bims-mascan 2022-08-14 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2022–08–14
28 papers selected by
Giovanny Rodríguez Blanco, University of Edinburgh

Rapid and in-depth coverage of the (phospho-)proteome with deep libraries and optimal window design for dia-PASEF.
Targeted analysis of sugar phosphates from glycolysis pathway by phosphate methylation with liquid chromatography coupled to tandem mass spectrometry.
High-Sensitivity Glycoproteomic Analysis of Biological Samples by CZE-ESI-MS.
Assessing the Energy Status of Low Numbers of Mammalian Cells by Capillary Electrophoresis-Mass Spectrometry.
Reprogrammed Lipid Metabolism and the Lipid-Associated Hallmarks of Colorectal Cancer.
Introducing the Lipidomics Minimal Reporting Checklist.
Biomarker enrichment medium: A defined medium for metabolomic analysis of microbial pathogens.
The adipocyte microenvironment and cancer.
Advanced unified monophasic lipid extraction protocol with wide coverage on the polarity scale optimized for large-scale untargeted clinical lipidomics analysis of platelets.
AI/ML-driven advances in untargeted metabolomics and exposomics for biomedical applications.
Spectral Library-Based Single-Cell Proteomics Resolves Cellular Heterogeneity.
Top-Down Proteomics by Capillary Zone Electrophoresis-Tandem Mass Spectrometry for Large-Scale Characterization of Proteoforms in Complex Samples.
High sensitivity and high-confidence compound identification with a flexible BoxCar acquisition method.
Comprehensive two-dimensional gas chromatography with mass spectrometry: an advanced bioanalytical technique for clinical metabolomics studies.
Connections between metabolism and epigenetics: mechanisms and novel anti-cancer strategy.
Optimization of protein-level tandem mass tag (TMT) labeling conditions in complex samples with top-down proteomics.
Ferroptosis as ultimate target of cancer therapy.
On-line Immobilized Enzyme Microreactor Capillary Zone Electrophoresis-Mass Spectrometry for Peptide Mapping.
Hepatic Metabolic Profiling of Lifelong Exercise Training Rats.
Microfabricated Liquid Junction Capillary Electrophoresis-Mass Spectrometry Interface.
The Differential Metabolic Signature of Breast Cancer Cellular Response to Olaparib Treatment.
In-Source Fragmentation for the Identification of Compounds by CE-ESI-TOF in Human Plasma. L-Proline as Case Study.
Lactate is an epigenetic metabolite that drives survival in model systems of glioblastoma.
Novel Diagnostic Biomarkers for High-Grade Serous Ovarian Cancer Uncovered by Data-Independent Acquisition Mass Spectrometry.
MYC sensitises cells to apoptosis by driving energetic demand.
Native metabolomics identifies the rivulariapeptolide family of protease inhibitors.
Criteria of slope and endogenous level for selection of matrix in the quantitation of endogenous compounds by LC-MS/MS.
Use of In-Sample Calibration Curve approach for quantification of peptides with high resolution Mass Spectrometry.

Mol Cell Proteomics. 2022 Aug 06. pii: S1535-9476(22)00087-1. [Epub ahead of print] 100279

Rapid and in-depth coverage of the (phospho-)proteome with deep libraries and optimal window design for dia-PASEF.

Patricia Skowronek, Marvin Thielert, Eugenia Voytik, Maria C Tanzer, Fynn M Hansen, Sander Willems, Özge Karayel, Andreas-David Brunner, Florian Meier, Matthias Mann.

  Data-independent acquisition (DIA) methods have become increasingly attractive in mass spectrometry (MS)-based proteomics, because they enable high data completeness and a wide dynamic range. Recently, we combined DIA with parallel accumulation - serial fragmentation (dia-PASEF) on a Bruker trapped ion mobility separated (TIMS) quadrupole time-of-flight (TOF) mass spectrometer. This requires alignment of the ion mobility separation with the downstream mass selective quadrupole, leading to a more complex scheme for dia-PASEF window placement compared to DIA. To achieve high data completeness and deep proteome coverage, here we employ variable isolation windows that are placed optimally depending on precursor density in the m/z and ion mobility plane. This Automatic Isolation Design procedure is implemented in the freely available py_diAID package. In combination with in-depth project-specific proteomics libraries and the Evosep LC system, we reproducibly identified over 7,700 proteins in a human cancer cell line in 44 minutes with quadruplicate single-shot injections at high sensitivity. Even at a throughput of 100 samples per day (11 minutes LC gradients), we consistently quantified more than 6,000 proteins in mammalian cell lysates by injecting four replicates. We found that optimal dia-PASEF window placement facilitates in-depth phosphoproteomics with very high sensitivity, quantifying more than 35,000 phosphosites in a human cancer cell line stimulated with an epidermal growth factor (EGF) in triplicate 21 minutes runs. This covers a substantial part of the regulated phosphoproteome with high sensitivity, opening up for extensive systems-biological studies.

Keywords:  PASEF; TIMS; data-independent acquisition; phosphoproteomics; systems biology

DOI:  https://doi.org/10.1016/j.mcpro.2022.100279
Anal Chim Acta. 2022 Aug 15. pii: S0003-2670(22)00670-5. [Epub ahead of print]1221 340099

Targeted analysis of sugar phosphates from glycolysis pathway by phosphate methylation with liquid chromatography coupled to tandem mass spectrometry.

Peng Li, Min Su, Madhumita Chatterjee, Michael Lämmerhofer.

  Monitoring the glycolysis pathway remains an analytical challenge as most metabolites involved are sugar phosphates. Structural similarity, instability, high polarity, and rich negative charges of sugar phosphates make LC-MS based analysis challenging. Here, we developed an improved workflow integrating uniformly 13C-labeled yeast metabolite extract, TiO2-based enrichment, differential stable isotope labeling phosphate methylation, porous graphic carbon column, and selected reaction monitoring acquisition. Uniformly 13C labeled yeast metabolite extract was used as internal standards while differential stable isotope labeled sugar phosphates worked as calibrants. The established method was validated in human plasma, platelet and cultured HeLa cells. The limits of quantification ranged between 0.25 and 0.54 pmol on column. The method was adapted and its applicability tested for human platelets in which activation with collagen-related peptide (CRP) clearly showed the upregulation of some SPx metabolites. The results document that this newly established method can be successfully used to monitor glycolysis in different biological samples. As an extension, more phosphorylated and carboxylated metabolites from the central carbon metabolism (pentose phosphate cycle, TCA cycle) were tested as well. This method showed superior performance, especially for multiple phosphorylated and carboxylated metabolites. For quantitative purpose, the concept of SPx in three sets (12C-analytes, U-13C-IS, deuterated calibrants) has the potential to be adapted for more anionic metabolites.

