Effect of mobile phase on electrospray ionization efficiency

Signal interference between drugs and metabolites in LC-ESI-MS quantitative analysis and its evaluation strategy

Liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI-MS) is a widely utilized technique for in vivo pharmaceutical analysis. Ionization interference within electrospray ion source, occurring between drugs and metabolites, can lead to signal variations, potentially compromising quantitative accuracy. Currently, method validation often overlooks this type of signal interference, which may result in systematic errors in quantitative results without matrix-matched calibration. In this study, we conducted an investigation using ten different groups of drugs and their corresponding metabolites across three LC-ESI-MS systems to assess the prevalence of signal interference. Such interferences can potentially cause or enhance nonlinearity in the calibration curves of drugs and metabolites, thereby altering the relationship between analyte response and concentration for quantification. Finally, we established an evaluation scheme through a step-by-step dilution assay and employed three resolution methods: chromatographic separation, dilution, and stable labeled isotope internal standards correction. The above strategies were integrated into the method establishment process to improve quantitative accuracy.

Prediction of mass spectrometry ionization efficiency based on COSMO-RS and machine learning algorithms

Non-targeted analysis of high-resolution mass spectrometry (MS) can identify thousands of compounds, which also gives a huge challenge to their quantification. The aim of this study is to investigate the impact of mass spectrometry ionization efficiency on various compounds in food at different solvent ratios and to develop a predictive model for mass spectrometry ionization efficiency to enable non-targeted quantitative prediction of unknown compounds. This study covered 70 compounds in 14 different mobile phase ratio environments in positive ion mode to analyze the rules of the matrix effect. With the organic phase ratio from low to high, most compounds changed by 1.0 log units in log IE. The addition of formic acid enhanced the signal but also promoted the matrix effect, which often occurred in compounds with strong ionization capacity. It was speculated that the matrix effect was mainly in the form of competitive charge and charged droplet' gasification sites during MS detection. Subsequently, we present a log IE prediction method built using the COSMO-RS software and the artificial neural network (ANN) algorithm to address this difficulty and overcome the shortcomings of previous models, which always ignore the matrix effect. This model was developed following the principles of QSAR modeling recommended by the Organization for Economic Cooperation and Development (OECD). Furthermore, we validated this approach by predicting the log IE of 70 compounds, including those not involved in the log IE model development. The results presented demonstrate that the method we put forward has an excellent prediction accuracy for log IE (R2pred = 0.880), which means that it has the potential to predict the log IE of new compounds without authentic standards.

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.

High-Speed Schlieren Imaging of Vapor Formation in Electrospray Plume

Previous mechanistic descriptions of electrosprays mostly focused on the dynamics of Taylor cones, initial droplets, and progeny droplets. However, vapor formation during droplet desolvation in an electrospray plume has not been discussed to a great extent. Here, we implement a double-pass on-axis schlieren high-speed imaging system to observe generation and propagation of vapors in an offline electrospray source under different conditions. Switching between turbulent and laminar vapor flow was observed for all of the scanned conditions, which may be attributed to randomly occurring disturbances in the sample flow inside the electrospray emitter. Calculation of mean vapor flow velocity and analysis of vapor flow patterns were performed using in-house developed image processing programs. Experiments performed at different electrospray voltages (0-6 kV), solvent flow rates (100-600 μL min-1), and methanol concentrations (50-100%), indicate only a weak dependency between electrospray voltage and mean vapor velocity, implying that the vapor is mostly neutral; thus, the vapor is not accelerated by electric field. On the other hand, electrospraying solutions of analytes (with mass 151 Da or 12 kDa) did not remarkably increase the overall vapor flow velocity. The source of vapor's velocity is attributed to the inertia of the electrospray droplets. Although there are some differences between a modern electrospray ionization (ESI) setup and the setup used in our experiment (e.g., using a higher flow rate and larger emitter), we believe the findings of our study can be projected to a modern ESI setup.

Moderate Signal Enhancement in Electrospray Ionization Mass Spectrometry by Focusing Electrospray Plume with a Dielectric Layer around the Mass Spectrometer's Orifice

Electrospray ionization (ESI) is among the commonly used atmospheric pressure ionization techniques in mass spectrometry (MS). One of the drawbacks of ESI is the formation of divergent plumes composed of polydisperse microdroplets, which lead to low transmission efficiency. Here, we propose a new method to potentially improve the transmission efficiency of ESI, which does not require additional electrical components and complex interface modification. A dielectric plate-made of ceramic-was used in place of a regular metallic sampling cone. Due to the charge accumulation on the dielectric surface, the dielectric layer around the MS orifice distorts the electric field, focusing the charged electrospray cloud towards the MS inlet. The concept was first verified using charge measurement on the dielectric material surface and computational simulation; then, online experiments were carried out to demonstrate the potential of this method in MS applications. In the online experiment, signal enhancements were observed for dielectric plates with different geometries, distances of the electrospray needle axis from the MS inlet, and various compounds. For example, in the case of acetaminophen (15 μM), the signal enhancement was up to 1.82 times (plate B) using the default distance of the electrospray needle axis from the MS inlet (d = 1.5 mm) and 12.18 times (plate C) using a longer distance (d = 7 mm).

Ultrahigh performance LC/FT-MS non-targeted screening for biomass burning organic aerosol with MZmine2 and MFAssignR

In recent years, ultrahigh performance liquid chromatography Fourier transform mass spectrometry (LC/FT-MS) based non-targeted screening (NTS) methods have become increasingly popular for comprehensive analysis of complex organic mixtures. However, applying these methods for environmental complex mixture analysis is challenging due to the extreme complexity of natural samples and a lack of standard samples or surrogates for environmental complex mixtures. Furthermore, limited molecular markers in the databases and insufficient data processing software workflows make the application of these methods more challenging for environmental complex mixtures. In this work, we implement a new NTS data processing workflow to process data collected from ultrahigh performance liquid chromatography and Fourier transform Orbitrap Elite Mass Spectrometry (LC/FT-MS) by combining MZmine2 and MFAssignR, two opensource data processing tools and commercial Mesquite liquid smoke as a surrogate for biomass burning organic aerosol. MZmine2.53 data extraction followed MFAssignR molecular formula assignment offered noise free and highly accurate 1733 individual molecular formulas presented in liquid smoke with 4906 molecular species, including isomers. The results of this new approach were consistent with the results of direct infusion FT-MS analysis confirming its reliability. Over 90% of the molecular formulas presented in mesquite liquid smoke were matched with the molecular formulas of ambient biomass burning organic aerosol. This suggests the potential use of commercial liquid smoke is an acceptable surrogate for biomass burning organic aerosol research. The presented method significantly improves the identification of the molecular composition of biomass burning organic aerosol by successfully addressing some of the limitations related to the data analysis and giving a semi quantitative insight into the analysis.

