pH Effects on Electrospray Ionization Efficiency

Matrix effect evaluation using multi-component post-column infusion in untargeted hydrophilic interaction liquid chromatography-mass spectrometry plasma metabolomics

Metabolomics based on hydrophilic interaction liquid chromatography (HILIC) coupled with mass spectrometry (MS) is a powerful tool for polar metabolite identification and quantification to further contribute to biomarker discovery and disease mechanism elucidation. However, matrix effect (ME), which may lead to altered ionization efficiency due to co-eluting compounds, is a significant challenge during biological analysis. Therefore, ME evaluation plays a crucial role during method development. Two approaches to evaluate ME are using stable isotope labelled-internal standards (SIL-IS) and post-column infusion (PCI) of standards. In this study, we developed an untargeted HILIC-MS method by applying four PCI standards for ME evaluation. We found PCI is a compelling approach for ME assessment compared to SIL-IS method due to its advantage in untargeted analysis. Through the ME evaluation and chromatographic performance comparison of 18 SIL standards across three columns and three different mobile phase pH conditions, our findings revealed that the BEH-Z-HILIC column operated at pH 4 with 10 mM ammonium formate exhibited minimal ME and superior performance. The method showed exceptional linearity (R² > 0.98), reliable repeatability (RSD < 15 %), good inter-day precision (RSD < 30 %), and acceptable recovery (>75 %) for all SIL standards. Absolute matrix effect (AME) and relative matrix effect (RME) assessment in three plasma donors revealed a high consistency between PCI and SIL-IS approaches. Finally, this method coupled with the PCI approach was applied to 40 plasma samples. Fifty endogenous compounds were detected and their AME and RME were evaluated. Results showed that many compounds experienced severe ion suppression, though their ME variation between 40 samples is low. In conclusion, PCI method is a robust alternative for monitoring ME and evaluating ME of endogenous compounds during untargeted method optimization and biological analysis.

Comprehensive LC-MS/MS analysis of nitrogen-related plant metabolites

We have developed and validated a novel LC-MS/MS method for simultaneously analyzing amino acids, biogenic amines, and their acetylated and methylated derivatives in plants. This method involves a one-step extraction of 2-5 mg of lyophilized plant material followed by fractionation of different biogenic amine forms, and exploits an efficient combination of hydrophilic interaction liquid chromatography (HILIC), reversed phase (RP) chromatography with pre-column derivatization, and tandem mass spectrometry (MS). This approach enables high-throughput processing of plant samples, significantly reducing the time needed for analysis and its cost. We also present a new synthetic route for deuterium-labeled polyamines. The LC-MS/MS method was rigorously validated by quantifying levels of nitrogen-related metabolites in seedlings of seven plant species, including Arabidopsis, maize, and barley, all of which are commonly used model organisms in plant science research. Our results revealed substantial variations in the abundance of these metabolites between species, developmental stages, and growth conditions, particularly for the acetylated and methylated derivatives and the various polyamine fractions. However, the biological relevance of these plant metabolites is currently unclear. Overall, this work contributes significantly to plant science by providing a powerful analytical tool and setting the stage for future investigations into the functions of these nitrogen-related metabolites in plants.

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

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.

Native Mass Spectrometric Insights into the Formation and Stability of DNA Triplexes

Deoxyribonucleic acid is a genetic biomacromolecule that contains the inherited information required to build and maintain a living organism. While the canonical duplex DNA structure is rigorously characterized, the structure and function of higher order DNA structures such as DNA triplexes are comparatively poorly understood. Previous literature has shown that these triplexes can form under physiological conditions, and native mass spectrometry offers a useful platform to study their formation and stability. However, experimental conditions including buffer salt concentration, pH, and instrumentation parameters such as ion mode can confound analysis by impacting the amount of triplex observed by mass spectrometry. Using model 30mer Y-type triplex sequences, we demonstrate the influence a range of experimental variables have on the detection of DNA triplex structures, informing suitable conditions for the study. When carefully considered conditions are used, mass spectrometry offers a powerful complementary tool for the analysis of higher order DNA assemblies.

Quantitative Nontarget Analysis of CECs in Environmental Samples Can Be Improved by Considering All Mass Adducts

Quantitative nontarget analysis (qNTA) for liquid chromatography coupled to high-resolution mass spectrometry enables a more comprehensive assessment of environmental samples. Previous studies have shown that correlations between a compound's ionization efficiency and a range of molecular descriptors can predict the compound's concentration within a factor of 5. In this study, the qNTA approach was further improved by considering all mass adducts instead of only the protonated ion. The model was based on a quantitative structure-property relationship (QSPR), including 216 contaminants of emerging concern (CECs), of which 80 exhibited adduct formation that accounted for >10% of the total peak intensity. When all mass adducts were included, the test set coefficient of determination improved to Q2 = 0.855 compared to Q2 = 0.670 when only the protonated ions were considered (test set median RF error factor 1.6). The inclusion of all adducts was also important to transfer the RF QSPR model reliably. It was assumed that RF variations are sequence-dependent; therefore, a second QSPR model for the prediction of the transferability factor was built for each sequence. For validation, samples were analyzed up to two years apart. The median prediction fold change was 1.74 for analytical standards (63 compounds) and 2.4 for enriched wastewater effluent samples (41 compounds), with 80% of the compounds predicted within a fold change of 2.4 and 3.3, respectively. The model was also validated on a second instrument, where 80% of the 26 compounds in wastewater effluent were predicted within a factor of 3.8.

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

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

Quantitative Analytical and Computational Workflow for Large-Scale Targeted Plasma Metabolomics

Quantifying metabolites from various biological samples is necessary for the clinical and biomedical translation of metabolomics research. One of the ongoing challenges in biomedical metabolomics studies is the large-scale quantification of targeted metabolites, mainly due to the complexity of biological sample matrices. Furthermore, in LC-MS analysis, the response of compounds is influenced by their physicochemical properties, chromatographic conditions, eluent composition, sample preparation, type of MS ionization source, and analyzer used. To facilitate large-scale metabolite quantification, we evaluated the relative response factor (RRF) approach combined with an integrated analytical and computational workflow. This approach considers a compound's individual response in LC-MS analysis relative to that of a non-endogenous reference compound to correct matrix effects. We created a quantitative LC-MS library using the Skyline/Panorama web platform for data processing and public sharing of data. In this study, we developed and validated a metabolomics method for over 280 standard metabolites and quantified over 90 metabolites. The RRF quantification was validated and compared with conventional external calibration approaches as well as literature reports. The Skyline software environment was adapted for processing such metabolomics data, and the results are shared as a "quantitative chromatogram library" with the Panorama web application. This new workflow was found to be suitable for large-scale quantification of metabolites in human plasma samples. In conclusion, we report a novel quantitative chromatogram library with a targeted data analysis workflow for biomedical metabolomic applications.

