bims-metlip 2024-09-08 papers

bims-metlip

Biomed News

on Methods and protocols in metabolomics and lipidomics

Issue of 2024‒09‒08
24 papers selected by
Sofia Costa, Matterworks

Novel sampling and gas-phase derivatization strategy: Proof-of-concept by profiling ionic polar metabolites using gas chromatography-mass spectrometry.
MSIGen: An Open-Source Python Package for Processing and Visualizing Mass Spectrometry Imaging Data.
HormonomicsDB: a novel workflow for the untargeted analysis of plant growth regulators and hormones.
Enabling high-sensitivity live single-cell mass spectrometry using an integrated electrical lysis and nano electrospray ionization interface.
Standardization via Post Column Infusion-A Novel and Convenient Quantification Approach for LC-MS/MS.
Pharmacokinetic study of iptacopan and its two acyl glucuronide metabolites in monkey plasma by liquid chromatography combined with electrospray ionization tandem mass spectrometry.
Leveraging Supervised Machine Learning Algorithms for System Suitability Testing of Mass Spectrometry Imaging Platforms.
Impact of internal standard selection on measurement results for long chain fatty acids in blood.
Metabolic signatures of metabolites of the purine degradation pathway in human plasma using HILIC UHPLC-HRMS.
Multi-class plant hormone HILIC-MS/MS analysis coupled with high-throughput phenotyping to investigate plant-environment interactions.
Fast and broad-coverage lipidomics enabled by ion mobility-mass spectrometry.
Development of an UPLC-MS/MS approach to detect and quantify N-nitroso mirabegron in mirabegron.
Comparative analysis of feature annotation methods for SESI-HRMS in exhaled breath analysis.
[Recent advances in capillary electrophoresis-mass spectrometry analysis of ‍trace biomolecules].
A Decade of Computational Mass Spectrometry from Reference Spectra to Deep Learning.
Simultaneous determination of three tyrosine kinase inhibitors and three triazoles in human plasma by LC-MS/MS: applications to therapeutic drug monitoring and drug-drug interaction studies.
Exploring methandienone metabolites generated via homogenized camel liver: Advancements for anti-doping applications through High Resolution-Liquid Chromatography Mass Spectrometry analysis.
UPLC-MS/MS method for fluconazole determination in plasma and its application in Mexican patients with candidaemia.
SCMeTA: A pipeline for single-cell metabolic analysis data processing.
Analytical Methods for the Determination of Pharmaceuticals and Personal Care Products in Solid and Liquid Environmental Matrices: A Review.
High-temperature liquid chromatography-isotope ratio mass spectrometry methodology for carbon isotope ratio determination of anabolic steroids in urine.
Optimized method development and validation for determining donepezil in rat plasma: A liquid-liquid extraction, LC-MS/MS, and design of experiments approach.
Targeted metabolomics assisted rapid screening and characterization of aristolochic acids and their DNA adducts in aristolochia plants by ultra-high performance liquid chromatography coupled with ion mobility quadrupole time-of-flight mass spectrometry.
Development and validation of a simple chromatographic method to screen oral fluid samples for drugs in DUID investigations.

J Biosci Bioeng. 2024 Sep 03. pii: S1389-1723(24)00230-5. [Epub ahead of print]

Novel sampling and gas-phase derivatization strategy: Proof-of-concept by profiling ionic polar metabolites using gas chromatography-mass spectrometry.

Kazuhiro Kawamura, Eiichiro Fukusaki.

  Metabolomic research involves the comprehensive analysis of metabolites in biological samples and has many applications. Gas chromatography-mass spectrometry (GC-MS) is an established and widely used approach for metabolic profiling. However, sample preparation and metabolite derivatization are time-consuming, and derivatization options are limited. We propose gas-solid phase derivatization (GSPD) as a novel sampling and derivatization method that uses a silica monolith substrate and gaseous derivatization reagents for metabolomics using GC-MS. We developed a method to measure the organic acids and sugar phosphates responsible for glycolysis and the tricarboxylic acid (TCA) cycle. GSPD simplifies the sample preparation and can be applied to derivatization reactions that are difficult to perform in solution owing to solvent limitations. The developed method was applied to human plasma and tomato pulp and was shown to have a higher detection performance than the conventional method. This study provides a strategy to simplify sample preparation and expand derivatization options for GC-MS-based metabolomics.

Keywords:  Derivatization; Gas chromatography/mass spectrometry; Metabolomics; Organic acid; Silica monolith; Sugar phosphate

DOI:  https://doi.org/10.1016/j.jbiosc.2024.07.019
J Am Soc Mass Spectrom. 2024 Sep 02.

MSIGen: An Open-Source Python Package for Processing and Visualizing Mass Spectrometry Imaging Data.

Emerson Hernly, Hang Hu, Julia Laskin.

  Mass spectrometry imaging (MSI) provides information about the spatial localization of molecules in complex samples with high sensitivity and molecular selectivity. Although point-wise data acquisition, in which mass spectra are acquired at predefined points in a grid pattern, is common in MSI, several MSI techniques use line-wise data acquisition. In line-wise mode, the imaged surface is continuously sampled along consecutive parallel lines and MSI data are acquired as a collection of line scans across the sample. Furthermore, aside from the standard imaging mode in which full mass spectra are acquired, other acquisition modes have been developed to enhance molecular specificity, enable separation of isobaric and isomeric species, and improve sensitivity to facilitate the imaging of low abundance species. These methods, including MS/MS-MSI in both MS2 and MS3 modes, multiple-reaction monitoring (MRM)-MSI, and ion mobility spectrometry (IMS)-MSI have all demonstrated their capabilities, but their broader implementation is limited by the existing MSI analysis software. Here, we present MSIGen, an open-source Python package for the visualization of MSI experiments performed in line-wise acquisition mode containing MS1, MS2, MRM, and IMS data, which is available at https://github.com/LabLaskin/MSIGen. The package supports multiple vendor-specific and open-source data formats and contains tools for targeted extraction of ion images, normalization, and exportation as images, arrays, or publication-style images. MSIGen offers multiple interfaces, allowing for accessibility and easy integration with other workflows. Considering its support for a wide variety of MSI imaging modes and vendor formats, MSIGen is a valuable tool for the visualization and analysis of MSI data.

