bims-mascan 2024-01-07 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2024‒01‒07
thirty-two papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh

Investigating the Metabolic Heterogeneity of Cancer Cells Using Functional Single-Cell Selection and nLC Combined with Multinozzle Emitter Mass Spectrometry.
Improved quantification of carbonyl sub-metabolome by liquid chromatography mass spectrometry using a fragment controlled multiplexed isotopic tag.
Fatty Acid Metabolism: A New Perspective in Breast Cancer Precision Therapy.
Acquisition and analysis of DIA-based proteomic data: a comprehensive survey in 2023.
Absolute quantification of nicotinamide mononucleotide in biological samples by double isotope-mediated liquid chromatography-tandem mass spectrometry (dimeLC-MS/MS).
An interactive web application for exploring human plasma and fibroblast metabolomics data from patients with inborn errors of metabolism.
Polarity-regulated derivatization-assisted LC-MS method for amino-containing metabolites profiling in gastric cancer.
Fast mass spectrometry search and clustering of untargeted metabolomics data.
A crustacean neuropeptide spectral library for data-independent acquisition (DIA) mass spectrometry applications.
Cell cycle arrest induces lipid droplet formation and confers ferroptosis resistance.
NME4 mediates metabolic reprogramming and promotes nonalcoholic fatty liver disease progression.
Comparison of LC-MS-based methods for the determination of carboxylic acids in animal matrices.
Glutamine addiction in tumor cell: oncogene regulation and clinical treatment.
Serine synthesis via reversed SHMT2 activity drives glycine depletion and acetaminophen hepatotoxicity in MASLD.
Identification of Unambiguous Borrelia Peptides in Human Urine Using Affinity Capture and Mass Spectrometry.
Increasing coverage of the urinary polar metabolome using ultra high-performance hydrophobic interaction liquid chromatography combined with linear and cyclic travelling wave ion mobility and mass spectrometry.
LiLA: lipid lung-based ATLAS built through a comprehensive workflow designed for an accurate lipid annotation.
Deep Characterisation of the sn-Isomer Lipidome Using High-Throughput Data-Independent Acquisition and Ozone-Induced Dissociation.
Proteomic profiling of ovarian clear cell carcinomas identifies prognostic biomarkers for chemotherapy.
Enabling Lipidomic Biomarker Studies for Protected Populations by Combining Noninvasive Fingerprint Sampling with MS Analysis and Machine Learning.
Comparison of high-resolution mass spectrometry acquisition methods for the simultaneous quantification and identification of per- and polyfluoroalkyl substances (PFAS).
PepPre: Promote Peptide Identification Using Accurate and Comprehensive Precursors.
Metabolic reprogramming by histone deacetylase inhibition preferentially targets NRF2-activated tumors.
Lipid metabolism, amino acid metabolism, and prostate cancer: a crucial metabolic journey.
Metabolomics Analysis and Diagnosis of Lung Cancer: Insights from Diverse Sample Types.
An evaluation of untargeted metabolomics methods to characterize inborn errors of metabolism.
Decoding Complexity in Synthetic Oligonucleotides: Unraveling Coeluting Isobaric Impurity Ions by High Resolution Mass Spectrometry.
Blocking methionine catabolism induces senescence and confers vulnerability to GSK3 inhibition in liver cancer.
Glycine homeostasis requires reverse SHMT flux.
Absolute Quantification of Human Serum Albumin Isoforms by Internal Calibration Based on a Top-Down LC-MS Approach.
Comparison between ammonium formate and ammonium fluoride in the analysis of stratum corneum lipids by reversed phase chromatography coupled with high resolution mass spectrometry.
Accelerating Pharmaceutical Process Development with an Acoustic Droplet Ejection-Multiple Reaction Monitoring-Mass Spectrometry Workflow.

Anal Chem. 2023 Dec 29.

Investigating the Metabolic Heterogeneity of Cancer Cells Using Functional Single-Cell Selection and nLC Combined with Multinozzle Emitter Mass Spectrometry.

Kai-Wen Cheng, Pin-Rui Su, Kate Jo-Ann Feller, Miao-Ping Chien, Cheng-Chih Hsu.

Tumor metastasis and cancer recurrence are often a result of cell heterogeneity, where specific subpopulations of tumor cells may be resistant to radio- or chemotherapy. To investigate this physiological and phenotypic diversity, single-cell metabolomics provides a powerful approach at the chemical level, where distinct lipid profiles can be found in different tumor cells. Here, we established a highly sensitive platform using nanoflow liquid chromatography (nLC) combined with multinozzle emitter electrospray ionization mass spectrometry for more in-depth metabolomics profiling. Our platform identified 15 and 17 lipids from individual osteosarcoma (U2OS) and glioblastoma (GBM) cells when analyzing single-cell samples. Additionally, we used the functional single-cell selection (fSCS) pipeline to analyze the subpopulations of cells with a DNA damage response (DDR) in U2OS cells and fast migration in GBM cells. Specifically, we observed a down-regulation of polyunsaturated fatty acids (PUFAs) in U2OS cells undergoing DDR, such as fatty acids FA 20:3; O2 and FA 17:4; O3. Furthermore, ceramides (Cer 38:0; O3) and triglycerides (TG 36:0) were found to be down-regulated in fast-migrating GBM cells compared to the slow-migrating subpopulation. These findings suggest the potential roles of these metabolites and/or lipids in the cellular behavior of the subpopulations.

DOI: https://doi.org/10.1021/acs.analchem.3c03688
Anal Chim Acta. 2024 Jan 25. pii: S0003-2670(23)01338-7. [Epub ahead of print]1287 342117

Improved quantification of carbonyl sub-metabolome by liquid chromatography mass spectrometry using a fragment controlled multiplexed isotopic tag.

Xiaobo Tian, Gérard Hopfgartner.

  BACKGROUND: Carbonyl-containing metabolites are a class of key intermediate in metabolism, which has potentials to be biomarkers. Since their poor ionization, derivatization reagents, such as dansylhydrazine, are usually used to improve the sensitivity and/or to facilitate quantification. However, most current carbonyl derivatization reagents only have two channels, one is isotopically labeled and the other one is non-labeled. To quantify more samples in a run and using data-independent acquisition (DIA) mode to get comprehensive and unbiased mass fragmentation, we proposed a fragment-controlled isotopic tag, called DiMe-FP-NHNH2 (FP) which has five channels: Δ0, Δ3, Δ6, Δ9, and Δ12, thus up to 5 samples can be analyzed in a run.RESULTS: The most important improvement is that the FP tag can produce multiple characteristic signals in tandem mass, diagnostic ions and neutral losses, which helps to selectively detect aldehydes/ketones for targeted and untargeted analysis. To exhibit all capabilities of the FP tag, we mimicked an untargeted metabolomics experiment, which comprises two steps. First, discovery step, using Data-Independent Analysis (SWATH-MS) and the labeling of two channels (Δ0 and Δ3), we picked out aldehyde/ketone from the pooled urine samples based on three characteristic signals, including isotope patterns, diagnostic ions, and neutral losses. Second, five-plex quantification, relative and absolute quantification were achieved in a single LC-MS analysis. Notably, because of different nominal masses, the FP tag can be used on any low or high resolution mass spectrometers.
SIGNIFICANCE: The benefits and performance of the FP tag are demonstrated by the analysis of urine samples collected from patients from a prostate cancer study, in which more than a thousand features were found based on MS1 fingerprint, but only around 120 aldehyde/ketone candidates were confirmed with characteristic signals and nine of which were quantified showing significant differences from healthy and reference urine samples.

