bims-mascan 2024-06-09 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2024‒06‒09
nineteen papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh

Common data models to streamline metabolomics processing and annotation, and implementation in a Python pipeline.
Analysis of Metabolic Changes in Endogenous Metabolites and Diagnostic Biomarkers for Various Diseases Using Liquid Chromatography and Mass Spectrometry.
Mass spectrometry imaging-based multi-omics approaches to understand drug metabolism and disposition.
Death and the desaturase: Implication of Stearoyl-CoA desaturase-1 in the mechanisms of cell stress, apoptosis, and ferroptosis.
Statistical and computational methods for integrating microbiome, host genomics, and metabolomics data.
Increasing Proteome Coverage Through a Reduction in Analyte Complexity in Single-Cell Equivalent Samples.
Tidy-Direct-to-MS: An Open-Source Data-Processing Pipeline for Direct Mass Spectrometry-Based Metabolomics Experiments.
Publisher Correction: METLIN-CCS Lipid Database: An authentic standards resource for lipid classification and identification.
Extracellular vesicle proteins as breast cancer biomarkers: Mass spectrometry-based analysis.
Metabolic dysregulation of tricarboxylic acid cycle and oxidative phosphorylation in glioblastoma.
Hyphenation of Liquid Chromatography and Trapped Ion Mobility - Mass Spectrometry for Characterization of Isomeric Phosphatidylethanolamines with Focus on N-Acylated Species.
Role of lipid metabolism in hepatocellular carcinoma.
UnitedMet harnesses RNA-metabolite covariation to impute metabolite levels in clinical samples.
De novo and salvage purine synthesis pathways across tissues and tumors.
ModiFinder: Tandem Mass Spectral Alignment Enables Structural Modification Site Localization.
iLipidome: enhancing statistical power and interpretability using hidden biosynthetic interdependencies in the lipidome.
Exploring sample treatment strategies for untargeted metabolomics: A comparative study of solid phase microextraction (SPME) and homogenization with solid-liquid extraction (SLE) in renal tissue.
Targeted Quantification of Glutathione/Arginine Redox Metabolism Based on a Novel Paired Mass Spectrometry Probe Approach for the Functional Assessment of Redox Status.
Deciphering pathophysiological mechanisms underlying cystathionine beta-synthase-deficient homocystinuria using targeted metabolomics, liver proteomics, sphingolipidomics and analysis of mitochondrial function.

PLoS Comput Biol. 2024 Jun 06. 20(6): e1011912

Common data models to streamline metabolomics processing and annotation, and implementation in a Python pipeline.

Joshua M Mitchell, Yuanye Chi, Maheshwor Thapa, Zhiqiang Pang, Jianguo Xia, Shuzhao Li.

To standardize metabolomics data analysis and facilitate future computational developments, it is essential to have a set of well-defined templates for common data structures. Here we describe a collection of data structures involved in metabolomics data processing and illustrate how they are utilized in a full-featured Python-centric pipeline. We demonstrate the performance of the pipeline, and the details in annotation and quality control using large-scale LC-MS metabolomics and lipidomics data and LC-MS/MS data. Multiple previously published datasets are also reanalyzed to showcase its utility in biological data analysis. This pipeline allows users to streamline data processing, quality control, annotation, and standardization in an efficient and transparent manner. This work fills a major gap in the Python ecosystem for computational metabolomics.

DOI: https://doi.org/10.1371/journal.pcbi.1011912
Biol Pharm Bull. 2024 ;47(6): 1087-1105

Analysis of Metabolic Changes in Endogenous Metabolites and Diagnostic Biomarkers for Various Diseases Using Liquid Chromatography and Mass Spectrometry.

Masamitsu Maekawa.

