bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2026–04–05
eighteen papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz



  1. Angew Chem Int Ed Engl. 2026 Mar 30. e22119
      Accurate molecular annotation is essential for deciphering biochemical processes in spatial biology. Here, we present a scalable and broadly applicable molecular annotation tool for tandem mass spectrometry imaging (MS2I). Our workflow includes parallel image acquisition (PIA) for parallel MS2I and an open-access computational framework for spatial similarity networking (SSN) that enables molecular annotation of MS2I data with isomeric specificity. The PIA enables simultaneous untargeted MSI and targeted MS2I ensuring structure-specific imaging of hundreds of molecules in a single experiment. The SSN increases annotation confidence through graph-based spatial correlation of product ion distributions, opening up new avenues for data investigation and annotation from both MSI and MS2I data. By integrating PIA and SSN into a single workflow, we visualize and annotate 134 phospholipid isomers and isobars in mouse brain tissue. Furthermore, we demonstrate the biological utility of the platform by mapping cholesterol metabolism in human multiple sclerosis brain tissue, revealing lesion-associated cholesterol oxidation pathways. Finally, we propose annotation confidence levels for structural annotation in MSI. Overall, PIA and SSN together provide large-scale, structure-specific MSI, expanding the scope for spatial metabolomics, lipidomics, and chemical pathology through molecular annotation beyond current capabilities.
    Keywords:  annotation; isomers; lipids; mass spectrometry imaging; multiple sclerosis
    DOI:  https://doi.org/10.1002/anie.202522119
  2. J Am Soc Mass Spectrom. 2026 Apr 03.
      Protein O-glycosylation is one of the most common and important modifications in human cells. It regulates protein folding, trafficking, stability, and interactions with other molecules, and its dysregulation is directly related to numerous diseases such as cancer and neurodegenerative diseases. Modern mass spectrometry (MS)-based proteomics provides a unique opportunity to systematically characterize O-glycosylated proteins. However, it is still extremely challenging due to the low abundance of many glycoproteins, the heterogeneity of O-glycans, and the complexity of biological samples. In this review, we discuss recent advances in MS-based proteomics methods designed to overcome the challenges for global and site-specific characterization of protein O-glycosylation. We begin with an overview of the biosynthetic pathways underlying the major classes of protein O-glycosylation. Then, we discuss different methods to enrich O-glycopeptides with diverse structures of O-glycans. Furthermore, various MS dissociation techniques for intact glycopeptide profiling are covered. In addition, different quantitative approaches are included for studying protein O-glycosylation in biological and biomedical research. We also discuss computational tools for intact O-glycopeptide identification, highlighting the challenges in search space requirement, false discovery rate control, and glycosylation site localization. The advancements of MS-based glycoproteomics are critical for gaining insights into the critical roles of protein O-glycosylation in biology and human disease.
    Keywords:  Bottom-up Proteomics; Enrichment Methods; Fragmentation; Intact O-Glycopeptides; Mass Spectrometry; O-Glycoproteomics
