bims-mascan 2023-02-26 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2023‒02‒26
twenty-two papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh

Comprehensive Lipidomic Workflow for Multicohort Population Phenotyping Using Stable Isotope Dilution Targeted Liquid Chromatography-Mass Spectrometry.
Four-dimensional trapped ion mobility spectrometry lipidomics for high throughput clinical profiling of human blood samples.
Nucleotide metabolism is linked to cysteine availability during ferroptosis.
Applied Clinical Tandem Mass Spectrometry-Based Quantification Methods for Lipid-Derived Biomarkers, Steroids and Cannabinoids: Fit-for-Purpose Validation Methods.
LC-MS-Based Targeted Metabolomics for FACS-Purified Rare Cells.
A Novel Blood Proteomic Signature for Prostate Cancer.
Regularized adversarial learning for normalization of multi-batch untargeted metabolomics data.
HIF: a master regulator of nutrient availability and metabolic cross-talk in the tumor microenvironment.
A proposed framework to evaluate the quality and reliability of targeted metabolomics assays from the UK Consortium on Metabolic Phenotyping (MAP/UK).
CD40 signal rewires fatty acid and glutamine metabolism for stimulating macrophage anti-tumorigenic functions.
Robust and Easy-to-Use One-Pot Workflow for Label-Free Single-Cell Proteomics.
Comprehensive chromatin proteomics resolves functional phases of pluripotency and identifies changes in regulatory components.
Targeting immune-onco-metabolism for precision cancer therapy.
Metabolomics in oncology.
Simultaneous measurement of kynurenine metabolites and explorative metabolomics using liquid chromatography-mass spectrometry: A novel accurate method applied to serum and plasma samples from a large healthy cohort.
Liquid chromatography and differential mobility spectrometry-data-independent mass spectrometry for comprehensive multidimensional separations in metabolomics.
Vacuum Insulated Probe Heated ElectroSpray Ionization source (VIP-HESI) enhances micro flow rate chromatography signals in the Bruker timsTOF mass spectrometer.
Quantitative Analysis of Nucleoside Triphosphate Pools in Mouse Muscle Using Hydrophilic Interaction Liquid Chromatography Coupled with Tandem Mass Spectrometry Detection.
The mitochondrial chaperone TRAP-1 regulates the glutamine metabolism in tumor cells.
Quantitative SWATH-based proteomic profiling of urine for the identification of endometrial cancer biomarkers in symptomatic women.
Expression of malic enzyme reveals subcellular carbon partitioning for storage reserve production in soybeans.
Fitm2 is required for ER homeostasis and normal function of murine liver.

J Proteome Res. 2023 Feb 24.

Comprehensive Lipidomic Workflow for Multicohort Population Phenotyping Using Stable Isotope Dilution Targeted Liquid Chromatography-Mass Spectrometry.

Monique J Ryan, Alanah Grant-St James, Nathan G Lawler, Mark W Fear, Edward Raby, Fiona M Wood, Garth L Maker, Julien Wist, Elaine Holmes, Jeremy K Nicholson, Luke Whiley, Nicola Gray.

  Dysregulated lipid metabolism underpins many chronic diseases including cardiometabolic diseases. Mass spectrometry-based lipidomics is an important tool for understanding mechanisms of lipid dysfunction and is widely applied in epidemiology and clinical studies. With ever-increasing sample numbers, single batch acquisition is often unfeasible, requiring advanced methods that are accurate and robust to batch-to-batch and interday analytical variation. Herein, an optimized comprehensive targeted workflow for plasma and serum lipid quantification is presented, combining stable isotope internal standard dilution, automated sample preparation, and ultrahigh performance liquid chromatography-tandem mass spectrometry with rapid polarity switching to target 1163 lipid species spanning 20 subclasses. The resultant method is robust to common sources of analytical variation including blood collection tubes, hemolysis, freeze-thaw cycles, storage stability, analyte extraction technique, interinstrument variation, and batch-to-batch variation with 820 lipids reporting a relative standard deviation of <30% in 1048 replicate quality control plasma samples acquired across 16 independent batches (total injection count = 6142). However, sample hemolysis of ≥0.4% impacted lipid concentrations, specifically for phosphatidylethanolamines (PEs). Low interinstrument variability across two identical LC-MS systems indicated feasibility for intra/inter-lab parallelization of the assay. In summary, we have optimized a comprehensive lipidomic protocol to support rigorous analysis for large-scale, multibatch applications in precision medicine. The mass spectrometry lipidomics data have been deposited to massIVE: data set identifiers MSV000090952 and 10.25345/C5NP1WQ4S.

Keywords:  lipid profiling; lipid quantification; lipidomics; lipids; liquid chromatography-mass spectrometry; metabolic phenotyping; molecular epidemiology

DOI:  https://doi.org/10.1021/acs.jproteome.2c00682
Nat Commun. 2023 Feb 20. 14(1): 937

Four-dimensional trapped ion mobility spectrometry lipidomics for high throughput clinical profiling of human blood samples.