  Analysis of endogenous metabolites in various diseases is useful for searching diagnostic biomarkers and elucidating the molecular mechanisms of pathophysiology. The author and collaborators have developed some LC/tandem mass spectrometry (LC/MS/MS) methods for metabolites and applied them to disease-related samples. First, we identified urinary conjugated cholesterol metabolites and serum N-palmitoyl-O-phosphocholine serine as useful biomarkers for Niemann-Pick disease type C (NPC). For the purpose of intraoperative diagnosis of glioma patients, we developed the LC/MS/MS analysis methods for 2-hydroxyglutaric acid or cystine and found that they could be good differential biomarkers. For renal cell carcinoma, we searched for various biomarkers for early diagnosis, malignancy evaluation and recurrence prediction by global metabolome analysis and targeted LC/MS/MS analysis. In pathological analysis, we developed a simultaneous LC/MS/MS analysis method for 13 steroid hormones and applied it to NPC cells, we found 6 types of reductions in NPC model cells. For non-alcoholic steatohepatitis (NASH), model mice were prepared with special diet and plasma bile acids were measured, and as a result, hydrophilic bile acids were significantly increased. In addition, we developed an LC/MS/MS method for 17 sterols and analyzed liver cholesterol metabolites and found a decrease in phytosterols and cholesterol synthetic markers and an increase in non-enzymatic oxidative sterols in the pre-onset stage of NASH. We will continue to challenge themselves to add value to clinical practice based on cutting-edge analytical chemistry methodology.

Keywords:  LC/tandem mass spectrometry (LC/MS/MS); biomarker; identification; metabolite; pathological analysis; quantification

DOI:  https://doi.org/10.1248/bpb.b24-00073
J Mass Spectrom. 2024 Jul;59(7): e5042

Mass spectrometry imaging-based multi-omics approaches to understand drug metabolism and disposition.

Nav Raj Phulara, Herana Kamal Seneviratne.



Keywords:  drug metabolism and disposition; drugs; lipids; mass spectrometry imaging; proteins

DOI:  https://doi.org/10.1002/jms.5042
Biochimie. 2024 May 31. pii: S0300-9084(24)00125-1. [Epub ahead of print]225 156-167

Death and the desaturase: Implication of Stearoyl-CoA desaturase-1 in the mechanisms of cell stress, apoptosis, and ferroptosis.

R Ariel Igal.

Growth and proliferation of normal and cancerous cells necessitate a finely-tuned regulation of lipid metabolic pathways to ensure the timely supply of structural, energetic, and signaling lipid molecules. The synthesis and remodeling of lipids containing fatty acids with an appropriate carbon length and insaturation level are required for supporting each phase of the mechanisms of cell replication and survival. Mammalian Stearoyl-CoA desaturases (SCD), particularly SCD1, play a crucial role in modulating the fatty acid composition of cellular lipids, converting saturated fatty acids (SFA) into monounsaturated fatty acids (MUFA) in the endoplasmic reticulum (ER). Extensive research has elucidated in great detail the participation of SCD1 in the molecular mechanisms that govern cell replication in normal and cancer cells. More recently, investigations have shed new light on the functional and regulatory role of the Δ9-desaturase in the processes of cell stress and cell death. This review will examine the latest findings on the involvement of SCD1 in the molecular pathways of cell survival, particularly on the mechanisms of ER stress and autophagy, as well in apoptotic and non-apoptotic cell death.

DOI: https://doi.org/10.1016/j.biochi.2024.05.023
Elife. 2024 Jun 04. pii: e88956. [Epub ahead of print]13

Statistical and computational methods for integrating microbiome, host genomics, and metabolomics data.

Rebecca A Deek, Siyuan Ma, James Lewis, Hongzhe Li.

  Large-scale microbiome studies are progressively utilizing multiomics designs, which include the collection of microbiome samples together with host genomics and metabolomics data. Despite the increasing number of data sources, there remains a bottleneck in understanding the relationships between different data modalities due to the limited number of statistical and computational methods for analyzing such data. Furthermore, little is known about the portability of general methods to the metagenomic setting and few specialized techniques have been developed. In this review, we summarize and implement some of the commonly used methods. We apply these methods to real data sets where shotgun metagenomic sequencing and metabolomics data are available for microbiome multiomics data integration analysis. We compare results across methods, highlight strengths and limitations of each, and discuss areas where statistical and computational innovation is needed.

