bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2026–09–06
58 papers selected by
Sofia Costa, Matterworks
  1. A Robust Isotope Ratio LC-MS/MS Workflow for High-Throughput Metabolic Profiling of Bacteria.
  2. LC-MS Data Processing Using xcms.
  3. LC-MS Data Processing Using OpenMS.
  4. Metabolomics Data Processing Using the Asari Toolkit.
  5. LC-MS/MS-Based Untargeted Lipidomics Using MS-DIAL.
  6. LC-MS/MS-Based Untargeted Hydrophilic Metabolomics Using MS-DIAL.
  7. Large-Scale Metabolite Annotation in Untargeted Metabolomics Using MetDNA.
  8. Metabolomics Data Analysis with the HMDB.
  9. Development and application of a simple, high-throughput magnetic bead-assisted liquid chromatography-tandem mass spectrometry method for the quantification of vitamin K1 and vitamin K2 (menaquinone-4 and menaquinone-7) in human serum.
  10. mzmine: Unifying Mass Spectrometry Data Processing.
  11. Tandem Mass Spectral Databases and Their Use in Non-Targeted Metabolomics.
  12. Lipid and Metabolite Annotation Using Lipid Data Analyzer.
  13. Metabolomics Spectral Processing, Data Analysis, and Multiomics Integration Using MetaboAnalyst 6.0.
  14. Computational Tools for LC-IMS-MS Data Processing in Metabolomics.
  15. Heptafluorobutyl Chloroformate Derivatization Enables Molecular-Ion-Centric Metabolite Screening and Fluorine-Assisted Elemental-Composition Assignment by GC-APCI-HRMS.
  16. Collection and Purification of Secondary Metabolites from Root Exudates for LC-MS/MS Analyses.
  17. FastRet: Fast and Simple Retention Time Prediction in Liquid Chromatography.
  18. Development and ICH M10-compliant validation of an LC-MS/MS method for quantification of atirmociclib in mouse plasma and its application to preclinical pharmacokinetic studies.
  19. Simultaneous GC-MS determination of unsubstituted, hydroxy-, amino-, and hydroxy-amino short-chain fatty acids together with amino acids in biological and food samples following derivatization.
  20. A High-Throughput Workflow for High-Content Microplate-Based Assays via Mass Spectrometry Imaging.
  21. An isotope dilution-liquid chromatography-tandem mass spectrometry-based candidate reference measurement procedure for the quantification of piperacillin in human serum and plasma.
  22. Standardizing Methods for Shoot Metabolomics in Mycorrhizal Plants.
  23. Triboelectric Nanogenerator-Driven Laser Ablation Electrospray Ionization Enables Neutral Lipid Ionization and in Situ Double-Bond Localization.
  24. An Analyte-Specific LC-IMS-HRMS Framework for Enhanced Identification Confidence in Target Screening of Contaminants in Complex Matrices.
  25. Sustainable UHPLC-MS/MS assay for ultra-sensitive simultaneous quantification of amoxicillin and flucloxacillin with application to a bioequivalence study.
  26. [Development and Validation of an Analytical Method for the Determination of Diethylstilbestrol, Dienestrol, Hexestrol, and Their Conjugates in Bovine Muscle].
  27. Quantification of Disaccharide Isomers via Porous Graphitic Carbon Chromatography Coupled with Microdroplet Chemistry with Online Tandem Mass Spectrometry.
  28. Pharmacokinetic and Tissue Distribution Analysis of Scutellarin and Iso-Scutellarin From Breviscapine Injection in Rats by a Validated UPLC-MS/MS Method.
  29. Comprehensive LC-MS Metabolomics Data Processing with notame R/Bioconductor Package.
  30. Revealing Hidden Variables in DESI-Based Spatial Metabolomics: Solvent Composition and Tissue Type as Critical Drivers.
  31. mspix: A Data Format for High Pixel Count Mass Spectral Images.
  32. Boronic Acid Mass Tag Empowered Detection of Glucose for MALDI MS Imaging.
  33. Chiral Carbohydrate Adducts are Effective for Enantiomeric Ion Mobility Separations.
  34. A Streamlined Automated Liquid Handling and 96-Well Solid-Phase Extraction for Single Low-Volume Urine Aliquot Multiclass Biomarker Analysis in Human Biomonitoring.
  35. TRACE: An Integrated Isotope-Tracing Framework for Metabolite Validation and Nutrient Fate Mapping.
  36. Prediction, Targeting, and Annotation of Oxidized Lipids Using LPPtiger2 Software.
  37. Fast Diffusion-Based Metabolomics Profiling by 3D Pure Shift HSQC-DOSY NMR with COLMARvista.
  38. On-Line Three-Dimensional High-Performance Liquid Chromatographic System for the Comprehensive and Enantio/Stereoselective Determination of All Proteinogenic Amino Acids in Human Plasma and Urine.
  39. A strategy for relative quantification of chiral amines in nontargeted metabolomics via formation of fixed adduct ions.
  40. High-sensitivity quantification of angiotensin oligopeptides using methoxyacetylation coupled with LC-TIMS-qTOF/MS.
  41. Redefining reference materials for the evolving metabolomics landscape.
  42. Metabolomic Study in Ustilaginaceae with GC-MS/MS.
  43. Rapid and validated LC-APCI-MS/MS method for determination of N-nitroso vonoprazan in pharmaceutical products.
  44. MSlineaR: An R Package Assessing Linear Behavior to Improve Quality Assurance and Statistical Robustness in Untargeted Metabolomics.
  45. Optimized LC-MS/MS method for simultaneous determination of multiclass veterinary anthelmintic residues in animal-derived matrices.
  46. Development and Preliminary Application of a Method to Detect Sucralose in Placenta and Serum.
  47. Development and comparative evaluation of chemical ionization and electron ionization for GC-MS targeted metabolomics applied to the brain of a pollinating insect.
  48. Chiral HPLC in biomedical and pharmaceutical analysis: Method development challenges and application-oriented strategies.
  49. [Development of an Analytical Method for Simultaneous Determination of Deoxynivalenol and Ochratoxin A in Wheat].
  50. Metabolomics Data Analysis with TIGER.
  51. Comparability of serum folate concentration measured by a microbiological method, LC-MS/MS and immunoassay.
  52. Impact of Salt and Urine Matrices on Electrokinetic Stacking Coupled to Paper Spray Mass Spectrometry.
  53. Profiling and Identification of Novel Tiletamine Metabolites in Human Urine and Hair by Liquid Chromatography Coupled With Quadrupole-Orbitrap Mass Spectrometry.
  54. Determination of xylazine, xylazine-4-hydroxy, and 2,6-dimethylaniline in canine urine: veterinary and forensic applications in two suspected poisoning cases.
  55. Sequential MALDI and Nano-DESI MS Imaging of Lipids and Proteins on Stretched Tissue Samples.
  56. Integrating Computational Chemistry and Ion Mobility Spectrometry into Non-Targeted Analysis Workflows for the Structural Elucidation of Emerging PFAS.
  57. A valve-assisted 4-in-1 polarity-partitioned LC-QTOF-MS workflow reveals amino acid dysregulation in human chlorfenapyr poisoning.
  58. Development of a Large-Scale Serum Metabolome Relative Quantitative Method and Application for Metabolic Traits of Colon Cancer.
  1. Anal Chem. 2026 Aug 25. 98(33): 23989-23997
    A Robust Isotope Ratio LC-MS/MS Workflow for High-Throughput Metabolic Profiling of Bacteria.
    Catarina Rocha, Sergi Pujol Pinto, Sheila Ingemann Jensen, Lars Keld Nielsen, Stefano Donati.
      Stable isotope dilution mass spectrometry (IDMS) has become a cornerstone of quantitative metabolomics, enabling accurate intracellular metabolite quantification across a range of biological systems. However, the broader adoption of IDMS in high-throughput studies remains limited by the high costs of commercially available 13C-labeled internal standards (ISs), labor-intensive in-house IS production, and the narrow applicability of existing methods to different organisms. Here, we present a robust and scalable IDMS-based LC-MS/MS workflow for the high-throughput profiling of primary metabolism in diverse bacteria. The analytical method couples ion-pairing liquid chromatography with multiple reaction monitoring (MRM) to quantify 96 intracellular metabolites in under 16 min, with an average RSD of 21%. We developed a protocol for large-scale production of high-quality 13C-labeled IS, considerably lowering the costs and labor necessary to perform high-throughput IDMS studies. We then demonstrated the applicability of the same workflow by performing relative quantification of 5 diverse bacterial species in different cultivation conditions. This work provides a versatile platform for microbial metabolomics, supporting systems biology and data-driven metabolic engineering at scale.
    DOI:  https://doi.org/10.1021/acs.analchem.5c04931
  2. Methods Mol Biol. 2026 ;3063 19-50
    LC-MS Data Processing Using xcms.
    Marilyn De Graeve, Philippine Louail, Johannes Rainer.
      Liquid chromatography-mass spectrometry (LC-MS) is a key technology in metabolomics, enabling high-throughput detection of small molecules across diverse biological samples. However, raw LC-MS data are complex, requiring careful preprocessing to ensure accurate and reproducible feature detection. This chapter introduces a step-by-step protocol for LC-MS data preprocessing using the open-source xcms package in R. Designed for users ranging from beginners to experienced analysts, the chapter outlines critical stages including data inspection, peak detection, retention time alignment, correspondence, and result export. Special attention is given to parameter optimization and diagnostic visualization to guide users in making informed decisions tailored to their specific datasets. We demonstrate the approach on human serum samples, using real-life example compounds such as proline to showcase retention time alignment and peak correspondence. By combining practical code snippets with conceptual insights, this chapter empowers researchers to harness xcms for robust, reproducible LC-MS workflows in untargeted metabolomics. Whether you are setting up your first analysis or refining an established pipeline, this chapter serves as both a tutorial and a reference for high-quality LC-MS data processing.
    Keywords:  Data processing; Liquid chromatography; Mass spectrometry; Metabolomics; Peak detection; Preprocessing; Quality control; Retention time correction; xcms
    DOI:  https://doi.org/10.1007/978-1-0716-5452-1_2
  3. Methods Mol Biol. 2026 ;3063 67-84
    LC-MS Data Processing Using OpenMS.
    Axel Walter, Eftychia E Kontou, Payam Emami, Oliver Kohlbacher.
      Liquid chromatography-mass spectrometry (LC-MS) is a cornerstone of metabolomics, enabling detailed analysis of complex biological samples. Untargeted approaches, however, face challenges in handling complex data and ensuring scalability. UmetaFlow, built on the OpenMS platform, addresses these challenges through a unique re-quantification step for low-abundance metabolites and a suite of complementary annotation tools. Available in four formats, from command-line tools to an interactive WebApp, UmetaFlow supports both high-throughput automation and manual data exploration. This chapter provides a step-by-step guide to UmetaFlow and its applications.
    Keywords:  OpenMS; UmetaFlow; Untargeted metabolomics; Workflow managers; Workflows
    DOI:  https://doi.org/10.1007/978-1-0716-5452-1_4
  4. Methods Mol Biol. 2026 ;3063 85-100
    Metabolomics Data Processing Using the Asari Toolkit.
    Joshua Mitchell, Jasmine Chong, Shuzhao Li.
      Asari is a software tool for metabolomics data processing, which is designed from the ground up to address issues in reproducibility, performance and interoperability by introducing new algorithms and data structures. It is significantly faster than other tools and offers qualities that are suitable for large-scale metabolomic and exposomic analyses. The reusable data structures and modular libraries enabled the rapid development of a full-scale pipeline that includes QA/QC, MS/MS integration, annotation, and extension to untargeted stable isotope tracing data. This chapter provides an overview of the key concepts and designs in Asari, step-by-step applications to metabolomics data processing and annotation, and resources related to both LC-MS and GC-MS data.
    Keywords:  Asari; Data processing; Metabolomics; Pipeline
    DOI:  https://doi.org/10.1007/978-1-0716-5452-1_5
  5. Methods Mol Biol. 2026 ;3063 101-123
    LC-MS/MS-Based Untargeted Lipidomics Using MS-DIAL.
    Bujinlkham Buyantogtokh, Yoshimasa Todoroki, Hiroshi Tsugawa.
      Mass spectrometry (MS) has become the cornerstone of metabolomics and lipidomics because of its high sensitivity, specificity, and ability to analyze complex biological samples. However, the data complexity necessitates the use of robust computational tools. MS-DIAL is a versatile and user-friendly software for untargeted metabolomics and lipidomic workflows. It was launched as a universal program for untargeted metabolomics and supports multiple instruments (GC/MS, GC/MS/MS, LC/MS, and LC/MS/MS) and MS vendors (Agilent, Bruker, LECO, Sciex, Shimadzu, Thermo, and Waters). Common data formats such as netCDF (AIA) and mzML can also be managed. In addition, several MSP files, including EI and MS/MS spectra, were included as a "start-up kit." Moreover, MS-DIAL has an internal version of the Fiehn lab's GC/MS database (oriented by the FAME RI index), in silico retention time, and MS/MS database for LC/MS/MS-based lipidomics. Isotope-labeled tracking can be executed using an LC/MS project. This chapter provides two detailed protocols using LC-MS/MS for hydrophilic metabolome and lipidome analyses using MS-DIAL. Each protocol covers the key steps, including raw data import, peak detection, alignment, annotation, and export. Practical tips, troubleshooting strategies, and case studies are included to enhance the reproducibility and interpretation of the results.