Raissa Lerner, Dhanwin Baker, Claudia Schwitter, Sarah Neuhaus, Tony Hauptmann, Julia M Post, Stefan Kramer, Laura Bindila.

Lipidomics encompassing automated lipid extraction, a four-dimensional (4D) feature selection strategy for confident lipid annotation as well as reproducible and cross-validated quantification can expedite clinical profiling. Here, we determine 4D descriptors (mass to charge, retention time, collision cross section, and fragmentation spectra) of 200 lipid standards and 493 lipids from reference plasma via trapped ion mobility mass spectrometry to enable the implementation of stringent criteria for lipid annotation. We use 4D lipidomics to confidently annotate 370 lipids in reference plasma samples and 364 lipids in serum samples, and reproducibly quantify 359 lipids using level-3 internal standards. We show the utility of our 4D lipidomics workflow for high-throughput applications by reliable profiling of intra-individual lipidome phenotypes in plasma, serum, whole blood, venous and finger-prick dried blood spots.

DOI: https://doi.org/10.1038/s41467-023-36520-1
J Biol Chem. 2023 Feb 17. pii: S0021-9258(23)00171-0. [Epub ahead of print] 103039

Nucleotide metabolism is linked to cysteine availability during ferroptosis.

Annamarie E Allen, Yudong Sun, Fangchao Wei, Michael A Reid, Jason W Locasale.

The small molecule erastin inhibits the cystine-glutamate antiporter, system xc-, which leads to intracellular cysteine and glutathione depletion. This can cause ferroptosis, which is an oxidative cell death process characterized by uncontrolled lipid peroxidation. Erastin and other ferroptosis inducers have been shown to affect metabolism but the metabolic effects of these drugs have not been systematically studied. To this end, we investigated how erastin impacts global metabolism in cultured cells and compared this metabolic profile to that caused by the ferroptosis inducer RSL3 or in-vivo cysteine deprivation. Common among the metabolic profiles were alterations in nucleotide and central carbon metabolism. Supplementing nucleosides to cysteine-deprived cells rescued cell proliferation in certain contexts, showing that these alterations to nucleotide metabolism can affect cellular fitness. While inhibition of the glutathione peroxidase GPX4 caused a similar metabolic profile as cysteine deprivation, nucleoside treatment did not rescue cell viability or proliferation under RSL3 treatment, suggesting that these metabolic changes have varying importance in different scenarios of ferroptosis. Together, our study shows how global metabolism is affected during ferroptosis, and points to nucleotide metabolism as an important target of cysteine deprivation.

DOI: https://doi.org/10.1016/j.jbc.2023.103039
Biomolecules. 2023 Feb 17. pii: 383. [Epub ahead of print]13(2):

Applied Clinical Tandem Mass Spectrometry-Based Quantification Methods for Lipid-Derived Biomarkers, Steroids and Cannabinoids: Fit-for-Purpose Validation Methods.

Isabelle Matias, Ilaria Belluomo, Pierre-Louis Raux, Monique Vallée.

  The emergence of metabolomics and quantification approaches is revealing new biomarkers applied to drug discovery. In this context, tandem mass spectrometry is the method of choice, requiring a specific validation process for preclinical and clinical applications. Research on the two classes of lipid mediators, steroids and cannabinoids, has revealed a potential interaction in cannabis addiction and metabolism-related disorders. Here we present the development of GC-MS/MS and LC-MS/MS methods for routine quantification of targeted steroids and cannabinoids, respectively. The methods were developed using an isotopic approach, including validation for linearity, selectivity, LLOQ determination, matrix effect, carryover, between- and within-run accuracy and precision, and stability tests to measure 11 steroids and seven cannabinoids in human plasma. These methods were satisfactory for most validity conditions, although not all met the acceptance criteria for all analytes. A comparison of calibration curves in biological and surrogate matrices and in methanol showed that the latter condition was more applicable for our quantification of endogenous compounds. In conclusion, the validation of our methods met the criteria for GLP-qualified rather than GLP-validated methods, which can be used for routine analytical studies for dedicated preclinical and clinical purposes, by combining appropriate system suitability testing, including quality controls in the biological matrix.

Keywords:  GC-MS/MS; LC-MS/MS; cannabinoids; human plasma; quantification methods; steroids; tandem mass spectrometry; validation

DOI:  https://doi.org/10.3390/biom13020383
Anal Chem. 2023 Feb 22.

LC-MS-Based Targeted Metabolomics for FACS-Purified Rare Cells.

Katharina Schönberger, Michael Mitterer, Katharina Glaser, Manuel Stecher, Sebastian Hobitz, Dominik Schain-Zota, Konrad Schuldes, Tim Lämmermann, Angelika S Rambold, Nina Cabezas-Wallscheid, Joerg M Buescher.

