bims-mascan 2024-10-06 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2024‒10‒06
23 papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh

Recommendations for Accurate Lipid Annotation and Semi-absolute Quantification from LC-MS/MS Datasets.
Reversed-Phase Ultrahigh-Performance Liquid Chromatography-Mass Spectrometry Method for High-Throughput Lipidomic Quantitation.
Distinguishing Artifactual Fatty Acid Dimers from Fatty Acid Esters of Hydroxy Fatty Acids in Untargeted LC-MS Pipelines.
Modular, Scalable, and Customizable LC-HRMS for Exposomics.
CE-MS-Based Clinical Metabolomics of Human Plasma.
Stable Isotope Tracing Experiments Using LC-MS.
Rapid Lipid Mediator Profiling by Convergence Chromatography-MS/MS.
Annotation of Metabolites in Stable Isotope Tracing Untargeted Metabolomics via Khipu-web.
Extracting Knowledge from MS Clinical Metabolomic Data: Processing and Analysis Strategies.
Quantification of Total Ketone Bodies in Biological Matrices Using Stable Isotope-Labeled Internal Standards and RP-UHPLC-MS/MS.
(Pre)Clinical Metabolomics Analysis.
Global Metabolomics Using LC-MS for Clinical Applications.
Data-Independent Acquisition Mass Spectrometry as a Tool for Metaproteomics: Interlaboratory Comparison Using a Model Microbiome.
NMR-Based Analysis of Cellular Central Energy Metabolism and Exchange Rates.
Application of a Computational Metabolomics Workflow for the Diagnosis of Inborn Errors of Metabolism in a Laboratory Setting.
Ultrahigh-Performance Supercritical Fluid Chromatography-Mass Spectrometry in the Clinical Lipidomic Analysis.
High-Throughput RPLC-MS/MS Quantification of Short- and Medium-Chain Fatty Acids.
Comprehensive Proteomic Profiling of Converted Adipocyte-like Cells from Normal Human Dermal Fibroblasts Using Data-Independent Acquisition Mass Spectrometry.
In Situ Isotope Tracing at Single-Cell Resolution Using Mass Spectrometry Imaging.
A Multiplexed Quantitative Proteomics Approach to the Human Plasma Protein Signature.
Differential Mobility Spectrometry-Based Cardiolipin Analysis.
Intrinsic temperature increase drives lipid metabolism towards ferroptosis evasion and chemotherapy resistance in pancreatic cancer.
Optimized high-throughput protocols for comprehensive metabolomic and lipidomic profiling of brain sample.

Methods Mol Biol. 2025 ;2855 269-287

Recommendations for Accurate Lipid Annotation and Semi-absolute Quantification from LC-MS/MS Datasets.

Michele Wölk, Maria Fedorova.

  Recent developments in LC-MS instrumentation and analytical technologies together with bioinformatics tools supporting high-throughput processing of large omics datasets significantly enhanced our capabilities and efficiency of identification and quantification of lipids in diverse biological materials. However, each biological matrix is characterized by its unique lipid composition, thus requiring optimization of analytical and bioinformatics workflows for each studied lipidome. Here, we describe an integrated workflow for deep lipidome profiling, accurate annotation, and semi-absolute quantification of complex lipidomes based on reversed phase chromatography and high resolution mass spectrometry. This chapter provides details on selection of the optimal extraction protocol, acquisition of LC-MS/MS data for accurate annotation of lipid molecular species, and design of lipidome-specific mixtures of internal standards to assist quantitative analysis of complex, native lipidomes.

Keywords:  High resolution mass spectrometry; Lipid annotations; Lipidomics; Quantitative lipidomics

DOI:  https://doi.org/10.1007/978-1-0716-4116-3_16
Methods Mol Biol. 2025 ;2855 185-194

Reversed-Phase Ultrahigh-Performance Liquid Chromatography-Mass Spectrometry Method for High-Throughput Lipidomic Quantitation.

Zuzana Vaňková, Ondřej Peterka, Robert Jirásko, Michal Holčapek.

  Reversed-phase ultrahigh-performance liquid chromatography-mass spectrometry (RP-UHPLC/MS) method is optimized for the quantitation of a large number of lipid species in biological samples, primarily in human plasma and serum. The method uses a C18 bridged ethylene hybrid (BEH) column (150 × 2.1 mm; 1.7 μm) for the separation of lipids from 23 subclasses with a total run time of 25 min. Lipid species separation allows the resolution of isobaric and isomeric lipid forms. A triple quadrupole mass spectrometer is used for targeted lipidomic analysis using multiple reaction monitoring (MRM) in the positive ion mode. Data are evaluated by Skyline software, and the concentrations of analytes are determined using internal standards per each individual lipid class.