Keywords:  Carbonyl sub-metabolome; Derivatization; LC-MS; Metabolomics; Multiplexing; QUAL/QUANT

DOI:  https://doi.org/10.1016/j.aca.2023.342117
Front Biosci (Landmark Ed). 2023 Dec 26. 28(12): 348

Fatty Acid Metabolism: A New Perspective in Breast Cancer Precision Therapy.

Mengye He, Suzhen Xu, Feifei Yan, Jian Ruan, Xiaochen Zhang.

  Breast cancer has a special tumor microenvironment compared to other solid tumors, which is usually surrounded by a large number of adipocytes that can produce and secrete fatty acids and adipokines. Adipocytes have a remodeling effect on breast cancer lipid metabolism, while fatty acids and lipid droplets can make breast cancer cells more aggressive. Lipid metabolism, especially the synthesis of fatty acids, is an important cellular process for membrane biosynthesis, energy storage, and signal molecule production. Therefore, blocking the lipid supply to cancer cells or changing the lipid composition has an important impact on the signal transmission and cell proliferation of cancer cells. Alterations in lipid availability can also affect cancer cell migration, induction of angiogenesis, metabolic symbiosis, evasion of immune surveillance, and cancer drug resistance. Fatty acid synthesis and metabolism have received extensive attention as potential targets for cancer therapy, and studies on modulating the tumor lipid microenvironment to improve the sensitivity of antitumor drugs have also been discussed; however, strategies to target these processes have not been translated into clinical practice.

Keywords:  drug discovery; drug resistance; fatty acid; lipid metabolism

DOI:  https://doi.org/10.31083/j.fbl2812348
Mol Cell Proteomics. 2024 Jan 03. pii: S1535-9476(24)00002-1. [Epub ahead of print] 100712

Acquisition and analysis of DIA-based proteomic data: a comprehensive survey in 2023.

Ronghui Lou, Wenqing Shui.

  Data-independent acquisition (DIA) mass spectrometry (MS) has emerged as a powerful technology for high-throughput, accurate and reproducible quantitative proteomics. This review provides a comprehensive overview of recent advances in both the experimental and computational methods for DIA proteomics, from data acquisition schemes to analysis strategies and software tools. DIA acquisition schemes are categorized based on the design of precursor isolation windows, highlighting wide-window, overlapping-window, narrow-window, scanning quadrupole-based, and parallel accumulation-serial fragmentation (PASEF)-enhanced DIA methods. For DIA data analysis, major strategies are classified into spectrum reconstruction, sequence-based search, library-based search, de novo sequencing and sequencing-independent approaches. A wide array of software tools implementing these strategies are reviewed, with details on their overall workflows and scoring approaches at different steps. The generation and optimization of spectral libraries, which are critical resources for DIA analysis, are also discussed. Publicly available benchmark datasets covering global proteomics and phosphoproteomics are summarized to facilitate performance evaluation of various software tools and analysis workflows. Continued advances and synergistic developments of versatile components in DIA workflows are expected to further enhance the power of DIA-based proteomics.

Keywords:  DIA data analysis; benchmark data; bottom-up proteomics; data-independent acquisition; spectral library

DOI:  https://doi.org/10.1016/j.mcpro.2024.100712
NPJ Aging. 2024 Jan 02. 10(1): 2

Absolute quantification of nicotinamide mononucleotide in biological samples by double isotope-mediated liquid chromatography-tandem mass spectrometry (dimeLC-MS/MS).

Junya Unno, Kathryn F Mills, Tairo Ogura, Masayuki Nishimura, Shin-Ichiro Imai.

Nicotinamide adenine dinucleotide (NAD+) is an essential metabolite for fundamental biological phenomena, including aging. Nicotinamide mononucleotide (NMN) is a key NAD+ intermediate that has been extensively tested as an effective NAD+-boosting compound in mice and humans. However, the accurate measurement of NMN in biological samples has long been a challenge in the field. Here, we have established an accurate, quantitative methodology for measuring NMN by using liquid chromatography-triple quadrupole mass spectrometry (LC-MS/MS) with double isotopic NMN standards. In this new methodology, the matrix effects of biological samples were properly adjusted, and the fate of NMN could be traced during sample processing. We have demonstrated that this methodology can accurately quantitate NMN levels in mouse plasma and confirmed quick, direct NMN uptake into blood circulation and cells. This double isotope-mediated LC-MS/MS (dimeLC-MS/MS) can easily be expanded to other NAD+-related metabolites as a reliable standard methodology for NAD+ biology.

DOI: https://doi.org/10.1038/s41514-023-00133-1
bioRxiv. 2023 Dec 12. pii: 2023.12.11.571124. [Epub ahead of print]

An interactive web application for exploring human plasma and fibroblast metabolomics data from patients with inborn errors of metabolism.

Ling Cai, Hieu S Vu, Wen Gu, Hongli Chen, Jordan Franklin, Lea Abou Haidar, Zheng Wu, Chunxiao Pan, Feng Cai, Phong Nguyen, Bookyung Ko, Chendong Yang, Lauren G Zacharias, Jessica Sudderth, Sarah Montgomery, Crescenda Uhles, Heather Fisher, Julianna Hudnall, Callie Hornbuckle, Christine Quinn, Donnice Michel, Luis Umaña, Angela Scheuerle, Markey C McNutt, Garrett K Gotway, Bushra Afroze, Min Ni, Ralph DeBerardinis.

Metabolomic profiling is instrumental in understanding the systemic and cellular impact of inborn errors of metabolism (IEMs), monogenic disorders caused by pathogenic genomic variants in genes involved in metabolism. This study encompasses untargeted metabolomics analysis of plasma from 474 individuals and fibroblasts from 67 subjects, incorporating healthy controls, patients with 65 different monogenic diseases, and numerous undiagnosed cases. We introduce a web application designed for the in-depth exploration of this extensive metabolomics database. The application offers a user-friendly interface for data review, download, and detailed analysis of metabolic deviations linked to IEMs at the level of individual patients or groups of patients with the same diagnosis. It also provides interactive tools for investigating metabolic relationships and offers comparative analyses of plasma and fibroblast profiles. This tool emphasizes the metabolic interplay within and across biological matrices, enriching our understanding of metabolic regulation in health and disease. As a resource, the application provides broad utility in research, offering novel insights into metabolic pathways and their alterations in various disorders.

DOI: https://doi.org/10.1101/2023.12.11.571124
J Pharm Anal. 2023 Nov;13(11): 1353-1364

Polarity-regulated derivatization-assisted LC-MS method for amino-containing metabolites profiling in gastric cancer.

Jie Han, Shilin Gong, Xiqing Bian, Yun Qian, Guilan Wang, Na Li, Jian-Lin Wu.

