PUBLICATIONS

Evaluation of Nontargeted Mass Spectral Data Acquisition Strategies for Water Analysis and Toxicity-Based Feature Prioritization by MS2Tox

Pilleriin Peets, May Britt Rian, Jonathan W. Martin, Anneli Kruve

ES&T 2024

DOI: 10.1021/acs.est.4c02833

The machine-learning tool MS2Tox can prioritize hazardous nontargeted molecular features in environmental waters, by predicting acute fish lethality of unknown molecules based on their MS2 spectra, prior to structural annotation. It has yet to be investigated how the extent of molecular coverage, MS2 spectra quality, and toxicity prediction confidence depend on sample complexity and MS2 data acquisition strategies. We compared two common nontargeted MS2 acquisition strategies with liquid chromatography high-resolution mass spectrometry for structural annotation accuracy by SIRIUS+CSI:FingerID and MS2Tox toxicity prediction of 191 reference chemicals spiked to LC-MS water, groundwater, surface water, and wastewater. Data-dependent acquisition (DDA) resulted in higher rates (19–62%) of correct structural annotations among reference chemicals in all matrices except wastewaters, compared to data-independent acquisition (DIA, 19–50%). However, DIA resulted in higher MS2 detection rates (59–84% DIA, 37–82% DDA), leading to higher true positive rates for spectral library matching, 40–73% compared to 34–72%. DDA resulted in higher MS2Tox toxicity prediction accuracy than DIA, with root-mean-square errors of 0.62 and 0.71 log-mM, respectively. Given the importance of MS2 spectral quality, we introduce a “CombinedConfidence” score to convey relative confidence in MS2Tox predictions and apply this approach to prioritize potentially ecotoxic nontargeted features in environmental waters.

Prioritization, Identification, and Quantification of Emerging Contaminants in Recycled Textiles Using Non-Targeted and Suspect Screening Workflows by LC-ESI-HRMS

Drew Szabo, Stellan Fischer, Aji P Mathew, Anneli Kruve

Anal. Chem. 2024

DOI: 10.1021/acs.analchem.4c02041

Recycled textiles are becoming widely available to consumers as manufacturers adopt circular economy principles to reduce the negative impact of garment production. Still, the quality of the source material directly impacts the final product, where the presence of harmful chemicals is of utmost concern. Here, we develop a risk-based suspect and non-targeted screening workflow for the detection, identification, and prioritization of the chemicals present in consumer-based recycled textile products after manufacture and transport. We apply the workflow to characterize 13 recycled textile products from major retail outlets in Sweden. Samples were extracted and analyzed by liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS). In positive and negative ionization mode, 20,119 LC-HRMS features were detected and screened against persistent, mobile, and toxic (PMT) as well as other textile-related chemicals. Six substances were matched with PMT substances that are regulated in the European Union (EU) with a Level 2/3 confidence. Forty-three substances were confidently matched with textile-related chemicals reported for use in Sweden. For estimating the relative priority score, aquatic toxicity and concentrations were predicted for 7416 features with tandem mass spectra (MS2) and used to rank the non-targeted features. The top 10 substances were evaluated due to elevated environmental risk linked to the recycling process and potential release at end-of-life.

Critical review on in silico methods for structural annotation of chemicals detected with LC/HRMS non-targeted screening

Henrik Hupatz, Ida Rahu, Wei-Chieh Wang, Pilleriin Peets, Emma H Palm, Anneli Kruve

Anal. Banal. Chem. 2024

DOI: 10.1007/s00216-024-05471-x

Non-targeted screening with liquid chromatography coupled to high-resolution mass spectrometry (LC/HRMS) is increasingly leveraging in silico methods, including machine learning, to obtain candidate structures for structural annotation of LC/HRMS features and their further prioritization. Candidate structures are commonly retrieved based on the tandem mass spectral information either from spectral or structural databases; however, the vast majority of the detected LC/HRMS features remain unannotated, constituting what we refer to as a part of the unknown chemical space. Recently, the exploration of this chemical space has become accessible through generative models. Furthermore, the evaluation of the candidate structures benefits from the complementary empirical analytical information such as retention time, collision cross section values, and ionization type. In this critical review, we provide an overview of the current approaches for retrieving and prioritizing candidate structures. These approaches come with their own set of advantages and limitations, as we showcase in the example of structural annotation of ten known and ten unknown LC/HRMS features. We emphasize that these limitations stem from both experimental and computational considerations. Finally, we highlight three key considerations for the future development of in silico methods.

Estimating LoD-s Based on the Ionization Efficiency Values for the Reporting and Harmonization of Amenable Chemical Space in Nontargeted Screening LC/ESI/HRMS

Amina Souihi, Anneli Kruve

Anal. Chem. 2024

DOI: 10.1021/acs.analchem.4c01002

Nontargeted LC/ESI/HRMS aims to detect and identify organic compounds present in the environment without prior knowledge; however, in practice no LC/ESI/HRMS method is capable of detecting all chemicals, and the scope depends on the instrumental conditions. Different experimental conditions, instruments, and methods used for sample preparation and nontargeted LC/ESI/HRMS as well as different workflows for data processing may lead to challenges in communicating the results and sharing data between laboratories as well as reduced reproducibility. One of the reasons is that only a fraction of method performance characteristics can be determined for a nontargeted analysis method due to the lack of prior information and analytical standards of the chemicals present in the sample. The limit of detection (LoD) is one of the most important performance characteristics in target analysis and directly describes the detectability of a chemical. Recently, the identification and quantification in nontargeted LC/ESI/HRMS (e.g., via predicting ionization efficiency, risk scores, and retention times) have significantly improved due to employing machine learning. In this work, we hypothesize that the predicted ionization efficiency could be used to estimate LoD and thereby enable evaluating the suitability of the LC/ESI/HRMS nontargeted method for the detection of suspected chemicals even if analytical standards are lacking. For this, 221 representative compounds were selected from the NORMAN SusDat list (S0), and LoD values were determined by using 4 complementary approaches. The LoD values were correlated to ionization efficiency values predicted with previously trained random forest regression. A robust regression was then used to estimate LoD values of unknown features detected in the nontargeted screening of wastewater samples. These estimated LoD values were used for prioritization of the unknown features. Furthermore, we present LoD values for the NORMAN SusDat list with a reversed-phase C18 LC method.

Gas Phase Reactivity of Isomeric Hydroxylated Polychlorinated Biphenyls

Emma H Palm, Josefin Engelhardt, Sofja Tshepelevitsh, Jana Weiss, Anneli Kruve

JASMS 2024

DOI: 10.1021/jasms.4c00035

Identification of stereo- and positional isomers detected with high-resolution mass spectrometry (HRMS) is often challenging due to near-identical fragmentation spectra (MS2), similar retention times, and collision cross-section values (CCS). Here we address this challenge on the example of hydroxylated polychlorinated biphenyls (OH-PCBs) with the aim to (1) distinguish between isomers of OH-PCBs using two-dimensional ion mobility spectrometry (2D-IMS) and (2) investigate the structure of the fragments of OH-PCBs and their fragmentation mechanisms by ion mobility spectrometry coupled to high-resolution mass spectrometry (IMS-HRMS). The MS2 spectra as well as CCS values of the deprotonated molecule and fragment ions were measured for 18 OH-PCBs using flow injections coupled to a cyclic IMS-HRMS. The MS2 spectra as well as the CCS values of the parent and fragment ions were similar between parent compound isomers; however, ion mobility separation of the fragment ions is hinting at the formation of isomeric fragments. Different parent compound isomers also yielded different numbers of isomeric fragment mobilogram peaks giving new insights into the fragmentation of these compounds and indicating new possibilities for identification. For spectral interpretation, Gibbs free energies and CCS values for the fragment ions of 4′-OH-CB35, 4′-OH-CB79, 2-OH-CB77 and 4-OH-CB107 were calculated and enabled assignment of structures to the isomeric mobilogram peaks of [M-H-HCl]− fragments. Finally, further fragmentation of the isomeric fragments revealed different fragmentation pathways depending on the isomeric fragment ions.