Keywords:  High-throughput lipidomics; Mass spectrometry; Plasma; Quantitation; Reversed-phase; Serum; Ultrahigh-performance liquid chromatography

DOI:  https://doi.org/10.1007/978-1-0716-4116-3_12
Methods Mol Biol. 2025 ;2855 67-84

Distinguishing Artifactual Fatty Acid Dimers from Fatty Acid Esters of Hydroxy Fatty Acids in Untargeted LC-MS Pipelines.

Alisa B Nelson, Eric D Queathem, Patrycja Puchalska.

  Untargeted metabolomics is a powerful profiling tool for the discovery of possible biomarkers of disease onset and progression. Analytical pipelines applying liquid chromatography (LC) and mass spectrometry (MS)-based methods are widely used to survey a broad range of metabolites within various metabolic pathways, including organic acids, amino acids, nucleosides, and lipids. Accurate and complete identification of putative metabolites is an ongoing challenge in untargeted metabolomics studies. Highly sensitive instrumentation can result in the detection of adduct and fragment ions that form reproducibly and contain identifiable ions that are difficult to distinguish from metabolic pathway intermediates, which may result in false-positive identification. At concentrations as low as 10 μM, free fatty acids have been found to form homo- and heterodimers in untargeted metabolomics pipelines that resemble the lipid class fatty acid esters of hydroxy fatty acids (FAHFAs), resulting in misidentification. This chapter details a protocol for LC-MS-based untargeted metabolomics using hydrophilic interaction chromatography (HILIC) that specifically aids in distinguishing artifactual fatty acid dimers from endogenous FAHFAs.

Keywords:  Fatty acid dimers; Fatty acid esters of hydroxy fatty acids; LC-MS; Lipidomics; Untargeted metabolomics

DOI:  https://doi.org/10.1007/978-1-0716-4116-3_4
Methods Mol Biol. 2025 ;2855 41-66

Modular, Scalable, and Customizable LC-HRMS for Exposomics.

Vinicius Verri Hernandes, Benedikt Warth.

  In this chapter, we describe a multi-purpose, reversed-phase liquid chromatography-high-resolution mass spectrometry (LC-HRMS) workflow for acquiring high-quality, non-targeted exposomics data utilizing data-dependent acquisition (DDA) combined with the use of toxicant inclusion lists for semi-targeted analysis. In addition, we describe expected retention times for >160 highly diverse xenobiotics in human plasma and serum samples. The method described is intended to serve as a generic LC-HRMS exposomics workflow for research and educational purposes. Moreover, it may be employed as a primer, allowing for further adaptations according to specialized research needs, e.g., by including reference and/or internal standards, by expanding to data-independent acquisition (DIA), or by modifying the list of compounds prioritized in fragmentation experiments (MS2).

Keywords:  Analytical toxicology; Biomonitoring; Data-dependent analysis; Environmental and food contaminants; Exposome research; High-resolution mass spectrometry; Untargeted metabolomics and exposomics

DOI:  https://doi.org/10.1007/978-1-0716-4116-3_3
Methods Mol Biol. 2025 ;2855 389-423

CE-MS-Based Clinical Metabolomics of Human Plasma.

Maricruz Mamani-Huanca, Sara Martínez, Ángeles López-López, Ángeles López-Gonzálvez, Oihane E Albóniga, Ana Gradillas, Coral Barbas, Víctor González-Ruiz.

  Capillary electrophoresis coupled to mass spectrometry (CE-MS) has emerged as a powerful analytical technique with significant implications for clinical research and diagnostics. The integration of information from CE and MS strengthens confidence in the identification of compounds present in clinical samples. The ability of CE to separate molecules based on their electrophoretic mobility coupled to MS enables the accurate identification and quantification of analytes, even in complex biological matrices such as human plasma.Here, we present a detailed protocol for an untargeted metabolomics study using CE-MS and its application in a study on human plasma from patients suffering Long COVID syndrome. The protocol ranges from sample preparation to biological interpretation, detailing a workflow enabling the analysis of cationic and anionic compounds, metabolite identification, and data processing.

Keywords:  CE-MS; Clinical metabolomics; Human plasma; Long COVID; Polar metabolome; Untargeted metabolomics

DOI:  https://doi.org/10.1007/978-1-0716-4116-3_23
Methods Mol Biol. 2025 ;2855 103-116

Stable Isotope Tracing Experiments Using LC-MS.