    DOI:  https://doi.org/10.1021/jasms.6c00005
  3. Anal Chem. 2026 Apr 02.
      Single-cell proteomics (SCP) has emerged as a powerful approach for understanding cellular heterogeneity and biological processes at unprecedented resolution. However, the extremely limited protein content of individual cells (femtogram to picogram levels) pushes current mass spectrometry instrumentation to its sensitivity limits, creating a critical analytical bottleneck. While selected reaction monitoring (SRM) using triple quadrupole (QqQ) instruments offers advantages in sensitivity and reproducibility for targeted proteomics quantification, SRM still struggles with sensitivity for quantification of moderate- or low-abundance proteins from single-cell sample amounts. Here, we report the development and systematic evaluation of a dual ion funnel interface designed to address the sensitivity limitation by significantly enhancing ion transmission efficiency in commercial QqQ mass spectrometers. The dual ion funnel interface, composed of a curved S-funnel followed by a conventional ion funnel, improves ion transmission efficiency while reducing chemical noise through selective ion focusing. The performance of the dual ion funnel interface was systematically compared to standard interface on a TSQ Vantage platform across samples with different levels of complexity. The dual funnel interface demonstrated to provide up to 25-fold improvement in sensitivity across a wide range of protein concentrations in different biological matrices (low complex mouse macrophage and high complex human cells). Critically, enhanced sensitivity was accompanied by increased analytical reproducibility with lower coefficient of variations. Most importantly, the dual funnel interface enabled reliable quantification of low-abundance proteins that were barely detectable or not detected by the standard interface, extending analysis to single-cell equivalent amounts while maintaining excellent reproducibility. These results demonstrate that the dual funnel interface addresses the critical bottleneck in quantitative targeted proteomics, providing a technological foundation for ultrasensitive targeted SCP that requires both high sensitivity and robust quantitative performance.
    DOI:  https://doi.org/10.1021/acs.analchem.6c00113
  4. Sci Data. 2026 Apr 02. pii: 524. [Epub ahead of print]13(1):
      The domestic dog, Canis lupus familiaris, plays a vital role as companion or service animal, and the well-being and healthy aging of dogs is gaining importance. Proteins are key actors in cells, tissues and body fluids, and the ability to measure their composition and abundance is crucial to understand biological processes. We report a mass spectrometry-based proteomics approach analyzing canine tissues, plasma and urine obtained from Labrador retrievers to develop two comprehensive resources to advance the study of the dog proteome. Firstly, we developed a Labrador PeptideAtlas covering 49% of the predicted UniProtKB proteome and secondly, a Labrador spectral assay library for targeted applications by data-independent acquisition that enables the identification and quantification of 11,792 proteins (11,564 protein groups) of the dog proteome (56%). We demonstrate the performance of the library with gradients of different length and quantify 10,140 proteins in tissues and 385 proteins in plasma.
    DOI:  https://doi.org/10.1038/s41597-026-06647-z
  5. Anal Chem. 2026 Apr 01.
      Untargeted small molecule analysis by high-resolution mass spectrometry is integral to environmental and biological research, enabling comprehensive characterization of complex samples. However, data interpretation and reporting remain challenging due to the complexity and high dimensionality of molecular features in untargeted data sets. Current data analysis platforms provide integrated tools for processing and annotation yet lack a standardized framework for assigning and reporting annotation confidence. Communicating varying levels of confidence in untargeted data sets continues to pose challenges without an automated ranking system. To address this, a custom scripting node was developed that assigns annotation confidence levels based on the widely adopted Schymanski et al. scoring scheme. While implemented here for metabolomics, the scoring approach is broadly applicable to other untargeted small molecule workflows. The script can be incorporated into a commercial data analysis software package and functions as a standalone postprocessing node, expanding the original five-level system with four new sublevels (levels 3a/3b and 4a/4b) to improve specificity and distinguish cases that fall between established categories. Annotation confidence is assessed using available information from all compound identification workflow nodes (e.g., Predicted Composition, mzVault, mzCloud, ChemSpider), and the consensus scoring algorithm is used to evaluate agreement among search nodes for greater accuracy. Validation using NIST SRM 1950 plasma samples demonstrated 100% scoring accuracy in negative mode and >99.5% in positive mode across both RPLC and HILIC separations. This tool enhances data reporting, improves transparency, and promotes consistency across studies, facilitating standardization and comparability of untargeted metabolomics results.