Metabolism plays a fundamental role in regulating cellular functions and fate decisions. Liquid chromatography-mass spectrometry (LC-MS)-based targeted metabolomic approaches provide high-resolution insights into the metabolic state of a cell. However, the typical sample size is in the order of 105-107 cells and thus not compatible with rare cell populations, especially in the case of a prior flow cytometry-based purification step. Here, we present a comprehensively optimized protocol for targeted metabolomics on rare cell types, such as hematopoietic stem cells and mast cells. Only 5000 cells per sample are required to detect up to 80 metabolites above background. The use of regular-flow liquid chromatography allows for robust data acquisition, and the omission of drying or chemical derivatization avoids potential sources of error. Cell-type-specific differences are preserved while the addition of internal standards, generation of relevant background control samples, and targeted metabolite with quantifiers and qualifiers ensure high data quality. This protocol could help numerous studies to gain thorough insights into cellular metabolic profiles and simultaneously reduce the number of laboratory animals and the time-consuming and costly experiments associated with rare cell-type purification.

DOI: https://doi.org/10.1021/acs.analchem.2c04396
Cancers (Basel). 2023 Feb 07. pii: 1051. [Epub ahead of print]15(4):

A Novel Blood Proteomic Signature for Prostate Cancer.

Ammara Muazzam, Matt Spick, Olivier N F Cexus, Bethany Geary, Fowz Azhar, Hardev Pandha, Agnieszka Michael, Rachel Reed, Sarah Lennon, Lee A Gethings, Robert S Plumb, Anthony D Whetton, Nophar Geifman, Paul A Townsend.

  Prostate cancer is the most common malignant tumour in men. Improved testing for diagnosis, risk prediction, and response to treatment would improve care. Here, we identified a proteomic signature of prostate cancer in peripheral blood using data-independent acquisition mass spectrometry combined with machine learning. A highly predictive signature was derived, which was associated with relevant pathways, including the coagulation, complement, and clotting cascades, as well as plasma lipoprotein particle remodeling. We further validated the identified biomarkers against a second cohort, identifying a panel of five key markers (GP5, SERPINA5, ECM1, IGHG1, and THBS1) which retained most of the diagnostic power of the overall dataset, achieving an AUC of 0.91. Taken together, this study provides a proteomic signature complementary to PSA for the diagnosis of patients with localised prostate cancer, with the further potential for assessing risk of future development of prostate cancer. Data are available via ProteomeXchange with identifier PXD025484.

Keywords:  SWATH-MS; biomarkers; clinical onset; complement cascade; prostate cancer; proteomics

DOI:  https://doi.org/10.3390/cancers15041051
Bioinformatics. 2023 Feb 24. pii: btad096. [Epub ahead of print]

Regularized adversarial learning for normalization of multi-batch untargeted metabolomics data.

Andrei Dmitrenko, Michelle Reid, Nicola Zamboni.

MOTIVATION: Untargeted metabolomics by mass spectrometry is the method of choice for unbiased analysis of molecules in complex samples of biological, clinical, or environmental relevance. The exceptional versatility and sensitivity of modern high-resolution instruments allows profiling of thousands of known and unknown molecules in parallel. Inter-batch differences constitute a common and unresolved problem in untargeted metabolomics, and hinder the analysis of multi-batch studies or the intercomparison of experiments.RESULTS: We present a new method, Regularized Adversarial Learning Preserving Similarity (RALPS), for the normalization of multi-batch untargeted metabolomics data. RALPS builds on deep adversarial learning with a three-term loss function that mitigates batch effects while preserving biological identity, spectral properties, and coefficients of variation. Using two large metabolomics datasets, we showcase the superior performance of RALPS as compared with six state-of-the-art methods for batch correction. Further, we demonstrate that RALPS scales well, is robust, deals with missing values, and can handle different experimental designs.
AVAILABILITY: https://github.com/zamboni-lab/RALPS.
SUPPLEMENTARY INFORMATION: Supplementary material is available at Bioinformatics online.

DOI: https://doi.org/10.1093/bioinformatics/btad096
EMBO J. 2023 Feb 20. e112067

HIF: a master regulator of nutrient availability and metabolic cross-talk in the tumor microenvironment.

Rindert Missiaen, Nicholas P Lesner, M Celeste Simon.

  A role for hypoxia-inducible factors (HIFs) in hypoxia-dependent regulation of tumor cell metabolism has been thoroughly investigated and covered in reviews. However, there is limited information available regarding HIF-dependent regulation of nutrient fates in tumor and stromal cells. Tumor and stromal cells may generate nutrients necessary for function (metabolic symbiosis) or deplete nutrients resulting in possible competition between tumor cells and immune cells, a result of altered nutrient fates. HIF and nutrients in the tumor microenvironment (TME) affect stromal and immune cell metabolism in addition to intrinsic tumor cell metabolism. HIF-dependent metabolic regulation will inevitably result in the accumulation or depletion of essential metabolites in the TME. In response, various cell types in the TME will respond to these hypoxia-dependent alterations by activating HIF-dependent transcription to alter nutrient import, export, and utilization. In recent years, the concept of metabolic competition has been proposed for critical substrates, including glucose, lactate, glutamine, arginine, and tryptophan. In this review, we discuss how HIF-mediated mechanisms control nutrient sensing and availability in the TME, the competition for nutrients, and the metabolic cross-talk between tumor and stromal cells.

