bims-mascan 2025-05-18 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2025–05–18
28 papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Recombinant Protein Spectral Library (rPSL) DIA-MS method improves identification and quantification of low-abundance cancer-associated and kynurenine pathway proteins.
Approaches to stable isotope tracing and in vivo metabolomics in the cancer clinic.
Quantitative Proteomics on Immune Cells of ME/CFS Patients Using SWATH-MS.
Mitochondrial HSP90 paralog TRAP1 deletion drives glutamine addiction in tumor cells via destablization of the Cys/Glu antiporter SLC7A11/xCT.
A Multipoint Validation of Quantification in Capillary Electrophoresis Mass Spectrometry Proteomics: Isobaric Multiplexing with Tandem Mass Tags.
Metabolic pathway analysis of tumors using stable isotopes.
A universal language for finding mass spectrometry data patterns.
Computational modeling of cancer cell metabolism along the catabolic-anabolic axes.
Direct Microplate Sampling Mass Spectrometry for High-Throughput Screening of Biocatalytic Activity.
Mathematical model-assisted HPLC-MS/MS analysis on global, pseudo-targeted ceramide profiling and quantitation in serum.
Advances in Spatial Multi-Omics: A Review of Multi-Modal Mass Spectrometry Imaging and Laser Capture Microdissection-LCMS Integration.
ProteoPlotter: An Executable Proteomics Visualization Tool Compatible with Perseus.
Single-Cell Proteomics Using the One-Step Droplet-in-Oil Digestion Method Reveals Proteins Important for Male Meiotic Progression.
Mass spectrometry-based metabolomic as a powerful tool to unravel the component and mechanism in TCM.
Technical Evaluation of Plasma Proteomics Technologies.
Practical Considerations for Implementing Targeted Mass Spectrometry for Urine Drug Testing in Clinical Laboratories.
Stearoyl-CoA Desaturase 1 deficiency drives saturated lipid accumulation and increases liver and plasma acylcarnitines.
Metabolic reprogramming of interleukin-17-producing γδ T cells promotes ACC1-mediated de novo lipogenesis under psoriatic conditions.
Serum Norepinephrine and Cholesterol Concentrations as Novel Diagnostic Biomarkers for Vitamin E Deficiency in Holstein Cows.
Benchmarking of Trapped Ion Mobility Spectrometry in Differentiating Plasmalogens from Other Ether Lipids in Lipidomics Experiments.
Proteome Birthdating: A Single-Sample Approach for Measuring Global Turnover Dynamics and "Protein Age".
Automated Quality Assurance Rules for Liquid Chromatography-Mass Spectrometry Testing in a Clinical Laboratory.
LC-ESI(±)-LTQ MSn-Based Metabolomic Profiling of Coffee: Fragmentation Pathways for Identification of Major Polar Compounds.
Polar Lipid Extraction and Analysis During Conifer Needle Abscission.
Basic features of cellular inositol metabolism as revealed by a newly developed LC-MS method.
Wide-range and high-throughput quantification of anamorelin in human plasma using ultra-high-performance liquid chromatography coupled to tandem mass spectrometry.
Benzoyl Chloride Derivatization Coupled With Liquid Chromatography-Mass Spectrometry for the Simultaneous Quantification of Molnupiravir and Its Metabolite β-d-N4-hydroxycytidine in Human Plasma.
Recommendations for sample selection, collection and preparation for NMR-based metabolomics studies of blood.

Commun Chem. 2025 May 10. 8(1): 141

Recombinant Protein Spectral Library (rPSL) DIA-MS method improves identification and quantification of low-abundance cancer-associated and kynurenine pathway proteins.

Shivani Krishnamurthy, Bavani Gunasegaran, Moumita Paul-Heng, Abidali Mohamedali, William P Klare, C N Ignatius Pang, Laurence Gluch, Joo-Shik Shin, Charles Chan, Mark S Baker, Seong Beom Ahn, Benjamin Heng.

Data-independent acquisition mass spectrometry (DIA-MS) is a powerful tool for quantitative proteomics, but a well-constructed reference spectral library is crucial to optimize DIA analysis, particularly for low-abundance proteins. In this study, we evaluate the efficacy of a recombinant protein spectral library (rPSL), generated from tryptic digestion of 42 human recombinant proteins, in enhancing the detection and quantification of lower-abundance cancer-associated proteins. Additionally, we generated a combined sample-specific biological-rPSL by integrating the rPSL with a spectral library derived from pooled biological samples. We compared the performance of these libraries for DIA data extraction with standard methods, including sample-specific biological spectral library and library-free DIA methods. Our specific focus was on quantifying cancer-associated proteins, including key enzymes involved in kynurenine pathway, across patient-derived tissues and cell lines. Both rPSL and biological-rPSL-DIA approaches provided significantly improved coverage of lower-abundance proteins, enhancing sensitivity and more consistent protein quantification across matched tumour and adjacent noncancerous tissues from breast and colorectal cancer patients and in cancer cell lines. Overall, our study demonstrates that rPSL and biological-rPSL coupled with DIA-MS workflows, can address the limitations of both biological library-based and library-free DIA methods, offering a robust approach for quantifying low-abundance cancer-associated proteins in complex biological samples.

DOI: https://doi.org/10.1038/s42004-025-01531-0
EMBO J. 2025 May 12.

Approaches to stable isotope tracing and in vivo metabolomics in the cancer clinic.

Brandon Faubert, Alpaslan Tasdogan.



Keywords:  Cancer Metabolism; Intraoperative Patient Infusions; Stable Isotope Tracing

DOI:  https://doi.org/10.1038/s44318-025-00450-z
Methods Mol Biol. 2025 ;2920 113-140

Quantitative Proteomics on Immune Cells of ME/CFS Patients Using SWATH-MS.

Abhishek Kumar, Katie Peppercorn, Torsten Kleffmann.

  Proteomics is one of the "omics" disciplines that has provided molecular insights into the pathophysiology of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Here we describe a complete SWATH-MS workflow for the quantitative profiling of proteins extracted from peripheral mononuclear blood cells to investigate proteomic alterations in ME/CFS. This workflow covers all steps of sample preparation, data acquisition, and data analysis. We describe the process of generating a comprehensive spectral library from a pre-fractionated peptide reference sample followed by the acquisition of DIA data sets of individual samples using a 5600+ TripleTOF mass spectrometer. Examples of both library-based and library-free data analysis pipelines are presented based on the PeakView/MarkerView software package (commercial) and DIA-NN (free) software respectively.

Keywords:  ME/CFS; Quantitative proteomics; SWATH-MS

DOI:  https://doi.org/10.1007/978-1-0716-4498-0_8
Mol Cancer Res. 2025 May 16.

