bims-metlip 2024-10-13 papers

bims-metlip

Biomed News

on Methods and protocols in metabolomics and lipidomics

Issue of 2024–10–13
twenty papers selected by
Sofia Costa, Matterworks

A validated LC-MS/MS method for the simultaneous quantification of iothalamate and hippuran in serum and urine for non-radioactive kidney function assessment.
Development of a Versatile High-through-put Oligonucleotide LC-MS Method to Accelerate Drug Discovery.
Insights into predicting small molecule retention times in liquid chromatography using deep learning.
Mobile Phase Contaminants Affect Neutral Lipid Analysis in LC-MS-Based Lipidomics Studies.
Evaluating protocols for reproducible targeted metabolomics by NMR.
High-Performance Liquid Chromatography-Tandem Mass Spectrometry Method Development and Validation for Simultaneous Determination of Seven Nitrosamine and Azidomethyl-Biphenyl-Tetrazole Impurities in Losartan.
Detailed lipid investigation of edible seaweeds by photochemical derivatization and untargeted lipidomics.
Development of a rapid and robust hydrop interaction liquid chromatography tandem mass spectrometry method for the detection of 13 endogenous amino acids as well as trimethylamine oxide in serum and tissues of the mice.
Chemical Exposomics in Human Plasma by Lipid Removal and Large-Volume Injection Gas Chromatography-High-Resolution Mass Spectrometry.
Comprehensive Data Evaluation Methods Used in Developing the SWGDRUG Mass Spectral Reference Library for Seized Drug Identification.
Quantification of MDR-TB drug JBD0131 and its metabolite in plasma via UPLC-MS/MS: application in first-in-human study.
Advances in mass spectrometry for metabolomics: Strategies, challenges, and innovations in disease biomarker discovery.
Quantitation of the DNA-dependent protein kinase inhibitor peposertib (M3814) and metabolite in human plasma by LC-MS/MS.
Evaluation of 4 quantification methods for monitoring 16 antidepressant drugs and their metabolites in human plasma by LC-MS/MS.
Automated kapok fiber-based pipette-tip solid-phase extraction coupled with liquid chromatography-tandem mass spectrometry for rapid and sensitive analysis of tyrosine kinase inhibitors in plasma.
Interpretable dimensionality reduction and classification of mass spectrometry imaging data in a visceral pain model via non-negative matrix factorization.
Identification of organic contaminants in water and related matrices using untargeted liquid chromatography high-resolution mass spectrometry screening with MS/MS libraries.
Determination of Ibuprofen Enantiomers in Mouse Blood Using Liquid Chromatography-Tandem Mass Spectrometry and Its Application to a Pharmacokinetic Study.
Simultaneous determination of semi-essential nutrients taurine, l-carnitine and choline in infant formulas and adult/pediatric nutritional formulas by hydrophilic interaction liquid chromatography-electrospray ionization-tandem mass spectrometry.
Detection of Inverse Stable Isotopic Labeling in Untargeted Metabolomic Data.

J Chromatogr B Analyt Technol Biomed Life Sci. 2024 Sep 28. pii: S1570-0232(24)00338-6. [Epub ahead of print]1247 124329

A validated LC-MS/MS method for the simultaneous quantification of iothalamate and hippuran in serum and urine for non-radioactive kidney function assessment.

Abdulfataah A A Mohamed, Peter Walland, Jasper Stevens, Marco van Londen, Hiddo J L Heerspink, Ron T Gansevoort, Nico C van de Merbel.

  A novel liquid chromatography-tandem mass spectrometry method is described for the quantitative determination of the kidney function markers iothalamate and hippuran in human serum and urine. It is based on protein precipitation with methanol followed by dilution of the supernatant for serum and simple dilution for urine. The polar analytes are chromatographically separated by a 6.5-min gradient on a low-ligand density reversed-phase column; detection is performed by electrospray ionization tandem mass spectrometry in the positive ion mode against stable-isotope labeled internal standards. The results of a thorough method validation show that iothalamate and hippuran can be simultaneously quantified in the concentration ranges 0.500-30.0 ng/mL and 10.0-5000 ng/mL for serum and urine, respectively, with values for CV and absolute bias not exceeding 10 %, and with sufficient stability in all relevant matrices and solvents. The method was successfully applied for the analysis of serum and urine samples of multiple individuals who received both iothalamate and hippuran.

Keywords:  ERPF; Exogenous filtration markers; Hippuran; Iothalamate; Kidney function; LC-MS/MS; Non-radioactive; Validation; mGFR

DOI:  https://doi.org/10.1016/j.jchromb.2024.124329
AAPS PharmSciTech. 2024 Oct 10. 25(7): 239

Development of a Versatile High-through-put Oligonucleotide LC-MS Method to Accelerate Drug Discovery.

Changhong Yun, Hyun Chong Woo, Ditte Lovatt, Craig A Parish, Daniel S Spellman, Honglue Shen.