  Amino-containing compounds, including amino acids, aliphatic amines, aromatic amines, small peptides and catecholamines, are involved in various biological processes and play vital roles in multiple metabolic pathways. Previous studies indicated that some amino-containing metabolites are significant diagnostic and prognostic biomarkers of gastric cancer. However, the discovery of precise biomarkers for the preoperative diagnosis of gastric cancer is still in an urgent need. Herein, we established a polarity-regulated derivatization method coupled with liquid chromatography-mass spectrometry (LC-MS) for amino-containing metabolites profiling in the serum samples of patients with gastric cancer and healthy controls, based on our newly designed and synthesized derivatization reagent (S)-3-(1-(diisopropoxyphosphoryl) pyrrolidine-2-carboxamido)-N-hydroxysuccinimidyl ester (3-DP-NHS). Enhanced separation efficiency and detection sensitivity for amino-containing metabolites were achieved after derivatization. This method exhibited good linearity, recovery, intra- and inter-day precision and accuracy. Only 5 μL serum is needed for untargeted analysis, enabling 202 amino-containing metabolites to be detected. Statistical analysis revealed altered amino acid metabolisms in patients with gastric cancer. Furthermore, ultra high performance liquid chromatography coupled with mass spectrometry (UHPLC-MS/MS) analysis quantification revealed increased serum levels of tryptamine and decreased concentrations of arginine and tryptophan in patients with gastric cancer. Receiver operating characteristic (ROC) curves indicated that an increased tryptamine/tryptophan ratio could serve as a potential biomarker for gastric cancer diagnosis. This study demostrated the possibility of using serum amino acid biomarkers for gastric cancer diagnosis, providing new avenues for the treatment of gastric cancer.

Keywords:  Amino-containing metabolites; Gastric cancer; Liquid chromatography-mass spectrometry; Polarity-regulated derivatization

DOI:  https://doi.org/10.1016/j.jpha.2023.06.009
Nat Biotechnol. 2024 Jan 02.

Fast mass spectrometry search and clustering of untargeted metabolomics data.

Mihir Mongia, Tyler M Yasaka, Yudong Liu, Mustafa Guler, Liang Lu, Aditya Bhagwat, Bahar Behsaz, Mingxun Wang, Pieter C Dorrestein, Hosein Mohimani.

The throughput of mass spectrometers and the amount of publicly available metabolomics data are growing rapidly, but analysis tools such as molecular networking and Mass Spectrometry Search Tool do not scale to searching and clustering billions of mass spectral data in metabolomics repositories. To address this limitation, we designed MASST+ and Networking+, which can process datasets that are up to three orders of magnitude larger than those processed by state-of-the-art tools.

DOI: https://doi.org/10.1038/s41587-023-01985-4
Proteomics. 2024 Jan 03. e2300285

A crustacean neuropeptide spectral library for data-independent acquisition (DIA) mass spectrometry applications.

Lauren Fields, Min Ma, Kellen DeLaney, Ashley Phetsanthad, Lingjun Li.

  Neuropeptides have tremendous potential for application in modern medicine, including utility as biomarkers and therapeutics. To overcome the inherent challenges associated with neuropeptide identification and characterization, data-independent acquisition (DIA) is a fitting mass spectrometry (MS) method of choice to achieve sensitive and accurate analysis. It is advantageous for preliminary neuropeptidomic studies to occur in less complex organisms, with crustacean models serving as a popular choice due to their relatively simple nervous system. With spectral libraries serving as a means to interpret DIA-MS output spectra, and Cancer borealis as a model of choice for neuropeptide analysis, we performed the first spectral library mapping of crustacean neuropeptides. Leveraging pre-existing data-dependent acquisition (DDA) spectra, a spectral library was built using PEAKS Online. The library is comprised of 333 unique neuropeptides. The identification results obtained through the use of this spectral library were compared with those achieved through library-free analysis of crustacean brain, pericardial organs (PO), and thoracic ganglia (TG) tissues. A statistically significant increase (Student's t-test, P value < 0.05) in the number of identifications achieved from the TG data was observed in the spectral library results. Furthermore, in each of the tissues, a distinctly different set of identifications was found in the library search compared to the library-free search. This work highlights the necessity for the use of spectral libraries in neuropeptide analysis, illustrating the advantage of spectral libraries for interpreting DIA spectra in a reproducible manner with greater neuropeptidomic depth.

Keywords:  data-independent acquisition; neuropeptide; peptidomics; spectral library

DOI:  https://doi.org/10.1002/pmic.202300285
Nat Commun. 2024 Jan 02. 15(1): 79

Cell cycle arrest induces lipid droplet formation and confers ferroptosis resistance.

Hyemin Lee, Amber Horbath, Lavanya Kondiparthi, Jitendra Kumar Meena, Guang Lei, Shayani Dasgupta, Xiaoguang Liu, Li Zhuang, Pranavi Koppula, Mi Li, Iqbal Mahmud, Bo Wei, Philip L Lorenzi, Khandan Keyomarsi, Masha V Poyurovsky, Kellen Olszewski, Boyi Gan.

How cells coordinate cell cycling with cell survival and death remains incompletely understood. Here, we show that cell cycle arrest has a potent suppressive effect on ferroptosis, a form of regulated cell death induced by overwhelming lipid peroxidation at cellular membranes. Mechanistically, cell cycle arrest induces diacylglycerol acyltransferase (DGAT)-dependent lipid droplet formation to sequester excessive polyunsaturated fatty acids (PUFAs) that accumulate in arrested cells in triacylglycerols (TAGs), resulting in ferroptosis suppression. Consequently, DGAT inhibition orchestrates a reshuffling of PUFAs from TAGs to phospholipids and re-sensitizes arrested cells to ferroptosis. We show that some slow-cycling antimitotic drug-resistant cancer cells, such as 5-fluorouracil-resistant cells, have accumulation of lipid droplets and that combined treatment with ferroptosis inducers and DGAT inhibitors effectively suppresses the growth of 5-fluorouracil-resistant tumors by inducing ferroptosis. Together, these results reveal a role for cell cycle arrest in driving ferroptosis resistance and suggest a ferroptosis-inducing therapeutic strategy to target slow-cycling therapy-resistant cancers.

DOI: https://doi.org/10.1038/s41467-023-44412-7
EMBO Rep. 2023 Dec 14.

NME4 mediates metabolic reprogramming and promotes nonalcoholic fatty liver disease progression.

Shaofang Xie, Lei Yuan, Yue Sui, Shan Feng, Hengle Li, Xu Li.

  Nonalcoholic fatty liver disease (NAFLD) is mainly characterized by excessive fat accumulation in the liver, and it is associated with liver-related complications and adverse systemic diseases. NAFLD has become the most prevalent liver disease; however, effective therapeutic agents for NAFLD are still lacking. We combined clinical data with proteomics and metabolomics data, and found that the mitochondrial nucleoside diphosphate kinase NME4 plays a central role in mitochondrial lipid metabolism. Nme4 is markedly upregulated in mice fed with high-fat diet, and its expression is positively correlated with the level of steatosis. Hepatic deletion of Nme4 suppresses the progression of hepatic steatosis. Further studies demonstrated that NME4 interacts with several key enzymes in coenzyme A (CoA) metabolism and increases the level of acetyl-CoA and malonyl-CoA, which are the major lipid components of the liver in NAFLD. Increased level of acetyl-CoA and malonyl-CoA lead to increased triglyceride levels and lipid accumulation in the liver. Taken together, these findings reveal that NME4 is a critical regulator of NAFLD progression and a potential therapeutic target for NAFLD.