Predicting the Activity of Unidentified Chemicals in Complementary Bioassays from the HRMS Data to Pinpoint Potential Endocrine Disruptors

Ida Rahu, Meelis Kull, Anneli Kruve

J. Chem. Inf. Model 2024

DOI: 10.1021/acs.jcim.3c02050

The majority of chemicals detected via nontarget liquid chromatography high-resolution mass spectrometry (HRMS) in environmental samples remain unidentified, challenging the capability of existing machine learning models to pinpoint potential endocrine disruptors (EDs). Here, we predict the activity of unidentified chemicals across 12 bioassays related to EDs within the Tox21 10K dataset. Single- and multi-output models, utilizing various machine learning algorithms and molecular fingerprint features as an input, were trained for this purpose. To evaluate the models under near real-world conditions, Monte Carlo sampling was implemented for the first time. This technique enables the use of probabilistic fingerprint features derived from the experimental HRMS data with SIRIUS+CSI:FingerID as an input for models trained on true binary fingerprint features. Depending on the bioassay, the lowest false-positive rate at 90% recall ranged from 0.251 (sr.mmp, mitochondrial membrane potential) to 0.824 (nr.ar, androgen receptor), which is consistent with the trends observed in the models’ performances submitted for the Tox21 Data Challenge. These findings underscore the informativeness of fingerprint features that can be compiled from HRMS in predicting the endocrine-disrupting activity. Moreover, an in-depth SHapley Additive exPlanations analysis unveiled the models’ ability to pinpoint structural patterns linked to the modes of action of active chemicals. Despite the superior performance of the single-output models compared to that of the multi-output models, the latter’s potential cannot be disregarded for similar tasks in the field of in silico toxicology. This study presents a significant advancement in identifying potentially toxic chemicals within complex mixtures without unambiguous identification and effectively reducing the workload for postprocessing by up to 75% in nontarget HRMS.

Online and Offline Prioritization of Chemicals of Interest in Suspect Screening and Non-targeted Screening with High-Resolution Mass Spectrometry

Drew Szabo, Travis M Falconer, Christine M Fisher, Ted Heise, Allison L Phillips, Gyorgy Vas, Antony J Williams, Anneli Kruve

Anal Chem 2024

DOI: 10.1021/acs.analchem.3c05705

Recent advances in high-resolution mass spectrometry (HRMS) have enabled the detection of thousands of chemicals from a single sample, while computational methods have improved the identification and quantification of these chemicals in the absence of reference standards typically required in targeted analysis. However, to determine the presence of chemicals of interest that may pose an overall impact on ecological and human health, prioritization strategies must be used to effectively and efficiently highlight chemicals for further investigation. Prioritization can be based on a chemical’s physicochemical properties, structure, exposure, and toxicity, in addition to its regulatory status. This Perspective aims to provide a framework for the strategies used for chemical prioritization that can be implemented to facilitate high-quality research and communication of results. These strategies are categorized as either “online” or “offline” prioritization techniques. Online prioritization techniques trigger the isolation and fragmentation of ions from the low-energy mass spectra in real time, with user-defined parameters. Offline prioritization techniques, in contrast, highlight chemicals of interest after the data has been acquired; detected features can be filtered and ranked based on the relative abundance or the predicted structure, toxicity, and concentration imputed from the tandem mass spectrum (MS2). Here we provide an overview of these prioritization techniques and how they have been successfully implemented and reported in the literature to find chemicals of elevated risk to human and ecological environments. A complete list of software and tools is available from https://nontargetedanalysis.org/.

Closing the Organofluorine Mass Balance in Marine Mammals Using Suspect Screening and Machine Learning-Based Quantification

Mélanie Z. Lauria, Helen Sepman, Thomas Ledbetter, Merle Plassmann, Anna M. Roos, Malene Simon, Jonathan P. Benskin, Anneli Kruve

ES&T 2024

DOI: 10.1021/acs.est.3c07220

High-resolution mass spectrometry (HRMS)-based suspect and nontarget screening has identified a growing number of novel per- and polyfluoroalkyl substances (PFASs) in the environment. However, without analytical standards, the fraction of overall PFAS exposure accounted for by these suspects remains ambiguous. Fortunately, recent developments in ionization efficiency (IE) prediction using machine learning offer the possibility to quantify suspects lacking analytical standards. In the present work, a gradient boosted tree-based model for predicting log IE in negative mode was trained and then validated using 33 PFAS standards. The root-mean-square errors were 0.79 (for the entire test set) and 0.29 (for the 7 PFASs in the test set) log IE units. Thereafter, the model was applied to samples of liver from pilot whales (n = 5; East Greenland) and white beaked dolphins (n = 5, West Greenland; n = 3, Sweden) which contained a significant fraction (up to 70%) of unidentified organofluorine and 35 unquantified suspect PFASs (confidence level 2–4). IE-based quantification reduced the fraction of unidentified extractable organofluorine to 0–27%, demonstrating the utility of the method for closing the fluorine mass balance in the absence of analytical standards.

Scientometric review: Concentration and toxicity assessment in environmental non-targeted LC/HRMS analysis

Helen Sepman, Louise Malm, Pilleriin Peets, Anneli Kruve

TrEAC 2023

DOI: 10.1016/j.teac.2023.e00217

Non-targeted screening with LC/HRMS is a go-to approach to discover relevant contaminants in environmental water samples that contain an abundance of chemicals. The rapidly increasing popularity of non-targeted LC/HRMS screening has initiated development of a diverse set of methods for assessing the concentration and toxicity of the detected chemicals. This review aims to benchmark the trends in the environmental NTS literature with particular focus on (1) methods used for the quantification of tentatively identified chemicals that lack analytical standards, (2) methods for assessing the toxicity of detected chemicals, and (3) methods combining the former into a risk evaluation. Here we provide a scientometric review of these strategies based on the Web of Science referenced papers published between 2019 and 2022. General trends show that quantification and toxicity assessments are widely employed in NTS, reaching 66 % and 45 % over four years, respectively. Simultaneously, only 13 % of the papers covered here combine these results into a risk factor or similar. With this review we aim to highlight the advantages and gaps in the approaches used for concentration and toxicity assessment and provide guidelines for more homogeneous data interrogation and extrapolation.

NORMAN guidance on suspect and non-target screening in environmental monitoring

Juliane Hollenter, et al.

Environmental Sciences Europe 2023

DOI: 10.1186/s12302-023-00779-4

Increasing production and use of chemicals and awareness of their impact on ecosystems and humans has led to large interest for broadening the knowledge on the chemical status of the environment and human health by suspect and non-target screening (NTS). To facilitate effective implementation of NTS in scientific, commercial and governmental laboratories, as well as acceptance by managers, regulators and risk assessors, more harmonisation in NTS is required. To address this, NORMAN Association members involved in NTS activities have prepared this guidance document, based on the current state of knowledge. The document is intended to provide guidance on performing high quality NTS studies and data interpretation while increasing awareness of the promise but also pitfalls and challenges associated with these techniques. Guidance is provided for all steps; from sampling and sample preparation to analysis by chromatography (liquid and gas-LC and GC) coupled via various ionisation techniques to high-resolution tandem mass spectrometry (HRMS/MS), through to data evaluation and reporting in the context of NTS. Although most experience within the NORMAN network still involves water analysis of polar compounds using LC-HRMS/MS, other matrices (sediment, soil, biota, dust, air) and instrumentation (GC, ion mobility) are covered, reflecting the rapid development and extension of the field. Due to the ongoing developments, the different questions addressed with NTS and manifold techniques in use, NORMAN members feel that no standard operation process can be provided at this stage. However, appropriate analytical methods, data processing techniques and databases commonly compiled in NTS workflows are introduced, their limitations are discussed and recommendations for different cases are provided. Proper quality assurance, quantification without reference standards and reporting results with clear confidence of identification assignment complete the guidance together with a glossary of definitions. The NORMAN community greatly supports the sharing of experiences and data via open science and hopes that this guideline supports this effort.