Esther A Zaal, Jeroen W A Jansen, Celia R Berkers.

  Metabolomics has emerged as a pivotal field in understanding cellular function, particularly in the context of disease. In numerous diseases, including cancer, alterations in metabolism play an essential role in disease progression and drug response. Hence, unraveling the metabolic rewiring is of importance to find novel diagnostic and therapeutic strategies. Isotope tracing is a powerful technique for delving deeper into the metabolic wiring of cells. By tracking an isotopically labeled substrate through biochemical reactions in the cell, this technique provides a dynamic understanding of cellular metabolism. This chapter outlines a robust isotope tracing protocol utilizing high-resolution mass spectrometry coupled to liquid chromatography in cell culture-based models. We cover essential aspects of experimental design and analyses, providing a valuable resource for researchers aiming to employ isotopic tracing.

Keywords:  Fluxomics; High-performance liquid chromatography; Isotope tracing; Mass spectrometry; Metabolomics

DOI:  https://doi.org/10.1007/978-1-0716-4116-3_6
Methods Mol Biol. 2025 ;2855 341-354

Rapid Lipid Mediator Profiling by Convergence Chromatography-MS/MS.

Guille Metzler, Richard C King, Carmen Fernández-Metzler, Amitava Das, T Gregg Davis, Besnik Bajrami, Tom Bretschneider, David Kvaskoff.

  Bioactive lipid mediators derived from arachidonic acid constitute an attractive pool of metabolites that reflect cellular function and signaling, as well as potential biomarkers that may respond quantitatively to disease progression or pharmacological treatment. Their quantitative measurement in biological samples is complicated by the number of isomers that share common structural features, which are not easily distinguished by immunoassays or reverse phase chromatography-tandem mass spectrometry. Here, we present a method that enables the rapid analysis of a panel of over 25 biologically important eicosanoids in a 96-well format for cell culture supernatants, plasma, and organ tissues using convergence chromatography-tandem mass spectrometry to resolve these analytes of interest.

Keywords:  Convergence chromatography; High-throughput; Oxylipins; Sample pre-treatment

DOI:  https://doi.org/10.1007/978-1-0716-4116-3_20
J Am Soc Mass Spectrom. 2024 Sep 30.

Annotation of Metabolites in Stable Isotope Tracing Untargeted Metabolomics via Khipu-web.

Joshua M Mitchell, Yuanye Chi, Shujian Zheng, Maheshwor Thapa, Eric Wang, Shuzhao Li.

Stable isotope tracing is a crucial technique for understanding the metabolic wiring of biological systems, determining metabolic flux through pathways of interest, and detecting novel metabolites and pathways. Despite the potential insights provided by this technique, its application remains limited to a small number of targeted molecules and pathways. Because previous software tools usually require chemical formulas to find relevant features, and the data are highly complex, especially in untargeted metabolomics and when the downstream reactions and metabolites are poorly characterized. We report here Khipu version 2 and its new user-friendly web application. New functions are added to enhance analyzing stable isotope tracing data including metrics that evaluate peak enrichment in labeled samples, scoring methods to facilitate robust detection of intensity patterns and integrated natural abundance correction. We demonstrate that this approach can be applied to untargeted metabolomics to systematically extract isotope-labeled compounds and annotate the unidentified metabolites.

DOI: https://doi.org/10.1021/jasms.4c00175
Methods Mol Biol. 2025 ;2855 539-554

Extracting Knowledge from MS Clinical Metabolomic Data: Processing and Analysis Strategies.

Isabel Meister, Julien Boccard, Serge Rudaz.

  Assessing potential alterations of metabolic pathways using large-scale approaches plays today a central role in clinical research. Because several thousands of mass features can be measured for each sample with separation techniques hyphenated to mass spectrometry (MS) detection, adapted strategies have to be implemented to detect altered pathways and help to elucidate the mechanisms of pathologies. These procedures include peak detection, sample alignment, normalization, statistical analysis, and metabolite annotation. Interestingly, considerable advances have been made over the last years in terms of analytics, bioinformatics, and chemometrics to help massive and complex metabolomic data to be more adequately handled with automated processing and data analysis workflows. Recent developments and remaining challenges related to MS signal processing, metabolite annotation, and biomarker discovery based on statistical models are illustrated in this chapter in light of their application to clinical research.

