bims-mascan 2023-11-12 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2023‒11‒12
twenty-one papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh

Q-RAI data-independent acquisition for lipidomic quantitative profiling.
Introducing untargeted data-independent acquisition for metaproteomics of complex microbial samples.
Mobility-Modulated Sequential Dissociation Analysis Enables Structural Lipidomics in Mass Spectrometry Imaging.
Decoding the molecular interplay in the central dogma: An overview of mass spectrometry-based methods to investigate protein-metabolite interactions.
Automated Identification of Modified Nucleosides during HRAM-LC-MS/MS using a Metabolomics ID Workflow with Neutral Loss Detection.
Automated Composition Assessment of Natural Extracts: Untargeted Mass Spectrometry-Based Metabolite Profiling Integrating Semiquantitative Detection.
LC-MS/MS method for quantitative profiling of ketone bodies, α-keto acids, lactate, pyruvate and their stable isotopically labelled tracers in human plasma: An analytical panel for clinical metabolic kinetics and interactions.
Determination of vitamin D metabolites in various biological samples through an improved chemical derivatization assisted liquid chromatography-tandem mass spectrometry approach.
Comprehensive Profiling of Amine-Containing Metabolite Isomers with Chiral Phosphorus Reagents.
Lipidomic analysis of Porphyromonas gingivalis reveals novel glycerol bisphosphoceramide, phosphatidyl- and phosphoglycerol dipeptide lipid families.
An In Silico Database for Automated Feature Identification of High-Resolution Tandem Mass Spectrometry 13C-Trimethylation Enhancement Using Diazomethane (13C-TrEnDi)-Modified Lipid Data.
A Guide to Ferroptosis, the biological rust of cellular membranes.
Regulatory mechanisms of one-carbon metabolism enzymes.
SREBF1/SREBP-1 concurrently regulates lipid synthesis and lipophagy to maintain lipid homeostasis and tumor growth.
Diazo-carboxyl Click Derivatization Enables Sensitive Analysis of Carboxylic Acid Metabolites in Biosamples.
Metabolomics 2022 workshop report: state of QA/QC best practices in LC-MS-based untargeted metabolomics, informed through mQACC community engagement initiatives.
Vitamin B5 supports MYC oncogenic metabolism and tumor progression in breast cancer.
Deuterated water as a substrate-agnostic isotope tracer for investigating reversibility and thermodynamics of reactions in central carbon metabolism.
Targeted quantitative lipidomic uncovers lipid biomarkers for predicting the presence of compensated cirrhosis and discriminating decompensated cirrhosis from compensated cirrhosis.
Pitfalls in RNA Modification Quantification Using Nucleoside Mass Spectrometry.
Application of liquid-liquid extraction for N-terminal myristoylation proteomics.

Sci Rep. 2023 11 07. 13(1): 19281

Q-RAI data-independent acquisition for lipidomic quantitative profiling.

Jing Kai Chang, Guoshou Teo, Yael Pewzner-Jung, Daniel J Cuthbertson, Anthony H Futerman, Markus R Wenk, Hyungwon Choi, Federico Torta.

Untargeted lipidomics has been increasingly adopted for hypothesis generation in a biological context or discovery of disease biomarkers. Most of the current liquid chromatography mass spectrometry (LC-MS) based untargeted methodologies utilize a data dependent acquisition (DDA) approach in pooled samples for identification and MS-only acquisition for semi-quantification in individual samples. In this study, we present for the first time an untargeted lipidomic workflow that makes use of the newly implemented Quadrupole Resolved All-Ions (Q-RAI) acquisition function on the Agilent 6546 quadrupole time-of-flight (Q-TOF) mass spectrometer to acquire MS2 spectra in data independent acquisition (DIA) mode. This is followed by data processing and analysis on MetaboKit, a software enabling DDA-based spectral library construction and extraction of MS1 and MS2 peak areas, for reproducible identification and quantification of lipids in DIA analysis. This workflow was tested on lipid extracts from human plasma and showed quantification at MS1 and MS2 levels comparable to multiple reaction monitoring (MRM) targeted analysis of the same samples. Analysis of serum from Ceramide Synthase 2 (CerS2) null mice using the Q-RAI DIA workflow identified 88 lipid species significantly different between CerS2 null and wild type mice, including well-characterized changes previously associated with this phenotype. Our results show the Q-RAI DIA as a reliable option to perform simultaneous identification and reproducible relative quantification of lipids in exploratory biological studies.

DOI: https://doi.org/10.1038/s41598-023-46312-8
ISME Commun. 2022 Jun 29. 2(1): 51

Introducing untargeted data-independent acquisition for metaproteomics of complex microbial samples.

Sami Pietilä, Tomi Suomi, Laura L Elo.