    DOI:  https://doi.org/10.1021/acs.analchem.5c03229
  6. Angew Chem Int Ed Engl. 2026 Mar 30. e19836
      Combined proteomics, metabolomics, and lipidomics analyses require long liquid chromatography-mass spectrometry (LC-MS) run times, limiting throughput and increasing costs for large-scale studies. Here, we present single-injection multi-omics analysis by direct infusion (SMAD), an integrated platform leveraging ion mobility mass spectrometry and self-developed software tools to enable single injection multi-omics analysis without liquid chromatography. SMAD allows quantification of over 9000 metabolite m/z features and over 1300 proteins from the same sample in less than 5 min. We validated the efficiency and reliability of SMAD with three case studies: (1) mouse macrophages after M1/M2 polarization and senescence, (2) a pilot drug screen in human cells, and (3) large-scale high-throughput drug screening of mammalian cells in 96-well plates. Finally, relationships between proteomic and metabolomic data are discovered by machine learning and validated.
    Keywords:  chemical biology; lipidomics; macrophages; metabolomics; proteomics
    DOI:  https://doi.org/10.1002/anie.202519836
  7. mBio. 2026 Apr 02. e0378825
      Iron is required to support essential cellular processes. Due to diverse and dynamic host environments, the obligate intracellular parasite Toxoplasma gondii must adapt to iron-limited conditions. To investigate the adaptations critical to parasite survival under these conditions, we conducted proteomic and metabolomic profiling of Toxoplasma cultured in iron-depleted conditions. We find that iron depletion results in remodeling of the parasite proteome and triggers swift translational repression, prior to decreases in the key translational factor ABCE1. In the context of repressed translation, we also observe a significant rewiring of energy metabolism. Iron-depleted Toxoplasma have altered mitochondrial morphology and a profound reduction in mitochondrial respiration. Untargeted metabolomics revealed changes in central carbon metabolism, with the accumulation of intermediates of glycolysis and the tricarboxylic acid (TCA) cycle. Stable isotope labeling revealed that iron deprivation leads to a fundamental disconnect between these pathways, with reduced incorporation of glucose-derived carbon into cellular macromolecules and disruption of the TCA cycle. Instead, iron-deprived parasites continued to take up glucose and maintain glycolysis for energy generation. Limiting glucose availability, either in culture media or by genetic ablation of glucose uptake, caused a significant increase in sensitivity to iron restriction. Conversely, the limitation of mitochondrially metabolized glutamine improved parasite fitness in iron-depleted conditions. Together, our results establish iron as a key regulator of parasite translation and metabolic flexibility and demonstrate an increased reliance on glycolysis for energy generation and survival under acute iron deprivation.IMPORTANCEThis study determines the effects of iron deprivation on the parasite Toxoplasma gondii. Using proteomics and metabolomics, we reveal iron as a novel regulator of both protein translation and energy metabolism in Toxoplasma, underpinning the importance of this nutrient for essential cellular processes. We find that iron depletion introduces a metabolic bottleneck, whereby parasites become dependent on glucose as their major carbon source. By modulating the parasite's metabolism by altering carbon source availability, we identify nutrient conditions that improve parasite survival under iron restriction. These data reveal a key role for adaptive plasticity of Toxoplasma central carbon metabolism to drive survival under iron-limited conditions. Understanding the interactions between parasite nutrient availability and metabolism allows us both to map the metabolic flexibility of these parasites and identify potential vulnerabilities.
    Keywords:  Toxoplasma gondii; carbon metabolism; iron metabolism; iron regulation; mitochondrial metabolism; proteomics; translation
    DOI:  https://doi.org/10.1128/mbio.03788-25
  8. Anal Chim Acta. 2026 Jun 01. pii: S0003-2670(26)00268-0. [Epub ahead of print]1401 345318
       BACKGROUND: The structural elucidation and quantification of complex triacylglycerol (TAG) mixtures remain a major challenge in lipidomics due to extensive isomeric and isobaric diversity arising from differences in fatty-acyl chain length, unsaturation, and positional arrangement. Genetically engineering oilseeds to produce long-chain omega-3 fatty acids further expands this complexity by introducing numerous novel and low-abundance TAG species. A comprehensive method to quantify a wide diversity of TAG is required [67].