Keywords:  Data analysis, Annotation; Data processing; Mass spectrometry; Metabolomics

DOI:  https://doi.org/10.1007/978-1-0716-4116-3_29
Methods Mol Biol. 2025 ;2855 117-131

Quantification of Total Ketone Bodies in Biological Matrices Using Stable Isotope-Labeled Internal Standards and RP-UHPLC-MS/MS.

Eric D Queathem, Alisa B Nelson, Patrycja Puchalska.

  Acetoacetate (AcAc) and D-beta-hydroxybutyrate (D-βOHB), the two major ketone bodies found in circulation, are linked to multiple physiological and pathophysiological states. Therefore, analytical methodologies surrounding the quantification of total ketone body (TKB) concentrations in biological matrices are paramount. Traditional methods to quantify TKBs relied on indirect spectrophotometric assays with narrow dynamic ranges, which have been significantly improved upon by modern mass spectrometry (MS)-based approaches. However, the lack of stable isotope-labeled internal standards (ISs) for AcAc and the need to distinguish D-βOHB from its closely related structural and enantiomeric isomers pose significant obstacles. Here, we provide a protocol to synthesize and quantify a [13C] stable isotope-labeled IS for AcAc, which, in conjunction with a commercially available [2H] stable isotope-labeled IS for βOHB, allows TKBs to be measured across multiple biological matrices. This rapid (7 min) analysis employs reverse phase ultra-high performance liquid chromatography (RP-UHPLC) coupled to tandem MS (MS/MS) to distinguish βOHB from three structural isomers using parallel reaction monitoring (PRM), providing excellent specificity and selectivity. Finally, a method is provided that distinguishes D-βOHB from L-βOHB using a simple one-step derivatization to produce the corresponding diastereomers, which can be chromatographically resolved using the same rapid RP-UHPLC separation with new PRM transitions. In summary, this method provides a rigorous analytical pipeline for the analysis of TKBs in biological matrices via leveraging two authentic stable isotope-labeled ISs and RP-UHPLC-MS/MS.

Keywords:  Acetoacetate; D-β-hydroxybutyrate; Ketone bodies; L-β-hydroxybutyrate; Stable isotope-labeled internal standards; Tandem mass spectrometry; Ultra-high performance liquid chromatography

DOI:  https://doi.org/10.1007/978-1-0716-4116-3_7
Methods Mol Biol. 2025 ;2855 3-19

(Pre)Clinical Metabolomics Analysis.

Ratna Budhi Pebriana, Elena Sánchez-López, Martin Giera.

  Metabolomics is the scientific field with the eager goal to comprehensively analyze the entirety of all small molecules of a biological system, i.e., the metabolome. Over the last few years, metabolomics has matured to become an analytical cornerstone of life science research across diverse fields, from fundamental biochemical applications to preclinical studies, including biomarker discovery and drug development. In this chapter, we provide an introduction to (pre)clinical metabolomics. We define key metabolomics aspects and provide the basis to thoroughly understand the relevance of this field in a biological and clinical context. We present and explain state-of-the-art analytical technologies devoted to metabolomic analysis as well as emerging technologies, discussing both strengths and weaknesses. Given the ever-increasing demand for handling complex datasets, the role of bioinformatics approaches in the context of metabolomic analysis is also illustrated.

Keywords:  Clinical samples; Lipidomics; Mass spectrometry; Metabolomics; Nuclear magnetic resonance

DOI:  https://doi.org/10.1007/978-1-0716-4116-3_1
Methods Mol Biol. 2025 ;2855 23-39

Global Metabolomics Using LC-MS for Clinical Applications.

Hanne Bendiksen Skogvold, Elise Sandås Sand, Katja Benedikte Prestø Elgstøen.

  Metabolomics can be used for a multitude of purposes, including monitoring of treatment effects and for increasing the knowledge of the pathophysiology of a wide range of diseases. Global (commonly referred to as "untargeted") metabolomics is hypothesis-generating and provides the opportunity to discover new biomarkers. Being versatile and having a high degree of selectivity and sensitivity, liquid chromatography-mass spectrometry (LC-MS) is the most common technique applied for metabolomics. We here present our global metabolomics LC-electrospray ionization-MS/MS method. The sample preparation procedures for plasma, serum, dried blood spots, urine, and cerebrospinal fluid are simple and nonspecific to reduce the risk of analyte loss. The method is based on reversed-phase chromatography using a diphenyl column. The high-resolution Q Exactive Orbitrap MS with data-dependent acquisition provides MS/MS spectra of a wide range of analytes. Our method covers a large part of the metabolome regarding hydrophobicity and compound class.