Keywords:  Data visualization; Mass spectrometry imaging; Nano-DESI MSI; Open access software; Python package

DOI:  https://doi.org/10.1021/jasms.4c00178
F1000Res. 2022 ;11 1191

HormonomicsDB: a novel workflow for the untargeted analysis of plant growth regulators and hormones.

Ryland T Giebelhaus, Lauren A E Erland, Susan J Murch.

  Background: Metabolomics is the simultaneous determination of all metabolites in a system. Despite significant advances in the field, compound identification remains a challenge. Prior knowledge of the compound classes of interest can improve metabolite identification. Hormones are a small signaling molecules, which function in coordination to direct all aspects of development, function and reproduction in living systems and which also pose challenges as environmental contaminants. Hormones are inherently present at low levels in tissues, stored in many forms and mobilized rapidly in response to a stimulus making them difficult to measure, identify and quantify.Methods: An in-depth literature review was performed for known hormones, their precursors, metabolites and conjugates in plants to generate the database and an RShiny App developed to enable web-based searches against the database. An accompanying liquid chromatography - mass spectrometry (LC-MS) protocol was developed with retention time prediction in Retip. A meta-analysis of 14 plant metabolomics studies was used for validation.
Results: We developed HormonomicsDB, a tool which can be used to query an untargeted mass spectrometry (MS) dataset against a database of more than 200 known hormones, their precursors and metabolites. The protocol encompasses sample preparation, analysis, data processing and hormone annotation and is designed to minimize degradation of labile hormones. The plant system is used a model to illustrate the workflow and data acquisition and interpretation. Analytical conditions were standardized to a 30 min analysis time using a common solvent system to allow for easy transfer by a researcher with basic knowledge of MS. Incorporation of synthetic biotransformations enables prediction of novel metabolites.
Conclusions: HormonomicsDB is suitable for use on any LC-MS based system with compatible column and buffer system, enables the characterization of the known hormonome across a diversity of samples, and hypothesis generation to reveal knew insights into hormone signaling networks.

Keywords:  Plant metabolomics; hormonomics; phytohormones; synthetic biotransformations

DOI:  https://doi.org/10.12688/f1000research.124194.2
Anal Chim Acta. 2024 Oct 02. pii: S0003-2670(24)00869-9. [Epub ahead of print]1324 343068

Enabling high-sensitivity live single-cell mass spectrometry using an integrated electrical lysis and nano electrospray ionization interface.

Kanchana Pandian, Luís Daniel de Aguiar Homem E Almeida de Matos, Laura A Hetzel, Raphaël Zwier, Peter van Veldhuizen, Charelle Schubert, Jayaprakash Karuppusamy, Amy C Harms, Ahmed Ali, Thomas Hankemeier.

  BACKGROUND: Live single-cell metabolomic studies encounter inherent difficulties attributed to the limited sample volume, minimal compound quantity, and insufficient sensitivity in the Mass Spectrometry (MS) method used to obtain single-cell data. However, understanding cellular heterogeneity, functional diversity, and metabolic processes within individual cells is essential. Exploring how individual cells respond to stimuli, including drugs, environmental changes, or signaling molecules, offers insights into biology, oncology, and drug discovery. Efficient release of cell contents (lysis) is vital for accurate metabolite detection at the single-cell level. Despite this, traditional approaches in live single cell metabolomics methods do not emphasize efficient lysis to prevent sample dilution. Instead, current live single cell metabolomics methods use direct infusion to introduce the cell into the mass spectrometry without prior chromatographic separation or a lysis step, which adversely affects sensitivity and metabolic coverage.RESULTS: To address this, we developed an integrated single-cell electrical lysis and nano spray (SCEL-nS) platform coupled to an Orbitrap MS capable of efficiently lysing a single cell after being sampled with specially manufactured micropipettes. Lysis efficiency was validated by comparing live cell stain fluorescent intensities of intact and electrically lysed cells through microscopy imaging. The SCEL-nS platform successfully induced the breakdown of a single cell, significantly reducing the live cell stain's fluorescent intensity indicating cell membrane breakdown. Additionally, SCEL-nS was validated by measuring single cells spiked with the anti-cancer drug tamoxifen by MS. SCEL-nS use resulted in statistically significant increase in the peak measured by the method compared to the traditional non-lysis method.
SIGNIFICANCE: Overall, our results demonstrate that the newly incorporated SCEL-nS platform achieved higher sensitivities compared to traditional live single cell analysis methods.

Keywords:  Mass spectrometry; Nano spray; Single-cell electrical lysis; Single-cell metabolomics

DOI:  https://doi.org/10.1016/j.aca.2024.343068
Molecules. 2024 Aug 12. pii: 3829. [Epub ahead of print]29(16):

Standardization via Post Column Infusion-A Novel and Convenient Quantification Approach for LC-MS/MS.

Katharina Habler, Arber Rexhaj, Felix L Happich, Michael Vogeser.