Keywords:  causal inference; computational biology; data integration; network analysis; systems biology

DOI:  https://doi.org/10.7554/eLife.88956
J Proteome Res. 2024 Jun 04.

Increasing Proteome Coverage Through a Reduction in Analyte Complexity in Single-Cell Equivalent Samples.

Marion Pang, Jeff J Jones, Ting-Yu Wang, Baiyi Quan, Nicole J Kubat, Yanping Qiu, Michael L Roukes, Tsui-Fen Chou.

  The advancement of sophisticated instrumentation in mass spectrometry has catalyzed an in-depth exploration of complex proteomes. This exploration necessitates a nuanced balance in experimental design, particularly between quantitative precision and the enumeration of analytes detected. In bottom-up proteomics, a key challenge is that oversampling of abundant proteins can adversely affect the identification of a diverse array of unique proteins. This issue is especially pronounced in samples with limited analytes, such as small tissue biopsies or single-cell samples. Methods such as depletion and fractionation are suboptimal to reduce oversampling in single cell samples, and other improvements on LC and mass spectrometry technologies and methods have been developed to address the trade-off between precision and enumeration. We demonstrate that by using a monosubstrate protease for proteomic analysis of single-cell equivalent digest samples, an improvement in quantitative accuracy can be achieved, while maintaining high proteome coverage established by trypsin. This improvement is particularly vital for the field of single-cell proteomics, where single-cell samples with limited number of protein copies, especially in the context of low-abundance proteins, can benefit from considering analyte complexity. Considerations about analyte complexity, alongside chromatographic complexity, integration with data acquisition methods, and other factors such as those involving enzyme kinetics, will be crucial in the design of future single-cell workflows.

Keywords:  bottom-up proteomics; peptide identification optimization; protease choice; single-cell proteomics

DOI:  https://doi.org/10.1021/acs.jproteome.4c00062
J Proteome Res. 2024 Jun 04.

Tidy-Direct-to-MS: An Open-Source Data-Processing Pipeline for Direct Mass Spectrometry-Based Metabolomics Experiments.

Christoph Bueschl, Gabriel Riquelme, Nicolás Zabalegui, Maximilian A Rey, María Eugenia Monge.

  Direct-to-Mass Spectrometry and ambient ionization techniques can be used for biochemical fingerprinting in a fast way. Data processing is typically accomplished with vendor-provided software tools. Here, a novel, open-source functionality, entitled Tidy-Direct-to-MS, was developed for data processing of direct-to-MS data sets. It allows for fast and user-friendly processing using different modules for optional sample position detection and separation, mass-to-charge ratio drift detection and correction, consensus spectra calculation, and bracketing across sample positions as well as feature abundance calculation. The tool also provides functionality for the automated comparison of different sets of parameters, thereby assisting the user in the complex task of finding an optimal combination to maximize the total number of detected features while also checking for the detection of user-provided reference features. In addition, Tidy-Direct-to-MS has the capability for data quality review and subsequent data analysis, thereby simplifying the workflow of untargeted ambient MS-based metabolomics studies. Tidy-Direct-to-MS is implemented in the Python programming language as part of the TidyMS library and can thus be easily extended. Capabilities of Tidy-Direct-to-MS are showcased in a data set acquired in a marine metabolomics study reported in MetaboLights (MTBLS1198) using a transmission mode Direct Analysis in Real Time-Mass Spectrometry (TM-DART-MS)-based method.

Keywords:  DART; TidyMS; data processing; mass spectrometry; metabolomics; quality control

DOI:  https://doi.org/10.1021/acs.jproteome.3c00784
Nat Metab. 2024 Jun 07.

Publisher Correction: METLIN-CCS Lipid Database: An authentic standards resource for lipid classification and identification.

Erin S Baker, Winnie Uritboonthai, Aries Aisporna, Corey Hoang, Heino M Heyman, Lisa Connell, Damien Olivier-Jimenez, Martin Giera, Gary Siuzdak.