Mobile phase and column chemistry selection for high sensitivity non-targeted LC/ESI/HRMS screening of water

Systematic selection of mobile phase and column chemistry type can be critical for achieving optimal chromatographic separation, high sensitivity, and low detection limits in liquid chromatography electrospray high resolution mass spectrometry (LC/MS). However, the selection process is challenging for non-targeted screening where the compounds of interest are not preselected nor available for method optimization. To provide general guidance, twenty different mobile phase compositions and four columns were compared for the analysis of 78 compounds with a wide range of physicochemical properties (logP range from -1.46 to 5.48), and analyte sensitivity was compared between methods. The pH, additive type, column, and organic modifier had significant effects on the analyte response factors, and acidic mobile phases (e.g. 0.1% formic acid) yielded highest sensitivity. In some cases, the effect was attributable to the difference in organic modifier content at the time of elution, depending on the mobile phase and column chemistry. Based on these findings, 0.1% formic acid, 0.1% ammonia and 5.0 mM ammonium fluoride were further evaluated for their performance in non-targeted LC/ESI/HRMS analysis of wastewater treatment plan influent and effluent, using a data dependent MS² acquisition and two different data processing workflows (MS-DIAL, patRoon 2.1) to compare number of detected features and sensitivity. Both data-processing workflows indicated that 0.1% formic acid yielded the highest number of features in full scan spectrum (MS¹)^, as well as the highest number of features that triggered fragmentation spectra (MS²) when dynamic exclusion was used.

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.

Electrospray Ionization Efficiency Predictions and Analytical Standard Free Quantification for SFC/ESI/HRMS

Supercritical fluid chromatography (SFC) is a promising, sustainable, and complementary alternative to liquid chromatography (LC) and has often been coupled with high resolution mass spectrometry (HRMS) for nontarget screening (NTS). Recent developments in predicting the ionization efficiency for LC/ESI/HRMS have enabled quantification of chemicals detected in NTS even if the analytical standards of the detected and tentatively identified chemicals are unavailable. This poses the question of whether analytical standard free quantification can also be applied in SFC/ES/HRMS. We evaluate both the possibility to transfer an ionization efficiency predictions model, previously trained on LC/ESI/HRMS data, to SFC/ESI/HRMS as well as training a new predictive model on SFC/ESI/HRMS data for 127 chemicals. The response factors of these chemicals ranged over 4 orders of magnitude in spite of a postcolumn makeup flow, expectedly enhancing the ionization of the analytes. The ionization efficiency values were predicted based on a random forest regression model from PaDEL descriptors and predicted values showed statistically significant correlation with the measured response factors (p < 0.05) with Spearman's rho of 0.584 and 0.669 for SFC and LC data, respectively. Moreover, the most significant descriptors showed similarities independent of the chromatography used for collecting the training data. We also investigated the possibility to quantify the detected chemicals based on predicted ionization efficiency values. The model trained on SFC data showed very high prediction accuracy with median prediction error of 2.20×, while the model pretrained on LC/ESI/HRMS data yielded median prediction error of 5.11×. This is expected, as the training and test data for SFC/ESI/HRMS have been collected on the same instrument with the same chromatography. Still, the correlation observed between response factors measured with SFC/ESI/HRMS and predicted with a model trained on LC data hints that more abundant LC/ESI/HRMS data prove useful in understanding and predicting the ionization behavior in SFC/ESI/HRMS.

Method validation and dissipation kinetics of the novel HPPD-inhibiting herbicide cypyrafluone in winter wheat using QuEChERS method coupled with UPLC-MS/MS

Cypyrafluone, a novel hydroxyphenylpyruvate dioxygenase (HPPD)-inhibiting herbicide, can successfully control a wide species of grass and broadleaf weed in wheat fields. However, the dissipation behaviors and terminal residues of cypyrafluone in wheat fields remain unclear. Here, a simple, accurate, and dependable approach for the analysis of cypyrafluone in soil, wheat plant, and grain was constructed utilizing an adapted QuEChERS extraction combined with UPLC-MS/MS. For accurate quantification, matrix-matched calibrations with high linearity (R² >0.99) were employed to eliminate matrix interference. The method possessed high accuracy with recoveries in the range of 85.5%- 100.6% and precision with relative standard deviations < 14.3%, as well as high sensitivity with limits of quantifications of 0.001 mg kg^-1 in the three matrixes. The dissipation kinetics and terminal residues of cypyrafluone were determined at two separate locations with different climates, soil types and cropping systems in 2018. The half-lives of cypyrafluone in soil and wheat plant were 1.47-1.55 d and 1.00-1.03 d, respectively. At harvest, the terminal residue values of cypyrafluone detected in wheat plants were 0-0.0025 mg kg^-1 and 0.0044-0.0057 mg kg^-1 at the recommended dose and 1.5 times of the recommended dose, respectively, and 0.0049 mg kg^-1 of this herbicide was detected in grain at 1.5 times of the recommended dose, which was below the maximum residue limit (MRL). Finally, the risk quotient for cypyrafluone ranged from 0.33% to 0.81% (<1) for different age groups in China, indicating that the impact of residues from the cypyrafluone application on wheat was acceptable. These findings above will offer scientific guidelines for cypyrafluone application in the wheat field ecosystem.

Rapid Acid/Base Switching in Flow Injection Analysis and Isocratic Elution Liquid Chromatography with Mass Spectrometric Detection for Improved Sensitivity

Ion signals in electrospray ionization (ESI) mass spectrometry (MS) are affected by addition of acid or base. Acids or bases are typically added to samples to enhance detection of analytes in positive- or negative-ion mode, respectively. To carry out simultaneous monitoring of analytes with different ionogenic moieties by ESI-MS, a rapid acid/base switching system was developed. The system was further coupled with flow injection analysis (FIA) and liquid chromatography (LC) MS. The two variants enable detection of separated analytes immediately after alternating addition of acid and base. The methods were tested using a set of phospholipids (PLs) as analytes. The rapid acid/base switching enhanced signals of some of the PL analytes in both ion modes of MS. Both FIA-MS and LC-MS with acid/base switching show signal enhancements (∼1.3-23.2 times) of some analyte signals when compared with analysis conducted without acid/base switching. The proposed methods are suitable for simultaneous analysis of cationic and anionic analytes. The FIA-MS and LC-MS methods with acid/base switching were also applied in analysis of lipid extract from real samples (sausage and porcine liver). However, the FIA-MS results were affected by ionization competition and isobaric interference due to the complexity of the sample matrix and diversity of PL species. In contrast, the LC-MS mode provides adequate selectivity to observe signal enhancement for specific analyte ions. Overall, alternating addition of acid and base immediately before the ESI source can improve analytical performance without the need to carry out separate analyses targeting different types of analytes.