Keywords:  Derivatization; Isotope labeling; Porous graphitic carbon column; Solid-phase extraction; Sugar phosphate; Targeted metabolomics

DOI:  https://doi.org/10.1016/j.aca.2022.340099
Methods Mol Biol. 2022 ;2531 143-162

High-Sensitivity Glycoproteomic Analysis of Biological Samples by CZE-ESI-MS.

W Wang, G S M Lageveen-Kammeijer.

  Capillary zone electrophoresis-tandem mass spectrometry (CZE-MS/MS) is a powerful tool for the characterization and identification of the macro- and microheterogeneity of a glycoprotein in a bottom-up approach. This chapter describes in detail the sample preparation procedures using a purified biological sample, prostate-specific antigen, as a model protein, including proteolytic digestion (trypsin). In addition, insights are provided into the strengths of using capillary electrophoresis for obtaining isomer separation of differently linked sialic acids. Lastly, approaches and potential pitfalls for the integration and quantitation of glycopeptide signals from the obtained CZE-MS data are discussed.

Keywords:  Bottom-up proteomics; Capillary electrophoresis-mass spectrometry (CE-MS); Data analysis; Glycoform profiling; Glycopeptide analysis; Glycoproteomics; Prostate-specific antigen (PSA)

DOI:  https://doi.org/10.1007/978-1-0716-2493-7_10
Methods Mol Biol. 2022 ;2531 203-209

Assessing the Energy Status of Low Numbers of Mammalian Cells by Capillary Electrophoresis-Mass Spectrometry.

Wei Zhang, Rawi Ramautar.

  Capillary electrophoresis-mass spectrometry (CE-MS) employing a sheathless porous tip interface has become a strong analytical tool for the efficient profiling of highly polar and charged metabolites in volume/material-restricted biological samples. As more and more metabolomics studies are (intrinsically) dealing with low numbers of mammalian cells, it would be important to use an additional performance metric to effectively evaluate the sampling and sample preparation procedure, in particular quenching. An established parameter to assess the sampling and sample preparation quality when working with cell cultures is the adenylate energy charge (AEC), which represents an index of the energy state of a cell. In this protocol, a CE-MS strategy is proposed for the reliable determination of the adenylate energy charge (AEC) in metabolomics studies dealing with low numbers of mammalian cells.

Keywords:  Adenylate energy charge; Biomass-limited samples; Capillary electrophoresis; Mass spectrometry; Metabolic profiling

DOI:  https://doi.org/10.1007/978-1-0716-2493-7_13
Cancers (Basel). 2022 Jul 29. pii: 3714. [Epub ahead of print]14(15):

Reprogrammed Lipid Metabolism and the Lipid-Associated Hallmarks of Colorectal Cancer.

Timothy Salita, Yepy H Rustam, Dmitri Mouradov, Oliver M Sieber, Gavin E Reid.

  Lipids have diverse structures, with multifarious regulatory functions in membrane homeostasis and bioenergetic metabolism, in mediating functional protein-lipid and protein-protein interactions, as in cell signalling and proliferation. An increasing body of evidence supports the notion that aberrant lipid metabolism involving remodelling of cellular membrane structure and changes in energy homeostasis and signalling within cancer-associated pathways play a pivotal role in the onset, progression, and maintenance of colorectal cancer (CRC) and their tumorigenic properties. Recent advances in analytical lipidome analysis technologies have enabled the comprehensive identification and structural characterization of lipids and, consequently, our understanding of the role they play in tumour progression. However, despite progress in our understanding of cancer cell metabolism and lipidomics, the key lipid-associated changes in CRC have yet not been explicitly associated with the well-established 'hallmarks of cancer' defined by Hanahan and Weinberg. In this review, we summarize recent findings that highlight the role of reprogrammed lipid metabolism in CRC and use this growing body of evidence to propose eight lipid metabolism-associated hallmarks of colorectal cancer, and to emphasize their importance and linkages to the established cancer hallmarks.

Keywords:  CRC; cancer hallmarks; colorectal cancer; lipid metabolism; lipids; metabolomics

DOI:  https://doi.org/10.3390/cancers14153714
Nat Metab. 2022 Aug 08.

Introducing the Lipidomics Minimal Reporting Checklist.

Jeffrey G McDonald, Christer S Ejsing, Dominik Kopczynski, Michal Holčapek, Junken Aoki, Makoto Arita, Masanori Arita, Erin S Baker, Justine Bertrand-Michel, John A Bowden, Britta Brügger, Shane R Ellis, Maria Fedorova, William J Griffiths, Xianlin Han, Jürgen Hartler, Nils Hoffmann, Jeremy P Koelmel, Harald C Köfeler, Todd W Mitchell, Valerie B O'Donnell, Daisuke Saigusa, Dominik Schwudke, Andrej Shevchenko, Candice Z Ulmer, Markus R Wenk, Michael Witting, Denise Wolrab, Yu Xia, Robert Ahrends, Gerhard Liebisch, Kim Ekroos.

DOI: https://doi.org/10.1038/s42255-022-00628-3
Front Microbiol. 2022 ;13 957158

Biomarker enrichment medium: A defined medium for metabolomic analysis of microbial pathogens.

Maryam Mapar, Thomas Rydzak, Ryan A Groves, Ian A Lewis.