Bypassing the identification: MS2Quant for concentration estimations of chemicals detected with nontarget LC-HRMS from MS2 data

Helen Sepman, Louise Malm, Pilleriin Peets, Matthew MacLeod, Jonathan W. Martin, Magnus Breitholtz, Anneli Kruve

Anal Chem 2023

DOI: 10.1021/acs.analchem.3c01744

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 knowledge of the structure of the chemical. However, the majority of features detected in non-target 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 root means 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 mean prediction error of 7.4×, geometric mean of 4.5× and 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 comparable mean prediction error of 9.5×, geometric mean of 5.6× and 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 non-target screening.

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

Amina Souihi, Miklos Peter Mohai, Jonathan W Martin, Anneli Kruve

Anal Chim Acta 2023

DOI: 10.1016/j.aca.2023.341573

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.

Complementary methods for structural assignment of isomeric candidate structures in non-target liquid chromatography ion mobility high-resolution mass spectrometric analysis

Masoumeh Akhlaqi, Wei-Chieh Wang, Claudia Möckel, Anneli Kruve

Anal Bioanal Chemy A 2022

DOI: 10.1007/s00216-023-04852-y

Non-target screening with LC/IMS/HRMS is increasingly employed for detecting and identifying the structure of potentially hazardous chemicals in the environment and food. Structural assignment relies on a combination of multidimensional instrumental methods and computational methods. The candidate structures are often isomeric, and unfortunately, assigning the correct structure among a number of isomeric candidate structures still is a key challenge both instrumentally and computationally. While practicing non-target screening, it is usually impossible to evaluate separately the limitations arising from (1) the inability of LC/IMS/HRMS to resolve the isomeric candidate structures and (2) the uncertainty of in silico methods in predicting the analytical information of isomeric candidate structures due to the lack of analytical standards for all candidate structures. Here we evaluate the feasibility of structural assignment of isomeric candidate structures based on in silico–predicted retention time and database collision cross-section (CCS) values as well as based on matching the empirical analytical properties of the detected feature with those of the analytical standards. For this, we investigated 14 candidate structures corresponding to five features detected with LC/HRMS in a spiked surface water sample. Considering the predicted retention times and database CCS values with the accompanying uncertainty, only one of the isomeric candidate structures could be deemed as unlikely; therefore, the annotation of the LC/IMS/HRMS features remained ambiguous. To further investigate if unequivocal annotation is possible via analytical standards, the reversed-phase LC retention times and low- and high-resolution ion mobility spectrometry separation, as well as high-resolution MS2 spectra of analytical standards were studied. Reversed-phase LC separated the highest number of candidate structures while low-resolution ion mobility and high-resolution MS2 spectra provided little means for pinpointing the correct structure among the isomeric candidate structures even if analytical standards were available for comparison. Furthermore, the question arises which prediction accuracy is required from the in silico methods to par the analytical separation. Based on the experimental data of the isomeric candidate structures studied here and previously published in the literature (516 retention time and 569 CCS values), we estimate that to reduce the candidate list by 95% of the structures, the confidence interval of the predicted retention times would need to decrease to below 0.05 min for a 15-min gradient while that of CCS values would need to decrease to 0.15%. Hereby, we set a clear goal to the in silico methods for retention time and CCS prediction.

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

Stefan Bieber, Thomas Letzel, Anneli Kruve

JASMS 2023

DOI: 10.1021/jasms.3c00156

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.

MS2Tox Machine Learning Tool for Predicting the Ecotoxicity of Unidentified Chemicals in Water by Nontarget LC-HRMS

Pilleriin Peets, Wei-Chieh Wang, Matthew MacLeod, Magnus Breitholtz, Jonathan W. Martin, Anneli Kruve

ES&T 2022

DOI: 10.1021/acs.est.2c02536

To achieve water quality objectives of the zero pollution action plan in Europe, rapid methods are needed to identify the presence of toxic substances in complex water samples. However, only a small fraction of chemicals detected with nontarget high-resolution mass spectrometry can be identified, and fewer have ecotoxicological data available. We hypothesized that ecotoxicological data could be predicted for unknown molecular features in data-rich high-resolution mass spectrometry (HRMS) spectra, thereby circumventing time-consuming steps of molecular identification and rapidly flagging molecules of potentially high toxicity in complex samples. Here, we present MS2Tox, a machine learning method, to predict the toxicity of unidentified chemicals based on high-resolution accurate mass tandem mass spectra (MS2). The MS2Tox model for fish toxicity was trained and tested on 647 lethal concentration (LC50) values from the CompTox database and validated for 219 chemicals and 420 MS2 spectra from MassBank. The root mean square error (RMSE) of MS2Tox predictions was below 0.89 log-mM, while the experimental repeatability of LC50 values in CompTox was 0.44 log-mM. MS2Tox allowed accurate prediction of fish LC50 values for 22 chemicals detected in water samples, and empirical evidence suggested the right directionality for another 68 chemicals. Moreover, by incorporating structural information, e.g., the presence of carbonyl-benzene, amide moieties, or hydroxyl groups, MS2Tox outperforms baseline models that use only the exact mass or log KOW.

Protomer Formation Can Aid the Structural Identification of Caffeine Metabolites

Helen Sepman, Sofja Tshepelevitsh, Henrik Hupatz, Anneli Kruve

Anal Chem 2022

DOI: 10.1021/acs.analchem.2c00257

The structural annotation of isomeric metabolites remains a key challenge in untargeted electrospray ionization/high-resolution mass spectrometry (ESI/HRMS) metabolomic analysis. Many metabolites are polyfunctional compounds that may form protomers in electrospray ionization sources and therefore yield multiple peaks in ion mobility spectra. Protomer formation is strongly structure-specific. Here, we explore the possibility of using protomer formation for structural elucidation in metabolomics on the example of caffeine, its eight metabolites, and structurally related compounds. It is observed that two-thirds of the studied compounds formed high- and low-mobility species in high-resolution ion mobility. Structures in which proton hopping was hindered by a methyl group at the purine ring nitrogen (position 3) yielded structure-indicative fragments with collision-induced dissociation (CID) for high- and low-mobility ions. For compounds where such a methyl group was not present, a gas-phase equilibrium could be observed for tautomeric species with two-dimensional ion mobility. We show that the protomer formation and the gas-phase properties of the protomers can be related to the structure of caffeine metabolites and facilitate the identification of the structural isomers.

Uncertainty estimation strategies for quantitative non-targeted analysis

Louis C Groff, Jarod N Grossman, Anneli Kruve, Jeffrey M Minucci, Charles N Lowe, James P McCord, Dustin F Kapraun, Katherine A Phillips, S Thomas Purucker, Alex Chao, Caroline L Ring, Antony J Williams, Jon R Sobus

Anal Bioanal Chemy A 2022

DOI: 10.1007/s00216-022-04118-z

Non-targeted analysis (NTA) methods are widely used for chemical discovery but seldom employed for quantitation due to a lack of robust methods to estimate chemical concentrations with confidence limits. Herein, we present and evaluate new statistical methods for quantitative NTA (qNTA) using high-resolution mass spectrometry (HRMS) data from EPA’s Non-Targeted Analysis Collaborative Trial (ENTACT). Experimental intensities of ENTACT analytes were observed at multiple concentrations using a semi-automated NTA workflow. Chemical concentrations and corresponding confidence limits were first estimated using traditional calibration curves. Two qNTA estimation methods were then implemented using experimental response factor (RF) data (where RF = intensity/concentration). The bounded response factor method used a non-parametric bootstrap procedure to estimate select quantiles of training set RF distributions. Quantile estimates then were applied to test set HRMS intensities to inversely estimate concentrations with confidence limits. The ionization efficiency estimation method restricted the distribution of likely RFs for each analyte using ionization efficiency predictions. Given the intended future use for chemical risk characterization, predicted upper confidence limits (protective values) were compared to known chemical concentrations. Using traditional calibration curves, 95% of upper confidence limits were within ~tenfold of the true concentrations. The error increased to ~60-fold (ESI+) and ~120-fold (ESI−) for the ionization efficiency estimation method and to ~150-fold (ESI+) and ~130-fold (ESI−) for the bounded response factor method. This work demonstrates successful implementation of confidence limit estimation strategies to support qNTA studies and marks a crucial step towards translating NTA data in a risk-based context.