Keywords:  HIF; tumor metabolism; tumor microenvironment

DOI:  https://doi.org/10.15252/embj.2022112067
Nat Protoc. 2023 Feb 24.

A proposed framework to evaluate the quality and reliability of targeted metabolomics assays from the UK Consortium on Metabolic Phenotyping (MAP/UK).

UK Consortium on Metabolic Phenotyping (MAP/UK)

Targeted metabolite assays that measure tens or hundreds of pre-selected metabolites, typically using liquid chromatography-mass spectrometry, are increasingly being developed and applied to metabolic phenotyping studies. These are used both as standalone phenotyping methods and for the validation of putative metabolic biomarkers obtained from untargeted metabolomics studies. However, there are no widely accepted standards in the scientific community for ensuring reliability of the development and validation of targeted metabolite assays (referred to here as 'targeted metabolomics'). Most current practices attempt to adopt, with modifications, the strict guidance provided by drug regulatory authorities for analytical methods designed largely for measuring drugs and other xenobiotic analytes. Here, the regulatory guidance provided by the European Medicines Agency, US Food and Drug Administration and International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use are summarized. In this Perspective, we have adapted these guidelines and propose a less onerous 'tiered' approach to evaluate the reliability of a wide range of metabolomics analyses, addressing the need for community-accepted, harmonized guidelines for tiers other than full validation. This 'fit-for-purpose' tiered approach comprises four levels-discovery, screening, qualification and validation-and is discussed in the context of a range of targeted and untargeted metabolomics assays. Issues arising with targeted multiplexed metabolomics assays, and how these might be addressed, are considered. Furthermore, guidance is provided to assist the community with selecting the appropriate degree of reliability for a series of well-defined applications of metabolomics.

DOI: https://doi.org/10.1038/s41596-022-00801-8
Nat Immunol. 2023 Feb 23.

CD40 signal rewires fatty acid and glutamine metabolism for stimulating macrophage anti-tumorigenic functions.

Pu-Ste Liu, Yi-Ting Chen, Xiaoyun Li, Pei-Chun Hsueh, Sheue-Fen Tzeng, Hsi Chen, Pei-Zhu Shi, Xin Xie, Sweta Parik, Mélanie Planque, Sarah-Maria Fendt, Ping-Chih Ho.

Exposure of lipopolysaccharide triggers macrophage pro-inflammatory polarization accompanied by metabolic reprogramming, characterized by elevated aerobic glycolysis and a broken tricarboxylic acid cycle. However, in contrast to lipopolysaccharide, CD40 signal is able to drive pro-inflammatory and anti-tumorigenic polarization by some yet undefined metabolic programming. Here we show that CD40 activation triggers fatty acid oxidation (FAO) and glutamine metabolism to promote ATP citrate lyase-dependent epigenetic reprogramming of pro-inflammatory genes and anti-tumorigenic phenotypes in macrophages. Mechanistically, glutamine usage reinforces FAO-induced pro-inflammatory and anti-tumorigenic activation by fine-tuning the NAD+/NADH ratio via glutamine-to-lactate conversion. Genetic ablation of important metabolic enzymes involved in CD40-mediated metabolic reprogramming abolishes agonistic anti-CD40-induced antitumor responses and reeducation of tumor-associated macrophages. Together these data show that metabolic reprogramming, which includes FAO and glutamine metabolism, controls the activation of pro-inflammatory and anti-tumorigenic polarization, and highlight a therapeutic potential of metabolic preconditioning of tumor-associated macrophages before agonistic anti-CD40 treatments.

DOI: https://doi.org/10.1038/s41590-023-01430-3
Anal Chem. 2023 Feb 20.

Robust and Easy-to-Use One-Pot Workflow for Label-Free Single-Cell Proteomics.

Manuel Matzinger, Elisabeth Müller, Gerhard Dürnberger, Peter Pichler, Karl Mechtler.

The analysis of ultralow input samples or even individual cells is essential to answering a multitude of biomedical questions, but current proteomic workflows are limited in their sensitivity and reproducibility. Here, we report a comprehensive workflow that includes improved strategies for all steps, from cell lysis to data analysis. Thanks to convenient-to-handle 1 μL sample volume and standardized 384-well plates, the workflow is easy for even novice users to implement. At the same time, it can be performed semi-automatized using CellenONE, which allows for the highest reproducibility. To achieve high throughput, ultrashort gradient lengths down to 5 min were tested using advanced μ-pillar columns. Data-dependent acquisition (DDA), wide-window acquisition (WWA), data-independent acquisition (DIA), and commonly used advanced data analysis algorithms were benchmarked. Using DDA, 1790 proteins covering a dynamic range of four orders of magnitude were identified in a single cell. Using DIA, proteome coverage increased to more than 2200 proteins identified from single-cell level input in a 20 min active gradient. The workflow enabled differentiation of two cell lines, demonstrating its suitability to cellular heterogeneity determination.