  Mass spectrometry (MS) is a widely used analytical technique including medical diagnostics, forensic toxicology, food and water analysis. The gold standard for quantifying compounds involves using stable isotope-labeled internal standards (SIL-IS). However, when these standards are not commercially available, are prohibitively expensive, or are extremely difficult to synthesize, alternative external quantification techniques are employed. We hereby present a novel, convenient and cheap quantification approach-quantification via post column infusion (PCI). As a proof of concept, we demonstrated PCI quantification for the immunosuppressant tacrolimus in whole blood using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The validation results met the criteria according to the guideline on bioanalytical method validation of the European Medicine Agency (EMA), achieving imprecisions and inaccuracies with coefficient of variation and relative bias below 15%. Anonymized and leftover whole blood samples from immunosuppressed patients receiving tacrolimus were used for method comparison (PCI quantification vs. conventional internal standard (IS) quantification). Both methods showed strong agreement with a Pearson correlation coefficient of r = 0.9532. This novel PCI quantification technique (using the target analyte itself) expands the quantification options available in MS, providing reliable results, particularly when internal standards are unavailable or unaffordable. With the current paper, we aim to demonstrate that our innovative PCI technique has great potential to overcome practical issues in quantification and to provide guidance on how to incorporate PCI in existing or new LC-MS methods. Moreover, this study demonstrated a more convenient method for correcting matrix effects in comparison to alternative PCI techniques.

Keywords:  isotope-labeled internal standard; liquid chromatography tandem mass spectrometry; post column infusion; quantification techniques

DOI:  https://doi.org/10.3390/molecules29163829
Biomed Chromatogr. 2024 Sep 03. e6002

Pharmacokinetic study of iptacopan and its two acyl glucuronide metabolites in monkey plasma by liquid chromatography combined with electrospray ionization tandem mass spectrometry.

Jingchu Li, Shanshan Liu, Chenglin Jia, Jiacheng Li, Zhihui Zhang, Jian Chen, Yongbin Cao, Chao Ma.

  In this study, a simple and sensitive liquid chromatography tandem mass spectrometric method was developed and validated for the determination of iptacopan and two acyl glucuronidation metabolites in monkey plasma. The plasma sample was precipitated with acetonitrile and then separated on an Acquity UPLC BEH C18 column (2.1 × 100 mm, 1.7 μm) using 0.1% formic acid and 5 mM ammonium acetate in water and acetonitrile as the mobile phase. The mass spectrometry (MS) detection was performed in positive multiple reactions monitoring (MRM) mode with precursor-to-production transitions. The developed assay was validated over the range of 1-2000 ng/mL for three analytes with correlation coefficient (r) more than 0.99. The validation parameters including accuracy, precision, carryover effect, matrix effect, recovery, and stability were all within the acceptable limits. The validated method has been applied to investigate the pharmacokinetics of iptacopan and its two acyl glucuronidation metabolites in monkey plasma. After intravenous administration, iptacopan showed low clearance (2.75 mL/min/kg) in monkey plasma. After oral administration, the bioavailability was 55.43%. The exposure (AUC0-t) of direct acyl glucuronide (AG) of iptacopan accounts for 9.73% of the iptacopan plasma exposure. The AUC0-t of AG of dealkylated metabolite of iptacopan was present at a lower level, accounting for 0.5% of the iptacopan plasma exposure.

Keywords:  acyl glucuronide; bioavailability; iptacopan; pharmacokinetics

DOI:  https://doi.org/10.1002/bmc.6002
J Proteome Res. 2024 Sep 03.

Leveraging Supervised Machine Learning Algorithms for System Suitability Testing of Mass Spectrometry Imaging Platforms.

Russell R Kibbe, Alexandria L Sohn, David C Muddiman.

  Quality control and system suitability testing are vital protocols implemented to ensure the repeatability and reproducibility of data in mass spectrometry investigations. However, mass spectrometry imaging (MSI) analyses present added complexity since both chemical and spatial information are measured. Herein, we employ various machine learning algorithms and a novel quality control mixture to classify the working conditions of an MSI platform. Each algorithm was evaluated in terms of its performance on unseen data, validated with negative control data sets to rule out confounding variables or chance agreement, and utilized to determine the necessary sample size to achieve a high level of accurate classifications. In this work, a robust machine learning workflow was established where models could accurately classify the instrument condition as clean or compromised based on data metrics extracted from the analyzed quality control sample. This work highlights the power of machine learning to recognize complex patterns in MSI data and use those relationships to perform a system suitability test for MSI platforms.

Keywords:  IR-MALDESI; machine learning; mass spectrometry imaging; quality control; system suitability testing

DOI:  https://doi.org/10.1021/acs.jproteome.4c00360
J Mass Spectrom Adv Clin Lab. 2024 Aug;33 22-30

Impact of internal standard selection on measurement results for long chain fatty acids in blood.

John M Goodwin, Heather C Kuiper, Barrett Brister, Hubert W Vesper.

  Introduction: Internal standards correct for measurement variation due to sample loss. Isotope labeled analytes are ideal internal standards for the measurement of fatty acids in human plasma but are not always readily available. For this reason, quantification of multiple analytes at once is most often done using only a single or few internal standards. The magnitude of the impact this has on method accuracy and precision is not well studied for gas chromatography-mass spectrometry systems.Objective: This study aims to estimate bias and changes in uncertainty associated with using alternative fatty acid isotopologue internal standards for the estimation of similar or dissimilar long chain fatty acids.
Method: Using a previously reported method for the quantification of 27 fatty acids in human plasma using 18 internal standards we obtained estimates of bias and uncertainty at up to three levels of fatty acid concentration.
Results: With some notable exceptions, method accuracy remained relatively stable when using an alternative internal standard (Median Relative Absolute Percent Bias: 1.76%, Median Spike-Recovery Absolute Percent Bias: 8.82%), with larger changes in method precision (Median Increase in Variance: 141%). Additionally, the degree of difference between analyte and internal standard structure was related to the magnitude of bias and uncertainty of the measurement.
Conclusion: The data presented here show that the choice of internal standard used to estimate fatty acid concentration can affect the accuracy and reliability of measurement results and, therefore, needs to be assessed carefully when developing analytical methods for the measurement of fatty acid profiles.Disclaimer: The findings and conclusions in this report are those of the author(s) and do not necessarily represent the official position of the Centers for Disease Control and Prevention/the Agency for Toxic Substances and Disease Registry. Use of trade names is for identification only and does not imply endorsement by the Centers for Disease Control and Prevention, the Public Health Service, and the US Department of Health and Human Services.