Mass spectrometry-based metaproteomics is a relatively new field of research that enables the characterization of the functionality of microbiota. Recently, we demonstrated the applicability of data-independent acquisition (DIA) mass spectrometry to the analysis of complex metaproteomic samples. This allowed us to circumvent many of the drawbacks of the previously used data-dependent acquisition (DDA) mass spectrometry, mainly the limited reproducibility when analyzing samples with complex microbial composition. However, the DDA-assisted DIA approach still required additional DDA data on the samples to assist the analysis. Here, we introduce, for the first time, an untargeted DIA metaproteomics tool that does not require any DDA data, but instead generates a pseudospectral library directly from the DIA data. This reduces the amount of required mass spectrometry data to a single DIA run per sample. The new DIA-only metaproteomics approach is implemented as a new open-source software package named glaDIAtor, including a modern web-based graphical user interface to facilitate wide use of the tool by the community.

DOI: https://doi.org/10.1038/s43705-022-00137-0
Angew Chem Int Ed Engl. 2023 Nov 09. e202312275

Mobility-Modulated Sequential Dissociation Analysis Enables Structural Lipidomics in Mass Spectrometry Imaging.

Yao Qian, Xiangyu Guo, Yunfang Wang, Zheng Ouyang, Xiaoxiao Ma.

  Spatial lipidomics based on mass spectrometry imaging (MSI) is a powerful tool for fundamental biology studies and biomarker discovery. But the structure-resolving capability of MSI is limited because of the lack of multiplexed tandem mass spectrometry (MS/MS) method, primarily due to the small sample amount available from each pixel and the poor ion usage in MS/MS analysis. Here, we report a mobility-modulated sequential dissociation (MMSD) strategy for multiplex MS/MS imaging of distinct lipids from biological tissues. With ion mobility-enabled data-independent acquisition and automated spectrum deconvolution, MS/MS spectra of a large number of lipid species from each tissue pixel are acquired, at no expense of imaging speed. MMSD imaging is highlighted by MS/MS imaging of 24 structurally distinct lipids in the mouse brain and the revealing of the correlation of a structurally distinct phosphatidylethanolamine isomer (PE 18:1_18:1) from a human hepatocellular carcinoma (HCC) tissue. Mapping of structurally distinct lipid isomers is now enabled and spatial lipidomics becomes feasible for MSI.

Keywords:  mass spectrometry, structural analysis, lipidomics, ion mobility, molecular fragmentation

DOI:  https://doi.org/10.1002/anie.202312275
Proteomics. 2023 Nov 06. e2200533

Decoding the molecular interplay in the central dogma: An overview of mass spectrometry-based methods to investigate protein-metabolite interactions.

Paolo Stincone, Amira Naimi, Anthony J Saviola, Raphael Reher, Daniel Petras.

  With the emergence of next-generation nucleotide sequencing and mass spectrometry-based proteomics and metabolomics tools, we have comprehensive and scalable methods to analyze the genes, transcripts, proteins, and metabolites of a multitude of biological systems. Despite the fascinating new molecular insights at the genome, transcriptome, proteome and metabolome scale, we are still far from fully understanding cellular organization, cell cycles and biology at the molecular level. Significant advances in sensitivity and depth for both sequencing as well as mass spectrometry-based methods allow the analysis at the single cell and single molecule level. At the same time, new tools are emerging that enable the investigation of molecular interactions throughout the central dogma of molecular biology. In this review, we provide an overview of established and recently developed mass spectrometry-based tools to probe metabolite-protein interactions-from individual interaction pairs to interactions at the proteome-metabolome scale. This article is protected by copyright. All rights reserved.

Keywords:  Mass Spectrometry; Metabolite-Protein interaction; Metabolomics; Proteomics; Target ID

DOI:  https://doi.org/10.1002/pmic.202200533
J Am Soc Mass Spectrom. 2023 Nov 10.

Automated Identification of Modified Nucleosides during HRAM-LC-MS/MS using a Metabolomics ID Workflow with Neutral Loss Detection.

Robert L Ross, Ningxi Yu, Ruoxia Zhao, Andrew Wood, Patrick A Limbach.

The role of post-transcriptional modification in biological processes has been an ongoing field of study for several decades. Improvements in liquid chromatography platforms and mass spectrometry instrumentation have resulted in the enhanced identification, characterization, and quantification of modified nucleosides in biological systems. One consequence of the rapid technological improvements in the analytical acquisition of modified nucleosides has been a dearth of robust data processing workflows for analyzing more than a handful of samples at a time. To improve the utility of LC-MS/MS for batch analyses of modified nucleosides, a workflow for automated nucleoside identification has been developed. We adapted the Thermo Fisher Scientific metabolomics identification software package, Compound Discoverer, to accurately identify modified nucleosides from batch LC-MS/MS acquisitions. Three points of identification are used: accurate mass from a monoisotopic mass list, spectral matching from a spectral library, and neutral loss identification. This workflow was applied to a batch (n = 24) of urinary nucleosides, resulting in the accurate identification and relative quantification of 16 known nucleosides in less than 1 h.

DOI: https://doi.org/10.1021/jasms.3c00298
J Agric Food Chem. 2023 Nov 10.