Keywords:  Clinical metabolomics; Data quality evaluation; Dried blood spots; Global metabolomics; LC-MS; Untargeted metabolomics

DOI:  https://doi.org/10.1007/978-1-0716-4116-3_2
bioRxiv. 2024 Sep 22. pii: 2024.09.18.613707. [Epub ahead of print]

Data-Independent Acquisition Mass Spectrometry as a Tool for Metaproteomics: Interlaboratory Comparison Using a Model Microbiome.

Andrew T Rajczewski, J Alfredo Blakeley-Ruiz, Annaliese Meyer, Simina Vintila, Matthew R McIlvin, Tim Van Den Bossche, Brian C Searle, Timothy J Griffin, Mak A Saito, Manuel Kleiner, Pratik D Jagtap.

Mass spectrometry (MS)-based metaproteomics is used to identify and quantify proteins in microbiome samples, with the frequently used methodology being Data-Dependent Acquisition mass spectrometry (DDA-MS). However, DDA-MS is limited in its ability to reproducibly identify and quantify lower abundant peptides and proteins. To address DDA-MS deficiencies, proteomics researchers have started using Data-Independent Acquisition Mass Spectrometry (DIA-MS) for reproducible detection and quantification of peptides and proteins. We sought to evaluate the reproducibility and accuracy of DIA-MS metaproteomic measurements relative to DDA-MS using a mock community of known taxonomic composition. Artificial microbial communities of known composition were analyzed independently in three laboratories using DDA- and DIA-MS acquisition methods. DIA-MS yielded more protein and peptide identifications than DDA-MS in each laboratory. In addition, the protein and peptide identifications were more reproducible in all laboratories and provided an accurate quantification of proteins and taxonomic groups in the samples. We also identified some limitations of current DIA tools when applied to metaproteomic data, highlighting specific needs to improve DIA tools enabling analysis of metaproteomic datasets from complex microbiomes. Ultimately, DIA-MS represents a promising strategy for MS-based metaproteomics due to its large number of detected proteins and peptides, reproducibility, deep sequencing capabilities, and accurate quantitation.

DOI: https://doi.org/10.1101/2024.09.18.613707
Methods Mol Biol. 2025 ;2855 505-519

NMR-Based Analysis of Cellular Central Energy Metabolism and Exchange Rates.

Sarantos Kostidis.

  Cell cultures are widely used in studies to gain mechanistic insights of metabolic processes. The foundation of these studies lies on the quantification of intracellular and extracellular metabolites, and nuclear magnetic resonance (NMR) is one of the key analytical platforms used to this aim. Among the factors influencing the quality of the produced data are the sampling procedures as well as the acquisition and processing of spectroscopic data. Here we provide our workflow for obtaining quantitative metabolic data from adherent mammalian cells using NMR spectroscopy. The described protocol is compatible with other analytical methods like LC- or GC-MS-based lipidomics and untargeted metabolomics from the same sample. We also show how the collected extracellular data can be used to extract exchange flux rates, particularly useful for flux analysis studies and metabolic engineering of human-induced pluripotent stem cells.

Keywords:  Central energy metabolism; Exchange flux rates; Mammalian cells; Metabolic engineering; Metabolomics; NMR spectroscopy; Sample preparation

DOI:  https://doi.org/10.1007/978-1-0716-4116-3_27
Methods Mol Biol. 2025 ;2855 555-571

Application of a Computational Metabolomics Workflow for the Diagnosis of Inborn Errors of Metabolism in a Laboratory Setting.

Udo F H Engelke, Alan Zammit, Albert Gerritsen, Marloes A H M Michels, Karlien L M Coene, Leo A J Kluijtmans, Purva Kulkarni.

  Inborn errors of metabolism constitute a set of hereditary diseases that impose severe medical and physical challenges in the affected individual, in particular, for the pediatric patient population. Timely diagnosis is crucial for these patients, as any delay could result in irreversible health damage, underscoring the importance of early initiation of personalized treatment. Current routine diagnostic screening for inborn errors of metabolism relies on various targeted analyses of established biomarkers. However, this approach is time-consuming, focuses on a limited number of tests (based on clinical information) with a relatively small number of biomarkers, and does not facilitate the identification of new markers. In contrast, untargeted metabolomics-based screening offers a more efficient diagnostic solution, by assessing thousands of metabolites across multiple metabolic pathways in a single test. This not only saves time but also conserves resources for clinicians, the diagnostic laboratory, and for patients.This chapter describes the computational workflow of our "Next Generation Metabolic Screening" approach, which is a metabolomics-based method that is currently applied at the Translational Metabolic Laboratory of the Radboud University Medical Center (the Netherlands) for the diagnosis of inborn errors of metabolism.