Keywords:  Fatty acids; Gas chromatography; Internal standards; Isotope dilution; Mass spectrometry

DOI:  https://doi.org/10.1016/j.jmsacl.2024.07.002
J Pharm Biomed Anal. 2024 Aug 26. pii: S0731-7085(24)00491-6. [Epub ahead of print]251 116451

Metabolic signatures of metabolites of the purine degradation pathway in human plasma using HILIC UHPLC-HRMS.

Rui Liu, Qingke Wu, Chuanlong Wu, Yingnan Qu, Yanming Fang, Jiyangzong De, Ronghua Fan, Wenjing Song.

  The metabolic disorders in the purine degradation pathway have proven to be closely associated with several human diseases. However, the etiology is not yet fully understood. Profile assay of purine intermediates and uric acid involved in the metabolic pathway can provide additional insight into the nature and severity of related diseases. Purine metabolites are endogenous chemicals with high hydrophilicity, polarity, and similar structures, thus there is a great need for a specific method to quantify them directly in biological fluids with a short running time. Herein, eight purine degradation pathway metabolites, including xanthine, hypoxanthine, guanine, xanthosine, inosine, guanosine, adenosine and uric acid, in human plasma were quantitatively measured using hydrophilic interaction chromatography-tandem high-resolution mass spectrometry (HILIC-HRMS) in a short running time of 10 min. The method was systematically validated for specificity, linearity of the calibration curve, the limit of detection, the limit of quantification, the lower limit of quantification, precision, accuracy, extraction recovery, matrix effect, and stability. The results showed that the method was linear (R2 > 0.99), accurate (the intra- and inter-day recoveries of all analytes ranged from 90.0 % to 110.0 %), and precise (the intra- and inter-day precisions were less than 6.7 % and 8.9 %, respectively) with the lower limits of quantification ranging from 3 to 10,000 ng/mL. The extraction recoveries and matrix effects were repeatable and stable. All the analytes were stable in the autosampler and could be subject to three freeze-thaw cycles. The developed method was ultimately applied to 100 plasma specimens from healthy individuals. The results showed that the concentrations of different purine metabolites varied dramatically in plasma specimens. Diet and body mass index (BMI) were the most significant factors determining purine levels, followed by drinking and sex. Age, smoking and bedtime showed a very weak correlation with purine metabolism. The findings of the present work reveal the characteristics of purine metabolism in human plasma under non-pathological conditions. The results also highlight the factors that can cause changes in purine metabolism, which are useful in developing effective treatment strategies for metabolic disorders of purines, particularly for those caused by lifestyle factors.

Keywords:  HILIC; Purine degradation pathway; Purine intermediates; ROC analysis; Risk factor

DOI:  https://doi.org/10.1016/j.jpba.2024.116451
Plant J. 2024 Sep 02.

Multi-class plant hormone HILIC-MS/MS analysis coupled with high-throughput phenotyping to investigate plant-environment interactions.

Ondřej Vrobel, Sanja Ćavar Zeljković, Jan Dehner, Lukáš Spíchal, Nuria De Diego, Petr Tarkowski.

  Plant hormones are chemical signals governing almost every aspect of a plant's life cycle and responses to environmental cues. They are enmeshed within complex signaling networks that can only be deciphered by using broad-scale analytical methods to capture information about several plant hormone classes simultaneously. Methods used for this purpose are all based on reversed-phase (RP) liquid chromatography and mass spectrometric detection. Hydrophilic interaction chromatography (HILIC) is an alternative chromatographic method that performs well in analyses of biological samples. We therefore developed and validated a HILIC method for broad-scale plant hormone analysis including a rapid sample preparation procedure; moreover, derivatization or fractionation is not required. The method enables plant hormone screening focused on polar and moderately polar analytes including cytokinins, auxins, jasmonates, abscisic acid and its metabolites, salicylates, indoleamines (melatonin), and 1-aminocyclopropane-1-carboxylic acid (ACC), for a total of 45 analytes. Importantly, the major pitfalls of ACC analysis have been addressed. Furthermore, HILIC provides orthogonal selectivity to conventional RP methods and displays greater sensitivity, resulting in lower limits of quantification. However, it is less robust, so procedures to increase its reproducibility were established. The method's potential is demonstrated in a case study by employing an approach combining hormonal analysis with phenomics to examine responses of three Arabidopsis ecotypes toward three abiotic stress treatments: salinity, low nutrient availability, and their combination. The case study showcases the value of the simultaneous determination of several plant hormone classes coupled with phenomics data when unraveling processes involving complex cross-talk under diverse plant-environment interactions.

Keywords:  ACC; high‐throughput phenotyping; hydrophilic interaction chromatography; mass spectrometry; melatonin; multifactorial plant stress; plant hormone; technical advance

DOI:  https://doi.org/10.1111/tpj.17010
Analyst. 2024 Sep 02.

Fast and broad-coverage lipidomics enabled by ion mobility-mass spectrometry.

Yuping Cai, Xi Chen, Fandong Ren, Hongmiao Wang, Yandong Yin, Zheng-Jiang Zhu.