  Liquid chromatography-mass spectrometry (LC-MS) is an effective tool for high-throughput quantification of oligonucleotides that is crucial for understanding their biological roles and developing diagnostic tests. This paper presents a high-throughput LC-MS/MS method that may be versatilely applied for a wide range of oligonucleotides, making it a valuable tool for rapid screening and discovery. The method is demonstrated using an in-house synthesized MALAT-1 Antisense oligonucleotide (ASO) as a test case. Biological samples were purified using a reversed liquid-liquid extraction process automated by a liquid handling workstation and analyzed with ion-pairing LC-MS/MS. The assay was evaluated for sensitivity (LLOQ = 2 nM), specificity, precision, accuracy, recovery, matrix effect, and stability in rat cerebrospinal fluid (CSF) and plasma. Besides some existing considerations such as column selection, ion-pairing reagent, and sample purification, our work focused on the following four subtopics: 1) selecting the appropriate Multiple Reaction Monitoring (MRM) transition to maximize sensitivity for trace-level ASO in biological samples; 2) utilizing a generic risk-free internal standard (tenofovir) to avoid crosstalk interference from the oligo internal standard commonly utilized in the LC-MS assay; 3) automating the sample preparation process to increase precision and throughput; and 4) comparing liquid-liquid extraction (LLE) and solid-phase extraction (SPE) as sample purification methods in oligo method development. The study quantified the concentration of MALAT-1 ASO in rat CSF and plasma after intrathecal injection and used the difference between the two matrices to evaluate the injection technique. The results provide a solid foundation for further internal oligonucleotide discovery and development.

Keywords:  LC–MS; crosstalk-free internal standard; high-through-put; oligonucleotide (Oligo); sensitivity improvement

DOI:  https://doi.org/10.1208/s12249-024-02934-3
J Cheminform. 2024 Oct 07. 16(1): 113

Insights into predicting small molecule retention times in liquid chromatography using deep learning.

Yuting Liu, Akiyasu C Yoshizawa, Yiwei Ling, Shujiro Okuda.

  In untargeted metabolomics, structures of small molecules are annotated using liquid chromatography-mass spectrometry by leveraging information from the molecular retention time (RT) in the chromatogram and m/z (formerly called ''mass-to-charge ratio'') in the mass spectrum. However, correct identification of metabolites is challenging due to the vast array of small molecules. Therefore, various in silico tools for mass spectrometry peak alignment and compound prediction have been developed; however, the list of candidate compounds remains extensive. Accurate RT prediction is important to exclude false candidates and facilitate metabolite annotation. Recent advancements in artificial intelligence (AI) have led to significant breakthroughs in the use of deep learning models in various fields. Release of a large RT dataset has mitigated the bottlenecks limiting the application of deep learning models, thereby improving their application in RT prediction tasks. This review lists the databases that can be used to expand training datasets and concerns the issue about molecular representation inconsistencies in datasets. It also discusses the application of AI technology for RT prediction, particularly in the 5 years following the release of the METLIN small molecule RT dataset. This review provides a comprehensive overview of the AI applications used for RT prediction, highlighting the progress and remaining challenges. SCIENTIFIC CONTRIBUTION: This article focuses on the advancements in small molecule retention time prediction in computational metabolomics over the past five years, with a particular emphasis on the application of AI technologies in this field. It reviews the publicly available datasets for small molecule retention time, the molecular representation methods, the AI algorithms applied in recent studies. Furthermore, it discusses the effectiveness of these models in assisting with the annotation of small molecule structures and the challenges that must be addressed to achieve practical applications.

Keywords:  Deep learning; Liquid chromatography; MassBank; PredRet; QSRR; RepoRT; Retention time prediction; SMRT; Small molecules; Untargeted metabolomics

DOI:  https://doi.org/10.1186/s13321-024-00905-1
J Am Soc Mass Spectrom. 2024 Oct 07.

Mobile Phase Contaminants Affect Neutral Lipid Analysis in LC-MS-Based Lipidomics Studies.

Joshua A Roberts, Angela S Radnoff, Aleksandra Bushueva, Jocelyn A Menard, Karl V Wasslen, Meaghan Harley, Jeffrey M Manthorpe, Jeffrey C Smith.

  Lipidomics is a well-established field, enabled by modern liquid chromatography mass spectrometry (LC-MS) technology, rapidly generating large amounts of data. Lipid extracts derived from biological samples are complex, and most spectral features in LC-MS lipidomics data sets remain unidentified. In-depth analyses of commercial triacylglycerol, diacylglycerol, and cholesterol ester standards revealed the expected ammoniated and sodiated ions as well as five additional unidentified higher mass peaks with relatively high intensities. The identities and origin of these unknown peaks were investigated by modifying the chromatographic mobile-phase components and LC-MS source parameters. Tandem MS (MS/MS) of each unknown adduct peak yielded no lipid structural information, producing only an intense ion of the adducted species. The unknown adducts were identified as low-mass contaminants originating from methanol and isopropanol in the mobile phase. Each contaminant was determined to be an alkylated amine species using their monoisotopic masses to calculate molecular formulas. Analysis of bovine liver extract identified 33 neutral lipids with an additional 73 alkyl amine adducts. Analysis of LC-MS-grade methanol and isopropanol from different vendors revealed substantial alkylated amine contamination in one out of three different brands that were tested. Substituting solvents for ones with lower levels of alkyl amine contamination increased lipid annotations by 36.5% or 27.4%, depending on the vendor, and resulted in >2.5-fold increases in peak area for neutral lipid species without affecting polar lipid analysis. These findings demonstrate the importance of solvent selection and disclosure for lipidomics protocols and highlight some of the major challenges when comparing data between experiments.

