Influence of mobile phase, source parameters and source type on electrospray ionization efficiency in negative ion mode

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.

Development of UHPLC-Q-Exactive Orbitrap/MS Technique for Determination of Proanthocyanidins (PAs) Monomer Composition Content in Persimmon

The main units of persimmon proanthocyanidins (PAs) are composed of flavan-3-ols including epigallocatechin gallate (EGCG) and gallocatechin gallate (GCG). Precise quantification of GCG is challenging due to its trace amounts in persimmon. In this study, to establish the optimal UHPLC-Q-Exactive Orbitrap/MS technique for the determination of PAs monomer composition in persimmon fruit flesh of different astringency types, mass spectrometry and chromatographic conditions were optimized. The results showed that when operating in negative ion mode, using a T3 chromatographic column (a type of C18 column with high-strength silica), acetonitrile as the organic phase, a 0.1% mobile phase acid content, and a mobile phase flow rate of 0.2 mL/min, the chromatographic peak shape and resolution of the PAs monomer composition improved. Additionally, there was no tailing phenomenon observed in the chromatographic peaks. At the same time, the intra-day and inter-day precision, stability, and recovery of the procedure were good. The relative standard deviation (RSD) of stability was less than 5%. The intra-day precision was in the range of 1.14% to 2.36%, and the inter-day precision ranged from 1.03% to 2.92%, both of which were less than 5%. The recovery rate ranged from 94.43% to 98.59% with an RSD less than 5%. The results showed that the UHPLC-Q-Exactive Orbitrap/MS technique established in this study can not only be used for the quantification of EGCG and GCG in persimmon fruit flesh but also be suitable for analyzing other PAs monomer compositions, providing robust support for the related research on persimmon PAs.

Exploration of the Lipid Profile of Edible Oleaginous Microgreens by Mass Spectrometry-Based Lipidomics

The spreading awareness of the health benefits associated with the consumption of plant-based foods is fueling the market of innovative vegetable products, including microgreens, recognized as a promising source of bioactive compounds. To evaluate the potential of oleaginous plant microgreens as a source of bioactive fatty acids, gas chromatography-mass spectrometry was exploited to characterize the total fatty acid content of five microgreens, namely, chia, flax, soy, sunflower, and rapeseed (canola). Chia and flax microgreens appeared as interesting sources of α-linolenic acid (ALA), with total concentrations of 2.6 and 2.9 g/100 g of dried weight (DW), respectively. Based on these amounts, approximately 15% of the ALA daily intake recommended by the European Food Safety Authority can be provided by 100 g of the corresponding fresh products. Flow injection analysis with high-resolution Fourier transform single and tandem mass spectrometry enabled a semi-quantitative profiling of triacylglycerols (TGs) and sterol esters (SEs) in the examined microgreen crops, confirming their role as additional sources of fatty acids like ALA and linoleic acid (LA), along with glycerophospholipids. The highest amounts of TGs and SEs were observed in rapeseed and sunflower microgreens (ca. 50 and 4-5 μmol/g of DW, respectively), followed by flax (ca. 20 and 3 μmol/g DW). TG 54:9, 54:8, and 54:7 prevailed in the case of flax and chia, whereas TG 54:3, 54:4, and 54:5 were the most abundant TGs in the case of rapeseed. β-Sitosteryl linoleate and linolenate were generally prevailing in the SE profiles, although campesteryl oleate, linoleate, and linolenate exhibited a comparable amount in the case of rapeseed microgreens.

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.