    RESULTS: To address these analytical demands, we developed a robust workflow using a Q-Exactive Orbitrap platform that integrates untargeted data dependent acquisition (DDA) with targeted parallel reaction monitoring (PRM) for accurate identification and quantification of TAG in genetically modified Camelina sativa engineered to synthesize EPA (20:5) and DHA (22:6). The combined DDA-PRM strategy, supported by retention-time validation, resolved 86% of isobaric TAG pairs and enabled confident assignment of 162 fully fatty-acid resolved TAG species. This is the highest number reported for any plant oil to date, including TAG containing non-native fatty-acids 22:6, 20:5, 22:5, 18:4, and 20:4 which were generated from the engineered enzyme activities. Quantitative accuracy was achieved using a response-factor approach that corrects for ionization efficiency differences, with validation against orthogonal GC-FID analysis [125].
    SIGNIFICANCE: The method provides four orders of linear dynamic range, exceeding previous PRM-based lipidomics on Q-TOF instruments. Custom scripts for response-factor calculation and PRM scheduling improved throughput and scalability. This integrated workflow bridges discovery driven lipidomics and high-precision quantitation, offering a versatile and reliable platform for TAG profiling in applications spanning plant metabolic engineering, nutritional quality assessment, and food authenticity [58].
    Keywords:  Camelina sativa; Mass spectrometry; Parallel reaction monitoring; Targeted lipidomics; Triacylglycerols
    DOI:  https://doi.org/10.1016/j.aca.2026.345318
  9. J Vis Exp. 2026 03 13.
      Plasma, the cell-free component of blood, offers a minimally invasive and rich source of biomolecular information, making it ideal for investigating systemic diseases. The advent of high-throughput proteomic technologies has revolutionized plasma analysis by enabling large-scale identification and quantification of circulating proteins. These advances have facilitated biomarker discovery for early diagnosis, prognosis, and therapeutic targeting of various disorders, including cancers and inflammatory diseases. However, the inherent complexity of plasma, along with inconsistent sample preparation and analysis methods, has historically limited proteome coverage and reproducibility. Early approaches relying on crude plasma analysis often suffered from poor consistency and significant batch effects, impeding reliable comparative studies across clinical cohorts. To overcome these limitations, the current study introduces a robust and scalable plasma proteomics workflow. The protocol integrates key preparatory steps such as immunodepletion, molecular weight cutoff filtration, lyophilization, protein quantification and normalization, enzymatic digestion, and LC-MS/MS profiling. This optimized strategy significantly enhances proteome depth and reduces variability, thereby enabling more accurate and reproducible differential protein expression analysis between disease cases and healthy controls. The workflow provides a valuable platform for researchers aiming to generate high-quality proteomic data from plasma, ultimately contributing to the advancement of biomarker-driven diagnostics and personalized medicine.
    DOI:  https://doi.org/10.3791/69359
  10. Methods Mol Biol. 2026 ;3026 69-77
      Cytokinins (CKs) are adenine-derived plant hormones regulating almost every aspect of plant growth and development. But CK-like compounds may also occur in microbial as well as mammalian systems. Detecting CKs in animal matrices is challenging due to low abundance and complex backgrounds. We describe a high-performance liquid chromatography-high-resolution mass spectrometry (HPLC-HRMS) protocol for CK extraction, purification, and quantification. Samples are frozen or lyophilized, homogenized, and extracted with methanol: water (80:20, v/v) containing stable isotope labeled CKs as internal standards. Solid-phase extraction (SPE) with C18 cartridges removes proteins and lipids, and purified eluates are dried, reconstituted, and analyzed by reversed-phase HPLC coupled to an Orbitrap mass spectrometer. Accurate-mass detection (≤5 ppm) and diagnostic fragmentation confirm identity, while isotope-dilution calibration enables picomolar sensitivity. This method provides high recovery (>75%) and selectivity, enabling investigation of CK occurrence in ex-planta cellular systems.