Automated Composition Assessment of Natural Extracts: Untargeted Mass Spectrometry-Based Metabolite Profiling Integrating Semiquantitative Detection.

Adriano Rutz, Jean-Luc Wolfender.

  Recent developments in mass spectrometry-based metabolite profiling allow unprecedented qualitative coverage of complex biological extract composition. However, the electrospray ionization used in metabolite profiling generates multiple artifactual signals for a single analyte. This leads to thousands of signals per analysis without satisfactory means of filtering those corresponding to abundant constituents. Generic approaches are therefore needed for the qualitative and quantitative annotation of a broad range of relevant constituents. For this, we used an analytical platform combining liquid chromatography-mass spectrometry (LC-MS) with Charged Aerosol Detection (CAD). We established a generic metabolite profiling for the concomitant recording of qualitative MS data and semiquantitative CAD profiles. The MS features (recorded in high-resolution tandem MS) are grouped and annotated using state-of-the-art tools. To efficiently attribute features to their corresponding extracted and integrated CAD peaks, a custom signal pretreatment and peak-shape comparison workflow is built. This strategy allows us to automatically contextualize features at both major and minor metabolome levels, together with a detailed reporting of their annotation including relevant orthogonal information (taxonomy, retention time). Signals not attributed to CAD peaks are considered minor metabolites. Results are illustrated on an ethanolic extract of Swertia chirayita (Roxb.) H. Karst., a bitter plant of industrial interest, exhibiting the typical complexity of plant extracts as a proof of concept. This generic qualitative and quantitative approach paves the way to automatically assess the composition of single natural extracts of interest or broader collections, thus facilitating new ingredient registrations or natural-extracts-based drug discovery campaigns.

Keywords:  Charged Aerosol Detection; automated composition assessment; liquid chromatography–mass spectrometry; metabolite profiling; natural extract

DOI:  https://doi.org/10.1021/acs.jafc.3c03099
J Chromatogr B Analyt Technol Biomed Life Sci. 2023 Oct 31. pii: S1570-0232(23)00316-1. [Epub ahead of print]1230 123906

LC-MS/MS method for quantitative profiling of ketone bodies, α-keto acids, lactate, pyruvate and their stable isotopically labelled tracers in human plasma: An analytical panel for clinical metabolic kinetics and interactions.

Minoo Afshar, Gerrit van Hall.

  An important area within clinical research is in vivo metabolism of ketone bodies (β-hydroxybutyrate and acetoacetate) and in connection metabolites that may affect their production and/or cellular transport such as the keto-acids from the branched-chain amino acids, lactate and pyruvate. To determine in vivo metabolite turnover, availability of accurate and sensitive methods for analyzing the plasma concentrations of these metabolites and their stable isotopically labeled enrichments is mandatory. Therefore, the present study describes a high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for simultaneous analysis of ketone bodies, α-keto acids, lactate, pyruvate, and their tracer enrichments in humans using 2 different derivatization techniques with 4-bromo-N-methylbenzylamine and O-benzylhydroxylamine as derivatization reagents, and 1-ethyl-3-dimethylaminopropyl carbodiimide as coupling compound followed by a single LC-MS/MS run. The method was validated for matrix effects, linearity, accuracy, precision, recovery, stability, and enrichment (ratio) analysis of a stable isotopically labelled analytes (tracers) continuously infused in humans divided by the unlabeled endogenous analyte (tracee) that makes it possible to quantify the analyte in vivo synthesis and degradation rates. The applied parallel derivatization procedure yielded good sensitivity for all analytes of interest and their tracers. Despite the double derivatization method, mixing the ethyl acetate portions at the final stage made it possible to simultaneously analyze all compounds in a single LC-MS/MS run. Moreover, the liquid chromatography method was optimized to robustly quantify the keto acids derived from leucine (α-keto-isocaproic acid) and isoleucine (α-keto-β-methylvaleric acid), the compounds with similar chemical structure and identical molecular weights. The presented method is designed and validated for human plasma. However, care should be taken in blood sampling and processing procedures as well as quick freezing and storage at -80 °C due to the instability of especially acetoacetate.

Keywords:  Acetoacetate; LC-MS/MS; Lactate; Plasma; Pyruvate; Tracer enrichment; α-keto acids; β-hydroxybutyrate

DOI:  https://doi.org/10.1016/j.jchromb.2023.123906
Anal Methods. 2023 Nov 06.

Determination of vitamin D metabolites in various biological samples through an improved chemical derivatization assisted liquid chromatography-tandem mass spectrometry approach.

Qin-Feng Zhang, Hua-Ming Xiao, Na An, Quan-Fei Zhu, Yu-Qi Feng.