Predicting liquid chromatography-electrospray ionization/mass spectrometry signal from the structure of model compounds and experimental factors; case study of aripiprazole and its impurities

A priori estimation of analyte response is crucial for the efficient development of liquid chromatography-electrospray ionization/mass spectrometry (LC-ESI/MS) methods, but remains a demanding task given the lack of knowledge about the factors affecting the experimental outcome. In this research, we address the challenge of discovering the interactive relationship between signal response and structural properties, method parameters and solvent-related descriptors throughout an approach featuring quantitative structure-property relationship (QSPR) and design of experiments (DoE). To systematically investigate the experimental domain within which QSPR prediction should be undertaken, we varied LC and instrumental factors according to the Box-Behnken DoE scheme. Seven compounds, including aripiprazole and its impurities, were subjected to 57 different experimental conditions, resulting in 399 LC-ESI/MS data endpoints. To obtain a more standard distribution of the measured response, the peak areas were log-transformed before modeling. QSPR predictions were made using features selected by Genetic Algorithm (GA) and providing Gradient Boosted Trees (GBT) with training data. Proposed model showed satisfactory performance on test data with a RMSEP of 1.57 % and a of 96.48 %. This is the first QSPR study in LC-ESI/MS that provided a holistic overview of the analyte's response behavior across the experimental and chemical space. Since intramolecular electronic effects and molecular size were given great importance, the GA-GBT model improved the understanding of signal response generation of model compounds. It also highlighted the need to fine-tune the parameters affecting desolvation and droplet charging efficiency.

Ion suppression, reduced long-term robustness and leakage current of the spray voltage during the ionization of trichloroacetic acid; a case study with a methylmalonic acid assay

Sample clean-up with the protein precipitation solvent trichloroacetic acid (TCA), combined with a stable isotope labeled internal standard, is widely used for the analysis of endogenous and exogenous compounds in serum and plasma with liquid chromatography-tandem mass spectrometry (LC-MS/MS). During the application of an assay for methylmalonic acid (MMA), used for routine analysis in patient care, negative long-term side effects of TCA on assay performance were observed. Step-by-step extensive troubleshooting disclosed the limitations of using TCA in MS. After running over 2000 samples with the MMA assay over a course of one year, a black coating formed between the probe and the heater that was traced to the use of TCA. The MMA assay used a C18 column with an isocratic eluent of 95% water (0.1% formic acid) as starting condition, on which TCA was more retained than MMA. Next, concentrations of 2.2% TCA in the prepared serum or plasma sample caused a drop in spray voltage during ionization into the MS. This was caused by the strong acid properties of TCA, resulting in current loss of the spray voltage between the heated electrospray ionization (HESI) needle and the union holder, which had also a grounding function. Replacing the original metal HESI needle with a custom made fussed silica HESI needle or detaching the union from the union holder, eliminated the effect of the drop in spray voltage. In conclusion, TCA can seriously affect the long-term robustness by affecting the source of the MS. We recommend the use of a very low sample injection volume, and/or shifting the mobile phase to waste when TCA is eluting, when using TCA in LC-MS/MS analysis.

Supercritical Fluid Nanospray Mass Spectrometry: II. Effects on Ionization

Nanospraying supercritical fluids coupled to a mass spectrometer (nSF-MS) using a 90% supercritical fluid CO₂ carrier (sCO₂) has shown an enhanced desolvation compared to traditional liquid eluents. Capillaries of 25, 50, and 75 μm internal diameter (i.d.) with pulled emitter tips provided high MS detection sensitivity. Presented here is an evaluation of the effect of proton affinity, hydrophobicity, and nanoemitter tip size on the nSF-MS signal. This was done using a set of primary, secondary, tertiary, and quaternary amines with butyl, hexyl, octyl, and decyl chains as analytes. Each amine class was analyzed individually to evaluate hydrophobicity and proton affinity effects on signal intensity. The system has shown a mass sensitive detection on a linear dynamic range of 0.1-100 μM. Results indicate that hydrophobicity has a larger effect on the signal response than proton affinity. Nanospraying a mixture of all amine classes using the 75 μm emitter has shown a quaternary amine signal not suppressed by competing analytes. Competing ionization was observed for primary, secondary, and tertiary amines. The 75 and 50 μm emitters demonstrated increased signal with increasing hydrophobicity. Surprisingly, the 25 μm i.d. emitter yielded a signal decrease as the alkyl chain length increased, contrary to conventional understanding. Nanospraying the evaporative fluid in a sub-500 nm emitter likely resulted in differences in the ionization mechanism. Results suggest that 90% sCO₂ with 9.99% methanol and 0.01% formic acid yielded fast desolvation, high ionization efficiency, and low matrix effect, which could benefit complex biological matrix analysis.

Understanding mobile phase buffer composition and chemical structure effects on electrospray ionization mass spectrometry response

Mobile phase selection is of critical importance in liquid chromatography - mass spectrometry (LC-MS) based studies, since it affects retention, chromatographic selectivity, ionization, limits of detection and quantification, and linear dynamic range. Generalized LC-MS mobile phase selection criteria, suitable for a broad class of chemical compounds, do not exist thus far. Here we have performed a large-scale qualitative assessment of the effect of solvent composition used for reversed-phase LC separations on electrospray ionization (ESI) response for 240 small molecular weight drugs, representing various chemical compound classes. Of these 240 analytes 224 were detectable using ESI. The main chemical structural features affecting ESI response were found to all be surface area or surface charge-related. Mobile phase composition was found to be less differentiating, although for some compounds a pH effect was noted. Unsurprisingly, chemical structure was found to be the dominant factor for ESI response for the majority of the investigated analytes, representing about 85% of the replicating detectable complement of the sample data set. A weak correlation between ESI response and structure complexity was observed. Solvents based on isopropanol, and those containing phosphoric or di- and trifluoracetic acids, performed relatively poorly in terms of chromatographic or ESI response, whilst the best performing 'generic' LC solvents were based on methanol, acetonitrile using formic acid and ammonium acetate as buffer components, consistent with current practice in many laboratories.