    Keywords:  Active form; Cytokinins; Non-plant systems; Plant hormones; Signalling molecules; Storage form; Two-component systems
    DOI:  https://doi.org/10.1007/978-1-0716-5214-5_6
  11. Proteomics. 2026 Mar 29. e70123
      Sensitivity, robustness, and reproducibility of sample preparation are main determinants of data quality in bottom-up mass spectrometry-based proteomics. To this end, in-gel protein clean-up and digestion has been used for decades and is characterized by its robustness and compatibility with harsh lysis conditions. Single-pot solid-phase-enhanced sample preparation (SP3) has gained substantial popularity recently and has been widely adapted as a standard workflow often replacing in-gel digestion-based workflows. Noteworthy, until today no direct comparison between the two workflows has been conducted. Here, we performed a systematic comparison of in-gel and SP3 based sample preparation workflows assessing sensitivity, robustness, reproducibility, and fractionation possibilities on human cellular lysates and blood plasma. Both methods performed similarly regarding number of identified proteins, however, showed specific biases. SP3 outperformed the in-gel workflow regarding higher sensitivity when handling limited sample amounts, especially below 5 µg of input material. In contrast, in-gel sample preparation was superior in the identification of low molecular weight proteins. In conclusion, while SP3 is indeed the state-of-the-art proteomics sample preparation method, in-gel digestion can deliver competitive and complementary results and still has advantages in some applications, such as measurement of small proteins or when there is a need for protein-level separation, e. g. in plasma samples.
    Keywords:  bottom‐up proteomics; in‐gel digestion; protein and peptide level fractionation; sample preparation; single‐pot Solid‐Phase Enhanced Sample preparation (SP3)
    DOI:  https://doi.org/10.1002/pmic.70123
  12. Anal Chem. 2026 Apr 02.
      Blood proteome is a highly informative biological fluid, reflecting physiological and pathological states across the entire body. It contains thousands of proteins spanning a dynamic range of more than 10 orders of magnitude. This makes blood proteome an ideal matrix for disease diagnosis, prognosis, therapeutic selection, and monitoring. However, comprehensive and reproducible analysis of blood proteins remains technically challenging, primarily due to the overwhelming presence of high-abundance proteins that obscure low-abundance targets. Blood proteome analysis offers several advantages over tissue-based diagnostics: it enables real time, longitudinal sampling, captures systemic physiological or pathological changes, and provides access to tissue-derived proteins. Automation offers consistent handling, reduced human error, and better reproducibility, which are essential for translating proteomics into routine biomedical workflows. We designed this platform to integrate Magnetic-COF-based protein capture with scalable robotic handling, enabling blood protein enrichment and LC-MS/MS analysis, resulting in more than 4000 plasma proteins identified with a throughput of 30 samples per day. By combining molecular selectivity, magnetic enrichment, and automation, our strategy addresses key limitations in current blood proteomics workflows and offers a flexible foundation for the research and discovery of proteomics from pancreatic ductal adenocarcinoma patients.
    DOI:  https://doi.org/10.1021/acs.analchem.5c08111
  13. J Proteome Res. 2026 Mar 30.
      Database search remains the primary strategy for peptide detection in mass spectrometry-based proteomics, but growing data sets and increasingly expansive peptide search spaces now challenge its computational limits. At the same time, machine learning has transformed multiple aspects of spectrum identification and is increasingly applied directly to peptide-spectrum matching. Neural network models have been proposed as core engines for database search, yet the computational complexities of such approaches have not been systematically defined or compared. Here, we present a range of emerging approaches for database search and a theoretical framework for runtime and scaling in spectrum identification, contrasting classical search strategies with emerging neural network-based methods. We analyze asymptotic complexity in the number of spectra and peptide candidates and estimate practical wall time and memory requirements under realistic hardware assumptions. Our framework highlights trade-offs and provides a guide for selecting and developing scalable peptide search strategies in the era of large models and proteomics data sets. We therefore consider whether learned scoring models may progressively replace or augment classical similarity functions at the peptide-spectrum scoring level.