    Keywords:  Annotations; Curations; LC–MS/MS; Lipidomics; MS-DIAL
    DOI:  https://doi.org/10.1007/978-1-0716-5452-1_6
  6. Methods Mol Biol. 2026 ;3063 125-144
    LC-MS/MS-Based Untargeted Hydrophilic Metabolomics Using MS-DIAL.
    Yoshimasa Todoroki, Bujinlkham Buyantogtokh, Hiroshi Tsugawa.
      Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is widely used in the field of metabolomics because it enables the simultaneous detection of hundreds to thousands of metabolites in a single analysis. MS-DIAL 5 is a software platform that facilitates the analysis of mass spectrometry data, including those obtained from LC-MS/MS, and provides a function for creating molecular spectral networks. In the analysis of hydrophilic metabolites, the availability of standard compounds is limited compared with that of lipids, and the utilization of MS/MS libraries is often restricted. To address this challenge, molecular spectral networking serves as an effective strategy for extending annotations to unknown ions. In this chapter, we introduce an analytical strategy for hydrophilic metabolite analysis using MS-DIAL 5, which utilizes retention time prediction and molecular spectral networking to enhance the reliability and comprehensiveness of metabolite annotation.
    Keywords:  Hydrophilic metabolomics; LC–MS/MS; MS-DIAL; Molecular spectral network; Retention time prediction
    DOI:  https://doi.org/10.1007/978-1-0716-5452-1_7
  7. Methods Mol Biol. 2026 ;3063 189-204
    Large-Scale Metabolite Annotation in Untargeted Metabolomics Using MetDNA.
    Haosong Zhang, Zheng-Jiang Zhu.
      MetDNA ( http://metdna.zhulab.cn/ ) is a network-based computational platform for large-scale metabolite annotation in untargeted metabolomics using liquid chromatography-mass spectrometry (LC-MS). By using a metabolic reaction network (MRN) to guide recursive MS2 spectral similarity matching, MetDNA can accurately annotate both known and unknown metabolites, going beyond the limits of conventional spectral libraries. Since 2019, the platform has evolved from MetDNA to MetDNA2 and now to MetDNA3, with improvements in efficiency, coverage, and confidence in metabolite annotation for untargeted metabolomics. In this protocol, we outline best practices for data preparation, parameter configuration, and result interpretation, offering users a practical workflow to maximize the utility of MetDNA for high-confidence metabolite annotation.
    Keywords:  LC–MS; MetDNA; Metabolite annotation; Untargeted metabolomics
    DOI:  https://doi.org/10.1007/978-1-0716-5452-1_11
  8. Methods Mol Biol. 2026 ;3063 363-379
    Metabolomics Data Analysis with the HMDB.
    Yamilé López-Hernández, Prashanthi Kovur, David S Wishart.
      The Human Metabolome Database (HMDB) is a web-based resource that supports metabolite identification and interpretation for human studies. This chapter outlines five protocols: (1) identifying metabolites using mass spectrometry with retention time or collision cross-section data (MS-RT/CCS); (2) identifying metabolites using tandem mass spectrometry (MS/MS); (3) identifying metabolites using nuclear magnetic resonance (NMR); (4) comparing measured concentrations to HMDB reference values; and (5) interpreting metabolomics results via HMDB's MetaboCards and PathBank links.
    Keywords:  Data analysis; Database; Disease; Human; Metabolomics
    DOI:  https://doi.org/10.1007/978-1-0716-5452-1_18
  9. Talanta. 2026 Sep 01. pii: S0039-9140(26)01208-7. [Epub ahead of print]312(Pt C): 130552
    Development and application of a simple, high-throughput magnetic bead-assisted liquid chromatography-tandem mass spectrometry method for the quantification of vitamin K1 and vitamin K2 (menaquinone-4 and menaquinone-7) in human serum.
    Yinglan Zhu, Yu Zhou, Jing Du, Yanan Wang, Lingli Yan, Yangxiao Zhou, Jun Xia.
      Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has become the preferred method for vitamin K quantification, yet conventional workflows are labor-intensive and scale poorly. We developed and validated a simple, high-throughput automated magnetic bead-assisted LC-MS/MS method for simultaneous quantification of vitamin K1 (VK1), menaquinone-4 (MK-4), and menaquinone-7 (MK-7) in human serum according to Clinical and Laboratory Standards Institute (CLSI) C62 (2nd ed.) guidelines. This method used MSi050/PLS magnetic beads (5 mg/mL) for extraction via methanol loading and acetonitrile elution, requiring only 100 μL of serum to complete sample pretreatment within 17 min. All three calibration curves were linear from 0.20 to 10.00 ng/mL (r > 0.99), with a lower limit of quantification of 0.10 ng/mL. Total coefficients of variation for VK1, MK-4, and MK-7 ranged from 1.98% to 3.54%, 2.53% to 3.73%, and 2.77% to 4.59%, respectively. The recoveries of VK1, MK-4, and MK-7 were 94.8% to 112%, 98.0% to 113%, and 90.3% to 106%, respectively. Both matrix effects and carryover met CLSI acceptance criteria. Because vitamin K2 is photosensitive, all samples were processed under light-protected conditions. Unextracted samples were stable for 14 days at -20 °C, and extracted samples were stable for 48 h at 4 °C. Additionally, our method was applied to 245 healthy volunteers to characterize serum VK distribution profiles. By integrating automated magnetic bead extraction with rapid LC-MS/MS detection, this robust strategy markedly improves analytical throughput and reproducibility while maintaining high accuracy, offering a practical solution for large-scale clinical vitamin K assessment.
    Keywords:  Liquid chromatography-tandem mass spectrometry; MK-4; MK-7; Magnetic bead extraction method; Vitamin K1
    DOI:  https://doi.org/10.1016/j.talanta.2026.130552
  10. Methods Mol Biol. 2026 ;3063 51-66
    mzmine: Unifying Mass Spectrometry Data Processing.
    Ansgar Korf, Robin Schmid, Steffen Heuckeroth, Tomáš Pluskal.
      Modern mass spectrometry (MS) experiments generate increasingly complex, multidimensional datasets across diverse analytical modalities, including liquid chromatography (LC)-MS, gas chromatography (GC)-MS, ion mobility spectrometry, and mass spectrometry imaging. Efficient analysis of such heterogeneous data has traditionally required multiple vendor-specific software tools, limiting reproducibility and integration. mzmine 4 addresses this challenge by providing a unified, vendor-neutral, and extensible software platform for comprehensive MS data processing and interpretation. Building on nearly two decades of community-driven development, mzmine 4 introduces substantial improvements in performance, scalability, and usability, enabling the routine analysis of large-scale and multimodal datasets on standard consumer hardware. The software integrates workflows for feature detection, alignment, spectral library matching, molecular networking, small molecule annotation, and advanced MS2 interpretation within a single graphical environment. New capabilities, including interactive molecular networking, guided workflow automation, enhanced visualization, and machine learning-based spectral similarity scoring, further support exploratory and reproducible data analysis. The transition to an enterprise-supported yet open innovation model ensures long-term sustainability while preserving open-source principles. Together, these advances position mzmine 4 as a comprehensive, future-ready platform for untargeted metabolomics and mass spectrometry-based research.
    Keywords:  Interactive molecular networking; Mass spectrometry data processing; Multimodal mass spectrometry; Universal mass spectrometry platform; Vendor-neutral data integration
    DOI:  https://doi.org/10.1007/978-1-0716-5452-1_3
  11. Methods Mol Biol. 2026 ;3063 159-176
    Tandem Mass Spectral Databases and Their Use in Non-Targeted Metabolomics.
    Valentina Ramundi, Michael Witting.
      Liquid chromatography-mass spectrometry (LC-MS)-based non-targeted metabolomics produces intricate datasets that need advanced tools for identifying metabolites (MetID). Metabolite annotation and identification in non-targeted metabolomics require high-quality fragmentation data from biological samples and reference libraries. Public and commercial databases, such as NIST, MassBank, MoNA, GNPS, HMDB, mzCloud, and METLIN, are vital resources for both spectral matching and providing training data for machine-learning-driven MetID tools. These libraries differ in their coverage, curation, and access models, and they are often supplemented by in-house databases that cater to specific laboratory conditions, ensuring the highest level of confidence in identifications. To maximize the benefits of MS2 libraries and ensure they work seamlessly together, we rely heavily on standardized file formats. Standard formats, such as mzML, MGF, MSP, JSON, and the MassBank format, each come with different levels of metadata richness and compatibility with various software tools. This chapter gives an overview of key MS2 libraries, discusses the strengths and weaknesses of standard data formats, and introduces R-based solutions for better integration.
    Keywords:  Data formats; MS2 libraries; Mass spectrometry; Metabolite identification; Metabolomics; R; Spectra package
    DOI:  https://doi.org/10.1007/978-1-0716-5452-1_9
  12. Methods Mol Biol. 2026 ;3063 205-225
    Lipid and Metabolite Annotation Using Lipid Data Analyzer.
    Leonida M Lamp, Jürgen Hartler, Gerhard G Thallinger.
      The Lipid Data Analyzer (LDA) is a platform-independent software tool for the automated identification and quantification of lipid species and other metabolites in both untargeted and targeted mass spectrometry (MS) data. LDA mirrors the decision-making process of trained MS experts, enabling automated, high-throughput analyses across any instrumental setup through customizable, rule-based logic. These decision rule sets represent chemical and structural logic, yielding annotation results of high reliability. Furthermore, decision rules can be easily extended to accommodate new lipid classes, adduct forms, or fragmentation mechanisms. This makes LDA particularly effective for identifying novel lipid species or structural isomers that are often missed by traditional approaches, and enables users without a bioinformatics background to easily adapt to evolving analytical protocols. Moreover, LDA supports the identification of double bond positions and other modifications, such as oxidations. Here, we present a step-by-step guide and practical tips for efficient operation of LDA, and provide an introductory discussion of common pitfalls in lipidomics data analysis.
    Keywords:  Chromatography; LDA; Lipid identification; Lipidomics; Mass spectrometry; Metabolomics; Oxidized lipids; Untargeted; double bond localization
    DOI:  https://doi.org/10.1007/978-1-0716-5452-1_12
  13. Methods Mol Biol. 2026 ;3063 293-334
    Metabolomics Spectral Processing, Data Analysis, and Multiomics Integration Using MetaboAnalyst 6.0.
    Zhiqiang Pang, Fiona Hui, Jianguo Xia.
      MetaboAnalyst is a comprehensive, user-friendly web-based platform for metabolomics data analysis and interpretation. It offers a unified analytical workflow with an intuitive interface designed to streamline data analysis for both targeted and untargeted metabolomics, while supporting integration with other omics datasets. MetaboAnalyst 6.0 represents a significant advancement toward this vision by supporting LC-MS raw spectral processing and MS2 spectral annotation. This chapter builds on our 2019 protocols, which presented 12 step-by-step procedures for statistical and functional analysis using MetaboAnalyst 4.0, with emphasis on targeted metabolomics. Here, we extend that foundation with eight new or substantially revised protocols for MetaboAnalyst 6.0, centered mainly on LC-MS untargeted metabolomics, advanced statistics, and functional analysis. The main topics covered include: Basic Protocol 1: LC-MS raw spectral processing with or without MS2 spectra Basic Protocol 2: MS2 spectral annotation Basic Protocol 3: Functional analysis of untargeted LC-MS metabolomics data Basic Protocol 4: Advanced statistical analysis for studies with multiple factors Basic Protocol 5: Dose-response analysis Basic Protocol 6: Pathway and joint-pathway analysis Basic Protocol 7: Causal analysis Basic Protocol 8: Using MetaboAnalystR for batch processing.
    Keywords:  Causal analysis; Compound identification; Covariate adjustment; Dose response analysis; LC–MS; MS/MS; Mendelian randomization; Pathway analysis; Spectral processing
    DOI:  https://doi.org/10.1007/978-1-0716-5452-1_16
  14. Methods Mol Biol. 2026 ;3063 145-157
    Computational Tools for LC-IMS-MS Data Processing in Metabolomics.
    Dylan H Ross, Nathalie Muñoz, Harsh Bhotika, Xueyun Zheng, Aivett Bilbao.
      This chapter provides resources and step-by-step processing guidelines for analyzing liquid chromatography-ion mobility spectrometry-mass spectrometry (LC-IMS-MS) data in metabolomics. The methods described here are based on open-source software and freely available executables developed at Pacific Northwest National Laboratory (PNNL), including PNNL-PreProcessor, MZA, mzapy, LipidOz, PeakQC, and IonToolPack. Importantly, the same software ecosystem is broadly applicable to IMS-MS workflows both with and without LC and includes algorithms that support other modalities such as proteomics, making it suitable for a wide range of experimental designs. The chapter is written for scientists seeking to establish reproducible workflows to analyze multidimensional metabolomics data, regardless of prior experience with IMS. Demonstrations for both Python-based programmatic data processing and graphical user interface (GUI) workflows are provided to facilitate implementation by users with different levels of computational expertise. Following these procedures, researchers can successfully process, visualize, and interpret LC-IMS-MS data using freely available software and data resources.
    Keywords:  AI; Ion mobility spectrometry; Liquid chromatography; MZA; Mass spectrometry; Metabolomics; Software; mzapy
    DOI:  https://doi.org/10.1007/978-1-0716-5452-1_8
  15. Anal Chem. 2026 Sep 01. 98(34): 24669-24676
    Heptafluorobutyl Chloroformate Derivatization Enables Molecular-Ion-Centric Metabolite Screening and Fluorine-Assisted Elemental-Composition Assignment by GC-APCI-HRMS.