Keywords:  Bioinformatics workflow; Diagnostics; Inborn errors of metabolism; Mass spectrometry; Untargeted metabolomics

DOI:  https://doi.org/10.1007/978-1-0716-4116-3_30
Methods Mol Biol. 2025 ;2855 305-314

Ultrahigh-Performance Supercritical Fluid Chromatography-Mass Spectrometry in the Clinical Lipidomic Analysis.

Ondřej Peterka, Denise Wolrab, Robert Jirásko, Mária Kanásová, Zuzana Dolečková, Michal Holčapek.

  Ultrahigh-performance supercritical fluid chromatography-mass spectrometry (UHPSFC/MS) method is optimized for the high-throughput quantitation of lipids in human serum and plasma with an emphasis on robustness and accurate quantitation. Bridged ethylene hybrid (BEH) silica column (100 × 3 mm; 1.7 μm) is used for the separation of 17 nonpolar and polar lipid classes in 4.4 min using the positive ion electrospray ionization mode. The lipid class separation approach in UHPSFC/MS results in the coelution of all lipid species within one lipid class in one chromatographic peak, including two exogenous internal standards (IS) per lipid class, which provides the optimal conditions for robust quantitation. The method was validated according to European Medicines Agency and Food and Drug Administration recommendations. UHPSFC/MS combined with LipidQuant software allows a semiautomated process to determine lipid concentrations with a total run time of only 8 min including column equilibration, which enables the analysis of 160 samples per day.

Keywords:  High-throughput lipidomics; Mass spectrometry; Plasma; Quantitation; Serum; Ultrahigh-performance supercritical fluid chromatography; Validation

DOI:  https://doi.org/10.1007/978-1-0716-4116-3_18
Methods Mol Biol. 2025 ;2855 195-207

High-Throughput RPLC-MS/MS Quantification of Short- and Medium-Chain Fatty Acids.

Stefan Schauer, Alaa Othman.

  Short- and medium-chain fatty acids (SMCFA) are monocarboxylic acids with a carbon chain length of 1-12 carbon atoms. They are mainly produced in humans by the gut microbiota, play crucial metabolic roles, are vital for intestinal health, and have multifaceted impact on immune and neurological functions. Accurate detection and quantification of SMCFA in different human biofluids is achieved using 3-nitro phenylhydrazine (3-NPH) derivatization of the free fatty acids followed by reverse phase liquid chromatography (RPLC) separation and detection by tandem mass spectrometry (MS/MS). Here, we describe the simultaneous measurement of 14 SMCFA and lactate in detail. All 3-NPH-SMCFA-hydrazones are separated in less than 5 min with an 8-min total run time (injection-to-injection). Linear dynamic range over 0.1-500 μM is achieved for most SCFAs, while it is 0.05-100 μM for MCFAs. Validation of the procedure depicts good linearity (R2 > 0.98) and repeatability (CV ≤ 20%). The lower limit of detection (LLOD) is 10-30 nM. The lower limit of quantification (LLOQ) is 50-100 nM for most analytes, while it is 0.5 μM for acetate. In conclusion, the method offers several benefits compared to alternative methods regarding throughput, selectivity, sensitivity, and robustness.

Keywords:  3-Nitrophenylhydrazine derivatization; Branched-short-chain fatty acids; Cancer therapy; Gut microbiome; Immune system; Medium-chain fatty acids; Personalized medicine; Short-chain fatty acids; Signaling molecules; Targeted metabolomics

DOI:  https://doi.org/10.1007/978-1-0716-4116-3_13
ACS Omega. 2024 Sep 24. 9(38): 40034-40050

Comprehensive Proteomic Profiling of Converted Adipocyte-like Cells from Normal Human Dermal Fibroblasts Using Data-Independent Acquisition Mass Spectrometry.

Sunkyu Choi, Rajaa S D Dalloul, Praveen Babu Vemulapalli, Sondos Yousef, Neha Goswami, Frank Schmidt.