Elucidating the Role of Ion Suppression in Secondary Electrospray Ionization

Ion suppression is a known matrix effect in electrospray ionization (ESI), ambient pressure chemical ionization (APCI), and desorption electrospray ionization (DESI), but its characterization in secondary electrospray ionization (SESI) is lacking. A thorough understanding of this effect is crucial for quantitative applications of SESI, such as breath analysis. In this study, gas standards were generated by using an evaporation-based system to assess the susceptibility and suppression potential of acetone, deuterated acetone, deuterated acetic acid, and pyridine. Gas-phase effects were found to dominate ion suppression, with pyridine exhibiting the most significant suppressive effect, which is potentially linked to its gas-phase basicity. The impact of increased acetone levels on the volatiles from exhaled breath condensate was also examined. In humid conditions, a noticeable decrease in intensity of approximately 30% was observed for several features at an acetone concentration of 1 ppm. Considering that this concentration is expected for breath analysis, it becomes crucial to account for this effect when SESI is utilized to quantitatively determine specific compounds.

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.

Ion transmission in an electrospray ionization-mass spectrometry interface using an S-lens

We present the design and performance of an in-house built electrospray ionization-mass spectrometry (ESI-MS) interface equipped with an S-lens ion guide. The ion source was designed specifically for our ion beam experiments to investigate the chemical reactivity and deposition of the clusters and nanoparticles. It includes standard ESI-MS interface components, such as nanoelectrospray, ion transfer capillary, and the S-lens. A custom design enables systematic optimization of all relevant factors influencing ion formation and transfer through the interface. By varying the ESI voltage and flow rate, we determined the optimal operating conditions for selected silica emitters. A comparison of the pulled silica emitters with different tip inner diameters reveals that the total ion current is highest for the largest tip, whereas a tip with the smallest diameter exhibited the highest transmission efficiency through the ESI-MS interface. Ion transmission through the transfer capillary is strongly limited by its length, but the loss of ions can be reduced by increasing the capillary voltage and temperature. The S-lens was characterized over a wide range of RF frequencies and amplitudes. Maximum ion current was detected at RF amplitudes greater than 50 V peak-to-peak (p/p) and frequencies above 750 kHz, with a stable ion transmission region of about 20%. A factor of 2.6 increase in total ion current is observed for 650 kHz as RF amplitudes reach 400 V p/p. Higher RF amplitudes also focus the ions into a narrow beam, which mitigates their losses when passing through the ion guide.

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.

μPESI-MS/MS System for Screening and Quantitating Drugs in Plasma Samples

Recently, we developed a novel microprobe electrospray ionization (μPESI) source and its coupled MS (μPESI-MS/MS) system. Here, we aimed to widely validate the μPESI-MS/MS method for quantitative analysis of drugs in plasma samples. Furthermore, the relationship between the quantitative performance of the μPESI-MS/MS method and the physicochemical properties of target drugs was analyzed. The μPESI-MS/MS methods for quantitative analysis of 5 representative drugs with a relatively wide range of molecular weight, pK_a, and log P values were developed and validated. The results showed that the linearity, accuracy, and precision of these methods met the requirements of the European Medicines Agency (EMA) guidance. Then a total of 75 drugs from plasma samples were primarily detected using the μPESI-MS/MS methods, among which 48 drugs could be quantitatively measured. Logistics regression suggested that drugs with significantly greater log P and physiological charge had better quantitative performance using the μPESI-MS/MS method. Collectively, these results clearly demonstrate the practical application of the μPESI-MS/MS system as a rapid approach to the quantitative analysis of drugs in plasma samples.

Equilibration for Electrospray Ionization Mass Spectrometry in Quantitative Analysis

Electrospray ionization mass spectrometry (ESI-MS) is widely used in drug development, therapeutic drug monitoring, and other fields. However, unstable mass spectral signals, especially during the initial stages of instrument operation, plague analysts. Generally, in quantitative experiments, the stability of response can be achieved by running the analytical system for some time. However, the equilibration time required for the responses of different compounds to stabilize has been elusive. To investigate the response stability of the ESI-MS system, 72 compounds with different physicochemical properties were employed on three systems, and flow injection analysis was performed in positive ion mode. With the use of 5.00% (response stable factor, RSF) as the stability limit, about 80% of the compounds were stable within 60 min. Under a 2.00% criterion, the stabilization time was significantly longer. The stabilization time varies with different instruments and physicochemical properties of the compounds. When positive ion detection is performed in an acidic mobile phase, the octanol-water partition coefficient (Log P), molecular weight, and molar volume can all affect the time required to stabilize the response. In general, it is necessary to balance the ESI-MS system for an appropriate time before sample detection, especially for the analysis of compounds with strong hydrophilicity, small molecular weight, or small molar volume under the conditions above.