DOI: https://doi.org/10.1038/s42255-024-01075-y
Proteomics. 2024 Jun;24(11): e2300062

Extracellular vesicle proteins as breast cancer biomarkers: Mass spectrometry-based analysis.

Raju Bandu, Jae Won Oh, Kwang Pyo Kim.

  Extracellular vesicles (EVs) are membrane-surrounded vesicles released by various cell types into the extracellular microenvironment. Although EVs vary in size, biological function, and components, their importance in cancer progression and the potential use of EV molecular species to serve as novel cancer biomarkers have become increasingly evident. Cancer cells actively release EVs into surrounding tissues, which play vital roles in cancer progression and metastasis, including invasion and immune modulation. EVs released by cancer cells are usually chosen as a gateway in the search for biomarkers for cancer. In this review, we mainly focused on molecular profiling of EV protein constituents from breast cancer, emphasizing mass spectrometry (MS)-based proteomic approaches. To further investigate the potential use of EVs as a source of breast cancer biomarkers, we have discussed the use of these proteins as predictive marker candidates. Besides, we have also summarized the key characteristics of EVs as potential therapeutic targets in breast cancer and provided significant information on their implications in breast cancer development and progression. Information provided in this review may help understand the recent progress in understanding EV biology and their potential role as new noninvasive biomarkers as well as emerging therapeutic opportunities and associated challenges.

Keywords:  biomarker; cancer; extracellular vesicles; mass spectrometry; proteins

DOI:  https://doi.org/10.1002/pmic.202300062
Rev Neurosci. 2024 Jun 07.

Metabolic dysregulation of tricarboxylic acid cycle and oxidative phosphorylation in glioblastoma.

Cristina Trejo-Solís, Norma Serrano-García, Rosa Angelica Castillo-Rodríguez, Diana Xochiquetzal Robledo-Cadena, Dolores Jimenez-Farfan, Álvaro Marín-Hernández, Daniela Silva-Adaya, Citlali Ekaterina Rodríguez-Pérez, Juan Carlos Gallardo-Pérez.

  Glioblastoma multiforme (GBM) exhibits genetic alterations that induce the deregulation of oncogenic pathways, thus promoting metabolic adaptation. The modulation of metabolic enzyme activities is necessary to generate nucleotides, amino acids, and fatty acids, which provide energy and metabolic intermediates essential for fulfilling the biosynthetic needs of glioma cells. Moreover, the TCA cycle produces intermediates that play important roles in the metabolism of glucose, fatty acids, or non-essential amino acids, and act as signaling molecules associated with the activation of oncogenic pathways, transcriptional changes, and epigenetic modifications. In this review, we aim to explore how dysregulated metabolic enzymes from the TCA cycle and oxidative phosphorylation, along with their metabolites, modulate both catabolic and anabolic metabolic pathways, as well as pro-oncogenic signaling pathways, transcriptional changes, and epigenetic modifications in GBM cells, contributing to the formation, survival, growth, and invasion of glioma cells. Additionally, we discuss promising therapeutic strategies targeting key players in metabolic regulation. Therefore, understanding metabolic reprogramming is necessary to fully comprehend the biology of malignant gliomas and significantly improve patient survival.

Keywords:  glioma; metabolism; oncogenic signaling pathways

DOI:  https://doi.org/10.1515/revneuro-2024-0054
J Am Soc Mass Spectrom. 2024 Jun 06.

Hyphenation of Liquid Chromatography and Trapped Ion Mobility - Mass Spectrometry for Characterization of Isomeric Phosphatidylethanolamines with Focus on N-Acylated Species.

Edward Rudt, Svenja Schneider, Heiko Hayen.