Keywords:  HPLC; LC-MS-grade solvents; contaminants; informatics; lipidomics; mass spectrometry; neutral lipids; untargeted lipidomics

DOI:  https://doi.org/10.1021/jasms.4c00320
Analyst. 2024 Oct 08.

Evaluating protocols for reproducible targeted metabolomics by NMR.

Darcy Cochran, Panteleimon G Takis, James L Alexander, Benjamin H Mullish, Nick Powell, Julian R Marchesi, Robert Powers.

Metabolomics aims to study the downstream effects of variables like diet, environment, or disease on a given biological system. However, inconsistencies in sample preparation, data acquisition/processing protocols lead to reproducibility and accuracy concerns. A systematic study was conducted to assess how sample preparation methods and data analysis platforms affect metabolite susceptibility. A targeted panel of 25 metabolites was evaluated in 69 clinical metabolomics samples prepared following three different protocols: intact, ultrafiltration, and protein precipitation. The resulting metabolic profiles were characterized by 1D 1H nuclear magnetic resonance (NMR) spectroscopy and analyzed with Chenomx v8.3 and SMolESY software packages. Greater than 90% of the metabolites were extracted more efficiently using protein precipitation than filtration, which aligns with previously reported results. Additionally, analysis of data processing software suggests that metabolite concentrations were overestimated by Chenomx batch-fitting, which only appears reliable for determining relative fold changes rather than absolute quantification. However, an assisted-fit method provided sufficient guidance to achieve accurate results while avoiding a time-consuming fully manual-fitting approach. By combining our results with previous studies, we can now provide a list of 5 common metabolites [2-hydroxybutyrate (2-HB), choline, dimethylamine (DMA), glutamate, lactate] with a high degree of variability in reported fold changes and standard deviations that need careful consideration before being annotated as potential biomarkers. Our results show that sample preparation and data processing package critically impact clinical metabolomics study success. There is a clear need for an increased degree of standardization and harmonization of methods across the metabolomics community to ensure reliable outcomes.

DOI: https://doi.org/10.1039/d4an01015a
J Sep Sci. 2024 Oct;47(19): e202400277

High-Performance Liquid Chromatography-Tandem Mass Spectrometry Method Development and Validation for Simultaneous Determination of Seven Nitrosamine and Azidomethyl-Biphenyl-Tetrazole Impurities in Losartan.

Nguyen Minh Luan, Vo Thi Kim Khuyen, Nguyen Duc Tuan.

  Nitrosamine-related impurities (N-nitrosomethylamino butyric acid [NMBA], N-nitrosodiethylamine [NDEA], N-nitrosodiisopropylamine [NDIPA], N-nitrosomethylphenylamine [NMPA], N-nitrosodibutylamine [NDBA], N-nitrosodimethylamine [NDMA], and N-nitrosoethylisopropylamine [NEIPA]) and 5-[4'-(azidomethyl)-[1,1'-biphenyl]-2-yl]-2H-tetrazole (AZBT) formed during the manufacture of sartan medicines have been classified into human mutagens and carcinogens after long-term treatment. The study developed a simple, economical but highly sensitive procedure for the simultaneous quantification of seven nitrosamines and AZBT impurities in sartan pharmaceuticals. After extraction with methanol (MeOH) 50%, the compounds were analyzed with a reversed-phase liquid chromatography-tandem mass spectroscopy with atmospheric-pressure chemical ionization (APCI) mode (APCI[+] for nitrosamines and APCI[-] for AZBT), selected reaction monitoring, C18 column, gradient elution with 0.1% formic acid in water and in MeOH, respectively. The validated procedure obtained high extraction efficiency (>90%), wide linear range (0.2-50.0 ng/mL NMBA, NDEA, NDIPA, NMPA, and NDBA; 0.5-50.0 ng/mL NDMA and NEIPA; 2.0-100 ng/mL AZBT), limit of quantification < 10% of the acceptance level, recovery range of 85%-115% with relative standard deviation < 15% and minimum matrix effects for all impurities. The procedure was applied to test 16 commercial losartan samples. As a result, eight samples contained AZBT within the current regulatory limits, but no nitrosamine impurities were detected in all samples.

Keywords:  atmospheric‐pressure chemical ionization | azidomethyl‐biphenyl‐tetrazole | impurities | losartan | method validation | N‐nitrosamines

DOI:  https://doi.org/10.1002/jssc.202400277
Anal Bioanal Chem. 2024 Oct 11.

Detailed lipid investigation of edible seaweeds by photochemical derivatization and untargeted lipidomics.