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

Sara Khabazbashi, Josefin Engelhardt, Claudia Möckel, Jana Weiss, Anneli Kruve

Anal Bioanal Chem 2022

DOI: 10.1007/s00216-022-04096-2

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.

MultiConditionRT: Predicting liquid chromatography retention time for emerging contaminants for a wide range of eluent compositions and stationary phases

Amina Souihi, Miklos Mohai, Emma Palm Louise Malm, Anneli Kruve

Journal of Chromatography A 2022

DOI: 10.1016/j.chroma.2022.462867

Structural elucidation of compounds detected with liquid chromatography coupled to high resolution mass spectrometry is a challenging and time-consuming step in the workflow of non-targeted analysis and often requires manual validation of the results. Retention time, alongside exact mass, isotope pattern, fragmentation spectra, and collision cross-section, is valuable information for ruling out unlikely structures and increasing the confidence in others. Different approaches to predict retention times have been used previously for reversed phase chromatography and hydrophilic interaction liquid chromatography (HILIC), but application is limited to a small set of mobile phases and gradient profiles. Here, we expand the toolbox available for retention time predictions by developing a random forest regression model for predicting retention times for four column types and twenty mobile phase systems. MultiConditionRT was built using a dataset containing 78 compounds analyzed with C18 reversed phase, mixed mode, HILIC, and biphenyl columns. In addition, different eluent compositions were used: both methanol and acetonitrile were combined with different aqueous phases with pH from 2.1 to 10.0 (formic acid, acetic acid, trifluoroacetic acid, formate, acetate, bicarbonate, and ammonia). The root mean square error (RMSE) of the test set predictions was 1.55 min for C18 reversed phase, 1.79 min for mixed-mode, 1.93 min for HILIC, and 1.56 min for biphenyl column. Additionally, MultiConditionRT can be applied to different gradient profiles with a general additive model-based calibration approach. The approach of MultiConditionRT was validated externally and internally with 356 and 151 compounds respectively, yielding an RMSE of 2.68 and 2.32 min. 324 and 84 of these compounds were not in the dataset used in the model development.

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

Emma Palm, Anneli Kruve

Molecules 2022

DOI: 10.3390/molecules27031013

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.

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

Riccardo Costalunga, Sofja Tshepelevitsh, Helen Sepman, Meelis Kull, Anneli Kruve

Analytica Chimica Acta 2021

DOI: 10.1016/j.aca.2021.339402

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

Quantitative electrospray ionization efficiency scale: 10 years after

Merit Oss, Sofja Tshepelevitsh, Anneli Kruve, Piia Liigand, Jaanus Liigand, Riin Rebane, Sigrid Selberg, Kristel Ets, Koit Herodes, Ivo Leito

Rapid Commun Mass Spectrum 2021

DOI: 10.1002/rcm.9178

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 pKaH 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.

Risk-based prioritization of suspects detected in riverine water using complementary chromatographic techniques

Frederic Been, Anneli Kruve, Dennis Vughs, Nienke Meekel, Astrid Reus, Anne Zwartsen, Arnoud Wessel, Astrid Fischer, Thomas ter Laak, Andrea M. Brunner

Water Research 2021

DOI: 10.1016/j.watres.2021.117612

Surface waters are widely used as drinking water sources and hence their quality needs to be continuously monitored. However, current routine monitoring programs are not comprehensive as they generally cover only a limited number of known pollutants and emerging contaminants. This study presents a risk-based approach combining suspect and non-target screening (NTS) to help extend the coverage of current monitoring schemes. In particular, the coverage of NTS was widened by combining three complementary separations modes: Reverse phase (RP), Hydrophilic interaction liquid chromatography (HILIC) and Mixed-mode chromatography (MMC). Suspect lists used were compiled from databases of relevant substances of very high concern (e.g., SVHCs) and the concentration of detected suspects was evaluated based on ionization efficiency prediction. Results show that suspect candidates can be prioritized based on their potential risk (i.e., hazard and exposure) by combining ionization efficiency-based concentration estimation, in vitro toxicity data or, if not available, structural alerts and QSAR.based toxicity predictions. The acquired information shows that NTS analyses have the potential to complement target analyses, allowing to update and adapt current monitoring programs, ultimately leading to improved monitoring of drinking water sources.

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

Louise Malm, Emma Palm, Amina Souihi, Merle Plassmann, Jaanus Liigand, Anneli Kruve

Molecules 2021, 26(12), 3524

DOI: 10.3390/molecules26123524

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.

Presentations from conferences can be found here.

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

Piia Liigand, Jaanus Liigand, Karl Kaupmees and Anneli Kruve

Analytica Chimica Acta 2021, 1152, 238117

DOI: 10.1016/j.aca.2020.11.049

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.

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

Anneli Kruve, Karin Kiefer, Juliane Hollender

Analytical and Bioanalytical Chemistry 2021, 413(6), 1549-1559

DOI: 10.1007/s00216-020-03109-2

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.

Our poster presentations from conferences can be found here.

Standard substances free quantification makes LC/ESI/MS non-targeted screening of pesticides in cereals comparable between labs

TingtingWang, JaanusLiigand, Henrik LauritzFrandsen, JørnSmedsgaard, AnneliKruve

Food Chemistry 2020, 318

DOI: 10.1016/j.foodchem.2020.126460

LC/ESI/MS is the technique of choice for qualitative and quantitative food monitoring; however, analysis of a large number of compounds is challenged by the availability of standard substances. The impediment of detection of food contaminants has been overcome by the suspect and non-targeted screening. Still, the results from one laboratory cannot be compared with the results of another laboratory as quantitative results are required for this purpose. Here we show that the results of the suspect and non-targeted screening for pesticides can be made quantitative with the aid of in silico predicted electrospray ionization efficiencies and this allows direct comparison of the results obtained in two different laboratories. For this purpose, six cereal matrices were spiked with 134 pesticides and analysed in two independent labs; a high correlation for the results with the R2 of 0.85.

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

Artur Gornischeff, AnneliKruve, Riin Rebane

Journal of Chromatography A 2020

DOI: 10.1016/j.chroma.2020.461012

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.

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

Anneli Kruve

Analytical Chemistry 2020

DOI: 10.1021/acs.analchem.9b03481

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.

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

Jaanus Liigand, Tingting Wang, Joshua Kellogg, Jørn Smedsgaard, Nadja Cech, Anneli Kruve

Scientific Reports 2020

DOI: 10.1038/s41598-020-62573-z

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 (RF) 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 5.9 times, which is well compatible with the accuracy of the toxicology predictions.