Aberrant lipid metabolism has been widely recognized as a hallmark of various diseases. However, the comprehensive analysis of distinct lipids is challenging due to the complexity of lipid molecular structures, wide concentration ranges, and numerous isobaric and isomeric lipids. Usually, liquid chromatography-mass spectrometry (LC-MS)-based lipidomics requires a long time for chromatographic separation to achieve optimal separation and selectivity. Ion mobility (IM) adds a new separation dimension to LC-MS, significantly enhancing the coverage, sensitivity, and resolving power. We took advantage of the rapid separation provided by ion mobility and optimized a fast and broad-coverage lipidomics method using the LC-IM-MS technology. The method required only 8 minutes for separation and detected over 1000 lipid molecules in a single analysis of common biological samples. The high reproducibility and accurate quantification of this high-throughput lipidomics method were systematically characterized. We then applied the method to comprehensively measure dysregulated lipid metabolism in patients with colorectal cancer (CRC). Our results revealed 115 significantly changed lipid species between preoperative and postoperative plasma of patients with CRC and also disclosed associated differences in lipid classes such as phosphatidylcholines (PC), sphingomyelins (SM), and triglycerides (TG) regarding carbon number and double bond. Together, a fast and broad-coverage lipidomics method was developed using ion mobility-mass spectrometry. This method is feasible for large-scale clinical lipidomic studies, as it effectively balances the requirements of high-throughput and broad-coverage in clinical studies.

DOI: https://doi.org/10.1039/d4an00751d
Rapid Commun Mass Spectrom. 2024 Nov 30. 38(22): e9911

Development of an UPLC-MS/MS approach to detect and quantify N-nitroso mirabegron in mirabegron.

Ravi Uppala, Rakesh Chandrakant Prabhu, Arthanareeswari Maruthapillai, Bandaru Venkatasubbaiah, Gopal Chandru Senadi, Sundaramurthy Devikala.

In the mirabegron (MIR) synthesis, the N-nitroso mirabegron (NNM) is obtained during synthetic process of MIR; water is being used in reaction under acidic condition. Nitrite source is from water, and secondary amine source is from MIR as it has secondary amine; NNM is generated as an impurity during the synthesis of MIR. The presence of NNM in MIR could potentially affect its effectiveness. The purpose of this study was to establish a Ultra-performance liquid chromatography-mass spectrometry/mass spectrometry (UPLC-MS/MS) methodology to identify NNM in MIR samples. The method for NNM analysis was developed on Acquity HSS T3 (100*2.1) mm 1.8 μm column with gradient elution using mobile phase consisted of 0.1% formic acid in water (mobile phase A) and 0.1% formic acid in methanol (mobile phase B). Mass spectrometer with electrospray ionization operated in the MRM mode was used in the analysis of NNM (m/ z 426.20 → 170.00). The UPLC-MS/MS methodology proposed showed a good linearity (0.02 to 0.72 ppm), good system precision (RSD = 0.57%), good method precision (RSD = 0.87%), acceptable accuracy (94.5-116.5%), low detection limit (0.006 ppm) and low quantification limit (0.02 ppm) for NNM. The UPLC-MS/MS methodology proposed can be utilized to assess the quality of MIR sample for the presence of NNM impurity.

DOI: https://doi.org/10.1002/rcm.9911
J Chromatogr A. 2024 Aug 23. pii: S0021-9673(24)00670-8. [Epub ahead of print]1734 465296

Comparative analysis of feature annotation methods for SESI-HRMS in exhaled breath analysis.

Cedric Wüthrich, Albin Vadakkechira, Pascal Fuchsmann, Simon Wacker, Renato Zenobi, Stamatios Giannoukos.

  Secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS) is a powerful method for the analysis of exhaled breath in real time. However, feature annotation is challenging due to the flow-injection nature of the technique. To evaluate alternative methods for enhancing feature annotation, a study was conducted where the exhaled breath of sixteen subjects was condensed and analyzed using dynamic headspace vacuum in-trap extraction gas chromatography-mass spectrometry (DHS-V-ITEX-GC-MS) and liquid chromatography coupled to mass spectrometry (LC-MS) using polar and reverse-phase conditions along with a data-independent MS2-acquisition method based on multiple injections. The annotation results obtained from these methods were compared to those from SESI-HRMS. The use of these techniques on breath condensate is unprecedented. The GC-MS method primarily detected compounds of exogenous origin, particularly additives in oral hygiene products like menthol. On the other hand, LC-MS detected a vast number of features, especially with the utilized data-independent acquisition method. Chemical classes to these features were assigned in-silico. In positive ion mode, mostly amino acids and amines were detected, while the largest group in negative ion mode consisted of carboxylic acids. Approximately 25% and 5% of SESI features had a corresponding match with LC-MS and GC-MS. While both GC-MS and LC-MS methods partially overlapped with the SESI features, there was limited overlap of both in the mass-to-charge range from 150 to 200. In conclusion, both GC-MS and LC-MS analysis of breath condensate can serve as supplementary tools for annotating features obtained from SESI-MS. However, to increase confidence in the annotation results, combining these methods with additional on-line fragmentation techniques is recommended.

Keywords:  Exhaled breath condensate; Gas chromatography; Liquid chromatography; Mass spectrometry; SESI

DOI:  https://doi.org/10.1016/j.chroma.2024.465296
Nihon Yakurigaku Zasshi. 2024 ;159(5): 321-326

[Recent advances in capillary electrophoresis-mass spectrometry analysis of ‍trace biomolecules].

Takayuki Kawai.

In recent years, various trace bioanalysis methods have been developed, including single-cell transcriptome analysis methods. As the sample volume and amount of biomolecules contained therein are extremely limited, development of new single-cell analysis methods require extremely high-level techniques. It is necessary to design an appropriate analysis system that integrates a highly sensitive detection system and a pretreatment protocol for minimizing sample loss, where separation method is especially important for analyzing diverse mixtures of biomolecules. Among them, capillary electrophoresis (CE) can separate biomolecules in nanoliter-scale solutions with high resolution, making it highly compatible with trace samples such as single cells. By combining with highly sensitive nano-electrospray ionization-mass spectrometry (MS), it is possible to detect nanomolar to sub-nanomolar biomolecules, which can be further improved by using online sample preconcentration methods. These highly sensitive analytical techniques have made it possible to analyze trace amounts of metabolites, proteins, lipids, etc. This review paper summarizes the research on CE-MS trace bioanalysis that has been reported to date, with a focus on single-cell analysis.