  In prior research, hydrophilic interaction liquid chromatography coupled to tandem mass spectrometry (HILIC-MS/MS) has demonstrated applicability for characterizing regioisomers in lipidomics studies, including phosphatidylglycerols (PG) and bis(monoacyl)glycerophosphates (BMP). However, there are other lipid regioisomers, such as phosphatidylethanolamines (PE) and lyso-N-acyl-PE (LNAPE), that have not been studied as extensively. Therefore, hyphenated mass spectrometric methods are needed to investigate PE and LNAPE regioisomers individually. The asymmetric structure of LNAPE favors isomeric species, which can result in coelution and chimeric MS/MS spectra. One way to address the challenge of chimeric MS/MS spectra is through mobility-resolved fragmentation using trapped ion mobility spectrometry (TIMS). Therefore, we developed a multidimensional HILIC-TIMS-MS/MS approach for the structural characterization of isomeric phosphatidylethanolamines in both negative and positive ionization modes. The study revealed the complementary fragmentation pattern and ion mobility behavior of LNAPE in both ionization modes, which was confirmed by a self-synthesized LNAPE standard. With this knowledge, a distinction of regioisomeric PE and LNAPE was achieved in human plasma samples. Furthermore, regioisomeric LNAPE species containing at least one unsaturated fatty acid were noted to exhibit a change in collision cross-section in positive ionization mode, leading to a lipid characterization with respect to fatty acyl positional level. Similar mobility behavior was also observed for the biological LNAPE precursor N-acyl-PE (NAPE). Application of this approach to plasma and cereal samples demonstrated its effectiveness in regioisomeric LNAPE and NAPE species' elucidation.

Keywords:  HILIC; LNAPE; NAPE; PASEF; TIMS; ion mobility; lipidomics; regioisomers

DOI:  https://doi.org/10.1021/jasms.4c00162
Discov Oncol. 2024 Jun 04. 15(1): 206

Role of lipid metabolism in hepatocellular carcinoma.

Yulin Cheng, Jun He, Bin Zuo, Yang He.

  Hepatocellular carcinoma (HCC), an aggressive malignancy with a dismal prognosis, poses a significant public health challenge. Recent research has highlighted the crucial role of lipid metabolism in HCC development, with enhanced lipid synthesis and uptake contributing to the rapid proliferation and tumorigenesis of cancer cells. Lipids, primarily synthesized and utilized in the liver, play a critical role in the pathological progression of various cancers, particularly HCC. Cancer cells undergo metabolic reprogramming, an essential adaptation to the tumor microenvironment (TME), with fatty acid metabolism emerging as a key player in this process. This review delves into intricate interplay between HCC and lipid metabolism, focusing on four key areas: de novo lipogenesis, fatty acid oxidation, dysregulated lipid metabolism of immune cells in the TME, and therapeutic strategies targeting fatty acid metabolism for HCC treatment.

Keywords:  De novo lipogenesis; Fatty acid oxidation; Hepatocellular carcinoma; Lipid metabolism; Therapeutic strategy; Tumor microenvironment

DOI:  https://doi.org/10.1007/s12672-024-01069-y
medRxiv. 2024 May 25. pii: 2024.05.24.24307903. [Epub ahead of print]

UnitedMet harnesses RNA-metabolite covariation to impute metabolite levels in clinical samples.

Amy X Xie, Wesley Tansey, Ed Reznik.

Comprehensively studying metabolism requires the measurement of metabolite levels. However, in contrast to the broad availability of gene expression data, metabolites are rarely measured in large molecularly-defined cohorts of tissue samples. To address this basic barrier to metabolic discovery, we propose a Bayesian framework ("UnitedMet") which leverages the empirical strength of RNA-metabolite covariation to impute otherwise unmeasured metabolite levels from widely available transcriptomic data. We demonstrate that UnitedMet is equally capable of imputing whole pool sizes as well as the outcomes of isotope tracing experiments. We apply UnitedMet to investigate the metabolic impact of driver mutations in kidney cancer, identifying a novel association between BAP1 and a highly oxidative tumor phenotype. We similarly apply UnitedMet to determine that advanced kidney cancers upregulate oxidative phosphorylation relative to early-stage disease, that oxidative metabolism in kidney cancer is associated with inferior outcomes to combination therapy, and that kidney cancer metastases themselves demonstrate elevated oxidative phosphorylation relative to primary tumors. UnitedMet therefore enables the assessment of metabolic phenotypes in contexts where metabolite measurements were not taken or are otherwise infeasible, opening new avenues for the generation and evaluation of metabolite-centered hypotheses. UnitedMet is open source and publicly available ( https://github.com/reznik-lab/UnitedMet ).