    Iva Karlínová, Petr Vodrážka, Stanislav Opekar, Lucie Řimnáčová, Jan Bednář, Petra Urajová, Pavel Hrouzek, Petr Šimek, Martin Moos.
      Metabolomics enables the simultaneous monitoring of hundreds to thousands of metabolites in complex biological matrices; however, confident identification of low-abundance and unknown compounds remains challenging. Gas chromatography-mass spectrometry (GC-MS) workflows based on electron ionization (EI) often provide limited molecular-ion information because of extensive fragmentation. Here, we present a novel rapid screening workflow combining 1 min heptafluorobutyl chloroformate (HFBCF) derivatization of protic metabolites and concurrent liquid-liquid microextraction with gas chromatography-atmospheric pressure chemical ionization mass spectrometry (GC-APCI-MS). The proven HFBCF-mediated reaction produces stable heptafluorobutyl derivatives that yield abundant protonated molecular ions in the APCI mass spectra, predictable class-specific fragmentation, and characteristic fluorine-specific mass signatures. Compared with conventional full-scan GC-EI-MS, full-scan GC-APCI-MS provided up to 10-1000-fold higher sensitivity, enabling metabolite screening from extremely limited sample amounts. In low-input HeLa cell extracts, at least 100 metabolites were consistently detected from as few as 15,000 cells. Specific heptafluorobutyl-derived mass shifts and fluorine-based elemental constraints facilitated determination of the number and, in selected cases, the type of derivatized functional groups and supported elemental-composition assignment of unknown metabolites, even at mass accuracies of several tens of ppm. To aid compound annotation, we established an openly accessible database comprising more than 620 derivatizable metabolites and experimentally characterized retention and mass-spectral data for 240 reference standards. Together, these results establish HFBCF-GC-APCI-MS as a sensitive molecular-ion-centric workflow for exploratory metabolomics, enabling annotation of unknown metabolites across defined confidence levels, from standard-confirmed identifications to database-supported candidate assignments, suitable for limited biological samples.
    DOI:  https://doi.org/10.1021/acs.analchem.6c04134
  16. Methods Mol Biol. 2026 ;3045 105-112
    Collection and Purification of Secondary Metabolites from Root Exudates for LC-MS/MS Analyses.
    Javier Lidoy, Juan A López-Ráez.
      Plants communicate with their environment through the production of root exudates. These contain a variety of secondary metabolites that mediate plant interactions in the rhizosphere. Collecting these exudates without altering root structure, the metabolites, and the environmental conditions is crucial to understanding real processes occurring in our studies, enabling time-course experiments and separate analysis of roots and exudates. The present chapter shows an easy and non-destructive method to collect root exudates from intact plants, as well as their purification and concentration using C18 solid-phase extraction (SPE) columns for subsequent liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses. Interestingly, this methodology allows for repeated exudate collection over time from the same plant to efficiently recover charged metabolites, including rhizosphere signaling molecules such as strigolactones and flavonoids. We show an easy, viable, and non-destructive method for quantifying low-abundance root exudate metabolites from intact plants.
    Keywords:  C18 columns; Flavonoids; LC–MS/MS; Root exudates; Secondary metabolites; Strigolactones
    DOI:  https://doi.org/10.1007/978-1-0716-5324-1_8
  17. J Chem Inf Model. 2026 Aug 24. 66(16): 10412-10425
    FastRet: Fast and Simple Retention Time Prediction in Liquid Chromatography.
    Fadi Fadil, Tobias Schmidt, Christian Amesoeder, Simon Heckscher, Marian Schoen, Wolfram Gronwald, Peter J Oefner, Rainer Spang, Katja Dettmer.
      Feature annotation in liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics remains challenging. Retention time (RT) prediction can support candidate prioritization and improve annotation confidence. Here, we present FastRet, an R package predicting RTs using Least Absolute Shrinkage and Selection Operator (LASSO) and Boosted Regression Trees (BRT) on molecular descriptors. FastRet provides a flexible framework combining from-scratch model training, selective measuring to prioritize metabolites for remeasurement, and model adjustment to adapt existing models to changed chromatographic conditions. Model training and prediction are completed within seconds on a single CPU core, and FastRet is accessible both from the R console and through a web interface. We validated FastRet on three in-house data sets covering reversed-phase chromatography (RP; N = 458), RP-anion-exchange mixed-mode chromatography (RP-AXMM; N = 436), and hydrophilic interaction chromatography (HILIC; N = 388), plus one external HILIC data set from the Retip package (N = 970). Using a 2:1 training/test split, BRT models trained from scratch achieved a test-set coefficient of determination (R2) of 0.86, 0.66, and 0.81 for the three in-house data sets. FastRet can also adjust a model to new chromatographic conditions from a few remeasured metabolites: using 25 RP metabolites measured under six modified conditions, adjustment reached R2 of 0.74 to 0.84 on unseen metabolites, a mean 0.22 gain over from-scratch models. Compared with published methods on identical splits, FastRet showed competitive performance for de novo prediction and superior performance in low-data transfer scenarios, while generalizing to 14 external data sets (median held-out R2 0.59). FastRet is available on CRAN with the web interface hosted at https://fastret.spang-lab.de.
    DOI:  https://doi.org/10.1021/acs.jcim.6c01344
  18. J Chromatogr B Analyt Technol Biomed Life Sci. 2026 Aug 28. pii: S1570-0232(26)00360-0. [Epub ahead of print]1284 125271
    Development and ICH M10-compliant validation of an LC-MS/MS method for quantification of atirmociclib in mouse plasma and its application to preclinical pharmacokinetic studies.
    Ashwani Gaur, Urvesh Patel, Ashutosh Gavali, Sasikumar Sekar, Vijay Nadawade, Harikesh Kalonia, Amol Raje, Kanagamakula Changappa, Pradeep Jadhavar, Samadhan Kadam, Swapan Samanta, Subhendu Mohanty.
      Atirmociclib is a selective cyclin-dependent kinase 4 (CDK4) inhibitor currently under clinical investigation for the treatment of advanced malignancies, particularly hormone receptor positive (HR+) or human epidermal growth factor receptor 2 negative (HER2-) breast cancer. Here, we report the first validated liquid chromatography tandem mass spectrometry (LC-MS/MS) bioanalytical method for the quantification of atirmociclib in mouse plasma, validated in compliance with international council for harmonisation-M10 (ICH-M10) guidelines. Sample preparation involved a rapid and straightforward protein precipitation approach using acetonitrile, yielding consistent recovery (>80%) across low to high concentration levels. Chromatographic separation was achieved on a Kinetex C18 column (50 mm length × 2.1 mm internal diameter, 5 μm particle size) using gradient elution with 5 mM ammonium acetate in water (mobile phase A) and 0.1% v/v formic acid in acetonitrile (mobile phase B). The analyte (atirmociclib) and internal standard (warfarin) were detected using Q1/Q3 (m/z) mass transitions 464.2/303.9 and 309.0/163.0 respectively. The method demonstrated excellent selectivity, accuracy, precision, and linearity over a concentration range of 1-1000 ng/mL. Additionally, reliable quantification was maintained for samples exceeding the upper limit of quantification following up to 10-fold dilution. All validation parameters, including stability in biological matrices and solution, met the predefined acceptance criteria. This sensitive, and reproducible method was successfully applied to support preclinical pharmacokinetic study of atirmociclib in mouse, providing a valuable analytical tool.
    Keywords:  Atirmociclib; CDK4; LC-MS/MS; Plasma
    DOI:  https://doi.org/10.1016/j.jchromb.2026.125271
  19. Anal Biochem. 2026 Aug 31. pii: S0003-2697(26)00197-1. [Epub ahead of print]720 116241
    Simultaneous GC-MS determination of unsubstituted, hydroxy-, amino-, and hydroxy-amino short-chain fatty acids together with amino acids in biological and food samples following derivatization.
    Kalliroi Maria Katsari, Constantine D Stalikas.
      The simultaneous determination of short-chain fatty acids (SCFAs) and amino acids is of increasing interest, as these metabolite classes are important indicators of host metabolism and gut microbiota activity. They also serve as biomarkers for disease diagnosis and indicators of food composition. In this study, a gas chromatography-mass spectrometry method was developed for the simultaneous determination of both substituted (hydroxy-, amino- and hydroxy-amino-) and unsubstituted SCFAs, alongside amino acids, following derivatization and liquid-liquid extraction. Isobutyl chloroformate was employed as the derivatization reagent. The proposed method demonstrated excellent linearity, with coefficients of determination (R2) ranging from 0.9840 to 0.9992. Method limits of detection ranged from 0.011 to 7.2 μg/mL, while method limits of quantification ranged from 0.033 to 8.0 μg/mL. Intra-day precision (%RSD) ranged from 1.0% to 6.5% for biological samples and from 1.1% to 4.5% for eggs. Inter-day precision (%RSD) ranged from 1.0% to 5.6% for biological samples and from 2.0% to 6.7% for eggs. Matrix effects ranged from 98% to 108% for biological samples and from 96% to 113% for eggs, while recoveries ranged from 90% to 111% and from 95% to 108%, respectively. To the best of our knowledge, this is the first GC-MS method enabling the simultaneous determination of substituted and unsubstituted SCFAs together with amino acids in a single analytical procedure. The proposed approach provides a reliable and versatile platform for metabolomics, microbiome research, clinical investigations, and food analysis, while also providing considerable potential for expansion to a wider range of target metabolites.
    Keywords:  Amino acids; Gas chromatography-mass spectrometry; Isobutyl chloroformate derivatization; Short-chain fatty acids; Simultaneous determination
    DOI:  https://doi.org/10.1016/j.ab.2026.116241
  20. Anal Chem. 2026 Sep 01. 98(34): 24817-24830
    A High-Throughput Workflow for High-Content Microplate-Based Assays via Mass Spectrometry Imaging.
    Xinyue Min, Meng Yu, Jianpeng Huang, Junwen Shi, Hongtao Jin, Xiuli Gao, Lixin Sun, Jiuming He.
      Microplate-based assays are indispensable in life sciences and drug discovery; however, conventional optical readouts provide limited chemical information. Here, we report a microplate-based mass spectrometry imaging (MP-MSI) workflow based on air flow-assisted desorption electrospray ionization (AFADESI) that enables high-throughput molecular analysis of complex biological samples with minimal sample consumption (down to 1 μL). In contrast to existing MSI-based high-throughput strategies that primarily perform single-mode screening, this platform integrates targeted quantitation and untargeted metabolomics from the same sample spot. Using formaldehyde (FA) as a model analyte, we developed a rapid spermidine derivatization method and performed full method validation in blank mouse plasma. The targeted assay achieved an interbatch precision of 6.18% RSD for the analyte-to-internal standard ratio across 0.01-0.8 mmol/L, with a minimum detectable concentration change of 1.12-fold. For untargeted metabolomics, the median within-run RSD evaluated from 180 repeated spottings of blank mouse plasma was 19.1%, corresponding to a minimum detectable fold change of 1.38, at a throughput of 2.2 min per sample. To demonstrate dual-mode integration, we applied the validated FA method to plasma from an Alzheimer's disease mouse model (APP/PS1 and wild-type, 10 and 12 months of age), simultaneously quantifying FA and profiling the global metabolome from the same acquisition. Age- and genotype-dependent metabolic alterations were revealed. The platform was further extended to cell coculture models and to drug quantitation (e.g., irinotecan in plasma), demonstrating versatility across sample types and analytes. This integrated strategy offers a versatile platform for high-content screening in biomedical and pharmacological research.
    DOI:  https://doi.org/10.1021/acs.analchem.6c01560
  21. Clin Chem Lab Med. 2026 Sep 01.
    An isotope dilution-liquid chromatography-tandem mass spectrometry-based candidate reference measurement procedure for the quantification of piperacillin in human serum and plasma.
    Sandra Fleischer, Judith Taibon, Neeraj Singh, Carina Schuster, Arber Rexhaj, Michael Vogeser, Friederike Bauland, Andrea Geistanger, Elie Fux.
       OBJECTIVES: Piperacillin is a broad-spectrum antibiotic used to treat critically ill patients with severe infections, requiring therapeutic drug monitoring (TDM). We report the development of an isotope dilution-liquid chromatography-tandem mass spectrometry-based candidate reference measurement procedure (RMP) to quantify piperacillin in human plasma and serum.
    METHODS: Primary reference material was characterized by quantitative nuclear magnetic resonance (qNMR) to ensure traceability to the International System of Units (SI). Piperacillin was analyzed using LC-MS/MS operating in positive electrospray ionization and multiple reaction monitoring mode. Method validation evaluated selectivity, matrix effects, precision, accuracy, and measurement uncertainty (MU) according to GUM guidelines.
    RESULTS: This RMP allowed quantification of piperacillin within the range of 0.773 µmol/L (0.400 µg/mL) to 464 µmol/L (240 µg/mL), with selectivity, sensitivity and matrix-independence. Intermediate precision was <2.3 % and <1.1 % for spiked analyte in free human serum and native patient pools, respectively. The repeatability CV ranged from 0.7 to 2.0 % and relative mean bias ranged from -1.5 to 2.9 % across matrices and concentrations. Single measurement expanded MU ranged from 2.8 % to 5.0 %. Expanded MU (k=2) for target value assignment ranged from 2.0 % to 3.4 % across the primary therapeutic range, reaching 7.1 % total error at the lower limit of the measuring interval (LLMI).
    CONCLUSIONS: This candidate RMP enables accurate determination of piperacillin in human serum and plasma, providing a standardized platform to facilitate reliable clinical TDM and routine assay harmonization.