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.

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).

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.

Liquid chromatography versus supercritical fluid chromatography coupled to mass spectrometry: a comparative study of performance for multiresidue analysis of pesticides

Abundant studies have been published evaluating different parameters of reverse-phase liquid chromatography (LC) and supercritical fluid chromatography (SFC), both coupled to electrospray (ESI)/mass spectrometry (MS) for pesticide residue analysis. However, there is a lack of a comprehensive comparative study that facilitates deep knowledge about the benefits of using each technique. In the present study, the same mass spectrometer was used coupled to both liquid and supercritical fluid chromatographies with a multiresidue method of 215 compounds, for the analysis of pesticide residues in food samples. Through the injection of the spiked extracts, separate experiments were conducted. A study of the optimum ion source temperature using the different chromatography modes was performed. The results were evaluated in terms of sensitivity with tomato, leek, onion, and orange as representative fruit and vegetable matrices. The compounds which reported the highest area values in each chromatography were evaluated through their substance groups and polarity values. The impact of matrix effects obtained in tomato matrix was similar for both cases; however, SFC clearly showed better results in analyzing matrices with a higher number of natural co-extracted compounds. This can be explained by the combination of two effects: (i) chromatography separation and (ii) ion source efficiency. The chromatographic elution presented different profiles of matrix components, which had diverse impact on the coelution with the analytes, being more beneficial when SFC was used in the matrices studied. The data showed that the best results obtained in SFC are also related to a higher ionization efficiency even when the ESI emitter tip was not optimized for SFC flow. In the present study a comprehensive evaluation of the benefits and drawbacks of these chromatography modes for routine pesticide residue analysis related to target compounds/commodities is provided.

Determination of inflammation-related lipids in depressive rats by on-line supercritical fluid extraction-supercritical fluid chromatography-tandem mass spectrometry

An on-line supercritical fluid extraction coupled with supercritical fluid chromatography-quadrupole tandem mass spectrometry method was developed to determine lipids related to inflammation in brain tissues of depressed rats. The analysis of 23 lipids from extraction to separation and detection only took 15 min and required 1 mg of brain tissue powder. The matrix effect of the on-line method for endogenous lipids was systematically investigated, and targeted lipids were quantified by matrix effect corrected calibration curves in this study. The on-line method was comprehensively optimized and evaluated. All calibration curves for lipids showed good linearity (correlation coefficient >0.99). The limits of detection and the limits of quantification were in the range of 0.0261-0.396 pg and 0.0791-1.20 pg. The recoveries and the matrix effect were in the range of 85.3-117.5% and 51.9-176.6%, respectively. The relative standard deviations of precision ranged from 2.7 to 14.2%, with accuracies higher than 87.2%. Compared with liquid-liquid extraction coupled with liquid chromatography-tandem mass spectrometry method, the on-line method obtained higher recovery and sensitivity with significantly reduced analytical time, manual operations, and sample amounts. Finally, this on-line method was applied to analyses of brain tissues of depressed rats. Six pro-inflammatory lipids increased in depressed rats, while six anti-inflammatory lipids decreased. Liquiritin and fluoxetine were presumed to promote a similar synthesis of anti-inflammatory lipids. Based on the results, this on-line method showed great promise in analyzing lipids in complex biological samples.

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.