Mitochondrial HSP90 paralog TRAP1 deletion drives glutamine addiction in tumor cells via destablization of the Cys/Glu antiporter SLC7A11/xCT.

Abhinav Joshi, Li Dai, Marisa Maisiak, Sunmin Lee, Elizabeth Lopez, Takeshi Ito, Len Neckers.

TRAP1, the mitochondrial isoform of HSP90, has emerged as a key regulator of cancer cell metabolism, yet the mechanisms by which it rewires nutrient utilization remain poorly understood. We previously reported that TRAP1 loss increases glutamine dependency of mitochondrial respiration following glucose withdrawal. Here, we investigate how TRAP1 deletion impacts glucose metabolism and the mechanisms enabling glutamine retention to support mitochondrial respiration via reductive carboxylation and the oxidative TCA cycle. TRAP1 knockout (KO) in bladder and prostate cancer cells recapitulates the carbon source-specific metabolic rewiring previously observed. Stable isotope tracing reveals that although glucose oxidation remains functional, TRAP1 KO reduces overall glucose uptake and its contribution to glycolysis and the pentose phosphate pathway. This effect is consistent across multiple cell lines. Concurrently, TRAP1-deficient cells exhibit increased glutamine retention and reliance, potentially due to downregulation of the cystine/glutamate antiporter SLC7A11/xCT. Supporting this, xCT overexpression reduces glutamine-dependent respiration in TRAP1 KO cells. qPCR and proteasome inhibition assays suggest xCT is regulated post-translationally via protein stability. Notably, xCT suppression does not trigger ferroptosis, indicating a selective adaptation rather than induction of cell death. Together, our findings suggest that TRAP1 loss decreases glucose uptake while preserving its metabolic fate, promoting glutamine conservation through xCT downregulation to maintain mitochondrial respiration without inducing ferroptosis. Implications: These results reveal a TRAP1-dependent mechanism of metabolic rewiring in cancer cells and identify xCT-mediated glutamine conservation as a key adaptive response, underscoring TRAP1 as a potential metabolic vulnerability and therapeutic target in tumors with altered nutrient utilization.

DOI: https://doi.org/10.1158/1541-7786.MCR-24-0194
Anal Chem. 2025 May 13.

A Multipoint Validation of Quantification in Capillary Electrophoresis Mass Spectrometry Proteomics: Isobaric Multiplexing with Tandem Mass Tags.

Laura G Rodriguez, Camille Lombard-Banek, Vi M Quach, Sam B Choi, M Chiara Manzini, Peter Nemes.

Multiplexing quantification using isobaric barcoding has gained traction in trace-sensitive and single-cell mass spectrometry (MS), both in nanoflow liquid chromatography (nanoLC) and capillary electrophoresis (CE). In nanoLC-MS, ratio compression from isobaric interferences is known to challenge quantification accuracy during tandem MS (MS2), which is effectively remedied using simultaneous precursor selection (SPS) MS3. Despite mounting interest in CE-MS for trace-sensitive bottom-up proteomics, the fidelity of multiplexed quantification is unknown using this technology. Here, we address this fundamental knowledge gap by holistically investigating quantification depth, reproducibility, and accuracy using a validated mouse-yeast two-proteome model. CE-based quantification via the MS2 and SPS-MS3 strategies were benchmarked against the nanoLC SPS-MS3 gold standard. We found electrophoresis-correlative (Eco) ion sorting to order peptides into high-flux transients of nominally isobaric m/z values (Δm/z < 1-2 Th). While the MS2 approach struggled with ratio distortion, the SPS-MS3 robustly eliminated them for both separations. The reproducibility and accuracy proved indistinguishable between CE and nanoLC using MS2 or SPS-MS3 quantification. CE enhanced the depth of quantification by ∼12-fold. These analytical insights can be used to design trace CE-MS studies with high scientific rigor.

DOI: https://doi.org/10.1021/acs.analchem.5c01832
Semin Cancer Biol. 2025 May 08. pii: S1044-579X(25)00063-X. [Epub ahead of print]113 9-24

Metabolic pathway analysis of tumors using stable isotopes.

Qiufen Bi, Junzhang Zhao, Jun Nie, Fang Huang.

  Metabolic reprogramming is pivotal in malignant transformation and cancer progression. Tumor metabolism is shaped by a complex interplay of both intrinsic and extrinsic factors that are not yet fully elucidated. It is of great value to unravel the complex metabolic activity of tumors in patients. Metabolic flux analysis (MFA) is a versatile technique for investigating tumor metabolism in vivo, it has increasingly been applied to the assessment of metabolic activity in cancer in the past decade. Stable-isotope tracing have shown that human tumors use diverse nutrients to fuel central metabolic pathways, such as the tricarboxylic acid cycle and macromolecule synthesis. Precisely how tumors use different fuels, and the contribution of alternative metabolic pathways in tumor progression, remain areas of intensive investigation. In this review, we systematically summarize the evidence from in vivo stable- isotope tracing in tumors and describe the catabolic and anabolic processes involved in altered tumor metabolism. We also discuss current challenges and future perspectives for MFA of human cancers, which may provide new approaches in diagnosis and treatment of cancer.

Keywords:  Cancer metabolism; Metabolic flux analysis; Stable-isotope tracing

DOI:  https://doi.org/10.1016/j.semcancer.2025.05.002
Nat Methods. 2025 May 12.

A universal language for finding mass spectrometry data patterns.

Tito Damiani, Alan K Jarmusch, Allegra T Aron, Daniel Petras, Vanessa V Phelan, Haoqi Nina Zhao, Wout Bittremieux, Deepa D Acharya, Mohammed M A Ahmed, Anelize Bauermeister, Matthew J Bertin, Paul D Boudreau, Ricardo M Borges, Benjamin P Bowen, Christopher J Brown, Fernanda O Chagas, Kenneth D Clevenger, Mario S P Correia, William J Crandall, Max Crüsemann, Eoin Fahy, Oliver Fiehn, Neha Garg, William H Gerwick, Jeffrey R Gilbert, Daniel Globisch, Paulo Wender P Gomes, Steffen Heuckeroth, C Andrew James, Scott A Jarmusch, Sarvar A Kakhkhorov, Kyo Bin Kang, Nikolas Kessler, Roland D Kersten, Hyunwoo Kim, Riley D Kirk, Oliver Kohlbacher, Eftychia E Kontou, Ken Liu, Itzel Lizama-Chamu, Gordon T Luu, Tal Luzzatto Knaan, Helena Mannochio-Russo, Michael T Marty, Yuki Matsuzawa, Andrew C McAvoy, Laura-Isobel McCall, Osama G Mohamed, Omri Nahor, Heiko Neuweger, Timo H J Niedermeyer, Kozo Nishida, Trent R Northen, Kirsten E Overdahl, Johannes Rainer, Raphael Reher, Elys Rodriguez, Timo T Sachsenberg, Laura M Sanchez, Robin Schmid, Cole Stevens, Shankar Subramaniam, Zhenyu Tian, Ashootosh Tripathi, Hiroshi Tsugawa, Justin J J van der Hooft, Andrea Vicini, Axel Walter, Tilmann Weber, Quanbo Xiong, Tao Xu, Tomáš Pluskal, Pieter C Dorrestein, Mingxun Wang.