DOI: https://doi.org/10.1101/2024.05.24.24307903
Cell. 2024 May 30. pii: S0092-8674(24)00520-8. [Epub ahead of print]

De novo and salvage purine synthesis pathways across tissues and tumors.

Diem H Tran, Dohun Kim, Rushendhiran Kesavan, Harrison Brown, Trishna Dey, Mona Hoseini Soflaee, Hieu S Vu, Alpaslan Tasdogan, Jason Guo, Divya Bezwada, Houssam Al Saad, Feng Cai, Ashley Solmonson, Halie Rion, Rawand Chabatya, Salma Merchant, Nathan J Manales, Vanina T Tcheuyap, Megan Mulkey, Thomas P Mathews, James Brugarolas, Sean J Morrison, Hao Zhu, Ralph J DeBerardinis, Gerta Hoxhaj.

  Purine nucleotides are vital for RNA and DNA synthesis, signaling, metabolism, and energy homeostasis. To synthesize purines, cells use two principal routes: the de novo and salvage pathways. Traditionally, it is believed that proliferating cells predominantly rely on de novo synthesis, whereas differentiated tissues favor the salvage pathway. Unexpectedly, we find that adenine and inosine are the most effective circulating precursors for supplying purine nucleotides to tissues and tumors, while hypoxanthine is rapidly catabolized and poorly salvaged in vivo. Quantitative metabolic analysis demonstrates comparative contribution from de novo synthesis and salvage pathways in maintaining purine nucleotide pools in tumors. Notably, feeding mice nucleotides accelerates tumor growth, while inhibiting purine salvage slows down tumor progression, revealing a crucial role of the salvage pathway in tumor metabolism. These findings provide fundamental insights into how normal tissues and tumors maintain purine nucleotides and highlight the significance of purine salvage in cancer.

Keywords:  cancer metabolism; de novo purine synthesis; in vivo isotope tracing; nucleotide diet; nucleotide metabolism; purine bases; purine degradation; purine salvage; tissue; tumor growth

DOI:  https://doi.org/10.1016/j.cell.2024.05.011
J Am Soc Mass Spectrom. 2024 Jun 03.

ModiFinder: Tandem Mass Spectral Alignment Enables Structural Modification Site Localization.

Mohammad Reza Zare Shahneh, Michael Strobel, Giovanni Andrea Vitale, Christian Geibel, Yasin El Abiead, Neha Garg, Berenike Wagner, Karl Forchhammer, Allegra Aron, Vanessa V Phelan, Daniel Petras, Mingxun Wang.

Untargeted tandem mass spectrometry (MS/MS) has become a high-throughput method to measure small molecules in complex samples. One key goal is the transformation of these MS/MS spectra into chemical structures. Computational techniques such as MS/MS library search have enabled the reidentification of known compounds. Analog library search and molecular networking extend this identification to unknown compounds. While there have been advancements in metrics for the similarity of MS/MS spectra of structurally similar compounds, there is still a lack of automated methods to provide site specific information about structural modifications. Here we introduce ModiFinder which leverages the alignment of peaks in MS/MS spectra between structurally related known and unknown small molecules. Specifically, ModiFinder focuses on shifted MS/MS fragment peaks in the MS/MS alignment. These shifted peaks putatively represent substructures of the known molecule that contain the site of the modification. ModiFinder synthesizes this information together and scores the likelihood for each atom in the known molecule to be the modification site. We demonstrate in this manuscript how ModiFinder can effectively localize modifications which extends the capabilities of MS/MS analog searching and molecular networking to accelerate the discovery of novel compounds.

