bims-mascan 2024-05-12 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2024–05–12
eightteen papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Data-dependent and -independent acquisition lipidomics analysis reveals the tissue-dependent effect of metformin on lipid metabolism.
Boosting the Sensitivity of Quantitative Single-Cell Proteomics with Infrared-Tandem Mass Tags.
Comparison of Three Widely Employed Extraction Methods for Metabolomic Analysis of Trypanosoma brucei.
The Future of Proteomics is Up in the Air: Can Ion Mobility Replace Liquid Chromatography for High Throughput Proteomics?
BERNN: Enhancing classification of Liquid Chromatography Mass Spectrometry data with batch effect removal neural networks.
Top-Down Proteomics Analysis of Picogram-Level Complex Samples Using Spray-Capillary-Based Capillary Electrophoresis-Mass Spectrometry.
The use of sequential window acquisition of all theoretical fragment ion spectra (SWATH), a data-independent acquisition high-resolution mass spectrometry approach, in forensic toxicological regimes: A review.
CLIPPER 2.0: Peptide level annotation and data analysis for positional proteomics.
Sphingolipid profiling reveals differential functions of sphingolipid biosynthesis isozymes of C. elegans.
Native N-glycome profiling of single cells and ng-level blood isolates using label-free capillary electrophoresis-mass spectrometry.
An inflection point in high-throughput proteomics with Orbitrap Astral: analysis of biofluids, cells, and tissues.
Fructose-induced metabolic reprogramming of cancer cells.
Phospholipase PLA2G7 is complementary to GPX4 in mitigating punicic-acid-induced ferroptosis in prostate cancer cells.
An untargeted analytical workflow based on Kendrick mass defect filtering reveals dysregulations in acylcarnitines in prostate cancer tissue.
Reprogrammed mitochondria: a central hub of cancer cell metabolism.
Mass Sportrometry: An annual look back at applications of mass spectrometry in sport and exercise science.
Chewing the fat: How lipidomics is changing our understanding of human health and disease in 2022.
A Hitchhiker's guide to high-dimensional tissue imaging with multiplexed ion beam imaging.

Metabolomics. 2024 May 09. 20(3): 53

Data-dependent and -independent acquisition lipidomics analysis reveals the tissue-dependent effect of metformin on lipid metabolism.

Grace Scheidemantle, Likun Duan, Mareca Lodge, Magdalina J Cummings, Dalton Hilovsky, Eva Pham, Xiaoqiu Wang, Arion Kennedy, Xiaojing Liu.

   INTRODUCTION: Despite the well-recognized health benefits, the mechanisms and site of action of metformin remains elusive. Metformin-induced global lipidomic changes in plasma of animal models and human subjects have been reported. However, there is a lack of systemic evaluation of metformin-induced lipidomic changes in different tissues. Metformin uptake requires active transporters such as organic cation transporters (OCTs), and hence, it is anticipated that metformin actions are tissue-dependent. In this study, we aim to characterize metformin effects in non-diabetic male mice with a special focus on lipidomics analysis. The findings from this study will help us to better understand the cell-autonomous (direct actions in target cells) or non-cell-autonomous (indirect actions in target cells) mechanisms of metformin and provide insights into the development of more potent yet safe drugs targeting a particular organ instead of systemic metabolism for metabolic regulations without major side effects.
OBJECTIVES: To characterize metformin-induced lipidomic alterations in different tissues of non-diabetic male mice and further identify lipids affected by metformin through cell-autonomous or systemic mechanisms based on the correlation between lipid alterations in tissues and the corresponding in-tissue metformin concentrations.
METHODS: A dual extraction method involving 80% methanol followed by MTBE (methyl tert-butyl ether) extraction enables the analysis of free fatty acids, polar metabolites, and lipids. Extracts from tissues and plasma of male mice treated with or without metformin in drinking water for 12 days were analyzed using HILIC chromatography coupled to Q Exactive Plus mass spectrometer or reversed-phase liquid chromatography coupled to MS/MS scan workflow (hybrid mode) on LC-Orbitrap Exploris 480 mass spectrometer using biologically relevant lipids-containing inclusion list for data-independent acquisition (DIA), named as BRI-DIA workflow followed by data-dependent acquisition (DDA), to maximum the coverage of lipids and minimize the negative effect of stochasticity of precursor selection on experimental consistency and reproducibility.
RESULTS: Lipidomics analysis of 6 mouse tissues and plasma allowed a systemic evaluation of lipidomic changes induced by metformin in different tissues. We observed that (1) the degrees of lipidomic changes induced by metformin treatment overly correlated with tissue concentrations of metformin; (2) the impact on lysophosphatidylcholine (lysoPC) and cardiolipins was positively correlated with tissue concentrations of metformin, while neutral lipids such as triglycerides did not correlate with the corresponding tissue metformin concentrations; (3) increase of intestinal tricarboxylic acid (TCA) cycle intermediates after metformin treatment.
CONCLUSION: The data collected in this study from non-diabetic mice with 12-day metformin treatment suggest that the overall metabolic effect of metformin is positively correlated with tissue concentrations and the effect on individual lipid subclass is via both cell-autonomous mechanisms (cardiolipins and lysoPC) and non-cell-autonomous mechanisms (triglycerides).