Despite being information rich, the vast majority of untargeted mass spectrometry data are underutilized; most analytes are not used for downstream interpretation or reanalysis after publication. The inability to dive into these rich raw mass spectrometry datasets is due to the limited flexibility and scalability of existing software tools. Here we introduce a new language, the Mass Spectrometry Query Language (MassQL), and an accompanying software ecosystem that addresses these issues by enabling the community to directly query mass spectrometry data with an expressive set of user-defined mass spectrometry patterns. Illustrated by real-world examples, MassQL provides a data-driven definition of chemical diversity by enabling the reanalysis of all public untargeted metabolomics data, empowering scientists across many disciplines to make new discoveries. MassQL has been widely implemented in multiple open-source and commercial mass spectrometry analysis tools, which enhances the ability, interoperability and reproducibility of mining of mass spectrometry data for the research community.

DOI: https://doi.org/10.1038/s41592-025-02660-z
NPJ Syst Biol Appl. 2025 May 10. 11(1): 46

Computational modeling of cancer cell metabolism along the catabolic-anabolic axes.

Javier Villela-Castrejon, Herbert Levine, Benny A Kaipparettu, José N Onuchic, Jason T George, Dongya Jia.

Abnormal metabolism is a hallmark of cancer, this was initially recognized nearly a century ago through the observation of aerobic glycolysis in cancer cells. Mitochondrial respiration can also drive tumor progression and metastasis. However, it remains largely unclear the mechanisms by which cancer cells mix and match different metabolic modalities (oxidative/reductive) and leverage various metabolic ingredients (glucose, fatty acids, glutamine) to meet their bioenergetic and biosynthetic needs. Here, we formulate a phenotypic model for cancer metabolism by coupling master gene regulators (AMPK, HIF-1, MYC) with key metabolic substrates (glucose, fatty acids, and glutamine). The model predicts that cancer cells can acquire four metabolic phenotypes: a catabolic phenotype characterized by vigorous oxidative processes-O, an anabolic phenotype characterized by pronounced reductive activities-W, and two complementary hybrid metabolic states-one exhibiting both high catabolic and high anabolic activity-W/O, and the other relying mainly on glutamine oxidation-Q. Using this framework, we quantified gene and metabolic pathway activity by developing scoring metrics based on gene expression. We validated the model-predicted gene-metabolic pathway association and the characterization of the four metabolic phenotypes by analyzing RNA-seq data of tumor samples from TCGA. Strikingly, carcinoma samples exhibiting hybrid metabolic phenotypes are often associated with the worst survival outcomes relative to other metabolic phenotypes. Our mathematical model and scoring metrics serve as a platform to quantify cancer metabolism and study how cancer cells adapt their metabolism upon perturbations, which ultimately could facilitate an effective treatment targeting cancer metabolic plasticity.

DOI: https://doi.org/10.1038/s41540-025-00525-x
Anal Chem. 2025 May 15.

Direct Microplate Sampling Mass Spectrometry for High-Throughput Screening of Biocatalytic Activity.

Shuai Guo, Zhizhong Wen, Long Chen, Mengchen Jia, Yajing Wang, Jingfang Sun.

The development of biocatalysis depends heavily on high-throughput screening (HTS) approaches to uncover engineered enzymes with superior biocatalytic activity. Recent advances in mass spectrometry (MS) enable label-free, high-speed analysis of biocatalytic samples in standard microplates by omitting the chromatographic separation. However, most MS methods need a complicated sampling interface system and face challenges due to biological matrix interferences, which can diminish the sensitivity and reliability. Herein, we established a direct microplate sampling (DMS)-MS technique for HTS of the enzymatic activity of 17β-hydroxysteroid dehydrogenase (17β-HSD) in steroid biocatalysis. The implementation of an open port interface (OPI) probe with a customized ion source for microwell direct insertion sampling and ionization has streamlined the setup, reduced operational complexity, and shortened the analysis time to 0.9-6.5 s/sample. A sample preparation strategy involving derivatization, followed by high-ratio dilution (e.g., 10,000-fold), was further integrated prior to DMS-MS for mitigating ion suppression effects across diverse biological matrices. Ultimately, this workflow, when applied for monitoring multiple steroids in 17β-HSD biocatalytic processes, demonstrated high stability (peak area RSDs < 7%), minimal carryover (<1%), and quantitative accuracy comparable to conventional liquid chromatography (LC) experiments while providing a >150-fold throughput enhancement. After screening a total of 5760 17β-HSD mutants across three different steroid conversion reactions, we identified and verified two new variants with enhanced biocatalytic activities. This study successfully established a DMS-MS-based HTS workflow for microplate screening, providing a simplified, robust, and highly reliable analytical platform for microbial or enzyme engineering projects involving complex biological matrices.

DOI: https://doi.org/10.1021/acs.analchem.5c00267
Anal Chim Acta. 2025 Jul 08. pii: S0003-2670(25)00493-3. [Epub ahead of print]1358 344099

Mathematical model-assisted HPLC-MS/MS analysis on global, pseudo-targeted ceramide profiling and quantitation in serum.

Fei Ge, Jingai Jian, Na Li, Jingzhi Yang, Yufan Chao, Xin Dong.

  Ceramides (Cers) play a crucial role in sphingolipid metabolism with multiple biological activities and functions. Due to the high regularity and variability of their structures, there exist thousands of possible Cers. The structural diversity endows them with various biological functions but also poses significant challenges for qualitative and quantitative analysis. The lack of in-depth characterization methods for such lipids resulted in only a small fraction of Cers being reported, severely hindering the exploration of their biological functions and activities. This work presented a lipid analysis method based on a liquid chromatography-mass spectrometry platform, enabling the accurate quantification of 337 Cers simultaneously. Supported by a mathematical model, this work succeeded in generating a quadratic equation relationship between retention time and Cers carbon number. Subsequently, this method was applied to the large-scale quantitative detection of Cers in serum samples from Alzheimer's disease (AD) patients, identifying and characterizing 62 differential Cers. These could potentially serve as serum biomarkers for AD diagnosis. This study demonstrates a strategy for the large-scale in-depth characterization of complex endogenous lipid molecules with highly variable and regular structures in the absence of sufficient commercial standard materials. This work provides a novel analysis method and reference for exploring and developing the functions of such endogenous bioactive molecules.