Comparison of Sample Preparation Techniques for the (-)ESI-FT-ICR-MS Analysis of Humic and Fulvic Acids

Soil organic matter (SOM) plays a key role in the global carbon and nitrogen cycles. Soil biogeochemistry is regularly studied by extracting the base-soluble fractions of SOM: acid-insoluble humic acid (HA) and acid-soluble fulvic acid (FA). Electrospray ionization-Fourier transform-ion cyclotron resonance-mass spectrometry (ESI-FT-ICR-MS) is commonly utilized for molecularly characterizing these fractions. Different sample preparation techniques exist for the analysis of HA and FA though questions remain regarding data comparability following different preparations. Comparisons of different sample preparation techniques here revealed that the negative-mode ESI-FT-ICR-MS analytical window can be skewed to detect different groups of molecules, with primary differences in oxygenation, aromaticity, and molecular weight. It was also observed that HA and FA from soils versus an aquatic matrix behaved very differently. Thus, we conclude that sample preparation techniques determined to be "most optimal" in our study are in no way universal. We recommend that future studies of HA and FA involve similar comparative studies for determining the most suitable sample preparation technique for their particular type of HA or FA matrices. This will enhance data comparability among different studies and environmental systems and ultimately allow us to better understand the complex composition of environmental matrices.

Standard-Free Quantification of Dicarboxylic Acids: Case Studies with Salt-Rich Effluents and Serum

The present study evaluates the ionization efficiency (IE) of linear and branched C₂-C₁₄ dicarboxylic acids (DCAs) by electrospray ionization (ESI) under different conditions. The influence of the concentration of organic modifier (MeOH); mobile phase additive; and its concentration, pH, and DCA structure on IE values is studied using flow injection analysis. The IE values of DCAs increase with the increase of MeOH concentration but also decrease with an increase of pH. The former is due to the increase in solvent evaporation rates; the latter is caused by an ion-pairing between the diacid and the cation (ammonium), which is confirmed by the study with different amines. The investigation of DCA ionization in the presence of different acidic mobile phase additives showed that a significant improvement in the (-)ESI responses of analytes was achieved in the presence of weak hydrophobic carboxylic acids, such as butyric or propanoic acid. Conversely, the use of strong carboxylic acids, such as trichloroacetic acid, was found to cause signal suppression. The results of the IE studies were used to develop the liquid chromatography-high-resolution mass spectrometry (LC-HRMS) method that provided instrumental limits of detection in the range from 6 to 180 pg. Furthermore, upon applying the nonparametric Gaussian process, a model for the prediction of IE values was developed, which contains the number of carbons in the molecule and MeOH concentration as model parameters. As a case study, dicarboxylic acids are quantified in salt-rich effluent and blood serum samples using the developed LC-HRMS method.

Estimation of the concentrations of hydroxylated polychlorinated biphenyls in human serum using ionization efficiency prediction for electrospray

Hydroxylated PCBs are an important class of metabolites of the widely distributed environmental contaminants polychlorinated biphenyls (PCBs). However, the absence of authentic standards is often a limitation when subject to detection, identification, and quantification. Recently, new strategies to quantify compounds detected with non-targeted LC/ESI/HRMS based on predicted ionization efficiency values have emerged. Here, we evaluate the impact of chemical space coverage and sample matrix on the accuracy of ionization efficiency-based quantification. We show that extending the chemical space of interest is crucial in improving the performance of quantification. Therefore, we extend the ionization efficiency-based quantification approach to hydroxylated PCBs in serum samples with a retraining approach that involves 14 OH-PCBs and validate it with an additional four OH-PCBs. The predicted and measured ionization efficiency values of the OH-PCBs agreed within the mean error of 2.1 × and enabled quantification with the mean error of 4.4 × or better. We observed that the error mostly arose from the ionization efficiency predictions and the impact of matrix effects was of less importance, varying from 37 to 165%. The results show that there is potential for predictive machine learning models for quantification even in very complex matrices such as serum. Further, retraining the already developed models provides a timely and cost-effective solution for extending the chemical space of the application area.

Machine Learning for Absolute Quantification of Unidentified Compounds in Non-Targeted LC/HRMS

LC/ESI/HRMS is increasingly employed for monitoring chemical pollutants in water samples, with non-targeted analysis becoming more common. Unfortunately, due to the lack of analytical standards, non-targeted analysis is mostly qualitative. To remedy this, models have been developed to evaluate the response of compounds from their structure, which can then be used for quantification in non-targeted analysis. Still, these models rely on tentatively known structures while for most detected compounds, a list of structural candidates, or sometimes only exact mass and retention time are identified. In this study, a quantification approach was developed, where LC/ESI/HRMS descriptors are used for quantification of compounds even if the structure is unknown. The approach was developed based on 92 compounds analyzed in parallel in both positive and negative ESI mode with mobile phases at pH 2.7, 8.0, and 10.0. The developed approach was compared with two baseline approaches- one assuming equal response factors for all compounds and one using the response factor of the closest eluting standard. The former gave a mean prediction error of a factor of 29, while the latter gave a mean prediction error of a factor of 1300. In the machine learning-based quantification approach developed here, the corresponding prediction error was a factor of 10. Furthermore, the approach was validated by analyzing two blind samples containing 48 compounds spiked into tap water and ultrapure water. The obtained mean prediction error was lower than a factor of 6.0 for both samples. The errors were found to be comparable to approaches using structural information.

Understanding the electrospray ionization response factors of per- and poly-fluoroalkyl substances (PFAS)

Per- and polyfluoroalkyl substances (PFAS) are used extensively in commercial products. Their unusual solubility properties make them an ideal class of compounds for various applications. However, these same properties have led to significant contamination and bioaccumulation given their persistence in the environment. Development of analytical techniques to detect and quantify these compounds must take into account the potential for these properties to perturb these measurements, specifically the potential to bias the electrospray ionization (ESI) process. Direct injection ESI analysis of 23 different PFAS species revealed that hydrophobicity and PFAS class can predict the ESI overall response factors. In this study, a method for predicting the behavior of individual PFAS compounds, including relative retention order in chromatography, is presented which is simply based on the number of fluorine atoms in the molecule as well as the class of the compound (e.g., perfluroalkylcarboxylic acids) vs. computational estimations (e.g., non-polar surface area and logP).