Keywords:  Coenzyme A Metabolism; Lipid Accumulation; NAFLD; NME4

DOI:  https://doi.org/10.1038/s44319-023-00012-6
Anal Bioanal Chem. 2024 Jan 05.

Comparison of LC-MS-based methods for the determination of carboxylic acids in animal matrices.

Heidi E Schwartz-Zimmermann, Manuel Hündler, Nicole Reiterer, Sara Ricci, Raul Rivera-Chacon, Ezequias Castillo-Lopez, Qendrim Zebeli, Franz Berthiller.

  Carboxylic acids (CAs) are key players in human and animal metabolism. As they are hardly retained under reversed-phase liquid chromatography (RP-LC) conditions in their native form, derivatization is an option to make them accessible to RP-LC and simultaneously increase their response for mass spectrometric detection. In this work, two RP-LC tandem mass spectrometry-based methods using aniline or 3-nitrophenylhydrazine (3-NPH) as derivatization agents were compared with respect to several factors including completeness of derivatization, apparent recoveries (RAs) in both cow feces and ruminal fluid, and concentrations obtained in feces and ruminal fluid of cows. Anion exchange chromatography coupled to high-resolution mass spectrometry (AIC-HR-MS) served as reference method. Derivatization efficiencies were close to 100% for 3-NPH derivatization but variable (20-100%) and different in solvent solutions and matrix extracts for aniline derivatization. Likewise, average RAs of 13C-labeled short-chain fatty acids as internal standards were around 100% for 3-NPH derivatization but only 45% for aniline derivatization. Quantification of CAs in feces and ruminal fluid of cows initially fed a forage-only diet and then transitioned to a 65% high-grain diet which yielded similar concentrations for 3-NPH derivatization and AIC-HR-MS, but concentrations determined by aniline derivatization were on average five times lower. For these reasons, derivatization with aniline is not recommended for the quantitative analysis of CAs in animal samples.

Keywords:  Anion exchange chromatography; Derivatization; Mass spectrometry; Reversed-phase high-performance liquid chromatography; Short-chain fatty acids

DOI:  https://doi.org/10.1007/s00216-023-05113-8
Cell Commun Signal. 2024 Jan 03. 22(1): 12

Glutamine addiction in tumor cell: oncogene regulation and clinical treatment.

Xian Li, Xueqiang Peng, Yan Li, Shibo Wei, Guangpeng He, Jiaxing Liu, Xinyu Li, Shuo Yang, Dai Li, Weikai Lin, Jianjun Fang, Liang Yang, Hangyu Li.

   After undergoing metabolic reprogramming, tumor cells consume additional glutamine to produce amino acids, nucleotides, fatty acids, and other substances to facilitate their unlimited proliferation. As such, the metabolism of glutamine is intricately linked to the survival and progression of cancer cells. Consequently, targeting the glutamine metabolism presents a promising strategy to inhibit growth of tumor cell and cancer development. This review describes glutamine uptake, metabolism, and transport in tumor cells and its pivotal role in biosynthesis of amino acids, fatty acids, nucleotides, and more. Furthermore, we have also summarized the impact of oncogenes like C-MYC, KRAS, HIF, and p53 on the regulation of glutamine metabolism and the mechanisms through which glutamine triggers mTORC1 activation. In addition, role of different anti-cancer agents in targeting glutamine metabolism has been described and their prospective applications are assessed.

Keywords:  Glutamine; Metabolism; Oncogene clinical treatment; Tumor

DOI:  https://doi.org/10.1186/s12964-023-01449-x
Cell Metab. 2024 Jan 02. pii: S1550-4131(23)00464-3. [Epub ahead of print]36(1): 116-129.e7

Serine synthesis via reversed SHMT2 activity drives glycine depletion and acetaminophen hepatotoxicity in MASLD.

Alia Ghrayeb, Alexandra C Finney, Bella Agranovich, Daniel Peled, Sumit Kumar Anand, M Peyton McKinney, Mahasen Sarji, Dongshan Yang, Natan Weissman, Shani Drucker, Sara Isabel Fernandes, Jonatan Fernández-García, Kyle Mahan, Zaid Abassi, Lin Tan, Philip L Lorenzi, James Traylor, Jifeng Zhang, Ifat Abramovich, Y Eugene Chen, Oren Rom, Inbal Mor, Eyal Gottlieb.

  Metabolic dysfunction-associated steatotic liver disease (MASLD) affects one-third of the global population. Understanding the metabolic pathways involved can provide insights into disease progression and treatment. Untargeted metabolomics of livers from mice with early-stage steatosis uncovered decreased methylated metabolites, suggesting altered one-carbon metabolism. The levels of glycine, a central component of one-carbon metabolism, were lower in mice with hepatic steatosis, consistent with clinical evidence. Stable-isotope tracing demonstrated that increased serine synthesis from glycine via reverse serine hydroxymethyltransferase (SHMT) is the underlying cause for decreased glycine in steatotic livers. Consequently, limited glycine availability in steatotic livers impaired glutathione synthesis under acetaminophen-induced oxidative stress, enhancing acute hepatotoxicity. Glycine supplementation or hepatocyte-specific ablation of the mitochondrial SHMT2 isoform in mice with hepatic steatosis mitigated acetaminophen-induced hepatotoxicity by supporting de novo glutathione synthesis. Thus, early metabolic changes in MASLD that limit glycine availability sensitize mice to xenobiotics even at the reversible stage of this disease.

Keywords:  MASLD; SHMT; acetaminophen hepatotoxicity; glutathione; glycine; one-carbon metabolism; xenobiotic

DOI:  https://doi.org/10.1016/j.cmet.2023.12.013
Methods Mol Biol. 2024 ;2742 105-122

Identification of Unambiguous Borrelia Peptides in Human Urine Using Affinity Capture and Mass Spectrometry.

Rocio Cornero, Sumaiya Safia Irfan, Silvia Cachaco, Weidong Zhou, Ahana Byne, Marissa Howard, Hope McIntyre, Barbara Birkaya, Lance Liotta, Alessandra Luchini.

  The combination of advanced mass spectrometry and enrichment-based sample preparation methods has enhanced analytical capabilities in clinical proteomics. In this chapter, we describe a method of proteome analysis to identify Borrelia-derived peptides in urine that includes a sample affinity enrichment method coupled with liquid chromatography tandem mass spectrometry analysis and a bioinformatic peptide authentication algorithm.

Keywords:  Affinity capture; Borrelia; Direct test; Mass spectrometry; Polyamide; Sudan IV; Sudan black B; Urine

DOI:  https://doi.org/10.1007/978-1-0716-3561-2_9
J Chromatogr A. 2024 Jan 11. pii: S0021-9673(23)00762-8. [Epub ahead of print]1714 464537

Increasing coverage of the urinary polar metabolome using ultra high-performance hydrophobic interaction liquid chromatography combined with linear and cyclic travelling wave ion mobility and mass spectrometry.