    Keywords:  AI models; database search; de novo peptide sequencing; hybrid proteomics searches; machine learning; mass spectrometry; peptide spectrum match; proteomics; reference database
    DOI:  https://doi.org/10.1021/acs.jproteome.5c01153
  14. J Proteome Res. 2026 Mar 31.
      Laser capture microdissection (LCM) combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) enables spatial proteomics at the few-cell level but is constrained by cumulative losses during specimen capture, surface adsorption during processing, and sample transfer prior to LC-MS/MS analysis. The capture-associated losses are particularly relevant for pressure catapulting systems such as the legacy Zeiss PALM MicroBeam, which, despite discontinuation, remains in active use and therefore requires compatible low-loss workflows. We present MR-SP2 (microreactor-based sample preparation for spatial proteomics), a one-pot workflow integrating reproducible Zeiss LCM-cut specimen capture, processing with minimized adsorptive losses, and pipetting-free transfer with Evotip disposable precolumns. The workflow was evaluated using a formalin-fixed paraffin-embedded (FFPE) murine kidney tissue analyzed by timsTOF flex LC-MS/MS analysis. Across 50,000 μm3 regions (22 cells), MR-SP2 modestly improved proteome depth (3381 ± 80 versus 3174 ± 59 proteins). Decreasing sample input further accentuated the advantage of MR-SP2 in maintaining higher identification rates, highlighting the successful reduction of the adsorptive losses. At 12,500 μm3 (5-6 cells), identifications increased to 1145 ± 188 versus 302 ± 126. At 3125 μm3 (1-2 cells), identifications reached 695 ± 112 versus 206 ± 51. MR-SP2 improves identification depth for few-cell FFPE samples by nearly 3-fold compared to conventional tube-based workflows.
    Keywords:  FFPE; LC-MS/MS; LCM; few-cell proteomics; sample preparation; spatial proteomics
    DOI:  https://doi.org/10.1021/acs.jproteome.5c01231
  15. Clin Transl Oncol. 2026 Mar 28.
       BACKGROUND: Metabolomics offers novel insights into metabolic alterations in colorectal cancer (CRC), including changes in amino acid profiles. Several studies have reported differences between CRC patients and controls, suggesting potential diagnostic utility.
    PURPOSE: To evaluate evidence on amino acid alterations in CRC and advanced precursors across biological matrices and their potential as non-invasive biomarkers.
    METHOD: A comprehensive search of MEDLINE, EMBASE, and Cochrane CENTRAL identifi ed 77 studies analysing amino acids in faeces, urine, serum, plasma, tissue, and saliva.
    RESULTS: Few studies included advanced adenomas and none assessed advanced serrated polyps. Results were heterogeneous across matrices, except for tissue, where most amino acids were consistently upregulated in CRC. Reported diagnostic performance varied widely (AUC 0.28-0.91), with limited external validation.
    CONCLUSION: Overall, amino acids show limited standalone diagnostic value but may enhance multi-metabolitepanels. Standardisation, inclusion of early lesions, and robust validation are essential for future biomarker research.
    Keywords:  Amino acids; Colorectal cancer; Non-invasive biomarker; Sensitivity; Specificity
    DOI:  https://doi.org/10.1007/s12094-026-04278-9
  16. Clin Chim Acta. 2026 Mar 26. pii: S0009-8981(26)00168-3. [Epub ahead of print]588 120986
       BACKGROUND: Therapeutic drug monitoring (TDM) of tacrolimus requires accurate, high-throughput methods, but conventional liquid chromatography-tandem mass spectrometry (LC-MS/MS) is limited by lengthy run times and complex sample preparation.