DOI: https://doi.org/10.1021/jasms.4c00061
bioRxiv. 2024 May 21. pii: 2024.05.16.594607. [Epub ahead of print]

iLipidome: enhancing statistical power and interpretability using hidden biosynthetic interdependencies in the lipidome.

Wen-Jen Lin, Austin W T Chiang, Evanston H Zhou, Chenguang Liang, Chia-Hsin Liu, Wen-Lung Ma, Wei-Chung Cheng, Nathan E Lewis.

Numerous biological processes and diseases are influenced by lipid composition. Advances in lipidomics are elucidating their roles, but analyzing and interpreting lipidomics data at the systems level remain challenging. To address this, we present iLipidome, a method for analyzing lipidomics data in the context of the lipid biosynthetic network, thus accounting for the interdependence of measured lipids. iLipidome enhances statistical power, enables reliable clustering and lipid enrichment analysis, and links lipidomic changes to their genetic origins. We applied iLipidome to investigate mechanisms driving changes in cellular lipidomes following supplementation of docosahexaenoic acid (DHA) and successfully identified the genetic causes of alterations. We further demonstrated how iLipidome can disclose enzyme-substrate specificity and pinpoint prospective glioblastoma therapeutic targets. Finally, iLipidome enabled us to explore underlying mechanisms of cardiovascular disease and could guide the discovery of early lipid biomarkers. Thus, iLipidome can assist researchers studying the essence of lipidomic data and advance the field of lipid biology.

DOI: https://doi.org/10.1101/2024.05.16.594607
Anal Chim Acta. 2024 Jul 11. pii: S0003-2670(24)00559-2. [Epub ahead of print]1312 342758

Exploring sample treatment strategies for untargeted metabolomics: A comparative study of solid phase microextraction (SPME) and homogenization with solid-liquid extraction (SLE) in renal tissue.

Paula Cuevas-Delgado, Natalia Warmuzińska, Kamil Łuczykowski, Barbara Bojko, Coral Barbas.

  BACKGROUND: The selection of the sample treatment strategy is a crucial step in the metabolomics workflow. Solid phase microextraction (SPME) is a sample processing methodology with great potential for use in untargeted metabolomics of tissue samples. However, its utilization is not as widespread as other standard protocols involving steps of tissue collection, metabolism quenching, homogenization, and extraction of metabolites by solvents. Since SPME allows us to perform all these steps in one action in tissue samples, in addition to other advantages, it is necessary to know whether this methodology produces similar or comparable metabolome and lipidome coverage and performance to classical methods.RESULTS: SPME and homogenization with solid-liquid extraction (Homo-SLE) sample treatment methods were applied to healthy murine kidney tissue, followed by comprehensive metabolomics and lipidomics analyses. In addition, it has been tested whether freezing and storage of the tissue causes alterations in the renal metabolome and lipidome, so the analyses were performed on fresh and frozen tissue samples Lipidomics analysis revealed the exclusive presence of different structural membrane and intracellular lipids in the Homo-SLE group. Conversely, all annotated metabolites were detected in both groups. Notably, the freezing of the sample mainly causes a decrease in the levels of most lipid species and an increase in metabolites such as amino acids, purines, and pyrimidines. These alterations are principally detected in a statistically significant way by SPME methodology. Finally, the samples of both methodologies show a positive correlation in all the analyses.
SIGNIFICANCE: These results demonstrate that in SPME processing, as long as the fundamentals of non-exhaustive extraction in a pre-equilibrium kinetic regime, extraction in a tissue localized area, the chemistry of the fiber coating and non-homogenization of the tissue are taken into account, is an excellent method to use in kidney tissue metabolomics; since this methodology presents an easy-to-use, efficient, and less invasive approach that simplifies the different sample processing steps.

Keywords:  Kidney; Lipidomics; SPME; Sample processing; Storage; Tissue freezing

DOI:  https://doi.org/10.1016/j.aca.2024.342758
Anal Chem. 2024 Jun 07.

