will allow a joined community effort to collect and unify the current knowledge about the ionization processes.