  Microbes have diverse metabolic capabilities and differences in these phenotypes are critical for differentiating strains, species, and broader taxa of microorganisms. Recent advances in liquid chromatography-mass spectrometry (LC-MS) allow researchers to track the complex combinations of molecules that are taken up by each cell type and to quantify the rates that individual metabolites enter or exit the cells. This metabolomics-based approach allows complex metabolic phenotypes to be captured in a single assay, enables computational models of microbial metabolism to be constructed, and can serve as a diagnostic approach for clinical microbiology. Unfortunately, metabolic phenotypes are directly affected by the molecular composition of the culture medium and many traditional media are subject to molecular-level heterogeneity. Herein, we show that commercially sourced Mueller Hinton (MH) medium, a Clinical and Laboratory Standards Institute (CLSI) approved medium for clinical microbiology, has significant lot-to-lot and supplier-to-supplier variability in the concentrations of individual nutrients. We show that this variability does not affect microbial growth rates but does affect the metabolic phenotypes observed in vitro-including metabolic phenotypes that distinguish six common pathogens. To address this, we used a combination of isotope-labeling, substrate exclusion, and nutritional supplementation experiments using Roswell Park Memorial Institute (RPMI) medium to identify the specific nutrients used by the microbes to produce diagnostic biomarkers, and to formulate a Biomarker Enrichment Medium (BEM) as an alternative to complex undefined media for metabolomics research, clinical diagnostics, antibiotic susceptibility testing, and other applications where the analysis of stable microbial metabolic phenotypes is important.

Keywords:  LC-MS; Mueller Hinton; biomarker enrichment medium; biomarkers; metabolomics

DOI:  https://doi.org/10.3389/fmicb.2022.957158
Cancer Metastasis Rev. 2022 Aug 08.

The adipocyte microenvironment and cancer.

Abir Mukherjee, Agnes J Bilecz, Ernst Lengyel.

  Many epithelial tumors grow in the vicinity of or metastasize to adipose tissue. As tumors develop, crosstalk between adipose tissue and cancer cells leads to changes in adipocyte function and paracrine signaling, promoting a microenvironment that supports tumor growth. Over the last decade, it became clear that tumor cells co-opt adipocytes in the tumor microenvironment, converting them into cancer-associated adipocytes (CAA). As adipocytes and cancer cells engage, a metabolic symbiosis ensues that is driven by bi-directional signaling. Many cancers (colon, breast, prostate, lung, ovarian cancer, and hematologic malignancies) stimulate lipolysis in adipocytes, followed by the uptake of fatty acids (FA) from the surrounding adipose tissue. The FA enters the cancer cell through specific fatty acid receptors and binding proteins (e.g., CD36, FATP1) and are used for membrane synthesis, energy metabolism (β-oxidation), or lipid-derived cell signaling molecules (derivatives of arachidonic and linolenic acid). Therefore, blocking adipocyte-derived lipid uptake or lipid-associated metabolic pathways in cancer cells, either with a single agent or in combination with standard of care chemotherapy, might prove to be an effective strategy against cancers that grow in lipid-rich tumor microenvironments.

Keywords:  Adipose tissue; Cancer; Immune cells; Lipids; Metabolism; Metastasis

DOI:  https://doi.org/10.1007/s10555-022-10059-x
Anal Chim Acta. 2022 Aug 15. pii: S0003-2670(22)00726-7. [Epub ahead of print]1221 340155

Advanced unified monophasic lipid extraction protocol with wide coverage on the polarity scale optimized for large-scale untargeted clinical lipidomics analysis of platelets.

Xiaoqing Fu, Carlos Calderón, Tobias Harm, Meinrad Gawaz, Michael Lämmerhofer.

  Lipid extraction is a critical step in sample preparation of lipidomics studies. Biphasic liquid-liquid extraction protocol with methyl tert-butyl ether (MTBE)/methanol (MeOH) as organic solvents are widely adopted by researchers nowadays as an eco-friendly replacement of classic Folch, and Bligh&Dyer protocols. Yet, it has some limitations such as suboptimal performance for the most polar lipids (e.g. acylcarnitines), complicated handling as it requires phase separation, and is therefore non-ideal for large-scale clinical studies. To advance the extraction protocol for large-scale clinical lipidomics, in this study we explored i) 6 different extraction solvent systems, ii) distinct processing procedures (sonication, mechanical cell lysis and bead homogenizer), and iii) also 7 different reconstitution solvents. The extraction systems investigated included biphasic systems MTBE/MeOH/H2O and Hexane/2-propanol (IPA)/1 M acetic acid, and monophasic systems MTBE/MeOH/CHCl3, IPA/H2O (90% IPA), MeOH/MTBE/IPA, and IPA/H2O/MTBE as solvent system for lipid extraction of human platelets. Extraction recovery was investigated by repeated extraction cycles. Subcellular extraction efficiency was assessed by the mitochondria-specific cardiolipins. It turned out that monophasic extraction with MeOH/MTBE/IPA (1.3:1:1, v/v/v), bead homogenizer for cell disruption and MeOH/MTBE (1:1, v/v) as reconstitution solvent provide optimal cellular and subcellular extraction efficiencies for both polar (e.g. acylcarnitines) and apolar lipids (e.g. triglycerides). It is simplified (no phase separation), eco-friendly (reduced solvent consumption and no halogenated ones), fast (5 min for 24 samples in parallel), and can be easily adapted for cells, plasma, and tissue. Therefore, it has great potential for large-scale clinical lipidomics studies.

Keywords:  Cell lysis; Cellular/subcellular lipid extraction; Clinical analysis; Green technology; Lipidomics; Monophasic lipid extraction

DOI:  https://doi.org/10.1016/j.aca.2022.340155
Cell Rep Phys Sci. 2022 Jul 20. pii: 100978. [Epub ahead of print]3(7):

AI/ML-driven advances in untargeted metabolomics and exposomics for biomedical applications.

Lauren M Petrick, Noam Shomron.

Metabolomics describes a high-throughput approach for measuring a repertoire of metabolites and small molecules in biological samples. One utility of untargeted metabolomics, unbiased global analysis of the metabolome, is to detect key metabolites as contributors to, or readouts of, human health and disease. In this perspective, we discuss how artificial intelligence (AI) and machine learning (ML) have promoted major advances in untargeted metabolomics workflows and facilitated pivotal findings in the areas of disease screening and diagnosis. We contextualize applications of AI and ML to the emerging field of high-resolution mass spectrometry (HRMS) exposomics, which unbiasedly detects endogenous metabolites and exogenous chemicals in human tissue to characterize exposure linked with disease outcomes. We discuss the state of the science and suggest potential opportunities for using AI and ML to improve data quality, rigor, detection, and chemical identification in untargeted metabolomics and exposomics studies.