Vitamin D (VD) metabolites are involved in a variety of important metabolic processes and physiological effects in organisms. Profiling of VD metabolites favors a deep understanding of the physiological role of VD. However, VD metabolites are difficult to detect due to their high chemical structural rigidity, structural similarity, and low sensitivities under liquid chromatography-tandem mass spectrometry (LC-MS). Herein, we present a chemical derivatization assisted LC-MS/MS strategy for the detection of VDs, in which 4-phenyl-1,2,4-triazoline-3,5-dione (PTAD) is employed to derivatize the conjugated diene of VD metabolites and provides sensitizing reporters for MS detection. After PTAD derivatization, the sensitivities of seven VD metabolites increased by 24-276 folds, with the limits of detection ranging from 3 to 20 pg mL-1. Using this method, we achieved a sensitive and accurate quantification of 7 VD metabolites (vitamin D2, vitamin D3, 25-hydroxyvitamin D2, 25-hydroxyvitamin D3, 1,25-dihydroxyvitamin D2, 1,25-dihydroxyvitamin D3, and 1,24,25-trihydroxyvitamin D3) of the VD metabolic pathway in different trace biological samples, including human serum, mouse tissues (namely liver, kidney, lung, and spleen), and cells. We believe that the present method can provide a promising tool for an in-depth analysis of VD metabolism.

DOI: https://doi.org/10.1039/d3ay01769a
Anal Chem. 2023 Nov 09.

Comprehensive Profiling of Amine-Containing Metabolite Isomers with Chiral Phosphorus Reagents.

Xingxing Liu, Yifan Wu, Lei Guo, Xiaoyu Wang, Changkai Shan, Yaru Liu, Hanxiang An, Xinmei Kang, Rong Ding, Zongwei Cai, Jiyang Dong, Yufen Zhao, Xiang Gao.

Metabolite isomers play diverse and crucial roles in various metabolic processes. However, in untargeted metabolomics analysis, it remains a great challenge to distinguish between the constitutional isomers and enantiomers of amine-containing metabolites due to their similar chemical structures and physicochemical properties. In this work, the triplex stable isotope N-phosphoryl amino acids labeling (SIPAL) is developed to identify and relatively quantify the amine-containing metabolites and their isomers by using chiral phosphorus reagents coupled with high-resolution tandem mass spectroscopy. The constitutional isomers could be effectively distinguished with stereo isomers by using the diagnosis ions in MS/MS spectra. The in-house software MS-Isomerism has been parallelly developed for high-throughput screening and quantification. The proposed strategy enables the unbiased detection and relative quantification of isomers of amine-containing metabolites. Based on the characteristic triplet peaks with SIPAL tags, a total of 854 feature peaks with 154 isomer groups are successfully recognized as amine-containing metabolites in liver cells, in which 37 amine-containing metabolites, including amino acids, polyamines, and small peptides, are found to be significantly different between liver cancer cells and normal cells. Notably, it is the first time to identify S-acetyl-glutathione as an endogenous metabolite in liver cells. The SIPAL strategy could provide spectacular insight into the chemical structures and biological functions of the fascinating amine-containing metabolite isomers. The feasibility of SIPAL in isomeric metabolomics analysis may reach a deeper understanding of the mirror-chemistry in life and further advance the discovery of novel biomarkers for disease diagnosis.

DOI: https://doi.org/10.1021/acs.analchem.3c02325
J Lipid Res. 2023 Nov 02. pii: S0022-2275(23)00143-8. [Epub ahead of print] 100470

Lipidomic analysis of Porphyromonas gingivalis reveals novel glycerol bisphosphoceramide, phosphatidyl- and phosphoglycerol dipeptide lipid families.

Brian A Kleiboeker, Cheryl Frankfater, Mary E Davey, Fong-Fu Hsu.

  Porphyromonas gingivalis, like other members of the phylum Bacteroidetes (synonym Bacteroidota), synthesizes several classes of dihydroceramides and peptidolipids. Using a similar strategy as that recently used to delimit the lipidome of its close relative Bacteroides fragilis, we applied linear ion-trap (LIT) multiple-stage mass spectrometry (LIT MSn) with high resolution mass spectrometry (HRMS), to structurally characterize the complete lipidome of P. gingivalis and compare it to B. fragilis. This analysis discovered that the P. gingivalis lipidome consists of several previously unidentified lipid families including dihydroceramide-1-phosphophate (DHC-1-P), acylated DHC-1-P, phosphoglycerol glycylserine lipid (PG-GS), and bis(phosphodihydroceramide) glycerol (DHC-PGP-DHC). Interestingly, we also found a novel sphingolipid family containing a polyunsaturated long-chain base (LCB), and a new lipoglycylserine phosphatic acid (GS-PA) containing unsaturated acyl chains not reported for the lipid family. The comprehensive coverage of the lipidome of P. gingivalis provided in this study has revealed more than 140 lipid species in over 20 lipid families/subfamilies.

Keywords:  bacterial lipids; bisphosphorylceramide glycerol; lipidomics; peptidolipids; sphingolipids; tandem mass spectrometry

DOI:  https://doi.org/10.1016/j.jlr.2023.100470
J Am Soc Mass Spectrom. 2023 Nov 06.

An In Silico Database for Automated Feature Identification of High-Resolution Tandem Mass Spectrometry 13C-Trimethylation Enhancement Using Diazomethane (13C-TrEnDi)-Modified Lipid Data.