Adam King, Lee A Gethings, Johannes P C Vissers, Robert S Plumb, Ian D Wilson.

  The use of HILIC-based separations for the analysis of polar metabolites in metabolic phenotyping studies is well established. Here, we demonstrate the increased coverage of the polar metabolome obtained by travelling wave (TW) ion mobility (IM) instruments combined with HILIC and mass spectrometry (MS) for metabotyping rat and mouse urine samples. Profiling was performed using either a linear TW IM-MS based instrument with a path length of 40 cm or an instrument with a cyclic travelling wave analyser (cIM) with a path length of 95 cm. Due to the added resolution afforded by using both the linear and cyclic IM geometries with MS detection (IM-MS) significant increases in feature count (m/z-tR pairs) were generally obtained compared to HILIC-MS alone. In addition, the use of both linear and cyclic IM-MS improved the quality of the mass spectra obtained as a result of the separation of co-eluting analytes. As would be expected from the increased path length of the cyclic IM-MS instrument compared to the linear device, the largest gains in feature detection were obtained for the HILIC-cIM-MS combination. By increasing the resolution of coeluting components, the cyclic IM-MS instrumentation also provided the largest improvement in the quality of the mass spectral data obtained. When applied to mouse urines obtained from both control and gefitinib-dosed mice, time-related changes were detected in those obtained from the treated animals that were not seen in the controls. Polar metabolites affected by drug administration included, but were not limited to, hypoxanthine, 1,3-dimethyluracil and acetylcarnitine. The changes seen in the relative concentrations of these endogenous metabolites appeared to be related to drug concentrations in the plasma and urine suggesting a pharmacometabodynamic link.

Keywords:  Ion mobility; Metabolic phenotyping; Metabolite identification; Polar metabolites; Urine

DOI:  https://doi.org/10.1016/j.chroma.2023.464537
Commun Biol. 2024 Jan 05. 7(1): 45

LiLA: lipid lung-based ATLAS built through a comprehensive workflow designed for an accurate lipid annotation.

Belén Fernández Requena, Sajid Nadeem, Vineel P Reddy, Vanessa Naidoo, Joel N Glasgow, Adrie J C Steyn, Coral Barbas, Carolina Gonzalez-Riano.

Accurate lipid annotation is crucial for understanding the role of lipids in health and disease and identifying therapeutic targets. However, annotating the wide variety of lipid species in biological samples remains challenging in untargeted lipidomic studies. In this work, we present a lipid annotation workflow based on LC-MS and MS/MS strategies, the combination of four bioinformatic tools, and a decision tree to support the accurate annotation and semi-quantification of the lipid species present in lung tissue from control mice. The proposed workflow allowed us to generate a lipid lung-based ATLAS (LiLA), which was then employed to unveil the lipidomic signatures of the Mycobacterium tuberculosis infection at two different time points for a deeper understanding of the disease progression. This workflow, combined with manual inspection strategies of MS/MS data, can enhance the annotation process for lipidomic studies and guide the generation of sample-specific lipidome maps. LiLA serves as a freely available data resource that can be employed in future studies to address lipidomic alterations in mice lung tissue.

DOI: https://doi.org/10.1038/s42003-023-05680-7
Angew Chem Int Ed Engl. 2024 Jan 02. e202316793

Deep Characterisation of the sn-Isomer Lipidome Using High-Throughput Data-Independent Acquisition and Ozone-Induced Dissociation.

Jesse A Michael, Reuben S E Young, Rachelle Balez, Lachlan J Jekimovs, David L Marshall, Berwyck L J Poad, Todd W Mitchell, Stephen J Blanksby, Christer S Ejsing, Shane R Ellis.

  In recent years there has been a significant interest in the development of innovative lipidomics techniques capable of resolving lipid isomers. To date, methods applied to resolving sn-isomers have resolved only a limited number of species. We report a workflow based on ozone-induced dissociation for untargeted characterisation of hundreds of sn-resolved glycerophospholipid isomers from biological extracts in under 20 minutes, coupled with an automated data analysis pipeline. It provides an order of magnitude increase over the number of sn-isomer pairs identified compared to previous reports and reveals that sn-isomer populations are tightly regulated and significantly different between cell lines. The sensitivity of this method and potential for de novo molecular discovery is further demonstrated by the identification of unexpected lipids containing ultra-long chain monounsaturated acyl chains at the sn-1 position.

Keywords:  lipids, mass spectrometry, isomers, ozonolysis, long chain fatty acids

DOI:  https://doi.org/10.1002/anie.202316793
Proteomics. 2024 Jan 03. e2300242

Proteomic profiling of ovarian clear cell carcinomas identifies prognostic biomarkers for chemotherapy.

Liang Yue, Tingting Gong, Wenhao Jiang, Liujia Qian, Wangang Gong, Yaoting Sun, Xue Cai, Heli Xu, Fanghua Liu, He Wang, Sainan Li, Yi Zhu, Zhiguo Zheng, Qijun Wu, Tiannan Guo.

  Clear cell ovarian carcinoma (CCOC) is a relatively rare subtype of ovarian cancer (OC) with high degree of resistance to standard chemotherapy. Little is known about the underlying molecular mechanisms, and it remains a challenge to predict its prognosis after chemotherapy. Here, we first analyzed the proteome of 35 formalin-fixed paraffin-embedded (FFPE) CCOC tissue specimens from a cohort of 32 patients with CCOC (H1 cohort) and characterized 8697 proteins using data-independent acquisition mass spectrometry (DIA-MS). We then performed proteomic analysis of 28 fresh frozen (FF) CCOC tissue specimens from an independent cohort of 24 patients with CCOC (H2 cohort), leading to the identification of 9409 proteins with DIA-MS. After bioinformatics analysis, we narrowed our focus to 15 proteins significantly correlated with the recurrence free survival (RFS) in both cohorts. These proteins are mainly involved in DNA damage response, extracellular matrix (ECM), and mitochondrial metabolism. Parallel reaction monitoring (PRM)-MS was adopted to validate the prognostic potential of the 15 proteins in the H1 cohort and an independent confirmation cohort (H3 cohort). Interferon-inducible transmembrane protein 1 (IFITM1) was observed as a robust prognostic marker for CCOC in both PRM data and immunohistochemistry (IHC) data. Taken together, this study presents a CCOC proteomic data resource and a single promising protein, IFITM1, which could potentially predict the recurrence and survival of CCOC.

Keywords:  chemotherapy resistance; clear cell ovarian carcinoma; clear cell renal carcinoma; data-independent acquisition; overall survival; prognosis; proteomics; recurrence free survival; targeted proteomics

DOI:  https://doi.org/10.1002/pmic.202300242
J Proteome Res. 2024 Jan 03.

Enabling Lipidomic Biomarker Studies for Protected Populations by Combining Noninvasive Fingerprint Sampling with MS Analysis and Machine Learning.

Madeline Isom, Eden P Go, Heather Desaire.