DOI: https://doi.org/10.1016/j.xcrp.2022.100978
Cells. 2022 Aug 07. pii: 2450. [Epub ahead of print]11(15):

Spectral Library-Based Single-Cell Proteomics Resolves Cellular Heterogeneity.

Lakmini Senavirathna, Cheng Ma, Ru Chen, Sheng Pan.

  Dissecting the proteome of cell types and states at single-cell resolution, while being highly challenging, has significant implications in basic science and biomedicine. Mass spectrometry (MS)-based single-cell proteomics represents an emerging technology for system-wide, unbiased profiling of proteins in single cells. However, significant challenges remain in analyzing an extremely small amount of proteins collected from a single cell, as a proteome-wide amplification of proteins is not currently feasible. Here, we report an integrated spectral library-based single-cell proteomics (SLB-SCP) platform that is ultrasensitive and well suited for a large-scale analysis. To overcome the low MS/MS signal intensity intrinsically associated with a single-cell analysis, this approach takes an alternative approach by extracting a breadth of information that specifically defines the physicochemical characteristics of a peptide from MS1 spectra, including monoisotopic mass, isotopic distribution, and retention time (hydrophobicity), and uses a spectral library for proteomic identification. This conceptually unique MS platform, coupled with the DIRECT sample preparation method, enabled identification of more than 2000 proteins in a single cell to distinguish different proteome landscapes associated with cellular types and heterogeneity. We characterized individual normal and cancerous pancreatic ductal cells (HPDE and PANC-1, respectively) and demonstrated the substantial difference in the proteomes between HPDE and PANC-1 at the single-cell level. A significant upregulation of multiple protein networks in cancer hallmarks was identified in the PANC-1 cells, functionally discriminating the PANC-1 cells from the HPDE cells. This integrated platform can be built on high-resolution MS and widely accepted proteomic software, making it possible for community-wide applications.

Keywords:  cellular heterogeneity; mass spectrometry; proteomics; single-cell proteomics; spectral library; systems biology

DOI:  https://doi.org/10.3390/cells11152450
Methods Mol Biol. 2022 ;2531 107-124

Top-Down Proteomics by Capillary Zone Electrophoresis-Tandem Mass Spectrometry for Large-Scale Characterization of Proteoforms in Complex Samples.

Elijah N McCool, Rachele A Lubeckyj, Daoyang Chen, Liangliang Sun.

  Capillary zone electrophoresis (CZE) is a fundamentally simple and highly efficient separation technique based on differences in electrophoretic mobilities of analytes. CZE-mass spectrometry (MS) has become an important analytical tool in top-down proteomics which aims to delineate proteoforms in cells comprehensively, because of the improvement of capillary coatings, sample stacking methods, and CE-MS interfaces. Here, we present a CZE-MS/MS-based top-down proteomics procedure for the characterization of a standard protein mixture and an Escherichia coli (E. coli) cell lysate using linear polyacrylamide-coated capillaries, a dynamic pH junction sample stacking method, a commercialized electro-kinetically pumped sheath flow CE-MS interface and an Orbitrap mass spectrometer. CZE-MS/MS can identify hundreds of proteoforms routinely from the E. coli sample with a 1% proteoform-level false discovery rate (FDR).

Keywords:  Analytical method; CE-MS interface; Capillary zone electrophoresis; Dynamic pH junction; Linear polyacrylamide coating; Mass spectrometry; Proteoform; Separation; Top-down proteomics

DOI:  https://doi.org/10.1007/978-1-0716-2493-7_8
J Pharm Biomed Anal. 2022 Jul 29. pii: S0731-7085(22)00394-6. [Epub ahead of print]219 114973

High sensitivity and high-confidence compound identification with a flexible BoxCar acquisition method.

Jikang Wu, Hongxia Wang, Xueqing Zhao, Haibo Qiu, Ning Li.

  Liquid chromatography-mass spectrometry (LC-MS) is in wide use for compound identification and quantification in complex matrices. While advances in mass spectrometry and the incorporation of new acquisition methods have resulted in greatly improved detection, there is an ongoing need to expand the limits of highly sensitive and confident identification of low abundance species in complex samples. The data acquisition method known as "BoxCar" was originally designed to achieve in-depth proteome profiling on an Orbitrap mass analyzer by decomposing ions into segments with narrow m/z windows. Using this method, selected segments are packaged in C-trap and all ions are then sent to Orbitrap for detection. In this study, we developed a flexible BoxCar acquisition method by placing more segments in the low m/z range for small molecule profiling. This new MS1 acquisition method was successfully integrated with iterative data dependent MS/MS acquisition by generating an inclusion list of ions detected in the flexible BoxCar to trigger the fragmentation of parent ions. The developed acquisition method was applied to the analysis of cell culture media, which plays a key role in antibody production. This challenging goal is of critical importance, as none of the currently available methods provide a comprehensive understanding of how individual components, metabolites, and impurities associated with the cell culture process might influence recombinant antibody production. Even when present at relatively low abundance, some components or impurities in the cell culture medium could have a profound impact on the quality and titer of the antibodies produced. The complex soy hydrolysate cell culture medium used in antibody generation has not been fully characterized. Using the developed flexible BoxCar acquisition method, we achieved 90 % higher sensitivity in experiments designed to detect spiked chemical substances at low abundance at the MS1 level compared to the full scan method. Iterative data-dependent acquisition (DDA) based on the targeted inclusion list generated much higher quality MS2 spectra and facilitated confident identification of low-abundance compounds. Our method achieved a 50 % increase in MS2 coverage of compounds present at low concentrations compared to conventional DDA methods. The results of our study demonstrate that this data acquisition workflow can be easily operated on Orbitrap mass spectrometers and used as a highly effective approach to improve sensitivity and high-confidence small molecule profiling in soy hydrolysate-based cell culture medium and thus provides significant support for therapeutic monoclonal antibody production.

Keywords:  Cell culture medium; Flexible BoxCar; Iterative data-dependent acquisition; Mass spectrometry; Small-molecule profiling; Soy hydrolysate

DOI:  https://doi.org/10.1016/j.jpba.2022.114973
Analyst. 2022 Aug 12.