    Keywords:  SI units; isotope dilution-liquid chromatography-tandem mass spectrometry; piperacillin; qNMR characterization; reference measurement procedure; traceability
    DOI:  https://doi.org/10.1515/cclm-2026-0427
  22. Methods Mol Biol. 2026 ;3045 113-125
    Standardizing Methods for Shoot Metabolomics in Mycorrhizal Plants.
    Beatriz Ramírez-Serrano, Isaac Vega, Víctor Flors, Zhivko Minchev.
      With the latest advances in analytical techniques based on liquid chromatography (LC) coupled with mass spectrometry (MS), knowledge of plant metabolomics has risen exponentially in recent years. The study of metabolomic changes associated with mycorrhizal symbiosis interacting with different environmental situations exemplifies the expansion of knowledge in this field. In the present chapter, we aim to provide a standard procedure for the analysis of shoot metabolites using liquid chromatography coupled with high-resolution mass spectrometry. The provided information includes an extraction buffer of compromised polarity, as well as LC and MS conditions suitable for a general characterization of secondary metabolites from mycorrhizal plants. These conditions may require further adaptation in case a lipidomic or highly polar compound analysis is required or when a different instrumentation is used. In addition, we provide a protocol for a preliminary bioinformatic analysis of the identified features using public non-proprietary software, which, combined with the construction of pure standard libraries, can yield a powerful tool for the identification and semi-quantitative analysis of hundreds of secondary metabolites from mycorrhizal plants.
    Keywords:  Arbuscular mycorrhiza; LC-MS; Libraries; Untargeted metabolomics; qTOF
    DOI:  https://doi.org/10.1007/978-1-0716-5324-1_9
  23. J Am Soc Mass Spectrom. 2026 Sep 02. 37(9): 2085-2093
    Triboelectric Nanogenerator-Driven Laser Ablation Electrospray Ionization Enables Neutral Lipid Ionization and in Situ Double-Bond Localization.
    Joseph L Corstvet, David P Lewis, Dmitry Leontyev, Xin Ma, Carter K Asef, Rebecca S Arnold, John A Petros, Facundo M Fernández.
      Ambient ionization mass spectrometry includes numerous techniques, many of which are useful for analyzing lipids in biological samples. We report the development of a triboelectric nanogenerator (TENG)-driven laser ablation electrospray ionization (LAESI) platform, a novel ambient ionization method for the direct analysis of lipid mixtures. Detailed structural lipid annotation remains challenging due to the structural diversity of lipids. Previous research has shown that a TENG-driven dual nanoelectrospray ionization (nESI) and atmospheric pressure chemical ionization (APCI) mechanism helps localize lipid double bonds. In this study, we integrated infrared (IR) laser ablation with TENG nESI (TENG-LAESI). This novel ionization platform can ablate and ionize neutral lipids, including cholesterol and its derivatives, unsaturated fatty acids, and complex lipid mixtures. Rapid MS analysis reveals distinct ionization regimes within each TENG pulse and provides temporal resolution for various sterol species. Critically, the APCI stage drives epoxidation of fatty acid double bonds, generating diagnostic fragmentation patterns that enable reagent-free double-bond position assignment through tandem MS experiments, without chemical derivatization. Lastly, a novel TENG device was created and compared to existing designs, showing increased epoxidation efficiency and ionization potential. These experiments demonstrate the analytical potential of TENG-LAESI for structural lipid annotation and establish a foundation for its future development as a spatially resolved ambient MS imaging platform.
    Keywords:  lipid annotation; lipidomics; mass spectrometry imaging; triboelectric nanogenerator
    DOI:  https://doi.org/10.1021/jasms.6c00123
  24. Anal Chem. 2026 Sep 01. 98(34): 24690-24706
    An Analyte-Specific LC-IMS-HRMS Framework for Enhanced Identification Confidence in Target Screening of Contaminants in Complex Matrices.
    Konstantina S Diamanti, Dimitrios E Damalas, Georgios O Gkotsis, Eleni I Panagopoulou, Maria-Christina Nika, Carsten Baessmann, Karin Wendt, Birgit Schneider, Bob Galvin, Nikolaos S Thomaidis.
      Reliable identification of contaminants in complex matrices remains hampered by low-abundance signals, complex spectra, and coeluting isobars in liquid chromatography-high-resolution mass spectrometry (LC-HRMS) analyses with data-independent acquisitions. Moreover, wide-scope target screening workflows covering hundreds to thousands of known compounds from reference standards analyses often fail to fully exploit the acquired data, leading to false positives and false negatives. Herein, trapped ion mobility spectrometry (TIMS) was integrated into LC-HRMS, and an enriched database and an analyte-specific framework were introduced for enhanced identification confidence. The database including 1948 contaminants incorporated all MS and MS/MS qualifier ions together with their CCS values and mobility filtering windows, alongside the principal ion. Specific qualifiers were designated as mandatory for the first time by evaluating their relative intensity compared to the principal ion (≥50%), with the established identification points systems being refined accordingly to increase confidence. Regarding TIMS data, ∼2500 CCS values were determined, exhibiting high repeatability (RSD ≤ 0.70%) and interinstrument reproducibility (|ΔCCS|≤ 2%). Comparison with literature data across different IMS-HRMS platforms showed CCS accuracy within 2% for 89% of the ions. In matrix spiking experiments (raptor's eggs, human urine, wastewater), the cleaner mobility-filtered spectra resulted in improved selectivity for several contaminants' qualifiers, which improved detection at low concentrations, minimizing false negatives. Additionally, both differentiation based on CCS values (e.g., atenolol-practolol) and mandatory detection of predefined qualifiers (e.g., prometryn-terbutryn) decreased false positives. By incorporating the TIMS dimension and mandatory qualifiers as additional identification information, this work provides a robust framework for high-throughput environmental monitoring and human exposure assessment.
    DOI:  https://doi.org/10.1021/acs.analchem.5c08047
  25. Anal Bioanal Chem. 2026 Aug 31.
    Sustainable UHPLC-MS/MS assay for ultra-sensitive simultaneous quantification of amoxicillin and flucloxacillin with application to a bioequivalence study.
    Maha A Hegazy, Ashraf S Ibrahim, M Kenawy, Magdy M Saqer, Tebra M Elwakeel, Samia A Tawfik, Aya T Soudi.
      A novel, highly sensitive and robust ultra-performance liquid chromatography-tandem mass spectrometric (UHPLC-MS/MS) method was developed, optimized, and validated for the simultaneous quantification of amoxicillin (AMOX) and flucloxacillin (FLUX) in human plasma. The proposed method employs stable isotope-labelled isotopes, AMOX-d4 and FLUX‑13C4 sodium as an ideal internal standard of the studied compounds. The method is considered the first bioanalytical assay designed to concurrently measure both antibiotics in plasma, offering significant value for clinical and pharmacokinetic studies. Protein precipitation using acetonitrile was selected as a simple and effective approach for sample preparation. Chromatographic separation was achieved on an Inert Sustain Swift C18 column with an isocratic mobile phase of 0.1% formic acid and acetonitrile (55:45, v/v), delivered at a flow rate of 0.3 mL/min. Detection was carried out using positive electrospray ionization in multiple reaction monitoring mode with the following mass transitions: AMOX (m/z 366.284 → 114.000), AMOX-d4 (m/z 370.178 → 114.000), FLUX (m/z 454.206 → 160.100), and FLUX‑13C4 (m/z 458.135 → 160.100). Full validation, in accordance with FDA bioanalytical guidelines, was conducted over a linearity range of 0.05-6.00 µg/mL for AMOX and 0.05-15.00 µg/mL for FLUX, adequately covering their respective Cmax values. The method's sustainability was comprehensively evaluated by the recently introduced Sustainability Assessment Method for Instrumental Analysis (SAMI), highlighting the study's alignment with the United Nations Sustainable Development Goals (UN-SDGs). Furthermore, the developed method was successfully applied in a bioequivalence study involving 33 healthy volunteers following oral administration of a single 5 mL dose of Flucamox® 250 mg, enabling comprehensive pharmacokinetic evaluation while promoting sustainable and resource-efficient analytical practices.
    Keywords:  Amoxicillin and flucloxacillin; Bioequivalence study; Human plasma; Isotopically labelled compounds; LC–MS/MS; Pharmacokinetic study
    DOI:  https://doi.org/10.1007/s00216-026-06752-3
  26. Shokuhin Eiseigaku Zasshi. 2026 ;67(4): 174-180
    [Development and Validation of an Analytical Method for the Determination of Diethylstilbestrol, Dienestrol, Hexestrol, and Their Conjugates in Bovine Muscle].
    Chikako Ikegawa, Hiroko Hata, Seiichiro Iizuka, Youichi Kouno, Rie Ito, Tomoaki Tsutsumi, Hiroshi Akiyama, Shizuka Saito-Shida.
      A reliable and sensitive analytical method was developed for the determination of stilbenes-namely diethylstilbestrol, dienestrol, hexestrol, and their conjugates-in bovine muscle. The method involves the addition of internal standards to samples, extraction with ethanol/water (9 : 1, v/v),enzymatic hydrolysis using β-glucuronidase and aryl sulfatase, cleanup using hydrophilic-modified styrene-divinylbenzene copolymer and aminopropyl silica solid-phase extraction cartridges, and subsequent LC-MS/MS analysis. The method was validated for diethylstilbestrol, dienestrol, and hexestrol in bovine muscle spiked at 0.5 μg/kg for each analyte. The results demonstrated satisfactory analytical performance, with trueness values of 94-100%, repeatability below 5%, and within-laboratory reproducibility below 8%. No interfering peaks were observed, confirming the high selectivity of the method, and matrix effects were negligible. The developed method is applicable not only to diethylstilbestrol and its conjugates regulated in Japan but also to dienestrol and hexestrol, whose use for growth promotion in food-producing animals is prohibited in the EU. Although the conjugates of dienestrol and hexestrol were not directly validated in this study, they were presumed to be quantifiable based on their structural similarity to diethylstilbestrol conjugates.
    Keywords:  bovine muscle; dienestrol; diethylstilbestrol; hexestrol; stilbene
    DOI:  https://doi.org/10.3358/shokueishi.67.174
  27. Anal Chem. 2026 Sep 01. 98(34): 25402-25412
    Quantification of Disaccharide Isomers via Porous Graphitic Carbon Chromatography Coupled with Microdroplet Chemistry with Online Tandem Mass Spectrometry.
    Santosh R Acharya, Niraj K Panday, Shixiang Xu, Enoch Amoah, Abraham K Badu-Tawiah.
      The structural characterization of isomeric disaccharides remains analytically challenging due to their high polarity, low ionization efficiency, and lack of specificity in fragmentation patterns. Herein, we report a method based on porous graphitic carbon chromatography (PGCC) coupled with contained electrospray ionization (cESI), which enabled online microdroplet chemistry to be performed on disaccharides eluting from the PGCC system to form chloride-saccharide adducts. The adducts were subsequently subjected to tandem mass spectrometry (MS/MS) in real time. This PGCC-cESI-MS/MS platform integrates high-resolution chromatographic separation with specific fragmentation patterns to enable confident differentiation and quantification of native disaccharide isomers in complex mixtures. The platform enabled 15 structurally related (linkage, constitution, and anomeric isomers) disaccharides to be resolved and characterized based on complementary retention-time and diagnostic MS/MS fragmentation patterns. The method demonstrated wide quantitative linearity (R2 = 0.9999), low limits of detection (0.16 μM), good recoveries (101.3-109.1%), accuracy (96.1-104.3%), and high precision (CV ≤ 9.9%) with minimal sample preparation. Application to complex matrices, including mono- and polyfloral honey, beer, apple, milk, and soft drinks, enabled the identification and quantification of known disaccharides, as well as the detection of multiple unknown isomeric species. The integration of chromatographic separation with microdroplet adduction and MS/MS enables rapid, robust, and comprehensive analysis of disaccharides in complex matrices.
    DOI:  https://doi.org/10.1021/acs.analchem.6c04488
  28. Biomed Chromatogr. 2026 Oct;40(10): e70608
    Pharmacokinetic and Tissue Distribution Analysis of Scutellarin and Iso-Scutellarin From Breviscapine Injection in Rats by a Validated UPLC-MS/MS Method.
    Min Wen, Lijuan Fan, Lipan Yang, Qi Zhang, Xiaobo Lv.
      Breviscapine injection (BI), a standardized botanical drug for cardiovascular and cerebrovascular diseases, lacks adequate characterization of its pharmacokinetics and tissue distribution. A UPLC-MS/MS method was developed and validated for simultaneous quantification of scutellarin and its metabolite iso-scutellarin in rat plasma and tissues after intravenous BI administration. Sample preparation used methanol protein precipitation, with detection via positive electrospray ionization MRM. Validation followed the Chinese Pharmacopoeia and bioanalytical PK guidance. The assay showed LLQs of 10.0 ng/mL (scutellarin) and 5.0 ng/mL (iso-scutellarin), good linearity (r2 ≥ 0.990), precision (RSD ≤ 11.1%), accuracy (91.7%-106.8%), and acceptable recovery and matrix effects. PK analysis revealed moderate-to-rapid systemic elimination of scutellarin. Both analytes distributed to tissues within 0.25 h postdose, with exposure ranking: bladder > small intestine > kidney > small intestine > kidney > stomach > liver > plasma > heart > skeletal muscle > pancreas > skin > fat > lung > ovary > testis > adrenal > heart > skeletal muscle > pancreas > thymus > spleen > brain. The method is suitable for BI studies. The limited brain penetration suggests formulation optimization to prolong plasma exposure may be worth exploring, and the relatively high hepatic distribution points to a potential need for monitoring liver and kidney function.