  Triacylglycerols and wax esters are two lipid classes that have been linked to diseases, including autism, Alzheimer's disease, dementia, cardiovascular disease, dry eye disease, and diabetes, and thus are molecules worthy of biomarker exploration studies. Since triacylglycerols and wax esters make up the majority of skin-surface lipid secretions, a viable sampling method for these potential biomarkers would be that of groomed latent fingerprints. Currently, however, blood-based sampling protocols predominate in the field. The invasiveness of a blood draw limits its utility to protected populations, including children and the elderly. Herein we describe a noninvasive means for sample collection (from fingerprints) paired with fast MS data-acquisition (MassIVE data set MSV000092742) and efficient data analysis via machine learning. Using both supervised and unsupervised classification, we demonstrate the usefulness of this method in determining whether a variable of interest imparts measurable change within the lipidomic data set. As a proof-of-concept, we show that the method is capable of distinguishing between the fingerprints of different individuals as well as between anatomical sebum collection regions. This noninvasive, high-throughput approach enables future lipidomic biomarker researchers to more easily include underrepresented, protected populations, such as children and the elderly, thus moving the field closer to definitive disease diagnoses that apply to all.

Keywords:  biomarkers; fingerprints; lipidomics; lipids; machine learning; mass spectrometry; noninvasive sampling

DOI:  https://doi.org/10.1021/acs.jproteome.3c00368
Anal Bioanal Chem. 2023 Dec 30.

Comparison of high-resolution mass spectrometry acquisition methods for the simultaneous quantification and identification of per- and polyfluoroalkyl substances (PFAS).

Jordan M Partington, Sahil Rana, Drew Szabo, Tarun Anumol, Bradley O Clarke.

  Simultaneous identification and quantification of per- and polyfluoroalkyl substances (PFAS) were evaluated for three quadrupole time-of-flight mass spectrometry (QTOF) acquisition methods. The acquisition methods investigated were MS-Only, all ion fragmentation (All-Ions), and automated tandem mass spectrometry (Auto-MS/MS). Target analytes were the 25 PFAS of US EPA Method 533 and the acquisition methods were evaluated by analyte response, limit of quantification (LOQ), accuracy, precision, and target-suspect screening identification limit (IL). PFAS LOQs were consistent across acquisition methods, with individual PFAS LOQs within an order of magnitude. The mean and range for MS-Only, All-Ions, and Auto-MS/MS are 1.3 (0.34-5.1), 2.1 (0.49-5.1), and 1.5 (0.20-5.1) pg on column. For fast data processing and tentative identification with lower confidence, MS-Only is recommended; however, this can lead to false-positives. Where high-confidence identification, structural characterisation, and quantification are desired, Auto-MS/MS is recommended; however, cycle time should be considered where many compounds are anticipated to be present. For comprehensive screening workflows and sample archiving, All-Ions is recommended, facilitating both quantification and retrospective analysis. This study validated HRMS acquisition approaches for quantification (based upon precursor data) and exploration of identification workflows for a range of PFAS compounds.

Keywords:  Analytical chemistry; EPA Method 533; Emerging contaminants; Quadrupole time-of-flight mass spectrometry (QTOF); Suspect screening

DOI:  https://doi.org/10.1007/s00216-023-05075-x
J Proteome Res. 2023 Dec 29.

PepPre: Promote Peptide Identification Using Accurate and Comprehensive Precursors.

Ching Tarn, Yu-Zhuo Wu, Kai-Fei Wang.

  Accurate and comprehensive peptide precursor ions are crucial to tandem mass-spectrometry-based peptide identification. An identification engine can derive great advantages from the search space reduction enabled by credible and detailed precursors. Furthermore, by considering multiple precursors per spectrum, both the number of identifications and the spectrum explainability can be substantially improved. Here, we introduce PepPre, which detects precursors by decomposing peaks into multiple isotope clusters using linear programming methods. The detected precursors are scored and ranked, and the high-scoring ones are used for subsequent peptide identification. PepPre is evaluated both on regular and cross-linked peptide data sets and compared with 11 methods. The experimental results show that PepPre achieves a remarkable increase of 203% in PSM and 68% in peptide identifications compared to instrument software for regular peptides and 99% in PSM and 27% in peptide pair identifications for cross-linked peptides, surpassing the performance of all other evaluated methods. In addition to the increased identification numbers, further credibility evaluations evidence the reliability of the identified results. Moreover, by widening the isolation window of data acquisition from 2 to 8 Th, with PepPre, an engine is able to identify at least 64% more PSMs, thereby demonstrating the potential advantages of wide-window data acquisition. PepPre is open-source and available at http://peppre.ctarn.io.

Keywords:  deisotope; linear programming; mass spectrometry; peptide identification; precursor ion detection

DOI:  https://doi.org/10.1021/acs.jproteome.3c00293
Cell Rep. 2023 Dec 30. pii: S2211-1247(23)01640-6. [Epub ahead of print]43(1): 113629

Metabolic reprogramming by histone deacetylase inhibition preferentially targets NRF2-activated tumors.

Dimitris Karagiannis, Warren Wu, Albert Li, Makiko Hayashi, Xiao Chen, Michaela Yip, Vaibhav Mangipudy, Xinjing Xu, Francisco J Sánchez-Rivera, Yadira M Soto-Feliciano, Jiangbin Ye, Thales Papagiannakopoulos, Chao Lu.

  The interplay between metabolism and chromatin signaling is implicated in cancer progression. However, whether and how metabolic reprogramming in tumors generates chromatin vulnerabilities remain unclear. Lung adenocarcinoma (LUAD) tumors frequently harbor aberrant activation of the NRF2 antioxidant pathway, which drives aggressive and chemo-resistant disease. Using a chromatin-focused CRISPR screen, we report that NRF2 activation sensitizes LUAD cells to genetic and chemical inhibition of class I histone deacetylases (HDACs). This association is observed across cultured cells, mouse models, and patient-derived xenografts. Integrative epigenomic, transcriptomic, and metabolomic analysis demonstrates that HDAC inhibition causes widespread redistribution of H4ac and its reader protein, which transcriptionally downregulates metabolic enzymes. This results in reduced flux into amino acid metabolism and de novo nucleotide synthesis pathways that are preferentially required for the survival of NRF2-active cancer cells. Together, our findings suggest NRF2 activation as a potential biomarker for effective repurposing of HDAC inhibitors to treat solid tumors.

Keywords:  CP: Cancer; HDAC inhibitors; NRF2 pathway; cancer epigenetics; cancer metabolism; cancer targeted therapy; epigenetic reprogramming; lung cancer

DOI:  https://doi.org/10.1016/j.celrep.2023.113629
Asian J Androl. 2023 Dec 26.

Lipid metabolism, amino acid metabolism, and prostate cancer: a crucial metabolic journey.

Lin Chen, Yu-Xin Xu, Yuan-Shuo Wang, Jian-Liang Zhou.