Instrumental techniques in the analysis of natural red textile dyes

Pilleriin Peets, Signe vahur, Anneli Kruve, Tõiv Haljasorg, Koit Herodes, Todd Pagano, Ivo Leito

Journal of Cultural Heritage 2020, 42, 19-27

DOI: 10.1016/j.culher.2019.09.002

Various dyes present in historical objects can be indicative of different usage, age and origin of the artifacts. Knowledge about the composition and origin of textile dyes is essential for the preservation and conservation of the items. In this paper, we compare different instrumental techniques to detect and identify natural red dyes from historical textiles without the need for standard substances of the dye components. Several instrumental techniques were used, including liquid chromatography with photodiode array, fluorescence and mass -spectrometric detectors, as well as Fourier transform ion cyclotron resonance mass spectrometry with electrospray ionization and matrix-assisted laser desorption/ionization sources. Seven natural red dye sources were investigated, including dyer’s madder, redwood, logwood, sandalwood, kermes, American cochineal and bloodred webcap (Cortinarius sanguineus). The dye components of the latter source have not been characterized before with all of these analytical techniques. A substantial library of chromatograms and mass spectra, along with absorption and fluorescence spectra (altogether 113 chromatograms/spectra), of dyes and/or dye components were recorded and a comparison of the utility of the different analytical techniques in the analysis of the dye sources is provided. The usefulness of the assembled library of chromatograms/spectra is demonstrated on the analysis of several historical textile samples from museum artifacts..

The NORMAN Association and the European Partnership for Chemicals Risk Assessment (PARC): let’s cooperate!

Valeria Dulio, et al.

Environmental Sciences Europe 2020, 32, 100

DOI:  10.1186/s12302-020-00375-w

The Partnership for Chemicals Risk Assessment (PARC) is currently under development as a joint research and innovation programme to strengthen the scientific basis for chemical risk assessment in the EU. The plan is to bring chemical risk assessors and managers together with scientists to accelerate method development and the production of necessary data and knowledge, and to facilitate the transition to next-generation evidence-based risk assessment, a non-toxic environment and the European Green Deal. The NORMAN Network is an independent, well-established and competent network of more than 80 organisations in the field of emerging substances and has enormous potential to contribute to the implementation of the PARC partnership. NORMAN stands ready to provide expert advice to PARC, drawing on its long experience in the development, harmonisation and testing of advanced tools in relation to chemicals of emerging concern and in support of a European Early Warning System to unravel the risks of contaminants of emerging concern (CECs) and close the gap between research and innovation and regulatory processes. In this commentary we highlight the tools developed by NORMAN that we consider most relevant to supporting the PARC initiative: (i) joint data space and cutting-edge research tools for risk assessment of contaminants of emerging concern; (ii) collaborative European framework to improve data quality and comparability; (iii) advanced data analysis tools for a European early warning system and (iv) support to national and European chemical risk assessment thanks to harnessing, combining and sharing evidence and expertise on CECs. By combining the extensive knowledge and experience of the NORMAN network with the financial and policy-related strengths of the PARC initiative, a large step towards the goal of a non-toxic environment can be taken.

Our poster presentations from conferences can be found here.

Ion-Mobility Mass Spectrometry for the Rapid Determination of the Topology of Interlocked and Knotted Molecules

Anneli Kruve, Kenji Caprice, Roy lavendomme, Jan M. Wollschlaeger, Stefan Schoder, Henrik V. Schröder, Jonathan R. Nitschke, Fabien B.L. Cougnon, Christoph A. Schalley

Angewandte Chemie 2019, 58(33), 11324-11328

DOI: 10.1002/anie.201904541

A rapid screening method based on traveling‐wave ion‐mobility spectrometry (TWIMS) combined with tandem mass spectrometry provides insight into the topology of interlocked and knotted molecules, even when they exist in complex mixtures, such as interconverting dynamic combinatorial libraries. A TWIMS characterization of structure‐indicative fragments generated by collision‐induced dissociation (CID) together with a floppiness parameter defined based on parent‐ and fragment‐ion arrival times provide a straightforward topology identification. To demonstrate its broad applicability, this approach is applied here to six Hopf and two Solomon links, a trefoil knot, and a [3]catenate.

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

Riin Rebane, Anneli Kruve, Jaanus Liigand, Piia Liigand, Artur Gornischeff, Ivo Leito

Rapid Communications in Mass Spectrometry 2019, 33(23), 1834-1843

DOI: 10.1002/rcm.8545

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.

Our poster presentations from conferences can be found here.

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

Piia Liigand, Karl Kaupmees and Anneli Kruve

Journal of Mass Spectrometry 2019, 54(6), 481-487

DOI: 10.1002/jms.4348

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 5 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.

ESI outcompetes other ion sources in LC/MS trace analysis

Asko Laaniste, Ivo Leito, Anneli Kruve

Analytical and Bioanalytical Chemistry 2019, 411(16), 3533-3542

DOI: 10.1007/s00216-019-01832-z

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

Jaanus Liigand, Ronald de Vries, Filip Cuyckens

Rapid Communications in Mass Spectrometry 2019, 33(3), 314-322

DOI: 10.1002/rcm.8352

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 pKa). 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.

Anion-driven encapsulation of cationic guests inside pyridine[4]arene dimers

Anniina Kiesila, Jani O. Moilanen, AnneliKruve, Christoph A. Schalley, Perdita Barran, Elina Kalenius

Bielstein Journal of Organic Chemistry 2019, 15, 2486-2492

DOI:  10.3762/bjoc.15.241

Pyridine[4]arenes have previously been considered as anion binding hosts due to the electron-poor nature of the pyridine ring. Herein, we demonstrate the encapsulation of Me4N+ cations inside a dimeric hydrogen-bonded pyridine[4]arene capsule, which contradicts with earlier assumptions. The complexation of a cationic guest inside the pyridine[4]arene dimer has been detected and studied by multiple gas-phase techniques, ESI-QTOF-MS, IRMPD, and DT-IMMS experiments, as well as DFT calculations. The comparison of classical resorcinarenes with pyridinearenes by MS and NMR experiments reveals clear differences in their host-guest chemistry and implies that cation encapsulation in pyridine[4] arene is an anion-driven process.

Our poster presentations from conferences can be found here.

Semi‐quantitative non‐target analysis of water with LC/HRMS: how far are we?

Anneli Kruve

Rapid Communications in Mass Spectrometry 2018, in press

DOI: 10.1002/rcm.8208

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.

Ionisation efficiencies can be predicted in complicated biological matrices: A proof of concept

Piia Liigand, Jaanus Liigand, Filip Cuyckens, Rob J. Vreeken and Anneli Kruve

Analytica Chimica Acta 2018, 1032, 68-74

DOI: 10.1016/j.aca.2018.05.072

The importance of metabolites is assessed based on their abundance. Most of the metabolites are at present identified based on ESI/MS measurements and the relative abundance is assessed from the relative peak areas of these metabolites. Unfortunately, relative intensities can be highly misleading as different compounds ionise with vastly different efficiency in the ESI source and matrix components may cause severe ionisation suppression. In order to reduce this inaccuracy, we propose predicting the ionisation efficiencies of the analytes in seven biological matrices (neat solvent, blood, plasma, urine, cerebrospinal fluid, brain and liver tissue homogenates). We demonstrate, that this approach may lead to an order of magnitude increase in accuracy even in complicated matrices. For the analyses of 10 compounds, mostly drugs, in negative electrospray ionisation mode we reduce the predicted abundance mismatch compared to the actual abundance on average from 660 to 8 times. The ionisation efficiencies were predicted based on i) the charge delocalisation parameter WAPS and ii) the degree of ionisation α, and the prediction model was subsequently validated based on the cross-validation method ‘leave-one-out’.

Modifying the Acidity of Charged Droplets

Mari Ojakivi, Jaanus Liigand and Anneli Kruve

Chemistry Select 2018, 3, 335 – 338

DOI: 10.1002/slct.201702269

The concept of acidity in confined spaces is up to date poorly understood; especially, in case of media violating electroneutrality. Here, we describe the acidity of charged droplets via their ability to protonate simple nitrogen bases and we propose ways to modify the protonation efficiency with the help of additives. We observed that the protonation of compounds in charged water droplets is independent of solution-phase acidity; instead, it can be adjusted with the help of additive type. On the other hand, the extent of protonation in charged methanol droplets can be adjusted with the
conventional approach of changing the pH.