Rapid Quantitative Analysis of Metabolites in Kimchi Using LC-Q-Orbitrap MS

Kimchi is a traditional Korean salted spontaneous lactic acid bacteria (LAB)-fermented food made using various vegetables. Organic acids, free sugars, and amino acids are key metabolites produced during LAB fermentation that determine the taste and quality of kimchi. However, each metabolite is typically analyzed using an independent analytical method, which is time-consuming and expensive. Therefore, in this study, we developed a method based on LC-Q-Orbitrap MS using which 20 types of representative fermented kimchi metabolites were selected and simultaneously analyzed within 10 min. The established method was validated, and its detection and quantification limits, linearity, precision, and accuracy were found to satisfy the Association of Official Agricultural Chemists (AOAC) validation guidelines. The 20 metabolites were simultaneously extracted from kimchi with different degrees of fermentation and quantitatively analyzed using LC-Q-Orbitrap MS. These results were analyzed using linear discriminant analysis and heat mapping, and the metabolites were grouped into early, middle, and late stages of fermentation. Malic acid (6.518-7.701 mMol) was only present in the initial stage of fermentation, and l-phenylalanine rapidly increased from the middle stage (2.180 mMol) to late stage (4.770 mMol). Lactic acid, which is representative of the sour taste of kimchi, was detected in the middle stage and increased rapidly up to 74.452 mMol in the late stage. In summary, in this study, 20 major kimchi metabolites were accurately analyzed within 10 min and grouped based on the degree of fermentation. Therefore, the method established in this study accurately and rapidly provides information on kimchi consumption and fermentation that could be highly valuable to the kimchi industry and kimchi consumers.

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

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

Non-Targeted Chemical Characterization of JUUL-Menthol-Flavored Aerosols Using Liquid and Gas Chromatography

The aerosol constituents generated from JUUL Menthol pods with 3.0% and 5.0% nicotine by weight (Me3 and Me5) are characterized by a non-targeted approach, which was developed to detect aerosol constituents that are not known to be present beforehand or that may be measured with targeted methods. Three replicates from three production batches (n = 9) were aerosolized using two puffing regimens (intense and non-intense). Each of the 18 samples were analyzed by gas chromatography electron ionization mass spectrometry and by liquid chromatography electrospray ionization high-resolving power mass spectrometry. All chemical constituents determined to differ from control were identified and semi-quantified. To have a complete understanding of the aerosol constituents and chemistry, each chemical constituent was categorized into one of five groups: (1) flavorants, (2) harmful and potentially harmful constituents, (3) leachables, (4) reaction products, and (5) chemical constituents that were unable to be identified or rationalized (e.g., chemical constituents that could not be categorized in groups (1–4). Under intense puffing, 74 chemical constituents were identified in Me3 aerosols and 68 under non-intense puffing, with 53 chemical constituents common between both regimens. Eighty-three chemical constituents were identified in Me5 aerosol using an intense puffing regimen and seventy-five with a non-intense puffing regimen, with sixty-two chemical constituents in common. Excluding primary constituents, reaction products accounted for the greatest number of chemical constituents (approximately 60% in all cases, ranging from about 0.05% to 0.1% by mass), and flavorants—excluding menthol—comprised the second largest number of chemical constituents (approximately 25%, ranging consistently around 0.01% by mass). The chemical constituents detected in JUUL aerosols were then compared to known constituents from cigarette smoke to determine the relative chemical complexities and commonalities/differences between the two. This revealed (1) a substantial decrease in the chemical complexity of JUUL aerosols vs. cigarette smoke and (2) that there are between 55 (Me3) and 61 (Me5) unique chemical constituents in JUUL aerosols not reported in cigarette smoke. Understanding the chemical complexity of JUUL aerosols is important because the health effects of combustible cigarette smoke are related to the combined effect of these chemical constituents through multiple mechanisms, not just the effects of any single smoke constituent.

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

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

In a pursuit of optimal glycan fluorescent label for negative MS mode for high-throughput N-glycan analysis

Over the past few decades, essential role of glycosylation in protein functioning has become widely recognized, rapidly advancing glycan analysis techniques. Because free glycan’s lack chromophore or fluorophore properties, and do not ionize well, they are often derivatized to facilitate their separation or detection, and to enhance the sensitivity of the analysis. Released glycan’s are usually derivatized using a fluorescent tag, which enables their optical detection in LC profiling. Some fluorescent labels can also promote ionization efficiency, thus facilitating MS detection. For this reason, there is a need to design fluorophores that will contribute more to the fluorescence and ionization of glycan’s and the need to quantify these contributions to improve glycan analysis methods. In this paper we focused on negative MS mode as these methods are more informative than methods involving positive MS mode, allowing for a less ambiguous elucidation of detailed glycan structures. Additionally, traditional glycan labels in negative mode MS usually result with diminished sensitivity compared to positive mode, thus making selection of appropriate label even more important for successful high-throughput analysis. Therefore, eleven fluorescent labels of different chemo-physical properties were chosen to study the influence of label hydrophobicity and presence of a negative charge on glycan ionization in negative MS mode. N-glycans released from IgG sample were labeled with one of the eleven labels, purified with HILIC-SPE and analyzed with HILIC-UPLC-FLR-MS. To make evaluation of studied labels performance more objective, analysis was performed in two laboratories and at two mobile phase pH (4.4 and 7.4). Although there was a notable trend of more hydrophobic labels having bigger signal intensities in one laboratory, we observed no such trend in the other laboratory. The results show that MS parameters and intrinsic configuration of the spectrometer have even bigger effect on the final ESI response of the labeled-glycan ionization in negative MS mode that the labels themselves. With this in mind, further research and development of fluorophores that will be suitable for high-throughput glycan analysis in the negative MS mode are proposed.

Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry: A Strategy for Optimization, Characterization, and Quantification of Antioxidant Nitro Derivatives

As an antioxidant, N-phenyl-β-naphthylamine (PBNA) inhibits the activity of oxidants, such as NO _x , to prevent the degradation of energetic materials. In the presence of NO _x , nitrated products can be generated in the process potentially. To characterize nitrated PBNA in a nontargeted analysis of complex samples as such, liquid chromatography tandem quadrupole time-of-flight (LC-QTOF), as an excellent analytic technique, is used due to its high resolution and sensitivity. However, a systematic approach of instrumentation optimization, data interpretation, and quantitative determination of products is needed. Through a step-by-step evaluation of the instrumental parameters used in the Q0, Q1, and Q2 compartments of LC-QTOF, optimal ion yields of precursor ions and high-resolution MS² fragmentation spectra at low mass defects were obtained in both negative and positive electrospray ionization modes. Through rationalization of the fragmentation pathways and verification using theoretical masses, the mononitro derivative of PBNA was accurately identified as N-(4-nitrophenyl)-naphthalen-2-amine and further confirmed using a reference standard. Using strict criteria provided by the analytical guidelines (e.g., SANTE), limit of quantitation, limit of detection, and calibration were established for the quantitation of PBNA and nitrated PBNA. From optimization to characterization and subsequent quantification of the mononitro-PBNA derivative, for the first time, the applicability of this strategy is demonstrated in the aged energetic binders.