Carmela Maria Montone, Chiara Cavaliere, Andrea Cerrato, Aldo Laganà, Susy Piovesana, Enrico Taglioni, Anna Laura Capriotti.

  Seaweeds are macrophytic algae that have been gaining interest as alternative healthy foods, renewable drug sources, and climate change mitigation agents. In terms of their nutritional value, seaweeds are renowned for their high content of biologically active polyunsaturated fatty acids. However, little is known about the regiochemistry-the geometry and position of carbon-carbon double bonds-of free and conjugated fatty acids in seaweeds. In the present work, a detailed characterization of the seaweed lipidome was achieved based on untargeted HRMS-based analysis and lipid derivatization with a photochemical aza-Paternò-Büchi reaction. A triple-data processing strategy was carried out to achieve high structural detail on the seaweed lipidome, i.e., (i) a first data processing workflow with all samples for aligning peak and statistical analysis that led to the definition of lipid sum compositions (e.g., phosphatidylglycerol (PG) 34:1), (ii) a second data processing workflow in which the samples of each seaweed were processed separately to annotate molecular lipids with known fatty acyl isomerism (e.g., PG 16:0_18:1), and (iii) the annotation of lipid regioisomers following MS/MS annotation of the lipid derivatives obtained following the aza-Paternò-Büchi reaction (e.g., PG 16:0_18:1 ω-9). Once the platform was set up, the lipid extracts from 8 seaweed species from different seaweed families were characterized, describing over 900 different lipid species, and information on the regiochemistry of carbon-carbon double bonds uncovered unknown peculiarities of seaweeds belonging to different families. The overall analytical approach helped to fill a gap in the knowledge of the nutritional composition of seaweeds.

Keywords:  Aza-Paternò–Büchi; Carbon–carbon double bonds; Data processing; Fatty acids; High-resolution mass spectrometry

DOI:  https://doi.org/10.1007/s00216-024-05573-6
Biomed Chromatogr. 2024 Oct 10. e6010

Development of a rapid and robust hydrop interaction liquid chromatography tandem mass spectrometry method for the detection of 13 endogenous amino acids as well as trimethylamine oxide in serum and tissues of the mice.

Didi Hu, Xudong Liu, Ying Yao, Shijie Wei, Hongyan Ji, Yang Yang, Jing Chen, Linwei Chen.

  This work aimed to establish an HILIC-MS/MS method to simultaneously determine the levels of 13 endogenous amino acids and trimethylamine oxide in the biological samples from the mice. Electrospray ion source was used for the analysis of mass spectrometry. The 20 min separation was applied in a Dikma Inspire Hilic column (2.1 × 100.0 mm, 3 μM). Positive ion mode under an MRM model gave a satisfying response value. The limits of quantitation were evaluated by accuracy from -12.59% to 7.89% and precision from 1.77% to 14.00% as well as acceptable interday and intraday precision, matrix effect, recovery, and stability. Later, the assay was successfully used to measure the concentrations of the determinands in the biological samples. Individual and tissue distribution differences for these metabolites were observable. The amino acids had a consistent highest content in the spleens, while the lowest levels were found in the livers. Alanine was the most abundant amino acid in the serum, and taurine kept the highest content in all of the tissues. Trimethylamine oxide remained low level, especially in the liver samples.

Keywords:  LC–MS/MS; TMAO; endogenous amino acids; hydrophilia HILIC column; simultaneous analysis

DOI:  https://doi.org/10.1002/bmc.6010
Environ Sci Technol. 2024 Oct 08. 58(40): 17592-17605

Chemical Exposomics in Human Plasma by Lipid Removal and Large-Volume Injection Gas Chromatography-High-Resolution Mass Spectrometry.

Hongyu Xie, Kalliroi Sdougkou, Bénilde Bonnefille, Stefano Papazian, Ingvar A Bergdahl, Panu Rantakokko, Jonathan W Martin.

  For comprehensive chemical exposomics in blood, analytical workflows are evolving through advances in sample preparation and instrumental methods. We hypothesized that gas chromatography-high-resolution mass spectrometry (GC-HRMS) workflows could be enhanced by minimizing lipid coextractives, thereby enabling larger injection volumes and lower matrix interference for improved target sensitivity and nontarget molecular discovery. A simple protocol was developed for small plasma volumes (100-200 μL) by using isohexane (H) to extract supernatants of acetonitrile-plasma (A-P). The HA-P method was quantitative for a wide range of hydrophobic multiclass target analytes (i.e., log Kow > 3.0), and the extracts were free of major lipids, thereby enabling robust large-volume injections (LVIs; 25 μL) in long sequences (60-70 h, 70-80 injections) to a GC-Orbitrap HRMS. Without lipid removal, LVI was counterproductive because method sensitivity suffered from the abundant matrix signal, resulting in low ion injection times to the Orbitrap. The median method quantification limit was 0.09 ng/mL (range 0.005-4.83 ng/mL), and good accuracy was shown for a certified reference serum. Applying the method to plasma from a Swedish cohort (n = 32; 100 μL), 51 of 103 target analytes were detected. Simultaneous nontarget analysis resulted in 112 structural annotations (12.8% annotation rate), and Level 1 identification was achieved for 7 of 8 substances in follow-up confirmations. The HA-P method is potentially scalable for application in cohort studies and is also compatible with many liquid-chromatography-based exposomics workflows.