Keywords:  DIA; Intestinal metabolism; Lipidomics; Metformin

DOI:  https://doi.org/10.1007/s11306-024-02113-2
J Proteome Res. 2024 May 07.

Boosting the Sensitivity of Quantitative Single-Cell Proteomics with Infrared-Tandem Mass Tags.

Trenton M Peters-Clarke, Yiran Liang, Keaton L Mertz, Kenneth W Lee, Michael S Westphall, Joshua D Hinkle, Graeme C McAlister, John E P Syka, Ryan T Kelly, Joshua J Coon.

  Single-cell proteomics is a powerful approach to precisely profile protein landscapes within individual cells toward a comprehensive understanding of proteomic functions and tissue and cellular states. The inherent challenges associated with limited starting material demand heightened analytical sensitivity. Just as advances in sample preparation maximize the amount of material that makes it from the cell to the mass spectrometer, we strive to maximize the number of ions that make it from ion source to the detector. In isobaric tagging experiments, limited reporter ion generation limits quantitative accuracy and precision. The combination of infrared photoactivation and ion parking circumvents the m/z dependence inherent in HCD, maximizing reporter generation and avoiding unintended degradation of TMT reporter molecules in infrared-tandem mass tags (IR-TMT). The method was applied to single-cell human proteomes using 18-plex TMTpro, resulting in 4-5-fold increases in reporter signal compared to conventional SPS-MS3 approaches. IR-TMT enables faster duty cycles, higher throughput, and increased peptide identification and quantification. Comparative experiments showcase 4-5-fold lower injection times for IR-TMT, providing superior sensitivity without compromising accuracy. In all, IR-TMT enhances the dynamic range of proteomic experiments and is compatible with gas-phase fractionation and real-time searching, promising increased gains in the study of cellular heterogeneity.

Keywords:  infrared; mass spectrometry; multiplex; peptide quantification; photoactivation; single-cell proteomics; tandem mass tags

DOI:  https://doi.org/10.1021/acs.jproteome.4c00076
Curr Protoc. 2024 May;4(5): e1043

Comparison of Three Widely Employed Extraction Methods for Metabolomic Analysis of Trypanosoma brucei.

Fanta Fall, Lieven Desmet, Lúcia Mamede, Laura Schioppa, Pascal de Tullio, Michel Frédérich, Bernadette Govaerts, Joëlle Quetin-Leclercq.

  Trypanosoma brucei (Tb) is the causative agent of human African trypanosomiasis (HAT), also known as sleeping sickness, which can be fatal if left untreated. An understanding of the parasite's cellular metabolism is vital for the discovery of new antitrypanosomal drugs and for disease eradication. Metabolomics can be used to analyze numerous metabolic pathways described as essential to Tb. brucei but has some limitations linked to the metabolites' physicochemical properties and the extraction process. To develop an optimized method for extracting and analyzing Tb. brucei metabolites, we tested the three most commonly used extraction methods, analyzed the extracts by hydrophilic interaction liquid chromatography high-resolution mass spectrometry (HILIC LC-HRMS), and further evaluated the results using quantitative criteria including the number, intensity, reproducibility, and variability of features, as well as qualitative criteria such as the specific coverage of relevant metabolites. Here, we present the resulting protocols for untargeted metabolomic analysis of Tb. brucei using (HILIC LC-HRMS). © 2024 Wiley Periodicals LLC. Basic Protocol 1: Culture of Trypanosoma brucei brucei parasites Basic Protocol 2: Preparation of samples for metabolomic analysis of Trypanosoma brucei brucei Basic Protocol 3: LC-HRMS-based metabolomic data analysis of Trypanosoma brucei brucei.