Quantitative and sensitive mapping of imidacloprid on plants using Multiphoton Electron Extraction Spectroscopy

Anneli Kruve, Valery Bulatov and Israel Schechter

Chemical Physics, in press

DOI: 10.1016/j.chemphys.2018.03.031

Neonicotinoids, including imidacloprid, are extensively used for plant protection against insects. Unfortunately, these effective pesticides are one of the reasons for the decline of the bee population in recent decades. Ensuring application of minimal pesticide quantity and preventing excess requires a fast method for monitoring the coverage on plants. We present a new, method based on multiphoton electron extraction spectroscopy (MEES), for detecting, quantifying and mapping of imidacloprid coverage on plants. Imaging and quantitative analyses were demonstrated on several plant surfaces including olive and mint leaves and orange peel. Method provides both low detection limits (down to nanogram level) and good trueness. This method is fast and can be directly performed with no sample pre-treatment, thus, it is a good candidate for field analyses.

pH Effects on Electrospray Ionization Efficiency

Jaanus Liigand, Asko Laaniste and Anneli Kruve

J. Am. Soc. Mass Spectrom. 2017,28( 3), 461 – 469

DOI: 10.1007/s13361-016-1563-1

Electrospray ionization efficiency is known to be affected by mobile phase composition. In this paper, a detailed study of analyte ionization efficiency dependence on mobile phase pH is presented. The pH effect was studied on 28 compounds with different chemical properties. Neither pKa nor solution phase ionization degree by itself was observed to be sufficient at describing how aqueous phase pH affects the ionization efficiency of the analyte. Therefore, the analyte behavior was related to various physicochemical properties via linear discriminant analyses. Distinction between pH-dependent and pH-independent compounds was achieved using two parameters: number of potential charge centers and hydrogen bonding acceptor capacity (in the case of 80% acetonitrile) or polarity of neutral form of analyte and pKa (in the case of 20% acetonitrile). It was also observed that decreasing pH may increase ionization efficiency of a compound by more than two orders of magnitude.

Think Negative: Finding the Best Electrospray Ionization/MS Mode for Your Analyte

Piia Liigand, Karl Kaupmees, Kristjan Haav, Jaanus Liigand,Ivo Leito, Marion Girod, Rodolphe Antoine and Anneli Kruve

Anal. Chem. 2017, 89( 11), 5665 – 5668

DOI: 10.1021/acs.analchem.7b00096

For the first time, the electrospray ionization efficiency (IE) scales in positive and negative mode are united into a single system enabling direct comparison of IE values across ionization modes. This is made possible by the use of a reference compound that ionizes to a similar extent in both positive and negative modes. Thus, choosing the optimal (i.e., most sensitive) ionization conditions for a given set of analytes is enabled. Ionization efficiencies of 33 compounds ionizing in both modes demonstrate that, contrary to general practice, negative mode allows better sensitivity for 46% of such compounds whereas the positive mode is preferred for only 18%, and for 36%, the results for both modes are comparable.

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

Piia Liigand, Agnes Heering (Suu), Karl Kaupmees, Ivo Leito, Marion Girod, Rodolphe Antoine and Anneli Kruve

J. Am. Soc. Mass Spectrom. 2017, 28 (10), 2124-2131

DOI: 10.1007/s13361-017-1737-5

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 (pHabsH2O) – to describe pH change in the plume that takes into account organic solvent content in the mobile phase. pHabsH2O 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.

Adduct Formation in ESI/MS by Mobile Phase Additives

Anneli Kruve and Karl Kaupmees

J. Am. Soc. Mass Spectrom. 2017, 28 (5), 887-894

DOI: 10.1007/s13361-017-1626-y

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. Though 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.

Imine-based [2]catenanes in water

Kenji Caprice, Marion Pupier, Anneli Kruve, Christoph Schalley and Fabien B. L. Cougnon

Chemical Science 2017, 28 (5), 887-894

DOI: 10.1039/C7SC04901C

We report the efficient condensation of imine-based macrocycles from dialdehyde A and aliphatic diamines Bn in pure water. Within the libraries, we identified a family of homologous amphiphilic [2]catenanes, whose self-assembly is primarily driven by the hydrophobic effect. The length and odd-even character of the diamine alkyl linker dictate both the yield and the conformation of the [2]catenanes, whose particular thermodynamic stability further shifts the overall equilibrium in favour of imine condensation. These findings highlight the role played by solvophobic effects in the self-assembly of complex architectures.

Laser Applications in Chromatography

Anneli Kruve and Israeli Schechter

Advances in Chromatography 2017, 55, 23-49

WEB: 10.1039/C7SC04901C

In this chapter we give overview of the state of the art methods using lasers in chromatographic detection systems. More precisely, we will focus on Surface Enhances Raman Spectroscopy (SERS), Laser Induced Fluorescence (LIF), Multiangle Light Scattering (MALS) and different methods allowing connecting chromatography and mass spectrometry (MS), such as Single Photon Ionization (SPI), Multiphoton Ionization (MPI), Matrix Assisted Laser Desorption/Ionization (MALDI) together with novel ambient laser induced ionization methods. We introduce the principle of these methods, describe the advantages, possible interferences and technical solutions used. For each method we also describe up to date applications in several fields together with the obtained advantages over conventional detectors.

Determination of glyphosate in surface water with high organic matter content

Vahur Toss, Ivo Leito, Sergei Yurchenko, Rene Freiberg and Anneli Kruve

Environ Sci Pollut Res 2018, 66 (1), 7880-7888

DOI: 10.1007/s11356-017-8522-7

In this paper, we investigate the sample preparation and analysis process in order to achieve adequate results for surface water collected from rivers that flow through swamps and are consequently rich in organic matter. We show that matrix effects in glyphosate determination can be reduced by optimizing sample volume, liquid chromatography (LC) mobile phase buffer concentration and pH as well as gradient speed. Also, aspects of derivatization procedure (borate buffer concentration, fluorenylmethyloxycarbonyl chloride concentration) and their influence on accuracy are considered in detail. We encountered a cross-talk effect in the mass spectra, interfering with quantization during analysis, which was removed by optimizing MS parameters. As a result it was demonstrated that isotope-labelled internal standard with just one 13C atom is sufficient for the analysis. All these aspects were found to strongly impact the accuracy of the glyphosate determination but have received little or no attention in earlier works. We propose a reliable solid phase extraction and LC/ESI/MS/MS method for determination of glyphosate in organic-rich waters and demonstrate that LoD can be decreased by about two times using an ESI nebulizer with a modified design.

Predicting ESI/MS Signal Change for Anions in Different Solvents

Anneli Kruve and Karl Kaupmees

Anal Chem 2017, 89 (9), 5079-5086.

DOI: 10.1021/acsanalchem.7b00595

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 physico-chemical 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.

Ionization Efficiency of Doubly Charged Ions Formed from Polyprotic Acids in Electrospray Negative Mode

Piia Liigand, Karl Kaupmees and Anneli Kruve

J. Am. Soc. Mass Spectrom. 2016, 27 (7), 1211-1218

DOI: 10.1007/s13361-016-1384-2

The ability of polyprotic acids to give doubly charged ions in negative mode electrospray was studied and related to physicochemical properties of the acids via linear discriminant analysis (LDA). It was discovered that the compound has to be strongly acidic (low pKa1 and pKa2) and to have high hydrophobicity (logPow) to become multiply charged. Ability to give multiply charged ions in ESI/MS cannot be directly predicted from the solution phase acidities. Therefore, for the first time, a quantitative model to predict the charge state of the analyte in ESI/MS is proposed and validated for small anions. Also, a model to predict ionization efficiencies of these analytes was developed. Results indicate that acidity of the analyte, its octanol-water partition coefficient, and charge delocalization are important factors that influence ionization efficiencies as well as charge states of the analytes. The pH of the solvent was also found to be an important factor influencing the ionization efficiency of doubly charged ions.