Joshua A Roberts, Christian A Rosales, Karl V Wasslen, Angela S Radnoff, Elena Godbout, Jean-Simon Diallo, Jeffrey M Manthorpe, Jeffrey C Smith.

  13C-Trimethylation enhancement using diazomethane (13C-TrEnDi) is a chemical derivatization technique that uses 13C-labeled diazomethane to increase mass spectrometry (MS) signal intensities for phosphatidylcholine (PC) and phosphatidylethanolamine (PE) lipid classes, both of which are of major interest in biochemistry. In silico mass spectrometry databases have become mainstays in lipidomics experiments; however, 13C-TrEnDi-modified PC and PE species have altered m/z and fragmentation patterns from their native counterparts. To build a database of 13C-TrEnDi-modified PC and PE species, a lipid extract from nutritional yeast was derivatized and fragmentation spectra of modified PC and PE species were mined using diagnostic fragmentation filtering by searching 13C-TrEnDi-modified headgroups with m/z 199 (PC) and 202 (PE). Identities of 25 PC and 10 PE species were assigned after comparing to predicted masses from the Lipid Maps Structure Database with no false positive identifications observed; neutral lipids could still be annotated after derivatization. Collision energies from 16 to 52 eV were examined, resulting in three additional class-specific fragment ions emerging, as well as a combined sn-1/sn-2 fragment ion, allowing sum-composition level annotations to be assigned. Using the Lipid Blast templates, a NIST-compatible 13C-TrEnDi database was produced based on fragmentation spectra observed at 36 eV and tested on HEK 293T cell lipid extracts, identifying 47 PC and 24 PE species, representing a 1.8-fold and 2.2-fold increase in annotations, respectively. The 13C-TrEnDi database is freely available, MS vendor-independent, and widely compatible with MS data processing pipelines, increasing the throughput and accessibility of TrEnDi for lipidomics applications.

Keywords:  TrEnDi; database; diazomethane; glycerophospholipids; lipidomics; lipids; mass spectrometry

DOI:  https://doi.org/10.1021/jasms.3c00273
FEBS J. 2023 Nov 07.

A Guide to Ferroptosis, the biological rust of cellular membranes.

Geraldine Veeckmans, Emily Van San, Tom Vanden Berghe.

  Unprotected iron can rust due to oxygen exposure. Similarly, in our body, oxidative stress can kill cells in an iron-dependent manner, which can give rise to devastating diseases. This type of cell death is referred to as ferroptosis. Generally, ferroptosis is defined as an iron-catalyzed form of regulated necrosis that occurs through excessive peroxidation of polyunsaturated fatty acids within cellular membranes. This review summarizes how ferroptosis is executed by a rather primitive biochemical process, under tight regulation of lipid, iron, and redox metabolic processes. An overview is given of major classes of ferroptosis inducers and inhibitors, and how to detect ferroptosis. Finally, its detrimental role in disease is briefly discussed.

Keywords:  FSP1; Ferroptosis; GPX4; iron; lipid; lipid peroxidation; metabolism; radical trapping antioxidant; redox

DOI:  https://doi.org/10.1111/febs.16993
J Biol Chem. 2023 Nov 08. pii: S0021-9258(23)02485-7. [Epub ahead of print] 105457

Regulatory mechanisms of one-carbon metabolism enzymes.

Boryana Petrova, Adam G Maynard, Peng Wang, Naama Kanarek.

  One-carbon metabolism is a central metabolic pathway critical for the biosynthesis of several amino acids, methyl group donors, and nucleotides. The pathway mostly relies on the transfer of a carbon unit from the amino acid serine, through the cofactor folate (in its several forms), and to the ultimate carbon acceptors that include nucleotides and methyl groups used for methylation of proteins, RNA, and DNA. Nucleotides are required for DNA replication, DNA repair, gene expression, and protein translation, through ribosomal RNA. Therefore, the one-carbon metabolism pathway is essential for cell growth and function in all cells, but is specifically important for rapidly proliferating cells. The regulation of one-carbon metabolism is a critical aspect of the normal and pathological function of the pathway, such as in cancer, where hijacking these regulatory mechanisms feeds an increased need for nucleotides. One-carbon metabolism is regulated at several levels: via gene expression, posttranslational modification, sub-cellular compartmentalization, allosteric inhibition, and feedback regulation. In this review we aim to inform the readers of relevant one-carbon metabolism regulation mechanisms, and to bring forward the need to further study this aspect of one-carbon metabolism. The review aims to integrate two major aspects of cancer metabolism - signaling downstream of nutrient sensing, and one-carbon metabolism, because while each of these is critical for the proliferation of cancerous cells, their integration is critical for comprehensive understating of cellular metabolism in transformed cells and can lead to clinically-relevant insights.