DOI: https://doi.org/10.1021/acs.analchem.2c05022
Nucleic Acids Res. 2023 Feb 20. pii: gkad058. [Epub ahead of print]

Comprehensive chromatin proteomics resolves functional phases of pluripotency and identifies changes in regulatory components.

Enes Ugur, Alexandra de la Porte, Weihua Qin, Sebastian Bultmann, Alina Ivanova, Micha Drukker, Matthias Mann, Michael Wierer, Heinrich Leonhardt.

The establishment of cellular identity is driven by transcriptional and epigenetic regulators of the chromatin proteome - the chromatome. Comprehensive analyses of the chromatome composition and dynamics can therefore greatly improve our understanding of gene regulatory mechanisms. Here, we developed an accurate mass spectrometry (MS)-based proteomic method called Chromatin Aggregation Capture (ChAC) followed by Data-Independent Acquisition (DIA) and analyzed chromatome reorganizations during major phases of pluripotency. This enabled us to generate a comprehensive atlas of proteomes, chromatomes, and chromatin affinities for the ground, formative and primed pluripotency states, and to pinpoint the specific binding and rearrangement of regulatory components. These comprehensive datasets combined with extensive analyses identified phase-specific factors like QSER1 and JADE1/2/3 and provide a detailed foundation for an in-depth understanding of mechanisms that govern the phased progression of pluripotency. The technical advances reported here can be readily applied to other models in development and disease.

DOI: https://doi.org/10.1093/nar/gkad058
Front Oncol. 2023 ;13 1124715

Targeting immune-onco-metabolism for precision cancer therapy.

Sakshi Pajai, Jyoti E John, Satyendra Chandra Tripathi.

  Immune cells play a key role in host defence against infection and cancer. Unlike infection, cancer is a multidimensional disease where cancer cells require continuous activation of certain pathways to sustain their growth and survival. The tumour milieu plays an important role in defining the metabolic reprogramming to support this growth and evasion from the immune system. Cancer and stromal cells modulate each other's metabolism during cancer progression or regression. The mechanism related to change in the metabolism and its role in the crosstalk between tumour and immune cells is still an area of immense importance. Current treatment modalities can be immensely complemented and benefited by targeting the immuno-oncology metabolism, that can improve patient prognosis. This emerging aspect of immune-oncology metabolism is reviewed here, discussing therapeutic possibilities within various metabolic pathways and their effect on immune and cancer cell metabolism.

Keywords:  cancer; immune cells; immuno-oncology; metabolic reprogramming; metabolism; therapeutics; tumour immunology

DOI:  https://doi.org/10.3389/fonc.2023.1124715
Cancer Rep (Hoboken). 2023 Feb 21. e1795

Metabolomics in oncology.

Gurparsad Singh Suri, Gurleen Kaur, Giuseppina M Carbone, Dheeraj Shinde.

  BACKGROUND: Oncogenic transformation alters intracellular metabolism and contributes to the growth of malignant cells. Metabolomics, or the study of small molecules, can reveal insight about cancer progression that other biomarker studies cannot. Number of metabolites involved in this process have been in spotlight for cancer detection, monitoring, and therapy.RECENT FINDINGS: In this review, the "Metabolomics" is defined in terms of current technology having both clinical and translational applications. Researchers have shown metabolomics can be used to discern metabolic indicators non-invasively using different analytical methods like positron emission tomography, magnetic resonance spectroscopic imaging etc. Metabolomic profiling is a powerful and technically feasible way to track changes in tumor metabolism and gauge treatment response across time. Recent studies have shown metabolomics can also predict individual metabolic changes in response to cancer treatment, measure medication efficacy, and monitor drug resistance. Its significance in cancer development and treatment is summarized in this review.
CONCLUSION: Although in infancy, metabolomics can be used to identify treatment options and/or predict responsiveness to cancer treatments. Technical challenges like database management, cost and methodical knowhow still persist. Overcoming these challenges in near further can help in designing new treatment régimes with increased sensitivity and specificity.

Keywords:  biomarker; cancer; metabolic reprogramming; metabolism; metabolomics

DOI:  https://doi.org/10.1002/cnr2.1795
J Pharm Biomed Anal. 2023 Feb 16. pii: S0731-7085(23)00073-0. [Epub ahead of print]227 115304

Simultaneous measurement of kynurenine metabolites and explorative metabolomics using liquid chromatography-mass spectrometry: A novel accurate method applied to serum and plasma samples from a large healthy cohort.

Peter Preben Eggertsen, Jakob Hansen, Malene Lundfold Andersen, Jørgen Feldbæk Nielsen, Rikke Katrine Jentoft Olsen, Johan Palmfeldt.