Adipocytes play an important role in the regulation of systemic energy homeostasis and are closely related to metabolic disorders, such as type-2 diabetes and inflammatory bowel diseases. Particularly, there is an increasing need for a human adipocyte model for studying metabolic diseases and obesity. However, utilizing human primary adipocyte culture and stem-cell-based models presents several practical limitations due to their time-consuming nature, requirement for relatively intensive labor, and high cost. Here, we applied direct conversion of normal human dermal fibroblasts (NHDFs) into adipocyte-like cells using an adipogenic cocktail containing 3-isobutyl-1-methylxanthine (IBMX), dexamethasone, insulin, and rosiglitazone and confirmed prominent lipid droplet accumulation in the converted cells. For profiling the proteome changes in the converted cells, we conducted a comprehensive quantitative proteome analysis of both the intracellular and extracellular proteome fractions using data-independent acquisition mass spectrometry. We observed that several proteins, which are known to be highly expressed in adipocytes specifically, were dominantly increased in the converted cells. In this study, we suggest that NHDFs can be converted into adipocyte-like cells by an adipogenic cocktail and can serve as a useful tool for studying human adipocytes and their metabolism.

DOI: https://doi.org/10.1021/acsomega.4c05852
Methods Mol Biol. 2025 ;2855 523-535

In Situ Isotope Tracing at Single-Cell Resolution Using Mass Spectrometry Imaging.

Rosalie G J Rietjens, Bram Heijs.

  Mass spectrometry imaging (MSI) allows for label-free spatial molecular interrogation of tissues. With advances in the field over recent years, the spatial resolution at which MSI data can be recorded has reached the single-cell level. This makes MSI complementary to other single-cell omics technologies. As metabolism is a highly dynamic process, capturing the metabolic turnover adds a valuable layer of information. Here, we describe how to set up in situ stable isotope tracing followed by MSI-enabled spatial metabolomics to perform dynamic metabolomics at the single-cell level.

Keywords:  Isotope tracing; Mass spectrometry imaging; Tissue metabolomics; Vibratome sectioning

DOI:  https://doi.org/10.1007/978-1-0716-4116-3_28
Biomedicines. 2024 Sep 18. pii: 2118. [Epub ahead of print]12(9):

A Multiplexed Quantitative Proteomics Approach to the Human Plasma Protein Signature.

Estefanía Núñez, María Gómez-Serrano, Enrique Calvo, Elena Bonzon-Kulichenko, Marco Trevisan-Herraz, José Manuel Rodríguez, Fernando García-Marqués, Ricardo Magni, Enrique Lara-Pezzi, José Luis Martín-Ventura, Emilio Camafeita, Jesús Vázquez.

  Despite the plasma proteome being able to provide a unique insight into the health and disease status of individuals, holding singular promise as a source of protein biomarkers that could be pivotal in the context of personalized medicine, only around 100 proteins covering a few human conditions have been approved as biomarkers by the US Food and Drug Administration (FDA) so far. Mass spectrometry (MS) currently has enormous potential for high-throughput analysis in clinical research; however, plasma proteomics remains challenging mainly due to the wide dynamic range of plasma protein abundances and the time-consuming procedures required. We applied a new MS-based multiplexed proteomics workflow to quantitate proteins, encompassing 67 FDA-approved biomarkers, in >1300 human plasma samples from a clinical cohort. Our results indicate that this workflow is suitable for large-scale clinical studies, showing good accuracy and reproducibility (coefficient of variation (CV) < 20 for 90% of the proteins). Furthermore, we identified plasma signature proteins (stable in time on an individual basis), stable proteins (exhibiting low biological variability and high temporal stability), and highly variable proteins (with low temporal stability) that can be used for personalized health monitoring and medicine.

Keywords:  LC-MS/MS; atherosclerosis; clinical proteomics; human plasma; personalized medicine; plasma proteomics

DOI:  https://doi.org/10.3390/biomedicines12092118
Methods Mol Biol. 2025 ;2855 373-385

Differential Mobility Spectrometry-Based Cardiolipin Analysis.

Fabien Riols, Michael Witting, Mark Haid.

  Cardiolipins (CL) are special lipids in many respects. First of all, CL are composed of four fatty acids linked by two phosphatidic acids, which provide CL a unique molecular structure. Secondly, in eukaryotic cells they are specific to a single organelle, mitochondria, where they are also synthetized. CL are one of the most abundant lipid classes in mitochondria, mainly localized in the inner membrane. They are key determinants of mitochondrial health and homeostasis by modulating membrane integrity and fluidity, mitochondrial shapes, and metabolic pathways. Disturbances in mitochondrial CL composition can lead to tissue malfunction and diseases. It is therefore important to develop analytical tools to study the mitochondrial lipidome, and more particularly the CL. The method described here allows the quantification of cardiolipins at the sum composition level in isolated mitochondria or in liver tissue by flow injection analysis coupled to differential mobility spectrometry (FIA-DMS), also known as DMS-based shotgun lipidomics.