DOI: https://doi.org/10.1254/fpj.24036
Chimia (Aarau). 2024 Aug 21. 78(7-8): 525-530

A Decade of Computational Mass Spectrometry from Reference Spectra to Deep Learning.

Michael A Stravs.

  Computational methods are playing an increasingly important role as a complement to conventional data evaluation methods in analytical chemistry, and particularly mass spectrometry. Computational mass spectrometry (CompMS) is the application of computational methods on mass spectrometry data. Herein, advances in CompMS for small molecule chemistry are discussed in the areas of spectral libraries, spectrum prediction, and tentative structure identification (annotation): Automatic spectrum curation is facilitating the expansion of openly available spectral libraries, a crucial resource both for compound annotation directly and as a resource for machine learning algorithms. Spectrum prediction and molecular fingerprint prediction have emerged as two key approaches to compound annotation. For both, multiple methods based on classical machine learning and deep learning have been developed. Driven by advances in deep learning-based generative chemistry, de novo structure generation from fragment spectra is emerging as a new field of research. This review highlights key publications in these fields, including our approaches RMassBank (automatic spectrum curation) and MSNovelist (de novo structure generation).

Keywords:  Machine Learning; Mass spectrometry; Small molecules

DOI:  https://doi.org/10.2533/chimia.2024.525
J Chromatogr B Analyt Technol Biomed Life Sci. 2024 Aug 20. pii: S1570-0232(24)00285-X. [Epub ahead of print]1246 124276

Simultaneous determination of three tyrosine kinase inhibitors and three triazoles in human plasma by LC-MS/MS: applications to therapeutic drug monitoring and drug-drug interaction studies.

Ninghong Li, Lu Liu, Dong Liu, Hengyi Yu, Guangjie Yang, Lihui Qiu, Yufei Chen, Dong Xiang, Xuepeng Gong.

  Tyrosine kinase inhibitors (TKIs) and triazole antifungals are the first-line drugs for treating chronic myeloid leukemia (CML) and fungal infections, respectively, but both suffer from large exposure differences and narrow therapeutic windows. Moreover, these two types of drugs are commonly used together in CML patients with fungal infections. Multiple studies and guidelines have suggested the importance of therapeutic drug monitoring (TDM) of TKIs and triazoles. Currently, methods for the simultaneous determination of both types of drugs are limited. We developed a simple, rapid, and reliable liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for simultaneous quantification of three commonly used TKIs (imatinib, dasatinib, and nilotinib) and three commonly used triazoles (voriconazole, itraconazole, and posaconazole) in human plasma. The analytes were eluted on a Welch XB-C18 analytical column (50 × 2.1 mm, 5 µm) at 0.7 mL/min, using a gradient elution of 10 mM ammonium formate (A) and methanol-acetonitrile-isopropanol (80:10:10, v/v/v) containing 0.2 % formic acid (B) with a total analysis time of 3.5 min. The calibration curves were linear over the range from 20 to 4000 ng/mL for imatinib and nilotinib, from 2 to 400 ng/mL for dasatinib, and from 50 to 10,000 ng/mL for voriconazole, itraconazole, and posaconazole. Selectivity, accuracy, precision, recovery, matrix effect, and stability all met the validation requirements. The method was successfully used for TDM in CML patients who co-treated with both TKIs and triazoles. Drug-drug interaction analysis between TKIs and triazoles showed that a significant positive correlation was observed between imatinib and voriconazole, as well as dasatinib and voriconazole. Therefore, this method can be well applied in clinical TDM for patients receiving TKIs, triazoles, or both simultaneously.

Keywords:  Chronic myeloid leukemia; Drug-drug interactions; LC-MS/MS; Therapeutic drug monitoring; Triazole antifungal drugs; Tyrosine kinase inhibitor

DOI:  https://doi.org/10.1016/j.jchromb.2024.124276
Rapid Commun Mass Spectrom. 2024 Dec 30. 38(22): e9902

Exploring methandienone metabolites generated via homogenized camel liver: Advancements for anti-doping applications through High Resolution-Liquid Chromatography Mass Spectrometry analysis.

Ramees Abdulla Vazhat, N A Mohamed Farook, Jahfar Nalakath, Praseen Ondern Komathu.

RATIONALE: Anabolic steroids, also known as anabolic-androgenic steroids (AAS), encompass steroidal androgens such as testosterone, as well as synthetic counterparts with similar structures and effects. The misuse of AAS has increased over the years, leading to ethical and welfare concerns in sports. The World Anti-Doping Agency (WADA) and the International Federation for Equestrian Sports (FEI) have banned AAS in relevant sports. Methandienone is one of the most identified anabolic androgenic steroids in sports drug testing, Therefore, reliable detection methods are crucial for effective doping control and maintaining the integrity of the sports.METHODS: This study explores the use of homogenized camel liver for detecting methandienone metabolites in camels. The biotransformation pathways of methandienone in homogenized camel liver tissues are analyzed using Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS) to identify and characterize the phase I and phase II metabolites. Chromatographic separation was achieved using a Thermo-Hypersil C18 column.
RESULTS: The study has identified 11 methandienone metabolites (M1-M11), this includes 10 phase I and one phase II metabolite. A glucuronic acid conjugate of methandienone was observed in this study, but no sulfonic acid conjugations were found. The metabolites and their possible chemical structures, along with their fragmentation patterns are confirmed using MSMS (MS2) experiments in data-independent acquisition (DIA) mode.
CONCLUSIONS: These findings serve as a vital tool for the rapid detection of methandienone, combating its illicit use in camel racing. Comprehensive screenings covering both the parent drug and its metabolites are recommended to improve detection accuracy and ensure regulatory compliance in sports doping. Future research should explore methandienone's metabolite profile in administered camel samples.

DOI: https://doi.org/10.1002/rcm.9902
Bioanalysis. 2024 Sep 05. 1-9

UPLC-MS/MS method for fluconazole determination in plasma and its application in Mexican patients with candidaemia.