    Keywords:  UPLC‐MS/MS; breviscapine injection; pharmacokinetics; quantification; tissue distribution
    DOI:  https://doi.org/10.1002/bmc.70608
  29. Methods Mol Biol. 2026 ;3063 243-272
    Comprehensive LC-MS Metabolomics Data Processing with notame R/Bioconductor Package.
    Ville Koistinen, Retu Haikonen, Atte Lihtamo, Vilhelm Suksi, Olli Kärkkäinen, Leo Lahti, Kati Hanhineva.
      Liquid chromatography-mass spectrometry (LC-MS) is widely used in metabolomics. Raw LC-MS data is relatively complex, consisting of molecular features originating not only from unique metabolites but also from redundant adducts, in-source fragments, artifacts, and impurities. It is also prone to signal intensity drift during long sequences, missing values, and false positives in statistical tests. To tackle these instrument-related and data-dependent challenges with robust pre-processing and quality evaluation tools, we have developed the notame R package bundle, which recently became available as a R/Bioconductor release and now supports SummarizedExperiment data format. It pre-processes LC-MS metabolomics data by correcting signal intensity drift, flagging potential low-quality and contaminant features, imputing missing values, and clustering features likely originating from the same metabolite. Most of the functions include default recommended values that can be modified by the user. Univariate and multivariate statistics with parametric and non-parametric alternatives and false discovery rate can be performed with notameStats package. Results and data visualizations, such as quality control figures, PCA, heatmaps, volcano plots, and feature-wise graphs, are available in notameViz package. Together, these packages contribute to a complete metabolomics data analysis workflow, connecting the phases between signal detection/alignment and metabolite identification while producing publication-ready illustrations.
    Keywords:  Preprocessing, Statistics, Quality assurance, Data visualization, Programming
    DOI:  https://doi.org/10.1007/978-1-0716-5452-1_14
  30. J Proteome Res. 2026 Sep 04. 25(9): 4614-4623
    Revealing Hidden Variables in DESI-Based Spatial Metabolomics: Solvent Composition and Tissue Type as Critical Drivers.
    Marco Giampà, Peter D E M Verhaert, Jan Claereboudt, Emmanuelle Claude, Bernard Drotleff, Geert Goeminne, Veerle Heedfeld, Jakub Idkowiak, Emrys A Jones, Alexander Muck, Janick Mathys, Alaa Othmann, Nina Ravoet, Julio Lopes-Sampaio, Johannes V Swinnen, Ina Jochmans, Bart Ghesquière.
      In the development of a desorption electrospray ionization (DESI) workflow for spatial metabolomics, we investigated the impact of two commonly used solvent systems, 90% acetonitrile (ACN) and 90% methanol (MeOH), on the spatial metabolomic profiling of various murine tissues. The performance of both solvents was evaluated across several metabolite classes (central carbon metabolites, amino acids, and fatty acids). Although the ACN-based solvent system led to higher signal intensities for small polar metabolites involved in glycolysis, the tricarboxylic acid (TCA) cycle, and amino acid metabolism, the MeOH-based solvent system provided superior signal intensities for fatty acids. These findings demonstrate that the solvent composition differentially influences metabolite extraction and ionization processes in DESI and should be carefully matched to the biological questions and metabolite classes of interest. As a proof-of-principle, the ACN solvent system was applied to a pilot study based on a rat model of renal ischemic injury, revealing region-specific metabolic changes between normoxic and ischemic conditions. Together, these results demonstrate the importance of solvent selection in DESI-based spatial metabolomics and showcase the ability of this approach to uncover spatially resolved metabolic adaptations associated with tissue injury.
    Keywords:  DESI; mass spectrometry imaging; metabolomics
    DOI:  https://doi.org/10.1021/acs.jproteome.6c00001
  31. J Am Soc Mass Spectrom. 2026 Sep 02. 37(9): 2247-2250
    mspix: A Data Format for High Pixel Count Mass Spectral Images.
    Kasper Krijnen, Ron M A Heeren, Ian G M Anthony.
      The existing open file format for mass spectrometry imaging (MSI) data, imzML is suitable for high-mass complexity images. However, when the pixel count exceeds many megapixels to a gigapixel, imzML becomes an inefficient storage option due to the required per-pixel XML component. In some targeted MSI cases, the Open Microscopy Environment tagged image file format (OME-TIFF) is preferred; however, OME-TIFF images are unable to capture the mass complexity of even a low-mass resolution image. Here we present "mspix", a file format that is suitable for high-pixel count single-stage mass spectrometry (MS1) images. We convert mass spectral images from differing file formats to mspix and benchmark their access speed with our Python implementation. We show that, in our cases, mspix is more space-efficient than both native and imzML file formats, especially for high-pixel count images. For mass images of fewer than 10 million pixels, imzML remains the recommended open, vendor-neutral format. Our implementation of mspix can process mass images of greater than 1 billion pixels, which, to our knowledge, is not supported in any other MSI software library or package.
    Keywords:  Data storage; File format; High-pixel-count imaging; Mass spectrometry imaging (MSI); mspix
    DOI:  https://doi.org/10.1021/jasms.6c00079
  32. J Am Soc Mass Spectrom. 2026 Sep 02. 37(9): 2130-2140
    Boronic Acid Mass Tag Empowered Detection of Glucose for MALDI MS Imaging.
    Justine Gatein, Nassim Maarouf-Mesli, Dzila Aharoutian, William D Lubell, Pierre Chaurand.
      Glucose is a key metabolite involved in energy production, biosynthesis, and signaling. The metabolism of glucose is also dysregulated in many diseases, such as cancer, in which metabolic reprogramming of the carbohydrate is a hallmark of malignancy. In spite interest in using mass spectrometry imaging (MSI) to study the spatial temporal concentrations of glucose in normal and diseased tissues, poor ionization efficiency inhibits matrix-assisted laser desorption ionization (MALDI) analysis of the endogenous metabolite. A novel mass tag featuring a diol-targeting boronic acid warhead linked to a positively charged absorbing moiety is reported for on-tissue chemical derivatization to enhance glucose detection sensitivity and ionization efficiency. Spray deposition of the borate mass tag followed by 2,5-dihydroxyacetophenone matrix and MSI acquisition in the positive ion mode gave up to 10-fold greater sensitivity for glucose compared to standard analysis using N-(1-naphthyl)ethylenediamine dinitrate matrix and enabled imaging at 10 and 5 μm spatial resolution on brain tissue, which displayed glucose distribution without delocalization or edge effects. Empowering spatially resolved analysis of glucose metabolism with high sensitivity, boronic acid tag offers strong potential for studying disease-specific metabolic reprogramming.
    Keywords:  glucose; mass spectrometry imaging (MSI); on tissue chemical derivatization OTCD
    DOI:  https://doi.org/10.1021/jasms.6c00159
  33. J Am Soc Mass Spectrom. 2026 Sep 02. 37(9): 2228-2237
    Chiral Carbohydrate Adducts are Effective for Enantiomeric Ion Mobility Separations.
    Noah D Roberts, Gabe Nagy.
      Enantiomers play important roles in biology and the pharmaceutical industry but remain notoriously difficult to separate and characterize. Gold-standard chromatography and nuclear magnetic resonance-based methods are slow, laborious, and expensive, motivating the development of rapid methodologies for enantiomer characterization. While ion mobility spectrometry-mass spectrometry (IMS-MS) has emerged as a rapid technique for chiral analysis, current approaches often rely on derivatization, complicated chiral complexes, or large host molecules that can produce complex spectra. Herein, we investigate small carbohydrates as chiral adducts for the ion mobility separation of amino acid and drug enantiomers. Six commercially available nonreducing or reduced carbohydrates were evaluated as chiral adduct molecules using cyclic IMS-MS. All carbohydrate adducts readily formed simple 1:1 complexes in the MS dimension that produced two discrete IMS peaks for each enantiomeric pair and remained sufficiently stable for extended path length separations. The carbohydrate panel enabled chiral separation of all 15 amino acid and drug enantiomer pairs at pathlengths as low as 1 m. Relative arrival time measurements further enabled unbiased comparison of separation performance across analyte-adduct pairs. The developed carbohydrate-based method was used to quantify enantiomeric excess down to a 99:1 molar ratio with estimated limits of detection down to 5 nM. These results demonstrate that small carbohydrates are effective chiral adducts for IMS-MS-based enantiomer separations and that simple analyte-adduct complexes can provide rapid and broadly applicable enantiomer differentiation without derivatization or the use of multimolecule complexes.
    DOI:  https://doi.org/10.1021/jasms.6c00250
  34. Environ Chem Ecotoxicol. 2026 ;8 2693-2721
    A Streamlined Automated Liquid Handling and 96-Well Solid-Phase Extraction for Single Low-Volume Urine Aliquot Multiclass Biomarker Analysis in Human Biomonitoring.
    Ravikumar Jagani, Dhavalkumar Patel, Anil K Meher, Divya Pulivarthi, Jasmin Chovatiya, Hiraj Patel, Sandipkumar Teraiya, Syam S Andra.
      Laboratory automation has gained significant importance in large-scale biomonitoring studies, providing notable advantages in sample handling, pre-treatment, and cleanup processes. This study introduces a validated automated 96-well format method for the simultaneous extraction and analysis of various urinary biomarkers belonging to different chemical classes. These chemical classes, listed in alphabetical order, include compounds or their metabolites belonging to cannabinoids, environmental phenols, organophosphate flame retardants, non-persistent pesticides, polycyclic aromatic hydrocarbons, tobacco, and volatile organic compounds. The automated workflow employs an epMotion 5075 vtc workstation for sample preparation, featuring automated sample aliquoting, enzymatic pre-treatment, and solid-phase extraction cleanup, followed by liquid chromatography-tandem mass spectrometry analysis. Method validation was performed using urine quality control pools spiked with 0.1 to 10 ppb of each analyte. Results demonstrated excellent precision, with coefficients of variation below 20% for both native and internal standard responses across the chemical classes. Recovery rates for spiked samples consistently ranged from 80% to 120%, affirming the method's accuracy and reliability. The consistency in performance across different chemical classes and concentration ranges highlights the robustness of the automated method. The automated system effectively quantified biomarkers at low ng/mL concentrations in native (unspiked) urine samples, demonstrating sensitivity that is appropriate for comprehensive exposure assessment studies.
    Keywords:  96-well format; Automated sample preparation; Environmental chemical biomarkers; Exposomics; Multi-biomarker analysis; epMotion workstation
    DOI:  https://doi.org/10.1016/j.enceco.2026.08.006
  35. Anal Chem. 2026 Sep 01. 98(34): 24964-24975
    TRACE: An Integrated Isotope-Tracing Framework for Metabolite Validation and Nutrient Fate Mapping.
    Rui Li, Junyao Wang, Yuanhong Shan, Zuohan Xie, Yuzhe Xiao, Weidong Zhuang, Yongzhen Tao, Jinyu Zhou, Lifeng Yang, Lin Wang.
      Untargeted LC-MS metabolomics offers a broad view of the microbial metabolism. However, its application is hindered by two intertwined challenges: distinguishing true biological signals from chemical artifacts and quantifying nutrient partitioning under nutrient-competitive conditions. Here, we present TRACE, an integrated experimental and computational framework that dynamically calibrates mass and retention time tolerances from the data itself to construct isotope-informed peak networks, enabling rigorous discrimination of biological metabolites from artifacts. Across four LC-MS platforms, TRACE reveals that the proportion of high-confidence annotations fell from 2.94 to 1.48%, while the total features increased by 331% from lower- to higher-sensitivity instruments. TRACE also maps nutrient fates into metabolic pathways by detecting isotopic dilution in Saccharomyces cerevisiae cultured with 13C-glucose, 15N-ammonium, and other unlabeled nutrients. Specifically, labeling of glutathione, a linear assembly of three amino acids, accurately reflect direct incorporation from its constituent amino acids; NAD+, whose biosynthesis proceeds through concurrent salvage and de novo pathways, revealed how adenine, tryptophan, and glutamine shaped its final isotopologue pattern. By converting untargeted LC-MS data into functional maps of nutrient flow, TRACE establishes a system-level approach to interrogate microbial metabolism under physiologically relevant competitive conditions.
    DOI:  https://doi.org/10.1021/acs.analchem.6c02292
  36. Methods Mol Biol. 2026 ;3063 227-242
    Prediction, Targeting, and Annotation of Oxidized Lipids Using LPPtiger2 Software.
    Zhixu Ni, Maria Fedorova.
      The epilipidome, a subset of the natural lipidome arising from enzymatic and non-enzymatic lipid modifications, remains largely unexplored. Within this emerging class, oxidized complex lipids have raised considerable interest due to their diverse biological functions, including the modulation of inflammation, cell fate decisions, and the execution of programmed cell death. However, the discovery and annotation of these typically low-abundant yet structurally diverse lipid species present significant analytical challenges, often necessitating advanced bioinformatics tools. Here, we present a computational pipeline powered by LPPtiger2 software, designed for the comprehensive discovery, detection, and annotation of complex oxidized lipids within the context of a defined lipidome. The LPPtiger2 hybrid workflow offers a robust solution for high-quality epilipid profiling by integrating a predictive algorithm with a semi-targeted experimental protocol. Using a knowledge-based in silico epilipidome prediction algorithm, it generates a highly customized, sample-specific search space prior to data acquisition. This approach transforms the conventional untargeted lipidomics pipeline into a semi-targeted workflow that selectively focuses on predicted epilipid precursors. Such specificity enhances LPPtiger2-supported annotation of modified epilipids through improved sensitivity, superior MS/MS spectral quality, and a tailored lipid search space.