Establishing Atmospheric Pressure Chemical Ionization Efficiency Scale

Riin Rebane, Anneli Kruve, Piia Liigand, Jaanus Liigand, Koit Herodes and Ivo Leito

Anal. Chem. 2016, 88( 7), 3435 – 3439

DOI: 10.1021/acs.analchem.5b04852

Recent evidence has shown that the atmospheric pressure chemical ionization (APCI) mechanism can be more complex than generally assumed. In order to better understand the processes in the APCI source, for the first time, an ionization efficiency scale for an APCI source has been created. The scale spans over 5 logIE (were IE is ionization efficiency) units and includes 40 compounds with a wide range of chemical and physical properties. The results of the experiments show that for most of the compounds the ionization efficiency order in the APCI source is surprisingly similar to that in the ESI source. Most of the compounds that are best ionized in the APCI source are not small volatile molecules. Large tetraalkylammonium cations are a prominent example. At the same time, low-polarity hydrocarbons pyrene and anthracene are ionized in the APCI source but not in the ESI source. These results strongly imply that in APCI several ionization mechanisms operate in parallel and a mechanism not relying on evaporation of neutral molecules from droplets has significantly higher influence than commonly assumed.

Determination of neonicotinoids in Estonian honey by liquid chromatography–electrospray mass spectrometry

Asko Laaniste, Ivo Leito, Riin Rebane, Rünno Lõhmus, Ants Lõhmus, Fredrik Punga and Anneli Kruve

J. Environ. Sci. Health. Part B 2016, 51, 455-464.

DOI: 10.1080/03601234.2016.1159457

The aim of the study was to provide a comprehensive overview of neonicotinoid pesticide residues in honey samples for a single country and compare the results with the import data for neonicotinoid pesticides. The levels of four neonicotinoid pesticides, namely thiamethoxam, imidacloprid, acetamiprid and thiacloprid, were determined in 294 honey samples harvested from 2005 to 2013 from more than 200 locations in Estonia. For the analyzed honey samples, 27% contained thiacloprid and its levels, in all cases, were below the maximum residue level (MRL) set by the European Union (EU). The other neonicotinoids were not detected. The proportion of thiacloprid-positive samples for the different years correlates well with the data on thiacloprid imports into Estonia, indicating that honey contamination with neonicotinoids can be estimated based on import data.

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

Anneli Kruve

J. Am. Soc. Mass Spectrom. 2016, 51 (8), 596-602.

DOI: 10.1002/jms.3790

Electrospray ionisation (ESI) efficiency is known to be affected by the properties of the analytes, source design and source parameters. In this study, the ionisation efficiency of 17 acidic compounds at various conditions in ESI negative ion mode was evaluated. Namely, the influence of organic solvent content in the mobile phase, ionisation source parameters, ionisation source geometry and functionality (conventional ESI, ESI with thermal focusing and with additional internal nebuliser gas) was studied. It was observed that the ionisation efficiency in thermal focusing ESI is only marginally affected by the organic solvent composition, while for conventional ESI and ESI with internal nebuliser gas, the ionisation efficiency increases significantly with increasing organic modifier content. For all ionisation sources and mobile phase compositions, the ionisation efficiency values between different setups showed good correlation.

Transferability of the Electrospray Ionization Efficiency Scale between Different Instruments

Jaanus Liigand,Anneli Kruve, Piia Liigand, Asko Laaniste, Marion Girod, Rodolphe Antoine and Ivo Leito

J. Am. Soc. Mass Spectrom. 2015, 26( 11), 1923 – 1930

DOI: 10.1007/s13361-015-1219-6

For the first time, quantitative electrospray (ESI) ionization efficiencies (IE), expressed as logIE values, obtained on different mass-spectrometric setups (four mass analyzers and four ESI sources) are compared for 15 compounds of diverse properties. The general trends of change of IE with molecular structure are the same with all experimental setups. The obtained IE scales could be applied on different setups: there were no statistically significant changes in the order of ionization efficiency and the root mean of squared differences of the logIE values of compounds between the scales compiled on different instruments were found to be between 0.21 and 0.55 log units. The results show that orthogonal ESI source geometry gives better differentiating power and additional pneumatic assistance improves it even more. It is also shown that the ionization efficiency values are transferable between different mass-spectrometric setups by three anchoring points and a linear model. The root mean square error of logIE prediction ranged from 0.24 to 0.72 depending on the instrument. This work demonstrates for the first time the inter-instrument transferability of quantitative electrospray ionization efficiency data.

Unified pH Values of Liquid Chromatography Mobile Phases

Agnes Suu, Lauri Jalukse, Jaanus Liigand, Anneli Kruve, Daniel Himmel, Ingo Krossing, Marti Rosés and Ivo Leito

Anal. Chem. 2015, 87( 5), 2623–2630

DOI: 10.1021/ac504692m

This work introduces a conceptually new approach of measuring pH of mixed-solvent liquid chromatography (LC) mobile phases. Mobile phase pH is very important in LC, but its correct measurement is not straightforward, and all commonly used approaches have deficiencies. The new approach is based on the recently introduced unified pH (pHabs) scale, which enables direct comparison of acidities of solutions made in different solvents based on chemical potential of the proton in the solutions. This work represents the first experimental realization of the pHabs concept using differential potentiometric measurement for comparison of the chemical potentials of the proton in different solutions (connected by a salt bridge), together with earlier published reference points for obtaining the pHabs values (referenced to the gas phase) or pHabsH2O values (referenced to the aqueous solution). The liquid junction potentials were estimated in the framework of Izutsu’s three-component method. pHabs values for a number of common LC and LC–MS mobile phases have been determined. The pHabs scale enables for the first time direct comparison of acidities of any LC mobile phases, with different organic additives, different buffer components, etc. A possible experimental protocol of putting this new approach into chromatographic practice has been envisaged and its applicability tested. It has been demonstrated that the ionization behavior of bases (cationic acids) in the mobile phases can be better predicted by using the pHabsH2O values and aqueous pKa values than by using the alternative means of expressing mobile phase acidity. Description of the ionization behavior of acids on the basis of pHabsH2O values is possible if the change of their pKa values with solvent composition change is taken into account.

Paper spray ionization mass spectrometry: Study of a method for fast-screening analysis of pesticides in fruits and vegetables

Hanno Evard, Anneli Kruve, Rünno Lõhmus and Ivo Leito

J. Food Compos. Anal. 2015, 41, 221-225.

DOI: 10.1016/j.jfca.2015.01.010

New faster and simpler methods for determination of pesticides in agricultural products are necessary as requirements for food safety are becoming increasingly stringent. One possibility is to introduce a fast, easy and low-cost screening method before liquid chromatography mass spectrometry analyses. We hereby present a systematic proof of concept study of paper spray mass spectrometry method for pesticide detection as a screening method. Two sampling approaches – wiping the surface with paper and applying the sample homogenate directly on the paper – were used. The wiping method was more extensively studied for imazalil and thiabendazole originally present in oranges.. For homogenized samples three matrices – oranges, tomatoes and grapes – and five pesticides of different chemical nature and polarity – thiabendazole, aldicarb, imazalil, methomyl and methiocarb – were chosen. It has been shown that limits of detection below maximum residue levels can be achieved for both methods. The methods are therefore suitable for fast screening of samples. Moreover, the wiping method was also applied for 11 samples – oranges, grapefruits, lemons, limes, mandarins, tomatoes, apples, pears, strawberries, grapes and sweet peppers – from the local supermarket to screen for different pesticides. Three positive samples for thiabendazole and imazalil and one positive sample for only imazalil were found.