Keywords:  allosteric inhibition; cancer metabolism; metabolic adaptation; metabolic compartmentalization; post-translational modifications; transcriptional regulation

DOI:  https://doi.org/10.1016/j.jbc.2023.105457
Autophagy. 2023 Nov 05. 1-3

SREBF1/SREBP-1 concurrently regulates lipid synthesis and lipophagy to maintain lipid homeostasis and tumor growth.

Feng Geng, Deliang Guo.

  Cholesterol is an essential structural component of the cell membrane, whereas excess cholesterol can be toxic and thus is stored in intracellular lipid droplets (LDs). Malignant tumor cells grow rapidly and require abundant cholesterol to build new membranes. How they maintain cholesterol homeostasis is largely unknown. We recently revealed that SREBF1/SREBP-1 (sterol regulatory element binding transcription factor 1), a key lipogenic transcription factor, plays a critical role in maintaining cholesterol homeostasis in tumor cells. We found that in addition to activation of de novo lipid synthesis and cholesterol uptake, SREBF1 also upregulates macroautophagy/autophagy to hydrolyze LDs, and increases the expression of NPC2, a lysosome cholesterol transporter, actively mobilizing LD-stored cholesterol and fatty acids to promote tumor growth. Our study demonstrates that SREBF1 controls the balance of lipid synthesis, uptake, storage and liberation to maintain lipid homeostasis for rapid tumor growth, while suggesting it as a very promising molecular target for cancer treatment.

Keywords:  Autophagy; cancer; cholesterol; glioblastoma; lipid droplets; lipophagy

DOI:  https://doi.org/10.1080/15548627.2023.2275501
Anal Chem. 2023 Nov 09.

Diazo-carboxyl Click Derivatization Enables Sensitive Analysis of Carboxylic Acid Metabolites in Biosamples.

Cong Li, Kunlun Cheng, Qijin Zhao, Li Jin, Xuelian Wang, Tongling Liufu, Xutong Zhao, Xiaochuan Li, Xiao Wang, Jia Lyu, Dong Huang, Pingping Li, Xiao-Wei Chen, Zhaoxia Wang, Xinli Hu, Li Quan, Zhixing Chen.

Carboxylic acids are central metabolites in bioenergetics, signal transduction, and post-translation protein regulation. However, the quantitative analysis of carboxylic acids as an indispensable part of metabolomics is prohibitively challenging, particularly in trace amounts of biosamples. Here we report a diazo-carboxyl/hydroxylamine-ketone double click derivatization method for the sensitive analysis of hydrophilic, low-molecular-weight carboxylic acids. In general, our method renders a 5- to 2000-fold higher response in mass spectrometry along with improved chromatographic separation. With this method, we presented the near-single-cell analysis of carboxylic acid metabolites in 10 mouse egg cells before and after fertilization. Malate, fumarate, and β-hydroxybutyrate were found to decrease after fertilization. We also monitored the isotope labeling kinetics of carboxylic acids inside adherent cells cultured in 96-well plates during drug treatment. Finally, we applied this method to plasma or serum samples (5 μL) collected from mice and humans under pathological and physiological conditions. The double click derivatization method paves a way toward single-cell metabolomics and bedside diagnostics.

DOI: https://doi.org/10.1021/acs.analchem.3c03277
Metabolomics. 2023 Nov 08. 19(11): 93

Metabolomics 2022 workshop report: state of QA/QC best practices in LC-MS-based untargeted metabolomics, informed through mQACC community engagement initiatives.

Metabolomics Quality Assurance and Quality Control Consortium (mQACC)

  INTRODUCTION: The Metabolomics Quality Assurance and Quality Control Consortium (mQACC) organized a workshop during the Metabolomics 2022 conference.OBJECTIVES: The goal of the workshop was to disseminate recent findings from mQACC community-engagement efforts and to solicit feedback about a living guidance document of QA/QC best practices for untargeted LC-MS metabolomics.
METHODS: Four QC-related topics were presented.
RESULTS: During the discussion, participants expressed the need for detailed guidance on a broad range of QA/QC-related topics accompanied by use-cases.
CONCLUSIONS: Ongoing efforts will continue to identify, catalog, harmonize, and disseminate QA/QC best practices, including outreach activities, to establish and continually update QA/QC guidelines.

Keywords:  Analytical batch; Blanks; Internal standards; Liquid chromatography–mass spectrometry (LC–MS); Metabolomics; Quality control (QC) samples; System suitability testing (SST)

DOI:  https://doi.org/10.1007/s11306-023-02060-4
Nat Metab. 2023 Nov 09.

Vitamin B5 supports MYC oncogenic metabolism and tumor progression in breast cancer.