Keywords:  Trypanosoma brucei; extraction; mass spectrometry; metabolomics

DOI:  https://doi.org/10.1002/cpz1.1043
J Proteome Res. 2024 May 07.

The Future of Proteomics is Up in the Air: Can Ion Mobility Replace Liquid Chromatography for High Throughput Proteomics?

Yuming Jiang, Daniel DeBord, Heidi Vitrac, Jordan Stewart, Ali Haghani, Jennifer E Van Eyk, Justyna Fert-Bober, Jesse G Meyer.

  The coevolution of liquid chromatography (LC) with mass spectrometry (MS) has shaped contemporary proteomics. LC hyphenated to MS now enables quantification of more than 10,000 proteins in a single injection, a number that likely represents most proteins in specific human cells or tissues. Separations by ion mobility spectrometry (IMS) have recently emerged to complement LC and further improve the depth of proteomics. Given the theoretical advantages in speed and robustness of IMS in comparison to LC, we envision that ongoing improvements to IMS paired with MS may eventually make LC obsolete, especially when combined with targeted or simplified analyses, such as rapid clinical proteomics analysis of defined biomarker panels. In this perspective, we describe the need for faster analysis that might drive this transition, the current state of direct infusion proteomics, and discuss some technical challenges that must be overcome to fully complete the transition to entirely gas phase proteomics.

Keywords:  direct infusion; high throughput; ion mobility; shotgun proteomics

DOI:  https://doi.org/10.1021/acs.jproteome.4c00248
Nat Commun. 2024 May 06. 15(1): 3777

BERNN: Enhancing classification of Liquid Chromatography Mass Spectrometry data with batch effect removal neural networks.

Simon J Pelletier, Mickaël Leclercq, Florence Roux-Dalvai, Matthijs B de Geus, Shannon Leslie, Weiwei Wang, TuKiet T Lam, Angus C Nairn, Steven E Arnold, Becky C Carlyle, Frédéric Precioso, Arnaud Droit.

Liquid Chromatography Mass Spectrometry (LC-MS) is a powerful method for profiling complex biological samples. However, batch effects typically arise from differences in sample processing protocols, experimental conditions, and data acquisition techniques, significantly impacting the interpretability of results. Correcting batch effects is crucial for the reproducibility of omics research, but current methods are not optimal for the removal of batch effects without compressing the genuine biological variation under study. We propose a suite of Batch Effect Removal Neural Networks (BERNN) to remove batch effects in large LC-MS experiments, with the goal of maximizing sample classification performance between conditions. More importantly, these models must efficiently generalize in batches not seen during training. A comparison of batch effect correction methods across five diverse datasets demonstrated that BERNN models consistently showed the strongest sample classification performance. However, the model producing the greatest classification improvements did not always perform best in terms of batch effect removal. Finally, we show that the overcorrection of batch effects resulted in the loss of some essential biological variability. These findings highlight the importance of balancing batch effect removal while preserving valuable biological diversity in large-scale LC-MS experiments.

DOI: https://doi.org/10.1038/s41467-024-48177-5
Anal Chem. 2024 May 09.

Top-Down Proteomics Analysis of Picogram-Level Complex Samples Using Spray-Capillary-Based Capillary Electrophoresis-Mass Spectrometry.

Zhitao Zhao, Yanting Guo, Trishika Chowdhury, Samin Anjum, Jiaxue Li, Lushuang Huang, Kellye A Cupp-Sutton, Anthony Burgett, Dingjing Shi, Si Wu.