  Kynurenine metabolites are emerging as promising clinical biomarkers in several diseases, especially within psychiatry. Unfortunately, they are difficult to detect, particularly the challenging neurotoxic metabolite quinolinic acid (QUIN). The aim of this study was twofold: First, to develop a liquid chromatography-mass spectrometry method (LC-MS) for simultaneous targeted quantification of key kynurenine metabolites together with untargeted metabolomics, and second, to demonstrate the feasibility of the method by exploring serum/plasma and gender differences in 120 healthy young adults between 18 and 30 years of age. A range of analytical columns (C18 and biphenyl columns) and mobile phases (acidic and alkaline) were systematically evaluated. The optimized LC-MS method was based on a biphenyl column, a water-methanol gradient with 0.2% formic acid, and authentic isotope-labeled standards for each kynurenine metabolite. Precision and accuracy of targeted quantification of the key kynurenine metabolites tryptophan (TRP), kynurenine (KYN), kynurenic acid (KYNA), 3-hydroxykynurenine (3-HK), and QUIN were excellent, far exceeding the acceptance criteria specified by international guidelines. Median inter- and intra-day precision were < 6% in serum and plasma; the median accuracy was 2.4% in serum and 8% in plasma. Serum concentrations were ≤ 10% different from the corresponding concentrations in plasma for all kynurenine metabolites in healthy young adults. Men had higher levels (8-18%) of TRP, KYN, and KYNA than women (p ≤ 0.009), while no differences were observed for 3-HK and QUIN (p > 0.70). Incurred sample reanalysis of 10% of the samples yielded a median difference < 5% from the initial measurement, demonstrating the robustness of the method. Besides the targeted quantification of key kynurenine metabolites, our method was found to be suitable for simultaneous untargeted metabolomics analyses of hundreds of metabolites. A range of compound classes could be detected including amino acids, nucleic acids, dipeptides, antioxidants, and acylcarnitines, making explorative studies highly feasible. For example, we identified an additional kynurenine metabolite, 2-Quinolinecarboxylic acid, which was 47% higher in males than females (adjusted p-value = 0.001). In conclusion, in this study, we present a reliable and robust LC-MS method for simultaneous targeted and untargeted metabolomics ready for both research and clinical use. We show that both serum and plasma can be used for kynurenine studies, and the reported gender differences are in accordance with the literature. Future studies should consider using biphenyl-based LC-MS columns to successfully detect QUIN.

Keywords:  Biomarker; Human blood; Kynurenine metabolites; LC-MS; Untargeted metabolomics

DOI:  https://doi.org/10.1016/j.jpba.2023.115304
Anal Bioanal Chem. 2023 Feb 23.

Liquid chromatography and differential mobility spectrometry-data-independent mass spectrometry for comprehensive multidimensional separations in metabolomics.

Lysi Ekmekciu, Gérard Hopfgartner.

  The benefits of combining drift time ion mobility (DTIMS) with liquid chromatography-high-resolution mass spectrometry (HRMS) have been reported for metabolomics but the use of differential time mobility spectrometry (DMS) is less obvious due to the need for rapid scanning of the DMS cell. Drift DTIMS provides additional precursor ion selectivity and collisional cross-section information but the separation resolution between analytes remains cell- and component-dependent. With DMS, the addition of 2-propanol modifier can improve the selectivity but on cost of analyte MS response. In the present work, we investigate the liquid chromatography-mass spectrometry (LC-MS) analysis of a mix of 50 analytes, representative for urine and plasma metabolites, using scanning DMS with the single modifiers cyclohexane (Ch), toluene (Tol), acetonitrile (ACN), ethanol (EtOH), and 2-propanol (IPA), and a binary modifier mixture (cyclohexane/2-propanol) with emphasis on selectivity and signal sensitivity. 1.5% IPA in the N2 stream was found to suppress the signal of 50% of the analytes which could be partially recovered with the use of IPA to 0.05% as a Ch/IPA mixture. The potential to use the separation voltage/compensation voltage/modifier (SV/CoV/Mod) feature as an additional analyte identifier for qualitative analysis is also presented and applied to a data-independent LCxDMS-SWATH-MS workflow for the analysis of endogenous metabolites and drugs of abuse in human urine samples from traffic control.

Keywords:  Differential mobility spectrometry; Human urine; Liquid chromatography–mass spectrometry; Metabolomics; SWATH-MS; Toxicology

DOI:  https://doi.org/10.1007/s00216-023-04602-0
bioRxiv. 2023 Feb 17. pii: 2023.02.15.528699. [Epub ahead of print]

Vacuum Insulated Probe Heated ElectroSpray Ionization source (VIP-HESI) enhances micro flow rate chromatography signals in the Bruker timsTOF mass spectrometer.

Mukul K Midha, Charu Kapil, Michal Maes, David H Baxter, Seamus R Morrone, Timothy J Prokop, Robert L Moritz.