Detection of Biosignatures by Capillary Electrophoresis Mass Spectrometry in the Presence of Salts Relevant to Ocean Worlds Missions

Capillary electrophoresis (CE) is a promising liquid-based technique for in situ chemical analysis on ocean worlds that allows the detection of a wide range of organic molecules relevant to the search for life. CE coupled with mass spectrometry (MS) is particularly valuable as it also enables the discovery of unknown compounds. Here we demonstrate that CE coupled to MS via electrospray ionization (ESI) can readily analyze samples containing up to half the saturation levels of salts relevant to ocean worlds when using 5 M acetic acid as the separation media. A mixture containing amino acids, peptides, nucleobases, and nucleosides was analyzed in the presence of two salts, NaCl and MgSO₄, based on their relevance to Europa and Enceladus. We demonstrate here CE-MS limits of detection for these organics ranging from 0.05 to 1 μM (8 to 89 ppb) in the absence of salts. More importantly, we demonstrate here for the first time that organics in the low micromolar range (1-50 μM) are detected by CE-MS in the presence of 3 M NaCl without desalting, preconcentration, or derivatization. This demonstration highlights how CE-MS is uniquely suited for organic analysis on future missions to ocean worlds.

Metabolite Profiling of Soy By-Products: A Comprehensive Approach

Soy is the major oilseed crop as soybeans are widely used to produce biofuel, food, and feed. Other parts of the plant are left on the ground after harvest. The accumulation of such by-products on the soil can cause environmental problems. This work presents for the first time a comprehensive metabolite profiling of soy by-products collected directly from the ground just after mechanical harvesting. A two-liquid-phase extraction using n-heptane and EtOH-H2O 7:3 (v/v) provided extracts with complete characterization by gas chromatography and ultra-high-performance liquid chromatography both coupled to time-of-flight mass spectrometry. A total of 146 metabolites, including flavones, flavonols, isoflavonoids, fatty acids, steroids, mono-, sesqui-, di-, and triterpenoids, were tentatively identified in soy by-products and soybeans. These proved to be sources of a wide range of bioactive metabolites, thus suggesting that they could be valorized while reducing potential environmental damage in line with a circular economy model.

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

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

Review of the Use of Liquid Chromatography-Tandem Mass Spectrometry in Clinical Laboratories: Part I-Development

The process of method development for a diagnostic assay based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) involves several disparate technologies and specialties. Additionally, method development details are typically not disclosed in journal publications. Method developers may need to search widely for pertinent information on their assay(s). This review summarizes the current practices and procedures in method development. Additionally, it probes aspects of method development that are generally not discussed, such as how exactly to calibrate an assay or where to place quality controls, using examples from the literature. This review intends to provide a comprehensive resource and induce critical thinking around the experiments for and execution of developing a clinically meaningful LC-MS/MS assay.

Development and validation of a quantitative method for 15 antiviral drugs in poultry muscle using liquid chromatography coupled to tandem mass spectrometry

The objective of this work was to develop a quantitative multi-residue method for analysing antiviral drug residues and their metabolites in poultry meat samples. Antiviral drugs are not licensed for the treatment of influenza in food producing animals. However, there have been some reports indicating their illegal use in poultry. In this study, a method was developed for the analysis of 15 antiviral drug residues in poultry muscle (chicken, duck, quail and turkey) using liquid chromatography coupled to tandem mass spectrometry. This included 13 drugs against influenza and associated metabolites, but also two drugs employed for the treatment of herpes (acyclovir and ganciclovir). The method required the development of a novel chromatographic separation using a hydrophilic interaction chromatographic (HILIC) BEH amide column, which was necessary to retain the highly polar compounds. The analytes were detected using a triple quadrupole mass spectrometer operating in positive electrospray ionization mode. A range of different sample preparation protocols suitable for polar compounds were evaluated. The most effective procedure was based on a simple acetonitrile-based protein precipitation step followed by a further dilution in a methanol/water solution. The confirmatory method was validated according to the EU 2021/808 guidelines on different species including chicken, duck, turkey and quail. The validation was performed using various calibration curves ranging from 0.1 µg kg^-1to 200 µg kg^-1, according to the analyte. Depending on the analyte sensitivity, decision limits achieved ranged from 0.12 µg kg^-1 for arbidol to 34.7 µg kg^-1 for ribavirin. Overall, the reproducibility precision values ranged from 2.8% to 22.7% and the recoveries from 84% to 127%. The method was applied to 120 commercial poultry samples from the Irish market, which were all found to be residue-free.

Quantitative electrospray ionization efficiency scale: 10 years after

RATIONALE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Microsampling with a Solid-Phase Extraction Cartridge: Storage and Online Mass Spectrometry Analysis

This study aims to introduce the concept of utilizing a solid-phase extraction (SPE) cartridge for remote biofluid collection, followed by direct sample analysis at a later time. For this, a dried matrix spot was prepared in a syringe, in the form of SPE cartridge for the first time to enable small biofluid collection (microsampling), storage, shipment, and online electrospray ionization (ESI) mass spectrometry (MS) analysis of the stored dried samples. The SPE sorbents were packed into an ESI syringe and the resultant cartridge was used for sampling small volumes (<20 μL) of different complex biological fluids including blood, plasma, serum, and urine. The collected sample was stored in the dry state within the confinement of the SPE sorbent at room temperature, and analyte stability (e.g., diazepam) was maintained for more than a year. Direct coupling of the SPE cartridge to MS provides excellent accuracy, precision, and sensitivity for analyzing illicit drugs present in the biofluid. The corresponding mechanism of wrong-way positive ion generation from highly basic elution solvents was explored. Without chromatography, our direct SPE-ESI-MS analysis technique afforded detection limits as low as 26 and 140 pg/mL for raw urine and untreated plasma, respectively. These promising results proved that the new syringe-based SPE cartridge can serve as a good alternative to conventional microsampling techniques in terms of analyte stability, ease of operation and versatility, and analytical sensitivity and speed.

Bioanalytical strategies in drug discovery and development

A reliable, rapid, and effective bioanalytical method is essential for the determination of the pharmacokinetic, pharmacodynamic, and toxicokinetic parameters that inform the safety and efficacy profile of investigational drugs. The overall goal of bioanalytical method development is to elucidate the procedure and operating conditions under which a method can sufficiently extract, qualify, and/or quantify the analyte(s) of interest and/or their metabolites for the intended purpose. Given the difference in the physicochemical properties of small and large molecule drugs, different strategies need to be adopted for the development of an effective and efficient bioanalytical method. Herein, we provide an overview of different sample preparation strategies, analytical platforms, as well as procedures for achieving high throughput for bioanalysis of small and large molecule drugs.