Keywords:  GC-HRMS; blood plasma; chemical exposome; exposure; molecular discovery; sample preparation

DOI:  https://doi.org/10.1021/acs.est.4c05942
Anal Chem. 2024 Oct 08.

Comprehensive Data Evaluation Methods Used in Developing the SWGDRUG Mass Spectral Reference Library for Seized Drug Identification.

Weihua Ji, William E Wallace.

The mass spectral library of the Scientific Working Group for the Analysis of Seized Drugs (SWGDRUG) is the most comprehensive free reference database of its kind in the world. It provides reliable mass spectra for identification of seized drugs, their metabolites, and related forensic compounds when using gas chromatography/mass spectrometry (GC/MS). The SWGDRUG library (version 3.13) contains spectra for 3598 compounds. All spectra are evaluated by the Mass Spectrometry Data Center (MSDC) at the National Institute of Standards and Technology (NIST). Over the past few years, new evaluation methods aided by improved software have been developed. First, all chemical information, such as chemical structure and name, is confirmed. Second, the product ions in each spectrum are verified to match the compound structure using the NIST MS Interpreter software tool. Subsequently, the mass spectra are compared to the same or similar compounds across six different mass spectral reference libraries using three distinct library search methods. Additionally, the NIST Artificial Intelligence Retention Indices (AIRI) software is used to help confirm the corresponding compounds of spectra, especially for those without molecular ions. Low-quality and incorrect spectra are rejected for inclusion in the library.

DOI: https://doi.org/10.1021/acs.analchem.4c04425
Bioanalysis. 2024 Oct 07. 1-12

Quantification of MDR-TB drug JBD0131 and its metabolite in plasma via UPLC-MS/MS: application in first-in-human study.

Tiantao Gao, Xiaoxue Ou, Jia Miao, Yongping Qin.

  Aim: JBD0131, a novel anti-multidrug-resistant tuberculosis (MDR-TB) drug, can target and inhibit the synthesis of mycolic acids, which are crucial components of the cell wall of the Mycobacterium tuberculosis complex. To support the results of this clinical trial in healthy subjects, development of a specific and accurate quantification method for detecting JBD0131 and its metabolite DM131 in human plasma is needed.Materials & methods: Samples with prior added stabilizer were pretreated by protein precipitation method and the extracts were subjected to ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The m/z transitions for the precursor/product ion pairs were 402.1/273 for JBD0131, 333.1/273 for DM131 and 386.1/257 for the internal standard (IS).Results: This method showed good linearity from 1 to 2000 ng/ml for JBD0131 and 0.25 to 500 ng/ml for DM131 and was validated in terms of selectivity, linearity, accuracy, precision, matrix effect, recovery of pretreament and stability.Conclusion: This method was sensitive and specific for measuring the plasma concentrations of JBD0131 and its metabolites. And it was applied for the investigation of the pharmacokinetics of JBD0131 and DM131 in a clinical trial.

Keywords:  JBD0131 and metabolite; UPLC-MS/MS; multidrug-resistant tuberculosis; pharmacokinetics; stabilizer

DOI:  https://doi.org/10.1080/17576180.2024.2404311
Biomed Chromatogr. 2024 Oct 07. e6019

Advances in mass spectrometry for metabolomics: Strategies, challenges, and innovations in disease biomarker discovery.

Nikhil Titkare, Sachin Chaturvedi, Sapan Borah, Nitish Sharma.

  Mass spectrometry (MS) plays a crucial role in metabolomics, especially in the discovery of disease biomarkers. This review outlines strategies for identifying metabolites, emphasizing precise and detailed use of MS techniques. It explores various methods for quantification, discusses challenges encountered, and examines recent breakthroughs in biomarker discovery. In the field of diagnostics, MS has revolutionized approaches by enabling a deeper understanding of tissue-specific metabolic changes associated with disease. The reliability of results is ensured through robust experimental design and stringent system suitability criteria. In the past, data quality, standardization, and reproducibility were often overlooked despite their significant impact on MS-based metabolomics. Progress in this field heavily depends on continuous training and education. The review also highlights the emergence of innovative MS technologies and methodologies. MS has the potential to transform our understanding of metabolic landscapes, which is crucial for disease biomarker discovery. This article serves as an invaluable resource for researchers in metabolomics, presenting fresh perspectives and advancements that propels the field forward.

Keywords:  biomarker; disease; mass spectrometry; metabolomics

DOI:  https://doi.org/10.1002/bmc.6019
Biomed Chromatogr. 2024 Oct 08. e6024

Quantitation of the DNA-dependent protein kinase inhibitor peposertib (M3814) and metabolite in human plasma by LC-MS/MS.