Proteomics analysis of mass-limited samples has become increasingly important for understanding biological systems in physiologically relevant contexts such as patient samples, multicellular organoids, spheroids, and single cells. However, relatively low sensitivity in top-down proteomics methods makes their application to mass-limited samples challenging. Capillary electrophoresis (CE) has emerged as an ideal separation method for mass-limited samples due to its high separation resolution, ultralow detection limit, and minimal sample volume requirements. Recently, we developed "spray-capillary", an electrospray ionization (ESI)-assisted device, that is capable of quantitative ultralow-volume sampling (e.g., pL-nL level). Here, we developed a spray-capillary-CE-MS platform for ultrasensitive top-down proteomics analysis of intact proteins in mass-limited complex biological samples. Specifically, to improve the sensitivity of the spray-capillary platform, we incorporated a polyethylenimine (PEI)-coated capillary and optimized the spray-capillary inner diameter. Under optimized conditions, we successfully detected over 200 proteoforms from 50 pg of E. coli lysate. To our knowledge, the spray-capillary CE-MS platform developed here represents one of the most sensitive detection methods for top-down proteomics. Furthermore, in a proof-of-principle experiment, we detected 261 ± 65 and 174 ± 45 intact proteoforms from fewer than 50 HeLa and OVCAR-8 cells, respectively, by coupling nanodroplet-based sample preparation with our optimized CE-MS platform. Overall, our results demonstrate the capability of the modified spray-capillary CE-MS platform to perform top-down proteomics analysis on picogram amounts of samples. This advancement presents the possibility of meaningful top-down proteomics analysis of mass-limited samples down to the level of single mammalian cells.

DOI: https://doi.org/10.1021/acs.analchem.4c01119
Drug Test Anal. 2024 May 09.

The use of sequential window acquisition of all theoretical fragment ion spectra (SWATH), a data-independent acquisition high-resolution mass spectrometry approach, in forensic toxicological regimes: A review.

Maria Sarkisian, Luke N Rodda.

  Sequential window acquisition of all theoretical fragment ion spectra (SWATH) is a type of high-resolution mass spectrometry that uses data-independent acquisition. Compared with more targeted acquisition schemes, the power behind this data-independent acquisition technique comes from its ability to mitigate interferences via the use of SWATH acquisition windows (Q1 quadrupole isolation windows) while still obtaining all accurate mass information. However, consistent with high-resolution mass spectrometry techniques, its routine and high throughput implementation in forensic toxicology is limited due to the complex processing power required to effectively manage the large amount of acquired data. It is therefore pivotal to create an efficient and validated identification criterion that confidently reports suspected positive detections as a confirmational technique for final reporting. This review examines all publications that implemented SWATH in a forensic toxicological framework with suggestive best practices and commonly used criteria. Seventeen publications were reviewed for extraction, liquid chromatography and mass spectrometry parameters, and more specifically for all SWATH applicable characteristics including spray voltages, collision energies and spreads, mass error, isotopic ratio difference, retention time error, and library score thresholds. Notwithstanding the challenges SWATH implementation faces for a laboratory, the technique demonstrates its potential to be utilized in routine forensic toxicology testing regimes and aids in the detection of both common and emerging novel drugs simultaneously.

Keywords:  QTOF/MS; best practices; comprehensive forensic toxicology; liquid chromatography–tandem mass spectrometry; sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH)

DOI:  https://doi.org/10.1002/dta.3700
Mol Cell Proteomics. 2024 May 02. pii: S1535-9476(24)00071-9. [Epub ahead of print] 100781

CLIPPER 2.0: Peptide level annotation and data analysis for positional proteomics.

Konstantinos Kalogeropoulos, Aleksander Moldt Haack, Elizabeta Madzharova, Antea Di Lorenzo, Rawad Hanna, Erwin M Schoof, Ulrich Auf dem Keller.

  Positional proteomics methodologies have transformed protease research, and have brought mass spectrometry (MS)-based degradomics studies to the forefront of protease characterization and system-wide interrogation of protease signaling. Considerable advancements in both sensitivity and throughput of liquid chromatography (LC)-MS/MS instrumentation enable the generation of enormous positional proteomics datasets of natural and protein termini and neo-termini of cleaved protease substrates. However, a concomitant progress has not been observed to the same extent in data analysis and post-processing steps, arguably constituting the largest bottleneck in positional proteomics workflows. Here, we present a computational tool, CLIPPER 2.0, that builds on prior algorithms developed for MS-based protein termini analysis, facilitating peptide level annotation and data analysis. CLIPPER 2.0 can be used with several sample preparation workflows and proteomics search algorithms, and enables fast and automated database information retrieval, statistical and network analysis, as well as visualization of terminomic datasets. We demonstrate the applicability of our tool by analyzing GluC and MMP9 cleavages in HeLa lysates. CLIPPER 2.0 is available at https://github.com/UadKLab/CLIPPER-2.0.