    METHODS: We developed a chromatography-free assay for quantification of tacrolimus in whole blood by integrating cold-induced phase separation with acoustic ejection mass spectrometry (AEMS). This workflow only requires less than 10 μL of whole blood, eliminates centrifugation, and enables direct nanoliter-scale injection into the mass spectrometer. The AEMS assay performance was validated in accordance with CLSI C62-A and ICH M10 guidelines using 62 patient samples and matrix-matched calibrators, demonstrating its suitability for high-throughput therapeutic drug monitoring.
    RESULTS: The AEMS assay exhibited excellent linearity (0.5-50 μg/L; R2 = 0.9987), with a lower limit of quantification of 0.5 μg/L, which was well below clinically relevant trough concentrations. Accuracy (93.3%-100.1%) and precision (intra-day RSD: 3.7%-11.3%; inter-day RSD: 2.3%-12.4%) met regulatory acceptance criteria. Results showed strong concordance with routine LC-MS/MS (Spearman ρ = 0.972; Passing-Bablok slope = 1.100 [95% CI: 1.026-1.177]). The total analysis cycle time was less than 3 s per sample, enabling a throughput exceeding 1000 samples per hour theoretically.
    CONCLUSION: This study establishes the first chromatography-free mass spectrometry platform validated for clinical TDM of TAC. By integrating ultra-high throughput capability, minimal sample consumption, and robust analytical performance, the AEMS workflow offers a transformative analytical solution for high-demand clinical environments, including transplant centers and pediatric monitoring settings.
    Keywords:  AEMS; High throughput; Tacrolimus; Therapeutic drug monitoring
    DOI:  https://doi.org/10.1016/j.cca.2026.120986
  17. Anal Chem. 2026 Apr 03.
      Formic acid has long been the default acidic additive in reversed-phase LC-MS-based bottom-up proteomics, offering a practical balance between chromatographic performance and electrospray ionization (ESI) efficiency. Here, we evaluate propionic acid as an alternative mobile phase acidifier, a candidate that has been largely overlooked in efforts to improve ESI efficiency without compromising chromatography. By reducing both the ionic strength and surface tension of the mobile phase, propionic acid markedly enhanced ESI efficiency, yielding an average 39% increase in peptide identifications compared to formic acid and even a 12% increase relative to the recently revived acetic acid. These gains were consistent across interlaboratory data sets encompassing analytical- and microflow LC-MS configurations, diverse column chemistries, and varying sample complexities. Importantly, chromatographic performance remained virtually unaffected, with only a minor reduction in peptide retention. The mobile phase containing propionic acid was stable, instrument-compatible, and introduced a negligible background signal. Collectively, these findings challenge the long-standing reliance on formic acid and establish propionic acid as a robust, drop-in alternative for high-flow LC-MS workflows prioritizing MS sensitivity and proteome depth.
    DOI:  https://doi.org/10.1021/acs.analchem.5c07595
  18. Methods Mol Biol. 2026 ;3026 59-68
      Carotenoid oxidative cleavage products (apocarotenoids; APOs) represent an important class of specialized metabolites that exert diverse and important biological functions. Apocarotenoids are precursors of the plant hormones abscisic acid and strigolactones, pigments such as crocin and picrocrocin, and volatiles such as β-ionone and β-cyclocitral. Recently, carotenoid-derived bioactive metabolites such as zaxinone, anchorene, β-cyclocitral, and retinal have been identified as plant root growth regulators. Analysis of plant APOs is crucial for elucidating their biological function and metabolism as well as for determining their content in food. In this chapter, we describe an efficient protocol for a simultaneous analysis of plant APOs utilizing ultra-high performance liquid chromatographic (UPLC) separation and tandem mass spectrometry (MS). Additionally, we introduce practical details to assist researchers in setting up their experiments, extraction, and analysis of APOs.
    Keywords:  Apocarotenoids; Liquid chromatography; Mass spectrometry; Qualitative and quantitative analysis; Rice; Zaxinone
    DOI:  https://doi.org/10.1007/978-1-0716-5214-5_5