CRUK Rosetta Grand Challenge Consortium

Tumors are intrinsically heterogeneous and it is well established that this directs their evolution, hinders their classification and frustrates therapy1-3. Consequently, spatially resolved omics-level analyses are gaining traction4-9. Despite considerable therapeutic interest, tumor metabolism has been lagging behind this development and there is a paucity of data regarding its spatial organization. To address this shortcoming, we set out to study the local metabolic effects of the oncogene c-MYC, a pleiotropic transcription factor that accumulates with tumor progression and influences metabolism10,11. Through correlative mass spectrometry imaging, we show that pantothenic acid (vitamin B5) associates with MYC-high areas within both human and murine mammary tumors, where its conversion to coenzyme A fuels Krebs cycle activity. Mechanistically, we show that this is accomplished by MYC-mediated upregulation of its multivitamin transporter SLC5A6. Notably, we show that SLC5A6 over-expression alone can induce increased cell growth and a shift toward biosynthesis, whereas conversely, dietary restriction of pantothenic acid leads to a reversal of many MYC-mediated metabolic changes and results in hampered tumor growth. Our work thus establishes the availability of vitamins and cofactors as a potential bottleneck in tumor progression, which can be exploited therapeutically. Overall, we show that a spatial understanding of local metabolism facilitates the identification of clinically relevant, tractable metabolic targets.

DOI: https://doi.org/10.1038/s42255-023-00915-7
Metab Eng. 2023 Nov 01. pii: S1096-7176(23)00146-5. [Epub ahead of print]80 254-266

Deuterated water as a substrate-agnostic isotope tracer for investigating reversibility and thermodynamics of reactions in central carbon metabolism.

Melanie M Callaghan, Eashant Thusoo, Bishal D Sharma, Fitsum Getahun, David M Stevenson, Costas Maranas, Daniel G Olson, Lee R Lynd, Daniel Amador-Noguez.

  Stable isotope tracers are a powerful tool for the quantitative analysis of microbial metabolism, enabling pathway elucidation, metabolic flux quantification, and assessment of reaction and pathway thermodynamics. 13C and 2H metabolic flux analysis commonly relies on isotopically labeled carbon substrates, such as glucose. However, the use of 2H-labeled nutrient substrates faces limitations due to their high cost and limited availability in comparison to 13C-tracers. Furthermore, isotope tracer studies in industrially relevant bacteria that metabolize complex substrates such as cellulose, hemicellulose, or lignocellulosic biomass, are challenging given the difficulty in obtaining these as isotopically labeled substrates. In this study, we examine the potential of deuterated water (2H2O) as an affordable, substrate-neutral isotope tracer for studying central carbon metabolism. We apply 2H2O labeling to investigate the reversibility of glycolytic reactions across three industrially relevant bacterial species -C. thermocellum, Z. mobilis, and E. coli-harboring distinct glycolytic pathways with unique thermodynamics. We demonstrate that 2H2O labeling recapitulates previous reversibility and thermodynamic findings obtained with established 13C and 2H labeled nutrient substrates. Furthermore, we exemplify the utility of this 2H2O labeling approach by applying it to high-substrate C. thermocellum fermentations -a setting in which the use of conventional tracers is impractical-thereby identifying the glycolytic enzyme phosphofructokinase as a major bottleneck during high-substrate fermentations and unveiling critical insights that will steer future engineering efforts to enhance ethanol production in this cellulolytic organism. This study demonstrates the utility of deuterated water as a substrate-agnostic isotope tracer for examining flux and reversibility of central carbon metabolic reactions, which yields biological insights comparable to those obtained using costly 2H-labeled nutrient substrates.

Keywords:  Acetivibrio thermocellus; Biofuels; Clostridium thermocellum; Deuterated water; Isotope tracers; Metabolic bottleneck; Metabolic flux analysis; Thermodynamics; Zymomonas mobilis

DOI:  https://doi.org/10.1016/j.ymben.2023.10.006
Clin Chem Lab Med. 2023 Nov 06.

Targeted quantitative lipidomic uncovers lipid biomarkers for predicting the presence of compensated cirrhosis and discriminating decompensated cirrhosis from compensated cirrhosis.

Yongbin Zeng, Li Zhang, Zhiyi Zheng, Jingyi Su, Ya Fu, Tianbin Chen, Kun Lin, Can Liu, Huanhuan Huang, Qishui Ou, Yongjun Zeng.

  OBJECTIVES: This study aimed to characterize serum lipid metabolism and identify potential biomarkers for compensated cirrhosis (CC) predicting and decompensated cirrhosis (DC) discrimination using targeted quantitative lipidomics and machine learning approaches.METHODS: Serum samples from a cohort of 120 participants was analyzed, including 90 cirrhosis patients (45 CC patients and 45 DC patients) and 30 healthy individuals. Lipid metabolic profiling was performed using targeted LC-MS/MS. Two machine learning methods, least absolute shrinkage and selection operator (LASSO), and random forest (RF) were applied to screen for candidate metabolite biomarkers.
RESULTS: The metabolic profiling analysis showed a significant disruption in patients with CC and DC. Compared to the CC group, the DC group exhibited a significant upregulation in the abundance of glycochenodeoxycholic acid (GCDCA), glyco-ursodeoxycholic acid (GUDCA), glycocholic acid (GCA), phosphatidylethanolamine (PE), N-acyl-lyso-phosphatidylethanolamine (LNAPE), and triglycerides (TG), and a significant downregulation in the abundance of ceramides (Cer) and lysophosphatidylcholines (LPC). Machine learning identified 11 lipid metabolites (abbreviated as BMP11) as potential CC biomarkers with excellent prediction performance, with an AUC of 0.944, accuracy of 94.7 %, precision of 95.6 %, and recall of 95.6 %. For DC discrimination, eight lipids (abbreviated as BMP8) were identified, demonstrating strong efficacy, with an AUC of 0.968, accuracy of 92.2 %, precision of 88.0 %, and recall of 97.8 %.
CONCLUSIONS: This study unveiled distinct lipidomic profiles in CC and DC patients and established robust lipid-based models for CC predicting and DC discrimination.