Susan M Christner, Robert A Parise, Christopher J Bakkenist, S Lindsey Davis, Ye Feng, Timothy Synold, Steven Gore, Jan H Beumer.

  The DNA-dependent protein kinase (DNA-PK) is an abundant nuclear protein that mediates DNA double-strand break repair by nonhomologous end joining (NHEJ). As such, DNA-PK is critical for V(D)J recombination in lymphocytes and for survival in cells exposed to ionizing radiation and clastogens. Peposertib (M3814) is a small molecule DNA-PK inhibitor currently in preclinical and clinical development for cancer treatment. We have developed a high-performance liquid chromatography-mass spectrometry method for quantitating peposertib and its metabolite in 0.1 mL human plasma. After MTBE liquid-liquid extraction, chromatographic separation was achieved with a Phenomenex Synergi polar reverse phase (4 μm, 2 × 50 mm) column and a gradient of 0.1% formic acid in acetonitrile and water over an 8 min run time. Mass spectrometric detection was performed on an ABI SCIEX 4000 with electrospray, positive-mode ionization. The assay was linear from 10 to 3000 ng/mL for peposertib and 1-300 ng/mL for the metabolite and proved to be both accurate (97.3%-103.7%) and precise (<8.9%CV) fulfilling criteria from the Food and Drug Administration (FDA) guidance on bioanalytical method validation. This liquid chromatography-tandem mass spectroscopy (LC-MS/MS) assay will support several ongoing clinical studies by defining peposertib pharmacokinetics.

Keywords:  DNA‐PK; assay; chromatography; peposertib; tandem mass spectrometry; validation

DOI:  https://doi.org/10.1002/bmc.6024
J Pharmacol Toxicol Methods. 2024 Oct 07. pii: S1056-8719(24)00078-9. [Epub ahead of print] 107568

Evaluation of 4 quantification methods for monitoring 16 antidepressant drugs and their metabolites in human plasma by LC-MS/MS.

Lingjiao Wang, Mengqiang Zhao, Jiao Li, Hongtao Xu, Yang Song, Yuanyuan Zhao, Jing Yu, Chunhua Zhou.

   BACKGROUND: Therapeutic drug monitoring for antidepressants (ADs) is vital due to the potentially serious consequences and disputes related to medical events. Therefore, we created a quick and convenient analysis way for separation and quantification of ADs.
METHODS: To ensure quantitative stability, we divided the 16 ADs or their metabolites into 4 pools (AD1-AD4), considering the hospital frequency that the clinician prescribed, the physicochemical properties of medicines, and the calibration range of selected ADs. After precipitation with methanol, the analytes were eluted for at least 3.5 min on a BEH C18 analytical column by different gradient elution methods.
RESULTS: The LLOQ and LOD were 1.25-10 ng/mL and 0.42-5 ng/mL, respectively. High precision (<12 %) and accuracy (87.07-111.47 %) were demonstrated by quality control samples both within and between days. All the compounds were stable at room temperature and within -80 °C.
CONCLUSION: The method is of wide clinical and laboratory interest due to simpler sample cleanup, shorter chromatographic run times, and wider calibration range compared to other methods.

Keywords:  Analysis methods; Antidepressant drugs; LC-MS/MS; Therapeutic drug monitoring

DOI:  https://doi.org/10.1016/j.vascn.2024.107568
J Chromatogr A. 2024 Oct 05. pii: S0021-9673(24)00794-5. [Epub ahead of print]1736 465420

Automated kapok fiber-based pipette-tip solid-phase extraction coupled with liquid chromatography-tandem mass spectrometry for rapid and sensitive analysis of tyrosine kinase inhibitors in plasma.

Qianqian Wang, Yuanyuan Zheng, Bowen Deng, Di Chen, Liuqun Jia, Nian Shi.

  This study delineates the development of a novel automated pipette-tip solid-phase extraction (SPE) methodology, employing kapok fiber as a naturally efficient and cost-effective adsorbent for the selective extraction of eleven tyrosine kinase inhibitors (TKIs) from plasma. The uniqueness of this method lies in its assembly, where kapok fibers are ingeniously wrapped around a stainless-steel spring within the pipette tip, ensuring an obstruction-free central space for effortless solution aspiration and dispensation. This design significantly minimizes backpressure, enhancing operational efficiency and ensuring compatibility with pipettors, including the implementation of an electric pipettor to streamline the sample preparation process and facilitate automation. The method's analytical performance, rigorously validated through liquid chromatography-tandem mass spectrometry, exhibits outstanding linearity in ranges of 0.1/0.5-200 ng mL-1 (R² > 0.993), commendable accuracy (86.3%-114.8%), and consistent precision (3.4-11.3%), alongside remarkably low detection limits that span from 0.024 to 0.130 ng mL-1. The assembly of kapok fiber within the pipette tip, in this unique configuration, results in a practical, cost-effective, eco-friendly, and automated pipette-tip SPE method. This innovation signifies a significant advancement in bioanalytical methodologies, offering an efficient and sustainable approach for extracting analytes from complex biological samples. This process notably enhances both the sensitivity and selectivity of subsequent instrumental analyses.