Comprehensive two-dimensional gas chromatography with mass spectrometry: an advanced bioanalytical technique for clinical metabolomics studies.

Atiqah Zaid, Mohammad Sharif Khan, Dandan Yan, Philip J Marriott, Yong Foo Wong.

The detection of human-derived metabolites as potential diagnostic biomarkers of genetic disorders, metabolic diseases, systemic diseases, and infectious diseases has been much studied in recent years, especially as technical capabilities improve, and statistical procedures are increasingly able to tease critical chemical attributes from complex data sets. Given the complex distribution of human biological matrices, the characterization and/or identification of these chemical entities is technically challenging, and is often confounded by incomplete chromatographic resolution or insufficient discriminatory power of the mass spectrometry (MS) domain. Recently, comprehensive two-dimensional gas chromatography (GC×GC) has evolved into a mature higher separation order technique that offers unprecedented resolving power, which in turn can greatly advantage clinical metabolomics studies via the expansion of metabolite coverage. In this contribution, the current state of knowledge in the development of GC×GC coupled to MS as a high-resolution bioanalytical technique for the analysis of clinical metabolites is reviewed. Selected recent applications (years 2012 to 2021) that emphasize improved GC×GC-MS strategies for clinical human metabolites' detection, identification, and quantitative analysis are described. In addition, we share our perspectives on current challenges and potential future directions of GC×GC in clinical applications.

DOI: https://doi.org/10.1039/d2an00584k
Front Pharmacol. 2022 ;13 935536

Connections between metabolism and epigenetics: mechanisms and novel anti-cancer strategy.

Chen Chen, Zehua Wang, Yanru Qin.

  Cancer cells undergo metabolic adaptations to sustain their growth and proliferation under several stress conditions thereby displaying metabolic plasticity. Epigenetic modification is known to occur at the DNA, histone, and RNA level, which can alter chromatin state. For almost a century, our focus in cancer biology is dominated by oncogenic mutations. Until recently, the connection between metabolism and epigenetics in a reciprocal manner was spotlighted. Explicitly, several metabolites serve as substrates and co-factors of epigenetic enzymes to carry out post-translational modifications of DNA and histone. Genetic mutations in metabolic enzymes facilitate the production of oncometabolites that ultimately impact epigenetics. Numerous evidences also indicate epigenome is sensitive to cancer metabolism. Conversely, epigenetic dysfunction is certified to alter metabolic enzymes leading to tumorigenesis. Further, the bidirectional relationship between epigenetics and metabolism can impact directly and indirectly on immune microenvironment, which might create a new avenue for drug discovery. Here we summarize the effects of metabolism reprogramming on epigenetic modification, and vice versa; and the latest advances in targeting metabolism-epigenetic crosstalk. We also discuss the principles linking cancer metabolism, epigenetics and immunity, and seek optimal immunotherapy-based combinations.

Keywords:  cancer metabolism; epigenetics; immunity; novel anti-cancer strategy; oncology

DOI:  https://doi.org/10.3389/fphar.2022.935536
Anal Chim Acta. 2022 Aug 15. pii: S0003-2670(22)00608-0. [Epub ahead of print]1221 340037

Optimization of protein-level tandem mass tag (TMT) labeling conditions in complex samples with top-down proteomics.

Yanting Guo, Dahang Yu, Kellye A Cupp-Sutton, Xiaowen Liu, Si Wu.

  Isobaric chemical tag labels (e.g., iTRAQ and TMT) have been extensively utilized as a standard quantification approach in bottom-up proteomics, which provides high multiplexing capacity and enables MS2-level quantification while not complicating the MS1 scans. We recently demonstrated the feasibility of intact protein TMT labeling for the identification and quantification with top-down proteomics of smaller intact proteoforms (<35 kDa) in complex biological samples through the removal of large proteins prior to labeling. Still, the production of side products during TMT labeling (i.e., incomplete labeling or labeling of unintended residues) complicated the analysis of complex protein samples. In this study, we systematically evaluated the protein-level TMT labeling reaction parameters, including TMT-to-protein mass ratio, pH/concentration of quenching buffer, protein concentration, reaction time, and reaction buffer. Our results indicated that: (1) high TMT-to-protein mass ratio (e.g., 8:1, 4:1), (2) high pH/concentration of quenching buffer (pH > 9.1, final hydroxylamine concentration >0.3%), and (3) high protein concentration (e.g., > 1.0 μg/μL) resulted in optimal labeling efficiency and minimized production of over/underlabeled side products. >90% labeling efficiency was achieved for E. coli cell lysate after optimization of protein-level TMT labeling conditions. In addition, a double labeling approach was developed for efficiently labeling limited biological samples with low concentrations. This research provides practical guidance for efficient TMT labeling of complex intact protein samples, which can be readily adopted in the high-throughput quantification top-down proteomics.

Keywords:  Isobaric labeling; Quantitative proteomics; Tandem mass tags (TMT); Top-down proteomics

DOI:  https://doi.org/10.1016/j.aca.2022.340037
Antioxid Redox Signal. 2022 Aug 09.

Ferroptosis as ultimate target of cancer therapy.

Yashiro Motooka, Shinya Toyokuni.

Ferroptosis is a new form of regulated non-apoptotic cell death, which is characterized by iron-dependent lipid peroxidation, leading eventually to plasma membrane rupture. Its core mechanisms have been elucidated consisting of a driving force as catalytic Fe(II)-dependent Fenton reaction and an incorporation of polyunsaturated fatty acids to membrane phospholipids via peroxisome-dependent and -independent pathways, whereas suppressing factors are the prevention of lipid peroxidation by glutathione peroxidase 4 to protect lipid peroxidation and direct membrane repair via coenzyme Q10 and ESCRT-III pathways. The significance of ferroptosis in cancer therapeutics has now been unveiled. Specific ferroptosis inducers are expected as a promising strategy for cancer treatment, especially in cancers with epithelial mesenchymal transition and possibly in cancers with activated Hippo signaling pathways, both of which cause resistance to traditional chemotherapy but tend to show ferroptosis susceptibility. Developments of ferroptosis inducers are in progress by nanotechnology-based drugs or by innovative engineering devices. Especially, low-temperature (non-thermal) plasma is a novel technology at the preclinical stage. The exposure can induce ferroptosis selectively in cancer cells which are generally rich in catalytic Fe(II). Here we summarize and discuss the recently uncovered responsible molecular mechanisms in association with iron metabolism, ferroptosis and cancer therapeutics. Finally, we also highlight the current classification of ferroptosis inducers.