Prostate cancer (PCa) is one of the most common malignancies in males worldwide, and its development and progression involve the regulation of multiple metabolic pathways. Alterations in lipid metabolism affect the proliferation and metastatic capabilities of PCa cells. Cancer cells increase lipid synthesis and regulate fatty acid oxidation to meet their growth and energy demands. Similarly, changes occur in amino acid metabolism in PCa. Cancer cells exhibit an increased demand for specific amino acids, and they regulate amino acid transport and metabolic pathways to fulfill their proliferation and survival requirements. These changes are closely associated with disease progression and treatment response in PCa cells. Therefore, a comprehensive investigation of the metabolic characteristics of PCa is expected to offer novel insights and approaches for the early diagnosis and treatment of this disease.

DOI: https://doi.org/10.4103/aja202363
Int J Med Sci. 2024 ;21(2): 234-252

Metabolomics Analysis and Diagnosis of Lung Cancer: Insights from Diverse Sample Types.

Simin Liang, Xiujun Cao, Yingshuang Wang, Ping Leng, Xiaoxia Wen, Guojing Xie, Huaichao Luo, Rong Yu.

  Lung cancer is a highly fatal disease that poses a significant global health burden. The absence of characteristic clinical symptoms frequently results in the diagnosis of most patients at advanced stages of lung cancer. Although low-dose computed tomography (LDCT) screening has become increasingly prevalent in clinical practice, its high rate of false positives continues to present a significant challenge. In addition to LDCT screening, tumor biomarker detection represents a critical approach for early diagnosis of lung cancer; unfortunately, no tumor marker with optimal sensitivity and specificity is currently available. Metabolomics has recently emerged as a promising field for developing novel tumor biomarkers. In this paper, we introduce metabolic pathways, instrument platforms, and a wide variety of sample types for lung cancer metabolomics. Specifically, we explore the strengths, limitations, and distinguishing features of various sample types employed in lung cancer metabolomics research. Additionally, we present the latest advances in lung cancer metabolomics research that utilize diverse sample types. We summarize and enumerate research studies that have investigated lung cancer metabolomics using different metabolomic sample types. Finally, we provide a perspective on the future of metabolomics research in lung cancer. Our discussion of the potential of metabolomics in developing new tumor biomarkers may inspire further study and innovation in this dynamic field.

Keywords:  Biological Marker; Biomarkers; Chromatography; Lung Neoplasms; Lung cancer; Mass spectrometry; Metabolomics; Metabonomics

DOI:  https://doi.org/10.7150/ijms.85704
Mol Genet Metab. 2023 Dec 15. pii: S1096-7192(23)00745-X. [Epub ahead of print]141(1): 108115

An evaluation of untargeted metabolomics methods to characterize inborn errors of metabolism.

Rachel Wurth, Coleman Turgeon, Zinandré Stander, Devin Oglesbee.

  Inborn errors of metabolism (IEMs) encompass a diverse group of disorders that can be difficult to classify due to heterogenous clinical, molecular, and biochemical manifestations. Untargeted metabolomics platforms have become a popular approach to analyze IEM patient samples because of their ability to detect many metabolites at once, accelerating discovery of novel biomarkers, and metabolic mechanisms of disease. However, there are concerns about the reproducibility of untargeted metabolomics research due to the absence of uniform reporting practices, data analyses, and experimental design guidelines. Therefore, we critically evaluated published untargeted metabolomic platforms used to characterize IEMs to summarize the strengths and areas for improvement of this technology as it progresses towards the clinical laboratory. A total of 96 distinct IEMs were collectively evaluated by the included studies. However, most of these IEMs were evaluated by a single untargeted metabolomic method, in a single study, with a limited cohort size (55/96, 57%). The goals of the included studies generally fell into two, often overlapping, categories: detecting known biomarkers from many biochemically distinct IEMs using a single platform, and detecting novel metabolites or metabolic pathways. There was notable diversity in the design of the untargeted metabolomic platforms. Importantly, the majority of studies reported adherence to quality metrics, including the use of quality control samples and internal standards in their experiments, as well as confirmation of at least some of their feature annotations with commercial reference standards. Future applications of untargeted metabolomics platforms to the study of IEMs should move beyond single-subject analyses, and evaluate reproducibility using a prospective, or validation cohort.

Keywords:  Biomarker; Inborn errors of metabolism; Metabolomic methods; Quality; Research design; Untargeted metabolomics

DOI:  https://doi.org/10.1016/j.ymgme.2023.108115
Anal Chem. 2023 Dec 29.

Decoding Complexity in Synthetic Oligonucleotides: Unraveling Coeluting Isobaric Impurity Ions by High Resolution Mass Spectrometry.

A M Abdullah, Cynthia Sommers, Jason D Rodriguez, Deyi Zhang, Darby Kozak, Jessica Hawes, Mohan Sapru, Kui Yang.

Analyzing coeluting impurities with similar masses in synthetic oligonucleotides by liquid chromatography-mass spectrometry (LC-MS) poses challenges due to inadequate separation in either dimension. Herein, we present a direct method employing fully resolved isotopic envelopes, enabled by high resolution mass spectrometry (HRMS), to identify and quantify isobaric impurity ions resulting from the deletion or addition of a uracil (U) or cytosine (C) nucleotide from or to the full-length sequence. These impurities may each encompass multiple sequence variants arising from various deletion or addition sites. The method utilizes a full or targeted MS analysis to measure accurate isotopic distributions that are chemical formula dependent but nucleotide sequence independent. This characteristic enables the quantification of isobaric impurity ions involving sequence variants, a capability typically unavailable in sequence-dependent MS/MS methods. Notably, this approach does not rely on standard curves to determine isobaric impurity compositions in test samples; instead, it utilizes the individual isotopic distributions measured for each impurity standard. Moreover, in cases where specific impurity standards are unavailable, the measured isotopic distributions can be adequately replaced with the theoretical distributions (calculated based on chemical formulas of standards) adjusted using experiment-specific correction factors. In summary, this streamlined approach overcomes the limitations of LC-MS analysis for coeluting isobaric impurity ions, offering a promising solution for the in-depth profiling of complex impurity mixtures in synthetic oligonucleotide therapeutics.

DOI: https://doi.org/10.1021/acs.analchem.3c05016
Nat Cancer. 2024 Jan 02.

Blocking methionine catabolism induces senescence and confers vulnerability to GSK3 inhibition in liver cancer.

Fuming Li, Pingyu Liu, Wen Mi, Liucheng Li, Nicole M Anderson, Nicholas P Lesner, Michelle Burrows, Jacqueline Plesset, Ariana Majer, Guanlin Wang, Jinyang Li, Lingzhi Zhu, Brian Keith, M Celeste Simon.

Availability of the essential amino acid methionine affects cellular metabolism and growth, and dietary methionine restriction has been implicated as a cancer therapeutic strategy. Nevertheless, how liver cancer cells respond to methionine deprivation and underlying mechanisms remain unclear. Here we find that human liver cancer cells undergo irreversible cell cycle arrest upon methionine deprivation in vitro. Blocking methionine adenosyl transferase 2A (MAT2A)-dependent methionine catabolism induces cell cycle arrest and DNA damage in liver cancer cells, resulting in cellular senescence. A pharmacological screen further identified GSK3 inhibitors as senolytics that selectively kill MAT2A-inhibited senescent liver cancer cells. Importantly, combined treatment with MAT2A and GSK3 inhibitors therapeutically blunts liver tumor growth in vitro and in vivo across multiple models. Together, methionine catabolism is essential for liver tumor growth, and its inhibition can be exploited as an improved pro-senescence strategy for combination with senolytic agents to treat liver cancer.