Karla Paulina Valero Rivera, Martin Magaña Aquino, Julia Sagahón Azúa, María Del Carmen Romero Méndez, Susanna Edith Medellín Garibay, Rosa Del Carmen Milán Segovia, Fidel Martínez Gutiérrez, Silvia Romano Moreno.

  Aim: An accurate and fast ultra-high performance liquid chromatography coupled with tandem mass spectrometry analytical method was developed and validated for quantifying fluconazole levels in human plasma according to the US FDA guidelines.Materials & methods: A simple protein precipitation by acetonitrile was employed for the sample preparation. The chromatographic separation was carried out using isocratic elution of water (0.1% formic acid) and acetonitrile on an Acquity ultra-high performance liquid chromatography HSS T3 column. Samples from ten adult patients diagnosed with candidemia who received fluconazole treatment were analyzed.Results & conclusion: The method demonstrated excellent linearity and stability within the 1-50 μg/ml range (r2 >0.999). The intraday and interday precision were determined with coefficient of variation values ranging from 1.4 to 4.38% and 2.8 to 6.6%, respectively. This rapid and selective method has successfully analyzed 27 plasma samples. The straightforward sample preparation in a single step and the reduced analysis time make this method suitable for adult patients with candidemia, leading to improved clinical outcomes.

Keywords:  LC–MS/MS bioanalysis pharmacokinetics; UPLC–MS/MS; analytical method validation; fluconazole

DOI:  https://doi.org/10.1080/17576180.2024.2387452
Bioinformatics. 2024 Sep 06. pii: btae545. [Epub ahead of print]

SCMeTA: A pipeline for single-cell metabolic analysis data processing.

Xingyu Pan, Siyuan Pan, Murong Du, Jinlei Yang, Huan Yao, Xinrong Zhang, Sichun Zhang.

SUMMARY: To address the challenges in single-cell metabolomics (SCM) research, we have developed an open-source Python-based modular library, named SCMeTA, for SCM data processing. We designed standardized pipeline and inter-container communication format and have developed modular components to adapt to the diverse needs of SCM studies. The validation was carried out on multiple SCM experiment data. The results demonstrated significant improvements in batch effects, accuracy of results, metabolic extraction rate, cell matching rate, as well as processing speed. This library is of great significance in advancing the practical application of SCM analysis and makes a foundation for wide-scale adoption in biological studies.AVAILABILITY: SCMeTA is freely available on https://github.com/SCMeTA/SCMeTA and https://doi.org/10.5281/zenodo.13569643.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DOI: https://doi.org/10.1093/bioinformatics/btae545
Molecules. 2024 Aug 17. pii: 3900. [Epub ahead of print]29(16):

Analytical Methods for the Determination of Pharmaceuticals and Personal Care Products in Solid and Liquid Environmental Matrices: A Review.

Abdulmalik M Alqarni.

  Among the various compounds regarded as emerging contaminants (ECs), pharmaceuticals and personal care products (PPCPs) are of particular concern. Their continuous release into the environment has a negative global impact on human life. This review summarizes the sources, occurrence, persistence, consequences of exposure, and toxicity of PPCPs, and evaluates the various analytical methods used in the identification and quantification of PPCPs in a variety of solid and liquid environmental matrices. The current techniques of choice for the analysis of PPCPs are state-of-the-art liquid chromatography coupled to mass spectrometry (LC-MS) or tandem mass spectrometry (LC-MS2). However, the complexity of the environmental matrices and the trace levels of micropollutants necessitate the use of advanced sample treatments before these instrumental analyses. Solid-phase extraction (SPE) with different sorbents is now the predominant method used for the extraction of PPCPs from environmental samples. This review also addresses the ongoing analytical method challenges, including sample clean-up and matrix effects, focusing on the occurrence, sample preparation, and analytical methods presently available for the determination of environmental residues of PPCPs. Continuous development of innovative analytical methods is essential for overcoming existing limitations and ensuring the consistency and diversity of analytical methods used in investigations of environmental multi-class compounds.

Keywords:  PPCPs; STP; WWTPs; analytical challenges; clean-up; instrumental analysis; matrix effect; persistence; sample preparation

DOI:  https://doi.org/10.3390/molecules29163900
Anal Chim Acta. 2024 Oct 02. pii: S0003-2670(24)00893-6. [Epub ahead of print]1324 343092

High-temperature liquid chromatography-isotope ratio mass spectrometry methodology for carbon isotope ratio determination of anabolic steroids in urine.

Lenka Honesova, Wouter Viaene, Peter Van Eenoo, Michaël Polet.

BACKGROUND: Gas Chromatography Isotope Ratio Mass Spectrometry (GC-C-IRMS) has long been used in routine laboratories to determine the δ13C values of anabolic steroids in urine, differentiating between, e.g., endogenous and synthetic testosterone (T) in sports doping control. Until now, liquid chromatography (LC-IRMS) has not been used. The LC-IRMS setup doesn't allow organic solvents or modifiers in the mobile phase for δ13C determinations. Mid-to non-polar analytes such as steroids can be analysed in water heated to High Temperatures (HT, up to 200 °C) because at 200 °C has a similar polarity as 80/20 methanol/water at ambient temperature. In this work, we developed a method for steroids in urine, extending the application of the LC-IRMS to non-polar analytes in complex matrices.RESULT: An HT-LC-IRMS method capable of determining the δ13C values of four steroids (i.e., testosterone (T), 5α-androstane-3α,17β-diol (ααβ), 5β-androstane-3α,17β-diol (βαβ) and pregnanetriol (PT)) in urine was developed and validated. Accuracy ranged from 0.23 ‰ (ααβ and βαβ) to 0.49 ‰ (T), and the detection limit was set at 10 ng mL-1 (T, ααβ+βαβ). The validation data and a comparison of authentic urine samples analysed with HT-LC-IRMS and GC-C-IRMS indicated a comparable performance between HT-LC-IRMS and GC-C-IRMS.
SIGNIFICANCE: HT-LC-IRMS can be used to determine δ13C values of anabolic steroids, extending the applicability of both HT-LC and LC-IRMS to non-polar substances determined in a complex matrix in routine laboratory practice.