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

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

Direct Liquid Extraction and Ionization Techniques for Understanding Multimolecular Environments in Biological Systems (Secondary Publication)

A combination of direct liquid extraction using a small volume of solvent and electrospray ionization allows the rapid measurement of complex chemical components in biological samples and visualization of their distribution in tissue sections. This review describes the development of such techniques and their application to biological research since the first reports in the early 2000s. An overview of electrospray ionization, ion suppression in samples, and the acceleration of specific chemical reactions in charged droplets is also presented. Potential future applications for visualizing multimolecular environments in biological systems are discussed.

Hand-Held Diode Laser for On-Site Analysis Using Transportable Mass Spectrometry

A hand-held laser diode thermal desorption electrospray ionization (LDTD-ESI) mass spectrometry (MS) method was developed for rapid screening of illegal substances in solid samples. To achieve that, a simple, inexpensive, battery-powered surgical laser diode at 940 nm was employed to ablate the solid samples. The potential of using a black polytetrafluoroethylene substrate to enhance the analytes’ desorption to the gas phase was investigated and demonstrated. Among the optimized ESI parameters, the solvent (methanol/water, 50:50, v/v) and the flow rate (50 μL h^–1) were critical to obtain the best sensitivity. The applicability was demonstrated for the rapid identification of selective androgen receptor modulators (SARMs) in pills and powders based on accurate mass measurements by time-of-flight MS. Also, the hand-held LDTD-ESI was combined with a transportable single quadrupole MS. The same SARMs samples were analyzed, and identifications were based on in-source cone voltage fragmentation patterns observed. These initial results demonstrate the applicability of the developed simplified LDTD-ESI MS method for future on-site testing of organic compounds in solid samples.

Mapping the plant proteome: tools for surveying coordinating pathways

Plants rapidly respond to environmental fluctuations through coordinated, multi-scalar regulation, enabling complex reactions despite their inherently sessile nature. In particular, protein post-translational signaling and protein-protein interactions combine to manipulate cellular responses and regulate plant homeostasis with precise temporal and spatial control. Understanding these proteomic networks are essential to addressing ongoing global crises, including those of food security, rising global temperatures, and the need for renewable materials and fuels. Technological advances in mass spectrometry-based proteomics are enabling investigations of unprecedented depth, and are increasingly being optimized for and applied to plant systems. This review highlights recent advances in plant proteomics, with an emphasis on spatially and temporally resolved analysis of post-translational modifications and protein interactions. It also details the necessity for generation of a comprehensive plant cell atlas while highlighting recent accomplishments within the field.

Protein-induced conformational change in glycans decreases the resolution of glycoproteins in hydrophilic interaction liquid chromatography

An understanding of why hydrophilic interaction liquid chromatography gives a higher resolution for glycans than for glycoproteins would facilitate column improvements. Separations of the glycoforms of ribonuclease B compared to its released glycans were studied using a commercial hydrophilic interaction liquid chromatography column. The findings were used to devise a new hydrophilic interaction liquid chromatography column. For the commercial column, chromatograms and van Deemter plots showed that selectivity and efficiency are comparable factors in the higher resolution of the released glycans. The higher selectivity for the released glycans was associated with more water molecules displaced per added mannose. To investigate why, three-dimensional structures of the glycoprotein and the glycan were computed under chromatographic conditions. These showed that hydrogen bonding within the free glycan makes its topology more planar, which would increase contact with the bonded phase. The protein sterically blocks the hydrogen bonding. The more globular-shaped glycan of the glycoprotein suggests that a thicker bonded phase might improve selectivity. This was tested by making a column with a copolymer bonded phase. The results confirmed that selectivity is increased. The findings are possibly broadly relevant to glycoprotein analysis since the structural motif involved in internal hydrogen bonding is common to N-linked glycans of human glycoproteins.

Highly Sensitive Determination of Amino Acids by LC-MS under Neutral Conditions

Peptide drug leads possess unusual structural features that allow them to exert their unique biological activities and ideal physicochemical properties. In particular, these peptides often have D-amino acids, and therefore the absolute configurations of the component amino acids have to be elucidated during the structural determination of newly isolated peptide drug leads. Recently, we developed the highly sensitive labeling reagents D/L-FDVDA and D/L-FDLDA for the structural determination of the component amino acids in peptides. In an LC-MS-based structural study of peptides, these reagents enabled us to detect infinitesimal amounts of amino acids derived from mild degradative analysis of the samples. Herein, we firstly report the improved LC-MS protocols for the highly sensitive analyses of amino acids. Second, two new labeling reagents were synthesized and their detection sensitivities evaluated. These studies increase our understanding of the structural basis of these highly sensitive labeling reagents, and should provide opportunities for future on-demand structural modifications of the reagents to enhance their hydrophobicity, stability, and affinity for applications to specialized HPLC columns.

One step extraction followed by HPLC-ESI-MS/MS for multi-residue analysis of diacylhydrazine insecticides in water, sediment, and aquatic products

A multi-residue analysis of six diacylhydrazine insecticides in water, sediment, and aquatic products was established by liquid chromatography triple quadrupole tandem mass spectrometry (LC-MS/MS). The water sample was extracted with acetonitrile by low-temperature enrichment liquid-liquid extraction technology. The sediment and aquatic products were prepared using QuEChERS technique. Method validation showed perfect linearity with correlation coefficients (R) more than 0.9992 for all insecticides, and the matrix effects were nearly negligible (-1.42% to -0.27%) for water, sediment and aquatic products. The recoveries were 80.0-99.7% at three spiked levels (0.02 ng·mL^-1, 0.1 ng·mL^-1, 0.5 ng·mL^-1; 2.0, 10, and 50 ng·g^-1) and the precisions (intra-day and inter-day precision) were lower than 5.28%, with the low LODs (3.8 ~ 9.6 pg·mL^-1; 0.38-0.96 ng·g^-1) and LOQs (12.7 ~ 32.0 pg·mL^-1; 1.27-3.20 ng·g^-1) for water, sediment, and aquatic products, indicating the good accuracy and precision of the proposed method. The applicability, efficiency, and sensitivity of this method have been proved in the analysis of six diacylhydrazine insecticides in water, sediment, and crucian carp in Rice- crucian carp - integrated planting system.