Rapid determination of pharmaceuticals in wastewater by direct infusion HRMS using target and suspect screening analysis

A wide-scope screening of active pharmaceutical ingredients (APIs) and their transformation products (TPs) in wastewater can yield valuable insights and pinpoint emerging contaminants that have not been previously reported. Such information is relevant to investigate their occurrence and fate in various environmental compartments. In this study, we explored the applicability of direct infusion high resolution mass spectrometry (DI-HRMS) for comprehensive and rapid detection of APIs and their TPs in wastewater samples. The method was developed using a Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) system and incorporated both wide-scope suspect screening and semi-quantitative determination of selected analytes. The identification strategy was based on the following criteria: narrow accurate mass window (±1.25 ppm) for two most abundant full-MS signals, isotopic pattern fit and additional confirmation on the basis of MS² spectra at three fragmentation levels. The tentative identification of suspects and target compounds relied on an in-house database containing more than 500 different APIs and TPs. The measured fragment spectra were matched against experimental MS² patterns obtained from a publicly available spectral library (MassBank of North America) and in-silico generated fragmentation features (from the CFM-ID algorithm). In total, 79 suspects were identified and 24 target compounds were semi-quantified in 72 wastewater samples. The highest detection frequencies in treated wastewater effluents were observed for diclofenac, metoprolol and telmisartan, while hydroxydiclofenac, dextrorphan, and carbamazepine metabolites were the most frequently detected TPs. The obtained API profiles were in accordance with the national consumption statistics and the origin of wastewater samples. The developed method is suitable for rapid screening of APIs in wastewater and can be used as a complementary tool to characterize API emissions from wastewater treatment facilities and to identify problematic compounds that require more rigorous monitoring.

Assessment of Tissue Distribution and Metabolism of MP1, a Novel Pyrrolomycin, in Mice Using a Validated LC-MS/MS Method

MP1 is a novel marinopyrrole analogue with activity in MYCN amplified neuroblastoma cell lines. A rapid, selective, and sensitive liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) method was developed and validated for quantitation of MP1 in mouse plasma. Analyte separation was achieved using a Waters Acquity UPLC^®BEH C18 column (1.7 µm, 100 × 2.1 mm). Mobile phase consisted of 0.1% acetic acid in water (10%) and methanol (90%) at a total flow rate of 0.25 mL/min. The mass spectrometer was operated at unit resolution in the multiple reaction monitoring (MRM) mode, using precursor ion > product ion transitions of 324.10 > 168.30 m/z for MP1 and 411.95 > 224.15 m/z for PL-3. The MS/MS response was linear over the concentration range from 0.2-500 ng/mL for MP1, correlation coefficient (r²) of 0.988. Precision (% RSD) and accuracy (% bias) were within the acceptable limits as per FDA guidelines. MP1 was stable under storage and laboratory handling conditions. The validated method was successfully applied to assess the solubility, in-vitro metabolism, plasma protein binding, and bio-distribution studies of MP1.

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.

Targeted and non-targeted unexpected food contaminants analysis by LC/HRMS: Feasibility study on rice

A widely applicable analytical LC/HRMS method based on ion source optimization, data treatment optimization on rice matrix was developed. The effects of key parameters of ion source, and their interactions on ESI response were studied on HPLC-QTOF. Compared with center points, 40% and 20% increase of response factors in the positive and negative mode can be achieved by ion source optimization, respectively. Data processing strategies inspired from metabolomics and multi-targeted analysis were compared and developed using case and control rice samples. Highly automated workflow using XCMS achieved highest mass accuracy, highest detection rate of 96% for 5 μg/kg in a non-targeted way. A clear distinction between the control and contaminated samples by PCA and PLS-DA was also achieved by this workflow using XCMS, even for the concentration of 5 μg/kg.

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.

A Tailored High-Efficiency Sample Pretreatment Method for Simultaneous Quantification of 10 Classes of Known Endogenous Phytohormones