    Keywords:  Epilipidomics; Lipid annotations; Lipidomics; Oxidized lipids; Software
    DOI:  https://doi.org/10.1007/978-1-0716-5452-1_13
  37. Anal Chem. 2026 Aug 25. 98(33): 24047-24056
    Fast Diffusion-Based Metabolomics Profiling by 3D Pure Shift HSQC-DOSY NMR with COLMARvista.
    R Cabrera Allpas, K Lee, D-W Li, M Choo, L Bruschweiler-Li, R Brüschweiler.
      Peak overlap is a major obstacle for comprehensive metabolite profiling in NMR-based metabolomics. It is most severe for 1D 1H NMR spectra but can also persist for 2D NMR. Here, we demonstrate how metabolite-specific translational diffusion coefficients obtained from a pure shift pseudo-3D HSQC-DOSY experiment can resolve metabolite ambiguities caused by (near-)degenerate chemical shifts. In addition to the NMR pulse sequence, a novel pseudo-3D processing module implemented in COLMARvista is presented, which is a JavaScript-based standalone software for the automated processing, peak picking, quantification, and visualization of pseudo-3D HSQC-DOSY data sets. As is demonstrated for mouse urine, Pseudomonas aeruginosa biofilm, and a carbohydrate mixture, the pseudo-3D real-time pure shift HSQC-DOSY experiment is an effective tool for analyzing complex NMR metabolomics samples. Moreover, it is shown how the increased sensitivity and resolution of this experiment, compared to standard pseudo-3D-DOSY, yield more precise diffusion coefficients of the metabolomic mixture components even when using a minimal set of 2D planes.
    DOI:  https://doi.org/10.1021/acs.analchem.6c01028
  38. Anal Chem. 2026 Sep 01. 98(34): 25166-25173
    On-Line Three-Dimensional High-Performance Liquid Chromatographic System for the Comprehensive and Enantio/Stereoselective Determination of All Proteinogenic Amino Acids in Human Plasma and Urine.
    Yuri Nagata, Takeyuki Akita, Chiharu Ishii, Masataka Ikeda, Masashi Mita, Tomomi Ide, Kenji Hamase.
      An online three-dimensional (3D) HPLC system was designed/developed for the comprehensive determination of all proteinogenic amino acid enantiomers, including allo-isoleucine, allo-threonine (aThr), and 3 cystine (Cys) stereoisomers (dd/dl/ll-forms), in real-world samples with one injection. d-Amino acids are candidates for physiologically active molecules and/or biomarkers, and the simultaneous determination of all the proteinogenic chiral amino acids is expected. However, the amounts of d-amino acids in biological samples are usually much lower than those of other intrinsic substances, including l-amino acids and peptides; thus, the analytical method for the determination of d-amino acids requires high selectivity. In the present study, a reversed-phase column (Singularity RP18) and a mixed-mode column (Singularity MX-103) were utilized to separate all of the proteinogenic amino acids as their scalemic mixtures, and a Pirkle-type enantioselective column (Singularity CSP-001S) was used for the chiral separations. By using the 3D-HPLC system, all of the proteinogenic amino acids and allo-forms were enantioselectively separated, and the determination of these chiral amino acids in human plasma and urine was carried out without interference from intrinsic substances. As a result, 5 d-amino acids (alanine, asparagine, aThr, proline, and serine) were clearly determined in human plasma, and the peaks of 19 d-amino acids (i.e., all the target d-amino acids except for d-isoleucine and dd-Cys) and dl-Cys were observed in human urine. The present 3D-HPLC system achieved the simultaneous and selective determination of all proteinogenic amino acid enantiomers, including 2 allo-forms and 3 Cys stereoisomers, in biological matrices for the first time, to the best of our knowledge.
    DOI:  https://doi.org/10.1021/acs.analchem.6c03014
  39. Talanta. 2026 Aug 31. pii: S0039-9140(26)01184-7. [Epub ahead of print]312(Pt C): 130528
    A strategy for relative quantification of chiral amines in nontargeted metabolomics via formation of fixed adduct ions.
    Yuxuan Li, Xinxin Kong, Yihao Liu, Xi-Ling Li, Mingshan Zheng, Toufeng Jin, Jun Zhe Min.
      Chemical derivatization technology significantly expands the detection scope and enhances the sensitivity of untargeted metabolomics. However, the complex adduct ion formations and diverse ionization patterns of derivatized products present substantial challenges for compound screening and data interpretation. Additionally, understanding the correlations between chiral metabolites and biological systems is essential for uncovering molecular mechanisms underlying physiological processes. To address these challenges, this study developed the (S), (R)-(5-(2-(((1-((N,4-dimethylphenyl) sulfonamido) vinyl) oxy) carbonyl) pyrrolidin-1-yl)-5-oxopentyl) triphenylphosphonium ((S), (R)-TPP-BSA) and d15-(S)-TPP-BSA probes, establishing a relative quantitative non-targeted metabolomics strategy for chiral amine-containing metabolites (RQ-NMCA). RQ-NMCA facilitates the formation of stable [M]+ adduct ions of amine derivatives in mass spectrometry, enabling effective identification and analysis of chiral amine metabolites. By leveraging isotope structures, relative quantitative analysis of amine-containing metabolites between groups is achievable. In serum samples from healthy volunteers (HV) and colorectal cancer (CRC) patients, 38 significant differential amine-containing metabolites were identified, including 15 chiral amines. RQ-NMCA introduces the fixed addition ion concept into chemical labeling non-targeted metabolomics, significantly enhancing ionization efficiency while simplifying the screening and identification processes. Furthermore, the integration of chiral recognition and relative quantification approaches is pivotal for understanding the relationship between chiral amine-containing metabolites and physiological or pathological states. This technology provides a robust platform for chiral non-targeted metabolomics research and will facilitate the identification of novel biomarkers for disease diagnosis.
    Keywords:  Chiral recognition; Fixed adduct ions; Nontargeted analysis; Relative quantification; TPP-BSA
    DOI:  https://doi.org/10.1016/j.talanta.2026.130528
  40. Talanta. 2026 Aug 24. pii: S0039-9140(26)01163-X. [Epub ahead of print]312(Pt C): 130507
    High-sensitivity quantification of angiotensin oligopeptides using methoxyacetylation coupled with LC-TIMS-qTOF/MS.
    Xiaoqi Yang, Jueri Kawada, Tadashi Hayama, Toshiro Matsui.
      Quantification of key effectors in the circulating renin-angiotensin system (RAS), including angiotensin (Ang) I, Ang (1-9), Ang II, Ang (1-7), and Ang A, is essential for understanding RAS-mediated blood pressure regulation. Herein, we present a highly sensitive and selective analytical method based on methoxyacetylation coupled with liquid chromatography-trapped ion mobility spectrometry-quadrupole time-of-flight mass spectrometry (LC-TIMS-qTOF/MS) operated in parallel reaction monitoring-parallel accumulation serial fragmentation (prm-PASEF) mode. Methoxyacetylation using an NHS ester reagent modulated protonation and fragmentation behavior, resulting in enhanced signal intensity and more concentrated product-ion formation. The TIMS parameters were optimized to achieve maximal sensitivity, with an inverse reduced mobility (1/k0) range of 0.7-1.1 cm2 V-1 s-1 and accumulation and ramp times of 150 ms. Under these conditions, the method exhibited excellent analytical performance, with limits of detection ranging from 0.6 to 3.4 fmol/mL, precision below 9.3% (CV), and accuracy within 95.1-105.8%. Using [13C5,15N]-labeled Ang II as an internal standard, all five target angiotensin peptides were successfully quantified from 100 μL of Sprague-Dawley rat plasma. The developed method provides a robust and sensitive platform for multiplexed quantification of angiotensin metabolites and enables detailed investigation of RAS dynamics in biological systems.
    DOI:  https://doi.org/10.1016/j.talanta.2026.130507
  41. Anal Bioanal Chem. 2026 Sep 02.
    Redefining reference materials for the evolving metabolomics landscape.
    Tracey B Schock, Fabio Casu, Ashley S P Boggs, Amanda L Bayless, Hariharan Iyer, Kristine Gierz, W Clay Davis.
      The evolution of metabolomics, a field aimed at comprehensively measuring the small organic molecule composition of a biological matrix, fundamentally reshaped the landscape of analytical measurement reliability. The 2011 release of Standard Reference Material (SRM) 1950 Metabolites in Frozen Human Plasma by the National Institute of Standards and Technology (NIST) marked the first reference material providing certification for 45 analytes to address the measurement precision of complex biological matrices. Assigning high-order values to many compounds is highly resource-intensive for a National Metrology Institute. Furthermore, certified values for individual metabolites cannot resolve the broad challenges associated with sample processing, analytical measurement, and data processing in untargeted workflows. The metabolomics community recognized the potential for SRM 1950 to serve as a benchmark material for method development and technical quality control (QC) rather than strictly for quantification. Recognizing this consumer-driven shift, NIST launched a novel reference material (RM) development strategy to provide accessible, fit-for-purpose materials evaluated by a new statistical framework for production homogeneity, the Coefficient of Disagreement. Here, we introduce the transition toward matrix-specific QC Suites featuring phenotypically distinct metabolite profiles, the first generation of which includes a human plasma suite, urine suite, liver suite, and fecal material. By prioritizing efficient production and embracing a community engagement model for consensus-based deep characterization, these suites offer a reliable tool for laboratory comparisons, instrument assessment, software development, and training. This new class of RMs underpins the next phase of measurement reliability, complementing traditional measurand certification while supporting the diverse needs of comprehensive metabolic profiling.
    Keywords:  Coefficient of disagreement; Metabolomics; Metrology; Quality control; Reference materials
    DOI:  https://doi.org/10.1007/s00216-026-06769-8
  42. Methods Mol Biol. 2026 ;3050 435-446
    Metabolomic Study in Ustilaginaceae with GC-MS/MS.
    An N T Phan, Philipp Westhoff, Stefan Krüger, Lars M Blank.
      Ustilago maydis, the causative agent of corn smut in maize, is a well-established model organism for fundamental biological research. In addition, this fungus has growing biotechnological importance, as it proliferates in a haploid, non-filamentous form and efficiently converts renewable substrates into a range of industrially valuable products. To complement the extensive molecular and genetic tools already available, metabolomics provides essential insights into cellular physiology and supports the exploitation of its production potential. Here, a GC-MS-based workflow for the absolute quantification of intracellular metabolites in U. maydis is presented. This protocol enables systematic analysis of metabolic network operation and can be readily extended to metabolomics studies in related fungi in the Ustilaginaceae family.
    Keywords:   Ustilago maydis; Central carbon metabolism; GC–MS; Metabolic engineering; Metabolomics; Sample preparation; Ustilaginaceae
    DOI:  https://doi.org/10.1007/978-1-0716-5364-7_37
  43. J Chromatogr Sci. 2026 Aug 31. pii: bmag024. [Epub ahead of print]64(8):
    Rapid and validated LC-APCI-MS/MS method for determination of N-nitroso vonoprazan in pharmaceutical products.
    Filiz Demir, Sıdıka Ertürk Toker.
      The primary objective of this study was to develop and validate a liquid chromatography-atmospheric pressure chemical ionization-tandem mass spectrometric (LC-APCI-MS/MS) method for the determination of trace levels of N-nitroso vonoprazan (NVNP) in vonoprazan active pharmaceutical ingredient (API) and pharmaceutical products. Chromatographic separation was achieved on an Acquity® Premier HSS T3 column under isocratic conditions using 0.1% formic acid in water and acetonitrile as the mobile phase. Detection was performed in positive ion mode using multiple reaction monitoring. The method was validated according to ICH Q2(R2) guidelines for selectivity, linearity, accuracy, precision, robustness, matrix effect, limit of detection (LOD), and limit of quantification (LOQ). The method was linear over the concentration range of 0.24-50.0 ng/mL (R2 = 0.9971), with recoveries of 85.6%-99.2% and relative standard deviation values below 6.1%. The validated LOD and LOQ were 0.10 and 0.24 ng/mL, respectively; the latter corresponds to 0.24 μg/g (240 ppb) in the pharmaceutical product. Matrix effect evaluation showed 91.6% response (8.4% ion suppression), indicating minimal matrix interference. The validated LC-APCI-MS/MS method was successfully applied to both API and finished products and is suitable for routine quality control, stability studies, nitrosamine risk assessment, and regulatory monitoring of NVNP.
    DOI:  https://doi.org/10.1093/chromsci/bmag024
  44. Anal Chem. 2026 Sep 01. 98(34): 24677-24689
    MSlineaR: An R Package Assessing Linear Behavior to Improve Quality Assurance and Statistical Robustness in Untargeted Metabolomics.
    Janine Wiebach, Álvaro Fernández-Ochoa, Ulrike Bruning, Jochen Kruppa-Scheetz, Maëlle Bonhomme, Dominique-Marie Votion, Jennifer A Kirwan.