By far the largest contribution to ion detectability in liquid chromatography-driven mass spectrometry-based proteomics is the efficient generation of peptide ions by the electrospray source. To maximize the transfer of peptides from liquid to a gaseous phase to allow molecular ions to enter the mass spectrometer at micro-spray flow rates, an efficient electrospray process is required. Here we describe superior performance of new Vacuum-Insulated-Probe-Heated-ElectroSpray-Ionization source (VIP-HESI) coupled with micro-spray flow rate chromatography and Bruker timsTOF PRO mass spectrometer. VIP-HESI significantly improves chromatography signals in comparison to nano-spray ionization using the CaptiveSpray source and provides increased protein detection with higher quantitative precision, enhancing reproducibility of sample injection amounts. Protein quantitation of human K562 lymphoblast samples displayed excellent chromatographic retention time reproducibility (<10% coefficient-of-variation (CV)) with no signal degradation over extended periods of time, and a mouse plasma proteome analysis identified 12% more plasma protein groups allowing large-scale analysis to proceed with confidence (1,267 proteins at 0.4% CV). We show that Slice-PASEF mode with VIP-HESI setup is sensitive in identifying low amounts of peptide without losing quantitative precision. We demonstrate that VIP-HESI coupled with micro-flow-rate chromatography achieves higher depth of coverage and run-to-run reproducibility for a broad range of proteomic applications.

DOI: https://doi.org/10.1101/2023.02.15.528699
Methods Mol Biol. 2023 ;2615 267-280

Quantitative Analysis of Nucleoside Triphosphate Pools in Mouse Muscle Using Hydrophilic Interaction Liquid Chromatography Coupled with Tandem Mass Spectrometry Detection.

Sushma Sharma, Ziqing Kong, Shaodong Jia, Phong Tran, Anna Karin Nilsson, Andrei Chabes.

  Defects in deoxyribonucleoside triphosphate (dNTP) metabolism are associated with a number of mitochondrial DNA (mtDNA) depletion syndromes (MDS). These disorders affect the muscles, liver, and brain, and the concentrations of dNTPs in these tissues are already normally low and are, therefore, difficult to measure. Thus, information about the concentrations of dNTPs in tissues of healthy animals and animals with MDS are important for mechanistic studies of mtDNA replication, analysis of disease progression, and the development of therapeutic interventions. Here, we present a sensitive method for the simultaneous analysis of all four dNTPs as well as all four ribonucleoside triphosphates (NTPs) in mouse muscles using hydrophilic interaction liquid chromatography coupled with triple quadrupole mass spectrometry. The simultaneous detection of NTPs allows them to be used as internal standards for the normalization of dNTP concentrations. The method can be applied for measuring dNTP and NTP pools in other tissues and organisms.

Keywords:  Deoxyribonucleoside triphosphates; Differentiated tissues; Liquid chromatography; Triple quadrupole mass spectrometry; ZIC–HILIC

DOI:  https://doi.org/10.1007/978-1-0716-2922-2_19
Mitochondrion. 2023 Feb 22. pii: S1567-7249(23)00020-X. [Epub ahead of print]

The mitochondrial chaperone TRAP-1 regulates the glutamine metabolism in tumor cells.

Shrikant Purushottam Dharaskar, Amere Subbarao Sreedhar.

  Understanding cancer cell metabolism always provides information on hidden dimensions of tumor adaptations. Warburg's theory that cancer cells opt for aerobic glycolysis over the mitochondrial oxidative phosphorylation (OXPHOS) system is widely accepted. However, the hypothesis does not explain the mitochondrion's role in these cells. Here, we demonstrate that intact mitochondria are used for anaplerotic functions and ATP production by utilizing glutamine with the help of mitochondrial chaperone TRAP-1 (Tumor Necrosis Factor Receptor-associated Protein 1). TRAP-1 otherwise promotes aerobic glycolysis by lowering the mitochondrial OXPHOS in the presence of glucose. Here, we show that TRAP-1 maintains mitochondrial integrity and augments glutamine metabolism upon glucose deprivation to meet the cellular energy demand. The enhanced PER and ECAR correlating with increased ATP production suggest that glutamine fuels mitochondria in the presence of TRAP-1. We also found that TRAP1-dependent glutamine utilization involves the HIF2α-SLC1A5-GLS axis and is independent of hypoxia. Subsequently, we found that the metastatic potential of tumor cells is linked with glucose utilization, whereas the proliferative potential is linked with both glucose and glutamine utilization. Our findings establish that TRAP-1 contributes to enhanced glutamine utilization through the HIF2α-SLC1A5-GLS axis. Our results endow that TRAP-1 inhibitors can be potential drug candidates to combat tumor metabolism. Therefore, their use, either alone or in combination with existing chemotherapeutic agents, may target tumor metabolism and improve anticancer treatment response.

Keywords:  TRAP-1; cancer; glutamine; metabolism; mitochondria

DOI:  https://doi.org/10.1016/j.mito.2023.02.011
Br J Cancer. 2023 Feb 17.

Quantitative SWATH-based proteomic profiling of urine for the identification of endometrial cancer biomarkers in symptomatic women.

Kelechi Njoku, Andrew Pierce, Bethany Geary, Amy E Campbell, Janet Kelsall, Rachel Reed, Alexander Armit, Rachel Da Sylva, Liqun Zhang, Heather Agnew, Ivona Baricevic-Jones, Davide Chiasserini, Anthony D Whetton, Emma J Crosbie.