Targeted Quantification of Glutathione/Arginine Redox Metabolism Based on a Novel Paired Mass Spectrometry Probe Approach for the Functional Assessment of Redox Status.

Zhu-Jun Zhong, Jing Ling, Zhong-Ping Yao, Li-Fang Liu, Jia-Yi Zheng, Gui-Zhong Xin.

Glutathione (GSH) redox control and arginine metabolism are critical in regulating the physiological response to injury and oxidative stress. Quantification assessment of the GSH/arginine redox metabolism supports monitoring metabolic pathway shifts during pathological processes and their linkages to redox regulation. However, assessing the redox status of organisms with complex matrices is challenging, and single redox molecule analysis may not be accurate for interrogating the redox status in cells and in vivo. Herein, guided by a paired derivatization strategy, we present a new ultraperformance liquid chromatography tandem mass spectrometry (UPLC-MS/MS)-based approach for the functional assessment of biological redox status. Two structurally analogous probes, 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) and newly synthesized 2-methyl-6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (MeAQC), were set for paired derivatization. The developed approach was successfully applied to LPS-stimulated RAW 264.7 cells and HDM-induced asthma mice to obtain quantitative information on GSH/arginine redox metabolism. The results suggest that the redox status was remarkably altered upon LPS and HDM stimulation. We expect that this approach will be of good use in a clinical biomarker assay and potential drug screening associated with redox metabolism, oxidative damage, and redox signaling.

DOI: https://doi.org/10.1021/acs.analchem.4c00732
Redox Biol. 2024 Jun 04. pii: S2213-2317(24)00200-3. [Epub ahead of print]73 103222

Deciphering pathophysiological mechanisms underlying cystathionine beta-synthase-deficient homocystinuria using targeted metabolomics, liver proteomics, sphingolipidomics and analysis of mitochondrial function.

Tomas Majtan, Thomas Olsen, Jitka Sokolova, Jakub Krijt, Michaela Křížková, Tomoaki Ida, Tamás Ditrói, Hana Hansikova, Ondrej Vit, Jiri Petrak, Ladislav Kuchař, Warren D Kruger, Péter Nagy, Takaaki Akaike, Viktor Kožich.

  BACKGROUND: Cystathionine β-synthase (CBS)-deficient homocystinuria (HCU) is an inherited disorder of sulfur amino acid metabolism with varying severity and organ complications, and a limited knowledge about underlying pathophysiological processes. Here we aimed at getting an in-depth insight into disease mechanisms using a transgenic mouse model of HCU (I278T).METHODS: We assessed metabolic, proteomic and sphingolipidomic changes, and mitochondrial function in tissues and body fluids of I278T mice and WT controls. Furthermore, we evaluated the efficacy of methionine-restricted diet (MRD) in I278T mice.
RESULTS: In WT mice, we observed a distinct tissue/body fluid compartmentalization of metabolites with up to six-orders of magnitude differences in concentrations among various organs. The I278T mice exhibited the anticipated metabolic imbalance with signs of an increased production of hydrogen sulfide and disturbed persulfidation of free aminothiols. HCU resulted in a significant dysregulation of liver proteome affecting biological oxidations, conjugation of compounds, and metabolism of amino acids, vitamins, cofactors and lipids. Liver sphingolipidomics indicated upregulation of the pro-proliferative sphingosine-1-phosphate signaling pathway. Liver mitochondrial function of HCU mice did not seem to be impaired compared to controls. MRD in I278T mice improved metabolic balance in all tissues and substantially reduced dysregulation of liver proteome.
CONCLUSION: The study highlights distinct tissue compartmentalization of sulfur-related metabolites in normal mice, extensive metabolome, proteome and sphingolipidome disruptions in I278T mice, and the efficacy of MRD to alleviate some of the HCU-related biochemical abnormalities.

Keywords:  Cystathionine beta-synthase; Homocystinuria; Metabolomics; Methionine restriction; Proteomics

DOI:  https://doi.org/10.1016/j.redox.2024.103222