Keywords:  LC-MS; computational proteomics; degradomics; positional proteomics; post-translational modification

DOI:  https://doi.org/10.1016/j.mcpro.2024.100781
J Lipid Res. 2024 May 02. pii: S0022-2275(24)00058-0. [Epub ahead of print] 100553

Sphingolipid profiling reveals differential functions of sphingolipid biosynthesis isozymes of C. elegans.

Hui Luo, Xue Zhao, Zi-Dan Wang, Gang Wu, Yu Xia, Meng-Qiu Dong, Yan Ma.

  Multiple isozymes are encoded in the C. elegans genome for the various sphingolipid biosynthesis reactions, but the contributions of individual isozymes are characterized only in part. We developed a simple but effective reversed-phase liquid chromatography-tandem mass spectrometry (RPLC-MS/MS) method that enables simultaneous identification and quantification of ceramides (Cer), glucosylceramides (GlcCer), and sphingomyelins (SM), three important classes of sphingolipids from the same MS run. Validating this sphingolipid profiling method, we show that nearly all 47 quantifiable sphingolipid species found in young adult worms were reduced upon RNA interference (RNAi) of sptl-1 or elo-5, which are required for synthesis of the id17:1 sphingoid base. We also confirm that HYL-1 and HYL-2, but not LAGR-1, constitute the major ceramide synthase activity with different preference for fatty acid substrates, and that CGT-3, but not CGT-1 and CGT-2, plays a major role in producing glucosylceramides. Deletion of sms-5 hardly affects SM levels. RNAi of sms-1, -2, and -3 all lower the abundance of sphingomyelins with an odd number of carbon atoms (mostly C21 and C23, with or without hydroxylation) in the N-acyl chain, and only sms-1 RNAi does not elevate sphingomyelins containing even-numbered N-acyl chains. This suggests that sphingolipids containing even-numbered N-acyl chains could be regulated separately, sometimes in opposite directions, with those containing odd-numbered N-acyls, presumably monomethyl branched chain fatty acyls. We also find that ceramide levels are kept in balance with those of glucosylceramides and sphingomyelins.

Keywords:  Caenorhabditis elegans, mass spectrometry; and monomethyl branched chain fatty acid; ceramide; glucosylceramide; sphingolipid; sphingomyelin

DOI:  https://doi.org/10.1016/j.jlr.2024.100553
Nat Commun. 2024 May 08. 15(1): 3847

Native N-glycome profiling of single cells and ng-level blood isolates using label-free capillary electrophoresis-mass spectrometry.

Anne-Lise Marie, Yunfan Gao, Alexander R Ivanov.

The development of reliable single-cell dispensers and substantial sensitivity improvement in mass spectrometry made proteomic profiling of individual cells achievable. Yet, there are no established methods for single-cell glycome analysis due to the inability to amplify glycans and sample losses associated with sample processing and glycan labeling. In this work, we present an integrated platform coupling online in-capillary sample processing with high-sensitivity label-free capillary electrophoresis-mass spectrometry for N-glycan profiling of single mammalian cells. Direct and unbiased quantitative characterization of single-cell surface N-glycomes are demonstrated for HeLa and U87 cells, with the detection of up to 100 N-glycans per single cell. Interestingly, N-glycome alterations are unequivocally detected at the single-cell level in HeLa and U87 cells stimulated with lipopolysaccharide. The developed workflow is also applied to the profiling of ng-level amounts (5-500 ng) of blood-derived protein, extracellular vesicle, and total plasma isolates, resulting in over 170, 220, and 370 quantitated N-glycans, respectively.

DOI: https://doi.org/10.1038/s41467-024-47772-w
bioRxiv. 2024 Apr 27. pii: 2024.04.26.591396. [Epub ahead of print]

An inflection point in high-throughput proteomics with Orbitrap Astral: analysis of biofluids, cells, and tissues.

Nathan G Hendricks, Santosh D Bhosale, Angel J Keoseyan, Josselin Ortiz, Aleksandr Stotland, Saeed Seyedmohammad, Chi D L Nguyen, Jonathan Bui, Annie Moradian, Susan M Mockus, Jennifer E Van Eyk.