Quantitative non-targeted analysis: Bridging the gap between contaminant discovery and risk characterization

Chemical risk assessments follow a long-standing paradigm that integrates hazard, dose-response, and exposure information to facilitate quantitative risk characterization. Targeted analytical measurement data directly support risk assessment activities, as well as downstream risk management and compliance monitoring efforts. Yet, targeted methods have struggled to keep pace with the demands for data regarding the vast, and growing, number of known chemicals. Many contemporary monitoring studies therefore utilize non-targeted analysis (NTA) methods to screen for known chemicals with limited risk information. Qualitative NTA data has enabled identification of previously unknown compounds and characterization of data-poor compounds in support of hazard identification and exposure assessment efforts. In spite of this, NTA data have seen limited use in risk-based decision making due to uncertainties surrounding their quantitative interpretation. Significant efforts have been made in recent years to bridge this quantitative gap. Based on these advancements, quantitative NTA data, when coupled with other high-throughput data streams and predictive models, are poised to directly support 21st-century risk-based decisions. This article highlights components of the chemical risk assessment process that are influenced by NTA data, surveys the existing literature for approaches to derive quantitative estimates of chemicals from NTA measurements, and presents a conceptual framework for incorporating NTA data into contemporary risk assessment frameworks.

Impact of pesticide formulation excipients and employed analytical approach on relative matrix effects of pesticide determination in strawberries

Relative matrix effects between an ambient mass spectrometric technique known as coated blade spray (CBS) and liquid chromatographic separation approach when applied to multiresidue pesticide analysis in strawberry samples are explored. Acceptable slope relative standard deviations (RSD <15 %) were observed for the 9 compounds under study for both CBS-MS/MS (2.2-12.6 %) and LC-MS/MS (2.8-12.9 %) approaches. The findings signify both the elimination of relative matrix effects with the sample preparation and matrix match calibration with internal standard correction methods employed along with no matrix effect compromise made when using the direct-to-MS approach. Similarly, slopes of pesticides spiked from commercially available formulations (containing one or two pesticides) were found to not differ significantly from slopes generated with multiresidue pesticide standards (containing 24 additional pesticides besides the target 9 analytes) with either technique, highlighting the resistance of the employed methods to the excipients present in pesticide formulations in large amounts.

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.

Soil Organic Matter Characterization by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR MS): A Critical Review of Sample Preparation, Analysis, and Data Interpretation

The biogeochemical cycling of soil organic matter (SOM) plays a central role in regulating soil health, water quality, carbon storage, and greenhouse gas emissions. Thus, many studies have been conducted to reveal how anthropogenic and climate variables affect carbon sequestration and nutrient cycling. Among the analytical techniques used to better understand the speciation and transformation of SOM, Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) is the only technique that has sufficient mass resolving power to separate and accurately assign elemental compositions to individual SOM molecules. The global increase in the application of FTICR MS to address SOM complexity has highlighted the many challenges and opportunities associated with SOM sample preparation, FTICR MS analysis, and mass spectral interpretation. Here, we provide a critical review of recent strategies for SOM characterization by FTICR MS with emphasis on SOM sample collection, preparation, analysis, and data interpretation. Data processing and visualization methods are presented with suggested workflows that detail the considerations needed for the application of molecular information derived from FTICR MS. Finally, we highlight current research gaps, biases, and future directions needed to improve our understanding of organic matter chemistry and cycling within terrestrial ecosystems.

Guide to Semi-Quantitative Non-Targeted Screening Using LC/ESI/HRMS

Non-targeted screening (NTS) with reversed phase liquid chromatography electrospray ionization high resolution mass spectrometry (LC/ESI/HRMS) is increasingly employed as an alternative to targeted analysis; however, it is not possible to quantify all compounds found in a sample with analytical standards. As an alternative, semi-quantification strategies are, or at least should be, used to estimate the concentrations of the unknown compounds before final decision making. All steps in the analytical chain, from sample preparation to ionization conditions and data processing can influence the signals obtained, and thus the estimated concentrations. Therefore, each step needs to be considered carefully. Generally, less is more when it comes to choosing sample preparation as well as chromatographic and ionization conditions in NTS. By combining the positive and negative ionization mode, the performance of NTS can be improved, since different compounds ionize better in one or the other mode. Furthermore, NTS gives opportunities for retrospective analysis. In this tutorial, strategies for semi-quantification are described, sources potentially decreasing the signals are identified and possibilities to improve NTS are discussed. Additionally, examples of retrospective analysis are presented. Finally, we present a checklist for carrying out semi-quantitative NTS.

Non-aqueous electrophoresis integrated with electrospray ionization mass spectrometry on a thiol-ene polymer-based microchip device

Non-aqueous capillary electrophoresis (NACE) on microfluidic chips is still a comparatively little explored area, despite the inherent advantages of this technique and its application potential for, in particular, lipophilic compounds. A main reason is probably the fact that implementation of NACE on microchips largely precluded the use of polymeric substrate materials. Here, we report non-aqueous electrophoresis on a thiol-ene-based microfluidic chip coupled to mass spectrometry via an on-chip ESI interface. Microchips with an integrated ESI emitter were fabricated using a double-molding approach. The durability of thiol-ene, when exposed to different organic solvents, was investigated with respect to swelling and decomposition of the polymer. Thiol-ene exhibited good stability against organic solvents such as methanol, ethanol, N-methylformamide, and formamide, which allows for a wide range of background electrolyte compositions. The integrated ESI emitter provided a stable spray with RSD% of the ESI signal ≤8%. Separation efficiency of the developed microchip electrophoresis system in different non-aqueous buffer solutions was tested with a mixture of several drugs of abuse. Ethanol- and methanol-based buffers provided comparable high theoretical plate numbers (≈ 6.6 × 10⁴-1.6 × 10⁵ m^-1) with ethanol exhibiting the best separation efficiency. Direct coupling of non-aqueous electrophoresis to mass spectrometry allowed for fast analysis of hydrophobic compounds in the range of 0.1-5 μg mL^-1 and 0.2-10 μg mL^-1 and very good sensitivities (LOD ≈ 0.06-0.28 μg mL^-1; LOQ ≈ 0.20-0.90 μg mL^-1). The novel combination of non-aqueous CE on a microfluidic thiol-ene device and ESI-MS provides a mass-producible and highly versatile system for the analysis of, in particular, lipophilic compounds in a wide range of organic solvents. This offers promising potential for future applications in forensic, clinical, and environmental analysis. Graphical abstract.