Physicochemical Property Correlations with Ionization Efficiency in Capillary Vibrating Sharp-Edge Spray Ionization (cVSSI)

The relative contributions to ionization efficiency by three molecular chemical properties have been examined for field-free and field-enabled capillary vibrating sharp-edge spray ionization (cVSSI) using mass spectrometry (MS) analysis. Ion intensities have been recorded for model compounds under each operational ionization mode as well as for aqueous and nonaqueous (methanol) solvent systems. Multiple regression analysis suggests that for field-free cVSSI, ion intensity is mostly associated with the log of the base dissociation constant (pK_b) and proton affinity (PA) for both aqueous and methanol solutions. Comparatively, for field-enabled cVSSI using aqueous solutions, the dominant factor correlated with ion intensity is the log of the partition coefficient (log P). To a lesser degree, this is observed for methanol solutions as well. For ESI, pK_b is the dominant factor associated with ion signal levels from methanol and aqueous solutions. These results are supported by studies conducted on two different mass spectrometers employing different cVSSI emitter tips. The relationship of ion intensity and pK_b in ESI is supported by multiple studies; however, the shift to other chemical properties with the addition of cVSSI suggests the possibility that a different (or combinations of) ionization mechanism(s) may be operative for these ionization modes. These results are briefly considered in light of the different ESI mechanisms.

A novel method to detect intracellular metabolite alterations in MCF-7 cells by doxorubicin induced cell death

BACKGROUND

Metabolic reprogramming within cancer cells has been recognized as a potential barrier to chemotherapy. Additionally, metabolic tumor heterogeneity is the one of factors behind discernible hallmarks such as drug resistance, relapse of the tumor and the formation of secondary tumors.

METHODS

In this paper, cell-based assays including PI/annexin V staining and immunoblot assay were performed to show the apoptotic cell death in MCF-7 cells treated with DOX. Further, MCF-7 cells were lysed in a hypotonic buffer and the whole cell lysate was purified by a novel and specifically designed metabolite (~ 100 to 1000 Da) fractionation system called vertical tube gel electrophoresis (VTGE). Further, purified intracellular metabolites were subjected to identification by LC-HRMS technique.

RESULTS

Cleaved PARP 1 in MCF-7 cells treated with DOX was observed in the present study. Concomitantly, data showed the absence of active caspase 3 in MCF-7 cells. Novel findings are to identify key intracellular metabolites assisted by VTGE system that include lipid (CDP-DG, phytosphingosine, dodecanamide), non-lipid (N-acetyl-D-glucosamine, N1-acetylspermidine and gamma-L-glutamyl-L-cysteine) and tripeptide metabolites in MCF-7 cells treated by DOX. Interestingly, we reported the first evidence of doxorubicinone, an aglycone form of DOX in MCF-7 cells that are potentially linked to the mechanism of cell death in MCF-7 cells.

CONCLUSION

This paper reported novel methods and processes that involve VTGE system based purification of hypotonically lysed novel intracellular metabolites of MCF-7 cells treated by DOX. Here, these identified intracellular metabolites corroborate to caspase 3 independent and mitochondria induced apoptotic cell death in MCF-7 cells. Finally, these findings validate a proof of concept on the applications of novel VTGE assisted purification and analysis of intracellular metabolites from various cell culture models.

Machine learning guided prediction of liquid chromatography-mass spectrometry ionization efficiency for genotoxic impurities in pharmaceutical products

The limitation and control of genotoxic impurities (GTIs) has continued to receive attention from pharmaceutical companies and authorities for several decades. Because GTIs have the ability to damage deoxyribonucleic acid (DNA) and the potential to cause cancer, low-level quantitation is required to protect patients. A quick and easy method of determining the liquid chromatography-mass spectrometry (LC/MS) conditions for high-sensitivity analysis of GTIs may prospectively accelerate pharmaceutical development. In this study, a quantitative structure-property relationship (QSPR) model was developed for predicting the ionization efficiency of compounds using liquid-chromatography-mass spectrometry (LC/MS) parameters and molecular descriptors. Before implementing the QSPR prediction model, linear regression analysis was performed to model the relationship between the ionization efficiency and the LC/MS parameters for each compound. Comparison of the predicted peak areas with the experimentally observed peak areas showed good agreement based on the coefficient of determination (R² > 0.96). The machine learning-based QSPR approach begins with computation of the molecular descriptors expressing the physicochemical properties of a compound, followed by a genetic algorithm-based feature selection. Linear and nonlinear regression were performed, and support vector machine (SVM) was selected as the best machine learning algorithm for the prediction. The SVM algorithm was developed and optimized using 1031 experimental data points for nine compounds, including well-known GTIs. Validation of the model by comparison of the predicted and observed relative ionization efficiencies (RIE) showed a high coefficient of determination (R² = 0.96) and low root mean squared error value (RMSE = 0.118). Finally, this established prediction model was applied to hydrophilic interaction liquid chromatography coupled with MS for a new compound in new mobile phase compositions and new MS parameter settings. The RMSE of the predicted versus observed RIE was 0.203. This prediction accuracy was sufficient to determine the starting point of the LC/MS method development. The methodology demonstrated in this study can be used to determine the LC/MS conditions for high sensitivity analysis of GTIs.

LC-MS/MS quantification of fat soluble vitamers - A systematic review

Fat soluble vitamers (FSV) are several biochemically diverse micronutrients essential for healthy development, growth, metabolism, and cell regulation. We cannot synthesize FSV completely or at the required concentrations. Deficiency or excess of FSV can result in many health problems. Plasma is the most accessible sample matrix for the quantification of FSV. However, due to its complexity and other analytical challenges (e.g., FSV sensitivity to light, oxygen, heat, pH, chemical heterogeneity, standard availability), developing a method for the simultaneous quantification of multiple FSV at physiological concentrations has been challenging. In this systematic review, we examine the parameters and criteria used in existing Liquid Chromatography with tandem Mass Spectrometry (LC-MS/MS) methods for FSV quantification to the extraction method, chromatographic resolution, matrix effects, and method validation as critical to a sensitive and robust method. We conclude that the final FSV method sensitivity is predominantly based on aforementioned criteria and future method development using LC-MS/MS will benefit from the application of this systematic review.