DOI: https://doi.org/10.1038/s43018-023-00671-3
Cell Metab. 2024 Jan 02. pii: S1550-4131(23)00452-7. [Epub ahead of print]36(1): 103-115.e4

Glycine homeostasis requires reverse SHMT flux.

Matthew J McBride, Craig J Hunter, Zhaoyue Zhang, Tara TeSlaa, Xincheng Xu, Gregory S Ducker, Joshua D Rabinowitz.

  The folate-dependent enzyme serine hydroxymethyltransferase (SHMT) reversibly converts serine into glycine and a tetrahydrofolate-bound one-carbon unit. Such one-carbon unit production plays a critical role in development, the immune system, and cancer. Using rodent models, here we show that the whole-body SHMT flux acts to net consume rather than produce glycine. Pharmacological inhibition of whole-body SHMT1/2 and genetic knockout of liver SHMT2 elevated circulating glycine levels up to eight-fold. Stable-isotope tracing revealed that the liver converts glycine to serine, which is then converted by serine dehydratase into pyruvate and burned in the tricarboxylic acid cycle. In response to diets deficient in serine and glycine, de novo biosynthetic flux was unaltered, but SHMT2- and serine-dehydratase-mediated catabolic flux was lower. Thus, glucose-derived serine synthesis is largely insensitive to systemic demand. Instead, circulating serine and glycine homeostasis is maintained through variable consumption, with liver SHMT2 a major glycine-consuming enzyme.

Keywords:  SHMT; amino acid metabolism; folate cycle; glycine; hepatic clearance; homeostasis; serine

DOI:  https://doi.org/10.1016/j.cmet.2023.12.001
Anal Chem. 2024 Jan 02.

Absolute Quantification of Human Serum Albumin Isoforms by Internal Calibration Based on a Top-Down LC-MS Approach.

Roy Lakis, François-Ludovic Sauvage, Emilie Pinault, Pierre Marquet, Franck Saint-Marcoux, Souleiman El Balkhi.

Well-characterized biomarkers using reliable quantitative methods are essential for the management of various pathologies such as diabetes, kidney, and liver diseases. Human serum albumin (HSA) isoforms are gaining interest as biomarkers of advanced liver pathologies. In view of the structural alterations observed for HSA, insights into its isoforms are required to establish them as reliable biomarkers. Therefore, a robust absolute quantification method seems necessary. In this study, we developed and validated a far more advanced top-down liquid chromatography-mass spectrometry (LC-MS) method for the absolute quantification of HSA isoforms, using myoglobin (Mb) as an internal standard for quantification and for mass recalibration. Two different quantification approaches were investigated based on peak integration from the deconvoluted spectrum and extracted ion chromatogram (XIC). The protein mixture human serum albumin/myoglobin eluted in well-shaped separated peaks. Mb allowed a systematic mass recalibration for every sample, resulting in extremely low mass deviations compared to conventional deconvolution-based methods. In total, eight HSA isoforms of interest were quantified. Specific-isoform calibration curves showing good linearity were obtained by using the deconvoluted peaks. Noticeably, the HSA ionization behavior appeared to be isoform-dependent, suggesting that the use of an enriched isoform solution as a calibration standard for absolute quantification studies of HSA isoforms is necessary. Good repeatability, reproducibility, and accuracy were observed, with better sensitivity for samples with low albumin concentrations compared to routine biochemical assays. With a relatively simple workflow, the application of this method for absolute quantification shows great potential, especially for HSA isoform studies in a clinical context, where a high-throughput method and sensitivity are needed.

DOI: https://doi.org/10.1021/acs.analchem.3c03933
Sci Rep. 2024 01 02. 14(1): 40

Comparison between ammonium formate and ammonium fluoride in the analysis of stratum corneum lipids by reversed phase chromatography coupled with high resolution mass spectrometry.

Miriam Maiellaro, Grazia Bottillo, Alessia Cavallo, Emanuela Camera.

Lipids are key constituents of the barrier function in the human stratum corneum (SC), which is the outermost layer of the epidermis and amenable to non-invasive sampling by tape stripping. The three major lipid classes in the SC, i.e., ceramides, fatty acids, and cholesterol, present equimolar concentration. Liquid chromatography coupled with mass spectrometry (LCMS) is elective in profiling lipids in the SC in both positive and negative ion modes. Nevertheless, the latter one allows for the simultaneous detection of the three major epidermal components of the SC. Determination of ceramides in the SC poses analytical challenges due to their wide range of structures and concentrations especially in the case of limited sample amounts. Ammonium formate is a commonly used modifier added to the mobile phase to assist ionization. However, it introduces uncertainty in the identification of ceramides when operating in negative ion mode, even with high resolution MS. We tested the advantages of using fluoride in the lipid profiling of SC and unambiguous identification of ceramides subclasses. The use of fluoride enhanced the ionization of ceramides, regardless the specific substructure, solved misidentification issues, and was successfully applied to the simultaneous detection of all three lipid classes in the human SC.

DOI: https://doi.org/10.1038/s41598-023-50051-1
Anal Chem. 2024 Jan 02.

Accelerating Pharmaceutical Process Development with an Acoustic Droplet Ejection-Multiple Reaction Monitoring-Mass Spectrometry Workflow.

Hang Hu, Andrew N Singh, Dan Lehnherr, Velabo Mdluli, Stephanie W Chun, Amanda M Makarewicz, Joseph R Gouker, Ophelia Ukaegbu, Shasha Li, Xiujuan Wen, David G McLaren, Juan E Velasquez, Jeffrey C Moore, Stephanie Galanie, Emmanuel Appiah-Amponsah, Erik L Regalado.

Fast-paced pharmaceutical process developments (e.g., high-throughput experimentation, directed evolution, and machine learning) involve the introduction of fast, sensitive, and accurate analytical assays using limited sample volumes. In recent years, acoustic droplet ejection (ADE) coupled with an open port interface has been invented as a sampling technology for mass spectrometry, providing high-throughput nanoliter analytical measurements directly from the standard microplates. Herein, we introduce an ADE-multiple reaction monitoring-mass spectrometry (ADE-MRM-MS) workflow to accelerate pharmaceutical process research and development (PR&D). This systematic workflow outlines the selection of MRM transitions and optimization of assay parameters in a data-driven manner using rapid measurements (1 sample/s). The synergy between ADE sampling and MRM analysis enables analytical assays with excellent sensitivity, selectivity, and speed for PR&D reaction screenings. This workflow was utilized to develop new ADE-MRM-MS assays guiding a variety of industrial processes, including (1) screening of Ni-based catalysts for C-N cross-coupling reaction at 1 Hz and (2) high-throughput regioisomer analysis-enabled enzyme library screening for peptide ligation reaction. ADE-MRM-MS assays were demonstrated to deliver accurate results that are comparable to conventional liquid chromatography (LC) experiments while providing >100-fold throughput enhancement.

DOI: https://doi.org/10.1021/acs.analchem.3c04211