Keywords:  Alzheimer's disease; Ceramide; High performance liquid chromatography-mass spectrometry; Pseudo-targeted lipid analysis; Sphingolipid metabolism

DOI:  https://doi.org/10.1016/j.aca.2025.344099
Proteomics. 2025 May 12. e202400378

Advances in Spatial Multi-Omics: A Review of Multi-Modal Mass Spectrometry Imaging and Laser Capture Microdissection-LCMS Integration.

Jessica K Lukowski, Byoung-Kyu Cho, Antonia Zamacona Calderon, Borna Dianati, Katherine Stumpo, Savannah Snyder, Young Ah Goo.

  Mass spectrometry has long been utilized to characterize a variety of biomolecules such as proteins, metabolites, and lipids. Most MS-based omics studies rely on bulk analysis; however, bulk approaches often overlook low-abundance molecules that may exert critical biological effects. Recently, multi-omics analyses have been driving an explosion of knowledge about how biomolecules interact within biological systems. In particular, spatial multi-omics has emerged as a groundbreaking approach for implementing multi-omic and multi-modal analyses. Broadly defined, spatial omics has the ability to analyze biomolecules within their native spatial contexts, offering transformative insights. This review focuses on mass spectrometry-based spatial omics, specifically matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). We will explore how MALDI-MSI, in combination with laser capture microdissection (LCM) and traditional liquid chromatography-mass spectrometry (LC-MS) workflow, is advancing spatially resolved multi-omics research.

Keywords:  LCM‐LC‐MS/MS; MALDI‐MSI; spatial multi‐omics

DOI:  https://doi.org/10.1002/pmic.202400378
J Proteome Res. 2025 May 13.

ProteoPlotter: An Executable Proteomics Visualization Tool Compatible with Perseus.

Esther Olabisi-Adeniyi, Jason A McAlister, Daniela Ferretti, Juergen Cox, Jennifer Geddes-McAlister.

  Mass spectrometry-based proteomics experiments produce complex data sets requiring robust statistical testing and effective visualization tools to ensure meaningful conclusions are drawn. The publicly available proteomics data analysis platform, Perseus, is extensively used to perform such tasks, but opportunities to enhance visualization tools and promote accessibility of the data exist. In this study, we developed ProteoPlotter, a user-friendly, executable tool to complement Perseus for visualization of proteomics data sets. ProteoPlotter is built on the Shiny framework for R programming and enables illustration of multidimensional proteomics data. ProteoPlotter supports mapping of one-dimensional enrichment analyses, enhanced adaptability of volcano plots through incorporation of Gene Ontology terminology, visualization of 95% confidence intervals in principal component analysis plots using data ellipses, and customizable features. ProteoPlotter is designed for intuitive use by biological and computational researchers alike, providing descriptive instructions (i.e., Help Guide) for preparing and uploading Perseus output files. Herein, we demonstrate the application of ProteoPlotter toward microbial proteome remodeling under altered nutrient conditions and highlight the diversity of visualizations enabled with the platform for enhanced biological insights. Through its comprehensive data visualization capabilities, linked to the power of Perseus data handling and statistical analyses, ProteoPlotter facilitates enhanced visualization of proteomics data to drive new biological discoveries.

Keywords:  1D annotation enrichment; Klebsiella pneumoniae; Perseus; UpSet plots; Venn diagrams; data visualization; dynamic range; heat maps; proteomics; volcano plots

DOI:  https://doi.org/10.1021/acs.jproteome.4c00963
Anal Chem. 2025 May 14.

Single-Cell Proteomics Using the One-Step Droplet-in-Oil Digestion Method Reveals Proteins Important for Male Meiotic Progression.

Yue Wang, Hao Chen, Zongze Li, Mengmeng Gao, Qingyun Yu, Xu Chen, Chenghao Situ, Yaling Qi, Yan Li, Yueshuai Guo, Hui Zhu, Xuejiang Guo.

Different from DNA or RNA, proteins cannot be amplified. The performance of single-cell proteomics is limited by sample loss during sample preparation. Here, we present a one-step droplet-in-oil digestion (OSDO) method that involves one-step water-in-oil processing using cyclohexane or n-heptane, which can reduce the sample adsorption loss and sample volume change due to evaporation and increase the sensitivity and stability of single-cell proteomics. The OSDO is demonstrated to be compatible with tandem mass tag (TMT) labeling to improve the throughput. The OSDO, followed by data-independent acquisition (DIA), quantified more than 3700 proteins per cell during meiotic progression from pachytene to metaphase I, with no correlation between protein and mRNA levels. Inhibition of VPS34 and DNMT1, two proteins up-regulated in metaphase I, both affected metaphase I formation. The OSDO is an easy-to-operate method compatible with both subsequent labeled and unlabeled quantification to expand the depth, throughput, and applicability in single-cell proteomics.

DOI: https://doi.org/10.1021/acs.analchem.4c06467
Chin Med. 2025 May 12. 20(1): 62

Mass spectrometry-based metabolomic as a powerful tool to unravel the component and mechanism in TCM.

Guang-Qin Liao, Hong-Mei Tang, Yuan-Di Yu, Li-Zhi Fu, Shuang-Jiao Li, Mai-Xun Zhu.

  Mass spectrometry (MS)-based metabolomics has emerged as a transformative tool to unraveling components and their mechanisms in traditional Chinese medicine (TCM). The integration of advanced analytical platforms, such as LC-MS and GC-MS, coupled with metabolomics, has propelled the qualitative and quantitative characterization of TCM's complex components. This review comprehensively examines the applications of MS-based metabolomics in elucidating TCM efficacy, spanning chemical composition analysis, molecular target identification, mechanism-of-action studies, and syndrome differentiation. Recent innovations in functional metabolomics, spatial metabolomics, single-cell metabolomics, and metabolic flux analysis have further expanded TCM research horizons. Artificial intelligence (AI) and bioinformatics integration offer promising avenues for overcoming analytical bottlenecks, enhancing database standardization, and driving interdisciplinary breakthroughs. However, challenges remain, including the need for improved data processing standardization, database expansion, and understanding of metabolite-gene-protein interactions. By addressing these gaps, metabolomics can bridge traditional practices and modern biomedical research, fostering global acceptance of TCM. This review highlights the synergy of advanced MS techniques, computational tools, and TCM's holistic philosophy, presenting a forward-looking perspective on its clinical translation and internationalization.