Keywords:  Cardiolipins; Differential mobility spectrometry; Flow injection analysis; Mass spectrometry; Mitochondria

DOI:  https://doi.org/10.1007/978-1-0716-4116-3_22
Nat Commun. 2024 Oct 02. 15(1): 8540

Intrinsic temperature increase drives lipid metabolism towards ferroptosis evasion and chemotherapy resistance in pancreatic cancer.

Vincent de Laat, Halit Topal, Xander Spotbeen, Ali Talebi, Jonas Dehairs, Jakub Idkowiak, Frank Vanderhoydonc, Tessa Ostyn, Peihua Zhao, Maarten Jacquemyn, Michele Wölk, Anna Sablina, Koen Augustyns, Tom Vanden Berghe, Tania Roskams, Dirk Daelemans, Maria Fedorova, Baki Topal, Johannes V Swinnen.

A spontaneously occurring temperature increase in solid tumors has been reported sporadically, but is largely overlooked in terms of cancer biology. Here we show that temperature is increased in tumors of patients with pancreatic ductal adenocarcinoma (PDAC) and explore how this could affect therapy response. By mimicking this observation in PDAC cell lines, we demonstrate that through adaptive changes in lipid metabolism, the temperature increase found in human PDAC confers protection to lipid peroxidation and contributes to gemcitabine resistance. Consistent with the recently uncovered role of p38 MAPK in ferroptotic cell death, we find that the reduction in lipid peroxidation potential following adaptation to tumoral temperature allows for p38 MAPK inhibition, conferring chemoresistance. As an increase in tumoral temperature is observed in several other tumor types, our findings warrant taking tumoral temperature into account in subsequent studies related to ferroptosis and therapy resistance. More broadly, our findings indicate that tumoral temperature affects cancer biology.

DOI: https://doi.org/10.1038/s41467-024-52978-z
Talanta. 2024 Sep 26. pii: S0039-9140(24)01332-8. [Epub ahead of print]282 126953

Optimized high-throughput protocols for comprehensive metabolomic and lipidomic profiling of brain sample.

Cemil Can Eylem, Emirhan Nemutlu, Aysegul Dogan, Vedat Acik, Selcuk Matyar, Yurdal Gezercan, Suleyman Altintas, Ali Ihsan Okten, Nursabah Elif Basci Akduman.

  Establishing direct causal and functional links between genotype and phenotype requires thoroughly analyzing metabolites and lipids in systems biology. Tissue samples, which provide localized and direct information and contain unique compounds, play a significant role in objectively classifying diseases, predicting prognosis, and deciding personalized therapeutic strategies. Comprehensive metabolomic and lipidomic analyses in tissue samples need efficient sample preparation steps, optimized analysis conditions, and the integration of orthogonal analytical platforms because of the physicochemical diversities of biomolecules. Here, we propose simple, rapid, and robust high-throughput analytical protocols based on the design of experiment (DoE) strategies, with the various parameters systematically tested for comprehensively analyzing the heterogeneous brain samples. The suggested protocols present a systematically DoE-based strategy for performing the most comprehensive analysis for integrated GC-MS and LC-qTOF-MS from brain samples. The five different DoE models, including D-optimal, full factorial, fractional, and Box-Behnken, were applied to increase extraction efficiency for metabolites and lipids and optimize instrumental parameters, including sample preparation and chromatographic parameters. The superior simultaneous extraction of metabolites and lipids from brain samples was achieved by the methanol-water-dichloromethane (2:1:3, v/v/v) mixture. For GC-MS based metabolomics analysis, incubation time, temperature, and methoxyamine concentration (10 mg/mL) affected metabolite coverage significantly. For LC-qTOF-MS based metabolomics analysis, the extraction solvent (methanol-water; 2:1, v/v) and the reconstitution solvent (%0.1 FA in acetonitrile) were superior on the metabolite coverage. On the other hand, the ionic strength and column temperature were critical and significant parameters for high throughput metabolomics and lipidomics studies using LC-qTOF-MS. In conclusion, DoE-based optimization strategies for a three-in-one single-step extraction enabled rapid, comprehensive, high-throughput, and simultaneous analysis of metabolites, lipids, and even proteins from a 10 mg brain sample. Under optimized conditions, 475 lipids and 158 metabolites were identified in brain samples.

Keywords:  Brain; Experimental design; Lipidomics; Metabolomics; Multi-omics; Sample preparation

DOI:  https://doi.org/10.1016/j.talanta.2024.126953