Impact of Ambient Vapors Present in an Electrospray Ionization Source on Gas-Phase Ion Structures

According to current consensus, structures of protomeric (or deprotomeric) tautomers of gaseous ions generated by electrospray ionization depend primarily on the nature of the spray solvent. To probe the effect of the spray solvent on protonation, 4-aminobenzoic acid (PABA) has often been selected as the model compound. It is widely accepted that the protonation in the gas phase takes place primarily on the carbonyl oxygen atom when the sample is sprayed in methanol and on the nitrogen atom when acetonitrile is used as the spray solvent. Although this observation is valid, our current results indicate that the determination of the predominant protomer in the gas phase by the spray solvent is an indirect effect moderated by the solvent vapor molecules present in the ambient ion source. To investigate real-time changes in protomer distributions due to solvents, we used ion-mobility mass spectrometry (IM-MS). Initially, when a PABA solution in methanol was electrosprayed, the ion-mobility arrival-time profile recorded showed essentially one peak for the O-protomer. However, when acetonitrile or acetone vapors were introduced to the ambient-pressure ion source via the flowing desolvation gas, the intensity of the O-protomer peak diminished rapidly, and the N-protomer signal became dominant. The moment the acetonitrile (or acetone) vapors were removed from the ion source, the protomer-distribution signals began gradually reverting back to their original intensities. Furthermore, when PABA samples in methanol and acetonitrile were electrosprayed separately via a dual-sprayer setup, which allowed for the selective blocking of the gaseous ion-generation cascade of charged droplets from either sprayer, the predominant signal corresponded only to the N-protomer, irrespective of the position of the mechanical barrier. Because the mechanical barrier prevents only the gaseous ion formation, but not the physical access of solvent vapors to the ion source, it is evident that the solvent vapor that engulfs the ion source is the governing factor that decides the protomer distribution, not the nature of the spray solvent. Noticeably, acetonitrile wields a stronger effect on the manifested protomer distribution than many other solvents, including methanol, water, hexanes, and toluene. Apparently, the so-called "memory" of the solution-phase structures and the phenomenon described as "kinetic trapping" are both due to indirect effects caused by the solvent vapor engulfing the atmospheric-pressure ion source. Moreover, the so-called "memory" effect can either be "saved" or "erased" by exposing the initially formed gaseous ions to different solvent vapors from an alternative source.

Benchmarking of the quantification approaches for the non-targeted screening of micropollutants and their transformation products in groundwater

A wide range of micropollutants can be monitored with non-targeted screening; however, the quantification of the newly discovered compounds is challenging. Transformation products (TPs) are especially problematic because analytical standards are rarely available. Here, we compared three quantification approaches for non-target compounds that do not require the availability of analytical standards. The comparison is based on a unique set of concentration data for 341 compounds, mainly pesticides, pharmaceuticals, and their TPs in 31 groundwater samples from Switzerland. The best accuracy was observed with the predicted ionization efficiency-based quantification, the mean error of concentration prediction for the groundwater samples was a factor of 1.8, and all of the 74 micropollutants detected in the groundwater were quantified with an error less than a factor of 10. The quantification of TPs with the parent compounds had significantly lower accuracy (mean error of a factor of 3.8) and could only be applied to a fraction of the detected compounds, while the mean performance (mean error of a factor of 3.2) of the closest eluting standard approach was similar to the parent compound approach.

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.

Characterization of wines with liquid chromatography electrospray ionization mass spectrometry: Quantification of amino acids via ionization efficiency values

Quantification of analysis results for the suspect and non-targeted screening is essential for obtaining meaningful insight from the measurements. Ionization efficiency predictions is a possible approach to enable quantitation without standard substances. This is, however, especially challenging for the analysis carried out by combining the full scan mode either with fragmentation experiments in data-dependent or data-independent acquisition mode. Here we investigate the correlation of ionization efficiency values measured in full scan mode with the response factors measured in multiple reaction monitoring (MRM) mode for derivatized amino acids. We observe good correlation (R² of 0.80) for 6-Aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) derivatized amino acids. This encourages the use of the measured ionization efficiency values to estimate amino acid concentrations in different beverages. We apply the measured ionization efficiency values for estimating the concentration of amino acids for measurements done both in full scan as well as in MRM mode in wines and beers. We show that the calculated concentrations are in very good correlation with measured values (R² of 0.71 to 1.00). The method possesses average trueness of 70.5% and shows an insignificant matrix effect.

Quantification for non-targeted LC/MS screening without standard substances

Non-targeted and suspect analyses with liquid chromatography/electrospray/high-resolution mass spectrometry (LC/ESI/HRMS) are gaining importance as they enable identification of hundreds or even thousands of compounds in a single sample. Here, we present an approach to address the challenge to quantify compounds identified from LC/HRMS data without authentic standards. The approach uses random forest regression to predict the response of the compounds in ESI/HRMS with a mean error of 2.2 and 2.0 times for ESI positive and negative mode, respectively. We observe that the predicted responses can be transferred between different instruments via a regression approach. Furthermore, we applied the predicted responses to estimate the concentration of the compounds without the standard substances. The approach was validated by quantifying pesticides and mycotoxins in six different cereal samples. For applicability, the accuracy of the concentration prediction needs to be compatible with the effect (e.g. toxicology) predictions. We achieved the average quantification error of 5.4 times, which is well compatible with the accuracy of the toxicology predictions.

Strategies for Drawing Quantitative Conclusions from Nontargeted Liquid Chromatography-High-Resolution Mass Spectrometry Analysis

This Feature aims at giving an overview of different possibilities for quantitatively comparing the results obtained from LC-HRMS-based nontargeted analysis. More specifically, quantification via structurally similar internal standards, different isotope labeling strategies, radiolabeling, and predicted ionization efficiencies are reviewed.

Ionization efficiency ladders as tools for choosing ionization mode and solvent in liquid chromatography/mass spectrometry

RATIONALE

The choice of mobile phase components and optimal ion source, mainly electrospray ionization (ESI) or atmospheric pressure chemical ionization (APCI), is a crucial part in liquid chromatography/mass spectrometry (LC/MS) method development to achieve higher sensitivity and lower detection limits. In this study we demonstrate how to rigorously solve these questions by using ionization efficiency scales.

METHODS

Four ionization efficiency scales are used: recorded with both APCI and ESI sources and using both methanol- and acetonitrile-containing mobile phases. Each scale contains altogether more than 50 compounds. In addition, measurements with a chromatographic column were also performed.