This technical note presents a comprehensive proteomics workflow for the new combination of Orbitrap and Astral mass analyzers across biofluids, cells, and tissues. Central to our workflow is the integration of Adaptive Focused Acoustics (AFA) technology for cells and tissue lysis, to ensure robust and reproducible sample preparation in a high-throughput manner. Furthermore, we automated the detergent-compatible single-pot, solid-phase-enhanced sample Preparation (SP3) method for protein digestion, a technique that streamlines the process by combining purification and digestion steps, thereby reducing sample loss and improving efficiency. The synergy of these advanced methodologies facilitates a robust and high-throughput approach for cells and tissue analysis, an important consideration in translational research. This work disseminates our platform workflow, analyzes the effectiveness, demonstrates reproducibility of the results, and highlights the potential of these technologies in biomarker discovery and disease pathology. For cells and tissues (heart, liver, lung, and intestine) proteomics analysis by data-independent acquisition mode, identifications exceeding 10,000 proteins can be achieved with a 24-minute active gradient. In 200ng injections of HeLa digest across multiple gradients, an average of more than 80% of proteins have a CV less than 20%, and a 45-minute run covers ∼90% of the expressed proteome. In plasma samples including naive, depleted, perchloric acid precipitated, and Seer nanoparticle captured, all with a 24-minute gradient length, we identified 87, 108, 96 and 137 out of 216 FDA approved circulating protein biomarkers, respectively. This complete workflow allows for large swaths of the proteome to be identified and is compatible across diverse sample types.
Graphical abstract created with biorendercom:

DOI: https://doi.org/10.1101/2024.04.26.591396
Front Immunol. 2024 ;15 1375461

Fructose-induced metabolic reprogramming of cancer cells.

Kenneth K Y Ting.

  Excess dietary fructose consumption has been long proposed as a culprit for the world-wide increase of incidence in metabolic disorders and cancer within the past decades. Understanding that cancer cells can gradually accumulate metabolic mutations in the tumor microenvironment, where glucose is often depleted, this raises the possibility that fructose can be utilized by cancer cells as an alternative source of carbon. Indeed, recent research has increasingly identified various mechanisms that show how cancer cells can metabolize fructose to support their proliferating and migrating needs. In light of this growing interest, this review will summarize the recent advances in understanding how fructose can metabolically reprogram different types of cancer cells, as well as how these metabolic adaptations can positively support cancer cells development and malignancy.

Keywords:  GLUT5; cancer; fructose; glycolysis; ketohexokinase (KHK); metabolic reprogramming; metabolism; tumor microenvironment (TME)

DOI:  https://doi.org/10.3389/fimmu.2024.1375461
iScience. 2024 May 17. 27(5): 109774

Phospholipase PLA2G7 is complementary to GPX4 in mitigating punicic-acid-induced ferroptosis in prostate cancer cells.

Perrine Vermonden, Manon Martin, Katarzyna Glowacka, Ineke Neefs, Josef Ecker, Marcus Höring, Gerhard Liebisch, Cathy Debier, Olivier Feron, Yvan Larondelle.

  Ferroptosis is a cell death pathway that can be promoted by peroxidizable polyunsaturated fatty acids in cancer cells. Here, we investigated the mechanisms underlying the toxicity of punicic acid (PunA), an isomer of conjugated linolenic acids (CLnAs) bearing three conjugated double bonds highly prone to peroxidation, on prostate cancer (PCa) cells. PunA induced ferroptosis in PCa cells and triggered massive lipidome remodeling, more strongly in PC3 androgen-negative cells than in androgen-positive cells. The greater sensitivity of androgen-negative cells to PunA was associated with lower expression of glutathione peroxidase 4 (GPX4). We then identified the phospholipase PLA2G7 as a PunA-induced ferroptosis suppressor in PCa cells. Overexpressing PLA2G7 decreased lipid peroxidation levels, suggesting that PLA2G7 hydrolyzes hydroperoxide-containing phospholipids, thus preventing ferroptosis. Importantly, overexpressing both PLA2G7 and GPX4 strongly prevented PunA-induced ferroptosis in androgen-negative PCa cells. This study shows that PLA2G7 acts complementary to GPX4 to protect PCa cells from CLnA-induced ferroptosis.