DOI: https://doi.org/10.1089/ars.2022.0048
Methods Mol Biol. 2022 ;2531 77-91

On-line Immobilized Enzyme Microreactor Capillary Zone Electrophoresis-Mass Spectrometry for Peptide Mapping.

Roger Pero-Gascon, Laura Pont, Estela Giménez, Victoria Sanz-Nebot, Fernando Benavente.

  Peptide mapping is a routine procedure for protein characterization in proteomics. This bottom-up analysis requires digestion of proteins into peptides before liquid chromatography- or capillary zone electrophoresis-mass spectrometry (LC-MS or CZE-MS, respectively). Proteins are usually digested off-line using proteolytic enzymes, typically trypsin, in solution or immobilized on appropriate supports. As an alternative, here we describe on-line immobilized enzyme microreactor capillary zone electrophoresis-mass spectrometry (IMER-CZE-MS) for a straightforward, rapid, and efficient protein digestion followed by separation, detection, and characterization of the generated peptides.

Keywords:  Bottom-up proteomics; Capillary zone electrophoresis; Immobilized enzyme; In-line; Mass spectrometry; Microcartridge; Microreactor; On-line

DOI:  https://doi.org/10.1007/978-1-0716-2493-7_6
J Proteome Res. 2022 Aug 08.

Hepatic Metabolic Profiling of Lifelong Exercise Training Rats.

Dimitra Diamantidou, Olga Deda, Ioannis Zervos, Ioannis Taitzoglou, Helen Gika, Georgios Theodoridis, Filippos Michopoulos.

  Regular physical exercise has been investigated as a primary preventive measure of several chronic diseases and premature death. Moreover, it has been shown to synchronize responses across multiple organs. In particular, hepatic tissue has proven to be a descriptive matrix to monitor the effect of physical activity. In this study, we performed an untargeted metabolomics-based analysis of hepatic tissue extracts from rats that have undergone either lifelong or chronic exercise training. For this purpose, 56 hepatic samples were collected and were analyzed by UHPLC-TOF-MS in negative ionization mode. This approach involved untargeted metabolite detection on hepatic tissue extracts accompanied by an in-house retention time/accurate mass library enabling confident metabolite identification. Unsupervised (PCA) and supervised (OPLS-DA) multivariate analysis showed significant metabolic perturbation on a panel of 28 metabolites, including amino acids, vitamins, nucleotides, and sugars. The training regime employed in this study resulted in a probable acceleration of the bioenergetic processes (glycolysis, glycogen metabolism), promoted catabolism of purines, and supplied biosynthetic precursors via the pentose phosphate pathway and pentose and glucuronate interconversions. Overall, the applied methodology was able to discriminate the different training schedules based on the rat liver metabolome.

Keywords:  UHPLC-TOF-MS; biomarker discovery; exercise; metabolic profiling; metabolomics; rats

DOI:  https://doi.org/10.1021/acs.jproteome.2c00094
Methods Mol Biol. 2022 ;2531 61-68

Microfabricated Liquid Junction Capillary Electrophoresis-Mass Spectrometry Interface.

Jana Krenkova, Frantisek Foret.

  Coupling of capillary electrophoresis (CE) with mass spectrometry (MS) represents a powerful combination for performing rapid, efficient, and sensitive analysis of a variety of compounds. Here we describe a construction, operation, and application of a microfabricated liquid junction CE-MS interface. The interface is designed as a microfabricated unit with an integrated liquid junction and electrospray tip made from polyimide, which is positioned in a plastic connection block securing the separation CE capillary and attachable to the CE instrument. The application was demonstrated by CE-MS analysis of dextran oligomers labeled by (2-aminoethyl)trimethylammonium (AETMA) salt.

Keywords:  CE-MS interface; Capillary electrophoresis; Liquid junction; Mass spectrometry

DOI:  https://doi.org/10.1007/978-1-0716-2493-7_4
Cancers (Basel). 2022 Jul 27. pii: 3661. [Epub ahead of print]14(15):

The Differential Metabolic Signature of Breast Cancer Cellular Response to Olaparib Treatment.

Domenica Berardi, Yasmin Hunter, Lisa van den Driest, Gillian Farrell, Nicholas J W Rattray, Zahra Rattray.

  Metabolic reprogramming and genomic instability are key hallmarks of cancer, the combined analysis of which has gained recent popularity. Given the emerging evidence indicating the role of oncometabolites in DNA damage repair and its routine use in breast cancer treatment, it is timely to fingerprint the impact of olaparib treatment in cellular metabolism. Here, we report the biomolecular response of breast cancer cell lines with DNA damage repair defects to olaparib exposure. Following evaluation of olaparib sensitivity in breast cancer cell lines, we immunoprobed DNA double strand break foci and evaluated changes in cellular metabolism at various olaparib treatment doses using untargeted mass spectrometry-based metabolomics analysis. Following identification of altered features, we performed pathway enrichment analysis to measure key metabolic changes occurring in response to olaparib treatment. We show a cell-line-dependent response to olaparib exposure, and an increased susceptibility to DNA damage foci accumulation in triple-negative breast cancer cell lines. Metabolic changes in response to olaparib treatment were cell-line and dose-dependent, where we predominantly observed metabolic reprogramming of glutamine-derived amino acids and lipids metabolism. Our work demonstrates the effectiveness of combining molecular biology and metabolomics studies for the comprehensive characterisation of cell lines with different genetic profiles. Follow-on studies are needed to map the baseline metabolism of breast cancer cells and their unique response to drug treatment. Fused with genomic and transcriptomics data, such readout can be used to identify key oncometabolites and inform the rationale for the design of novel drugs or chemotherapy combinations.

Keywords:  DNA damage; breast cancer; metabolic reprogramming; oncometabolites; precision medicine; triple-negative

DOI:  https://doi.org/10.3390/cancers14153661
Methods Mol Biol. 2022 ;2531 185-202

In-Source Fragmentation for the Identification of Compounds by CE-ESI-TOF in Human Plasma. L-Proline as Case Study.