BACKGROUND: A non-invasive endometrial cancer detection tool that can accurately triage symptomatic women for definitive testing would improve patient care. Urine is an attractive biofluid for cancer detection due to its simplicity and ease of collection. The aim of this study was to identify urine-based proteomic signatures that can discriminate endometrial cancer patients from symptomatic controls.METHODS: This was a prospective case-control study of symptomatic post-menopausal women (50 cancers, 54 controls). Voided self-collected urine samples were processed for mass spectrometry and run using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning techniques were used to identify important discriminatory proteins, which were subsequently combined in multi-marker panels using logistic regression.
RESULTS: The top discriminatory proteins individually showed moderate accuracy (AUC > 0.70) for endometrial cancer detection. However, algorithms combining the most discriminatory proteins performed well with AUCs > 0.90. The best performing diagnostic model was a 10-marker panel combining SPRR1B, CRNN, CALML3, TXN, FABP5, C1RL, MMP9, ECM1, S100A7 and CFI and predicted endometrial cancer with an AUC of 0.92 (0.96-0.97). Urine-based protein signatures showed good accuracy for the detection of early-stage cancers (AUC 0.92 (0.86-0.9)).
CONCLUSION: A patient-friendly, urine-based test could offer a non-invasive endometrial cancer detection tool in symptomatic women. Validation in a larger independent cohort is warranted.

DOI: https://doi.org/10.1038/s41416-022-02139-0
New Phytol. 2023 Feb 24.

Expression of malic enzyme reveals subcellular carbon partitioning for storage reserve production in soybeans.

Stewart A Morley, Fangfang Ma, Mazen Alazem, Cheryl Frankfater, Hochul Yi, Tessa Burch-Smith, Tom Elmo Clemente, Veena Veena, Hanh Nguyen, Doug K Allen.

  Central metabolism produces amino and fatty acids for protein and lipids that establish seed value. Biosynthesis of storage reserves occurs in multiple organelles that exchange central intermediates including two essential metabolites, malate and pyruvate that are linked by malic enzyme. Malic enzyme can be active in multiple subcellular compartments, partitioning carbon and reducing equivalents for anabolic and catabolic requirements. Prior studies based on isotopic labeling and steady state metabolic flux analyses indicated malic enzyme provides carbon for fatty acid biosynthesis in plants, though genetic evidence confirming this role is lacking. We hypothesized that increasing malic enzyme flux would alter carbon partitioning and result in increased lipid levels in soybeans. Homozygous transgenic soybean plants expressing Arabidopsis malic enzyme alleles, targeting the translational products to plastid or outside the plastid during seed development, were verified by transcript and enzyme activity analyses, organelle proteomics and transient expression assays. Protein, oil, central metabolites, cofactors, and acyl-acyl carrier protein (ACPs) levels were quantified over development. Amino and fatty acid levels were altered resulting in an increase in lipids by 0.5-2% of seed biomass (i.e., 2-9% change in oil). Subcellular targeting of a single gene product in central metabolism impacts carbon and reducing equivalent partitioning for seed storage reserves in soybeans.

Keywords:  Carbon partitioning; Central carbon metabolism; Lipid production; Malic enzyme; Metabolic flux; Soybean seed composition; Subcellular compartmentation

DOI:  https://doi.org/10.1111/nph.18835
J Biol Chem. 2023 Feb 15. pii: S0021-9258(23)00154-0. [Epub ahead of print] 103022

Fitm2 is required for ER homeostasis and normal function of murine liver.

Laura M Bond, Ayon Ibrahim, Zon W Lai, Rosemary L Walzem, Roderick T Bronson, Olga R Ilkayeva, Tobias C Walther, Robert V Farese.

  The endoplasmic reticulum (ER)-resident protein fat storage-inducing transmembrane protein 2 (FIT2) catalyzes acyl-CoA cleavage in vitro and is required for ER homeostasis and normal lipid storage in cells. The gene encoding FIT2 is essential for the viability of mice and worms. Whether FIT2 acts as an acyl-CoA diphosphatase in vivo and how this activity affects the liver, where the protein was discovered, are unknown. Here, we report that hepatocyte-specific Fitm2 knockout (FIT2-LKO) mice fed a chow diet exhibited elevated acyl-CoA levels, ER stress, and signs of liver injury. These mice also had more triglycerides in their livers than control littermates due, in part, to impaired secretion of triglyceride-rich lipoproteins and reduced capacity for fatty acid oxidation. We found that challenging FIT2-LKO mice with a high-fat diet worsened hepatic ER stress and liver injury, but unexpectedly reversed the steatosis phenotype, similar to what is observed in FIT2-deficient cells loaded with fatty acids. Our findings support the model that FIT2 acts as an acyl-CoA diphosphatase in vivo and is crucial for normal hepatocyte function and ER homeostasis in murine liver.

Keywords:  FITM2; acyl-CoA; endoplasmic reticulum; lipid metabolism; liver

DOI:  https://doi.org/10.1016/j.jbc.2023.103022