      Mass spectrometry-based untargeted metabolomics analyzes complex biological matrices containing thousands of individual features. Linearity is a key analytical parameter in quantitative mass spectrometry, reflecting proportionality between signal intensity and analyte concentration within a defined range. In untargeted metabolomics, linearity cannot be directly assessed due to the absence of reference concentrations. Instead, the range in which features exhibit approximately linear dilution-dependent behavior (ALB) can be evaluated as a practical proxy. Feature selection based on this response enables the early removal of noise and unreliable features, thereby reducing the risk of false-positive findings and improving analytical robustness, while the reduced number of retained features lowers the multiple-testing burden in downstream statistical analyses. We present MSlineaR, an open-source R-based software tool implementing a six-step process to assess dilution-dependent response behavior in metabolomic data sets. MSlineaR evaluates dilution curves to identify nonclassical response patterns, detect outliers, and iteratively trim boundary regions to remove plateau effects. It then reassesses the remaining data to retain features exhibiting ALB. Importantly, it defines boundaries of the approximately linear range (ALR) and applies them for data curation, enabling exclusion of unreliable signals while preserving robust features. Application to three independent data sets demonstrated a ∼10% improvement in the number of features classified as exhibiting ALB compared to classical linear regression-based approaches. MSlineaR was complementary to relative standard deviation (RSD) filtering, improved median RSD values and enhanced the robustness of statistical modeling.
    DOI:  https://doi.org/10.1021/acs.analchem.5c04480
  45. Food Sci Anim Resour. 2026 Sep 01. pii: 98. [Epub ahead of print]46(1):
    Optimized LC-MS/MS method for simultaneous determination of multiclass veterinary anthelmintic residues in animal-derived matrices.
    Ye-Bin Jang, Yeong-Ju Jo, Mi-Ok Kim, Gui-Hyun Jang, Jae-Eun Mun.
      Anthelmintics are veterinary drugs used to treat or prevent diseases in livestock and fishery products. However, their residues in animal-derived foods pose potential risks to human health. In Korea, maximum residue limits (MRLs) have been established to regulate such residues; however, for certain substances, including niclosamide, a widely used anthelmintic, only qualitative analytical methods are available, limiting effective residue monitoring. This study developed a multiresidue quantitative analytical method for 18 anthelmintic compounds. Method validation was conducted in accordance with CODEX guidelines (CAC/GL-71) using six livestock products (beef, pork, chicken, eggs, milk, and porcine fat) and three fishery products (flatfish, eel, and shrimp). Sample preparation was performed using the QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) extraction method followed by dispersive solid-phase extraction (d-SPE) clean-up. Simultaneous determination of the 18 anthelmintics was performed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The matrix-matched calibration curves exhibited coefficients of determination (R²) exceeding 0.99 for all target compounds. Furthermore, recovery rates at all target concentrations satisfied CODEX performance criteria, demonstrating acceptable accuracy and precision. The developed method can enhance the efficiency of residue analysis and provide a technical basis for establishing safety management standards for livestock and fishery products.
    Keywords:  Anthelmintics; Liquid chromatography–tandem mass spectrometry (LC-MS/MS); Matrix-matched calibration curves; Maximum residue limits (MRLs)
    DOI:  https://doi.org/10.1007/s44463-026-00098-1
  46. Biomed Chromatogr. 2026 Oct;40(10): e70610
    Development and Preliminary Application of a Method to Detect Sucralose in Placenta and Serum.
    Ying He, Xin Yin, Run Ling, Yan Zhang, Yidan Ma, Junlin He.
      Sucralose, an artificial sweetener widely used in sugar-free foods and beverages, raises human exposure and potential accumulation in tissues and organs. Given the profound long-term impact of maternal diet on offspring, its safety during pregnancy is of particular concern. Existing detection methods primarily target food matrices and lack reliable, efficient approaches for biological sample analysis. To address this gap, we developed an ultrahigh-performance liquid chromatography-multiple reaction monitoring tandem mass spectrometry (UHPLC-MS/MS) method based on existing food detection methods to quantify sucralose in mouse serum and placenta. Method validation showed excellent linearity in the range of 20-1250 nmol/L, with limit of detection (LOD) of 4.88 nmol/L and limit of quantification (LOQ) of 9.77 nmol/L. The precision, accuracy, matrix effects, and freeze-thaw stability were all within acceptable limits. Using the method described above, we detected sucralose in both serum and placenta of mice following subchronic exposure, confirming its bioaccumulation, systemic absorption, and transplacental transfer, suggesting the need for further reproductive toxicity studies. In summary, this study developed and preliminarily applied a method for determining sucralose in mouse serum and placenta, providing a methodological reference for the toxicological evaluation and safety assessment of sucralose, and aids in improving food safety risk systems and the formulation of evidence-based public health policies.
    Keywords:  UHPLC–MS/MS; placenta; serum; sucralose
    DOI:  https://doi.org/10.1002/bmc.70610
  47. J Chromatogr A. 2026 Aug 26. pii: S0021-9673(26)00721-1. [Epub ahead of print]1787 467394
    Development and comparative evaluation of chemical ionization and electron ionization for GC-MS targeted metabolomics applied to the brain of a pollinating insect.
    Simon Palmer, Teddy Strandberg, David O'Carroll, Elisa Rigosi, Peter Spégel.
      Metabolomics has been suggested as an informative tool to assess effects of chemical pollution, including pesticide exposure in insects. However, the small size of insects is challenging and has often precluded tissue-specific analyses in single animals. In the present study, a gas chromatography-chemical ionization/mass spectrometry (GCCI/MS) method employing single reaction monitoring (SRM) was developed, including optimization of ion source temperature, reagent gas pressure and ionization energy, for targeted profiling of 51 metabolites in central carbon metabolism. The method was compared to an independently optimized GC-electron ionization (EI)/MS SRM method using standard validation parameters. Finally, the best-performing method was used to assess the immediate (1 min) metabolic effect of acetamiprid, a commonly used insecticide, in the brain of the hoverfly Eristalis tenax. A high reagent gas pressure benefited detection of the vast majority of metabolites, with effects of ion source temperature and ionization energy being more ambiguous. Both methods demonstrated adequate precision, poor trueness, and high selectivity, with EI outperforming CI with regards to sensitivity and detection limits. While trueness was poor, EI provided for adequate relative quantification of a majority of the targeted metabolites in a single E. tenax brain. Profiling of brain metabolites in E. tenax exposed to acetamiprid revealed a large variation in the responses to acetamiprid exposure. In conclusion, EI was found to perform better than CI in profiling of metabolites in insect brains and shows promise to further develop our understanding of pesticide effects in pollinating insects.
    Keywords:  Acetamiprid; Gas chromatography; Mass spectrometry; Single reaction monitoring; Validation
    DOI:  https://doi.org/10.1016/j.chroma.2026.467394
  48. J Chromatogr B Analyt Technol Biomed Life Sci. 2026 Sep 02. pii: S1570-0232(26)00378-8. [Epub ahead of print]1284 125289
    Chiral HPLC in biomedical and pharmaceutical analysis: Method development challenges and application-oriented strategies.
    Mihajlo V Jakanovski, Mila Č Lazović, Mirjana D Mosić, Marko D Jović, Milica S Jankov, Sandra B Šegan.
      Chiral high-performance liquid chromatography (HPLC) remains one of the most important analytical techniques for investigating the stereochemical behavior of bioactive compounds. Although many commercial chiral stationary phases are available and new selector chemistries are continually introduced, successful enantioseparation alone does not ensure analytical applicability. In pharmaceutical and biomedical practice, chromatographic methods must perform reliably with complex sample matrices, low analyte concentrations, stringent validation requirements, and increasingly frequent coupling with mass spectrometric (MS) detection. Although achieving adequate enantioseparation remains a major challenge for many structurally complex analytes, increasing attention is being devoted to developing robust, validated, and application-oriented analytical methods suitable for pharmaceutical and biomedical analysis. Instead of presenting another catalog of chiral stationary phases or reported enantioseparations, this review examines chiral HPLC from a method development perspective. It discusses how chromatographic selectivity, sample preparation, matrix effects, detection strategy, elution order assignment, stereochemical stability, and validation requirements interact throughout the analytical workflow. Special emphasis is given to the transition from initial column screening to validated methods suitable for pharmaceutical quality control, stereoselective pharmacokinetic studies, drug-protein binding investigations, forensic toxicology, and chiral metabolomics. By integrating selector chemistry with practical analytical requirements, the review provides a framework for application-driven method development and highlights current trends shaping the future of chiral HPLC in biomedical and pharmaceutical sciences.
    Keywords:  Chiral metabolomics; Enantioseparation; Quality control; Stereoselective pharmacokinetics
    DOI:  https://doi.org/10.1016/j.jchromb.2026.125289
  49. Shokuhin Eiseigaku Zasshi. 2026 ;67(4): 152-160
    [Development of an Analytical Method for Simultaneous Determination of Deoxynivalenol and Ochratoxin A in Wheat].
    Tomoya Yoshinari, Yaeko Shichinohe, Yuki Hara, Masaru Taniguchi, Osamu Tokumoto, Mamiko Goto, Eiko Sato, Toru Fukumitsu, Takayuki Asakura, Kazuaki Ishida, Shunsuke Zama, Takahiro Ohnishi.
      A simultaneous analytical method was developed for the determination of deoxynivalenol (DON) and ochratoxin A (OTA) in wheat. Analytes were purified from wheat extracts by a multifunctional column and quantified by LC-MS/MS. An interlaboratory study was conducted to validate the analytical method using three spiked and two contaminated wheat samples. The ranges of mean recoveries of DON and OTA were 88-89% and 91-96%, respectively. The RSDs for repeatability and reproducibility were all ≤15%. Furthermore, the levels of DON and OTA in artificially contaminated wheat samples were analyzed by the simultaneous analytical method. The results showed that the developed analytical method yielded analytical values equivalent to those obtained when analyzing DON and OTA individually by existing analytical methods. Based on these results, the simultaneous analytical method for DON and OTA in wheat developed in this study is considered suitable as an alternative to the methods for analyzing each mycotoxin individually.
    Keywords:  deoxynivalenol; ochratoxin A; simultaneous analytical method; wheat
    DOI:  https://doi.org/10.3358/shokueishi.67.152
  50. Methods Mol Biol. 2026 ;3063 273-291
    Metabolomics Data Analysis with TIGER.
    Rui Wang-Sattler, Siyu Han.
      TIGER, a non-parametric method, was developed to address technical variations (e.g., plate and batch effects) in targeted and non-targeted metabolomics datasets. It integrates the random forest (RF) algorithm into a flexible ensemble learning framework, combining multiple base models with a meta-model. These base models are trained using diverse RF hyperparameter combinations, eliminating the need for manual hyperparameter tuning. This chapter highlights practical considerations for using TIGER effectively, including incorporating quality control (QC) samples into study design. When QCs are unavailable, randomly selected samples can be remeasured to facilitate cross-kit corrections. To optimize processing time, highly correlated metabolites from QC samples are selected to train the base models, with weights assigned via an exponential decay function. TIGER employs relative standard deviation (RSD) and mean absolute percentage error (MAPE) as key metrics to ensure models generalize well to unseen data while avoiding overfitting. Additionally, the developed dynamic website has been demonstrated with raw and TIGER-normalized data, enabling performance evaluation and visualization of longitudinal patterns of metabolites or metabolite ratios. This platform demonstrates TIGER's ability to accurately normalize data and uncover trends across three time points spanning a decade. With its proper application, TIGER stands to be a powerful tool for metabolomics studies.
    Keywords:  Batch correction; Cross-kit correction; Data-preprocessing; ML algorithms; Metabolomics; Non-targeted metabolomics; Targeted metabolomics
    DOI:  https://doi.org/10.1007/978-1-0716-5452-1_15
  51. Ann Clin Biochem. 2026 Sep 01. 45632261488256
    Comparability of serum folate concentration measured by a microbiological method, LC-MS/MS and immunoassay.
    Sarah Meadows, Amanda McKillion, Damon A Parkington, Albert Koulman, Kerry S Jones.
      Background Folate, vitamin B9, is an essential micronutrient for DNA replication and repair. Deficiency is associated with megaloblastic anaemia and fetal neural tube defects. Serum folate measurement provides a convenient biomarker of folate status in clinical and research settings. The overall aim of this evaluation was to compare serum folate results measured from three different technologies within the same laboratory to determine systematic biases and equivalence between methods. Methods 58 serum samples from the UK National Diet and Nutrition Survey were used to compare a microbiological method, a liquid chromatography tandem mass spectrometry method (LC-MS/MS) and a commercial immunoassay (Tosoh CL1200). Results Within-run imprecision of all three assays was ≤7%, measured at two concentrations. The microbiological and LC-MS/MS methods were accurate against NIST Standard Reference Material and VITAL External Quality Assessment (EQA) target values. The plasma-based sample used for the NIST Standard Reference Material (SRM) was unsuitable for analysis by the Tosoh immunoassay, however comparison with the VITAL EQA target values showed good accuracy. Using the serum samples, both the LC-MS/MS and Tosoh immunoassay methods showed a slight positive proportional bias compared to the microbiological method, whilst the Tosoh method also had an additional constant bias of 3-4 nmol/L compared to the other methods. Conclusions This data shows that the microbiological method, LC-MS/MS and Tosoh CL1200 immunoassay have acceptable accuracy, imprecision and agreement. The small concentration dependant bias is likely explainable by the expected characteristics of the individual methods and ability to detect and respond to different forms of folate.
    Keywords:  Immunoassay; Laboratory methods; Mass spectrometry
    DOI:  https://doi.org/10.1177/00045632261488256
  52. J Am Soc Mass Spectrom. 2026 Sep 02. 37(9): 2201-2214
    Impact of Salt and Urine Matrices on Electrokinetic Stacking Coupled to Paper Spray Mass Spectrometry.
    Jamison R Polley, Varadaraju V Dyavegowda, Lahiru Wedasingha, Merlin L Bruening, Nicholas E Manicke.