RESULTS

We observed a correlation between calibration graph slopes under LC conditions and logIE values in ESI (but not APCI) thereby validating the use of logIE values for choosing the ion source. Most of the studied compounds preferred ESI as an ion source and methanol as mobile organic phase. APCI remains the ion source of choice for polycyclic aromatic hydrocarbons. For APCI, both acetonitrile and methanol provide similar ionization efficiencies with few exceptions.

CONCLUSIONS

Overall the results of this work give a concise guideline for practitioners in choosing an ion source for LC/MS analysis on the basis of the chemical nature of the analytes.

Improving Lipidomic Coverage Using UPLC-ESI-Q-TOF-MS for Marine Shellfish by Optimizing the Mobile Phase and Resuspension Solvents

Reversed-phase ultrahigh-performance-liquid chromatography-mass spectrometry (UPLC-MS) is the typical method for the lipidomic analysis of most of biological samples, which was rarely used for the comprehensive lipidomic analysis of marine shellfish. Thus, a range of columns, modifiers, and resuspension solvents were evaluated using UPLC-electrospray ionization-quadrupole time-of-flight-MS to facilitate the ionization efficiency in both the positive and negative electrospray ionization (ESI(+)/(-)) modes for abalone lipids. Optimal lipidomic coverage was acquired with 10 mM ammonium formate in both ESI(+)/(-) modes. The selected resuspension solvents also influenced ionization efficiency through the matrix effect, and resuspension in methanol enhanced the signal intensities by reducing ion suppression. Because of the higher glycerophospholipid content in shellfish, bridged ethylene hybrid C₈ columns showed clear advantages over charged surface hybrid C₁₈ columns. A series of glycerophospholipids, lyso-glycerophospholipids, glycerolipids, and fatty acids in different shellfish can be annotated and semiquantified in one injection by the optimized method.

Semi-quantitative non-target analysis of water with liquid chromatography/high-resolution mass spectrometry: How far are we?

Combining high-resolution mass spectrometry (HRMS) with liquid chromatography (LC) has considerably increased the capability of analytical chemistry. Among others, it has stimulated the growth of the non-target analysis, which aims at identifying compounds without their preceding selection. This approach is already widely applied in various fields, such as metabolomics, proteomics, etc. The applicability of LC/HRMS-based non-target analysis in environmental analyses, such as water studies, would be beneficial for understanding the environmental fate of polar pollutants and evaluating the health risks exposed by the new emerging contaminants. During the last five to seven years the use of LC/HRMS-based non-target analysis has grown rapidly. However, routine non-target analysis is still uncommon for most environmental monitoring agencies and environmental scientists. The main reasons are the complicated data processing and the inability to provide quantitative information about identified compounds. The latter shortcoming follows from the lack of standard substances, considered so far as the soul of each quantitative analysis for the newly discovered pollutants. To overcome this, non-target analyses could be combined with semi-quantitation. This Perspective aims at describing the current methods for non-target analysis, the possibilities and challenges of standard substance-free semi-quantitative analysis, and proposes tools to join these two fields together.

Strategies and analytical workflows to extend the dynamic range in quantitative LC–MS/MS analysis

Aim: To evaluate alternative analytical strategies to extend the dynamic range in quantitative LC–MS/MS. Methods & results: Two approaches based on prior or no prior knowledge of expected exposure levels were evaluated. These approaches make use of two analytical strategies, which include the use of more than one injection volume or dilution of sample extract with solvents or solvent mixtures. A total of 16 compounds with varying logP values were classified into polar and nonpolar groups and used in this evaluation. From the two analytical strategies, three workflows were derived. Conclusion: All three workflows were successfully evaluated and resulted in good accuracy (80–120%) for all the compound groups.

Influence of the amino acid composition on the ionization efficiencies of small peptides

Electrospray ionization is widely used to generate gas phase ions from a variety of molecules ranging from small ions to large proteins, while the ionization mechanism is claimed to depend on the size of the molecule. For small molecules, the ionization efficiency, the amount of gas phase ions produced in the electrospray process, depends on the properties of the compound. Here, we show that the amino acid composition also influences the ionization efficiency of the oligopeptide. Additionally, we show that the ionization efficiencies of oligopeptides consisting of more than five amino acid residues are very similar to one another, and assuming equal ionization efficiencies is feasible. Therefore, accurate ionization efficiency predictions are needed mainly for small oligopeptides. For these oligopeptides, the amino acid composition can be used to estimate the ionization efficiency in an easy to use manner.

Optimization of flow splitting and make-up flow conditions in liquid chromatography/electrospray ionization mass spectrometry

RATIONALE

In liquid chromatography/mass spectrometry (LC/MS) the LC flow is often split prior to the mass spectrometer, for instance, when collecting fractions of the separated sample for other purposes or when less sensitive parallel detection is applied. The aim of this study is to optimize the actual split ratio and make-up flow composition.

METHODS

Different types of splitters were evaluated in combination with a make-up flow. A home-made 1/10 T-piece splitter and commercial 1/10, 1/100 and 1/250 splitters were evaluated by continuous and accurate measurements of the actual split ratio throughout the LC gradient. The make-up flow composition was optimized for maximum electrospray ionization (ESI)-MS sensitivity in the positive mode using ESI efficiency measurements.

RESULTS

Altogether 22 different solvent conditions were tested on 20 pharmaceutical compounds with a wide variety of functional groups and physicochemical properties (molecular weight, logP, and pK_a ). Methanol/10 mM formic acid in water (90/10) provided on average the best results.

CONCLUSIONS

Methanol/10 mM formic acid in water (90/10) proved to be the best make-up flow composition in relation to the average sensitivity obtained. Stronger acidic conditions using oxalic acid or higher formic acid concentrations had a clear positive effect on the sensitivity of compounds with low ionization efficiency. The tested split ratios were relatively stable over the main part of the gradient but showed some variation at very low and very high organic conditions. Differences were larger with methanol compared with acetonitrile containing solvent compositions and when applied without a column or with very long connecting tubing.