Maricruz Mamani-Huanca, Ana Gradillas, Ángeles López-Gonzálvez, Coral Barbas.

  One of the aims of untargeted metabolomics is searching for selective biomarkers of different pathophysiological conditions. Modified amino acids originated from the posttranslational modification of proteins play a key role as potential biomarkers; however, they are very often still classified as unknown after metabolite annotation. We have developed an analytical workflow for the targeted screening of these compounds using CE-ESI-MS. The workflow is based on the in-source fragmentation of molecules that produces diagnostic ions that we have collected in an open-source library. In this chapter, we describe in detail the strategy for the targeted screening of modified amino acids (MAAs), using as an example L-proline and its modified derivatives. We illustrate the strategy with two case studies in human plasma.

Keywords:  Diagnostic ion; Identification; In-source fragmentation; Modified L-prolines

DOI:  https://doi.org/10.1007/978-1-0716-2493-7_12
Mol Cell. 2022 Aug 09. pii: S1097-2765(22)00647-5. [Epub ahead of print]

Lactate is an epigenetic metabolite that drives survival in model systems of glioblastoma.

Consuelo Torrini, Trang Thi Thu Nguyen, Chang Shu, Angeliki Mela, Nelson Humala, Aayushi Mahajan, Erin Heather Seeley, Guoan Zhang, Mike-Andrew Westhoff, Georg Karpel-Massler, Jeffrey N Bruce, Peter Canoll, Markus D Siegelin.

  Lactate accumulates to a significant amount in glioblastomas (GBMs), the most common primary malignant brain tumor with an unfavorable prognosis. However, it remains unclear whether lactate is metabolized by GBMs. Here, we demonstrated that lactate rescued patient-derived xenograft (PDX) GBM cells from nutrient-deprivation-mediated cell death. Transcriptome analysis, ATAC-seq, and ChIP-seq showed that lactate entertained a signature of oxidative energy metabolism. LC/MS analysis demonstrated that U-13C-lactate elicited substantial labeling of TCA-cycle metabolites, acetyl-CoA, and histone protein acetyl-residues in GBM cells. Lactate enhanced chromatin accessibility and histone acetylation in a manner dependent on oxidative energy metabolism and the ATP-citrate lyase (ACLY). Utilizing orthotopic PDX models of GBM, a combined tracer experiment unraveled that lactate carbons were substantially labeling the TCA-cycle metabolites. Finally, pharmacological blockage of oxidative energy metabolism extended overall survival in two orthotopic PDX models in mice. These results establish lactate metabolism as a novel druggable pathway for GBM.

Keywords:  ATAC-seq; ChIP-seq; glioblastoma; lactate; metabolic flux analysis; tumor metabolism

DOI:  https://doi.org/10.1016/j.molcel.2022.06.030
J Proteome Res. 2022 Aug 08.

Novel Diagnostic Biomarkers for High-Grade Serous Ovarian Cancer Uncovered by Data-Independent Acquisition Mass Spectrometry.

Sunghyun Huh, Chaewon Kang, Ji Eun Park, Dowoon Nam, Se Ik Kim, Aeran Seol, Kyerim Choi, Daehee Hwang, Myeong-Hee Yu, Hyun Hoon Chung, Sang-Won Lee, Un-Beom Kang.

  High-grade serous ovarian cancer (HGSOC) represents the major histological type of ovarian cancer, and the lack of effective screening tools and early detection methods significantly contributes to the poor prognosis of HGSOC. Currently, there are no reliable diagnostic biomarkers for HGSOC. In this study, we performed liquid chromatography data-independent acquisition tandem mass spectrometry (MS) on depleted serum samples from 26 HGSOC cases and 24 healthy controls (HCs) to discover potential HGSOC diagnostic biomarkers. A total of 1,847 proteins were identified across all samples, among which 116 proteins showed differential expressions between HGSOC patients and HCs. Network modeling showed activations of coagulation and complement cascades, platelet activation and aggregation, neutrophil extracellular trap formation, toll-like receptor 4, insulin-like growth factor, and transforming growth factor β signaling, as well as suppression of lipoprotein assembly and Fc gamma receptor activation in HGSOC. Based on the network model, we prioritized 28 biomarker candidates and validated 18 of them using targeted MS assays in an independent cohort. Predictive modeling showed a sensitivity of 1 and a specificity of 0.91 in the validation cohort. Finally, in vitro functional assays on four potential biomarkers (FGA, VWF, ARHGDIB, and SERPINF2) suggested that they may play an important role in cancer cell proliferation and migration in HGSOC. All raw data were deposited in PRIDE (PXD033169).

Keywords:  data-independent acquisition; high-grade serous ovarian cancer; mass spectrometry; proteomics; serum biomarker

DOI:  https://doi.org/10.1021/acs.jproteome.2c00218
Nat Commun. 2022 Aug 09. 13(1): 4674

MYC sensitises cells to apoptosis by driving energetic demand.

Joy Edwards-Hicks, Huizhong Su, Maurizio Mangolini, Kubra K Yoneten, Jimi Wills, Giovanny Rodriguez-Blanco, Christine Young, Kevin Cho, Heather Barker, Morwenna Muir, Ania Naila Guerrieri, Xue-Feng Li, Rachel White, Piotr Manasterski, Elena Mandrou, Karen Wills, Jingyu Chen, Emily Abraham, Kianoosh Sateri, Bin-Zhi Qian, Peter Bankhead, Mark Arends, Noor Gammoh, Alex von Kriegsheim, Gary J Patti, Andrew H Sims, Juan Carlos Acosta, Valerie Brunton, Kamil R Kranc, Maria Christophorou, Erika L Pearce, Ingo Ringshausen, Andrew J Finch.

The MYC oncogene is a potent driver of growth and proliferation but also sensitises cells to apoptosis, which limits its oncogenic potential. MYC induces several biosynthetic programmes and primary cells overexpressing MYC are highly sensitive to glutamine withdrawal suggesting that MYC-induced sensitisation to apoptosis may be due to imbalance of metabolic/energetic supply and demand. Here we show that MYC elevates global transcription and translation, even in the absence of glutamine, revealing metabolic demand without corresponding supply. Glutamine withdrawal from MRC-5 fibroblasts depletes key tricarboxylic acid (TCA) cycle metabolites and, in combination with MYC activation, leads to AMP accumulation and nucleotide catabolism indicative of energetic stress. Further analyses reveal that glutamine supports viability through TCA cycle energetics rather than asparagine biosynthesis and that TCA cycle inhibition confers tumour suppression on MYC-driven lymphoma in vivo. In summary, glutamine supports the viability of MYC-overexpressing cells through an energetic rather than a biosynthetic mechanism.