Tutorial review on validation of liquid chromatography–mass spectrometry methods: Part I

Anneli Kruve, Riin Rebane, Karin Kipper, Maarja-Liisa Oldekop, Hanno Evard, Koit Herodes, Pekka Ravio and Ivo Leito

Analytica Chimica Acta 2015, 870, 29-44

DOI: 10.1016/j.aca.2015.02.017

This is the part I of a tutorial review intending to give an overview of the state of the art of method validation in liquid chromatography mass spectrometry (LC-MS) and discuss specific issues that arise with MS (and MS/MS) detection in LC (as opposed to the “conventional” detectors). The Part I briefly introduces the principles of operation of LC-MS (emphasizing the aspects important from the validation point of view, in particular the ionization process and ionization suppression/enhancement); reviews the main validation guideline documents and discusses in detail the following performance parameters: selectivity/specificity/identity, ruggedness/robustness, limit of detection, limit of quantification, decision limit and detection capability. With every method performance characteristic its essence and terminology are addressed, the current status of treating it is reviewed and recommendations are given, how to determine it, specifically in the case of LC-MS methods.

Tutorial review on validation of liquid chromatography–mass spectrometry methods: Part II

Anneli Kruve, Riin Rebane, Karin Kipper, Maarja-Liisa Oldekop, Hanno Evard, Koit Herodes, Pekka Ravio and Ivo Leito

Analytica Chimica Acta 2015, 870, 8-28.

DOI: 10.1016/j.aca.2015.02.016

This is the part II of a tutorial review intending to give an overview of the state of the art of method validation in liquid chromatography mass spectrometry (LC-MS) and discuss specific issues that arise with MS (and MSMS) detection in LC (as opposed to the “conventional” detectors). The Part II starts with briefly introducing the main quantitation methods and then addresses the performance related to quantification: linearity of signal, sensitivity, precision, trueness, accuracy, stability and measurement uncertainty. The last section is devoted to practical considerations in validation. With every performance characteristic its essence and terminology are addressed, the current status of treating it is reviewed and recommendations are given, how to handle it, specifically in the case of LC-MS methods.

Negative Electrospray Ionization via Deprotonation: Predicting the Ionization Efficiency

Anneli Kruve, Karl Kaupmees, Jaanus Liigand and Ivo Leito

Anal. Chem. 2014, 86( 10), 4822–4830

DOI: 10.1021/ac404066v

Electrospray ionization (ESI) in the negative ion mode has received less attention in fundamental studies than the positive ion electrospray ionization. In this paper, we study the efficiency of negative ion formation in the ESI source via deprotonation of substituted phenols and benzoic acids and explore correlations of the obtained ionization efficiency values (logIE) with different molecular properties. It is observed that stronger acids (i.e., fully deprotonated in the droplets) yielding anions with highly delocalized charge [quantified by the weighted average positive sigma (WAPS) parameter rooted in the COSMO theory] have higher ionization efficiency and give higher signals in the negative-ion ESI/MS. A linear model was obtained, which equally well describes the logIE of both phenols and benzoic acids (R2 = 0.83, S = 0.40 log units) and contains only an ionization degree in solution (α) and WAPS as molecular parameters. Both parameters can easily be calculated with the COSMO-RS method. The model was successfully validated using a test set of acids belonging neither to phenols nor to benzoic acids, thereby demonstrating its broad applicability and the universality of the above-described relationships between IE and molecular properties.

Effect of Mobile Phase on Electrospray Ionization Efficiency

Jaanus Liigand,Anneli Kruve,Ivo Leito, Marion Girod and Rodolphe Antoine

J. Am. Soc. Mass Spectrom. 2014, 25( 11), 1853 – 1861

DOI: 10.1007/s13361-014-0969-x

Electrospray (ESI) ionization efficiencies (IE) of a set of 10 compounds differing by chemical nature, extent of ionization in solution (basicity), and by hydrophobicity (tetrapropylammonium and tetraethylammonium ion, triethylamine, 1-naphthylamine, N,N-dimethylaniline, diphenylphthalate, dimethylphtahalate, piperidine, pyrrolidine, pyridine) have been measured in seven mobile phases (three acetonitrile percentages 20%, 50%, and 80%, and three different pH-adjusting additives, 0.1% formic acid, 1 mM ammonia, pH 5.0 buffer combination) using the relative measurement method. MS parameters were optimized separately for each ion. The resulting relative IE data were converted into comparable logIE values by anchoring them to the logIE of tetrapropylammonium ion taking into account the differences of ionization in different solvents and thereby making the logIE values of the compounds comparable across solvents. The following conclusions were made from analysis of the data. The compounds with pKa values in the range of the solution pH values displayed higher IE at lower pH. The sensitivity of IE towards pH depends on hydrophobicity being very strong with pyridine, weaker with N,N-dimethylaniline, and weakest with 1-naphthylamine. IEs of tetraalkylammonium ions and triethylamine were expectedly insensitive towards solution pH. Surprisingly high IEs of phthalate esters were observed. The differences in solutions with different acetonitrile content and similar pH were smaller compared with the pH effects. These results highlight the importance of hydrophobicity in electrospray and demonstrate that high hydrophobicity can sometimes successfully compensate for low basicity.

Comparison of different methods aiming to account for/overcome matrix effects in LC/ESI/MS on the example of pesticide analyses

Anneli Kruve and Ivo Leito

Analytical methods 2013, 5(12), 3035-3044.

DOI: 10.1039/C3AY26551J

In this paper some of the most common methods for overcoming matrix effects in LC/ESI/MS (matrix-matched calibration, standard addition, post-column standard infusion, extrapolative dilution, and post-column flow splitting) are compared according to their ability to give both true and accurate results for pesticide determination in complicated matrices such as onion and garlic. In order to provide a quantitative comparison we use a measure of accuracy that would account for both average trueness and scatter of the results. Extrapolative dilution and standard addition were found to give results statistically insignificantly different from the correct values. In addition extrapolative dilution – a hybrid approach for both reducing and correcting for matrix effects – was found to result in the highest accuracy of the measurements.

Ensuring repeatability and robustness of poly(glycidyl methacrylate-co-ethylene dimethacrylate) HPLC monolithic columns of 3 mm id through covalent bonding to the column wall

Asko Laaniste, Anneli Kruve and Ivo Leito

J Sep Sci 2013, 15(36), 2458-2463

DOI: 10.1002/jssc.201300133

Two different methods to reinforce the poly(glycidyl methacrylate-co-ethylene dimethacrylate) HPLC monolithic columns of 3 mm id in a glass column reservoir were studied: composite columns with polymeric particles in the monolith and surface treatment of the reservoir wall. Of the two methods used to counter the mechanical instability and formation of flow channels (composite columns and column wall surface treatment), we demonstrated that proper column wall surface treatment was sufficient to solve both problems. Our study also indicated that no surface treatment is efficient, and of the methods studied silanization in acidified ethanol solution and constant renewal of the reaction mixture (dynamic mode) proved to be the most effective. As a result of this study, we have been able to prepare repeatable and durable methacrylate HPLC columns with good efficiencies.

Enhanced Nebulization Efficiency of Electrospray Mass Spectrometry: Improved Sensitivity and Detection Limit

Anneli Kruve, Ivo Leito, Koit Herodes, Asko Laaniste and Rünno Lõhmus

J Am. Soc. Mass Specrom. 2012, 12(23), 2051-2054.

DOI: 10.1007/s13361-012-0475-y

A novel electrospray nebulizer has been designed, which includes an additional nebulization gas capillary inside the liquid capillary. This design offers significantly enhanced ionization efficiency compared with the classic nebulizer design and leads to improved sensitivity (by three to 10 times) and decreases the detection limit, on an average 10 times. We see these results as the first step in the design of ESI nebulizers offering improved sensitivity and higher robustness. Possible future developments would include optimization of the dimensions of the capillaries as well as testing the nebulizer for other matrices and analytes.