Keywords:  biomarkers; cirrhosis; decompensated; lipids; machine learning

DOI:  https://doi.org/10.1515/cclm-2023-0798
Acc Chem Res. 2023 Nov 09.

Pitfalls in RNA Modification Quantification Using Nucleoside Mass Spectrometry.

Gregor Ammann, Maximilian Berg, Jan Felix Dalwigk, Stefanie M Kaiser.

ConspectusIn recent years, there has been a high interest in researching RNA modifications, as they are involved in many cellular processes and in human diseases. A substantial set of enzymes within the cell, called RNA writers, place RNA modifications selectively and site-specifically. Another set of enzymes, called readers, recognize these modifications which guide the fate of the modified RNA. Although RNA is a transient molecule and RNA modification could be removed by RNA degradation, a subclass of enzymes, called RNA erasers, remove RNA modifications selectively and site-specifically to alter the characteristics of the RNA. The detection of RNA modifications can be done by various methods including second and next generation sequencing but also mass spectrometry. An approach capable of both qualitative and quantitative RNA modification analysis is liquid chromatography coupled to mass spectrometry of enzymatic hydrolysates of RNA into nucleosides. However, for successful detection and quantification, various factors must be considered to avoid biased identification and inaccurate quantification. In this Account, we identify three classes of errors that may distort the analysis. These classes comprise (I) errors related to chemical instabilities, (II) errors revolving around enzymatic hydrolysis to nucleosides, and (III) errors arising from issues with chromatographic separation and/or subsequent mass spectrometric analysis.A prominent example for class 1 is Dimroth rearrangement of m1A to m6A, but class 1 also comprises hydrolytic reactions and reactions with buffer components. Here, we also present the conversion of m3C to m3U under mild alkaline conditions and propose a practical solution to overcome these instabilities. Class 2 errors-such as contaminations in hydrolysis reagents or nuclease specificities-have led to erroneous discoveries of nucleosides in the past and possess the potential for misquantification of nucleosides. Impurities in the samples may also lead to class 3 errors: For instance, issues with chromatographic separation may arise from residual organic solvents, and salt adducts may hamper mass spectrometric quantification. This Account aims to highlight various errors connected to mass spectrometry analysis of nucleosides and presents solutions for how to overcome or circumnavigate those issues. Therefore, the authors anticipate that many scientists, but especially those who plan on doing nucleoside mass spectrometry, will benefit from the collection of data presented in this Account as a raised awareness, toward the variety of potential pitfalls, may further enhance the quality of data.

DOI: https://doi.org/10.1021/acs.accounts.3c00402
Mol Cell Proteomics. 2023 Nov 08. pii: S1535-9476(23)00188-3. [Epub ahead of print] 100677

Application of liquid-liquid extraction for N-terminal myristoylation proteomics.

Kazuya Tsumagari, Yosuke Isobe, Yasushi Ishihama, Jun Seita, Makoto Arita, Koshi Imami.

  Proteins can be modified by lipids in various ways, for example by myristoylation, palmitoylation, farnesylation, and geranylgeranylation-these processes are collectively referred to as lipidation. Current chemical proteomics using alkyne lipids has enabled the identification of lipidated protein candidates but does not identify endogenous lipidation sites and is not readily applicable to in vivo systems. Here, we introduce a proteomic methodology for global analysis of endogenous protein N-terminal myristoylation sites that combines liquid-liquid extraction of hydrophobic lipidated peptides with liquid chromatography-tandem mass spectrometry using a gradient program of acetonitrile in the high concentration range. We applied this method to explore myristoylation sites in HeLa cells, and identified a total of 75 protein N-terminal myristoylation sites, which is more than the number of high-confidence myristoylated proteins identified by myristic acid analog-based chemical proteomics. Isolation of myristoylated peptides from HeLa digests prepared with different proteases enabled the identification of different myristoylated sites, extending the coverage of N-myristoylome. Finally, we analyzed in vivo myristoylation sites in mouse tissues and found that the lipidation profile is tissue-specific. This simple method (not requiring chemical labeling or affinity purification) should be a promising tool for global profiling of protein N-terminal myristoylation.

Keywords:  Myristoylation; lipidation; liquid-liquid extraction

DOI:  https://doi.org/10.1016/j.mcpro.2023.100677