Enhanced Sensitivity for the Analysis of Perfluoroethercarboxylic Acids Using LC-ESI-MS/MS: Effects of Probe Position, Mobile Phase Additive, and Capillary Voltage

Perfluoroethercarboxylic acids (PFECAs) have recently emerged as replacements for toxic per- and polyfluorinated alkyl substances (PFAS) including perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS). Compared with other PFAS, many PFECAs including hexafluoropropylene oxide dimer acid (HFPO-DA, trade name GenX) exhibit poor sensitivity during analysis using liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) and are therefore often difficult to quantify. This study examined changes in ESI probe position, mobile phase additive, and capillary voltage with the goal of enhancing PFECA sensitivity. In addition, the relative contributions of existing mechanistic theories for PFAS ionization during ESI are discussed. Results indicated that the LC-ESI-MS/MS sensitivity for 9 PFECAs can be improved significantly by altering the ESI probe position. At the optimal probe position, lowering the capillary voltage from 2.0 to 0.5 kV universally enhanced the LC-ESI-MS/MS sensitivity for PFAS analysis. For most analytes, the use of ammonium bicarbonate rather than ammonium acetate as a mobile phase additive also enhanced the analytical response. These effects have not been previously reported and suggest that many laboratories may be conducting analyses of PFECAs under suboptimal conditions. Using the strategies outlined in this study, PFECAs can be more easily incorporated into comprehensive methods for PFAS analysis. Here, we describe analytical parameters that enhance the sensitivity for some PFECAs by up to 36-fold while maintaining high sensitivity for legacy PFAS. This work not only highlights solutions to mitigate inadequate PFECA sensitivity but also provides insight into the mechanisms underlying PFAS ionization efficiency during LC-ESI-MS/MS.

Undetectable Free Aromatic Amino Acids in Nails of Breast Carcinoma: Biomarker Discovery by a Novel Metabolite Purification VTGE System

Background: Metabolic reprogramming in breast cancer is depicted as a crucial change in the tumor microenvironment. Besides the molecular understanding of metabolic heterogeneity, appreciable attention is drawn to characterizing metabolite profiles in tumor tissue and derived biological fluids and tissue materials. Several findings reported on the metabolic alterations of free aromatic amino acids (FAAAs) and other metabolites in biological fluids. Furthermore, there is a significant gap in the development of a suitable method for the purification and analysis of metabolite biomarkers in nails of cancer patients. Methods: To address the metabolite alterations, specifically FAAA levels in nails, fingernail clippings of breast cancer patients (N = 10) and healthy subjects (N-12) were used for extraction and purification of metabolites. Here, we reported a novel and specifically designed vertical tube gel electrophoresis (VTGE) system that helped in the purification of metabolites in the range of 100-1,000 Da from nail materials. Here, the VTGE system uses 15% polyacrylamide under non-denaturing and non-reducing conditions, which makes eluted metabolites directly compatible with LC-HRMS and other analytical techniques. Qualitative and quantitative determination of FAAAs in nail lysates was done in positive ESI mode of the Agilent LC-HRMS platform. Results: The analysis on collected data of nail metabolites clearly suggested that FAAAs including tryptophan, tyrosine, phenylalanine, and histidine were undetectable in nail lysates of breast cancer over healthy subjects. This is a first report that showed highly reduced levels of FAAAs in nails of breast cancer patients. Furthermore, the present observation is in consonance with previous findings that showed cancer cachexia and high amino acid catabolism in breast cancer patients that drive metabolite-led cancer growth and proliferation. Conclusion: This paper provides a proof of concept for a novel and specifically developed VTGE process that showed first evidence on the undetectable level of FAAAs in nails of breast cancer patients as metabolite biomarkers. Here, the authors propose the potential use of a VTGE-assisted process to achieve metabolomic discovery in nails of breast cancer and other tumor types.

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

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

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

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

Methodology and validation of a new tandem mass spectrometer method for the quantification of inorganic and organic 18O-phosphate species

Phosphorus (P) fertilizers are crucial to achieve peak productivity in agricultural systems. However, the fate of P fertilizers via microorganism incorporation and the exchange processes between soil pools is not well understood. 18Oxygen-labelled phosphate (18O- Pi) can be tracked as it cycles through soil systems. Our study describes biological and geochemical P dynamics using a tandem mass spectrometry (MS/MS) method for the absolute quantification of 18O- Pi. Soil microcosms underwent three treatments: (i) 18O- Pi, (ii) unlabelled phosphate (16O- Pi) or (iii) Milli-Q control, dissolved in a bio-stimulatory solution. During a 6-week series the microcosms were sampled to measure P by Hedley sequential fractionation and DNA extraction samples digested to 3'-deoxynucleoside 5'-monophosphates (dNMP). A MS/MS attached to a HPLC analyzed each P-species through collision-induced dissociation. The resin-extractable and bicarbonate 18O- Pi and 16O- Pi fractions displayed similar precipitation and adsorption-desorption trends. Biotic activity measured in the NaOH and dNMP fractions rapidly delabelled 18O- Pi; however, the MS/MS measured some 18O that remained between the P backbone and deoxyribose sugars. After 6 weeks, the 18O- Pi had not reached the HCl soil pool, highlighting the long-term nature of P movement. Our methodology improves on previous isotopic tracking methods as endogenous P does not dilute the system, unlike 32P techniques, and measured total P is not a ratio, dissimilar from natural abundance techniques. Measuring 18O- Pi using MS/MS provides information to enhance land sustainability and stewardship practices regardless of soil type by understanding both the inorganic movement of P fertilizers and the dynamic P pool in microbial DNA.

Quantitative analysis of underivatized 17 β-estradiol using a high-throughput LC-MS/MS assay - Application to support a pharmacokinetic study in ovariectomized guinea pigs

Difference in female sex hormone, β-estradiol (E₂), levels can contribute to sex differences in biological processes that underlie target tissue functions (QT interval), vulnerability to diseases (hepatitis or HIV), and response toward therapies. Accurate quantification of plasma E₂ level is thus an important aspect in both basic science research examining hormone-regulated physiological mechanisms and in clinical settings to support patient care associated with altered E₂ levels. Due to lack of a high-throughput high-sensitivity analytical method, we developed and validated a LC-MS/MS assay for accurate low-level quantification of E₂ and demonstrated its application to a guinea pig pharmacokinetic study in which guinea pigs were treated with 10 or 40 μg/kg E₂ subcutaneously and blood samples collected at 0 (pre-dose), 0.25, 0.5, 1, 2, 4, 8, 12 and 24 h post-dosing. E₂ was extracted using 90 μL ovariectomized guinea pig plasma by liquid-liquid extraction. The method was robust, sensitive with linear range from 3.9 to 1000 pg/mL, and the assay met acceptance criteria for validation parameters listed in the current FDA Guidance on Bioanalytical Method Validation. Compared to the 10 μg/kg dose, more than dose proportional increase in maximum E₂ plasma concentration (C_max) and AUC_0-∞ and correspondingly longer half-life were observed after 40 μg/kg dose. This assay is a significant improvement over existing E₂ quantification methods in bioanalytical field, with high precision and accuracy, low sample and injection volumes, no derivatization, and short assay run time of 3 min. This assay is amenable in high-throughput settings requiring low-level E₂ quantitation in basic science research and clinical settings.