Keywords:  Kapok fiber; LC-MS/MS; Pipette-tip solid-phase extraction; Plasma; Tyrosine kinase inhibitors

DOI:  https://doi.org/10.1016/j.chroma.2024.465420
PLoS One. 2024 ;19(10): e0300526

Interpretable dimensionality reduction and classification of mass spectrometry imaging data in a visceral pain model via non-negative matrix factorization.

Kasun Pathirage, Aman Virmani, Alison J Scott, Richard J Traub, Robert K Ernst, Reza Ghodssi, Behtash Babadi, Pamela Ann Abshire.

Mass spectrometry imaging (MSI) is a powerful scientific tool for understanding the spatial distribution of biochemical compounds in tissue structures. In this paper, we introduce three novel approaches in MSI data processing to perform the tasks of data augmentation, feature ranking, and image registration. We use these approaches in conjunction with non-negative matrix factorization (NMF) to resolve two of the biggest challenges in MSI data analysis, namely: 1) the large file sizes and associated computational resource requirements and 2) the complexity of interpreting the very high dimensional raw spectral data. There are many dimensionality reduction techniques that address the first challenge but do not necessarily result in readily interpretable features, leaving the second challenge unaddressed. We demonstrate that NMF is an effective dimensionality reduction algorithm that reduces the size of MSI datasets by three orders of magnitude with limited loss of information, yielding spatial and spectral components with meaningful correlation to tissue structure that may be used directly for subsequent data analysis without the need for additional clustering steps. This analysis is demonstrated on an MSI dataset from female Sprague-Dawley rats for an animal model of comorbid visceral pain hypersensitivity (CPH). We find that high-dimensional MSI data (∼ 100,000 ions per pixel) can be reduced to 20 spectral NMF components with < 20% loss in reconstruction accuracy. The resulting spatial NMF components are reproducible and correlate well with H&E-stained tissue images. These components may also be used to generate images with enhanced specificity for different tissue types. Small patches of NMF data (i.e., 20 spatial NMF components over 20 × 20 pixels) provide an accuracy of ∼ 87% in classifying CPH vs naïve control subjects. This paper presents the novel data processing methodologies that were used to produce these results, encompassing novel data processing pipelines for data augmentation to support training for classification, ranking of features according to their contribution to classification, and image registration to enhance tissue-specific imaging.

DOI: https://doi.org/10.1371/journal.pone.0300526
Chemosphere. 2024 Oct 05. pii: S0045-6535(24)02389-0. [Epub ahead of print]366 143489

Identification of organic contaminants in water and related matrices using untargeted liquid chromatography high-resolution mass spectrometry screening with MS/MS libraries.

Peter Tarábek, Nataliia Leonova, Olga Konovalova, Michal Kirchner.

  Nontargeted and suspect screening with liquid chromatography-high resolution mass spectrometry (LC-HRMS) has become an indispensable tool for quality assessment in the aquatic environment - complementary to targeted analysis of organic (micro)contaminants. An LC-HRMS method is presented, suitable for the analysis of a wide variety of water related matrices: surface water, groundwater, wastewater, sediment and sludge, including extracts from passive samplers and on-site solid phase enrichment, while focusing on the data processing aspect of the method. A field study is included to demonstrate the practical application and versatility of the whole process. HRMS/MS data were recorded following LC separation in both (ESI) positive and negative ionization modes using data dependent as well as data independent acquisition. Two vendor (Agilent's Personal Compound Database and Library and from National Institute of Standards and Technology) and one open (MassBank/EU) tandem mass spectral libraries were utilized for the identification of compounds via mass spectral match. The development of a novel software tool for parsing, grouping and reduction of MS/MS features in data files converted to mascot generic format (MGF) helped to substantially decrease the amount of time and effort needed for MS library search. While applying the method, in the course of the entire field study, 18771 detections (from 870 individual compounds) in total were recorded in 275 samples, resulting in 68.3 identified compounds per sample, on average. Among the top ten most frequently detected contaminants across all samples and sample types were pharmaceutical compounds carbamazepine, 4-acetamidoantipyrine, 4-formylaminoantipyrine, tramadol, lamotrigine and phenazone and industrial contaminants toluene-2-sulfonamide, tolytriazole, tris(2-butoxyethyl) phosphate and benzotriazole. Exploratory data analysis methods and tools enabled us to discover organic pollutant occurrence patterns within the comprehensive sets of qualitative data collected from various projects between the years 2018-2023. The results may be used as valuable inputs for future water quality monitoring programs.

Keywords:  Emerging contaminants; Environmental analysis; LC-HRMS; Non-target screening; Tandem mass spectral libraries; Water quality

DOI:  https://doi.org/10.1016/j.chemosphere.2024.143489
Chirality. 2024 Oct;36(10): e23721

Determination of Ibuprofen Enantiomers in Mouse Blood Using Liquid Chromatography-Tandem Mass Spectrometry and Its Application to a Pharmacokinetic Study.