Keywords:  Component analysis; Mass spectrometry; Mechanism; Metabolomics; Traditional Chinese medicine

DOI:  https://doi.org/10.1186/s13020-025-01112-2
J Proteome Res. 2025 May 14.

Technical Evaluation of Plasma Proteomics Technologies.

William F Beimers, Katherine A Overmyer, Pavel Sinitcyn, Noah M Lancaster, Scott T Quarmby, Joshua J Coon.

  Plasma proteomics technologies are rapidly evolving and of critical importance to the field of biomedical research. Here, we report a technical evaluation of six notable plasma proteomics technologies─unenriched (Neat), acid depletion, PreOmics ENRICHplus, Mag-Net, Seer Proteograph XT, and Olink Explore HT. The methods were compared on proteomic depth, reproducibility, linearity, tolerance to lipid interference, and limit of detection/quantification. In total, we performed 618 LC-MS/MS experiments and 93 Olink Explore HT assays. The Seer method achieved the greatest proteomic depth (∼4500 proteins detected), while Olink detected ∼2600 proteins. Other MS-based methods ranged from ∼500-2200 proteins detected. In our analysis, Neat, Mag-Net, Seer, and Olink had good reproducibility, while PreOmics and Acid had higher variability (>20% median coefficient of variation). All MS methods showed good linearity with spiked-in C-reactive protein (CRP); CRP was surprisingly not in the Olink assay. None of the methods were affected by lipid interference. Seer produced the highest number of quantifiable proteins with a measurable LOD (4407) and LOQ (2696). Olink had the next highest number of quantifiable proteins, with 2002 having an LOD and 1883 having an LOQ. Finally, we tested the applicability of these methods for detecting differences between healthy and cancer groups in a nonsmall cell lung cancer (NSCLC) cohort. All six methods detected differentially abundant proteins between the cancer and healthy samples but disagreed on which proteins were significant, highlighting the contrast between each method.

Keywords:  LC-MS; Mag-Net; Olink; PreOmics; Seer; mass spectrometry; method comparison; plasma; proteomics

DOI:  https://doi.org/10.1021/acs.jproteome.5c00221
Clin Lab Med. 2025 Jun;pii: S0272-2712(25)00003-4. [Epub ahead of print]45(2): 165-176

Practical Considerations for Implementing Targeted Mass Spectrometry for Urine Drug Testing in Clinical Laboratories.

Patrick D DeArmond, Dustin R Bunch.

  The use of tandem mass spectrometry (MS/MS) for urine drug testing has expanded in recent decades due to an increasing demand for compliance testing and confirmation of positive immunoassay results. While it has been demonstrated to be a robust methodology, MS/MS cannot control all variables associated with sample collection and testing. This review will touch on many factors of targeted MS/MS assays pertaining to drugs, metabolism, and proper method development. Various preanalytical and analytical considerations will be discussed, and best practice guidelines are suggested for controlling sample-to-sample variability.

Keywords:  Compliance; Drugs of abuse; Internal standard; LC-MS/MS; Liquid chromatography; Sample cleanup; Toxicology

DOI:  https://doi.org/10.1016/j.cll.2025.01.002
J Lipid Res. 2025 May 09. pii: S0022-2275(25)00084-7. [Epub ahead of print] 100824

Stearoyl-CoA Desaturase 1 deficiency drives saturated lipid accumulation and increases liver and plasma acylcarnitines.

Mugagga Kalyesubula, Helaina Von Bank, Jessica W Davidson, Maggie S Burhans, Madelaine M Becker, Ahmed Aljohani, Judith Simcox, James M Ntambi.

  Stearoyl-CoA desaturase-1 (SCD1) is a critical regulator of lipogenesis that catalyzes the synthesis of monounsaturated fatty acids (MUFA), mainly oleate (18:1n-9) and palmitoleate (16:1n-7) from saturated fatty acids (SFA), stearoyl-CoA (18:0) and palmitoyl-CoA (16:0), respectively. Elevated SCD1 expression and its products are associated with obesity, metabolic dysfunction-associated steatotic liver disease, insulin resistance, and cancer. Conversely, Scd1 deficiency diminishes de novo lipogenesis and protects mice against adiposity, hepatic steatosis, and hyperglycemia. Yet, the comprehensive impact of Scd1 deficiency on hepatic and circulating lipids remains incompletely understood. To further delineate the effects of SCD1 on lipid metabolism, we employed lipidomics on the liver from mice under a lipogenic high carbohydrate, very low-fat diet. We found that Scd1 deficiency leads to an accumulation of saturated lipids and an increase in hepatic and plasma acylcarnitines. Remarkably, transgenic replenishment of de novo oleate synthesis by human SCD5 in the liver of Scd1-deficient mice not only restored hepatic lipid desaturation levels but also attenuated acylcarnitine accumulation, highlighting the distinct role of SCD1 and oleate in regulating intracellular lipid homeostasis.

Keywords:  Acylcarnitines; SCD1; SCD5; SFA; lipidomics; oleate

DOI:  https://doi.org/10.1016/j.jlr.2025.100824
Nat Metab. 2025 May 13.

Metabolic reprogramming of interleukin-17-producing γδ T cells promotes ACC1-mediated de novo lipogenesis under psoriatic conditions.

Yu-San Kao, Mario Lauterbach, Aleksandra Lopez Krol, Ute Distler, Gloria Janet Godoy, Matthias Klein, Rafael Jose Argüello, Fatima Boukhallouk, Sara Vallejo Fuente, Kathrin Luise Braband, Assel Nurbekova, Monica Romero, Panagiota Mamareli, Luana Silva, Luis Eduardo Alves Damasceno, Francesca Rampoldi, Luciana Berod, Lydia Lynch, Karsten Hiller, Tim Sparwasser.

Metabolic reprogramming determines γδ T cell fate during thymic development; however, the metabolic requirements of interleukin (IL)-17A-producing γδ T cells (γδT17 cells) under psoriatic conditions are unclear. Combining high-throughput techniques, including RNA sequencing, SCENITH, proteomics and stable isotope tracing, we demonstrated that psoriatic inflammation caused γδT17 cells to switch toward aerobic glycolysis. Under psoriatic conditions, γδT17 cells upregulated ATP-citrate synthase to convert citrate to acetyl-CoA, linking carbohydrate metabolism and fatty acid synthesis (FAS). Accordingly, we used a pharmacological inhibitor, Soraphen A, which blocks acetyl-CoA carboxylase (ACC), to impair FAS in γδT17 cells, reducing their intracellular lipid stores and ability to produce IL-17A under psoriatic conditions in vitro. We pinpointed the pathogenic role of ACC1 in γδT17 cells in vivo by genetic ablation, ameliorating inflammation in a psoriatic mouse model. Furthermore, ACC inhibition limited human IL-17A-producing γδT17 cells. Targeting ACC1 to attenuate pathogenic γδT17 cell function has important implications for psoriasis management.