Comparative study of five different amine-derivatization methods for metabolite analyses by liquid chromatography-tandem mass spectrometry

Current metabolomics research utilizes liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses to handle biological samples that contain thousands of quantifiable metabolites. However, no LC-MS/MS condition is suitable for directly analyzing all metabolites. An alternative approach is to derivatize metabolites to impart desirable properties such as better chromatographic separation, enhanced ionization efficiency, or fluorescence detection. An important category of metabolites is amine-containing compounds, which includes amino acids, neurotransmitters, alkaloids, biogenic amines, etc. Various derivatization methods have been developed for amine groups, but few studies have compared their relative strengths and weaknesses. We chose Dansyl-Cl, o-phthalaldehyde (OPA), Fmoc-Cl, Dabsyl-Cl, and Marfey's reagent to systematically compare their reactivity, absorbance, fluorescence, chromatographic separation, and ionization efficiencies under three pH conditions-2.6, 5.0, and 8.0. Their MS/MS fragmentation patterns were also examined under different collision energies. Overall, Dansyl-Cl is a very versatile derivatization method, generating products with fluorescence and high ionization efficiency. Fmoc-Cl is similarly useful under highly acidic chromatography conditions. Dabsyl-Cl may be a good alternative at weakly acidic and weakly basic conditions. OPA is a versatile fluorogenic reagent and its chemistry may be fine-tuned by incorporating different thiol molecules. Marfey's reagent is suboptimal in general, but its chiral property is useful for the separation of enantiomers. All five were applied to the analyses of Coptis chinensis, a Chinese medical herb, identifying hundreds of amine-containing metabolites through MS/MS analyses. None of the five methods is clearly superior, and their compound coverage profiles are rather distinct. A combination of multiple derivatization reagents is required for comprehensive coverage. Our comparative data provide useful guidelines for designing more efficient metabolomics experiments for different analytical goals.

Simultaneous LC/MS Analysis of Carotenoids and Fat-Soluble Vitamins in Costa Rican Avocados (Persea americana Mill.)

Avocado (a fruit that represents a billion-dollar industry) has become a relevant crop in global trade. The benefits of eating avocados have also been thoroughly described as they contain important nutrients needed to ensure biological functions. For example, avocados contain considerable amounts of vitamins and other phytonutrients, such as carotenoids (e.g., β-carotene), which are fat-soluble. Hence, there is a need to assess accurately these types of compounds. Herein we describe a method that chromatographically separates commercial standard solutions containing both fat-soluble vitamins (vitamin A acetate and palmitate, Vitamin D₂ and D₃, vitamin K₁, α-, δ-, and γ-vitamin E isomers) and carotenoids (β-cryptoxanthin, zeaxanthin, lutein, β-carotene, and lycopene) effectively (i.e., analytical recoveries ranging from 80.43% to 117.02%, for vitamins, and from 43.80% to 108.63%). We optimized saponification conditions and settled at 80 °C using 1 mmol KOH L⁻¹ ethanol during 1 h. We used a non-aqueous gradient that included methanol and methyl tert-butyl ether (starting at an 80:20 ratio) and a C₃₀ chromatographic column to achieve analyte separation (in less than 40 min) and applied this method to avocado, a fruit that characteristically contains both types of compounds. We obtained a method with good linearity at the mid to low range of the mg L⁻¹ (determination coefficients 0.9006–0.9964). To determine both types of compounds in avocado, we developed and validated for the simultaneous analysis of carotenoids and fat-soluble vitamins based on liquid chromatography and single quadrupole mass detection (LC/MS). From actual avocado samples, we found relevant concentrations for cholecalciferol (ranging from 103.5 to 119.5), δ-tocopherol (ranging from 6.16 to 42.48), and lutein (ranging from 6.41 to 15.13 mg/100 g dry weight basis). Simmonds cultivar demonstrated the higher values for all analytes (ranging from 0.03 (zeaxanthin) to 119.5 (cholecalciferol) mg/100 g dry weight basis).

Influence of Solvent Composition and Surface Tension on the Signal Intensity of Amino Acids in Electrospray Ionization Mass Spectrometry

The influence of solvent composition and surface tension on the signal intensity of deprotonated molecules [M−H]⁻ in electrospray ionization mass spectrometry (ESI MS) was evaluated using alanine (Ala), threonine (Thr) and phenylalanine (Phe), which have differing levels of hydrophobicity. The surface tension of the ESI solution was varied by changing the ratio of the organic solvents methanol (MeOH) and acetonitrile (MeCN) in water (H₂O). In ESI MS, the signal intensity of all the amino acids was increased with decreasing surface tension for the two solutions, H₂O/MeOH and H₂O/MeCN. The use of H₂O/MeCN was more favorable for achieving a strong signal for the analytes compared to H₂O/MeOH. The smaller vaporization enthalpy of MeCN compared to MeOH was proposed as one of the most plausible explanation for this. The order of the signal intensity of amino acids was Phe>Thr>Ala, the same order as their hydrophobicity. It can be practically concluded that the use of solutions with lower surface tensions and lower vaporization enthalpies would result in higher signal intensities in ESI MS.

Reply to the 'Comment on "The chemical reactions in electrosprays of water do not always correspond to those at the pristine air-water interface"' by A. J. Colussi and S. Enami, Chem. Sci., 2019, , DOI: 10.1039/c9sc00991d

We explain why chemical reactions in/on electrosprays of water may not always represent those at the air–water interface. Thus, electrospray-based techniques cannot be relied upon as generalized “surface-specific” platforms for water.

The air–water interface serves as a crucial site for numerous chemical and physical processes in environmental science and engineering, such as cloud chemistry, ocean-atmosphere exchange, and wastewater treatment. The development of “surface-selective” techniques for probing interfacial properties of water therefore lies at the forefront of research in chemical science. Recently, researchers have adapted electrospray ionization mass spectrometry (ESIMS) to generate microdroplets of water to investigate interfacial phenomena at thermodynamic equilibrium. In contrast, using a broad set of experimental and theoretical techniques, we found that electrosprays of water could facilitate partially hydrated (gas-phase) ions (e.g., H₃O⁺·(H₂O)₂) to drive/catalyze chemical reactions that are otherwise not possible to accomplish by purely interfacial effects (e.g., enhanced water–hydrophobe surface area) (Chem. Sci., 2019, 10, 2566). Thus, techniques exploiting electrosprays of water cannot be relied upon as generalized surface-selective platforms. Here, we respond to the comments raised by Colussi & Enami (Chem. Sci., 2019, 10, DOI: ; 10.1039/c9sc00991d) on our paper.

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

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