Response in Ambient Low Temperature Plasma Ionization Compared to Electrospray and Atmospheric Pressure Chemical Ionization for Mass Spectrometry

Modern technical evolution made mass spectrometry (MS) an absolute must for analytical chemistry in terms of application range, detection limits and speed. When it comes to mass spectrometric detection, one of the critical steps is to ionize the analyte and bring it into the gas phase. Several ionization techniques were developed for this purpose among which electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) are two of the most frequently applied atmospheric pressure methods to ionize target compounds from liquid matrices or solutions. Moreover, recent efforts in the emerging field of "ambient" MS enable the applicability of newly developed atmospheric pressure techniques to solid matrices, greatly simplifying the analysis of samples with MS and anticipating, to ease the required or even leave out any sample preparation and enable analysis at ambient conditions, outside the instrument itself. These developments greatly extend the range of applications of modern mass spectrometry (MS). Ambient methods comprise many techniques; a particular prominent group is, however, the plasma-based methods. Although ambient MS is a rather new field of research, the interest in further developing the corresponding techniques and enhancing their performance is very strong due to their simplicity and often low cost of manufacturing. A precondition for improving the performance of such ion sources is a profound understanding how ionization works and which parameters determine signal response. Therefore, we review relevant compound characteristics for ionization with the two traditional methods ESI and APCI and compare those with one of the most frequently employed representatives of the plasma-based methods, i.e., low temperature plasma ionization. We present a detailed analysis in which compound characteristics are most beneficial for the response of aromatic nitrogen-containing compounds with these three methods and provide evidence that desorption characteristics appear to have the main common, general impact on signal response. In conclusion, our report provides a very useful resource to the optimization of instrumental conditions with respect to most important requirements of the three ionization techniques and, at the same time, for future developments in the field of ambient ionization.

Comprehensive analysis of oxylipins in human plasma using reversed-phase liquid chromatography-triple quadrupole mass spectrometry with heatmap-assisted selection of transitions

Oxylipins, a subclass of lipid mediators, are metabolites of various polyunsaturated fatty acids with crucial functions in regulation of systemic inflammation. Elucidation of their roles in pathological conditions requires accurate quantification of their levels in biological samples. We refined an ultra-performance liquid chromatography-multiple reaction monitoring-mass spectrometry (UPLC-MRM-MS)-based workflow for comprehensive and specific quantification of 131 endogenous oxylipins in human plasma, in which we optimized LC mobile phase additives, column, and gradient conditions. We employed heatmap-assisted strategy to identify unique transitions to improve the assay selectivity and optimized solid phase extraction procedures to achieve better analyte recovery. The method was validated according to FDA guidelines. Overall, 94.4% and 95.7% of analytes at tested concentrations were within acceptable accuracy (80-120%) and precision (CV < 15%), respectively. Good linearity for most analytes was obtained with R² > 0.99. The method was also validated using a standard reference material-SRM 1950 frozen human plasma to demonstrate inter-lab compatibility. Graphical abstract ᅟ.

A systematic approach toward comparing electrospray ionization efficiencies of derivatized and non-derivatized amino acids and biogenic amines

Ionization efficiency (IE) in mass spectrometry (MS) has been studied for many different compounds, and different IE scales have been constructed in order to quantitatively characterize IE. In the case of MS, derivatization has been used to increase the sensitivity of the method and to lower the limits of detection. However, the influence of derivatization on IE across different compounds and different derivatization reagents has not been thoroughly researched, so that practitioners do not have information on the IE-enhancing abilities of different derivatization reagents. Moreover, measuring IE via direct infusion of compounds cannot be considered fully adequate. Since derivatized compounds are in complex mixtures, a chromatographic method is needed to separate these compounds to minimize potential matrix effects. In this work, an IE measurement system with a chromatographic column was developed for mainly amino acids and some biogenic amines. IE measurements with liquid chromatography electrospray ionization mass spectrometry (LC/ESI/MS) were carried out, and IE scales were constructed with a calibration curve for compounds with and without derivatization reagent diethyl ethoxymethylenemalonate. Additionally, eluent composition effects on ionization were investigated. Results showed that derivatization increases IE for most of the compounds (by average 0.9 and up to 2-2.5 logIE units) and derivatized compounds have more similar logIE values than without derivatization. Mobile phase composition effects on ionization efficiencies were negligible. It was also noted that the use of chromatographic separation instead of flow injection mode slightly increases IE. In this work, for the first time, IE enhancement of derivatization reagents was quantified under real LC/ESI/MS conditions and obtained logIE values of derivatized compounds were linked with the existing scale.

The Evolution of Electrospray Generated Droplets is Not Affected by Ionization Mode

Ionization efficiency and mechanism in ESI is strongly affected by the properties of mobile phase. The use of mobile-phase properties to accurately describe droplets in ESI source is convenient but may be inadequate as the composition of the droplets is changing in the plume due to electrochemical reactions occurring in the needle tip as well as continuous drying and fission of droplets. Presently, there is paucity of research on the effect of the polarity of the ESI mode on mobile phase composition in the droplets. In this paper, the change in the organic solvent content, pH, and droplet size are studied in the ESI plume in both ESI+ and ESI- ionization mode. We introduce a rigorous way - the absolute pH (pH_abs^H₂^O) - to describe pH change in the plume that takes into account organic solvent content in the mobile phase. pH_abs^H₂^O enables comparing acidities of ESI droplets with different organic solvent contents. The results are surprisingly similar for both ionization modes, indicating that the dynamics of the change of mobile-phase properties is independent from the ESI mode used. This allows us to conclude that the evolution of ESI droplets first of all proceeds via the evaporation of the organic modifier and to a lesser extent via fission of smaller droplets from parent droplets. Secondly, our study shows that qualitative findings related to the ESI process obtained on the ESI+ mode can almost directly be applied also in the ESI- mode. Graphical Abstract ᅟ.

Plant Metabolomics: Maximizing Metabolome Coverage by Optimizing Mobile Phase Additives for Nontargeted Mass Spectrometry in Positive and Negative Electrospray Ionization Mode

Nontargeted screening methods with ultrahigh-performance liquid chromatography-electrospray ionization/quadrupole-time-of-flight mass spectrometry have been extensively applied to plant metabolomics to very diverse scientific issues in plant metabolomics. In this study, different mobile phase additives were tested in order to improve the electrospray ionization process and to detect as many metabolites as possible with high peak intensities in positive and negative ionization mode. Influences of modifiers were examined for nonpolar and polar compounds, as optimal conditions are not always the same. By combining different additives, metabolite coverage could be significantly increased. The best results for polar metabolites in positive ionization mode were achieved by using 0.1% acetic acid and 0.1% formic acid in negative ionization mode. For measurements of nonpolar metabolites in positive ionization mode, the application of 10 mmol/L ammonium formate led to the best findings, while the use of 0.02% acetic acid was more appropriate in negative ionization mode.