DOI: https://doi.org/10.1038/s42255-025-01276-z
Animals (Basel). 2025 May 06. pii: 1333. [Epub ahead of print]15(9):

Serum Norepinephrine and Cholesterol Concentrations as Novel Diagnostic Biomarkers for Vitamin E Deficiency in Holstein Cows.

Yuxi Song, Xuejie Jiang, Yu Hao, Rui Sun, Yunlong Bai, Chuang Xu, Cheng Xia.

  Vitamin E deficiency (VED) represents a common micronutrient deficiency in dairy cows (DCs), leading to severe degenerative diseases, oxidative stress, immune dysfunction, and various health issues, ultimately causing significant economic losses for the global dairy sector. Accordingly, our objective was to explore the metabolic features of VED-afflicted cows by combining the untargeted gas chromatography-time-of-flight mass spectrometry (GC-TOF-MS) and targeted liquid chromatography-mass spectrometry (LC-MS) to identify effective serum VED biomarkers. Untargeted GC-TOF-MS analysis identified 31 differential metabolites (DMs): 20 were overexpressed and 11 were suppressed in the VED group compared to the healthy control group. These DMs were enriched in six major metabolic pathways: glycine, serine, and threonine; alanine, aspartate, and glutamate; cysteine and methionine; tyrosine; primary bile acid biosynthesis; and nitrogen metabolisms. These outcomes show that VED significantly disrupts amino acid/lipid/energy metabolism pathways in DCs. Further targeted LC-MS quantification revealed significant alterations in key metabolites, including increased levels of norepinephrine, glycine, cysteine, and L-glutamine, as well as a significant reduction in cholesterol concentrations. Binary logistic regression analysis identified norepinephrine and cholesterol as strong candidate biomarkers for VED. Receiver operating characteristic curve analysis established outstanding diagnostic accuracy for norepinephrine and cholesterol (for both p < 0.001, area under the curve = 0.980 and 0.990, correspondingly), with sensitivities and specificities of 90% and 100%, respectively. In conclusion, this study integrates untargeted and targeted metabolomics approaches to reveal VED-caused metabolic disruptions in DCs, particularly in amino acid/lipid/energy metabolism pathways. Norepinephrine and cholesterol were identified as highly accurate serum VED biomarkers with excellent diagnostic performance. Early detection and timely intervention using these biomarkers could promote disease treatment and cow health, as well as productivity, and decrease economic losses.

Keywords:  GC-TOF-MS; LC-MS; dairy cows; metabolomics; vitamin E deficiency

DOI:  https://doi.org/10.3390/ani15091333
Anal Chem. 2025 May 13.

Benchmarking of Trapped Ion Mobility Spectrometry in Differentiating Plasmalogens from Other Ether Lipids in Lipidomics Experiments.

Jakob Koch, Lukas Neumann, Katharina Lackner, Monica L Fernández-Quintero, Katrin Watschinger, Markus A Keller.

Trapped Ion Mobility Spectrometry (TIMS) has demonstrated promising potential as a powerful discriminating method when coupled with mass spectrometry, enhancing the precision of feature annotation. Such a technique is particularly valuable for lipids, where a large number of isobaric but structurally distinct molecular species often coexist within the same sample matrix. In this study, we explored the potential of ion mobility for ether lipid isomer differentiation. Mammalian ether phospholipids are characterized by a fatty alcohol residue at the sn-1 position of their glycerol backbone. They can make up to 20% of the total phospholipid mass and are present in a broad range of tissues. There they are, for example, crucial for nervous system function, membrane homeostasis, and inter- as well as intracellular signaling. Molecular ether lipid species are difficult to distinguish analytically, as they occur as 1-O-alkyl and 1-O-alkenyl subclasses, with the latter being also known as plasmalogens. Isomeric ether lipid pairs can be separated with reversed-phase chromatography. However, their precise identification remains challenging due to the lack of clear internal reference points, inherent to the nature of lipid profiles and the lack of sufficient commercially available standard substances. Here, we demonstrate─with focus on phosphatidylethanolamines─that ion mobility measurements allow to discriminate between the ether lipid subclasses through distinct differences in their gas phase geometries. This approach offers significant advantages as it does not depend on potential retention time differences between different chromatographic systems. However, the current resolution in the ion mobility dimension is not sufficient to baseline separate 1-O-alkyl and 1-O-alkenyl isobars, and the observed differences are not yet accurately represented in existing collision cross section databases. Despite these challenges, the predictable properties of the ion mobility behavior of ether lipid species can significantly support their accurate annotation and hold promise for future advancements in lipid research.

DOI: https://doi.org/10.1021/acs.analchem.4c06617
Bio Protoc. 2025 May 05. 15(9): e5296

Proteome Birthdating: A Single-Sample Approach for Measuring Global Turnover Dynamics and "Protein Age".

Michael E Meadow, Sarah Broas, Margaret Hoare, Maria Ahmed, Fatemeh Alimohammadi, Kevin A Welle, Kyle Swovick, Jennifer R Hryhorenko, Anushka Jain, John C Martinez, Andrei Seluanov, Vera Gorbunova, Abigail Buchwalter, Sina Ghaemmaghami.

  Within a cell, proteins have distinct and highly variable half-lives. As a result, the molecular ages of proteins can range from seconds to years. How the age of a protein influences its environmental interactions is a largely unexplored area of biology. To facilitate such studies, we recently developed a technique termed "proteome birthdating" that differentially labels proteins based on their time of synthesis. Proteome birthdating enables analyses of age distributions of the proteome by tandem mass spectrometry (LC-MS/MS) and provides a methodology for investigating the protein age selectivity of diverse cellular pathways. Proteome birthdating can also provide measurements of protein turnover kinetics from single, sequentially labeled samples. Here, we provide a practical guide for conducting proteome birthdating in in vitro model systems. The outlined workflow covers cell culture, isotopic labeling, protein extraction, enzymatic digestion, peptide cleanup, mass spectrometry, data processing, and theoretical considerations for interpretation of the resulting data. Key features • Proteome birthdating barcodes the proteome with isotopically labeled precursors based on time of synthesis or "age." • Global protein turnover kinetics can be analyzed from single, sequentially labeled biological samples. • Protein age distributions of subsets of the proteome can be analyzed (e.g., ubiquitinated proteins). • Age selectivity of protein properties, cellular pathways, or disease states can be investigated.