Keywords:  Cell biology; Lipidomics; Molecular biology

DOI:  https://doi.org/10.1016/j.isci.2024.109774
Anal Chim Acta. 2024 Jun 08. pii: S0003-2670(24)00375-1. [Epub ahead of print]1307 342574

An untargeted analytical workflow based on Kendrick mass defect filtering reveals dysregulations in acylcarnitines in prostate cancer tissue.

Andrea Cerrato, Sara Elsa Aita, Alessandra Biancolillo, Aldo Laganà, Federico Marini, Carmela Maria Montone, Davide Rosati, Stefano Salciccia, Alessandro Sciarra, Enrico Taglioni, Anna Laura Capriotti.

   BACKGROUND: Metabolomics is nowadays considered one the most powerful analytical for the discovery of metabolic dysregulations associated with the insurgence of cancer, given the reprogramming of the cell metabolism to meet the bioenergetic and biosynthetic demands of the malignant cell. Notwithstanding, several challenges still exist regarding quality control, method standardization, data processing, and compound identification. Therefore, there is a need for effective and straightforward approaches for the untargeted analysis of structurally related classes of compounds, such as acylcarnitines, that have been widely investigated in prostate cancer research for their role in energy metabolism and transport and β-oxidation of fatty acids.
RESULTS: In the present study, an innovative analytical platform was developed for the straightforward albeit comprehensive characterization of acylcarnitines based on high-resolution mass spectrometry, Kendrick mass defect filtering, and confirmation by prediction of their retention time in reversed-phase chromatography. In particular, a customized data processing workflow was set up on Compound Discoverer software to enable the Kendrick mass defect filtering, which allowed filtering out more than 90 % of the initial features resulting from the processing of 25 tumoral and adjacent non-malignant prostate tissues collected from patients undergoing radical prostatectomy. Later, a partial least square-discriminant analysis model validated by repeated double cross-validation was built on the dataset of 74 annotated acylcarnitines, with classification rates higher than 93 % for both groups, and univariate statistical analysis helped elucidate the individual role of the annotated metabolites.
SIGNIFICANCE: Hydroxylation of short- and medium-chain minor acylcarnitines appeared to be a significant variable in describing tissue differences, suggesting the hypothesis that the neoplastic growth is linked to oxidation phenomena on selected metabolites and reinforcing the need for effective methods for the annotation of minor metabolites.

Keywords:  Metabolomics; PLS-DA; Prostatic neoplasm; Repeated double cross validation; Retention time prediction; β-oxidation

DOI:  https://doi.org/10.1016/j.aca.2024.342574
Biochem Soc Trans. 2024 May 08. pii: BST20231090. [Epub ahead of print]

Reprogrammed mitochondria: a central hub of cancer cell metabolism.

Fabio Ciccarone, Maria Rosa Ciriolo.

  Mitochondria represent the metabolic hub of normal cells and play this role also in cancer but with different functional purposes. While cells in differentiated tissues have the prerogative of maintaining basal metabolism and support the biosynthesis of specialized products, cancer cells have to rewire the metabolic constraints imposed by the differentiation process. They need to balance the bioenergetic supply with the anabolic requirements that entail the intense proliferation rate, including nucleotide and membrane lipid biosynthesis. For this aim, mitochondrial metabolism is reprogrammed following the activation of specific oncogenic pathways or due to specific mutations of mitochondrial proteins. The main process leading to mitochondrial metabolic rewiring is the alteration of the tricarboxylic acid cycle favoring the appropriate orchestration of anaplerotic and cataplerotic reactions. According to the tumor type or the microenvironmental conditions, mitochondria may decouple glucose catabolism from mitochondrial oxidation in favor of glutaminolysis or disable oxidative phosphorylation for avoiding harmful production of free radicals. These and other metabolic settings can be also determined by the neo-production of oncometabolites that are not specific for the tissue of origin or the accumulation of metabolic intermediates able to boost pro-proliferative metabolism also impacting epigenetic/transcriptional programs. The full characterization of tumor-specific mitochondrial signatures may provide the identification of new biomarkers and therapeutic opportunities based on metabolic approaches.

Keywords:  TCA cycle; metabolic disorders; mitochondrial dysfunction

DOI:  https://doi.org/10.1042/BST20231090
Anal Sci Adv. 2023 May;4(3-4): 60-80

Mass Sportrometry: An annual look back at applications of mass spectrometry in sport and exercise science.

Marilyn Ly Ong, Christopher G Green, Samantha N Rowland, Liam M Heaney.