Assessing the Interplay between the Physicochemical Parameters of Ion-Pairing Reagents and the Analyte Sequence on the Electrospray Desorption Process for Oligonucleotides

Alkylamines are widely used as ion-pairing agents during LC-MS of oligonucleotides. In addition to a better chromatographic separation, they also assist with the desorption of oligonucleotide ions into the gas phase, cause charge state reduction, and decrease cation adduction. However, the choice of such ion-pairing agents has considerable influence on the MS signal intensity of oligonucleotides as they can also cause significant ion suppression. Interestingly, optimal ion-pairing agents should be selected on a case by case basis as their choice is strongly influenced by the sequence of the oligonucleotide under investigation. Despite imposing major practical difficulties to analytical method development, such a highly variable system that responds very strongly to the nuances of the electrospray composition provides an excellent opportunity for a fundamental study of the electrospray ionization process. Our investigations using this system quantitatively revealed the major factors that influenced the ESI ionization efficiency of oligonucleotides. Parameters such as boiling point, proton affinity, partition coefficient, water solubility, and Henry's law constants for the ion-pairing reagents and the hydrophobic thymine content of the oligonucleotides were found to be the most significant contributors. Identification of these parameters also allowed for the development of a statistical predictive algorithm that can assist with the choice of an optimum IP agent for each particular oligonucleotide sequence. We believe that research in the field of oligonucleotide bioanalysis will significantly benefit from this algorithm (included in Supplementary Material) as it advocates for the use of lesser-known but more suitable ion-pair alternatives to TEA for many oligonucleotide sequences. Graphical Abstract ᅟ.

Targeted Metabolomics of the Phenylpropanoid Pathway in Arabidopsis thaliana using Reversed Phase Liquid Chromatography Coupled with Tandem Mass Spectrometry

INTRODUCTION

The phenylpropanoid pathway is a source of a diverse group of compounds derived from phenylalanine, many of which are involved in lignin biosynthesis and serve as precursors for the production of valuable compounds, such as coumarins, flavonoids, and lignans. Consequently, recent efforts have been invested in mechanistically understanding monolignol biosynthesis, making the quantification of these metabolites vital.

OBJECTIVE

To develop an improved and comprehensive analytical method for (i) extensively profiling, and (ii) accurately quantifiying intermediates of the monolignol biosynthetic network, using Arabidopsis thaliana as a model system.

METHOD

A liquid chromatography-tandem mass spectrometry with electrospray ionization was developed to quantify phenylpropanoid metabolites in Arabidopsis wildtype and cinnamoyl CoA reductase1 (CCR1) deficient lines (ccr1).

RESULTS

Vortexing at high temperatures (65°C) enhanced release of phenylpropanoids, specifically the more hydrophobic compounds. A pH of 5.3 and ammonium acetate buffer concentration of 2.5 mM resulted in an optimal analyte response across standards. Ion suppression was estimated using standard spike recovery studies for accurate quantitation. The optimized method was used to profile Arabidopsis wildtype and ccr1 stems. An increase in hydroxycinnamic acid derivatives and a decrease in the hydroxycinnamyl aldehydes and alcohols in ccr1 lines, supports a shift of flux from lignin synthesis to other secondary metabolites and phenylpropanoid derivatives.

CONCLUSIONS

Compared to existing targeted profiling techniques, our method is capable of quantifying a wider range of intermediates (15 out of 22 in WT Arabidopsis stems) at low in vivo concentrations (~50 pmol/g-FW for certain compounds), while requiring minimal sample preparation. Copyright © 2017 John Wiley & Sons, Ltd.

Adduct Formation in ESI/MS by Mobile Phase Additives

Adduct formation is a common ionization method in electrospray ionization mass spectrometry (ESI/MS). However, this process is poorly understood and complicated to control. We demonstrate possibilities to control adduct formation via mobile phase additives in ESI positive mode for 17 oxygen and nitrogen bases. Mobile phase additives were found to be a very effective measure for manipulating the formation efficiencies of adducts. An appropriate choice of additive may increase sensitivity by up to three orders of magnitude. In general, sodium adduct [M + Na]⁺ and protonated molecule [M + H]⁺ formation efficiencies were found to be in good correlation; however, the former were significantly more influenced by mobile phase properties. Although the highest formation efficiencies for both species were observed in water/acetonitrile mixtures not containing additives, the repeatability of the formation efficiencies was found to be improved by additives. It is concluded that mobile phase additives are powerful, yet not limiting factors, for altering adduct formation. Graphical Abstract ᅟ.

Predicting ESI/MS Signal Change for Anions in Different Solvents

LC/ESI/MS is a technique widely used for qualitative and quantitative analysis in various fields. However, quantification is currently possible only for compounds for which the standard substances are available, as the ionization efficiency of different compounds in ESI source differs by orders of magnitude. In this paper we present an approach for quantitative LC/ESI/MS analysis without standard substances. This approach relies on accurately predicting the ionization efficiencies in ESI source based on a model, which uses physicochemical parameters of analytes. Furthermore, the model has been made transferable between different mobile phases and instrument setups by using a suitable set of calibration compounds. This approach has been validated both in flow injection and chromatographic mode with gradient elution.

Evaluation of relative MS response factors of drug metabolites for semi-quantitative assessment of chemical liabilities in drug discovery

Drug metabolism studies are performed in drug discovery to identify metabolic soft spots, detect potentially toxic or reactive metabolites and provide an early insight into potential species differences. The relative peak area approach is often used to semi-quantitatively estimate the abundance of metabolites. Differences in the liquid chromatography-mass spectrometry responses result in an underestimation or overestimation of the metabolite and misinterpretation of results. The relative MS response factors (RF) of 132 structurally diverse drug candidates and their 233 corresponding metabolites were evaluated using a capillary-liquid chromatography/high-resolution mass spectrometry system. All of the synthesized metabolites discussed here were previously identified as key biotransformation products in discovery investigations or predicted to be formed. The most commonly occurring biotransformation mechanisms such as oxygenation, dealkylation and amide cleavage are represented within this dataset. However, relatively few phase II metabolites were evaluated because of the limited availability of authentic standards. Approximately 85% of these metabolites had a relative RF in the range between 0.2 (fivefold under-prediction) and 2.0 (twofold over-prediction), and the median MS RF was 0.6. Exceptions to this included very small metabolites that were hardly detectable. Additional experiments performed to understand the impact of the MS platform, flow rate and concentration suggested that these parameters do not have a significant impact on the RF of the compounds tested. This indicates that the use of relative peak areas to semi-quantitatively estimate the abundance of metabolites is justified in the drug discovery setting in order to guide medicinal chemistry efforts. Copyright © 2017 John Wiley & Sons, Ltd.