Keywords:  Mass spectrometry; Neutron-encoded amino acids; Protein age; Protein turnover; Proteome birthdating

DOI:  https://doi.org/10.21769/BioProtoc.5296
Clin Lab Med. 2025 Jun;pii: S0272-2712(25)00007-1. [Epub ahead of print]45(2): 221-232

Automated Quality Assurance Rules for Liquid Chromatography-Mass Spectrometry Testing in a Clinical Laboratory.

Gina Cassella-Mclane, Myles McGowan, Jillian Kodger, Thomas J S Durant.

  Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has seen an enormous increase in applications, such as toxicology, biochemical genetics, endocrinology, therapeutic drug monitoring, and dietary monitoring. Although LC-MS/MS has the potential to offer significant clinical benefit to patients and clinicians, these assays often require significant effort and complex quality-assurance data review processes to ensure accurate results. Manual LC-MS/MS data review is time consuming and susceptible to human error. Automation of data review can reduce time spent on manually reviewing each chromatogram, reduce human error, and improve practice and ensure regulatory compliance with the rules and guidelines established by the College of American Pathologists (CAP), Clinical Laboratory Improvement Amendments (CLIA), and Clinical and Laboratory Standards Institute (CLSI) C62-A.

Keywords:  CLSI 62-A; Chromatography; Data review; Data validation; LC-MS; LDT; Quality assurance

DOI:  https://doi.org/10.1016/j.cll.2025.01.006
J Am Soc Mass Spectrom. 2025 May 13.

LC-ESI(±)-LTQ MSn-Based Metabolomic Profiling of Coffee: Fragmentation Pathways for Identification of Major Polar Compounds.

Marcos Valério Vieira Lyrio, Danieli Grancieri Debona, Amanda Eiriz Feu, Nayara Araujo Dos Santos, Arlan da Silva Gonçalves, Ricardo Machado Kuster, Eustáquio Vinícius Ribeiro de Castro, Wanderson Romão.

  Coffee is characterized by a complex chemical matrix that significantly influences its organoleptic properties and market value. This complexity is driven by factors such as botanical species, geographical origin, cultivation conditions, and post-harvest processing methods. Metabolomic studies aim to elucidate how these factors impact the biosynthesis of metabolites that contribute to the sensory qualities of high-quality coffee. Among various analytical techniques, liquid chromatography-mass spectrometry (LC-MS) is particularly effective for separating, identifying, and quantifying these compounds. Most metabolomic studies employ high-resolution mass spectrometry (HRMS) for its superior mass accuracy (<1 ppm), whereas the interpretation of low-resolution data requires additional effort, often relying on literature references and proposed fragmentation mechanisms. In this study, we applied LC-ESI(±)LTQ MSn to comprehensively profile coffee metabolites, identifying 60 compounds, including polar compounds and their isomers such as chlorogenic acids, carbohydrates, amino acids, alkaloids, glycosylated diterpenes, and flavonoids. Fragmentation mechanisms were proposed and discussed. The results demonstrate the effectiveness of LC-ESI(±)LTQ MSn in a detailed metabolomic analysis, providing a robust platform for future research in coffee metabolomics.

Keywords:  Coffee; Linear ion trap; Liquid chromatography; Mass spectrometry; Tandem MS

DOI:  https://doi.org/10.1021/jasms.4c00418
Methods Mol Biol. 2025 ;2916 109-119

Polar Lipid Extraction and Analysis During Conifer Needle Abscission.

Mason T MacDonald, Chijioke U Emenike.

  Extracting and analyzing polar lipids during conifer needle abscission is crucial for comprehending the associated lipid dynamics. A combination of polar and nonpolar solvents for lipid extraction is actively used in lipid analysis during conifer needle abscission. Conifer needle tissue is particularly difficult to work on for several reasons, which must be considered during sample preparation and lipid extraction. Further, conditions like in situ tissue harvest, postharvest tissue harvest, and extraction protocol influence the analysis of target lipids in the plant. The use of electrospray ionization tandem mass spectrometry (ESI-MS/MS) facilitates the simultaneous and thorough analysis of many polar lipids in conifer tissue samples.

Keywords:  Chloroform:methanol; Conifer; Fatty acid; Galactolipid; Mass spectrometry; Phospholipid; Plant lipids

DOI:  https://doi.org/10.1007/978-1-0716-4470-6_11
Biochem J. 2025 May 13. pii: BCJ-2025-3028. [Epub ahead of print]

Basic features of cellular inositol metabolism as revealed by a newly developed LC-MS method.

Xue Bessie Su, Valeria Fedeli, Guizhen Liu, Meike Amma, Paraskevi Boulasiki, Jingyi Wang, Mariano Bizzarri, Henning Jessen, Dorothea Fiedler, Antonella Riccio, Adolfo Saiardi.

  Inositol plays key roles in many cellular processes. Several studies focussed on the quantitative analysis of phosphorylated forms of inositol, enabled by analytical tools developed to detect these highly charged molecules. Direct measurement of free inositol however has been challenging, because the molecule is uncharged and polar. As a result, the mechanisms maintaining the homeostasis of the inositol remains poorly understood. In this study, we overcome these challenges by developing a quantitative liquid chromatography - mass spectrometry (LC-MS) protocol that can resolve and quantify the three main sugar molecules present inside cells: glucose, fructose, and inositol, as well as distinguish the clinically relevant isomers of inositol: myo-, scyllo-, and chiro-inositol. The quantitative power of the new method was validated by accurately monitoring the changes of inositol levels under well-established conditions in Saccharomyces cerevisiae, where the endogenous synthesis of inositol is increased in the transcription repressor OPI1 knockout opi1D and decreased when wild type yeast is fed with exogenous inositol. The method also revealed a new layer of regulation that takes place when exogenous inositol is added to further boost endogenous inositol synthesis in opi1D in a positive feedback loop. Analyses of mammalian cell lines provided many new insights into inositol metabolism. First, different cell lines displayed distinct sugar profiles and inositol concentrations and responded differently to inositol starvation. Second, mammalian cells can synthesize and import scyllo- but not chiro-inositol. Importantly, our method lent direct evidence to the previous hypothesis that lithium treatment could significantly reduce inositol levels in primary cortical neurons, thus diminishing the pool of free inositol available to the phosphoinositide cycle.