DOI: https://doi.org/10.1016/j.aca.2024.343092
PLoS One. 2024 ;19(9): e0309802

Optimized method development and validation for determining donepezil in rat plasma: A liquid-liquid extraction, LC-MS/MS, and design of experiments approach.

Ye Bin Shin, Jin Hwan Kim, Min Kyeong Kwon, Jin Hyuk Myung, Dong Geon Lee, Sung Giu Jin, Myung Joo Kang, Yong Seok Choi.

Donepezil (DPZ), a piperidine-based reversible cholinesterase inhibitor, finds extensive use in treating Alzheimer's disease (AD). Originally designed as an oral formulation, DPZ encounters drawbacks such as a brief duration of action and reduced treatment effectiveness in elderly patients with memory impairment or difficulty swallowing medications. To address these issues and improve patient compliance, researchers are actively exploring alternative DPZ formulations. Consequently, reliable methods are necessary to quantitate DPZ in biological samples for in vivo assessment. Therefore, we propose an efficient, sensitive, wide-dynamic, and cost-effective method for quantitating DPZ in rat plasma. Our method employs liquid-liquid extraction (LLE) followed by liquid chromatography and tandem mass spectrometry, enabling in vivo evaluation of novel DPZ formulations. Notably, our method requires only 20 μL of rat plasma and employs icopezil as the internal standard-a cost-effective compound with chemical similarity to DPZ. We meticulously optimized LLE conditions, taking into account factor interactions through design of experiments (DOE). Our rapid and straightforward extraction and purification involved using 500 μL of pure methyl tert-butyl ether to extract DPZ from the sample within five minutes. The dynamic range of the method extends from 0.5 ng/mL to 1,000 ng/mL, demonstrating excellent sensitivity and suitability for pharmacokinetic studies across diverse DPZ formulations. Following the FDA guidelines, we rigorously validated the developed method, evaluating selectivity, linearity (with a coefficient of determination ≥0.9999), accuracy (ranging from 96.0% to 109.6%), precision (≤13.9%), matrix effect (92.2% to 103.8%), recovery (98.5% to 106.8%), the lower limit of quantitation (0.5 ng/mL), and stability. Finally, we effectively employed the validated method for the long-term pharmacokinetic assessment of a DPZ formulation. We expect that this approach will make a substantial contribution to the advancement of new DPZ formulations, ultimately benefiting individuals afflicted by AD.

DOI: https://doi.org/10.1371/journal.pone.0309802
J Chromatogr A. 2024 Aug 27. pii: S0021-9673(24)00691-5. [Epub ahead of print]1734 465317

Targeted metabolomics assisted rapid screening and characterization of aristolochic acids and their DNA adducts in aristolochia plants by ultra-high performance liquid chromatography coupled with ion mobility quadrupole time-of-flight mass spectrometry.

Ying Shi, Yi-Wen Wu, Qian-Xue Shen, Jun Cao.

  Aristolochic acids are one of the major compounds in aristolochia plants, which are nephrotoxic and carcinogenic. A method was established for the detection and identification of aristolochic acids and their DNA adducts in four different herbs using ultra-high performance liquid chromatography-ion mobility quadrupole time-of flight mass spectrometry. Solid phase extraction conditions were optimized to improve the sensitivity of the experiment by using 40 mg of C18 as adsorbent and 100 μL ethanol as elution solvent. At a collision energy of 10-40 eV, these compounds and cleavage patterns were precisely identified and analyzed by secondary fragmentation and collision cross section values. The obtained mass spectrometry data were then analyzed by targeted metabolomics, including principal component analysis, partial least squares-discriminant analysis and hierarchical clustering analysis, and importing the samples in the established model, the confidence values can reach 0.61 and 0.76. All in all, this method can provide a useful tool for the detection of aristolochic acids and deoxyribonucleic acid adducts. In conclusion, this method was successfully used for the detection and identification of aristolochic acids and their DNA adducts.

Keywords:  Aristolochic acids; DNA adducts; Ion mobility quadrupole time-of-flight mass spectrometry; Solid phase extraction; Targeted metabolomics; Ultra-high performance liquid chromatography

DOI:  https://doi.org/10.1016/j.chroma.2024.465317
J Anal Toxicol. 2024 Aug 06. pii: bkae068. [Epub ahead of print]

Development and validation of a simple chromatographic method to screen oral fluid samples for drugs in DUID investigations.

Gregory G Sarris, Dustin L Abbott, Tiffany M Moreno, Kelly J Maychack, Jennifer F Limoges.

A simple and rapid qualitative chromatographic method with a unique extraction approach was developed and validated to screen oral fluid samples for 31 compounds in driving under the influence of drugs investigations. The scope and sensitivity of the method meets or exceeds Tier I recommendations established by the National Safety Council's Alcohol, Drugs and Impairment Division. Since this is a targeted chromatographic screen (rather than an immunoassay), cutoffs were set to match the confirmation levels in the recommendations. Sample preparation involved a single-step liquid-liquid extraction procedure, using a mixture of methyl tert-butyl ether, isopropanol, and hexane and was applied to samples collected with the QuantisalTM device. Instrument analysis was conducted by liquid chromatography-tandem mass spectrometry, using a Restek RaptorTM biphenyl column for chromatographic separations and a total run time of 8 min. Validation results met all requirements of ANSI/ASB Standard 036 (1st edition)-Standard Practices for Method Validation in Forensic Toxicology.

DOI: https://doi.org/10.1093/jat/bkae068