One of the hottest topics in plant hormone biology is the crosstalk mechanisms, whereby multiple classes of phytohormones interplay with each other through signaling networks. To better understand the roles of hormonal crosstalks in their complex regulatory networks, it is of high significance to investigate the spatial and temporal distributions of multiple -phytohormones simultaneously from one plant tissue sample. In this study, we develop a high-sensitivity and high-throughput method for the simultaneous quantitative analysis of 44 phytohormone compounds, covering currently known 10 major classes of phytohormones (strigolactones, brassinosteroids, gibberellins, auxin, abscisic acid, jasmonic acid, salicylic acid, cytokinins, ethylene, and polypeptide hormones [e.g., phytosulfokine]) from only 100 mg of plant sample. These compounds were grouped and purified separately with a tailored solid-phase extraction procedure based on their physicochemical properties and then analyzed by LC-MS/MS. The recoveries of our method ranged from 49.6% to 99.9% and the matrix effects from 61.8% to 102.5%, indicating that the overall sample pretreatment design resulted in good purification. The limits of quantitation (LOQs) of our method ranged from 0.06 to 1.29 pg/100 mg fresh weight and its precision was less than 13.4%, indicating high sensitivity and good reproducibility of the method. Tests of our method in different plant matrices demonstrated its wide applicability. Collectively, these advantages will make our method helpful in clarifying the crosstalk networks of phytohormones.

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.

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.

ESI outcompetes other ion sources in LC/MS trace analysis

Choosing an appropriate ion source is a crucial step in liquid chromatography mass spectrometry (LC/MS) method development. In this paper, we compare four ion sources for LC/MS analysis of 40 pesticides in tomato and garlic matrices. We compare electrospray ionisation (ESI) source, thermally focused/heated electrospray (HESI), atmospheric pressure photoionisation (APPI) source with and without dopant, and multimode source in ESI mode, atmospheric pressure chemical ionisation (APCI) mode, and combined mode using both ESI and APCI, i.e. altogether seven different ionisation modes. The lowest limits of detection (LoDs) were obtained by ESI and HESI. Widest linear ranges were observed with the conventional ESI source without heated nebuliser gas. In comparison to HESI, ESI source was significantly less affected by matrix effect. APPI ranked second (after ESI) by not being influenced by matrix effect; therefore, it would be a good alternative to ESI if low LoDs are not required. Graphical abstract.

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.

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.

Determination of a PDE4 inhibitor Hemay005 in human plasma and urine by UPLC-MS/MS and its application to a PK study

AIM

Hemay005 is a novel small-molecule inhibitor of phosphodiesterase-4 developed for the treatment of psoriasis. Measurement of Hemay005 in biological samples is critical for evaluation of its pharmacokinetics in clinical studies. Methodology & results: Plasma and urine samples were extracted and then chromatographed on an Acquity UPLC HSS T3 column with a gradient elution. Detection was performed on a Xevo TQ-S tandem mass spectrometer using negative ESI.

CONCLUSION

For the first time, a sensitive and robust ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was established and validated for the quantitative determination of Hemay005 in human plasma and urine, and it was successfully applied to evaluate the pharmacokinetics of Hemay005 in healthy subjects in a first-in-human study.

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.

DMSO Assisted Electrospray Ionization for the Detection of Small Peptide Hormones in Urine by Dilute-and-Shoot-Liquid-Chromatography-High Resolution Mass Spectrometry

The mobile phase additive (DMSO) has been described as a useful tool to enhance electrospray ionization (ESI) of peptides and proteins. So far, this technique has mainly been used in proteomic/peptide research, and its applicability in a routine clinical laboratory setting (i.e., doping control analysis) has not been described yet. This work provides a simple, easy to implement screening method for the detection of doping relevant small peptides (GHRPs, GnRHs, GHS, and vasopressin-analogues) with molecular weight less than 2 kDa applying DMSO in the mobile phase. The gain in sensitivity was sufficient to inject the urine samples after a 2-fold dilution step omitting a time consuming sample preparation. The employed analytical procedure was validated for the qualitative determination of 36 compounds, including 13 metabolites. The detection limits (LODs) ranged between 50 and 1000 pg/mL and were compliant with the 2 ng/mL minimum detection level required by the World Anti-Doping Agency (WADA) for all the target peptides. To demonstrate the feasibility of the work, urine samples obtained from patients who have been treated with desmopressin or leuprolide and urine samples that have been declared as adverse analytical findings were analyzed. 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.