Keywords:  ISYNA1; Ino1; Inositide signalling; Inositol polyphosphates; LC-MS; Opi1; Phosphatidylinositol; chiro-inositol; inositol depletion hypothesis; lithium; myo-inositol; scyllo-inositol; sugar

DOI:  https://doi.org/10.1042/BCJ20253028
Clin Biochem. 2025 May 13. pii: S0009-9120(25)00078-5. [Epub ahead of print] 110949

Wide-range and high-throughput quantification of anamorelin in human plasma using ultra-high-performance liquid chromatography coupled to tandem mass spectrometry.

Takahiro Sumimoto, Ryota Tanaka, Ayaka Sato, Ryosuke Tatsuta, Hiroki Itoh.

   OBJECTIVE: Cancer cachexia is characterized by weight loss, muscle mass loss, and reduced food intake. Anamorelin is a ghrelin receptor agonist approved for the treatment of cancer cachexia. In this study, we established and validated an assay for quantification of anamorelin in human plasma.
METHODS: For quantification of anamorelin, samples were pretreated with solid-phase extraction and analyzed by ultra-high performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS). This analytical method was validated in accordance with the Food and Drug Administration (FDA) bioanalytical method validation guidance. We used the established assay to quantify plasma anamorelin concentrations in five patients with cancer cachexia treated with anamorelin.
RESULTS: The validation results of this assay method met the acceptance criteria recommended by the FDA guidance. Within-batch and batch-to-batch precision at the lower limit of quantification and three quality control levels were within 6.20 % and 6.55 % coefficient of variation, respectively. Within-batch and batch-to-batch accuracies ranged from -2.58 to -1.33 % and -3.78 to -1.69 %, respectively. Recovery rates and matrix effects corrected by internal standard were 82.7-84.2 % and 102.7-104.6 %, respectively. Using the established assay with a calibration range of 0.1-2500 ng/mL, plasma anamorelin concentrations were successfully quantified in all 15 plasma samples from 5 patients with cancer cachexia.
CONCLUSIONS: We established and validated a method to measure plasma anamorelin concentrations using UHPLC/MS-MS combined with SPE, and successfully applied the novel method to measure plasma anamorelin concentrations in patients with cancer cachexia. By measuring plasma anamorelin concentrations in large scale studies, the established quantitative method is expected to contribute to the pharmacokinetic study of anamorelin.

Keywords:  Anamorelin; Cachexia; Solid-phase extraction; UHPLC-MS/MS

DOI:  https://doi.org/10.1016/j.clinbiochem.2025.110949
J Sep Sci. 2025 May;48(5): e70162

Benzoyl Chloride Derivatization Coupled With Liquid Chromatography-Mass Spectrometry for the Simultaneous Quantification of Molnupiravir and Its Metabolite β-d-N4-hydroxycytidine in Human Plasma.

Zhilong Yuan, Tao Ma, Lin Xia, Kaile Zheng, Mengdan Liu, Xiujuan Han, Wenjing Zhang, Zhuo Wang.

  A sensitive and efficient method for simultaneous quantifying molnupiravir and its active metabolite β-d-N4-hydroxycytidine in human plasma was developed by combining chemical derivatization with liquid chromatography-tandem mass spectrometry. Through benzoyl chloride chemical derivatization, the analytes exhibited improved mass spectral responses and enhanced chromatographic retention. Besides, the fragmentation patterns were optimized to identify analyte-specific fragments, enhancing detection specificity beyond the common benzoyl fragments. These advancements enabled the method to achieve the lower limits of quantification of 0.4 ng/mL for molnupiravir and 1.0 ng/mL for β-d-N4-hydroxycytidine, which represents the lowest reported quantification limits values to date while demonstrating a 30-fold sensitivity enhancement compared to the non-derivatized method under identical instrument conditions. In addition, the sample preparation protocol was streamlined, combining derivatization and sample extraction in a single step, completed within 5 min, eliminating the need for additional handling or reaction time. After undergoing comprehensive validations, the method was successfully applied to clinical samples from patients receiving molnupiravir therapy, demonstrating its practicality for pharmacokinetic monitoring. By combining operational simplicity with sensitivity, this assay provides a reliable tool for advancing research on molnupiravir metabolism and therapeutic drug monitoring.

Keywords:  COVID‐19; LC‐MS/MS; chemical derivatization; molnupiravir

DOI:  https://doi.org/10.1002/jssc.70162
Metabolomics. 2025 May 10. 21(3): 66

Recommendations for sample selection, collection and preparation for NMR-based metabolomics studies of blood.

Abdul-Hamid Emwas, Helena U Zacharias, Marcos Rodrigo Alborghetti, G A Nagana Gowda, Daniel Raftery, Ryan T McKay, Chung-Ke Chang, Edoardo Saccenti, Wolfram Gronwald, Sven Schuchardt, Roland Leiminger, Jasmeen Merzaban, Nour Y Madhoun, Mazhar Iqbal, Rawiah A Alsiary, Rupali Shivapurkar, Arnab Pain, Dhanasekaran Shanmugam, Danielle Ryan, Raja Roy, Horst Joachim Schirra, Vanessa Morris, Ana Carolina Zeri, Fatimah Alahmari, Rima Kaddurah-Daouk, Reza M Salek, Marcia LeVatte, Mark Berjanskii, Brian Lee, David S Wishart.

   BACKGROUND: Metabolic profiling of blood metabolites, particularly in plasma and serum, is vital for studying human diseases, human conditions, drug interventions and toxicology. The clinical significance of blood arises from its close ties to all human cells and facile accessibility. However, patient-specific variables such as age, sex, diet, lifestyle and health status, along with pre-analytical conditions (sample handling, storage, etc.), can significantly affect metabolomic measurements in whole blood, plasma, or serum studies. These factors, referred to as confounders, must be mitigated to reveal genuine metabolic changes due to illness or intervention onset.
REVIEW OBJECTIVE: This review aims to aid metabolomics researchers in collecting reliable, standardized datasets for NMR-based blood (whole/serum/plasma) metabolomics. The goal is to reduce the impact of confounding factors and enhance inter-laboratory comparability, enabling more meaningful outcomes in metabolomics studies.
KEY CONCEPTS: This review outlines the main factors affecting blood metabolite levels and offers practical suggestions for what to measure and expect, how to mitigate confounding factors, how to properly prepare, handle and store blood, plasma and serum biosamples and how to report data in targeted NMR-based metabolomics studies of blood, plasma and serum.

Keywords:  Blood; Metabolites; Metabolomics; NMR; Plasma; Serum; Standardization

DOI:  https://doi.org/10.1007/s11306-025-02259-7