      Relative to liquid chromatography coupled to electrospray ionization (ESI), paper spray ionization (PSI) can more rapidly ionize analytes from complex matrices with less sample preparation and less expensive instrumentation. However, matrix effects can lead to ion suppression and poorer sensitivity. To overcome these problems, we combined on-paper faradaic ion concentration polarization (f-ICP), a form of electrokinetic stacking, with PSI to preconcentrate analytes directly on the spray substrate prior to ionization. Electrokinetic stacking also enables desalting because of the separation of analyte molecules from small ions like sodium. 3D-printed cartridges containing chemically modified PTFE papers were utilized with a high voltage isolated power supply to perform on-paper stacking from the same device as paper spray. In this study, ion suppression was compared for paper spray with and without electrokinetic stacking in the presence of five salts and artificial urine at varying concentrations. The signal enhancement achieved for f-ICP/PSI relative to normal PSI was also quantified. Finally, the effect of salt type and concentration on stacking time was assessed. Increasing salt concentrations generally results in longer stacking times and increased currents, indicative of increasing quantities of charge being desalted. In the presence of single salt-containing matrices, f-ICP/PSI frequently decreased ion suppression and gave a signal enhancement of 2 to >200× for small molecule drugs compared to unstacked paper spray (uPSI). In artificial urine, a more complex matrix with various salts and metabolites, f-ICP/PSI did not reliably decrease matrix effects due to creatinine and other matrix components costacking with the analytes. Nevertheless, f-ICP/PSI still resulted in signal enhancements of 8 to >50× relative to uPSI due to analyte preconcentration from electrokinetic stacking. Overall, this research demonstrated that f-ICP/PSI results in significant sensitivity improvements relative to uPSI.
    Keywords:  LTQ-XL; ambient ionization; chronoamperometry; electrochemistry; glass fiber; ion trap; method comparison; oxidation–reduction; platinum electrode; polyethylene; polytetrafluoroethylene; silylation; statistical analysis; toxicology
    DOI:  https://doi.org/10.1021/jasms.6c00238
  53. Rapid Commun Mass Spectrom. 2026 Nov 30. 40(22): e70171
    Profiling and Identification of Novel Tiletamine Metabolites in Human Urine and Hair by Liquid Chromatography Coupled With Quadrupole-Orbitrap Mass Spectrometry.
    Shiyang Qin, Guibin Bi, Yuanfeng Wang, Bing Liu, Zhenjia Cui, Xuxiao Zhao, Xiaopei Wu, Jing Jing, Jianghai Lu.
       RATIONALE: Tiletamine, an animal tranquilizer increasingly misused by humans, lacks comprehensive metabolic characterization in authentic biological matrices. To date, tiletamine phase II metabolism remains poorly characterized. This study investigated the metabolic fate of tiletamine in human urine and hair by identifying novel metabolites and elucidating biotransformation pathways relevant to forensic toxicological monitoring.
    METHODS: Authentic human urine (n = 3) and hair (n = 2) samples from individuals with documented tiletamine exposure were analyzed using liquid chromatography coupled with Q Extractive HF hybrid quadrupole-Orbitrap high-resolution mass spectrometry (LC-QE-HF-MS). Metabolites were detected and identified based on full-scan MS and data-dependent MS/MS (ddMS2) fragmentation patterns. Structural elucidation, including the assignment of hydroxylation sites, was achieved through a diagnostic fragment ion analysis.
    RESULTS: A total of 14 urinary metabolites were identified, 11 of which (4 phase I and 7 phase II) were previously unreported. Hydroxylation was the predominant phase I process, whereas glucuronidation predominated among phase II reactions. Methylation and glucuronidation were identified as previously unreported metabolic pathways. In hair samples, tiletamine and four metabolites, including three reduced metabolites and T1, were identified for the first time. In addition, three metabolic transformations, namely, reduction, hydroxylation, and methylation, were newly identified in this matrix. Notably, T1 exhibited substantially higher signal intensities than all other metabolites across all urine samples.
    CONCLUSIONS: This study substantially expands the known urinary metabolome by identifying novel phase I and II metabolites. The consistently high abundance of T1 in urine suggests that it is a promising urinary biomarker for monitoring tiletamine use. These findings broaden the range of analytical targets available for toxicological screening and confirmational analysis, thereby improving the detection and monitoring of tiletamine exposure.
    Keywords:  hair; human urine; liquid chromatography‐Q Extractive HF hybrid quadrupole‐Orbitrap‐mass spectrometer; metabolic profiles; tiletamine
    DOI:  https://doi.org/10.1002/rcm.70171
  54. Forensic Toxicol. 2026 Aug 31.
    Determination of xylazine, xylazine-4-hydroxy, and 2,6-dimethylaniline in canine urine: veterinary and forensic applications in two suspected poisoning cases.
    Zeynep Arslan, Cenk Bulut, Bengü Bilgiç, Yeter Erol Öztürk, Mehmet Erman Or, Zeynep Türkmen.
       PURPOSE: Xylazine, an α2-adrenergic agonist, is widely used in veterinary medicine for anesthesia, sedation, and analgesia. However, non-therapeutic use, overdose, and deliberate administration may pose serious health risks to animals, necessitating reliable detection methods for both clinical and forensic purposes.
    METHODS: In this study, a liquid chromatography-high-resolution mass spectrometry (LC-HRMS) method was developed and fully validated for the determination of xylazine and its metabolites in canine urine.
    RESULTS: The method exhibited excellent selectivity and linearity over the range of 0.05-100 ng/mL, with coefficients of determination (R²) ≥ 0.9989. Recovery values ranged from 70.3% to 93.4%, with matrix effect values between 78.6% and 95.6%, and process efficiency values ranging from 74.9% to 94.3%. Precision and accuracy values were within ± 15% at all quality control levels, and the analytes were stable under all tested conditions (+ 8 °C for 3 days, + 4 °C and - 20 °C for 5 days). In two forensic cases, urine samples collected from canines presenting with unconsciousness contained xylazine and its metabolites, while no other sedative or toxic agents were detected.
    CONCLUSION: The presence of both 2,6-dimethylaniline (DMA) and 4-hydroxyxylazine supports the necessity for including metabolite analysis in exposure assessment. This study highlights the applicability of LC-HRMS for the detection of xylazine-related compounds in canine urine and its potential use in veterinary and forensic toxicology contexts.
    Keywords:  2,6-Dimethylaniline; Forensic toxicology; Veterinary toxicology; Xylazine; Xylazine-4-hydroxy
    DOI:  https://doi.org/10.1007/s11419-026-00784-1
  55. Anal Chem. 2026 Aug 25. 98(33): 24249-24258
    Sequential MALDI and Nano-DESI MS Imaging of Lipids and Proteins on Stretched Tissue Samples.
    Timothy J Trinklein, Mushfeqa Iqfath, Emily A Clayton, Stanislav S Rubakhin, Julia Laskin, Jonathan V Sweedler.
      Imaging of both lipids and proteoforms in the same tissue section is a powerful approach to obtaining comprehensive molecular maps of biological systems. However, achieving high spatial resolution for both molecular classes remains challenging. Here, we combine tissue expansion with sequential imaging of lipids via matrix-assisted laser desorption/ionization (MALDI) and intact proteins via nanospray desorption electrospray ionization (nano-DESI) on the same tissue section to achieve comprehensive high-resolution molecular maps. Physical stretching of the tissue on Parafilm "M" produced a 4.5-fold effective resolution enhancement in both the X and Y dimensions (a ∼20-fold increase in area) in the mouse cerebellum for both MALDI and nano-DESI measurements. We further leveraged MALDI data to sharpen nano-DESI images using a partial least-squares (PLS) regression framework with a data consistency constraint. Finally, we applied midlevel fusion of MALDI and nano-DESI data to identify lipids and proteins localized to the same anatomical structures. Together, this straightforward workflow enables multimodal imaging of lipids and proteins from the same tissue section with improved spatial resolution and integrated analysis.
    DOI:  https://doi.org/10.1021/acs.analchem.6c02482
  56. J Am Soc Mass Spectrom. 2026 Sep 02. 37(9): 2168-2178
    Integrating Computational Chemistry and Ion Mobility Spectrometry into Non-Targeted Analysis Workflows for the Structural Elucidation of Emerging PFAS.
    Allison N Fry, Christian Ieritano, W Scott Hopkins, P B Armentrout, James N Dodds, Erin S Baker.
      Per- and polyfluoroalkyl substances (PFAS) are an evolving class of synthetic chemicals that are pervasive in the environment due to widespread manufacturing and consumer use, such that PFAS contamination is of great concern. Although thousands of PFAS structures have been reported to date, this number increases daily with the identification of new PFAS from advances in non-targeted analysis (NTA) workflows. Ion mobility spectrometry in combination with mass spectrometry (IMS-MS) has recently been incorporated into PFAS NTA studies. Although MS provides essential precursor and fragmentation data, IMS offers complementary structural information via the measurement of the ion-neutral collision cross section (CCS) values. Experimental CCS values can then be compared with those calculated in silico from candidate 3D structures to meet confidence-level criteria in analyte assignments within NTA workflows. Although this approach has been applied since the late 1990s, PFAS often exhibited poorer agreement between the calculated and experimental CCS values. To address this limitation, we propose an optimized computational workflow to calculate Boltzmann-weighted CCS values for PFAS structures generated via quantum-chemical calculations. This workflow was assessed with experimental CCS values from 56 known PFAS structures across seven classes and resulted in an average percent error of 2.0%. Moreover, 11 new PFAS structures were proposed from NTA, with average errors of 1.3%. The combination of this new computational workflow and experimental IMS-MS measurements therefore establishes a workflow for structural elucidation of emerging PFAS.
    Keywords:  ion mobility spectrometry; non-targeted analysis; quantum chemistry; structural elucidation
    DOI:  https://doi.org/10.1021/jasms.6c00201
  57. Anal Bioanal Chem. 2026 Sep 01.
    A valve-assisted 4-in-1 polarity-partitioned LC-QTOF-MS workflow reveals amino acid dysregulation in human chlorfenapyr poisoning.
    Gen Ba, Decai Cao, Jing Zhang, Zengzhen Wei, Beiyan Zhang, Mengxuan Chen, Jinsong Zhang, Huijie Huang, Yun Zhang, Zhengsheng Mao.
      Untargeted metabolomics of clinical toxicology samples is often constrained by limited sample volume, incomplete metabolome coverage, and technical variability introduced by multiple LC-MS injections. Here, we applied and evaluated a valve-assisted 4-in-1 polarity-partitioned LC-QTOF-MS workflow for single-injection plasma metabolomic profiling. The term "4-in-1" refers to four complementary LC-ionization data channels acquired from a single injection: HILIC-ESI(+), HILIC-ESI(-), C8-ESI(+), and C8-ESI(-). The workflow combines valve-controlled collection and transfer of weakly retained HILIC effluent with sequential HILIC and C8 analyses and dual-polarity MS acquisition. Quality-control analyses demonstrated stable retention behavior and reproducible feature detection, and the single-injection design reduced the need for multiple separate LC-MS injections. As a clinical toxicology application, the workflow was applied to plasma samples from patients with chlorfenapyr poisoning and healthy controls, with poisoned patients further stratified according to plasma tralopyril concentration. PCA and OPLS-DA were used as exploratory tools to visualize global metabolic differences. Differential LC-MS features were screened using multivariate and univariate statistical criteria, followed by metabolite annotation and pathway enrichment analysis based on annotated differential metabolites. Prominent perturbations were observed in amino acid metabolism, the urea cycle, and energy-related pathways. Several annotated amino acids, including glutamine, asparagine, alanine, and threonine, differed among the exposure groups. These exploratory findings support the feasibility of the workflow for limited-volume clinical plasma metabolomics and identify candidate metabolic alterations consistent with mitochondrial metabolic stress in chlorfenapyr poisoning.
    Keywords:  Amino acid metabolism; Chlorfenapyr poisoning; Polarity-partitioned workflow; Untargeted metabolomics; Valve-assisted LC-QTOF-MS
    DOI:  https://doi.org/10.1007/s00216-026-06784-9
  58. J Proteome Res. 2026 Sep 04. 25(9): 4734-4743
    Development of a Large-Scale Serum Metabolome Relative Quantitative Method and Application for Metabolic Traits of Colon Cancer.
    Shuting Yu, Guifang Ye, Jiaxin Gai, Rui Wei, Xinru Huang, Runjian Ren.
      Colon cancer (CC) is one of the malignant tumors with high incidence and mortality rates worldwide, necessitating innovative diagnostic tools to improve early detection and management. In this study, we developed a large-scale metabolome relative quantitative method workflow using ultrahigh-performance liquid chromatography coupled with Q-TRAP mass spectrometry to identify novel biomarkers in the serum of CC patients. This method enables the detection of 776 metabolic features, spanning 16 chemical classes and 63 metabolic pathways. All detected features were evaluated by multiple identification criteria and assigned confidence scores to ensure annotation reliability. Through validation and application of this method to clinical samples, we compared the serum metabolic profiles of CC patients with those of healthy controls and screened 72 significantly altered metabolites. Pathway enrichment analysis revealed perturbations in tryptophan metabolism, arginine biosynthesis, and the TCA cycle. Notably, three differential metabolites (indole, tryptophan, and xanthurenic acid) were identified that could potentially serve as diagnostic biomarkers with area under the curve values exceeding 0.9. Our large-scale metabolome relative quantitative method demonstrates applicability in identifying potential metabolite biomarkers for CC and provides a promising tool for both basic and clinical metabolomics research.
    Keywords:  LC-MS; colon cancer; metabolite biomarkers; serum metabolomics
    DOI:  https://doi.org/10.1021/acs.jproteome.6c00263
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