DOI: https://doi.org/10.1038/s41467-022-32368-z
Nat Commun. 2022 Aug 08. 13(1): 4619

Native metabolomics identifies the rivulariapeptolide family of protease inhibitors.

Raphael Reher, Allegra T Aron, Pavla Fajtová, Paolo Stincone, Berenike Wagner, Alicia I Pérez-Lorente, Chenxi Liu, Ido Y Ben Shalom, Wout Bittremieux, Mingxun Wang, Kyowon Jeong, Marie L Matos-Hernandez, Kelsey L Alexander, Eduardo J Caro-Diaz, C Benjamin Naman, J H William Scanlan, Phil M M Hochban, Wibke E Diederich, Carlos Molina-Santiago, Diego Romero, Khaled A Selim, Peter Sass, Heike Brötz-Oesterhelt, Chambers C Hughes, Pieter C Dorrestein, Anthony J O'Donoghue, William H Gerwick, Daniel Petras.

The identity and biological activity of most metabolites still remain unknown. A bottleneck in the exploration of metabolite structures and pharmaceutical activities is the compound purification needed for bioactivity assignments and downstream structure elucidation. To enable bioactivity-focused compound identification from complex mixtures, we develop a scalable native metabolomics approach that integrates non-targeted liquid chromatography tandem mass spectrometry and detection of protein binding via native mass spectrometry. A native metabolomics screen for protease inhibitors from an environmental cyanobacteria community reveals 30 chymotrypsin-binding cyclodepsipeptides. Guided by the native metabolomics results, we select and purify five of these compounds for full structure elucidation via tandem mass spectrometry, chemical derivatization, and nuclear magnetic resonance spectroscopy as well as evaluation of their biological activities. These results identify rivulariapeptolides as a family of serine protease inhibitors with nanomolar potency, highlighting native metabolomics as a promising approach for drug discovery, chemical ecology, and chemical biology studies.

DOI: https://doi.org/10.1038/s41467-022-32016-6
Bioanalysis. 2022 Jun;14(11): 807-816

Criteria of slope and endogenous level for selection of matrix in the quantitation of endogenous compounds by LC-MS/MS.

Allena Ji Ji, Guangxin Xu, Lin Tao, Hongqin Jenny Jiao, Rachel Elisabeth Palmer.

  Selection of the appropriate matrix for standard curve is critical for an accurate and sensitive biomarker method. Slope of a standard curve is the key factor for parallelism assessment between tested matrix and authentic matrix for LC-MS/MS assays. Here the authors have established slope criteria using a generic equation and endogenous level criteria for achieving assay sensitivity. The slope difference criterion is from -13.0 to +17.6% for LC-MS assays with ± 15% bias criteria. When the ratio of endogenous concentration in the tested matrix to the lower limit of quantitation is <4.0, the lower limit of quantitation is achievable. If these criteria are met, the tested matrix can be used for assays. The utility of the two criteria has been illustrated with case studies.

Keywords:  LC-MS; background subtraction method; biomarker; endogenous level criterion; parallelism; pharmacokinetic assay; relative matrix effect; slope acceptance criterion; surrogate matrix

DOI:  https://doi.org/10.4155/bio-2022-0066
Rapid Commun Mass Spectrom. 2022 Aug 08. e9377

Use of In-Sample Calibration Curve approach for quantification of peptides with high resolution Mass Spectrometry.

Soumya Kandi, John P Savaryn, Qin C Ji, Gary J Jenkins.

Rationale In-sample calibration curve (ISCC) approach of quantification utilizes response of isotopologue ions from spiked-in stable isotope labeled internal standard (SIL-IS) to build standard curve. The quantitative analysis of the study sample is achieved based on the response of selected monoisotopic analyte ion against the calibration curve. Although, this methodology has been demonstrated to be feasible by unit and high-resolution mass spectrometers (HRMS), quantitation on HRMS with product ions has not been tested. We tested the feasibility of this approach using product ions on a HRMS on an orbitrap detector.
METHODS: Using a proteomics workflow for sample preparation, two surrogate peptides were quantified from a complex matrix of protein digest from human peripheral blood mononuclear cells (hPBMCs). SIL-IS were spiked in at different levels to construct calibration curves in a traditional sense. ISCCs were prepared using extracted ion chromatograms from isotopically resolved mass spectra and compared with traditional calibration curves.
RESULTS: A linear response was observed with ISCC approach for at least 2-3 orders of magnitude in MS1 as well as targeted MS2 (tMS2). From protein digests, isobaric interferences were observed for endogenous peptides on the MS1 level; this was circumvented with product ion-based quantitation where for one peptide, %CV for endogenous levels was < 20% with ISCC, but higher with traditional calibration curve approach. For the second peptide, endogenous levels could not be determined in the traditional approach as calibrant levels did not bracket the lower end and with the ISCC approach, isotopologues at abundances lower than endogenous level allowed for quantitative assessments.
CONCLUSIONS: ISCC demonstrated improved precision across surrogate peptides from endogenous protein digests. In samples where endogenous analyte concentrations were low in abundance, ISCC rescued what would have been a non-reportable result in a traditional bioanalytical assay as calibrant levels were not prepared at adequately low levels to bracket unknowns. ISCC using HRMS is feasible and ideal compared to unit resolution mass spectrometers. HRMS allows for isotopic resolution for analytes with >+2 charge state and provides flexibility in quantification using multiple product ions. ISCC by HRMS allows for simultaneous assaying of low abundance isotopologues, the signal acquisition of which is not constrained by limits in data acquisition or calibrant preparation as with other approaches but rather limited by platform sensitivity. In contrast to unit resolution mass spectrometers, these features offered by HRMS could be especially useful for the drug discovery assay support where there is less lead time for assay development than for the assays to support the drug development studies.

DOI: https://doi.org/10.1002/rcm.9377