Yuexin Li, Jinglai Li, Huanhuan Yang, Huan Luo, Shiqi Liu, Furong Han, Zhipeng Ruan, Zhili Xiong.

  The aim of this study was to establish a simple, fast, and sensitive method with liquid chromatography-tandem mass spectrometry (LC-MS/MS) for simultaneously determining ibuprofen enantiomers using mouse blood in very small volumes. LC-MS/MS equipped with an electrospray ionization (ESI) source was used in negative ion mode and multiple-reaction monitoring mode. Enantiomer chromatographic separation was carried out on a Lux® 5 μm Cellulose-3 (250 × 4.6 mm, 5 μm) column at a flow rate of 0.6 mL/min. Samples were pretreated by extracting only 5 μL of blood with 40 μL of acetonitrile (containing 1.3% formic acid) so that a concentration-time profile could be completed using a single mouse. 2-(4-Propylphenyl) propanoic acid was used as an internal standard. Standard curves for each enantiomer were linear from 0.04 to 80.00 μg/mL, demonstrating a lower limit of quantitation (LLOQ) than all previously reported methods. This method was completely validated and successfully executed to investigate the pharmacokinetics of ibuprofen enantiomers after intravenous administration of racemic ibuprofen, (S)-(+)-ibuprofen, and (R)-(-)-ibuprofen in Kunming mice, respectively. The results showed that the pharmacokinetic profiles of the (R)-(-)-ibuprofen and (S)-(+)-ibuprofen were significantly different, indicating the unidirectional inversion of R-(-)-ibuprofen to (S)-(+)-ibuprofen.

Keywords:  (R)‐(−)‐ibuprofen; (S)‐(+)‐ibuprofen; LC–MS/MS; enantiomer; mouse; stereoselective pharmacokinetics

DOI:  https://doi.org/10.1002/chir.23721
J Sci Food Agric. 2024 Nov;104(14): 8553-8560

Simultaneous determination of semi-essential nutrients taurine, l-carnitine and choline in infant formulas and adult/pediatric nutritional formulas by hydrophilic interaction liquid chromatography-electrospray ionization-tandem mass spectrometry.

Myriam Bustamante-Rangel, Encarnación Rodríguez-Gonzalo, José Luis Pérez-Pavón.

   BACKGROUND: The nutritional intake of formula-fed newborns is often limited to a single source, so it must be supplemented with essential nutrients for the growth and proper development of infants. Taurine, l-carnitine, and choline are considered conditionally essential nutrients especially in newborns and infants.
RESULTS: In this work, a simple routine hydrophilic interaction liquid chromatography-electrospray ionization-tandem mass spectrometry (HILIC-ESI-MS/MS) method was developed and validated for the simultaneous determination of these semi-essential nutrients in infant and adult/pediatric milk formulas. The extraction recoveries were between 90% and 114%. Precision of the method offered relative standard deviation below 5% and 7% for intra-day and inter-day precision, respectively. The proposed method was successfully applied to quantification of taurine, l-carnitine, and choline in milk formula. The contents found were in good agreement with those provided on the product label for almost all samples.
CONCLUSION: In view of these results, it can be concluded that the developed method can be a useful approach for the simultaneous determination of taurine, l-carnitine and choline in powdered milk samples, so it can be useful in the routine quality control of this kind of samples. © 2024 The Author(s). Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Keywords:   l‐carnitine; HILIC‐ESI‐MS/MS; adult/pediatric formula; choline; infant formula; taurine

DOI:  https://doi.org/10.1002/jsfa.13682
Anal Chem. 2024 Oct 05.

Detection of Inverse Stable Isotopic Labeling in Untargeted Metabolomic Data.

Tashi C E Liebergesell, Ethan G Murdock, Aaron W Puri.

Stable isotopic labeling is a powerful tool for determining the biosynthetic origin of metabolites and for discovering natural products that incorporate precursors of interest. When isotopically substituted precursors are not available commercially or synthetically, inverse stable isotopic labeling (InverSIL) is a useful alternative. With InverSIL, an organism is grown on an isotopically substituted medium and then fed precursors of natural isotopic abundance which can be tracked by mass spectrometry, thereby bypassing issues with precursor availability. Currently, there is no automated way to identify precursor incorporation in untargeted metabolomic data using InverSIL without specifying an expected change in the mass-to-charge ratio of metabolites that have incorporated the precursor. This makes it difficult to identify unknown natural products that may incorporate portions of precursors of interest using new biochemistry or to rapidly identify incorporation of multiple precursors into different metabolites simultaneously. To address this, we developed a new, robust workflow for the automated identification of inverse labeling in untargeted metabolomic data. We then use this method to identify metabolites that incorporate para-aminobenzoic acid and different portions of l-methionine, including in the same sample, and in the process discover the likely biosynthetic origin for the C-7 and C-9 methyl groups of the pterin portion of dephosphotetrahydromethanopterin, a C1 transfer coenzyme used by methylotrophic bacteria. This workflow can be applied in the future to streamline the use of the versatile InverSIL approach for natural product and metabolism research.

DOI: https://doi.org/10.1021/acs.analchem.4c03528