  Research in sport and exercise science (SES) is reliant on robust analyses of biomarker measurements to assist with the interpretation of physiological outcomes. Mass spectrometry (MS) is an analytical approach capable of highly sensitive, specific, precise, and accurate analyses of a range of biomolecules, many of which are of interest in SES including, but not limited to, endogenous metabolites, exogenously administered compounds (e.g. supplements), mineral ions, and circulating/tissue proteins. This annual review provides a summary of the applications of MS across studies investigating aspects related to sport or exercise in manuscripts published, or currently in press, in 2022. In total, 93 publications are included and categorized according to their methodologies including targeted analyses, metabolomics, lipidomics, proteomics, and isotope ratio/elemental MS. The advantageous analytical opportunities afforded by MS technologies are discussed across a selection of relevant articles. In addition, considerations for the future of MS in SES, including the need to improve the reporting of assay characteristics and validation data, are discussed, alongside the recommendation for selected current methods to be superseded by MS-based approaches where appropriate. The review identifies that a targeted, mostly quantitative, approach is the most commonly applied MS approach within SES, although there has also been a keen interest in the use of 'omics' to perform hypothesis-generating research studies. Nonetheless, MS is not commonplace in SES at this time, but its use to expand, and possibly improve, the analytical options should be continually considered to exploit the benefits of analytical chemistry in exercise/sports-based research. Overall, it is exciting to see the gradually increasing adoption of MS in SES and it is expected that the number, and quality, of MS-based assays in SES will increase over time, with the potential for 2023 to further establish this technique within the field.

Keywords:  analytical science; exercise; mass spectrometry; nutrition; sport

DOI:  https://doi.org/10.1002/ansa.202300003
Anal Sci Adv. 2023 May;4(3-4): 104-131

Chewing the fat: How lipidomics is changing our understanding of human health and disease in 2022.

Caroline Géhin, Stephen J Fowler, Drupad K Trivedi.

Lipids are biological molecules that play vital roles in all living organisms. They perform many cellular functions, such as 1) forming cellular and subcellular membranes, 2) storing and using energy, and 3) serving as chemical messengers during intra- and inter-cellular signal transduction. The large-scale study of the pathways and networks of cellular lipids in biological systems is called "lipidomics" and is one of the fastest-growing omics technologies of the last two decades. With state-of-the-art mass spectrometry instrumentation and sophisticated data handling, clinical studies show how human lipid composition changes in health and disease, thereby making it a valuable medium to collect for clinical applications, such as disease diagnostics, therapeutic decision-making, and drug development. This review gives a comprehensive overview of current workflows used in clinical research, from sample collection and preparation to data and clinical interpretations. This is followed by an appraisal of applications in 2022 and a perspective on the exciting future of clinical lipidomics.

DOI: https://doi.org/10.1002/ansa.202300009
Methods Cell Biol. 2024 ;pii: S0091-679X(24)00049-9. [Epub ahead of print]186 213-231

A Hitchhiker's guide to high-dimensional tissue imaging with multiplexed ion beam imaging.

Yao Yu Yeo, Precious Cramer, Addison Deisher, Yunhao Bai, Bokai Zhu, Wan-Jin Yeo, Margaret A Shipp, Scott J Rodig, Sizun Jiang.

  Advancements in multiplexed tissue imaging technologies are vital in shaping our understanding of tissue microenvironmental influences in disease contexts. These technologies now allow us to relate the phenotype of individual cells to their higher-order roles in tissue organization and function. Multiplexed Ion Beam Imaging (MIBI) is one of such technologies, which uses metal isotope-labeled antibodies and secondary ion mass spectrometry (SIMS) to image more than 40 protein markers simultaneously within a single tissue section. Here, we describe an optimized MIBI workflow for high-plex analysis of Formalin-Fixed Paraffin-Embedded (FFPE) tissues following antigen retrieval, metal isotope-conjugated antibody staining, imaging using the MIBI instrument, and subsequent data processing and analysis. While this workflow is focused on imaging human FFPE samples using the MIBI, this workflow can be easily extended to model systems, biological questions, and multiplexed imaging modalities.

Keywords:  Immunohistochemistry; MIBI; Multiplexed imaging; Spatial proteomics

DOI:  https://doi.org/10.1016/bs.mcb.2024.02.018